diff --git a/bye_cycle/utils.py b/bye_cycle/utils.py
index afa6d40..03ad33a 100644
--- a/bye_cycle/utils.py
+++ b/bye_cycle/utils.py
@@ -17,20 +17,23 @@ def interpol_cycle(cell_cycle_data, columns=['voltage', 'current', 'cycle_index'
     return np.array(interpol_cell_cycle_data).T
 
 
-def clean_cycle_data(cell_data, cycle_number, columns=['voltage', 'current', 'cycle_index', 'discharge_capacity']):
-    selected_cell_data = cell_data.structured_data[columns].dropna()
+def clean_cycle_data(cell_data, cycle_number, columns=['voltage', 'current', 'cycle_index', 'discharge_capacity'], exclude_step_type=None):
+    selected_cell_data = cell_data.structured_data[columns]
+    if exclude_step_type is not None:
+        selected_cell_data = selected_cell_data[selected_cell_data['step_type'] != exclude_step_type]
+    selected_cell_data = selected_cell_data.dropna()
     # Getting rid of 0 dishcarge data
     clean_cell_data_cycle_number = selected_cell_data.loc[(selected_cell_data['cycle_index'] == cycle_number) 
                                               & (selected_cell_data['discharge_capacity']!=0)]
     return clean_cell_data_cycle_number[columns]
 
 
-def prep_features_per_cell(cell, n_points=100, columns=['voltage', 'current', 'cycle_index'], interpol_kind='linear'):
+def prep_features_per_cell(cell, n_points=100, columns=['voltage', 'current', 'cycle_index'], interpol_kind='linear', exclude_step_type=None):
     max_cycle_idx = max(cell.structured_data['cycle_index'])
     interp_clean_cell = []
     empty_cycles = []
     for i in tqdm(range(max_cycle_idx)):
-        clean_dat = clean_cycle_data(cell, i, columns=columns)
+        clean_dat = clean_cycle_data(cell, i, columns=columns,  exclude_step_type=exclude_step_type)
         # Looks like there are some missing cycle measurements so ...
         if clean_dat.shape[0] not in [0, 1, 2]:
             interp_clean_cell.append(interpol_cycle(clean_dat, n_points=n_points, columns=columns, interpol_kind=interpol_kind))
@@ -66,7 +69,7 @@ def find_renumbedred_index(cell):
 
 
 def index_convoluter(cell, cycle_window_size=20, overlap_cycle_window=False,
-                     overlap_size=5, skip_diagnistic_in_window=False):
+                     overlap_size=5, skip_diagnostic_in_window=False):
     '''This function generates a nested list of indices by convolting the cycles based on cycle_window_size. 
         You can choose to have your window of cycles overlap, or skipp the windows that involve diagnostic cycles in between.
     '''
@@ -80,7 +83,7 @@ def index_convoluter(cell, cycle_window_size=20, overlap_cycle_window=False,
     else:
         non_overlap = cycle_window_size
     intervals = range(0, max_cycle_index, non_overlap)
-    if not skip_diagnistic_in_window:
+    if not skip_diagnostic_in_window:
         index_covolutions = [list(range(x, x + cycle_window_size)) for x in intervals if x <= max_cycle_index-cycle_window_size]
     else:
 #         skipped_indices = [5, 6, 7, 20]
diff --git a/examples/LFP.ipynb b/examples/LFP.ipynb
new file mode 100644
index 0000000..fe5e556
--- /dev/null
+++ b/examples/LFP.ipynb
@@ -0,0 +1,7433 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "21c608be",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2022-08-08 03:49:56.663981: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA\n",
+      "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
+      "2022-08-08 03:49:56.849994: E tensorflow/stream_executor/cuda/cuda_blas.cc:2981] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
+      "2022-08-08 03:49:57.569680: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda/lib:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:/opt/amazon/efa/lib64:/opt/amazon/openmpi/lib64:/usr/local/lib:/usr/lib:/lib:/usr/local/cuda/lib:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:/opt/amazon/efa/lib64:/opt/amazon/openmpi/lib64:/usr/local/lib:/usr/lib:/lib::/home/ec2-user/anaconda3/envs/beep/lib/\n",
+      "2022-08-08 03:49:57.569805: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda/lib:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:/opt/amazon/efa/lib64:/opt/amazon/openmpi/lib64:/usr/local/lib:/usr/lib:/lib:/usr/local/cuda/lib:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:/opt/amazon/efa/lib64:/opt/amazon/openmpi/lib64:/usr/local/lib:/usr/lib:/lib::/home/ec2-user/anaconda3/envs/beep/lib/\n",
+      "2022-08-08 03:49:57.569817: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.\n"
+     ]
+    }
+   ],
+   "source": [
+    "import os\n",
+    "import bye_cycle\n",
+    "import tensorflow as tf\n",
+    "from tqdm import tqdm\n",
+    "import numpy as np\n",
+    "import pickle as pkl\n",
+    "import matplotlib.pyplot as plt\n",
+    "from beep.structure.cli import auto_load_processed"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "e88559d8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Disabling tf warnings\n",
+    "tf.get_logger().setLevel('INFO')\n",
+    "# Disabling GPU\n",
+    "RUN_ON_GPU = True\n",
+    "if not RUN_ON_GPU:\n",
+    "    os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"-1\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "bba2e472",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "structure_path = '/home/ec2-user/SageMaker/Amalie/competition/structured/'\n",
+    "#Get all structured files with the correct prefix\n",
+    "names = [os.path.join(structure_path, n) for n in os.listdir(structure_path) if \"FastCharge\" in n]\n",
+    "#exclude stitched files\n",
+    "# excuded_cells = [str(_) for _ in list(range(292,295)) + list(range(297,307))]\n",
+    "# names = [n for n in names if (not \"p2_structure\" in n and \".gz\" in n and not any(x in n for x in excuded_cells))]\n",
+    "N = len(names)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "94945520",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pickle\n",
+    "structured_columns = ['voltage', 'current', 'cycle_index', 'discharge_capacity', 'charge_capacity','step_type', 'test_time']\n",
+    "summary_columns = ['cycle_index', 'discharge_capacity', 'charge_capacity', 'discharge_energy',\n",
+    "                   'charge_energy', 'charge_throughput', 'energy_throughput']\n",
+    "exclude_count = 0\n",
+    "for i,n in enumerate(names):\n",
+    "    structured_data = []\n",
+    "    summary_data = []\n",
+    "    notes = []\n",
+    "    # check to see if the cell was aleady excluded\n",
+    "    exclude_checker = False\n",
+    "    with open('CACHED_DATA/pre_processed_pandas/LFP_new_structured_by_Amalie/notes.txt', 'r') as f:\n",
+    "        if n[46:-5] in f.read():\n",
+    "            exclude_checker = True\n",
+    "            print(f'Cell {n[55:-5]} is already excluded. Please check notes.txt for more details.')\n",
+    "#     print(n[46:-5])\n",
+    "#     print(n)\n",
+    "#     break   \n",
+    "    if not exclude_checker:\n",
+    "        if not os.path.exists(f'CACHED_DATA/pre_processed_pandas/LFP_new_structured_by_Amalie/{n[55:-5]}.pkl'):\n",
+    "            # excluding charge data\n",
+    "            \n",
+    "            cell = auto_load_processed(n)\n",
+    "#             a = a[a['step_type'] != 'charge'] \n",
+    "            manufacturding_nominal_discharge_capacity = 1.1\n",
+    "            # excluding cells that that have less than 50 cycles\n",
+    "            cycle_idx_threshold = 50\n",
+    "            max_cycle_idx = max(cell.structured_data['cycle_index'])\n",
+    "            if not max_cycle_idx < cycle_idx_threshold:\n",
+    "                nominal_discharge_capacity_drop = 1- cell.structured_summary['discharge_capacity'][1]/manufacturding_nominal_discharge_capacity\n",
+    "                # excluding cells that that have more that 80% drop in discharge capacity within 1st cycle\n",
+    "                nominal_discharge_capacity_drop_threshold = 0.8\n",
+    "                if nominal_discharge_capacity_drop < nominal_discharge_capacity_drop_threshold:\n",
+    "                    print(f'Pre-processing data for cell {n[55:-5]}.')\n",
+    "                    for c in tqdm(cell.structured_summary['cycle_index']):\n",
+    "                        clean_cell_structured_data = bye_cycle.clean_cycle_data(cell, c, columns=structured_columns, exclude_step_type='charge')\n",
+    "                        structured_data.append(clean_cell_structured_data)\n",
+    "                        break\n",
+    "                    summary_data.append(cell.structured_summary[summary_columns])\n",
+    "        #             features.append(bye_cycle.prep_features_per_cell(cell, n_points,\n",
+    "        #                                                              interpol_kind='quadratic',\n",
+    "        #                                                              columns=['voltage', 'current', 'cycle_index', 'discharge_capacity', 'charge_capacity']))\n",
+    "\n",
+    "                    with open(f'CACHED_DATA/pre_processed_pandas/LFP_new_structured_by_Amalie/{n[55:-5]}.pkl','wb') as f: \n",
+    "                        pickle.dump([structured_data, summary_data], f) \n",
+    "                else:\n",
+    "                    if nominal_discharge_capacity_drop > nominal_discharge_capacity_drop_threshold:\n",
+    "                        add_txt = f'\\n- Cell {n[55:-8]} was skipped as the nominal discharge capacity drop ({nominal_discharge_capacity_drop:.3f}) exceeds {nominal_discharge_capacity_drop_threshold}.\\n'\n",
+    "                        print(add_txt)\n",
+    "                        with open('CACHED_DATA/pre_processed_pandas/LFP_new_structured_by_Amalie/notes.txt', 'r+') as f:\n",
+    "                            lines_list = f.readlines()\n",
+    "                            if add_txt not in lines_list: \n",
+    "                                f.write(add_txt)\n",
+    "                    if max_cycle_idx < cycle_idx_threshold:\n",
+    "                        add_txt = f'\\n- Cell {n[55:-5]} was skipped as the cycle numbers ({max_cycle_idx}) is less than {cycle_idx_threshold}.\\n'\n",
+    "                        print(add_txt)\n",
+    "                        with open('CACHED_DATA/pre_processed_pandas/LFP_new_structured_by_Amalie/notes.txt', 'r+') as f:\n",
+    "                            lines_list = f.readlines()\n",
+    "                            if add_txt not in lines_list: \n",
+    "                                f.write(add_txt)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "769cd58e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def drop_increasing_column(cycle_dataframe, column='discharge_capacity'):\n",
+    "    cycle_data = cycle_dataframe.copy()\n",
+    "#     print(len(cycle_data))\n",
+    "    diff = cycle_data[column] - cycle_data[column].shift(1)\n",
+    "    drop_indices = np.where(diff > 0)[0]\n",
+    "#     print(len(drop_indices))\n",
+    "    drop_cycle_indices = list(cycle_data['cycle_index'].iloc[drop_indices])\n",
+    "    cycle_data.drop(cycle_data.index[drop_indices], axis=0, inplace=True)\n",
+    "    return cycle_data, drop_cycle_indices\n",
+    "\n",
+    "# drop_increasing_column(summary_data[0])['discharge_capacity'].is_monotonic_decreasing \n",
+    "# test = summary_data[0]\n",
+    "def decrease_monotonically(cycle_dataframe, column='discharge_capacity', renumber_cycle_index=True):\n",
+    "    cycle_indices_dropped = []\n",
+    "#     row_wise_difference = (cycle_dataframe[column].shift(1) - cycle_dataframe[column])[1:]\n",
+    "#     print(row_wise_difference)\n",
+    "\n",
+    "    while not cycle_dataframe[column].is_monotonic_decreasing:\n",
+    "        cycle_dataframe, _ = drop_increasing_column(cycle_dataframe, column=column)\n",
+    "#         print(len(cycle_dataframe))\n",
+    "        cycle_indices_dropped.append(_)\n",
+    "    cycle_indices_dropped = [x for xs in cycle_indices_dropped for x in xs]\n",
+    "    if renumber_cycle_index:\n",
+    "        cycle_dataframe['cycle_index'] = cycle_dataframe.reset_index(drop=True).index\n",
+    "    return cycle_dataframe, cycle_indices_dropped\n",
+    "# a = decrease_monotonically(summary_data[0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "8b1e3f1a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0 FastCharge_000039_CH28_structure.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
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+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1 FastCharge_000060_CH29_structure.pkl\n"
+     ]
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+     "text": [
+      "2 FastCharge_000017_CH25_structure.pkl\n"
+     ]
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+     "name": "stdout",
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+     "text": [
+      "3 FastCharge_000040_CH32_structure.pkl\n"
+     ]
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+     "text": [
+      "4 FastCharge_000004_CH2_structure.pkl\n"
+     ]
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+      "5 FastCharge_000008_CH47_structure.pkl\n"
+     ]
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+    {
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+      "6 FastCharge_000029_CH10_structure.pkl\n"
+     ]
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+      "7 FastCharge_000022_CH24_structure.pkl\n"
+     ]
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+     "text": [
+      "8 FastCharge_000013_CH13_structure.pkl\n"
+     ]
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+    {
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+     "name": "stdout",
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+     "text": [
+      "9 FastCharge_000017_CH9_structure.pkl\n"
+     ]
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+      "10 FastCharge_000036_CH48_structure.pkl\n"
+     ]
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+      "11 FastCharge_000037_CH22_structure.pkl\n"
+     ]
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+     "text": [
+      "12 FastCharge_000028_CH19_structure.pkl\n"
+     ]
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+     "text": [
+      "13 FastCharge_000012_CH23_structure.pkl\n"
+     ]
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+     "text": [
+      "14 FastCharge_000062_CH47_structure.pkl\n"
+     ]
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+    {
+     "name": "stdout",
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+     "text": [
+      "15 FastCharge_000007_CH24_structure.pkl\n"
+     ]
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "16 FastCharge_000006_CH8_structure.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
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+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "17 FastCharge_000047_CH21_structure.pkl\n"
+     ]
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+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "18 .ipynb_checkpoints\n",
+      "19 FastCharge_000037_CH21_structure.pkl\n"
+     ]
+    },
+    {
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+    {
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+     "output_type": "stream",
+     "text": [
+      "20 FastCharge_000015_CH28_structure.pkl\n"
+     ]
+    },
+    {
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+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "21 FastCharge_000019_CH30_structure.pkl\n"
+     ]
+    },
+    {
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+    {
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+      "58 FastCharge_000070_CH46_structure.pkl\n"
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+      "59 FastCharge_000056_CH11_structure.pkl\n"
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+      "60 FastCharge_000066_CH25_structure.pkl\n"
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+      "66 FastCharge_000015_CH4_structure.pkl\n"
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+      "67 FastCharge_000026_CH5_structure.pkl\n"
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+      "68 FastCharge_000009_CH8_structure.pkl\n"
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+      "69 FastCharge_000012_CH13_structure.pkl\n"
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+      "70 FastCharge_000015_CH20_structure.pkl\n"
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+      "72 FastCharge_000045_CH3_structure.pkl\n"
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+      "73 FastCharge_000041_CH10_structure.pkl\n",
+      "74 FastCharge_000061_CH43_structure.pkl\n"
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+      "75 FastCharge_000054_CH15_structure.pkl\n"
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+      "76 FastCharge_000073_CH35_structure.pkl\n"
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+      "98 FastCharge_000045_CH2_structure.pkl\n"
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+      "99 FastCharge_000027_CH31_structure.pkl\n"
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+      "100 FastCharge_000050_CH40_structure.pkl\n"
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+     "text": [
+      "101 FastCharge_000017_CH6_structure.pkl\n"
+     ]
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+     "text": [
+      "102 FastCharge_000048_CH43_structure.pkl\n"
+     ]
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+     "text": [
+      "103 FastCharge_000057_CH36_structure.pkl\n"
+     ]
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+     "name": "stdout",
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+      "104 FastCharge_000018_CH18_structure.pkl\n"
+     ]
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+     "text": [
+      "105 FastCharge_000059_CH33_structure.pkl\n"
+     ]
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+     "text": [
+      "106 FastCharge_000051_CH15_structure.pkl\n"
+     ]
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+     "text": [
+      "107 FastCharge_000048_CH44_structure.pkl\n"
+     ]
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+     "text": [
+      "108 FastCharge_000007_CH39_structure.pkl\n"
+     ]
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+     "name": "stderr",
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+     "text": [
+      "109 FastCharge_000046_CH31_structure.pkl\n"
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+     "text": [
+      "110 FastCharge_000000_CH19_structure.pkl\n"
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+     "text": [
+      "111 FastCharge_000071_CH40_structure.pkl\n"
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+     "text": [
+      "112 FastCharge_000002_CH10_structure.pkl\n"
+     ]
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+     "text": [
+      "113 FastCharge_000026_CH6_structure.pkl\n"
+     ]
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+     "text": [
+      "114 FastCharge_000020_CH23_structure.pkl\n"
+     ]
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+     "name": "stdout",
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+     "text": [
+      "115 FastCharge_000014_CH23_structure.pkl\n"
+     ]
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+     "text": [
+      "116 FastCharge_000065_CH34_structure.pkl\n"
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+     "text": [
+      "117 FastCharge_000013_CH14_structure.pkl\n"
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+     "text": [
+      "118 FastCharge_000028_CH20_structure.pkl\n"
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+     "text": [
+      "119 FastCharge_000064_CH39_structure.pkl\n"
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+     "name": "stdout",
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+     "text": [
+      "120 FastCharge_000017_CH1_structure.pkl\n"
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+     "name": "stderr",
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+     "name": "stdout",
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+     "text": [
+      "121 FastCharge_000050_CH32_structure.pkl\n"
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+     "name": "stderr",
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+     "name": "stdout",
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+     "text": [
+      "122 FastCharge_000030_CH30_structure.pkl\n"
+     ]
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+     "name": "stderr",
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+     "name": "stdout",
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+     "text": [
+      "123 FastCharge_000003_CH39_structure.pkl\n"
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+     "name": "stdout",
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+     "text": [
+      "124 FastCharge_000044_CH11_structure.pkl\n"
+     ]
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+     "name": "stderr",
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+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "125 FastCharge_000033_CH14_structure.pkl\n"
+     ]
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+     "name": "stderr",
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+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "126 FastCharge_000004_CH3_structure.pkl\n"
+     ]
+    },
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+     "name": "stderr",
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+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "127 FastCharge_000049_CH37_structure.pkl\n"
+     ]
+    },
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+     "name": "stderr",
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+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "128 notes.txt\n",
+      "129 FastCharge_000012_CH5_structure.pkl\n"
+     ]
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+     "name": "stderr",
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+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "130 FastCharge_000067_CH41_structure.pkl\n"
+     ]
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+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 93%|█████████▎| 131/141 [02:04<00:06,  1.60it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "131 FastCharge_000072_CH34_structure.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 94%|█████████▎| 132/141 [02:06<00:08,  1.04it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "132 FastCharge_000031_CH9_structure.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 94%|█████████▍| 133/141 [02:06<00:06,  1.26it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "133 FastCharge_000010_CH44_structure.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 95%|█████████▌| 134/141 [02:07<00:05,  1.39it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "134 FastCharge_000006_CH43_structure.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 96%|█████████▌| 135/141 [02:08<00:05,  1.14it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "135 FastCharge_000011_CH26_structure.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 96%|█████████▋| 136/141 [02:09<00:03,  1.27it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "136 FastCharge_000009_CH4_structure.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 97%|█████████▋| 137/141 [02:09<00:02,  1.39it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "137 FastCharge_000015_CH22_structure.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 98%|█████████▊| 138/141 [02:10<00:02,  1.30it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "138 FastCharge_000006_CH48_structure.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 99%|█████████▊| 139/141 [02:11<00:01,  1.10it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "139 FastCharge_000043_CH16_structure.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 99%|█████████▉| 140/141 [02:12<00:00,  1.20it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "140 FastCharge_000003_CH40_structure.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████| 141/141 [02:13<00:00,  1.06it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CACHED data is loaded.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "# read CACHED data \n",
+    "# excluding all diagnostic cycles and those with increase in discharge cap, renumber \n",
+    "input_window_size = 50\n",
+    "output_window_size = 50\n",
+    "skip_window_after_diagnostic = 50\n",
+    "structured_data_list = []\n",
+    "summary_data_list = []\n",
+    "nominal_cell_capacity = 1.1\n",
+    "drop_following_diagnostic = False\n",
+    "\n",
+    "for i,cell_file in enumerate(tqdm(os.listdir('CACHED_DATA/pre_processed_pandas/LFP_new_structured_by_Amalie/'))):\n",
+    "    print(i, cell_file)\n",
+    "    if cell_file.startswith(\"Fast\"):\n",
+    "        with open(f'CACHED_DATA/pre_processed_pandas/LFP_new_structured_by_Amalie/{cell_file}', 'rb') as f:\n",
+    "            structured_data, summary_data = pickle.load(f)\n",
+    "        structured_data = structured_data[1:]\n",
+    "        # dropping first cycle\n",
+    "        summary_data[0] = summary_data[0].iloc[1: , :]\n",
+    "#         a = find_renumbedred_index(structured_data)\n",
+    "#         print(len(summary_data[0]))\n",
+    "#         break\n",
+    "#         equivalent_cycle_index = summary_data[0]['charge_throughput']/nominal_cell_capacity\n",
+    "#         summary_data[0]['cycle_index'] = equivalent_cycle_index\n",
+    "#         print(summary_data[0]['cycle_index'])\n",
+    "#         print(len(summary_data[0]))\n",
+    "#         break\n",
+    "        if not drop_following_diagnostic:\n",
+    "            cycle_indices_dropped = []\n",
+    "        else:\n",
+    "            summary_data[0], cycle_indices_dropped = decrease_monotonically(summary_data[0])\n",
+    "            print(cycle_indices_dropped)\n",
+    "#         print(len(summary_data[0]))\n",
+    "        # getting equivalent cycle index\n",
+    "\n",
+    "#         break\n",
+    "#         print(len(summary_data[0]))\n",
+    "#         skipped_cycles = [list(range(m+1,m+skip_window_after_diagnostic+1)) for m in a]\n",
+    "#         flatten_skipped_cycles = [x for xs in skipped_cycles for x in xs]\n",
+    "        # check if the cell has enough cycles based on the $window_cycles_size\n",
+    "        if len(summary_data[0]) >= input_window_size * 2:\n",
+    "            cycle_list = []\n",
+    "            new_cycle_indices = []\n",
+    "            j = 0\n",
+    "            for i, cycle in enumerate(structured_data):\n",
+    "                \n",
+    "                # drop first cycle\n",
+    "                cycle_copy = cycle.tail(cycle.shape[0]-1).copy()\n",
+    "                if len(cycle_copy) > 2 and np.unique(cycle_copy['cycle_index']) !=0:\n",
+    "                    cycle_copy['cycle_index'] = cycle_copy['cycle_index'].subtract(1)\n",
+    "                    if cycle_copy['cycle_index'].iloc[0] == 0:\n",
+    "                        t0 = cycle_copy['test_time'].iloc[0]\n",
+    "                    cycle_copy = cycle_copy.reset_index(drop=True)\n",
+    "                    cycle_copy['test_time'] = cycle_copy['test_time'] - t0\n",
+    "                    cycle_list.append(cycle_copy)\n",
+    "#                     cycle_index_value = np.unique(cycle['cycle_index'])[0]\n",
+    "#                     if cycle_index_value not in cycle_indices_dropped:\n",
+    "# #                         print('hi')\n",
+    "# #                       # renumber\n",
+    "#                         cycle.loc[:,'cycle_index'] = j\n",
+    "#                         cycle_list.append(cycle_copy)\n",
+    "#                         new_cycle_indices.append(j)\n",
+    "#                         j += 1\n",
+    "#                 else:\n",
+    "#                     print(f'TIME-SERIES THRESHOLD ALEERT FOR {i, cell_file}')\n",
+    "            structured_data_list.append(cycle_list)\n",
+    "#             summary_data[0][summary_data[0]['summary_data[0]'] != flatten_skipped_cycles]\n",
+    "#             summary_data[0] = summary_data[0][~summary_data[0]['cycle_index'].isin(flatten_skipped_cycles)]\n",
+    "#             summary_data[0]['cycle_index'] = new_cycle_indices\n",
+    "            summary_data_list.append(summary_data[0])\n",
+    "#             print(len(summary_data_list[i]), len(structured_data_list[i]))\n",
+    "        else:\n",
+    "            print(f'NUMBER OF CYCLES THRESHOLD ALEERT FOR {i, cell_file}')\n",
+    "#         dat.append(cell_data)\n",
+    "#     break\n",
+    "#     if i ==2:\n",
+    "#         break\n",
+    "print('CACHED data is loaded.')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "2d3087b0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>voltage</th>\n",
+       "      <th>current</th>\n",
+       "      <th>cycle_index</th>\n",
+       "      <th>discharge_capacity</th>\n",
+       "      <th>charge_capacity</th>\n",
+       "      <th>step_type</th>\n",
+       "      <th>test_time</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1992</th>\n",
+       "      <td>3.588789</td>\n",
+       "      <td>-0.485110</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.000004</td>\n",
+       "      <td>1.068717</td>\n",
+       "      <td>discharge</td>\n",
+       "      <td>12182.836790</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1991</th>\n",
+       "      <td>3.587187</td>\n",
+       "      <td>-0.557813</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.000004</td>\n",
+       "      <td>1.068717</td>\n",
+       "      <td>discharge</td>\n",
+       "      <td>12182.846581</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1990</th>\n",
+       "      <td>3.585586</td>\n",
+       "      <td>-0.630517</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.000004</td>\n",
+       "      <td>1.068717</td>\n",
+       "      <td>discharge</td>\n",
+       "      <td>12182.856371</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1989</th>\n",
+       "      <td>3.583984</td>\n",
+       "      <td>-0.703220</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.000004</td>\n",
+       "      <td>1.068717</td>\n",
+       "      <td>discharge</td>\n",
+       "      <td>12182.866162</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1988</th>\n",
+       "      <td>3.582382</td>\n",
+       "      <td>-0.775924</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.000004</td>\n",
+       "      <td>1.068717</td>\n",
+       "      <td>discharge</td>\n",
+       "      <td>12182.875952</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1004</th>\n",
+       "      <td>2.006406</td>\n",
+       "      <td>-4.399851</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.053747</td>\n",
+       "      <td>1.068717</td>\n",
+       "      <td>discharge</td>\n",
+       "      <td>13045.588711</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1010</th>\n",
+       "      <td>2.016016</td>\n",
+       "      <td>-4.400044</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.053747</td>\n",
+       "      <td>1.068717</td>\n",
+       "      <td>discharge</td>\n",
+       "      <td>13045.589276</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1002</th>\n",
+       "      <td>2.003203</td>\n",
+       "      <td>-4.399971</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.053747</td>\n",
+       "      <td>1.068717</td>\n",
+       "      <td>discharge</td>\n",
+       "      <td>13045.598217</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1003</th>\n",
+       "      <td>2.004805</td>\n",
+       "      <td>-4.399829</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.053747</td>\n",
+       "      <td>1.068717</td>\n",
+       "      <td>discharge</td>\n",
+       "      <td>13045.626556</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1000</th>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>-0.121990</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1.064125</td>\n",
+       "      <td>1.068717</td>\n",
+       "      <td>discharge</td>\n",
+       "      <td>13166.751575</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>993 rows × 7 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       voltage   current  cycle_index  discharge_capacity  charge_capacity  \\\n",
+       "1992  3.588789 -0.485110            1            0.000004         1.068717   \n",
+       "1991  3.587187 -0.557813            1            0.000004         1.068717   \n",
+       "1990  3.585586 -0.630517            1            0.000004         1.068717   \n",
+       "1989  3.583984 -0.703220            1            0.000004         1.068717   \n",
+       "1988  3.582382 -0.775924            1            0.000004         1.068717   \n",
+       "...        ...       ...          ...                 ...              ...   \n",
+       "1004  2.006406 -4.399851            1            1.053747         1.068717   \n",
+       "1010  2.016016 -4.400044            1            1.053747         1.068717   \n",
+       "1002  2.003203 -4.399971            1            1.053747         1.068717   \n",
+       "1003  2.004805 -4.399829            1            1.053747         1.068717   \n",
+       "1000  2.000000 -0.121990            1            1.064125         1.068717   \n",
+       "\n",
+       "      step_type     test_time  \n",
+       "1992  discharge  12182.836790  \n",
+       "1991  discharge  12182.846581  \n",
+       "1990  discharge  12182.856371  \n",
+       "1989  discharge  12182.866162  \n",
+       "1988  discharge  12182.875952  \n",
+       "...         ...           ...  \n",
+       "1004  discharge  13045.588711  \n",
+       "1010  discharge  13045.589276  \n",
+       "1002  discharge  13045.598217  \n",
+       "1003  discharge  13045.626556  \n",
+       "1000  discharge  13166.751575  \n",
+       "\n",
+       "[993 rows x 7 columns]"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "structured_data[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "82040e11",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0         0.000000\n",
+       "1         0.011166\n",
+       "2         0.022332\n",
+       "3         0.033499\n",
+       "4         0.044665\n",
+       "          ...     \n",
+       "987     869.558205\n",
+       "988     869.558551\n",
+       "989     869.599701\n",
+       "990     916.169617\n",
+       "991    1111.381354\n",
+       "Name: test_time, Length: 992, dtype: float64"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "structured_data_list[0][0]['test_time'] - structured_data_list[0][0]['test_time'].iloc[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "e26fa428",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "with open('CACHED_DATA/pre_processed_pandas/LFP_new_structured_by_Amalie/FastCharge_000034_CH27_structure.pkl', 'rb') as f:\n",
+    "    a = pkl.load(f)  \n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "5af7b9ee",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7f6d68c37610>]"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "a = structured_data_list[0][0].sort_values('test_time', ascending=True)\n",
+    "plt.plot(a['test_time'], a['voltage'])\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "6c8509f3",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(0.8, 1.2)"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1800x1200 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(dpi=300, facecolor='white')\n",
+    "for i,c in enumerate(summary_data_list):\n",
+    "    plt.scatter(c['cycle_index'][1:], c['discharge_capacity'][1:], \n",
+    "                s=0.1, color=f'C{i}', label='actual cycle_index', alpha=0.3)\n",
+    "plt.xlabel('Cycle index')\n",
+    "plt.ylabel('Discharge capacity (Ah/Wh)')\n",
+    "plt.ylim([0.8, 1.2])\n",
+    "# plt.savefig(f'media/LFP/LFP_dataset.png', dpi=400, transparent=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "e907911d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def index_convoluter(cell, input_window_size=20, output_window_size=20, overlap_cycle_window=False,\n",
+    "                     overlap_size=5, skip_diagnostic_in_window=False):\n",
+    "    '''This function generates a nested list of indices by convolting the cycles based on cycle_window_size. \n",
+    "        You can choose to have your window of cycles overlap, or skipp the windows that involve diagnostic cycles in between.\n",
+    "    '''\n",
+    "    max_cycle_index = len(cell) #30 #\n",
+    "    print(max_cycle_index)\n",
+    "    if input_window_size < overlap_size:\n",
+    "        raise ValueError(f'If overlapping, overlap_size ({overlap_size}) should be samller than cycle_window_size ({input_window_size}). Please check inputs.')\n",
+    "    if not input_window_size < max_cycle_index:\n",
+    "        raise ValueError(f'cycle_window_size ({input_window_size}) should be samller than maximum number of cycles in cell ({max_cycle_index}). Please check inputs.')\n",
+    "    if overlap_cycle_window:\n",
+    "        non_overlap =  input_window_size - overlap_size\n",
+    "    else:\n",
+    "        non_overlap = input_window_size\n",
+    "    intervals = range(0, max_cycle_index, non_overlap)\n",
+    "    if not skip_diagnostic_in_window:\n",
+    "        input_covolutions = [list(range(x, x + input_window_size)) for x in intervals if x <= max_cycle_index-input_window_size]\n",
+    "    else:\n",
+    "#         skipped_indices = [5, 6, 7, 20]\n",
+    "        skipped_indices = find_renumbedred_index(cell)\n",
+    "        input_covolutions = [list(range(x, x + input_window_size)) for x in intervals if x <= max_cycle_index-input_window_size\n",
+    "                             and not (set(list(range(x, x + cycle_window_size))[:-1]) & set(skipped_indices))]\n",
+    "    output_covolutions = [list(range(x[-1]+1, x[-1] + output_window_size +1)) for x in input_covolutions if x[-1] < max_cycle_index- output_window_size]\n",
+    "        \n",
+    "    return input_covolutions[:len(output_covolutions)], output_covolutions"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "2ea7907d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "917\n"
+     ]
+    }
+   ],
+   "source": [
+    "skip_diagnostic_in_window=False\n",
+    "\n",
+    "input_covolutions, output_covolutions  = index_convoluter(structured_data_list[0], overlap_cycle_window=False, \n",
+    "                                     overlap_size=10, input_window_size=input_window_size,\n",
+    "                                                          output_window_size=output_window_size,\n",
+    "                                               skip_diagnostic_in_window=skip_diagnostic_in_window)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "6f3cfaba",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# input_covolutions, output_covolutions  = index_convoluter(cell, overlap_cycle_window=False, \n",
+    "#                                              overlap_size=10, input_window_size=50, output_window_size=100,\n",
+    "#                                                        skip_diagnostic_in_window=skip_diagnostic_in_window)\n",
+    "# # print(output_covolutions)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "bf4a8333",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  0%|          | 0/139 [00:00<?, ?it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "917\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  1%|          | 1/139 [00:02<06:04,  2.64s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "521\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  1%|▏         | 2/139 [00:04<04:21,  1.91s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1638\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  2%|▏         | 3/139 [00:08<07:18,  3.23s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "520\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  3%|▎         | 4/139 [00:10<05:38,  2.50s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "982\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  4%|▎         | 5/139 [00:13<05:49,  2.61s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "616\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  4%|▍         | 6/139 [00:14<05:05,  2.30s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "636\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  5%|▌         | 7/139 [00:16<04:37,  2.11s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "496\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  6%|▌         | 8/139 [00:17<03:59,  1.83s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "905\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  6%|▋         | 9/139 [00:20<04:30,  2.08s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1801\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  7%|▋         | 10/139 [00:27<07:38,  3.56s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "746\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  8%|▊         | 11/139 [00:29<06:34,  3.09s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "896\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
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+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "547\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 94%|█████████▎| 130/139 [05:14<00:16,  1.83s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "327\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 94%|█████████▍| 131/139 [05:15<00:12,  1.52s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "488\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 95%|█████████▍| 132/139 [05:16<00:10,  1.45s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1158\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 96%|█████████▌| 133/139 [05:19<00:12,  2.07s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "523\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 96%|█████████▋| 134/139 [05:21<00:09,  1.88s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "525\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 97%|█████████▋| 135/139 [05:22<00:06,  1.75s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "816\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 98%|█████████▊| 136/139 [05:25<00:05,  1.94s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1156\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 99%|█████████▊| 137/139 [05:28<00:04,  2.41s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "597\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 99%|█████████▉| 138/139 [05:30<00:02,  2.17s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "703\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████| 139/139 [05:32<00:00,  2.39s/it]\n"
+     ]
+    }
+   ],
+   "source": [
+    "def find_slope(cycle_window_label):\n",
+    "    mid_window_index = len(cycle_window_label)//2\n",
+    "    low = np.array(cycle_window_label)[0]\n",
+    "    mid = np.array(cycle_window_label)[mid_window_index]\n",
+    "    high = np.array(cycle_window_label)[-1]\n",
+    "#     print(low[0], mid[0], high[0])\n",
+    "    slope_1 = (mid[1] - low[1]) / (mid[0] - low[0]) # mid_window_index #\n",
+    "    slope_2 = (high[1] - mid[1]) / (mid[0] - low[0]) # mid_window_index\n",
+    "    return slope_1, slope_2\n",
+    "\n",
+    "import pickle as pkl\n",
+    "pkl_f_l_filename = f'CACHED_DATA/pickled_cycle_windows/LFP_new_structured_by_Amalie/features_labels_inputs_window_{input_window_size}_outputs_window_{output_window_size}.pkl'\n",
+    "\n",
+    "test_conv = True\n",
+    "if not os.path.exists(pkl_f_l_filename) or test_conv:\n",
+    "\n",
+    "    skip_diagnostic_in_window = False\n",
+    "\n",
+    "    features_columns = ['cycle_index', 'test_time','voltage', 'current']\n",
+    "    label_columns = ['cycle_index', 'discharge_capacity']\n",
+    "    # features = np.empty([0, None,100, 3])\n",
+    "    monitored_cycles_discharge_capacity = []\n",
+    "    labels = np.empty([0, 2])\n",
+    "    cell_features = []\n",
+    "    cell_labels = []\n",
+    "    cell_discharge_caps = []\n",
+    "    initial_discharge_cap_windows = []\n",
+    "    for i, cell in enumerate(tqdm(structured_data_list)):\n",
+    "    #     print(i)\n",
+    "    #     n = len(cell)//cycle_numbers\n",
+    "        if len(cell) > 0:\n",
+    "            cycle_window_features = []\n",
+    "            cycle_window_labels = []\n",
+    "            initial_discharge_cap = []\n",
+    "            cell_cycle_indices = summary_data_list[i]['cycle_index'].values\n",
+    "            input_covolutions, output_covolutions  = index_convoluter(cell, overlap_cycle_window=False, \n",
+    "                                                 overlap_size=10, input_window_size=input_window_size,\n",
+    "                                                                      output_window_size=output_window_size,\n",
+    "                                                           skip_diagnostic_in_window=skip_diagnostic_in_window)\n",
+    "        #     print(len(index_convolution))\n",
+    "    #         for j, index_list in enumerate(index_convolution):\n",
+    "            for j, (input_index_list, output_index_list) in enumerate(zip(input_covolutions, output_covolutions)):\n",
+    "        #         if (j < len(index_convolution)-1):\n",
+    "                    cycle_window_features.append(list(zip(*[(bye_cycle.interpol_cycle(cell[cycle_index], columns=features_columns, n_points=100, interpol_kind='cubic')\n",
+    "                                                             , max(cell[cycle_index]['test_time'])- min(cell[cycle_index]['test_time']) )\n",
+    "                                         for cycle_index in input_index_list])))\n",
+    "            #         break\n",
+    "            #         print (index_list)\n",
+    "            #         print(summary_data_list[i][label_columns])\n",
+    "            #         discharge_cap_cycle_window = np.array(summary_data_list[i][label_columns])[index_list]\n",
+    "        #             print(index_convolution[j])\n",
+    "                    discharge_cap_cycle_window = np.array(summary_data_list[i][label_columns])[output_index_list]\n",
+    "    #                 print(j, discharge_cap_cycle_window )\n",
+    "\n",
+    "                    cycle_window_labels.append(list([find_slope(discharge_cap_cycle_window), discharge_cap_cycle_window]))\n",
+    "        #         if j == 0:\n",
+    "        #             initial_discharge_cap.append(np.array(summary_data_list[i][label_columns])[index_convolution[j]])\n",
+    "            #         cycle_window_labels.append(discharge_cap_cycle_window)\n",
+    "            #     break\n",
+    "            cell_features.append(cycle_window_features)\n",
+    "            cell_labels.append(cycle_window_labels)\n",
+    "#         break\n",
+    "    #     initial_discharge_cap_windows.append(initial_discharge_cap)\n",
+    "#     with open(pkl_f_l_filename, 'wb') as f:\n",
+    "#         pkl.dump([cell_features, cell_labels], f)\n",
+    "else:\n",
+    "    print('Loaded CACHED pickled files for features and labels.')\n",
+    "    with open(pkl_f_l_filename, 'rb') as f:\n",
+    "        [cell_features, cell_labels] = pkl.load(f)  "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "258ce258",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7f6d37375fa0>]"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Checking interpolation\n",
+    "c = cycle_window_features[1][0][0]\n",
+    "plt.plot(c[:,1], c[:,2])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "02ce6fae",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# cell = structured_data_list[0]\n",
+    "\n",
+    "# def index_convoluter(cell, input_window_size=20, output_window_size=20, overlap_cycle_window=False, \n",
+    "#                      overlap_size=5, skip_diagnostic_in_window=False):\n",
+    "#     '''This function generates a nested list of indices by convolting the cycles based on cycle_window_size. \n",
+    "#         You can choose to have your window of cycles overlap, or skipp the windows that involve diagnostic cycles in between.\n",
+    "#     '''\n",
+    "# #     input_window_size = 20\n",
+    "#     output_window_size = 40\n",
+    "#     max_cycle_index = len(cell) #30 #\n",
+    "#     print(max_cycle_index)\n",
+    "#     if cycle_window_size < overlap_size:\n",
+    "#         raise ValueError(f'If overlapping, overlap_size ({overlap_size}) should be samller than cycle_window_size ({input_window_size}). Please check inputs.')\n",
+    "#     if not cycle_window_size < max_cycle_index:\n",
+    "#         raise ValueError(f'cycle_window_size ({input_window_size}) should be samller than maximum number of cycles in cell ({max_cycle_index}). Please check inputs.')\n",
+    "#     if overlap_cycle_window:\n",
+    "#         non_overlap =  input_window_size - overlap_size\n",
+    "#     else:\n",
+    "#         non_overlap = input_window_size\n",
+    "#     intervals = range(0, max_cycle_index, non_overlap)\n",
+    "#     if not skip_diagnostic_in_window:\n",
+    "#         index_covolutions = [list(range(x, x + input_window_size)) for x in intervals if x <= max_cycle_index-input_window_size]\n",
+    "#     else:\n",
+    "# #         skipped_indices = [5, 6, 7, 20]\n",
+    "#         skipped_indices = find_renumbedred_index(cell)\n",
+    "#         index_covolutions = [list(range(x, x + input_window_size)) for x in intervals if x <= max_cycle_index-input_window_size\n",
+    "#                              and not (set(list(range(x, x + cycle_window_size))[:-1]) & set(skipped_indices))]\n",
+    "#     output_covolutions = [list(range(x[-1]+1, x[-1] + output_window_size +1)) for x in index_covolutions if x[-1] < max_cycle_index- output_window_size]\n",
+    "        \n",
+    "#     return index_covolutions[:len(output_covolutions)], output_covolutions\n",
+    "\n",
+    "# input_window_size = 20\n",
+    "# output_window_size = 50\n",
+    "# index_convolution, output_covolution = index_convoluter(cell, overlap_cycle_window=False, \n",
+    "#                                      overlap_size=10, input_window_size=input_window_size,\n",
+    "#                                                skip_diagnostic_in_window=False)\n",
+    "# # print(index_convolution)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "5f6b229a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# # print(index_convolution[-1])\n",
+    "# for m,n in zip(index_convolution, output_covolution):\n",
+    "#     print(m,n)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "9c7ef22e",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "100 24 14 138\n"
+     ]
+    }
+   ],
+   "source": [
+    "import random\n",
+    "prepared_data = list(zip(cell_features, cell_labels))\n",
+    "\n",
+    "random.seed(0)\n",
+    "shuffled_indices = list(range(len(prepared_data)))\n",
+    "random.shuffle(prepared_data)\n",
+    "# prepared_data = prepared_data[shuffled_indices]\n",
+    "\n",
+    "train_size = 0.9\n",
+    "val_size = 0.2\n",
+    "N_train = int(train_size *len(prepared_data))\n",
+    "N_val = int(val_size * N_train)\n",
+    "train_cells = prepared_data[:N_train]\n",
+    "test_cells = prepared_data[N_train:]\n",
+    "\n",
+    "val_cells = train_cells[:N_val]\n",
+    "train_cells = train_cells[N_val:]\n",
+    "print(len(train_cells), len(val_cells), len(test_cells), len(train_cells)+len(test_cells)+len(val_cells))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "57cb2968",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[501.      0.937]\n",
+      "[[[ 0.000e+00  0.000e+00  3.587e+00 -5.641e-01]\n",
+      "  [ 0.000e+00  1.039e-01  3.571e+00 -1.273e+00]\n",
+      "  [ 0.000e+00  1.995e-01  3.555e+00 -1.931e+00]\n",
+      "  ...\n",
+      "  [ 0.000e+00  8.563e+02  2.024e+00 -4.400e+00]\n",
+      "  [ 0.000e+00  8.564e+02  2.010e+00 -4.400e+00]\n",
+      "  [ 0.000e+00  1.006e+03  2.000e+00 -1.288e-01]]\n",
+      "\n",
+      " [[ 1.000e+00  3.602e+03  3.587e+00 -5.630e-01]\n",
+      "  [ 1.000e+00  3.602e+03  3.571e+00 -1.271e+00]\n",
+      "  [ 1.000e+00  3.602e+03  3.555e+00 -1.918e+00]\n",
+      "  ...\n",
+      "  [ 1.000e+00  4.460e+03  2.032e+00 -4.400e+00]\n",
+      "  [ 1.000e+00  4.461e+03  2.011e+00 -4.400e+00]\n",
+      "  [ 1.000e+00  4.688e+03  2.000e+00 -7.158e-02]]\n",
+      "\n",
+      " [[ 2.000e+00  7.203e+03  3.586e+00 -6.553e-01]\n",
+      "  [ 2.000e+00  7.203e+03  3.570e+00 -1.361e+00]\n",
+      "  [ 2.000e+00  7.203e+03  3.554e+00 -2.011e+00]\n",
+      "  ...\n",
+      "  [ 2.000e+00  8.063e+03  2.035e+00 -4.400e+00]\n",
+      "  [ 2.000e+00  8.064e+03  2.006e+00 -4.401e+00]\n",
+      "  [ 2.000e+00  8.289e+03  2.000e+00 -7.579e-02]]\n",
+      "\n",
+      " ...\n",
+      "\n",
+      " [[ 4.700e+01  1.693e+05  3.587e+00 -5.863e-01]\n",
+      "  [ 4.700e+01  1.693e+05  3.571e+00 -1.305e+00]\n",
+      "  [ 4.700e+01  1.693e+05  3.555e+00 -1.963e+00]\n",
+      "  ...\n",
+      "  [ 4.700e+01  1.701e+05  2.027e+00 -4.400e+00]\n",
+      "  [ 4.700e+01  1.701e+05  2.011e+00 -4.400e+00]\n",
+      "  [ 4.700e+01  1.703e+05  2.002e+00 -6.893e-01]]\n",
+      "\n",
+      " [[ 4.800e+01  1.729e+05  3.587e+00 -6.111e-01]\n",
+      "  [ 4.800e+01  1.729e+05  3.571e+00 -1.325e+00]\n",
+      "  [ 4.800e+01  1.729e+05  3.555e+00 -1.996e+00]\n",
+      "  ...\n",
+      "  [ 4.800e+01  1.737e+05  2.026e+00 -4.400e+00]\n",
+      "  [ 4.800e+01  1.737e+05  2.019e+00 -4.400e+00]\n",
+      "  [ 4.800e+01  1.739e+05  2.002e+00 -8.958e-01]]\n",
+      "\n",
+      " [[ 4.900e+01  1.765e+05  3.586e+00 -6.647e-01]\n",
+      "  [ 4.900e+01  1.765e+05  3.570e+00 -1.383e+00]\n",
+      "  [ 4.900e+01  1.765e+05  3.554e+00 -2.036e+00]\n",
+      "  ...\n",
+      "  [ 4.900e+01  1.773e+05  2.021e+00 -4.400e+00]\n",
+      "  [ 4.900e+01  1.773e+05  2.024e+00 -4.400e+00]\n",
+      "  [ 4.900e+01  1.775e+05  2.000e+00 -1.301e-01]]]\n",
+      "len features 1499\n",
+      "0.0\n",
+      "[51.     1.089]\n"
+     ]
+    }
+   ],
+   "source": [
+    "def scale(inputs, scaler=None):\n",
+    "    from sklearn import preprocessing\n",
+    "    inputs_shape = inputs.shape\n",
+    "    if scaler is None:\n",
+    "        scaler = preprocessing.StandardScaler().fit(inputs.reshape(-1, inputs_shape[-1]))\n",
+    "    scaled_input = scaler.transform(inputs.reshape(-1, inputs_shape[-1])).reshape(inputs_shape)\n",
+    "    return scaler, scaled_input\n",
+    "\n",
+    "def rev_scale(scaled_inputs, scaler):\n",
+    "    scaled_inputs_shape = scaled_inputs.shape\n",
+    "    origin_inputs = scaler.inverse_transform(scaled_X_train_time_series.reshape(-1, scaled_inputs_shape[-1]))\n",
+    "    return origin_inputs.reshape(scaled_inputs_shape)\n",
+    "\n",
+    "\n",
+    "\n",
+    "def standardize_train(inputs):\n",
+    "    fstd = np.std(inputs, axis=0)\n",
+    "    fmean = np.mean(inputs, axis=0)\n",
+    "    std_features = (inputs - fmean) / fstd\n",
+    "    return std_features, fmean, fstd\n",
+    "\n",
+    "def standardize_non_train(inputs, fmean_train, fstd_train):\n",
+    "    std_features = (inputs - fmean_train) / fstd_train\n",
+    "    return std_features\n",
+    "\n",
+    "def de_standardize_non_train(inputs, fmean_train, fstd_train):\n",
+    "    return inputs*fstd_train + fmean_train\n",
+    "\n",
+    "def make_feature_arrays(data):\n",
+    "    X_dt_values = []\n",
+    "    X_time_series = []\n",
+    "    for X in data:\n",
+    "        X_dt_values.append(X[1])\n",
+    "        X_time_series.append(X[0])\n",
+    "#         break\n",
+    "    return np.array(X_time_series), np.array(X_dt_values)\n",
+    "\n",
+    "def make_label_arrays(data):\n",
+    "    slopes = []\n",
+    "    discharge_cap = []\n",
+    "    for Y in data:\n",
+    "        discharge_cap.append(Y[1])\n",
+    "        slopes.append(Y[0])\n",
+    "    return np.array(discharge_cap), np.array(slopes)\n",
+    "\n",
+    "X_train = [x for xs in train_cells for x in xs[0]]\n",
+    "# Y_train = np.array([x for xs in train_cells for x in xs[1]])\n",
+    "Y_train = [x for xs in train_cells for x in xs[1]]\n",
+    "dc_train, slopes_train = make_label_arrays(Y_train)\n",
+    "X_train_time_series, X_train_dt = make_feature_arrays(X_train)\n",
+    "# print(X_train_time_series[-1][-1])\n",
+    "print(dc_train[-1][0])\n",
+    "print(X_train_time_series[0])\n",
+    "import random\n",
+    "random.seed(0)\n",
+    "indices = list(range(len(X_train_time_series)))\n",
+    "random.shuffle(indices)\n",
+    "print(f'len features {len(X_train_time_series)}')\n",
+    "X_train_time_series = X_train_time_series[indices]\n",
+    "X_train_dt = X_train_dt[indices]\n",
+    "dc_train = dc_train[indices]\n",
+    "slopes_train = slopes_train[indices]\n",
+    "\n",
+    "\n",
+    "# standardized_train_slopes, mean_train_slopes, std_train_slopes= standardize_train(slopes_train)\n",
+    "\n",
+    "print(X_train_time_series[0,0,0,0])\n",
+    "print(dc_train[0][0])\n",
+    "\n",
+    "X_val = [x for xs in val_cells for x in xs[0]]\n",
+    "# Y_val= np.array([x for xs in val_cells for x in xs[1]])\n",
+    "Y_val = [x for xs in val_cells for x in xs[1]]\n",
+    "dc_val, slopes_val = make_label_arrays(Y_val)\n",
+    "# standardized_val_slopes= standardize_non_train(slopes_val, mean_train_slopes, std_train_slopes)\n",
+    "X_val_time_series, X_val_dt = make_feature_arrays(X_val)\n",
+    "\n",
+    "X_test = [x for xs in test_cells for x in xs[0]]\n",
+    "# Y_test= np.array([x for xs in test_cells for x in xs[1]])\n",
+    "Y_test = [x for xs in test_cells for x in xs[1]]\n",
+    "dc_test, slopes_test = make_label_arrays(Y_test)\n",
+    "# standardized_test_slopes= standardize_non_train(slopes_test, mean_train_slopes, std_train_slopes)\n",
+    "X_test_time_series, X_test_dt = make_feature_arrays(X_test)\n",
+    "\n",
+    "f_scaler, scaled_X_train_time_series = scale(X_train_time_series[...,1:])\n",
+    "_ , scaled_X_val_time_series = scale(X_val_time_series[...,1:], f_scaler)\n",
+    "_ , scaled_X_test_time_series = scale(X_test_time_series[...,1:], f_scaler)\n",
+    "\n",
+    "\n",
+    "dt_scaler, scaled_X_train_dt = scale(X_train_dt)\n",
+    "_ , scaled_X_val_dt = scale(X_val_dt, dt_scaler)\n",
+    "_ , scaled_X_test_dt = scale(X_test_dt, dt_scaler)\n",
+    "\n",
+    "l_scaler, scaled_slopes_train = scale(slopes_train)\n",
+    "_ , scaled_slopes_val = scale(slopes_val, l_scaler)\n",
+    "_ , scaled_slopes_test = scale(slopes_test, l_scaler)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "5dea1c4e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7f6d2f324d90>]"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.plot(scaled_X_train_time_series[0,0,:,0], scaled_X_train_time_series[0,0,:,1])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "b20f83f7",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[ 0.   ,  0.   ,  3.587, -0.563],\n",
+       "       [ 0.   ,  0.104,  3.571, -1.284],\n",
+       "       [ 0.   ,  0.198,  3.555, -1.945],\n",
+       "       [ 0.   ,  0.291,  3.539, -2.571],\n",
+       "       [ 0.   ,  0.378,  3.523, -3.165]])"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "X_train_time_series[0][0][:5]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "69198219",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 4200x1200 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "time_series_dat_1 = X_train_time_series[10][...,1:].reshape(-1,3)\n",
+    "fig , ax = plt.subplots(2,1, figsize=(14,4), dpi=300, facecolor='white')\n",
+    "ax[0].scatter(time_series_dat_1[:,0], time_series_dat_1[:,1], color='C7', s=2, marker='o')\n",
+    "ax[0].set_ylabel('Voltage')\n",
+    "ax[1].scatter(time_series_dat_1[:,0] ,time_series_dat_1[:,2], color='C7', s=2)\n",
+    "ax[1].set_xlabel('Time')\n",
+    "ax[1].set_ylabel('Current')\n",
+    "xmin, xmax = plt.xlim()\n",
+    "plt.savefig(f'media/generative.png', dpi=400, transparent=False, bbox_inches=\"tight\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "a13e1b16",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 4200x1200 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig , ax = plt.subplots(2,1, figsize=(14,4), dpi=300, facecolor='white')\n",
+    "features_index = time_series_dat_1.shape[0]//2\n",
+    "ax[0].scatter(time_series_dat_1[:features_index,0],time_series_dat_1[:features_index,1], label='Features', color='C9', s=2)\n",
+    "ax[0].scatter(time_series_dat_1[features_index:,0],time_series_dat_1[features_index:,1], label='Labels', color='C1', s=2)\n",
+    "ax[0].set_ylabel('Voltage')\n",
+    "ax[0].set_xlim([xmin, xmax])\n",
+    "ax[1].scatter(time_series_dat_1[:features_index,0], time_series_dat_1[:features_index,2], label='Features', color='C9', s=2)\n",
+    "ax[1].scatter(time_series_dat_1[features_index:,0], time_series_dat_1[features_index:,2], label='Labels', color='C1', s=2)\n",
+    "ax[1].set_xlabel('Time')\n",
+    "ax[1].set_ylabel('Current')\n",
+    "ax[1].set_xlim([xmin, xmax])\n",
+    "# plt.legend(markerscale=5, bbox_to_anchor=[1.12,2])\n",
+    "plt.savefig(f'media/generative_f_l.png', dpi=400, transparent=False, bbox_inches=\"tight\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "45982195",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[ 1.663e+04,  3.587e+00, -6.050e-01],\n",
+       "       [ 1.663e+04,  3.571e+00, -1.311e+00],\n",
+       "       [ 1.663e+04,  3.555e+00, -1.982e+00],\n",
+       "       ...,\n",
+       "       [ 1.733e+05,  2.032e+00, -4.400e+00],\n",
+       "       [ 1.733e+05,  2.024e+00, -4.400e+00],\n",
+       "       [ 1.736e+05,  2.002e+00, -7.174e-01]])"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "time_series_dat_1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "id": "f282371b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'slope 1')"
+      ]
+     },
+     "execution_count": 60,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.hist(slopes_train[:,0])\n",
+    "plt.title('slope 1')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "id": "243f5783",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'slope 1')"
+      ]
+     },
+     "execution_count": 61,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.hist(scaled_slopes_train[:,0])\n",
+    "plt.title('slope 1')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "id": "674631c7",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'slope 2')"
+      ]
+     },
+     "execution_count": 62,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.hist(scaled_slopes_train[:,1])\n",
+    "plt.title('slope 2')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "43718ff5",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 289,
+   "id": "9c9430c2",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████| 2/2 [00:00<00:00,  4.07it/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "def oversample(f_time_series, f_dt, labels, oversample_label_index=1):\n",
+    "    counts, bins, patches = plt.hist(labels[:,oversample_label_index], bins=20)\n",
+    "    plt.close()\n",
+    "    import numpy_indexed as npi\n",
+    "    import random\n",
+    "    max_samples = max(counts)\n",
+    "    ind = np.digitize(labels[:,oversample_label_index], bins)\n",
+    "    label_groups = npi.group_by(ind).split(labels[:,oversample_label_index])\n",
+    "\n",
+    "    balanced_f_time_series = f_time_series\n",
+    "    balanced_labels = labels\n",
+    "    balanced_f_dt = f_dt\n",
+    "    for sg in tqdm(label_groups[:-2]):\n",
+    "        n_samples = int(max_samples - len(sg))\n",
+    "        # Find indices for samples\n",
+    "        sample_indices = npi.indices(labels[:, oversample_label_index], np.random.choice(sg, n_samples))\n",
+    "        balanced_f_time_series = np.append(balanced_f_time_series,\n",
+    "                                                     f_time_series[sample_indices], axis=0)\n",
+    "        balanced_labels = np.append(balanced_labels,\n",
+    "                                                     labels[sample_indices], axis=0)\n",
+    "        balanced_f_dt = np.append(balanced_f_dt,\n",
+    "                                                f_dt[sample_indices], axis=0)\n",
+    "    \n",
+    "#     random.seed(0)\n",
+    "    shuffled_indices = list(range(len(balanced_f_time_series)))\n",
+    "    random.shuffle(indices)\n",
+    "    return balanced_f_time_series[shuffled_indices], balanced_f_dt[shuffled_indices], balanced_labels[shuffled_indices]\n",
+    "\n",
+    "balanced_X_train_time_series, balanced_X_train_dt, balanced_slopes_train = oversample(scaled_X_train_time_series,\n",
+    "                                                                                               X_train_dt,\n",
+    "                                                                                               scaled_slopes_train, oversample_label_index=1)\n",
+    "# balanced_X_train_time_series, balanced_X_train_dt, balanced_slopes_train = oversample(balanced_X_train_time_series,\n",
+    "#                                                                                                balanced_X_train_dt,\n",
+    "#                                                                                                balanced_slopes_train, oversample_label_index=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 290,
+   "id": "9daad0bb",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'slope 1')"
+      ]
+     },
+     "execution_count": 290,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.hist(balanced_slopes_train[:,0])\n",
+    "plt.title('slope 1')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 291,
+   "id": "f34f500c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'slope 2')"
+      ]
+     },
+     "execution_count": 291,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAX0AAAEICAYAAACzliQjAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8qNh9FAAAACXBIWXMAAAsTAAALEwEAmpwYAAASVElEQVR4nO3df8xe9V3/8efL8mNTpoB0DWurxdlNu8SV2S+g7ptMyKAwtZjohKirC9qZlGRL+ONbpgnbtPmyRIeZTmIX6jrdYI2bUl0jVsTMHxlwM5FRkHCPlbS10HsW2JZ9xW/Z2z+uT91Fd9+9f/TudbF9no/kynXO+3zOuT7npPfrPv1c55w7VYUkqQ/fMe4OSJJGx9CXpI4Y+pLUEUNfkjpi6EtSRwx9SeqIoa+uJXlPkj8ddz+kUTH0pRFL8soktyf59yTPJfmnJBePu1/qg6Evjd5ZwP3AjwLnAjuATyc5a6y9UhcMfXUhyf9JcjDJV5I8luSyGdr9TJK9SZ5N8vdJfnho2b4kNyZ5JMkzSf44ycuGlv9Ukgfbuv+c5Eem+4yqeqKqPlBVh6rqharaBpwBvHax91s6nqGvb3tJXgtcD/yvqnoFcAWwb5p2rwFuB94FLAV2A3+Z5IyhZr/Y1n818BrgN9u6FwLbgXcA3wv8EbAryZlz6N9aBqE/uZD9k+bD0FcPXgDOBNYkOb2q9lXVF6Zp9wvAp6tqT1X9f+B3gJcDPz7U5g+qan9VHQG2Ate2+ibgj6rq3nb2vgN4HrjkRB1L8t3AnwDvrarnTmYnpbkw9PVtr6omGZy9vwc4nOSOJK+apumrgCeH1vs6sB9YPtRm/9D0k20dgO8HbmhDO88meRZYObT8myR5OfCXwGer6v/Oc7ekBTH01YWq+nhVvZFBOBfw/mma/XtbDkCSMAjug0NtVg5Nf19bBwa/DLZW1dlDr++sqtun608b9vkL4ACDISFpJAx9fdtL8tokl7ag/U/g/wFfn6bpTuAtSS5LcjpwA4Mhmn8earM5yYok5wK/AXyi1T8M/HqSizPwXUnekuQV0/TndODPWj82tv9RSCNh6KsHZwI3A18CngJeCdx4fKOqegz4JeD3W9ufBn66qv5rqNnHgb8BngC+APx2W3cC+DXgD4BnGHwp+ysz9OfHgZ8CLgeeTfLV9vrfJ7WX0hzEP6IizU2SfcCvVtXfjrsv0kJ5pi9JHTH0JakjDu9IUkc805ekjpw27g6cyHnnnVerVq0adzck6VvKAw888KWqWjrdspd06K9atYqJiYlxd0OSvqUkeXKmZQ7vSFJHDH1J6sisoZ/kZUnuS/Kv7Tnj7231C5Lcm2QyySeOPX42yZltfrItXzW0rRtb/bEkV5yyvZIkTWsuZ/rPA5dW1euBtcD6JJcweGDVLVX1gwxuO7+utb8OeKbVb2ntSLIGuAZ4HbAe+MMkSxZxXyRJs5g19Gvgq2329PYq4FIGD42CwZ97u7pNb2jztOWXtacVbgDuqKrnq+qLDJ5NctFi7IQkaW7mNKafZEmSB4HDwB4GD5p6tqqOtiYH+MYzx5fTnjnelj/H4C8J/U99mnWGP2tTkokkE1NTU/PeIUnSzOYU+u0vAa0FVjA4O/+hU9WhqtpWVeuqat3SpdNeZipJWqB5Xb1TVc8C9wA/Bpyd5Nh1/iv4xh+aOEj7QxNt+fcA/zFcn2YdSdIIzOXqnaVJzm7TLwfeDDzKIPx/rjXbCNzZpne1edryv6vBA352Ade0q3suAFYD9y3SfkiS5mAud+SeD+xoV9p8B7Czqv4qySPAHUl+G/gX4LbW/jbgT5JMAkcYXLFDVe1NshN4BDgKbK6qFxZ3d15s1ZZPn8rNz2jfzW8Zy+dK0mxmDf2qegi4cJr6E0xz9U1V/Sfw8zNsayuwdf7dlCQtBu/IlaSOGPqS1BFDX5I6YuhLUkcMfUnqiKEvSR0x9CWpI4a+JHXE0Jekjhj6ktQRQ1+SOmLoS1JHDH1J6oihL0kdMfQlqSOGviR1xNCXpI4Y+pLUEUNfkjpi6EtSRwx9SeqIoS9JHTH0Jakjhr4kdcTQl6SOGPqS1JFZQz/JyiT3JHkkyd4k72z19yQ5mOTB9rpqaJ0bk0wmeSzJFUP19a02mWTLqdklSdJMTptDm6PADVX1uSSvAB5Isqctu6Wqfme4cZI1wDXA64BXAX+b5DVt8YeANwMHgPuT7KqqRxZjRyRJs5s19KvqEHCoTX8lyaPA8hOssgG4o6qeB76YZBK4qC2brKonAJLc0doa+pI0IvMa00+yCrgQuLeVrk/yUJLtSc5pteXA/qHVDrTaTHVJ0ojMOfSTnAV8EnhXVX0ZuBV4NbCWwf8EfncxOpRkU5KJJBNTU1OLsUlJUjOn0E9yOoPA/1hVfQqgqp6uqheq6uvAh/nGEM5BYOXQ6itabab6i1TVtqpaV1Xrli5dOt/9kSSdwFyu3glwG/BoVX1gqH7+ULOfBR5u07uAa5KcmeQCYDVwH3A/sDrJBUnOYPBl767F2Q1J0lzM5eqdnwB+Gfh8kgdb7d3AtUnWAgXsA94BUFV7k+xk8AXtUWBzVb0AkOR64C5gCbC9qvYu2p5IkmY1l6t3/hHINIt2n2CdrcDWaeq7T7SeJOnU8o5cSeqIoS9JHTH0Jakjhr4kdcTQl6SOGPqS1BFDX5I6YuhLUkcMfUnqiKEvSR0x9CWpI4a+JHXE0Jekjhj6ktQRQ1+SOmLoS1JHDH1J6oihL0kdMfQlqSOGviR1xNCXpI4Y+pLUEUNfkjpi6EtSRwx9SeqIoS9JHZk19JOsTHJPkkeS7E3yzlY/N8meJI+393NaPUk+mGQyyUNJ3jC0rY2t/eNJNp663ZIkTWcuZ/pHgRuqag1wCbA5yRpgC3B3Va0G7m7zAFcCq9trE3ArDH5JADcBFwMXATcd+0UhSRqNWUO/qg5V1efa9FeAR4HlwAZgR2u2A7i6TW8APloDnwXOTnI+cAWwp6qOVNUzwB5g/WLujCTpxOY1pp9kFXAhcC+wrKoOtUVPAcva9HJg/9BqB1ptprokaUTmHPpJzgI+Cbyrqr48vKyqCqjF6FCSTUkmkkxMTU0txiYlSc2cQj/J6QwC/2NV9alWfroN29DeD7f6QWDl0OorWm2m+otU1baqWldV65YuXTqffZEkzWIuV+8EuA14tKo+MLRoF3DsCpyNwJ1D9be1q3guAZ5rw0B3AZcnOad9gXt5q0mSRuS0ObT5CeCXgc8nebDV3g3cDOxMch3wJPDWtmw3cBUwCXwNeDtAVR1J8lvA/a3d+6rqyGLshCRpbmYN/ar6RyAzLL5smvYFbJ5hW9uB7fPpoCRp8XhHriR1xNCXpI4Y+pLUEUNfkjpi6EtSRwx9SeqIoS9JHTH0Jakjhr4kdcTQl6SOGPqS1BFDX5I6YuhLUkcMfUnqiKEvSR0x9CWpI4a+JHXE0Jekjhj6ktQRQ1+SOmLoS1JHDH1J6oihL0kdMfQlqSOGviR1xNCXpI7MGvpJtic5nOThodp7khxM8mB7XTW07MYkk0keS3LFUH19q00m2bL4uyJJms1czvQ/Aqyfpn5LVa1tr90ASdYA1wCva+v8YZIlSZYAHwKuBNYA17a2kqQROm22BlX1mSSr5ri9DcAdVfU88MUkk8BFbdlkVT0BkOSO1vaR+XdZkrRQJzOmf32Sh9rwzzmtthzYP9TmQKvNVJckjdBCQ/9W4NXAWuAQ8LuL1aEkm5JMJJmYmpparM1KkpjD8M50qurpY9NJPgz8VZs9CKwcarqi1ThB/fhtbwO2Aaxbt64W0r9xW7Xl02P77H03v2Vsny3ppW9BZ/pJzh+a/Vng2JU9u4BrkpyZ5AJgNXAfcD+wOskFSc5g8GXvroV3W5K0ELOe6Se5HXgTcF6SA8BNwJuSrAUK2Ae8A6Cq9ibZyeAL2qPA5qp6oW3neuAuYAmwvar2LvbOSJJObC5X71w7Tfm2E7TfCmydpr4b2D2v3kmSFpV35EpSRwx9SeqIoS9JHTH0Jakjhr4kdcTQl6SOGPqS1BFDX5I6YuhLUkcMfUnqiKEvSR0x9CWpI4a+JHXE0Jekjhj6ktQRQ1+SOmLoS1JHDH1J6oihL0kdMfQlqSOGviR1xNCXpI4Y+pLUEUNfkjpi6EtSRwx9SeqIoS9JHZk19JNsT3I4ycNDtXOT7EnyeHs/p9WT5INJJpM8lOQNQ+tsbO0fT7Lx1OyOJOlE5nKm/xFg/XG1LcDdVbUauLvNA1wJrG6vTcCtMPglAdwEXAxcBNx07BeFJGl0Zg39qvoMcOS48gZgR5veAVw9VP9oDXwWODvJ+cAVwJ6qOlJVzwB7+OZfJJKkU2yhY/rLqupQm34KWNamlwP7h9odaLWZ6t8kyaYkE0kmpqamFtg9SdJ0TvqL3KoqoBahL8e2t62q1lXVuqVLly7WZiVJLDz0n27DNrT3w61+EFg51G5Fq81UlySN0EJDfxdw7AqcjcCdQ/W3tat4LgGea8NAdwGXJzmnfYF7eatJkkbotNkaJLkdeBNwXpIDDK7CuRnYmeQ64Engra35buAqYBL4GvB2gKo6kuS3gPtbu/dV1fFfDkuSTrFZQ7+qrp1h0WXTtC1g8wzb2Q5sn1fvJEmLyjtyJakjhr4kdcTQl6SOGPqS1BFDX5I6YuhLUkcMfUnqiKEvSR0x9CWpI4a+JHXE0Jekjhj6ktQRQ1+SOmLoS1JHDH1J6oihL0kdMfQlqSOGviR1xNCXpI4Y+pLUEUNfkjpi6EtSRwx9SeqIoS9JHTH0Jakjhr4kdeSkQj/JviSfT/JgkolWOzfJniSPt/dzWj1JPphkMslDSd6wGDsgSZq7xTjT/8mqWltV69r8FuDuqloN3N3mAa4EVrfXJuDWRfhsSdI8nIrhnQ3Ajja9A7h6qP7RGvgscHaS80/B50uSZnCyoV/A3yR5IMmmVltWVYfa9FPAsja9HNg/tO6BVnuRJJuSTCSZmJqaOsnuSZKGnXaS67+xqg4meSWwJ8m/DS+sqkpS89lgVW0DtgGsW7duXutKkk7spM70q+pgez8M/DlwEfD0sWGb9n64NT8IrBxafUWrSZJGZMGhn+S7krzi2DRwOfAwsAvY2JptBO5s07uAt7WreC4BnhsaBpIkjcDJDO8sA/48ybHtfLyq/jrJ/cDOJNcBTwJvbe13A1cBk8DXgLefxGdLkhZgwaFfVU8Ar5+m/h/AZdPUC9i80M+TJJ0878iVpI4Y+pLUEUNfkjpi6EtSRwx9SeqIoS9JHTH0Jakjhr4kdcTQl6SOGPqS1BFDX5I6YuhLUkcMfUnqiKEvSR0x9CWpI4a+JHXE0Jekjhj6ktQRQ1+SOmLoS1JHDH1J6oihL0kdMfQlqSOGviR1xNCXpI4Y+pLUkZGHfpL1SR5LMplky6g/X5J6NtLQT7IE+BBwJbAGuDbJmlH2QZJ6Nuoz/YuAyap6oqr+C7gD2DDiPkhSt04b8ectB/YPzR8ALh5ukGQTsKnNfjXJYyPq2zicB3xpMTeY9y/m1l4yFv04fZvyOM2ul2P0/TMtGHXoz6qqtgHbxt2PUUgyUVXrxt2PlzqP09x4nGbnMRr98M5BYOXQ/IpWkySNwKhD/35gdZILkpwBXAPsGnEfJKlbIx3eqaqjSa4H7gKWANurau8o+/AS08Uw1iLwOM2Nx2l23R+jVNW4+yBJGhHvyJWkjhj6ktQRQ39MfBzF9JJsT3I4ycNDtXOT7EnyeHs/Z5x9HLckK5Pck+SRJHuTvLPVPU5DkrwsyX1J/rUdp/e2+gVJ7m0/e59oF5V0w9AfAx9HcUIfAdYfV9sC3F1Vq4G723zPjgI3VNUa4BJgc/v343F6seeBS6vq9cBaYH2SS4D3A7dU1Q8CzwDXja+Lo2foj4ePo5hBVX0GOHJceQOwo03vAK4eZZ9eaqrqUFV9rk1/BXiUwd3uHqchNfDVNnt6exVwKfBnrd7dcTL0x2O6x1EsH1NfvhUsq6pDbfopYNk4O/NSkmQVcCFwLx6nb5JkSZIHgcPAHuALwLNVdbQ16e5nz9DXt5QaXGPsdcZAkrOATwLvqqovDy/zOA1U1QtVtZbB3f8XAT803h6Nn6E/Hj6OYn6eTnI+QHs/POb+jF2S0xkE/seq6lOt7HGaQVU9C9wD/BhwdpJjN6Z297Nn6I+Hj6OYn13Axja9EbhzjH0ZuyQBbgMeraoPDC3yOA1JsjTJ2W365cCbGXz/cQ/wc61Zd8fJO3LHJMlVwO/xjcdRbB1vj14aktwOvInBI3CfBm4C/gLYCXwf8CTw1qo6/svebiR5I/APwOeBr7fyuxmM63ucmiQ/wuCL2iUMTnB3VtX7kvwAg4snzgX+Bfilqnp+fD0dLUNfkjri8I4kdcTQl6SOGPqS1BFDX5I6YuhLUkcMfUnqiKEvSR35b/sbDowedds6AAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.hist(balanced_slopes_train[:,1])\n",
+    "plt.title('slope 2')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 292,
+   "id": "f23a8b0e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'slope 2')"
+      ]
+     },
+     "execution_count": 292,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.hist(scaled_slopes_train[:,1])\n",
+    "plt.title('slope 2')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 293,
+   "id": "ad6a6878",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# scaled_X_train_dt, mean_X_train_dt, std_X_train_dt  = standardize_train(X_train_dt)\n",
+    "# scaled_X_val_dt = standardize_non_train(X_val_dt, mean_X_train_dt, std_X_train_dt)\n",
+    "\n",
+    "# scaled_X_train_time_series, mean_X_train_time_series, std_X_train_time_series = standardize_train(X_train_time_series)\n",
+    "# scaled_X_val_time_series = standardize_non_train(X_val_time_series, mean_X_train_time_series, std_X_train_time_series)\n",
+    "# X_train_time_series = X_train_time_series\n",
+    "# print\n",
+    "# scaled_X_train_time_series = scaled_X_train_time_series[...,1:]\n",
+    "# scaled_X_val_time_series = scaled_X_val_time_series[...,1:]\n",
+    "\n",
+    "\n",
+    "# test_X_train_time_series = rev_scale(scaled_X_train_time_series[...,1:], scaler)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 294,
+   "id": "5526fd4c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# # best model\n",
+    "# from dataclasses import dataclass\n",
+    "# @dataclass\n",
+    "# class Config:\n",
+    "#     batch_size: int\n",
+    "#     buffer_size: int\n",
+    "#     rnn_units: int\n",
+    "#     hidden_dim: int\n",
+    "#     embedding_dim: int\n",
+    "#     reg_strength: float\n",
+    "#     lr: float\n",
+    "#     drop_rate: float\n",
+    "        \n",
+    "# config = Config(batch_size=16, \n",
+    "#                 buffer_size=10000,\n",
+    "#                 rnn_units=64,\n",
+    "#                 hidden_dim=64,\n",
+    "#                 embedding_dim=32,\n",
+    "#                 reg_strength=0,\n",
+    "#                 lr=1e-3,\n",
+    "#                 drop_rate=0.1\n",
+    "#                )\n",
+    "\n",
+    "# def build_model(L, T, cycle_window_size=10, reg_strength=0, n_features=3):\n",
+    "#     inputs = tf.keras.Input(shape=(cycle_window_size, T , n_features))\n",
+    "#     input_dt = tf.keras.Input(shape=(cycle_window_size))\n",
+    "#     print(f'input: {inputs.shape}')\n",
+    "#     print(f'input_dt: {input_dt.shape}')\n",
+    "# #     x=inputs.Reshape(100, cycle_window_size, 3)\n",
+    "# #     x =  tf.keras.layers.Reshape((cycle_window_size* T , 2))(inputs)\n",
+    "# #     conv_1d_layer = tf.keras.layers.Conv1D(32, 50, activation='relu')\n",
+    "# #     max_pooling = \n",
+    "# #     blstm_layer = tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(16))\n",
+    "# #     x = tf.keras.layers.Embedding(100,16)(inputs)\n",
+    "#     x = tf.keras.layers.TimeDistributed(tf.keras.layers.Conv1D(32, 100), input_shape=(cycle_window_size, T , n_features))(inputs)\n",
+    "# #     x = tf.keras.layers.TimeDistributed(tf.keras.layers.Conv1D(32, 25), input_shape=(cycle_window_size, T , 2))(x)\n",
+    "# #     x = tf.keras.layers.TimeDistributed(tf.keras.layers.Conv1D(32, 25), input_shape=(cycle_window_size, T , 2))(x)\n",
+    "# #     x = tf.keras.layers.TimeDistributed(tf.keras.layers.Conv1D(32, 25), input_shape=(cycle_window_size, T , 2))(x)\n",
+    "\n",
+    "#     print(f'output 1 conv: {x.shape}')\n",
+    "# #     x = tf.keras.layers.TimeDistributed(tf.keras.layers.MaxPool1D(pool_size=2))(x)\n",
+    "# #     print(f'output max_pooling 1: {x.shape}')\n",
+    "# #     x = tf.keras.layers.TimeDistributed(tf.keras.layers.Conv1D(32, 25), input_shape=(cycle_window_size, 10 ,2))(x)\n",
+    "# #     print(f'output 2 conv: {x.shape}')\n",
+    "# #     x = tf.keras.layers.TimeDistributed(tf.keras.layers.MaxPool1D(pool_size=2))(x)\n",
+    "# #     print(f'output max_pooling 2: {x.shape}')\n",
+    "# #     x = tf.keras.layers.TimeDistributed(tf.keras.layers.Conv1D(32, 25), input_shape=(cycle_window_size, 2))(x)\n",
+    "# #     print(f'output 3 conv: {x.shape}')\n",
+    "# #     x = tf.keras.layers.TimeDistributed(tf.keras.layers.MaxPool1D(pool_size=2))(x)\n",
+    "# #     print(f'output max_pooling 3: {x.shape}')\n",
+    "# #     x = tf.keras.layers.TimeDistributed(tf.keras.layers.Conv1D(32, 10), input_shape=(cycle_window_size, 2))(x)\n",
+    "# #     x = tf.keras.layers.TimeDistributed(tf.keras.layers.Conv1D(32, 25), input_shape=(100, 2))(x)\n",
+    "# #     print(f'output 3 conv: {x.shape}')\n",
+    "# #     x = tf.keras.layers.TimeDistributed(max_pooling)(x)\n",
+    "# #     print(f'output max_pooling 2: {x.shape}')\n",
+    "# #     x = tf.keras.layers.LayerNormalization()(x)\n",
+    "#     x = tf.keras.layers.TimeDistributed(tf.keras.layers.Dropout(config.drop_rate))(x)\n",
+    "#     print(f'output dropout: {x.shape}')\n",
+    "# #     x = tf.keras.layers.Reshape((cycle_window_size, 32))(x)\n",
+    "#     x = tf.keras.layers.TimeDistributed(tf.keras.layers.GlobalAveragePooling1D())(x)\n",
+    "# #     x = tf.keras.layers.Flatten()(x)\n",
+    "# #     x = tf.keras.layers.TimeDistributed(tf.keras.layers.Flatten())(x)\n",
+    "# #     \n",
+    "#     print(f'output GlobalAveragePooling1D: {x.shape}')\n",
+    "# #     conv_1d_layer = tf.keras.layers.Conv1D(64, 5, input_shape=(100,64))\n",
+    "# #     x = tf.keras.layers.TimeDistributed(conv_1d_layer, input_shape=(100,))(x)\n",
+    "#     print(x.shape)\n",
+    "#     x = tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(16, return_sequences=True))(x)\n",
+    "#     x = tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(16, return_sequences=False))(x)\n",
+    "#     print(f'output bilstm dist: {x.shape}')\n",
+    "# #     x = tf.keras.layers.Concatenate()([x, input_dt])\n",
+    "# #     x = tf.keras.layers.LayerNormalization()(x)\n",
+    "# #     x = tf.keras.layers.BatchNormalization()(x)\n",
+    "# #     x = tf.keras.layers.Dropout(config.drop_rate)(x)\n",
+    "#     x = tf.keras.layers.Dense(64, kernel_regularizer=tf.keras.regularizers.L1(l1=reg_strength), activation='tanh')(x)\n",
+    "# #     x = tf.keras.layers.BatchNormalization()(x)\n",
+    "#     x = tf.keras.layers.LayerNormalization()(x)\n",
+    "#     x = tf.keras.layers.Dropout(config.drop_rate)(x)\n",
+    "#     x = tf.keras.layers.Dense(16, kernel_regularizer=tf.keras.regularizers.L1(l1=reg_strength), activation='tanh')(x)\n",
+    "# #     x = tf.keras.layers.BatchNormalization()(x)\n",
+    "# #     e = tf.keras.layers.Embedding(input_dim=config.vocab_size, \n",
+    "# #                                     output_dim=config.embedding_dim,\n",
+    "# #                                     mask_zero=True)(inputs)\n",
+    "#     x = tf.keras.layers.LayerNormalization()(x)\n",
+    "#     x = tf.keras.layers.Dropout(config.drop_rate)(x)\n",
+    "#     yhat = tf.keras.layers.Dense(2, kernel_regularizer=tf.keras.regularizers.L1(l1=reg_strength)\n",
+    "#                                  )(x) # activation=tf.keras.layers.LeakyReLU(alpha=0.01)\n",
+    "#     model = tf.keras.Model(inputs=[inputs, input_dt], outputs=yhat)\n",
+    "# #     model = tf.keras.Model(inputs=inputs, outputs=yhat)\n",
+    "#     return model\n",
+    "# tf.keras.backend.clear_session()\n",
+    "# L = None\n",
+    "# T = 100\n",
+    "\n",
+    "# from keras import backend as K\n",
+    "# def root_mean_squared_error(y_true, y_pred):\n",
+    "#         return K.sqrt(K.mean(K.square(y_pred - y_true), axis=-1)) \n",
+    "# n_features = scaled_X_train_time_series.shape[-1]\n",
+    "# model = build_model(L, T, cycle_window_size=input_window_size, reg_strength=0.001, n_features=n_features)\n",
+    "# opt = tf.optimizers.Adam(1e-3)\n",
+    "# model.compile(opt, loss='mae')  #root_mean_squared_error\n",
+    "# #   loss='mean_absolute_error')\n",
+    "  \n",
+    "# model.summary()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 324,
+   "id": "4b988b3f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "input: (None, 50, 100, 3)\n",
+      "input_dt: (None, 50)\n",
+      "output 1 conv: (None, 50, 1, 32)\n",
+      "output dropout: (None, 50, 1, 32)\n",
+      "output GlobalAveragePooling1D: (None, 50, 32)\n",
+      "(None, 50, 32)\n",
+      "output bilstm dist: (None, 16)\n",
+      "Model: \"model\"\n",
+      "__________________________________________________________________________________________________\n",
+      " Layer (type)                   Output Shape         Param #     Connected to                     \n",
+      "==================================================================================================\n",
+      " input_1 (InputLayer)           [(None, 50, 100, 3)  0           []                               \n",
+      "                                ]                                                                 \n",
+      "                                                                                                  \n",
+      " time_distributed (TimeDistribu  (None, 50, 1, 32)   9632        ['input_1[0][0]']                \n",
+      " ted)                                                                                             \n",
+      "                                                                                                  \n",
+      " time_distributed_1 (TimeDistri  (None, 50, 1, 32)   0           ['time_distributed[0][0]']       \n",
+      " buted)                                                                                           \n",
+      "                                                                                                  \n",
+      " time_distributed_2 (TimeDistri  (None, 50, 32)      0           ['time_distributed_1[0][0]']     \n",
+      " buted)                                                                                           \n",
+      "                                                                                                  \n",
+      " lstm (LSTM)                    (None, 50, 16)       3136        ['time_distributed_2[0][0]']     \n",
+      "                                                                                                  \n",
+      " lstm_1 (LSTM)                  (None, 16)           2112        ['lstm[0][0]']                   \n",
+      "                                                                                                  \n",
+      " dense (Dense)                  (None, 32)           544         ['lstm_1[0][0]']                 \n",
+      "                                                                                                  \n",
+      " layer_normalization (LayerNorm  (None, 32)          64          ['dense[0][0]']                  \n",
+      " alization)                                                                                       \n",
+      "                                                                                                  \n",
+      " dropout_1 (Dropout)            (None, 32)           0           ['layer_normalization[0][0]']    \n",
+      "                                                                                                  \n",
+      " dense_1 (Dense)                (None, 16)           528         ['dropout_1[0][0]']              \n",
+      "                                                                                                  \n",
+      " layer_normalization_1 (LayerNo  (None, 16)          32          ['dense_1[0][0]']                \n",
+      " rmalization)                                                                                     \n",
+      "                                                                                                  \n",
+      " dropout_2 (Dropout)            (None, 16)           0           ['layer_normalization_1[0][0]']  \n",
+      "                                                                                                  \n",
+      " input_2 (InputLayer)           [(None, 50)]         0           []                               \n",
+      "                                                                                                  \n",
+      " dense_2 (Dense)                (None, 2)            34          ['dropout_2[0][0]']              \n",
+      "                                                                                                  \n",
+      "==================================================================================================\n",
+      "Total params: 16,082\n",
+      "Trainable params: 16,082\n",
+      "Non-trainable params: 0\n",
+      "__________________________________________________________________________________________________\n"
+     ]
+    }
+   ],
+   "source": [
+    "# best model\n",
+    "from dataclasses import dataclass\n",
+    "@dataclass\n",
+    "class Config:\n",
+    "    batch_size: int\n",
+    "    buffer_size: int\n",
+    "    rnn_units: int\n",
+    "    hidden_dim: int\n",
+    "    embedding_dim: int\n",
+    "    reg_strength: float\n",
+    "    lr: float\n",
+    "    drop_rate: float\n",
+    "        \n",
+    "config = Config(batch_size=16, \n",
+    "                buffer_size=10000,\n",
+    "                rnn_units=64,\n",
+    "                hidden_dim=64,\n",
+    "                embedding_dim=32,\n",
+    "                reg_strength=0,\n",
+    "                lr=1e-3,\n",
+    "                drop_rate=0.1\n",
+    "               )\n",
+    "\n",
+    "def build_model(L, T, cycle_window_size=10, reg_strength=0, n_features=3):\n",
+    "    inputs = tf.keras.Input(shape=(cycle_window_size, T , n_features))\n",
+    "    input_dt = tf.keras.Input(shape=(cycle_window_size))\n",
+    "    print(f'input: {inputs.shape}')\n",
+    "    print(f'input_dt: {input_dt.shape}')\n",
+    "#     x=inputs.Reshape(100, cycle_window_size, 3)\n",
+    "#     x =  tf.keras.layers.Reshape((cycle_window_size* T , 2))(inputs)\n",
+    "#     conv_1d_layer = tf.keras.layers.Conv1D(32, 50, activation='relu')\n",
+    "#     max_pooling = \n",
+    "#     blstm_layer = tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(16))\n",
+    "#     x = tf.keras.layers.Embedding(100,16)(inputs)\n",
+    "    x = tf.keras.layers.TimeDistributed(tf.keras.layers.Conv1D(32, 100), input_shape=(cycle_window_size, T , n_features))(inputs)\n",
+    "#     x = tf.keras.layers.TimeDistributed(tf.keras.layers.MaxPool1D(pool_size=2))(x)\n",
+    "\n",
+    "    #     x = tf.keras.layers.TimeDistributed(tf.keras.layers.Conv1D(32, 25), input_shape=(cycle_window_size, T , 2))(x)\n",
+    "#     x = tf.keras.layers.TimeDistributed(tf.keras.layers.Conv1D(32, 25), input_shape=(cycle_window_size, T , 2))(x)\n",
+    "#     x = tf.keras.layers.TimeDistributed(tf.keras.layers.Conv1D(32, 25), input_shape=(cycle_window_size, T , 2))(x)\n",
+    "\n",
+    "    print(f'output 1 conv: {x.shape}')\n",
+    "#     x = tf.keras.layers.TimeDistributed(tf.keras.layers.MaxPool1D(pool_size=2))(x)\n",
+    "#     print(f'output max_pooling 1: {x.shape}')\n",
+    "#     x = tf.keras.layers.TimeDistributed(tf.keras.layers.Conv1D(32, 25), input_shape=(cycle_window_size, 10 ,2))(x)\n",
+    "#     print(f'output 2 conv: {x.shape}')\n",
+    "#     x = tf.keras.layers.TimeDistributed(tf.keras.layers.MaxPool1D(pool_size=2))(x)\n",
+    "#     print(f'output max_pooling 2: {x.shape}')\n",
+    "#     x = tf.keras.layers.TimeDistributed(tf.keras.layers.Conv1D(32, 25), input_shape=(cycle_window_size, 2))(x)\n",
+    "#     print(f'output 3 conv: {x.shape}')\n",
+    "#     x = tf.keras.layers.TimeDistributed(tf.keras.layers.MaxPool1D(pool_size=2))(x)\n",
+    "#     print(f'output max_pooling 3: {x.shape}')\n",
+    "#     x = tf.keras.layers.TimeDistributed(tf.keras.layers.Conv1D(32, 10), input_shape=(cycle_window_size, 2))(x)\n",
+    "#     x = tf.keras.layers.TimeDistributed(tf.keras.layers.Conv1D(32, 25), input_shape=(100, 2))(x)\n",
+    "#     print(f'output 3 conv: {x.shape}')\n",
+    "#     x = tf.keras.layers.TimeDistributed(max_pooling)(x)\n",
+    "#     print(f'output max_pooling 2: {x.shape}')\n",
+    "#     x = tf.keras.layers.LayerNormalization()(x)\n",
+    "    x = tf.keras.layers.TimeDistributed(tf.keras.layers.Dropout(config.drop_rate))(x)\n",
+    "    print(f'output dropout: {x.shape}')\n",
+    "#     x = tf.keras.layers.Reshape((cycle_window_size, 32))(x)\n",
+    "    x = tf.keras.layers.TimeDistributed(tf.keras.layers.GlobalAveragePooling1D())(x)\n",
+    "#     x = tf.keras.layers.Flatten()(x)\n",
+    "#     x = tf.keras.layers.TimeDistributed(tf.keras.layers.Flatten())(x)\n",
+    "#     \n",
+    "    print(f'output GlobalAveragePooling1D: {x.shape}')\n",
+    "#     conv_1d_layer = tf.keras.layers.Conv1D(64, 5, input_shape=(100,64))\n",
+    "#     x = tf.keras.layers.TimeDistributed(conv_1d_layer, input_shape=(100,))(x)\n",
+    "    print(x.shape)\n",
+    "#     x = tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(16, return_sequences=True))(x)\n",
+    "#     x = tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(16, return_sequences=False))(x)\n",
+    "    x = tf.keras.layers.LSTM(16, return_sequences=True)(x)\n",
+    "    x = tf.keras.layers.LSTM(16, return_sequences=False)(x)\n",
+    "\n",
+    "    print(f'output bilstm dist: {x.shape}')\n",
+    "#     x = tf.keras.layers.Concatenate()([x, input_dt])\n",
+    "#     x = tf.keras.layers.LayerNormalization()(x)\n",
+    "#     x = tf.keras.layers.BatchNormalization()(x)\n",
+    "#     x = tf.keras.layers.Dropout(config.drop_rate)(x)\n",
+    "    x = tf.keras.layers.Dense(32, kernel_regularizer=tf.keras.regularizers.L1(l1=reg_strength), activation='tanh')(x)\n",
+    "#     x = tf.keras.layers.BatchNormalization()(x)\n",
+    "    x = tf.keras.layers.LayerNormalization()(x)\n",
+    "    x = tf.keras.layers.Dropout(config.drop_rate)(x)\n",
+    "    x = tf.keras.layers.Dense(16, kernel_regularizer=tf.keras.regularizers.L1(l1=reg_strength), activation='tanh')(x)\n",
+    "#     x = tf.keras.layers.BatchNormalization()(x)\n",
+    "#     e = tf.keras.layers.Embedding(input_dim=config.vocab_size, \n",
+    "#                                     output_dim=config.embedding_dim,\n",
+    "#                                     mask_zero=True)(inputs)\n",
+    "    x = tf.keras.layers.LayerNormalization()(x)\n",
+    "    x = tf.keras.layers.Dropout(config.drop_rate)(x)\n",
+    "    yhat = tf.keras.layers.Dense(2, kernel_regularizer=tf.keras.regularizers.L1(l1=reg_strength),\n",
+    "                                 activation='tanh')(x) # activation=tf.keras.layers.LeakyReLU(alpha=0.01)\n",
+    "    model = tf.keras.Model(inputs=[inputs, input_dt], outputs=yhat)\n",
+    "#     model = tf.keras.Model(inputs=inputs, outputs=yhat)\n",
+    "    return model\n",
+    "tf.keras.backend.clear_session()\n",
+    "L = None\n",
+    "T = 100\n",
+    "\n",
+    "from keras import backend as K\n",
+    "def root_mean_squared_error(y_true, y_pred):\n",
+    "        return K.sqrt(K.mean(K.square(y_pred - y_true), axis=-1)) \n",
+    "n_features = scaled_X_train_time_series.shape[-1]\n",
+    "model = build_model(L, T, cycle_window_size=input_window_size, reg_strength=0.001, n_features=n_features)\n",
+    "opt = tf.optimizers.Adam(1e-3)\n",
+    "model.compile(opt, loss='huber')  #root_mean_squared_error\n",
+    "#   loss='mean_absolute_error')\n",
+    "  \n",
+    "model.summary()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 325,
+   "id": "b9a600aa",
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Epoch 1/1000\n",
+      "94/94 [==============================] - 7s 34ms/step - loss: 0.4357 - val_loss: 0.3653 - lr: 0.0010\n",
+      "Epoch 2/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.4040 - val_loss: 0.3462 - lr: 0.0010\n",
+      "Epoch 3/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.3799 - val_loss: 0.3315 - lr: 0.0010\n",
+      "Epoch 4/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.3574 - val_loss: 0.3115 - lr: 0.0010\n",
+      "Epoch 5/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.3366 - val_loss: 0.3046 - lr: 0.0010\n",
+      "Epoch 6/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.3155 - val_loss: 0.2851 - lr: 0.0010\n",
+      "Epoch 7/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.3007 - val_loss: 0.2767 - lr: 0.0010\n",
+      "Epoch 8/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.2846 - val_loss: 0.2638 - lr: 0.0010\n",
+      "Epoch 9/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.2661 - val_loss: 0.2435 - lr: 0.0010\n",
+      "Epoch 10/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.2606 - val_loss: 0.2472 - lr: 0.0010\n",
+      "Epoch 11/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.2471 - val_loss: 0.2304 - lr: 0.0010\n",
+      "Epoch 12/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.2349 - val_loss: 0.2178 - lr: 0.0010\n",
+      "Epoch 13/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.2196 - val_loss: 0.2273 - lr: 0.0010\n",
+      "Epoch 14/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.2131 - val_loss: 0.2295 - lr: 0.0010\n",
+      "Epoch 15/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.2011 - val_loss: 0.1907 - lr: 0.0010\n",
+      "Epoch 16/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.2061 - val_loss: 0.1913 - lr: 0.0010\n",
+      "Epoch 17/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1881 - val_loss: 0.1918 - lr: 0.0010\n",
+      "Epoch 18/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1982 - val_loss: 0.1919 - lr: 0.0010\n",
+      "Epoch 19/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1846 - val_loss: 0.1900 - lr: 0.0010\n",
+      "Epoch 20/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1791 - val_loss: 0.1969 - lr: 0.0010\n",
+      "Epoch 21/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1843 - val_loss: 0.1821 - lr: 0.0010\n",
+      "Epoch 22/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1755 - val_loss: 0.1816 - lr: 0.0010\n",
+      "Epoch 23/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1741 - val_loss: 0.1570 - lr: 0.0010\n",
+      "Epoch 24/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1668 - val_loss: 0.1515 - lr: 0.0010\n",
+      "Epoch 25/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1633 - val_loss: 0.1520 - lr: 0.0010\n",
+      "Epoch 26/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1524 - val_loss: 0.1575 - lr: 0.0010\n",
+      "Epoch 27/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1566 - val_loss: 0.2214 - lr: 0.0010\n",
+      "Epoch 28/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1870 - val_loss: 0.1548 - lr: 0.0010\n",
+      "Epoch 29/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1609 - val_loss: 0.1544 - lr: 0.0010\n",
+      "Epoch 30/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1513 - val_loss: 0.1390 - lr: 9.0000e-04\n",
+      "Epoch 31/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1506 - val_loss: 0.1539 - lr: 9.0000e-04\n",
+      "Epoch 32/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1529 - val_loss: 0.1724 - lr: 9.0000e-04\n",
+      "Epoch 33/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1496 - val_loss: 0.1395 - lr: 9.0000e-04\n",
+      "Epoch 34/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1483 - val_loss: 0.1747 - lr: 9.0000e-04\n",
+      "Epoch 35/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1503 - val_loss: 0.1379 - lr: 9.0000e-04\n",
+      "Epoch 36/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1450 - val_loss: 0.1772 - lr: 9.0000e-04\n",
+      "Epoch 37/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1451 - val_loss: 0.1751 - lr: 9.0000e-04\n",
+      "Epoch 38/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1422 - val_loss: 0.1339 - lr: 9.0000e-04\n",
+      "Epoch 39/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1382 - val_loss: 0.1492 - lr: 9.0000e-04\n",
+      "Epoch 40/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1410 - val_loss: 0.1442 - lr: 9.0000e-04\n",
+      "Epoch 41/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1421 - val_loss: 0.1396 - lr: 9.0000e-04\n",
+      "Epoch 42/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1383 - val_loss: 0.1314 - lr: 9.0000e-04\n",
+      "Epoch 43/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1405 - val_loss: 0.1362 - lr: 9.0000e-04\n",
+      "Epoch 44/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1397 - val_loss: 0.1319 - lr: 9.0000e-04\n",
+      "Epoch 45/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1415 - val_loss: 0.1389 - lr: 9.0000e-04\n",
+      "Epoch 46/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1376 - val_loss: 0.1346 - lr: 9.0000e-04\n",
+      "Epoch 47/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1427 - val_loss: 0.1292 - lr: 9.0000e-04\n",
+      "Epoch 48/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1389 - val_loss: 0.1289 - lr: 9.0000e-04\n",
+      "Epoch 49/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1368 - val_loss: 0.1331 - lr: 9.0000e-04\n",
+      "Epoch 50/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1368 - val_loss: 0.1311 - lr: 9.0000e-04\n",
+      "Epoch 51/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1362 - val_loss: 0.1332 - lr: 9.0000e-04\n",
+      "Epoch 52/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1343 - val_loss: 0.1259 - lr: 9.0000e-04\n",
+      "Epoch 53/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1417 - val_loss: 0.1350 - lr: 9.0000e-04\n",
+      "Epoch 54/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1362 - val_loss: 0.1277 - lr: 9.0000e-04\n",
+      "Epoch 55/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1343 - val_loss: 0.1295 - lr: 9.0000e-04\n",
+      "Epoch 56/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1330 - val_loss: 0.1325 - lr: 9.0000e-04\n",
+      "Epoch 57/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1346 - val_loss: 0.1364 - lr: 9.0000e-04\n",
+      "Epoch 58/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1393 - val_loss: 0.1425 - lr: 8.1000e-04\n",
+      "Epoch 59/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1368 - val_loss: 0.1288 - lr: 8.1000e-04\n",
+      "Epoch 60/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1380 - val_loss: 0.1272 - lr: 8.1000e-04\n",
+      "Epoch 61/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1337 - val_loss: 0.1292 - lr: 8.1000e-04\n",
+      "Epoch 62/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1367 - val_loss: 0.1386 - lr: 8.1000e-04\n",
+      "Epoch 63/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1363 - val_loss: 0.1350 - lr: 7.2900e-04\n",
+      "Epoch 64/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1306 - val_loss: 0.1278 - lr: 7.2900e-04\n",
+      "Epoch 65/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1323 - val_loss: 0.1330 - lr: 7.2900e-04\n",
+      "Epoch 66/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1321 - val_loss: 0.1284 - lr: 7.2900e-04\n",
+      "Epoch 67/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1328 - val_loss: 0.1248 - lr: 7.2900e-04\n",
+      "Epoch 68/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1298 - val_loss: 0.1253 - lr: 7.2900e-04\n",
+      "Epoch 69/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1320 - val_loss: 0.1302 - lr: 7.2900e-04\n",
+      "Epoch 70/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1316 - val_loss: 0.1289 - lr: 7.2900e-04\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Epoch 71/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1321 - val_loss: 0.1271 - lr: 7.2900e-04\n",
+      "Epoch 72/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1305 - val_loss: 0.1276 - lr: 7.2900e-04\n",
+      "Epoch 73/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1301 - val_loss: 0.1248 - lr: 6.5610e-04\n",
+      "Epoch 74/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1275 - val_loss: 0.1271 - lr: 6.5610e-04\n",
+      "Epoch 75/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1357 - val_loss: 0.1360 - lr: 6.5610e-04\n",
+      "Epoch 76/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1301 - val_loss: 0.1262 - lr: 6.5610e-04\n",
+      "Epoch 77/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1336 - val_loss: 0.1283 - lr: 6.5610e-04\n",
+      "Epoch 78/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1293 - val_loss: 0.1292 - lr: 5.9049e-04\n",
+      "Epoch 79/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1325 - val_loss: 0.1295 - lr: 5.9049e-04\n",
+      "Epoch 80/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1292 - val_loss: 0.1273 - lr: 5.9049e-04\n",
+      "Epoch 81/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1307 - val_loss: 0.1312 - lr: 5.9049e-04\n",
+      "Epoch 82/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1371 - val_loss: 0.1249 - lr: 5.9049e-04\n",
+      "Epoch 83/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1327 - val_loss: 0.1243 - lr: 5.3144e-04\n",
+      "Epoch 84/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1282 - val_loss: 0.1248 - lr: 5.3144e-04\n",
+      "Epoch 85/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1299 - val_loss: 0.1362 - lr: 5.3144e-04\n",
+      "Epoch 86/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1268 - val_loss: 0.1267 - lr: 5.3144e-04\n",
+      "Epoch 87/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1286 - val_loss: 0.1433 - lr: 5.3144e-04\n",
+      "Epoch 88/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1325 - val_loss: 0.1292 - lr: 5.3144e-04\n",
+      "Epoch 89/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1264 - val_loss: 0.1278 - lr: 4.7830e-04\n",
+      "Epoch 90/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1283 - val_loss: 0.1288 - lr: 4.7830e-04\n",
+      "Epoch 91/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1297 - val_loss: 0.1253 - lr: 4.7830e-04\n",
+      "Epoch 92/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1299 - val_loss: 0.1226 - lr: 4.7830e-04\n",
+      "Epoch 93/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1264 - val_loss: 0.1214 - lr: 4.7830e-04\n",
+      "Epoch 94/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1266 - val_loss: 0.1233 - lr: 4.7830e-04\n",
+      "Epoch 95/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1288 - val_loss: 0.1253 - lr: 4.7830e-04\n",
+      "Epoch 96/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1230 - val_loss: 0.1267 - lr: 4.7830e-04\n",
+      "Epoch 97/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1270 - val_loss: 0.1269 - lr: 4.7830e-04\n",
+      "Epoch 98/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1249 - val_loss: 0.1285 - lr: 4.7830e-04\n",
+      "Epoch 99/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1256 - val_loss: 0.1206 - lr: 4.3047e-04\n",
+      "Epoch 100/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1238 - val_loss: 0.1226 - lr: 4.3047e-04\n",
+      "Epoch 101/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1253 - val_loss: 0.1206 - lr: 4.3047e-04\n",
+      "Epoch 102/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1284 - val_loss: 0.1247 - lr: 4.3047e-04\n",
+      "Epoch 103/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1240 - val_loss: 0.1306 - lr: 4.3047e-04\n",
+      "Epoch 104/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1272 - val_loss: 0.1212 - lr: 4.3047e-04\n",
+      "Epoch 105/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1248 - val_loss: 0.1315 - lr: 3.8742e-04\n",
+      "Epoch 106/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1240 - val_loss: 0.1222 - lr: 3.8742e-04\n",
+      "Epoch 107/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1271 - val_loss: 0.1222 - lr: 3.8742e-04\n",
+      "Epoch 108/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1248 - val_loss: 0.1337 - lr: 3.8742e-04\n",
+      "Epoch 109/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1227 - val_loss: 0.1215 - lr: 3.8742e-04\n",
+      "Epoch 110/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1250 - val_loss: 0.1238 - lr: 3.4868e-04\n",
+      "Epoch 111/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1250 - val_loss: 0.1224 - lr: 3.4868e-04\n",
+      "Epoch 112/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1235 - val_loss: 0.1260 - lr: 3.4868e-04\n",
+      "Epoch 113/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1245 - val_loss: 0.1220 - lr: 3.4868e-04\n",
+      "Epoch 114/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1227 - val_loss: 0.1214 - lr: 3.4868e-04\n",
+      "Epoch 115/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1256 - val_loss: 0.1194 - lr: 3.1381e-04\n",
+      "Epoch 116/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1248 - val_loss: 0.1218 - lr: 3.1381e-04\n",
+      "Epoch 117/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1233 - val_loss: 0.1416 - lr: 3.1381e-04\n",
+      "Epoch 118/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1251 - val_loss: 0.1221 - lr: 3.1381e-04\n",
+      "Epoch 119/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1236 - val_loss: 0.1212 - lr: 3.1381e-04\n",
+      "Epoch 120/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1228 - val_loss: 0.1217 - lr: 3.1381e-04\n",
+      "Epoch 121/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1237 - val_loss: 0.1208 - lr: 2.8243e-04\n",
+      "Epoch 122/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1216 - val_loss: 0.1249 - lr: 2.8243e-04\n",
+      "Epoch 123/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1219 - val_loss: 0.1203 - lr: 2.8243e-04\n",
+      "Epoch 124/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1243 - val_loss: 0.1220 - lr: 2.8243e-04\n",
+      "Epoch 125/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1216 - val_loss: 0.1238 - lr: 2.8243e-04\n",
+      "Epoch 126/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1219 - val_loss: 0.1225 - lr: 2.5419e-04\n",
+      "Epoch 127/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1221 - val_loss: 0.1195 - lr: 2.5419e-04\n",
+      "Epoch 128/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1222 - val_loss: 0.1186 - lr: 2.5419e-04\n",
+      "Epoch 129/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1220 - val_loss: 0.1232 - lr: 2.5419e-04\n",
+      "Epoch 130/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1223 - val_loss: 0.1361 - lr: 2.5419e-04\n",
+      "Epoch 131/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1245 - val_loss: 0.1193 - lr: 2.5419e-04\n",
+      "Epoch 132/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1209 - val_loss: 0.1205 - lr: 2.5419e-04\n",
+      "Epoch 133/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1219 - val_loss: 0.1222 - lr: 2.5419e-04\n",
+      "Epoch 134/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1218 - val_loss: 0.1182 - lr: 2.2877e-04\n",
+      "Epoch 135/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1212 - val_loss: 0.1203 - lr: 2.2877e-04\n",
+      "Epoch 136/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1214 - val_loss: 0.1260 - lr: 2.2877e-04\n",
+      "Epoch 137/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1219 - val_loss: 0.1191 - lr: 2.2877e-04\n",
+      "Epoch 138/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1211 - val_loss: 0.1208 - lr: 2.2877e-04\n",
+      "Epoch 139/1000\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1216 - val_loss: 0.1234 - lr: 2.2877e-04\n",
+      "Epoch 140/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1207 - val_loss: 0.1196 - lr: 2.0589e-04\n",
+      "Epoch 141/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1209 - val_loss: 0.1246 - lr: 2.0589e-04\n",
+      "Epoch 142/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1196 - val_loss: 0.1227 - lr: 2.0589e-04\n",
+      "Epoch 143/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1205 - val_loss: 0.1185 - lr: 2.0589e-04\n",
+      "Epoch 144/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1206 - val_loss: 0.1198 - lr: 2.0589e-04\n",
+      "Epoch 145/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1208 - val_loss: 0.1188 - lr: 1.8530e-04\n",
+      "Epoch 146/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1212 - val_loss: 0.1193 - lr: 1.8530e-04\n",
+      "Epoch 147/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1196 - val_loss: 0.1179 - lr: 1.8530e-04\n",
+      "Epoch 148/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1212 - val_loss: 0.1174 - lr: 1.8530e-04\n",
+      "Epoch 149/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1223 - val_loss: 0.1180 - lr: 1.8530e-04\n",
+      "Epoch 150/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1215 - val_loss: 0.1286 - lr: 1.8530e-04\n",
+      "Epoch 151/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1208 - val_loss: 0.1302 - lr: 1.8530e-04\n",
+      "Epoch 152/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1213 - val_loss: 0.1239 - lr: 1.8530e-04\n",
+      "Epoch 153/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1200 - val_loss: 0.1176 - lr: 1.8530e-04\n",
+      "Epoch 154/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1188 - val_loss: 0.1219 - lr: 1.6677e-04\n",
+      "Epoch 155/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1204 - val_loss: 0.1201 - lr: 1.6677e-04\n",
+      "Epoch 156/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1198 - val_loss: 0.1237 - lr: 1.6677e-04\n",
+      "Epoch 157/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1191 - val_loss: 0.1239 - lr: 1.6677e-04\n",
+      "Epoch 158/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1190 - val_loss: 0.1214 - lr: 1.6677e-04\n",
+      "Epoch 159/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1201 - val_loss: 0.1185 - lr: 1.5009e-04\n",
+      "Epoch 160/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1197 - val_loss: 0.1233 - lr: 1.5009e-04\n",
+      "Epoch 161/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1193 - val_loss: 0.1192 - lr: 1.5009e-04\n",
+      "Epoch 162/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1197 - val_loss: 0.1213 - lr: 1.5009e-04\n",
+      "Epoch 163/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1204 - val_loss: 0.1221 - lr: 1.5009e-04\n",
+      "Epoch 164/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1197 - val_loss: 0.1332 - lr: 1.3509e-04\n",
+      "Epoch 165/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1212 - val_loss: 0.1187 - lr: 1.3509e-04\n",
+      "Epoch 166/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1185 - val_loss: 0.1189 - lr: 1.3509e-04\n",
+      "Epoch 167/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1191 - val_loss: 0.1179 - lr: 1.3509e-04\n",
+      "Epoch 168/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1220 - val_loss: 0.1173 - lr: 1.3509e-04\n",
+      "Epoch 169/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1180 - val_loss: 0.1205 - lr: 1.2158e-04\n",
+      "Epoch 170/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1189 - val_loss: 0.1177 - lr: 1.2158e-04\n",
+      "Epoch 171/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1191 - val_loss: 0.1296 - lr: 1.2158e-04\n",
+      "Epoch 172/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1189 - val_loss: 0.1188 - lr: 1.2158e-04\n",
+      "Epoch 173/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1196 - val_loss: 0.1183 - lr: 1.2158e-04\n",
+      "Epoch 174/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1181 - val_loss: 0.1181 - lr: 1.0942e-04\n",
+      "Epoch 175/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1186 - val_loss: 0.1202 - lr: 1.0942e-04\n",
+      "Epoch 176/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1207 - val_loss: 0.1200 - lr: 1.0942e-04\n",
+      "Epoch 177/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1187 - val_loss: 0.1187 - lr: 1.0942e-04\n",
+      "Epoch 178/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1173 - val_loss: 0.1186 - lr: 1.0942e-04\n",
+      "Epoch 179/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1197 - val_loss: 0.1179 - lr: 9.8477e-05\n",
+      "Epoch 180/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1182 - val_loss: 0.1169 - lr: 9.8477e-05\n",
+      "Epoch 181/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1196 - val_loss: 0.1174 - lr: 9.8477e-05\n",
+      "Epoch 182/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1187 - val_loss: 0.1208 - lr: 9.8477e-05\n",
+      "Epoch 183/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1184 - val_loss: 0.1242 - lr: 9.8477e-05\n",
+      "Epoch 184/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1196 - val_loss: 0.1182 - lr: 9.8477e-05\n",
+      "Epoch 185/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1187 - val_loss: 0.1198 - lr: 9.8477e-05\n",
+      "Epoch 186/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1181 - val_loss: 0.1197 - lr: 8.8629e-05\n",
+      "Epoch 187/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1187 - val_loss: 0.1176 - lr: 8.8629e-05\n",
+      "Epoch 188/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1186 - val_loss: 0.1196 - lr: 8.8629e-05\n",
+      "Epoch 189/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1193 - val_loss: 0.1192 - lr: 8.8629e-05\n",
+      "Epoch 190/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1190 - val_loss: 0.1255 - lr: 8.8629e-05\n",
+      "Epoch 191/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1176 - val_loss: 0.1170 - lr: 7.9766e-05\n",
+      "Epoch 192/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1183 - val_loss: 0.1196 - lr: 7.9766e-05\n",
+      "Epoch 193/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1183 - val_loss: 0.1191 - lr: 7.9766e-05\n",
+      "Epoch 194/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1179 - val_loss: 0.1220 - lr: 7.9766e-05\n",
+      "Epoch 195/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1200 - val_loss: 0.1179 - lr: 7.9766e-05\n",
+      "Epoch 196/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1189 - val_loss: 0.1217 - lr: 7.1790e-05\n",
+      "Epoch 197/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1181 - val_loss: 0.1189 - lr: 7.1790e-05\n",
+      "Epoch 198/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1191 - val_loss: 0.1181 - lr: 7.1790e-05\n",
+      "Epoch 199/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1178 - val_loss: 0.1203 - lr: 7.1790e-05\n",
+      "Epoch 200/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1183 - val_loss: 0.1168 - lr: 7.1790e-05\n",
+      "Epoch 201/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1177 - val_loss: 0.1198 - lr: 6.4611e-05\n",
+      "Epoch 202/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1185 - val_loss: 0.1186 - lr: 6.4611e-05\n",
+      "Epoch 203/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1174 - val_loss: 0.1170 - lr: 6.4611e-05\n",
+      "Epoch 204/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1172 - val_loss: 0.1191 - lr: 6.4611e-05\n",
+      "Epoch 205/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1174 - val_loss: 0.1183 - lr: 6.4611e-05\n",
+      "Epoch 206/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1180 - val_loss: 0.1181 - lr: 5.8150e-05\n",
+      "Epoch 207/1000\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1179 - val_loss: 0.1211 - lr: 5.8150e-05\n",
+      "Epoch 208/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1170 - val_loss: 0.1187 - lr: 5.8150e-05\n",
+      "Epoch 209/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1169 - val_loss: 0.1206 - lr: 5.8150e-05\n",
+      "Epoch 210/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1177 - val_loss: 0.1182 - lr: 5.8150e-05\n",
+      "Epoch 211/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1172 - val_loss: 0.1178 - lr: 5.2335e-05\n",
+      "Epoch 212/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1172 - val_loss: 0.1191 - lr: 5.2335e-05\n",
+      "Epoch 213/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1170 - val_loss: 0.1179 - lr: 5.2335e-05\n",
+      "Epoch 214/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1189 - val_loss: 0.1174 - lr: 5.2335e-05\n",
+      "Epoch 215/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1184 - val_loss: 0.1185 - lr: 5.2335e-05\n",
+      "Epoch 216/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1170 - val_loss: 0.1174 - lr: 4.7101e-05\n",
+      "Epoch 217/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1170 - val_loss: 0.1188 - lr: 4.7101e-05\n",
+      "Epoch 218/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1167 - val_loss: 0.1204 - lr: 4.7101e-05\n",
+      "Epoch 219/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1178 - val_loss: 0.1188 - lr: 4.7101e-05\n",
+      "Epoch 220/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1181 - val_loss: 0.1188 - lr: 4.7101e-05\n",
+      "Epoch 221/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1184 - val_loss: 0.1179 - lr: 4.2391e-05\n",
+      "Epoch 222/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1171 - val_loss: 0.1200 - lr: 4.2391e-05\n",
+      "Epoch 223/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1164 - val_loss: 0.1190 - lr: 4.2391e-05\n",
+      "Epoch 224/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1190 - val_loss: 0.1205 - lr: 4.2391e-05\n",
+      "Epoch 225/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1179 - val_loss: 0.1193 - lr: 4.2391e-05\n",
+      "Epoch 226/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1168 - val_loss: 0.1190 - lr: 3.8152e-05\n",
+      "Epoch 227/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1183 - val_loss: 0.1181 - lr: 3.8152e-05\n",
+      "Epoch 228/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1168 - val_loss: 0.1191 - lr: 3.8152e-05\n",
+      "Epoch 229/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1176 - val_loss: 0.1188 - lr: 3.8152e-05\n",
+      "Epoch 230/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1168 - val_loss: 0.1181 - lr: 3.8152e-05\n",
+      "Epoch 231/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1171 - val_loss: 0.1186 - lr: 3.4337e-05\n",
+      "Epoch 232/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1161 - val_loss: 0.1183 - lr: 3.4337e-05\n",
+      "Epoch 233/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1172 - val_loss: 0.1166 - lr: 3.4337e-05\n",
+      "Epoch 234/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1171 - val_loss: 0.1179 - lr: 3.4337e-05\n",
+      "Epoch 235/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1164 - val_loss: 0.1194 - lr: 3.4337e-05\n",
+      "Epoch 236/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1162 - val_loss: 0.1185 - lr: 3.4337e-05\n",
+      "Epoch 237/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1175 - val_loss: 0.1179 - lr: 3.4337e-05\n",
+      "Epoch 238/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1173 - val_loss: 0.1196 - lr: 3.4337e-05\n",
+      "Epoch 239/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1172 - val_loss: 0.1183 - lr: 3.0903e-05\n",
+      "Epoch 240/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1181 - val_loss: 0.1186 - lr: 3.0903e-05\n",
+      "Epoch 241/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1172 - val_loss: 0.1173 - lr: 3.0903e-05\n",
+      "Epoch 242/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1175 - val_loss: 0.1181 - lr: 3.0903e-05\n",
+      "Epoch 243/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1160 - val_loss: 0.1173 - lr: 3.0903e-05\n",
+      "Epoch 244/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1174 - val_loss: 0.1174 - lr: 2.7813e-05\n",
+      "Epoch 245/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1160 - val_loss: 0.1169 - lr: 2.7813e-05\n",
+      "Epoch 246/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1168 - val_loss: 0.1199 - lr: 2.7813e-05\n",
+      "Epoch 247/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1159 - val_loss: 0.1182 - lr: 2.7813e-05\n",
+      "Epoch 248/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1168 - val_loss: 0.1179 - lr: 2.7813e-05\n",
+      "Epoch 249/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1169 - val_loss: 0.1197 - lr: 2.5032e-05\n",
+      "Epoch 250/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1183 - val_loss: 0.1191 - lr: 2.5032e-05\n",
+      "Epoch 251/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1172 - val_loss: 0.1181 - lr: 2.5032e-05\n",
+      "Epoch 252/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1183 - val_loss: 0.1186 - lr: 2.5032e-05\n",
+      "Epoch 253/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1165 - val_loss: 0.1184 - lr: 2.5032e-05\n",
+      "Epoch 254/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1158 - val_loss: 0.1185 - lr: 2.2528e-05\n",
+      "Epoch 255/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1165 - val_loss: 0.1189 - lr: 2.2528e-05\n",
+      "Epoch 256/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1164 - val_loss: 0.1185 - lr: 2.2528e-05\n",
+      "Epoch 257/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1178 - val_loss: 0.1174 - lr: 2.2528e-05\n",
+      "Epoch 258/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1169 - val_loss: 0.1194 - lr: 2.2528e-05\n",
+      "Epoch 259/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1177 - val_loss: 0.1185 - lr: 2.0276e-05\n",
+      "Epoch 260/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1165 - val_loss: 0.1185 - lr: 2.0276e-05\n",
+      "Epoch 261/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1162 - val_loss: 0.1194 - lr: 2.0276e-05\n",
+      "Epoch 262/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1170 - val_loss: 0.1182 - lr: 2.0276e-05\n",
+      "Epoch 263/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1156 - val_loss: 0.1174 - lr: 2.0276e-05\n",
+      "Epoch 264/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1167 - val_loss: 0.1178 - lr: 1.8248e-05\n",
+      "Epoch 265/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1172 - val_loss: 0.1183 - lr: 1.8248e-05\n",
+      "Epoch 266/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1174 - val_loss: 0.1188 - lr: 1.8248e-05\n",
+      "Epoch 267/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1167 - val_loss: 0.1188 - lr: 1.8248e-05\n",
+      "Epoch 268/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1176 - val_loss: 0.1174 - lr: 1.8248e-05\n",
+      "Epoch 269/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1170 - val_loss: 0.1186 - lr: 1.6423e-05\n",
+      "Epoch 270/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1173 - val_loss: 0.1181 - lr: 1.6423e-05\n",
+      "Epoch 271/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1161 - val_loss: 0.1182 - lr: 1.6423e-05\n",
+      "Epoch 272/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1169 - val_loss: 0.1182 - lr: 1.6423e-05\n",
+      "Epoch 273/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1161 - val_loss: 0.1176 - lr: 1.6423e-05\n",
+      "Epoch 274/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1170 - val_loss: 0.1186 - lr: 1.4781e-05\n",
+      "Epoch 275/1000\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1167 - val_loss: 0.1183 - lr: 1.4781e-05\n",
+      "Epoch 276/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1164 - val_loss: 0.1189 - lr: 1.4781e-05\n",
+      "Epoch 277/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1159 - val_loss: 0.1184 - lr: 1.4781e-05\n",
+      "Epoch 278/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1156 - val_loss: 0.1182 - lr: 1.4781e-05\n",
+      "Epoch 279/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1171 - val_loss: 0.1181 - lr: 1.3303e-05\n",
+      "Epoch 280/1000\n",
+      "94/94 [==============================] - 2s 22ms/step - loss: 0.1155 - val_loss: 0.1185 - lr: 1.3303e-05\n",
+      "Epoch 281/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1178 - val_loss: 0.1183 - lr: 1.3303e-05\n",
+      "Epoch 282/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1163 - val_loss: 0.1189 - lr: 1.3303e-05\n",
+      "Epoch 283/1000\n",
+      "94/94 [==============================] - 2s 23ms/step - loss: 0.1171 - val_loss: 0.1184 - lr: 1.3303e-05\n"
+     ]
+    }
+   ],
+   "source": [
+    "# result = model.fit(\n",
+    "#     scaled_X_train_time_series, -np.log(-balanced_slopes_train), # standardize\n",
+    "# #     scaled_X_train_time_series, balanced_slopes_train,\n",
+    "#     validation_data=(scaled_X_val_time_series, -np.log(-slopes_val)), \n",
+    "# #     validation_data=(scaled_X_val_time_series, slopes_val), \n",
+    "#     callbacks=[tf.keras.callbacks.ReduceLROnPlateau(\n",
+    "#             monitor=\"val_loss\", factor=0.9, patience=5, min_lr=1e-5\n",
+    "#         ), tf.keras.callbacks.EarlyStopping(monitor='val_loss', mode='min', restore_best_weights=True, patience=10)],\n",
+    "# # #         tf.keras.callbacks.LambdaCallback(\n",
+    "# # #         on_epoch_begin=lambda epochs,logs: print('lr =',lr_decayed_fn(opt.iterations).numpy())\n",
+    "# # #         ),\n",
+    "# #         ,\n",
+    "#     epochs=150, batch_size=16)\n",
+    "\n",
+    "result = model.fit( \n",
+    "#     balanced_X_train_time_series, balanced_slopes_train, # standardize\n",
+    "    (scaled_X_train_time_series, scaled_X_train_dt), scaled_slopes_train, # standardize\n",
+    "\n",
+    "#     (scaled_X_train_time_series, scaled_X_train_dt), scaled_slopes_train, # standardize\n",
+    "\n",
+    "#     scaled_X_train_time_series, scaled_slopes_train, # standardize\n",
+    "    validation_data=([scaled_X_val_time_series, X_val_dt], scaled_slopes_val), \n",
+    "    callbacks=[tf.keras.callbacks.ReduceLROnPlateau(\n",
+    "            monitor=\"val_loss\", factor=0.9, patience=5, min_lr=1e-5\n",
+    "        ), \n",
+    "               tf.keras.callbacks.EarlyStopping(monitor='val_loss', mode='min', restore_best_weights=True, patience=50)],\n",
+    "# #         tf.keras.callbacks.LambdaCallback(\n",
+    "# #         on_epoch_begin=lambda epochs,logs: print('lr =',lr_decayed_fn(opt.iterations).numpy())\n",
+    "# #         ),\n",
+    "#         ,\n",
+    "    epochs=1000, batch_size=16)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 326,
+   "id": "966d8db5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# model_json = model.to_json()\n",
+    "# with open(f\"saved_models/LFP/model_window_size_inputs_window_{input_window_size}_outputs_window_{output_window_size}.json\", \"w\") as json_file:\n",
+    "#     json_file.write(model_json)\n",
+    "# # serialize weights to HDF5\n",
+    "# model.save_weights(f\"saved_models/LFP/model_window_size_inputs_window_{input_window_size}_outputs_window_{output_window_size}.h5\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 327,
+   "id": "d2f24938",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 0, 'Epochs')"
+      ]
+     },
+     "execution_count": 327,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 600x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(dpi=100, facecolor='white')\n",
+    "plt.plot(result.history['loss'], color='C0', label='Train')\n",
+    "plt.plot(result.history['val_loss'], color='C1', label='Validation')\n",
+    "plt.legend()\n",
+    "plt.ylabel('MAE')\n",
+    "plt.xlabel('Epochs')\n",
+    "# plt.savefig(f'media/LFP/img/loss_{input_window_size}_out_{output_window_size}_window.png', dpi=400, transparent=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 328,
+   "id": "7d66fb2a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "6/6 [==============================] - 0s 9ms/step - loss: 0.1117\n"
+     ]
+    }
+   ],
+   "source": [
+    "# slope_mae = model.evaluate([scaled_X_test_time_series, scaled_X_test_dt], scaled_slopes_test)\n",
+    "slope_mae = model.evaluate([scaled_X_test_time_series, scaled_X_test_dt], scaled_slopes_test)\n",
+    "\n",
+    "\n",
+    "# slope_mae = model.evaluate(scaled_X_test_time_series, scaled_slopes_test)\n",
+    "# test_result = model.evaluate(scaled_X_test_time_series, slopes_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 329,
+   "id": "7123d513",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# dict_results = {'Input_window_size':cycle_window_size,\n",
+    "#                 'Prediction_window_size':cycle_window_size,\n",
+    "#                 'Test MAE':test_result\n",
+    "#                }\n",
+    "# import json\n",
+    "# with open(f'CACHED_DATA/results/LFP/input_window_{cycle_window_size}_output_window_{cycle_window_size}.json', 'w') as f:\n",
+    "#     json.dump(dict_results, f,  indent=4)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 330,
+   "id": "b6cffb09",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "6/6 [==============================] - 1s 7ms/step\n"
+     ]
+    }
+   ],
+   "source": [
+    "Y_hat_test = model.predict([scaled_X_test_time_series, scaled_X_test_dt])\n",
+    "# Y_hat_test = np.log(Y_hat_test)\n",
+    "\n",
+    "# Y_hat_test = model.predict(scaled_X_test_time_series)\n",
+    "\n",
+    "Y_hat_test = l_scaler.inverse_transform(Y_hat_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 331,
+   "id": "445c1aeb",
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([1.800e+01, 1.050e+02, 1.374e+03, 1.000e+00, 0.000e+00, 0.000e+00,\n",
+       "        0.000e+00, 0.000e+00, 0.000e+00, 1.000e+00]),\n",
+       " array([-5.922, -3.654, -1.386,  0.881,  3.149,  5.417,  7.685,  9.952,\n",
+       "        12.22 , 14.488, 16.756]),\n",
+       " <BarContainer object of 10 artists>)"
+      ]
+     },
+     "execution_count": 331,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1600x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(1, dpi=200, figsize=(8,3), facecolor='white')\n",
+    "ax.hist(scaled_slopes_train[:,0], alpha=0.4, label='True Train', color='C2')\n",
+    "# ax.hist(scaled_slopes_train[:,0], alpha=0.4, label='True Train', color='C2')\n",
+    "# ax.hist(np.exp(slopes_train[:,0]), alpha=0.4, label='True Train', color='C2')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 332,
+   "id": "8a874660",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x7f27965295e0>"
+      ]
+     },
+     "execution_count": 332,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1600x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(1, dpi=200, figsize=(8,3), facecolor='white')\n",
+    "n, bins = np.histogram(slopes_test[:,0], bins=10)\n",
+    "ax.hist(slopes_test[:,0], alpha=0.6, label='Ground-truth Test', color='C0', bins=bins, edgecolor='C0')\n",
+    "# ax[0].set_title('True Test value m1')\n",
+    "ax.hist(Y_hat_test[:,0],  alpha=0.5, label='Predicted Test', color='C2', bins=bins, edgecolor='C2')\n",
+    "# ax[0].set_title('Predicted Test value m1')\n",
+    "# ax.hist(balanced_slopes_train[:,0], alpha=0.4, label='True Train', color='C2')\n",
+    "ax.set_title(r'$m_1$')\n",
+    "plt.legend()\n",
+    "# plt.savefig(f'media/LFP/img/m1_hist_in_{input_window_size}_out_{output_window_size}_window.png', dpi=400, transparent=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 333,
+   "id": "047b28cc",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1600x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import seaborn as sns\n",
+    "fig, ax = plt.subplots(1, dpi=200, figsize=(8,3), facecolor='white')\n",
+    "sns.kdeplot(slopes_test[:,0], alpha=0.25, label='Ground-truth Test', color='C0', fill=True)\n",
+    "sns.kdeplot(Y_hat_test[:,0],  alpha=0.25, label='Predicted Test', color='C2', fill=True)\n",
+    "ax.set_title(r'$m_1$')\n",
+    "plt.legend(loc='upper left')\n",
+    "ymin, ymax = plt.ylim()\n",
+    "xmin, xmax = plt.xlim()\n",
+    "# plt.savefig(f'media/LFP/img/m1_kde_in_{input_window_size}_out_{output_window_size}_window.png', dpi=400, transparent=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 334,
+   "id": "1ccdafca",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x7f24641d2250>"
+      ]
+     },
+     "execution_count": 334,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1600x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(1, dpi=200, figsize=(8,3), facecolor='white')\n",
+    "n, bins = np.histogram(slopes_test[:,1], bins=10)\n",
+    "ax.hist(slopes_test[:,1], alpha=0.6, label='Gound-truth Test', color='C0', bins=bins, edgecolor='C0')\n",
+    "# ax[0].set_title('True Test value m1')\n",
+    "ax.hist(Y_hat_test[:,1],  alpha=0.5, label='Predicted Test', color='C2', bins=bins, edgecolor='C2')\n",
+    "# ax.hist(balanced_slopes_train[:,1], alpha=0.4, label='True Train', color='C2')\n",
+    "ax.set_title(r'$m_2$')\n",
+    "plt.legend()\n",
+    "# plt.savefig(f'media/LFP/img/m2_hist_in_{input_window_size}_out_{output_window_size}_window.png', dpi=400, transparent=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 335,
+   "id": "9e91dc72",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(0.0, 5241.129724810535)"
+      ]
+     },
+     "execution_count": 335,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1600x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(1, dpi=200, figsize=(8,3), facecolor='white')\n",
+    "sns.kdeplot(slopes_test[:,1], alpha=0.25, label='Ground-truth Test', color='C0', fill=True)\n",
+    "sns.kdeplot(Y_hat_test[:,1],  alpha=0.25, label='Predicted Test', color='C2', fill=True)\n",
+    "ax.set_title(r'$m_2$')\n",
+    "plt.legend(loc='upper left')\n",
+    "plt.xlim([xmin, xmax])\n",
+    "plt.ylim([ymin, ymax])\n",
+    "# plt.savefig(f'media/LFP/img/m2_kde_in_{input_window_size}_out_{output_window_size}_window.png', dpi=400, transparent=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 336,
+   "id": "bab09739",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'Predicted Value')"
+      ]
+     },
+     "execution_count": 336,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 600x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from sklearn.metrics import r2_score\n",
+    "plt.figure(figsize=(3, 3), dpi=200, facecolor='white')\n",
+    "plt.scatter(slopes_test[:,0], Y_hat_test[:,0], alpha=0.4)\n",
+    "# plt.scatter(-slopes_test[:,0], -Y_hat_test[:,0], alpha=0.4)\n",
+    "# plt.plot([2,8], [2,8], color='C1', alpha=0.2, linestyle='--')\n",
+    "plt.plot([-0.002,0.001], [-0.002,0.001], color='C1', alpha=0.2, linestyle='--')\n",
+    "plt.title(r'$m_1$')\n",
+    "plt.xlabel('Observed Value')\n",
+    "plt.ylabel('Predicted Value')\n",
+    "# plt.savefig(f'media/LFP/img/m1_parity_in_{input_window_size}_out_{output_window_size}_window.png', dpi=400, transparent=False, bbox_inches=\"tight\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 337,
+   "id": "e71f4d01",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 600x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from sklearn.metrics import r2_score\n",
+    "plt.figure(figsize=(3, 3), dpi=200, facecolor='white')\n",
+    "plt.scatter(slopes_test[:,1], Y_hat_test[:,1], alpha=0.4)\n",
+    "# plt.scatter(-slopes_test[:,0], -Y_hat_test[:,0], alpha=0.4)\n",
+    "# plt.plot([2,8], [2,8], color='C1', alpha=0.2, linestyle='--')\n",
+    "plt.plot([-0.002,0.001], [-0.002,0.001], color='C1', alpha=0.2, linestyle='--')\n",
+    "plt.title(r'$m_2$')\n",
+    "plt.xlabel('Observed Value')\n",
+    "plt.ylabel('Predicted Value')\n",
+    "ax=plt.gca()\n",
+    "# plt.savefig(f'media/LFP/img/m2_parity_in_{input_window_size}_out_{output_window_size}_window.png', dpi=400, transparent=False, bbox_inches=\"tight\")\n",
+    "# import matplotlib.ticker as mtick\n",
+    "# ax.yaxis.set_major_formatter(mtick.FormatStrFormatter('%1.2e'))\n",
+    "# ax.xaxis.set_major_formatter(mtick.FormatStrFormatter('%1.2e'))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 338,
+   "id": "2ad14411",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1/1 [==============================] - 0s 55ms/step\n"
+     ]
+    }
+   ],
+   "source": [
+    "# testing on data\n",
+    "test_cell_number =3\n",
+    "tested_cell = [test_cells[test_cell_number]]\n",
+    "# X_train_tested_cell = [x for xs in train_cells for x in xs[0]]\n",
+    "# Y_train = np.array([x for xs in train_cells for x in xs[1]])\n",
+    "# Y_train_tested_cell = [x for xs in train_cells for x in xs[1]]\n",
+    "X_tested_cell = [x for cycle in tested_cell for x in cycle[0]]\n",
+    "# Y_test = [x for xs in test_cells for x in xs[1]]\n",
+    "Y_tested_cell = [y for cycle in tested_cell for y in cycle[1]]\n",
+    "dc_tested_cell, slopes_tested_cell = make_label_arrays(Y_tested_cell)\n",
+    "X_tested_cell_time_series, X_tested_cell_dt = make_feature_arrays(X_tested_cell)\n",
+    "\n",
+    "# scaled_X_tested_cell_dt = standardize_non_train(X_tested_cell_dt, mean_X_train_dt, std_X_train_dt)\n",
+    "# scaled_X_tested_cell_time_series = standardize_non_train(X_tested_cell_time_series, mean_X_train_time_series, std_X_train_time_series)[...,1:]\n",
+    "\n",
+    "# std_X_tested_cell_time_series = standardize(X_tested_cell_time_series[...,1:])\n",
+    "all_test_slopes = [y[0] for y in Y_tested_cell]\n",
+    "all_test_dc = np.array([y[1] for y in Y_tested_cell])\n",
+    "# Y_hat_tested_cell = model.predict([scaled_X_tested_cell_time_series, scaled_X_tested_cell_dt])\n",
+    "_, scaled_X_tested_cell_time_series = scale(X_tested_cell_time_series[...,1:], f_scaler)\n",
+    "_, scaled_X_tested_cell_dt = scale(X_tested_cell_dt, dt_scaler)\n",
+    "Y_hat_tested_cell = model.predict([scaled_X_tested_cell_time_series, scaled_X_tested_cell_dt])\n",
+    "# Y_hat_tested_cell = model.predict(scaled_X_tested_cell_time_series)\n",
+    "\n",
+    "Y_hat_tested_cell = l_scaler.inverse_transform(Y_hat_tested_cell)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 339,
+   "id": "7a112750",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(13, 50, 100, 3)"
+      ]
+     },
+     "execution_count": 339,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "scaled_X_tested_cell_time_series.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 340,
+   "id": "43a3db87",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(13, 2)"
+      ]
+     },
+     "execution_count": 340,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "Y_hat_tested_cell.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 341,
+   "id": "1bcd1e35",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7f260c3b33a0>]"
+      ]
+     },
+     "execution_count": 341,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.plot(all_test_dc.reshape([-1,2])[1:,1])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 342,
+   "id": "aab2d2c1",
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "predicted slope: -7.929895218694583e-05, True slope: -3.6703999999998516e-05\n",
+      "predicted slope: -9.601353667676449e-05, True slope: -3.6751999999999895e-05\n",
+      "[[51.0, 1.0832438], [75.5, 1.0813009756714198], [100.0, 1.078948644022839]]\n",
+      "predicted slope: -6.692701572319493e-05, True slope: -4.3079999999999784e-05\n",
+      "predicted slope: -8.011526369955391e-05, True slope: -5.376399999999393e-05\n",
+      "[[101.0, 1.0813658], [125.5, 1.0797260881147817], [150.0, 1.0777632641541426]]\n",
+      "predicted slope: -8.433844050159678e-05, True slope: -4.441600000000712e-05\n",
+      "predicted slope: -0.00010238115646643564, True slope: -6.358799999999221e-05\n",
+      "[[151.0, 1.0788846], [175.5, 1.076818308207711], [200.0, 1.0743099698742833]]\n",
+      "predicted slope: -8.175655239028856e-05, True slope: -4.22359999999955e-05\n",
+      "predicted slope: -9.91673514363356e-05, True slope: -7.291999999999633e-05\n",
+      "[[201.0, 1.0760773], [225.5, 1.0740742644664378], [250.0, 1.0716446643562476]]\n",
+      "predicted slope: -9.323782433057204e-05, True slope: -7.006399999999858e-05\n",
+      "predicted slope: -0.00011348107364028692, True slope: -6.726800000000033e-05\n",
+      "[[251.0, 1.0731699], [275.5, 1.0708855733039009], [300.0, 1.0681052869997139]]\n",
+      "predicted slope: -8.84765904629603e-05, True slope: -7.89799999999996e-05\n",
+      "predicted slope: -0.00010757301788544282, True slope: 1.1800000000050658e-06\n",
+      "[[301.0, 1.0697222], [325.5, 1.0675545235336574], [350.0, 1.064918984595464]]\n",
+      "predicted slope: -7.352991815423593e-05, True slope: -0.00010875999999999663\n",
+      "predicted slope: -8.869219163898379e-05, True slope: -0.0001579120000000067\n",
+      "[[351.0, 1.0677211], [375.5, 1.0659196170052212], [400.0, 1.063746658310066]]\n",
+      "predicted slope: -8.312559657497332e-05, True slope: -0.00011298400000000264\n",
+      "predicted slope: -0.00010090562864206731, True slope: -0.00012556399999999357\n",
+      "[[401.0, 1.0623802], [425.5, 1.0603436228839132], [450.0, 1.0578714349821825]]\n",
+      "predicted slope: -6.548058445332572e-05, True slope: -0.00017451600000000233\n",
+      "predicted slope: -7.82148854341358e-05, True slope: -0.00017161999999999898\n",
+      "[[451.0, 1.0566722], [475.5, 1.0550679256808935], [500.0, 1.0531516609877571]]\n",
+      "predicted slope: -8.719259494682774e-05, True slope: -0.00024583599999999705\n",
+      "predicted slope: -0.00010591099999146536, True slope: -0.0003258720000000004\n",
+      "[[501.0, 1.0474379], [525.5, 1.0453016814238028], [550.0, 1.0427068619240119]]\n",
+      "predicted slope: -0.00011299757898086682, True slope: -0.00047733200000000587\n",
+      "predicted slope: -0.0001373539271298796, True slope: -0.0007251399999999997\n",
+      "[[551.0, 1.0328375], [575.5, 1.0300690593149688], [600.0, 1.0267038881002868]]\n",
+      "predicted slope: -0.000245809176703915, True slope: -0.0008876064000000028\n",
+      "predicted slope: -0.0002853040932677686, True slope: -0.0010461352000000002\n",
+      "[[601.0, 1.001297], [625.5, 0.9952746751707542], [650.0, 0.9882847248856939]]\n",
+      "predicted slope: -0.0005428148433566093, True slope: -0.0011978028000000007\n",
+      "predicted slope: -0.0009794230572879314, True slope: -0.001231923199999998\n",
+      "[[651.0, 0.95194536], [675.5, 0.938646396337763], [700.0, 0.9146505314342087]]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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pppuOqsa4uDj69u3L8uXLI6/16NEjslzuQIqKinC73SxcuJDTTjut3vcXLUdTX0FBAX6/n8WLF9cL9AYNGsSoUaPo168fXq+XyZMnH/eBk2Y4iYiIiIiIyAmp7pKqtLS0Js8Lh8OsXbu2ya9AINDo+5KSknjppZeanK/097//HQC73c6UKVPqhU21brvtNs477zygZhZUbm7uIX9/R+pvf/tbo51Uw4YN48wzzwRodFj6yy+/TDgcBuDVV1+tFzbVuvHGG7nwwgujXPHh+d3vflcvbDrWPPHEE412j51yyilccsklACxcuLCFq4o+BU4iIiIiIiJyQqqoqIg8PtByuvLycvr169fk1+7duxt937hx44iPj2/0WDAY5NtvvwVqOpmysrKavP9tt90Wec/BhlgfraSkJH7xi180eXzQoEEAbNu2rcGx2tlM/fr1i5zXmJtvvvkoqzw61113Xave/0AMw+Daa69t8njtz7W4uDgqA9hbk5bUiYiIiIiIyAmpbhhUWVkZ9ev379+/yWPbtm2jqqoKINI11JS6x9euXRud4prQvXt3LJame09SUlKA+mEdgM/nY/PmzcDBl6cNGTKkyWO7d++mpKSk0WPJyclHPcPK7XbTtWvXo7pGc2rTpg2pqalNHq/9+UPN30FSUlILVNU81OEkIiIiIiIiAHj8HpbnLcfj97R2KVFR94N9QUFBk+clJSVhmma9r0OZQ5ScnNzkseLi4sjjtm3bHvA6GRkZjb6vOcTGxh7weG0YVbt0rlZJSQmmaQIH/37S09ObPPbQQw812Un20EMPHcq3cEDHekBzqD9/gFAo1NzlNCsFTiIiIiIiIoLH7+HBhQ+yJHcJDy588IQInerO8Vm5cmXUr2+1Wg/pvKZmPB2vjuXv51D/TqT5KXASERERERERNhRvoEdyD+wWO92Tu7OxZGNrl3TU+vbtG+lyWrBgQWSJW0uouzQqPz//gOfm5eU1+j6o3/Gyf9dRXc2xZLCuup1DB/t+DnR86tSpDbrJar+mTp0apWoP7Fj5mZ7oFDiJiIiIiIgIvVJ6salkE/6wn80lm+mZ3LO1SzpqhmFw/fXXAzWDwadNm9Zi9+7atWtk+dR33313wHOXLl0aedy3b996x+rOoWpq9hHApk2bjqTMQ+ZyuejevTsAy5YtO+C5Bzt+qJqrkypaP9NjudPrWKDASURERERERHA73Dw17CnOyjyLp4Y9hdvRcMv749G9996Ly+UC4Pe//z3bt29vkfvabDZGjhwJwOeff05OTk6T57722muR94waNaresS5dukQeL1++vMlrvPPOO0dR7aE577zzAFizZs0Blyi+/vrrUblf7d8b1Awtj5bOnTtHHh/oZ/rvf//7gNdprvpOFAqcREREREREBKgJnQalDzphwiaAjh078uKLLwJQVlbGsGHDWLhw4QHfY5pmVLakv/vuuwHw+/3ccsstBAKBBue8/vrrzJs3D4DLLruMdu3a1Tt+1llnYbPVbDD//PPPRwZ31/Xss8/W65JqLnfccUekq+f2229vdMnZW2+9xX/+85+o3K/uz2Lr1q1RuSbUDHuv3WFwypQpjQ5qX7hwIS+88EKr1HeisLV2ASIiIiIiIiLN6bbbbmP37t08/vjj7Nmzh+HDh3POOecwbtw4+vXrR0pKCqFQiLy8PFasWMF7773HunXrgJoh1A6H44ju+4tf/IIrr7ySGTNmMG/ePH72s59x77330qtXL0pKSnjnnXci3UApKSk899xzDa7Rtm1brrzySv79738zd+5cxo8fz9133016ejq7du3ijTfe4IMPPuCss87iv//975H/kA7Baaedxt13381LL73E8uXLOeOMM3jggQfo168fZWVlzJgxg1dffZUzzjjjgJ1Dh2rgwIG4XC68Xi+PPPIIdrudTp06RWYwtW/fnpiYmCO69t13380dd9xBfn4+w4cP55FHHqFnz54UFxcze/ZsJk+ezBlnnHHAn2lz1nciUOAkIiIiIiIiJ7xJkyZx2mmncd9997Ft2za++uorvvrqqybPNwyD0aNH8+yzz5KZmXnE950+fTrBYJCPPvqIFStWRGZK1ZWZmcns2bNp3759o9d4/vnnWb58OZs3b+bTTz/l008/rXf8l7/8JbfeemtkyVtzeu6559izZw8ffvghGzZsYOLEifWOd+nShXfffZdu3bod9b3i4+O55557+POf/8yKFSu44IIL6h3/+uuvGyxBPFS33norc+bM4eOPP2b9+vVcc8019Y7369ePDz74oEHHWUvVdyLQkjoRERERERE5KVx66aVs3LiR9957j1tuuYU+ffrQpk0bbDYbCQkJdOnShfHjx/OnP/2JrVu3MmfOnAZDvA+Xy+Xiww8/ZObMmVx22WVkZmbicDhITk7mzDPP5E9/+hMbN25kwIABTV4jPT2d7777jgceeIDu3bvjdDpJSUlhxIgRvPnmm/z73//GarUeVZ2Hym6388EHH/DGG28wfPhwEhMTiY2NpXfv3jz44IN8//33dO3aNWr3e/rpp/nnP//J8OHDSUlJidr3abFYeP/99/n73//O4MGDiYuLIy4ujv79+/Pkk0/y3XffkZGR0Wr1nQgMs7EFoCKNyMnJISsrC4Ds7Gw6dOjQyhWJiIiIiBx/Nm/eTDAYxGazRXb9EhGJhiP5/dJcn/XV4SQiIiIiIiIiIlGlwElERERERERERKJKgZOIiIiIiIiIiESVAicREREREREREYkqBU4iIiIiIiIiIhJVCpxERERERERERCSqFDiJiIiIiIiIiEhUKXASEREREREREZGoUuAkIiIiIiIiIiJRpcBJRERERERERESiSoGTiIiIiIiIiIhElQInERERERERERGJKgVOIiIiIiIiIiISVQqcREREREREREQkqhQ4iYiIiIiIiIhIVClwEhERERERERGRqFLgJCIiIiIiIiIiUaXASUREREREREREokqBk4iIiIiIiIiIRJUCJxEREREREZEoWLt2Lddffz1ZWVk4HA4Mw8AwDFatWtXapR1TOnfujGEYTJgwobVLkWakwElEREREREROWN98800k+Jk0aVKz3ef7779nyJAhvPXWW+Tk5BAIBJrtXiLHA1trFyAiIiIiIiJyvPv9739PdXU1CQkJPP3005xxxhnExMQAcMopp7RydSItT4GTiIiIiIiIyFEIBAJ8++23ANx+++3ceeedrVyRSOvTkjoRERERERGRo1BYWIjf7wegR48erVyNyLFBgZOIiIiIiIjIUfD5fJHHdru9FSsROXYocBIREREREZGTUt2B4t988w0A7733Hueeey5paWnExMTQs2dPfve731FcXNzg/ZMmTcIwDLp06RJ5beLEiZFrNjWo3Ov18tJLL3HuueeSkZGBw+Ggbdu2nHfeefzrX/8iGAw2WfP+O7x9//33TJgwgS5duuB0OjEM44jOrVVWVsaf/vQnzj77bNLS0nA4HLRr145x48bx/vvvY5rmQX+uc+bM4aKLLiItLY3Y2Fh69OjBvffey+7duw/6XjlxaIaTiIiIiIiInPTC4TA33HADb775Zr3XN23axLPPPstHH33EggULyMjIOKr7/PDDD1x88cXs3Lmz3usFBQV8+eWXfPnll7zyyivMmjWL9PT0A17r5Zdf5te//vUBA6rDOffLL7/k6quvpqioqN7reXl5fPrpp3z66adcdNFFvPvuu7jd7kavce+99/L888/Xe23z5s08//zzvPnmm/znP/85aK1yYlDgJCIiIiIiIie9Rx55hP/+979ccskl3HjjjXTq1In8/Hz+/ve/M3v2bLZs2cL//u//8u9//zvynrvuuosrrriCPXv2MHr0aAD++Mc/cvHFF0fOadu2beTxli1bGDlyJGVlZSQkJHD33XczZMgQsrKyKCoqYubMmbzyyissW7aMiy++mAULFjS5RG/ZsmW8+eabZGVlcd9993HGGWcQDAZZsGDBEZ27aNEiLrzwQgKBAOnp6fz617/mtNNOIzMzkz179vDuu+9GAqObbrqJDz74oMF9/vrXv0bCpszMTH7/+98zZMgQvF4vs2fP5q9//StXXnklVVVVh/m3I8cjBU4iIiIiIiLHmHDYpMJ78K6VaCut8rO7tJr2STEkxTpa7L7xLhsWS8PlXS3pv//9L3/84x956KGH6r0+ZswYxowZw7x583j//fd58cUXSUtLA2rCpLZt29br9mnfvj19+/Zt9B433XQTZWVlDBw4kHnz5tGmTZt6xy+44ALGjh3LL37xC7777jumTp3Kbbfd1ui11q9fT79+/Zg/fz5JSUmR188+++zDPjcQCHD99dcTCAQYM2YMH3zwAbGxsZHzTj/9dMaOHcuIESO4/fbb+fDDD/n88885//zzI+fs3bs38rPr1KkTS5YsqdcNNmLECEaPHs3o0aMPqSNLjn8KnERERERERI4xFd4g1//ruxa9Z1l1gIKKfcOv0+KdJMa0zADsN285k8TY1h22PWjQIB588MEGrxuGwb333su8efMIBoMsXryY8ePHH/b1FyxYwH//+18Apk2b1iBsqjVmzBiuuOIK3nvvvQMGTgB///vf6wVIB3Kgc9955x127NiBy+Vi+vTp9cKmum677TZee+01li5dytSpU+sFTtOmTYt0Lv3f//1fo0sPzznnHG677Tb+8Y9/HFLNcnzT0HAREREREZGTXDAUpqDCRyhs4guGCIVNCip8BEPh1i6txVx77bWNDtGGmjCq1rZt247o+jNnzgSgZ8+e9OvX74DnjhgxAqhZCtdUN1BWVhbDhw8/pHsf7Nza2kaOHBnp3jpYbYsXL673+hdffAFAcnJyvSWF+7v55psPqWY5/qnDSURERERE5CTn/ylYCobDmD/9abVY8YfC2KwnR59Cr169mjyWkpISeVxRUXFE11++fDkAGzdubDLY2l8gEKC4uLjeHKha/fv3P+R7H+zc2trmzp17yLXl5eXVe75mzRoABg4ciM3WdNQwYMAAHA4Hfr//kO4jx6+T4zeHiIiIiIiINMnxU6hks1gwfvqz7usng6aWkQFYLPt+DqFQ6Iiuv3fv3iN6X1MDtpOTkw/5Ggc790hqq66urve8uLgYoNFwrC6bzVYvwJMTlzqcREREREREjjHxLhtv3nJmi97zqw17+dfCbYRNsBhwy7CunNPrwOFBtMS7TvyPprVB1Wmnncabb755yO9r3759o69brdZDvsbBzq2t7cILL+TPf/7zIV+3MYfaISUnvhP/n+om7N27l6VLl7J06VKWLVvGsmXLKCoqAmp2Dpg6dWpU7hMMBlmzZk3kPkuXLmX9+vWRf6C3b99O586dD3qdzp07s3PnzoOe16lTJ3bs2HGUVYuIiIiISGuyWIwWH6J96entGdUzjeySKrKSY0mOa7ld6k4GqampAHg8niZ3sWstqamp7NmzB7/ff8S1JScnk5eXR35+/gHPCwaDkW4oObGdtIFTenp6i9znySefZNKkSS1yLxERERERkaORHOdQ0NRMBg4cyH//+1+2bdtGXl5eo7u4tZaBAweyZ88eli9fjt/vx+E4/P8N9OvXj7y8PFatWkUwGGxyjtMPP/yg+U0niZNnQe4BdOzYkQsuuKBZrm2aZuSxy+XiZz/7Gd26dTvi61188cWsWbOmya958+ZFo2wRERERERGJovHjxwM1nxFfeOGFVq6mvtraysrKmDJlyhFd47zzzgNqZjnNmjWryfNef/31I7q+HH9O2sDp0UcfZdasWeTl5bFz505eeeWVZrnP0KFDefnll1mxYgUVFRUsXryYYcOGHfH1kpKS6Nu3b5NfPXr0iGL1IiIiIiIiEg0XXHABQ4YMAeDZZ5/lvffeO+D5a9asOWBwE0033XQTWVlZANx3333Mnz//gOcvXLiQb7/9tsE1YmJiALj33nsbXVr37bff8uqrr0apajnWnbRL6h5//PEWuc/o0aNb5D4iIiIiIiJybHv77bcZMmQIxcXFXH311bz55ptcffXVdO/eHavVyt69e1m5ciWzZs1iyZIl/Pa3v2XcuHHNXpfT6eS9995j1KhReDwezjnnHH75y19yySWX0KVLF8LhMLm5uXz//fd89NFHrFmzhr/97W+MHDkyco309HSeeOIJ7rvvPnbs2MGgQYP4/e9/z5AhQ/B6vfznP//h+eefp3379lRVVVFQUNDs35e0rpM2cBIRERERERFpSd26dWPx4sVcfvnlrF27llmzZh2wiykhIaHFavvZz37GN998w1VXXUV2djZvvfUWb7311mHV9tvf/pZdu3bx4osvsnv3bn71q1/VO96mTRtmzJjBlVdeGfX65dijwElERERERESkhfTo0YNVq1bx3nvv8cEHH7Bs2TIKCgoIhUKkpqbSs2dPhg0bxqWXXsrpp5/eorX97Gc/Y/PmzUydOpVZs2axcuVKCgsLsVgspKWl0bt3b0aOHMnll19Oz549G73GCy+8wOjRo3nxxRdZtmwZVVVVdOjQgYsuuoj777+fDh06tOj3JK1HgdNxZv78+QwYMICtW7cSCoVIT09nyJAhXHPNNVx88cUYhtHaJYqIiIiIiBwzRo0aVW8zp0M9tr8Dnde5c+dDvg6A1Wrlmmuu4Zprrjnk99TasWNHs5xby+l0cscdd3DHHXcc9ntrXXTRRVx00UVRrUuOPwqcjjPbt2+v93zHjh3s2LGD9957j7PPPpt3332X9u3bH9G1c3JyDng8Nzf3iK4rIiIiIiIiIicXBU7HCYfDwfjx47ngggvo27cviYmJlJaWsnjxYv7xj3+QnZ3NokWLOP/881m8eDGJiYmHfY/aXQlERERERERERI6GAqfjxNKlS0lKSmrw+qhRo/jVr37FFVdcwbx58/jxxx95/PHHee6551q+SBERERERERERFDgdNxoLm2rFx8fz3nvv0bVrV4qLi3n11Vd5+umncTgch3WP7OzsAx7Pzc1lyJAhh3VNERERERERETn5KHA6QSQmJvLLX/6SyZMnU1lZyfLlyznrrLMO6xraLUBEREREREREosHS2gVI9PTp0yfyePfu3a1YiYiIiIiIiIiczBQ4nUAMw2jtEkREREREREREFDidSNavXx95nJmZ2YqViIiIiIiIiMjJTIHTCaKsrIx33nkHgNjYWM4444xWrkhERERERERETlYKnI7C1KlTMQwDwzCYNGlSs93ns88+o7q6usnjHo+Hq666iqKiIgBuueUWnE5ns9UjIiIiIiIiInIgJ+0udQsXLmTLli2R54WFhZHHW7ZsYerUqfXOnzBhwhHdx+Px8P7779d7re5933//fdq0aRN5PmDAAAYMGFDv/KeffprrrruOyy67jGHDhtGtWzfcbjdlZWX897//5eWXX2bXrl0A9OzZs1nDLxERERERERGRgzlpA6fXXnuNadOmNXps0aJFLFq0qN5rRxo4FRYWMnHixCaP33///fWeP/bYYw0CJ4Di4mJee+01XnvttSavNXLkSN566y1SUlKOqFYREREREWl+FkvNQpNQKIRpmtr8R0SiwjRNQqEQsO/3TGs6aQOn48lf/vIXvvzySxYvXszGjRspLCyktLSU2NhYMjMzOfPMM7nmmmu44IIL9C8rEREREZFjnMPhwO/3Y5omPp8Pl8vV2iWJyAnA5/NhmiZQ83umtRlmbTUiB5GTk0NWVhYA2dnZdOjQoZUrEhERERE5/hQXF5Ofnw9Aamoqbdu2beWKROREsHfv3shs5/T09ENe/dRcn/Vbv8dKRERERETkJOJ2uyOPi4qKKCoqiiyDERE5XKFQKPK7pFbd3zOtRUvqREREREREWpDD4SAtLY2CggKgpith7969WK1WjcgQkcNSd25TrbS0tGNiSZ0CJxERERERkRaWmpqK3++nrKws8pq6nETkaCUmJpKamtraZQAKnERERERERFqcYRhkZmaSkpJCaWkpVVVVCpxE5IhYrVZiY2NJSko6pjYhUOAkIiIiIiLSSlwuFxkZGa1dhohI1GlouIiIiIiIiIiIRJUCJxERERERERERiSoFTiIiIiIiIiIiElUKnEREREREREREJKoUOImIiIiIiIiISFQpcBIRERERERERkahS4CQiIiIiIiIiIlGlwElERERERERERKJKgZOIiIiIiIiIiESVAicREREREREREYkqBU4iIiIiIiIiIhJVCpxERERERERERCSqFDiJiIiIiIiIiEhUKXASEREREREREZGoUuAkIiIiIiIiIiJRpcBJRERERERERESiSoGTiIiIiIiIiIhElQInERERERERERGJKgVOIiIiIiIiIiISVQqcREREREREREQkqmwtfcOCggK2bdtGXl4elZWV2O12kpKS6NixI6eccgpWq7WlSxIRERERERERkShq9sCpsrKSTz75hDlz5vDtt9+ye/fuJs91Op0MHDiQCy64gEsvvZT+/fs3d3kiIiIiIiIiIhJlhmmaZnNceOXKlfztb39jxowZVFVVAXCotzIMA4BTTz2Vu+++mxtuuIHY2NjmKFMOQ05ODllZWQBkZ2fToUOHVq5IRERERERERI5Gc33Wj3rgtHLlSh555BHmzJkD7AuZMjIyGDJkCIMGDaJt27akpKSQnJxMdXU1xcXFlJSUsGnTJpYtW8bq1asJBAI1BRoGqamp/O53v+PXv/41TqczmuXKYVDgJCIiIiIiInJiaa7P+lFdUjdx4kTeeOMNwuEwAKeffjrXXXcdl19+OR07djzk6/j9fubPn89bb73FRx99RGFhIQ888ACTJ09m+vTpDBs2LJpli4iIiIiIiIhIFEV1l7pp06Zhs9m47bbb2LBhA8uXL+d///d/DytsAnA4HJx33nlMmTKF/Px8pk+fTs+ePdmxYwdfffVVNEsWEREREREREZEoi2qH01133cUDDzwQacWKBqfTyfXXX891113HjBkzCIVCUbu2iIiIiIiIiIhEX1QDp5deeimal6vHMAyuuuqqZru+iIiIiIiIiIhER1SX1ImIiIiIiIiIiChwEhERERERERGRqFLgJCIiIiIiIiIiURXVGU6H4ocffmDBggVs27aNioqKgw4BNwyDf/3rXy1UnYiIiIiIiIiIHK0WC5w2btzIzTffzJIlSw75PaZpKnASERERERERETnOtEjgtHv3bkaMGEFhYSGmaQLgdrtJTk7GYtGqPhERERERERGRE0mLBE5PPvkkBQUFGIbBrbfeyn333UePHj1a4tYiIiIiIiIiItLCWiRw+uyzzzAMgxtvvJFXX321JW4pIiIiIiIiIiKtpEXWs+3ZsweAG2+8sSVuJyIiIiIiIiIirahFAqfk5GQAkpKSWuJ2IiIiIiIiIiLSilokcDrjjDMA2LRpU0vcTkREREREREREWlGLBE733HMPpmlqfpOIiIiIiIiIyEmgRQKn888/nwceeICvv/6aO++8k0Ag0BK3FRERERERERGRVhDVXeqmT5/e5LHevXtz1lln8eqrrzJr1iyuuOIKevXqRWxs7EGvq2HjIiIiIiIiIiLHD8M0TTNaF7NYLBiGEa3LAWAYBsFgMKrXlCOTk5NDVlYWANnZ2XTo0KGVKxIRERERERGRo9Fcn/Wj2uEEEMX8SkREREREREREjkNRDZy2b98ezcuJiIiIiIiIiMhxKKqBU6dOnaJ5OREREREREREROQ61yC51IiIiIiIiIiJy8oh64DR37lw8Hk+0LysiIiIiIiIiIseJqA8Nv/DCC7HZbJx22mmMGDGCESNGMHz4cFJSUqJ9KxEREREREREROQZFPXACCAaDrFixghUrVvDXv/4VwzDo3bt3JIAaMWIE7dq1a45bi4iIiIiIiIhIK4t64PTYY4+xcOFClixZQmVlJQCmabJ+/XrWr1/Pyy+/DEDXrl0ZPnx4JIDq2rVrtEsREREREREREZFWYJimaTbHhUOhECtWrGDBggUsWLCAhQsXUlRUVP/mhhF5nJmZWS+A6tOnT3OUJUchJyeHrKwsALKzs+nQoUMrVyQiIiIiIiIiR6O5Pus3W+DUmB9//DESQC1YsIBdu3bVL6ZOAJWamsqwYcMYOXIkv/nNb1qqRDkABU4iIiIiIiIiJ5YTInDaX3Z2diR8mj9/Phs2bGD/cgzDIBQKtVKFUpcCJxEREREREZETS3N91rdE5SpHKCsri2uvvZZ//OMfrFu3jr179/Lyyy/TtWvXet1OIiIiIiIiIiJy/GiWXeoOx86dO5k/f36k02nTpk0ADTqdRERERERERETk+NDigdP69esjS+gWLFjA7t27gfoBU0pKCmeddRbDhg1j+PDhLV2iiIiIiIiIiIgchWYNnOruVDd//nwWLVpEcXExUD9g6ty5M8OGDYt8aYc6EREREREREZHjV9QDp2+++SayPG7JkiVUVlYC+wImi8VCv379It1Lw4YNIzMzM9pliIiIiIiIiIhIK4l64HTOOedEBn6bpklMTAxDhgyJdC+dddZZxMfHR/u2IiIiIiIiIiJyjGi2JXVWq5Urr7yS3/zmNwwePFi7zomIiIiIiIiInCSiHjgZhoFpmgSDQd555x3eeecd4uPjGTp0KGeffTbDhw/nzDPPxOVyRfvWIiIiIiIiIiJyDIh64FRcXMzChQsjg8K///57ysvLmTt3LvPmzQPAbrczcODAyAynYcOGkZKSEu1SRERERERERESkFRhm3e3imoHX62XJkiXMnz+/wSDxusvsevXqFQmfhg8fTufOnZuzLDkCOTk5ZGVlAZCdnU2HDh1auSIRERERERERORrN9Vm/2QOn/YVCIVasWBEJoBYuXEhxcfG+gn4KoTIzMyNL8O6+++6WLFGaoMBJRERERERE5MRywgROjVm3bh0LFiyIfOXk5ESOGYZBKBSK+j337t3L0qVLWbp0KcuWLWPZsmUUFRUBcNNNNzF16tSo3CcYDLJmzZrIfZYuXcr69esj39P27dsPq5ursLCQF198kY8//pgdO3YA0LlzZy655BJ+85vfkJqaGpW6G6PASUREREREROTE0lyf9Zttl7rDceqpp9KlSxe6d+9Ot27dePvtt9m+fTvNmYWlp6c327XrevLJJ5k0aVJUrvXdd99xySWXkJeXV+/1NWvWsGbNGl577TU+/vhjhgwZEpX7iYiIiIiIiIgciVYLnPYfLr5y5cp6nUwt2XjVsWNHevXqFRlqHk11vw+Xy8WAAQMoKChg69ath3Wd7Oxsxo0bR0FBATabjXvvvZexY8cC8Omnn/Lcc8+Rm5vLuHHj+P7779V9JCIiIiIiIiKtpsUCp927d0fmNi1YsIAff/yxXhhT93FMTAxnnnkmI0aMYMSIEc1Sz6OPPsrgwYMZPHgw6enp7Nixgy5dukT9PkOHDuXll19myJAh9OvXD5vNxoQJEw47cHrooYcoKCgA4O233+bKK6+MHBs+fDiDBg3i6quvZu/evTz88MNRWxIoIiIiIiIiInK4mi1w2rRpU72AaefOnfWO1w2YEhMTIwPCR4wYwRlnnIHdbm+u0gB4/PHHm/X6tUaPHn3U18jLy+Ott96KXK9u2FTrqquu4vXXX2fu3Lm88cYbPP3002RkZBz1vUVEREREREREDlfUA6crrriChQsXRrpxoOHyuLZt2zJ8+PBIwHTaaadFdqeThmbOnEk4HAZg4sSJTZ43YcIE5s6dSzgcZubMmdx+++0tVaKIiIiIiIiISETUA6cPP/wQwzDqhUwdO3aMLI8bPnw4PXv2jPZtT2gLFy6MPB45cmST59U9tmjRIgVOIiIiIiIiItIqmmVJXY8ePeoFTB07dmyO25w01q9fD9QsPTzQMrl27dqRkJBAeXk5P/74Y0uVJyIiIiIiIiJST9QDp/z8fNLS0qJ92ZNaTk4OwCHtPJeVlcW6devIzs4+4vs0JTc397CvKSIiIiIiIiInn6gHTrfffjvjx4/noosuIj09PdqXPylVVFQA4Ha7D3puXFwcAB6P57Dvk5WVddjvERERERERERHZX9QDp08++YSZM2diGAZnnHEGY8eOZdy4cZx22mnRvtVJw+v1AuBwOA56rtPpBKC6urpZaxIRERERERERaUrUA6dbb72V2bNnk5uby9KlS1m2bBmPPfYYHTp0YOzYsYwdO5Zzzz33kMITqeFyuaiqqsLv9x/0XJ/PB0BMTMxh3+dgy/Byc3MZMmTIYV9XRERERERERE4uUQ+cXn31VQC+//57Zs2axaxZs1i5ciXZ2dm8/PLLvPzyy8TGxnLeeecxbtw4fvGLX2jp3UHEx8dTVVV1SMvkKisrgUNbfre/Q5kRJSIiIiIiIiJyMJbmuvCgQYOYNGkS33//PTk5Obz88stcdNFFuFwuKisr+eSTT7jtttto3749Z555Jn/84x/54Ycfmquc41ptEHSwod6wr0tJ85hEREREREREpLU0W+BUV2ZmJrfffjuzZs2iqKiImTNnctttt5GRkUE4HI4suzv99NPp1KkTd911F3PmzDmkJWQngz59+gBQVlZGXl5ek+fl5uZSXl4OQO/evVukNhERERERERGR/bVI4FSXy+Vi7NixvPLKK+zevTsSNg0cOBDTNMnOzuaVV15h7NixpKamcumll/Kvf/2L/Pz8li71mDFs2LDI42+//bbJ8+oeO/vss5u1JhERERERERGRprR44LS/QYMG8dhjj7F8+fIml97dfvvttG/fnr/97W+tXW6rGD9+PBZLzV/VlClTmjxv6tSpAFgsFsaPH98SpYmIiIiIiIiINNDqgVNdTS29a9euHeFwmJKSktYusZ6pU6diGAaGYTBp0qRmu09GRgbXXXcdAHPnzuX9999vcM6MGTOYO3cuADfccAMZGRnNVo+IiIiIiIiIyIFEfZe6aKldejd27FgAVqxYQSgUitr1Fy5cyJYtWyLPCwsLI4+3bNkS6RaqNWHChCO6j8fjaRAQ1b3v+++/T5s2bSLPBwwYwIABAxpc58knn+Szzz6joKCAa665huXLl0d+Np9++in/93//B0BaWhp//OMfj6hWEREREREREZFoOGYDp/2dfvrpUb3ea6+9xrRp0xo9tmjRIhYtWlTvtSMNnAoLC5k4cWKTx++///56zx977LFGA6esrCxmzZrFJZdcQl5eHs888wzPPPNMvXMyMjL4+OOPI7vaiYiIiIiIiIi0hlYLnMrLy6moqDikrqWOHTu2QEXHvjPPPJM1a9bwwgsv8PHHH7Njxw4AunTpwsUXX8z//M//kJqa2rpFioiIiIiIiMhJzzBN02ypm33++edMnjyZhQsXUlxcfEjvMQyDYDDYzJXJocjJySErKwuA7OxsdVKJiIiIiIiIHOea67N+i3U43XPPPfz9738HoAUzLhERERERERERaWEtEji9/fbbvPTSS0DNMPBLLrmEQYMGkZKSgsVyTG2UJyIiIiIiIiIiR6lFAqdXXnkFqBl8/dVXX9GtW7eWuK2IiIiIiIiIiLSCFmkvWr16NYZh8NhjjylsEhERERERERE5wbVI4BQIBAAYOHBgS9xORERERERERERaUYsETp07dwbA4/G0xO1ERERERERERKQVtUjgdNlllwHw5ZdftsTtRERERERERESkFbVI4PTb3/6Wjh078te//pUNGza0xC1FRERERERERKSVtEjglJiYyNy5c0lPT+ess85i8uTJlJSUtMStRURERERERESkhdmiebGuXbse8HhVVRWlpaX8+te/5p577qFNmzbExsYe8D2GYbB169ZolikiIiIiIiIiIs0oqoHTjh07Duk80zQxTZO9e/ce9FzDMI6yKhERERERERERaUlRDZxuuummaF5ORERERERERESOQ1ENnKZMmRLNy4mIiIiIiIiIyHGoRYaGi4iIiIiIiIjIyeOYDpwKCgp44YUXWrsMERERERERERE5DMdc4OT3+5kxYwbjxo2jQ4cO/Pa3v23tkkQOqKTSz+qcUkoq/QB4/B4W5CxgQc4C8ivzWZ63HI/f08pVioiIiIiIiLScqM5wOhqLFi1i+vTpzJgxg7KyMqBmNzvtUifHskteWsi2wkpMQtiscHb3BDZ7P8VHIVZ7FX6KuajbKF5c8SLPjnyW9Lj01i5ZREREREREpNm1auC0fft2pk+fzptvvsm2bduAmpAJwOFwcN5553H55Ze3ZokiTdpb4WVDfgW+YADTNDCMMLN/KMAZ05uQGcBusWEC07YFiXUOZ9zGdzk9szvxLkh1O+md1oGK8B4cdh9p7hj6tOnJppJNVAeribHFMLDtQABW7l0JwMC2A3E73K34HYuIiIiIiIgcmhYPnMrKynj33Xd54403+O9//wvsC5lcLhejR4/miiuuYNy4cSQkJLR0eSKHbP2ecsJmGMyalammacGwmIRCBlggaIYwTROn1UGVNwReN19v3EPIDGMzbITNbVgMK0EziM2wgXU1DrufgFFMfIxBmns+DoeP8tBurLYqspKSubr3JcTYYuiR3KNeOHW4zxVeiYiIiIiISHNqkcApFAoxZ84cpk+fzqefforP5wNqgiar1UooFMIwDKZMmcLVV1/dEiWJHDWXzYrFsIARgJ86nDBN4p0x+MLQJqYNTquTPZ49xNhiqApWYTWsQM0yUYthBfjpNSAUhz8Uh0kSHq+V6jIrYTOMQXcAdoT9LPp+O3a7F9PyDS5nEC8FJMZY8IU9OC1xVFs30TbBRlWwkjh7HEXeIlJdqVQG9j1Pi0mjg7sDl/e4/KjCK4AeyT3IrsimV0ov3A43H63MAdPAFwzRPT2eTqmxJMXYsVmPuXFxIiIiIiIi0oyaNXBasWIF06dP55133qGgoADY1800YMAArr/+eq699loyMzMBNK9Jjiv9sxK59/yevP3dDjx+L2HTSr/2CRgWH6FgLOXVIcImdEzoSHWwmlB1CH/IT8gM/dThFMJiWBp9bmAQDAYiHVBWw4IB2Igl5HcRNhPwVINJJ/YWOgkG436q6nw8jnJcsUVUOiqx2Cood1Zjs3sImlUk2MFhc7C5dDPPLnsWu9WOx+9pMpxq6nm8Ix4Tk6pAFWM6j+H55c9zfe+b+Ms8g8IKPyZgMSy0cTuw2/w47CYJMVbaJyYRMspxOoIkxzjon9GNjIQEkmLsJMU6SIq1Y1c4JSIiIiIictyLeuC0Z88e3nzzTd544w3Wr18P7AuZsrKyuPbaa7nhhhvo06dPtG8t0qJiHTZuH9GVKwd1ILukiqzkWJLjHJHjobBJSZWfIo+fIo+P3WXlrM7fTrHHT5XXSjgUx57yCvzBMBYsOG1OfCEfYTMcCaYMDPwhP06bk6pAFf6wH0wi4VQwHCYcjMM0jZqlfUaYgD8BkwB+byLB/cKsoBnCbvNjc3hIjrPgs5USthTjc1TjtrkAP3H2OCyGhSRnEoZhNPo81h6LaZrYrXa+2PUF3qCXJxf+kz2l1wKWmuWFRog9ZX7szhJCBLCV2vhhT3a9ZYQOax7JrmQsGDhtLnxBbyScykyoE07FOujRpj3lwVxsNj+pcS4GtuvB9vItgOZbiYiIiIiIHGuiHjh17NgR0zQjIVNiYiJXXHEF119/PSNHjoz27URaXXKco17QVMtqMWjjdtLG7QTigTZcSdd655imiccXrAmlKn0UemoCqtyyCj7d8i0OM5Uij58UVztSXClUB6vBJBJOVftDFAchGIKaf+Is2C3QLq4TFmuQsNkwzAIo8Zaw1+sHs029MMpmsWBYK3A6qwlYCkmIMQlaCnHHBKkI59AmLo6qYGWkG7HMV0ZaTBq+oA9rMAsMAzNsAQxMEwzDBNOO1VJz37rLCA3DwBvykleZh4HxUx0/hVGNhFNhc/t+zzdjs4Wx2rzEOlfw885nYlo8uF0G7d0ZZJfn0jYpSOc2sQzI6MGW0s2NLgtUWCUiIiIiIhJ9UQ+cwuEwhmEQHx/PX/7yF2688UacTme0byNyQjAMg3iXnXiXnc5t4uodu2NUJzaWbKRnck9sRgzFlX6KK/0UeHwUe/wUenzsKa1m5g97qA6E8AfD2CwWrIZBrN2Bzeqqdz27xR55HGePaxBeNQinwmEslT899/iIM8OESy10T0rATiXJsRa6pqfwyY7pOIwYApYyDMMPhuOnDicT0wyD0fgyQjAxfqqrNgiDfTOt9p9x1ejzsA2v10LQb+ODH9ZiNayEgg6CgfKa8Ms0sduLMGwbcDj8BI0S4lxhQpYPiXOaWO1VpMT9m4fP/h8qQ3lYLEZkLlVWfFbkz/1nWNWdW3UwJZX+RjvgRERERERETmSGWduKFCUWiyXS/WC327nooou4/vrrGTt2LA5H4x+2at/z73//m6uuuiqa5UgU5eTkkJWVBUB2djYdOnRo5YoEYO66PCZ/s5VQKEzYhPEDMumcGkt+uY/8ci955V72lvsoqw40y/1DZojqYDWVXpOyKhN/KAyYJMYFGdxrL70yncRb0/EHHLit6WwpzqWsKkClD34s2EWF1yQYdNYEXLWdVkbNwPSDPa8NlSyGURNAmRZ83gRM08D8aYmhYZg4nCUYBpiYGBiAicWwEAgHsVlsBMNBbBYLFpsXLBWckprOrup1DEjvyrrS74h1hagI7yEtzok3XMn4ruPZUraFX/a8hh7JPdjcSPdU2DT5w3sB8sq9GAbYrQbn9GpDxwwPibEWzs7qS8eUZJw2a7P8vRwL/H4/3333HevXr2fbtm34fD6cTiddu3alT58+nHnmmU3+e0FERERERFpGc33Wj3qH05QpU5g+fTrffPMNfr+fTz75hE8++SSytO66667T0jqRKBp9agZDOqcctIum2h8iv9xbL4TKizz24g2EG33fwVgNKy5LLHnVVYRNE0wDiyWE0+onwb2Um079FbH2ut1bnSKPqgLt+LH4R8JhaOPqyIbCbIoqgwQCTlyWtuwoLaS0KoTXb4dwPPmeSiq8gGngsDrxhryUeEtxWZ14Ah7C4Zrv3TR/GjxuWjCMIITBagsRCoewWn4Kq0wDm2FimEGcFguGAYRcEHKxK98gGO7NqnIrwfAIqqhZJpxtGDhsfmbnWag225G3awmFvreIdQbwkk9KjIWgUUiCy0FldTLbCm/CNH/amdAw+XDFHuzOcgwjjM2STbu4dtjsQdyuMG3cdk5pk4afIlzOAGnxLga260ZlOI9T2/Q+rpb9VVZWMnXqVD766CNKS0sJhU18wTCmaWIYBk6bBavFICkpiUsvvZQJEyYQFxd38AuLiIiIiMhxI+odTrVycnKYPn06b775Jhs2bKi52U+dTx06dKg3PFwdTscHdTiduEzTpLw6SH6Fl7yyfSFUXrmX/HIfeyt8hMNN/6qo8gfZU+rFFwxhAjYLZCX7eXhMDKd3ONogof7ulaZpUumH0mqTsuowBZU+thUXgpnA1qJyFmyOJxC04AuCxTCxWCArySCEPxJ4OCwOfCEfZb4ynFYnlQEPhlETUtV2UoXMENY6nVW1z03TrFlmGPThsrnwhwM/zazb9/OxW0N4fbFU+VLqVo5hhLE7qgjjw2qxEgoHsfz0p9Viw4zM0wrWdHERJtGRQMhSyhnte+JweIl1BmnjdnJqehYVod04HD7auGPoldKz3lwqgA3FG+iV0guAlXtXRrqw9j8ezTBr6dKlPP744+Tm5VNeHaDcG8AfbBhmOmwWElx2EmLstMtI57HHHmPIkCFRq0NERERERA5Nc33Wb7bAqa5ly5Yxbdo03n33XYqKimpu/FP41L9/f3744QcFTscBBU4nr3DYpNDjI/+nrqj8nwKp3DIv+RU+Csq97CiqIhgOEwqbJLigQ5KFl66KJSnGcpR3P7xfUV9tCvD6Yj9hEwwDrh5op3eGlZIqk6Iqk+JKk+Kqmq+CigD5Hj8GNvzhAJhgEqYqUFUzD8oMEWuPxTAsmGYYAws2i43C6kLCZqjmZ2OGMQxLZOi5aYYBK56qNjRoIjVCWO0V1CzpM376PWj+FIQ1/J4Nw8A0w9gsNvwhP1aL9aflf7VBmEHIrFkOiLUCl9OP3VFNapyDWFeALilt2O75AZfdRm65hwpzO+nxbjq4O2Cz2OiW1I1Ve1cx6axJ7PbsrhdIHUkINWfOHB577DE83gB7K7yETAtteg4i9ZSBuNt2xOaKJeitwrN3F0VbVlK48XusRpi28S7cLjuPP/44F1544WHfV0REREREjtxxHTjVCgaDzJ49m+nTpzN79mz8fn9NEXXCp5tuuonLLruMjh07tlRZcogUOElTfMEQ73+fw5SFW/EGArhsQX41KpkL+rRplXpKq0LklAbokGQnKfbAM5JM06TcG6a4MkRRZYjc8kpm/Pg5LiOD/IpqsuL6UVYN3kDNr8rqYDVVwSowIWgGibPHYcEgjImFmqV+FV4fBRUWAmELNeGRgcWA7ukx2OxedpYUYiMOT8BT0z0VDkfCqprwquZ52Axht9prOqEMCyYmJuHIHCrDINK1ZQJWw4KBgYmJ3WLDH/YRDjoIBGJqAi0jSHzCXtq1KSfFbWGvfyPJcRZ2V/9IoiueIm8RaTFpdHB34PIelwM02NWvqR3+li5dyq9+9StKq3wU+HyknNGRzNPPI8E1EAsxjf7svWWFbJ47jdKdP9I2wUlSrJOXXnpJnU4iIiIiIi3ohAic6iopKeHtt9/mjTfeYOnSpTXF1PlP/IMGDeKKK67g8ssvp1u3bq1RouxHgZMczN6yvWzfu4c2MXm0TWyL1Xr8zB2qqypQyfay7XRJ7BKZP1XlD1NUGWJPmYcpqz8kztqePWWV9EkaSrnXoNATwuOrWToWDJvsLPYTCkEwDC67lcwkF3+58jQSY+xUBarYWLwNp5nKj4XZFFf68flt2MxEskuLKakKUeU1ABsFVQU4rE4qA5UY1HZS2X4Kp4zIkj+TnzqeInOqQtgsDnzeWEwsYBpAzRD1mJhqwgSwGhYC4QBWC9jsHiz2cuJi/QSNAmwODz4jjzS3napQBfGOeExMPH5P5HGyM5knzn6CLQVbeOrPT7E3v4T8bB8ZNyTjSIoBLNjCKbj9wwCw4MARak/QWogjVPP7o9rYTO6aLyje8iOpVQ7a9WjDa395jaJQUWSHQOCIu65EREREROTATrjAqa5NmzYxbdo03nrrLXbt2gXsC58MwyAYDLZmefITBU5yMIFACX5/Pl7vThyOtOM2cDqYxgIpAH8wTHFViOLKEJ+tzeU/68L4QgZOu52bz+7COb3aHvI9amZVhcgtK2d9wS4s4QS2FedTWhWkymchFHSxt6JmGaOBBYfVjsdfiS/kx2axETbDVAeChIOxhMIG/NQXZbWCzVZJjMNKhb8Ct8MdmWEVCgex/jTLymqpCbcMA6y2amJivDgclZi2YuJiAnjC2bRJsFHizcP0mVQEKwh6TCyxVhy2toQsFdjDbQlaSmq+H6MaS9iNafiJC5yB17oDi2knaCkhbCkjWB4CaxDrJgsxA1xc1ucy5uyYg9vurhduFXuLoz53SkRERETkZHZCB051ffPNN0yfPp0PPviAiooKDMMgFAq1dlmCAic5uJMlcDoUPl8OOaUONhXG4nJk0Dktjhj7gZf3Ha6waVJeHaCkKkBJpZ+8Cg8fb/wCl6UNhRXVpNi6sHlvFaZpEDZr50aZxLj8WA2DMGFsho1YeyyBcACo6dCq8FcQCPsJmbXDzGu6qGruGaq3lM9hD+AL5IG1FJNSHG4Di7MUw16IYfFjwYrFjCNs8ULYimHYMA0flrCLkKUcazih5lgQqouKsFQZOJOtDO4zmCJvERhQUFVASkwKRVVFXNb9MnaU7+ChMx9iU8mmyNyp2qV++z+HfUPU6w5O75Hcg+yKbIVXIiIiInLSO2kCp1rV1dV8+OGHvPHGG3z22WetXY6gwEkOToHTPj5fDhU+F6W+REq8abSJd0Y9cGpMVaCK7eXb6ZLQhVh7LN9u3MtbS3fhD5qEwianto9jQ+lKrOEUij1BUp3tfhpO/tOoctMkZJr4Qr5I0OSw2msCKQOcVge+kJcyXylOq5MKfwXhULhmxZ4JhtXAYsZg4sdGLDjywV4A1lIwHVhdu3A6TEx7ERDCNEKYRhWWcDxBfymh6iA2t0FqTCph276B6S6riwx3Bt2SupHgSGBF/gpKfaUUVBeQ6kqlMlBJnD2OIm9R5Hnt0r8EewJxjjjyKvMi51cHqxnTeQzri9Y3GJreVHh1tEPVRURERESORSdd4CTHHgVOcjAKnPZprcCpMWXVAfLKvGQkuiIzpLaXb6dzfGfCYQcFFT72Vvgo9PgijwsqfJR7A3WCKGqGlv/0b4ywaRII+6n2VFFeWU4wHMYe48ZqiwVCGNjhp+HmQdNPOFz7vRtYXXtIb7cBvyUXt/8soGa+U+nudRR7vsQdttJrQE9uP+92AKatncapbU5l3s55XNDpApblLqNzUmeyy7Mp85dhs9gwTRPLTzOpap/H2GMoqCrAbXdTFagiNSYVT8CDzWLDbrVTHaimbUxbtpdtJ8GZUC+s2j+8qn1ed6h6Y51UCqJERERE5HjTXJ/1bQc/RUREjmeJMXYSY+yR57H2WE5NPTXyPN5lp2taw6DEGwhRUOGj4KcgqjaM2lvuo6TKj9104QlUYAbADBtYYmPAtAJWav9LhgmEQ3bq/ZcNX3ucPgdJXFhvBzvT6aY09CXhUiipKmFou6G4HW6GthvKxpKNXN3zaiYtnsSQdkOYs2MOMbYYSn2lkVAo1h5b73lNl5aJgUGMveZcT8BDqiuVwqpCuiR2Ib8yn7TYNALhAEnOJAzDqNl50LA0+txhc7C5dDPPLnsWu9XeYIj6c6OeI84ex8q9KwHUHSUiIiIiJ62oBk7PPfccd955JzExjW+BfbSWL19OYWEhY8aMaZbri4jIPi67layUWLJSYhscC4TCFFX6ee7v/2TVrmyqiSE59RxChkEwXBMvmYAZbnhdwzAw/J2xOOr/K8juTKH4jRAZ3Wz0it03W8ntcDMofRDL85YzJGMIdoud8d3Gk+JKoYO7AzG2GLond2dz6WaqA9WR56sLVzNt7TQGpg9ka+lWLj3lUgBibDFkujOZtHgS53Q8h892fHbQ8Kr2eSgcwsAg051JZaAS0zRx2pwUVBXgsrm495t7cdvd7KncQ8gM4fF76nVHdU7ozKNDH410RdXtkGpsKd+B5kx5/B42FG/QHCoREREROSZFNXC67777ePbZZ/ntb3/LnXfeSVxc3MHfdAgWL17ME088wdy5c3nssccUOImItDK71UJGgou2dh+2gk34y70kDTwbV2IqplkzLyoQNvEHwhRV+QmZNcvxDGoCJ4fV0uCaIW8Vpg+MPRbiTmv4749eKb2Yvn463ZO7s7N8J3f0v6Ne0JIel17v/PPjzo90R+1/LsDkcyezsWQjN/e9uUFY1dRzgPc3vc/uyt2EzXC9Tip/0E+n+E7kVeaR4kqJBFK13VEx9hhiHbHc+829lPvLI4FUbYdU3XCq7pyp55c/z4S+E+if1j8SSAF8suUTuiV1a3Ac0FB0EREREWl1UQ2chg8fzoIFC3jggQeYNGkSF198Mddeey1jxozBaj282SXbtm3j7bff5u2332bjxo2YpkliYiKDBg2KZskiInIUOmRlRcKjqqI9uBJTMQwDm9XAZoUYuxWr1aCw0g+ABWgb78TWSODkyd8JgNNmoVu3bg2Oux1unhr2FBtLNjLx1ImHFKTUdkcd7Nj+YdWBng/NHMqqglVgUq+T6tQ2p/LZjs+ItcXWm/9U2x1lt9jJLsvG7XBjs9gigVSsPRbTNOuFU4ZhkOhK5ItdX+ANenl66dMEwoFIIBVvj8dhdbC9fDvlvvLI8drwqipQ1WRYpaV9IiIiItISoho4ffvtt8yYMYNHH32UjRs38s477/DOO+8QFxfH6aefzuDBgxk4cCBt27YlOTmZ5ORkqqurKS4upqSkhE2bNrFs2TKWLl3Krl27gJqtt51OJ3fffTcPPfQQycnJ0SxZRESOwindumG1GNitFkp3rSela78G57idNqwWg3DYJMZhI8bR+H+AKNqyEofNgtVi0KdPn0bPOVCA1FLcDjfD2g+LPK/tpJq5dSYXd7sYu8XOLs8u+qT04aIuFzXojsrx5NTbXc8wDIAGS/kKqwpJi0nDF/SR6EykOlgdCaTiHHEUVRURZ4/DwIgcrw2v7FZ7k2FV3cHnQIPlewAr965ssEsfaDC6iIiIiBy6qA8Nv/LKK7niiiuYMWMGL7zwAosXL8bj8TB//nwWLFhwSNeo3TgvIyODiRMn8v/+3/+LTEwXEZFjx2mnnUZ8fDzu6gAl29fhO6MEp7vhfxioDaWsFqPR63jLCinctILUWDtJSUkMGTKkuUuPKrfDzfhu43lw4YN0T+6OL+jjyh5X4na4I91Ry/OW0y+tH33b9G0QSNV2S9VdypfpzuSRRY/gD/vxhrwNuqW6J3WnKlCFYRiR47XhVZmvrMmwqnbw+TNLn6EiUBFZvje+23heX/s6oXCoQSgW74jHMAw6xXeKzKDaP5BqLKDS0HQRERGRk1ez7FJnGAZXXXUVV111FRs3buS9997j66+/5rvvvqO6uvqA7+3atSvDhw/n4osvZty4cYe9FE9ERFqO3W7n/PPP5/0PPqTcG2Dngo/oPmZiJPg4FGY4zOa507AaYRJi7Fx66aU4HI5mrLp5HGzJX90ZVI0FUtBwKd8r579Sb/le3UBqQNsBAA2OY3LAsKp28HmiMxGrxYphGKTEpFBYXUgoHCJshom1xdbbpS/WHovb7o7MoCr1ldYLpOrOnqoNqPafS1W3s0rhk4iIiMiJzzBr24laQDAYZOXKleTk5FBQUEBxcTEul4u0tDTS0tLo168f7dq1a6ly5DDl5OREOs2ys7Pp0KFDK1ckx5pAoAS/Px+vdycORxpW68n7YdLny6HC56LUl0iJN4028U5i7CdmgF5dXc1vfvMbcvL2srfcS1qvIXQ8a3y90MkfCmMxarqcHLZ985vMcJitX7xF7g/fkpkUQ9eO7Xn33XejtunEscbj97CxZCM9k3s2e9ji8XsaDaugZmlftiebwurCSEhUW4/H7yHWHkuxt7jBMbvFTrekbmSXZ1PmL8NmsUVmTwXCgchzt8ONaZpUBiojx+IccZR5y7AaVuxWO8nOZJ44+wl2e3Zr+Z6IiIhIK2quz/otGjjJ8U2BkxyMAqd9TqbACWD16tX84Q9/oMLrp8jjJyGzG52GXxpZXtdY4OQtK2Tz3GmU7vyRtglOkmKdvPTSS8fdcrrjUW0YVdstVR2s5pucb8iIzcAf9pPiSqGDu0Nkl77aweh92/Rlzo45xNhi6gVSTQVUdcOreHs8AO3i2rGzYmdNV1VlIQnOhEa7o+oGUtBweZ6W64mIiIhER3N91m+WJXUiInJy6d+/P/fccw8vvvgiVouForxtrJ3xPMmdTyWpU28cKe2xOZyEAj7KCnZQtGUlhZtWYDXCZCbF4HbZ+cMf/qCwqYXsP/jc4/cwa9ssMuIy2Fm+kzv631EvvEmuSOZnmT/DbrEzvtv4BoFU3aV+dZf2NdZZtbVsa033k6+StNg0AuFAveV7TpuTgqoC7FY7N/znBpJcSQ2W5+2/lC8tJo3OCZ0j86WABrOksiuyyYrPivypTioRERGR5qUOJzlk6nCSg1GH0z4nW4dTrdWrV/PSSy9RUFiExxvA4wsSCIUxYpMg4MP0VRKuLMZhs5DgspMQY6ddRjqPPfaYwqZWdqDlfh6/JzIQfXPJZp4a9tQRhTQev4fFuYuZtnYap7Y5lc92fNagW8pmseEP+XFZXbgdbuxWe4Plefsv5UtwJtAlsQt7KvZQ7i8nZIbw+D2RbqmqQBVjOo9h7s65jO40mjk75uC2uxt0UrV2t5TH72FD8QZ6pfRSCCYiIiItRkvqpNUpcJKDUeC0z8kaOEHNTKcPP/yQzz//nIqKCkJhE689HgJeLIFqYgJlWC0GSUlJXHrppUyYMOGEndl0Ionm/Knaa3Vwd2jQHVW7fK82kIqzx0Xes//SvdrnaTFpxNvjcTvcBMIBKgOVkaV9pmkSJky7uHZ4/B7cDje5nlwwoKCqoMHSvrrDzYEmd96DxrujPH4PK/euPOxd/AA+2fIJvVN7s75oPdf0ukYzrURERKRFKHCSVqfASQ5GgdM+J3PgVCsQCLB69Wq2bNnKxux8wv5q4h0Gp3VrT58+fRgyZMhxuRudNL/9A6nGdulrbLlejien3u55tQFNVaCKc7LOYd7OeYzuNJovsr/AaljrdVIFwoF6w80NDCoCFY3uvNfYnKna0OiDTR80qONQdvGLt8fjsrkYljmML7O/pH9af77P/x633Y1hGHSK78QzI55R6CQiIiJRp8BJWp0CJzkYBU77KHCqb09pNW6njZQ4Jx1TY1u7HDnBLM9bzpLcJZimyS7PLvqk9OGiLhdFwqpMdyaTFk+iT0of1hevZ9LQSWwt29ro0r7a4eaJzkQ8AU+jO+/F2GMa7Y5q6r2Hs4tfMBwkbIbrLSl02920c7fjoi4XUft/29T9JCIiItGioeEiIiIijeiV0ovp66fTPbk7vqCPK3tcidvhJj0uHagJpIZkDMFusTM4YzAlvhLO73Q+Q9sNZWPJRm7ue3ODbqlsTzalvtJIV5JhGABUBirxhXyNDj6vDY1KfaV4Ap56S/+aulbtMbvFTtuYtmS6M9lUuolERyI7ynaQ6EqkMlBJdaCaKZVT2Fu1t8GMqmRnMs+Neo44exwr964EFEKJiIhI61PgJCIiIsc1t8PNU8OeYmPJRiaeOrFB0FI3kNpcspmJp06MvG9Q+iCASDgFMDRzKKsKVjW5897+c6ZibDGR0Kh7Uneu6HEFwGHt4ld77MnvnuTnWT/nh4IfeOOiNyKdWJnuTFbsXUF7d3sqA5WYphnZ0c9lc3HvN/fitrvZU7kHE5P2ce0bnUNVd5ZUdkW2BpSLiIhIs9GSOjlkWlInB6MldftoSV19WlInrS2aQ8/rXm//wecD2g44quvvX2fd5YJzdszBH/LjsDrw+D2RHf2SnEl0T+5OXmUeDqsD0zTJ8eQ0mENVd5ZUdbCaMZ3HsL5oPZPOmlRvl76mBp3X3cUP0I56IiIiJwgtqRMRERE5QnW7maJ9vbrdUdG8LtTvzuqc0JlLT7m0yR39Ym2xkVlSBgaJzkSsFiuGYRBnj8NiWEhyJmEYBomuRL7K/oq2MW254T83ROZQNTXovPZ5WkwaGbEZeENe+rXpx4srXmTSWZMo9hYrfBIREZF61OEkh0wdTnIw6nDaRx1O9anDSeTIHag7y+P3MHPrTPIq87Bb7Ozy7KJbYjdW5q8k25NNYXVhvVlSxd5iUl2plPvL6ZLYhfzKfOLscZFd+poadF53uHlRVREpMSnkenLpmtiV7IpsxnYd22i3lGZJiYiIHPuO6w6n999/n4svvhi73d4StxMRERE5YRyoO8vtcDO+23geXPhgZGj69b2v5/re1zc6h6r2ee3Ofed0PKfeHKqmBp3XPg+FQ8TZ4/D4PSQ4EthTuYes+KxGu6XSYtLo4O6gWVIiIiInqRbpcLJYLKSmpnL99dczceJE+vfv39y3lGagDic5GHU47aMOp/rU4STSvI5kRlVTc6iaGnReu4vfx1s+pkN8B2Zvm83oTqOZu3MunRM7N+iWqt2172CzpMZ3G8+O8h08dOZDDWZFNdbRpZ34REREoqu5Puu3WOAERLYBHjhwILfccgvXXnstiYmJzX17iRIFTnIwCpz2UeBUnwInkRNH3aAqx5NDsjOZSYsn0Tuld6RbqthbTLw9HoBEZyKegKfR5Xoum4t+bfqR4EhgRf4KSn2lFFQX1OuOqg2fKgOV3PvNvZT6SjEMo8md+EBhlIiIyOE4rgOnTz/9lClTpvDpp58SCARqbmwYOJ1OLr30UiZOnMh5553X3GXIUVLgJAejwGkfBU71KXASObE11i0F8P6m9w84S6o6WM3ozqNZlruMzkmdyS7PpsxfFumOshpWnDYn7ePa4wl4qA5WU1BVQMeEjuRW5jbonop3xEfCqOv7XK/gSURE5BAc14FTrcLCQt544w2mTp3KmjVragr4qeupY8eOTJgwgQkTJtCpU6eWKkkOgwInORgFTvsocKpPgZPIycnj9xzSLKk+KX2Ys2NOg+6oDvEdME0Tf9hPpjuTTcWbKPWVYjEs2C32Bt1TboebGGsMeyr3cHr66ewu382EvhPon9Zf3U8iIiJNOCECp7pWrFjB66+/zr///W9KSkpqijEMDMNg1KhR3HLLLVx22WU4nc7WKE8aocBJDkaB0z4KnOpT4CQijVmet5wluUuwW+x4Ah5SXCl0cNf8/4v9u6Nqu6HWFq7lmp7XMGvbrAbdU26HG3/Ij91ixzAMyn3lOK1OAuEA8Y54TEySnck8cfYT9XbT03I8ERE5mZ1wgVMtv9/Pxx9/zJQpU/j8888Jh8M1hRkGiYmJXHPNNUycOJEzzjijNcsUFDjJwSlw2keBU30KnESkMR6/J7LD3uaSzTw17KlI2OPxe5ixaQYbijbQIb4D/rCfdnHtGN9tPG6H+4DdU1PXTY0sv0uLTasJluwxFFQVkBKTQmFlYWQ3vbrL8fYPpIAGO+spkBIRkRPNCRs41bV7926mTZvG3/72N/Lz84F9S+769u3LnXfeycSJE9X11EoUOMnBKHDaR4FTfQqcRKQpB9ph70CB1IHkV+Zz7zf3UuIriVzHZrHhD/lxWV24He7Ibnq1y/H2D6SSXEmYmHj8nsjOeo0NM68NvzYUb6BXSi8A7aQnIiLHlRM+cKqqqmLGjBlMmTKFBQsWALB/aYZhkJGRwUsvvcSll17aGmWe1BQ4ycEocNpHgVN9CpxE5EgdKJA62PtWFawCE7ond2d14WqmrZ3GqW1OrbebXm2H0/6BlN1qxzRNKgOVkZ316g4zt1vtJDuT+f2Q3/Pn5X+mT0of1hSswWV3sbdqLyamhpeLiMhx4YQNnBYuXMiUKVOYMWMGlZWVQE3QlJiYyLXXXssNN9zA2rVref3111myZElN0YbB7NmzGTNmTGuWftJR4CQHo8BpHwVO9SlwEpFjQWO76dUux9s/kIqzx0XeU7uzXu0w83Zx7dhZsZOUmBTyPfl0SezCtrJttItrR4m3hM6JnTFNkz2Veziz3ZmUeEu4ptc1mhUlIiLHpBMqcKpdOjd16lS2bt0K7OtmGj58OLfeeitXXnklLper3vvmz5/PTTfdxM6dOzn77LMjnVDSMhQ4ycEocNpHgVN9CpxE5HiwfyBV2x1VG05BzTDzrWVb8Qa9uKwu0mLT2FO5B4fFgYmJzWIjGA4C4LQ6OSfrHL7O+Zo+qX34Lvc73HZ3vVlRxd5ieqX0UvgkIiKtprk+69uicpVD4Pf7+eijj5gyZQpffvkl4XA4EjKlp6dz4403cuutt9K9e/cmrzFixAiee+45Lr/8ctasWdNSpYuIiIjIScDtcDMofRAA6XHpkdfrPh6aOZTFuYsj3VDzds7j3KxzmbdzHmO7jmVXxS4uPaVm9MPHWz4mryoPX9CHaZqkulLBgIKqAuxWOzfOuZHLul/G62tfr9cBVXf3vOyKbAVSIiJyXGqRwOmuu+7i3XffpbS0FKjpZrJYLIwZM4Zbb72VcePGYbMdWil9+/YFoKKiornKFRERERFplNvh5vxO5zO03VA2lmzk5r43k+PJ4Y7T7iDHk1Nv1lT/tP7c+829OKwO1hWtiwwvN02TSl8lnRM7U1hdyK6KXczaNovvcr8j1hYb2T2vOljNmM5jeHHFi0w6a1Jk57yBbQcCGk4uIiLHthYJnF5++eXI406dOnHzzTdz88030759+8O+ltPppGPHjlgslmiWKCIiIiJyyBrrhqrbCQWQXZHN0MyhmKZJblUuP8/6OUC97qi0mLR6HVC+kI8kZxKGYZDoSuSr7K9oG9OWG/5zQ2TnvAR7AnGOOPZW7SVkhrQ8T0REjkktEjjZ7XYuueQSbr31Vs477zwMwzjia3Xs2JEdO3ZErzgRERERkWbQK6UX09dPp3tydzx+D0PbDcXtcEe6o67ueTWPLHqkXgdUrD2WUl8pqa5UCqsK6ZLYhfzKfNJi07BYLBRUFdQEWJW5ZMVnsbNiZ2R53tiuY3l++fNM6DuB/mn9IwPKa5fmZcVnaYmeiIi0mBYZGl5UVERqampz30aamYaGy8FoaPg+Ghpen4aGi8jJqnYQed2ldrWW5y1nSe6Seh1QMbaYyO55me5MJi2eRO+U3ny24zOshhV/yE+CI4EwYaoCVYTNcGR4eUF1Ad6gF6fVSSAcIN4Rj4lJVaCKc7POZe7OuYzrNo6d5Tu55JRLAIixxWhJnojISe64Hhq+bt06AAYPHkxMTMwhvcfr9bJ06VKgZlh4tO3du5elS5eydOlSli1bxrJlyygqKgLgpptuYurUqVG/57///W+mTJnC6tWrKS0tJT09neHDh3P33XczdOjQA7531KhRfPvtt4d0n1bYeFBEREREGlF36d3+muqAqmvyuZMjs6JWF65m2tppDEwfyNbSrVzY+ULe3fgup7Y5ldnbZtMmpg2+oI9EZyLVwWpi7bGYpondaueL7C+IscXw+c7PsVlsPLP0GSoCFaTFpNHB3YHLe1wOKIASEZHoaZEOJ4vFgsViYfXq1fTp0+eQ3rN161a6d++OxWIhGAxGvaYDLeuLduBUXV3NFVdcwX/+859Gj1ssFh599FEee+yxJq9xLARO6nCSg1GH0z7qcKpPHU4iIo07UAfUoZxf+zzZmcwjix6hxFcSOa/2emW+MjrGd2Rb2TYy4jIo9ZaSGpOKJ+AhzhFHmbcMA6NBAKXwSUTk5HBcdzjBkYcgLdGt07FjR3r16sW8efOa5fo333xzJGz6+c9/zm9+8xsyMzNZs2YNTz31FFu3bmXSpEm0a9eO22+//YDXOuOMM5gyZUqz1CkiIiIiLetAHVCHcn7d56+c/wqrClaBCd2Tu7O5dDOYRJbmXXLKJawtXEubmDbkVuZS6islFA5hYJDoTMRqseKwOdhcuplnlz2L3WqPDCSv3SGvdh6U5kCJiMjBtFjgdLjC4TAAVmvzdAQ8+uijDB48mMGDB5Oens6OHTvo0qVL1O/z1Vdf8c477wAwbtw4Pvroo8j3NHjwYMaPH8+gQYPYtWsXDzzwAFdeeSXJyclNXi8uLo6+fftGvU4REREROb65HW6GtR8WeV5317zapXm/HvhrAFYVrKI6UA3A+5veJ9uTXS+ASo9Njwwkr7tDXlWgijGdx0SGkw/NbLgMUEREBI7hwGnnzp0AJCYmNsv1H3/88Wa57v7+8pe/AGCz2Zg8eXKDAK1NmzY888wzXHPNNZSWlvLaa69x//33t0htIiIiInJy2L8zqm4wNTRzaIMAamvZVkzTpNJXSVpsGnarfd88qF1f4A16+fOyP9M1savmP4mISKOaJXDatWtXo6/n5ubidh/4X0A+n4+tW7fyyCOPYBgGp556anOU2CIqKir48ssvATjvvPOaXAd52WWXkZCQQHl5OR999JECJxERERFpMft3Rg3NHMri3MVMWzuNU9ucymc7PiPOHgfUzINKi0nDF/TRNrYtm0s3H3AAuZbgiYicvJolcGpsaZppmlxwwQWHfa0bb7wxGiW1imXLluH3+wEYOXJkk+c5HA5+9rOfMW/ePJYtW0YgEMBut7dUmSIiIiIiEW6Hm/M7nc/QdkMjO+TVnQf1yKJH8If95FflNzr/qTaASnWlUh2sZny38by+9nWu6XUNPZJ7sKlkE0CkG8rj97CheANZ8VlsKtlEdbBa3VIiIieAZgmcmhr0fTgDwF0uF/fccw8333xztMpqcevXr4887tWr1wHPrR1aHgwG2bx5c5O7+W3YsIEzzzyTjRs34vV6adOmDYMGDeLyyy/nmmuuUVAlIiIiIlFRdxle3XlQtcPJqwPVjc5/qg2gDMMgJSaF3MpcNpVs4qMtH/F9/ve47W4Mw6B9XHsu73E5n2z5hG5J3fhk6yfE2mIp8hZFuqWu73O9gicRkeNUswRO+++iNnHiRAzD4IknnqB9+/ZNvs8wDFwuF+3atWPgwIEHXX53rMvJyYk8Pti2grVbEELNNoRNBU75+fnk5+dHnu/evZvdu3czc+ZMnnnmGd5//3169+591PU2Jjc394iuKyIiIiInjrpL8Bqb/1QbQKW6UimsKqTUW4o/5Gf13tUkO5OxW+3EWGPYWraV9za+x87yncTaY0l1peIL+UhyJuGwOdhatpXPdnzGjE0zeGrYUwqdRESOM80SON100031nk+cOBGASy65pMkg5URUUVEReXyw8CwuLi7y2OPxNDhusVg499xzueiiizjttNNITU2loqKCFStW8Morr/Djjz+yfv16fv7zn7N06VI6dux42PXWDb1ERERERA6msflPtQFUjC2G6mA1n+/6nPVF60l0JLKjbAeJrkRKvCXYLXb2VO6hOljN9/nfEwwHibXHRrqlXDYXKc4U/CE/MzbN4KIuF2kelIjIcaRFdqn7+uuvgcZnO53IvF5v5LHD4TjguU6nM/K4urq6wfEPP/yQpKSkBq8PHz6cu+66i9tuu41p06aRn5/P//zP//Dhhx8eeeEiIiIiIkdg/wDK4/cwa9ssfp71c34o+IE3LnqjJmQKVDN13VRsFhsWLPRJ7cP5nc+vCanqdEt9mf0lhdWFrC1cy7R10xjTeQwvrniRZ0c+S5w9jg3FGxRAiYgco1okcDrQwOwTmcvlijyuHR7eFJ/PF3kcExPT4HhjYVMtu93Oa6+9xpIlS9i4cSMfffQRu3fvPuDyxcZkZ2cf8Hhubi5Dhgw5rGuKiIiIyMnL7XDz1LCn2FiykTv634Hb4aZrUlcA+qf15/759/Pzjj9nZ/lOhrYbWi84ctlcvPXjW6TFpFEZqMRhc/BV9le0i2vHb776DVaLlUHpg5i+frqW3ImIHIMsrV3AiSw+Pj7yuLFlcnVVVlZGHh/J7CqbzcYtt9wSef7tt98e9jU6dOhwwK927dod9jVFRERE5ORWO3x8/0AoPS6dyedOZlTWqEYDo4FtB2IxLBR5i6gKVlFYVUjb2LYUVRext3ov3pCXr3Z9hdPqZFXBqhb8jkRE5FBEtcNp+vTpkcc33nhjo68fibrXOp7UHRSek5PDGWec0eS5dbuLjnSWUt35WLt37z6ia4iIiIiItJS6O+E1duzPI/5cEyaZkOnOZNLiSfRO7c26onVUB6sp95Wzau8qyn3lmKapHe1ERI4hUQ2cJkyYgGEYGIZRLySqff1I7H+t40ndAGjDhg0HPLf2uM1mo3v37kd0vyP9GYuIiIiIHIv2nwk1+dzJrCpYRVWgilh7LKv2ruKcjuewaM8iZm2bxT9X/5NnRz5Lelx6K1YtIiLQDEvqTNPENM0mXz+Sr+PV4MGDI8PCD7TEze/3s2TJksh77Hb7Ed1v/fr1kceZmZlHdA0RERERkWNVbQD1zIhnuPiUi+mR3IMKfwVhM8z6ovUYhsH98+/H4z/wOAsREWl+Ue1w2r59+2G9fqKLj4/n3HPPZc6cOXzxxRfk5OTUW2ZX68MPP6S8vByASy+99IjuFQwGef311yPPR4wYcWRFi4iIiIgc42qDpwFpA1hVsIqd5TuxWWyUeEsYmTWSjSUb6ZncM7KLHcCG4g1kxWeRXZGtne1ERFpAVAOnTp06Hdbrx7upU6cyceJEAB577DEmTZrU4Jz77ruPOXPmEAwGufvuu/nwww+xWq2R44WFhTzwwANAzU50t956a4NrfP311wwcOLDJneoCgQC33XYbP/74IwDjxo074jlQIiIiIiLHi9rgqXtSd+6ffz9DM4fyw94fGN1pNHd9eRd9Uvrw/PLncTvddEnowqfbPmVct3G8vvZ1LjnlEmJsMZr7JCLSTKIaOB1PFi5cyJYtWyLPCwsLI4+3bNnC1KlT650/YcKEI7rPOeecwy9/+UveeecdZs6cyfnnn8///M//kJmZyZo1a3jyySfZtWsXAM888wzJyckNrjFt2jTGjx/P+PHjGTVqFD179iQhIQGPx8P333/Pq6++GllO17ZtW1544YUjqlVERERE5HiUHpfOsyOe5f7599MntQ//74v/R1Z8Fh9t+Yh2ce3Iq8pja+lWYmwxfL7zc2wWG88uexanzUmn+E48OvRRdT6JiETZSRs4vfbaa0ybNq3RY4sWLWLRokX1XjvSwAng9ddfp7y8nP/85z98/fXXfP311/WOWywWHnnkEW6//fYmr+HxeHj77bd5++23mzynX79+vPPOO3Tp0uWIaxUREREROR5lV2QzJGMIe6v20jmhM9mebBIcCXgCHkxM3A43eZ48MuIyKPWW0jmxMxbDQqwjlvvn38+AtAG8uOJFJp01id2emh2f1f0kInLkWiRwKisri3Td3HbbbbRr1+6A5+fm5vLPf/4TgN/+9rfExcU1e43NKSYmhtmzZ/P2228zdepUfvjhB0pLS0lPT2f48OH86le/YujQoU2+/4EHHmDAgAEsXryY9evXU1BQQHFxMU6nk/T0dM444wyuuOIKLr300nrL9URERERETha9Unoxff10OiV0Ynflbs7NOpd5O+cxtutYtpVtoypQxc9O+RlrC9fSJqYN+VX5AFQHqmnnbsdX2V+R5Ejihv/cQJIrCROTZGcyz416TrveiYgcAcNsgW3gJk+ezK9+9Su6d+/Oxo0bD3q+aZr06tWLLVu28Oqrr3LLLbc0d4lyCHJyciKzobKzsxsdgC4nt0CgBL8/H693Jw5HGlbryftfBH2+HCp8Lkp9iZR402gT7yTGfvIGwntKq3E7baTEOemYGtva5YiIyAnK4/ewsWQjHdwdyPHkRP7smdwTIDJMHGBVwSqqA9W8v+l9tpVtozpYjcvqwu1wY7FYKKgqIC02DbfdzbMjnmVTySYAeiT30PI7ETmhNNdnfUtUrnIQc+bMwTAMrrrqqkM63zAMfvnLX2KaJrNmzWrm6kRERERE5ETgdrgZlD6I9Lj0en+6He7IsdrHw9oPI9mVTL+0fozpPAaXzUW/tv0o8ZVQ6i3FNE38QT+nJJ7C7Z/fztNLn+ZPS//E1Z9ezRc7v+CuL+4ivzK/tb9lEZFjVosETqtWrQLgrLPOOuT31C4xq32viIiIiIhINPVK6cWmkk04bA56JPfg8lMu572x7/H7M39P54TOnN3+bObtnIeBQbmvHJfVRaIrka+yvyJshrnzizsVOomINKFFAqe9e/cCHHR2U10ZGRkA5OfrF7iIiIiIiESf2+HmqWFPcVbmWfx5xJ8Z1mEY6XHpnN/pfF4+/2U6JXRibNexBMNBTExKfaUUVhWS6kplc+lmYu01A8c9fg9Qs6Rved7yyHMRkZNZiwROLpcLgKqqqkN+T+25GoItIiIiIiLNpe5Su/1fH99tPHsq9/Dzjj+nU0InHhzyIG9c+Aa+kI/uyd0p95VzWtpprCpYxYKcBTww/wHm58zXcjsREVoocKrtbFq+fPkhv6f23NpOJxERERERkZZU2wE1KmsUr5z/Cud1Po+uSV35x3n/wGJYGJk1ko3FG/nHqn8wa+sstpdvr7fcblvpNnU8ichJq0UCp+HDh2OaJpMnTyYQCBz0/EAgwOTJkzEMg2HDhrVAhSIiIiIiIg011gGVHpfO5HMnc2a7M6kMVGKz2FhftB5v0IvVYmVz6WacVic3zrmR+TnzeXDhgwqdROSk0yKB08SJEwHYvHkz11577QGX1lVVVXHNNdewadOmeu8VERERERE5VrgdblxWF4PSB1HiLSElJoW2MW0xTIPuyd0prC6kc2JnyvxldEroxMytM8mvzFfHk4icNFokcDrrrLP45S9/iWmafPjhh/Tu3Zs//vGPfPvtt2zatIlNmzbx7bff8sQTT9C7d28++ugjDMPgiiuuYOTIkS1RooiIiIiIyGHpldKLHeU7GJlV85nlhXNe4JXzX8FiWDin4zns9uzGipWPNn/E1tKt/HL2L/li5xfcMe8OPt/xuYInETmhGaZpmi1xI6/Xy/jx4/niiy8wDKPJ82rLOf/88/nkk08iA8el9eXk5JCVlQVAdnY2HTp0aOWK5FgTCJTg9+fj9e7E4UjDanUf/E0nKJ8vhwqfi1JfIiXeNNrEO4mxn7ybIOwprcbttJES56RjamxrlyMiIhI1Hr+HjSUb6ZncM7Lsrva1ZGcy9317H7H2WPIr82kT04aC6gK8QS8xthi6Jnbl+j7XM7DtwAZDy0VEWkpzfdZvkQ4nqNmpbu7cufz1r3+lffv2mKbZ6FdWVhYvvvgin332mcImERERERE5pjU246n2tWJvMcPaD6PcV07b2LZsL9uO2+7GwKBtbFu2lm3lsx2f8eDCB7XcTkROOLaWvJlhGNxzzz38+te/ZtWqVaxcuZLCwkIA2rRpw+mnn85pp512wA4oERERERGR40GvlF5MXz+dkVkj+aHgB1674DX+tPRP+MN+8qvycVqdZMRmkOJK4f759zMgbQDPL3+eCX0nMDRzqLqeROS41qKBUy3DMBg4cCADBw5sjduLiIiIiIg0O7fDzVPDnmJjyUbu6H8HboebV85/hVUFq6gOVPPxlo/xh/0sylnEwPSBfLXrK0p9pfx52Z+13E5EjnsttqRORERERETkZLP/kju3w82w9sM4v/P5PDr0UX4o+IEh7YYwd8dcbBZbveV2s7bN4q4v7iK/Mr+VvwsRkcOnwElERERERKQVZFdkMyRjCMmuZH7R9ReYmMQ748mvysdusbO+aD2GYXD//PvJr8xnQc4CFuQs0JwnETkutPiSOtM0WbVqFT/88AOFhYVUV1dzsI3yHn300RaqTkREREREpGXUznjqntyd3MpcXj3/VTaXbqY6UM3UdVOxWWyUeEsYmjmUe7+5l3J/OSEzRLIzmSfOfoJibzG9UnppyZ2IHJMM82BpTxRNmzaNxx9/nJ07dx7W+0KhUDNVJIejubZKlBNHIFCC35+P17sThyMNq/Xk/T8/Pl8OFT4Xpb5ESrxptIl3EmO3tnZZrWZPaTVup42UOCcdU2NbuxwREZFjhsfvYWPJRnom96wXHOVX5nP//PvpndKbZbnL6JzUmaKqIraVbyMlJoWiqiLGdh3L+qL1PDvyWdLj0lvxuxCR41lzfdZvsSV1Dz30EDfffDM7duzANM0DfgENnouIiIiIiJxo9p/xVCs9Lp1nRzzLj8U/MqTdEL7P/55sTzamaVLpqyQrPouvsr+KLLnTMjsROda0SOD03Xff8ac//QmA888/n1WrVrFixQqgZse6UChEQUEBc+bMYfz48ZimybBhw8jNzSUcDrdEiSIiIiIiIseUujOexncbz1U9r6JzQmfO7XQu2RXZtI1tS4m3hNPSTmNVwSrNeBKRY0qLzHD6xz/+AUCnTp2YPXs2NpuNdevWRY4bhkFqaiqjR49m9OjR/OMf/+Duu+9mzJgxfPfddzgcjpYoU0RERERE5JhRd8bTzvKdPDXsKa7vfT0bSzZydc+rmbR4EkMzh7IibwXri9azt2ovJibt49pzfZ/rGdh2oOY7iUiraZEOp//+978YhsE999yDzXbwjOvOO+/k8ssvZ/Xq1UyePLkFKhQRERERETm2uB1unhr2FGdlnsVTw57C7XBHluB1TeoaWXLXPr49O8t3kuJKIcWZwtayrczaNou7vriL/Mr81v42ROQk1SKBU25uLgCnnnrqvhtb9t06EAg0eM8NN9yAaZq8++67zV+giIiIiIjIMaipGU+wb8ldVnwWDquD3Z7d7Kncg91iZ33ResJmmDu/uJP8ynw8fg/L85ZruZ2ItJgWCZxqA6W2bdtGXnO79/3CLCgoaPCe2qnoW7ZsaebqREREREREjj+9UnqxqWQTGNA5oTMPDH6ABwY/QIorhSRHEptLNxNrj+Xeb+7lgfkPsCR3CQ8ufFChk4i0iBaZ4ZSWlsaePXsoLy+PvJaeno7VaiUcDvPjjz+SmZlZ7z21XVEVFRUtUaKIiIiIiMhxpXbJ3caSjUw8dWKkC6p/Wn/u/OJOuid3p9xXTs+UnjisDkzTxG13szh3McnOZHql9NKMJxFpNi3S4VS7lG7Dhg2R1xwOR+T1xpbNvfHGGwANgigRERERERGp0diSu/S4dP5x3j+wGBZGZo2kzFfG1pKtzNkxh1UFq3hyyZPMz5mvbicRaVYtEjgNHz4c0zT5+uuv671+9dVXY5omr7/+Oo899hjr1q1j6dKl3HXXXbz33nsYhsGFF17YEiWKiIiIiIicMNLj0pl87mTObHcmdoudjgkdCYQCnJp6Kp0SOlFYXYjT6mTGphkKnUSkWRimaZrNfZN169bRr18/3G43OTk5JCQkAFBVVUXfvn3ZsWMHhmHUe49pmqSkpLBq1arIPCdpXTk5OWRlZQGQnZ2tvxdpIBAowe/Px+vdicORhtV68rZo+3w5VPhclPoSKfGm0SbeSYzd2tpltZo9pdW4nTZS4px0TI1t7XJEREROGsvzlrMkdwmmaTJ351x6p/Zmae5SYmwxFHuLSYtJo3NCZ54Z8YyW14mcpJrrs36LLan7+uuv+eijjwgGg5HXY2Nj+frrrzn77LMxTbPeV9++ffnyyy8VaoiIiIiIiByhuoPFO8Z35OKuF/PwmQ/TOaEzvVN60za2LYmuRFYVrNIudiISVS0yNBxg5MiRjb7eqVMnFixYwMaNG1m3bh3BYJDu3bszcODAlipNRERERETkhNTYYHGP38NHWz6iyFsEgAUL/1j1D/q16ceLK17k2ZHPkh6X3sqVi8jxrsUCp4Pp2bMnPXv2bO0yRERERERETii1g8XrPv/ziD+zqmAV1YFqpq6bioHBR1s+ontyd+795l5uOvUmYmwxDGw7UEvtROSIHDOBk4iIiIiIiLQMt8PNsPbDWJ63nEHpg5izfQ4JjgTyKvOwWWw8u+xZnDYnneI7ab6TiByRVgmcgsEgK1asYM2aNRQXFwOQkpJC3759Of3007Hb7a1RloiIiIiIyEmlV0ovpq+fzjkdz2H2ttkMzhjMmsI1tHe3x2JYiHXEMnPrTMZ3G6/QSUQOS4sGTpWVlTzxxBP861//igRN+0tOTuaWW27h4YcfJj4+viXLExEREREROanUnfF0c9+b2Vy6mapAFbsrdxM2w2wv20672HY8uPBBnhr2lEInETlkLRY4bdy4kTFjxrBr1y5M02zyvOLiYv7yl7/w7rvvMnfuXM11EhERERERaUZ1Zzylx6UzIG0AqwpWsbl4MyW+EuLscXRK6MTMrTM5t+O5ZFdk0yull8InETkgS0vcpKysjHPPPTcSNvX9/9m787iq6vyP46/DckG4ICCLC7iLuJSQS5kaLqlZabZn00/bV8vK0cqaaprJFlvGprTJVpvSsrJcysxy3zXQUsRdwAUQ2ffl/P4w7ogsgsG9LO/n48Hjcbnne77nTZwoPny/n9OzJzNmzGD16tXs2bOHPXv2sHr1al577TUuuOACTNMkLi6Oyy+/nPT0dHtEFBEREREREf7X3+nGrjdyOOMwp/JOsXDfQg6kHeCWpbewJmEN09ZNI6sgy9FRRaQes0vB6ZVXXuHYsWMA/OMf/2DHjh1MnjyZQYMGERoaSmhoKIMGDeLxxx8nOjqaf/7znwAcO3aMV155xR4RRURERERE5AxWi5WnL36arSe20r55e9YkrKGNtQ0nc0/i5uzGgr0LVHQSkUrZpeC0cOFCDMPgpptu4umnn8YwjErHGobBtGnTuPnmmzFNk4ULF9ojooiIiIiIiJwlPjOegW0GkpGfQaBHIIfSDvFr0q+sTljNV3u/4ok1T6joJCIVskvB6ciRIwDcfvvt1T6ndGzpuSIiIiIiImJfYX5hHM44TGRIJM5OzjzZ70nae7enm183Aj0CbU+xU9FJRM5ml4JT6dPmAgMDq31O6VirVY3oREREREREHKH0KXaDQwYza9gshrQdgpPhREpeCok5iWw9vpW4jDgeXPEgidmJjo4rIvWIXQpOF1xwAQD79u2r9jmlY0vPFREREREREfsrfYqd1WLFarHy6mWv8mS/J7mxy41c0f4KNhzbQIlZwgMrHlDRSURs7FJwuu+++zBNk3/961+UlJScc3xJSQlvvvkmhmFw77332iGhiIiIiIiIVMeZT7HbnbIbb4s3+9L24eHqweOrHmdtwlptsRMR+xScbrzxRu644w42bdrE2LFjOXHiRKVjExMTue6669i8eTO33347N998sz0iioiIiIiISA1YLVZmRM4gpyiHLr5dSMtLIzU/lcUHF/Pgigc5mHaQbSe2qfgk0kS52OMic+fOJTIykt9//50lS5bQsWNHRowYQd++fQkMDMQwDBITE9m6dSvLly8nPz+fvn37EhkZydy5cyudd/z48faILyLSYPzl/c1EtPUhPMSHXsE+BHi5OTqSiIiINGJBnkHMvnw2U9ZMoVuLbuxK2cXulN34WHwY/8N4ru54NW/9+hYzImcQ5Bnk6LgiYkeGaZpmXV/EyckJwzBsn5umWebzM1V17EyGYVBUVFRrGeXcEhISCAkJASA+Pp7g4GAHJ5L6prAwlYKCRPLyjmCxBODs3HSb/ufnJ5CZ705afnNS8wLw93KjmatznV933JxNJGXkU/pjtLVPM8JDfGwffp6WOs9QkWNpuVjdXPDzdKNtCw+HZBAREZG6k1WQRXRyNLOjZ+Pi5MKxrGP4N/MnJS+FwGaB5BTlMPvy2So6idRDdfW7vl1WOMHpQlJVn1f3mIiIVG7ePZdwIj2PqPg0ouJS2RGfztKdx1m68ziGAcG+Hn8Un5ozuGv1nxwqIiIiUpXSvk5dfLowZc0UhrYdytKDSwnxCmFf2j66+Hbh8VWPc3+v+4kIjMBqabp/mBRpKuxScDp06JA9LiMiIkDL5u6Mat6SUT1bAnA0NZfo+DSi49PYdiSVJTuPsWTnMRWcREREpNYFeQYxa9gsYlNjubnrzfx19V9t/Z1KKGHZ4WUs2LuA6QOnq+gk0sjZpeDUrl07e1xGRETOkltYzNG0XI6m5RKfmkNmXiGmCc0sdb+9T0RERJomq8VK76DeAGX6O8WcisHPzY+C4gIW7F3AjaE3qugk0ojZbUudiIjUvYKiEn4/mv7Hlro09iVlUlRs4ubiRI/W3twxoD3hIT6EtfR2dFQRERFpAkpXPEUnR5OxK4Of43/mZO5JdqfsZtuJbbxy2SsqOok0Uio4iYg0ImPeWU9RcQkuzk50a+nFrf3aEt7Wh+6tvHF1dnJ0PBEREWmCSvs7mabJZzGfEdAsACfDiebuzYlNjbWthhKRxkW/fYiINCKFRSWYJnRr6cXFHfy4pGMLLmzTXMUmERERcbiIwAicDCdS8lJIzk0mJSeFlNwU1iasJasgy9HxRKSW2X2F08qVK/n222/ZsWMHJ0+eJDc3t8qn0hmGwYEDB+yYUESk4Xrhmh5E/dEg/P11h4BDeFhcuDC4ORFtfYgI8aFjgJati4iIiP1ZLVZevexVopOjyS3M5au9X/HvqH9jYtLOq52214k0MnYrOCUlJXHLLbewevVqgEqLTIZhlDlmGIZd8olIw3T06Dt4e1+C1doLw9Au4QGd/RnQ2R+A9NzC00+ni0tjR0IaGw+kYBjg7e5KeIgPz47u7uC0IiIi0tSUbq/bdmIbLZq1oLCkkKKSIorMIqKToxnYZqCjI4pILbHLb2eFhYWMGjWK6OhoTNMkPDycNm3asHTpUgzD4LbbbuPUqVP8+uuvHD9+HMMwuOiii+jZs6c94olIA3b06L85evRtnJzcsVrD8fa+GC+vi7FaL8QwmvaT2Jo3cyUyNIDI0ABOZuXzy54kvtgaT1pOIWv2JTs6noiIiDRhYX5hpOWncSLnBCdzTxLQLIB5MfMIDwjXKieRRsIuBaePP/6YqKgoDMPgo48+YsKECezatYulS5cC8Mknn9jGfvvtt0ycOJHdu3fz5JNPcv3119sjoog0UGFhc8nI2Exm5iYyM7eRkbERMHByaoaXVwReXhfj7X0Jnp49MYym08coLaeA6Pi009vr4tI4mpYLgGmCn9VCRIiPYwOKiIhIk1a6vW7B3gXsSdlDsFcwBSUFLDqwiDGdxqjoJNII2KXg9PXXXwNwxRVXMGHChCrHjh07lgsuuIA+ffpw++23c+GFF9KlSxd7xBSRBsjbux/e3v2AhykpySczc/sfBagtZGRsJj19AwDOzp707r3NsWHt4N+/7Cc6Po0jKdnA6QKTj8fplU7hIT6Eh/gQ4ufh4JQiIiIip4tON4beyLR10ygoKWDJwSWMbDeSB1c8yIzIGQR5Bjk6ooj8CXb5c/+OHTtsW+cqcnY/p06dOjFp0iSys7OZOXOmPSKKSCPg5ORG8+aXEhLyGB06/JM2bR7BxcUXMCkuznZ0PLv4Nuoop7ILGNjZn4lDOvPB7X34+oFL+dvV3Rndq7WKTSIiIlKvWC1Wpg+cTivPVoxsN5INxzZQYpbwwIoHSMxOdHQ8EfkT7LLC6dSpUwB06NDB9p7FYrG9zsnJwdPTs8w5w4YN44UXXuCnn36yR0QRaeDy8o6QkbHJtrqpsDAFMHFza4ev7+V4e1/s6Ih28d743nTSU+hERESkAbFarIzpNIYHVzyIt8WbfWn76OLbhcdXPc79ve4nIjBCW+xEGiC7FJwsFgtFRUVlikze3t6210ePHiU0NLTMOe7u7rZjIiKVOXBgKpmZmykoSAJMLJbWNG8+CG/vi/H27o/F0rSWYqvYJCIiIg2R1WJlRuQMHljxAF18u5CWl0YJJSw7vIwFexcwfeB0FZ1EGhi7FJzatm3Lnj17SEz835LIoKAgvLy8yMrKYvPmzeUKTr///jsAhmHYI6KINFApKYsAA2/v/gQHP4LVGu7oSPXCifQ8VsQksj85i5z8YjzcnOkSaGVYWBAtm7s7Op6IiIhIOUGeQcy+fDZT1kyhW4tuxJyKwc/ND9M0iU6OZmCbgY6OKCI1YJeC00UXXcSePXuIiopi1KhRtvcvu+wyli5dysyZM7nppptwc3MDIC0tjVdeeQXDMOjevbs9IopIA+XjM/SPRuEb2L17I82adcLb+xK8vS/By6sfLi7e556kkfn61wTeW3OQ4hKTM1vkrd17krkbj3DvZR25/qJgxwUUERERqUSQZxCzhs0iOjmajF0ZrExYCUBKbgqmaWp7nUgDYpeC07Bhw/jss89YunQp06ZNs71///33s3TpUqKiorjwwgsZM2YM2dnZLF68mKNHj2IYBuPHj7dHRBFpoEJDZ2GaJjk5MWRkbCIzcwsnT35LYuJ/ASc8PML+2F53CT4+kY6OW+c2Hkhh1soDNG/myg29gwkP8cHPaiE1u4CouDS+2p7A7FUHaOPTjEs6tnB0XBEREZFyrBYrA9sMxDRNlh1ehp+bHysTVrL44GLm7JyjJ9iJNBCGefYj4upAWloa4eHhmKbJL7/8QqdOnWzH7r77bj788MPTYf7YPlcaaeTIkSxduhQnJ7s8TE/OISEhgZCQEADi4+MJDtYKCSmrsDCVgoJE8vKOYLEE4OzsmL8+mWYJ2dm7SE9fS2LifykqSgUM+vXbbbcM+fkJZOa7k5bfnNS8APy93Gjm6lzn1338yx0cTM5izvg+BHi5lTuelJHHvZ9up1Oglddv7FXneUodS8vF6uaCn6cbbVvoSXkiIiJyblkFWUxbNw2rq5Xo5GicDCdauLfAxGTWsFla6SRSS+rqd327rHDy8fHh8OHDFR57//336d+/P++//z67du2iqKiILl26MH78eCZNmqRik4hU2+lC029kZGwmI2MzWVm/UlKSC4Bh1H2xpz7Yl5TJ5WFBFRabAAK93RncNZCf9+gxwyIiIlK/WS1Wpg+cTnRyNEcyjuDi5EJKbgrdWnRTTyeRBsAuBadzueuuu7jrrrscHUNEGqDs7F1nFJi2UVycA5gYhgseHj3+2E53MV5evR0d1S6Kik3cXasu1DdzdaKouM4Xt4qIiIj8aaXb67r4dOHxVY9TQgkxp2LIickhPCBcq5xE6rF6UXASETlfu3Zd/8crJzw9u+HlVVpg6oOzs6dDszlCsG8zNh48xd2DOuLsVP4pn8UlJpsOniLYt5kD0omIiIicnyDPIO7vdT/LDi+jpUdLCkoKWHRgEWM6jVHRSaSe0n41EWnQgoIm0KXLLC66aDM9enxN27ZT8fGJbJLFJoAR3YOIP5XD1K93sjcxs8yx2BOZPPn1TuJTcxjRo6WDEoqIiIicn4jACDILMikoKWDJwSXEZcTx4IoHScxWqwCR+qhOCk4//PADF110ERdddBGff/55jc79/PPPbeeuWLGiLuKJSCPSrt1T+PoOxcXFy9FR6oXrLgrm0k4tiI5L48HPfuWqt9bxl/c3c9Vb63jo81/5NS6N/p1acP1FbRwdVURERKRGSns6tfJsxch2I9lwbAOGYTBlzRSyCrIcHU9EzlLrBSfTNHnsscfYsWMHAQEB3HrrrTU6f9y4cfj7+xMdHc3kyZNrO56INGIFBYmkpa0iJWUJaWmrKChoen/tcnYy+MfYnjxxRVd6hfjg6myQlJmPq7NBeIgPT4wK4x/X9MTJKL/dTkRERKS+s1qsjOk0ht0pu/F19yUlN4UgjyCik6MdHU1EzlLrPZx++eUX9u7di7OzM2+++WaNzzcMg3/961/06tWL33//ndWrVxMZGVnbMUWkEcnLO8Lhw8+TkbGp3DFv7/60b/8c7u7tHJDMcUb0aKltcyIiItIoWS1WZkTOUBNxkXqu1lc4ff311wAMHz6c7t27n9cc3bt3Z+TIkQB89dVXtZZNRBqf/PzjxMTcSkbGRtzdOxAQcCNt2jxEYOBNNGvWkYyMDcTE/IX8/OOOjioiIiIitaS0iXhEYAQj242ko09HFh1YpK11IvVIra9w2rJlC4ZhMHr06D81z9VXX83333/Ppk3lVyyIiJQ6duxtCgtTaN/+OQICbsE4a6tYUtJ8Dh9+nmPH3qFDh386KGXdSczIO+9zg7zdazGJiIiIiH1FBEawYO8C/Nz9WHJwCSPbjeTBFQ8yI3IGQZ5Bjo4n0uTVesHpyJEjAHTt2vVPzRMaGgrA4cOH/2ykCiUlJbFlyxa2bNnC1q1b2bp1KykpKQBMmDCBjz/+uNavOW/ePD766CN27txJWloaQUFBDBo0iIceeoj+/ftXa46cnBzefvttFixYwIEDB8jPzyckJISrrrqKRx55hHbtmta2IZH09HX4+AwhMHBchccDA28hLW01aWlr7JzMPm6ds5nzbce04nFtVxYREZGGq7SJ+KIDi2xNxL0t3jyw4gFmXz5bRScRB6v1glN6ejoAfn5+f2qe0vMzMjL+dKaKBAXZ74dPbm4uN9xwA99//32Z9+Pi4vjss8+YN28ezz77LM8991yV8+zfv58rr7ySffv2lXk/NjaW2NhY3n//fT777DOuvvrqWv8aROqrwsIUmjULrXJMs2ahpKevtVMi+xrRo/zPsuPpefyWkI7V3YVOAVZ8PVxJzSnkQHIWWXlFXBDcnFbNtbpJREREGr7SJuIPrngQb4s3+9L20cW3C1PWTGHWsFnq6STiQLVecPL29iY1NZW0tLQ/NU/p+V5edf+o87Zt2xIWFsby5cvrZP4777zTVmwaMmQIkyZNonXr1vz2229Mnz6dAwcO8Pzzz9OqVSvuvffeCufIzMzkqquushWb7rnnHm655RaaNWvGypUreemll8jIyODmm29m/fr1hIeH18nXIlLfuLj4kZe3v8oxeXn7cXH5c0Xw+uqJK8LKfH7oZDaPzI/i1ovbcuvFbWnm6mw7lltYzGebjrBox3EevbyLvaOKiIiI1InSJuIPrHiALr5dyMjPoH/r/iw6sIgxncao6CTiILXeNDwgIACA3bt3/6l5YmJiAAgMDPzTmSry7LPPsnjxYk6cOMGRI0f4z3/+UyfX+eWXX5g/fz4Ao0eP5qeffuKaa66hb9++3HnnnWzatIm2bdsC8MQTT5CamlrhPDNmzGDv3r0AvPrqq7z33nsMHTqU/v37M23aNH788UdcXFzIycnh0UcfrZOvRaQ+at58IKmpv5CcvKDC48nJX5GauhIfn0F2TuYY7605SFhLb+4a2KFMsQmgmaszdw/qSNcgK++tOeighCIiIiK1L8gziNmXz8bJcKJ/6/4sP7KcuIw4HlzxIInZiY6OJ9Ik1XrBqV+/fpimyeLFi//UPN999x2GYdC3b99aSlbW3//+d66++uo631r32muvAeDi4sKsWbNwdi77C6C/vz+vvPIKcHpV1/vvv19ujsLCQt566y0AunXrxuTJk8uNufTSS7nrrrsAWL16NVu3bq3Vr0OkvmrTZiIuLj4cOvQsv/02msOHX+Do0Xc4fPgFfvttNIcO/Q0XFx9at57o6Kh28fuxdMJaVr0yNKyVN78dTbdTIhERERH7CPIMYtawWbTzbmfr6WQYBlPWTNHT60QcoNYLTqNGjQJg+fLlrFu37rzmWLNmjW17W+l8DVFmZiY///wzAJdffjnBwcEVjrvuuuvw9vYGYOHCheWOr1y50tYba8KECTg5Vfxtu/32222vK5pHpDFyc2tN9+7z8PLqS27uPpKSPufo0X+TlPQ5ubn78PbuR7dun+Hm1srRUe3CNOFYWm6VYxJSc8G0UyAREREROyrt6bQ7ZTe+7r6k5qXSK6AXsamxjo4m0uTUesHp+uuvp3379pimyY033liuwfW57N27l5tuugnDMGjfvj033HBDbUe0m61bt1JQUABAZGTlT4OyWCxccskltnMKCwvLHD+zcFfVPH369MHDwwOA9evXn3dukYbG3b093brNpVevlXTpMouOHV+lS5dZ9Oq1krCwT2jWrIOjI9rNhcHNWbPvJL/sSarw+M8xSazdl8wFwc3tnExERETEPkp7OpmY9G/dnx1JO/B182XbiW1a6SRiR7VecHJ1dbVtI0tKSqJ3797MnDmT7OzsKs/LysriX//6F3369CEp6fQvSq+//jouLrXe19xuzuxjFRYWVsXI/x0vKioqV6Sr7jwuLi507twZ+F8PLJGmxM2tFb6+Q/H3H4Ov79Ams6rpTPde1hF3Fyemfx/DvXO389bP+/h04xHe+nkf987dzks/xNDM4sy9l3V0dFQRERGROhPkGcSMy2YQcyqG7i26c9fyu1iTsIZp66ap6CRiJ3VSzbnuuuv4+9//znPPPUd2djaPP/44f/vb3xg0aBC9e/cmMDAQT09PsrOzSUxM5Ndff2Xt2rVkZ2djmqf3efz9739n7NixdRHPbhISEmyvK9tOVyokJMT2Oj4+nu7du5ebx9PTEx8fn3POs3PnTpKTk8nPz8fNze288lbk+PHj1Z5LRByjfQtP3hoXwVs/72NnQjoHksv+D9WFwc15ZFgX2rfwdFBCEREREfuIz4ynX8t+JOUk0darLekF6XTx7UJsaiy9g3o7Op5Io1dny4f+9re/ERwczMMPP0xOTg5ZWVksW7aMZcuWVTi+tNDk4eHB22+/XaYfUUOVmZlpe221Vv0oTk/P//3yl5VV9hfE0nnONUdF89Sk4HRm0UukvoqJGX9e5xmGQVjYJ7Wcpn7q4O/JmzeHk5SRx4HkbLILivC0uNApwJNAb3dHxxMRERGxizC/MObunks773bEZcZxYcCF7Evdxx097nB0NJEmoU73q91xxx2MHDmSN954g7lz53Ly5MlKx/r7+zNhwgQee+wxWrduXZex7CYvL8/22mKxVDn2zMJQbm7Zhr+l85xrjnPNI9IYZGZuqeSIQcWdsEvfN+osU30V6O2uApOIiIg0WVaLlekDpxObGstt3W5jX9o++rXsR3ZhNntO7SHMLwyr5dx/1BeR81PnDZJat27Na6+9xmuvvcauXbvYsWMHKSkpZGZm4uXlRYsWLejVqxc9evSo6yh25+7+v1/0SpuHVyY/P9/2ulmzZhXOc645zjXPucTHx1d5/Pjx4/Tr169Gc4rUtn799pT5vKSkgP37HyEv7witWz+Al1cfXF39KSw8SWbmVo4dexd39/Z07jzTQYlFRERExFGsFiu9g3qTVZDFl7Ff0t67Pc9ueJaR7Uby1q9vMSNyBkGeQY6OKdIo2bUjd48ePRplYakyXl5ettdnb5M725lN1c/eOlc6z7nmONc853KuPlMi9dHRo2+Rk7OXCy5YjLPz/7aUurm1xs3tGnx9h/Hbb2M4evQtQkL+6sCk9nM4JZtvo44ReyKTrPwiSsyKVn7BZ3dfbOdkIiIiIo6x59QeQn1DScpJoo1nG36J/4XAZoE8sOIBZl8+W0UnkTpQ60+pk/85s4BzrobcZ64uOruXUuk82dnZpKWlVWuegICAGvVvEmmoUlKW4Oc3skyx6UzOzlb8/EaQkrLUzskcY0d8Gvf/91cW7zjGgeQsCopKME0q/BARERFpKsL8wtibupfmbs05nHGYFu4t2Je2Dw9XD6asmaIn14nUAbuucGpqznzS3J49e6oY+b/jLi4udOnSpdw8X3/9tW3cJZdcUuEcRUVFHDhwAIBu3bqdd26RhqSw8BSmWVjlGNMsorAwxU6JHGvO2oMUl5j8dUQoI3q0xNmp6fWuEhERETnbmf2cru18LX9d/Ve6+HYhIz+D/q37s+jAIsZ0GqOeTiK1SCuc6lDfvn1tjb5Xr15d6biCggI2bdpkO8fV1bXM8YEDB9peVzXPtm3bbFvqBgwYcN65RRoSd/e2nDq1jMLC1AqPFxae4tSpZbi7t7NzMsc4kJzNkK4BjLqglYpNIiIiImco7efU0acjsy+fjZPhRP/W/Vl+ZDlxGXE8uOJBErMTHR1TpNFQwakOeXl5MWzYMABWrFhR6ba6b775hoyMDACuvfbacscHDx5M8+bNAfjkk08wK9kL8/HHH9teVzSPSGMUFDSBwsKT7Np1HSdOfEJ29u/k5x8nO/t3Tpz4mF27rqOwMIWWLSc4OqpduLs64+tx7idaioiIiDRlQZ5BzBo2i3be7RjZbiQbjm3AMAxtrxOpRSo4/Qkff/wxhmFgGAbPP/98hWP++tfTTYqLiop46KGHKC4uLnP85MmTPPHEEwD4+Phw9913l5vDYrHwyCOPABATE8Nrr71WbszGjRv54IMPAIiMjKRv377n/XWJNCSBgTfSps3DFBYmExf3Mrt23ciOHUPZtetG4uJeprAwmTZtJhIQcIOjo9rFxR382Hk03dExREREROo9q8XKmE5j2J2yG193X1JyUwjyCCI6OdrR0UQahSbbw2ndunXs37/f9vnJkydtr/fv319mtRDA7bfffl7XGTp0KLfccgvz589n0aJFDB8+nEcffZTWrVvz22+/8eKLLxIXFwfAK6+8gq+vb4XzTJkyhS+++IK9e/cydepU9u/fzy233EKzZs1YuXIl06dPp6ioiGbNmvGvf/3rvLKKNFRt2jxEixajSUlZRE7OXoqLM3F29sLDoystWozG3b2toyPazX2RHZk0P5p//7KfewZ1wN3V2dGRREREROotq8XKjMgZPL7qcUooIeZUDDkxOYQHhKufk8if1GQLTu+//z6ffPJJhcfWr1/P+vXry7x3vgUngA8//JCMjAy+//57Vq5cycqVK8scd3Jy4m9/+xv33ntvpXN4eXmxdOlSrrzySvbt28d7773He++9V2aMt7c3n332GeHh4eedVaShcndvS5s2Ex0dw+H+sSQGd1dnvos+yo+7ThDs2wwPS/kf9YYBr9/YywEJRUREROqXIM8g7u91P8sOL6OlR0sKSgrURFykFmhLnR00a9aMpUuX8tlnnzF8+HACAwOxWCyEhIRw6623sm7dukq35J2pc+fOREVF8corr9CnTx98fHzw8PCga9euPPbYY+zcuZOrr7667r8gEam3dsSncSApC9OE3IJi9iVmsSM+rcIPERERETktIjCCzIJMCkoKWHJwiZqIi9QCw6ysA7XIWRISEggJCQEgPj6e4OBgByeS+qawMJWCgkTy8o5gsQTg7Gy/vwhlZe0kO/s3ioszMM3iCkYYtGnzkN3y5OcnkJnvTlp+c1LzAvD3cqNZE97ediwtF6ubC36ebrRt4eHoOCIiIiLlZBVksejAIuIy4thwbAO+7r6YmMwaNksrnaRRq6vf9ZvsljoRaRyKitLYt+8hMjN/Baqqn9u34CQiIiIiDUtpE/EHVzyIr7svqXmpRIZEEpsaS++g3o6OJ9Lg2L3gVFJSwsqVK9m4cSMnTpwgJyeHF198kVatWtnGFBQUUFRUhLOzM25ubvaOKCINSFzcy2RmbsfLqx/+/tdisbTEMJruSiIREREROX+lTcSnrJlC/9b92ZG0g9u63eboWCINkl0LTkuWLOGRRx7hyJEjZd7/61//Wqbg9P777/Pwww9jtVo5duwYnp6e9owpIg1IWtpKPD0vJCzsEwzDcHQcu1u+6wQAA7v442FxsX1eHSN6tKyrWCIiIiINVpBnEDMuO110Cg8M5+8b/864sHFEBEZoa51IDdit4DRnzhzuv/9+SltG+fv7c/LkyQp/Qbz77rt55plnSE9PZ+HChdx2myrKIlKxkpJ8vLz6NMliE8Ary2IxDOjWyhsPPxfb51UxzdNPqVPBSURERKRi8Znx9GvZD9M0icuMY9nhZSzYu4DpA6er6CRSTXYpOO3bt4+HHjrdO2Xo0KG8/fbbhIWF4eRU8UPyLBYL119/PR988AHLly9XwUlEKuXhEUZBwVFHx3CYKSO7YhjQwmoBYOoVXR2cSERERKThC/MLY+7uuVhdTxeX/Nz8ME2T6ORoBrYZ6OB0Ig2DXQpOb775JkVFRfTs2ZPvv/8ei8VyznMGDRrEBx98QFRUlB0SikhD1abNRPbufYCsrGis1nBHx7G7K3qWXaU0UquWRERERP40q8XK9IHTiU6OJiU3hZUJKwFIyU3BNE1trxOpBrsUnH755RcMw+DRRx+tVrEJoHPnzsDpR/KJiFSmsPAkPj6DiYm5jRYtRuPp2QNn54r/4+/vP9a+4URERESkwbJarAxsMxDTNFl2eBl+bn6sTFip7XUi1WSXglNCQgIAvXr1qvY5pY3Cc3Jy6iSTiDQOBw8+CRiAycmTCzl5cuEfn5/JBIwmUXCavGAHESE+hIf40K2VN85OTbO3lYiIiEhtiQiMYMHeBbZ+xNpeJ1I9dik4lTbzrUnxKCUlBYDmzZvXSSYRaRw6dHjJ0RHqld+PphMdl4ZhgMXFiR6tm9sKUF1beqkAJSIiIlJDFW2vKzFLOJJxhC4+XQjyDHJ0RJF6yS4FpzZt2rBv3z4OHjzIoEGDqnXOunXrAOjYsWNdRhORBi4g4FpHR6hXFk8cyO7jGUTHpREVn8rOhDR+PZKKYYC7qzM9W3sTHuJDrz9WQImIiIjIuZ25vW7xwcXsTtmNi5MLU9ZMYdawWdpaJ1KBih8TV8sGDx6MaZp88skn1Rqfnp7Ou+++i2EYDB06tI7TiYg0HhYXJ8JDfLh9QHtm3hLBoocG8OoNFzKuX1s6+Hvya1wa7687xMPz9EAGERERkZqKCIzgRNYJWri3IDUvlW5+3Vh0YBFZBVmOjiZS79il4HTfffdhGAarV6/m448/rnJsSkoKY8eO5cSJE7i4uHD//ffbI6KISKPk5upMgNUNf6sbLTwtNLM4Y5rwRwsCEREREakBq8XKjMgZmJj0b92f5UeWcyL7BNPWTVPRSeQsdtlSFxERwaRJk/jXv/7FXXfdxQ8//MD1119vO75hwwaio6NZv349n3/+ORkZGRiGwd/+9jfatWtnj4gi0kBs2RIGOHHBBUtp1qzDH59Xpy+RQb9+u+s4Xf1wNC33jy11aeyITyM1pwDThNY+zbisSwDhIT5EtPVxdEwRERGRBinIM4hZw2ax6MAiRnccjauTK1ZXq5qIi5zFLgUngNdff538/Hxmz57NV199xVdffWVrJn7ffffZxpV2/n/00Ud55pln7BVPRBoIL6++ADg7NyvzuZx2y3ubOJmVD0CAlxt92vvamoYHers7OJ2IiIhI42C1WBnTaQxT10wlLjMOgPT8dMIDwtXPSeQPdis4GYbBO++8w9ixY3n55ZdZvXo1JSUl5cb079+fZ555hlGjRtkrmog0IN26fVrl501dcubpYtNF7Xy56oKWRIT40tzD1cGpRERERBofq8XKuLBxLDu8DD83P1LyUrTKSeQMdis4lRo+fDjDhw8nMzOTqKgokpKSKC4upkWLFoSHh+Pv72/vSCIijcYDgzuxIz6NnUfTiYpLBaB9C0/bNrpeIT5Y3ez+o19ERESkUYoIjGDennnsSN4BaJWTyJkc9luHl5cXl112maMuLyKNxMmT3+LtfQkWS0tHR6kXbugdzA29gzFNk31JWUTFpREdn8aPu0+wMOooTk4GnQI8uaitL/de1tHRcUVEREQatDNXObX0aElBSQGLDixiTKcxKjpJk2eXp9SJiNSVgwefJDp6CDt2jODQoWc4eXIxBQVJjo7lcIZhEBrkxc19Q3jpugv4+v5LuT+yI97uLuxLzOLLbfGOjigiIiLSKEQERpBZkElBSQFLDi7RU+tE/qB9FSLSoHXoMJ2MjM1kZm4hOfkrkpO/BsDdvR1eXv3w9r4Eb+9+uLo2re26JaZJ7IlMouNPr3D6/WgG+UXFmCa4OBt0DfJydEQRERGRRsFqsTJ94HTbU+s8XT3p4tuF2NRYegf1dnQ8EYexS8HpzjvvrPE5hmHg7u5O8+bN6dKlC5dccgndunWrg3Qi0pAFBFxHQMB1AOTlxZORsYnMzE1kZGwlOflLkpMXANCsWUcuuGCpI6PaxYJt8UTFp/Hb0XRyC04XmJycDEKDrIT/8bS6C9o0x93V2dFRRURERBqN0qfWTVs3jS6+XdiXuo87etzh6FgiDmWXgtPHH3+MYRh/ep4+ffrwxhtvMGDAgFpIJSKNjbt7CO7uIQQG3khxcRZJSQs4fnwORUWnyM096Oh4dvHu6oMYBnQO/F+B6cLg5nhYtKBVREREpC6VrnSKTo6mq29XopKiiAiMUC8nabLs8htI27ZtMQyDnJwckpOTbe9bLBb8/PwASE1NJT//9OO8DcPA398fd3d3MjIySE9PB2Dr1q1ERkbyySef8Je//MUe0UWkgSgpySMzcxsZGZvJyNhMTs5uTLMYJyd3vL0H4O19saMj2sUL1/SgV7APVncVmEREREQc4fOYz4nPjMfEpI1nG27rfpsKT9Ik2aVp+OHDh1m4cCFeXl5YLBYee+wxoqKiyMnJ4dixYxw7dozs7GyioqJ49NFHcXV1xWq1snDhQlJTU4mPj+eVV17By8uLkpIS7r77buLj1fBWRCAhYSa7d9/K9u19iY29mxMnPsHJyZ3WrR+gW7f/ctFFWwgL+4DWre91dFS7GNDZX8UmEREREQfZc2oPPm4+BDQLwM/NjwPpB1h2eJmaiEuTZJffShITE7nyyivJyMhg5cqV9O/fv9wYJycnevXqxRtvvMGNN97I5ZdfzpVXXklUVBRt2rRhypQpXH755QwcOJC8vDzefvttXnnlFXvEF5F67Nix2YCBt3d/WrW6Gy+vPjg5WRwdS0RERESaoDC/MNLy00jKTSKvKA83Zzf83PwwTZPo5GgGthno6IgidmOXFU6vv/46J06c4PHHH6+w2HS2/v378/jjj5OUlMSMGTNs70dERHDnnXdimiY//fRTXUYWkQbCw6MrABkZG9i//2H273+EEyc+Jjs7xsHJRERERKSpsVqsvHrZqzzZ70me6PsEwdZgViasJDo5mtnRs0nMTnR0RBG7sUvB6bvvvsMwDEaOHFntc6644goAli4t+1SpUaNGAae36YmI9Oz5HRddtJHOnf+Nv/+15OcfJS7uZXbtuo5ff72YffseJjHxv+Tm7nd0VBERERFpAqwWKwPbDGR4++Hc1v02urfojpPhhIuTC1PWTNHWOmky7LKlLiEhAQA3N7dqn1M6tvTcUq1btwYgJyenltKJSEPn4uKDn99w/PyGA1BYeIrMzC1kZGzm1KkfSU1dARj067fbsUFFREREpEmJCIxgzs45tHBvQWpeKv1b92fRgUWM6TRGTcSl0bPLCidPT08Atm/fXu1ztm3bBoCHh0eZ90ufZFf6dDsRkTMVFp4kI2Mj6ekbSE9fT1HRKcD840NERERExH6sFiszImdgYtK/dX+WH1nOiewTaiIuTYJdVjj17t2bH3/8kZdeeombbroJX1/fKsenpKTw8ssvYxgGffr0KXMsNjYWgICAgDrLKyINR2Fhqm01U0bGJvLyDv1xxMTV1R8/v6vw9r4Yb++LHZpTRERERJqmIM8gZg2bxaIDixjdcTSuTq5YXa1qIi6Nnl1WOD344IMAxMfHc8kll7Bs2bJKx/7www9ceumlxMXFAfDQQw+VOb5s2TIMw6Bv3751F1hEGoyoqEvZv/9RkpI+p6goFT+/EbRr9zcuuGApERHr6Nz5dQIDb8LdvZ2jo9rF5W+s5tONR6oc899NR7j8jdV2SiQiIiIiVouVMZ3GsD9tPz8e+ZGdJ3cyL2aeVjlJo2aXFU6jR4/mgQceYPbs2ezfv5+rrroKf39/wsPDbSuVkpOTiY6O5uTJk7bz7rvvPq6++mrb5ydOnODbb7/FNE1bU3ERadp8fYfi5XUJ3t4X4+ER6ug4DmeaYGr7oIiIiEi9Y7VYGRc2jmWHl9HSoyUFJQXq5ySNml0KTgDvvPMO7dq14/nnnycvL4/k5GRWrFhRZoxpnv4lyc3Njeeee44nn3yyzHFvb29iYk4/6rxNmzb2CS4i9VqXLu84OkKDk5ZbiMXFLgtcRUREROQMEYERLNi7AD93P5YcXMLojqOZtm4a0wdOV9FJGh27FZwApk6dyoQJE/jkk09YsWIFv//+O6mpqQD4+vrSo0cPhg0bxoQJE2jVqlW58z08PGjXrmlsixERqa7lu06U+Xx/Una59wCKTUjOzOOn3Yl08Pe0VzwRERER+YPVYmX6wOnq5yRNgl0LTgBBQUFMnTqVqVOn2vvSIiKN0ivLYjGM068NAzYcOMmGAyfLjftjESluLk5M6N/efgFFRERExKa0n9PUNVOJyzzduzg9P53wgHCtcpJGxS4Fp44dOwLw+OOPM3HiRHtcUkSkyZh6RVfgdEFpxo+xDOjsz4DOLcqNczIMvNxd6NHaGy93V3vHFBEREZE/nNnPyc/Nj5S8FK1ykkbHLgWnhIQEiouLCQ8Pt8flRESalJE9Wtpe70hIY2BnfwZ09ndgIhERERE5l4jACObtmceO5B2AVjlJ42OXrrEtW57+ZahZs2b2uJyISJP1xBVhKjaJiIiINAClq5x6BfRiZLuRdPTpyKIDi8gqyHJ0NJFaYZeC08UXXwzArl277HE5EZEmKzEjr9ofIiIiIuJYEYERZBZkUlBSwJKDSziRfYJp66ap6CSNgl221D3wwAN8/fXXvPnmm4wbNw5XV/UOEZHacfDgU/j6Xo6v77BKx6SmriQ1dTkdO75kx2SOceuczbYG4uey4vHIug0jIiIiIlU6+6l1nq6edPHtQmxqLL2Dejs6nsifYpcVTkOHDuWpp55ix44dXH311cTHx9vjsiLSBJw8uZCcnJgqx+Tm7uHkyW/tE8jBRvQIYnj38h+XdvInyNsd04QLg5szvHuQo6OKiIiICP97at3hjMNkFWax9fhWgq3Bjo4l8qfZZYXTCy+8gJubGxdccAE//fQTHTt2ZMCAAVx44YX4+vri7Oxc5fnPPvusPWKKSCNVUpKPYVT9c6axeOKKsEqPmabJl9sS+GJrPH8d0dWOqURERESkKlaLlacvfpopa6bQvUV3pqyewozIGQR56o+E0nDZpeD0/PPPY/yxx8MwDIqLi1m7di1r166t1vkqOIlI1SreQ2aaJgUFx0lLW4Ora6CdM9U/hmFwc98QNh9K4T9rDvL3MT0cHUlERERE/hCfGU94QDir4lfh6+7LlDVTmDVslp5aJw2WXQpOcPoXv6o+FxGpri1bwjizyHT06NscPfp2FWeYtGp1T53naihCg7z4/rcTjo4hIiIiImcI8wvjrV/fwtfdl9S8VCJDItXLSRo0uxScSkpK7HEZEWkivLz62l5nZm7DYmmFm1ubcuMMwxkXl+Z4e19CQMBN9oxYrx1Ly6O4REV/ERERkfrEarEyI3IGU9ZMITIkkiMZR+jqqzYI0nDZbYWTiEht6dbtU9vrLVvCCAi4jjZtJjowUf1XYpqczMznx12JbDhwkoi2vo6OJCIiIiJnCfIMYtawWcSmxhJsDSYqKQqAiMAIba2TBkcFJxFp0Pr12+PoCPXKsNdXY1Tc0goA0wQvdxceiOxov1AiIiIiUm1Wi5Wuvl2ZumYq8ZnxFJvF+Lr58sbgN9REXBoUFZxERBqRC4ObV1hwMgwDLzcXurb04oqeLfH1sNg/nIiIiIhUy55Te/Bx8yG7IJuDGQdxd3FXE3FpcFRwEpEGLSZmfLXGGYZBWNgndZzG8d68OdzREURERETkTwrzCyMtP42j2UdPP3m5qIBerXupibg0KHYtOBUUFPDZZ5/x7bffsmPHDk6ePElubm6V5xiGQVFRkZ0SikhDk5m55RwjDMDkzKfaiYiIiIjUZ1aLlVcve5WNxzfyye+fEBEUwYG0A/Rr2Y+sgiytcpIGwW4Fp7179zJ27FhiY2MxTT0dSURqR2U9nIqLs8jO3kVCwptYLEF06vSGnZM5VkFRCZsPnWJ/UibZ+cV4ujnTOdCLizv4YXFxcnQ8ERERETkHq8XK8HbD6d+qP9HJ0RxMO8iO5B0s2LuA6QOnq+gk9Z5dCk7Z2dmMGjWKQ4cO4eTkxDXXXENAQABz5szBMAyeeeYZTp06xbZt29i8eTOGYdC/f3+GDx9uj3gi0gg5O1vx9r6Yrl3f57ffxnDs2Owm8yS79ftP8sZPe0nPLeTM+r5hgI+HhceHd+HSTv6OCygiIiIi1Wa1WHF3dqdbi26YponV1Up0cjQD2wx0dDSRKtml4PTuu+9y6NAhnJ2d+fHHHxk6dCi7du1izpw5APz973+3jY2KiuL//u//2LRpE7fccgsTJzaNXxBFpG44O1vx8RlEcvI3TaLg9OuRVJ5fvBsnA67o2ZIL2zTH19NCanYBOxPS+SkmkecW7eaV6y/gora+jo4rIiIiItUQ5hfGh79/SFxmHADp+emEB4RrlZPUa3YpOC1evBjDMLjpppsYOnRolWMjIiJYuXIlvXr14vHHH6d///707q2maCLyZzhRWJjs6BB28fGGw7i5OPHvcRF08Pcsc2xEj5Zce1EbHpkXzScbDqvgJCIiItJAWC1WxoWNY9nhZfi5+ZGSl6JVTlLv2aWRx+7duwG49tprKzxeUlJS5vOAgAAef/xxioqKePvtt+s8n4g0Xnl58Zw6tQw3tzaOjmIX+5OyGNw1oFyxqVSnACuDuwawLzHLzslERERE5M+ICIwgNS+VlQkr2XlyJ/Ni5pFVoP+nk/rLLiuc0tLSAGjXrp3tPTc3N9vr7OxsvLy8ypwzYMAAAFavXl33AUWkwTp48KkK3zfNYgoLE8nM3I5pFhEc/IidkzmGm6szPs1cqxzj4+GKm6uznRKJiIiISG04c5VTS4+WFJQUsOjAIsZ0GqOtdVIv2WWFk4eHBwCG8b/Hkvv4+Nhex8XFVXruiRMn6iyXiDR8J08urPAjJWURGRmbcXMLoX37fxAYOM7RUe3iorY+bI9Lq3LMr0fS6N1O2+lEREREGpqIwAgyCzIpKClgycElnMg+wbR107TSSeolu6xw6tChAzt37uTYsWO29/z9/fHz8yM1NZX169fTo0ePMuds374dAIvFYo+IItJA9er1cyVHnHBx8cLZuWn9tef+yE48Mj+Kl37Yw10D2hPo7W47lpSRx/vrDpGeW8g/xvaoYhYRERERqY+sFivTB05n0YFFjO44GlcnVz21TuotuxSc+vTpw86dO9m2bRtjxoyxvT9s2DAWLFjAjBkzuOGGG/Dz8wPg4MGDvPzyyxiGQXh4uD0iikgD1VR6M1XXSz/swcvNlZ9jElm5J4lAbzd8PSyk5hSQlJFPiWnS0d/K9O/3lDnPMOD1G3s5KLWIiIiIVJfVYmVMpzFMXTNVT62Tes0uW+qGDx+OaZosWrSozPuPPHK6p8rBgwcJDQ3lxhtv5MorryQ8PNy2Guree++1R0QRaSTy8uLJzt5NXl68o6M4xI74NA4kZ2GaUFxicjwtj93HMjielkdxiYlpwoHkLHbEp5X7EBEREZGGobSfU6+AXoxsN5KwFmHEpsY6OpZIGXZZ4XT11Vdz2WWXUVxczIEDB+jUqRNwujH4s88+ywsvvMCpU6f45ptvADBNE4A77riDW2+91R4RRaQBKyrK5OjRmZw8+R3Fxf/bv+7sbMXffyxt2jyCi4tXFTM0Hj9PjnR0BBERERGxg4jACBbsXUBLz5bEpMQQHhBOVkGWVjlJvWGXgpOHhwerVq2q8Njzzz/PoEGDeP/999m1axdFRUV06dKF8ePHc/3119sjnog0YIWFKcTE3Epe3hGcnb3x8uqLq6s/hYUnycnZQ2Lip6Snr6Fbt89xdW3h6LgiIiIiIrWitJ9TdHI0e1L2sPXEVubsnMOMyBkEeQY5Op6IfQpO5zJs2DCGDRvm6Bgi0gDFx79OXt4RWrW6l9at78fZ2cN2rLg4h2PHZnP8+BwSEt6gQ4cXHZjUPh7/cgdX9AhiRI+WlY75aXciP/x+gjduUs8mERERkYbMarHi7uxOJ59OrIpfha+7L1PWTGHWsFla6SQOZ5ceTiIidSUtbSXe3pcQEvJ4mWITgLOzByEhk/Hy6kdq6i8OSmhfO+LTOJGRV+WYxIw8diak2SeQiIiIiNSpML8wopOi8XX3JSU3hSCPIKKTox0dS0QFJxFp2EpKcrFaq16pY7VGUFJSdRGmKckrLMbZyXB0DBERERGpBVaLlRmRMygqKaKEEmJOxTAvZh5ZBVnnPlmkDjlsS11GRgaZmZkUFxefc2zbtm3tkEhEGqJmzbqQn3+0yjEFBQk0a9bFTonsL/GsFU1Z+UXl3gMoMU2SMvNZs+8kLb3d7RVPREREROpYkGcQ9/e6n2WHl9HSoyUFJQUsOrCIMZ3GaGudOIxdC04//fQTs2bNYt26dZw6dapa5xiGQVFRUR0nE5GGqnXr+9i//zH8/a+jefNLyx1PT1/HqVM/0rnzWw5IZx+3ztmM8ceCJcOAb349yje/Vl6EM024L7KjndKJiIiIiD2UPrXOz92PJQeXMLrjaKatm8b0gdNVdBKHsFvB6ZFHHuGdd94BwDRNe11WRBq54uIsmjcfQGzsXTRvfilWa2/bU+oyM7eTkbEBH5/BFBdncPLkt2XO9fcf65DMtW1Ej/89hWT5rkQ6BVjpFOhZbpyzYeDl7kJEW1/6dfCzZ0QRERERqWOlT61bdGARozuOxtXJFaurlejkaAa2GejoeNIE2aXg9Pnnn/P2228D4O7uztixY+nduzd+fn44OamNlIicv4MHnwQMwCQ9fT3p6evLjUlLW0la2qoz3jEBo9EUnJ64Isz2ekd8Olf0DOK6i4IdmEhEREREHMFqsTKm0ximrplKXGYcAOn56YQHhGuVk9idXQpO//nPfwAICQnhl19+oVOnTva4rIg0AR06vOToCPXK5/dc7OgIIiIiIuJAVouVcWHjbP2cMCA2NZbeQb0dHU2aGLsUnHbu3IlhGDz33HMqNolIrQoIuNbREURERERE6pXSfk4tPVuyL3Ufd/S4w9GRpAmyS8GpsLAQgIiICHtcrsaOHDnCW2+9xdKlS4mPj8fNzY1OnTpx00038dBDD+Hh4fGnr3Ho0CHeeustfvrpJ44cOUJJSQmtW7dm+PDhPPTQQ/To0aPK82+//XY++eSTal+rffv2fzqziDQ8f3l/c7XHfna3VkOJiIiINEal/Zyik6MJDwgnuzCbPaf2EOYXpq11Yjd2KTi1b9+emJgYsrKy7HG5Glm8eDG33XYbGRkZtvdycnLYtm0b27Zt4/3332fp0qV07tz5vK/x3nvv8fDDD1NQUFDm/f3797N//34++OADXn/9dSZOnHje1xBp6kyziNzcQxQXZ2CaJRWO8fbua+dU9ldimhgY5d7PLigiK+/0Ez/9rBZc1T9PREREpNH7MvZL2nu359kNzzK642jm7p6rp9aJ3dil4HTdddfx4osv8vPPPzNo0CB7XLJaoqKiuPnmm8nNzcVqtfLUU08xZMgQcnNzmT9/PnPmzGHv3r1cddVVbNu2DS8vrxpfY/78+dx3330ANG/enMmTJzN06FDc3NyIiori1VdfZf/+/TzyyCMEBgZy0003VTlf69at+fHHH6sc06ZNmxrnFGmoTNPk6NGZJCb+l+Li7CrH9usXY6dUjjPvnksqPXYiPY9Zqw6QmlPAjBsutGMqEREREbG3Paf2EOobSlJOEm292nIy96SeWid2ZZeC0+TJk/n000/517/+xS233EJYWNi5T7KDSZMmkZubi4uLC8uXL6d///62Y0OHDqVLly5MnTqVvXv38vrrr/P888/XaP6cnBwmTZoEgNVqZd26dfTs2dN2vE+fPtx8880MHDiQ3377jUceeYQrr7wSq7XyarOrq2uZOUSaumPH3uHYsXdxdvbG338sFksQhmGXH20NTsvm7jx7dTfumbudD9Yd4qEh579yU0RERETqtzC/MObunks773YczjhMcm4yToaTnlondmOXPRXNmzfnxx9/JCgoiEsvvZRZs2aRmppqj0tXasuWLaxduxaAu+66q0yxqdTkyZPp1q0bADNnzrT1oqqu77//nqSkJOB0cauiQpG3tzdvvPEGAImJiXz88cc1uoZIU5ec/A0WS2suvPBHOnZ8ieDgR2nTZmKFHwIuzk70bufLqr3Jjo4iIiIiInWotI/T4JDBPHPxM0QERjAkeAjN3ZoTnRzt6HjSBNTqMoCOHTtWeTwnJ4e0tDQefvhhHnnkEfz9/c/ZkNswDA4cOFCbMQH49ttvba/vuKPijv1OTk6MHz+ep556irS0NFauXMmIESOqfY1t27bZXo8aNarScYMHD8bd3Z28vDy++uor9XISqYHCwmQCA8fh6urr6CgNRl5RMZl/9HMSERERkcbLarHSO6g3WQVZLNy/kB3JOwC0yknsolYLTocPH67WONM0MU3TtvqnKoZRvvltbVi3bh0Anp6e9O7du9JxkZGRttfr16+vUcEpJSXF9jooKKjScS4uLvj5+XHs2DE2btxIUVERLi7aEiRSHW5uwRQX178HEtRXOxPS+GVPEiG+zRwdRURERETsxGqxMi5sHMsOL6OlR0sKSgpYdGARYzqNUdFJ6kytVjUmTJhQm9PVqZiY082DO3fuXGVx58x+U6XnVNeZvZjS09MrHWeapu0peQUFBezfv7/SPlcpKSlERkby+++/k5WVhZ+fHxdeeCGjR4/mzjvvPOeKMZHGJjBwHMeOvUthYQquri0cHcfhHv9yR4XvF5eYnMzKJzEjD4D/69/OnrFERERExMEiAiNYsHcBfu5+LDm4hNEdRzNt3TQ9tU7qTK0WnD766KPanK7O5OXlcfLkSQCCg4OrHOvr64unpyfZ2dnEx8fX6Dql/Z8AVq9eXelKqqioKLKy/rdCIy4urtKCU1ZWFmvWrLF9fuLECU6cOMHy5ct5+eWX+fLLL7n00ktrlLNUQkJClcePHz9+XvOK1CVf32FkZm5j9+5baNPmITw8uuPsXPF/MN3cWts5nf3tiE+r8H3DAKubC33a+XJD72D6tPezbzARERERcajSnk6LDixidMfRuDq56ql1Uqea5L6tzMxM2+uqnghXqrTgdGZRqDpGjRqFi4sLRUVFvPHGG4wfPx5/f/8yY0pKSnj66acrzVfKMAwuueQSRo8ezUUXXURQUBB5eXn89ttvfPDBB2zZsoWjR48yYsQI1q5dS0RERI2yAoSEhNT4HBFH27FjGGAAJgcPPlXFSIN+/XbbKZXj/Dw58tyDRERERKRJslqsjOk0hqlrphKXGQeon5PUnSZZcMrLy7O9tlgs5xzv5uYGQG5ubo2uExISwv3338/bb7/N0aNHGTBgAK+++ipDhgzBYrEQHR3N888/z48//ojFYqGgoKDS67z55pv4+PiUe79///7cc889PPPMM0yfPp3s7Gzuvvtutm3bVmf9r0TqE3//sZwuOImIiIiIyLmon5PYi90KTnFxp6unQUFBtgJOZfLy8mwNxdu2bVvrWdzd3W2vS4s8VcnPzwegWbOaN9l97bXXOHjwIN9//z179+5l7Nix5cb06dOHvn37Mnv2bAC8vLzKjamo2FTKMAxefPFFNm/ezM8//8yvv/7Khg0bGDBgQI2ynmvL4PHjx+nXr1+N5hSpax07vuzoCPVScmY+p7JP/3zz87QQ4FX1z10RERERaTrUz0nswS4Fp+XLlzNq1CisViuHDx8+Z8EpJyeHHj16kJuby4oVKxg8eHCt5jmzoFOdbXLZ2dlA9bbfnc3NzY3Fixfz4Ycf8s4777Bjxw5M0wQgMDDQtjrpscces53j63t+j3e/7777+Pnnn4HTPaNqWnA6Vz8rEanfcguK+WJbPMt+P8HJrPwyx/ytbozq2ZKb+oTQzOLsoIQiIiIiUh+c3c/J09WTLr5diE2NpXdQ5U9xF6kJJ3tcZMGCBZimydixY6tVTPHz8+P666+npKSEL774otbzuLu706LF6adZnatRdmpqqq3gdL49jpycnLj77ruJiooiPT2dffv2cfToUY4fP84///lP3N3d2bdvn2189+7dz+s6Z5539OjR85pDRBqmo2m53Pff7fx30xGSM/Px87QQ1tKLsJZe+HlaSM7M59NNR7jvv9s5nl6z7cEiIiIi0viU9nM6nHGYrMIsth7fSrBVixCk9thlhdPGjRsxDIMRI0ZU+5yRI0cyd+5cNm7cWCeZunfvztq1a9m/fz9FRUW4uFT8j2LPnj2212c+de58eXl5ldsyV1xcTHR0NAAdO3Ys11i8utSzSZqK2Nh7zuMsg65d36v1LPVBQVEJ0775jaOpuQzrFshtl7SjrZ9HmTFxp3L476Yj/ByTxFPf/M57/9cbi4td/uYgIiIiIvWU1WLl6YufZsqaKYQHhvPi5he1rU5qjV0KTocPHwYgNDS02ud07twZgEOHDtVFJAYOHMjatWvJzs5m+/btXHzxxRWOW716te11TbeoVdfKlStJSUkB4Oabbz7veXbv/t8TuFq3bvyPf5emKz197Xmc1XgLsot2HCMhNZfx/dsx4dL2FY5p6+fBtCu7EeLrwccbDrN45zGuv0h/wRIRERFp6uIz4+nXsh+maWJ1tRKdHM3ANgMdHUsaAbsUnIqKigBwdq5+35DSsWc+Ua42jR07lpdeegmAjz76qMKCU0lJCXPnzgVON+0eMmRIrecwTZPnn38eAFdXV+6553xWbpz2n//8x/Y6MlKPRpfGq1evnx0doV5Zuy+ZNr7NGN+/3TnH3nZJW36KSWR1bLIKTiIiIiJCmF8YH/7+IXGZpx/0lZ6fTnhAuFY5yZ9ml/0UpVvEDh48WO1zSsf6+fnVSaZ+/foxaNAgAD744IMKt+69/vrrxMTEADBp0iRcXV3LHF+1ahWGYWAYBrfffnuF10lJSbE95e5sxcXFTJw4kfXr1wPw1FNP0aFDh3LjNm3axPHjxyv9WkzT5JlnnmHFihUA9OrVq85WY4nUB25ubc7ro7E6kpJD73a+1dpWaxgGfdr5Encqxw7JRERERKS+s1qsjAsbR6+AXoxsN5KwFmHEpsY6OpY0AnZZ4RQeHs7x48f54osvuOGGG6p1zvz58wHo2bNnneWaOXMmAwYMIDc3lxEjRjBt2jSGDBlCbm4u8+fP5733Tvd7CQ0NZfLkyed1jZUrVzJx4kRuueUWIiMjadu2LXl5eezcuZP33nvP1rtp1KhRPP300xXOsWzZMl5++WWuuOIKhg8fTvfu3fHx8SE/P5+dO3fy4YcfsnnzZgA8PDyYM2eO+jmJNCG5hcVY3ar/49zTzYXcwuI6TCQiIiIiDUlEYAQL9i6gpWdLYlJiCA8IJ6sgS6uc5E+xS8Hpmmuu4fvvv+ebb75hwYIF3HjjjVWO//LLL/nmm28wDIOxY8fWWa6IiAi++OILbrvtNjIyMpg2bVq5MaGhoSxdurRco++aSExMZObMmcycObPcMcMwuOOOO5g1axYWi6XSOfLz8/nuu+/47rvvKh3Ttm1bPv/8c/r27XveWUWk4fH1sHA0tfpPnjuWlotPs8p/3oiIiIhI02K1WJk+cDrRydHsSdnD1hNbmbNzDjMiZxDkGeToeNJA2WVL3YQJE2jfvj2maXLrrbfy17/+lfj4+HLj4uPjefzxx/nLX/6CYRiEhIRw991312m20aNHs3PnTh577DFCQ0Px8PDAx8eHPn368MorrxAVFWVrYH4+Bg0axIwZMxg1ahQdOnTAw8MDq9VKaGgo9913Hxs3buSDDz7Azc2t0jlKC1L/93//R69evWjVqhUWiwUPDw/atm3L2LFj+eCDD4iNjdVWOpEmqHsrb7YcPsWp7IJzjj2VXcCmg6fo2cbbDslEREREpKGwWqy4O7vTyacTq+JPt4+ZsmYKWQVZjo4mDZRhmqZpjwtFR0dz2WWXkZWVZdvu1bZtW1q1agXA8ePHiYs73aTMNE2sViurV68mIiLCHvGkGhISEggJCQFOFweDg9VwWMoqLEyloCCRvLwjWCwBODs33SW4+fkJZOa7k5bfnNS8APy93GjmWv0HJ9REVFwqf12wk26tvHhx7AU093CtcFx6biFPL/yNPScyefWGC7morW+d5KnIsbRcrG4u+Hm60baFh92uKyIiIiLVl1WQxYMrHsQwDFLzUokMiWRwyGB6B/V2dDSpQ3X1u75dVjjB6T5OmzdvJiIiAtM0MU2TI0eOsHnzZjZv3syRI0ds7/fu3ZstW7ao2CQiUg0RbX256sJWxBzP5PaPt/LBukP8GpdKQmoOCak5/BqXygfrDnHHR1uJOZ7JFT1b2rXYJCIiIiINg9ViZUbkDExM+rfuz46kHQRbtdBAzo9dejiV6tatG9u3b+enn35iyZIlREVFcfLkSeD0k+wuuugiRo8ezbBhw+wZS0SkwZs0rAseFme+2p7AvC1xzNsSV+a4aYJhwA29g7n3so4OSikiIiIi9V2QZxAzLpvBlDVTCA8M58XNLzJ94HQ1EJcas2vBqdTw4cMZPny4Iy4tItIoOTsZ3B/ZiasvbMWPuxLZdSyD1D96Ovl6WujR2psR3YMI8dN2NhERERGpWnxmPP1a9sPVyZV23u1YdGARYzqNUdFJasQhBScREakbwb4e3DWwg6NjiIiIiEgDFuYXxtzdc2nn3Y4lB5cwuuNopq2bppVOUiN26+FUHQcOHGDz5s0kJiY6OoqIiIiIiIhIk2S1WJk+cDqtPFsxuuNoPF096eLbhdjUWEdHkwbELgWnpKQkZs2axaxZs0hPTy93fP/+/fTu3ZvQ0FAuvfRS2rRpw/XXX09qaqo94omIiIiIiIjIGawWK2M6jeFwxmEKSgrYl7qPrr5dHR1LGhC7FJy++eYbJk6cyMyZM2nevHmZY/n5+YwaNYro6GjbU+pKSkr49ttvueaaa+wRT0RERERERETOUrrSKSIwgqs7Xk1UUhRZBVmOjiUNhF16OC1fvhzDMLj22mvLHfv44485cOAAhmEwZswYhg0bxooVK1i8eDHr16/niy++4Oabb7ZHTBERERERERE5y+cxnxOfGY+JSTuvdrxy2Svq5STnZJcVTrGxp/d5XnLJJeWOff755wAMHTqUb7/9locffpjvvvuOyy+/HNM0mT9/vj0iioiIiIiIiMhZ9pzag4+bDwHNAghoFoCHxYNFBxZppZOck10KTsnJyQAEBweXeT83N5dNmzZhGAb33ntvmWN33nknAL/++qs9IoqIiIiIiIjIWcL8wkjLTyMpN4nEnES2Ht/KiewTTFs3TUUnqZJdttSlpaUB4ORUtr61adMmCgsLcXJy4vLLLy9zrEOH04/1TkpKskdEERERERERETmL1WLl1cteJTo5mn2n9pGan4qrkytWVyvRydEMbDPQ0RGlnrJLwclqtZKens6JEyfKvL9q1SoAunfvjq+vb5ljrq6upwO62CWiiIiIiIiIiFTAarEysM1AwgPCmbpmKnGZcQCk56cTHhCufk5SIbtsqQsLCwNg2bJlZd7/+uuvMQyDyMjIcueUFqeCgoLqPqCIiIiIiIiIVMlqsTIubBy9Anoxst1IwlqEEZsa6+hYUk/ZpeB01VVXYZom7733HrNnz+b333/nr3/9K7t37wbguuuuK3dOae+mNm3a2COiiIiIiIiIiJxDRGAEmQWZFJQUsPX4VoKtwec+SZokuxScJk6cSKtWrSgoKGDixIn06tWLN998E4D+/fszZMiQcucsXrwYwzDo27evPSKKiIiIiIiIyDlYLVaevvhpdiTvIDwwnBc3v6jm4VIhuxScmjdvzooVK7joooswTdP2MWjQIL788sty43fs2MHWrVsBGD58uD0iioiIiIiIiEg1xGfG069lPzxdPWnn3Y5FBxap6CTl2KXgBNCtWze2bdvGgQMHWL9+PQcPHmT16tW0bt26wvEfffQRH374IUOHDrVXRBERERERERE5hzC/MPam7iWrMIslB5dwIvsE09ZNU9FJyrD7I+A6dOhAhw4dqhzTq1cvevXqZadEIiIiIiIiIlJdVouV6QOns+jAIkZ3HI2rkytWVyvRydEMbDPQ0fGknrB7wUlEREREREREGjarxcqYTmOYumYqcZlxAKTnpxMeEI7VYnVwOqkP7LalTkREREREREQaD6vFyriwcfQK6MXIdiPp6NNR/ZzEplZXOL3wwgu2188++2yF75+PM+cSERERERERkfohIjCCBXsX4Ofux5KDSxjdcTTT1k1j+sDpWunUxBmmaZq1NZmTkxOGYQBQXFxc4fvn48y5xHESEhIICQkBID4+nuDgYAcnkvqmsDCVgoJE8vKOYLEE4OzcdP8Dk5+fQGa+O2n5zUnNC8Dfy41mrs6OjuUwx9Jysbq54OfpRtsWHo6OIyIiIiK1KKsgi0UHFnEi+wSerp4UlBRwaetL6R3U29HRpBrq6nf9Wt9SZ5omFdWwSt8/nw8RERERERERqZ9K+zkdzjhMVmEWW49vJdiqBQpNXa0WnEpKSmwflb1/Ph8iIiIiIiIiUn9ZLVaevvhpdiTvoHuL7kxZPYXE7ERHxxIHUtNwEREREREREfnT4jPjCQ8IZ8OxDRiGwZQ1U9RAvAlTwUlERERERERE/rQwvzCik6LxdfclNS+VXgG9iE2NdXQscRAVnERERERERETkT7NarMyInIGJSWRIJAfSDpBTmKNVTk2Uiz0uUlxczNatW1m7di179+4lNTWVzMxMvL298fPzo2vXrgwcOJA+ffrg5KQamIiIiIiIiEhDFOQZxKxhs4hOjuZg2kF2JO9gwd4FTB84Haul6T7Fuimq04JTUVER77zzDq+99hrHjh075/iQkBCmTJnC/fffj7Nz0318uIiIiIiIiEhDZbVYcXd2p1uLbpimidXVSnRyNAPbDHR0NLGjOis4paSkcO2117J+/XoATNM85znx8fE88sgjfPPNNyxYsAA/P7+6iiciIiIiIiIidSTML4wPf/+QuMw4ANLz0wkPCNcqpyakTgpOxcXFXHXVVWzduhXTNDEMgxEjRnD55Zdz0UUX0aJFC6xWK5mZmZw8eZKoqCh++uknfv75Z0zTZNWqVYwZM4Y1a9Zoi52IiIiIiIhIA2O1WBkXNo5lh5fh5+ZHSl6KVjk1MXVScHr55ZfZsmULhmEQERHBp59+Svfu3Ssdf/nllzNlyhR+//13xo8fT3R0NBs3bmTGjBk88cQTdRFRREREREREROpQRGAE8/bMY0fyDkCrnJqaWl8+VFhYyFtvvWUrNq1fv77KYtOZevbsyYYNG4iIiMA0Td58802KiopqO6KIiIiIiIiI1LHSVU69Anoxst1IwlqEEZsa6+hYYie1XnBavHgxycnJGIbBf//7X9zd3Wt0vru7O59++imGYZCcnMySJUtqO6KIiIiIiIiI2EFEYASZBZlgQExKDDmFOWQVZDk6lthBrRec1q1bB5zeJhcWFnZec3Tv3p3hw4cDsHbt2lrLJiIiIiIiIiL2Y7VYmT5wOhGBERgY7EjewbR101R0agJqveC0fft2DMNg2LBhf2qeYcOGYZom27dvr6VkIiIiIiIiImJvVosVd2d3urXohmmaWF2tRCdHOzqW1LFabxoeHx8PwIUXXvin5ik9/8iRI386k4iIiIiIiIg4TphfGB/+/iFxmXGAGog3BbW+wik9PR0AX1/fPzVP6fml84mIiIiIiIhIw3RmA/EhwUNo7tZcq5wauVpf4ZSRkQGA1frnqpSenp4AZGZm/ulMIiIiIiIiIuJYEYERzNszjx3JOwCtcmrsar3gVFxcjGEYtTZfSUlJrc0lIiIiIiIiIo5Ruspp2eFltPRoCQbEpsbSO6i3o6NJHaj1LXUiIiIiIiIiIhWJCIwgsyATDIhJiSGnMEdPrGukan2FU6lZs2YRGBh43ucnJSXVYhoRERERERERcTSrxcr0gdOJTo5mT8oediTvYMHeBUwfOF1b6xqZOis4zZ49u66mFhEREREREZEGymqx4u7sTrcW3TBNE6urlejkaAa2GejoaFKL6qTgZJpmXUwrIiIiIiIiIo1AmF8YH/7+IXGZcYAaiDdGtV5wWrlyZW1PKSIiIiIiIiKNyNkNxAtKClh0YBFjOo1R0amRqPWCU2RkZG1PKSIiIiIiIiKNTERgBAv2LsDP3Y8lB5cwuuNopq2bpn5OjYSeUiciIiIiIiIidlfaQLyVZytGdxyNq5OrrZ+TNHx11jRcRERERERERKQqVouVMZ3GMHXNVPVzamRUcBIRERERERERhzm7nxMGxKbG0juot6OjyZ+gLXUiIiIiIiIi4lARgRFkFmSCAftS99HVt6ujI8mfpBVOIiIiIiIiIuJQpf2cYlNjuaPHHdpO1whohZOIiIiIiIiIOJzVYqWrb1f2nNpDYnYi205sI6sgy9Gx5Dyp4CQiIiIiIiIiDpdVkMW0ddNYk7CGW5bewpqENUxbN01FpwZKBScRERERERERcbg9p/YQ6htKWn4abb3acjL3JFZXK9HJ0Y6OJudBPZxERERERERExOHC/MKYu3su7bzbcTjjMMm5yTgZTqTnpxMeEK6+Tg2MCk4iIiIiIiIi4nBnNg6/0P9CViWsoqVHSzAgNjWW3kG9HR1RakBb6kRERERERESkXrBarPQO6k3/1v3JLMikoKSArce3EmwNdnQ0qSEVnERERERERESkXrFarDx98dPsSN5BeGA4L25+Uc3DGxgVnERERERERESk3onPjKdfy354unrSzrsdiw4sUtGpAVHBSURERERERETqnTC/MPam7iWrMIslB5dwIvsE09ZNU9GpgVDBSURERERERETqndIm4q08WzG642g8XT3p4tuF2NRYR0eTalDBSURERERERETqJavFyphOYziccZiswiw1EG9AVHASERERERERkXpLDcQbJhWcRERERERERKReK20g7urkitXVSnRytKMjyTm4ODqAiIiIiIiIiEhVwvzC+PD3D4nLjAMgPT+d8IBwrBarg5NJZbTCSURERERERETqNavFyriwcfQK6MXIdiPp6NORRQcWaWtdPaaCk4iIiIiIiIjUexGBEWQWZFJQUsCSg0s4kX2CaeumqehUT6ngJCIiIiIiIiL1ntViZfrA6bTybMXojqPVz6meUw8nEREREREREWkQrBYrYzqNYeqaqernVM+p4CQiIiIiIiIiDUZpP6dlh5fR0qMlGBCbGkvvoN6OjiZn0JY64MiRI0yePJmwsDA8PT3x8/Ojb9++zJgxg5ycnFq5xqFDh3jsscfo2bMnXl5eeHp60qVLFx588EF27dpV7XmKiop49913GTRoEAEBATRr1oxOnTpx33331WgeERERERERkYbqzH5OW49vJdga7OhIchbDNE3T0SEcafHixdx2221kZGRUeDw0NJSlS5fSuXPn877Ge++9x8MPP0xBQUGFxy0WC6+//joTJ06scp6TJ09y5ZVXsnXr1gqPu7m58fbbb3P33Xefd9aqJCQkEBISAkB8fDzBwfoXWsoqLEyloCCRvLwjWCwBODs33SWt+fkJZOa7k5bfnNS8APy93Gjm6uzoWA5zLC0Xq5sLfp5utG3h4eg4IiIiItIIJGYnMmXNFMIDwjmccZjpA6drW915qKvf9Zv0CqeoqChuvvlmMjIysFqtvPjii2zYsIGff/6Ze+65B4C9e/dy1VVXkZmZeV7XmD9/Pvfddx8FBQU0b96cF154gXXr1rF161bee+89OnfuTEFBAY888ghffvllpfMUFxdz7bXX2opN1113HT/88AObN2/mrbfeIjAwkPz8fO677z5++OGH88oqIiIiIiIi0lDEZ8bTr2U/PF09aefdjkUHFumJdfVIk17hdNlll7F27VpcXFxYs2YN/fv3L3N8xowZTJ06FYDnnnuO559/vkbz5+Tk0KFDB5KSkrBarWzcuJGePXuWGZORkcHAgQP57bffCAoKYv/+/Vit5SuyH374IXfddRcADz74IO+8806Z4/v376d3795kZGTQuXNnYmJicHGp3RZdWuEk56IVTv+jFU5laYWTiIiIiNS2rIIspq2bRjvvdiw5uITRHUdrpdN50AqnWrZlyxbWrl0LwF133VWu2AQwefJkunXrBsDMmTMpLCys0TW+//57kpKSAJg0aVK5YhOAt7c3b7zxBgCJiYl8/PHHFc712muvAeDn58eMGTPKHe/cuTNPPfUUcLr4tHDhwhplFREREREREWlIrBYr0wdOp5VnK0Z3HI2rkytWVyvRydGOjiY04YLTt99+a3t9xx13VDjGycmJ8ePHA5CWlsbKlStrdI1t27bZXo8aNarScYMHD8bd3R2Ar776qtzxvXv3EhMTA8BNN92Eh0fFqwNuv/1222sVnERERERERKSxs1qsjOk0hv1p+/nxyI/sPLmTeTHztLWuHmiyBad169YB4OnpSe/elT86MTIy0vZ6/fr1NbpGSkqK7XVQUFCl41xcXPDz8wNg48aNFBUVVZj17Dxna9myJaGhoeeVVURERERERKQhslqsjAsbR6+AXoxsN5KwFmHEpsY6OlaT12QLTqUrhjp37lxlr6OwsLBy51TXmb2Y0tPTKx1nmqbtKXkFBQXs37+/zPHdu3dXmKeqvPHx8WRnZ9cor4iIiIiIiEhDFBEYQWZBJhiwL3UfXX27OjpSk1e7XaUbiLy8PE6ePAlwzmZYvr6+eHp6kp2dTXx8fI2uU9r/CWD16tWVrqSKiooiK+t/y/3i4uLKFJYSEhJsr8+Vt7TRl2maJCQk0LVr9f8lO/M6FTl+/Hi15xIRERERERGxl9J+TrGpsdwUehN7Tu0hzC9MzcMdqEkWnDIzM22vK3oi3NlKC05nFoWqY9SoUbi4uFBUVMQbb7zB+PHj8ff3LzOmpKSEp59+utJ8Nc3r6elpe13TvKXFKhEREREREZGGxmqx0tW3K9PWTaO9d3ve+vUtZkTOIMiz8hY3Unea5Ja6vLw822uLxXLO8W5ubgDk5ubW6DohISHcf//9ABw9epQBAwbw3XffkZGRQV5eHps2beLKK69k2bJlZXKcfZ2a5C3Nej55RURERERERBqyPaf20N67PaviV2EYBlPWTFEDcQdpkiucSp8IB6d7Jp1Lfn4+AM2aNavxtV577TUOHjzI999/z969exk7dmy5MX369KFv377Mnj0bAC8vryrznvl5ZVnPJ++5tgweP36cfv361WhOEREREREREXsJ8wvjrV/fwtfdl9S8VCJDIolNjaV3UOUPC5O60SRXOJ1Z0KnOtrPS5tvV2X53Njc3NxYvXsycOXMIDw/HMAzbscDAQJ5++mnWrl2LaZq29319fc8775mNwmuaNzg4uMqPVq1a1Wg+EREREREREXuyWqzMiJyBiUn/1v3ZkbQDXzdftp3YppVOdtYkC07u7u60aNECOHej7NTUVFsR53x7HDk5OXH33XcTFRVFeno6+/bt4+jRoxw/fpx//vOfuLu7s2/fPtv47t27lzn/zEbh58pbukrJMIxzNhgXERERERERaWyCPIOYcdkMYk7F0L1Fd+5afhdrEtYwbd00FZ3sqEkWnOB/RZ39+/dTVFRU6bg9e/bYXp/51Lnz5eXlRefOnWndujVOTqf/8RcXFxMdHQ1Ax44dyzUWP7MAdWaeqvKGhISUaSAuIiIiIiIi0lTEZ8bTr2U/copyaOvVlvSCdLr4diE2NdbR0ZqMJltwGjhwIHB6C9r27dsrHbd69Wrb6wEDBtRJlpUrV5KSkgLAzTffXO54adaz85ztxIkT7N27F6i7rCIiIiIiIiL1XZhfGHtT99LcrTlxmXF4W7zZl7qPrr5dHR2tyWiyBaczm3d/9NFHFY4pKSlh7ty5APj4+DBkyJBaz2GaJs8//zwArq6u3HPPPeXGhIaG2lZXffnll+Tk5FQ418cff2x7fe2119Z6VhEREREREZGGwGqxMn3gdAaHDGb+VfMZHDKY6QOnY7XUvDeznJ8mW3Dq168fgwYNAuCDDz5g48aN5ca8/vrrxMTEADBp0iRcXV3LHF+16vRjFg3D4Pbbb6/wOikpKWWeHHem4uJiJk6cyPr16wF46qmn6NChQ4Vj//rXvwJw6tQppk6dWu74gQMHeOmllwDo3LmzCk4iIiIiIiLSpFktVnoH9SbIM4iuvl3Zc2qPejjZkYujAzjSzJkzGTBgALm5uYwYMYJp06YxZMgQcnNzmT9/Pu+99x5weoXR5MmTz+saK1euZOLEidxyyy1ERkbStm1b8vLy2LlzJ++9956td9OoUaN4+umnK51nwoQJfPjhh6xfv5533nmHEydOcM899+Dr68uWLVv4xz/+QUZGBk5OTrz11lu4uDTpb62IiIiIiIgIAFkFWUxbN41Q31Dm7p6rlU520qSrEhEREXzxxRfcdtttZGRkMG3atHJjQkNDWbp0KV5eXud9ncTERGbOnMnMmTPLHTMMgzvuuINZs2ZhsVgqncPZ2Zlvv/2WK6+8kq1bt/L111/z9ddflxnj5ubG22+/zahRo847q4iIiIiIiEhjsufUHkJ9QzFNE6urlejkaAa2GXjuE+VPadIFJ4DRo0ezc+dOZs6cydKlS0lISMBisdC5c2duvPFGJk6ciIeHx3nPP2jQIGbMmMEvv/zCnj17SExMxMnJidatWzNkyBDuuOMOLr744mrN5e/vz4YNG5gzZw6ff/45MTExZGdn07p1a4YNG8akSZPo0aPHeWcVERERERERaWzC/ML48PcPicuMAyA9P53wgHCtcqpjhmmapqNDSMOQkJBASEgIAPHx8QQHBzs4kdQ3hYWpFBQkkpd3BIslAGfnpvsDPD8/gcx8d9Lym5OaF4C/lxvNXJ0dHcthjqXlYnVzwc/TjbYtzr+ILyIiIiJyPtYmrGXZ4WW09GgJBlza+lJ6B/V2dKx6oa5+12+yTcNFREREREREpGmICIwgsyATDIhJiSGnMEcNxOuYCk4iIiIiIiIi0qhZLVamD5xORGAEBgY7kncwbd00FZ3qkApOIiIiIiIiItLoWS1W3J3d6daiW5kG4lI3mnzTcBERERERERFpGtRA3H5UcBIRERERERGRJsFqsTIubFyZBuKxqbFqIF4HtKVORERERERERJqMMxuI70vdR1ffro6O1ChphZOIiIiIiIiINBmlDcRjU2O5o8cd2k5XR1RwEhEREREREZEmxWqxahtdHdOWOhERERERERERqVUqOImIiIiIiIiISK1SwUlERERERERERGqVCk4iIiIiIiIiIlKrVHASEREREREREZFapYKTiIiIiIiIiIjUKhWcRERERERERESkVqngJCIiIiIiIiIitUoFJxERERERERERqVUqOImIiIiIiIiISK1SwUlERERERERERGqVCk4iIiIiIiIiIlKrVHASEREREREREZFapYKTiIiIiIiIiIjUKhWcRERERERERESkVqngJCIiIiIiIiIitUoFJxERERERERERqVUqOImIiIiIiIiISK1SwUlERERERERERGqVCk4iIiIiIiIiIlKrVHASEREREREREZFapYKTiIiIiIiIiIjUKhWcRERERERERESkVqngJCIiIiIiIiIitUoFJxERERERERERqVUqOImIiIiIiIiISK1SwUlERERERERERGqVCk4iIiIiIiIiIlKrVHASEREREREREZFapYKTiIiIiIiIiIjUKhWcRERERERERESkVqngJCIiIiIiIiIitUoFJxERERERERERqVUqOImIiIiIiIiISK1SwUlERERERERERGqVCk4iIiIiIiIiIlKrVHASEREREREREZFapYKTiIiIiIiIiIjUKhWcRERERERERESkVqngJCIiIiIiIiIitUoFJxERERERERERqVUqOImIiIiIiIiISK1SwUlERERERERERGqVCk4iIiIiIiIiIlKrVHASEREREREREZFapYKTiIiIiIiIiIjUKhWcRERERERERESkVqngJCIiIiIiIiIitUoFJxERERERERERqVUqOImIiIiIiIiISK1SwUlERERERERERGqVCk4iIiIiIiIiIlKrVHASEREREREREZFapYKTiIiIiIiIiIjUKhWcRERERERERESkVqngJCIiIiIiIiIitUoFJxERERERERERqVUqOImIiIiIiIiISK1SwUlERERERERERGqVCk4iIiIiIiIiIlKrVHASEREREREREZFapYITcOTIESZPnkxYWBienp74+fnRt29fZsyYQU5OTq1c4/DhwzzxxBP07t0bHx8fXF1d8fPz49JLL+WFF14gKSmpyvMHDx6MYRjV+hARERERERERcSQXRwdwtMWLF3PbbbeRkZFhey8nJ4dt27axbds23n//fZYuXUrnzp3P+xqffvop9913H7m5uWXeT01NZePGjWzcuJGZM2cyf/58hg8fft7XERERERERERGpD5p0wSkqKoqbb76Z3NxcrFYrTz31FEOGDCE3N5f58+czZ84c9u7dy1VXXcW2bdvw8vKq8TXWr1/P7bffTklJCU5OTkyYMIFrrrmG1q1bExcXxyeffMLixYs5deoU11xzDb///jsdO3asdL4+ffrw0Ucf/ZkvW0RERERERESkTjXpgtOkSZPIzc3FxcWF5cuX079/f9uxoUOH0qVLF6ZOncrevXt5/fXXef7552t8jZdeeomSkhIA/v3vf/Pggw/ajvXt25frr7+eyZMn88Ybb5Cbm8sbb7zB22+/Xel8np6e9OzZs8Y5RERERERERETspcn2cNqyZQtr164F4K677ipTbCo1efJkunXrBsDMmTMpLCys8XU2bNgAQIsWLcoUm8707LPP2l5v3LixxtcQEREREREREalPmmzB6dtvv7W9vuOOOyoc4+TkxPjx4wFIS0tj5cqVNb5OQUEBAB06dKh0TPPmzfH39y8zXkRERERERESkoWqyBad169YBp7eo9e7du9JxkZGRttfr16+v8XW6du0KwKFDhyodk5GRwcmTJ8uMFxERERERERFpqJpswSkmJgaAzp074+JSeSursLCwcufUxP333w9ASkoK7777boVj/vGPf5QbX5k9e/Zw8cUX4+Pjg7u7O8HBwVxzzTXMnTv3vLb8iYiIiIiIiIjUtibZNDwvL8+2oig4OLjKsb6+vnh6epKdnU18fHyNr3XnnXeybt065s6dy0MPPcT27dsZM2YMrVq1Ii4ujk8//dS2ve/pp5/m8ssvr3K+xMREEhMTbZ8fPXqUo0ePsmjRIl555RW++uorW9+pmkpISKjy+Jlf//Hjx8/rGtK4FRamUVh4kvz8ZFxdS3B2znJ0JIfJz08mu8CNjIJc0vILKcq04O7q7OhYDpOUkUe2xZl8Dzeccps5Oo6IiIiIiPzhzN/vi4qKam1ewzRNs9ZmayCSk5MJDAwE4Oabb2b+/PlVjg8KCiIpKYmePXvy22+/ndc1v/rqK6ZPn05UVFS5Y0OGDGHatGlVFpuGDh2Kk5MTV155Jb169aJFixZkZmby66+/8p///Me2+iooKIgtW7bQtm3bGmc0DKPG54iIiIiIiIhI47Blyxb69u1bK3M12RVOpSwWyznHu7m5AZCbm3te14uJiWHu3LmVFqs2btzIBx98QLdu3WjTpk2FY7755ht8fHzKvT9o0CAefPBB7rnnHj755BMSExN59NFH+eabb84rq4iIiIiIiIjIn9UkC07u7u6219V5Klx+fj4AzZrVfBvI2rVrGT16NOnp6bRr145//vOfDB8+HD8/PxITE1m0aBF/+9vfmD9/PmvWrGH58uX06NGj3DwVFZtKubq68v7777Np0yZiY2NZuHAhR48erbR4VZlzbRk8dOgQl112GQAbNmwgJCSkRvNL43b8+HH69esHnK6Kt2rVysGJpL7QvSFV0f0hVdH9IVXR/SFV0f0hVdH9UVZRURHJyckAXHDBBbU2b5MsOHl5edleZ2Wdu8dMdnY2AFartUbXyc/PZ9y4caSnp9OyZUs2bdpEy5YtbceDg4N58MEHiYyMpE+fPhw7dowJEyawbdu2Gl0HwMXFhbvuuoupU6cCsHr1am699dYazXGuflZnCgkJqdF4aVpatWql+0MqpHtDqqL7Q6qi+0OqovtDqqL7Q6qi++O09u3b1/qcTfIpde7u7rRo0QI4d6Ps1NRUW8Gppit6li1bxtGjRwF4+OGHyxSbztSjRw9uu+02ALZv386OHTtqdJ1S3bt3t70uva6IiIiIiIiIiL01yYIT/K84s3///iq7sO/Zs8f2uqZPfytt5A1w0UUXVTm2d+/eFV6zJtT0W0RERERERETqgyZbcBo4cCBwervc9u3bKx23evVq2+sBAwbU6BouLv/bsXiuRwsWFhZWeF5N7N692/a6devW5zWHiIiIiIiIiMif1WQLTmPHjrW9/uijjyocU1JSwty5c4HTTbuHDBlSo2t06NDB9nrt2rVVjj2zsHXmedVVVFTEhx9+aPu8tLm3iIiIiIiIiIi9NdmCU79+/Rg0aBAAH3zwARs3biw35vXXX7dti5s0aRKurq5ljq9atQrDMDAMg9tvv73c+cOGDcPDwwOA2bNn89tvv1WY5YcffmDhwoUAtGnThvDw8DLHV65cSVpaWqVfS2FhIXfffbct6+jRo/UEORERERERERFxmCb5lLpSM2fOZMCAAeTm5jJixAimTZvGkCFDyM3NZf78+bz33nsAhIaGMnny5BrP7+Pjw5NPPsmzzz5LZmYml156KQ8//DDDhw/H19eXxMREvvvuO+bMmUNJSQkAL7/8Mk5OZeuAn3zyCWPGjGHMmDEMHjyYrl274u3tTVZWFtu3b+e9996zbacLDAxk5syZf/KfjIiIiIiIiIjI+WvSBaeIiAi++OILbrvtNjIyMpg2bVq5MaGhoSxduhQvL6/zusYzzzzDqVOnmDlzJllZWbz00ku89NJL5ca5uroyffp029PqzpaVlcXnn3/O559/Xum1LrjgAubPn39eW/JERERERERERGqLYZqm6egQjnbkyBFmzpzJ0qVLSUhIwGKx0LlzZ2688UYmTpxo2xZ3tlWrVtn6Ok2YMIGPP/640mts376d999/n3Xr1nHkyBFycnKwWq107tyZyMhI7rvvPkJDQys8NyYmhh9//JGNGzeye/dukpOTOXXqFG5ubgQFBdGnTx9uuOEGrr32Wpydnf/0Pw8RERERERERkT9DBScREREREREREalVTbZpuIiIiIiIiIiI1A0VnEREREREREREpFap4CQiIiIiIiIiIrVKBScREREREREREalVKjiJiIiIiIiIiEitUsFJRERERERERERqlQpOIiIiIiIiIiJSq1RwEhERERERERGRWqWCk4iIiIiIiIiI1CoVnKRajhw5wuTJkwkLC8PT0xM/Pz/69u3LjBkzyMnJcXQ8qYGkpCSWLFnCs88+y6hRo/D398cwDAzD4Pbbb6/xfD/88APXXnstwcHBuLm5ERwczLXXXssPP/xQ7TmKiop49913GTRoEAEBATRr1oxOnTpx3333sWvXrhpnkvO3bds2XnjhBUaMGGH7nlqtVkJDQ7njjjtYt25djebT/dF4ZGRkMH/+fCZPnkxkZCSdO3emefPmWCwWAgMDGTx4MK+++iopKSnVmm/Dhg3cdttttGvXDnd3d1q2bMnIkSOZN29ejXLNmzePESNG0LJlS9zd3WnXrh233XYbGzduPJ8vU+rAE088YfvvjGEYrFq16pzn6GdH43PmPVDVx+DBg885l+6Pxi0uLo7nnnuOPn36EBAQgLu7OyEhIQwaNIhnn32W33//vcrzdX80LoMHD672z4/q/HdG94edmSLnsGjRItPb29sEKvwIDQ019+3b5+iYUk2VfR8Bc8KECdWep7i42LzrrruqnO/uu+82i4uLq5wnOTnZ7Nu3b6VzuLm5mXPmzPmTX7VUx6BBg6r8fpZ+jB8/3szPz69yLt0fjc9PP/1UrfvD39/fXLZsWZVzPffcc6aTk1Olc1x11VVmbm5ulXPk5OSYV155ZaVzODk5mc8//3xt/iOQ8xAVFWW6uLiU+d6sXLmy0vH62dF4VefnB2BGRkZWOofuj8bvrbfeMj09Pav8Hk+aNKnCc3V/NE6RkZHV/vlR+t//hISEcvPo/nAMFZykSr/++qvZrFkzEzCtVqv54osvmhs2bDB//vln85577rH9ixUaGmpmZGQ4Oq5Uw5k/ENu2bWuOGDHC9nlNCk5PPvmk7byIiAhz3rx55pYtW8x58+aZERERtmNPPfVUpXMUFRWZAwcOtI297rrrzB9++MHcvHmz+dZbb5mBgYG2/3B8//33tfDVS1U6depkAmbr1q3NSZMmmV999ZW5ZcsWc+PGjeYbb7xhtmnTxva9GjduXJVz6f5ofH766SczJCTEHD9+vDlz5kzzm2++MTdu3GiuX7/e/OKLL8wbb7zRdHZ2NgHTYrGY0dHRFc7z7rvv2r6nnTp1Mj/44ANzy5Yt5rfffmsOGTKk2vfYLbfcYhs7ZMgQ89tvvzW3bNlifvDBB7Z7GTD/85//1MU/DqmG4uJi2/+Ul/77eq6Ck352NF6l348HHnjA/O233yr9OHjwYKVz6P5o3P7xj3+U+d1ixowZ5qpVq8yoqChzxYoV5owZM8xLL73UfOyxxyo8X/dH43Tw4MEqf2b89ttv5hdffGH7ng0fPrzCeXR/OIYKTlKl0hUPLi4u5oYNG8odf/XVV23/wj333HP2Dyg19uyzz5qLFy82T5w4YZqmaR46dKjGBafY2FjbX6z79Olj5uTklDmenZ1t9unTx3bvVLYC7oMPPrBd+8EHHyx3fN++fbbVdZ07dzYLCwtr9sVKjVx11VXmF198YRYVFVV4PDk52QwNDbV9z1avXl3hON0fjVNl98WZFi5caPueXXvtteWOp6SkmM2bN7cVvJOTk8tdY/To0ecsTPz888+2MaNHjy6XLTk52Wzbtq0JmD4+PuapU6eq/4VKrXnzzTdNwAwLCzOfeuqpc35f9bOjcfuz/7+o+6NxW7Fihe37Mn78eLOgoKDSsRWtstb90bRNnTrV9n379NNPyx3X/eE4KjhJpTZv3mz7F+q+++6rcExxcbHZrVs32//UV/UfB6mfzqfg9MADD9jO2bhxY4VjNm7cWOUPZNM0bfeOn5+fmZ2dXeGYl156yTbPl19+Wa18UncWL15s+348/PDDFY7R/dG0de3a1YTTW+vO9sorr9i+X/Pmzavw/Pj4eNtKqSuvvLLCMaNGjbL9T2F8fHyFY+bNm2e71quvvnr+X5CclyNHjphWq9UEzFWrVpnPPffcOQtO+tnRuP3ZgpPuj8aruLjY7NKliwmYvXr1Oq9f0nV/NF3FxcW2VfhWq7XC75vuD8dRwUkqdeZfIzdt2lTpuDP/pfrxxx/tmFBqQ00LTiUlJWbr1q1tf7WuSukvnm3atDFLSkrKHIuNjbVd9/777690juPHj9vGnWuLjdS9rKws2/ejomKA7g8p/Quh1Wotd6x///4mYHp7e1fZB2zkyJEmnO6DcPZ27YyMDNNisZiAecUVV1Q6R35+vu2vjP379z//L0jOy9VXX13mvyvnKjjpZ0fj92cKTro/GrcffvjB9s/7888/r/H5uj+atuXLl9u+H7fffnu547o/HEtPqZNKlT6NytPTk969e1c6LjIy0vZ6/fr1dZ5LHOvQoUMcO3YMKPu9r0jp8aNHj3L48OEyx8582llV87Rs2ZLQ0FBA91d9kJ+fb3vt7Oxc7rjuj6YtNjaW6OhoAMLCwsocKygoYMuWLQD0798fi8VS6Tyl3/P8/Hy2bdtW5tjWrVspKCgoM64iFouFSy65xHZOYWFhzb4YOW9ffvklS5Yswc/Pj9dee61a5+hnh1RF90fjtmDBAuD0kwyvvvpq2/unTp1i3759nDp1qsrzdX80bXPnzrW9Hj9+fLnjuj8cSwUnqVRMTAwAnTt3xsXFpdJxZ/5SUXqONF67d++2vT77F8qzVXVvnM888fHxZGdnVzur1L7Vq1fbXnfr1q3ccd0fTU9OTg779u3jjTfeIDIykqKiIgAeffTRMuP27t1LcXExYP97o6ioiH379lX9hUitSEtLY9KkSQC88sor+Pv7V+s8/exoOhYsWED37t3x8PDAy8uLLl26MGHCBFauXFnpObo/GrdNmzYB0L59e7y8vPj888+54IILaNGiBaGhobRo0YKuXbvy2muvlfnDVyndH01XVlYWCxcuBKBdu3YMHjy43BjdH46lgpNUKC8vj5MnTwIQHBxc5VhfX188PT2B0/9SSeOWkJBge32ueyMkJMT2+ux743zmMU2zzHliXyUlJbz88su2z2+66aZyY3R/NA0ff/wxhmFgGAaenp6EhoYyefJkEhMTAXjyySe59dZby5zjyHujonmkbkydOpUTJ04wYMAA7rrrrmqfp58dTcfu3buJiYkhNzeXrKws9u/fz9y5cxk6dCjXXnst6enp5c7R/dF4lZSUsGfPHgD8/f2ZNGkSf/nLX/j999/LjNu7dy9Tpkxh6NChpKWllTmm+6Pp+vrrr20Fndtuuw3DMMqN0f3hWCo4SYUyMzNtr61W6znHlxacsrKy6iyT1A81uTdK7wsof2/U1jxiP2+++aZtS9R1111X4VZb3R9NW3h4OFu2bOGll14q9z99ujcav7Vr1/L+++/j4uLCu+++W+H/+FdG90fj5+HhwS233MKcOXNYu3YtUVFRLF++nKeffpoWLVoA8O2333LNNdeU2wKr+6PxSk9Pp6SkBIDffvuNt956i1atWvHf//6XU6dOkZOTw+rVq21bpDds2MCdd95ZZg7dH03XubbTge4PR6t8n5Q0aXl5ebbXVfXZKOXm5gZAbm5unWWS+qEm90bpfQHl743amkfsY/Xq1Tz55JMABAYGMnv27ArH6f5oGsaOHUufPn2A0//MDxw4wJdffsnChQsZN24c//rXv8r04QDdG41dQUEB9957L6Zp8thjj9GzZ88ana/7o/E7evQoPj4+5d4fPnw4Dz/8MKNGjSIqKorVq1cze/ZsHnnkEdsY3R+N15nbjfLy8vDw8GDlypV07drV9v5ll13GL7/8Qv/+/dmxYwcLFy5k8+bNXHzxxbbzSun+aDoSEhJYtWoVAJdccomtb9LZdH84llY4SYXc3d1tr0ubs1aldD91s2bN6iyT1A81uTfO3Gd/9r1RW/NI3du1axfXXnstRUVFuLu7s2DBAgIDAyscq/ujafDx8aFnz5707NmTvn37csstt/DNN98wd+5cDh48yDXXXMPHH39c5hzdG43b9OnT2bNnD23btuW5556r8fm6Pxq/iopNpYKCgvjqq69wdXUF4N///neZ47o/Gq8zvycAd999d5liU6lmzZrx4osv2j7/4osvKpxD90fT8d///te2Om7ChAmVjtP94VgqOEmFvLy8bK+rswyw9K8T1dl+Jw1bTe6NM/9qdfa9UVvzSN06dOgQI0aMIDU1FWdnZ+bPn89ll11W6XjdH03b//3f/3HjjTdSUlLCxIkTyzxZSPdG47Vnzx5eeukl4HSh4MytBNWl+0M6duzI8OHDAdi/f7/tqVKg+6MxO/N7AjBixIhKxw4bNsz2IKOtW7dWOIfuj6bj00//v717D4ryPPs4/ltAQPGAaLHRECSaLUqMIWpGg+dqEkRFJYnRxhjjoXWwdWzS1I6tNnWaVm20HdPUTlvAvkZRjKeEhIgFlUZMUWKstWIcIR4QI2ADlVQ53O8fvvu8i7AcZGUt+X5mduZh7wP38lwsy7X3c+3/SLq5m2j69Oku+xEfnkXCCfXy9/e3rqdvrNDZ1atXrV8q50JraJuci+Q1FhvOxfZujY3bmcdmszVapA/uU1hYqHHjxqmwsFA2m00JCQmKjY1tcAzxAUeMXLt2TWlpadb9noyN+uaB+6xbt043btzQ/fffr4qKCiUnJ9e5ORcAzsjIsO53vH7guQOS1L9/f+v44sWL1jHx0Xb5+fnpa1/7mvV1Q8/V/v7+1idfXrlyxbqf+PjqOXLkiPWpcRMnTlTXrl1d9iU+PIsaTnCpf//+ysrK0pkzZ1RVVWW9o3ArxydLSPV/TDraFucXg87nvj4Nxcat8zz88MONzhMSEnJb75yj+YqLizV+/HidPXtW0s1dC66KMTojPuD8j8Nnn31mHdvtdnl7e6u6utqtsdGUeXx8fPTAAw80vnjcFselA2fPntWMGTMa7b9y5UrrOD8/XwEBATx3QJJcFponPtq2iIgIqxZPdXV1g30d7c7/lxAfXz3OxcIbupxOIj48jR1OcGn48OGSbr5LffToUZf9Dhw4YB1HRUXd8XXBs8LCwtSzZ09Jtc99fQ4ePChJ6tWrl3r37l2rzRFfjc1TVFSk06dPSyK+WssXX3yhJ554wnrn6Je//KXi4+ObNJb4gPOuBOdt5L6+vnr00UclSdnZ2Q3WP3Cccz8/P6s4ucOQIUOsYp0NxcaNGzd0+PBha4yjNgzuTjx3QJL1d0eSFQ8S8dHWOV+q73ijqz5lZWUqLi6WdPP8OhAfXy2VlZVKTk6WdPNNrujo6Ab7Ex+eRcIJLk2ZMsU6TkxMrLdPTU2NlWEODAzUmDFjWmNp8CCbzWZdMnPq1CnrH7pbHT582Mrux8bG1nnX0m63W+8cbNu2TRUVFfXO41x4eOrUqS1dPhpRUVGhmJgY5ebmSpKWLVumH/7wh00eT3wgJSXFOh4wYECtNsfflbKyMu3YsaPe8RcuXNC+ffsk3azXcWt9j06dOumb3/ymJGnfvn0ut7Xv2LFDZWVlkoiNOy0pKUnGmAZvzoXEMzMzrfsdL+h57kB+fr7S09MlSX369KmVUCA+2ra4uDjreOfOnS777dy5U8YYSdKIESOs+4mPr5b333/fuqRy5syZLq/CcSA+PMwADRgxYoSRZHx8fMyhQ4fqtK9evdpIMpLMihUrWn+BaLH8/HzrHM6ePbtJY/Ly8oy3t7eRZAYPHmwqKipqtVdUVJjBgwdbsXP69Ol65/nTn/5kfe/4+Pg67WfOnDGdO3c2kkzfvn1NZWVlsx8fmu769evm8ccft87J4sWLb2se4qNtSkxMNF9++WWDfdauXWuds7CwMFNVVVWrvaSkxHTp0sVIMqGhoaa4uLhWe1VVlZk0aZI1R2ZmZr3f5y9/+YvVZ/LkyXW+z5UrV8x9991nJJnAwEBTWlra/AcMt1qxYkWj55XnjrZrz549Df6ci4qKTGRkpHXeXn/99Tp9iI+2LTo62kgyXl5eZt++fXXaL126ZO69914jyfj6+poLFy7Uaic+vjri4uKsc3T06NEmjSE+PIeEExqUm5tr2rdvbySZjh07mtdee81kZ2ebjIwMs2DBAusXzm63m7KyMk8vF02QlZVlEhMTrduaNWus8xgVFVWrLTEx0eU8S5cutcZFRkaa5ORkk5OTY5KTk2u9aPzRj37kco6qqioTFRVl9Y2LizNpaWnmo48+MuvXrzfBwcHWi4/33nvvDvw04GzatGnWuRg7dqw5fvy4+fvf/+7ylpeX53Iu4qPtCQ0NNUFBQWb+/Plm48aN5q9//as5duyYycrKMm+++Watc+Xr62vS09PrnWfDhg1Wvz59+piEhASTk5Njdu/ebcaMGWO1zZgxo8H1PPvss1bfMWPGmN27d5ucnByTkJBg+vTpY7X9/ve/vxM/DjRTUxJOFnzW7gAADtxJREFUxvDc0VaFhoaanj17mu9+97tm8+bN5tChQ+bjjz826enpZtmyZaZ79+7W+Ro+fLj5z3/+U+88xEfblZeXZwIDA40k4+/vb5YuXWoOHjxocnJyzG9/+1sr2STJrFq1qt45iI+2r7S01Pj5+RlJ5sEHH2zWWOLDM0g4oVF79uyxMrX13ex2u/n00089vUw00ezZs12ey/purlRXV5sXX3yxwbFz58411dXVDa7nypUrZsiQIS7n8PPzM3/4wx/c/WNAPZoTF9LNHSquEB9tT2hoaJPi4t577zV79+5tcK7ly5cbm83mco4JEyY0upuqoqLCTJgwweUcXl5e7Ly9izQ14cRzR9vU1OePuLg4c/XqVZfzEB9tW1ZWlunRo4fL82Kz2cyPf/xjl+OJj7bvd7/7nXUeVq9e3ayxxIdnkHBCkxQUFJglS5YYu91uOnToYAIDA83gwYPNqlWrzLVr1zy9PDSDuxJODqmpqSY2Ntb07NnT+Pr6mp49e5rY2NhmZfUrKyvNm2++aYYPH266detm/P39zf3332/mz59vTpw40ZKHi2ZwZ8LJgfhoO06dOmVef/11M23aNPPQQw+ZHj16GB8fH9OpUyfTp08fExcXZxITE5v8N+HDDz80M2fONCEhIcbX19cEBweb8ePHm82bNzdrXW+99ZYZP368CQ4ONr6+viYkJMTMnDmz3svA4TlNTTg58NzRtuzfv9+8+uqr5sknnzR2u90EBQUZHx8fExgYaAYMGGC+/e1vN+t3lvhou4qLi82KFSvMwIEDTefOnY2/v78JCwszc+bMMbm5uU2ag/houx577DEjyXh7e5uLFy/e1hzER+uyGfN/ldcAAAAAAAAAN+BT6gAAAAAAAOBWJJwAAAAAAADgViScAAAAAAAA4FYknAAAAAAAAOBWJJwAAAAAAADgViScAAAAAAAA4FYknAAAAAAAAOBWJJwAAAAAAADgViScAAAAAAAA4FYknAAAAAAAAOBWJJwAAAAAAADgViScAAAAAAAA4FYknAAAAAAAAOBWJJwAAAAAAADgViScAAAAAAAA4FYknAAAAAAAAOBWJJwAAABwW5KSkmSz2WSz2VRQUODp5QAAgLsICScAAAAPu3HjhrZs2aLnn39e4eHh6tatm9q1a6fu3btr0KBBWrhwofbt26eamhpPLxUAAKBJfDy9AAAAgK+yHTt26KWXXqp3h1BJSYlKSkqUm5urDRs2yG63a+3atYqJiWn9hQIAADQDCScAAAAPWblypZYvX259PX78eE2ePFn9+/dXYGCgSktLlZeXp3feeUfp6ek6ffq0li1bRsIJAADc9Ug4AQAAeEBiYqKVbAoODta2bds0atSoOv3GjRun+Ph4nThxQkuWLNGVK1dae6kAAADNRsIJAACglV28eFGLFi2SJAUEBOjAgQMKDw9vcMyDDz6oDz74QJs3b26NJQIAALQIRcMBAABa2bp161RRUSFJ+tnPftZossnBy8tLzz33nCTp+9//vmw2m7y9vXXx4sVGxw4aNEg2m039+/evt72mpkZbtmxRXFyc7rvvPrVv317t27eX3W7Xt771LW3fvl2VlZVNfIS1VVdXa+PGjZo4caJ69uwpPz8/devWTcOHD9fatWv15ZdfNjj+6NGjmjt3rux2uwICAuTv76+QkBANGjRI8fHx2rNnj4wxt7U2AABwZ9gMf50BAABajTFGwcHBKi4uVkBAgC5duqROnTo1e56TJ08qIiJCkvSLX/xCS5cuddn3+PHjGjhwoCRpzZo1evnll2u1FxQUaOrUqTp27FiD3zMzM1OjR4+2vk5KStKcOXMkSfn5+erdu3edMefOndPkyZP1ySefuJy3b9++Sk1Nld1ur9O2bt06vfzyy41+Ql95ebk6duzYYB8AANB6uKQOAACgFf3jH/9QcXGxJGnEiBG3lWySpP79+2vYsGHKzs5WUlJSgwmnxMRESZKPj49mzZpVq+3y5cuKiopSYWGhJGns2LGaPXu2wsPDZbPZlJ+fr4yMDKWkpDR7jSUlJRo+fLjOnz8vPz8/zZ8/X6NGjVLv3r3173//W3v37tVvfvMbnTlzRtHR0crNzVWXLl2s8cePH7eSTWFhYVq0aJEefvhhBQUFqby8XHl5ecrMzNTu3bubvTYAAHBnkXACAABoRc47fQYNGtSiuebNm6fs7Gzl5eXp0KFDeuyxx+r0qays1KZNmyRJMTEx6tGjR632hQsXWsmmVatW6ZVXXqnVPmTIED3zzDP61a9+1exL6r73ve/p/PnzCg0NVWZmpsLCwmq1jx49Wk8//bRGjBihs2fPavXq1fr5z39utW/fvl01NTUKCAhQdnZ2nbWPGDFC8+bN0xdffKEOHTo0a20AAODOooYTAABAKyopKbGOg4ODWzTX9OnTrR1Sjl1Mt3rnnXe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+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "def linear_fit(new_x_point, slope, point_xy):\n",
+    "    return slope*(new_x_point-point_xy[0]) + point_xy[1]\n",
+    "\n",
+    "def eval_dc_reconstruction(predicted_dc, ground_truth_dc):\n",
+    "    from scipy.interpolate import interp1d\n",
+    "    f = interp1d(ground_truth_dc[:,0], ground_truth_dc[:,1], kind='cubic')\n",
+    "    interpolated_dc_ground_truth = f(predicted_dc[:,0])\n",
+    "    return np.sqrt(((interpolated_dc_ground_truth - predicted_dc[:,1]) ** 2).mean())\n",
+    "\n",
+    "\n",
+    "# testing on data\n",
+    "# tested_cell = [test_cells[3]]\n",
+    "# # X_train_tested_cell = [x for xs in train_cells for x in xs[0]]\n",
+    "# # Y_train = np.array([x for xs in train_cells for x in xs[1]])\n",
+    "# # Y_train_tested_cell = [x for xs in train_cells for x in xs[1]]\n",
+    "# X_tested_cell = [x for cycle in tested_cell for x in cycle[0]]\n",
+    "# # Y_test = [x for xs in test_cells for x in xs[1]]\n",
+    "# Y_tested_cell = [y for cycle in tested_cell for y in cycle[1]]\n",
+    "# dc_tested_cell, slopes_tested_cell = make_label_arrays(Y_tested_cell)\n",
+    "# X_tested_cell_time_series, X_tested_cell_dt = make_feature_arrays(X_tested_cell)\n",
+    "\n",
+    "# # scaled_X_tested_cell_dt = standardize_non_train(X_tested_cell_dt, mean_X_train_dt, std_X_train_dt)\n",
+    "# # scaled_X_tested_cell_time_series = standardize_non_train(X_tested_cell_time_series, mean_X_train_time_series, std_X_train_time_series)[...,1:]\n",
+    "\n",
+    "# # std_X_tested_cell_time_series = standardize(X_tested_cell_time_series[...,1:])\n",
+    "# all_test_slopes = [y[0] for y in Y_tested_cell]\n",
+    "# all_test_dc = np.array([y[1] for y in Y_tested_cell])\n",
+    "# # Y_hat_tested_cell = model.predict([scaled_X_tested_cell_time_series, scaled_X_tested_cell_dt])\n",
+    "# Y_hat_tested_cell = model.predict(X_tested_cell_time_series[...,1:])\n",
+    "\n",
+    "# initial_dc = all_test_dc.reshape([-1, 2])[cycle_indices[0]]\n",
+    "# index_0 = initial_dc[0]\n",
+    "# for i,m in enumerate(all_test_dc.reshape([-1,2])):\n",
+    "#     plt.scatter(*list(zip(*all_test_dc.reshape([-1,2]))), color = 'C2', s=2, label='Ground-truth' if i == 0 else \"\")\n",
+    "\n",
+    "# window_size = 100\n",
+    "all_predicted_dc_values = []\n",
+    "max_cycle_index = all_test_dc.reshape([-1,2])[-1,0]\n",
+    "for i,m in enumerate(all_test_dc):\n",
+    "    plt.figure(dpi=200, facecolor='white')\n",
+    "#     print(m[0,0], m[5,0], m[9,0])\n",
+    "    plt.scatter(*list(zip(*all_test_dc.reshape([-1,2]))), color = 'C2', s=0.1, label='Ground-truth', alpha=0.8) #if i == 0 else \"\")\n",
+    "#     if i == 0:\n",
+    "#         initial_dc = m[0]\n",
+    "    initial_dc = m[0].tolist()\n",
+    "#     print(m)\n",
+    "#     print(m)\n",
+    "#     break\n",
+    "    predicted_dc_values = [initial_dc]\n",
+    "#     print(initial_dc)\n",
+    "#     if i%2 == 0:\n",
+    "    new_cycle_index = m[0,0]\n",
+    "#         print(f'hi {i}')\n",
+    "    for j,slope in enumerate(Y_hat_tested_cell[i]):\n",
+    "        new_cycle_index += (output_window_size-1)/2#np.floor(window_size/2)\n",
+    "        new_predicted_dc = linear_fit(new_cycle_index, slope, initial_dc) # slopes_tested_cell[i,j]\n",
+    "#         new_predicted_dc = linear_fit(new_cycle_index, -np.exp(-slope), initial_dc)\n",
+    "\n",
+    "        print(f'predicted slope: {slope}, True slope: {np.array(slopes_tested_cell)[i,j]}')\n",
+    "        predicted_dc_values.append([new_cycle_index , new_predicted_dc])\n",
+    "        initial_dc = predicted_dc_values[-1]\n",
+    "#         print(initial_dc)\n",
+    "      # \n",
+    "    print(predicted_dc_values)\n",
+    "#     break\n",
+    "#     initial_dc = np.array([new_cycle_index, new_predicted_dc]) \n",
+    "    \n",
+    "#     print(i)\n",
+    "#     print(predicted_dc_values)\n",
+    "#     initial_dc = predicted_dc_values[-1]\n",
+    "    \n",
+    "#     if i==2 or i==1:\n",
+    "#         print(m)\n",
+    "#         break\n",
+    "#     if i ==2:\n",
+    "#         break\n",
+    "    all_predicted_dc_values.append(predicted_dc_values)\n",
+    "#     print(np.array(scatters).T)\n",
+    "    plt.plot(*np.array(all_predicted_dc_values).T, color='C0', label='Inferred', #if i == 0 else \"\",\n",
+    "             marker='o', markersize=1, alpha=0.8)\n",
+    "    plt.scatter(*np.array(predicted_dc_values[-1]).T, c='C0', #if i == 0 else \"\",\n",
+    "         marker='o', s=50, edgecolor='k', linewidth=1, facecolor='C0', zorder=-1, alpha=0.8)\n",
+    "    plt.xlabel('Cycles')\n",
+    "    plt.ylabel('Discharge Capacity (Ah/Wh)')\n",
+    "    plt.ylim([0.85,1.2])\n",
+    "    plt.xlim([0 , max_cycle_index+50])\n",
+    "    ax = plt.gca()\n",
+    "    hand, labl = ax.get_legend_handles_labels()\n",
+    "    plt.legend(np.unique(labl))\n",
+    "    plt.tight_layout()\n",
+    "    show_input_output_windows = True\n",
+    "    if show_input_output_windows:\n",
+    "#         print(*list(zip([all_test_dc[i][0] - output_window_size, all_test_dc[i][0]-1], all_test_dc[i][-1])))\n",
+    "#         print(all_test_dc[i][-1])\n",
+    "#         print(all_test_dc[i][0,0])\n",
+    "        input_window_cycle_index = [all_test_dc[i][0,0] - output_window_size, all_test_dc[i][0,0]-1]\n",
+    "#         print(input_window_cycle_index)\n",
+    "        input_window_dc = [all_test_dc[i][0, -1], all_test_dc[i][1, -1]]\n",
+    "#         print(f'input_window: {all_test_dc[i][0,0]}')\n",
+    "#         print(f'dcvalues {input_window_dc}')\n",
+    "#         print(*list(zip(input_window, input_window_dc)))\n",
+    "#         print(predicted_dc_values)\n",
+    "#         break\n",
+    "        input_fill_between = plt.fill_between(*list([input_window_cycle_index, input_window_dc]), alpha=.15,\n",
+    "                                              edgecolor='y', color='y')\n",
+    "        (x0, y0), (x1, y1) = input_fill_between.get_paths()[0].get_extents().get_points()\n",
+    "        ax.text((x0 + x1) / 2, 0.91*y1, \"Input window\", ha='center', va='center', fontsize=7, color='y', rotation=90)\n",
+    "\n",
+    "        prediction_fill_between = plt.fill_between(*list(zip(*predicted_dc_values)), alpha=.15, edgecolor='C0', color='C0')\n",
+    "        (x0, y0), (x1, y1) = prediction_fill_between.get_paths()[0].get_extents().get_points()\n",
+    "        ax.text((x0 + x1) / 2, 0.91*y1, \"Output window\", ha='center', va='center', fontsize=7, color='C0', rotation=90)\n",
+    "\n",
+    "#     break\n",
+    "    save_gif = False\n",
+    "    if save_gif:\n",
+    "        plt.savefig(f'media/LFP/img/discharge_curve_in_{input_window_size}_out_{output_window_size}_window_test_{test_cell_number}_{i:04d}.png', dpi=400, transparent=False)\n",
+    "#     if i ==20:\n",
+    "        \n",
+    "#         break\n",
+    "#     plt.close()\n",
+    "#     break\n",
+    "#     if i == 2:\n",
+    "        \n",
+    "#     break\n",
+    "\n",
+    "# copy last frame\n",
+    "if save_gif:\n",
+    "    for j in range(10):\n",
+    "        os.system(f\"cp media/LFP/img/discharge_curve_in_{input_window_size}_out_{output_window_size}_window_test_{test_cell_number}_{i:04d}.png media/LFP/img/discharge_curve_in_{input_window_size}_out_{output_window_size}_window_test_{test_cell_number}_{i+j:04d}.png\")\n",
+    "    os.system(f\"ffmpeg -framerate 1 -i media/LFP/img/discharge_curve_in_{input_window_size}_out_{output_window_size}_window_test_{test_cell_number}_%04d.png -c:v h264 -crf 14 -c:v libx264 -movflags +faststart -vf format=yuv420p -maxrate 50M -tune animation -bufsize 1MB -t 15 -y media/LFP/mp4/discharge_curve_in_{input_window_size}_out{output_window_size}_window_test_{test_cell_number}.mp4\")\n",
+    "    os.system(f'ffmpeg -i media/LFP/mp4/discharge_curve_in_{input_window_size}_out{output_window_size}_window_test_{test_cell_number}.mp4 -framerate 1 -vf \"fps=24, scale=2000:-1:flags=lanczos\" -loop 0 -y media/LFP/gif/discharge_curve_in_{input_window_size}_out{output_window_size}_window_test_{test_cell_number}.gif')\n",
+    "# ffmpeg -i discharge_curve_50_window_test_3.mp4 -r 40 -vf \"fps=20, scale=2000:-1:flags=lanczos\" -f image2pipe -vcodec ppm - | convert -delay 10 -loop 0 - test.gif"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 343,
+   "id": "dfa6777b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'input_window_size': 50,\n",
+       " 'prediction_window_size': 50,\n",
+       " 'test_slope_MAE': 0.11168668419122696,\n",
+       " 'test_dc_RMSE': 0.008968439382723377}"
+      ]
+     },
+     "execution_count": 343,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dc_rmse = eval_dc_reconstruction(np.array(all_predicted_dc_values).reshape(-1,2), all_test_dc.reshape([-1,2]))\n",
+    "dict_results = {'input_window_size':input_window_size,\n",
+    "                'prediction_window_size':output_window_size,\n",
+    "                'test_slope_MAE':slope_mae,\n",
+    "                'test_dc_RMSE': dc_rmse\n",
+    "               }\n",
+    "import json\n",
+    "# with open(f'CACHED_DATA/results/LFP/input_window_{input_window_size}_output_window_{output_window_size}.json', 'w') as f:\n",
+    "#     json.dump(dict_results, f,  indent=4)\n",
+    "dict_results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "20fc0f66",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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atMinNtWnpqZG48aNMwViHnvsMS1dulQXXnih22yL+Ph43XLLLVqzZo26d+/uPP7SSy9p7dq1AWlToOzatUsZGRnOYFFKSorp9Xbt2mn27Nm65ZZbTMddgxOu3n//fX3xxRfOdGRkpD7//HM98sgjatOmjSlv37599eGHH+qBBx6QJFMAxxc33nijaem6W2+9VatXr9a4ceMUFxdnyhsVFaWrr75aq1ev1hlnnOE8vnDhQi1YsMBrHWPHjjX9Gxw9elTXXHONqqurTfkcDoeuvfZa00ybcePG6eabb/brmgAAABA4BGMAAAAANJrrPhytW7d2W1oqGG699Vbn/1dVVenNN9/0qZzrLBrXh/y1PfbYY6b0+PHjNXPmzDo3XK/tl7/8pU/56vOvf/1LGzdudKYnT56shx9+uN5/5/bt2+vDDz80tbf20lUnA5vNpg8++MA0U8STP//5z6ag03/+8x85HA6v+Wtvei9JTzzxhM4+++w66/jTn/6kc88914dW/9fy5ctNQZ/zzz9fL730kmlfI0+SkpL04YcfKj4+3nmsvvdm5syZ6tu3rzO9YsUK3X///aY8TzzxhBYvXuxMZ2Zm6uWXX/bpWgAAABAcBGMAAAAANJprMCbY+6acMHHiREVGRjrTr776ar1lCgoKNG/ePGe6bdu2uvDCCz3mXblypX744QdnOj4+Xn//+98b0eKGqz07JyYmRk899ZTPZfv372/aw+ejjz6S3W4PZPMa5corr/RpWbvk5GT96le/cqbLysrcZmWdkJ2dreXLlzvT7du31x133OFTe/7yl7/4lO8E15lTf/3rX30ORqanp5tmrHz//fd17lcTHR2t999/XzExMc5jzz77rHPJtm+//dYUQAwPD3fbbwYAAAChRzAGAAAAQKOVlJSY0p6W7gqGlJQUXXXVVc50dna2vvvuuzrLvPXWW6qsrHSmb7zxRrfN7k/4z3/+Y0rfcMMNIQs01Zafn6+VK1c60xdddJGSk5P9OkftIMaxY8dOqqXKxo4d63PeQYMGmdL79u3zmG/JkiWm9Lhx4+qdqXLCwIED3erxxuFwmGbFZGVlqWfPnj6VPaH2eyMdD6jUpU+fPnrhhRecacMwNGHCBG3YsEHjx483BdpmzJgR9P2bAAAAUD+CMQAAAAAarfYyS5JUWloasrqnTJliSrsuQeaq9usWi0WTJk3ymtf1ofgFF1zQgBY23nfffWfaiL0hD9c7depkSmdnZze6XYHiz/W47vVy9OhRj/lqB68kafTo0X61ydf8GzZsMLUhVO/NpEmTdM011zjTubm5GjZsmHJycpzHLrjgAt15551+twcAAACBRzAGAAAAQKO1atXKlPb2gDwYzjrrLNMeGh988IHX+n/44Qdt2rTJmf7lL3+prl27ej33zp07TemmmmHg+nD+7rvvlsVi8evHdSk216XlmpJrgKUurrOuysvLPebbvXu3Kd2vXz+/2tS/f3+f8rm+N//4xz/8fm9q91/J9/fm5ZdfVrdu3Zzpqqoq5/+3a9dOb7zxRkj2bgIAAED9CMYAAAAAaDTXYExubm5I6588ebLz/8vLyzVnzhyP+Vz3lLnlllvqPG/th+IWi0WpqamNaGXD5efnB/ycoQyY1ScqKqrBZWvPGKqtqKjIlE5JSfHrvL7mb8r3Jj4+Xu+9954iIiJMx61Wq+bMmdNk/RUAAADuCMYAAAAAaLRevXqZ0iUlJdqxY0fI6r/hhhtMG5p7WqqspKREc+fOdaZTU1N12WWX1Xne2nvhxMTEyGptmlso18BCIDgcjoCf82Ry7NgxU7p2//CFr/seNfV7U15ebtojRjoeSBowYECgmwUAAIBG8LxLJQAAAAD44Re/+IXCwsJUU1PjPLZ69WrTEkrBlJiYqLFjx2r27NmSpJ9++kmrV682LSv2zjvvmPaymTBhgtuMAlfx8fEqLCyUJJWVlcnhcDRJQMY1kDBt2jS3Zcf8VdfybC2BazClrKzMbW+juvi675Hre3PNNdfopptu8rkeT9q1a+dTvoKCAo0fP94tGJObm6sbb7xRH330UaPaAQAAgMAhGAMAAACg0WJjYzVkyBDTpukff/yxxo0bF7I2TJkyxRmMkY7PjqkdjPF3iTLp+PJrJ4IxhmEoLy/Pr/1NAsV1uam2bdvqnHPOCXk7mpOkpCRTOi8vz69gjK/Lj7m+N0lJSSF7b2666Sbt27fP42sff/yxXnzxRf3ud78LSVsAAABQN5YpAwAAABAQl19+uSk9b968oOyn4U1WVpYGDRrkTL/77rvO2Q0nZsqcMHLkSPXs2bPec3bv3t2Urn2OUOrSpYspHcol4Jor15k/Gzdu9Kv8+vXrfcrXVO/Niy++aJr50r59e7333nummVvTp0/XTz/9FJL2AAAAoG4EYwAAAAAExOTJkxUXF+dMV1ZW6s9//nNI2zBlyhTn/5eUlOi9996T5L6HjC+zYiRpxIgRpvTChQsb2cKGGTNmjCn99ddfN0k7mpPhw4eb0kuXLvWrvK/5s7KyTEuVLVu2TBUVFX7V5a+ffvpJ06dPd6ZtNpvmzJmjsWPH6t5773Uer6ys1Lhx43xecg0AAADBQzAGAAAAQEAkJydr0qRJpmPPPfecVqxY0ehz+xoEGT9+vCkg9Morr6i8vFzvvPOOqZ1XXXWVT+c777zzTOm33norKBu216d9+/bq16+fM71z5059/vnnIW9HczJ69GhT+r333lN1dbVPZdetW+fzjJKIiAidffbZznRpaalpubxAKy0t1dixY1VZWek89uCDD2rUqFGSpMcee0xnnHGG87WtW7fqt7/9bdDaAwAAAN8QjAEAAAAQMI8++qgyMjKcabvdrssuu0wbNmxo0Pmqq6t11113+fwwOT4+Xtdee60zvWLFCj300EOmAMp1112nqKgon843ZMgQnXXWWc50cXFxkz3Yrj0TQpKmTZumo0ePNklbmoM+ffrotNNOc6b379+vF154waeyrv/W/uZ/5JFHtHfvXr/O4avbbrtN27Ztc6ZHjhyphx56yJkOCwvTu+++q+TkZOexN954Q3PmzAlKewAAAOAbgjEAAAAAAiYpKUlz585VeHi489ihQ4c0atQovfvuuzIMw+dzLV26VMOGDdOzzz7rV7naS5VJ0rPPPmtK+7pE2QmPPPKILBaLM/3OO+9o2rRpPrfpq6++8qs+b6699lr17dvXmd62bZvOP/98HThwwOdzVFdX64033gj58nFNZdq0aab0Aw88oMWLF9dZ5qGHHtKXX37pVz0jR47Ur3/9a2c6NzdXv/rVr7Rlyxafz+FwOLRgwQLdc889XvO8+eabevPNN53plJQUvfPOO7LZbKZ8nTp10quvvmo6NnXqVPYaAgAAaEIEYwAAAAAEVFZWll555RXTRuKFhYUaP368TjvtNL388steZw1s375dzz33nM444wyNHj3a503Uaxs0aJCysrI8vnbaaaepf//+fp3vnHPO0R/+8AfTsZkzZ2ro0KGaN2+ex/04duzYoZkzZ2rYsGE655xz/KrPG5vNpg8//FCJiYnOYz/88IP69eunRx55xDRborbDhw/r008/1eTJk9W+fXtNnDhR2dnZAWnTyW7cuHGmf//Kykqdd955euyxx5Sbm2vKu3nzZl111VX605/+JEmmGV6+ePPNN9WxY0dneuvWrRo6dKimTZumdevWeQzeFRYWatGiRbrzzjuVkZGhyy+/3Ouyftu2bXOblTV79my1b9/eY/4rrrhCU6dOdaZLSko0btw4VVVV+XVdAAAACIywpm4AAAAAgJZnwoQJSkxM1IQJE1RcXOw8vmrVKq1atUqS1KpVK7Vu3VqJiYnKz8/XwYMHVVZW5vF8bdu29av+KVOmaOXKlW7H/Z0Vc8KMGTO0b98+vf/++85ja9eu1ZVXXqmIiAh17txZrVq1UmlpqXJycoK2r0zPnj01f/58XXnllSosLJR0/IH+448/rscff1ypqalKT09XbGysiouLlZeX5xZ0ONXMnj1bZ511ln7++WdJUlVVlR599FH96U9/UpcuXZSUlKSDBw8qJyfHWaZ9+/aaMWOGxo0b53M9bdq00WeffaYLL7xQ+/btkySVlZVp5syZmjlzphITE9W+fXvFx8fr2LFjKigo0MGDB306d2VlpcaNG6djx445j91xxx26+OKL6yz33HPP6fvvv3cGNdesWaN7771Xzz33nM/XBQAAgMBgZgwAAACAoLjsssu0bt06XXrppR5fLygo0NatW7Vy5Urt3LnTYyAmJSVFf/3rX/XNN9/4VffYsWOVlJRkOhYfH+/Xw/XawsLC9N577+nBBx80LcEmHX+4v337dq1YsUIbN24MWiDmhDFjxmjVqlUaPny422t5eXnauHGjVqxYoezsbI+BGIvFYprB0dJ16NBBX331lTIzM03Ha2pqtH37dq1atcoUiGnXrp2++OILpaWl+V1X//79tWbNGtOSZSccPXpUmzdv1ooVK7Rp0yavgZhOnTq5HZs+fbrWrl3rTA8ePFh/+ctf6m1PVFSU5s6dq5iYGOex559/XgsXLvTlcgAAABBABGMAAAAABE1GRoYWLFigtWvX6rbbblN6enq9ZWJjY3X++efrvffe0/79+zVt2jS3AEh9YmJiNHbsWNOxa665RrGxsX6dpzaLxaL/+Z//UXZ2tiZOnOgW7HGVlpamm2++2eMMncbKzMzUypUr9fHHH+vss89WREREnfltNptOP/10Pf7449qxY4f+53/+J+BtOpllZmZq/fr1uueee0wb29cWGRmpW265RevWrVO/fv0aXFfr1q31xRdf6JtvvtHFF19cb5+zWCwaPHiw7r33Xq1fv960J4wkffzxx3rxxRed6bi4OM2dO7fe9/yEXr16mcobhqEJEyb4tdcQAAAAGs9i+LMTJgAAAAA00s6dO7Vx40bt27dPJSUlMgxDSUlJatWqlfr06aO+ffu6bUjeECNHjtS3337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+      "text/plain": [
+       "<Figure size 1800x1200 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(dpi=300, facecolor='white')\n",
+    "for i,c in enumerate(summary_data_list):\n",
+    "    plt.scatter(c['cycle_index'][1:], c['discharge_capacity'][1:], \n",
+    "                s=0.1, color=f'C{i}', label='actual cycle_index', alpha=0.3)\n",
+    "plt.xlabel('Cycle index')\n",
+    "plt.ylabel('Discharge capacity (Ah/Wh)')\n",
+    "# plt.savefig(f'LFP_dataset.png', dpi=400, transparent=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a7c2c6ef",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "63619785",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "87b97e39",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "conda_beep",
+   "language": "python",
+   "name": "conda_beep"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/examples/featurizer.ipynb b/examples/featurizer.ipynb
index fcb3b49..af4d173 100644
--- a/examples/featurizer.ipynb
+++ b/examples/featurizer.ipynb
@@ -3,7 +3,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "261dcaa0",
+   "id": "b98789cf",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -18,7 +18,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "ae05f134",
+   "id": "a9fc154c",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -33,7 +33,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "c68cd2ad",
+   "id": "15bf0847",
    "metadata": {},
    "outputs": [
     {
@@ -62,7 +62,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "1cebaa99",
+   "id": "aead8661",
    "metadata": {},
    "outputs": [
     {
@@ -90,7 +90,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "f7ebbe5c",
+   "id": "15530be8",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -101,7 +101,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "id": "bc1f5513",
+   "id": "4d27f0b0",
    "metadata": {},
    "outputs": [
     {
@@ -133,7 +133,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "048454bb",
+   "id": "0f41f7c6",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -159,7 +159,7 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "id": "0a6b7ab8",
+   "id": "ad295955",
    "metadata": {},
    "outputs": [
     {
@@ -177,7 +177,7 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "id": "8e8294c7",
+   "id": "41bebb29",
    "metadata": {},
    "outputs": [
     {
@@ -197,7 +197,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "7f776935",
+   "id": "9ca04981",
    "metadata": {},
    "outputs": [
     {
@@ -570,7 +570,7 @@
   {
    "cell_type": "code",
    "execution_count": 52,
-   "id": "6d9e2f57",
+   "id": "d46761ea",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -583,14 +583,14 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "07e5b365",
+   "id": "420ea4bd",
    "metadata": {},
    "outputs": [],
    "source": []
   },
   {
    "cell_type": "markdown",
-   "id": "0d035c21",
+   "id": "5c603292",
    "metadata": {},
    "source": [
     "The printed cycles above are diagnostic cycles."
@@ -599,7 +599,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "206e3e8b",
+   "id": "4c3920f8",
    "metadata": {},
    "outputs": [
     {
@@ -696,7 +696,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "0b1a8156",
+   "id": "a815719b",
    "metadata": {},
    "outputs": [
     {
@@ -716,7 +716,7 @@
   {
    "cell_type": "code",
    "execution_count": 43,
-   "id": "f61d6596",
+   "id": "73e716f4",
    "metadata": {},
    "outputs": [
     {
@@ -739,7 +739,7 @@
   {
    "cell_type": "code",
    "execution_count": 21,
-   "id": "847a09e8",
+   "id": "0f14996b",
    "metadata": {},
    "outputs": [
     {
@@ -762,7 +762,7 @@
   {
    "cell_type": "code",
    "execution_count": 22,
-   "id": "b64092e7",
+   "id": "9782ba3e",
    "metadata": {},
    "outputs": [
     {
@@ -14178,7 +14178,7 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "id": "2d8e207a",
+   "id": "5660f2ea",
    "metadata": {},
    "outputs": [
     {
@@ -14332,7 +14332,7 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "id": "5116aa1b",
+   "id": "495dcc32",
    "metadata": {},
    "outputs": [
     {
@@ -14364,7 +14364,7 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "id": "140ebbb9",
+   "id": "c9156c5f",
    "metadata": {},
    "outputs": [
     {
@@ -14383,7 +14383,7 @@
   {
    "cell_type": "code",
    "execution_count": 94,
-   "id": "a55e6cd5",
+   "id": "2b9dc223",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -14416,7 +14416,7 @@
   {
    "cell_type": "code",
    "execution_count": 95,
-   "id": "c28fd2d2",
+   "id": "3e519438",
    "metadata": {
     "scrolled": true
    },
@@ -17766,7 +17766,7 @@
   {
    "cell_type": "code",
    "execution_count": 83,
-   "id": "bc78a1b1",
+   "id": "a6ee35be",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -17778,7 +17778,7 @@
   {
    "cell_type": "code",
    "execution_count": 84,
-   "id": "1915d5ce",
+   "id": "32da10ca",
    "metadata": {},
    "outputs": [
     {
@@ -17907,7 +17907,7 @@
   {
    "cell_type": "code",
    "execution_count": 33,
-   "id": "a72de0e7",
+   "id": "1f1c1050",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -17929,7 +17929,7 @@
   {
    "cell_type": "code",
    "execution_count": 68,
-   "id": "f891157c",
+   "id": "bec05c0b",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -17940,130 +17940,10 @@
     "            interp_clean_cell.append(bye_cycle.interpol_cycle(clean_dat, n_points=n_points, columns=columns, interpol_kind='linear'))"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 69,
-   "id": "64ac7ff0",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[ 3.501e+00, -9.682e+00,  4.346e+03,  1.631e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.628e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.625e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.622e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.619e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.616e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.613e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.610e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.607e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.604e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.601e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.598e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.595e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.592e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.589e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.586e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.583e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.580e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.577e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.574e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.571e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.568e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.565e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.562e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.559e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.556e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.553e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.550e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.547e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.544e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.541e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.538e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.535e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.532e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.529e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.527e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.524e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.521e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.518e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.515e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.512e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.509e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.506e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.503e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.500e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.497e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.494e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.491e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.488e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.485e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.482e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.479e-04],\n",
-       "       [ 3.501e+00, -9.682e+00,  4.346e+03,  1.476e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.473e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.470e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.467e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.464e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.461e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.458e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.455e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.452e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.449e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.446e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.443e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.440e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.437e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.434e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.431e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.428e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.425e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.422e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.419e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.416e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.413e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.410e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.407e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.404e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.401e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.398e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.395e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.392e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.389e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.386e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.383e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.381e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.378e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.375e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.372e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.369e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.366e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.363e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.360e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.357e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.354e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.351e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.348e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.345e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.342e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.339e-04],\n",
-       "       [ 3.502e+00, -9.682e+00,  4.346e+03,  1.336e-04]])"
-      ]
-     },
-     "execution_count": 69,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "a"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 66,
-   "id": "66bad63b",
+   "id": "eb34cff6",
    "metadata": {},
    "outputs": [
     {
@@ -18383,7 +18263,7 @@
   {
    "cell_type": "code",
    "execution_count": 49,
-   "id": "fc7b3b66",
+   "id": "5164b9fe",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -18396,7 +18276,7 @@
   {
    "cell_type": "code",
    "execution_count": 50,
-   "id": "20508a68",
+   "id": "0fe1bb76",
    "metadata": {},
    "outputs": [
     {
@@ -18449,7 +18329,7 @@
   {
    "cell_type": "code",
    "execution_count": 70,
-   "id": "76b537c1",
+   "id": "ed90d460",
    "metadata": {
     "scrolled": true
    },
@@ -18462,7 +18342,7 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "id": "0b017401",
+   "id": "c58be6e2",
    "metadata": {},
    "outputs": [
     {
@@ -18483,7 +18363,7 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "id": "df6a8e3f",
+   "id": "534f4eae",
    "metadata": {},
    "outputs": [
     {
@@ -18515,7 +18395,7 @@
   {
    "cell_type": "code",
    "execution_count": 20,
-   "id": "adde3e66",
+   "id": "de04c99f",
    "metadata": {},
    "outputs": [
     {
@@ -18549,7 +18429,7 @@
   {
    "cell_type": "code",
    "execution_count": 21,
-   "id": "d9346d75",
+   "id": "66dbc95d",
    "metadata": {},
    "outputs": [
     {
@@ -18597,7 +18477,7 @@
   {
    "cell_type": "code",
    "execution_count": 22,
-   "id": "c54b7ffd",
+   "id": "fb66b72a",
    "metadata": {},
    "outputs": [
     {
@@ -18617,7 +18497,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "3931f69b",
+   "id": "5e4908f7",
    "metadata": {},
    "outputs": [],
    "source": []
diff --git a/examples/shifting_cycles.ipynb b/examples/shifting_cycles.ipynb
new file mode 100644
index 0000000..043ac82
--- /dev/null
+++ b/examples/shifting_cycles.ipynb
@@ -0,0 +1,80734 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "7883c2a4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "import bye_cycle\n",
+    "import tensorflow as tf\n",
+    "from tqdm import tqdm\n",
+    "import numpy as np\n",
+    "import pickle\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "eaafba38",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Disabling tf warnings\n",
+    "tf.get_logger().setLevel('INFO')\n",
+    "# Disabling GPU\n",
+    "RUN_ON_GPU = True\n",
+    "if not RUN_ON_GPU:\n",
+    "    os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"-1\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "6ccefc31",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def drop_increasing_column(cycle_dataframe, column='discharge_capacity'):\n",
+    "    cycle_data = cycle_dataframe.copy()\n",
+    "#     print(len(cycle_data))\n",
+    "    diff = cycle_data[column] - cycle_data[column].shift(1)\n",
+    "    drop_indices = np.where(diff > 0)[0]\n",
+    "#     print(len(drop_indices))\n",
+    "    drop_cycle_indices = list(cycle_data['cycle_index'].iloc[drop_indices])\n",
+    "    cycle_data.drop(cycle_data.index[drop_indices], axis=0, inplace=True)\n",
+    "    return cycle_data, drop_cycle_indices\n",
+    "\n",
+    "# drop_increasing_column(summary_data[0])['discharge_capacity'].is_monotonic_decreasing \n",
+    "# test = summary_data[0]\n",
+    "def decrease_monotonically(cycle_dataframe, column='discharge_capacity', renumber_cycle_index=True):\n",
+    "    cycle_indices_dropped = []\n",
+    "    while not cycle_dataframe[column].is_monotonic_decreasing:\n",
+    "        cycle_dataframe, _ = drop_increasing_column(cycle_dataframe, column=column)\n",
+    "#         print(len(cycle_dataframe))\n",
+    "        cycle_indices_dropped.append(_)\n",
+    "    cycle_indices_dropped = [x for xs in cycle_indices_dropped for x in xs]\n",
+    "    if renumber_cycle_index:\n",
+    "        cycle_dataframe['cycle_index'] = cycle_dataframe.reset_index(drop=True).index\n",
+    "    return cycle_dataframe, cycle_indices_dropped\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "f38d0cf4",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  0%|          | 0/338 [00:00<?, ?it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0 PreDiag_000333_000180_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  0%|          | 1/338 [00:03<16:51,  3.00s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1 PredictionDiagnostics_000131_00004B_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (1, 'PredictionDiagnostics_000131_00004B_structured.pkl')\n",
+      "2 PreDiag_000314_000196_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  1%|          | 3/338 [00:04<06:29,  1.16s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "3 PreDiag_000317_000193_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  1%|          | 4/338 [00:04<05:20,  1.04it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "4 PreDiag_000272_0000C5_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  1%|▏         | 5/338 [00:07<08:01,  1.45s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "5 PredictionDiagnostics_000170_000256_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "  2%|▏         | 7/338 [00:07<04:13,  1.31it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (5, 'PredictionDiagnostics_000170_000256_structured.pkl')\n",
+      "6 PredictionDiagnostics_000142_000031_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (6, 'PredictionDiagnostics_000142_000031_structured.pkl')\n",
+      "7 PreDiag_000251_00020D_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  2%|▏         | 8/338 [00:11<10:27,  1.90s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "8 PreDiag_000374_0001D9_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  3%|▎         | 9/338 [00:12<07:46,  1.42s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "9 PreDiag_000335_00017E_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  3%|▎         | 10/338 [00:13<07:24,  1.35s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "10 PreDiag_000340_000178_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  3%|▎         | 11/338 [00:18<14:25,  2.65s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "11 PreDiag_000407_00008A_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  4%|▎         | 12/338 [00:19<11:18,  2.08s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "12 PredictionDiagnostics_000151_00001E_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  4%|▍         | 13/338 [00:20<08:47,  1.62s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "13 PredictionDiagnostics_000174_00023E_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  4%|▍         | 14/338 [00:20<06:57,  1.29s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "14 PreDiag_000234_00021D_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  4%|▍         | 15/338 [00:25<12:07,  2.25s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "15 PreDiag_000246_000217_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  5%|▍         | 16/338 [00:27<11:38,  2.17s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "16 PreDiag_000456_0001E1_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  5%|▌         | 17/338 [00:29<12:11,  2.28s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "17 PreDiag_000387_0001F1_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  5%|▌         | 18/338 [00:30<09:40,  1.81s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "18 PreDiag_000436_0000F8_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  6%|▌         | 19/338 [00:31<07:59,  1.50s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "19 PredictionDiagnostics_000181_00023A_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  6%|▌         | 20/338 [00:32<06:51,  1.29s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "20 PredictionDiagnostics_000148_000038_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  6%|▌         | 21/338 [00:33<06:18,  1.19s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "21 PreDiag_000446_000101_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  7%|▋         | 22/338 [00:34<07:17,  1.38s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "22 PreDiag_000362_000161_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  7%|▋         | 23/338 [00:37<08:39,  1.65s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "23 PreDiag_000405_000088_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  7%|▋         | 24/338 [00:38<08:36,  1.64s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "24 PredictionDiagnostics_000161_000252_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  7%|▋         | 25/338 [00:39<06:46,  1.30s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "25 PredictionDiagnostics_000162_000021_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  8%|▊         | 26/338 [00:39<05:11,  1.00it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "26 PreDiag_000420_000097_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  8%|▊         | 27/338 [00:40<04:27,  1.16it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "27 PreDiag_000375_0001F7_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  8%|▊         | 28/338 [00:40<03:28,  1.48it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "28 PreDiag_000211_000209_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  9%|▊         | 29/338 [00:51<19:41,  3.82s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "29 PredictionDiagnostics_000140_000033_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (29, 'PredictionDiagnostics_000140_000033_structured.pkl')\n",
+      "30 PreDiag_000400_000084_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  9%|▉         | 31/338 [00:51<10:56,  2.14s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "31 PreDiag_000199_0000DA_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  9%|▉         | 32/338 [00:55<12:24,  2.43s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "32 PreDiag_000482_0000E9_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 10%|▉         | 33/338 [00:57<11:44,  2.31s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "33 PredictionDiagnostics_000116_00003D_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (33, 'PredictionDiagnostics_000116_00003D_structured.pkl')\n",
+      "34 PreDiag_000477_0000EF_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 10%|█         | 35/338 [00:59<09:03,  1.79s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "35 PredictionDiagnostics_000185_000243_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 11%|█         | 36/338 [01:00<08:26,  1.68s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "36 .ipynb_checkpoints\n",
+      "37 PredictionDiagnostics_000110_0001BD_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (37, 'PredictionDiagnostics_000110_0001BD_structured.pkl')\n",
+      "38 PreDiag_000311_000199_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 12%|█▏        | 39/338 [01:01<04:31,  1.10it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "39 PreDiag_000401_000086_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 12%|█▏        | 40/338 [01:02<05:20,  1.08s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "40 PreDiag_000377_00009F_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 12%|█▏        | 41/338 [01:03<04:39,  1.06it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "41 PreDiag_000226_0001D0_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 12%|█▏        | 42/338 [01:05<05:30,  1.12s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "42 PredictionDiagnostics_000135_00002C_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (42, 'PredictionDiagnostics_000135_00002C_structured.pkl')\n",
+      "43 PredictionDiagnostics_000134_00002B_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (43, 'PredictionDiagnostics_000134_00002B_structured.pkl')\n",
+      "44 PreDiag_000223_0001A2_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 13%|█▎        | 45/338 [01:06<03:40,  1.33it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "45 PreDiag_000412_00008F_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (45, 'PreDiag_000412_00008F_structured.pkl')\n",
+      "46 PreDiag_000356_000167_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 14%|█▍        | 47/338 [01:12<07:33,  1.56s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "47 PreDiag_000465_0001C3_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 14%|█▍        | 48/338 [01:14<07:55,  1.64s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "48 PreDiag_000245_00021A_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 14%|█▍        | 49/338 [01:15<07:17,  1.51s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "49 PreDiag_000198_000207_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 15%|█▍        | 50/338 [01:18<08:44,  1.82s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "50 PreDiag_000324_00018A_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 15%|█▌        | 51/338 [01:19<07:35,  1.59s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "51 PreDiag_000217_00019C_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 16%|█▌        | 54/338 [01:32<12:09,  2.57s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "52 PredictionDiagnostics_000125_0001AF_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (52, 'PredictionDiagnostics_000125_0001AF_structured.pkl')\n",
+      "53 PredictionDiagnostics_000138_000039_structured.pkl\n",
+      "54 PredictionDiagnostics_000115_0001BB_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (54, 'PredictionDiagnostics_000115_0001BB_structured.pkl')\n",
+      "55 PreDiag_000205_00005A_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 17%|█▋        | 59/338 [01:32<04:32,  1.03it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (55, 'PreDiag_000205_00005A_structured.pkl')\n",
+      "56 PredictionDiagnostics_000109_0001BC_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (56, 'PredictionDiagnostics_000109_0001BC_structured.pkl')\n",
+      "57 PreDiag_000370_0001C9_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (57, 'PreDiag_000370_0001C9_structured.pkl')\n",
+      "58 PreDiag_000368_0001DE_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (58, 'PreDiag_000368_0001DE_structured.pkl')\n",
+      "59 PreDiag_000455_0001E0_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 18%|█▊        | 60/338 [01:35<05:27,  1.18s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "60 PreDiag_000355_000168_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 18%|█▊        | 61/338 [01:40<09:36,  2.08s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "61 PreDiag_000453_000108_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 18%|█▊        | 62/338 [01:43<09:49,  2.13s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "62 PreDiag_000261_0000C8_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 19%|█▊        | 63/338 [01:55<21:09,  4.62s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "63 PredictionDiagnostics_000175_000247_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 19%|█▉        | 64/338 [01:56<17:05,  3.74s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "64 PreDiag_000336_00017C_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 19%|█▉        | 65/338 [01:57<13:35,  2.99s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "65 PredictionDiagnostics_000154_000024_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 20%|█▉        | 66/338 [01:57<10:18,  2.27s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "66 PredictionDiagnostics_000160_000251_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 20%|█▉        | 67/338 [01:59<09:13,  2.04s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "67 PreDiag_000445_000100_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 20%|██        | 68/338 [02:00<07:30,  1.67s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "68 PreDiag_000471_00006B_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 20%|██        | 69/338 [02:02<07:58,  1.78s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "69 PreDiag_000276_0000C2_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 21%|██        | 70/338 [02:16<24:53,  5.57s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "70 PreDiag_000452_000107_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 21%|██        | 71/338 [02:19<20:25,  4.59s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "71 PreDiag_000413_000090_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 21%|██▏       | 72/338 [02:20<15:28,  3.49s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "72 PreDiag_000380_000063_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 22%|██▏       | 73/338 [02:20<11:16,  2.55s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "73 PreDiag_000473_00006D_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 22%|██▏       | 74/338 [02:22<10:10,  2.31s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "74 PreDiag_000366_0001EF_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (74, 'PreDiag_000366_0001EF_structured.pkl')\n",
+      "75 PredictionDiagnostics_000164_000239_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 22%|██▏       | 76/338 [02:22<05:41,  1.30s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "76 PredictionDiagnostics_000100_0001B0_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (76, 'PredictionDiagnostics_000100_0001B0_structured.pkl')\n",
+      "77 PreDiag_000263_0000C6_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 23%|██▎       | 78/338 [02:33<12:37,  2.91s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "78 PredictionDiagnostics_000193_00024B_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 23%|██▎       | 79/338 [02:37<14:14,  3.30s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "79 PredictionDiagnostics_000166_000246_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 24%|██▎       | 80/338 [02:38<11:27,  2.67s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "80 PredictionDiagnostics_000178_00023B_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 24%|██▍       | 81/338 [02:42<12:34,  2.93s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "81 PreDiag_000392_00010B_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 24%|██▍       | 82/338 [02:42<09:37,  2.26s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "82 PreDiag_000397_000110_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 25%|██▍       | 83/338 [02:43<07:46,  1.83s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "83 PreDiag_000334_00017F_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 25%|██▍       | 84/338 [02:46<09:19,  2.20s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "84 PreDiag_000472_00006E_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 25%|██▌       | 85/338 [02:47<08:30,  2.02s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "85 PreDiag_000418_000095_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 25%|██▌       | 86/338 [02:48<06:40,  1.59s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "86 PreDiag_000415_000092_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 26%|██▌       | 87/338 [02:49<05:32,  1.32s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "87 PredictionDiagnostics_000122_000043_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (87, 'PredictionDiagnostics_000122_000043_structured.pkl')\n",
+      "88 PreDiag_000322_0001D5_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 26%|██▋       | 89/338 [02:53<06:42,  1.62s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "89 PredictionDiagnostics_000137_00002F_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (89, 'PredictionDiagnostics_000137_00002F_structured.pkl')\n",
+      "90 PreDiag_000213_0001CF_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 27%|██▋       | 91/338 [03:06<15:05,  3.67s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "91 PreDiag_000271_0000C4_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 27%|██▋       | 92/338 [03:07<12:36,  3.08s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "92 PredictionDiagnostics_000163_000022_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 28%|██▊       | 93/338 [03:09<10:59,  2.69s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "93 PredictionDiagnostics_000177_00002A_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 28%|██▊       | 94/338 [03:09<08:36,  2.12s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "94 PreDiag_000463_0001C5_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 28%|██▊       | 95/338 [03:10<07:03,  1.74s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "95 PreDiag_000244_00021C_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 28%|██▊       | 96/338 [03:10<05:32,  1.37s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "96 PredictionDiagnostics_000188_00024A_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 29%|██▊       | 97/338 [03:12<05:55,  1.48s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "97 PreDiag_000315_000195_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 29%|██▉       | 98/338 [03:13<05:04,  1.27s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "98 PreDiag_000350_00016D_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 29%|██▉       | 99/338 [03:14<04:51,  1.22s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "99 PreDiag_000229_000229_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 30%|██▉       | 100/338 [03:16<06:21,  1.60s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "100 PreDiag_000232_000221_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 30%|███       | 102/338 [03:17<03:47,  1.04it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "101 PredictionDiagnostics_000152_000026_structured.pkl\n",
+      "102 PreDiag_000396_00010F_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 30%|███       | 103/338 [03:17<02:54,  1.35it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "103 PreDiag_000320_00019F_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 31%|███       | 104/338 [03:20<05:10,  1.33s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "104 PreDiag_000332_000182_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 31%|███       | 105/338 [03:23<07:35,  1.96s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "105 PreDiag_000411_00008E_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 31%|███▏      | 106/338 [03:24<06:01,  1.56s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "106 PreDiag_000425_0000E3_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 32%|███▏      | 107/338 [03:25<04:57,  1.29s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "107 PreDiag_000388_0001F3_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 32%|███▏      | 108/338 [03:26<04:20,  1.13s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "108 PreDiag_000238_000223_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 32%|███▏      | 109/338 [03:28<05:19,  1.40s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "109 PreDiag_000270_0001EA_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 33%|███▎      | 110/338 [03:29<05:02,  1.33s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "110 PreDiag_000273_0000C3_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 33%|███▎      | 112/338 [03:33<05:59,  1.59s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "111 PreDiag_000371_0001E8_structured.pkl\n",
+      "112 PreDiag_000394_00010D_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 33%|███▎      | 113/338 [03:33<04:32,  1.21s/it]"
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+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "113 PredictionDiagnostics_000149_00003A_structured.pkl\n"
+     ]
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+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 34%|███▎      | 114/338 [03:34<03:38,  1.02it/s]"
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+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "114 PreDiag_000278_000237_structured.pkl\n"
+     ]
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+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 34%|███▍      | 115/338 [03:47<17:16,  4.65s/it]"
+     ]
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+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "115 PredictionDiagnostics_000147_000035_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (115, 'PredictionDiagnostics_000147_000035_structured.pkl')\n",
+      "116 PreDiag_000409_00008C_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 35%|███▍      | 117/338 [03:48<09:55,  2.69s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "117 PreDiag_000363_000160_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 35%|███▍      | 118/338 [03:49<08:51,  2.42s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "118 PreDiag_000330_000184_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 35%|███▌      | 119/338 [03:52<08:56,  2.45s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "119 PreDiag_000288_000234_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 36%|███▌      | 120/338 [04:10<24:43,  6.80s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "120 PreDiag_000227_00005D_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 36%|███▌      | 121/338 [04:17<24:38,  6.81s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "121 PreDiag_000319_000191_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 36%|███▌      | 122/338 [04:18<18:08,  5.04s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "122 PredictionDiagnostics_000158_00024F_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 36%|███▋      | 123/338 [04:18<13:08,  3.67s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "123 PreDiag_000259_00021B_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 37%|███▋      | 124/338 [04:23<13:45,  3.86s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "124 PredictionDiagnostics_000103_0001B3_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (124, 'PredictionDiagnostics_000103_0001B3_structured.pkl')\n",
+      "125 PredictionDiagnostics_000123_00004A_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (125, 'PredictionDiagnostics_000123_00004A_structured.pkl')\n",
+      "126 PreDiag_000404_000082_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 38%|███▊      | 127/338 [04:24<07:00,  1.99s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "127 PreDiag_000254_000213_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 38%|███▊      | 128/338 [04:34<12:50,  3.67s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "128 PredictionDiagnostics_000129_000045_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (128, 'PredictionDiagnostics_000129_000045_structured.pkl')\n",
+      "129 PreDiag_000440_0000FB_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 38%|███▊      | 130/338 [04:36<09:13,  2.66s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "130 PredictionDiagnostics_000132_00004C_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (130, 'PredictionDiagnostics_000132_00004C_structured.pkl')\n",
+      "131 PreDiag_000339_000179_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 39%|███▉      | 132/338 [04:43<10:22,  3.02s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "132 PredictionDiagnostics_000111_0001BE_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (132, 'PredictionDiagnostics_000111_0001BE_structured.pkl')\n",
+      "133 PreDiag_000346_000171_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 40%|███▉      | 134/338 [04:48<09:15,  2.72s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "134 PreDiag_000210_0001E9_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 40%|███▉      | 135/338 [04:52<10:33,  3.12s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "135 PreDiag_000457_0001E2_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 40%|████      | 136/338 [04:55<10:22,  3.08s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "136 PredictionDiagnostics_000194_000242_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 41%|████      | 137/338 [04:57<08:52,  2.65s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "137 PreDiag_000384_0001CC_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 41%|████      | 138/338 [04:57<06:51,  2.06s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "138 PreDiag_000359_000164_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 41%|████      | 139/338 [04:58<05:34,  1.68s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "139 PreDiag_000257_000218_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 41%|████▏     | 140/338 [04:59<05:34,  1.69s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "140 PredictionDiagnostics_000145_000037_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (140, 'PredictionDiagnostics_000145_000037_structured.pkl')\n",
+      "141 PreDiag_000249_000211_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 42%|████▏     | 142/338 [05:04<06:47,  2.08s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "142 PreDiag_000224_0001D3_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 43%|████▎     | 144/338 [05:09<06:25,  1.99s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "143 PreDiag_000367_0001ED_structured.pkl\n",
+      "144 PreDiag_000328_000186_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 43%|████▎     | 145/338 [05:10<05:17,  1.65s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "145 PreDiag_000220_00005E_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 43%|████▎     | 146/338 [05:10<04:09,  1.30s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "146 PredictionDiagnostics_000127_000047_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (146, 'PredictionDiagnostics_000127_000047_structured.pkl')\n",
+      "147 PreDiag_000447_000102_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 44%|████▍     | 148/338 [05:13<04:34,  1.45s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "148 PreDiag_000393_00010C_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 44%|████▍     | 149/338 [05:14<03:40,  1.17s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "149 PreDiag_000434_0000F6_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 44%|████▍     | 150/338 [05:14<03:21,  1.07s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "150 PredictionDiagnostics_000157_000020_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 45%|████▍     | 151/338 [05:15<02:49,  1.10it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "151 PreDiag_000461_000064_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 45%|████▌     | 153/338 [05:16<02:28,  1.25it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "152 PredictionDiagnostics_000141_000032_structured.pkl\n",
+      "153 PreDiag_000202_00005B_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 46%|████▌     | 154/338 [05:20<05:07,  1.67s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "154 PreDiag_000372_0001DF_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 46%|████▌     | 155/338 [05:20<03:52,  1.27s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "155 PreDiag_000448_000103_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 46%|████▌     | 156/338 [05:22<04:16,  1.41s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "156 PreDiag_000449_000104_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 46%|████▋     | 157/338 [05:24<04:50,  1.61s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "157 PreDiag_000443_0000FE_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 47%|████▋     | 158/338 [05:26<04:58,  1.66s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "158 PreDiag_000214_0001A3_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 47%|████▋     | 159/338 [05:39<14:32,  4.87s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "159 PreDiag_000462_000065_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 47%|████▋     | 160/338 [05:40<11:03,  3.73s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "160 PredictionDiagnostics_000176_000028_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 48%|████▊     | 161/338 [05:40<08:04,  2.74s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "161 PredictionDiagnostics_000126_000048_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (161, 'PredictionDiagnostics_000126_000048_structured.pkl')\n",
+      "162 PreDiag_000329_000185_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 48%|████▊     | 163/338 [05:44<07:15,  2.49s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "163 PreDiag_000423_0000F0_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 49%|████▊     | 164/338 [05:45<05:52,  2.03s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "164 PreDiag_000308_0001A0_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 49%|████▉     | 165/338 [05:45<04:39,  1.62s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "165 PreDiag_000265_0000D0_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 49%|████▉     | 166/338 [05:48<05:40,  1.98s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "166 PreDiag_000258_000219_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 50%|█████     | 169/338 [05:52<03:43,  1.32s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "167 PredictionDiagnostics_000121_000042_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (167, 'PredictionDiagnostics_000121_000042_structured.pkl')\n",
+      "168 PredictionDiagnostics_000168_000253_structured.pkl\n",
+      "169 PredictionDiagnostics_000183_000018_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 50%|█████     | 170/338 [05:52<02:59,  1.07s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "170 PreDiag_000282_00022F_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 51%|█████     | 171/338 [05:54<03:42,  1.33s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "171 PredictionDiagnostics_000128_000046_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (171, 'PredictionDiagnostics_000128_000046_structured.pkl')\n",
+      "172 PreDiag_000284_00022D_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 51%|█████     | 173/338 [06:00<05:46,  2.10s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "173 PreDiag_000421_000098_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 51%|█████▏    | 174/338 [06:01<04:34,  1.67s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "174 PredictionDiagnostics_000195_00024C_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 52%|█████▏    | 175/338 [06:02<04:35,  1.69s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "175 PreDiag_000281_000231_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 52%|█████▏    | 177/338 [06:04<03:19,  1.24s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "176 PredictionDiagnostics_000155_00001F_structured.pkl\n",
+      "177 PreDiag_000435_0000F7_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 53%|█████▎    | 178/338 [06:07<04:15,  1.60s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "178 PredictionDiagnostics_000114_00003C_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (178, 'PredictionDiagnostics_000114_00003C_structured.pkl')\n",
+      "179 PreDiag_000289_000235_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 53%|█████▎    | 180/338 [06:09<03:41,  1.40s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "180 PreDiag_000343_000175_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 54%|█████▎    | 181/338 [06:13<05:06,  1.95s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "181 PreDiag_000378_0001F9_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 54%|█████▍    | 182/338 [06:13<04:05,  1.57s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "182 PreDiag_000253_000212_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 54%|█████▍    | 183/338 [06:15<04:37,  1.79s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "183 PredictionDiagnostics_000133_00004D_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (183, 'PredictionDiagnostics_000133_00004D_structured.pkl')\n",
+      "184 PreDiag_000468_000068_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 55%|█████▍    | 185/338 [06:18<04:13,  1.66s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "185 PreDiag_000248_000202_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 55%|█████▌    | 186/338 [06:22<05:06,  2.01s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "186 PreDiag_000361_000162_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 55%|█████▌    | 187/338 [06:22<04:19,  1.72s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "187 PreDiag_000417_000094_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 56%|█████▌    | 189/338 [06:23<02:43,  1.10s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "188 PreDiag_000390_0001F4_structured.pkl\n",
+      "189 PreDiag_000414_000091_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 56%|█████▌    | 190/338 [06:24<02:30,  1.01s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "190 PreDiag_000352_00016B_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 57%|█████▋    | 192/338 [06:26<02:04,  1.18it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "191 PreDiag_000383_0001CB_structured.pkl\n",
+      "192 PreDiag_000347_000170_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 57%|█████▋    | 193/338 [06:28<03:07,  1.30s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "193 PreDiag_000247_000215_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 58%|█████▊    | 195/338 [06:29<02:09,  1.10it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "194 PreDiag_000398_0000C1_structured.pkl\n",
+      "195 PreDiag_000316_000194_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 58%|█████▊    | 196/338 [06:30<02:13,  1.07it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "196 PredictionDiagnostics_000113_0001C0_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (196, 'PredictionDiagnostics_000113_0001C0_structured.pkl')\n",
+      "197 PreDiag_000341_000177_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 59%|█████▊    | 198/338 [06:33<02:39,  1.14s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "198 PreDiag_000419_000096_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 59%|█████▉    | 199/338 [06:33<02:15,  1.03it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "199 PredictionDiagnostics_000108_0001BA_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (199, 'PredictionDiagnostics_000108_0001BA_structured.pkl')\n",
+      "200 PreDiag_000287_000128_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 59%|█████▉    | 201/338 [06:45<06:41,  2.93s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "201 PreDiag_000438_0000F9_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 60%|██████    | 203/338 [06:47<04:49,  2.15s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "202 PredictionDiagnostics_000144_00002E_structured.pkl\n",
+      "203 PreDiag_000345_000173_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 60%|██████    | 204/338 [06:52<06:32,  2.93s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "204 PreDiag_000444_0000FF_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 61%|██████    | 205/338 [06:55<06:09,  2.78s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "205 PredictionDiagnostics_000101_0001B2_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (205, 'PredictionDiagnostics_000101_0001B2_structured.pkl')\n",
+      "206 PreDiag_000485_0000E6_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 61%|██████    | 207/338 [06:57<04:26,  2.03s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "207 PreDiag_000389_0001F2_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 62%|██████▏   | 208/338 [06:58<03:44,  1.73s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "208 PreDiag_000344_000174_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 62%|██████▏   | 209/338 [07:03<05:34,  2.59s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "209 PreDiag_000260_0000C9_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 62%|██████▏   | 210/338 [07:11<08:30,  3.99s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "210 PreDiag_000325_000189_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 62%|██████▏   | 211/338 [07:11<06:22,  3.01s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "211 PredictionDiagnostics_000153_000025_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 63%|██████▎   | 212/338 [07:11<04:44,  2.25s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "212 PredictionDiagnostics_000192_000241_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 63%|██████▎   | 213/338 [07:13<04:29,  2.16s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "213 PredictionDiagnostics_000172_000257_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 63%|██████▎   | 214/338 [07:19<06:21,  3.07s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "214 PreDiag_000295_00015A_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 64%|██████▎   | 215/338 [07:21<05:38,  2.75s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "215 PreDiag_000427_0000E0_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 64%|██████▍   | 216/338 [07:22<04:34,  2.25s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "216 PreDiag_000464_0001C4_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 64%|██████▍   | 217/338 [07:23<04:03,  2.01s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "217 PreDiag_000351_00016C_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 64%|██████▍   | 218/338 [07:26<04:31,  2.26s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "218 PreDiag_000312_000198_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 65%|██████▍   | 219/338 [07:26<03:22,  1.70s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "219 PreDiag_000439_0000FA_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 65%|██████▌   | 221/338 [07:28<02:07,  1.09s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "220 PreDiag_000369_0001E7_structured.pkl\n",
+      "221 PreDiag_000241_000228_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 66%|██████▌   | 223/338 [07:31<02:34,  1.35s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "222 PreDiag_000382_0001CD_structured.pkl\n",
+      "223 PreDiag_000236_000220_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 66%|██████▋   | 224/338 [07:41<07:32,  3.97s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "224 PreDiag_000376_0001F8_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 67%|██████▋   | 225/338 [07:42<05:23,  2.86s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "225 PreDiag_000313_000197_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 67%|██████▋   | 226/338 [07:42<04:03,  2.18s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "226 PreDiag_000353_00016A_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 67%|██████▋   | 227/338 [07:49<06:48,  3.68s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "227 PreDiag_000327_000187_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 67%|██████▋   | 228/338 [07:50<04:58,  2.71s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "228 PreDiag_000399_000085_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 68%|██████▊   | 229/338 [07:50<03:37,  2.00s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "229 PreDiag_000221_00019D_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 68%|██████▊   | 231/338 [07:52<02:19,  1.30s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "230 PredictionDiagnostics_000169_000254_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (230, 'PredictionDiagnostics_000169_000254_structured.pkl')\n",
+      "231 PreDiag_000318_000192_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 69%|██████▊   | 232/338 [07:52<01:55,  1.09s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "232 PreDiag_000458_0001E3_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 69%|██████▉   | 233/338 [07:54<02:26,  1.40s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "233 PreDiag_000331_000183_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 69%|██████▉   | 234/338 [07:57<03:16,  1.89s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "234 PredictionDiagnostics_000130_000044_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (234, 'PredictionDiagnostics_000130_000044_structured.pkl')\n",
+      "235 PreDiag_000358_000165_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 70%|██████▉   | 236/338 [08:06<05:07,  3.02s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "236 PreDiag_000470_00006A_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 70%|███████   | 237/338 [08:08<04:25,  2.63s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "237 PreDiag_000424_0000E2_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 70%|███████   | 238/338 [08:08<03:36,  2.16s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "238 PreDiag_000484_0000E7_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 71%|███████   | 239/338 [08:12<04:17,  2.60s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "239 PreDiag_000395_00010E_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 71%|███████   | 240/338 [08:13<03:15,  2.00s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "240 PreDiag_000469_000069_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 71%|███████▏  | 241/338 [08:13<02:34,  1.59s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "241 PreDiag_000286_000232_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 72%|███████▏  | 242/338 [08:15<02:40,  1.67s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "242 PreDiag_000432_0000F3_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 72%|███████▏  | 243/338 [08:16<02:15,  1.43s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "243 PreDiag_000250_00020C_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 72%|███████▏  | 244/338 [08:17<02:06,  1.35s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "244 PredictionDiagnostics_000191_000249_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 72%|███████▏  | 245/338 [08:19<02:33,  1.65s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "245 PredictionDiagnostics_000182_00023C_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 73%|███████▎  | 246/338 [08:20<01:55,  1.26s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "246 PreDiag_000275_0000D6_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 73%|███████▎  | 247/338 [08:24<03:15,  2.15s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "247 PreDiag_000454_000109_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 73%|███████▎  | 248/338 [08:26<03:02,  2.03s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "248 PreDiag_000406_000089_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 74%|███████▎  | 249/338 [08:27<02:36,  1.76s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "249 PreDiag_000385_0001EC_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 74%|███████▍  | 250/338 [08:27<01:56,  1.33s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "250 PreDiag_000430_0000DD_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 74%|███████▍  | 251/338 [08:28<01:49,  1.26s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "251 PreDiag_000222_00019E_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 75%|███████▍  | 252/338 [08:31<02:32,  1.78s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "252 PredictionDiagnostics_000156_000023_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 75%|███████▍  | 253/338 [08:32<01:53,  1.33s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "253 PredictionDiagnostics_000124_000049_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (253, 'PredictionDiagnostics_000124_000049_structured.pkl')\n",
+      "254 PredictionDiagnostics_000184_000244_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 75%|███████▌  | 255/338 [08:37<02:42,  1.96s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "255 PreDiag_000431_0000DC_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 76%|███████▌  | 256/338 [08:39<02:46,  2.03s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "256 PreDiag_000467_000067_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 76%|███████▌  | 257/338 [08:41<02:32,  1.89s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "257 PreDiag_000403_000083_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 76%|███████▋  | 258/338 [08:42<02:18,  1.73s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "258 PreDiag_000422_000099_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 77%|███████▋  | 259/338 [08:42<01:46,  1.35s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "259 PreDiag_000235_00021E_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 77%|███████▋  | 260/338 [08:47<02:57,  2.28s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "260 PredictionDiagnostics_000180_00023D_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 77%|███████▋  | 261/338 [08:47<02:12,  1.72s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "261 PredictionDiagnostics_000143_000030_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (261, 'PredictionDiagnostics_000143_000030_structured.pkl')\n",
+      "262 PreDiag_000354_000169_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 78%|███████▊  | 263/338 [08:55<03:13,  2.58s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "263 PreDiag_000321_00018C_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 78%|███████▊  | 264/338 [08:57<03:02,  2.47s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "264 PreDiag_000481_0000EA_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 79%|███████▊  | 266/338 [08:58<01:51,  1.55s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "265 PreDiag_000381_0001CA_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (265, 'PreDiag_000381_0001CA_structured.pkl')\n",
+      "266 PreDiag_000441_0000FC_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 79%|███████▉  | 268/338 [09:00<01:33,  1.34s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "267 PreDiag_000365_0001F0_structured.pkl\n",
+      "268 PreDiag_000476_0000EE_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 80%|███████▉  | 269/338 [09:02<01:38,  1.43s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "269 PreDiag_000442_0000FD_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 80%|███████▉  | 270/338 [09:03<01:27,  1.29s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "270 PreDiag_000475_000070_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 80%|████████  | 271/338 [09:05<01:31,  1.37s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "271 PreDiag_000460_0001C7_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 80%|████████  | 272/338 [09:05<01:15,  1.14s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "272 PredictionDiagnostics_000146_000036_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (272, 'PredictionDiagnostics_000146_000036_structured.pkl')\n",
+      "273 PreDiag_000269_0000D9_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 81%|████████  | 274/338 [09:06<00:49,  1.28it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "274 PreDiag_000196_00020B_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 81%|████████▏ | 275/338 [09:07<00:55,  1.14it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "275 PreDiag_000479_0000ED_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 82%|████████▏ | 276/338 [09:10<01:31,  1.47s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "276 PredictionDiagnostics_000120_000041_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (276, 'PredictionDiagnostics_000120_000041_structured.pkl')\n",
+      "277 PreDiag_000428_0000DF_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 82%|████████▏ | 278/338 [09:12<01:07,  1.12s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "278 PredictionDiagnostics_000136_00002D_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 83%|████████▎ | 279/338 [09:12<01:01,  1.04s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "279 PreDiag_000408_00008B_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 83%|████████▎ | 280/338 [09:13<01:01,  1.05s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "280 PreDiag_000437_000071_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 83%|████████▎ | 281/338 [09:15<01:11,  1.25s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "281 PreDiag_000285_000230_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 83%|████████▎ | 282/338 [09:25<03:18,  3.54s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "282 PreDiag_000326_000188_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 84%|████████▎ | 283/338 [09:25<02:27,  2.68s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "283 PreDiag_000402_000087_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 84%|████████▍ | 284/338 [09:27<02:05,  2.33s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "284 PreDiag_000360_000163_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 84%|████████▍ | 285/338 [09:28<01:42,  1.93s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "285 PreDiag_000450_000105_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 85%|████████▍ | 286/338 [09:30<01:46,  2.05s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "286 PreDiag_000483_0000E8_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 85%|████████▍ | 287/338 [09:32<01:46,  2.08s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "287 PredictionDiagnostics_000107_0001B9_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (287, 'PredictionDiagnostics_000107_0001B9_structured.pkl')\n",
+      "288 PreDiag_000451_000106_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 86%|████████▌ | 289/338 [09:34<01:18,  1.61s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "289 PredictionDiagnostics_000139_000034_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (289, 'PredictionDiagnostics_000139_000034_structured.pkl')\n",
+      "290 PreDiag_000262_0000C7_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 86%|████████▌ | 291/338 [09:39<01:27,  1.87s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "291 PredictionDiagnostics_000150_00003B_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 86%|████████▋ | 292/338 [09:39<01:10,  1.54s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "292 PreDiag_000256_000216_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 87%|████████▋ | 294/338 [09:40<00:44,  1.01s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "293 PredictionDiagnostics_000165_000245_structured.pkl\n",
+      "294 PredictionDiagnostics_000167_000255_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 87%|████████▋ | 295/338 [09:40<00:34,  1.25it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "295 PreDiag_000268_0000D8_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 88%|████████▊ | 296/338 [09:40<00:28,  1.50it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "296 PredictionDiagnostics_000173_000248_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 88%|████████▊ | 297/338 [09:43<00:46,  1.12s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "297 PreDiag_000323_00018B_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 88%|████████▊ | 298/338 [09:43<00:37,  1.06it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "298 PreDiag_000410_00008D_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 88%|████████▊ | 299/338 [09:44<00:33,  1.18it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "299 PreDiag_000239_000224_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 89%|████████▉ | 300/338 [09:57<02:48,  4.43s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "300 notes.txt\n",
+      "301 PreDiag_000373_0001DA_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (301, 'PreDiag_000373_0001DA_structured.pkl')\n",
+      "302 PreDiag_000233_00021F_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 90%|████████▉ | 303/338 [09:59<01:23,  2.38s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "303 PreDiag_000478_000200_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 90%|████████▉ | 304/338 [10:01<01:14,  2.20s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "304 PredictionDiagnostics_000105_0001B5_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (304, 'PredictionDiagnostics_000105_0001B5_structured.pkl')\n",
+      "305 PreDiag_000296_00270E_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 91%|█████████ | 306/338 [10:01<00:48,  1.50s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "306 PreDiag_000310_00019A_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 91%|█████████ | 308/338 [10:02<00:29,  1.00it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "307 PreDiag_000379_000061_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (307, 'PreDiag_000379_000061_structured.pkl')\n",
+      "308 PredictionDiagnostics_000104_0001B4_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (308, 'PredictionDiagnostics_000104_0001B4_structured.pkl')\n",
+      "309 PreDiag_000349_00016E_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 92%|█████████▏| 311/338 [10:03<00:16,  1.65it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "310 PredictionDiagnostics_000171_000027_structured.pkl\n",
+      "311 PredictionDiagnostics_000112_0001BF_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (311, 'PredictionDiagnostics_000112_0001BF_structured.pkl')\n",
+      "312 PreDiag_000459_0001C8_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 93%|█████████▎| 313/338 [10:05<00:21,  1.18it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "313 PreDiag_000357_000166_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 93%|█████████▎| 314/338 [10:16<01:12,  3.00s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "314 PreDiag_000307_000150_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 93%|█████████▎| 315/338 [10:16<00:55,  2.42s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "315 PreDiag_000474_00006F_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 93%|█████████▎| 316/338 [10:19<00:52,  2.40s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "316 PreDiag_000348_00016F_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 94%|█████████▍| 317/338 [10:20<00:46,  2.21s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "317 PreDiag_000364_00015F_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 95%|█████████▍| 320/338 [10:22<00:20,  1.17s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "318 PredictionDiagnostics_000118_00003F_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (318, 'PredictionDiagnostics_000118_00003F_structured.pkl')\n",
+      "319 PreDiag_000386_0001EE_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (319, 'PreDiag_000386_0001EE_structured.pkl')\n",
+      "320 PredictionDiagnostics_000117_00003E_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (320, 'PredictionDiagnostics_000117_00003E_structured.pkl')\n",
+      "321 PredictionDiagnostics_000102_0001B1_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (321, 'PredictionDiagnostics_000102_0001B1_structured.pkl')\n",
+      "322 PreDiag_000338_00017A_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 96%|█████████▌| 323/338 [10:29<00:26,  1.74s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "323 PredictionDiagnostics_000189_00023F_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 96%|█████████▌| 324/338 [10:30<00:22,  1.58s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "324 PreDiag_000426_0000E1_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 96%|█████████▌| 325/338 [10:31<00:18,  1.42s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "325 PreDiag_000274_0000D7_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 96%|█████████▋| 326/338 [10:32<00:16,  1.37s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "326 PreDiag_000208_000206_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 97%|█████████▋| 327/338 [10:34<00:16,  1.49s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "327 PreDiag_000416_000093_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 97%|█████████▋| 328/338 [10:35<00:12,  1.26s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "328 PreDiag_000480_0000EC_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 97%|█████████▋| 329/338 [10:37<00:13,  1.51s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "329 PreDiag_000337_00017B_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 98%|█████████▊| 330/338 [10:39<00:14,  1.82s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "330 PreDiag_000429_0000DE_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 98%|█████████▊| 331/338 [10:41<00:11,  1.66s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "331 PredictionDiagnostics_000159_000250_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 98%|█████████▊| 332/338 [10:41<00:07,  1.25s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "332 PreDiag_000280_000233_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 99%|█████████▊| 333/338 [10:41<00:04,  1.02it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "333 PreDiag_000466_000066_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 99%|█████████▉| 334/338 [10:42<00:03,  1.15it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "334 PreDiag_000309_00019B_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 99%|█████████▉| 335/338 [10:42<00:02,  1.41it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "335 PreDiag_000277_0000D3_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      " 99%|█████████▉| 336/338 [10:44<00:01,  1.06it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "336 PredictionDiagnostics_000119_000040_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (336, 'PredictionDiagnostics_000119_000040_structured.pkl')\n",
+      "337 PreDiag_000391_00010A_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████| 338/338 [10:44<00:00,  1.91s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CACHED data is loaded.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "# read CACHED data \n",
+    "# excluding all diagnostic cycles and those with increase in discharge cap, renumber based on EFC\n",
+    "cycle_window_size = 100\n",
+    "skip_window_after_diagnostic = 50\n",
+    "structured_data_list = []\n",
+    "summary_data_list = []\n",
+    "nominal_cell_capacity = 4.83\n",
+    "for i,cell_file in enumerate(tqdm(os.listdir('CACHED_DATA/pre_processed_pandas/'))):\n",
+    "    print(i, cell_file)\n",
+    "    if cell_file.startswith(\"Pre\"):\n",
+    "        with open(f'CACHED_DATA/pre_processed_pandas/{cell_file}', 'rb') as f:\n",
+    "            structured_data, summary_data = pickle.load(f)\n",
+    "#         a = find_renumbedred_index(structured_data)\n",
+    "#         print(len(summary_data[0]))\n",
+    "#         break\n",
+    "#         equivalent_cycle_index = summary_data[0]['charge_throughput']/nominal_cell_capacity\n",
+    "#         summary_data[0]['cycle_index'] = equivalent_cycle_index\n",
+    "#         print(summary_data[0]['cycle_index'])\n",
+    "#         print(len(summary_data[0]))\n",
+    "        summary_data[0], cycle_indices_dropped = decrease_monotonically(summary_data[0])\n",
+    "#         print(len(summary_data[0]))\n",
+    "        # getting equivalent cycle index\n",
+    "\n",
+    "#         break\n",
+    "#         print(len(summary_data[0]))\n",
+    "#         skipped_cycles = [list(range(m+1,m+skip_window_after_diagnostic+1)) for m in a]\n",
+    "#         flatten_skipped_cycles = [x for xs in skipped_cycles for x in xs]\n",
+    "        # check if the cell has enough cycles based on the $window_cycles_size\n",
+    "        if len(summary_data[0]) >= cycle_window_size * 2:\n",
+    "            cycle_list = []\n",
+    "            new_cycle_indices = []\n",
+    "            j = 0\n",
+    "            for cycle in structured_data:\n",
+    "                if len(cycle) > 2:\n",
+    "                    cycle_index_value = np.unique(cycle['cycle_index'])[0]\n",
+    "                    if  cycle_index_value not in cycle_indices_dropped:\n",
+    "                        cycle.loc[:,'cycle_index'] = j\n",
+    "                        cycle_list.append(cycle)\n",
+    "                        new_cycle_indices.append(j)\n",
+    "                        j += 1\n",
+    "#                 else:\n",
+    "#                     print(f'TIME-SERIES THRESHOLD ALEERT FOR {i, cell_file}')\n",
+    "            structured_data_list.append(cycle_list)\n",
+    "#             summary_data[0][summary_data[0]['summary_data[0]'] != flatten_skipped_cycles]\n",
+    "#             summary_data[0] = summary_data[0][~summary_data[0]['cycle_index'].isin(flatten_skipped_cycles)]\n",
+    "#             summary_data[0]['cycle_index'] = new_cycle_indices\n",
+    "            summary_data_list.append(summary_data[0])\n",
+    "#             print(len(summary_data_list[i]), len(structured_data_list[i]))\n",
+    "        else:\n",
+    "            print(f'NUMBER OF CYCLES THRESHOLD ALEERT FOR {i, cell_file}')\n",
+    "#         dat.append(cell_data)\n",
+    "#     if i ==2:\n",
+    "#         break\n",
+    "print('CACHED data is loaded.')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 566,
+   "id": "c8c2c1bd",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  0%|          | 0/338 [00:00<?, ?it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0 PreDiag_000333_000180_structured.pkl\n",
+      "[0, 30, 230, 430, 630, 830, 1030, 1230, 1430, 1630, 1830, 1982]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  0%|          | 1/338 [00:02<13:47,  2.45s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1 PredictionDiagnostics_000131_00004B_structured.pkl\n",
+      "[0, 30, 130, 132]\n",
+      "2 PreDiag_000314_000196_structured.pkl\n",
+      "[0, 30, 130, 230, 330, 430, 530, 630, 730, 830, 930, 1030, 1032]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  1%|          | 2/338 [00:03<10:20,  1.85s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CACHED data is loaded.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "# read CACHED data \n",
+    "# excluding all diagnostic cycles and few cycles after them then renumbering cycle_index.\n",
+    "cycle_window_size = 40\n",
+    "skip_window_after_diagnostic = 50\n",
+    "structured_data_list = []\n",
+    "summary_data_list = []\n",
+    "for i,cell_file in enumerate(tqdm(os.listdir('CACHED_DATA/pre_processed_pandas/'))):\n",
+    "    print(i, cell_file)\n",
+    "    if cell_file.startswith(\"Pre\"):\n",
+    "        with open(f'CACHED_DATA/pre_processed_pandas/{cell_file}', 'rb') as f:\n",
+    "            structured_data, summary_data = pickle.load(f)\n",
+    "        a = find_renumbedred_index(structured_data)\n",
+    "        print(a)\n",
+    "        skipped_cycles = [list(range(m+1,m+skip_window_after_diagnostic+1)) for m in a]\n",
+    "        flatten_skipped_cycles = [x for xs in skipped_cycles for x in xs]\n",
+    "        # check if the cell has enough cycles based on the $window_cycles_size\n",
+    "        if len(summary_data[0]) >= cycle_window_size * 2:\n",
+    "            cycle_list = []\n",
+    "            new_cycle_indices = []\n",
+    "            j = 0\n",
+    "            for cycle in structured_data:\n",
+    "                cycle_index_value = np.unique(cycle['cycle_index'])[0]\n",
+    "                if len(cycle) > 2 and cycle_index_value not in flatten_skipped_cycles:\n",
+    "                    cycle.loc[:,'cycle_index'] = j\n",
+    "                    cycle_list.append(cycle)\n",
+    "                    new_cycle_indices.append(j)\n",
+    "                    j += 1\n",
+    "#                 else:\n",
+    "#                     print(f'TIME-SERIES THRESHOLD ALEERT FOR {i, cell_file}')\n",
+    "            structured_data_list.append(cycle_list)\n",
+    "#             summary_data[0][summary_data[0]['summary_data[0]'] != flatten_skipped_cycles]\n",
+    "            summary_data[0] = summary_data[0][~summary_data[0]['cycle_index'].isin(flatten_skipped_cycles)]\n",
+    "            summary_data[0]['cycle_index'] = new_cycle_indices\n",
+    "            summary_data_list.append(summary_data[0])\n",
+    "        else:\n",
+    "            print(f'NUMBER OF CYCLES THRESHOLD ALEERT FOR {i, cell_file}')\n",
+    "#         dat.append(cell_data)\n",
+    "    if i ==2:\n",
+    "        break\n",
+    "print('CACHED data is loaded.')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1133,
+   "id": "b7b6df89",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  0%|          | 0/338 [00:00<?, ?it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0 PreDiag_000333_000180_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  0%|          | 1/338 [00:03<18:46,  3.34s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1 PredictionDiagnostics_000131_00004B_structured.pkl\n",
+      "NUMBER OF CYCLES THRESHOLD ALEERT FOR (1, 'PredictionDiagnostics_000131_00004B_structured.pkl')\n",
+      "2 PreDiag_000314_000196_structured.pkl\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "  1%|          | 2/338 [00:04<12:05,  2.16s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CACHED data is loaded.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "# read CACHED data \n",
+    "# excluding all diagnostic cycles and those with increase in discharge cap\n",
+    "cycle_window_size = 100\n",
+    "skip_window_after_diagnostic = 50\n",
+    "structured_data_list = []\n",
+    "summary_data_list = []\n",
+    "for i,cell_file in enumerate(tqdm(os.listdir('CACHED_DATA/pre_processed_pandas/'))):\n",
+    "    print(i, cell_file)\n",
+    "    if cell_file.startswith(\"Pre\"):\n",
+    "        with open(f'CACHED_DATA/pre_processed_pandas/{cell_file}', 'rb') as f:\n",
+    "            structured_data, summary_data = pickle.load(f)\n",
+    "#         a = find_renumbedred_index(structured_data)\n",
+    "#         print(len(summary_data[0]))\n",
+    "        summary_data[0], cycle_indices_dropped = decrease_monotonically(summary_data[0])\n",
+    "#         print(len(summary_data[0]))\n",
+    "#         skipped_cycles = [list(range(m+1,m+skip_window_after_diagnostic+1)) for m in a]\n",
+    "#         flatten_skipped_cycles = [x for xs in skipped_cycles for x in xs]\n",
+    "        # check if the cell has enough cycles based on the $window_cycles_size\n",
+    "        if len(summary_data[0]) >= cycle_window_size * 2:\n",
+    "            cycle_list = []\n",
+    "            new_cycle_indices = []\n",
+    "            j = 0\n",
+    "            for cycle in structured_data:\n",
+    "                if len(cycle) > 2:\n",
+    "                    cycle_index_value = np.unique(cycle['cycle_index'])[0]\n",
+    "                    if  cycle_index_value not in cycle_indices_dropped:\n",
+    "                        cycle.loc[:,'cycle_index'] = j\n",
+    "                        cycle_list.append(cycle)\n",
+    "                        new_cycle_indices.append(j)\n",
+    "                        j += 1\n",
+    "#                 else:\n",
+    "#                     print(f'TIME-SERIES THRESHOLD ALEERT FOR {i, cell_file}')\n",
+    "            structured_data_list.append(cycle_list)\n",
+    "#             summary_data[0][summary_data[0]['summary_data[0]'] != flatten_skipped_cycles]\n",
+    "#             summary_data[0] = summary_data[0][~summary_data[0]['cycle_index'].isin(flatten_skipped_cycles)]\n",
+    "#             summary_data[0]['cycle_index'] = new_cycle_indices\n",
+    "            summary_data_list.append(summary_data[0])\n",
+    "        else:\n",
+    "            print(f'NUMBER OF CYCLES THRESHOLD ALEERT FOR {i, cell_file}')\n",
+    "#         dat.append(cell_data)\n",
+    "    if i ==2:\n",
+    "        break\n",
+    "print('CACHED data is loaded.')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 77,
+   "id": "ebd27418",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>cycle_index</th>\n",
+       "      <th>discharge_capacity</th>\n",
+       "      <th>charge_capacity</th>\n",
+       "      <th>discharge_energy</th>\n",
+       "      <th>charge_energy</th>\n",
+       "      <th>charge_throughput</th>\n",
+       "      <th>energy_throughput</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>4.735778</td>\n",
+       "      <td>4.534594</td>\n",
+       "      <td>17.373621</td>\n",
+       "      <td>17.351986</td>\n",
+       "      <td>4.534595</td>\n",
+       "      <td>17.351986</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>4.418770</td>\n",
+       "      <td>4.292343</td>\n",
+       "      <td>15.932717</td>\n",
+       "      <td>16.700058</td>\n",
+       "      <td>8.826938</td>\n",
+       "      <td>34.052044</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2</td>\n",
+       "      <td>4.414213</td>\n",
+       "      <td>4.412000</td>\n",
+       "      <td>15.915223</td>\n",
+       "      <td>17.147264</td>\n",
+       "      <td>13.238937</td>\n",
+       "      <td>51.199306</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>3</td>\n",
+       "      <td>4.411719</td>\n",
+       "      <td>4.410510</td>\n",
+       "      <td>15.905056</td>\n",
+       "      <td>17.140506</td>\n",
+       "      <td>17.649448</td>\n",
+       "      <td>68.339813</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>4</td>\n",
+       "      <td>4.406859</td>\n",
+       "      <td>4.407058</td>\n",
+       "      <td>15.884789</td>\n",
+       "      <td>17.126206</td>\n",
+       "      <td>22.056505</td>\n",
+       "      <td>85.466019</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>422</th>\n",
+       "      <td>308</td>\n",
+       "      <td>0.140919</td>\n",
+       "      <td>0.142851</td>\n",
+       "      <td>0.477259</td>\n",
+       "      <td>0.599984</td>\n",
+       "      <td>710.446533</td>\n",
+       "      <td>2842.571289</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>423</th>\n",
+       "      <td>309</td>\n",
+       "      <td>0.139951</td>\n",
+       "      <td>0.142027</td>\n",
+       "      <td>0.474333</td>\n",
+       "      <td>0.596522</td>\n",
+       "      <td>710.588562</td>\n",
+       "      <td>2843.167725</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>426</th>\n",
+       "      <td>310</td>\n",
+       "      <td>0.138042</td>\n",
+       "      <td>0.140872</td>\n",
+       "      <td>0.468451</td>\n",
+       "      <td>0.591672</td>\n",
+       "      <td>711.012268</td>\n",
+       "      <td>2844.947510</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>428</th>\n",
+       "      <td>311</td>\n",
+       "      <td>0.137813</td>\n",
+       "      <td>0.139228</td>\n",
+       "      <td>0.467678</td>\n",
+       "      <td>0.584768</td>\n",
+       "      <td>711.290955</td>\n",
+       "      <td>2846.118164</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>429</th>\n",
+       "      <td>312</td>\n",
+       "      <td>0.137296</td>\n",
+       "      <td>0.138872</td>\n",
+       "      <td>0.466132</td>\n",
+       "      <td>0.583270</td>\n",
+       "      <td>711.429871</td>\n",
+       "      <td>2846.701416</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>313 rows × 7 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     cycle_index  discharge_capacity  charge_capacity  discharge_energy  \\\n",
+       "0              0            4.735778         4.534594         17.373621   \n",
+       "1              1            4.418770         4.292343         15.932717   \n",
+       "2              2            4.414213         4.412000         15.915223   \n",
+       "3              3            4.411719         4.410510         15.905056   \n",
+       "4              4            4.406859         4.407058         15.884789   \n",
+       "..           ...                 ...              ...               ...   \n",
+       "422          308            0.140919         0.142851          0.477259   \n",
+       "423          309            0.139951         0.142027          0.474333   \n",
+       "426          310            0.138042         0.140872          0.468451   \n",
+       "428          311            0.137813         0.139228          0.467678   \n",
+       "429          312            0.137296         0.138872          0.466132   \n",
+       "\n",
+       "     charge_energy  charge_throughput  energy_throughput  \n",
+       "0        17.351986           4.534595          17.351986  \n",
+       "1        16.700058           8.826938          34.052044  \n",
+       "2        17.147264          13.238937          51.199306  \n",
+       "3        17.140506          17.649448          68.339813  \n",
+       "4        17.126206          22.056505          85.466019  \n",
+       "..             ...                ...                ...  \n",
+       "422       0.599984         710.446533        2842.571289  \n",
+       "423       0.596522         710.588562        2843.167725  \n",
+       "426       0.591672         711.012268        2844.947510  \n",
+       "428       0.584768         711.290955        2846.118164  \n",
+       "429       0.583270         711.429871        2846.701416  \n",
+       "\n",
+       "[313 rows x 7 columns]"
+      ]
+     },
+     "execution_count": 77,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "summary_data_list[-1]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 757,
+   "id": "7c88275f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>voltage</th>\n",
+       "      <th>current</th>\n",
+       "      <th>cycle_index</th>\n",
+       "      <th>discharge_capacity</th>\n",
+       "      <th>charge_capacity</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>429118</th>\n",
+       "      <td>2.700801</td>\n",
+       "      <td>-2.419913</td>\n",
+       "      <td>312</td>\n",
+       "      <td>0.137183</td>\n",
+       "      <td>0.138872</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>429119</th>\n",
+       "      <td>2.702502</td>\n",
+       "      <td>-2.419886</td>\n",
+       "      <td>312</td>\n",
+       "      <td>0.136992</td>\n",
+       "      <td>0.138872</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>429120</th>\n",
+       "      <td>2.704204</td>\n",
+       "      <td>-2.419752</td>\n",
+       "      <td>312</td>\n",
+       "      <td>0.136809</td>\n",
+       "      <td>0.138872</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>429121</th>\n",
+       "      <td>2.705906</td>\n",
+       "      <td>-2.419617</td>\n",
+       "      <td>312</td>\n",
+       "      <td>0.136625</td>\n",
+       "      <td>0.138872</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>429122</th>\n",
+       "      <td>2.707608</td>\n",
+       "      <td>-2.419547</td>\n",
+       "      <td>312</td>\n",
+       "      <td>0.136440</td>\n",
+       "      <td>0.138872</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>429877</th>\n",
+       "      <td>3.992392</td>\n",
+       "      <td>-2.424505</td>\n",
+       "      <td>312</td>\n",
+       "      <td>0.000037</td>\n",
+       "      <td>0.138872</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>429878</th>\n",
+       "      <td>3.994094</td>\n",
+       "      <td>-2.424723</td>\n",
+       "      <td>312</td>\n",
+       "      <td>0.000033</td>\n",
+       "      <td>0.138872</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>429879</th>\n",
+       "      <td>3.995796</td>\n",
+       "      <td>-2.424941</td>\n",
+       "      <td>312</td>\n",
+       "      <td>0.000029</td>\n",
+       "      <td>0.138872</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>429880</th>\n",
+       "      <td>3.997498</td>\n",
+       "      <td>-2.425158</td>\n",
+       "      <td>312</td>\n",
+       "      <td>0.000025</td>\n",
+       "      <td>0.138872</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>429881</th>\n",
+       "      <td>3.999199</td>\n",
+       "      <td>-2.425376</td>\n",
+       "      <td>312</td>\n",
+       "      <td>0.000021</td>\n",
+       "      <td>0.138872</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>764 rows × 5 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       "429118  2.700801 -2.419913          312            0.137183         0.138872\n",
+       "429119  2.702502 -2.419886          312            0.136992         0.138872\n",
+       "429120  2.704204 -2.419752          312            0.136809         0.138872\n",
+       "429121  2.705906 -2.419617          312            0.136625         0.138872\n",
+       "429122  2.707608 -2.419547          312            0.136440         0.138872\n",
+       "...          ...       ...          ...                 ...              ...\n",
+       "429877  3.992392 -2.424505          312            0.000037         0.138872\n",
+       "429878  3.994094 -2.424723          312            0.000033         0.138872\n",
+       "429879  3.995796 -2.424941          312            0.000029         0.138872\n",
+       "429880  3.997498 -2.425158          312            0.000025         0.138872\n",
+       "429881  3.999199 -2.425376          312            0.000021         0.138872\n",
+       "\n",
+       "[764 rows x 5 columns]"
+      ]
+     },
+     "execution_count": 757,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "structured_data_list[-1][-1]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1162,
+   "id": "3c31cb67",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'Discharge capacity (Ah/Wh)')"
+      ]
+     },
+     "execution_count": 1162,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1800x1200 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(dpi=300, facecolor='white')\n",
+    "for i,c in enumerate(summary_data_list):\n",
+    "    plt.scatter(c['cycle_index'], c['discharge_capacity'], \n",
+    "                s=0.1, color=f'C{i}', label='actual cycle_index', alpha=0.3)\n",
+    "plt.xlabel('Cycle index')\n",
+    "plt.ylabel('Discharge capacity (Ah/Wh)')\n",
+    "# plt.savefig(f'dc_vs_cycle_index_dropped.png', dpi=400, transparent=False)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1163,
+   "id": "0a8409d5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x7efb5e172a30>"
+      ]
+     },
+     "execution_count": 1163,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(dpi =200)\n",
+    "plt.scatter(test['cycle_index'], test['discharge_capacity'], \n",
+    "            s=0.1, color='C2', alpha=0.5, label='Monotonically decreasing')\n",
+    "plt.scatter(cell_summary['cycle_index'], cell_summary['discharge_capacity'], \n",
+    "            s=0.1, color='C1', alpha=0.5, label='Raw from Structured_summary')\n",
+    "plt.legend()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "370a0f3e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[30,\n",
+       " 36,\n",
+       " 128,\n",
+       " 130,\n",
+       " 209,\n",
+       " 230,\n",
+       " 231,\n",
+       " 290,\n",
+       " 291,\n",
+       " 294,\n",
+       " 295,\n",
+       " 298,\n",
+       " 299,\n",
+       " 311,\n",
+       " 313,\n",
+       " 314,\n",
+       " 315,\n",
+       " 332,\n",
+       " 334,\n",
+       " 352,\n",
+       " 354,\n",
+       " 357,\n",
+       " 358,\n",
+       " 360,\n",
+       " 361,\n",
+       " 367,\n",
+       " 368,\n",
+       " 374,\n",
+       " 375,\n",
+       " 377,\n",
+       " 378,\n",
+       " 380,\n",
+       " 381,\n",
+       " 383,\n",
+       " 385,\n",
+       " 389,\n",
+       " 390,\n",
+       " 392,\n",
+       " 394,\n",
+       " 397,\n",
+       " 398,\n",
+       " 401,\n",
+       " 402,\n",
+       " 414,\n",
+       " 415,\n",
+       " 418,\n",
+       " 420,\n",
+       " 423,\n",
+       " 425,\n",
+       " 426,\n",
+       " 427,\n",
+       " 429,\n",
+       " 430,\n",
+       " 431]"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "def find_renumbedred_index(cell):\n",
+    "    '''This function finds the renumbered index for the cycles that are followed by a diagnostic cycle'''\n",
+    "    renumbered_index_for_cycle_following_a_diagnostic_cycle = []\n",
+    "    i = 0\n",
+    "    for k,cycle in enumerate(cell):\n",
+    "        actual_cycle_index = np.unique(cycle['cycle_index'])[0]\n",
+    "#         print(i, actual_cycle_index)\n",
+    "        if actual_cycle_index != i:\n",
+    "            renumbered_index_for_cycle_following_a_diagnostic_cycle.append(k-1)\n",
+    "            i = actual_cycle_index\n",
+    "        i += 1\n",
+    "#     print(i, actual_cycle_index)\n",
+    "    return renumbered_index_for_cycle_following_a_diagnostic_cycle\n",
+    "find_renumbedred_index(structured_data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 452,
+   "id": "438cfb98",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# plt.figure(dpi=300, facecolor='white')\n",
+    "# for i,d in enumerate(summary_data_list):\n",
+    "#     plt.scatter(d['cycle_index'], d['discharge_capacity'], s=0.03, color=f'C{i}', alpha=0.2)\n",
+    "# #     break\n",
+    "# plt.xlabel('Cycle index')\n",
+    "# plt.ylabel('Discharge capacity (Ah/Wh)')\n",
+    "# plt.savefig(f'dc_vs_cycle_index.png', dpi=400, transparent=False)\n",
+    "# plt.figure(dpi=300, facecolor='white')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3458ff7d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1165,
+   "id": "714ae578",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x7efb143488b0>"
+      ]
+     },
+     "execution_count": 1165,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1800x1200 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(dpi=300)\n",
+    "# cell_summary_rmeoved_d_cycles_50 = summary_data_list[2]\n",
+    "# cell_summary_rmeoved_d_cycles_30 = summary_data_list[2]\n",
+    "cell_summary_rmeoved_d_cycles_50 = summary_data_list[2]\n",
+    "# plt.scatter(cell_summary['cycle_index'], cell_summary['discharge_capacity'], \n",
+    "#             s=0.1, color='C2', alpha=1, label='Skip window after diagnostic: None')\n",
+    "plt.scatter(cell_summary_rmeoved_d_cycles_30['cycle_index'], cell_summary_rmeoved_d_cycles_30['discharge_capacity'], \n",
+    "            s=0.1, color='C3', alpha=1, label='Skip window after diagnostic: 30')\n",
+    "plt.scatter(cell_summary_rmeoved_d_cycles_50['cycle_index'], cell_summary_rmeoved_d_cycles_50['discharge_capacity'], \n",
+    "            s=0.1, color='C1', alpha=1, label='Skip window after diagnostic: 50')\n",
+    "\n",
+    "plt.legend()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "a0487e6e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from beep.structure.cli import auto_load_processed\n",
+    "cell_1 = auto_load_processed('/home/ec2-user/SageMaker/data_cache/structure/PreDiag_000314_000196_structured.json.gz')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "2dc58cb2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x7ff2f00dc820>"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 900x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(dpi=150)\n",
+    "plt.scatter(cell_1.structured_summary['cycle_index'], cell_1.structured_summary['discharge_capacity'], \n",
+    "            s=0.1, color='C0', label='actual cycle_index')\n",
+    "plt.scatter(list(range(len(cell_1.structured_summary['discharge_capacity']))), cell_1.structured_summary['discharge_capacity'], \n",
+    "            s=0.1, color='C2', label='Renumbered cycle_index')\n",
+    "plt.xlabel('cycle index')\n",
+    "plt.ylabel('Discharge capacity')\n",
+    "plt.legend()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "75228dd4",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████| 336/336 [05:30<00:00,  1.02it/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# def find_slope(cycle_window_label):\n",
+    "#     mid_window_index = len(cycle_window_label)//2\n",
+    "#     low = np.array(cycle_window_label)[0]\n",
+    "#     mid = np.array(cycle_window_label)[mid_window_index]\n",
+    "#     high = np.array(cycle_window_label)[-1]\n",
+    "#     slope_1 = (mid[1] - low[1]) / (mid[0] - low[0]) \n",
+    "#     slope_2 = (high[1] - mid[1]) / (high[0] - mid[0]) \n",
+    "#     return slope_1, slope_2\n",
+    "\n",
+    "# features_columns = ['cycle_index','voltage', 'current']\n",
+    "# label_columns = ['cycle_index', 'discharge_capacity']\n",
+    "# # features = np.empty([0, None,100, 3])\n",
+    "# cycle_numbers = 20\n",
+    "# monitored_cycles_discharge_capacity = []\n",
+    "# labels = np.empty([0, 2])\n",
+    "# cell_features = []\n",
+    "# cell_labels = []\n",
+    "# for i, cell in enumerate(tqdm(structured_data_list)):\n",
+    "#     n = len(cell)//cycle_numbers\n",
+    "#     cycle_window_features = []\n",
+    "#     cycle_window_labels = []\n",
+    "#     cell_cycle_indices = summary_data_list[i]['cycle_index'].values\n",
+    "# #     for cycle in cell:\n",
+    "#     for j in range(n-1): \n",
+    "#         cycle_window_features.append([np.array(cell[c][features_columns]) for c in list(range(cycle_numbers*j,cycle_numbers*(j+1)))])\n",
+    "# #         cycle_window_features.append(np.array(cell[0][features_columns])) # [cycle_numbers*j:cycle_numbers*(j+1)]\n",
+    "#         discharge_cap_cycle_window = summary_data_list[i][label_columns][cycle_numbers*(j+1):cycle_numbers*(j+2)]\n",
+    "#         cycle_window_labels.append(find_slope(discharge_cap_cycle_window))\n",
+    "# #         cycle_window_labels.append(discharge_cap_cycle_window)\n",
+    "#     cell_features.append(cycle_window_features)\n",
+    "#     cell_labels.append(cycle_window_labels)\n",
+    "#     break"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1171,
+   "id": "59b22eef",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1984"
+      ]
+     },
+     "execution_count": 1171,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(structured_data_list[0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1172,
+   "id": "521dbb2c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1149"
+      ]
+     },
+     "execution_count": 1172,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(summary_data_list[0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "bdb4cec4",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████| 282/282 [03:28<00:00,  1.35it/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "def find_slope(cycle_window_label):\n",
+    "    mid_window_index = len(cycle_window_label)//2\n",
+    "    low = np.array(cycle_window_label)[0]\n",
+    "    mid = np.array(cycle_window_label)[mid_window_index]\n",
+    "    high = np.array(cycle_window_label)[-1]\n",
+    "    slope_1 = (mid[1] - low[1]) / (mid[0] - low[0]) # mid_window_index #\n",
+    "    slope_2 = (high[1] - mid[1]) / (mid[0] - low[0]) # mid_window_index\n",
+    "    return slope_1, slope_2\n",
+    "\n",
+    "skip_diagnostic_in_window = True\n",
+    "\n",
+    "features_columns = ['cycle_index','voltage', 'current']\n",
+    "label_columns = ['cycle_index', 'discharge_capacity']\n",
+    "# features = np.empty([0, None,100, 3])\n",
+    "monitored_cycles_discharge_capacity = []\n",
+    "labels = np.empty([0, 2])\n",
+    "cell_features = []\n",
+    "cell_labels = []\n",
+    "cell_discharge_caps = []\n",
+    "initial_discharge_cap_windows = []\n",
+    "for i, cell in enumerate(tqdm(structured_data_list)):\n",
+    "#     print(i)\n",
+    "#     n = len(cell)//cycle_numbers\n",
+    "    cycle_window_features = []\n",
+    "    cycle_window_labels = []\n",
+    "    initial_discharge_cap = []\n",
+    "    cell_cycle_indices = summary_data_list[i]['cycle_index'].values\n",
+    "    index_convolution = bye_cycle.index_convoluter(cell, overlap_cycle_window=False, \n",
+    "                                         overlap_size=10, cycle_window_size=cycle_window_size,\n",
+    "                                                   skip_diagnostic_in_window=skip_diagnostic_in_window)\n",
+    "#     print(len(index_convolution))\n",
+    "    for j, index_list in enumerate(index_convolution):\n",
+    "#         if (j < len(index_convolution)-1):\n",
+    "            cycle_window_features.append(list(zip(*[(bye_cycle.interpol_cycle(cell[cycle_index], columns=features_columns, n_points=100)\n",
+    "                                                     , len(cell[cycle_index]))\n",
+    "                                 for cycle_index in index_list])))\n",
+    "    #         break\n",
+    "    #         print (index_list)\n",
+    "    #         print(summary_data_list[i][label_columns])\n",
+    "    #         discharge_cap_cycle_window = np.array(summary_data_list[i][label_columns])[index_list]\n",
+    "#             print(index_convolution[j])\n",
+    "            discharge_cap_cycle_window = np.array(summary_data_list[i][label_columns])[index_convolution[j]]\n",
+    "\n",
+    "            cycle_window_labels.append(list([find_slope(discharge_cap_cycle_window),discharge_cap_cycle_window]))\n",
+    "#         if j == 0:\n",
+    "#             initial_discharge_cap.append(np.array(summary_data_list[i][label_columns])[index_convolution[j]])\n",
+    "    #         cycle_window_labels.append(discharge_cap_cycle_window)\n",
+    "    #     break\n",
+    "    cell_features.append(cycle_window_features)\n",
+    "    cell_labels.append(cycle_window_labels)\n",
+    "#     initial_discharge_cap_windows.append(initial_discharge_cap)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 471,
+   "id": "de230629",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39], [30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69], [60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99], [90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129], [120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159], [150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189], [180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219], [210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249], [240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279], [270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309], [300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338, 339], [330, 331, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363, 364, 365, 366, 367, 368, 369], [360, 361, 362, 363, 364, 365, 366, 367, 368, 369, 370, 371, 372, 373, 374, 375, 376, 377, 378, 379, 380, 381, 382, 383, 384, 385, 386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399], [390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "def find_renumbedred_index(cell):\n",
+    "    '''This function finds the renumbered index for the cycles that are followed by a diagnostic cycle'''\n",
+    "    renumbered_index_for_cycle_following_a_diagnostic_cycle = []\n",
+    "    i = 0\n",
+    "    for k,cycle in enumerate(cell):\n",
+    "        actual_cycle_index = np.unique(cycle['cycle_index'])[0]\n",
+    "#         print(i, actual_cycle_index)\n",
+    "        if actual_cycle_index != i:\n",
+    "            renumbered_index_for_cycle_following_a_diagnostic_cycle.append(k-1)\n",
+    "            i = actual_cycle_index\n",
+    "        i += 1\n",
+    "#     print(i, actual_cycle_index)\n",
+    "    return renumbered_index_for_cycle_following_a_diagnostic_cycle\n",
+    "\n",
+    "\n",
+    "def index_convoluter(cell, cycle_window_size=20, overlap_cycle_window=False,\n",
+    "                     overlap_size=5, skip_diagnostic_in_window=False):\n",
+    "    '''This function generates a nested list of indices by convolting the cycles based on cycle_window_size. \n",
+    "        You can choose to have your window of cycles overlap, or skipp the windows that involve diagnostic cycles in between.\n",
+    "    '''\n",
+    "    max_cycle_index = len(cell) #30 #\n",
+    "    if cycle_window_size < overlap_size:\n",
+    "        raise ValueError(f'If overlapping, overlap_size ({overlap_size}) should be samller than cycle_window_size ({cycle_window_size}). Please check inputs.')\n",
+    "    if not cycle_window_size < max_cycle_index:\n",
+    "        raise ValueError(f'cycle_window_size ({cycle_window_size}) should be samller than maximum number of cycles in cell ({max_cycle_index}). Please check inputs.')\n",
+    "    if overlap_cycle_window:\n",
+    "        non_overlap =  cycle_window_size - overlap_size\n",
+    "    else:\n",
+    "        non_overlap = cycle_window_size\n",
+    "    intervals = range(0, max_cycle_index, non_overlap)\n",
+    "    if not skip_diagnostic_in_window:\n",
+    "        index_covolutions = [list(range(x, x + cycle_window_size)) for x in intervals if x <= max_cycle_index-cycle_window_size]\n",
+    "    else:\n",
+    "#         skipped_indices = [5, 6, 7, 20]\n",
+    "        skipped_indices = find_renumbedred_index(cell)\n",
+    "        print(f'One before diagnostic {skipped_indices}\\n')\n",
+    "        index_covolutions = [list(range(x, x + cycle_window_size)) for x in intervals if x <= max_cycle_index-cycle_window_size\n",
+    "                             and not (set(list(range(x, x + cycle_window_size))[:-1]) & set(skipped_indices))]\n",
+    "    return index_covolutions\n",
+    "\n",
+    "\n",
+    "index_convolution = index_convoluter(cell, overlap_cycle_window=True, \n",
+    "                                         overlap_size=10, cycle_window_size=window_cycles_size,\n",
+    "                                               skip_diagnostic_in_window=False)\n",
+    "print(index_convolution)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 469,
+   "id": "ba77280a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "One before diagnostic [0, 30, 130, 230, 330, 430, 431]\n",
+      "\n",
+      "[[40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79], [80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119], [160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199], [240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279], [280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319], [360, 361, 362, 363, 364, 365, 366, 367, 368, 369, 370, 371, 372, 373, 374, 375, 376, 377, 378, 379, 380, 381, 382, 383, 384, 385, 386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "index_convolution = index_convoluter(cell, overlap_cycle_window=False, \n",
+    "                                         overlap_size=10, cycle_window_size=window_cycles_size,\n",
+    "                                               skip_diagnostic_in_window=True)\n",
+    "print(index_convolution)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "821903c3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Split train-val-test data by cells\n",
+    "# prepared_data = [(cell_features[i], cell_labels[i]) for i in range(len(cell_features))]\n",
+    "prepared_data = list(zip(cell_features, cell_labels))\n",
+    "\n",
+    "train_size = 0.9\n",
+    "val_size = 0.2\n",
+    "N_train = int(train_size *len(prepared_data))\n",
+    "N_val = int(val_size * N_train)\n",
+    "train_cells = prepared_data[:N_train]\n",
+    "test_cells = prepared_data[N_train:]\n",
+    "\n",
+    "val_cells = train_cells[:N_val]\n",
+    "train_cells = train_cells[N_val:]\n",
+    "print(len(train_cells),len(val_cells), len(test_cells), len(train_cells)+len(test_cells)+len(val_cells))\n",
+    "# train_indices = random.sample(range(len(dat)), N_train)\n",
+    "# test_cells = prepared_data[N_train:]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "a9064d1d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "203 50 29 282\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(len(train_cells),len(val_cells), len(test_cells), len(train_cells)+len(test_cells)+len(val_cells))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "8383b4d8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "203"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(train_cells)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "2a52d706",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "50"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "N_val"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "4799698b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "29"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(test_cells)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 409,
+   "id": "2c18efc7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Y_train = [x for xs in train_cells for x in xs[1]]\n",
+    "# dc_train, slopes_train = make_label_arrays(Y_train)\n",
+    "# print(slopes_train)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "909c240f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.0\n",
+      "[100.      3.266]\n",
+      "len features 1259\n",
+      "100.0\n",
+      "[200.      3.036]\n"
+     ]
+    }
+   ],
+   "source": [
+    "def standardize(inputs):\n",
+    "    fstd = np.std(inputs, axis=0)\n",
+    "    fmean = np.mean(inputs, axis=0)\n",
+    "    std_features = (inputs - fmean) / fstd\n",
+    "    return std_features\n",
+    "\n",
+    "def make_feature_arrays(data):\n",
+    "    X_dt_values = []\n",
+    "    X_time_series = []\n",
+    "    for X in data[:-1]:\n",
+    "        X_dt_values.append(X[1])\n",
+    "        X_time_series.append(X[0])\n",
+    "#         break\n",
+    "    return np.array(X_time_series), np.array(X_dt_values)\n",
+    "\n",
+    "def make_label_arrays(data):\n",
+    "    slopes = []\n",
+    "    discharge_cap = []\n",
+    "    for Y in data[1:]:\n",
+    "        discharge_cap.append(Y[1])\n",
+    "        slopes.append(Y[0])\n",
+    "    return np.array(discharge_cap), np.array(slopes)\n",
+    "\n",
+    "X_train = [x for xs in train_cells for x in xs[0]]\n",
+    "# Y_train = np.array([x for xs in train_cells for x in xs[1]])\n",
+    "Y_train = [x for xs in train_cells for x in xs[1]]\n",
+    "dc_train, slopes_train = make_label_arrays(Y_train)\n",
+    "X_train_time_series, X_train_dt = make_feature_arrays(X_train)\n",
+    "print(X_train_time_series[0,0,0,0])\n",
+    "print(dc_train[0][0])\n",
+    "# print(X_train_time_series[0])\n",
+    "import random\n",
+    "random.seed(0)\n",
+    "indices = list(range(len(X_train_time_series)))\n",
+    "random.shuffle(indices)\n",
+    "print(f'len features {len(X_train_time_series)}')\n",
+    "X_train_time_series = X_train_time_series[indices]\n",
+    "X_train_dt = X_train_dt[indices]\n",
+    "\n",
+    "slopes_train = slopes_train[indices]\n",
+    "dc_train = dc_train[indices]\n",
+    "print(X_train_time_series[0,0,0,0])\n",
+    "print(dc_train[0][0])\n",
+    "\n",
+    "X_val = [x for xs in val_cells for x in xs[0]]\n",
+    "# Y_val= np.array([x for xs in val_cells for x in xs[1]])\n",
+    "Y_val = [x for xs in val_cells for x in xs[1]]\n",
+    "dc_val, slopes_val = make_label_arrays(Y_val)\n",
+    "X_val_time_series, X_val_dt = make_feature_arrays(X_val)\n",
+    "\n",
+    "X_test = [x for xs in test_cells for x in xs[0]]\n",
+    "# Y_test= np.array([x for xs in test_cells for x in xs[1]])\n",
+    "Y_test = [x for xs in test_cells for x in xs[1]]\n",
+    "dc_test, slopes_test = make_label_arrays(Y_test)\n",
+    "X_test_time_series, X_test_dt = make_feature_arrays(X_test)\n",
+    "\n",
+    "# std_X_train_time_series = standardize(X_train_time_series[...,1:])\n",
+    "# std_X_val_time_series = standardize(X_val_time_series[...,1:])\n",
+    "# std_X_test_time_series = standardize(X_test_time_series[...,1:]) \n",
+    "\n",
+    "# X_train_time_series = X_train_time_series[...,1:]\n",
+    "\n",
+    "# X_val_time_series = X_val_time_series[...,1:]\n",
+    "# X_test_time_series = X_test_time_series[...,1:]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 453,
+   "id": "1e71aba1",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1054.0\n",
+      "[1100.       2.708]\n",
+      "1139.0\n",
+      "[1.140e+03 6.001e-01]\n",
+      "549.0\n",
+      "[595.      3.338]\n",
+      "929.0\n",
+      "[930.     2.88]\n",
+      "539.0\n",
+      "[540.      1.765]\n",
+      "129.0\n",
+      "[175.      3.693]\n",
+      "2734.0\n",
+      "[50.     3.711]\n",
+      "2314.0\n",
+      "[2360.      2.48]\n",
+      "1389.0\n",
+      "[1435.       2.474]\n",
+      "549.0\n",
+      "[595.      2.857]\n"
+     ]
+    }
+   ],
+   "source": [
+    "for i in range(10):\n",
+    "    print(X_train_time_series[i,-1,-1,0])\n",
+    "    print(dc_train[i][0])\n",
+    "#     break"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "d3dcdc02",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def standardize_train(inputs):\n",
+    "    fstd = np.std(inputs, axis=0)\n",
+    "    fmean = np.mean(inputs, axis=0)\n",
+    "    std_features = (inputs - fmean) / fstd\n",
+    "    return std_features, fmean, fstd\n",
+    "\n",
+    "def standardize_non_train(inputs, fmean_train, fstd_train):\n",
+    "    std_features = (inputs - fmean_train) / fstd_train\n",
+    "    return std_features"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "af01c737",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'slope 1')"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.hist(slopes_train[:,0])\n",
+    "plt.title('slope 1')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "52fb8129",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████| 9/9 [00:06<00:00,  1.39it/s]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "def oversample(f_time_series, f_dt, labels, oversample_label_index=1):\n",
+    "    counts, bins, patches = plt.hist(labels[:,oversample_label_index])\n",
+    "    import numpy_indexed as npi\n",
+    "    import random\n",
+    "    max_samples = max(counts)\n",
+    "    ind = np.digitize(labels[:,oversample_label_index], bins)\n",
+    "    label_groups = npi.group_by(ind).split(labels[:,oversample_label_index])\n",
+    "\n",
+    "    balanced_f_time_series = f_time_series\n",
+    "    balanced_labels = labels\n",
+    "    balanced_f_dt = f_dt\n",
+    "    for sg in tqdm(label_groups[:-2]):\n",
+    "        n_samples = int(max_samples - len(sg))\n",
+    "        # Find indices for samples\n",
+    "        sample_indices = npi.indices(labels[:, oversample_label_index], np.random.choice(sg, n_samples))\n",
+    "        balanced_f_time_series = np.append(balanced_f_time_series,\n",
+    "                                                     f_time_series[sample_indices], axis=0)\n",
+    "        balanced_labels = np.append(balanced_labels,\n",
+    "                                                     labels[sample_indices], axis=0)\n",
+    "        balanced_f_dt = np.append(balanced_f_dt,\n",
+    "                                                f_dt[sample_indices], axis=0)\n",
+    "    \n",
+    "#     random.seed(0)\n",
+    "    shuffled_indices = list(range(len(balanced_f_time_series)))\n",
+    "    random.shuffle(indices)\n",
+    "    return balanced_f_time_series[shuffled_indices], balanced_f_dt[shuffled_indices], balanced_labels[shuffled_indices]\n",
+    "\n",
+    "balanced_X_train_time_series, balanced_X_train_dt, balanced_slopes_train = oversample(X_train_time_series,\n",
+    "                                                                                               X_train_dt,\n",
+    "                                                                                               slopes_train, oversample_label_index=1)\n",
+    "# balanced_X_train_time_series, balanced_X_train_dt, balanced_slopes_train = oversample(balanced_X_train_time_series,\n",
+    "#                                                                                                balanced_X_train_dt,\n",
+    "#                                                                                                balanced_slopes_train, oversample_label_index=0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "6674e027",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'slope 1')"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.hist(balanced_slopes_train[:,0])\n",
+    "plt.title('slope 1')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "17e78cbc",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'slope 2')"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.hist(balanced_slopes_train[:,1])\n",
+    "plt.title('slope 2')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 766,
+   "id": "4d77bac3",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.PathCollection at 0x7efb5e5955e0>"
+      ]
+     },
+     "execution_count": 766,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(slopes_train[:,0], slopes_train[:,0].shape[0] * [0])\n",
+    "# plt.scatter( X, [0] * X.shape[0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "c377e1ee",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(10500, 100, 100, 2)"
+      ]
+     },
+     "execution_count": 34,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "scaled_X_train_time_series.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "965fe714",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "scaled_X_train_dt, mean_X_train_dt, std_X_train_dt  = standardize_train(balanced_X_train_dt)\n",
+    "scaled_X_val_dt = standardize_non_train(X_val_dt, mean_X_train_dt, std_X_train_dt)\n",
+    "\n",
+    "scaled_X_train_time_series, mean_X_train_time_series, std_X_train_time_series = standardize_train(balanced_X_train_time_series)\n",
+    "scaled_X_val_time_series = standardize_non_train(X_val_time_series, mean_X_train_time_series, std_X_train_time_series)\n",
+    "# X_train_time_series = X_train_time_series\n",
+    "\n",
+    "scaled_X_train_time_series = scaled_X_train_time_series[...,1:]\n",
+    "scaled_X_val_time_series = scaled_X_val_time_series[...,1:]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "c4aa00e6",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "input: (None, 100, 100, 2)\n",
+      "input_dt: (None, 100)\n",
+      "output 1 conv: (None, 100, 91, 32)\n",
+      "output max_pooling 1: (None, 100, 45, 32)\n",
+      "output 2 conv: (None, 100, 36, 32)\n",
+      "output max_pooling 2: (None, 100, 18, 32)\n",
+      "output dropout: (None, 100, 18, 32)\n",
+      "output GlobalAveragePooling1D: (None, 100, 18, 32)\n",
+      "(None, 100, 18, 32)\n"
+     ]
+    },
+    {
+     "ename": "ValueError",
+     "evalue": "Input 0 of layer \"bidirectional\" is incompatible with the layer: expected ndim=3, found ndim=4. Full shape received: (None, 100, 18, 32)",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
+      "Input \u001b[0;32mIn [32]\u001b[0m, in \u001b[0;36m<cell line: 88>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     85\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mroot_mean_squared_error\u001b[39m(y_true, y_pred):\n\u001b[1;32m     86\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m K\u001b[38;5;241m.\u001b[39msqrt(K\u001b[38;5;241m.\u001b[39mmean(K\u001b[38;5;241m.\u001b[39msquare(y_pred \u001b[38;5;241m-\u001b[39m y_true), axis\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m)) \n\u001b[0;32m---> 88\u001b[0m model \u001b[38;5;241m=\u001b[39m \u001b[43mbuild_model\u001b[49m\u001b[43m(\u001b[49m\u001b[43mL\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mT\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcycle_window_size\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcycle_window_size\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mreg_strength\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m     89\u001b[0m opt \u001b[38;5;241m=\u001b[39m tf\u001b[38;5;241m.\u001b[39moptimizers\u001b[38;5;241m.\u001b[39mSGD(\u001b[38;5;241m1e-3\u001b[39m)\n\u001b[1;32m     90\u001b[0m model\u001b[38;5;241m.\u001b[39mcompile(\n\u001b[1;32m     91\u001b[0m   opt,\n\u001b[1;32m     92\u001b[0m   loss\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mmean_absolute_error\u001b[39m\u001b[38;5;124m'\u001b[39m)\n",
+      "Input \u001b[0;32mIn [32]\u001b[0m, in \u001b[0;36mbuild_model\u001b[0;34m(L, T, cycle_window_size, reg_strength)\u001b[0m\n\u001b[1;32m     58\u001b[0m \u001b[38;5;66;03m#     conv_1d_layer = tf.keras.layers.Conv1D(64, 5, input_shape=(100,64))\u001b[39;00m\n\u001b[1;32m     59\u001b[0m \u001b[38;5;66;03m#     x = tf.keras.layers.TimeDistributed(conv_1d_layer, input_shape=(100,))(x)\u001b[39;00m\n\u001b[1;32m     60\u001b[0m     \u001b[38;5;28mprint\u001b[39m(x\u001b[38;5;241m.\u001b[39mshape)\n\u001b[0;32m---> 61\u001b[0m     x \u001b[38;5;241m=\u001b[39m \u001b[43mtf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mkeras\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlayers\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mBidirectional\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mkeras\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlayers\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mLSTM\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m32\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mreturn_sequences\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[43mx\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     62\u001b[0m     x \u001b[38;5;241m=\u001b[39m tf\u001b[38;5;241m.\u001b[39mkeras\u001b[38;5;241m.\u001b[39mlayers\u001b[38;5;241m.\u001b[39mBidirectional(tf\u001b[38;5;241m.\u001b[39mkeras\u001b[38;5;241m.\u001b[39mlayers\u001b[38;5;241m.\u001b[39mLSTM(\u001b[38;5;241m32\u001b[39m, return_sequences\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m))(x)\n\u001b[1;32m     63\u001b[0m     \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124moutput bilstm dist: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mx\u001b[38;5;241m.\u001b[39mshape\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m)\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/keras/layers/rnn/bidirectional.py:249\u001b[0m, in \u001b[0;36mBidirectional.__call__\u001b[0;34m(self, inputs, initial_state, constants, **kwargs)\u001b[0m\n\u001b[1;32m    246\u001b[0m   inputs \u001b[38;5;241m=\u001b[39m inputs[\u001b[38;5;241m0\u001b[39m]\n\u001b[1;32m    248\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m initial_state \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m constants \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m--> 249\u001b[0m   \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mBidirectional\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[38;5;21;43m__call__\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43minputs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    251\u001b[0m \u001b[38;5;66;03m# Applies the same workaround as in `RNN.__call__`\u001b[39;00m\n\u001b[1;32m    252\u001b[0m additional_inputs \u001b[38;5;241m=\u001b[39m []\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/keras/utils/traceback_utils.py:67\u001b[0m, in \u001b[0;36mfilter_traceback.<locals>.error_handler\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m     65\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:  \u001b[38;5;66;03m# pylint: disable=broad-except\u001b[39;00m\n\u001b[1;32m     66\u001b[0m   filtered_tb \u001b[38;5;241m=\u001b[39m _process_traceback_frames(e\u001b[38;5;241m.\u001b[39m__traceback__)\n\u001b[0;32m---> 67\u001b[0m   \u001b[38;5;28;01mraise\u001b[39;00m e\u001b[38;5;241m.\u001b[39mwith_traceback(filtered_tb) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28mNone\u001b[39m\n\u001b[1;32m     68\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[1;32m     69\u001b[0m   \u001b[38;5;28;01mdel\u001b[39;00m filtered_tb\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/keras/engine/input_spec.py:214\u001b[0m, in \u001b[0;36massert_input_compatibility\u001b[0;34m(input_spec, inputs, layer_name)\u001b[0m\n\u001b[1;32m    212\u001b[0m   ndim \u001b[38;5;241m=\u001b[39m shape\u001b[38;5;241m.\u001b[39mrank\n\u001b[1;32m    213\u001b[0m   \u001b[38;5;28;01mif\u001b[39;00m ndim \u001b[38;5;241m!=\u001b[39m spec\u001b[38;5;241m.\u001b[39mndim:\n\u001b[0;32m--> 214\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mInput \u001b[39m\u001b[38;5;132;01m{\u001b[39;00minput_index\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m of layer \u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mlayer_name\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m \u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m    215\u001b[0m                      \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mis incompatible with the layer: \u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m    216\u001b[0m                      \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mexpected ndim=\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mspec\u001b[38;5;241m.\u001b[39mndim\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m, found ndim=\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mndim\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m. \u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m    217\u001b[0m                      \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mFull shape received: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mtuple\u001b[39m(shape)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m    218\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m spec\u001b[38;5;241m.\u001b[39mmax_ndim \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m    219\u001b[0m   ndim \u001b[38;5;241m=\u001b[39m x\u001b[38;5;241m.\u001b[39mshape\u001b[38;5;241m.\u001b[39mrank\n",
+      "\u001b[0;31mValueError\u001b[0m: Input 0 of layer \"bidirectional\" is incompatible with the layer: expected ndim=3, found ndim=4. Full shape received: (None, 100, 18, 32)"
+     ]
+    }
+   ],
+   "source": [
+    "from dataclasses import dataclass\n",
+    "@dataclass\n",
+    "class Config:\n",
+    "    batch_size: int\n",
+    "    buffer_size: int\n",
+    "    rnn_units: int\n",
+    "    hidden_dim: int\n",
+    "    embedding_dim: int\n",
+    "    reg_strength: float\n",
+    "    lr: float\n",
+    "    drop_rate: float\n",
+    "        \n",
+    "config = Config(batch_size=16, \n",
+    "                buffer_size=10000,\n",
+    "                rnn_units=64,\n",
+    "                hidden_dim=64,\n",
+    "                embedding_dim=32,\n",
+    "                reg_strength=0,\n",
+    "                lr=1e-3,\n",
+    "                drop_rate=0.3\n",
+    "               )\n",
+    "\n",
+    "def build_model(L, T, cycle_window_size=10, reg_strength=0):\n",
+    "    inputs = tf.keras.Input(shape=(cycle_window_size,T,2))\n",
+    "    input_dt = tf.keras.Input(shape=(cycle_window_size))\n",
+    "    print(f'input: {inputs.shape}')\n",
+    "    print(f'input_dt: {input_dt.shape}')\n",
+    "#     conv_1d_layer = tf.keras.layers.Conv1D(32, 50, activation='relu')\n",
+    "#     max_pooling = \n",
+    "#     blstm_layer = tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(16))\n",
+    "#     x = tf.keras.layers.Embedding(100,16)(inputs)\n",
+    "    x = tf.keras.layers.TimeDistributed(tf.keras.layers.Conv1D(32, 10), input_shape=(cycle_window_size, 10, 2))(inputs)\n",
+    "    print(f'output 1 conv: {x.shape}')\n",
+    "    x = tf.keras.layers.TimeDistributed(tf.keras.layers.MaxPool1D(pool_size=2))(x)\n",
+    "    print(f'output max_pooling 1: {x.shape}')\n",
+    "    x = tf.keras.layers.TimeDistributed(tf.keras.layers.Conv1D(32, 10), input_shape=(cycle_window_size, 20 ,2))(x)\n",
+    "    print(f'output 2 conv: {x.shape}')\n",
+    "    x = tf.keras.layers.TimeDistributed(tf.keras.layers.MaxPool1D(pool_size=2))(x)\n",
+    "    print(f'output max_pooling 2: {x.shape}')\n",
+    "#     x = tf.keras.layers.TimeDistributed(tf.keras.layers.Conv1D(32, 10), input_shape=(cycle_window_size, 2))(x)\n",
+    "#     print(f'output 3 conv: {x.shape}')\n",
+    "#     x = tf.keras.layers.TimeDistributed(tf.keras.layers.MaxPool1D(pool_size=2))(x)\n",
+    "#     print(f'output max_pooling 3: {x.shape}')\n",
+    "#     x = tf.keras.layers.TimeDistributed(tf.keras.layers.Conv1D(32, 10), input_shape=(cycle_window_size, 2))(x)\n",
+    "#     x = tf.keras.layers.TimeDistributed(tf.keras.layers.Conv1D(32, 25), input_shape=(100, 2))(x)\n",
+    "#     print(f'output 3 conv: {x.shape}')\n",
+    "#     x = tf.keras.layers.TimeDistributed(max_pooling)(x)\n",
+    "#     print(f'output max_pooling 2: {x.shape}')\n",
+    "#     x = tf.keras.layers.LayerNormalization()(x)\n",
+    "    x = tf.keras.layers.TimeDistributed(tf.keras.layers.Dropout(config.drop_rate))(x)\n",
+    "    print(f'output dropout: {x.shape}')\n",
+    "#     x = tf.keras.layers.Reshape((cycle_window_size, 32))(x)\n",
+    "#     x = tf.keras.layers.TimeDistributed(tf.keras.layers.GlobalAveragePooling1D())(x)\n",
+    "#     x = tf.keras.layers.Flatten()(x)\n",
+    "#     x = tf.keras.layers.TimeDistributed(tf.keras.layers.Flatten())(x)\n",
+    "#     \n",
+    "    print(f'output GlobalAveragePooling1D: {x.shape}')\n",
+    "#     conv_1d_layer = tf.keras.layers.Conv1D(64, 5, input_shape=(100,64))\n",
+    "#     x = tf.keras.layers.TimeDistributed(conv_1d_layer, input_shape=(100,))(x)\n",
+    "    print(x.shape)\n",
+    "    x = tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(32, return_sequences=True))(x)\n",
+    "    x = tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(32, return_sequences=False))(x)\n",
+    "    print(f'output bilstm dist: {x.shape}')\n",
+    "#     x = tf.keras.layers.Concatenate()([x, input_dt])\n",
+    "    x = tf.keras.layers.LayerNormalization()(x)\n",
+    "    x = tf.keras.layers.Dropout(config.drop_rate)(x)\n",
+    "    x = tf.keras.layers.Dense(32, kernel_regularizer=tf.keras.regularizers.L2(l2=reg_strength), activation='tanh')(x)\n",
+    "    x = tf.keras.layers.LayerNormalization()(x)\n",
+    "    x = tf.keras.layers.Dropout(config.drop_rate)(x)\n",
+    "    x = tf.keras.layers.Dense(16, kernel_regularizer=tf.keras.regularizers.L2(l2=reg_strength), activation='tanh')(x)\n",
+    "#     e = tf.keras.layers.Embedding(input_dim=config.vocab_size, \n",
+    "#                                     output_dim=config.embedding_dim,\n",
+    "#                                     mask_zero=True)(inputs)\n",
+    "    x = tf.keras.layers.LayerNormalization()(x)\n",
+    "    x = tf.keras.layers.Dropout(config.drop_rate)(x)\n",
+    "    yhat = tf.keras.layers.Dense(2, kernel_regularizer=tf.keras.regularizers.L2(l2=reg_strength))(x)\n",
+    "#     model = tf.keras.Model(inputs=[inputs, input_dt], outputs=yhat)\n",
+    "    model = tf.keras.Model(inputs=inputs, outputs=yhat)\n",
+    "    return model\n",
+    "tf.keras.backend.clear_session()\n",
+    "L = None\n",
+    "T = 100\n",
+    "\n",
+    "from keras import backend as K\n",
+    "def root_mean_squared_error(y_true, y_pred):\n",
+    "        return K.sqrt(K.mean(K.square(y_pred - y_true), axis=-1)) \n",
+    "    \n",
+    "model = build_model(L, T, cycle_window_size=cycle_window_size, reg_strength=0)\n",
+    "opt = tf.optimizers.SGD(1e-3)\n",
+    "model.compile(\n",
+    "  opt,\n",
+    "  loss='mean_absolute_error')\n",
+    "#   loss=root_mean_squared_error)\n",
+    "model.summary()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "6d5991c2",
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Epoch 1/150\n",
+      "657/657 [==============================] - 61s 82ms/step - loss: 1.5870 - val_loss: 2.1153 - lr: 0.0010\n",
+      "Epoch 2/150\n",
+      "657/657 [==============================] - 52s 79ms/step - loss: 1.1901 - val_loss: 2.1412 - lr: 0.0010\n",
+      "Epoch 3/150\n",
+      "657/657 [==============================] - 52s 79ms/step - loss: 1.1292 - val_loss: 2.1746 - lr: 0.0010\n",
+      "Epoch 4/150\n",
+      "657/657 [==============================] - 52s 79ms/step - loss: 1.0867 - val_loss: 2.1704 - lr: 0.0010\n",
+      "Epoch 5/150\n",
+      "657/657 [==============================] - 52s 79ms/step - loss: 1.0673 - val_loss: 2.2104 - lr: 0.0010\n",
+      "Epoch 6/150\n",
+      "657/657 [==============================] - 52s 79ms/step - loss: 1.0400 - val_loss: 2.1915 - lr: 0.0010\n",
+      "Epoch 7/150\n",
+      " 78/657 [==>...........................] - ETA: 45s - loss: 1.0264"
+     ]
+    },
+    {
+     "ename": "KeyboardInterrupt",
+     "evalue": "",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
+      "Input \u001b[0;32mIn [25]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfit\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m      2\u001b[0m \u001b[43m    \u001b[49m\u001b[43mscaled_X_train_time_series\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlog\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43mbalanced_slopes_train\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;66;43;03m# standardize\u001b[39;49;00m\n\u001b[1;32m      3\u001b[0m \u001b[38;5;66;43;03m#     scaled_X_train_time_series, balanced_slopes_train,\u001b[39;49;00m\n\u001b[1;32m      4\u001b[0m \u001b[43m    \u001b[49m\u001b[43mvalidation_data\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mscaled_X_val_time_series\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlog\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43mslopes_val\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\n\u001b[1;32m      5\u001b[0m \u001b[38;5;66;43;03m#     validation_data=(scaled_X_val_time_series, slopes_val), \u001b[39;49;00m\n\u001b[1;32m      6\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[43mtf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mkeras\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcallbacks\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mReduceLROnPlateau\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m      7\u001b[0m \u001b[43m            \u001b[49m\u001b[43mmonitor\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mval_loss\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfactor\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m0.9\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpatience\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m5\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmin_lr\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m1e-5\u001b[39;49m\n\u001b[1;32m      8\u001b[0m \u001b[43m        \u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mkeras\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcallbacks\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mEarlyStopping\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmonitor\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mval_loss\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmode\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mmin\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrestore_best_weights\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpatience\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m10\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      9\u001b[0m \u001b[38;5;66;43;03m# #         tf.keras.callbacks.LambdaCallback(\u001b[39;49;00m\n\u001b[1;32m     10\u001b[0m \u001b[38;5;66;43;03m# #         on_epoch_begin=lambda epochs,logs: print('lr =',lr_decayed_fn(opt.iterations).numpy())\u001b[39;49;00m\n\u001b[1;32m     11\u001b[0m \u001b[38;5;66;43;03m# #         ),\u001b[39;49;00m\n\u001b[1;32m     12\u001b[0m \u001b[38;5;66;43;03m#         ,\u001b[39;49;00m\n\u001b[1;32m     13\u001b[0m \u001b[43m    \u001b[49m\u001b[43mepochs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m150\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbatch_size\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m16\u001b[39;49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/keras/utils/traceback_utils.py:64\u001b[0m, in \u001b[0;36mfilter_traceback.<locals>.error_handler\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m     62\u001b[0m filtered_tb \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m     63\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m---> 64\u001b[0m   \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     65\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:  \u001b[38;5;66;03m# pylint: disable=broad-except\u001b[39;00m\n\u001b[1;32m     66\u001b[0m   filtered_tb \u001b[38;5;241m=\u001b[39m _process_traceback_frames(e\u001b[38;5;241m.\u001b[39m__traceback__)\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/keras/engine/training.py:1414\u001b[0m, in \u001b[0;36mModel.fit\u001b[0;34m(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing)\u001b[0m\n\u001b[1;32m   1412\u001b[0m logs \u001b[38;5;241m=\u001b[39m tmp_logs  \u001b[38;5;66;03m# No error, now safe to assign to logs.\u001b[39;00m\n\u001b[1;32m   1413\u001b[0m end_step \u001b[38;5;241m=\u001b[39m step \u001b[38;5;241m+\u001b[39m data_handler\u001b[38;5;241m.\u001b[39mstep_increment\n\u001b[0;32m-> 1414\u001b[0m \u001b[43mcallbacks\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mon_train_batch_end\u001b[49m\u001b[43m(\u001b[49m\u001b[43mend_step\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlogs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1415\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstop_training:\n\u001b[1;32m   1416\u001b[0m   \u001b[38;5;28;01mbreak\u001b[39;00m\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/keras/callbacks.py:438\u001b[0m, in \u001b[0;36mCallbackList.on_train_batch_end\u001b[0;34m(self, batch, logs)\u001b[0m\n\u001b[1;32m    431\u001b[0m \u001b[38;5;124;03m\"\"\"Calls the `on_train_batch_end` methods of its callbacks.\u001b[39;00m\n\u001b[1;32m    432\u001b[0m \n\u001b[1;32m    433\u001b[0m \u001b[38;5;124;03mArgs:\u001b[39;00m\n\u001b[1;32m    434\u001b[0m \u001b[38;5;124;03m    batch: Integer, index of batch within the current epoch.\u001b[39;00m\n\u001b[1;32m    435\u001b[0m \u001b[38;5;124;03m    logs: Dict. Aggregated metric results up until this batch.\u001b[39;00m\n\u001b[1;32m    436\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m    437\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_should_call_train_batch_hooks:\n\u001b[0;32m--> 438\u001b[0m   \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call_batch_hook\u001b[49m\u001b[43m(\u001b[49m\u001b[43mModeKeys\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mTRAIN\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mend\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbatch\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlogs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlogs\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/keras/callbacks.py:297\u001b[0m, in \u001b[0;36mCallbackList._call_batch_hook\u001b[0;34m(self, mode, hook, batch, logs)\u001b[0m\n\u001b[1;32m    295\u001b[0m   \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_call_batch_begin_hook(mode, batch, logs)\n\u001b[1;32m    296\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m hook \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mend\u001b[39m\u001b[38;5;124m'\u001b[39m:\n\u001b[0;32m--> 297\u001b[0m   \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call_batch_end_hook\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmode\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbatch\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlogs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    298\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    299\u001b[0m   \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m    300\u001b[0m       \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mUnrecognized hook: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mhook\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m. Expected values are [\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mbegin\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m, \u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mend\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m]\u001b[39m\u001b[38;5;124m'\u001b[39m)\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/keras/callbacks.py:318\u001b[0m, in \u001b[0;36mCallbackList._call_batch_end_hook\u001b[0;34m(self, mode, batch, logs)\u001b[0m\n\u001b[1;32m    315\u001b[0m   batch_time \u001b[38;5;241m=\u001b[39m time\u001b[38;5;241m.\u001b[39mtime() \u001b[38;5;241m-\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_batch_start_time\n\u001b[1;32m    316\u001b[0m   \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_batch_times\u001b[38;5;241m.\u001b[39mappend(batch_time)\n\u001b[0;32m--> 318\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call_batch_hook_helper\u001b[49m\u001b[43m(\u001b[49m\u001b[43mhook_name\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbatch\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlogs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    320\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_batch_times) \u001b[38;5;241m>\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_num_batches_for_timing_check:\n\u001b[1;32m    321\u001b[0m   end_hook_name \u001b[38;5;241m=\u001b[39m hook_name\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/keras/callbacks.py:356\u001b[0m, in \u001b[0;36mCallbackList._call_batch_hook_helper\u001b[0;34m(self, hook_name, batch, logs)\u001b[0m\n\u001b[1;32m    354\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m callback \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcallbacks:\n\u001b[1;32m    355\u001b[0m   hook \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mgetattr\u001b[39m(callback, hook_name)\n\u001b[0;32m--> 356\u001b[0m   \u001b[43mhook\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbatch\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlogs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    358\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_check_timing:\n\u001b[1;32m    359\u001b[0m   \u001b[38;5;28;01mif\u001b[39;00m hook_name \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_hook_times:\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/keras/callbacks.py:1034\u001b[0m, in \u001b[0;36mProgbarLogger.on_train_batch_end\u001b[0;34m(self, batch, logs)\u001b[0m\n\u001b[1;32m   1033\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mon_train_batch_end\u001b[39m(\u001b[38;5;28mself\u001b[39m, batch, logs\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m):\n\u001b[0;32m-> 1034\u001b[0m   \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_batch_update_progbar\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbatch\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlogs\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/keras/callbacks.py:1106\u001b[0m, in \u001b[0;36mProgbarLogger._batch_update_progbar\u001b[0;34m(self, batch, logs)\u001b[0m\n\u001b[1;32m   1102\u001b[0m   \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mseen \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m add_seen\n\u001b[1;32m   1104\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mverbose \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m1\u001b[39m:\n\u001b[1;32m   1105\u001b[0m   \u001b[38;5;66;03m# Only block async when verbose = 1.\u001b[39;00m\n\u001b[0;32m-> 1106\u001b[0m   logs \u001b[38;5;241m=\u001b[39m \u001b[43mtf_utils\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msync_to_numpy_or_python_type\u001b[49m\u001b[43m(\u001b[49m\u001b[43mlogs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1107\u001b[0m   \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mprogbar\u001b[38;5;241m.\u001b[39mupdate(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mseen, \u001b[38;5;28mlist\u001b[39m(logs\u001b[38;5;241m.\u001b[39mitems()), finalize\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/keras/utils/tf_utils.py:607\u001b[0m, in \u001b[0;36msync_to_numpy_or_python_type\u001b[0;34m(tensors)\u001b[0m\n\u001b[1;32m    604\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m t\n\u001b[1;32m    605\u001b[0m   \u001b[38;5;28;01mreturn\u001b[39;00m t\u001b[38;5;241m.\u001b[39mitem() \u001b[38;5;28;01mif\u001b[39;00m np\u001b[38;5;241m.\u001b[39mndim(t) \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m t\n\u001b[0;32m--> 607\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mtf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mnest\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmap_structure\u001b[49m\u001b[43m(\u001b[49m\u001b[43m_to_single_numpy_or_python_type\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtensors\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/tensorflow/python/util/nest.py:916\u001b[0m, in \u001b[0;36mmap_structure\u001b[0;34m(func, *structure, **kwargs)\u001b[0m\n\u001b[1;32m    912\u001b[0m flat_structure \u001b[38;5;241m=\u001b[39m (flatten(s, expand_composites) \u001b[38;5;28;01mfor\u001b[39;00m s \u001b[38;5;129;01min\u001b[39;00m structure)\n\u001b[1;32m    913\u001b[0m entries \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mzip\u001b[39m(\u001b[38;5;241m*\u001b[39mflat_structure)\n\u001b[1;32m    915\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m pack_sequence_as(\n\u001b[0;32m--> 916\u001b[0m     structure[\u001b[38;5;241m0\u001b[39m], [func(\u001b[38;5;241m*\u001b[39mx) \u001b[38;5;28;01mfor\u001b[39;00m x \u001b[38;5;129;01min\u001b[39;00m entries],\n\u001b[1;32m    917\u001b[0m     expand_composites\u001b[38;5;241m=\u001b[39mexpand_composites)\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/tensorflow/python/util/nest.py:916\u001b[0m, in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m    912\u001b[0m flat_structure \u001b[38;5;241m=\u001b[39m (flatten(s, expand_composites) \u001b[38;5;28;01mfor\u001b[39;00m s \u001b[38;5;129;01min\u001b[39;00m structure)\n\u001b[1;32m    913\u001b[0m entries \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mzip\u001b[39m(\u001b[38;5;241m*\u001b[39mflat_structure)\n\u001b[1;32m    915\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m pack_sequence_as(\n\u001b[0;32m--> 916\u001b[0m     structure[\u001b[38;5;241m0\u001b[39m], [\u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mx\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mfor\u001b[39;00m x \u001b[38;5;129;01min\u001b[39;00m entries],\n\u001b[1;32m    917\u001b[0m     expand_composites\u001b[38;5;241m=\u001b[39mexpand_composites)\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/keras/utils/tf_utils.py:601\u001b[0m, in \u001b[0;36msync_to_numpy_or_python_type.<locals>._to_single_numpy_or_python_type\u001b[0;34m(t)\u001b[0m\n\u001b[1;32m    598\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_to_single_numpy_or_python_type\u001b[39m(t):\n\u001b[1;32m    599\u001b[0m   \u001b[38;5;66;03m# Don't turn ragged or sparse tensors to NumPy.\u001b[39;00m\n\u001b[1;32m    600\u001b[0m   \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(t, tf\u001b[38;5;241m.\u001b[39mTensor):\n\u001b[0;32m--> 601\u001b[0m     t \u001b[38;5;241m=\u001b[39m \u001b[43mt\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mnumpy\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    602\u001b[0m   \u001b[38;5;66;03m# Strings, ragged and sparse tensors don't have .item(). Return them as-is.\u001b[39;00m\n\u001b[1;32m    603\u001b[0m   \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(t, (np\u001b[38;5;241m.\u001b[39mndarray, np\u001b[38;5;241m.\u001b[39mgeneric)):\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/tensorflow/python/framework/ops.py:1159\u001b[0m, in \u001b[0;36m_EagerTensorBase.numpy\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m   1136\u001b[0m \u001b[38;5;124;03m\"\"\"Copy of the contents of this Tensor into a NumPy array or scalar.\u001b[39;00m\n\u001b[1;32m   1137\u001b[0m \n\u001b[1;32m   1138\u001b[0m \u001b[38;5;124;03mUnlike NumPy arrays, Tensors are immutable, so this method has to copy\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   1156\u001b[0m \u001b[38;5;124;03m    NumPy dtype.\u001b[39;00m\n\u001b[1;32m   1157\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m   1158\u001b[0m \u001b[38;5;66;03m# TODO(slebedev): Consider avoiding a copy for non-CPU or remote tensors.\u001b[39;00m\n\u001b[0;32m-> 1159\u001b[0m maybe_arr \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_numpy\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m  \u001b[38;5;66;03m# pylint: disable=protected-access\u001b[39;00m\n\u001b[1;32m   1160\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m maybe_arr\u001b[38;5;241m.\u001b[39mcopy() \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(maybe_arr, np\u001b[38;5;241m.\u001b[39mndarray) \u001b[38;5;28;01melse\u001b[39;00m maybe_arr\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/tensorflow/python/framework/ops.py:1125\u001b[0m, in \u001b[0;36m_EagerTensorBase._numpy\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m   1123\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_numpy\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[1;32m   1124\u001b[0m   \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 1125\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_numpy_internal\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1126\u001b[0m   \u001b[38;5;28;01mexcept\u001b[39;00m core\u001b[38;5;241m.\u001b[39m_NotOkStatusException \u001b[38;5;28;01mas\u001b[39;00m e:  \u001b[38;5;66;03m# pylint: disable=protected-access\u001b[39;00m\n\u001b[1;32m   1127\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m core\u001b[38;5;241m.\u001b[39m_status_to_exception(e) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28mNone\u001b[39m\n",
+      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
+     ]
+    }
+   ],
+   "source": [
+    "result = model.fit(\n",
+    "    scaled_X_train_time_series, -np.log(-balanced_slopes_train), # standardize\n",
+    "#     scaled_X_train_time_series, balanced_slopes_train,\n",
+    "    validation_data=(scaled_X_val_time_series, -np.log(-slopes_val)), \n",
+    "#     validation_data=(scaled_X_val_time_series, slopes_val), \n",
+    "    callbacks=[tf.keras.callbacks.ReduceLROnPlateau(\n",
+    "            monitor=\"val_loss\", factor=0.9, patience=5, min_lr=1e-5\n",
+    "        ), tf.keras.callbacks.EarlyStopping(monitor='val_loss', mode='min', restore_best_weights=True, patience=10)],\n",
+    "# #         tf.keras.callbacks.LambdaCallback(\n",
+    "# #         on_epoch_begin=lambda epochs,logs: print('lr =',lr_decayed_fn(opt.iterations).numpy())\n",
+    "# #         ),\n",
+    "#         ,\n",
+    "    epochs=150, batch_size=16)\n",
+    "\n",
+    "# result = model.fit(\n",
+    "#     [scaled_X_train_time_series, scaled_X_train_dt], -np.log(-balanced_slopes_train), # standardize\n",
+    "#     validation_data=([scaled_X_val_time_series, scaled_X_val_dt], -np.log(-slopes_val)), \n",
+    "#     callbacks=[tf.keras.callbacks.ReduceLROnPlateau(\n",
+    "#             monitor=\"val_loss\", factor=0.9, patience=5, min_lr=1e-5\n",
+    "#         ), tf.keras.callbacks.EarlyStopping(monitor='val_loss', mode='min', restore_best_weights=True, patience=20)],\n",
+    "# # #         tf.keras.callbacks.LambdaCallback(\n",
+    "# # #         on_epoch_begin=lambda epochs,logs: print('lr =',lr_decayed_fn(opt.iterations).numpy())\n",
+    "# # #         ),\n",
+    "# #         ,\n",
+    "#     epochs=150, batch_size=64)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "cf78fed4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "plt.figure(dpi=100)\n",
+    "plt.plot(result.history['loss'], color='C0', label='Train')\n",
+    "plt.plot(result.history['val_loss'], color='C1', label='Validation')\n",
+    "plt.legend()\n",
+    "plt.ylabel('MAE')\n",
+    "plt.xlabel('Epochs')\n",
+    "# plt.xlim([100, 150])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 181,
+   "id": "fbda5c64",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "7/7 [==============================] - 0s 16ms/step - loss: 1.7377\n"
+     ]
+    }
+   ],
+   "source": [
+    "scaled_X_test_dt = standardize_non_train(X_test_dt, mean_X_train_dt, std_X_train_dt)\n",
+    "scaled_X_test_time_series = standardize_non_train(X_test_time_series, mean_X_train_time_series, std_X_train_time_series)[...,1:]\n",
+    "\n",
+    "# test_result = model.evaluate([scaled_X_test_time_series, scaled_X_test_dt], -np.log(-slopes_test))\n",
+    "# test_result = model.evaluate(scaled_X_test_time_series, slopes_test)\n",
+    "test_result = model.evaluate(scaled_X_test_time_series, -np.log(-slopes_test))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 172,
+   "id": "99f28aaf",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "7/7 [==============================] - 1s 12ms/step\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Y_hat_test = model.predict([scaled_X_test_time_series, scaled_X_test_dt])\n",
+    "Y_hat_test = model.predict(scaled_X_test_time_series)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 173,
+   "id": "09bdea34",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "4.796485581289604\n",
+      "5.573594295499582\n",
+      "4.919692990844324\n",
+      "4.9175953432903245\n",
+      "6.537595047603457\n",
+      "5.256434345521801\n",
+      "5.256418272303801\n",
+      "7.059912982235535\n",
+      "5.358749321925463\n",
+      "5.3588027640674625\n",
+      "5.358737277447463\n",
+      "5.3598883447894625\n",
+      "7.6855089226259965\n",
+      "4.951428551434133\n",
+      "4.951456400458133\n",
+      "4.951472744308133\n",
+      "4.953453974770133\n",
+      "4.956340921212133\n",
+      "4.953329444684133\n",
+      "4.95168812589645\n",
+      "4.6254482290447205\n",
+      "5.272378451968022\n",
+      "5.26642809902976\n",
+      "5.247198669192449\n",
+      "5.247270080927726\n",
+      "4.8321788530138905\n",
+      "4.759861375040119\n",
+      "4.134456329372922\n",
+      "4.134356256170162\n",
+      "4.519021845550424\n",
+      "5.04145143054765\n",
+      "4.626905122927891\n",
+      "5.273385307020021\n",
+      "5.272122961407117\n",
+      "4.843348473963515\n",
+      "4.166248702611916\n",
+      "4.6211216294464865\n",
+      "4.501245275101648\n",
+      "5.272424265386022\n",
+      "5.252277392229365\n",
+      "5.247192904831273\n",
+      "5.247195690351912\n",
+      "4.831918350974973\n",
+      "4.777588408536906\n",
+      "4.13509381127094\n",
+      "4.1335135022841625\n",
+      "4.132449023089341\n",
+      "5.013619988828199\n",
+      "4.27568320531201\n",
+      "4.735408041206037\n",
+      "7.059978845207535\n",
+      "5.358790783473463\n",
+      "5.358807930289463\n",
+      "5.3587287349614625\n",
+      "5.3588901908969415\n",
+      "5.358870456861258\n",
+      "5.358919738081574\n",
+      "5.481056961394493\n",
+      "7.867510234397285\n",
+      "4.044603796773676\n",
+      "3.9468581903756816\n",
+      "3.513332817875753\n",
+      "3.513353790231753\n",
+      "3.513379602787753\n",
+      "3.513279576261753\n",
+      "3.395676170760942\n",
+      "3.477362603578258\n",
+      "3.6709008475833693\n",
+      "3.7691383667389884\n",
+      "3.768792932010657\n",
+      "4.303481020872223\n",
+      "4.2997582661602225\n",
+      "4.296696219658223\n",
+      "5.400820423771824\n",
+      "5.124804777762705\n",
+      "5.36442931817986\n",
+      "4.5097942742202815\n",
+      "4.511133860076281\n",
+      "4.509632737596282\n",
+      "4.509689826850281\n",
+      "7.685040517663996\n",
+      "4.951087746316133\n",
+      "4.950940690304133\n",
+      "4.950926339130133\n",
+      "4.950917777890133\n",
+      "4.950943748784133\n",
+      "4.951790215518133\n",
+      "4.499768718020263\n",
+      "5.266443259785771\n",
+      "5.247157866943506\n",
+      "4.834456504415002\n",
+      "4.160005890504686\n",
+      "4.006424702462131\n",
+      "5.011696233815679\n",
+      "5.043866755387651\n",
+      "6.440262262974867\n",
+      "4.0486532380654765\n",
+      "3.9480294662456816\n",
+      "3.514133024851753\n",
+      "3.5146888187777527\n",
+      "3.4117116286328066\n",
+      "3.4045493750042373\n",
+      "4.01231151465298\n",
+      "7.464152464315696\n",
+      "4.381649771531\n",
+      "4.381641392485\n",
+      "4.381240264335\n",
+      "4.381239716841\n",
+      "4.381194612965\n",
+      "4.381103149281\n",
+      "4.381185361737\n",
+      "4.381172243287\n",
+      "4.381128627245\n",
+      "4.381153914775\n",
+      "4.381221874071\n",
+      "4.381961761471\n",
+      "4.548983485165905\n",
+      "5.262377389755726\n",
+      "4.704462082182644\n",
+      "4.129223917249435\n",
+      "4.133046125580067\n",
+      "4.134153051050162\n",
+      "4.1348225084281625\n",
+      "5.02119647629368\n",
+      "5.04024723159565\n",
+      "4.639894083921182\n",
+      "4.917456180654324\n",
+      "4.917411688856324\n",
+      "4.917541681570325\n",
+      "4.917627048726324\n",
+      "4.918309061874324\n",
+      "4.918941878246324\n",
+      "4.918461654880324\n",
+      "4.918088319308324\n",
+      "4.918695581724324\n",
+      "4.917994749778324\n",
+      "4.9176501731523246\n",
+      "4.919246309250324\n",
+      "6.1940668015316405\n",
+      "4.715321448047416\n",
+      "4.461577191919598\n",
+      "4.031148209921785\n",
+      "4.030669083520514\n",
+      "3.7142569813906827\n",
+      "3.730093768178592\n",
+      "4.0550486034368225\n",
+      "5.612615509953387\n",
+      "4.332496482808224\n",
+      "4.332378457326224\n",
+      "4.332448682306224\n",
+      "4.332574561124225\n",
+      "4.335669058276225\n",
+      "4.331867854708225\n",
+      "4.332196444316224\n",
+      "4.332988593854225\n",
+      "4.332678875192225\n",
+      "4.7077033575685\n",
+      "5.388091207985471\n",
+      "5.388175718923692\n",
+      "5.3940602090156915\n",
+      "5.387794587083691\n",
+      "4.344176260990225\n",
+      "3.7951602570992002\n",
+      "7.684925458421996\n",
+      "4.9510509694941325\n",
+      "4.951066832824133\n",
+      "4.950985742096133\n",
+      "4.950911006216133\n",
+      "4.950902397458133\n",
+      "4.950927189326133\n",
+      "4.961064449694133\n",
+      "5.307089435361559\n",
+      "4.245270388001565\n",
+      "3.6701020869768635\n",
+      "3.670189479984863\n",
+      "5.166002323135396\n",
+      "5.165706277103396\n",
+      "5.165656804099396\n",
+      "5.166448777663397\n",
+      "5.615456477335386\n",
+      "4.919332556382324\n",
+      "4.918634273594324\n",
+      "4.918157956092324\n",
+      "4.9179159671943244\n",
+      "4.918669633910325\n",
+      "4.917958640531166\n",
+      "4.78321365951773\n",
+      "4.771733439871584\n",
+      "4.2309938882506195\n",
+      "4.3519934495326345\n",
+      "4.134526628333363\n",
+      "4.187364367612347\n",
+      "4.487401008861223\n",
+      "4.1232022245533635\n",
+      "4.299093076783693\n",
+      "4.2844417966407145\n",
+      "4.800882388104355\n",
+      "7.3587095493742405\n",
+      "4.952421464812133\n",
+      "4.957056820350132\n",
+      "4.9542940317621325\n",
+      "4.952724044084133\n",
+      "4.626809633213891\n",
+      "5.2733613928120215\n",
+      "5.267746395610613\n",
+      "5.249309854129789\n",
+      "4.138390825398189\n",
+      "6.440333251044867\n",
+      "4.359745640147343\n",
+      "4.04845692359167\n",
+      "3.9477390681256814\n",
+      "3.513869247377753\n",
+      "3.514052360017753\n",
+      "3.3974346047682373\n",
+      "3.4001958133582373\n",
+      "3.682044905173369\n",
+      "4.3249276565362225\n",
+      "4.49964963742447\n",
+      "5.051665446532223\n"
+     ]
+    }
+   ],
+   "source": [
+    "for i in range(len(slopes_test[:,0])):\n",
+    "    print(np.abs(slopes_test[i,1]- Y_hat_test[i,1]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 174,
+   "id": "ceaaa22f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([4.781, 4.975, 4.578, 4.578, 6.81 , 5.645, 5.645, 6.942, 4.901,\n",
+       "       4.901, 4.901, 4.901, 6.831, 4.403, 4.403, 4.403, 4.403, 4.403,\n",
+       "       4.403, 4.403, 4.017, 5.859, 5.864, 5.86 , 5.86 , 5.645, 5.472,\n",
+       "       5.261, 5.261, 5.168, 4.993, 4.017, 5.859, 5.861, 5.645, 5.273,\n",
+       "       5.153, 4.193, 5.859, 5.856, 5.86 , 5.86 , 5.645, 5.482, 5.261,\n",
+       "       5.261, 5.261, 4.986, 4.215, 4.589, 6.942, 4.901, 4.901, 4.901,\n",
+       "       4.901, 4.901, 4.901, 4.956, 7.295, 5.299, 5.192, 4.988, 4.988,\n",
+       "       4.988, 4.988, 4.943, 4.892, 5.143, 5.213, 5.212, 5.606, 5.606,\n",
+       "       5.606, 6.024, 4.746, 5.038, 4.053, 4.053, 4.053, 4.053, 6.831,\n",
+       "       4.403, 4.403, 4.403, 4.403, 4.403, 4.403, 4.194, 5.864, 5.86 ,\n",
+       "       5.645, 5.273, 5.238, 4.986, 4.993, 5.586, 5.3  , 5.192, 4.988,\n",
+       "       4.988, 4.956, 4.943, 5.381, 6.43 , 3.949, 3.949, 3.949, 3.949,\n",
+       "       3.949, 3.949, 3.949, 3.949, 3.949, 3.949, 3.949, 3.949, 4.189,\n",
+       "       5.857, 5.498, 5.333, 5.261, 5.261, 5.261, 4.986, 4.993, 4.514,\n",
+       "       4.578, 4.578, 4.578, 4.578, 4.578, 4.578, 4.578, 4.578, 4.578,\n",
+       "       4.578, 4.578, 4.578, 5.627, 5.56 , 5.396, 5.259, 5.259, 5.003,\n",
+       "       5.078, 5.467, 4.92 , 4.564, 4.564, 4.564, 4.564, 4.564, 4.564,\n",
+       "       4.564, 4.564, 4.564, 4.626, 5.099, 5.099, 5.099, 5.099, 4.564,\n",
+       "       3.99 , 6.831, 4.403, 4.403, 4.403, 4.403, 4.403, 4.403, 4.403,\n",
+       "       5.11 , 4.166, 3.725, 3.725, 4.913, 4.913, 4.913, 4.913, 4.92 ,\n",
+       "       4.578, 4.578, 4.578, 4.578, 4.578, 4.578, 4.48 , 4.474, 5.169,\n",
+       "       4.643, 3.969, 3.978, 4.7  , 3.969, 4.585, 4.681, 4.866, 6.411,\n",
+       "       4.403, 4.403, 4.403, 4.403, 4.017, 5.859, 5.864, 5.863, 5.26 ,\n",
+       "       5.586, 5.436, 5.3  , 5.192, 4.988, 4.988, 4.943, 4.943, 5.143,\n",
+       "       5.606, 4.34 , 4.45 ], dtype=float32)"
+      ]
+     },
+     "execution_count": 174,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    " Y_hat_test[:,0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 177,
+   "id": "f91959e8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'Predicted Value')"
+      ]
+     },
+     "execution_count": 177,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 450x450 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from sklearn.metrics import r2_score\n",
+    "plt.figure(figsize=(3, 3), dpi=150, facecolor='white')\n",
+    "plt.scatter(-np.log(-slopes_test[:,0]), Y_hat_test[:,0], alpha=0.4)\n",
+    "# plt.scatter(-slopes_test[:,0], -Y_hat_test[:,0], alpha=0.4)\n",
+    "plt.plot([2,8], [2,8], color='C1', alpha=0.2, linestyle='--')\n",
+    "# plt.plot([0,0.06], [0,0.06], color='C1', alpha=0.2, linestyle='--')\n",
+    "plt.title(f'-log(-Slope 1) predictions')\n",
+    "plt.xlabel('Observed Value')\n",
+    "plt.ylabel('Predicted Value')\n",
+    "# plt.savefig('img/parity plot_100_slope_1.png', dpi=400, transparent=False)\n",
+    "#  R$^2$ =  {r2_score(-np.log(-slopes_test[:,0]), Y_hat_test[:,0]):.3f}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7d6f90a5",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 156,
+   "id": "770e873d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'Predicted Value')"
+      ]
+     },
+     "execution_count": 156,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 450x450 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from sklearn.metrics import r2_score\n",
+    "plt.figure(figsize=(3, 3), dpi=150, facecolor='white')\n",
+    "# plt.scatter(-np.log(-slopes_test[:,1]), Y_hat_test[:,1], alpha=0.4, )\n",
+    "plt.scatter(-slopes_test[:,1], -Y_hat_test[:,1], alpha=0.4, )\n",
+    "\n",
+    "# plt.plot([2,8], [2,8], color='C1', alpha=0.2, linestyle='--')\n",
+    "plt.plot([0,0.06], [0,0.06], color='C1', alpha=0.2, linestyle='--')\n",
+    "plt.title(f'-log(-Slope 2) predictions')\n",
+    "# plt.title(f'slo predictions for test data - R$^2$ = {r2_score(-np.log(-slopes_test[:,1]), Y_hat_test[:,1]):.3f}')\n",
+    "plt.xlabel('Observed Value')\n",
+    "plt.ylabel('Predicted Value')\n",
+    "# plt.savefig('img/parity plot_100_slope_2.png', dpi=400, transparent=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 157,
+   "id": "fa4a9e72",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1/1 [==============================] - 0s 47ms/step\n"
+     ]
+    }
+   ],
+   "source": [
+    "# testing on data\n",
+    "tested_cell = [test_cells[4]]\n",
+    "# X_train_tested_cell = [x for xs in train_cells for x in xs[0]]\n",
+    "# Y_train = np.array([x for xs in train_cells for x in xs[1]])\n",
+    "# Y_train_tested_cell = [x for xs in train_cells for x in xs[1]]\n",
+    "X_tested_cell = [x for cycle in tested_cell for x in cycle[0]]\n",
+    "# Y_test = [x for xs in test_cells for x in xs[1]]\n",
+    "Y_tested_cell = [y for cycle in tested_cell for y in cycle[1]]\n",
+    "dc_tested_cell, slopes_tested_cell = make_label_arrays(Y_tested_cell)\n",
+    "X_tested_cell_time_series, X_tested_cell_dt = make_feature_arrays(X_tested_cell)\n",
+    "\n",
+    "scaled_X_tested_cell_dt = standardize_non_train(X_tested_cell_dt, mean_X_train_dt, std_X_train_dt)\n",
+    "scaled_X_tested_cell_time_series = standardize_non_train(X_tested_cell_time_series, mean_X_train_time_series, std_X_train_time_series)[...,1:]\n",
+    "\n",
+    "# std_X_tested_cell_time_series = standardize(X_tested_cell_time_series[...,1:])\n",
+    "all_test_slopes = [y[0] for y in Y_tested_cell]\n",
+    "all_test_dc = np.array([y[1] for y in Y_tested_cell])\n",
+    "# Y_hat_tested_cell = model.predict([scaled_X_tested_cell_time_series, scaled_X_tested_cell_dt])\n",
+    "Y_hat_tested_cell = model.predict(scaled_X_tested_cell_time_series)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 158,
+   "id": "14357a14",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(10, 100, 100, 2)"
+      ]
+     },
+     "execution_count": 158,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "scaled_X_tested_cell_time_series.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 159,
+   "id": "79a58de3",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(10, 2)"
+      ]
+     },
+     "execution_count": 159,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "Y_hat_tested_cell.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 160,
+   "id": "047f792c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[-0.006 -0.008]\n"
+     ]
+    }
+   ],
+   "source": [
+    "for m in Y_hat_tested_cell:\n",
+    "    print(m)\n",
+    "    break"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 161,
+   "id": "cb987d36",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# for i,m in enumerate(all_test_dc[1:]):\n",
+    "#     print(i)\n",
+    "#     if i%2 == 0:\n",
+    "#         print(m[5,0])\n",
+    "#         n = m\n",
+    "#     else:\n",
+    "#         print(n[9,0])\n",
+    "#     print(m)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 162,
+   "id": "4c838cb5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def linear_fit(new_x_point, slope, point_xy):\n",
+    "    return slope*(new_x_point-point_xy[0]) + point_xy[1]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 163,
+   "id": "cc82e8e9",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(1.0, 4.0)"
+      ]
+     },
+     "execution_count": 163,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(dpi=200, facecolor='white')\n",
+    "plt.scatter(*list(zip(*all_test_dc.reshape([-1,2]))), color = 'C2', s=1, label='Ground-truth')\n",
+    "plt.xlabel('Cycles')\n",
+    "plt.ylabel('Discharge Capacity')\n",
+    "plt.ylim([1,4])\n",
+    "# plt.savefig(f'img/ground-truth.png', dpi=200, transparent=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 164,
+   "id": "c39804fe",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[-0.001, -0.001],\n",
+       "       [-0.001, -0.001],\n",
+       "       [-0.001, -0.001],\n",
+       "       [-0.001, -0.001],\n",
+       "       [-0.001, -0.001],\n",
+       "       [-0.001, -0.001],\n",
+       "       [-0.002, -0.004],\n",
+       "       [-0.003, -0.002],\n",
+       "       [-0.002, -0.003],\n",
+       "       [-0.003, -0.004]])"
+      ]
+     },
+     "execution_count": 164,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "slopes_tested_cell"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 165,
+   "id": "373df34d",
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1/1 [==============================] - 0s 49ms/step\n",
+      "predicted slope: -0.006156782619655132, True slope: -0.001181725401999998\n",
+      "predicted slope: -0.00776252243667841, True slope: -0.0007987043560000017\n",
+      "[array([100.   ,   3.805]), array([150.   ,   3.497]), array([200.   ,   3.109])]\n",
+      "predicted slope: -0.006224344484508038, True slope: -0.000872539341999996\n",
+      "predicted slope: -0.006782315205782652, True slope: -0.0006980968960000045\n",
+      "[array([200.   ,   3.704]), array([250.   ,   3.393]), array([300.   ,   3.054])]\n",
+      "predicted slope: -0.006224334239959717, True slope: -0.0008011742580000014\n",
+      "predicted slope: -0.006782321725040674, True slope: -0.0006862739259999984\n",
+      "[array([300.   ,   3.625]), array([350.   ,   3.314]), array([400.   ,   2.975])]\n",
+      "predicted slope: -0.006146408151835203, True slope: -0.0007818841600000059\n",
+      "predicted slope: -0.006833966355770826, True slope: -0.0007358472319999975\n",
+      "[array([400.  ,   3.55]), array([450.   ,   3.243]), array([500.   ,   2.901])]\n",
+      "predicted slope: -0.006146651692688465, True slope: -0.0008182830299999999\n",
+      "predicted slope: -0.006833805236965418, True slope: -0.0007853244579999963\n",
+      "[array([500.   ,   3.473]), array([550.   ,   3.166]), array([600.   ,   2.824])]\n",
+      "predicted slope: -0.006146497558802366, True slope: -0.0006464799739999982\n",
+      "predicted slope: -0.0068339076824486256, True slope: -0.0009677629260000043\n",
+      "[array([600.   ,   3.392]), array([650.   ,   3.084]), array([700.   ,   2.743])]\n",
+      "predicted slope: -0.005890450906008482, True slope: -0.0016249467319999944\n",
+      "predicted slope: -0.007005227264016867, True slope: -0.004468823618000002\n",
+      "[array([700.  ,   3.31]), array([750.   ,   3.015]), array([800.   ,   2.665])]\n",
+      "predicted slope: -0.005350216291844845, True slope: -0.002942159023999995\n",
+      "predicted slope: -0.007375457789748907, True slope: -0.002334289578000002\n",
+      "[array([800.   ,   3.001]), array([850.   ,   2.734]), array([900.   ,   2.365])]\n",
+      "predicted slope: -0.0045004067942500114, True slope: -0.0016790409579999998\n",
+      "predicted slope: -0.007984805852174759, True slope: -0.0025951821040000045\n",
+      "[array([900.   ,   2.736]), array([950.   ,   2.511]), array([1000.   ,    2.112])]\n",
+      "predicted slope: -0.004500318318605423, True slope: -0.0028661796360000035\n",
+      "predicted slope: -0.007984869182109833, True slope: -0.0038808352660000003\n",
+      "[array([1000.  ,    2.52]), array([1050.   ,    2.295]), array([1100.   ,    1.896])]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# testing on data\n",
+    "tested_cell = [test_cells[4]]\n",
+    "# X_train_tested_cell = [x for xs in train_cells for x in xs[0]]\n",
+    "# Y_train = np.array([x for xs in train_cells for x in xs[1]])\n",
+    "# Y_train_tested_cell = [x for xs in train_cells for x in xs[1]]\n",
+    "X_tested_cell = [x for cycle in tested_cell for x in cycle[0]]\n",
+    "# Y_test = [x for xs in test_cells for x in xs[1]]\n",
+    "Y_tested_cell = [y for cycle in tested_cell for y in cycle[1]]\n",
+    "dc_tested_cell, slopes_tested_cell = make_label_arrays(Y_tested_cell)\n",
+    "X_tested_cell_time_series, X_tested_cell_dt = make_feature_arrays(X_tested_cell)\n",
+    "\n",
+    "scaled_X_tested_cell_dt = standardize_non_train(X_tested_cell_dt, mean_X_train_dt, std_X_train_dt)\n",
+    "scaled_X_tested_cell_time_series = standardize_non_train(X_tested_cell_time_series, mean_X_train_time_series, std_X_train_time_series)[...,1:]\n",
+    "\n",
+    "# std_X_tested_cell_time_series = standardize(X_tested_cell_time_series[...,1:])\n",
+    "all_test_slopes = [y[0] for y in Y_tested_cell]\n",
+    "all_test_dc = np.array([y[1] for y in Y_tested_cell])\n",
+    "# Y_hat_tested_cell = model.predict([scaled_X_tested_cell_time_series, scaled_X_tested_cell_dt])\n",
+    "Y_hat_tested_cell = model.predict(scaled_X_tested_cell_time_series)\n",
+    "\n",
+    "# initial_dc = all_test_dc.reshape([-1, 2])[cycle_indices[0]]\n",
+    "# index_0 = initial_dc[0]\n",
+    "# for i,m in enumerate(all_test_dc.reshape([-1,2])):\n",
+    "#     plt.scatter(*list(zip(*all_test_dc.reshape([-1,2]))), color = 'C2', s=2, label='Ground-truth' if i == 0 else \"\")\n",
+    "\n",
+    "window_size = 100\n",
+    "scatters = []\n",
+    "for i,m in enumerate(all_test_dc[1:]):\n",
+    "    plt.figure(dpi=200, facecolor='white')\n",
+    "#     print(m[0,0], m[5,0], m[9,0])\n",
+    "    plt.scatter(*list(zip(*all_test_dc.reshape([-1,2]))), color = 'C2', s=1, label='Ground-truth') #if i == 0 else \"\")\n",
+    "#     if i == 0:\n",
+    "#         initial_dc = m[0]\n",
+    "    initial_dc = m[0]\n",
+    "#     print(m)\n",
+    "#     print(m)\n",
+    "#     break\n",
+    "    predicted_dc_values = [initial_dc]\n",
+    "#     print(initial_dc)\n",
+    "#     if i%2 == 0:\n",
+    "    new_cycle_index = m[0,0]\n",
+    "#         print(f'hi {i}')\n",
+    "    for j,slope in enumerate(Y_hat_tested_cell[i]):\n",
+    "        new_cycle_index += window_size//2\n",
+    "        new_predicted_dc = linear_fit(new_cycle_index, slope, initial_dc) # slopes_tested_cell[i,j]\n",
+    "#         new_predicted_dc = linear_fit(new_cycle_index, -np.exp(-slope), initial_dc)\n",
+    "\n",
+    "        print(f'predicted slope: {slope}, True slope: {np.array(slopes_tested_cell)[i,j]}')\n",
+    "        predicted_dc_values.append(np.array([new_cycle_index , new_predicted_dc]))\n",
+    "        initial_dc = predicted_dc_values[-1]\n",
+    "#         print(initial_dc)\n",
+    "      # \n",
+    "    print(predicted_dc_values)\n",
+    "#     initial_dc = np.array([new_cycle_index, new_predicted_dc]) \n",
+    "    \n",
+    "#     print(i)\n",
+    "#     print(predicted_dc_values)\n",
+    "#     initial_dc = predicted_dc_values[-1]\n",
+    "    \n",
+    "#     if i==2 or i==1:\n",
+    "#         print(m)\n",
+    "#         break\n",
+    "#     if i ==2:\n",
+    "#         break\n",
+    "    scatters.append(predicted_dc_values)\n",
+    "#     print(np.array(scatters).T)\n",
+    "    plt.plot(*np.array(scatters).T, color='C0', label='Inferred', #if i == 0 else \"\",\n",
+    "             marker='o', markersize=1)\n",
+    "    plt.scatter(*np.array(predicted_dc_values[-1]).T, c='C3', #if i == 0 else \"\",\n",
+    "         marker='o', s=50, edgecolor='k', linewidth=1, facecolor='C3', zorder=-1)\n",
+    "    plt.xlabel('Cycles')\n",
+    "    plt.ylabel('Discharge Capacity')\n",
+    "    plt.ylim([1,4])\n",
+    "    ax = plt.gca()\n",
+    "    hand, labl = ax.get_legend_handles_labels()\n",
+    "    plt.legend(np.unique(labl))\n",
+    "    plt.tight_layout()\n",
+    "#     break\n",
+    "#     plt.savefig(f'img/discharge_curve_100_window_test_4_{i:04d}.png', dpi=200, transparent=False)\n",
+    "#     if i ==20:\n",
+    "        \n",
+    "#         break\n",
+    "#     plt.close()\n",
+    "#     break\n",
+    "#     break\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "id": "91cc3a74",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "-0.0011800000000000033"
+      ]
+     },
+     "execution_count": 50,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "(3.746 - 3.805)/50"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "id": "e0fbd984",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2.9259096291"
+      ]
+     },
+     "execution_count": 49,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "linear_fit(150, -0.017581807418000004, [100, 3.805])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1067,
+   "id": "167fb203",
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1/1 [==============================] - 0s 242ms/step\n",
+      "slope: -0.0008221308817155659\n",
+      "slope: -0.0007360809249803424\n",
+      "[array([100.   ,   2.785]), array([150.   ,   2.744]), array([200.   ,   2.707])]\n",
+      "slope: -0.000848281430080533\n",
+      "slope: -0.00074186542769894\n",
+      "[array([200.   ,   2.663]), array([250.   ,   2.621]), array([300.   ,   2.583])]\n",
+      "slope: -0.0008483611745759845\n",
+      "slope: -0.0007419254980050027\n",
+      "[array([300.   ,   2.565]), array([350.   ,   2.523]), array([400.   ,   2.486])]\n",
+      "slope: -0.0008491977350786328\n",
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+      "slope: -0.0008501758566126227\n",
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+      "slope: -0.0008560233982279897\n",
+      "slope: -0.0007463083020411432\n",
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+      "slope: -0.0008555512176826596\n",
+      "slope: -0.0007459397311322391\n",
+      "[array([700.  ,   1.64]), array([750.   ,   1.598]), array([800.  ,   1.56])]\n"
+     ]
+    },
+    {
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+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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6oi5evOiKEoFqIa/zSZJGaqQ9gFqfsF6r4ldVeO7TyviVWhm/ktlPAAAAAACXcEng1LFjR504cUI///yz+vbtK0ny9PRUx44dtXfvXi1evFiDBg0qcM8HH3wgSYWCKKAusW+9axmlKT2maPfp3dp2cluFh44X1f1kyNDEqycqskGkUrNSCaEAAAAAAJXmksCpb9++WrNmjdavX68HHnjAfvyOO+7Qjz/+qHfffVeNGzfWmDFjdPnyZUVHRysmJkaGYWjo0KGuKBGo9vKHT/m33u06vatS3U+mTM39cW6h42zDAwAAAABUlGGaZsXfzV5G+/fvV+fOneXv76/ExEQFBgZKktLS0tSpUycdOXJEhlFwWLJpmgoODtaePXsc9kq+uspZrzhE9ZGUnlTp7qfi5N+GR/cTAAAAANQuzsoMXBI4SdKGDRtktVrVrVs3BQcH248fPXpU99xzj7Zs2VLg+k6dOumDDz5Qly5dXFFerUbgVLfkhU+VnftUktGRo3Vn2zt1NPWoZIgQCgAAAABqqBofOJXm4MGD2r9/v6xWq9q0aaNu3bpVdUm1BoFT3ZUXPlXmrXdlNTxiuLo37E4XFAAAAADUILU+cILzEDghT/4AatfpXVp9eLVsps3h6+Rtw+vdpDfhEwAAAABUYwROqDACJxQnKT1J8SnxCvIK0tHUo07bhjc6crQmdZ1E8AQAAAAA1UytCpysVqu+//577d27V8nJyZKk4OBgderUSddcc43q1avn6pJqNQInlIeztuEZMjTx6omKbBDJ3CcAAAAAqCZqReB0+fJlPffcc1qwYIE9aLpSgwYNdN9992natGkKCAhwVWm1GoETKsMZQ8ht2QEyTTf1b3i7Hulzp9qFNnFApQAAAACA8qrxgdPBgwd100036dixYyptScMwFB4eri+//FJt27Z1RXm1GoETHCUvfJIhtQhoocUHF1eoA+pS3N9kWhtIMiSZamy5qJHdWivIP0u9W7RSh7AmcnMznPI9AAAAAAB+U6MDpwsXLqhjx446efKkTNNUp06dNG7cOPXq1UsNGzaUJJ0+fVo7duzQwoULtXfvXklS06ZNtW/fPtWvX9/ZJdZqBE5wpvxb8CTpwLkDiomNKfb6nGx/pf3ylHLDpqK5u+WoUZCH2jYMUvtGwWpl8Vcri58iLH5q4Ofp6G8BAAAAAOqsGh04Pfnkk3rxxRdlGIZmzpypJ598UoZR9B82TdPUCy+8oGnTpskwDD3++OP65z//6ewSazUCJ7haUnqS5uyZU2TwlJ3aURnH/1DhZwf51lOExU+tLP6KCPVTK8tvX9713CtTNgAAAADUOTU6cGrfvr1iY2M1ZswYffLJJ2W656677tLixYvVtm1b/fTTT06usHYjcEJVyQuelsYtlc20SZKsF9sqPfFep6zXNMinQADVKtRPrS3+atrAR+5s0QMAAACAQmp04OTr66vMzEx9/vnnGjJkSJnu+fLLLzV06FB5e3srLS3NyRXWbgROqGpJ6UmKT4lXkFeQFh9crA+3JSjz9DBJ7pJscvNOlOQmW1aoZPNy+Pqe7m5qHuJr35aX2xmVu03P4u9ZbMclAAAAANR2zsoMPBzylFIEBAQoMzNTYWFhZb4n71p/f39nlQXARSw+Fll8LJKk6X2m66GuSXpl23z996fvZHidlpvHJUmSaUqmNUC2LIv9y8wK/fVzsCr6W1ZWjk2/nLmkX85cKnQuwMtDrUL97Nv08j63tPjJ38slv0UCAAAAQK3jkj9Nde7cWevXr1dcXJy6detWpnvi4uLs9wKoXSw+Fr0w4An9pfdvb72LS47T3B/nyqx3UW71Lkp+hwvcY5puMrMb/BZGZeaFUqEyrUEVruViplU/Jl7Qj4kXCp0LC/Cyd0NF5Num1zzYV/Xc3Sq8JgAAAADUdi7ZUrdkyRLdcccd6t27tzZv3iw3t5L/oGaz2XTddddp+/bt+vjjj3XHHXc4u8RajS11qCny3ni3PmG9Vh9ebZ/7VBrTVq9AV5QtK/TXQCpUsvk4vE53N0PNg30LzIuKCPVThMVfDQO92KIHAAAAoMao0TOcJOm+++7Te++9p2HDhmnevHlq1KhRkdedPn1aEydO1IoVK3TvvfdqwYIFriivViNwQk105dynJbFLZKp8v12ZpmTm+MrMC6EK/DNEMus5vG5fT3e1DPGzb82LCPVTkI+nrDmmujSvr7AAb4evCQAAAAAVVaMDp/fff1+S9Pbbb2vHjh3y9vbWjTfeqJ49eyosLEyGYej06dPasWOH1qxZo8zMTPXo0UOTJ08u8bljx451dum1AoETaoOKdj8VxzQNmdb6smWG2mdFNfHqpkuXfXTuoilTzulSahrko67hQQoP9lXzYF+1CMn9Z+P63vJgmx4AAAAAF6vRgZObm1uBLSamaRa75aSkc/kZhiGr1eqwGmszAifUNo7ofiqJafOQLTtYtsxQdao/QCHuHXTo7EWdSrHpUoZzgih3N0NNg3zUPNhXzX8NofK+woN9Vd/H8d1YAAAAAFDjAydHMwxDOTk5Dn9ubUTghNour/spNStVknTg3AGHh1B5zBwf2bJC1KX+jQrxaKfMjCAdT7bqcNJlpWc77/ekIN969vApL4hq8euv6Y4CAAAAUFE1OnA6evSoU57bokULpzy3tiFwQl2UfwveqvhVTgmfJMmQodGRo9U+uINS06SzqW5KvewjMytUR5OyteWXc05ZNz8PN0NNG/gU6Iqyh1Mhvgr0pjsKAAAAQNFqdOCEqkXghLouL3ySIcUlx2nuj3OdFkDlyQuiUpM6a9m3HrKZhtwM6ZYuTdQw0FvHktN09FyajiWn6VKmc7cHN7iiO6pFyG+fG9f3kbsbb9UDAAAA6ioCJ1QYgRNQUP4teLtO73LIEPKS2Kz+smWGyc3rjO7oMFR3tr1TR1OPSobUNbSrPMz6Opac9tvXud8+n7yQLpsTf5eu5/7r7KgQPzUP9inYHRXsqwC6owAAAIBajcAJFUbgBJQs/xDyo6lHnb4N70rDI4ZrQPMBahHQwh5EdQvrJouPRVlWm46npNsDqIRfA6mjv352dndUsJ9nvrlRPmoR7Gffqtco0JvuKAAAAKCGI3BChRE4AeWXfxteXhBUFUFU94bdFegVaA+g8jNNU+fTsvN1Rl3OF0yl68SFdDnzd/h67oaaNSg4NyrQp55sNlN9WoeopcXPeYsDAAAAcIhaEzitX79en332mX744QclJSUpPT1dJZVgGIYOHTrkwgprHwInwHHyb8dz5tvwrpQ3E6pDSAf7seKCqDyZ1hwdP5/+W2fUr19Hz+X++nKWc9/0+fv/a65/jOjs1DUAAAAAVE6ND5zOnDmjO++8Uxs2bJCkYkMmwzAKnDMMQzk5zv1DUW1H4AQ4T/4AKo+rg6iJV09UZIPIAlvxSmOappIvZxU5NyohOU0nUzMq3R3l7mZo6xMDFRbgXbkHAQAAAHAaZ2UGHg55Simys7M1dOhQ7dmzR6ZpqmvXrmratKlWr14twzB0zz33KDk5Wd9//71OnjwpwzB0zTXXqFOnTq4oDwAqzOJjUVTLqALHRmqkHur6UIHB5M7aimfK1Nwf5xY4ln8mVEpmiiKCIgqFUIZhKMTfSyH+XurWvEGh52Zac5SYvzsqXyB1LDlNaWXojsqxmfrlzCUCJwAAAKAOckmH0/z58zVx4kQZhqF3331X48aN0/79+9W5c+dCHUyfffaZHn74YZ0/f17vv/++Ro4c6ezyaj06nICqd+VMqMUHF7u0C2pYxDANaD6gzB1QJTFNU+d+7Y5K+HWLXuzpi1r948kC342Hm6Fv6XACAAAAqrUavaXupptu0po1azR06FCtXr1akooNnCTp0KFD6tGjh6xWq77//nu1adPG2SXWagROQPWUfzteoFegy4Ko0ZGjdWfbOwu9Ea+yFm0/pmmf7ZPVZsrdzdA/buukO3s1d0DFAAAAAJylRgdOjRs31pkzZ/Thhx/qrrvuklQwcLJarTKMgq/WnjFjhmbOnKlJkybprbfecnaJtRqBE1CzXDkXyhUzocqyDa8szlzM0C9nLumqMH86mwAAAIAaoEYHTl5eXrJardqyZYt69+4tSYqLi1Pbtm1lGIZSU1Pl51fw9dmbNm1S//791aZNGx08eNDZJdZqBE5AzXdlCLXr9C6tPrxaNtPmlPXytuF1b9hdUulvxAMAAABQM9XooeGenp6yWq3y9PS0HwsMDLR/Pn78uCIjIwvc4+3tbT8HAHXdlcPJR0aO1JQeUxSfEq8gryCHb8UzZWpl/EqtjF9pP2bI0OjI0eoQ0kESIRQAAACA4rkkcGrevLl+/vlnnT592n6sYcOGCggI0KVLl/Tdd98VCpz27dsnSYW22gEAcll8LPawZ3qf6QXejBfoFai45DjN/XGuQ0OomNiYAscMGZp49URFNohUSmaqLqVLl9L8FdWms9qFNnHIugAAAABqHpcETtdcc41+/vln7d69W0OHDrUf79evn1avXq3XX39dY8aMkZeXlyQpJSVF//rXv2QYhjp06OCKEgGgxruyCyqqRZTGtBuj3ad3a33Ceq2KX+XwOVCmTM39ca4k6dIvf5GZbZFk1SvapdZN12ri9VfL8Dyj+n7SNQ2voRsKAAAAqCNcMsMpOjpaEyZMUJ8+fbRlyxb78dWrV2v48OEyDENXXXWVbrnlFl2+fFkrV67U8ePHZRiG3njjDU2ePNnZJdZqzHACIP02B0qGHP5GPJvVX5fjnpJUTFeqW4bcPM+qeYiXujZtrN4tWqlr08ZqGeIn73rulV4fAAAAQMXU6KHhKSkp6tq1q0zT1Lp169S6dWv7ufvvv1/vvvtubjG/bp/LK2nIkCFavXq13NzcnF1irUbgBKA4+YeRV2YbXnZqB2UcH1vu9Q2ZauBvKizIVLPgeuoR3lxdmjRS61A/hQZ4sa0aAAAAcLIaHTiVZsGCBXrnnXe0f/9+Wa1WtWnTRmPHjtUjjzwiDw+X7Pqr1QicAJTHlW/Ek6QD5w6U2A1lvdhW6Yn3OrQO73qmGjVwU4dGIerQKFgRof5qHeqvFiG+dEUBAAAADlKrAyc4F4ETAEfIH0TtOr1Lqw+vls20SZJMm4eykgYo69wASW6STBkeF2Tm+EqmZ4nPLS9DkiVQahNWX+0aBqt1mJ8iLP5qHeanUH+6ogAAAIDyIHBChRE4AXCGpPQkxafEK8grSEdTjyo1K1Wbj/6oL+N+kOF1Wm4el2SahkxroGyZYbJlheZ+ZVpkywqVaQ1yeE3e9Uw1buCm9r92RbUO9VcEXVEAAABAsQicUGEETgBcqazDyU2bpz18yg2ifv1nlsXxXVGGZAnI7Ypq3yhYEaF+v4ZRdEUBAACgbqtRgdMXX3yhp556SpI0depU3X333WW+9+OPP9bLL78sSfr3v/+twYMHO7q8OofACUBVy78dr7R5ULldUfXzBVB5XVFhMq31HV6bj6cUEeqntmFBah3mrwiLn1qH5XZFeXnQFQUAAIDarcYETqZpqn379oqLi9PgwYP15Zdflvv+IUOGaO3atercubN++OEHR5ZXJxE4AahurhxMfuVMqOKYOZ72LqiCXVGhklnPoTW6GVJ4sK8iLH72geV5nVEWf0+dvZSpX85c0lVh/goL8Hbo2gAAAICr1JjA6euvv1ZUVJTc3d31ww8/qEOHDuV+xoEDB9SlSxfZbDatW7dO/fv3d2SJdQ6BE4Ca4MqZUOsT1mtV/KpiO6HyK7orKvTXWVGO74ry8nBTpjU3HHMzpFHdm+mOnuEKD/Zlix4AAABqFGdlBh4OeUo+y5YtkyRFRUVVKGySpA4dOmjIkCH64osvtHTpUgInAKgDLD4WWXwskqTI4EhFtYzSlB5T7J1QgV6Bxc6EMgxTRr0UudVLkRRX4LkFu6LC7NvzcmdFVawrKi9skiSbKcXsTFTMzkRJkk89dzUP9lV4sK9ahPiqebCvmv/6z2YNfNimBwAAgDrB4YHT9u3bZRiGhg8fXqnnDBs2TJ9//rm2bdvmoMoAADWNxceiqJZRBY5N7zNdD3V9qFAQVVxXlOGeJXef43L3OV7gOYW6ovJ1R1WmKyo9O0cHT1/UwdMXC50zDKlxoLc9gGoR4pcbTAXn/jrItx7dUQAAAKgVHB44HT16VJLUtm3bSj0nMjJSknTkyJHKlgQAqGWKCqKc0xVVcGh5ZbqiJMk0pRMXMnTiQoa2xScXOh/g7ZHbEZWvK6pFsJ+aB/uqSZC3PNzdKrw2AAAA4EoOD5wuXLggSQoODq7Uc/LuT01NrXRNAIC6ozxdUUUFUVIpXVHZQcpKvlbZ56+T5CbJlOF+UabNp9KDyy9mWLX/RKr2nyj8v33uboaaBvmoRYhvga6ovGAqwNuxQ9MBAACAynB44BQYGKjz588rJSWlUs/Juz8gIKDyRQEA6rzSgqj1CetLfVOeYZgyPM/Lu9FqeVo2yJYZJjevM3LzuPTrFr0A2bJCZGYHy5YVIlt2sGxZwTKzg2Xm+Feq/hybqWPJaTqWnFbk+WA/T4UH53VFFQyjGgV6y82NrXoAAABwHYcHTqGhoTp//rwOHDigG264ocLP+emnnyRJYWFhDqoMAIDC8oKovO14ZX1TnpvHJbl5XLL/OneLXqrc6qVKOlzoejPHK18AFSJbVnC+XzeQVLlh4smXs5R8OUs/JKQUOufp7qZmwT75gii/X2dI+Sq8ga98PBlkDgAAAMdyeODUq1cvHTx4UCtXrtSkSZMq/Jz//ve/MgxDPXv2dGB1AAAUr6Q35clQidvwSmO4Z8rd/aTcvU8WOmeabjKz68v2axBl/hpE5XZJhUg270p9X1k5NsWfvaz4s5eLPB8W4FV4dtSvW/dC/b109lKmfjlzSVeF+SssoHK1AAAAoG4wTNMs3/9jLsWiRYt09913yzAMbdiwQddff325n7Fx40bdcMMNMgxDH330ke68805HlljnJCYmKjw8XJKUkJCgZs2aVXFFAFCzJaUn2edBSVKgV6DikuM098e55Q6iSmOaknJ87d1QtuxgmfbteiEyrYHKnSXlHPXcDWXn5H5PhiE9MqiNHh0c6bT1AAAA4FrOygwcHjhlZ2erbdu2OnLkiBo2bKiNGzeqTZs2Zb4/NjZW/fr109mzZ9WyZUsdPHhQHh4Ob8SqUwicAMA1XBlE5TFt7jKzG+QLpEJk/vpPW1awZHo6dD13w9DWJwfS6QQAAFBLOCszcHiSU69ePb388ssaNWqUzpw5o+7du+u5557T/fffLz8/v2Lvu3Tpkt555x09/fTTunTpkgzD0CuvvELYBACoMYoaTB7VIkpj2o2xB1G7Tu8qdTh5eRhuOTK8kuTmlVTonGlKZo5/gQDKHkhlBcvMCSz3ejmmqV/OXCJwAgAAQIkc3uGU57nnntMzzzwjw8h9K46fn5/69u2r7t27KywsTH5+frp8+bJOnz6t77//Xps2bdLly5eVV87MmTM1bdo0Z5RW59DhBADVS1J6UoHh5HkdUY4Oo0pj2urlmxlV8K16tuxgySz8lz7uboa2PkGHEwAAQG1RY7bU5ffee+/pT3/6k9LScl/hnBc+FSWvDF9fX7311lsaP368s8qqcwicAKDmKCqMcnUQJUmmaci0BuryoUcl01uSIcmUm9dJ3XyNh7o2baKGQYZ6N73GPmgdAAAANU+NDJwk6cSJE3r11Vf1/vvvKympcLt/HovFonHjxumxxx5TkyZNnFlSnUPgBAA1X3FB1Kr4VU6bD5WT7a+0X55SbthUNMPjvBoGSVeFBah5iJe6NGmkQL909Wh2lUJ9Q51SFwAAABynxgZO+e3fv18//PCDzp07p4sXLyogIEAhISHq0qWLOnbs6Koy6hwCJwCovfIGlcuQWgS0cGhXVHZqR2Uc/0PFbjYy1SAgWy0tPgoP8VSnRqEKCsjUtS1bq1lgwwrXBAAAAMeqFYETqgaBEwDUTZWdFZWd2kEZx8c6vC5fnww1C66nsPqmmod46fqWbdStWRM1CvQucfs9AAAAHI/ACRVG4AQAuFJxYZQkBXoFKi45TnN+mKvMc9cr6+xQSW6SbDI8z0iml8zsBg6vycvDVMMgN3VoHKz2DUMUEeqn1qH+amXxk4+nu8PXAwAAAIETKoHACQBQEXnb9RJTUrX58C/afn6F5J4bTOW+4c6S+5UZ9uvnUNkyQyXTy+G1NPA31biBm65uHKaOjS2KCPVX61B/NQz0oisKAACgEpyVGRR+33EdsXPnTn3++efavHmzDhw4oLNnz6pevXpq0qSJrrvuOt133326/vrrK73OjBkz9Oyzz5bp2vXr1+uGG26o9JoAADiCxceiqJZRkqR7u0pJ6ffZu6IWH1ysJbFLZHqfLHCPaUqmNdAePtmyfvuqTFfU+UuGzl8ydSDhtKTT9uNeHqZC65tqEuyhbk0bq3OTMEVY/BUR6ifvenRFAQAAVJU6GTj169dPmzZtKnQ8KytLcXFxiouLU3R0tMaOHav58+fL09OzCqoEAKB6sfhYZPGxSJKm95muh7o+pN2nd9u34+VtxZv741y51UuV/A4VuP+3rqi8MKryXVGZVkOJ5wwlnrNpe9xxScclSYZMBflLTRq4qfOvXVGtQ/0VQVcUAACAS9TJwOnEiROSpCZNmmj06NHq27evmjdvrpycHG3dulWvvPKKjh8/rvfff1/Z2dn6+OOPHbLu3r17SzzfqlUrh6wDAIAr5O+AyhPVIkpj2o0pNogyvE/KvaxdUZmhMq0V64oyZej8Jen8JVP7i+mKCq1vqnmIp3q3aKWuTRurlcVPqRnZ+uXMJV0V5q+wAO8KrV2dZWRkaO3atdqxY4cOHDig9PR0+fj4qEOHDurZs6cGDx4sb+/a930DAADXq5MznIYNG6axY8dq5MiRcncv3G6flJSk6667TrGxsZKkDRs2qF+/fhVaK/+Wuqr6UTPDCQBQHeTNhMo/oPzAuQO5W/NU9P9GFu6K+rUzyimzovJqMGRIGtg+WKO7t1LzYF81D/GVv1fN/Xu61NRUvfjii5o/f76SkpKKvc5iseiBBx7Q3//+dwUGBrqwQgAAUFUYGu5iq1at0vDhwyVJf/rTn/TGG29U6DkETgAAlCwviFqfsF6r4lcVGz7l91tXVJhsmRaHdEWVxt/bVEiAqeAAU00b1FP3Zi3VoWGYWoT4KSzAS25u1XOb3tq1azVhwgQlJCSU+Z7w8HC99957GjRokBMrAwAA1QFDw11swIAB9s+HDh0q4UoAAFAZeVvzolpGaUqPKdp9erdkSC0CWuho6lGlZqVq1+ldBcIow5CMeqm/zor6pcDziuyK+vWfMis+l/FShqFLGYaOnpV2y6ZVu+IlxUuSPNxNhQYaam0J0lWhQWoe7KsWIb5qHuyr8GDfKhtg/tFHH2ncuHHKycnJrVPSkIBADfT3V3tvb9V3c9MFm00/ZWRo3aVL+vJiqqzK/T+bQ4YM0cKFC/X73/++SmoHAAA1G4FTMTIzM+2fi9p2BwAAHO/KuVCRwZGSpJGRI0sMo1YfXi2baZMkGW7Zci9xVlReV1SYfXteZbuirDmGTp6XTp5P0ea4lELnGwZ6qUWwn8LzBVHNf/1niJ+nU4aYr127VmPHjpXNlvtz6e3rq+caNVLTegVDtwaSWnp6amhgoB7Ntmj6qVPalpamnJwcjRs3To0aNaLTCQAAlBuBUzE2bNhg/9y+fXuHPPPGG2/Unj17lJKSoqCgIHXo0EE33XSTJk6cqAYNnNP+DwBAbVFaGBWfEq8gr6AKd0VlneuvrKSBktwk2WR4npNs9WRaA389VnGnUzN1OjVT248kFzrn5+mu8GDfAl1RzUP81DzYV02DfOTpUf61L1y4oAkTJtjDpjuDgjQtrKHcSgm2mtbz1DvNwvXc6dNafCFFOTk5uvfee7Vv3z5mOgEAgHJx+Qwnm82m9evXa+vWrTp16pTS0tL0j3/8Q40bN7Zfk5WVJavVKnd3d3l5OXogaNlq7NOnj7Zv3y5J2rlzp7p3716hZ+Wf4VScoKAgRUdH69Zbb63QGomJiSWeP3nypHr16iWJGU4AgLolbz7UlV1Rea4cWm6z+suWGSY3rzNy87gkSTJtHrJlN5CZHSxbVohs2cGyZQX/+uvgSm3TK42bITWu71OoK6p5sK9aBPupvm+9Iu978skn9cILL0jK7Wx6p1l4qWFTfjbT1P2JCdqWliZJeuKJJ/TPf/6z8t8QAACodmrF0PBVq1bpz3/+s44ePVrg+N69e9WhQwf7r2fPnq0//elP8vf314kTJ+Tn5+eqEiVJr7zyiqZOnSpJuv3227Vs2bIKP2vGjBlavny5brvtNvXq1UtNmjRRdna2Dh48qI8++khr1qyRlLttb+XKlRo6dGi51yhPGz6BEwAABV359rwrt+iVJHebXoBs2cEy84VReb82cwKcWnugt4da/NoNlRdGNfb30JibB+ns0Vh5mDZ9ERFRaBtdWSRmZel3h+NlVe7b6xITE6vkLwIBAIBz1fjAaf78+frjH/9of1ObxWJRUlKSDMMoFDhlZWWpUaNGunDhghYuXKh77rnHFSVKyt1KN3jwYFmtVoWFhWnv3r0KCwur8PPyts8V5z//+Y/++Mc/SpKaNGmiQ4cOydvbu1xrEDgBAOBYSelJhbbo5XdlZ1RxcgeYB8uWHSLz1yAqr0vKzGogZ043MHOs8rqYpM6ZKWp0OVmN086p0eVzanz5nBqlJSvD3VMJAWEKv3hGwZkXi3zG1BPH9fnF3HOrVq3SzTff7LR6AQBA1ajRb6mLi4vT5MmTJUkDBw7UW2+9pXbt2snNreiZBJ6enho5cqQWLFigNWvWuCxw2r9/v0aMGCGr1Spvb28tWbKkUmGTpBLDJkmaOHGiduzYoQULFujEiRNatmxZud8GU9prjvNvqQMAAKWz+Fhk8bFI+m1WVH4jNVIPdX3I3hlVXFdU7gDz03L3Pl3oGaZp/DrEPKTIDinlVK7D23D3UFZQI+1So6IvME3JMGSYpu6IXatxP31Z6JJB/gH2wGnHjh0ETgAAoMxcEjjNmjVLVqtVnTp10ueffy5Pz9Lbuvv27asFCxZo9+7dLqhQOnz4sG688UadP39e7u7uWrRokfr16+eStSdOnKgFCxZIyu2wKm/gRMcSAACul3+IeVGDy9cnrC8wtPxKhmHKqHdBbvUuSIovdN7M8bZ3R+WfGWXLDpaZ3UCVHWSuXzukTcNQTJuBGh7/baFOp/b5uq73799fufUAAECd4pLAad26dTIMQ48++miZwiZJuuqqqySV3r3jCCdOnNDgwYN14sQJGYahd999t8IDvCsi/3bC48ePu2xdAADgOFd2RUW1jNKUHlPsXVCBXoFqEdBCiw8uLtN2PMM9Q+4+J+Tuc6LQOdN0k5kddMUQ8xB7QCVb+WYt2dzc9VNomK5LLBg4BebrRk9PTy/XMwEAQN3mksAp7y1qXbp0KfM9eYPC0359O4qzJCUlKSoqSvHxuX+z+Oabb2rs2LFOXfNK5ZnBBAAAao78XVB5pveZXmA7XnmDKEkyDJsMz2S5eSYXOmeakpnjl68jKn+HVIhMa/0inpij1+5I0v69hlqf+u3oOasUGBSozNOZsjWzKSk9yR6qAQAAlMQlgVNeoFKe8OjcuXOSpPr1i/o/RY5x4cIFDRkyRAcOHJAkvfjii/ZZU66Ut76UOzgcAADUbmUJoiQp0CtQcclxmvvj3DIFUVLuTjnD47LkcVnuPoU7xU2bh7LO9VNW0mDlbsuzyavRZzI8L2ttd3etLXC1u5qruUzTVIKRoIExAzUsYpi6N+yuQK9AdQvrRgAFAACK5JLAqWnTpoqLi1N8fLz69u1bpns2b94sSYqIiHBKTWlpabr55pv1/fffS5KeeuopPf74405ZqzT/+c9/7J/79+9fJTUAAICqV1QQFdUiSmPajSlXEGWaZrEd1IabVV6h61SvwXbZMsPk5nVGbh6XSqwr71mmTK2MX6mV8Stzj8vQ6MjR6hDy23gAgigAACC5KHC64YYbFBsbq4ULF2rcuHGlXn/hwgXNnTtXhmFo4MCBDq8nKytLI0aM0JYtWyRJjzzyiJ5//vlyPyc6Olr33nuvJOmZZ57RjBkzCpzfu3evfHx87POoijJv3jy98847kqRGjRppxIgR5a4DAADUbmUNoiTJ2/DW5Gcmyz/KX4bbFaHTr2+mkyQ3j0ulBk2lMWUqJjam0HFDhiZePVGRDSLt2wYJoQAAqFtcEjhNnDhR8+fP14YNGxQdHa3x48cXe+25c+c0atQonTp1SvXq1dMf//hHh9dz1113ac2aNZKkgQMH6r777tO+ffuKvd7T01ORkYVfiVyaXbt26f7779eAAQM0dOhQde7cWSEhIbJarfr555/10Ucf2etwd3fXvHnz7LOrAAAASlNUECVJW1pu0UuPvSTfq3x1VZC3xjcIln+WocbJptZ0c9PabobMK8MoBzJlau6PcwsdHx05Wne2vVNHU49KhgihAACoxVwSOHXr1k2PPPKIXnvtNd1333364osvNHLkSPv5b7/9Vnv27NGWLVv08ccfKzU1VYZhaPr06WrRooXD61m+fLn987p163T11VeXeH2LFi105MiRCq2Vk5OjtWvXau3atcVeExISogULFmj48OEVWgMAACC/v//97/rwww+VsCtB3ytVbepnaXrDhnIzDD2wxqbRW6Sfmxq67J17fXxjQ2u7OjeEkqQlsUu0JHZJgWPDI4bbZ0K1CGihlMwURQRFEEQBAFDDuSRwkqRXXnlFmZmZmjNnjpYuXaqlS5fa5wFMnDjRfp1p5s4hePTRRzVt2jRXlecUv/vd77RgwQJt3bpVu3fv1unTp3Xu3DmZpqng4GB16dJFN910k8aPH6/AwMCqLhcAANQSgYGBevfdd3XTTTcpJydHiy+k6Gh2lmY2bKRmnp4Kuiz1jv1t9tOgH02N3ixtaWjVJ1mpis/KkiQZboae+stT8mnmU67B5eWRfyZUHkNGgeHkBFEAANQ8hpmX8LjIV199pRdffFEbNmyQzWYrWIxhqHfv3po2bZqGDh3qyrJqtcTERIWHh0uSEhIS1KxZsyquCAAAuMJHH32kcePGKScnR1Lu3zTeGBCgQf4Bau/trUA3N6XabPopI0NfX7qoNRcvyvrrve7u7nr//fd19913S5KS0pMKzIs6cO6AlsQucUoIVZz8QZTEgHIAABzBWZmBywOnPBcvXtTu3bt15swZ5eTkKCQkRF27dpXFwv9hcDQCJwAA6q61a9dqwoQJSkhIKPM94eHheu+99zRo0KASr7syhNp1epdWH14tm2kr8T5HKu5NeXRFAQBQNrUucILrEDgBAFC3paam6sUXX9T8+fOVlJRU7HUWi0UPPPCA/v73v1d4u39SepLiU+IV5BWko6lHtT5hvVbFr3JpJ1R+dEUBAFAyAidUGIETAACQpMzMTK1du1Y7duzQ/v37lZ6eLh8fH3Xs2FE9e/bU4MGD5eXl5fB18zqhZEgtAlpo8cHFLt+Ol19RXVESYRQAoG4icEKFETgBAIDq5srteIFegYpLjnPacPKyKmmL3tHUo5IhQikAQK1SowOnCRMmlPsewzDk7e2t+vXrq02bNurdu7fat2/vhOpqPwInAABQU1TXIOpKwyOG29+iRwAFAKjJanTg5ObmJsMwKv2cHj166NVXX9V1113ngKrqDgInAABQ010ZRElV86a8ohTXFUUQBQCoCWp04NSyZUsZhqG0tDSdPXvWftzT01PBwcGSpPPnzyszMzO3KMOQxWKRt7e3UlNTdeHCBfs9bm5uWrhwoX7/+987u+xag8AJAADUVkUFUdWlK+rKIIoQCgBQHdXowEmS9uzZo1GjRikxMVGTJ0/W2LFj1blzZ7m5uUmSbDab9u7dq4ULF2r27Nlq2rSplixZomuuuUbHjx/Xxx9/rOeff14XL16Ul5eXYmNj7T8QlIzACQAA1EXVtStqdORo3dn2TmZCAQCqhRodOJ0+fVrdunVTamqqvvrqK/Xp06fE67du3arBgwcrICBAu3fvVuPGjSVJu3fv1vXXX6+MjAxNnTpV//rXv5xdeq1A4AQAAPCbooIoqWrDqOERwzWg+QC1CGihlMwURQRFEEIBAFyiRgdOf/vb3/Tyyy9r2rRpmjlzZpnumT59uv7xj3/o0Ucf1auvvmo//qc//Ulvv/22unbtqu+//95ZJdcqBE4AAABlU9wWvRYBLbT44GKXBVKGDA2LGKbuDbsXqIEwCgDgaDU6cGrbtq1++eUXbdy4scwDv7ds2aK+ffuqTZs2OnjwoP34559/rmHDhikoKEjJycnOKrlWIXACAABwjCsDqaroisofRhFEAQAqy1mZgYdDnlKKxMRESZKXl1eZ78m7Nu/ePE2aNJEkpaWlOag6AAAAoGwsPhZFtYyy/3qkRuqhrg+5dFaUKVMr41dqZfzKAseL6opiPhQAoKq4JHDy8/NTRkaGdu3apR49epTpnp07d0qSfH19CxzPe5Nd3tvtAAAAgKp0ZQglFQ6idp3epVXxq5zaCVVUEMWb8gAAVcUlgVP37t315Zdf6oUXXtCYMWPUoEGDEq8/d+6cXnzxRRmGUSigytteFxoa6rR6AQAAgMrKH0SNjBypKT2maPfp3ZIhl82EMmUqJjam0PH8b8rL68wijAIAOJJLAqdJkybpyy+/VEJCgnr37q3XX39dN910U5HXfvHFF3r00Ud17NgxGYahyZMnFzj/v//9T4ZhqGfPnq4oHQAAAHCIKzuhpveZXqALKtArUHHJcZr741ynz4RaErtES2KXFDpuyNDEqycqskFkocHphFEAgPJwydBwSZo8ebLmzJkjwzAkSRaLRV27drV3Kp09e1Z79uxRUlKSJMk0Tf3xj3/U7Nmz7c84deqUIiIilJGRoZiYGI0aNcoVpdd4DA0HAACoOYp7U56rwqji5A+jZIgACgBqiRr9lro8//73vzVjxgxlZGTkLv5r+JQnrxQvLy8988wz+vvf/17gfFpams6ePStJatq0qTw8XNKgVeMROAEAANQOV4ZRVR1EDY8YrgHNB/CmPACowWpF4CRJp0+f1sKFC7V27Vrt27dP58+flyQ1aNBAHTt21KBBgzRu3Dg1btzYlWXVagROAAAAtVtRXVHOfFNecfLelDeg+QA6oACghqg1gRNcj8AJAACgbsofRLniTXlXyj+cnG14AFA91ejAKSIiQpI0ZcoUPfzww85eDlcgcAIAAID0WwCV96a8vLfU7Tq9S6sPr5bNtDm9htGRozWp6ySCJwCoJmp04OTp6amcnBxt2LBB119/vbOXwxUInAAAAFCapPQkxafEK8gryB5ESXJKGMUAcgCoPpyVGbhk6najRo10/Phx+fj4uGI5AAAAAOVk8bHYQ5/I4Ej78ZGRIzWlxxR7GLX44OJKz4YyZWruj3MLHBseMVzdG3ZXoFcgARQA1AIuCZz+7//+T8uXL9f+/fvVvXt3VywJAAAAwEHyh1HT+0zXQ10fss+GctSb8lbGr9TK+JWScjugRkeOVoeQDpJECAUANZBLttStW7dOgwcPVpcuXbR9+3bVq1fP2UsiH7bUAQAAwNny5kOtT1jvlOHkbMMDAOeo0TOcJOmpp57SCy+8oKioKL3zzjv2bwbOR+AEAAAAV7pyOPnig4sVExvj8HXyb8NrEdBCKZkpigiKIIgCgHKo0YHTzJkzJUnLli3T3r175e7uruuuu05XX321GjRoIHd39xLvf/rpp51dYq1G4AQAAICqlpSepDl75mhp3FKnvg3PkKFhEcOYBwUAZVSjAyc3NzcZhmH/tWmaBX5dmpycHGeUVWcQOAEAAKC6yP82PEcMIC9N/q14eTOnCKEA4Dc1PnCqDJvNeX8DUhcQOAEAAKC6ytt+l5qVKkk6cO6AS0KoKd2naHyn8U5bAwBqCmdlBi55Sx2BEQAAAICiWHwsimoZZf/1SI0s8Ba8Xad3afXh1Q7dhmfK1Cu7XpFhGBrXcZzDngsA+I3Lhoaj6tDhBAAAgJrMWdvw3A13rR29lu11AOq0Gt3hBAAAAAAVZfGx2EOh6X2mF+iAkqRAr0DFJcdp7o9zyxVE5Zg5ik+JJ3ACACcgcAIAAABQo1y5DU+SolpEaUy7MeXaiudheCgiKMLZ5QJAnUTgBAAAAKBWyB9EjYwcqSk9pti34h1NPar1CevtIZSH4aFpvafR3QQATuLSwCkrK0sfffSRPvvsM/3www9KSkpSenp6ifcYhiGr1eqiCgEAAADUFvm34kUGRyqqZZQ9hIoIiiBsAgAnclngFBsbq9tuu00HDx4Uc8oBAAAAVIX8IRQAwHlcEjhdvnxZQ4cO1eHDh+Xm5qZbb71VoaGhmj9/vgzD0LRp05ScnKydO3fqu+++k2EY6tOnj6Kiokp/OAAAAAAAAKoVlwROc+fO1eHDh+Xu7q4vv/xSAwcO1P79+zV//nxJ0rPPPmu/dvfu3frDH/6gbdu26c4779TDDz/sihIBAAAAAADgIG6uWGTlypUyDENjxozRwIEDS7y2W7duWr9+vcLCwjRlyhTt2rXLFSUCAAAAAADAQVwSOB04cECSNGLEiCLP22wFX1UaGhqqKVOmyGq16q233nJ6fQAAAADqjqT0JG0/uV2xybHafnK7ktKTqrokAKh1XLKlLiUlRZLUokUL+zEvLy/758uXLysgIKDAPdddd50kacOGDc4vEAAAAECdsCx2mZ7f9rys5m9vwjZkaFjEMA1oPkDdwroxVBwAHMAlHU6+vr6SJMMw7MeCgoLsn48dO1bsvadOnXJaXQAAAADqjqT0pEJhkySZMrUyfqWmfDNFA2IGaObWmXQ9AUAluSRwatWqlSTpxIkT9mMWi0XBwcGSpC1bthS6J292k6enpwsqBAAAAFDbxafEFwqbirIkdokGxgzUc1uf07LYZfrq6FcEUABQTi4JnHr06CFJ2rlzZ4HjgwYNkmmaeumll5ScnGw/Hh8frxdffFGGYahr166uKBEAAABALRcRFCEPo2xTRUyZiomN0YytMwp0PjH3CQDKxiWBU1RUlEzT1IoVKwoc//Of/ywpN2CKjIzU6NGj9bvf/U5du3a1d0M9+OCDrigRAAAAQC1n8bFoWu9pZQ6drrQkdolGrhyp+9bcp4ExA/XkpifpfgKAYhimaZrOXiQtLU2/+93vlJOTo+joaLVu3dp+bsaMGZo5c2ZuMb/OeMoracKECXrnnXecXV6tl5iYqPDwcElSQkKCmjVrVsUVAQAAAFUnKT1J8Snx2nlqp+b+OFemKv9HotGRozWp6yQGjgOocZyVGbgkcCrN119/rXfeeUf79++X1WpVmzZtNHbsWI0cObKqS6sVCJwAAACAoiWlJ2n36d1an7Beq+JXVSp8MmRodORodQjpIEkK9ArkrXcAqr1aHTjBuQicAAAAgNLlhU/bTm7TktglDul8MmRo4tUTFdkgUjJEAAWg2iFwQoUROAEAAADl48jOp/zcDDc93ftpjYxkNweA6oHACRVG4AQAAABUXF74JEOKS46r9NwnQ4aWDl+qyOBIB1YJABVT6wKn1NRUXbx4UTk5OaVe27x5cxdUVHsROAEAAACO46jup790/4vGdxrv2OIAoJxqReD01Vdfafbs2dq8ebOSk5PLdI9hGLJarU6urHYjcAIAAACco7Jzn8Z1GKd+zfopIiiC2U4AqkSND5z+/Oc/6+2335YklWdJwzDK1AWF4hE4AQAAAM6XFz6lZqVq1+ldWn14tWymrUz3uslNj3V/jI4nAC7nrMzAwyFPKcXHH3+st956S5Lk7e2t2267Td27d1dwcLDc3NxcUQIAAAAAOJXFx6KollGSpJGRIzWlxxTFp8TLNE098NUDJXY/2WTTK7teUVxKnB7r/hjdTgBqPJcETv/5z38kSeHh4Vq3bp1at27timUBAAAAoMpYfCz24OiZPs/o2a3PlrrlbsWhFVp5aKWmdJ9CtxOAGs0l7UU//vijDMPQM888Q9gEAAAAoM4ZGTlS68as0/CI4aVea8rUK7te0ZObntRXR79SUnqSCyoEAMdySYdTdna2JKlbt26uWA4AAAAAqh2Lj0X/7PtPtQ1uq1m7ZinHLHlW7cr4lVoZv1KSNDpytCZ1ncRWOwA1hks6nFq2bClJunTpkiuWAwAAAIBqa1zHcVo7eq0W3LhA49qPK9M9S2KXaEDMAM3cOlOxybHafnI7nU8AqjWXBE633367JOnrr792xXIAAAAAUK1ZfCzq1biXpvaaqqk9ppb5viWxSzRy5Ujdt+Y+DYwZqJlbZxI8AaiWDNM0S55a5wAXLlxQ165ddf78eW3btk3t2rVz9pLIx1mvOAQAAADgGEnpSZqzZ46WxC4pdbB4UdhyB6CinJUZuKTDqX79+vryyy/VsGFDXXvttZo9e7bOnz/viqUBAAAAoNqz+Fg0vc90rRuzTuM6lG2bXX5LYpdoYMxAvb37bbbbAagWHNrhFBERUeL5tLQ0nTlzRoZhyDAMWSwW+fr6llygYejQoUOOKrFOosMJAAAAqFnyOp5iYmMqdL8hQ6MiR9H1BKBUzsoMHBo4ubk5vmHKMAzl5JT89gaUjMAJAAAAqJkqu9XOkKEp3adofKfxji8OQK3grMzAwyFP+dW4ceVv/QQAAAAAFC1vq91DXR/S7tO7JUOKS47TnB/nlOl+U6Ze2fWK0qxpmtR1kpOrBYDfuGRoOKoWHU4AAABA7VKRLXfDI4ZrQPMB6hbWjW12AOxq9NBwAAAAAIDj5HU+rR+zXmMix8jNKP2PdivjV2rKN1M0MGagovdFO79IAHUaHU51AB1OAAAAQO2WlJ6k+JR47Ty1s8zb7W5pfYse6/4Y3U5AHVfjO5yOHTumY8eOKTMzs9RrMzIy7NcDAAAAAEpm8bGoV+NemtRtktaPWa/hEcNLvWfFoRV0OwFwGpcETmvWrFGrVq3UuXNnpaWllXp9WlqaOnbsqIiICH3zzTfOLxAAAAAAagmLj0X/7PtPTe0xVW6l/JEvb6j4k5ue1FdHv1JSepKLqgRQ27kkcFqyZIlM09Rtt92mBg0alHp9cHCwRo4cKZvNpsWLF7ugQgAAAACoXcZ1HKevx3ytcR1Kf5t43nynATEDNHPrTIInAJXmksBp69atMgxDN954Y5nvGTJkiP1eAAAAAED5WXwsmtpzapm32UnSktglbLUDUGkuCZyOHDkiSYqMjCzzPVdddZUk6fDhw84oCQAAAADqjPzb7Moib6vdc1ufo9sJQIW4JHCyWq2SJHd39zLfk3dtRkaGU2oCAAAAgLpmXMdxWj9mvcZEjpEho9TrY2JjNChmEN1OAMrNJYGTxZL7ms34+Pgy35N3bXBwsFNqAgAAAIC6yOJj0fQ+07VuzLoyzXeyyaZXdr2i2Xtmu6A6ALWFSwKnrl27SlK5BoAvWrRIktSpUydnlAQAAAAAdVr++U5jIseUev2cH+boqc1PscUOQJm4JHC69dZbZZqmli9friVLlpR6fUxMjJYvXy7DMHTbbbc5v0AAAAAAqKPyOp7KstVuxaEVDBQHUCaGaZqmsxfJyspSu3btdOTIEbm7u+uRRx7RI488ovDw8ALXJSQkaNasWXrzzTdls9kUHh6ugwcPysvLy9kl1mqJiYn2n3VCQoKaNWtWxRUBAAAAqK6S0pM0Z88cxcTGlHjd8IjhGtB8gLqFdZPFx+Ki6gA4mrMyA5cETpK0Z88e9evXT5cuXZJh5CbmzZs3V+PGjSVJJ0+e1LFjxyRJpmnK399fGzZsULdu3VxRXq1G4AQAAACgvGbvma05P8wp9To3w01P935aIyNHuqAqAI7mrMzAJVvqpNw5Tt999526desm0zRlmqaOHj2q7777Tt99952OHj1qP969e3dt376dsAkAAAAAqsikrpP0UJeHSr3OZtr03LbnmO0EoAAPVy7Wvn177dq1S1999ZVWrVql3bt3Kykp9zcli8Wia665RsOHD9egQYNcWRYAAAAAoAiTuk6SXz0/vbzz5RKvyzFzFJ8Sz9Y6AHYuDZzyREVFKSoqqiqWBgAAAACUw7iO43RzxM2as2eOlsQukamip7L8lPyTejXu5eLqAFRXLttSBwAAAAComfLeZLduzDqN6zCuyGtm7ZzFtjoAdtUqcDp06JC+++47nT59uqpLAQAAAABcweJj0dSeU/XqDa8WOpejHM3ZU/qQcQB1g0sCpzNnzmj27NmaPXu2Lly4UOj8L7/8ou7duysyMlLXXnutmjZtqpEjR+r8+fOuKA8AAAAAUA7dwrrJXe6FjsfExui5rQwQB+CiwGn58uV6+OGH9frrr6t+/foFzmVmZmro0KHas2eP/S11NptNn332mW699VZXlAcAAAAAKAeLj0X3dLinyHMxsTEavGSwlsUuc3FVAKoTlwROa9askWEYGjFiRKFz0dHROnTokCTplltu0euvv67hw4fLNE1t2bJFixcvdkWJAAAAAIByGN9pvNyK+SNljplDpxNQx7kkcDp48KAkqXfv3oXOffzxx5KkgQMH6rPPPtOf/vQn/fe//9XgwYNlmqYWLVrklJp27typmTNn6sYbb1SzZs3k5eUlf39/RUZG6t5779XmzZsdvuYnn3yiG2+8UY0aNZK3t7datGihe+65R1u3bnX4WgAAAADgTBYfix7r/lix55npBNRthmmaRb/T0oHCwsJ07tw5fffdd+rRo4f9eHp6uoKCgmS1WrVo0SKNHj3afm7RokW6++67FR4erqNHjzq0nn79+mnTpk2lXjd27FjNnz9fnp6elVovPT1do0aN0ueff17keTc3Nz399NN65plnKrVOcRITExUeHi5JSkhIULNmzZyyDgAAAIC6Z+H+hXp156uyyVbk+Ye6PKRJXSe5uCoAZeWszMAlHU4pKSm5i7kVXG7btm3Kzs6WYRgaPHhwgXOtWrWSlDtw3NFOnDghSWrSpIkeeeQRLV26VNu3b9fWrVv16quvqmnTppKk999/X+PHj6/0ehMmTLCHTQMGDNBnn32m7du3a8GCBWrdurVsNptmzJihefPmVXotAAAAAHClcR3H6esxX+vGFjcWeX7OD3O0cP9CF1cFoKq5JHDy9/eXJJ06darA8W+++UaS1KFDBzVo0KDAuXr16kmSPDw8HF5Pu3bttHjxYh07dkyvvfaaRo4cqZ49e6p379567LHHtGfPHkVGRkrK3Qa3cePGCq+1bt06+7bA4cOH66uvvtKtt96qnj17asKECdq2bZuaN28uSXr88cd5Mx8AAACAGsfiY9ET//dEsTOdXtn5imKTY11cFYCq5JLAqV27dpKk//3vfwWOL1u2TIZhqH///oXuyQunGjZs6PB6Vq1apTFjxsjdvfBrPCXJYrHolVdesf966dKlFV7r5ZdflpQbnM2ePbvQmhaLRf/6178k5XaCvfPOOxVeCwAAAACqSkkznUyZGrVyFG+uA+oQlwRON998s0zT1Lx58zRnzhzt27dPU6dO1YEDByRJt99+e6F7vv/+e0myb29ztQEDBtg/571Fr7wuXryor7/+WpI0ePDgYvdB3n777QoMDJQkffrppxVaCwAAAACq2vhO4/VQl4eKPGfK1MytM+l0AuoIlwRODz/8sBo3bqysrCw9/PDD6tKli2bNmiVJ6tOnT4FwJ8/KlStlGIZ69uzpihILyczMtH8urhOqNDt27FBWVpYkFdnFlcfT09P+Br8dO3YoOzu7QusBAAAAQFWb1HWSxkSOKfKcTTaNWTWGTiegDnBJ4FS/fn2tXbtW11xzjUzTtH/17dtXMTExha7/4YcftGPHDklSVFSUK0osZMOGDfbP7du3r9Az8jq4pN+2FRYn77zValVcXFyF1gMAAACA6uChrg8VO88px8zR89ueV1J6kourAuBKjp/IXYz27dtr586dOnz4sE6dOqXGjRurZcuWxV7/3nvvSZIGDhzoogp/Y7PZ9OKLL9p/PWZM0el8aRITE+2fS3utYN4rCKXc1xB26NChQusU5eTJk2V+FgAAAABUlsXHoqf7PK2ZW2fKJluh81bTqviUeFl8LFVQHQBXcFnglKdVq1Zq1apVidd06dJFXbp0cVFFhc2aNUvbt2+XlDtfqXv37hV6zsWLF+2f897UVxw/Pz/750uXLpVrnfxhFQAAAABUByMjR6p/eH9tSNigmdtmymYWDJ5+Sv5JvRr3qqLqADibS7bU1SQbNmzQ3//+d0lSWFiY5syZU+FnZWRk2D97enqWeK2Xl5f9c3p6eoXXBAAAAIDqwuJj0cjIkXrsmsJvr5u1cxbb6oBazOUdTtXZ/v37NWLECFmtVnl7e2vJkiUKCwur8PO8vb3tn/OGhxcn/5ByHx+fcq2TkJBQ4vmTJ0+qVy/+5gAAAABA1egQUnhkSI5yFL0vWlN7Tq2CigA4m0MDp5kzZ9o/P/3000Uer4j8z3KWw4cP68Ybb9T58+fl7u6uRYsWqV+/fpV6ZkBAgP1zadvkLl++bP9c2va7K5U2HwoAAAAAqlJEUITc5a4c5RQ4/uFPH2p8p/HMcgJqIYcGTjNmzJBhGJIKhkT5j1eEswOnEydOaPDgwTpx4oQMw9C7776rW2+9tdLPzR8EJSYmqkePHsVem79LiZlMAAAAAGoTi49F93S4RwsPLCxwPMfMYXg4UEs5fIaTaZoyTbPY4xX5cqakpCRFRUUpPj5ekvTmm29q7NixDnl2/jfN/fzzzyVem3few8NDbdq0ccj6AAAAAFBdjO80Xu6Ge6HjPyX/VAXVAHA2hwZONpvN/lXc8Yp8OcuFCxc0ZMgQHThwQJL04osvavLkyQ57fs+ePe3Dwjds2FDsdVlZWdq2bZv9nnr16jmsBgAAAACoDiw+Fj16zaOFjjM8HKid6uxb6tLS0nTzzTfr+++/lyQ99dRTevzxxx26RkBAgAYNGiRJWrt2rRITE4u8bvny5UpNTZUkjRgxwqE1AAAAAEB1Udzw8Be+e4HQCahl6mTglJWVpREjRmjLli2SpEceeUTPP/98uZ8THf3/7d17WNRl/v/x1yAiiBripGXgsUbzkJrayuYRD2VmZiabbQWlHdTa1rLT1Ve0vMospd3aldpNw7I00DTNDnhAM8U8m2aK5gnzkGimiakM9+8Pf/NZEGYAnYEBno/r4rpGPvfnnjfzdhRe3J/7kySbzSabzaZx48YVOmb06At3XMjJydHIkSPldObfJC8rK8sKusLCwjRs2LAS1wEAAAAA5YFr8/CLpe5LVa+UXpqTMacMqgLgC17dNLy8GDJkiFJTUyVJ0dHRGjp0qLZu3ep2fFBQkBwOxyU9V3R0tO655x7NmjVL8+fPV+/evfX3v/9d9evX15YtW/TKK69o//79kqSJEyeqdu3al/Q8AAAAAODv3G0eLl3YQHx8+nh1i+zGJuJABVAqgZPT6dTatWu1YsUKZWRk6Ndff9WpU6dUq1YthYeHq1mzZurcubM6dOiggADfL7r69NNPrcdLly7VDTfc4HF8w4YNtXfv3kt+vmnTpunkyZP64osvlJaWprS0tHzHAwICNGbMGD3yyCOX/BwAAAAAUB7EtYrTjB9nyGmcBY455VTS1iSN7ji6DCoD4E0+DZxycnL073//W5MmTdLBgweLHB8ZGalnnnlGjz32mKpUKbjMsrwKCQnRwoUL9fHHHyspKUmbN2/WiRMnVK9ePXXp0kWPP/64oqKiyrpMAAAAAPA5e4hdYzqN0fj08XKqYOj04bYPFdcqjlVOQDlnM8YYX0x87NixfPskFedpbDabJKl79+5KSUlReHi4L0qrdA4cOKDIyEhJUmZmpiIiIsq4IgAAAACVXdaZLE34boJS96UWOBbbIpZVTkAp8VVm4JPAyel06uabb9batWtljJHNZlPv3r3Vq1cv3XjjjapTp45q1KihU6dOKSsrSxs3btSiRYu0ZMkSa3xUVJS++eabUrnErqIjcAIAAADgj7LOZKlnck/lKjff5wMUoCUxS1jlBJQCX2UGPklzXnvtNa1Zs0aS1K5dO23ZskVfffWVRo8erejoaLVp00ZNmzZV27Zt1atXLz3zzDNKTU3V5s2b1bZtWxljlJ6erjfeeMMX5QEAAAAA/IA9xK77W9xf4PO5ylXipsQyqAiAt3g9cDp//rzeeust2Ww2tWvXTitXrlSLFi2KdW6rVq20atUqtWvXTsYYvfnmm8rJyfF2iQAAAAAAPxHXKk4BhfxompyRrOk/FLybHYDyweuB04IFC3T06FHZbDbNmDFDwcHBJTo/ODhYH374oWw2m44eParPP//c2yUCAAAAAPyEu1VOkpSwLkFZZ7JKuSIA3uD1wOnbb7+VJPXq1UvNmze/pDlatGih3r17S5JWrFjhtdoAAAAAAP7H3SqnXOUqaWtS6RcE4LJ5PXBav369bDabevbseVnz9OzZU8YYrV+/3kuVAQAAAAD8kT3ErlHtRxV67MNtHyrjeEYpVwTgcnk9cMrMzJQk3XDDDZc1j+v8ffv2XXZNAAAAAAD/FtcqTjGOmAKfz1WuBi8YzEonoJzxeuD022+/SZJq1659WfO4znfNBwAAAACo2Ia3Ha4qtioFPp+rXE1eP1lTNk0pg6oAXAqvB04nT56UJNWoUeOy5gkNDZUknTp16rJrAgAAAAD4P3uIXWM6jSl0PydJStycyJ3rgHLC64GT0+n06ny5ublenQ8AAAAA4L8GOQYppX+K29DpzfVvcuc6oBzweuAEAAAAAMDlcIQ73G4i7jRO7T6xu5QrAlBSgb6aeMqUKapbt+4ln//LL794sRoAAAAAQHkS1ypO2TnZStycmO/zVVRFTcKalFFVAIrLZ4FTYmJi0YMAAAAAAHBjRNsRCq0aqsnrJsvISJKMzWh55nINcgwq4+oAeOKTS+qMMV75AAAAAABUbv2a9FOA7X8/uuaaXI1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+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# testing on data\n",
+    "tested_cell = [test_cells[3]]\n",
+    "# X_train_tested_cell = [x for xs in train_cells for x in xs[0]]\n",
+    "# Y_train = np.array([x for xs in train_cells for x in xs[1]])\n",
+    "# Y_train_tested_cell = [x for xs in train_cells for x in xs[1]]\n",
+    "X_tested_cell = [x for cycle in tested_cell for x in cycle[0]]\n",
+    "# Y_test = [x for xs in test_cells for x in xs[1]]\n",
+    "Y_tested_cell = [y for cycle in tested_cell for y in cycle[1]]\n",
+    "dc_tested_cell, slopes_tested_cell = make_label_arrays(Y_tested_cell)\n",
+    "X_tested_cell_time_series, X_tested_cell_dt = make_feature_arrays(X_tested_cell)\n",
+    "\n",
+    "scaled_X_tested_cell_dt = standardize_non_train(X_tested_cell_dt, mean_X_train_dt, std_X_train_dt)\n",
+    "scaled_X_tested_cell_time_series = standardize_non_train(X_tested_cell_time_series, mean_X_train_time_series, std_X_train_time_series)[...,1:]\n",
+    "\n",
+    "# std_X_tested_cell_time_series = standardize(X_tested_cell_time_series[...,1:])\n",
+    "all_test_slopes = [y[0] for y in Y_tested_cell]\n",
+    "all_test_dc = np.array([y[1] for y in Y_tested_cell])\n",
+    "Y_hat_tested_cell = model.predict([scaled_X_tested_cell_time_series, scaled_X_tested_cell_dt])\n",
+    "\n",
+    "# initial_dc = all_test_dc.reshape([-1, 2])[cycle_indices[0]]\n",
+    "# index_0 = initial_dc[0]\n",
+    "# for i,m in enumerate(all_test_dc.reshape([-1,2])):\n",
+    "#     plt.scatter(*list(zip(*all_test_dc.reshape([-1,2]))), color = 'C2', s=2, label='Ground-truth' if i == 0 else \"\")\n",
+    "\n",
+    "window_size = 100\n",
+    "scatters = []\n",
+    "for i,m in enumerate(all_test_dc[1:]):\n",
+    "    plt.figure(dpi=200, facecolor='white')\n",
+    "#     print(m[0,0], m[5,0], m[9,0])\n",
+    "    plt.scatter(*list(zip(*all_test_dc.reshape([-1,2]))), color = 'C2', s=1, label='Ground-truth') #if i == 0 else \"\")\n",
+    "#     if i == 0:\n",
+    "#         initial_dc = m[0]\n",
+    "    initial_dc = m[0]\n",
+    "#     print(m)\n",
+    "#     print(m)\n",
+    "#     break\n",
+    "    predicted_dc_values = [initial_dc]\n",
+    "#     print(initial_dc)\n",
+    "#     if i%2 == 0:\n",
+    "    new_cycle_index = m[0,0]\n",
+    "#         print(f'hi {i}')\n",
+    "    for j,slope in enumerate(Y_hat_tested_cell[i]):\n",
+    "        new_cycle_index += window_size//2\n",
+    "        new_predicted_dc = linear_fit(new_cycle_index, -np.exp(-slope), initial_dc)\n",
+    "        print(f'slope: {-np.exp(-slope)}')\n",
+    "        predicted_dc_values.append(np.array([new_cycle_index , new_predicted_dc]))\n",
+    "        initial_dc = predicted_dc_values[-1]\n",
+    "#         print(initial_dc)\n",
+    "      # \n",
+    "    print(predicted_dc_values)\n",
+    "#     initial_dc = np.array([new_cycle_index, new_predicted_dc]) \n",
+    "    \n",
+    "#     print(i)\n",
+    "#     print(predicted_dc_values)\n",
+    "#     initial_dc = predicted_dc_values[-1]\n",
+    "    \n",
+    "#     if i==2 or i==1:\n",
+    "#         print(m)\n",
+    "#         break\n",
+    "#     if i ==2:\n",
+    "#         break\n",
+    "    scatters.append(predicted_dc_values)\n",
+    "#     print(np.array(scatters).T)\n",
+    "    plt.plot(*np.array(scatters).T, color='C0', label='Inferred', #if i == 0 else \"\",\n",
+    "             marker='o', markersize=1)\n",
+    "    plt.scatter(*np.array(predicted_dc_values[-1]).T, c='C3', #if i == 0 else \"\",\n",
+    "         marker='o', s=50, edgecolor='k', linewidth=1, facecolor='C3', zorder=-1)\n",
+    "    plt.xlabel('Cycles')\n",
+    "    plt.ylabel('Discharge Capacity')\n",
+    "    plt.ylim([1,4])\n",
+    "    ax = plt.gca()\n",
+    "    hand, labl = ax.get_legend_handles_labels()\n",
+    "    plt.legend(np.unique(labl))\n",
+    "    plt.tight_layout()\n",
+    "#     plt.savefig(f'img/discharge_curve_100_window_{i:04d}.png', dpi=200, transparent=False)\n",
+    "#     if i ==20:\n",
+    "        \n",
+    "#         break\n",
+    "#     plt.close()\n",
+    "#     break\n",
+    "#     break\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1082,
+   "id": "a0944576",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[6.165, 6.38 ],\n",
+       "       [6.421, 6.589],\n",
+       "       [6.41 , 6.581],\n",
+       "       [6.404, 6.577],\n",
+       "       [6.403, 6.576],\n",
+       "       [6.382, 6.56 ],\n",
+       "       [6.355, 6.542],\n",
+       "       [6.27 , 6.478],\n",
+       "       [5.947, 6.178],\n",
+       "       [4.587, 5.011]], dtype=float32)"
+      ]
+     },
+     "execution_count": 1082,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "Y_hat_tested_cell"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1084,
+   "id": "f437f2da",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[5.841, 6.057],\n",
+       "       [6.073, 6.256],\n",
+       "       [6.059, 6.249],\n",
+       "       [6.047, 6.242],\n",
+       "       [6.035, 6.235],\n",
+       "       [6.08 , 6.275],\n",
+       "       [5.563, 5.8  ],\n",
+       "       [4.677, 5.05 ]], dtype=float32)"
+      ]
+     },
+     "execution_count": 1084,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "Y_hat_tested_cell"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1083,
+   "id": "e0e81855",
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1/1 [==============================] - 0s 266ms/step\n",
+      "slope: -0.0029065932612866163\n",
+      "slope: -0.00234186090528965\n",
+      "[array([100.   ,   3.779]), array([150.   ,   3.634]), array([200.   ,   3.517])]\n",
+      "slope: -0.0023047919385135174\n",
+      "slope: -0.0019195347558706999\n",
+      "[array([200.   ,   3.657]), array([250.   ,   3.542]), array([300.   ,   3.446])]\n",
+      "slope: -0.002336573787033558\n",
+      "slope: -0.0019320618594065309\n",
+      "[array([300.   ,   3.527]), array([350.  ,   3.41]), array([400.   ,   3.313])]\n",
+      "slope: -0.002366095781326294\n",
+      "slope: -0.0019467717502266169\n",
+      "[array([400.   ,   3.382]), array([450.   ,   3.264]), array([500.   ,   3.166])]\n",
+      "slope: -0.002393354196101427\n",
+      "slope: -0.001959422370418906\n",
+      "[array([500.  ,   3.24]), array([550.   ,   3.121]), array([600.   ,   3.023])]\n",
+      "slope: -0.0022870381362736225\n",
+      "slope: -0.0018822874408215284\n",
+      "[array([600.   ,   3.107]), array([650.   ,   2.992]), array([700.   ,   2.898])]\n",
+      "slope: -0.0038386816158890724\n",
+      "slope: -0.003027202095836401\n",
+      "[array([700.   ,   2.908]), array([750.   ,   2.716]), array([800.   ,   2.564])]\n",
+      "slope: -0.009303156286478043\n",
+      "slope: -0.00640686322003603\n",
+      "[array([800.   ,   2.494]), array([850.   ,   2.029]), array([900.   ,   1.709])]\n"
+     ]
+    },
+    {
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+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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AAADAfgicUGkETsD1i72YruV747V0d5yOJqaVO97TzaSh7RtqZJfGujWsvtxcKt/LrqqdSS742r/fE6fohPK/9sq+6a489IMCAAAAbM+pA6dLly7p3//+tyTpscceU6NGjcocf/bsWX322WeSpD/84Q/y8bGioS1KReAE2I7ZbNbBs6laFhWn7/fEK/FyVrnP1PNx14gbG2lk1ybqGhJQ6bd2VgeHz6VqWVS8IvfGKy4lo/wHjGy5+h2Um//eCr3pzhpFd0IRQgEAAACV49SB08cff6wnn3xSrVu31pEjR8odbzab1bZtWx07dkyzZs3So48+au8SazQCJ8A+8vLN2hZzQUuj4vSf/eeUllX2W+4kqXmgt+7u0kQjuzRWaH1fB1RpH/n5Zu06fVHLouK0ct9ZpaTnlP+QyxW5+e2Ta529FXrTXUWMCRujcW3G6VTqKaVmp0oijAIAAADK4tSBU3h4uFatWqW//OUveu2116x65uWXX9Zrr72mu+66S8uWLbNvgTUcgRNgfxnZeVp7KEHLouK0Kfq8cvPL/9HaOSRAo7o01ojOjRXk6+GAKu0jOzdfW46d17KoeK05mKCMnPJ3MdXzlVo1vaQDWREyKvimu8piRxQAAABwLacOnEJCQhQfH68VK1Zo+PDhVj3zn//8R3fccYeaNWumkydP2rfAGo7ACXCs5CvZWvlbvJZGxWn36ZRyx7uYDN3auqDZ+ND2DeTt7rzNxq9k5VqCt5+OJinPiuCtUV1DwcEndTx3gQz38puz2xIhFAAAAGo7pw6cPDw8lJubq127dqlLly5WPbNnzx7ddNNN8vDwUEaGFX1CUCoCJ6DqnLpwRcui4rVsT5xOJJX/5jZvdxfd3qGhRnZtoltuCJSrEzcbr8yb7m5oYOjGltnq0jJPvl7SroRdWhGzQmY57v0WhFAAAACoTZw6cKpTp47S0tK0efNm3XLLLVY988svv6hv377y9vZWWpo1b0VCaQicgKpnNpv1W+wlLY2KU+TeeF24Uv6b2+r7eSj8xsYa1bWJOjbxd+pm4xV9052LyVC/1kG6u0tj3dTSTdEpvyk1O7VKAihDhh6/8XGF1Q2jLxQAAABqHKcOnNq2baujR4/qvffe09NPP23VM++//76eeeYZhYaG6tixY3ausGYjcAKql5y8fG05lqRlUXFafcC6nkc31PfRqK5NdHeXJgqp5+2AKu2nom+683QzaWj7hrq7c2PdGlZfqTnJikqIsoQ/VRFCFSrcDUUABQAAAGfl1IHTY489ptmzZyssLEz79u2Tm5tbmeNzcnLUqVMnHT16VA899JAiIiJsWk9qaqpWrVqlHTt2aOfOnYqLi9P58+eVkZGhgIAAtW/fXnfccYceffRRBQYGVnqdiIgIPfLII1aNnTt3riZMmFDptcpC4ARUX1eycrX64DktjYrXlqPnZUXLI/VoUVd3d2miOzs1Ul0fd/sXaSeVedNdgLeb7ujUSP1bB8nXw02tG/oq2M9TSRlJikqIkgypuV9zy1vqHB1GEUABAADA2Th14FR4PM4wDN1zzz364osv5O1d8n+hT09P18MPP6wlS5bIMAytX79e/fv3t2k9a9eu1dChQ8sdFxQUpK+//lrDhg2r1DoETgAqIvFypiL3ntWyqDjti7tU7ng3F0MD2gRrVNcmGtQ2WJ5uLg6o0j4q86Y7STIMacItLfT87W1L/foLw6iq2BFFPygAAABUd04dOEnSAw88oPnz58swDDVt2lSPPfaY+vXrp0aNGkmSzp49q59++kmff/65YmNjJUn33nuvFixYYPNa1q5dq4kTJ2rgwIHq1q2bQkJC1KhRI+Xn5ys2NlbfffedlixZory8PLm7u2v79u3q3LlzhdcpGjj9+OOPaty4caljmzZtqoCAgMp+SWUicAKcz7HENH2/J05Lo+IUe7H8Y2d+Hq4a3qmg2XivloEymZy331Nl3nTn6WpS39b1NbhdsAa2CVbDOp5ljq8OIZS/h7+a+zVXSlaKWtZpqfre9e2+NgAAAHA1pw+cMjMzddddd2nt2rVlNr4tLGfo0KH6/vvv5elZ9l8aKiMvL08uLmXvBFi2bJlGjRolSRo1apSWLFlS4XWKBk4nTpxQixYtKjyHLRA4Ac7LbDZr16mLWlqBY2eN6njqri4FzcbbNvR3QJX2U5k33UlS+0b+GtQ2WIPaBatz0wC5WBHAlRRCrTyxUvnm/ErXb62M0xPUyD9QnZsEqGtongJ82REFAAAAx3D6wEkq+IvTBx98oLffftuyi+lqISEh+uMf/6ipU6dW+RuZ2rZtqyNHjigoKEjnz5+v8PMETgBsKTs3X5uiz2tZVJzWHEpQdm75QUjbhn4a1bWJ+rQKVGpmrloFF/Q8ckZnktP1zfbTmrnxeIWeq+fjrgFh9TWwbbBuDauvOl5l9xEsKikjSTEpMQrwCLBbX6j87Lq6cvz5Ip+Y5eJ9VB4N/iOTR7zGthmjKV2mEDwBAADALmpE4FTIbDZrz549ioqKUlJSkqSCfkk33XSTOnfuXOVBU6EePXpo586d8vX11eXLlyv8PIETAHtJzczRf/ad07I9cdoac0HW/iQ3GdL0Ee31SJ+W9i3QjuZvP60Xl+236qjd1VxMhro3r1uw+6ltsFoF+1bq3zlFd0NdbwCVmXibci4MKvGeyT1BrnWi5Oa/V3e37UtDcgAAANhcjQqcnMGRI0fUsWNH5ebmqnv37tqxY0eF5yBwAuAIZy9laPmeeC2NitPhc+WH4y6Goa1/GeS0O52kggbrxxLT1CrYV64mkzZFJ2r94fPadCRRqZm5Vs8TUs9Lg9oEa2DbYPUKDax04/XrCaDSjv1J5px65Y5z8Trx3/BpnwyXDN6IBwAAAJsgcHKA9PR0xcXFKTIyUv/85z+VkJAgSfr666/1u9/9rsLzFQ2cBgwYoCNHjigpKUn+/v5q1aqVhgwZoieeeEJNmjSx6ddxNQInoPY4dDZVy/bEafmeeJ29lFnquG8eu1m33FDzAorcvHztOnVR648kasPhREUnpFn9rJebi/q0CrLsfiqv8XhZKtKUPDejoTJOPi3JZOXsuXL1PSLXOlFy9T0sw1QQsIWHhmtgs4GWRuShAaGEUAAAACgXgZOdFA2FSvLnP/9Zr7/+eqWOXJQ3tyR5enrqX//6lx5//PEKz1+otH5Yhc6ePauePXtKInACaov8fLN+PZGsb7ef1vK98cXuuZoM/fKCc+9wstaZ5HRtOJKo9YcT9cvxC1b1vSrUrpG/Brct2P3UJcS6xuNluTqE8vfw19Hko/rkt0+UdbG7ss6NlOQiKV9yyZDyfMqf1JQpN799cq2zRy7eMTKM//0r3ZChEaEj2AUFAACAMtWYwKmwf9PevXuVlJSkjIwMlVfCX//6V7vVU1oo1KVLF82aNUs9evS4rrlfe+013XPPPerdu7flH2BMTIwWL16s7777zvK1f/rpp5o8eXKl1qlIGEbgBNQ+X209qZeXH1C+uaCH0d9HdtS4ns2quiyHS8/O1S/HLlh2P5W1A+xq9Xzc1T+svgZVovF4eQqDqNiUVCVeMim4Tr6iU3dp2YHflHupq3JSb5Tyvcudx3C9JFf/PXKrs0cmj7Mq6V8NhcfwJN6CBwAAgAI1InD64osv9Morr+jUqVMVei4vL89OFUkpKSmWHUIZGRk6fvy4Fi5cqKVLl+qGG27Qv/71L40YMaJSc1+6dEn+/v6lBkIrVqzQPffco5ycHHl7e+v48eNq2LBhhdchcAJQnqI9j2rDzqbymM1mHTp72bL7Ker0RVnbg9zFZKhb87oafJ2Nx8uTlJGkmXtmauGRJcpNa62cS12Vm9ZOMpcfdpk8zsnVP6ogfHK7VObYwqN4hE8AAAC1k9MHTi+++KLeeOONcnczSQUBStFx+fnWH4Gwla+++krjx4+XYRiaPXu2JkyYYJd1/va3v2n69OmW6xdffLHCc3CkDgCuT/KV7Eo3Hm9a18vS9+l6Go+XpuhRvK2xe7RiX6xyLnVRXnqorOn75OIdUxA++e+X4ZJR5lh2QAEAANQ+Th04/frrr+rdu7cMw9CQIUP01ltvKT8/XzfddJMMw1Bubq6Sk5O1c+dOzZw5U8uXL1ffvn21aNEiNWjQwN7lleq+++7TwoUL5ePjo9OnT6tevfLfIlRRiYmJatiwocxms4YOHarVq1fbfA2ahgOA9XLz8rX7dIrWHU6oZOPxQA38bwDVqI6XzesrDKDOXExV5N6z2nvCQ/lZjct/0MiVq+9hufpHydX3iKXZeHmKNiM/lXpKMkQQBQAAUIM4deA0YcIEffnll2rRooWio6Pl6uqqAwcOqFOnTjIM45ojczNnztTUqVPVuXNn/frrr3J3d7d3iSX65ptvLG+nmzdvnh544AG7rFO/fn0lJSWpffv2OnDggM3nJ3ACgMq73sbjg9oW9H7qElL3uhuPlyQpI0krDu3ST4cztSfGVcnW5GOmDLn575Orf5RcvE8WazZurcLdUOyEAgAAcG72ygxcbTJLOX755RcZhqGnn35arq7lL/nEE09o/fr1WrJkiT7++GM988wz9i+yBPXr17dcV7TvVEXYo/cHAMA2Qup56+HeLfRw7xbKyM7TL8eTtO6wdY3HD51N1aGzqfpow3HV9XbTgDYFb73r37q+6njbpvF4kFeQJtw0TBNuKng74Y6TyZq/M0Y/7k9UenYpD+V7KSelp3JSespwTZFbnT0F4ZNngtXrRsZEKjIm0vJ7juMBAACgKIcETmfPnpUkdejQwfKZyfS/vhM5OTlycyv+B++HHnpIixcv1oIFC6oscIqLi7Nc+/r62mWN8+fPKykpSZLUuLEVRyIAAFXGy91Fg9s10OB2DWQ2m3X43GWtP2xd4/GL6TlaGhWnpVFxlsbjhb2fWtuo8bjJZOjm0EDdHBqorHvytOHweX2/J05rDyUoJ6/k4sy5Acq+MEDZFwbI5HFWbnWi5Oq/Rya31AqtfXUAJRFCAQAA1GYOCZxycnIkScHBwZbPigY458+fvyZsKdzCdezYMQdUWLJFixZZrjt16mSXNWbNmmVpkN6/f3+7rAEAsD3DMNSukb/aNfLX1IGtdPFKtjZFn9f6w4naWE7j8bx8s7afSNb2E8l644fDalrXS71DA9Wyvo/Cb2yskHre112fh6uLbu/YULd3bKhLGTn6Yd9ZLdsTp20xyaU+k5/VSFmJjZSVeLtcvE8UhE9++2S4ZFWqhrJCKAIoAACAms0hPZxCQkIUHx+vjRs3ql+/fpKk7Oxs+fj4KD8/X6tXr9bgwYOLPbNy5UqFh4fL3d1dmZllH1moqIiICI0bN06enqW/Gvy9997TtGnTJEktW7bU0aNH5eLyvzcPbdy4UQMHDpQkjR8/XhEREcWeP3nypC5evKiuXbuWusaKFSs0evRoZWdny8vLS0ePHlWTJk2u4ysrGT2cAMCxChuPr//v0bsjCZcr9PyfhrXRlIGt7FJbfEqGlu+N17KoOB0+Z0VdRo5cfQ/Jtc4eufockWHKK/8ZKxkyNCZsjNoHtpfELigAAICq4NQ9nDp06KD4+HgdPnzYEji5u7urQ4cO2rdvnxYsWHBN4PTVV19Jss8xsxkzZugPf/iDRo8erb59++qGG26Qr6+vLl++rH379mnevHn6+eefLXXOmjWrWNhkjZMnT2rgwIHq3bu3wsPD1blzZ8sOr5iYGH333Xf67rvvLLub3n77bbuETQAAx3N1Malny3rq2bKe/jy8rWIvpmvD4f81Hs8qp/H4u2uidW/3pgr2K/0/jFRW4wAv/V//G/R//W/QobOpWrYnTt9Hxetcain/ccfsptzLNyr38o1yd8uV2WeXXOtEycXrVKWajRebWmYtjF54zedFj+JJBFEAAADOyCGBU79+/bR69Wpt2LBBjz32mOXz++67T7/99pvmzJmjRo0aaezYsbpy5YoiIiK0cOFCGYah4cOH26Wm5ORkffbZZ/rss89KHdO0aVPNmTNHQ4YMqfQ6W7du1datW0u97+3trffee0+TJ0+u9BoAgOqtaV1vPdS7hR4q0ni8cPdTfAmNx3PzzTqWmGaXwKmowiOBzw9rq19PJGtZVJxW7Tury1klHwfMznGVUm5WTsrNqutrVqMGsTpl/k4mD+ubjVujpKN4Ej2hAAAAnIlDjtQdOHBAnTp1kq+vr2JjY+Xv7y9JSk9PV8eOHXXy5MlrmqWazWbVq1dPe/bssfkRsCNHjmjlypX6+eefdezYMSUkJOjChQvy8vJScHCwunTpohEjRmjs2LHy9i65j0Z5R+ouX76s5cuXa+vWrdq5c6fOnj2rpKQk5ebmqm7duurQoYMGDx6sSZMmFettZQ8cqQOA6slsNmtrzAU9+PmvxRqOu5oM/fLCILsHTiXJzMnThsOJWhoVpw1HEkttNl5USKChLqHZ6npDno5d3qUVMStklt3/eCGJnlAAAADXy16ZgUMCJ0natGmTcnNz1bVrV9WrV8/y+alTp/Tggw9ajrAV6tixo7766it17tzZEeXVaAROAFC9zd9+Wi8t26/cfLNcTYb+NrKjxvVsVtVlKSU9W6v2ndOyqDhtP1l6s/FChiHdckOghnSoIzev04q7lK7gOvk66sAQakzYGI1rM06nUk8pNTuVIAoAAKAcTh84lefIkSM6cOCAcnNz1bp16zKbbaNiCJwAoPpLvJypY4lpahXsWyU7m8oTezFd3+8paDZ+NDHN6udMhjT9zvYK7+anqIQopWanSpIOXjioRdGLHL4TSuI4HgAAQFE1PnCC/RA4AQBsxWw26+DZVC2LitPyvfFKSM2y6rkuIQG6vWNDDW4brFbBvjIMQ0kZSZYQaleCY4/iSRzHAwAAkAiccB0InAAA9pCXb9a2mAtaFhWnH/afU1opzcavFlLPS4PbNtDAtsG6uWU9eboVvAm2aABVyJFBVHhouAY2G0j4BAAAapUaFTjl5uZq9+7d2rdvn5KTC3pC1KtXTx07dtRNN90kNzc3R5dUoxE4AQDsLTMnT2sPJWjBjjPafDTJ6ue83V3Ut1WQBrcL1sA2wQr2v/Y44dVBlCNCKI7gAQCA2qJGBE5XrlzRa6+9ptmzZ1uCpqvVrVtXjz76qF566SX5+fk5qrQajcAJAOBIs7fE6O8rDxV78561OjWpo0FtgzW4XbA6Nq4jk8kocZyjj+Nlnh2pbk2bqEOjBmoamC9/b4IoAABQMzh94HTkyBHdfvvtOn36tMpb0jAMhYSE6Mcff1SbNm0cUV6NRuAEAHC0wiboTQO8dez8Za07lKj1hxN19lKm1XME+XpoUNv6GtS2gfq2DpKvh2upYwsDKBlSc7/mOpV6ShvObLBJEJWXFaz0mGlFPjHLre4WeTT4QYaRTy8oAADg1Jw6cLp06ZI6dOigs2fPymw2q2PHjho/frx69uypBg0aSJISEhK0Y8cOffHFF9q3b58kqUmTJtq/f7/q1Klj7xJrNAInAEB1YDabdfjcZa0/nKh1hxIUdSZF1v4pxN3FpJtD6xXsfmrbQM0Cva16zhbH8TLP3aWci7dce8N0WW4Be+RWJ0omj3gZ/92MxXE8AADgTJw6cPrLX/6iN954Q4Zh6NVXX9Vf/vIXGUbJW+TNZrP+8Y9/6KWXXpJhGHr++ef1+uuv27vEGo3ACQBQHV1Iy9Km6PNadzhRPx05r8tWNh2XpFbBvhrUNliD2garW/O6cnMxWf1sRY7jmc2G0qJflPJ9y5zT5HFOrv5RcquzRya3S9fcZxcUAACorpw6cGrXrp2io6M1duxYffvtt1Y9c//992vBggVq06aNDh06ZOcKazYCJwBAdZeTl68dJ5O14XCi1h1OVMz5K1Y/6+/pqlvD6mtwu2ANCAtWXR/3Cq1dGECVdATPbDYp52J3ZSWMklTyfywrLl8u3ifkVme3XP32y3DJKnFU4Rvxmvs1V0pWikIDQgmhAABAlXDqwMnb21tZWVlatWqVhg0bZtUzP/74o4YPHy5PT0+lp6fbucKajcAJAOBsTiRd0frDiVp/OEHbTyQrJ8+6P66YDOmmZnU1qF3B7qc2DfxK3VVdkquP4EnSwQsHNe/XE8o8N1KSiySzrAqfjBy5+h2Um/9uufgelWHklz5UhkaEjuAoHgAAcDinDpwaNGigpKQk7dy5U127drXqmaioKHXr1k1BQUFKTEy0c4U1G4ETAMCZXc7M0ZajSVp3OFEbDifqwpVsq59tEuBVcPSuXbB6hwbK082lUjUkZSRp44ndOn7+ioLr5Gvn2YNas/+Sci51kTm3brnPGy5pcvXfW9DvyTNW1mZgRftBSQRRAADA9pw6cBoyZIg2bNigb7/9VmPHjrXqmYULF2rcuHEaOHCg1q1bZ+cKazYCJwBATZGfb9ZvcZe0/lCC1h1O1IH41PIf+i9PN5P6tgrSoLYNNKhtsBrW8byuWpIykrTr3G7tPZOmH/dd1PG4OlK+V7nPmdwT5VonSm7+e2Ryv1iptekJBQAAbMWpA6dFixbpvvvuU69evbRlyxaZTGU39szPz1efPn20fft2ffPNN7rvvvvsXWKNRuAEAKipzl3K1IYjiVp3KFFbjp1XZk7px9au1r6Rvwb/9+hd56YBMpmsP3pXkrjLifpqe5Q2H8nSoTMm5ZvLn8/F64Rc6+yWm/8+GS6ZlV6bAAoAAFSWUwdOkvToo49q7ty5GjFihGbNmqWGDRuWOC4hIUGPP/64li9frkceeUSzZ892RHk1GoETAKA2yMzJ09aYCwWNxw8lKi4lw+pnA33cNaBNsAa3C1a/1kHy83S7rlqSr2RrxW/xWrTrlPbFppX/gJEjV99Dcq2zR66+R2QYeZVe25ChMWFj1D6wvSSO4QEAgLI5deD05ZdfSpI++ugj7dixQ56enrrtttvUo0cPBQcHyzAMJSQkaMeOHVq9erWysrLUvXt3TZ06tcx5H374YXuXXiMQOAEAahuz2azohDStO5yg9YcStfv0ReVb+SceV5Ohni3raVDbYA1u10Atg3yuq5YTSVe0NCpOy6LidDq5/BehGC5X5Or/m9zq7JbJ84zV/Z7Kc3U/KIkwCgAAOHngZDKZir0hxmw2l/rGmLLuFWUYhnJzc21WY01G4AQAqO0uXsnWpujzWnc4UZuOJCo10/o/Q4QG+WhQ22Dd1CxAvp5uatvIT8F+Fe//ZDabtevURS2NitOK387qUkZOuc8YbklyqxNV0GzcPbnCa1qraBhFCAUAQO3i9IGTrRmGoby8ym83r00InAAA+J/cvHztOnVR6w8nat3hRB1LtOLIWxGGpFfu7qCHe7eodA1ZuXnacPi8lkbFav3hROXklf/HsaC6qUrzWCdX/99kuFh/XLCywkPDNbDZQMInAABqOKcOnE6dOmWXeZs3b26XeWsaAicAAEp3+kK61h8ueOvdrzHJys4rv/G4q8nQLy8MqtROp6ulpGdr5b6zWro7TjtPlf/WOheT1K5pnuoGRWvPlXmSyf47vseEjdG4NuN0KvWUZIgQCgCAGsSpAydULQInAACscyUrV1uOJWn9oUStP5Ko85ezSh37zWM365YbbBu6nL6QrmV74rQ0Kk4nkq6UO97P00VdW5rVqWWGWjYw61DyQS2KXiSz7P/HO3ZAAQBQMxA4odIInAAAqLj8fLP2x19S5N54fbb5RLF7ttzhVBKz2aw9Z1K0NCpOkXvjdTG9/H5PIfW8NKpLE/Vv763k3MNKzU7VroRdWhGzwu4BVGEPKPo/AQDgfAicUGkETgAAXJ/520/rxWX7lZdvlqvJ0N9GdtS4ns0csnZOXr42HTmvpVFxWnMoQdm55R/56xwSoHu6NtGIGxvJ7HJZUQlRSs1OLTbGnmEUu58AAHAeBE6oNAInAACuX+LlTB1LTFOrYF+77Wwqz6WMHP1n/1kt2R2nX0+U/9Y6V5Oh/mH1NeqmJhrSroE83VyK3U/KSCoWRtkjhOINeAAAVG81JnDasGGDli1bpr179yopKUkZGRkqqwTDMHT8+HEHVljzEDgBAFDzxF5M1/d74rVkd6yOn7ei35OHq+7o1Eijbmqini3qyWQyShxXGEJtOLPBrjugOIIHAED14PSBU2JiosaNG6dNmzZJUqkhk2EYxe4ZhqG8vDxHlFhjETgBAFBzmc1m7Y9L1ZKoWEXujVdSWna5zzQJ8NLQdsHq0KSO+repX+qOrcLwSYbU3K+5FhxZYPOm5IYMjQkbo/aB7S2fEUQBAOA4Th045eTkqFevXtqzZ4/MZrO6dOmiJk2aaOXKlTIMQw8++KCSk5O1e/dunT17VoZh6KabblLHjh0lSXPnzrV3iTUagRMAALVDTl6+thxN0tKoOK0+eE6ZOeX3e5Kkvq2CNGXADerRsp7cXExljnXEDqhC7IQCAMD+nDpw+uyzz/T444/LMAzNmTNH48eP14EDB9SpU6drdjAtW7ZMTz75pC5evKgvv/xSo0ePtnd5NR6BEwAAtc/lzBz9Z/85LY2K09aYC7LmT3x+Hq66tU19DW4brIFtglXXx73M8UV7QDnijXhjwsZoSpcpBE8AANiQUwdOt99+u1avXq3hw4dr5cqVklRq4CRJx48fV/fu3ZWbm6vdu3erdevW9i6xRiNwAgCgdjt7KUPf74nX0t1xOpJw2apnTIZ0U7O6GtQuWEPaNVDrYF8ZRsl9nwo5avdT0UbkEkfwAAC4Hk4dODVq1EiJiYn6+uuvdf/990sqHjjl5uZe8weYGTNm6NVXX9WUKVP04Ycf2rvEGo3ACQAASAX9nrYcS9LDc7ZbteOpqKZ1vTS4bbAGt2ugm0PrycPVpczxjngD3tXCQ8M1sNlANfdrrlOpp5SanUoYBQBAOZw6cPLw8FBubq5+/vln9erVS5J09OhRtWnTRoZhKDU1VT4+PsWe2bx5s/r376/WrVvryJEj9i6xRiNwAgAARc3fflovLduv3HyzTIbUKMBLcRczrH7e291F/VoHaXC7BhrYJlj1/Tyseu7qEOrghYM2b0JeGvpBAQBQMqcOnPz8/JSenq4dO3bopptukiQlJCSoUaNGMgxDhw4dUlhYWLFnduzYoZtvvlne3t5KS0uzd4k1GoETAAC4WuLlTB1LTFOrYF8F+3kqITVTGw4nat3hRG05mqSMHOvfEtw5JEBD2gZrULtgtW/kX+7Ru6KqYieUxLE8AAAKOXXg1KFDBx0+fFgrVqzQ8OHDLZ/XqVNHaWlpioiI0EMPPVTsmblz5+rRRx+Vj4+PLl+2rtcASkbgBAAAKiIzJ09bYy5o/aFErTuUoPhLmVY/26iOpwa1DdbgdsG65YYgebqVffSuJFc3I4+MiazwHJXFTigAQG3j1IHTQw89pG+++Uavvfaa/vKXv1g+Dw8P18qVK3XTTTfp559/lodHwXbslJQU9erVS0ePHlX37t3166+/2rvEGo3ACQAAVJbZbNbhc5e1/nBB+BR1JsXq/k+ebib1bRWkQW0baFDbYDWs41mpGpIykjRzz0yHHb8rigAKAFDTOXXgFBERoYkTJ6p37976+eefLZ+vXLlS4eHhMgxDrVq10l133aUrV64oMjJScXFxMgxD77//vqZOnWrvEms0AicAAGArSWlZ2njkvNYdStBP0ed1Jdv6o3cdm/hrUNsGGtw2WJ2a1JHJZP3RO+l/O58SLiXohx9+0E8//aT8xvmq26eujCJzmc3mCh3rs5YhQ2PCxqh9YPtinxNGAQCcmVMHTikpKerSpYvMZrPWr1+vG264wXJv0qRJmjNnTkEx//2DQWFJw4YN08qVK2UymexdYo1G4AQAAOwhOzdf208ka93hBK07lKjTyelWP1vfz0OD2hT0ferXOkje7q5WPbd27VpNnDhRZ86csXzmWsdV3q28ZfI2KT89X1kJWfJo4CHfLr7XhFH2VPiWPMInAIAzcerAqTyzZ8/W559/rgMHDig3N1etW7fWww8/rN///vdydbXuDx8oHYETAACwN7PZrOPn07TuUKLWHUrUzlPJyrfyT5nurib1Dg3U4HbBGtQ2WE3repc4bt68eRo/frzy8gp2VblKGubnr0G+vmrn6ak6JpMu5efrUGam1qel6cfLqdJ/wygXXxfd9shtOqiDvBUPAIAianTgBPsicAIAAI6Wkp6tTdHntfZQojYeSdTlzFyrn23b0O+/jccbqEtIgFxMhtauXathw4YpPz9fktTL21uvNWyoJm7upc4Tl5Ot6efOaVt6wc4rFxcXLVq1SL5hvpa34kmOeTNe0bfiEUIBAKoTAidUGoETAACoSjl5+dp16qLWHUrQusOJijl/xepn6/m4q0/LAH0/82+K3blG5uwMjQsI0EvBDWSyok9Tvtms1xIStOBSiiQpJCRE+/fvl7+/f7FxV78Zz94BlCSNCRujcW3G6VTqKUsARhgFAHA0AidUGoETAACoTk4kXdG6QwlafzhR208kK9fKs3fmvBx5xB/S+Isx6nXukBqnX7DquXyzWZNiz1h2Or3wwgt6/fXXy3ymaAAlSQcvHHToW/I4kgcAcBSnCpx++OEHvfjii5Kk5557Tg888IDVz37zzTd6++23JUn//Oc/NWTIEFuXV+sQOAEAgOoqNTNHP0Wf1/pDidpwJFEX03OsfjbkcoJ6njukm88dVPvkk3Ix55c6NjY7W3eciFGupKCgIMXGxsrDw6NCtV4dQkmOOY4nEUABAOzHaQIns9msdu3a6ejRoxoyZIh+/PHHCj8/bNgwrV27Vp06ddLevXttWV6tROAEAACcQV6+WVGnL2rd4UStP5SoIwmXrX7WOztdrVNi1TfuN/WP3yu/nIxrxjwXH6dVlwvmXLFihe68806b1F0YRG04s8Eh4ZNUvCeUxFE8AEDlOU3gtG7dOg0dOlQuLi7au3ev2rdvX+E5Dh48qM6dOys/P1/r169X//79bVlirUPgBAAAnNGZ5HT94d252hR9QZ7NbpTh6mbVc35ZV7Tgh5d1dYenH1JT9Yez8ZKkl19+WTNmzLBtwaqaXlBFhYeGa2CzgWru19zSG4owCgBQFntlBq42maWIxYsXS5KGDh1aqbBJktq3b69hw4bphx9+0HfffUfgBAAAUAuF1POW+chGJX73nQw3T/395tt1omkn7WjQThc9/Ut9Ls3dSxc9/FQvq/gOqXaenpbrAwcO2KXmIK8gDW0xVJI0Omy0pnWfVuwYnr1DqMiYSEXGRJZ4j2N5AABHsnngtH37dhmGofDw8OuaZ8SIEVq1apW2bdtmo8oAAADgbDIyCo7GmXMy1f/sfo08f1j5MnQ0oKl+bdhem5p2Ubxv/WLPmA2TzvgFXxM4+ZtM18xrb0UDKKl4CCVDxXYiOTqMIoACANiTzQOnU6dOSZLatGlzXfOEhYVJkk6ePHm9JQEAAMBJeXl5Wa4v5eerriSTzGqTckZtUs5oxIlf9PCwl5RncrGMc8nPU8jlxGvmSs3/X1PxovM62tUhVFi9gj/3Xr0jigAKAODMbB44Xbp0SZJUr16965qn8PnU1NRyRgIAAKCmKtqi4VBmplq4uxe7Xy/rsp7cu1gfdh6tPJOLXPLz9OTexdfsbip8vlCHDh3sV/R1KOtIXlUEUAObDSR8AgBUis0DJ39/f128eFEpKSnXNU/h835+ftdfFAAAAJxSjx49LNfr09I03P/a3k23n9qunucO6YxfsEIuJ5YYNknSurT/fV503uqsvJ5Qkv36QhUNoMaEjdG4NuMsx/8k3owHACibzQOn+vXr6+LFizp48KAGDBhQ6XkOHTokSQoODrZRZQAAAHA2Q4YMUVBQkJKSkvTj5VQ9kxOkJm7u14yrl3W51KBJkmKzs7X6csH9oKAgDRkyxG4129PVx/Gka4Mofw9/S2+oDWc22CSMWhS9SIuiF5V4r/AoXlGEUQAAmwdOPXv21JEjRxQZGakpU6ZUep7vv/9ehmE4zX99AgAAgO15enrqscce0z/+8Q/lSpp+7pw+bxoik2FYPUe+2ay/JpxT7n9//9hjj8nDw8Mu9VaVkoKosHphGtpiqN2P5ZX3ZjyO5QFA7WSYzWab7r2dP3++HnjgARmGoU2bNqlv374VnuOnn37SgAEDZBiG5s2bp3HjxtmyxFonNjZWISEhkqQzZ86oadOmVVwRAACA9VJTU9WxY0edOXNGknRfnQBNb9DAqtAp32zWawkJWnApRZLUrFkz7du3T/4lHM2rLZIykhzWF6qoojuh2AEFANWHvTIDmwdOOTk5atOmjU6ePKkGDRrop59+UuvWra1+Pjo6WrfeeqvOnz+vFi1a6MiRI3J1tflGrFqFwAkAADi7tWvX6vbbb1deXp4kqZe3t15t0FBN3a89XlcoNjtbf004p23p6ZIkFxcX/fjjjxo8eLBDanYWVRVASdf2hiKIAgDHc5rASZKWLFmie++9V4ZhyMfHR6+99pomTZokHx+fUp9JS0vT559/rr/+9a9KS0uTYRhavHixRo4caevyah0CJwAAUBPMmzdP48ePt4ROrpJu8/PTYF8/tfP0lL/JpNT8fB3KzNS6tMtaffmy5Ridi4uLvvzySz3wwANVVr+zKAygbNX/qTLYDQUAjuNUgZMkvfbaa3r55Zdl/Hers4+Pj/r166du3bopODhYPj4+unLlihISErR7925t3rxZV65cUWE5r776ql566SV7lFbrEDgBAICaYu3atZo4caLleJ01QkJCNHfuXHY2VUJh+CRDlkbkVbETSvpfCEUABQC25XSBkyTNnTtXTz31lNL/u43ZKOOcfWEZ3t7e+vDDDzVhwgR7lVXrEDgBAICaJDU1VW+88YY+++wzJSUllTouKChIjz32mP785z/X6p5N9lL0KF5RjgqjCKAAwDacMnCSpPj4eL377rv68ssvy/0Dwfjx4/Xss8+qcePG9iyp1iFwAgAANVFWVpbWrl2rHTt26MCBA8rIyJCXl5c6dOigHj16aMiQITXubXTOoiqO5RFAAUDlOG3gVNSBAwe0d+9eXbhwQZcvX5afn58CAwPVuXNndejQwVFl1DoETgAAAKgqV++EcsQOKEOGxoSNUfvA9pbPCKIAoGQ1InBC1SBwAgAAQHVSUm8oR+2GYicUABRH4IRKI3ACAACAM6iK3VC8EQ9AbUfghEojcAIAAICzKhpCObIh+cBmAwmfANQKBE42lJqaqlWrVmnHjh3auXOn4uLidP78eWVkZCggIEDt27fXHXfcoUcffVSBgYE2WfOHH37QrFmztGPHDp0/f17169dXjx49NHnyZA0fPtwma5SGwAkAAAA1haMDqKJH8Jr7NVdKVopCA0IJogDUGARONrR27VoNHTq03HFBQUH6+uuvNWzYsEqvlZ+fr8mTJ2v27Nmljpk0aZI+/fRTmUymSq9TFgInAAAA1FRXH8M7eOGgFkUvsntT8nvD7tWULlMIngA4PQInG1q7dq0mTpyogQMHqlu3bgoJCVGjRo2Un5+v2NhYfffdd1qyZIny8vLk7u6u7du3q3PnzpVa64UXXtAbb7whSeratav+9Kc/6YYbbtDx48f1z3/+U1FRUZZxr7/+us2+xqIInAAAAFCbOLIXFMfvADg7AicbysvLk4uLS5ljli1bplGjRkmSRo0apSVLllR4nejoaHXo0EG5ubnq3r27fvrpJ3l5eVnup6enq3///tq5c6dcXV116NAhtWrVqsLrlIfACQAAALWdI47iET4BcEYETlWgbdu2OnLkiIKCgnT+/PkKPz9lyhTNnDlTkrR161b16tXrmjHbtm1T7969LeM/+uij6yu6BAROAAAAQHH23gVF+ATAWRA4VYEePXpo586d8vX11eXLlyv0rNlsVtOmTRUfH6+2bdvq0KFDpY4tDLaaNGmiM2fOyDCM6y29GAInAAAAoHyFIdSGMxtsHj51a9BNkuTv4U8IBaBasVdm4GqTWWqgI0eOaM+ePZIKAqGKOnHihOLj4yVJ/fv3L3Ns//79deTIEcXFxenkyZNq2bJlhdcDAAAAcH2CvII0tMVQDW0xVNO6Tyu2A8rfw19Hk49q5m8zKzxvZEykImMii33GDigANR2BUxHp6emKi4tTZGSk/vnPfyo3N1eS9Mwzz1R4roMHD1quywusit4/dOgQgRMAAABQxQrDp6KGNh+qsW3Hauaemdf9JrzCEMqQoTFhY9Q+sD27nwDUKA4PnPLz87VhwwZt3bpV586dU3p6uv7+97+rUaNGljHZ2dnKzc2Vi4uLPDw87FpPRESEHnnkkVLv//nPf9YDDzxQ4XljY2Mt1+VtRyvcuiYVbF+7nrVKcvbs2QrPCQAAAOBaQV5Bmt57up7o8oRNjt+ZZdbC6IXFPmP3E4CawKGB04oVK/T000/r1KlTxT5/7rnnigVOn3/+uZ566in5+voqPj5ePj4+jixTktSlSxfNmjVLPXr0qNTzRXs++fr6ljm26NeXlpZW4bWKBlYAAAAA7K+k43e26v1U9AheYf8ndj8BcDYmRy302Wef6e6779bJkydlNpsVGBio0vqVT5o0SXXq1FFaWpqWLl1q17pGjhypffv2ad++fdq+fbu+/fZbjRo1Snv27NH999+vFStWVGrezMxMy7W7u3uZY4vu4srIyKjUegAAAACqRmH49Hq/17V+7Hq92/9dhYeGy9D1vwwoMiZSM7bO0LSN0zRw4UC9uvVVJWUk2aBqALAvh+xwOnr0qKZOnSpJGjRokD788EO1bdtWJlPJeZe7u7tGjx6t2bNna/Xq1XrwwQftVltAQIACAgIsv+/Ro4fGjRunr776SuPHj9fdd9+t2bNna8KECRWa19PT03KdnZ1d5tisrCzLtZeXV4XWkco/hnf27Fn17NmzwvMCAAAAqJiyGo/vSth13TugFkUv0qLoRRy7A1DtOSRweu+995Sbm6uOHTtq1apV5e74kaR+/fpp9uzZioqKckCF13rooYe0YsUKLVy4UE8++aTuuusu1atXz+rn/fz8LNflHZO7cuWK5bq843clsdUrCwEAAADYztWNx0eHjS4WQh28cLDSzceLHrsbEzZGU7pMIXgCUK045Ejd+vXrZRiGnnnmGavCJklq1aqVpMo10baVu+++W1JBIPSf//ynQs8WDYHKa+pd9GukHxMAAABQcxWGUKPDRmt67+k2OYK3KHoRx+0AVDsO2eFUGLh07tzZ6mcKG2mnp6fbpSZr1K9f33J9daPz8rRv395yffjw4TLHFr3frl27Cq0DAAAAwHnZsvl44XG7MWFjNK7NOKVkpSg0IJSdTwCqhEMCJ8MoSOorEh5duHBBklSnTh271GSNuLg4y3VFj7q1bNlSjRs3Vnx8vDZt2lTm2J9++kmS1KRJE7Vo0aLCdQIAAABwfqX1f9qVsMtyfM4ahcGTJBkydG/YvRy5A+BwDjlS16RJE0lSTEyM1c9s2bJFkhQaGmqXmqyxaNEiy3WnTp0q9KxhGJYjeYcPH9a2bdtKHLdt2zbLDqe7777bEs4BAAAAqL2KHr17vd/r2jB2g8aGja3wsTuzzBy5A1AlHBI4DRgwQGazWV988YVV4y9duqRPPvlEhmFo0KBBNq8nIiJCmZmZZY557733tGrVKkkFu5X69etX7P7GjRtlGIYMwyj1DXbPPPOMXFxcJElPPfWUMjIyit3PyMjQU089JUlydXXVM888U4mvBgAAAEBNF+QVdE3Pp4paFL1IgxYOUsT+CNsXCABXcUjg9Pjjj8swDG3atEkRERFljr1w4YJGjhypc+fOydXVVf/3f/9n83pmzJihJk2aaPLkyfryyy/1888/a+/evdqyZYtmzpypvn37atq0aZIkd3d3zZo1yxIcVURYWJj++Mc/SpJ27typPn36aMGCBdq5c6cWLFigPn36aOfOnZKkP/7xj2rdurXtvkgAAAAANU7hzqeiu54qwiyz3tn1jl7c8iK7nQDYlWE2myv+Ds5KmDZtmv71r3/JMAzde++9Gj16tMaNGyfDMPTpp5/K29tbP//8s7755hulpqZKkl555RW99NJLNq+lRYsWVjUBb9q0qebMmaOhQ4dec2/jxo0aOHCgJGn8+PGlBmn5+fl67LHHNGfOnFLXefTRRzVr1iyZTPbJ/2JjYy1vvztz5kyxN+gBAAAAcG5JGUmauWemFkUvqlCjcUOGpnWbpgkdJ9ivOADVnr0yA4cFTmazWU8++aRmzpxZZp+iwnKeeeYZvfvuu3ap5ciRI1q5cqV+/vlnHTt2TAkJCbpw4YK8vLwUHBysLl26aMSIERo7dqy8vb1LnMPawKnQqlWrNGvWLO3YsUNJSUkKCgpSjx499Pjjj2v48OG2/hKLIXACAAAAar6kjCRFJURJhnQ0+ahm/jbTqufuuuEuPdvtWZqKA7WU0wdOhdasWaM33nhDmzZtUn5+fvFiDEO9evXSSy+9ZPcQpjYhcAIAAABqn8KdTwujF1o1fkzYGN5mB9RCNSZwKnT58mVFRUUpMTFReXl5CgwMVJcuXRQUxA83WyNwAgAAAGqvpIwkvbvzXUXGRJY7lmN2QO1jr8zA1SazVIKfn59uvfXWqloeAAAAAGqFIK8gvd7vdbWp10Zv73y7zLGFTcWPphzlmB2A6+KQt9QBAAAAAKrW+A7jtWHsBoWHhpc7dvnx5Rq0cJAi9kfYvzAANRKBEwAAAADUEoW7nZ7r/ly5Ywt3O7245UUlZSQ5oDoANYlDejhNnDixws8YhiFPT0/VqVNHrVu3Vq9evdSuXTs7VFfz0cMJAAAAwNUq0lSc3k5AzeXUTcNNJpMMw7juebp37653331Xffr0sUFVtQeBEwAAAIDSVKSp+NiwsXqiyxP0dgJqEHtlBg45UtesWTM1a9ZMQUFBMpvNll9ubm5q0KCBGjRoIHd3d8vnkhQUFKSmTZvK39/f8vmOHTvUv39/zZs3zxFlAwAAAECNV5FjdgujF2rQwkF6deurHLMDUCaHBE4nT57U0qVL5efnJ3d3dz377LOKiopSenq64uPjFR8frytXrigqKkrPPPOM3Nzc5Ovrq6VLl+rixYs6c+aM3nzzTfn5+Sk/P1+TJk3SmTNnHFE6AAAAANQK1jYVN8usRdGLaCoOoEwOOVKXkJCgrl27KjU1VWvWrFHv3r3LHL9161YNGTJEfn5+ioqKUqNGjSRJUVFR6tu3rzIzM/Xcc8/pzTfftHfpNQJH6gAAAABUxBcHvtDbO9+2auwTnZ/QlC5T7FwRAHtx6iN177zzjs6dO6dp06aVGzZJUu/evTVt2jQlJibqrbfesnzetWtXTZw4UWazWWvWrLFnyQAAAABQaxXudhobNlaGyu7HO3PvTH2852MHVQbAWTgkcPr+++9lGIaGDRtm9TO33367JGnlypXFPh8+fLikgmN6AAAAAAD7CPIK0vTe07V+7HqNDRtb5lhCJwBXc0jgFBsbK0ny8PCw+pnCsYXPFmrcuLEkKT093UbVAQAAAABKUxg8lddUfObemXpxy4s0EwcgyUGBk4+PjyRp165dVj+zc+dOSZK3t3exz7OysiRJ9erVs1F1AAAAAIDyWNNUfPnx5Rq8aLAWRy92YGUAqiOHBE7dunWT2WzWP/7xD128eLHc8RcuXNAbb7whwzDUvXv3YveOHDkiSapfv75dagUAAAAAlCzIK0iv93tdT3R+otQx+eZ8vbr1VXY6AbWcQwKnKVMK3lhw5swZ9erVS//5z39KHfvDDz/olltu0enTpyVJU6dOLXb/P//5jwzDUI8ePexXMAAAAACgVFO6TCk7dFK+Zu6Z6cCKAFQ3ro5YJDw8XE888YRmzpypY8eO6c4771RQUJC6dOli2al0/vx57dmzR0lJ/0vBH3/8cY0YMcLy+3PnzmnZsmUym82WpuIAAAAAAMeb0qVgY8HMvSUHSwujFyrQK9AyDkDt4pDASZI++ugjNW/eXDNmzFBmZqbOnz+vtWvXFhtjNpslFTQMf/nll/XnP/+52H1/f38dOnRIktSkSRPHFA4AAAAAKNGULlPk4+ajt3e+XeL9wjCK0AmofQxzYcrjIAkJCfriiy+0du1a7d+/39LTqW7duurQoYMGDx6s8ePHq1GjRo4sq0aLjY1VSEiIpIJjjU2bNq3iigAAAADUJNHJ0bo38l6ZVfJfL5/o/AShE1BN2SszcHjgBMcjcAIAAABgbxH7I/TOrndKvU/oBFRP9soMHNI0PDQ0VKGhofrwww8dsRwAAAAAwMEmdJxQZiPxmXtn6uM9HzuwIgBVySE9nGJjY5WXl6cuXbo4YjkAAAAAQBUor5E4PZ2A2sMhO5waNmwoSfLy8nLEcgAAAACAKjKlyxR2OgFwTOB08803S5IOHDjgiOUAAAAAAFWI0AmAQwKnJ554QmazWe+9955ycnIcsSQAAAAAoAoROgG1m0MCp0GDBumFF17Q3r17NWLECJ05c8YRywIAAAAAqhChE1B7OaRp+KuvvioPDw916tRJa9asUWhoqPr06aMbb7xRdevWlYuLS5nP//Wvf3VEmQAAAAAAG7OmkfiFjAt6ossTCvIKcmRpAOzIMJvNZnsvYjKZZBiG5fdms7nY78uTl5dnj7JqjdjYWIWEhEiSzpw5o6ZNm1ZxRQAAAABqm4/3fFxq6CRJJpn0bLdnNaHjBMcVBcBumYFDdjhJBSFTWb8HAAAAANRc5e10yle+3tn1jtJz0y1jATgvhwRO+fn5jlgGAAAAAFCNlRc6Fb1H6AQ4N4c0DQcAAAAAQCoIkp7r/pxMZfx1dObemXpxy4tKykhyYGUAbInACQAAAADgUOM7jNe6ses0NmxsqWOWH1+uwYsGa3H0YgdWBsBWCJwAAAAAAA4X5BWk6b2n64nOT5Q6Jt+cr1e2vqLo5GgHVgbAFgicAAAAAABVZkqXKWWGTmaZNTpytCL2RziuKADXzaGBU3Z2tubOnau7775bLVq0kK+vr1xcXMr85erqsBfpAQAAAACqQHmhkyS9s+sd+joBTsRhaU50dLRGjhypI0eOyGw2O2pZAAAAAIATmNJlinzcfPT2zrdLHbP8+HJFHo/UtG7TNKHjBMcVB6DCHBI4XblyRcOHD9eJEydkMpl09913q379+vrss89kGIZeeuklJScna+fOnfr1119lGIZ69+6toUOHOqI8AAAAAEA1ML7DePVu1Fv3Rt4rs0reqGCWWe/sekfpuema0mWKgysEYC2HHKn75JNPdOLECbm4uGj16tVasmSJnn76acv9V155RR988IG2bt2qXbt2qV27dtq2bZsCAwP18ssvO6JEAAAAAEA1EFYvTC/3flmGjDLHzdw7kyN2QDXmkMApMjJShmFo7NixGjRoUJlju3btqg0bNig4OFjTpk3Trl27HFEiAAAAAKCaGB02WuvHrld4aHiZ45YfX65BCwfRUByohhwSOB08eFCSNGrUqBLv5+fnF/t9/fr1NW3aNOXm5urDDz+0e30AAAAAgOolyCtIr/d7Xc91f67McYVH7NjtBFQvDgmcUlJSJEnNmze3fObh4WG5vnLlyjXP9OnTR5K0adMm+xYHAAAAAKi2xncYrw1jN1i122ngwoF6deurBE9ANeCQwMnb21uSZBj/O4MbEBBguT59+nSpz547d85udQEAAAAAqr/C3U5PdH6i3LGLohdp0MJBenvH2wRPQBVySODUsmVLSVJ8fLzls6CgINWrV0+S9PPPP1/zTGHvJnd3dwdUCAAAAACo7qZ0mVLuETup4JjdFwe/0KCFg9jxBFQRhwRO3bt3lyTt3Lmz2OeDBw+W2WzWW2+9peTkZMvnMTExeuONN2QYhrp06eKIEgEAAAAATsDaI3ZSQfBUuOOJxuKAYzkkcBo6dKjMZrOWL19e7POnn35aUkHAFBYWpjFjxuiOO+5Qly5dLLuhJk+e7IgSAQAAAABOwtqG4oVoLA44nkMCpxEjRujWW2+Vn5+fjh8/bvm8T58++utf/yqz2azk5GQtWbJEP/74o9LS0iRJjzzyiB544AFHlAgAAAAAcDKFu53Gho2VIaPc8TQWBxzHMJvN5qouYt26dfr888914MAB5ebmqnXr1nr44Yc1evToqi6tRoiNjVVISIgk6cyZM2ratGkVVwQAAAAAtpWUkaSohChtOLNBkTGRVj0zJmyMpnSZoiCvIDtXB1Rf9soMqkXgBPsicAIAAABQm3xx4Au9vfNtq8eHh4ZrYLOB6hrclfAJtY69MgOHHKkDAAAAAMBRKtJYXJIiYyI1beM0jtsBNkTgBAAAAACocSraWLzQouhFBE+ADVTZkbrU1FRdvnxZeXl55Y5t1qyZAyqquThSBwAAAKA2S8pI0sw9M7UwemGFn6XPE2q6GtHDac2aNfr444+1ZcsWJScnW/WMYRjKzc21c2U1G4ETAAAAAFx/8DSuzTilZKUoNCCUAAo1htMHTk8//bQ++ugjSVJFljQMw6pdUCgdgRMAAAAA/E9h8LQoepHMqvhfiQ0ZujfsXnY+oUZw6sDpm2++0YMPPihJ8vT01MiRI9WtWzfVq1dPJlP5baTGjx9v7xJrNAInAAAAALhWUkaSohKitOHMBkXGRFZqDo7cwdk5deDUv39/bd68WSEhIVq/fr1uuOEGey+JIgicAAAAAKBs13PcTpLCQ8M1sNlAdQ3uSvgEp+LUgVPdunWVmpqqzz77TBMnTrT3crgKgRMAAAAAWOd6gyeJ8AnOxakDJ19fX2VkZGjnzp3q2rWrvZfDVQicAAAAAKBirrfPUyHCJ1R39soMXG0ySzlatGihQ4cOKS0tzRHLAQAAAABwXYK8gjS993Q90eUJRSVESYZ0NPmoZv42s0LzRMZEWvpDET6hNim/Y7cN3HPPPZKkdevWOWI5AAAAAABsIsgrSENbDNXQ5kM1pesUbRi7QWPDxlZqrsiYSE3bOE0DFw7UXzb/RWtOrVF0crS2n92upIwkG1cOVC2HHKm7dOmSunTpoosXL2rbtm1q27atvZdEERypAwAAAADbstWRu0KGDI0IHaFuDbrJ38OfXVBwGHtlBg7Z4VSnTh39+OOPatCggW655RZ9/PHHunjxoiOWLtXOnTv16quv6rbbblPTpk3l4eEhX19fhYWF6ZFHHtGWLVtsss6MGTNkGIZVvzZu3GiTNQEAAAAA9lV45G792PV6t/+7Cg8NlyGj0vOZZVZkTKRmbJ1h2QX16tZX2fkEp2XTHU6hoaFl3k9PT1diYqIlYAkKCpK3t3fZBRqGjh8/bqsSJUm33nqrNm/eXO64hx9+WJ999pnc3d0rvdaMGTP0yiuvWDV2w4YNGjBgQKXXKg07nAAAAADA/pIykhSVEKUNZzZoRcwKm+x8kqQxYWM0pcsUdjzBLpyiafjJkyetGmc2m2U2m5WYmFjuWMOofEJcmvj4eElS48aNNWbMGPXr10/NmjVTXl6etm7dqnfeeUdxcXH68ssvlZOTo2+++cYm6+7bt6/M+y1btrTJOgAAAAAAx7P0e2oxVNO6T7NZ+LQoepG+i/5O07pN04SOE2xXMGBHNg2cxo8fb8vp7KZt27Z6/fXXNXr0aLm4uBS716tXLz300EPq06ePoqOj9e233+r//u//dOutt173uh07drzuOQAAAAAA1Z+twyezzHpn1zsyDEPjOzjH371Ru9k0cJo7d64tp7ObFStWlHk/KChI77zzjsLDwyVJ3333nU0CJwAAAABA7VNS+JSanSp/D38dTT6qT377xOoQ6r1d7+nO0Ds5Xodqz6aBU00ycOBAy7Wte0gBAAAAAGqnwvCp0NDmQzW27VhLCLUrYZciYyJLfT7PnKeYlBgCJ1R7DnlLnTPKysqyXF997A4AAAAAAFspDKFGh43W6/1e14axGzQ2bGyJY10NV4UGlP3CLqA6cFjgdPr0aZ0+fbpYkFOazMxMy/iqsmnTJst1u3btbDLnbbfdpuDgYLm7uys4OFgDBgzQG2+8oYsXL9pkfgAAAACA8wvyCtL03tMtwZPJKPiruyFDo1qPquLqAOs4JHBavXq1WrZsqU6dOik9Pb3c8enp6erQoYNCQ0O18f/bu/O4Ksv8/+PvGxBBzFBPmAa5VISoqan9rNwVyzEXpJxpU0pb1GYcG9seldqeZdoyo9Wog2WpaGou1aCJ5IK5m2ZuIQmh5lFRU5Pt/v3B95wBOez3OWyv5+NxHo+bc1/3dX+ocym+ua7rXrvW/QVeJicnR2+++abz66FDXSfLpbVq1SqdOHFCmZmZOnHihBISEvTcc8+pRYsW+vLLL8vcb2pqapGvo0ePWlI/AAAAAMBzHMHTkx2elCFDpkwtPLBQvWJ7KWZPTEWXBxTJI3s4LVy4UKZpavDgwapfv36x7Rs0aKCoqCh98sknWrBggXr06OH+IvOYNm2aNm/eLEkaMmSIOnToUK7+2rRpo8GDB+uWW25RkyZNlJmZqf379+uzzz5TXFyc0tPTFRUVpeXLl6tfv36l7j8kJKRc9QEAAAAAKif7RbumbZ2Wb1NxxxPrDqYf1LgO49jPCZWSYZpm6Z/HWEqtW7fWTz/9pE8++UT3339/ia6ZN2+e7r//ft10003auXOnewvMIyEhQX369FFWVpaCgoK0e/duBQUFlbm/9PR0BQYGFnr+o48+0uOPPy5JatKkiX7++Wf5+fmV6h6GYZS4bUpKioKDg0vVPwAAAACgYmw+ulkj4kYU2eae0Hs0ut1ogieUSWpqqnMii5WZgUeW1CUnJ0uSQkNDS3zN9ddfL0k6fPiwO0py6ccff1RkZKSysrLk5+enhQsXlitsklRk2CRJjz32mEaMyP3DIy0tTV988UWp75GSklLkyzFbCwAAAABQtbQIbCFvFf0gK5bZoTLySOCUlZUlqXRPe3O0/eOPP9xS0+UOHz6svn376vTp0/L29tb8+fPVrVs3j9z7sccecx7n3ay8pIKDg4t8NW7c2MpyAQAAAAAe4tjHyVDRK1scy+ym75zuocqAonkkcLLZcqf1JSUllfg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\n",
+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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2nHIsSHL0SXdVKdkFVYLjeAAAAIDrEDihxgicgCsXfyFHK/Ynatm+BMWmZFc53svdpAm9Wmlq/za6tnuI3N1q3suurp05X/zZv4lK0NHkqj97TZ90VxX6QQEAAADO16ADp4yMDP3nP/+RJD344INq3bp1peOTkpL0wQcfSJL+8Ic/yNfXgYa2qBCBE+A8NptNh5MytTwyQd9EJSolK7/KOS18PTT5qtaaOqCtBrQPrPFTO+uD6LOZWh6ZqJX7E5WQnlv1BKNAZv/Dcg/YX60n3Tmi9E4oQigAAACgZhp04PTOO+/o0UcfVbdu3RQTE1PleJvNpvDwcB07dkzz5s3TAw884OoSGzUCJ8A1iqw27Yw7p2WRCfru4Fll51f+lDtJ6hjko5v7t9XU/m0UFuJXC1W6htVq097TF7Q8MkGrDyQpPaew6kluF+Xuf0DmZvur9aS76pjefbpm9JihU5mnlFmQKYkwCgAAAKhMgw6cpkyZojVr1uhPf/qTXnrpJYfmvPDCC3rppZd00003afny5a4tsJEjcAJcL7egSOuPJGt5ZIK2HE2VxVr1t9Z+7QN1S/82mtyvjYL9PGuhStcosFi1/Viqlkcmat3hZOUWVr2LqYWf1LVdhg7lR8io5pPuaoodUQAAAMDlGnTg1L59eyUmJmrVqlWaNGmSQ3O+++473XDDDerQoYNOnjzp2gIbOQInoHadv1ig1T8nallkgvadTq9yvJvJ0LXdipuNT+jVUj4eDbfZ+MV8iz142xqbpiIHgrfWzQ2Fhp7UcctXMjyqbs7uTIRQAAAAaOoadODk6ekpi8WivXv3qn///g7NiYqK0sCBA+Xp6ancXAf6hKBCBE5A3Tl17qKWRyZqeVSCTqRV/eQ2Hw83Xd+7laYOaKuruwTJ3ICbjdfkSXddWhq6qnOB+ncukp+3tDd5r1bFrZJNtfd8C0IoAAAANCUNOnBq1qyZsrOztW3bNl199dUOzfnxxx81YsQI+fj4KDvbkacioSIETkDds9ls+jk+Q8siE7Ryf6LOXaz6yW0h/p6aclUb3TKgrfq0DWjQzcar+6Q7N5Ohkd2CdXP/NhrY2V1H039WZkFmnQRQhgw9dNVD6t68O32hAAAA0Og06MApPDxcsbGxeuONN/S73/3OoTn//e9/9dhjjyksLEzHjh1zcYWNG4ETUL8UFlm1/VialkcmaO0hx3oedQnx1S0D2urm/m3VvoVPLVTpOtV90p2Xu0kTerXSzf3a6NruIcosPK/I5Eh7+FMXIVSJkt1QBFAAAABoqBp04PTggw9q/vz56t69uw4cOCB3d/dKxxcWFqpv376KjY3VPffco4iICKfWk5mZqTVr1mj37t3as2ePEhISlJqaqtzcXAUGBqpXr1664YYb9MADDygoKKjG60REROi+++5zaOxHH32kWbNm1XityhA4AfXXxXyL1h4+q2WRidoemyoHWh5pSKfmurl/W93Yt7Wa+3q4vkgXqcmT7gJ93HVD39Ya1S1Yfp7u6tbKT6H+XkrLTVNkcqRkSB39O9qfUlfbYRQBFAAAABqaBh04lRyPMwxDt956qz7++GP5+JT/X+hzcnJ07733aunSpTIMQxs3btSoUaOcWs/69es1YcKEKscFBwfrs88+08SJE2u0DoETgOpIycrTyv1JWh6ZoAMJGVWOd3czNLpHqG4Z0FZjw0Pl5e5WC1W6Rk2edCdJhiHNurqTnr4+vMLPXxJG1cWOKPpBAQAAoL5r0IGTJN15551auHChDMNQu3bt9OCDD2rkyJFq3bq1JCkpKUlbt27Vhx9+qPj4eEnSbbfdpq+++srptaxfv17333+/xowZo0GDBql9+/Zq3bq1rFar4uPj9fXXX2vp0qUqKiqSh4eHdu3apX79+lV7ndKB0/fff682bdpUOLZdu3YKDAys6UeqFIET0PAcS8nWN1EJWhaZoPgLVR878/c0a1Lf4mbjwzoHyWRquP2eavKkOy+zSSO6hWhcz1CN6RGqVs28Kh1fH0KoAM8AdfTvqPT8dHVu1lkhPiEuXxsAAAC4VIMPnPLy8nTTTTdp/fr1lTa+LSlnwoQJ+uabb+TlVfkPDTVRVFQkN7fKdwIsX75ct9xyiyTplltu0dKlS6u9TunA6cSJE+rUqVO17+EMBE5Aw2Wz2bT31AUtq8axs9bNvHRT/+Jm4+GtAmqhStepyZPuJKlX6wCNDQ/V2J6h6tcuUG4OBHDlhVCrT6yW1Watcf2Oyj09S60DgtSvbaAGhBUp0I8dUQAAAKgdDT5wkop/cHrzzTf1r3/9y76L6VLt27fX//t//09z586t8ycyhYeHKyYmRsHBwUpNTa32fAInAM5UYLFqy9FULY9M0LojySqwVB2EhLfy1y0D2uqarkHKzLOoa2hxz6OG6Mz5HH2x67Te3Xy8WvNa+HpodPcQjQkP1bXdQ9TMu/I+gqWl5aYpLj1OgZ6BLusLZS1orovHny71jk1uPrHybPmdTJ6J+nWP6Xqk/yMETwAAAHCJRhE4lbDZbIqKilJkZKTS0tIkFfdLGjhwoPr161fnQVOJIUOGaM+ePfLz81NWVla15xM4AXCVzLxCfXfgrJZHJWhH3Dk5+p3cZEjPT+6l+67p7NoCXWjhrtN6dvlBh47aXcrNZGhwx+bFu5/CQ9U11K9Gf+eU3g11pQFUXsp1Kjw3ttxrJo9kmZtFyj1gv24OH0FDcgAAADhdowqcGoKYmBj16dNHFotFgwcP1u7du6t9DwInALUhKSNXK6IStSwyQdFnqw7H3QxDO/40tsHudJKKG6wfS8lW11A/mU0mbTmaoo3RqdoSk6LMPIvD92nfwltje4RqTHiohoUF1bjx+pUEUNnHnpKtsEWV49y8T/wSPh2Q4ZbLE/EAAADgFAROtSAnJ0cJCQlauXKl/vGPfyg5OVmS9Nlnn+muu+6q9v1KB06jR49WTEyM0tLSFBAQoK5du2r8+PF6+OGH1bZtW6d+jksROAFNx5GkTC2PStCKqEQlZeRVOO6LB3+lq7s0voDCUmTV3lMXtDEmRZuiU3Q0Odvhud7ubrqma7B991NVjccrU52m5JbcVso9+TtJJgfvbpHZL0bmZpEy+0XLMBUHbFPCpmhMhzH2RuRhgWGEUAAAAKgSgZOLlA6FyvPHP/5Rr7zySo2OXFR1b0ny8vLSv//9bz300EPVvn+JivphlUhKStLQoUMlETgBTYXVatNPJ87ry12ntWJ/YplrZpOhH59p2DucHHXmfI42xaRoY3SKfjx+zqG+VyV6tg7QuPDi3U/92zvWeLwyl4ZQAZ4Bij0fq/d+fk/5FwYr/+xUSW6SrJJbrlTkW/VNTXly9z8gc7MoufnEyTD+91e6IUOTwyazCwoAAACVajSBU0n/pv379ystLU25ubmqqoQ///nPLqunolCof//+mjdvnoYMGXJF937ppZd06623avjw4fY/wLi4OC1ZskRff/21/bO///77mjNnTo3WqU4YRuAEND2f7jipF1YcktVW3MPob1P7aMbQDnVdVq3LKbDox2Pn7LufKtsBdqkWvh4a1T1EY2vQeLwqJUFUfHqmUjJMCm1m1dHMvVp+6GdZMgaoMPMqyepT5X0Mc4bMAVFybxYlk2eSyvuroeQYnsRT8AAAAFCsUQROH3/8sf7yl7/o1KlT1ZpXVFTkooqk9PR0+w6h3NxcHT9+XIsWLdKyZcvUpUsX/fvf/9bkyZNrdO+MjAwFBARUGAitWrVKt956qwoLC+Xj46Pjx4+rVatW1V6HwAlAVUr3PGoKO5uqYrPZdCQpy777KfL0BTnag9zNZGhQx+Yad4WNx6uSlpumd6Pe1aKYpbJkd1NhxgBZsntKtqrDLpPnWZkDIovDJ/eMSseWHMUjfAIAAGiaGnzg9Oyzz+rVV1+tcjeTVByglB5ntTp+BMJZPv30U82cOVOGYWj+/PmaNWuWS9Z5+eWX9fzzz9tfP/vss9W+B0fqAODKnL9YUOPG4+2ae9v7Pl1J4/GKlD6KtyM+SqsOxKswo7+KcsLkSN8nN5+44vAp4KAMt9xKx7IDCgAAoOlp0IHTTz/9pOHDh8swDI0fP17//Oc/ZbVaNXDgQBmGIYvFovPnz2vPnj169913tWLFCo0YMUKLFy9Wy5YtXV1ehW6//XYtWrRIvr6+On36tFq0qPopQtWVkpKiVq1ayWazacKECVq7dq3T16BpOAA4zlJk1b7T6doQnVzDxuNBGvNLANW6mbfT6ysJoM5cyNTK/Unaf8JT1vw2VU80LDL7RcscECmzX4y92XhVSjcjP5V5SjJEEAUAANCINOjAadasWfrkk0/UqVMnHT16VGazWYcOHVLfvn1lGMZlR+beffddzZ07V/369dNPP/0kDw8PV5dYri+++ML+dLrPP/9cd955p0vWCQkJUVpamnr16qVDhw45/f4ETgBQc1faeHxseHHvp/7tm19x4/HypOWmadWRvdoanaeoOLPOO5KPmXLlHnBA5oBIufmcLNNs3FElu6HYCQUAANCwuSozMDvlLlX48ccfZRiGfve738lsrnrJhx9+WBs3btTSpUv1zjvv6LHHHnN9keUICQmxv65u36nqcEXvDwCAc7Rv4aN7h3fSvcM7KbegSD8eT9OGaMcajx9JytSRpEy9vem4mvu4a3SP4qfejeoWomY+zmk8HuwdrFkDJ2rWwOKnE+4+eV4L98Tp+4MpyimoYJLVW4XpQ1WYPlSGOV3uzaKKwyevZIfXXRm3UivjVtp/z3E8AAAAlFYrgVNSUpIkqXfv3vb3TKb/9Z0oLCyUu3vZf3jfc889WrJkib766qs6C5wSEhLsr/38/FyyRmpqqtLS0iRJbdo4cCQCAFBnvD3cNK5nS43r2VI2m03RZ7O0MdqxxuMXcgq1LDJByyIT7I3HS3o/dXNS43GTydCvwoL0q7Ag5d9apE3RqfomKkHrjySrsKj84myWQBWcG62Cc6Nl8kySe7NImQOiZHLPrNbalwZQEiEUAABAU1YrgVNhYaEkKTQ01P5e6QAnNTX1srClZAvXsWPHaqHC8i1evNj+um/fvi5ZY968efYG6aNGjXLJGgAA5zMMQz1bB6hn6wDNHdNVFy4WaMvRVG2MTtHmKhqPF1lt2nXivHadOK9Xv41Wu+beGh4WpM4hvppyVRu1b+FzxfV5mt10fZ9Wur5PK2XkFurbA0laHpWgnXHnK5xjzW+t/JTWyk+5Xm4+J4rDJ/8DMtzya1RDZSEUARQAAEDjVis9nNq3b6/ExERt3rxZI0eOlCQVFBTI19dXVqtVa9eu1bhx48rMWb16taZMmSIPDw/l5VV+ZKG6IiIiNGPGDHl5Vfxo8DfeeENPPPGEJKlz586KjY2Vm9v/njy0efNmjRkzRpI0c+ZMRURElJl/8uRJXbhwQQMGDKhwjVWrVmnatGkqKCiQt7e3YmNj1bZt2yv4ZOWjhxMA1K6SxuMbfzl6F5OcVa35T03soUfGdHVJbYnpuVqxP1HLIxMUfdaBuoxCmf2OyNwsSmbfGBmmoqrnOMiQoendp6tXUC9J7IICAACoCw26h1Pv3r2VmJio6Ohoe+Dk4eGh3r1768CBA/rqq68uC5w+/fRTSa45Zvbiiy/qD3/4g6ZNm6YRI0aoS5cu8vPzU1ZWlg4cOKDPP/9cP/zwg73OefPmlQmbHHHy5EmNGTNGw4cP15QpU9SvXz/7Dq+4uDh9/fXX+vrrr+27m/71r3+5JGwCANQ+s5tJQzu30NDOLfTHSeGKv5CjTdH/azyeX0Xj8dfXHdVtg9sp1L/i/zBSU20CvfWbUV30m1FddCQpU8ujEvRNZKLOZlbwH3ds7rJkXSVL1lXycLfI5rtX5maRcvM+VaNm42VuLZsWHV102fulj+JJBFEAAAANUa0ETiNHjtTatWu1adMmPfjgg/b3b7/9dv38889asGCBWrdurV//+te6ePGiIiIitGjRIhmGoUmTJrmkpvPnz+uDDz7QBx98UOGYdu3aacGCBRo/fnyN19mxY4d27NhR4XUfHx+98cYbmjNnTo3XAADUb+2a++ie4Z10T6nG4yW7nxLLaTxusdp0LCXbJYFTaSVHAp+eGK6fTpzX8sgErTmQpKz88o8DFhSapfRfqTD9V2ruZ1PrlvE6ZftaJk/Hm407oryjeBI9oQAAABqSWjlSd+jQIfXt21d+fn6Kj49XQECAJCknJ0d9+vTRyZMnL2uWarPZ1KJFC0VFRTn9CFhMTIxWr16tH374QceOHVNycrLOnTsnb29vhYaGqn///po8ebJ+/etfy8en/D4aVR2py8rK0ooVK7Rjxw7t2bNHSUlJSktLk8ViUfPmzdW7d2+NGzdOs2fPLtPbyhU4UgcA9ZPNZtOOuHO6+8OfyjQcN5sM/fjMWJcHTuXJKyzSpugULYtM0KaYlAqbjZfWPshQ/7ACDehSpGNZe7UqbpVscvk/LyTREwoAAOBKuSozqJXASZK2bNkii8WiAQMGqEWLFvb3T506pbvvvtt+hK1Enz599Omnn6pfv361UV6jRuAEAPXbwl2n9dzyg7JYbTKbDL08tY9mDO1Q12UpPadAaw6c1fLIBO06WXGz8RKGIV3dJUjjezeTu/dpJWTkKLSZVbG1GEJN7z5dM3rM0KnMU8osyCSIAgAAqEKDD5yqEhMTo0OHDslisahbt26VNttG9RA4AUD9l5KVp2Mp2eoa6lcnO5uqEn8hR99EFTcbj03JdnieyZCev7GXpgzyV2RypDILMiVJh88d1uKji2t9J5TEcTwAAIDSGn3gBNchcAIAOIvNZtPhpEwtj0zQiv2JSs7Md2he//aBur5PK40LD1XXUD8ZhqG03DR7CLU3uXaP4kkcxwMAAJAInHAFCJwAAK5QZLVpZ9w5LY9M0LcHzyq7gmbjl2rfwlvjwltqTHioftW5hbzci58EWzqAKlGbQdSUsCka02EM4RMAAGhSGlXgZLFYtG/fPh04cEDnzxf3hGjRooX69OmjgQMHyt3dvbZLatQInAAArpZXWKT1R5L11e4z2hab5vA8Hw83jegarHE9QzWmR6hCAy4/TnhpEFUbIRRH8AAAQFPRKAKnixcv6qWXXtL8+fPtQdOlmjdvrgceeEDPPfec/P39a6u0Ro3ACQBQm+Zvj9PfVh8p8+Q9R/Vt20xjw0M1rmeo+rRpJpPJKHdcbR/Hy0uaqkHt2qp365ZqF2RVgA9BFAAAaBwafOAUExOj66+/XqdPn1ZVSxqGofbt2+v7779Xjx49aqO8Ro3ACQBQ20qaoLcL9NGx1CxtOJKijdEpSsrIc/gewX6eGhseorHhLTWiW7D8PM0Vji0JoGRIHf076lTmKW06s8kpQVRRfqhy4p4o9Y5N7s23y7PltzIMK72gAABAg9agA6eMjAz17t1bSUlJstls6tOnj2bOnKmhQ4eqZcuWkqTk5GTt3r1bH3/8sQ4cOCBJatu2rQ4ePKhmzZq5usRGjcAJAFAf2Gw2RZ/N0sboFG04kqzIM+ly9F8hHm4m/SqsRfHup/CW6hDk49A8ZxzHyzt7kwovXH35BVOW3AOj5N4sUibPRBm/bMbiOB4AAGhIGnTg9Kc//UmvvvqqDMPQX//6V/3pT3+SYZS/Rd5ms+nvf/+7nnvuORmGoaefflqvvPKKq0ts1AicAAD10bnsfG05mqoN0SnaGpOqLAebjktS11A/jQ0P1djwUA3q2FzubiaH51bnOJ7NZij76LOS1a/Se5o8z8ocECn3ZlEyuWdcdp1dUAAAoL5q0IFTz549dfToUf3617/Wl19+6dCcO+64Q1999ZV69OihI0eOuLjCxo3ACQBQ3xUWWbX75Hltik7RhugUxaVedHhugJdZ13YP0bieoRrdPVTNfT2qtXZJAFXeETybzaTCC4OVn3yLpPL/Y1lZVrn5nJB7s30y+x+U4ZZf7qiSJ+J19O+o9Px0hQWGEUIBAIA60aADJx8fH+Xn52vNmjWaOHGiQ3O+//57TZo0SV5eXsrJyXFxhY0bgRMAoKE5kXZRG6NTtDE6WbtOnFdhkWP/XDEZ0sAOzTW2Z/Hupx4t/SvcVV2eS4/gSdLhc4f1+U8nlHd2qiQ3STY5FD4ZhTL7H5Z7wD65+cXKMKwVD5WhyWGTOYoHAABqXYMOnFq2bKm0tDTt2bNHAwYMcGhOZGSkBg0apODgYKWkpLi4wsaNwAkA0JBl5RVqe2yaNkSnaFN0is5dLHB4bttA7+Kjdz1DNTwsSF7ubjWqIS03TZtP7NPx1IsKbWbVnqTDWncwQ4UZ/WWzNK9yvuGWLXPA/uJ+T17xcjQDK90PSiKIAgAAztegA6fx48dr06ZN+vLLL/XrX//aoTmLFi3SjBkzNGbMGG3YsMHFFTZuBE4AgMbCarXp54QMbTySrA3RKTqUmFn1pF94uZs0omuwxoa31NjwULVq5nVFtaTlpmnv2X3afyZb3x+4oOMJzSSrd5XzTB4pMjeLlHtAlEweF2q0Nj2hAACAszTowGnx4sW6/fbbNWzYMG3fvl0mU+WNPa1Wq6655hrt2rVLX3zxhW6//XZXl9ioETgBABqrsxl52hSTog1HUrT9WKryCis+tnapXq0DNO6Xo3f92gXKZHL86F15ErJS9OmuSG2LydeRMyZZbVXfz837hMzN9sk94IAMt7war00ABQAAaqpBB06S9MADD+ijjz7S5MmTNW/ePLVq1arcccnJyXrooYe0YsUK3XfffZo/f35tlNeoETgBAJqCvMIi7Yg7V9x4/EiKEtJzHZ4b5Ouh0T1CNa5nqEZ2C5a/l/sV1XL+YoFW/ZyoxXtP6UB8dtUTjEKZ/Y7I3CxKZr8YGUZRjdc2ZGh69+nqFdRLEsfwAABA5Rp04PTJJ59Ikt5++23t3r1bXl5euu666zRkyBCFhobKMAwlJydr9+7dWrt2rfLz8zV48GDNnTu30vvee++9ri69USBwAgA0NTabTUeTs7UhOlkbj6Ro3+kLsjr4Lx6zydDQzi00NjxU43q2VOdg3yuq5UTaRS2LTNDyyASdPl/1g1AMt4syB/ws92b7ZPI643C/p6pc2g9KIowCAAANPHAymUxlnhBjs9kqfGJMZddKMwxDFovFaTU2ZgROAICm7sLFAm05mqoN0SnaEpOizDzH/w0RFuyrseGhGtghUH5e7gpv7a9Q/+r3f7LZbNp76oKWRSZo1c9JysgtrHKO4Z4m92aRxc3GPc5Xe01HlQ6jCKEAAGhaGnzg5GyGYaioqObbzZsSAicAAP7HUmTV3lMXtDE6RRuiU3QsxYEjb6UYkv5yc2/dO7xTjWvItxRpU3SqlkXGa2N0igqLqv7nWHDzTGV7bpA54GcZbo4fF6ypKWFTNKbDGMInAAAauQYdOJ06dcol9+3YsaNL7tvYEDgBAFCx0+dytDG6+Kl3P8WdV0FR1Y3HzSZDPz4ztkY7nS6VnlOg1QeStGxfgvacqvqpdW4mqWe7IjUPPqqoi59LJtfv+J7efbpm9JihU5mnJEOEUAAANCINOnBC3SJwAgDAMRfzLdp+LE0bj6RoY0yKUrPyKxz7xYO/0tVdnBu6nD6Xo+VRCVoWmaATaRerHO/v5aYBnW3q2zlXnVvadOT8YS0+ulg2uf6fd+yAAgCgcSBwQo0ROAEAUH1Wq00HEzO0cn+iPth2osw1Z+5wKo/NZlPUmXQti0zQyv2JupBTdb+n9i28dUv/thrVy0fnLdHKLMjU3uS9WhW3yuUBVEkPKPo/AQDQ8BA4ocYInAAAuDILd53Ws8sPqshqk9lk6OWpfTRjaIdaWbuwyKotMalaFpmgdUeSVWCp+shfv/aBunVAW02+qrVsblmKTI5UZkFmmTGuDKPY/QQAQMNB4IQaI3ACAODKpWTl6VhKtrqG+rlsZ1NVMnIL9d3BJC3dl6CfTlT91DqzydCo7iG6ZWBbje/ZUl7ubmWup+WmlQmjXBFC8QQ8AADqt0YTOG3atEnLly/X/v37lZaWptzcXFVWgmEYOn78eC1W2PgQOAEA0PjEX8jRN1GJWrovXsdTHej35GnWDX1b65aBbTW0UwuZTEa540pCqE1nNrl0BxRH8AAAqB8afOCUkpKiGTNmaMuWLZJUYchkGEaZa4ZhqKioqDZKbLQInAAAaLxsNpsOJmRqaWS8Vu5PVFp2QZVz2gZ6a0LPUPVu20yjeoRUuGOrJHySIXX076ivYr5yelNyQ4amd5+uXkG97O8RRAEAUHsadOBUWFioYcOGKSoqSjabTf3791fbtm21evVqGYahu+++W+fPn9e+ffuUlJQkwzA0cOBA9enTR5L00UcfubrERo3ACQCApqGwyKrtsWlaFpmgtYfPKq+w6n5PkjSia7AeGd1FQzq3kLubqdKxtbEDqgQ7oQAAcL0GHTh98MEHeuihh2QYhhYsWKCZM2fq0KFD6tu372U7mJYvX65HH31UFy5c0CeffKJp06a5urxGj8AJAICmJyuvUN8dPKtlkQnaEXdOjvyLz9/TrGt7hGhceKjG9AhVc1+PSseX7gFVG0/Em959uh7p/wjBEwAATtSgA6frr79ea9eu1aRJk7R69WpJqjBwkqTjx49r8ODBslgs2rdvn7p16+bqEhs1AicAAJq2pIxcfROVqGX7EhSTnOXQHJMhDezQXGN7hmp8z5bqFuonwyi/71OJ2tr9VLoRuVR8BK9/SH+F+IS4ZD0AABqzBh04tW7dWikpKfrss890xx13SCobOFkslsv+AfPiiy/qr3/9qx555BG99dZbri6xUSNwAgAAUnG/p+3H0nTvgl0O7XgqrV1zb40LD9W4ni31q7AW8jS7VTq+Np6AV8JW5Kns44+rXbBF0wa31A29Out01mllFmRyHA8AgCo06MDJ09NTFotFP/zwg4YNGyZJio2NVY8ePWQYhjIzM+Xr61tmzrZt2zRq1Ch169ZNMTExri6xUSNwAgAApS3cdVrPLT8oi9UmkyG1DvRWwoVch+f7eLhpZLdgjevZUmN6hCrE39OheZeGUIfPHXZKE/LcxNtkyRhs/73hlin3Fj/IvVmUTO4ZkugHBQBARRp04OTv76+cnBzt3r1bAwcOlCQlJyerdevWMgxDR44cUffu3cvM2b17t371q1/Jx8dH2dnZri6xUSNwAgAAl0rJytOxlGx1DfVTqL+XkjPztCk6RRuiU7Q9Nk25hY4/Jbhf+0CNDw/V2J6h6tU6oMqjd6Vd6U4oq8VPF2OflVTemla5+RyXe7NImQMOyjD97wl+5R3LI4gCADRFDTpw6t27t6Kjo7Vq1SpNmjTJ/n6zZs2UnZ2tiIgI3XPPPWXmfPTRR3rggQfk6+urrCzHeg2gfAROAACgOvIKi7Qj7pw2HknRhiPJSszIc3hu62ZeGhseqnE9Q3V1l2B5uVd+9K48lzYjXxm3ssKxhRl9lJd4d9U3NQpk9j8o92b75OZ7XIZR/j+B2QkFAGhqGnTgdM899+iLL77QSy+9pD/96U/296dMmaLVq1dr4MCB+uGHH+TpWbwdOz09XcOGDVNsbKwGDx6sn376ydUlNmoETgAAoKZsNpuiz2ZpY3Rx+BR5Jt3h/k9e7iaN6BqsseEtNTY8VK2aedWohrTcNL0b9W65x++Kdzg9I8nxYMswZxTvemq2T26eKZWOJYACADR2DTpwioiI0P3336/hw4frhx9+sL+/evVqTZkyRYZhqGvXrrrpppt08eJFrVy5UgkJCTIMQ//97381d+5cV5fYqBE4AQAAZ0nLztfmmFRtOJKsrUdTdbHA8aN3fdoGaGx4S40LD1Xfts1kMjl+9E66/PidVHwEb+nes8o7O1XFoVOR3LxPqyi/tWStOuAyecX/cuRuv0zmyts4GDI0vft09QrqVeZ9wigAQEPWoAOn9PR09e/fXzabTRs3blSXLl3s12bPnq0FCxYUF/PLef+SkiZOnKjVq1fLZDK5usRGjcAJAAC4QoHFql0nzmtDdLI2HEnR6fM5Ds8N8ffU2B7FfZ9GdguWj4e5xnWk5aZp84l9Op56UV1CfXVVy06KPX9SX+w9qJ+O2mS52E1V74AqkpvfUbk32yez3xEZJku165gSNkVjOowhfAIANCgNOnCqyvz58/Xhhx/q0KFDslgs6tatm+699179/ve/l9lc8398oBiBEwAAcDWbzabjqdnacCRFG46kaM+p87I6+K9MD7NJw8OCNK5nqMaGh6pdcx+n1ZWWm6YtJ/Zpa0yOth7J14VMv6onmXLlHvCzzM0i5eZ9UtXogW7HUTwAQEPRqAMnuBaBEwAAqG3pOQXacjRV64+kaHNMirLyHN8xFN7K/5fG4y3Vv32g3Kp59K4yO0+e1kc7DmlHbJEyc6q+r+F+Tu7NIuXeLFImj3M1Xrf0U/EIoQAA9QmBE2qMwAkAANSlwiKr9p66oA1HkrUhOkVxqRcdntvC10Oje4RofM+WGtktWP5e7k6pqchq04/H07R0X4K+O3hWuYVV96IyeZ8sDp8CfpbhlnvFNUzvPl0zeszQqcxT9r5UhFEAgNpG4IQaI3ACAAD1yYm0i9pwJFkbo1O068R5WRw8e+fuZmho5xYaG95S43uGqmOQr1Pqyc636LuDZ7V0X7x2xJ2r+il8hkVmvyNyb7ZPbn5HZRiON053FEfyAAC1pUEFTt9++62effZZSdKTTz6pO++80+G5X3zxhf71r39Jkv7xj39o/Pjxzi6vySFwAgAA9VVmXqG2Hk3VxiMp2hSTogs5hQ7P7RLiq3E9i596N6hjc5ndrvxBM4npuVoelaAle+N13IGdWJ4ehbL57pa52T6ZvOJr1O/JEQRQAABXaTCBk81mU8+ePRUbG6vx48fr+++/r/b8iRMnav369erbt6/279/vzPKaJAInAADQEBRZbYo8fUEbolO08UiKYpKzHJ7r72VW37bNNKlPK93Ur62a+VzZ0TubzaYDCRlaui9BK/Yn6vzFgirnBPjmKN9nq8zNImVyz7ii9atSuieUxFE8AEDNNZjAacOGDZowYYLc3Ny0f/9+9erVq9r3OHz4sPr16yer1aqNGzdq1KhRziyxySFwAgAADdGZ8znaGJ2iDdEp2nn8nAqKrA7NC/R2V+SfJ8hw0najAotVW46mallkvNYfTqmyDkNSl9ZFCg49rkO5n0tu+U6pwxFTwqZoTIcx6ujf0d4bijAKAFAZV2UGZqfcpZQlS5ZIkiZMmFCjsEmSevXqpYkTJ+rbb7/V119/TeAEAADQBLVv4aOZV3fSzKs76WK+Rdti07QxOlkbo1OVll1xiJORV6jU7HyF+ns5pQ4Ps0kTerXUhF4tlZFTqFUHErV0X4L2nrpQ7nibpGNJbjqW1F2e5pfUv7PULyxP3VpbFZm6V6viVskm17RRXRm3UivjVpZ7jWN5AIDa5PTAadeuXTIMQ1OmTLmi+0yePFlr1qzRzp07nVQZAAAAGipfT7Ou79NK1/dpJavVpp8TMrTxSLJW7E/UyXM5ZcbabNKxlGynBU6lNfNx112/6qi7ftVRJ9MuamlkgpZFxuvM+fKfWpdvseqnWOmnWA+1DPDU1P73aN7o3yjLFiMZKrMTaW9y7YZRBFAAAFdy+pG6kJAQnT9/XuvWrdPYsWNrfJ+NGzdq/PjxCgoKUmpqqhMrbHo4UgcAABqrlKw8Df/7RhWVetKd2WTox2fGuiRwKo/NZtOeUxe0dF+8Vv2cpKw8S5VzercJ0C0D2urm/m0V4u9pfz8tN02RyZG1EkBdigAKAJqmBtPDycPDQ0VFRdq7d6/69+9f4/tERUVp4MCBcnd3V35+7Z17b4wInAAAQGO2cNdpPbf8oCxWm8wmQy9P7aMZQzvUSS15hUVafyRZy/YlaPPR1DJBWHncTIau7RasWwe204ReLeXl7lbmel0HUGM6jCF8AoBGrsEETsHBwbpw4YI2bNig0aNH1/g+mzdv1tixY9WiRQulpaU5r8AmiMAJAAA0dilZeTqWkq2uoX61trOpKmnZ+VoRlailkfE6mJBZ5Xh/T7Nu6Ntatw5sqyGdWshkurzpeekAqkRtBFHTu0/XjB4z7Mf/JJ6MBwCNRYMJnHr27KmjR4/qzTff1COPPFLj+7z77ruaO3euwsPDdfjwYSdW2PQQOAEAANStmLNZWhoZr+WRCUrOrHr3frvm3prYq6V6tQnQyO4hVYZopYOoAM8Ae2+oTWc2uTyMKjmKVxphFAA0HA0mcJo5c6Y+/fRT+1Pmaur666/XunXrdPfdd+vjjz92YoVND4ETAABA/VBktWnH8XNaui9e3x48q9zCIofmXdstWHPHdNWgjs1ldjNVa02O5QEAKtNgAqeFCxfqzjvvlGEY2rJli0aMGFHte2zdulWjR4+WYRj6/PPPNWPGDGeW2OQQOAEAANQ/F/Mt+u7gWS2NjNePx8/JkX+VB/q4a3T3EI3r2VLXdg9RM2/3aq9bFwGUrchDXY371b9dG3UMsapdc3ZAAUB90WACp8LCQvXo0UMnT55Uy5YttXXrVnXr1s3h+UePHtW1116r1NRUderUSTExMTKbzc4ssckhcAIAAKjfkjJytTwyUUv2xetYSrZDc8wmQ0M6tdC4nqEa37OlOgX71mjt2gigchNvlSVj6C+/s8ncbLe8Wq3Sr8NvLtMbiqN4AFD7GkzgJElLly7VbbfdJsMw5Ovrq5deekmzZ8+Wr2/FfwlmZ2frww8/1J///GdlZ2fLMAwtWbJEU6dOdXZ5TQ6BEwAAQMNgs9m07WiaZkbscmjHU2ldQnw1vmdLjQ0PrdHRuxIlAZSz+j9ZLX66GPuspEuboBfIHHBE7gFRcvM9KsP0v+OFpftCEUIBgGs1qMBJkl566SW98MILMoziv1h8fX01cuRIDRo0SKGhofL19dXFixeVnJysffv2adu2bbp48aJKyvnrX/+q5557zhWlNTkETgAAAA3Lwl2n9dzyg7JYbTIZUmiAl85m5Dk8v/TRu1E9QhTgVf2jd9L/wicZsjcir+5OqMLMXspLuLfyQaZcuQcckDkgSm4+J2QYl9+3JIQigAIA52pwgZMkffTRR/rtb3+rnJyc4sWMyx/tWqKkDB8fH7311luaNWuWq8pqcgicAAAAGp6UrDwdS8lW11A/hfp7KSE9VxuPJGv9kRTtOH5OBUVWh+5jNhka2rmFxoZf2dG7S5U+ilfapWGUJae9ck89ost3OJXPMGfKHLBf7gH7ZfKKV0U/QhBAAYBzNMjASZISExP1+uuv65NPPlFaWlqF44KDgzVz5kw9/vjjatOmjStLanIInAAAABqXi/kWbT+Wpg1HkrUxOkVp2QUOzy05ejeuZ0sN7BBY46N3lbn0WF7+hcHKPztVkpsk2y+/ql7XcE+Te7MomQP2y80ztdKxBFAAUDMNNnAq7dChQ9q/f7/OnTunrKws+fv7KygoSP369VPv3r1rq4wmh8AJAACg8bJabdofn64NR1K0ITpFR5Iyq570C2cdvatMSfgUn56plAyTzhZEad3ptSrM6i1LRn8V5XZ26D4mzwR7+GRyr/wzGjI0vft09QrqZX+PIAoAytcoAifUDQInAACApuNKj96N69lS43uGqmOQc47elad0bygvaxstjzqjDUcylJ7p58Bsq9x8TsocECV3/4MyzDnVWpudUABQFoETaozACQAAoGm6mG/Rttg0bYyun0fvLrXr9Gl9vPOQdsZadC7LkfWK5OZ3VO4BUTL7H5FhcvzzleCJeACaOgIn1BiBEwAAAEofvVt/JFnRZ7Mcnhvo464xPUI1NjzUZUfvSrPZbIo6k64V+xO1IipB5y4WVj3JKJDZ/7DcA/bLze+oDKOoxutPCZuiMR3GED4BaBIInJwoMzNTa9as0e7du7Vnzx4lJCQoNTVVubm5CgwMVK9evXTDDTfogQceUFBQkFPW/PbbbzVv3jzt3r1bqampCgkJ0ZAhQzRnzhxNmjTJKWtUhMAJAAAAl4q/kKNN0Sn1+uidJBVZbdpx/JxW7E/QtwfPKivPUvUkU47cAw4UNxv3OSHDqPmPPKWP4HX076j0/HSFBYYRRAFoNAicnGj9+vWaMGFCleOCg4P12WefaeLEiTVey2q1as6cOZo/f36FY2bPnq33339fJpNrtikTOAEAAKAyJUfvNhxJ1qaY+nv0Lq+wSJtjUrVyf6LWH0lWvqXqkMwwZ8gc8LPcA6Jk8kqQYVx5HYYM3db9Nj3S/xGCJwANHoGTE61fv17333+/xowZo0GDBql9+/Zq3bq1rFar4uPj9fXXX2vp0qUqKiqSh4eHdu3apX79+tVorWeeeUavvvqqJGnAgAF66qmn1KVLFx0/flz/+Mc/FBkZaR/3yiuvOO0zlkbgBAAAAEc54+jduJ6hura7a4/eZeUVau2hZK3Yn6jtx9JUZK36xxrDI1XuAfuLwyfPNKfUwfE7AA0dgZMTFRUVyc3NrdIxy5cv1y233CJJuuWWW7R06dJqr3P06FH17t1bFotFgwcP1tatW+Xt7W2/npOTo1GjRmnPnj0ym806cuSIunbtWu11qkLgBAAAgJqKv5Cjjb8cvdtZT4/epWXn69sDSfomKlF7Tl1waI7JK7642XjAzzK5ZzqlDsInAA0RgVMdCA8PV0xMjIKDg5Wamlrt+Y888ojeffddSdKOHTs0bNiwy8bs3LlTw4cPt49/++23r6zochA4AQAAwBmu5OhdpyAf9WnbTDf1a6Ox4aEuO3oXfyFHK/cn6ZuoBId2ZxmyKayVVUEhJ3Qk/wvJLccpdRA+AWgoCJzqwJAhQ7Rnzx75+fkpK8vxrcRS8ZM12rVrp8TERIWHh+vIkSMVji0Jttq2baszZ87IcMbB8lIInAAAAOBsVqtNUfHp2nAkWRuOpFTr6F2XEF9t+MNo1xX3i5izWVqxP0Er9ifqzPncKsebTYZ6t5d8m0frQO7nksnxQK0yJY3HJSnAM4AQCkC94qrMwOyUuzRCMTExioqKklQcCFXXiRMnlJiYKEkaNWpUpWNHjRqlmJgYJSQk6OTJk+rcuXO11wMAAABqk8lkaGCH5hrYobn+38Twah29O5F2USlZeQr193JpjT1a+ev/tQrXk9f1UOSZdK2IStSqnxMr3Jllsdq0/5SkUz3k5f6yruoo9e2Up+5trWrhE6DY87F69+d3q13HyriVWhm3ssx77IAC0NgROJWSk5OjhIQErVy5Uv/4xz9ksRQ/cvWxxx6r9r0OHz5sf11VYFX6+pEjRwicAAAA0OC0a+6je4d30r3DOyk736LtsanacCRF3x86q8w8S5mxVpt0LCXb5YFTCcP4Xzj23I09tSPunL6JStT3B88qK99S7py8Qqt2HZN2HfNQoI+7bujbSjf1G6gN06fr/f3vafHRxbKp5odFSkIoQ4amd5+uXkG92P0EoFGp9cDJarVq06ZN2rFjh86ePaucnBz97W9/U+vWre1jCgoKZLFY5ObmJk9PT5fWExERofvuu6/C63/84x915513Vvu+8fHx9tdVbUcr2bomFW9fu5K1ypOUlFTtewIAAAA15edp1vV9Wuv6Pq315HU9dPVrG8s8Rc5sMtQ11K9OajO7mTSyW4hGdgvRy1P7aHNMir6JStSG6BQVWMrflZWeU6gvfjqtL346rdbNvDSl3216Z+S9SsqN1ndHo/TT+W9kmKvXgqOETTYtOrqozHvsfgLQGNRq4LRq1Sr97ne/06lTp8q8/+STT5YJnD788EP99re/lZ+fnxITE+Xr67onWlSkf//+mjdvnoYMGVKj+aV7Pvn5Vf6XaenPl52dXe21SgdWAAAAQH3SspmX/ja1j55bflAWq01mk6GXp/aptd1NlfFyd7MHY5l5hVp7KFnfRCXoh2NpslaweSkpI0/ztsZp3taSd/rIzeijO0e6qch/q1bFrbqinU9S2SN4Jf2f2P0EoKGptcDpgw8+0G9+8xuV9CgPDg5WWlpauQ2yZ8+ereeee04ZGRlatmyZ7r77bpfVNXXqVA0ePFiSlJubq+PHj2vRokVatmyZ7rjjDv373//W5MmTq33fvLw8+2sPD49Kx5bexZWbW3UzQwAAAKAhmTG0g8b2DNWxlGx1DfWrF2HTpQK83HXboHa6bVA7pWbla82B4ifd7TudXuXcIpv06dYiTeozTU/1vFe+Aae1O3Wz08MnSZrefboe6f8IwROAeq9WAqfY2FjNnTtXkjR27Fi99dZbCg8Pl8lU/qNQPTw8NG3aNM2fP19r1651aeAUGBiowMBA+++HDBmiGTNm6NNPP9XMmTN18803a/78+Zo1a1a17uvl9b+/RAsKKn+6RX5+vv21t7d3tdaRqj6Gl5SUpKFDh1b7vgAAAICzhPp71cugqTwh/p6aeXUnzby6k86cz9GK/YlauT+xyifxfXvwrL49KJkMaUCHyboz7HYFtzirZgHZMhnS3uS9VxxCLT66WIuPLubYHYB6r1YCpzfeeEMWi0V9+vTRmjVrqtzxI0kjR47U/PnzFRkZWQsVXu6ee+7RqlWrtGjRIj366KO66aab1KJFC4fn+/v7219XdUzu4sWL9tdVHb8rj7MeWQgAAACgrPYtfDR3TFfNHdNV0WcztSIqUcsiE5SUkVfhHKtN2nvqgvaeuiBJCvFvptHdQzS6x9V68Kbf6VjGAWUWZOrwucM1bj5eeucTu54A1EflbzFyso0bN8owDD322GMOhU2S1LVrV0k1a6LtLDfffLOk4kDou+++q9bc0iFQVU29S39G+jEBAAAA9VN4qwA9dX24fvzjWD08qovK6Q5SrtSsfC3eG6+5X+zT+H/u0wff+yklsb9u6/R7bZi+Qa+Pel1TwqbIkIM3vMTio4s1ZtEY/XXHX5WWm1ajewCAs9XKDqeSwKVfv34OzylppJ2Tk+OSmhwREhJif31po/Oq9OrVy/46Ojq60rGlr/fs2bNa6wAAAACoXYZh6OlJ4bpvRCcdS8mWj7ubDiRkaHNMqn44nqa8wvKfdidJRVabdp04r10nzuu176LVKsBLY8JbanSP3+mhvr/X0fSftenMphodvSs5bje9+3TN6DFD6fnpCgsMY+cTgDpRK4FTSWPw6oRH586dkyQ1a9bMJTU5IiEhwf66ukfdOnfurDZt2igxMVFbtmypdOzWrcWPuGjbtq06depU7ToBAAAA1L7Sfan6d2iue4Z3Ul5hkX46cV6bolO0OSZFJ89V/jPQ2cw8fbnrjL7cdUbuboaGdGqhMT1ma/6Yh3Wh6IiyCrO0N3lvmcbhVSkJniTJkKHbut/GkTsAta5WAqe2bdsqNjZWcXFxGjlypENztm/fLkkKCwtzZWmVWrx4sf113759qzXXMAzdfPPNevfddxUdHa2dO3dq2LBhl43buXOnfYfTzTffXO5T+wAAAAA0DF7ubhrVPUSjuodI6q0TaRe1OSZFm2JStTPunAosFe9+Kiyy6cfj5/Tj8eL/+N6uubfG9OihcT1G6OGrfq+Iw/Oq3fPJJluZnU+XBk95eXlav369du/ercOHDys3N1fe3t7q1auXhgwZovHjx5d5IBIAOMqw2WxX9pxOB/zmN7/RvHnzNHr0aG3cuNH+vslkkmEYOnDgQJkjaBkZGerZs6eSk5P11FNP6e9//7tT64mIiNCMGTMq/cb5xhtv6IknnpBUvFspNjZWbm5u9uubN2/WmDFjJEkzZ85URETEZfc4evSoevXqpaKiIg0ePFhbt24t8xS63NxcXXvttdqzZ4/MZrMOHz6sbt26OelT/k98fLy9N9SZM2doMg4AAADUgZwCi3YcP6dNMSnaFJ2qhPRch+d6mE0aFhakoWE+at48UYcyN1dr11MJQ4aeGPSEbu1wq1599VV98MEHSkuruO9TcHCwHnzwQf3xj39UQEBAtdcDUP+5KjOolcApMjJSgwcPliTNnz9fs2bNklR+4HTu3Dnddttt2rJli9zd3XX06FF17NjRqfV06tRJWVlZmjZtmkaMGKEuXbrIz89PWVlZOnDggD7//HP98MMPkiQPDw+tXr1a48ePL3MPRwInSXrmmWf06quvSpIGDBigp59+Wl26dNHx48f12muv2Z/C98wzz+iVV15x6ucsQeAEAAAA1C82m03HU7O1KTpVm2JStPvkeRUWOf6jWacgHw3r4q8Lbtv1w/mPZZgs1Vo/f1++Tnx8QpYMx+a1b99eH330kcaNG1etdQDUfw06cJKkJ554Qv/+979lGIZuu+02TZs2TTNmzJBhGHr//ffl4+OjH374QV988YUyMzMlSX/5y1/03HPPOb2WTp06OdQEvF27dlqwYIEmTJhw2TVHAyer1aoHH3xQCxYsqHCdBx54QPPmzZPJ5JqHBhI4AQAAAPVbdr5FPxxLKz5+F52qs5l5Ds/1NJsUGnRBqdosN79omTwuODTPZrUp5auzGvpjocb6+amnl5eamUzKsFp1JC9PG7Oz9X1WpkoiKTc3N3388ce66667avAJAdRXDT5wstlsevTRR/Xuu+9W2qeopJzHHntMr7/+uktqiYmJ0erVq/XDDz/o2LFjSk5O1rlz5+Tt7a3Q0FD1799fkydP1q9//Wv5+PiUew9HA6cSa9as0bx587R7926lpaUpODhYQ4YM0UMPPaRJkyY5+yOWQeAEAAAANBw2m00xyVn23U97T11QkdXxH9taN5fahWboYO4iufmclGEUVbaYrj1g1d2bbQq8ePnlhMICPX/2rHb+8gAoNzc3ff/99+x0AhqRBh84lVi3bp1effVVbdmyRVZr2YZ5hmFo2LBheu6551wewjQlBE4AAABAw5WRW6jtsWn25uNp2fkOz3V3K5LNO1puftEy+8XI5J5Z/kCrTRMirZr+w+XBk9Vm00vJyfoqI11S8fG6gwcP0tMJaCQaTeBUIisrS5GRkUpJSVFRUZGCgoLUv39/BQfzqE5nI3ACAAAAGger1abDSZnaFJ2iTTEpijqTrmpsfpLJM0lmvxi5+cXIzfuUDOOSp+ZZbbpno1VTdtsuedum2fFn7DudXNmDFkDtanSBE2oPgRMAAADQOF24WKCtsanaHJOqLUdTdf5igeOTTbky+8YWB1C+R2Vyzyp+v4JjdvEFBbrhRJwsKn56XXx8vDw9PZ36eQDUPldlBman3AUAAAAAUOua+3ro5v5tdXP/tiqy2nQgIUObolO0OSZF++MzKp9s9ZYl6ypZsq6SJBmeiXLzPCv3gP3a0veotvaxltnt1M7DQ9f5+2tNVpbS0tK0fv163Xjjja7+iAAaKNc8Fg0AAAAAUKvcTIb6tw/U4xO665tHR2j3s+P1f9P7qZPpnIpys6qcb8tvI0vmQOXG36fcU3Mkk6FPx5n01o2G0n2Lx4zz87eP3717t6s+CoBGoFZ2ON1///3VnmMYhry8vNSsWTN169ZNw4YNU8+ePV1QHQAAAAA0PiH+npo2qJ0WvrpSW5YslWebHpo1cLyOtumjuMC2lc4tyu0oq8VPJnO2tl7lpq19ins79f3Byz7m0KFDrv4IABqwWgmcIiIiZBjGFd9n8ODBev3113XNNdc4oSoAAAAAaPxyc3Mlm1X5CUd0r1ehmh9dp3NeAdoT2kO7W/bU7lbhKnDzuGSWSdb8UJnM2b/8tni308hmHjJ/ZpYlw1J8XwCoQK0ETh06dJBhGMrJyVFqaqr9fQ8PD7Vo0UKSdOHCBeXnFz/e0zAMBQcHy8vLS5mZmcrIKD57vHv3bo0aNUoff/yx7rrrrtooHQAAAAAaNG9vb/vrDKtVzSUF5WVq4undmnh6t1K9AjTrumdlNbmVmlUkk2dK2RsZhrYNMavHwB46v/m83K3utVI/gIapVno4nTx5UsuWLZO/v788PDz0+OOPKzIyUjk5OUpMTFRiYqIuXryoyMhIPfbYY3J3d5efn5+WLVumCxcu6MyZM3rttdfk7+8vq9Wq2bNn68yZM7VROgAAAAA0aL169bK/PpKXd9n1kLxM/Xb/ErlZiyRJhq1Inq2W/W930yUMN0NB44J0bPwxRRyMcEnNABo+w2az2Vy9SHJysgYMGKDMzEytW7dOw4cPr3T8jh07NH78ePn7+ysyMlKtW7eWJEVGRmrEiBHKy8vTk08+qddee83VpTcKrnrEIQAAAID6b9WqVZoyZYok6Ub/AP2zTZtyx5339NcZ/1C1z0rRD/2y9ekYk2SqujXKw/0e1iP9H3FqzQBqj6syg1rZ4fR///d/Onv2rJ544okqwyZJGj58uJ544gmlpKTon//8p/39AQMG6P7775fNZtO6detcWTIAAAAANArjx49XcHCwJOn7rEwlFBaUO65Ffpb6pR1Xi/wsTdll07y3ijRhr1WGtfI9Cu/uf1fvRL3j9LoBNGy1Ejh98803MgxDEydOdHjO9ddfL0lavXp1mfcnTZokqfiYHgAAAACgcl5eXnrwwQclSRZJz589K6sDB10CL0oPrrXq/beKNH5vkVTJHEInAJeqlcApPj5ekuTp6enwnJKxJXNLtPll+2dOTo6TqgMAAACAxu2Pf/yj/cjMzpwcvZSc7FDoJEkB2TYlfZKkpIVnZatkt9O7+9/Vs9ufVVpumlNqBtCw1Urg5OvrK0nau3evw3P27NkjSfLx8SnzfsmT7EqebgcAAAAAqFxAQIAWLFggN7fiJ9F9lZGu2fFnFF9Q/vG6EvEFBZodf0ZfZaTr3PfnFPuHWA32Hlzh+BXHV2jc4nFacnSJU+sH0PDUSuA0aNAg2Ww2/f3vf9eFCxeqHH/u3Dm9+uqrMgxDgweX/WYWExMjSQoJCXFJrQAAAADQGI0fP14ff/yxPXTamZOjG07E6cnEBH2bmamTBQU6b7HoZEGBvs3M1JOJCbrhRJx2/nK6xM3NTR+99ZE++vVHerjfwxWuY7VZ9dcdf2WnE9DE1Urg9MgjxU8sOHPmjIYNG6bvvvuuwrHffvutrr76ap0+fVqSNHfu3DLXv/vuOxmGoSFDhriuYAAAAABohO666y5999139uN1FklrsrL0h6RE3XAiTiOOH9MNJ+L0h6RErcnKkuWXee3bt9f333+vO++8U5L0SP9HKg+dZNW7Ue+6+NMAqM/MtbHIlClT9PDDD+vdd9/VsWPHdOONNyo4OFj9+/e371RKTU1VVFSU0tL+l4I/9NBDmjx5sv33Z8+e1fLly2Wz2exNxQEAAAAAjhs/frwOHjyoV199VR988EGZn8EuFRwcrAcffFB//OMfFRAQUObaI/2LNxa8u7/8YGnR0UUK8g6yjwPQtBg2m4Od4pzgH//4h1588UXl5eUVL24YZa6XlOLp6akXXnhBf/zjH8tcz8nJUWpqqiSpbdu2MptrJS9r8OLj4+3/BePMmTNq165dHVcEAAAAoD7Iz8/X+vXrtXv3bh06dEi5ubny9vZW7969NWTIEI0fP77Khz99fOhj/WvPvyq8/nC/hwmdgHrMVZlBrQZOkpScnKyPP/5Y69ev18GDB+09nZo3b67evXtr3Lhxmjlzplq3bl2bZTVqBE4AAAAAXOno+aO6beVtsqn8Hy8JnYD6q9EETqh9BE4AAAAAXC3iYIT+b+//VXid0Amon1yVGdRK0/CwsDCFhYXprbfeqo3lAAAAAAC1bFafWZU2En93/7t6J+qdWqwIQF2qlSZI8fHxKioqUv/+/WtjOQAAAABAHaiqkXjJ++x0Ahq/Wtnh1KpVK0mSt7d3bSwHAAAAAKgjj/R/hJ1OAGoncPrVr34lSTp06FBtLAcAAAAAqEOETgBqJXB6+OGHZbPZ9MYbb6iwsLA2lgQAAAAA1CFCJ6Bpq5XAaezYsXrmmWe0f/9+TZ48WWfOnKmNZQEAAAAAdYjQCWi6aqVp+F//+ld5enqqb9++WrduncLCwnTNNdfoqquuUvPmzeXm5lbp/D//+c+1USYAAAAAwMkcaSR+LvecHu7/sIK9g2uzNAAuZNhsNpurFzGZTDIMw/57m81W5vdVKSoqckVZTUZ8fLzat28vSTpz5ozatWtXxxUBAAAAaGreiXqnwtBJkkwy6fFBj2tWn1m1VxQAl2UGtbLDSSoOmSr7PQAAwP9v797jqqry/4+/NyCCmKGesAy8UBHeUlP7auYNxXLMFClmugmmU6nzzdGxqflVajWVTl5mphltSg27aWhaXrrgBUkN85pppqhIYqh5xFtiIrB/f/A9Z0DusM/h9no+Hufx2Jy99tof6izFN2utDQCovUqb6ZSrXM3cMVOZ2ZnOtgBqLrcETrm5ue64DQAAAACgGistdMp/jtAJqNncsmk4AAAAAABSXpA0qeskeZTwz9G5u+fquU3PyX7J7sbKAFiJwAkAAAAA4FbR7aK1LmqdokKiim2z4vAK9V/SXx8nf+zGygBYhcAJAAAAAOB2Nl+bXujxgsZ0HFNsm1wzVy8mvajkjGQ3VgbACgROAAAAAIAqM7bT2BJDJ1OmIldGKnZvrPuKAlBpbg2csrKy9M4772jo0KFq1aqVGjZsKE9PzxJfXl5ue5AeAAAAAKAKlBY6SdLMHTPZ1wmoQdyW5iQnJ2vYsGE6cOCATNN0120BAAAAADXA2E5j5VfPTzO2zyi2zYrDK7Ty8EpN7DJRMe1j3FccgHJzS+B08eJFDRo0SEeOHJGHh4eGDh2q6667Tm+//bYMw9Dzzz+vjIwMbd++Xd98840Mw1CPHj0UHh7ujvIAAAAAANVAdLto9bihh+5feb9MFT1RwZSpmTtmKjM7U2M7jXVzhQDKyi1L6t58800dOXJEnp6eio+P17Jly/TUU085z7/44ot64403lJSUpB07dqhNmzbasmWLmjZtqilTprijRAAAAABANRDSJERTekyRIaPEdnN3z2WJHVCNuSVwWrlypQzDUFRUlMLCwkps27lzZyUkJCggIEATJ07Ujh073FEiAAAAAKCaiAyJ1Pqo9RoSPKTEdisOr1BYXBgbigPVkFsCp3379kmSIiIiijyfm5tb4OvrrrtOEydOVHZ2tv71r3+5vD4AAAAAQPVi87Xp1V6valLXSSW2cyyxY7YTUL24JXA6e/asJKlly5bO9+rXr+88vnjxYqFrevbsKUlKTEx0bXEAAAAAgGorul20EqISyjTbqV9cP72U9BLBE1ANuCVwatCggSTJMP67Btff3995fPTo0WKvPXHihMvqAgAAAABUf47ZTmM6jim17ZLkJQqLC9OMbTMInoAq5JbAqXXr1pKk9PR053s2m01NmjSRJG3evLnQNY69m7y9vd1QIQAAAACguhvbaWypS+ykvGV2C/ctVFhcGDOegCrilsCpa9eukqTt27cXeL9///4yTVOvv/66MjIynO+npKRo2rRpMgxDnTp1ckeJAAAAAIAaoKxL7KS84Mkx44mNxQH3ckvgFB4eLtM0tWLFigLvP/XUU5LyAqaQkBA98MAD+s1vfqNOnTo5Z0M9/vjj7igRAAAAAFBDlHVDcQc2Fgfczy2B07333qvevXvrmmuu0eHDh53v9+zZU5MnT5ZpmsrIyNCyZcv05Zdf6pdffpEkjRw5Ug899JA7SgQAAAAA1DCO2U5RIVEyZJTano3FAfcxTNM0q7qIdevWad68efr++++VnZ2tW265RSNGjFBkZGRVl1YrHDt2TEFBQZKktLQ0BQYGVnFFAAAAAGAt+yW7dp3cpYS0BK1MWVmmax4IeUBjO42Vzdfm4uqA6stVmUG1CJzgWgROAAAAAOqShd8v1IztM8rcfkjwEPVr0U+dAzoTPqHOcVVm4JYldQAAAAAAuEt5NhaXpJUpKzVxw0SW2wEWInACAAAAANQ65d1Y3GFJ8hKCJ8ACVbak7vz587pw4YJycnJKbduiRQs3VFR7saQOAAAAQF1mv2TX3G/nKi45rtzXss8TartasYfTmjVrNGfOHG3atEkZGRllusYwDGVnZ7u4stqNwAkAAAAAKh88/e7W3+ns5bMK9g8mgEKtUeMDp6eeekr//ve/JUnluaVhGGWaBYXiETgBAAAAwH85gqclyUtkqvz/JDZk6P6Q+5n5hFqhRgdOH374oR555BFJko+Pj4YNG6YuXbqoSZMm8vAofRup6OhoV5dYqxE4AQAAAEBh9kt27Tq5SwlpCVqZsrJCfbDkDjVdjQ6c+vTpo40bNyooKEjr16/XTTfd5OpbIh8CJwAAAAAoWWWW20nSkOAh6teinzoHdCZ8Qo1SowOnxo0b6/z583r77bf12GOPufp2uAqBEwAAAACUTWWDJ4nwCTVLjQ6cGjZsqEuXLmn79u3q3Lmzq2+HqxA4AQAAAED5VHafJwfCJ1R3rsoMvCzppRStWrXSDz/8oF9++cUdtwMAAAAAoFJsvja90OMFjek0RrtO7pIM6WDGQc39bm65+lmZstK5PxThE+qS0nfstsDw4cMlSevWrXPH7QAAAAAAsITN16bwVuEKbxmusZ3HKiEqQVEhURXqa2XKSk3cMFH94vrp/238f1rz4xolZyRr6/Gtsl+yW1w5ULXcsqTu3Llz6tSpk86cOaMtW7YoNDTU1bdEPiypAwAAAABrWbXkzsGQoXuD71WXZl3UqH4jZkHBbVyVGbhlhtO1116rL7/8Us2aNdOdd96pOXPm6MyZM+64dbG2b9+ul156SQMHDlRgYKDq16+vhg0bKiQkRCNHjtSmTZssuc/UqVNlGEaZXhs2bLDkngAAAAAA13IsuVsftV6z+szSkOAhMmRUuD9TplamrNTUpKnOWVAvJb3EzCfUWJbOcAoODi7xfGZmpn7++WdnwGKz2dSgQYOSCzQMHT582KoSJUm9e/fWxo0bS203YsQIvf322/L29q7wvaZOnaoXX3yxTG0TEhLUt2/fCt+rOMxwAgAAAADXs1+ya9fJXUpIS9CqlFWWzHySpAdCHtDYTmOZ8QSXqBGbhqemppapnWmaMk1TP//8c6ltDaPiCXFx0tPTJUnNmzfXAw88oF69eqlFixbKyclRUlKSZs6cqZ9++knvvvuurly5og8//NCS++7Zs6fE861bt7bkPgAAAAAA93Pu99QqXBO7TrQsfFqSvERLk5dqYpeJimkfY13BgAtZGjhFR0db2Z3LhIaG6tVXX1VkZKQ8PT0LnOvevbseffRR9ezZU8nJyVq0aJGefPJJ9e7du9L3bd++faX7AAAAAABUf1aHT6ZMzdwxU4ZhKLpdzfi3N+o2SwOnd955x8ruXGbVqlUlnrfZbJo5c6aGDBkiSVq6dKklgRMAAAAAoO4pKnw6n3Vejeo30sGMg3rzuzfLHELN3jFbg4MHs7wO1Z6lgVNt0q9fP+ex1XtIAQAAAADqJkf45BDeMlxRoVHOEGrHyR1ambKy2OtzzBylnE0hcEK155an1NVEly9fdh5fvewOAAAAAACrOEKoyJBIvdrrVSVEJSgqJKrItl6Gl4L9S35gF1AduC1wOnr0qI4ePVogyCnOr7/+6mxfVRITE53Hbdq0saTPgQMHKiAgQN7e3goICFDfvn01bdo0nTlzxpL+AQAAAAA1n83Xphd6vOAMnjyMvH+6GzIUcUtEFVcHlI1bAqf4+Hi1bt1aHTp0UGZmZqntMzMz1a5dOwUHB2vDhg2uL/Aqubm5mjZtmvPrqKiik+XyWrNmjU6dOqUrV67o1KlTSkxM1F/+8hcFBwfr008/rXC/x44dK/F1/PhxS+oHAAAAALiPI3ia2GWiDBkyZWpJ8hKFxYUpdm9sVZcHlMgtezgtWbJEpmlq2LBhaty4cantmzRposjISL377rv66KOP1LdvX9cXmc/s2bO1detWSdLw4cPVpUuXSvXXoUMHDRs2THfccYeaN2+uK1eu6MCBA/rggw8UHx+vs2fPKjIyUitXrtSgQYPK3X9QUFCl6gMAAAAAVE/2S3bN3j67wKbijifWHTx7UBO6TGA/J1RLhmma5X8eYzm1b99eP/zwg9599109/PDDZbpm0aJFevjhh3Xbbbfp22+/dW2B+SQmJmrAgAHKzs5WQECA9uzZo4CAgAr3d/bsWfn7+xd7/j//+Y+efPJJSVLz5s11+PBh+fj4lOsehmGUuW1aWpoCAwPL1T8AAAAAoGpsPb5Vo+JHldjmgZAHNLbTWIInVMixY8ecE1mszAzcsqQuNTVVkhQSElLma26++WZJ0pEjR1xRUpG+//57RUREKDs7Wz4+PlqyZEmlwiZJJYZNkvTEE09o1Ki8PzzS09P18ccfl/seaWlpJb4cs7UAAAAAADVLsH+wPFXyg6xYZofqyC2BU3Z2tqTyPe3N0fbXX391SU1XO3LkiAYOHKgzZ87I09NTixcvVu/evd1y7yeeeMJ5nH+z8rIKDAws8XXDDTdYWS4AAAAAwE0c+zgZKnlli2OZ3Zxv57ipMqBkbgmcbLa8aX0pKSllvsbRtkmTJi6pKb/09HQNGDBA6enpMgxDCxYs0NChQ11+X4e2bds6j3/66Se33RcAAAAAUP1FhkRqfdR6DQkeUmrbubvn6rlNzyk5I1lbj2+V/ZLdDRUChbklcOrUqZMk6aOPPirzNYsXL5aUt/+TK9ntdoWHhzsDrjfeeEMjRoxw6T2vVp49mAAAAAAAdY/N16ZXe72qSV0nldp2xeEVilwZqVHxo9Q/rj9L7VAl3BI4DR06VKZpatmyZVqyZEmp7ePi4rRs2TIZhqFhw4a5rK5z587p7rvv1r59+yRJ06ZN07hx41x2v+I47i/lbRwOAAAAAEBRottFKyEqQVEhUWVqn6tczdwxU89teo7ZTnArtwRO0dHRatWqlUzT1EMPPaRJkyYpLS2tULu0tDRNnDhRDz/8sAzDUFBQkEaPHu2SmjIzMzV48GDt3LlTkvTcc8/pmWeeccm9SvOf//zHedynT58qqQEAAAAAUDM49nVKiEoo0zI7KW/WU7+4fnop6SWCJ7iFWwInb29vLVu2TA0bNlROTo5mz56tVq1aqXXr1rrzzjt15513qnXr1mrVqpX+8Y9/KCcnR35+flq+fLnq169veT1ZWVmKiIjQ5s2bJUnjx4/XX//613L3ExsbK8MwZBiGpk6dWuj8nj17dOjQoRL7eOuttzRv3jxJ0vXXX6+IiIhy1wEAAAAAqHscy+zGdBxT5mt4oh3cxctdN+rUqZO++eYbPfLII9q1a5ck6ccff9TRo0clSaZpOtt26dJF7733nkJDQ11Sy4MPPqj4+HhJUlhYmEaNGqW9e/cW297b21shISHlvs+OHTs0evRo9evXT4MGDVKHDh3UtGlTZWdna//+/frggw+cdXh6euqtt96Sn59fxb4pAAAAAECdNLbTWPnV89PM7TNlyiy1veOJdnvse3RP63vUOaCzbL42N1SKusRtgZMktWnTRjt27NCaNWu0atUq7dq1S3Z73lQ+m82m22+/XUOGDFH//v1dWseyZcucx+vXr9dtt91WYvuWLVsqNTW1QvfKycnR2rVrtXbt2mLbNG3aVPPnz9eQIWWbCgkAAAAAQH7R7aI1OHiwdp3cJRnS7pO7tfCHhSVeE/9jvOJ/jJchQxO7TFRM+xj3FIs6wa2Bk0N4eLjCw8Or4tZu9Zvf/Ebz589XUlKSdu3apZMnT+r06dMyTVNNmjRRx44ddc899ygmJkaNGjWq6nIBAAAAADWYzdem8FZ5/9YObxmu6/yu04ztM0q9jhlPcAXDzL+WDbXSsWPHFBQUJClvY/bAwMAqrggAAAAA4A72S3bN/Xau4pLjynwNM57qFldlBm7ZNLysDh8+rG+++UYnT56s6lIAAAAAAKjxKvJEO8eMpz9t+JPW/LiGp9qhQtwSOP3888+aM2eO5syZo3PnzhU6f+jQIXXp0kUhISG68847deONNyoyMlJnzpxxR3kAAAAAANRqjifaTeo6SYaMMl0T/2O8Jm6YyFPtUCFuWVL35ptvauzYsbrlllt04MCBAucuX76s9u3bKyUlpcCT6gzDUM+ePfXVV1+5urxajyV1AAAAAAAH+yW7dp3cpc+PfK41R9eU+br7brpPE7pMYH+nWqZGL6mLj4+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+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1200x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# testing on data\n",
+    "tested_cell = [test_cells[15]]\n",
+    "# X_train_tested_cell = [x for xs in train_cells for x in xs[0]]\n",
+    "# Y_train = np.array([x for xs in train_cells for x in xs[1]])\n",
+    "# Y_train_tested_cell = [x for xs in train_cells for x in xs[1]]\n",
+    "X_tested_cell = [x for cycle in tested_cell for x in cycle[0]]\n",
+    "# Y_test = [x for xs in test_cells for x in xs[1]]\n",
+    "Y_tested_cell = [y for cycle in tested_cell for y in cycle[1]]\n",
+    "dc_tested_cell, slopes_tested_cell = make_label_arrays(Y_tested_cell)\n",
+    "X_tested_cell_time_series, X_tested_cell_dt = make_feature_arrays(X_tested_cell)\n",
+    "\n",
+    "scaled_X_tested_cell_dt = standardize_non_train(X_tested_cell_dt, mean_X_train_dt, std_X_train_dt)\n",
+    "scaled_X_tested_cell_time_series = standardize_non_train(X_tested_cell_time_series, mean_X_train_time_series, std_X_train_time_series)[...,1:]\n",
+    "\n",
+    "# std_X_tested_cell_time_series = standardize(X_tested_cell_time_series[...,1:])\n",
+    "all_test_slopes = [y[0] for y in Y_tested_cell]\n",
+    "all_test_dc = np.array([y[1] for y in Y_tested_cell])\n",
+    "Y_hat_tested_cell = model.predict([scaled_X_tested_cell_time_series, scaled_X_tested_cell_dt])\n",
+    "\n",
+    "# initial_dc = all_test_dc.reshape([-1, 2])[cycle_indices[0]]\n",
+    "# index_0 = initial_dc[0]\n",
+    "# for i,m in enumerate(all_test_dc.reshape([-1,2])):\n",
+    "#     plt.scatter(*list(zip(*all_test_dc.reshape([-1,2]))), color = 'C2', s=2, label='Ground-truth' if i == 0 else \"\")\n",
+    "\n",
+    "window_size = 100\n",
+    "scatters = []\n",
+    "for i,m in enumerate(all_test_dc[1:]):\n",
+    "    plt.figure(dpi=200, facecolor='white')\n",
+    "#     print(m[0,0], m[5,0], m[9,0])\n",
+    "    plt.scatter(*list(zip(*all_test_dc.reshape([-1,2]))), color = 'C2', s=1, label='Ground-truth') #if i == 0 else \"\")\n",
+    "#     if i == 0:\n",
+    "#         initial_dc = m[0]\n",
+    "    initial_dc = m[0]\n",
+    "#     print(m)\n",
+    "#     print(m)\n",
+    "#     break\n",
+    "    predicted_dc_values = [initial_dc]\n",
+    "#     print(initial_dc)\n",
+    "#     if i%2 == 0:\n",
+    "    new_cycle_index = m[0,0]\n",
+    "#         print(f'hi {i}')\n",
+    "    for j,slope in enumerate(Y_hat_tested_cell[i]):\n",
+    "        new_cycle_index += window_size//2\n",
+    "        new_predicted_dc = linear_fit(new_cycle_index, -np.exp(-slope), initial_dc)\n",
+    "        print(f'slope: {-np.exp(-slope)}')\n",
+    "        predicted_dc_values.append(np.array([new_cycle_index , new_predicted_dc]))\n",
+    "        initial_dc = predicted_dc_values[-1]\n",
+    "#         print(initial_dc)\n",
+    "      # \n",
+    "    print(predicted_dc_values)\n",
+    "#     initial_dc = np.array([new_cycle_index, new_predicted_dc]) \n",
+    "    \n",
+    "#     print(i)\n",
+    "#     print(predicted_dc_values)\n",
+    "#     initial_dc = predicted_dc_values[-1]\n",
+    "    \n",
+    "#     if i==2 or i==1:\n",
+    "#         print(m)\n",
+    "#         break\n",
+    "#     if i ==2:\n",
+    "#         break\n",
+    "    scatters.append(predicted_dc_values)\n",
+    "#     print(np.array(scatters).T)\n",
+    "    plt.plot(*np.array(scatters).T, color='C0', label='Inferred', #if i == 0 else \"\",\n",
+    "             marker='o', markersize=1)\n",
+    "    plt.scatter(*np.array(predicted_dc_values[-1]).T, c='C3', #if i == 0 else \"\",\n",
+    "         marker='o', s=50, edgecolor='k', linewidth=1, facecolor='C3', zorder=-1)\n",
+    "    plt.xlabel('Cycles')\n",
+    "    plt.ylabel('Discharge Capacity')\n",
+    "    plt.ylim([1,5])\n",
+    "    ax = plt.gca()\n",
+    "    hand, labl = ax.get_legend_handles_labels()\n",
+    "    plt.legend(np.unique(labl))\n",
+    "    plt.tight_layout()\n",
+    "#     plt.savefig(f'img/discharge_curve_100_window_{i:04d}.png', dpi=200, transparent=False)\n",
+    "#     if i ==20:\n",
+    "        \n",
+    "#         break\n",
+    "#     plt.close()\n",
+    "#     break\n",
+    "#     break\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "316330e5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# window_size = 40\n",
+    "# scatters = []\n",
+    "# for i,m in enumerate(all_test_dc[1:]):\n",
+    "#     plt.figure(dpi=200, facecolor='white')\n",
+    "# #     print(m[0,0], m[5,0], m[9,0])\n",
+    "#     plt.scatter(*list(zip(*all_test_dc.reshape([-1,2]))), color = 'C2', s=1, label='Ground-truth') #if i == 0 else \"\")\n",
+    "#     if i == 0:\n",
+    "#         initial_dc = m[0]\n",
+    "        \n",
+    "# #     print(m)\n",
+    "# #     print(m)\n",
+    "#     predicted_dc_values = [initial_dc]\n",
+    "# #     print(initial_dc)\n",
+    "#     if i%2 == 0:\n",
+    "#         new_cycle_index = m[19,0]\n",
+    "# #         print(f'hi {i}')\n",
+    "#     else: \n",
+    "#         new_cycle_index = m[-1,0]\n",
+    "#     for j,slope in enumerate(Y_hat_tested_cell[i]):\n",
+    "#         if j == 0:\n",
+    "#             new_cycle_index = m[19,0]\n",
+    "#         else:\n",
+    "#             new_cycle_index = m[39,0]\n",
+    "#         new_predicted_dc = linear_fit(new_cycle_index, -np.exp(-slope), initial_dc)\n",
+    "#         predicted_dc_values.append(np.array([new_cycle_index , new_predicted_dc]))\n",
+    "#         initial_dc = predicted_dc_values[-1]\n",
+    "# #         print(initial_dc)\n",
+    "#       # \n",
+    "#     print(predicted_dc_values)\n",
+    "# #     initial_dc = np.array([new_cycle_index, new_predicted_dc]) \n",
+    "    \n",
+    "# #     print(i)\n",
+    "# #     print(predicted_dc_values)\n",
+    "#     initial_dc = predicted_dc_values[-1]\n",
+    "# #     if i==2 or i==1:\n",
+    "# #         print(m)\n",
+    "# #         break\n",
+    "# #     if i ==2:\n",
+    "# #         break\n",
+    "#     scatters.append(predicted_dc_values)\n",
+    "# #     print(np.array(scatters).T)\n",
+    "#     plt.plot(*np.array(scatters).T, color='C0', label='Inferred', #if i == 0 else \"\",\n",
+    "#              marker='o', markersize=1)\n",
+    "#     plt.scatter(*np.array(predicted_dc_values[-1]).T, c='C3', #if i == 0 else \"\",\n",
+    "#          marker='o', s=50, edgecolor='k', linewidth=1, facecolor='C3', zorder=-1)\n",
+    "#     plt.xlabel('Cycles')\n",
+    "#     plt.ylabel('Discharge Capacity')\n",
+    "#     plt.ylim([1,4])\n",
+    "#     ax = plt.gca()\n",
+    "#     hand, labl = ax.get_legend_handles_labels()\n",
+    "#     plt.legend(np.unique(labl))\n",
+    "#     plt.tight_layout()\n",
+    "# #     plt.savefig(f'img/discharge_curve_{i:04d}.png', dpi=200, transparent=False)\n",
+    "# #     if i ==20:\n",
+    "        \n",
+    "# #         break\n",
+    "# #     plt.close()\n",
+    "# #     break\n",
+    "# #     break"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 287,
+   "id": "c24ab24e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[1245.   ,    2.199],\n",
+       "       [1246.   ,    2.195],\n",
+       "       [1247.   ,    2.191],\n",
+       "       [1248.   ,    2.187],\n",
+       "       [1249.   ,    2.183],\n",
+       "       [1250.   ,    2.179],\n",
+       "       [1251.   ,    2.175],\n",
+       "       [1252.   ,    2.172],\n",
+       "       [1253.   ,    2.167],\n",
+       "       [1254.   ,    2.164]])"
+      ]
+     },
+     "execution_count": 287,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "m"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 288,
+   "id": "48efc661",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# obtain initial dc value from GT\n",
+    "window_size = 10\n",
+    "scatters = []\n",
+    "for i,m in enumerate(all_test_dc[1:]):\n",
+    "    plt.figure(dpi=200, facecolor='white')\n",
+    "#     print(m[0,0], m[5,0], m[9,0])\n",
+    "    plt.scatter(*list(zip(*all_test_dc.reshape([-1,2]))), color = 'C2', s=1, label='Ground-truth') #if i == 0 else \"\")\n",
+    "#     if i == 0:\n",
+    "    initial_dc = m[0]\n",
+    "#     print(m)\n",
+    "#     print(m)\n",
+    "    predicted_dc_values = [initial_dc]\n",
+    "#     print(initial_dc)\n",
+    "    if i%2 == 0:\n",
+    "        new_cycle_index = m[5,0]\n",
+    "#         print(f'hi {i}')\n",
+    "    else: \n",
+    "        new_cycle_index = m[-1,0]\n",
+    "    for j,slope in enumerate(Y_hat_tested_cell[i]):\n",
+    "        if j == 0:\n",
+    "            new_cycle_index = m[5,0]\n",
+    "        else:\n",
+    "            new_cycle_index = m[9,0]\n",
+    "        new_predicted_dc = linear_fit(new_cycle_index, slope, initial_dc)\n",
+    "        predicted_dc_values.append(np.array([new_cycle_index , new_predicted_dc]))\n",
+    "#         initial_dc = predicted_dc_values[-1]\n",
+    "      # \n",
+    "#     initial_dc = np.array([new_cycle_index, new_predicted_dc]) \n",
+    "    \n",
+    "#     print(i)\n",
+    "#     print(predicted_dc_values)\n",
+    "    initial_dc = predicted_dc_values[-1]\n",
+    "#     if i==2 or i==1:\n",
+    "#         print(m)\n",
+    "#         break\n",
+    "#     if i ==2:\n",
+    "#         break\n",
+    "    scatters.append(predicted_dc_values)\n",
+    "#     print(np.array(scatters).T)\n",
+    "    plt.plot(*np.array(scatters).T, color='C0', label='Inferred', #if i == 0 else \"\",\n",
+    "             marker='o', markersize=1)\n",
+    "    plt.scatter(*np.array(predicted_dc_values[-1]).T, c='C3', #if i == 0 else \"\",\n",
+    "         marker='o', s=50, edgecolor='k', linewidth=1, facecolor='C3', zorder=-1)\n",
+    "    plt.xlabel('Cycles')\n",
+    "    plt.ylabel('Discharge Capacity')\n",
+    "    plt.ylim([1,4])\n",
+    "    ax = plt.gca()\n",
+    "    hand, labl = ax.get_legend_handles_labels()\n",
+    "    plt.legend(np.unique(labl))\n",
+    "    plt.tight_layout()\n",
+    "    plt.savefig(f'img/discharge_curve_initial_dc_from_GT_{i:04d}.png', dpi=200, transparent=False)\n",
+    "#     if i ==20:\n",
+    "        \n",
+    "#         break\n",
+    "    plt.close()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d7b2952e",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 137,
+   "id": "97bede2e",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "-0.0020526012\n",
+      "[array([9.   , 3.968]), array([11.   ,  3.964])]\n",
+      "-0.0016694856\n",
+      "[array([11.   ,  3.964]), array([13.  ,  3.96])]\n",
+      "-0.0020041084\n",
+      "[array([13.  ,  3.96]), array([15.   ,  3.956])]\n",
+      "-0.0016058914\n",
+      "[array([15.   ,  3.956]), array([17.   ,  3.953])]\n",
+      "-0.0020050171\n",
+      "[array([17.   ,  3.953]), array([19.   ,  3.949])]\n",
+      "-0.0016071951\n",
+      "[array([19.   ,  3.949]), array([21.   ,  3.946])]\n",
+      "-0.0020037354\n",
+      "[array([21.   ,  3.946]), array([23.   ,  3.942])]\n",
+      "-0.0016053959\n",
+      "[array([23.   ,  3.942]), array([25.   ,  3.939])]\n",
+      "-0.0020038148\n",
+      "[array([25.   ,  3.939]), array([27.   ,  3.935])]\n",
+      "-0.0016055123\n",
+      "[array([27.   ,  3.935]), array([29.   ,  3.932])]\n",
+      "-0.0020033927\n",
+      "[array([29.   ,  3.932]), array([31.   ,  3.928])]\n",
+      "-0.0016049109\n",
+      "[array([31.   ,  3.928]), array([33.   ,  3.924])]\n",
+      "-0.0020021512\n",
+      "[array([33.   ,  3.924]), array([35.  ,  3.92])]\n",
+      "-0.0016034532\n",
+      "[array([35.  ,  3.92]), array([37.   ,  3.917])]\n",
+      "-0.0020040404\n",
+      "[array([37.   ,  3.917]), array([39.   ,  3.913])]\n",
+      "-0.0016057711\n",
+      "[array([39.   ,  3.913]), array([41.  ,  3.91])]\n",
+      "-0.002002531\n",
+      "[array([41.  ,  3.91]), array([43.   ,  3.906])]\n",
+      "-0.0016036653\n",
+      "[array([43.   ,  3.906]), array([45.   ,  3.903])]\n",
+      "-0.00200082\n",
+      "[array([45.   ,  3.903]), array([47.   ,  3.899])]\n",
+      "-0.0016014037\n",
+      "[array([47.   ,  3.899]), array([49.   ,  3.896])]\n",
+      "-0.0019991626\n",
+      "[array([49.   ,  3.896]), array([51.   ,  3.892])]\n",
+      "-0.0015990222\n",
+      "[array([51.   ,  3.892]), array([53.   ,  3.888])]\n",
+      "-0.0019965407\n",
+      "[array([53.   ,  3.888]), array([55.   ,  3.884])]\n",
+      "-0.001595309\n",
+      "[array([55.   ,  3.884]), array([57.   ,  3.881])]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "Text(0, 0.5, 'Discharge Capacity')"
+      ]
+     },
+     "execution_count": 137,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 900x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "\n",
+    "for i,slope in enumerate(Y_hat_tested_cell.flatten()):\n",
+    "    print(slope)\n",
+    "#     print(cycle_indices[i], cycle_indices[i+1])\n",
+    "    predicted_dc_values = [initial_dc]\n",
+    "    new_cycle_index = index_0 + cycle_window//2*(i+1)\n",
+    "#     new_predicted_dc = linear_fit(cycle_indices[i+1], slope, predicted_dc_values[0])\n",
+    "    new_predicted_dc = linear_fit(new_cycle_index, slope, predicted_dc_values[0]) \n",
+    "    predicted_dc_values.append(np.array([new_cycle_index , new_predicted_dc]))\n",
+    "    initial_dc = np.array([new_cycle_index, new_predicted_dc]) \n",
+    "    plt.plot(*np.array(predicted_dc_values).T, color='C0')\n",
+    "#         break\n",
+    "    print(predicted_dc_values)\n",
+    "    \n",
+    "#     print(predicted_dc_values)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 140,
+   "id": "fa695326",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([20.   ,  3.907])"
+      ]
+     },
+     "execution_count": 140,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.array(predicted_dc_values)[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 128,
+   "id": "297017d5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([20.   ,  3.907])"
+      ]
+     },
+     "execution_count": 128,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "predicted_dc[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "id": "2ef48f46",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.PathCollection at 0x7fa132368bb0>"
+      ]
+     },
+     "execution_count": 63,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.scatter(*all_test_dc)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "id": "82fa0909",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "4"
+      ]
+     },
+     "execution_count": 52,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "X_test = [x for xs in test_cells for x in xs[0]]\n",
+    "# Y_test= np.array([x for xs in test_cells for x in xs[1]])\n",
+    "Y_test = [x for xs in test_cells for x in xs[1]]\n",
+    "dc_test, slopes_test = make_label_arrays(Y_test)\n",
+    "X_test_time_series, X_test_dt = make_feature_arrays(X_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "id": "05a6e465",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[(-0.07988863284999996, -0.007702071219999995),\n",
+       " array([[ 0.   ,  4.74 ],\n",
+       "        [ 6.   ,  3.981],\n",
+       "        [ 7.   ,  3.974],\n",
+       "        [ 8.   ,  3.971],\n",
+       "        [ 9.   ,  3.968],\n",
+       "        [10.   ,  3.966],\n",
+       "        [11.   ,  3.961],\n",
+       "        [12.   ,  3.956],\n",
+       "        [13.   ,  3.952],\n",
+       "        [14.   ,  3.947],\n",
+       "        [15.   ,  3.941],\n",
+       "        [16.   ,  3.937],\n",
+       "        [17.   ,  3.931],\n",
+       "        [18.   ,  3.925],\n",
+       "        [19.   ,  3.915],\n",
+       "        [20.   ,  3.907],\n",
+       "        [21.   ,  3.899],\n",
+       "        [22.   ,  3.889],\n",
+       "        [23.   ,  3.877],\n",
+       "        [24.   ,  3.864]])]"
+      ]
+     },
+     "execution_count": 53,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "X_train_tested_cell[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3659e867",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "# X_train = [d[0] for d in train_data]\n",
+    "# y_train = [d[1]for d in train_data]\n",
+    "# Now flatten nested lists\n",
+    "# train_time_series_features = [(x[0],x[1]) for xs in train_cells for (x[0],x[1]) in xs]\n",
+    "train_time_values = [x for xs in train_cells for x in xs]\n",
+    "# y_train = [(x,y) for ys in train_cells for (x,y) in ys]\n",
+    "\n",
+    "# X_val = [x for xs in val_cells for x in xs[0]]\n",
+    "# y_val = [y for ys in val_data for y in ys[1]]\n",
+    "\n",
+    "# X_test = [x for xs in test_cells for x in xs[0]]\n",
+    "# y_test = [y for ys in test_data for y in ys[1]]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 274,
+   "id": "3d254220",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "features_list = []\n",
+    "labels_list = []\n",
+    "for cell in train_cells:\n",
+    "    f = cell[0]\n",
+    "#     features_list.append(cell[0])\n",
+    "#     labels_list.append(cell[1])\n",
+    "    l = cell[1]\n",
+    "    break"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "00169b49",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "99e409db",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5f9dd67c",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 229,
+   "id": "11f2b9f4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# need to fix not including diagnostic in window\n",
+    "def find_renumbedred_index(cell):\n",
+    "    '''This function finds the renumbered index for the cycles that are followed by a diagnostic cycle'''\n",
+    "    renumbered_index_for_cycle_following_a_diagnostic_cycle = []\n",
+    "    i = 0\n",
+    "    for k,cycle in enumerate(cell):\n",
+    "        actual_cycle_index = np.unique(cycle['cycle_index'])[0]\n",
+    "#         print(i, actual_cycle_index)\n",
+    "        if actual_cycle_index != i:\n",
+    "            renumbered_index_for_cycle_following_a_diagnostic_cycle.append(k-1)\n",
+    "            i = actual_cycle_index\n",
+    "        i += 1\n",
+    "#     print(i, actual_cycle_index)\n",
+    "    return renumbered_index_for_cycle_following_a_diagnostic_cycle\n",
+    "\n",
+    "\n",
+    "def index_convoluter(cell, cycle_window_size=20, overlap_cycle_window=False,\n",
+    "                     overlap_size=5, skip_diagnistic_in_window=False):\n",
+    "    '''This function generates a nested list of indices by convolting the cycles based on cycle_window_size. \n",
+    "        You can choose to have your window of cycles overlap, or skipp the windows that involve diagnostic cycles in between.\n",
+    "    '''\n",
+    "    max_cycle_index = len(cell) #30 #\n",
+    "    if cycle_window_size < overlap_size:\n",
+    "        raise ValueError(f'If overlapping, overlap_size ({overlap_size}) should be samller than cycle_window_size ({cycle_window_size}). Please check inputs.')\n",
+    "    if not cycle_window_size < max_cycle_index:\n",
+    "        raise ValueError(f'cycle_window_size ({cycle_window_size}) should be samller than maximum number of cycles in cell ({max_cycle_index}). Please check inputs.')\n",
+    "    if overlap_cycle_window:\n",
+    "        non_overlap =  cycle_window_size - overlap_size\n",
+    "    else:\n",
+    "        non_overlap = cycle_window_size\n",
+    "    intervals = range(0, max_cycle_index, non_overlap)\n",
+    "    if not skip_diagnistic_in_window:\n",
+    "        index_covolutions = [list(range(x, x + cycle_window_size)) for x in intervals if x <= max_cycle_index-cycle_window_size]\n",
+    "    else:\n",
+    "#         skipped_indices = [5, 6, 7, 20]\n",
+    "        skipped_indices = find_renumbedred_index(cell)\n",
+    "        print(skipped_indices)\n",
+    "        index_covolutions = [list(range(x, x + cycle_window_size)) for x in intervals if x <= max_cycle_index-cycle_window_size]\n",
+    "                             and not (set(list(range(x, x + cycle_window_size))[:-1]) & set(skipped_indices))]\n",
+    "    return index_covolutions"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6da24cf1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 283,
+   "id": "01777e2b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([[ 0.   ,  2.701, -0.691],\n",
+       "        [ 0.   ,  2.716, -0.692],\n",
+       "        [ 0.   ,  2.731, -0.691],\n",
+       "        [ 0.   ,  2.746, -0.692],\n",
+       "        [ 0.   ,  2.76 , -0.692],\n",
+       "        [ 0.   ,  2.775, -0.692],\n",
+       "        [ 0.   ,  2.79 , -0.692],\n",
+       "        [ 0.   ,  2.805, -0.692],\n",
+       "        [ 0.   ,  2.82 , -0.692],\n",
+       "        [ 0.   ,  2.835, -0.692],\n",
+       "        [ 0.   ,  2.85 , -0.692],\n",
+       "        [ 0.   ,  2.865, -0.692],\n",
+       "        [ 0.   ,  2.88 , -0.691],\n",
+       "        [ 0.   ,  2.895, -0.691],\n",
+       "        [ 0.   ,  2.91 , -0.692],\n",
+       "        [ 0.   ,  2.925, -0.691],\n",
+       "        [ 0.   ,  2.94 , -0.692],\n",
+       "        [ 0.   ,  2.954, -0.692],\n",
+       "        [ 0.   ,  2.969, -0.692],\n",
+       "        [ 0.   ,  2.984, -0.692],\n",
+       "        [ 0.   ,  2.999, -0.692],\n",
+       "        [ 0.   ,  3.014, -0.691],\n",
+       "        [ 0.   ,  3.029, -0.692],\n",
+       "        [ 0.   ,  3.044, -0.692],\n",
+       "        [ 0.   ,  3.059, -0.692],\n",
+       "        [ 0.   ,  3.074, -0.691],\n",
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+       " 869)"
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+     },
+     "execution_count": 283,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "f[0][0][0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 266,
+   "id": "faf9954d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "          [24.   ,  3.239, -0.968],\n",
+       "          [24.   ,  3.253, -0.968],\n",
+       "          [24.   ,  3.268, -0.968],\n",
+       "          [24.   ,  3.282, -0.968],\n",
+       "          [24.   ,  3.297, -0.968],\n",
+       "          [24.   ,  3.312, -0.968],\n",
+       "          [24.   ,  3.326, -0.968],\n",
+       "          [24.   ,  3.341, -0.968],\n",
+       "          [24.   ,  3.355, -0.968],\n",
+       "          [24.   ,  3.37 , -0.968],\n",
+       "          [24.   ,  3.384, -0.968],\n",
+       "          [24.   ,  3.399, -0.967],\n",
+       "          [24.   ,  3.413, -0.968],\n",
+       "          [24.   ,  3.428, -0.968],\n",
+       "          [24.   ,  3.442, -0.968],\n",
+       "          [24.   ,  3.457, -0.968],\n",
+       "          [24.   ,  3.472, -0.968],\n",
+       "          [24.   ,  3.486, -0.968],\n",
+       "          [24.   ,  3.501, -0.968],\n",
+       "          [24.   ,  3.515, -0.968],\n",
+       "          [24.   ,  3.53 , -0.968],\n",
+       "          [24.   ,  3.544, -0.968],\n",
+       "          [24.   ,  3.559, -0.968],\n",
+       "          [24.   ,  3.573, -0.968],\n",
+       "          [24.   ,  3.588, -0.968],\n",
+       "          [24.   ,  3.602, -0.968],\n",
+       "          [24.   ,  3.617, -0.968],\n",
+       "          [24.   ,  3.631, -0.968],\n",
+       "          [24.   ,  3.646, -0.968],\n",
+       "          [24.   ,  3.661, -0.968],\n",
+       "          [24.   ,  3.675, -0.968],\n",
+       "          [24.   ,  3.69 , -0.968],\n",
+       "          [24.   ,  3.704, -0.968],\n",
+       "          [24.   ,  3.719, -0.968],\n",
+       "          [24.   ,  3.733, -0.968],\n",
+       "          [24.   ,  3.748, -0.968],\n",
+       "          [24.   ,  3.762, -0.968],\n",
+       "          [24.   ,  3.777, -0.968],\n",
+       "          [24.   ,  3.791, -0.968],\n",
+       "          [24.   ,  3.806, -0.968],\n",
+       "          [24.   ,  3.821, -0.968],\n",
+       "          [24.   ,  3.835, -0.968],\n",
+       "          [24.   ,  3.85 , -0.968],\n",
+       "          [24.   ,  3.864, -0.968],\n",
+       "          [24.   ,  3.879, -0.968],\n",
+       "          [24.   ,  3.893, -0.968],\n",
+       "          [24.   ,  3.908, -0.968],\n",
+       "          [24.   ,  3.922, -0.968],\n",
+       "          [24.   ,  3.937, -0.968],\n",
+       "          [24.   ,  3.951, -0.968],\n",
+       "          [24.   ,  3.966, -0.968],\n",
+       "          [24.   ,  3.98 , -0.968],\n",
+       "          [24.   ,  3.995, -0.968],\n",
+       "          [24.   ,  4.01 , -0.968],\n",
+       "          [24.   ,  4.024, -0.968],\n",
+       "          [24.   ,  4.039, -0.968],\n",
+       "          [24.   ,  4.053, -0.968],\n",
+       "          [24.   ,  4.068, -0.968],\n",
+       "          [24.   ,  4.082, -0.968],\n",
+       "          [24.   ,  4.097, -0.968],\n",
+       "          [24.   ,  4.111, -0.968],\n",
+       "          [24.   ,  4.126, -0.968],\n",
+       "          [24.   ,  4.14 , -0.973]]),\n",
+       "   847),)]"
+      ]
+     },
+     "execution_count": 266,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_time_values[0][0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 262,
+   "id": "5d280564",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "20"
+      ]
+     },
+     "execution_count": 262,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(cell_features[0][0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 250,
+   "id": "9513a524",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "544"
+      ]
+     },
+     "execution_count": 250,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(train_time_values)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 244,
+   "id": "b6145088",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "X_train = [d[0] for d in train_data]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 245,
+   "id": "27dda858",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "272"
+      ]
+     },
+     "execution_count": 245,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(X_train)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 178,
+   "id": "f84152c1",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "27\n"
+     ]
+    }
+   ],
+   "source": [
+    "labels = []\n",
+    "time_series_features = []\n",
+    "time_value_features = []\n",
+    "for d in train_cells:\n",
+    "#     x , y = (d[0][0], d[0][1]), d[1]\n",
+    "#     print(d[0][0])\n",
+    "    time_series_f = d[0][0]\n",
+    "    time_values_f = d[0][1]\n",
+    "    slope_values = d[1]\n",
+    "    print(len(slope_values))\n",
+    "    labels.append(slope_values)\n",
+    "    time_series_features.append(time_series_f)\n",
+    "    time_value_features.append(slope_values)\n",
+    "#     print(d[1])\n",
+    "    break"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 107,
+   "id": "10c7a476",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "X_train = [(d[0][0], d[0][1]) for d in train_cells]\n",
+    "y_train = [d[1]for d in train_cells]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 134,
+   "id": "611372c3",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "72"
+      ]
+     },
+     "execution_count": 134,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(train_cells[2][1])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 167,
+   "id": "9f20d8d2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([[540.   ,   2.701,  -0.968],\n",
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+       "        [540.   ,   4.096,  -0.972]]),\n",
+       " array([[541.   ,   2.701,  -0.968],\n",
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+       "        [559.   ,   3.948,  -0.968],\n",
+       "        [559.   ,   3.962,  -0.968],\n",
+       "        [559.   ,   3.976,  -0.968],\n",
+       "        [559.   ,   3.99 ,  -0.968],\n",
+       "        [559.   ,   4.004,  -0.968],\n",
+       "        [559.   ,   4.018,  -0.968],\n",
+       "        [559.   ,   4.032,  -0.968],\n",
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+       "        [559.   ,   4.06 ,  -0.968],\n",
+       "        [559.   ,   4.074,  -0.968],\n",
+       "        [559.   ,   4.088,  -0.974]]))"
+      ]
+     },
+     "execution_count": 167,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "time_series_f"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 153,
+   "id": "3c8c2c42",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(1, 20, 100, 3)"
+      ]
+     },
+     "execution_count": 153,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.array(time_series_features).shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 155,
+   "id": "569e6160",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
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+       "          [132.   ,   3.988,  -0.973]]),\n",
+       "   array([[133.   ,   2.702,  -0.968],\n",
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+       "          [133.   ,   3.988,  -0.971]]),\n",
+       "   array([[134.   ,   2.702,  -0.968],\n",
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+       "          [134.   ,   2.87 ,  -0.968],\n",
+       "          [134.   ,   2.883,  -0.968],\n",
+       "          [134.   ,   2.896,  -0.968],\n",
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+       "          [134.   ,   3.13 ,  -0.968],\n",
+       "          [134.   ,   3.143,  -0.968],\n",
+       "          [134.   ,   3.156,  -0.968],\n",
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+       "          [134.   ,   3.195,  -0.968],\n",
+       "          [134.   ,   3.208,  -0.968],\n",
+       "          [134.   ,   3.221,  -0.968],\n",
+       "          [134.   ,   3.234,  -0.968],\n",
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+       "          [134.   ,   3.26 ,  -0.968],\n",
+       "          [134.   ,   3.273,  -0.968],\n",
+       "          [134.   ,   3.286,  -0.968],\n",
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+       "          [134.   ,   3.403,  -0.968],\n",
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+       "          [134.   ,   3.585,  -0.968],\n",
+       "          [134.   ,   3.598,  -0.968],\n",
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+       "          [134.   ,   3.637,  -0.968],\n",
+       "          [134.   ,   3.65 ,  -0.968],\n",
+       "          [134.   ,   3.663,  -0.968],\n",
+       "          [134.   ,   3.676,  -0.968],\n",
+       "          [134.   ,   3.689,  -0.968],\n",
+       "          [134.   ,   3.702,  -0.968],\n",
+       "          [134.   ,   3.715,  -0.968],\n",
+       "          [134.   ,   3.728,  -0.968],\n",
+       "          [134.   ,   3.741,  -0.968],\n",
+       "          [134.   ,   3.754,  -0.968],\n",
+       "          [134.   ,   3.767,  -0.968],\n",
+       "          [134.   ,   3.78 ,  -0.968],\n",
+       "          [134.   ,   3.793,  -0.968],\n",
+       "          [134.   ,   3.806,  -0.968],\n",
+       "          [134.   ,   3.819,  -0.968],\n",
+       "          [134.   ,   3.832,  -0.968],\n",
+       "          [134.   ,   3.845,  -0.968],\n",
+       "          [134.   ,   3.858,  -0.968],\n",
+       "          [134.   ,   3.871,  -0.968],\n",
+       "          [134.   ,   3.884,  -0.968],\n",
+       "          [134.   ,   3.897,  -0.968],\n",
+       "          [134.   ,   3.91 ,  -0.968],\n",
+       "          [134.   ,   3.923,  -0.968],\n",
+       "          [134.   ,   3.936,  -0.968],\n",
+       "          [134.   ,   3.949,  -0.968],\n",
+       "          [134.   ,   3.962,  -0.968],\n",
+       "          [134.   ,   3.975,  -0.968],\n",
+       "          [134.   ,   3.988,  -0.973]])),\n",
+       "  (862,\n",
+       "   861,\n",
+       "   860,\n",
+       "   859,\n",
+       "   856,\n",
+       "   841,\n",
+       "   837,\n",
+       "   854,\n",
+       "   859,\n",
+       "   859,\n",
+       "   858,\n",
+       "   857,\n",
+       "   857,\n",
+       "   856,\n",
+       "   858,\n",
+       "   858,\n",
+       "   858,\n",
+       "   858,\n",
+       "   858,\n",
+       "   858)]]"
+      ]
+     },
+     "execution_count": 155,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "labels"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "id": "25e57c0d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[(array([[540.   ,   2.701,  -0.968],\n",
+      "       [540.   ,   2.715,  -0.968],\n",
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+      "       [540.   ,   2.757,  -0.968],\n",
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+      "       [559.   ,   3.962,  -0.968],\n",
+      "       [559.   ,   3.976,  -0.968],\n",
+      "       [559.   ,   3.99 ,  -0.968],\n",
+      "       [559.   ,   4.004,  -0.968],\n",
+      "       [559.   ,   4.018,  -0.968],\n",
+      "       [559.   ,   4.032,  -0.968],\n",
+      "       [559.   ,   4.046,  -0.968],\n",
+      "       [559.   ,   4.06 ,  -0.968],\n",
+      "       [559.   ,   4.074,  -0.968],\n",
+      "       [559.   ,   4.088,  -0.974]])), (821, 821, 821, 821, 820, 819, 819, 818, 818, 818, 818, 818, 818, 817, 817, 816, 817, 817, 816, 816)]\n"
+     ]
+    }
+   ],
+   "source": [
+    "for cycle_window in train_cells:\n",
+    "    time_series_feature = cycle_window[0]\n",
+    "    print(cycle_window[0])\n",
+    "    break"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
+   "id": "5d66b6ef",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "([(array([[540.   ,   2.701,  -0.968],\n",
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+       "          [540.   ,   2.743,  -0.968],\n",
+       "          [540.   ,   2.757,  -0.968],\n",
+       "          [540.   ,   2.771,  -0.968],\n",
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+       "          [540.   ,   2.799,  -0.968],\n",
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+       "          [540.   ,   2.828,  -0.968],\n",
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+       "          [540.   ,   4.082,  -0.968],\n",
+       "          [540.   ,   4.096,  -0.972]]),\n",
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+       "          [559.   ,   4.088,  -0.974]])),\n",
+       "  (821,\n",
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+       "   821,\n",
+       "   820,\n",
+       "   819,\n",
+       "   819,\n",
+       "   818,\n",
+       "   818,\n",
+       "   818,\n",
+       "   818,\n",
+       "   818,\n",
+       "   818,\n",
+       "   817,\n",
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+       "   816,\n",
+       "   817,\n",
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+       "   816,\n",
+       "   816)],\n",
+       " [(-0.0037489326300000235, -0.0035031330444444584),\n",
+       "  (-0.0007022220999999718, -0.0037131750333334107),\n",
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+       "  (-0.0031555101600000413, -0.002844497211111118),\n",
+       "  (-0.0038854463199999856, -0.002869585811111186),\n",
+       "  (-0.0025414743399999828, -0.002627822066666674),\n",
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+       "  (-0.0028863953100000117, -0.0024492504000000162),\n",
+       "  (-0.0035607091600000198, -0.0031467999888889053),\n",
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+       "  (-0.0024269733100000133, -0.0023235090000000014),\n",
+       "  (-0.0022675067999999854, -0.002198623866666644),\n",
+       "  (-0.003055209179999974, -0.002860354311111103),\n",
+       "  (-0.002774031560000001, -0.0028830247555555744),\n",
+       "  (-0.003365734089999961, -0.0035808389),\n",
+       "  (-0.003375701720000013, -0.0029364649666667),\n",
+       "  (-0.0026847851699999927, -0.002885987477777796),\n",
+       "  (-0.010438482110000003, -0.016535917055555533),\n",
+       "  (-0.01521384159000001, -0.008291128222222197),\n",
+       "  (-0.009630038590000023, -0.011032531666666647),\n",
+       "  (-0.011591536330000008, -0.014800701066666644),\n",
+       "  (-0.01823946687999998, -0.01849171450000004),\n",
+       "  (-0.016165883369999978, -0.013401437811111114)])"
+      ]
+     },
+     "execution_count": 79,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "id": "174b5539",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "         [559.   ,   4.074,  -0.968],\n",
+       "         [559.   ,   4.088,  -0.974]])),\n",
+       " (821,\n",
+       "  821,\n",
+       "  821,\n",
+       "  821,\n",
+       "  820,\n",
+       "  819,\n",
+       "  819,\n",
+       "  818,\n",
+       "  818,\n",
+       "  818,\n",
+       "  818,\n",
+       "  818,\n",
+       "  818,\n",
+       "  817,\n",
+       "  817,\n",
+       "  816,\n",
+       "  817,\n",
+       "  817,\n",
+       "  816,\n",
+       "  816)]"
+      ]
+     },
+     "execution_count": 72,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_time_series_features[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "id": "a99d297a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       " (-0.0006506309599999982, -0.0005774139000000024),\n",
+       " (-0.0005317902000000041, -0.0005242893888888952),\n",
+       " (-0.00048338679999999635, -0.00037850703333333315),\n",
+       " (-0.00043447744000000286, -0.0003438184777777822),\n",
+       " (-0.0003498031000000124, -0.00031600487777776957),\n",
+       " (-0.0008533507600000156, -0.0006511993111111033),\n",
+       " (-0.0005796370299999909, -0.0005293456333333384),\n",
+       " (-0.0005266291499999909, -0.00041734625555554946),\n",
+       " (-0.0004449584799999906, -0.00041343308888889635),\n",
+       " (-0.0004164602199999923, -0.0003482724111111156),\n",
+       " (-0.0006266612600000166, -0.0005978351999999828),\n",
+       " (-0.0005296561700000035, -0.0004743692222222151),\n",
+       " (-0.0004304434599999851, -0.0004173043666666734),\n",
+       " (-0.0003774692299999938, -0.00040239375555555727),\n",
+       " (-0.0003462556899999969, -0.00034353716666666066),\n",
+       " (-0.0011848373599999905, -0.0006948373666666699),\n",
+       " (-0.0005524935799999797, -0.0004585117111111339),\n",
+       " (-0.0004543556299999807, -0.0004737939666666789),\n",
+       " (-0.00043955932999999446, -0.00039852227777778835),\n",
+       " (-0.0003521978700000039, -0.0003479989555555581),\n",
+       " (-0.0003616013700000087, -0.000279896733333334),\n",
+       " (-0.0007333950100000042, -0.000563132366666657),\n",
+       " (-0.0004885256599999943, -0.0004549580555555593),\n",
+       " (-0.0004306997599999862, -0.00042180598888889403),\n",
+       " (-0.0004086667499999974, -0.00036380800000000864),\n",
+       " (-0.00033797664999999364, -0.00036744557777779185),\n",
+       " (-0.0006135306799999851, -0.0004719912888888869),\n",
+       " (-0.0004290971100000096, -0.000449853344444436),\n",
+       " (-0.0003766612000000169, -0.00035458442222221126),\n",
+       " (-0.0004460263599999958, -0.00035638907777777205),\n",
+       " (-0.0003737223799999967, -0.00035009267777777155),\n",
+       " (-0.0011383299000000014, -0.0006171358777777858),\n",
+       " (-0.0004927733299999959, -0.000466329411111108),\n",
+       " (-0.0003756013999999919, -0.0004089209444444464),\n",
+       " (-0.00036562828999999744, -0.0003357795111111154),\n",
+       " (-0.00035514903000000153, -0.00034023684444445875),\n",
+       " (-0.000335520460000005, -0.00031696613333334313),\n",
+       " (-0.0007404055699999912, -0.0005227783999999976),\n",
+       " (-0.00047884757000000723, -0.0003527803888888749),\n",
+       " (-0.00038689713999999763, -0.0004059905111111206),\n",
+       " (-0.00037182975000000785, -0.00034500662222221773),\n",
+       " (-0.00033607729000000307, -0.0003680331333333342),\n",
+       " (-0.0005750681600000141, -0.0004633209777777678),\n",
+       " (-0.0004051460399999929, -0.00038443077777778397),\n",
+       " (-0.00034865612999999127, -0.0003781986666666626),\n",
+       " (-0.0003559800100000121, -0.0003088794777777644),\n",
+       " (-0.0003225959999999972, -0.0003268508000000065),\n",
+       " (-0.0011493605899999925, -0.0005561998888888987),\n",
+       " (-0.00046028001000000265, -0.00040927606666666766),\n",
+       " (-0.00041053017999999054, -0.0003495339666666671),\n",
+       " (-0.0003871373499999997, -0.00031697742222222856),\n",
+       " (-0.00033823688000000907, -0.00035397857777777177),\n",
+       " (-0.0003121217599999948, -0.00027421112222223185),\n",
+       " (-0.0007291219000000071, -0.000490801288888898),\n",
+       " (-0.00043876121999999464, -0.0003082703222222359),\n",
+       " (-0.0003177788599999953, -0.00038325351111111335),\n",
+       " (-0.00033821882000000246, -0.0003247271777777863),\n",
+       " (-0.0003414371499999902, -0.00031576355555556427),\n",
+       " (-0.0005842104799999914, -0.0004468813666666824),\n",
+       " (-0.0004129686399999999, -0.00035307906666666905),\n",
+       " (-0.0003301567800000127, -0.0003527834333333245),\n",
+       " ...]"
+      ]
+     },
+     "execution_count": 68,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_time_values"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "id": "af08e66a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[(-0.0037489326300000235, -0.0035031330444444584),\n",
+       " (-0.0007022220999999718, -0.0037131750333334107),\n",
+       " (-0.0025793766699999665, -0.0034727224555555956),\n",
+       " (-0.0034187527599999433, -0.0031196004222222326),\n",
+       " (-0.0031555101600000413, -0.002844497211111118),\n",
+       " (-0.0038854463199999856, -0.002869585811111186),\n",
+       " (-0.0025414743399999828, -0.002627822066666674),\n",
+       " (-0.002692514560000081, -0.002542764255555527),\n",
+       " (-0.002442564600000008, -0.0025086789222222234),\n",
+       " (-0.002292511630000016, -0.0029226585888888737),\n",
+       " (-0.0028863953100000117, -0.0024492504000000162),\n",
+       " (-0.0035607091600000198, -0.0031467999888889053),\n",
+       " (-0.002926258680000027, -0.002637391877777784),\n",
+       " (-0.002602507939999965, -0.002392465511111139),\n",
+       " (-0.0024269733100000133, -0.0023235090000000014),\n",
+       " (-0.0022675067999999854, -0.002198623866666644),\n",
+       " (-0.003055209179999974, -0.002860354311111103),\n",
+       " (-0.002774031560000001, -0.0028830247555555744),\n",
+       " (-0.003365734089999961, -0.0035808389),\n",
+       " (-0.003375701720000013, -0.0029364649666667),\n",
+       " (-0.0026847851699999927, -0.002885987477777796),\n",
+       " (-0.010438482110000003, -0.016535917055555533),\n",
+       " (-0.01521384159000001, -0.008291128222222197),\n",
+       " (-0.009630038590000023, -0.011032531666666647),\n",
+       " (-0.011591536330000008, -0.014800701066666644),\n",
+       " (-0.01823946687999998, -0.01849171450000004),\n",
+       " (-0.016165883369999978, -0.013401437811111114)]"
+      ]
+     },
+     "execution_count": 67,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_time_series_features = [x for xs in train_cells for x in xs]\n",
+    "train_time_series_features[1]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "83e8bfd3",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "ValueError",
+     "evalue": "Can't convert non-rectangular Python sequence to Tensor.",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/tensorflow/python/data/util/structure.py:102\u001b[0m, in \u001b[0;36mnormalize_element\u001b[0;34m(element, element_signature)\u001b[0m\n\u001b[1;32m    101\u001b[0m   \u001b[38;5;28;01mif\u001b[39;00m spec \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m--> 102\u001b[0m     spec \u001b[38;5;241m=\u001b[39m \u001b[43mtype_spec_from_value\u001b[49m\u001b[43m(\u001b[49m\u001b[43mt\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43muse_fallback\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[1;32m    103\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m:\n\u001b[1;32m    104\u001b[0m   \u001b[38;5;66;03m# TypeError indicates it was not possible to compute a `TypeSpec` for\u001b[39;00m\n\u001b[1;32m    105\u001b[0m   \u001b[38;5;66;03m# the value. As a fallback try converting the value to a tensor.\u001b[39;00m\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/tensorflow/python/data/util/structure.py:485\u001b[0m, in \u001b[0;36mtype_spec_from_value\u001b[0;34m(element, use_fallback)\u001b[0m\n\u001b[1;32m    482\u001b[0m     logging\u001b[38;5;241m.\u001b[39mvlog(\n\u001b[1;32m    483\u001b[0m         \u001b[38;5;241m3\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFailed to convert \u001b[39m\u001b[38;5;132;01m%r\u001b[39;00m\u001b[38;5;124m to tensor: \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;241m%\u001b[39m (\u001b[38;5;28mtype\u001b[39m(element)\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m, e))\n\u001b[0;32m--> 485\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCould not build a `TypeSpec` for \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m with type \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mformat(\n\u001b[1;32m    486\u001b[0m     element,\n\u001b[1;32m    487\u001b[0m     \u001b[38;5;28mtype\u001b[39m(element)\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m))\n",
+      "\u001b[0;31mTypeError\u001b[0m: Could not build a `TypeSpec` for [[(array([[540.   ,   2.701,  -0.968],\n       [540.   ,   2.715,  -0.968],\n       [540.   ,   2.729,  -0.968],\n       [540.   ,   2.743,  -0.968],\n       [540.   ,   2.757,  -0.968],\n       [540.   ,   2.771,  -0.968],\n       [540.   ,   2.785,  -0.968],\n       [540.   ,   2.799,  -0.968],\n       [540.   ,   2.814,  -0.968],\n       [540.   ,   2.828,  -0.968],\n       [540.   ,   2.842,  -0.968],\n       [540.   ,   2.856,  -0.968],\n       [540.   ,   2.87 ,  -0.968],\n       [540.   ,   2.884,  -0.968],\n       [540.   ,   2.898,  -0.968],\n       [540.   ,   2.912,  -0.968],\n       [540.   ,   2.926,  -0.968],\n       [540.   ,   2.94 ,  -0.968],\n       [540.   ,   2.955,  -0.968],\n       [540.   ,   2.969,  -0.968],\n       [540.   ,   2.983,  -0.968],\n       [540.   ,   2.997,  -0.968],\n       [540.   ,   3.011,  -0.968],\n       [540.   ,   3.025,  -0.968],\n       [540.   ,   3.039,  -0.968],\n       [540.   ,   3.053,  -0.968],\n       [540.   ,   3.067,  -0.968],\n       [540.   ,   3.081,  -0.968],\n       [540.   ,   3.095,  -0.968],\n       [540.   ,   3.11 ,  -0.968],\n       [540.   ,   3.124,  -0.968],\n       [540.   ,   3.138,  -0.968],\n       [540.   ,   3.152,  -0.968],\n       [540.   ,   3.166,  -0.968],\n       [540.   ,   3.18 ,  -0.968],\n       [540.   ,   3.194,  -0.968],\n       [540.   ,   3.208,  -0.968],\n       [540.   ,   3.222,  -0.968],\n       [540.   ,   3.236,  -0.968],\n       [540.   ,   3.251,  -0.968],\n       [540.   ,   3.265,  -0.968],\n       [540.   ,   3.279,  -0.968],\n       [540.   ,   3.293,  -0.968],\n       [540.   ,   3.307,  -0.968],\n       [540.   ,   3.321,  -0.968],\n       [540.   ,   3.335,  -0.968],\n       [540.   ,   3.349,  -0.968],\n       [540.   ,   3.363,  -0.968],\n       [540.   ,   3.377,  -0.968],\n       [540.   ,   3.391,  -0.968],\n       [540.   ,   3.406,  -0.968],\n       [540.   ,   3.42 ,  -0.968],\n       [540.   ,   3.434,  -0.968],\n       [540.   ,   3.448,  -0.967],\n       [540.   ,   3.462,  -0.968],\n       [540.   ,   3.476,  -0.968],\n       [540.   ,   3.49 ,  -0.968],\n       [540.   ,   3.504,  -0.968],\n       [540.   ,   3.518,  -0.968],\n       [540.   ,   3.532,  -0.968],\n       [540.   ,   3.546,  -0.968],\n       [540.   ,   3.561,  -0.968],\n       [540.   ,   3.575,  -0.968],\n       [540.   ,   3.589,  -0.968],\n       [540.   ,   3.603,  -0.968],\n       [540.   ,   3.617,  -0.968],\n       [540.   ,   3.631,  -0.968],\n       [540.   ,   3.645,  -0.968],\n       [540.   ,   3.659,  -0.968],\n       [540.   ,   3.673,  -0.967],\n       [540.   ,   3.687,  -0.968],\n       [540.   ,   3.702,  -0.968],\n       [540.   ,   3.716,  -0.968],\n       [540.   ,   3.73 ,  -0.968],\n       [540.   ,   3.744,  -0.968],\n       [540.   ,   3.758,  -0.968],\n       [540.   ,   3.772,  -0.968],\n       [540.   ,   3.786,  -0.968],\n       [540.   ,   3.8  ,  -0.968],\n       [540.   ,   3.814,  -0.968],\n       [540.   ,   3.828,  -0.968],\n       [540.   ,   3.842,  -0.968],\n       [540.   ,   3.857,  -0.968],\n       [540.   ,   3.871,  -0.968],\n       [540.   ,   3.885,  -0.968],\n       [540.   ,   3.899,  -0.968],\n       [540.   ,   3.913,  -0.968],\n       [540.   ,   3.927,  -0.968],\n       [540.   ,   3.941,  -0.968],\n       [540.   ,   3.955,  -0.968],\n       [540.   ,   3.969,  -0.968],\n       [540.   ,   3.983,  -0.968],\n       [540.   ,   3.998,  -0.968],\n       [540.   ,   4.012,  -0.968],\n       [540.   ,   4.026,  -0.968],\n       [540.   ,   4.04 ,  -0.968],\n       [540.   ,   4.054,  -0.968],\n       [540.   ,   4.068,  -0.968],\n       [540.   ,   4.082,  -0.968],\n       [540.   ,   4.096,  -0.972]]), array([[541.   ,   2.701,  -0.968],\n       [541.   ,   2.715,  -0.968],\n       [541.   ,   2.729,  -0.968],\n       [541.   ,   2.743,  -0.968],\n       [541.   ,   2.757,  -0.967],\n       [541.   ,   2.771,  -0.968],\n       [541.   ,   2.785,  -0.968],\n       [541.   ,   2.799,  -0.968],\n       [541.   ,   2.814,  -0.968],\n       [541.   ,   2.828,  -0.968],\n       [541.   ,   2.842,  -0.968],\n       [541.   ,   2.856,  -0.968],\n       [541.   ,   2.87 ,  -0.968],\n       [541.   ,   2.884,  -0.968],\n       [541.   ,   2.898,  -0.968],\n       [541.   ,   2.912,  -0.968],\n       [541.   ,   2.926,  -0.968],\n       [541.   ,   2.94 ,  -0.968],\n       [541.   ,   2.955,  -0.968],\n       [541.   ,   2.969,  -0.968],\n       [541.   ,   2.983,  -0.968],\n       [541.   ,   2.997,  -0.968],\n       [541.   ,   3.011,  -0.968],\n       [541.   ,   3.025,  -0.968],\n       [541.   ,   3.039,  -0.968],\n       [541.   ,   3.053,  -0.968],\n       [541.   ,   3.067,  -0.967],\n       [541.   ,   3.081,  -0.968],\n       [541.   ,   3.095,  -0.968],\n       [541.   ,   3.11 ,  -0.968],\n       [541.   ,   3.124,  -0.968],\n       [541.   ,   3.138,  -0.968],\n       [541.   ,   3.152,  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2.810e+03,  3.248e+00, -1.452e+01],\n       [ 2.810e+03,  3.259e+00, -1.452e+01],\n       [ 2.810e+03,  3.269e+00, -1.452e+01],\n       [ 2.810e+03,  3.279e+00, -1.452e+01],\n       [ 2.810e+03,  3.290e+00, -1.452e+01],\n       [ 2.810e+03,  3.300e+00, -1.452e+01],\n       [ 2.810e+03,  3.310e+00, -1.452e+01],\n       [ 2.810e+03,  3.321e+00, -1.452e+01],\n       [ 2.810e+03,  3.331e+00, -1.452e+01],\n       [ 2.810e+03,  3.341e+00, -1.452e+01],\n       [ 2.810e+03,  3.352e+00, -1.452e+01],\n       [ 2.810e+03,  3.362e+00, -1.452e+01],\n       [ 2.810e+03,  3.372e+00, -1.452e+01],\n       [ 2.810e+03,  3.383e+00, -1.452e+01],\n       [ 2.810e+03,  3.393e+00, -1.452e+01],\n       [ 2.810e+03,  3.403e+00, -1.452e+01],\n       [ 2.810e+03,  3.414e+00, -1.452e+01],\n       [ 2.810e+03,  3.424e+00, -1.452e+01],\n       [ 2.810e+03,  3.434e+00, -1.452e+01],\n       [ 2.810e+03,  3.445e+00, -1.452e+01],\n       [ 2.810e+03,  3.455e+00, -1.452e+01],\n       [ 2.810e+03,  3.465e+00, -1.452e+01],\n       [ 2.810e+03,  3.476e+00, -1.452e+01],\n       [ 2.810e+03,  3.486e+00, -1.452e+01],\n       [ 2.810e+03,  3.496e+00, -1.452e+01],\n       [ 2.810e+03,  3.507e+00, -1.452e+01],\n       [ 2.810e+03,  3.517e+00, -1.452e+01],\n       [ 2.810e+03,  3.527e+00, -1.452e+01],\n       [ 2.810e+03,  3.538e+00, -1.452e+01],\n       [ 2.810e+03,  3.548e+00, -1.452e+01],\n       [ 2.810e+03,  3.558e+00, -1.452e+01],\n       [ 2.810e+03,  3.569e+00, -1.452e+01],\n       [ 2.810e+03,  3.579e+00, -1.452e+01],\n       [ 2.810e+03,  3.589e+00, -1.452e+01],\n       [ 2.810e+03,  3.600e+00, -1.452e+01],\n       [ 2.810e+03,  3.610e+00, -1.452e+01],\n       [ 2.810e+03,  3.620e+00, -1.452e+01],\n       [ 2.810e+03,  3.631e+00, -1.452e+01],\n       [ 2.810e+03,  3.641e+00, -1.452e+01],\n       [ 2.810e+03,  3.651e+00, -1.452e+01],\n       [ 2.810e+03,  3.662e+00, -1.452e+01],\n       [ 2.810e+03,  3.672e+00, -1.452e+01],\n       [ 2.810e+03,  3.682e+00, -1.452e+01],\n       [ 2.810e+03,  3.693e+00, -1.453e+01],\n       [ 2.810e+03,  3.703e+00, -1.453e+01],\n       [ 2.810e+03,  3.713e+00, -1.453e+01],\n       [ 2.810e+03,  3.724e+00, -1.453e+01]]), array([[ 2.811e+03,  2.701e+00, -1.452e+01],\n       [ 2.811e+03,  2.711e+00, -1.452e+01],\n       [ 2.811e+03,  2.721e+00, -1.452e+01],\n       [ 2.811e+03,  2.732e+00, -1.452e+01],\n       [ 2.811e+03,  2.742e+00, -1.452e+01],\n       [ 2.811e+03,  2.752e+00, -1.452e+01],\n       [ 2.811e+03,  2.763e+00, -1.452e+01],\n       [ 2.811e+03,  2.773e+00, -1.452e+01],\n       [ 2.811e+03,  2.783e+00, -1.452e+01],\n       [ 2.811e+03,  2.794e+00, -1.452e+01],\n       [ 2.811e+03,  2.804e+00, -1.452e+01],\n       [ 2.811e+03,  2.814e+00, -1.452e+01],\n       [ 2.811e+03,  2.825e+00, -1.452e+01],\n       [ 2.811e+03,  2.835e+00, -1.452e+01],\n       [ 2.811e+03,  2.845e+00, -1.452e+01],\n       [ 2.811e+03,  2.856e+00, -1.452e+01],\n       [ 2.811e+03,  2.866e+00, -1.452e+01],\n       [ 2.811e+03,  2.876e+00, -1.452e+01],\n       [ 2.811e+03,  2.887e+00, -1.452e+01],\n       [ 2.811e+03,  2.897e+00, -1.452e+01],\n       [ 2.811e+03,  2.907e+00, -1.452e+01],\n       [ 2.811e+03,  2.918e+00, -1.452e+01],\n       [ 2.811e+03,  2.928e+00, -1.452e+01],\n       [ 2.811e+03,  2.938e+00, -1.452e+01],\n       [ 2.811e+03,  2.949e+00, -1.452e+01],\n       [ 2.811e+03,  2.959e+00, -1.452e+01],\n       [ 2.811e+03,  2.969e+00, -1.452e+01],\n       [ 2.811e+03,  2.980e+00, -1.452e+01],\n       [ 2.811e+03,  2.990e+00, -1.452e+01],\n       [ 2.811e+03,  3.000e+00, -1.452e+01],\n       [ 2.811e+03,  3.011e+00, -1.452e+01],\n       [ 2.811e+03,  3.021e+00, -1.452e+01],\n       [ 2.811e+03,  3.031e+00, -1.452e+01],\n       [ 2.811e+03,  3.042e+00, -1.452e+01],\n       [ 2.811e+03,  3.052e+00, -1.452e+01],\n       [ 2.811e+03,  3.062e+00, -1.452e+01],\n       [ 2.811e+03,  3.073e+00, -1.452e+01],\n       [ 2.811e+03,  3.083e+00, -1.452e+01],\n       [ 2.811e+03,  3.093e+00, -1.452e+01],\n       [ 2.811e+03,  3.104e+00, -1.452e+01],\n       [ 2.811e+03,  3.114e+00, -1.452e+01],\n       [ 2.811e+03,  3.124e+00, -1.452e+01],\n       [ 2.811e+03,  3.135e+00, -1.452e+01],\n       [ 2.811e+03,  3.145e+00, -1.452e+01],\n       [ 2.811e+03,  3.155e+00, -1.452e+01],\n       [ 2.811e+03,  3.166e+00, -1.452e+01],\n       [ 2.811e+03,  3.176e+00, -1.452e+01],\n       [ 2.811e+03,  3.186e+00, -1.452e+01],\n       [ 2.811e+03,  3.197e+00, -1.452e+01],\n       [ 2.811e+03,  3.207e+00, -1.452e+01],\n       [ 2.811e+03,  3.217e+00, -1.452e+01],\n       [ 2.811e+03,  3.228e+00, -1.452e+01],\n       [ 2.811e+03,  3.238e+00, -1.452e+01],\n       [ 2.811e+03,  3.248e+00, -1.452e+01],\n       [ 2.811e+03,  3.259e+00, -1.452e+01],\n       [ 2.811e+03,  3.269e+00, -1.452e+01],\n       [ 2.811e+03,  3.279e+00, -1.452e+01],\n       [ 2.811e+03,  3.290e+00, -1.452e+01],\n       [ 2.811e+03,  3.300e+00, -1.452e+01],\n       [ 2.811e+03,  3.310e+00, -1.452e+01],\n       [ 2.811e+03,  3.321e+00, -1.452e+01],\n       [ 2.811e+03,  3.331e+00, -1.452e+01],\n       [ 2.811e+03,  3.341e+00, -1.452e+01],\n       [ 2.811e+03,  3.352e+00, -1.452e+01],\n       [ 2.811e+03,  3.362e+00, -1.452e+01],\n       [ 2.811e+03,  3.372e+00, -1.452e+01],\n       [ 2.811e+03,  3.383e+00, -1.452e+01],\n       [ 2.811e+03,  3.393e+00, -1.452e+01],\n       [ 2.811e+03,  3.403e+00, -1.452e+01],\n       [ 2.811e+03,  3.414e+00, -1.452e+01],\n       [ 2.811e+03,  3.424e+00, -1.452e+01],\n       [ 2.811e+03,  3.434e+00, -1.452e+01],\n       [ 2.811e+03,  3.445e+00, -1.452e+01],\n       [ 2.811e+03,  3.455e+00, -1.452e+01],\n       [ 2.811e+03,  3.465e+00, -1.452e+01],\n       [ 2.811e+03,  3.476e+00, -1.452e+01],\n       [ 2.811e+03,  3.486e+00, -1.452e+01],\n       [ 2.811e+03,  3.496e+00, -1.452e+01],\n       [ 2.811e+03,  3.507e+00, -1.452e+01],\n       [ 2.811e+03,  3.517e+00, -1.452e+01],\n       [ 2.811e+03,  3.527e+00, -1.452e+01],\n       [ 2.811e+03,  3.538e+00, -1.452e+01],\n       [ 2.811e+03,  3.548e+00, -1.452e+01],\n       [ 2.811e+03,  3.558e+00, -1.452e+01],\n       [ 2.811e+03,  3.569e+00, -1.452e+01],\n       [ 2.811e+03,  3.579e+00, -1.452e+01],\n       [ 2.811e+03,  3.589e+00, -1.452e+01],\n       [ 2.811e+03,  3.600e+00, -1.452e+01],\n       [ 2.811e+03,  3.610e+00, -1.452e+01],\n       [ 2.811e+03,  3.620e+00, -1.452e+01],\n       [ 2.811e+03,  3.631e+00, -1.452e+01],\n       [ 2.811e+03,  3.641e+00, -1.452e+01],\n       [ 2.811e+03,  3.651e+00, -1.452e+01],\n       [ 2.811e+03,  3.662e+00, -1.452e+01],\n       [ 2.811e+03,  3.672e+00, -1.452e+01],\n       [ 2.811e+03,  3.682e+00, -1.452e+01],\n       [ 2.811e+03,  3.693e+00, -1.453e+01],\n       [ 2.811e+03,  3.703e+00, -1.453e+01],\n       [ 2.811e+03,  3.713e+00, -1.453e+01],\n       [ 2.811e+03,  3.724e+00, -1.453e+01]]), array([[ 2.812e+03,  2.701e+00, -1.452e+01],\n       [ 2.812e+03,  2.711e+00, -1.452e+01],\n       [ 2.812e+03,  2.721e+00, -1.452e+01],\n       [ 2.812e+03,  2.732e+00, -1.452e+01],\n       [ 2.812e+03,  2.742e+00, -1.452e+01],\n       [ 2.812e+03,  2.752e+00, -1.452e+01],\n       [ 2.812e+03,  2.763e+00, -1.452e+01],\n       [ 2.812e+03,  2.773e+00, -1.452e+01],\n       [ 2.812e+03,  2.783e+00, -1.452e+01],\n       [ 2.812e+03,  2.794e+00, -1.452e+01],\n       [ 2.812e+03,  2.804e+00, -1.452e+01],\n       [ 2.812e+03,  2.814e+00, -1.452e+01],\n       [ 2.812e+03,  2.825e+00, -1.452e+01],\n       [ 2.812e+03,  2.835e+00, -1.452e+01],\n       [ 2.812e+03,  2.845e+00, -1.452e+01],\n       [ 2.812e+03,  2.856e+00, -1.452e+01],\n       [ 2.812e+03,  2.866e+00, -1.452e+01],\n       [ 2.812e+03,  2.876e+00, -1.452e+01],\n       [ 2.812e+03,  2.887e+00, -1.452e+01],\n       [ 2.812e+03,  2.897e+00, -1.452e+01],\n       [ 2.812e+03,  2.907e+00, -1.452e+01],\n       [ 2.812e+03,  2.918e+00, -1.452e+01],\n       [ 2.812e+03,  2.928e+00, -1.452e+01],\n       [ 2.812e+03,  2.938e+00, -1.452e+01],\n       [ 2.812e+03,  2.949e+00, -1.452e+01],\n       [ 2.812e+03,  2.959e+00, -1.452e+01],\n       [ 2.812e+03,  2.969e+00, -1.452e+01],\n       [ 2.812e+03,  2.980e+00, -1.452e+01],\n       [ 2.812e+03,  2.990e+00, -1.452e+01],\n       [ 2.812e+03,  3.000e+00, -1.452e+01],\n       [ 2.812e+03,  3.011e+00, -1.452e+01],\n       [ 2.812e+03,  3.021e+00, -1.452e+01],\n       [ 2.812e+03,  3.031e+00, -1.452e+01],\n       [ 2.812e+03,  3.042e+00, -1.452e+01],\n       [ 2.812e+03,  3.052e+00, -1.452e+01],\n       [ 2.812e+03,  3.062e+00, -1.452e+01],\n       [ 2.812e+03,  3.073e+00, -1.452e+01],\n       [ 2.812e+03,  3.083e+00, -1.452e+01],\n       [ 2.812e+03,  3.093e+00, -1.452e+01],\n       [ 2.812e+03,  3.104e+00, -1.452e+01],\n       [ 2.812e+03,  3.114e+00, -1.452e+01],\n       [ 2.812e+03,  3.124e+00, -1.452e+01],\n       [ 2.812e+03,  3.135e+00, -1.452e+01],\n       [ 2.812e+03,  3.145e+00, -1.452e+01],\n       [ 2.812e+03,  3.155e+00, -1.452e+01],\n       [ 2.812e+03,  3.166e+00, -1.452e+01],\n       [ 2.812e+03,  3.176e+00, -1.452e+01],\n       [ 2.812e+03,  3.186e+00, -1.452e+01],\n       [ 2.812e+03,  3.197e+00, -1.452e+01],\n       [ 2.812e+03,  3.207e+00, -1.452e+01],\n       [ 2.812e+03,  3.217e+00, -1.452e+01],\n       [ 2.812e+03,  3.228e+00, -1.452e+01],\n       [ 2.812e+03,  3.238e+00, -1.452e+01],\n       [ 2.812e+03,  3.248e+00, -1.452e+01],\n       [ 2.812e+03,  3.259e+00, -1.452e+01],\n       [ 2.812e+03,  3.269e+00, -1.452e+01],\n       [ 2.812e+03,  3.279e+00, -1.452e+01],\n       [ 2.812e+03,  3.290e+00, -1.452e+01],\n       [ 2.812e+03,  3.300e+00, -1.452e+01],\n       [ 2.812e+03,  3.310e+00, -1.452e+01],\n       [ 2.812e+03,  3.321e+00, -1.452e+01],\n       [ 2.812e+03,  3.331e+00, -1.452e+01],\n       [ 2.812e+03,  3.341e+00, -1.452e+01],\n       [ 2.812e+03,  3.352e+00, -1.452e+01],\n       [ 2.812e+03,  3.362e+00, -1.452e+01],\n       [ 2.812e+03,  3.372e+00, -1.452e+01],\n       [ 2.812e+03,  3.383e+00, -1.452e+01],\n       [ 2.812e+03,  3.393e+00, -1.452e+01],\n       [ 2.812e+03,  3.403e+00, -1.452e+01],\n       [ 2.812e+03,  3.414e+00, -1.452e+01],\n       [ 2.812e+03,  3.424e+00, -1.452e+01],\n       [ 2.812e+03,  3.434e+00, -1.452e+01],\n       [ 2.812e+03,  3.445e+00, -1.452e+01],\n       [ 2.812e+03,  3.455e+00, -1.452e+01],\n       [ 2.812e+03,  3.465e+00, -1.452e+01],\n       [ 2.812e+03,  3.476e+00, -1.452e+01],\n       [ 2.812e+03,  3.486e+00, -1.452e+01],\n       [ 2.812e+03,  3.496e+00, -1.452e+01],\n       [ 2.812e+03,  3.507e+00, -1.452e+01],\n       [ 2.812e+03,  3.517e+00, -1.452e+01],\n       [ 2.812e+03,  3.527e+00, -1.452e+01],\n       [ 2.812e+03,  3.538e+00, -1.452e+01],\n       [ 2.812e+03,  3.548e+00, -1.452e+01],\n       [ 2.812e+03,  3.558e+00, -1.452e+01],\n       [ 2.812e+03,  3.569e+00, -1.452e+01],\n       [ 2.812e+03,  3.579e+00, -1.452e+01],\n       [ 2.812e+03,  3.589e+00, -1.452e+01],\n       [ 2.812e+03,  3.600e+00, -1.452e+01],\n       [ 2.812e+03,  3.610e+00, -1.452e+01],\n       [ 2.812e+03,  3.620e+00, -1.452e+01],\n       [ 2.812e+03,  3.631e+00, -1.452e+01],\n       [ 2.812e+03,  3.641e+00, -1.452e+01],\n       [ 2.812e+03,  3.651e+00, -1.452e+01],\n       [ 2.812e+03,  3.662e+00, -1.452e+01],\n       [ 2.812e+03,  3.672e+00, -1.452e+01],\n       [ 2.812e+03,  3.682e+00, -1.452e+01],\n       [ 2.812e+03,  3.693e+00, -1.452e+01],\n       [ 2.812e+03,  3.703e+00, -1.453e+01],\n       [ 2.812e+03,  3.713e+00, -1.453e+01],\n       [ 2.812e+03,  3.724e+00, -1.453e+01]]), array([[ 2.813e+03,  2.701e+00, -1.452e+01],\n       [ 2.813e+03,  2.711e+00, -1.452e+01],\n       [ 2.813e+03,  2.721e+00, -1.452e+01],\n       [ 2.813e+03,  2.732e+00, -1.452e+01],\n       [ 2.813e+03,  2.742e+00, -1.452e+01],\n       [ 2.813e+03,  2.752e+00, -1.452e+01],\n       [ 2.813e+03,  2.763e+00, -1.452e+01],\n       [ 2.813e+03,  2.773e+00, -1.452e+01],\n       [ 2.813e+03,  2.783e+00, -1.452e+01],\n       [ 2.813e+03,  2.794e+00, -1.452e+01],\n       [ 2.813e+03,  2.804e+00, -1.452e+01],\n       [ 2.813e+03,  2.814e+00, -1.452e+01],\n       [ 2.813e+03,  2.825e+00, -1.452e+01],\n       [ 2.813e+03,  2.835e+00, -1.452e+01],\n       [ 2.813e+03,  2.845e+00, -1.452e+01],\n       [ 2.813e+03,  2.856e+00, -1.452e+01],\n       [ 2.813e+03,  2.866e+00, -1.452e+01],\n       [ 2.813e+03,  2.876e+00, -1.452e+01],\n       [ 2.813e+03,  2.887e+00, -1.452e+01],\n       [ 2.813e+03,  2.897e+00, -1.452e+01],\n       [ 2.813e+03,  2.907e+00, -1.452e+01],\n       [ 2.813e+03,  2.918e+00, -1.452e+01],\n       [ 2.813e+03,  2.928e+00, -1.452e+01],\n       [ 2.813e+03,  2.938e+00, -1.452e+01],\n       [ 2.813e+03,  2.949e+00, -1.452e+01],\n       [ 2.813e+03,  2.959e+00, -1.452e+01],\n       [ 2.813e+03,  2.969e+00, -1.452e+01],\n       [ 2.813e+03,  2.980e+00, -1.452e+01],\n       [ 2.813e+03,  2.990e+00, -1.452e+01],\n       [ 2.813e+03,  3.000e+00, -1.452e+01],\n       [ 2.813e+03,  3.011e+00, -1.452e+01],\n       [ 2.813e+03,  3.021e+00, -1.452e+01],\n       [ 2.813e+03,  3.031e+00, -1.452e+01],\n       [ 2.813e+03,  3.042e+00, -1.452e+01],\n       [ 2.813e+03,  3.052e+00, 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2.813e+03,  3.507e+00, -1.452e+01],\n       [ 2.813e+03,  3.517e+00, -1.452e+01],\n       [ 2.813e+03,  3.527e+00, -1.452e+01],\n       [ 2.813e+03,  3.538e+00, -1.452e+01],\n       [ 2.813e+03,  3.548e+00, -1.452e+01],\n       [ 2.813e+03,  3.558e+00, -1.452e+01],\n       [ 2.813e+03,  3.569e+00, -1.452e+01],\n       [ 2.813e+03,  3.579e+00, -1.452e+01],\n       [ 2.813e+03,  3.589e+00, -1.452e+01],\n       [ 2.813e+03,  3.600e+00, -1.452e+01],\n       [ 2.813e+03,  3.610e+00, -1.452e+01],\n       [ 2.813e+03,  3.620e+00, -1.452e+01],\n       [ 2.813e+03,  3.631e+00, -1.452e+01],\n       [ 2.813e+03,  3.641e+00, -1.452e+01],\n       [ 2.813e+03,  3.651e+00, -1.452e+01],\n       [ 2.813e+03,  3.662e+00, -1.452e+01],\n       [ 2.813e+03,  3.672e+00, -1.452e+01],\n       [ 2.813e+03,  3.682e+00, -1.452e+01],\n       [ 2.813e+03,  3.693e+00, -1.452e+01],\n       [ 2.813e+03,  3.703e+00, -1.453e+01],\n       [ 2.813e+03,  3.713e+00, -1.453e+01],\n       [ 2.813e+03,  3.724e+00, -1.453e+01]]), array([[ 2.814e+03,  2.701e+00, -1.452e+01],\n       [ 2.814e+03,  2.711e+00, -1.452e+01],\n       [ 2.814e+03,  2.721e+00, -1.452e+01],\n       [ 2.814e+03,  2.732e+00, -1.452e+01],\n       [ 2.814e+03,  2.742e+00, -1.452e+01],\n       [ 2.814e+03,  2.752e+00, -1.452e+01],\n       [ 2.814e+03,  2.763e+00, -1.452e+01],\n       [ 2.814e+03,  2.773e+00, -1.452e+01],\n       [ 2.814e+03,  2.783e+00, -1.452e+01],\n       [ 2.814e+03,  2.794e+00, -1.452e+01],\n       [ 2.814e+03,  2.804e+00, -1.452e+01],\n       [ 2.814e+03,  2.814e+00, -1.452e+01],\n       [ 2.814e+03,  2.825e+00, -1.452e+01],\n       [ 2.814e+03,  2.835e+00, -1.452e+01],\n       [ 2.814e+03,  2.845e+00, -1.452e+01],\n       [ 2.814e+03,  2.856e+00, -1.452e+01],\n       [ 2.814e+03,  2.866e+00, -1.452e+01],\n       [ 2.814e+03,  2.876e+00, -1.452e+01],\n       [ 2.814e+03,  2.887e+00, -1.452e+01],\n       [ 2.814e+03,  2.897e+00, -1.452e+01],\n       [ 2.814e+03,  2.907e+00, -1.452e+01],\n       [ 2.814e+03, 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2.814e+03,  3.145e+00, -1.452e+01],\n       [ 2.814e+03,  3.155e+00, -1.452e+01],\n       [ 2.814e+03,  3.166e+00, -1.452e+01],\n       [ 2.814e+03,  3.176e+00, -1.452e+01],\n       [ 2.814e+03,  3.186e+00, -1.452e+01],\n       [ 2.814e+03,  3.197e+00, -1.452e+01],\n       [ 2.814e+03,  3.207e+00, -1.452e+01],\n       [ 2.814e+03,  3.217e+00, -1.452e+01],\n       [ 2.814e+03,  3.228e+00, -1.452e+01],\n       [ 2.814e+03,  3.238e+00, -1.452e+01],\n       [ 2.814e+03,  3.248e+00, -1.452e+01],\n       [ 2.814e+03,  3.259e+00, -1.452e+01],\n       [ 2.814e+03,  3.269e+00, -1.452e+01],\n       [ 2.814e+03,  3.279e+00, -1.452e+01],\n       [ 2.814e+03,  3.290e+00, -1.452e+01],\n       [ 2.814e+03,  3.300e+00, -1.452e+01],\n       [ 2.814e+03,  3.310e+00, -1.452e+01],\n       [ 2.814e+03,  3.321e+00, -1.452e+01],\n       [ 2.814e+03,  3.331e+00, -1.452e+01],\n       [ 2.814e+03,  3.341e+00, -1.452e+01],\n       [ 2.814e+03,  3.352e+00, -1.452e+01],\n       [ 2.814e+03,  3.362e+00, -1.452e+01],\n       [ 2.814e+03,  3.372e+00, -1.452e+01],\n       [ 2.814e+03,  3.383e+00, -1.452e+01],\n       [ 2.814e+03,  3.393e+00, -1.452e+01],\n       [ 2.814e+03,  3.403e+00, -1.452e+01],\n       [ 2.814e+03,  3.414e+00, -1.452e+01],\n       [ 2.814e+03,  3.424e+00, -1.452e+01],\n       [ 2.814e+03,  3.434e+00, -1.452e+01],\n       [ 2.814e+03,  3.445e+00, -1.452e+01],\n       [ 2.814e+03,  3.455e+00, -1.452e+01],\n       [ 2.814e+03,  3.465e+00, -1.452e+01],\n       [ 2.814e+03,  3.476e+00, -1.452e+01],\n       [ 2.814e+03,  3.486e+00, -1.452e+01],\n       [ 2.814e+03,  3.496e+00, -1.452e+01],\n       [ 2.814e+03,  3.507e+00, -1.452e+01],\n       [ 2.814e+03,  3.517e+00, -1.452e+01],\n       [ 2.814e+03,  3.527e+00, -1.452e+01],\n       [ 2.814e+03,  3.538e+00, -1.452e+01],\n       [ 2.814e+03,  3.548e+00, -1.452e+01],\n       [ 2.814e+03,  3.558e+00, -1.452e+01],\n       [ 2.814e+03,  3.569e+00, -1.452e+01],\n       [ 2.814e+03,  3.579e+00, -1.452e+01],\n       [ 2.814e+03,  3.589e+00, -1.452e+01],\n       [ 2.814e+03,  3.600e+00, -1.452e+01],\n       [ 2.814e+03,  3.610e+00, -1.452e+01],\n       [ 2.814e+03,  3.620e+00, -1.452e+01],\n       [ 2.814e+03,  3.631e+00, -1.452e+01],\n       [ 2.814e+03,  3.641e+00, -1.452e+01],\n       [ 2.814e+03,  3.651e+00, -1.452e+01],\n       [ 2.814e+03,  3.662e+00, -1.452e+01],\n       [ 2.814e+03,  3.672e+00, -1.452e+01],\n       [ 2.814e+03,  3.682e+00, -1.452e+01],\n       [ 2.814e+03,  3.693e+00, -1.452e+01],\n       [ 2.814e+03,  3.703e+00, -1.452e+01],\n       [ 2.814e+03,  3.713e+00, -1.452e+01],\n       [ 2.814e+03,  3.724e+00, -1.452e+01]]), array([[ 2.815e+03,  2.701e+00, -1.452e+01],\n       [ 2.815e+03,  2.711e+00, -1.452e+01],\n       [ 2.815e+03,  2.721e+00, -1.452e+01],\n       [ 2.815e+03,  2.732e+00, -1.452e+01],\n       [ 2.815e+03,  2.742e+00, -1.452e+01],\n       [ 2.815e+03,  2.752e+00, -1.452e+01],\n       [ 2.815e+03,  2.763e+00, -1.452e+01],\n       [ 2.815e+03,  2.773e+00, -1.452e+01],\n       [ 2.815e+03,  2.783e+00, -1.452e+01],\n       [ 2.815e+03,  2.794e+00, -1.452e+01],\n       [ 2.815e+03,  2.804e+00, -1.452e+01],\n       [ 2.815e+03,  2.814e+00, -1.452e+01],\n       [ 2.815e+03,  2.825e+00, -1.452e+01],\n       [ 2.815e+03,  2.835e+00, -1.452e+01],\n       [ 2.815e+03,  2.845e+00, -1.452e+01],\n       [ 2.815e+03,  2.856e+00, -1.452e+01],\n       [ 2.815e+03,  2.866e+00, -1.452e+01],\n       [ 2.815e+03,  2.876e+00, -1.452e+01],\n       [ 2.815e+03,  2.886e+00, -1.452e+01],\n       [ 2.815e+03,  2.897e+00, -1.452e+01],\n       [ 2.815e+03,  2.907e+00, -1.452e+01],\n       [ 2.815e+03,  2.917e+00, -1.452e+01],\n       [ 2.815e+03,  2.928e+00, -1.452e+01],\n       [ 2.815e+03,  2.938e+00, -1.452e+01],\n       [ 2.815e+03,  2.948e+00, -1.452e+01],\n       [ 2.815e+03,  2.959e+00, -1.452e+01],\n       [ 2.815e+03,  2.969e+00, -1.452e+01],\n       [ 2.815e+03,  2.979e+00, -1.452e+01],\n       [ 2.815e+03,  2.990e+00, -1.452e+01],\n       [ 2.815e+03,  3.000e+00, 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3.227e+00, -1.452e+01],\n       [ 2.815e+03,  3.237e+00, -1.452e+01],\n       [ 2.815e+03,  3.247e+00, -1.452e+01],\n       [ 2.815e+03,  3.258e+00, -1.452e+01],\n       [ 2.815e+03,  3.268e+00, -1.452e+01],\n       [ 2.815e+03,  3.278e+00, -1.452e+01],\n       [ 2.815e+03,  3.289e+00, -1.452e+01],\n       [ 2.815e+03,  3.299e+00, -1.452e+01],\n       [ 2.815e+03,  3.309e+00, -1.452e+01],\n       [ 2.815e+03,  3.320e+00, -1.452e+01],\n       [ 2.815e+03,  3.330e+00, -1.452e+01],\n       [ 2.815e+03,  3.340e+00, -1.452e+01],\n       [ 2.815e+03,  3.351e+00, -1.452e+01],\n       [ 2.815e+03,  3.361e+00, -1.452e+01],\n       [ 2.815e+03,  3.371e+00, -1.452e+01],\n       [ 2.815e+03,  3.381e+00, -1.452e+01],\n       [ 2.815e+03,  3.392e+00, -1.452e+01],\n       [ 2.815e+03,  3.402e+00, -1.452e+01],\n       [ 2.815e+03,  3.412e+00, -1.452e+01],\n       [ 2.815e+03,  3.423e+00, -1.452e+01],\n       [ 2.815e+03,  3.433e+00, -1.452e+01],\n       [ 2.815e+03,  3.443e+00, -1.452e+01],\n       [ 2.815e+03,  3.454e+00, -1.452e+01],\n       [ 2.815e+03,  3.464e+00, -1.452e+01],\n       [ 2.815e+03,  3.474e+00, -1.452e+01],\n       [ 2.815e+03,  3.485e+00, -1.452e+01],\n       [ 2.815e+03,  3.495e+00, -1.452e+01],\n       [ 2.815e+03,  3.505e+00, -1.452e+01],\n       [ 2.815e+03,  3.516e+00, -1.452e+01],\n       [ 2.815e+03,  3.526e+00, -1.452e+01],\n       [ 2.815e+03,  3.536e+00, -1.452e+01],\n       [ 2.815e+03,  3.546e+00, -1.452e+01],\n       [ 2.815e+03,  3.557e+00, -1.452e+01],\n       [ 2.815e+03,  3.567e+00, -1.452e+01],\n       [ 2.815e+03,  3.577e+00, -1.452e+01],\n       [ 2.815e+03,  3.588e+00, -1.452e+01],\n       [ 2.815e+03,  3.598e+00, -1.452e+01],\n       [ 2.815e+03,  3.608e+00, -1.452e+01],\n       [ 2.815e+03,  3.619e+00, -1.452e+01],\n       [ 2.815e+03,  3.629e+00, -1.452e+01],\n       [ 2.815e+03,  3.639e+00, -1.452e+01],\n       [ 2.815e+03,  3.650e+00, -1.452e+01],\n       [ 2.815e+03,  3.660e+00, -1.452e+01],\n       [ 2.815e+03,  3.670e+00, -1.452e+01],\n       [ 2.815e+03,  3.681e+00, -1.452e+01],\n       [ 2.815e+03,  3.691e+00, -1.452e+01],\n       [ 2.815e+03,  3.701e+00, -1.453e+01],\n       [ 2.815e+03,  3.712e+00, -1.453e+01],\n       [ 2.815e+03,  3.722e+00, -1.453e+01]]), array([[ 2.816e+03,  2.701e+00, -1.452e+01],\n       [ 2.816e+03,  2.711e+00, -1.452e+01],\n       [ 2.816e+03,  2.721e+00, -1.452e+01],\n       [ 2.816e+03,  2.732e+00, -1.452e+01],\n       [ 2.816e+03,  2.742e+00, -1.452e+01],\n       [ 2.816e+03,  2.752e+00, -1.452e+01],\n       [ 2.816e+03,  2.763e+00, -1.452e+01],\n       [ 2.816e+03,  2.773e+00, -1.452e+01],\n       [ 2.816e+03,  2.783e+00, -1.452e+01],\n       [ 2.816e+03,  2.794e+00, -1.452e+01],\n       [ 2.816e+03,  2.804e+00, -1.452e+01],\n       [ 2.816e+03,  2.814e+00, -1.452e+01],\n       [ 2.816e+03,  2.825e+00, -1.452e+01],\n       [ 2.816e+03,  2.835e+00, -1.452e+01],\n       [ 2.816e+03,  2.845e+00, -1.452e+01],\n       [ 2.816e+03,  2.856e+00, -1.452e+01],\n       [ 2.816e+03,  2.866e+00, -1.452e+01],\n       [ 2.816e+03,  2.876e+00, -1.452e+01],\n       [ 2.816e+03,  2.887e+00, -1.452e+01],\n       [ 2.816e+03,  2.897e+00, -1.452e+01],\n       [ 2.816e+03,  2.907e+00, -1.452e+01],\n       [ 2.816e+03,  2.918e+00, -1.452e+01],\n       [ 2.816e+03,  2.928e+00, -1.452e+01],\n       [ 2.816e+03,  2.938e+00, -1.452e+01],\n       [ 2.816e+03,  2.949e+00, -1.452e+01],\n       [ 2.816e+03,  2.959e+00, -1.452e+01],\n       [ 2.816e+03,  2.969e+00, -1.452e+01],\n       [ 2.816e+03,  2.980e+00, -1.452e+01],\n       [ 2.816e+03,  2.990e+00, -1.452e+01],\n       [ 2.816e+03,  3.000e+00, -1.452e+01],\n       [ 2.816e+03,  3.011e+00, -1.452e+01],\n       [ 2.816e+03,  3.021e+00, -1.452e+01],\n       [ 2.816e+03,  3.031e+00, -1.452e+01],\n       [ 2.816e+03,  3.042e+00, -1.452e+01],\n       [ 2.816e+03,  3.052e+00, -1.452e+01],\n       [ 2.816e+03,  3.062e+00, -1.452e+01],\n       [ 2.816e+03,  3.073e+00, -1.452e+01],\n       [ 2.816e+03,  3.083e+00, -1.452e+01],\n       [ 2.816e+03,  3.093e+00, -1.452e+01],\n       [ 2.816e+03,  3.104e+00, -1.452e+01],\n       [ 2.816e+03,  3.114e+00, -1.452e+01],\n       [ 2.816e+03,  3.124e+00, -1.452e+01],\n       [ 2.816e+03,  3.135e+00, -1.452e+01],\n       [ 2.816e+03,  3.145e+00, -1.452e+01],\n       [ 2.816e+03,  3.155e+00, -1.452e+01],\n       [ 2.816e+03,  3.166e+00, -1.452e+01],\n       [ 2.816e+03,  3.176e+00, -1.452e+01],\n       [ 2.816e+03,  3.186e+00, -1.452e+01],\n       [ 2.816e+03,  3.197e+00, -1.452e+01],\n       [ 2.816e+03,  3.207e+00, -1.452e+01],\n       [ 2.816e+03,  3.217e+00, -1.452e+01],\n       [ 2.816e+03,  3.228e+00, -1.452e+01],\n       [ 2.816e+03,  3.238e+00, -1.452e+01],\n       [ 2.816e+03,  3.248e+00, -1.452e+01],\n       [ 2.816e+03,  3.259e+00, -1.452e+01],\n       [ 2.816e+03,  3.269e+00, -1.452e+01],\n       [ 2.816e+03,  3.279e+00, -1.452e+01],\n       [ 2.816e+03,  3.290e+00, -1.452e+01],\n       [ 2.816e+03,  3.300e+00, -1.452e+01],\n       [ 2.816e+03,  3.310e+00, -1.452e+01],\n       [ 2.816e+03,  3.321e+00, -1.452e+01],\n       [ 2.816e+03,  3.331e+00, -1.452e+01],\n       [ 2.816e+03,  3.341e+00, -1.452e+01],\n       [ 2.816e+03,  3.352e+00, -1.452e+01],\n       [ 2.816e+03,  3.362e+00, -1.452e+01],\n       [ 2.816e+03,  3.372e+00, -1.452e+01],\n       [ 2.816e+03,  3.383e+00, -1.452e+01],\n       [ 2.816e+03,  3.393e+00, -1.452e+01],\n       [ 2.816e+03,  3.403e+00, -1.452e+01],\n       [ 2.816e+03,  3.414e+00, -1.452e+01],\n       [ 2.816e+03,  3.424e+00, -1.452e+01],\n       [ 2.816e+03,  3.434e+00, -1.452e+01],\n       [ 2.816e+03,  3.445e+00, -1.452e+01],\n       [ 2.816e+03,  3.455e+00, -1.452e+01],\n       [ 2.816e+03,  3.465e+00, -1.452e+01],\n       [ 2.816e+03,  3.476e+00, -1.452e+01],\n       [ 2.816e+03,  3.486e+00, -1.452e+01],\n       [ 2.816e+03,  3.496e+00, -1.452e+01],\n       [ 2.816e+03,  3.507e+00, -1.452e+01],\n       [ 2.816e+03,  3.517e+00, -1.452e+01],\n       [ 2.816e+03,  3.527e+00, -1.452e+01],\n       [ 2.816e+03,  3.538e+00, -1.452e+01],\n       [ 2.816e+03,  3.548e+00, -1.452e+01],\n       [ 2.816e+03,  3.558e+00, -1.452e+01],\n       [ 2.816e+03,  3.569e+00, -1.452e+01],\n       [ 2.816e+03,  3.579e+00, -1.452e+01],\n       [ 2.816e+03,  3.589e+00, -1.452e+01],\n       [ 2.816e+03,  3.600e+00, -1.452e+01],\n       [ 2.816e+03,  3.610e+00, -1.452e+01],\n       [ 2.816e+03,  3.620e+00, -1.452e+01],\n       [ 2.816e+03,  3.631e+00, -1.452e+01],\n       [ 2.816e+03,  3.641e+00, -1.452e+01],\n       [ 2.816e+03,  3.651e+00, -1.452e+01],\n       [ 2.816e+03,  3.662e+00, -1.452e+01],\n       [ 2.816e+03,  3.672e+00, -1.452e+01],\n       [ 2.816e+03,  3.682e+00, -1.452e+01],\n       [ 2.816e+03,  3.693e+00, -1.452e+01],\n       [ 2.816e+03,  3.703e+00, -1.452e+01],\n       [ 2.816e+03,  3.713e+00, -1.452e+01],\n       [ 2.816e+03,  3.724e+00, -1.452e+01]]), array([[ 2.817e+03,  2.701e+00, -1.452e+01],\n       [ 2.817e+03,  2.711e+00, -1.452e+01],\n       [ 2.817e+03,  2.721e+00, -1.452e+01],\n       [ 2.817e+03,  2.732e+00, -1.452e+01],\n       [ 2.817e+03,  2.742e+00, -1.452e+01],\n       [ 2.817e+03,  2.752e+00, -1.452e+01],\n       [ 2.817e+03,  2.763e+00, -1.452e+01],\n       [ 2.817e+03,  2.773e+00, -1.452e+01],\n       [ 2.817e+03,  2.783e+00, -1.452e+01],\n       [ 2.817e+03,  2.794e+00, -1.452e+01],\n       [ 2.817e+03,  2.804e+00, -1.452e+01],\n       [ 2.817e+03,  2.814e+00, -1.452e+01],\n       [ 2.817e+03,  2.825e+00, -1.452e+01],\n       [ 2.817e+03,  2.835e+00, -1.452e+01],\n       [ 2.817e+03,  2.845e+00, -1.452e+01],\n       [ 2.817e+03,  2.856e+00, -1.452e+01],\n       [ 2.817e+03,  2.866e+00, -1.452e+01],\n       [ 2.817e+03,  2.876e+00, -1.452e+01],\n       [ 2.817e+03,  2.886e+00, -1.452e+01],\n       [ 2.817e+03,  2.897e+00, -1.452e+01],\n       [ 2.817e+03,  2.907e+00, -1.452e+01],\n       [ 2.817e+03,  2.917e+00, -1.452e+01],\n       [ 2.817e+03,  2.928e+00, -1.452e+01],\n       [ 2.817e+03,  2.938e+00, -1.452e+01],\n       [ 2.817e+03,  2.948e+00, -1.452e+01],\n       [ 2.817e+03,  2.959e+00, -1.452e+01],\n       [ 2.817e+03,  2.969e+00, -1.452e+01],\n       [ 2.817e+03,  2.979e+00, -1.452e+01],\n       [ 2.817e+03,  2.990e+00, -1.452e+01],\n       [ 2.817e+03,  3.000e+00, -1.452e+01],\n       [ 2.817e+03,  3.010e+00, -1.452e+01],\n       [ 2.817e+03,  3.021e+00, -1.452e+01],\n       [ 2.817e+03,  3.031e+00, -1.452e+01],\n       [ 2.817e+03,  3.041e+00, -1.452e+01],\n       [ 2.817e+03,  3.051e+00, -1.452e+01],\n       [ 2.817e+03,  3.062e+00, -1.452e+01],\n       [ 2.817e+03,  3.072e+00, -1.452e+01],\n       [ 2.817e+03,  3.082e+00, -1.452e+01],\n       [ 2.817e+03,  3.093e+00, -1.452e+01],\n       [ 2.817e+03,  3.103e+00, -1.452e+01],\n       [ 2.817e+03,  3.113e+00, -1.452e+01],\n       [ 2.817e+03,  3.124e+00, -1.452e+01],\n       [ 2.817e+03,  3.134e+00, -1.452e+01],\n       [ 2.817e+03,  3.144e+00, -1.452e+01],\n       [ 2.817e+03,  3.155e+00, -1.452e+01],\n       [ 2.817e+03,  3.165e+00, -1.452e+01],\n       [ 2.817e+03,  3.175e+00, -1.452e+01],\n       [ 2.817e+03,  3.186e+00, -1.452e+01],\n       [ 2.817e+03,  3.196e+00, -1.452e+01],\n       [ 2.817e+03,  3.206e+00, -1.452e+01],\n       [ 2.817e+03,  3.216e+00, -1.452e+01],\n       [ 2.817e+03,  3.227e+00, -1.452e+01],\n       [ 2.817e+03,  3.237e+00, -1.452e+01],\n       [ 2.817e+03,  3.247e+00, -1.452e+01],\n       [ 2.817e+03,  3.258e+00, -1.452e+01],\n       [ 2.817e+03,  3.268e+00, -1.452e+01],\n       [ 2.817e+03,  3.278e+00, -1.452e+01],\n       [ 2.817e+03,  3.289e+00, -1.452e+01],\n       [ 2.817e+03,  3.299e+00, -1.452e+01],\n       [ 2.817e+03,  3.309e+00, -1.452e+01],\n       [ 2.817e+03,  3.320e+00, -1.452e+01],\n       [ 2.817e+03,  3.330e+00, -1.452e+01],\n       [ 2.817e+03,  3.340e+00, -1.452e+01],\n       [ 2.817e+03,  3.351e+00, -1.452e+01],\n       [ 2.817e+03,  3.361e+00, -1.452e+01],\n       [ 2.817e+03,  3.371e+00, -1.452e+01],\n       [ 2.817e+03,  3.381e+00, -1.452e+01],\n       [ 2.817e+03,  3.392e+00, -1.452e+01],\n       [ 2.817e+03,  3.402e+00, -1.452e+01],\n       [ 2.817e+03,  3.412e+00, -1.452e+01],\n       [ 2.817e+03,  3.423e+00, -1.452e+01],\n       [ 2.817e+03,  3.433e+00, -1.452e+01],\n       [ 2.817e+03,  3.443e+00, -1.452e+01],\n       [ 2.817e+03,  3.454e+00, -1.452e+01],\n       [ 2.817e+03,  3.464e+00, -1.452e+01],\n       [ 2.817e+03,  3.474e+00, -1.452e+01],\n       [ 2.817e+03,  3.485e+00, -1.452e+01],\n       [ 2.817e+03,  3.495e+00, -1.452e+01],\n       [ 2.817e+03,  3.505e+00, -1.452e+01],\n       [ 2.817e+03,  3.516e+00, -1.452e+01],\n       [ 2.817e+03,  3.526e+00, -1.452e+01],\n       [ 2.817e+03,  3.536e+00, -1.452e+01],\n       [ 2.817e+03,  3.546e+00, -1.452e+01],\n       [ 2.817e+03,  3.557e+00, -1.452e+01],\n       [ 2.817e+03,  3.567e+00, -1.452e+01],\n       [ 2.817e+03,  3.577e+00, -1.452e+01],\n       [ 2.817e+03,  3.588e+00, -1.452e+01],\n       [ 2.817e+03,  3.598e+00, -1.452e+01],\n       [ 2.817e+03,  3.608e+00, -1.452e+01],\n       [ 2.817e+03,  3.619e+00, -1.452e+01],\n       [ 2.817e+03,  3.629e+00, -1.452e+01],\n       [ 2.817e+03,  3.639e+00, -1.452e+01],\n       [ 2.817e+03,  3.650e+00, -1.452e+01],\n       [ 2.817e+03,  3.660e+00, -1.452e+01],\n       [ 2.817e+03,  3.670e+00, -1.452e+01],\n       [ 2.817e+03,  3.681e+00, -1.452e+01],\n       [ 2.817e+03,  3.691e+00, -1.452e+01],\n       [ 2.817e+03,  3.701e+00, -1.452e+01],\n       [ 2.817e+03,  3.712e+00, -1.452e+01],\n       [ 2.817e+03,  3.722e+00, -1.453e+01]]), array([[ 2.818e+03,  2.701e+00, -1.452e+01],\n       [ 2.818e+03,  2.711e+00, -1.452e+01],\n       [ 2.818e+03,  2.721e+00, -1.452e+01],\n       [ 2.818e+03,  2.732e+00, -1.452e+01],\n       [ 2.818e+03,  2.742e+00, -1.452e+01],\n       [ 2.818e+03,  2.752e+00, -1.452e+01],\n       [ 2.818e+03,  2.763e+00, -1.452e+01],\n       [ 2.818e+03,  2.773e+00, -1.452e+01],\n       [ 2.818e+03,  2.783e+00, -1.452e+01],\n       [ 2.818e+03,  2.794e+00, -1.452e+01],\n       [ 2.818e+03,  2.804e+00, -1.452e+01],\n       [ 2.818e+03, 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2.818e+03,  3.042e+00, -1.452e+01],\n       [ 2.818e+03,  3.052e+00, -1.452e+01],\n       [ 2.818e+03,  3.062e+00, -1.452e+01],\n       [ 2.818e+03,  3.073e+00, -1.452e+01],\n       [ 2.818e+03,  3.083e+00, -1.452e+01],\n       [ 2.818e+03,  3.093e+00, -1.452e+01],\n       [ 2.818e+03,  3.104e+00, -1.452e+01],\n       [ 2.818e+03,  3.114e+00, -1.452e+01],\n       [ 2.818e+03,  3.124e+00, -1.452e+01],\n       [ 2.818e+03,  3.135e+00, -1.452e+01],\n       [ 2.818e+03,  3.145e+00, -1.452e+01],\n       [ 2.818e+03,  3.155e+00, -1.452e+01],\n       [ 2.818e+03,  3.166e+00, -1.452e+01],\n       [ 2.818e+03,  3.176e+00, -1.452e+01],\n       [ 2.818e+03,  3.186e+00, -1.452e+01],\n       [ 2.818e+03,  3.197e+00, -1.452e+01],\n       [ 2.818e+03,  3.207e+00, -1.452e+01],\n       [ 2.818e+03,  3.217e+00, -1.452e+01],\n       [ 2.818e+03,  3.228e+00, -1.452e+01],\n       [ 2.818e+03,  3.238e+00, -1.452e+01],\n       [ 2.818e+03,  3.248e+00, -1.452e+01],\n       [ 2.818e+03,  3.259e+00, 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3.486e+00, -1.452e+01],\n       [ 2.818e+03,  3.496e+00, -1.452e+01],\n       [ 2.818e+03,  3.507e+00, -1.452e+01],\n       [ 2.818e+03,  3.517e+00, -1.452e+01],\n       [ 2.818e+03,  3.527e+00, -1.452e+01],\n       [ 2.818e+03,  3.538e+00, -1.452e+01],\n       [ 2.818e+03,  3.548e+00, -1.452e+01],\n       [ 2.818e+03,  3.558e+00, -1.452e+01],\n       [ 2.818e+03,  3.569e+00, -1.452e+01],\n       [ 2.818e+03,  3.579e+00, -1.452e+01],\n       [ 2.818e+03,  3.589e+00, -1.452e+01],\n       [ 2.818e+03,  3.600e+00, -1.452e+01],\n       [ 2.818e+03,  3.610e+00, -1.452e+01],\n       [ 2.818e+03,  3.620e+00, -1.452e+01],\n       [ 2.818e+03,  3.631e+00, -1.452e+01],\n       [ 2.818e+03,  3.641e+00, -1.452e+01],\n       [ 2.818e+03,  3.651e+00, -1.452e+01],\n       [ 2.818e+03,  3.662e+00, -1.452e+01],\n       [ 2.818e+03,  3.672e+00, -1.452e+01],\n       [ 2.818e+03,  3.682e+00, -1.452e+01],\n       [ 2.818e+03,  3.693e+00, -1.452e+01],\n       [ 2.818e+03,  3.703e+00, -1.453e+01],\n       [ 2.818e+03,  3.713e+00, -1.453e+01],\n       [ 2.818e+03,  3.724e+00, -1.453e+01]]), array([[ 2.819e+03,  2.701e+00, -1.452e+01],\n       [ 2.819e+03,  2.711e+00, -1.452e+01],\n       [ 2.819e+03,  2.721e+00, -1.452e+01],\n       [ 2.819e+03,  2.732e+00, -1.452e+01],\n       [ 2.819e+03,  2.742e+00, -1.452e+01],\n       [ 2.819e+03,  2.752e+00, -1.452e+01],\n       [ 2.819e+03,  2.763e+00, -1.452e+01],\n       [ 2.819e+03,  2.773e+00, -1.452e+01],\n       [ 2.819e+03,  2.783e+00, -1.452e+01],\n       [ 2.819e+03,  2.794e+00, -1.452e+01],\n       [ 2.819e+03,  2.804e+00, -1.452e+01],\n       [ 2.819e+03,  2.814e+00, -1.452e+01],\n       [ 2.819e+03,  2.825e+00, -1.452e+01],\n       [ 2.819e+03,  2.835e+00, -1.452e+01],\n       [ 2.819e+03,  2.845e+00, -1.452e+01],\n       [ 2.819e+03,  2.856e+00, -1.452e+01],\n       [ 2.819e+03,  2.866e+00, -1.452e+01],\n       [ 2.819e+03,  2.876e+00, -1.452e+01],\n       [ 2.819e+03,  2.886e+00, -1.452e+01],\n       [ 2.819e+03,  2.897e+00, 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2.819e+03,  3.351e+00, -1.452e+01],\n       [ 2.819e+03,  3.361e+00, -1.452e+01],\n       [ 2.819e+03,  3.371e+00, -1.452e+01],\n       [ 2.819e+03,  3.381e+00, -1.452e+01],\n       [ 2.819e+03,  3.392e+00, -1.452e+01],\n       [ 2.819e+03,  3.402e+00, -1.452e+01],\n       [ 2.819e+03,  3.412e+00, -1.452e+01],\n       [ 2.819e+03,  3.423e+00, -1.452e+01],\n       [ 2.819e+03,  3.433e+00, -1.452e+01],\n       [ 2.819e+03,  3.443e+00, -1.452e+01],\n       [ 2.819e+03,  3.454e+00, -1.452e+01],\n       [ 2.819e+03,  3.464e+00, -1.452e+01],\n       [ 2.819e+03,  3.474e+00, -1.452e+01],\n       [ 2.819e+03,  3.485e+00, -1.452e+01],\n       [ 2.819e+03,  3.495e+00, -1.452e+01],\n       [ 2.819e+03,  3.505e+00, -1.452e+01],\n       [ 2.819e+03,  3.516e+00, -1.452e+01],\n       [ 2.819e+03,  3.526e+00, -1.452e+01],\n       [ 2.819e+03,  3.536e+00, -1.452e+01],\n       [ 2.819e+03,  3.546e+00, -1.452e+01],\n       [ 2.819e+03,  3.557e+00, -1.452e+01],\n       [ 2.819e+03,  3.567e+00, -1.452e+01],\n       [ 2.819e+03,  3.577e+00, -1.452e+01],\n       [ 2.819e+03,  3.588e+00, -1.452e+01],\n       [ 2.819e+03,  3.598e+00, -1.452e+01],\n       [ 2.819e+03,  3.608e+00, -1.452e+01],\n       [ 2.819e+03,  3.619e+00, -1.452e+01],\n       [ 2.819e+03,  3.629e+00, -1.452e+01],\n       [ 2.819e+03,  3.639e+00, -1.452e+01],\n       [ 2.819e+03,  3.650e+00, -1.452e+01],\n       [ 2.819e+03,  3.660e+00, -1.452e+01],\n       [ 2.819e+03,  3.670e+00, -1.452e+01],\n       [ 2.819e+03,  3.681e+00, -1.452e+01],\n       [ 2.819e+03,  3.691e+00, -1.452e+01],\n       [ 2.819e+03,  3.701e+00, -1.453e+01],\n       [ 2.819e+03,  3.712e+00, -1.453e+01],\n       [ 2.819e+03,  3.722e+00, -1.453e+01]]), array([[ 2.820e+03,  2.701e+00, -1.452e+01],\n       [ 2.820e+03,  2.711e+00, -1.452e+01],\n       [ 2.820e+03,  2.721e+00, -1.452e+01],\n       [ 2.820e+03,  2.732e+00, -1.452e+01],\n       [ 2.820e+03,  2.742e+00, -1.452e+01],\n       [ 2.820e+03,  2.752e+00, -1.452e+01],\n       [ 2.820e+03, 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2.820e+03,  2.990e+00, -1.452e+01],\n       [ 2.820e+03,  3.000e+00, -1.452e+01],\n       [ 2.820e+03,  3.010e+00, -1.452e+01],\n       [ 2.820e+03,  3.021e+00, -1.452e+01],\n       [ 2.820e+03,  3.031e+00, -1.452e+01],\n       [ 2.820e+03,  3.041e+00, -1.452e+01],\n       [ 2.820e+03,  3.051e+00, -1.452e+01],\n       [ 2.820e+03,  3.062e+00, -1.452e+01],\n       [ 2.820e+03,  3.072e+00, -1.452e+01],\n       [ 2.820e+03,  3.082e+00, -1.452e+01],\n       [ 2.820e+03,  3.093e+00, -1.452e+01],\n       [ 2.820e+03,  3.103e+00, -1.452e+01],\n       [ 2.820e+03,  3.113e+00, -1.452e+01],\n       [ 2.820e+03,  3.124e+00, -1.452e+01],\n       [ 2.820e+03,  3.134e+00, -1.452e+01],\n       [ 2.820e+03,  3.144e+00, -1.452e+01],\n       [ 2.820e+03,  3.155e+00, -1.452e+01],\n       [ 2.820e+03,  3.165e+00, -1.452e+01],\n       [ 2.820e+03,  3.175e+00, -1.452e+01],\n       [ 2.820e+03,  3.186e+00, -1.452e+01],\n       [ 2.820e+03,  3.196e+00, -1.452e+01],\n       [ 2.820e+03,  3.206e+00, 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3.433e+00, -1.452e+01],\n       [ 2.820e+03,  3.443e+00, -1.452e+01],\n       [ 2.820e+03,  3.454e+00, -1.452e+01],\n       [ 2.820e+03,  3.464e+00, -1.452e+01],\n       [ 2.820e+03,  3.474e+00, -1.452e+01],\n       [ 2.820e+03,  3.485e+00, -1.452e+01],\n       [ 2.820e+03,  3.495e+00, -1.452e+01],\n       [ 2.820e+03,  3.505e+00, -1.452e+01],\n       [ 2.820e+03,  3.516e+00, -1.452e+01],\n       [ 2.820e+03,  3.526e+00, -1.452e+01],\n       [ 2.820e+03,  3.536e+00, -1.452e+01],\n       [ 2.820e+03,  3.546e+00, -1.452e+01],\n       [ 2.820e+03,  3.557e+00, -1.452e+01],\n       [ 2.820e+03,  3.567e+00, -1.452e+01],\n       [ 2.820e+03,  3.577e+00, -1.452e+01],\n       [ 2.820e+03,  3.588e+00, -1.452e+01],\n       [ 2.820e+03,  3.598e+00, -1.452e+01],\n       [ 2.820e+03,  3.608e+00, -1.452e+01],\n       [ 2.820e+03,  3.619e+00, -1.452e+01],\n       [ 2.820e+03,  3.629e+00, -1.452e+01],\n       [ 2.820e+03,  3.639e+00, -1.452e+01],\n       [ 2.820e+03,  3.650e+00, -1.452e+01],\n       [ 2.820e+03,  3.660e+00, -1.452e+01],\n       [ 2.820e+03,  3.670e+00, -1.452e+01],\n       [ 2.820e+03,  3.681e+00, -1.452e+01],\n       [ 2.820e+03,  3.691e+00, -1.452e+01],\n       [ 2.820e+03,  3.701e+00, -1.452e+01],\n       [ 2.820e+03,  3.712e+00, -1.452e+01],\n       [ 2.820e+03,  3.722e+00, -1.452e+01]]), array([[ 2.821e+03,  2.701e+00, -1.452e+01],\n       [ 2.821e+03,  2.711e+00, -1.452e+01],\n       [ 2.821e+03,  2.721e+00, -1.452e+01],\n       [ 2.821e+03,  2.732e+00, -1.452e+01],\n       [ 2.821e+03,  2.742e+00, -1.452e+01],\n       [ 2.821e+03,  2.752e+00, -1.452e+01],\n       [ 2.821e+03,  2.763e+00, -1.452e+01],\n       [ 2.821e+03,  2.773e+00, -1.452e+01],\n       [ 2.821e+03,  2.783e+00, -1.452e+01],\n       [ 2.821e+03,  2.794e+00, -1.452e+01],\n       [ 2.821e+03,  2.804e+00, -1.452e+01],\n       [ 2.821e+03,  2.814e+00, -1.452e+01],\n       [ 2.821e+03,  2.825e+00, -1.452e+01],\n       [ 2.821e+03,  2.835e+00, -1.452e+01],\n       [ 2.821e+03,  2.845e+00, 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3.072e+00, -1.452e+01],\n       [ 2.821e+03,  3.082e+00, -1.452e+01],\n       [ 2.821e+03,  3.093e+00, -1.452e+01],\n       [ 2.821e+03,  3.103e+00, -1.452e+01],\n       [ 2.821e+03,  3.113e+00, -1.452e+01],\n       [ 2.821e+03,  3.124e+00, -1.452e+01],\n       [ 2.821e+03,  3.134e+00, -1.452e+01],\n       [ 2.821e+03,  3.144e+00, -1.452e+01],\n       [ 2.821e+03,  3.155e+00, -1.452e+01],\n       [ 2.821e+03,  3.165e+00, -1.452e+01],\n       [ 2.821e+03,  3.175e+00, -1.452e+01],\n       [ 2.821e+03,  3.186e+00, -1.452e+01],\n       [ 2.821e+03,  3.196e+00, -1.452e+01],\n       [ 2.821e+03,  3.206e+00, -1.452e+01],\n       [ 2.821e+03,  3.216e+00, -1.452e+01],\n       [ 2.821e+03,  3.227e+00, -1.452e+01],\n       [ 2.821e+03,  3.237e+00, -1.452e+01],\n       [ 2.821e+03,  3.247e+00, -1.452e+01],\n       [ 2.821e+03,  3.258e+00, -1.452e+01],\n       [ 2.821e+03,  3.268e+00, -1.452e+01],\n       [ 2.821e+03,  3.278e+00, -1.452e+01],\n       [ 2.821e+03,  3.289e+00, -1.452e+01],\n       [ 2.821e+03,  3.299e+00, -1.452e+01],\n       [ 2.821e+03,  3.309e+00, -1.452e+01],\n       [ 2.821e+03,  3.320e+00, -1.452e+01],\n       [ 2.821e+03,  3.330e+00, -1.452e+01],\n       [ 2.821e+03,  3.340e+00, -1.452e+01],\n       [ 2.821e+03,  3.351e+00, -1.452e+01],\n       [ 2.821e+03,  3.361e+00, -1.452e+01],\n       [ 2.821e+03,  3.371e+00, -1.452e+01],\n       [ 2.821e+03,  3.381e+00, -1.452e+01],\n       [ 2.821e+03,  3.392e+00, -1.452e+01],\n       [ 2.821e+03,  3.402e+00, -1.452e+01],\n       [ 2.821e+03,  3.412e+00, -1.452e+01],\n       [ 2.821e+03,  3.423e+00, -1.452e+01],\n       [ 2.821e+03,  3.433e+00, -1.452e+01],\n       [ 2.821e+03,  3.443e+00, -1.452e+01],\n       [ 2.821e+03,  3.454e+00, -1.452e+01],\n       [ 2.821e+03,  3.464e+00, -1.452e+01],\n       [ 2.821e+03,  3.474e+00, -1.452e+01],\n       [ 2.821e+03,  3.485e+00, -1.452e+01],\n       [ 2.821e+03,  3.495e+00, -1.452e+01],\n       [ 2.821e+03,  3.505e+00, -1.452e+01],\n       [ 2.821e+03,  3.516e+00, -1.452e+01],\n       [ 2.821e+03,  3.526e+00, -1.452e+01],\n       [ 2.821e+03,  3.536e+00, -1.452e+01],\n       [ 2.821e+03,  3.546e+00, -1.452e+01],\n       [ 2.821e+03,  3.557e+00, -1.452e+01],\n       [ 2.821e+03,  3.567e+00, -1.452e+01],\n       [ 2.821e+03,  3.577e+00, -1.452e+01],\n       [ 2.821e+03,  3.588e+00, -1.452e+01],\n       [ 2.821e+03,  3.598e+00, -1.452e+01],\n       [ 2.821e+03,  3.608e+00, -1.452e+01],\n       [ 2.821e+03,  3.619e+00, -1.452e+01],\n       [ 2.821e+03,  3.629e+00, -1.452e+01],\n       [ 2.821e+03,  3.639e+00, -1.452e+01],\n       [ 2.821e+03,  3.650e+00, -1.452e+01],\n       [ 2.821e+03,  3.660e+00, -1.452e+01],\n       [ 2.821e+03,  3.670e+00, -1.452e+01],\n       [ 2.821e+03,  3.681e+00, -1.452e+01],\n       [ 2.821e+03,  3.691e+00, -1.452e+01],\n       [ 2.821e+03,  3.701e+00, -1.453e+01],\n       [ 2.821e+03,  3.712e+00, -1.453e+01],\n       [ 2.821e+03,  3.722e+00, -1.453e+01]]), array([[ 2.822e+03,  2.701e+00, -1.452e+01],\n       [ 2.822e+03, 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2.822e+03,  2.938e+00, -1.452e+01],\n       [ 2.822e+03,  2.948e+00, -1.452e+01],\n       [ 2.822e+03,  2.959e+00, -1.452e+01],\n       [ 2.822e+03,  2.969e+00, -1.452e+01],\n       [ 2.822e+03,  2.979e+00, -1.452e+01],\n       [ 2.822e+03,  2.990e+00, -1.452e+01],\n       [ 2.822e+03,  3.000e+00, -1.452e+01],\n       [ 2.822e+03,  3.010e+00, -1.452e+01],\n       [ 2.822e+03,  3.021e+00, -1.452e+01],\n       [ 2.822e+03,  3.031e+00, -1.452e+01],\n       [ 2.822e+03,  3.041e+00, -1.452e+01],\n       [ 2.822e+03,  3.051e+00, -1.452e+01],\n       [ 2.822e+03,  3.062e+00, -1.452e+01],\n       [ 2.822e+03,  3.072e+00, -1.452e+01],\n       [ 2.822e+03,  3.082e+00, -1.452e+01],\n       [ 2.822e+03,  3.093e+00, -1.452e+01],\n       [ 2.822e+03,  3.103e+00, -1.452e+01],\n       [ 2.822e+03,  3.113e+00, -1.452e+01],\n       [ 2.822e+03,  3.124e+00, -1.452e+01],\n       [ 2.822e+03,  3.134e+00, -1.452e+01],\n       [ 2.822e+03,  3.144e+00, -1.452e+01],\n       [ 2.822e+03,  3.155e+00, -1.452e+01],\n       [ 2.822e+03,  3.165e+00, -1.452e+01],\n       [ 2.822e+03,  3.175e+00, -1.452e+01],\n       [ 2.822e+03,  3.186e+00, -1.452e+01],\n       [ 2.822e+03,  3.196e+00, -1.452e+01],\n       [ 2.822e+03,  3.206e+00, -1.452e+01],\n       [ 2.822e+03,  3.216e+00, -1.452e+01],\n       [ 2.822e+03,  3.227e+00, -1.452e+01],\n       [ 2.822e+03,  3.237e+00, -1.452e+01],\n       [ 2.822e+03,  3.247e+00, -1.452e+01],\n       [ 2.822e+03,  3.258e+00, -1.452e+01],\n       [ 2.822e+03,  3.268e+00, -1.452e+01],\n       [ 2.822e+03,  3.278e+00, -1.452e+01],\n       [ 2.822e+03,  3.289e+00, -1.452e+01],\n       [ 2.822e+03,  3.299e+00, -1.452e+01],\n       [ 2.822e+03,  3.309e+00, -1.452e+01],\n       [ 2.822e+03,  3.320e+00, -1.452e+01],\n       [ 2.822e+03,  3.330e+00, -1.452e+01],\n       [ 2.822e+03,  3.340e+00, -1.452e+01],\n       [ 2.822e+03,  3.351e+00, -1.452e+01],\n       [ 2.822e+03,  3.361e+00, -1.452e+01],\n       [ 2.822e+03,  3.371e+00, -1.452e+01],\n       [ 2.822e+03,  3.381e+00, -1.452e+01],\n       [ 2.822e+03,  3.392e+00, -1.452e+01],\n       [ 2.822e+03,  3.402e+00, -1.452e+01],\n       [ 2.822e+03,  3.412e+00, -1.452e+01],\n       [ 2.822e+03,  3.423e+00, -1.452e+01],\n       [ 2.822e+03,  3.433e+00, -1.452e+01],\n       [ 2.822e+03,  3.443e+00, -1.452e+01],\n       [ 2.822e+03,  3.454e+00, -1.452e+01],\n       [ 2.822e+03,  3.464e+00, -1.452e+01],\n       [ 2.822e+03,  3.474e+00, -1.452e+01],\n       [ 2.822e+03,  3.485e+00, -1.452e+01],\n       [ 2.822e+03,  3.495e+00, -1.452e+01],\n       [ 2.822e+03,  3.505e+00, -1.452e+01],\n       [ 2.822e+03,  3.516e+00, -1.452e+01],\n       [ 2.822e+03,  3.526e+00, -1.452e+01],\n       [ 2.822e+03,  3.536e+00, -1.452e+01],\n       [ 2.822e+03,  3.546e+00, -1.452e+01],\n       [ 2.822e+03,  3.557e+00, -1.452e+01],\n       [ 2.822e+03,  3.567e+00, -1.452e+01],\n       [ 2.822e+03,  3.577e+00, -1.452e+01],\n       [ 2.822e+03,  3.588e+00, -1.452e+01],\n       [ 2.822e+03,  3.598e+00, -1.452e+01],\n       [ 2.822e+03,  3.608e+00, -1.452e+01],\n       [ 2.822e+03,  3.619e+00, -1.452e+01],\n       [ 2.822e+03,  3.629e+00, -1.452e+01],\n       [ 2.822e+03,  3.639e+00, -1.452e+01],\n       [ 2.822e+03,  3.650e+00, -1.452e+01],\n       [ 2.822e+03,  3.660e+00, -1.452e+01],\n       [ 2.822e+03,  3.670e+00, -1.452e+01],\n       [ 2.822e+03,  3.681e+00, -1.452e+01],\n       [ 2.822e+03,  3.691e+00, -1.452e+01],\n       [ 2.822e+03,  3.701e+00, -1.452e+01],\n       [ 2.822e+03,  3.712e+00, -1.452e+01],\n       [ 2.822e+03,  3.722e+00, -1.453e+01]]), array([[ 2.823e+03,  2.701e+00, -1.452e+01],\n       [ 2.823e+03,  2.711e+00, -1.452e+01],\n       [ 2.823e+03,  2.721e+00, -1.452e+01],\n       [ 2.823e+03,  2.732e+00, -1.452e+01],\n       [ 2.823e+03,  2.742e+00, -1.452e+01],\n       [ 2.823e+03,  2.752e+00, -1.452e+01],\n       [ 2.823e+03,  2.763e+00, -1.452e+01],\n       [ 2.823e+03,  2.773e+00, -1.452e+01],\n       [ 2.823e+03,  2.783e+00, -1.452e+01],\n       [ 2.823e+03,  2.794e+00, -1.452e+01],\n       [ 2.823e+03,  2.804e+00, -1.452e+01],\n       [ 2.823e+03,  2.814e+00, -1.452e+01],\n       [ 2.823e+03,  2.825e+00, -1.452e+01],\n       [ 2.823e+03,  2.835e+00, -1.452e+01],\n       [ 2.823e+03,  2.845e+00, -1.452e+01],\n       [ 2.823e+03,  2.856e+00, -1.452e+01],\n       [ 2.823e+03,  2.866e+00, -1.452e+01],\n       [ 2.823e+03,  2.876e+00, -1.452e+01],\n       [ 2.823e+03,  2.886e+00, -1.452e+01],\n       [ 2.823e+03,  2.897e+00, -1.452e+01],\n       [ 2.823e+03,  2.907e+00, -1.452e+01],\n       [ 2.823e+03,  2.917e+00, -1.452e+01],\n       [ 2.823e+03,  2.928e+00, -1.452e+01],\n       [ 2.823e+03,  2.938e+00, -1.452e+01],\n       [ 2.823e+03,  2.948e+00, -1.452e+01],\n       [ 2.823e+03,  2.959e+00, -1.452e+01],\n       [ 2.823e+03,  2.969e+00, -1.452e+01],\n       [ 2.823e+03,  2.979e+00, -1.452e+01],\n       [ 2.823e+03,  2.990e+00, -1.452e+01],\n       [ 2.823e+03,  3.000e+00, -1.452e+01],\n       [ 2.823e+03,  3.010e+00, -1.452e+01],\n       [ 2.823e+03,  3.021e+00, -1.452e+01],\n       [ 2.823e+03,  3.031e+00, -1.452e+01],\n       [ 2.823e+03,  3.041e+00, -1.452e+01],\n       [ 2.823e+03,  3.051e+00, -1.452e+01],\n       [ 2.823e+03,  3.062e+00, -1.452e+01],\n       [ 2.823e+03,  3.072e+00, -1.452e+01],\n       [ 2.823e+03,  3.082e+00, -1.452e+01],\n       [ 2.823e+03,  3.093e+00, -1.452e+01],\n       [ 2.823e+03,  3.103e+00, -1.452e+01],\n       [ 2.823e+03,  3.113e+00, -1.452e+01],\n       [ 2.823e+03,  3.124e+00, -1.452e+01],\n       [ 2.823e+03,  3.134e+00, -1.452e+01],\n       [ 2.823e+03,  3.144e+00, -1.452e+01],\n       [ 2.823e+03,  3.155e+00, -1.452e+01],\n       [ 2.823e+03,  3.165e+00, -1.452e+01],\n       [ 2.823e+03,  3.175e+00, -1.452e+01],\n       [ 2.823e+03,  3.186e+00, -1.452e+01],\n       [ 2.823e+03,  3.196e+00, -1.452e+01],\n       [ 2.823e+03,  3.206e+00, -1.452e+01],\n       [ 2.823e+03,  3.216e+00, -1.452e+01],\n       [ 2.823e+03,  3.227e+00, -1.452e+01],\n       [ 2.823e+03,  3.237e+00, -1.452e+01],\n       [ 2.823e+03,  3.247e+00, -1.452e+01],\n       [ 2.823e+03,  3.258e+00, -1.452e+01],\n       [ 2.823e+03,  3.268e+00, -1.452e+01],\n       [ 2.823e+03,  3.278e+00, -1.452e+01],\n       [ 2.823e+03,  3.289e+00, -1.452e+01],\n       [ 2.823e+03,  3.299e+00, -1.452e+01],\n       [ 2.823e+03,  3.309e+00, -1.452e+01],\n       [ 2.823e+03,  3.320e+00, -1.452e+01],\n       [ 2.823e+03,  3.330e+00, -1.452e+01],\n       [ 2.823e+03,  3.340e+00, -1.452e+01],\n       [ 2.823e+03,  3.351e+00, -1.452e+01],\n       [ 2.823e+03,  3.361e+00, -1.452e+01],\n       [ 2.823e+03,  3.371e+00, -1.452e+01],\n       [ 2.823e+03,  3.381e+00, -1.452e+01],\n       [ 2.823e+03,  3.392e+00, -1.452e+01],\n       [ 2.823e+03,  3.402e+00, -1.452e+01],\n       [ 2.823e+03,  3.412e+00, -1.452e+01],\n       [ 2.823e+03,  3.423e+00, -1.452e+01],\n       [ 2.823e+03,  3.433e+00, -1.452e+01],\n       [ 2.823e+03,  3.443e+00, -1.452e+01],\n       [ 2.823e+03,  3.454e+00, -1.452e+01],\n       [ 2.823e+03,  3.464e+00, -1.452e+01],\n       [ 2.823e+03,  3.474e+00, -1.452e+01],\n       [ 2.823e+03,  3.485e+00, -1.452e+01],\n       [ 2.823e+03,  3.495e+00, -1.452e+01],\n       [ 2.823e+03,  3.505e+00, -1.452e+01],\n       [ 2.823e+03,  3.516e+00, -1.452e+01],\n       [ 2.823e+03,  3.526e+00, -1.452e+01],\n       [ 2.823e+03,  3.536e+00, -1.452e+01],\n       [ 2.823e+03,  3.546e+00, -1.452e+01],\n       [ 2.823e+03,  3.557e+00, -1.452e+01],\n       [ 2.823e+03,  3.567e+00, -1.452e+01],\n       [ 2.823e+03,  3.577e+00, -1.452e+01],\n       [ 2.823e+03,  3.588e+00, -1.452e+01],\n       [ 2.823e+03,  3.598e+00, -1.452e+01],\n       [ 2.823e+03,  3.608e+00, -1.452e+01],\n       [ 2.823e+03,  3.619e+00, -1.452e+01],\n       [ 2.823e+03,  3.629e+00, -1.452e+01],\n       [ 2.823e+03,  3.639e+00, -1.452e+01],\n       [ 2.823e+03,  3.650e+00, -1.452e+01],\n       [ 2.823e+03,  3.660e+00, -1.452e+01],\n       [ 2.823e+03,  3.670e+00, -1.452e+01],\n       [ 2.823e+03,  3.681e+00, -1.452e+01],\n       [ 2.823e+03,  3.691e+00, -1.452e+01],\n       [ 2.823e+03,  3.701e+00, -1.452e+01],\n       [ 2.823e+03,  3.712e+00, -1.453e+01],\n       [ 2.823e+03,  3.722e+00, -1.453e+01]]), array([[ 2.824e+03,  2.701e+00, -1.452e+01],\n       [ 2.824e+03,  2.711e+00, -1.452e+01],\n       [ 2.824e+03,  2.721e+00, -1.452e+01],\n       [ 2.824e+03,  2.732e+00, -1.452e+01],\n       [ 2.824e+03,  2.742e+00, -1.452e+01],\n       [ 2.824e+03,  2.752e+00, -1.452e+01],\n       [ 2.824e+03,  2.763e+00, -1.452e+01],\n       [ 2.824e+03,  2.773e+00, -1.452e+01],\n       [ 2.824e+03,  2.783e+00, -1.452e+01],\n       [ 2.824e+03,  2.794e+00, -1.452e+01],\n       [ 2.824e+03,  2.804e+00, -1.452e+01],\n       [ 2.824e+03,  2.814e+00, -1.452e+01],\n       [ 2.824e+03,  2.825e+00, -1.452e+01],\n       [ 2.824e+03,  2.835e+00, -1.452e+01],\n       [ 2.824e+03,  2.845e+00, -1.452e+01],\n       [ 2.824e+03,  2.856e+00, -1.452e+01],\n       [ 2.824e+03,  2.866e+00, -1.452e+01],\n       [ 2.824e+03,  2.876e+00, -1.452e+01],\n       [ 2.824e+03,  2.886e+00, -1.452e+01],\n       [ 2.824e+03,  2.897e+00, -1.452e+01],\n       [ 2.824e+03,  2.907e+00, -1.452e+01],\n       [ 2.824e+03,  2.917e+00, -1.452e+01],\n       [ 2.824e+03,  2.928e+00, -1.452e+01],\n       [ 2.824e+03,  2.938e+00, -1.452e+01],\n       [ 2.824e+03,  2.948e+00, -1.452e+01],\n       [ 2.824e+03,  2.959e+00, -1.452e+01],\n       [ 2.824e+03,  2.969e+00, -1.452e+01],\n       [ 2.824e+03,  2.979e+00, -1.452e+01],\n       [ 2.824e+03,  2.990e+00, -1.452e+01],\n       [ 2.824e+03,  3.000e+00, -1.452e+01],\n       [ 2.824e+03,  3.010e+00, -1.452e+01],\n       [ 2.824e+03,  3.021e+00, -1.452e+01],\n       [ 2.824e+03,  3.031e+00, -1.452e+01],\n       [ 2.824e+03,  3.041e+00, -1.452e+01],\n       [ 2.824e+03,  3.051e+00, -1.452e+01],\n       [ 2.824e+03,  3.062e+00, -1.452e+01],\n       [ 2.824e+03,  3.072e+00, -1.452e+01],\n       [ 2.824e+03,  3.082e+00, -1.452e+01],\n       [ 2.824e+03,  3.093e+00, -1.452e+01],\n       [ 2.824e+03,  3.103e+00, 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3.330e+00, -1.452e+01],\n       [ 2.824e+03,  3.340e+00, -1.452e+01],\n       [ 2.824e+03,  3.351e+00, -1.452e+01],\n       [ 2.824e+03,  3.361e+00, -1.452e+01],\n       [ 2.824e+03,  3.371e+00, -1.452e+01],\n       [ 2.824e+03,  3.381e+00, -1.452e+01],\n       [ 2.824e+03,  3.392e+00, -1.452e+01],\n       [ 2.824e+03,  3.402e+00, -1.452e+01],\n       [ 2.824e+03,  3.412e+00, -1.452e+01],\n       [ 2.824e+03,  3.423e+00, -1.452e+01],\n       [ 2.824e+03,  3.433e+00, -1.452e+01],\n       [ 2.824e+03,  3.443e+00, -1.452e+01],\n       [ 2.824e+03,  3.454e+00, -1.452e+01],\n       [ 2.824e+03,  3.464e+00, -1.452e+01],\n       [ 2.824e+03,  3.474e+00, -1.452e+01],\n       [ 2.824e+03,  3.485e+00, -1.452e+01],\n       [ 2.824e+03,  3.495e+00, -1.452e+01],\n       [ 2.824e+03,  3.505e+00, -1.452e+01],\n       [ 2.824e+03,  3.516e+00, -1.452e+01],\n       [ 2.824e+03,  3.526e+00, -1.452e+01],\n       [ 2.824e+03,  3.536e+00, -1.452e+01],\n       [ 2.824e+03,  3.546e+00, -1.452e+01],\n       [ 2.824e+03,  3.557e+00, -1.452e+01],\n       [ 2.824e+03,  3.567e+00, -1.452e+01],\n       [ 2.824e+03,  3.577e+00, -1.452e+01],\n       [ 2.824e+03,  3.588e+00, -1.452e+01],\n       [ 2.824e+03,  3.598e+00, -1.452e+01],\n       [ 2.824e+03,  3.608e+00, -1.452e+01],\n       [ 2.824e+03,  3.619e+00, -1.452e+01],\n       [ 2.824e+03,  3.629e+00, -1.452e+01],\n       [ 2.824e+03,  3.639e+00, -1.452e+01],\n       [ 2.824e+03,  3.650e+00, -1.452e+01],\n       [ 2.824e+03,  3.660e+00, -1.452e+01],\n       [ 2.824e+03,  3.670e+00, -1.452e+01],\n       [ 2.824e+03,  3.681e+00, -1.452e+01],\n       [ 2.824e+03,  3.691e+00, -1.453e+01],\n       [ 2.824e+03,  3.701e+00, -1.453e+01],\n       [ 2.824e+03,  3.712e+00, -1.453e+01],\n       [ 2.824e+03,  3.722e+00, -1.453e+01]]), array([[ 2.825e+03,  2.701e+00, -1.452e+01],\n       [ 2.825e+03,  2.711e+00, -1.452e+01],\n       [ 2.825e+03,  2.721e+00, -1.452e+01],\n       [ 2.825e+03,  2.732e+00, -1.452e+01],\n       [ 2.825e+03,  2.742e+00, 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2.969e+00, -1.452e+01],\n       [ 2.825e+03,  2.979e+00, -1.452e+01],\n       [ 2.825e+03,  2.989e+00, -1.452e+01],\n       [ 2.825e+03,  2.999e+00, -1.452e+01],\n       [ 2.825e+03,  3.010e+00, -1.452e+01],\n       [ 2.825e+03,  3.020e+00, -1.452e+01],\n       [ 2.825e+03,  3.030e+00, -1.452e+01],\n       [ 2.825e+03,  3.041e+00, -1.452e+01],\n       [ 2.825e+03,  3.051e+00, -1.452e+01],\n       [ 2.825e+03,  3.061e+00, -1.452e+01],\n       [ 2.825e+03,  3.071e+00, -1.452e+01],\n       [ 2.825e+03,  3.082e+00, -1.452e+01],\n       [ 2.825e+03,  3.092e+00, -1.452e+01],\n       [ 2.825e+03,  3.102e+00, -1.452e+01],\n       [ 2.825e+03,  3.113e+00, -1.452e+01],\n       [ 2.825e+03,  3.123e+00, -1.452e+01],\n       [ 2.825e+03,  3.133e+00, -1.452e+01],\n       [ 2.825e+03,  3.144e+00, -1.452e+01],\n       [ 2.825e+03,  3.154e+00, -1.452e+01],\n       [ 2.825e+03,  3.164e+00, -1.452e+01],\n       [ 2.825e+03,  3.174e+00, -1.452e+01],\n       [ 2.825e+03,  3.185e+00, -1.452e+01],\n       [ 2.825e+03,  3.195e+00, -1.452e+01],\n       [ 2.825e+03,  3.205e+00, -1.452e+01],\n       [ 2.825e+03,  3.216e+00, -1.452e+01],\n       [ 2.825e+03,  3.226e+00, -1.452e+01],\n       [ 2.825e+03,  3.236e+00, -1.452e+01],\n       [ 2.825e+03,  3.246e+00, -1.452e+01],\n       [ 2.825e+03,  3.257e+00, -1.452e+01],\n       [ 2.825e+03,  3.267e+00, -1.452e+01],\n       [ 2.825e+03,  3.277e+00, -1.452e+01],\n       [ 2.825e+03,  3.288e+00, -1.452e+01],\n       [ 2.825e+03,  3.298e+00, -1.452e+01],\n       [ 2.825e+03,  3.308e+00, -1.452e+01],\n       [ 2.825e+03,  3.319e+00, -1.452e+01],\n       [ 2.825e+03,  3.329e+00, -1.452e+01],\n       [ 2.825e+03,  3.339e+00, -1.452e+01],\n       [ 2.825e+03,  3.349e+00, -1.452e+01],\n       [ 2.825e+03,  3.360e+00, -1.452e+01],\n       [ 2.825e+03,  3.370e+00, -1.452e+01],\n       [ 2.825e+03,  3.380e+00, -1.452e+01],\n       [ 2.825e+03,  3.391e+00, -1.452e+01],\n       [ 2.825e+03,  3.401e+00, -1.452e+01],\n       [ 2.825e+03,  3.411e+00, 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3.638e+00, -1.452e+01],\n       [ 2.825e+03,  3.648e+00, -1.452e+01],\n       [ 2.825e+03,  3.658e+00, -1.452e+01],\n       [ 2.825e+03,  3.669e+00, -1.452e+01],\n       [ 2.825e+03,  3.679e+00, -1.452e+01],\n       [ 2.825e+03,  3.689e+00, -1.452e+01],\n       [ 2.825e+03,  3.700e+00, -1.452e+01],\n       [ 2.825e+03,  3.710e+00, -1.453e+01],\n       [ 2.825e+03,  3.720e+00, -1.453e+01]]), array([[ 2.826e+03,  2.701e+00, -1.452e+01],\n       [ 2.826e+03,  2.711e+00, -1.452e+01],\n       [ 2.826e+03,  2.721e+00, -1.452e+01],\n       [ 2.826e+03,  2.732e+00, -1.452e+01],\n       [ 2.826e+03,  2.742e+00, -1.452e+01],\n       [ 2.826e+03,  2.752e+00, -1.452e+01],\n       [ 2.826e+03,  2.763e+00, -1.452e+01],\n       [ 2.826e+03,  2.773e+00, -1.452e+01],\n       [ 2.826e+03,  2.783e+00, -1.452e+01],\n       [ 2.826e+03,  2.794e+00, -1.452e+01],\n       [ 2.826e+03,  2.804e+00, -1.452e+01],\n       [ 2.826e+03,  2.814e+00, -1.452e+01],\n       [ 2.826e+03,  2.825e+00, -1.452e+01],\n       [ 2.826e+03,  2.835e+00, -1.452e+01],\n       [ 2.826e+03,  2.845e+00, -1.452e+01],\n       [ 2.826e+03,  2.856e+00, -1.452e+01],\n       [ 2.826e+03,  2.866e+00, -1.452e+01],\n       [ 2.826e+03,  2.876e+00, -1.452e+01],\n       [ 2.826e+03,  2.886e+00, -1.452e+01],\n       [ 2.826e+03,  2.897e+00, -1.452e+01],\n       [ 2.826e+03,  2.907e+00, -1.452e+01],\n       [ 2.826e+03,  2.917e+00, -1.452e+01],\n       [ 2.826e+03,  2.928e+00, -1.452e+01],\n       [ 2.826e+03,  2.938e+00, -1.452e+01],\n       [ 2.826e+03,  2.948e+00, -1.452e+01],\n       [ 2.826e+03,  2.959e+00, -1.452e+01],\n       [ 2.826e+03,  2.969e+00, -1.452e+01],\n       [ 2.826e+03,  2.979e+00, -1.452e+01],\n       [ 2.826e+03,  2.990e+00, -1.452e+01],\n       [ 2.826e+03,  3.000e+00, -1.452e+01],\n       [ 2.826e+03,  3.010e+00, -1.452e+01],\n       [ 2.826e+03,  3.021e+00, -1.452e+01],\n       [ 2.826e+03,  3.031e+00, -1.452e+01],\n       [ 2.826e+03,  3.041e+00, -1.452e+01],\n       [ 2.826e+03,  3.051e+00, -1.452e+01],\n       [ 2.826e+03,  3.062e+00, -1.452e+01],\n       [ 2.826e+03,  3.072e+00, -1.452e+01],\n       [ 2.826e+03,  3.082e+00, -1.452e+01],\n       [ 2.826e+03,  3.093e+00, -1.452e+01],\n       [ 2.826e+03,  3.103e+00, -1.452e+01],\n       [ 2.826e+03,  3.113e+00, -1.452e+01],\n       [ 2.826e+03,  3.124e+00, -1.452e+01],\n       [ 2.826e+03,  3.134e+00, -1.452e+01],\n       [ 2.826e+03,  3.144e+00, -1.452e+01],\n       [ 2.826e+03,  3.155e+00, -1.452e+01],\n       [ 2.826e+03,  3.165e+00, -1.452e+01],\n       [ 2.826e+03,  3.175e+00, -1.452e+01],\n       [ 2.826e+03,  3.186e+00, -1.452e+01],\n       [ 2.826e+03,  3.196e+00, -1.452e+01],\n       [ 2.826e+03,  3.206e+00, -1.452e+01],\n       [ 2.826e+03,  3.216e+00, -1.452e+01],\n       [ 2.826e+03,  3.227e+00, -1.452e+01],\n       [ 2.826e+03,  3.237e+00, -1.452e+01],\n       [ 2.826e+03,  3.247e+00, -1.452e+01],\n       [ 2.826e+03,  3.258e+00, -1.452e+01],\n       [ 2.826e+03,  3.268e+00, -1.452e+01],\n       [ 2.826e+03,  3.278e+00, -1.452e+01],\n       [ 2.826e+03,  3.289e+00, -1.452e+01],\n       [ 2.826e+03,  3.299e+00, -1.452e+01],\n       [ 2.826e+03,  3.309e+00, -1.452e+01],\n       [ 2.826e+03,  3.320e+00, -1.452e+01],\n       [ 2.826e+03,  3.330e+00, -1.452e+01],\n       [ 2.826e+03,  3.340e+00, -1.452e+01],\n       [ 2.826e+03,  3.351e+00, -1.452e+01],\n       [ 2.826e+03,  3.361e+00, -1.452e+01],\n       [ 2.826e+03,  3.371e+00, -1.452e+01],\n       [ 2.826e+03,  3.381e+00, -1.452e+01],\n       [ 2.826e+03,  3.392e+00, -1.452e+01],\n       [ 2.826e+03,  3.402e+00, -1.452e+01],\n       [ 2.826e+03,  3.412e+00, -1.452e+01],\n       [ 2.826e+03,  3.423e+00, -1.452e+01],\n       [ 2.826e+03,  3.433e+00, -1.452e+01],\n       [ 2.826e+03,  3.443e+00, -1.452e+01],\n       [ 2.826e+03,  3.454e+00, -1.452e+01],\n       [ 2.826e+03,  3.464e+00, -1.452e+01],\n       [ 2.826e+03,  3.474e+00, -1.452e+01],\n       [ 2.826e+03,  3.485e+00, -1.452e+01],\n       [ 2.826e+03,  3.495e+00, -1.452e+01],\n       [ 2.826e+03,  3.505e+00, -1.452e+01],\n       [ 2.826e+03,  3.516e+00, -1.452e+01],\n       [ 2.826e+03,  3.526e+00, -1.452e+01],\n       [ 2.826e+03,  3.536e+00, -1.452e+01],\n       [ 2.826e+03,  3.546e+00, -1.452e+01],\n       [ 2.826e+03,  3.557e+00, -1.452e+01],\n       [ 2.826e+03,  3.567e+00, -1.452e+01],\n       [ 2.826e+03,  3.577e+00, -1.452e+01],\n       [ 2.826e+03,  3.588e+00, -1.452e+01],\n       [ 2.826e+03,  3.598e+00, -1.452e+01],\n       [ 2.826e+03,  3.608e+00, -1.452e+01],\n       [ 2.826e+03,  3.619e+00, -1.452e+01],\n       [ 2.826e+03,  3.629e+00, -1.452e+01],\n       [ 2.826e+03,  3.639e+00, -1.452e+01],\n       [ 2.826e+03,  3.650e+00, -1.452e+01],\n       [ 2.826e+03,  3.660e+00, -1.452e+01],\n       [ 2.826e+03,  3.670e+00, -1.452e+01],\n       [ 2.826e+03,  3.681e+00, -1.452e+01],\n       [ 2.826e+03,  3.691e+00, -1.452e+01],\n       [ 2.826e+03,  3.701e+00, -1.452e+01],\n       [ 2.826e+03,  3.712e+00, -1.452e+01],\n       [ 2.826e+03,  3.722e+00, -1.452e+01]]), array([[ 2.827e+03,  2.701e+00, -1.452e+01],\n       [ 2.827e+03,  2.711e+00, -1.452e+01],\n       [ 2.827e+03,  2.721e+00, -1.452e+01],\n       [ 2.827e+03,  2.732e+00, -1.452e+01],\n       [ 2.827e+03,  2.742e+00, -1.452e+01],\n       [ 2.827e+03,  2.752e+00, -1.452e+01],\n       [ 2.827e+03,  2.763e+00, -1.452e+01],\n       [ 2.827e+03,  2.773e+00, -1.452e+01],\n       [ 2.827e+03,  2.783e+00, -1.452e+01],\n       [ 2.827e+03,  2.793e+00, -1.452e+01],\n       [ 2.827e+03,  2.804e+00, -1.452e+01],\n       [ 2.827e+03,  2.814e+00, -1.452e+01],\n       [ 2.827e+03,  2.824e+00, -1.452e+01],\n       [ 2.827e+03,  2.835e+00, -1.452e+01],\n       [ 2.827e+03,  2.845e+00, -1.452e+01],\n       [ 2.827e+03,  2.855e+00, -1.452e+01],\n       [ 2.827e+03,  2.866e+00, -1.452e+01],\n       [ 2.827e+03,  2.876e+00, -1.452e+01],\n       [ 2.827e+03,  2.886e+00, -1.452e+01],\n       [ 2.827e+03,  2.896e+00, -1.452e+01],\n       [ 2.827e+03,  2.907e+00, -1.452e+01],\n       [ 2.827e+03, 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2.827e+03,  3.144e+00, -1.452e+01],\n       [ 2.827e+03,  3.154e+00, -1.452e+01],\n       [ 2.827e+03,  3.164e+00, -1.452e+01],\n       [ 2.827e+03,  3.174e+00, -1.452e+01],\n       [ 2.827e+03,  3.185e+00, -1.452e+01],\n       [ 2.827e+03,  3.195e+00, -1.452e+01],\n       [ 2.827e+03,  3.205e+00, -1.452e+01],\n       [ 2.827e+03,  3.216e+00, -1.452e+01],\n       [ 2.827e+03,  3.226e+00, -1.452e+01],\n       [ 2.827e+03,  3.236e+00, -1.452e+01],\n       [ 2.827e+03,  3.246e+00, -1.452e+01],\n       [ 2.827e+03,  3.257e+00, -1.452e+01],\n       [ 2.827e+03,  3.267e+00, -1.452e+01],\n       [ 2.827e+03,  3.277e+00, -1.452e+01],\n       [ 2.827e+03,  3.288e+00, -1.452e+01],\n       [ 2.827e+03,  3.298e+00, -1.452e+01],\n       [ 2.827e+03,  3.308e+00, -1.452e+01],\n       [ 2.827e+03,  3.319e+00, -1.452e+01],\n       [ 2.827e+03,  3.329e+00, -1.452e+01],\n       [ 2.827e+03,  3.339e+00, -1.452e+01],\n       [ 2.827e+03,  3.349e+00, -1.452e+01],\n       [ 2.827e+03,  3.360e+00, -1.452e+01],\n       [ 2.827e+03,  3.370e+00, -1.452e+01],\n       [ 2.827e+03,  3.380e+00, -1.452e+01],\n       [ 2.827e+03,  3.391e+00, -1.452e+01],\n       [ 2.827e+03,  3.401e+00, -1.452e+01],\n       [ 2.827e+03,  3.411e+00, -1.452e+01],\n       [ 2.827e+03,  3.422e+00, -1.452e+01],\n       [ 2.827e+03,  3.432e+00, -1.452e+01],\n       [ 2.827e+03,  3.442e+00, -1.452e+01],\n       [ 2.827e+03,  3.452e+00, -1.452e+01],\n       [ 2.827e+03,  3.463e+00, -1.452e+01],\n       [ 2.827e+03,  3.473e+00, -1.452e+01],\n       [ 2.827e+03,  3.483e+00, -1.452e+01],\n       [ 2.827e+03,  3.494e+00, -1.452e+01],\n       [ 2.827e+03,  3.504e+00, -1.452e+01],\n       [ 2.827e+03,  3.514e+00, -1.452e+01],\n       [ 2.827e+03,  3.524e+00, -1.452e+01],\n       [ 2.827e+03,  3.535e+00, -1.452e+01],\n       [ 2.827e+03,  3.545e+00, -1.452e+01],\n       [ 2.827e+03,  3.555e+00, -1.452e+01],\n       [ 2.827e+03,  3.566e+00, -1.452e+01],\n       [ 2.827e+03,  3.576e+00, -1.452e+01],\n       [ 2.827e+03,  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-1.452e+01],\n       [ 3.895e+03,  3.241e+00, -1.452e+01],\n       [ 3.895e+03,  3.248e+00, -1.452e+01],\n       [ 3.895e+03,  3.255e+00, -1.452e+01],\n       [ 3.895e+03,  3.262e+00, -1.452e+01],\n       [ 3.895e+03,  3.269e+00, -1.452e+01],\n       [ 3.895e+03,  3.275e+00, -1.452e+01],\n       [ 3.895e+03,  3.282e+00, -1.452e+01],\n       [ 3.895e+03,  3.289e+00, -1.452e+01],\n       [ 3.895e+03,  3.296e+00, -1.452e+01],\n       [ 3.895e+03,  3.303e+00, -1.452e+01],\n       [ 3.895e+03,  3.310e+00, -1.452e+01],\n       [ 3.895e+03,  3.317e+00, -1.452e+01],\n       [ 3.895e+03,  3.323e+00, -1.452e+01],\n       [ 3.895e+03,  3.330e+00, -1.452e+01],\n       [ 3.895e+03,  3.337e+00, -1.452e+01],\n       [ 3.895e+03,  3.344e+00, -1.452e+01],\n       [ 3.895e+03,  3.351e+00, -1.452e+01],\n       [ 3.895e+03,  3.358e+00, -1.452e+01],\n       [ 3.895e+03,  3.364e+00, -1.452e+01],\n       [ 3.895e+03,  3.371e+00, -1.452e+01],\n       [ 3.895e+03,  3.378e+00, -1.453e+01]]), array([[ 3.896e+03, 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3.896e+03,  2.851e+00, -1.452e+01],\n       [ 3.896e+03,  2.858e+00, -1.452e+01],\n       [ 3.896e+03,  2.865e+00, -1.452e+01],\n       [ 3.896e+03,  2.872e+00, -1.452e+01],\n       [ 3.896e+03,  2.879e+00, -1.452e+01],\n       [ 3.896e+03,  2.886e+00, -1.452e+01],\n       [ 3.896e+03,  2.892e+00, -1.452e+01],\n       [ 3.896e+03,  2.899e+00, -1.452e+01],\n       [ 3.896e+03,  2.906e+00, -1.452e+01],\n       [ 3.896e+03,  2.913e+00, -1.452e+01],\n       [ 3.896e+03,  2.920e+00, -1.452e+01],\n       [ 3.896e+03,  2.927e+00, -1.452e+01],\n       [ 3.896e+03,  2.933e+00, -1.452e+01],\n       [ 3.896e+03,  2.940e+00, -1.452e+01],\n       [ 3.896e+03,  2.947e+00, -1.452e+01],\n       [ 3.896e+03,  2.954e+00, -1.452e+01],\n       [ 3.896e+03,  2.961e+00, -1.452e+01],\n       [ 3.896e+03,  2.968e+00, -1.452e+01],\n       [ 3.896e+03,  2.974e+00, -1.452e+01],\n       [ 3.896e+03,  2.981e+00, -1.452e+01],\n       [ 3.896e+03,  2.988e+00, -1.452e+01],\n       [ 3.896e+03,  2.995e+00, 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3.145e+00, -1.452e+01],\n       [ 3.896e+03,  3.152e+00, -1.452e+01],\n       [ 3.896e+03,  3.159e+00, -1.452e+01],\n       [ 3.896e+03,  3.166e+00, -1.452e+01],\n       [ 3.896e+03,  3.173e+00, -1.452e+01],\n       [ 3.896e+03,  3.180e+00, -1.452e+01],\n       [ 3.896e+03,  3.187e+00, -1.452e+01],\n       [ 3.896e+03,  3.193e+00, -1.452e+01],\n       [ 3.896e+03,  3.200e+00, -1.452e+01],\n       [ 3.896e+03,  3.207e+00, -1.452e+01],\n       [ 3.896e+03,  3.214e+00, -1.452e+01],\n       [ 3.896e+03,  3.221e+00, -1.452e+01],\n       [ 3.896e+03,  3.228e+00, -1.452e+01],\n       [ 3.896e+03,  3.234e+00, -1.452e+01],\n       [ 3.896e+03,  3.241e+00, -1.452e+01],\n       [ 3.896e+03,  3.248e+00, -1.452e+01],\n       [ 3.896e+03,  3.255e+00, -1.452e+01],\n       [ 3.896e+03,  3.262e+00, -1.452e+01],\n       [ 3.896e+03,  3.269e+00, -1.452e+01],\n       [ 3.896e+03,  3.275e+00, -1.452e+01],\n       [ 3.896e+03,  3.282e+00, -1.452e+01],\n       [ 3.896e+03,  3.289e+00, -1.452e+01],\n       [ 3.896e+03,  3.296e+00, -1.452e+01],\n       [ 3.896e+03,  3.303e+00, -1.452e+01],\n       [ 3.896e+03,  3.310e+00, -1.452e+01],\n       [ 3.896e+03,  3.317e+00, -1.452e+01],\n       [ 3.896e+03,  3.323e+00, -1.452e+01],\n       [ 3.896e+03,  3.330e+00, -1.452e+01],\n       [ 3.896e+03,  3.337e+00, -1.452e+01],\n       [ 3.896e+03,  3.344e+00, -1.452e+01],\n       [ 3.896e+03,  3.351e+00, -1.452e+01],\n       [ 3.896e+03,  3.358e+00, -1.452e+01],\n       [ 3.896e+03,  3.364e+00, -1.452e+01],\n       [ 3.896e+03,  3.371e+00, -1.453e+01],\n       [ 3.896e+03,  3.378e+00, -1.453e+01]]), array([[ 3.897e+03,  2.701e+00, -1.452e+01],\n       [ 3.897e+03,  2.708e+00, -1.452e+01],\n       [ 3.897e+03,  2.714e+00, -1.452e+01],\n       [ 3.897e+03,  2.721e+00, -1.452e+01],\n       [ 3.897e+03,  2.728e+00, -1.452e+01],\n       [ 3.897e+03,  2.735e+00, -1.452e+01],\n       [ 3.897e+03,  2.742e+00, -1.452e+01],\n       [ 3.897e+03,  2.749e+00, -1.452e+01],\n       [ 3.897e+03,  2.756e+00, -1.452e+01],\n       [ 3.897e+03,  2.762e+00, -1.452e+01],\n       [ 3.897e+03,  2.769e+00, -1.452e+01],\n       [ 3.897e+03,  2.776e+00, -1.452e+01],\n       [ 3.897e+03,  2.783e+00, -1.452e+01],\n       [ 3.897e+03,  2.790e+00, -1.452e+01],\n       [ 3.897e+03,  2.797e+00, -1.452e+01],\n       [ 3.897e+03,  2.803e+00, -1.452e+01],\n       [ 3.897e+03,  2.810e+00, -1.452e+01],\n       [ 3.897e+03,  2.817e+00, -1.452e+01],\n       [ 3.897e+03,  2.824e+00, -1.452e+01],\n       [ 3.897e+03,  2.831e+00, -1.452e+01],\n       [ 3.897e+03,  2.838e+00, -1.452e+01],\n       [ 3.897e+03,  2.844e+00, -1.452e+01],\n       [ 3.897e+03,  2.851e+00, -1.452e+01],\n       [ 3.897e+03,  2.858e+00, -1.452e+01],\n       [ 3.897e+03,  2.865e+00, -1.452e+01],\n       [ 3.897e+03,  2.872e+00, -1.452e+01],\n       [ 3.897e+03,  2.879e+00, -1.452e+01],\n       [ 3.897e+03,  2.886e+00, -1.452e+01],\n       [ 3.897e+03,  2.892e+00, -1.452e+01],\n       [ 3.897e+03,  2.899e+00, -1.452e+01],\n       [ 3.897e+03,  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3.897e+03,  3.057e+00, -1.452e+01],\n       [ 3.897e+03,  3.063e+00, -1.452e+01],\n       [ 3.897e+03,  3.070e+00, -1.452e+01],\n       [ 3.897e+03,  3.077e+00, -1.452e+01],\n       [ 3.897e+03,  3.084e+00, -1.452e+01],\n       [ 3.897e+03,  3.091e+00, -1.452e+01],\n       [ 3.897e+03,  3.098e+00, -1.452e+01],\n       [ 3.897e+03,  3.104e+00, -1.452e+01],\n       [ 3.897e+03,  3.111e+00, -1.452e+01],\n       [ 3.897e+03,  3.118e+00, -1.452e+01],\n       [ 3.897e+03,  3.125e+00, -1.452e+01],\n       [ 3.897e+03,  3.132e+00, -1.452e+01],\n       [ 3.897e+03,  3.139e+00, -1.452e+01],\n       [ 3.897e+03,  3.145e+00, -1.452e+01],\n       [ 3.897e+03,  3.152e+00, -1.452e+01],\n       [ 3.897e+03,  3.159e+00, -1.452e+01],\n       [ 3.897e+03,  3.166e+00, -1.452e+01],\n       [ 3.897e+03,  3.173e+00, -1.452e+01],\n       [ 3.897e+03,  3.180e+00, -1.452e+01],\n       [ 3.897e+03,  3.187e+00, -1.452e+01],\n       [ 3.897e+03,  3.193e+00, -1.452e+01],\n       [ 3.897e+03,  3.200e+00, -1.452e+01],\n       [ 3.897e+03,  3.207e+00, -1.452e+01],\n       [ 3.897e+03,  3.214e+00, -1.452e+01],\n       [ 3.897e+03,  3.221e+00, -1.452e+01],\n       [ 3.897e+03,  3.228e+00, -1.452e+01],\n       [ 3.897e+03,  3.234e+00, -1.452e+01],\n       [ 3.897e+03,  3.241e+00, -1.452e+01],\n       [ 3.897e+03,  3.248e+00, -1.452e+01],\n       [ 3.897e+03,  3.255e+00, -1.452e+01],\n       [ 3.897e+03,  3.262e+00, -1.452e+01],\n       [ 3.897e+03,  3.269e+00, -1.452e+01],\n       [ 3.897e+03,  3.275e+00, -1.452e+01],\n       [ 3.897e+03,  3.282e+00, -1.452e+01],\n       [ 3.897e+03,  3.289e+00, -1.452e+01],\n       [ 3.897e+03,  3.296e+00, -1.452e+01],\n       [ 3.897e+03,  3.303e+00, -1.452e+01],\n       [ 3.897e+03,  3.310e+00, -1.452e+01],\n       [ 3.897e+03,  3.317e+00, -1.452e+01],\n       [ 3.897e+03,  3.323e+00, -1.452e+01],\n       [ 3.897e+03,  3.330e+00, -1.452e+01],\n       [ 3.897e+03,  3.337e+00, -1.452e+01],\n       [ 3.897e+03,  3.344e+00, -1.452e+01],\n       [ 3.897e+03,  3.351e+00, -1.452e+01],\n       [ 3.897e+03,  3.358e+00, -1.452e+01],\n       [ 3.897e+03,  3.364e+00, -1.452e+01],\n       [ 3.897e+03,  3.371e+00, -1.452e+01],\n       [ 3.897e+03,  3.378e+00, -1.453e+01]]), array([[ 3.898e+03,  2.701e+00, -1.452e+01],\n       [ 3.898e+03,  2.708e+00, -1.452e+01],\n       [ 3.898e+03,  2.714e+00, -1.452e+01],\n       [ 3.898e+03,  2.721e+00, -1.452e+01],\n       [ 3.898e+03,  2.728e+00, -1.452e+01],\n       [ 3.898e+03,  2.735e+00, -1.452e+01],\n       [ 3.898e+03,  2.742e+00, -1.452e+01],\n       [ 3.898e+03,  2.749e+00, -1.452e+01],\n       [ 3.898e+03,  2.756e+00, -1.452e+01],\n       [ 3.898e+03,  2.762e+00, -1.452e+01],\n       [ 3.898e+03,  2.769e+00, -1.452e+01],\n       [ 3.898e+03,  2.776e+00, -1.452e+01],\n       [ 3.898e+03,  2.783e+00, -1.452e+01],\n       [ 3.898e+03,  2.790e+00, -1.452e+01],\n       [ 3.898e+03,  2.797e+00, -1.452e+01],\n       [ 3.898e+03,  2.803e+00, -1.452e+01],\n       [ 3.898e+03,  2.810e+00, -1.452e+01],\n       [ 3.898e+03,  2.817e+00, -1.452e+01],\n       [ 3.898e+03,  2.824e+00, -1.452e+01],\n       [ 3.898e+03,  2.831e+00, -1.452e+01],\n       [ 3.898e+03,  2.838e+00, -1.452e+01],\n       [ 3.898e+03,  2.844e+00, -1.452e+01],\n       [ 3.898e+03,  2.851e+00, -1.452e+01],\n       [ 3.898e+03,  2.858e+00, -1.452e+01],\n       [ 3.898e+03,  2.865e+00, -1.452e+01],\n       [ 3.898e+03,  2.872e+00, -1.452e+01],\n       [ 3.898e+03,  2.879e+00, -1.452e+01],\n       [ 3.898e+03,  2.886e+00, -1.452e+01],\n       [ 3.898e+03,  2.892e+00, -1.452e+01],\n       [ 3.898e+03,  2.899e+00, -1.452e+01],\n       [ 3.898e+03,  2.906e+00, -1.452e+01],\n       [ 3.898e+03,  2.913e+00, -1.452e+01],\n       [ 3.898e+03,  2.920e+00, -1.452e+01],\n       [ 3.898e+03,  2.927e+00, -1.452e+01],\n       [ 3.898e+03,  2.933e+00, -1.452e+01],\n       [ 3.898e+03,  2.940e+00, -1.452e+01],\n       [ 3.898e+03,  2.947e+00, -1.452e+01],\n       [ 3.898e+03,  2.954e+00, -1.452e+01],\n       [ 3.898e+03,  2.961e+00, 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3.111e+00, -1.452e+01],\n       [ 3.898e+03,  3.118e+00, -1.452e+01],\n       [ 3.898e+03,  3.125e+00, -1.452e+01],\n       [ 3.898e+03,  3.132e+00, -1.452e+01],\n       [ 3.898e+03,  3.139e+00, -1.452e+01],\n       [ 3.898e+03,  3.145e+00, -1.452e+01],\n       [ 3.898e+03,  3.152e+00, -1.452e+01],\n       [ 3.898e+03,  3.159e+00, -1.452e+01],\n       [ 3.898e+03,  3.166e+00, -1.452e+01],\n       [ 3.898e+03,  3.173e+00, -1.452e+01],\n       [ 3.898e+03,  3.180e+00, -1.452e+01],\n       [ 3.898e+03,  3.187e+00, -1.452e+01],\n       [ 3.898e+03,  3.193e+00, -1.452e+01],\n       [ 3.898e+03,  3.200e+00, -1.452e+01],\n       [ 3.898e+03,  3.207e+00, -1.452e+01],\n       [ 3.898e+03,  3.214e+00, -1.452e+01],\n       [ 3.898e+03,  3.221e+00, -1.452e+01],\n       [ 3.898e+03,  3.228e+00, -1.452e+01],\n       [ 3.898e+03,  3.234e+00, -1.452e+01],\n       [ 3.898e+03,  3.241e+00, -1.452e+01],\n       [ 3.898e+03,  3.248e+00, -1.452e+01],\n       [ 3.898e+03,  3.255e+00, -1.452e+01],\n       [ 3.898e+03,  3.262e+00, -1.452e+01],\n       [ 3.898e+03,  3.269e+00, -1.452e+01],\n       [ 3.898e+03,  3.275e+00, -1.452e+01],\n       [ 3.898e+03,  3.282e+00, -1.452e+01],\n       [ 3.898e+03,  3.289e+00, -1.452e+01],\n       [ 3.898e+03,  3.296e+00, -1.452e+01],\n       [ 3.898e+03,  3.303e+00, -1.452e+01],\n       [ 3.898e+03,  3.310e+00, -1.452e+01],\n       [ 3.898e+03,  3.317e+00, -1.452e+01],\n       [ 3.898e+03,  3.323e+00, -1.452e+01],\n       [ 3.898e+03,  3.330e+00, -1.452e+01],\n       [ 3.898e+03,  3.337e+00, -1.452e+01],\n       [ 3.898e+03,  3.344e+00, -1.452e+01],\n       [ 3.898e+03,  3.351e+00, -1.452e+01],\n       [ 3.898e+03,  3.358e+00, -1.452e+01],\n       [ 3.898e+03,  3.364e+00, -1.452e+01],\n       [ 3.898e+03,  3.371e+00, -1.453e+01],\n       [ 3.898e+03,  3.378e+00, -1.453e+01]]), array([[ 3.899e+03,  2.701e+00, -1.452e+01],\n       [ 3.899e+03,  2.708e+00, -1.452e+01],\n       [ 3.899e+03,  2.714e+00, -1.452e+01],\n       [ 3.899e+03,  2.721e+00, 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3.317e+00, -1.452e+01],\n       [ 3.899e+03,  3.323e+00, -1.452e+01],\n       [ 3.899e+03,  3.330e+00, -1.452e+01],\n       [ 3.899e+03,  3.337e+00, -1.452e+01],\n       [ 3.899e+03,  3.344e+00, -1.452e+01],\n       [ 3.899e+03,  3.351e+00, -1.452e+01],\n       [ 3.899e+03,  3.358e+00, -1.452e+01],\n       [ 3.899e+03,  3.364e+00, -1.452e+01],\n       [ 3.899e+03,  3.371e+00, -1.452e+01],\n       [ 3.899e+03,  3.378e+00, -1.453e+01]]), array([[ 3.900e+03,  2.701e+00, -1.452e+01],\n       [ 3.900e+03,  2.708e+00, -1.452e+01],\n       [ 3.900e+03,  2.714e+00, -1.452e+01],\n       [ 3.900e+03,  2.721e+00, -1.452e+01],\n       [ 3.900e+03,  2.728e+00, -1.452e+01],\n       [ 3.900e+03,  2.735e+00, -1.452e+01],\n       [ 3.900e+03,  2.742e+00, -1.452e+01],\n       [ 3.900e+03,  2.749e+00, -1.452e+01],\n       [ 3.900e+03,  2.756e+00, -1.452e+01],\n       [ 3.900e+03,  2.762e+00, -1.452e+01],\n       [ 3.900e+03,  2.769e+00, -1.452e+01],\n       [ 3.900e+03,  2.776e+00, -1.452e+01],\n       [ 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3.900e+03,  3.228e+00, -1.452e+01],\n       [ 3.900e+03,  3.234e+00, -1.452e+01],\n       [ 3.900e+03,  3.241e+00, -1.452e+01],\n       [ 3.900e+03,  3.248e+00, -1.452e+01],\n       [ 3.900e+03,  3.255e+00, -1.452e+01],\n       [ 3.900e+03,  3.262e+00, -1.452e+01],\n       [ 3.900e+03,  3.269e+00, -1.452e+01],\n       [ 3.900e+03,  3.275e+00, -1.452e+01],\n       [ 3.900e+03,  3.282e+00, -1.452e+01],\n       [ 3.900e+03,  3.289e+00, -1.452e+01],\n       [ 3.900e+03,  3.296e+00, -1.452e+01],\n       [ 3.900e+03,  3.303e+00, -1.452e+01],\n       [ 3.900e+03,  3.310e+00, -1.452e+01],\n       [ 3.900e+03,  3.317e+00, -1.452e+01],\n       [ 3.900e+03,  3.323e+00, -1.452e+01],\n       [ 3.900e+03,  3.330e+00, -1.452e+01],\n       [ 3.900e+03,  3.337e+00, -1.452e+01],\n       [ 3.900e+03,  3.344e+00, -1.452e+01],\n       [ 3.900e+03,  3.351e+00, -1.452e+01],\n       [ 3.900e+03,  3.358e+00, -1.452e+01],\n       [ 3.900e+03,  3.364e+00, -1.452e+01],\n       [ 3.900e+03,  3.371e+00, -1.452e+01],\n       [ 3.900e+03,  3.378e+00, -1.453e+01]]), array([[ 3.901e+03,  2.701e+00, -1.452e+01],\n       [ 3.901e+03,  2.708e+00, -1.452e+01],\n       [ 3.901e+03,  2.714e+00, -1.452e+01],\n       [ 3.901e+03,  2.721e+00, -1.452e+01],\n       [ 3.901e+03,  2.728e+00, -1.452e+01],\n       [ 3.901e+03,  2.735e+00, -1.452e+01],\n       [ 3.901e+03,  2.742e+00, -1.452e+01],\n       [ 3.901e+03,  2.749e+00, -1.452e+01],\n       [ 3.901e+03,  2.756e+00, -1.452e+01],\n       [ 3.901e+03,  2.762e+00, -1.452e+01],\n       [ 3.901e+03,  2.769e+00, -1.452e+01],\n       [ 3.901e+03,  2.776e+00, -1.452e+01],\n       [ 3.901e+03,  2.783e+00, -1.452e+01],\n       [ 3.901e+03,  2.790e+00, -1.452e+01],\n       [ 3.901e+03,  2.797e+00, -1.452e+01],\n       [ 3.901e+03,  2.803e+00, -1.452e+01],\n       [ 3.901e+03,  2.810e+00, -1.452e+01],\n       [ 3.901e+03,  2.817e+00, -1.452e+01],\n       [ 3.901e+03,  2.824e+00, -1.452e+01],\n       [ 3.901e+03,  2.831e+00, -1.452e+01],\n       [ 3.901e+03,  2.838e+00, -1.452e+01],\n       [ 3.901e+03,  2.844e+00, -1.452e+01],\n       [ 3.901e+03,  2.851e+00, -1.452e+01],\n       [ 3.901e+03,  2.858e+00, -1.452e+01],\n       [ 3.901e+03,  2.865e+00, -1.452e+01],\n       [ 3.901e+03,  2.872e+00, -1.452e+01],\n       [ 3.901e+03,  2.879e+00, -1.452e+01],\n       [ 3.901e+03,  2.886e+00, -1.452e+01],\n       [ 3.901e+03,  2.892e+00, -1.452e+01],\n       [ 3.901e+03,  2.899e+00, -1.452e+01],\n       [ 3.901e+03,  2.906e+00, -1.452e+01],\n       [ 3.901e+03,  2.913e+00, -1.452e+01],\n       [ 3.901e+03,  2.920e+00, -1.452e+01],\n       [ 3.901e+03,  2.927e+00, -1.452e+01],\n       [ 3.901e+03,  2.933e+00, -1.452e+01],\n       [ 3.901e+03,  2.940e+00, -1.452e+01],\n       [ 3.901e+03,  2.947e+00, -1.452e+01],\n       [ 3.901e+03,  2.954e+00, -1.452e+01],\n       [ 3.901e+03,  2.961e+00, -1.452e+01],\n       [ 3.901e+03,  2.968e+00, -1.452e+01],\n       [ 3.901e+03,  2.974e+00, -1.452e+01],\n       [ 3.901e+03,  2.981e+00, -1.452e+01],\n       [ 3.901e+03,  2.988e+00, -1.452e+01],\n       [ 3.901e+03,  2.995e+00, -1.452e+01],\n       [ 3.901e+03,  3.002e+00, -1.452e+01],\n       [ 3.901e+03,  3.009e+00, -1.452e+01],\n       [ 3.901e+03,  3.015e+00, -1.452e+01],\n       [ 3.901e+03,  3.022e+00, -1.452e+01],\n       [ 3.901e+03,  3.029e+00, -1.452e+01],\n       [ 3.901e+03,  3.036e+00, -1.452e+01],\n       [ 3.901e+03,  3.043e+00, -1.452e+01],\n       [ 3.901e+03,  3.050e+00, -1.452e+01],\n       [ 3.901e+03,  3.057e+00, -1.452e+01],\n       [ 3.901e+03,  3.063e+00, -1.452e+01],\n       [ 3.901e+03,  3.070e+00, -1.452e+01],\n       [ 3.901e+03,  3.077e+00, -1.452e+01],\n       [ 3.901e+03,  3.084e+00, -1.452e+01],\n       [ 3.901e+03,  3.091e+00, -1.452e+01],\n       [ 3.901e+03,  3.098e+00, -1.452e+01],\n       [ 3.901e+03,  3.104e+00, -1.452e+01],\n       [ 3.901e+03,  3.111e+00, -1.452e+01],\n       [ 3.901e+03,  3.118e+00, -1.452e+01],\n       [ 3.901e+03,  3.125e+00, -1.452e+01],\n       [ 3.901e+03,  3.132e+00, -1.452e+01],\n       [ 3.901e+03,  3.139e+00, -1.452e+01],\n       [ 3.901e+03,  3.145e+00, -1.452e+01],\n       [ 3.901e+03,  3.152e+00, -1.452e+01],\n       [ 3.901e+03,  3.159e+00, -1.452e+01],\n       [ 3.901e+03,  3.166e+00, -1.452e+01],\n       [ 3.901e+03,  3.173e+00, -1.452e+01],\n       [ 3.901e+03,  3.180e+00, -1.452e+01],\n       [ 3.901e+03,  3.187e+00, -1.452e+01],\n       [ 3.901e+03,  3.193e+00, -1.452e+01],\n       [ 3.901e+03,  3.200e+00, -1.452e+01],\n       [ 3.901e+03,  3.207e+00, -1.452e+01],\n       [ 3.901e+03,  3.214e+00, -1.452e+01],\n       [ 3.901e+03,  3.221e+00, -1.452e+01],\n       [ 3.901e+03,  3.228e+00, -1.452e+01],\n       [ 3.901e+03,  3.234e+00, -1.452e+01],\n       [ 3.901e+03,  3.241e+00, -1.452e+01],\n       [ 3.901e+03,  3.248e+00, -1.452e+01],\n       [ 3.901e+03,  3.255e+00, -1.452e+01],\n       [ 3.901e+03,  3.262e+00, -1.452e+01],\n       [ 3.901e+03,  3.269e+00, -1.452e+01],\n       [ 3.901e+03,  3.275e+00, -1.452e+01],\n       [ 3.901e+03,  3.282e+00, -1.452e+01],\n       [ 3.901e+03,  3.289e+00, -1.452e+01],\n       [ 3.901e+03,  3.296e+00, -1.452e+01],\n       [ 3.901e+03,  3.303e+00, -1.452e+01],\n       [ 3.901e+03,  3.310e+00, -1.452e+01],\n       [ 3.901e+03,  3.317e+00, -1.452e+01],\n       [ 3.901e+03,  3.323e+00, -1.452e+01],\n       [ 3.901e+03,  3.330e+00, -1.452e+01],\n       [ 3.901e+03,  3.337e+00, -1.452e+01],\n       [ 3.901e+03,  3.344e+00, -1.452e+01],\n       [ 3.901e+03,  3.351e+00, -1.452e+01],\n       [ 3.901e+03,  3.358e+00, -1.452e+01],\n       [ 3.901e+03,  3.364e+00, -1.452e+01],\n       [ 3.901e+03,  3.371e+00, -1.452e+01],\n       [ 3.901e+03,  3.378e+00, -1.452e+01]]), array([[ 3.902e+03,  2.701e+00, -1.452e+01],\n       [ 3.902e+03,  2.708e+00, -1.452e+01],\n       [ 3.902e+03,  2.714e+00, -1.452e+01],\n       [ 3.902e+03,  2.721e+00, -1.452e+01],\n       [ 3.902e+03,  2.728e+00, -1.452e+01],\n       [ 3.902e+03,  2.735e+00, -1.452e+01],\n       [ 3.902e+03,  2.742e+00, -1.452e+01],\n       [ 3.902e+03,  2.749e+00, -1.452e+01],\n       [ 3.902e+03,  2.756e+00, -1.452e+01],\n       [ 3.902e+03,  2.762e+00, -1.452e+01],\n       [ 3.902e+03,  2.769e+00, -1.452e+01],\n       [ 3.902e+03,  2.776e+00, -1.452e+01],\n       [ 3.902e+03,  2.783e+00, -1.452e+01],\n       [ 3.902e+03,  2.790e+00, -1.452e+01],\n       [ 3.902e+03,  2.797e+00, -1.452e+01],\n       [ 3.902e+03,  2.803e+00, -1.452e+01],\n       [ 3.902e+03,  2.810e+00, -1.452e+01],\n       [ 3.902e+03,  2.817e+00, -1.452e+01],\n       [ 3.902e+03,  2.824e+00, -1.452e+01],\n       [ 3.902e+03,  2.831e+00, -1.452e+01],\n       [ 3.902e+03,  2.838e+00, -1.452e+01],\n       [ 3.902e+03,  2.844e+00, -1.452e+01],\n       [ 3.902e+03,  2.851e+00, -1.452e+01],\n       [ 3.902e+03,  2.858e+00, -1.452e+01],\n       [ 3.902e+03,  2.865e+00, -1.452e+01],\n       [ 3.902e+03,  2.872e+00, -1.452e+01],\n       [ 3.902e+03,  2.879e+00, -1.452e+01],\n       [ 3.902e+03,  2.886e+00, -1.452e+01],\n       [ 3.902e+03,  2.892e+00, -1.452e+01],\n       [ 3.902e+03,  2.899e+00, -1.452e+01],\n       [ 3.902e+03,  2.906e+00, -1.452e+01],\n       [ 3.902e+03,  2.913e+00, -1.452e+01],\n       [ 3.902e+03,  2.920e+00, -1.452e+01],\n       [ 3.902e+03,  2.927e+00, -1.452e+01],\n       [ 3.902e+03,  2.933e+00, -1.452e+01],\n       [ 3.902e+03,  2.940e+00, -1.452e+01],\n       [ 3.902e+03,  2.947e+00, -1.452e+01],\n       [ 3.902e+03,  2.954e+00, -1.452e+01],\n       [ 3.902e+03,  2.961e+00, -1.452e+01],\n       [ 3.902e+03,  2.968e+00, -1.452e+01],\n       [ 3.902e+03,  2.974e+00, -1.452e+01],\n       [ 3.902e+03,  2.981e+00, -1.452e+01],\n       [ 3.902e+03,  2.988e+00, -1.452e+01],\n       [ 3.902e+03,  2.995e+00, -1.452e+01],\n       [ 3.902e+03,  3.002e+00, -1.452e+01],\n       [ 3.902e+03,  3.009e+00, -1.452e+01],\n       [ 3.902e+03,  3.015e+00, -1.452e+01],\n       [ 3.902e+03,  3.022e+00, -1.452e+01],\n       [ 3.902e+03,  3.029e+00, -1.452e+01],\n       [ 3.902e+03,  3.036e+00, -1.452e+01],\n       [ 3.902e+03,  3.043e+00, -1.452e+01],\n       [ 3.902e+03,  3.050e+00, -1.452e+01],\n       [ 3.902e+03,  3.057e+00, -1.452e+01],\n       [ 3.902e+03,  3.063e+00, -1.452e+01],\n       [ 3.902e+03,  3.070e+00, -1.452e+01],\n       [ 3.902e+03,  3.077e+00, -1.452e+01],\n       [ 3.902e+03,  3.084e+00, -1.452e+01],\n       [ 3.902e+03,  3.091e+00, -1.452e+01],\n       [ 3.902e+03,  3.098e+00, -1.452e+01],\n       [ 3.902e+03,  3.104e+00, -1.452e+01],\n       [ 3.902e+03,  3.111e+00, -1.452e+01],\n       [ 3.902e+03,  3.118e+00, -1.452e+01],\n       [ 3.902e+03,  3.125e+00, -1.452e+01],\n       [ 3.902e+03,  3.132e+00, -1.452e+01],\n       [ 3.902e+03,  3.139e+00, -1.452e+01],\n       [ 3.902e+03,  3.145e+00, -1.452e+01],\n       [ 3.902e+03,  3.152e+00, -1.452e+01],\n       [ 3.902e+03,  3.159e+00, -1.452e+01],\n       [ 3.902e+03,  3.166e+00, -1.452e+01],\n       [ 3.902e+03,  3.173e+00, -1.452e+01],\n       [ 3.902e+03,  3.180e+00, -1.452e+01],\n       [ 3.902e+03,  3.187e+00, -1.452e+01],\n       [ 3.902e+03,  3.193e+00, -1.452e+01],\n       [ 3.902e+03,  3.200e+00, -1.452e+01],\n       [ 3.902e+03,  3.207e+00, -1.452e+01],\n       [ 3.902e+03,  3.214e+00, -1.452e+01],\n       [ 3.902e+03,  3.221e+00, -1.452e+01],\n       [ 3.902e+03,  3.228e+00, -1.452e+01],\n       [ 3.902e+03,  3.234e+00, -1.452e+01],\n       [ 3.902e+03,  3.241e+00, -1.452e+01],\n       [ 3.902e+03,  3.248e+00, -1.452e+01],\n       [ 3.902e+03,  3.255e+00, -1.452e+01],\n       [ 3.902e+03,  3.262e+00, -1.452e+01],\n       [ 3.902e+03,  3.269e+00, -1.452e+01],\n       [ 3.902e+03,  3.275e+00, -1.452e+01],\n       [ 3.902e+03,  3.282e+00, -1.452e+01],\n       [ 3.902e+03,  3.289e+00, -1.452e+01],\n       [ 3.902e+03,  3.296e+00, -1.452e+01],\n       [ 3.902e+03,  3.303e+00, -1.452e+01],\n       [ 3.902e+03,  3.310e+00, -1.452e+01],\n       [ 3.902e+03,  3.317e+00, -1.452e+01],\n       [ 3.902e+03,  3.323e+00, -1.452e+01],\n       [ 3.902e+03,  3.330e+00, -1.452e+01],\n       [ 3.902e+03,  3.337e+00, -1.452e+01],\n       [ 3.902e+03,  3.344e+00, -1.452e+01],\n       [ 3.902e+03,  3.351e+00, -1.452e+01],\n       [ 3.902e+03,  3.358e+00, -1.452e+01],\n       [ 3.902e+03,  3.364e+00, -1.452e+01],\n       [ 3.902e+03,  3.371e+00, -1.452e+01],\n       [ 3.902e+03,  3.378e+00, -1.453e+01]]), array([[ 3.903e+03,  2.701e+00, -1.452e+01],\n       [ 3.903e+03,  2.708e+00, -1.452e+01],\n       [ 3.903e+03,  2.714e+00, -1.452e+01],\n       [ 3.903e+03,  2.721e+00, -1.452e+01],\n       [ 3.903e+03,  2.728e+00, -1.452e+01],\n       [ 3.903e+03,  2.735e+00, -1.452e+01],\n       [ 3.903e+03,  2.742e+00, -1.452e+01],\n       [ 3.903e+03,  2.749e+00, -1.452e+01],\n       [ 3.903e+03,  2.756e+00, -1.452e+01],\n       [ 3.903e+03,  2.762e+00, -1.452e+01],\n       [ 3.903e+03,  2.769e+00, -1.452e+01],\n       [ 3.903e+03,  2.776e+00, -1.452e+01],\n       [ 3.903e+03,  2.783e+00, -1.452e+01],\n       [ 3.903e+03,  2.790e+00, -1.452e+01],\n       [ 3.903e+03,  2.797e+00, -1.452e+01],\n       [ 3.903e+03, 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3.903e+03,  2.954e+00, -1.452e+01],\n       [ 3.903e+03,  2.961e+00, -1.452e+01],\n       [ 3.903e+03,  2.968e+00, -1.452e+01],\n       [ 3.903e+03,  2.974e+00, -1.452e+01],\n       [ 3.903e+03,  2.981e+00, -1.452e+01],\n       [ 3.903e+03,  2.988e+00, -1.452e+01],\n       [ 3.903e+03,  2.995e+00, -1.452e+01],\n       [ 3.903e+03,  3.002e+00, -1.452e+01],\n       [ 3.903e+03,  3.009e+00, -1.452e+01],\n       [ 3.903e+03,  3.015e+00, -1.452e+01],\n       [ 3.903e+03,  3.022e+00, -1.452e+01],\n       [ 3.903e+03,  3.029e+00, -1.452e+01],\n       [ 3.903e+03,  3.036e+00, -1.452e+01],\n       [ 3.903e+03,  3.043e+00, -1.452e+01],\n       [ 3.903e+03,  3.050e+00, -1.452e+01],\n       [ 3.903e+03,  3.057e+00, -1.452e+01],\n       [ 3.903e+03,  3.063e+00, -1.452e+01],\n       [ 3.903e+03,  3.070e+00, -1.452e+01],\n       [ 3.903e+03,  3.077e+00, -1.452e+01],\n       [ 3.903e+03,  3.084e+00, -1.452e+01],\n       [ 3.903e+03,  3.091e+00, -1.452e+01],\n       [ 3.903e+03,  3.098e+00, -1.452e+01],\n       [ 3.903e+03,  3.104e+00, -1.452e+01],\n       [ 3.903e+03,  3.111e+00, -1.452e+01],\n       [ 3.903e+03,  3.118e+00, -1.452e+01],\n       [ 3.903e+03,  3.125e+00, -1.452e+01],\n       [ 3.903e+03,  3.132e+00, -1.452e+01],\n       [ 3.903e+03,  3.139e+00, -1.452e+01],\n       [ 3.903e+03,  3.145e+00, -1.452e+01],\n       [ 3.903e+03,  3.152e+00, -1.452e+01],\n       [ 3.903e+03,  3.159e+00, -1.452e+01],\n       [ 3.903e+03,  3.166e+00, -1.452e+01],\n       [ 3.903e+03,  3.173e+00, -1.452e+01],\n       [ 3.903e+03,  3.180e+00, -1.452e+01],\n       [ 3.903e+03,  3.187e+00, -1.452e+01],\n       [ 3.903e+03,  3.193e+00, -1.452e+01],\n       [ 3.903e+03,  3.200e+00, -1.452e+01],\n       [ 3.903e+03,  3.207e+00, -1.452e+01],\n       [ 3.903e+03,  3.214e+00, -1.452e+01],\n       [ 3.903e+03,  3.221e+00, -1.452e+01],\n       [ 3.903e+03,  3.228e+00, -1.452e+01],\n       [ 3.903e+03,  3.234e+00, -1.452e+01],\n       [ 3.903e+03,  3.241e+00, -1.452e+01],\n       [ 3.903e+03,  3.248e+00, -1.452e+01],\n       [ 3.903e+03,  3.255e+00, -1.452e+01],\n       [ 3.903e+03,  3.262e+00, -1.452e+01],\n       [ 3.903e+03,  3.269e+00, -1.452e+01],\n       [ 3.903e+03,  3.275e+00, -1.452e+01],\n       [ 3.903e+03,  3.282e+00, -1.452e+01],\n       [ 3.903e+03,  3.289e+00, -1.452e+01],\n       [ 3.903e+03,  3.296e+00, -1.452e+01],\n       [ 3.903e+03,  3.303e+00, -1.452e+01],\n       [ 3.903e+03,  3.310e+00, -1.452e+01],\n       [ 3.903e+03,  3.317e+00, -1.452e+01],\n       [ 3.903e+03,  3.323e+00, -1.452e+01],\n       [ 3.903e+03,  3.330e+00, -1.452e+01],\n       [ 3.903e+03,  3.337e+00, -1.452e+01],\n       [ 3.903e+03,  3.344e+00, -1.452e+01],\n       [ 3.903e+03,  3.351e+00, -1.452e+01],\n       [ 3.903e+03,  3.358e+00, -1.452e+01],\n       [ 3.903e+03,  3.364e+00, -1.452e+01],\n       [ 3.903e+03,  3.371e+00, -1.452e+01],\n       [ 3.903e+03,  3.378e+00, -1.453e+01]]), array([[ 3.904e+03,  2.701e+00, -1.452e+01],\n       [ 3.904e+03,  2.708e+00, -1.452e+01],\n       [ 3.904e+03,  2.714e+00, -1.452e+01],\n       [ 3.904e+03,  2.721e+00, -1.452e+01],\n       [ 3.904e+03,  2.728e+00, -1.452e+01],\n       [ 3.904e+03,  2.735e+00, -1.452e+01],\n       [ 3.904e+03,  2.742e+00, -1.452e+01],\n       [ 3.904e+03,  2.749e+00, -1.452e+01],\n       [ 3.904e+03,  2.756e+00, -1.452e+01],\n       [ 3.904e+03,  2.762e+00, -1.452e+01],\n       [ 3.904e+03,  2.769e+00, -1.452e+01],\n       [ 3.904e+03,  2.776e+00, -1.452e+01],\n       [ 3.904e+03,  2.783e+00, -1.452e+01],\n       [ 3.904e+03,  2.790e+00, -1.452e+01],\n       [ 3.904e+03,  2.797e+00, -1.452e+01],\n       [ 3.904e+03,  2.803e+00, -1.452e+01],\n       [ 3.904e+03,  2.810e+00, -1.452e+01],\n       [ 3.904e+03,  2.817e+00, -1.452e+01],\n       [ 3.904e+03,  2.824e+00, -1.452e+01],\n       [ 3.904e+03,  2.831e+00, -1.452e+01],\n       [ 3.904e+03,  2.838e+00, -1.452e+01],\n       [ 3.904e+03,  2.844e+00, -1.452e+01],\n       [ 3.904e+03,  2.851e+00, -1.452e+01],\n       [ 3.904e+03,  2.858e+00, -1.452e+01],\n       [ 3.904e+03,  2.865e+00, -1.452e+01],\n       [ 3.904e+03,  2.872e+00, -1.452e+01],\n       [ 3.904e+03,  2.879e+00, -1.452e+01],\n       [ 3.904e+03,  2.886e+00, -1.452e+01],\n       [ 3.904e+03,  2.892e+00, -1.452e+01],\n       [ 3.904e+03,  2.899e+00, -1.452e+01],\n       [ 3.904e+03,  2.906e+00, -1.452e+01],\n       [ 3.904e+03,  2.913e+00, -1.452e+01],\n       [ 3.904e+03,  2.920e+00, -1.452e+01],\n       [ 3.904e+03,  2.927e+00, -1.452e+01],\n       [ 3.904e+03,  2.933e+00, -1.452e+01],\n       [ 3.904e+03,  2.940e+00, -1.452e+01],\n       [ 3.904e+03,  2.947e+00, -1.452e+01],\n       [ 3.904e+03,  2.954e+00, -1.452e+01],\n       [ 3.904e+03,  2.961e+00, -1.452e+01],\n       [ 3.904e+03,  2.968e+00, -1.452e+01],\n       [ 3.904e+03,  2.974e+00, -1.452e+01],\n       [ 3.904e+03,  2.981e+00, -1.452e+01],\n       [ 3.904e+03,  2.988e+00, -1.452e+01],\n       [ 3.904e+03,  2.995e+00, -1.452e+01],\n       [ 3.904e+03,  3.002e+00, -1.452e+01],\n       [ 3.904e+03,  3.009e+00, -1.452e+01],\n       [ 3.904e+03,  3.015e+00, -1.452e+01],\n       [ 3.904e+03,  3.022e+00, -1.452e+01],\n       [ 3.904e+03,  3.029e+00, -1.452e+01],\n       [ 3.904e+03,  3.036e+00, -1.452e+01],\n       [ 3.904e+03,  3.043e+00, -1.452e+01],\n       [ 3.904e+03,  3.050e+00, -1.452e+01],\n       [ 3.904e+03,  3.057e+00, -1.452e+01],\n       [ 3.904e+03,  3.063e+00, -1.452e+01],\n       [ 3.904e+03,  3.070e+00, -1.452e+01],\n       [ 3.904e+03,  3.077e+00, -1.452e+01],\n       [ 3.904e+03,  3.084e+00, -1.452e+01],\n       [ 3.904e+03,  3.091e+00, -1.452e+01],\n       [ 3.904e+03,  3.098e+00, -1.452e+01],\n       [ 3.904e+03,  3.104e+00, -1.452e+01],\n       [ 3.904e+03,  3.111e+00, -1.452e+01],\n       [ 3.904e+03,  3.118e+00, -1.452e+01],\n       [ 3.904e+03,  3.125e+00, -1.452e+01],\n       [ 3.904e+03,  3.132e+00, -1.452e+01],\n       [ 3.904e+03,  3.139e+00, -1.452e+01],\n       [ 3.904e+03,  3.145e+00, -1.452e+01],\n       [ 3.904e+03,  3.152e+00, -1.452e+01],\n       [ 3.904e+03,  3.159e+00, -1.452e+01],\n       [ 3.904e+03,  3.166e+00, -1.452e+01],\n       [ 3.904e+03,  3.173e+00, -1.452e+01],\n       [ 3.904e+03,  3.180e+00, -1.452e+01],\n       [ 3.904e+03,  3.187e+00, -1.452e+01],\n       [ 3.904e+03,  3.193e+00, -1.452e+01],\n       [ 3.904e+03,  3.200e+00, -1.452e+01],\n       [ 3.904e+03,  3.207e+00, -1.452e+01],\n       [ 3.904e+03,  3.214e+00, -1.452e+01],\n       [ 3.904e+03,  3.221e+00, -1.452e+01],\n       [ 3.904e+03,  3.228e+00, -1.452e+01],\n       [ 3.904e+03,  3.234e+00, -1.452e+01],\n       [ 3.904e+03,  3.241e+00, -1.452e+01],\n       [ 3.904e+03,  3.248e+00, -1.452e+01],\n       [ 3.904e+03,  3.255e+00, -1.452e+01],\n       [ 3.904e+03,  3.262e+00, -1.452e+01],\n       [ 3.904e+03,  3.269e+00, -1.452e+01],\n       [ 3.904e+03,  3.275e+00, -1.452e+01],\n       [ 3.904e+03,  3.282e+00, -1.452e+01],\n       [ 3.904e+03,  3.289e+00, -1.452e+01],\n       [ 3.904e+03,  3.296e+00, -1.452e+01],\n       [ 3.904e+03,  3.303e+00, -1.452e+01],\n       [ 3.904e+03,  3.310e+00, -1.452e+01],\n       [ 3.904e+03,  3.317e+00, -1.452e+01],\n       [ 3.904e+03,  3.323e+00, -1.452e+01],\n       [ 3.904e+03,  3.330e+00, -1.452e+01],\n       [ 3.904e+03,  3.337e+00, -1.452e+01],\n       [ 3.904e+03,  3.344e+00, -1.452e+01],\n       [ 3.904e+03,  3.351e+00, -1.452e+01],\n       [ 3.904e+03,  3.358e+00, -1.452e+01],\n       [ 3.904e+03,  3.364e+00, -1.452e+01],\n       [ 3.904e+03,  3.371e+00, -1.452e+01],\n       [ 3.904e+03,  3.378e+00, -1.453e+01]]), array([[ 3.905e+03,  2.701e+00, -1.452e+01],\n       [ 3.905e+03,  2.708e+00, -1.452e+01],\n       [ 3.905e+03,  2.714e+00, -1.452e+01],\n       [ 3.905e+03,  2.721e+00, -1.452e+01],\n       [ 3.905e+03,  2.728e+00, -1.452e+01],\n       [ 3.905e+03,  2.735e+00, -1.452e+01],\n       [ 3.905e+03,  2.742e+00, -1.452e+01],\n       [ 3.905e+03,  2.749e+00, -1.452e+01],\n       [ 3.905e+03,  2.756e+00, -1.452e+01],\n       [ 3.905e+03,  2.762e+00, -1.452e+01],\n       [ 3.905e+03,  2.769e+00, -1.452e+01],\n       [ 3.905e+03,  2.776e+00, -1.452e+01],\n       [ 3.905e+03,  2.783e+00, -1.452e+01],\n       [ 3.905e+03,  2.790e+00, -1.452e+01],\n       [ 3.905e+03,  2.797e+00, -1.452e+01],\n       [ 3.905e+03,  2.803e+00, -1.452e+01],\n       [ 3.905e+03,  2.810e+00, -1.452e+01],\n       [ 3.905e+03,  2.817e+00, -1.452e+01],\n       [ 3.905e+03,  2.824e+00, -1.452e+01],\n       [ 3.905e+03,  2.831e+00, -1.452e+01],\n       [ 3.905e+03,  2.838e+00, -1.452e+01],\n       [ 3.905e+03,  2.844e+00, -1.452e+01],\n       [ 3.905e+03,  2.851e+00, -1.452e+01],\n       [ 3.905e+03,  2.858e+00, -1.452e+01],\n       [ 3.905e+03,  2.865e+00, -1.452e+01],\n       [ 3.905e+03,  2.872e+00, -1.452e+01],\n       [ 3.905e+03,  2.879e+00, -1.452e+01],\n       [ 3.905e+03,  2.886e+00, -1.452e+01],\n       [ 3.905e+03,  2.892e+00, -1.452e+01],\n       [ 3.905e+03,  2.899e+00, -1.452e+01],\n       [ 3.905e+03,  2.906e+00, -1.452e+01],\n       [ 3.905e+03,  2.913e+00, -1.452e+01],\n       [ 3.905e+03,  2.920e+00, -1.452e+01],\n       [ 3.905e+03,  2.927e+00, -1.452e+01],\n       [ 3.905e+03,  2.933e+00, -1.452e+01],\n       [ 3.905e+03,  2.940e+00, -1.452e+01],\n       [ 3.905e+03,  2.947e+00, -1.452e+01],\n       [ 3.905e+03,  2.954e+00, -1.452e+01],\n       [ 3.905e+03,  2.961e+00, -1.452e+01],\n       [ 3.905e+03,  2.968e+00, -1.452e+01],\n       [ 3.905e+03,  2.974e+00, -1.452e+01],\n       [ 3.905e+03,  2.981e+00, -1.452e+01],\n       [ 3.905e+03,  2.988e+00, -1.452e+01],\n       [ 3.905e+03,  2.995e+00, -1.452e+01],\n       [ 3.905e+03,  3.002e+00, -1.452e+01],\n       [ 3.905e+03,  3.009e+00, -1.452e+01],\n       [ 3.905e+03,  3.015e+00, -1.452e+01],\n       [ 3.905e+03,  3.022e+00, -1.452e+01],\n       [ 3.905e+03,  3.029e+00, -1.452e+01],\n       [ 3.905e+03,  3.036e+00, -1.452e+01],\n       [ 3.905e+03,  3.043e+00, -1.452e+01],\n       [ 3.905e+03,  3.050e+00, -1.452e+01],\n       [ 3.905e+03,  3.057e+00, -1.452e+01],\n       [ 3.905e+03,  3.063e+00, -1.452e+01],\n       [ 3.905e+03,  3.070e+00, -1.452e+01],\n       [ 3.905e+03,  3.077e+00, -1.452e+01],\n       [ 3.905e+03,  3.084e+00, -1.452e+01],\n       [ 3.905e+03,  3.091e+00, -1.452e+01],\n       [ 3.905e+03,  3.098e+00, -1.452e+01],\n       [ 3.905e+03,  3.104e+00, -1.452e+01],\n       [ 3.905e+03,  3.111e+00, -1.452e+01],\n       [ 3.905e+03,  3.118e+00, -1.452e+01],\n       [ 3.905e+03,  3.125e+00, -1.452e+01],\n       [ 3.905e+03,  3.132e+00, -1.452e+01],\n       [ 3.905e+03,  3.139e+00, -1.452e+01],\n       [ 3.905e+03,  3.145e+00, -1.452e+01],\n       [ 3.905e+03,  3.152e+00, -1.452e+01],\n       [ 3.905e+03,  3.159e+00, -1.452e+01],\n       [ 3.905e+03,  3.166e+00, -1.452e+01],\n       [ 3.905e+03,  3.173e+00, -1.452e+01],\n       [ 3.905e+03,  3.180e+00, -1.452e+01],\n       [ 3.905e+03,  3.187e+00, -1.452e+01],\n       [ 3.905e+03,  3.193e+00, -1.452e+01],\n       [ 3.905e+03,  3.200e+00, -1.452e+01],\n       [ 3.905e+03,  3.207e+00, -1.452e+01],\n       [ 3.905e+03,  3.214e+00, -1.452e+01],\n       [ 3.905e+03,  3.221e+00, -1.452e+01],\n       [ 3.905e+03,  3.228e+00, -1.452e+01],\n       [ 3.905e+03,  3.234e+00, -1.452e+01],\n       [ 3.905e+03,  3.241e+00, -1.452e+01],\n       [ 3.905e+03,  3.248e+00, -1.452e+01],\n       [ 3.905e+03,  3.255e+00, -1.452e+01],\n       [ 3.905e+03,  3.262e+00, -1.452e+01],\n       [ 3.905e+03,  3.269e+00, -1.452e+01],\n       [ 3.905e+03,  3.275e+00, -1.452e+01],\n       [ 3.905e+03,  3.282e+00, -1.452e+01],\n       [ 3.905e+03,  3.289e+00, -1.452e+01],\n       [ 3.905e+03,  3.296e+00, -1.452e+01],\n       [ 3.905e+03,  3.303e+00, -1.452e+01],\n       [ 3.905e+03,  3.310e+00, -1.452e+01],\n       [ 3.905e+03,  3.317e+00, -1.452e+01],\n       [ 3.905e+03,  3.323e+00, -1.452e+01],\n       [ 3.905e+03,  3.330e+00, -1.452e+01],\n       [ 3.905e+03,  3.337e+00, -1.452e+01],\n       [ 3.905e+03,  3.344e+00, -1.452e+01],\n       [ 3.905e+03,  3.351e+00, -1.452e+01],\n       [ 3.905e+03,  3.358e+00, -1.452e+01],\n       [ 3.905e+03,  3.364e+00, -1.452e+01],\n       [ 3.905e+03,  3.371e+00, -1.453e+01],\n       [ 3.905e+03,  3.378e+00, -1.453e+01]]), array([[ 3.906e+03,  2.701e+00, -1.452e+01],\n       [ 3.906e+03,  2.708e+00, -1.452e+01],\n       [ 3.906e+03,  2.714e+00, -1.452e+01],\n       [ 3.906e+03,  2.721e+00, -1.452e+01],\n       [ 3.906e+03,  2.728e+00, -1.452e+01],\n       [ 3.906e+03,  2.735e+00, -1.452e+01],\n       [ 3.906e+03,  2.742e+00, -1.452e+01],\n       [ 3.906e+03,  2.749e+00, -1.452e+01],\n       [ 3.906e+03,  2.756e+00, -1.452e+01],\n       [ 3.906e+03,  2.762e+00, -1.452e+01],\n       [ 3.906e+03,  2.769e+00, -1.452e+01],\n       [ 3.906e+03,  2.776e+00, -1.452e+01],\n       [ 3.906e+03,  2.783e+00, -1.452e+01],\n       [ 3.906e+03,  2.790e+00, -1.452e+01],\n       [ 3.906e+03,  2.797e+00, -1.452e+01],\n       [ 3.906e+03,  2.803e+00, -1.452e+01],\n       [ 3.906e+03,  2.810e+00, -1.452e+01],\n       [ 3.906e+03,  2.817e+00, -1.452e+01],\n       [ 3.906e+03,  2.824e+00, 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-1.452e+01],\n       [ 3.906e+03,  3.275e+00, -1.452e+01],\n       [ 3.906e+03,  3.282e+00, -1.452e+01],\n       [ 3.906e+03,  3.289e+00, -1.452e+01],\n       [ 3.906e+03,  3.296e+00, -1.452e+01],\n       [ 3.906e+03,  3.303e+00, -1.452e+01],\n       [ 3.906e+03,  3.310e+00, -1.452e+01],\n       [ 3.906e+03,  3.317e+00, -1.452e+01],\n       [ 3.906e+03,  3.323e+00, -1.452e+01],\n       [ 3.906e+03,  3.330e+00, -1.452e+01],\n       [ 3.906e+03,  3.337e+00, -1.452e+01],\n       [ 3.906e+03,  3.344e+00, -1.452e+01],\n       [ 3.906e+03,  3.351e+00, -1.452e+01],\n       [ 3.906e+03,  3.358e+00, -1.452e+01],\n       [ 3.906e+03,  3.364e+00, -1.452e+01],\n       [ 3.906e+03,  3.371e+00, -1.453e+01],\n       [ 3.906e+03,  3.378e+00, -1.453e+01]]), array([[ 3.907e+03,  2.701e+00, -1.452e+01],\n       [ 3.907e+03,  2.708e+00, -1.452e+01],\n       [ 3.907e+03,  2.714e+00, -1.452e+01],\n       [ 3.907e+03,  2.721e+00, -1.452e+01],\n       [ 3.907e+03,  2.728e+00, -1.452e+01],\n       [ 3.907e+03, 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3.180e+00, -1.452e+01],\n       [ 3.907e+03,  3.187e+00, -1.452e+01],\n       [ 3.907e+03,  3.193e+00, -1.452e+01],\n       [ 3.907e+03,  3.200e+00, -1.452e+01],\n       [ 3.907e+03,  3.207e+00, -1.452e+01],\n       [ 3.907e+03,  3.214e+00, -1.452e+01],\n       [ 3.907e+03,  3.221e+00, -1.452e+01],\n       [ 3.907e+03,  3.228e+00, -1.452e+01],\n       [ 3.907e+03,  3.234e+00, -1.452e+01],\n       [ 3.907e+03,  3.241e+00, -1.452e+01],\n       [ 3.907e+03,  3.248e+00, -1.452e+01],\n       [ 3.907e+03,  3.255e+00, -1.452e+01],\n       [ 3.907e+03,  3.262e+00, -1.452e+01],\n       [ 3.907e+03,  3.269e+00, -1.452e+01],\n       [ 3.907e+03,  3.275e+00, -1.452e+01],\n       [ 3.907e+03,  3.282e+00, -1.452e+01],\n       [ 3.907e+03,  3.289e+00, -1.452e+01],\n       [ 3.907e+03,  3.296e+00, -1.452e+01],\n       [ 3.907e+03,  3.303e+00, -1.452e+01],\n       [ 3.907e+03,  3.310e+00, -1.452e+01],\n       [ 3.907e+03,  3.317e+00, -1.452e+01],\n       [ 3.907e+03,  3.323e+00, -1.452e+01],\n       [ 3.907e+03,  3.330e+00, -1.452e+01],\n       [ 3.907e+03,  3.337e+00, -1.452e+01],\n       [ 3.907e+03,  3.344e+00, -1.452e+01],\n       [ 3.907e+03,  3.351e+00, -1.452e+01],\n       [ 3.907e+03,  3.358e+00, -1.452e+01],\n       [ 3.907e+03,  3.364e+00, -1.452e+01],\n       [ 3.907e+03,  3.371e+00, -1.452e+01],\n       [ 3.907e+03,  3.378e+00, -1.452e+01]]), array([[ 3.908e+03,  2.701e+00, -1.452e+01],\n       [ 3.908e+03,  2.708e+00, -1.452e+01],\n       [ 3.908e+03,  2.714e+00, -1.452e+01],\n       [ 3.908e+03,  2.721e+00, -1.452e+01],\n       [ 3.908e+03,  2.728e+00, -1.452e+01],\n       [ 3.908e+03,  2.735e+00, -1.452e+01],\n       [ 3.908e+03,  2.742e+00, -1.452e+01],\n       [ 3.908e+03,  2.749e+00, -1.452e+01],\n       [ 3.908e+03,  2.756e+00, -1.452e+01],\n       [ 3.908e+03,  2.762e+00, -1.452e+01],\n       [ 3.908e+03,  2.769e+00, -1.452e+01],\n       [ 3.908e+03,  2.776e+00, -1.452e+01],\n       [ 3.908e+03,  2.783e+00, -1.452e+01],\n       [ 3.908e+03,  2.790e+00, 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2.940e+00, -1.452e+01],\n       [ 3.908e+03,  2.947e+00, -1.452e+01],\n       [ 3.908e+03,  2.954e+00, -1.452e+01],\n       [ 3.908e+03,  2.961e+00, -1.452e+01],\n       [ 3.908e+03,  2.968e+00, -1.452e+01],\n       [ 3.908e+03,  2.974e+00, -1.452e+01],\n       [ 3.908e+03,  2.981e+00, -1.452e+01],\n       [ 3.908e+03,  2.988e+00, -1.452e+01],\n       [ 3.908e+03,  2.995e+00, -1.452e+01],\n       [ 3.908e+03,  3.002e+00, -1.452e+01],\n       [ 3.908e+03,  3.009e+00, -1.452e+01],\n       [ 3.908e+03,  3.015e+00, -1.452e+01],\n       [ 3.908e+03,  3.022e+00, -1.452e+01],\n       [ 3.908e+03,  3.029e+00, -1.452e+01],\n       [ 3.908e+03,  3.036e+00, -1.452e+01],\n       [ 3.908e+03,  3.043e+00, -1.452e+01],\n       [ 3.908e+03,  3.050e+00, -1.452e+01],\n       [ 3.908e+03,  3.057e+00, -1.452e+01],\n       [ 3.908e+03,  3.063e+00, -1.452e+01],\n       [ 3.908e+03,  3.070e+00, -1.452e+01],\n       [ 3.908e+03,  3.077e+00, -1.452e+01],\n       [ 3.908e+03,  3.084e+00, -1.452e+01],\n       [ 3.908e+03,  3.091e+00, -1.452e+01],\n       [ 3.908e+03,  3.098e+00, -1.452e+01],\n       [ 3.908e+03,  3.104e+00, -1.452e+01],\n       [ 3.908e+03,  3.111e+00, -1.452e+01],\n       [ 3.908e+03,  3.118e+00, -1.452e+01],\n       [ 3.908e+03,  3.125e+00, -1.452e+01],\n       [ 3.908e+03,  3.132e+00, -1.452e+01],\n       [ 3.908e+03,  3.139e+00, -1.452e+01],\n       [ 3.908e+03,  3.145e+00, -1.452e+01],\n       [ 3.908e+03,  3.152e+00, -1.452e+01],\n       [ 3.908e+03,  3.159e+00, -1.452e+01],\n       [ 3.908e+03,  3.166e+00, -1.452e+01],\n       [ 3.908e+03,  3.173e+00, -1.452e+01],\n       [ 3.908e+03,  3.180e+00, -1.452e+01],\n       [ 3.908e+03,  3.187e+00, -1.452e+01],\n       [ 3.908e+03,  3.193e+00, -1.452e+01],\n       [ 3.908e+03,  3.200e+00, -1.452e+01],\n       [ 3.908e+03,  3.207e+00, -1.452e+01],\n       [ 3.908e+03,  3.214e+00, -1.452e+01],\n       [ 3.908e+03,  3.221e+00, -1.452e+01],\n       [ 3.908e+03,  3.228e+00, -1.452e+01],\n       [ 3.908e+03,  3.234e+00, -1.452e+01],\n       [ 3.908e+03,  3.241e+00, -1.452e+01],\n       [ 3.908e+03,  3.248e+00, -1.452e+01],\n       [ 3.908e+03,  3.255e+00, -1.452e+01],\n       [ 3.908e+03,  3.262e+00, -1.452e+01],\n       [ 3.908e+03,  3.269e+00, -1.452e+01],\n       [ 3.908e+03,  3.275e+00, -1.452e+01],\n       [ 3.908e+03,  3.282e+00, -1.452e+01],\n       [ 3.908e+03,  3.289e+00, -1.452e+01],\n       [ 3.908e+03,  3.296e+00, -1.452e+01],\n       [ 3.908e+03,  3.303e+00, -1.452e+01],\n       [ 3.908e+03,  3.310e+00, -1.452e+01],\n       [ 3.908e+03,  3.317e+00, -1.452e+01],\n       [ 3.908e+03,  3.323e+00, -1.452e+01],\n       [ 3.908e+03,  3.330e+00, -1.452e+01],\n       [ 3.908e+03,  3.337e+00, -1.452e+01],\n       [ 3.908e+03,  3.344e+00, -1.452e+01],\n       [ 3.908e+03,  3.351e+00, -1.452e+01],\n       [ 3.908e+03,  3.358e+00, -1.452e+01],\n       [ 3.908e+03,  3.364e+00, -1.452e+01],\n       [ 3.908e+03,  3.371e+00, -1.453e+01],\n       [ 3.908e+03,  3.378e+00, -1.453e+01]]), array([[ 3.909e+03, 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3.909e+03,  2.851e+00, -1.452e+01],\n       [ 3.909e+03,  2.858e+00, -1.452e+01],\n       [ 3.909e+03,  2.865e+00, -1.452e+01],\n       [ 3.909e+03,  2.872e+00, -1.452e+01],\n       [ 3.909e+03,  2.879e+00, -1.452e+01],\n       [ 3.909e+03,  2.886e+00, -1.452e+01],\n       [ 3.909e+03,  2.892e+00, -1.452e+01],\n       [ 3.909e+03,  2.899e+00, -1.452e+01],\n       [ 3.909e+03,  2.906e+00, -1.452e+01],\n       [ 3.909e+03,  2.913e+00, -1.452e+01],\n       [ 3.909e+03,  2.920e+00, -1.452e+01],\n       [ 3.909e+03,  2.927e+00, -1.452e+01],\n       [ 3.909e+03,  2.933e+00, -1.452e+01],\n       [ 3.909e+03,  2.940e+00, -1.452e+01],\n       [ 3.909e+03,  2.947e+00, -1.452e+01],\n       [ 3.909e+03,  2.954e+00, -1.452e+01],\n       [ 3.909e+03,  2.961e+00, -1.452e+01],\n       [ 3.909e+03,  2.968e+00, -1.452e+01],\n       [ 3.909e+03,  2.974e+00, -1.452e+01],\n       [ 3.909e+03,  2.981e+00, -1.452e+01],\n       [ 3.909e+03,  2.988e+00, -1.452e+01],\n       [ 3.909e+03,  2.995e+00, 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3.145e+00, -1.452e+01],\n       [ 3.909e+03,  3.152e+00, -1.452e+01],\n       [ 3.909e+03,  3.159e+00, -1.452e+01],\n       [ 3.909e+03,  3.166e+00, -1.452e+01],\n       [ 3.909e+03,  3.173e+00, -1.452e+01],\n       [ 3.909e+03,  3.180e+00, -1.452e+01],\n       [ 3.909e+03,  3.187e+00, -1.452e+01],\n       [ 3.909e+03,  3.193e+00, -1.452e+01],\n       [ 3.909e+03,  3.200e+00, -1.452e+01],\n       [ 3.909e+03,  3.207e+00, -1.452e+01],\n       [ 3.909e+03,  3.214e+00, -1.452e+01],\n       [ 3.909e+03,  3.221e+00, -1.452e+01],\n       [ 3.909e+03,  3.228e+00, -1.452e+01],\n       [ 3.909e+03,  3.234e+00, -1.452e+01],\n       [ 3.909e+03,  3.241e+00, -1.452e+01],\n       [ 3.909e+03,  3.248e+00, -1.452e+01],\n       [ 3.909e+03,  3.255e+00, -1.452e+01],\n       [ 3.909e+03,  3.262e+00, -1.452e+01],\n       [ 3.909e+03,  3.269e+00, -1.452e+01],\n       [ 3.909e+03,  3.275e+00, -1.452e+01],\n       [ 3.909e+03,  3.282e+00, -1.452e+01],\n       [ 3.909e+03,  3.289e+00, -1.452e+01],\n       [ 3.909e+03,  3.296e+00, -1.452e+01],\n       [ 3.909e+03,  3.303e+00, -1.452e+01],\n       [ 3.909e+03,  3.310e+00, -1.452e+01],\n       [ 3.909e+03,  3.317e+00, -1.452e+01],\n       [ 3.909e+03,  3.323e+00, -1.452e+01],\n       [ 3.909e+03,  3.330e+00, -1.452e+01],\n       [ 3.909e+03,  3.337e+00, -1.452e+01],\n       [ 3.909e+03,  3.344e+00, -1.452e+01],\n       [ 3.909e+03,  3.351e+00, -1.452e+01],\n       [ 3.909e+03,  3.358e+00, -1.452e+01],\n       [ 3.909e+03,  3.364e+00, -1.452e+01],\n       [ 3.909e+03,  3.371e+00, -1.453e+01],\n       [ 3.909e+03,  3.378e+00, -1.453e+01]]), array([[ 3.910e+03,  2.701e+00, -1.452e+01],\n       [ 3.910e+03,  2.708e+00, -1.452e+01],\n       [ 3.910e+03,  2.714e+00, -1.452e+01],\n       [ 3.910e+03,  2.721e+00, -1.452e+01],\n       [ 3.910e+03,  2.728e+00, -1.452e+01],\n       [ 3.910e+03,  2.735e+00, -1.452e+01],\n       [ 3.910e+03,  2.742e+00, -1.452e+01],\n       [ 3.910e+03,  2.749e+00, -1.452e+01],\n       [ 3.910e+03,  2.756e+00, -1.452e+01],\n       [ 3.910e+03,  2.762e+00, -1.452e+01],\n       [ 3.910e+03,  2.769e+00, -1.452e+01],\n       [ 3.910e+03,  2.776e+00, -1.452e+01],\n       [ 3.910e+03,  2.783e+00, -1.452e+01],\n       [ 3.910e+03,  2.790e+00, -1.452e+01],\n       [ 3.910e+03,  2.797e+00, -1.452e+01],\n       [ 3.910e+03,  2.803e+00, -1.452e+01],\n       [ 3.910e+03,  2.810e+00, -1.452e+01],\n       [ 3.910e+03,  2.817e+00, -1.452e+01],\n       [ 3.910e+03,  2.824e+00, -1.452e+01],\n       [ 3.910e+03,  2.831e+00, -1.452e+01],\n       [ 3.910e+03,  2.838e+00, -1.452e+01],\n       [ 3.910e+03,  2.844e+00, -1.452e+01],\n       [ 3.910e+03,  2.851e+00, -1.452e+01],\n       [ 3.910e+03,  2.858e+00, -1.452e+01],\n       [ 3.910e+03,  2.865e+00, -1.452e+01],\n       [ 3.910e+03,  2.872e+00, -1.452e+01],\n       [ 3.910e+03,  2.879e+00, -1.452e+01],\n       [ 3.910e+03,  2.886e+00, -1.452e+01],\n       [ 3.910e+03,  2.892e+00, -1.452e+01],\n       [ 3.910e+03,  2.899e+00, -1.452e+01],\n       [ 3.910e+03,  2.906e+00, -1.452e+01],\n       [ 3.910e+03,  2.913e+00, -1.452e+01],\n       [ 3.910e+03,  2.920e+00, -1.452e+01],\n       [ 3.910e+03,  2.927e+00, -1.452e+01],\n       [ 3.910e+03,  2.933e+00, -1.452e+01],\n       [ 3.910e+03,  2.940e+00, -1.452e+01],\n       [ 3.910e+03,  2.947e+00, -1.452e+01],\n       [ 3.910e+03,  2.954e+00, -1.452e+01],\n       [ 3.910e+03,  2.961e+00, -1.452e+01],\n       [ 3.910e+03,  2.968e+00, -1.452e+01],\n       [ 3.910e+03,  2.974e+00, -1.452e+01],\n       [ 3.910e+03,  2.981e+00, -1.452e+01],\n       [ 3.910e+03,  2.988e+00, -1.452e+01],\n       [ 3.910e+03,  2.995e+00, -1.452e+01],\n       [ 3.910e+03,  3.002e+00, -1.452e+01],\n       [ 3.910e+03,  3.009e+00, -1.452e+01],\n       [ 3.910e+03,  3.015e+00, -1.452e+01],\n       [ 3.910e+03,  3.022e+00, -1.452e+01],\n       [ 3.910e+03,  3.029e+00, -1.452e+01],\n       [ 3.910e+03,  3.036e+00, -1.452e+01],\n       [ 3.910e+03,  3.043e+00, -1.452e+01],\n       [ 3.910e+03,  3.050e+00, -1.452e+01],\n       [ 3.910e+03,  3.057e+00, -1.452e+01],\n       [ 3.910e+03,  3.063e+00, -1.452e+01],\n       [ 3.910e+03,  3.070e+00, -1.452e+01],\n       [ 3.910e+03,  3.077e+00, -1.452e+01],\n       [ 3.910e+03,  3.084e+00, -1.452e+01],\n       [ 3.910e+03,  3.091e+00, -1.452e+01],\n       [ 3.910e+03,  3.098e+00, -1.452e+01],\n       [ 3.910e+03,  3.104e+00, -1.452e+01],\n       [ 3.910e+03,  3.111e+00, -1.452e+01],\n       [ 3.910e+03,  3.118e+00, -1.452e+01],\n       [ 3.910e+03,  3.125e+00, -1.452e+01],\n       [ 3.910e+03,  3.132e+00, -1.452e+01],\n       [ 3.910e+03,  3.139e+00, -1.452e+01],\n       [ 3.910e+03,  3.145e+00, -1.452e+01],\n       [ 3.910e+03,  3.152e+00, -1.452e+01],\n       [ 3.910e+03,  3.159e+00, -1.452e+01],\n       [ 3.910e+03,  3.166e+00, -1.452e+01],\n       [ 3.910e+03,  3.173e+00, -1.452e+01],\n       [ 3.910e+03,  3.180e+00, -1.452e+01],\n       [ 3.910e+03,  3.187e+00, -1.452e+01],\n       [ 3.910e+03,  3.193e+00, -1.452e+01],\n       [ 3.910e+03,  3.200e+00, -1.452e+01],\n       [ 3.910e+03,  3.207e+00, -1.452e+01],\n       [ 3.910e+03,  3.214e+00, -1.452e+01],\n       [ 3.910e+03,  3.221e+00, -1.452e+01],\n       [ 3.910e+03,  3.228e+00, -1.452e+01],\n       [ 3.910e+03,  3.234e+00, -1.452e+01],\n       [ 3.910e+03,  3.241e+00, -1.452e+01],\n       [ 3.910e+03,  3.248e+00, -1.452e+01],\n       [ 3.910e+03,  3.255e+00, -1.452e+01],\n       [ 3.910e+03,  3.262e+00, -1.452e+01],\n       [ 3.910e+03,  3.269e+00, -1.452e+01],\n       [ 3.910e+03,  3.275e+00, -1.452e+01],\n       [ 3.910e+03,  3.282e+00, -1.452e+01],\n       [ 3.910e+03,  3.289e+00, -1.452e+01],\n       [ 3.910e+03,  3.296e+00, -1.452e+01],\n       [ 3.910e+03,  3.303e+00, -1.452e+01],\n       [ 3.910e+03,  3.310e+00, -1.452e+01],\n       [ 3.910e+03,  3.317e+00, -1.452e+01],\n       [ 3.910e+03,  3.323e+00, -1.452e+01],\n       [ 3.910e+03,  3.330e+00, -1.452e+01],\n       [ 3.910e+03,  3.337e+00, -1.452e+01],\n       [ 3.910e+03,  3.344e+00, -1.452e+01],\n       [ 3.910e+03,  3.351e+00, -1.452e+01],\n       [ 3.910e+03,  3.358e+00, -1.452e+01],\n       [ 3.910e+03,  3.364e+00, -1.452e+01],\n       [ 3.910e+03,  3.371e+00, -1.452e+01],\n       [ 3.910e+03,  3.378e+00, -1.453e+01]]), array([[ 3.911e+03,  2.701e+00, -1.452e+01],\n       [ 3.911e+03,  2.708e+00, -1.452e+01],\n       [ 3.911e+03,  2.714e+00, -1.452e+01],\n       [ 3.911e+03,  2.721e+00, -1.452e+01],\n       [ 3.911e+03,  2.728e+00, -1.452e+01],\n       [ 3.911e+03,  2.735e+00, -1.452e+01],\n       [ 3.911e+03,  2.742e+00, -1.452e+01],\n       [ 3.911e+03,  2.749e+00, -1.452e+01],\n       [ 3.911e+03,  2.756e+00, -1.452e+01],\n       [ 3.911e+03,  2.762e+00, -1.452e+01],\n       [ 3.911e+03,  2.769e+00, -1.452e+01],\n       [ 3.911e+03,  2.776e+00, -1.452e+01],\n       [ 3.911e+03,  2.783e+00, -1.452e+01],\n       [ 3.911e+03,  2.790e+00, -1.452e+01],\n       [ 3.911e+03,  2.797e+00, -1.452e+01],\n       [ 3.911e+03,  2.803e+00, -1.452e+01],\n       [ 3.911e+03,  2.810e+00, -1.452e+01],\n       [ 3.911e+03,  2.817e+00, -1.452e+01],\n       [ 3.911e+03,  2.824e+00, -1.452e+01],\n       [ 3.911e+03,  2.831e+00, -1.452e+01],\n       [ 3.911e+03,  2.838e+00, -1.452e+01],\n       [ 3.911e+03,  2.844e+00, -1.452e+01],\n       [ 3.911e+03,  2.851e+00, -1.452e+01],\n       [ 3.911e+03,  2.858e+00, -1.452e+01],\n       [ 3.911e+03,  2.865e+00, -1.452e+01],\n       [ 3.911e+03,  2.872e+00, -1.452e+01],\n       [ 3.911e+03,  2.879e+00, -1.452e+01],\n       [ 3.911e+03,  2.886e+00, -1.452e+01],\n       [ 3.911e+03,  2.892e+00, -1.452e+01],\n       [ 3.911e+03,  2.899e+00, -1.452e+01],\n       [ 3.911e+03,  2.906e+00, -1.452e+01],\n       [ 3.911e+03,  2.913e+00, -1.452e+01],\n       [ 3.911e+03,  2.920e+00, -1.452e+01],\n       [ 3.911e+03,  2.927e+00, -1.452e+01],\n       [ 3.911e+03,  2.933e+00, -1.452e+01],\n       [ 3.911e+03,  2.940e+00, -1.452e+01],\n       [ 3.911e+03,  2.947e+00, -1.452e+01],\n       [ 3.911e+03,  2.954e+00, -1.452e+01],\n       [ 3.911e+03,  2.961e+00, 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3.911e+03,  3.262e+00, -1.452e+01],\n       [ 3.911e+03,  3.269e+00, -1.452e+01],\n       [ 3.911e+03,  3.275e+00, -1.452e+01],\n       [ 3.911e+03,  3.282e+00, -1.452e+01],\n       [ 3.911e+03,  3.289e+00, -1.452e+01],\n       [ 3.911e+03,  3.296e+00, -1.452e+01],\n       [ 3.911e+03,  3.303e+00, -1.452e+01],\n       [ 3.911e+03,  3.310e+00, -1.452e+01],\n       [ 3.911e+03,  3.317e+00, -1.452e+01],\n       [ 3.911e+03,  3.323e+00, -1.452e+01],\n       [ 3.911e+03,  3.330e+00, -1.452e+01],\n       [ 3.911e+03,  3.337e+00, -1.452e+01],\n       [ 3.911e+03,  3.344e+00, -1.452e+01],\n       [ 3.911e+03,  3.351e+00, -1.452e+01],\n       [ 3.911e+03,  3.358e+00, -1.452e+01],\n       [ 3.911e+03,  3.364e+00, -1.452e+01],\n       [ 3.911e+03,  3.371e+00, -1.453e+01],\n       [ 3.911e+03,  3.378e+00, -1.453e+01]]), array([[ 3.912e+03,  2.701e+00, -1.452e+01],\n       [ 3.912e+03,  2.708e+00, -1.452e+01],\n       [ 3.912e+03,  2.714e+00, -1.452e+01],\n       [ 3.912e+03,  2.721e+00, 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2.872e+00, -1.452e+01],\n       [ 3.912e+03,  2.879e+00, -1.452e+01],\n       [ 3.912e+03,  2.886e+00, -1.452e+01],\n       [ 3.912e+03,  2.892e+00, -1.452e+01],\n       [ 3.912e+03,  2.899e+00, -1.452e+01],\n       [ 3.912e+03,  2.906e+00, -1.452e+01],\n       [ 3.912e+03,  2.913e+00, -1.452e+01],\n       [ 3.912e+03,  2.920e+00, -1.452e+01],\n       [ 3.912e+03,  2.927e+00, -1.452e+01],\n       [ 3.912e+03,  2.933e+00, -1.452e+01],\n       [ 3.912e+03,  2.940e+00, -1.452e+01],\n       [ 3.912e+03,  2.947e+00, -1.452e+01],\n       [ 3.912e+03,  2.954e+00, -1.452e+01],\n       [ 3.912e+03,  2.961e+00, -1.452e+01],\n       [ 3.912e+03,  2.968e+00, -1.452e+01],\n       [ 3.912e+03,  2.974e+00, -1.452e+01],\n       [ 3.912e+03,  2.981e+00, -1.452e+01],\n       [ 3.912e+03,  2.988e+00, -1.452e+01],\n       [ 3.912e+03,  2.995e+00, -1.452e+01],\n       [ 3.912e+03,  3.002e+00, -1.452e+01],\n       [ 3.912e+03,  3.009e+00, -1.452e+01],\n       [ 3.912e+03,  3.015e+00, -1.452e+01],\n       [ 3.912e+03,  3.022e+00, -1.452e+01],\n       [ 3.912e+03,  3.029e+00, -1.452e+01],\n       [ 3.912e+03,  3.036e+00, -1.452e+01],\n       [ 3.912e+03,  3.043e+00, -1.452e+01],\n       [ 3.912e+03,  3.050e+00, -1.452e+01],\n       [ 3.912e+03,  3.057e+00, -1.452e+01],\n       [ 3.912e+03,  3.063e+00, -1.452e+01],\n       [ 3.912e+03,  3.070e+00, -1.452e+01],\n       [ 3.912e+03,  3.077e+00, -1.452e+01],\n       [ 3.912e+03,  3.084e+00, -1.452e+01],\n       [ 3.912e+03,  3.091e+00, -1.452e+01],\n       [ 3.912e+03,  3.098e+00, -1.452e+01],\n       [ 3.912e+03,  3.104e+00, -1.452e+01],\n       [ 3.912e+03,  3.111e+00, -1.452e+01],\n       [ 3.912e+03,  3.118e+00, -1.452e+01],\n       [ 3.912e+03,  3.125e+00, -1.452e+01],\n       [ 3.912e+03,  3.132e+00, -1.452e+01],\n       [ 3.912e+03,  3.139e+00, -1.452e+01],\n       [ 3.912e+03,  3.145e+00, -1.452e+01],\n       [ 3.912e+03,  3.152e+00, -1.452e+01],\n       [ 3.912e+03,  3.159e+00, -1.452e+01],\n       [ 3.912e+03,  3.166e+00, 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3.317e+00, -1.452e+01],\n       [ 3.912e+03,  3.323e+00, -1.452e+01],\n       [ 3.912e+03,  3.330e+00, -1.452e+01],\n       [ 3.912e+03,  3.337e+00, -1.452e+01],\n       [ 3.912e+03,  3.344e+00, -1.452e+01],\n       [ 3.912e+03,  3.351e+00, -1.452e+01],\n       [ 3.912e+03,  3.358e+00, -1.452e+01],\n       [ 3.912e+03,  3.364e+00, -1.452e+01],\n       [ 3.912e+03,  3.371e+00, -1.452e+01],\n       [ 3.912e+03,  3.378e+00, -1.453e+01]]), array([[ 3.913e+03,  2.701e+00, -1.452e+01],\n       [ 3.913e+03,  2.708e+00, -1.452e+01],\n       [ 3.913e+03,  2.714e+00, -1.452e+01],\n       [ 3.913e+03,  2.721e+00, -1.452e+01],\n       [ 3.913e+03,  2.728e+00, -1.452e+01],\n       [ 3.913e+03,  2.735e+00, -1.452e+01],\n       [ 3.913e+03,  2.742e+00, -1.452e+01],\n       [ 3.913e+03,  2.749e+00, -1.452e+01],\n       [ 3.913e+03,  2.756e+00, -1.452e+01],\n       [ 3.913e+03,  2.762e+00, -1.452e+01],\n       [ 3.913e+03,  2.769e+00, -1.452e+01],\n       [ 3.913e+03,  2.776e+00, -1.452e+01],\n       [ 3.913e+03,  2.783e+00, -1.452e+01],\n       [ 3.913e+03,  2.790e+00, -1.452e+01],\n       [ 3.913e+03,  2.797e+00, -1.452e+01],\n       [ 3.913e+03,  2.803e+00, -1.452e+01],\n       [ 3.913e+03,  2.810e+00, -1.452e+01],\n       [ 3.913e+03,  2.817e+00, -1.452e+01],\n       [ 3.913e+03,  2.824e+00, -1.452e+01],\n       [ 3.913e+03,  2.831e+00, -1.452e+01],\n       [ 3.913e+03,  2.838e+00, -1.452e+01],\n       [ 3.913e+03,  2.844e+00, -1.452e+01],\n       [ 3.913e+03,  2.851e+00, -1.452e+01],\n       [ 3.913e+03,  2.858e+00, -1.452e+01],\n       [ 3.913e+03,  2.865e+00, -1.452e+01],\n       [ 3.913e+03,  2.872e+00, -1.452e+01],\n       [ 3.913e+03,  2.879e+00, -1.452e+01],\n       [ 3.913e+03,  2.886e+00, -1.452e+01],\n       [ 3.913e+03,  2.892e+00, -1.452e+01],\n       [ 3.913e+03,  2.899e+00, -1.452e+01],\n       [ 3.913e+03,  2.906e+00, -1.452e+01],\n       [ 3.913e+03,  2.913e+00, -1.452e+01],\n       [ 3.913e+03,  2.920e+00, -1.452e+01],\n       [ 3.913e+03,  2.927e+00, 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3.851e+03,  3.928e+00, -4.840e+00],\n       [ 3.851e+03,  3.931e+00, -4.840e+00],\n       [ 3.851e+03,  3.934e+00, -4.840e+00],\n       [ 3.851e+03,  3.937e+00, -4.840e+00],\n       [ 3.851e+03,  3.940e+00, -4.840e+00],\n       [ 3.851e+03,  3.943e+00, -4.840e+00],\n       [ 3.851e+03,  3.945e+00, -4.840e+00],\n       [ 3.851e+03,  3.948e+00, -4.840e+00],\n       [ 3.851e+03,  3.951e+00, -4.840e+00],\n       [ 3.851e+03,  3.954e+00, -4.840e+00],\n       [ 3.851e+03,  3.957e+00, -4.840e+00],\n       [ 3.851e+03,  3.960e+00, -4.840e+00],\n       [ 3.851e+03,  3.963e+00, -4.840e+00],\n       [ 3.851e+03,  3.966e+00, -4.841e+00],\n       [ 3.851e+03,  3.969e+00, -4.841e+00],\n       [ 3.851e+03,  3.972e+00, -4.842e+00],\n       [ 3.851e+03,  3.974e+00, -4.842e+00],\n       [ 3.851e+03,  3.977e+00, -4.843e+00],\n       [ 3.851e+03,  3.980e+00, -4.843e+00],\n       [ 3.851e+03,  3.983e+00, -4.844e+00],\n       [ 3.851e+03,  3.986e+00, -4.844e+00],\n       [ 3.851e+03,  3.989e+00, -4.845e+00]]), array([[ 3.852e+03,  3.701e+00, -4.840e+00],\n       [ 3.852e+03,  3.704e+00, -4.840e+00],\n       [ 3.852e+03,  3.707e+00, -4.840e+00],\n       [ 3.852e+03,  3.710e+00, -4.840e+00],\n       [ 3.852e+03,  3.713e+00, -4.840e+00],\n       [ 3.852e+03,  3.716e+00, -4.840e+00],\n       [ 3.852e+03,  3.719e+00, -4.840e+00],\n       [ 3.852e+03,  3.722e+00, -4.840e+00],\n       [ 3.852e+03,  3.725e+00, -4.840e+00],\n       [ 3.852e+03,  3.728e+00, -4.840e+00],\n       [ 3.852e+03,  3.730e+00, -4.840e+00],\n       [ 3.852e+03,  3.733e+00, -4.840e+00],\n       [ 3.852e+03,  3.736e+00, -4.840e+00],\n       [ 3.852e+03,  3.739e+00, -4.840e+00],\n       [ 3.852e+03,  3.742e+00, -4.840e+00],\n       [ 3.852e+03,  3.745e+00, -4.840e+00],\n       [ 3.852e+03,  3.748e+00, -4.840e+00],\n       [ 3.852e+03,  3.751e+00, -4.840e+00],\n       [ 3.852e+03,  3.754e+00, -4.840e+00],\n       [ 3.852e+03,  3.757e+00, -4.840e+00],\n       [ 3.852e+03,  3.759e+00, -4.840e+00],\n       [ 3.852e+03, 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3.853e+03,  3.725e+00, -4.840e+00],\n       [ 3.853e+03,  3.728e+00, -4.840e+00],\n       [ 3.853e+03,  3.730e+00, -4.840e+00],\n       [ 3.853e+03,  3.733e+00, -4.840e+00],\n       [ 3.853e+03,  3.736e+00, -4.840e+00],\n       [ 3.853e+03,  3.739e+00, -4.840e+00],\n       [ 3.853e+03,  3.742e+00, -4.840e+00],\n       [ 3.853e+03,  3.745e+00, -4.840e+00],\n       [ 3.853e+03,  3.748e+00, -4.840e+00],\n       [ 3.853e+03,  3.751e+00, -4.840e+00],\n       [ 3.853e+03,  3.754e+00, -4.840e+00],\n       [ 3.853e+03,  3.757e+00, -4.840e+00],\n       [ 3.853e+03,  3.759e+00, -4.840e+00],\n       [ 3.853e+03,  3.762e+00, -4.840e+00],\n       [ 3.853e+03,  3.765e+00, -4.840e+00],\n       [ 3.853e+03,  3.768e+00, -4.840e+00],\n       [ 3.853e+03,  3.771e+00, -4.840e+00],\n       [ 3.853e+03,  3.774e+00, -4.840e+00],\n       [ 3.853e+03,  3.777e+00, -4.840e+00],\n       [ 3.853e+03,  3.780e+00, -4.840e+00],\n       [ 3.853e+03,  3.783e+00, -4.840e+00],\n       [ 3.853e+03,  3.786e+00, 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3.854e+03,  3.812e+00, -4.840e+00],\n       [ 3.854e+03,  3.815e+00, -4.840e+00],\n       [ 3.854e+03,  3.818e+00, -4.840e+00],\n       [ 3.854e+03,  3.821e+00, -4.840e+00],\n       [ 3.854e+03,  3.823e+00, -4.840e+00],\n       [ 3.854e+03,  3.826e+00, -4.840e+00],\n       [ 3.854e+03,  3.829e+00, -4.840e+00],\n       [ 3.854e+03,  3.832e+00, -4.840e+00],\n       [ 3.854e+03,  3.835e+00, -4.840e+00],\n       [ 3.854e+03,  3.838e+00, -4.840e+00],\n       [ 3.854e+03,  3.841e+00, -4.840e+00],\n       [ 3.854e+03,  3.844e+00, -4.840e+00],\n       [ 3.854e+03,  3.847e+00, -4.840e+00],\n       [ 3.854e+03,  3.850e+00, -4.840e+00],\n       [ 3.854e+03,  3.852e+00, -4.840e+00],\n       [ 3.854e+03,  3.855e+00, -4.840e+00],\n       [ 3.854e+03,  3.858e+00, -4.840e+00],\n       [ 3.854e+03,  3.861e+00, -4.840e+00],\n       [ 3.854e+03,  3.864e+00, -4.840e+00],\n       [ 3.854e+03,  3.867e+00, -4.840e+00],\n       [ 3.854e+03,  3.870e+00, -4.840e+00],\n       [ 3.854e+03,  3.873e+00, 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3.937e+00, -4.840e+00],\n       [ 3.854e+03,  3.940e+00, -4.840e+00],\n       [ 3.854e+03,  3.943e+00, -4.840e+00],\n       [ 3.854e+03,  3.945e+00, -4.840e+00],\n       [ 3.854e+03,  3.948e+00, -4.840e+00],\n       [ 3.854e+03,  3.951e+00, -4.840e+00],\n       [ 3.854e+03,  3.954e+00, -4.840e+00],\n       [ 3.854e+03,  3.957e+00, -4.840e+00],\n       [ 3.854e+03,  3.960e+00, -4.840e+00],\n       [ 3.854e+03,  3.963e+00, -4.840e+00],\n       [ 3.854e+03,  3.966e+00, -4.840e+00],\n       [ 3.854e+03,  3.969e+00, -4.841e+00],\n       [ 3.854e+03,  3.972e+00, -4.841e+00],\n       [ 3.854e+03,  3.974e+00, -4.841e+00],\n       [ 3.854e+03,  3.977e+00, -4.841e+00],\n       [ 3.854e+03,  3.980e+00, -4.841e+00],\n       [ 3.854e+03,  3.983e+00, -4.841e+00],\n       [ 3.854e+03,  3.986e+00, -4.841e+00],\n       [ 3.854e+03,  3.989e+00, -4.841e+00]]), array([[ 3.855e+03,  3.701e+00, -4.840e+00],\n       [ 3.855e+03,  3.704e+00, -4.840e+00],\n       [ 3.855e+03,  3.707e+00, -4.840e+00],\n       [ 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3.855e+03,  3.899e+00, -4.839e+00],\n       [ 3.855e+03,  3.902e+00, -4.839e+00],\n       [ 3.855e+03,  3.905e+00, -4.839e+00],\n       [ 3.855e+03,  3.908e+00, -4.840e+00],\n       [ 3.855e+03,  3.911e+00, -4.840e+00],\n       [ 3.855e+03,  3.913e+00, -4.840e+00],\n       [ 3.855e+03,  3.916e+00, -4.840e+00],\n       [ 3.855e+03,  3.919e+00, -4.840e+00],\n       [ 3.855e+03,  3.922e+00, -4.840e+00],\n       [ 3.855e+03,  3.925e+00, -4.840e+00],\n       [ 3.855e+03,  3.928e+00, -4.840e+00],\n       [ 3.855e+03,  3.931e+00, -4.840e+00],\n       [ 3.855e+03,  3.934e+00, -4.840e+00],\n       [ 3.855e+03,  3.937e+00, -4.840e+00],\n       [ 3.855e+03,  3.940e+00, -4.840e+00],\n       [ 3.855e+03,  3.943e+00, -4.840e+00],\n       [ 3.855e+03,  3.945e+00, -4.840e+00],\n       [ 3.855e+03,  3.948e+00, -4.840e+00],\n       [ 3.855e+03,  3.951e+00, -4.840e+00],\n       [ 3.855e+03,  3.954e+00, -4.840e+00],\n       [ 3.855e+03,  3.957e+00, -4.840e+00],\n       [ 3.855e+03,  3.960e+00, 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3.856e+03,  3.986e+00, -4.843e+00],\n       [ 3.856e+03,  3.989e+00, -4.843e+00]]), array([[ 3.857e+03,  3.701e+00, -4.840e+00],\n       [ 3.857e+03,  3.704e+00, -4.840e+00],\n       [ 3.857e+03,  3.707e+00, -4.840e+00],\n       [ 3.857e+03,  3.710e+00, -4.840e+00],\n       [ 3.857e+03,  3.713e+00, -4.840e+00],\n       [ 3.857e+03,  3.716e+00, -4.840e+00],\n       [ 3.857e+03,  3.719e+00, -4.840e+00],\n       [ 3.857e+03,  3.722e+00, -4.840e+00],\n       [ 3.857e+03,  3.725e+00, -4.840e+00],\n       [ 3.857e+03,  3.728e+00, -4.841e+00],\n       [ 3.857e+03,  3.730e+00, -4.840e+00],\n       [ 3.857e+03,  3.733e+00, -4.840e+00],\n       [ 3.857e+03,  3.736e+00, -4.840e+00],\n       [ 3.857e+03,  3.739e+00, -4.840e+00],\n       [ 3.857e+03,  3.742e+00, -4.840e+00],\n       [ 3.857e+03,  3.745e+00, -4.840e+00],\n       [ 3.857e+03,  3.748e+00, -4.840e+00],\n       [ 3.857e+03,  3.751e+00, -4.840e+00],\n       [ 3.857e+03,  3.754e+00, -4.840e+00],\n       [ 3.857e+03,  3.757e+00, 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3.906e+00, -4.840e+00],\n       [ 3.858e+03,  3.909e+00, -4.840e+00],\n       [ 3.858e+03,  3.912e+00, -4.840e+00],\n       [ 3.858e+03,  3.915e+00, -4.839e+00],\n       [ 3.858e+03,  3.918e+00, -4.840e+00],\n       [ 3.858e+03,  3.921e+00, -4.840e+00],\n       [ 3.858e+03,  3.924e+00, -4.840e+00],\n       [ 3.858e+03,  3.927e+00, -4.840e+00],\n       [ 3.858e+03,  3.930e+00, -4.840e+00],\n       [ 3.858e+03,  3.932e+00, -4.840e+00],\n       [ 3.858e+03,  3.935e+00, -4.840e+00],\n       [ 3.858e+03,  3.938e+00, -4.840e+00],\n       [ 3.858e+03,  3.941e+00, -4.840e+00],\n       [ 3.858e+03,  3.944e+00, -4.840e+00],\n       [ 3.858e+03,  3.947e+00, -4.840e+00],\n       [ 3.858e+03,  3.950e+00, -4.840e+00],\n       [ 3.858e+03,  3.953e+00, -4.840e+00],\n       [ 3.858e+03,  3.956e+00, -4.840e+00],\n       [ 3.858e+03,  3.958e+00, -4.840e+00],\n       [ 3.858e+03,  3.961e+00, -4.840e+00],\n       [ 3.858e+03,  3.964e+00, -4.840e+00],\n       [ 3.858e+03,  3.967e+00, -4.840e+00],\n       [ 3.858e+03,  3.970e+00, -4.841e+00],\n       [ 3.858e+03,  3.973e+00, -4.841e+00],\n       [ 3.858e+03,  3.976e+00, -4.841e+00],\n       [ 3.858e+03,  3.979e+00, -4.842e+00],\n       [ 3.858e+03,  3.982e+00, -4.842e+00],\n       [ 3.858e+03,  3.984e+00, -4.842e+00],\n       [ 3.858e+03,  3.987e+00, -4.843e+00]]), array([[ 3.859e+03,  3.701e+00, -4.840e+00],\n       [ 3.859e+03,  3.704e+00, -4.840e+00],\n       [ 3.859e+03,  3.707e+00, -4.840e+00],\n       [ 3.859e+03,  3.710e+00, -4.840e+00],\n       [ 3.859e+03,  3.713e+00, -4.839e+00],\n       [ 3.859e+03,  3.716e+00, -4.839e+00],\n       [ 3.859e+03,  3.719e+00, -4.840e+00],\n       [ 3.859e+03,  3.722e+00, -4.840e+00],\n       [ 3.859e+03,  3.725e+00, -4.840e+00],\n       [ 3.859e+03,  3.728e+00, -4.840e+00],\n       [ 3.859e+03,  3.730e+00, -4.840e+00],\n       [ 3.859e+03,  3.733e+00, -4.840e+00],\n       [ 3.859e+03,  3.736e+00, -4.840e+00],\n       [ 3.859e+03,  3.739e+00, -4.840e+00],\n       [ 3.859e+03,  3.742e+00, 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3.806e+00, -4.840e+00],\n       [ 3.859e+03,  3.809e+00, -4.840e+00],\n       [ 3.859e+03,  3.812e+00, -4.840e+00],\n       [ 3.859e+03,  3.815e+00, -4.840e+00],\n       [ 3.859e+03,  3.818e+00, -4.840e+00],\n       [ 3.859e+03,  3.821e+00, -4.840e+00],\n       [ 3.859e+03,  3.823e+00, -4.840e+00],\n       [ 3.859e+03,  3.826e+00, -4.840e+00],\n       [ 3.859e+03,  3.829e+00, -4.840e+00],\n       [ 3.859e+03,  3.832e+00, -4.840e+00],\n       [ 3.859e+03,  3.835e+00, -4.840e+00],\n       [ 3.859e+03,  3.838e+00, -4.840e+00],\n       [ 3.859e+03,  3.841e+00, -4.840e+00],\n       [ 3.859e+03,  3.844e+00, -4.840e+00],\n       [ 3.859e+03,  3.847e+00, -4.840e+00],\n       [ 3.859e+03,  3.850e+00, -4.840e+00],\n       [ 3.859e+03,  3.852e+00, -4.840e+00],\n       [ 3.859e+03,  3.855e+00, -4.840e+00],\n       [ 3.859e+03,  3.858e+00, -4.840e+00],\n       [ 3.859e+03,  3.861e+00, -4.840e+00],\n       [ 3.859e+03,  3.864e+00, -4.840e+00],\n       [ 3.859e+03,  3.867e+00, -4.840e+00],\n       [ 3.859e+03,  3.870e+00, -4.840e+00],\n       [ 3.859e+03,  3.873e+00, -4.840e+00],\n       [ 3.859e+03,  3.876e+00, -4.840e+00],\n       [ 3.859e+03,  3.879e+00, -4.840e+00],\n       [ 3.859e+03,  3.882e+00, -4.840e+00],\n       [ 3.859e+03,  3.884e+00, -4.840e+00],\n       [ 3.859e+03,  3.887e+00, -4.840e+00],\n       [ 3.859e+03,  3.890e+00, -4.840e+00],\n       [ 3.859e+03,  3.893e+00, -4.840e+00],\n       [ 3.859e+03,  3.896e+00, -4.840e+00],\n       [ 3.859e+03,  3.899e+00, -4.840e+00],\n       [ 3.859e+03,  3.902e+00, -4.840e+00],\n       [ 3.859e+03,  3.905e+00, -4.840e+00],\n       [ 3.859e+03,  3.908e+00, -4.840e+00],\n       [ 3.859e+03,  3.911e+00, -4.840e+00],\n       [ 3.859e+03,  3.913e+00, -4.840e+00],\n       [ 3.859e+03,  3.916e+00, -4.840e+00],\n       [ 3.859e+03,  3.919e+00, -4.840e+00],\n       [ 3.859e+03,  3.922e+00, -4.840e+00],\n       [ 3.859e+03,  3.925e+00, -4.840e+00],\n       [ 3.859e+03,  3.928e+00, -4.840e+00],\n       [ 3.859e+03,  3.931e+00, -4.840e+00],\n       [ 3.859e+03,  3.934e+00, -4.840e+00],\n       [ 3.859e+03,  3.937e+00, -4.840e+00],\n       [ 3.859e+03,  3.940e+00, -4.840e+00],\n       [ 3.859e+03,  3.943e+00, -4.840e+00],\n       [ 3.859e+03,  3.945e+00, -4.840e+00],\n       [ 3.859e+03,  3.948e+00, -4.840e+00],\n       [ 3.859e+03,  3.951e+00, -4.840e+00],\n       [ 3.859e+03,  3.954e+00, -4.840e+00],\n       [ 3.859e+03,  3.957e+00, -4.840e+00],\n       [ 3.859e+03,  3.960e+00, -4.840e+00],\n       [ 3.859e+03,  3.963e+00, -4.841e+00],\n       [ 3.859e+03,  3.966e+00, -4.841e+00],\n       [ 3.859e+03,  3.969e+00, -4.841e+00],\n       [ 3.859e+03,  3.972e+00, -4.842e+00],\n       [ 3.859e+03,  3.974e+00, -4.842e+00],\n       [ 3.859e+03,  3.977e+00, -4.842e+00],\n       [ 3.859e+03,  3.980e+00, -4.842e+00],\n       [ 3.859e+03,  3.983e+00, -4.843e+00],\n       [ 3.859e+03,  3.986e+00, -4.843e+00],\n       [ 3.859e+03,  3.989e+00, -4.843e+00]]), array([[ 3.860e+03,  3.701e+00, -4.840e+00],\n       [ 3.860e+03, 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3.860e+03,  3.768e+00, -4.840e+00],\n       [ 3.860e+03,  3.771e+00, -4.839e+00],\n       [ 3.860e+03,  3.774e+00, -4.840e+00],\n       [ 3.860e+03,  3.777e+00, -4.840e+00],\n       [ 3.860e+03,  3.780e+00, -4.840e+00],\n       [ 3.860e+03,  3.783e+00, -4.840e+00],\n       [ 3.860e+03,  3.786e+00, -4.840e+00],\n       [ 3.860e+03,  3.789e+00, -4.840e+00],\n       [ 3.860e+03,  3.791e+00, -4.840e+00],\n       [ 3.860e+03,  3.794e+00, -4.840e+00],\n       [ 3.860e+03,  3.797e+00, -4.840e+00],\n       [ 3.860e+03,  3.800e+00, -4.840e+00],\n       [ 3.860e+03,  3.803e+00, -4.840e+00],\n       [ 3.860e+03,  3.806e+00, -4.840e+00],\n       [ 3.860e+03,  3.809e+00, -4.840e+00],\n       [ 3.860e+03,  3.812e+00, -4.840e+00],\n       [ 3.860e+03,  3.815e+00, -4.840e+00],\n       [ 3.860e+03,  3.818e+00, -4.840e+00],\n       [ 3.860e+03,  3.821e+00, -4.840e+00],\n       [ 3.860e+03,  3.823e+00, -4.840e+00],\n       [ 3.860e+03,  3.826e+00, -4.840e+00],\n       [ 3.860e+03,  3.829e+00, 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3.893e+00, -4.840e+00],\n       [ 3.860e+03,  3.896e+00, -4.840e+00],\n       [ 3.860e+03,  3.899e+00, -4.840e+00],\n       [ 3.860e+03,  3.902e+00, -4.840e+00],\n       [ 3.860e+03,  3.905e+00, -4.839e+00],\n       [ 3.860e+03,  3.908e+00, -4.839e+00],\n       [ 3.860e+03,  3.911e+00, -4.840e+00],\n       [ 3.860e+03,  3.913e+00, -4.840e+00],\n       [ 3.860e+03,  3.916e+00, -4.840e+00],\n       [ 3.860e+03,  3.919e+00, -4.840e+00],\n       [ 3.860e+03,  3.922e+00, -4.840e+00],\n       [ 3.860e+03,  3.925e+00, -4.840e+00],\n       [ 3.860e+03,  3.928e+00, -4.840e+00],\n       [ 3.860e+03,  3.931e+00, -4.840e+00],\n       [ 3.860e+03,  3.934e+00, -4.840e+00],\n       [ 3.860e+03,  3.937e+00, -4.840e+00],\n       [ 3.860e+03,  3.940e+00, -4.840e+00],\n       [ 3.860e+03,  3.943e+00, -4.840e+00],\n       [ 3.860e+03,  3.945e+00, -4.840e+00],\n       [ 3.860e+03,  3.948e+00, -4.840e+00],\n       [ 3.860e+03,  3.951e+00, -4.840e+00],\n       [ 3.860e+03,  3.954e+00, -4.840e+00],\n       [ 3.860e+03,  3.957e+00, -4.840e+00],\n       [ 3.860e+03,  3.960e+00, -4.840e+00],\n       [ 3.860e+03,  3.963e+00, -4.840e+00],\n       [ 3.860e+03,  3.966e+00, -4.841e+00],\n       [ 3.860e+03,  3.969e+00, -4.841e+00],\n       [ 3.860e+03,  3.972e+00, -4.842e+00],\n       [ 3.860e+03,  3.974e+00, -4.842e+00],\n       [ 3.860e+03,  3.977e+00, -4.843e+00],\n       [ 3.860e+03,  3.980e+00, -4.843e+00],\n       [ 3.860e+03,  3.983e+00, -4.844e+00],\n       [ 3.860e+03,  3.986e+00, -4.845e+00],\n       [ 3.860e+03,  3.989e+00, -4.845e+00]]), array([[ 3.861e+03,  3.701e+00, -4.840e+00],\n       [ 3.861e+03,  3.704e+00, -4.840e+00],\n       [ 3.861e+03,  3.707e+00, -4.840e+00],\n       [ 3.861e+03,  3.710e+00, -4.840e+00],\n       [ 3.861e+03,  3.713e+00, -4.840e+00],\n       [ 3.861e+03,  3.716e+00, -4.840e+00],\n       [ 3.861e+03,  3.719e+00, -4.840e+00],\n       [ 3.861e+03,  3.722e+00, -4.840e+00],\n       [ 3.861e+03,  3.725e+00, -4.840e+00],\n       [ 3.861e+03,  3.728e+00, 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3.862e+03,  3.943e+00, -4.840e+00],\n       [ 3.862e+03,  3.945e+00, -4.840e+00],\n       [ 3.862e+03,  3.948e+00, -4.840e+00],\n       [ 3.862e+03,  3.951e+00, -4.840e+00],\n       [ 3.862e+03,  3.954e+00, -4.840e+00],\n       [ 3.862e+03,  3.957e+00, -4.840e+00],\n       [ 3.862e+03,  3.960e+00, -4.840e+00],\n       [ 3.862e+03,  3.963e+00, -4.840e+00],\n       [ 3.862e+03,  3.966e+00, -4.841e+00],\n       [ 3.862e+03,  3.969e+00, -4.841e+00],\n       [ 3.862e+03,  3.972e+00, -4.841e+00],\n       [ 3.862e+03,  3.974e+00, -4.842e+00],\n       [ 3.862e+03,  3.977e+00, -4.842e+00],\n       [ 3.862e+03,  3.980e+00, -4.843e+00],\n       [ 3.862e+03,  3.983e+00, -4.843e+00],\n       [ 3.862e+03,  3.986e+00, -4.843e+00],\n       [ 3.862e+03,  3.989e+00, -4.844e+00]]), array([[ 3.863e+03,  3.701e+00, -4.841e+00],\n       [ 3.863e+03,  3.704e+00, -4.840e+00],\n       [ 3.863e+03,  3.707e+00, -4.840e+00],\n       [ 3.863e+03,  3.710e+00, -4.840e+00],\n       [ 3.863e+03,  3.713e+00, 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-4.843e+00]]), array([[ 3.865e+03,  3.701e+00, -4.840e+00],\n       [ 3.865e+03,  3.704e+00, -4.840e+00],\n       [ 3.865e+03,  3.707e+00, -4.840e+00],\n       [ 3.865e+03,  3.710e+00, -4.840e+00],\n       [ 3.865e+03,  3.713e+00, -4.840e+00],\n       [ 3.865e+03,  3.716e+00, -4.840e+00],\n       [ 3.865e+03,  3.719e+00, -4.840e+00],\n       [ 3.865e+03,  3.722e+00, -4.840e+00],\n       [ 3.865e+03,  3.725e+00, -4.840e+00],\n       [ 3.865e+03,  3.728e+00, -4.840e+00],\n       [ 3.865e+03,  3.730e+00, -4.840e+00],\n       [ 3.865e+03,  3.733e+00, -4.840e+00],\n       [ 3.865e+03,  3.736e+00, -4.840e+00],\n       [ 3.865e+03,  3.739e+00, -4.840e+00],\n       [ 3.865e+03,  3.742e+00, -4.840e+00],\n       [ 3.865e+03,  3.745e+00, -4.840e+00],\n       [ 3.865e+03,  3.748e+00, -4.840e+00],\n       [ 3.865e+03,  3.751e+00, -4.840e+00],\n       [ 3.865e+03,  3.754e+00, -4.840e+00],\n       [ 3.865e+03,  3.757e+00, -4.840e+00],\n       [ 3.865e+03,  3.759e+00, -4.840e+00],\n       [ 3.865e+03, 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[856.   ,   3.669,  -0.968],\n       [856.   ,   3.676,  -0.968],\n       [856.   ,   3.684,  -0.968],\n       [856.   ,   3.691,  -0.968],\n       [856.   ,   3.698,  -0.968],\n       [856.   ,   3.705,  -0.968],\n       [856.   ,   3.712,  -0.968],\n       [856.   ,   3.72 ,  -0.968],\n       [856.   ,   3.727,  -0.968],\n       [856.   ,   3.734,  -0.968],\n       [856.   ,   3.741,  -0.968],\n       [856.   ,   3.748,  -0.968],\n       [856.   ,   3.756,  -0.968],\n       [856.   ,   3.763,  -0.968],\n       [856.   ,   3.77 ,  -0.968],\n       [856.   ,   3.777,  -0.968],\n       [856.   ,   3.784,  -0.968],\n       [856.   ,   3.792,  -0.968],\n       [856.   ,   3.799,  -0.968],\n       [856.   ,   3.806,  -0.968],\n       [856.   ,   3.813,  -0.968],\n       [856.   ,   3.82 ,  -0.968],\n       [856.   ,   3.828,  -0.968],\n       [856.   ,   3.835,  -0.968],\n       [856.   ,   3.842,  -0.968],\n       [856.   ,   3.849,  -0.968],\n       [856.   ,   3.856,  -0.968],\n       [856.   ,   3.864,  -0.968],\n       [856.   ,   3.871,  -0.968],\n       [856.   ,   3.878,  -0.968],\n       [856.   ,   3.885,  -0.968],\n       [856.   ,   3.893,  -0.968],\n       [856.   ,   3.9  ,  -0.968],\n       [856.   ,   3.907,  -0.968],\n       [856.   ,   3.914,  -0.971]]), array([[857.   ,   3.201,  -0.968],\n       [857.   ,   3.208,  -0.968],\n       [857.   ,   3.216,  -0.968],\n       [857.   ,   3.223,  -0.968],\n       [857.   ,   3.23 ,  -0.968],\n       [857.   ,   3.238,  -0.968],\n       [857.   ,   3.245,  -0.968],\n       [857.   ,   3.252,  -0.968],\n       [857.   ,   3.259,  -0.968],\n       [857.   ,   3.267,  -0.968],\n       [857.   ,   3.274,  -0.968],\n       [857.   ,   3.281,  -0.968],\n       [857.   ,   3.289,  -0.968],\n       [857.   ,   3.296,  -0.968],\n       [857.   ,   3.303,  -0.968],\n       [857.   ,   3.31 ,  -0.968],\n       [857.   ,   3.318,  -0.968],\n       [857.   ,   3.325,  -0.968],\n       [857.   ,   3.332,  -0.968],\n       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[857.   ,   3.536,  -0.968],\n       [857.   ,   3.544,  -0.968],\n       [857.   ,   3.551,  -0.968],\n       [857.   ,   3.558,  -0.968],\n       [857.   ,   3.566,  -0.968],\n       [857.   ,   3.573,  -0.967],\n       [857.   ,   3.58 ,  -0.968],\n       [857.   ,   3.587,  -0.968],\n       [857.   ,   3.595,  -0.968],\n       [857.   ,   3.602,  -0.968],\n       [857.   ,   3.609,  -0.968],\n       [857.   ,   3.617,  -0.968],\n       [857.   ,   3.624,  -0.968],\n       [857.   ,   3.631,  -0.968],\n       [857.   ,   3.638,  -0.968],\n       [857.   ,   3.646,  -0.968],\n       [857.   ,   3.653,  -0.968],\n       [857.   ,   3.66 ,  -0.968],\n       [857.   ,   3.668,  -0.968],\n       [857.   ,   3.675,  -0.968],\n       [857.   ,   3.682,  -0.968],\n       [857.   ,   3.689,  -0.968],\n       [857.   ,   3.697,  -0.968],\n       [857.   ,   3.704,  -0.968],\n       [857.   ,   3.711,  -0.968],\n       [857.   ,   3.719,  -0.968],\n       [857.   ,   3.726,  -0.968],\n       [857.   ,   3.733,  -0.968],\n       [857.   ,   3.74 ,  -0.968],\n       [857.   ,   3.748,  -0.968],\n       [857.   ,   3.755,  -0.968],\n       [857.   ,   3.762,  -0.968],\n       [857.   ,   3.77 ,  -0.968],\n       [857.   ,   3.777,  -0.968],\n       [857.   ,   3.784,  -0.968],\n       [857.   ,   3.791,  -0.968],\n       [857.   ,   3.799,  -0.968],\n       [857.   ,   3.806,  -0.967],\n       [857.   ,   3.813,  -0.968],\n       [857.   ,   3.821,  -0.968],\n       [857.   ,   3.828,  -0.968],\n       [857.   ,   3.835,  -0.968],\n       [857.   ,   3.842,  -0.968],\n       [857.   ,   3.85 ,  -0.968],\n       [857.   ,   3.857,  -0.968],\n       [857.   ,   3.864,  -0.968],\n       [857.   ,   3.872,  -0.968],\n       [857.   ,   3.879,  -0.968],\n       [857.   ,   3.886,  -0.968],\n       [857.   ,   3.893,  -0.968],\n       [857.   ,   3.901,  -0.968],\n       [857.   ,   3.908,  -0.968],\n       [857.   ,   3.915,  -0.968],\n       [857.   ,   3.923,  -0.973]]), array([[858.   ,   3.201,  -0.967],\n       [858.   ,   3.208,  -0.968],\n       [858.   ,   3.216,  -0.968],\n       [858.   ,   3.223,  -0.968],\n       [858.   ,   3.23 ,  -0.968],\n       [858.   ,   3.237,  -0.968],\n       [858.   ,   3.244,  -0.968],\n       [858.   ,   3.252,  -0.968],\n       [858.   ,   3.259,  -0.968],\n       [858.   ,   3.266,  -0.968],\n       [858.   ,   3.273,  -0.968],\n       [858.   ,   3.281,  -0.968],\n       [858.   ,   3.288,  -0.968],\n       [858.   ,   3.295,  -0.968],\n       [858.   ,   3.302,  -0.968],\n       [858.   ,   3.309,  -0.968],\n       [858.   ,   3.317,  -0.968],\n       [858.   ,   3.324,  -0.968],\n       [858.   ,   3.331,  -0.968],\n       [858.   ,   3.338,  -0.968],\n       [858.   ,   3.345,  -0.968],\n       [858.   ,   3.353,  -0.968],\n       [858.   ,   3.36 ,  -0.968],\n       [858.   ,   3.367,  -0.968],\n       [858.   ,   3.374,  -0.968],\n       [858.   ,   3.382,  -0.968],\n       [858.   ,   3.389,  -0.967],\n  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   [858.   ,   3.591,  -0.968],\n       [858.   ,   3.598,  -0.968],\n       [858.   ,   3.605,  -0.968],\n       [858.   ,   3.613,  -0.968],\n       [858.   ,   3.62 ,  -0.968],\n       [858.   ,   3.627,  -0.968],\n       [858.   ,   3.634,  -0.968],\n       [858.   ,   3.641,  -0.968],\n       [858.   ,   3.649,  -0.968],\n       [858.   ,   3.656,  -0.968],\n       [858.   ,   3.663,  -0.968],\n       [858.   ,   3.67 ,  -0.968],\n       [858.   ,   3.678,  -0.968],\n       [858.   ,   3.685,  -0.968],\n       [858.   ,   3.692,  -0.968],\n       [858.   ,   3.699,  -0.968],\n       [858.   ,   3.706,  -0.968],\n       [858.   ,   3.714,  -0.968],\n       [858.   ,   3.721,  -0.968],\n       [858.   ,   3.728,  -0.968],\n       [858.   ,   3.735,  -0.968],\n       [858.   ,   3.743,  -0.968],\n       [858.   ,   3.75 ,  -0.968],\n       [858.   ,   3.757,  -0.968],\n       [858.   ,   3.764,  -0.968],\n       [858.   ,   3.771,  -0.968],\n       [858.   ,   3.779,  -0.968],\n       [858.   ,   3.786,  -0.968],\n       [858.   ,   3.793,  -0.968],\n       [858.   ,   3.8  ,  -0.968],\n       [858.   ,   3.808,  -0.968],\n       [858.   ,   3.815,  -0.968],\n       [858.   ,   3.822,  -0.968],\n       [858.   ,   3.829,  -0.968],\n       [858.   ,   3.836,  -0.968],\n       [858.   ,   3.844,  -0.968],\n       [858.   ,   3.851,  -0.968],\n       [858.   ,   3.858,  -0.968],\n       [858.   ,   3.865,  -0.968],\n       [858.   ,   3.872,  -0.968],\n       [858.   ,   3.88 ,  -0.968],\n       [858.   ,   3.887,  -0.968],\n       [858.   ,   3.894,  -0.968],\n       [858.   ,   3.901,  -0.968],\n       [858.   ,   3.909,  -0.968],\n       [858.   ,   3.916,  -0.973]]), array([[859.   ,   3.201,  -0.968],\n       [859.   ,   3.208,  -0.968],\n       [859.   ,   3.216,  -0.968],\n       [859.   ,   3.223,  -0.968],\n       [859.   ,   3.23 ,  -0.968],\n       [859.   ,   3.237,  -0.968],\n       [859.   ,   3.244,  -0.968],\n       [859.   ,   3.252,  -0.968],\n       [859.   ,   3.259,  -0.968],\n       [859.   ,   3.266,  -0.968],\n       [859.   ,   3.273,  -0.968],\n       [859.   ,   3.28 ,  -0.968],\n       [859.   ,   3.288,  -0.968],\n       [859.   ,   3.295,  -0.968],\n       [859.   ,   3.302,  -0.968],\n       [859.   ,   3.309,  -0.968],\n       [859.   ,   3.316,  -0.968],\n       [859.   ,   3.324,  -0.968],\n       [859.   ,   3.331,  -0.968],\n       [859.   ,   3.338,  -0.968],\n       [859.   ,   3.345,  -0.968],\n       [859.   ,   3.352,  -0.968],\n       [859.   ,   3.36 ,  -0.968],\n       [859.   ,   3.367,  -0.968],\n       [859.   ,   3.374,  -0.968],\n       [859.   ,   3.381,  -0.968],\n       [859.   ,   3.388,  -0.968],\n       [859.   ,   3.396,  -0.968],\n       [859.   ,   3.403,  -0.968],\n       [859.   ,   3.41 ,  -0.968],\n       [859.   ,   3.417,  -0.968],\n       [859.   ,   3.424,  -0.968],\n       [859.   ,   3.432,  -0.968],\n       [859.   ,   3.439,  -0.968],\n       [859.   ,   3.446,  -0.967],\n       [859.   ,   3.453,  -0.968],\n       [859.   ,   3.46 ,  -0.968],\n       [859.   ,   3.468,  -0.968],\n       [859.   ,   3.475,  -0.968],\n       [859.   ,   3.482,  -0.968],\n       [859.   ,   3.489,  -0.968],\n       [859.   ,   3.496,  -0.968],\n       [859.   ,   3.504,  -0.968],\n       [859.   ,   3.511,  -0.968],\n       [859.   ,   3.518,  -0.968],\n       [859.   ,   3.525,  -0.968],\n       [859.   ,   3.532,  -0.968],\n       [859.   ,   3.54 ,  -0.968],\n       [859.   ,   3.547,  -0.968],\n       [859.   ,   3.554,  -0.968],\n       [859.   ,   3.561,  -0.968],\n       [859.   ,   3.568,  -0.968],\n       [859.   ,   3.576,  -0.967],\n       [859.   ,   3.583,  -0.968],\n       [859.   ,   3.59 ,  -0.968],\n       [859.   ,   3.597,  -0.968],\n       [859.   ,   3.604,  -0.968],\n       [859.   ,   3.612,  -0.969],\n       [859.   ,   3.619,  -0.968],\n       [859.   ,   3.626,  -0.968],\n       [859.   ,   3.633,  -0.968],\n       [859.   ,   3.64 ,  -0.968],\n       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-9.683e+00],\n       [ 4.211e+03,  3.944e+00, -9.683e+00],\n       [ 4.211e+03,  3.946e+00, -9.683e+00],\n       [ 4.211e+03,  3.949e+00, -9.683e+00],\n       [ 4.211e+03,  3.952e+00, -9.683e+00],\n       [ 4.211e+03,  3.955e+00, -9.684e+00],\n       [ 4.211e+03,  3.958e+00, -9.684e+00],\n       [ 4.211e+03,  3.961e+00, -9.684e+00],\n       [ 4.211e+03,  3.963e+00, -9.684e+00],\n       [ 4.211e+03,  3.966e+00, -9.684e+00],\n       [ 4.211e+03,  3.969e+00, -9.684e+00],\n       [ 4.211e+03,  3.972e+00, -9.684e+00],\n       [ 4.211e+03,  3.975e+00, -9.684e+00],\n       [ 4.211e+03,  3.978e+00, -9.684e+00],\n       [ 4.211e+03,  3.980e+00, -9.684e+00]]), array([[ 4.212e+03,  3.700e+00, -9.680e+00],\n       [ 4.212e+03,  3.703e+00, -9.680e+00],\n       [ 4.212e+03,  3.705e+00, -9.680e+00],\n       [ 4.212e+03,  3.708e+00, -9.680e+00],\n       [ 4.212e+03,  3.711e+00, -9.680e+00],\n       [ 4.212e+03,  3.714e+00, -9.680e+00],\n       [ 4.212e+03,  3.717e+00, -9.680e+00],\n       [ 4.212e+03, 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4.212e+03,  3.781e+00, -9.680e+00],\n       [ 4.212e+03,  3.784e+00, -9.680e+00],\n       [ 4.212e+03,  3.787e+00, -9.680e+00],\n       [ 4.212e+03,  3.790e+00, -9.680e+00],\n       [ 4.212e+03,  3.793e+00, -9.680e+00],\n       [ 4.212e+03,  3.796e+00, -9.680e+00],\n       [ 4.212e+03,  3.798e+00, -9.680e+00],\n       [ 4.212e+03,  3.801e+00, -9.680e+00],\n       [ 4.212e+03,  3.804e+00, -9.680e+00],\n       [ 4.212e+03,  3.807e+00, -9.680e+00],\n       [ 4.212e+03,  3.810e+00, -9.680e+00],\n       [ 4.212e+03,  3.812e+00, -9.680e+00],\n       [ 4.212e+03,  3.815e+00, -9.680e+00],\n       [ 4.212e+03,  3.818e+00, -9.680e+00],\n       [ 4.212e+03,  3.821e+00, -9.680e+00],\n       [ 4.212e+03,  3.824e+00, -9.680e+00],\n       [ 4.212e+03,  3.827e+00, -9.680e+00],\n       [ 4.212e+03,  3.829e+00, -9.680e+00],\n       [ 4.212e+03,  3.832e+00, -9.680e+00],\n       [ 4.212e+03,  3.835e+00, -9.680e+00],\n       [ 4.212e+03,  3.838e+00, -9.680e+00],\n       [ 4.212e+03,  3.841e+00, 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4.212e+03,  3.965e+00, -9.686e+00],\n       [ 4.212e+03,  3.968e+00, -9.686e+00],\n       [ 4.212e+03,  3.970e+00, -9.686e+00],\n       [ 4.212e+03,  3.973e+00, -9.686e+00],\n       [ 4.212e+03,  3.976e+00, -9.686e+00],\n       [ 4.212e+03,  3.979e+00, -9.686e+00]]), array([[ 4.213e+03,  3.700e+00, -9.680e+00],\n       [ 4.213e+03,  3.703e+00, -9.680e+00],\n       [ 4.213e+03,  3.705e+00, -9.680e+00],\n       [ 4.213e+03,  3.708e+00, -9.680e+00],\n       [ 4.213e+03,  3.711e+00, -9.680e+00],\n       [ 4.213e+03,  3.714e+00, -9.680e+00],\n       [ 4.213e+03,  3.717e+00, -9.680e+00],\n       [ 4.213e+03,  3.720e+00, -9.680e+00],\n       [ 4.213e+03,  3.722e+00, -9.680e+00],\n       [ 4.213e+03,  3.725e+00, -9.680e+00],\n       [ 4.213e+03,  3.728e+00, -9.680e+00],\n       [ 4.213e+03,  3.731e+00, -9.680e+00],\n       [ 4.213e+03,  3.734e+00, -9.680e+00],\n       [ 4.213e+03,  3.737e+00, -9.680e+00],\n       [ 4.213e+03,  3.739e+00, -9.680e+00],\n       [ 4.213e+03,  3.742e+00, 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4.214e+03,  3.951e+00, -9.684e+00],\n       [ 4.214e+03,  3.954e+00, -9.684e+00],\n       [ 4.214e+03,  3.956e+00, -9.684e+00],\n       [ 4.214e+03,  3.959e+00, -9.685e+00],\n       [ 4.214e+03,  3.962e+00, -9.685e+00],\n       [ 4.214e+03,  3.965e+00, -9.685e+00],\n       [ 4.214e+03,  3.968e+00, -9.685e+00],\n       [ 4.214e+03,  3.970e+00, -9.685e+00],\n       [ 4.214e+03,  3.973e+00, -9.685e+00],\n       [ 4.214e+03,  3.976e+00, -9.685e+00],\n       [ 4.214e+03,  3.979e+00, -9.685e+00]]), array([[ 4.215e+03,  3.700e+00, -9.679e+00],\n       [ 4.215e+03,  3.703e+00, -9.680e+00],\n       [ 4.215e+03,  3.705e+00, -9.680e+00],\n       [ 4.215e+03,  3.708e+00, -9.680e+00],\n       [ 4.215e+03,  3.711e+00, -9.680e+00],\n       [ 4.215e+03,  3.714e+00, -9.680e+00],\n       [ 4.215e+03,  3.717e+00, -9.680e+00],\n       [ 4.215e+03,  3.720e+00, -9.680e+00],\n       [ 4.215e+03,  3.722e+00, -9.680e+00],\n       [ 4.215e+03,  3.725e+00, -9.680e+00],\n       [ 4.215e+03,  3.728e+00, 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-9.683e+00],\n       [ 4.215e+03,  3.915e+00, -9.683e+00],\n       [ 4.215e+03,  3.918e+00, -9.684e+00],\n       [ 4.215e+03,  3.921e+00, -9.684e+00],\n       [ 4.215e+03,  3.924e+00, -9.684e+00],\n       [ 4.215e+03,  3.927e+00, -9.684e+00],\n       [ 4.215e+03,  3.929e+00, -9.684e+00],\n       [ 4.215e+03,  3.932e+00, -9.684e+00],\n       [ 4.215e+03,  3.935e+00, -9.685e+00],\n       [ 4.215e+03,  3.938e+00, -9.685e+00],\n       [ 4.215e+03,  3.941e+00, -9.685e+00],\n       [ 4.215e+03,  3.944e+00, -9.685e+00],\n       [ 4.215e+03,  3.946e+00, -9.685e+00],\n       [ 4.215e+03,  3.949e+00, -9.685e+00],\n       [ 4.215e+03,  3.952e+00, -9.686e+00],\n       [ 4.215e+03,  3.955e+00, -9.686e+00],\n       [ 4.215e+03,  3.958e+00, -9.686e+00],\n       [ 4.215e+03,  3.961e+00, -9.686e+00],\n       [ 4.215e+03,  3.963e+00, -9.686e+00],\n       [ 4.215e+03,  3.966e+00, -9.686e+00],\n       [ 4.215e+03,  3.969e+00, -9.687e+00],\n       [ 4.215e+03,  3.972e+00, -9.687e+00],\n       [ 4.215e+03,  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4.216e+03,  3.937e+00, -9.684e+00],\n       [ 4.216e+03,  3.940e+00, -9.684e+00],\n       [ 4.216e+03,  3.942e+00, -9.685e+00],\n       [ 4.216e+03,  3.945e+00, -9.685e+00],\n       [ 4.216e+03,  3.948e+00, -9.685e+00],\n       [ 4.216e+03,  3.951e+00, -9.685e+00],\n       [ 4.216e+03,  3.954e+00, -9.685e+00],\n       [ 4.216e+03,  3.956e+00, -9.685e+00],\n       [ 4.216e+03,  3.959e+00, -9.685e+00],\n       [ 4.216e+03,  3.962e+00, -9.686e+00],\n       [ 4.216e+03,  3.965e+00, -9.686e+00],\n       [ 4.216e+03,  3.968e+00, -9.686e+00],\n       [ 4.216e+03,  3.970e+00, -9.686e+00],\n       [ 4.216e+03,  3.973e+00, -9.686e+00],\n       [ 4.216e+03,  3.976e+00, -9.686e+00],\n       [ 4.216e+03,  3.979e+00, -9.687e+00]]), array([[ 4.217e+03,  3.701e+00, -9.680e+00],\n       [ 4.217e+03,  3.704e+00, -9.680e+00],\n       [ 4.217e+03,  3.707e+00, -9.680e+00],\n       [ 4.217e+03,  3.710e+00, -9.680e+00],\n       [ 4.217e+03,  3.713e+00, -9.680e+00],\n       [ 4.217e+03,  3.715e+00, 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4.220e+03,  3.910e+00, -9.682e+00],\n       [ 4.220e+03,  3.913e+00, -9.682e+00],\n       [ 4.220e+03,  3.916e+00, -9.683e+00],\n       [ 4.220e+03,  3.918e+00, -9.683e+00],\n       [ 4.220e+03,  3.921e+00, -9.683e+00],\n       [ 4.220e+03,  3.924e+00, -9.683e+00],\n       [ 4.220e+03,  3.927e+00, -9.683e+00],\n       [ 4.220e+03,  3.930e+00, -9.683e+00],\n       [ 4.220e+03,  3.933e+00, -9.683e+00],\n       [ 4.220e+03,  3.935e+00, -9.683e+00],\n       [ 4.220e+03,  3.938e+00, -9.684e+00],\n       [ 4.220e+03,  3.941e+00, -9.684e+00],\n       [ 4.220e+03,  3.944e+00, -9.684e+00],\n       [ 4.220e+03,  3.947e+00, -9.684e+00],\n       [ 4.220e+03,  3.949e+00, -9.684e+00],\n       [ 4.220e+03,  3.952e+00, -9.684e+00],\n       [ 4.220e+03,  3.955e+00, -9.684e+00],\n       [ 4.220e+03,  3.958e+00, -9.684e+00],\n       [ 4.220e+03,  3.961e+00, -9.685e+00],\n       [ 4.220e+03,  3.964e+00, -9.685e+00],\n       [ 4.220e+03,  3.966e+00, -9.685e+00],\n       [ 4.220e+03,  3.969e+00, 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4.225e+03,  3.965e+00, -9.684e+00],\n       [ 4.225e+03,  3.968e+00, -9.685e+00],\n       [ 4.225e+03,  3.970e+00, -9.685e+00],\n       [ 4.225e+03,  3.973e+00, -9.685e+00],\n       [ 4.225e+03,  3.976e+00, -9.685e+00],\n       [ 4.225e+03,  3.979e+00, -9.685e+00]]), array([[ 4.226e+03,  3.701e+00, -9.680e+00],\n       [ 4.226e+03,  3.704e+00, -9.679e+00],\n       [ 4.226e+03,  3.707e+00, -9.679e+00],\n       [ 4.226e+03,  3.710e+00, -9.679e+00],\n       [ 4.226e+03,  3.713e+00, -9.679e+00],\n       [ 4.226e+03,  3.715e+00, -9.679e+00],\n       [ 4.226e+03,  3.718e+00, -9.679e+00],\n       [ 4.226e+03,  3.721e+00, -9.679e+00],\n       [ 4.226e+03,  3.724e+00, -9.680e+00],\n       [ 4.226e+03,  3.727e+00, -9.680e+00],\n       [ 4.226e+03,  3.730e+00, -9.680e+00],\n       [ 4.226e+03,  3.732e+00, -9.680e+00],\n       [ 4.226e+03,  3.735e+00, -9.680e+00],\n       [ 4.226e+03,  3.738e+00, -9.680e+00],\n       [ 4.226e+03,  3.741e+00, -9.680e+00],\n       [ 4.226e+03,  3.744e+00, 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4.227e+03,  3.951e+00, -9.685e+00],\n       [ 4.227e+03,  3.954e+00, -9.685e+00],\n       [ 4.227e+03,  3.956e+00, -9.685e+00],\n       [ 4.227e+03,  3.959e+00, -9.686e+00],\n       [ 4.227e+03,  3.962e+00, -9.686e+00],\n       [ 4.227e+03,  3.965e+00, -9.686e+00],\n       [ 4.227e+03,  3.968e+00, -9.686e+00],\n       [ 4.227e+03,  3.970e+00, -9.686e+00],\n       [ 4.227e+03,  3.973e+00, -9.686e+00],\n       [ 4.227e+03,  3.976e+00, -9.686e+00],\n       [ 4.227e+03,  3.979e+00, -9.687e+00]]), array([[ 4.228e+03,  3.701e+00, -9.680e+00],\n       [ 4.228e+03,  3.704e+00, -9.680e+00],\n       [ 4.228e+03,  3.707e+00, -9.680e+00],\n       [ 4.228e+03,  3.710e+00, -9.680e+00],\n       [ 4.228e+03,  3.713e+00, -9.680e+00],\n       [ 4.228e+03,  3.715e+00, -9.680e+00],\n       [ 4.228e+03,  3.718e+00, -9.680e+00],\n       [ 4.228e+03,  3.721e+00, -9.679e+00],\n       [ 4.228e+03,  3.724e+00, -9.679e+00],\n       [ 4.228e+03,  3.727e+00, -9.679e+00],\n       [ 4.228e+03,  3.729e+00, 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3.522e+03,  3.772e+00, -9.680e+00],\n       [ 3.522e+03,  3.776e+00, -9.680e+00],\n       [ 3.522e+03,  3.780e+00, -9.680e+00],\n       [ 3.522e+03,  3.784e+00, -9.680e+00],\n       [ 3.522e+03,  3.788e+00, -9.680e+00],\n       [ 3.522e+03,  3.792e+00, -9.680e+00],\n       [ 3.522e+03,  3.796e+00, -9.680e+00],\n       [ 3.522e+03,  3.800e+00, -9.680e+00],\n       [ 3.522e+03,  3.804e+00, -9.680e+00],\n       [ 3.522e+03,  3.808e+00, -9.680e+00],\n       [ 3.522e+03,  3.812e+00, -9.680e+00],\n       [ 3.522e+03,  3.816e+00, -9.680e+00],\n       [ 3.522e+03,  3.819e+00, -9.680e+00],\n       [ 3.522e+03,  3.823e+00, -9.680e+00],\n       [ 3.522e+03,  3.827e+00, -9.680e+00],\n       [ 3.522e+03,  3.831e+00, -9.680e+00],\n       [ 3.522e+03,  3.835e+00, -9.680e+00],\n       [ 3.522e+03,  3.839e+00, -9.680e+00],\n       [ 3.522e+03,  3.843e+00, -9.680e+00],\n       [ 3.522e+03,  3.847e+00, -9.680e+00],\n       [ 3.522e+03,  3.851e+00, -9.681e+00],\n       [ 3.522e+03,  3.855e+00, -9.681e+00],\n       [ 3.522e+03,  3.859e+00, -9.681e+00],\n       [ 3.522e+03,  3.863e+00, -9.682e+00],\n       [ 3.522e+03,  3.867e+00, -9.682e+00],\n       [ 3.522e+03,  3.871e+00, -9.682e+00],\n       [ 3.522e+03,  3.875e+00, -9.683e+00],\n       [ 3.522e+03,  3.878e+00, -9.683e+00],\n       [ 3.522e+03,  3.882e+00, -9.683e+00],\n       [ 3.522e+03,  3.886e+00, -9.684e+00],\n       [ 3.522e+03,  3.890e+00, -9.684e+00]]), array([[ 3.523e+03,  3.501e+00, -9.680e+00],\n       [ 3.523e+03,  3.505e+00, -9.679e+00],\n       [ 3.523e+03,  3.508e+00, -9.680e+00],\n       [ 3.523e+03,  3.512e+00, -9.680e+00],\n       [ 3.523e+03,  3.516e+00, -9.680e+00],\n       [ 3.523e+03,  3.520e+00, -9.680e+00],\n       [ 3.523e+03,  3.524e+00, -9.680e+00],\n       [ 3.523e+03,  3.528e+00, -9.680e+00],\n       [ 3.523e+03,  3.532e+00, -9.680e+00],\n       [ 3.523e+03,  3.536e+00, -9.680e+00],\n       [ 3.523e+03,  3.540e+00, -9.680e+00],\n       [ 3.523e+03,  3.544e+00, -9.680e+00],\n       [ 3.523e+03, 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3.523e+03,  3.890e+00, -9.686e+00]]), array([[ 3.524e+03,  3.501e+00, -9.680e+00],\n       [ 3.524e+03,  3.505e+00, -9.680e+00],\n       [ 3.524e+03,  3.508e+00, -9.680e+00],\n       [ 3.524e+03,  3.512e+00, -9.680e+00],\n       [ 3.524e+03,  3.516e+00, -9.680e+00],\n       [ 3.524e+03,  3.520e+00, -9.680e+00],\n       [ 3.524e+03,  3.524e+00, -9.680e+00],\n       [ 3.524e+03,  3.528e+00, -9.680e+00],\n       [ 3.524e+03,  3.532e+00, -9.680e+00],\n       [ 3.524e+03,  3.536e+00, -9.680e+00],\n       [ 3.524e+03,  3.540e+00, -9.680e+00],\n       [ 3.524e+03,  3.544e+00, -9.680e+00],\n       [ 3.524e+03,  3.548e+00, -9.680e+00],\n       [ 3.524e+03,  3.552e+00, -9.680e+00],\n       [ 3.524e+03,  3.556e+00, -9.680e+00],\n       [ 3.524e+03,  3.560e+00, -9.680e+00],\n       [ 3.524e+03,  3.564e+00, -9.680e+00],\n       [ 3.524e+03,  3.568e+00, -9.680e+00],\n       [ 3.524e+03,  3.571e+00, -9.680e+00],\n       [ 3.524e+03,  3.575e+00, -9.680e+00],\n       [ 3.524e+03,  3.579e+00, 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3.524e+03,  3.753e+00, -9.680e+00],\n       [ 3.524e+03,  3.756e+00, -9.680e+00],\n       [ 3.524e+03,  3.760e+00, -9.680e+00],\n       [ 3.524e+03,  3.764e+00, -9.680e+00],\n       [ 3.524e+03,  3.768e+00, -9.680e+00],\n       [ 3.524e+03,  3.772e+00, -9.679e+00],\n       [ 3.524e+03,  3.776e+00, -9.680e+00],\n       [ 3.524e+03,  3.780e+00, -9.680e+00],\n       [ 3.524e+03,  3.784e+00, -9.680e+00],\n       [ 3.524e+03,  3.788e+00, -9.679e+00],\n       [ 3.524e+03,  3.792e+00, -9.680e+00],\n       [ 3.524e+03,  3.796e+00, -9.680e+00],\n       [ 3.524e+03,  3.800e+00, -9.680e+00],\n       [ 3.524e+03,  3.804e+00, -9.680e+00],\n       [ 3.524e+03,  3.808e+00, -9.680e+00],\n       [ 3.524e+03,  3.812e+00, -9.680e+00],\n       [ 3.524e+03,  3.816e+00, -9.680e+00],\n       [ 3.524e+03,  3.819e+00, -9.680e+00],\n       [ 3.524e+03,  3.823e+00, -9.680e+00],\n       [ 3.524e+03,  3.827e+00, -9.680e+00],\n       [ 3.524e+03,  3.831e+00, -9.680e+00],\n       [ 3.524e+03,  3.835e+00, -9.680e+00],\n       [ 3.524e+03,  3.839e+00, -9.680e+00],\n       [ 3.524e+03,  3.843e+00, -9.680e+00],\n       [ 3.524e+03,  3.847e+00, -9.680e+00],\n       [ 3.524e+03,  3.851e+00, -9.681e+00],\n       [ 3.524e+03,  3.855e+00, -9.681e+00],\n       [ 3.524e+03,  3.859e+00, -9.682e+00],\n       [ 3.524e+03,  3.863e+00, -9.682e+00],\n       [ 3.524e+03,  3.867e+00, -9.682e+00],\n       [ 3.524e+03,  3.871e+00, -9.683e+00],\n       [ 3.524e+03,  3.875e+00, -9.683e+00],\n       [ 3.524e+03,  3.878e+00, -9.684e+00],\n       [ 3.524e+03,  3.882e+00, -9.684e+00],\n       [ 3.524e+03,  3.886e+00, -9.685e+00],\n       [ 3.524e+03,  3.890e+00, -9.685e+00]]), array([[ 3.525e+03,  3.501e+00, -9.680e+00],\n       [ 3.525e+03,  3.505e+00, -9.680e+00],\n       [ 3.525e+03,  3.508e+00, -9.680e+00],\n       [ 3.525e+03,  3.512e+00, -9.680e+00],\n       [ 3.525e+03,  3.516e+00, -9.680e+00],\n       [ 3.525e+03,  3.520e+00, -9.680e+00],\n       [ 3.525e+03,  3.524e+00, -9.680e+00],\n       [ 3.525e+03,  3.528e+00, -9.680e+00],\n       [ 3.525e+03,  3.532e+00, -9.680e+00],\n       [ 3.525e+03,  3.536e+00, -9.680e+00],\n       [ 3.525e+03,  3.540e+00, -9.680e+00],\n       [ 3.525e+03,  3.544e+00, -9.680e+00],\n       [ 3.525e+03,  3.548e+00, -9.680e+00],\n       [ 3.525e+03,  3.552e+00, -9.680e+00],\n       [ 3.525e+03,  3.556e+00, -9.680e+00],\n       [ 3.525e+03,  3.560e+00, -9.680e+00],\n       [ 3.525e+03,  3.564e+00, -9.680e+00],\n       [ 3.525e+03,  3.568e+00, -9.680e+00],\n       [ 3.525e+03,  3.571e+00, -9.680e+00],\n       [ 3.525e+03,  3.575e+00, -9.680e+00],\n       [ 3.525e+03,  3.579e+00, -9.680e+00],\n       [ 3.525e+03,  3.583e+00, -9.680e+00],\n       [ 3.525e+03,  3.587e+00, -9.679e+00],\n       [ 3.525e+03,  3.591e+00, -9.680e+00],\n       [ 3.525e+03,  3.595e+00, -9.680e+00],\n       [ 3.525e+03,  3.599e+00, -9.680e+00],\n       [ 3.525e+03,  3.603e+00, -9.680e+00],\n       [ 3.525e+03,  3.607e+00, -9.680e+00],\n       [ 3.525e+03,  3.611e+00, -9.680e+00],\n       [ 3.525e+03,  3.615e+00, -9.680e+00],\n       [ 3.525e+03,  3.619e+00, -9.680e+00],\n       [ 3.525e+03,  3.623e+00, -9.680e+00],\n       [ 3.525e+03,  3.627e+00, -9.680e+00],\n       [ 3.525e+03,  3.630e+00, -9.680e+00],\n       [ 3.525e+03,  3.634e+00, -9.680e+00],\n       [ 3.525e+03,  3.638e+00, -9.679e+00],\n       [ 3.525e+03,  3.642e+00, -9.680e+00],\n       [ 3.525e+03,  3.646e+00, -9.680e+00],\n       [ 3.525e+03,  3.650e+00, -9.680e+00],\n       [ 3.525e+03,  3.654e+00, -9.680e+00],\n       [ 3.525e+03,  3.658e+00, -9.680e+00],\n       [ 3.525e+03,  3.662e+00, -9.680e+00],\n       [ 3.525e+03,  3.666e+00, -9.680e+00],\n       [ 3.525e+03,  3.670e+00, -9.680e+00],\n       [ 3.525e+03,  3.674e+00, -9.680e+00],\n       [ 3.525e+03,  3.678e+00, -9.680e+00],\n       [ 3.525e+03,  3.682e+00, -9.680e+00],\n       [ 3.525e+03,  3.686e+00, -9.680e+00],\n       [ 3.525e+03,  3.690e+00, -9.680e+00],\n       [ 3.525e+03,  3.693e+00, -9.680e+00],\n       [ 3.525e+03,  3.697e+00, -9.680e+00],\n       [ 3.525e+03,  3.701e+00, -9.680e+00],\n       [ 3.525e+03,  3.705e+00, -9.680e+00],\n       [ 3.525e+03,  3.709e+00, -9.680e+00],\n       [ 3.525e+03,  3.713e+00, -9.680e+00],\n       [ 3.525e+03,  3.717e+00, -9.680e+00],\n       [ 3.525e+03,  3.721e+00, -9.680e+00],\n       [ 3.525e+03,  3.725e+00, -9.680e+00],\n       [ 3.525e+03,  3.729e+00, -9.680e+00],\n       [ 3.525e+03,  3.733e+00, -9.680e+00],\n       [ 3.525e+03,  3.737e+00, -9.680e+00],\n       [ 3.525e+03,  3.741e+00, -9.679e+00],\n       [ 3.525e+03,  3.745e+00, -9.680e+00],\n       [ 3.525e+03,  3.749e+00, -9.680e+00],\n       [ 3.525e+03,  3.753e+00, -9.680e+00],\n       [ 3.525e+03,  3.756e+00, -9.680e+00],\n       [ 3.525e+03,  3.760e+00, -9.680e+00],\n       [ 3.525e+03,  3.764e+00, -9.680e+00],\n       [ 3.525e+03,  3.768e+00, -9.680e+00],\n       [ 3.525e+03,  3.772e+00, -9.680e+00],\n       [ 3.525e+03,  3.776e+00, -9.680e+00],\n       [ 3.525e+03,  3.780e+00, -9.680e+00],\n       [ 3.525e+03,  3.784e+00, -9.680e+00],\n       [ 3.525e+03,  3.788e+00, -9.680e+00],\n       [ 3.525e+03,  3.792e+00, -9.680e+00],\n       [ 3.525e+03,  3.796e+00, -9.680e+00],\n       [ 3.525e+03,  3.800e+00, -9.680e+00],\n       [ 3.525e+03,  3.804e+00, -9.680e+00],\n       [ 3.525e+03,  3.808e+00, -9.680e+00],\n       [ 3.525e+03,  3.812e+00, -9.680e+00],\n       [ 3.525e+03,  3.816e+00, -9.680e+00],\n       [ 3.525e+03,  3.819e+00, -9.680e+00],\n       [ 3.525e+03,  3.823e+00, -9.680e+00],\n       [ 3.525e+03,  3.827e+00, -9.680e+00],\n       [ 3.525e+03,  3.831e+00, -9.680e+00],\n       [ 3.525e+03,  3.835e+00, -9.680e+00],\n       [ 3.525e+03,  3.839e+00, -9.680e+00],\n       [ 3.525e+03,  3.843e+00, -9.680e+00],\n       [ 3.525e+03,  3.847e+00, -9.681e+00],\n       [ 3.525e+03,  3.851e+00, -9.681e+00],\n       [ 3.525e+03,  3.855e+00, -9.682e+00],\n       [ 3.525e+03,  3.859e+00, -9.682e+00],\n       [ 3.525e+03,  3.863e+00, -9.683e+00],\n       [ 3.525e+03,  3.867e+00, -9.683e+00],\n       [ 3.525e+03,  3.871e+00, -9.684e+00],\n       [ 3.525e+03,  3.875e+00, -9.684e+00],\n       [ 3.525e+03,  3.878e+00, -9.685e+00],\n       [ 3.525e+03,  3.882e+00, -9.685e+00],\n       [ 3.525e+03,  3.886e+00, -9.686e+00],\n       [ 3.525e+03,  3.890e+00, -9.686e+00]]), array([[ 3.526e+03,  3.501e+00, -9.680e+00],\n       [ 3.526e+03,  3.505e+00, -9.680e+00],\n       [ 3.526e+03,  3.508e+00, -9.680e+00],\n       [ 3.526e+03,  3.512e+00, -9.680e+00],\n       [ 3.526e+03,  3.516e+00, -9.680e+00],\n       [ 3.526e+03,  3.520e+00, -9.680e+00],\n       [ 3.526e+03,  3.524e+00, -9.680e+00],\n       [ 3.526e+03,  3.528e+00, -9.680e+00],\n       [ 3.526e+03,  3.532e+00, -9.681e+00],\n       [ 3.526e+03,  3.536e+00, -9.680e+00],\n       [ 3.526e+03,  3.540e+00, -9.680e+00],\n       [ 3.526e+03,  3.544e+00, -9.680e+00],\n       [ 3.526e+03,  3.548e+00, -9.680e+00],\n       [ 3.526e+03,  3.552e+00, -9.680e+00],\n       [ 3.526e+03,  3.556e+00, -9.680e+00],\n       [ 3.526e+03,  3.560e+00, -9.680e+00],\n       [ 3.526e+03,  3.564e+00, -9.680e+00],\n       [ 3.526e+03,  3.568e+00, -9.680e+00],\n       [ 3.526e+03,  3.571e+00, -9.680e+00],\n       [ 3.526e+03,  3.575e+00, -9.680e+00],\n       [ 3.526e+03,  3.579e+00, -9.680e+00],\n       [ 3.526e+03,  3.583e+00, -9.680e+00],\n       [ 3.526e+03,  3.587e+00, -9.680e+00],\n       [ 3.526e+03,  3.591e+00, -9.680e+00],\n       [ 3.526e+03,  3.595e+00, -9.680e+00],\n       [ 3.526e+03,  3.599e+00, -9.680e+00],\n       [ 3.526e+03,  3.603e+00, -9.680e+00],\n       [ 3.526e+03,  3.607e+00, -9.680e+00],\n       [ 3.526e+03,  3.611e+00, -9.680e+00],\n       [ 3.526e+03,  3.615e+00, -9.680e+00],\n       [ 3.526e+03,  3.619e+00, -9.680e+00],\n       [ 3.526e+03,  3.623e+00, -9.680e+00],\n       [ 3.526e+03,  3.627e+00, -9.680e+00],\n       [ 3.526e+03,  3.630e+00, -9.680e+00],\n       [ 3.526e+03,  3.634e+00, -9.680e+00],\n       [ 3.526e+03,  3.638e+00, -9.680e+00],\n       [ 3.526e+03,  3.642e+00, -9.680e+00],\n       [ 3.526e+03,  3.646e+00, -9.680e+00],\n       [ 3.526e+03,  3.650e+00, -9.680e+00],\n       [ 3.526e+03,  3.654e+00, -9.680e+00],\n       [ 3.526e+03,  3.658e+00, -9.680e+00],\n       [ 3.526e+03,  3.662e+00, -9.680e+00],\n       [ 3.526e+03,  3.666e+00, -9.680e+00],\n       [ 3.526e+03,  3.670e+00, -9.680e+00],\n       [ 3.526e+03,  3.674e+00, -9.680e+00],\n       [ 3.526e+03,  3.678e+00, -9.680e+00],\n       [ 3.526e+03,  3.682e+00, -9.680e+00],\n       [ 3.526e+03,  3.686e+00, -9.680e+00],\n       [ 3.526e+03,  3.690e+00, -9.680e+00],\n       [ 3.526e+03,  3.693e+00, -9.680e+00],\n       [ 3.526e+03,  3.697e+00, -9.680e+00],\n       [ 3.526e+03,  3.701e+00, -9.680e+00],\n       [ 3.526e+03,  3.705e+00, -9.680e+00],\n       [ 3.526e+03,  3.709e+00, -9.680e+00],\n       [ 3.526e+03,  3.713e+00, -9.680e+00],\n       [ 3.526e+03,  3.717e+00, -9.680e+00],\n       [ 3.526e+03,  3.721e+00, -9.680e+00],\n       [ 3.526e+03,  3.725e+00, -9.680e+00],\n       [ 3.526e+03,  3.729e+00, -9.680e+00],\n       [ 3.526e+03,  3.733e+00, -9.680e+00],\n       [ 3.526e+03,  3.737e+00, -9.680e+00],\n       [ 3.526e+03,  3.741e+00, -9.680e+00],\n       [ 3.526e+03,  3.745e+00, -9.680e+00],\n       [ 3.526e+03,  3.749e+00, -9.680e+00],\n       [ 3.526e+03,  3.753e+00, -9.680e+00],\n       [ 3.526e+03,  3.756e+00, -9.680e+00],\n       [ 3.526e+03,  3.760e+00, -9.680e+00],\n       [ 3.526e+03,  3.764e+00, -9.680e+00],\n       [ 3.526e+03,  3.768e+00, -9.680e+00],\n       [ 3.526e+03,  3.772e+00, -9.680e+00],\n       [ 3.526e+03,  3.776e+00, -9.680e+00],\n       [ 3.526e+03,  3.780e+00, -9.680e+00],\n       [ 3.526e+03,  3.784e+00, -9.680e+00],\n       [ 3.526e+03,  3.788e+00, -9.680e+00],\n       [ 3.526e+03,  3.792e+00, -9.680e+00],\n       [ 3.526e+03,  3.796e+00, -9.680e+00],\n       [ 3.526e+03,  3.800e+00, -9.680e+00],\n       [ 3.526e+03,  3.804e+00, -9.680e+00],\n       [ 3.526e+03,  3.808e+00, -9.680e+00],\n       [ 3.526e+03,  3.812e+00, -9.680e+00],\n       [ 3.526e+03,  3.816e+00, -9.680e+00],\n       [ 3.526e+03,  3.819e+00, -9.680e+00],\n       [ 3.526e+03,  3.823e+00, -9.680e+00],\n       [ 3.526e+03,  3.827e+00, -9.680e+00],\n       [ 3.526e+03,  3.831e+00, -9.680e+00],\n       [ 3.526e+03,  3.835e+00, -9.680e+00],\n       [ 3.526e+03,  3.839e+00, -9.680e+00],\n       [ 3.526e+03,  3.843e+00, -9.680e+00],\n       [ 3.526e+03,  3.847e+00, -9.680e+00],\n       [ 3.526e+03,  3.851e+00, -9.681e+00],\n       [ 3.526e+03,  3.855e+00, -9.681e+00],\n       [ 3.526e+03,  3.859e+00, -9.682e+00],\n       [ 3.526e+03,  3.863e+00, -9.682e+00],\n       [ 3.526e+03,  3.867e+00, -9.683e+00],\n       [ 3.526e+03,  3.871e+00, -9.683e+00],\n       [ 3.526e+03,  3.875e+00, -9.684e+00],\n       [ 3.526e+03,  3.878e+00, -9.684e+00],\n       [ 3.526e+03,  3.882e+00, -9.685e+00],\n       [ 3.526e+03,  3.886e+00, -9.685e+00],\n       [ 3.526e+03,  3.890e+00, -9.686e+00]]), array([[ 3.527e+03,  3.501e+00, -9.680e+00],\n       [ 3.527e+03,  3.505e+00, -9.680e+00],\n       [ 3.527e+03, 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3.527e+03,  3.595e+00, -9.680e+00],\n       [ 3.527e+03,  3.599e+00, -9.680e+00],\n       [ 3.527e+03,  3.603e+00, -9.680e+00],\n       [ 3.527e+03,  3.607e+00, -9.680e+00],\n       [ 3.527e+03,  3.611e+00, -9.680e+00],\n       [ 3.527e+03,  3.615e+00, -9.680e+00],\n       [ 3.527e+03,  3.619e+00, -9.680e+00],\n       [ 3.527e+03,  3.623e+00, -9.680e+00],\n       [ 3.527e+03,  3.627e+00, -9.680e+00],\n       [ 3.527e+03,  3.630e+00, -9.680e+00],\n       [ 3.527e+03,  3.634e+00, -9.680e+00],\n       [ 3.527e+03,  3.638e+00, -9.680e+00],\n       [ 3.527e+03,  3.642e+00, -9.680e+00],\n       [ 3.527e+03,  3.646e+00, -9.680e+00],\n       [ 3.527e+03,  3.650e+00, -9.680e+00],\n       [ 3.527e+03,  3.654e+00, -9.680e+00],\n       [ 3.527e+03,  3.658e+00, -9.680e+00],\n       [ 3.527e+03,  3.662e+00, -9.679e+00],\n       [ 3.527e+03,  3.666e+00, -9.680e+00],\n       [ 3.527e+03,  3.670e+00, -9.680e+00],\n       [ 3.527e+03,  3.674e+00, -9.680e+00],\n       [ 3.527e+03,  3.678e+00, 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3.527e+03,  3.851e+00, -9.681e+00],\n       [ 3.527e+03,  3.855e+00, -9.681e+00],\n       [ 3.527e+03,  3.859e+00, -9.682e+00],\n       [ 3.527e+03,  3.863e+00, -9.682e+00],\n       [ 3.527e+03,  3.867e+00, -9.683e+00],\n       [ 3.527e+03,  3.871e+00, -9.684e+00],\n       [ 3.527e+03,  3.875e+00, -9.684e+00],\n       [ 3.527e+03,  3.878e+00, -9.685e+00],\n       [ 3.527e+03,  3.882e+00, -9.685e+00],\n       [ 3.527e+03,  3.886e+00, -9.686e+00],\n       [ 3.527e+03,  3.890e+00, -9.686e+00]]), array([[ 3.528e+03,  3.501e+00, -9.680e+00],\n       [ 3.528e+03,  3.505e+00, -9.680e+00],\n       [ 3.528e+03,  3.508e+00, -9.680e+00],\n       [ 3.528e+03,  3.512e+00, -9.680e+00],\n       [ 3.528e+03,  3.516e+00, -9.680e+00],\n       [ 3.528e+03,  3.520e+00, -9.680e+00],\n       [ 3.528e+03,  3.524e+00, -9.680e+00],\n       [ 3.528e+03,  3.528e+00, -9.680e+00],\n       [ 3.528e+03,  3.532e+00, -9.680e+00],\n       [ 3.528e+03,  3.536e+00, -9.680e+00],\n       [ 3.528e+03,  3.540e+00, 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3.529e+03,  3.575e+00, -9.680e+00],\n       [ 3.529e+03,  3.579e+00, -9.680e+00],\n       [ 3.529e+03,  3.583e+00, -9.680e+00],\n       [ 3.529e+03,  3.587e+00, -9.680e+00],\n       [ 3.529e+03,  3.591e+00, -9.680e+00],\n       [ 3.529e+03,  3.595e+00, -9.679e+00],\n       [ 3.529e+03,  3.599e+00, -9.680e+00],\n       [ 3.529e+03,  3.603e+00, -9.680e+00],\n       [ 3.529e+03,  3.607e+00, -9.680e+00],\n       [ 3.529e+03,  3.611e+00, -9.680e+00],\n       [ 3.529e+03,  3.615e+00, -9.680e+00],\n       [ 3.529e+03,  3.619e+00, -9.680e+00],\n       [ 3.529e+03,  3.623e+00, -9.680e+00],\n       [ 3.529e+03,  3.627e+00, -9.680e+00],\n       [ 3.529e+03,  3.630e+00, -9.680e+00],\n       [ 3.529e+03,  3.634e+00, -9.680e+00],\n       [ 3.529e+03,  3.638e+00, -9.680e+00],\n       [ 3.529e+03,  3.642e+00, -9.680e+00],\n       [ 3.529e+03,  3.646e+00, -9.681e+00],\n       [ 3.529e+03,  3.650e+00, -9.680e+00],\n       [ 3.529e+03,  3.654e+00, -9.680e+00],\n       [ 3.529e+03,  3.658e+00, 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-9.680e+00],\n       [ 3.532e+03,  3.760e+00, -9.680e+00],\n       [ 3.532e+03,  3.764e+00, -9.680e+00],\n       [ 3.532e+03,  3.768e+00, -9.680e+00],\n       [ 3.532e+03,  3.772e+00, -9.680e+00],\n       [ 3.532e+03,  3.776e+00, -9.680e+00],\n       [ 3.532e+03,  3.780e+00, -9.680e+00],\n       [ 3.532e+03,  3.784e+00, -9.680e+00],\n       [ 3.532e+03,  3.788e+00, -9.680e+00],\n       [ 3.532e+03,  3.792e+00, -9.680e+00],\n       [ 3.532e+03,  3.796e+00, -9.680e+00],\n       [ 3.532e+03,  3.800e+00, -9.680e+00],\n       [ 3.532e+03,  3.804e+00, -9.680e+00],\n       [ 3.532e+03,  3.808e+00, -9.680e+00],\n       [ 3.532e+03,  3.812e+00, -9.680e+00],\n       [ 3.532e+03,  3.816e+00, -9.680e+00],\n       [ 3.532e+03,  3.819e+00, -9.679e+00],\n       [ 3.532e+03,  3.823e+00, -9.680e+00],\n       [ 3.532e+03,  3.827e+00, -9.680e+00],\n       [ 3.532e+03,  3.831e+00, -9.680e+00],\n       [ 3.532e+03,  3.835e+00, -9.680e+00],\n       [ 3.532e+03,  3.839e+00, -9.680e+00],\n       [ 3.532e+03,  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3.533e+03,  3.536e+00, -9.680e+00],\n       [ 3.533e+03,  3.540e+00, -9.680e+00],\n       [ 3.533e+03,  3.544e+00, -9.680e+00],\n       [ 3.533e+03,  3.548e+00, -9.680e+00],\n       [ 3.533e+03,  3.552e+00, -9.680e+00],\n       [ 3.533e+03,  3.556e+00, -9.680e+00],\n       [ 3.533e+03,  3.560e+00, -9.680e+00],\n       [ 3.533e+03,  3.564e+00, -9.680e+00],\n       [ 3.533e+03,  3.568e+00, -9.680e+00],\n       [ 3.533e+03,  3.571e+00, -9.680e+00],\n       [ 3.533e+03,  3.575e+00, -9.680e+00],\n       [ 3.533e+03,  3.579e+00, -9.680e+00],\n       [ 3.533e+03,  3.583e+00, -9.680e+00],\n       [ 3.533e+03,  3.587e+00, -9.680e+00],\n       [ 3.533e+03,  3.591e+00, -9.680e+00],\n       [ 3.533e+03,  3.595e+00, -9.680e+00],\n       [ 3.533e+03,  3.599e+00, -9.680e+00],\n       [ 3.533e+03,  3.603e+00, -9.680e+00],\n       [ 3.533e+03,  3.607e+00, -9.680e+00],\n       [ 3.533e+03,  3.611e+00, -9.680e+00],\n       [ 3.533e+03,  3.615e+00, -9.680e+00],\n       [ 3.533e+03,  3.619e+00, 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3.533e+03,  3.792e+00, -9.680e+00],\n       [ 3.533e+03,  3.796e+00, -9.680e+00],\n       [ 3.533e+03,  3.800e+00, -9.680e+00],\n       [ 3.533e+03,  3.804e+00, -9.680e+00],\n       [ 3.533e+03,  3.808e+00, -9.680e+00],\n       [ 3.533e+03,  3.812e+00, -9.680e+00],\n       [ 3.533e+03,  3.816e+00, -9.680e+00],\n       [ 3.533e+03,  3.819e+00, -9.680e+00],\n       [ 3.533e+03,  3.823e+00, -9.680e+00],\n       [ 3.533e+03,  3.827e+00, -9.680e+00],\n       [ 3.533e+03,  3.831e+00, -9.680e+00],\n       [ 3.533e+03,  3.835e+00, -9.680e+00],\n       [ 3.533e+03,  3.839e+00, -9.680e+00],\n       [ 3.533e+03,  3.843e+00, -9.680e+00],\n       [ 3.533e+03,  3.847e+00, -9.680e+00],\n       [ 3.533e+03,  3.851e+00, -9.680e+00],\n       [ 3.533e+03,  3.855e+00, -9.681e+00],\n       [ 3.533e+03,  3.859e+00, -9.681e+00],\n       [ 3.533e+03,  3.863e+00, -9.681e+00],\n       [ 3.533e+03,  3.867e+00, -9.682e+00],\n       [ 3.533e+03,  3.871e+00, -9.682e+00],\n       [ 3.533e+03,  3.875e+00, -9.682e+00],\n       [ 3.533e+03,  3.878e+00, -9.683e+00],\n       [ 3.533e+03,  3.882e+00, -9.683e+00],\n       [ 3.533e+03,  3.886e+00, -9.683e+00],\n       [ 3.533e+03,  3.890e+00, -9.684e+00]]), array([[ 3.534e+03,  3.501e+00, -9.680e+00],\n       [ 3.534e+03,  3.505e+00, -9.680e+00],\n       [ 3.534e+03,  3.508e+00, -9.680e+00],\n       [ 3.534e+03,  3.512e+00, -9.680e+00],\n       [ 3.534e+03,  3.516e+00, -9.680e+00],\n       [ 3.534e+03,  3.520e+00, -9.680e+00],\n       [ 3.534e+03,  3.524e+00, -9.679e+00],\n       [ 3.534e+03,  3.528e+00, -9.680e+00],\n       [ 3.534e+03,  3.532e+00, -9.680e+00],\n       [ 3.534e+03,  3.536e+00, -9.680e+00],\n       [ 3.534e+03,  3.540e+00, -9.680e+00],\n       [ 3.534e+03,  3.544e+00, -9.680e+00],\n       [ 3.534e+03,  3.548e+00, -9.680e+00],\n       [ 3.534e+03,  3.552e+00, -9.680e+00],\n       [ 3.534e+03,  3.556e+00, -9.680e+00],\n       [ 3.534e+03,  3.560e+00, -9.680e+00],\n       [ 3.534e+03,  3.564e+00, -9.680e+00],\n       [ 3.534e+03, 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3.534e+03,  3.654e+00, -9.680e+00],\n       [ 3.534e+03,  3.658e+00, -9.680e+00],\n       [ 3.534e+03,  3.662e+00, -9.680e+00],\n       [ 3.534e+03,  3.666e+00, -9.680e+00],\n       [ 3.534e+03,  3.670e+00, -9.680e+00],\n       [ 3.534e+03,  3.674e+00, -9.680e+00],\n       [ 3.534e+03,  3.678e+00, -9.680e+00],\n       [ 3.534e+03,  3.682e+00, -9.680e+00],\n       [ 3.534e+03,  3.686e+00, -9.680e+00],\n       [ 3.534e+03,  3.690e+00, -9.680e+00],\n       [ 3.534e+03,  3.693e+00, -9.680e+00],\n       [ 3.534e+03,  3.697e+00, -9.680e+00],\n       [ 3.534e+03,  3.701e+00, -9.680e+00],\n       [ 3.534e+03,  3.705e+00, -9.680e+00],\n       [ 3.534e+03,  3.709e+00, -9.680e+00],\n       [ 3.534e+03,  3.713e+00, -9.680e+00],\n       [ 3.534e+03,  3.717e+00, -9.680e+00],\n       [ 3.534e+03,  3.721e+00, -9.680e+00],\n       [ 3.534e+03,  3.725e+00, -9.680e+00],\n       [ 3.534e+03,  3.729e+00, -9.680e+00],\n       [ 3.534e+03,  3.733e+00, -9.680e+00],\n       [ 3.534e+03,  3.737e+00, 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3.962e+03,  3.812e+00, -1.452e+01],\n       [ 3.962e+03,  3.815e+00, -1.452e+01],\n       [ 3.962e+03,  3.819e+00, -1.452e+01],\n       [ 3.962e+03,  3.823e+00, -1.452e+01],\n       [ 3.962e+03,  3.826e+00, -1.452e+01],\n       [ 3.962e+03,  3.830e+00, -1.452e+01],\n       [ 3.962e+03,  3.834e+00, -1.452e+01],\n       [ 3.962e+03,  3.837e+00, -1.452e+01],\n       [ 3.962e+03,  3.841e+00, -1.452e+01],\n       [ 3.962e+03,  3.845e+00, -1.452e+01],\n       [ 3.962e+03,  3.848e+00, -1.452e+01],\n       [ 3.962e+03,  3.852e+00, -1.452e+01],\n       [ 3.962e+03,  3.856e+00, -1.453e+01],\n       [ 3.962e+03,  3.859e+00, -1.453e+01],\n       [ 3.962e+03,  3.863e+00, -1.453e+01]]), array([[ 3.963e+03,  3.501e+00, -1.452e+01],\n       [ 3.963e+03,  3.504e+00, -1.452e+01],\n       [ 3.963e+03,  3.508e+00, -1.452e+01],\n       [ 3.963e+03,  3.512e+00, -1.452e+01],\n       [ 3.963e+03,  3.515e+00, -1.452e+01],\n       [ 3.963e+03,  3.519e+00, -1.452e+01],\n       [ 3.963e+03,  3.523e+00, 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3.964e+03,  3.793e+00, -1.452e+01],\n       [ 3.964e+03,  3.797e+00, -1.452e+01],\n       [ 3.964e+03,  3.801e+00, -1.452e+01],\n       [ 3.964e+03,  3.804e+00, -1.452e+01],\n       [ 3.964e+03,  3.808e+00, -1.452e+01],\n       [ 3.964e+03,  3.812e+00, -1.452e+01],\n       [ 3.964e+03,  3.815e+00, -1.452e+01],\n       [ 3.964e+03,  3.819e+00, -1.452e+01],\n       [ 3.964e+03,  3.823e+00, -1.452e+01],\n       [ 3.964e+03,  3.826e+00, -1.453e+01],\n       [ 3.964e+03,  3.830e+00, -1.453e+01],\n       [ 3.964e+03,  3.834e+00, -1.453e+01],\n       [ 3.964e+03,  3.837e+00, -1.453e+01],\n       [ 3.964e+03,  3.841e+00, -1.453e+01],\n       [ 3.964e+03,  3.845e+00, -1.453e+01],\n       [ 3.964e+03,  3.848e+00, -1.453e+01],\n       [ 3.964e+03,  3.852e+00, -1.453e+01],\n       [ 3.964e+03,  3.856e+00, -1.453e+01],\n       [ 3.964e+03,  3.859e+00, -1.453e+01],\n       [ 3.964e+03,  3.863e+00, -1.453e+01]]), array([[ 3.965e+03,  3.501e+00, -1.452e+01],\n       [ 3.965e+03,  3.504e+00, 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3.966e+03,  3.775e+00, -1.452e+01],\n       [ 3.966e+03,  3.779e+00, -1.452e+01],\n       [ 3.966e+03,  3.783e+00, -1.452e+01],\n       [ 3.966e+03,  3.786e+00, -1.452e+01],\n       [ 3.966e+03,  3.790e+00, -1.452e+01],\n       [ 3.966e+03,  3.793e+00, -1.452e+01],\n       [ 3.966e+03,  3.797e+00, -1.452e+01],\n       [ 3.966e+03,  3.801e+00, -1.452e+01],\n       [ 3.966e+03,  3.804e+00, -1.452e+01],\n       [ 3.966e+03,  3.808e+00, -1.452e+01],\n       [ 3.966e+03,  3.812e+00, -1.452e+01],\n       [ 3.966e+03,  3.815e+00, -1.452e+01],\n       [ 3.966e+03,  3.819e+00, -1.452e+01],\n       [ 3.966e+03,  3.823e+00, -1.452e+01],\n       [ 3.966e+03,  3.826e+00, -1.452e+01],\n       [ 3.966e+03,  3.830e+00, -1.452e+01],\n       [ 3.966e+03,  3.834e+00, -1.452e+01],\n       [ 3.966e+03,  3.837e+00, -1.452e+01],\n       [ 3.966e+03,  3.841e+00, -1.452e+01],\n       [ 3.966e+03,  3.845e+00, -1.452e+01],\n       [ 3.966e+03,  3.848e+00, -1.452e+01],\n       [ 3.966e+03,  3.852e+00, 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3.971e+03,  3.848e+00, -1.452e+01],\n       [ 3.971e+03,  3.852e+00, -1.452e+01],\n       [ 3.971e+03,  3.856e+00, -1.453e+01],\n       [ 3.971e+03,  3.859e+00, -1.453e+01],\n       [ 3.971e+03,  3.863e+00, -1.453e+01]]), array([[ 3.972e+03,  3.501e+00, -1.452e+01],\n       [ 3.972e+03,  3.504e+00, -1.452e+01],\n       [ 3.972e+03,  3.508e+00, -1.452e+01],\n       [ 3.972e+03,  3.512e+00, -1.452e+01],\n       [ 3.972e+03,  3.515e+00, -1.452e+01],\n       [ 3.972e+03,  3.519e+00, -1.452e+01],\n       [ 3.972e+03,  3.523e+00, -1.452e+01],\n       [ 3.972e+03,  3.526e+00, -1.452e+01],\n       [ 3.972e+03,  3.530e+00, -1.452e+01],\n       [ 3.972e+03,  3.534e+00, -1.452e+01],\n       [ 3.972e+03,  3.537e+00, -1.452e+01],\n       [ 3.972e+03,  3.541e+00, -1.452e+01],\n       [ 3.972e+03,  3.545e+00, -1.452e+01],\n       [ 3.972e+03,  3.548e+00, -1.452e+01],\n       [ 3.972e+03,  3.552e+00, -1.452e+01],\n       [ 3.972e+03,  3.556e+00, -1.452e+01],\n       [ 3.972e+03,  3.559e+00, 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3.973e+03,  3.830e+00, -1.453e+01],\n       [ 3.973e+03,  3.834e+00, -1.453e+01],\n       [ 3.973e+03,  3.837e+00, -1.453e+01],\n       [ 3.973e+03,  3.841e+00, -1.453e+01],\n       [ 3.973e+03,  3.845e+00, -1.453e+01],\n       [ 3.973e+03,  3.848e+00, -1.453e+01],\n       [ 3.973e+03,  3.852e+00, -1.453e+01],\n       [ 3.973e+03,  3.856e+00, -1.453e+01],\n       [ 3.973e+03,  3.859e+00, -1.453e+01],\n       [ 3.973e+03,  3.863e+00, -1.453e+01]]), array([[ 3.974e+03,  3.501e+00, -1.452e+01],\n       [ 3.974e+03,  3.504e+00, -1.452e+01],\n       [ 3.974e+03,  3.508e+00, -1.452e+01],\n       [ 3.974e+03,  3.512e+00, -1.452e+01],\n       [ 3.974e+03,  3.515e+00, -1.452e+01],\n       [ 3.974e+03,  3.519e+00, -1.452e+01],\n       [ 3.974e+03,  3.523e+00, -1.452e+01],\n       [ 3.974e+03,  3.526e+00, -1.452e+01],\n       [ 3.974e+03,  3.530e+00, -1.452e+01],\n       [ 3.974e+03,  3.534e+00, -1.452e+01],\n       [ 3.974e+03,  3.537e+00, -1.452e+01],\n       [ 3.974e+03,  3.541e+00, 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3.859e+00, -1.453e+01],\n       [ 3.974e+03,  3.863e+00, -1.453e+01]]), array([[ 3.975e+03,  3.501e+00, -1.452e+01],\n       [ 3.975e+03,  3.504e+00, -1.452e+01],\n       [ 3.975e+03,  3.508e+00, -1.452e+01],\n       [ 3.975e+03,  3.511e+00, -1.452e+01],\n       [ 3.975e+03,  3.515e+00, -1.452e+01],\n       [ 3.975e+03,  3.518e+00, -1.452e+01],\n       [ 3.975e+03,  3.522e+00, -1.452e+01],\n       [ 3.975e+03,  3.525e+00, -1.452e+01],\n       [ 3.975e+03,  3.529e+00, -1.452e+01],\n       [ 3.975e+03,  3.532e+00, -1.452e+01],\n       [ 3.975e+03,  3.535e+00, -1.452e+01],\n       [ 3.975e+03,  3.539e+00, -1.452e+01],\n       [ 3.975e+03,  3.542e+00, -1.452e+01],\n       [ 3.975e+03,  3.546e+00, -1.452e+01],\n       [ 3.975e+03,  3.549e+00, -1.452e+01],\n       [ 3.975e+03,  3.553e+00, -1.452e+01],\n       [ 3.975e+03,  3.556e+00, -1.452e+01],\n       [ 3.975e+03,  3.560e+00, -1.452e+01],\n       [ 3.975e+03,  3.563e+00, -1.452e+01],\n       [ 3.975e+03,  3.567e+00, -1.452e+01],\n       [ 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3.975e+03,  3.797e+00, -1.452e+01],\n       [ 3.975e+03,  3.801e+00, -1.452e+01],\n       [ 3.975e+03,  3.804e+00, -1.452e+01],\n       [ 3.975e+03,  3.808e+00, -1.452e+01],\n       [ 3.975e+03,  3.811e+00, -1.452e+01],\n       [ 3.975e+03,  3.815e+00, -1.452e+01],\n       [ 3.975e+03,  3.818e+00, -1.452e+01],\n       [ 3.975e+03,  3.822e+00, -1.452e+01],\n       [ 3.975e+03,  3.825e+00, -1.452e+01],\n       [ 3.975e+03,  3.829e+00, -1.452e+01],\n       [ 3.975e+03,  3.832e+00, -1.452e+01],\n       [ 3.975e+03,  3.836e+00, -1.452e+01],\n       [ 3.975e+03,  3.839e+00, -1.452e+01],\n       [ 3.975e+03,  3.843e+00, -1.452e+01],\n       [ 3.975e+03,  3.846e+00, -1.452e+01]]), array([[ 3.976e+03,  3.501e+00, -1.452e+01],\n       [ 3.976e+03,  3.504e+00, -1.452e+01],\n       [ 3.976e+03,  3.508e+00, -1.452e+01],\n       [ 3.976e+03,  3.511e+00, -1.452e+01],\n       [ 3.976e+03,  3.515e+00, -1.452e+01],\n       [ 3.976e+03,  3.518e+00, -1.452e+01],\n       [ 3.976e+03,  3.522e+00, 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2.808e+03,  3.590e+00, -9.680e+00],\n       [ 2.808e+03,  3.602e+00, -9.680e+00],\n       [ 2.808e+03,  3.613e+00, -9.680e+00],\n       [ 2.808e+03,  3.625e+00, -9.680e+00],\n       [ 2.808e+03,  3.636e+00, -9.680e+00],\n       [ 2.808e+03,  3.648e+00, -9.680e+00],\n       [ 2.808e+03,  3.660e+00, -9.680e+00],\n       [ 2.808e+03,  3.671e+00, -9.680e+00],\n       [ 2.808e+03,  3.683e+00, -9.680e+00],\n       [ 2.808e+03,  3.694e+00, -9.680e+00],\n       [ 2.808e+03,  3.706e+00, -9.680e+00],\n       [ 2.808e+03,  3.717e+00, -9.680e+00],\n       [ 2.808e+03,  3.729e+00, -9.680e+00],\n       [ 2.808e+03,  3.740e+00, -9.680e+00],\n       [ 2.808e+03,  3.752e+00, -9.680e+00],\n       [ 2.808e+03,  3.763e+00, -9.681e+00],\n       [ 2.808e+03,  3.775e+00, -9.682e+00],\n       [ 2.808e+03,  3.787e+00, -9.683e+00],\n       [ 2.808e+03,  3.798e+00, -9.684e+00],\n       [ 2.808e+03,  3.810e+00, -9.685e+00],\n       [ 2.808e+03,  3.821e+00, -9.685e+00],\n       [ 2.808e+03,  3.833e+00, -9.686e+00],\n       [ 2.808e+03,  3.844e+00, -9.687e+00]]), array([[ 2.809e+03,  2.701e+00, -9.680e+00],\n       [ 2.809e+03,  2.712e+00, -9.681e+00],\n       [ 2.809e+03,  2.724e+00, -9.680e+00],\n       [ 2.809e+03,  2.735e+00, -9.679e+00],\n       [ 2.809e+03,  2.747e+00, -9.680e+00],\n       [ 2.809e+03,  2.759e+00, -9.680e+00],\n       [ 2.809e+03,  2.770e+00, -9.680e+00],\n       [ 2.809e+03,  2.782e+00, -9.679e+00],\n       [ 2.809e+03,  2.793e+00, -9.680e+00],\n       [ 2.809e+03,  2.805e+00, -9.680e+00],\n       [ 2.809e+03,  2.816e+00, -9.679e+00],\n       [ 2.809e+03,  2.828e+00, -9.680e+00],\n       [ 2.809e+03,  2.839e+00, -9.680e+00],\n       [ 2.809e+03,  2.851e+00, -9.680e+00],\n       [ 2.809e+03,  2.863e+00, -9.680e+00],\n       [ 2.809e+03,  2.874e+00, -9.680e+00],\n       [ 2.809e+03,  2.886e+00, -9.680e+00],\n       [ 2.809e+03,  2.897e+00, -9.680e+00],\n       [ 2.809e+03,  2.909e+00, -9.680e+00],\n       [ 2.809e+03,  2.920e+00, -9.680e+00],\n       [ 2.809e+03, 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2.810e+03,  3.532e+00, -9.679e+00],\n       [ 2.810e+03,  3.544e+00, -9.681e+00],\n       [ 2.810e+03,  3.556e+00, -9.680e+00],\n       [ 2.810e+03,  3.567e+00, -9.680e+00],\n       [ 2.810e+03,  3.579e+00, -9.680e+00],\n       [ 2.810e+03,  3.590e+00, -9.680e+00],\n       [ 2.810e+03,  3.602e+00, -9.680e+00],\n       [ 2.810e+03,  3.613e+00, -9.680e+00],\n       [ 2.810e+03,  3.625e+00, -9.680e+00],\n       [ 2.810e+03,  3.636e+00, -9.680e+00],\n       [ 2.810e+03,  3.648e+00, -9.680e+00],\n       [ 2.810e+03,  3.660e+00, -9.680e+00],\n       [ 2.810e+03,  3.671e+00, -9.680e+00],\n       [ 2.810e+03,  3.683e+00, -9.680e+00],\n       [ 2.810e+03,  3.694e+00, -9.680e+00],\n       [ 2.810e+03,  3.706e+00, -9.680e+00],\n       [ 2.810e+03,  3.717e+00, -9.680e+00],\n       [ 2.810e+03,  3.729e+00, -9.680e+00],\n       [ 2.810e+03,  3.740e+00, -9.680e+00],\n       [ 2.810e+03,  3.752e+00, -9.681e+00],\n       [ 2.810e+03,  3.763e+00, -9.681e+00],\n       [ 2.810e+03,  3.775e+00, -9.682e+00],\n       [ 2.810e+03,  3.787e+00, -9.683e+00],\n       [ 2.810e+03,  3.798e+00, -9.684e+00],\n       [ 2.810e+03,  3.810e+00, -9.684e+00],\n       [ 2.810e+03,  3.821e+00, -9.685e+00],\n       [ 2.810e+03,  3.833e+00, -9.686e+00],\n       [ 2.810e+03,  3.844e+00, -9.687e+00]]), array([[ 2.811e+03,  2.701e+00, -9.680e+00],\n       [ 2.811e+03,  2.712e+00, -9.681e+00],\n       [ 2.811e+03,  2.724e+00, -9.680e+00],\n       [ 2.811e+03,  2.735e+00, -9.680e+00],\n       [ 2.811e+03,  2.747e+00, -9.679e+00],\n       [ 2.811e+03,  2.759e+00, -9.680e+00],\n       [ 2.811e+03,  2.770e+00, -9.680e+00],\n       [ 2.811e+03,  2.782e+00, -9.680e+00],\n       [ 2.811e+03,  2.793e+00, -9.680e+00],\n       [ 2.811e+03,  2.805e+00, -9.680e+00],\n       [ 2.811e+03,  2.816e+00, -9.680e+00],\n       [ 2.811e+03,  2.828e+00, -9.681e+00],\n       [ 2.811e+03,  2.839e+00, -9.680e+00],\n       [ 2.811e+03,  2.851e+00, -9.679e+00],\n       [ 2.811e+03,  2.863e+00, -9.680e+00],\n       [ 2.811e+03, 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2.811e+03,  3.128e+00, -9.680e+00],\n       [ 2.811e+03,  3.140e+00, -9.680e+00],\n       [ 2.811e+03,  3.151e+00, -9.681e+00],\n       [ 2.811e+03,  3.163e+00, -9.680e+00],\n       [ 2.811e+03,  3.174e+00, -9.680e+00],\n       [ 2.811e+03,  3.186e+00, -9.680e+00],\n       [ 2.811e+03,  3.197e+00, -9.680e+00],\n       [ 2.811e+03,  3.209e+00, -9.680e+00],\n       [ 2.811e+03,  3.221e+00, -9.681e+00],\n       [ 2.811e+03,  3.232e+00, -9.680e+00],\n       [ 2.811e+03,  3.244e+00, -9.680e+00],\n       [ 2.811e+03,  3.255e+00, -9.680e+00],\n       [ 2.811e+03,  3.267e+00, -9.680e+00],\n       [ 2.811e+03,  3.278e+00, -9.680e+00],\n       [ 2.811e+03,  3.290e+00, -9.680e+00],\n       [ 2.811e+03,  3.301e+00, -9.680e+00],\n       [ 2.811e+03,  3.313e+00, -9.681e+00],\n       [ 2.811e+03,  3.325e+00, -9.681e+00],\n       [ 2.811e+03,  3.336e+00, -9.680e+00],\n       [ 2.811e+03,  3.348e+00, -9.680e+00],\n       [ 2.811e+03,  3.359e+00, -9.681e+00],\n       [ 2.811e+03,  3.371e+00, 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3.625e+00, -9.680e+00],\n       [ 2.811e+03,  3.636e+00, -9.680e+00],\n       [ 2.811e+03,  3.648e+00, -9.680e+00],\n       [ 2.811e+03,  3.660e+00, -9.680e+00],\n       [ 2.811e+03,  3.671e+00, -9.680e+00],\n       [ 2.811e+03,  3.683e+00, -9.680e+00],\n       [ 2.811e+03,  3.694e+00, -9.680e+00],\n       [ 2.811e+03,  3.706e+00, -9.680e+00],\n       [ 2.811e+03,  3.717e+00, -9.680e+00],\n       [ 2.811e+03,  3.729e+00, -9.680e+00],\n       [ 2.811e+03,  3.740e+00, -9.680e+00],\n       [ 2.811e+03,  3.752e+00, -9.681e+00],\n       [ 2.811e+03,  3.763e+00, -9.682e+00],\n       [ 2.811e+03,  3.775e+00, -9.682e+00],\n       [ 2.811e+03,  3.787e+00, -9.683e+00],\n       [ 2.811e+03,  3.798e+00, -9.684e+00],\n       [ 2.811e+03,  3.810e+00, -9.685e+00],\n       [ 2.811e+03,  3.821e+00, -9.685e+00],\n       [ 2.811e+03,  3.833e+00, -9.686e+00],\n       [ 2.811e+03,  3.844e+00, -9.687e+00]]), array([[ 2.812e+03,  2.701e+00, -9.680e+00],\n       [ 2.812e+03,  2.712e+00, -9.680e+00],\n       [ 2.812e+03,  2.724e+00, -9.680e+00],\n       [ 2.812e+03,  2.735e+00, -9.680e+00],\n       [ 2.812e+03,  2.747e+00, -9.680e+00],\n       [ 2.812e+03,  2.759e+00, -9.680e+00],\n       [ 2.812e+03,  2.770e+00, -9.680e+00],\n       [ 2.812e+03,  2.782e+00, -9.680e+00],\n       [ 2.812e+03,  2.793e+00, -9.680e+00],\n       [ 2.812e+03,  2.805e+00, -9.680e+00],\n       [ 2.812e+03,  2.816e+00, -9.679e+00],\n       [ 2.812e+03,  2.828e+00, -9.679e+00],\n       [ 2.812e+03,  2.839e+00, -9.680e+00],\n       [ 2.812e+03,  2.851e+00, -9.679e+00],\n       [ 2.812e+03,  2.863e+00, -9.681e+00],\n       [ 2.812e+03,  2.874e+00, -9.680e+00],\n       [ 2.812e+03,  2.886e+00, -9.680e+00],\n       [ 2.812e+03,  2.897e+00, -9.680e+00],\n       [ 2.812e+03,  2.909e+00, -9.680e+00],\n       [ 2.812e+03,  2.920e+00, -9.680e+00],\n       [ 2.812e+03,  2.932e+00, -9.680e+00],\n       [ 2.812e+03,  2.943e+00, -9.680e+00],\n       [ 2.812e+03,  2.955e+00, -9.680e+00],\n       [ 2.812e+03,  2.966e+00, -9.680e+00],\n       [ 2.812e+03,  2.978e+00, -9.680e+00],\n       [ 2.812e+03,  2.990e+00, -9.680e+00],\n       [ 2.812e+03,  3.001e+00, -9.680e+00],\n       [ 2.812e+03,  3.013e+00, -9.679e+00],\n       [ 2.812e+03,  3.024e+00, -9.680e+00],\n       [ 2.812e+03,  3.036e+00, -9.680e+00],\n       [ 2.812e+03,  3.047e+00, -9.680e+00],\n       [ 2.812e+03,  3.059e+00, -9.680e+00],\n       [ 2.812e+03,  3.070e+00, -9.680e+00],\n       [ 2.812e+03,  3.082e+00, -9.679e+00],\n       [ 2.812e+03,  3.094e+00, -9.680e+00],\n       [ 2.812e+03,  3.105e+00, -9.680e+00],\n       [ 2.812e+03,  3.117e+00, -9.680e+00],\n       [ 2.812e+03,  3.128e+00, -9.680e+00],\n       [ 2.812e+03,  3.140e+00, -9.680e+00],\n       [ 2.812e+03,  3.151e+00, -9.680e+00],\n       [ 2.812e+03,  3.163e+00, -9.680e+00],\n       [ 2.812e+03,  3.174e+00, -9.679e+00],\n       [ 2.812e+03,  3.186e+00, -9.680e+00],\n       [ 2.812e+03,  3.197e+00, -9.681e+00],\n       [ 2.812e+03,  3.209e+00, -9.680e+00],\n       [ 2.812e+03,  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[443.   ,   3.447,  -0.968],\n       [443.   ,   3.459,  -0.968],\n       [443.   ,   3.47 ,  -0.968],\n       [443.   ,   3.482,  -0.968],\n       [443.   ,   3.493,  -0.968],\n       [443.   ,   3.505,  -0.968],\n       [443.   ,   3.516,  -0.968],\n       [443.   ,   3.528,  -0.968],\n       [443.   ,   3.539,  -0.968],\n       [443.   ,   3.55 ,  -0.968],\n       [443.   ,   3.562,  -0.968],\n       [443.   ,   3.573,  -0.968],\n       [443.   ,   3.585,  -0.968],\n       [443.   ,   3.596,  -0.968],\n       [443.   ,   3.608,  -0.968],\n       [443.   ,   3.619,  -0.968],\n       [443.   ,   3.631,  -0.968],\n       [443.   ,   3.642,  -0.968],\n       [443.   ,   3.654,  -0.968],\n       [443.   ,   3.665,  -0.968],\n       [443.   ,   3.677,  -0.968],\n       [443.   ,   3.688,  -0.968],\n       [443.   ,   3.7  ,  -0.968],\n       [443.   ,   3.711,  -0.968],\n       [443.   ,   3.723,  -0.968],\n       [443.   ,   3.734,  -0.968],\n       [443.   ,   3.746,  -0.968],\n       [443.   ,   3.757,  -0.968],\n       [443.   ,   3.769,  -0.968],\n       [443.   ,   3.78 ,  -0.968],\n       [443.   ,   3.792,  -0.968],\n       [443.   ,   3.803,  -0.968],\n       [443.   ,   3.815,  -0.968],\n       [443.   ,   3.826,  -0.968],\n       [443.   ,   3.838,  -0.974]]), array([[444.   ,   2.701,  -0.968],\n       [444.   ,   2.712,  -0.968],\n       [444.   ,   2.724,  -0.968],\n       [444.   ,   2.735,  -0.968],\n       [444.   ,   2.747,  -0.968],\n       [444.   ,   2.758,  -0.968],\n       [444.   ,   2.77 ,  -0.968],\n       [444.   ,   2.781,  -0.968],\n       [444.   ,   2.793,  -0.968],\n       [444.   ,   2.804,  -0.968],\n       [444.   ,   2.816,  -0.968],\n       [444.   ,   2.827,  -0.968],\n       [444.   ,   2.839,  -0.968],\n       [444.   ,   2.85 ,  -0.968],\n       [444.   ,   2.862,  -0.968],\n       [444.   ,   2.873,  -0.968],\n       [444.   ,   2.885,  -0.968],\n       [444.   ,   2.896,  -0.968],\n       [444.   ,   2.907,  -0.968],\n       [444.   ,   2.919,  -0.968],\n       [444.   ,   2.93 ,  -0.968],\n       [444.   ,   2.942,  -0.968],\n       [444.   ,   2.953,  -0.968],\n       [444.   ,   2.965,  -0.968],\n       [444.   ,   2.976,  -0.968],\n       [444.   ,   2.988,  -0.967],\n       [444.   ,   2.999,  -0.968],\n       [444.   ,   3.011,  -0.968],\n       [444.   ,   3.022,  -0.968],\n       [444.   ,   3.034,  -0.968],\n       [444.   ,   3.045,  -0.968],\n       [444.   ,   3.057,  -0.967],\n       [444.   ,   3.068,  -0.968],\n       [444.   ,   3.08 ,  -0.968],\n       [444.   ,   3.091,  -0.968],\n       [444.   ,   3.103,  -0.968],\n       [444.   ,   3.114,  -0.968],\n       [444.   ,   3.126,  -0.968],\n       [444.   ,   3.137,  -0.968],\n       [444.   ,   3.149,  -0.968],\n       [444.   ,   3.16 ,  -0.968],\n       [444.   ,   3.172,  -0.968],\n       [444.   ,   3.183,  -0.968],\n       [444.   ,   3.195,  -0.968],\n       [444.   ,   3.206,  -0.968],\n       [444.   ,   3.217,  -0.968],\n       [444.   ,   3.229,  -0.968],\n       [444.   ,   3.24 ,  -0.968],\n       [444.   ,   3.252,  -0.968],\n       [444.   ,   3.263,  -0.968],\n       [444.   ,   3.275,  -0.968],\n       [444.   ,   3.286,  -0.968],\n       [444.   ,   3.298,  -0.968],\n       [444.   ,   3.309,  -0.968],\n       [444.   ,   3.321,  -0.968],\n       [444.   ,   3.332,  -0.968],\n       [444.   ,   3.344,  -0.968],\n       [444.   ,   3.355,  -0.968],\n       [444.   ,   3.367,  -0.968],\n       [444.   ,   3.378,  -0.968],\n       [444.   ,   3.39 ,  -0.968],\n       [444.   ,   3.401,  -0.967],\n       [444.   ,   3.413,  -0.968],\n       [444.   ,   3.424,  -0.968],\n       [444.   ,   3.436,  -0.968],\n       [444.   ,   3.447,  -0.968],\n       [444.   ,   3.459,  -0.968],\n       [444.   ,   3.47 ,  -0.968],\n       [444.   ,   3.482,  -0.968],\n       [444.   ,   3.493,  -0.968],\n       [444.   ,   3.505,  -0.968],\n       [444.   ,   3.516,  -0.968],\n       [444.   ,   3.528,  -0.968],\n       [444.   ,   3.539,  -0.968],\n       [444.   ,   3.55 ,  -0.968],\n       [444.   ,   3.562,  -0.968],\n       [444.   ,   3.573,  -0.968],\n       [444.   ,   3.585,  -0.968],\n       [444.   ,   3.596,  -0.968],\n       [444.   ,   3.608,  -0.968],\n       [444.   ,   3.619,  -0.968],\n       [444.   ,   3.631,  -0.968],\n       [444.   ,   3.642,  -0.968],\n       [444.   ,   3.654,  -0.968],\n       [444.   ,   3.665,  -0.968],\n       [444.   ,   3.677,  -0.968],\n       [444.   ,   3.688,  -0.968],\n       [444.   ,   3.7  ,  -0.968],\n       [444.   ,   3.711,  -0.968],\n       [444.   ,   3.723,  -0.968],\n       [444.   ,   3.734,  -0.968],\n       [444.   ,   3.746,  -0.968],\n       [444.   ,   3.757,  -0.968],\n       [444.   ,   3.769,  -0.968],\n       [444.   ,   3.78 ,  -0.968],\n       [444.   ,   3.792,  -0.968],\n       [444.   ,   3.803,  -0.968],\n       [444.   ,   3.815,  -0.967],\n       [444.   ,   3.826,  -0.968],\n       [444.   ,   3.838,  -0.971]]), array([[445.   ,   2.701,  -0.967],\n       [445.   ,   2.712,  -0.968],\n       [445.   ,   2.724,  -0.968],\n       [445.   ,   2.735,  -0.968],\n       [445.   ,   2.747,  -0.968],\n       [445.   ,   2.758,  -0.968],\n       [445.   ,   2.77 ,  -0.968],\n       [445.   ,   2.781,  -0.968],\n       [445.   ,   2.793,  -0.968],\n       [445.   ,   2.804,  -0.968],\n       [445.   ,   2.816,  -0.968],\n       [445.   ,   2.827,  -0.968],\n       [445.   ,   2.839,  -0.968],\n       [445.   ,   2.85 ,  -0.968],\n       [445.   ,   2.862,  -0.968],\n       [445.   ,   2.873,  -0.967],\n       [445.   ,   2.885,  -0.968],\n       [445.   ,   2.896,  -0.968],\n       [445.   ,   2.907,  -0.968],\n       [445.   ,   2.919,  -0.968],\n       [445.   ,   2.93 ,  -0.968],\n       [445.   ,   2.942,  -0.968],\n       [445.   ,   2.953,  -0.968],\n       [445.   ,   2.965,  -0.968],\n       [445.   ,   2.976,  -0.968],\n       [445.   ,   2.988,  -0.968],\n       [445.   ,   2.999,  -0.968],\n       [445.   ,   3.011,  -0.968],\n       [445.   ,   3.022,  -0.967],\n       [445.   ,   3.034,  -0.968],\n       [445.   ,   3.045,  -0.968],\n       [445.   ,   3.057,  -0.968],\n       [445.   ,   3.068,  -0.968],\n       [445.   ,   3.08 ,  -0.968],\n       [445.   ,   3.091,  -0.968],\n       [445.   ,   3.103,  -0.968],\n       [445.   ,   3.114,  -0.968],\n       [445.   ,   3.126,  -0.968],\n       [445.   ,   3.137,  -0.968],\n       [445.   ,   3.149,  -0.967],\n       [445.   ,   3.16 ,  -0.968],\n       [445.   ,   3.172,  -0.968],\n       [445.   ,   3.183,  -0.968],\n       [445.   ,   3.195,  -0.968],\n       [445.   ,   3.206,  -0.968],\n       [445.   ,   3.217,  -0.968],\n       [445.   ,   3.229,  -0.968],\n       [445.   ,   3.24 ,  -0.968],\n       [445.   ,   3.252,  -0.968],\n       [445.   ,   3.263,  -0.968],\n       [445.   ,   3.275,  -0.968],\n       [445.   ,   3.286,  -0.967],\n       [445.   ,   3.298,  -0.968],\n       [445.   ,   3.309,  -0.968],\n       [445.   ,   3.321,  -0.968],\n       [445.   ,   3.332,  -0.968],\n       [445.   ,   3.344,  -0.968],\n       [445.   ,   3.355,  -0.968],\n       [445.   ,   3.367,  -0.967],\n       [445.   ,   3.378,  -0.968],\n       [445.   ,   3.39 ,  -0.968],\n       [445.   ,   3.401,  -0.968],\n       [445.   ,   3.413,  -0.968],\n       [445.   ,   3.424,  -0.967],\n       [445.   ,   3.436,  -0.967],\n       [445.   ,   3.447,  -0.968],\n       [445.   ,   3.459,  -0.968],\n       [445.   ,   3.47 ,  -0.968],\n       [445.   ,   3.482,  -0.968],\n       [445.   ,   3.493,  -0.968],\n       [445.   ,   3.505,  -0.968],\n       [445.   ,   3.516,  -0.968],\n       [445.   ,   3.528,  -0.967],\n       [445.   ,   3.539,  -0.968],\n       [445.   ,   3.55 ,  -0.968],\n       [445.   ,   3.562,  -0.968],\n       [445.   ,   3.573,  -0.968],\n       [445.   ,   3.585,  -0.968],\n       [445.   ,   3.596,  -0.967],\n       [445.   ,   3.608,  -0.968],\n       [445.   ,   3.619,  -0.968],\n       [445.   ,   3.631,  -0.968],\n       [445.   ,   3.642,  -0.968],\n       [445.   ,   3.654,  -0.967],\n       [445.   ,   3.665,  -0.968],\n       [445.   ,   3.677,  -0.968],\n       [445.   ,   3.688,  -0.968],\n       [445.   ,   3.7  ,  -0.968],\n       [445.   ,   3.711,  -0.968],\n       [445.   ,   3.723,  -0.968],\n       [445.   ,   3.734,  -0.968],\n       [445.   ,   3.746,  -0.968],\n       [445.   ,   3.757,  -0.968],\n       [445.   ,   3.769,  -0.968],\n       [445.   ,   3.78 ,  -0.968],\n       [445.   ,   3.792,  -0.968],\n       [445.   ,   3.803,  -0.968],\n       [445.   ,   3.815,  -0.968],\n       [445.   ,   3.826,  -0.968],\n       [445.   ,   3.838,  -0.971]]), array([[446.   ,   2.701,  -0.968],\n       [446.   ,   2.712,  -0.968],\n       [446.   ,   2.724,  -0.968],\n       [446.   ,   2.735,  -0.968],\n       [446.   ,   2.747,  -0.968],\n       [446.   ,   2.758,  -0.968],\n       [446.   ,   2.77 ,  -0.968],\n       [446.   ,   2.781,  -0.968],\n       [446.   ,   2.793,  -0.968],\n       [446.   ,   2.804,  -0.967],\n       [446.   ,   2.816,  -0.968],\n       [446.   ,   2.827,  -0.968],\n       [446.   ,   2.839,  -0.968],\n       [446.   ,   2.85 ,  -0.968],\n       [446.   ,   2.862,  -0.968],\n       [446.   ,   2.873,  -0.968],\n       [446.   ,   2.885,  -0.968],\n       [446.   ,   2.896,  -0.968],\n       [446.   ,   2.907,  -0.968],\n       [446.   ,   2.919,  -0.968],\n       [446.   ,   2.93 ,  -0.967],\n       [446.   ,   2.942,  -0.968],\n       [446.   ,   2.953,  -0.968],\n       [446.   ,   2.965,  -0.968],\n       [446.   ,   2.976,  -0.968],\n       [446.   ,   2.988,  -0.968],\n       [446.   ,   2.999,  -0.968],\n       [446.   ,   3.011,  -0.968],\n       [446.   ,   3.022,  -0.968],\n       [446.   ,   3.034,  -0.968],\n       [446.   ,   3.045,  -0.968],\n       [446.   ,   3.057,  -0.968],\n       [446.   ,   3.068,  -0.968],\n       [446.   ,   3.08 ,  -0.967],\n       [446.   ,   3.091,  -0.968],\n       [446.   ,   3.103,  -0.968],\n       [446.   ,   3.114,  -0.968],\n       [446.   ,   3.126,  -0.968],\n       [446.   ,   3.137,  -0.968],\n       [446.   ,   3.149,  -0.968],\n       [446.   ,   3.16 ,  -0.968],\n       [446.   ,   3.172,  -0.968],\n       [446.   ,   3.183,  -0.968],\n       [446.   ,   3.195,  -0.967],\n       [446.   ,   3.206,  -0.968],\n       [446.   ,   3.217,  -0.968],\n       [446.   ,   3.229,  -0.968],\n       [446.   ,   3.24 ,  -0.968],\n       [446.   ,   3.252,  -0.968],\n       [446.   ,   3.263,  -0.968],\n       [446.   ,   3.275,  -0.968],\n       [446.   ,   3.286,  -0.968],\n       [446.   ,   3.298,  -0.968],\n       [446.   ,   3.309,  -0.968],\n       [446.   ,   3.321,  -0.968],\n       [446.   ,   3.332,  -0.968],\n       [446.   ,   3.344,  -0.968],\n       [446.   ,   3.355,  -0.968],\n       [446.   ,   3.367,  -0.968],\n       [446.   ,   3.378,  -0.968],\n       [446.   ,   3.39 ,  -0.968],\n       [446.   ,   3.401,  -0.968],\n       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array([[841.   ,   2.701,  -0.967],\n       [841.   ,   2.714,  -0.967],\n       [841.   ,   2.726,  -0.968],\n       [841.   ,   2.739,  -0.968],\n       [841.   ,   2.752,  -0.969],\n       [841.   ,   2.764,  -0.968],\n       [841.   ,   2.777,  -0.968],\n       [841.   ,   2.79 ,  -0.968],\n       [841.   ,   2.803,  -0.968],\n       [841.   ,   2.815,  -0.968],\n       [841.   ,   2.828,  -0.968],\n       [841.   ,   2.841,  -0.968],\n       [841.   ,   2.853,  -0.968],\n       [841.   ,   2.866,  -0.968],\n       [841.   ,   2.879,  -0.968],\n       [841.   ,   2.892,  -0.968],\n       [841.   ,   2.904,  -0.968],\n       [841.   ,   2.917,  -0.968],\n       [841.   ,   2.93 ,  -0.969],\n       [841.   ,   2.942,  -0.968],\n       [841.   ,   2.955,  -0.968],\n       [841.   ,   2.968,  -0.968],\n       [841.   ,   2.981,  -0.968],\n       [841.   ,   2.993,  -0.968],\n       [841.   ,   3.006,  -0.968],\n       [841.   ,   3.019,  -0.968],\n       [841.   ,   3.032,  -0.968],\n  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3.787e+03,  3.299e+00, -9.680e+00],\n       [ 3.787e+03,  3.307e+00, -9.680e+00],\n       [ 3.787e+03,  3.315e+00, -9.680e+00],\n       [ 3.787e+03,  3.322e+00, -9.680e+00],\n       [ 3.787e+03,  3.330e+00, -9.680e+00],\n       [ 3.787e+03,  3.338e+00, -9.680e+00],\n       [ 3.787e+03,  3.346e+00, -9.680e+00],\n       [ 3.787e+03,  3.353e+00, -9.680e+00],\n       [ 3.787e+03,  3.361e+00, -9.680e+00],\n       [ 3.787e+03,  3.369e+00, -9.680e+00],\n       [ 3.787e+03,  3.377e+00, -9.680e+00],\n       [ 3.787e+03,  3.385e+00, -9.680e+00],\n       [ 3.787e+03,  3.392e+00, -9.680e+00],\n       [ 3.787e+03,  3.400e+00, -9.680e+00],\n       [ 3.787e+03,  3.408e+00, -9.680e+00],\n       [ 3.787e+03,  3.416e+00, -9.680e+00],\n       [ 3.787e+03,  3.423e+00, -9.681e+00],\n       [ 3.787e+03,  3.431e+00, -9.680e+00],\n       [ 3.787e+03,  3.439e+00, -9.680e+00],\n       [ 3.787e+03,  3.447e+00, -9.681e+00],\n       [ 3.787e+03,  3.454e+00, -9.683e+00],\n       [ 3.787e+03,  3.462e+00, -9.684e+00],\n       [ 3.787e+03,  3.470e+00, -9.686e+00]]), array([[ 3.788e+03,  2.701e+00, -9.681e+00],\n       [ 3.788e+03,  2.709e+00, -9.680e+00],\n       [ 3.788e+03,  2.716e+00, -9.680e+00],\n       [ 3.788e+03,  2.724e+00, -9.680e+00],\n       [ 3.788e+03,  2.732e+00, -9.679e+00],\n       [ 3.788e+03,  2.740e+00, -9.680e+00],\n       [ 3.788e+03,  2.747e+00, -9.680e+00],\n       [ 3.788e+03,  2.755e+00, -9.680e+00],\n       [ 3.788e+03,  2.763e+00, -9.680e+00],\n       [ 3.788e+03,  2.771e+00, -9.680e+00],\n       [ 3.788e+03,  2.778e+00, -9.680e+00],\n       [ 3.788e+03,  2.786e+00, -9.680e+00],\n       [ 3.788e+03,  2.794e+00, -9.680e+00],\n       [ 3.788e+03,  2.802e+00, -9.681e+00],\n       [ 3.788e+03,  2.810e+00, -9.680e+00],\n       [ 3.788e+03,  2.817e+00, -9.680e+00],\n       [ 3.788e+03,  2.825e+00, -9.680e+00],\n       [ 3.788e+03,  2.833e+00, -9.680e+00],\n       [ 3.788e+03,  2.841e+00, -9.680e+00],\n       [ 3.788e+03,  2.848e+00, -9.680e+00],\n       [ 3.788e+03, 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-9.680e+00],\n       [ 3.788e+03,  3.198e+00, -9.680e+00],\n       [ 3.788e+03,  3.206e+00, -9.680e+00],\n       [ 3.788e+03,  3.214e+00, -9.680e+00],\n       [ 3.788e+03,  3.221e+00, -9.679e+00],\n       [ 3.788e+03,  3.229e+00, -9.679e+00],\n       [ 3.788e+03,  3.237e+00, -9.680e+00],\n       [ 3.788e+03,  3.245e+00, -9.679e+00],\n       [ 3.788e+03,  3.252e+00, -9.680e+00],\n       [ 3.788e+03,  3.260e+00, -9.680e+00],\n       [ 3.788e+03,  3.268e+00, -9.680e+00],\n       [ 3.788e+03,  3.276e+00, -9.680e+00],\n       [ 3.788e+03,  3.284e+00, -9.680e+00],\n       [ 3.788e+03,  3.291e+00, -9.680e+00],\n       [ 3.788e+03,  3.299e+00, -9.680e+00],\n       [ 3.788e+03,  3.307e+00, -9.680e+00],\n       [ 3.788e+03,  3.315e+00, -9.680e+00],\n       [ 3.788e+03,  3.322e+00, -9.680e+00],\n       [ 3.788e+03,  3.330e+00, -9.680e+00],\n       [ 3.788e+03,  3.338e+00, -9.680e+00],\n       [ 3.788e+03,  3.346e+00, -9.681e+00],\n       [ 3.788e+03,  3.353e+00, -9.680e+00],\n       [ 3.788e+03,  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3.789e+03,  2.755e+00, -9.680e+00],\n       [ 3.789e+03,  2.763e+00, -9.680e+00],\n       [ 3.789e+03,  2.770e+00, -9.680e+00],\n       [ 3.789e+03,  2.778e+00, -9.680e+00],\n       [ 3.789e+03,  2.786e+00, -9.680e+00],\n       [ 3.789e+03,  2.793e+00, -9.679e+00],\n       [ 3.789e+03,  2.801e+00, -9.680e+00],\n       [ 3.789e+03,  2.809e+00, -9.680e+00],\n       [ 3.789e+03,  2.817e+00, -9.680e+00],\n       [ 3.789e+03,  2.824e+00, -9.680e+00],\n       [ 3.789e+03,  2.832e+00, -9.680e+00],\n       [ 3.789e+03,  2.840e+00, -9.680e+00],\n       [ 3.789e+03,  2.847e+00, -9.680e+00],\n       [ 3.789e+03,  2.855e+00, -9.680e+00],\n       [ 3.789e+03,  2.863e+00, -9.680e+00],\n       [ 3.789e+03,  2.871e+00, -9.680e+00],\n       [ 3.789e+03,  2.878e+00, -9.680e+00],\n       [ 3.789e+03,  2.886e+00, -9.680e+00],\n       [ 3.789e+03,  2.894e+00, -9.680e+00],\n       [ 3.789e+03,  2.901e+00, -9.680e+00],\n       [ 3.789e+03,  2.909e+00, -9.680e+00],\n       [ 3.789e+03,  2.917e+00, 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3.789e+03,  3.256e+00, -9.680e+00],\n       [ 3.789e+03,  3.264e+00, -9.680e+00],\n       [ 3.789e+03,  3.272e+00, -9.680e+00],\n       [ 3.789e+03,  3.280e+00, -9.680e+00],\n       [ 3.789e+03,  3.287e+00, -9.680e+00],\n       [ 3.789e+03,  3.295e+00, -9.680e+00],\n       [ 3.789e+03,  3.303e+00, -9.680e+00],\n       [ 3.789e+03,  3.311e+00, -9.680e+00],\n       [ 3.789e+03,  3.318e+00, -9.680e+00],\n       [ 3.789e+03,  3.326e+00, -9.680e+00],\n       [ 3.789e+03,  3.334e+00, -9.680e+00],\n       [ 3.789e+03,  3.341e+00, -9.679e+00],\n       [ 3.789e+03,  3.349e+00, -9.679e+00],\n       [ 3.789e+03,  3.357e+00, -9.681e+00],\n       [ 3.789e+03,  3.365e+00, -9.680e+00],\n       [ 3.789e+03,  3.372e+00, -9.680e+00],\n       [ 3.789e+03,  3.380e+00, -9.680e+00],\n       [ 3.789e+03,  3.388e+00, -9.679e+00],\n       [ 3.789e+03,  3.395e+00, -9.680e+00],\n       [ 3.789e+03,  3.403e+00, -9.680e+00],\n       [ 3.789e+03,  3.411e+00, -9.680e+00],\n       [ 3.789e+03,  3.419e+00, -9.680e+00],\n       [ 3.789e+03,  3.426e+00, -9.680e+00],\n       [ 3.789e+03,  3.434e+00, -9.680e+00],\n       [ 3.789e+03,  3.442e+00, -9.680e+00],\n       [ 3.789e+03,  3.449e+00, -9.680e+00],\n       [ 3.789e+03,  3.457e+00, -9.679e+00],\n       [ 3.789e+03,  3.465e+00, -9.679e+00]]), array([[ 3.790e+03,  2.701e+00, -9.680e+00],\n       [ 3.790e+03,  2.709e+00, -9.680e+00],\n       [ 3.790e+03,  2.716e+00, -9.680e+00],\n       [ 3.790e+03,  2.724e+00, -9.680e+00],\n       [ 3.790e+03,  2.732e+00, -9.680e+00],\n       [ 3.790e+03,  2.739e+00, -9.680e+00],\n       [ 3.790e+03,  2.747e+00, -9.680e+00],\n       [ 3.790e+03,  2.755e+00, -9.680e+00],\n       [ 3.790e+03,  2.763e+00, -9.680e+00],\n       [ 3.790e+03,  2.770e+00, -9.680e+00],\n       [ 3.790e+03,  2.778e+00, -9.680e+00],\n       [ 3.790e+03,  2.786e+00, -9.680e+00],\n       [ 3.790e+03,  2.793e+00, -9.680e+00],\n       [ 3.790e+03,  2.801e+00, -9.680e+00],\n       [ 3.790e+03,  2.809e+00, -9.680e+00],\n       [ 3.790e+03, 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3.790e+03,  2.986e+00, -9.680e+00],\n       [ 3.790e+03,  2.994e+00, -9.680e+00],\n       [ 3.790e+03,  3.002e+00, -9.679e+00],\n       [ 3.790e+03,  3.010e+00, -9.680e+00],\n       [ 3.790e+03,  3.017e+00, -9.680e+00],\n       [ 3.790e+03,  3.025e+00, -9.680e+00],\n       [ 3.790e+03,  3.033e+00, -9.680e+00],\n       [ 3.790e+03,  3.040e+00, -9.680e+00],\n       [ 3.790e+03,  3.048e+00, -9.680e+00],\n       [ 3.790e+03,  3.056e+00, -9.680e+00],\n       [ 3.790e+03,  3.064e+00, -9.680e+00],\n       [ 3.790e+03,  3.071e+00, -9.680e+00],\n       [ 3.790e+03,  3.079e+00, -9.680e+00],\n       [ 3.790e+03,  3.087e+00, -9.679e+00],\n       [ 3.790e+03,  3.094e+00, -9.680e+00],\n       [ 3.790e+03,  3.102e+00, -9.680e+00],\n       [ 3.790e+03,  3.110e+00, -9.680e+00],\n       [ 3.790e+03,  3.118e+00, -9.680e+00],\n       [ 3.790e+03,  3.125e+00, -9.680e+00],\n       [ 3.790e+03,  3.133e+00, -9.680e+00],\n       [ 3.790e+03,  3.141e+00, -9.680e+00],\n       [ 3.790e+03,  3.148e+00, 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3.318e+00, -9.680e+00],\n       [ 3.790e+03,  3.326e+00, -9.679e+00],\n       [ 3.790e+03,  3.334e+00, -9.679e+00],\n       [ 3.790e+03,  3.341e+00, -9.680e+00],\n       [ 3.790e+03,  3.349e+00, -9.679e+00],\n       [ 3.790e+03,  3.357e+00, -9.680e+00],\n       [ 3.790e+03,  3.365e+00, -9.680e+00],\n       [ 3.790e+03,  3.372e+00, -9.680e+00],\n       [ 3.790e+03,  3.380e+00, -9.680e+00],\n       [ 3.790e+03,  3.388e+00, -9.680e+00],\n       [ 3.790e+03,  3.395e+00, -9.679e+00],\n       [ 3.790e+03,  3.403e+00, -9.680e+00],\n       [ 3.790e+03,  3.411e+00, -9.680e+00],\n       [ 3.790e+03,  3.419e+00, -9.680e+00],\n       [ 3.790e+03,  3.426e+00, -9.680e+00],\n       [ 3.790e+03,  3.434e+00, -9.680e+00],\n       [ 3.790e+03,  3.442e+00, -9.680e+00],\n       [ 3.790e+03,  3.449e+00, -9.679e+00],\n       [ 3.790e+03,  3.457e+00, -9.678e+00],\n       [ 3.790e+03,  3.465e+00, -9.677e+00]]), array([[ 3.791e+03,  2.701e+00, -9.680e+00],\n       [ 3.791e+03,  2.709e+00, -9.680e+00],\n       [ 3.791e+03,  2.716e+00, -9.679e+00],\n       [ 3.791e+03,  2.724e+00, -9.680e+00],\n       [ 3.791e+03,  2.732e+00, -9.680e+00],\n       [ 3.791e+03,  2.740e+00, -9.680e+00],\n       [ 3.791e+03,  2.747e+00, -9.680e+00],\n       [ 3.791e+03,  2.755e+00, -9.680e+00],\n       [ 3.791e+03,  2.763e+00, -9.679e+00],\n       [ 3.791e+03,  2.771e+00, -9.680e+00],\n       [ 3.791e+03,  2.778e+00, -9.680e+00],\n       [ 3.791e+03,  2.786e+00, -9.680e+00],\n       [ 3.791e+03,  2.794e+00, -9.680e+00],\n       [ 3.791e+03,  2.802e+00, -9.680e+00],\n       [ 3.791e+03,  2.810e+00, -9.680e+00],\n       [ 3.791e+03,  2.817e+00, -9.680e+00],\n       [ 3.791e+03,  2.825e+00, -9.680e+00],\n       [ 3.791e+03,  2.833e+00, -9.680e+00],\n       [ 3.791e+03,  2.841e+00, -9.680e+00],\n       [ 3.791e+03,  2.848e+00, -9.680e+00],\n       [ 3.791e+03,  2.856e+00, -9.680e+00],\n       [ 3.791e+03,  2.864e+00, -9.680e+00],\n       [ 3.791e+03,  2.872e+00, -9.680e+00],\n       [ 3.791e+03,  2.879e+00, -9.680e+00],\n       [ 3.791e+03,  2.887e+00, -9.680e+00],\n       [ 3.791e+03,  2.895e+00, -9.680e+00],\n       [ 3.791e+03,  2.903e+00, -9.680e+00],\n       [ 3.791e+03,  2.911e+00, -9.680e+00],\n       [ 3.791e+03,  2.918e+00, -9.680e+00],\n       [ 3.791e+03,  2.926e+00, -9.679e+00],\n       [ 3.791e+03,  2.934e+00, -9.680e+00],\n       [ 3.791e+03,  2.942e+00, -9.680e+00],\n       [ 3.791e+03,  2.949e+00, -9.680e+00],\n       [ 3.791e+03,  2.957e+00, -9.680e+00],\n       [ 3.791e+03,  2.965e+00, -9.680e+00],\n       [ 3.791e+03,  2.973e+00, -9.680e+00],\n       [ 3.791e+03,  2.980e+00, -9.680e+00],\n       [ 3.791e+03,  2.988e+00, -9.680e+00],\n       [ 3.791e+03,  2.996e+00, -9.680e+00],\n       [ 3.791e+03,  3.004e+00, -9.680e+00],\n       [ 3.791e+03,  3.012e+00, -9.680e+00],\n       [ 3.791e+03,  3.019e+00, -9.680e+00],\n       [ 3.791e+03,  3.027e+00, -9.680e+00],\n       [ 3.791e+03,  3.035e+00, -9.680e+00],\n       [ 3.791e+03,  3.043e+00, -9.680e+00],\n       [ 3.791e+03,  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3.791e+03,  3.221e+00, -9.680e+00],\n       [ 3.791e+03,  3.229e+00, -9.680e+00],\n       [ 3.791e+03,  3.237e+00, -9.679e+00],\n       [ 3.791e+03,  3.245e+00, -9.680e+00],\n       [ 3.791e+03,  3.252e+00, -9.680e+00],\n       [ 3.791e+03,  3.260e+00, -9.680e+00],\n       [ 3.791e+03,  3.268e+00, -9.680e+00],\n       [ 3.791e+03,  3.276e+00, -9.680e+00],\n       [ 3.791e+03,  3.284e+00, -9.680e+00],\n       [ 3.791e+03,  3.291e+00, -9.680e+00],\n       [ 3.791e+03,  3.299e+00, -9.680e+00],\n       [ 3.791e+03,  3.307e+00, -9.680e+00],\n       [ 3.791e+03,  3.315e+00, -9.680e+00],\n       [ 3.791e+03,  3.322e+00, -9.680e+00],\n       [ 3.791e+03,  3.330e+00, -9.680e+00],\n       [ 3.791e+03,  3.338e+00, -9.679e+00],\n       [ 3.791e+03,  3.346e+00, -9.680e+00],\n       [ 3.791e+03,  3.353e+00, -9.680e+00],\n       [ 3.791e+03,  3.361e+00, -9.680e+00],\n       [ 3.791e+03,  3.369e+00, -9.679e+00],\n       [ 3.791e+03,  3.377e+00, -9.680e+00],\n       [ 3.791e+03,  3.385e+00, -9.680e+00],\n       [ 3.791e+03,  3.392e+00, -9.680e+00],\n       [ 3.791e+03,  3.400e+00, -9.680e+00],\n       [ 3.791e+03,  3.408e+00, -9.680e+00],\n       [ 3.791e+03,  3.416e+00, -9.679e+00],\n       [ 3.791e+03,  3.423e+00, -9.680e+00],\n       [ 3.791e+03,  3.431e+00, -9.680e+00],\n       [ 3.791e+03,  3.439e+00, -9.680e+00],\n       [ 3.791e+03,  3.447e+00, -9.681e+00],\n       [ 3.791e+03,  3.454e+00, -9.682e+00],\n       [ 3.791e+03,  3.462e+00, -9.684e+00],\n       [ 3.791e+03,  3.470e+00, -9.685e+00]]), array([[ 3.792e+03,  2.701e+00, -9.680e+00],\n       [ 3.792e+03,  2.709e+00, -9.679e+00],\n       [ 3.792e+03,  2.716e+00, -9.680e+00],\n       [ 3.792e+03,  2.724e+00, -9.680e+00],\n       [ 3.792e+03,  2.732e+00, -9.680e+00],\n       [ 3.792e+03,  2.739e+00, -9.680e+00],\n       [ 3.792e+03,  2.747e+00, -9.680e+00],\n       [ 3.792e+03,  2.755e+00, -9.680e+00],\n       [ 3.792e+03,  2.763e+00, -9.680e+00],\n       [ 3.792e+03,  2.770e+00, -9.680e+00],\n       [ 3.792e+03, 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3.792e+03,  2.948e+00, -9.680e+00],\n       [ 3.792e+03,  2.955e+00, -9.679e+00],\n       [ 3.792e+03,  2.963e+00, -9.680e+00],\n       [ 3.792e+03,  2.971e+00, -9.680e+00],\n       [ 3.792e+03,  2.979e+00, -9.680e+00],\n       [ 3.792e+03,  2.986e+00, -9.679e+00],\n       [ 3.792e+03,  2.994e+00, -9.680e+00],\n       [ 3.792e+03,  3.002e+00, -9.680e+00],\n       [ 3.792e+03,  3.010e+00, -9.680e+00],\n       [ 3.792e+03,  3.017e+00, -9.680e+00],\n       [ 3.792e+03,  3.025e+00, -9.680e+00],\n       [ 3.792e+03,  3.033e+00, -9.680e+00],\n       [ 3.792e+03,  3.040e+00, -9.680e+00],\n       [ 3.792e+03,  3.048e+00, -9.680e+00],\n       [ 3.792e+03,  3.056e+00, -9.680e+00],\n       [ 3.792e+03,  3.064e+00, -9.680e+00],\n       [ 3.792e+03,  3.071e+00, -9.680e+00],\n       [ 3.792e+03,  3.079e+00, -9.680e+00],\n       [ 3.792e+03,  3.087e+00, -9.680e+00],\n       [ 3.792e+03,  3.094e+00, -9.680e+00],\n       [ 3.792e+03,  3.102e+00, -9.680e+00],\n       [ 3.792e+03,  3.110e+00, 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3.280e+00, -9.680e+00],\n       [ 3.792e+03,  3.287e+00, -9.680e+00],\n       [ 3.792e+03,  3.295e+00, -9.680e+00],\n       [ 3.792e+03,  3.303e+00, -9.680e+00],\n       [ 3.792e+03,  3.311e+00, -9.679e+00],\n       [ 3.792e+03,  3.318e+00, -9.680e+00],\n       [ 3.792e+03,  3.326e+00, -9.680e+00],\n       [ 3.792e+03,  3.334e+00, -9.680e+00],\n       [ 3.792e+03,  3.341e+00, -9.680e+00],\n       [ 3.792e+03,  3.349e+00, -9.680e+00],\n       [ 3.792e+03,  3.357e+00, -9.680e+00],\n       [ 3.792e+03,  3.365e+00, -9.680e+00],\n       [ 3.792e+03,  3.372e+00, -9.680e+00],\n       [ 3.792e+03,  3.380e+00, -9.680e+00],\n       [ 3.792e+03,  3.388e+00, -9.680e+00],\n       [ 3.792e+03,  3.395e+00, -9.680e+00],\n       [ 3.792e+03,  3.403e+00, -9.680e+00],\n       [ 3.792e+03,  3.411e+00, -9.680e+00],\n       [ 3.792e+03,  3.419e+00, -9.680e+00],\n       [ 3.792e+03,  3.426e+00, -9.680e+00],\n       [ 3.792e+03,  3.434e+00, -9.681e+00],\n       [ 3.792e+03,  3.442e+00, -9.681e+00],\n       [ 3.792e+03,  3.449e+00, -9.681e+00],\n       [ 3.792e+03,  3.457e+00, -9.680e+00],\n       [ 3.792e+03,  3.465e+00, -9.680e+00]]), array([[ 3.793e+03,  2.701e+00, -9.680e+00],\n       [ 3.793e+03,  2.709e+00, -9.680e+00],\n       [ 3.793e+03,  2.716e+00, -9.680e+00],\n       [ 3.793e+03,  2.724e+00, -9.680e+00],\n       [ 3.793e+03,  2.732e+00, -9.680e+00],\n       [ 3.793e+03,  2.739e+00, -9.680e+00],\n       [ 3.793e+03,  2.747e+00, -9.680e+00],\n       [ 3.793e+03,  2.755e+00, -9.680e+00],\n       [ 3.793e+03,  2.763e+00, -9.680e+00],\n       [ 3.793e+03,  2.770e+00, -9.680e+00],\n       [ 3.793e+03,  2.778e+00, -9.680e+00],\n       [ 3.793e+03,  2.786e+00, -9.680e+00],\n       [ 3.793e+03,  2.793e+00, -9.680e+00],\n       [ 3.793e+03,  2.801e+00, -9.680e+00],\n       [ 3.793e+03,  2.809e+00, -9.680e+00],\n       [ 3.793e+03,  2.817e+00, -9.680e+00],\n       [ 3.793e+03,  2.824e+00, -9.680e+00],\n       [ 3.793e+03,  2.832e+00, -9.680e+00],\n       [ 3.793e+03,  2.840e+00, 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3.793e+03,  3.179e+00, -9.680e+00],\n       [ 3.793e+03,  3.187e+00, -9.680e+00],\n       [ 3.793e+03,  3.195e+00, -9.680e+00],\n       [ 3.793e+03,  3.202e+00, -9.680e+00],\n       [ 3.793e+03,  3.210e+00, -9.680e+00],\n       [ 3.793e+03,  3.218e+00, -9.680e+00],\n       [ 3.793e+03,  3.226e+00, -9.680e+00],\n       [ 3.793e+03,  3.233e+00, -9.680e+00],\n       [ 3.793e+03,  3.241e+00, -9.681e+00],\n       [ 3.793e+03,  3.249e+00, -9.681e+00],\n       [ 3.793e+03,  3.256e+00, -9.680e+00],\n       [ 3.793e+03,  3.264e+00, -9.680e+00],\n       [ 3.793e+03,  3.272e+00, -9.680e+00],\n       [ 3.793e+03,  3.280e+00, -9.680e+00],\n       [ 3.793e+03,  3.287e+00, -9.680e+00],\n       [ 3.793e+03,  3.295e+00, -9.680e+00],\n       [ 3.793e+03,  3.303e+00, -9.680e+00],\n       [ 3.793e+03,  3.311e+00, -9.680e+00],\n       [ 3.793e+03,  3.318e+00, -9.680e+00],\n       [ 3.793e+03,  3.326e+00, -9.680e+00],\n       [ 3.793e+03,  3.334e+00, -9.681e+00],\n       [ 3.793e+03,  3.341e+00, -9.680e+00],\n       [ 3.793e+03,  3.349e+00, -9.680e+00],\n       [ 3.793e+03,  3.357e+00, -9.680e+00],\n       [ 3.793e+03,  3.365e+00, -9.680e+00],\n       [ 3.793e+03,  3.372e+00, -9.680e+00],\n       [ 3.793e+03,  3.380e+00, -9.680e+00],\n       [ 3.793e+03,  3.388e+00, -9.680e+00],\n       [ 3.793e+03,  3.395e+00, -9.680e+00],\n       [ 3.793e+03,  3.403e+00, -9.680e+00],\n       [ 3.793e+03,  3.411e+00, -9.679e+00],\n       [ 3.793e+03,  3.419e+00, -9.680e+00],\n       [ 3.793e+03,  3.426e+00, -9.680e+00],\n       [ 3.793e+03,  3.434e+00, -9.680e+00],\n       [ 3.793e+03,  3.442e+00, -9.681e+00],\n       [ 3.793e+03,  3.449e+00, -9.681e+00],\n       [ 3.793e+03,  3.457e+00, -9.680e+00],\n       [ 3.793e+03,  3.465e+00, -9.680e+00]]), array([[ 3.794e+03,  2.701e+00, -9.680e+00],\n       [ 3.794e+03,  2.709e+00, -9.680e+00],\n       [ 3.794e+03,  2.716e+00, -9.681e+00],\n       [ 3.794e+03,  2.724e+00, -9.680e+00],\n       [ 3.794e+03,  2.732e+00, -9.680e+00],\n       [ 3.794e+03, 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3.794e+03,  2.910e+00, -9.680e+00],\n       [ 3.794e+03,  2.918e+00, -9.680e+00],\n       [ 3.794e+03,  2.926e+00, -9.680e+00],\n       [ 3.794e+03,  2.933e+00, -9.680e+00],\n       [ 3.794e+03,  2.941e+00, -9.681e+00],\n       [ 3.794e+03,  2.949e+00, -9.680e+00],\n       [ 3.794e+03,  2.957e+00, -9.680e+00],\n       [ 3.794e+03,  2.964e+00, -9.680e+00],\n       [ 3.794e+03,  2.972e+00, -9.680e+00],\n       [ 3.794e+03,  2.980e+00, -9.680e+00],\n       [ 3.794e+03,  2.988e+00, -9.681e+00],\n       [ 3.794e+03,  2.995e+00, -9.680e+00],\n       [ 3.794e+03,  3.003e+00, -9.680e+00],\n       [ 3.794e+03,  3.011e+00, -9.680e+00],\n       [ 3.794e+03,  3.019e+00, -9.680e+00],\n       [ 3.794e+03,  3.026e+00, -9.680e+00],\n       [ 3.794e+03,  3.034e+00, -9.680e+00],\n       [ 3.794e+03,  3.042e+00, -9.679e+00],\n       [ 3.794e+03,  3.050e+00, -9.680e+00],\n       [ 3.794e+03,  3.057e+00, -9.680e+00],\n       [ 3.794e+03,  3.065e+00, -9.680e+00],\n       [ 3.794e+03,  3.073e+00, 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3.794e+03,  3.414e+00, -9.679e+00],\n       [ 3.794e+03,  3.422e+00, -9.680e+00],\n       [ 3.794e+03,  3.430e+00, -9.680e+00],\n       [ 3.794e+03,  3.437e+00, -9.680e+00],\n       [ 3.794e+03,  3.445e+00, -9.680e+00],\n       [ 3.794e+03,  3.453e+00, -9.681e+00],\n       [ 3.794e+03,  3.461e+00, -9.683e+00],\n       [ 3.794e+03,  3.468e+00, -9.684e+00]]), array([[ 3.795e+03,  2.701e+00, -9.680e+00],\n       [ 3.795e+03,  2.709e+00, -9.680e+00],\n       [ 3.795e+03,  2.716e+00, -9.680e+00],\n       [ 3.795e+03,  2.724e+00, -9.680e+00],\n       [ 3.795e+03,  2.732e+00, -9.680e+00],\n       [ 3.795e+03,  2.740e+00, -9.680e+00],\n       [ 3.795e+03,  2.747e+00, -9.680e+00],\n       [ 3.795e+03,  2.755e+00, -9.680e+00],\n       [ 3.795e+03,  2.763e+00, -9.680e+00],\n       [ 3.795e+03,  2.771e+00, -9.680e+00],\n       [ 3.795e+03,  2.778e+00, -9.680e+00],\n       [ 3.795e+03,  2.786e+00, -9.680e+00],\n       [ 3.795e+03,  2.794e+00, -9.680e+00],\n       [ 3.795e+03,  2.802e+00, 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-9.680e+00],\n       [ 3.795e+03,  3.313e+00, -9.680e+00],\n       [ 3.795e+03,  3.321e+00, -9.680e+00],\n       [ 3.795e+03,  3.329e+00, -9.680e+00],\n       [ 3.795e+03,  3.336e+00, -9.680e+00],\n       [ 3.795e+03,  3.344e+00, -9.680e+00],\n       [ 3.795e+03,  3.352e+00, -9.680e+00],\n       [ 3.795e+03,  3.360e+00, -9.680e+00],\n       [ 3.795e+03,  3.367e+00, -9.680e+00],\n       [ 3.795e+03,  3.375e+00, -9.680e+00],\n       [ 3.795e+03,  3.383e+00, -9.680e+00],\n       [ 3.795e+03,  3.391e+00, -9.680e+00],\n       [ 3.795e+03,  3.398e+00, -9.680e+00],\n       [ 3.795e+03,  3.406e+00, -9.680e+00],\n       [ 3.795e+03,  3.414e+00, -9.680e+00],\n       [ 3.795e+03,  3.422e+00, -9.680e+00],\n       [ 3.795e+03,  3.430e+00, -9.679e+00],\n       [ 3.795e+03,  3.437e+00, -9.679e+00],\n       [ 3.795e+03,  3.445e+00, -9.681e+00],\n       [ 3.795e+03,  3.453e+00, -9.682e+00],\n       [ 3.795e+03,  3.461e+00, -9.683e+00],\n       [ 3.795e+03,  3.468e+00, -9.685e+00]]), array([[ 3.796e+03, 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3.796e+03,  3.371e+00, -9.680e+00],\n       [ 3.796e+03,  3.378e+00, -9.679e+00],\n       [ 3.796e+03,  3.386e+00, -9.679e+00],\n       [ 3.796e+03,  3.394e+00, -9.679e+00],\n       [ 3.796e+03,  3.402e+00, -9.680e+00],\n       [ 3.796e+03,  3.409e+00, -9.681e+00],\n       [ 3.796e+03,  3.417e+00, -9.679e+00],\n       [ 3.796e+03,  3.425e+00, -9.680e+00],\n       [ 3.796e+03,  3.432e+00, -9.681e+00],\n       [ 3.796e+03,  3.440e+00, -9.681e+00],\n       [ 3.796e+03,  3.448e+00, -9.680e+00],\n       [ 3.796e+03,  3.455e+00, -9.680e+00],\n       [ 3.796e+03,  3.463e+00, -9.680e+00]]), array([[ 3.797e+03,  2.701e+00, -9.680e+00],\n       [ 3.797e+03,  2.709e+00, -9.680e+00],\n       [ 3.797e+03,  2.716e+00, -9.680e+00],\n       [ 3.797e+03,  2.724e+00, -9.680e+00],\n       [ 3.797e+03,  2.732e+00, -9.680e+00],\n       [ 3.797e+03,  2.739e+00, -9.680e+00],\n       [ 3.797e+03,  2.747e+00, -9.680e+00],\n       [ 3.797e+03,  2.755e+00, -9.680e+00],\n       [ 3.797e+03,  2.762e+00, 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3.800e+03,  3.294e+00, -9.680e+00],\n       [ 3.800e+03,  3.301e+00, -9.680e+00],\n       [ 3.800e+03,  3.309e+00, -9.680e+00],\n       [ 3.800e+03,  3.317e+00, -9.680e+00],\n       [ 3.800e+03,  3.325e+00, -9.680e+00],\n       [ 3.800e+03,  3.332e+00, -9.680e+00],\n       [ 3.800e+03,  3.340e+00, -9.680e+00],\n       [ 3.800e+03,  3.348e+00, -9.679e+00],\n       [ 3.800e+03,  3.355e+00, -9.680e+00],\n       [ 3.800e+03,  3.363e+00, -9.680e+00],\n       [ 3.800e+03,  3.371e+00, -9.680e+00],\n       [ 3.800e+03,  3.378e+00, -9.679e+00],\n       [ 3.800e+03,  3.386e+00, -9.680e+00],\n       [ 3.800e+03,  3.394e+00, -9.680e+00],\n       [ 3.800e+03,  3.402e+00, -9.681e+00],\n       [ 3.800e+03,  3.409e+00, -9.680e+00],\n       [ 3.800e+03,  3.417e+00, -9.679e+00],\n       [ 3.800e+03,  3.425e+00, -9.680e+00],\n       [ 3.800e+03,  3.432e+00, -9.680e+00],\n       [ 3.800e+03,  3.440e+00, -9.680e+00],\n       [ 3.800e+03,  3.448e+00, -9.681e+00],\n       [ 3.800e+03,  3.455e+00, -9.682e+00],\n       [ 3.800e+03,  3.463e+00, -9.683e+00]]), array([[ 3.801e+03,  2.701e+00, -9.680e+00],\n       [ 3.801e+03,  2.709e+00, -9.680e+00],\n       [ 3.801e+03,  2.716e+00, -9.680e+00],\n       [ 3.801e+03,  2.724e+00, -9.680e+00],\n       [ 3.801e+03,  2.732e+00, -9.680e+00],\n       [ 3.801e+03,  2.740e+00, -9.680e+00],\n       [ 3.801e+03,  2.747e+00, -9.680e+00],\n       [ 3.801e+03,  2.755e+00, -9.680e+00],\n       [ 3.801e+03,  2.763e+00, -9.680e+00],\n       [ 3.801e+03,  2.771e+00, -9.680e+00],\n       [ 3.801e+03,  2.778e+00, -9.680e+00],\n       [ 3.801e+03,  2.786e+00, -9.680e+00],\n       [ 3.801e+03,  2.794e+00, -9.680e+00],\n       [ 3.801e+03,  2.802e+00, -9.680e+00],\n       [ 3.801e+03,  2.809e+00, -9.680e+00],\n       [ 3.801e+03,  2.817e+00, -9.680e+00],\n       [ 3.801e+03,  2.825e+00, -9.680e+00],\n       [ 3.801e+03,  2.833e+00, -9.680e+00],\n       [ 3.801e+03,  2.840e+00, -9.680e+00],\n       [ 3.801e+03,  2.848e+00, -9.680e+00],\n       [ 3.801e+03, 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3.801e+03,  3.026e+00, -9.680e+00],\n       [ 3.801e+03,  3.034e+00, -9.680e+00],\n       [ 3.801e+03,  3.042e+00, -9.680e+00],\n       [ 3.801e+03,  3.050e+00, -9.681e+00],\n       [ 3.801e+03,  3.057e+00, -9.680e+00],\n       [ 3.801e+03,  3.065e+00, -9.680e+00],\n       [ 3.801e+03,  3.073e+00, -9.680e+00],\n       [ 3.801e+03,  3.081e+00, -9.680e+00],\n       [ 3.801e+03,  3.088e+00, -9.680e+00],\n       [ 3.801e+03,  3.096e+00, -9.680e+00],\n       [ 3.801e+03,  3.104e+00, -9.680e+00],\n       [ 3.801e+03,  3.112e+00, -9.680e+00],\n       [ 3.801e+03,  3.119e+00, -9.679e+00],\n       [ 3.801e+03,  3.127e+00, -9.680e+00],\n       [ 3.801e+03,  3.135e+00, -9.680e+00],\n       [ 3.801e+03,  3.143e+00, -9.680e+00],\n       [ 3.801e+03,  3.150e+00, -9.680e+00],\n       [ 3.801e+03,  3.158e+00, -9.679e+00],\n       [ 3.801e+03,  3.166e+00, -9.680e+00],\n       [ 3.801e+03,  3.174e+00, -9.680e+00],\n       [ 3.801e+03,  3.181e+00, -9.680e+00],\n       [ 3.801e+03,  3.189e+00, 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3.360e+00, -9.680e+00],\n       [ 3.801e+03,  3.367e+00, -9.680e+00],\n       [ 3.801e+03,  3.375e+00, -9.679e+00],\n       [ 3.801e+03,  3.383e+00, -9.680e+00],\n       [ 3.801e+03,  3.391e+00, -9.680e+00],\n       [ 3.801e+03,  3.398e+00, -9.680e+00],\n       [ 3.801e+03,  3.406e+00, -9.680e+00],\n       [ 3.801e+03,  3.414e+00, -9.680e+00],\n       [ 3.801e+03,  3.422e+00, -9.680e+00],\n       [ 3.801e+03,  3.430e+00, -9.680e+00],\n       [ 3.801e+03,  3.437e+00, -9.680e+00],\n       [ 3.801e+03,  3.445e+00, -9.680e+00],\n       [ 3.801e+03,  3.453e+00, -9.682e+00],\n       [ 3.801e+03,  3.461e+00, -9.684e+00],\n       [ 3.801e+03,  3.468e+00, -9.685e+00]]), array([[ 3.802e+03,  2.701e+00, -9.680e+00],\n       [ 3.802e+03,  2.709e+00, -9.680e+00],\n       [ 3.802e+03,  2.716e+00, -9.680e+00],\n       [ 3.802e+03,  2.724e+00, -9.680e+00],\n       [ 3.802e+03,  2.732e+00, -9.680e+00],\n       [ 3.802e+03,  2.740e+00, -9.680e+00],\n       [ 3.802e+03,  2.747e+00, -9.680e+00],\n       [ 3.802e+03,  2.755e+00, -9.680e+00],\n       [ 3.802e+03,  2.763e+00, -9.680e+00],\n       [ 3.802e+03,  2.771e+00, -9.680e+00],\n       [ 3.802e+03,  2.778e+00, -9.680e+00],\n       [ 3.802e+03,  2.786e+00, -9.680e+00],\n       [ 3.802e+03,  2.794e+00, -9.680e+00],\n       [ 3.802e+03,  2.802e+00, -9.680e+00],\n       [ 3.802e+03,  2.810e+00, -9.680e+00],\n       [ 3.802e+03,  2.817e+00, -9.680e+00],\n       [ 3.802e+03,  2.825e+00, -9.681e+00],\n       [ 3.802e+03,  2.833e+00, -9.680e+00],\n       [ 3.802e+03,  2.841e+00, -9.680e+00],\n       [ 3.802e+03,  2.848e+00, -9.680e+00],\n       [ 3.802e+03,  2.856e+00, -9.680e+00],\n       [ 3.802e+03,  2.864e+00, -9.680e+00],\n       [ 3.802e+03,  2.872e+00, -9.680e+00],\n       [ 3.802e+03,  2.879e+00, -9.679e+00],\n       [ 3.802e+03,  2.887e+00, -9.680e+00],\n       [ 3.802e+03,  2.895e+00, -9.680e+00],\n       [ 3.802e+03,  2.903e+00, -9.680e+00],\n       [ 3.802e+03,  2.911e+00, -9.680e+00],\n       [ 3.802e+03,  2.918e+00, 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[440.   ,   3.801,  -0.968],\n       [440.   ,   3.813,  -0.968],\n       [440.   ,   3.825,  -0.968],\n       [440.   ,   3.837,  -0.968],\n       [440.   ,   3.849,  -0.968],\n       [440.   ,   3.861,  -0.968],\n       [440.   ,   3.873,  -0.968],\n       [440.   ,   3.885,  -0.973]]), array([[441.   ,   2.701,  -0.968],\n       [441.   ,   2.713,  -0.968],\n       [441.   ,   2.725,  -0.968],\n       [441.   ,   2.737,  -0.968],\n       [441.   ,   2.749,  -0.968],\n       [441.   ,   2.761,  -0.968],\n       [441.   ,   2.773,  -0.968],\n       [441.   ,   2.785,  -0.968],\n       [441.   ,   2.797,  -0.968],\n       [441.   ,   2.808,  -0.968],\n       [441.   ,   2.82 ,  -0.968],\n       [441.   ,   2.832,  -0.968],\n       [441.   ,   2.844,  -0.967],\n       [441.   ,   2.856,  -0.968],\n       [441.   ,   2.868,  -0.968],\n       [441.   ,   2.88 ,  -0.968],\n       [441.   ,   2.892,  -0.968],\n       [441.   ,   2.904,  -0.968],\n       [441.   ,   2.916,  -0.968],\n       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[441.   ,   3.574,  -0.968],\n       [441.   ,   3.586,  -0.968],\n       [441.   ,   3.598,  -0.968],\n       [441.   ,   3.61 ,  -0.968],\n       [441.   ,   3.622,  -0.968],\n       [441.   ,   3.634,  -0.968],\n       [441.   ,   3.646,  -0.968],\n       [441.   ,   3.658,  -0.968],\n       [441.   ,   3.67 ,  -0.968],\n       [441.   ,   3.682,  -0.968],\n       [441.   ,   3.694,  -0.968],\n       [441.   ,   3.706,  -0.968],\n       [441.   ,   3.718,  -0.968],\n       [441.   ,   3.73 ,  -0.968],\n       [441.   ,   3.742,  -0.968],\n       [441.   ,   3.754,  -0.968],\n       [441.   ,   3.766,  -0.968],\n       [441.   ,   3.778,  -0.968],\n       [441.   ,   3.789,  -0.968],\n       [441.   ,   3.801,  -0.968],\n       [441.   ,   3.813,  -0.968],\n       [441.   ,   3.825,  -0.968],\n       [441.   ,   3.837,  -0.968],\n       [441.   ,   3.849,  -0.968],\n       [441.   ,   3.861,  -0.968],\n       [441.   ,   3.873,  -0.968],\n       [441.   ,   3.885,  -0.972]]), array([[442.   ,   2.701,  -0.968],\n       [442.   ,   2.713,  -0.968],\n       [442.   ,   2.725,  -0.968],\n       [442.   ,   2.737,  -0.968],\n       [442.   ,   2.749,  -0.968],\n       [442.   ,   2.761,  -0.968],\n       [442.   ,   2.773,  -0.968],\n       [442.   ,   2.785,  -0.968],\n       [442.   ,   2.797,  -0.968],\n       [442.   ,   2.808,  -0.968],\n       [442.   ,   2.82 ,  -0.968],\n       [442.   ,   2.832,  -0.968],\n       [442.   ,   2.844,  -0.968],\n       [442.   ,   2.856,  -0.968],\n       [442.   ,   2.868,  -0.968],\n       [442.   ,   2.88 ,  -0.968],\n       [442.   ,   2.892,  -0.968],\n       [442.   ,   2.904,  -0.968],\n       [442.   ,   2.916,  -0.968],\n       [442.   ,   2.928,  -0.968],\n       [442.   ,   2.94 ,  -0.968],\n       [442.   ,   2.952,  -0.968],\n       [442.   ,   2.964,  -0.968],\n       [442.   ,   2.976,  -0.967],\n       [442.   ,   2.988,  -0.968],\n       [442.   ,   3.   ,  -0.968],\n       [442.   ,   3.012,  -0.968],\n  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   [442.   ,   3.347,  -0.968],\n       [442.   ,   3.359,  -0.968],\n       [442.   ,   3.371,  -0.968],\n       [442.   ,   3.383,  -0.968],\n       [442.   ,   3.395,  -0.968],\n       [442.   ,   3.407,  -0.968],\n       [442.   ,   3.419,  -0.968],\n       [442.   ,   3.431,  -0.968],\n       [442.   ,   3.443,  -0.968],\n       [442.   ,   3.454,  -0.968],\n       [442.   ,   3.466,  -0.968],\n       [442.   ,   3.478,  -0.968],\n       [442.   ,   3.49 ,  -0.968],\n       [442.   ,   3.502,  -0.968],\n       [442.   ,   3.514,  -0.968],\n       [442.   ,   3.526,  -0.968],\n       [442.   ,   3.538,  -0.968],\n       [442.   ,   3.55 ,  -0.968],\n       [442.   ,   3.562,  -0.968],\n       [442.   ,   3.574,  -0.968],\n       [442.   ,   3.586,  -0.968],\n       [442.   ,   3.598,  -0.968],\n       [442.   ,   3.61 ,  -0.968],\n       [442.   ,   3.622,  -0.968],\n       [442.   ,   3.634,  -0.968],\n       [442.   ,   3.646,  -0.968],\n       [442.   ,   3.658,  -0.968],\n       [442.   ,   3.67 ,  -0.968],\n       [442.   ,   3.682,  -0.968],\n       [442.   ,   3.694,  -0.968],\n       [442.   ,   3.706,  -0.968],\n       [442.   ,   3.718,  -0.968],\n       [442.   ,   3.73 ,  -0.968],\n       [442.   ,   3.742,  -0.968],\n       [442.   ,   3.754,  -0.968],\n       [442.   ,   3.766,  -0.968],\n       [442.   ,   3.778,  -0.968],\n       [442.   ,   3.789,  -0.968],\n       [442.   ,   3.801,  -0.968],\n       [442.   ,   3.813,  -0.968],\n       [442.   ,   3.825,  -0.968],\n       [442.   ,   3.837,  -0.968],\n       [442.   ,   3.849,  -0.968],\n       [442.   ,   3.861,  -0.968],\n       [442.   ,   3.873,  -0.968],\n       [442.   ,   3.885,  -0.972]]), array([[443.   ,   2.701,  -0.968],\n       [443.   ,   2.713,  -0.967],\n       [443.   ,   2.725,  -0.968],\n       [443.   ,   2.737,  -0.968],\n       [443.   ,   2.749,  -0.968],\n       [443.   ,   2.761,  -0.968],\n       [443.   ,   2.773,  -0.968],\n       [443.   ,   2.785,  -0.968],\n       [443.   ,   2.797,  -0.967],\n       [443.   ,   2.808,  -0.968],\n       [443.   ,   2.82 ,  -0.968],\n       [443.   ,   2.832,  -0.968],\n       [443.   ,   2.844,  -0.968],\n       [443.   ,   2.856,  -0.967],\n       [443.   ,   2.868,  -0.968],\n       [443.   ,   2.88 ,  -0.968],\n       [443.   ,   2.892,  -0.968],\n       [443.   ,   2.904,  -0.968],\n       [443.   ,   2.916,  -0.968],\n       [443.   ,   2.928,  -0.968],\n       [443.   ,   2.94 ,  -0.968],\n       [443.   ,   2.952,  -0.968],\n       [443.   ,   2.964,  -0.968],\n       [443.   ,   2.976,  -0.968],\n       [443.   ,   2.988,  -0.968],\n       [443.   ,   3.   ,  -0.968],\n       [443.   ,   3.012,  -0.967],\n       [443.   ,   3.024,  -0.968],\n       [443.   ,   3.036,  -0.968],\n       [443.   ,   3.048,  -0.968],\n       [443.   ,   3.06 ,  -0.968],\n       [443.   ,   3.072,  -0.968],\n       [443.   ,   3.084,  -0.968],\n       [443.   ,   3.096,  -0.968],\n       [443.   ,   3.108,  -0.968],\n       [443.   ,   3.12 ,  -0.968],\n       [443.   ,   3.131,  -0.967],\n       [443.   ,   3.143,  -0.968],\n       [443.   ,   3.155,  -0.967],\n       [443.   ,   3.167,  -0.968],\n       [443.   ,   3.179,  -0.968],\n       [443.   ,   3.191,  -0.968],\n       [443.   ,   3.203,  -0.968],\n       [443.   ,   3.215,  -0.968],\n       [443.   ,   3.227,  -0.968],\n       [443.   ,   3.239,  -0.968],\n       [443.   ,   3.251,  -0.968],\n       [443.   ,   3.263,  -0.968],\n       [443.   ,   3.275,  -0.968],\n       [443.   ,   3.287,  -0.968],\n       [443.   ,   3.299,  -0.968],\n       [443.   ,   3.311,  -0.968],\n       [443.   ,   3.323,  -0.967],\n       [443.   ,   3.335,  -0.968],\n       [443.   ,   3.347,  -0.968],\n       [443.   ,   3.359,  -0.968],\n       [443.   ,   3.371,  -0.968],\n       [443.   ,   3.383,  -0.968],\n       [443.   ,   3.395,  -0.967],\n       [443.   ,   3.407,  -0.968],\n       [443.   ,   3.419,  -0.968],\n       [443.   ,   3.431,  -0.968],\n       [443.   ,   3.443,  -0.968],\n       [443.   ,   3.454,  -0.968],\n       [443.   ,   3.466,  -0.968],\n       [443.   ,   3.478,  -0.968],\n       [443.   ,   3.49 ,  -0.968],\n       [443.   ,   3.502,  -0.968],\n       [443.   ,   3.514,  -0.968],\n       [443.   ,   3.526,  -0.968],\n       [443.   ,   3.538,  -0.968],\n       [443.   ,   3.55 ,  -0.968],\n       [443.   ,   3.562,  -0.968],\n       [443.   ,   3.574,  -0.968],\n       [443.   ,   3.586,  -0.968],\n       [443.   ,   3.598,  -0.968],\n       [443.   ,   3.61 ,  -0.968],\n       [443.   ,   3.622,  -0.968],\n       [443.   ,   3.634,  -0.967],\n       [443.   ,   3.646,  -0.968],\n       [443.   ,   3.658,  -0.968],\n       [443.   ,   3.67 ,  -0.968],\n       [443.   ,   3.682,  -0.968],\n       [443.   ,   3.694,  -0.968],\n       [443.   ,   3.706,  -0.968],\n       [443.   ,   3.718,  -0.968],\n       [443.   ,   3.73 ,  -0.968],\n       [443.   ,   3.742,  -0.968],\n       [443.   ,   3.754,  -0.968],\n       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array([[156.   ,   2.702,  -0.968],\n       [156.   ,   2.716,  -0.968],\n       [156.   ,   2.73 ,  -0.968],\n       [156.   ,   2.744,  -0.968],\n       [156.   ,   2.759,  -0.968],\n       [156.   ,   2.773,  -0.968],\n       [156.   ,   2.787,  -0.968],\n       [156.   ,   2.801,  -0.968],\n       [156.   ,   2.816,  -0.968],\n       [156.   ,   2.83 ,  -0.968],\n       [156.   ,   2.844,  -0.968],\n       [156.   ,   2.858,  -0.968],\n       [156.   ,   2.873,  -0.968],\n       [156.   ,   2.887,  -0.968],\n       [156.   ,   2.901,  -0.968],\n       [156.   ,   2.915,  -0.968],\n       [156.   ,   2.93 ,  -0.968],\n       [156.   ,   2.944,  -0.967],\n       [156.   ,   2.958,  -0.968],\n       [156.   ,   2.972,  -0.968],\n       [156.   ,   2.987,  -0.968],\n       [156.   ,   3.001,  -0.968],\n       [156.   ,   3.015,  -0.968],\n       [156.   ,   3.029,  -0.968],\n       [156.   ,   3.044,  -0.968],\n       [156.   ,   3.058,  -0.968],\n       [156.   ,   3.072,  -0.968],\n  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3.583e+03,  3.897e+00, -9.686e+00],\n       [ 3.583e+03,  3.901e+00, -9.686e+00],\n       [ 3.583e+03,  3.905e+00, -9.686e+00],\n       [ 3.583e+03,  3.909e+00, -9.687e+00]]), array([[ 3.584e+03,  3.501e+00, -9.680e+00],\n       [ 3.584e+03,  3.505e+00, -9.681e+00],\n       [ 3.584e+03,  3.509e+00, -9.680e+00],\n       [ 3.584e+03,  3.513e+00, -9.680e+00],\n       [ 3.584e+03,  3.517e+00, -9.680e+00],\n       [ 3.584e+03,  3.521e+00, -9.680e+00],\n       [ 3.584e+03,  3.525e+00, -9.680e+00],\n       [ 3.584e+03,  3.529e+00, -9.680e+00],\n       [ 3.584e+03,  3.534e+00, -9.680e+00],\n       [ 3.584e+03,  3.538e+00, -9.680e+00],\n       [ 3.584e+03,  3.542e+00, -9.680e+00],\n       [ 3.584e+03,  3.546e+00, -9.680e+00],\n       [ 3.584e+03,  3.550e+00, -9.680e+00],\n       [ 3.584e+03,  3.554e+00, -9.680e+00],\n       [ 3.584e+03,  3.558e+00, -9.680e+00],\n       [ 3.584e+03,  3.562e+00, -9.680e+00],\n       [ 3.584e+03,  3.567e+00, -9.680e+00],\n       [ 3.584e+03,  3.571e+00, 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3.585e+03,  3.876e+00, -9.683e+00],\n       [ 3.585e+03,  3.880e+00, -9.683e+00],\n       [ 3.585e+03,  3.884e+00, -9.684e+00],\n       [ 3.585e+03,  3.888e+00, -9.684e+00],\n       [ 3.585e+03,  3.893e+00, -9.684e+00],\n       [ 3.585e+03,  3.897e+00, -9.684e+00],\n       [ 3.585e+03,  3.901e+00, -9.684e+00],\n       [ 3.585e+03,  3.905e+00, -9.684e+00],\n       [ 3.585e+03,  3.909e+00, -9.685e+00]]), array([[ 3.586e+03,  3.501e+00, -9.680e+00],\n       [ 3.586e+03,  3.505e+00, -9.680e+00],\n       [ 3.586e+03,  3.509e+00, -9.680e+00],\n       [ 3.586e+03,  3.513e+00, -9.680e+00],\n       [ 3.586e+03,  3.517e+00, -9.680e+00],\n       [ 3.586e+03,  3.521e+00, -9.680e+00],\n       [ 3.586e+03,  3.525e+00, -9.679e+00],\n       [ 3.586e+03,  3.529e+00, -9.680e+00],\n       [ 3.586e+03,  3.534e+00, -9.680e+00],\n       [ 3.586e+03,  3.538e+00, -9.680e+00],\n       [ 3.586e+03,  3.542e+00, -9.680e+00],\n       [ 3.586e+03,  3.546e+00, -9.680e+00],\n       [ 3.586e+03,  3.550e+00, 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3.591e+03,  3.814e+00, -9.681e+00],\n       [ 3.591e+03,  3.818e+00, -9.681e+00],\n       [ 3.591e+03,  3.822e+00, -9.682e+00],\n       [ 3.591e+03,  3.827e+00, -9.682e+00],\n       [ 3.591e+03,  3.831e+00, -9.682e+00],\n       [ 3.591e+03,  3.835e+00, -9.682e+00],\n       [ 3.591e+03,  3.839e+00, -9.682e+00],\n       [ 3.591e+03,  3.843e+00, -9.683e+00],\n       [ 3.591e+03,  3.847e+00, -9.683e+00],\n       [ 3.591e+03,  3.851e+00, -9.683e+00],\n       [ 3.591e+03,  3.855e+00, -9.683e+00],\n       [ 3.591e+03,  3.860e+00, -9.684e+00],\n       [ 3.591e+03,  3.864e+00, -9.684e+00],\n       [ 3.591e+03,  3.868e+00, -9.684e+00],\n       [ 3.591e+03,  3.872e+00, -9.684e+00],\n       [ 3.591e+03,  3.876e+00, -9.684e+00],\n       [ 3.591e+03,  3.880e+00, -9.685e+00],\n       [ 3.591e+03,  3.884e+00, -9.685e+00],\n       [ 3.591e+03,  3.888e+00, -9.685e+00],\n       [ 3.591e+03,  3.893e+00, -9.685e+00],\n       [ 3.591e+03,  3.897e+00, -9.686e+00],\n       [ 3.591e+03,  3.901e+00, -9.686e+00],\n       [ 3.591e+03,  3.905e+00, -9.686e+00],\n       [ 3.591e+03,  3.909e+00, -9.686e+00]]), array([[ 3.592e+03,  3.501e+00, -9.680e+00],\n       [ 3.592e+03,  3.505e+00, -9.680e+00],\n       [ 3.592e+03,  3.509e+00, -9.680e+00],\n       [ 3.592e+03,  3.513e+00, -9.680e+00],\n       [ 3.592e+03,  3.517e+00, -9.680e+00],\n       [ 3.592e+03,  3.521e+00, -9.680e+00],\n       [ 3.592e+03,  3.525e+00, -9.680e+00],\n       [ 3.592e+03,  3.529e+00, -9.680e+00],\n       [ 3.592e+03,  3.534e+00, -9.680e+00],\n       [ 3.592e+03,  3.538e+00, -9.680e+00],\n       [ 3.592e+03,  3.542e+00, -9.680e+00],\n       [ 3.592e+03,  3.546e+00, -9.680e+00],\n       [ 3.592e+03,  3.550e+00, -9.680e+00],\n       [ 3.592e+03,  3.554e+00, -9.680e+00],\n       [ 3.592e+03,  3.558e+00, -9.680e+00],\n       [ 3.592e+03,  3.562e+00, -9.680e+00],\n       [ 3.592e+03,  3.567e+00, -9.680e+00],\n       [ 3.592e+03,  3.571e+00, -9.680e+00],\n       [ 3.592e+03,  3.575e+00, -9.679e+00],\n       [ 3.592e+03, 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3.593e+03,  3.793e+00, -9.680e+00],\n       [ 3.593e+03,  3.798e+00, -9.680e+00],\n       [ 3.593e+03,  3.802e+00, -9.680e+00],\n       [ 3.593e+03,  3.806e+00, -9.680e+00],\n       [ 3.593e+03,  3.810e+00, -9.681e+00],\n       [ 3.593e+03,  3.814e+00, -9.681e+00],\n       [ 3.593e+03,  3.818e+00, -9.681e+00],\n       [ 3.593e+03,  3.822e+00, -9.681e+00],\n       [ 3.593e+03,  3.827e+00, -9.681e+00],\n       [ 3.593e+03,  3.831e+00, -9.682e+00],\n       [ 3.593e+03,  3.835e+00, -9.682e+00],\n       [ 3.593e+03,  3.839e+00, -9.682e+00],\n       [ 3.593e+03,  3.843e+00, -9.682e+00],\n       [ 3.593e+03,  3.847e+00, -9.682e+00],\n       [ 3.593e+03,  3.851e+00, -9.683e+00],\n       [ 3.593e+03,  3.855e+00, -9.683e+00],\n       [ 3.593e+03,  3.860e+00, -9.683e+00],\n       [ 3.593e+03,  3.864e+00, -9.683e+00],\n       [ 3.593e+03,  3.868e+00, -9.684e+00],\n       [ 3.593e+03,  3.872e+00, -9.684e+00],\n       [ 3.593e+03,  3.876e+00, -9.684e+00],\n       [ 3.593e+03,  3.880e+00, 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[280.   ,   4.07 ,  -0.967],\n       [280.   ,   4.084,  -0.968],\n       [280.   ,   4.098,  -0.973]]), array([[281.   ,   2.702,  -0.968],\n       [281.   ,   2.716,  -0.968],\n       [281.   ,   2.73 ,  -0.968],\n       [281.   ,   2.744,  -0.968],\n       [281.   ,   2.758,  -0.968],\n       [281.   ,   2.772,  -0.968],\n       [281.   ,   2.786,  -0.968],\n       [281.   ,   2.8  ,  -0.968],\n       [281.   ,   2.814,  -0.968],\n       [281.   ,   2.828,  -0.968],\n       [281.   ,   2.842,  -0.968],\n       [281.   ,   2.856,  -0.967],\n       [281.   ,   2.87 ,  -0.968],\n       [281.   ,   2.884,  -0.968],\n       [281.   ,   2.899,  -0.968],\n       [281.   ,   2.913,  -0.968],\n       [281.   ,   2.927,  -0.968],\n       [281.   ,   2.941,  -0.968],\n       [281.   ,   2.955,  -0.968],\n       [281.   ,   2.969,  -0.968],\n       [281.   ,   2.983,  -0.968],\n       [281.   ,   2.997,  -0.968],\n       [281.   ,   3.011,  -0.968],\n       [281.   ,   3.025,  -0.968],\n       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3.141e+03,  3.629e+00, -9.680e+00],\n       [ 3.141e+03,  3.641e+00, -9.680e+00],\n       [ 3.141e+03,  3.652e+00, -9.680e+00],\n       [ 3.141e+03,  3.664e+00, -9.680e+00],\n       [ 3.141e+03,  3.675e+00, -9.680e+00],\n       [ 3.141e+03,  3.687e+00, -9.681e+00],\n       [ 3.141e+03,  3.699e+00, -9.680e+00],\n       [ 3.141e+03,  3.710e+00, -9.680e+00],\n       [ 3.141e+03,  3.722e+00, -9.680e+00],\n       [ 3.141e+03,  3.733e+00, -9.679e+00],\n       [ 3.141e+03,  3.745e+00, -9.679e+00],\n       [ 3.141e+03,  3.757e+00, -9.680e+00],\n       [ 3.141e+03,  3.768e+00, -9.680e+00],\n       [ 3.141e+03,  3.780e+00, -9.680e+00],\n       [ 3.141e+03,  3.791e+00, -9.680e+00],\n       [ 3.141e+03,  3.803e+00, -9.679e+00],\n       [ 3.141e+03,  3.815e+00, -9.679e+00],\n       [ 3.141e+03,  3.826e+00, -9.679e+00],\n       [ 3.141e+03,  3.838e+00, -9.679e+00],\n       [ 3.141e+03,  3.849e+00, -9.679e+00]]), array([[ 3.142e+03,  2.701e+00, -9.680e+00],\n       [ 3.142e+03,  2.713e+00, 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3.142e+03,  3.228e+00, -9.680e+00],\n       [ 3.142e+03,  3.239e+00, -9.680e+00],\n       [ 3.142e+03,  3.251e+00, -9.680e+00],\n       [ 3.142e+03,  3.263e+00, -9.680e+00],\n       [ 3.142e+03,  3.274e+00, -9.679e+00],\n       [ 3.142e+03,  3.286e+00, -9.680e+00],\n       [ 3.142e+03,  3.298e+00, -9.680e+00],\n       [ 3.142e+03,  3.309e+00, -9.680e+00],\n       [ 3.142e+03,  3.321e+00, -9.680e+00],\n       [ 3.142e+03,  3.333e+00, -9.680e+00],\n       [ 3.142e+03,  3.345e+00, -9.680e+00],\n       [ 3.142e+03,  3.356e+00, -9.680e+00],\n       [ 3.142e+03,  3.368e+00, -9.680e+00],\n       [ 3.142e+03,  3.380e+00, -9.680e+00],\n       [ 3.142e+03,  3.391e+00, -9.680e+00],\n       [ 3.142e+03,  3.403e+00, -9.680e+00],\n       [ 3.142e+03,  3.415e+00, -9.680e+00],\n       [ 3.142e+03,  3.427e+00, -9.680e+00],\n       [ 3.142e+03,  3.438e+00, -9.679e+00],\n       [ 3.142e+03,  3.450e+00, -9.680e+00],\n       [ 3.142e+03,  3.462e+00, -9.680e+00],\n       [ 3.142e+03,  3.473e+00, 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3.143e+03,  3.571e+00, -9.680e+00],\n       [ 3.143e+03,  3.583e+00, -9.680e+00],\n       [ 3.143e+03,  3.594e+00, -9.680e+00],\n       [ 3.143e+03,  3.606e+00, -9.680e+00],\n       [ 3.143e+03,  3.617e+00, -9.680e+00],\n       [ 3.143e+03,  3.629e+00, -9.680e+00],\n       [ 3.143e+03,  3.641e+00, -9.680e+00],\n       [ 3.143e+03,  3.652e+00, -9.680e+00],\n       [ 3.143e+03,  3.664e+00, -9.680e+00],\n       [ 3.143e+03,  3.675e+00, -9.680e+00],\n       [ 3.143e+03,  3.687e+00, -9.680e+00],\n       [ 3.143e+03,  3.699e+00, -9.680e+00],\n       [ 3.143e+03,  3.710e+00, -9.680e+00],\n       [ 3.143e+03,  3.722e+00, -9.680e+00],\n       [ 3.143e+03,  3.733e+00, -9.680e+00],\n       [ 3.143e+03,  3.745e+00, -9.680e+00],\n       [ 3.143e+03,  3.757e+00, -9.680e+00],\n       [ 3.143e+03,  3.768e+00, -9.680e+00],\n       [ 3.143e+03,  3.780e+00, -9.680e+00],\n       [ 3.143e+03,  3.791e+00, -9.680e+00],\n       [ 3.143e+03,  3.803e+00, -9.680e+00],\n       [ 3.143e+03,  3.815e+00, 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3.148e+03,  3.813e+00, -9.682e+00],\n       [ 3.148e+03,  3.825e+00, -9.682e+00],\n       [ 3.148e+03,  3.836e+00, -9.683e+00],\n       [ 3.148e+03,  3.848e+00, -9.683e+00],\n       [ 3.148e+03,  3.860e+00, -9.684e+00]]), array([[ 3.149e+03,  2.701e+00, -9.680e+00],\n       [ 3.149e+03,  2.713e+00, -9.680e+00],\n       [ 3.149e+03,  2.724e+00, -9.680e+00],\n       [ 3.149e+03,  2.736e+00, -9.680e+00],\n       [ 3.149e+03,  2.748e+00, -9.680e+00],\n       [ 3.149e+03,  2.759e+00, -9.680e+00],\n       [ 3.149e+03,  2.771e+00, -9.680e+00],\n       [ 3.149e+03,  2.783e+00, -9.680e+00],\n       [ 3.149e+03,  2.794e+00, -9.680e+00],\n       [ 3.149e+03,  2.806e+00, -9.680e+00],\n       [ 3.149e+03,  2.818e+00, -9.680e+00],\n       [ 3.149e+03,  2.830e+00, -9.680e+00],\n       [ 3.149e+03,  2.841e+00, -9.680e+00],\n       [ 3.149e+03,  2.853e+00, -9.680e+00],\n       [ 3.149e+03,  2.865e+00, -9.680e+00],\n       [ 3.149e+03,  2.876e+00, -9.680e+00],\n       [ 3.149e+03,  2.888e+00, 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3.149e+03,  3.403e+00, -9.680e+00],\n       [ 3.149e+03,  3.415e+00, -9.680e+00],\n       [ 3.149e+03,  3.427e+00, -9.680e+00],\n       [ 3.149e+03,  3.438e+00, -9.680e+00],\n       [ 3.149e+03,  3.450e+00, -9.680e+00],\n       [ 3.149e+03,  3.462e+00, -9.680e+00],\n       [ 3.149e+03,  3.473e+00, -9.680e+00],\n       [ 3.149e+03,  3.485e+00, -9.680e+00],\n       [ 3.149e+03,  3.497e+00, -9.680e+00],\n       [ 3.149e+03,  3.508e+00, -9.680e+00],\n       [ 3.149e+03,  3.520e+00, -9.680e+00],\n       [ 3.149e+03,  3.532e+00, -9.680e+00],\n       [ 3.149e+03,  3.544e+00, -9.680e+00],\n       [ 3.149e+03,  3.555e+00, -9.680e+00],\n       [ 3.149e+03,  3.567e+00, -9.680e+00],\n       [ 3.149e+03,  3.579e+00, -9.680e+00],\n       [ 3.149e+03,  3.590e+00, -9.680e+00],\n       [ 3.149e+03,  3.602e+00, -9.680e+00],\n       [ 3.149e+03,  3.614e+00, -9.680e+00],\n       [ 3.149e+03,  3.626e+00, -9.680e+00],\n       [ 3.149e+03,  3.637e+00, -9.680e+00],\n       [ 3.149e+03,  3.649e+00, -9.680e+00],\n       [ 3.149e+03,  3.661e+00, -9.680e+00],\n       [ 3.149e+03,  3.672e+00, -9.680e+00],\n       [ 3.149e+03,  3.684e+00, -9.680e+00],\n       [ 3.149e+03,  3.696e+00, -9.681e+00],\n       [ 3.149e+03,  3.707e+00, -9.681e+00],\n       [ 3.149e+03,  3.719e+00, -9.681e+00],\n       [ 3.149e+03,  3.731e+00, -9.680e+00],\n       [ 3.149e+03,  3.743e+00, -9.680e+00],\n       [ 3.149e+03,  3.754e+00, -9.680e+00],\n       [ 3.149e+03,  3.766e+00, -9.680e+00],\n       [ 3.149e+03,  3.778e+00, -9.681e+00],\n       [ 3.149e+03,  3.789e+00, -9.681e+00],\n       [ 3.149e+03,  3.801e+00, -9.682e+00],\n       [ 3.149e+03,  3.813e+00, -9.682e+00],\n       [ 3.149e+03,  3.825e+00, -9.683e+00],\n       [ 3.149e+03,  3.836e+00, -9.684e+00],\n       [ 3.149e+03,  3.848e+00, -9.684e+00],\n       [ 3.149e+03,  3.860e+00, -9.685e+00]]), array([[ 3.150e+03,  2.701e+00, -9.680e+00],\n       [ 3.150e+03,  2.713e+00, -9.680e+00],\n       [ 3.150e+03,  2.724e+00, -9.680e+00],\n       [ 3.150e+03, 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3.150e+03,  2.993e+00, -9.680e+00],\n       [ 3.150e+03,  3.005e+00, -9.680e+00],\n       [ 3.150e+03,  3.017e+00, -9.680e+00],\n       [ 3.150e+03,  3.029e+00, -9.680e+00],\n       [ 3.150e+03,  3.040e+00, -9.680e+00],\n       [ 3.150e+03,  3.052e+00, -9.680e+00],\n       [ 3.150e+03,  3.064e+00, -9.680e+00],\n       [ 3.150e+03,  3.075e+00, -9.680e+00],\n       [ 3.150e+03,  3.087e+00, -9.680e+00],\n       [ 3.150e+03,  3.099e+00, -9.680e+00],\n       [ 3.150e+03,  3.110e+00, -9.680e+00],\n       [ 3.150e+03,  3.122e+00, -9.680e+00],\n       [ 3.150e+03,  3.134e+00, -9.680e+00],\n       [ 3.150e+03,  3.146e+00, -9.680e+00],\n       [ 3.150e+03,  3.157e+00, -9.680e+00],\n       [ 3.150e+03,  3.169e+00, -9.680e+00],\n       [ 3.150e+03,  3.181e+00, -9.680e+00],\n       [ 3.150e+03,  3.192e+00, -9.680e+00],\n       [ 3.150e+03,  3.204e+00, -9.680e+00],\n       [ 3.150e+03,  3.216e+00, -9.680e+00],\n       [ 3.150e+03,  3.228e+00, -9.680e+00],\n       [ 3.150e+03,  3.239e+00, 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3.497e+00, -9.680e+00],\n       [ 3.150e+03,  3.508e+00, -9.680e+00],\n       [ 3.150e+03,  3.520e+00, -9.679e+00],\n       [ 3.150e+03,  3.532e+00, -9.680e+00],\n       [ 3.150e+03,  3.544e+00, -9.680e+00],\n       [ 3.150e+03,  3.555e+00, -9.680e+00],\n       [ 3.150e+03,  3.567e+00, -9.680e+00],\n       [ 3.150e+03,  3.579e+00, -9.680e+00],\n       [ 3.150e+03,  3.590e+00, -9.680e+00],\n       [ 3.150e+03,  3.602e+00, -9.680e+00],\n       [ 3.150e+03,  3.614e+00, -9.680e+00],\n       [ 3.150e+03,  3.626e+00, -9.680e+00],\n       [ 3.150e+03,  3.637e+00, -9.680e+00],\n       [ 3.150e+03,  3.649e+00, -9.680e+00],\n       [ 3.150e+03,  3.661e+00, -9.680e+00],\n       [ 3.150e+03,  3.672e+00, -9.680e+00],\n       [ 3.150e+03,  3.684e+00, -9.680e+00],\n       [ 3.150e+03,  3.696e+00, -9.680e+00],\n       [ 3.150e+03,  3.707e+00, -9.680e+00],\n       [ 3.150e+03,  3.719e+00, -9.681e+00],\n       [ 3.150e+03,  3.731e+00, -9.680e+00],\n       [ 3.150e+03,  3.743e+00, -9.679e+00],\n       [ 3.150e+03,  3.754e+00, -9.680e+00],\n       [ 3.150e+03,  3.766e+00, -9.680e+00],\n       [ 3.150e+03,  3.778e+00, -9.680e+00],\n       [ 3.150e+03,  3.789e+00, -9.681e+00],\n       [ 3.150e+03,  3.801e+00, -9.682e+00],\n       [ 3.150e+03,  3.813e+00, -9.682e+00],\n       [ 3.150e+03,  3.825e+00, -9.683e+00],\n       [ 3.150e+03,  3.836e+00, -9.683e+00],\n       [ 3.150e+03,  3.848e+00, -9.684e+00],\n       [ 3.150e+03,  3.860e+00, -9.684e+00]]), array([[ 3.151e+03,  2.701e+00, -9.680e+00],\n       [ 3.151e+03,  2.712e+00, -9.680e+00],\n       [ 3.151e+03,  2.724e+00, -9.680e+00],\n       [ 3.151e+03,  2.736e+00, -9.680e+00],\n       [ 3.151e+03,  2.747e+00, -9.680e+00],\n       [ 3.151e+03,  2.759e+00, -9.680e+00],\n       [ 3.151e+03,  2.770e+00, -9.680e+00],\n       [ 3.151e+03,  2.782e+00, -9.680e+00],\n       [ 3.151e+03,  2.794e+00, -9.680e+00],\n       [ 3.151e+03,  2.805e+00, -9.680e+00],\n       [ 3.151e+03,  2.817e+00, -9.680e+00],\n       [ 3.151e+03,  2.828e+00, 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3.151e+03,  3.339e+00, -9.680e+00],\n       [ 3.151e+03,  3.351e+00, -9.680e+00],\n       [ 3.151e+03,  3.362e+00, -9.680e+00],\n       [ 3.151e+03,  3.374e+00, -9.680e+00],\n       [ 3.151e+03,  3.385e+00, -9.680e+00],\n       [ 3.151e+03,  3.397e+00, -9.680e+00],\n       [ 3.151e+03,  3.409e+00, -9.679e+00],\n       [ 3.151e+03,  3.420e+00, -9.680e+00],\n       [ 3.151e+03,  3.432e+00, -9.680e+00],\n       [ 3.151e+03,  3.443e+00, -9.680e+00],\n       [ 3.151e+03,  3.455e+00, -9.680e+00],\n       [ 3.151e+03,  3.467e+00, -9.680e+00],\n       [ 3.151e+03,  3.478e+00, -9.680e+00],\n       [ 3.151e+03,  3.490e+00, -9.680e+00],\n       [ 3.151e+03,  3.501e+00, -9.680e+00],\n       [ 3.151e+03,  3.513e+00, -9.680e+00],\n       [ 3.151e+03,  3.525e+00, -9.680e+00],\n       [ 3.151e+03,  3.536e+00, -9.680e+00],\n       [ 3.151e+03,  3.548e+00, -9.680e+00],\n       [ 3.151e+03,  3.559e+00, -9.680e+00],\n       [ 3.151e+03,  3.571e+00, -9.680e+00],\n       [ 3.151e+03,  3.583e+00, -9.679e+00],\n       [ 3.151e+03,  3.594e+00, -9.680e+00],\n       [ 3.151e+03,  3.606e+00, -9.680e+00],\n       [ 3.151e+03,  3.617e+00, -9.680e+00],\n       [ 3.151e+03,  3.629e+00, -9.680e+00],\n       [ 3.151e+03,  3.641e+00, -9.680e+00],\n       [ 3.151e+03,  3.652e+00, -9.679e+00],\n       [ 3.151e+03,  3.664e+00, -9.680e+00],\n       [ 3.151e+03,  3.675e+00, -9.680e+00],\n       [ 3.151e+03,  3.687e+00, -9.680e+00],\n       [ 3.151e+03,  3.699e+00, -9.680e+00],\n       [ 3.151e+03,  3.710e+00, -9.680e+00],\n       [ 3.151e+03,  3.722e+00, -9.680e+00],\n       [ 3.151e+03,  3.733e+00, -9.680e+00],\n       [ 3.151e+03,  3.745e+00, -9.680e+00],\n       [ 3.151e+03,  3.757e+00, -9.680e+00],\n       [ 3.151e+03,  3.768e+00, -9.680e+00],\n       [ 3.151e+03,  3.780e+00, -9.680e+00],\n       [ 3.151e+03,  3.791e+00, -9.680e+00],\n       [ 3.151e+03,  3.803e+00, -9.681e+00],\n       [ 3.151e+03,  3.815e+00, -9.681e+00],\n       [ 3.151e+03,  3.826e+00, -9.681e+00],\n       [ 3.151e+03,  3.838e+00, -9.681e+00],\n       [ 3.151e+03,  3.849e+00, -9.681e+00]]), array([[ 3.152e+03,  2.701e+00, -9.680e+00],\n       [ 3.152e+03,  2.712e+00, -9.680e+00],\n       [ 3.152e+03,  2.724e+00, -9.680e+00],\n       [ 3.152e+03,  2.736e+00, -9.680e+00],\n       [ 3.152e+03,  2.747e+00, -9.680e+00],\n       [ 3.152e+03,  2.759e+00, -9.680e+00],\n       [ 3.152e+03,  2.770e+00, -9.680e+00],\n       [ 3.152e+03,  2.782e+00, -9.680e+00],\n       [ 3.152e+03,  2.794e+00, -9.680e+00],\n       [ 3.152e+03,  2.805e+00, -9.680e+00],\n       [ 3.152e+03,  2.817e+00, -9.680e+00],\n       [ 3.152e+03,  2.828e+00, -9.679e+00],\n       [ 3.152e+03,  2.840e+00, -9.680e+00],\n       [ 3.152e+03,  2.852e+00, -9.680e+00],\n       [ 3.152e+03,  2.863e+00, -9.680e+00],\n       [ 3.152e+03,  2.875e+00, -9.680e+00],\n       [ 3.152e+03,  2.886e+00, -9.680e+00],\n       [ 3.152e+03,  2.898e+00, -9.680e+00],\n       [ 3.152e+03,  2.910e+00, -9.680e+00],\n       [ 3.152e+03,  2.921e+00, -9.680e+00],\n       [ 3.152e+03,  2.933e+00, -9.680e+00],\n       [ 3.152e+03,  2.944e+00, -9.680e+00],\n       [ 3.152e+03,  2.956e+00, -9.680e+00],\n       [ 3.152e+03,  2.968e+00, -9.680e+00],\n       [ 3.152e+03,  2.979e+00, -9.680e+00],\n       [ 3.152e+03,  2.991e+00, -9.680e+00],\n       [ 3.152e+03,  3.002e+00, -9.680e+00],\n       [ 3.152e+03,  3.014e+00, -9.680e+00],\n       [ 3.152e+03,  3.026e+00, -9.680e+00],\n       [ 3.152e+03,  3.037e+00, -9.680e+00],\n       [ 3.152e+03,  3.049e+00, -9.680e+00],\n       [ 3.152e+03,  3.060e+00, -9.680e+00],\n       [ 3.152e+03,  3.072e+00, -9.680e+00],\n       [ 3.152e+03,  3.084e+00, -9.680e+00],\n       [ 3.152e+03,  3.095e+00, -9.680e+00],\n       [ 3.152e+03,  3.107e+00, -9.680e+00],\n       [ 3.152e+03,  3.118e+00, -9.680e+00],\n       [ 3.152e+03,  3.130e+00, -9.680e+00],\n       [ 3.152e+03,  3.142e+00, -9.681e+00],\n       [ 3.152e+03,  3.153e+00, -9.680e+00],\n       [ 3.152e+03,  3.165e+00, -9.680e+00],\n       [ 3.152e+03,  3.177e+00, 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3.152e+03,  3.687e+00, -9.680e+00],\n       [ 3.152e+03,  3.699e+00, -9.680e+00],\n       [ 3.152e+03,  3.710e+00, -9.680e+00],\n       [ 3.152e+03,  3.722e+00, -9.679e+00],\n       [ 3.152e+03,  3.733e+00, -9.679e+00],\n       [ 3.152e+03,  3.745e+00, -9.679e+00],\n       [ 3.152e+03,  3.757e+00, -9.680e+00],\n       [ 3.152e+03,  3.768e+00, -9.680e+00],\n       [ 3.152e+03,  3.780e+00, -9.681e+00],\n       [ 3.152e+03,  3.791e+00, -9.681e+00],\n       [ 3.152e+03,  3.803e+00, -9.682e+00],\n       [ 3.152e+03,  3.815e+00, -9.682e+00],\n       [ 3.152e+03,  3.826e+00, -9.683e+00],\n       [ 3.152e+03,  3.838e+00, -9.683e+00],\n       [ 3.152e+03,  3.849e+00, -9.684e+00]]), array([[ 3.153e+03,  2.701e+00, -9.680e+00],\n       [ 3.153e+03,  2.713e+00, -9.680e+00],\n       [ 3.153e+03,  2.724e+00, -9.679e+00],\n       [ 3.153e+03,  2.736e+00, -9.679e+00],\n       [ 3.153e+03,  2.748e+00, -9.680e+00],\n       [ 3.153e+03,  2.759e+00, -9.680e+00],\n       [ 3.153e+03,  2.771e+00, 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3.154e+03,  3.637e+00, -9.680e+00],\n       [ 3.154e+03,  3.649e+00, -9.680e+00],\n       [ 3.154e+03,  3.661e+00, -9.679e+00],\n       [ 3.154e+03,  3.672e+00, -9.679e+00],\n       [ 3.154e+03,  3.684e+00, -9.680e+00],\n       [ 3.154e+03,  3.696e+00, -9.680e+00],\n       [ 3.154e+03,  3.707e+00, -9.680e+00],\n       [ 3.154e+03,  3.719e+00, -9.679e+00],\n       [ 3.154e+03,  3.731e+00, -9.680e+00],\n       [ 3.154e+03,  3.743e+00, -9.680e+00],\n       [ 3.154e+03,  3.754e+00, -9.680e+00],\n       [ 3.154e+03,  3.766e+00, -9.680e+00],\n       [ 3.154e+03,  3.778e+00, -9.680e+00],\n       [ 3.154e+03,  3.789e+00, -9.681e+00],\n       [ 3.154e+03,  3.801e+00, -9.682e+00],\n       [ 3.154e+03,  3.813e+00, -9.683e+00],\n       [ 3.154e+03,  3.825e+00, -9.683e+00],\n       [ 3.154e+03,  3.836e+00, -9.684e+00],\n       [ 3.154e+03,  3.848e+00, -9.685e+00],\n       [ 3.154e+03,  3.860e+00, -9.685e+00]]), array([[ 3.155e+03,  2.701e+00, -9.680e+00],\n       [ 3.155e+03,  2.713e+00, 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3.155e+03,  3.228e+00, -9.680e+00],\n       [ 3.155e+03,  3.239e+00, -9.680e+00],\n       [ 3.155e+03,  3.251e+00, -9.680e+00],\n       [ 3.155e+03,  3.263e+00, -9.681e+00],\n       [ 3.155e+03,  3.274e+00, -9.680e+00],\n       [ 3.155e+03,  3.286e+00, -9.680e+00],\n       [ 3.155e+03,  3.298e+00, -9.680e+00],\n       [ 3.155e+03,  3.309e+00, -9.680e+00],\n       [ 3.155e+03,  3.321e+00, -9.680e+00],\n       [ 3.155e+03,  3.333e+00, -9.680e+00],\n       [ 3.155e+03,  3.345e+00, -9.680e+00],\n       [ 3.155e+03,  3.356e+00, -9.680e+00],\n       [ 3.155e+03,  3.368e+00, -9.680e+00],\n       [ 3.155e+03,  3.380e+00, -9.680e+00],\n       [ 3.155e+03,  3.391e+00, -9.680e+00],\n       [ 3.155e+03,  3.403e+00, -9.680e+00],\n       [ 3.155e+03,  3.415e+00, -9.680e+00],\n       [ 3.155e+03,  3.427e+00, -9.680e+00],\n       [ 3.155e+03,  3.438e+00, -9.680e+00],\n       [ 3.155e+03,  3.450e+00, -9.679e+00],\n       [ 3.155e+03,  3.462e+00, -9.680e+00],\n       [ 3.155e+03,  3.473e+00, -9.680e+00],\n       [ 3.155e+03,  3.485e+00, -9.680e+00],\n       [ 3.155e+03,  3.497e+00, -9.680e+00],\n       [ 3.155e+03,  3.508e+00, -9.680e+00],\n       [ 3.155e+03,  3.520e+00, -9.680e+00],\n       [ 3.155e+03,  3.532e+00, -9.680e+00],\n       [ 3.155e+03,  3.544e+00, -9.680e+00],\n       [ 3.155e+03,  3.555e+00, -9.680e+00],\n       [ 3.155e+03,  3.567e+00, -9.680e+00],\n       [ 3.155e+03,  3.579e+00, -9.680e+00],\n       [ 3.155e+03,  3.590e+00, -9.680e+00],\n       [ 3.155e+03,  3.602e+00, -9.680e+00],\n       [ 3.155e+03,  3.614e+00, -9.680e+00],\n       [ 3.155e+03,  3.626e+00, -9.680e+00],\n       [ 3.155e+03,  3.637e+00, -9.680e+00],\n       [ 3.155e+03,  3.649e+00, -9.680e+00],\n       [ 3.155e+03,  3.661e+00, -9.680e+00],\n       [ 3.155e+03,  3.672e+00, -9.680e+00],\n       [ 3.155e+03,  3.684e+00, -9.680e+00],\n       [ 3.155e+03,  3.696e+00, -9.680e+00],\n       [ 3.155e+03,  3.707e+00, -9.680e+00],\n       [ 3.155e+03,  3.719e+00, -9.680e+00],\n       [ 3.155e+03,  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3.156e+03,  3.579e+00, -9.679e+00],\n       [ 3.156e+03,  3.590e+00, -9.680e+00],\n       [ 3.156e+03,  3.602e+00, -9.680e+00],\n       [ 3.156e+03,  3.614e+00, -9.681e+00],\n       [ 3.156e+03,  3.626e+00, -9.680e+00],\n       [ 3.156e+03,  3.637e+00, -9.680e+00],\n       [ 3.156e+03,  3.649e+00, -9.679e+00],\n       [ 3.156e+03,  3.661e+00, -9.680e+00],\n       [ 3.156e+03,  3.672e+00, -9.680e+00],\n       [ 3.156e+03,  3.684e+00, -9.680e+00],\n       [ 3.156e+03,  3.696e+00, -9.680e+00],\n       [ 3.156e+03,  3.707e+00, -9.679e+00],\n       [ 3.156e+03,  3.719e+00, -9.680e+00],\n       [ 3.156e+03,  3.731e+00, -9.680e+00],\n       [ 3.156e+03,  3.743e+00, -9.680e+00],\n       [ 3.156e+03,  3.754e+00, -9.680e+00],\n       [ 3.156e+03,  3.766e+00, -9.680e+00],\n       [ 3.156e+03,  3.778e+00, -9.680e+00],\n       [ 3.156e+03,  3.789e+00, -9.681e+00],\n       [ 3.156e+03,  3.801e+00, -9.682e+00],\n       [ 3.156e+03,  3.813e+00, -9.682e+00],\n       [ 3.156e+03,  3.825e+00, -9.683e+00],\n       [ 3.156e+03,  3.836e+00, -9.684e+00],\n       [ 3.156e+03,  3.848e+00, -9.685e+00],\n       [ 3.156e+03,  3.860e+00, -9.685e+00]]), array([[ 3.157e+03,  2.701e+00, -9.680e+00],\n       [ 3.157e+03,  2.713e+00, -9.679e+00],\n       [ 3.157e+03,  2.724e+00, -9.680e+00],\n       [ 3.157e+03,  2.736e+00, -9.680e+00],\n       [ 3.157e+03,  2.748e+00, -9.680e+00],\n       [ 3.157e+03,  2.759e+00, -9.680e+00],\n       [ 3.157e+03,  2.771e+00, -9.680e+00],\n       [ 3.157e+03,  2.783e+00, -9.680e+00],\n       [ 3.157e+03,  2.794e+00, -9.680e+00],\n       [ 3.157e+03,  2.806e+00, -9.680e+00],\n       [ 3.157e+03,  2.818e+00, -9.680e+00],\n       [ 3.157e+03,  2.830e+00, -9.680e+00],\n       [ 3.157e+03,  2.841e+00, -9.679e+00],\n       [ 3.157e+03,  2.853e+00, -9.680e+00],\n       [ 3.157e+03,  2.865e+00, -9.680e+00],\n       [ 3.157e+03,  2.876e+00, -9.680e+00],\n       [ 3.157e+03,  2.888e+00, -9.680e+00],\n       [ 3.157e+03,  2.900e+00, -9.680e+00],\n       [ 3.157e+03, 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3.158e+03,  3.506e+00, -9.680e+00],\n       [ 3.158e+03,  3.518e+00, -9.680e+00],\n       [ 3.158e+03,  3.529e+00, -9.680e+00],\n       [ 3.158e+03,  3.541e+00, -9.680e+00],\n       [ 3.158e+03,  3.553e+00, -9.680e+00],\n       [ 3.158e+03,  3.564e+00, -9.680e+00],\n       [ 3.158e+03,  3.576e+00, -9.680e+00],\n       [ 3.158e+03,  3.588e+00, -9.680e+00],\n       [ 3.158e+03,  3.599e+00, -9.679e+00],\n       [ 3.158e+03,  3.611e+00, -9.680e+00],\n       [ 3.158e+03,  3.623e+00, -9.680e+00],\n       [ 3.158e+03,  3.635e+00, -9.680e+00],\n       [ 3.158e+03,  3.646e+00, -9.680e+00],\n       [ 3.158e+03,  3.658e+00, -9.680e+00],\n       [ 3.158e+03,  3.670e+00, -9.680e+00],\n       [ 3.158e+03,  3.681e+00, -9.680e+00],\n       [ 3.158e+03,  3.693e+00, -9.680e+00],\n       [ 3.158e+03,  3.705e+00, -9.680e+00],\n       [ 3.158e+03,  3.716e+00, -9.680e+00],\n       [ 3.158e+03,  3.728e+00, -9.680e+00],\n       [ 3.158e+03,  3.740e+00, -9.680e+00],\n       [ 3.158e+03,  3.751e+00, -9.679e+00],\n       [ 3.158e+03,  3.763e+00, -9.680e+00],\n       [ 3.158e+03,  3.775e+00, -9.680e+00],\n       [ 3.158e+03,  3.786e+00, -9.681e+00],\n       [ 3.158e+03,  3.798e+00, -9.681e+00],\n       [ 3.158e+03,  3.810e+00, -9.682e+00],\n       [ 3.158e+03,  3.821e+00, -9.682e+00],\n       [ 3.158e+03,  3.833e+00, -9.683e+00],\n       [ 3.158e+03,  3.845e+00, -9.683e+00],\n       [ 3.158e+03,  3.856e+00, -9.684e+00]]), array([[ 3.159e+03,  2.701e+00, -9.680e+00],\n       [ 3.159e+03,  2.712e+00, -9.680e+00],\n       [ 3.159e+03,  2.724e+00, -9.680e+00],\n       [ 3.159e+03,  2.736e+00, -9.680e+00],\n       [ 3.159e+03,  2.747e+00, -9.680e+00],\n       [ 3.159e+03,  2.759e+00, -9.680e+00],\n       [ 3.159e+03,  2.771e+00, -9.680e+00],\n       [ 3.159e+03,  2.782e+00, -9.680e+00],\n       [ 3.159e+03,  2.794e+00, -9.680e+00],\n       [ 3.159e+03,  2.806e+00, -9.680e+00],\n       [ 3.159e+03,  2.818e+00, -9.680e+00],\n       [ 3.159e+03,  2.829e+00, -9.680e+00],\n       [ 3.159e+03, 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3.159e+03,  3.856e+00, -9.685e+00]]), array([[ 3.160e+03,  2.701e+00, -9.680e+00],\n       [ 3.160e+03,  2.712e+00, -9.680e+00],\n       [ 3.160e+03,  2.724e+00, -9.680e+00],\n       [ 3.160e+03,  2.736e+00, -9.680e+00],\n       [ 3.160e+03,  2.747e+00, -9.680e+00],\n       [ 3.160e+03,  2.759e+00, -9.680e+00],\n       [ 3.160e+03,  2.771e+00, -9.680e+00],\n       [ 3.160e+03,  2.782e+00, -9.680e+00],\n       [ 3.160e+03,  2.794e+00, -9.680e+00],\n       [ 3.160e+03,  2.806e+00, -9.680e+00],\n       [ 3.160e+03,  2.818e+00, -9.680e+00],\n       [ 3.160e+03,  2.829e+00, -9.680e+00],\n       [ 3.160e+03,  2.841e+00, -9.680e+00],\n       [ 3.160e+03,  2.853e+00, -9.680e+00],\n       [ 3.160e+03,  2.864e+00, -9.680e+00],\n       [ 3.160e+03,  2.876e+00, -9.680e+00],\n       [ 3.160e+03,  2.888e+00, -9.680e+00],\n       [ 3.160e+03,  2.899e+00, -9.680e+00],\n       [ 3.160e+03,  2.911e+00, -9.679e+00],\n       [ 3.160e+03,  2.923e+00, -9.680e+00],\n       [ 3.160e+03,  2.934e+00, 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-9.680e+00],\n       [ 3.162e+03,  3.646e+00, -9.680e+00],\n       [ 3.162e+03,  3.658e+00, -9.680e+00],\n       [ 3.162e+03,  3.670e+00, -9.680e+00],\n       [ 3.162e+03,  3.681e+00, -9.680e+00],\n       [ 3.162e+03,  3.693e+00, -9.680e+00],\n       [ 3.162e+03,  3.705e+00, -9.680e+00],\n       [ 3.162e+03,  3.716e+00, -9.680e+00],\n       [ 3.162e+03,  3.728e+00, -9.680e+00],\n       [ 3.162e+03,  3.740e+00, -9.680e+00],\n       [ 3.162e+03,  3.751e+00, -9.680e+00],\n       [ 3.162e+03,  3.763e+00, -9.680e+00],\n       [ 3.162e+03,  3.775e+00, -9.681e+00],\n       [ 3.162e+03,  3.786e+00, -9.682e+00],\n       [ 3.162e+03,  3.798e+00, -9.683e+00],\n       [ 3.162e+03,  3.810e+00, -9.684e+00],\n       [ 3.162e+03,  3.821e+00, -9.685e+00],\n       [ 3.162e+03,  3.833e+00, -9.686e+00],\n       [ 3.162e+03,  3.845e+00, -9.686e+00],\n       [ 3.162e+03,  3.856e+00, -9.687e+00]]), array([[ 3.163e+03,  2.701e+00, -9.680e+00],\n       [ 3.163e+03,  2.712e+00, -9.680e+00],\n       [ 3.163e+03, 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3.163e+03,  2.981e+00, -9.680e+00],\n       [ 3.163e+03,  2.993e+00, -9.680e+00],\n       [ 3.163e+03,  3.004e+00, -9.680e+00],\n       [ 3.163e+03,  3.016e+00, -9.680e+00],\n       [ 3.163e+03,  3.028e+00, -9.680e+00],\n       [ 3.163e+03,  3.039e+00, -9.680e+00],\n       [ 3.163e+03,  3.051e+00, -9.680e+00],\n       [ 3.163e+03,  3.063e+00, -9.680e+00],\n       [ 3.163e+03,  3.074e+00, -9.680e+00],\n       [ 3.163e+03,  3.086e+00, -9.680e+00],\n       [ 3.163e+03,  3.098e+00, -9.680e+00],\n       [ 3.163e+03,  3.109e+00, -9.680e+00],\n       [ 3.163e+03,  3.121e+00, -9.679e+00],\n       [ 3.163e+03,  3.133e+00, -9.680e+00],\n       [ 3.163e+03,  3.144e+00, -9.680e+00],\n       [ 3.163e+03,  3.156e+00, -9.680e+00],\n       [ 3.163e+03,  3.168e+00, -9.680e+00],\n       [ 3.163e+03,  3.179e+00, -9.680e+00],\n       [ 3.163e+03,  3.191e+00, -9.680e+00],\n       [ 3.163e+03,  3.203e+00, -9.680e+00],\n       [ 3.163e+03,  3.214e+00, -9.680e+00],\n       [ 3.163e+03,  3.226e+00, 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3.163e+03,  3.740e+00, -9.680e+00],\n       [ 3.163e+03,  3.751e+00, -9.679e+00],\n       [ 3.163e+03,  3.763e+00, -9.680e+00],\n       [ 3.163e+03,  3.775e+00, -9.680e+00],\n       [ 3.163e+03,  3.786e+00, -9.681e+00],\n       [ 3.163e+03,  3.798e+00, -9.681e+00],\n       [ 3.163e+03,  3.810e+00, -9.682e+00],\n       [ 3.163e+03,  3.821e+00, -9.683e+00],\n       [ 3.163e+03,  3.833e+00, -9.683e+00],\n       [ 3.163e+03,  3.845e+00, -9.684e+00],\n       [ 3.163e+03,  3.856e+00, -9.684e+00]]), array([[ 3.164e+03,  2.701e+00, -9.680e+00],\n       [ 3.164e+03,  2.712e+00, -9.680e+00],\n       [ 3.164e+03,  2.724e+00, -9.680e+00],\n       [ 3.164e+03,  2.736e+00, -9.680e+00],\n       [ 3.164e+03,  2.747e+00, -9.680e+00],\n       [ 3.164e+03,  2.759e+00, -9.680e+00],\n       [ 3.164e+03,  2.771e+00, -9.680e+00],\n       [ 3.164e+03,  2.782e+00, -9.680e+00],\n       [ 3.164e+03,  2.794e+00, -9.680e+00],\n       [ 3.164e+03,  2.806e+00, -9.680e+00],\n       [ 3.164e+03,  2.818e+00, -9.680e+00],\n       [ 3.164e+03,  2.829e+00, -9.680e+00],\n       [ 3.164e+03,  2.841e+00, -9.680e+00],\n       [ 3.164e+03,  2.853e+00, -9.680e+00],\n       [ 3.164e+03,  2.864e+00, -9.680e+00],\n       [ 3.164e+03,  2.876e+00, -9.680e+00],\n       [ 3.164e+03,  2.888e+00, -9.680e+00],\n       [ 3.164e+03,  2.899e+00, -9.680e+00],\n       [ 3.164e+03,  2.911e+00, -9.680e+00],\n       [ 3.164e+03,  2.923e+00, -9.680e+00],\n       [ 3.164e+03,  2.934e+00, -9.679e+00],\n       [ 3.164e+03,  2.946e+00, -9.680e+00],\n       [ 3.164e+03,  2.958e+00, -9.680e+00],\n       [ 3.164e+03,  2.969e+00, -9.680e+00],\n       [ 3.164e+03,  2.981e+00, -9.680e+00],\n       [ 3.164e+03,  2.993e+00, -9.680e+00],\n       [ 3.164e+03,  3.004e+00, -9.680e+00],\n       [ 3.164e+03,  3.016e+00, -9.680e+00],\n       [ 3.164e+03,  3.028e+00, -9.680e+00],\n       [ 3.164e+03,  3.039e+00, -9.680e+00],\n       [ 3.164e+03,  3.051e+00, -9.680e+00],\n       [ 3.164e+03,  3.063e+00, -9.680e+00],\n       [ 3.164e+03,  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3.164e+03,  3.331e+00, -9.680e+00],\n       [ 3.164e+03,  3.343e+00, -9.680e+00],\n       [ 3.164e+03,  3.354e+00, -9.680e+00],\n       [ 3.164e+03,  3.366e+00, -9.680e+00],\n       [ 3.164e+03,  3.378e+00, -9.680e+00],\n       [ 3.164e+03,  3.389e+00, -9.680e+00],\n       [ 3.164e+03,  3.401e+00, -9.680e+00],\n       [ 3.164e+03,  3.413e+00, -9.680e+00],\n       [ 3.164e+03,  3.424e+00, -9.680e+00],\n       [ 3.164e+03,  3.436e+00, -9.680e+00],\n       [ 3.164e+03,  3.448e+00, -9.680e+00],\n       [ 3.164e+03,  3.459e+00, -9.680e+00],\n       [ 3.164e+03,  3.471e+00, -9.680e+00],\n       [ 3.164e+03,  3.483e+00, -9.680e+00],\n       [ 3.164e+03,  3.494e+00, -9.680e+00],\n       [ 3.164e+03,  3.506e+00, -9.680e+00],\n       [ 3.164e+03,  3.518e+00, -9.680e+00],\n       [ 3.164e+03,  3.529e+00, -9.680e+00],\n       [ 3.164e+03,  3.541e+00, -9.680e+00],\n       [ 3.164e+03,  3.553e+00, -9.679e+00],\n       [ 3.164e+03,  3.564e+00, -9.680e+00],\n       [ 3.164e+03,  3.576e+00, -9.680e+00],\n       [ 3.164e+03,  3.588e+00, -9.680e+00],\n       [ 3.164e+03,  3.599e+00, -9.680e+00],\n       [ 3.164e+03,  3.611e+00, -9.680e+00],\n       [ 3.164e+03,  3.623e+00, -9.680e+00],\n       [ 3.164e+03,  3.635e+00, -9.679e+00],\n       [ 3.164e+03,  3.646e+00, -9.680e+00],\n       [ 3.164e+03,  3.658e+00, -9.680e+00],\n       [ 3.164e+03,  3.670e+00, -9.680e+00],\n       [ 3.164e+03,  3.681e+00, -9.680e+00],\n       [ 3.164e+03,  3.693e+00, -9.680e+00],\n       [ 3.164e+03,  3.705e+00, -9.680e+00],\n       [ 3.164e+03,  3.716e+00, -9.680e+00],\n       [ 3.164e+03,  3.728e+00, -9.680e+00],\n       [ 3.164e+03,  3.740e+00, -9.680e+00],\n       [ 3.164e+03,  3.751e+00, -9.680e+00],\n       [ 3.164e+03,  3.763e+00, -9.680e+00],\n       [ 3.164e+03,  3.775e+00, -9.680e+00],\n       [ 3.164e+03,  3.786e+00, -9.681e+00],\n       [ 3.164e+03,  3.798e+00, -9.681e+00],\n       [ 3.164e+03,  3.810e+00, -9.682e+00],\n       [ 3.164e+03,  3.821e+00, -9.682e+00],\n       [ 3.164e+03,  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3.568e+03,  3.563e+00, -1.452e+01],\n       [ 3.568e+03,  3.573e+00, -1.452e+01],\n       [ 3.568e+03,  3.583e+00, -1.452e+01],\n       [ 3.568e+03,  3.593e+00, -1.452e+01],\n       [ 3.568e+03,  3.603e+00, -1.452e+01],\n       [ 3.568e+03,  3.614e+00, -1.452e+01],\n       [ 3.568e+03,  3.624e+00, -1.452e+01],\n       [ 3.568e+03,  3.634e+00, -1.452e+01],\n       [ 3.568e+03,  3.644e+00, -1.452e+01],\n       [ 3.568e+03,  3.654e+00, -1.452e+01],\n       [ 3.568e+03,  3.664e+00, -1.452e+01],\n       [ 3.568e+03,  3.674e+00, -1.453e+01],\n       [ 3.568e+03,  3.685e+00, -1.453e+01],\n       [ 3.568e+03,  3.695e+00, -1.453e+01],\n       [ 3.568e+03,  3.705e+00, -1.453e+01]]), array([[ 3.569e+03,  2.701e+00, -1.452e+01],\n       [ 3.569e+03,  2.711e+00, -1.452e+01],\n       [ 3.569e+03,  2.721e+00, -1.452e+01],\n       [ 3.569e+03,  2.731e+00, -1.452e+01],\n       [ 3.569e+03,  2.741e+00, -1.452e+01],\n       [ 3.569e+03,  2.751e+00, -1.452e+01],\n       [ 3.569e+03,  2.762e+00, 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3.570e+03,  3.511e+00, -1.452e+01],\n       [ 3.570e+03,  3.521e+00, -1.452e+01],\n       [ 3.570e+03,  3.531e+00, -1.452e+01],\n       [ 3.570e+03,  3.541e+00, -1.452e+01],\n       [ 3.570e+03,  3.551e+00, -1.452e+01],\n       [ 3.570e+03,  3.561e+00, -1.452e+01],\n       [ 3.570e+03,  3.571e+00, -1.452e+01],\n       [ 3.570e+03,  3.582e+00, -1.452e+01],\n       [ 3.570e+03,  3.592e+00, -1.452e+01],\n       [ 3.570e+03,  3.602e+00, -1.452e+01],\n       [ 3.570e+03,  3.612e+00, -1.452e+01],\n       [ 3.570e+03,  3.622e+00, -1.452e+01],\n       [ 3.570e+03,  3.632e+00, -1.452e+01],\n       [ 3.570e+03,  3.642e+00, -1.452e+01],\n       [ 3.570e+03,  3.652e+00, -1.452e+01],\n       [ 3.570e+03,  3.663e+00, -1.452e+01],\n       [ 3.570e+03,  3.673e+00, -1.453e+01],\n       [ 3.570e+03,  3.683e+00, -1.453e+01],\n       [ 3.570e+03,  3.693e+00, -1.453e+01],\n       [ 3.570e+03,  3.703e+00, -1.453e+01]]), array([[ 3.571e+03,  2.701e+00, -1.452e+01],\n       [ 3.571e+03,  2.711e+00, 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3.581e+03,  3.561e+00, -1.452e+01],\n       [ 3.581e+03,  3.571e+00, -1.452e+01],\n       [ 3.581e+03,  3.582e+00, -1.452e+01],\n       [ 3.581e+03,  3.592e+00, -1.452e+01],\n       [ 3.581e+03,  3.602e+00, -1.452e+01],\n       [ 3.581e+03,  3.612e+00, -1.452e+01],\n       [ 3.581e+03,  3.622e+00, -1.452e+01],\n       [ 3.581e+03,  3.632e+00, -1.452e+01],\n       [ 3.581e+03,  3.642e+00, -1.452e+01],\n       [ 3.581e+03,  3.652e+00, -1.452e+01],\n       [ 3.581e+03,  3.663e+00, -1.452e+01],\n       [ 3.581e+03,  3.673e+00, -1.452e+01],\n       [ 3.581e+03,  3.683e+00, -1.452e+01],\n       [ 3.581e+03,  3.693e+00, -1.453e+01],\n       [ 3.581e+03,  3.703e+00, -1.453e+01]]), array([[ 3.582e+03,  2.701e+00, -1.452e+01],\n       [ 3.582e+03,  2.711e+00, -1.452e+01],\n       [ 3.582e+03,  2.721e+00, -1.452e+01],\n       [ 3.582e+03,  2.731e+00, -1.452e+01],\n       [ 3.582e+03,  2.741e+00, -1.452e+01],\n       [ 3.582e+03,  2.751e+00, -1.452e+01],\n       [ 3.582e+03,  2.761e+00, 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3.582e+03,  3.206e+00, -1.452e+01],\n       [ 3.582e+03,  3.216e+00, -1.452e+01],\n       [ 3.582e+03,  3.226e+00, -1.452e+01],\n       [ 3.582e+03,  3.236e+00, -1.452e+01],\n       [ 3.582e+03,  3.247e+00, -1.452e+01],\n       [ 3.582e+03,  3.257e+00, -1.452e+01],\n       [ 3.582e+03,  3.267e+00, -1.452e+01],\n       [ 3.582e+03,  3.277e+00, -1.452e+01],\n       [ 3.582e+03,  3.287e+00, -1.452e+01],\n       [ 3.582e+03,  3.297e+00, -1.452e+01],\n       [ 3.582e+03,  3.307e+00, -1.452e+01],\n       [ 3.582e+03,  3.317e+00, -1.452e+01],\n       [ 3.582e+03,  3.327e+00, -1.452e+01],\n       [ 3.582e+03,  3.338e+00, -1.452e+01],\n       [ 3.582e+03,  3.348e+00, -1.452e+01],\n       [ 3.582e+03,  3.358e+00, -1.452e+01],\n       [ 3.582e+03,  3.368e+00, -1.452e+01],\n       [ 3.582e+03,  3.378e+00, -1.452e+01],\n       [ 3.582e+03,  3.388e+00, -1.452e+01],\n       [ 3.582e+03,  3.398e+00, -1.452e+01],\n       [ 3.582e+03,  3.408e+00, -1.452e+01],\n       [ 3.582e+03,  3.418e+00, 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3.641e+00, -1.452e+01],\n       [ 3.582e+03,  3.651e+00, -1.452e+01],\n       [ 3.582e+03,  3.661e+00, -1.453e+01],\n       [ 3.582e+03,  3.671e+00, -1.453e+01],\n       [ 3.582e+03,  3.681e+00, -1.453e+01],\n       [ 3.582e+03,  3.691e+00, -1.453e+01],\n       [ 3.582e+03,  3.701e+00, -1.453e+01]]), array([[ 3.583e+03,  2.701e+00, -1.452e+01],\n       [ 3.583e+03,  2.711e+00, -1.452e+01],\n       [ 3.583e+03,  2.721e+00, -1.452e+01],\n       [ 3.583e+03,  2.731e+00, -1.452e+01],\n       [ 3.583e+03,  2.741e+00, -1.452e+01],\n       [ 3.583e+03,  2.751e+00, -1.452e+01],\n       [ 3.583e+03,  2.761e+00, -1.452e+01],\n       [ 3.583e+03,  2.772e+00, -1.452e+01],\n       [ 3.583e+03,  2.782e+00, -1.452e+01],\n       [ 3.583e+03,  2.792e+00, -1.452e+01],\n       [ 3.583e+03,  2.802e+00, -1.452e+01],\n       [ 3.583e+03,  2.812e+00, -1.452e+01],\n       [ 3.583e+03,  2.822e+00, -1.452e+01],\n       [ 3.583e+03,  2.832e+00, -1.452e+01],\n       [ 3.583e+03,  2.842e+00, -1.452e+01],\n       [ 3.583e+03,  2.852e+00, -1.452e+01],\n       [ 3.583e+03,  2.863e+00, -1.452e+01],\n       [ 3.583e+03,  2.873e+00, -1.452e+01],\n       [ 3.583e+03,  2.883e+00, -1.452e+01],\n       [ 3.583e+03,  2.893e+00, -1.452e+01],\n       [ 3.583e+03,  2.903e+00, -1.452e+01],\n       [ 3.583e+03,  2.913e+00, -1.452e+01],\n       [ 3.583e+03,  2.923e+00, -1.452e+01],\n       [ 3.583e+03,  2.933e+00, -1.452e+01],\n       [ 3.583e+03,  2.943e+00, -1.452e+01],\n       [ 3.583e+03,  2.953e+00, -1.452e+01],\n       [ 3.583e+03,  2.964e+00, -1.452e+01],\n       [ 3.583e+03,  2.974e+00, -1.452e+01],\n       [ 3.583e+03,  2.984e+00, -1.452e+01],\n       [ 3.583e+03,  2.994e+00, -1.452e+01],\n       [ 3.583e+03,  3.004e+00, -1.452e+01],\n       [ 3.583e+03,  3.014e+00, -1.452e+01],\n       [ 3.583e+03,  3.024e+00, -1.452e+01],\n       [ 3.583e+03,  3.034e+00, -1.452e+01],\n       [ 3.583e+03,  3.044e+00, -1.452e+01],\n       [ 3.583e+03,  3.055e+00, -1.452e+01],\n       [ 3.583e+03,  3.065e+00, 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3.583e+03,  3.509e+00, -1.452e+01],\n       [ 3.583e+03,  3.519e+00, -1.452e+01],\n       [ 3.583e+03,  3.530e+00, -1.452e+01],\n       [ 3.583e+03,  3.540e+00, -1.452e+01],\n       [ 3.583e+03,  3.550e+00, -1.452e+01],\n       [ 3.583e+03,  3.560e+00, -1.452e+01],\n       [ 3.583e+03,  3.570e+00, -1.452e+01],\n       [ 3.583e+03,  3.580e+00, -1.452e+01],\n       [ 3.583e+03,  3.590e+00, -1.452e+01],\n       [ 3.583e+03,  3.600e+00, -1.452e+01],\n       [ 3.583e+03,  3.610e+00, -1.452e+01],\n       [ 3.583e+03,  3.621e+00, -1.452e+01],\n       [ 3.583e+03,  3.631e+00, -1.452e+01],\n       [ 3.583e+03,  3.641e+00, -1.452e+01],\n       [ 3.583e+03,  3.651e+00, -1.452e+01],\n       [ 3.583e+03,  3.661e+00, -1.452e+01],\n       [ 3.583e+03,  3.671e+00, -1.452e+01],\n       [ 3.583e+03,  3.681e+00, -1.453e+01],\n       [ 3.583e+03,  3.691e+00, -1.453e+01],\n       [ 3.583e+03,  3.701e+00, -1.453e+01]]), array([[ 3.584e+03,  2.701e+00, -1.452e+01],\n       [ 3.584e+03,  2.711e+00, 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[802.   ,   3.769,  -0.968],\n       [802.   ,   3.777,  -0.968],\n       [802.   ,   3.785,  -0.968],\n       [802.   ,   3.793,  -0.968],\n       [802.   ,   3.801,  -0.968],\n       [802.   ,   3.81 ,  -0.968],\n       [802.   ,   3.818,  -0.968],\n       [802.   ,   3.826,  -0.968],\n       [802.   ,   3.834,  -0.968],\n       [802.   ,   3.842,  -0.968],\n       [802.   ,   3.85 ,  -0.968],\n       [802.   ,   3.858,  -0.967],\n       [802.   ,   3.866,  -0.968],\n       [802.   ,   3.874,  -0.968],\n       [802.   ,   3.883,  -0.968],\n       [802.   ,   3.891,  -0.968],\n       [802.   ,   3.899,  -0.968],\n       [802.   ,   3.907,  -0.968],\n       [802.   ,   3.915,  -0.968],\n       [802.   ,   3.923,  -0.968],\n       [802.   ,   3.931,  -0.968],\n       [802.   ,   3.939,  -0.968],\n       [802.   ,   3.948,  -0.968],\n       [802.   ,   3.956,  -0.968],\n       [802.   ,   3.964,  -0.968],\n       [802.   ,   3.972,  -0.968],\n       [802.   ,   3.98 ,  -0.968],\n       [802.   ,   3.988,  -0.967],\n       [802.   ,   3.996,  -0.968],\n       [802.   ,   4.004,  -0.972]]), array([[803.   ,   3.201,  -0.968],\n       [803.   ,   3.209,  -0.968],\n       [803.   ,   3.217,  -0.968],\n       [803.   ,   3.225,  -0.968],\n       [803.   ,   3.234,  -0.968],\n       [803.   ,   3.242,  -0.968],\n       [803.   ,   3.25 ,  -0.968],\n       [803.   ,   3.258,  -0.968],\n       [803.   ,   3.266,  -0.968],\n       [803.   ,   3.274,  -0.968],\n       [803.   ,   3.282,  -0.967],\n       [803.   ,   3.29 ,  -0.968],\n       [803.   ,   3.298,  -0.968],\n       [803.   ,   3.307,  -0.968],\n       [803.   ,   3.315,  -0.968],\n       [803.   ,   3.323,  -0.968],\n       [803.   ,   3.331,  -0.968],\n       [803.   ,   3.339,  -0.968],\n       [803.   ,   3.347,  -0.968],\n       [803.   ,   3.355,  -0.968],\n       [803.   ,   3.363,  -0.968],\n       [803.   ,   3.371,  -0.968],\n       [803.   ,   3.38 ,  -0.968],\n       [803.   ,   3.388,  -0.968],\n       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2.791e+03,  3.904e+00, -4.840e+00],\n       [ 2.791e+03,  3.917e+00, -4.840e+00],\n       [ 2.791e+03,  3.930e+00, -4.841e+00],\n       [ 2.791e+03,  3.943e+00, -4.841e+00],\n       [ 2.791e+03,  3.957e+00, -4.842e+00],\n       [ 2.791e+03,  3.970e+00, -4.842e+00],\n       [ 2.791e+03,  3.983e+00, -4.843e+00],\n       [ 2.791e+03,  3.996e+00, -4.843e+00]]), array([[ 2.792e+03,  2.701e+00, -4.840e+00],\n       [ 2.792e+03,  2.714e+00, -4.840e+00],\n       [ 2.792e+03,  2.727e+00, -4.840e+00],\n       [ 2.792e+03,  2.740e+00, -4.840e+00],\n       [ 2.792e+03,  2.753e+00, -4.840e+00],\n       [ 2.792e+03,  2.766e+00, -4.840e+00],\n       [ 2.792e+03,  2.779e+00, -4.840e+00],\n       [ 2.792e+03,  2.792e+00, -4.840e+00],\n       [ 2.792e+03,  2.805e+00, -4.840e+00],\n       [ 2.792e+03,  2.819e+00, -4.840e+00],\n       [ 2.792e+03,  2.832e+00, -4.840e+00],\n       [ 2.792e+03,  2.845e+00, -4.840e+00],\n       [ 2.792e+03,  2.858e+00, -4.840e+00],\n       [ 2.792e+03,  2.871e+00, 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array([[798.   ,   3.201,  -0.968],\n       [798.   ,   3.209,  -0.968],\n       [798.   ,   3.217,  -0.968],\n       [798.   ,   3.226,  -0.968],\n       [798.   ,   3.234,  -0.968],\n       [798.   ,   3.242,  -0.968],\n       [798.   ,   3.25 ,  -0.968],\n       [798.   ,   3.258,  -0.968],\n       [798.   ,   3.266,  -0.968],\n       [798.   ,   3.275,  -0.968],\n       [798.   ,   3.283,  -0.968],\n       [798.   ,   3.291,  -0.968],\n       [798.   ,   3.299,  -0.968],\n       [798.   ,   3.307,  -0.968],\n       [798.   ,   3.315,  -0.968],\n       [798.   ,   3.324,  -0.968],\n       [798.   ,   3.332,  -0.968],\n       [798.   ,   3.34 ,  -0.967],\n       [798.   ,   3.348,  -0.968],\n       [798.   ,   3.356,  -0.968],\n       [798.   ,   3.364,  -0.968],\n       [798.   ,   3.373,  -0.968],\n       [798.   ,   3.381,  -0.968],\n       [798.   ,   3.389,  -0.968],\n       [798.   ,   3.397,  -0.968],\n       [798.   ,   3.405,  -0.968],\n       [798.   ,   3.413,  -0.968],\n  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array([[637.   ,   2.702,  -0.968],\n       [637.   ,   2.715,  -0.968],\n       [637.   ,   2.729,  -0.968],\n       [637.   ,   2.743,  -0.968],\n       [637.   ,   2.757,  -0.968],\n       [637.   ,   2.77 ,  -0.968],\n       [637.   ,   2.784,  -0.968],\n       [637.   ,   2.798,  -0.968],\n       [637.   ,   2.812,  -0.968],\n       [637.   ,   2.826,  -0.968],\n       [637.   ,   2.839,  -0.968],\n       [637.   ,   2.853,  -0.968],\n       [637.   ,   2.867,  -0.968],\n       [637.   ,   2.881,  -0.968],\n       [637.   ,   2.895,  -0.967],\n       [637.   ,   2.908,  -0.968],\n       [637.   ,   2.922,  -0.968],\n       [637.   ,   2.936,  -0.968],\n       [637.   ,   2.95 ,  -0.968],\n       [637.   ,   2.963,  -0.968],\n       [637.   ,   2.977,  -0.968],\n       [637.   ,   2.991,  -0.968],\n       [637.   ,   3.005,  -0.968],\n       [637.   ,   3.019,  -0.968],\n       [637.   ,   3.032,  -0.967],\n       [637.   ,   3.046,  -0.968],\n       [637.   ,   3.06 ,  -0.968],\n  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[854.   ,   3.185,  -0.968],\n       [854.   ,   3.198,  -0.968],\n       [854.   ,   3.21 ,  -0.968],\n       [854.   ,   3.223,  -0.968],\n       [854.   ,   3.236,  -0.968],\n       [854.   ,   3.248,  -0.968],\n       [854.   ,   3.261,  -0.968],\n       [854.   ,   3.274,  -0.968],\n       [854.   ,   3.287,  -0.968],\n       [854.   ,   3.299,  -0.968],\n       [854.   ,   3.312,  -0.968],\n       [854.   ,   3.325,  -0.968],\n       [854.   ,   3.338,  -0.968],\n       [854.   ,   3.35 ,  -0.968],\n       [854.   ,   3.363,  -0.968],\n       [854.   ,   3.376,  -0.968],\n       [854.   ,   3.389,  -0.968],\n       [854.   ,   3.401,  -0.968],\n       [854.   ,   3.414,  -0.968],\n       [854.   ,   3.427,  -0.968],\n       [854.   ,   3.44 ,  -0.968],\n       [854.   ,   3.452,  -0.967],\n       [854.   ,   3.465,  -0.968],\n       [854.   ,   3.478,  -0.968],\n       [854.   ,   3.49 ,  -0.968],\n       [854.   ,   3.503,  -0.968],\n       [854.   ,   3.516,  -0.968],\n       [854.   ,   3.529,  -0.968],\n       [854.   ,   3.541,  -0.968],\n       [854.   ,   3.554,  -0.968],\n       [854.   ,   3.567,  -0.968],\n       [854.   ,   3.58 ,  -0.968],\n       [854.   ,   3.592,  -0.968],\n       [854.   ,   3.605,  -0.968],\n       [854.   ,   3.618,  -0.968],\n       [854.   ,   3.631,  -0.968],\n       [854.   ,   3.643,  -0.968],\n       [854.   ,   3.656,  -0.968],\n       [854.   ,   3.669,  -0.968],\n       [854.   ,   3.682,  -0.968],\n       [854.   ,   3.694,  -0.968],\n       [854.   ,   3.707,  -0.968],\n       [854.   ,   3.72 ,  -0.968],\n       [854.   ,   3.732,  -0.968],\n       [854.   ,   3.745,  -0.968],\n       [854.   ,   3.758,  -0.968],\n       [854.   ,   3.771,  -0.968],\n       [854.   ,   3.783,  -0.968],\n       [854.   ,   3.796,  -0.968],\n       [854.   ,   3.809,  -0.968],\n       [854.   ,   3.822,  -0.968],\n       [854.   ,   3.834,  -0.968],\n       [854.   ,   3.847,  -0.968],\n       [854.   ,   3.86 ,  -0.968],\n       [854.   ,   3.873,  -0.968],\n       [854.   ,   3.885,  -0.968],\n       [854.   ,   3.898,  -0.968],\n       [854.   ,   3.911,  -0.968],\n       [854.   ,   3.924,  -0.968],\n       [854.   ,   3.936,  -0.968],\n       [854.   ,   3.949,  -0.968],\n       [854.   ,   3.962,  -0.974]]), array([[855.   ,   2.701,  -0.968],\n       [855.   ,   2.714,  -0.968],\n       [855.   ,   2.726,  -0.968],\n       [855.   ,   2.739,  -0.968],\n       [855.   ,   2.752,  -0.968],\n       [855.   ,   2.764,  -0.968],\n       [855.   ,   2.777,  -0.968],\n       [855.   ,   2.79 ,  -0.968],\n       [855.   ,   2.803,  -0.968],\n       [855.   ,   2.815,  -0.968],\n       [855.   ,   2.828,  -0.968],\n       [855.   ,   2.841,  -0.968],\n       [855.   ,   2.853,  -0.968],\n       [855.   ,   2.866,  -0.968],\n       [855.   ,   2.879,  -0.968],\n       [855.   ,   2.892,  -0.968],\n       [855.   ,   2.904,  -0.968],\n       [855.   ,   2.917,  -0.968],\n       [855.   ,   2.93 ,  -0.967],\n       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array([[856.   ,   2.701,  -0.968],\n       [856.   ,   2.714,  -0.968],\n       [856.   ,   2.726,  -0.968],\n       [856.   ,   2.739,  -0.968],\n       [856.   ,   2.752,  -0.968],\n       [856.   ,   2.764,  -0.968],\n       [856.   ,   2.777,  -0.968],\n       [856.   ,   2.79 ,  -0.968],\n       [856.   ,   2.803,  -0.968],\n       [856.   ,   2.815,  -0.968],\n       [856.   ,   2.828,  -0.968],\n       [856.   ,   2.841,  -0.968],\n       [856.   ,   2.853,  -0.968],\n       [856.   ,   2.866,  -0.968],\n       [856.   ,   2.879,  -0.968],\n       [856.   ,   2.892,  -0.968],\n       [856.   ,   2.904,  -0.968],\n       [856.   ,   2.917,  -0.968],\n       [856.   ,   2.93 ,  -0.968],\n       [856.   ,   2.942,  -0.968],\n       [856.   ,   2.955,  -0.968],\n       [856.   ,   2.968,  -0.968],\n       [856.   ,   2.981,  -0.968],\n       [856.   ,   2.993,  -0.968],\n       [856.   ,   3.006,  -0.968],\n       [856.   ,   3.019,  -0.968],\n       [856.   ,   3.032,  -0.967],\n  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4.043e+03,  3.729e+00, -9.680e+00],\n       [ 4.043e+03,  3.732e+00, -9.680e+00],\n       [ 4.043e+03,  3.735e+00, -9.680e+00],\n       [ 4.043e+03,  3.738e+00, -9.680e+00],\n       [ 4.043e+03,  3.741e+00, -9.680e+00],\n       [ 4.043e+03,  3.745e+00, -9.680e+00],\n       [ 4.043e+03,  3.748e+00, -9.680e+00],\n       [ 4.043e+03,  3.751e+00, -9.680e+00],\n       [ 4.043e+03,  3.754e+00, -9.680e+00],\n       [ 4.043e+03,  3.757e+00, -9.680e+00],\n       [ 4.043e+03,  3.760e+00, -9.680e+00],\n       [ 4.043e+03,  3.763e+00, -9.680e+00],\n       [ 4.043e+03,  3.767e+00, -9.680e+00],\n       [ 4.043e+03,  3.770e+00, -9.680e+00],\n       [ 4.043e+03,  3.773e+00, -9.680e+00],\n       [ 4.043e+03,  3.776e+00, -9.680e+00],\n       [ 4.043e+03,  3.779e+00, -9.680e+00],\n       [ 4.043e+03,  3.782e+00, -9.680e+00],\n       [ 4.043e+03,  3.785e+00, -9.680e+00],\n       [ 4.043e+03,  3.788e+00, -9.680e+00],\n       [ 4.043e+03,  3.792e+00, -9.681e+00],\n       [ 4.043e+03,  3.795e+00, 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4.045e+03,  3.510e+00, -9.680e+00],\n       [ 4.045e+03,  3.513e+00, -9.680e+00],\n       [ 4.045e+03,  3.516e+00, -9.680e+00],\n       [ 4.045e+03,  3.519e+00, -9.680e+00],\n       [ 4.045e+03,  3.522e+00, -9.680e+00],\n       [ 4.045e+03,  3.526e+00, -9.680e+00],\n       [ 4.045e+03,  3.529e+00, -9.680e+00],\n       [ 4.045e+03,  3.532e+00, -9.680e+00],\n       [ 4.045e+03,  3.535e+00, -9.680e+00],\n       [ 4.045e+03,  3.538e+00, -9.680e+00],\n       [ 4.045e+03,  3.541e+00, -9.680e+00],\n       [ 4.045e+03,  3.544e+00, -9.680e+00],\n       [ 4.045e+03,  3.548e+00, -9.680e+00],\n       [ 4.045e+03,  3.551e+00, -9.680e+00],\n       [ 4.045e+03,  3.554e+00, -9.680e+00],\n       [ 4.045e+03,  3.557e+00, -9.680e+00],\n       [ 4.045e+03,  3.560e+00, -9.680e+00],\n       [ 4.045e+03,  3.563e+00, -9.680e+00],\n       [ 4.045e+03,  3.566e+00, -9.680e+00],\n       [ 4.045e+03,  3.569e+00, -9.680e+00],\n       [ 4.045e+03,  3.573e+00, -9.680e+00],\n       [ 4.045e+03,  3.576e+00, 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4.048e+03,  3.792e+00, -9.681e+00],\n       [ 4.048e+03,  3.795e+00, -9.682e+00],\n       [ 4.048e+03,  3.798e+00, -9.683e+00],\n       [ 4.048e+03,  3.801e+00, -9.683e+00],\n       [ 4.048e+03,  3.804e+00, -9.684e+00],\n       [ 4.048e+03,  3.807e+00, -9.685e+00],\n       [ 4.048e+03,  3.810e+00, -9.686e+00]]), array([[ 4.049e+03,  3.501e+00, -9.680e+00],\n       [ 4.049e+03,  3.504e+00, -9.680e+00],\n       [ 4.049e+03,  3.507e+00, -9.680e+00],\n       [ 4.049e+03,  3.510e+00, -9.680e+00],\n       [ 4.049e+03,  3.513e+00, -9.680e+00],\n       [ 4.049e+03,  3.516e+00, -9.680e+00],\n       [ 4.049e+03,  3.519e+00, -9.680e+00],\n       [ 4.049e+03,  3.522e+00, -9.680e+00],\n       [ 4.049e+03,  3.526e+00, -9.680e+00],\n       [ 4.049e+03,  3.529e+00, -9.680e+00],\n       [ 4.049e+03,  3.532e+00, -9.680e+00],\n       [ 4.049e+03,  3.535e+00, -9.680e+00],\n       [ 4.049e+03,  3.538e+00, -9.680e+00],\n       [ 4.049e+03,  3.541e+00, -9.680e+00],\n       [ 4.049e+03,  3.544e+00, 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-9.680e+00],\n       [ 4.049e+03,  3.751e+00, -9.680e+00],\n       [ 4.049e+03,  3.754e+00, -9.680e+00],\n       [ 4.049e+03,  3.757e+00, -9.680e+00],\n       [ 4.049e+03,  3.760e+00, -9.679e+00],\n       [ 4.049e+03,  3.763e+00, -9.680e+00],\n       [ 4.049e+03,  3.767e+00, -9.680e+00],\n       [ 4.049e+03,  3.770e+00, -9.680e+00],\n       [ 4.049e+03,  3.773e+00, -9.680e+00],\n       [ 4.049e+03,  3.776e+00, -9.680e+00],\n       [ 4.049e+03,  3.779e+00, -9.680e+00],\n       [ 4.049e+03,  3.782e+00, -9.680e+00],\n       [ 4.049e+03,  3.785e+00, -9.680e+00],\n       [ 4.049e+03,  3.788e+00, -9.680e+00],\n       [ 4.049e+03,  3.792e+00, -9.681e+00],\n       [ 4.049e+03,  3.795e+00, -9.682e+00],\n       [ 4.049e+03,  3.798e+00, -9.683e+00],\n       [ 4.049e+03,  3.801e+00, -9.684e+00],\n       [ 4.049e+03,  3.804e+00, -9.685e+00],\n       [ 4.049e+03,  3.807e+00, -9.686e+00],\n       [ 4.049e+03,  3.810e+00, -9.687e+00]]), array([[ 4.050e+03,  3.501e+00, -9.680e+00],\n       [ 4.050e+03, 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4.050e+03,  3.776e+00, -9.680e+00],\n       [ 4.050e+03,  3.779e+00, -9.680e+00],\n       [ 4.050e+03,  3.782e+00, -9.680e+00],\n       [ 4.050e+03,  3.785e+00, -9.680e+00],\n       [ 4.050e+03,  3.788e+00, -9.680e+00],\n       [ 4.050e+03,  3.792e+00, -9.681e+00],\n       [ 4.050e+03,  3.795e+00, -9.682e+00],\n       [ 4.050e+03,  3.798e+00, -9.683e+00],\n       [ 4.050e+03,  3.801e+00, -9.684e+00],\n       [ 4.050e+03,  3.804e+00, -9.685e+00],\n       [ 4.050e+03,  3.807e+00, -9.686e+00],\n       [ 4.050e+03,  3.810e+00, -9.687e+00]]), array([[ 4.051e+03,  3.501e+00, -9.680e+00],\n       [ 4.051e+03,  3.504e+00, -9.680e+00],\n       [ 4.051e+03,  3.507e+00, -9.680e+00],\n       [ 4.051e+03,  3.510e+00, -9.680e+00],\n       [ 4.051e+03,  3.513e+00, -9.680e+00],\n       [ 4.051e+03,  3.516e+00, -9.680e+00],\n       [ 4.051e+03,  3.519e+00, -9.680e+00],\n       [ 4.051e+03,  3.522e+00, -9.680e+00],\n       [ 4.051e+03,  3.526e+00, -9.680e+00],\n       [ 4.051e+03,  3.529e+00, 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-9.684e+00]]), array([[ 4.055e+03,  3.501e+00, -9.680e+00],\n       [ 4.055e+03,  3.504e+00, -9.680e+00],\n       [ 4.055e+03,  3.507e+00, -9.680e+00],\n       [ 4.055e+03,  3.510e+00, -9.680e+00],\n       [ 4.055e+03,  3.513e+00, -9.680e+00],\n       [ 4.055e+03,  3.516e+00, -9.680e+00],\n       [ 4.055e+03,  3.519e+00, -9.680e+00],\n       [ 4.055e+03,  3.522e+00, -9.680e+00],\n       [ 4.055e+03,  3.526e+00, -9.680e+00],\n       [ 4.055e+03,  3.529e+00, -9.680e+00],\n       [ 4.055e+03,  3.532e+00, -9.680e+00],\n       [ 4.055e+03,  3.535e+00, -9.680e+00],\n       [ 4.055e+03,  3.538e+00, -9.680e+00],\n       [ 4.055e+03,  3.541e+00, -9.680e+00],\n       [ 4.055e+03,  3.544e+00, -9.680e+00],\n       [ 4.055e+03,  3.548e+00, -9.680e+00],\n       [ 4.055e+03,  3.551e+00, -9.680e+00],\n       [ 4.055e+03,  3.554e+00, -9.680e+00],\n       [ 4.055e+03,  3.557e+00, -9.680e+00],\n       [ 4.055e+03,  3.560e+00, -9.680e+00],\n       [ 4.055e+03,  3.563e+00, -9.680e+00],\n       [ 4.055e+03, 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4.056e+03,  3.729e+00, -9.680e+00],\n       [ 4.056e+03,  3.732e+00, -9.680e+00],\n       [ 4.056e+03,  3.735e+00, -9.680e+00],\n       [ 4.056e+03,  3.738e+00, -9.680e+00],\n       [ 4.056e+03,  3.741e+00, -9.680e+00],\n       [ 4.056e+03,  3.745e+00, -9.680e+00],\n       [ 4.056e+03,  3.748e+00, -9.680e+00],\n       [ 4.056e+03,  3.751e+00, -9.680e+00],\n       [ 4.056e+03,  3.754e+00, -9.680e+00],\n       [ 4.056e+03,  3.757e+00, -9.680e+00],\n       [ 4.056e+03,  3.760e+00, -9.680e+00],\n       [ 4.056e+03,  3.763e+00, -9.680e+00],\n       [ 4.056e+03,  3.767e+00, -9.680e+00],\n       [ 4.056e+03,  3.770e+00, -9.680e+00],\n       [ 4.056e+03,  3.773e+00, -9.680e+00],\n       [ 4.056e+03,  3.776e+00, -9.680e+00],\n       [ 4.056e+03,  3.779e+00, -9.680e+00],\n       [ 4.056e+03,  3.782e+00, -9.680e+00],\n       [ 4.056e+03,  3.785e+00, -9.680e+00],\n       [ 4.056e+03,  3.788e+00, -9.680e+00],\n       [ 4.056e+03,  3.792e+00, -9.681e+00],\n       [ 4.056e+03,  3.795e+00, 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array([[280.   ,   2.701,  -0.968],\n       [280.   ,   2.713,  -0.968],\n       [280.   ,   2.725,  -0.968],\n       [280.   ,   2.737,  -0.968],\n       [280.   ,   2.749,  -0.968],\n       [280.   ,   2.761,  -0.968],\n       [280.   ,   2.774,  -0.968],\n       [280.   ,   2.786,  -0.968],\n       [280.   ,   2.798,  -0.968],\n       [280.   ,   2.81 ,  -0.968],\n       [280.   ,   2.822,  -0.968],\n       [280.   ,   2.834,  -0.968],\n       [280.   ,   2.846,  -0.968],\n       [280.   ,   2.858,  -0.968],\n       [280.   ,   2.87 ,  -0.968],\n       [280.   ,   2.883,  -0.967],\n       [280.   ,   2.895,  -0.968],\n       [280.   ,   2.907,  -0.967],\n       [280.   ,   2.919,  -0.968],\n       [280.   ,   2.931,  -0.968],\n       [280.   ,   2.943,  -0.968],\n       [280.   ,   2.955,  -0.968],\n       [280.   ,   2.967,  -0.968],\n       [280.   ,   2.98 ,  -0.968],\n       [280.   ,   2.992,  -0.968],\n       [280.   ,   3.004,  -0.968],\n       [280.   ,   3.016,  -0.968],\n  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[281.   ,   3.451,  -0.968],\n       [281.   ,   3.463,  -0.968],\n       [281.   ,   3.475,  -0.968],\n       [281.   ,   3.487,  -0.968],\n       [281.   ,   3.499,  -0.968],\n       [281.   ,   3.512,  -0.968],\n       [281.   ,   3.524,  -0.968],\n       [281.   ,   3.536,  -0.968],\n       [281.   ,   3.548,  -0.967],\n       [281.   ,   3.56 ,  -0.968],\n       [281.   ,   3.572,  -0.968],\n       [281.   ,   3.584,  -0.968],\n       [281.   ,   3.596,  -0.968],\n       [281.   ,   3.608,  -0.968],\n       [281.   ,   3.62 ,  -0.968],\n       [281.   ,   3.633,  -0.968],\n       [281.   ,   3.645,  -0.968],\n       [281.   ,   3.657,  -0.968],\n       [281.   ,   3.669,  -0.968],\n       [281.   ,   3.681,  -0.968],\n       [281.   ,   3.693,  -0.968],\n       [281.   ,   3.705,  -0.968],\n       [281.   ,   3.717,  -0.968],\n       [281.   ,   3.729,  -0.968],\n       [281.   ,   3.741,  -0.968],\n       [281.   ,   3.754,  -0.968],\n       [281.   ,   3.766,  -0.968],\n       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3.904e+00, -9.678e-01],\n       [ 1.444e+03,  3.910e+00, -9.679e-01],\n       [ 1.444e+03,  3.917e+00, -9.676e-01],\n       [ 1.444e+03,  3.923e+00, -9.678e-01],\n       [ 1.444e+03,  3.929e+00, -9.677e-01],\n       [ 1.444e+03,  3.936e+00, -9.678e-01],\n       [ 1.444e+03,  3.942e+00, -9.678e-01],\n       [ 1.444e+03,  3.949e+00, -9.680e-01],\n       [ 1.444e+03,  3.955e+00, -9.680e-01],\n       [ 1.444e+03,  3.961e+00, -9.680e-01],\n       [ 1.444e+03,  3.968e+00, -9.680e-01],\n       [ 1.444e+03,  3.974e+00, -9.681e-01],\n       [ 1.444e+03,  3.981e+00, -9.682e-01],\n       [ 1.444e+03,  3.987e+00, -9.677e-01],\n       [ 1.444e+03,  3.993e+00, -9.676e-01],\n       [ 1.444e+03,  4.000e+00, -9.681e-01],\n       [ 1.444e+03,  4.006e+00, -9.680e-01],\n       [ 1.444e+03,  4.012e+00, -9.683e-01],\n       [ 1.444e+03,  4.019e+00, -9.680e-01],\n       [ 1.444e+03,  4.025e+00, -9.680e-01],\n       [ 1.444e+03,  4.032e+00, -9.708e-01]])), (373, 373, 373, 373, 373, 373, 373, 372, 372, 372, 376, 372, 376, 372, 372, 372, 372, 375, 372, 372)], [(-0.0026013719099999832, -0.0018724677111111216), (-0.0017620536099999917, -0.0015304004222222506), (-0.001424126289999972, -0.0014069825555555779), (0.0017991306800000384, -0.0014288297333333588), (-0.0016351810800000256, -6.513130000001471e-05), (-0.004334669830000015, -0.002291229388888865), (-0.0019785076600000286, -0.0016654060333333041), (-0.001548338799999982, -0.0013597511555555701), (-0.0013999247300000128, -0.0011620520111111057), (-0.001186697499999978, -0.0011605502666666527), (-0.0010848343700000207, -0.0005926716444444066), (-0.0028399203999999846, -0.001900488355555563), (-0.0015741469499999995, -0.0013144363777777774), (-0.0011915483499999712, -0.0011497830555555508), (-0.0010030825099999862, -0.0011635619444444838), (-0.0012418565800000002, -0.0009335194777777803), (-0.0023226496599999978, -0.0016339793000000017), (-0.0014496779699999963, -0.0012862755666666675), (-0.00107836818, -0.001043776855555567), (-0.0009431111900000122, -0.0007919153999999848), (-0.0008240154700000169, -0.0008217868444444498), (-0.004586648100000002, -0.0023434890666666794), (-0.0018918890700000191, -0.001447645022222203), (-0.0013367374900000062, -0.001063481277777741), (-0.0009388518899999809, -0.0010132922999999867), (-0.0008901376500000336, -0.0007979138999999592), (-0.0008076214400000392, -0.0007581413222221833), (-0.0029896644899999993, -0.0020058915333333654), (-0.0016754779300000243, -0.0013451638777777714), (-0.0012148929899999938, -0.0010332999222221811), (-0.0010009321400000104, -0.0009122945999999743), (-0.0008297075900000284, -0.0007387442111110865), (-0.002379702510000037, -0.0017233150111110656), (-0.0015604055099999847, -0.0011916152333333071), (-0.001108477530000007, -0.0010138786444444411), (-0.0009160006100000118, -0.000986658533333351), (-0.0009783867399999924, -0.0007796701777778026), (-0.004263441800000001, -0.0024686695555555557), (-0.002001363639999987, -0.0015665097666666622), (-0.0013178886599999994, -0.0012528869888888867), (-0.0011162670800000107, -0.0009810167777777818), (-0.0009926412700000053, -0.0008363876777777909), (-0.0008656981600000168, -0.0008206049111110718), (-0.0030337443100000084, -0.0020468704222222417), (-0.001833079080000033, 0.008896329433333369), (-0.0031482864100000007, -0.0025564482777777403), (-0.00237720162999997, -0.0019216461888889036), (-0.0017427032000000065, -0.0014927356444444466), (-0.0022277496199999635, -0.0019903650555555727), (-0.0017332688700000265, -0.001435110366666671), (-0.0013257141900000046, -0.001176370266666677), (-0.0011109241199999786, -0.007172687344444453), (0.0032507059800000347, -0.006916094377777811), (-0.004231209409999969, -0.00912571773333336), (-0.0032437258699999916, -0.0023404672111111166), (-0.0025930614700000023, -0.00821970710000001), (-0.0021645457900000054, 0.003615470599999979), (-0.00272856184000001, -0.0033606844888888826), (0.001379213970000004, -0.01014861255555556), (-0.008138426539999988, -0.006979734966666657), (-0.011645344470000008, -0.005730157477777769), (-0.0055424217899999965, 0.0005081429444444563), (0.0005836785100000075, -0.009386548111111108), (-0.0033507091599999984, -0.002925695000000012), (-0.004389866669999987, -0.0038974429777777824), (-0.003178358190000008, -0.002880612922222229), (-0.0029517549799999987, -0.0027064522333333477), (-0.00267888730000001, -0.0023506468777777633), (-0.0026218406799999984, -0.0020310225777777882), (-0.004327482259999993, -0.0032318800555555497), (0.0010237755200000142, -0.007384190655555573)]] with type list",
+      "\nDuring handling of the above exception, another exception occurred:\n",
+      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
+      "Input \u001b[0;32mIn [27]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mtf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdata\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mDataset\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_tensor_slices\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX_train\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/tensorflow/python/data/ops/dataset_ops.py:809\u001b[0m, in \u001b[0;36mDatasetV2.from_tensor_slices\u001b[0;34m(tensors, name)\u001b[0m\n\u001b[1;32m    731\u001b[0m \u001b[38;5;129m@staticmethod\u001b[39m\n\u001b[1;32m    732\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mfrom_tensor_slices\u001b[39m(tensors, name\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m):\n\u001b[1;32m    733\u001b[0m   \u001b[38;5;124;03m\"\"\"Creates a `Dataset` whose elements are slices of the given tensors.\u001b[39;00m\n\u001b[1;32m    734\u001b[0m \n\u001b[1;32m    735\u001b[0m \u001b[38;5;124;03m  The given tensors are sliced along their first dimension. This operation\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    807\u001b[0m \u001b[38;5;124;03m    Dataset: A `Dataset`.\u001b[39;00m\n\u001b[1;32m    808\u001b[0m \u001b[38;5;124;03m  \"\"\"\u001b[39;00m\n\u001b[0;32m--> 809\u001b[0m   \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mTensorSliceDataset\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtensors\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mname\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mname\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/tensorflow/python/data/ops/dataset_ops.py:4551\u001b[0m, in \u001b[0;36mTensorSliceDataset.__init__\u001b[0;34m(self, element, is_files, name)\u001b[0m\n\u001b[1;32m   4549\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__init__\u001b[39m(\u001b[38;5;28mself\u001b[39m, element, is_files\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m, name\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m):\n\u001b[1;32m   4550\u001b[0m   \u001b[38;5;124;03m\"\"\"See `Dataset.from_tensor_slices()` for details.\"\"\"\u001b[39;00m\n\u001b[0;32m-> 4551\u001b[0m   element \u001b[38;5;241m=\u001b[39m \u001b[43mstructure\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mnormalize_element\u001b[49m\u001b[43m(\u001b[49m\u001b[43melement\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   4552\u001b[0m   batched_spec \u001b[38;5;241m=\u001b[39m structure\u001b[38;5;241m.\u001b[39mtype_spec_from_value(element)\n\u001b[1;32m   4553\u001b[0m   \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_tensors \u001b[38;5;241m=\u001b[39m structure\u001b[38;5;241m.\u001b[39mto_batched_tensor_list(batched_spec, element)\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/tensorflow/python/data/util/structure.py:107\u001b[0m, in \u001b[0;36mnormalize_element\u001b[0;34m(element, element_signature)\u001b[0m\n\u001b[1;32m    102\u001b[0m     spec \u001b[38;5;241m=\u001b[39m type_spec_from_value(t, use_fallback\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n\u001b[1;32m    103\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m:\n\u001b[1;32m    104\u001b[0m   \u001b[38;5;66;03m# TypeError indicates it was not possible to compute a `TypeSpec` for\u001b[39;00m\n\u001b[1;32m    105\u001b[0m   \u001b[38;5;66;03m# the value. As a fallback try converting the value to a tensor.\u001b[39;00m\n\u001b[1;32m    106\u001b[0m   normalized_components\u001b[38;5;241m.\u001b[39mappend(\n\u001b[0;32m--> 107\u001b[0m       \u001b[43mops\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconvert_to_tensor\u001b[49m\u001b[43m(\u001b[49m\u001b[43mt\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mname\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mcomponent_\u001b[39;49m\u001b[38;5;132;43;01m%d\u001b[39;49;00m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m%\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mi\u001b[49m\u001b[43m)\u001b[49m)\n\u001b[1;32m    108\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    109\u001b[0m   \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(spec, sparse_tensor\u001b[38;5;241m.\u001b[39mSparseTensorSpec):\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/tensorflow/python/profiler/trace.py:183\u001b[0m, in \u001b[0;36mtrace_wrapper.<locals>.inner_wrapper.<locals>.wrapped\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    181\u001b[0m   \u001b[38;5;28;01mwith\u001b[39;00m Trace(trace_name, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mtrace_kwargs):\n\u001b[1;32m    182\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m func(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m--> 183\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/tensorflow/python/framework/ops.py:1640\u001b[0m, in \u001b[0;36mconvert_to_tensor\u001b[0;34m(value, dtype, name, as_ref, preferred_dtype, dtype_hint, ctx, accepted_result_types)\u001b[0m\n\u001b[1;32m   1631\u001b[0m       \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\n\u001b[1;32m   1632\u001b[0m           _add_error_prefix(\n\u001b[1;32m   1633\u001b[0m               \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mConversion function \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mconversion_func\u001b[38;5;132;01m!r}\u001b[39;00m\u001b[38;5;124m for type \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   1636\u001b[0m               \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mactual = \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mret\u001b[38;5;241m.\u001b[39mdtype\u001b[38;5;241m.\u001b[39mbase_dtype\u001b[38;5;241m.\u001b[39mname\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m   1637\u001b[0m               name\u001b[38;5;241m=\u001b[39mname))\n\u001b[1;32m   1639\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m ret \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m-> 1640\u001b[0m   ret \u001b[38;5;241m=\u001b[39m \u001b[43mconversion_func\u001b[49m\u001b[43m(\u001b[49m\u001b[43mvalue\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdtype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mname\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mas_ref\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mas_ref\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1642\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m ret \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28mNotImplemented\u001b[39m:\n\u001b[1;32m   1643\u001b[0m   \u001b[38;5;28;01mcontinue\u001b[39;00m\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/tensorflow/python/framework/constant_op.py:343\u001b[0m, in \u001b[0;36m_constant_tensor_conversion_function\u001b[0;34m(v, dtype, name, as_ref)\u001b[0m\n\u001b[1;32m    340\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_constant_tensor_conversion_function\u001b[39m(v, dtype\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, name\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m    341\u001b[0m                                          as_ref\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m):\n\u001b[1;32m    342\u001b[0m   _ \u001b[38;5;241m=\u001b[39m as_ref\n\u001b[0;32m--> 343\u001b[0m   \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mconstant\u001b[49m\u001b[43m(\u001b[49m\u001b[43mv\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdtype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mname\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mname\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/tensorflow/python/framework/constant_op.py:267\u001b[0m, in \u001b[0;36mconstant\u001b[0;34m(value, dtype, shape, name)\u001b[0m\n\u001b[1;32m    170\u001b[0m \u001b[38;5;129m@tf_export\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mconstant\u001b[39m\u001b[38;5;124m\"\u001b[39m, v1\u001b[38;5;241m=\u001b[39m[])\n\u001b[1;32m    171\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mconstant\u001b[39m(value, dtype\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, shape\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, name\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mConst\u001b[39m\u001b[38;5;124m\"\u001b[39m):\n\u001b[1;32m    172\u001b[0m   \u001b[38;5;124;03m\"\"\"Creates a constant tensor from a tensor-like object.\u001b[39;00m\n\u001b[1;32m    173\u001b[0m \n\u001b[1;32m    174\u001b[0m \u001b[38;5;124;03m  Note: All eager `tf.Tensor` values are immutable (in contrast to\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    265\u001b[0m \u001b[38;5;124;03m    ValueError: if called on a symbolic tensor.\u001b[39;00m\n\u001b[1;32m    266\u001b[0m \u001b[38;5;124;03m  \"\"\"\u001b[39;00m\n\u001b[0;32m--> 267\u001b[0m   \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_constant_impl\u001b[49m\u001b[43m(\u001b[49m\u001b[43mvalue\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mshape\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mverify_shape\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m    268\u001b[0m \u001b[43m                        \u001b[49m\u001b[43mallow_broadcast\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/tensorflow/python/framework/constant_op.py:279\u001b[0m, in \u001b[0;36m_constant_impl\u001b[0;34m(value, dtype, shape, name, verify_shape, allow_broadcast)\u001b[0m\n\u001b[1;32m    277\u001b[0m     \u001b[38;5;28;01mwith\u001b[39;00m trace\u001b[38;5;241m.\u001b[39mTrace(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtf.constant\u001b[39m\u001b[38;5;124m\"\u001b[39m):\n\u001b[1;32m    278\u001b[0m       \u001b[38;5;28;01mreturn\u001b[39;00m _constant_eager_impl(ctx, value, dtype, shape, verify_shape)\n\u001b[0;32m--> 279\u001b[0m   \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_constant_eager_impl\u001b[49m\u001b[43m(\u001b[49m\u001b[43mctx\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvalue\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mshape\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mverify_shape\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    281\u001b[0m g \u001b[38;5;241m=\u001b[39m ops\u001b[38;5;241m.\u001b[39mget_default_graph()\n\u001b[1;32m    282\u001b[0m tensor_value \u001b[38;5;241m=\u001b[39m attr_value_pb2\u001b[38;5;241m.\u001b[39mAttrValue()\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/tensorflow/python/framework/constant_op.py:304\u001b[0m, in \u001b[0;36m_constant_eager_impl\u001b[0;34m(ctx, value, dtype, shape, verify_shape)\u001b[0m\n\u001b[1;32m    302\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_constant_eager_impl\u001b[39m(ctx, value, dtype, shape, verify_shape):\n\u001b[1;32m    303\u001b[0m   \u001b[38;5;124;03m\"\"\"Creates a constant on the current device.\"\"\"\u001b[39;00m\n\u001b[0;32m--> 304\u001b[0m   t \u001b[38;5;241m=\u001b[39m \u001b[43mconvert_to_eager_tensor\u001b[49m\u001b[43m(\u001b[49m\u001b[43mvalue\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mctx\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    305\u001b[0m   \u001b[38;5;28;01mif\u001b[39;00m shape \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m    306\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m t\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/tensorflow/python/framework/constant_op.py:102\u001b[0m, in \u001b[0;36mconvert_to_eager_tensor\u001b[0;34m(value, ctx, dtype)\u001b[0m\n\u001b[1;32m    100\u001b[0m     dtype \u001b[38;5;241m=\u001b[39m dtypes\u001b[38;5;241m.\u001b[39mas_dtype(dtype)\u001b[38;5;241m.\u001b[39mas_datatype_enum\n\u001b[1;32m    101\u001b[0m ctx\u001b[38;5;241m.\u001b[39mensure_initialized()\n\u001b[0;32m--> 102\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mops\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mEagerTensor\u001b[49m\u001b[43m(\u001b[49m\u001b[43mvalue\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mctx\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdevice_name\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[43m)\u001b[49m\n",
+      "\u001b[0;31mValueError\u001b[0m: Can't convert non-rectangular Python sequence to Tensor."
+     ]
+    }
+   ],
+   "source": [
+    "tf.data.Dataset.from_tensor_slices(X_train)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "aa920c4e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(X_train[0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "b4409dfc",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[(array([[2180.   ,    2.701,   -4.84 ],\n",
+       "         [2180.   ,    2.71 ,   -4.84 ],\n",
+       "         [2180.   ,    2.718,   -4.84 ],\n",
+       "         [2180.   ,    2.727,   -4.84 ],\n",
+       "         [2180.   ,    2.736,   -4.84 ],\n",
+       "         [2180.   ,    2.745,   -4.84 ],\n",
+       "         [2180.   ,    2.753,   -4.84 ],\n",
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+       "         [2199.   ,    3.558,   -4.841],\n",
+       "         [2199.   ,    3.567,   -4.843]])),\n",
+       " (510,\n",
+       "  510,\n",
+       "  510,\n",
+       "  510,\n",
+       "  510,\n",
+       "  510,\n",
+       "  510,\n",
+       "  510,\n",
+       "  510,\n",
+       "  510,\n",
+       "  510,\n",
+       "  510,\n",
+       "  510,\n",
+       "  510,\n",
+       "  509,\n",
+       "  509,\n",
+       "  510,\n",
+       "  510,\n",
+       "  509,\n",
+       "  510)]"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_data = tf.data.Dataset.from_tensor_slices((shuffled_features, shuffled_labels)).map(lambda x,y: ((x, counts_aa(x)), y))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "922c6030",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "c54ab529",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "ValueError",
+     "evalue": "Failed to find data adapter that can handle input: (<class 'list'> containing values of types {'(<class \\'list\\'> containing values of types {\"<class \\'numpy.ndarray\\'>\"})'}), (<class 'list'> containing values of types {'(<class \\'tuple\\'> containing values of types {\"<class \\'numpy.float64\\'>\"})'})",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
+      "Input \u001b[0;32mIn [12]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfit\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m      2\u001b[0m \u001b[43m    \u001b[49m\u001b[43mX_train\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my_train\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      3\u001b[0m \u001b[38;5;66;43;03m#     validation_data=val_data, \u001b[39;49;00m\n\u001b[1;32m      4\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[43mtf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mkeras\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcallbacks\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mReduceLROnPlateau\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m      5\u001b[0m \u001b[43m            \u001b[49m\u001b[43mmonitor\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mval_loss\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfactor\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m0.9\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpatience\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m5\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmin_lr\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m1e-5\u001b[39;49m\n\u001b[1;32m      6\u001b[0m \u001b[43m        \u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mkeras\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcallbacks\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mEarlyStopping\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmonitor\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mval_loss\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmode\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mmin\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrestore_best_weights\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpatience\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m10\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      7\u001b[0m \u001b[38;5;66;43;03m# #         tf.keras.callbacks.LambdaCallback(\u001b[39;49;00m\n\u001b[1;32m      8\u001b[0m \u001b[38;5;66;43;03m# #         on_epoch_begin=lambda epochs,logs: print('lr =',lr_decayed_fn(opt.iterations).numpy())\u001b[39;49;00m\n\u001b[1;32m      9\u001b[0m \u001b[38;5;66;43;03m# #         ),\u001b[39;49;00m\n\u001b[1;32m     10\u001b[0m \u001b[38;5;66;43;03m#         ,\u001b[39;49;00m\n\u001b[1;32m     11\u001b[0m \u001b[43m    \u001b[49m\u001b[43mepochs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m150\u001b[39;49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/keras/utils/traceback_utils.py:67\u001b[0m, in \u001b[0;36mfilter_traceback.<locals>.error_handler\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m     65\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:  \u001b[38;5;66;03m# pylint: disable=broad-except\u001b[39;00m\n\u001b[1;32m     66\u001b[0m   filtered_tb \u001b[38;5;241m=\u001b[39m _process_traceback_frames(e\u001b[38;5;241m.\u001b[39m__traceback__)\n\u001b[0;32m---> 67\u001b[0m   \u001b[38;5;28;01mraise\u001b[39;00m e\u001b[38;5;241m.\u001b[39mwith_traceback(filtered_tb) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28mNone\u001b[39m\n\u001b[1;32m     68\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[1;32m     69\u001b[0m   \u001b[38;5;28;01mdel\u001b[39;00m filtered_tb\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/keras/engine/data_adapter.py:985\u001b[0m, in \u001b[0;36mselect_data_adapter\u001b[0;34m(x, y)\u001b[0m\n\u001b[1;32m    982\u001b[0m adapter_cls \u001b[38;5;241m=\u001b[39m [\u001b[38;5;28mcls\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m \u001b[38;5;28mcls\u001b[39m \u001b[38;5;129;01min\u001b[39;00m ALL_ADAPTER_CLS \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39mcan_handle(x, y)]\n\u001b[1;32m    983\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m adapter_cls:\n\u001b[1;32m    984\u001b[0m   \u001b[38;5;66;03m# TODO(scottzhu): This should be a less implementation-specific error.\u001b[39;00m\n\u001b[0;32m--> 985\u001b[0m   \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m    986\u001b[0m       \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFailed to find data adapter that can handle \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    987\u001b[0m       \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124minput: \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m, \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mformat(\n\u001b[1;32m    988\u001b[0m           _type_name(x), _type_name(y)))\n\u001b[1;32m    989\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(adapter_cls) \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m1\u001b[39m:\n\u001b[1;32m    990\u001b[0m   \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\n\u001b[1;32m    991\u001b[0m       \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mData adapters should be mutually exclusive for \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    992\u001b[0m       \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhandling inputs. Found multiple adapters \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m to handle \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    993\u001b[0m       \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124minput: \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m, \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mformat(\n\u001b[1;32m    994\u001b[0m           adapter_cls, _type_name(x), _type_name(y)))\n",
+      "\u001b[0;31mValueError\u001b[0m: Failed to find data adapter that can handle input: (<class 'list'> containing values of types {'(<class \\'list\\'> containing values of types {\"<class \\'numpy.ndarray\\'>\"})'}), (<class 'list'> containing values of types {'(<class \\'tuple\\'> containing values of types {\"<class \\'numpy.float64\\'>\"})'})"
+     ]
+    }
+   ],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "41715b72",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3766a86d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 456,
+   "id": "4e4404e4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def check_cell(cell, cycle_threshold=50):\n",
+    "    short_cell = []\n",
+    "    for i, cycle in enumerate(cell):\n",
+    "        if len(cycle) < cycle_threshold:\n",
+    "            short_cell.append(i)\n",
+    "#     print(short_cell)\n",
+    "    if short_cell:\n",
+    "        return short_cell"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 473,
+   "id": "132ea8ec",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Cycles window skipping diagnostic[[5, 6, 7, 8, 9], [10, 11, 12, 13, 14], [15, 16, 17, 18, 19], [20, 21, 22, 23, 24], [25, 26, 27, 28, 29], [35, 36, 37, 38, 39], [40, 41, 42, 43, 44], [45, 46, 47, 48, 49], [50, 51, 52, 53, 54], [55, 56, 57, 58, 59], [60, 61, 62, 63, 64], [65, 66, 67, 68, 69], [70, 71, 72, 73, 74], [75, 76, 77, 78, 79], [80, 81, 82, 83, 84], [85, 86, 87, 88, 89], [90, 91, 92, 93, 94], [95, 96, 97, 98, 99], [100, 101, 102, 103, 104], [105, 106, 107, 108, 109], [110, 111, 112, 113, 114], [115, 116, 117, 118, 119], [120, 121, 122, 123, 124], [125, 126, 127, 128, 129], [135, 136, 137, 138, 139], [140, 141, 142, 143, 144], [145, 146, 147, 148, 149], [150, 151, 152, 153, 154], [155, 156, 157, 158, 159], [160, 161, 162, 163, 164], [165, 166, 167, 168, 169], [170, 171, 172, 173, 174], [175, 176, 177, 178, 179], [180, 181, 182, 183, 184], [185, 186, 187, 188, 189], [190, 191, 192, 193, 194], [195, 196, 197, 198, 199], [200, 201, 202, 203, 204], [205, 206, 207, 208, 209], [210, 211, 212, 213, 214], [215, 216, 217, 218, 219], [220, 221, 222, 223, 224], [225, 226, 227, 228, 229], [235, 236, 237, 238, 239], [240, 241, 242, 243, 244], [245, 246, 247, 248, 249], [250, 251, 252, 253, 254], [255, 256, 257, 258, 259], [260, 261, 262, 263, 264], [265, 266, 267, 268, 269], [270, 271, 272, 273, 274], [275, 276, 277, 278, 279], [280, 281, 282, 283, 284], [285, 286, 287, 288, 289], [290, 291, 292, 293, 294], [295, 296, 297, 298, 299], [300, 301, 302, 303, 304], [305, 306, 307, 308, 309], [310, 311, 312, 313, 314], [315, 316, 317, 318, 319], [320, 321, 322, 323, 324], [325, 326, 327, 328, 329], [335, 336, 337, 338, 339], [340, 341, 342, 343, 344], [345, 346, 347, 348, 349], [350, 351, 352, 353, 354], [355, 356, 357, 358, 359], [360, 361, 362, 363, 364], [365, 366, 367, 368, 369], [370, 371, 372, 373, 374], [375, 376, 377, 378, 379], [380, 381, 382, 383, 384], [385, 386, 387, 388, 389], [390, 391, 392, 393, 394], [395, 396, 397, 398, 399], [400, 401, 402, 403, 404], [405, 406, 407, 408, 409], [410, 411, 412, 413, 414], [415, 416, 417, 418, 419], [420, 421, 422, 423, 424], [425, 426, 427, 428, 429]] \n",
+      "\n",
+      "81\n"
+     ]
+    }
+   ],
+   "source": [
+    "# add this to bye-cycle\n",
+    "\n",
+    "def find_renumbedred_index(cell):\n",
+    "    '''This function finds the renumbered index for the cycles that are followed by a diagnostic cycle'''\n",
+    "    renumbered_index_for_cycle_following_a_diagnostic_cycle = []\n",
+    "    i = 0\n",
+    "    for k,cycle in enumerate(cell):\n",
+    "        actual_cycle_index = np.unique(cycle['cycle_index'])[0]\n",
+    "#         print(i, actual_cycle_index)\n",
+    "        if actual_cycle_index != i:\n",
+    "            renumbered_index_for_cycle_following_a_diagnostic_cycle.append(k-1)\n",
+    "            i = actual_cycle_index\n",
+    "        i += 1\n",
+    "#     print(i, actual_cycle_index)\n",
+    "    return renumbered_index_for_cycle_following_a_diagnostic_cycle\n",
+    "# find_renumbedred_index(cell)\n",
+    "\n",
+    "\n",
+    "def index_convoluter(cell, cycle_window_size=20, overlap_cycle_window=False,\n",
+    "                     overlap_size=5, skip_diagnistic_in_window=False):\n",
+    "    '''This function generates a nested list of indices by convolting the cycles based on cycle_window_size. \n",
+    "        You can choose to have your window of cycles overlap, or skipp the windows that involve diagnostic cycles in between.\n",
+    "    '''\n",
+    "    max_cycle_index = len(cell) #30 #\n",
+    "    if cycle_window_size < overlap_size:\n",
+    "        raise ValueError(f'If overlapping, overlap_size ({overlap_size}) should be samller than cycle_window_size ({cycle_window_size}). Please check inputs.')\n",
+    "    if not cycle_window_size < max_cycle_index:\n",
+    "        raise ValueError(f'cycle_window_size ({cycle_window_size}) should be samller than maximum number of cycles in cell ({max_cycle_index}). Please check inputs.')\n",
+    "    if overlap_cycle_window:\n",
+    "        non_overlap =  cycle_window_size - overlap_size\n",
+    "    else:\n",
+    "        non_overlap = cycle_window_size\n",
+    "    intervals = range(0, max_cycle_index, non_overlap)\n",
+    "    if not skip_diagnistic_in_window:\n",
+    "        index_covolutions = [list(range(x, x + cycle_window_size)) for x in intervals if x <= max_cycle_index-cycle_window_size]\n",
+    "    else:\n",
+    "#         skipped_indices = [5, 6, 7, 20]\n",
+    "        skipped_indices = find_renumbedred_index(cell)\n",
+    "        index_covolutions = [list(range(x, x + cycle_window_size)) for x in intervals if x <= max_cycle_index-cycle_window_size\n",
+    "                             and not (set(list(range(x, x + cycle_window_size))[:-1]) & set(skipped_indices))]\n",
+    "    return index_covolutions\n",
+    "\n",
+    "test = index_convoluter(cell, overlap_cycle_window=True, overlap_size=4,\n",
+    "                        cycle_window_size=5, skip_diagnistic_in_window=False)\n",
+    "test_skipped = index_convoluter(cell, overlap_cycle_window=False, overlap_size=4,\n",
+    "                        cycle_window_size=5, skip_diagnistic_in_window=True)\n",
+    "# print(f'Cycles window not skipping diagnostic{test} \\n')\n",
+    "# print(len(test))\n",
+    "print(f'Cycles window skipping diagnostic{test_skipped} \\n')\n",
+    "print(len(test_skipped))\n",
+    "# print(test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 413,
+   "id": "8bcfb08a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[[0, 1, 2, 3, 4],\n",
+       " [10, 11, 12, 13, 14],\n",
+       " [15, 16, 17, 18, 19],\n",
+       " [25, 26, 27, 28, 29]]"
+      ]
+     },
+     "execution_count": 413,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "test = index_convoluter(cell, overlap_cycle_window=False, overlap_size=4,\n",
+    "                        cycle_window_size=5, skip_diagnistic_in_window=True)\n",
+    "test"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "id": "05b7e927",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "range(1, 2193, 2193)"
+      ]
+     },
+     "execution_count": 41,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "def index_convoluter(cell, cycle_window_size=20, overlap_cycle_window=False, overlap_size=5):\n",
+    "    max_cycle_index = len(cell)\n",
+    "    if overlap_cycle_window:\n",
+    "        non_overlap = cycle_window_size - overlap_size\n",
+    "    else:\n",
+    "        non_overlap = cycle_window_size\n",
+    "    index_covolution = [list(range(x, x + cycle_window_size)) for x in range(1, max_cycle, non_overlap)]\n",
+    "    return index_covolution\n",
+    "\n",
+    "index_convoluter(cell, overlap_cycle_window=True, overlap_size=5,  cycle_window_size=10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "264d8bf9",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19]\n",
+      "[20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39]\n",
+      "[40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59]\n",
+      "[60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79]\n",
+      "[80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99]\n",
+      "[100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119]\n",
+      "[120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139]\n",
+      "[140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159]\n",
+      "[160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179]\n",
+      "[180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199]\n",
+      "[200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219]\n",
+      "[220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239]\n",
+      "[240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259]\n",
+      "[260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279]\n",
+      "[280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299]\n",
+      "[300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319]\n",
+      "[320, 321, 322, 323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338, 339]\n",
+      "[340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359]\n",
+      "[360, 361, 362, 363, 364, 365, 366, 367, 368, 369, 370, 371, 372, 373, 374, 375, 376, 377, 378, 379]\n",
+      "[380, 381, 382, 383, 384, 385, 386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399]\n",
+      "[400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419]\n",
+      "[420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 433, 434, 435, 436, 437, 438, 439]\n",
+      "[440, 441, 442, 443, 444, 445, 446, 447, 448, 449, 450, 451, 452, 453, 454, 455, 456, 457, 458, 459]\n",
+      "[460, 461, 462, 463, 464, 465, 466, 467, 468, 469, 470, 471, 472, 473, 474, 475, 476, 477, 478, 479]\n",
+      "[480, 481, 482, 483, 484, 485, 486, 487, 488, 489, 490, 491, 492, 493, 494, 495, 496, 497, 498, 499]\n",
+      "[500, 501, 502, 503, 504, 505, 506, 507, 508, 509, 510, 511, 512, 513, 514, 515, 516, 517, 518, 519]\n",
+      "[520, 521, 522, 523, 524, 525, 526, 527, 528, 529, 530, 531, 532, 533, 534, 535, 536, 537, 538, 539]\n",
+      "[540, 541, 542, 543, 544, 545, 546, 547, 548, 549, 550, 551, 552, 553, 554, 555, 556, 557, 558, 559]\n",
+      "[560, 561, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 578, 579]\n",
+      "[580, 581, 582, 583, 584, 585, 586, 587, 588, 589, 590, 591, 592, 593, 594, 595, 596, 597, 598, 599]\n",
+      "[600, 601, 602, 603, 604, 605, 606, 607, 608, 609, 610, 611, 612, 613, 614, 615, 616, 617, 618, 619]\n",
+      "[620, 621, 622, 623, 624, 625, 626, 627, 628, 629, 630, 631, 632, 633, 634, 635, 636, 637, 638, 639]\n",
+      "[640, 641, 642, 643, 644, 645, 646, 647, 648, 649, 650, 651, 652, 653, 654, 655, 656, 657, 658, 659]\n",
+      "[660, 661, 662, 663, 664, 665, 666, 667, 668, 669, 670, 671, 672, 673, 674, 675, 676, 677, 678, 679]\n",
+      "[680, 681, 682, 683, 684, 685, 686, 687, 688, 689, 690, 691, 692, 693, 694, 695, 696, 697, 698, 699]\n",
+      "[700, 701, 702, 703, 704, 705, 706, 707, 708, 709, 710, 711, 712, 713, 714, 715, 716, 717, 718, 719]\n",
+      "[720, 721, 722, 723, 724, 725, 726, 727, 728, 729, 730, 731, 732, 733, 734, 735, 736, 737, 738, 739]\n",
+      "[740, 741, 742, 743, 744, 745, 746, 747, 748, 749, 750, 751, 752, 753, 754, 755, 756, 757, 758, 759]\n",
+      "[760, 761, 762, 763, 764, 765, 766, 767, 768, 769, 770, 771, 772, 773, 774, 775, 776, 777, 778, 779]\n",
+      "[780, 781, 782, 783, 784, 785, 786, 787, 788, 789, 790, 791, 792, 793, 794, 795, 796, 797, 798, 799]\n",
+      "[800, 801, 802, 803, 804, 805, 806, 807, 808, 809, 810, 811, 812, 813, 814, 815, 816, 817, 818, 819]\n",
+      "[820, 821, 822, 823, 824, 825, 826, 827, 828, 829, 830, 831, 832, 833, 834, 835, 836, 837, 838, 839]\n",
+      "[840, 841, 842, 843, 844, 845, 846, 847, 848, 849, 850, 851, 852, 853, 854, 855, 856, 857, 858, 859]\n",
+      "[860, 861, 862, 863, 864, 865, 866, 867, 868, 869, 870, 871, 872, 873, 874, 875, 876, 877, 878, 879]\n",
+      "[880, 881, 882, 883, 884, 885, 886, 887, 888, 889, 890, 891, 892, 893, 894, 895, 896, 897, 898, 899]\n",
+      "[900, 901, 902, 903, 904, 905, 906, 907, 908, 909, 910, 911, 912, 913, 914, 915, 916, 917, 918, 919]\n",
+      "[920, 921, 922, 923, 924, 925, 926, 927, 928, 929, 930, 931, 932, 933, 934, 935, 936, 937, 938, 939]\n",
+      "[940, 941, 942, 943, 944, 945, 946, 947, 948, 949, 950, 951, 952, 953, 954, 955, 956, 957, 958, 959]\n",
+      "[960, 961, 962, 963, 964, 965, 966, 967, 968, 969, 970, 971, 972, 973, 974, 975, 976, 977, 978, 979]\n",
+      "[980, 981, 982, 983, 984, 985, 986, 987, 988, 989, 990, 991, 992, 993, 994, 995, 996, 997, 998, 999]\n",
+      "[1000, 1001, 1002, 1003, 1004, 1005, 1006, 1007, 1008, 1009, 1010, 1011, 1012, 1013, 1014, 1015, 1016, 1017, 1018, 1019]\n",
+      "[1020, 1021, 1022, 1023, 1024, 1025, 1026, 1027, 1028, 1029, 1030, 1031, 1032, 1033, 1034, 1035, 1036, 1037, 1038, 1039]\n",
+      "[1040, 1041, 1042, 1043, 1044, 1045, 1046, 1047, 1048, 1049, 1050, 1051, 1052, 1053, 1054, 1055, 1056, 1057, 1058, 1059]\n",
+      "[1060, 1061, 1062, 1063, 1064, 1065, 1066, 1067, 1068, 1069, 1070, 1071, 1072, 1073, 1074, 1075, 1076, 1077, 1078, 1079]\n",
+      "[1080, 1081, 1082, 1083, 1084, 1085, 1086, 1087, 1088, 1089, 1090, 1091, 1092, 1093, 1094, 1095, 1096, 1097, 1098, 1099]\n",
+      "[1100, 1101, 1102, 1103, 1104, 1105, 1106, 1107, 1108, 1109, 1110, 1111, 1112, 1113, 1114, 1115, 1116, 1117, 1118, 1119]\n",
+      "[1120, 1121, 1122, 1123, 1124, 1125, 1126, 1127, 1128, 1129, 1130, 1131, 1132, 1133, 1134, 1135, 1136, 1137, 1138, 1139]\n",
+      "[1140, 1141, 1142, 1143, 1144, 1145, 1146, 1147, 1148, 1149, 1150, 1151, 1152, 1153, 1154, 1155, 1156, 1157, 1158, 1159]\n",
+      "[1160, 1161, 1162, 1163, 1164, 1165, 1166, 1167, 1168, 1169, 1170, 1171, 1172, 1173, 1174, 1175, 1176, 1177, 1178, 1179]\n",
+      "[1180, 1181, 1182, 1183, 1184, 1185, 1186, 1187, 1188, 1189, 1190, 1191, 1192, 1193, 1194, 1195, 1196, 1197, 1198, 1199]\n",
+      "[1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211, 1212, 1213, 1214, 1215, 1216, 1217, 1218, 1219]\n",
+      "[1220, 1221, 1222, 1223, 1224, 1225, 1226, 1227, 1228, 1229, 1230, 1231, 1232, 1233, 1234, 1235, 1236, 1237, 1238, 1239]\n",
+      "[1240, 1241, 1242, 1243, 1244, 1245, 1246, 1247, 1248, 1249, 1250, 1251, 1252, 1253, 1254, 1255, 1256, 1257, 1258, 1259]\n",
+      "[1260, 1261, 1262, 1263, 1264, 1265, 1266, 1267, 1268, 1269, 1270, 1271, 1272, 1273, 1274, 1275, 1276, 1277, 1278, 1279]\n",
+      "[1280, 1281, 1282, 1283, 1284, 1285, 1286, 1287, 1288, 1289, 1290, 1291, 1292, 1293, 1294, 1295, 1296, 1297, 1298, 1299]\n",
+      "[1300, 1301, 1302, 1303, 1304, 1305, 1306, 1307, 1308, 1309, 1310, 1311, 1312, 1313, 1314, 1315, 1316, 1317, 1318, 1319]\n",
+      "[1320, 1321, 1322, 1323, 1324, 1325, 1326, 1327, 1328, 1329, 1330, 1331, 1332, 1333, 1334, 1335, 1336, 1337, 1338, 1339]\n",
+      "[1340, 1341, 1342, 1343, 1344, 1345, 1346, 1347, 1348, 1349, 1350, 1351, 1352, 1353, 1354, 1355, 1356, 1357, 1358, 1359]\n",
+      "[1360, 1361, 1362, 1363, 1364, 1365, 1366, 1367, 1368, 1369, 1370, 1371, 1372, 1373, 1374, 1375, 1376, 1377, 1378, 1379]\n",
+      "[1380, 1381, 1382, 1383, 1384, 1385, 1386, 1387, 1388, 1389, 1390, 1391, 1392, 1393, 1394, 1395, 1396, 1397, 1398, 1399]\n",
+      "[1400, 1401, 1402, 1403, 1404, 1405, 1406, 1407, 1408, 1409, 1410, 1411, 1412, 1413, 1414, 1415, 1416, 1417, 1418, 1419]\n",
+      "[1420, 1421, 1422, 1423, 1424, 1425, 1426, 1427, 1428, 1429, 1430, 1431, 1432, 1433, 1434, 1435, 1436, 1437, 1438, 1439]\n",
+      "[1440, 1441, 1442, 1443, 1444, 1445, 1446, 1447, 1448, 1449, 1450, 1451, 1452, 1453, 1454, 1455, 1456, 1457, 1458, 1459]\n",
+      "[1460, 1461, 1462, 1463, 1464, 1465, 1466, 1467, 1468, 1469, 1470, 1471, 1472, 1473, 1474, 1475, 1476, 1477, 1478, 1479]\n",
+      "[1480, 1481, 1482, 1483, 1484, 1485, 1486, 1487, 1488, 1489, 1490, 1491, 1492, 1493, 1494, 1495, 1496, 1497, 1498, 1499]\n",
+      "[1500, 1501, 1502, 1503, 1504, 1505, 1506, 1507, 1508, 1509, 1510, 1511, 1512, 1513, 1514, 1515, 1516, 1517, 1518, 1519]\n",
+      "[1520, 1521, 1522, 1523, 1524, 1525, 1526, 1527, 1528, 1529, 1530, 1531, 1532, 1533, 1534, 1535, 1536, 1537, 1538, 1539]\n",
+      "[1540, 1541, 1542, 1543, 1544, 1545, 1546, 1547, 1548, 1549, 1550, 1551, 1552, 1553, 1554, 1555, 1556, 1557, 1558, 1559]\n",
+      "[1560, 1561, 1562, 1563, 1564, 1565, 1566, 1567, 1568, 1569, 1570, 1571, 1572, 1573, 1574, 1575, 1576, 1577, 1578, 1579]\n",
+      "[1580, 1581, 1582, 1583, 1584, 1585, 1586, 1587, 1588, 1589, 1590, 1591, 1592, 1593, 1594, 1595, 1596, 1597, 1598, 1599]\n",
+      "[1600, 1601, 1602, 1603, 1604, 1605, 1606, 1607, 1608, 1609, 1610, 1611, 1612, 1613, 1614, 1615, 1616, 1617, 1618, 1619]\n",
+      "[1620, 1621, 1622, 1623, 1624, 1625, 1626, 1627, 1628, 1629, 1630, 1631, 1632, 1633, 1634, 1635, 1636, 1637, 1638, 1639]\n",
+      "[1640, 1641, 1642, 1643, 1644, 1645, 1646, 1647, 1648, 1649, 1650, 1651, 1652, 1653, 1654, 1655, 1656, 1657, 1658, 1659]\n",
+      "[1660, 1661, 1662, 1663, 1664, 1665, 1666, 1667, 1668, 1669, 1670, 1671, 1672, 1673, 1674, 1675, 1676, 1677, 1678, 1679]\n",
+      "[1680, 1681, 1682, 1683, 1684, 1685, 1686, 1687, 1688, 1689, 1690, 1691, 1692, 1693, 1694, 1695, 1696, 1697, 1698, 1699]\n",
+      "[1700, 1701, 1702, 1703, 1704, 1705, 1706, 1707, 1708, 1709, 1710, 1711, 1712, 1713, 1714, 1715, 1716, 1717, 1718, 1719]\n",
+      "[1720, 1721, 1722, 1723, 1724, 1725, 1726, 1727, 1728, 1729, 1730, 1731, 1732, 1733, 1734, 1735, 1736, 1737, 1738, 1739]\n",
+      "[1740, 1741, 1742, 1743, 1744, 1745, 1746, 1747, 1748, 1749, 1750, 1751, 1752, 1753, 1754, 1755, 1756, 1757, 1758, 1759]\n",
+      "[1760, 1761, 1762, 1763, 1764, 1765, 1766, 1767, 1768, 1769, 1770, 1771, 1772, 1773, 1774, 1775, 1776, 1777, 1778, 1779]\n",
+      "[1780, 1781, 1782, 1783, 1784, 1785, 1786, 1787, 1788, 1789, 1790, 1791, 1792, 1793, 1794, 1795, 1796, 1797, 1798, 1799]\n",
+      "[1800, 1801, 1802, 1803, 1804, 1805, 1806, 1807, 1808, 1809, 1810, 1811, 1812, 1813, 1814, 1815, 1816, 1817, 1818, 1819]\n",
+      "[1820, 1821, 1822, 1823, 1824, 1825, 1826, 1827, 1828, 1829, 1830, 1831, 1832, 1833, 1834, 1835, 1836, 1837, 1838, 1839]\n",
+      "[1840, 1841, 1842, 1843, 1844, 1845, 1846, 1847, 1848, 1849, 1850, 1851, 1852, 1853, 1854, 1855, 1856, 1857, 1858, 1859]\n",
+      "[1860, 1861, 1862, 1863, 1864, 1865, 1866, 1867, 1868, 1869, 1870, 1871, 1872, 1873, 1874, 1875, 1876, 1877, 1878, 1879]\n",
+      "[1880, 1881, 1882, 1883, 1884, 1885, 1886, 1887, 1888, 1889, 1890, 1891, 1892, 1893, 1894, 1895, 1896, 1897, 1898, 1899]\n",
+      "[1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919]\n",
+      "[1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939]\n",
+      "[1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959]\n",
+      "[1960, 1961, 1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1979]\n",
+      "[1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999]\n",
+      "[2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019]\n",
+      "[2020, 2021, 2022, 2023, 2024, 2025, 2026, 2027, 2028, 2029, 2030, 2031, 2032, 2033, 2034, 2035, 2036, 2037, 2038, 2039]\n",
+      "[2040, 2041, 2042, 2043, 2044, 2045, 2046, 2047, 2048, 2049, 2050, 2051, 2052, 2053, 2054, 2055, 2056, 2057, 2058, 2059]\n",
+      "[2060, 2061, 2062, 2063, 2064, 2065, 2066, 2067, 2068, 2069, 2070, 2071, 2072, 2073, 2074, 2075, 2076, 2077, 2078, 2079]\n",
+      "[2080, 2081, 2082, 2083, 2084, 2085, 2086, 2087, 2088, 2089, 2090, 2091, 2092, 2093, 2094, 2095, 2096, 2097, 2098, 2099]\n",
+      "[2100, 2101, 2102, 2103, 2104, 2105, 2106, 2107, 2108, 2109, 2110, 2111, 2112, 2113, 2114, 2115, 2116, 2117, 2118, 2119]\n",
+      "[2120, 2121, 2122, 2123, 2124, 2125, 2126, 2127, 2128, 2129, 2130, 2131, 2132, 2133, 2134, 2135, 2136, 2137, 2138, 2139]\n",
+      "[2140, 2141, 2142, 2143, 2144, 2145, 2146, 2147, 2148, 2149, 2150, 2151, 2152, 2153, 2154, 2155, 2156, 2157, 2158, 2159]\n",
+      "108\n"
+     ]
+    }
+   ],
+   "source": [
+    "list_indices = []\n",
+    "for j in range(n-1):\n",
+    "    ran = list(range(cycle_numbers*j,cycle_numbers*(j+1)))\n",
+    "    print(ran)\n",
+    "    list_indices.append(ran)\n",
+    "print(len(list_indices))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "60cb271e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x7fb0fb1143d0>"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "i=0\n",
+    "a = np.array(cell[0][features_columns])\n",
+    "interpol_a = bye_cycle.interpol_cycle(cell[0], columns=features_columns, n_points=1000, interpol_kind='cubic')\n",
+    "plt.plot(a[:,1], color='C0', label='a')\n",
+    "plt.plot(interpol_a[:,1], color='C2', label='interpol a')\n",
+    "plt.legend()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "04c55cf8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7fb0fb1a3be0>]"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.plot(a[:,1])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 481,
+   "id": "b882767a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "100"
+      ]
+     },
+     "execution_count": 481,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(X_train[0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "672afe79",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 70%|██████▉   | 11278/16165 [16:16<07:03, 11.55it/s]\n"
+     ]
+    },
+    {
+     "ename": "KeyboardInterrupt",
+     "evalue": "",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
+      "Input \u001b[0;32mIn [17]\u001b[0m, in \u001b[0;36m<cell line: 2>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m ragged_list \u001b[38;5;241m=\u001b[39m []\n\u001b[1;32m      2\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m x \u001b[38;5;129;01min\u001b[39;00m tqdm(X_train):\n\u001b[0;32m----> 3\u001b[0m     ragged_list\u001b[38;5;241m.\u001b[39mappend(\u001b[43mtf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mragged\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconstant\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX_train\u001b[49m\u001b[43m[\u001b[49m\u001b[43mi\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m)\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/tensorflow/python/util/traceback_utils.py:150\u001b[0m, in \u001b[0;36mfilter_traceback.<locals>.error_handler\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    148\u001b[0m filtered_tb \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m    149\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 150\u001b[0m   \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    151\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m    152\u001b[0m   filtered_tb \u001b[38;5;241m=\u001b[39m _process_traceback_frames(e\u001b[38;5;241m.\u001b[39m__traceback__)\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py:1082\u001b[0m, in \u001b[0;36madd_dispatch_support.<locals>.decorator.<locals>.op_dispatch_handler\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m   1080\u001b[0m \u001b[38;5;66;03m# Fallback dispatch system (dispatch v1):\u001b[39;00m\n\u001b[1;32m   1081\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 1082\u001b[0m   \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mdispatch_target\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1083\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m (\u001b[38;5;167;01mTypeError\u001b[39;00m, \u001b[38;5;167;01mValueError\u001b[39;00m):\n\u001b[1;32m   1084\u001b[0m   \u001b[38;5;66;03m# Note: convert_to_eager_tensor currently raises a ValueError, not a\u001b[39;00m\n\u001b[1;32m   1085\u001b[0m   \u001b[38;5;66;03m# TypeError, when given unexpected types.  So we need to catch both.\u001b[39;00m\n\u001b[1;32m   1086\u001b[0m   result \u001b[38;5;241m=\u001b[39m dispatch(op_dispatch_handler, args, kwargs)\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/tensorflow/python/ops/ragged/ragged_factory_ops.py:82\u001b[0m, in \u001b[0;36mconstant\u001b[0;34m(pylist, dtype, ragged_rank, inner_shape, name, row_splits_dtype)\u001b[0m\n\u001b[1;32m     78\u001b[0m   \u001b[38;5;28;01mreturn\u001b[39;00m ragged_tensor\u001b[38;5;241m.\u001b[39mRaggedTensor\u001b[38;5;241m.\u001b[39mfrom_row_splits(values, row_splits,\n\u001b[1;32m     79\u001b[0m                                                     validate\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n\u001b[1;32m     81\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m ops\u001b[38;5;241m.\u001b[39mname_scope(name, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mRaggedConstant\u001b[39m\u001b[38;5;124m\"\u001b[39m):\n\u001b[0;32m---> 82\u001b[0m   \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_constant_value\u001b[49m\u001b[43m(\u001b[49m\u001b[43mragged_factory\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconstant_op\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconstant\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpylist\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     83\u001b[0m \u001b[43m                         \u001b[49m\u001b[43mragged_rank\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minner_shape\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/tensorflow/python/ops/ragged/ragged_factory_ops.py:186\u001b[0m, in \u001b[0;36m_constant_value\u001b[0;34m(ragged_factory, inner_factory, pylist, dtype, ragged_rank, inner_shape)\u001b[0m\n\u001b[1;32m    182\u001b[0m   \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m    183\u001b[0m       \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mInvalid ragged_rank=\u001b[39m\u001b[38;5;132;01m%r\u001b[39;00m\u001b[38;5;124m: must be nonnegative\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;241m%\u001b[39m ragged_rank)\n\u001b[1;32m    185\u001b[0m \u001b[38;5;66;03m# Find the depth of scalar values in `pylist`.\u001b[39;00m\n\u001b[0;32m--> 186\u001b[0m scalar_depth, max_depth \u001b[38;5;241m=\u001b[39m \u001b[43m_find_scalar_and_max_depth\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpylist\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    187\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m scalar_depth \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m    188\u001b[0m   \u001b[38;5;28;01mif\u001b[39;00m max_depth \u001b[38;5;241m>\u001b[39m scalar_depth:\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/tensorflow/python/ops/ragged/ragged_factory_ops.py:266\u001b[0m, in \u001b[0;36m_find_scalar_and_max_depth\u001b[0;34m(pylist)\u001b[0m\n\u001b[1;32m    264\u001b[0m max_depth \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m    265\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m child \u001b[38;5;129;01min\u001b[39;00m pylist:\n\u001b[0;32m--> 266\u001b[0m   child_scalar_depth, child_max_depth \u001b[38;5;241m=\u001b[39m \u001b[43m_find_scalar_and_max_depth\u001b[49m\u001b[43m(\u001b[49m\u001b[43mchild\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    267\u001b[0m   \u001b[38;5;28;01mif\u001b[39;00m child_scalar_depth \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m    268\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m scalar_depth \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m scalar_depth \u001b[38;5;241m!=\u001b[39m child_scalar_depth \u001b[38;5;241m+\u001b[39m \u001b[38;5;241m1\u001b[39m:\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/tensorflow/python/ops/ragged/ragged_factory_ops.py:266\u001b[0m, in \u001b[0;36m_find_scalar_and_max_depth\u001b[0;34m(pylist)\u001b[0m\n\u001b[1;32m    264\u001b[0m max_depth \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m    265\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m child \u001b[38;5;129;01min\u001b[39;00m pylist:\n\u001b[0;32m--> 266\u001b[0m   child_scalar_depth, child_max_depth \u001b[38;5;241m=\u001b[39m \u001b[43m_find_scalar_and_max_depth\u001b[49m\u001b[43m(\u001b[49m\u001b[43mchild\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    267\u001b[0m   \u001b[38;5;28;01mif\u001b[39;00m child_scalar_depth \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m    268\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m scalar_depth \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m scalar_depth \u001b[38;5;241m!=\u001b[39m child_scalar_depth \u001b[38;5;241m+\u001b[39m \u001b[38;5;241m1\u001b[39m:\n",
+      "File \u001b[0;32m~/anaconda3/envs/beep/lib/python3.8/site-packages/tensorflow/python/ops/ragged/ragged_factory_ops.py:271\u001b[0m, in \u001b[0;36m_find_scalar_and_max_depth\u001b[0;34m(pylist)\u001b[0m\n\u001b[1;32m    269\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mall scalar values must have the same nesting depth\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m    270\u001b[0m       scalar_depth \u001b[38;5;241m=\u001b[39m child_scalar_depth \u001b[38;5;241m+\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[0;32m--> 271\u001b[0m     max_depth \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mmax\u001b[39m(max_depth, \u001b[43mchild_max_depth\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m)\n\u001b[1;32m    272\u001b[0m   \u001b[38;5;28;01mreturn\u001b[39;00m (scalar_depth, max_depth)\n\u001b[1;32m    273\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m (\u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m0\u001b[39m)\n",
+      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
+     ]
+    }
+   ],
+   "source": [
+    "ragged_list = []\n",
+    "for x in tqdm(X_train):\n",
+    "    ragged_list.append(tf.ragged.constant(X_train[i]))\n",
+    "#     print(len(X_train[50][i]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "d1a74f34",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "TensorShape([20, None, None])"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ragged_list[0].shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "cef505dc",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ac = tf.ragged.stack([tf.ragged.constant(x) for x in X_train[0:5]], axis=0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "ea23ce54",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "TensorShape([20, None, None])"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tf.ragged.constant(X_train[0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "360d9e8b",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "NameError",
+     "evalue": "name 'dataset' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "Input \u001b[0;32mIn [32]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0m dataset \u001b[38;5;241m=\u001b[39m \u001b[43mdataset\u001b[49m\u001b[38;5;241m.\u001b[39mmap(\u001b[38;5;28;01mlambda\u001b[39;00m x,y: tf\u001b[38;5;241m.\u001b[39mRaggedTensor\u001b[38;5;241m.\u001b[39mfrom_tensor(x_train), y)\n",
+      "\u001b[0;31mNameError\u001b[0m: name 'dataset' is not defined"
+     ]
+    }
+   ],
+   "source": [
+    "dataset = dataset.map(lambda x,y: tf.RaggedTensor.from_tensor(x_train), y)\n",
+    "                                                            "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "49817eba",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dataset = tf.data.Dataset.from_tensor_slices(train_data).map(lambda x,y: tf.RaggedTensor.from_tensor(x), y)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "2c986b75",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "([[array([[ 0.   ,  2.701, -0.691],\n",
+       "          [ 0.   ,  2.703, -0.692],\n",
+       "          [ 0.   ,  2.704, -0.692],\n",
+       "          ...,\n",
+       "          [ 0.   ,  4.174, -0.691],\n",
+       "          [ 0.   ,  4.176, -0.694],\n",
+       "          [ 0.   ,  4.178, -0.698]]),\n",
+       "   array([[ 6.   ,  2.701, -0.968],\n",
+       "          [ 6.   ,  2.703, -0.968],\n",
+       "          [ 6.   ,  2.704, -0.968],\n",
+       "          ...,\n",
+       "          [ 6.   ,  4.137, -0.968],\n",
+       "          [ 6.   ,  4.139, -0.97 ],\n",
+       "          [ 6.   ,  4.14 , -0.972]]),\n",
+       "   array([[ 7.   ,  2.701, -0.968],\n",
+       "          [ 7.   ,  2.703, -0.968],\n",
+       "          [ 7.   ,  2.704, -0.968],\n",
+       "          ...,\n",
+       "          [ 7.   ,  4.137, -0.968],\n",
+       "          [ 7.   ,  4.139, -0.97 ],\n",
+       "          [ 7.   ,  4.14 , -0.972]]),\n",
+       "   array([[ 8.   ,  2.701, -0.968],\n",
+       "          [ 8.   ,  2.703, -0.968],\n",
+       "          [ 8.   ,  2.704, -0.968],\n",
+       "          ...,\n",
+       "          [ 8.   ,  4.139, -0.97 ],\n",
+       "          [ 8.   ,  4.14 , -0.972],\n",
+       "          [ 8.   ,  4.142, -0.973]]),\n",
+       "   array([[ 9.   ,  2.701, -0.968],\n",
+       "          [ 9.   ,  2.703, -0.968],\n",
+       "          [ 9.   ,  2.704, -0.968],\n",
+       "          ...,\n",
+       "          [ 9.   ,  4.139, -0.97 ],\n",
+       "          [ 9.   ,  4.14 , -0.971],\n",
+       "          [ 9.   ,  4.142, -0.972]]),\n",
+       "   array([[10.   ,  2.701, -0.968],\n",
+       "          [10.   ,  2.703, -0.968],\n",
+       "          [10.   ,  2.704, -0.968],\n",
+       "          ...,\n",
+       "          [10.   ,  4.139, -0.969],\n",
+       "          [10.   ,  4.14 , -0.971],\n",
+       "          [10.   ,  4.142, -0.973]]),\n",
+       "   array([[11.   ,  2.701, -0.968],\n",
+       "          [11.   ,  2.703, -0.968],\n",
+       "          [11.   ,  2.704, -0.968],\n",
+       "          ...,\n",
+       "          [11.   ,  4.139, -0.969],\n",
+       "          [11.   ,  4.14 , -0.97 ],\n",
+       "          [11.   ,  4.142, -0.972]]),\n",
+       "   array([[12.   ,  2.701, -0.967],\n",
+       "          [12.   ,  2.703, -0.967],\n",
+       "          [12.   ,  2.704, -0.967],\n",
+       "          ...,\n",
+       "          [12.   ,  4.139, -0.97 ],\n",
+       "          [12.   ,  4.14 , -0.972],\n",
+       "          [12.   ,  4.142, -0.974]]),\n",
+       "   array([[13.   ,  2.701, -0.968],\n",
+       "          [13.   ,  2.703, -0.968],\n",
+       "          [13.   ,  2.704, -0.968],\n",
+       "          ...,\n",
+       "          [13.   ,  4.139, -0.97 ],\n",
+       "          [13.   ,  4.14 , -0.971],\n",
+       "          [13.   ,  4.142, -0.973]]),\n",
+       "   array([[14.   ,  2.701, -0.968],\n",
+       "          [14.   ,  2.703, -0.968],\n",
+       "          [14.   ,  2.704, -0.968],\n",
+       "          ...,\n",
+       "          [14.   ,  4.139, -0.97 ],\n",
+       "          [14.   ,  4.14 , -0.971],\n",
+       "          [14.   ,  4.142, -0.973]]),\n",
+       "   array([[15.   ,  2.701, -0.968],\n",
+       "          [15.   ,  2.703, -0.968],\n",
+       "          [15.   ,  2.704, -0.968],\n",
+       "          ...,\n",
+       "          [15.   ,  4.139, -0.97 ],\n",
+       "          [15.   ,  4.14 , -0.972],\n",
+       "          [15.   ,  4.142, -0.974]]),\n",
+       "   array([[16.   ,  2.701, -0.968],\n",
+       "          [16.   ,  2.703, -0.968],\n",
+       "          [16.   ,  2.704, -0.968],\n",
+       "          ...,\n",
+       "          [16.   ,  4.139, -0.97 ],\n",
+       "          [16.   ,  4.14 , -0.972],\n",
+       "          [16.   ,  4.142, -0.974]]),\n",
+       "   array([[17.   ,  2.701, -0.968],\n",
+       "          [17.   ,  2.703, -0.968],\n",
+       "          [17.   ,  2.704, -0.968],\n",
+       "          ...,\n",
+       "          [17.   ,  4.137, -0.968],\n",
+       "          [17.   ,  4.139, -0.969],\n",
+       "          [17.   ,  4.14 , -0.971]]),\n",
+       "   array([[18.   ,  2.701, -0.968],\n",
+       "          [18.   ,  2.703, -0.968],\n",
+       "          [18.   ,  2.704, -0.968],\n",
+       "          ...,\n",
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+       "          [493.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [493.   ,   4.105,  -0.972],\n",
+       "          [493.   ,   4.106,  -0.973],\n",
+       "          [493.   ,   4.108,  -0.974]]),\n",
+       "   array([[494.   ,   2.701,  -0.968],\n",
+       "          [494.   ,   2.703,  -0.968],\n",
+       "          [494.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [494.   ,   4.105,  -0.972],\n",
+       "          [494.   ,   4.106,  -0.973],\n",
+       "          [494.   ,   4.108,  -0.974]]),\n",
+       "   array([[495.   ,   2.701,  -0.968],\n",
+       "          [495.   ,   2.703,  -0.968],\n",
+       "          [495.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [495.   ,   4.105,  -0.971],\n",
+       "          [495.   ,   4.106,  -0.972],\n",
+       "          [495.   ,   4.108,  -0.973]]),\n",
+       "   array([[496.   ,   2.701,  -0.968],\n",
+       "          [496.   ,   2.703,  -0.968],\n",
+       "          [496.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [496.   ,   4.105,  -0.971],\n",
+       "          [496.   ,   4.106,  -0.972],\n",
+       "          [496.   ,   4.108,  -0.973]]),\n",
+       "   array([[497.   ,   2.701,  -0.968],\n",
+       "          [497.   ,   2.703,  -0.968],\n",
+       "          [497.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [497.   ,   4.105,  -0.971],\n",
+       "          [497.   ,   4.106,  -0.972],\n",
+       "          [497.   ,   4.108,  -0.973]]),\n",
+       "   array([[498.   ,   2.701,  -0.968],\n",
+       "          [498.   ,   2.703,  -0.968],\n",
+       "          [498.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [498.   ,   4.105,  -0.972],\n",
+       "          [498.   ,   4.106,  -0.973],\n",
+       "          [498.   ,   4.108,  -0.974]]),\n",
+       "   array([[499.   ,   2.701,  -0.968],\n",
+       "          [499.   ,   2.703,  -0.968],\n",
+       "          [499.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [499.   ,   4.103,  -0.97 ],\n",
+       "          [499.   ,   4.105,  -0.971],\n",
+       "          [499.   ,   4.106,  -0.972]]),\n",
+       "   array([[500.   ,   2.701,  -0.968],\n",
+       "          [500.   ,   2.703,  -0.968],\n",
+       "          [500.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [500.   ,   4.103,  -0.971],\n",
+       "          [500.   ,   4.105,  -0.972],\n",
+       "          [500.   ,   4.106,  -0.973]]),\n",
+       "   array([[501.   ,   2.701,  -0.968],\n",
+       "          [501.   ,   2.703,  -0.968],\n",
+       "          [501.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [501.   ,   4.103,  -0.971],\n",
+       "          [501.   ,   4.105,  -0.972],\n",
+       "          [501.   ,   4.106,  -0.973]]),\n",
+       "   array([[502.   ,   2.701,  -0.968],\n",
+       "          [502.   ,   2.703,  -0.968],\n",
+       "          [502.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [502.   ,   4.103,  -0.972],\n",
+       "          [502.   ,   4.105,  -0.973],\n",
+       "          [502.   ,   4.106,  -0.974]]),\n",
+       "   array([[503.   ,   2.701,  -0.968],\n",
+       "          [503.   ,   2.703,  -0.968],\n",
+       "          [503.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [503.   ,   4.103,  -0.971],\n",
+       "          [503.   ,   4.105,  -0.971],\n",
+       "          [503.   ,   4.106,  -0.972]]),\n",
+       "   array([[504.   ,   2.701,  -0.968],\n",
+       "          [504.   ,   2.703,  -0.968],\n",
+       "          [504.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [504.   ,   4.103,  -0.971],\n",
+       "          [504.   ,   4.105,  -0.972],\n",
+       "          [504.   ,   4.106,  -0.973]]),\n",
+       "   array([[505.   ,   2.701,  -0.968],\n",
+       "          [505.   ,   2.703,  -0.968],\n",
+       "          [505.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [505.   ,   4.103,  -0.971],\n",
+       "          [505.   ,   4.105,  -0.972],\n",
+       "          [505.   ,   4.106,  -0.973]]),\n",
+       "   array([[506.   ,   2.701,  -0.968],\n",
+       "          [506.   ,   2.703,  -0.968],\n",
+       "          [506.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [506.   ,   4.103,  -0.972],\n",
+       "          [506.   ,   4.105,  -0.973],\n",
+       "          [506.   ,   4.106,  -0.974]]),\n",
+       "   array([[507.   ,   2.701,  -0.968],\n",
+       "          [507.   ,   2.703,  -0.968],\n",
+       "          [507.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [507.   ,   4.103,  -0.972],\n",
+       "          [507.   ,   4.105,  -0.973],\n",
+       "          [507.   ,   4.106,  -0.974]]),\n",
+       "   array([[508.   ,   2.701,  -0.968],\n",
+       "          [508.   ,   2.703,  -0.968],\n",
+       "          [508.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [508.   ,   4.103,  -0.97 ],\n",
+       "          [508.   ,   4.105,  -0.971],\n",
+       "          [508.   ,   4.106,  -0.971]]),\n",
+       "   array([[509.   ,   2.701,  -0.968],\n",
+       "          [509.   ,   2.703,  -0.968],\n",
+       "          [509.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [509.   ,   4.103,  -0.971],\n",
+       "          [509.   ,   4.105,  -0.972],\n",
+       "          [509.   ,   4.106,  -0.973]])],\n",
+       "  [array([[510.   ,   2.701,  -0.968],\n",
+       "          [510.   ,   2.703,  -0.968],\n",
+       "          [510.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [510.   ,   4.101,  -0.971],\n",
+       "          [510.   ,   4.103,  -0.972],\n",
+       "          [510.   ,   4.105,  -0.973]]),\n",
+       "   array([[511.   ,   2.701,  -0.968],\n",
+       "          [511.   ,   2.703,  -0.968],\n",
+       "          [511.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [511.   ,   4.101,  -0.97 ],\n",
+       "          [511.   ,   4.103,  -0.971],\n",
+       "          [511.   ,   4.105,  -0.971]]),\n",
+       "   array([[512.   ,   2.701,  -0.968],\n",
+       "          [512.   ,   2.703,  -0.968],\n",
+       "          [512.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [512.   ,   4.101,  -0.971],\n",
+       "          [512.   ,   4.103,  -0.972],\n",
+       "          [512.   ,   4.105,  -0.973]]),\n",
+       "   array([[513.   ,   2.701,  -0.968],\n",
+       "          [513.   ,   2.703,  -0.968],\n",
+       "          [513.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [513.   ,   4.101,  -0.972],\n",
+       "          [513.   ,   4.103,  -0.974],\n",
+       "          [513.   ,   4.105,  -0.975]]),\n",
+       "   array([[514.   ,   2.701,  -0.968],\n",
+       "          [514.   ,   2.703,  -0.968],\n",
+       "          [514.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [514.   ,   4.101,  -0.972],\n",
+       "          [514.   ,   4.103,  -0.973],\n",
+       "          [514.   ,   4.105,  -0.974]]),\n",
+       "   array([[515.   ,   2.701,  -0.968],\n",
+       "          [515.   ,   2.703,  -0.968],\n",
+       "          [515.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [515.   ,   4.101,  -0.971],\n",
+       "          [515.   ,   4.103,  -0.972],\n",
+       "          [515.   ,   4.105,  -0.973]]),\n",
+       "   array([[516.   ,   2.701,  -0.968],\n",
+       "          [516.   ,   2.703,  -0.968],\n",
+       "          [516.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [516.   ,   4.101,  -0.971],\n",
+       "          [516.   ,   4.103,  -0.971],\n",
+       "          [516.   ,   4.105,  -0.972]]),\n",
+       "   array([[517.   ,   2.701,  -0.968],\n",
+       "          [517.   ,   2.703,  -0.968],\n",
+       "          [517.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [517.   ,   4.1  ,  -0.971],\n",
+       "          [517.   ,   4.101,  -0.972],\n",
+       "          [517.   ,   4.103,  -0.973]]),\n",
+       "   array([[518.   ,   2.701,  -0.968],\n",
+       "          [518.   ,   2.703,  -0.968],\n",
+       "          [518.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [518.   ,   4.1  ,  -0.971],\n",
+       "          [518.   ,   4.101,  -0.971],\n",
+       "          [518.   ,   4.103,  -0.972]]),\n",
+       "   array([[519.   ,   2.701,  -0.968],\n",
+       "          [519.   ,   2.703,  -0.968],\n",
+       "          [519.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [519.   ,   4.1  ,  -0.972],\n",
+       "          [519.   ,   4.101,  -0.973],\n",
+       "          [519.   ,   4.103,  -0.974]]),\n",
+       "   array([[520.   ,   2.701,  -0.968],\n",
+       "          [520.   ,   2.703,  -0.968],\n",
+       "          [520.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [520.   ,   4.1  ,  -0.97 ],\n",
+       "          [520.   ,   4.101,  -0.971],\n",
+       "          [520.   ,   4.103,  -0.971]]),\n",
+       "   array([[521.   ,   2.701,  -0.968],\n",
+       "          [521.   ,   2.703,  -0.968],\n",
+       "          [521.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [521.   ,   4.1  ,  -0.972],\n",
+       "          [521.   ,   4.101,  -0.973],\n",
+       "          [521.   ,   4.103,  -0.974]]),\n",
+       "   array([[522.   ,   2.701,  -0.968],\n",
+       "          [522.   ,   2.703,  -0.968],\n",
+       "          [522.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [522.   ,   4.1  ,  -0.972],\n",
+       "          [522.   ,   4.101,  -0.972],\n",
+       "          [522.   ,   4.103,  -0.973]]),\n",
+       "   array([[523.   ,   2.701,  -0.968],\n",
+       "          [523.   ,   2.703,  -0.968],\n",
+       "          [523.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [523.   ,   4.098,  -0.971],\n",
+       "          [523.   ,   4.1  ,  -0.972],\n",
+       "          [523.   ,   4.101,  -0.973]]),\n",
+       "   array([[524.   ,   2.701,  -0.968],\n",
+       "          [524.   ,   2.703,  -0.968],\n",
+       "          [524.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [524.   ,   4.098,  -0.97 ],\n",
+       "          [524.   ,   4.1  ,  -0.971],\n",
+       "          [524.   ,   4.101,  -0.971]]),\n",
+       "   array([[525.   ,   2.701,  -0.968],\n",
+       "          [525.   ,   2.703,  -0.968],\n",
+       "          [525.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [525.   ,   4.098,  -0.971],\n",
+       "          [525.   ,   4.1  ,  -0.972],\n",
+       "          [525.   ,   4.101,  -0.973]]),\n",
+       "   array([[526.   ,   2.701,  -0.968],\n",
+       "          [526.   ,   2.703,  -0.968],\n",
+       "          [526.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [526.   ,   4.098,  -0.972],\n",
+       "          [526.   ,   4.1  ,  -0.973],\n",
+       "          [526.   ,   4.101,  -0.974]]),\n",
+       "   array([[527.   ,   2.701,  -0.968],\n",
+       "          [527.   ,   2.703,  -0.968],\n",
+       "          [527.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [527.   ,   4.098,  -0.971],\n",
+       "          [527.   ,   4.1  ,  -0.972],\n",
+       "          [527.   ,   4.101,  -0.972]]),\n",
+       "   array([[528.   ,   2.701,  -0.968],\n",
+       "          [528.   ,   2.703,  -0.968],\n",
+       "          [528.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [528.   ,   4.098,  -0.971],\n",
+       "          [528.   ,   4.1  ,  -0.972],\n",
+       "          [528.   ,   4.101,  -0.973]]),\n",
+       "   array([[529.   ,   2.701,  -0.968],\n",
+       "          [529.   ,   2.703,  -0.968],\n",
+       "          [529.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [529.   ,   4.096,  -0.971],\n",
+       "          [529.   ,   4.098,  -0.972],\n",
+       "          [529.   ,   4.1  ,  -0.972]])],\n",
+       "  [array([[530.   ,   2.701,  -0.968],\n",
+       "          [530.   ,   2.703,  -0.968],\n",
+       "          [530.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [530.   ,   4.096,  -0.972],\n",
+       "          [530.   ,   4.098,  -0.973],\n",
+       "          [530.   ,   4.1  ,  -0.973]]),\n",
+       "   array([[531.   ,   2.701,  -0.968],\n",
+       "          [531.   ,   2.703,  -0.968],\n",
+       "          [531.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [531.   ,   4.096,  -0.973],\n",
+       "          [531.   ,   4.098,  -0.973],\n",
+       "          [531.   ,   4.1  ,  -0.974]]),\n",
+       "   array([[532.   ,   2.701,  -0.968],\n",
+       "          [532.   ,   2.703,  -0.968],\n",
+       "          [532.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [532.   ,   4.094,  -0.972],\n",
+       "          [532.   ,   4.096,  -0.973],\n",
+       "          [532.   ,   4.098,  -0.974]]),\n",
+       "   array([[533.   ,   2.701,  -0.968],\n",
+       "          [533.   ,   2.703,  -0.968],\n",
+       "          [533.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [533.   ,   4.094,  -0.972],\n",
+       "          [533.   ,   4.096,  -0.972],\n",
+       "          [533.   ,   4.098,  -0.973]]),\n",
+       "   array([[534.   ,   2.701,  -0.968],\n",
+       "          [534.   ,   2.703,  -0.968],\n",
+       "          [534.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [534.   ,   4.094,  -0.972],\n",
+       "          [534.   ,   4.096,  -0.972],\n",
+       "          [534.   ,   4.098,  -0.973]]),\n",
+       "   array([[535.   ,   2.701,  -0.968],\n",
+       "          [535.   ,   2.703,  -0.968],\n",
+       "          [535.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [535.   ,   4.093,  -0.972],\n",
+       "          [535.   ,   4.094,  -0.973],\n",
+       "          [535.   ,   4.096,  -0.974]]),\n",
+       "   array([[536.   ,   2.701,  -0.968],\n",
+       "          [536.   ,   2.703,  -0.968],\n",
+       "          [536.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [536.   ,   4.093,  -0.972],\n",
+       "          [536.   ,   4.094,  -0.973],\n",
+       "          [536.   ,   4.096,  -0.974]]),\n",
+       "   array([[537.   ,   2.701,  -0.967],\n",
+       "          [537.   ,   2.703,  -0.968],\n",
+       "          [537.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [537.   ,   4.093,  -0.972],\n",
+       "          [537.   ,   4.094,  -0.973],\n",
+       "          [537.   ,   4.096,  -0.973]]),\n",
+       "   array([[538.   ,   2.701,  -0.968],\n",
+       "          [538.   ,   2.703,  -0.968],\n",
+       "          [538.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [538.   ,   4.093,  -0.971],\n",
+       "          [538.   ,   4.094,  -0.971],\n",
+       "          [538.   ,   4.096,  -0.972]]),\n",
+       "   array([[539.   ,   2.701,  -0.968],\n",
+       "          [539.   ,   2.703,  -0.968],\n",
+       "          [539.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [539.   ,   4.093,  -0.971],\n",
+       "          [539.   ,   4.094,  -0.972],\n",
+       "          [539.   ,   4.096,  -0.973]]),\n",
+       "   array([[540.   ,   2.701,  -0.968],\n",
+       "          [540.   ,   2.703,  -0.968],\n",
+       "          [540.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [540.   ,   4.093,  -0.971],\n",
+       "          [540.   ,   4.094,  -0.972],\n",
+       "          [540.   ,   4.096,  -0.972]]),\n",
+       "   array([[541.   ,   2.701,  -0.968],\n",
+       "          [541.   ,   2.703,  -0.968],\n",
+       "          [541.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [541.   ,   4.093,  -0.972],\n",
+       "          [541.   ,   4.094,  -0.972],\n",
+       "          [541.   ,   4.096,  -0.973]]),\n",
+       "   array([[542.   ,   2.701,  -0.968],\n",
+       "          [542.   ,   2.703,  -0.968],\n",
+       "          [542.   ,   2.704,  -0.968],\n",
+       "          ...,\n",
+       "          [542.   ,   4.093,  -0.971],\n",
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+       "  (-0.0034082263299999747, -0.0029281042222222275),\n",
+       "  (-0.002774031560000001, -0.0028830247555555744),\n",
+       "  (-0.0035093394099999565, -0.0034305925000000454),\n",
+       "  (-0.002841476180000013, -0.002909357455555551),\n",
+       "  (-0.00286134603999999, -0.0025491408142857314),\n",
+       "  (-0.013767971060000005, -0.01580585042222222),\n",
+       "  (-0.008542816809999998, -0.010590696033333291),\n",
+       "  (-0.011591536330000008, -0.014800701066666644),\n",
+       "  (-0.019911456340000022, -0.01672480028888885),\n",
+       "  (-0.013500703630000022, -0.012606910885714275)])"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_data[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "id": "82f53ae2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "r_train_x = tf.ragged.constant(X_train[0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "id": "40436319",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "TensorShape([20, None, None])"
+      ]
+     },
+     "execution_count": 57,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "r_train_x.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 301,
+   "id": "fe3dd584",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(20, 3)"
+      ]
+     },
+     "execution_count": 301,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "X_train[0].shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 302,
+   "id": "0035c906",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       " array([], shape=(0, 3), dtype=float64),\n",
+       " array([], shape=(0, 3), dtype=float64),\n",
+       " array([], shape=(0, 3), dtype=float64),\n",
+       " array([], shape=(0, 3), dtype=float64),\n",
+       " array([], shape=(0, 3), dtype=float64),\n",
+       " array([], shape=(0, 3), dtype=float64),\n",
+       " array([], shape=(0, 3), dtype=float64),\n",
+       " array([], shape=(0, 3), dtype=float64),\n",
+       " array([], shape=(0, 3), dtype=float64),\n",
+       " array([], shape=(0, 3), dtype=float64),\n",
+       " array([], shape=(0, 3), dtype=float64),\n",
+       " array([], shape=(0, 3), dtype=float64),\n",
+       " array([], shape=(0, 3), dtype=float64),\n",
+       " array([], shape=(0, 3), dtype=float64),\n",
+       " array([], shape=(0, 3), dtype=float64),\n",
+       " array([], shape=(0, 3), dtype=float64),\n",
+       " array([], shape=(0, 3), dtype=float64),\n",
+       " array([], shape=(0, 3), dtype=float64),\n",
+       " array([], shape=(0, 3), dtype=float64),\n",
+       " array([], shape=(0, 3), dtype=float64),\n",
+       " array([], shape=(0, 3), dtype=float64),\n",
+       " array([], shape=(0, 3), dtype=float64),\n",
+       " array([], shape=(0, 3), dtype=float64),\n",
+       " array([], shape=(0, 3), dtype=float64),\n",
+       " array([], shape=(0, 3), dtype=float64),\n",
+       " ...]"
+      ]
+     },
+     "execution_count": 302,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "X_train"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 290,
+   "id": "2a4cf499",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# flat_list = [x for xs[0] in train_data for x in xs]\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 292,
+   "id": "e4fd6e69",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "6901"
+      ]
+     },
+     "execution_count": 292,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(tes_y)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 280,
+   "id": "ba761d9a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "212"
+      ]
+     },
+     "execution_count": 280,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(tes_X)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 244,
+   "id": "88e668fa",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 246,
+   "id": "ee4b5f21",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "TensorShape([26, None, None])"
+      ]
+     },
+     "execution_count": 246,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "r_train_x.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "id": "3f56fc19",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.PathCollection at 0x7fb84d1657c0>"
+      ]
+     },
+     "execution_count": 65,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "for cycles in cell_labels[0]:\n",
+    "#     print(c)\n",
+    "    plt.scatter(cycles['cycle_index'], cycles['discharge_capacity'], color='C0', s=0.1)\n",
+    "#     print(c)\n",
+    "#     print(c['cycle_index'])\n",
+    "#     break\n",
+    "plt.scatter(cell_1.structured_summary['cycle_index'], cell_1.structured_summary['discharge_capacity'], s=0.1, color='C1')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 241,
+   "id": "9311de63",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(20, 3)"
+      ]
+     },
+     "execution_count": 241,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_data[0][0][0].shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 210,
+   "id": "544ea983",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[-0.0028216217699999825,\n",
+       " -0.0027839635299999888,\n",
+       " -0.00220835934000001,\n",
+       " -0.0018347065800000007,\n",
+       " -0.002192231059999994,\n",
+       " -0.0019204339299999872,\n",
+       " -0.0030049884899999934,\n",
+       " -0.002297327010000005,\n",
+       " -0.002141450750000029,\n",
+       " -0.001709654950000017,\n",
+       " -0.0017677507000000148,\n",
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+       " 6.721815000000353e-05,\n",
+       " 0.0008160637500000068,\n",
+       " ...]"
+      ]
+     },
+     "execution_count": 210,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "flat_train"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 188,
+   "id": "c54a24c7",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2"
+      ]
+     },
+     "execution_count": 188,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(cell_labels[0][0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 184,
+   "id": "0e69921c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
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+       "\n",
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+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>cycle_index</th>\n",
+       "      <th>discharge_capacity</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>400</th>\n",
+       "      <td>425</td>\n",
+       "      <td>0.156420</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>401</th>\n",
+       "      <td>426</td>\n",
+       "      <td>0.156104</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>402</th>\n",
+       "      <td>427</td>\n",
+       "      <td>0.156171</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>403</th>\n",
+       "      <td>428</td>\n",
+       "      <td>0.155647</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>404</th>\n",
+       "      <td>429</td>\n",
+       "      <td>0.154739</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>405</th>\n",
+       "      <td>430</td>\n",
+       "      <td>0.154504</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>406</th>\n",
+       "      <td>431</td>\n",
+       "      <td>0.153200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>407</th>\n",
+       "      <td>432</td>\n",
+       "      <td>0.152232</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>408</th>\n",
+       "      <td>433</td>\n",
+       "      <td>0.151734</td>\n",
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+       "    <tr>\n",
+       "      <th>409</th>\n",
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+       "      <th>410</th>\n",
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+       "      <td>0.150511</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>411</th>\n",
+       "      <td>436</td>\n",
+       "      <td>0.149456</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>412</th>\n",
+       "      <td>437</td>\n",
+       "      <td>0.148931</td>\n",
+       "    </tr>\n",
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+       "      <th>413</th>\n",
+       "      <td>438</td>\n",
+       "      <td>0.148414</td>\n",
+       "    </tr>\n",
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+       "      <th>414</th>\n",
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+       "      <td>0.147513</td>\n",
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+       "      <th>416</th>\n",
+       "      <td>441</td>\n",
+       "      <td>0.146027</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>417</th>\n",
+       "      <td>442</td>\n",
+       "      <td>0.144165</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>418</th>\n",
+       "      <td>443</td>\n",
+       "      <td>0.143110</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>419</th>\n",
+       "      <td>444</td>\n",
+       "      <td>0.143218</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     cycle_index  discharge_capacity\n",
+       "400          425            0.156420\n",
+       "401          426            0.156104\n",
+       "402          427            0.156171\n",
+       "403          428            0.155647\n",
+       "404          429            0.154739\n",
+       "405          430            0.154504\n",
+       "406          431            0.153200\n",
+       "407          432            0.152232\n",
+       "408          433            0.151734\n",
+       "409          434            0.151297\n",
+       "410          435            0.150511\n",
+       "411          436            0.149456\n",
+       "412          437            0.148931\n",
+       "413          438            0.148414\n",
+       "414          439            0.146780\n",
+       "415          440            0.147513\n",
+       "416          441            0.146027\n",
+       "417          442            0.144165\n",
+       "418          443            0.143110\n",
+       "419          444            0.143218"
+      ]
+     },
+     "execution_count": 184,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "discharge_cap_cycle_window"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "92186898",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[      voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 118  2.700801 -0.692075            0            4.743129         3.847404\n",
+       " 119  2.702502 -0.691463            0            4.742295         3.847404\n",
+       " 120  2.704204 -0.691348            0            4.741422         3.847404\n",
+       " 121  2.705906 -0.692106            0            4.740579         3.847404\n",
+       " 122  2.707608 -0.691691            0            4.739734         3.847404\n",
+       " ..        ...       ...          ...                 ...              ...\n",
+       " 981  4.169369 -0.691708            0            0.000355         3.847404\n",
+       " 982  4.171071 -0.691713            0            0.000127         3.847404\n",
+       " 983  4.172773 -0.691269            0            0.000041         3.847404\n",
+       " 984  4.174474 -0.693504            0            0.000024         3.847404\n",
+       " 985  4.176176 -0.696056            0            0.000012         3.847404\n",
+       " \n",
+       " [868 rows x 5 columns],\n",
+       "        voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 1118  2.700801 -4.839723            6            4.443045         4.405115\n",
+       " 1119  2.702502 -4.839571            6            4.442033         4.405115\n",
+       " 1120  2.704204 -4.839418            6            4.441022         4.405115\n",
+       " 1121  2.705906 -4.839378            6            4.440028         4.405115\n",
+       " 1122  2.707608 -4.839526            6            4.439063         4.405115\n",
+       " ...        ...       ...          ...                 ...              ...\n",
+       " 1917  4.060461 -4.843602            6            0.000131         4.405115\n",
+       " 1918  4.062162 -4.844227            6            0.000111         4.405115\n",
+       " 1919  4.063864 -4.844851            6            0.000090         4.405115\n",
+       " 1920  4.065566 -4.845476            6            0.000070         4.405115\n",
+       " 1921  4.067267 -4.846101            6            0.000050         4.405115\n",
+       " \n",
+       " [804 rows x 5 columns],\n",
+       "        voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 2118  2.700801 -4.840235            7            4.440760         4.444087\n",
+       " 2119  2.702502 -4.840086            7            4.439772         4.444087\n",
+       " 2120  2.704204 -4.839935            7            4.438784         4.444087\n",
+       " 2121  2.705906 -4.839785            7            4.437796         4.444087\n",
+       " 2122  2.707608 -4.839926            7            4.436804         4.444087\n",
+       " ...        ...       ...          ...                 ...              ...\n",
+       " 2918  4.062162 -4.843096            7            0.000122         4.444087\n",
+       " 2919  4.063864 -4.843617            7            0.000102         4.444087\n",
+       " 2920  4.065566 -4.844138            7            0.000082         4.444087\n",
+       " 2921  4.067267 -4.844659            7            0.000063         4.444087\n",
+       " 2922  4.068969 -4.845180            7            0.000043         4.444087\n",
+       " \n",
+       " [805 rows x 5 columns],\n",
+       "        voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 3118  2.700801 -4.839849            8            4.436189         4.440933\n",
+       " 3119  2.702502 -4.839895            8            4.435250         4.440933\n",
+       " 3120  2.704204 -4.839743            8            4.434279         4.440933\n",
+       " 3121  2.705906 -4.839591            8            4.433308         4.440933\n",
+       " 3122  2.707608 -4.839662            8            4.432335         4.440933\n",
+       " ...        ...       ...          ...                 ...              ...\n",
+       " 3918  4.062162 -4.844300            8            0.000123         4.440933\n",
+       " 3919  4.063864 -4.844897            8            0.000104         4.440933\n",
+       " 3920  4.065566 -4.845494            8            0.000085         4.440933\n",
+       " 3921  4.067267 -4.846091            8            0.000065         4.440933\n",
+       " 3922  4.068969 -4.846688            8            0.000046         4.440933\n",
+       " \n",
+       " [805 rows x 5 columns],\n",
+       "        voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 4118  2.700801 -4.840451            9            4.434543         4.438245\n",
+       " 4119  2.702502 -4.840303            9            4.433573         4.438245\n",
+       " 4120  2.704204 -4.840155            9            4.432604         4.438245\n",
+       " 4121  2.705906 -4.840008            9            4.431635         4.438245\n",
+       " 4122  2.707608 -4.839934            9            4.430670         4.438245\n",
+       " ...        ...       ...          ...                 ...              ...\n",
+       " 4918  4.062162 -4.843077            9            0.000131         4.438245\n",
+       " 4919  4.063864 -4.843581            9            0.000112         4.438245\n",
+       " 4920  4.065566 -4.844086            9            0.000093         4.438245\n",
+       " 4921  4.067267 -4.844590            9            0.000074         4.438245\n",
+       " 4922  4.068969 -4.845095            9            0.000055         4.438245\n",
+       " \n",
+       " [805 rows x 5 columns],\n",
+       "        voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 5118  2.700801 -4.839662           10            4.430778         4.434467\n",
+       " 5119  2.702502 -4.839637           10            4.429825         4.434467\n",
+       " 5120  2.704204 -4.839787           10            4.428891         4.434467\n",
+       " 5121  2.705906 -4.839937           10            4.427956         4.434467\n",
+       " 5122  2.707608 -4.839970           10            4.427000         4.434467\n",
+       " ...        ...       ...          ...                 ...              ...\n",
+       " 5918  4.062162 -4.843475           10            0.000131         4.434467\n",
+       " 5919  4.063864 -4.844029           10            0.000112         4.434467\n",
+       " 5920  4.065566 -4.844584           10            0.000094         4.434467\n",
+       " 5921  4.067267 -4.845138           10            0.000075         4.434467\n",
+       " 5922  4.068969 -4.845692           10            0.000056         4.434467\n",
+       " \n",
+       " [805 rows x 5 columns],\n",
+       "        voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 6118  2.700801 -4.840223           11            4.426877         4.430998\n",
+       " 6119  2.702502 -4.840149           11            4.425930         4.430998\n",
+       " 6120  2.704204 -4.840075           11            4.424982         4.430998\n",
+       " 6121  2.705906 -4.840002           11            4.424037         4.430998\n",
+       " 6122  2.707608 -4.839929           11            4.423117         4.430998\n",
+       " ...        ...       ...          ...                 ...              ...\n",
+       " 6918  4.062162 -4.842043           11            0.000130         4.430998\n",
+       " 6919  4.063864 -4.842375           11            0.000111         4.430998\n",
+       " 6920  4.065566 -4.842708           11            0.000093         4.430998\n",
+       " 6921  4.067267 -4.843040           11            0.000075         4.430998\n",
+       " 6922  4.068969 -4.843373           11            0.000056         4.430998\n",
+       " \n",
+       " [805 rows x 5 columns],\n",
+       "        voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 7118  2.700801 -4.840143           12            4.423570         4.427185\n",
+       " 7119  2.702502 -4.839918           12            4.422618         4.427185\n",
+       " 7120  2.704204 -4.839693           12            4.421665         4.427185\n",
+       " 7121  2.705906 -4.839580           12            4.420711         4.427185\n",
+       " 7122  2.707608 -4.839654           12            4.419754         4.427185\n",
+       " ...        ...       ...          ...                 ...              ...\n",
+       " 7918  4.062162 -4.842777           12            0.000127         4.427185\n",
+       " 7919  4.063864 -4.843106           12            0.000109         4.427185\n",
+       " 7920  4.065566 -4.843435           12            0.000091         4.427185\n",
+       " 7921  4.067267 -4.843764           12            0.000073         4.427185\n",
+       " 7922  4.068969 -4.844092           12            0.000054         4.427185\n",
+       " \n",
+       " [805 rows x 5 columns],\n",
+       "        voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 8118  2.700801 -4.839859           13            4.420738         4.423994\n",
+       " 8119  2.702502 -4.840030           13            4.419798         4.423994\n",
+       " 8120  2.704204 -4.840200           13            4.418859         4.423994\n",
+       " 8121  2.705906 -4.840122           13            4.417902         4.423994\n",
+       " 8122  2.707608 -4.839972           13            4.416941         4.423994\n",
+       " ...        ...       ...          ...                 ...              ...\n",
+       " 8918  4.062162 -4.842946           13            0.000128         4.423994\n",
+       " 8919  4.063864 -4.843331           13            0.000109         4.423994\n",
+       " 8920  4.065566 -4.843717           13            0.000091         4.423994\n",
+       " 8921  4.067267 -4.844102           13            0.000073         4.423994\n",
+       " 8922  4.068969 -4.844487           13            0.000055         4.423994\n",
+       " \n",
+       " [805 rows x 5 columns],\n",
+       "        voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 9118  2.700801 -4.840238           14            4.418033         4.421894\n",
+       " 9119  2.702502 -4.840238           14            4.417089         4.421894\n",
+       " 9120  2.704204 -4.840238           14            4.416145         4.421894\n",
+       " 9121  2.705906 -4.840076           14            4.415202         4.421894\n",
+       " 9122  2.707608 -4.839854           14            4.414259         4.421894\n",
+       " ...        ...       ...          ...                 ...              ...\n",
+       " 9919  4.063864 -4.844114           14            0.000112         4.421894\n",
+       " 9920  4.065566 -4.844673           14            0.000094         4.421894\n",
+       " 9921  4.067267 -4.845232           14            0.000077         4.421894\n",
+       " 9922  4.068969 -4.845791           14            0.000059         4.421894\n",
+       " 9923  4.070671 -4.846350           14            0.000042         4.421894\n",
+       " \n",
+       " [806 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 10118  2.700801 -4.839780           15            4.412203         4.416853\n",
+       " 10119  2.702502 -4.839780           15            4.411271         4.416853\n",
+       " 10120  2.704204 -4.839780           15            4.410347         4.416853\n",
+       " 10121  2.705906 -4.839780           15            4.409435         4.416853\n",
+       " 10122  2.707608 -4.839780           15            4.408522         4.416853\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 10918  4.062162 -4.843073           15            0.000120         4.416853\n",
+       " 10919  4.063864 -4.843503           15            0.000103         4.416853\n",
+       " 10920  4.065566 -4.843933           15            0.000085         4.416853\n",
+       " 10921  4.067267 -4.844363           15            0.000068         4.416853\n",
+       " 10922  4.068969 -4.844793           15            0.000050         4.416853\n",
+       " \n",
+       " [805 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 11118  2.700801 -4.839819           16            4.408051         4.411975\n",
+       " 11119  2.702502 -4.839903           16            4.407122         4.411975\n",
+       " 11120  2.704204 -4.839987           16            4.406193         4.411975\n",
+       " 11121  2.705906 -4.840009           16            4.405266         4.411975\n",
+       " 11122  2.707608 -4.840009           16            4.404340         4.411975\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 11918  4.062162 -4.841878           16            0.000120         4.411975\n",
+       " 11919  4.063864 -4.842120           16            0.000102         4.411975\n",
+       " 11920  4.065566 -4.842361           16            0.000085         4.411975\n",
+       " 11921  4.067267 -4.842602           16            0.000067         4.411975\n",
+       " 11922  4.068969 -4.842844           16            0.000050         4.411975\n",
+       " \n",
+       " [805 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 12118  2.700801 -4.839618           17            4.404367         4.407828\n",
+       " 12119  2.702502 -4.839759           17            4.403409         4.407828\n",
+       " 12120  2.704204 -4.839780           17            4.402490         4.407828\n",
+       " 12121  2.705906 -4.839780           17            4.401577         4.407828\n",
+       " 12122  2.707608 -4.839780           17            4.400665         4.407828\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 12918  4.062162 -4.842327           17            0.000118         4.407828\n",
+       " 12919  4.063864 -4.842677           17            0.000100         4.407828\n",
+       " 12920  4.065566 -4.843027           17            0.000083         4.407828\n",
+       " 12921  4.067267 -4.843377           17            0.000066         4.407828\n",
+       " 12922  4.068969 -4.843727           17            0.000048         4.407828\n",
+       " \n",
+       " [805 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 13118  2.700801 -4.840009           18            4.400363         4.404699\n",
+       " 13119  2.702502 -4.840009           18            4.399440         4.404699\n",
+       " 13120  2.704204 -4.840009           18            4.398509         4.404699\n",
+       " 13121  2.705906 -4.840009           18            4.397552         4.404699\n",
+       " 13122  2.707608 -4.840009           18            4.396595         4.404699\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 13918  4.062162 -4.844109           18            0.000112         4.404699\n",
+       " 13919  4.063864 -4.844601           18            0.000095         4.404699\n",
+       " 13920  4.065566 -4.845094           18            0.000078         4.404699\n",
+       " 13921  4.067267 -4.845586           18            0.000061         4.404699\n",
+       " 13922  4.068969 -4.846078           18            0.000044         4.404699\n",
+       " \n",
+       " [805 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 14118  2.700801 -4.840068           19            4.395958         4.399664\n",
+       " 14119  2.702502 -4.839780           19            4.395018         4.399664\n",
+       " 14120  2.704204 -4.839780           19            4.394083         4.399664\n",
+       " 14121  2.705906 -4.839780           19            4.393149         4.399664\n",
+       " 14122  2.707608 -4.839806           19            4.392216         4.399664\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 14918  4.062162 -4.844100           19            0.000110         4.399664\n",
+       " 14919  4.063864 -4.844611           19            0.000093         4.399664\n",
+       " 14920  4.065566 -4.845122           19            0.000076         4.399664\n",
+       " 14921  4.067267 -4.845632           19            0.000058         4.399664\n",
+       " 14922  4.068969 -4.846143           19            0.000041         4.399664\n",
+       " \n",
+       " [805 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 15118  2.700801 -4.839869           20            4.391492         4.394867\n",
+       " 15119  2.702502 -4.839833           20            4.390546         4.394867\n",
+       " 15120  2.704204 -4.839908           20            4.389624         4.394867\n",
+       " 15121  2.705906 -4.839983           20            4.388702         4.394867\n",
+       " 15122  2.707608 -4.840058           20            4.387772         4.394867\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 15917  4.060461 -4.844227           20            0.000123         4.394867\n",
+       " 15918  4.062162 -4.844767           20            0.000106         4.394867\n",
+       " 15919  4.063864 -4.845305           20            0.000089         4.394867\n",
+       " 15920  4.065566 -4.845845           20            0.000072         4.394867\n",
+       " 15921  4.067267 -4.846384           20            0.000055         4.394867\n",
+       " \n",
+       " [804 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 16118  2.700801 -4.840009           21            4.385295         4.389851\n",
+       " 16119  2.702502 -4.840009           21            4.384377         4.389851\n",
+       " 16120  2.704204 -4.840026           21            4.383452         4.389851\n",
+       " 16121  2.705906 -4.840101           21            4.382500         4.389851\n",
+       " 16122  2.707608 -4.840176           21            4.381547         4.389851\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 16917  4.060461 -4.842576           21            0.000118         4.389851\n",
+       " 16918  4.062162 -4.842858           21            0.000101         4.389851\n",
+       " 16919  4.063864 -4.843141           21            0.000084         4.389851\n",
+       " 16920  4.065566 -4.843423           21            0.000068         4.389851\n",
+       " 16921  4.067267 -4.843706           21            0.000051         4.389851\n",
+       " \n",
+       " [804 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 17118  2.700801 -4.839895           22            4.380204         4.384093\n",
+       " 17119  2.702502 -4.840142           22            4.379294         4.384093\n",
+       " 17120  2.704204 -4.840390           22            4.378385         4.384093\n",
+       " 17121  2.705906 -4.840416           22            4.377456         4.384093\n",
+       " 17122  2.707608 -4.840342           22            4.376517         4.384093\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 17917  4.060461 -4.844692           22            0.000111         4.384093\n",
+       " 17918  4.062162 -4.845267           22            0.000094         4.384093\n",
+       " 17919  4.063864 -4.845842           22            0.000077         4.384093\n",
+       " 17920  4.065566 -4.846418           22            0.000060         4.384093\n",
+       " 17921  4.067267 -4.846993           22            0.000043         4.384093\n",
+       " \n",
+       " [804 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 18118  2.700801 -4.840111           23            4.374356         4.378807\n",
+       " 18119  2.702502 -4.839837           23            4.373419         4.378807\n",
+       " 18120  2.704204 -4.839564           23            4.372482         4.378807\n",
+       " 18121  2.705906 -4.839623           23            4.371547         4.378807\n",
+       " 18122  2.707608 -4.839698           23            4.370612         4.378807\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 18917  4.060461 -4.844676           23            0.000109         4.378807\n",
+       " 18918  4.062162 -4.845255           23            0.000092         4.378807\n",
+       " 18919  4.063864 -4.845834           23            0.000076         4.378807\n",
+       " 18920  4.065566 -4.846413           23            0.000059         4.378807\n",
+       " 18921  4.067267 -4.846992           23            0.000043         4.378807\n",
+       " \n",
+       " [804 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 19118  2.700801 -4.840370           24            4.369560         4.373428\n",
+       " 19119  2.702502 -4.840161           24            4.368660         4.373428\n",
+       " 19120  2.704204 -4.839989           24            4.367753         4.373428\n",
+       " 19121  2.705906 -4.839914           24            4.366822         4.373428\n",
+       " 19122  2.707608 -4.839839           24            4.365892         4.373428\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 19917  4.060461 -4.844534           24            0.000106         4.373428\n",
+       " 19918  4.062162 -4.845060           24            0.000089         4.373428\n",
+       " 19919  4.063864 -4.845586           24            0.000073         4.373428\n",
+       " 19920  4.065566 -4.846113           24            0.000056         4.373428\n",
+       " 19921  4.067267 -4.846639           24            0.000040         4.373428\n",
+       " \n",
+       " [804 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 20118  2.700801 -4.839780           25            4.362947         4.367811\n",
+       " 20119  2.702502 -4.839780           25            4.362020         4.367811\n",
+       " 20120  2.704204 -4.839817           25            4.361091         4.367811\n",
+       " 20121  2.705906 -4.839891           25            4.360161         4.367811\n",
+       " 20122  2.707608 -4.839965           25            4.359231         4.367811\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 20916  4.058759 -4.843616           25            0.000116         4.367811\n",
+       " 20917  4.060461 -4.844066           25            0.000100         4.367811\n",
+       " 20918  4.062162 -4.844516           25            0.000084         4.367811\n",
+       " 20919  4.063864 -4.844966           25            0.000067         4.367811\n",
+       " 20920  4.065566 -4.845416           25            0.000051         4.367811\n",
+       " \n",
+       " [803 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 21118  2.700801 -4.840084           26            4.358254         4.363298\n",
+       " 21119  2.702502 -4.840238           26            4.357300         4.363298\n",
+       " 21120  2.704204 -4.840238           26            4.356378         4.363298\n",
+       " 21121  2.705906 -4.840238           26            4.355455         4.363298\n",
+       " 21122  2.707608 -4.840234           26            4.354533         4.363298\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 21916  4.058759 -4.843864           26            0.000115         4.363298\n",
+       " 21917  4.060461 -4.844319           26            0.000099         4.363298\n",
+       " 21918  4.062162 -4.844773           26            0.000083         4.363298\n",
+       " 21919  4.063864 -4.845228           26            0.000066         4.363298\n",
+       " 21920  4.065566 -4.845682           26            0.000050         4.363298\n",
+       " \n",
+       " [803 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 22118  2.700801 -4.839880           27            4.350898         4.355431\n",
+       " 22119  2.702502 -4.839980           27            4.349951         4.355431\n",
+       " 22120  2.704204 -4.839906           27            4.349030         4.355431\n",
+       " 22121  2.705906 -4.839832           27            4.348109         4.355431\n",
+       " 22122  2.707608 -4.839803           27            4.347173         4.355431\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 22916  4.058759 -4.842062           27            0.000106         4.355431\n",
+       " 22917  4.060461 -4.842288           27            0.000090         4.355431\n",
+       " 22918  4.062162 -4.842515           27            0.000074         4.355431\n",
+       " 22919  4.063864 -4.842741           27            0.000057         4.355431\n",
+       " 22920  4.065566 -4.842968           27            0.000041         4.355431\n",
+       " \n",
+       " [803 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 23118  2.700801 -4.839782           28            4.344365         4.349618\n",
+       " 23119  2.702502 -4.839857           28            4.343439         4.349618\n",
+       " 23120  2.704204 -4.839932           28            4.342513         4.349618\n",
+       " 23121  2.705906 -4.840007           28            4.341587         4.349618\n",
+       " 23122  2.707608 -4.840009           28            4.340626         4.349618\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 23915  4.057057 -4.843357           28            0.000118         4.349618\n",
+       " 23916  4.058759 -4.843752           28            0.000102         4.349618\n",
+       " 23917  4.060461 -4.844147           28            0.000086         4.349618\n",
+       " 23918  4.062162 -4.844543           28            0.000070         4.349618\n",
+       " 23919  4.063864 -4.844938           28            0.000053         4.349618\n",
+       " \n",
+       " [802 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 24118  2.700801 -4.840196           29            4.338979         4.343386\n",
+       " 24119  2.702502 -4.840105           29            4.338031         4.343386\n",
+       " 24120  2.704204 -4.840014           29            4.337083         4.343386\n",
+       " 24121  2.705906 -4.839939           29            4.336153         4.343386\n",
+       " 24122  2.707608 -4.839865           29            4.335223         4.343386\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 24915  4.057057 -4.842513           29            0.000116         4.343386\n",
+       " 24916  4.058759 -4.842807           29            0.000100         4.343386\n",
+       " 24917  4.060461 -4.843102           29            0.000084         4.343386\n",
+       " 24918  4.062162 -4.843396           29            0.000068         4.343386\n",
+       " 24919  4.063864 -4.843690           29            0.000051         4.343386\n",
+       " \n",
+       " [802 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 25118  2.700801 -4.839738           30            4.331031         4.336436\n",
+       " 25119  2.702502 -4.839647           30            4.330078         4.336436\n",
+       " 25120  2.704204 -4.839556           30            4.329125         4.336436\n",
+       " 25121  2.705906 -4.839695           30            4.328176         4.336436\n",
+       " 25122  2.707608 -4.839845           30            4.327229         4.336436\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 25915  4.057057 -4.843243           30            0.000110         4.336436\n",
+       " 25916  4.058759 -4.843601           30            0.000094         4.336436\n",
+       " 25917  4.060461 -4.843958           30            0.000078         4.336436\n",
+       " 25918  4.062162 -4.844315           30            0.000062         4.336436\n",
+       " 25919  4.063864 -4.844673           30            0.000046         4.336436\n",
+       " \n",
+       " [802 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 26118  2.700801 -4.840009           31            4.324510         4.329797\n",
+       " 26119  2.702502 -4.840012           31            4.323554         4.329797\n",
+       " 26120  2.704204 -4.840085           31            4.322616         4.329797\n",
+       " 26121  2.705906 -4.840158           31            4.321678         4.329797\n",
+       " 26122  2.707608 -4.840230           31            4.320740         4.329797\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 26915  4.057057 -4.843648           31            0.000107         4.329797\n",
+       " 26916  4.058759 -4.844092           31            0.000091         4.329797\n",
+       " 26917  4.060461 -4.844536           31            0.000075         4.329797\n",
+       " 26918  4.062162 -4.844980           31            0.000059         4.329797\n",
+       " 26919  4.063864 -4.845424           31            0.000043         4.329797\n",
+       " \n",
+       " [802 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 27118  2.700801 -4.839780           32            4.317779         4.322463\n",
+       " 27119  2.702502 -4.839803           32            4.316831         4.322463\n",
+       " 27120  2.704204 -4.839877           32            4.315879         4.322463\n",
+       " 27121  2.705906 -4.839951           32            4.314928         4.322463\n",
+       " 27122  2.707608 -4.840024           32            4.313976         4.322463\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 27914  4.055356 -4.843420           32            0.000118         4.322463\n",
+       " 27915  4.057057 -4.843848           32            0.000102         4.322463\n",
+       " 27916  4.058759 -4.844276           32            0.000086         4.322463\n",
+       " 27917  4.060461 -4.844705           32            0.000070         4.322463\n",
+       " 27918  4.062162 -4.845133           32            0.000054         4.322463\n",
+       " \n",
+       " [801 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 28118  2.700801 -4.840009           33            4.309946         4.315415\n",
+       " 28119  2.702502 -4.840009           33            4.308983         4.315415\n",
+       " 28120  2.704204 -4.839952           33            4.308018         4.315415\n",
+       " 28121  2.705906 -4.839877           33            4.307053         4.315415\n",
+       " 28122  2.707608 -4.839802           33            4.306087         4.315415\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 28914  4.055356 -4.843303           33            0.000114         4.315415\n",
+       " 28915  4.057057 -4.843675           33            0.000098         4.315415\n",
+       " 28916  4.058759 -4.844047           33            0.000082         4.315415\n",
+       " 28917  4.060461 -4.844419           33            0.000066         4.315415\n",
+       " 28918  4.062162 -4.844790           33            0.000051         4.315415\n",
+       " \n",
+       " [801 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 29118  2.700801 -4.839643           34            4.302573         4.307833\n",
+       " 29119  2.702502 -4.839780           34            4.301587         4.307833\n",
+       " 29120  2.704204 -4.839780           34            4.300639         4.307833\n",
+       " 29121  2.705906 -4.839780           34            4.299692         4.307833\n",
+       " 29122  2.707608 -4.839765           34            4.298738         4.307833\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 29914  4.055356 -4.843952           34            0.000110         4.307833\n",
+       " 29915  4.057057 -4.844407           34            0.000094         4.307833\n",
+       " 29916  4.058759 -4.844862           34            0.000078         4.307833\n",
+       " 29917  4.060461 -4.845317           34            0.000062         4.307833\n",
+       " 29918  4.062162 -4.845772           34            0.000046         4.307833\n",
+       " \n",
+       " [801 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 30118  2.700801 -4.839901           35            4.294234          4.30101\n",
+       " 30119  2.702502 -4.839817           35            4.293274          4.30101\n",
+       " 30120  2.704204 -4.839891           35            4.292308          4.30101\n",
+       " 30121  2.705906 -4.839966           35            4.291343          4.30101\n",
+       " 30122  2.707608 -4.840042           35            4.290368          4.30101\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 30914  4.055356 -4.843244           35            0.000104          4.30101\n",
+       " 30915  4.057057 -4.843632           35            0.000088          4.30101\n",
+       " 30916  4.058759 -4.844019           35            0.000072          4.30101\n",
+       " 30917  4.060461 -4.844407           35            0.000056          4.30101\n",
+       " 30918  4.062162 -4.844794           35            0.000041          4.30101\n",
+       " \n",
+       " [801 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 31118  2.700801 -4.839821           41            4.323713         4.239964\n",
+       " 31119  2.702502 -4.839907           41            4.322809         4.239964\n",
+       " 31120  2.704204 -4.839993           41            4.321904         4.239964\n",
+       " 31121  2.705906 -4.839948           41            4.320985         4.239964\n",
+       " 31122  2.707608 -4.839872           41            4.320064         4.239964\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 31916  4.058759 -4.844514           41            0.000111         4.239964\n",
+       " 31917  4.060461 -4.845007           41            0.000096         4.239964\n",
+       " 31918  4.062162 -4.845500           41            0.000081         4.239964\n",
+       " 31919  4.063864 -4.845993           41            0.000066         4.239964\n",
+       " 31920  4.065566 -4.846486           41            0.000052         4.239964\n",
+       " \n",
+       " [803 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 32118  2.700801 -4.840407           42            4.313706         4.320747\n",
+       " 32119  2.702502 -4.840280           42            4.312791         4.320747\n",
+       " 32120  2.704204 -4.840137           42            4.311845         4.320747\n",
+       " 32121  2.705906 -4.839987           42            4.310884         4.320747\n",
+       " 32122  2.707608 -4.839837           42            4.309923         4.320747\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 32916  4.058759 -4.842972           42            0.000112         4.320747\n",
+       " 32917  4.060461 -4.843300           42            0.000097         4.320747\n",
+       " 32918  4.062162 -4.843628           42            0.000083         4.320747\n",
+       " 32919  4.063864 -4.843956           42            0.000068         4.320747\n",
+       " 32920  4.065566 -4.844284           42            0.000053         4.320747\n",
+       " \n",
+       " [803 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 33118  2.700801 -4.839859           43            4.301708         4.308702\n",
+       " 33119  2.702502 -4.840009           43            4.300827         4.308702\n",
+       " 33120  2.704204 -4.840009           43            4.299859         4.308702\n",
+       " 33121  2.705906 -4.840009           43            4.298891         4.308702\n",
+       " 33122  2.707608 -4.840021           43            4.297922         4.308702\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 33915  4.057057 -4.844145           43            0.000111         4.308702\n",
+       " 33916  4.058759 -4.844567           43            0.000096         4.308702\n",
+       " 33917  4.060461 -4.844988           43            0.000082         4.308702\n",
+       " 33918  4.062162 -4.845410           43            0.000067         4.308702\n",
+       " 33919  4.063864 -4.845831           43            0.000052         4.308702\n",
+       " \n",
+       " [802 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 34118  2.700801 -4.839847           44            4.291670         4.297814\n",
+       " 34119  2.702502 -4.839988           44            4.290695         4.297814\n",
+       " 34120  2.704204 -4.840074           44            4.289735         4.297814\n",
+       " 34121  2.705906 -4.840150           44            4.288777         4.297814\n",
+       " 34122  2.707608 -4.840227           44            4.287819         4.297814\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 34915  4.057057 -4.844548           44            0.000099         4.297814\n",
+       " 34916  4.058759 -4.844954           44            0.000084         4.297814\n",
+       " 34917  4.060461 -4.845360           44            0.000070         4.297814\n",
+       " 34918  4.062162 -4.845766           44            0.000055         4.297814\n",
+       " 34919  4.063864 -4.846172           44            0.000040         4.297814\n",
+       " \n",
+       " [802 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 35118  2.700801 -4.840180           45            4.282351         4.288517\n",
+       " 35119  2.702502 -4.840055           45            4.281400         4.288517\n",
+       " 35120  2.704204 -4.839962           45            4.280420         4.288517\n",
+       " 35121  2.705906 -4.839887           45            4.279424         4.288517\n",
+       " 35122  2.707608 -4.839812           45            4.278427         4.288517\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 35914  4.055356 -4.842854           45            0.000103         4.288517\n",
+       " 35915  4.057057 -4.843149           45            0.000088         4.288517\n",
+       " 35916  4.058759 -4.843444           45            0.000074         4.288517\n",
+       " 35917  4.060461 -4.843739           45            0.000059         4.288517\n",
+       " 35918  4.062162 -4.844033           45            0.000044         4.288517\n",
+       " \n",
+       " [801 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 36118  2.700801 -4.839908           46            4.272636          4.27929\n",
+       " 36119  2.702502 -4.839691           46            4.271698          4.27929\n",
+       " 36120  2.704204 -4.839606           46            4.270736          4.27929\n",
+       " 36121  2.705906 -4.839758           46            4.269729          4.27929\n",
+       " 36122  2.707608 -4.839911           46            4.268722          4.27929\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 36913  4.053654 -4.844103           46            0.000110          4.27929\n",
+       " 36914  4.055356 -4.844539           46            0.000095          4.27929\n",
+       " 36915  4.057057 -4.844975           46            0.000080          4.27929\n",
+       " 36916  4.058759 -4.845410           46            0.000066          4.27929\n",
+       " 36917  4.060461 -4.845846           46            0.000051          4.27929\n",
+       " \n",
+       " [800 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 37118  2.700801 -4.839912           47            4.263072         4.268782\n",
+       " 37119  2.702502 -4.840196           47            4.262123         4.268782\n",
+       " 37120  2.704204 -4.840175           47            4.261152         4.268782\n",
+       " 37121  2.705906 -4.840101           47            4.260179         4.268782\n",
+       " 37122  2.707608 -4.840027           47            4.259205         4.268782\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 37913  4.053654 -4.844343           47            0.000102         4.268782\n",
+       " 37914  4.055356 -4.844778           47            0.000087         4.268782\n",
+       " 37915  4.057057 -4.845212           47            0.000073         4.268782\n",
+       " 37916  4.058759 -4.845646           47            0.000058         4.268782\n",
+       " 37917  4.060461 -4.846081           47            0.000043         4.268782\n",
+       " \n",
+       " [800 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 38118  2.700801 -4.839467           48            4.254888         4.260946\n",
+       " 38119  2.702502 -4.839776           48            4.253915         4.260946\n",
+       " 38120  2.704204 -4.839780           48            4.252937         4.260946\n",
+       " 38121  2.705906 -4.839780           48            4.251960         4.260946\n",
+       " 38122  2.707608 -4.839780           48            4.250982         4.260946\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 38912  4.051952 -4.844121           48            0.000112         4.260946\n",
+       " 38913  4.053654 -4.844537           48            0.000097         4.260946\n",
+       " 38914  4.055356 -4.844952           48            0.000083         4.260946\n",
+       " 38915  4.057057 -4.845367           48            0.000068         4.260946\n",
+       " 38916  4.058759 -4.845782           48            0.000054         4.260946\n",
+       " \n",
+       " [799 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 39118  2.700801 -4.839622           49            4.245386          4.25135\n",
+       " 39119  2.702502 -4.839775           49            4.244392          4.25135\n",
+       " 39120  2.704204 -4.839927           49            4.243399          4.25135\n",
+       " 39121  2.705906 -4.839941           49            4.242414          4.25135\n",
+       " 39122  2.707608 -4.839793           49            4.241441          4.25135\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 39912  4.051952 -4.844606           49            0.000106          4.25135\n",
+       " 39913  4.053654 -4.845052           49            0.000091          4.25135\n",
+       " 39914  4.055356 -4.845498           49            0.000077          4.25135\n",
+       " 39915  4.057057 -4.845944           49            0.000062          4.25135\n",
+       " 39916  4.058759 -4.846390           49            0.000048          4.25135\n",
+       " \n",
+       " [799 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 40118  2.700801 -4.840009           50            4.236239         4.242552\n",
+       " 40119  2.702502 -4.840009           50            4.235265         4.242552\n",
+       " 40120  2.704204 -4.839999           50            4.234285         4.242552\n",
+       " 40121  2.705906 -4.839924           50            4.233275         4.242552\n",
+       " 40122  2.707608 -4.839849           50            4.232266         4.242552\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 40911  4.050250 -4.844419           50            0.000112         4.242552\n",
+       " 40912  4.051952 -4.844915           50            0.000097         4.242552\n",
+       " 40913  4.053654 -4.845412           50            0.000083         4.242552\n",
+       " 40914  4.055356 -4.845908           50            0.000068         4.242552\n",
+       " 40915  4.057057 -4.846405           50            0.000054         4.242552\n",
+       " \n",
+       " [798 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 41118  2.700801 -4.840009           51            4.227606         4.233596\n",
+       " 41119  2.702502 -4.840009           51            4.226625         4.233596\n",
+       " 41120  2.704204 -4.839962           51            4.225641         4.233596\n",
+       " 41121  2.705906 -4.839887           51            4.224653         4.233596\n",
+       " 41122  2.707608 -4.839812           51            4.223665         4.233596\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 41911  4.050250 -4.843726           51            0.000109         4.233596\n",
+       " 41912  4.051952 -4.844099           51            0.000095         4.233596\n",
+       " 41913  4.053654 -4.844471           51            0.000080         4.233596\n",
+       " 41914  4.055356 -4.844843           51            0.000066         4.233596\n",
+       " 41915  4.057057 -4.845216           51            0.000051         4.233596\n",
+       " \n",
+       " [798 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 42118  2.700801 -4.839927           52            4.218776         4.224729\n",
+       " 42119  2.702502 -4.839806           52            4.217803         4.224729\n",
+       " 42120  2.704204 -4.839961           52            4.216827         4.224729\n",
+       " 42121  2.705906 -4.840116           52            4.215850         4.224729\n",
+       " 42122  2.707608 -4.840238           52            4.214861         4.224729\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 42911  4.050250 -4.843613           52            0.000105         4.224729\n",
+       " 42912  4.051952 -4.843982           52            0.000090         4.224729\n",
+       " 42913  4.053654 -4.844351           52            0.000076         4.224729\n",
+       " 42914  4.055356 -4.844720           52            0.000061         4.224729\n",
+       " 42915  4.057057 -4.845089           52            0.000047         4.224729\n",
+       " \n",
+       " [798 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 43118  2.700801 -4.840342           53            4.208975         4.215786\n",
+       " 43119  2.702502 -4.840073           53            4.207973         4.215786\n",
+       " 43120  2.704204 -4.840066           53            4.206982         4.215786\n",
+       " 43121  2.705906 -4.840141           53            4.205994         4.215786\n",
+       " 43122  2.707608 -4.840217           53            4.205006         4.215786\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 43911  4.050250 -4.842741           53            0.000100         4.215786\n",
+       " 43912  4.051952 -4.843019           53            0.000086         4.215786\n",
+       " 43913  4.053654 -4.843295           53            0.000071         4.215786\n",
+       " 43914  4.055356 -4.843572           53            0.000057         4.215786\n",
+       " 43915  4.057057 -4.843849           53            0.000042         4.215786\n",
+       " \n",
+       " [798 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 44118  2.700801 -4.839793           54            4.200200         4.206812\n",
+       " 44119  2.702502 -4.839622           54            4.199181         4.206812\n",
+       " 44120  2.704204 -4.839770           54            4.198164         4.206812\n",
+       " 44121  2.705906 -4.839919           54            4.197146         4.206812\n",
+       " 44122  2.707608 -4.840009           54            4.196128         4.206812\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 44911  4.050250 -4.842850           54            0.000098         4.206812\n",
+       " 44912  4.051952 -4.843112           54            0.000083         4.206812\n",
+       " 44913  4.053654 -4.843374           54            0.000069         4.206812\n",
+       " 44914  4.055356 -4.843636           54            0.000054         4.206812\n",
+       " 44915  4.057057 -4.843898           54            0.000040         4.206812\n",
+       " \n",
+       " [798 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 45118  2.700801 -4.840238           55            4.189658         4.196794\n",
+       " 45119  2.702502 -4.840238           55            4.188623         4.196794\n",
+       " 45120  2.704204 -4.840238           55            4.187590         4.196794\n",
+       " 45121  2.705906 -4.840202           55            4.186559         4.196794\n",
+       " 45122  2.707608 -4.840052           55            4.185535         4.196794\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 45910  4.048549 -4.842662           55            0.000108         4.196794\n",
+       " 45911  4.050250 -4.842923           55            0.000094         4.196794\n",
+       " 45912  4.051952 -4.843184           55            0.000079         4.196794\n",
+       " 45913  4.053654 -4.843446           55            0.000065         4.196794\n",
+       " 45914  4.055356 -4.843707           55            0.000050         4.196794\n",
+       " \n",
+       " [797 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 46118  2.700801 -4.840313           56            4.180357         4.187159\n",
+       " 46119  2.702502 -4.839984           56            4.179366         4.187159\n",
+       " 46120  2.704204 -4.839655           56            4.178374         4.187159\n",
+       " 46121  2.705906 -4.839708           56            4.177348         4.187159\n",
+       " 46122  2.707608 -4.839937           56            4.176305         4.187159\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 46910  4.048549 -4.843475           56            0.000104         4.187159\n",
+       " 46911  4.050250 -4.843830           56            0.000089         4.187159\n",
+       " 46912  4.051952 -4.844185           56            0.000075         4.187159\n",
+       " 46913  4.053654 -4.844540           56            0.000060         4.187159\n",
+       " 46914  4.055356 -4.844894           56            0.000046         4.187159\n",
+       " \n",
+       " [797 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 47118  2.700801 -4.839594           57            4.169956         4.176821\n",
+       " 47119  2.702502 -4.839745           57            4.168924         4.176821\n",
+       " 47120  2.704204 -4.839895           57            4.167892         4.176821\n",
+       " 47121  2.705906 -4.839992           57            4.166857         4.176821\n",
+       " 47122  2.707608 -4.839916           57            4.165812         4.176821\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 47910  4.048549 -4.842840           57            0.000098         4.176821\n",
+       " 47911  4.050250 -4.843103           57            0.000084         4.176821\n",
+       " 47912  4.051952 -4.843367           57            0.000069         4.176821\n",
+       " 47913  4.053654 -4.843631           57            0.000055         4.176821\n",
+       " 47914  4.055356 -4.843895           57            0.000040         4.176821\n",
+       " \n",
+       " [797 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 48118  2.700801 -4.840125           58            4.160315         4.166723\n",
+       " 48119  2.702502 -4.839882           58            4.159301         4.166723\n",
+       " 48120  2.704204 -4.839823           58            4.158280         4.166723\n",
+       " 48121  2.705906 -4.839898           58            4.157255         4.166723\n",
+       " 48122  2.707608 -4.839972           58            4.156229         4.166723\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 48909  4.046847 -4.842127           58            0.000108         4.166723\n",
+       " 48910  4.048549 -4.842404           58            0.000094         4.166723\n",
+       " 48911  4.050250 -4.842681           58            0.000079         4.166723\n",
+       " 48912  4.051952 -4.842957           58            0.000065         4.166723\n",
+       " 48913  4.053654 -4.843235           58            0.000051         4.166723\n",
+       " \n",
+       " [796 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 49118  2.700801 -4.839899           59            4.149799         4.156341\n",
+       " 49119  2.702502 -4.839661           59            4.148781         4.156341\n",
+       " 49120  2.704204 -4.839592           59            4.147756         4.156341\n",
+       " 49121  2.705906 -4.839667           59            4.146724         4.156341\n",
+       " 49122  2.707608 -4.839742           59            4.145692         4.156341\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 49909  4.046847 -4.843437           59            0.000104         4.156341\n",
+       " 49910  4.048549 -4.843745           59            0.000090         4.156341\n",
+       " 49911  4.050250 -4.844052           59            0.000076         4.156341\n",
+       " 49912  4.051952 -4.844360           59            0.000061         4.156341\n",
+       " 49913  4.053654 -4.844667           59            0.000047         4.156341\n",
+       " \n",
+       " [796 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 50118  2.700801 -4.840145           60            4.139518         4.146362\n",
+       " 50119  2.702502 -4.839944           60            4.138506         4.146362\n",
+       " 50120  2.704204 -4.839780           60            4.137488         4.146362\n",
+       " 50121  2.705906 -4.839780           60            4.136439         4.146362\n",
+       " 50122  2.707608 -4.839780           60            4.135389         4.146362\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 50909  4.046847 -4.842502           60            0.000101         4.146362\n",
+       " 50910  4.048549 -4.842779           60            0.000086         4.146362\n",
+       " 50911  4.050250 -4.843057           60            0.000072         4.146362\n",
+       " 50912  4.051952 -4.843334           60            0.000057         4.146362\n",
+       " 50913  4.053654 -4.843612           60            0.000043         4.146362\n",
+       " \n",
+       " [796 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 51118  2.700801 -4.839984           61            4.129361         4.135852\n",
+       " 51119  2.702502 -4.839909           61            4.128325         4.135852\n",
+       " 51120  2.704204 -4.839834           61            4.127288         4.135852\n",
+       " 51121  2.705906 -4.839780           61            4.126254         4.135852\n",
+       " 51122  2.707608 -4.839780           61            4.125225         4.135852\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 51908  4.045145 -4.843488           61            0.000109         4.135852\n",
+       " 51909  4.046847 -4.843817           61            0.000095         4.135852\n",
+       " 51910  4.048549 -4.844147           61            0.000080         4.135852\n",
+       " 51911  4.050250 -4.844477           61            0.000065         4.135852\n",
+       " 51912  4.051952 -4.844807           61            0.000050         4.135852\n",
+       " \n",
+       " [795 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 52118  2.700801 -4.840004           62            4.118953         4.125921\n",
+       " 52119  2.702502 -4.839930           62            4.117943         4.125921\n",
+       " 52120  2.704204 -4.839854           62            4.116933         4.125921\n",
+       " 52121  2.705906 -4.839779           62            4.115922         4.125921\n",
+       " 52122  2.707608 -4.839703           62            4.114844         4.125921\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 52908  4.045145 -4.842462           62            0.000107         4.125921\n",
+       " 52909  4.046847 -4.842725           62            0.000092         4.125921\n",
+       " 52910  4.048549 -4.842989           62            0.000077         4.125921\n",
+       " 52911  4.050250 -4.843253           62            0.000063         4.125921\n",
+       " 52912  4.051952 -4.843517           62            0.000048         4.125921\n",
+       " \n",
+       " [795 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 53118  2.700801 -4.840009           63            4.109108         4.115542\n",
+       " 53119  2.702502 -4.840009           63            4.108129         4.115542\n",
+       " 53120  2.704204 -4.839907           63            4.107111         4.115542\n",
+       " 53121  2.705906 -4.839678           63            4.106046         4.115542\n",
+       " 53122  2.707608 -4.839449           63            4.104980         4.115542\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 53908  4.045145 -4.844180           63            0.000103         4.115542\n",
+       " 53909  4.046847 -4.844645           63            0.000088         4.115542\n",
+       " 53910  4.048549 -4.845110           63            0.000074         4.115542\n",
+       " 53911  4.050250 -4.845576           63            0.000059         4.115542\n",
+       " 53912  4.051952 -4.846042           63            0.000044         4.115542\n",
+       " \n",
+       " [795 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 54118  2.700801 -4.839822           64            4.098242         4.105879\n",
+       " 54119  2.702502 -4.839911           64            4.097227         4.105879\n",
+       " 54120  2.704204 -4.840001           64            4.096212         4.105879\n",
+       " 54121  2.705906 -4.840009           64            4.095161         4.105879\n",
+       " 54122  2.707608 -4.840009           64            4.094107         4.105879\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 54908  4.045145 -4.843044           64            0.000100         4.105879\n",
+       " 54909  4.046847 -4.843307           64            0.000085         4.105879\n",
+       " 54910  4.048549 -4.843569           64            0.000071         4.105879\n",
+       " 54911  4.050250 -4.843831           64            0.000056         4.105879\n",
+       " 54912  4.051952 -4.844093           64            0.000042         4.105879\n",
+       " \n",
+       " [795 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 55118  2.700801 -4.840009           65            4.086635         4.094151\n",
+       " 55119  2.702502 -4.840009           65            4.085639         4.094151\n",
+       " 55120  2.704204 -4.840009           65            4.084642         4.094151\n",
+       " 55121  2.705906 -4.839966           65            4.083599         4.094151\n",
+       " 55122  2.707608 -4.839889           65            4.082518         4.094151\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 55907  4.043444 -4.844044           65            0.000109         4.094151\n",
+       " 55908  4.045145 -4.844449           65            0.000094         4.094151\n",
+       " 55909  4.046847 -4.844854           65            0.000080         4.094151\n",
+       " 55910  4.048549 -4.845258           65            0.000065         4.094151\n",
+       " 55911  4.050250 -4.845663           65            0.000050         4.094151\n",
+       " \n",
+       " [794 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 56118  2.700801 -4.839874           66            4.075892         4.083415\n",
+       " 56119  2.702502 -4.840074           66            4.074892         4.083415\n",
+       " 56120  2.704204 -4.840238           66            4.073877         4.083415\n",
+       " 56121  2.705906 -4.840238           66            4.072789         4.083415\n",
+       " 56122  2.707608 -4.840238           66            4.071702         4.083415\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 56907  4.043444 -4.843298           66            0.000108         4.083415\n",
+       " 56908  4.045145 -4.843625           66            0.000093         4.083415\n",
+       " 56909  4.046847 -4.843951           66            0.000078         4.083415\n",
+       " 56910  4.048549 -4.844278           66            0.000064         4.083415\n",
+       " 56911  4.050250 -4.844605           66            0.000049         4.083415\n",
+       " \n",
+       " [794 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 57118  2.700801 -4.839701           67            4.065419         4.072347\n",
+       " 57119  2.702502 -4.839561           67            4.064415         4.072347\n",
+       " 57120  2.704204 -4.839636           67            4.063384         4.072347\n",
+       " 57121  2.705906 -4.839711           67            4.062352         4.072347\n",
+       " 57122  2.707608 -4.839791           67            4.061317         4.072347\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 57907  4.043444 -4.842457           67            0.000107         4.072347\n",
+       " 57908  4.045145 -4.842719           67            0.000092         4.072347\n",
+       " 57909  4.046847 -4.842980           67            0.000078         4.072347\n",
+       " 57910  4.048549 -4.843242           67            0.000063         4.072347\n",
+       " 57911  4.050250 -4.843503           67            0.000049         4.072347\n",
+       " \n",
+       " [794 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 58118  2.700801 -4.839911           68            4.053965          4.06193\n",
+       " 58119  2.702502 -4.840055           68            4.052956          4.06193\n",
+       " 58120  2.704204 -4.840128           68            4.051935          4.06193\n",
+       " 58121  2.705906 -4.840203           68            4.050913          4.06193\n",
+       " 58122  2.707608 -4.840160           68            4.049861          4.06193\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 58907  4.043444 -4.843080           68            0.000104          4.06193\n",
+       " 58908  4.045145 -4.843424           68            0.000089          4.06193\n",
+       " 58909  4.046847 -4.843769           68            0.000075          4.06193\n",
+       " 58910  4.048549 -4.844113           68            0.000060          4.06193\n",
+       " 58911  4.050250 -4.844458           68            0.000045          4.06193\n",
+       " \n",
+       " [794 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 59118  2.700801 -4.840172           69            4.042803         4.050208\n",
+       " 59119  2.702502 -4.840030           69            4.041770         4.050208\n",
+       " 59120  2.704204 -4.839946           69            4.040751         4.050208\n",
+       " 59121  2.705906 -4.839872           69            4.039734         4.050208\n",
+       " 59122  2.707608 -4.839798           69            4.038717         4.050208\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 59907  4.043444 -4.843369           69            0.000103         4.050208\n",
+       " 59908  4.045145 -4.843647           69            0.000089         4.050208\n",
+       " 59909  4.046847 -4.843925           69            0.000074         4.050208\n",
+       " 59910  4.048549 -4.844204           69            0.000060         4.050208\n",
+       " 59911  4.050250 -4.844482           69            0.000045         4.050208\n",
+       " \n",
+       " [794 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 60118  2.700801 -4.839939           70            4.033422         4.039702\n",
+       " 60119  2.702502 -4.840009           70            4.032387         4.039702\n",
+       " 60120  2.704204 -4.840009           70            4.031344         4.039702\n",
+       " 60121  2.705906 -4.840009           70            4.030302         4.039702\n",
+       " 60122  2.707608 -4.840009           70            4.029232         4.039702\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 60907  4.043444 -4.843048           70            0.000100         4.039702\n",
+       " 60908  4.045145 -4.843314           70            0.000085         4.039702\n",
+       " 60909  4.046847 -4.843580           70            0.000070         4.039702\n",
+       " 60910  4.048549 -4.843846           70            0.000055         4.039702\n",
+       " 60911  4.050250 -4.844113           70            0.000041         4.039702\n",
+       " \n",
+       " [794 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 61118  2.700801 -4.840044           71            4.021760         4.028771\n",
+       " 61119  2.702502 -4.840288           71            4.020759         4.028771\n",
+       " 61120  2.704204 -4.840363           71            4.019749         4.028771\n",
+       " 61121  2.705906 -4.840438           71            4.018739         4.028771\n",
+       " 61122  2.707608 -4.840421           71            4.017689         4.028771\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 61906  4.041742 -4.843581           71            0.000112         4.028771\n",
+       " 61907  4.043444 -4.843925           71            0.000097         4.028771\n",
+       " 61908  4.045145 -4.844268           71            0.000083         4.028771\n",
+       " 61909  4.046847 -4.844612           71            0.000068         4.028771\n",
+       " 61910  4.048549 -4.844955           71            0.000053         4.028771\n",
+       " \n",
+       " [793 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 62118  2.700801 -4.839918           72            4.007693         4.016519\n",
+       " 62119  2.702502 -4.839825           72            4.006684         4.016519\n",
+       " 62120  2.704204 -4.839973           72            4.005637         4.016519\n",
+       " 62121  2.705906 -4.840121           72            4.004590         4.016519\n",
+       " 62122  2.707608 -4.840238           72            4.003540         4.016519\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 62906  4.041742 -4.843210           72            0.000108         4.016519\n",
+       " 62907  4.043444 -4.843552           72            0.000094         4.016519\n",
+       " 62908  4.045145 -4.843893           72            0.000079         4.016519\n",
+       " 62909  4.046847 -4.844234           72            0.000065         4.016519\n",
+       " 62910  4.048549 -4.844576           72            0.000050         4.016519\n",
+       " \n",
+       " [793 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 63118  2.700801 -4.839960           73            3.996118         4.003242\n",
+       " 63119  2.702502 -4.839853           73            3.995100         4.003242\n",
+       " 63120  2.704204 -4.839850           73            3.994071         4.003242\n",
+       " 63121  2.705906 -4.840072           73            3.993019         4.003242\n",
+       " 63122  2.707608 -4.840294           73            3.991968         4.003242\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 63906  4.041742 -4.843416           73            0.000105         4.003242\n",
+       " 63907  4.043444 -4.843726           73            0.000091         4.003242\n",
+       " 63908  4.045145 -4.844035           73            0.000076         4.003242\n",
+       " 63909  4.046847 -4.844344           73            0.000062         4.003242\n",
+       " 63910  4.048549 -4.844654           73            0.000047         4.003242\n",
+       " \n",
+       " [793 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 64118  2.700801 -4.840096           74            3.984123         3.992291\n",
+       " 64119  2.702502 -4.839789           74            3.983128         3.992291\n",
+       " 64120  2.704204 -4.839585           74            3.982115         3.992291\n",
+       " 64121  2.705906 -4.839736           74            3.981044         3.992291\n",
+       " 64122  2.707608 -4.839885           74            3.979972         3.992291\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 64906  4.041742 -4.844754           74            0.000103         3.992291\n",
+       " 64907  4.043444 -4.845190           74            0.000089         3.992291\n",
+       " 64908  4.045145 -4.845625           74            0.000074         3.992291\n",
+       " 64909  4.046847 -4.846061           74            0.000059         3.992291\n",
+       " 64910  4.048549 -4.846497           74            0.000045         3.992291\n",
+       " \n",
+       " [793 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 65118  2.700801 -4.839597           75            3.972947         3.980993\n",
+       " 65119  2.702502 -4.839619           75            3.971924         3.980993\n",
+       " 65120  2.704204 -4.839695           75            3.970890         3.980993\n",
+       " 65121  2.705906 -4.839771           75            3.969856         3.980993\n",
+       " 65122  2.707608 -4.839846           75            3.968824         3.980993\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 65906  4.041742 -4.843115           75            0.000103         3.980993\n",
+       " 65907  4.043444 -4.843457           75            0.000088         3.980993\n",
+       " 65908  4.045145 -4.843800           75            0.000073         3.980993\n",
+       " 65909  4.046847 -4.844142           75            0.000059         3.980993\n",
+       " 65910  4.048549 -4.844484           75            0.000044         3.980993\n",
+       " \n",
+       " [793 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 66118  2.700801 -4.839817           76            3.960813         3.968174\n",
+       " 66119  2.702502 -4.839895           76            3.959794         3.968174\n",
+       " 66120  2.704204 -4.839974           76            3.958774         3.968174\n",
+       " 66121  2.705906 -4.840009           76            3.957743         3.968174\n",
+       " 66122  2.707608 -4.840009           76            3.956702         3.968174\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 66906  4.041742 -4.842000           76            0.000101         3.968174\n",
+       " 66907  4.043444 -4.842232           76            0.000087         3.968174\n",
+       " 66908  4.045145 -4.842463           76            0.000072         3.968174\n",
+       " 66909  4.046847 -4.842694           76            0.000058         3.968174\n",
+       " 66910  4.048549 -4.842926           76            0.000043         3.968174\n",
+       " \n",
+       " [793 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 67118  2.700801 -4.839780           77            3.949652         3.957153\n",
+       " 67119  2.702502 -4.839780           77            3.948623         3.957153\n",
+       " 67120  2.704204 -4.839780           77            3.947593         3.957153\n",
+       " 67121  2.705906 -4.839817           77            3.946561         3.957153\n",
+       " 67122  2.707608 -4.839969           77            3.945518         3.957153\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 67905  4.040040 -4.843297           77            0.000111         3.957153\n",
+       " 67906  4.041742 -4.843657           77            0.000096         3.957153\n",
+       " 67907  4.043444 -4.844018           77            0.000082         3.957153\n",
+       " 67908  4.045145 -4.844378           77            0.000067         3.957153\n",
+       " 67909  4.046847 -4.844738           77            0.000052         3.957153\n",
+       " \n",
+       " [792 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 68118  2.700801 -4.839653           78            3.939151         3.946277\n",
+       " 68119  2.702502 -4.839870           78            3.938181         3.946277\n",
+       " 68120  2.704204 -4.839982           78            3.937178         3.946277\n",
+       " 68121  2.705906 -4.839904           78            3.936115         3.946277\n",
+       " 68122  2.707608 -4.839827           78            3.935051         3.946277\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 68905  4.040040 -4.842415           78            0.000109         3.946277\n",
+       " 68906  4.041742 -4.842633           78            0.000094         3.946277\n",
+       " 68907  4.043444 -4.842851           78            0.000079         3.946277\n",
+       " 68908  4.045145 -4.843069           78            0.000065         3.946277\n",
+       " 68909  4.046847 -4.843287           78            0.000050         3.946277\n",
+       " \n",
+       " [792 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 69118  2.700801 -4.839611           79            3.927950         3.935179\n",
+       " 69119  2.702502 -4.839386           79            3.926956         3.935179\n",
+       " 69120  2.704204 -4.839686           79            3.925889         3.935179\n",
+       " 69121  2.705906 -4.839986           79            3.924821         3.935179\n",
+       " 69122  2.707608 -4.840226           79            3.923764         3.935179\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 69905  4.040040 -4.844292           79            0.000108         3.935179\n",
+       " 69906  4.041742 -4.844694           79            0.000094         3.935179\n",
+       " 69907  4.043444 -4.845097           79            0.000079         3.935179\n",
+       " 69908  4.045145 -4.845499           79            0.000065         3.935179\n",
+       " 69909  4.046847 -4.845901           79            0.000050         3.935179\n",
+       " \n",
+       " [792 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 70118  2.700801 -4.839932           80            3.915649         3.924111\n",
+       " 70119  2.702502 -4.840258           80            3.914647         3.924111\n",
+       " 70120  2.704204 -4.840413           80            3.913629         3.924111\n",
+       " 70121  2.705906 -4.840263           80            3.912579         3.924111\n",
+       " 70122  2.707608 -4.840113           80            3.911530         3.924111\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 70905  4.040040 -4.843595           80            0.000106         3.924111\n",
+       " 70906  4.041742 -4.844011           80            0.000092         3.924111\n",
+       " 70907  4.043444 -4.844427           80            0.000077         3.924111\n",
+       " 70908  4.045145 -4.844843           80            0.000063         3.924111\n",
+       " 70909  4.046847 -4.845260           80            0.000048         3.924111\n",
+       " \n",
+       " [792 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 71118  2.700801 -4.839742           81            3.901664         3.910451\n",
+       " 71119  2.702502 -4.839983           81            3.900653         3.910451\n",
+       " 71120  2.704204 -4.839908           81            3.899634         3.910451\n",
+       " 71121  2.705906 -4.839833           81            3.898615         3.910451\n",
+       " 71122  2.707608 -4.839803           81            3.897582         3.910451\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 71905  4.040040 -4.844477           81            0.000103         3.910451\n",
+       " 71906  4.041742 -4.844927           81            0.000088         3.910451\n",
+       " 71907  4.043444 -4.845377           81            0.000073         3.910451\n",
+       " 71908  4.045145 -4.845827           81            0.000059         3.910451\n",
+       " 71909  4.046847 -4.846277           81            0.000044         3.910451\n",
+       " \n",
+       " [792 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 72118  2.700801 -4.840147           82            3.891107         3.898761\n",
+       " 72119  2.702502 -4.839987           82            3.890091         3.898761\n",
+       " 72120  2.704204 -4.839913           82            3.889075         3.898761\n",
+       " 72121  2.705906 -4.839839           82            3.888058         3.898761\n",
+       " 72122  2.707608 -4.839765           82            3.887034         3.898761\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 72905  4.040040 -4.843805           82            0.000104         3.898761\n",
+       " 72906  4.041742 -4.844191           82            0.000089         3.898761\n",
+       " 72907  4.043444 -4.844576           82            0.000075         3.898761\n",
+       " 72908  4.045145 -4.844962           82            0.000060         3.898761\n",
+       " 72909  4.046847 -4.845347           82            0.000046         3.898761\n",
+       " \n",
+       " [792 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 73118  2.700801 -4.839865           83            3.878302         3.886344\n",
+       " 73119  2.702502 -4.839556           83            3.877302         3.886344\n",
+       " 73120  2.704204 -4.839695           83            3.876300         3.886344\n",
+       " 73121  2.705906 -4.839841           83            3.875298         3.886344\n",
+       " 73122  2.707608 -4.839987           83            3.874295         3.886344\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 73905  4.040040 -4.842825           83            0.000099         3.886344\n",
+       " 73906  4.041742 -4.843088           83            0.000085         3.886344\n",
+       " 73907  4.043444 -4.843351           83            0.000070         3.886344\n",
+       " 73908  4.045145 -4.843614           83            0.000056         3.886344\n",
+       " 73909  4.046847 -4.843877           83            0.000041         3.886344\n",
+       " \n",
+       " [792 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 74118  2.700801 -4.840009           84            3.867149         3.875019\n",
+       " 74119  2.702502 -4.840009           84            3.866122         3.875019\n",
+       " 74120  2.704204 -4.840009           84            3.865094         3.875019\n",
+       " 74121  2.705906 -4.840009           84            3.864066         3.875019\n",
+       " 74122  2.707608 -4.840009           84            3.863030         3.875019\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 74905  4.040040 -4.843033           84            0.000100         3.875019\n",
+       " 74906  4.041742 -4.843296           84            0.000086         3.875019\n",
+       " 74907  4.043444 -4.843558           84            0.000071         3.875019\n",
+       " 74908  4.045145 -4.843820           84            0.000057         3.875019\n",
+       " 74909  4.046847 -4.844082           84            0.000042         3.875019\n",
+       " \n",
+       " [792 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 75118  2.700801 -4.840011           85            3.854026         3.862498\n",
+       " 75119  2.702502 -4.840085           85            3.853018         3.862498\n",
+       " 75120  2.704204 -4.840158           85            3.852009         3.862498\n",
+       " 75121  2.705906 -4.840232           85            3.851001         3.862498\n",
+       " 75122  2.707608 -4.840238           85            3.849981         3.862498\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 75905  4.040040 -4.843720           85            0.000099         3.862498\n",
+       " 75906  4.041742 -4.844044           85            0.000084         3.862498\n",
+       " 75907  4.043444 -4.844368           85            0.000070         3.862498\n",
+       " 75908  4.045145 -4.844692           85            0.000056         3.862498\n",
+       " 75909  4.046847 -4.845016           85            0.000041         3.862498\n",
+       " \n",
+       " [792 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 76118  2.700801 -4.839894           86            3.844079         3.851625\n",
+       " 76119  2.702502 -4.839970           86            3.843077         3.851625\n",
+       " 76120  2.704204 -4.839895           86            3.842058         3.851625\n",
+       " 76121  2.705906 -4.839820           86            3.841039         3.851625\n",
+       " 76122  2.707608 -4.839745           86            3.840009         3.851625\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 76905  4.040040 -4.843144           86            0.000100         3.851625\n",
+       " 76906  4.041742 -4.843435           86            0.000085         3.851625\n",
+       " 76907  4.043444 -4.843725           86            0.000071         3.851625\n",
+       " 76908  4.045145 -4.844016           86            0.000057         3.851625\n",
+       " 76909  4.046847 -4.844306           86            0.000042         3.851625\n",
+       " \n",
+       " [792 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 77118  2.700801 -4.840101           87            3.831159         3.839479\n",
+       " 77119  2.702502 -4.840216           87            3.830143         3.839479\n",
+       " 77120  2.704204 -4.840140           87            3.829125         3.839479\n",
+       " 77121  2.705906 -4.840065           87            3.828106         3.839479\n",
+       " 77122  2.707608 -4.839990           87            3.827080         3.839479\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 77904  4.038338 -4.843245           87            0.000110         3.839479\n",
+       " 77905  4.040040 -4.843571           87            0.000095         3.839479\n",
+       " 77906  4.041742 -4.843897           87            0.000081         3.839479\n",
+       " 77907  4.043444 -4.844223           87            0.000066         3.839479\n",
+       " 77908  4.045145 -4.844549           87            0.000052         3.839479\n",
+       " \n",
+       " [791 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 78118  2.700801 -4.839780           88            3.816310         3.825625\n",
+       " 78119  2.702502 -4.839780           88            3.815311         3.825625\n",
+       " 78120  2.704204 -4.839780           88            3.814269         3.825625\n",
+       " 78121  2.705906 -4.839780           88            3.813219         3.825625\n",
+       " 78122  2.707608 -4.839780           88            3.812170         3.825625\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 78904  4.038338 -4.843763           88            0.000108         3.825625\n",
+       " 78905  4.040040 -4.844134           88            0.000093         3.825625\n",
+       " 78906  4.041742 -4.844505           88            0.000079         3.825625\n",
+       " 78907  4.043444 -4.844877           88            0.000064         3.825625\n",
+       " 78908  4.045145 -4.845248           88            0.000050         3.825625\n",
+       " \n",
+       " [791 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 79118  2.700801 -4.839984           89            3.805041         3.813699\n",
+       " 79119  2.702502 -4.840081           89            3.804040         3.813699\n",
+       " 79120  2.704204 -4.840155           89            3.803041         3.813699\n",
+       " 79121  2.705906 -4.840229           89            3.802041         3.813699\n",
+       " 79122  2.707608 -4.840104           89            3.800996         3.813699\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 79902  4.034935 -4.839342           89            0.000128         3.813699\n",
+       " 79903  4.036637 -4.839239           89            0.000112         3.813699\n",
+       " 79904  4.038338 -4.839135           89            0.000096         3.813699\n",
+       " 79905  4.040040 -4.839032           89            0.000079         3.813699\n",
+       " 79906  4.041742 -4.838929           89            0.000063         3.813699\n",
+       " \n",
+       " [789 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 80118  2.700801 -4.839368           90            3.793230         3.801251\n",
+       " 80119  2.702502 -4.839601           90            3.792181         3.801251\n",
+       " 80120  2.704204 -4.839832           90            3.791131         3.801251\n",
+       " 80121  2.705906 -4.839992           90            3.790082         3.801251\n",
+       " 80122  2.707608 -4.839916           90            3.789032         3.801251\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 80904  4.038338 -4.843840           90            0.000105         3.801251\n",
+       " 80905  4.040040 -4.844209           90            0.000090         3.801251\n",
+       " 80906  4.041742 -4.844578           90            0.000076         3.801251\n",
+       " 80907  4.043444 -4.844947           90            0.000061         3.801251\n",
+       " 80908  4.045145 -4.845316           90            0.000047         3.801251\n",
+       " \n",
+       " [791 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 81118  2.700801 -4.839790           91            3.782242         3.789964\n",
+       " 81119  2.702502 -4.839940           91            3.781223         3.789964\n",
+       " 81120  2.704204 -4.840090           91            3.780204         3.789964\n",
+       " 81121  2.705906 -4.840238           91            3.779185         3.789964\n",
+       " 81122  2.707608 -4.840238           91            3.778140         3.789964\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 81904  4.038338 -4.843296           91            0.000105         3.789964\n",
+       " 81905  4.040040 -4.843633           91            0.000090         3.789964\n",
+       " 81906  4.041742 -4.843971           91            0.000076         3.789964\n",
+       " 81907  4.043444 -4.844308           91            0.000061         3.789964\n",
+       " 81908  4.045145 -4.844645           91            0.000047         3.789964\n",
+       " \n",
+       " [791 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 82118  2.700801 -4.840009           92            3.770985         3.778757\n",
+       " 82119  2.702502 -4.840009           92            3.770032         3.778757\n",
+       " 82120  2.704204 -4.840043           92            3.769040         3.778757\n",
+       " 82121  2.705906 -4.840118           92            3.767999         3.778757\n",
+       " 82122  2.707608 -4.840193           92            3.766958         3.778757\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 82904  4.038338 -4.843404           92            0.000103         3.778757\n",
+       " 82905  4.040040 -4.843727           92            0.000088         3.778757\n",
+       " 82906  4.041742 -4.844050           92            0.000074         3.778757\n",
+       " 82907  4.043444 -4.844373           92            0.000060         3.778757\n",
+       " 82908  4.045145 -4.844696           92            0.000045         3.778757\n",
+       " \n",
+       " [791 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 83118  2.700801 -4.840233           93            3.758488         3.766853\n",
+       " 83119  2.702502 -4.840159           93            3.757506         3.766853\n",
+       " 83120  2.704204 -4.840086           93            3.756524         3.766853\n",
+       " 83121  2.705906 -4.840012           93            3.755541         3.766853\n",
+       " 83122  2.707608 -4.840083           93            3.754483         3.766853\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 83904  4.038338 -4.843047           93            0.000101         3.766853\n",
+       " 83905  4.040040 -4.843350           93            0.000087         3.766853\n",
+       " 83906  4.041742 -4.843653           93            0.000073         3.766853\n",
+       " 83907  4.043444 -4.843956           93            0.000059         3.766853\n",
+       " 83908  4.045145 -4.844259           93            0.000044         3.766853\n",
+       " \n",
+       " [791 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 84118  2.700801 -4.840366           94            3.747813         3.755125\n",
+       " 84119  2.702502 -4.840148           94            3.746843         3.755125\n",
+       " 84120  2.704204 -4.839954           94            3.745840         3.755125\n",
+       " 84121  2.705906 -4.839799           94            3.744776         3.755125\n",
+       " 84122  2.707608 -4.839644           94            3.743713         3.755125\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 84904  4.038338 -4.844692           94            0.000098         3.755125\n",
+       " 84905  4.040040 -4.845117           94            0.000083         3.755125\n",
+       " 84906  4.041742 -4.845542           94            0.000069         3.755125\n",
+       " 84907  4.043444 -4.845968           94            0.000055         3.755125\n",
+       " 84908  4.045145 -4.846394           94            0.000041         3.755125\n",
+       " \n",
+       " [791 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 85118  2.700801 -4.839677           95            3.737521         3.744543\n",
+       " 85119  2.702502 -4.839455           95            3.736537         3.744543\n",
+       " 85120  2.704204 -4.839412           95            3.735534         3.744543\n",
+       " 85121  2.705906 -4.839634           95            3.734504         3.744543\n",
+       " 85122  2.707608 -4.839856           95            3.733474         3.744543\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 85903  4.036637 -4.844160           95            0.000110         3.744543\n",
+       " 85904  4.038338 -4.844615           95            0.000096         3.744543\n",
+       " 85905  4.040040 -4.845069           95            0.000082         3.744543\n",
+       " 85906  4.041742 -4.845524           95            0.000068         3.744543\n",
+       " 85907  4.043444 -4.845978           95            0.000053         3.744543\n",
+       " \n",
+       " [790 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 86118  2.700801 -4.840009           96            3.725731         3.733378\n",
+       " 86119  2.702502 -4.840009           96            3.724719         3.733378\n",
+       " 86120  2.704204 -4.840009           96            3.723707         3.733378\n",
+       " 86121  2.705906 -4.840009           96            3.722696         3.733378\n",
+       " 86122  2.707608 -4.840009           96            3.721685         3.733378\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 86903  4.036637 -4.843191           96            0.000104         3.733378\n",
+       " 86904  4.038338 -4.843449           96            0.000090         3.733378\n",
+       " 86905  4.040040 -4.843707           96            0.000076         3.733378\n",
+       " 86906  4.041742 -4.843966           96            0.000061         3.733378\n",
+       " 86907  4.043444 -4.844224           96            0.000047         3.733378\n",
+       " \n",
+       " [790 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 87118  2.700801 -4.839551           97            3.712551         3.720451\n",
+       " 87119  2.702502 -4.839551           97            3.711557         3.720451\n",
+       " 87120  2.704204 -4.839599           97            3.710553         3.720451\n",
+       " 87121  2.705906 -4.839749           97            3.709526         3.720451\n",
+       " 87122  2.707608 -4.839899           97            3.708498         3.720451\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 87903  4.036637 -4.842200           97            0.000101         3.720451\n",
+       " 87904  4.038338 -4.842381           97            0.000087         3.720451\n",
+       " 87905  4.040040 -4.842562           97            0.000073         3.720451\n",
+       " 87906  4.041742 -4.842742           97            0.000059         3.720451\n",
+       " 87907  4.043444 -4.842923           97            0.000045         3.720451\n",
+       " \n",
+       " [790 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 88118  2.700801 -4.839481           98            3.702236         3.709437\n",
+       " 88119  2.702502 -4.839798           98            3.701209         3.709437\n",
+       " 88120  2.704204 -4.839949           98            3.700204         3.709437\n",
+       " 88121  2.705906 -4.840099           98            3.699198         3.709437\n",
+       " 88122  2.707608 -4.840233           98            3.698192         3.709437\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 88903  4.036637 -4.843170           98            0.000099         3.709437\n",
+       " 88904  4.038338 -4.843459           98            0.000084         3.709437\n",
+       " 88905  4.040040 -4.843747           98            0.000070         3.709437\n",
+       " 88906  4.041742 -4.844036           98            0.000056         3.709437\n",
+       " 88907  4.043444 -4.844325           98            0.000041         3.709437\n",
+       " \n",
+       " [790 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 89118  2.700801 -4.840009           99            3.689188         3.697786\n",
+       " 89119  2.702502 -4.840009           99            3.688203         3.697786\n",
+       " 89120  2.704204 -4.840009           99            3.687203         3.697786\n",
+       " 89121  2.705906 -4.840009           99            3.686162         3.697786\n",
+       " 89122  2.707608 -4.840009           99            3.685122         3.697786\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 89902  4.034935 -4.843946           99            0.000109         3.697786\n",
+       " 89903  4.036637 -4.844261           99            0.000095         3.697786\n",
+       " 89904  4.038338 -4.844576           99            0.000081         3.697786\n",
+       " 89905  4.040040 -4.844892           99            0.000067         3.697786\n",
+       " 89906  4.041742 -4.845207           99            0.000053         3.697786\n",
+       " \n",
+       " [789 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 90118  2.700801 -4.839622          100            3.678584         3.686718\n",
+       " 90119  2.702502 -4.839772          100            3.677605         3.686718\n",
+       " 90120  2.704204 -4.839852          100            3.676583         3.686718\n",
+       " 90121  2.705906 -4.839928          100            3.675558         3.686718\n",
+       " 90122  2.707608 -4.840004          100            3.674533         3.686718\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 90902  4.034935 -4.843928          100            0.000108         3.686718\n",
+       " 90903  4.036637 -4.844347          100            0.000094         3.686718\n",
+       " 90904  4.038338 -4.844767          100            0.000080         3.686718\n",
+       " 90905  4.040040 -4.845186          100            0.000066         3.686718\n",
+       " 90906  4.041742 -4.845605          100            0.000052         3.686718\n",
+       " \n",
+       " [789 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 91118  2.700801 -4.839655          101            3.669010         3.676453\n",
+       " 91119  2.702502 -4.839780          101            3.667979         3.676453\n",
+       " 91120  2.704204 -4.839780          101            3.666996         3.676453\n",
+       " 91121  2.705906 -4.839780          101            3.666014         3.676453\n",
+       " 91122  2.707608 -4.839780          101            3.665009         3.676453\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 91902  4.034935 -4.844877          101            0.000105         3.676453\n",
+       " 91903  4.036637 -4.845359          101            0.000091         3.676453\n",
+       " 91904  4.038338 -4.845840          101            0.000077         3.676453\n",
+       " 91905  4.040040 -4.846323          101            0.000063         3.676453\n",
+       " 91906  4.041742 -4.846805          101            0.000049         3.676453\n",
+       " \n",
+       " [789 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 92118  2.700801 -4.839817          102            3.658368         3.665819\n",
+       " 92119  2.702502 -4.839894          102            3.657368         3.665819\n",
+       " 92120  2.704204 -4.839971          102            3.656368         3.665819\n",
+       " 92121  2.705906 -4.840048          102            3.655363         3.665819\n",
+       " 92122  2.707608 -4.840124          102            3.654351         3.665819\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 92902  4.034935 -4.842976          102            0.000104         3.665819\n",
+       " 92903  4.036637 -4.843230          102            0.000089         3.665819\n",
+       " 92904  4.038338 -4.843484          102            0.000075         3.665819\n",
+       " 92905  4.040040 -4.843739          102            0.000061         3.665819\n",
+       " 92906  4.041742 -4.843994          102            0.000047         3.665819\n",
+       " \n",
+       " [789 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 93118  2.700801 -4.840353          103            3.649407         3.656236\n",
+       " 93119  2.702502 -4.840120          103            3.648398         3.656236\n",
+       " 93120  2.704204 -4.839895          103            3.647392         3.656236\n",
+       " 93121  2.705906 -4.839670          103            3.646387         3.656236\n",
+       " 93122  2.707608 -4.839622          103            3.645374         3.656236\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 93902  4.034935 -4.843277          103            0.000103         3.656236\n",
+       " 93903  4.036637 -4.843623          103            0.000088         3.656236\n",
+       " 93904  4.038338 -4.843969          103            0.000074         3.656236\n",
+       " 93905  4.040040 -4.844316          103            0.000060         3.656236\n",
+       " 93906  4.041742 -4.844662          103            0.000046         3.656236\n",
+       " \n",
+       " [789 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 94118  2.700801 -4.840009          104            3.636462         3.645391\n",
+       " 94119  2.702502 -4.840009          104            3.635441         3.645391\n",
+       " 94120  2.704204 -4.840009          104            3.634420         3.645391\n",
+       " 94121  2.705906 -4.840034          104            3.633408         3.645391\n",
+       " 94122  2.707608 -4.840109          104            3.632416         3.645391\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 94902  4.034935 -4.842510          104            0.000098         3.645391\n",
+       " 94903  4.036637 -4.842735          104            0.000084         3.645391\n",
+       " 94904  4.038338 -4.842961          104            0.000070         3.645391\n",
+       " 94905  4.040040 -4.843187          104            0.000056         3.645391\n",
+       " 94906  4.041742 -4.843413          104            0.000042         3.645391\n",
+       " \n",
+       " [789 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 95118  2.700801 -4.840101          105            3.626051         3.633273\n",
+       " 95119  2.702502 -4.839806          105            3.625059         3.633273\n",
+       " 95120  2.704204 -4.839561          105            3.624061         3.633273\n",
+       " 95121  2.705906 -4.839637          105            3.623020         3.633273\n",
+       " 95122  2.707608 -4.839712          105            3.621979         3.633273\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 95901  4.033233 -4.844070          105            0.000111         3.633273\n",
+       " 95902  4.034935 -4.844499          105            0.000096         3.633273\n",
+       " 95903  4.036637 -4.844926          105            0.000082         3.633273\n",
+       " 95904  4.038338 -4.845355          105            0.000068         3.633273\n",
+       " 95905  4.040040 -4.845782          105            0.000053         3.633273\n",
+       " \n",
+       " [788 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 96118  2.700801 -4.839856          106            3.615440         3.622563\n",
+       " 96119  2.702502 -4.840018          106            3.614412         3.622563\n",
+       " 96120  2.704204 -4.840180          106            3.613384         3.622563\n",
+       " 96121  2.705906 -4.840238          106            3.612359         3.622563\n",
+       " 96122  2.707608 -4.840238          106            3.611335         3.622563\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 96901  4.033233 -4.842944          106            0.000106         3.622563\n",
+       " 96902  4.034935 -4.843246          106            0.000092         3.622563\n",
+       " 96903  4.036637 -4.843548          106            0.000078         3.622563\n",
+       " 96904  4.038338 -4.843850          106            0.000064         3.622563\n",
+       " 96905  4.040040 -4.844152          106            0.000049         3.622563\n",
+       " \n",
+       " [788 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 97118  2.700801 -4.839872          107            3.606350         3.612914\n",
+       " 97119  2.702502 -4.839986          107            3.605348         3.612914\n",
+       " 97120  2.704204 -4.839910          107            3.604350         3.612914\n",
+       " 97121  2.705906 -4.839834          107            3.603352         3.612914\n",
+       " 97122  2.707608 -4.839780          107            3.602341         3.612914\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 97901  4.033233 -4.844110          107            0.000107         3.612914\n",
+       " 97902  4.034935 -4.844501          107            0.000092         3.612914\n",
+       " 97903  4.036637 -4.844893          107            0.000078         3.612914\n",
+       " 97904  4.038338 -4.845284          107            0.000064         3.612914\n",
+       " 97905  4.040040 -4.845676          107            0.000050         3.612914\n",
+       " \n",
+       " [788 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 98118  2.700801 -4.839901          108            3.595955          3.60376\n",
+       " 98119  2.702502 -4.839669          108            3.594947          3.60376\n",
+       " 98120  2.704204 -4.839551          108            3.593926          3.60376\n",
+       " 98121  2.705906 -4.839551          108            3.592895          3.60376\n",
+       " 98122  2.707608 -4.839551          108            3.591863          3.60376\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 98901  4.033233 -4.844304          108            0.000103          3.60376\n",
+       " 98902  4.034935 -4.844727          108            0.000089          3.60376\n",
+       " 98903  4.036637 -4.845150          108            0.000075          3.60376\n",
+       " 98904  4.038338 -4.845573          108            0.000060          3.60376\n",
+       " 98905  4.040040 -4.845996          108            0.000046          3.60376\n",
+       " \n",
+       " [788 rows x 5 columns],\n",
+       "         voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 99118  2.700801 -4.840048          109            3.586137         3.592937\n",
+       " 99119  2.702502 -4.840132          109            3.585149         3.592937\n",
+       " 99120  2.704204 -4.840216          109            3.584161         3.592937\n",
+       " 99121  2.705906 -4.840183          109            3.583135         3.592937\n",
+       " 99122  2.707608 -4.840108          109            3.582094         3.592937\n",
+       " ...         ...       ...          ...                 ...              ...\n",
+       " 99901  4.033233 -4.844245          109            0.000102         3.592937\n",
+       " 99902  4.034935 -4.844638          109            0.000088         3.592937\n",
+       " 99903  4.036637 -4.845030          109            0.000073         3.592937\n",
+       " 99904  4.038338 -4.845423          109            0.000059         3.592937\n",
+       " 99905  4.040040 -4.845816          109            0.000045         3.592937\n",
+       " \n",
+       " [788 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 100118  2.700801 -4.839827          110            3.575907         3.582862\n",
+       " 100119  2.702502 -4.839927          110            3.574978         3.582862\n",
+       " 100120  2.704204 -4.840009          110            3.574020         3.582862\n",
+       " 100121  2.705906 -4.840009          110            3.572929         3.582862\n",
+       " 100122  2.707608 -4.840009          110            3.571839         3.582862\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 100901  4.033233 -4.843418          110            0.000099         3.582862\n",
+       " 100902  4.034935 -4.843748          110            0.000085         3.582862\n",
+       " 100903  4.036637 -4.844078          110            0.000071         3.582862\n",
+       " 100904  4.038338 -4.844409          110            0.000057         3.582862\n",
+       " 100905  4.040040 -4.844739          110            0.000043         3.582862\n",
+       " \n",
+       " [788 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 101118  2.700801 -4.839970          111            3.567271         3.573931\n",
+       " 101119  2.702502 -4.839884          111            3.566247         3.573931\n",
+       " 101120  2.704204 -4.839799          111            3.565222         3.573931\n",
+       " 101121  2.705906 -4.839838          111            3.564207         3.573931\n",
+       " 101122  2.707608 -4.839912          111            3.563194         3.573931\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 101901  4.033233 -4.843665          111            0.000099         3.573931\n",
+       " 101902  4.034935 -4.843995          111            0.000085         3.573931\n",
+       " 101903  4.036637 -4.844324          111            0.000071         3.573931\n",
+       " 101904  4.038338 -4.844653          111            0.000056         3.573931\n",
+       " 101905  4.040040 -4.844983          111            0.000042         3.573931\n",
+       " \n",
+       " [788 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 102118  2.700801 -4.840009          112            3.558630         3.564821\n",
+       " 102119  2.702502 -4.840009          112            3.557641         3.564821\n",
+       " 102120  2.704204 -4.839949          112            3.556614         3.564821\n",
+       " 102121  2.705906 -4.839873          112            3.555578         3.564821\n",
+       " 102122  2.707608 -4.839798          112            3.554542         3.564821\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 102900  4.031531 -4.843357          112            0.000108         3.564821\n",
+       " 102901  4.033233 -4.843659          112            0.000094         3.564821\n",
+       " 102902  4.034935 -4.843961          112            0.000080         3.564821\n",
+       " 102903  4.036637 -4.844263          112            0.000066         3.564821\n",
+       " 102904  4.038338 -4.844565          112            0.000052         3.564821\n",
+       " \n",
+       " [787 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 103118  2.700801 -4.839843          113            3.548180         3.555725\n",
+       " 103119  2.702502 -4.839977          113            3.547154         3.555725\n",
+       " 103120  2.704204 -4.840009          113            3.546124         3.555725\n",
+       " 103121  2.705906 -4.840009          113            3.545092         3.555725\n",
+       " 103122  2.707608 -4.840009          113            3.544060         3.555725\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 103900  4.031531 -4.843545          113            0.000105         3.555725\n",
+       " 103901  4.033233 -4.843920          113            0.000091         3.555725\n",
+       " 103902  4.034935 -4.844296          113            0.000076         3.555725\n",
+       " 103903  4.036637 -4.844671          113            0.000062         3.555725\n",
+       " 103904  4.038338 -4.845047          113            0.000048         3.555725\n",
+       " \n",
+       " [787 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 104118  2.700801 -4.840009          114            3.539206         3.545244\n",
+       " 104119  2.702502 -4.840009          114            3.538195         3.545244\n",
+       " 104120  2.704204 -4.840009          114            3.537189         3.545244\n",
+       " 104121  2.705906 -4.840009          114            3.536184         3.545244\n",
+       " 104122  2.707608 -4.840009          114            3.535178         3.545244\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 104900  4.031531 -4.843968          114            0.000103         3.545244\n",
+       " 104901  4.033233 -4.844359          114            0.000089         3.545244\n",
+       " 104902  4.034935 -4.844749          114            0.000075         3.545244\n",
+       " 104903  4.036637 -4.845140          114            0.000061         3.545244\n",
+       " 104904  4.038338 -4.845530          114            0.000047         3.545244\n",
+       " \n",
+       " [787 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 105118  2.700801 -4.839855          115            3.531228         3.536793\n",
+       " 105119  2.702502 -4.840007          115            3.530234         3.536793\n",
+       " 105120  2.704204 -4.839932          115            3.529197         3.536793\n",
+       " 105121  2.705906 -4.839857          115            3.528161         3.536793\n",
+       " 105122  2.707608 -4.839782          115            3.527125         3.536793\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 105900  4.031531 -4.843238          115            0.000100         3.536793\n",
+       " 105901  4.033233 -4.843552          115            0.000086         3.536793\n",
+       " 105902  4.034935 -4.843866          115            0.000072         3.536793\n",
+       " 105903  4.036637 -4.844181          115            0.000058         3.536793\n",
+       " 105904  4.038338 -4.844495          115            0.000044         3.536793\n",
+       " \n",
+       " [787 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 106118  2.700801 -4.839758          116            3.522978         3.529334\n",
+       " 106119  2.702502 -4.839682          116            3.521940         3.529334\n",
+       " 106120  2.704204 -4.839606          116            3.520901         3.529334\n",
+       " 106121  2.705906 -4.839635          116            3.519865         3.529334\n",
+       " 106122  2.707608 -4.839931          116            3.518835         3.529334\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 106900  4.031531 -4.844060          116            0.000099         3.529334\n",
+       " 106901  4.033233 -4.844403          116            0.000085         3.529334\n",
+       " 106902  4.034935 -4.844747          116            0.000071         3.529334\n",
+       " 106903  4.036637 -4.845090          116            0.000057         3.529334\n",
+       " 106904  4.038338 -4.845433          116            0.000043         3.529334\n",
+       " \n",
+       " [787 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 107118  2.700801 -4.839896          117            3.515166          3.52086\n",
+       " 107119  2.702502 -4.839780          117            3.514181          3.52086\n",
+       " 107120  2.704204 -4.839780          117            3.513197          3.52086\n",
+       " 107121  2.705906 -4.839780          117            3.512212          3.52086\n",
+       " 107122  2.707608 -4.839780          117            3.511186          3.52086\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 107900  4.031531 -4.843208          117            0.000097          3.52086\n",
+       " 107901  4.033233 -4.843491          117            0.000083          3.52086\n",
+       " 107902  4.034935 -4.843773          117            0.000069          3.52086\n",
+       " 107903  4.036637 -4.844056          117            0.000055          3.52086\n",
+       " 107904  4.038338 -4.844339          117            0.000041          3.52086\n",
+       " \n",
+       " [787 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 108118  2.700801 -4.839872          118            3.506390         3.512999\n",
+       " 108119  2.702502 -4.839780          118            3.505396         3.512999\n",
+       " 108120  2.704204 -4.839780          118            3.504408         3.512999\n",
+       " 108121  2.705906 -4.839780          118            3.503420         3.512999\n",
+       " 108122  2.707608 -4.839906          118            3.502388         3.512999\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 108899  4.029830 -4.843032          118            0.000109         3.512999\n",
+       " 108900  4.031531 -4.843298          118            0.000095         3.512999\n",
+       " 108901  4.033233 -4.843565          118            0.000081         3.512999\n",
+       " 108902  4.034935 -4.843831          118            0.000067         3.512999\n",
+       " 108903  4.036637 -4.844098          118            0.000053         3.512999\n",
+       " \n",
+       " [786 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 109118  2.700801 -4.839782          119            3.496947         3.503677\n",
+       " 109119  2.702502 -4.839856          119            3.495934         3.503677\n",
+       " 109120  2.704204 -4.839930          119            3.494922         3.503677\n",
+       " 109121  2.705906 -4.840003          119            3.493909         3.503677\n",
+       " 109122  2.707608 -4.839941          119            3.492881         3.503677\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 109899  4.029830 -4.844460          119            0.000105         3.503677\n",
+       " 109900  4.031531 -4.844872          119            0.000092         3.503677\n",
+       " 109901  4.033233 -4.845284          119            0.000078         3.503677\n",
+       " 109902  4.034935 -4.845695          119            0.000064         3.503677\n",
+       " 109903  4.036637 -4.846107          119            0.000050         3.503677\n",
+       " \n",
+       " [786 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 110118  2.700801 -4.839816          120            3.490125          3.49508\n",
+       " 110119  2.702502 -4.839892          120            3.489123          3.49508\n",
+       " 110120  2.704204 -4.839968          120            3.488120          3.49508\n",
+       " 110121  2.705906 -4.840009          120            3.487100          3.49508\n",
+       " 110122  2.707608 -4.840009          120            3.486059          3.49508\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 110899  4.029830 -4.844700          120            0.000103          3.49508\n",
+       " 110900  4.031531 -4.845134          120            0.000089          3.49508\n",
+       " 110901  4.033233 -4.845568          120            0.000075          3.49508\n",
+       " 110902  4.034935 -4.846003          120            0.000061          3.49508\n",
+       " 110903  4.036637 -4.846437          120            0.000047          3.49508\n",
+       " \n",
+       " [786 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 111118  2.700801 -4.840009          121            3.480037         3.486813\n",
+       " 111119  2.702502 -4.840009          121            3.479025         3.486813\n",
+       " 111120  2.704204 -4.840009          121            3.478012         3.486813\n",
+       " 111121  2.705906 -4.839954          121            3.476998         3.486813\n",
+       " 111122  2.707608 -4.839879          121            3.475984         3.486813\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 111899  4.029830 -4.843527          121            0.000099         3.486813\n",
+       " 111900  4.031531 -4.843884          121            0.000085         3.486813\n",
+       " 111901  4.033233 -4.844240          121            0.000071         3.486813\n",
+       " 111902  4.034935 -4.844596          121            0.000057         3.486813\n",
+       " 111903  4.036637 -4.844952          121            0.000043         3.486813\n",
+       " \n",
+       " [786 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 112118  2.700801 -4.840177          122            3.473931         3.479208\n",
+       " 112119  2.702502 -4.840368          122            3.472950         3.479208\n",
+       " 112120  2.704204 -4.840218          122            3.471944         3.479208\n",
+       " 112121  2.705906 -4.840068          122            3.470939         3.479208\n",
+       " 112122  2.707608 -4.840009          122            3.469896         3.479208\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 112899  4.029830 -4.842865          122            0.000097         3.479208\n",
+       " 112900  4.031531 -4.843118          122            0.000083         3.479208\n",
+       " 112901  4.033233 -4.843372          122            0.000069         3.479208\n",
+       " 112902  4.034935 -4.843626          122            0.000055         3.479208\n",
+       " 112903  4.036637 -4.843880          122            0.000041         3.479208\n",
+       " \n",
+       " [786 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 113118  2.700801 -4.839948          123            3.465178          3.47114\n",
+       " 113119  2.702502 -4.839818          123            3.464186          3.47114\n",
+       " 113120  2.704204 -4.839885          123            3.463183          3.47114\n",
+       " 113121  2.705906 -4.840031          123            3.462177          3.47114\n",
+       " 113122  2.707608 -4.840177          123            3.461170          3.47114\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 113898  4.028128 -4.844158          123            0.000107          3.47114\n",
+       " 113899  4.029830 -4.844529          123            0.000094          3.47114\n",
+       " 113900  4.031531 -4.844900          123            0.000080          3.47114\n",
+       " 113901  4.033233 -4.845271          123            0.000066          3.47114\n",
+       " 113902  4.034935 -4.845642          123            0.000052          3.47114\n",
+       " \n",
+       " [785 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 114118  2.700801 -4.839501          124            3.458569         3.464636\n",
+       " 114119  2.702502 -4.839392          124            3.457561         3.464636\n",
+       " 114120  2.704204 -4.839375          124            3.456547         3.464636\n",
+       " 114121  2.705906 -4.839524          124            3.455521         3.464636\n",
+       " 114122  2.707608 -4.839672          124            3.454495         3.464636\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 114898  4.028128 -4.843181          124            0.000106         3.464636\n",
+       " 114899  4.029830 -4.843479          124            0.000092         3.464636\n",
+       " 114900  4.031531 -4.843777          124            0.000078         3.464636\n",
+       " 114901  4.033233 -4.844074          124            0.000064         3.464636\n",
+       " 114902  4.034935 -4.844372          124            0.000050         3.464636\n",
+       " \n",
+       " [785 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 115118  2.700801 -4.840009          125            3.450583         3.456607\n",
+       " 115119  2.702502 -4.840009          125            3.449573         3.456607\n",
+       " 115120  2.704204 -4.840009          125            3.448563         3.456607\n",
+       " 115121  2.705906 -4.840009          125            3.447540         3.456607\n",
+       " 115122  2.707608 -4.840009          125            3.446512         3.456607\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 115898  4.028128 -4.843570          125            0.000103         3.456607\n",
+       " 115899  4.029830 -4.843894          125            0.000089         3.456607\n",
+       " 115900  4.031531 -4.844219          125            0.000075         3.456607\n",
+       " 115901  4.033233 -4.844544          125            0.000061         3.456607\n",
+       " 115902  4.034935 -4.844868          125            0.000047         3.456607\n",
+       " \n",
+       " [785 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 116118  2.700801 -4.839872          126            3.444250         3.450202\n",
+       " 116119  2.702502 -4.839577          126            3.443270         3.450202\n",
+       " 116120  2.704204 -4.839343          126            3.442279         3.450202\n",
+       " 116121  2.705906 -4.839496          126            3.441218         3.450202\n",
+       " 116122  2.707608 -4.839648          126            3.440157         3.450202\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 116898  4.028128 -4.844089          126            0.000103         3.450202\n",
+       " 116899  4.029830 -4.844501          126            0.000089         3.450202\n",
+       " 116900  4.031531 -4.844913          126            0.000075         3.450202\n",
+       " 116901  4.033233 -4.845325          126            0.000061         3.450202\n",
+       " 116902  4.034935 -4.845737          126            0.000047         3.450202\n",
+       " \n",
+       " [785 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 117118  2.700801 -4.839551          127            3.436082         3.441898\n",
+       " 117119  2.702502 -4.839551          127            3.435085         3.441898\n",
+       " 117120  2.704204 -4.839602          127            3.434079         3.441898\n",
+       " 117121  2.705906 -4.839677          127            3.433069         3.441898\n",
+       " 117122  2.707608 -4.839752          127            3.432060         3.441898\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 117898  4.028128 -4.844397          127            0.000098         3.441898\n",
+       " 117899  4.029830 -4.844763          127            0.000085         3.441898\n",
+       " 117900  4.031531 -4.845129          127            0.000071         3.441898\n",
+       " 117901  4.033233 -4.845494          127            0.000057         3.441898\n",
+       " 117902  4.034935 -4.845860          127            0.000043         3.441898\n",
+       " \n",
+       " [785 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 118118  2.700801 -4.839845          128            3.427220         3.433833\n",
+       " 118119  2.702502 -4.839983          128            3.426248         3.433833\n",
+       " 118120  2.704204 -4.839890          128            3.425250         3.433833\n",
+       " 118121  2.705906 -4.839742          128            3.424246         3.433833\n",
+       " 118122  2.707608 -4.839594          128            3.423242         3.433833\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 118898  4.028128 -4.842945          128            0.000096         3.433833\n",
+       " 118899  4.029830 -4.843178          128            0.000082         3.433833\n",
+       " 118900  4.031531 -4.843411          128            0.000068         3.433833\n",
+       " 118901  4.033233 -4.843645          128            0.000055         3.433833\n",
+       " 118902  4.034935 -4.843878          128            0.000041         3.433833\n",
+       " \n",
+       " [785 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 119118  2.700801 -4.840119          129            3.419982         3.425259\n",
+       " 119119  2.702502 -4.839864          129            3.418970         3.425259\n",
+       " 119120  2.704204 -4.839780          129            3.417963         3.425259\n",
+       " 119121  2.705906 -4.839780          129            3.416957         3.425259\n",
+       " 119122  2.707608 -4.839780          129            3.415952         3.425259\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 119897  4.026426 -4.844031          129            0.000107         3.425259\n",
+       " 119898  4.028128 -4.844427          129            0.000093         3.425259\n",
+       " 119899  4.029830 -4.844823          129            0.000079         3.425259\n",
+       " 119900  4.031531 -4.845219          129            0.000066         3.425259\n",
+       " 119901  4.033233 -4.845615          129            0.000052         3.425259\n",
+       " \n",
+       " [784 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 120118  2.700801 -4.839643          130            3.411809         3.418534\n",
+       " 120119  2.702502 -4.839758          130            3.410830         3.418534\n",
+       " 120120  2.704204 -4.839684          130            3.409852         3.418534\n",
+       " 120121  2.705906 -4.839610          130            3.408874         3.418534\n",
+       " 120122  2.707608 -4.839583          130            3.407876         3.418534\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 120897  4.026426 -4.843990          130            0.000103         3.418534\n",
+       " 120898  4.028128 -4.844376          130            0.000089         3.418534\n",
+       " 120899  4.029830 -4.844762          130            0.000075         3.418534\n",
+       " 120900  4.031531 -4.845148          130            0.000061         3.418534\n",
+       " 120901  4.033233 -4.845534          130            0.000047         3.418534\n",
+       " \n",
+       " [784 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 121118  2.700801 -4.840051          131            3.403858         3.408937\n",
+       " 121119  2.702502 -4.840140          131            3.402863         3.408937\n",
+       " 121120  2.704204 -4.840230          131            3.401869         3.408937\n",
+       " 121121  2.705906 -4.840103          131            3.400850         3.408937\n",
+       " 121122  2.707608 -4.839955          131            3.399829         3.408937\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 121897  4.026426 -4.842902          131            0.000100         3.408937\n",
+       " 121898  4.028128 -4.843176          131            0.000087         3.408937\n",
+       " 121899  4.029830 -4.843451          131            0.000073         3.408937\n",
+       " 121900  4.031531 -4.843726          131            0.000060         3.408937\n",
+       " 121901  4.033233 -4.844001          131            0.000046         3.408937\n",
+       " \n",
+       " [784 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 122118  2.700801 -4.839822          132            3.396008         3.401889\n",
+       " 122119  2.702502 -4.839911          132            3.395020         3.401889\n",
+       " 122120  2.704204 -4.840001          132            3.394031         3.401889\n",
+       " 122121  2.705906 -4.839940          132            3.392992         3.401889\n",
+       " 122122  2.707608 -4.839864          132            3.391950         3.401889\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 122897  4.026426 -4.844348          132            0.000098         3.401889\n",
+       " 122898  4.028128 -4.844724          132            0.000084         3.401889\n",
+       " 122899  4.029830 -4.845100          132            0.000071         3.401889\n",
+       " 122900  4.031531 -4.845476          132            0.000057         3.401889\n",
+       " 122901  4.033233 -4.845852          132            0.000044         3.401889\n",
+       " \n",
+       " [784 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 123118  2.700801 -4.839937          133            3.388560         3.393318\n",
+       " 123119  2.702502 -4.839782          133            3.387543         3.393318\n",
+       " 123120  2.704204 -4.839780          133            3.386527         3.393318\n",
+       " 123121  2.705906 -4.839780          133            3.385511         3.393318\n",
+       " 123122  2.707608 -4.839780          133            3.384495         3.393318\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 123897  4.026426 -4.842446          133            0.000095         3.393318\n",
+       " 123898  4.028128 -4.842694          133            0.000081         3.393318\n",
+       " 123899  4.029830 -4.842942          133            0.000067         3.393318\n",
+       " 123900  4.031531 -4.843190          133            0.000054         3.393318\n",
+       " 123901  4.033233 -4.843438          133            0.000040         3.393318\n",
+       " \n",
+       " [784 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 124118  2.700801 -4.839789          134            3.380919         3.386518\n",
+       " 124119  2.702502 -4.839938          134            3.379924         3.386518\n",
+       " 124120  2.704204 -4.840086          134            3.378929         3.386518\n",
+       " 124121  2.705906 -4.840233          134            3.377934         3.386518\n",
+       " 124122  2.707608 -4.840165          134            3.376864         3.386518\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 124897  4.026426 -4.842158          134            0.000096         3.386518\n",
+       " 124898  4.028128 -4.842304          134            0.000082         3.386518\n",
+       " 124899  4.029830 -4.842449          134            0.000069         3.386518\n",
+       " 124900  4.031531 -4.842595          134            0.000055         3.386518\n",
+       " 124901  4.033233 -4.842740          134            0.000041         3.386518\n",
+       " \n",
+       " [784 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 125118  2.700801 -4.839780          135            3.374240         3.378658\n",
+       " 125119  2.702502 -4.839780          135            3.373246         3.378658\n",
+       " 125120  2.704204 -4.839780          135            3.372253         3.378658\n",
+       " 125121  2.705906 -4.839780          135            3.371239         3.378658\n",
+       " 125122  2.707608 -4.839780          135            3.370200         3.378658\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 125896  4.024725 -4.843284          135            0.000108         3.378658\n",
+       " 125897  4.026426 -4.843595          135            0.000094         3.378658\n",
+       " 125898  4.028128 -4.843905          135            0.000080         3.378658\n",
+       " 125899  4.029830 -4.844216          135            0.000067         3.378658\n",
+       " 125900  4.031531 -4.844527          135            0.000053         3.378658\n",
+       " \n",
+       " [783 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 126118  2.700801 -4.840176          136            3.365736         3.372073\n",
+       " 126119  2.702502 -4.840041          136            3.364726         3.372073\n",
+       " 126120  2.704204 -4.840065          136            3.363700         3.372073\n",
+       " 126121  2.705906 -4.840139          136            3.362670         3.372073\n",
+       " 126122  2.707608 -4.840214          136            3.361640         3.372073\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 126896  4.024725 -4.844396          136            0.000105         3.372073\n",
+       " 126897  4.026426 -4.844781          136            0.000091         3.372073\n",
+       " 126898  4.028128 -4.845166          136            0.000077         3.372073\n",
+       " 126899  4.029830 -4.845551          136            0.000063         3.372073\n",
+       " 126900  4.031531 -4.845935          136            0.000049         3.372073\n",
+       " \n",
+       " [783 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 127118  2.700801 -4.839815          137            3.359027         3.363105\n",
+       " 127119  2.702502 -4.839890          137            3.358017         3.363105\n",
+       " 127120  2.704204 -4.839965          137            3.357007         3.363105\n",
+       " 127121  2.705906 -4.840009          137            3.355984         3.363105\n",
+       " 127122  2.707608 -4.840009          137            3.354944         3.363105\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 127896  4.024725 -4.842936          137            0.000102         3.363105\n",
+       " 127897  4.026426 -4.843197          137            0.000088         3.363105\n",
+       " 127898  4.028128 -4.843458          137            0.000075         3.363105\n",
+       " 127899  4.029830 -4.843719          137            0.000061         3.363105\n",
+       " 127900  4.031531 -4.843980          137            0.000047         3.363105\n",
+       " \n",
+       " [783 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 128118  2.700801 -4.840009          138            3.354270         3.358155\n",
+       " 128119  2.702502 -4.840009          138            3.353294         3.358155\n",
+       " 128120  2.704204 -4.840023          138            3.352302         3.358155\n",
+       " 128121  2.705906 -4.840099          138            3.351237         3.358155\n",
+       " 128122  2.707608 -4.840175          138            3.350172         3.358155\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 128896  4.024725 -4.842886          138            0.000099         3.358155\n",
+       " 128897  4.026426 -4.843119          138            0.000086         3.358155\n",
+       " 128898  4.028128 -4.843353          138            0.000072         3.358155\n",
+       " 128899  4.029830 -4.843586          138            0.000058         3.358155\n",
+       " 128900  4.031531 -4.843820          138            0.000044         3.358155\n",
+       " \n",
+       " [783 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 129118  2.700801 -4.839972          139            3.348676         3.352148\n",
+       " 129119  2.702502 -4.839892          139            3.347669         3.352148\n",
+       " 129120  2.704204 -4.839812          139            3.346662         3.352148\n",
+       " 129121  2.705906 -4.839825          139            3.345638         3.352148\n",
+       " 129122  2.707608 -4.839899          139            3.344604         3.352148\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 129896  4.024725 -4.843556          139            0.000096         3.352148\n",
+       " 129897  4.026426 -4.843865          139            0.000082         3.352148\n",
+       " 129898  4.028128 -4.844174          139            0.000068         3.352148\n",
+       " 129899  4.029830 -4.844483          139            0.000055         3.352148\n",
+       " 129900  4.031531 -4.844792          139            0.000041         3.352148\n",
+       " \n",
+       " [783 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 130118  2.700801 -4.839884          140            3.339049         3.345308\n",
+       " 130119  2.702502 -4.840009          140            3.338068         3.345308\n",
+       " 130120  2.704204 -4.840009          140            3.337050         3.345308\n",
+       " 130121  2.705906 -4.840009          140            3.336031         3.345308\n",
+       " 130122  2.707608 -4.840009          140            3.334992         3.345308\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 130895  4.023023 -4.843844          140            0.000105         3.345308\n",
+       " 130896  4.024725 -4.844193          140            0.000091         3.345308\n",
+       " 130897  4.026426 -4.844541          140            0.000077         3.345308\n",
+       " 130898  4.028128 -4.844889          140            0.000064         3.345308\n",
+       " 130899  4.029830 -4.845237          140            0.000050         3.345308\n",
+       " \n",
+       " [782 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 131118  2.700801 -4.840238          146            3.778105         3.593608\n",
+       " 131119  2.702502 -4.840222          146            3.777202         3.593608\n",
+       " 131120  2.704204 -4.840145          146            3.776207         3.593608\n",
+       " 131121  2.705906 -4.840067          146            3.775212         3.593608\n",
+       " 131122  2.707608 -4.840009          146            3.774215         3.593608\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 131903  4.036637 -4.843781          146            0.000096         3.593608\n",
+       " 131904  4.038338 -4.844104          146            0.000084         3.593608\n",
+       " 131905  4.040040 -4.844429          146            0.000071         3.593608\n",
+       " 131906  4.041742 -4.844752          146            0.000059         3.593608\n",
+       " 131907  4.043444 -4.845076          146            0.000047         3.593608\n",
+       " \n",
+       " [790 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 132118  2.700801 -4.839630          147            3.731559         3.749051\n",
+       " 132119  2.702502 -4.839797          147            3.730561         3.749051\n",
+       " 132120  2.704204 -4.839964          147            3.729563         3.749051\n",
+       " 132121  2.705906 -4.840009          147            3.728577         3.749051\n",
+       " 132122  2.707608 -4.840009          147            3.727594         3.749051\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 132901  4.033233 -4.843476          147            0.000097         3.749051\n",
+       " 132902  4.034935 -4.843768          147            0.000084         3.749051\n",
+       " 132903  4.036637 -4.844060          147            0.000072         3.749051\n",
+       " 132904  4.038338 -4.844351          147            0.000060         3.749051\n",
+       " 132905  4.040040 -4.844643          147            0.000047         3.749051\n",
+       " \n",
+       " [788 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 133118  2.700801 -4.839815          148            3.695192         3.716533\n",
+       " 133119  2.702502 -4.839890          148            3.694221         3.716533\n",
+       " 133120  2.704204 -4.839965          148            3.693251         3.716533\n",
+       " 133121  2.705906 -4.840009          148            3.692252         3.716533\n",
+       " 133122  2.707608 -4.840009          148            3.691211         3.716533\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 133901  4.033233 -4.841826          148            0.000090         3.716533\n",
+       " 133902  4.034935 -4.841999          148            0.000078         3.716533\n",
+       " 133903  4.036637 -4.842172          148            0.000065         3.716533\n",
+       " 133904  4.038338 -4.842345          148            0.000053         3.716533\n",
+       " 133905  4.040040 -4.842518          148            0.000040         3.716533\n",
+       " \n",
+       " [788 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 134118  2.700801 -4.840009          149            3.662021         3.682135\n",
+       " 134119  2.702502 -4.840009          149            3.661043         3.682135\n",
+       " 134120  2.704204 -4.840009          149            3.660065         3.682135\n",
+       " 134121  2.705906 -4.840009          149            3.659070         3.682135\n",
+       " 134122  2.707608 -4.840009          149            3.658069         3.682135\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 134900  4.031531 -4.843089          149            0.000094         3.682135\n",
+       " 134901  4.033233 -4.843331          149            0.000081         3.682135\n",
+       " 134902  4.034935 -4.843574          149            0.000069         3.682135\n",
+       " 134903  4.036637 -4.843816          149            0.000056         3.682135\n",
+       " 134904  4.038338 -4.844059          149            0.000043         3.682135\n",
+       " \n",
+       " [787 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 135118  2.700801 -4.840117          150            3.632478         3.650791\n",
+       " 135119  2.702502 -4.840166          150            3.631444         3.650791\n",
+       " 135120  2.704204 -4.840016          150            3.630456         3.650791\n",
+       " 135121  2.705906 -4.839866          150            3.629469         3.650791\n",
+       " 135122  2.707608 -4.839876          150            3.628466         3.650791\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 135897  4.026426 -4.838977          150            0.000117         3.650791\n",
+       " 135898  4.028128 -4.838902          150            0.000103         3.650791\n",
+       " 135899  4.029830 -4.838827          150            0.000089         3.650791\n",
+       " 135900  4.031531 -4.838752          150            0.000075         3.650791\n",
+       " 135901  4.033233 -4.838677          150            0.000061         3.650791\n",
+       " \n",
+       " [784 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 136118  2.700801 -4.840009          151            3.607475         3.622972\n",
+       " 136119  2.702502 -4.840009          151            3.606462         3.622972\n",
+       " 136120  2.704204 -4.840009          151            3.605448         3.622972\n",
+       " 136121  2.705906 -4.839883          151            3.604459         3.622972\n",
+       " 136122  2.707608 -4.839737          151            3.603474         3.622972\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 136899  4.029830 -4.842485          151            0.000096         3.622972\n",
+       " 136900  4.031531 -4.842701          151            0.000083         3.622972\n",
+       " 136901  4.033233 -4.842916          151            0.000071         3.622972\n",
+       " 136902  4.034935 -4.843132          151            0.000058         3.622972\n",
+       " 136903  4.036637 -4.843348          151            0.000045         3.622972\n",
+       " \n",
+       " [786 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 137118  2.700801 -4.839815          152            3.583220         3.598963\n",
+       " 137119  2.702502 -4.839890          152            3.582232         3.598963\n",
+       " 137120  2.704204 -4.839965          152            3.581244         3.598963\n",
+       " 137121  2.705906 -4.839947          152            3.580245         3.598963\n",
+       " 137122  2.707608 -4.839797          152            3.579231         3.598963\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 137898  4.028128 -4.843540          152            0.000101         3.598963\n",
+       " 137899  4.029830 -4.843850          152            0.000089         3.598963\n",
+       " 137900  4.031531 -4.844160          152            0.000076         3.598963\n",
+       " 137901  4.033233 -4.844470          152            0.000063         3.598963\n",
+       " 137902  4.034935 -4.844779          152            0.000051         3.598963\n",
+       " \n",
+       " [785 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 138118  2.700801 -4.839592          153            3.562138         3.575322\n",
+       " 138119  2.702502 -4.839681          153            3.561120         3.575322\n",
+       " 138120  2.704204 -4.839768          153            3.560101         3.575322\n",
+       " 138121  2.705906 -4.839780          153            3.559119         3.575322\n",
+       " 138122  2.707608 -4.839780          153            3.558142         3.575322\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 138898  4.028128 -4.843539          153            0.000094         3.575322\n",
+       " 138899  4.029830 -4.843838          153            0.000082         3.575322\n",
+       " 138900  4.031531 -4.844137          153            0.000069         3.575322\n",
+       " 138901  4.033233 -4.844435          153            0.000056         3.575322\n",
+       " 138902  4.034935 -4.844734          153            0.000043         3.575322\n",
+       " \n",
+       " [785 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 139118  2.700801 -4.839780          154            3.538285         3.552735\n",
+       " 139119  2.702502 -4.839780          154            3.537316         3.552735\n",
+       " 139120  2.704204 -4.839811          154            3.536339         3.552735\n",
+       " 139121  2.705906 -4.840040          154            3.535305         3.552735\n",
+       " 139122  2.707608 -4.840268          154            3.534271         3.552735\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 139897  4.026426 -4.842867          154            0.000097         3.552735\n",
+       " 139898  4.028128 -4.843096          154            0.000084         3.552735\n",
+       " 139899  4.029830 -4.843325          154            0.000072         3.552735\n",
+       " 139900  4.031531 -4.843554          154            0.000059         3.552735\n",
+       " 139901  4.033233 -4.843783          154            0.000046         3.552735\n",
+       " \n",
+       " [784 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 140118  2.700801 -4.840022          155            3.519148         3.532185\n",
+       " 140119  2.702502 -4.839816          155            3.518148         3.532185\n",
+       " 140120  2.704204 -4.839890          155            3.517157         3.532185\n",
+       " 140121  2.705906 -4.839964          155            3.516166         3.532185\n",
+       " 140122  2.707608 -4.840038          155            3.515157         3.532185\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 140897  4.026426 -4.844226          155            0.000094         3.532185\n",
+       " 140898  4.028128 -4.844577          155            0.000081         3.532185\n",
+       " 140899  4.029830 -4.844928          155            0.000069         3.532185\n",
+       " 140900  4.031531 -4.845279          155            0.000056         3.532185\n",
+       " 140901  4.033233 -4.845630          155            0.000043         3.532185\n",
+       " \n",
+       " [784 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 141118  2.700801 -4.840238          156            3.499707         3.512666\n",
+       " 141119  2.702502 -4.840238          156            3.498733         3.512666\n",
+       " 141120  2.704204 -4.840225          156            3.497743         3.512666\n",
+       " 141121  2.705906 -4.840149          156            3.496685         3.512666\n",
+       " 141122  2.707608 -4.840075          156            3.495626         3.512666\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 141896  4.024725 -4.843726          156            0.000100         3.512666\n",
+       " 141897  4.026426 -4.844052          156            0.000088         3.512666\n",
+       " 141898  4.028128 -4.844378          156            0.000075         3.512666\n",
+       " 141899  4.029830 -4.844703          156            0.000062         3.512666\n",
+       " 141900  4.031531 -4.845029          156            0.000049         3.512666\n",
+       " \n",
+       " [783 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 142118  2.700801 -4.839952          157            3.483841         3.495019\n",
+       " 142119  2.702502 -4.839831          157            3.482856         3.495019\n",
+       " 142120  2.704204 -4.839780          157            3.481867         3.495019\n",
+       " 142121  2.705906 -4.839780          157            3.480875         3.495019\n",
+       " 142122  2.707608 -4.839780          157            3.479882         3.495019\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 142896  4.024725 -4.844135          157            0.000097         3.495019\n",
+       " 142897  4.026426 -4.844484          157            0.000085         3.495019\n",
+       " 142898  4.028128 -4.844833          157            0.000072         3.495019\n",
+       " 142899  4.029830 -4.845183          157            0.000060         3.495019\n",
+       " 142900  4.031531 -4.845532          157            0.000047         3.495019\n",
+       " \n",
+       " [783 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 143118  2.700801 -4.840009          158            3.467448         3.477948\n",
+       " 143119  2.702502 -4.840009          158            3.466457         3.477948\n",
+       " 143120  2.704204 -4.840009          158            3.465453         3.477948\n",
+       " 143121  2.705906 -4.840009          158            3.464449         3.477948\n",
+       " 143122  2.707608 -4.840009          158            3.463434         3.477948\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 143896  4.024725 -4.843747          158            0.000093         3.477948\n",
+       " 143897  4.026426 -4.844059          158            0.000080         3.477948\n",
+       " 143898  4.028128 -4.844370          158            0.000067         3.477948\n",
+       " 143899  4.029830 -4.844681          158            0.000055         3.477948\n",
+       " 143900  4.031531 -4.844993          158            0.000042         3.477948\n",
+       " \n",
+       " [783 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 144118  2.700801 -4.839670          159            3.452258         3.462776\n",
+       " 144119  2.702502 -4.839737          159            3.451248         3.462776\n",
+       " 144120  2.704204 -4.839663          159            3.450269         3.462776\n",
+       " 144121  2.705906 -4.839587          159            3.449290         3.462776\n",
+       " 144122  2.707608 -4.839631          159            3.448267         3.462776\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 144895  4.023023 -4.844276          159            0.000101         3.462776\n",
+       " 144896  4.024725 -4.844626          159            0.000088         3.462776\n",
+       " 144897  4.026426 -4.844977          159            0.000075         3.462776\n",
+       " 144898  4.028128 -4.845327          159            0.000063         3.462776\n",
+       " 144899  4.029830 -4.845677          159            0.000050         3.462776\n",
+       " \n",
+       " [782 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 145118  2.700801 -4.840226          160            3.440030         3.448395\n",
+       " 145119  2.702502 -4.840165          160            3.439015         3.448395\n",
+       " 145120  2.704204 -4.840090          160            3.438001         3.448395\n",
+       " 145121  2.705906 -4.840015          160            3.436986         3.448395\n",
+       " 145122  2.707608 -4.840009          160            3.435954         3.448395\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 145895  4.023023 -4.842734          160            0.000098         3.448395\n",
+       " 145896  4.024725 -4.842936          160            0.000086         3.448395\n",
+       " 145897  4.026426 -4.843139          160            0.000073         3.448395\n",
+       " 145898  4.028128 -4.843341          160            0.000060         3.448395\n",
+       " 145899  4.029830 -4.843544          160            0.000048         3.448395\n",
+       " \n",
+       " [782 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 146118  2.700801 -4.839812          161            3.426620          3.43649\n",
+       " 146119  2.702502 -4.839887          161            3.425589          3.43649\n",
+       " 146120  2.704204 -4.839962          161            3.424557          3.43649\n",
+       " 146121  2.705906 -4.839982          161            3.423532          3.43649\n",
+       " 146122  2.707608 -4.839908          161            3.422519          3.43649\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 146895  4.023023 -4.843048          161            0.000093          3.43649\n",
+       " 146896  4.024725 -4.843304          161            0.000081          3.43649\n",
+       " 146897  4.026426 -4.843560          161            0.000068          3.43649\n",
+       " 146898  4.028128 -4.843815          161            0.000055          3.43649\n",
+       " 146899  4.029830 -4.844071          161            0.000043          3.43649\n",
+       " \n",
+       " [782 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 147118  2.700801 -4.839649          162            3.413011         3.422412\n",
+       " 147119  2.702502 -4.839857          162            3.411983         3.422412\n",
+       " 147120  2.704204 -4.840029          162            3.410954         3.422412\n",
+       " 147121  2.705906 -4.840103          162            3.409924         3.422412\n",
+       " 147122  2.707608 -4.840177          162            3.408894         3.422412\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 147894  4.021321 -4.844268          162            0.000102         3.422412\n",
+       " 147895  4.023023 -4.844663          162            0.000089         3.422412\n",
+       " 147896  4.024725 -4.845057          162            0.000076         3.422412\n",
+       " 147897  4.026426 -4.845452          162            0.000064         3.422412\n",
+       " 147898  4.028128 -4.845847          162            0.000051         3.422412\n",
+       " \n",
+       " [781 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 148118  2.700801 -4.840359          163            3.397955         3.407437\n",
+       " 148119  2.702502 -4.840127          163            3.396960         3.407437\n",
+       " 148120  2.704204 -4.839973          163            3.395953         3.407437\n",
+       " 148121  2.705906 -4.839900          163            3.394933         3.407437\n",
+       " 148122  2.707608 -4.839828          163            3.393914         3.407437\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 148894  4.021321 -4.842772          163            0.000096         3.407437\n",
+       " 148895  4.023023 -4.842975          163            0.000083         3.407437\n",
+       " 148896  4.024725 -4.843179          163            0.000071         3.407437\n",
+       " 148897  4.026426 -4.843382          163            0.000058         3.407437\n",
+       " 148898  4.028128 -4.843586          163            0.000045         3.407437\n",
+       " \n",
+       " [781 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 149118  2.700801 -4.839780          164            3.388101         3.394786\n",
+       " 149119  2.702502 -4.839780          164            3.387109         3.394786\n",
+       " 149120  2.704204 -4.839780          164            3.386102         3.394786\n",
+       " 149121  2.705906 -4.839780          164            3.385079         3.394786\n",
+       " 149122  2.707608 -4.839780          164            3.384056         3.394786\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 149894  4.021321 -4.844332          164            0.000094         3.394786\n",
+       " 149895  4.023023 -4.844712          164            0.000082         3.394786\n",
+       " 149896  4.024725 -4.845092          164            0.000069         3.394786\n",
+       " 149897  4.026426 -4.845472          164            0.000056         3.394786\n",
+       " 149898  4.028128 -4.845852          164            0.000043         3.394786\n",
+       " \n",
+       " [781 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 150118  2.700801 -4.839811          165            3.376377         3.383672\n",
+       " 150119  2.702502 -4.839609          165            3.375371         3.383672\n",
+       " 150120  2.704204 -4.839757          165            3.374393         3.383672\n",
+       " 150121  2.705906 -4.839905          165            3.373415         3.383672\n",
+       " 150122  2.707608 -4.840009          165            3.372410         3.383672\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 150894  4.021321 -4.843614          165            0.000091         3.383672\n",
+       " 150895  4.023023 -4.843856          165            0.000078         3.383672\n",
+       " 150896  4.024725 -4.844099          165            0.000065         3.383672\n",
+       " 150897  4.026426 -4.844341          165            0.000053         3.383672\n",
+       " 150898  4.028128 -4.844584          165            0.000040         3.383672\n",
+       " \n",
+       " [781 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 151118  2.700801 -4.839912          166            3.366918         3.373892\n",
+       " 151119  2.702502 -4.839910          166            3.365923         3.373892\n",
+       " 151120  2.704204 -4.839760          166            3.364922         3.373892\n",
+       " 151121  2.705906 -4.839610          166            3.363921         3.373892\n",
+       " 151122  2.707608 -4.839687          166            3.362908         3.373892\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 151893  4.019619 -4.843546          166            0.000099         3.373892\n",
+       " 151894  4.021321 -4.843816          166            0.000087         3.373892\n",
+       " 151895  4.023023 -4.844086          166            0.000074         3.373892\n",
+       " 151896  4.024725 -4.844357          166            0.000061         3.373892\n",
+       " 151897  4.026426 -4.844626          166            0.000049         3.373892\n",
+       " \n",
+       " [780 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 152118  2.700801 -4.839780          167            3.356068         3.363186\n",
+       " 152119  2.702502 -4.839780          167            3.355054         3.363186\n",
+       " 152120  2.704204 -4.839780          167            3.354040         3.363186\n",
+       " 152121  2.705906 -4.839785          167            3.353024         3.363186\n",
+       " 152122  2.707608 -4.839860          167            3.351983         3.363186\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 152893  4.019619 -4.843816          167            0.000097         3.363186\n",
+       " 152894  4.021321 -4.844138          167            0.000084         3.363186\n",
+       " 152895  4.023023 -4.844460          167            0.000072         3.363186\n",
+       " 152896  4.024725 -4.844783          167            0.000059         3.363186\n",
+       " 152897  4.026426 -4.845105          167            0.000046         3.363186\n",
+       " \n",
+       " [780 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 153118  2.700801 -4.840044          168            3.347467          3.35335\n",
+       " 153119  2.702502 -4.840119          168            3.346462          3.35335\n",
+       " 153120  2.704204 -4.840194          168            3.345456          3.35335\n",
+       " 153121  2.705906 -4.840144          168            3.344445          3.35335\n",
+       " 153122  2.707608 -4.839919          168            3.343427          3.35335\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 153893  4.019619 -4.843353          168            0.000092          3.35335\n",
+       " 153894  4.021321 -4.843649          168            0.000080          3.35335\n",
+       " 153895  4.023023 -4.843946          168            0.000067          3.35335\n",
+       " 153896  4.024725 -4.844242          168            0.000054          3.35335\n",
+       " 153897  4.026426 -4.844539          168            0.000042          3.35335\n",
+       " \n",
+       " [780 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 154118  2.700801 -4.839700          169            3.339725         3.345248\n",
+       " 154119  2.702502 -4.839891          169            3.338731         3.345248\n",
+       " 154120  2.704204 -4.840039          169            3.337749         3.345248\n",
+       " 154121  2.705906 -4.840187          169            3.336766         3.345248\n",
+       " 154122  2.707608 -4.840238          169            3.335742         3.345248\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 154893  4.019619 -4.844057          169            0.000092         3.345248\n",
+       " 154894  4.021321 -4.844352          169            0.000079         3.345248\n",
+       " 154895  4.023023 -4.844647          169            0.000066         3.345248\n",
+       " 154896  4.024725 -4.844943          169            0.000054         3.345248\n",
+       " 154897  4.026426 -4.845239          169            0.000041         3.345248\n",
+       " \n",
+       " [780 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 155118  2.700801 -4.840009          170            3.332974         3.339008\n",
+       " 155119  2.702502 -4.840009          170            3.331958         3.339008\n",
+       " 155120  2.704204 -4.840009          170            3.330942         3.339008\n",
+       " 155121  2.705906 -4.840009          170            3.329926         3.339008\n",
+       " 155122  2.707608 -4.840009          170            3.328907         3.339008\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 155892  4.017918 -4.843036          170            0.000102         3.339008\n",
+       " 155893  4.019619 -4.843306          170            0.000089         3.339008\n",
+       " 155894  4.021321 -4.843576          170            0.000076         3.339008\n",
+       " 155895  4.023023 -4.843846          170            0.000064         3.339008\n",
+       " 155896  4.024725 -4.844117          170            0.000051         3.339008\n",
+       " \n",
+       " [779 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 156118  2.700801 -4.839712          171            3.323654         3.330481\n",
+       " 156119  2.702502 -4.839665          171            3.322649         3.330481\n",
+       " 156120  2.704204 -4.839818          171            3.321629         3.330481\n",
+       " 156121  2.705906 -4.839970          171            3.320608         3.330481\n",
+       " 156122  2.707608 -4.840065          171            3.319594         3.330481\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 156892  4.017918 -4.843852          171            0.000099         3.330481\n",
+       " 156893  4.019619 -4.844202          171            0.000087         3.330481\n",
+       " 156894  4.021321 -4.844552          171            0.000074         3.330481\n",
+       " 156895  4.023023 -4.844902          171            0.000061         3.330481\n",
+       " 156896  4.024725 -4.845252          171            0.000049         3.330481\n",
+       " \n",
+       " [779 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 157118  2.700801 -4.839886          172            3.313412         3.319983\n",
+       " 157119  2.702502 -4.840113          172            3.312406         3.319983\n",
+       " 157120  2.704204 -4.840172          172            3.311399         3.319983\n",
+       " 157121  2.705906 -4.840024          172            3.310391         3.319983\n",
+       " 157122  2.707608 -4.839876          172            3.309383         3.319983\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 157892  4.017918 -4.845098          172            0.000095         3.319983\n",
+       " 157893  4.019619 -4.845498          172            0.000083         3.319983\n",
+       " 157894  4.021321 -4.845898          172            0.000070         3.319983\n",
+       " 157895  4.023023 -4.846298          172            0.000058         3.319983\n",
+       " 157896  4.024725 -4.846697          172            0.000045         3.319983\n",
+       " \n",
+       " [779 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 158118  2.700801 -4.840413          173            3.305240         3.311536\n",
+       " 158119  2.702502 -4.840297          173            3.304265         3.311536\n",
+       " 158120  2.704204 -4.840163          173            3.303268         3.311536\n",
+       " 158121  2.705906 -4.840011          173            3.302248         3.311536\n",
+       " 158122  2.707608 -4.839858          173            3.301227         3.311536\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 158892  4.017918 -4.843987          173            0.000092         3.311536\n",
+       " 158893  4.019619 -4.844346          173            0.000080         3.311536\n",
+       " 158894  4.021321 -4.844705          173            0.000067         3.311536\n",
+       " 158895  4.023023 -4.845064          173            0.000055         3.311536\n",
+       " 158896  4.024725 -4.845423          173            0.000042         3.311536\n",
+       " \n",
+       " [779 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 159118  2.700801 -4.840414          174            3.298087         3.303459\n",
+       " 159119  2.702502 -4.840301          174            3.297141         3.303459\n",
+       " 159120  2.704204 -4.840136          174            3.296155         3.303459\n",
+       " 159121  2.705906 -4.839907          174            3.295121         3.303459\n",
+       " 159122  2.707608 -4.839678          174            3.294088         3.303459\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 159892  4.017918 -4.844206          174            0.000090         3.303459\n",
+       " 159893  4.019619 -4.844527          174            0.000078         3.303459\n",
+       " 159894  4.021321 -4.844848          174            0.000065         3.303459\n",
+       " 159895  4.023023 -4.845168          174            0.000053         3.303459\n",
+       " 159896  4.024725 -4.845489          174            0.000040         3.303459\n",
+       " \n",
+       " [779 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 160118  2.700801 -4.839880          175            3.289984          3.29511\n",
+       " 160119  2.702502 -4.839952          175            3.288969          3.29511\n",
+       " 160120  2.704204 -4.839804          175            3.287970          3.29511\n",
+       " 160121  2.705906 -4.839655          175            3.286970          3.29511\n",
+       " 160122  2.707608 -4.839573          175            3.285959          3.29511\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 160891  4.016216 -4.844255          175            0.000101          3.29511\n",
+       " 160892  4.017918 -4.844603          175            0.000089          3.29511\n",
+       " 160893  4.019619 -4.844950          175            0.000076          3.29511\n",
+       " 160894  4.021321 -4.845297          175            0.000064          3.29511\n",
+       " 160895  4.023023 -4.845645          175            0.000051          3.29511\n",
+       " \n",
+       " [778 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 161118  2.700801 -4.839780          176            3.281460         3.287504\n",
+       " 161119  2.702502 -4.839780          176            3.280463         3.287504\n",
+       " 161120  2.704204 -4.839901          176            3.279456         3.287504\n",
+       " 161121  2.705906 -4.840052          176            3.278446         3.287504\n",
+       " 161122  2.707608 -4.840202          176            3.277436         3.287504\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 161891  4.016216 -4.843882          176            0.000101         3.287504\n",
+       " 161892  4.017918 -4.844222          176            0.000088         3.287504\n",
+       " 161893  4.019619 -4.844561          176            0.000075         3.287504\n",
+       " 161894  4.021321 -4.844901          176            0.000062         3.287504\n",
+       " 161895  4.023023 -4.845240          176            0.000050         3.287504\n",
+       " \n",
+       " [778 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 162118  2.700801 -4.840106          177            3.273926         3.277743\n",
+       " 162119  2.702502 -4.839822          177            3.272918         3.277743\n",
+       " 162120  2.704204 -4.839780          177            3.271913         3.277743\n",
+       " 162121  2.705906 -4.839780          177            3.270907         3.277743\n",
+       " 162122  2.707608 -4.839780          177            3.269902         3.277743\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 162891  4.016216 -4.843777          177            0.000101         3.277743\n",
+       " 162892  4.017918 -4.844088          177            0.000088         3.277743\n",
+       " 162893  4.019619 -4.844398          177            0.000075         3.277743\n",
+       " 162894  4.021321 -4.844709          177            0.000063         3.277743\n",
+       " 162895  4.023023 -4.845019          177            0.000050         3.277743\n",
+       " \n",
+       " [778 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 163118  2.700801 -4.840009          178            3.267015         3.272352\n",
+       " 163119  2.702502 -4.840009          178            3.266033         3.272352\n",
+       " 163120  2.704204 -4.840009          178            3.265028         3.272352\n",
+       " 163121  2.705906 -4.840009          178            3.263999         3.272352\n",
+       " 163122  2.707608 -4.840009          178            3.262969         3.272352\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 163891  4.016216 -4.843853          178            0.000098         3.272352\n",
+       " 163892  4.017918 -4.844165          178            0.000085         3.272352\n",
+       " 163893  4.019619 -4.844478          178            0.000072         3.272352\n",
+       " 163894  4.021321 -4.844790          178            0.000059         3.272352\n",
+       " 163895  4.023023 -4.845102          178            0.000047         3.272352\n",
+       " \n",
+       " [778 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 164118  2.700801 -4.840009          179            3.259714          3.26385\n",
+       " 164119  2.702502 -4.840009          179            3.258683          3.26385\n",
+       " 164120  2.704204 -4.840009          179            3.257702          3.26385\n",
+       " 164121  2.705906 -4.840009          179            3.256721          3.26385\n",
+       " 164122  2.707608 -4.840009          179            3.255724          3.26385\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 164891  4.016216 -4.843688          179            0.000095          3.26385\n",
+       " 164892  4.017918 -4.843998          179            0.000082          3.26385\n",
+       " 164893  4.019619 -4.844309          179            0.000070          3.26385\n",
+       " 164894  4.021321 -4.844619          179            0.000057          3.26385\n",
+       " 164895  4.023023 -4.844930          179            0.000044          3.26385\n",
+       " \n",
+       " [778 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 165118  2.700801 -4.840009          180            3.253069         3.257379\n",
+       " 165119  2.702502 -4.839951          180            3.252055         3.257379\n",
+       " 165120  2.704204 -4.839877          180            3.251042         3.257379\n",
+       " 165121  2.705906 -4.839803          180            3.250029         3.257379\n",
+       " 165122  2.707608 -4.839832          180            3.249008         3.257379\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 165891  4.016216 -4.842920          180            0.000091         3.257379\n",
+       " 165892  4.017918 -4.843164          180            0.000078         3.257379\n",
+       " 165893  4.019619 -4.843409          180            0.000065         3.257379\n",
+       " 165894  4.021321 -4.843653          180            0.000053         3.257379\n",
+       " 165895  4.023023 -4.843898          180            0.000040         3.257379\n",
+       " \n",
+       " [778 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 166118  2.700801 -4.840009          181            3.246871         3.250824\n",
+       " 166119  2.702502 -4.840009          181            3.245878         3.250824\n",
+       " 166120  2.704204 -4.840009          181            3.244884         3.250824\n",
+       " 166121  2.705906 -4.840009          181            3.243890         3.250824\n",
+       " 166122  2.707608 -4.840009          181            3.242847         3.250824\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 166890  4.014514 -4.843229          181            0.000100         3.250824\n",
+       " 166891  4.016216 -4.843513          181            0.000088         3.250824\n",
+       " 166892  4.017918 -4.843797          181            0.000075         3.250824\n",
+       " 166893  4.019619 -4.844080          181            0.000062         3.250824\n",
+       " 166894  4.021321 -4.844364          181            0.000050         3.250824\n",
+       " \n",
+       " [777 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 167118  2.700801 -4.839975          182            3.239122         3.243775\n",
+       " 167119  2.702502 -4.839901          182            3.238148         3.243775\n",
+       " 167120  2.704204 -4.839827          182            3.237175         3.243775\n",
+       " 167121  2.705906 -4.839808          182            3.236189         3.243775\n",
+       " 167122  2.707608 -4.839883          182            3.235184         3.243775\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 167890  4.014514 -4.843781          182            0.000098         3.243775\n",
+       " 167891  4.016216 -4.844102          182            0.000086         3.243775\n",
+       " 167892  4.017918 -4.844423          182            0.000073         3.243775\n",
+       " 167893  4.019619 -4.844744          182            0.000060         3.243775\n",
+       " 167894  4.021321 -4.845064          182            0.000048         3.243775\n",
+       " \n",
+       " [777 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 168118  2.700801 -4.840014          183            3.235412         3.237536\n",
+       " 168119  2.702502 -4.840090          183            3.234410         3.237536\n",
+       " 168120  2.704204 -4.840167          183            3.233407         3.237536\n",
+       " 168121  2.705906 -4.840230          183            3.232404         3.237536\n",
+       " 168122  2.707608 -4.840079          183            3.231399         3.237536\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 168890  4.014514 -4.841670          183            0.000093         3.237536\n",
+       " 168891  4.016216 -4.841818          183            0.000081         3.237536\n",
+       " 168892  4.017918 -4.841966          183            0.000068         3.237536\n",
+       " 168893  4.019619 -4.842113          183            0.000055         3.237536\n",
+       " 168894  4.021321 -4.842261          183            0.000043         3.237536\n",
+       " \n",
+       " [777 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 169118  2.700801 -4.839967          184            3.229650         3.234387\n",
+       " 169119  2.702502 -4.839878          184            3.228660         3.234387\n",
+       " 169120  2.704204 -4.839788          184            3.227671         3.234387\n",
+       " 169121  2.705906 -4.839780          184            3.226666         3.234387\n",
+       " 169122  2.707608 -4.839780          184            3.225659         3.234387\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 169890  4.014514 -4.843811          184            0.000090         3.234387\n",
+       " 169891  4.016216 -4.844118          184            0.000078         3.234387\n",
+       " 169892  4.017918 -4.844424          184            0.000065         3.234387\n",
+       " 169893  4.019619 -4.844730          184            0.000053         3.234387\n",
+       " 169894  4.021321 -4.845037          184            0.000040         3.234387\n",
+       " \n",
+       " [777 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 170118  2.700801 -4.839598          185            3.223549         3.228962\n",
+       " 170119  2.702502 -4.839698          185            3.222567         3.228962\n",
+       " 170120  2.704204 -4.839794          185            3.221583         3.228962\n",
+       " 170121  2.705906 -4.839869          185            3.220586         3.228962\n",
+       " 170122  2.707608 -4.839944          185            3.219589         3.228962\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 170890  4.014514 -4.844290          185            0.000090         3.228962\n",
+       " 170891  4.016216 -4.844648          185            0.000077         3.228962\n",
+       " 170892  4.017918 -4.845006          185            0.000065         3.228962\n",
+       " 170893  4.019619 -4.845365          185            0.000052         3.228962\n",
+       " 170894  4.021321 -4.845723          185            0.000040         3.228962\n",
+       " \n",
+       " [777 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 171118  2.700801 -4.840045          186            3.216722         3.221662\n",
+       " 171119  2.702502 -4.840123          186            3.215745         3.221662\n",
+       " 171120  2.704204 -4.840200          186            3.214768         3.221662\n",
+       " 171121  2.705906 -4.840162          186            3.213766         3.221662\n",
+       " 171122  2.707608 -4.840012          186            3.212738         3.221662\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 171889  4.012813 -4.842543          186            0.000100         3.221662\n",
+       " 171890  4.014514 -4.842729          186            0.000088         3.221662\n",
+       " 171891  4.016216 -4.842914          186            0.000075         3.221662\n",
+       " 171892  4.017918 -4.843100          186            0.000063         3.221662\n",
+       " 171893  4.019619 -4.843286          186            0.000050         3.221662\n",
+       " \n",
+       " [776 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 172118  2.700801 -4.839962          187            3.211517         3.215633\n",
+       " 172119  2.702502 -4.839862          187            3.210535         3.215633\n",
+       " 172120  2.704204 -4.839780          187            3.209546         3.215633\n",
+       " 172121  2.705906 -4.839780          187            3.208528         3.215633\n",
+       " 172122  2.707608 -4.839780          187            3.207509         3.215633\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 172889  4.012813 -4.843281          187            0.000098         3.215633\n",
+       " 172890  4.014514 -4.843561          187            0.000086         3.215633\n",
+       " 172891  4.016216 -4.843841          187            0.000073         3.215633\n",
+       " 172892  4.017918 -4.844121          187            0.000061         3.215633\n",
+       " 172893  4.019619 -4.844400          187            0.000048         3.215633\n",
+       " \n",
+       " [776 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 173118  2.700801 -4.839823          188            3.203819         3.209791\n",
+       " 173119  2.702502 -4.839914          188            3.202850         3.209791\n",
+       " 173120  2.704204 -4.840005          188            3.201880         3.209791\n",
+       " 173121  2.705906 -4.840009          188            3.200851         3.209791\n",
+       " 173122  2.707608 -4.840009          188            3.199820         3.209791\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 173889  4.012813 -4.843050          188            0.000096         3.209791\n",
+       " 173890  4.014514 -4.843290          188            0.000084         3.209791\n",
+       " 173891  4.016216 -4.843531          188            0.000071         3.209791\n",
+       " 173892  4.017918 -4.843771          188            0.000058         3.209791\n",
+       " 173893  4.019619 -4.844012          188            0.000046         3.209791\n",
+       " \n",
+       " [776 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 174118  2.700801 -4.840423          189            3.199083         3.202597\n",
+       " 174119  2.702502 -4.840328          189            3.198106         3.202597\n",
+       " 174120  2.704204 -4.840231          189            3.197125         3.202597\n",
+       " 174121  2.705906 -4.840079          189            3.196078         3.202597\n",
+       " 174122  2.707608 -4.839926          189            3.195030         3.202597\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 174889  4.012813 -4.843638          189            0.000095         3.202597\n",
+       " 174890  4.014514 -4.843903          189            0.000083         3.202597\n",
+       " 174891  4.016216 -4.844168          189            0.000070         3.202597\n",
+       " 174892  4.017918 -4.844433          189            0.000058         3.202597\n",
+       " 174893  4.019619 -4.844698          189            0.000045         3.202597\n",
+       " \n",
+       " [776 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 175118  2.700801 -4.839780          190            3.192663         3.197839\n",
+       " 175119  2.702502 -4.839780          190            3.191728         3.197839\n",
+       " 175120  2.704204 -4.839862          190            3.190743         3.197839\n",
+       " 175121  2.705906 -4.840015          190            3.189713         3.197839\n",
+       " 175122  2.707608 -4.840167          190            3.188684         3.197839\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 175889  4.012813 -4.843469          190            0.000092         3.197839\n",
+       " 175890  4.014514 -4.843737          190            0.000080         3.197839\n",
+       " 175891  4.016216 -4.844005          190            0.000067         3.197839\n",
+       " 175892  4.017918 -4.844273          190            0.000054         3.197839\n",
+       " 175893  4.019619 -4.844541          190            0.000042         3.197839\n",
+       " \n",
+       " [776 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 176118  2.700801 -4.840009          191            3.188177         3.192446\n",
+       " 176119  2.702502 -4.840009          191            3.187166         3.192446\n",
+       " 176120  2.704204 -4.840009          191            3.186154         3.192446\n",
+       " 176121  2.705906 -4.840070          191            3.185160         3.192446\n",
+       " 176122  2.707608 -4.840144          191            3.184169         3.192446\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 176889  4.012813 -4.844120          191            0.000092         3.192446\n",
+       " 176890  4.014514 -4.844455          191            0.000079         3.192446\n",
+       " 176891  4.016216 -4.844790          191            0.000067         3.192446\n",
+       " 176892  4.017918 -4.845125          191            0.000054         3.192446\n",
+       " 176893  4.019619 -4.845459          191            0.000041         3.192446\n",
+       " \n",
+       " [776 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 177118  2.700801 -4.839910          192            3.181518         3.185799\n",
+       " 177119  2.702502 -4.839780          192            3.180500         3.185799\n",
+       " 177120  2.704204 -4.839780          192            3.179532         3.185799\n",
+       " 177121  2.705906 -4.839780          192            3.178564         3.185799\n",
+       " 177122  2.707608 -4.839818          192            3.177576         3.185799\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 177888  4.011111 -4.843288          192            0.000101         3.185799\n",
+       " 177889  4.012813 -4.843555          192            0.000088         3.185799\n",
+       " 177890  4.014514 -4.843823          192            0.000076         3.185799\n",
+       " 177891  4.016216 -4.844090          192            0.000063         3.185799\n",
+       " 177892  4.017918 -4.844357          192            0.000051         3.185799\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 178118  2.700801 -4.839865          193            3.178946         3.181631\n",
+       " 178119  2.702502 -4.839556          193            3.177973         3.181631\n",
+       " 178120  2.704204 -4.839702          193            3.176954         3.181631\n",
+       " 178121  2.705906 -4.839854          193            3.175933         3.181631\n",
+       " 178122  2.707608 -4.840006          193            3.174913         3.181631\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 178888  4.011111 -4.841479          193            0.000101         3.181631\n",
+       " 178889  4.012813 -4.841598          193            0.000089         3.181631\n",
+       " 178890  4.014514 -4.841717          193            0.000076         3.181631\n",
+       " 178891  4.016216 -4.841836          193            0.000064         3.181631\n",
+       " 178892  4.017918 -4.841956          193            0.000052         3.181631\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 179118  2.700801 -4.839802          194            3.174082         3.178197\n",
+       " 179119  2.702502 -4.839917          194            3.173103         3.178197\n",
+       " 179120  2.704204 -4.839767          194            3.172132         3.178197\n",
+       " 179121  2.705906 -4.839617          194            3.171162         3.178197\n",
+       " 179122  2.707608 -4.839594          194            3.170146         3.178197\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 179888  4.011111 -4.843711          194            0.000098         3.178197\n",
+       " 179889  4.012813 -4.844042          194            0.000086         3.178197\n",
+       " 179890  4.014514 -4.844373          194            0.000074         3.178197\n",
+       " 179891  4.016216 -4.844703          194            0.000061         3.178197\n",
+       " 179892  4.017918 -4.845034          194            0.000049         3.178197\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 180118  2.700801 -4.840009          195            3.171999         3.174046\n",
+       " 180119  2.702502 -4.840009          195            3.171016         3.174046\n",
+       " 180120  2.704204 -4.840009          195            3.170014         3.174046\n",
+       " 180121  2.705906 -4.840009          195            3.169012         3.174046\n",
+       " 180122  2.707608 -4.840009          195            3.167996         3.174046\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 180888  4.011111 -4.843987          195            0.000097         3.174046\n",
+       " 180889  4.012813 -4.844264          195            0.000085         3.174046\n",
+       " 180890  4.014514 -4.844542          195            0.000072         3.174046\n",
+       " 180891  4.016216 -4.844820          195            0.000060         3.174046\n",
+       " 180892  4.017918 -4.845097          195            0.000048         3.174046\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 181118  2.700801 -4.839735          196            3.168009         3.172507\n",
+       " 181119  2.702502 -4.840009          196            3.167008         3.172507\n",
+       " 181120  2.704204 -4.840009          196            3.166039         3.172507\n",
+       " 181121  2.705906 -4.840009          196            3.165070         3.172507\n",
+       " 181122  2.707608 -4.839979          196            3.164085         3.172507\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 181888  4.011111 -4.843343          196            0.000095         3.172507\n",
+       " 181889  4.012813 -4.843622          196            0.000083         3.172507\n",
+       " 181890  4.014514 -4.843902          196            0.000070         3.172507\n",
+       " 181891  4.016216 -4.844181          196            0.000058         3.172507\n",
+       " 181892  4.017918 -4.844460          196            0.000045         3.172507\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 182118  2.700801 -4.840134          197            3.165545         3.169174\n",
+       " 182119  2.702502 -4.840009          197            3.164571         3.169174\n",
+       " 182120  2.704204 -4.840009          197            3.163574         3.169174\n",
+       " 182121  2.705906 -4.840009          197            3.162578         3.169174\n",
+       " 182122  2.707608 -4.840009          197            3.161568         3.169174\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 182886  4.007708 -4.840058          197            0.000110         3.169174\n",
+       " 182887  4.009409 -4.840102          197            0.000096         3.169174\n",
+       " 182888  4.011111 -4.840147          197            0.000082         3.169174\n",
+       " 182889  4.012813 -4.840190          197            0.000068         3.169174\n",
+       " 182890  4.014514 -4.840235          197            0.000054         3.169174\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 183118  2.700801 -4.839783          198            3.161422         3.164944\n",
+       " 183119  2.702502 -4.839630          198            3.160439         3.164944\n",
+       " 183120  2.704204 -4.839780          198            3.159434         3.164944\n",
+       " 183121  2.705906 -4.839931          198            3.158428         3.164944\n",
+       " 183122  2.707608 -4.840044          198            3.157416         3.164944\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 183888  4.011111 -4.843479          198            0.000095         3.164944\n",
+       " 183889  4.012813 -4.843725          198            0.000082         3.164944\n",
+       " 183890  4.014514 -4.843971          198            0.000070         3.164944\n",
+       " 183891  4.016216 -4.844218          198            0.000058         3.164944\n",
+       " 183892  4.017918 -4.844464          198            0.000046         3.164944\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 184118  2.700801 -4.839742          199            3.158149         3.161119\n",
+       " 184119  2.702502 -4.840035          199            3.157200         3.161119\n",
+       " 184120  2.704204 -4.840110          199            3.156182         3.161119\n",
+       " 184121  2.705906 -4.840185          199            3.155163         3.161119\n",
+       " 184122  2.707608 -4.840195          199            3.154149         3.161119\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 184888  4.011111 -4.844336          199            0.000092         3.161119\n",
+       " 184889  4.012813 -4.844662          199            0.000080         3.161119\n",
+       " 184890  4.014514 -4.844988          199            0.000068         3.161119\n",
+       " 184891  4.016216 -4.845315          199            0.000055         3.161119\n",
+       " 184892  4.017918 -4.845641          199            0.000043         3.161119\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 185118  2.700801 -4.839626          200            3.154541         3.157866\n",
+       " 185119  2.702502 -4.839786          200            3.153562         3.157866\n",
+       " 185120  2.704204 -4.839945          200            3.152583         3.157866\n",
+       " 185121  2.705906 -4.840055          200            3.151579         3.157866\n",
+       " 185122  2.707608 -4.840131          200            3.150558         3.157866\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 185888  4.011111 -4.845112          200            0.000091         3.157866\n",
+       " 185889  4.012813 -4.845479          200            0.000079         3.157866\n",
+       " 185890  4.014514 -4.845846          200            0.000067         3.157866\n",
+       " 185891  4.016216 -4.846212          200            0.000054         3.157866\n",
+       " 185892  4.017918 -4.846579          200            0.000042         3.157866\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 186118  2.700801 -4.840308          201            3.148093         3.153113\n",
+       " 186119  2.702502 -4.840119          201            3.147108         3.153113\n",
+       " 186120  2.704204 -4.839969          201            3.146111         3.153113\n",
+       " 186121  2.705906 -4.839818          201            3.145115         3.153113\n",
+       " 186122  2.707608 -4.840001          201            3.144103         3.153113\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 186888  4.011111 -4.844589          201            0.000089         3.153113\n",
+       " 186889  4.012813 -4.844932          201            0.000077         3.153113\n",
+       " 186890  4.014514 -4.845273          201            0.000065         3.153113\n",
+       " 186891  4.016216 -4.845616          201            0.000052         3.153113\n",
+       " 186892  4.017918 -4.845958          201            0.000040         3.153113\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 187118  2.700801 -4.839780          202            3.143798         3.146037\n",
+       " 187119  2.702502 -4.839852          202            3.142816         3.146037\n",
+       " 187120  2.704204 -4.839926          202            3.141834         3.146037\n",
+       " 187121  2.705906 -4.840000          202            3.140852         3.146037\n",
+       " 187122  2.707608 -4.840009          202            3.139835         3.146037\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 187887  4.009409 -4.844513          202            0.000100         3.146037\n",
+       " 187888  4.011111 -4.844858          202            0.000088         3.146037\n",
+       " 187889  4.012813 -4.845201          202            0.000075         3.146037\n",
+       " 187890  4.014514 -4.845545          202            0.000063         3.146037\n",
+       " 187891  4.016216 -4.845889          202            0.000051         3.146037\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 188118  2.700801 -4.839780          203            3.138533         3.142476\n",
+       " 188119  2.702502 -4.839780          203            3.137533         3.142476\n",
+       " 188120  2.704204 -4.839780          203            3.136534         3.142476\n",
+       " 188121  2.705906 -4.839828          203            3.135534         3.142476\n",
+       " 188122  2.707608 -4.839903          203            3.134532         3.142476\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 188888  4.011111 -4.842219          203            0.000090         3.142476\n",
+       " 188889  4.012813 -4.842353          203            0.000078         3.142476\n",
+       " 188890  4.014514 -4.842487          203            0.000065         3.142476\n",
+       " 188891  4.016216 -4.842621          203            0.000052         3.142476\n",
+       " 188892  4.017918 -4.842755          203            0.000040         3.142476\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 189118  2.700801 -4.839810          204            3.133744         3.136071\n",
+       " 189119  2.702502 -4.839963          204            3.132728         3.136071\n",
+       " 189120  2.704204 -4.840115          204            3.131712         3.136071\n",
+       " 189121  2.705906 -4.840223          204            3.130698         3.136071\n",
+       " 189122  2.707608 -4.840147          204            3.129696         3.136071\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 189887  4.009409 -4.842788          204            0.000098         3.136071\n",
+       " 189888  4.011111 -4.843027          204            0.000085         3.136071\n",
+       " 189889  4.012813 -4.843266          204            0.000073         3.136071\n",
+       " 189890  4.014514 -4.843506          204            0.000060         3.136071\n",
+       " 189891  4.016216 -4.843745          204            0.000048         3.136071\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 190118  2.700801 -4.840009          205            3.129385         3.132736\n",
+       " 190119  2.702502 -4.840009          205            3.128402         3.132736\n",
+       " 190120  2.704204 -4.840009          205            3.127418         3.132736\n",
+       " 190121  2.705906 -4.840041          205            3.126411         3.132736\n",
+       " 190122  2.707608 -4.840116          205            3.125370         3.132736\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 190887  4.009409 -4.843688          205            0.000095         3.132736\n",
+       " 190888  4.011111 -4.843995          205            0.000083         3.132736\n",
+       " 190889  4.012813 -4.844302          205            0.000070         3.132736\n",
+       " 190890  4.014514 -4.844608          205            0.000058         3.132736\n",
+       " 190891  4.016216 -4.844914          205            0.000045         3.132736\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 191118  2.700801 -4.840009          206            3.127661         3.128958\n",
+       " 191119  2.702502 -4.840009          206            3.126670         3.128958\n",
+       " 191120  2.704204 -4.840009          206            3.125673         3.128958\n",
+       " 191121  2.705906 -4.840009          206            3.124674         3.128958\n",
+       " 191122  2.707608 -4.840009          206            3.123676         3.128958\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 191887  4.009409 -4.844894          206            0.000093         3.128958\n",
+       " 191888  4.011111 -4.845253          206            0.000080         3.128958\n",
+       " 191889  4.012813 -4.845612          206            0.000068         3.128958\n",
+       " 191890  4.014514 -4.845971          206            0.000055         3.128958\n",
+       " 191891  4.016216 -4.846330          206            0.000043         3.128958\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 192118  2.700801 -4.839960          207            3.124383         3.127167\n",
+       " 192119  2.702502 -4.839853          207            3.123427         3.127167\n",
+       " 192120  2.704204 -4.839756          207            3.122450         3.127167\n",
+       " 192121  2.705906 -4.839680          207            3.121425         3.127167\n",
+       " 192122  2.707608 -4.839604          207            3.120400         3.127167\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 192887  4.009409 -4.843634          207            0.000093         3.127167\n",
+       " 192888  4.011111 -4.843909          207            0.000080         3.127167\n",
+       " 192889  4.012813 -4.844185          207            0.000068         3.127167\n",
+       " 192890  4.014514 -4.844460          207            0.000056         3.127167\n",
+       " 192891  4.016216 -4.844736          207            0.000043         3.127167\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 193118  2.700801 -4.839780          208            3.122960         3.123251\n",
+       " 193119  2.702502 -4.839780          208            3.122009         3.123251\n",
+       " 193120  2.704204 -4.839780          208            3.121058         3.123251\n",
+       " 193121  2.705906 -4.839780          208            3.120082         3.123251\n",
+       " 193122  2.707608 -4.839780          208            3.119088         3.123251\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 193887  4.009409 -4.842808          208            0.000090         3.123251\n",
+       " 193888  4.011111 -4.843018          208            0.000078         3.123251\n",
+       " 193889  4.012813 -4.843228          208            0.000066         3.123251\n",
+       " 193890  4.014514 -4.843438          208            0.000053         3.123251\n",
+       " 193891  4.016216 -4.843648          208            0.000041         3.123251\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 194118  2.700801 -4.839849          209            3.117386         3.121109\n",
+       " 194119  2.702502 -4.839994          209            3.116418         3.121109\n",
+       " 194120  2.704204 -4.839879          209            3.115446         3.121109\n",
+       " 194121  2.705906 -4.839733          209            3.114474         3.121109\n",
+       " 194122  2.707608 -4.839587          209            3.113502         3.121109\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 194886  4.007708 -4.843480          209            0.000097         3.121109\n",
+       " 194887  4.009409 -4.843767          209            0.000085         3.121109\n",
+       " 194888  4.011111 -4.844053          209            0.000072         3.121109\n",
+       " 194889  4.012813 -4.844340          209            0.000060         3.121109\n",
+       " 194890  4.014514 -4.844626          209            0.000048         3.121109\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 195118  2.700801 -4.839959          210            3.112344         3.117079\n",
+       " 195119  2.702502 -4.839850          210            3.111374         3.117079\n",
+       " 195120  2.704204 -4.839780          210            3.110386         3.117079\n",
+       " 195121  2.705906 -4.839780          210            3.109366         3.117079\n",
+       " 195122  2.707608 -4.839780          210            3.108346         3.117079\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 195886  4.007708 -4.842032          210            0.000096         3.117079\n",
+       " 195887  4.009409 -4.842189          210            0.000084         3.117079\n",
+       " 195888  4.011111 -4.842346          210            0.000072         3.117079\n",
+       " 195889  4.012813 -4.842503          210            0.000060         3.117079\n",
+       " 195890  4.014514 -4.842659          210            0.000047         3.117079\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 196118  2.700801 -4.840009          211            3.108503         3.112309\n",
+       " 196119  2.702502 -4.840009          211            3.107542         3.112309\n",
+       " 196120  2.704204 -4.839972          211            3.106559         3.112309\n",
+       " 196121  2.705906 -4.839895          211            3.105552         3.112309\n",
+       " 196122  2.707608 -4.839819          211            3.104545         3.112309\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 196886  4.007708 -4.844547          211            0.000095         3.112309\n",
+       " 196887  4.009409 -4.844909          211            0.000083         3.112309\n",
+       " 196888  4.011111 -4.845272          211            0.000070         3.112309\n",
+       " 196889  4.012813 -4.845635          211            0.000058         3.112309\n",
+       " 196890  4.014514 -4.845998          211            0.000046         3.112309\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 197118  2.700801 -4.840009          212            3.104625         3.108351\n",
+       " 197119  2.702502 -4.839879          212            3.103653         3.108351\n",
+       " 197120  2.704204 -4.839731          212            3.102693         3.108351\n",
+       " 197121  2.705906 -4.839582          212            3.101732         3.108351\n",
+       " 197122  2.707608 -4.839732          212            3.100717         3.108351\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 197886  4.007708 -4.842453          212            0.000094         3.108351\n",
+       " 197887  4.009409 -4.842673          212            0.000082         3.108351\n",
+       " 197888  4.011111 -4.842894          212            0.000070         3.108351\n",
+       " 197889  4.012813 -4.843115          212            0.000058         3.108351\n",
+       " 197890  4.014514 -4.843336          212            0.000046         3.108351\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 198118  2.700801 -4.839941          213            3.100646         3.104242\n",
+       " 198119  2.702502 -4.839796          213            3.099643         3.104242\n",
+       " 198120  2.704204 -4.839780          213            3.098667         3.104242\n",
+       " 198121  2.705906 -4.839780          213            3.097693         3.104242\n",
+       " 198122  2.707608 -4.839780          213            3.096720         3.104242\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 198886  4.007708 -4.844698          213            0.000094         3.104242\n",
+       " 198887  4.009409 -4.845034          213            0.000081         3.104242\n",
+       " 198888  4.011111 -4.845370          213            0.000069         3.104242\n",
+       " 198889  4.012813 -4.845706          213            0.000057         3.104242\n",
+       " 198890  4.014514 -4.846042          213            0.000045         3.104242\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 199118  2.700801 -4.839568          214            3.097132         3.101057\n",
+       " 199119  2.702502 -4.839720          214            3.096116         3.101057\n",
+       " 199120  2.704204 -4.839873          214            3.095100         3.101057\n",
+       " 199121  2.705906 -4.840009          214            3.094084         3.101057\n",
+       " 199122  2.707608 -4.840009          214            3.093072         3.101057\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 199886  4.007708 -4.843466          214            0.000092         3.101057\n",
+       " 199887  4.009409 -4.843727          214            0.000080         3.101057\n",
+       " 199888  4.011111 -4.843987          214            0.000068         3.101057\n",
+       " 199889  4.012813 -4.844247          214            0.000056         3.101057\n",
+       " 199890  4.014514 -4.844508          214            0.000043         3.101057\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 200118  2.700801 -4.839839          215            3.094979         3.097387\n",
+       " 200119  2.702502 -4.839582          215            3.093973         3.097387\n",
+       " 200120  2.704204 -4.839731          215            3.093013         3.097387\n",
+       " 200121  2.705906 -4.839879          215            3.092052         3.097387\n",
+       " 200122  2.707608 -4.840018          215            3.091084         3.097387\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 200886  4.007708 -4.843324          215            0.000091         3.097387\n",
+       " 200887  4.009409 -4.843572          215            0.000079         3.097387\n",
+       " 200888  4.011111 -4.843820          215            0.000066         3.097387\n",
+       " 200889  4.012813 -4.844068          215            0.000054         3.097387\n",
+       " 200890  4.014514 -4.844316          215            0.000042         3.097387\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 201118  2.700801 -4.840009          216            3.094646         3.096283\n",
+       " 201119  2.702502 -4.840009          216            3.093657         3.096283\n",
+       " 201120  2.704204 -4.840009          216            3.092661         3.096283\n",
+       " 201121  2.705906 -4.840009          216            3.091664         3.096283\n",
+       " 201122  2.707608 -4.839977          216            3.090666         3.096283\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 201886  4.007708 -4.842985          216            0.000093         3.096283\n",
+       " 201887  4.009409 -4.843243          216            0.000081         3.096283\n",
+       " 201888  4.011111 -4.843501          216            0.000069         3.096283\n",
+       " 201889  4.012813 -4.843759          216            0.000057         3.096283\n",
+       " 201890  4.014514 -4.844017          216            0.000045         3.096283\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 202118  2.700801 -4.840174          217            3.091648         3.094283\n",
+       " 202119  2.702502 -4.839948          217            3.090660         3.094283\n",
+       " 202120  2.704204 -4.839723          217            3.089672         3.094283\n",
+       " 202121  2.705906 -4.839551          217            3.088684         3.094283\n",
+       " 202122  2.707608 -4.839551          217            3.087696         3.094283\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 202886  4.007708 -4.843971          217            0.000090         3.094283\n",
+       " 202887  4.009409 -4.844231          217            0.000078         3.094283\n",
+       " 202888  4.011111 -4.844491          217            0.000066         3.094283\n",
+       " 202889  4.012813 -4.844752          217            0.000053         3.094283\n",
+       " 202890  4.014514 -4.845013          217            0.000041         3.094283\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 203118  2.700801 -4.839783          218            3.088259          3.09106\n",
+       " 203119  2.702502 -4.839629          218            3.087273          3.09106\n",
+       " 203120  2.704204 -4.839777          218            3.086312          3.09106\n",
+       " 203121  2.705906 -4.839925          218            3.085352          3.09106\n",
+       " 203122  2.707608 -4.840009          218            3.084363          3.09106\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 203886  4.007708 -4.843301          218            0.000089          3.09106\n",
+       " 203887  4.009409 -4.843560          218            0.000077          3.09106\n",
+       " 203888  4.011111 -4.843819          218            0.000065          3.09106\n",
+       " 203889  4.012813 -4.844079          218            0.000053          3.09106\n",
+       " 203890  4.014514 -4.844337          218            0.000041          3.09106\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 204118  2.700801 -4.840011          219            3.082583         3.086295\n",
+       " 204119  2.702502 -4.840085          219            3.081614         3.086295\n",
+       " 204120  2.704204 -4.840158          219            3.080645         3.086295\n",
+       " 204121  2.705906 -4.840232          219            3.079676         3.086295\n",
+       " 204122  2.707608 -4.840238          219            3.078669         3.086295\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 204885  4.006006 -4.843579          219            0.000098         3.086295\n",
+       " 204886  4.007708 -4.843836          219            0.000086         3.086295\n",
+       " 204887  4.009409 -4.844093          219            0.000074         3.086295\n",
+       " 204888  4.011111 -4.844350          219            0.000062         3.086295\n",
+       " 204889  4.012813 -4.844607          219            0.000049         3.086295\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 205118  2.700801 -4.839918          220            3.081560         3.085255\n",
+       " 205119  2.702502 -4.839780          220            3.080614         3.085255\n",
+       " 205120  2.704204 -4.839780          220            3.079640         3.085255\n",
+       " 205121  2.705906 -4.839780          220            3.078667         3.085255\n",
+       " 205122  2.707608 -4.839796          220            3.077686         3.085255\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 205885  4.006006 -4.843283          220            0.000098         3.085255\n",
+       " 205886  4.007708 -4.843551          220            0.000086         3.085255\n",
+       " 205887  4.009409 -4.843820          220            0.000074         3.085255\n",
+       " 205888  4.011111 -4.844089          220            0.000062         3.085255\n",
+       " 205889  4.012813 -4.844357          220            0.000050         3.085255\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 206118  2.700801 -4.840009          221            3.079341         3.082128\n",
+       " 206119  2.702502 -4.840009          221            3.078386         3.082128\n",
+       " 206120  2.704204 -4.840009          221            3.077430         3.082128\n",
+       " 206121  2.705906 -4.840009          221            3.076475         3.082128\n",
+       " 206122  2.707608 -4.840009          221            3.075445         3.082128\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 206885  4.006006 -4.843408          221            0.000095         3.082128\n",
+       " 206886  4.007708 -4.843665          221            0.000083         3.082128\n",
+       " 206887  4.009409 -4.843922          221            0.000071         3.082128\n",
+       " 206888  4.011111 -4.844179          221            0.000059         3.082128\n",
+       " 206889  4.012813 -4.844436          221            0.000047         3.082128\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 207118  2.700801 -4.839822          222            3.077083         3.080282\n",
+       " 207119  2.702502 -4.839911          222            3.076120         3.080282\n",
+       " 207120  2.704204 -4.840001          222            3.075158         3.080282\n",
+       " 207121  2.705906 -4.839941          222            3.074164         3.080282\n",
+       " 207122  2.707608 -4.839866          222            3.073168         3.080282\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 207885  4.006006 -4.842766          222            0.000096         3.080282\n",
+       " 207886  4.007708 -4.843009          222            0.000084         3.080282\n",
+       " 207887  4.009409 -4.843252          222            0.000072         3.080282\n",
+       " 207888  4.011111 -4.843494          222            0.000060         3.080282\n",
+       " 207889  4.012813 -4.843737          222            0.000048         3.080282\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 208118  2.700801 -4.839780          223            3.073329         3.076107\n",
+       " 208119  2.702502 -4.839838          223            3.072339         3.076107\n",
+       " 208120  2.704204 -4.839986          223            3.071366         3.076107\n",
+       " 208121  2.705906 -4.840134          223            3.070392         3.076107\n",
+       " 208122  2.707608 -4.840195          223            3.069415         3.076107\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 208885  4.006006 -4.844770          223            0.000093         3.076107\n",
+       " 208886  4.007708 -4.845144          223            0.000081         3.076107\n",
+       " 208887  4.009409 -4.845518          223            0.000069         3.076107\n",
+       " 208888  4.011111 -4.845892          223            0.000057         3.076107\n",
+       " 208889  4.012813 -4.846266          223            0.000045         3.076107\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 209118  2.700801 -4.840009          224            3.071419         3.073992\n",
+       " 209119  2.702502 -4.840009          224            3.070448         3.073992\n",
+       " 209120  2.704204 -4.840009          224            3.069477         3.073992\n",
+       " 209121  2.705906 -4.839974          224            3.068500         3.073992\n",
+       " 209122  2.707608 -4.839900          224            3.067517         3.073992\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 209885  4.006006 -4.843720          224            0.000096         3.073992\n",
+       " 209886  4.007708 -4.843998          224            0.000084         3.073992\n",
+       " 209887  4.009409 -4.844276          224            0.000073         3.073992\n",
+       " 209888  4.011111 -4.844554          224            0.000061         3.073992\n",
+       " 209889  4.012813 -4.844832          224            0.000049         3.073992\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 210118  2.700801 -4.839805          225            3.069803         3.071456\n",
+       " 210119  2.702502 -4.839878          225            3.068835         3.071456\n",
+       " 210120  2.704204 -4.839951          225            3.067867         3.071456\n",
+       " 210121  2.705906 -4.840009          225            3.066897         3.071456\n",
+       " 210122  2.707608 -4.840009          225            3.065919         3.071456\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 210885  4.006006 -4.843104          225            0.000096         3.071456\n",
+       " 210886  4.007708 -4.843324          225            0.000084         3.071456\n",
+       " 210887  4.009409 -4.843543          225            0.000072         3.071456\n",
+       " 210888  4.011111 -4.843762          225            0.000060         3.071456\n",
+       " 210889  4.012813 -4.843981          225            0.000048         3.071456\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 211118  2.700801 -4.840106          226            3.066835         3.068782\n",
+       " 211119  2.702502 -4.839959          226            3.065881         3.068782\n",
+       " 211120  2.704204 -4.839883          226            3.064950         3.068782\n",
+       " 211121  2.705906 -4.839807          226            3.064019         3.068782\n",
+       " 211122  2.707608 -4.839780          226            3.063025         3.068782\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 211885  4.006006 -4.842235          226            0.000094         3.068782\n",
+       " 211886  4.007708 -4.842409          226            0.000081         3.068782\n",
+       " 211887  4.009409 -4.842582          226            0.000069         3.068782\n",
+       " 211888  4.011111 -4.842756          226            0.000056         3.068782\n",
+       " 211889  4.012813 -4.842930          226            0.000044         3.068782\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 212118  2.700801 -4.839632          227            3.062199         3.064647\n",
+       " 212119  2.702502 -4.839805          227            3.061233         3.064647\n",
+       " 212120  2.704204 -4.839978          227            3.060268         3.064647\n",
+       " 212121  2.705906 -4.839888          227            3.059292         3.064647\n",
+       " 212122  2.707608 -4.839740          227            3.058314         3.064647\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 212885  4.006006 -4.842846          227            0.000095         3.064647\n",
+       " 212886  4.007708 -4.843081          227            0.000083         3.064647\n",
+       " 212887  4.009409 -4.843315          227            0.000070         3.064647\n",
+       " 212888  4.011111 -4.843550          227            0.000058         3.064647\n",
+       " 212889  4.012813 -4.843784          227            0.000046         3.064647\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 213118  2.700801 -4.840047          228            3.058721         3.061237\n",
+       " 213119  2.702502 -4.840130          228            3.057763         3.061237\n",
+       " 213120  2.704204 -4.840212          228            3.056805         3.061237\n",
+       " 213121  2.705906 -4.840188          228            3.055822         3.061237\n",
+       " 213122  2.707608 -4.840113          228            3.054827         3.061237\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 213885  4.006006 -4.842706          228            0.000093         3.061237\n",
+       " 213886  4.007708 -4.842927          228            0.000081         3.061237\n",
+       " 213887  4.009409 -4.843149          228            0.000069         3.061237\n",
+       " 213888  4.011111 -4.843370          228            0.000056         3.061237\n",
+       " 213889  4.012813 -4.843591          228            0.000044         3.061237\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 214118  2.700801 -4.840163          229            3.053263          3.05599\n",
+       " 214119  2.702502 -4.840001          229            3.052306          3.05599\n",
+       " 214120  2.704204 -4.839839          229            3.051349          3.05599\n",
+       " 214121  2.705906 -4.839878          229            3.050363          3.05599\n",
+       " 214122  2.707608 -4.840031          229            3.049361          3.05599\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 214885  4.006006 -4.843001          229            0.000089          3.05599\n",
+       " 214886  4.007708 -4.843221          229            0.000077          3.05599\n",
+       " 214887  4.009409 -4.843441          229            0.000065          3.05599\n",
+       " 214888  4.011111 -4.843660          229            0.000053          3.05599\n",
+       " 214889  4.012813 -4.843880          229            0.000041          3.05599\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 215118  2.700801 -4.839969          230            3.052111         3.053115\n",
+       " 215119  2.702502 -4.839882          230            3.051135         3.053115\n",
+       " 215120  2.704204 -4.839796          230            3.050159         3.053115\n",
+       " 215121  2.705906 -4.839840          230            3.049193         3.053115\n",
+       " 215122  2.707608 -4.839913          230            3.048229         3.053115\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 215885  4.006006 -4.842140          230            0.000088         3.053115\n",
+       " 215886  4.007708 -4.842294          230            0.000076         3.053115\n",
+       " 215887  4.009409 -4.842448          230            0.000064         3.053115\n",
+       " 215888  4.011111 -4.842601          230            0.000052         3.053115\n",
+       " 215889  4.012813 -4.842755          230            0.000040         3.053115\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 216118  2.700801 -4.840238          231            3.051766         3.051822\n",
+       " 216119  2.702502 -4.840238          231            3.050799         3.051822\n",
+       " 216120  2.704204 -4.840238          231            3.049832         3.051822\n",
+       " 216121  2.705906 -4.840175          231            3.048883         3.051822\n",
+       " 216122  2.707608 -4.840102          231            3.047936         3.051822\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 216884  4.004304 -4.843141          231            0.000097         3.051822\n",
+       " 216885  4.006006 -4.843398          231            0.000085         3.051822\n",
+       " 216886  4.007708 -4.843655          231            0.000073         3.051822\n",
+       " 216887  4.009409 -4.843912          231            0.000061         3.051822\n",
+       " 216888  4.011111 -4.844169          231            0.000049         3.051822\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 217118  2.700801 -4.840293          232            3.049388         3.052211\n",
+       " 217119  2.702502 -4.840412          232            3.048453         3.052211\n",
+       " 217120  2.704204 -4.840386          232            3.047483         3.052211\n",
+       " 217121  2.705906 -4.840236          232            3.046482         3.052211\n",
+       " 217122  2.707608 -4.840086          232            3.045481         3.052211\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 217884  4.004304 -4.842210          232            0.000096         3.052211\n",
+       " 217885  4.006006 -4.842377          232            0.000084         3.052211\n",
+       " 217886  4.007708 -4.842544          232            0.000072         3.052211\n",
+       " 217887  4.009409 -4.842710          232            0.000060         3.052211\n",
+       " 217888  4.011111 -4.842877          232            0.000047         3.052211\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 218118  2.700801 -4.839860          233            3.045367         3.048809\n",
+       " 218119  2.702502 -4.839554          233            3.044376         3.048809\n",
+       " 218120  2.704204 -4.839629          233            3.043427         3.048809\n",
+       " 218121  2.705906 -4.839704          233            3.042479         3.048809\n",
+       " 218122  2.707608 -4.839779          233            3.041531         3.048809\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 218884  4.004304 -4.843785          233            0.000094         3.048809\n",
+       " 218885  4.006006 -4.844067          233            0.000081         3.048809\n",
+       " 218886  4.007708 -4.844349          233            0.000069         3.048809\n",
+       " 218887  4.009409 -4.844631          233            0.000057         3.048809\n",
+       " 218888  4.011111 -4.844913          233            0.000045         3.048809\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 219118  2.700801 -4.840184          234            3.043969         3.046526\n",
+       " 219119  2.702502 -4.839576          234            3.043062         3.046526\n",
+       " 219120  2.704204 -4.839452          234            3.042099         3.046526\n",
+       " 219121  2.705906 -4.839674          234            3.041095         3.046526\n",
+       " 219122  2.707608 -4.839896          234            3.040091         3.046526\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 219884  4.004304 -4.843150          234            0.000096         3.046526\n",
+       " 219885  4.006006 -4.843403          234            0.000085         3.046526\n",
+       " 219886  4.007708 -4.843656          234            0.000073         3.046526\n",
+       " 219887  4.009409 -4.843908          234            0.000061         3.046526\n",
+       " 219888  4.011111 -4.844161          234            0.000049         3.046526\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 220118  2.700801 -4.840163          235            3.043367         3.045318\n",
+       " 220119  2.702502 -4.840456          235            3.042408         3.045318\n",
+       " 220120  2.704204 -4.840303          235            3.041433         3.045318\n",
+       " 220121  2.705906 -4.840150          235            3.040457         3.045318\n",
+       " 220122  2.707608 -4.839998          235            3.039480         3.045318\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 220884  4.004304 -4.842895          235            0.000098         3.045318\n",
+       " 220885  4.006006 -4.843151          235            0.000086         3.045318\n",
+       " 220886  4.007708 -4.843407          235            0.000074         3.045318\n",
+       " 220887  4.009409 -4.843663          235            0.000062         3.045318\n",
+       " 220888  4.011111 -4.843918          235            0.000050         3.045318\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 221118  2.700801 -4.840009          236            3.038611         3.043005\n",
+       " 221119  2.702502 -4.840009          236            3.037624         3.043005\n",
+       " 221120  2.704204 -4.840009          236            3.036636         3.043005\n",
+       " 221121  2.705906 -4.839982          236            3.035655         3.043005\n",
+       " 221122  2.707608 -4.839908          236            3.034686         3.043005\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 221884  4.004304 -4.842183          236            0.000094         3.043005\n",
+       " 221885  4.006006 -4.842360          236            0.000082         3.043005\n",
+       " 221886  4.007708 -4.842538          236            0.000070         3.043005\n",
+       " 221887  4.009409 -4.842716          236            0.000058         3.043005\n",
+       " 221888  4.011111 -4.842894          236            0.000046         3.043005\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 222118  2.700801 -4.839865          237            3.037155         3.038159\n",
+       " 222119  2.702502 -4.839978          237            3.036216         3.038159\n",
+       " 222120  2.704204 -4.839828          237            3.035250         3.038159\n",
+       " 222121  2.705906 -4.839677          237            3.034285         3.038159\n",
+       " 222122  2.707608 -4.839564          237            3.033315         3.038159\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 222884  4.004304 -4.842948          237            0.000092         3.038159\n",
+       " 222885  4.006006 -4.843164          237            0.000080         3.038159\n",
+       " 222886  4.007708 -4.843379          237            0.000069         3.038159\n",
+       " 222887  4.009409 -4.843595          237            0.000057         3.038159\n",
+       " 222888  4.011111 -4.843810          237            0.000045         3.038159\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 223118  2.700801 -4.839899          238            3.033157         3.037202\n",
+       " 223119  2.702502 -4.839661          238            3.032216         3.037202\n",
+       " 223120  2.704204 -4.839673          238            3.031254         3.037202\n",
+       " 223121  2.705906 -4.839898          238            3.030275         3.037202\n",
+       " 223122  2.707608 -4.840123          238            3.029296         3.037202\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 223884  4.004304 -4.844242          238            0.000092         3.037202\n",
+       " 223885  4.006006 -4.844583          238            0.000080         3.037202\n",
+       " 223886  4.007708 -4.844923          238            0.000068         3.037202\n",
+       " 223887  4.009409 -4.845263          238            0.000056         3.037202\n",
+       " 223888  4.011111 -4.845603          238            0.000044         3.037202\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 224118  2.700801 -4.839889          239            3.030263         3.032679\n",
+       " 224119  2.702502 -4.840009          239            3.029269         3.032679\n",
+       " 224120  2.704204 -4.840009          239            3.028322         3.032679\n",
+       " 224121  2.705906 -4.840009          239            3.027375         3.032679\n",
+       " 224122  2.707608 -4.840039          239            3.026401         3.032679\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 224884  4.004304 -4.843635          239            0.000089         3.032679\n",
+       " 224885  4.006006 -4.843862          239            0.000078         3.032679\n",
+       " 224886  4.007708 -4.844089          239            0.000066         3.032679\n",
+       " 224887  4.009409 -4.844316          239            0.000054         3.032679\n",
+       " 224888  4.011111 -4.844543          239            0.000042         3.032679\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 225118  2.700801 -4.839944          240            3.030219         3.031552\n",
+       " 225119  2.702502 -4.840201          240            3.029309         3.031552\n",
+       " 225120  2.704204 -4.839975          240            3.028348         3.031552\n",
+       " 225121  2.705906 -4.839750          240            3.027387         3.031552\n",
+       " 225122  2.707608 -4.839551          240            3.026423         3.031552\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 225884  4.004304 -4.844999          240            0.000090         3.031552\n",
+       " 225885  4.006006 -4.845392          240            0.000078         3.031552\n",
+       " 225886  4.007708 -4.845785          240            0.000066         3.031552\n",
+       " 225887  4.009409 -4.846177          240            0.000054         3.031552\n",
+       " 225888  4.011111 -4.846570          240            0.000042         3.031552\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 226118  2.700801 -4.840009          241            3.028227         3.030846\n",
+       " 226119  2.702502 -4.839985          241            3.027266         3.030846\n",
+       " 226120  2.704204 -4.839837          241            3.026305         3.030846\n",
+       " 226121  2.705906 -4.839689          241            3.025345         3.030846\n",
+       " 226122  2.707608 -4.839557          241            3.024384         3.030846\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 226884  4.004304 -4.844015          241            0.000089         3.030846\n",
+       " 226885  4.006006 -4.844318          241            0.000077         3.030846\n",
+       " 226886  4.007708 -4.844621          241            0.000065         3.030846\n",
+       " 226887  4.009409 -4.844924          241            0.000053         3.030846\n",
+       " 226888  4.011111 -4.845228          241            0.000042         3.030846\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 227118  2.700801 -4.840210          242            3.028423         3.028458\n",
+       " 227119  2.702502 -4.840136          242            3.027467         3.028458\n",
+       " 227120  2.704204 -4.840062          242            3.026511         3.028458\n",
+       " 227121  2.705906 -4.840031          242            3.025547         3.028458\n",
+       " 227122  2.707608 -4.840107          242            3.024562         3.028458\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 227883  4.002603 -4.843564          242            0.000098         3.028458\n",
+       " 227884  4.004304 -4.843867          242            0.000086         3.028458\n",
+       " 227885  4.006006 -4.844171          242            0.000074         3.028458\n",
+       " 227886  4.007708 -4.844474          242            0.000062         3.028458\n",
+       " 227887  4.009409 -4.844777          242            0.000050         3.028458\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 228118  2.700801 -4.840008          243            3.026736         3.030806\n",
+       " 228119  2.702502 -4.839933          243            3.025774         3.030806\n",
+       " 228120  2.704204 -4.839858          243            3.024813         3.030806\n",
+       " 228121  2.705906 -4.839783          243            3.023852         3.030806\n",
+       " 228122  2.707608 -4.839780          243            3.022856         3.030806\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 228883  4.002603 -4.844771          243            0.000098         3.030806\n",
+       " 228884  4.004304 -4.845149          243            0.000087         3.030806\n",
+       " 228885  4.006006 -4.845526          243            0.000075         3.030806\n",
+       " 228886  4.007708 -4.845903          243            0.000063         3.030806\n",
+       " 228887  4.009409 -4.846280          243            0.000051         3.030806\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 229118  2.700801 -4.839780          244            3.026008         3.027682\n",
+       " 229119  2.702502 -4.839780          244            3.025045         3.027682\n",
+       " 229120  2.704204 -4.839780          244            3.024082         3.027682\n",
+       " 229121  2.705906 -4.839742          244            3.023122         3.027682\n",
+       " 229122  2.707608 -4.839667          244            3.022165         3.027682\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 229884  4.004304 -4.842840          244            0.000089         3.027682\n",
+       " 229885  4.006006 -4.843040          244            0.000077         3.027682\n",
+       " 229886  4.007708 -4.843241          244            0.000065         3.027682\n",
+       " 229887  4.009409 -4.843441          244            0.000053         3.027682\n",
+       " 229888  4.011111 -4.843641          244            0.000041         3.027682\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 230118  2.700801 -4.839780          245            3.026684         3.028399\n",
+       " 230119  2.702502 -4.839780          245            3.025732         3.028399\n",
+       " 230120  2.704204 -4.839780          245            3.024758         3.028399\n",
+       " 230121  2.705906 -4.839780          245            3.023785         3.028399\n",
+       " 230122  2.707608 -4.839825          245            3.022802         3.028399\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 230884  4.004304 -4.843523          245            0.000090         3.028399\n",
+       " 230885  4.006006 -4.843824          245            0.000079         3.028399\n",
+       " 230886  4.007708 -4.844126          245            0.000067         3.028399\n",
+       " 230887  4.009409 -4.844428          245            0.000055         3.028399\n",
+       " 230888  4.011111 -4.844729          245            0.000043         3.028399\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 231118  2.700801 -4.839872          251            3.429013         3.249756\n",
+       " 231119  2.702502 -4.840068          251            3.428050         3.249756\n",
+       " 231120  2.704204 -4.840238          251            3.427087         3.249756\n",
+       " 231121  2.705906 -4.840238          251            3.426126         3.249756\n",
+       " 231122  2.707608 -4.840238          251            3.425164         3.249756\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 231896  4.024725 -4.843005          251            0.000089         3.249756\n",
+       " 231897  4.026426 -4.843201          251            0.000078         3.249756\n",
+       " 231898  4.028128 -4.843397          251            0.000068         3.249756\n",
+       " 231899  4.029830 -4.843593          251            0.000057         3.249756\n",
+       " 231900  4.031531 -4.843789          251            0.000046         3.249756\n",
+       " \n",
+       " [783 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 232118  2.700801 -4.839830          252            3.387462         3.392013\n",
+       " 232119  2.702502 -4.839936          252            3.386481         3.392013\n",
+       " 232120  2.704204 -4.839986          252            3.385504         3.392013\n",
+       " 232121  2.705906 -4.839912          252            3.384535         3.392013\n",
+       " 232122  2.707608 -4.839838          252            3.383565         3.392013\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 232893  4.019619 -4.843691          252            0.000090         3.392013\n",
+       " 232894  4.021321 -4.843940          252            0.000079         3.392013\n",
+       " 232895  4.023023 -4.844189          252            0.000068         3.392013\n",
+       " 232896  4.024725 -4.844437          252            0.000057         3.392013\n",
+       " 232897  4.026426 -4.844686          252            0.000046         3.392013\n",
+       " \n",
+       " [780 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 233118  2.700801 -4.839821          253            3.356671         3.370071\n",
+       " 233119  2.702502 -4.839910          253            3.355684         3.370071\n",
+       " 233120  2.704204 -4.839997          253            3.354696         3.370071\n",
+       " 233121  2.705906 -4.839817          253            3.353759         3.370071\n",
+       " 233122  2.707608 -4.839595          253            3.352829         3.370071\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 233892  4.017918 -4.843977          253            0.000093         3.370071\n",
+       " 233893  4.019619 -4.844252          253            0.000081         3.370071\n",
+       " 233894  4.021321 -4.844527          253            0.000070         3.370071\n",
+       " 233895  4.023023 -4.844802          253            0.000059         3.370071\n",
+       " 233896  4.024725 -4.845077          253            0.000048         3.370071\n",
+       " \n",
+       " [779 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 234118  2.700801 -4.839891          254            3.322363         3.342694\n",
+       " 234119  2.702502 -4.840238          254            3.321363         3.342694\n",
+       " 234120  2.704204 -4.840238          254            3.320402         3.342694\n",
+       " 234121  2.705906 -4.840238          254            3.319440         3.342694\n",
+       " 234122  2.707608 -4.840167          254            3.318466         3.342694\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 234891  4.016216 -4.843918          254            0.000095         3.342694\n",
+       " 234892  4.017918 -4.844190          254            0.000084         3.342694\n",
+       " 234893  4.019619 -4.844461          254            0.000073         3.342694\n",
+       " 234894  4.021321 -4.844732          254            0.000062         3.342694\n",
+       " 234895  4.023023 -4.845003          254            0.000051         3.342694\n",
+       " \n",
+       " [778 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 235118  2.700801 -4.840009          255            3.304504         3.318288\n",
+       " 235119  2.702502 -4.840069          255            3.303549         3.318288\n",
+       " 235120  2.704204 -4.840144          255            3.302575         3.318288\n",
+       " 235121  2.705906 -4.840219          255            3.301600         3.318288\n",
+       " 235122  2.707608 -4.840128          255            3.300604         3.318288\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 235891  4.016216 -4.843137          255            0.000097         3.318288\n",
+       " 235892  4.017918 -4.843382          255            0.000086         3.318288\n",
+       " 235893  4.019619 -4.843626          255            0.000074         3.318288\n",
+       " 235894  4.021321 -4.843870          255            0.000063         3.318288\n",
+       " 235895  4.023023 -4.844114          255            0.000051         3.318288\n",
+       " \n",
+       " [778 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 236118  2.700801 -4.840217          256            3.278944          3.29287\n",
+       " 236119  2.702502 -4.840141          256            3.277974          3.29287\n",
+       " 236120  2.704204 -4.840066          256            3.277004          3.29287\n",
+       " 236121  2.705906 -4.840009          256            3.276031          3.29287\n",
+       " 236122  2.707608 -4.840009          256            3.275053          3.29287\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 236890  4.014514 -4.842038          256            0.000092          3.29287\n",
+       " 236891  4.016216 -4.842192          256            0.000080          3.29287\n",
+       " 236892  4.017918 -4.842347          256            0.000069          3.29287\n",
+       " 236893  4.019619 -4.842501          256            0.000058          3.29287\n",
+       " 236894  4.021321 -4.842655          256            0.000047          3.29287\n",
+       " \n",
+       " [777 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 237118  2.700801 -4.840009          257            3.255848         3.268762\n",
+       " 237119  2.702502 -4.840009          257            3.254908         3.268762\n",
+       " 237120  2.704204 -4.840009          257            3.253968         3.268762\n",
+       " 237121  2.705906 -4.839974          257            3.253012         3.268762\n",
+       " 237122  2.707608 -4.839900          257            3.252038         3.268762\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 237890  4.014514 -4.844631          257            0.000086         3.268762\n",
+       " 237891  4.016216 -4.844958          257            0.000075         3.268762\n",
+       " 237892  4.017918 -4.845284          257            0.000063         3.268762\n",
+       " 237893  4.019619 -4.845611          257            0.000052         3.268762\n",
+       " 237894  4.021321 -4.845938          257            0.000040         3.268762\n",
+       " \n",
+       " [777 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 238118  2.700801 -4.839780          258            3.236755         3.247447\n",
+       " 238119  2.702502 -4.839780          258            3.235841         3.247447\n",
+       " 238120  2.704204 -4.839780          258            3.234926         3.247447\n",
+       " 238121  2.705906 -4.839905          258            3.233939         3.247447\n",
+       " 238122  2.707608 -4.840058          258            3.232937         3.247447\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 238889  4.012813 -4.843280          258            0.000093         3.247447\n",
+       " 238890  4.014514 -4.843509          258            0.000082         3.247447\n",
+       " 238891  4.016216 -4.843738          258            0.000070         3.247447\n",
+       " 238892  4.017918 -4.843966          258            0.000059         3.247447\n",
+       " 238893  4.019619 -4.844195          258            0.000048         3.247447\n",
+       " \n",
+       " [776 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 239118  2.700801 -4.839620          259            3.221372         3.230483\n",
+       " 239119  2.702502 -4.839765          259            3.220421         3.230483\n",
+       " 239120  2.704204 -4.839780          259            3.219450         3.230483\n",
+       " 239121  2.705906 -4.839780          259            3.218477         3.230483\n",
+       " 239122  2.707608 -4.839780          259            3.217503         3.230483\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 239888  4.011111 -4.842352          259            0.000097         3.230483\n",
+       " 239889  4.012813 -4.842571          259            0.000085         3.230483\n",
+       " 239890  4.014514 -4.842789          259            0.000074         3.230483\n",
+       " 239891  4.016216 -4.843008          259            0.000062         3.230483\n",
+       " 239892  4.017918 -4.843225          259            0.000051         3.230483\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 240118  2.700801 -4.839971          260            3.207805         3.215722\n",
+       " 240119  2.702502 -4.840161          260            3.206833         3.215722\n",
+       " 240120  2.704204 -4.839940          260            3.205881         3.215722\n",
+       " 240121  2.705906 -4.839717          260            3.204929         3.215722\n",
+       " 240122  2.707608 -4.839589          260            3.203960         3.215722\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 240888  4.011111 -4.844874          260            0.000092         3.215722\n",
+       " 240889  4.012813 -4.845211          260            0.000080         3.215722\n",
+       " 240890  4.014514 -4.845547          260            0.000069         3.215722\n",
+       " 240891  4.016216 -4.845883          260            0.000058         3.215722\n",
+       " 240892  4.017918 -4.846220          260            0.000046         3.215722\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 241118  2.700801 -4.839780          261            3.196613         3.202959\n",
+       " 241119  2.702502 -4.839813          261            3.195663         3.202959\n",
+       " 241120  2.704204 -4.839888          261            3.194728         3.202959\n",
+       " 241121  2.705906 -4.839963          261            3.193793         3.202959\n",
+       " 241122  2.707608 -4.840009          261            3.192828         3.202959\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 241888  4.011111 -4.842702          261            0.000086         3.202959\n",
+       " 241889  4.012813 -4.842883          261            0.000075         3.202959\n",
+       " 241890  4.014514 -4.843064          261            0.000063         3.202959\n",
+       " 241891  4.016216 -4.843245          261            0.000052         3.202959\n",
+       " 241892  4.017918 -4.843425          261            0.000041         3.202959\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 242118  2.700801 -4.840238          262            3.184865         3.191971\n",
+       " 242119  2.702502 -4.840238          262            3.183915         3.191971\n",
+       " 242120  2.704204 -4.840238          262            3.182966         3.191971\n",
+       " 242121  2.705906 -4.840230          262            3.182012         3.191971\n",
+       " 242122  2.707608 -4.840154          262            3.181023         3.191971\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 242887  4.009409 -4.843914          262            0.000093         3.191971\n",
+       " 242888  4.011111 -4.844198          262            0.000082         3.191971\n",
+       " 242889  4.012813 -4.844482          262            0.000071         3.191971\n",
+       " 242890  4.014514 -4.844767          262            0.000060         3.191971\n",
+       " 242891  4.016216 -4.845051          262            0.000048         3.191971\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 243118  2.700801 -4.840189          263            3.172836         3.181666\n",
+       " 243119  2.702502 -4.840082          263            3.171880         3.181666\n",
+       " 243120  2.704204 -4.840009          263            3.170918         3.181666\n",
+       " 243121  2.705906 -4.840009          263            3.169940         3.181666\n",
+       " 243122  2.707608 -4.840009          263            3.168962         3.181666\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 243887  4.009409 -4.842655          263            0.000089         3.181666\n",
+       " 243888  4.011111 -4.842835          263            0.000078         3.181666\n",
+       " 243889  4.012813 -4.843015          263            0.000067         3.181666\n",
+       " 243890  4.014514 -4.843194          263            0.000055         3.181666\n",
+       " 243891  4.016216 -4.843374          263            0.000044         3.181666\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 244118  2.700801 -4.839901          264            3.162912         3.170088\n",
+       " 244119  2.702502 -4.840161          264            3.161952         3.170088\n",
+       " 244120  2.704204 -4.840420          264            3.160991         3.170088\n",
+       " 244121  2.705906 -4.840285          264            3.160041         3.170088\n",
+       " 244122  2.707608 -4.840063          264            3.159094         3.170088\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 244887  4.009409 -4.845580          264            0.000088         3.170088\n",
+       " 244888  4.011111 -4.845984          264            0.000077         3.170088\n",
+       " 244889  4.012813 -4.846389          264            0.000066         3.170088\n",
+       " 244890  4.014514 -4.846794          264            0.000055         3.170088\n",
+       " 244891  4.016216 -4.847198          264            0.000043         3.170088\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 245118  2.700801 -4.840192          265            3.152790         3.160501\n",
+       " 245119  2.702502 -4.840094          265            3.151833         3.160501\n",
+       " 245120  2.704204 -4.839989          265            3.150872         3.160501\n",
+       " 245121  2.705906 -4.839839          265            3.149889         3.160501\n",
+       " 245122  2.707608 -4.839689          265            3.148905         3.160501\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 245886  4.007708 -4.843225          265            0.000096         3.160501\n",
+       " 245887  4.009409 -4.843453          265            0.000084         3.160501\n",
+       " 245888  4.011111 -4.843680          265            0.000073         3.160501\n",
+       " 245889  4.012813 -4.843908          265            0.000062         3.160501\n",
+       " 245890  4.014514 -4.844136          265            0.000051         3.160501\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 246118  2.700801 -4.839737          266            3.142092         3.149035\n",
+       " 246119  2.702502 -4.839644          266            3.141144         3.149035\n",
+       " 246120  2.704204 -4.839551          266            3.140195         3.149035\n",
+       " 246121  2.705906 -4.839628          266            3.139224         3.149035\n",
+       " 246122  2.707608 -4.839704          266            3.138253         3.149035\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 246886  4.007708 -4.843425          266            0.000092         3.149035\n",
+       " 246887  4.009409 -4.843677          266            0.000080         3.149035\n",
+       " 246888  4.011111 -4.843928          266            0.000069         3.149035\n",
+       " 246889  4.012813 -4.844180          266            0.000058         3.149035\n",
+       " 246890  4.014514 -4.844432          266            0.000047         3.149035\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 247118  2.700801 -4.840009          267            3.135442         3.140499\n",
+       " 247119  2.702502 -4.840009          267            3.134474         3.140499\n",
+       " 247120  2.704204 -4.840033          267            3.133498         3.140499\n",
+       " 247121  2.705906 -4.840108          267            3.132506         3.140499\n",
+       " 247122  2.707608 -4.840183          267            3.131513         3.140499\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 247886  4.007708 -4.844357          267            0.000091         3.140499\n",
+       " 247887  4.009409 -4.844652          267            0.000080         3.140499\n",
+       " 247888  4.011111 -4.844947          267            0.000069         3.140499\n",
+       " 247889  4.012813 -4.845242          267            0.000058         3.140499\n",
+       " 247890  4.014514 -4.845536          267            0.000047         3.140499\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 248118  2.700801 -4.840158          268            3.130274         3.133405\n",
+       " 248119  2.702502 -4.839984          268            3.129324         3.133405\n",
+       " 248120  2.704204 -4.839811          268            3.128373         3.133405\n",
+       " 248121  2.705906 -4.839902          268            3.127400         3.133405\n",
+       " 248122  2.707608 -4.840050          268            3.126423         3.133405\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 248886  4.007708 -4.843269          268            0.000088         3.133405\n",
+       " 248887  4.009409 -4.843519          268            0.000077         3.133405\n",
+       " 248888  4.011111 -4.843770          268            0.000066         3.133405\n",
+       " 248889  4.012813 -4.844020          268            0.000055         3.133405\n",
+       " 248890  4.014514 -4.844271          268            0.000044         3.133405\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 249118  2.700801 -4.840238          269            3.124130         3.129047\n",
+       " 249119  2.702502 -4.840238          269            3.123208         3.129047\n",
+       " 249120  2.704204 -4.840187          269            3.122250         3.129047\n",
+       " 249121  2.705906 -4.840111          269            3.121274         3.129047\n",
+       " 249122  2.707608 -4.840034          269            3.120298         3.129047\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 249886  4.007708 -4.842672          269            0.000088         3.129047\n",
+       " 249887  4.009409 -4.842849          269            0.000077         3.129047\n",
+       " 249888  4.011111 -4.843026          269            0.000066         3.129047\n",
+       " 249889  4.012813 -4.843204          269            0.000055         3.129047\n",
+       " 249890  4.014514 -4.843381          269            0.000044         3.129047\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 250118  2.700801 -4.839924          270            3.118218         3.121937\n",
+       " 250119  2.702502 -4.840234          270            3.117246         3.121937\n",
+       " 250120  2.704204 -4.840019          270            3.116307         3.121937\n",
+       " 250121  2.705906 -4.839797          270            3.115368         3.121937\n",
+       " 250122  2.707608 -4.839575          270            3.114429         3.121937\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 250886  4.007708 -4.842950          270            0.000085         3.121937\n",
+       " 250887  4.009409 -4.843127          270            0.000074         3.121937\n",
+       " 250888  4.011111 -4.843304          270            0.000063         3.121937\n",
+       " 250889  4.012813 -4.843481          270            0.000052         3.121937\n",
+       " 250890  4.014514 -4.843657          270            0.000041         3.121937\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 251118  2.700801 -4.840113          271            3.112773         3.118284\n",
+       " 251119  2.702502 -4.840139          271            3.111845         3.118284\n",
+       " 251120  2.704204 -4.839910          271            3.110865         3.118284\n",
+       " 251121  2.705906 -4.839682          271            3.109885         3.118284\n",
+       " 251122  2.707608 -4.839583          271            3.108908         3.118284\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 251885  4.006006 -4.843258          271            0.000094         3.118284\n",
+       " 251886  4.007708 -4.843484          271            0.000083         3.118284\n",
+       " 251887  4.009409 -4.843711          271            0.000072         3.118284\n",
+       " 251888  4.011111 -4.843938          271            0.000061         3.118284\n",
+       " 251889  4.012813 -4.844164          271            0.000049         3.118284\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 252118  2.700801 -4.840333          272            3.108167         3.111826\n",
+       " 252119  2.702502 -4.840392          272            3.107178         3.111826\n",
+       " 252120  2.704204 -4.840173          272            3.106249         3.111826\n",
+       " 252121  2.705906 -4.839954          272            3.105319         3.111826\n",
+       " 252122  2.707608 -4.839780          272            3.104379         3.111826\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 252885  4.006006 -4.845041          272            0.000092         3.111826\n",
+       " 252886  4.007708 -4.845385          272            0.000081         3.111826\n",
+       " 252887  4.009409 -4.845728          272            0.000070         3.111826\n",
+       " 252888  4.011111 -4.846071          272            0.000058         3.111826\n",
+       " 252889  4.012813 -4.846415          272            0.000047         3.111826\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 253118  2.700801 -4.840128          273            3.103810         3.107934\n",
+       " 253119  2.702502 -4.840114          273            3.102836         3.107934\n",
+       " 253120  2.704204 -4.839895          273            3.101919         3.107934\n",
+       " 253121  2.705906 -4.839676          273            3.101003         3.107934\n",
+       " 253122  2.707608 -4.839650          273            3.100045         3.107934\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 253885  4.006006 -4.844377          273            0.000091         3.107934\n",
+       " 253886  4.007708 -4.844672          273            0.000080         3.107934\n",
+       " 253887  4.009409 -4.844967          273            0.000068         3.107934\n",
+       " 253888  4.011111 -4.845263          273            0.000057         3.107934\n",
+       " 253889  4.012813 -4.845558          273            0.000046         3.107934\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 254118  2.700801 -4.840442          274            3.100398         3.103252\n",
+       " 254119  2.702502 -4.840367          274            3.099459         3.103252\n",
+       " 254120  2.704204 -4.840292          274            3.098520         3.103252\n",
+       " 254121  2.705906 -4.840217          274            3.097575         3.103252\n",
+       " 254122  2.707608 -4.840140          274            3.096617         3.103252\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 254885  4.006006 -4.843520          274            0.000093         3.103252\n",
+       " 254886  4.007708 -4.843743          274            0.000081         3.103252\n",
+       " 254887  4.009409 -4.843967          274            0.000070         3.103252\n",
+       " 254888  4.011111 -4.844192          274            0.000059         3.103252\n",
+       " 254889  4.012813 -4.844416          274            0.000048         3.103252\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 255118  2.700801 -4.840088          275            3.093783           3.0979\n",
+       " 255119  2.702502 -4.840229          275            3.092852           3.0979\n",
+       " 255120  2.704204 -4.840153          275            3.091907           3.0979\n",
+       " 255121  2.705906 -4.840076          275            3.090963           3.0979\n",
+       " 255122  2.707608 -4.840018          275            3.090013           3.0979\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 255885  4.006006 -4.844230          275            0.000092           3.0979\n",
+       " 255886  4.007708 -4.844554          275            0.000081           3.0979\n",
+       " 255887  4.009409 -4.844878          275            0.000069           3.0979\n",
+       " 255888  4.011111 -4.845202          275            0.000058           3.0979\n",
+       " 255889  4.012813 -4.845527          275            0.000047           3.0979\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 256118  2.700801 -4.839939          276            3.086469         3.090136\n",
+       " 256119  2.702502 -4.840219          276            3.085537         3.090136\n",
+       " 256120  2.704204 -4.840067          276            3.084584         3.090136\n",
+       " 256121  2.705906 -4.839915          276            3.083630         3.090136\n",
+       " 256122  2.707608 -4.839789          276            3.082675         3.090136\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 256885  4.006006 -4.843854          276            0.000091         3.090136\n",
+       " 256886  4.007708 -4.844119          276            0.000079         3.090136\n",
+       " 256887  4.009409 -4.844384          276            0.000068         3.090136\n",
+       " 256888  4.011111 -4.844648          276            0.000057         3.090136\n",
+       " 256889  4.012813 -4.844913          276            0.000045         3.090136\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 257118  2.700801 -4.840009          277            3.081821         3.084305\n",
+       " 257119  2.702502 -4.840009          277            3.080895         3.084305\n",
+       " 257120  2.704204 -4.840009          277            3.079951         3.084305\n",
+       " 257121  2.705906 -4.840009          277            3.079008         3.084305\n",
+       " 257122  2.707608 -4.840009          277            3.078022         3.084305\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 257885  4.006006 -4.843514          277            0.000088         3.084305\n",
+       " 257886  4.007708 -4.843765          277            0.000076         3.084305\n",
+       " 257887  4.009409 -4.844017          277            0.000065         3.084305\n",
+       " 257888  4.011111 -4.844267          277            0.000054         3.084305\n",
+       " 257889  4.012813 -4.844519          277            0.000043         3.084305\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 258118  2.700801 -4.839572          278            3.079613         3.081642\n",
+       " 258119  2.702502 -4.839647          278            3.078665         3.081642\n",
+       " 258120  2.704204 -4.839721          278            3.077718         3.081642\n",
+       " 258121  2.705906 -4.839780          278            3.076769         3.081642\n",
+       " 258122  2.707608 -4.839780          278            3.075813         3.081642\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 258885  4.006006 -4.845028          278            0.000086         3.081642\n",
+       " 258886  4.007708 -4.845360          278            0.000075         3.081642\n",
+       " 258887  4.009409 -4.845693          278            0.000064         3.081642\n",
+       " 258888  4.011111 -4.846025          278            0.000053         3.081642\n",
+       " 258889  4.012813 -4.846357          278            0.000042         3.081642\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 259118  2.700801 -4.839738          279            3.075386         3.077722\n",
+       " 259119  2.702502 -4.839649          279            3.074444         3.077722\n",
+       " 259120  2.704204 -4.839560          279            3.073502         3.077722\n",
+       " 259121  2.705906 -4.839686          279            3.072556         3.077722\n",
+       " 259122  2.707608 -4.839834          279            3.071608         3.077722\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 259884  4.004304 -4.844115          279            0.000094         3.077722\n",
+       " 259885  4.006006 -4.844400          279            0.000083         3.077722\n",
+       " 259886  4.007708 -4.844685          279            0.000072         3.077722\n",
+       " 259887  4.009409 -4.844970          279            0.000061         3.077722\n",
+       " 259888  4.011111 -4.845255          279            0.000049         3.077722\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 260118  2.700801 -4.840009          280            3.073973         3.074057\n",
+       " 260119  2.702502 -4.840009          280            3.073059         3.074057\n",
+       " 260120  2.704204 -4.840009          280            3.072131         3.074057\n",
+       " 260121  2.705906 -4.840009          280            3.071196         3.074057\n",
+       " 260122  2.707608 -4.840009          280            3.070261         3.074057\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 260884  4.004304 -4.843834          280            0.000091         3.074057\n",
+       " 260885  4.006006 -4.844095          280            0.000080         3.074057\n",
+       " 260886  4.007708 -4.844356          280            0.000069         3.074057\n",
+       " 260887  4.009409 -4.844616          280            0.000058         3.074057\n",
+       " 260888  4.011111 -4.844877          280            0.000047         3.074057\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 261118  2.700801 -4.840008          281            3.070162         3.073633\n",
+       " 261119  2.702502 -4.839563          281            3.069233         3.073633\n",
+       " 261120  2.704204 -4.839713          281            3.068307         3.073633\n",
+       " 261121  2.705906 -4.839863          281            3.067381         3.073633\n",
+       " 261122  2.707608 -4.840007          281            3.066454         3.073633\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 261884  4.004304 -4.842944          281            0.000090         3.073633\n",
+       " 261885  4.006006 -4.843152          281            0.000079         3.073633\n",
+       " 261886  4.007708 -4.843360          281            0.000068         3.073633\n",
+       " 261887  4.009409 -4.843568          281            0.000057         3.073633\n",
+       " 261888  4.011111 -4.843776          281            0.000046         3.073633\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 262118  2.700801 -4.839780          282            3.065797         3.069683\n",
+       " 262119  2.702502 -4.839780          282            3.064848         3.069683\n",
+       " 262120  2.704204 -4.839800          282            3.063898         3.069683\n",
+       " 262121  2.705906 -4.839874          282            3.062942         3.069683\n",
+       " 262122  2.707608 -4.839948          282            3.061985         3.069683\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 262884  4.004304 -4.843723          282            0.000089         3.069683\n",
+       " 262885  4.006006 -4.843968          282            0.000078         3.069683\n",
+       " 262886  4.007708 -4.844213          282            0.000067         3.069683\n",
+       " 262887  4.009409 -4.844457          282            0.000056         3.069683\n",
+       " 262888  4.011111 -4.844702          282            0.000045         3.069683\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 263118  2.700801 -4.840009          283            3.063800         3.066995\n",
+       " 263119  2.702502 -4.840009          283            3.062893         3.066995\n",
+       " 263120  2.704204 -4.839975          283            3.061957         3.066995\n",
+       " 263121  2.705906 -4.839900          283            3.060982         3.066995\n",
+       " 263122  2.707608 -4.839825          283            3.060008         3.066995\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 263884  4.004304 -4.843885          283            0.000089         3.066995\n",
+       " 263885  4.006006 -4.844142          283            0.000078         3.066995\n",
+       " 263886  4.007708 -4.844399          283            0.000067         3.066995\n",
+       " 263887  4.009409 -4.844656          283            0.000056         3.066995\n",
+       " 263888  4.011111 -4.844913          283            0.000045         3.066995\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 264118  2.700801 -4.840189          284            3.060936         3.063556\n",
+       " 264119  2.702502 -4.840086          284            3.059999         3.063556\n",
+       " 264120  2.704204 -4.840029          284            3.059060         3.063556\n",
+       " 264121  2.705906 -4.840105          284            3.058112         3.063556\n",
+       " 264122  2.707608 -4.840179          284            3.057164         3.063556\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 264884  4.004304 -4.844228          284            0.000090         3.063556\n",
+       " 264885  4.006006 -4.844558          284            0.000079         3.063556\n",
+       " 264886  4.007708 -4.844888          284            0.000068         3.063556\n",
+       " 264887  4.009409 -4.845218          284            0.000057         3.063556\n",
+       " 264888  4.011111 -4.845548          284            0.000046         3.063556\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 265118  2.700801 -4.839937          285            3.056574         3.060254\n",
+       " 265119  2.702502 -4.839782          285            3.055683         3.060254\n",
+       " 265120  2.704204 -4.839856          285            3.054722         3.060254\n",
+       " 265121  2.705906 -4.839931          285            3.053760         3.060254\n",
+       " 265122  2.707608 -4.840008          285            3.052798         3.060254\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 265884  4.004304 -4.843496          285            0.000089         3.060254\n",
+       " 265885  4.006006 -4.843745          285            0.000077         3.060254\n",
+       " 265886  4.007708 -4.843995          285            0.000066         3.060254\n",
+       " 265887  4.009409 -4.844244          285            0.000055         3.060254\n",
+       " 265888  4.011111 -4.844493          285            0.000044         3.060254\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 266118  2.700801 -4.839718          286            3.051834          3.05536\n",
+       " 266119  2.702502 -4.839583          286            3.050926          3.05536\n",
+       " 266120  2.704204 -4.839666          286            3.050001          3.05536\n",
+       " 266121  2.705906 -4.839816          286            3.049071          3.05536\n",
+       " 266122  2.707608 -4.839966          286            3.048140          3.05536\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 266884  4.004304 -4.843383          286            0.000086          3.05536\n",
+       " 266885  4.006006 -4.843620          286            0.000074          3.05536\n",
+       " 266886  4.007708 -4.843858          286            0.000063          3.05536\n",
+       " 266887  4.009409 -4.844095          286            0.000052          3.05536\n",
+       " 266888  4.011111 -4.844333          286            0.000041          3.05536\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 267118  2.700801 -4.840190          287            3.051167         3.052214\n",
+       " 267119  2.702502 -4.840088          287            3.050244         3.052214\n",
+       " 267120  2.704204 -4.840009          287            3.049313         3.052214\n",
+       " 267121  2.705906 -4.840009          287            3.048356         3.052214\n",
+       " 267122  2.707608 -4.840009          287            3.047399         3.052214\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 267884  4.004304 -4.844064          287            0.000086         3.052214\n",
+       " 267885  4.006006 -4.844300          287            0.000075         3.052214\n",
+       " 267886  4.007708 -4.844536          287            0.000064         3.052214\n",
+       " 267887  4.009409 -4.844773          287            0.000053         3.052214\n",
+       " 267888  4.011111 -4.845009          287            0.000041         3.052214\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 268118  2.700801 -4.840238          288            3.050556          3.05196\n",
+       " 268119  2.702502 -4.840238          288            3.049647          3.05196\n",
+       " 268120  2.704204 -4.840088          288            3.048712          3.05196\n",
+       " 268121  2.705906 -4.839935          288            3.047777          3.05196\n",
+       " 268122  2.707608 -4.839783          288            3.046841          3.05196\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 268884  4.004304 -4.843633          288            0.000087          3.05196\n",
+       " 268885  4.006006 -4.843858          288            0.000076          3.05196\n",
+       " 268886  4.007708 -4.844083          288            0.000065          3.05196\n",
+       " 268887  4.009409 -4.844308          288            0.000054          3.05196\n",
+       " 268888  4.011111 -4.844532          288            0.000042          3.05196\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 269118  2.700801 -4.839872          289            3.047565         3.049543\n",
+       " 269119  2.702502 -4.840068          289            3.046642         3.049543\n",
+       " 269120  2.704204 -4.840228          289            3.045714         3.049543\n",
+       " 269121  2.705906 -4.840153          289            3.044748         3.049543\n",
+       " 269122  2.707608 -4.840078          289            3.043782         3.049543\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 269884  4.004304 -4.845761          289            0.000086         3.049543\n",
+       " 269885  4.006006 -4.846136          289            0.000075         3.049543\n",
+       " 269886  4.007708 -4.846511          289            0.000064         3.049543\n",
+       " 269887  4.009409 -4.846885          289            0.000053         3.049543\n",
+       " 269888  4.011111 -4.847260          289            0.000042         3.049543\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 270118  2.700801 -4.840009          290            3.045147         3.047377\n",
+       " 270119  2.702502 -4.840009          290            3.044230         3.047377\n",
+       " 270120  2.704204 -4.839975          290            3.043302         3.047377\n",
+       " 270121  2.705906 -4.839825          290            3.042341         3.047377\n",
+       " 270122  2.707608 -4.839675          290            3.041380         3.047377\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 270884  4.004304 -4.843758          290            0.000085         3.047377\n",
+       " 270885  4.006006 -4.844016          290            0.000074         3.047377\n",
+       " 270886  4.007708 -4.844273          290            0.000063         3.047377\n",
+       " 270887  4.009409 -4.844531          290            0.000052         3.047377\n",
+       " 270888  4.011111 -4.844789          290            0.000041         3.047377\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 271118  2.700801 -4.839899          291            3.044641         3.046614\n",
+       " 271119  2.702502 -4.840155          291            3.043704         3.046614\n",
+       " 271120  2.704204 -4.840189          291            3.042765         3.046614\n",
+       " 271121  2.705906 -4.840114          291            3.041827         3.046614\n",
+       " 271122  2.707608 -4.840040          291            3.040888         3.046614\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 271884  4.004304 -4.842932          291            0.000086         3.046614\n",
+       " 271885  4.006006 -4.843106          291            0.000075         3.046614\n",
+       " 271886  4.007708 -4.843280          291            0.000064         3.046614\n",
+       " 271887  4.009409 -4.843455          291            0.000053         3.046614\n",
+       " 271888  4.011111 -4.843629          291            0.000042         3.046614\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 272118  2.700801 -4.839987          292            3.042880          3.04456\n",
+       " 272119  2.702502 -4.840174          292            3.041938          3.04456\n",
+       " 272120  2.704204 -4.840026          292            3.041025          3.04456\n",
+       " 272121  2.705906 -4.839878          292            3.040113          3.04456\n",
+       " 272122  2.707608 -4.839780          292            3.039176          3.04456\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 272884  4.004304 -4.843123          292            0.000085          3.04456\n",
+       " 272885  4.006006 -4.843308          292            0.000074          3.04456\n",
+       " 272886  4.007708 -4.843493          292            0.000064          3.04456\n",
+       " 272887  4.009409 -4.843679          292            0.000053          3.04456\n",
+       " 272888  4.011111 -4.843864          292            0.000042          3.04456\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 273118  2.700801 -4.839780          293            3.042057         3.043641\n",
+       " 273119  2.702502 -4.839780          293            3.041171         3.043641\n",
+       " 273120  2.704204 -4.839818          293            3.040251         3.043641\n",
+       " 273121  2.705906 -4.839892          293            3.039299         3.043641\n",
+       " 273122  2.707608 -4.839968          293            3.038347         3.043641\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 273884  4.004304 -4.844316          293            0.000084         3.043641\n",
+       " 273885  4.006006 -4.844608          293            0.000073         3.043641\n",
+       " 273886  4.007708 -4.844901          293            0.000062         3.043641\n",
+       " 273887  4.009409 -4.845192          293            0.000051         3.043641\n",
+       " 273888  4.011111 -4.845485          293            0.000040         3.043641\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 274118  2.700801 -4.840135          294            3.037341         3.040572\n",
+       " 274119  2.702502 -4.840192          294            3.036391         3.040572\n",
+       " 274120  2.704204 -4.840117          294            3.035469         3.040572\n",
+       " 274121  2.705906 -4.840042          294            3.034548         3.040572\n",
+       " 274122  2.707608 -4.840009          294            3.033611         3.040572\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 274883  4.002603 -4.844106          294            0.000092         3.040572\n",
+       " 274884  4.004304 -4.844400          294            0.000081         3.040572\n",
+       " 274885  4.006006 -4.844695          294            0.000070         3.040572\n",
+       " 274886  4.007708 -4.844988          294            0.000059         3.040572\n",
+       " 274887  4.009409 -4.845283          294            0.000048         3.040572\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 275118  2.700801 -4.839772          295            3.035686         3.037559\n",
+       " 275119  2.702502 -4.839697          295            3.034742         3.037559\n",
+       " 275120  2.704204 -4.839622          295            3.033799         3.037559\n",
+       " 275121  2.705906 -4.839556          295            3.032856         3.037559\n",
+       " 275122  2.707608 -4.839630          295            3.031926         3.037559\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 275884  4.004304 -4.843407          295            0.000084         3.037559\n",
+       " 275885  4.006006 -4.843641          295            0.000073         3.037559\n",
+       " 275886  4.007708 -4.843875          295            0.000062         3.037559\n",
+       " 275887  4.009409 -4.844110          295            0.000051         3.037559\n",
+       " 275888  4.011111 -4.844344          295            0.000040         3.037559\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 276118  2.700801 -4.839722          296            3.031392         3.033432\n",
+       " 276119  2.702502 -4.839598          296            3.030471         3.033432\n",
+       " 276120  2.704204 -4.839646          296            3.029546         3.033432\n",
+       " 276121  2.705906 -4.839796          296            3.028620         3.033432\n",
+       " 276122  2.707608 -4.839946          296            3.027694         3.033432\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 276884  4.004304 -4.844177          296            0.000085         3.033432\n",
+       " 276885  4.006006 -4.844450          296            0.000073         3.033432\n",
+       " 276886  4.007708 -4.844723          296            0.000062         3.033432\n",
+       " 276887  4.009409 -4.844996          296            0.000051         3.033432\n",
+       " 276888  4.011111 -4.845269          296            0.000040         3.033432\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 277118  2.700801 -4.839896          297            3.030024         3.031171\n",
+       " 277119  2.702502 -4.840146          297            3.029110         3.031171\n",
+       " 277120  2.704204 -4.840284          297            3.028180         3.031171\n",
+       " 277121  2.705906 -4.840359          297            3.027242         3.031171\n",
+       " 277122  2.707608 -4.840433          297            3.026303         3.031171\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 277883  4.002603 -4.844115          297            0.000094         3.031171\n",
+       " 277884  4.004304 -4.844399          297            0.000083         3.031171\n",
+       " 277885  4.006006 -4.844683          297            0.000072         3.031171\n",
+       " 277886  4.007708 -4.844967          297            0.000061         3.031171\n",
+       " 277887  4.009409 -4.845252          297            0.000050         3.031171\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 278118  2.700801 -4.839951          298            3.027735         3.028723\n",
+       " 278119  2.702502 -4.839827          298            3.026843         3.028723\n",
+       " 278120  2.704204 -4.839828          298            3.025913         3.028723\n",
+       " 278121  2.705906 -4.839902          298            3.024961         3.028723\n",
+       " 278122  2.707608 -4.839978          298            3.024008         3.028723\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 278883  4.002603 -4.843341          298            0.000093         3.028723\n",
+       " 278884  4.004304 -4.843598          298            0.000082         3.028723\n",
+       " 278885  4.006006 -4.843856          298            0.000071         3.028723\n",
+       " 278886  4.007708 -4.844114          298            0.000060         3.028723\n",
+       " 278887  4.009409 -4.844371          298            0.000049         3.028723\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 279118  2.700801 -4.840012          299            3.025823         3.026947\n",
+       " 279119  2.702502 -4.839819          299            3.024894         3.026947\n",
+       " 279120  2.704204 -4.839893          299            3.023990         3.026947\n",
+       " 279121  2.705906 -4.839967          299            3.023086         3.026947\n",
+       " 279122  2.707608 -4.840042          299            3.022159         3.026947\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 279883  4.002603 -4.844658          299            0.000091         3.026947\n",
+       " 279884  4.004304 -4.844984          299            0.000080         3.026947\n",
+       " 279885  4.006006 -4.845309          299            0.000069         3.026947\n",
+       " 279886  4.007708 -4.845634          299            0.000058         3.026947\n",
+       " 279887  4.009409 -4.845960          299            0.000047         3.026947\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 280118  2.700801 -4.839780          300            3.025509         3.025567\n",
+       " 280119  2.702502 -4.839780          300            3.024583         3.025567\n",
+       " 280120  2.704204 -4.839780          300            3.023675         3.025567\n",
+       " 280121  2.705906 -4.839780          300            3.022766         3.025567\n",
+       " 280122  2.707608 -4.839752          300            3.021840         3.025567\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 280883  4.002603 -4.843300          300            0.000089         3.025567\n",
+       " 280884  4.004304 -4.843532          300            0.000079         3.025567\n",
+       " 280885  4.006006 -4.843763          300            0.000068         3.025567\n",
+       " 280886  4.007708 -4.843995          300            0.000057         3.025567\n",
+       " 280887  4.009409 -4.844226          300            0.000046         3.025567\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 281118  2.700801 -4.839826          301            3.027226         3.026726\n",
+       " 281119  2.702502 -4.839780          301            3.026302         3.026726\n",
+       " 281120  2.704204 -4.839780          301            3.025380         3.026726\n",
+       " 281121  2.705906 -4.839780          301            3.024458         3.026726\n",
+       " 281122  2.707608 -4.839845          301            3.023525         3.026726\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 281883  4.002603 -4.841613          301            0.000087         3.026726\n",
+       " 281884  4.004304 -4.841717          301            0.000077         3.026726\n",
+       " 281885  4.006006 -4.841821          301            0.000066         3.026726\n",
+       " 281886  4.007708 -4.841925          301            0.000055         3.026726\n",
+       " 281887  4.009409 -4.842029          301            0.000044         3.026726\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 282118  2.700801 -4.839617          302            3.023844         3.026639\n",
+       " 282119  2.702502 -4.839846          302            3.022935         3.026639\n",
+       " 282120  2.704204 -4.840074          302            3.022027         3.026639\n",
+       " 282121  2.705906 -4.840196          302            3.021112         3.026639\n",
+       " 282122  2.707608 -4.840045          302            3.020182         3.026639\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 282883  4.002603 -4.843771          302            0.000086         3.026639\n",
+       " 282884  4.004304 -4.844012          302            0.000076         3.026639\n",
+       " 282885  4.006006 -4.844252          302            0.000065         3.026639\n",
+       " 282886  4.007708 -4.844493          302            0.000054         3.026639\n",
+       " 282887  4.009409 -4.844733          302            0.000043         3.026639\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 283118  2.700801 -4.839684          303            3.022696          3.02544\n",
+       " 283119  2.702502 -4.839780          303            3.021770          3.02544\n",
+       " 283120  2.704204 -4.839780          303            3.020840          3.02544\n",
+       " 283121  2.705906 -4.839780          303            3.019909          3.02544\n",
+       " 283122  2.707608 -4.839914          303            3.018980          3.02544\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 283883  4.002603 -4.842963          303            0.000087          3.02544\n",
+       " 283884  4.004304 -4.843124          303            0.000076          3.02544\n",
+       " 283885  4.006006 -4.843286          303            0.000066          3.02544\n",
+       " 283886  4.007708 -4.843447          303            0.000055          3.02544\n",
+       " 283887  4.009409 -4.843608          303            0.000044          3.02544\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 284118  2.700801 -4.839987          304            3.021668         3.023745\n",
+       " 284119  2.702502 -4.839839          304            3.020764         3.023745\n",
+       " 284120  2.704204 -4.839691          304            3.019860         3.023745\n",
+       " 284121  2.705906 -4.839560          304            3.018955         3.023745\n",
+       " 284122  2.707608 -4.839710          304            3.018024         3.023745\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 284883  4.002603 -4.842153          304            0.000087         3.023745\n",
+       " 284884  4.004304 -4.842290          304            0.000076         3.023745\n",
+       " 284885  4.006006 -4.842428          304            0.000065         3.023745\n",
+       " 284886  4.007708 -4.842565          304            0.000055         3.023745\n",
+       " 284887  4.009409 -4.842702          304            0.000044         3.023745\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 285118  2.700801 -4.840009          305            3.020283         3.022635\n",
+       " 285119  2.702502 -4.840009          305            3.019380         3.022635\n",
+       " 285120  2.704204 -4.840009          305            3.018476         3.022635\n",
+       " 285121  2.705906 -4.840009          305            3.017572         3.022635\n",
+       " 285122  2.707608 -4.840009          305            3.016626         3.022635\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 285883  4.002603 -4.843457          305            0.000087         3.022635\n",
+       " 285884  4.004304 -4.843664          305            0.000076         3.022635\n",
+       " 285885  4.006006 -4.843872          305            0.000065         3.022635\n",
+       " 285886  4.007708 -4.844079          305            0.000054         3.022635\n",
+       " 285887  4.009409 -4.844286          305            0.000043         3.022635\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 286118  2.700801 -4.840165          306            3.016556         3.019378\n",
+       " 286119  2.702502 -4.840008          306            3.015647         3.019378\n",
+       " 286120  2.704204 -4.839851          306            3.014738         3.019378\n",
+       " 286121  2.705906 -4.839822          306            3.013820         3.019378\n",
+       " 286122  2.707608 -4.839897          306            3.012894         3.019378\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 286883  4.002603 -4.843429          306            0.000086         3.019378\n",
+       " 286884  4.004304 -4.843647          306            0.000075         3.019378\n",
+       " 286885  4.006006 -4.843865          306            0.000064         3.019378\n",
+       " 286886  4.007708 -4.844084          306            0.000053         3.019378\n",
+       " 286887  4.009409 -4.844303          306            0.000042         3.019378\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 287118  2.700801 -4.839568          307            3.017256         3.017859\n",
+       " 287119  2.702502 -4.839720          307            3.016330         3.017859\n",
+       " 287120  2.704204 -4.839873          307            3.015403         3.017859\n",
+       " 287121  2.705906 -4.840017          307            3.014478         3.017859\n",
+       " 287122  2.707608 -4.840092          307            3.013561         3.017859\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 287883  4.002603 -4.843671          307            0.000086         3.017859\n",
+       " 287884  4.004304 -4.843937          307            0.000076         3.017859\n",
+       " 287885  4.006006 -4.844203          307            0.000065         3.017859\n",
+       " 287886  4.007708 -4.844470          307            0.000054         3.017859\n",
+       " 287887  4.009409 -4.844736          307            0.000043         3.017859\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 288118  2.700801 -4.840158          308            3.015125         3.017134\n",
+       " 288119  2.702502 -4.840001          308            3.014207         3.017134\n",
+       " 288120  2.704204 -4.839844          308            3.013289         3.017134\n",
+       " 288121  2.705906 -4.839825          308            3.012361         3.017134\n",
+       " 288122  2.707608 -4.839899          308            3.011427         3.017134\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 288883  4.002603 -4.844331          308            0.000086         3.017134\n",
+       " 288884  4.004304 -4.844606          308            0.000075         3.017134\n",
+       " 288885  4.006006 -4.844882          308            0.000064         3.017134\n",
+       " 288886  4.007708 -4.845157          308            0.000053         3.017134\n",
+       " 288887  4.009409 -4.845432          308            0.000042         3.017134\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 289118  2.700801 -4.840238          309            3.014561         3.015533\n",
+       " 289119  2.702502 -4.840238          309            3.013641         3.015533\n",
+       " 289120  2.704204 -4.840138          309            3.012721         3.015533\n",
+       " 289121  2.705906 -4.839917          309            3.011799         3.015533\n",
+       " 289122  2.707608 -4.839694          309            3.010878         3.015533\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 289883  4.002603 -4.844871          309            0.000084         3.015533\n",
+       " 289884  4.004304 -4.845195          309            0.000073         3.015533\n",
+       " 289885  4.006006 -4.845518          309            0.000062         3.015533\n",
+       " 289886  4.007708 -4.845841          309            0.000051         3.015533\n",
+       " 289887  4.009409 -4.846165          309            0.000041         3.015533\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 290118  2.700801 -4.839637          310            3.012832         3.014392\n",
+       " 290119  2.702502 -4.839866          310            3.011888         3.014392\n",
+       " 290120  2.704204 -4.840095          310            3.010944         3.014392\n",
+       " 290121  2.705906 -4.840210          310            3.010014         3.014392\n",
+       " 290122  2.707608 -4.840137          310            3.009110         3.014392\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 290883  4.002603 -4.843498          310            0.000085         3.014392\n",
+       " 290884  4.004304 -4.843705          310            0.000074         3.014392\n",
+       " 290885  4.006006 -4.843911          310            0.000063         3.014392\n",
+       " 290886  4.007708 -4.844118          310            0.000052         3.014392\n",
+       " 290887  4.009409 -4.844324          310            0.000041         3.014392\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 291118  2.700801 -4.839972          311            3.013232         3.014214\n",
+       " 291119  2.702502 -4.839894          311            3.012319         3.014214\n",
+       " 291120  2.704204 -4.839816          311            3.011406         3.014214\n",
+       " 291121  2.705906 -4.839822          311            3.010488         3.014214\n",
+       " 291122  2.707608 -4.839897          311            3.009566         3.014214\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 291883  4.002603 -4.843467          311            0.000086         3.014214\n",
+       " 291884  4.004304 -4.843672          311            0.000076         3.014214\n",
+       " 291885  4.006006 -4.843877          311            0.000065         3.014214\n",
+       " 291886  4.007708 -4.844082          311            0.000054         3.014214\n",
+       " 291887  4.009409 -4.844287          311            0.000043         3.014214\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 292118  2.700801 -4.839972          312            3.013999         3.015296\n",
+       " 292119  2.702502 -4.839892          312            3.013085         3.015296\n",
+       " 292120  2.704204 -4.839812          312            3.012172         3.015296\n",
+       " 292121  2.705906 -4.839780          312            3.011259         3.015296\n",
+       " 292122  2.707608 -4.839780          312            3.010346         3.015296\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 292883  4.002603 -4.843295          312            0.000086         3.015296\n",
+       " 292884  4.004304 -4.843489          312            0.000075         3.015296\n",
+       " 292885  4.006006 -4.843683          312            0.000064         3.015296\n",
+       " 292886  4.007708 -4.843877          312            0.000054         3.015296\n",
+       " 292887  4.009409 -4.844071          312            0.000043         3.015296\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 293118  2.700801 -4.840009          313            3.015089         3.016502\n",
+       " 293119  2.702502 -4.840009          313            3.014176         3.016502\n",
+       " 293120  2.704204 -4.840009          313            3.013263         3.016502\n",
+       " 293121  2.705906 -4.839947          313            3.012342         3.016502\n",
+       " 293122  2.707608 -4.839797          313            3.011412         3.016502\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 293883  4.002603 -4.843327          313            0.000088         3.016502\n",
+       " 293884  4.004304 -4.843555          313            0.000077         3.016502\n",
+       " 293885  4.006006 -4.843783          313            0.000067         3.016502\n",
+       " 293886  4.007708 -4.844011          313            0.000056         3.016502\n",
+       " 293887  4.009409 -4.844239          313            0.000045         3.016502\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 294118  2.700801 -4.840009          314            3.013958         3.015464\n",
+       " 294119  2.702502 -4.840009          314            3.013042         3.015464\n",
+       " 294120  2.704204 -4.840009          314            3.012126         3.015464\n",
+       " 294121  2.705906 -4.839940          314            3.011205         3.015464\n",
+       " 294122  2.707608 -4.839867          314            3.010284         3.015464\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 294883  4.002603 -4.844144          314            0.000086         3.015464\n",
+       " 294884  4.004304 -4.844407          314            0.000075         3.015464\n",
+       " 294885  4.006006 -4.844670          314            0.000064         3.015464\n",
+       " 294886  4.007708 -4.844932          314            0.000054         3.015464\n",
+       " 294887  4.009409 -4.845195          314            0.000043         3.015464\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 295118  2.700801 -4.839745          315            3.012309         3.014174\n",
+       " 295119  2.702502 -4.839669          315            3.011405         3.014174\n",
+       " 295120  2.704204 -4.839592          315            3.010501         3.014174\n",
+       " 295121  2.705906 -4.839620          315            3.009587         3.014174\n",
+       " 295122  2.707608 -4.839768          315            3.008661         3.014174\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 295883  4.002603 -4.843263          315            0.000087         3.014174\n",
+       " 295884  4.004304 -4.843512          315            0.000076         3.014174\n",
+       " 295885  4.006006 -4.843762          315            0.000065         3.014174\n",
+       " 295886  4.007708 -4.844011          315            0.000055         3.014174\n",
+       " 295887  4.009409 -4.844261          315            0.000044         3.014174\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 296118  2.700801 -4.840217          316            3.011444         3.012017\n",
+       " 296119  2.702502 -4.840144          316            3.010518         3.012017\n",
+       " 296120  2.704204 -4.840071          316            3.009593         3.012017\n",
+       " 296121  2.705906 -4.840020          316            3.008672         3.012017\n",
+       " 296122  2.707608 -4.840093          316            3.007777         3.012017\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 296883  4.002603 -4.843995          316            0.000087         3.012017\n",
+       " 296884  4.004304 -4.844234          316            0.000076         3.012017\n",
+       " 296885  4.006006 -4.844473          316            0.000065         3.012017\n",
+       " 296886  4.007708 -4.844712          316            0.000055         3.012017\n",
+       " 296887  4.009409 -4.844952          316            0.000044         3.012017\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 297118  2.700801 -4.839932          317            3.009627         3.010999\n",
+       " 297119  2.702502 -4.839780          317            3.008762         3.010999\n",
+       " 297120  2.704204 -4.839780          317            3.007849         3.010999\n",
+       " 297121  2.705906 -4.839780          317            3.006937         3.010999\n",
+       " 297122  2.707608 -4.839776          317            3.006023         3.010999\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 297883  4.002603 -4.843186          317            0.000089         3.010999\n",
+       " 297884  4.004304 -4.843395          317            0.000078         3.010999\n",
+       " 297885  4.006006 -4.843603          317            0.000067         3.010999\n",
+       " 297886  4.007708 -4.843812          317            0.000056         3.010999\n",
+       " 297887  4.009409 -4.844020          317            0.000045         3.010999\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 298118  2.700801 -4.839551          318            3.008263         3.009124\n",
+       " 298119  2.702502 -4.839551          318            3.007360         3.009124\n",
+       " 298120  2.704204 -4.839551          318            3.006455         3.009124\n",
+       " 298121  2.705906 -4.839551          318            3.005547         3.009124\n",
+       " 298122  2.707608 -4.839551          318            3.004622         3.009124\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 298883  4.002603 -4.843890          318            0.000089         3.009124\n",
+       " 298884  4.004304 -4.844145          318            0.000078         3.009124\n",
+       " 298885  4.006006 -4.844400          318            0.000067         3.009124\n",
+       " 298886  4.007708 -4.844656          318            0.000056         3.009124\n",
+       " 298887  4.009409 -4.844911          318            0.000045         3.009124\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 299118  2.700801 -4.840022          319            3.005873         3.007682\n",
+       " 299119  2.702502 -4.839863          319            3.004976         3.007682\n",
+       " 299120  2.704204 -4.839713          319            3.004081         3.007682\n",
+       " 299121  2.705906 -4.839563          319            3.003186         3.007682\n",
+       " 299122  2.707608 -4.839688          319            3.002254         3.007682\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 299883  4.002603 -4.843696          319            0.000088         3.007682\n",
+       " 299884  4.004304 -4.843951          319            0.000077         3.007682\n",
+       " 299885  4.006006 -4.844206          319            0.000066         3.007682\n",
+       " 299886  4.007708 -4.844461          319            0.000055         3.007682\n",
+       " 299887  4.009409 -4.844717          319            0.000044         3.007682\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 300118  2.700801 -4.840446          320            3.004576         3.005405\n",
+       " 300119  2.702502 -4.840370          320            3.003659         3.005405\n",
+       " 300120  2.704204 -4.840295          320            3.002742         3.005405\n",
+       " 300121  2.705906 -4.840238          320            3.001822         3.005405\n",
+       " 300122  2.707608 -4.840238          320            3.000897         3.005405\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 300883  4.002603 -4.844382          320            0.000086         3.005405\n",
+       " 300884  4.004304 -4.844648          320            0.000075         3.005405\n",
+       " 300885  4.006006 -4.844914          320            0.000064         3.005405\n",
+       " 300886  4.007708 -4.845181          320            0.000053         3.005405\n",
+       " 300887  4.009409 -4.845447          320            0.000042         3.005405\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 301118  2.700801 -4.839396          321            3.004496         3.005004\n",
+       " 301119  2.702502 -4.839553          321            3.003614         3.005004\n",
+       " 301120  2.704204 -4.839710          321            3.002733         3.005004\n",
+       " 301121  2.705906 -4.839864          321            3.001830         3.005004\n",
+       " 301122  2.707608 -4.840017          321            3.000908         3.005004\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 301883  4.002603 -4.844939          321            0.000085         3.005004\n",
+       " 301884  4.004304 -4.845236          321            0.000074         3.005004\n",
+       " 301885  4.006006 -4.845533          321            0.000063         3.005004\n",
+       " 301886  4.007708 -4.845830          321            0.000053         3.005004\n",
+       " 301887  4.009409 -4.846127          321            0.000042         3.005004\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 302118  2.700801 -4.840009          322            3.005403         3.005271\n",
+       " 302119  2.702502 -4.840009          322            3.004508         3.005271\n",
+       " 302120  2.704204 -4.840009          322            3.003613         3.005271\n",
+       " 302121  2.705906 -4.840044          322            3.002716         3.005271\n",
+       " 302122  2.707608 -4.840119          322            3.001816         3.005271\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 302883  4.002603 -4.842654          322            0.000086         3.005271\n",
+       " 302884  4.004304 -4.842835          322            0.000075         3.005271\n",
+       " 302885  4.006006 -4.843017          322            0.000065         3.005271\n",
+       " 302886  4.007708 -4.843198          322            0.000054         3.005271\n",
+       " 302887  4.009409 -4.843380          322            0.000043         3.005271\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 303118  2.700801 -4.839955          323            3.006049         3.005757\n",
+       " 303119  2.702502 -4.839839          323            3.005183         3.005757\n",
+       " 303120  2.704204 -4.839817          323            3.004290         3.005757\n",
+       " 303121  2.705906 -4.839891          323            3.003369         3.005757\n",
+       " 303122  2.707608 -4.839965          323            3.002447         3.005757\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 303883  4.002603 -4.845078          323            0.000083         3.005757\n",
+       " 303884  4.004304 -4.845407          323            0.000072         3.005757\n",
+       " 303885  4.006006 -4.845735          323            0.000062         3.005757\n",
+       " 303886  4.007708 -4.846064          323            0.000051         3.005757\n",
+       " 303887  4.009409 -4.846393          323            0.000041         3.005757\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 304118  2.700801 -4.840170          324            3.004581         3.006496\n",
+       " 304119  2.702502 -4.840024          324            3.003681         3.006496\n",
+       " 304120  2.704204 -4.840009          324            3.002786         3.006496\n",
+       " 304121  2.705906 -4.840009          324            3.001890         3.006496\n",
+       " 304122  2.707608 -4.840009          324            3.000995         3.006496\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 304883  4.002603 -4.843720          324            0.000083         3.006496\n",
+       " 304884  4.004304 -4.843935          324            0.000072         3.006496\n",
+       " 304885  4.006006 -4.844150          324            0.000061         3.006496\n",
+       " 304886  4.007708 -4.844365          324            0.000051         3.006496\n",
+       " 304887  4.009409 -4.844580          324            0.000040         3.006496\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 305118  2.700801 -4.840009          325            3.002814         3.004765\n",
+       " 305119  2.702502 -4.840009          325            3.001901         3.004765\n",
+       " 305120  2.704204 -4.840009          325            3.000988         3.004765\n",
+       " 305121  2.705906 -4.840102          325            3.000084         3.004765\n",
+       " 305122  2.707608 -4.840324          325            2.999193         3.004765\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 305882  4.000901 -4.843996          325            0.000092         3.004765\n",
+       " 305883  4.002603 -4.844257          325            0.000081         3.004765\n",
+       " 305884  4.004304 -4.844518          325            0.000071         3.004765\n",
+       " 305885  4.006006 -4.844779          325            0.000060         3.004765\n",
+       " 305886  4.007708 -4.845040          325            0.000049         3.004765\n",
+       " \n",
+       " [769 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 306118  2.700801 -4.840198          326            3.002390         3.004881\n",
+       " 306119  2.702502 -4.840111          326            3.001490         3.004881\n",
+       " 306120  2.704204 -4.840025          326            3.000590         3.004881\n",
+       " 306121  2.705906 -4.839890          326            2.999705         3.004881\n",
+       " 306122  2.707608 -4.839744          326            2.998822         3.004881\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 306883  4.002603 -4.844359          326            0.000084         3.004881\n",
+       " 306884  4.004304 -4.844631          326            0.000074         3.004881\n",
+       " 306885  4.006006 -4.844902          326            0.000063         3.004881\n",
+       " 306886  4.007708 -4.845174          326            0.000053         3.004881\n",
+       " 306887  4.009409 -4.845446          326            0.000042         3.004881\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 307118  2.700801 -4.840009          327            3.002141         3.003063\n",
+       " 307119  2.702502 -4.840009          327            3.001226         3.003063\n",
+       " 307120  2.704204 -4.840009          327            3.000311         3.003063\n",
+       " 307121  2.705906 -4.840009          327            2.999412         3.003063\n",
+       " 307122  2.707608 -4.840009          327            2.998516         3.003063\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 307883  4.002603 -4.844172          327            0.000087         3.003063\n",
+       " 307884  4.004304 -4.844420          327            0.000076         3.003063\n",
+       " 307885  4.006006 -4.844669          327            0.000066         3.003063\n",
+       " 307886  4.007708 -4.844917          327            0.000055         3.003063\n",
+       " 307887  4.009409 -4.845166          327            0.000044         3.003063\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 308118  2.700801 -4.839636          328            3.001148         3.003528\n",
+       " 308119  2.702502 -4.839861          328            3.000235         3.003528\n",
+       " 308120  2.704204 -4.840086          328            2.999322         3.003528\n",
+       " 308121  2.705906 -4.840167          328            2.998409         3.003528\n",
+       " 308122  2.707608 -4.839948          328            2.997497         3.003528\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 308883  4.002603 -4.843956          328            0.000086         3.003528\n",
+       " 308884  4.004304 -4.844204          328            0.000076         3.003528\n",
+       " 308885  4.006006 -4.844452          328            0.000065         3.003528\n",
+       " 308886  4.007708 -4.844700          328            0.000054         3.003528\n",
+       " 308887  4.009409 -4.844948          328            0.000044         3.003528\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 309118  2.700801 -4.839588          329            2.998466         3.000606\n",
+       " 309119  2.702502 -4.839666          329            2.997571         3.000606\n",
+       " 309120  2.704204 -4.839745          329            2.996676         3.000606\n",
+       " 309121  2.705906 -4.839780          329            2.995766         3.000606\n",
+       " 309122  2.707608 -4.839780          329            2.994844         3.000606\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 309883  4.002603 -4.843663          329            0.000085         3.000606\n",
+       " 309884  4.004304 -4.843934          329            0.000074         3.000606\n",
+       " 309885  4.006006 -4.844205          329            0.000064         3.000606\n",
+       " 309886  4.007708 -4.844476          329            0.000053         3.000606\n",
+       " 309887  4.009409 -4.844747          329            0.000042         3.000606\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 310118  2.700801 -4.839886          330            2.998662          2.99923\n",
+       " 310119  2.702502 -4.840113          330            2.997756          2.99923\n",
+       " 310120  2.704204 -4.840170          330            2.996845          2.99923\n",
+       " 310121  2.705906 -4.840017          330            2.995927          2.99923\n",
+       " 310122  2.707608 -4.839865          330            2.995010          2.99923\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 310883  4.002603 -4.843132          330            0.000085          2.99923\n",
+       " 310884  4.004304 -4.843312          330            0.000074          2.99923\n",
+       " 310885  4.006006 -4.843493          330            0.000064          2.99923\n",
+       " 310886  4.007708 -4.843674          330            0.000053          2.99923\n",
+       " 310887  4.009409 -4.843854          330            0.000042          2.99923\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 311118  2.700801 -4.839601          331            2.998815         2.999917\n",
+       " 311119  2.702502 -4.839707          331            2.997891         2.999917\n",
+       " 311120  2.704204 -4.839780          331            2.996970         2.999917\n",
+       " 311121  2.705906 -4.839780          331            2.996057         2.999917\n",
+       " 311122  2.707608 -4.839780          331            2.995144         2.999917\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 311883  4.002603 -4.843960          331            0.000084         2.999917\n",
+       " 311884  4.004304 -4.844221          331            0.000073         2.999917\n",
+       " 311885  4.006006 -4.844481          331            0.000063         2.999917\n",
+       " 311886  4.007708 -4.844741          331            0.000052         2.999917\n",
+       " 311887  4.009409 -4.845002          331            0.000041         2.999917\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 312118  2.700801 -4.839823          332            2.999389         2.999791\n",
+       " 312119  2.702502 -4.839914          332            2.998484         2.999791\n",
+       " 312120  2.704204 -4.840005          332            2.997579         2.999791\n",
+       " 312121  2.705906 -4.840009          332            2.996654         2.999791\n",
+       " 312122  2.707608 -4.840009          332            2.995727         2.999791\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 312883  4.002603 -4.845179          332            0.000084         2.999791\n",
+       " 312884  4.004304 -4.845531          332            0.000074         2.999791\n",
+       " 312885  4.006006 -4.845884          332            0.000063         2.999791\n",
+       " 312886  4.007708 -4.846236          332            0.000052         2.999791\n",
+       " 312887  4.009409 -4.846589          332            0.000041         2.999791\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 313118  2.700801 -4.839818          333            2.998090         2.999525\n",
+       " 313119  2.702502 -4.839901          333            2.997195         2.999525\n",
+       " 313120  2.704204 -4.839983          333            2.996300         2.999525\n",
+       " 313121  2.705906 -4.839958          333            2.995390         2.999525\n",
+       " 313122  2.707608 -4.839882          333            2.994473         2.999525\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 313883  4.002603 -4.843768          333            0.000084         2.999525\n",
+       " 313884  4.004304 -4.844014          333            0.000074         2.999525\n",
+       " 313885  4.006006 -4.844261          333            0.000063         2.999525\n",
+       " 313886  4.007708 -4.844507          333            0.000053         2.999525\n",
+       " 313887  4.009409 -4.844753          333            0.000042         2.999525\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 314118  2.700801 -4.840155          334            3.000239         3.000004\n",
+       " 314119  2.702502 -4.839975          334            2.999339         3.000004\n",
+       " 314120  2.704204 -4.839797          334            2.998439         3.000004\n",
+       " 314121  2.705906 -4.839919          334            2.997524         3.000004\n",
+       " 314122  2.707608 -4.840072          334            2.996606         3.000004\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 314883  4.002603 -4.844040          334            0.000085         3.000004\n",
+       " 314884  4.004304 -4.844276          334            0.000074         3.000004\n",
+       " 314885  4.006006 -4.844512          334            0.000064         3.000004\n",
+       " 314886  4.007708 -4.844748          334            0.000053         3.000004\n",
+       " 314887  4.009409 -4.844985          334            0.000042         3.000004\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 315118  2.700801 -4.839956          335            3.001266         3.002707\n",
+       " 315119  2.702502 -4.839843          335            3.000406         3.002707\n",
+       " 315120  2.704204 -4.839848          335            2.999522         3.002707\n",
+       " 315121  2.705906 -4.839998          335            2.998610         3.002707\n",
+       " 315122  2.707608 -4.840148          335            2.997697         3.002707\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 315883  4.002603 -4.843782          335            0.000086         3.002707\n",
+       " 315884  4.004304 -4.844016          335            0.000076         3.002707\n",
+       " 315885  4.006006 -4.844249          335            0.000065         3.002707\n",
+       " 315886  4.007708 -4.844481          335            0.000055         3.002707\n",
+       " 315887  4.009409 -4.844715          335            0.000044         3.002707\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 316118  2.700801 -4.840184          336            3.002178         3.003452\n",
+       " 316119  2.702502 -4.840068          336            3.001285         3.003452\n",
+       " 316120  2.704204 -4.839972          336            3.000378         3.003452\n",
+       " 316121  2.705906 -4.839899          336            2.999457         3.003452\n",
+       " 316122  2.707608 -4.839825          336            2.998535         3.003452\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 316883  4.002603 -4.845042          336            0.000086         3.003452\n",
+       " 316884  4.004304 -4.845356          336            0.000075         3.003452\n",
+       " 316885  4.006006 -4.845669          336            0.000065         3.003452\n",
+       " 316886  4.007708 -4.845983          336            0.000054         3.003452\n",
+       " 316887  4.009409 -4.846296          336            0.000044         3.003452\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 317118  2.700801 -4.840238          337            3.003220         3.003305\n",
+       " 317119  2.702502 -4.840199          337            3.002339         3.003305\n",
+       " 317120  2.704204 -4.840047          337            3.001449         3.003305\n",
+       " 317121  2.705906 -4.839894          337            3.000558         3.003305\n",
+       " 317122  2.707608 -4.839799          337            2.999662         3.003305\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 317883  4.002603 -4.842596          337            0.000087         3.003305\n",
+       " 317884  4.004304 -4.842785          337            0.000076         3.003305\n",
+       " 317885  4.006006 -4.842974          337            0.000066         3.003305\n",
+       " 317886  4.007708 -4.843163          337            0.000055         3.003305\n",
+       " 317887  4.009409 -4.843352          337            0.000045         3.003305\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 318118  2.700801 -4.839966          338            3.002994          3.00485\n",
+       " 318119  2.702502 -4.839873          338            3.002121          3.00485\n",
+       " 318120  2.704204 -4.839780          338            3.001249          3.00485\n",
+       " 318121  2.705906 -4.839857          338            3.000340          3.00485\n",
+       " 318122  2.707608 -4.839933          338            2.999432          3.00485\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 318883  4.002603 -4.844087          338            0.000088          3.00485\n",
+       " 318884  4.004304 -4.844342          338            0.000078          3.00485\n",
+       " 318885  4.006006 -4.844596          338            0.000067          3.00485\n",
+       " 318886  4.007708 -4.844851          338            0.000057          3.00485\n",
+       " 318887  4.009409 -4.845106          338            0.000047          3.00485\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 319118  2.700801 -4.840009          339            3.000786         3.001787\n",
+       " 319119  2.702502 -4.840009          339            2.999907         3.001787\n",
+       " 319120  2.704204 -4.840046          339            2.999004         3.001787\n",
+       " 319121  2.705906 -4.840121          339            2.998078         3.001787\n",
+       " 319122  2.707608 -4.840197          339            2.997152         3.001787\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 319883  4.002603 -4.845354          339            0.000086         3.001787\n",
+       " 319884  4.004304 -4.845697          339            0.000075         3.001787\n",
+       " 319885  4.006006 -4.846040          339            0.000065         3.001787\n",
+       " 319886  4.007708 -4.846384          339            0.000055         3.001787\n",
+       " 319887  4.009409 -4.846727          339            0.000044         3.001787\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 320118  2.700801 -4.840156          340            3.000763          3.00202\n",
+       " 320119  2.702502 -4.839980          340            2.999863          3.00202\n",
+       " 320120  2.704204 -4.839804          340            2.998964          3.00202\n",
+       " 320121  2.705906 -4.839716          340            2.998075          3.00202\n",
+       " 320122  2.707608 -4.839643          340            2.997189          3.00202\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 320883  4.002603 -4.844074          340            0.000089          3.00202\n",
+       " 320884  4.004304 -4.844332          340            0.000078          3.00202\n",
+       " 320885  4.006006 -4.844589          340            0.000068          3.00202\n",
+       " 320886  4.007708 -4.844847          340            0.000057          3.00202\n",
+       " 320887  4.009409 -4.845104          340            0.000047          3.00202\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 321118  2.700801 -4.839963          341            2.999155         2.999716\n",
+       " 321119  2.702502 -4.839943          341            2.998279         2.999716\n",
+       " 321120  2.704204 -4.839868          341            2.997397         2.999716\n",
+       " 321121  2.705906 -4.839793          341            2.996515         2.999716\n",
+       " 321122  2.707608 -4.839780          341            2.995588         2.999716\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 321883  4.002603 -4.845128          341            0.000087         2.999716\n",
+       " 321884  4.004304 -4.845470          341            0.000077         2.999716\n",
+       " 321885  4.006006 -4.845813          341            0.000066         2.999716\n",
+       " 321886  4.007708 -4.846156          341            0.000055         2.999716\n",
+       " 321887  4.009409 -4.846498          341            0.000044         2.999716\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 322118  2.700801 -4.839560          342            2.998368          2.99954\n",
+       " 322119  2.702502 -4.839634          342            2.997455          2.99954\n",
+       " 322120  2.704204 -4.839710          342            2.996543          2.99954\n",
+       " 322121  2.705906 -4.839780          342            2.995630          2.99954\n",
+       " 322122  2.707608 -4.839780          342            2.994713          2.99954\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 322883  4.002603 -4.844497          342            0.000088          2.99954\n",
+       " 322884  4.004304 -4.844770          342            0.000077          2.99954\n",
+       " 322885  4.006006 -4.845043          342            0.000067          2.99954\n",
+       " 322886  4.007708 -4.845315          342            0.000056          2.99954\n",
+       " 322887  4.009409 -4.845589          342            0.000045          2.99954\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 323118  2.700801 -4.840052          343            2.993863          2.99496\n",
+       " 323119  2.702502 -4.840143          343            2.992959          2.99496\n",
+       " 323120  2.704204 -4.840234          343            2.992054          2.99496\n",
+       " 323121  2.705906 -4.840167          343            2.991137          2.99496\n",
+       " 323122  2.707608 -4.840091          343            2.990220          2.99496\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 323883  4.002603 -4.844993          343            0.000086          2.99496\n",
+       " 323884  4.004304 -4.845318          343            0.000075          2.99496\n",
+       " 323885  4.006006 -4.845643          343            0.000065          2.99496\n",
+       " 323886  4.007708 -4.845967          343            0.000054          2.99496\n",
+       " 323887  4.009409 -4.846292          343            0.000044          2.99496\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 324118  2.700801 -4.840353          344            2.994165         2.994818\n",
+       " 324119  2.702502 -4.840111          344            2.993301         2.994818\n",
+       " 324120  2.704204 -4.839965          344            2.992416         2.994818\n",
+       " 324121  2.705906 -4.839890          344            2.991517         2.994818\n",
+       " 324122  2.707608 -4.839815          344            2.990617         2.994818\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 324883  4.002603 -4.842777          344            0.000084         2.994818\n",
+       " 324884  4.004304 -4.842934          344            0.000074         2.994818\n",
+       " 324885  4.006006 -4.843090          344            0.000063         2.994818\n",
+       " 324886  4.007708 -4.843246          344            0.000053         2.994818\n",
+       " 324887  4.009409 -4.843403          344            0.000042         2.994818\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 325118  2.700801 -4.839704          345            2.993449         2.993939\n",
+       " 325119  2.702502 -4.839563          345            2.992521         2.993939\n",
+       " 325120  2.704204 -4.839711          345            2.991604         2.993939\n",
+       " 325121  2.705906 -4.839859          345            2.990687         2.993939\n",
+       " 325122  2.707608 -4.840007          345            2.989770         2.993939\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 325880  3.997498 -4.839892          345            0.000106         2.993939\n",
+       " 325881  3.999199 -4.839867          345            0.000094         2.993939\n",
+       " 325882  4.000901 -4.839842          345            0.000082         2.993939\n",
+       " 325883  4.002603 -4.839818          345            0.000071         2.993939\n",
+       " 325884  4.004304 -4.839793          345            0.000059         2.993939\n",
+       " \n",
+       " [767 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 326118  2.700801 -4.840137          346            2.995342         2.994678\n",
+       " 326119  2.702502 -4.839920          346            2.994436         2.994678\n",
+       " 326120  2.704204 -4.839780          346            2.993534         2.994678\n",
+       " 326121  2.705906 -4.839780          346            2.992638         2.994678\n",
+       " 326122  2.707608 -4.839780          346            2.991743         2.994678\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 326883  4.002603 -4.844928          346            0.000084         2.994678\n",
+       " 326884  4.004304 -4.845227          346            0.000073         2.994678\n",
+       " 326885  4.006006 -4.845527          346            0.000063         2.994678\n",
+       " 326886  4.007708 -4.845827          346            0.000052         2.994678\n",
+       " 326887  4.009409 -4.846126          346            0.000042         2.994678\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 327118  2.700801 -4.840050          347            2.999110         2.997216\n",
+       " 327119  2.702502 -4.839647          347            2.998242         2.997216\n",
+       " 327120  2.704204 -4.839668          347            2.997347         2.997216\n",
+       " 327121  2.705906 -4.839820          347            2.996443         2.997216\n",
+       " 327122  2.707608 -4.839972          347            2.995539         2.997216\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 327883  4.002603 -4.843767          347            0.000085         2.997216\n",
+       " 327884  4.004304 -4.844008          347            0.000074         2.997216\n",
+       " 327885  4.006006 -4.844250          347            0.000064         2.997216\n",
+       " 327886  4.007708 -4.844491          347            0.000054         2.997216\n",
+       " 327887  4.009409 -4.844733          347            0.000043         2.997216\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 328118  2.700801 -4.839855          348            2.996855         2.999147\n",
+       " 328119  2.702502 -4.840004          348            2.995965         2.999147\n",
+       " 328120  2.704204 -4.839859          348            2.995074         2.999147\n",
+       " 328121  2.705906 -4.839713          348            2.994183         2.999147\n",
+       " 328122  2.707608 -4.839567          348            2.993292         2.999147\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 328883  4.002603 -4.843680          348            0.000082         2.999147\n",
+       " 328884  4.004304 -4.843900          348            0.000072         2.999147\n",
+       " 328885  4.006006 -4.844121          348            0.000062         2.999147\n",
+       " 328886  4.007708 -4.844340          348            0.000051         2.999147\n",
+       " 328887  4.009409 -4.844561          348            0.000041         2.999147\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 329118  2.700801 -4.839384          349            2.995535         2.997311\n",
+       " 329119  2.702502 -4.839601          349            2.994654         2.997311\n",
+       " 329120  2.704204 -4.839901          349            2.993776         2.997311\n",
+       " 329121  2.705906 -4.840202          349            2.992899         2.997311\n",
+       " 329122  2.707608 -4.840304          349            2.991975         2.997311\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 329883  4.002603 -4.844677          349            0.000083         2.997311\n",
+       " 329884  4.004304 -4.844985          349            0.000072         2.997311\n",
+       " 329885  4.006006 -4.845294          349            0.000062         2.997311\n",
+       " 329886  4.007708 -4.845602          349            0.000052         2.997311\n",
+       " 329887  4.009409 -4.845910          349            0.000041         2.997311\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 330118  2.700801 -4.840012          350            2.995419         2.996669\n",
+       " 330119  2.702502 -4.839742          350            2.994533         2.996669\n",
+       " 330120  2.704204 -4.839667          350            2.993646         2.996669\n",
+       " 330121  2.705906 -4.839593          350            2.992760         2.996669\n",
+       " 330122  2.707608 -4.839616          350            2.991866         2.996669\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 330883  4.002603 -4.844497          350            0.000084         2.996669\n",
+       " 330884  4.004304 -4.844781          350            0.000074         2.996669\n",
+       " 330885  4.006006 -4.845065          350            0.000064         2.996669\n",
+       " 330886  4.007708 -4.845349          350            0.000054         2.996669\n",
+       " 330887  4.009409 -4.845634          350            0.000043         2.996669\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 331118  2.700801 -4.840187          356            3.296049         3.132252\n",
+       " 331119  2.702502 -4.840009          356            3.295145         3.132252\n",
+       " 331120  2.704204 -4.840009          356            3.294254         3.132252\n",
+       " 331121  2.705906 -4.840009          356            3.293363         3.132252\n",
+       " 331122  2.707608 -4.840009          356            3.292443         3.132252\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 331894  4.021321 -4.844387          356            0.000083         3.132252\n",
+       " 331895  4.023023 -4.844634          356            0.000074         3.132252\n",
+       " 331896  4.024725 -4.844882          356            0.000064         3.132252\n",
+       " 331897  4.026426 -4.845129          356            0.000054         3.132252\n",
+       " 331898  4.028128 -4.845376          356            0.000045         3.132252\n",
+       " \n",
+       " [781 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 332118  2.700801 -4.839674          357            3.266016         3.267386\n",
+       " 332119  2.702502 -4.839939          357            3.265086         3.267386\n",
+       " 332120  2.704204 -4.840203          357            3.264155         3.267386\n",
+       " 332121  2.705906 -4.840173          357            3.263229         3.267386\n",
+       " 332122  2.707608 -4.840098          357            3.262302         3.267386\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 332892  4.017918 -4.844799          357            0.000080         3.267386\n",
+       " 332893  4.019619 -4.845083          357            0.000070         3.267386\n",
+       " 332894  4.021321 -4.845367          357            0.000060         3.267386\n",
+       " 332895  4.023023 -4.845651          357            0.000050         3.267386\n",
+       " 332896  4.024725 -4.845935          357            0.000041         3.267386\n",
+       " \n",
+       " [779 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 333118  2.700801 -4.839831          358            3.241389         3.251447\n",
+       " 333119  2.702502 -4.839940          358            3.240464         3.251447\n",
+       " 333120  2.704204 -4.840009          358            3.239537         3.251447\n",
+       " 333121  2.705906 -4.840009          358            3.238607         3.251447\n",
+       " 333122  2.707608 -4.840009          358            3.237676         3.251447\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 333891  4.016216 -4.843724          358            0.000080         3.251447\n",
+       " 333892  4.017918 -4.843934          358            0.000070         3.251447\n",
+       " 333893  4.019619 -4.844145          358            0.000061         3.251447\n",
+       " 333894  4.021321 -4.844355          358            0.000051         3.251447\n",
+       " 333895  4.023023 -4.844566          358            0.000041         3.251447\n",
+       " \n",
+       " [778 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 334118  2.700801 -4.839601          359            3.218775         3.231539\n",
+       " 334119  2.702502 -4.839751          359            3.217875         3.231539\n",
+       " 334120  2.704204 -4.839901          359            3.216975         3.231539\n",
+       " 334121  2.705906 -4.840031          359            3.216060         3.231539\n",
+       " 334122  2.707608 -4.840106          359            3.215103         3.231539\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 334890  4.014514 -4.844380          359            0.000082         3.231539\n",
+       " 334891  4.016216 -4.844644          359            0.000072         3.231539\n",
+       " 334892  4.017918 -4.844908          359            0.000062         3.231539\n",
+       " 334893  4.019619 -4.845172          359            0.000052         3.231539\n",
+       " 334894  4.021321 -4.845437          359            0.000042         3.231539\n",
+       " \n",
+       " [777 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 335118  2.700801 -4.840238          360            3.199670         3.210449\n",
+       " 335119  2.702502 -4.840310          360            3.198762         3.210449\n",
+       " 335120  2.704204 -4.840384          360            3.197854         3.210449\n",
+       " 335121  2.705906 -4.840458          360            3.196946         3.210449\n",
+       " 335122  2.707608 -4.840335          360            3.196014         3.210449\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 335889  4.012813 -4.844492          360            0.000088         3.210449\n",
+       " 335890  4.014514 -4.844743          360            0.000078         3.210449\n",
+       " 335891  4.016216 -4.844995          360            0.000069         3.210449\n",
+       " 335892  4.017918 -4.845245          360            0.000059         3.210449\n",
+       " 335893  4.019619 -4.845497          360            0.000049         3.210449\n",
+       " \n",
+       " [776 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 336118  2.700801 -4.839946          361            3.183090         3.192756\n",
+       " 336119  2.702502 -4.839796          361            3.182181         3.192756\n",
+       " 336120  2.704204 -4.839646          361            3.181273         3.192756\n",
+       " 336121  2.705906 -4.839551          361            3.180346         3.192756\n",
+       " 336122  2.707608 -4.839551          361            3.179388         3.192756\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 336889  4.012813 -4.843516          361            0.000081         3.192756\n",
+       " 336890  4.014514 -4.843716          361            0.000071         3.192756\n",
+       " 336891  4.016216 -4.843915          361            0.000062         3.192756\n",
+       " 336892  4.017918 -4.844115          361            0.000052         3.192756\n",
+       " 336893  4.019619 -4.844315          361            0.000042         3.192756\n",
+       " \n",
+       " [776 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 337118  2.700801 -4.839729          362            3.169966         3.178925\n",
+       " 337119  2.702502 -4.839618          362            3.169053         3.178925\n",
+       " 337120  2.704204 -4.839581          362            3.168133         3.178925\n",
+       " 337121  2.705906 -4.839655          362            3.167204         3.178925\n",
+       " 337122  2.707608 -4.839729          362            3.166274         3.178925\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 337888  4.011111 -4.843198          362            0.000088         3.178925\n",
+       " 337889  4.012813 -4.843388          362            0.000078         3.178925\n",
+       " 337890  4.014514 -4.843578          362            0.000069         3.178925\n",
+       " 337891  4.016216 -4.843768          362            0.000059         3.178925\n",
+       " 337892  4.017918 -4.843957          362            0.000049         3.178925\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 338118  2.700801 -4.840193          363            3.160434         3.167649\n",
+       " 338119  2.702502 -4.840097          363            3.159552         3.167649\n",
+       " 338120  2.704204 -4.840023          363            3.158664         3.167649\n",
+       " 338121  2.705906 -4.840175          363            3.157719         3.167649\n",
+       " 338122  2.707608 -4.840328          363            3.156775         3.167649\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 338888  4.011111 -4.842828          363            0.000086         3.167649\n",
+       " 338889  4.012813 -4.843006          363            0.000076         3.167649\n",
+       " 338890  4.014514 -4.843185          363            0.000067         3.167649\n",
+       " 338891  4.016216 -4.843363          363            0.000057         3.167649\n",
+       " 338892  4.017918 -4.843542          363            0.000047         3.167649\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 339118  2.700801 -4.840008          364            3.148685          3.15559\n",
+       " 339119  2.702502 -4.839551          364            3.147776          3.15559\n",
+       " 339120  2.704204 -4.839551          364            3.146868          3.15559\n",
+       " 339121  2.705906 -4.839551          364            3.145959          3.15559\n",
+       " 339122  2.707608 -4.839551          364            3.145051          3.15559\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 339888  4.011111 -4.843496          364            0.000082          3.15559\n",
+       " 339889  4.012813 -4.843695          364            0.000073          3.15559\n",
+       " 339890  4.014514 -4.843895          364            0.000063          3.15559\n",
+       " 339891  4.016216 -4.844094          364            0.000053          3.15559\n",
+       " 339892  4.017918 -4.844294          364            0.000043          3.15559\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 340118  2.700801 -4.839841          365            3.143524         3.147313\n",
+       " 340119  2.702502 -4.839972          365            3.142616         3.147313\n",
+       " 340120  2.704204 -4.840009          365            3.141683         3.147313\n",
+       " 340121  2.705906 -4.840009          365            3.140740         3.147313\n",
+       " 340122  2.707608 -4.840009          365            3.139797         3.147313\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 340888  4.011111 -4.842773          365            0.000082         3.147313\n",
+       " 340889  4.012813 -4.842929          365            0.000072         3.147313\n",
+       " 340890  4.014514 -4.843086          365            0.000062         3.147313\n",
+       " 340891  4.016216 -4.843243          365            0.000052         3.147313\n",
+       " 340892  4.017918 -4.843399          365            0.000042         3.147313\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 341118  2.700801 -4.839841          366            3.133589         3.140178\n",
+       " 341119  2.702502 -4.839551          366            3.132642         3.140178\n",
+       " 341120  2.704204 -4.839551          366            3.131773         3.140178\n",
+       " 341121  2.705906 -4.839551          366            3.130903         3.140178\n",
+       " 341122  2.707608 -4.839551          366            3.130033         3.140178\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 341887  4.009409 -4.842612          366            0.000089         3.140178\n",
+       " 341888  4.011111 -4.842779          366            0.000079         3.140178\n",
+       " 341889  4.012813 -4.842947          366            0.000069         3.140178\n",
+       " 341890  4.014514 -4.843114          366            0.000059         3.140178\n",
+       " 341891  4.016216 -4.843281          366            0.000049         3.140178\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 342118  2.700801 -4.839745          367            3.126518         3.131494\n",
+       " 342119  2.702502 -4.839360          367            3.125594         3.131494\n",
+       " 342120  2.704204 -4.839509          367            3.124694         3.131494\n",
+       " 342121  2.705906 -4.839656          367            3.123795         3.131494\n",
+       " 342122  2.707608 -4.839793          367            3.122886         3.131494\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 342887  4.009409 -4.844252          367            0.000087         3.131494\n",
+       " 342888  4.011111 -4.844513          367            0.000077         3.131494\n",
+       " 342889  4.012813 -4.844775          367            0.000067         3.131494\n",
+       " 342890  4.014514 -4.845036          367            0.000057         3.131494\n",
+       " 342891  4.016216 -4.845298          367            0.000047         3.131494\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 343118  2.700801 -4.839851          368            3.119444         3.124273\n",
+       " 343119  2.702502 -4.840004          368            3.118536         3.124273\n",
+       " 343120  2.704204 -4.840156          368            3.117627         3.124273\n",
+       " 343121  2.705906 -4.840204          368            3.116703         3.124273\n",
+       " 343122  2.707608 -4.840130          368            3.115760         3.124273\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 343887  4.009409 -4.843660          368            0.000086         3.124273\n",
+       " 343888  4.011111 -4.843857          368            0.000076         3.124273\n",
+       " 343889  4.012813 -4.844055          368            0.000066         3.124273\n",
+       " 343890  4.014514 -4.844253          368            0.000056         3.124273\n",
+       " 343891  4.016216 -4.844450          368            0.000046         3.124273\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 344118  2.700801 -4.839670          369            3.113031         3.116502\n",
+       " 344119  2.702502 -4.839926          369            3.112121         3.116502\n",
+       " 344120  2.704204 -4.840181          369            3.111212         3.116502\n",
+       " 344121  2.705906 -4.840180          369            3.110300         3.116502\n",
+       " 344122  2.707608 -4.840105          369            3.109387         3.116502\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 344887  4.009409 -4.843625          369            0.000081         3.116502\n",
+       " 344888  4.011111 -4.843856          369            0.000071         3.116502\n",
+       " 344889  4.012813 -4.844088          369            0.000061         3.116502\n",
+       " 344890  4.014514 -4.844319          369            0.000051         3.116502\n",
+       " 344891  4.016216 -4.844551          369            0.000041         3.116502\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 345118  2.700801 -4.840052          370            3.107927         3.111472\n",
+       " 345119  2.702502 -4.840143          370            3.107027         3.111472\n",
+       " 345120  2.704204 -4.840234          370            3.106128         3.111472\n",
+       " 345121  2.705906 -4.840167          370            3.105190         3.111472\n",
+       " 345122  2.707608 -4.840091          370            3.104251         3.111472\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 345887  4.009409 -4.844070          370            0.000081         3.111472\n",
+       " 345888  4.011111 -4.844299          370            0.000072         3.111472\n",
+       " 345889  4.012813 -4.844529          370            0.000062         3.111472\n",
+       " 345890  4.014514 -4.844759          370            0.000052         3.111472\n",
+       " 345891  4.016216 -4.844988          370            0.000042         3.111472\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 346118  2.700801 -4.840032          371            3.103920         3.107295\n",
+       " 346119  2.702502 -4.839647          371            3.103024         3.107295\n",
+       " 346120  2.704204 -4.839865          371            3.102134         3.107295\n",
+       " 346121  2.705906 -4.840084          371            3.101242         3.107295\n",
+       " 346122  2.707608 -4.840216          371            3.100332         3.107295\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 346886  4.007708 -4.842835          371            0.000089         3.107295\n",
+       " 346887  4.009409 -4.843003          371            0.000079         3.107295\n",
+       " 346888  4.011111 -4.843171          371            0.000069         3.107295\n",
+       " 346889  4.012813 -4.843339          371            0.000059         3.107295\n",
+       " 346890  4.014514 -4.843507          371            0.000049         3.107295\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 347118  2.700801 -4.839918          372            3.100729         3.104821\n",
+       " 347119  2.702502 -4.839877          372            3.099827         3.104821\n",
+       " 347120  2.704204 -4.839726          372            3.098918         3.104821\n",
+       " 347121  2.705906 -4.839576          372            3.098010         3.104821\n",
+       " 347122  2.707608 -4.839675          372            3.097084         3.104821\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 347887  4.009409 -4.845080          372            0.000080         3.104821\n",
+       " 347888  4.011111 -4.845350          372            0.000070         3.104821\n",
+       " 347889  4.012813 -4.845620          372            0.000060         3.104821\n",
+       " 347890  4.014514 -4.845890          372            0.000051         3.104821\n",
+       " 347891  4.016216 -4.846159          372            0.000041         3.104821\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 348118  2.700801 -4.839960          373            3.097350          3.10012\n",
+       " 348119  2.702502 -4.839853          373            3.096488          3.10012\n",
+       " 348120  2.704204 -4.839804          373            3.095600          3.10012\n",
+       " 348121  2.705906 -4.839879          373            3.094656          3.10012\n",
+       " 348122  2.707608 -4.839954          373            3.093713          3.10012\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 348887  4.009409 -4.843126          373            0.000080          3.10012\n",
+       " 348888  4.011111 -4.843312          373            0.000070          3.10012\n",
+       " 348889  4.012813 -4.843499          373            0.000061          3.10012\n",
+       " 348890  4.014514 -4.843685          373            0.000051          3.10012\n",
+       " 348891  4.016216 -4.843871          373            0.000041          3.10012\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 349118  2.700801 -4.839827          374            3.092754         3.096344\n",
+       " 349119  2.702502 -4.839927          374            3.091866         3.096344\n",
+       " 349120  2.704204 -4.839996          374            3.090970         3.096344\n",
+       " 349121  2.705906 -4.839921          374            3.090035         3.096344\n",
+       " 349122  2.707608 -4.839846          374            3.089100         3.096344\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 349886  4.007708 -4.843881          374            0.000085         3.096344\n",
+       " 349887  4.009409 -4.844133          374            0.000075         3.096344\n",
+       " 349888  4.011111 -4.844385          374            0.000066         3.096344\n",
+       " 349889  4.012813 -4.844637          374            0.000056         3.096344\n",
+       " 349890  4.014514 -4.844889          374            0.000046         3.096344\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 350118  2.700801 -4.839780          375            3.088177         3.091337\n",
+       " 350119  2.702502 -4.839780          375            3.087277         3.091337\n",
+       " 350120  2.704204 -4.839780          375            3.086378         3.091337\n",
+       " 350121  2.705906 -4.839842          375            3.085467         3.091337\n",
+       " 350122  2.707608 -4.839917          375            3.084555         3.091337\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 350886  4.007708 -4.844342          375            0.000087         3.091337\n",
+       " 350887  4.009409 -4.844582          375            0.000077         3.091337\n",
+       " 350888  4.011111 -4.844821          375            0.000068         3.091337\n",
+       " 350889  4.012813 -4.845061          375            0.000058         3.091337\n",
+       " 350890  4.014514 -4.845301          375            0.000048         3.091337\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 351118  2.700801 -4.839966          376            3.082620           3.0855\n",
+       " 351119  2.702502 -4.839873          376            3.081709           3.0855\n",
+       " 351120  2.704204 -4.839780          376            3.080799           3.0855\n",
+       " 351121  2.705906 -4.839931          376            3.079899           3.0855\n",
+       " 351122  2.707608 -4.840081          376            3.078999           3.0855\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 351886  4.007708 -4.843460          376            0.000087           3.0855\n",
+       " 351887  4.009409 -4.843648          376            0.000077           3.0855\n",
+       " 351888  4.011111 -4.843838          376            0.000067           3.0855\n",
+       " 351889  4.012813 -4.844027          376            0.000057           3.0855\n",
+       " 351890  4.014514 -4.844216          376            0.000047           3.0855\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 352118  2.700801 -4.839808          377            3.078230         3.080211\n",
+       " 352119  2.702502 -4.839882          377            3.077335         3.080211\n",
+       " 352120  2.704204 -4.839956          377            3.076440         3.080211\n",
+       " 352121  2.705906 -4.840031          377            3.075537         3.080211\n",
+       " 352122  2.707608 -4.840106          377            3.074615         3.080211\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 352886  4.007708 -4.844032          377            0.000085         3.080211\n",
+       " 352887  4.009409 -4.844254          377            0.000075         3.080211\n",
+       " 352888  4.011111 -4.844475          377            0.000065         3.080211\n",
+       " 352889  4.012813 -4.844697          377            0.000055         3.080211\n",
+       " 352890  4.014514 -4.844918          377            0.000045         3.080211\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 353118  2.700801 -4.839970          378            3.074000         3.076838\n",
+       " 353119  2.702502 -4.839884          378            3.073085         3.076838\n",
+       " 353120  2.704204 -4.839799          378            3.072171         3.076838\n",
+       " 353121  2.705906 -4.839780          378            3.071288         3.076838\n",
+       " 353122  2.707608 -4.839780          378            3.070415         3.076838\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 353886  4.007708 -4.843309          378            0.000083         3.076838\n",
+       " 353887  4.009409 -4.843497          378            0.000073         3.076838\n",
+       " 353888  4.011111 -4.843686          378            0.000063         3.076838\n",
+       " 353889  4.012813 -4.843875          378            0.000053         3.076838\n",
+       " 353890  4.014514 -4.844063          378            0.000043         3.076838\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 354118  2.700801 -4.839864          379            3.070544         3.072713\n",
+       " 354119  2.702502 -4.840043          379            3.069629         3.072713\n",
+       " 354120  2.704204 -4.840222          379            3.068714         3.072713\n",
+       " 354121  2.705906 -4.840172          379            3.067828         3.072713\n",
+       " 354122  2.707608 -4.840099          379            3.066946         3.072713\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 354886  4.007708 -4.844613          379            0.000082         3.072713\n",
+       " 354887  4.009409 -4.844873          379            0.000072         3.072713\n",
+       " 354888  4.011111 -4.845133          379            0.000062         3.072713\n",
+       " 354889  4.012813 -4.845393          379            0.000052         3.072713\n",
+       " 354890  4.014514 -4.845653          379            0.000043         3.072713\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 355118  2.700801 -4.839935          380            3.068447         3.069342\n",
+       " 355119  2.702502 -4.839775          380            3.067590         3.069342\n",
+       " 355120  2.704204 -4.839616          380            3.066732         3.069342\n",
+       " 355121  2.705906 -4.839598          380            3.065831         3.069342\n",
+       " 355122  2.707608 -4.839675          380            3.064899         3.069342\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 355885  4.006006 -4.844728          380            0.000089         3.069342\n",
+       " 355886  4.007708 -4.845021          380            0.000079         3.069342\n",
+       " 355887  4.009409 -4.845314          380            0.000069         3.069342\n",
+       " 355888  4.011111 -4.845606          380            0.000059         3.069342\n",
+       " 355889  4.012813 -4.845899          380            0.000049         3.069342\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 356118  2.700801 -4.839909          381            3.067193         3.068161\n",
+       " 356119  2.702502 -4.840185          381            3.066325         3.068161\n",
+       " 356120  2.704204 -4.840115          381            3.065418         3.068161\n",
+       " 356121  2.705906 -4.839962          381            3.064500         3.068161\n",
+       " 356122  2.707608 -4.839810          381            3.063582         3.068161\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 356885  4.006006 -4.844226          381            0.000088         3.068161\n",
+       " 356886  4.007708 -4.844487          381            0.000078         3.068161\n",
+       " 356887  4.009409 -4.844747          381            0.000068         3.068161\n",
+       " 356888  4.011111 -4.845008          381            0.000058         3.068161\n",
+       " 356889  4.012813 -4.845268          381            0.000049         3.068161\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 357118  2.700801 -4.839876          382            3.067537         3.067502\n",
+       " 357119  2.702502 -4.839983          382            3.066626         3.067502\n",
+       " 357120  2.704204 -4.839910          382            3.065761         3.067502\n",
+       " 357121  2.705906 -4.839836          382            3.064896         3.067502\n",
+       " 357122  2.707608 -4.839780          382            3.064018         3.067502\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 357885  4.006006 -4.842911          382            0.000087         3.067502\n",
+       " 357886  4.007708 -4.843068          382            0.000078         3.067502\n",
+       " 357887  4.009409 -4.843225          382            0.000068         3.067502\n",
+       " 357888  4.011111 -4.843381          382            0.000058         3.067502\n",
+       " 357889  4.012813 -4.843537          382            0.000048         3.067502\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 358118  2.700801 -4.839780          383            3.063266         3.066644\n",
+       " 358119  2.702502 -4.839780          383            3.062362         3.066644\n",
+       " 358120  2.704204 -4.839780          383            3.061484         3.066644\n",
+       " 358121  2.705906 -4.839780          383            3.060606         3.066644\n",
+       " 358122  2.707608 -4.839729          383            3.059710         3.066644\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 358885  4.006006 -4.844307          383            0.000087         3.066644\n",
+       " 358886  4.007708 -4.844555          383            0.000077         3.066644\n",
+       " 358887  4.009409 -4.844804          383            0.000067         3.066644\n",
+       " 358888  4.011111 -4.845053          383            0.000057         3.066644\n",
+       " 358889  4.012813 -4.845301          383            0.000048         3.066644\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 359118  2.700801 -4.839780          384            3.059720         3.062817\n",
+       " 359119  2.702502 -4.839780          384            3.058858         3.062817\n",
+       " 359120  2.704204 -4.839884          384            3.057958         3.062817\n",
+       " 359121  2.705906 -4.840039          384            3.057040         3.062817\n",
+       " 359122  2.707608 -4.840194          384            3.056123         3.062817\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 359883  4.002603 -4.840697          384            0.000096         3.062817\n",
+       " 359884  4.004304 -4.840753          384            0.000085         3.062817\n",
+       " 359885  4.006006 -4.840810          384            0.000075         3.062817\n",
+       " 359886  4.007708 -4.840867          384            0.000064         3.062817\n",
+       " 359887  4.009409 -4.840923          384            0.000053         3.062817\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 360118  2.700801 -4.840238          385            3.057121         3.059853\n",
+       " 360119  2.702502 -4.840151          385            3.056221         3.059853\n",
+       " 360120  2.704204 -4.839930          385            3.055322         3.059853\n",
+       " 360121  2.705906 -4.839707          385            3.054422         3.059853\n",
+       " 360122  2.707608 -4.839573          385            3.053511         3.059853\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 360885  4.006006 -4.844550          385            0.000086         3.059853\n",
+       " 360886  4.007708 -4.844798          385            0.000076         3.059853\n",
+       " 360887  4.009409 -4.845046          385            0.000067         3.059853\n",
+       " 360888  4.011111 -4.845294          385            0.000057         3.059853\n",
+       " 360889  4.012813 -4.845541          385            0.000047         3.059853\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 361118  2.700801 -4.839780          386            3.055633         3.057627\n",
+       " 361119  2.702502 -4.839780          386            3.054742         3.057627\n",
+       " 361120  2.704204 -4.839851          386            3.053847         3.057627\n",
+       " 361121  2.705906 -4.839926          386            3.052952         3.057627\n",
+       " 361122  2.707608 -4.840001          386            3.052057         3.057627\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 361885  4.006006 -4.844487          386            0.000085         3.057627\n",
+       " 361886  4.007708 -4.844756          386            0.000075         3.057627\n",
+       " 361887  4.009409 -4.845025          386            0.000065         3.057627\n",
+       " 361888  4.011111 -4.845293          386            0.000056         3.057627\n",
+       " 361889  4.012813 -4.845562          386            0.000046         3.057627\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 362118  2.700801 -4.839717          387            3.053851         3.056029\n",
+       " 362119  2.702502 -4.840074          387            3.052944         3.056029\n",
+       " 362120  2.704204 -4.840159          387            3.052032         3.056029\n",
+       " 362121  2.705906 -4.840014          387            3.051115         3.056029\n",
+       " 362122  2.707608 -4.839868          387            3.050199         3.056029\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 362885  4.006006 -4.844057          387            0.000085         3.056029\n",
+       " 362886  4.007708 -4.844315          387            0.000076         3.056029\n",
+       " 362887  4.009409 -4.844572          387            0.000066         3.056029\n",
+       " 362888  4.011111 -4.844830          387            0.000056         3.056029\n",
+       " 362889  4.012813 -4.845088          387            0.000047         3.056029\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 363118  2.700801 -4.840009          388            3.051921          3.05423\n",
+       " 363119  2.702502 -4.840009          388            3.051005          3.05423\n",
+       " 363120  2.704204 -4.840009          388            3.050106          3.05423\n",
+       " 363121  2.705906 -4.840009          388            3.049206          3.05423\n",
+       " 363122  2.707608 -4.840055          388            3.048296          3.05423\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 363885  4.006006 -4.844207          388            0.000087          3.05423\n",
+       " 363886  4.007708 -4.844477          388            0.000077          3.05423\n",
+       " 363887  4.009409 -4.844746          388            0.000067          3.05423\n",
+       " 363888  4.011111 -4.845015          388            0.000057          3.05423\n",
+       " 363889  4.012813 -4.845284          388            0.000048          3.05423\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 364118  2.700801 -4.839551          389            3.049112         3.051875\n",
+       " 364119  2.702502 -4.839551          389            3.048249         3.051875\n",
+       " 364120  2.704204 -4.839644          389            3.047347         3.051875\n",
+       " 364121  2.705906 -4.839792          389            3.046421         3.051875\n",
+       " 364122  2.707608 -4.839940          389            3.045495         3.051875\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 364885  4.006006 -4.844285          389            0.000085         3.051875\n",
+       " 364886  4.007708 -4.844543          389            0.000076         3.051875\n",
+       " 364887  4.009409 -4.844801          389            0.000066         3.051875\n",
+       " 364888  4.011111 -4.845059          389            0.000056         3.051875\n",
+       " 364889  4.012813 -4.845317          389            0.000047         3.051875\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 365118  2.700801 -4.839901          390            3.048208         3.048889\n",
+       " 365119  2.702502 -4.839816          390            3.047307         3.048889\n",
+       " 365120  2.704204 -4.839890          390            3.046433         3.048889\n",
+       " 365121  2.705906 -4.839964          390            3.045560         3.048889\n",
+       " 365122  2.707608 -4.840009          390            3.044664         3.048889\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 365885  4.006006 -4.843088          390            0.000085         3.048889\n",
+       " 365886  4.007708 -4.843264          390            0.000075         3.048889\n",
+       " 365887  4.009409 -4.843439          390            0.000065         3.048889\n",
+       " 365888  4.011111 -4.843615          390            0.000056         3.048889\n",
+       " 365889  4.012813 -4.843790          390            0.000046         3.048889\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 366118  2.700801 -4.840226          391            3.046922         3.047924\n",
+       " 366119  2.702502 -4.840361          391            3.046040         3.047924\n",
+       " 366120  2.704204 -4.840138          391            3.045132         3.047924\n",
+       " 366121  2.705906 -4.839917          391            3.044223         3.047924\n",
+       " 366122  2.707608 -4.839752          391            3.043307         3.047924\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 366885  4.006006 -4.844186          391            0.000084         3.047924\n",
+       " 366886  4.007708 -4.844423          391            0.000074         3.047924\n",
+       " 366887  4.009409 -4.844660          391            0.000065         3.047924\n",
+       " 366888  4.011111 -4.844897          391            0.000055         3.047924\n",
+       " 366889  4.012813 -4.845135          391            0.000045         3.047924\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 367118  2.700801 -4.839780          392            3.047231         3.048912\n",
+       " 367119  2.702502 -4.839785          392            3.046340         3.048912\n",
+       " 367120  2.704204 -4.839933          392            3.045440         3.048912\n",
+       " 367121  2.705906 -4.840081          392            3.044541         3.048912\n",
+       " 367122  2.707608 -4.840229          392            3.043641         3.048912\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 367885  4.006006 -4.843372          392            0.000086         3.048912\n",
+       " 367886  4.007708 -4.843577          392            0.000076         3.048912\n",
+       " 367887  4.009409 -4.843782          392            0.000067         3.048912\n",
+       " 367888  4.011111 -4.843987          392            0.000057         3.048912\n",
+       " 367889  4.012813 -4.844192          392            0.000048         3.048912\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 368118  2.700801 -4.839955          393            3.044016         3.045789\n",
+       " 368119  2.702502 -4.839839          393            3.043123         3.045789\n",
+       " 368120  2.704204 -4.839780          393            3.042223         3.045789\n",
+       " 368121  2.705906 -4.839780          393            3.041315         3.045789\n",
+       " 368122  2.707608 -4.839780          393            3.040406         3.045789\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 368885  4.006006 -4.843659          393            0.000083         3.045789\n",
+       " 368886  4.007708 -4.843866          393            0.000074         3.045789\n",
+       " 368887  4.009409 -4.844072          393            0.000064         3.045789\n",
+       " 368888  4.011111 -4.844278          393            0.000054         3.045789\n",
+       " 368889  4.012813 -4.844485          393            0.000045         3.045789\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 369118  2.700801 -4.839780          394            3.043418         3.044605\n",
+       " 369119  2.702502 -4.839780          394            3.042568         3.044605\n",
+       " 369120  2.704204 -4.839780          394            3.041697         3.044605\n",
+       " 369121  2.705906 -4.839780          394            3.040780         3.044605\n",
+       " 369122  2.707608 -4.839780          394            3.039862         3.044605\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 369885  4.006006 -4.844961          394            0.000084         3.044605\n",
+       " 369886  4.007708 -4.845278          394            0.000074         3.044605\n",
+       " 369887  4.009409 -4.845596          394            0.000065         3.044605\n",
+       " 369888  4.011111 -4.845914          394            0.000055         3.044605\n",
+       " 369889  4.012813 -4.846232          394            0.000045         3.044605\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 370118  2.700801 -4.840001          395            3.042683          3.04437\n",
+       " 370119  2.702502 -4.839926          395            3.041792          3.04437\n",
+       " 370120  2.704204 -4.839851          395            3.040901          3.04437\n",
+       " 370121  2.705906 -4.839780          395            3.040009          3.04437\n",
+       " 370122  2.707608 -4.839780          395            3.039092          3.04437\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 370885  4.006006 -4.844538          395            0.000085          3.04437\n",
+       " 370886  4.007708 -4.844793          395            0.000075          3.04437\n",
+       " 370887  4.009409 -4.845048          395            0.000065          3.04437\n",
+       " 370888  4.011111 -4.845304          395            0.000056          3.04437\n",
+       " 370889  4.012813 -4.845559          395            0.000046          3.04437\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 371118  2.700801 -4.839950          396            3.042231         3.043969\n",
+       " 371119  2.702502 -4.839946          396            3.041368         3.043969\n",
+       " 371120  2.704204 -4.839871          396            3.040504         3.043969\n",
+       " 371121  2.705906 -4.839796          396            3.039640         3.043969\n",
+       " 371122  2.707608 -4.839841          396            3.038704         3.043969\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 371885  4.006006 -4.843434          396            0.000083         3.043969\n",
+       " 371886  4.007708 -4.843640          396            0.000073         3.043969\n",
+       " 371887  4.009409 -4.843845          396            0.000064         3.043969\n",
+       " 371888  4.011111 -4.844051          396            0.000054         3.043969\n",
+       " 371889  4.012813 -4.844256          396            0.000045         3.043969\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 372118  2.700801 -4.839662          397            3.042359          3.04349\n",
+       " 372119  2.702502 -4.839551          397            3.041462          3.04349\n",
+       " 372120  2.704204 -4.839551          397            3.040567          3.04349\n",
+       " 372121  2.705906 -4.839551          397            3.039672          3.04349\n",
+       " 372122  2.707608 -4.839590          397            3.038759          3.04349\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 372885  4.006006 -4.842308          397            0.000085          3.04349\n",
+       " 372886  4.007708 -4.842450          397            0.000076          3.04349\n",
+       " 372887  4.009409 -4.842592          397            0.000066          3.04349\n",
+       " 372888  4.011111 -4.842734          397            0.000057          3.04349\n",
+       " 372889  4.012813 -4.842876          397            0.000047          3.04349\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 373118  2.700801 -4.839780          398            3.040882         3.042144\n",
+       " 373119  2.702502 -4.839780          398            3.040044         3.042144\n",
+       " 373120  2.704204 -4.839780          398            3.039167         3.042144\n",
+       " 373121  2.705906 -4.839780          398            3.038249         3.042144\n",
+       " 373122  2.707608 -4.839780          398            3.037332         3.042144\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 373885  4.006006 -4.843462          398            0.000084         3.042144\n",
+       " 373886  4.007708 -4.843655          398            0.000074         3.042144\n",
+       " 373887  4.009409 -4.843849          398            0.000065         3.042144\n",
+       " 373888  4.011111 -4.844042          398            0.000055         3.042144\n",
+       " 373889  4.012813 -4.844236          398            0.000046         3.042144\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 374118  2.700801 -4.840184          399            3.039085          3.04039\n",
+       " 374119  2.702502 -4.839962          399            3.038212          3.04039\n",
+       " 374120  2.704204 -4.839740          399            3.037338          3.04039\n",
+       " 374121  2.705906 -4.839574          399            3.036459          3.04039\n",
+       " 374122  2.707608 -4.839726          399            3.035546          3.04039\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 374885  4.006006 -4.842154          399            0.000084          3.04039\n",
+       " 374886  4.007708 -4.842235          399            0.000074          3.04039\n",
+       " 374887  4.009409 -4.842317          399            0.000064          3.04039\n",
+       " 374888  4.011111 -4.842398          399            0.000055          3.04039\n",
+       " 374889  4.012813 -4.842479          399            0.000045          3.04039\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 375118  2.700801 -4.840009          400            3.037347         3.039241\n",
+       " 375119  2.702502 -4.839960          400            3.036461         3.039241\n",
+       " 375120  2.704204 -4.839885          400            3.035566         3.039241\n",
+       " 375121  2.705906 -4.839809          400            3.034671         3.039241\n",
+       " 375122  2.707608 -4.839826          400            3.033765         3.039241\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 375885  4.006006 -4.844829          400            0.000084         3.039241\n",
+       " 375886  4.007708 -4.845125          400            0.000074         3.039241\n",
+       " 375887  4.009409 -4.845422          400            0.000065         3.039241\n",
+       " 375888  4.011111 -4.845718          400            0.000055         3.039241\n",
+       " 375889  4.012813 -4.846015          400            0.000045         3.039241\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 376118  2.700801 -4.839929          401            3.036192         3.036879\n",
+       " 376119  2.702502 -4.840009          401            3.035332         3.036879\n",
+       " 376120  2.704204 -4.840009          401            3.034455         3.036879\n",
+       " 376121  2.705906 -4.840009          401            3.033578         3.036879\n",
+       " 376122  2.707608 -4.840066          401            3.032654         3.036879\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 376885  4.006006 -4.842997          401            0.000084         3.036879\n",
+       " 376886  4.007708 -4.843192          401            0.000075         3.036879\n",
+       " 376887  4.009409 -4.843387          401            0.000065         3.036879\n",
+       " 376888  4.011111 -4.843582          401            0.000055         3.036879\n",
+       " 376889  4.012813 -4.843777          401            0.000046         3.036879\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 377118  2.700801 -4.839645          402            3.035014         3.036068\n",
+       " 377119  2.702502 -4.839845          402            3.034132         3.036068\n",
+       " 377120  2.704204 -4.840009          402            3.033243         3.036068\n",
+       " 377121  2.705906 -4.840009          402            3.032326         3.036068\n",
+       " 377122  2.707608 -4.840009          402            3.031409         3.036068\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 377885  4.006006 -4.842327          402            0.000087         3.036068\n",
+       " 377886  4.007708 -4.842461          402            0.000078         3.036068\n",
+       " 377887  4.009409 -4.842595          402            0.000068         3.036068\n",
+       " 377888  4.011111 -4.842730          402            0.000058         3.036068\n",
+       " 377889  4.012813 -4.842864          402            0.000048         3.036068\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 378118  2.700801 -4.840044          403            3.031535         3.033226\n",
+       " 378119  2.702502 -4.840043          403            3.030635         3.033226\n",
+       " 378120  2.704204 -4.839747          403            3.029753         3.033226\n",
+       " 378121  2.705906 -4.839451          403            3.028871         3.033226\n",
+       " 378122  2.707608 -4.839448          403            3.027969         3.033226\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 378885  4.006006 -4.841958          403            0.000084         3.033226\n",
+       " 378886  4.007708 -4.842083          403            0.000075         3.033226\n",
+       " 378887  4.009409 -4.842206          403            0.000065         3.033226\n",
+       " 378888  4.011111 -4.842330          403            0.000055         3.033226\n",
+       " 378889  4.012813 -4.842454          403            0.000045         3.033226\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 379118  2.700801 -4.839833          404            3.029199         3.030294\n",
+       " 379119  2.702502 -4.839571          404            3.028330         3.030294\n",
+       " 379120  2.704204 -4.839647          404            3.027453         3.030294\n",
+       " 379121  2.705906 -4.839723          404            3.026576         3.030294\n",
+       " 379122  2.707608 -4.839761          404            3.025683         3.030294\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 379885  4.006006 -4.845087          404            0.000083         3.030294\n",
+       " 379886  4.007708 -4.845386          404            0.000073         3.030294\n",
+       " 379887  4.009409 -4.845685          404            0.000063         3.030294\n",
+       " 379888  4.011111 -4.845984          404            0.000054         3.030294\n",
+       " 379889  4.012813 -4.846283          404            0.000044         3.030294\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 380118  2.700801 -4.839826          405            3.027993          3.02896\n",
+       " 380119  2.702502 -4.839924          405            3.027105          3.02896\n",
+       " 380120  2.704204 -4.839979          405            3.026215          3.02896\n",
+       " 380121  2.705906 -4.839754          405            3.025316          3.02896\n",
+       " 380122  2.707608 -4.839529          405            3.024416          3.02896\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 380885  4.006006 -4.843853          405            0.000083          3.02896\n",
+       " 380886  4.007708 -4.844068          405            0.000073          3.02896\n",
+       " 380887  4.009409 -4.844282          405            0.000064          3.02896\n",
+       " 380888  4.011111 -4.844496          405            0.000054          3.02896\n",
+       " 380889  4.012813 -4.844709          405            0.000044          3.02896\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 381118  2.700801 -4.840467          406            3.028139         3.028735\n",
+       " 381119  2.702502 -4.840467          406            3.027257         3.028735\n",
+       " 381120  2.704204 -4.840467          406            3.026375         3.028735\n",
+       " 381121  2.705906 -4.840434          406            3.025490         3.028735\n",
+       " 381122  2.707608 -4.840212          406            3.024586         3.028735\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 381885  4.006006 -4.843646          406            0.000082         3.028735\n",
+       " 381886  4.007708 -4.843862          406            0.000072         3.028735\n",
+       " 381887  4.009409 -4.844078          406            0.000063         3.028735\n",
+       " 381888  4.011111 -4.844293          406            0.000053         3.028735\n",
+       " 381889  4.012813 -4.844509          406            0.000043         3.028735\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 382118  2.700801 -4.839780          407            3.025968         3.027217\n",
+       " 382119  2.702502 -4.839722          407            3.025098         3.027217\n",
+       " 382120  2.704204 -4.839648          407            3.024216         3.027217\n",
+       " 382121  2.705906 -4.839574          407            3.023334         3.027217\n",
+       " 382122  2.707608 -4.839604          407            3.022427         3.027217\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 382885  4.006006 -4.843450          407            0.000080         3.027217\n",
+       " 382886  4.007708 -4.843665          407            0.000071         3.027217\n",
+       " 382887  4.009409 -4.843880          407            0.000061         3.027217\n",
+       " 382888  4.011111 -4.844094          407            0.000052         3.027217\n",
+       " 382889  4.012813 -4.844309          407            0.000042         3.027217\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 383118  2.700801 -4.840384          408            3.026245         3.026357\n",
+       " 383119  2.702502 -4.840161          408            3.025358         3.026357\n",
+       " 383120  2.704204 -4.839940          408            3.024472         3.026357\n",
+       " 383121  2.705906 -4.839738          408            3.023582         3.026357\n",
+       " 383122  2.707608 -4.839588          408            3.022687         3.026357\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 383885  4.006006 -4.845280          408            0.000081         3.026357\n",
+       " 383886  4.007708 -4.845593          408            0.000072         3.026357\n",
+       " 383887  4.009409 -4.845907          408            0.000062         3.026357\n",
+       " 383888  4.011111 -4.846220          408            0.000053         3.026357\n",
+       " 383889  4.012813 -4.846534          408            0.000043         3.026357\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 384118  2.700801 -4.839832          409            3.026450         3.026679\n",
+       " 384119  2.702502 -4.839943          409            3.025570         3.026679\n",
+       " 384120  2.704204 -4.839979          409            3.024679         3.026679\n",
+       " 384121  2.705906 -4.839905          409            3.023771         3.026679\n",
+       " 384122  2.707608 -4.839831          409            3.022862         3.026679\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 384885  4.006006 -4.844301          409            0.000079         3.026679\n",
+       " 384886  4.007708 -4.844533          409            0.000070         3.026679\n",
+       " 384887  4.009409 -4.844766          409            0.000060         3.026679\n",
+       " 384888  4.011111 -4.844999          409            0.000051         3.026679\n",
+       " 384889  4.012813 -4.845231          409            0.000041         3.026679\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 385118  2.700801 -4.840115          410            3.025385         3.027078\n",
+       " 385119  2.702502 -4.839851          410            3.024527         3.027078\n",
+       " 385120  2.704204 -4.839587          410            3.023669         3.027078\n",
+       " 385121  2.705906 -4.839551          410            3.022774         3.027078\n",
+       " 385122  2.707608 -4.839551          410            3.021875         3.027078\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 385884  4.004304 -4.843352          410            0.000087         3.027078\n",
+       " 385885  4.006006 -4.843554          410            0.000077         3.027078\n",
+       " 385886  4.007708 -4.843758          410            0.000068         3.027078\n",
+       " 385887  4.009409 -4.843961          410            0.000058         3.027078\n",
+       " 385888  4.011111 -4.844163          410            0.000049         3.027078\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 386118  2.700801 -4.839780          411            3.023328         3.025073\n",
+       " 386119  2.702502 -4.839780          411            3.022470         3.025073\n",
+       " 386120  2.704204 -4.839780          411            3.021600         3.025073\n",
+       " 386121  2.705906 -4.839780          411            3.020683         3.025073\n",
+       " 386122  2.707608 -4.839780          411            3.019766         3.025073\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 386885  4.006006 -4.842952          411            0.000079         3.025073\n",
+       " 386886  4.007708 -4.843122          411            0.000070         3.025073\n",
+       " 386887  4.009409 -4.843292          411            0.000061         3.025073\n",
+       " 386888  4.011111 -4.843462          411            0.000051         3.025073\n",
+       " 386889  4.012813 -4.843633          411            0.000042         3.025073\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 387118  2.700801 -4.839867          412            3.022916         3.024336\n",
+       " 387119  2.702502 -4.840053          412            3.022038         3.024336\n",
+       " 387120  2.704204 -4.840238          412            3.021160         3.024336\n",
+       " 387121  2.705906 -4.840090          412            3.020256         3.024336\n",
+       " 387122  2.707608 -4.839942          412            3.019352         3.024336\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 387885  4.006006 -4.844845          412            0.000079         3.024336\n",
+       " 387886  4.007708 -4.845118          412            0.000069         3.024336\n",
+       " 387887  4.009409 -4.845390          412            0.000060         3.024336\n",
+       " 387888  4.011111 -4.845663          412            0.000050         3.024336\n",
+       " 387889  4.012813 -4.845935          412            0.000041         3.024336\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 388118  2.700801 -4.840009          413            3.021158          3.02286\n",
+       " 388119  2.702502 -4.840009          413            3.020289          3.02286\n",
+       " 388120  2.704204 -4.840009          413            3.019420          3.02286\n",
+       " 388121  2.705906 -4.840009          413            3.018530          3.02286\n",
+       " 388122  2.707608 -4.840009          413            3.017635          3.02286\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 388885  4.006006 -4.843574          413            0.000079          3.02286\n",
+       " 388886  4.007708 -4.843765          413            0.000069          3.02286\n",
+       " 388887  4.009409 -4.843957          413            0.000060          3.02286\n",
+       " 388888  4.011111 -4.844149          413            0.000050          3.02286\n",
+       " 388889  4.012813 -4.844340          413            0.000041          3.02286\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 389118  2.700801 -4.839978          414            3.019832         3.021609\n",
+       " 389119  2.702502 -4.839902          414            3.018946         3.021609\n",
+       " 389120  2.704204 -4.839828          414            3.018060         3.021609\n",
+       " 389121  2.705906 -4.839836          414            3.017170         3.021609\n",
+       " 389122  2.707608 -4.839983          414            3.016275         3.021609\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 389884  4.004304 -4.844473          414            0.000087         3.021609\n",
+       " 389885  4.006006 -4.844727          414            0.000077         3.021609\n",
+       " 389886  4.007708 -4.844981          414            0.000068         3.021609\n",
+       " 389887  4.009409 -4.845234          414            0.000058         3.021609\n",
+       " 389888  4.011111 -4.845488          414            0.000049         3.021609\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 390118  2.700801 -4.840009          415            3.019092         3.019999\n",
+       " 390119  2.702502 -4.840009          415            3.018202         3.019999\n",
+       " 390120  2.704204 -4.840009          415            3.017312         3.019999\n",
+       " 390121  2.705906 -4.840112          415            3.016418         3.019999\n",
+       " 390122  2.707608 -4.840262          415            3.015523         3.019999\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 390885  4.006006 -4.845006          415            0.000079         3.019999\n",
+       " 390886  4.007708 -4.845288          415            0.000070         3.019999\n",
+       " 390887  4.009409 -4.845572          415            0.000060         3.019999\n",
+       " 390888  4.011111 -4.845854          415            0.000051         3.019999\n",
+       " 390889  4.012813 -4.846138          415            0.000041         3.019999\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 391118  2.700801 -4.840119          416            3.018234         3.020013\n",
+       " 391119  2.702502 -4.839966          416            3.017359         3.020013\n",
+       " 391120  2.704204 -4.839890          416            3.016490         3.020013\n",
+       " 391121  2.705906 -4.839813          416            3.015622         3.020013\n",
+       " 391122  2.707608 -4.839823          416            3.014716         3.020013\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 391885  4.006006 -4.843689          416            0.000080         3.020013\n",
+       " 391886  4.007708 -4.843902          416            0.000070         3.020013\n",
+       " 391887  4.009409 -4.844114          416            0.000061         3.020013\n",
+       " 391888  4.011111 -4.844326          416            0.000051         3.020013\n",
+       " 391889  4.012813 -4.844539          416            0.000042         3.020013\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 392118  2.700801 -4.840009          417            3.016553          3.01809\n",
+       " 392119  2.702502 -4.840009          417            3.015666          3.01809\n",
+       " 392120  2.704204 -4.840009          417            3.014780          3.01809\n",
+       " 392121  2.705906 -4.840041          417            3.013879          3.01809\n",
+       " 392122  2.707608 -4.840116          417            3.012957          3.01809\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 392885  4.006006 -4.843901          417            0.000081          3.01809\n",
+       " 392886  4.007708 -4.844113          417            0.000071          3.01809\n",
+       " 392887  4.009409 -4.844325          417            0.000062          3.01809\n",
+       " 392888  4.011111 -4.844537          417            0.000052          3.01809\n",
+       " 392889  4.012813 -4.844748          417            0.000043          3.01809\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 393118  2.700801 -4.839967          418            3.015509         3.016753\n",
+       " 393119  2.702502 -4.839876          418            3.014663         3.016753\n",
+       " 393120  2.704204 -4.839785          418            3.013817         3.016753\n",
+       " 393121  2.705906 -4.839710          418            3.012928         3.016753\n",
+       " 393122  2.707608 -4.839636          418            3.012037         3.016753\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 393885  4.006006 -4.844697          418            0.000080         3.016753\n",
+       " 393886  4.007708 -4.844936          418            0.000071         3.016753\n",
+       " 393887  4.009409 -4.845176          418            0.000061         3.016753\n",
+       " 393888  4.011111 -4.845416          418            0.000052         3.016753\n",
+       " 393889  4.012813 -4.845655          418            0.000043         3.016753\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 394118  2.700801 -4.839410          419            3.015672         3.016373\n",
+       " 394119  2.702502 -4.839715          419            3.014773         3.016373\n",
+       " 394120  2.704204 -4.840020          419            3.013873         3.016373\n",
+       " 394121  2.705906 -4.840174          419            3.012979         3.016373\n",
+       " 394122  2.707608 -4.839949          419            3.012097         3.016373\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 394885  4.006006 -4.842381          419            0.000080         3.016373\n",
+       " 394886  4.007708 -4.842523          419            0.000071         3.016373\n",
+       " 394887  4.009409 -4.842664          419            0.000061         3.016373\n",
+       " 394888  4.011111 -4.842805          419            0.000052         3.016373\n",
+       " 394889  4.012813 -4.842947          419            0.000042         3.016373\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 395118  2.700801 -4.839841          420            3.015344         3.016394\n",
+       " 395119  2.702502 -4.839850          420            3.014471         3.016394\n",
+       " 395120  2.704204 -4.839925          420            3.013593         3.016394\n",
+       " 395121  2.705906 -4.840000          420            3.012716         3.016394\n",
+       " 395122  2.707608 -4.839943          420            3.011799         3.016394\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 395885  4.006006 -4.844522          420            0.000080         3.016394\n",
+       " 395886  4.007708 -4.844754          420            0.000070         3.016394\n",
+       " 395887  4.009409 -4.844985          420            0.000061         3.016394\n",
+       " 395888  4.011111 -4.845218          420            0.000051         3.016394\n",
+       " 395889  4.012813 -4.845450          420            0.000042         3.016394\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 396118  2.700801 -4.840153          421            3.015979         3.016259\n",
+       " 396119  2.702502 -4.839971          421            3.015074         3.016259\n",
+       " 396120  2.704204 -4.839788          421            3.014169         3.016259\n",
+       " 396121  2.705906 -4.839712          421            3.013306         3.016259\n",
+       " 396122  2.707608 -4.839640          421            3.012444         3.016259\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 396885  4.006006 -4.842272          421            0.000081         3.016259\n",
+       " 396886  4.007708 -4.842381          421            0.000072         3.016259\n",
+       " 396887  4.009409 -4.842491          421            0.000062         3.016259\n",
+       " 396888  4.011111 -4.842601          421            0.000053         3.016259\n",
+       " 396889  4.012813 -4.842711          421            0.000044         3.016259\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 397118  2.700801 -4.840127          422            3.014952         3.016268\n",
+       " 397119  2.702502 -4.839910          422            3.014116         3.016268\n",
+       " 397120  2.704204 -4.839780          422            3.013248         3.016268\n",
+       " 397121  2.705906 -4.839780          422            3.012331         3.016268\n",
+       " 397122  2.707608 -4.839780          422            3.011413         3.016268\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 397885  4.006006 -4.844045          422            0.000081         3.016268\n",
+       " 397886  4.007708 -4.844276          422            0.000071         3.016268\n",
+       " 397887  4.009409 -4.844508          422            0.000062         3.016268\n",
+       " 397888  4.011111 -4.844740          422            0.000052         3.016268\n",
+       " 397889  4.012813 -4.844971          422            0.000043         3.016268\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 398118  2.700801 -4.840066          423            3.014839         3.016124\n",
+       " 398119  2.702502 -4.840188          423            3.013968         3.016124\n",
+       " 398120  2.704204 -4.840109          423            3.013077         3.016124\n",
+       " 398121  2.705906 -4.839887          423            3.012173         3.016124\n",
+       " 398122  2.707608 -4.839665          423            3.011270         3.016124\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 398885  4.006006 -4.842983          423            0.000080         3.016124\n",
+       " 398886  4.007708 -4.843144          423            0.000071         3.016124\n",
+       " 398887  4.009409 -4.843305          423            0.000061         3.016124\n",
+       " 398888  4.011111 -4.843466          423            0.000052         3.016124\n",
+       " 398889  4.012813 -4.843627          423            0.000042         3.016124\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 399118  2.700801 -4.839972          424            3.016221         3.016969\n",
+       " 399119  2.702502 -4.839894          424            3.015344         3.016969\n",
+       " 399120  2.704204 -4.839816          424            3.014468         3.016969\n",
+       " 399121  2.705906 -4.839739          424            3.013583         3.016969\n",
+       " 399122  2.707608 -4.839664          424            3.012693         3.016969\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 399885  4.006006 -4.844409          424            0.000083         3.016969\n",
+       " 399886  4.007708 -4.844648          424            0.000073         3.016969\n",
+       " 399887  4.009409 -4.844886          424            0.000064         3.016969\n",
+       " 399888  4.011111 -4.845124          424            0.000055         3.016969\n",
+       " 399889  4.012813 -4.845363          424            0.000045         3.016969\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 400118  2.700801 -4.839821          425            3.016452         3.017772\n",
+       " 400119  2.702502 -4.839910          425            3.015553         3.017772\n",
+       " 400120  2.704204 -4.839997          425            3.014653         3.017772\n",
+       " 400121  2.705906 -4.840009          425            3.013765         3.017772\n",
+       " 400122  2.707608 -4.840009          425            3.012878         3.017772\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 400885  4.006006 -4.845707          425            0.000082         3.017772\n",
+       " 400886  4.007708 -4.846018          425            0.000073         3.017772\n",
+       " 400887  4.009409 -4.846329          425            0.000063         3.017772\n",
+       " 400888  4.011111 -4.846640          425            0.000054         3.017772\n",
+       " 400889  4.012813 -4.846951          425            0.000044         3.017772\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 401118  2.700801 -4.840148          426            3.016605         3.017597\n",
+       " 401119  2.702502 -4.839956          426            3.015717         3.017597\n",
+       " 401120  2.704204 -4.839787          426            3.014827         3.017597\n",
+       " 401121  2.705906 -4.839862          426            3.013918         3.017597\n",
+       " 401122  2.707608 -4.839937          426            3.013010         3.017597\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 401885  4.006006 -4.843347          426            0.000083         3.017597\n",
+       " 401886  4.007708 -4.843516          426            0.000074         3.017597\n",
+       " 401887  4.009409 -4.843685          426            0.000064         3.017597\n",
+       " 401888  4.011111 -4.843854          426            0.000055         3.017597\n",
+       " 401889  4.012813 -4.844023          426            0.000046         3.017597\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 402118  2.700801 -4.839878          427            3.016959         3.017255\n",
+       " 402119  2.702502 -4.840086          427            3.016109         3.017255\n",
+       " 402120  2.704204 -4.840198          427            3.015236         3.017255\n",
+       " 402121  2.705906 -4.840047          427            3.014306         3.017255\n",
+       " 402122  2.707608 -4.839897          427            3.013376         3.017255\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 402885  4.006006 -4.843100          427            0.000082         3.017255\n",
+       " 402886  4.007708 -4.843280          427            0.000072         3.017255\n",
+       " 402887  4.009409 -4.843460          427            0.000063         3.017255\n",
+       " 402888  4.011111 -4.843639          427            0.000053         3.017255\n",
+       " 402889  4.012813 -4.843819          427            0.000044         3.017255\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 403118  2.700801 -4.840009          428            3.014745         3.016573\n",
+       " 403119  2.702502 -4.840009          428            3.013845         3.016573\n",
+       " 403120  2.704204 -4.840009          428            3.012945         3.016573\n",
+       " 403121  2.705906 -4.839950          428            3.012063         3.016573\n",
+       " 403122  2.707608 -4.839878          428            3.011185         3.016573\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 403885  4.006006 -4.844256          428            0.000083         3.016573\n",
+       " 403886  4.007708 -4.844525          428            0.000074         3.016573\n",
+       " 403887  4.009409 -4.844794          428            0.000064         3.016573\n",
+       " 403888  4.011111 -4.845064          428            0.000055         3.016573\n",
+       " 403889  4.012813 -4.845333          428            0.000046         3.016573\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 404118  2.700801 -4.839780          429            3.014901         3.015609\n",
+       " 404119  2.702502 -4.839780          429            3.014019         3.015609\n",
+       " 404120  2.704204 -4.839800          429            3.013132         3.015609\n",
+       " 404121  2.705906 -4.839948          429            3.012219         3.015609\n",
+       " 404122  2.707608 -4.840096          429            3.011307         3.015609\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 404885  4.006006 -4.844424          429            0.000082         3.015609\n",
+       " 404886  4.007708 -4.844664          429            0.000073         3.015609\n",
+       " 404887  4.009409 -4.844904          429            0.000063         3.015609\n",
+       " 404888  4.011111 -4.845144          429            0.000054         3.015609\n",
+       " 404889  4.012813 -4.845384          429            0.000044         3.015609\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 405118  2.700801 -4.839741          430            3.014732         3.015086\n",
+       " 405119  2.702502 -4.839658          430            3.013862         3.015086\n",
+       " 405120  2.704204 -4.839574          430            3.012991         3.015086\n",
+       " 405121  2.705906 -4.839714          430            3.012116         3.015086\n",
+       " 405122  2.707608 -4.839936          430            3.011238         3.015086\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 405885  4.006006 -4.844496          430            0.000084         3.015086\n",
+       " 405886  4.007708 -4.844755          430            0.000075         3.015086\n",
+       " 405887  4.009409 -4.845015          430            0.000066         3.015086\n",
+       " 405888  4.011111 -4.845274          430            0.000056         3.015086\n",
+       " 405889  4.012813 -4.845533          430            0.000047         3.015086\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 406118  2.700801 -4.840303          431            3.012473          3.01399\n",
+       " 406119  2.702502 -4.839951          431            3.011573          3.01399\n",
+       " 406120  2.704204 -4.839599          431            3.010674          3.01399\n",
+       " 406121  2.705906 -4.839676          431            3.009803          3.01399\n",
+       " 406122  2.707608 -4.839820          431            3.008937          3.01399\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 406885  4.006006 -4.844334          431            0.000084          3.01399\n",
+       " 406886  4.007708 -4.844535          431            0.000074          3.01399\n",
+       " 406887  4.009409 -4.844736          431            0.000065          3.01399\n",
+       " 406888  4.011111 -4.844937          431            0.000056          3.01399\n",
+       " 406889  4.012813 -4.845138          431            0.000046          3.01399\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 407118  2.700801 -4.839872          432            3.010789         3.012333\n",
+       " 407119  2.702502 -4.839913          432            3.009908         3.012333\n",
+       " 407120  2.704204 -4.840063          432            3.009026         3.012333\n",
+       " 407121  2.705906 -4.840213          432            3.008144         3.012333\n",
+       " 407122  2.707608 -4.840050          432            3.007236         3.012333\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 407885  4.006006 -4.844373          432            0.000085         3.012333\n",
+       " 407886  4.007708 -4.844655          432            0.000076         3.012333\n",
+       " 407887  4.009409 -4.844937          432            0.000066         3.012333\n",
+       " 407888  4.011111 -4.845220          432            0.000057         3.012333\n",
+       " 407889  4.012813 -4.845502          432            0.000047         3.012333\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 408118  2.700801 -4.840014          433            3.008213         3.009584\n",
+       " 408119  2.702502 -4.840089          433            3.007339         3.009584\n",
+       " 408120  2.704204 -4.840164          433            3.006466         3.009584\n",
+       " 408121  2.705906 -4.840237          433            3.005593         3.009584\n",
+       " 408122  2.707608 -4.840162          433            3.004689         3.009584\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 408885  4.006006 -4.844270          433            0.000083         3.009584\n",
+       " 408886  4.007708 -4.844544          433            0.000073         3.009584\n",
+       " 408887  4.009409 -4.844819          433            0.000064         3.009584\n",
+       " 408888  4.011111 -4.845092          433            0.000054         3.009584\n",
+       " 408889  4.012813 -4.845366          433            0.000044         3.009584\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 409118  2.700801 -4.840009          434            3.007472         3.008294\n",
+       " 409119  2.702502 -4.840009          434            3.006598         3.008294\n",
+       " 409120  2.704204 -4.840009          434            3.005725         3.008294\n",
+       " 409121  2.705906 -4.840009          434            3.004851         3.008294\n",
+       " 409122  2.707608 -4.839939          434            3.003933         3.008294\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 409885  4.006006 -4.843071          434            0.000083         3.008294\n",
+       " 409886  4.007708 -4.843252          434            0.000074         3.008294\n",
+       " 409887  4.009409 -4.843432          434            0.000064         3.008294\n",
+       " 409888  4.011111 -4.843614          434            0.000055         3.008294\n",
+       " 409889  4.012813 -4.843794          434            0.000045         3.008294\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 410118  2.700801 -4.840053          435            3.007280         3.007124\n",
+       " 410119  2.702502 -4.840148          435            3.006430         3.007124\n",
+       " 410120  2.704204 -4.840228          435            3.005578         3.007124\n",
+       " 410121  2.705906 -4.839999          435            3.004678         3.007124\n",
+       " 410122  2.707608 -4.839771          435            3.003779         3.007124\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 410885  4.006006 -4.844855          435            0.000082         3.007124\n",
+       " 410886  4.007708 -4.845158          435            0.000072         3.007124\n",
+       " 410887  4.009409 -4.845461          435            0.000063         3.007124\n",
+       " 410888  4.011111 -4.845763          435            0.000053         3.007124\n",
+       " 410889  4.012813 -4.846066          435            0.000044         3.007124\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 411118  2.700801 -4.840009          436            3.005873         3.007377\n",
+       " 411119  2.702502 -4.840009          436            3.005004         3.007377\n",
+       " 411120  2.704204 -4.840009          436            3.004135         3.007377\n",
+       " 411121  2.705906 -4.840009          436            3.003264         3.007377\n",
+       " 411122  2.707608 -4.840009          436            3.002391         3.007377\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 411885  4.006006 -4.842928          436            0.000081         3.007377\n",
+       " 411886  4.007708 -4.843098          436            0.000071         3.007377\n",
+       " 411887  4.009409 -4.843269          436            0.000062         3.007377\n",
+       " 411888  4.011111 -4.843439          436            0.000053         3.007377\n",
+       " 411889  4.012813 -4.843610          436            0.000043         3.007377\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 412118  2.700801 -4.839872          437            3.004452         3.005103\n",
+       " 412119  2.702502 -4.840068          437            3.003564         3.005103\n",
+       " 412120  2.704204 -4.840218          437            3.002674         3.005103\n",
+       " 412121  2.705906 -4.840068          437            3.001770         3.005103\n",
+       " 412122  2.707608 -4.839918          437            3.000866         3.005103\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 412885  4.006006 -4.842269          437            0.000081         3.005103\n",
+       " 412886  4.007708 -4.842379          437            0.000072         3.005103\n",
+       " 412887  4.009409 -4.842488          437            0.000063         3.005103\n",
+       " 412888  4.011111 -4.842597          437            0.000053         3.005103\n",
+       " 412889  4.012813 -4.842707          437            0.000044         3.005103\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 413118  2.700801 -4.839855          438            3.005638         3.005348\n",
+       " 413119  2.702502 -4.840009          438            3.004757         3.005348\n",
+       " 413120  2.704204 -4.840009          438            3.003866         3.005348\n",
+       " 413121  2.705906 -4.840009          438            3.002976         3.005348\n",
+       " 413122  2.707608 -4.840007          438            3.002085         3.005348\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 413885  4.006006 -4.845369          438            0.000080         3.005348\n",
+       " 413886  4.007708 -4.845668          438            0.000070         3.005348\n",
+       " 413887  4.009409 -4.845967          438            0.000061         3.005348\n",
+       " 413888  4.011111 -4.846266          438            0.000052         3.005348\n",
+       " 413889  4.012813 -4.846566          438            0.000042         3.005348\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 414118  2.700801 -4.840006          439            3.007243         3.006239\n",
+       " 414119  2.702502 -4.839508          439            3.006373         3.006239\n",
+       " 414120  2.704204 -4.839416          439            3.005490         3.006239\n",
+       " 414121  2.705906 -4.839563          439            3.004599         3.006239\n",
+       " 414122  2.707608 -4.839711          439            3.003708         3.006239\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 414885  4.006006 -4.843772          439            0.000080         3.006239\n",
+       " 414886  4.007708 -4.843961          439            0.000071         3.006239\n",
+       " 414887  4.009409 -4.844150          439            0.000061         3.006239\n",
+       " 414888  4.011111 -4.844338          439            0.000052         3.006239\n",
+       " 414889  4.012813 -4.844527          439            0.000043         3.006239\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 415118  2.700801 -4.839489          440            3.006923         3.008171\n",
+       " 415119  2.702502 -4.839845          440            3.006058         3.008171\n",
+       " 415120  2.704204 -4.840009          440            3.005182         3.008171\n",
+       " 415121  2.705906 -4.840009          440            3.004295         3.008171\n",
+       " 415122  2.707608 -4.840009          440            3.003409         3.008171\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 415885  4.006006 -4.844455          440            0.000079         3.008171\n",
+       " 415886  4.007708 -4.844703          440            0.000070         3.008171\n",
+       " 415887  4.009409 -4.844951          440            0.000060         3.008171\n",
+       " 415888  4.011111 -4.845198          440            0.000051         3.008171\n",
+       " 415889  4.012813 -4.845446          440            0.000042         3.008171\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 416118  2.700801 -4.839856          441            3.006450         3.007624\n",
+       " 416119  2.702502 -4.839563          441            3.005578         3.007624\n",
+       " 416120  2.704204 -4.839713          441            3.004692         3.007624\n",
+       " 416121  2.705906 -4.839863          441            3.003805         3.007624\n",
+       " 416122  2.707608 -4.840005          441            3.002919         3.007624\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 416885  4.006006 -4.844492          441            0.000079         3.007624\n",
+       " 416886  4.007708 -4.844728          441            0.000070         3.007624\n",
+       " 416887  4.009409 -4.844965          441            0.000061         3.007624\n",
+       " 416888  4.011111 -4.845201          441            0.000052         3.007624\n",
+       " 416889  4.012813 -4.845438          441            0.000042         3.007624\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 417118  2.700801 -4.840342          442            3.004744         3.006506\n",
+       " 417119  2.702502 -4.840073          442            3.003875         3.006506\n",
+       " 417120  2.704204 -4.840009          442            3.003010         3.006506\n",
+       " 417121  2.705906 -4.840009          442            3.002144         3.006506\n",
+       " 417122  2.707608 -4.840009          442            3.001279         3.006506\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 417885  4.006006 -4.844665          442            0.000080         3.006506\n",
+       " 417886  4.007708 -4.844909          442            0.000071         3.006506\n",
+       " 417887  4.009409 -4.845154          442            0.000061         3.006506\n",
+       " 417888  4.011111 -4.845398          442            0.000052         3.006506\n",
+       " 417889  4.012813 -4.845643          442            0.000043         3.006506\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 418118  2.700801 -4.840009          443            3.004736         3.005618\n",
+       " 418119  2.702502 -4.840009          443            3.003852         3.005618\n",
+       " 418120  2.704204 -4.839956          443            3.002972         3.005618\n",
+       " 418121  2.705906 -4.839882          443            3.002094         3.005618\n",
+       " 418122  2.707608 -4.839808          443            3.001216         3.005618\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 418885  4.006006 -4.844518          443            0.000078         3.005618\n",
+       " 418886  4.007708 -4.844756          443            0.000069         3.005618\n",
+       " 418887  4.009409 -4.844994          443            0.000060         3.005618\n",
+       " 418888  4.011111 -4.845232          443            0.000050         3.005618\n",
+       " 418889  4.012813 -4.845470          443            0.000041         3.005618\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 419118  2.700801 -4.839843          444            3.003729         3.005359\n",
+       " 419119  2.702502 -4.839977          444            3.002877         3.005359\n",
+       " 419120  2.704204 -4.839953          444            3.001998         3.005359\n",
+       " 419121  2.705906 -4.839879          444            3.001112         3.005359\n",
+       " 419122  2.707608 -4.839805          444            3.000225         3.005359\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 419885  4.006006 -4.844450          444            0.000081         3.005359\n",
+       " 419886  4.007708 -4.844686          444            0.000072         3.005359\n",
+       " 419887  4.009409 -4.844923          444            0.000062         3.005359\n",
+       " 419888  4.011111 -4.845159          444            0.000053         3.005359\n",
+       " 419889  4.012813 -4.845396          444            0.000044         3.005359\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 420118  2.700801 -4.840158          445            3.003846         3.004479\n",
+       " 420119  2.702502 -4.840458          445            3.002929         3.004479\n",
+       " 420120  2.704204 -4.840170          445            3.002051         3.004479\n",
+       " 420121  2.705906 -4.839883          445            3.001172         3.004479\n",
+       " 420122  2.707608 -4.839595          445            3.000294         3.004479\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 420885  4.006006 -4.842758          445            0.000080         3.004479\n",
+       " 420886  4.007708 -4.842916          445            0.000071         3.004479\n",
+       " 420887  4.009409 -4.843075          445            0.000061         3.004479\n",
+       " 420888  4.011111 -4.843234          445            0.000052         3.004479\n",
+       " 420889  4.012813 -4.843392          445            0.000043         3.004479\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 421118  2.700801 -4.840009          446            3.001460         3.003999\n",
+       " 421119  2.702502 -4.840009          446            3.000615         3.003999\n",
+       " 421120  2.704204 -4.840009          446            2.999734         3.003999\n",
+       " 421121  2.705906 -4.840009          446            2.998852         3.003999\n",
+       " 421122  2.707608 -4.840009          446            2.997970         3.003999\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 421885  4.006006 -4.845701          446            0.000081         3.003999\n",
+       " 421886  4.007708 -4.846016          446            0.000072         3.003999\n",
+       " 421887  4.009409 -4.846332          446            0.000062         3.003999\n",
+       " 421888  4.011111 -4.846647          446            0.000053         3.003999\n",
+       " 421889  4.012813 -4.846962          446            0.000044         3.003999\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 422118  2.700801 -4.840094          447            3.000238         3.001607\n",
+       " 422119  2.702502 -4.840254          447            2.999411         3.001607\n",
+       " 422120  2.704204 -4.840329          447            2.998533         3.001607\n",
+       " 422121  2.705906 -4.840404          447            2.997656         3.001607\n",
+       " 422122  2.707608 -4.840406          447            2.996771         3.001607\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 422885  4.006006 -4.843698          447            0.000080         3.001607\n",
+       " 422886  4.007708 -4.843906          447            0.000070         3.001607\n",
+       " 422887  4.009409 -4.844114          447            0.000061         3.001607\n",
+       " 422888  4.011111 -4.844322          447            0.000052         3.001607\n",
+       " 422889  4.012813 -4.844530          447            0.000042         3.001607\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 423118  2.700801 -4.840189          448            2.998585         3.000347\n",
+       " 423119  2.702502 -4.840082          448            2.997685         3.000347\n",
+       " 423120  2.704204 -4.840055          448            2.996787         3.000347\n",
+       " 423121  2.705906 -4.840204          448            2.995892         3.000347\n",
+       " 423122  2.707608 -4.840352          448            2.994996         3.000347\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 423885  4.006006 -4.844989          448            0.000079         3.000347\n",
+       " 423886  4.007708 -4.845276          448            0.000069         3.000347\n",
+       " 423887  4.009409 -4.845563          448            0.000060         3.000347\n",
+       " 423888  4.011111 -4.845850          448            0.000051         3.000347\n",
+       " 423889  4.012813 -4.846137          448            0.000041         3.000347\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 424118  2.700801 -4.840009          449            2.997905         2.998865\n",
+       " 424119  2.702502 -4.840074          449            2.997032         2.998865\n",
+       " 424120  2.704204 -4.840221          449            2.996176         2.998865\n",
+       " 424121  2.705906 -4.840370          449            2.995320         2.998865\n",
+       " 424122  2.707608 -4.840389          449            2.994432         2.998865\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 424885  4.006006 -4.841655          449            0.000079         2.998865\n",
+       " 424886  4.007708 -4.841754          449            0.000069         2.998865\n",
+       " 424887  4.009409 -4.841853          449            0.000060         2.998865\n",
+       " 424888  4.011111 -4.841952          449            0.000051         2.998865\n",
+       " 424889  4.012813 -4.842051          449            0.000041         2.998865\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 425118  2.700801 -4.840009          450            2.997379         2.998143\n",
+       " 425119  2.702502 -4.840009          450            2.996518         2.998143\n",
+       " 425120  2.704204 -4.840009          450            2.995623         2.998143\n",
+       " 425121  2.705906 -4.840009          450            2.994715         2.998143\n",
+       " 425122  2.707608 -4.840009          450            2.993806         2.998143\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 425885  4.006006 -4.843560          450            0.000079         2.998143\n",
+       " 425886  4.007708 -4.843747          450            0.000070         2.998143\n",
+       " 425887  4.009409 -4.843934          450            0.000061         2.998143\n",
+       " 425888  4.011111 -4.844121          450            0.000051         2.998143\n",
+       " 425889  4.012813 -4.844307          450            0.000042         2.998143\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 426118  2.700801 -4.840065          451            2.998425         2.998816\n",
+       " 426119  2.702502 -4.839694          451            2.997558         2.998816\n",
+       " 426120  2.704204 -4.839323          451            2.996691         2.998816\n",
+       " 426121  2.705906 -4.839623          451            2.995792         2.998816\n",
+       " 426122  2.707608 -4.839923          451            2.994892         2.998816\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 426885  4.006006 -4.844931          451            0.000082         2.998816\n",
+       " 426886  4.007708 -4.845205          451            0.000073         2.998816\n",
+       " 426887  4.009409 -4.845479          451            0.000064         2.998816\n",
+       " 426888  4.011111 -4.845754          451            0.000054         2.998816\n",
+       " 426889  4.012813 -4.846028          451            0.000045         2.998816\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 427118  2.700801 -4.840058          452            2.998343          2.99852\n",
+       " 427119  2.702502 -4.840162          452            2.997443          2.99852\n",
+       " 427120  2.704204 -4.840218          452            2.996545          2.99852\n",
+       " 427121  2.705906 -4.840144          452            2.995650          2.99852\n",
+       " 427122  2.707608 -4.840070          452            2.994754          2.99852\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 427885  4.006006 -4.842751          452            0.000080          2.99852\n",
+       " 427886  4.007708 -4.842907          452            0.000071          2.99852\n",
+       " 427887  4.009409 -4.843064          452            0.000062          2.99852\n",
+       " 427888  4.011111 -4.843222          452            0.000053          2.99852\n",
+       " 427889  4.012813 -4.843379          452            0.000043          2.99852\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 428118  2.700801 -4.840160          453            2.998580         2.999792\n",
+       " 428119  2.702502 -4.839557          453            2.997673         2.999792\n",
+       " 428120  2.704204 -4.839630          453            2.996786         2.999792\n",
+       " 428121  2.705906 -4.839703          453            2.995899         2.999792\n",
+       " 428122  2.707608 -4.839776          453            2.995013         2.999792\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 428885  4.006006 -4.843207          453            0.000080         2.999792\n",
+       " 428886  4.007708 -4.843364          453            0.000071         2.999792\n",
+       " 428887  4.009409 -4.843522          453            0.000062         2.999792\n",
+       " 428888  4.011111 -4.843679          453            0.000053         2.999792\n",
+       " 428889  4.012813 -4.843836          453            0.000043         2.999792\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 429118  2.700801 -4.839845          454            2.998364         2.998732\n",
+       " 429119  2.702502 -4.839983          454            2.997481         2.998732\n",
+       " 429120  2.704204 -4.839950          454            2.996595         2.998732\n",
+       " 429121  2.705906 -4.839876          454            2.995708         2.998732\n",
+       " 429122  2.707608 -4.839801          454            2.994822         2.998732\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 429885  4.006006 -4.844917          454            0.000081         2.998732\n",
+       " 429886  4.007708 -4.845203          454            0.000072         2.998732\n",
+       " 429887  4.009409 -4.845489          454            0.000062         2.998732\n",
+       " 429888  4.011111 -4.845774          454            0.000053         2.998732\n",
+       " 429889  4.012813 -4.846060          454            0.000044         2.998732\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 430118  2.700801 -4.839780          455            2.998486         2.999449\n",
+       " 430119  2.702502 -4.839780          455            2.997604         2.999449\n",
+       " 430120  2.704204 -4.839856          455            2.996723         2.999449\n",
+       " 430121  2.705906 -4.839931          455            2.995841         2.999449\n",
+       " 430122  2.707608 -4.840008          455            2.994959         2.999449\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 430885  4.006006 -4.843956          455            0.000080         2.999449\n",
+       " 430886  4.007708 -4.844151          455            0.000071         2.999449\n",
+       " 430887  4.009409 -4.844346          455            0.000062         2.999449\n",
+       " 430888  4.011111 -4.844541          455            0.000053         2.999449\n",
+       " 430889  4.012813 -4.844737          455            0.000043         2.999449\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 431118  2.700801 -4.840081          461            3.225545         3.077407\n",
+       " 431119  2.702502 -4.840236          461            3.224664         3.077407\n",
+       " 431120  2.704204 -4.840164          461            3.223791         3.077407\n",
+       " 431121  2.705906 -4.840089          461            3.222918         3.077407\n",
+       " 431122  2.707608 -4.840014          461            3.222044         3.077407\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 431893  4.019619 -4.844605          461            0.000082         3.077407\n",
+       " 431894  4.021321 -4.844843          461            0.000073         3.077407\n",
+       " 431895  4.023023 -4.845080          461            0.000064         3.077407\n",
+       " 431896  4.024725 -4.845317          461            0.000055         3.077407\n",
+       " 431897  4.026426 -4.845554          461            0.000046         3.077407\n",
+       " \n",
+       " [780 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 432118  2.700801 -4.839837          462            3.200171         3.203207\n",
+       " 432119  2.702502 -4.839959          462            3.199307         3.203207\n",
+       " 432120  2.704204 -4.839965          462            3.198412         3.203207\n",
+       " 432121  2.705906 -4.839890          462            3.197495         3.203207\n",
+       " 432122  2.707608 -4.839815          462            3.196578         3.203207\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 432892  4.017918 -4.843155          462            0.000077         3.203207\n",
+       " 432893  4.019619 -4.843336          462            0.000068         3.203207\n",
+       " 432894  4.021321 -4.843516          462            0.000059         3.203207\n",
+       " 432895  4.023023 -4.843696          462            0.000050         3.203207\n",
+       " 432896  4.024725 -4.843876          462            0.000041         3.203207\n",
+       " \n",
+       " [779 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 433118  2.700801 -4.840060          463            3.179294         3.189819\n",
+       " 433119  2.702502 -4.840134          463            3.178398         3.189819\n",
+       " 433120  2.704204 -4.839986          463            3.177512         3.189819\n",
+       " 433121  2.705906 -4.839838          463            3.176625         3.189819\n",
+       " 433122  2.707608 -4.839870          463            3.175731         3.189819\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 433891  4.016216 -4.844174          463            0.000077         3.189819\n",
+       " 433892  4.017918 -4.844384          463            0.000068         3.189819\n",
+       " 433893  4.019619 -4.844594          463            0.000059         3.189819\n",
+       " 433894  4.021321 -4.844804          463            0.000050         3.189819\n",
+       " 433895  4.023023 -4.845014          463            0.000041         3.189819\n",
+       " \n",
+       " [778 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 434118  2.700801 -4.840139          464            3.161738         3.171689\n",
+       " 434119  2.702502 -4.840193          464            3.160855         3.171689\n",
+       " 434120  2.704204 -4.840119          464            3.159973         3.171689\n",
+       " 434121  2.705906 -4.840044          464            3.159091         3.171689\n",
+       " 434122  2.707608 -4.839971          464            3.158184         3.171689\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 434890  4.014514 -4.843317          464            0.000080         3.171689\n",
+       " 434891  4.016216 -4.843498          464            0.000071         3.171689\n",
+       " 434892  4.017918 -4.843680          464            0.000062         3.171689\n",
+       " 434893  4.019619 -4.843862          464            0.000053         3.171689\n",
+       " 434894  4.021321 -4.844043          464            0.000044         3.171689\n",
+       " \n",
+       " [777 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 435118  2.700801 -4.839780          465            3.147177         3.156199\n",
+       " 435119  2.702502 -4.839780          465            3.146265         3.156199\n",
+       " 435120  2.704204 -4.839780          465            3.145351         3.156199\n",
+       " 435121  2.705906 -4.839780          465            3.144455         3.156199\n",
+       " 435122  2.707608 -4.839780          465            3.143577         3.156199\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 435890  4.014514 -4.843221          465            0.000077         3.156199\n",
+       " 435891  4.016216 -4.843382          465            0.000068         3.156199\n",
+       " 435892  4.017918 -4.843544          465            0.000059         3.156199\n",
+       " 435893  4.019619 -4.843706          465            0.000050         3.156199\n",
+       " 435894  4.021321 -4.843867          465            0.000042         3.156199\n",
+       " \n",
+       " [777 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 436118  2.700801 -4.840009          466            3.134708         3.142203\n",
+       " 436119  2.702502 -4.839980          466            3.133808         3.142203\n",
+       " 436120  2.704204 -4.839906          466            3.132908         3.142203\n",
+       " 436121  2.705906 -4.839832          466            3.132009         3.142203\n",
+       " 436122  2.707608 -4.839824          466            3.131105         3.142203\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 436889  4.012813 -4.844292          466            0.000083         3.142203\n",
+       " 436890  4.014514 -4.844537          466            0.000075         3.142203\n",
+       " 436891  4.016216 -4.844782          466            0.000066         3.142203\n",
+       " 436892  4.017918 -4.845028          466            0.000057         3.142203\n",
+       " 436893  4.019619 -4.845273          466            0.000048         3.142203\n",
+       " \n",
+       " [776 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 437118  2.700801 -4.839790          467            3.123831         3.130847\n",
+       " 437119  2.702502 -4.839942          467            3.122917         3.130847\n",
+       " 437120  2.704204 -4.840095          467            3.122004         3.130847\n",
+       " 437121  2.705906 -4.840234          467            3.121091         3.130847\n",
+       " 437122  2.707608 -4.840160          467            3.120179         3.130847\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 437889  4.012813 -4.842793          467            0.000080         3.130847\n",
+       " 437890  4.014514 -4.842935          467            0.000072         3.130847\n",
+       " 437891  4.016216 -4.843076          467            0.000063         3.130847\n",
+       " 437892  4.017918 -4.843218          467            0.000054         3.130847\n",
+       " 437893  4.019619 -4.843360          467            0.000045         3.130847\n",
+       " \n",
+       " [776 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 438118  2.700801 -4.840238          468            3.112968         3.119273\n",
+       " 438119  2.702502 -4.840238          468            3.112069         3.119273\n",
+       " 438120  2.704204 -4.840255          468            3.111166         3.119273\n",
+       " 438121  2.705906 -4.840329          468            3.110254         3.119273\n",
+       " 438122  2.707608 -4.840403          468            3.109341         3.119273\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 438889  4.012813 -4.843156          468            0.000077         3.119273\n",
+       " 438890  4.014514 -4.843336          468            0.000068         3.119273\n",
+       " 438891  4.016216 -4.843517          468            0.000059         3.119273\n",
+       " 438892  4.017918 -4.843697          468            0.000050         3.119273\n",
+       " 438893  4.019619 -4.843877          468            0.000041         3.119273\n",
+       " \n",
+       " [776 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 439118  2.700801 -4.840015          469            3.103557         3.109585\n",
+       " 439119  2.702502 -4.839556          469            3.102658         3.109585\n",
+       " 439120  2.704204 -4.839706          469            3.101749         3.109585\n",
+       " 439121  2.705906 -4.839857          469            3.100841         3.109585\n",
+       " 439122  2.707608 -4.840007          469            3.099932         3.109585\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 439888  4.011111 -4.845120          469            0.000083         3.109585\n",
+       " 439889  4.012813 -4.845385          469            0.000074         3.109585\n",
+       " 439890  4.014514 -4.845649          469            0.000066         3.109585\n",
+       " 439891  4.016216 -4.845914          469            0.000057         3.109585\n",
+       " 439892  4.017918 -4.846179          469            0.000048         3.109585\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 440118  2.700801 -4.839869          470            3.096004         3.101033\n",
+       " 440119  2.702502 -4.840042          470            3.095110         3.101033\n",
+       " 440120  2.704204 -4.840215          470            3.094215         3.101033\n",
+       " 440121  2.705906 -4.840175          470            3.093316         3.101033\n",
+       " 440122  2.707608 -4.840102          470            3.092417         3.101033\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 440888  4.011111 -4.844437          470            0.000081         3.101033\n",
+       " 440889  4.012813 -4.844665          470            0.000073         3.101033\n",
+       " 440890  4.014514 -4.844892          470            0.000064         3.101033\n",
+       " 440891  4.016216 -4.845120          470            0.000055         3.101033\n",
+       " 440892  4.017918 -4.845348          470            0.000046         3.101033\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 441118  2.700801 -4.839555          471            3.091659          3.09551\n",
+       " 441119  2.702502 -4.839781          471            3.090751          3.09551\n",
+       " 441120  2.704204 -4.840006          471            3.089842          3.09551\n",
+       " 441121  2.705906 -4.840231          471            3.088934          3.09551\n",
+       " 441122  2.707608 -4.840097          471            3.088013          3.09551\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 441888  4.011111 -4.843665          471            0.000083          3.09551\n",
+       " 441889  4.012813 -4.843856          471            0.000074          3.09551\n",
+       " 441890  4.014514 -4.844048          471            0.000065          3.09551\n",
+       " 441891  4.016216 -4.844239          471            0.000056          3.09551\n",
+       " 441892  4.017918 -4.844431          471            0.000047          3.09551\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 442118  2.700801 -4.840062          472            3.084185         3.088764\n",
+       " 442119  2.702502 -4.840176          472            3.083259         3.088764\n",
+       " 442120  2.704204 -4.840173          472            3.082339         3.088764\n",
+       " 442121  2.705906 -4.840027          472            3.081427         3.088764\n",
+       " 442122  2.707608 -4.839881          472            3.080514         3.088764\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 442888  4.011111 -4.844918          472            0.000079         3.088764\n",
+       " 442889  4.012813 -4.845154          472            0.000070         3.088764\n",
+       " 442890  4.014514 -4.845390          472            0.000061         3.088764\n",
+       " 442891  4.016216 -4.845627          472            0.000052         3.088764\n",
+       " 442892  4.017918 -4.845863          472            0.000043         3.088764\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 443118  2.700801 -4.840050          473            3.090804         3.093548\n",
+       " 443119  2.702502 -4.840138          473            3.089914         3.093548\n",
+       " 443120  2.704204 -4.840226          473            3.089025         3.093548\n",
+       " 443121  2.705906 -4.840302          473            3.088120         3.093548\n",
+       " 443122  2.707608 -4.840376          473            3.087211         3.093548\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 443889  4.012813 -4.844193          473            0.000076         3.093548\n",
+       " 443890  4.014514 -4.844399          473            0.000067         3.093548\n",
+       " 443891  4.016216 -4.844605          473            0.000058         3.093548\n",
+       " 443892  4.017918 -4.844812          473            0.000050         3.093548\n",
+       " 443893  4.019619 -4.845018          473            0.000041         3.093548\n",
+       " \n",
+       " [776 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 444118  2.700801 -4.840353          474            3.079024         3.082586\n",
+       " 444119  2.702502 -4.840111          474            3.078129         3.082586\n",
+       " 444120  2.704204 -4.839868          474            3.077234         3.082586\n",
+       " 444121  2.705906 -4.839828          474            3.076311         3.082586\n",
+       " 444122  2.707608 -4.839903          474            3.075372         3.082586\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 444888  4.011111 -4.842904          474            0.000080         3.082586\n",
+       " 444889  4.012813 -4.843072          474            0.000071         3.082586\n",
+       " 444890  4.014514 -4.843242          474            0.000062         3.082586\n",
+       " 444891  4.016216 -4.843410          474            0.000053         3.082586\n",
+       " 444892  4.017918 -4.843579          474            0.000045         3.082586\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 445118  2.700801 -4.840003          475            3.074196         3.077669\n",
+       " 445119  2.702502 -4.840177          475            3.073293         3.077669\n",
+       " 445120  2.704204 -4.840104          475            3.072406         3.077669\n",
+       " 445121  2.705906 -4.840031          475            3.071519         3.077669\n",
+       " 445122  2.707608 -4.839906          475            3.070596         3.077669\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 445888  4.011111 -4.843363          475            0.000078         3.077669\n",
+       " 445889  4.012813 -4.843540          475            0.000069         3.077669\n",
+       " 445890  4.014514 -4.843718          475            0.000060         3.077669\n",
+       " 445891  4.016216 -4.843895          475            0.000051         3.077669\n",
+       " 445892  4.017918 -4.844072          475            0.000043         3.077669\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 446118  2.700801 -4.839780          476            3.070964         3.073177\n",
+       " 446119  2.702502 -4.839780          476            3.070084         3.073177\n",
+       " 446120  2.704204 -4.839780          476            3.069180         3.073177\n",
+       " 446121  2.705906 -4.839780          476            3.068240         3.073177\n",
+       " 446122  2.707608 -4.839780          476            3.067300         3.073177\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 446888  4.011111 -4.844823          476            0.000077         3.073177\n",
+       " 446889  4.012813 -4.845095          476            0.000068         3.073177\n",
+       " 446890  4.014514 -4.845366          476            0.000059         3.073177\n",
+       " 446891  4.016216 -4.845638          476            0.000050         3.073177\n",
+       " 446892  4.017918 -4.845910          476            0.000041         3.073177\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 447118  2.700801 -4.839722          477            3.066737         3.069271\n",
+       " 447119  2.702502 -4.839598          477            3.065874         3.069271\n",
+       " 447120  2.704204 -4.839695          477            3.064971         3.069271\n",
+       " 447121  2.705906 -4.839923          477            3.064045         3.069271\n",
+       " 447122  2.707608 -4.840152          477            3.063118         3.069271\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 447888  4.011111 -4.844563          477            0.000077         3.069271\n",
+       " 447889  4.012813 -4.844790          477            0.000068         3.069271\n",
+       " 447890  4.014514 -4.845016          477            0.000059         3.069271\n",
+       " 447891  4.016216 -4.845243          477            0.000050         3.069271\n",
+       " 447892  4.017918 -4.845470          477            0.000041         3.069271\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 448118  2.700801 -4.839920          478            3.061307         3.064328\n",
+       " 448119  2.702502 -4.839727          478            3.060419         3.064328\n",
+       " 448120  2.704204 -4.839558          478            3.059528         3.064328\n",
+       " 448121  2.705906 -4.839632          478            3.058607         3.064328\n",
+       " 448122  2.707608 -4.839706          478            3.057685         3.064328\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 448888  4.011111 -4.843240          478            0.000076         3.064328\n",
+       " 448889  4.012813 -4.843403          478            0.000067         3.064328\n",
+       " 448890  4.014514 -4.843566          478            0.000058         3.064328\n",
+       " 448891  4.016216 -4.843729          478            0.000049         3.064328\n",
+       " 448892  4.017918 -4.843892          478            0.000040         3.064328\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 449118  2.700801 -4.839602          479            3.056510         3.058694\n",
+       " 449119  2.702502 -4.839711          479            3.055655         3.058694\n",
+       " 449120  2.704204 -4.839808          479            3.054770         3.058694\n",
+       " 449121  2.705906 -4.839882          479            3.053831         3.058694\n",
+       " 449122  2.707608 -4.839957          479            3.052891         3.058694\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 449887  4.009409 -4.844963          479            0.000084         3.058694\n",
+       " 449888  4.011111 -4.845210          479            0.000075         3.058694\n",
+       " 449889  4.012813 -4.845457          479            0.000066         3.058694\n",
+       " 449890  4.014514 -4.845704          479            0.000057         3.058694\n",
+       " 449891  4.016216 -4.845951          479            0.000048         3.058694\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 450118  2.700801 -4.840327          480            3.052765         3.055204\n",
+       " 450119  2.702502 -4.840238          480            3.051872         3.055204\n",
+       " 450120  2.704204 -4.840238          480            3.050981         3.055204\n",
+       " 450121  2.705906 -4.840238          480            3.050090         3.055204\n",
+       " 450122  2.707608 -4.840057          480            3.049159         3.055204\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 450888  4.011111 -4.844211          480            0.000075         3.055204\n",
+       " 450889  4.012813 -4.844419          480            0.000066         3.055204\n",
+       " 450890  4.014514 -4.844627          480            0.000058         3.055204\n",
+       " 450891  4.016216 -4.844835          480            0.000049         3.055204\n",
+       " 450892  4.017918 -4.845043          480            0.000040         3.055204\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 451118  2.700801 -4.839722          481            3.049569         3.051531\n",
+       " 451119  2.702502 -4.839598          481            3.048676         3.051531\n",
+       " 451120  2.704204 -4.839598          481            3.047774         3.051531\n",
+       " 451121  2.705906 -4.839672          481            3.046866         3.051531\n",
+       " 451122  2.707608 -4.839746          481            3.045958         3.051531\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 451887  4.009409 -4.844423          481            0.000082         3.051531\n",
+       " 451888  4.011111 -4.844651          481            0.000073         3.051531\n",
+       " 451889  4.012813 -4.844879          481            0.000064         3.051531\n",
+       " 451890  4.014514 -4.845107          481            0.000055         3.051531\n",
+       " 451891  4.016216 -4.845335          481            0.000046         3.051531\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 452118  2.700801 -4.840009          482            3.047288         3.048948\n",
+       " 452119  2.702502 -4.840009          482            3.046369         3.048948\n",
+       " 452120  2.704204 -4.840009          482            3.045473         3.048948\n",
+       " 452121  2.705906 -4.840009          482            3.044578         3.048948\n",
+       " 452122  2.707608 -4.839987          482            3.043674         3.048948\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 452887  4.009409 -4.842356          482            0.000082         3.048948\n",
+       " 452888  4.011111 -4.842488          482            0.000073         3.048948\n",
+       " 452889  4.012813 -4.842619          482            0.000064         3.048948\n",
+       " 452890  4.014514 -4.842751          482            0.000055         3.048948\n",
+       " 452891  4.016216 -4.842882          482            0.000047         3.048948\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 453118  2.700801 -4.839563          483            3.044931          3.04619\n",
+       " 453119  2.702502 -4.839494          483            3.044028          3.04619\n",
+       " 453120  2.704204 -4.839722          483            3.043110          3.04619\n",
+       " 453121  2.705906 -4.839951          483            3.042192          3.04619\n",
+       " 453122  2.707608 -4.840065          483            3.041276          3.04619\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 453887  4.009409 -4.844230          483            0.000078          3.04619\n",
+       " 453888  4.011111 -4.844418          483            0.000069          3.04619\n",
+       " 453889  4.012813 -4.844606          483            0.000060          3.04619\n",
+       " 453890  4.014514 -4.844794          483            0.000052          3.04619\n",
+       " 453891  4.016216 -4.844982          483            0.000043          3.04619\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 454118  2.700801 -4.840238          484            3.044440         3.044784\n",
+       " 454119  2.702502 -4.840186          484            3.043551         3.044784\n",
+       " 454120  2.704204 -4.840112          484            3.042682         3.044784\n",
+       " 454121  2.705906 -4.840038          484            3.041813         3.044784\n",
+       " 454122  2.707608 -4.840009          484            3.040904         3.044784\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 454887  4.009409 -4.844713          484            0.000078         3.044784\n",
+       " 454888  4.011111 -4.844947          484            0.000069         3.044784\n",
+       " 454889  4.012813 -4.845182          484            0.000060         3.044784\n",
+       " 454890  4.014514 -4.845417          484            0.000052         3.044784\n",
+       " 454891  4.016216 -4.845653          484            0.000043         3.044784\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 455118  2.700801 -4.839894          485            3.042373         3.044348\n",
+       " 455119  2.702502 -4.839971          485            3.041469         3.044348\n",
+       " 455120  2.704204 -4.839896          485            3.040586         3.044348\n",
+       " 455121  2.705906 -4.839822          485            3.039704         3.044348\n",
+       " 455122  2.707608 -4.839813          485            3.038798         3.044348\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 455887  4.009409 -4.844156          485            0.000078         3.044348\n",
+       " 455888  4.011111 -4.844361          485            0.000069         3.044348\n",
+       " 455889  4.012813 -4.844566          485            0.000060         3.044348\n",
+       " 455890  4.014514 -4.844771          485            0.000051         3.044348\n",
+       " 455891  4.016216 -4.844976          485            0.000043         3.044348\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 456118  2.700801 -4.839555          486            3.039093         3.041803\n",
+       " 456119  2.702502 -4.839777          486            3.038197         3.041803\n",
+       " 456120  2.704204 -4.839999          486            3.037302         3.041803\n",
+       " 456121  2.705906 -4.840221          486            3.036407         3.041803\n",
+       " 456122  2.707608 -4.840103          486            3.035496         3.041803\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 456887  4.009409 -4.843898          486            0.000077         3.041803\n",
+       " 456888  4.011111 -4.844112          486            0.000068         3.041803\n",
+       " 456889  4.012813 -4.844326          486            0.000060         3.041803\n",
+       " 456890  4.014514 -4.844540          486            0.000051         3.041803\n",
+       " 456891  4.016216 -4.844754          486            0.000042         3.041803\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 457118  2.700801 -4.840273          487            3.037955         3.039893\n",
+       " 457119  2.702502 -4.840350          487            3.037037         3.039893\n",
+       " 457120  2.704204 -4.840426          487            3.036119         3.039893\n",
+       " 457121  2.705906 -4.840364          487            3.035208         3.039893\n",
+       " 457122  2.707608 -4.840142          487            3.034304         3.039893\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 457887  4.009409 -4.843909          487            0.000077         3.039893\n",
+       " 457888  4.011111 -4.844125          487            0.000068         3.039893\n",
+       " 457889  4.012813 -4.844341          487            0.000059         3.039893\n",
+       " 457890  4.014514 -4.844557          487            0.000050         3.039893\n",
+       " 457891  4.016216 -4.844773          487            0.000041         3.039893\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 458118  2.700801 -4.839819          488            3.036231         3.037815\n",
+       " 458119  2.702502 -4.839903          488            3.035336         3.037815\n",
+       " 458120  2.704204 -4.839987          488            3.034441         3.037815\n",
+       " 458121  2.705906 -4.839900          488            3.033540         3.037815\n",
+       " 458122  2.707608 -4.839749          488            3.032636         3.037815\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 458887  4.009409 -4.844227          488            0.000076         3.037815\n",
+       " 458888  4.011111 -4.844424          488            0.000067         3.037815\n",
+       " 458889  4.012813 -4.844621          488            0.000059         3.037815\n",
+       " 458890  4.014514 -4.844818          488            0.000050         3.037815\n",
+       " 458891  4.016216 -4.845014          488            0.000041         3.037815\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 459118  2.700801 -4.839615          489            3.032463         3.035216\n",
+       " 459119  2.702502 -4.839837          489            3.031559         3.035216\n",
+       " 459120  2.704204 -4.840059          489            3.030655         3.035216\n",
+       " 459121  2.705906 -4.840195          489            3.029752         3.035216\n",
+       " 459122  2.707608 -4.839969          489            3.028852         3.035216\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 459887  4.009409 -4.842282          489            0.000077         3.035216\n",
+       " 459888  4.011111 -4.842394          489            0.000068         3.035216\n",
+       " 459889  4.012813 -4.842505          489            0.000059         3.035216\n",
+       " 459890  4.014514 -4.842617          489            0.000051         3.035216\n",
+       " 459891  4.016216 -4.842729          489            0.000042         3.035216\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 460118  2.700801 -4.839878          490            3.031039         3.032307\n",
+       " 460119  2.702502 -4.840174          490            3.030161         3.032307\n",
+       " 460120  2.704204 -4.840026          490            3.029279         3.032307\n",
+       " 460121  2.705906 -4.839878          490            3.028396         3.032307\n",
+       " 460122  2.707608 -4.839780          490            3.027493         3.032307\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 460887  4.009409 -4.844345          490            0.000078         3.032307\n",
+       " 460888  4.011111 -4.844559          490            0.000069         3.032307\n",
+       " 460889  4.012813 -4.844773          490            0.000060         3.032307\n",
+       " 460890  4.014514 -4.844987          490            0.000051         3.032307\n",
+       " 460891  4.016216 -4.845202          490            0.000043         3.032307\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 461118  2.700801 -4.840384          491            3.028029         3.031058\n",
+       " 461119  2.702502 -4.840161          491            3.027134         3.031058\n",
+       " 461120  2.704204 -4.839940          491            3.026239         3.031058\n",
+       " 461121  2.705906 -4.839780          491            3.025334         3.031058\n",
+       " 461122  2.707608 -4.839780          491            3.024403         3.031058\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 461886  4.007708 -4.843282          491            0.000084         3.031058\n",
+       " 461887  4.009409 -4.843452          491            0.000075         3.031058\n",
+       " 461888  4.011111 -4.843623          491            0.000066         3.031058\n",
+       " 461889  4.012813 -4.843793          491            0.000057         3.031058\n",
+       " 461890  4.014514 -4.843963          491            0.000048         3.031058\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 462118  2.700801 -4.840207          492            3.025487         3.027462\n",
+       " 462119  2.702502 -4.840131          492            3.024587         3.027462\n",
+       " 462120  2.704204 -4.840056          492            3.023688         3.027462\n",
+       " 462121  2.705906 -4.839981          492            3.022776         3.027462\n",
+       " 462122  2.707608 -4.839905          492            3.021845         3.027462\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 462887  4.009409 -4.844941          492            0.000077         3.027462\n",
+       " 462888  4.011111 -4.845184          492            0.000068         3.027462\n",
+       " 462889  4.012813 -4.845427          492            0.000059         3.027462\n",
+       " 462890  4.014514 -4.845669          492            0.000050         3.027462\n",
+       " 462891  4.016216 -4.845912          492            0.000041         3.027462\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 463118  2.700801 -4.840059          493            3.023747          3.02517\n",
+       " 463119  2.702502 -4.840209          493            3.022830          3.02517\n",
+       " 463120  2.704204 -4.840359          493            3.021912          3.02517\n",
+       " 463121  2.705906 -4.840382          493            3.020995          3.02517\n",
+       " 463122  2.707608 -4.840082          493            3.020078          3.02517\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 463886  4.007708 -4.843290          493            0.000084          3.02517\n",
+       " 463887  4.009409 -4.843459          493            0.000075          3.02517\n",
+       " 463888  4.011111 -4.843627          493            0.000066          3.02517\n",
+       " 463889  4.012813 -4.843796          493            0.000057          3.02517\n",
+       " 463890  4.014514 -4.843965          493            0.000048          3.02517\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 464118  2.700801 -4.839651          494            3.023263         3.024562\n",
+       " 464119  2.702502 -4.839809          494            3.022350         3.024562\n",
+       " 464120  2.704204 -4.839885          494            3.021437         3.024562\n",
+       " 464121  2.705906 -4.839960          494            3.020525         3.024562\n",
+       " 464122  2.707608 -4.840009          494            3.019603         3.024562\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 464886  4.007708 -4.843287          494            0.000084         3.024562\n",
+       " 464887  4.009409 -4.843456          494            0.000075         3.024562\n",
+       " 464888  4.011111 -4.843626          494            0.000066         3.024562\n",
+       " 464889  4.012813 -4.843795          494            0.000057         3.024562\n",
+       " 464890  4.014514 -4.843964          494            0.000048         3.024562\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 465118  2.700801 -4.840153          495            3.021634         3.022972\n",
+       " 465119  2.702502 -4.839971          495            3.020719         3.022972\n",
+       " 465120  2.704204 -4.839788          495            3.019803         3.022972\n",
+       " 465121  2.705906 -4.839710          495            3.018886         3.022972\n",
+       " 465122  2.707608 -4.839636          495            3.017969         3.022972\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 465886  4.007708 -4.844350          495            0.000083         3.022972\n",
+       " 465887  4.009409 -4.844584          495            0.000074         3.022972\n",
+       " 465888  4.011111 -4.844817          495            0.000065         3.022972\n",
+       " 465889  4.012813 -4.845051          495            0.000057         3.022972\n",
+       " 465890  4.014514 -4.845285          495            0.000048         3.022972\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 466118  2.700801 -4.839929          496            3.021022         3.022343\n",
+       " 466119  2.702502 -4.840067          496            3.020130         3.022343\n",
+       " 466120  2.704204 -4.840145          496            3.019222         3.022343\n",
+       " 466121  2.705906 -4.840222          496            3.018313         3.022343\n",
+       " 466122  2.707608 -4.840060          496            3.017366         3.022343\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 466886  4.007708 -4.844205          496            0.000083         3.022343\n",
+       " 466887  4.009409 -4.844420          496            0.000075         3.022343\n",
+       " 466888  4.011111 -4.844635          496            0.000066         3.022343\n",
+       " 466889  4.012813 -4.844850          496            0.000057         3.022343\n",
+       " 466890  4.014514 -4.845064          496            0.000048         3.022343\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 467118  2.700801 -4.840166          497            3.021039         3.021883\n",
+       " 467119  2.702502 -4.840011          497            3.020144         3.021883\n",
+       " 467120  2.704204 -4.839857          497            3.019249         3.021883\n",
+       " 467121  2.705906 -4.839780          497            3.018336         3.021883\n",
+       " 467122  2.707608 -4.839780          497            3.017405         3.021883\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 467886  4.007708 -4.844566          497            0.000084         3.021883\n",
+       " 467887  4.009409 -4.844800          497            0.000075         3.021883\n",
+       " 467888  4.011111 -4.845035          497            0.000066         3.021883\n",
+       " 467889  4.012813 -4.845269          497            0.000057         3.021883\n",
+       " 467890  4.014514 -4.845503          497            0.000048         3.021883\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 468118  2.700801 -4.839986          498            3.021778         3.022588\n",
+       " 468119  2.702502 -4.839836          498            3.020892         3.022588\n",
+       " 468120  2.704204 -4.839686          498            3.020005         3.022588\n",
+       " 468121  2.705906 -4.839567          498            3.019114         3.022588\n",
+       " 468122  2.707608 -4.839717          498            3.018184         3.022588\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 468887  4.009409 -4.844006          498            0.000076         3.022588\n",
+       " 468888  4.011111 -4.844201          498            0.000067         3.022588\n",
+       " 468889  4.012813 -4.844396          498            0.000059         3.022588\n",
+       " 468890  4.014514 -4.844591          498            0.000050         3.022588\n",
+       " 468891  4.016216 -4.844786          498            0.000041         3.022588\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 469118  2.700801 -4.840009          499            3.021122         3.022739\n",
+       " 469119  2.702502 -4.840014          499            3.020231         3.022739\n",
+       " 469120  2.704204 -4.840164          499            3.019331         3.022739\n",
+       " 469121  2.705906 -4.840314          499            3.018432         3.022739\n",
+       " 469122  2.707608 -4.840465          499            3.017532         3.022739\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 469887  4.009409 -4.843052          499            0.000076         3.022739\n",
+       " 469888  4.011111 -4.843200          499            0.000067         3.022739\n",
+       " 469889  4.012813 -4.843347          499            0.000059         3.022739\n",
+       " 469890  4.014514 -4.843494          499            0.000050         3.022739\n",
+       " 469891  4.016216 -4.843642          499            0.000041         3.022739\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 470118  2.700801 -4.839780          500            3.019871         3.021796\n",
+       " 470119  2.702502 -4.839780          500            3.018981         3.021796\n",
+       " 470120  2.704204 -4.839780          500            3.018091         3.021796\n",
+       " 470121  2.705906 -4.839780          500            3.017190         3.021796\n",
+       " 470122  2.707608 -4.839780          500            3.016282         3.021796\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 470887  4.009409 -4.843256          500            0.000075         3.021796\n",
+       " 470888  4.011111 -4.843413          500            0.000067         3.021796\n",
+       " 470889  4.012813 -4.843570          500            0.000058         3.021796\n",
+       " 470890  4.014514 -4.843726          500            0.000049         3.021796\n",
+       " 470891  4.016216 -4.843883          500            0.000041         3.021796\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 471118  2.700801 -4.839328          501            3.020163         3.020706\n",
+       " 471119  2.702502 -4.839628          501            3.019263         3.020706\n",
+       " 471120  2.704204 -4.839929          501            3.018363         3.020706\n",
+       " 471121  2.705906 -4.840229          501            3.017464         3.020706\n",
+       " 471122  2.707608 -4.840167          501            3.016547         3.020706\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 471887  4.009409 -4.844467          501            0.000076         3.020706\n",
+       " 471888  4.011111 -4.844661          501            0.000067         3.020706\n",
+       " 471889  4.012813 -4.844855          501            0.000058         3.020706\n",
+       " 471890  4.014514 -4.845049          501            0.000050         3.020706\n",
+       " 471891  4.016216 -4.845243          501            0.000041         3.020706\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 472118  2.700801 -4.839998          502            3.017608         3.019511\n",
+       " 472119  2.702502 -4.839921          502            3.016704         3.019511\n",
+       " 472120  2.704204 -4.839845          502            3.015800         3.019511\n",
+       " 472121  2.705906 -4.839780          502            3.014894         3.019511\n",
+       " 472122  2.707608 -4.839780          502            3.013976         3.019511\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 472886  4.007708 -4.844543          502            0.000083         3.019511\n",
+       " 472887  4.009409 -4.844784          502            0.000074         3.019511\n",
+       " 472888  4.011111 -4.845025          502            0.000065         3.019511\n",
+       " 472889  4.012813 -4.845266          502            0.000057         3.019511\n",
+       " 472890  4.014514 -4.845507          502            0.000048         3.019511\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 473118  2.700801 -4.840286          503            3.016114         3.017612\n",
+       " 473119  2.702502 -4.840388          503            3.015238         3.017612\n",
+       " 473120  2.704204 -4.840399          503            3.014349         3.017612\n",
+       " 473121  2.705906 -4.840094          503            3.013414         3.017612\n",
+       " 473122  2.707608 -4.839789          503            3.012479         3.017612\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 473887  4.009409 -4.843287          503            0.000076         3.017612\n",
+       " 473888  4.011111 -4.843434          503            0.000067         3.017612\n",
+       " 473889  4.012813 -4.843582          503            0.000058         3.017612\n",
+       " 473890  4.014514 -4.843729          503            0.000050         3.017612\n",
+       " 473891  4.016216 -4.843877          503            0.000041         3.017612\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 474118  2.700801 -4.839808          504            3.015121          3.01604\n",
+       " 474119  2.702502 -4.839882          504            3.014187          3.01604\n",
+       " 474120  2.704204 -4.839956          504            3.013253          3.01604\n",
+       " 474121  2.705906 -4.839947          504            3.012327          3.01604\n",
+       " 474122  2.707608 -4.839728          504            3.011423          3.01604\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 474886  4.007708 -4.843536          504            0.000083          3.01604\n",
+       " 474887  4.009409 -4.843749          504            0.000074          3.01604\n",
+       " 474888  4.011111 -4.843962          504            0.000065          3.01604\n",
+       " 474889  4.012813 -4.844175          504            0.000057          3.01604\n",
+       " 474890  4.014514 -4.844388          504            0.000048          3.01604\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 475118  2.700801 -4.840009          505            3.014711           3.0165\n",
+       " 475119  2.702502 -4.840009          505            3.013785           3.0165\n",
+       " 475120  2.704204 -4.840009          505            3.012859           3.0165\n",
+       " 475121  2.705906 -4.839967          505            3.011936           3.0165\n",
+       " 475122  2.707608 -4.839748          505            3.011024           3.0165\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 475887  4.009409 -4.845536          505            0.000077           3.0165\n",
+       " 475888  4.011111 -4.845795          505            0.000068           3.0165\n",
+       " 475889  4.012813 -4.846054          505            0.000060           3.0165\n",
+       " 475890  4.014514 -4.846313          505            0.000051           3.0165\n",
+       " 475891  4.016216 -4.846572          505            0.000042           3.0165\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 476118  2.700801 -4.840260          506            3.013360         3.014009\n",
+       " 476119  2.702502 -4.840042          506            3.012459         3.014009\n",
+       " 476120  2.704204 -4.840117          506            3.011554         3.014009\n",
+       " 476121  2.705906 -4.840192          506            3.010650         3.014009\n",
+       " 476122  2.707608 -4.840267          506            3.009736         3.014009\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 476886  4.007708 -4.845210          506            0.000083         3.014009\n",
+       " 476887  4.009409 -4.845501          506            0.000074         3.014009\n",
+       " 476888  4.011111 -4.845793          506            0.000066         3.014009\n",
+       " 476889  4.012813 -4.846084          506            0.000057         3.014009\n",
+       " 476890  4.014514 -4.846375          506            0.000048         3.014009\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 477118  2.700801 -4.840168          507            3.011217         3.013068\n",
+       " 477119  2.702502 -4.840018          507            3.010335         3.013068\n",
+       " 477120  2.704204 -4.839868          507            3.009453         3.013068\n",
+       " 477121  2.705906 -4.839780          507            3.008551         3.013068\n",
+       " 477122  2.707608 -4.839780          507            3.007621         3.013068\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 477887  4.009409 -4.844458          507            0.000076         3.013068\n",
+       " 477888  4.011111 -4.844654          507            0.000067         3.013068\n",
+       " 477889  4.012813 -4.844851          507            0.000059         3.013068\n",
+       " 477890  4.014514 -4.845047          507            0.000050         3.013068\n",
+       " 477891  4.016216 -4.845243          507            0.000041         3.013068\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 478118  2.700801 -4.839465          508            3.009323         3.009969\n",
+       " 478119  2.702502 -4.839769          508            3.008414         3.009969\n",
+       " 478120  2.704204 -4.840074          508            3.007505         3.009969\n",
+       " 478121  2.705906 -4.840170          508            3.006597         3.009969\n",
+       " 478122  2.707608 -4.840022          508            3.005689         3.009969\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 478887  4.009409 -4.844336          508            0.000076         3.009969\n",
+       " 478888  4.011111 -4.844562          508            0.000068         3.009969\n",
+       " 478889  4.012813 -4.844787          508            0.000059         3.009969\n",
+       " 478890  4.014514 -4.845013          508            0.000050         3.009969\n",
+       " 478891  4.016216 -4.845239          508            0.000041         3.009969\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 479118  2.700801 -4.840009          509            3.006424          3.00809\n",
+       " 479119  2.702502 -4.840009          509            3.005546          3.00809\n",
+       " 479120  2.704204 -4.840009          509            3.004667          3.00809\n",
+       " 479121  2.705906 -4.840009          509            3.003789          3.00809\n",
+       " 479122  2.707608 -4.840009          509            3.002872          3.00809\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 479886  4.007708 -4.843976          509            0.000083          3.00809\n",
+       " 479887  4.009409 -4.844191          509            0.000075          3.00809\n",
+       " 479888  4.011111 -4.844406          509            0.000066          3.00809\n",
+       " 479889  4.012813 -4.844621          509            0.000057          3.00809\n",
+       " 479890  4.014514 -4.844835          509            0.000048          3.00809\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 480118  2.700801 -4.839956          510            3.005687         3.006221\n",
+       " 480119  2.702502 -4.839843          510            3.004768         3.006221\n",
+       " 480120  2.704204 -4.839715          510            3.003863         3.006221\n",
+       " 480121  2.705906 -4.839569          510            3.002976         3.006221\n",
+       " 480122  2.707608 -4.839423          510            3.002090         3.006221\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 480886  4.007708 -4.845118          510            0.000082         3.006221\n",
+       " 480887  4.009409 -4.845388          510            0.000073         3.006221\n",
+       " 480888  4.011111 -4.845660          510            0.000064         3.006221\n",
+       " 480889  4.012813 -4.845931          510            0.000056         3.006221\n",
+       " 480890  4.014514 -4.846202          510            0.000047         3.006221\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 481118  2.700801 -4.840150          511            3.005748         3.006015\n",
+       " 481119  2.702502 -4.839961          511            3.004870         3.006015\n",
+       " 481120  2.704204 -4.839787          511            3.003990         3.006015\n",
+       " 481121  2.705906 -4.839940          511            3.003050         3.006015\n",
+       " 481122  2.707608 -4.840092          511            3.002110         3.006015\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 481886  4.007708 -4.845351          511            0.000082         3.006015\n",
+       " 481887  4.009409 -4.845621          511            0.000073         3.006015\n",
+       " 481888  4.011111 -4.845891          511            0.000064         3.006015\n",
+       " 481889  4.012813 -4.846161          511            0.000055         3.006015\n",
+       " 481890  4.014514 -4.846432          511            0.000047         3.006015\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 482118  2.700801 -4.839962          512            3.006097         3.006777\n",
+       " 482119  2.702502 -4.839871          512            3.005193         3.006777\n",
+       " 482120  2.704204 -4.839780          512            3.004287         3.006777\n",
+       " 482121  2.705906 -4.839707          512            3.003401         3.006777\n",
+       " 482122  2.707608 -4.839634          512            3.002514         3.006777\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 482886  4.007708 -4.844965          512            0.000082         3.006777\n",
+       " 482887  4.009409 -4.845215          512            0.000074         3.006777\n",
+       " 482888  4.011111 -4.845466          512            0.000065         3.006777\n",
+       " 482889  4.012813 -4.845716          512            0.000056         3.006777\n",
+       " 482890  4.014514 -4.845967          512            0.000047         3.006777\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 483118  2.700801 -4.839588          513            3.003886         3.004842\n",
+       " 483119  2.702502 -4.839666          513            3.002996         3.004842\n",
+       " 483120  2.704204 -4.839745          513            3.002105         3.004842\n",
+       " 483121  2.705906 -4.839863          513            3.001195         3.004842\n",
+       " 483122  2.707608 -4.840014          513            3.000269         3.004842\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 483886  4.007708 -4.843435          513            0.000080         3.004842\n",
+       " 483887  4.009409 -4.843584          513            0.000072         3.004842\n",
+       " 483888  4.011111 -4.843733          513            0.000063         3.004842\n",
+       " 483889  4.012813 -4.843882          513            0.000054         3.004842\n",
+       " 483890  4.014514 -4.844031          513            0.000045         3.004842\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 484118  2.700801 -4.839492          514            3.003769         3.004239\n",
+       " 484119  2.702502 -4.839365          514            3.002944         3.004239\n",
+       " 484120  2.704204 -4.839425          514            3.002048         3.004239\n",
+       " 484121  2.705906 -4.839578          514            3.001117         3.004239\n",
+       " 484122  2.707608 -4.839730          514            3.000186         3.004239\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 484886  4.007708 -4.844461          514            0.000080         3.004239\n",
+       " 484887  4.009409 -4.844683          514            0.000072         3.004239\n",
+       " 484888  4.011111 -4.844904          514            0.000063         3.004239\n",
+       " 484889  4.012813 -4.845125          514            0.000054         3.004239\n",
+       " 484890  4.014514 -4.845346          514            0.000046         3.004239\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 485118  2.700801 -4.840197          515            3.005001         3.004418\n",
+       " 485119  2.702502 -4.840109          515            3.004138         3.004418\n",
+       " 485120  2.704204 -4.840021          515            3.003274         3.004418\n",
+       " 485121  2.705906 -4.839945          515            3.002387         3.004418\n",
+       " 485122  2.707608 -4.839871          515            3.001496         3.004418\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 485886  4.007708 -4.844216          515            0.000081         3.004418\n",
+       " 485887  4.009409 -4.844437          515            0.000072         3.004418\n",
+       " 485888  4.011111 -4.844657          515            0.000064         3.004418\n",
+       " 485889  4.012813 -4.844878          515            0.000055         3.004418\n",
+       " 485890  4.014514 -4.845098          515            0.000047         3.004418\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 486118  2.700801 -4.839692          516            3.005194         3.005363\n",
+       " 486119  2.702502 -4.839551          516            3.004295         3.005363\n",
+       " 486120  2.704204 -4.839551          516            3.003431         3.005363\n",
+       " 486121  2.705906 -4.839551          516            3.002567         3.005363\n",
+       " 486122  2.707608 -4.839583          516            3.001686         3.005363\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 486886  4.007708 -4.844634          516            0.000079         3.005363\n",
+       " 486887  4.009409 -4.844874          516            0.000071         3.005363\n",
+       " 486888  4.011111 -4.845114          516            0.000062         3.005363\n",
+       " 486889  4.012813 -4.845354          516            0.000053         3.005363\n",
+       " 486890  4.014514 -4.845594          516            0.000045         3.005363\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 487118  2.700801 -4.840091          517            3.004303         3.005951\n",
+       " 487119  2.702502 -4.840201          517            3.003414         3.005951\n",
+       " 487120  2.704204 -4.839975          517            3.002523         3.005951\n",
+       " 487121  2.705906 -4.839750          517            3.001632         3.005951\n",
+       " 487122  2.707608 -4.839569          517            3.000736         3.005951\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 487886  4.007708 -4.844308          517            0.000081         3.005951\n",
+       " 487887  4.009409 -4.844510          517            0.000072         3.005951\n",
+       " 487888  4.011111 -4.844711          517            0.000064         3.005951\n",
+       " 487889  4.012813 -4.844912          517            0.000055         3.005951\n",
+       " 487890  4.014514 -4.845113          517            0.000047         3.005951\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 488118  2.700801 -4.840078          518            3.002991         3.004582\n",
+       " 488119  2.702502 -4.840408          518            3.002122         3.004582\n",
+       " 488120  2.704204 -4.840258          518            3.001222         3.004582\n",
+       " 488121  2.705906 -4.840108          518            3.000323         3.004582\n",
+       " 488122  2.707608 -4.839984          518            2.999418         3.004582\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 488886  4.007708 -4.843532          518            0.000081         3.004582\n",
+       " 488887  4.009409 -4.843706          518            0.000072         3.004582\n",
+       " 488888  4.011111 -4.843880          518            0.000063         3.004582\n",
+       " 488889  4.012813 -4.844054          518            0.000055         3.004582\n",
+       " 488890  4.014514 -4.844227          518            0.000046         3.004582\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 489118  2.700801 -4.839789          519            3.001893         3.003999\n",
+       " 489119  2.702502 -4.839938          519            3.001002         3.003999\n",
+       " 489120  2.704204 -4.840086          519            3.000111         3.003999\n",
+       " 489121  2.705906 -4.840233          519            2.999220         3.003999\n",
+       " 489122  2.707608 -4.840097          519            2.998300         3.003999\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 489886  4.007708 -4.844738          519            0.000081         3.003999\n",
+       " 489887  4.009409 -4.844995          519            0.000072         3.003999\n",
+       " 489888  4.011111 -4.845253          519            0.000063         3.003999\n",
+       " 489889  4.012813 -4.845510          519            0.000055         3.003999\n",
+       " 489890  4.014514 -4.845767          519            0.000046         3.003999\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 490118  2.700801 -4.840238          520            3.000333         3.001303\n",
+       " 490119  2.702502 -4.840238          520            2.999462         3.001303\n",
+       " 490120  2.704204 -4.840099          520            2.998574         3.001303\n",
+       " 490121  2.705906 -4.839877          520            2.997674         3.001303\n",
+       " 490122  2.707608 -4.839655          520            2.996774         3.001303\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 490886  4.007708 -4.845177          520            0.000079         3.001303\n",
+       " 490887  4.009409 -4.845454          520            0.000070         3.001303\n",
+       " 490888  4.011111 -4.845730          520            0.000061         3.001303\n",
+       " 490889  4.012813 -4.846007          520            0.000053         3.001303\n",
+       " 490890  4.014514 -4.846284          520            0.000044         3.001303\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 491118  2.700801 -4.839687          521            3.000200         3.002051\n",
+       " 491119  2.702502 -4.839979          521            2.999274         3.002051\n",
+       " 491120  2.704204 -4.840009          521            2.998387         3.002051\n",
+       " 491121  2.705906 -4.840009          521            2.997505         3.002051\n",
+       " 491122  2.707608 -4.840009          521            2.996623         3.002051\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 491886  4.007708 -4.844043          521            0.000081         3.002051\n",
+       " 491887  4.009409 -4.844254          521            0.000072         3.002051\n",
+       " 491888  4.011111 -4.844465          521            0.000063         3.002051\n",
+       " 491889  4.012813 -4.844676          521            0.000055         3.002051\n",
+       " 491890  4.014514 -4.844886          521            0.000046         3.002051\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 492118  2.700801 -4.839872          522            2.998031         2.999721\n",
+       " 492119  2.702502 -4.840009          522            2.997148         2.999721\n",
+       " 492120  2.704204 -4.840009          522            2.996248         2.999721\n",
+       " 492121  2.705906 -4.840009          522            2.995348         2.999721\n",
+       " 492122  2.707608 -4.840032          522            2.994443         2.999721\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 492886  4.007708 -4.843359          522            0.000080         2.999721\n",
+       " 492887  4.009409 -4.843524          522            0.000071         2.999721\n",
+       " 492888  4.011111 -4.843689          522            0.000063         2.999721\n",
+       " 492889  4.012813 -4.843854          522            0.000054         2.999721\n",
+       " 492890  4.014514 -4.844020          522            0.000045         2.999721\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 493118  2.700801 -4.839687          523            2.997303         2.998461\n",
+       " 493119  2.702502 -4.839979          523            2.996395         2.998461\n",
+       " 493120  2.704204 -4.840075          523            2.995487         2.998461\n",
+       " 493121  2.705906 -4.840147          523            2.994579         2.998461\n",
+       " 493122  2.707608 -4.840220          523            2.993671         2.998461\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 493886  4.007708 -4.844009          523            0.000080         2.998461\n",
+       " 493887  4.009409 -4.844229          523            0.000072         2.998461\n",
+       " 493888  4.011111 -4.844450          523            0.000063         2.998461\n",
+       " 493889  4.012813 -4.844669          523            0.000054         2.998461\n",
+       " 493890  4.014514 -4.844889          523            0.000046         2.998461\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 494118  2.700801 -4.839847          524            2.997109         2.998482\n",
+       " 494119  2.702502 -4.839499          524            2.996217         2.998482\n",
+       " 494120  2.704204 -4.839434          524            2.995309         2.998482\n",
+       " 494121  2.705906 -4.839659          524            2.994388         2.998482\n",
+       " 494122  2.707608 -4.839884          524            2.993466         2.998482\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 494886  4.007708 -4.843529          524            0.000081         2.998482\n",
+       " 494887  4.009409 -4.843704          524            0.000072         2.998482\n",
+       " 494888  4.011111 -4.843878          524            0.000063         2.998482\n",
+       " 494889  4.012813 -4.844052          524            0.000055         2.998482\n",
+       " 494890  4.014514 -4.844227          524            0.000046         2.998482\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 495118  2.700801 -4.839836          525            2.995519         2.996909\n",
+       " 495119  2.702502 -4.839954          525            2.994648         2.996909\n",
+       " 495120  2.704204 -4.839969          525            2.993739         2.996909\n",
+       " 495121  2.705906 -4.839894          525            2.992800         2.996909\n",
+       " 495122  2.707608 -4.839818          525            2.991861         2.996909\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 495886  4.007708 -4.844064          525            0.000080         2.996909\n",
+       " 495887  4.009409 -4.844277          525            0.000071         2.996909\n",
+       " 495888  4.011111 -4.844489          525            0.000062         2.996909\n",
+       " 495889  4.012813 -4.844701          525            0.000054         2.996909\n",
+       " 495890  4.014514 -4.844913          525            0.000045         2.996909\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 496118  2.700801 -4.840009          526            2.995654         2.997284\n",
+       " 496119  2.702502 -4.839971          526            2.994734         2.997284\n",
+       " 496120  2.704204 -4.839896          526            2.993848         2.997284\n",
+       " 496121  2.705906 -4.839822          526            2.992961         2.997284\n",
+       " 496122  2.707608 -4.839780          526            2.992052         2.997284\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 496886  4.007708 -4.844740          526            0.000082         2.997284\n",
+       " 496887  4.009409 -4.844987          526            0.000074         2.997284\n",
+       " 496888  4.011111 -4.845235          526            0.000065         2.997284\n",
+       " 496889  4.012813 -4.845482          526            0.000056         2.997284\n",
+       " 496890  4.014514 -4.845730          526            0.000048         2.997284\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 497118  2.700801 -4.839768          527            2.994627         2.994851\n",
+       " 497119  2.702502 -4.840232          527            2.993746         2.994851\n",
+       " 497120  2.704204 -4.840163          527            2.992833         2.994851\n",
+       " 497121  2.705906 -4.840087          527            2.991920         2.994851\n",
+       " 497122  2.707608 -4.840011          527            2.991007         2.994851\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 497886  4.007708 -4.843152          527            0.000081         2.994851\n",
+       " 497887  4.009409 -4.843307          527            0.000072         2.994851\n",
+       " 497888  4.011111 -4.843464          527            0.000064         2.994851\n",
+       " 497889  4.012813 -4.843620          527            0.000055         2.994851\n",
+       " 497890  4.014514 -4.843776          527            0.000047         2.994851\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 498118  2.700801 -4.839873          528            2.992189         2.994034\n",
+       " 498119  2.702502 -4.839581          528            2.991298         2.994034\n",
+       " 498120  2.704204 -4.839684          528            2.990380         2.994034\n",
+       " 498121  2.705906 -4.839832          528            2.989459         2.994034\n",
+       " 498122  2.707608 -4.839980          528            2.988537         2.994034\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 498886  4.007708 -4.843699          528            0.000079         2.994034\n",
+       " 498887  4.009409 -4.843891          528            0.000071         2.994034\n",
+       " 498888  4.011111 -4.844083          528            0.000062         2.994034\n",
+       " 498889  4.012813 -4.844275          528            0.000054         2.994034\n",
+       " 498890  4.014514 -4.844468          528            0.000045         2.994034\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 499118  2.700801 -4.840089          529            2.993180          2.99368\n",
+       " 499119  2.702502 -4.839780          529            2.992307          2.99368\n",
+       " 499120  2.704204 -4.839780          529            2.991390          2.99368\n",
+       " 499121  2.705906 -4.839780          529            2.990473          2.99368\n",
+       " 499122  2.707608 -4.839780          529            2.989555          2.99368\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 499883  4.002603 -4.839106          529            0.000099          2.99368\n",
+       " 499884  4.004304 -4.839057          529            0.000089          2.99368\n",
+       " 499885  4.006006 -4.839007          529            0.000080          2.99368\n",
+       " 499886  4.007708 -4.838958          529            0.000071          2.99368\n",
+       " 499887  4.009409 -4.838908          529            0.000061          2.99368\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 500118  2.700801 -4.839914          530            2.992124         2.993109\n",
+       " 500119  2.702502 -4.839832          530            2.991229         2.993109\n",
+       " 500120  2.704204 -4.839983          530            2.990321         2.993109\n",
+       " 500121  2.705906 -4.840132          530            2.989412         2.993109\n",
+       " 500122  2.707608 -4.840172          530            2.988504         2.993109\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 500886  4.007708 -4.844594          530            0.000079         2.993109\n",
+       " 500887  4.009409 -4.844842          530            0.000071         2.993109\n",
+       " 500888  4.011111 -4.845091          530            0.000062         2.993109\n",
+       " 500889  4.012813 -4.845340          530            0.000053         2.993109\n",
+       " 500890  4.014514 -4.845589          530            0.000045         2.993109\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 501118  2.700801 -4.840009          531            2.992898         2.993753\n",
+       " 501119  2.702502 -4.840009          531            2.992055         2.993753\n",
+       " 501120  2.704204 -4.840009          531            2.991159         2.993753\n",
+       " 501121  2.705906 -4.840009          531            2.990250         2.993753\n",
+       " 501122  2.707608 -4.840009          531            2.989342         2.993753\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 501886  4.007708 -4.843984          531            0.000081         2.993753\n",
+       " 501887  4.009409 -4.844203          531            0.000073         2.993753\n",
+       " 501888  4.011111 -4.844422          531            0.000064         2.993753\n",
+       " 501889  4.012813 -4.844641          531            0.000056         2.993753\n",
+       " 501890  4.014514 -4.844860          531            0.000047         2.993753\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 502118  2.700801 -4.840009          532            2.992410          2.99334\n",
+       " 502119  2.702502 -4.840022          532            2.991527          2.99334\n",
+       " 502120  2.704204 -4.840098          532            2.990623          2.99334\n",
+       " 502121  2.705906 -4.840174          532            2.989719          2.99334\n",
+       " 502122  2.707608 -4.840226          532            2.988809          2.99334\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 502886  4.007708 -4.844203          532            0.000080          2.99334\n",
+       " 502887  4.009409 -4.844433          532            0.000071          2.99334\n",
+       " 502888  4.011111 -4.844663          532            0.000063          2.99334\n",
+       " 502889  4.012813 -4.844892          532            0.000054          2.99334\n",
+       " 502890  4.014514 -4.845121          532            0.000045          2.99334\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 503118  2.700801 -4.840085          533            2.992311         2.993556\n",
+       " 503119  2.702502 -4.839786          533            2.991395         2.993556\n",
+       " 503120  2.704204 -4.839860          533            2.990517         2.993556\n",
+       " 503121  2.705906 -4.839934          533            2.989639         2.993556\n",
+       " 503122  2.707608 -4.840008          533            2.988761         2.993556\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 503886  4.007708 -4.843719          533            0.000081         2.993556\n",
+       " 503887  4.009409 -4.843902          533            0.000072         2.993556\n",
+       " 503888  4.011111 -4.844084          533            0.000063         2.993556\n",
+       " 503889  4.012813 -4.844267          533            0.000055         2.993556\n",
+       " 503890  4.014514 -4.844450          533            0.000046         2.993556\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 504118  2.700801 -4.839780          534            2.992505         2.993149\n",
+       " 504119  2.702502 -4.839718          534            2.991612         2.993149\n",
+       " 504120  2.704204 -4.839644          534            2.990717         2.993149\n",
+       " 504121  2.705906 -4.839571          534            2.989822         2.993149\n",
+       " 504122  2.707608 -4.839551          534            2.988903         2.993149\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 504886  4.007708 -4.845386          534            0.000081         2.993149\n",
+       " 504887  4.009409 -4.845652          534            0.000072         2.993149\n",
+       " 504888  4.011111 -4.845917          534            0.000063         2.993149\n",
+       " 504889  4.012813 -4.846182          534            0.000055         2.993149\n",
+       " 504890  4.014514 -4.846447          534            0.000046         2.993149\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 505118  2.700801 -4.839780          535            2.993714         2.994929\n",
+       " 505119  2.702502 -4.839780          535            2.992802         2.994929\n",
+       " 505120  2.704204 -4.839780          535            2.991858         2.994929\n",
+       " 505121  2.705906 -4.839780          535            2.990914         2.994929\n",
+       " 505122  2.707608 -4.839786          535            2.989972         2.994929\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 505886  4.007708 -4.844594          535            0.000081         2.994929\n",
+       " 505887  4.009409 -4.844831          535            0.000072         2.994929\n",
+       " 505888  4.011111 -4.845068          535            0.000064         2.994929\n",
+       " 505889  4.012813 -4.845305          535            0.000055         2.994929\n",
+       " 505890  4.014514 -4.845542          535            0.000047         2.994929\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 506118  2.700801 -4.840009          536            2.994068         2.994713\n",
+       " 506119  2.702502 -4.839893          536            2.993152         2.994713\n",
+       " 506120  2.704204 -4.839671          536            2.992248         2.994713\n",
+       " 506121  2.705906 -4.839449          536            2.991344         2.994713\n",
+       " 506122  2.707608 -4.839418          536            2.990438         2.994713\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 506886  4.007708 -4.844535          536            0.000081         2.994713\n",
+       " 506887  4.009409 -4.844782          536            0.000073         2.994713\n",
+       " 506888  4.011111 -4.845029          536            0.000064         2.994713\n",
+       " 506889  4.012813 -4.845276          536            0.000056         2.994713\n",
+       " 506890  4.014514 -4.845523          536            0.000047         2.994713\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 507118  2.700801 -4.839817          537            2.991820         2.993601\n",
+       " 507119  2.702502 -4.839894          537            2.990916         2.993601\n",
+       " 507120  2.704204 -4.839971          537            2.990012         2.993601\n",
+       " 507121  2.705906 -4.839971          537            2.989106         2.993601\n",
+       " 507122  2.707608 -4.839896          537            2.988197         2.993601\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 507886  4.007708 -4.845345          537            0.000082         2.993601\n",
+       " 507887  4.009409 -4.845607          537            0.000073         2.993601\n",
+       " 507888  4.011111 -4.845869          537            0.000065         2.993601\n",
+       " 507889  4.012813 -4.846130          537            0.000056         2.993601\n",
+       " 507890  4.014514 -4.846392          537            0.000048         2.993601\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 508118  2.700801 -4.839750          538            2.991537         2.992447\n",
+       " 508119  2.702502 -4.840009          538            2.990667         2.992447\n",
+       " 508120  2.704204 -4.840009          538            2.989768         2.992447\n",
+       " 508121  2.705906 -4.840009          538            2.988868         2.992447\n",
+       " 508122  2.707608 -4.839987          538            2.987959         2.992447\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 508887  4.009409 -4.845164          538            0.000074         2.992447\n",
+       " 508888  4.011111 -4.845416          538            0.000066         2.992447\n",
+       " 508889  4.012813 -4.845668          538            0.000057         2.992447\n",
+       " 508890  4.014514 -4.845921          538            0.000049         2.992447\n",
+       " 508891  4.016216 -4.846172          538            0.000040         2.992447\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 509118  2.700801 -4.839852          539            2.991141         2.991983\n",
+       " 509119  2.702502 -4.840007          539            2.990250         2.991983\n",
+       " 509120  2.704204 -4.840083          539            2.989347         2.991983\n",
+       " 509121  2.705906 -4.840158          539            2.988443         2.991983\n",
+       " 509122  2.707608 -4.840233          539            2.987539         2.991983\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 509886  4.007708 -4.843500          539            0.000080         2.991983\n",
+       " 509887  4.009409 -4.843682          539            0.000071         2.991983\n",
+       " 509888  4.011111 -4.843864          539            0.000063         2.991983\n",
+       " 509889  4.012813 -4.844047          539            0.000054         2.991983\n",
+       " 509890  4.014514 -4.844229          539            0.000046         2.991983\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 510118  2.700801 -4.839811          540            2.991642         2.992752\n",
+       " 510119  2.702502 -4.839922          540            2.990740         2.992752\n",
+       " 510120  2.704204 -4.840074          540            2.989831         2.992752\n",
+       " 510121  2.705906 -4.840227          540            2.988923         2.992752\n",
+       " 510122  2.707608 -4.840238          540            2.987986         2.992752\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 510886  4.007708 -4.844622          540            0.000081         2.992752\n",
+       " 510887  4.009409 -4.844849          540            0.000073         2.992752\n",
+       " 510888  4.011111 -4.845076          540            0.000064         2.992752\n",
+       " 510889  4.012813 -4.845303          540            0.000056         2.992752\n",
+       " 510890  4.014514 -4.845530          540            0.000047         2.992752\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 511118  2.700801 -4.840260          541            2.990760         2.991352\n",
+       " 511119  2.702502 -4.839977          541            2.989853         2.991352\n",
+       " 511120  2.704204 -4.839901          541            2.988936         2.991352\n",
+       " 511121  2.705906 -4.839827          541            2.988019         2.991352\n",
+       " 511122  2.707608 -4.839752          541            2.987105         2.991352\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 511886  4.007708 -4.843294          541            0.000081         2.991352\n",
+       " 511887  4.009409 -4.843466          541            0.000073         2.991352\n",
+       " 511888  4.011111 -4.843639          541            0.000064         2.991352\n",
+       " 511889  4.012813 -4.843812          541            0.000055         2.991352\n",
+       " 511890  4.014514 -4.843984          541            0.000047         2.991352\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 512118  2.700801 -4.840088          542            2.990079         2.990973\n",
+       " 512119  2.702502 -4.840238          542            2.989187         2.990973\n",
+       " 512120  2.704204 -4.840238          542            2.988279         2.990973\n",
+       " 512121  2.705906 -4.840238          542            2.987371         2.990973\n",
+       " 512122  2.707608 -4.840238          542            2.986462         2.990973\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 512887  4.009409 -4.844076          542            0.000074         2.990973\n",
+       " 512888  4.011111 -4.844258          542            0.000066         2.990973\n",
+       " 512889  4.012813 -4.844440          542            0.000057         2.990973\n",
+       " 512890  4.014514 -4.844622          542            0.000049         2.990973\n",
+       " 512891  4.016216 -4.844804          542            0.000040         2.990973\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 513118  2.700801 -4.839712          543            2.990131         2.990149\n",
+       " 513119  2.702502 -4.839567          543            2.989180         2.990149\n",
+       " 513120  2.704204 -4.839617          543            2.988295         2.990149\n",
+       " 513121  2.705906 -4.839690          543            2.987417         2.990149\n",
+       " 513122  2.707608 -4.839763          543            2.986538         2.990149\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 513887  4.009409 -4.843335          543            0.000075         2.990149\n",
+       " 513888  4.011111 -4.843472          543            0.000067         2.990149\n",
+       " 513889  4.012813 -4.843610          543            0.000058         2.990149\n",
+       " 513890  4.014514 -4.843748          543            0.000049         2.990149\n",
+       " 513891  4.016216 -4.843885          543            0.000041         2.990149\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 514118  2.700801 -4.839876          544            2.987500         2.990146\n",
+       " 514119  2.702502 -4.839960          544            2.986567         2.990146\n",
+       " 514120  2.704204 -4.839816          544            2.985705         2.990146\n",
+       " 514121  2.705906 -4.839672          544            2.984843         2.990146\n",
+       " 514122  2.707608 -4.839551          544            2.983969         2.990146\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 514887  4.009409 -4.845157          544            0.000076         2.990146\n",
+       " 514888  4.011111 -4.845406          544            0.000067         2.990146\n",
+       " 514889  4.012813 -4.845654          544            0.000058         2.990146\n",
+       " 514890  4.014514 -4.845902          544            0.000050         2.990146\n",
+       " 514891  4.016216 -4.846150          544            0.000041         2.990146\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 515118  2.700801 -4.839831          545            2.987985         2.987757\n",
+       " 515119  2.702502 -4.839940          545            2.987072         2.987757\n",
+       " 515120  2.704204 -4.839983          545            2.986151         2.987757\n",
+       " 515121  2.705906 -4.839909          545            2.985212         2.987757\n",
+       " 515122  2.707608 -4.839835          545            2.984273         2.987757\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 515887  4.009409 -4.844974          545            0.000077         2.987757\n",
+       " 515888  4.011111 -4.845204          545            0.000068         2.987757\n",
+       " 515889  4.012813 -4.845434          545            0.000060         2.987757\n",
+       " 515890  4.014514 -4.845664          545            0.000051         2.987757\n",
+       " 515891  4.016216 -4.845893          545            0.000042         2.987757\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 516118  2.700801 -4.840009          546            2.983804         2.985956\n",
+       " 516119  2.702502 -4.840009          546            2.982921         2.985956\n",
+       " 516120  2.704204 -4.840009          546            2.982016         2.985956\n",
+       " 516121  2.705906 -4.840009          546            2.981108         2.985956\n",
+       " 516122  2.707608 -4.840009          546            2.980200         2.985956\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 516886  4.007708 -4.844070          546            0.000081         2.985956\n",
+       " 516887  4.009409 -4.844274          546            0.000073         2.985956\n",
+       " 516888  4.011111 -4.844477          546            0.000064         2.985956\n",
+       " 516889  4.012813 -4.844680          546            0.000055         2.985956\n",
+       " 516890  4.014514 -4.844883          546            0.000047         2.985956\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 517118  2.700801 -4.839780          547            2.984132          2.98494\n",
+       " 517119  2.702502 -4.839780          547            2.983233          2.98494\n",
+       " 517120  2.704204 -4.839724          547            2.982297          2.98494\n",
+       " 517121  2.705906 -4.839650          547            2.981349          2.98494\n",
+       " 517122  2.707608 -4.839576          547            2.980402          2.98494\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 517886  4.007708 -4.843966          547            0.000082          2.98494\n",
+       " 517887  4.009409 -4.844187          547            0.000073          2.98494\n",
+       " 517888  4.011111 -4.844408          547            0.000065          2.98494\n",
+       " 517889  4.012813 -4.844628          547            0.000056          2.98494\n",
+       " 517890  4.014514 -4.844849          547            0.000047          2.98494\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 518118  2.700801 -4.840125          548            2.983507         2.983284\n",
+       " 518119  2.702502 -4.839931          548            2.982612         2.983284\n",
+       " 518120  2.704204 -4.839780          548            2.981708         2.983284\n",
+       " 518121  2.705906 -4.839630          548            2.980804         2.983284\n",
+       " 518122  2.707608 -4.839587          548            2.979887         2.983284\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 518886  4.007708 -4.843826          548            0.000080         2.983284\n",
+       " 518887  4.009409 -4.844038          548            0.000071         2.983284\n",
+       " 518888  4.011111 -4.844251          548            0.000063         2.983284\n",
+       " 518889  4.012813 -4.844463          548            0.000054         2.983284\n",
+       " 518890  4.014514 -4.844675          548            0.000045         2.983284\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 519118  2.700801 -4.839997          549            2.983749         2.984659\n",
+       " 519119  2.702502 -4.840165          549            2.982861         2.984659\n",
+       " 519120  2.704204 -4.840013          549            2.981970         2.984659\n",
+       " 519121  2.705906 -4.839860          549            2.981079         2.984659\n",
+       " 519122  2.707608 -4.839853          549            2.980165         2.984659\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 519886  4.007708 -4.845357          549            0.000082         2.984659\n",
+       " 519887  4.009409 -4.845621          549            0.000073         2.984659\n",
+       " 519888  4.011111 -4.845885          549            0.000064         2.984659\n",
+       " 519889  4.012813 -4.846149          549            0.000056         2.984659\n",
+       " 519890  4.014514 -4.846413          549            0.000047         2.984659\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 520118  2.700801 -4.839780          550            2.982798         2.983827\n",
+       " 520119  2.702502 -4.839780          550            2.981892         2.983827\n",
+       " 520120  2.704204 -4.839744          550            2.980978         2.983827\n",
+       " 520121  2.705906 -4.839670          550            2.980057         2.983827\n",
+       " 520122  2.707608 -4.839596          550            2.979135         2.983827\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 520886  4.007708 -4.843855          550            0.000081         2.983827\n",
+       " 520887  4.009409 -4.844056          550            0.000072         2.983827\n",
+       " 520888  4.011111 -4.844256          550            0.000064         2.983827\n",
+       " 520889  4.012813 -4.844456          550            0.000055         2.983827\n",
+       " 520890  4.014514 -4.844656          550            0.000047         2.983827\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 521118  2.700801 -4.839824          551            2.983734         2.984043\n",
+       " 521119  2.702502 -4.839919          551            2.982846         2.984043\n",
+       " 521120  2.704204 -4.840013          551            2.981956         2.984043\n",
+       " 521121  2.705906 -4.840088          551            2.981034         2.984043\n",
+       " 521122  2.707608 -4.840163          551            2.980112         2.984043\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 521886  4.007708 -4.843203          551            0.000081         2.984043\n",
+       " 521887  4.009409 -4.843349          551            0.000072         2.984043\n",
+       " 521888  4.011111 -4.843494          551            0.000064         2.984043\n",
+       " 521889  4.012813 -4.843639          551            0.000055         2.984043\n",
+       " 521890  4.014514 -4.843784          551            0.000047         2.984043\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 522118  2.700801 -4.840009          552            2.984543          2.98358\n",
+       " 522119  2.702502 -4.839961          552            2.983661          2.98358\n",
+       " 522120  2.704204 -4.839887          552            2.982779          2.98358\n",
+       " 522121  2.705906 -4.839812          552            2.981896          2.98358\n",
+       " 522122  2.707608 -4.839823          552            2.980992          2.98358\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 522886  4.007708 -4.843179          552            0.000080          2.98358\n",
+       " 522887  4.009409 -4.843334          552            0.000071          2.98358\n",
+       " 522888  4.011111 -4.843488          552            0.000062          2.98358\n",
+       " 522889  4.012813 -4.843643          552            0.000054          2.98358\n",
+       " 522890  4.014514 -4.843798          552            0.000045          2.98358\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 523118  2.700801 -4.840009          553            2.984936         2.985169\n",
+       " 523119  2.702502 -4.840195          553            2.984058         2.985169\n",
+       " 523120  2.704204 -4.840417          553            2.983180         2.985169\n",
+       " 523121  2.705906 -4.840639          553            2.982302         2.985169\n",
+       " 523122  2.707608 -4.840586          553            2.981385         2.985169\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 523886  4.007708 -4.843949          553            0.000080         2.985169\n",
+       " 523887  4.009409 -4.844130          553            0.000072         2.985169\n",
+       " 523888  4.011111 -4.844310          553            0.000063         2.985169\n",
+       " 523889  4.012813 -4.844491          553            0.000055         2.985169\n",
+       " 523890  4.014514 -4.844672          553            0.000046         2.985169\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 524118  2.700801 -4.840009          554            2.984859         2.984819\n",
+       " 524119  2.702502 -4.840009          554            2.983987         2.984819\n",
+       " 524120  2.704204 -4.839966          554            2.983099         2.984819\n",
+       " 524121  2.705906 -4.839892          554            2.982200         2.984819\n",
+       " 524122  2.707608 -4.839818          554            2.981300         2.984819\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 524886  4.007708 -4.843344          554            0.000079         2.984819\n",
+       " 524887  4.009409 -4.843516          554            0.000070         2.984819\n",
+       " 524888  4.011111 -4.843688          554            0.000062         2.984819\n",
+       " 524889  4.012813 -4.843859          554            0.000053         2.984819\n",
+       " 524890  4.014514 -4.844031          554            0.000045         2.984819\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 525118  2.700801 -4.839611          555            2.983722         2.985327\n",
+       " 525119  2.702502 -4.839551          555            2.982841         2.985327\n",
+       " 525120  2.704204 -4.839551          555            2.981955         2.985327\n",
+       " 525121  2.705906 -4.839551          555            2.981068         2.985327\n",
+       " 525122  2.707608 -4.839679          555            2.980156         2.985327\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 525886  4.007708 -4.843946          555            0.000079         2.985327\n",
+       " 525887  4.009409 -4.844134          555            0.000070         2.985327\n",
+       " 525888  4.011111 -4.844323          555            0.000062         2.985327\n",
+       " 525889  4.012813 -4.844511          555            0.000053         2.985327\n",
+       " 525890  4.014514 -4.844699          555            0.000045         2.985327\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 526118  2.700801 -4.839780          556            2.982692         2.983575\n",
+       " 526119  2.702502 -4.839780          556            2.981788         2.983575\n",
+       " 526120  2.704204 -4.839780          556            2.980884         2.983575\n",
+       " 526121  2.705906 -4.839812          556            2.979969         2.983575\n",
+       " 526122  2.707608 -4.839888          556            2.979038         2.983575\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 526886  4.007708 -4.842792          556            0.000078         2.983575\n",
+       " 526887  4.009409 -4.842935          556            0.000070         2.983575\n",
+       " 526888  4.011111 -4.843079          556            0.000061         2.983575\n",
+       " 526889  4.012813 -4.843223          556            0.000053         2.983575\n",
+       " 526890  4.014514 -4.843367          556            0.000044         2.983575\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 527118  2.700801 -4.840227          557            2.982127          2.98318\n",
+       " 527119  2.702502 -4.840153          557            2.981215          2.98318\n",
+       " 527120  2.704204 -4.840079          557            2.980302          2.98318\n",
+       " 527121  2.705906 -4.840005          557            2.979389          2.98318\n",
+       " 527122  2.707608 -4.839931          557            2.978472          2.98318\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 527886  4.007708 -4.843952          557            0.000078          2.98318\n",
+       " 527887  4.009409 -4.844143          557            0.000070          2.98318\n",
+       " 527888  4.011111 -4.844334          557            0.000061          2.98318\n",
+       " 527889  4.012813 -4.844524          557            0.000053          2.98318\n",
+       " 527890  4.014514 -4.844715          557            0.000044          2.98318\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 528118  2.700801 -4.839780          558            2.982540         2.983217\n",
+       " 528119  2.702502 -4.839780          558            2.981664         2.983217\n",
+       " 528120  2.704204 -4.839780          558            2.980790         2.983217\n",
+       " 528121  2.705906 -4.839780          558            2.979917         2.983217\n",
+       " 528122  2.707608 -4.839828          558            2.979012         2.983217\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 528886  4.007708 -4.842811          558            0.000079         2.983217\n",
+       " 528887  4.009409 -4.842946          558            0.000071         2.983217\n",
+       " 528888  4.011111 -4.843081          558            0.000062         2.983217\n",
+       " 528889  4.012813 -4.843217          558            0.000054         2.983217\n",
+       " 528890  4.014514 -4.843353          558            0.000045         2.983217\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 529118  2.700801 -4.840009          559            2.982314         2.983137\n",
+       " 529119  2.702502 -4.840059          559            2.981425         2.983137\n",
+       " 529120  2.704204 -4.840134          559            2.980517         2.983137\n",
+       " 529121  2.705906 -4.840209          559            2.979609         2.983137\n",
+       " 529122  2.707608 -4.840192          559            2.978695         2.983137\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 529886  4.007708 -4.843931          559            0.000079         2.983137\n",
+       " 529887  4.009409 -4.844121          559            0.000071         2.983137\n",
+       " 529888  4.011111 -4.844311          559            0.000062         2.983137\n",
+       " 529889  4.012813 -4.844501          559            0.000054         2.983137\n",
+       " 529890  4.014514 -4.844690          559            0.000045         2.983137\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 530118  2.700801 -4.840123          560            2.980805         2.983101\n",
+       " 530119  2.702502 -4.840238          560            2.979918         2.983101\n",
+       " 530120  2.704204 -4.840238          560            2.979006         2.983101\n",
+       " 530121  2.705906 -4.840238          560            2.978093         2.983101\n",
+       " 530122  2.707608 -4.840133          560            2.977172         2.983101\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 530886  4.007708 -4.844245          560            0.000080         2.983101\n",
+       " 530887  4.009409 -4.844461          560            0.000072         2.983101\n",
+       " 530888  4.011111 -4.844678          560            0.000063         2.983101\n",
+       " 530889  4.012813 -4.844894          560            0.000055         2.983101\n",
+       " 530890  4.014514 -4.845111          560            0.000046         2.983101\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 531118  2.700801 -4.839921          566            3.162990         3.026593\n",
+       " 531119  2.702502 -4.840009          566            3.162141         3.026593\n",
+       " 531120  2.704204 -4.840009          566            3.161268         3.026593\n",
+       " 531121  2.705906 -4.840009          566            3.160395         3.026593\n",
+       " 531122  2.707608 -4.839906          566            3.159525         3.026593\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 531893  4.019619 -4.843458          566            0.000073         3.026593\n",
+       " 531894  4.021321 -4.843623          566            0.000065         3.026593\n",
+       " 531895  4.023023 -4.843788          566            0.000057         3.026593\n",
+       " 531896  4.024725 -4.843952          566            0.000048         3.026593\n",
+       " 531897  4.026426 -4.844117          566            0.000040         3.026593\n",
+       " \n",
+       " [780 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 532118  2.700801 -4.840062          567            3.139986         3.145168\n",
+       " 532119  2.702502 -4.840176          567            3.139133         3.145168\n",
+       " 532120  2.704204 -4.840204          567            3.138261         3.145168\n",
+       " 532121  2.705906 -4.840128          567            3.137366         3.145168\n",
+       " 532122  2.707608 -4.840052          567            3.136471         3.145168\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 532891  4.016216 -4.842170          567            0.000077         3.145168\n",
+       " 532892  4.017918 -4.842249          567            0.000069         3.145168\n",
+       " 532893  4.019619 -4.842329          567            0.000060         3.145168\n",
+       " 532894  4.021321 -4.842408          567            0.000052         3.145168\n",
+       " 532895  4.023023 -4.842487          567            0.000044         3.145168\n",
+       " \n",
+       " [778 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 533118  2.700801 -4.840009          568            3.123511         3.132801\n",
+       " 533119  2.702502 -4.840009          568            3.122646         3.132801\n",
+       " 533120  2.704204 -4.840019          568            3.121781         3.132801\n",
+       " 533121  2.705906 -4.840095          568            3.120912         3.132801\n",
+       " 533122  2.707608 -4.840169          568            3.120043         3.132801\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 533890  4.014514 -4.844137          568            0.000080         3.132801\n",
+       " 533891  4.016216 -4.844321          568            0.000072         3.132801\n",
+       " 533892  4.017918 -4.844506          568            0.000064         3.132801\n",
+       " 533893  4.019619 -4.844690          568            0.000056         3.132801\n",
+       " 533894  4.021321 -4.844875          568            0.000047         3.132801\n",
+       " \n",
+       " [777 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 534118  2.700801 -4.839869          569            3.107412         3.117882\n",
+       " 534119  2.702502 -4.840057          569            3.106563         3.117882\n",
+       " 534120  2.704204 -4.840235          569            3.105711         3.117882\n",
+       " 534121  2.705906 -4.840158          569            3.104802         3.117882\n",
+       " 534122  2.707608 -4.840082          569            3.103893         3.117882\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 534890  4.014514 -4.844017          569            0.000075         3.117882\n",
+       " 534891  4.016216 -4.844203          569            0.000067         3.117882\n",
+       " 534892  4.017918 -4.844389          569            0.000059         3.117882\n",
+       " 534893  4.019619 -4.844575          569            0.000050         3.117882\n",
+       " 534894  4.021321 -4.844761          569            0.000042         3.117882\n",
+       " \n",
+       " [777 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 535118  2.700801 -4.839426          570            3.093609         3.102015\n",
+       " 535119  2.702502 -4.839583          570            3.092722         3.102015\n",
+       " 535120  2.704204 -4.839658          570            3.091853         3.102015\n",
+       " 535121  2.705906 -4.839732          570            3.090984         3.102015\n",
+       " 535122  2.707608 -4.839806          570            3.090106         3.102015\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 535890  4.014514 -4.843913          570            0.000073         3.102015\n",
+       " 535891  4.016216 -4.844080          570            0.000065         3.102015\n",
+       " 535892  4.017918 -4.844248          570            0.000056         3.102015\n",
+       " 535893  4.019619 -4.844415          570            0.000048         3.102015\n",
+       " 535894  4.021321 -4.844583          570            0.000040         3.102015\n",
+       " \n",
+       " [777 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 536118  2.700801 -4.840113          571            3.081077         3.088463\n",
+       " 536119  2.702502 -4.840173          571            3.080206         3.088463\n",
+       " 536120  2.704204 -4.840023          571            3.079337         3.088463\n",
+       " 536121  2.705906 -4.839872          571            3.078469         3.088463\n",
+       " 536122  2.707608 -4.839809          571            3.077590         3.088463\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 536889  4.012813 -4.844122          571            0.000077         3.088463\n",
+       " 536890  4.014514 -4.844326          571            0.000069         3.088463\n",
+       " 536891  4.016216 -4.844530          571            0.000061         3.088463\n",
+       " 536892  4.017918 -4.844733          571            0.000052         3.088463\n",
+       " 536893  4.019619 -4.844936          571            0.000044         3.088463\n",
+       " \n",
+       " [776 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 537118  2.700801 -4.839780          572            3.071539         3.078038\n",
+       " 537119  2.702502 -4.839780          572            3.070682         3.078038\n",
+       " 537120  2.704204 -4.839780          572            3.069789         3.078038\n",
+       " 537121  2.705906 -4.839780          572            3.068868         3.078038\n",
+       " 537122  2.707608 -4.839780          572            3.067946         3.078038\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 537889  4.012813 -4.843193          572            0.000075         3.078038\n",
+       " 537890  4.014514 -4.843362          572            0.000066         3.078038\n",
+       " 537891  4.016216 -4.843532          572            0.000058         3.078038\n",
+       " 537892  4.017918 -4.843701          572            0.000050         3.078038\n",
+       " 537893  4.019619 -4.843871          572            0.000041         3.078038\n",
+       " \n",
+       " [776 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 538118  2.700801 -4.839889          573            3.063110         3.067744\n",
+       " 538119  2.702502 -4.839938          573            3.062234         3.067744\n",
+       " 538120  2.704204 -4.839790          573            3.061369         3.067744\n",
+       " 538121  2.705906 -4.839642          573            3.060505         3.067744\n",
+       " 538122  2.707608 -4.839581          573            3.059613         3.067744\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 538889  4.012813 -4.843469          573            0.000076         3.067744\n",
+       " 538890  4.014514 -4.843617          573            0.000068         3.067744\n",
+       " 538891  4.016216 -4.843766          573            0.000060         3.067744\n",
+       " 538892  4.017918 -4.843915          573            0.000052         3.067744\n",
+       " 538893  4.019619 -4.844063          573            0.000043         3.067744\n",
+       " \n",
+       " [776 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 539118  2.700801 -4.839950          574            3.054645         3.060006\n",
+       " 539119  2.702502 -4.840222          574            3.053795         3.060006\n",
+       " 539120  2.704204 -4.840147          574            3.052926         3.060006\n",
+       " 539121  2.705906 -4.840072          574            3.052057         3.060006\n",
+       " 539122  2.707608 -4.839997          574            3.051180         3.060006\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 539888  4.011111 -4.845634          574            0.000080         3.060006\n",
+       " 539889  4.012813 -4.845889          574            0.000072         3.060006\n",
+       " 539890  4.014514 -4.846145          574            0.000063         3.060006\n",
+       " 539891  4.016216 -4.846400          574            0.000055         3.060006\n",
+       " 539892  4.017918 -4.846656          574            0.000047         3.060006\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 540118  2.700801 -4.839393          575            3.047050         3.052189\n",
+       " 540119  2.702502 -4.839543          575            3.046177         3.052189\n",
+       " 540120  2.704204 -4.839693          575            3.045304         3.052189\n",
+       " 540121  2.705906 -4.839812          575            3.044429         3.052189\n",
+       " 540122  2.707608 -4.839888          575            3.043552         3.052189\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 540888  4.011111 -4.843670          575            0.000079         3.052189\n",
+       " 540889  4.012813 -4.843864          575            0.000071         3.052189\n",
+       " 540890  4.014514 -4.844059          575            0.000062         3.052189\n",
+       " 540891  4.016216 -4.844253          575            0.000054         3.052189\n",
+       " 540892  4.017918 -4.844446          575            0.000046         3.052189\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 541118  2.700801 -4.840229          576            3.039832         3.043849\n",
+       " 541119  2.702502 -4.840078          576            3.038937         3.043849\n",
+       " 541120  2.704204 -4.839929          576            3.038042         3.043849\n",
+       " 541121  2.705906 -4.839781          576            3.037146         3.043849\n",
+       " 541122  2.707608 -4.839857          576            3.036247         3.043849\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 541888  4.011111 -4.842843          576            0.000075         3.043849\n",
+       " 541889  4.012813 -4.842984          576            0.000067         3.043849\n",
+       " 541890  4.014514 -4.843126          576            0.000058         3.043849\n",
+       " 541891  4.016216 -4.843268          576            0.000050         3.043849\n",
+       " 541892  4.017918 -4.843410          576            0.000042         3.043849\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 542118  2.700801 -4.839744          577            3.035814         3.039321\n",
+       " 542119  2.702502 -4.839667          577            3.034919         3.039321\n",
+       " 542120  2.704204 -4.839590          577            3.034024         3.039321\n",
+       " 542121  2.705906 -4.839551          577            3.033129         3.039321\n",
+       " 542122  2.707608 -4.839551          577            3.032233         3.039321\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 542888  4.011111 -4.845170          577            0.000075         3.039321\n",
+       " 542889  4.012813 -4.845408          577            0.000067         3.039321\n",
+       " 542890  4.014514 -4.845646          577            0.000059         3.039321\n",
+       " 542891  4.016216 -4.845885          577            0.000050         3.039321\n",
+       " 542892  4.017918 -4.846123          577            0.000042         3.039321\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 543118  2.700801 -4.839780          578            3.030772         3.033997\n",
+       " 543119  2.702502 -4.839780          578            3.029906         3.033997\n",
+       " 543120  2.704204 -4.839791          578            3.029038         3.033997\n",
+       " 543121  2.705906 -4.840019          578            3.028134         3.033997\n",
+       " 543122  2.707608 -4.840248          578            3.027230         3.033997\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 543888  4.011111 -4.842948          578            0.000075         3.033997\n",
+       " 543889  4.012813 -4.843062          578            0.000067         3.033997\n",
+       " 543890  4.014514 -4.843177          578            0.000059         3.033997\n",
+       " 543891  4.016216 -4.843291          578            0.000051         3.033997\n",
+       " 543892  4.017918 -4.843406          578            0.000042         3.033997\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 544118  2.700801 -4.840198          579            3.030466         3.033427\n",
+       " 544119  2.702502 -4.840111          579            3.029576         3.033427\n",
+       " 544120  2.704204 -4.840025          579            3.028687         3.033427\n",
+       " 544121  2.705906 -4.839824          579            3.027811         3.033427\n",
+       " 544122  2.707608 -4.839599          579            3.026938         3.033427\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 544888  4.011111 -4.844366          579            0.000075         3.033427\n",
+       " 544889  4.012813 -4.844578          579            0.000067         3.033427\n",
+       " 544890  4.014514 -4.844790          579            0.000059         3.033427\n",
+       " 544891  4.016216 -4.845003          579            0.000050         3.033427\n",
+       " 544892  4.017918 -4.845215          579            0.000042         3.033427\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 545118  2.700801 -4.839975          580            3.023021         3.026177\n",
+       " 545119  2.702502 -4.839902          580            3.022139         3.026177\n",
+       " 545120  2.704204 -4.839829          580            3.021256         3.026177\n",
+       " 545121  2.705906 -4.839852          580            3.020378         3.026177\n",
+       " 545122  2.707608 -4.840071          580            3.019508         3.026177\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 545888  4.011111 -4.843807          580            0.000073         3.026177\n",
+       " 545889  4.012813 -4.844002          580            0.000065         3.026177\n",
+       " 545890  4.014514 -4.844196          580            0.000056         3.026177\n",
+       " 545891  4.016216 -4.844391          580            0.000048         3.026177\n",
+       " 545892  4.017918 -4.844585          580            0.000040         3.026177\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 546118  2.700801 -4.839768          581            3.024019         3.024142\n",
+       " 546119  2.702502 -4.839780          581            3.023143         3.024142\n",
+       " 546120  2.704204 -4.839780          581            3.022266         3.024142\n",
+       " 546121  2.705906 -4.839780          581            3.021388         3.024142\n",
+       " 546122  2.707608 -4.839780          581            3.020494         3.024142\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 546888  4.011111 -4.843308          581            0.000074         3.024142\n",
+       " 546889  4.012813 -4.843450          581            0.000066         3.024142\n",
+       " 546890  4.014514 -4.843591          581            0.000058         3.024142\n",
+       " 546891  4.016216 -4.843732          581            0.000050         3.024142\n",
+       " 546892  4.017918 -4.843874          581            0.000041         3.024142\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 547118  2.700801 -4.839692          582            3.020598         3.023471\n",
+       " 547119  2.702502 -4.839611          582            3.019714         3.023471\n",
+       " 547120  2.704204 -4.839686          582            3.018823         3.023471\n",
+       " 547121  2.705906 -4.839761          582            3.017932         3.023471\n",
+       " 547122  2.707608 -4.839892          582            3.017025         3.023471\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 547888  4.011111 -4.845057          582            0.000074         3.023471\n",
+       " 547889  4.012813 -4.845278          582            0.000065         3.023471\n",
+       " 547890  4.014514 -4.845498          582            0.000057         3.023471\n",
+       " 547891  4.016216 -4.845718          582            0.000049         3.023471\n",
+       " 547892  4.017918 -4.845939          582            0.000041         3.023471\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 548118  2.700801 -4.840009          583            3.015847          3.01946\n",
+       " 548119  2.702502 -4.840009          583            3.014948          3.01946\n",
+       " 548120  2.704204 -4.840009          583            3.014048          3.01946\n",
+       " 548121  2.705906 -4.840009          583            3.013153          3.01946\n",
+       " 548122  2.707608 -4.840009          583            3.012270          3.01946\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 548887  4.009409 -4.842784          583            0.000081          3.01946\n",
+       " 548888  4.011111 -4.842916          583            0.000073          3.01946\n",
+       " 548889  4.012813 -4.843050          583            0.000064          3.01946\n",
+       " 548890  4.014514 -4.843182          583            0.000056          3.01946\n",
+       " 548891  4.016216 -4.843315          583            0.000048          3.01946\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 549118  2.700801 -4.840009          584            3.011873         3.015098\n",
+       " 549119  2.702502 -4.840009          584            3.010986         3.015098\n",
+       " 549120  2.704204 -4.840009          584            3.010100         3.015098\n",
+       " 549121  2.705906 -4.839984          584            3.009211         3.015098\n",
+       " 549122  2.707608 -4.839910          584            3.008315         3.015098\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 549887  4.009409 -4.842053          584            0.000080         3.015098\n",
+       " 549888  4.011111 -4.842151          584            0.000072         3.015098\n",
+       " 549889  4.012813 -4.842248          584            0.000064         3.015098\n",
+       " 549890  4.014514 -4.842345          584            0.000055         3.015098\n",
+       " 549891  4.016216 -4.842442          584            0.000047         3.015098\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 550118  2.700801 -4.839821          585            3.009374         3.010509\n",
+       " 550119  2.702502 -4.839907          585            3.008490         3.010509\n",
+       " 550120  2.704204 -4.839993          585            3.007606         3.010509\n",
+       " 550121  2.705906 -4.840009          585            3.006719         3.010509\n",
+       " 550122  2.707608 -4.840009          585            3.005833         3.010509\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 550887  4.009409 -4.843400          585            0.000080         3.010509\n",
+       " 550888  4.011111 -4.843550          585            0.000072         3.010509\n",
+       " 550889  4.012813 -4.843699          585            0.000063         3.010509\n",
+       " 550890  4.014514 -4.843849          585            0.000055         3.010509\n",
+       " 550891  4.016216 -4.843998          585            0.000047         3.010509\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 551118  2.700801 -4.840009          586            3.006566         3.008822\n",
+       " 551119  2.702502 -4.840009          586            3.005684         3.008822\n",
+       " 551120  2.704204 -4.839993          586            3.004800         3.008822\n",
+       " 551121  2.705906 -4.839917          586            3.003910         3.008822\n",
+       " 551122  2.707608 -4.839842          586            3.003019         3.008822\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 551887  4.009409 -4.844641          586            0.000079         3.008822\n",
+       " 551888  4.011111 -4.844869          586            0.000071         3.008822\n",
+       " 551889  4.012813 -4.845097          586            0.000063         3.008822\n",
+       " 551890  4.014514 -4.845325          586            0.000054         3.008822\n",
+       " 551891  4.016216 -4.845553          586            0.000046         3.008822\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 552118  2.700801 -4.839736          587            3.004979         3.005959\n",
+       " 552119  2.702502 -4.839642          587            3.004096         3.005959\n",
+       " 552120  2.704204 -4.839562          587            3.003212         3.005959\n",
+       " 552121  2.705906 -4.839790          587            3.002308         3.005959\n",
+       " 552122  2.707608 -4.840019          587            3.001404         3.005959\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 552887  4.009409 -4.844389          587            0.000078         3.005959\n",
+       " 552888  4.011111 -4.844583          587            0.000069         3.005959\n",
+       " 552889  4.012813 -4.844777          587            0.000061         3.005959\n",
+       " 552890  4.014514 -4.844971          587            0.000053         3.005959\n",
+       " 552891  4.016216 -4.845165          587            0.000044         3.005959\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 553118  2.700801 -4.839941          588            3.003238          3.00511\n",
+       " 553119  2.702502 -4.839796          588            3.002313          3.00511\n",
+       " 553120  2.704204 -4.839909          588            3.001441          3.00511\n",
+       " 553121  2.705906 -4.840053          588            3.000575          3.00511\n",
+       " 553122  2.707608 -4.840197          588            2.999709          3.00511\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 553887  4.009409 -4.844471          588            0.000078          3.00511\n",
+       " 553888  4.011111 -4.844691          588            0.000070          3.00511\n",
+       " 553889  4.012813 -4.844911          588            0.000062          3.00511\n",
+       " 553890  4.014514 -4.845130          588            0.000054          3.00511\n",
+       " 553891  4.016216 -4.845350          588            0.000045          3.00511\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 554118  2.700801 -4.840009          589            3.003014         3.003981\n",
+       " 554119  2.702502 -4.840009          589            3.002153         3.003981\n",
+       " 554120  2.704204 -4.840009          589            3.001279         3.003981\n",
+       " 554121  2.705906 -4.840009          589            3.000388         3.003981\n",
+       " 554122  2.707608 -4.840009          589            2.999498         3.003981\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 554887  4.009409 -4.845691          589            0.000078         3.003981\n",
+       " 554888  4.011111 -4.845946          589            0.000070         3.003981\n",
+       " 554889  4.012813 -4.846201          589            0.000062         3.003981\n",
+       " 554890  4.014514 -4.846456          589            0.000053         3.003981\n",
+       " 554891  4.016216 -4.846711          589            0.000045         3.003981\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 555118  2.700801 -4.839935          590            3.001283          3.00382\n",
+       " 555119  2.702502 -4.839783          590            3.000348          3.00382\n",
+       " 555120  2.704204 -4.839857          590            2.999484          3.00382\n",
+       " 555121  2.705906 -4.839931          590            2.998619          3.00382\n",
+       " 555122  2.707608 -4.840004          590            2.997754          3.00382\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 555887  4.009409 -4.845693          590            0.000078          3.00382\n",
+       " 555888  4.011111 -4.845948          590            0.000070          3.00382\n",
+       " 555889  4.012813 -4.846202          590            0.000062          3.00382\n",
+       " 555890  4.014514 -4.846457          590            0.000053          3.00382\n",
+       " 555891  4.016216 -4.846711          590            0.000045          3.00382\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 556118  2.700801 -4.840310          591            3.000104         3.001448\n",
+       " 556119  2.702502 -4.840465          591            2.999204         3.001448\n",
+       " 556120  2.704204 -4.840321          591            2.998318         3.001448\n",
+       " 556121  2.705906 -4.840173          591            2.997431         3.001448\n",
+       " 556122  2.707608 -4.840025          591            2.996545         3.001448\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 556887  4.009409 -4.845062          591            0.000078         3.001448\n",
+       " 556888  4.011111 -4.845309          591            0.000069         3.001448\n",
+       " 556889  4.012813 -4.845556          591            0.000061         3.001448\n",
+       " 556890  4.014514 -4.845804          591            0.000053         3.001448\n",
+       " 556891  4.016216 -4.846051          591            0.000044         3.001448\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 557118  2.700801 -4.839731          592            2.998841         3.000447\n",
+       " 557119  2.702502 -4.839624          592            2.997973         3.000447\n",
+       " 557120  2.704204 -4.839622          592            2.997092         3.000447\n",
+       " 557121  2.705906 -4.839848          592            2.996184         3.000447\n",
+       " 557122  2.707608 -4.840073          592            2.995275         3.000447\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 557887  4.009409 -4.843943          592            0.000077         3.000447\n",
+       " 557888  4.011111 -4.844137          592            0.000069         3.000447\n",
+       " 557889  4.012813 -4.844330          592            0.000060         3.000447\n",
+       " 557890  4.014514 -4.844523          592            0.000052         3.000447\n",
+       " 557891  4.016216 -4.844717          592            0.000044         3.000447\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 558118  2.700801 -4.840009          593            2.997786         2.999197\n",
+       " 558119  2.702502 -4.840009          593            2.996902         2.999197\n",
+       " 558120  2.704204 -4.840009          593            2.996019         2.999197\n",
+       " 558121  2.705906 -4.840009          593            2.995141         2.999197\n",
+       " 558122  2.707608 -4.840009          593            2.994263         2.999197\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 558887  4.009409 -4.843351          593            0.000078         2.999197\n",
+       " 558888  4.011111 -4.843517          593            0.000070         2.999197\n",
+       " 558889  4.012813 -4.843683          593            0.000062         2.999197\n",
+       " 558890  4.014514 -4.843848          593            0.000054         2.999197\n",
+       " 558891  4.016216 -4.844014          593            0.000045         2.999197\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 559118  2.700801 -4.840009          594            2.995752         2.997432\n",
+       " 559119  2.702502 -4.840009          594            2.994917         2.997432\n",
+       " 559120  2.704204 -4.839982          594            2.994067         2.997432\n",
+       " 559121  2.705906 -4.839829          594            2.993149         2.997432\n",
+       " 559122  2.707608 -4.839677          594            2.992232         2.997432\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 559887  4.009409 -4.845539          594            0.000076         2.997432\n",
+       " 559888  4.011111 -4.845794          594            0.000067         2.997432\n",
+       " 559889  4.012813 -4.846050          594            0.000059         2.997432\n",
+       " 559890  4.014514 -4.846306          594            0.000051         2.997432\n",
+       " 559891  4.016216 -4.846561          594            0.000042         2.997432\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 560118  2.700801 -4.839780          595            2.994251         2.995718\n",
+       " 560119  2.702502 -4.839780          595            2.993370         2.995718\n",
+       " 560120  2.704204 -4.839780          595            2.992482         2.995718\n",
+       " 560121  2.705906 -4.839780          595            2.991578         2.995718\n",
+       " 560122  2.707608 -4.839780          595            2.990674         2.995718\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 560887  4.009409 -4.844066          595            0.000075         2.995718\n",
+       " 560888  4.011111 -4.844243          595            0.000067         2.995718\n",
+       " 560889  4.012813 -4.844419          595            0.000058         2.995718\n",
+       " 560890  4.014514 -4.844596          595            0.000050         2.995718\n",
+       " 560891  4.016216 -4.844772          595            0.000042         2.995718\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 561118  2.700801 -4.839817          596            2.991636         2.992777\n",
+       " 561119  2.702502 -4.839894          596            2.990768         2.992777\n",
+       " 561120  2.704204 -4.839971          596            2.989900         2.992777\n",
+       " 561121  2.705906 -4.839971          596            2.989032         2.992777\n",
+       " 561122  2.707608 -4.839896          596            2.988163         2.992777\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 561887  4.009409 -4.843037          596            0.000077         2.992777\n",
+       " 561888  4.011111 -4.843177          596            0.000069         2.992777\n",
+       " 561889  4.012813 -4.843318          596            0.000060         2.992777\n",
+       " 561890  4.014514 -4.843459          596            0.000052         2.992777\n",
+       " 561891  4.016216 -4.843599          596            0.000044         2.992777\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 562118  2.700801 -4.839571          597            2.989213         2.990068\n",
+       " 562119  2.702502 -4.839120          597            2.988340         2.990068\n",
+       " 562120  2.704204 -4.839300          597            2.987450         2.990068\n",
+       " 562121  2.705906 -4.839519          597            2.986559         2.990068\n",
+       " 562122  2.707608 -4.839737          597            2.985668         2.990068\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 562887  4.009409 -4.845183          597            0.000076         2.990068\n",
+       " 562888  4.011111 -4.845413          597            0.000068         2.990068\n",
+       " 562889  4.012813 -4.845643          597            0.000059         2.990068\n",
+       " 562890  4.014514 -4.845872          597            0.000051         2.990068\n",
+       " 562891  4.016216 -4.846102          597            0.000043         2.990068\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 563118  2.700801 -4.839780          598            2.986760         2.987819\n",
+       " 563119  2.702502 -4.839734          598            2.985860         2.987819\n",
+       " 563120  2.704204 -4.839657          598            2.984969         2.987819\n",
+       " 563121  2.705906 -4.839581          598            2.984078         2.987819\n",
+       " 563122  2.707608 -4.839551          598            2.983196         2.987819\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 563887  4.009409 -4.843224          598            0.000075         2.987819\n",
+       " 563888  4.011111 -4.843383          598            0.000067         2.987819\n",
+       " 563889  4.012813 -4.843543          598            0.000058         2.987819\n",
+       " 563890  4.014514 -4.843702          598            0.000050         2.987819\n",
+       " 563891  4.016216 -4.843861          598            0.000042         2.987819\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 564118  2.700801 -4.839921          599            2.984217         2.985953\n",
+       " 564119  2.702502 -4.840220          599            2.983326         2.985953\n",
+       " 564120  2.704204 -4.840168          599            2.982431         2.985953\n",
+       " 564121  2.705906 -4.840095          599            2.981536         2.985953\n",
+       " 564122  2.707608 -4.840021          599            2.980641         2.985953\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 564887  4.009409 -4.842308          599            0.000075         2.985953\n",
+       " 564888  4.011111 -4.842413          599            0.000067         2.985953\n",
+       " 564889  4.012813 -4.842519          599            0.000058         2.985953\n",
+       " 564890  4.014514 -4.842624          599            0.000050         2.985953\n",
+       " 564891  4.016216 -4.842730          599            0.000042         2.985953\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 565118  2.700801 -4.839865          600            2.983349         2.983616\n",
+       " 565119  2.702502 -4.840025          600            2.982477         2.983616\n",
+       " 565120  2.704204 -4.840100          600            2.981626         2.983616\n",
+       " 565121  2.705906 -4.840175          600            2.980774         2.983616\n",
+       " 565122  2.707608 -4.840250          600            2.979912         2.983616\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 565887  4.009409 -4.845180          600            0.000074         2.983616\n",
+       " 565888  4.011111 -4.845425          600            0.000065         2.983616\n",
+       " 565889  4.012813 -4.845671          600            0.000057         2.983616\n",
+       " 565890  4.014514 -4.845916          600            0.000049         2.983616\n",
+       " 565891  4.016216 -4.846162          600            0.000041         2.983616\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 566118  2.700801 -4.839932          601            2.983464         2.984224\n",
+       " 566119  2.702502 -4.840258          601            2.982603         2.984224\n",
+       " 566120  2.704204 -4.840386          601            2.981725         2.984224\n",
+       " 566121  2.705906 -4.840161          601            2.980817         2.984224\n",
+       " 566122  2.707608 -4.839936          601            2.979908         2.984224\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 566887  4.009409 -4.843505          601            0.000074         2.984224\n",
+       " 566888  4.011111 -4.843654          601            0.000066         2.984224\n",
+       " 566889  4.012813 -4.843802          601            0.000058         2.984224\n",
+       " 566890  4.014514 -4.843951          601            0.000050         2.984224\n",
+       " 566891  4.016216 -4.844100          601            0.000041         2.984224\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 567118  2.700801 -4.840003          602            2.982358         2.982872\n",
+       " 567119  2.702502 -4.840465          602            2.981459         2.982872\n",
+       " 567120  2.704204 -4.840392          602            2.980598         2.982872\n",
+       " 567121  2.705906 -4.840319          602            2.979737         2.982872\n",
+       " 567122  2.707608 -4.840246          602            2.978876         2.982872\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 567886  4.007708 -4.844296          602            0.000080         2.982872\n",
+       " 567887  4.009409 -4.844500          602            0.000071         2.982872\n",
+       " 567888  4.011111 -4.844704          602            0.000063         2.982872\n",
+       " 567889  4.012813 -4.844907          602            0.000055         2.982872\n",
+       " 567890  4.014514 -4.845111          602            0.000046         2.982872\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 568118  2.700801 -4.840269          603            2.981430         2.981964\n",
+       " 568119  2.702502 -4.840037          603            2.980552         2.981964\n",
+       " 568120  2.704204 -4.840109          603            2.979707         2.981964\n",
+       " 568121  2.705906 -4.840181          603            2.978863         2.981964\n",
+       " 568122  2.707608 -4.840238          603            2.978013         2.981964\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 568886  4.007708 -4.844615          603            0.000080         2.981964\n",
+       " 568887  4.009409 -4.844841          603            0.000072         2.981964\n",
+       " 568888  4.011111 -4.845068          603            0.000064         2.981964\n",
+       " 568889  4.012813 -4.845294          603            0.000056         2.981964\n",
+       " 568890  4.014514 -4.845520          603            0.000047         2.981964\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 569118  2.700801 -4.840009          604            2.981855         2.981639\n",
+       " 569119  2.702502 -4.839980          604            2.981016         2.981639\n",
+       " 569120  2.704204 -4.839905          604            2.980157         2.981639\n",
+       " 569121  2.705906 -4.839830          604            2.979297         2.981639\n",
+       " 569122  2.707608 -4.839780          604            2.978429         2.981639\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 569886  4.007708 -4.844369          604            0.000079         2.981639\n",
+       " 569887  4.009409 -4.844604          604            0.000071         2.981639\n",
+       " 569888  4.011111 -4.844838          604            0.000063         2.981639\n",
+       " 569889  4.012813 -4.845071          604            0.000055         2.981639\n",
+       " 569890  4.014514 -4.845305          604            0.000047         2.981639\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 570118  2.700801 -4.839655          605            2.981056         2.981422\n",
+       " 570119  2.702502 -4.839551          605            2.980200         2.981422\n",
+       " 570120  2.704204 -4.839551          605            2.979332         2.981422\n",
+       " 570121  2.705906 -4.839551          605            2.978463         2.981422\n",
+       " 570122  2.707608 -4.839643          605            2.977587         2.981422\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 570886  4.007708 -4.843589          605            0.000078         2.981422\n",
+       " 570887  4.009409 -4.843754          605            0.000070         2.981422\n",
+       " 570888  4.011111 -4.843919          605            0.000061         2.981422\n",
+       " 570889  4.012813 -4.844084          605            0.000053         2.981422\n",
+       " 570890  4.014514 -4.844249          605            0.000045         2.981422\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 571118  2.700801 -4.839780          606            2.980187         2.981539\n",
+       " 571119  2.702502 -4.839780          606            2.979332         2.981539\n",
+       " 571120  2.704204 -4.839780          606            2.978477         2.981539\n",
+       " 571121  2.705906 -4.839780          606            2.977618         2.981539\n",
+       " 571122  2.707608 -4.839780          606            2.976754         2.981539\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 571886  4.007708 -4.843552          606            0.000078         2.981539\n",
+       " 571887  4.009409 -4.843727          606            0.000069         2.981539\n",
+       " 571888  4.011111 -4.843901          606            0.000061         2.981539\n",
+       " 571889  4.012813 -4.844076          606            0.000053         2.981539\n",
+       " 571890  4.014514 -4.844250          606            0.000045         2.981539\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 572118  2.700801 -4.840089          607            2.980058         2.980529\n",
+       " 572119  2.702502 -4.839953          607            2.979206         2.980529\n",
+       " 572120  2.704204 -4.839878          607            2.978350         2.980529\n",
+       " 572121  2.705906 -4.839803          607            2.977494         2.980529\n",
+       " 572122  2.707608 -4.839780          607            2.976614         2.980529\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 572886  4.007708 -4.844144          607            0.000078         2.980529\n",
+       " 572887  4.009409 -4.844336          607            0.000070         2.980529\n",
+       " 572888  4.011111 -4.844527          607            0.000062         2.980529\n",
+       " 572889  4.012813 -4.844718          607            0.000054         2.980529\n",
+       " 572890  4.014514 -4.844910          607            0.000045         2.980529\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 573118  2.700801 -4.839592          608            2.979643         2.981101\n",
+       " 573119  2.702502 -4.839681          608            2.978774         2.981101\n",
+       " 573120  2.704204 -4.839768          608            2.977906         2.981101\n",
+       " 573121  2.705906 -4.839843          608            2.977036         2.981101\n",
+       " 573122  2.707608 -4.839916          608            2.976166         2.981101\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 573886  4.007708 -4.843345          608            0.000078         2.981101\n",
+       " 573887  4.009409 -4.843510          608            0.000070         2.981101\n",
+       " 573888  4.011111 -4.843675          608            0.000062         2.981101\n",
+       " 573889  4.012813 -4.843840          608            0.000054         2.981101\n",
+       " 573890  4.014514 -4.844005          608            0.000046         2.981101\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 574118  2.700801 -4.839810          609            2.978767          2.97988\n",
+       " 574119  2.702502 -4.839960          609            2.977863          2.97988\n",
+       " 574120  2.704204 -4.840110          609            2.976959          2.97988\n",
+       " 574121  2.705906 -4.840217          609            2.976065          2.97988\n",
+       " 574122  2.707608 -4.840071          609            2.975225          2.97988\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 574886  4.007708 -4.841601          609            0.000080          2.97988\n",
+       " 574887  4.009409 -4.841696          609            0.000072          2.97988\n",
+       " 574888  4.011111 -4.841791          609            0.000063          2.97988\n",
+       " 574889  4.012813 -4.841886          609            0.000055          2.97988\n",
+       " 574890  4.014514 -4.841981          609            0.000047          2.97988\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 575118  2.700801 -4.839876          610            2.976951         2.978729\n",
+       " 575119  2.702502 -4.839983          610            2.976078         2.978729\n",
+       " 575120  2.704204 -4.839908          610            2.975209         2.978729\n",
+       " 575121  2.705906 -4.839833          610            2.974340         2.978729\n",
+       " 575122  2.707608 -4.839802          610            2.973470         2.978729\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 575886  4.007708 -4.845159          610            0.000077         2.978729\n",
+       " 575887  4.009409 -4.845386          610            0.000069         2.978729\n",
+       " 575888  4.011111 -4.845613          610            0.000061         2.978729\n",
+       " 575889  4.012813 -4.845841          610            0.000052         2.978729\n",
+       " 575890  4.014514 -4.846069          610            0.000044         2.978729\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 576118  2.700801 -4.839783          611            2.975784         2.976203\n",
+       " 576119  2.702502 -4.839935          611            2.974907         2.976203\n",
+       " 576120  2.704204 -4.840088          611            2.974029         2.976203\n",
+       " 576121  2.705906 -4.840236          611            2.973152         2.976203\n",
+       " 576122  2.707608 -4.840088          611            2.972248         2.976203\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 576886  4.007708 -4.843959          611            0.000078         2.976203\n",
+       " 576887  4.009409 -4.844141          611            0.000070         2.976203\n",
+       " 576888  4.011111 -4.844323          611            0.000062         2.976203\n",
+       " 576889  4.012813 -4.844505          611            0.000054         2.976203\n",
+       " 576890  4.014514 -4.844687          611            0.000045         2.976203\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 577118  2.700801 -4.839780          612            2.975032         2.976911\n",
+       " 577119  2.702502 -4.839780          612            2.974189         2.976911\n",
+       " 577120  2.704204 -4.839780          612            2.973345         2.976911\n",
+       " 577121  2.705906 -4.839780          612            2.972502         2.976911\n",
+       " 577122  2.707608 -4.839780          612            2.971611         2.976911\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 577886  4.007708 -4.844531          612            0.000078         2.976911\n",
+       " 577887  4.009409 -4.844739          612            0.000070         2.976911\n",
+       " 577888  4.011111 -4.844948          612            0.000061         2.976911\n",
+       " 577889  4.012813 -4.845156          612            0.000053         2.976911\n",
+       " 577890  4.014514 -4.845365          612            0.000045         2.976911\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 578118  2.700801 -4.840135          613            2.972721         2.974225\n",
+       " 578119  2.702502 -4.840098          613            2.971873         2.974225\n",
+       " 578120  2.704204 -4.839869          613            2.971018         2.974225\n",
+       " 578121  2.705906 -4.839641          613            2.970163         2.974225\n",
+       " 578122  2.707608 -4.839644          613            2.969281         2.974225\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 578886  4.007708 -4.844180          613            0.000077         2.974225\n",
+       " 578887  4.009409 -4.844371          613            0.000069         2.974225\n",
+       " 578888  4.011111 -4.844562          613            0.000060         2.974225\n",
+       " 578889  4.012813 -4.844753          613            0.000052         2.974225\n",
+       " 578890  4.014514 -4.844944          613            0.000044         2.974225\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 579118  2.700801 -4.839948          614            2.971750         2.973528\n",
+       " 579119  2.702502 -4.840009          614            2.970883         2.973528\n",
+       " 579120  2.704204 -4.840009          614            2.970018         2.973528\n",
+       " 579121  2.705906 -4.840009          614            2.969153         2.973528\n",
+       " 579122  2.707608 -4.839948          614            2.968267         2.973528\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 579886  4.007708 -4.845694          614            0.000078         2.973528\n",
+       " 579887  4.009409 -4.845947          614            0.000070         2.973528\n",
+       " 579888  4.011111 -4.846201          614            0.000062         2.973528\n",
+       " 579889  4.012813 -4.846455          614            0.000053         2.973528\n",
+       " 579890  4.014514 -4.846708          614            0.000045         2.973528\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 580118  2.700801 -4.839829          615            2.971518         2.971915\n",
+       " 580119  2.702502 -4.839926          615            2.970664         2.971915\n",
+       " 580120  2.704204 -4.840019          615            2.969804         2.971915\n",
+       " 580121  2.705906 -4.840095          615            2.968913         2.971915\n",
+       " 580122  2.707608 -4.840169          615            2.968023         2.971915\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 580886  4.007708 -4.843725          615            0.000078         2.971915\n",
+       " 580887  4.009409 -4.843906          615            0.000070         2.971915\n",
+       " 580888  4.011111 -4.844088          615            0.000062         2.971915\n",
+       " 580889  4.012813 -4.844269          615            0.000054         2.971915\n",
+       " 580890  4.014514 -4.844450          615            0.000046         2.971915\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 581118  2.700801 -4.839816          616            2.969902         2.971234\n",
+       " 581119  2.702502 -4.839892          616            2.969047         2.971234\n",
+       " 581120  2.704204 -4.839968          616            2.968193         2.971234\n",
+       " 581121  2.705906 -4.840077          616            2.967323         2.971234\n",
+       " 581122  2.707608 -4.840226          616            2.966436         2.971234\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 581886  4.007708 -4.843022          616            0.000076         2.971234\n",
+       " 581887  4.009409 -4.843170          616            0.000067         2.971234\n",
+       " 581888  4.011111 -4.843318          616            0.000059         2.971234\n",
+       " 581889  4.012813 -4.843465          616            0.000051         2.971234\n",
+       " 581890  4.014514 -4.843613          616            0.000043         2.971234\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 582118  2.700801 -4.840009          617            2.969000         2.970013\n",
+       " 582119  2.702502 -4.840009          617            2.968131         2.970013\n",
+       " 582120  2.704204 -4.840009          617            2.967262         2.970013\n",
+       " 582121  2.705906 -4.840009          617            2.966392         2.970013\n",
+       " 582122  2.707608 -4.840009          617            2.965518         2.970013\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 582886  4.007708 -4.844081          617            0.000077         2.970013\n",
+       " 582887  4.009409 -4.844288          617            0.000069         2.970013\n",
+       " 582888  4.011111 -4.844495          617            0.000061         2.970013\n",
+       " 582889  4.012813 -4.844701          617            0.000053         2.970013\n",
+       " 582890  4.014514 -4.844908          617            0.000045         2.970013\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 583118  2.700801 -4.840230          618            2.969629         2.969789\n",
+       " 583119  2.702502 -4.840154          618            2.968756         2.969789\n",
+       " 583120  2.704204 -4.840077          618            2.967883         2.969789\n",
+       " 583121  2.705906 -4.840002          618            2.967011         2.969789\n",
+       " 583122  2.707608 -4.839930          618            2.966146         2.969789\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 583886  4.007708 -4.844520          618            0.000077         2.969789\n",
+       " 583887  4.009409 -4.844737          618            0.000068         2.969789\n",
+       " 583888  4.011111 -4.844954          618            0.000060         2.969789\n",
+       " 583889  4.012813 -4.845171          618            0.000052         2.969789\n",
+       " 583890  4.014514 -4.845388          618            0.000044         2.969789\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 584118  2.700801 -4.839780          619            2.969589         2.970852\n",
+       " 584119  2.702502 -4.839780          619            2.968734         2.970852\n",
+       " 584120  2.704204 -4.839780          619            2.967887         2.970852\n",
+       " 584121  2.705906 -4.839780          619            2.967039         2.970852\n",
+       " 584122  2.707608 -4.839780          619            2.966160         2.970852\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 584886  4.007708 -4.844892          619            0.000077         2.970852\n",
+       " 584887  4.009409 -4.845126          619            0.000069         2.970852\n",
+       " 584888  4.011111 -4.845359          619            0.000061         2.970852\n",
+       " 584889  4.012813 -4.845593          619            0.000053         2.970852\n",
+       " 584890  4.014514 -4.845827          619            0.000044         2.970852\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 585118  2.700801 -4.840196          620            2.969766         2.970049\n",
+       " 585119  2.702502 -4.840107          620            2.968909         2.970049\n",
+       " 585120  2.704204 -4.840017          620            2.968051         2.970049\n",
+       " 585121  2.705906 -4.839942          620            2.967199         2.970049\n",
+       " 585122  2.707608 -4.839868          620            2.966347         2.970049\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 585886  4.007708 -4.844705          620            0.000078         2.970049\n",
+       " 585887  4.009409 -4.844921          620            0.000070         2.970049\n",
+       " 585888  4.011111 -4.845137          620            0.000062         2.970049\n",
+       " 585889  4.012813 -4.845353          620            0.000054         2.970049\n",
+       " 585890  4.014514 -4.845569          620            0.000046         2.970049\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 586118  2.700801 -4.840235          621            2.969223         2.970113\n",
+       " 586119  2.702502 -4.840087          621            2.968354         2.970113\n",
+       " 586120  2.704204 -4.839940          621            2.967485         2.970113\n",
+       " 586121  2.705906 -4.839792          621            2.966615         2.970113\n",
+       " 586122  2.707608 -4.839780          621            2.965762         2.970113\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 586886  4.007708 -4.843748          621            0.000077         2.970113\n",
+       " 586887  4.009409 -4.843930          621            0.000069         2.970113\n",
+       " 586888  4.011111 -4.844111          621            0.000061         2.970113\n",
+       " 586889  4.012813 -4.844293          621            0.000053         2.970113\n",
+       " 586890  4.014514 -4.844475          621            0.000045         2.970113\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 587118  2.700801 -4.839958          622            2.969481         2.970481\n",
+       " 587119  2.702502 -4.839847          622            2.968647         2.970481\n",
+       " 587120  2.704204 -4.839780          622            2.967795         2.970481\n",
+       " 587121  2.705906 -4.839780          622            2.966917         2.970481\n",
+       " 587122  2.707608 -4.839780          622            2.966039         2.970481\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 587886  4.007708 -4.844373          622            0.000077         2.970481\n",
+       " 587887  4.009409 -4.844572          622            0.000068         2.970481\n",
+       " 587888  4.011111 -4.844770          622            0.000060         2.970481\n",
+       " 587889  4.012813 -4.844970          622            0.000052         2.970481\n",
+       " 587890  4.014514 -4.845169          622            0.000044         2.970481\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 588118  2.700801 -4.839780          623            2.969192         2.970016\n",
+       " 588119  2.702502 -4.839780          623            2.968315         2.970016\n",
+       " 588120  2.704204 -4.839780          623            2.967442         2.970016\n",
+       " 588121  2.705906 -4.839780          623            2.966569         2.970016\n",
+       " 588122  2.707608 -4.839780          623            2.965696         2.970016\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 588886  4.007708 -4.843407          623            0.000077         2.970016\n",
+       " 588887  4.009409 -4.843562          623            0.000069         2.970016\n",
+       " 588888  4.011111 -4.843717          623            0.000061         2.970016\n",
+       " 588889  4.012813 -4.843872          623            0.000053         2.970016\n",
+       " 588890  4.014514 -4.844027          623            0.000045         2.970016\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 589118  2.700801 -4.839780          624            2.970141         2.970353\n",
+       " 589119  2.702502 -4.839780          624            2.969278         2.970353\n",
+       " 589120  2.704204 -4.839780          624            2.968415         2.970353\n",
+       " 589121  2.705906 -4.839780          624            2.967554         2.970353\n",
+       " 589122  2.707608 -4.839780          624            2.966693         2.970353\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 589886  4.007708 -4.844665          624            0.000077         2.970353\n",
+       " 589887  4.009409 -4.844898          624            0.000069         2.970353\n",
+       " 589888  4.011111 -4.845131          624            0.000061         2.970353\n",
+       " 589889  4.012813 -4.845365          624            0.000052         2.970353\n",
+       " 589890  4.014514 -4.845598          624            0.000044         2.970353\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 590118  2.700801 -4.839836          625            2.971085         2.971219\n",
+       " 590119  2.702502 -4.839984          625            2.970202         2.971219\n",
+       " 590120  2.704204 -4.840132          625            2.969320         2.971219\n",
+       " 590121  2.705906 -4.840217          625            2.968448         2.971219\n",
+       " 590122  2.707608 -4.840143          625            2.967600         2.971219\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 590886  4.007708 -4.844421          625            0.000078         2.971219\n",
+       " 590887  4.009409 -4.844602          625            0.000070         2.971219\n",
+       " 590888  4.011111 -4.844783          625            0.000062         2.971219\n",
+       " 590889  4.012813 -4.844965          625            0.000054         2.971219\n",
+       " 590890  4.014514 -4.845146          625            0.000045         2.971219\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 591118  2.700801 -4.839590          626            2.968813         2.970311\n",
+       " 591119  2.702502 -4.839672          626            2.967957         2.970311\n",
+       " 591120  2.704204 -4.839755          626            2.967101         2.970311\n",
+       " 591121  2.705906 -4.839832          626            2.966245         2.970311\n",
+       " 591122  2.707608 -4.839907          626            2.965389         2.970311\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 591886  4.007708 -4.843185          626            0.000077         2.970311\n",
+       " 591887  4.009409 -4.843340          626            0.000069         2.970311\n",
+       " 591888  4.011111 -4.843495          626            0.000061         2.970311\n",
+       " 591889  4.012813 -4.843650          626            0.000053         2.970311\n",
+       " 591890  4.014514 -4.843805          626            0.000045         2.970311\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 592118  2.700801 -4.839972          627            2.968348         2.969316\n",
+       " 592119  2.702502 -4.839894          627            2.967476         2.969316\n",
+       " 592120  2.704204 -4.839816          627            2.966604         2.969316\n",
+       " 592121  2.705906 -4.839780          627            2.965739         2.969316\n",
+       " 592122  2.707608 -4.839780          627            2.964878         2.969316\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 592886  4.007708 -4.843643          627            0.000077         2.969316\n",
+       " 592887  4.009409 -4.843798          627            0.000069         2.969316\n",
+       " 592888  4.011111 -4.843953          627            0.000061         2.969316\n",
+       " 592889  4.012813 -4.844108          627            0.000053         2.969316\n",
+       " 592890  4.014514 -4.844263          627            0.000045         2.969316\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 593118  2.700801 -4.839965          628            2.968160         2.968631\n",
+       " 593119  2.702502 -4.839870          628            2.967288         2.968631\n",
+       " 593120  2.704204 -4.839780          628            2.966417         2.968631\n",
+       " 593121  2.705906 -4.839780          628            2.965561         2.968631\n",
+       " 593122  2.707608 -4.839780          628            2.964705         2.968631\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 593886  4.007708 -4.842795          628            0.000078         2.968631\n",
+       " 593887  4.009409 -4.842933          628            0.000070         2.968631\n",
+       " 593888  4.011111 -4.843071          628            0.000062         2.968631\n",
+       " 593889  4.012813 -4.843208          628            0.000053         2.968631\n",
+       " 593890  4.014514 -4.843345          628            0.000045         2.968631\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 594118  2.700801 -4.839593          629            2.968925         2.969161\n",
+       " 594119  2.702502 -4.839683          629            2.968077         2.969161\n",
+       " 594120  2.704204 -4.839772          629            2.967231         2.969161\n",
+       " 594121  2.705906 -4.839849          629            2.966364         2.969161\n",
+       " 594122  2.707608 -4.839926          629            2.965496         2.969161\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 594886  4.007708 -4.843071          629            0.000077         2.969161\n",
+       " 594887  4.009409 -4.843200          629            0.000069         2.969161\n",
+       " 594888  4.011111 -4.843329          629            0.000061         2.969161\n",
+       " 594889  4.012813 -4.843457          629            0.000053         2.969161\n",
+       " 594890  4.014514 -4.843586          629            0.000045         2.969161\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 595118  2.700801 -4.839894          630            2.968036         2.968972\n",
+       " 595119  2.702502 -4.840137          630            2.967186         2.968972\n",
+       " 595120  2.704204 -4.840195          630            2.966333         2.968972\n",
+       " 595121  2.705906 -4.840121          630            2.965477         2.968972\n",
+       " 595122  2.707608 -4.840047          630            2.964621         2.968972\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 595886  4.007708 -4.843214          630            0.000078         2.968972\n",
+       " 595887  4.009409 -4.843359          630            0.000070         2.968972\n",
+       " 595888  4.011111 -4.843505          630            0.000062         2.968972\n",
+       " 595889  4.012813 -4.843651          630            0.000053         2.968972\n",
+       " 595890  4.014514 -4.843797          630            0.000045         2.968972\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 596118  2.700801 -4.840009          631            2.966910         2.968175\n",
+       " 596119  2.702502 -4.840009          631            2.966037         2.968175\n",
+       " 596120  2.704204 -4.839976          631            2.965159         2.968175\n",
+       " 596121  2.705906 -4.839903          631            2.964277         2.968175\n",
+       " 596122  2.707608 -4.839831          631            2.963394         2.968175\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 596886  4.007708 -4.844576          631            0.000078         2.968175\n",
+       " 596887  4.009409 -4.844775          631            0.000069         2.968175\n",
+       " 596888  4.011111 -4.844974          631            0.000061         2.968175\n",
+       " 596889  4.012813 -4.845172          631            0.000053         2.968175\n",
+       " 596890  4.014514 -4.845371          631            0.000045         2.968175\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 597118  2.700801 -4.840150          632            2.965218          2.96621\n",
+       " 597119  2.702502 -4.839977          632            2.964349          2.96621\n",
+       " 597120  2.704204 -4.839804          632            2.963480          2.96621\n",
+       " 597121  2.705906 -4.839780          632            2.962632          2.96621\n",
+       " 597122  2.707608 -4.839780          632            2.961787          2.96621\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 597886  4.007708 -4.843834          632            0.000075          2.96621\n",
+       " 597887  4.009409 -4.844009          632            0.000067          2.96621\n",
+       " 597888  4.011111 -4.844184          632            0.000059          2.96621\n",
+       " 597889  4.012813 -4.844359          632            0.000050          2.96621\n",
+       " 597890  4.014514 -4.844534          632            0.000042          2.96621\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 598118  2.700801 -4.840009          633            2.962706          2.96394\n",
+       " 598119  2.702502 -4.840009          633            2.961844          2.96394\n",
+       " 598120  2.704204 -4.840009          633            2.960982          2.96394\n",
+       " 598121  2.705906 -4.839965          633            2.960116          2.96394\n",
+       " 598122  2.707608 -4.839891          633            2.959247          2.96394\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 598886  4.007708 -4.843475          633            0.000076          2.96394\n",
+       " 598887  4.009409 -4.843623          633            0.000068          2.96394\n",
+       " 598888  4.011111 -4.843770          633            0.000060          2.96394\n",
+       " 598889  4.012813 -4.843917          633            0.000051          2.96394\n",
+       " 598890  4.014514 -4.844065          633            0.000043          2.96394\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 599118  2.700801 -4.840018          634            2.962077         2.962734\n",
+       " 599119  2.702502 -4.840153          634            2.961201         2.962734\n",
+       " 599120  2.704204 -4.840003          634            2.960354         2.962734\n",
+       " 599121  2.705906 -4.839852          634            2.959507         2.962734\n",
+       " 599122  2.707608 -4.839780          634            2.958644         2.962734\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 599886  4.007708 -4.844532          634            0.000076         2.962734\n",
+       " 599887  4.009409 -4.844751          634            0.000068         2.962734\n",
+       " 599888  4.011111 -4.844970          634            0.000060         2.962734\n",
+       " 599889  4.012813 -4.845188          634            0.000052         2.962734\n",
+       " 599890  4.014514 -4.845407          634            0.000043         2.962734\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 600118  2.700801 -4.839591          635            2.959617         2.960728\n",
+       " 600119  2.702502 -4.839674          635            2.958762         2.960728\n",
+       " 600120  2.704204 -4.839758          635            2.957906         2.960728\n",
+       " 600121  2.705906 -4.839890          635            2.957022         2.960728\n",
+       " 600122  2.707608 -4.840040          635            2.956127         2.960728\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 600886  4.007708 -4.843818          635            0.000076         2.960728\n",
+       " 600887  4.009409 -4.843993          635            0.000068         2.960728\n",
+       " 600888  4.011111 -4.844168          635            0.000059         2.960728\n",
+       " 600889  4.012813 -4.844343          635            0.000051         2.960728\n",
+       " 600890  4.014514 -4.844518          635            0.000043         2.960728\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 601118  2.700801 -4.839850          636            2.958159         2.959292\n",
+       " 601119  2.702502 -4.839840          636            2.957303         2.959292\n",
+       " 601120  2.704204 -4.839915          636            2.956443         2.959292\n",
+       " 601121  2.705906 -4.839990          636            2.955584         2.959292\n",
+       " 601122  2.707608 -4.840009          636            2.954707         2.959292\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 601886  4.007708 -4.843366          636            0.000076         2.959292\n",
+       " 601887  4.009409 -4.843540          636            0.000067         2.959292\n",
+       " 601888  4.011111 -4.843714          636            0.000059         2.959292\n",
+       " 601889  4.012813 -4.843887          636            0.000051         2.959292\n",
+       " 601890  4.014514 -4.844061          636            0.000043         2.959292\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 602118  2.700801 -4.839815          637            2.958196         2.958643\n",
+       " 602119  2.702502 -4.839890          637            2.957350         2.958643\n",
+       " 602120  2.704204 -4.839965          637            2.956503         2.958643\n",
+       " 602121  2.705906 -4.840009          637            2.955641         2.958643\n",
+       " 602122  2.707608 -4.840009          637            2.954759         2.958643\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 602886  4.007708 -4.845125          637            0.000074         2.958643\n",
+       " 602887  4.009409 -4.845377          637            0.000066         2.958643\n",
+       " 602888  4.011111 -4.845630          637            0.000058         2.958643\n",
+       " 602889  4.012813 -4.845882          637            0.000050         2.958643\n",
+       " 602890  4.014514 -4.846135          637            0.000041         2.958643\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 603118  2.700801 -4.840422          638            2.957195         2.958199\n",
+       " 603119  2.702502 -4.840193          638            2.956323         2.958199\n",
+       " 603120  2.704204 -4.839965          638            2.955450         2.958199\n",
+       " 603121  2.705906 -4.839795          638            2.954573         2.958199\n",
+       " 603122  2.707608 -4.839870          638            2.953677         2.958199\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 603886  4.007708 -4.844178          638            0.000075         2.958199\n",
+       " 603887  4.009409 -4.844377          638            0.000067         2.958199\n",
+       " 603888  4.011111 -4.844577          638            0.000059         2.958199\n",
+       " 603889  4.012813 -4.844776          638            0.000051         2.958199\n",
+       " 603890  4.014514 -4.844975          638            0.000043         2.958199\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 604118  2.700801 -4.840115          639            2.957300            2.957\n",
+       " 604119  2.702502 -4.839851          639            2.956406            2.957\n",
+       " 604120  2.704204 -4.839587          639            2.955511            2.957\n",
+       " 604121  2.705906 -4.839614          639            2.954660            2.957\n",
+       " 604122  2.707608 -4.839685          639            2.953815            2.957\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 604886  4.007708 -4.843841          639            0.000075            2.957\n",
+       " 604887  4.009409 -4.844014          639            0.000067            2.957\n",
+       " 604888  4.011111 -4.844188          639            0.000058            2.957\n",
+       " 604889  4.012813 -4.844361          639            0.000050            2.957\n",
+       " 604890  4.014514 -4.844534          639            0.000042            2.957\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 605118  2.700801 -4.839780          640            2.956500         2.957374\n",
+       " 605119  2.702502 -4.839780          640            2.955631         2.957374\n",
+       " 605120  2.704204 -4.839780          640            2.954762         2.957374\n",
+       " 605121  2.705906 -4.839745          640            2.953890         2.957374\n",
+       " 605122  2.707608 -4.839597          640            2.953008         2.957374\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 605886  4.007708 -4.844224          640            0.000073         2.957374\n",
+       " 605887  4.009409 -4.844423          640            0.000065         2.957374\n",
+       " 605888  4.011111 -4.844622          640            0.000057         2.957374\n",
+       " 605889  4.012813 -4.844821          640            0.000049         2.957374\n",
+       " 605890  4.014514 -4.845020          640            0.000041         2.957374\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 606118  2.700801 -4.839816          641            2.956406         2.956894\n",
+       " 606119  2.702502 -4.839892          641            2.955582         2.956894\n",
+       " 606120  2.704204 -4.839968          641            2.954759         2.956894\n",
+       " 606121  2.705906 -4.839974          641            2.953900         2.956894\n",
+       " 606122  2.707608 -4.839898          641            2.953000         2.956894\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 606886  4.007708 -4.843358          641            0.000074         2.956894\n",
+       " 606887  4.009409 -4.843488          641            0.000066         2.956894\n",
+       " 606888  4.011111 -4.843618          641            0.000057         2.956894\n",
+       " 606889  4.012813 -4.843748          641            0.000049         2.956894\n",
+       " 606890  4.014514 -4.843878          641            0.000041         2.956894\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 607118  2.700801 -4.839744          642            2.955872         2.956166\n",
+       " 607119  2.702502 -4.839665          642            2.955027         2.956166\n",
+       " 607120  2.704204 -4.839587          642            2.954183         2.956166\n",
+       " 607121  2.705906 -4.839551          642            2.953323         2.956166\n",
+       " 607122  2.707608 -4.839551          642            2.952450         2.956166\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 607885  4.006006 -4.843765          642            0.000080         2.956166\n",
+       " 607886  4.007708 -4.843930          642            0.000072         2.956166\n",
+       " 607887  4.009409 -4.844095          642            0.000064         2.956166\n",
+       " 607888  4.011111 -4.844259          642            0.000056         2.956166\n",
+       " 607889  4.012813 -4.844424          642            0.000048         2.956166\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 608118  2.700801 -4.839880          643            2.956577         2.956249\n",
+       " 608119  2.702502 -4.840092          643            2.955746         2.956249\n",
+       " 608120  2.704204 -4.840238          643            2.954899         2.956249\n",
+       " 608121  2.705906 -4.840238          643            2.954017         2.956249\n",
+       " 608122  2.707608 -4.840238          643            2.953135         2.956249\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 608885  4.006006 -4.843232          643            0.000079         2.956249\n",
+       " 608886  4.007708 -4.843371          643            0.000071         2.956249\n",
+       " 608887  4.009409 -4.843510          643            0.000063         2.956249\n",
+       " 608888  4.011111 -4.843649          643            0.000054         2.956249\n",
+       " 608889  4.012813 -4.843788          643            0.000046         2.956249\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 609118  2.700801 -4.839944          644            2.956168         2.956379\n",
+       " 609119  2.702502 -4.840214          644            2.955276         2.956379\n",
+       " 609120  2.704204 -4.840065          644            2.954425         2.956379\n",
+       " 609121  2.705906 -4.839918          644            2.953573         2.956379\n",
+       " 609122  2.707608 -4.839786          644            2.952720         2.956379\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 609885  4.006006 -4.844165          644            0.000079         2.956379\n",
+       " 609886  4.007708 -4.844347          644            0.000071         2.956379\n",
+       " 609887  4.009409 -4.844528          644            0.000063         2.956379\n",
+       " 609888  4.011111 -4.844709          644            0.000055         2.956379\n",
+       " 609889  4.012813 -4.844890          644            0.000047         2.956379\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 610118  2.700801 -4.839834          645            2.956223         2.956036\n",
+       " 610119  2.702502 -4.839951          645            2.955412         2.956036\n",
+       " 610120  2.704204 -4.839972          645            2.954568         2.956036\n",
+       " 610121  2.705906 -4.839897          645            2.953691         2.956036\n",
+       " 610122  2.707608 -4.839822          645            2.952813         2.956036\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 610885  4.006006 -4.845622          645            0.000079         2.956036\n",
+       " 610886  4.007708 -4.845880          645            0.000071         2.956036\n",
+       " 610887  4.009409 -4.846138          645            0.000063         2.956036\n",
+       " 610888  4.011111 -4.846397          645            0.000055         2.956036\n",
+       " 610889  4.012813 -4.846655          645            0.000047         2.956036\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 611118  2.700801 -4.839727          646            2.956260         2.957448\n",
+       " 611119  2.702502 -4.839614          646            2.955414         2.957448\n",
+       " 611120  2.704204 -4.839585          646            2.954556         2.957448\n",
+       " 611121  2.705906 -4.839660          646            2.953683         2.957448\n",
+       " 611122  2.707608 -4.839736          646            2.952810         2.957448\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 611885  4.006006 -4.845056          646            0.000079         2.957448\n",
+       " 611886  4.007708 -4.845287          646            0.000071         2.957448\n",
+       " 611887  4.009409 -4.845519          646            0.000063         2.957448\n",
+       " 611888  4.011111 -4.845750          646            0.000055         2.957448\n",
+       " 611889  4.012813 -4.845981          646            0.000047         2.957448\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 612118  2.700801 -4.840009          647            2.954992         2.956729\n",
+       " 612119  2.702502 -4.840009          647            2.954136         2.956729\n",
+       " 612120  2.704204 -4.839963          647            2.953276         2.956729\n",
+       " 612121  2.705906 -4.839815          647            2.952407         2.956729\n",
+       " 612122  2.707608 -4.839667          647            2.951538         2.956729\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 612885  4.006006 -4.843956          647            0.000078         2.956729\n",
+       " 612886  4.007708 -4.844136          647            0.000070         2.956729\n",
+       " 612887  4.009409 -4.844317          647            0.000062         2.956729\n",
+       " 612888  4.011111 -4.844497          647            0.000054         2.956729\n",
+       " 612889  4.012813 -4.844678          647            0.000046         2.956729\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 613118  2.700801 -4.840011          648            2.953131         2.954627\n",
+       " 613119  2.702502 -4.840085          648            2.952279         2.954627\n",
+       " 613120  2.704204 -4.840158          648            2.951427         2.954627\n",
+       " 613121  2.705906 -4.840232          648            2.950575         2.954627\n",
+       " 613122  2.707608 -4.840170          648            2.949695         2.954627\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 613885  4.006006 -4.844097          648            0.000078         2.954627\n",
+       " 613886  4.007708 -4.844294          648            0.000070         2.954627\n",
+       " 613887  4.009409 -4.844491          648            0.000062         2.954627\n",
+       " 613888  4.011111 -4.844688          648            0.000054         2.954627\n",
+       " 613889  4.012813 -4.844885          648            0.000046         2.954627\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 614118  2.700801 -4.839865          649            2.952336          2.95356\n",
+       " 614119  2.702502 -4.840025          649            2.951512          2.95356\n",
+       " 614120  2.704204 -4.840100          649            2.950647          2.95356\n",
+       " 614121  2.705906 -4.840175          649            2.949783          2.95356\n",
+       " 614122  2.707608 -4.840226          649            2.948917          2.95356\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 614885  4.006006 -4.843736          649            0.000078          2.95356\n",
+       " 614886  4.007708 -4.843916          649            0.000070          2.95356\n",
+       " 614887  4.009409 -4.844097          649            0.000062          2.95356\n",
+       " 614888  4.011111 -4.844277          649            0.000054          2.95356\n",
+       " 614889  4.012813 -4.844457          649            0.000046          2.95356\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 615118  2.700801 -4.840176          650            2.951492         2.952693\n",
+       " 615119  2.702502 -4.840041          650            2.950656         2.952693\n",
+       " 615120  2.704204 -4.840009          650            2.949791         2.952693\n",
+       " 615121  2.705906 -4.840009          650            2.948918         2.952693\n",
+       " 615122  2.707608 -4.840009          650            2.948044         2.952693\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 615885  4.006006 -4.845391          650            0.000078         2.952693\n",
+       " 615886  4.007708 -4.845657          650            0.000070         2.952693\n",
+       " 615887  4.009409 -4.845923          650            0.000062         2.952693\n",
+       " 615888  4.011111 -4.846189          650            0.000054         2.952693\n",
+       " 615889  4.012813 -4.846455          650            0.000046         2.952693\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 616118  2.700801 -4.840125          651            2.951355          2.95177\n",
+       " 616119  2.702502 -4.839882          651            2.950484          2.95177\n",
+       " 616120  2.704204 -4.839823          651            2.949622          2.95177\n",
+       " 616121  2.705906 -4.839898          651            2.948766          2.95177\n",
+       " 616122  2.707608 -4.839972          651            2.947909          2.95177\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 616885  4.006006 -4.844271          651            0.000079          2.95177\n",
+       " 616886  4.007708 -4.844476          651            0.000071          2.95177\n",
+       " 616887  4.009409 -4.844680          651            0.000063          2.95177\n",
+       " 616888  4.011111 -4.844885          651            0.000055          2.95177\n",
+       " 616889  4.012813 -4.845089          651            0.000047          2.95177\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 617118  2.700801 -4.839551          652            2.950858         2.952255\n",
+       " 617119  2.702502 -4.839551          652            2.949988         2.952255\n",
+       " 617120  2.704204 -4.839598          652            2.949118         2.952255\n",
+       " 617121  2.705906 -4.839672          652            2.948249         2.952255\n",
+       " 617122  2.707608 -4.839746          652            2.947380         2.952255\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 617885  4.006006 -4.844074          652            0.000079         2.952255\n",
+       " 617886  4.007708 -4.844270          652            0.000071         2.952255\n",
+       " 617887  4.009409 -4.844467          652            0.000063         2.952255\n",
+       " 617888  4.011111 -4.844663          652            0.000055         2.952255\n",
+       " 617889  4.012813 -4.844859          652            0.000047         2.952255\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 618118  2.700801 -4.839601          653            2.949173         2.950533\n",
+       " 618119  2.702502 -4.839707          653            2.948292         2.950533\n",
+       " 618120  2.704204 -4.839804          653            2.947409         2.950533\n",
+       " 618121  2.705906 -4.839878          653            2.946522         2.950533\n",
+       " 618122  2.707608 -4.839952          653            2.945636         2.950533\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 618885  4.006006 -4.844145          653            0.000078         2.950533\n",
+       " 618886  4.007708 -4.844334          653            0.000070         2.950533\n",
+       " 618887  4.009409 -4.844523          653            0.000062         2.950533\n",
+       " 618888  4.011111 -4.844711          653            0.000054         2.950533\n",
+       " 618889  4.012813 -4.844900          653            0.000046         2.950533\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 619118  2.700801 -4.839859          654            2.948581         2.949572\n",
+       " 619119  2.702502 -4.840009          654            2.947679         2.949572\n",
+       " 619120  2.704204 -4.840009          654            2.946831         2.949572\n",
+       " 619121  2.705906 -4.840009          654            2.945984         2.949572\n",
+       " 619122  2.707608 -4.840005          654            2.945136         2.949572\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 619885  4.006006 -4.843903          654            0.000079         2.949572\n",
+       " 619886  4.007708 -4.844090          654            0.000071         2.949572\n",
+       " 619887  4.009409 -4.844279          654            0.000063         2.949572\n",
+       " 619888  4.011111 -4.844467          654            0.000055         2.949572\n",
+       " 619889  4.012813 -4.844655          654            0.000047         2.949572\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 620118  2.700801 -4.839692          655            2.947672         2.949627\n",
+       " 620119  2.702502 -4.839992          655            2.946802         2.949627\n",
+       " 620120  2.704204 -4.840211          655            2.945930         2.949627\n",
+       " 620121  2.705906 -4.840061          655            2.945047         2.949627\n",
+       " 620122  2.707608 -4.839911          655            2.944165         2.949627\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 620885  4.006006 -4.843204          655            0.000078         2.949627\n",
+       " 620886  4.007708 -4.843350          655            0.000070         2.949627\n",
+       " 620887  4.009409 -4.843496          655            0.000062         2.949627\n",
+       " 620888  4.011111 -4.843642          655            0.000054         2.949627\n",
+       " 620889  4.012813 -4.843789          655            0.000046         2.949627\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 621118  2.700801 -4.839744          656            2.947384         2.948278\n",
+       " 621119  2.702502 -4.839667          656            2.946503         2.948278\n",
+       " 621120  2.704204 -4.839590          656            2.945621         2.948278\n",
+       " 621121  2.705906 -4.839551          656            2.944740         2.948278\n",
+       " 621122  2.707608 -4.839551          656            2.943857         2.948278\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 621885  4.006006 -4.842864          656            0.000079         2.948278\n",
+       " 621886  4.007708 -4.842984          656            0.000070         2.948278\n",
+       " 621887  4.009409 -4.843104          656            0.000062         2.948278\n",
+       " 621888  4.011111 -4.843225          656            0.000054         2.948278\n",
+       " 621889  4.012813 -4.843345          656            0.000046         2.948278\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 622118  2.700801 -4.839700          657            2.944184         2.946964\n",
+       " 622119  2.702502 -4.840009          657            2.943331         2.946964\n",
+       " 622120  2.704204 -4.840009          657            2.942467         2.946964\n",
+       " 622121  2.705906 -4.840009          657            2.941602         2.946964\n",
+       " 622122  2.707608 -4.840009          657            2.940738         2.946964\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 622885  4.006006 -4.844517          657            0.000078         2.946964\n",
+       " 622886  4.007708 -4.844722          657            0.000070         2.946964\n",
+       " 622887  4.009409 -4.844927          657            0.000062         2.946964\n",
+       " 622888  4.011111 -4.845131          657            0.000054         2.946964\n",
+       " 622889  4.012813 -4.845336          657            0.000046         2.946964\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 623118  2.700801 -4.839839          658            2.943255         2.944413\n",
+       " 623119  2.702502 -4.839963          658            2.942370         2.944413\n",
+       " 623120  2.704204 -4.840055          658            2.941490         2.944413\n",
+       " 623121  2.705906 -4.840130          658            2.940612         2.944413\n",
+       " 623122  2.707608 -4.840204          658            2.939734         2.944413\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 623885  4.006006 -4.844125          658            0.000077         2.944413\n",
+       " 623886  4.007708 -4.844322          658            0.000069         2.944413\n",
+       " 623887  4.009409 -4.844519          658            0.000061         2.944413\n",
+       " 623888  4.011111 -4.844715          658            0.000053         2.944413\n",
+       " 623889  4.012813 -4.844912          658            0.000045         2.944413\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 624118  2.700801 -4.839780          659            2.942482         2.943017\n",
+       " 624119  2.702502 -4.839780          659            2.941609         2.943017\n",
+       " 624120  2.704204 -4.839780          659            2.940736         2.943017\n",
+       " 624121  2.705906 -4.839780          659            2.939862         2.943017\n",
+       " 624122  2.707608 -4.839780          659            2.938940         2.943017\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 624882  4.000901 -4.839822          659            0.000092         2.943017\n",
+       " 624883  4.002603 -4.839813          659            0.000084         2.943017\n",
+       " 624884  4.004304 -4.839804          659            0.000075         2.943017\n",
+       " 624885  4.006006 -4.839795          659            0.000066         2.943017\n",
+       " 624886  4.007708 -4.839785          659            0.000058         2.943017\n",
+       " \n",
+       " [769 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 625118  2.700801 -4.840237          660            2.941841         2.943029\n",
+       " 625119  2.702502 -4.839797          660            2.941006         2.943029\n",
+       " 625120  2.704204 -4.840023          660            2.940133         2.943029\n",
+       " 625121  2.705906 -4.840248          660            2.939260         2.943029\n",
+       " 625122  2.707608 -4.840458          660            2.938386         2.943029\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 625885  4.006006 -4.843282          660            0.000076         2.943029\n",
+       " 625886  4.007708 -4.843420          660            0.000068         2.943029\n",
+       " 625887  4.009409 -4.843557          660            0.000060         2.943029\n",
+       " 625888  4.011111 -4.843695          660            0.000052         2.943029\n",
+       " 625889  4.012813 -4.843832          660            0.000044         2.943029\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 626118  2.700801 -4.840009          661            2.941867         2.942386\n",
+       " 626119  2.702502 -4.840009          661            2.941002         2.942386\n",
+       " 626120  2.704204 -4.840048          661            2.940139         2.942386\n",
+       " 626121  2.705906 -4.840121          661            2.939278         2.942386\n",
+       " 626122  2.707608 -4.840194          661            2.938417         2.942386\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 626885  4.006006 -4.845309          661            0.000076         2.942386\n",
+       " 626886  4.007708 -4.845558          661            0.000068         2.942386\n",
+       " 626887  4.009409 -4.845807          661            0.000060         2.942386\n",
+       " 626888  4.011111 -4.846056          661            0.000051         2.942386\n",
+       " 626889  4.012813 -4.846305          661            0.000043         2.942386\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 627118  2.700801 -4.839985          662            2.942138         2.943389\n",
+       " 627119  2.702502 -4.839912          662            2.941256         2.943389\n",
+       " 627120  2.704204 -4.839839          662            2.940373         2.943389\n",
+       " 627121  2.705906 -4.839780          662            2.939490         2.943389\n",
+       " 627122  2.707608 -4.839780          662            2.938604         2.943389\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 627885  4.006006 -4.843037          662            0.000077         2.943389\n",
+       " 627886  4.007708 -4.843174          662            0.000069         2.943389\n",
+       " 627887  4.009409 -4.843311          662            0.000061         2.943389\n",
+       " 627888  4.011111 -4.843448          662            0.000053         2.943389\n",
+       " 627889  4.012813 -4.843585          662            0.000045         2.943389\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 628118  2.700801 -4.840429          663            2.940829         2.941559\n",
+       " 628119  2.702502 -4.840251          663            2.939954         2.941559\n",
+       " 628120  2.704204 -4.840029          663            2.939081         2.941559\n",
+       " 628121  2.705906 -4.839807          663            2.938207         2.941559\n",
+       " 628122  2.707608 -4.839780          663            2.937315         2.941559\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 628885  4.006006 -4.844521          663            0.000077         2.941559\n",
+       " 628886  4.007708 -4.844735          663            0.000069         2.941559\n",
+       " 628887  4.009409 -4.844949          663            0.000061         2.941559\n",
+       " 628888  4.011111 -4.845163          663            0.000052         2.941559\n",
+       " 628889  4.012813 -4.845377          663            0.000044         2.941559\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 629118  2.700801 -4.839956          664            2.940623         2.941353\n",
+       " 629119  2.702502 -4.839843          664            2.939743         2.941353\n",
+       " 629120  2.704204 -4.839814          664            2.938853         2.941353\n",
+       " 629121  2.705906 -4.839889          664            2.937948         2.941353\n",
+       " 629122  2.707608 -4.839964          664            2.937044         2.941353\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 629885  4.006006 -4.844173          664            0.000075         2.941353\n",
+       " 629886  4.007708 -4.844371          664            0.000067         2.941353\n",
+       " 629887  4.009409 -4.844569          664            0.000059         2.941353\n",
+       " 629888  4.011111 -4.844767          664            0.000051         2.941353\n",
+       " 629889  4.012813 -4.844965          664            0.000043         2.941353\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 630118  2.700801 -4.839780          665            2.940515         2.940777\n",
+       " 630119  2.702502 -4.839780          665            2.939664         2.940777\n",
+       " 630120  2.704204 -4.839841          665            2.938767         2.940777\n",
+       " 630121  2.705906 -4.839916          665            2.937858         2.940777\n",
+       " 630122  2.707608 -4.839991          665            2.936950         2.940777\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 630885  4.006006 -4.843692          665            0.000074         2.940777\n",
+       " 630886  4.007708 -4.843847          665            0.000066         2.940777\n",
+       " 630887  4.009409 -4.844001          665            0.000058         2.940777\n",
+       " 630888  4.011111 -4.844155          665            0.000050         2.940777\n",
+       " 630889  4.012813 -4.844309          665            0.000042         2.940777\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 631118  2.700801 -4.840238          671            3.087609         2.925804\n",
+       " 631119  2.702502 -4.840238          671            3.086758         2.925804\n",
+       " 631120  2.704204 -4.840238          671            3.085908         2.925804\n",
+       " 631121  2.705906 -4.840310          671            3.085054         2.925804\n",
+       " 631122  2.707608 -4.840382          671            3.084201         2.925804\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 631890  4.014514 -4.843031          671            0.000077         2.925804\n",
+       " 631891  4.016216 -4.843165          671            0.000069         2.925804\n",
+       " 631892  4.017918 -4.843299          671            0.000062         2.925804\n",
+       " 631893  4.019619 -4.843432          671            0.000054         2.925804\n",
+       " 631894  4.021321 -4.843566          671            0.000046         2.925804\n",
+       " \n",
+       " [777 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 632118  2.700801 -4.839551          672            3.066633         3.069122\n",
+       " 632119  2.702502 -4.839648          672            3.065742         3.069122\n",
+       " 632120  2.704204 -4.839870          672            3.064877         3.069122\n",
+       " 632121  2.705906 -4.840092          672            3.064012         3.069122\n",
+       " 632122  2.707608 -4.840238          672            3.063148         3.069122\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 632889  4.012813 -4.845189          672            0.000073         3.069122\n",
+       " 632890  4.014514 -4.845423          672            0.000065         3.069122\n",
+       " 632891  4.016216 -4.845658          672            0.000058         3.069122\n",
+       " 632892  4.017918 -4.845893          672            0.000050         3.069122\n",
+       " 632893  4.019619 -4.846128          672            0.000042         3.069122\n",
+       " \n",
+       " [776 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 633118  2.700801 -4.839884          673            3.051743         3.060182\n",
+       " 633119  2.702502 -4.839977          673            3.050866         3.060182\n",
+       " 633120  2.704204 -4.839903          673            3.050019         3.060182\n",
+       " 633121  2.705906 -4.839829          673            3.049171         3.060182\n",
+       " 633122  2.707608 -4.839780          673            3.048302         3.060182\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 633888  4.011111 -4.845217          673            0.000077         3.060182\n",
+       " 633889  4.012813 -4.845467          673            0.000070         3.060182\n",
+       " 633890  4.014514 -4.845716          673            0.000062         3.060182\n",
+       " 633891  4.016216 -4.845965          673            0.000054         3.060182\n",
+       " 633892  4.017918 -4.846215          673            0.000046         3.060182\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 634118  2.700801 -4.839918          674            3.038356         3.046635\n",
+       " 634119  2.702502 -4.839944          674            3.037490         3.046635\n",
+       " 634120  2.704204 -4.839870          674            3.036616         3.046635\n",
+       " 634121  2.705906 -4.839796          674            3.035743         3.046635\n",
+       " 634122  2.707608 -4.839839          674            3.034849         3.046635\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 634888  4.011111 -4.845013          674            0.000073         3.046635\n",
+       " 634889  4.012813 -4.845239          674            0.000065         3.046635\n",
+       " 634890  4.014514 -4.845465          674            0.000057         3.046635\n",
+       " 634891  4.016216 -4.845692          674            0.000049         3.046635\n",
+       " 634892  4.017918 -4.845918          674            0.000041         3.046635\n",
+       " \n",
+       " [775 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 635118  2.700801 -4.839950          675            3.027579         3.033933\n",
+       " 635119  2.702502 -4.840238          675            3.026739         3.033933\n",
+       " 635120  2.704204 -4.840238          675            3.025844         3.033933\n",
+       " 635121  2.705906 -4.840238          675            3.024949         3.033933\n",
+       " 635122  2.707608 -4.840208          675            3.024053         3.033933\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 635887  4.009409 -4.844907          675            0.000078         3.033933\n",
+       " 635888  4.011111 -4.845123          675            0.000070         3.033933\n",
+       " 635889  4.012813 -4.845339          675            0.000062         3.033933\n",
+       " 635890  4.014514 -4.845555          675            0.000054         3.033933\n",
+       " 635891  4.016216 -4.845772          675            0.000047         3.033933\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 636118  2.700801 -4.839768          676            3.020279         3.024685\n",
+       " 636119  2.702502 -4.840232          676            3.019397         3.024685\n",
+       " 636120  2.704204 -4.840092          676            3.018498         3.024685\n",
+       " 636121  2.705906 -4.839944          676            3.017598         3.024685\n",
+       " 636122  2.707608 -4.839796          676            3.016699         3.024685\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 636887  4.009409 -4.843421          676            0.000075         3.024685\n",
+       " 636888  4.011111 -4.843581          676            0.000067         3.024685\n",
+       " 636889  4.012813 -4.843741          676            0.000059         3.024685\n",
+       " 636890  4.014514 -4.843901          676            0.000051         3.024685\n",
+       " 636891  4.016216 -4.844061          676            0.000043         3.024685\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 637118  2.700801 -4.840238          677            3.010900         3.017492\n",
+       " 637119  2.702502 -4.840174          677            3.010023         3.017492\n",
+       " 637120  2.704204 -4.840098          677            3.009150         3.017492\n",
+       " 637121  2.705906 -4.840022          677            3.008277         3.017492\n",
+       " 637122  2.707608 -4.840009          677            3.007364         3.017492\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 637887  4.009409 -4.842126          677            0.000074         3.017492\n",
+       " 637888  4.011111 -4.842217          677            0.000066         3.017492\n",
+       " 637889  4.012813 -4.842309          677            0.000058         3.017492\n",
+       " 637890  4.014514 -4.842401          677            0.000051         3.017492\n",
+       " 637891  4.016216 -4.842492          677            0.000043         3.017492\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 638118  2.700801 -4.840194          678            3.001838         3.006667\n",
+       " 638119  2.702502 -4.839969          678            3.000939         3.006667\n",
+       " 638120  2.704204 -4.839743          678            3.000039         3.006667\n",
+       " 638121  2.705906 -4.839562          678            2.999140         3.006667\n",
+       " 638122  2.707608 -4.839636          678            2.998245         3.006667\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 638886  4.007708 -4.844472          678            0.000078         3.006667\n",
+       " 638887  4.009409 -4.844681          678            0.000071         3.006667\n",
+       " 638888  4.011111 -4.844890          678            0.000063         3.006667\n",
+       " 638889  4.012813 -4.845099          678            0.000055         3.006667\n",
+       " 638890  4.014514 -4.845308          678            0.000047         3.006667\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 639118  2.700801 -4.839802          679            2.995476         2.999499\n",
+       " 639119  2.702502 -4.840009          679            2.994598         2.999499\n",
+       " 639120  2.704204 -4.840009          679            2.993685         2.999499\n",
+       " 639121  2.705906 -4.840009          679            2.992772         2.999499\n",
+       " 639122  2.707608 -4.840009          679            2.991865         2.999499\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 639886  4.007708 -4.844651          679            0.000077         2.999499\n",
+       " 639887  4.009409 -4.844876          679            0.000069         2.999499\n",
+       " 639888  4.011111 -4.845101          679            0.000062         2.999499\n",
+       " 639889  4.012813 -4.845327          679            0.000054         2.999499\n",
+       " 639890  4.014514 -4.845552          679            0.000046         2.999499\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 640118  2.700801 -4.839788          680            2.988705         2.993326\n",
+       " 640119  2.702502 -4.839862          680            2.987818         2.993326\n",
+       " 640120  2.704204 -4.839936          680            2.986932         2.993326\n",
+       " 640121  2.705906 -4.840008          680            2.986045         2.993326\n",
+       " 640122  2.707608 -4.839932          680            2.985118         2.993326\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 640886  4.007708 -4.844594          680            0.000075         2.993326\n",
+       " 640887  4.009409 -4.844795          680            0.000067         2.993326\n",
+       " 640888  4.011111 -4.844995          680            0.000060         2.993326\n",
+       " 640889  4.012813 -4.845196          680            0.000052         2.993326\n",
+       " 640890  4.014514 -4.845397          680            0.000044         2.993326\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 641118  2.700801 -4.839738          681            2.982377         2.987622\n",
+       " 641119  2.702502 -4.839647          681            2.981462         2.987622\n",
+       " 641120  2.704204 -4.839556          681            2.980546         2.987622\n",
+       " 641121  2.705906 -4.839551          681            2.979641         2.987622\n",
+       " 641122  2.707608 -4.839551          681            2.978737         2.987622\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 641886  4.007708 -4.845201          681            0.000074         2.987622\n",
+       " 641887  4.009409 -4.845426          681            0.000066         2.987622\n",
+       " 641888  4.011111 -4.845651          681            0.000058         2.987622\n",
+       " 641889  4.012813 -4.845876          681            0.000051         2.987622\n",
+       " 641890  4.014514 -4.846101          681            0.000043         2.987622\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 642118  2.700801 -4.839991          682            2.975794         2.979533\n",
+       " 642119  2.702502 -4.839916          682            2.974881         2.979533\n",
+       " 642120  2.704204 -4.839841          682            2.973968         2.979533\n",
+       " 642121  2.705906 -4.839795          682            2.973053         2.979533\n",
+       " 642122  2.707608 -4.839869          682            2.972127         2.979533\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 642886  4.007708 -4.843517          682            0.000072         2.979533\n",
+       " 642887  4.009409 -4.843667          682            0.000064         2.979533\n",
+       " 642888  4.011111 -4.843817          682            0.000056         2.979533\n",
+       " 642889  4.012813 -4.843967          682            0.000048         2.979533\n",
+       " 642890  4.014514 -4.844117          682            0.000040         2.979533\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 643118  2.700801 -4.840163          683            2.970276         2.974119\n",
+       " 643119  2.702502 -4.840001          683            2.969386         2.974119\n",
+       " 643120  2.704204 -4.839839          683            2.968496         2.974119\n",
+       " 643121  2.705906 -4.839878          683            2.967568         2.974119\n",
+       " 643122  2.707608 -4.840031          683            2.966619         2.974119\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 643886  4.007708 -4.843897          683            0.000072         2.974119\n",
+       " 643887  4.009409 -4.844062          683            0.000064         2.974119\n",
+       " 643888  4.011111 -4.844228          683            0.000057         2.974119\n",
+       " 643889  4.012813 -4.844394          683            0.000049         2.974119\n",
+       " 643890  4.014514 -4.844559          683            0.000041         2.974119\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 644118  2.700801 -4.840009          684            2.965497          2.96867\n",
+       " 644119  2.702502 -4.840009          684            2.964593          2.96867\n",
+       " 644120  2.704204 -4.840009          684            2.963689          2.96867\n",
+       " 644121  2.705906 -4.839984          684            2.962775          2.96867\n",
+       " 644122  2.707608 -4.839910          684            2.961840          2.96867\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 644885  4.006006 -4.843620          684            0.000078          2.96867\n",
+       " 644886  4.007708 -4.843770          684            0.000070          2.96867\n",
+       " 644887  4.009409 -4.843919          684            0.000063          2.96867\n",
+       " 644888  4.011111 -4.844068          684            0.000055          2.96867\n",
+       " 644889  4.012813 -4.844217          684            0.000047          2.96867\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 645118  2.700801 -4.839847          685            2.962600         2.965771\n",
+       " 645119  2.702502 -4.839988          685            2.961684         2.965771\n",
+       " 645120  2.704204 -4.840072          685            2.960760         2.965771\n",
+       " 645121  2.705906 -4.840146          685            2.959834         2.965771\n",
+       " 645122  2.707608 -4.840220          685            2.958909         2.965771\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 645885  4.006006 -4.844532          685            0.000078         2.965771\n",
+       " 645886  4.007708 -4.844732          685            0.000070         2.965771\n",
+       " 645887  4.009409 -4.844932          685            0.000062         2.965771\n",
+       " 645888  4.011111 -4.845132          685            0.000054         2.965771\n",
+       " 645889  4.012813 -4.845332          685            0.000046         2.965771\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 646118  2.700801 -4.840123          686            2.961902         2.964082\n",
+       " 646119  2.702502 -4.840238          686            2.960984         2.964082\n",
+       " 646120  2.704204 -4.840238          686            2.960062         2.964082\n",
+       " 646121  2.705906 -4.840238          686            2.959140         2.964082\n",
+       " 646122  2.707608 -4.840160          686            2.958198         2.964082\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 646886  4.007708 -4.844396          686            0.000073         2.964082\n",
+       " 646887  4.009409 -4.844606          686            0.000065         2.964082\n",
+       " 646888  4.011111 -4.844817          686            0.000057         2.964082\n",
+       " 646889  4.012813 -4.845027          686            0.000049         2.964082\n",
+       " 646890  4.014514 -4.845238          686            0.000041         2.964082\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 647118  2.700801 -4.839843          687            2.955335         2.958286\n",
+       " 647119  2.702502 -4.839977          687            2.954435         2.958286\n",
+       " 647120  2.704204 -4.839953          687            2.953496         2.958286\n",
+       " 647121  2.705906 -4.839879          687            2.952544         2.958286\n",
+       " 647122  2.707608 -4.839805          687            2.951592         2.958286\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 647885  4.006006 -4.843212          687            0.000076         2.958286\n",
+       " 647886  4.007708 -4.843362          687            0.000068         2.958286\n",
+       " 647887  4.009409 -4.843512          687            0.000060         2.958286\n",
+       " 647888  4.011111 -4.843662          687            0.000052         2.958286\n",
+       " 647889  4.012813 -4.843812          687            0.000044         2.958286\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 648118  2.700801 -4.839751          688            2.962671          2.96465\n",
+       " 648119  2.702502 -4.839601          688            2.961749          2.96465\n",
+       " 648120  2.704204 -4.839450          688            2.960828          2.96465\n",
+       " 648121  2.705906 -4.839345          688            2.959902          2.96465\n",
+       " 648122  2.707608 -4.839495          688            2.958954          2.96465\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 648886  4.007708 -4.843477          688            0.000074          2.96465\n",
+       " 648887  4.009409 -4.843627          688            0.000066          2.96465\n",
+       " 648888  4.011111 -4.843777          688            0.000058          2.96465\n",
+       " 648889  4.012813 -4.843927          688            0.000050          2.96465\n",
+       " 648890  4.014514 -4.844077          688            0.000042          2.96465\n",
+       " \n",
+       " [773 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 649118  2.700801 -4.840209          689            2.951691          2.95382\n",
+       " 649119  2.702502 -4.840133          689            2.950756          2.95382\n",
+       " 649120  2.704204 -4.840057          689            2.949821          2.95382\n",
+       " 649121  2.705906 -4.840009          689            2.948887          2.95382\n",
+       " 649122  2.707608 -4.840009          689            2.947956          2.95382\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 649885  4.006006 -4.844199          689            0.000076          2.95382\n",
+       " 649886  4.007708 -4.844383          689            0.000068          2.95382\n",
+       " 649887  4.009409 -4.844568          689            0.000060          2.95382\n",
+       " 649888  4.011111 -4.844752          689            0.000052          2.95382\n",
+       " 649889  4.012813 -4.844937          689            0.000044          2.95382\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 650118  2.700801 -4.839780          690            2.949601         2.952224\n",
+       " 650119  2.702502 -4.839780          690            2.948684         2.952224\n",
+       " 650120  2.704204 -4.839780          690            2.947766         2.952224\n",
+       " 650121  2.705906 -4.839780          690            2.946841         2.952224\n",
+       " 650122  2.707608 -4.839780          690            2.945897         2.952224\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 650885  4.006006 -4.844352          690            0.000076         2.952224\n",
+       " 650886  4.007708 -4.844553          690            0.000068         2.952224\n",
+       " 650887  4.009409 -4.844754          690            0.000060         2.952224\n",
+       " 650888  4.011111 -4.844955          690            0.000052         2.952224\n",
+       " 650889  4.012813 -4.845156          690            0.000044         2.952224\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 651118  2.700801 -4.840009          691            2.945487         2.948677\n",
+       " 651119  2.702502 -4.840009          691            2.944546         2.948677\n",
+       " 651120  2.704204 -4.840009          691            2.943604         2.948677\n",
+       " 651121  2.705906 -4.840009          691            2.942664         2.948677\n",
+       " 651122  2.707608 -4.840009          691            2.941725         2.948677\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 651885  4.006006 -4.843882          691            0.000075         2.948677\n",
+       " 651886  4.007708 -4.844040          691            0.000067         2.948677\n",
+       " 651887  4.009409 -4.844198          691            0.000059         2.948677\n",
+       " 651888  4.011111 -4.844357          691            0.000051         2.948677\n",
+       " 651889  4.012813 -4.844515          691            0.000043         2.948677\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 652118  2.700801 -4.839708          692            2.943688         2.946115\n",
+       " 652119  2.702502 -4.839553          692            2.942779         2.946115\n",
+       " 652120  2.704204 -4.839625          692            2.941823         2.946115\n",
+       " 652121  2.705906 -4.839701          692            2.940866         2.946115\n",
+       " 652122  2.707608 -4.839776          692            2.939909         2.946115\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 652885  4.006006 -4.843292          692            0.000075         2.946115\n",
+       " 652886  4.007708 -4.843425          692            0.000068         2.946115\n",
+       " 652887  4.009409 -4.843557          692            0.000060         2.946115\n",
+       " 652888  4.011111 -4.843690          692            0.000052         2.946115\n",
+       " 652889  4.012813 -4.843822          692            0.000044         2.946115\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 653118  2.700801 -4.839783          693            2.940758         2.943356\n",
+       " 653119  2.702502 -4.839296          693            2.939823         2.943356\n",
+       " 653120  2.704204 -4.839181          693            2.938875         2.943356\n",
+       " 653121  2.705906 -4.839331          693            2.937918         2.943356\n",
+       " 653122  2.707608 -4.839481          693            2.936961         2.943356\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 653885  4.006006 -4.843404          693            0.000074         2.943356\n",
+       " 653886  4.007708 -4.843570          693            0.000066         2.943356\n",
+       " 653887  4.009409 -4.843737          693            0.000058         2.943356\n",
+       " 653888  4.011111 -4.843903          693            0.000050         2.943356\n",
+       " 653889  4.012813 -4.844069          693            0.000043         2.943356\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 654118  2.700801 -4.840132          694            2.938538          2.94031\n",
+       " 654119  2.702502 -4.839905          694            2.937598          2.94031\n",
+       " 654120  2.704204 -4.839814          694            2.936645          2.94031\n",
+       " 654121  2.705906 -4.839889          694            2.935675          2.94031\n",
+       " 654122  2.707608 -4.839964          694            2.934705          2.94031\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 654885  4.006006 -4.843600          694            0.000075          2.94031\n",
+       " 654886  4.007708 -4.843766          694            0.000068          2.94031\n",
+       " 654887  4.009409 -4.843931          694            0.000060          2.94031\n",
+       " 654888  4.011111 -4.844096          694            0.000052          2.94031\n",
+       " 654889  4.012813 -4.844261          694            0.000044          2.94031\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 655118  2.700801 -4.839780          695            2.937010         2.938382\n",
+       " 655119  2.702502 -4.839780          695            2.936051         2.938382\n",
+       " 655120  2.704204 -4.839780          695            2.935092         2.938382\n",
+       " 655121  2.705906 -4.839889          695            2.934136         2.938382\n",
+       " 655122  2.707608 -4.840036          695            2.933180         2.938382\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 655885  4.006006 -4.844226          695            0.000073         2.938382\n",
+       " 655886  4.007708 -4.844418          695            0.000065         2.938382\n",
+       " 655887  4.009409 -4.844609          695            0.000058         2.938382\n",
+       " 655888  4.011111 -4.844801          695            0.000050         2.938382\n",
+       " 655889  4.012813 -4.844993          695            0.000042         2.938382\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 656118  2.700801 -4.839852          696            2.934439         2.936456\n",
+       " 656119  2.702502 -4.840007          696            2.933503         2.936456\n",
+       " 656120  2.704204 -4.840162          696            2.932567         2.936456\n",
+       " 656121  2.705906 -4.840200          696            2.931623         2.936456\n",
+       " 656122  2.707608 -4.840125          696            2.930670         2.936456\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 656885  4.006006 -4.842883          696            0.000073         2.936456\n",
+       " 656886  4.007708 -4.843016          696            0.000065         2.936456\n",
+       " 656887  4.009409 -4.843150          696            0.000057         2.936456\n",
+       " 656888  4.011111 -4.843284          696            0.000049         2.936456\n",
+       " 656889  4.012813 -4.843418          696            0.000041         2.936456\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 657118  2.700801 -4.839780          697            2.932684         2.934563\n",
+       " 657119  2.702502 -4.839780          697            2.931761         2.934563\n",
+       " 657120  2.704204 -4.839800          697            2.930832         2.934563\n",
+       " 657121  2.705906 -4.839951          697            2.929857         2.934563\n",
+       " 657122  2.707608 -4.840101          697            2.928883         2.934563\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 657885  4.006006 -4.844590          697            0.000074         2.934563\n",
+       " 657886  4.007708 -4.844799          697            0.000066         2.934563\n",
+       " 657887  4.009409 -4.845008          697            0.000058         2.934563\n",
+       " 657888  4.011111 -4.845218          697            0.000050         2.934563\n",
+       " 657889  4.012813 -4.845427          697            0.000043         2.934563\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 658118  2.700801 -4.839826          698            2.927473         2.930382\n",
+       " 658119  2.702502 -4.839846          698            2.926540         2.930382\n",
+       " 658120  2.704204 -4.839920          698            2.925597         2.930382\n",
+       " 658121  2.705906 -4.839993          698            2.924654         2.930382\n",
+       " 658122  2.707608 -4.840009          698            2.923690         2.930382\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 658885  4.006006 -4.842913          698            0.000073         2.930382\n",
+       " 658886  4.007708 -4.843040          698            0.000065         2.930382\n",
+       " 658887  4.009409 -4.843166          698            0.000057         2.930382\n",
+       " 658888  4.011111 -4.843293          698            0.000049         2.930382\n",
+       " 658889  4.012813 -4.843420          698            0.000041         2.930382\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 659118  2.700801 -4.839776          699            2.926358         2.927585\n",
+       " 659119  2.702502 -4.839699          699            2.925382         2.927585\n",
+       " 659120  2.704204 -4.839623          699            2.924406         2.927585\n",
+       " 659121  2.705906 -4.839556          699            2.923431         2.927585\n",
+       " 659122  2.707608 -4.839631          699            2.922456         2.927585\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 659885  4.006006 -4.843085          699            0.000074         2.927585\n",
+       " 659886  4.007708 -4.843220          699            0.000066         2.927585\n",
+       " 659887  4.009409 -4.843354          699            0.000058         2.927585\n",
+       " 659888  4.011111 -4.843488          699            0.000050         2.927585\n",
+       " 659889  4.012813 -4.843623          699            0.000043         2.927585\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 660118  2.700801 -4.839670          700            2.921970         2.924419\n",
+       " 660119  2.702502 -4.839926          700            2.921020         2.924419\n",
+       " 660120  2.704204 -4.840181          700            2.920071         2.924419\n",
+       " 660121  2.705906 -4.840122          700            2.919112         2.924419\n",
+       " 660122  2.707608 -4.839972          700            2.918151         2.924419\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 660885  4.006006 -4.844917          700            0.000072         2.924419\n",
+       " 660886  4.007708 -4.845118          700            0.000064         2.924419\n",
+       " 660887  4.009409 -4.845319          700            0.000056         2.924419\n",
+       " 660888  4.011111 -4.845520          700            0.000048         2.924419\n",
+       " 660889  4.012813 -4.845722          700            0.000040         2.924419\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 661118  2.700801 -4.839780          701            2.918879         2.920787\n",
+       " 661119  2.702502 -4.839780          701            2.917932         2.920787\n",
+       " 661120  2.704204 -4.839780          701            2.916984         2.920787\n",
+       " 661121  2.705906 -4.839780          701            2.916025         2.920787\n",
+       " 661122  2.707608 -4.839780          701            2.915059         2.920787\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 661884  4.004304 -4.843800          701            0.000079         2.920787\n",
+       " 661885  4.006006 -4.843958          701            0.000071         2.920787\n",
+       " 661886  4.007708 -4.844117          701            0.000063         2.920787\n",
+       " 661887  4.009409 -4.844276          701            0.000055         2.920787\n",
+       " 661888  4.011111 -4.844435          701            0.000047         2.920787\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 662118  2.700801 -4.840009          702            2.916363         2.917153\n",
+       " 662119  2.702502 -4.840009          702            2.915414         2.917153\n",
+       " 662120  2.704204 -4.839986          702            2.914457         2.917153\n",
+       " 662121  2.705906 -4.839911          702            2.913482         2.917153\n",
+       " 662122  2.707608 -4.839836          702            2.912507         2.917153\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 662884  4.004304 -4.843188          702            0.000077         2.917153\n",
+       " 662885  4.006006 -4.843338          702            0.000069         2.917153\n",
+       " 662886  4.007708 -4.843489          702            0.000061         2.917153\n",
+       " 662887  4.009409 -4.843639          702            0.000053         2.917153\n",
+       " 662888  4.011111 -4.843790          702            0.000045         2.917153\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 663118  2.700801 -4.840069          703            2.914379         2.916182\n",
+       " 663119  2.702502 -4.840196          703            2.913412         2.916182\n",
+       " 663120  2.704204 -4.840187          703            2.912460         2.916182\n",
+       " 663121  2.705906 -4.840111          703            2.911516         2.916182\n",
+       " 663122  2.707608 -4.840034          703            2.910572         2.916182\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 663884  4.004304 -4.843622          703            0.000076         2.916182\n",
+       " 663885  4.006006 -4.843781          703            0.000068         2.916182\n",
+       " 663886  4.007708 -4.843939          703            0.000060         2.916182\n",
+       " 663887  4.009409 -4.844098          703            0.000053         2.916182\n",
+       " 663888  4.011111 -4.844256          703            0.000045         2.916182\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 664118  2.700801 -4.840135          704            2.913714          2.91372\n",
+       " 664119  2.702502 -4.840403          704            2.912791          2.91372\n",
+       " 664120  2.704204 -4.840353          704            2.911835          2.91372\n",
+       " 664121  2.705906 -4.840202          704            2.910869          2.91372\n",
+       " 664122  2.707608 -4.840052          704            2.909903          2.91372\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 664884  4.004304 -4.843554          704            0.000076          2.91372\n",
+       " 664885  4.006006 -4.843729          704            0.000068          2.91372\n",
+       " 664886  4.007708 -4.843904          704            0.000060          2.91372\n",
+       " 664887  4.009409 -4.844078          704            0.000052          2.91372\n",
+       " 664888  4.011111 -4.844253          704            0.000044          2.91372\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 665118  2.700801 -4.839780          705            2.911514         2.913506\n",
+       " 665119  2.702502 -4.839780          705            2.910544         2.913506\n",
+       " 665120  2.704204 -4.839780          705            2.909595         2.913506\n",
+       " 665121  2.705906 -4.839780          705            2.908648         2.913506\n",
+       " 665122  2.707608 -4.839780          705            2.907700         2.913506\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 665884  4.004304 -4.844225          705            0.000075         2.913506\n",
+       " 665885  4.006006 -4.844409          705            0.000067         2.913506\n",
+       " 665886  4.007708 -4.844592          705            0.000059         2.913506\n",
+       " 665887  4.009409 -4.844776          705            0.000051         2.913506\n",
+       " 665888  4.011111 -4.844959          705            0.000043         2.913506\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 666118  2.700801 -4.839930          706            2.910614         2.911071\n",
+       " 666119  2.702502 -4.839771          706            2.909671         2.911071\n",
+       " 666120  2.704204 -4.839695          706            2.908705         2.911071\n",
+       " 666121  2.705906 -4.839619          706            2.907738         2.911071\n",
+       " 666122  2.707608 -4.839560          706            2.906773         2.911071\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 666884  4.004304 -4.844631          706            0.000074         2.911071\n",
+       " 666885  4.006006 -4.844830          706            0.000066         2.911071\n",
+       " 666886  4.007708 -4.845029          706            0.000058         2.911071\n",
+       " 666887  4.009409 -4.845229          706            0.000050         2.911071\n",
+       " 666888  4.011111 -4.845428          706            0.000043         2.911071\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 667118  2.700801 -4.839924          707            2.908702         2.909965\n",
+       " 667119  2.702502 -4.839812          707            2.907732         2.909965\n",
+       " 667120  2.704204 -4.839962          707            2.906780         2.909965\n",
+       " 667121  2.705906 -4.840112          707            2.905827         2.909965\n",
+       " 667122  2.707608 -4.840226          707            2.904870         2.909965\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 667884  4.004304 -4.844193          707            0.000073         2.909965\n",
+       " 667885  4.006006 -4.844392          707            0.000065         2.909965\n",
+       " 667886  4.007708 -4.844591          707            0.000057         2.909965\n",
+       " 667887  4.009409 -4.844790          707            0.000050         2.909965\n",
+       " 667888  4.011111 -4.844988          707            0.000042         2.909965\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 668118  2.700801 -4.840410          708            2.906978         2.908902\n",
+       " 668119  2.702502 -4.840261          708            2.906012         2.908902\n",
+       " 668120  2.704204 -4.840110          708            2.905046         2.908902\n",
+       " 668121  2.705906 -4.840009          708            2.904073         2.908902\n",
+       " 668122  2.707608 -4.840009          708            2.903085         2.908902\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 668884  4.004304 -4.844831          708            0.000072         2.908902\n",
+       " 668885  4.006006 -4.845046          708            0.000064         2.908902\n",
+       " 668886  4.007708 -4.845261          708            0.000057         2.908902\n",
+       " 668887  4.009409 -4.845475          708            0.000049         2.908902\n",
+       " 668888  4.011111 -4.845689          708            0.000041         2.908902\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 669118  2.700801 -4.839982          709            2.904256          2.90648\n",
+       " 669119  2.702502 -4.839909          709            2.903275          2.90648\n",
+       " 669120  2.704204 -4.839836          709            2.902294          2.90648\n",
+       " 669121  2.705906 -4.839798          709            2.901320          2.90648\n",
+       " 669122  2.707608 -4.839873          709            2.900367          2.90648\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 669884  4.004304 -4.845219          709            0.000071          2.90648\n",
+       " 669885  4.006006 -4.845458          709            0.000063          2.90648\n",
+       " 669886  4.007708 -4.845697          709            0.000056          2.90648\n",
+       " 669887  4.009409 -4.845936          709            0.000048          2.90648\n",
+       " 669888  4.011111 -4.846174          709            0.000040          2.90648\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 670118  2.700801 -4.839979          710            2.903217         2.904952\n",
+       " 670119  2.702502 -4.840009          710            2.902246         2.904952\n",
+       " 670120  2.704204 -4.840009          710            2.901276         2.904952\n",
+       " 670121  2.705906 -4.840009          710            2.900306         2.904952\n",
+       " 670122  2.707608 -4.839879          710            2.899322         2.904952\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 670884  4.004304 -4.844621          710            0.000072         2.904952\n",
+       " 670885  4.006006 -4.844835          710            0.000064         2.904952\n",
+       " 670886  4.007708 -4.845050          710            0.000056         2.904952\n",
+       " 670887  4.009409 -4.845265          710            0.000048         2.904952\n",
+       " 670888  4.011111 -4.845479          710            0.000041         2.904952\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 671118  2.700801 -4.839780          711            2.900558         2.903006\n",
+       " 671119  2.702502 -4.839901          711            2.899579         2.903006\n",
+       " 671120  2.704204 -4.840054          711            2.898590         2.903006\n",
+       " 671121  2.705906 -4.840206          711            2.897601         2.903006\n",
+       " 671122  2.707608 -4.840180          711            2.896615         2.903006\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 671884  4.004304 -4.845686          711            0.000071         2.903006\n",
+       " 671885  4.006006 -4.845925          711            0.000063         2.903006\n",
+       " 671886  4.007708 -4.846165          711            0.000055         2.903006\n",
+       " 671887  4.009409 -4.846404          711            0.000048         2.903006\n",
+       " 671888  4.011111 -4.846643          711            0.000040         2.903006\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 672118  2.700801 -4.839780          712            2.897486         2.900149\n",
+       " 672119  2.702502 -4.839852          712            2.896547         2.900149\n",
+       " 672120  2.704204 -4.839926          712            2.895608         2.900149\n",
+       " 672121  2.705906 -4.840000          712            2.894669         2.900149\n",
+       " 672122  2.707608 -4.839943          712            2.893664         2.900149\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 672884  4.004304 -4.844929          712            0.000071         2.900149\n",
+       " 672885  4.006006 -4.845126          712            0.000063         2.900149\n",
+       " 672886  4.007708 -4.845324          712            0.000056         2.900149\n",
+       " 672887  4.009409 -4.845521          712            0.000048         2.900149\n",
+       " 672888  4.011111 -4.845719          712            0.000040         2.900149\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 673118  2.700801 -4.839869          713            2.895497         2.897767\n",
+       " 673119  2.702502 -4.839727          713            2.894531         2.897767\n",
+       " 673120  2.704204 -4.839651          713            2.893560         2.897767\n",
+       " 673121  2.705906 -4.839574          713            2.892589         2.897767\n",
+       " 673122  2.707608 -4.839658          713            2.891580         2.897767\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 673884  4.004304 -4.845294          713            0.000071         2.897767\n",
+       " 673885  4.006006 -4.845517          713            0.000063         2.897767\n",
+       " 673886  4.007708 -4.845740          713            0.000055         2.897767\n",
+       " 673887  4.009409 -4.845963          713            0.000048         2.897767\n",
+       " 673888  4.011111 -4.846185          713            0.000040         2.897767\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 674118  2.700801 -4.839816          714            2.893458         2.895523\n",
+       " 674119  2.702502 -4.839892          714            2.892487         2.895523\n",
+       " 674120  2.704204 -4.839968          714            2.891515         2.895523\n",
+       " 674121  2.705906 -4.839975          714            2.890535         2.895523\n",
+       " 674122  2.707608 -4.839901          714            2.889544         2.895523\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 674883  4.002603 -4.845297          714            0.000077         2.895523\n",
+       " 674884  4.004304 -4.845529          714            0.000070         2.895523\n",
+       " 674885  4.006006 -4.845761          714            0.000062         2.895523\n",
+       " 674886  4.007708 -4.845992          714            0.000054         2.895523\n",
+       " 674887  4.009409 -4.846224          714            0.000046         2.895523\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 675118  2.700801 -4.839673          715            2.892637         2.894035\n",
+       " 675119  2.702502 -4.839932          715            2.891636         2.894035\n",
+       " 675120  2.704204 -4.840191          715            2.890635         2.894035\n",
+       " 675121  2.705906 -4.840118          715            2.889657         2.894035\n",
+       " 675122  2.707608 -4.839972          715            2.888685         2.894035\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 675884  4.004304 -4.844122          715            0.000071         2.894035\n",
+       " 675885  4.006006 -4.844295          715            0.000063         2.894035\n",
+       " 675886  4.007708 -4.844468          715            0.000055         2.894035\n",
+       " 675887  4.009409 -4.844640          715            0.000048         2.894035\n",
+       " 675888  4.011111 -4.844813          715            0.000040         2.894035\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 676118  2.700801 -4.840661          716            2.888884         2.891839\n",
+       " 676119  2.702502 -4.840584          716            2.887877         2.891839\n",
+       " 676120  2.704204 -4.840508          716            2.886869         2.891839\n",
+       " 676121  2.705906 -4.840364          716            2.885872         2.891839\n",
+       " 676122  2.707608 -4.840142          716            2.884885         2.891839\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 676883  4.002603 -4.844108          716            0.000078         2.891839\n",
+       " 676884  4.004304 -4.844296          716            0.000070         2.891839\n",
+       " 676885  4.006006 -4.844485          716            0.000063         2.891839\n",
+       " 676886  4.007708 -4.844673          716            0.000055         2.891839\n",
+       " 676887  4.009409 -4.844862          716            0.000047         2.891839\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 677118  2.700801 -4.839762          717            2.886708         2.888338\n",
+       " 677119  2.702502 -4.839686          717            2.885724         2.888338\n",
+       " 677120  2.704204 -4.839610          717            2.884739         2.888338\n",
+       " 677121  2.705906 -4.839604          717            2.883756         2.888338\n",
+       " 677122  2.707608 -4.839826          717            2.882778         2.888338\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 677883  4.002603 -4.845107          717            0.000076         2.888338\n",
+       " 677884  4.004304 -4.845339          717            0.000068         2.888338\n",
+       " 677885  4.006006 -4.845572          717            0.000060         2.888338\n",
+       " 677886  4.007708 -4.845804          717            0.000053         2.888338\n",
+       " 677887  4.009409 -4.846036          717            0.000045         2.888338\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 678118  2.700801 -4.840009          718            2.884350         2.886404\n",
+       " 678119  2.702502 -4.840009          718            2.883324         2.886404\n",
+       " 678120  2.704204 -4.840009          718            2.882298         2.886404\n",
+       " 678121  2.705906 -4.840009          718            2.881284         2.886404\n",
+       " 678122  2.707608 -4.840009          718            2.880291         2.886404\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 678883  4.002603 -4.844538          718            0.000078         2.886404\n",
+       " 678884  4.004304 -4.844735          718            0.000070         2.886404\n",
+       " 678885  4.006006 -4.844933          718            0.000062         2.886404\n",
+       " 678886  4.007708 -4.845130          718            0.000054         2.886404\n",
+       " 678887  4.009409 -4.845328          718            0.000047         2.886404\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 679118  2.700801 -4.840009          719            2.882020         2.884162\n",
+       " 679119  2.702502 -4.840009          719            2.881027         2.884162\n",
+       " 679120  2.704204 -4.840009          719            2.880034         2.884162\n",
+       " 679121  2.705906 -4.839901          719            2.879030         2.884162\n",
+       " 679122  2.707608 -4.839753          719            2.878022         2.884162\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 679883  4.002603 -4.843778          719            0.000078         2.884162\n",
+       " 679884  4.004304 -4.843942          719            0.000070         2.884162\n",
+       " 679885  4.006006 -4.844107          719            0.000062         2.884162\n",
+       " 679886  4.007708 -4.844271          719            0.000055         2.884162\n",
+       " 679887  4.009409 -4.844435          719            0.000047         2.884162\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 680118  2.700801 -4.840141          720            2.879889          2.88224\n",
+       " 680119  2.702502 -4.840238          720            2.878873          2.88224\n",
+       " 680120  2.704204 -4.840238          720            2.877883          2.88224\n",
+       " 680121  2.705906 -4.840238          720            2.876894          2.88224\n",
+       " 680122  2.707608 -4.840161          720            2.875885          2.88224\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 680883  4.002603 -4.844307          720            0.000078          2.88224\n",
+       " 680884  4.004304 -4.844505          720            0.000070          2.88224\n",
+       " 680885  4.006006 -4.844703          720            0.000062          2.88224\n",
+       " 680886  4.007708 -4.844901          720            0.000054          2.88224\n",
+       " 680887  4.009409 -4.845099          720            0.000047          2.88224\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 681118  2.700801 -4.839582          721            2.877394         2.878976\n",
+       " 681119  2.702502 -4.839619          721            2.876406         2.878976\n",
+       " 681120  2.704204 -4.839692          721            2.875421         2.878976\n",
+       " 681121  2.705906 -4.839765          721            2.874435         2.878976\n",
+       " 681122  2.707608 -4.839900          721            2.873401         2.878976\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 681883  4.002603 -4.844110          721            0.000076         2.878976\n",
+       " 681884  4.004304 -4.844306          721            0.000069         2.878976\n",
+       " 681885  4.006006 -4.844503          721            0.000061         2.878976\n",
+       " 681886  4.007708 -4.844700          721            0.000053         2.878976\n",
+       " 681887  4.009409 -4.844897          721            0.000045         2.878976\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 682118  2.700801 -4.839593          722            2.874871         2.877067\n",
+       " 682119  2.702502 -4.839683          722            2.873856         2.877067\n",
+       " 682120  2.704204 -4.839772          722            2.872840         2.877067\n",
+       " 682121  2.705906 -4.839919          722            2.871804         2.877067\n",
+       " 682122  2.707608 -4.840072          722            2.870766         2.877067\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 682883  4.002603 -4.844037          722            0.000076         2.877067\n",
+       " 682884  4.004304 -4.844201          722            0.000069         2.877067\n",
+       " 682885  4.006006 -4.844365          722            0.000061         2.877067\n",
+       " 682886  4.007708 -4.844529          722            0.000053         2.877067\n",
+       " 682887  4.009409 -4.844693          722            0.000045         2.877067\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 683118  2.700801 -4.839972          723            2.873206         2.874321\n",
+       " 683119  2.702502 -4.839894          723            2.872196         2.874321\n",
+       " 683120  2.704204 -4.839816          723            2.871186         2.874321\n",
+       " 683121  2.705906 -4.839821          723            2.870179         2.874321\n",
+       " 683122  2.707608 -4.839895          723            2.869175         2.874321\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 683883  4.002603 -4.843280          723            0.000076         2.874321\n",
+       " 683884  4.004304 -4.843410          723            0.000068         2.874321\n",
+       " 683885  4.006006 -4.843541          723            0.000061         2.874321\n",
+       " 683886  4.007708 -4.843672          723            0.000053         2.874321\n",
+       " 683887  4.009409 -4.843802          723            0.000045         2.874321\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 684118  2.700801 -4.839660          724            2.871153         2.873366\n",
+       " 684119  2.702502 -4.839891          724            2.870121         2.873366\n",
+       " 684120  2.704204 -4.840124          724            2.869090         2.873366\n",
+       " 684121  2.705906 -4.840201          724            2.868089         2.873366\n",
+       " 684122  2.707608 -4.840128          724            2.867116         2.873366\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 684883  4.002603 -4.844565          724            0.000075         2.873366\n",
+       " 684884  4.004304 -4.844770          724            0.000067         2.873366\n",
+       " 684885  4.006006 -4.844975          724            0.000060         2.873366\n",
+       " 684886  4.007708 -4.845181          724            0.000052         2.873366\n",
+       " 684887  4.009409 -4.845386          724            0.000044         2.873366\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 685118  2.700801 -4.840119          725            2.870393         2.871395\n",
+       " 685119  2.702502 -4.839864          725            2.869403         2.871395\n",
+       " 685120  2.704204 -4.839609          725            2.868413         2.871395\n",
+       " 685121  2.705906 -4.839668          725            2.867415         2.871395\n",
+       " 685122  2.707608 -4.839818          725            2.866414         2.871395\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 685883  4.002603 -4.845577          725            0.000074         2.871395\n",
+       " 685884  4.004304 -4.845816          725            0.000067         2.871395\n",
+       " 685885  4.006006 -4.846055          725            0.000059         2.871395\n",
+       " 685886  4.007708 -4.846294          725            0.000051         2.871395\n",
+       " 685887  4.009409 -4.846532          725            0.000043         2.871395\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 686118  2.700801 -4.840192          726            2.869633         2.871016\n",
+       " 686119  2.702502 -4.840094          726            2.868630         2.871016\n",
+       " 686120  2.704204 -4.840009          726            2.867623         2.871016\n",
+       " 686121  2.705906 -4.840009          726            2.866593         2.871016\n",
+       " 686122  2.707608 -4.840009          726            2.865564         2.871016\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 686883  4.002603 -4.841976          726            0.000073         2.871016\n",
+       " 686884  4.004304 -4.842050          726            0.000066         2.871016\n",
+       " 686885  4.006006 -4.842124          726            0.000058         2.871016\n",
+       " 686886  4.007708 -4.842198          726            0.000050         2.871016\n",
+       " 686887  4.009409 -4.842273          726            0.000042         2.871016\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 687118  2.700801 -4.840009          727            2.867665         2.869601\n",
+       " 687119  2.702502 -4.840009          727            2.866680         2.869601\n",
+       " 687120  2.704204 -4.839921          727            2.865672         2.869601\n",
+       " 687121  2.705906 -4.839768          727            2.864647         2.869601\n",
+       " 687122  2.707608 -4.839615          727            2.863622         2.869601\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 687883  4.002603 -4.843414          727            0.000073         2.869601\n",
+       " 687884  4.004304 -4.843578          727            0.000066         2.869601\n",
+       " 687885  4.006006 -4.843743          727            0.000058         2.869601\n",
+       " 687886  4.007708 -4.843908          727            0.000050         2.869601\n",
+       " 687887  4.009409 -4.844072          727            0.000042         2.869601\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 688118  2.700801 -4.839822          728            2.864695         2.867468\n",
+       " 688119  2.702502 -4.839903          728            2.863719         2.867468\n",
+       " 688120  2.704204 -4.839984          728            2.862744         2.867468\n",
+       " 688121  2.705906 -4.839957          728            2.861743         2.867468\n",
+       " 688122  2.707608 -4.839881          728            2.860732         2.867468\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 688883  4.002603 -4.844284          728            0.000074         2.867468\n",
+       " 688884  4.004304 -4.844456          728            0.000066         2.867468\n",
+       " 688885  4.006006 -4.844627          728            0.000058         2.867468\n",
+       " 688886  4.007708 -4.844799          728            0.000051         2.867468\n",
+       " 688887  4.009409 -4.844970          728            0.000043         2.867468\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 689118  2.700801 -4.839962          729            2.865809         2.866245\n",
+       " 689119  2.702502 -4.839862          729            2.864821         2.866245\n",
+       " 689120  2.704204 -4.839767          729            2.863822         2.866245\n",
+       " 689121  2.705906 -4.839692          729            2.862773         2.866245\n",
+       " 689122  2.707608 -4.839617          729            2.861723         2.866245\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 689883  4.002603 -4.844268          729            0.000073         2.866245\n",
+       " 689884  4.004304 -4.844449          729            0.000065         2.866245\n",
+       " 689885  4.006006 -4.844629          729            0.000057         2.866245\n",
+       " 689886  4.007708 -4.844810          729            0.000050         2.866245\n",
+       " 689887  4.009409 -4.844991          729            0.000042         2.866245\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 690118  2.700801 -4.840213          730            2.863623         2.866226\n",
+       " 690119  2.702502 -4.840138          730            2.862618         2.866226\n",
+       " 690120  2.704204 -4.840063          730            2.861613         2.866226\n",
+       " 690121  2.705906 -4.840009          730            2.860602         2.866226\n",
+       " 690122  2.707608 -4.840009          730            2.859577         2.866226\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 690883  4.002603 -4.843198          730            0.000074         2.866226\n",
+       " 690884  4.004304 -4.843353          730            0.000067         2.866226\n",
+       " 690885  4.006006 -4.843509          730            0.000059         2.866226\n",
+       " 690886  4.007708 -4.843664          730            0.000051         2.866226\n",
+       " 690887  4.009409 -4.843819          730            0.000044         2.866226\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 691118  2.700801 -4.839962          731            2.862168         2.864061\n",
+       " 691119  2.702502 -4.839862          731            2.861157         2.864061\n",
+       " 691120  2.704204 -4.839780          731            2.860142         2.864061\n",
+       " 691121  2.705906 -4.839780          731            2.859110         2.864061\n",
+       " 691122  2.707608 -4.839780          731            2.858078         2.864061\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 691883  4.002603 -4.843863          731            0.000074         2.864061\n",
+       " 691884  4.004304 -4.844026          731            0.000066         2.864061\n",
+       " 691885  4.006006 -4.844189          731            0.000058         2.864061\n",
+       " 691886  4.007708 -4.844353          731            0.000051         2.864061\n",
+       " 691887  4.009409 -4.844516          731            0.000043         2.864061\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 692118  2.700801 -4.839869          732            2.859254         2.861887\n",
+       " 692119  2.702502 -4.839569          732            2.858222         2.861887\n",
+       " 692120  2.704204 -4.839621          732            2.857217         2.861887\n",
+       " 692121  2.705906 -4.839695          732            2.856213         2.861887\n",
+       " 692122  2.707608 -4.839769          732            2.855209         2.861887\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 692883  4.002603 -4.845350          732            0.000072         2.861887\n",
+       " 692884  4.004304 -4.845604          732            0.000064         2.861887\n",
+       " 692885  4.006006 -4.845858          732            0.000057         2.861887\n",
+       " 692886  4.007708 -4.846111          732            0.000049         2.861887\n",
+       " 692887  4.009409 -4.846365          732            0.000041         2.861887\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 693118  2.700801 -4.839605          733            2.858211         2.860032\n",
+       " 693119  2.702502 -4.839722          733            2.857162         2.860032\n",
+       " 693120  2.704204 -4.839853          733            2.856117         2.860032\n",
+       " 693121  2.705906 -4.840001          733            2.855078         2.860032\n",
+       " 693122  2.707608 -4.840149          733            2.854040         2.860032\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 693883  4.002603 -4.842171          733            0.000073         2.860032\n",
+       " 693884  4.004304 -4.842252          733            0.000066         2.860032\n",
+       " 693885  4.006006 -4.842333          733            0.000058         2.860032\n",
+       " 693886  4.007708 -4.842414          733            0.000050         2.860032\n",
+       " 693887  4.009409 -4.842495          733            0.000043         2.860032\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 694118  2.700801 -4.840009          734            2.856916         2.858305\n",
+       " 694119  2.702502 -4.840009          734            2.855914         2.858305\n",
+       " 694120  2.704204 -4.840009          734            2.854909         2.858305\n",
+       " 694121  2.705906 -4.840009          734            2.853890         2.858305\n",
+       " 694122  2.707608 -4.840009          734            2.852871         2.858305\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 694883  4.002603 -4.843709          734            0.000072         2.858305\n",
+       " 694884  4.004304 -4.843864          734            0.000064         2.858305\n",
+       " 694885  4.006006 -4.844020          734            0.000056         2.858305\n",
+       " 694886  4.007708 -4.844176          734            0.000049         2.858305\n",
+       " 694887  4.009409 -4.844332          734            0.000041         2.858305\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 695118  2.700801 -4.839958          735            2.856030         2.857104\n",
+       " 695119  2.702502 -4.839847          735            2.855033         2.857104\n",
+       " 695120  2.704204 -4.839842          735            2.854019         2.857104\n",
+       " 695121  2.705906 -4.839994          735            2.852981         2.857104\n",
+       " 695122  2.707608 -4.840147          735            2.851942         2.857104\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 695883  4.002603 -4.843808          735            0.000073         2.857104\n",
+       " 695884  4.004304 -4.843987          735            0.000065         2.857104\n",
+       " 695885  4.006006 -4.844166          735            0.000058         2.857104\n",
+       " 695886  4.007708 -4.844346          735            0.000050         2.857104\n",
+       " 695887  4.009409 -4.844525          735            0.000042         2.857104\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 696118  2.700801 -4.839516          736            2.854698         2.856763\n",
+       " 696119  2.702502 -4.839440          736            2.853669         2.856763\n",
+       " 696120  2.704204 -4.839364          736            2.852639         2.856763\n",
+       " 696121  2.705906 -4.839428          736            2.851610         2.856763\n",
+       " 696122  2.707608 -4.839657          736            2.850580         2.856763\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 696883  4.002603 -4.843902          736            0.000074         2.856763\n",
+       " 696884  4.004304 -4.844057          736            0.000066         2.856763\n",
+       " 696885  4.006006 -4.844211          736            0.000058         2.856763\n",
+       " 696886  4.007708 -4.844366          736            0.000051         2.856763\n",
+       " 696887  4.009409 -4.844520          736            0.000043         2.856763\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 697118  2.700801 -4.840046          737            2.850708         2.853718\n",
+       " 697119  2.702502 -4.840124          737            2.849683         2.853718\n",
+       " 697120  2.704204 -4.840203          737            2.848659         2.853718\n",
+       " 697121  2.705906 -4.840238          737            2.847619         2.853718\n",
+       " 697122  2.707608 -4.840238          737            2.846565         2.853718\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 697883  4.002603 -4.844431          737            0.000071         2.853718\n",
+       " 697884  4.004304 -4.844635          737            0.000064         2.853718\n",
+       " 697885  4.006006 -4.844840          737            0.000056         2.853718\n",
+       " 697886  4.007708 -4.845045          737            0.000048         2.853718\n",
+       " 697887  4.009409 -4.845249          737            0.000041         2.853718\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 698118  2.700801 -4.839780          738            2.850116         2.851464\n",
+       " 698119  2.702502 -4.839780          738            2.849093         2.851464\n",
+       " 698120  2.704204 -4.839922          738            2.848070         2.851464\n",
+       " 698121  2.705906 -4.840072          738            2.847047         2.851464\n",
+       " 698122  2.707608 -4.840222          738            2.846024         2.851464\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 698883  4.002603 -4.844233          738            0.000073         2.851464\n",
+       " 698884  4.004304 -4.844419          738            0.000065         2.851464\n",
+       " 698885  4.006006 -4.844606          738            0.000058         2.851464\n",
+       " 698886  4.007708 -4.844793          738            0.000050         2.851464\n",
+       " 698887  4.009409 -4.844980          738            0.000042         2.851464\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 699118  2.700801 -4.839832          739            2.846903         2.848801\n",
+       " 699119  2.702502 -4.839943          739            2.845880         2.848801\n",
+       " 699120  2.704204 -4.840009          739            2.844846         2.848801\n",
+       " 699121  2.705906 -4.840009          739            2.843799         2.848801\n",
+       " 699122  2.707608 -4.840009          739            2.842752         2.848801\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 699882  4.000901 -4.843204          739            0.000078         2.848801\n",
+       " 699883  4.002603 -4.843343          739            0.000071         2.848801\n",
+       " 699884  4.004304 -4.843483          739            0.000063         2.848801\n",
+       " 699885  4.006006 -4.843623          739            0.000055         2.848801\n",
+       " 699886  4.007708 -4.843762          739            0.000047         2.848801\n",
+       " \n",
+       " [769 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 700118  2.700801 -4.839849          740            2.846474         2.848132\n",
+       " 700119  2.702502 -4.839997          740            2.845453         2.848132\n",
+       " 700120  2.704204 -4.840145          740            2.844431         2.848132\n",
+       " 700121  2.705906 -4.840209          740            2.843400         2.848132\n",
+       " 700122  2.707608 -4.840134          740            2.842353         2.848132\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 700883  4.002603 -4.843461          740            0.000073         2.848132\n",
+       " 700884  4.004304 -4.843616          740            0.000065         2.848132\n",
+       " 700885  4.006006 -4.843772          740            0.000057         2.848132\n",
+       " 700886  4.007708 -4.843927          740            0.000050         2.848132\n",
+       " 700887  4.009409 -4.844083          740            0.000042         2.848132\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 701118  2.700801 -4.840059          741            2.841650         2.844626\n",
+       " 701119  2.702502 -4.840165          741            2.840575         2.844626\n",
+       " 701120  2.704204 -4.840215          741            2.839513         2.844626\n",
+       " 701121  2.705906 -4.840141          741            2.838479         2.844626\n",
+       " 701122  2.707608 -4.840067          741            2.837445         2.844626\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 701883  4.002603 -4.843292          741            0.000072         2.844626\n",
+       " 701884  4.004304 -4.843439          741            0.000064         2.844626\n",
+       " 701885  4.006006 -4.843587          741            0.000056         2.844626\n",
+       " 701886  4.007708 -4.843735          741            0.000048         2.844626\n",
+       " 701887  4.009409 -4.843883          741            0.000041         2.844626\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 702118  2.700801 -4.840117          742            2.839457          2.84121\n",
+       " 702119  2.702502 -4.839858          742            2.838410          2.84121\n",
+       " 702120  2.704204 -4.839598          742            2.837363          2.84121\n",
+       " 702121  2.705906 -4.839671          742            2.836328          2.84121\n",
+       " 702122  2.707608 -4.839817          742            2.835296          2.84121\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 702883  4.002603 -4.844817          742            0.000072          2.84121\n",
+       " 702884  4.004304 -4.845039          742            0.000064          2.84121\n",
+       " 702885  4.006006 -4.845261          742            0.000056          2.84121\n",
+       " 702886  4.007708 -4.845483          742            0.000048          2.84121\n",
+       " 702887  4.009409 -4.845705          742            0.000041          2.84121\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 703118  2.700801 -4.839733          743            2.835479         2.837874\n",
+       " 703119  2.702502 -4.839631          743            2.834436         2.837874\n",
+       " 703120  2.704204 -4.839584          743            2.833393         2.837874\n",
+       " 703121  2.705906 -4.839730          743            2.832352         2.837874\n",
+       " 703122  2.707608 -4.839876          743            2.831311         2.837874\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 703883  4.002603 -4.843888          743            0.000071         2.837874\n",
+       " 703884  4.004304 -4.844061          743            0.000063         2.837874\n",
+       " 703885  4.006006 -4.844234          743            0.000055         2.837874\n",
+       " 703886  4.007708 -4.844408          743            0.000048         2.837874\n",
+       " 703887  4.009409 -4.844582          743            0.000040         2.837874\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 704118  2.700801 -4.839959          744            2.833895         2.835264\n",
+       " 704119  2.702502 -4.839861          744            2.832869         2.835264\n",
+       " 704120  2.704204 -4.839780          744            2.831841         2.835264\n",
+       " 704121  2.705906 -4.839780          744            2.830804         2.835264\n",
+       " 704122  2.707608 -4.839780          744            2.829768         2.835264\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 704883  4.002603 -4.846009          744            0.000072         2.835264\n",
+       " 704884  4.004304 -4.846272          744            0.000064         2.835264\n",
+       " 704885  4.006006 -4.846535          744            0.000056         2.835264\n",
+       " 704886  4.007708 -4.846798          744            0.000049         2.835264\n",
+       " 704887  4.009409 -4.847061          744            0.000041         2.835264\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 705118  2.700801 -4.840000          745            2.830987         2.833041\n",
+       " 705119  2.702502 -4.839866          745            2.829960         2.833041\n",
+       " 705120  2.704204 -4.840016          745            2.828928         2.833041\n",
+       " 705121  2.705906 -4.840166          745            2.827897         2.833041\n",
+       " 705122  2.707608 -4.840199          745            2.826855         2.833041\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 705882  4.000901 -4.844621          745            0.000078         2.833041\n",
+       " 705883  4.002603 -4.844844          745            0.000071         2.833041\n",
+       " 705884  4.004304 -4.845067          745            0.000063         2.833041\n",
+       " 705885  4.006006 -4.845289          745            0.000055         2.833041\n",
+       " 705886  4.007708 -4.845512          745            0.000047         2.833041\n",
+       " \n",
+       " [769 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 706118  2.700801 -4.839916          746            2.829945          2.83158\n",
+       " 706119  2.702502 -4.839715          746            2.828939          2.83158\n",
+       " 706120  2.704204 -4.839579          746            2.827922          2.83158\n",
+       " 706121  2.705906 -4.839731          746            2.826853          2.83158\n",
+       " 706122  2.707608 -4.839884          746            2.825783          2.83158\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 706882  4.000901 -4.843969          746            0.000078          2.83158\n",
+       " 706883  4.002603 -4.844142          746            0.000070          2.83158\n",
+       " 706884  4.004304 -4.844315          746            0.000062          2.83158\n",
+       " 706885  4.006006 -4.844488          746            0.000054          2.83158\n",
+       " 706886  4.007708 -4.844661          746            0.000047          2.83158\n",
+       " \n",
+       " [769 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 707118  2.700801 -4.839780          747            2.825645           2.8283\n",
+       " 707119  2.702502 -4.839780          747            2.824646           2.8283\n",
+       " 707120  2.704204 -4.839808          747            2.823631           2.8283\n",
+       " 707121  2.705906 -4.839960          747            2.822543           2.8283\n",
+       " 707122  2.707608 -4.840113          747            2.821455           2.8283\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 707882  4.000901 -4.843444          747            0.000075           2.8283\n",
+       " 707883  4.002603 -4.843593          747            0.000068           2.8283\n",
+       " 707884  4.004304 -4.843740          747            0.000060           2.8283\n",
+       " 707885  4.006006 -4.843888          747            0.000052           2.8283\n",
+       " 707886  4.007708 -4.844037          747            0.000045           2.8283\n",
+       " \n",
+       " [769 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 708118  2.700801 -4.839859          748            2.823848         2.825299\n",
+       " 708119  2.702502 -4.840030          748            2.822798         2.825299\n",
+       " 708120  2.704204 -4.840200          748            2.821748         2.825299\n",
+       " 708121  2.705906 -4.840180          748            2.820699         2.825299\n",
+       " 708122  2.707608 -4.840105          748            2.819649         2.825299\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 708882  4.000901 -4.842110          748            0.000075         2.825299\n",
+       " 708883  4.002603 -4.842200          748            0.000068         2.825299\n",
+       " 708884  4.004304 -4.842290          748            0.000060         2.825299\n",
+       " 708885  4.006006 -4.842381          748            0.000052         2.825299\n",
+       " 708886  4.007708 -4.842471          748            0.000045         2.825299\n",
+       " \n",
+       " [769 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 709118  2.700801 -4.839638          749            2.823125         2.824302\n",
+       " 709119  2.702502 -4.839824          749            2.822084         2.824302\n",
+       " 709120  2.704204 -4.840009          749            2.821043         2.824302\n",
+       " 709121  2.705906 -4.839934          749            2.819989         2.824302\n",
+       " 709122  2.707608 -4.839859          749            2.818935         2.824302\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 709882  4.000901 -4.843373          749            0.000075         2.824302\n",
+       " 709883  4.002603 -4.843537          749            0.000068         2.824302\n",
+       " 709884  4.004304 -4.843700          749            0.000060         2.824302\n",
+       " 709885  4.006006 -4.843863          749            0.000052         2.824302\n",
+       " 709886  4.007708 -4.844027          749            0.000045         2.824302\n",
+       " \n",
+       " [769 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 710118  2.700801 -4.840163          750            2.822689         2.823751\n",
+       " 710119  2.702502 -4.840456          750            2.821636         2.823751\n",
+       " 710120  2.704204 -4.840305          750            2.820600         2.823751\n",
+       " 710121  2.705906 -4.840155          750            2.819563         2.823751\n",
+       " 710122  2.707608 -4.840011          750            2.818527         2.823751\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 710882  4.000901 -4.844760          750            0.000075         2.823751\n",
+       " 710883  4.002603 -4.844972          750            0.000067         2.823751\n",
+       " 710884  4.004304 -4.845184          750            0.000060         2.823751\n",
+       " 710885  4.006006 -4.845396          750            0.000052         2.823751\n",
+       " 710886  4.007708 -4.845608          750            0.000044         2.823751\n",
+       " \n",
+       " [769 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 711118  2.700801 -4.839937          751            2.820080         2.821761\n",
+       " 711119  2.702502 -4.839782          751            2.819054         2.821761\n",
+       " 711120  2.704204 -4.839852          751            2.818021         2.821761\n",
+       " 711121  2.705906 -4.839925          751            2.816989         2.821761\n",
+       " 711122  2.707608 -4.839998          751            2.815956         2.821761\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 711882  4.000901 -4.844666          751            0.000074         2.821761\n",
+       " 711883  4.002603 -4.844854          751            0.000066         2.821761\n",
+       " 711884  4.004304 -4.845042          751            0.000059         2.821761\n",
+       " 711885  4.006006 -4.845230          751            0.000051         2.821761\n",
+       " 711886  4.007708 -4.845418          751            0.000043         2.821761\n",
+       " \n",
+       " [769 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 712118  2.700801 -4.839860          752            2.817739         2.819408\n",
+       " 712119  2.702502 -4.839780          752            2.816718         2.819408\n",
+       " 712120  2.704204 -4.839780          752            2.815681         2.819408\n",
+       " 712121  2.705906 -4.839780          752            2.814645         2.819408\n",
+       " 712122  2.707608 -4.839780          752            2.813584         2.819408\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 712882  4.000901 -4.845061          752            0.000072         2.819408\n",
+       " 712883  4.002603 -4.845272          752            0.000065         2.819408\n",
+       " 712884  4.004304 -4.845482          752            0.000057         2.819408\n",
+       " 712885  4.006006 -4.845693          752            0.000049         2.819408\n",
+       " 712886  4.007708 -4.845904          752            0.000042         2.819408\n",
+       " \n",
+       " [769 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 713118  2.700801 -4.839780          753            2.817358         2.817877\n",
+       " 713119  2.702502 -4.839833          753            2.816327         2.817877\n",
+       " 713120  2.704204 -4.839908          753            2.815299         2.817877\n",
+       " 713121  2.705906 -4.839983          753            2.814272         2.817877\n",
+       " 713122  2.707608 -4.840058          753            2.813224         2.817877\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 713882  4.000901 -4.843459          753            0.000073         2.817877\n",
+       " 713883  4.002603 -4.843613          753            0.000065         2.817877\n",
+       " 713884  4.004304 -4.843767          753            0.000058         2.817877\n",
+       " 713885  4.006006 -4.843920          753            0.000050         2.817877\n",
+       " 713886  4.007708 -4.844074          753            0.000042         2.817877\n",
+       " \n",
+       " [769 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 714118  2.700801 -4.840046          754            2.816285         2.817519\n",
+       " 714119  2.702502 -4.840126          754            2.815249         2.817519\n",
+       " 714120  2.704204 -4.840206          754            2.814214         2.817519\n",
+       " 714121  2.705906 -4.840148          754            2.813170         2.817519\n",
+       " 714122  2.707608 -4.839998          754            2.812121         2.817519\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 714882  4.000901 -4.844349          754            0.000071         2.817519\n",
+       " 714883  4.002603 -4.844519          754            0.000063         2.817519\n",
+       " 714884  4.004304 -4.844689          754            0.000056         2.817519\n",
+       " 714885  4.006006 -4.844860          754            0.000048         2.817519\n",
+       " 714886  4.007708 -4.845029          754            0.000040         2.817519\n",
+       " \n",
+       " [769 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 715118  2.700801 -4.839965          755            2.815676         2.816754\n",
+       " 715119  2.702502 -4.839870          755            2.814632         2.816754\n",
+       " 715120  2.704204 -4.839780          755            2.813588         2.816754\n",
+       " 715121  2.705906 -4.839780          755            2.812541         2.816754\n",
+       " 715122  2.707608 -4.839780          755            2.811493         2.816754\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 715882  4.000901 -4.841960          755            0.000071         2.816754\n",
+       " 715883  4.002603 -4.842041          755            0.000064         2.816754\n",
+       " 715884  4.004304 -4.842122          755            0.000056         2.816754\n",
+       " 715885  4.006006 -4.842203          755            0.000049         2.816754\n",
+       " 715886  4.007708 -4.842284          755            0.000041         2.816754\n",
+       " \n",
+       " [769 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 716118  2.700801 -4.839556          756            2.814862         2.815961\n",
+       " 716119  2.702502 -4.839631          756            2.813843         2.815961\n",
+       " 716120  2.704204 -4.839706          756            2.812825         2.815961\n",
+       " 716121  2.705906 -4.839782          756            2.811805         2.815961\n",
+       " 716122  2.707608 -4.839937          756            2.810728         2.815961\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 716881  3.999199 -4.843669          756            0.000078         2.815961\n",
+       " 716882  4.000901 -4.843807          756            0.000070         2.815961\n",
+       " 716883  4.002603 -4.843945          756            0.000063         2.815961\n",
+       " 716884  4.004304 -4.844083          756            0.000055         2.815961\n",
+       " 716885  4.006006 -4.844220          756            0.000047         2.815961\n",
+       " \n",
+       " [768 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 717118  2.700801 -4.839964          757            2.814517         2.816076\n",
+       " 717119  2.702502 -4.839736          757            2.813465         2.816076\n",
+       " 717120  2.704204 -4.839507          757            2.812413         2.816076\n",
+       " 717121  2.705906 -4.839352          757            2.811359         2.816076\n",
+       " 717122  2.707608 -4.839502          757            2.810297         2.816076\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 717882  4.000901 -4.845430          757            0.000072         2.816076\n",
+       " 717883  4.002603 -4.845664          757            0.000064         2.816076\n",
+       " 717884  4.004304 -4.845898          757            0.000057         2.816076\n",
+       " 717885  4.006006 -4.846132          757            0.000049         2.816076\n",
+       " 717886  4.007708 -4.846366          757            0.000041         2.816076\n",
+       " \n",
+       " [769 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 718118  2.700801 -4.840009          758            2.812013          2.81461\n",
+       " 718119  2.702502 -4.840009          758            2.810983          2.81461\n",
+       " 718120  2.704204 -4.840009          758            2.809953          2.81461\n",
+       " 718121  2.705906 -4.840000          758            2.808922          2.81461\n",
+       " 718122  2.707608 -4.839846          758            2.807872          2.81461\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 718882  4.000901 -4.842870          758            0.000071          2.81461\n",
+       " 718883  4.002603 -4.843007          758            0.000064          2.81461\n",
+       " 718884  4.004304 -4.843144          758            0.000056          2.81461\n",
+       " 718885  4.006006 -4.843281          758            0.000049          2.81461\n",
+       " 718886  4.007708 -4.843418          758            0.000041          2.81461\n",
+       " \n",
+       " [769 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 719118  2.700801 -4.839899          759            2.809489         2.812255\n",
+       " 719119  2.702502 -4.839924          759            2.808421         2.812255\n",
+       " 719120  2.704204 -4.839774          759            2.807363         2.812255\n",
+       " 719121  2.705906 -4.839623          759            2.806304         2.812255\n",
+       " 719122  2.707608 -4.839630          759            2.805244         2.812255\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 719882  4.000901 -4.843105          759            0.000071         2.812255\n",
+       " 719883  4.002603 -4.843243          759            0.000063         2.812255\n",
+       " 719884  4.004304 -4.843379          759            0.000056         2.812255\n",
+       " 719885  4.006006 -4.843516          759            0.000048         2.812255\n",
+       " 719886  4.007708 -4.843653          759            0.000041         2.812255\n",
+       " \n",
+       " [769 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 720118  2.700801 -4.839952          760            2.808208         2.810225\n",
+       " 720119  2.702502 -4.839803          760            2.807150         2.810225\n",
+       " 720120  2.704204 -4.839653          760            2.806092         2.810225\n",
+       " 720121  2.705906 -4.839551          760            2.805033         2.810225\n",
+       " 720122  2.707608 -4.839551          760            2.803975         2.810225\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 720882  4.000901 -4.844507          760            0.000071         2.810225\n",
+       " 720883  4.002603 -4.844692          760            0.000063         2.810225\n",
+       " 720884  4.004304 -4.844878          760            0.000056         2.810225\n",
+       " 720885  4.006006 -4.845063          760            0.000048         2.810225\n",
+       " 720886  4.007708 -4.845249          760            0.000041         2.810225\n",
+       " \n",
+       " [769 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 721118  2.700801 -4.839817          761            2.803459         2.807245\n",
+       " 721119  2.702502 -4.839894          761            2.802423         2.807245\n",
+       " 721120  2.704204 -4.839971          761            2.801387         2.807245\n",
+       " 721121  2.705906 -4.839932          761            2.800339         2.807245\n",
+       " 721122  2.707608 -4.839779          761            2.799278         2.807245\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 721881  3.999199 -4.845874          761            0.000077         2.807245\n",
+       " 721882  4.000901 -4.846122          761            0.000070         2.807245\n",
+       " 721883  4.002603 -4.846371          761            0.000062         2.807245\n",
+       " 721884  4.004304 -4.846619          761            0.000054         2.807245\n",
+       " 721885  4.006006 -4.846868          761            0.000047         2.807245\n",
+       " \n",
+       " [768 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 722118  2.700801 -4.839972          762            2.801221          2.80282\n",
+       " 722119  2.702502 -4.839894          762            2.800202          2.80282\n",
+       " 722120  2.704204 -4.839816          762            2.799182          2.80282\n",
+       " 722121  2.705906 -4.839780          762            2.798128          2.80282\n",
+       " 722122  2.707608 -4.839780          762            2.797045          2.80282\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 722881  3.999199 -4.845671          762            0.000076          2.80282\n",
+       " 722882  4.000901 -4.845921          762            0.000069          2.80282\n",
+       " 722883  4.002603 -4.846171          762            0.000061          2.80282\n",
+       " 722884  4.004304 -4.846421          762            0.000054          2.80282\n",
+       " 722885  4.006006 -4.846671          762            0.000046          2.80282\n",
+       " \n",
+       " [768 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 723118  2.700801 -4.839954          763            2.798971         2.801786\n",
+       " 723119  2.702502 -4.839835          763            2.797911         2.801786\n",
+       " 723120  2.704204 -4.839780          763            2.796850         2.801786\n",
+       " 723121  2.705906 -4.839780          763            2.795790         2.801786\n",
+       " 723122  2.707608 -4.839780          763            2.794730         2.801786\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 723881  3.999199 -4.843270          763            0.000077         2.801786\n",
+       " 723882  4.000901 -4.843398          763            0.000069         2.801786\n",
+       " 723883  4.002603 -4.843526          763            0.000062         2.801786\n",
+       " 723884  4.004304 -4.843655          763            0.000054         2.801786\n",
+       " 723885  4.006006 -4.843783          763            0.000047         2.801786\n",
+       " \n",
+       " [768 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 724118  2.700801 -4.840122          764            2.796904         2.799294\n",
+       " 724119  2.702502 -4.839873          764            2.795851         2.799294\n",
+       " 724120  2.704204 -4.839876          764            2.794787         2.799294\n",
+       " 724121  2.705906 -4.840028          764            2.793717         2.799294\n",
+       " 724122  2.707608 -4.840181          764            2.792648         2.799294\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 724881  3.999199 -4.844190          764            0.000076         2.799294\n",
+       " 724882  4.000901 -4.844367          764            0.000069         2.799294\n",
+       " 724883  4.002603 -4.844544          764            0.000061         2.799294\n",
+       " 724884  4.004304 -4.844722          764            0.000054         2.799294\n",
+       " 724885  4.006006 -4.844899          764            0.000046         2.799294\n",
+       " \n",
+       " [768 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 725118  2.700801 -4.839551          765            2.793529         2.796356\n",
+       " 725119  2.702502 -4.839551          765            2.792477         2.796356\n",
+       " 725120  2.704204 -4.839592          765            2.791417         2.796356\n",
+       " 725121  2.705906 -4.839817          765            2.790323         2.796356\n",
+       " 725122  2.707608 -4.840042          765            2.789230         2.796356\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 725881  3.999199 -4.844716          765            0.000076         2.796356\n",
+       " 725882  4.000901 -4.844925          765            0.000069         2.796356\n",
+       " 725883  4.002603 -4.845133          765            0.000061         2.796356\n",
+       " 725884  4.004304 -4.845342          765            0.000054         2.796356\n",
+       " 725885  4.006006 -4.845551          765            0.000046         2.796356\n",
+       " \n",
+       " [768 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 726118  2.700801 -4.839762          766            2.791750         2.794003\n",
+       " 726119  2.702502 -4.839688          766            2.790703         2.794003\n",
+       " 726120  2.704204 -4.839614          766            2.789655         2.794003\n",
+       " 726121  2.705906 -4.839562          766            2.788602         2.794003\n",
+       " 726122  2.707608 -4.839638          766            2.787518         2.794003\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 726881  3.999199 -4.845474          766            0.000076         2.794003\n",
+       " 726882  4.000901 -4.845715          766            0.000069         2.794003\n",
+       " 726883  4.002603 -4.845956          766            0.000061         2.794003\n",
+       " 726884  4.004304 -4.846197          766            0.000054         2.794003\n",
+       " 726885  4.006006 -4.846438          766            0.000046         2.794003\n",
+       " \n",
+       " [768 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 727118  2.700801 -4.840164          767            2.790688         2.792633\n",
+       " 727119  2.702502 -4.840004          767            2.789624         2.792633\n",
+       " 727120  2.704204 -4.839845          767            2.788560         2.792633\n",
+       " 727121  2.705906 -4.839825          767            2.787486         2.792633\n",
+       " 727122  2.707608 -4.839899          767            2.786403         2.792633\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 727881  3.999199 -4.845710          767            0.000076         2.792633\n",
+       " 727882  4.000901 -4.845952          767            0.000069         2.792633\n",
+       " 727883  4.002603 -4.846193          767            0.000061         2.792633\n",
+       " 727884  4.004304 -4.846436          767            0.000054         2.792633\n",
+       " 727885  4.006006 -4.846677          767            0.000046         2.792633\n",
+       " \n",
+       " [768 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 728118  2.700801 -4.840199          768            2.788049         2.790646\n",
+       " 728119  2.702502 -4.840116          768            2.787007         2.790646\n",
+       " 728120  2.704204 -4.840032          768            2.785964         2.790646\n",
+       " 728121  2.705906 -4.840009          768            2.784914         2.790646\n",
+       " 728122  2.707608 -4.840009          768            2.783860         2.790646\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 728881  3.999199 -4.844770          768            0.000076         2.790646\n",
+       " 728882  4.000901 -4.844971          768            0.000068         2.790646\n",
+       " 728883  4.002603 -4.845173          768            0.000061         2.790646\n",
+       " 728884  4.004304 -4.845374          768            0.000053         2.790646\n",
+       " 728885  4.006006 -4.845575          768            0.000046         2.790646\n",
+       " \n",
+       " [768 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 729118  2.700801 -4.840058          769            2.786223         2.788235\n",
+       " 729119  2.702502 -4.840162          769            2.785158         2.788235\n",
+       " 729120  2.704204 -4.840198          769            2.784079         2.788235\n",
+       " 729121  2.705906 -4.840047          769            2.782959         2.788235\n",
+       " 729122  2.707608 -4.839897          769            2.781839         2.788235\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 729881  3.999199 -4.844888          769            0.000077         2.788235\n",
+       " 729882  4.000901 -4.845105          769            0.000069         2.788235\n",
+       " 729883  4.002603 -4.845321          769            0.000062         2.788235\n",
+       " 729884  4.004304 -4.845537          769            0.000054         2.788235\n",
+       " 729885  4.006006 -4.845754          769            0.000047         2.788235\n",
+       " \n",
+       " [768 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 730118  2.700801 -4.839926          770            2.784583         2.786224\n",
+       " 730119  2.702502 -4.839746          770            2.783489         2.786224\n",
+       " 730120  2.704204 -4.839568          770            2.782394         2.786224\n",
+       " 730121  2.705906 -4.839686          770            2.781323         2.786224\n",
+       " 730122  2.707608 -4.839834          770            2.780254         2.786224\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 730881  3.999199 -4.843859          770            0.000076         2.786224\n",
+       " 730882  4.000901 -4.844011          770            0.000068         2.786224\n",
+       " 730883  4.002603 -4.844164          770            0.000061         2.786224\n",
+       " 730884  4.004304 -4.844316          770            0.000053         2.786224\n",
+       " 730885  4.006006 -4.844469          770            0.000046         2.786224\n",
+       " \n",
+       " [768 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 731118  2.700801 -4.840088          776            2.926842         2.697941\n",
+       " 731119  2.702502 -4.840259          776            2.925848         2.697941\n",
+       " 731120  2.704204 -4.840429          776            2.924853         2.697941\n",
+       " 731121  2.705906 -4.840292          776            2.923864         2.697941\n",
+       " 731122  2.707608 -4.840067          776            2.922876         2.697941\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 731887  4.009409 -4.844290          776            0.000072         2.697941\n",
+       " 731888  4.011111 -4.844464          776            0.000065         2.697941\n",
+       " 731889  4.012813 -4.844638          776            0.000057         2.697941\n",
+       " 731890  4.014514 -4.844812          776            0.000050         2.697941\n",
+       " 731891  4.016216 -4.844986          776            0.000042         2.697941\n",
+       " \n",
+       " [774 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 732118  2.700801 -4.839780          777            2.903393         2.904706\n",
+       " 732119  2.702502 -4.839780          777            2.902392         2.904706\n",
+       " 732120  2.704204 -4.839780          777            2.901391         2.904706\n",
+       " 732121  2.705906 -4.839832          777            2.900365         2.904706\n",
+       " 732122  2.707608 -4.839907          777            2.899329         2.904706\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 732885  4.006006 -4.843056          777            0.000076         2.904706\n",
+       " 732886  4.007708 -4.843183          777            0.000068         2.904706\n",
+       " 732887  4.009409 -4.843309          777            0.000061         2.904706\n",
+       " 732888  4.011111 -4.843436          777            0.000054         2.904706\n",
+       " 732889  4.012813 -4.843563          777            0.000046         2.904706\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 733118  2.700801 -4.840055          778            2.885354         2.895391\n",
+       " 733119  2.702502 -4.839663          778            2.884332         2.895391\n",
+       " 733120  2.704204 -4.839659          778            2.883296         2.895391\n",
+       " 733121  2.705906 -4.839809          778            2.882255         2.895391\n",
+       " 733122  2.707608 -4.839960          778            2.881215         2.895391\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 733885  4.006006 -4.845076          778            0.000071         2.895391\n",
+       " 733886  4.007708 -4.845290          778            0.000063         2.895391\n",
+       " 733887  4.009409 -4.845503          778            0.000056         2.895391\n",
+       " 733888  4.011111 -4.845717          778            0.000048         2.895391\n",
+       " 733889  4.012813 -4.845931          778            0.000041         2.895391\n",
+       " \n",
+       " [772 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 734118  2.700801 -4.839836          779            2.866349         2.874832\n",
+       " 734119  2.702502 -4.839954          779            2.865366         2.874832\n",
+       " 734120  2.704204 -4.840009          779            2.864329         2.874832\n",
+       " 734121  2.705906 -4.840009          779            2.863248         2.874832\n",
+       " 734122  2.707608 -4.840009          779            2.862167         2.874832\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 734884  4.004304 -4.844946          779            0.000069         2.874832\n",
+       " 734885  4.006006 -4.845142          779            0.000062         2.874832\n",
+       " 734886  4.007708 -4.845337          779            0.000055         2.874832\n",
+       " 734887  4.009409 -4.845532          779            0.000047         2.874832\n",
+       " 734888  4.011111 -4.845728          779            0.000040         2.874832\n",
+       " \n",
+       " [771 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 735118  2.700801 -4.840009          780            2.853010         2.862322\n",
+       " 735119  2.702502 -4.840009          780            2.852024         2.862322\n",
+       " 735120  2.704204 -4.839893          780            2.850957         2.862322\n",
+       " 735121  2.705906 -4.839741          780            2.849865         2.862322\n",
+       " 735122  2.707608 -4.839588          780            2.848773         2.862322\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 735883  4.002603 -4.844975          780            0.000074         2.862322\n",
+       " 735884  4.004304 -4.845187          780            0.000067         2.862322\n",
+       " 735885  4.006006 -4.845398          780            0.000059         2.862322\n",
+       " 735886  4.007708 -4.845610          780            0.000052         2.862322\n",
+       " 735887  4.009409 -4.845821          780            0.000045         2.862322\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 736118  2.700801 -4.839836          781            2.839731           2.8478\n",
+       " 736119  2.702502 -4.839954          781            2.838636           2.8478\n",
+       " 736120  2.704204 -4.839930          781            2.837548           2.8478\n",
+       " 736121  2.705906 -4.839782          781            2.836466           2.8478\n",
+       " 736122  2.707608 -4.839633          781            2.835384           2.8478\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 736883  4.002603 -4.844873          781            0.000071           2.8478\n",
+       " 736884  4.004304 -4.845077          781            0.000063           2.8478\n",
+       " 736885  4.006006 -4.845281          781            0.000056           2.8478\n",
+       " 736886  4.007708 -4.845485          781            0.000049           2.8478\n",
+       " 736887  4.009409 -4.845688          781            0.000041           2.8478\n",
+       " \n",
+       " [770 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 737118  2.700801 -4.839802          782            2.830004         2.836115\n",
+       " 737119  2.702502 -4.839551          782            2.828924         2.836115\n",
+       " 737120  2.704204 -4.839551          782            2.827878         2.836115\n",
+       " 737121  2.705906 -4.839551          782            2.826833         2.836115\n",
+       " 737122  2.707608 -4.839581          782            2.825763         2.836115\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 737882  4.000901 -4.845130          782            0.000075         2.836115\n",
+       " 737883  4.002603 -4.845351          782            0.000068         2.836115\n",
+       " 737884  4.004304 -4.845571          782            0.000060         2.836115\n",
+       " 737885  4.006006 -4.845791          782            0.000053         2.836115\n",
+       " 737886  4.007708 -4.846012          782            0.000046         2.836115\n",
+       " \n",
+       " [769 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 738118  2.700801 -4.839612          783            2.821664          2.82874\n",
+       " 738119  2.702502 -4.839743          783            2.820603          2.82874\n",
+       " 738120  2.704204 -4.839833          783            2.819527          2.82874\n",
+       " 738121  2.705906 -4.839907          783            2.818445          2.82874\n",
+       " 738122  2.707608 -4.839982          783            2.817363          2.82874\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 738882  4.000901 -4.843774          783            0.000074          2.82874\n",
+       " 738883  4.002603 -4.843947          783            0.000067          2.82874\n",
+       " 738884  4.004304 -4.844119          783            0.000060          2.82874\n",
+       " 738885  4.006006 -4.844291          783            0.000052          2.82874\n",
+       " 738886  4.007708 -4.844463          783            0.000045          2.82874\n",
+       " \n",
+       " [769 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 739118  2.700801 -4.839750          784            2.812309         2.817943\n",
+       " 739119  2.702502 -4.839851          784            2.811244         2.817943\n",
+       " 739120  2.704204 -4.839927          784            2.810174         2.817943\n",
+       " 739121  2.705906 -4.840003          784            2.809105         2.817943\n",
+       " 739122  2.707608 -4.839869          784            2.807986         2.817943\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 739882  4.000901 -4.845420          784            0.000072         2.817943\n",
+       " 739883  4.002603 -4.845646          784            0.000065         2.817943\n",
+       " 739884  4.004304 -4.845873          784            0.000057         2.817943\n",
+       " 739885  4.006006 -4.846100          784            0.000050         2.817943\n",
+       " 739886  4.007708 -4.846327          784            0.000043         2.817943\n",
+       " \n",
+       " [769 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 740118  2.700801 -4.839857          785            2.805189         2.811085\n",
+       " 740119  2.702502 -4.840003          785            2.804141         2.811085\n",
+       " 740120  2.704204 -4.839930          785            2.803055         2.811085\n",
+       " 740121  2.705906 -4.839856          785            2.801968         2.811085\n",
+       " 740122  2.707608 -4.839782          785            2.800882         2.811085\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 740882  4.000901 -4.842923          785            0.000070         2.811085\n",
+       " 740883  4.002603 -4.843049          785            0.000063         2.811085\n",
+       " 740884  4.004304 -4.843174          785            0.000055         2.811085\n",
+       " 740885  4.006006 -4.843300          785            0.000048         2.811085\n",
+       " 740886  4.007708 -4.843426          785            0.000041         2.811085\n",
+       " \n",
+       " [769 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 741118  2.700801 -4.839771          786            2.798329         2.803086\n",
+       " 741119  2.702502 -4.839637          786            2.797239         2.803086\n",
+       " 741120  2.704204 -4.839787          786            2.796163         2.803086\n",
+       " 741121  2.705906 -4.839937          786            2.795087         2.803086\n",
+       " 741122  2.707608 -4.840048          786            2.793988         2.803086\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 741881  3.999199 -4.842823          786            0.000076         2.803086\n",
+       " 741882  4.000901 -4.842948          786            0.000069         2.803086\n",
+       " 741883  4.002603 -4.843073          786            0.000061         2.803086\n",
+       " 741884  4.004304 -4.843198          786            0.000054         2.803086\n",
+       " 741885  4.006006 -4.843323          786            0.000047         2.803086\n",
+       " \n",
+       " [768 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 742118  2.700801 -4.840009          787            2.792487         2.797665\n",
+       " 742119  2.702502 -4.840076          787            2.791418         2.797665\n",
+       " 742120  2.704204 -4.840153          787            2.790343         2.797665\n",
+       " 742121  2.705906 -4.840229          787            2.789269         2.797665\n",
+       " 742122  2.707608 -4.840104          787            2.788148         2.797665\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 742881  3.999199 -4.843806          787            0.000076         2.797665\n",
+       " 742882  4.000901 -4.843963          787            0.000069         2.797665\n",
+       " 742883  4.002603 -4.844119          787            0.000062         2.797665\n",
+       " 742884  4.004304 -4.844275          787            0.000054         2.797665\n",
+       " 742885  4.006006 -4.844431          787            0.000047         2.797665\n",
+       " \n",
+       " [768 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 743118  2.700801 -4.840233          788            2.786999         2.790696\n",
+       " 743119  2.702502 -4.840158          788            2.785874         2.790696\n",
+       " 743120  2.704204 -4.840083          788            2.784750         2.790696\n",
+       " 743121  2.705906 -4.840008          788            2.783626         2.790696\n",
+       " 743122  2.707608 -4.839935          788            2.782529         2.790696\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 743881  3.999199 -4.844219          788            0.000073         2.790696\n",
+       " 743882  4.000901 -4.844400          788            0.000066         2.790696\n",
+       " 743883  4.002603 -4.844582          788            0.000059         2.790696\n",
+       " 743884  4.004304 -4.844763          788            0.000051         2.790696\n",
+       " 743885  4.006006 -4.844944          788            0.000044         2.790696\n",
+       " \n",
+       " [768 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 744118  2.700801 -4.839894          789            2.781919         2.786155\n",
+       " 744119  2.702502 -4.839971          789            2.780797         2.786155\n",
+       " 744120  2.704204 -4.839896          789            2.779706         2.786155\n",
+       " 744121  2.705906 -4.839822          789            2.778615         2.786155\n",
+       " 744122  2.707608 -4.839845          789            2.777510         2.786155\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 744881  3.999199 -4.844599          789            0.000072         2.786155\n",
+       " 744882  4.000901 -4.844804          789            0.000065         2.786155\n",
+       " 744883  4.002603 -4.845008          789            0.000058         2.786155\n",
+       " 744884  4.004304 -4.845213          789            0.000050         2.786155\n",
+       " 744885  4.006006 -4.845417          789            0.000043         2.786155\n",
+       " \n",
+       " [768 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 745118  2.700801 -4.839968          790            2.775729           2.7799\n",
+       " 745119  2.702502 -4.839880          790            2.774617           2.7799\n",
+       " 745120  2.704204 -4.839792          790            2.773506           2.7799\n",
+       " 745121  2.705906 -4.839975          790            2.772402           2.7799\n",
+       " 745122  2.707608 -4.840200          790            2.771299           2.7799\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 745881  3.999199 -4.843875          790            0.000072           2.7799\n",
+       " 745882  4.000901 -4.844040          790            0.000064           2.7799\n",
+       " 745883  4.002603 -4.844204          790            0.000057           2.7799\n",
+       " 745884  4.004304 -4.844369          790            0.000049           2.7799\n",
+       " 745885  4.006006 -4.844533          790            0.000042           2.7799\n",
+       " \n",
+       " [768 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 746118  2.700801 -4.840060          791            2.770139         2.774869\n",
+       " 746119  2.702502 -4.840212          791            2.769034         2.774869\n",
+       " 746120  2.704204 -4.840364          791            2.767928         2.774869\n",
+       " 746121  2.705906 -4.840417          791            2.766819         2.774869\n",
+       " 746122  2.707608 -4.840265          791            2.765700         2.774869\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 746881  3.999199 -4.843546          791            0.000072         2.774869\n",
+       " 746882  4.000901 -4.843678          791            0.000065         2.774869\n",
+       " 746883  4.002603 -4.843810          791            0.000057         2.774869\n",
+       " 746884  4.004304 -4.843942          791            0.000050         2.774869\n",
+       " 746885  4.006006 -4.844074          791            0.000043         2.774869\n",
+       " \n",
+       " [768 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 747118  2.700801 -4.840180          792            2.764385         2.768193\n",
+       " 747119  2.702502 -4.840055          792            2.763281         2.768193\n",
+       " 747120  2.704204 -4.839963          792            2.762190         2.768193\n",
+       " 747121  2.705906 -4.839889          792            2.761108         2.768193\n",
+       " 747122  2.707608 -4.839815          792            2.760026         2.768193\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 747881  3.999199 -4.843585          792            0.000070         2.768193\n",
+       " 747882  4.000901 -4.843718          792            0.000062         2.768193\n",
+       " 747883  4.002603 -4.843850          792            0.000055         2.768193\n",
+       " 747884  4.004304 -4.843983          792            0.000048         2.768193\n",
+       " 747885  4.006006 -4.844116          792            0.000040         2.768193\n",
+       " \n",
+       " [768 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 748118  2.700801 -4.839849          793            2.765084         2.769235\n",
+       " 748119  2.702502 -4.840122          793            2.764000         2.769235\n",
+       " 748120  2.704204 -4.840272          793            2.762924         2.769235\n",
+       " 748121  2.705906 -4.840422          793            2.761848         2.769235\n",
+       " 748122  2.707608 -4.840304          793            2.760718         2.769235\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 748881  3.999199 -4.844537          793            0.000071         2.769235\n",
+       " 748882  4.000901 -4.844709          793            0.000064         2.769235\n",
+       " 748883  4.002603 -4.844881          793            0.000056         2.769235\n",
+       " 748884  4.004304 -4.845053          793            0.000049         2.769235\n",
+       " 748885  4.006006 -4.845225          793            0.000042         2.769235\n",
+       " \n",
+       " [768 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 749118  2.700801 -4.839626          794            2.755386         2.758647\n",
+       " 749119  2.702502 -4.839786          794            2.754271         2.758647\n",
+       " 749120  2.704204 -4.839945          794            2.753156         2.758647\n",
+       " 749121  2.705906 -4.839965          794            2.752042         2.758647\n",
+       " 749122  2.707608 -4.839891          794            2.750929         2.758647\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 749880  3.997498 -4.844932          794            0.000075         2.758647\n",
+       " 749881  3.999199 -4.845143          794            0.000068         2.758647\n",
+       " 749882  4.000901 -4.845354          794            0.000061         2.758647\n",
+       " 749883  4.002603 -4.845564          794            0.000053         2.758647\n",
+       " 749884  4.004304 -4.845775          794            0.000046         2.758647\n",
+       " \n",
+       " [767 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 750118  2.700801 -4.839801          795            2.755528         2.758353\n",
+       " 750119  2.702502 -4.839876          795            2.754398         2.758353\n",
+       " 750120  2.704204 -4.839950          795            2.753268         2.758353\n",
+       " 750121  2.705906 -4.840024          795            2.752142         2.758353\n",
+       " 750122  2.707608 -4.840097          795            2.751034         2.758353\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 750881  3.999199 -4.845508          795            0.000069         2.758353\n",
+       " 750882  4.000901 -4.845735          795            0.000062         2.758353\n",
+       " 750883  4.002603 -4.845962          795            0.000055         2.758353\n",
+       " 750884  4.004304 -4.846189          795            0.000047         2.758353\n",
+       " 750885  4.006006 -4.846415          795            0.000040         2.758353\n",
+       " \n",
+       " [768 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 751118  2.700801 -4.839833          796            2.751753         2.754601\n",
+       " 751119  2.702502 -4.839947          796            2.750660         2.754601\n",
+       " 751120  2.704204 -4.839942          796            2.749559         2.754601\n",
+       " 751121  2.705906 -4.839792          796            2.748448         2.754601\n",
+       " 751122  2.707608 -4.839642          796            2.747336         2.754601\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 751880  3.997498 -4.843556          796            0.000076         2.754601\n",
+       " 751881  3.999199 -4.843720          796            0.000068         2.754601\n",
+       " 751882  4.000901 -4.843885          796            0.000061         2.754601\n",
+       " 751883  4.002603 -4.844049          796            0.000054         2.754601\n",
+       " 751884  4.004304 -4.844213          796            0.000046         2.754601\n",
+       " \n",
+       " [767 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 752118  2.700801 -4.839799          797            2.746856          2.74989\n",
+       " 752119  2.702502 -4.839875          797            2.745737          2.74989\n",
+       " 752120  2.704204 -4.839951          797            2.744618          2.74989\n",
+       " 752121  2.705906 -4.839992          797            2.743504          2.74989\n",
+       " 752122  2.707608 -4.839916          797            2.742406          2.74989\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 752880  3.997498 -4.844555          797            0.000075          2.74989\n",
+       " 752881  3.999199 -4.844749          797            0.000068          2.74989\n",
+       " 752882  4.000901 -4.844944          797            0.000061          2.74989\n",
+       " 752883  4.002603 -4.845138          797            0.000053          2.74989\n",
+       " 752884  4.004304 -4.845332          797            0.000046          2.74989\n",
+       " \n",
+       " [767 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 753118  2.700801 -4.840467          798            2.743768         2.747282\n",
+       " 753119  2.702502 -4.840467          798            2.742677         2.747282\n",
+       " 753120  2.704204 -4.840467          798            2.741586         2.747282\n",
+       " 753121  2.705906 -4.840275          798            2.740503         2.747282\n",
+       " 753122  2.707608 -4.840053          798            2.739421         2.747282\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 753880  3.997498 -4.843987          798            0.000075         2.747282\n",
+       " 753881  3.999199 -4.844159          798            0.000068         2.747282\n",
+       " 753882  4.000901 -4.844330          798            0.000060         2.747282\n",
+       " 753883  4.002603 -4.844501          798            0.000053         2.747282\n",
+       " 753884  4.004304 -4.844673          798            0.000046         2.747282\n",
+       " \n",
+       " [767 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 754118  2.700801 -4.840055          799            2.741991          2.74277\n",
+       " 754119  2.702502 -4.839663          799            2.740867          2.74277\n",
+       " 754120  2.704204 -4.839353          799            2.739747          2.74277\n",
+       " 754121  2.705906 -4.839574          799            2.738661          2.74277\n",
+       " 754122  2.707608 -4.839797          799            2.737574          2.74277\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 754880  3.997498 -4.844628          799            0.000073          2.74277\n",
+       " 754881  3.999199 -4.844823          799            0.000065          2.74277\n",
+       " 754882  4.000901 -4.845019          799            0.000058          2.74277\n",
+       " 754883  4.002603 -4.845214          799            0.000051          2.74277\n",
+       " 754884  4.004304 -4.845410          799            0.000043          2.74277\n",
+       " \n",
+       " [767 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 755118  2.700801 -4.839930          800            2.738540         2.742875\n",
+       " 755119  2.702502 -4.839760          800            2.737426         2.742875\n",
+       " 755120  2.704204 -4.839590          800            2.736311         2.742875\n",
+       " 755121  2.705906 -4.839609          800            2.735222         2.742875\n",
+       " 755122  2.707608 -4.839683          800            2.734140         2.742875\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 755880  3.997498 -4.844965          800            0.000073         2.742875\n",
+       " 755881  3.999199 -4.845183          800            0.000066         2.742875\n",
+       " 755882  4.000901 -4.845401          800            0.000058         2.742875\n",
+       " 755883  4.002603 -4.845619          800            0.000051         2.742875\n",
+       " 755884  4.004304 -4.845837          800            0.000044         2.742875\n",
+       " \n",
+       " [767 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 756118  2.700801 -4.840009          801            2.736024         2.738507\n",
+       " 756119  2.702502 -4.839945          801            2.734937         2.738507\n",
+       " 756120  2.704204 -4.839872          801            2.733862         2.738507\n",
+       " 756121  2.705906 -4.839799          801            2.732787         2.738507\n",
+       " 756122  2.707608 -4.839836          801            2.731671         2.738507\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 756880  3.997498 -4.845840          801            0.000072         2.738507\n",
+       " 756881  3.999199 -4.846074          801            0.000065         2.738507\n",
+       " 756882  4.000901 -4.846308          801            0.000058         2.738507\n",
+       " 756883  4.002603 -4.846541          801            0.000050         2.738507\n",
+       " 756884  4.004304 -4.846775          801            0.000043         2.738507\n",
+       " \n",
+       " [767 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 757118  2.700801 -4.839876          802            2.733104         2.736908\n",
+       " 757119  2.702502 -4.840034          802            2.731938         2.736908\n",
+       " 757120  2.704204 -4.840107          802            2.730859         2.736908\n",
+       " 757121  2.705906 -4.840180          802            2.729779         2.736908\n",
+       " 757122  2.707608 -4.840222          802            2.728686         2.736908\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 757880  3.997498 -4.843091          802            0.000072         2.736908\n",
+       " 757881  3.999199 -4.843223          802            0.000065         2.736908\n",
+       " 757882  4.000901 -4.843355          802            0.000057         2.736908\n",
+       " 757883  4.002603 -4.843488          802            0.000050         2.736908\n",
+       " 757884  4.004304 -4.843620          802            0.000043         2.736908\n",
+       " \n",
+       " [767 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 758118  2.700801 -4.840009          803            2.729513         2.732412\n",
+       " 758119  2.702502 -4.840009          803            2.728384         2.732412\n",
+       " 758120  2.704204 -4.840178          803            2.727258         2.732412\n",
+       " 758121  2.705906 -4.840400          803            2.726133         2.732412\n",
+       " 758122  2.707608 -4.840622          803            2.725007         2.732412\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 758880  3.997498 -4.844715          803            0.000071         2.732412\n",
+       " 758881  3.999199 -4.844902          803            0.000063         2.732412\n",
+       " 758882  4.000901 -4.845089          803            0.000056         2.732412\n",
+       " 758883  4.002603 -4.845276          803            0.000049         2.732412\n",
+       " 758884  4.004304 -4.845464          803            0.000041         2.732412\n",
+       " \n",
+       " [767 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 759118  2.700801 -4.839725          804            2.726993         2.729967\n",
+       " 759119  2.702502 -4.840099          804            2.725882         2.729967\n",
+       " 759120  2.704204 -4.840145          804            2.724772         2.729967\n",
+       " 759121  2.705906 -4.839997          804            2.723664         2.729967\n",
+       " 759122  2.707608 -4.839849          804            2.722556         2.729967\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 759880  3.997498 -4.842476          804            0.000072         2.729967\n",
+       " 759881  3.999199 -4.842592          804            0.000064         2.729967\n",
+       " 759882  4.000901 -4.842708          804            0.000057         2.729967\n",
+       " 759883  4.002603 -4.842824          804            0.000050         2.729967\n",
+       " 759884  4.004304 -4.842940          804            0.000043         2.729967\n",
+       " \n",
+       " [767 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 760118  2.700801 -4.840149          805            2.724424         2.727192\n",
+       " 760119  2.702502 -4.840132          805            2.723295         2.727192\n",
+       " 760120  2.704204 -4.839982          805            2.722232         2.727192\n",
+       " 760121  2.705906 -4.839832          805            2.721169         2.727192\n",
+       " 760122  2.707608 -4.839880          805            2.720040         2.727192\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 760880  3.997498 -4.843096          805            0.000072         2.727192\n",
+       " 760881  3.999199 -4.843227          805            0.000064         2.727192\n",
+       " 760882  4.000901 -4.843358          805            0.000057         2.727192\n",
+       " 760883  4.002603 -4.843490          805            0.000050         2.727192\n",
+       " 760884  4.004304 -4.843621          805            0.000043         2.727192\n",
+       " \n",
+       " [767 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 761118  2.700801 -4.840004          806            2.721001         2.724514\n",
+       " 761119  2.702502 -4.839930          806            2.719881         2.724514\n",
+       " 761120  2.704204 -4.839854          806            2.718761         2.724514\n",
+       " 761121  2.705906 -4.839780          806            2.717641         2.724514\n",
+       " 761122  2.707608 -4.839780          806            2.716526         2.724514\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 761880  3.997498 -4.842560          806            0.000070         2.724514\n",
+       " 761881  3.999199 -4.842661          806            0.000063         2.724514\n",
+       " 761882  4.000901 -4.842762          806            0.000056         2.724514\n",
+       " 761883  4.002603 -4.842863          806            0.000049         2.724514\n",
+       " 761884  4.004304 -4.842964          806            0.000041         2.724514\n",
+       " \n",
+       " [767 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 762118  2.700801 -4.840015          807            2.719777         2.721063\n",
+       " 762119  2.702502 -4.839554          807            2.718617         2.721063\n",
+       " 762120  2.704204 -4.839627          807            2.717512         2.721063\n",
+       " 762121  2.705906 -4.839700          807            2.716406         2.721063\n",
+       " 762122  2.707608 -4.839773          807            2.715301         2.721063\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 762880  3.997498 -4.843278          807            0.000070         2.721063\n",
+       " 762881  3.999199 -4.843426          807            0.000063         2.721063\n",
+       " 762882  4.000901 -4.843574          807            0.000056         2.721063\n",
+       " 762883  4.002603 -4.843722          807            0.000049         2.721063\n",
+       " 762884  4.004304 -4.843870          807            0.000041         2.721063\n",
+       " \n",
+       " [767 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 763118  2.700801 -4.839965          808            2.715701         2.718854\n",
+       " 763119  2.702502 -4.839870          808            2.714590         2.718854\n",
+       " 763120  2.704204 -4.839784          808            2.713479         2.718854\n",
+       " 763121  2.705906 -4.839859          808            2.712350         2.718854\n",
+       " 763122  2.707608 -4.839934          808            2.711221         2.718854\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 763880  3.997498 -4.845218          808            0.000070         2.718854\n",
+       " 763881  3.999199 -4.845451          808            0.000063         2.718854\n",
+       " 763882  4.000901 -4.845685          808            0.000056         2.718854\n",
+       " 763883  4.002603 -4.845918          808            0.000048         2.718854\n",
+       " 763884  4.004304 -4.846151          808            0.000041         2.718854\n",
+       " \n",
+       " [767 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 764118  2.700801 -4.840058          809            2.713176         2.714871\n",
+       " 764119  2.702502 -4.840162          809            2.712044         2.714871\n",
+       " 764120  2.704204 -4.840198          809            2.710919         2.714871\n",
+       " 764121  2.705906 -4.840050          809            2.709810         2.714871\n",
+       " 764122  2.707608 -4.839902          809            2.708702         2.714871\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 764880  3.997498 -4.844526          809            0.000070         2.714871\n",
+       " 764881  3.999199 -4.844706          809            0.000063         2.714871\n",
+       " 764882  4.000901 -4.844886          809            0.000056         2.714871\n",
+       " 764883  4.002603 -4.845065          809            0.000048         2.714871\n",
+       " 764884  4.004304 -4.845245          809            0.000041         2.714871\n",
+       " \n",
+       " [767 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 765118  2.700801 -4.840191          810            2.708110         2.711486\n",
+       " 765119  2.702502 -4.840091          810            2.707010         2.711486\n",
+       " 765120  2.704204 -4.839995          810            2.705903         2.711486\n",
+       " 765121  2.705906 -4.839920          810            2.704762         2.711486\n",
+       " 765122  2.707608 -4.839843          810            2.703621         2.711486\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 765879  3.995796 -4.844377          810            0.000076         2.711486\n",
+       " 765880  3.997498 -4.844556          810            0.000069         2.711486\n",
+       " 765881  3.999199 -4.844737          810            0.000062         2.711486\n",
+       " 765882  4.000901 -4.844917          810            0.000054         2.711486\n",
+       " 765883  4.002603 -4.845097          810            0.000047         2.711486\n",
+       " \n",
+       " [766 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 766118  2.700801 -4.839880          811            2.705304         2.707544\n",
+       " 766119  2.702502 -4.840092          811            2.704242         2.707544\n",
+       " 766120  2.704204 -4.840214          811            2.703163         2.707544\n",
+       " 766121  2.705906 -4.840138          811            2.702049         2.707544\n",
+       " 766122  2.707608 -4.840062          811            2.700934         2.707544\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 766880  3.997498 -4.843984          811            0.000070         2.707544\n",
+       " 766881  3.999199 -4.844132          811            0.000062         2.707544\n",
+       " 766882  4.000901 -4.844280          811            0.000055         2.707544\n",
+       " 766883  4.002603 -4.844428          811            0.000048         2.707544\n",
+       " 766884  4.004304 -4.844576          811            0.000040         2.707544\n",
+       " \n",
+       " [767 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 767118  2.700801 -4.839837          812            2.701932         2.704135\n",
+       " 767119  2.702502 -4.839959          812            2.700847         2.704135\n",
+       " 767120  2.704204 -4.839965          812            2.699736         2.704135\n",
+       " 767121  2.705906 -4.839890          812            2.698607         2.704135\n",
+       " 767122  2.707608 -4.839815          812            2.697478         2.704135\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 767879  3.995796 -4.843585          812            0.000076         2.704135\n",
+       " 767880  3.997498 -4.843740          812            0.000069         2.704135\n",
+       " 767881  3.999199 -4.843895          812            0.000061         2.704135\n",
+       " 767882  4.000901 -4.844050          812            0.000054         2.704135\n",
+       " 767883  4.002603 -4.844206          812            0.000047         2.704135\n",
+       " \n",
+       " [766 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 768118  2.700801 -4.839731          813            2.698294         2.700768\n",
+       " 768119  2.702502 -4.839624          813            2.697164         2.700768\n",
+       " 768120  2.704204 -4.839575          813            2.696029         2.700768\n",
+       " 768121  2.705906 -4.839650          813            2.694887         2.700768\n",
+       " 768122  2.707608 -4.839725          813            2.693745         2.700768\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 768879  3.995796 -4.843412          813            0.000073         2.700768\n",
+       " 768880  3.997498 -4.843569          813            0.000066         2.700768\n",
+       " 768881  3.999199 -4.843725          813            0.000059         2.700768\n",
+       " 768882  4.000901 -4.843882          813            0.000051         2.700768\n",
+       " 768883  4.002603 -4.844038          813            0.000044         2.700768\n",
+       " \n",
+       " [766 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 769118  2.700801 -4.840164          814            2.695537          2.69794\n",
+       " 769119  2.702502 -4.840009          814            2.694405          2.69794\n",
+       " 769120  2.704204 -4.840009          814            2.693324          2.69794\n",
+       " 769121  2.705906 -4.840009          814            2.692244          2.69794\n",
+       " 769122  2.707608 -4.840009          814            2.691164          2.69794\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 769879  3.995796 -4.844238          814            0.000073          2.69794\n",
+       " 769880  3.997498 -4.844416          814            0.000065          2.69794\n",
+       " 769881  3.999199 -4.844594          814            0.000058          2.69794\n",
+       " 769882  4.000901 -4.844772          814            0.000051          2.69794\n",
+       " 769883  4.002603 -4.844950          814            0.000044          2.69794\n",
+       " \n",
+       " [766 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 770118  2.700801 -4.839778          815            2.692803         2.695099\n",
+       " 770119  2.702502 -4.840049          815            2.691703         2.695099\n",
+       " 770120  2.704204 -4.840126          815            2.690588         2.695099\n",
+       " 770121  2.705906 -4.840201          815            2.689474         2.695099\n",
+       " 770122  2.707608 -4.840121          815            2.688350         2.695099\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 770879  3.995796 -4.842913          815            0.000073         2.695099\n",
+       " 770880  3.997498 -4.843029          815            0.000066         2.695099\n",
+       " 770881  3.999199 -4.843144          815            0.000058         2.695099\n",
+       " 770882  4.000901 -4.843260          815            0.000051         2.695099\n",
+       " 770883  4.002603 -4.843376          815            0.000044         2.695099\n",
+       " \n",
+       " [766 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 771118  2.700801 -4.839982          816            2.691851         2.692957\n",
+       " 771119  2.702502 -4.839909          816            2.690729         2.692957\n",
+       " 771120  2.704204 -4.839836          816            2.689607         2.692957\n",
+       " 771121  2.705906 -4.839798          816            2.688492         2.692957\n",
+       " 771122  2.707608 -4.839872          816            2.687401         2.692957\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 771879  3.995796 -4.843858          816            0.000072         2.692957\n",
+       " 771880  3.997498 -4.844020          816            0.000065         2.692957\n",
+       " 771881  3.999199 -4.844182          816            0.000058         2.692957\n",
+       " 771882  4.000901 -4.844345          816            0.000051         2.692957\n",
+       " 771883  4.002603 -4.844508          816            0.000043         2.692957\n",
+       " \n",
+       " [766 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 772118  2.700801 -4.840009          817            2.690421         2.691083\n",
+       " 772119  2.702502 -4.840067          817            2.689291         2.691083\n",
+       " 772120  2.704204 -4.840215          817            2.688191         2.691083\n",
+       " 772121  2.705906 -4.840363          817            2.687092         2.691083\n",
+       " 772122  2.707608 -4.840401          817            2.685987         2.691083\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 772879  3.995796 -4.844307          817            0.000071         2.691083\n",
+       " 772880  3.997498 -4.844477          817            0.000064         2.691083\n",
+       " 772881  3.999199 -4.844646          817            0.000057         2.691083\n",
+       " 772882  4.000901 -4.844815          817            0.000050         2.691083\n",
+       " 772883  4.002603 -4.844985          817            0.000042         2.691083\n",
+       " \n",
+       " [766 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 773118  2.700801 -4.839432          818            2.690494         2.691116\n",
+       " 773119  2.702502 -4.839668          818            2.689387         2.691116\n",
+       " 773120  2.704204 -4.839904          818            2.688280         2.691116\n",
+       " 773121  2.705906 -4.840009          818            2.687158         2.691116\n",
+       " 773122  2.707608 -4.840009          818            2.686025         2.691116\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 773879  3.995796 -4.843901          818            0.000070         2.691116\n",
+       " 773880  3.997498 -4.844063          818            0.000063         2.691116\n",
+       " 773881  3.999199 -4.844226          818            0.000056         2.691116\n",
+       " 773882  4.000901 -4.844388          818            0.000049         2.691116\n",
+       " 773883  4.002603 -4.844551          818            0.000041         2.691116\n",
+       " \n",
+       " [766 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 774118  2.700801 -4.839891          819            2.690397         2.690831\n",
+       " 774119  2.702502 -4.840238          819            2.689292         2.690831\n",
+       " 774120  2.704204 -4.840238          819            2.688196         2.690831\n",
+       " 774121  2.705906 -4.840238          819            2.687099         2.690831\n",
+       " 774122  2.707608 -4.840161          819            2.685992         2.690831\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 774879  3.995796 -4.843863          819            0.000071         2.690831\n",
+       " 774880  3.997498 -4.844032          819            0.000063         2.690831\n",
+       " 774881  3.999199 -4.844202          819            0.000056         2.690831\n",
+       " 774882  4.000901 -4.844372          819            0.000049         2.690831\n",
+       " 774883  4.002603 -4.844542          819            0.000042         2.690831\n",
+       " \n",
+       " [766 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 775118  2.700801 -4.840086          820            2.689964          2.69028\n",
+       " 775119  2.702502 -4.839577          820            2.688876          2.69028\n",
+       " 775120  2.704204 -4.839653          820            2.687796          2.69028\n",
+       " 775121  2.705906 -4.839727          820            2.686715          2.69028\n",
+       " 775122  2.707608 -4.839780          820            2.685627          2.69028\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 775879  3.995796 -4.843536          820            0.000069          2.69028\n",
+       " 775880  3.997498 -4.843683          820            0.000062          2.69028\n",
+       " 775881  3.999199 -4.843830          820            0.000055          2.69028\n",
+       " 775882  4.000901 -4.843976          820            0.000047          2.69028\n",
+       " 775883  4.002603 -4.844123          820            0.000040          2.69028\n",
+       " \n",
+       " [766 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 776118  2.700801 -4.839551          821            2.689427         2.690396\n",
+       " 776119  2.702502 -4.839551          821            2.688309         2.690396\n",
+       " 776120  2.704204 -4.839551          821            2.687191         2.690396\n",
+       " 776121  2.705906 -4.839551          821            2.686091         2.690396\n",
+       " 776122  2.707608 -4.839551          821            2.684996         2.690396\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 776879  3.995796 -4.843756          821            0.000070         2.690396\n",
+       " 776880  3.997498 -4.843902          821            0.000062         2.690396\n",
+       " 776881  3.999199 -4.844048          821            0.000055         2.690396\n",
+       " 776882  4.000901 -4.844193          821            0.000048         2.690396\n",
+       " 776883  4.002603 -4.844339          821            0.000041         2.690396\n",
+       " \n",
+       " [766 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 777118  2.700801 -4.840155          822            2.685396         2.688513\n",
+       " 777119  2.702502 -4.839975          822            2.684313         2.688513\n",
+       " 777120  2.704204 -4.839797          822            2.683229         2.688513\n",
+       " 777121  2.705906 -4.839849          822            2.682142         2.688513\n",
+       " 777122  2.707608 -4.839926          822            2.681054         2.688513\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 777878  3.994094 -4.844926          822            0.000076         2.688513\n",
+       " 777879  3.995796 -4.845133          822            0.000068         2.688513\n",
+       " 777880  3.997498 -4.845340          822            0.000061         2.688513\n",
+       " 777881  3.999199 -4.845547          822            0.000054         2.688513\n",
+       " 777882  4.000901 -4.845754          822            0.000047         2.688513\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 778118  2.700801 -4.840009          823            2.682787         2.685464\n",
+       " 778119  2.702502 -4.840009          823            2.681671         2.685464\n",
+       " 778120  2.704204 -4.840009          823            2.680554         2.685464\n",
+       " 778121  2.705906 -4.840009          823            2.679429         2.685464\n",
+       " 778122  2.707608 -4.840009          823            2.678305         2.685464\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 778878  3.994094 -4.844599          823            0.000075         2.685464\n",
+       " 778879  3.995796 -4.844783          823            0.000068         2.685464\n",
+       " 778880  3.997498 -4.844967          823            0.000061         2.685464\n",
+       " 778881  3.999199 -4.845151          823            0.000053         2.685464\n",
+       " 778882  4.000901 -4.845335          823            0.000046         2.685464\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 779118  2.700801 -4.840050          824            2.679091         2.682249\n",
+       " 779119  2.702502 -4.840138          824            2.677980         2.682249\n",
+       " 779120  2.704204 -4.840226          824            2.676868         2.682249\n",
+       " 779121  2.705906 -4.840174          824            2.675756         2.682249\n",
+       " 779122  2.707608 -4.840100          824            2.674644         2.682249\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 779878  3.994094 -4.844580          824            0.000074         2.682249\n",
+       " 779879  3.995796 -4.844771          824            0.000067         2.682249\n",
+       " 779880  3.997498 -4.844963          824            0.000060         2.682249\n",
+       " 779881  3.999199 -4.845154          824            0.000053         2.682249\n",
+       " 779882  4.000901 -4.845346          824            0.000046         2.682249\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 780118  2.700801 -4.840143          825            2.677834         2.679476\n",
+       " 780119  2.702502 -4.839939          825            2.676737         2.679476\n",
+       " 780120  2.704204 -4.839797          825            2.675633         2.679476\n",
+       " 780121  2.705906 -4.839872          825            2.674509         2.679476\n",
+       " 780122  2.707608 -4.839947          825            2.673384         2.679476\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 780878  3.994094 -4.843458          825            0.000075         2.679476\n",
+       " 780879  3.995796 -4.843596          825            0.000068         2.679476\n",
+       " 780880  3.997498 -4.843734          825            0.000060         2.679476\n",
+       " 780881  3.999199 -4.843872          825            0.000053         2.679476\n",
+       " 780882  4.000901 -4.844010          825            0.000046         2.679476\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 781118  2.700801 -4.840074          826            2.675226         2.677517\n",
+       " 781119  2.702502 -4.839722          826            2.674099         2.677517\n",
+       " 781120  2.704204 -4.839370          826            2.672972         2.677517\n",
+       " 781121  2.705906 -4.839638          826            2.671879         2.677517\n",
+       " 781122  2.707608 -4.840003          826            2.670790         2.677517\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 781878  3.994094 -4.843236          826            0.000074         2.677517\n",
+       " 781879  3.995796 -4.843374          826            0.000067         2.677517\n",
+       " 781880  3.997498 -4.843512          826            0.000060         2.677517\n",
+       " 781881  3.999199 -4.843650          826            0.000053         2.677517\n",
+       " 781882  4.000901 -4.843788          826            0.000046         2.677517\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 782118  2.700801 -4.839780          827            2.673980         2.676247\n",
+       " 782119  2.702502 -4.839780          827            2.672892         2.676247\n",
+       " 782120  2.704204 -4.839780          827            2.671804         2.676247\n",
+       " 782121  2.705906 -4.839833          827            2.670695         2.676247\n",
+       " 782122  2.707608 -4.839911          827            2.669577         2.676247\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 782878  3.994094 -4.842804          827            0.000075         2.676247\n",
+       " 782879  3.995796 -4.842934          827            0.000068         2.676247\n",
+       " 782880  3.997498 -4.843064          827            0.000061         2.676247\n",
+       " 782881  3.999199 -4.843194          827            0.000053         2.676247\n",
+       " 782882  4.000901 -4.843325          827            0.000046         2.676247\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 783118  2.700801 -4.840009          828            2.671690         2.673627\n",
+       " 783119  2.702502 -4.840009          828            2.670593         2.673627\n",
+       " 783120  2.704204 -4.840009          828            2.669495         2.673627\n",
+       " 783121  2.705906 -4.839939          828            2.668383         2.673627\n",
+       " 783122  2.707608 -4.839865          828            2.667270         2.673627\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 783878  3.994094 -4.844174          828            0.000075         2.673627\n",
+       " 783879  3.995796 -4.844350          828            0.000068         2.673627\n",
+       " 783880  3.997498 -4.844526          828            0.000061         2.673627\n",
+       " 783881  3.999199 -4.844702          828            0.000054         2.673627\n",
+       " 783882  4.000901 -4.844878          828            0.000047         2.673627\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 784118  2.700801 -4.840009          829            2.670360         2.672432\n",
+       " 784119  2.702502 -4.839948          829            2.669257         2.672432\n",
+       " 784120  2.704204 -4.839870          829            2.668121         2.672432\n",
+       " 784121  2.705906 -4.839793          829            2.666985         2.672432\n",
+       " 784122  2.707608 -4.839844          829            2.665852         2.672432\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 784878  3.994094 -4.844460          829            0.000074         2.672432\n",
+       " 784879  3.995796 -4.844629          829            0.000067         2.672432\n",
+       " 784880  3.997498 -4.844798          829            0.000060         2.672432\n",
+       " 784881  3.999199 -4.844967          829            0.000053         2.672432\n",
+       " 784882  4.000901 -4.845136          829            0.000046         2.672432\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 785118  2.700801 -4.839448          830            2.667382         2.670587\n",
+       " 785119  2.702502 -4.839716          830            2.666272         2.670587\n",
+       " 785120  2.704204 -4.839985          830            2.665162         2.670587\n",
+       " 785121  2.705906 -4.839942          830            2.664046         2.670587\n",
+       " 785122  2.707608 -4.839868          830            2.662929         2.670587\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 785878  3.994094 -4.843791          830            0.000075         2.670587\n",
+       " 785879  3.995796 -4.843952          830            0.000068         2.670587\n",
+       " 785880  3.997498 -4.844113          830            0.000061         2.670587\n",
+       " 785881  3.999199 -4.844274          830            0.000054         2.670587\n",
+       " 785882  4.000901 -4.844434          830            0.000047         2.670587\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 786118  2.700801 -4.840009          831            2.664905         2.667446\n",
+       " 786119  2.702502 -4.840009          831            2.663816         2.667446\n",
+       " 786120  2.704204 -4.840040          831            2.662713         2.667446\n",
+       " 786121  2.705906 -4.840115          831            2.661589         2.667446\n",
+       " 786122  2.707608 -4.840189          831            2.660464         2.667446\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 786878  3.994094 -4.842761          831            0.000075         2.667446\n",
+       " 786879  3.995796 -4.842898          831            0.000068         2.667446\n",
+       " 786880  3.997498 -4.843036          831            0.000061         2.667446\n",
+       " 786881  3.999199 -4.843174          831            0.000054         2.667446\n",
+       " 786882  4.000901 -4.843311          831            0.000047         2.667446\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 787118  2.700801 -4.840009          832            2.662781         2.665001\n",
+       " 787119  2.702502 -4.840009          832            2.661691         2.665001\n",
+       " 787120  2.704204 -4.840009          832            2.660602         2.665001\n",
+       " 787121  2.705906 -4.839946          832            2.659500         2.665001\n",
+       " 787122  2.707608 -4.839793          832            2.658381         2.665001\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 787878  3.994094 -4.845747          832            0.000075         2.665001\n",
+       " 787879  3.995796 -4.845978          832            0.000068         2.665001\n",
+       " 787880  3.997498 -4.846208          832            0.000061         2.665001\n",
+       " 787881  3.999199 -4.846437          832            0.000053         2.665001\n",
+       " 787882  4.000901 -4.846667          832            0.000046         2.665001\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 788118  2.700801 -4.839487          833            2.658149         2.662596\n",
+       " 788119  2.702502 -4.839839          833            2.657017         2.662596\n",
+       " 788120  2.704204 -4.840191          833            2.655885         2.662596\n",
+       " 788121  2.705906 -4.840110          833            2.654762         2.662596\n",
+       " 788122  2.707608 -4.839962          833            2.653641         2.662596\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 788878  3.994094 -4.844614          833            0.000075         2.662596\n",
+       " 788879  3.995796 -4.844797          833            0.000067         2.662596\n",
+       " 788880  3.997498 -4.844979          833            0.000060         2.662596\n",
+       " 788881  3.999199 -4.845162          833            0.000053         2.662596\n",
+       " 788882  4.000901 -4.845345          833            0.000046         2.662596\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 789118  2.700801 -4.839555          834            2.655544         2.657657\n",
+       " 789119  2.702502 -4.840053          834            2.654447         2.657657\n",
+       " 789120  2.704204 -4.840238          834            2.653305         2.657657\n",
+       " 789121  2.705906 -4.840238          834            2.652137         2.657657\n",
+       " 789122  2.707608 -4.840238          834            2.650969         2.657657\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 789878  3.994094 -4.844695          834            0.000074         2.657657\n",
+       " 789879  3.995796 -4.844863          834            0.000067         2.657657\n",
+       " 789880  3.997498 -4.845030          834            0.000060         2.657657\n",
+       " 789881  3.999199 -4.845198          834            0.000053         2.657657\n",
+       " 789882  4.000901 -4.845366          834            0.000046         2.657657\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 790118  2.700801 -4.840056          835            2.652493         2.655382\n",
+       " 790119  2.702502 -4.840156          835            2.651370         2.655382\n",
+       " 790120  2.704204 -4.840225          835            2.650249         2.655382\n",
+       " 790121  2.705906 -4.840149          835            2.649138         2.655382\n",
+       " 790122  2.707608 -4.840075          835            2.648027         2.655382\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 790878  3.994094 -4.844056          835            0.000074         2.655382\n",
+       " 790879  3.995796 -4.844215          835            0.000067         2.655382\n",
+       " 790880  3.997498 -4.844374          835            0.000059         2.655382\n",
+       " 790881  3.999199 -4.844533          835            0.000052         2.655382\n",
+       " 790882  4.000901 -4.844693          835            0.000045         2.655382\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 791118  2.700801 -4.840074          836            2.650936         2.652727\n",
+       " 791119  2.702502 -4.840211          836            2.649818         2.652727\n",
+       " 791120  2.704204 -4.840238          836            2.648690         2.652727\n",
+       " 791121  2.705906 -4.840238          836            2.647560         2.652727\n",
+       " 791122  2.707608 -4.840238          836            2.646430         2.652727\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 791878  3.994094 -4.843891          836            0.000072         2.652727\n",
+       " 791879  3.995796 -4.844044          836            0.000065         2.652727\n",
+       " 791880  3.997498 -4.844197          836            0.000058         2.652727\n",
+       " 791881  3.999199 -4.844350          836            0.000051         2.652727\n",
+       " 791882  4.000901 -4.844503          836            0.000044         2.652727\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 792118  2.700801 -4.840247          837            2.648614         2.651435\n",
+       " 792119  2.702502 -4.840659          837            2.647481         2.651435\n",
+       " 792120  2.704204 -4.840354          837            2.646393         2.651435\n",
+       " 792121  2.705906 -4.840049          837            2.645305         2.651435\n",
+       " 792122  2.707608 -4.839789          837            2.644206         2.651435\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 792878  3.994094 -4.845490          837            0.000072         2.651435\n",
+       " 792879  3.995796 -4.845696          837            0.000065         2.651435\n",
+       " 792880  3.997498 -4.845902          837            0.000058         2.651435\n",
+       " 792881  3.999199 -4.846108          837            0.000050         2.651435\n",
+       " 792882  4.000901 -4.846314          837            0.000043         2.651435\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 793118  2.700801 -4.839880          838            2.648500         2.650017\n",
+       " 793119  2.702502 -4.840092          838            2.647375         2.650017\n",
+       " 793120  2.704204 -4.840191          838            2.646252         2.650017\n",
+       " 793121  2.705906 -4.840041          838            2.645132         2.650017\n",
+       " 793122  2.707608 -4.839890          838            2.644012         2.650017\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 793878  3.994094 -4.843309          838            0.000072         2.650017\n",
+       " 793879  3.995796 -4.843440          838            0.000065         2.650017\n",
+       " 793880  3.997498 -4.843569          838            0.000058         2.650017\n",
+       " 793881  3.999199 -4.843699          838            0.000051         2.650017\n",
+       " 793882  4.000901 -4.843829          838            0.000044         2.650017\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 794118  2.700801 -4.839694          839            2.645977         2.648448\n",
+       " 794119  2.702502 -4.840001          839            2.644861         2.648448\n",
+       " 794120  2.704204 -4.840255          839            2.643736         2.648448\n",
+       " 794121  2.705906 -4.840332          839            2.642576         2.648448\n",
+       " 794122  2.707608 -4.840407          839            2.641417         2.648448\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 794878  3.994094 -4.845650          839            0.000073         2.648448\n",
+       " 794879  3.995796 -4.845862          839            0.000066         2.648448\n",
+       " 794880  3.997498 -4.846076          839            0.000059         2.648448\n",
+       " 794881  3.999199 -4.846289          839            0.000052         2.648448\n",
+       " 794882  4.000901 -4.846502          839            0.000045         2.648448\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 795118  2.700801 -4.840269          840            2.644236         2.645926\n",
+       " 795119  2.702502 -4.839843          840            2.643137         2.645926\n",
+       " 795120  2.704204 -4.839717          840            2.642026         2.645926\n",
+       " 795121  2.705906 -4.839643          840            2.640913         2.645926\n",
+       " 795122  2.707608 -4.839569          840            2.639801         2.645926\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 795878  3.994094 -4.844198          840            0.000073         2.645926\n",
+       " 795879  3.995796 -4.844381          840            0.000066         2.645926\n",
+       " 795880  3.997498 -4.844563          840            0.000059         2.645926\n",
+       " 795881  3.999199 -4.844746          840            0.000051         2.645926\n",
+       " 795882  4.000901 -4.844928          840            0.000044         2.645926\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 796118  2.700801 -4.840353          841            2.642687         2.645205\n",
+       " 796119  2.702502 -4.840111          841            2.641580         2.645205\n",
+       " 796120  2.704204 -4.840009          841            2.640463         2.645205\n",
+       " 796121  2.705906 -4.840009          841            2.639338         2.645205\n",
+       " 796122  2.707608 -4.840009          841            2.638214         2.645205\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 796878  3.994094 -4.844917          841            0.000075         2.645205\n",
+       " 796879  3.995796 -4.845129          841            0.000068         2.645205\n",
+       " 796880  3.997498 -4.845342          841            0.000060         2.645205\n",
+       " 796881  3.999199 -4.845555          841            0.000053         2.645205\n",
+       " 796882  4.000901 -4.845767          841            0.000046         2.645205\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 797118  2.700801 -4.840238          842            2.640553         2.642862\n",
+       " 797119  2.702502 -4.840238          842            2.639398         2.642862\n",
+       " 797120  2.704204 -4.840168          842            2.638279         2.642862\n",
+       " 797121  2.705906 -4.840095          842            2.637162         2.642862\n",
+       " 797122  2.707608 -4.840021          842            2.636045         2.642862\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 797878  3.994094 -4.844621          842            0.000073         2.642862\n",
+       " 797879  3.995796 -4.844811          842            0.000066         2.642862\n",
+       " 797880  3.997498 -4.845001          842            0.000059         2.642862\n",
+       " 797881  3.999199 -4.845191          842            0.000051         2.642862\n",
+       " 797882  4.000901 -4.845381          842            0.000044         2.642862\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 798118  2.700801 -4.840060          843            2.637368         2.639787\n",
+       " 798119  2.702502 -4.839677          843            2.636244         2.639787\n",
+       " 798120  2.704204 -4.839602          843            2.635134         2.639787\n",
+       " 798121  2.705906 -4.839677          843            2.634031         2.639787\n",
+       " 798122  2.707608 -4.839752          843            2.632929         2.639787\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 798878  3.994094 -4.843136          843            0.000073         2.639787\n",
+       " 798879  3.995796 -4.843249          843            0.000066         2.639787\n",
+       " 798880  3.997498 -4.843362          843            0.000059         2.639787\n",
+       " 798881  3.999199 -4.843476          843            0.000052         2.639787\n",
+       " 798882  4.000901 -4.843589          843            0.000045         2.639787\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 799118  2.700801 -4.839958          844            2.635186         2.637573\n",
+       " 799119  2.702502 -4.839834          844            2.634064         2.637573\n",
+       " 799120  2.704204 -4.839910          844            2.632922         2.637573\n",
+       " 799121  2.705906 -4.839986          844            2.631781         2.637573\n",
+       " 799122  2.707608 -4.839906          844            2.630648         2.637573\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 799878  3.994094 -4.845811          844            0.000072         2.637573\n",
+       " 799879  3.995796 -4.846045          844            0.000065         2.637573\n",
+       " 799880  3.997498 -4.846280          844            0.000058         2.637573\n",
+       " 799881  3.999199 -4.846514          844            0.000051         2.637573\n",
+       " 799882  4.000901 -4.846748          844            0.000044         2.637573\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 800118  2.700801 -4.839768          845            2.633029         2.634727\n",
+       " 800119  2.702502 -4.840046          845            2.631897         2.634727\n",
+       " 800120  2.704204 -4.840122          845            2.630752         2.634727\n",
+       " 800121  2.705906 -4.840198          845            2.629606         2.634727\n",
+       " 800122  2.707608 -4.840202          845            2.628470         2.634727\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 800878  3.994094 -4.845059          845            0.000071         2.634727\n",
+       " 800879  3.995796 -4.845263          845            0.000064         2.634727\n",
+       " 800880  3.997498 -4.845468          845            0.000057         2.634727\n",
+       " 800881  3.999199 -4.845672          845            0.000050         2.634727\n",
+       " 800882  4.000901 -4.845876          845            0.000043         2.634727\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 801118  2.700801 -4.840318          846            2.631127         2.634079\n",
+       " 801119  2.702502 -4.839999          846            2.629996         2.634079\n",
+       " 801120  2.704204 -4.839757          846            2.628862         2.634079\n",
+       " 801121  2.705906 -4.839683          846            2.627719         2.634079\n",
+       " 801122  2.707608 -4.839609          846            2.626576         2.634079\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 801878  3.994094 -4.845123          846            0.000070         2.634079\n",
+       " 801879  3.995796 -4.845321          846            0.000063         2.634079\n",
+       " 801880  3.997498 -4.845519          846            0.000056         2.634079\n",
+       " 801881  3.999199 -4.845716          846            0.000049         2.634079\n",
+       " 801882  4.000901 -4.845914          846            0.000041         2.634079\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 802118  2.700801 -4.839839          847            2.628022         2.630658\n",
+       " 802119  2.702502 -4.839583          847            2.626935         2.630658\n",
+       " 802120  2.704204 -4.839736          847            2.625790         2.630658\n",
+       " 802121  2.705906 -4.839889          847            2.624644         2.630658\n",
+       " 802122  2.707608 -4.839993          847            2.623495         2.630658\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 802878  3.994094 -4.844859          847            0.000071         2.630658\n",
+       " 802879  3.995796 -4.845055          847            0.000064         2.630658\n",
+       " 802880  3.997498 -4.845250          847            0.000057         2.630658\n",
+       " 802881  3.999199 -4.845446          847            0.000050         2.630658\n",
+       " 802882  4.000901 -4.845642          847            0.000043         2.630658\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 803118  2.700801 -4.840238          848            2.625317         2.628106\n",
+       " 803119  2.702502 -4.840199          848            2.624223         2.628106\n",
+       " 803120  2.704204 -4.840047          848            2.623082         2.628106\n",
+       " 803121  2.705906 -4.839894          848            2.621941         2.628106\n",
+       " 803122  2.707608 -4.839799          848            2.620797         2.628106\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 803878  3.994094 -4.844131          848            0.000070         2.628106\n",
+       " 803879  3.995796 -4.844290          848            0.000063         2.628106\n",
+       " 803880  3.997498 -4.844448          848            0.000056         2.628106\n",
+       " 803881  3.999199 -4.844606          848            0.000049         2.628106\n",
+       " 803882  4.000901 -4.844765          848            0.000042         2.628106\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 804118  2.700801 -4.840178          849            2.623702         2.626026\n",
+       " 804119  2.702502 -4.840051          849            2.622593         2.626026\n",
+       " 804120  2.704204 -4.839960          849            2.621458         2.626026\n",
+       " 804121  2.705906 -4.839885          849            2.620310         2.626026\n",
+       " 804122  2.707608 -4.839811          849            2.619163         2.626026\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 804878  3.994094 -4.844320          849            0.000071         2.626026\n",
+       " 804879  3.995796 -4.844486          849            0.000064         2.626026\n",
+       " 804880  3.997498 -4.844652          849            0.000056         2.626026\n",
+       " 804881  3.999199 -4.844818          849            0.000049         2.626026\n",
+       " 804882  4.000901 -4.844984          849            0.000042         2.626026\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 805118  2.700801 -4.839750          850            2.620955         2.623508\n",
+       " 805119  2.702502 -4.839922          850            2.619829         2.623508\n",
+       " 805120  2.704204 -4.840074          850            2.618706         2.623508\n",
+       " 805121  2.705906 -4.840227          850            2.617582         2.623508\n",
+       " 805122  2.707608 -4.840168          850            2.616434         2.623508\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 805878  3.994094 -4.843924          850            0.000071         2.623508\n",
+       " 805879  3.995796 -4.844074          850            0.000064         2.623508\n",
+       " 805880  3.997498 -4.844224          850            0.000057         2.623508\n",
+       " 805881  3.999199 -4.844375          850            0.000050         2.623508\n",
+       " 805882  4.000901 -4.844525          850            0.000043         2.623508\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 806118  2.700801 -4.839910          851            2.617946          2.62104\n",
+       " 806119  2.702502 -4.839809          851            2.616789          2.62104\n",
+       " 806120  2.704204 -4.839883          851            2.615699          2.62104\n",
+       " 806121  2.705906 -4.839957          851            2.614608          2.62104\n",
+       " 806122  2.707608 -4.839987          851            2.613497          2.62104\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 806878  3.994094 -4.843314          851            0.000070          2.62104\n",
+       " 806879  3.995796 -4.843449          851            0.000063          2.62104\n",
+       " 806880  3.997498 -4.843585          851            0.000056          2.62104\n",
+       " 806881  3.999199 -4.843721          851            0.000049          2.62104\n",
+       " 806882  4.000901 -4.843856          851            0.000042          2.62104\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 807118  2.700801 -4.840158          852            2.614155         2.616863\n",
+       " 807119  2.702502 -4.840182          852            2.613045         2.616863\n",
+       " 807120  2.704204 -4.840107          852            2.611947         2.616863\n",
+       " 807121  2.705906 -4.840032          852            2.610849         2.616863\n",
+       " 807122  2.707608 -4.840009          852            2.609702         2.616863\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 807878  3.994094 -4.844547          852            0.000069         2.616863\n",
+       " 807879  3.995796 -4.844720          852            0.000062         2.616863\n",
+       " 807880  3.997498 -4.844894          852            0.000055         2.616863\n",
+       " 807881  3.999199 -4.845068          852            0.000048         2.616863\n",
+       " 807882  4.000901 -4.845241          852            0.000041         2.616863\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 808118  2.700801 -4.840009          853            2.612375         2.614925\n",
+       " 808119  2.702502 -4.840007          853            2.611251         2.614925\n",
+       " 808120  2.704204 -4.839931          853            2.610127         2.614925\n",
+       " 808121  2.705906 -4.839854          853            2.609004         2.614925\n",
+       " 808122  2.707608 -4.839785          853            2.607879         2.614925\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 808878  3.994094 -4.844538          853            0.000070         2.614925\n",
+       " 808879  3.995796 -4.844712          853            0.000063         2.614925\n",
+       " 808880  3.997498 -4.844886          853            0.000056         2.614925\n",
+       " 808881  3.999199 -4.845059          853            0.000048         2.614925\n",
+       " 808882  4.000901 -4.845233          853            0.000041         2.614925\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 809118  2.700801 -4.839588          854            2.608866         2.610872\n",
+       " 809119  2.702502 -4.839738          854            2.607755         2.610872\n",
+       " 809120  2.704204 -4.839888          854            2.606643         2.610872\n",
+       " 809121  2.705906 -4.839994          854            2.605523         2.610872\n",
+       " 809122  2.707608 -4.839918          854            2.604364         2.610872\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 809878  3.994094 -4.844560          854            0.000069         2.610872\n",
+       " 809879  3.995796 -4.844734          854            0.000062         2.610872\n",
+       " 809880  3.997498 -4.844908          854            0.000055         2.610872\n",
+       " 809881  3.999199 -4.845082          854            0.000048         2.610872\n",
+       " 809882  4.000901 -4.845256          854            0.000040         2.610872\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 810118  2.700801 -4.840079          855            2.605875         2.609017\n",
+       " 810119  2.702502 -4.840230          855            2.604738         2.609017\n",
+       " 810120  2.704204 -4.840308          855            2.603615         2.609017\n",
+       " 810121  2.705906 -4.840382          855            2.602494         2.609017\n",
+       " 810122  2.707608 -4.840456          855            2.601373         2.609017\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 810877  3.992392 -4.842270          855            0.000075         2.609017\n",
+       " 810878  3.994094 -4.842369          855            0.000068         2.609017\n",
+       " 810879  3.995796 -4.842467          855            0.000061         2.609017\n",
+       " 810880  3.997498 -4.842566          855            0.000053         2.609017\n",
+       " 810881  3.999199 -4.842665          855            0.000046         2.609017\n",
+       " \n",
+       " [764 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 811118  2.700801 -4.839780          856            2.600945         2.603774\n",
+       " 811119  2.702502 -4.839780          856            2.599768         2.603774\n",
+       " 811120  2.704204 -4.839780          856            2.598591         2.603774\n",
+       " 811121  2.705906 -4.839763          856            2.597428         2.603774\n",
+       " 811122  2.707608 -4.839687          856            2.596313         2.603774\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 811877  3.992392 -4.844954          856            0.000075         2.603774\n",
+       " 811878  3.994094 -4.845159          856            0.000068         2.603774\n",
+       " 811879  3.995796 -4.845363          856            0.000061         2.603774\n",
+       " 811880  3.997498 -4.845568          856            0.000053         2.603774\n",
+       " 811881  3.999199 -4.845772          856            0.000046         2.603774\n",
+       " \n",
+       " [764 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 812118  2.700801 -4.839603          857            2.598955         2.600583\n",
+       " 812119  2.702502 -4.839714          857            2.597853         2.600583\n",
+       " 812120  2.704204 -4.839811          857            2.596732         2.600583\n",
+       " 812121  2.705906 -4.839887          857            2.595582         2.600583\n",
+       " 812122  2.707608 -4.839963          857            2.594432         2.600583\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 812877  3.992392 -4.845596          857            0.000075         2.600583\n",
+       " 812878  3.994094 -4.845809          857            0.000068         2.600583\n",
+       " 812879  3.995796 -4.846023          857            0.000061         2.600583\n",
+       " 812880  3.997498 -4.846237          857            0.000053         2.600583\n",
+       " 812881  3.999199 -4.846450          857            0.000046         2.600583\n",
+       " \n",
+       " [764 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 813118  2.700801 -4.839818          858            2.594531         2.596373\n",
+       " 813119  2.702502 -4.839894          858            2.593420         2.596373\n",
+       " 813120  2.704204 -4.839969          858            2.592309         2.596373\n",
+       " 813121  2.705906 -4.840009          858            2.591191         2.596373\n",
+       " 813122  2.707608 -4.840009          858            2.590067         2.596373\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 813877  3.992392 -4.844488          858            0.000073         2.596373\n",
+       " 813878  3.994094 -4.844655          858            0.000066         2.596373\n",
+       " 813879  3.995796 -4.844822          858            0.000059         2.596373\n",
+       " 813880  3.997498 -4.844990          858            0.000052         2.596373\n",
+       " 813881  3.999199 -4.845157          858            0.000045         2.596373\n",
+       " \n",
+       " [764 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 814118  2.700801 -4.839660          859            2.592289          2.59456\n",
+       " 814119  2.702502 -4.839780          859            2.591111          2.59456\n",
+       " 814120  2.704204 -4.839780          859            2.589999          2.59456\n",
+       " 814121  2.705906 -4.839780          859            2.588888          2.59456\n",
+       " 814122  2.707608 -4.839780          859            2.587767          2.59456\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 814877  3.992392 -4.844051          859            0.000074          2.59456\n",
+       " 814878  3.994094 -4.844211          859            0.000067          2.59456\n",
+       " 814879  3.995796 -4.844371          859            0.000060          2.59456\n",
+       " 814880  3.997498 -4.844531          859            0.000052          2.59456\n",
+       " 814881  3.999199 -4.844690          859            0.000045          2.59456\n",
+       " \n",
+       " [764 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 815118  2.700801 -4.839780          860            2.589055         2.591169\n",
+       " 815119  2.702502 -4.839820          860            2.587893         2.591169\n",
+       " 815120  2.704204 -4.839897          860            2.586765         2.591169\n",
+       " 815121  2.705906 -4.839972          860            2.585637         2.591169\n",
+       " 815122  2.707608 -4.840009          860            2.584502         2.591169\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 815877  3.992392 -4.844699          860            0.000073         2.591169\n",
+       " 815878  3.994094 -4.844873          860            0.000065         2.591169\n",
+       " 815879  3.995796 -4.845048          860            0.000058         2.591169\n",
+       " 815880  3.997498 -4.845222          860            0.000051         2.591169\n",
+       " 815881  3.999199 -4.845397          860            0.000044         2.591169\n",
+       " \n",
+       " [764 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 816118  2.700801 -4.839780          861            2.585151         2.588454\n",
+       " 816119  2.702502 -4.839780          861            2.584055         2.588454\n",
+       " 816120  2.704204 -4.839780          861            2.582943         2.588454\n",
+       " 816121  2.705906 -4.839780          861            2.581784         2.588454\n",
+       " 816122  2.707608 -4.839780          861            2.580624         2.588454\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 816877  3.992392 -4.843331          861            0.000071         2.588454\n",
+       " 816878  3.994094 -4.843460          861            0.000064         2.588454\n",
+       " 816879  3.995796 -4.843588          861            0.000057         2.588454\n",
+       " 816880  3.997498 -4.843717          861            0.000050         2.588454\n",
+       " 816881  3.999199 -4.843845          861            0.000043         2.588454\n",
+       " \n",
+       " [764 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 817118  2.700801 -4.839898          862            2.583435         2.584615\n",
+       " 817119  2.702502 -4.839780          862            2.582323         2.584615\n",
+       " 817120  2.704204 -4.839780          862            2.581212         2.584615\n",
+       " 817121  2.705906 -4.839780          862            2.580101         2.584615\n",
+       " 817122  2.707608 -4.839900          862            2.578948         2.584615\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 817877  3.992392 -4.844066          862            0.000070         2.584615\n",
+       " 817878  3.994094 -4.844239          862            0.000063         2.584615\n",
+       " 817879  3.995796 -4.844412          862            0.000056         2.584615\n",
+       " 817880  3.997498 -4.844584          862            0.000049         2.584615\n",
+       " 817881  3.999199 -4.844758          862            0.000042         2.584615\n",
+       " \n",
+       " [764 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 818118  2.700801 -4.840200          863            2.581806         2.583593\n",
+       " 818119  2.702502 -4.840117          863            2.580718         2.583593\n",
+       " 818120  2.704204 -4.840035          863            2.579630         2.583593\n",
+       " 818121  2.705906 -4.840009          863            2.578511         2.583593\n",
+       " 818122  2.707608 -4.840009          863            2.577379         2.583593\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 818877  3.992392 -4.845311          863            0.000070         2.583593\n",
+       " 818878  3.994094 -4.845514          863            0.000063         2.583593\n",
+       " 818879  3.995796 -4.845716          863            0.000056         2.583593\n",
+       " 818880  3.997498 -4.845919          863            0.000049         2.583593\n",
+       " 818881  3.999199 -4.846121          863            0.000042         2.583593\n",
+       " \n",
+       " [764 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 819118  2.700801 -4.839921          864            2.581455         2.582264\n",
+       " 819119  2.702502 -4.839732          864            2.580333         2.582264\n",
+       " 819120  2.704204 -4.839551          864            2.579210         2.582264\n",
+       " 819121  2.705906 -4.839551          864            2.578068         2.582264\n",
+       " 819122  2.707608 -4.839551          864            2.576926         2.582264\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 819877  3.992392 -4.844197          864            0.000069         2.582264\n",
+       " 819878  3.994094 -4.844348          864            0.000062         2.582264\n",
+       " 819879  3.995796 -4.844498          864            0.000055         2.582264\n",
+       " 819880  3.997498 -4.844648          864            0.000048         2.582264\n",
+       " 819881  3.999199 -4.844799          864            0.000041         2.582264\n",
+       " \n",
+       " [764 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 820118  2.700801 -4.840180          865            2.580327         2.581316\n",
+       " 820119  2.702502 -4.840067          865            2.579281         2.581316\n",
+       " 820120  2.704204 -4.839972          865            2.578185         2.581316\n",
+       " 820121  2.705906 -4.839897          865            2.577039         2.581316\n",
+       " 820122  2.707608 -4.839822          865            2.575892         2.581316\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 820877  3.992392 -4.843129          865            0.000068         2.581316\n",
+       " 820878  3.994094 -4.843264          865            0.000061         2.581316\n",
+       " 820879  3.995796 -4.843399          865            0.000054         2.581316\n",
+       " 820880  3.997498 -4.843534          865            0.000047         2.581316\n",
+       " 820881  3.999199 -4.843668          865            0.000040         2.581316\n",
+       " \n",
+       " [764 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 821118  2.700801 -4.839732          866            2.578639         2.580391\n",
+       " 821119  2.702502 -4.839628          866            2.577562         2.580391\n",
+       " 821120  2.704204 -4.839572          866            2.576472         2.580391\n",
+       " 821121  2.705906 -4.839648          866            2.575349         2.580391\n",
+       " 821122  2.707608 -4.839725          866            2.574225         2.580391\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 821876  3.990691 -4.844229          866            0.000075         2.580391\n",
+       " 821877  3.992392 -4.844392          866            0.000068         2.580391\n",
+       " 821878  3.994094 -4.844556          866            0.000061         2.580391\n",
+       " 821879  3.995796 -4.844720          866            0.000054         2.580391\n",
+       " 821880  3.997498 -4.844884          866            0.000047         2.580391\n",
+       " \n",
+       " [763 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 822118  2.700801 -4.840143          867            2.573474         2.577153\n",
+       " 822119  2.702502 -4.840009          867            2.572355         2.577153\n",
+       " 822120  2.704204 -4.840009          867            2.571275         2.577153\n",
+       " 822121  2.705906 -4.840009          867            2.570194         2.577153\n",
+       " 822122  2.707608 -4.840032          867            2.569088         2.577153\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 822876  3.990691 -4.843710          867            0.000072         2.577153\n",
+       " 822877  3.992392 -4.843852          867            0.000065         2.577153\n",
+       " 822878  3.994094 -4.843994          867            0.000058         2.577153\n",
+       " 822879  3.995796 -4.844135          867            0.000051         2.577153\n",
+       " 822880  3.997498 -4.844277          867            0.000044         2.577153\n",
+       " \n",
+       " [763 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 823118  2.700801 -4.839826          868            2.571811         2.573583\n",
+       " 823119  2.702502 -4.839924          868            2.570710         2.573583\n",
+       " 823120  2.704204 -4.840009          868            2.569601         2.573583\n",
+       " 823121  2.705906 -4.840009          868            2.568446         2.573583\n",
+       " 823122  2.707608 -4.840009          868            2.567292         2.573583\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 823876  3.990691 -4.843907          868            0.000072         2.573583\n",
+       " 823877  3.992392 -4.844056          868            0.000065         2.573583\n",
+       " 823878  3.994094 -4.844204          868            0.000058         2.573583\n",
+       " 823879  3.995796 -4.844353          868            0.000051         2.573583\n",
+       " 823880  3.997498 -4.844501          868            0.000044         2.573583\n",
+       " \n",
+       " [763 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 824118  2.700801 -4.840009          869            2.569120         2.572245\n",
+       " 824119  2.702502 -4.840009          869            2.567985         2.572245\n",
+       " 824120  2.704204 -4.840009          869            2.566850         2.572245\n",
+       " 824121  2.705906 -4.840051          869            2.565709         2.572245\n",
+       " 824122  2.707608 -4.840126          869            2.564563         2.572245\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 824876  3.990691 -4.844693          869            0.000071         2.572245\n",
+       " 824877  3.992392 -4.844870          869            0.000064         2.572245\n",
+       " 824878  3.994094 -4.845047          869            0.000058         2.572245\n",
+       " 824879  3.995796 -4.845224          869            0.000051         2.572245\n",
+       " 824880  3.997498 -4.845401          869            0.000044         2.572245\n",
+       " \n",
+       " [763 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 825118  2.700801 -4.839612          870            2.566659         2.569695\n",
+       " 825119  2.702502 -4.839691          870            2.565561         2.569695\n",
+       " 825120  2.704204 -4.839841          870            2.564458         2.569695\n",
+       " 825121  2.705906 -4.839991          870            2.563356         2.569695\n",
+       " 825122  2.707608 -4.840009          870            2.562204         2.569695\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 825876  3.990691 -4.843364          870            0.000071         2.569695\n",
+       " 825877  3.992392 -4.843482          870            0.000064         2.569695\n",
+       " 825878  3.994094 -4.843601          870            0.000057         2.569695\n",
+       " 825879  3.995796 -4.843719          870            0.000050         2.569695\n",
+       " 825880  3.997498 -4.843838          870            0.000043         2.569695\n",
+       " \n",
+       " [763 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 826118  2.700801 -4.840058          871            2.564922         2.567541\n",
+       " 826119  2.702502 -4.840162          871            2.563808         2.567541\n",
+       " 826120  2.704204 -4.840197          871            2.562680         2.567541\n",
+       " 826121  2.705906 -4.840044          871            2.561512         2.567541\n",
+       " 826122  2.707608 -4.839892          871            2.560344         2.567541\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 826876  3.990691 -4.844442          871            0.000071         2.567541\n",
+       " 826877  3.992392 -4.844627          871            0.000064         2.567541\n",
+       " 826878  3.994094 -4.844813          871            0.000057         2.567541\n",
+       " 826879  3.995796 -4.844998          871            0.000050         2.567541\n",
+       " 826880  3.997498 -4.845184          871            0.000043         2.567541\n",
+       " \n",
+       " [763 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 827118  2.700801 -4.839743          872            2.563344         2.566375\n",
+       " 827119  2.702502 -4.839662          872            2.562250         2.566375\n",
+       " 827120  2.704204 -4.839581          872            2.561155         2.566375\n",
+       " 827121  2.705906 -4.839601          872            2.560034         2.566375\n",
+       " 827122  2.707608 -4.839678          872            2.558898         2.566375\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 827876  3.990691 -4.843354          872            0.000072         2.566375\n",
+       " 827877  3.992392 -4.843472          872            0.000065         2.566375\n",
+       " 827878  3.994094 -4.843591          872            0.000058         2.566375\n",
+       " 827879  3.995796 -4.843709          872            0.000051         2.566375\n",
+       " 827880  3.997498 -4.843827          872            0.000044         2.566375\n",
+       " \n",
+       " [763 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 828118  2.700801 -4.840012          873            2.559410         2.563078\n",
+       " 828119  2.702502 -4.839820          873            2.558300         2.563078\n",
+       " 828120  2.704204 -4.839895          873            2.557193         2.563078\n",
+       " 828121  2.705906 -4.839970          873            2.556086         2.563078\n",
+       " 828122  2.707608 -4.840009          873            2.554956         2.563078\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 828876  3.990691 -4.844112          873            0.000071         2.563078\n",
+       " 828877  3.992392 -4.844267          873            0.000064         2.563078\n",
+       " 828878  3.994094 -4.844423          873            0.000057         2.563078\n",
+       " 828879  3.995796 -4.844578          873            0.000050         2.563078\n",
+       " 828880  3.997498 -4.844734          873            0.000043         2.563078\n",
+       " \n",
+       " [763 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 829118  2.700801 -4.840009          874            2.557034         2.559597\n",
+       " 829119  2.702502 -4.840009          874            2.555883         2.559597\n",
+       " 829120  2.704204 -4.840009          874            2.554732         2.559597\n",
+       " 829121  2.705906 -4.840008          874            2.553581         2.559597\n",
+       " 829122  2.707608 -4.839934          874            2.552447         2.559597\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 829876  3.990691 -4.843735          874            0.000071         2.559597\n",
+       " 829877  3.992392 -4.843875          874            0.000064         2.559597\n",
+       " 829878  3.994094 -4.844016          874            0.000057         2.559597\n",
+       " 829879  3.995796 -4.844156          874            0.000050         2.559597\n",
+       " 829880  3.997498 -4.844296          874            0.000043         2.559597\n",
+       " \n",
+       " [763 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 830118  2.700801 -4.839861          875            2.555072         2.557496\n",
+       " 830119  2.702502 -4.840034          875            2.553938         2.557496\n",
+       " 830120  2.704204 -4.840207          875            2.552805         2.557496\n",
+       " 830121  2.705906 -4.840178          875            2.551684         2.557496\n",
+       " 830122  2.707608 -4.840106          875            2.550566         2.557496\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 830876  3.990691 -4.844128          875            0.000070         2.557496\n",
+       " 830877  3.992392 -4.844283          875            0.000064         2.557496\n",
+       " 830878  3.994094 -4.844438          875            0.000057         2.557496\n",
+       " 830879  3.995796 -4.844593          875            0.000050         2.557496\n",
+       " 830880  3.997498 -4.844748          875            0.000043         2.557496\n",
+       " \n",
+       " [763 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 831118  2.700801 -4.839930          881            2.678844         2.398371\n",
+       " 831119  2.702502 -4.839760          881            2.677780         2.398371\n",
+       " 831120  2.704204 -4.839590          881            2.676715         2.398371\n",
+       " 831121  2.705906 -4.839668          881            2.675625         2.398371\n",
+       " 831122  2.707608 -4.839818          881            2.674527         2.398371\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 831882  4.000901 -4.842972          881            0.000069         2.398371\n",
+       " 831883  4.002603 -4.843081          881            0.000062         2.398371\n",
+       " 831884  4.004304 -4.843188          881            0.000056         2.398371\n",
+       " 831885  4.006006 -4.843296          881            0.000049         2.398371\n",
+       " 831886  4.007708 -4.843404          881            0.000042         2.398371\n",
+       " \n",
+       " [769 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 832118  2.700801 -4.840059          882            2.655212         2.651332\n",
+       " 832119  2.702502 -4.840165          882            2.654125         2.651332\n",
+       " 832120  2.704204 -4.840192          882            2.653040         2.651332\n",
+       " 832121  2.705906 -4.840044          882            2.651958         2.651332\n",
+       " 832122  2.707608 -4.839896          882            2.650876         2.651332\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 832880  3.997498 -4.844939          882            0.000071         2.651332\n",
+       " 832881  3.999199 -4.845113          882            0.000064         2.651332\n",
+       " 832882  4.000901 -4.845286          882            0.000057         2.651332\n",
+       " 832883  4.002603 -4.845460          882            0.000050         2.651332\n",
+       " 832884  4.004304 -4.845634          882            0.000044         2.651332\n",
+       " \n",
+       " [767 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 833118  2.700801 -4.839705          883            2.640255         2.647193\n",
+       " 833119  2.702502 -4.840003          883            2.639182         2.647193\n",
+       " 833120  2.704204 -4.839929          883            2.638115         2.647193\n",
+       " 833121  2.705906 -4.839853          883            2.637048         2.647193\n",
+       " 833122  2.707608 -4.839780          883            2.635979         2.647193\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 833879  3.995796 -4.844524          883            0.000073         2.647193\n",
+       " 833880  3.997498 -4.844676          883            0.000066         2.647193\n",
+       " 833881  3.999199 -4.844828          883            0.000060         2.647193\n",
+       " 833882  4.000901 -4.844979          883            0.000053         2.647193\n",
+       " 833883  4.002603 -4.845131          883            0.000046         2.647193\n",
+       " \n",
+       " [766 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 834118  2.700801 -4.840127          884            2.626405         2.634668\n",
+       " 834119  2.702502 -4.839890          884            2.625296         2.634668\n",
+       " 834120  2.704204 -4.839861          884            2.624186         2.634668\n",
+       " 834121  2.705906 -4.840011          884            2.623075         2.634668\n",
+       " 834122  2.707608 -4.840161          884            2.621964         2.634668\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 834879  3.995796 -4.843765          884            0.000069         2.634668\n",
+       " 834880  3.997498 -4.843903          884            0.000062         2.634668\n",
+       " 834881  3.999199 -4.844040          884            0.000055         2.634668\n",
+       " 834882  4.000901 -4.844178          884            0.000049         2.634668\n",
+       " 834883  4.002603 -4.844316          884            0.000042         2.634668\n",
+       " \n",
+       " [766 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 835118  2.700801 -4.840238          885            2.614661         2.622269\n",
+       " 835119  2.702502 -4.840238          885            2.613540         2.622269\n",
+       " 835120  2.704204 -4.840238          885            2.612419         2.622269\n",
+       " 835121  2.705906 -4.840236          885            2.611297         2.622269\n",
+       " 835122  2.707608 -4.840086          885            2.610182         2.622269\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 835878  3.994094 -4.844838          885            0.000072         2.622269\n",
+       " 835879  3.995796 -4.845026          885            0.000065         2.622269\n",
+       " 835880  3.997498 -4.845212          885            0.000058         2.622269\n",
+       " 835881  3.999199 -4.845400          885            0.000052         2.622269\n",
+       " 835882  4.000901 -4.845587          885            0.000045         2.622269\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 836118  2.700801 -4.840009          886            2.604405         2.610917\n",
+       " 836119  2.702502 -4.839863          886            2.603316         2.610917\n",
+       " 836120  2.704204 -4.839713          886            2.602227         2.610917\n",
+       " 836121  2.705906 -4.839563          886            2.601137         2.610917\n",
+       " 836122  2.707608 -4.839756          886            2.599998         2.610917\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 836878  3.994094 -4.843171          886            0.000069         2.610917\n",
+       " 836879  3.995796 -4.843287          886            0.000062         2.610917\n",
+       " 836880  3.997498 -4.843402          886            0.000056         2.610917\n",
+       " 836881  3.999199 -4.843518          886            0.000049         2.610917\n",
+       " 836882  4.000901 -4.843634          886            0.000042         2.610917\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 837118  2.700801 -4.839780          887            2.594970         2.600899\n",
+       " 837119  2.702502 -4.839780          887            2.593855         2.600899\n",
+       " 837120  2.704204 -4.839787          887            2.592738         2.600899\n",
+       " 837121  2.705906 -4.839862          887            2.591600         2.600899\n",
+       " 837122  2.707608 -4.839937          887            2.590463         2.600899\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 837877  3.992392 -4.844854          887            0.000073         2.600899\n",
+       " 837878  3.994094 -4.845036          887            0.000066         2.600899\n",
+       " 837879  3.995796 -4.845218          887            0.000059         2.600899\n",
+       " 837880  3.997498 -4.845399          887            0.000052         2.600899\n",
+       " 837881  3.999199 -4.845581          887            0.000045         2.600899\n",
+       " \n",
+       " [764 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 838118  2.700801 -4.839864          888            2.586964         2.592395\n",
+       " 838119  2.702502 -4.840043          888            2.585864         2.592395\n",
+       " 838120  2.704204 -4.840222          888            2.584765         2.592395\n",
+       " 838121  2.705906 -4.840169          888            2.583648         2.592395\n",
+       " 838122  2.707608 -4.840093          888            2.582529         2.592395\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 838877  3.992392 -4.843699          888            0.000071         2.592395\n",
+       " 838878  3.994094 -4.843844          888            0.000064         2.592395\n",
+       " 838879  3.995796 -4.843988          888            0.000057         2.592395\n",
+       " 838880  3.997498 -4.844132          888            0.000050         2.592395\n",
+       " 838881  3.999199 -4.844277          888            0.000044         2.592395\n",
+       " \n",
+       " [764 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 839118  2.700801 -4.839826          889            2.580727         2.585464\n",
+       " 839119  2.702502 -4.839575          889            2.579610         2.585464\n",
+       " 839120  2.704204 -4.839652          889            2.578442         2.585464\n",
+       " 839121  2.705906 -4.839729          889            2.577275         2.585464\n",
+       " 839122  2.707608 -4.839780          889            2.576124         2.585464\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 839877  3.992392 -4.844731          889            0.000070         2.585464\n",
+       " 839878  3.994094 -4.844903          889            0.000063         2.585464\n",
+       " 839879  3.995796 -4.845076          889            0.000056         2.585464\n",
+       " 839880  3.997498 -4.845249          889            0.000050         2.585464\n",
+       " 839881  3.999199 -4.845421          889            0.000043         2.585464\n",
+       " \n",
+       " [764 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 840118  2.700801 -4.839862          890            2.574250         2.580104\n",
+       " 840119  2.702502 -4.839997          890            2.573106         2.580104\n",
+       " 840120  2.704204 -4.839921          890            2.571981         2.580104\n",
+       " 840121  2.705906 -4.839847          890            2.570857         2.580104\n",
+       " 840122  2.707608 -4.839789          890            2.569732         2.580104\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 840877  3.992392 -4.843553          890            0.000068         2.580104\n",
+       " 840878  3.994094 -4.843690          890            0.000061         2.580104\n",
+       " 840879  3.995796 -4.843827          890            0.000055         2.580104\n",
+       " 840880  3.997498 -4.843964          890            0.000048         2.580104\n",
+       " 840881  3.999199 -4.844101          890            0.000041         2.580104\n",
+       " \n",
+       " [764 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 841118  2.700801 -4.840009          891            2.567299         2.572336\n",
+       " 841119  2.702502 -4.840009          891            2.566121         2.572336\n",
+       " 841120  2.704204 -4.840009          891            2.564977         2.572336\n",
+       " 841121  2.705906 -4.840009          891            2.563859         2.572336\n",
+       " 841122  2.707608 -4.840009          891            2.562741         2.572336\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 841876  3.990691 -4.843457          891            0.000073         2.572336\n",
+       " 841877  3.992392 -4.843594          891            0.000066         2.572336\n",
+       " 841878  3.994094 -4.843732          891            0.000059         2.572336\n",
+       " 841879  3.995796 -4.843869          891            0.000053         2.572336\n",
+       " 841880  3.997498 -4.844007          891            0.000046         2.572336\n",
+       " \n",
+       " [763 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 842118  2.700801 -4.840414          892            2.562503          2.56653\n",
+       " 842119  2.702502 -4.840301          892            2.561390          2.56653\n",
+       " 842120  2.704204 -4.840204          892            2.560246          2.56653\n",
+       " 842121  2.705906 -4.840128          892            2.559064          2.56653\n",
+       " 842122  2.707608 -4.840052          892            2.557883          2.56653\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 842876  3.990691 -4.843341          892            0.000073          2.56653\n",
+       " 842877  3.992392 -4.843456          892            0.000066          2.56653\n",
+       " 842878  3.994094 -4.843572          892            0.000059          2.56653\n",
+       " 842879  3.995796 -4.843687          892            0.000052          2.56653\n",
+       " 842880  3.997498 -4.843803          892            0.000045          2.56653\n",
+       " \n",
+       " [763 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 843118  2.700801 -4.839738          893            2.559187         2.562094\n",
+       " 843119  2.702502 -4.839649          893            2.558056         2.562094\n",
+       " 843120  2.704204 -4.839560          893            2.556925         2.562094\n",
+       " 843121  2.705906 -4.839759          893            2.555768         2.562094\n",
+       " 843122  2.707608 -4.839988          893            2.554609         2.562094\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 843876  3.990691 -4.844700          893            0.000071         2.562094\n",
+       " 843877  3.992392 -4.844873          893            0.000064         2.562094\n",
+       " 843878  3.994094 -4.845047          893            0.000058         2.562094\n",
+       " 843879  3.995796 -4.845221          893            0.000051         2.562094\n",
+       " 843880  3.997498 -4.845395          893            0.000044         2.562094\n",
+       " \n",
+       " [763 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 844118  2.700801 -4.839731          894            2.552977         2.558686\n",
+       " 844119  2.702502 -4.839624          894            2.551877         2.558686\n",
+       " 844120  2.704204 -4.839575          894            2.550757         2.558686\n",
+       " 844121  2.705906 -4.839650          894            2.549593         2.558686\n",
+       " 844122  2.707608 -4.839725          894            2.548429         2.558686\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 844876  3.990691 -4.844661          894            0.000071         2.558686\n",
+       " 844877  3.992392 -4.844841          894            0.000065         2.558686\n",
+       " 844878  3.994094 -4.845022          894            0.000058         2.558686\n",
+       " 844879  3.995796 -4.845202          894            0.000051         2.558686\n",
+       " 844880  3.997498 -4.845383          894            0.000044         2.558686\n",
+       " \n",
+       " [763 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 845118  2.700801 -4.840009          895            2.549799         2.551742\n",
+       " 845119  2.702502 -4.840009          895            2.548718         2.551742\n",
+       " 845120  2.704204 -4.840158          895            2.547576         2.551742\n",
+       " 845121  2.705906 -4.840308          895            2.546434         2.551742\n",
+       " 845122  2.707608 -4.840457          895            2.545292         2.551742\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 845876  3.990691 -4.843544          895            0.000069         2.551742\n",
+       " 845877  3.992392 -4.843682          895            0.000062         2.551742\n",
+       " 845878  3.994094 -4.843819          895            0.000055         2.551742\n",
+       " 845879  3.995796 -4.843956          895            0.000048         2.551742\n",
+       " 845880  3.997498 -4.844093          895            0.000041         2.551742\n",
+       " \n",
+       " [763 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 846118  2.700801 -4.839869          896            2.547158         2.550296\n",
+       " 846119  2.702502 -4.840009          896            2.546029         2.550296\n",
+       " 846120  2.704204 -4.840009          896            2.544878         2.550296\n",
+       " 846121  2.705906 -4.840009          896            2.543727         2.550296\n",
+       " 846122  2.707608 -4.839979          896            2.542583         2.550296\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 846876  3.990691 -4.843143          896            0.000069         2.550296\n",
+       " 846877  3.992392 -4.843266          896            0.000062         2.550296\n",
+       " 846878  3.994094 -4.843389          896            0.000055         2.550296\n",
+       " 846879  3.995796 -4.843511          896            0.000049         2.550296\n",
+       " 846880  3.997498 -4.843634          896            0.000042         2.550296\n",
+       " \n",
+       " [763 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 847118  2.700801 -4.839817          897            2.544437         2.547242\n",
+       " 847119  2.702502 -4.839967          897            2.543308         2.547242\n",
+       " 847120  2.704204 -4.840117          897            2.542179         2.547242\n",
+       " 847121  2.705906 -4.840238          897            2.541047         2.547242\n",
+       " 847122  2.707608 -4.840238          897            2.539901         2.547242\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 847876  3.990691 -4.842586          897            0.000069         2.547242\n",
+       " 847877  3.992392 -4.842680          897            0.000062         2.547242\n",
+       " 847878  3.994094 -4.842773          897            0.000055         2.547242\n",
+       " 847879  3.995796 -4.842867          897            0.000048         2.547242\n",
+       " 847880  3.997498 -4.842960          897            0.000041         2.547242\n",
+       " \n",
+       " [763 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 848118  2.700801 -4.839943          898            2.542605         2.545206\n",
+       " 848119  2.702502 -4.839801          898            2.541464         2.545206\n",
+       " 848120  2.704204 -4.839975          898            2.540330         2.545206\n",
+       " 848121  2.705906 -4.840204          898            2.539198         2.545206\n",
+       " 848122  2.707608 -4.840432          898            2.538066         2.545206\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 848876  3.990691 -4.846319          898            0.000068         2.545206\n",
+       " 848877  3.992392 -4.846565          898            0.000061         2.545206\n",
+       " 848878  3.994094 -4.846811          898            0.000054         2.545206\n",
+       " 848879  3.995796 -4.847057          898            0.000047         2.545206\n",
+       " 848880  3.997498 -4.847302          898            0.000041         2.545206\n",
+       " \n",
+       " [763 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 849118  2.700801 -4.839785          899            2.538857         2.541771\n",
+       " 849119  2.702502 -4.839859          899            2.537714         2.541771\n",
+       " 849120  2.704204 -4.839933          899            2.536572         2.541771\n",
+       " 849121  2.705906 -4.840007          899            2.535429         2.541771\n",
+       " 849122  2.707608 -4.840009          899            2.534257         2.541771\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 849876  3.990691 -4.844387          899            0.000068         2.541771\n",
+       " 849877  3.992392 -4.844544          899            0.000061         2.541771\n",
+       " 849878  3.994094 -4.844702          899            0.000054         2.541771\n",
+       " 849879  3.995796 -4.844860          899            0.000048         2.541771\n",
+       " 849880  3.997498 -4.845018          899            0.000041         2.541771\n",
+       " \n",
+       " [763 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 850118  2.700801 -4.839910          900            2.541092         2.544509\n",
+       " 850119  2.702502 -4.839809          900            2.539924         2.544509\n",
+       " 850120  2.704204 -4.839883          900            2.538785         2.544509\n",
+       " 850121  2.705906 -4.839957          900            2.537646         2.544509\n",
+       " 850122  2.707608 -4.840031          900            2.536500         2.544509\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 850876  3.990691 -4.843637          900            0.000072         2.544509\n",
+       " 850877  3.992392 -4.843789          900            0.000065         2.544509\n",
+       " 850878  3.994094 -4.843940          900            0.000058         2.544509\n",
+       " 850879  3.995796 -4.844092          900            0.000052         2.544509\n",
+       " 850880  3.997498 -4.844244          900            0.000045         2.544509\n",
+       " \n",
+       " [763 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 851118  2.700801 -4.840089          901            2.532614         2.535517\n",
+       " 851119  2.702502 -4.839952          901            2.531481         2.535517\n",
+       " 851120  2.704204 -4.839874          901            2.530331         2.535517\n",
+       " 851121  2.705906 -4.839797          901            2.529182         2.535517\n",
+       " 851122  2.707608 -4.839721          901            2.528010         2.535517\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 851876  3.990691 -4.845423          901            0.000067         2.535517\n",
+       " 851877  3.992392 -4.845609          901            0.000061         2.535517\n",
+       " 851878  3.994094 -4.845794          901            0.000054         2.535517\n",
+       " 851879  3.995796 -4.845980          901            0.000047         2.535517\n",
+       " 851880  3.997498 -4.846166          901            0.000041         2.535517\n",
+       " \n",
+       " [763 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 852118  2.700801 -4.839551          902            2.536471         2.539354\n",
+       " 852119  2.702502 -4.839561          902            2.535347         2.539354\n",
+       " 852120  2.704204 -4.839636          902            2.534187         2.539354\n",
+       " 852121  2.705906 -4.839711          902            2.533027         2.539354\n",
+       " 852122  2.707608 -4.839786          902            2.531868         2.539354\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 852876  3.990691 -4.845302          902            0.000070         2.539354\n",
+       " 852877  3.992392 -4.845504          902            0.000063         2.539354\n",
+       " 852878  3.994094 -4.845706          902            0.000056         2.539354\n",
+       " 852879  3.995796 -4.845908          902            0.000049         2.539354\n",
+       " 852880  3.997498 -4.846109          902            0.000042         2.539354\n",
+       " \n",
+       " [763 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 853118  2.700801 -4.840081          903            2.532314         2.532871\n",
+       " 853119  2.702502 -4.840236          903            2.531187         2.532871\n",
+       " 853120  2.704204 -4.840238          903            2.530028         2.532871\n",
+       " 853121  2.705906 -4.840238          903            2.528868         2.532871\n",
+       " 853122  2.707608 -4.840238          903            2.527708         2.532871\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 853876  3.990691 -4.843974          903            0.000069         2.532871\n",
+       " 853877  3.992392 -4.844118          903            0.000062         2.532871\n",
+       " 853878  3.994094 -4.844262          903            0.000055         2.532871\n",
+       " 853879  3.995796 -4.844406          903            0.000048         2.532871\n",
+       " 853880  3.997498 -4.844550          903            0.000041         2.532871\n",
+       " \n",
+       " [763 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 854118  2.700801 -4.840353          904            2.528797         2.532722\n",
+       " 854119  2.702502 -4.840158          904            2.527690         2.532722\n",
+       " 854120  2.704204 -4.840006          904            2.526562         2.532722\n",
+       " 854121  2.705906 -4.839853          904            2.525434         2.532722\n",
+       " 854122  2.707608 -4.839780          904            2.524271         2.532722\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 854876  3.990691 -4.842988          904            0.000068         2.532722\n",
+       " 854877  3.992392 -4.843096          904            0.000061         2.532722\n",
+       " 854878  3.994094 -4.843204          904            0.000055         2.532722\n",
+       " 854879  3.995796 -4.843311          904            0.000048         2.532722\n",
+       " 854880  3.997498 -4.843419          904            0.000041         2.532722\n",
+       " \n",
+       " [763 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 855118  2.700801 -4.839749          905            2.526286         2.528643\n",
+       " 855119  2.702502 -4.839675          905            2.525156         2.528643\n",
+       " 855120  2.704204 -4.839601          905            2.524026         2.528643\n",
+       " 855121  2.705906 -4.839577          905            2.522880         2.528643\n",
+       " 855122  2.707608 -4.839654          905            2.521698         2.528643\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 855876  3.990691 -4.844194          905            0.000068         2.528643\n",
+       " 855877  3.992392 -4.844345          905            0.000061         2.528643\n",
+       " 855878  3.994094 -4.844496          905            0.000054         2.528643\n",
+       " 855879  3.995796 -4.844646          905            0.000047         2.528643\n",
+       " 855880  3.997498 -4.844797          905            0.000041         2.528643\n",
+       " \n",
+       " [763 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 856118  2.700801 -4.839758          906            2.523774         2.525755\n",
+       " 856119  2.702502 -4.839977          906            2.522631         2.525755\n",
+       " 856120  2.704204 -4.839903          906            2.521510         2.525755\n",
+       " 856121  2.705906 -4.839829          906            2.520389         2.525755\n",
+       " 856122  2.707608 -4.839832          906            2.519241         2.525755\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 856875  3.988989 -4.844004          906            0.000073         2.525755\n",
+       " 856876  3.990691 -4.844170          906            0.000066         2.525755\n",
+       " 856877  3.992392 -4.844335          906            0.000059         2.525755\n",
+       " 856878  3.994094 -4.844501          906            0.000053         2.525755\n",
+       " 856879  3.995796 -4.844666          906            0.000046         2.525755\n",
+       " \n",
+       " [762 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 857118  2.700801 -4.840009          907            2.522963         2.525079\n",
+       " 857119  2.702502 -4.840009          907            2.521824         2.525079\n",
+       " 857120  2.704204 -4.840009          907            2.520677         2.525079\n",
+       " 857121  2.705906 -4.840009          907            2.519531         2.525079\n",
+       " 857122  2.707608 -4.840072          907            2.518373         2.525079\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 857876  3.990691 -4.845209          907            0.000067         2.525079\n",
+       " 857877  3.992392 -4.845395          907            0.000060         2.525079\n",
+       " 857878  3.994094 -4.845581          907            0.000053         2.525079\n",
+       " 857879  3.995796 -4.845767          907            0.000047         2.525079\n",
+       " 857880  3.997498 -4.845953          907            0.000040         2.525079\n",
+       " \n",
+       " [763 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 858118  2.700801 -4.840174          908            2.521021         2.524024\n",
+       " 858119  2.702502 -4.840036          908            2.519894         2.524024\n",
+       " 858120  2.704204 -4.840009          908            2.518738         2.524024\n",
+       " 858121  2.705906 -4.840009          908            2.517574         2.524024\n",
+       " 858122  2.707608 -4.840009          908            2.516410         2.524024\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 858876  3.990691 -4.845605          908            0.000068         2.524024\n",
+       " 858877  3.992392 -4.845798          908            0.000061         2.524024\n",
+       " 858878  3.994094 -4.845991          908            0.000055         2.524024\n",
+       " 858879  3.995796 -4.846184          908            0.000048         2.524024\n",
+       " 858880  3.997498 -4.846376          908            0.000041         2.524024\n",
+       " \n",
+       " [763 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 859118  2.700801 -4.840200          909            2.519011         2.521242\n",
+       " 859119  2.702502 -4.840467          909            2.517863         2.521242\n",
+       " 859120  2.704204 -4.840467          909            2.516699         2.521242\n",
+       " 859121  2.705906 -4.840467          909            2.515536         2.521242\n",
+       " 859122  2.707608 -4.840312          909            2.514359         2.521242\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 859876  3.990691 -4.844625          909            0.000067         2.521242\n",
+       " 859877  3.992392 -4.844782          909            0.000061         2.521242\n",
+       " 859878  3.994094 -4.844940          909            0.000054         2.521242\n",
+       " 859879  3.995796 -4.845097          909            0.000047         2.521242\n",
+       " 859880  3.997498 -4.845254          909            0.000041         2.521242\n",
+       " \n",
+       " [763 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 860118  2.700801 -4.839979          910            2.514446          2.51834\n",
+       " 860119  2.702502 -4.840208          910            2.513326          2.51834\n",
+       " 860120  2.704204 -4.840131          910            2.512177          2.51834\n",
+       " 860121  2.705906 -4.840053          910            2.511028          2.51834\n",
+       " 860122  2.707608 -4.839977          910            2.509860          2.51834\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 860875  3.988989 -4.844485          910            0.000073          2.51834\n",
+       " 860876  3.990691 -4.844643          910            0.000067          2.51834\n",
+       " 860877  3.992392 -4.844801          910            0.000060          2.51834\n",
+       " 860878  3.994094 -4.844959          910            0.000053          2.51834\n",
+       " 860879  3.995796 -4.845117          910            0.000046          2.51834\n",
+       " \n",
+       " [762 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 861118  2.700801 -4.840236          911            2.511925         2.514728\n",
+       " 861119  2.702502 -4.840428          911            2.510765         2.514728\n",
+       " 861120  2.704204 -4.840354          911            2.509639         2.514728\n",
+       " 861121  2.705906 -4.840280          911            2.508513         2.514728\n",
+       " 861122  2.707608 -4.840142          911            2.507369         2.514728\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 861875  3.988989 -4.844078          911            0.000073         2.514728\n",
+       " 861876  3.990691 -4.844228          911            0.000066         2.514728\n",
+       " 861877  3.992392 -4.844379          911            0.000059         2.514728\n",
+       " 861878  3.994094 -4.844530          911            0.000053         2.514728\n",
+       " 861879  3.995796 -4.844680          911            0.000046         2.514728\n",
+       " \n",
+       " [762 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 862118  2.700801 -4.840463          912            2.509682         2.512599\n",
+       " 862119  2.702502 -4.840244          912            2.508568         2.512599\n",
+       " 862120  2.704204 -4.840025          912            2.507454         2.512599\n",
+       " 862121  2.705906 -4.839807          912            2.506340         2.512599\n",
+       " 862122  2.707608 -4.839780          912            2.505162         2.512599\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 862875  3.988989 -4.845176          912            0.000073         2.512599\n",
+       " 862876  3.990691 -4.845385          912            0.000066         2.512599\n",
+       " 862877  3.992392 -4.845593          912            0.000059         2.512599\n",
+       " 862878  3.994094 -4.845802          912            0.000052         2.512599\n",
+       " 862879  3.995796 -4.846010          912            0.000046         2.512599\n",
+       " \n",
+       " [762 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 863118  2.700801 -4.839554          913            2.505809         2.508703\n",
+       " 863119  2.702502 -4.839706          913            2.504641         2.508703\n",
+       " 863120  2.704204 -4.839859          913            2.503473         2.508703\n",
+       " 863121  2.705906 -4.840009          913            2.502305         2.508703\n",
+       " 863122  2.707608 -4.840009          913            2.501148         2.508703\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 863875  3.988989 -4.844408          913            0.000072         2.508703\n",
+       " 863876  3.990691 -4.844586          913            0.000066         2.508703\n",
+       " 863877  3.992392 -4.844764          913            0.000059         2.508703\n",
+       " 863878  3.994094 -4.844943          913            0.000052         2.508703\n",
+       " 863879  3.995796 -4.845121          913            0.000045         2.508703\n",
+       " \n",
+       " [762 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 864118  2.700801 -4.839589          914            2.503598         2.506905\n",
+       " 864119  2.702502 -4.839670          914            2.502504         2.506905\n",
+       " 864120  2.704204 -4.839751          914            2.501409         2.506905\n",
+       " 864121  2.705906 -4.839828          914            2.500287         2.506905\n",
+       " 864122  2.707608 -4.839903          914            2.499149         2.506905\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 864875  3.988989 -4.844858          914            0.000071         2.506905\n",
+       " 864876  3.990691 -4.845045          914            0.000065         2.506905\n",
+       " 864877  3.992392 -4.845232          914            0.000058         2.506905\n",
+       " 864878  3.994094 -4.845418          914            0.000051         2.506905\n",
+       " 864879  3.995796 -4.845605          914            0.000044         2.506905\n",
+       " \n",
+       " [762 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 865118  2.700801 -4.839974          915            2.501566         2.503782\n",
+       " 865119  2.702502 -4.839898          915            2.500438         2.503782\n",
+       " 865120  2.704204 -4.839821          915            2.499310         2.503782\n",
+       " 865121  2.705906 -4.839816          915            2.498172         2.503782\n",
+       " 865122  2.707608 -4.839892          915            2.497022         2.503782\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 865875  3.988989 -4.843127          915            0.000072         2.503782\n",
+       " 865876  3.990691 -4.843241          915            0.000065         2.503782\n",
+       " 865877  3.992392 -4.843355          915            0.000058         2.503782\n",
+       " 865878  3.994094 -4.843470          915            0.000052         2.503782\n",
+       " 865879  3.995796 -4.843584          915            0.000045         2.503782\n",
+       " \n",
+       " [762 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 866118  2.700801 -4.840201          916            2.498872         2.501537\n",
+       " 866119  2.702502 -4.840121          916            2.497734         2.501537\n",
+       " 866120  2.704204 -4.840041          916            2.496595         2.501537\n",
+       " 866121  2.705906 -4.840009          916            2.495442         2.501537\n",
+       " 866122  2.707608 -4.840009          916            2.494278         2.501537\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 866875  3.988989 -4.843717          916            0.000071         2.501537\n",
+       " 866876  3.990691 -4.843853          916            0.000065         2.501537\n",
+       " 866877  3.992392 -4.843988          916            0.000058         2.501537\n",
+       " 866878  3.994094 -4.844124          916            0.000051         2.501537\n",
+       " 866879  3.995796 -4.844260          916            0.000045         2.501537\n",
+       " \n",
+       " [762 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 867118  2.700801 -4.840207          917            2.495433         2.498587\n",
+       " 867119  2.702502 -4.840133          917            2.494308         2.498587\n",
+       " 867120  2.704204 -4.840059          917            2.493182         2.498587\n",
+       " 867121  2.705906 -4.840009          917            2.492047         2.498587\n",
+       " 867122  2.707608 -4.840009          917            2.490891         2.498587\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 867875  3.988989 -4.844672          917            0.000070         2.498587\n",
+       " 867876  3.990691 -4.844859          917            0.000063         2.498587\n",
+       " 867877  3.992392 -4.845045          917            0.000056         2.498587\n",
+       " 867878  3.994094 -4.845232          917            0.000050         2.498587\n",
+       " 867879  3.995796 -4.845418          917            0.000043         2.498587\n",
+       " \n",
+       " [762 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 868118  2.700801 -4.840274          918            2.491521         2.494714\n",
+       " 868119  2.702502 -4.840352          918            2.490417         2.494714\n",
+       " 868120  2.704204 -4.840429          918            2.489313         2.494714\n",
+       " 868121  2.705906 -4.840391          918            2.488174         2.494714\n",
+       " 868122  2.707608 -4.840240          918            2.487001         2.494714\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 868875  3.988989 -4.844574          918            0.000070         2.494714\n",
+       " 868876  3.990691 -4.844731          918            0.000063         2.494714\n",
+       " 868877  3.992392 -4.844888          918            0.000056         2.494714\n",
+       " 868878  3.994094 -4.845045          918            0.000049         2.494714\n",
+       " 868879  3.995796 -4.845202          918            0.000043         2.494714\n",
+       " \n",
+       " [762 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 869118  2.700801 -4.839725          919            2.489741         2.492641\n",
+       " 869119  2.702502 -4.839606          919            2.488653         2.492641\n",
+       " 869120  2.704204 -4.839673          919            2.487526         2.492641\n",
+       " 869121  2.705906 -4.839898          919            2.486366         2.492641\n",
+       " 869122  2.707608 -4.840123          919            2.485207         2.492641\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 869875  3.988989 -4.845073          919            0.000071         2.492641\n",
+       " 869876  3.990691 -4.845267          919            0.000064         2.492641\n",
+       " 869877  3.992392 -4.845460          919            0.000057         2.492641\n",
+       " 869878  3.994094 -4.845653          919            0.000050         2.492641\n",
+       " 869879  3.995796 -4.845847          919            0.000044         2.492641\n",
+       " \n",
+       " [762 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 870118  2.700801 -4.840238          920            2.483986         2.488067\n",
+       " 870119  2.702502 -4.840238          920            2.482897         2.488067\n",
+       " 870120  2.704204 -4.840238          920            2.481808         2.488067\n",
+       " 870121  2.705906 -4.840097          920            2.480651         2.488067\n",
+       " 870122  2.707608 -4.839942          920            2.479488         2.488067\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 870875  3.988989 -4.844973          920            0.000069         2.488067\n",
+       " 870876  3.990691 -4.845145          920            0.000063         2.488067\n",
+       " 870877  3.992392 -4.845317          920            0.000056         2.488067\n",
+       " 870878  3.994094 -4.845489          920            0.000049         2.488067\n",
+       " 870879  3.995796 -4.845661          920            0.000042         2.488067\n",
+       " \n",
+       " [762 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 871118  2.700801 -4.839861          921            2.478975          2.48328\n",
+       " 871119  2.702502 -4.840034          921            2.477837          2.48328\n",
+       " 871120  2.704204 -4.840207          921            2.476698          2.48328\n",
+       " 871121  2.705906 -4.839988          921            2.475539          2.48328\n",
+       " 871122  2.707608 -4.839683          921            2.474375          2.48328\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 871875  3.988989 -4.843342          921            0.000069          2.48328\n",
+       " 871876  3.990691 -4.843472          921            0.000062          2.48328\n",
+       " 871877  3.992392 -4.843601          921            0.000055          2.48328\n",
+       " 871878  3.994094 -4.843730          921            0.000049          2.48328\n",
+       " 871879  3.995796 -4.843859          921            0.000042          2.48328\n",
+       " \n",
+       " [762 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 872118  2.700801 -4.839818          922            2.474046         2.477777\n",
+       " 872119  2.702502 -4.839899          922            2.472918         2.477777\n",
+       " 872120  2.704204 -4.839980          922            2.471790         2.477777\n",
+       " 872121  2.705906 -4.840009          922            2.470658         2.477777\n",
+       " 872122  2.707608 -4.840009          922            2.469523         2.477777\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 872875  3.988989 -4.845103          922            0.000070         2.477777\n",
+       " 872876  3.990691 -4.845295          922            0.000063         2.477777\n",
+       " 872877  3.992392 -4.845488          922            0.000056         2.477777\n",
+       " 872878  3.994094 -4.845680          922            0.000049         2.477777\n",
+       " 872879  3.995796 -4.845873          922            0.000043         2.477777\n",
+       " \n",
+       " [762 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 873118  2.700801 -4.839812          923            2.469587         2.473305\n",
+       " 873119  2.702502 -4.839887          923            2.468445         2.473305\n",
+       " 873120  2.704204 -4.839962          923            2.467302         2.473305\n",
+       " 873121  2.705906 -4.839981          923            2.466161         2.473305\n",
+       " 873122  2.707608 -4.839905          923            2.465019         2.473305\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 873875  3.988989 -4.843931          923            0.000069         2.473305\n",
+       " 873876  3.990691 -4.844081          923            0.000062         2.473305\n",
+       " 873877  3.992392 -4.844232          923            0.000056         2.473305\n",
+       " 873878  3.994094 -4.844382          923            0.000049         2.473305\n",
+       " 873879  3.995796 -4.844532          923            0.000042         2.473305\n",
+       " \n",
+       " [762 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 874118  2.700801 -4.839891          924            2.465858          2.46901\n",
+       " 874119  2.702502 -4.839946          924            2.464729          2.46901\n",
+       " 874120  2.704204 -4.839871          924            2.463604          2.46901\n",
+       " 874121  2.705906 -4.839796          924            2.462480          2.46901\n",
+       " 874122  2.707608 -4.839839          924            2.461351          2.46901\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 874875  3.988989 -4.843191          924            0.000068          2.46901\n",
+       " 874876  3.990691 -4.843306          924            0.000061          2.46901\n",
+       " 874877  3.992392 -4.843421          924            0.000054          2.46901\n",
+       " 874878  3.994094 -4.843535          924            0.000048          2.46901\n",
+       " 874879  3.995796 -4.843650          924            0.000041          2.46901\n",
+       " \n",
+       " [762 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 875118  2.700801 -4.839780          925            2.462680         2.465862\n",
+       " 875119  2.702502 -4.839780          925            2.461538         2.465862\n",
+       " 875120  2.704204 -4.839780          925            2.460396         2.465862\n",
+       " 875121  2.705906 -4.839780          925            2.459254         2.465862\n",
+       " 875122  2.707608 -4.839852          925            2.458111         2.465862\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 875874  3.987287 -4.843296          925            0.000073         2.465862\n",
+       " 875875  3.988989 -4.843418          925            0.000066         2.465862\n",
+       " 875876  3.990691 -4.843539          925            0.000060         2.465862\n",
+       " 875877  3.992392 -4.843661          925            0.000053         2.465862\n",
+       " 875878  3.994094 -4.843783          925            0.000046         2.465862\n",
+       " \n",
+       " [761 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 876118  2.700801 -4.839595          926            2.460083         2.462557\n",
+       " 876119  2.702502 -4.839690          926            2.458966         2.462557\n",
+       " 876120  2.704204 -4.839777          926            2.457849         2.462557\n",
+       " 876121  2.705906 -4.839701          926            2.456708         2.462557\n",
+       " 876122  2.707608 -4.839624          926            2.455567         2.462557\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 876874  3.987287 -4.844044          926            0.000073         2.462557\n",
+       " 876875  3.988989 -4.844201          926            0.000066         2.462557\n",
+       " 876876  3.990691 -4.844358          926            0.000059         2.462557\n",
+       " 876877  3.992392 -4.844515          926            0.000053         2.462557\n",
+       " 876878  3.994094 -4.844672          926            0.000046         2.462557\n",
+       " \n",
+       " [761 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 877118  2.700801 -4.840292          927            2.457636         2.460474\n",
+       " 877119  2.702502 -4.840408          927            2.456491         2.460474\n",
+       " 877120  2.704204 -4.840393          927            2.455345         2.460474\n",
+       " 877121  2.705906 -4.840243          927            2.454199         2.460474\n",
+       " 877122  2.707608 -4.840093          927            2.453052         2.460474\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 877874  3.987287 -4.844432          927            0.000073         2.460474\n",
+       " 877875  3.988989 -4.844604          927            0.000066         2.460474\n",
+       " 877876  3.990691 -4.844775          927            0.000059         2.460474\n",
+       " 877877  3.992392 -4.844946          927            0.000053         2.460474\n",
+       " 877878  3.994094 -4.845117          927            0.000046         2.460474\n",
+       " \n",
+       " [761 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 878118  2.700801 -4.839963          928            2.454389         2.457271\n",
+       " 878119  2.702502 -4.839865          928            2.453259         2.457271\n",
+       " 878120  2.704204 -4.839790          928            2.452127         2.457271\n",
+       " 878121  2.705906 -4.839866          928            2.450985         2.457271\n",
+       " 878122  2.707608 -4.839941          928            2.449843         2.457271\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 878874  3.987287 -4.843503          928            0.000072         2.457271\n",
+       " 878875  3.988989 -4.843630          928            0.000066         2.457271\n",
+       " 878876  3.990691 -4.843758          928            0.000059         2.457271\n",
+       " 878877  3.992392 -4.843885          928            0.000052         2.457271\n",
+       " 878878  3.994094 -4.844012          928            0.000046         2.457271\n",
+       " \n",
+       " [761 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 879118  2.700801 -4.840238          929            2.449880         2.453565\n",
+       " 879119  2.702502 -4.840202          929            2.448666         2.453565\n",
+       " 879120  2.704204 -4.839906          929            2.447571         2.453565\n",
+       " 879121  2.705906 -4.839611          929            2.446476         2.453565\n",
+       " 879122  2.707608 -4.839327          929            2.445380         2.453565\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 879874  3.987287 -4.844119          929            0.000071         2.453565\n",
+       " 879875  3.988989 -4.844268          929            0.000064         2.453565\n",
+       " 879876  3.990691 -4.844416          929            0.000058         2.453565\n",
+       " 879877  3.992392 -4.844564          929            0.000051         2.453565\n",
+       " 879878  3.994094 -4.844713          929            0.000044         2.453565\n",
+       " \n",
+       " [761 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 880118  2.700801 -4.839870          930            2.450258         2.451434\n",
+       " 880119  2.702502 -4.840063          930            2.449178         2.451434\n",
+       " 880120  2.704204 -4.840224          930            2.448091         2.451434\n",
+       " 880121  2.705906 -4.840069          930            2.446946         2.451434\n",
+       " 880122  2.707608 -4.839915          930            2.445801         2.451434\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 880874  3.987287 -4.843312          930            0.000070         2.451434\n",
+       " 880875  3.988989 -4.843440          930            0.000064         2.451434\n",
+       " 880876  3.990691 -4.843568          930            0.000057         2.451434\n",
+       " 880877  3.992392 -4.843696          930            0.000050         2.451434\n",
+       " 880878  3.994094 -4.843823          930            0.000044         2.451434\n",
+       " \n",
+       " [761 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 881118  2.700801 -4.839855          931            2.447678         2.450449\n",
+       " 881119  2.702502 -4.840014          931            2.446601         2.450449\n",
+       " 881120  2.704204 -4.840174          931            2.445523         2.450449\n",
+       " 881121  2.705906 -4.840192          931            2.444397         2.450449\n",
+       " 881122  2.707608 -4.840115          931            2.443238         2.450449\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 881874  3.987287 -4.844686          931            0.000069         2.450449\n",
+       " 881875  3.988989 -4.844871          931            0.000063         2.450449\n",
+       " 881876  3.990691 -4.845055          931            0.000056         2.450449\n",
+       " 881877  3.992392 -4.845240          931            0.000049         2.450449\n",
+       " 881878  3.994094 -4.845425          931            0.000043         2.450449\n",
+       " \n",
+       " [761 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 882118  2.700801 -4.839899          932            2.445459         2.447137\n",
+       " 882119  2.702502 -4.840009          932            2.444346         2.447137\n",
+       " 882120  2.704204 -4.840009          932            2.443232         2.447137\n",
+       " 882121  2.705906 -4.840009          932            2.442117         2.447137\n",
+       " 882122  2.707608 -4.840052          932            2.440998         2.447137\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 882874  3.987287 -4.844638          932            0.000070         2.447137\n",
+       " 882875  3.988989 -4.844828          932            0.000063         2.447137\n",
+       " 882876  3.990691 -4.845018          932            0.000057         2.447137\n",
+       " 882877  3.992392 -4.845207          932            0.000050         2.447137\n",
+       " 882878  3.994094 -4.845397          932            0.000043         2.447137\n",
+       " \n",
+       " [761 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 883118  2.700801 -4.839890          933            2.443429         2.445368\n",
+       " 883119  2.702502 -4.839824          933            2.442330         2.445368\n",
+       " 883120  2.704204 -4.839900          933            2.441194         2.445368\n",
+       " 883121  2.705906 -4.839976          933            2.440057         2.445368\n",
+       " 883122  2.707608 -4.839967          933            2.438932         2.445368\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 883874  3.987287 -4.845354          933            0.000068         2.445368\n",
+       " 883875  3.988989 -4.845551          933            0.000061         2.445368\n",
+       " 883876  3.990691 -4.845747          933            0.000055         2.445368\n",
+       " 883877  3.992392 -4.845944          933            0.000048         2.445368\n",
+       " 883878  3.994094 -4.846141          933            0.000041         2.445368\n",
+       " \n",
+       " [761 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 884118  2.700801 -4.840009          934            2.441939         2.443375\n",
+       " 884119  2.702502 -4.840009          934            2.440807         2.443375\n",
+       " 884120  2.704204 -4.840009          934            2.439676         2.443375\n",
+       " 884121  2.705906 -4.840009          934            2.438545         2.443375\n",
+       " 884122  2.707608 -4.840009          934            2.437410         2.443375\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 884874  3.987287 -4.843141          934            0.000067         2.443375\n",
+       " 884875  3.988989 -4.843267          934            0.000061         2.443375\n",
+       " 884876  3.990691 -4.843393          934            0.000054         2.443375\n",
+       " 884877  3.992392 -4.843520          934            0.000048         2.443375\n",
+       " 884878  3.994094 -4.843647          934            0.000041         2.443375\n",
+       " \n",
+       " [761 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 885118  2.700801 -4.840004          935            2.440850         2.442601\n",
+       " 885119  2.702502 -4.839928          935            2.439718         2.442601\n",
+       " 885120  2.704204 -4.839852          935            2.438585         2.442601\n",
+       " 885121  2.705906 -4.839785          935            2.437452         2.442601\n",
+       " 885122  2.707608 -4.839859          935            2.436309         2.442601\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 885874  3.987287 -4.843754          935            0.000068         2.442601\n",
+       " 885875  3.988989 -4.843893          935            0.000062         2.442601\n",
+       " 885876  3.990691 -4.844033          935            0.000055         2.442601\n",
+       " 885877  3.992392 -4.844172          935            0.000048         2.442601\n",
+       " 885878  3.994094 -4.844312          935            0.000042         2.442601\n",
+       " \n",
+       " [761 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 886118  2.700801 -4.839841          936            2.439162         2.440124\n",
+       " 886119  2.702502 -4.839920          936            2.438060         2.440124\n",
+       " 886120  2.704204 -4.840070          936            2.436962         2.440124\n",
+       " 886121  2.705906 -4.840220          936            2.435864         2.440124\n",
+       " 886122  2.707608 -4.840043          936            2.434734         2.440124\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 886874  3.987287 -4.843951          936            0.000068         2.440124\n",
+       " 886875  3.988989 -4.844098          936            0.000062         2.440124\n",
+       " 886876  3.990691 -4.844244          936            0.000055         2.440124\n",
+       " 886877  3.992392 -4.844391          936            0.000048         2.440124\n",
+       " 886878  3.994094 -4.844538          936            0.000042         2.440124\n",
+       " \n",
+       " [761 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 887118  2.700801 -4.839862          937            2.435635          2.43967\n",
+       " 887119  2.702502 -4.840038          937            2.434477          2.43967\n",
+       " 887120  2.704204 -4.840214          937            2.433319          2.43967\n",
+       " 887121  2.705906 -4.840174          937            2.432215          2.43967\n",
+       " 887122  2.707608 -4.840100          937            2.431120          2.43967\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 887873  3.985586 -4.844494          937            0.000072          2.43967\n",
+       " 887874  3.987287 -4.844656          937            0.000065          2.43967\n",
+       " 887875  3.988989 -4.844819          937            0.000058          2.43967\n",
+       " 887876  3.990691 -4.844982          937            0.000052          2.43967\n",
+       " 887877  3.992392 -4.845144          937            0.000045          2.43967\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 888118  2.700801 -4.839983          938            2.432764         2.435081\n",
+       " 888119  2.702502 -4.840417          938            2.431640         2.435081\n",
+       " 888120  2.704204 -4.840343          938            2.430511         2.435081\n",
+       " 888121  2.705906 -4.840267          938            2.429382         2.435081\n",
+       " 888122  2.707608 -4.840147          938            2.428245         2.435081\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 888873  3.985586 -4.843477          938            0.000072         2.435081\n",
+       " 888874  3.987287 -4.843611          938            0.000065         2.435081\n",
+       " 888875  3.988989 -4.843744          938            0.000059         2.435081\n",
+       " 888876  3.990691 -4.843878          938            0.000052         2.435081\n",
+       " 888877  3.992392 -4.844011          938            0.000046         2.435081\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 889118  2.700801 -4.839780          939            2.428692          2.43223\n",
+       " 889119  2.702502 -4.839843          939            2.427580          2.43223\n",
+       " 889120  2.704204 -4.839918          939            2.426469          2.43223\n",
+       " 889121  2.705906 -4.839993          939            2.425357          2.43223\n",
+       " 889122  2.707608 -4.840069          939            2.424240          2.43223\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 889873  3.985586 -4.844870          939            0.000072          2.43223\n",
+       " 889874  3.987287 -4.845045          939            0.000066          2.43223\n",
+       " 889875  3.988989 -4.845219          939            0.000059          2.43223\n",
+       " 889876  3.990691 -4.845394          939            0.000052          2.43223\n",
+       " 889877  3.992392 -4.845569          939            0.000046          2.43223\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 890118  2.700801 -4.839780          940            2.426669         2.428237\n",
+       " 890119  2.702502 -4.839780          940            2.425544         2.428237\n",
+       " 890120  2.704204 -4.839780          940            2.424418         2.428237\n",
+       " 890121  2.705906 -4.839836          940            2.423301         2.428237\n",
+       " 890122  2.707608 -4.839912          940            2.422186         2.428237\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 890873  3.985586 -4.845537          940            0.000070         2.428237\n",
+       " 890874  3.987287 -4.845726          940            0.000064         2.428237\n",
+       " 890875  3.988989 -4.845915          940            0.000057         2.428237\n",
+       " 890876  3.990691 -4.846104          940            0.000051         2.428237\n",
+       " 890877  3.992392 -4.846293          940            0.000044         2.428237\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 891118  2.700801 -4.840238          941            2.425089         2.427437\n",
+       " 891119  2.702502 -4.840238          941            2.423960         2.427437\n",
+       " 891120  2.704204 -4.840238          941            2.422831         2.427437\n",
+       " 891121  2.705906 -4.840238          941            2.421712         2.427437\n",
+       " 891122  2.707608 -4.840238          941            2.420614         2.427437\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 891873  3.985586 -4.845489          941            0.000071         2.427437\n",
+       " 891874  3.987287 -4.845685          941            0.000064         2.427437\n",
+       " 891875  3.988989 -4.845881          941            0.000058         2.427437\n",
+       " 891876  3.990691 -4.846076          941            0.000051         2.427437\n",
+       " 891877  3.992392 -4.846272          941            0.000045         2.427437\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 892118  2.700801 -4.840238          942            2.423581         2.425998\n",
+       " 892119  2.702502 -4.840238          942            2.422434         2.425998\n",
+       " 892120  2.704204 -4.840089          942            2.421289         2.425998\n",
+       " 892121  2.705906 -4.839867          942            2.420146         2.425998\n",
+       " 892122  2.707608 -4.839645          942            2.419003         2.425998\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 892873  3.985586 -4.841975          942            0.000070         2.425998\n",
+       " 892874  3.987287 -4.842045          942            0.000063         2.425998\n",
+       " 892875  3.988989 -4.842115          942            0.000057         2.425998\n",
+       " 892876  3.990691 -4.842185          942            0.000050         2.425998\n",
+       " 892877  3.992392 -4.842255          942            0.000044         2.425998\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 893118  2.700801 -4.839972          943            2.419167         2.423231\n",
+       " 893119  2.702502 -4.839890          943            2.418038         2.423231\n",
+       " 893120  2.704204 -4.839809          943            2.416910         2.423231\n",
+       " 893121  2.705906 -4.839780          943            2.415779         2.423231\n",
+       " 893122  2.707608 -4.839780          943            2.414645         2.423231\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 893873  3.985586 -4.844135          943            0.000070         2.423231\n",
+       " 893874  3.987287 -4.844281          943            0.000064         2.423231\n",
+       " 893875  3.988989 -4.844427          943            0.000057         2.423231\n",
+       " 893876  3.990691 -4.844573          943            0.000051         2.423231\n",
+       " 893877  3.992392 -4.844719          943            0.000044         2.423231\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 894118  2.700801 -4.839780          944            2.415843         2.419368\n",
+       " 894119  2.702502 -4.839780          944            2.414710         2.419368\n",
+       " 894120  2.704204 -4.839814          944            2.413572         2.419368\n",
+       " 894121  2.705906 -4.839964          944            2.412421         2.419368\n",
+       " 894122  2.707608 -4.840114          944            2.411270         2.419368\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 894873  3.985586 -4.844057          944            0.000069         2.419368\n",
+       " 894874  3.987287 -4.844175          944            0.000063         2.419368\n",
+       " 894875  3.988989 -4.844293          944            0.000056         2.419368\n",
+       " 894876  3.990691 -4.844411          944            0.000049         2.419368\n",
+       " 894877  3.992392 -4.844530          944            0.000043         2.419368\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 895118  2.700801 -4.840178          945            2.412604         2.415633\n",
+       " 895119  2.702502 -4.840051          945            2.411502         2.415633\n",
+       " 895120  2.704204 -4.840009          945            2.410377         2.415633\n",
+       " 895121  2.705906 -4.840009          945            2.409240         2.415633\n",
+       " 895122  2.707608 -4.840009          945            2.408103         2.415633\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 895873  3.985586 -4.845415          945            0.000069         2.415633\n",
+       " 895874  3.987287 -4.845589          945            0.000062         2.415633\n",
+       " 895875  3.988989 -4.845764          945            0.000056         2.415633\n",
+       " 895876  3.990691 -4.845938          945            0.000049         2.415633\n",
+       " 895877  3.992392 -4.846113          945            0.000043         2.415633\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 896118  2.700801 -4.840189          946            2.409061         2.413052\n",
+       " 896119  2.702502 -4.840082          946            2.407943         2.413052\n",
+       " 896120  2.704204 -4.839986          946            2.406814         2.413052\n",
+       " 896121  2.705906 -4.839911          946            2.405663         2.413052\n",
+       " 896122  2.707608 -4.839836          946            2.404512         2.413052\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 896873  3.985586 -4.844747          946            0.000069         2.413052\n",
+       " 896874  3.987287 -4.844914          946            0.000063         2.413052\n",
+       " 896875  3.988989 -4.845081          946            0.000056         2.413052\n",
+       " 896876  3.990691 -4.845248          946            0.000050         2.413052\n",
+       " 896877  3.992392 -4.845415          946            0.000043         2.413052\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 897118  2.700801 -4.839551          947            2.406519         2.409671\n",
+       " 897119  2.702502 -4.839610          947            2.405386         2.409671\n",
+       " 897120  2.704204 -4.839760          947            2.404279         2.409671\n",
+       " 897121  2.705906 -4.839911          947            2.403172         2.409671\n",
+       " 897122  2.707608 -4.840009          947            2.402035         2.409671\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 897873  3.985586 -4.843541          947            0.000069         2.409671\n",
+       " 897874  3.987287 -4.843674          947            0.000062         2.409671\n",
+       " 897875  3.988989 -4.843806          947            0.000056         2.409671\n",
+       " 897876  3.990691 -4.843939          947            0.000049         2.409671\n",
+       " 897877  3.992392 -4.844071          947            0.000043         2.409671\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 898118  2.700801 -4.839641          948            2.405605         2.407508\n",
+       " 898119  2.702502 -4.839834          948            2.404485         2.407508\n",
+       " 898120  2.704204 -4.840003          948            2.403362         2.407508\n",
+       " 898121  2.705906 -4.839926          948            2.402211         2.407508\n",
+       " 898122  2.707608 -4.839850          948            2.401061         2.407508\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 898873  3.985586 -4.845489          948            0.000069         2.407508\n",
+       " 898874  3.987287 -4.845698          948            0.000062         2.407508\n",
+       " 898875  3.988989 -4.845908          948            0.000056         2.407508\n",
+       " 898876  3.990691 -4.846117          948            0.000049         2.407508\n",
+       " 898877  3.992392 -4.846327          948            0.000043         2.407508\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 899118  2.700801 -4.839921          949            2.404707         2.406363\n",
+       " 899119  2.702502 -4.839800          949            2.403568         2.406363\n",
+       " 899120  2.704204 -4.839876          949            2.402445         2.406363\n",
+       " 899121  2.705906 -4.839952          949            2.401321         2.406363\n",
+       " 899122  2.707608 -4.839990          949            2.400185         2.406363\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 899873  3.985586 -4.844168          949            0.000069         2.406363\n",
+       " 899874  3.987287 -4.844314          949            0.000062         2.406363\n",
+       " 899875  3.988989 -4.844460          949            0.000056         2.406363\n",
+       " 899876  3.990691 -4.844606          949            0.000049         2.406363\n",
+       " 899877  3.992392 -4.844752          949            0.000043         2.406363\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 900118  2.700801 -4.840009          950            2.402813         2.405402\n",
+       " 900119  2.702502 -4.840009          950            2.401720         2.405402\n",
+       " 900120  2.704204 -4.840009          950            2.400627         2.405402\n",
+       " 900121  2.705906 -4.840009          950            2.399496         2.405402\n",
+       " 900122  2.707608 -4.840009          950            2.398360         2.405402\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 900873  3.985586 -4.843208          950            0.000069         2.405402\n",
+       " 900874  3.987287 -4.843312          950            0.000062         2.405402\n",
+       " 900875  3.988989 -4.843417          950            0.000056         2.405402\n",
+       " 900876  3.990691 -4.843521          950            0.000049         2.405402\n",
+       " 900877  3.992392 -4.843626          950            0.000043         2.405402\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 901118  2.700801 -4.839722          951            2.402332         2.404271\n",
+       " 901119  2.702502 -4.839598          951            2.401228         2.404271\n",
+       " 901120  2.704204 -4.839598          951            2.400102         2.404271\n",
+       " 901121  2.705906 -4.839672          951            2.398963         2.404271\n",
+       " 901122  2.707608 -4.839746          951            2.397825         2.404271\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 901873  3.985586 -4.844118          951            0.000070         2.404271\n",
+       " 901874  3.987287 -4.844270          951            0.000063         2.404271\n",
+       " 901875  3.988989 -4.844423          951            0.000056         2.404271\n",
+       " 901876  3.990691 -4.844576          951            0.000050         2.404271\n",
+       " 901877  3.992392 -4.844728          951            0.000043         2.404271\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 902118  2.700801 -4.839684          952            2.399424         2.401928\n",
+       " 902119  2.702502 -4.839967          952            2.398283         2.401928\n",
+       " 902120  2.704204 -4.840009          952            2.397149         2.401928\n",
+       " 902121  2.705906 -4.840009          952            2.396015         2.401928\n",
+       " 902122  2.707608 -4.840009          952            2.394882         2.401928\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 902873  3.985586 -4.842534          952            0.000070         2.401928\n",
+       " 902874  3.987287 -4.842630          952            0.000064         2.401928\n",
+       " 902875  3.988989 -4.842727          952            0.000057         2.401928\n",
+       " 902876  3.990691 -4.842824          952            0.000051         2.401928\n",
+       " 902877  3.992392 -4.842921          952            0.000044         2.401928\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 903118  2.700801 -4.839780          953            2.399710         2.400801\n",
+       " 903119  2.702502 -4.839780          953            2.398576         2.400801\n",
+       " 903120  2.704204 -4.839780          953            2.397442         2.400801\n",
+       " 903121  2.705906 -4.839933          953            2.396291         2.400801\n",
+       " 903122  2.707608 -4.840085          953            2.395141         2.400801\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 903873  3.985586 -4.843981          953            0.000068         2.400801\n",
+       " 903874  3.987287 -4.844120          953            0.000062         2.400801\n",
+       " 903875  3.988989 -4.844260          953            0.000055         2.400801\n",
+       " 903876  3.990691 -4.844399          953            0.000049         2.400801\n",
+       " 903877  3.992392 -4.844539          953            0.000042         2.400801\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 904118  2.700801 -4.839881          954            2.397219         2.400266\n",
+       " 904119  2.702502 -4.840099          954            2.396077         2.400266\n",
+       " 904120  2.704204 -4.840184          954            2.394943         2.400266\n",
+       " 904121  2.705906 -4.840034          954            2.393823         2.400266\n",
+       " 904122  2.707608 -4.839884          954            2.392703         2.400266\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 904873  3.985586 -4.844150          954            0.000070         2.400266\n",
+       " 904874  3.987287 -4.844296          954            0.000063         2.400266\n",
+       " 904875  3.988989 -4.844441          954            0.000056         2.400266\n",
+       " 904876  3.990691 -4.844587          954            0.000050         2.400266\n",
+       " 904877  3.992392 -4.844733          954            0.000043         2.400266\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 905118  2.700801 -4.839818          955            2.395167         2.397072\n",
+       " 905119  2.702502 -4.839901          955            2.394064         2.397072\n",
+       " 905120  2.704204 -4.839983          955            2.392961         2.397072\n",
+       " 905121  2.705906 -4.840009          955            2.391838         2.397072\n",
+       " 905122  2.707608 -4.840009          955            2.390706         2.397072\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 905873  3.985586 -4.843377          955            0.000069         2.397072\n",
+       " 905874  3.987287 -4.843495          955            0.000062         2.397072\n",
+       " 905875  3.988989 -4.843613          955            0.000056         2.397072\n",
+       " 905876  3.990691 -4.843731          955            0.000049         2.397072\n",
+       " 905877  3.992392 -4.843849          955            0.000043         2.397072\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 906118  2.700801 -4.840062          956            2.392278         2.395177\n",
+       " 906119  2.702502 -4.840176          956            2.391178         2.395177\n",
+       " 906120  2.704204 -4.840238          956            2.390058         2.395177\n",
+       " 906121  2.705906 -4.840238          956            2.388912         2.395177\n",
+       " 906122  2.707608 -4.840238          956            2.387766         2.395177\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 906873  3.985586 -4.844799          956            0.000068         2.395177\n",
+       " 906874  3.987287 -4.844959          956            0.000062         2.395177\n",
+       " 906875  3.988989 -4.845119          956            0.000055         2.395177\n",
+       " 906876  3.990691 -4.845280          956            0.000049         2.395177\n",
+       " 906877  3.992392 -4.845440          956            0.000042         2.395177\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 907118  2.700801 -4.839852          957            2.390510         2.391882\n",
+       " 907119  2.702502 -4.840007          957            2.389338         2.391882\n",
+       " 907120  2.704204 -4.839935          957            2.388252         2.391882\n",
+       " 907121  2.705906 -4.839860          957            2.387167         2.391882\n",
+       " 907122  2.707608 -4.839785          957            2.386082         2.391882\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 907873  3.985586 -4.845008          957            0.000067         2.391882\n",
+       " 907874  3.987287 -4.845181          957            0.000060         2.391882\n",
+       " 907875  3.988989 -4.845355          957            0.000054         2.391882\n",
+       " 907876  3.990691 -4.845529          957            0.000047         2.391882\n",
+       " 907877  3.992392 -4.845702          957            0.000041         2.391882\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 908118  2.700801 -4.839947          958            2.388721          2.39125\n",
+       " 908119  2.702502 -4.839812          958            2.387577          2.39125\n",
+       " 908120  2.704204 -4.839724          958            2.386464          2.39125\n",
+       " 908121  2.705906 -4.839650          958            2.385360          2.39125\n",
+       " 908122  2.707608 -4.839576          958            2.384256          2.39125\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 908873  3.985586 -4.842564          958            0.000068          2.39125\n",
+       " 908874  3.987287 -4.842660          958            0.000061          2.39125\n",
+       " 908875  3.988989 -4.842758          958            0.000055          2.39125\n",
+       " 908876  3.990691 -4.842854          958            0.000048          2.39125\n",
+       " 908877  3.992392 -4.842951          958            0.000042          2.39125\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 909118  2.700801 -4.839874          959            2.388299         2.389238\n",
+       " 909119  2.702502 -4.840074          959            2.387228         2.389238\n",
+       " 909120  2.704204 -4.840182          959            2.386143         2.389238\n",
+       " 909121  2.705906 -4.839873          959            2.384989         2.389238\n",
+       " 909122  2.707608 -4.839564          959            2.383835         2.389238\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 909873  3.985586 -4.844831          959            0.000067         2.389238\n",
+       " 909874  3.987287 -4.844991          959            0.000061         2.389238\n",
+       " 909875  3.988989 -4.845150          959            0.000054         2.389238\n",
+       " 909876  3.990691 -4.845309          959            0.000048         2.389238\n",
+       " 909877  3.992392 -4.845469          959            0.000041         2.389238\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 910118  2.700801 -4.839705          960            2.389892          2.39079\n",
+       " 910119  2.702502 -4.839998          960            2.388805          2.39079\n",
+       " 910120  2.704204 -4.839845          960            2.387668          2.39079\n",
+       " 910121  2.705906 -4.839693          960            2.386531          2.39079\n",
+       " 910122  2.707608 -4.839551          960            2.385398          2.39079\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 910873  3.985586 -4.844382          960            0.000068          2.39079\n",
+       " 910874  3.987287 -4.844535          960            0.000062          2.39079\n",
+       " 910875  3.988989 -4.844687          960            0.000055          2.39079\n",
+       " 910876  3.990691 -4.844840          960            0.000048          2.39079\n",
+       " 910877  3.992392 -4.844992          960            0.000042          2.39079\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 911118  2.700801 -4.839620          961            2.389414         2.390948\n",
+       " 911119  2.702502 -4.840039          961            2.388298         2.390948\n",
+       " 911120  2.704204 -4.840115          961            2.387157         2.390948\n",
+       " 911121  2.705906 -4.840191          961            2.386016         2.390948\n",
+       " 911122  2.707608 -4.840180          961            2.384871         2.390948\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 911873  3.985586 -4.843165          961            0.000068         2.390948\n",
+       " 911874  3.987287 -4.843283          961            0.000061         2.390948\n",
+       " 911875  3.988989 -4.843401          961            0.000055         2.390948\n",
+       " 911876  3.990691 -4.843518          961            0.000048         2.390948\n",
+       " 911877  3.992392 -4.843636          961            0.000042         2.390948\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 912118  2.700801 -4.839472          962            2.387492         2.390289\n",
+       " 912119  2.702502 -4.839350          962            2.386390         2.390289\n",
+       " 912120  2.704204 -4.839579          962            2.385271         2.390289\n",
+       " 912121  2.705906 -4.839808          962            2.384152         2.390289\n",
+       " 912122  2.707608 -4.840018          962            2.383027         2.390289\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 912873  3.985586 -4.843435          962            0.000069         2.390289\n",
+       " 912874  3.987287 -4.843538          962            0.000062         2.390289\n",
+       " 912875  3.988989 -4.843641          962            0.000056         2.390289\n",
+       " 912876  3.990691 -4.843743          962            0.000050         2.390289\n",
+       " 912877  3.992392 -4.843846          962            0.000043         2.390289\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 913118  2.700801 -4.840009          963            2.384787         2.387592\n",
+       " 913119  2.702502 -4.840009          963            2.383683         2.387592\n",
+       " 913120  2.704204 -4.840009          963            2.382579         2.387592\n",
+       " 913121  2.705906 -4.840009          963            2.381443         2.387592\n",
+       " 913122  2.707608 -4.840009          963            2.380274         2.387592\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 913873  3.985586 -4.844190          963            0.000068         2.387592\n",
+       " 913874  3.987287 -4.844334          963            0.000061         2.387592\n",
+       " 913875  3.988989 -4.844478          963            0.000055         2.387592\n",
+       " 913876  3.990691 -4.844622          963            0.000048         2.387592\n",
+       " 913877  3.992392 -4.844766          963            0.000042         2.387592\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 914118  2.700801 -4.840009          964            2.383515         2.385553\n",
+       " 914119  2.702502 -4.840009          964            2.382421         2.385553\n",
+       " 914120  2.704204 -4.840009          964            2.381318         2.385553\n",
+       " 914121  2.705906 -4.840009          964            2.380172         2.385553\n",
+       " 914122  2.707608 -4.840009          964            2.379027         2.385553\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 914873  3.985586 -4.844183          964            0.000068         2.385553\n",
+       " 914874  3.987287 -4.844327          964            0.000062         2.385553\n",
+       " 914875  3.988989 -4.844471          964            0.000055         2.385553\n",
+       " 914876  3.990691 -4.844615          964            0.000049         2.385553\n",
+       " 914877  3.992392 -4.844759          964            0.000042         2.385553\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 915118  2.700801 -4.840009          965            2.381804         2.384533\n",
+       " 915119  2.702502 -4.840009          965            2.380701         2.384533\n",
+       " 915120  2.704204 -4.839949          965            2.379570         2.384533\n",
+       " 915121  2.705906 -4.839873          965            2.378433         2.384533\n",
+       " 915122  2.707608 -4.839798          965            2.377295         2.384533\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 915873  3.985586 -4.845624          965            0.000067         2.384533\n",
+       " 915874  3.987287 -4.845810          965            0.000061         2.384533\n",
+       " 915875  3.988989 -4.845997          965            0.000054         2.384533\n",
+       " 915876  3.990691 -4.846184          965            0.000048         2.384533\n",
+       " 915877  3.992392 -4.846370          965            0.000041         2.384533\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 916118  2.700801 -4.839824          966            2.378570         2.381823\n",
+       " 916119  2.702502 -4.839916          966            2.377452         2.381823\n",
+       " 916120  2.704204 -4.840009          966            2.376334         2.381823\n",
+       " 916121  2.705906 -4.839934          966            2.375219         2.381823\n",
+       " 916122  2.707608 -4.839859          966            2.374103         2.381823\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 916873  3.985586 -4.844201          966            0.000067         2.381823\n",
+       " 916874  3.987287 -4.844345          966            0.000061         2.381823\n",
+       " 916875  3.988989 -4.844490          966            0.000054         2.381823\n",
+       " 916876  3.990691 -4.844634          966            0.000048         2.381823\n",
+       " 916877  3.992392 -4.844779          966            0.000041         2.381823\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 917118  2.700801 -4.839785          967            2.376171         2.378635\n",
+       " 917119  2.702502 -4.839859          967            2.375058         2.378635\n",
+       " 917120  2.704204 -4.839933          967            2.373945         2.378635\n",
+       " 917121  2.705906 -4.840007          967            2.372833         2.378635\n",
+       " 917122  2.707608 -4.840009          967            2.371692         2.378635\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 917873  3.985586 -4.845379          967            0.000067         2.378635\n",
+       " 917874  3.987287 -4.845571          967            0.000060         2.378635\n",
+       " 917875  3.988989 -4.845764          967            0.000054         2.378635\n",
+       " 917876  3.990691 -4.845956          967            0.000048         2.378635\n",
+       " 917877  3.992392 -4.846148          967            0.000041         2.378635\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 918118  2.700801 -4.839972          968            2.373251         2.375819\n",
+       " 918119  2.702502 -4.840185          968            2.372112         2.375819\n",
+       " 918120  2.704204 -4.840110          968            2.370983         2.375819\n",
+       " 918121  2.705906 -4.840035          968            2.369854         2.375819\n",
+       " 918122  2.707608 -4.839960          968            2.368719         2.375819\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 918873  3.985586 -4.845383          968            0.000067         2.375819\n",
+       " 918874  3.987287 -4.845574          968            0.000060         2.375819\n",
+       " 918875  3.988989 -4.845766          968            0.000054         2.375819\n",
+       " 918876  3.990691 -4.845957          968            0.000047         2.375819\n",
+       " 918877  3.992392 -4.846148          968            0.000041         2.375819\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 919118  2.700801 -4.839772          969            2.372650         2.374166\n",
+       " 919119  2.702502 -4.839696          969            2.371518         2.374166\n",
+       " 919120  2.704204 -4.839620          969            2.370386         2.374166\n",
+       " 919121  2.705906 -4.839551          969            2.369254         2.374166\n",
+       " 919122  2.707608 -4.839551          969            2.368131         2.374166\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 919873  3.985586 -4.843856          969            0.000066         2.374166\n",
+       " 919874  3.987287 -4.843979          969            0.000060         2.374166\n",
+       " 919875  3.988989 -4.844102          969            0.000053         2.374166\n",
+       " 919876  3.990691 -4.844225          969            0.000047         2.374166\n",
+       " 919877  3.992392 -4.844348          969            0.000040         2.374166\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 920118  2.700801 -4.840009          970            2.370908          2.37393\n",
+       " 920119  2.702502 -4.840009          970            2.369778          2.37393\n",
+       " 920120  2.704204 -4.840009          970            2.368648          2.37393\n",
+       " 920121  2.705906 -4.840030          970            2.367516          2.37393\n",
+       " 920122  2.707608 -4.840104          970            2.366377          2.37393\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 920869  3.978779 -4.839847          970            0.000084          2.37393\n",
+       " 920870  3.980480 -4.839832          970            0.000077          2.37393\n",
+       " 920871  3.982182 -4.839818          970            0.000071          2.37393\n",
+       " 920872  3.983884 -4.839803          970            0.000064          2.37393\n",
+       " 920873  3.985586 -4.839788          970            0.000057          2.37393\n",
+       " \n",
+       " [756 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 921118  2.700801 -4.840057          971            2.370053         2.370744\n",
+       " 921119  2.702502 -4.840159          971            2.368949         2.370744\n",
+       " 921120  2.704204 -4.840204          971            2.367833         2.370744\n",
+       " 921121  2.705906 -4.840052          971            2.366674         2.370744\n",
+       " 921122  2.707608 -4.839899          971            2.365515         2.370744\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 921872  3.983884 -4.845830          971            0.000070         2.370744\n",
+       " 921873  3.985586 -4.846049          971            0.000064         2.370744\n",
+       " 921874  3.987287 -4.846269          971            0.000058         2.370744\n",
+       " 921875  3.988989 -4.846488          971            0.000051         2.370744\n",
+       " 921876  3.990691 -4.846708          971            0.000045         2.370744\n",
+       " \n",
+       " [759 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 922118  2.700801 -4.839823          972            2.368767         2.371678\n",
+       " 922119  2.702502 -4.839971          972            2.367646         2.371678\n",
+       " 922120  2.704204 -4.840119          972            2.366524         2.371678\n",
+       " 922121  2.705906 -4.840209          972            2.365401         2.371678\n",
+       " 922122  2.707608 -4.840062          972            2.364266         2.371678\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 922873  3.985586 -4.842150          972            0.000067         2.371678\n",
+       " 922874  3.987287 -4.842238          972            0.000061         2.371678\n",
+       " 922875  3.988989 -4.842327          972            0.000054         2.371678\n",
+       " 922876  3.990691 -4.842416          972            0.000048         2.371678\n",
+       " 922877  3.992392 -4.842504          972            0.000041         2.371678\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 923118  2.700801 -4.840238          973            2.366892          2.36866\n",
+       " 923119  2.702502 -4.840238          973            2.365746          2.36866\n",
+       " 923120  2.704204 -4.840238          973            2.364601          2.36866\n",
+       " 923121  2.705906 -4.840234          973            2.363455          2.36866\n",
+       " 923122  2.707608 -4.840158          973            2.362318          2.36866\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 923873  3.985586 -4.844050          973            0.000066          2.36866\n",
+       " 923874  3.987287 -4.844181          973            0.000060          2.36866\n",
+       " 923875  3.988989 -4.844311          973            0.000053          2.36866\n",
+       " 923876  3.990691 -4.844441          973            0.000047          2.36866\n",
+       " 923877  3.992392 -4.844571          973            0.000041          2.36866\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 924118  2.700801 -4.839600          974            2.364630         2.367077\n",
+       " 924119  2.702502 -4.839704          974            2.363516         2.367077\n",
+       " 924120  2.704204 -4.839801          974            2.362396         2.367077\n",
+       " 924121  2.705906 -4.839877          974            2.361259         2.367077\n",
+       " 924122  2.707608 -4.839953          974            2.360122         2.367077\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 924873  3.985586 -4.845409          974            0.000066         2.367077\n",
+       " 924874  3.987287 -4.845603          974            0.000059         2.367077\n",
+       " 924875  3.988989 -4.845796          974            0.000053         2.367077\n",
+       " 924876  3.990691 -4.845989          974            0.000046         2.367077\n",
+       " 924877  3.992392 -4.846183          974            0.000040         2.367077\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 925118  2.700801 -4.840238          975            2.359629         2.362577\n",
+       " 925119  2.702502 -4.840176          975            2.358541         2.362577\n",
+       " 925120  2.704204 -4.840102          975            2.357459         2.362577\n",
+       " 925121  2.705906 -4.840028          975            2.356377         2.362577\n",
+       " 925122  2.707608 -4.840009          975            2.355231         2.362577\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 925873  3.985586 -4.843430          975            0.000066         2.362577\n",
+       " 925874  3.987287 -4.843546          975            0.000059         2.362577\n",
+       " 925875  3.988989 -4.843663          975            0.000053         2.362577\n",
+       " 925876  3.990691 -4.843780          975            0.000046         2.362577\n",
+       " 925877  3.992392 -4.843896          975            0.000040         2.362577\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 926118  2.700801 -4.839499          976            2.359593         2.360272\n",
+       " 926119  2.702502 -4.839780          976            2.358464         2.360272\n",
+       " 926120  2.704204 -4.839780          976            2.357349         2.360272\n",
+       " 926121  2.705906 -4.839780          976            2.356233         2.360272\n",
+       " 926122  2.707608 -4.839796          976            2.355113         2.360272\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 926872  3.983884 -4.844676          976            0.000072         2.360272\n",
+       " 926873  3.985586 -4.844842          976            0.000066         2.360272\n",
+       " 926874  3.987287 -4.845008          976            0.000059         2.360272\n",
+       " 926875  3.988989 -4.845173          976            0.000053         2.360272\n",
+       " 926876  3.990691 -4.845339          976            0.000046         2.360272\n",
+       " \n",
+       " [759 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 927118  2.700801 -4.839782          977            2.354185         2.357658\n",
+       " 927119  2.702502 -4.839859          977            2.353031         2.357658\n",
+       " 927120  2.704204 -4.839936          977            2.351877         2.357658\n",
+       " 927121  2.705906 -4.840014          977            2.350724         2.357658\n",
+       " 927122  2.707608 -4.840089          977            2.349586         2.357658\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 927872  3.983884 -4.844713          977            0.000069         2.357658\n",
+       " 927873  3.985586 -4.844885          977            0.000063         2.357658\n",
+       " 927874  3.987287 -4.845057          977            0.000056         2.357658\n",
+       " 927875  3.988989 -4.845230          977            0.000050         2.357658\n",
+       " 927876  3.990691 -4.845402          977            0.000043         2.357658\n",
+       " \n",
+       " [759 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 928118  2.700801 -4.840113          978            2.350994         2.354184\n",
+       " 928119  2.702502 -4.839963          978            2.349871         2.354184\n",
+       " 928120  2.704204 -4.839888          978            2.348747         2.354184\n",
+       " 928121  2.705906 -4.839813          978            2.347622         2.354184\n",
+       " 928122  2.707608 -4.839823          978            2.346483         2.354184\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 928872  3.983884 -4.844115          978            0.000070         2.354184\n",
+       " 928873  3.985586 -4.844266          978            0.000063         2.354184\n",
+       " 928874  3.987287 -4.844418          978            0.000057         2.354184\n",
+       " 928875  3.988989 -4.844569          978            0.000050         2.354184\n",
+       " 928876  3.990691 -4.844721          978            0.000044         2.354184\n",
+       " \n",
+       " [759 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 929118  2.700801 -4.839988          979            2.347619         2.349844\n",
+       " 929119  2.702502 -4.839872          979            2.346492         2.349844\n",
+       " 929120  2.704204 -4.840023          979            2.345380         2.349844\n",
+       " 929121  2.705906 -4.840173          979            2.344269         2.349844\n",
+       " 929122  2.707608 -4.840155          979            2.343140         2.349844\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 929872  3.983884 -4.841593          979            0.000069         2.349844\n",
+       " 929873  3.985586 -4.841648          979            0.000062         2.349844\n",
+       " 929874  3.987287 -4.841703          979            0.000056         2.349844\n",
+       " 929875  3.988989 -4.841758          979            0.000049         2.349844\n",
+       " 929876  3.990691 -4.841813          979            0.000043         2.349844\n",
+       " \n",
+       " [759 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 930118  2.700801 -4.840238          980            2.346348         2.348099\n",
+       " 930119  2.702502 -4.840238          980            2.345189         2.348099\n",
+       " 930120  2.704204 -4.840238          980            2.344029         2.348099\n",
+       " 930121  2.705906 -4.840238          980            2.342877         2.348099\n",
+       " 930122  2.707608 -4.840238          980            2.341736         2.348099\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 930872  3.983884 -4.844754          980            0.000069         2.348099\n",
+       " 930873  3.985586 -4.844919          980            0.000063         2.348099\n",
+       " 930874  3.987287 -4.845084          980            0.000056         2.348099\n",
+       " 930875  3.988989 -4.845249          980            0.000050         2.348099\n",
+       " 930876  3.990691 -4.845414          980            0.000043         2.348099\n",
+       " \n",
+       " [759 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 931118  2.700801 -4.839843          986            2.452863         2.120964\n",
+       " 931119  2.702502 -4.839977          986            2.451773         2.120964\n",
+       " 931120  2.704204 -4.840065          986            2.450657         2.120964\n",
+       " 931121  2.705906 -4.840139          986            2.449531         2.120964\n",
+       " 931122  2.707608 -4.840214          986            2.448405         2.120964\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 931878  3.994094 -4.844620          986            0.000068         2.120964\n",
+       " 931879  3.995796 -4.844765          986            0.000061         2.120964\n",
+       " 931880  3.997498 -4.844911          986            0.000055         2.120964\n",
+       " 931881  3.999199 -4.845056          986            0.000049         2.120964\n",
+       " 931882  4.000901 -4.845201          986            0.000043         2.120964\n",
+       " \n",
+       " [765 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 932118  2.700801 -4.839704          987            2.426754         2.416857\n",
+       " 932119  2.702502 -4.839539          987            2.425637         2.416857\n",
+       " 932120  2.704204 -4.839374          987            2.424520         2.416857\n",
+       " 932121  2.705906 -4.839477          987            2.423421         2.416857\n",
+       " 932122  2.707608 -4.839703          987            2.422332         2.416857\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 932875  3.988989 -4.841826          987            0.000068         2.416857\n",
+       " 932876  3.990691 -4.841880          987            0.000062         2.416857\n",
+       " 932877  3.992392 -4.841933          987            0.000056         2.416857\n",
+       " 932878  3.994094 -4.841987          987            0.000049         2.416857\n",
+       " 932879  3.995796 -4.842040          987            0.000043         2.416857\n",
+       " \n",
+       " [762 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 933118  2.700801 -4.840227          988            2.416522         2.421189\n",
+       " 933119  2.702502 -4.840152          988            2.415393         2.421189\n",
+       " 933120  2.704204 -4.840076          988            2.414264         2.421189\n",
+       " 933121  2.705906 -4.840009          988            2.413138         2.421189\n",
+       " 933122  2.707608 -4.840009          988            2.412034         2.421189\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 933874  3.987287 -4.843496          988            0.000071         2.421189\n",
+       " 933875  3.988989 -4.843624          988            0.000065         2.421189\n",
+       " 933876  3.990691 -4.843751          988            0.000058         2.421189\n",
+       " 933877  3.992392 -4.843879          988            0.000052         2.421189\n",
+       " 933878  3.994094 -4.844007          988            0.000046         2.421189\n",
+       " \n",
+       " [761 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 934118  2.700801 -4.839692          989            2.405563         2.410235\n",
+       " 934119  2.702502 -4.839992          989            2.404440         2.410235\n",
+       " 934120  2.704204 -4.840185          989            2.403312         2.410235\n",
+       " 934121  2.705906 -4.839889          989            2.402160         2.410235\n",
+       " 934122  2.707608 -4.839593          989            2.401009         2.410235\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 934874  3.987287 -4.844404          989            0.000066         2.410235\n",
+       " 934875  3.988989 -4.844558          989            0.000060         2.410235\n",
+       " 934876  3.990691 -4.844712          989            0.000053         2.410235\n",
+       " 934877  3.992392 -4.844867          989            0.000047         2.410235\n",
+       " 934878  3.994094 -4.845021          989            0.000041         2.410235\n",
+       " \n",
+       " [761 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 935118  2.700801 -4.839884          990            2.398383         2.402439\n",
+       " 935119  2.702502 -4.839872          990            2.397235         2.402439\n",
+       " 935120  2.704204 -4.840023          990            2.396111         2.402439\n",
+       " 935121  2.705906 -4.840173          990            2.394986         2.402439\n",
+       " 935122  2.707608 -4.840195          990            2.393835         2.402439\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 935873  3.985586 -4.843740          990            0.000070         2.402439\n",
+       " 935874  3.987287 -4.843866          990            0.000064         2.402439\n",
+       " 935875  3.988989 -4.843993          990            0.000058         2.402439\n",
+       " 935876  3.990691 -4.844120          990            0.000052         2.402439\n",
+       " 935877  3.992392 -4.844246          990            0.000045         2.402439\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 936118  2.700801 -4.839600          991            2.388902         2.394875\n",
+       " 936119  2.702502 -4.839746          991            2.387758         2.394875\n",
+       " 936120  2.704204 -4.839891          991            2.386615         2.394875\n",
+       " 936121  2.705906 -4.840009          991            2.385473         2.394875\n",
+       " 936122  2.707608 -4.840009          991            2.384338         2.394875\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 936873  3.985586 -4.843945          991            0.000067         2.394875\n",
+       " 936874  3.987287 -4.844091          991            0.000061         2.394875\n",
+       " 936875  3.988989 -4.844237          991            0.000055         2.394875\n",
+       " 936876  3.990691 -4.844383          991            0.000048         2.394875\n",
+       " 936877  3.992392 -4.844530          991            0.000042         2.394875\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 937118  2.700801 -4.840213          992            2.372881         2.385425\n",
+       " 937119  2.702502 -4.840651          992            2.371673         2.385425\n",
+       " 937120  2.704204 -4.840499          992            2.370530         2.385425\n",
+       " 937121  2.705906 -4.840281          992            2.369395         2.385425\n",
+       " 937122  2.707608 -4.840062          992            2.368260         2.385425\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 937873  3.985586 -4.844887          992            0.000065         2.385425\n",
+       " 937874  3.987287 -4.845039          992            0.000059         2.385425\n",
+       " 937875  3.988989 -4.845192          992            0.000052         2.385425\n",
+       " 937876  3.990691 -4.845345          992            0.000046         2.385425\n",
+       " 937877  3.992392 -4.845498          992            0.000040         2.385425\n",
+       " \n",
+       " [760 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 938118  2.700801 -4.839790          993            2.365304         2.371886\n",
+       " 938119  2.702502 -4.839940          993            2.364136         2.371886\n",
+       " 938120  2.704204 -4.840090          993            2.362967         2.371886\n",
+       " 938121  2.705906 -4.840236          993            2.361799         2.371886\n",
+       " 938122  2.707608 -4.840086          993            2.360639         2.371886\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 938872  3.983884 -4.842530          993            0.000070         2.371886\n",
+       " 938873  3.985586 -4.842623          993            0.000064         2.371886\n",
+       " 938874  3.987287 -4.842716          993            0.000058         2.371886\n",
+       " 938875  3.988989 -4.842809          993            0.000052         2.371886\n",
+       " 938876  3.990691 -4.842901          993            0.000045         2.371886\n",
+       " \n",
+       " [759 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 939118  2.700801 -4.840266          994            2.357690         2.363466\n",
+       " 939119  2.702502 -4.840342          994            2.356517         2.363466\n",
+       " 939120  2.704204 -4.840416          994            2.355344         2.363466\n",
+       " 939121  2.705906 -4.840392          994            2.354168         2.363466\n",
+       " 939122  2.707608 -4.840164          994            2.352986         2.363466\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 939872  3.983884 -4.845046          994            0.000068         2.363466\n",
+       " 939873  3.985586 -4.845199          994            0.000061         2.363466\n",
+       " 939874  3.987287 -4.845351          994            0.000055         2.363466\n",
+       " 939875  3.988989 -4.845503          994            0.000049         2.363466\n",
+       " 939876  3.990691 -4.845656          994            0.000043         2.363466\n",
+       " \n",
+       " [759 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 940118  2.700801 -4.839970          995            2.353381         2.357822\n",
+       " 940119  2.702502 -4.839884          995            2.352246         2.357822\n",
+       " 940120  2.704204 -4.839799          995            2.351112         2.357822\n",
+       " 940121  2.705906 -4.839839          995            2.349941         2.357822\n",
+       " 940122  2.707608 -4.839914          995            2.348759         2.357822\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 940872  3.983884 -4.843772          995            0.000067         2.357822\n",
+       " 940873  3.985586 -4.843905          995            0.000061         2.357822\n",
+       " 940874  3.987287 -4.844038          995            0.000055         2.357822\n",
+       " 940875  3.988989 -4.844171          995            0.000048         2.357822\n",
+       " 940876  3.990691 -4.844304          995            0.000042         2.357822\n",
+       " \n",
+       " [759 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 941118  2.700801 -4.839551          996            2.349934         2.353121\n",
+       " 941119  2.702502 -4.839551          996            2.348761         2.353121\n",
+       " 941120  2.704204 -4.839551          996            2.347588         2.353121\n",
+       " 941121  2.705906 -4.839580          996            2.346421         2.353121\n",
+       " 941122  2.707608 -4.839654          996            2.345266         2.353121\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 941872  3.983884 -4.843994          996            0.000066         2.353121\n",
+       " 941873  3.985586 -4.844134          996            0.000060         2.353121\n",
+       " 941874  3.987287 -4.844275          996            0.000054         2.353121\n",
+       " 941875  3.988989 -4.844415          996            0.000047         2.353121\n",
+       " 941876  3.990691 -4.844555          996            0.000041         2.353121\n",
+       " \n",
+       " [759 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 942118  2.700801 -4.839829          997            2.344123         2.349248\n",
+       " 942119  2.702502 -4.839977          997            2.342950         2.349248\n",
+       " 942120  2.704204 -4.840126          997            2.341776         2.349248\n",
+       " 942121  2.705906 -4.840185          997            2.340607         2.349248\n",
+       " 942122  2.707608 -4.839963          997            2.339451         2.349248\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 942872  3.983884 -4.843989          997            0.000065         2.349248\n",
+       " 942873  3.985586 -4.844135          997            0.000059         2.349248\n",
+       " 942874  3.987287 -4.844281          997            0.000053         2.349248\n",
+       " 942875  3.988989 -4.844428          997            0.000047         2.349248\n",
+       " 942876  3.990691 -4.844573          997            0.000040         2.349248\n",
+       " \n",
+       " [759 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 943118  2.700801 -4.840237          998            2.339921         2.344043\n",
+       " 943119  2.702502 -4.840162          998            2.338783         2.344043\n",
+       " 943120  2.704204 -4.840086          998            2.337645         2.344043\n",
+       " 943121  2.705906 -4.840012          998            2.336508         2.344043\n",
+       " 943122  2.707608 -4.839936          998            2.335319         2.344043\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 943871  3.982182 -4.843966          998            0.000070         2.344043\n",
+       " 943872  3.983884 -4.844092          998            0.000064         2.344043\n",
+       " 943873  3.985586 -4.844219          998            0.000058         2.344043\n",
+       " 943874  3.987287 -4.844345          998            0.000052         2.344043\n",
+       " 943875  3.988989 -4.844471          998            0.000045         2.344043\n",
+       " \n",
+       " [758 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 944118  2.700801 -4.839820          999            2.336936         2.339056\n",
+       " 944119  2.702502 -4.839905          999            2.335766         2.339056\n",
+       " 944120  2.704204 -4.839990          999            2.334597         2.339056\n",
+       " 944121  2.705906 -4.840066          999            2.333461         2.339056\n",
+       " 944122  2.707608 -4.840141          999            2.332336         2.339056\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 944871  3.982182 -4.844283          999            0.000070         2.339056\n",
+       " 944872  3.983884 -4.844442          999            0.000063         2.339056\n",
+       " 944873  3.985586 -4.844602          999            0.000057         2.339056\n",
+       " 944874  3.987287 -4.844761          999            0.000051         2.339056\n",
+       " 944875  3.988989 -4.844921          999            0.000045         2.339056\n",
+       " \n",
+       " [758 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 945118  2.700801 -4.839607         1000            2.332247         2.336856\n",
+       " 945119  2.702502 -4.839755         1000            2.331096         2.336856\n",
+       " 945120  2.704204 -4.839903         1000            2.329944         2.336856\n",
+       " 945121  2.705906 -4.839967         1000            2.328791         2.336856\n",
+       " 945122  2.707608 -4.839819         1000            2.327635         2.336856\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 945871  3.982182 -4.842419         1000            0.000068         2.336856\n",
+       " 945872  3.983884 -4.842493         1000            0.000062         2.336856\n",
+       " 945873  3.985586 -4.842566         1000            0.000056         2.336856\n",
+       " 945874  3.987287 -4.842639         1000            0.000050         2.336856\n",
+       " 945875  3.988989 -4.842712         1000            0.000043         2.336856\n",
+       " \n",
+       " [758 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 946118  2.700801 -4.840009         1001            2.327182          2.33109\n",
+       " 946119  2.702502 -4.840009         1001            2.326053          2.33109\n",
+       " 946120  2.704204 -4.840009         1001            2.324924          2.33109\n",
+       " 946121  2.705906 -4.840005         1001            2.323793          2.33109\n",
+       " 946122  2.707608 -4.839930         1001            2.322624          2.33109\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 946871  3.982182 -4.843979         1001            0.000070          2.33109\n",
+       " 946872  3.983884 -4.844105         1001            0.000064          2.33109\n",
+       " 946873  3.985586 -4.844232         1001            0.000057          2.33109\n",
+       " 946874  3.987287 -4.844357         1001            0.000051          2.33109\n",
+       " 946875  3.988989 -4.844483         1001            0.000045          2.33109\n",
+       " \n",
+       " [758 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 947118  2.700801 -4.839971         1002            2.323525         2.327027\n",
+       " 947119  2.702502 -4.839889         1002            2.322398         2.327027\n",
+       " 947120  2.704204 -4.839806         1002            2.321271         2.327027\n",
+       " 947121  2.705906 -4.839887         1002            2.320116         2.327027\n",
+       " 947122  2.707608 -4.840041         1002            2.318949         2.327027\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 947871  3.982182 -4.845358         1002            0.000067         2.327027\n",
+       " 947872  3.983884 -4.845552         1002            0.000060         2.327027\n",
+       " 947873  3.985586 -4.845746         1002            0.000054         2.327027\n",
+       " 947874  3.987287 -4.845940         1002            0.000048         2.327027\n",
+       " 947875  3.988989 -4.846134         1002            0.000042         2.327027\n",
+       " \n",
+       " [758 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 948118  2.700801 -4.839818         1003            2.317914         2.321334\n",
+       " 948119  2.702502 -4.839901         1003            2.316777         2.321334\n",
+       " 948120  2.704204 -4.839983         1003            2.315641         2.321334\n",
+       " 948121  2.705906 -4.839958         1003            2.314503         2.321334\n",
+       " 948122  2.707608 -4.839882         1003            2.313366         2.321334\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 948871  3.982182 -4.846022         1003            0.000066         2.321334\n",
+       " 948872  3.983884 -4.846221         1003            0.000060         2.321334\n",
+       " 948873  3.985586 -4.846420         1003            0.000054         2.321334\n",
+       " 948874  3.987287 -4.846620         1003            0.000048         2.321334\n",
+       " 948875  3.988989 -4.846819         1003            0.000041         2.321334\n",
+       " \n",
+       " [758 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 949118  2.700801 -4.839956         1004            2.314613         2.317684\n",
+       " 949119  2.702502 -4.839843         1004            2.313460         2.317684\n",
+       " 949120  2.704204 -4.839848         1004            2.312308         2.317684\n",
+       " 949121  2.705906 -4.839998         1004            2.311157         2.317684\n",
+       " 949122  2.707608 -4.840148         1004            2.310006         2.317684\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 949871  3.982182 -4.844827         1004            0.000065         2.317684\n",
+       " 949872  3.983884 -4.844993         1004            0.000059         2.317684\n",
+       " 949873  3.985586 -4.845160         1004            0.000053         2.317684\n",
+       " 949874  3.987287 -4.845326         1004            0.000046         2.317684\n",
+       " 949875  3.988989 -4.845492         1004            0.000040         2.317684\n",
+       " \n",
+       " [758 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 950118  2.700801 -4.839830         1005            2.312609         2.315155\n",
+       " 950119  2.702502 -4.839936         1005            2.311485         2.315155\n",
+       " 950120  2.704204 -4.839962         1005            2.310341         2.315155\n",
+       " 950121  2.705906 -4.839812         1005            2.309155         2.315155\n",
+       " 950122  2.707608 -4.839662         1005            2.307968         2.315155\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 950871  3.982182 -4.844283         1005            0.000065         2.315155\n",
+       " 950872  3.983884 -4.844416         1005            0.000059         2.315155\n",
+       " 950873  3.985586 -4.844548         1005            0.000052         2.315155\n",
+       " 950874  3.987287 -4.844681         1005            0.000046         2.315155\n",
+       " 950875  3.988989 -4.844814         1005            0.000040         2.315155\n",
+       " \n",
+       " [758 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 951118  2.700801 -4.840009         1006            2.311182         2.312608\n",
+       " 951119  2.702502 -4.840009         1006            2.310027         2.312608\n",
+       " 951120  2.704204 -4.840009         1006            2.308923         2.312608\n",
+       " 951121  2.705906 -4.840009         1006            2.307819         2.312608\n",
+       " 951122  2.707608 -4.840009         1006            2.306681         2.312608\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 951870  3.980480 -4.844355         1006            0.000071         2.312608\n",
+       " 951871  3.982182 -4.844493         1006            0.000064         2.312608\n",
+       " 951872  3.983884 -4.844632         1006            0.000058         2.312608\n",
+       " 951873  3.985586 -4.844771         1006            0.000052         2.312608\n",
+       " 951874  3.987287 -4.844910         1006            0.000046         2.312608\n",
+       " \n",
+       " [757 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 952118  2.700801 -4.839952         1007            2.307704         2.313002\n",
+       " 952119  2.702502 -4.839831         1007            2.306526         2.313002\n",
+       " 952120  2.704204 -4.839823         1007            2.305383         2.313002\n",
+       " 952121  2.705906 -4.839898         1007            2.304267         2.313002\n",
+       " 952122  2.707608 -4.839972         1007            2.303150         2.313002\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 952871  3.982182 -4.842608         1007            0.000065         2.313002\n",
+       " 952872  3.983884 -4.842701         1007            0.000059         2.313002\n",
+       " 952873  3.985586 -4.842793         1007            0.000053         2.313002\n",
+       " 952874  3.987287 -4.842886         1007            0.000046         2.313002\n",
+       " 952875  3.988989 -4.842979         1007            0.000040         2.313002\n",
+       " \n",
+       " [758 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 953118  2.700801 -4.840141         1008            2.316577         2.306789\n",
+       " 953119  2.702502 -4.839932         1008            2.315457         2.306789\n",
+       " 953120  2.704204 -4.839780         1008            2.314335         2.306789\n",
+       " 953121  2.705906 -4.839780         1008            2.313206         2.306789\n",
+       " 953122  2.707608 -4.839780         1008            2.312077         2.306789\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 953870  3.980480 -4.844899         1008            0.000070         2.306789\n",
+       " 953871  3.982182 -4.845071         1008            0.000064         2.306789\n",
+       " 953872  3.983884 -4.845243         1008            0.000057         2.306789\n",
+       " 953873  3.985586 -4.845415         1008            0.000051         2.306789\n",
+       " 953874  3.987287 -4.845588         1008            0.000045         2.306789\n",
+       " \n",
+       " [757 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 954118  2.700801 -4.839824         1009            2.302097         2.317242\n",
+       " 954119  2.702502 -4.839976         1009            2.300929         2.317242\n",
+       " 954120  2.704204 -4.840129         1009            2.299761         2.317242\n",
+       " 954121  2.705906 -4.840196         1009            2.298599         2.317242\n",
+       " 954122  2.707608 -4.840045         1009            2.297452         2.317242\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 954871  3.982182 -4.844770         1009            0.000067         2.317242\n",
+       " 954872  3.983884 -4.844937         1009            0.000061         2.317242\n",
+       " 954873  3.985586 -4.845105         1009            0.000055         2.317242\n",
+       " 954874  3.987287 -4.845273         1009            0.000048         2.317242\n",
+       " 954875  3.988989 -4.845440         1009            0.000042         2.317242\n",
+       " \n",
+       " [758 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 955118  2.700801 -4.840009         1010            2.298613         2.302275\n",
+       " 955119  2.702502 -4.840009         1010            2.297433         2.302275\n",
+       " 955120  2.704204 -4.840009         1010            2.296303         2.302275\n",
+       " 955121  2.705906 -4.840009         1010            2.295173         2.302275\n",
+       " 955122  2.707608 -4.840054         1010            2.294028         2.302275\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 955871  3.982182 -4.843625         1010            0.000066         2.302275\n",
+       " 955872  3.983884 -4.843745         1010            0.000060         2.302275\n",
+       " 955873  3.985586 -4.843865         1010            0.000053         2.302275\n",
+       " 955874  3.987287 -4.843986         1010            0.000047         2.302275\n",
+       " 955875  3.988989 -4.844106         1010            0.000041         2.302275\n",
+       " \n",
+       " [758 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 956118  2.700801 -4.839983         1011            2.296217         2.297784\n",
+       " 956119  2.702502 -4.840366         1011            2.295063         2.297784\n",
+       " 956120  2.704204 -4.840214         1011            2.293900         2.297784\n",
+       " 956121  2.705906 -4.840062         1011            2.292736         2.297784\n",
+       " 956122  2.707608 -4.839912         1011            2.291586         2.297784\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 956870  3.980480 -4.844878         1011            0.000071         2.297784\n",
+       " 956871  3.982182 -4.845051         1011            0.000064         2.297784\n",
+       " 956872  3.983884 -4.845224         1011            0.000058         2.297784\n",
+       " 956873  3.985586 -4.845398         1011            0.000052         2.297784\n",
+       " 956874  3.987287 -4.845571         1011            0.000046         2.297784\n",
+       " \n",
+       " [757 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 957118  2.700801 -4.840189         1012            2.295028         2.297415\n",
+       " 957119  2.702502 -4.840086         1012            2.293884         2.297415\n",
+       " 957120  2.704204 -4.840009         1012            2.292737         2.297415\n",
+       " 957121  2.705906 -4.840009         1012            2.291587         2.297415\n",
+       " 957122  2.707608 -4.840009         1012            2.290436         2.297415\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 957870  3.980480 -4.842000         1012            0.000071         2.297415\n",
+       " 957871  3.982182 -4.842060         1012            0.000065         2.297415\n",
+       " 957872  3.983884 -4.842120         1012            0.000058         2.297415\n",
+       " 957873  3.985586 -4.842180         1012            0.000052         2.297415\n",
+       " 957874  3.987287 -4.842240         1012            0.000046         2.297415\n",
+       " \n",
+       " [757 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 958118  2.700801 -4.840009         1013            2.292695          2.29501\n",
+       " 958119  2.702502 -4.840009         1013            2.291562          2.29501\n",
+       " 958120  2.704204 -4.839989         1013            2.290418          2.29501\n",
+       " 958121  2.705906 -4.839914         1013            2.289241          2.29501\n",
+       " 958122  2.707608 -4.839839         1013            2.288063          2.29501\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 958870  3.980480 -4.843553         1013            0.000070          2.29501\n",
+       " 958871  3.982182 -4.843672         1013            0.000064          2.29501\n",
+       " 958872  3.983884 -4.843791         1013            0.000057          2.29501\n",
+       " 958873  3.985586 -4.843910         1013            0.000051          2.29501\n",
+       " 958874  3.987287 -4.844029         1013            0.000045          2.29501\n",
+       " \n",
+       " [757 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 959118  2.700801 -4.839822         1014            2.291423         2.292995\n",
+       " 959119  2.702502 -4.839911         1014            2.290302         2.292995\n",
+       " 959120  2.704204 -4.840001         1014            2.289182         2.292995\n",
+       " 959121  2.705906 -4.839807         1014            2.288064         2.292995\n",
+       " 959122  2.707608 -4.839585         1014            2.286947         2.292995\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 959870  3.980480 -4.844740         1014            0.000070         2.292995\n",
+       " 959871  3.982182 -4.844899         1014            0.000063         2.292995\n",
+       " 959872  3.983884 -4.845058         1014            0.000057         2.292995\n",
+       " 959873  3.985586 -4.845218         1014            0.000051         2.292995\n",
+       " 959874  3.987287 -4.845376         1014            0.000045         2.292995\n",
+       " \n",
+       " [757 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 960118  2.700801 -4.840139         1015            2.289233         2.290689\n",
+       " 960119  2.702502 -4.839980         1015            2.288073         2.290689\n",
+       " 960120  2.704204 -4.839905         1015            2.286936         2.290689\n",
+       " 960121  2.705906 -4.839830         1015            2.285798         2.290689\n",
+       " 960122  2.707608 -4.839780         1015            2.284669         2.290689\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 960870  3.980480 -4.844562         1015            0.000069         2.290689\n",
+       " 960871  3.982182 -4.844713         1015            0.000063         2.290689\n",
+       " 960872  3.983884 -4.844864         1015            0.000056         2.290689\n",
+       " 960873  3.985586 -4.845016         1015            0.000050         2.290689\n",
+       " 960874  3.987287 -4.845167         1015            0.000044         2.290689\n",
+       " \n",
+       " [757 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 961118  2.700801 -4.839780         1016            2.286923         2.289063\n",
+       " 961119  2.702502 -4.839780         1016            2.285810         2.289063\n",
+       " 961120  2.704204 -4.839791         1016            2.284692         2.289063\n",
+       " 961121  2.705906 -4.839867         1016            2.283541         2.289063\n",
+       " 961122  2.707608 -4.839943         1016            2.282391         2.289063\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 961870  3.980480 -4.842635         1016            0.000067         2.289063\n",
+       " 961871  3.982182 -4.842715         1016            0.000061         2.289063\n",
+       " 961872  3.983884 -4.842794         1016            0.000055         2.289063\n",
+       " 961873  3.985586 -4.842874         1016            0.000048         2.289063\n",
+       " 961874  3.987287 -4.842954         1016            0.000042         2.289063\n",
+       " \n",
+       " [757 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 962118  2.700801 -4.839841         1017            2.285534         2.286767\n",
+       " 962119  2.702502 -4.839652         1017            2.284408         2.286767\n",
+       " 962120  2.704204 -4.839804         1017            2.283293         2.286767\n",
+       " 962121  2.705906 -4.839957         1017            2.282179         2.286767\n",
+       " 962122  2.707608 -4.840009         1017            2.281035         2.286767\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 962870  3.980480 -4.843221         1017            0.000068         2.286767\n",
+       " 962871  3.982182 -4.843320         1017            0.000062         2.286767\n",
+       " 962872  3.983884 -4.843419         1017            0.000056         2.286767\n",
+       " 962873  3.985586 -4.843517         1017            0.000049         2.286767\n",
+       " 962874  3.987287 -4.843616         1017            0.000043         2.286767\n",
+       " \n",
+       " [757 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 963118  2.700801 -4.840113         1018            2.283562         2.286093\n",
+       " 963119  2.702502 -4.839844         1018            2.282449         2.286093\n",
+       " 963120  2.704204 -4.839898         1018            2.281315         2.286093\n",
+       " 963121  2.705906 -4.840053         1018            2.280175         2.286093\n",
+       " 963122  2.707608 -4.840208         1018            2.279034         2.286093\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 963870  3.980480 -4.844763         1018            0.000069         2.286093\n",
+       " 963871  3.982182 -4.844920         1018            0.000063         2.286093\n",
+       " 963872  3.983884 -4.845078         1018            0.000056         2.286093\n",
+       " 963873  3.985586 -4.845235         1018            0.000050         2.286093\n",
+       " 963874  3.987287 -4.845392         1018            0.000044         2.286093\n",
+       " \n",
+       " [757 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 964118  2.700801 -4.840194         1019            2.281789         2.283535\n",
+       " 964119  2.702502 -4.839969         1019            2.280669         2.283535\n",
+       " 964120  2.704204 -4.839743         1019            2.279549         2.283535\n",
+       " 964121  2.705906 -4.839551         1019            2.278428         2.283535\n",
+       " 964122  2.707608 -4.839551         1019            2.277300         2.283535\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 964870  3.980480 -4.844412         1019            0.000066         2.283535\n",
+       " 964871  3.982182 -4.844564         1019            0.000059         2.283535\n",
+       " 964872  3.983884 -4.844716         1019            0.000053         2.283535\n",
+       " 964873  3.985586 -4.844868         1019            0.000047         2.283535\n",
+       " 964874  3.987287 -4.845020         1019            0.000041         2.283535\n",
+       " \n",
+       " [757 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 965118  2.700801 -4.840071         1020            2.278902          2.28214\n",
+       " 965119  2.702502 -4.840193         1020            2.277767          2.28214\n",
+       " 965120  2.704204 -4.840191         1020            2.276616          2.28214\n",
+       " 965121  2.705906 -4.840116         1020            2.275457          2.28214\n",
+       " 965122  2.707608 -4.840041         1020            2.274297          2.28214\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 965870  3.980480 -4.843735         1020            0.000066          2.28214\n",
+       " 965871  3.982182 -4.843880         1020            0.000060          2.28214\n",
+       " 965872  3.983884 -4.844025         1020            0.000054          2.28214\n",
+       " 965873  3.985586 -4.844170         1020            0.000048          2.28214\n",
+       " 965874  3.987287 -4.844315         1020            0.000042          2.28214\n",
+       " \n",
+       " [757 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 966118  2.700801 -4.839849         1021            2.275065         2.278658\n",
+       " 966119  2.702502 -4.840150         1021            2.273901         2.278658\n",
+       " 966120  2.704204 -4.839925         1021            2.272794         2.278658\n",
+       " 966121  2.705906 -4.839700         1021            2.271688         2.278658\n",
+       " 966122  2.707608 -4.839577         1021            2.270563         2.278658\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 966870  3.980480 -4.843880         1021            0.000065         2.278658\n",
+       " 966871  3.982182 -4.843998         1021            0.000058         2.278658\n",
+       " 966872  3.983884 -4.844117         1021            0.000052         2.278658\n",
+       " 966873  3.985586 -4.844236         1021            0.000046         2.278658\n",
+       " 966874  3.987287 -4.844355         1021            0.000040         2.278658\n",
+       " \n",
+       " [757 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 967118  2.700801 -4.839912         1022            2.271944         2.275738\n",
+       " 967119  2.702502 -4.839614         1022            2.270825         2.275738\n",
+       " 967120  2.704204 -4.839758         1022            2.269714         2.275738\n",
+       " 967121  2.705906 -4.839901         1022            2.268604         2.275738\n",
+       " 967122  2.707608 -4.839990         1022            2.267478         2.275738\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 967870  3.980480 -4.844621         1022            0.000065         2.275738\n",
+       " 967871  3.982182 -4.844779         1022            0.000059         2.275738\n",
+       " 967872  3.983884 -4.844938         1022            0.000053         2.275738\n",
+       " 967873  3.985586 -4.845096         1022            0.000047         2.275738\n",
+       " 967874  3.987287 -4.845255         1022            0.000040         2.275738\n",
+       " \n",
+       " [757 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 968118  2.700801 -4.839896         1023            2.269808         2.271826\n",
+       " 968119  2.702502 -4.839820         1023            2.268684         2.271826\n",
+       " 968120  2.704204 -4.839895         1023            2.267550         2.271826\n",
+       " 968121  2.705906 -4.839970         1023            2.266417         2.271826\n",
+       " 968122  2.707608 -4.840081         1023            2.265267         2.271826\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 968870  3.980480 -4.845019         1023            0.000065         2.271826\n",
+       " 968871  3.982182 -4.845191         1023            0.000059         2.271826\n",
+       " 968872  3.983884 -4.845361         1023            0.000053         2.271826\n",
+       " 968873  3.985586 -4.845532         1023            0.000047         2.271826\n",
+       " 968874  3.987287 -4.845704         1023            0.000041         2.271826\n",
+       " \n",
+       " [757 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 969118  2.700801 -4.839894         1024            2.266541         2.270842\n",
+       " 969119  2.702502 -4.840049         1024            2.265401         2.270842\n",
+       " 969120  2.704204 -4.840124         1024            2.264263         2.270842\n",
+       " 969121  2.705906 -4.840199         1024            2.263125         2.270842\n",
+       " 969122  2.707608 -4.840202         1024            2.261971         2.270842\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 969870  3.980480 -4.843059         1024            0.000065         2.270842\n",
+       " 969871  3.982182 -4.843151         1024            0.000059         2.270842\n",
+       " 969872  3.983884 -4.843243         1024            0.000053         2.270842\n",
+       " 969873  3.985586 -4.843335         1024            0.000047         2.270842\n",
+       " 969874  3.987287 -4.843428         1024            0.000041         2.270842\n",
+       " \n",
+       " [757 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 970118  2.700801 -4.839795         1025            2.263610         2.266216\n",
+       " 970119  2.702502 -4.839871         1025            2.262478         2.266216\n",
+       " 970120  2.704204 -4.839948         1025            2.261346         2.266216\n",
+       " 970121  2.705906 -4.839994         1025            2.260208         2.266216\n",
+       " 970122  2.707608 -4.839917         1025            2.259049         2.266216\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 970870  3.980480 -4.844886         1025            0.000065         2.266216\n",
+       " 970871  3.982182 -4.845037         1025            0.000059         2.266216\n",
+       " 970872  3.983884 -4.845189         1025            0.000053         2.266216\n",
+       " 970873  3.985586 -4.845340         1025            0.000046         2.266216\n",
+       " 970874  3.987287 -4.845491         1025            0.000040         2.266216\n",
+       " \n",
+       " [757 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 971118  2.700801 -4.839993         1026            2.261668         2.264385\n",
+       " 971119  2.702502 -4.839843         1026            2.260540         2.264385\n",
+       " 971120  2.704204 -4.839693         1026            2.259411         2.264385\n",
+       " 971121  2.705906 -4.839551         1026            2.258279         2.264385\n",
+       " 971122  2.707608 -4.839551         1026            2.257097         2.264385\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 971869  3.978779 -4.844682         1026            0.000071         2.264385\n",
+       " 971870  3.980480 -4.844846         1026            0.000064         2.264385\n",
+       " 971871  3.982182 -4.845011         1026            0.000058         2.264385\n",
+       " 971872  3.983884 -4.845176         1026            0.000052         2.264385\n",
+       " 971873  3.985586 -4.845340         1026            0.000046         2.264385\n",
+       " \n",
+       " [756 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 972118  2.700801 -4.839780         1027            2.258033         2.261279\n",
+       " 972119  2.702502 -4.839780         1027            2.256851         2.261279\n",
+       " 972120  2.704204 -4.839780         1027            2.255735         2.261279\n",
+       " 972121  2.705906 -4.839780         1027            2.254619         2.261279\n",
+       " 972122  2.707608 -4.839754         1027            2.253477         2.261279\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 972869  3.978779 -4.842527         1027            0.000070         2.261279\n",
+       " 972870  3.980480 -4.842619         1027            0.000064         2.261279\n",
+       " 972871  3.982182 -4.842711         1027            0.000058         2.261279\n",
+       " 972872  3.983884 -4.842803         1027            0.000052         2.261279\n",
+       " 972873  3.985586 -4.842895         1027            0.000046         2.261279\n",
+       " \n",
+       " [756 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 973118  2.700801 -4.839979         1028            2.257224         2.259762\n",
+       " 973119  2.702502 -4.839939         1028            2.256099         2.259762\n",
+       " 973120  2.704204 -4.839862         1028            2.254981         2.259762\n",
+       " 973121  2.705906 -4.839786         1028            2.253862         2.259762\n",
+       " 973122  2.707608 -4.839921         1028            2.252685         2.259762\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 973870  3.980480 -4.844047         1028            0.000065         2.259762\n",
+       " 973871  3.982182 -4.844178         1028            0.000059         2.259762\n",
+       " 973872  3.983884 -4.844309         1028            0.000053         2.259762\n",
+       " 973873  3.985586 -4.844440         1028            0.000047         2.259762\n",
+       " 973874  3.987287 -4.844572         1028            0.000040         2.259762\n",
+       " \n",
+       " [757 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 974118  2.700801 -4.840467         1029            2.253464         2.255285\n",
+       " 974119  2.702502 -4.840467         1029            2.252339         2.255285\n",
+       " 974120  2.704204 -4.840467         1029            2.251213         2.255285\n",
+       " 974121  2.705906 -4.840467         1029            2.250088         2.255285\n",
+       " 974122  2.707608 -4.840242         1029            2.248908         2.255285\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 974869  3.978779 -4.843127         1029            0.000070         2.255285\n",
+       " 974870  3.980480 -4.843239         1029            0.000064         2.255285\n",
+       " 974871  3.982182 -4.843351         1029            0.000057         2.255285\n",
+       " 974872  3.983884 -4.843464         1029            0.000051         2.255285\n",
+       " 974873  3.985586 -4.843576         1029            0.000045         2.255285\n",
+       " \n",
+       " [756 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 975118  2.700801 -4.839939         1030            2.251681         2.254504\n",
+       " 975119  2.702502 -4.840238         1030            2.250508         2.254504\n",
+       " 975120  2.704204 -4.840238         1030            2.249379         2.254504\n",
+       " 975121  2.705906 -4.840238         1030            2.248250         2.254504\n",
+       " 975122  2.707608 -4.840227         1030            2.247118         2.254504\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 975870  3.980480 -4.843593         1030            0.000065         2.254504\n",
+       " 975871  3.982182 -4.843725         1030            0.000059         2.254504\n",
+       " 975872  3.983884 -4.843856         1030            0.000053         2.254504\n",
+       " 975873  3.985586 -4.843988         1030            0.000046         2.254504\n",
+       " 975874  3.987287 -4.844120         1030            0.000040         2.254504\n",
+       " \n",
+       " [757 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 976118  2.700801 -4.839772         1031            2.248678         2.250901\n",
+       " 976119  2.702502 -4.839697         1031            2.247523         2.250901\n",
+       " 976120  2.704204 -4.839622         1031            2.246368         2.250901\n",
+       " 976121  2.705906 -4.839560         1031            2.245212         2.250901\n",
+       " 976122  2.707608 -4.839708         1031            2.244047         2.250901\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 976869  3.978779 -4.845641         1031            0.000069         2.250901\n",
+       " 976870  3.980480 -4.845852         1031            0.000063         2.250901\n",
+       " 976871  3.982182 -4.846064         1031            0.000057         2.250901\n",
+       " 976872  3.983884 -4.846275         1031            0.000051         2.250901\n",
+       " 976873  3.985586 -4.846487         1031            0.000044         2.250901\n",
+       " \n",
+       " [756 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 977118  2.700801 -4.839780         1032            2.249273         2.249515\n",
+       " 977119  2.702502 -4.839780         1032            2.248162         2.249515\n",
+       " 977120  2.704204 -4.839780         1032            2.247051         2.249515\n",
+       " 977121  2.705906 -4.839825         1032            2.245925         2.249515\n",
+       " 977122  2.707608 -4.840057         1032            2.244739         2.249515\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 977869  3.978779 -4.844562         1032            0.000070         2.249515\n",
+       " 977870  3.980480 -4.844706         1032            0.000064         2.249515\n",
+       " 977871  3.982182 -4.844850         1032            0.000058         2.249515\n",
+       " 977872  3.983884 -4.844994         1032            0.000052         2.249515\n",
+       " 977873  3.985586 -4.845138         1032            0.000046         2.249515\n",
+       " \n",
+       " [756 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 978118  2.700801 -4.839834         1033            2.245251         2.249211\n",
+       " 978119  2.702502 -4.839951         1033            2.244092         2.249211\n",
+       " 978120  2.704204 -4.840009         1033            2.242939         2.249211\n",
+       " 978121  2.705906 -4.840009         1033            2.241792         2.249211\n",
+       " 978122  2.707608 -4.840009         1033            2.240645         2.249211\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 978869  3.978779 -4.844702         1033            0.000069         2.249211\n",
+       " 978870  3.980480 -4.844873         1033            0.000062         2.249211\n",
+       " 978871  3.982182 -4.845045         1033            0.000056         2.249211\n",
+       " 978872  3.983884 -4.845216         1033            0.000050         2.249211\n",
+       " 978873  3.985586 -4.845387         1033            0.000044         2.249211\n",
+       " \n",
+       " [756 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 979118  2.700801 -4.840215         1034            2.243317         2.246128\n",
+       " 979119  2.702502 -4.840065         1034            2.242166         2.246128\n",
+       " 979120  2.704204 -4.839915         1034            2.241015         2.246128\n",
+       " 979121  2.705906 -4.839780         1034            2.239862         2.246128\n",
+       " 979122  2.707608 -4.839780         1034            2.238689         2.246128\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 979869  3.978779 -4.843803         1034            0.000070         2.246128\n",
+       " 979870  3.980480 -4.843915         1034            0.000064         2.246128\n",
+       " 979871  3.982182 -4.844026         1034            0.000058         2.246128\n",
+       " 979872  3.983884 -4.844137         1034            0.000052         2.246128\n",
+       " 979873  3.985586 -4.844249         1034            0.000046         2.246128\n",
+       " \n",
+       " [756 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 980118  2.700801 -4.839411         1035            2.238873         2.242619\n",
+       " 980119  2.702502 -4.839430         1035            2.237740         2.242619\n",
+       " 980120  2.704204 -4.839582         1035            2.236634         2.242619\n",
+       " 980121  2.705906 -4.839735         1035            2.235528         2.242619\n",
+       " 980122  2.707608 -4.839780         1035            2.234357         2.242619\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 980869  3.978779 -4.844203         1035            0.000069         2.242619\n",
+       " 980870  3.980480 -4.844334         1035            0.000062         2.242619\n",
+       " 980871  3.982182 -4.844465         1035            0.000056         2.242619\n",
+       " 980872  3.983884 -4.844597         1035            0.000050         2.242619\n",
+       " 980873  3.985586 -4.844728         1035            0.000044         2.242619\n",
+       " \n",
+       " [756 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 981118  2.700801 -4.840230         1036            2.236378         2.240222\n",
+       " 981119  2.702502 -4.840155         1036            2.235236         2.240222\n",
+       " 981120  2.704204 -4.840080         1036            2.234094         2.240222\n",
+       " 981121  2.705906 -4.840009         1036            2.232952         2.240222\n",
+       " 981122  2.707608 -4.840009         1036            2.231805         2.240222\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 981869  3.978779 -4.844457         1036            0.000070         2.240222\n",
+       " 981870  3.980480 -4.844621         1036            0.000064         2.240222\n",
+       " 981871  3.982182 -4.844785         1036            0.000058         2.240222\n",
+       " 981872  3.983884 -4.844949         1036            0.000052         2.240222\n",
+       " 981873  3.985586 -4.845112         1036            0.000046         2.240222\n",
+       " \n",
+       " [756 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 982118  2.700801 -4.840235         1037            2.233334         2.235813\n",
+       " 982119  2.702502 -4.840083         1037            2.232143         2.235813\n",
+       " 982120  2.704204 -4.839931         1037            2.230953         2.235813\n",
+       " 982121  2.705906 -4.839780         1037            2.229764         2.235813\n",
+       " 982122  2.707608 -4.839780         1037            2.228654         2.235813\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 982869  3.978779 -4.844383         1037            0.000068         2.235813\n",
+       " 982870  3.980480 -4.844527         1037            0.000062         2.235813\n",
+       " 982871  3.982182 -4.844672         1037            0.000056         2.235813\n",
+       " 982872  3.983884 -4.844816         1037            0.000049         2.235813\n",
+       " 982873  3.985586 -4.844961         1037            0.000043         2.235813\n",
+       " \n",
+       " [756 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 983118  2.700801 -4.840009         1038            2.233628          2.23462\n",
+       " 983119  2.702502 -4.840009         1038            2.232481          2.23462\n",
+       " 983120  2.704204 -4.840009         1038            2.231335          2.23462\n",
+       " 983121  2.705906 -4.840009         1038            2.230197          2.23462\n",
+       " 983122  2.707608 -4.840009         1038            2.229063          2.23462\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 983869  3.978779 -4.843744         1038            0.000069          2.23462\n",
+       " 983870  3.980480 -4.843876         1038            0.000062          2.23462\n",
+       " 983871  3.982182 -4.844007         1038            0.000056          2.23462\n",
+       " 983872  3.983884 -4.844139         1038            0.000050          2.23462\n",
+       " 983873  3.985586 -4.844270         1038            0.000044          2.23462\n",
+       " \n",
+       " [756 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 984118  2.700801 -4.839802         1039            2.230894         2.234167\n",
+       " 984119  2.702502 -4.839879         1039            2.229717         2.234167\n",
+       " 984120  2.704204 -4.839954         1039            2.228539         2.234167\n",
+       " 984121  2.705906 -4.840052         1039            2.227371         2.234167\n",
+       " 984122  2.707608 -4.840202         1039            2.226224         2.234167\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 984869  3.978779 -4.843594         1039            0.000069         2.234167\n",
+       " 984870  3.980480 -4.843704         1039            0.000063         2.234167\n",
+       " 984871  3.982182 -4.843814         1039            0.000057         2.234167\n",
+       " 984872  3.983884 -4.843925         1039            0.000051         2.234167\n",
+       " 984873  3.985586 -4.844035         1039            0.000045         2.234167\n",
+       " \n",
+       " [756 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 985118  2.700801 -4.839963         1040            2.231113         2.231732\n",
+       " 985119  2.702502 -4.839874         1040            2.229987         2.231732\n",
+       " 985120  2.704204 -4.839784         1040            2.228861         2.231732\n",
+       " 985121  2.705906 -4.839709         1040            2.227716         2.231732\n",
+       " 985122  2.707608 -4.839633         1040            2.226569         2.231732\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 985869  3.978779 -4.845290         1040            0.000070         2.231732\n",
+       " 985870  3.980480 -4.845472         1040            0.000064         2.231732\n",
+       " 985871  3.982182 -4.845654         1040            0.000058         2.231732\n",
+       " 985872  3.983884 -4.845836         1040            0.000052         2.231732\n",
+       " 985873  3.985586 -4.846018         1040            0.000045         2.231732\n",
+       " \n",
+       " [756 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 986118  2.700801 -4.839984         1041            2.225808         2.230144\n",
+       " 986119  2.702502 -4.839908         1041            2.224658         2.230144\n",
+       " 986120  2.704204 -4.839831         1041            2.223507         2.230144\n",
+       " 986121  2.705906 -4.839805         1041            2.222342         2.230144\n",
+       " 986122  2.707608 -4.839880         1041            2.221148         2.230144\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 986869  3.978779 -4.844954         1041            0.000068         2.230144\n",
+       " 986870  3.980480 -4.845124         1041            0.000062         2.230144\n",
+       " 986871  3.982182 -4.845294         1041            0.000056         2.230144\n",
+       " 986872  3.983884 -4.845463         1041            0.000049         2.230144\n",
+       " 986873  3.985586 -4.845633         1041            0.000043         2.230144\n",
+       " \n",
+       " [756 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 987118  2.700801 -4.839741         1042            2.225935         2.225667\n",
+       " 987119  2.702502 -4.839655         1042            2.224756         2.225667\n",
+       " 987120  2.704204 -4.839571         1042            2.223576         2.225667\n",
+       " 987121  2.705906 -4.839609         1042            2.222442         2.225667\n",
+       " 987122  2.707608 -4.839683         1042            2.221321         2.225667\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 987869  3.978779 -4.844376         1042            0.000068         2.225667\n",
+       " 987870  3.980480 -4.844521         1042            0.000062         2.225667\n",
+       " 987871  3.982182 -4.844665         1042            0.000056         2.225667\n",
+       " 987872  3.983884 -4.844810         1042            0.000050         2.225667\n",
+       " 987873  3.985586 -4.844954         1042            0.000044         2.225667\n",
+       " \n",
+       " [756 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 988118  2.700801 -4.839780         1043            2.224030         2.226048\n",
+       " 988119  2.702502 -4.839848         1043            2.222905         2.226048\n",
+       " 988120  2.704204 -4.839924         1043            2.221760         2.226048\n",
+       " 988121  2.705906 -4.840000         1043            2.220614         2.226048\n",
+       " 988122  2.707608 -4.839942         1043            2.219456         2.226048\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 988869  3.978779 -4.843390         1043            0.000068         2.226048\n",
+       " 988870  3.980480 -4.843502         1043            0.000062         2.226048\n",
+       " 988871  3.982182 -4.843613         1043            0.000056         2.226048\n",
+       " 988872  3.983884 -4.843724         1043            0.000049         2.226048\n",
+       " 988873  3.985586 -4.843836         1043            0.000043         2.226048\n",
+       " \n",
+       " [756 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 989118  2.700801 -4.839994         1044            2.223639         2.224265\n",
+       " 989119  2.702502 -4.839920         1044            2.222502         2.224265\n",
+       " 989120  2.704204 -4.839844         1044            2.221364         2.224265\n",
+       " 989121  2.705906 -4.839791         1044            2.220224         2.224265\n",
+       " 989122  2.707608 -4.839865         1044            2.219072         2.224265\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 989869  3.978779 -4.843392         1044            0.000068         2.224265\n",
+       " 989870  3.980480 -4.843503         1044            0.000062         2.224265\n",
+       " 989871  3.982182 -4.843614         1044            0.000056         2.224265\n",
+       " 989872  3.983884 -4.843725         1044            0.000049         2.224265\n",
+       " 989873  3.985586 -4.843836         1044            0.000043         2.224265\n",
+       " \n",
+       " [756 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 990118  2.700801 -4.840009         1045            2.222690         2.224319\n",
+       " 990119  2.702502 -4.840009         1045            2.221500         2.224319\n",
+       " 990120  2.704204 -4.840147         1045            2.220377         2.224319\n",
+       " 990121  2.705906 -4.840292         1045            2.219259         2.224319\n",
+       " 990122  2.707608 -4.840438         1045            2.218141         2.224319\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 990869  3.978779 -4.845442         1045            0.000067         2.224319\n",
+       " 990870  3.980480 -4.845612         1045            0.000061         2.224319\n",
+       " 990871  3.982182 -4.845782         1045            0.000054         2.224319\n",
+       " 990872  3.983884 -4.845952         1045            0.000048         2.224319\n",
+       " 990873  3.985586 -4.846121         1045            0.000042         2.224319\n",
+       " \n",
+       " [756 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 991118  2.700801 -4.839984         1046            2.219331         2.222386\n",
+       " 991119  2.702502 -4.839909         1046            2.218188         2.222386\n",
+       " 991120  2.704204 -4.839834         1046            2.217046         2.222386\n",
+       " 991121  2.705906 -4.839823         1046            2.215904         2.222386\n",
+       " 991122  2.707608 -4.839973         1046            2.214762         2.222386\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 991869  3.978779 -4.843778         1046            0.000067         2.222386\n",
+       " 991870  3.980480 -4.843908         1046            0.000061         2.222386\n",
+       " 991871  3.982182 -4.844038         1046            0.000055         2.222386\n",
+       " 991872  3.983884 -4.844169         1046            0.000049         2.222386\n",
+       " 991873  3.985586 -4.844300         1046            0.000042         2.222386\n",
+       " \n",
+       " [756 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 992118  2.700801 -4.840049         1047            2.215844         2.220181\n",
+       " 992119  2.702502 -4.840134         1047            2.214705         2.220181\n",
+       " 992120  2.704204 -4.840219         1047            2.213565         2.220181\n",
+       " 992121  2.705906 -4.840122         1047            2.212430         2.220181\n",
+       " 992122  2.707608 -4.839972         1047            2.211297         2.220181\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 992869  3.978779 -4.844220         1047            0.000068         2.220181\n",
+       " 992870  3.980480 -4.844350         1047            0.000062         2.220181\n",
+       " 992871  3.982182 -4.844480         1047            0.000055         2.220181\n",
+       " 992872  3.983884 -4.844610         1047            0.000049         2.220181\n",
+       " 992873  3.985586 -4.844740         1047            0.000043         2.220181\n",
+       " \n",
+       " [756 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 993118  2.700801 -4.839780         1048            2.213871         2.215846\n",
+       " 993119  2.702502 -4.839780         1048            2.212737         2.215846\n",
+       " 993120  2.704204 -4.839814         1048            2.211594         2.215846\n",
+       " 993121  2.705906 -4.839964         1048            2.210416         2.215846\n",
+       " 993122  2.707608 -4.840114         1048            2.209239         2.215846\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 993869  3.978779 -4.846198         1048            0.000067         2.215846\n",
+       " 993870  3.980480 -4.846400         1048            0.000061         2.215846\n",
+       " 993871  3.982182 -4.846602         1048            0.000055         2.215846\n",
+       " 993872  3.983884 -4.846804         1048            0.000049         2.215846\n",
+       " 993873  3.985586 -4.847006         1048            0.000043         2.215846\n",
+       " \n",
+       " [756 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 994118  2.700801 -4.840051         1049            2.212070         2.214088\n",
+       " 994119  2.702502 -4.840134         1049            2.210934         2.214088\n",
+       " 994120  2.704204 -4.840216         1049            2.209797         2.214088\n",
+       " 994121  2.705906 -4.840238         1049            2.208665         2.214088\n",
+       " 994122  2.707608 -4.840238         1049            2.207536         2.214088\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 994869  3.978779 -4.844670         1049            0.000066         2.214088\n",
+       " 994870  3.980480 -4.844813         1049            0.000059         2.214088\n",
+       " 994871  3.982182 -4.844956         1049            0.000053         2.214088\n",
+       " 994872  3.983884 -4.845099         1049            0.000047         2.214088\n",
+       " 994873  3.985586 -4.845242         1049            0.000041         2.214088\n",
+       " \n",
+       " [756 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 995118  2.700801 -4.840327         1050            2.211028         2.213699\n",
+       " 995119  2.702502 -4.840027         1050            2.209881         2.213699\n",
+       " 995120  2.704204 -4.839794         1050            2.208728         2.213699\n",
+       " 995121  2.705906 -4.839869         1050            2.207546         2.213699\n",
+       " 995122  2.707608 -4.839944         1050            2.206365         2.213699\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 995869  3.978779 -4.843835         1050            0.000067         2.213699\n",
+       " 995870  3.980480 -4.843952         1050            0.000061         2.213699\n",
+       " 995871  3.982182 -4.844068         1050            0.000055         2.213699\n",
+       " 995872  3.983884 -4.844184         1050            0.000049         2.213699\n",
+       " 995873  3.985586 -4.844301         1050            0.000043         2.213699\n",
+       " \n",
+       " [756 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 996118  2.700801 -4.840405         1051            2.209907         2.212026\n",
+       " 996119  2.702502 -4.840270         1051            2.208778         2.212026\n",
+       " 996120  2.704204 -4.840180         1051            2.207619         2.212026\n",
+       " 996121  2.705906 -4.840104         1051            2.206451         2.212026\n",
+       " 996122  2.707608 -4.840028         1051            2.205283         2.212026\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 996869  3.978779 -4.846255         1051            0.000066         2.212026\n",
+       " 996870  3.980480 -4.846450         1051            0.000060         2.212026\n",
+       " 996871  3.982182 -4.846645         1051            0.000054         2.212026\n",
+       " 996872  3.983884 -4.846840         1051            0.000048         2.212026\n",
+       " 996873  3.985586 -4.847035         1051            0.000042         2.212026\n",
+       " \n",
+       " [756 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 997118  2.700801 -4.840238         1052            2.207084         2.209474\n",
+       " 997119  2.702502 -4.840238         1052            2.205927         2.209474\n",
+       " 997120  2.704204 -4.840106         1052            2.204806         2.209474\n",
+       " 997121  2.705906 -4.839957         1052            2.203689         2.209474\n",
+       " 997122  2.707608 -4.839809         1052            2.202572         2.209474\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 997869  3.978779 -4.844010         1052            0.000066         2.209474\n",
+       " 997870  3.980480 -4.844146         1052            0.000059         2.209474\n",
+       " 997871  3.982182 -4.844283         1052            0.000053         2.209474\n",
+       " 997872  3.983884 -4.844420         1052            0.000047         2.209474\n",
+       " 997873  3.985586 -4.844557         1052            0.000041         2.209474\n",
+       " \n",
+       " [756 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 998118  2.700801 -4.840195         1053            2.205235         2.207264\n",
+       " 998119  2.702502 -4.840045         1053            2.204079         2.207264\n",
+       " 998120  2.704204 -4.839895         1053            2.202924         2.207264\n",
+       " 998121  2.705906 -4.839798         1053            2.201764         2.207264\n",
+       " 998122  2.707608 -4.839873         1053            2.200591         2.207264\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 998869  3.978779 -4.844251         1053            0.000066         2.207264\n",
+       " 998870  3.980480 -4.844380         1053            0.000060         2.207264\n",
+       " 998871  3.982182 -4.844510         1053            0.000054         2.207264\n",
+       " 998872  3.983884 -4.844640         1053            0.000048         2.207264\n",
+       " 998873  3.985586 -4.844769         1053            0.000042         2.207264\n",
+       " \n",
+       " [756 rows x 5 columns],\n",
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 999118  2.700801 -4.840053         1054            2.203581         2.205283\n",
+       " 999119  2.702502 -4.840145         1054            2.202496         2.205283\n",
+       " 999120  2.704204 -4.840238         1054            2.201411         2.205283\n",
+       " 999121  2.705906 -4.840086         1054            2.200243         2.205283\n",
+       " 999122  2.707608 -4.839933         1054            2.199075         2.205283\n",
+       " ...          ...       ...          ...                 ...              ...\n",
+       " 999869  3.978779 -4.843167         1054            0.000066         2.205283\n",
+       " 999870  3.980480 -4.843284         1054            0.000060         2.205283\n",
+       " 999871  3.982182 -4.843401         1054            0.000054         2.205283\n",
+       " 999872  3.983884 -4.843518         1054            0.000048         2.205283\n",
+       " 999873  3.985586 -4.843635         1054            0.000042         2.205283\n",
+       " \n",
+       " [756 rows x 5 columns],\n",
+       " ...]"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "structured_data_list[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 141,
+   "id": "54fa9d31",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "10\n"
+     ]
+    }
+   ],
+   "source": [
+    "mid_window_index = len(cycle_window_labels[1])//2\n",
+    "print(mid_window)\n",
+    "low = np.array(cycle_window_labels[0])[0]\n",
+    "mid = np.array(cycle_window_labels[0])[mid_window_index]\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 148,
+   "id": "df911b12",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[    cycle_index  discharge_capacity\n",
+       " 20           25            3.809959\n",
+       " 21           26            3.807600\n",
+       " 22           27            3.804501\n",
+       " 23           28            3.801214\n",
+       " 24           29            3.798881\n",
+       " 25           30            3.794310\n",
+       " 26           31            3.791211\n",
+       " 27           32            3.789114\n",
+       " 28           33            3.786210\n",
+       " 29           34            3.781344\n",
+       " 30           35            3.780261\n",
+       " 31           41            3.800649\n",
+       " 32           42            3.793537\n",
+       " 33           43            3.788503\n",
+       " 34           44            3.783945\n",
+       " 35           45            3.779441\n",
+       " 36           46            3.774118\n",
+       " 37           47            3.769795\n",
+       " 38           48            3.764975\n",
+       " 39           49            3.760485,\n",
+       "     cycle_index  discharge_capacity\n",
+       " 40           50            3.756755\n",
+       " 41           51            3.752721\n",
+       " 42           52            3.748500\n",
+       " 43           53            3.744379\n",
+       " 44           54            3.740676\n",
+       " 45           55            3.736864\n",
+       " 46           56            3.732623\n",
+       " 47           57            3.728455\n",
+       " 48           58            3.724294\n",
+       " 49           59            3.720187\n",
+       " 50           60            3.716792\n",
+       " 51           61            3.712786\n",
+       " 52           62            3.708961\n",
+       " 53           63            3.703563\n",
+       " 54           64            3.699517\n",
+       " 55           65            3.695847\n",
+       " 56           66            3.691571\n",
+       " 57           67            3.688130\n",
+       " 58           68            3.683243\n",
+       " 59           69            3.679660,\n",
+       "     cycle_index  discharge_capacity\n",
+       " 60           70            3.674135\n",
+       " 61           71            3.670753\n",
+       " 62           72            3.665436\n",
+       " 63           73            3.661188\n",
+       " 64           74            3.657551\n",
+       " 65           75            3.653269\n",
+       " 66           76            3.647220\n",
+       " 67           77            3.643039\n",
+       " 68           78            3.639153\n",
+       " 69           79            3.634918\n",
+       " 70           80            3.630609\n",
+       " 71           81            3.625353\n",
+       " 72           82            3.619780\n",
+       " 73           83            3.614880\n",
+       " 74           84            3.610417\n",
+       " 75           85            3.606189\n",
+       " 76           86            3.601429\n",
+       " 77           87            3.596516\n",
+       " 78           88            3.592422\n",
+       " 79           89            3.587185,\n",
+       "     cycle_index  discharge_capacity\n",
+       " 80           90            3.582561\n",
+       " 81           91            3.577116\n",
+       " 82           92            3.571073\n",
+       " 83           93            3.565675\n",
+       " 84           94            3.560936\n",
+       " 85           95            3.556258\n",
+       " 86           96            3.550490\n",
+       " 87           97            3.546296\n",
+       " 88           98            3.540844\n",
+       " 89           99            3.536072\n",
+       " 90          100            3.530082\n",
+       " 91          101            3.525222\n",
+       " 92          102            3.520664\n",
+       " 93          103            3.514769\n",
+       " 94          104            3.510864\n",
+       " 95          105            3.505459\n",
+       " 96          106            3.500041\n",
+       " 97          107            3.493656\n",
+       " 98          108            3.487949\n",
+       " 99          109            3.483035,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 100          110            3.476904\n",
+       " 101          111            3.470976\n",
+       " 102          112            3.466062\n",
+       " 103          113            3.460395\n",
+       " 104          114            3.454675\n",
+       " 105          115            3.449943\n",
+       " 106          116            3.444236\n",
+       " 107          117            3.438179\n",
+       " 108          118            3.432835\n",
+       " 109          119            3.427982\n",
+       " 110          120            3.422497\n",
+       " 111          121            3.416554\n",
+       " 112          122            3.411432\n",
+       " 113          123            3.404744\n",
+       " 114          124            3.398015\n",
+       " 115          125            3.392449\n",
+       " 116          126            3.386782\n",
+       " 117          127            3.380961\n",
+       " 118          128            3.376451\n",
+       " 119          129            3.370368,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 120          130            3.364385\n",
+       " 121          131            3.357831\n",
+       " 122          132            3.351936\n",
+       " 123          133            3.346760\n",
+       " 124          134            3.340865\n",
+       " 125          135            3.336482\n",
+       " 126          136            3.328375\n",
+       " 127          137            3.323132\n",
+       " 128          138            3.315570\n",
+       " 129          139            3.309890\n",
+       " 130          140            3.304949\n",
+       " 131          146            3.525733\n",
+       " 132          147            3.499732\n",
+       " 133          148            3.482316\n",
+       " 134          149            3.466398\n",
+       " 135          150            3.451220\n",
+       " 136          151            3.437036\n",
+       " 137          152            3.424748\n",
+       " 138          153            3.411701\n",
+       " 139          154            3.399366,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 140          155            3.386447\n",
+       " 141          156            3.375348\n",
+       " 142          157            3.364533\n",
+       " 143          158            3.352474\n",
+       " 144          159            3.342505\n",
+       " 145          160            3.333860\n",
+       " 146          161            3.323677\n",
+       " 147          162            3.313150\n",
+       " 148          163            3.304095\n",
+       " 149          164            3.295242\n",
+       " 150          165            3.284165\n",
+       " 151          166            3.277288\n",
+       " 152          167            3.268785\n",
+       " 153          168            3.260732\n",
+       " 154          169            3.253452\n",
+       " 155          170            3.244653\n",
+       " 156          171            3.236539\n",
+       " 157          172            3.228607\n",
+       " 158          173            3.219916\n",
+       " 159          174            3.212616,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 160          175            3.204469\n",
+       " 161          176            3.198137\n",
+       " 162          177            3.190977\n",
+       " 163          178            3.181271\n",
+       " 164          179            3.175396\n",
+       " 165          180            3.167605\n",
+       " 166          181            3.160211\n",
+       " 167          182            3.153549\n",
+       " 168          183            3.148797\n",
+       " 169          184            3.141477\n",
+       " 170          185            3.134762\n",
+       " 171          186            3.126164\n",
+       " 172          187            3.119193\n",
+       " 173          188            3.113923\n",
+       " 174          189            3.106751\n",
+       " 175          190            3.100096\n",
+       " 176          191            3.094490\n",
+       " 177          192            3.087835\n",
+       " 178          193            3.080643\n",
+       " 179          194            3.075648,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 180          195            3.069087\n",
+       " 181          196            3.063253\n",
+       " 182          197            3.057344\n",
+       " 183          198            3.051826\n",
+       " 184          199            3.046952\n",
+       " 185          200            3.039551\n",
+       " 186          201            3.032876\n",
+       " 187          202            3.026846\n",
+       " 188          203            3.022565\n",
+       " 189          204            3.016360\n",
+       " 190          205            3.012192\n",
+       " 191          206            3.006848\n",
+       " 192          207            3.000873\n",
+       " 193          208            2.995213\n",
+       " 194          209            2.989116\n",
+       " 195          210            2.982965\n",
+       " 196          211            2.977460\n",
+       " 197          212            2.972950\n",
+       " 198          213            2.969488\n",
+       " 199          214            2.963546,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 200          215            2.958652\n",
+       " 201          216            2.953234\n",
+       " 202          217            2.948838\n",
+       " 203          218            2.941632\n",
+       " 204          219            2.936449\n",
+       " 205          220            2.931690\n",
+       " 206          221            2.928376\n",
+       " 207          222            2.923449\n",
+       " 208          223            2.917654\n",
+       " 209          224            2.912566\n",
+       " 210          225            2.908002\n",
+       " 211          226            2.900184\n",
+       " 212          227            2.896117\n",
+       " 213          228            2.892601\n",
+       " 214          229            2.886975\n",
+       " 215          230            2.884058\n",
+       " 216          231            2.877511\n",
+       " 217          232            2.872832\n",
+       " 218          233            2.868866\n",
+       " 219          234            2.864006,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 220          235            2.858575\n",
+       " 221          236            2.855026\n",
+       " 222          237            2.849823\n",
+       " 223          238            2.845809\n",
+       " 224          239            2.841615\n",
+       " 225          240            2.837972\n",
+       " 226          241            2.832850\n",
+       " 227          242            2.827304\n",
+       " 228          243            2.822034\n",
+       " 229          244            2.819359\n",
+       " 230          245            2.817436\n",
+       " 231          251            3.222927\n",
+       " 232          252            3.163155\n",
+       " 233          253            3.124208\n",
+       " 234          254            3.094920\n",
+       " 235          255            3.068483\n",
+       " 236          256            3.045493\n",
+       " 237          257            3.024608\n",
+       " 238          258            3.006755\n",
+       " 239          259            2.989284,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 240          260            2.973682\n",
+       " 241          261            2.958746\n",
+       " 242          262            2.946156\n",
+       " 243          263            2.932530\n",
+       " 244          264            2.920101\n",
+       " 245          265            2.911040\n",
+       " 246          266            2.901474\n",
+       " 247          267            2.890585\n",
+       " 248          268            2.881215\n",
+       " 249          269            2.872321\n",
+       " 250          270            2.863059\n",
+       " 251          271            2.854199\n",
+       " 252          272            2.846630\n",
+       " 253          273            2.839505\n",
+       " 254          274            2.833313\n",
+       " 255          275            2.826793\n",
+       " 256          276            2.818593\n",
+       " 257          277            2.811783\n",
+       " 258          278            2.806453\n",
+       " 259          279            2.799146,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 260          280            2.793156\n",
+       " 261          281            2.787752\n",
+       " 262          282            2.783497\n",
+       " 263          283            2.779269\n",
+       " 264          284            2.771807\n",
+       " 265          285            2.767008\n",
+       " 266          286            2.762148\n",
+       " 267          287            2.757308\n",
+       " 268          288            2.751359\n",
+       " 269          289            2.746687\n",
+       " 270          290            2.743373\n",
+       " 271          291            2.738534\n",
+       " 272          292            2.733620\n",
+       " 273          293            2.728867\n",
+       " 274          294            2.724215\n",
+       " 275          295            2.719517\n",
+       " 276          296            2.713951\n",
+       " 277          297            2.711941\n",
+       " 278          298            2.708035\n",
+       " 279          299            2.705481,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 280          300            2.701018\n",
+       " 281          301            2.696434\n",
+       " 282          302            2.691910\n",
+       " 283          303            2.687594\n",
+       " 284          304            2.684529\n",
+       " 285          305            2.681484\n",
+       " 286          306            2.678990\n",
+       " 287          307            2.674412\n",
+       " 288          308            2.671851\n",
+       " 289          309            2.668033\n",
+       " 290          310            2.664578\n",
+       " 291          311            2.662568\n",
+       " 292          312            2.658481\n",
+       " 293          313            2.655590\n",
+       " 294          314            2.652115\n",
+       " 295          315            2.650926\n",
+       " 296          316            2.647598\n",
+       " 297          317            2.644130\n",
+       " 298          318            2.640560\n",
+       " 299          319            2.636849,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 300          320            2.635909\n",
+       " 301          321            2.633153\n",
+       " 302          322            2.630255\n",
+       " 303          323            2.627372\n",
+       " 304          324            2.625174\n",
+       " 305          325            2.623883\n",
+       " 306          326            2.618364\n",
+       " 307          327            2.616482\n",
+       " 308          328            2.616146\n",
+       " 309          329            2.613914\n",
+       " 310          330            2.613417\n",
+       " 311          331            2.608308\n",
+       " 312          332            2.606386\n",
+       " 313          333            2.605828\n",
+       " 314          334            2.600921\n",
+       " 315          335            2.598138\n",
+       " 316          336            2.596410\n",
+       " 317          337            2.594898\n",
+       " 318          338            2.595241\n",
+       " 319          339            2.590071,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 320          340            2.587860\n",
+       " 321          341            2.584653\n",
+       " 322          342            2.584102\n",
+       " 323          343            2.581326\n",
+       " 324          344            2.580042\n",
+       " 325          345            2.580183\n",
+       " 326          346            2.576748\n",
+       " 327          347            2.573199\n",
+       " 328          348            2.571693\n",
+       " 329          349            2.569650\n",
+       " 330          350            2.567667\n",
+       " 331          356            2.985883\n",
+       " 332          357            2.932012\n",
+       " 333          358            2.891734\n",
+       " 334          359            2.859563\n",
+       " 335          360            2.835283\n",
+       " 336          361            2.807978\n",
+       " 337          362            2.788646\n",
+       " 338          363            2.770684\n",
+       " 339          364            2.754754,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 340          365            2.740086\n",
+       " 341          366            2.726333\n",
+       " 342          367            2.714509\n",
+       " 343          368            2.703902\n",
+       " 344          369            2.694726\n",
+       " 345          370            2.685712\n",
+       " 346          371            2.675259\n",
+       " 347          372            2.666433\n",
+       " 348          373            2.659073\n",
+       " 349          374            2.652384\n",
+       " 350          375            2.646005\n",
+       " 351          376            2.640090\n",
+       " 352          377            2.632675\n",
+       " 353          378            2.626914\n",
+       " 354          379            2.621987\n",
+       " 355          380            2.615964\n",
+       " 356          381            2.610036\n",
+       " 357          382            2.606097\n",
+       " 358          383            2.603542\n",
+       " 359          384            2.598709,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 360          385            2.594340\n",
+       " 361          386            2.590119\n",
+       " 362          387            2.587712\n",
+       " 363          388            2.583497\n",
+       " 364          389            2.580042\n",
+       " 365          390            2.576392\n",
+       " 366          391            2.573643\n",
+       " 367          392            2.572803\n",
+       " 368          393            2.568870\n",
+       " 369          394            2.565872\n",
+       " 370          395            2.562155\n",
+       " 371          396            2.559869\n",
+       " 372          397            2.556650\n",
+       " 373          398            2.556327\n",
+       " 374          399            2.555003\n",
+       " 375          400            2.552677\n",
+       " 376          401            2.549961\n",
+       " 377          402            2.546452\n",
+       " 378          403            2.544698\n",
+       " 379          404            2.542554,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 380          405            2.540860\n",
+       " 381          406            2.538695\n",
+       " 382          407            2.536174\n",
+       " 383          408            2.535348\n",
+       " 384          409            2.533727\n",
+       " 385          410            2.531160\n",
+       " 386          411            2.529291\n",
+       " 387          412            2.526495\n",
+       " 388          413            2.524707\n",
+       " 389          414            2.521245\n",
+       " 390          415            2.519033\n",
+       " 391          416            2.520848\n",
+       " 392          417            2.519450\n",
+       " 393          418            2.518139\n",
+       " 394          419            2.515289\n",
+       " 395          420            2.513615\n",
+       " 396          421            2.511471\n",
+       " 397          422            2.510436\n",
+       " 398          423            2.507572\n",
+       " 399          424            2.505347,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 400          425            2.504951\n",
+       " 401          426            2.504292\n",
+       " 402          427            2.503963\n",
+       " 403          428            2.503069\n",
+       " 404          429            2.501435\n",
+       " 405          430            2.500118\n",
+       " 406          431            2.497415\n",
+       " 407          432            2.496535\n",
+       " 408          433            2.493799\n",
+       " 409          434            2.492454\n",
+       " 410          435            2.492071\n",
+       " 411          436            2.493537\n",
+       " 412          437            2.491386\n",
+       " 413          438            2.489813\n",
+       " 414          439            2.487561\n",
+       " 415          440            2.486627\n",
+       " 416          441            2.487043\n",
+       " 417          442            2.484684\n",
+       " 418          443            2.482896\n",
+       " 419          444            2.482224,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 420          445            2.481767\n",
+       " 421          446            2.481464\n",
+       " 422          447            2.481236\n",
+       " 423          448            2.480651\n",
+       " 424          449            2.478291\n",
+       " 425          450            2.475724\n",
+       " 426          451            2.475152\n",
+       " 427          452            2.472174\n",
+       " 428          453            2.470480\n",
+       " 429          454            2.470440\n",
+       " 430          455            2.469291\n",
+       " 431          461            2.840997\n",
+       " 432          462            2.796100\n",
+       " 433          463            2.762793\n",
+       " 434          464            2.735078\n",
+       " 435          465            2.711027\n",
+       " 436          466            2.692434\n",
+       " 437          467            2.675024\n",
+       " 438          468            2.659738\n",
+       " 439          469            2.645602,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 440          470            2.633159\n",
+       " 441          471            2.627600\n",
+       " 442          472            2.613027\n",
+       " 443          473            2.614412\n",
+       " 444          474            2.598756\n",
+       " 445          475            2.590286\n",
+       " 446          476            2.582617\n",
+       " 447          477            2.575874\n",
+       " 448          478            2.569630\n",
+       " 449          479            2.563399\n",
+       " 450          480            2.560676\n",
+       " 451          481            2.555991\n",
+       " 452          482            2.551548\n",
+       " 453          483            2.546903\n",
+       " 454          484            2.542406\n",
+       " 455          485            2.539650\n",
+       " 456          486            2.534884\n",
+       " 457          487            2.532094\n",
+       " 458          488            2.530266\n",
+       " 459          489            2.527167,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 460          490            2.523699\n",
+       " 461          491            2.519928\n",
+       " 462          492            2.518065\n",
+       " 463          493            2.515323\n",
+       " 464          494            2.512822\n",
+       " 465          495            2.509650\n",
+       " 466          496            2.508346\n",
+       " 467          497            2.506853\n",
+       " 468          498            2.505670\n",
+       " 469          499            2.501731\n",
+       " 470          500            2.498955\n",
+       " 471          501            2.498081\n",
+       " 472          502            2.497503\n",
+       " 473          503            2.494270\n",
+       " 474          504            2.492287\n",
+       " 475          505            2.491016\n",
+       " 476          506            2.489336\n",
+       " 477          507            2.488045\n",
+       " 478          508            2.485786\n",
+       " 479          509            2.485134,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 480          510            2.484731\n",
+       " 481          511            2.482701\n",
+       " 482          512            2.482351\n",
+       " 483          513            2.479105\n",
+       " 484          514            2.476860\n",
+       " 485          515            2.475582\n",
+       " 486          516            2.475320\n",
+       " 487          517            2.472880\n",
+       " 488          518            2.471482\n",
+       " 489          519            2.472040\n",
+       " 490          520            2.470716\n",
+       " 491          521            2.470252\n",
+       " 492          522            2.469102\n",
+       " 493          523            2.467126\n",
+       " 494          524            2.465224\n",
+       " 495          525            2.464014\n",
+       " 496          526            2.461930\n",
+       " 497          527            2.460586\n",
+       " 498          528            2.460223\n",
+       " 499          529            2.461318,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 500          530            2.460364\n",
+       " 501          531            2.459039\n",
+       " 502          532            2.458535\n",
+       " 503          533            2.458804\n",
+       " 504          534            2.456485\n",
+       " 505          535            2.455510\n",
+       " 506          536            2.455618\n",
+       " 507          537            2.453306\n",
+       " 508          538            2.451477\n",
+       " 509          539            2.451134\n",
+       " 510          540            2.450314\n",
+       " 511          541            2.449481\n",
+       " 512          542            2.449803\n",
+       " 513          543            2.447854\n",
+       " 514          544            2.448715\n",
+       " 515          545            2.449044\n",
+       " 516          546            2.447686\n",
+       " 517          547            2.446449\n",
+       " 518          548            2.446785\n",
+       " 519          549            2.446550,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 520          550            2.445663\n",
+       " 521          551            2.444318\n",
+       " 522          552            2.443243\n",
+       " 523          553            2.440621\n",
+       " 524          554            2.439485\n",
+       " 525          555            2.439418\n",
+       " 526          556            2.438833\n",
+       " 527          557            2.438995\n",
+       " 528          558            2.436877\n",
+       " 529          559            2.437482\n",
+       " 530          560            2.436763\n",
+       " 531          566            2.766645\n",
+       " 532          567            2.722595\n",
+       " 533          568            2.692199\n",
+       " 534          569            2.667489\n",
+       " 535          570            2.645831\n",
+       " 536          571            2.628924\n",
+       " 537          572            2.614156\n",
+       " 538          573            2.597526\n",
+       " 539          574            2.583766,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 540          575            2.572372\n",
+       " 541          576            2.563842\n",
+       " 542          577            2.555124\n",
+       " 543          578            2.545175\n",
+       " 544          579            2.538298\n",
+       " 545          580            2.534709\n",
+       " 546          581            2.525486\n",
+       " 547          582            2.522065\n",
+       " 548          583            2.516983\n",
+       " 549          584            2.511465\n",
+       " 550          585            2.507693\n",
+       " 551          586            2.502685\n",
+       " 552          587            2.499936\n",
+       " 553          588            2.495063\n",
+       " 554          589            2.491796\n",
+       " 555          590            2.487776\n",
+       " 556          591            2.485383\n",
+       " 557          592            2.483326\n",
+       " 558          593            2.481236\n",
+       " 559          594            2.476348,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 560          595            2.475630\n",
+       " 561          596            2.472860\n",
+       " 562          597            2.469613\n",
+       " 563          598            2.467623\n",
+       " 564          599            2.465096\n",
+       " 565          600            2.464182\n",
+       " 566          601            2.461870\n",
+       " 567          602            2.461177\n",
+       " 568          603            2.460343\n",
+       " 569          604            2.457675\n",
+       " 570          605            2.455289\n",
+       " 571          606            2.453400\n",
+       " 572          607            2.452237\n",
+       " 573          608            2.451370\n",
+       " 574          609            2.450402\n",
+       " 575          610            2.449978\n",
+       " 576          611            2.449394\n",
+       " 577          612            2.447296\n",
+       " 578          613            2.447229\n",
+       " 579          614            2.443948,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 580          615            2.441979\n",
+       " 581          616            2.440534\n",
+       " 582          617            2.438410\n",
+       " 583          618            2.439593\n",
+       " 584          619            2.438961\n",
+       " 585          620            2.438484\n",
+       " 586          621            2.434679\n",
+       " 587          622            2.433926\n",
+       " 588          623            2.434269\n",
+       " 589          624            2.432011\n",
+       " 590          625            2.430222\n",
+       " 591          626            2.429631\n",
+       " 592          627            2.428367\n",
+       " 593          628            2.428448\n",
+       " 594          629            2.427722\n",
+       " 595          630            2.425954\n",
+       " 596          631            2.424502\n",
+       " 597          632            2.424878\n",
+       " 598          633            2.422210\n",
+       " 599          634            2.421746,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 600          635            2.422714\n",
+       " 601          636            2.422331\n",
+       " 602          637            2.421753\n",
+       " 603          638            2.421537\n",
+       " 604          639            2.420341\n",
+       " 605          640            2.418781\n",
+       " 606          641            2.419023\n",
+       " 607          642            2.417726\n",
+       " 608          643            2.415683\n",
+       " 609          644            2.415992\n",
+       " 610          645            2.415595\n",
+       " 611          646            2.415730\n",
+       " 612          647            2.415441\n",
+       " 613          648            2.413270\n",
+       " 614          649            2.412718\n",
+       " 615          650            2.413330\n",
+       " 616          651            2.413142\n",
+       " 617          652            2.411885\n",
+       " 618          653            2.411663\n",
+       " 619          654            2.411461,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 620          655            2.410957\n",
+       " 621          656            2.410554\n",
+       " 622          657            2.409102\n",
+       " 623          658            2.408645\n",
+       " 624          659            2.407999\n",
+       " 625          660            2.406917\n",
+       " 626          661            2.405788\n",
+       " 627          662            2.402131\n",
+       " 628          663            2.400888\n",
+       " 629          664            2.399745\n",
+       " 630          665            2.398911\n",
+       " 631          671            2.694525\n",
+       " 632          672            2.651537\n",
+       " 633          673            2.628192\n",
+       " 634          674            2.607508\n",
+       " 635          675            2.588875\n",
+       " 636          676            2.570228\n",
+       " 637          677            2.555043\n",
+       " 638          678            2.541942\n",
+       " 639          679            2.529123,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 640          680            2.520089\n",
+       " 641          681            2.509334\n",
+       " 642          682            2.501993\n",
+       " 643          683            2.493886\n",
+       " 644          684            2.485974\n",
+       " 645          685            2.481229\n",
+       " 646          686            2.475206\n",
+       " 647          687            2.469170\n",
+       " 648          688            2.464242\n",
+       " 649          689            2.464195\n",
+       " 650          690            2.462246\n",
+       " 651          691            2.453595\n",
+       " 652          692            2.452620\n",
+       " 653          693            2.449588\n",
+       " 654          694            2.446853\n",
+       " 655          695            2.443747\n",
+       " 656          696            2.440252\n",
+       " 657          697            2.437039\n",
+       " 658          698            2.433489\n",
+       " 659          699            2.432468,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 660          700            2.430646\n",
+       " 661          701            2.428838\n",
+       " 662          702            2.427749\n",
+       " 663          703            2.426061\n",
+       " 664          704            2.425288\n",
+       " 665          705            2.421773\n",
+       " 666          706            2.419702\n",
+       " 667          707            2.418459\n",
+       " 668          708            2.416960\n",
+       " 669          709            2.415474\n",
+       " 670          710            2.414789\n",
+       " 671          711            2.413411\n",
+       " 672          712            2.413901\n",
+       " 673          713            2.412295\n",
+       " 674          714            2.412154\n",
+       " 675          715            2.411044\n",
+       " 676          716            2.409955\n",
+       " 677          717            2.408483\n",
+       " 678          718            2.408456\n",
+       " 679          719            2.406870,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 680          720            2.406467\n",
+       " 681          721            2.406063\n",
+       " 682          722            2.404739\n",
+       " 683          723            2.403005\n",
+       " 684          724            2.401076\n",
+       " 685          725            2.398945\n",
+       " 686          726            2.397963\n",
+       " 687          727            2.397419\n",
+       " 688          728            2.397419\n",
+       " 689          729            2.397345\n",
+       " 690          730            2.396848\n",
+       " 691          731            2.395691\n",
+       " 692          732            2.394421\n",
+       " 693          733            2.392888\n",
+       " 694          734            2.391752\n",
+       " 695          735            2.389467\n",
+       " 696          736            2.389769\n",
+       " 697          737            2.387773\n",
+       " 698          738            2.386012\n",
+       " 699          739            2.386529,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 700          740            2.384956\n",
+       " 701          741            2.383491\n",
+       " 702          742            2.383404\n",
+       " 703          743            2.379680\n",
+       " 704          744            2.378039\n",
+       " 705          745            2.375963\n",
+       " 706          746            2.372870\n",
+       " 707          747            2.372521\n",
+       " 708          748            2.371116\n",
+       " 709          749            2.368588\n",
+       " 710          750            2.367009\n",
+       " 711          751            2.367587\n",
+       " 712          752            2.365543\n",
+       " 713          753            2.363419\n",
+       " 714          754            2.362337\n",
+       " 715          755            2.359440\n",
+       " 716          756            2.357732\n",
+       " 717          757            2.355817\n",
+       " 718          758            2.352765\n",
+       " 719          759            2.350970,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 720          760            2.350096\n",
+       " 721          761            2.346527\n",
+       " 722          762            2.342621\n",
+       " 723          763            2.339717\n",
+       " 724          764            2.335072\n",
+       " 725          765            2.332874\n",
+       " 726          766            2.330932\n",
+       " 727          767            2.328539\n",
+       " 728          768            2.326986\n",
+       " 729          769            2.323114\n",
+       " 730          770            2.321043\n",
+       " 731          776            2.545740\n",
+       " 732          777            2.486385\n",
+       " 733          778            2.465533\n",
+       " 734          779            2.448735\n",
+       " 735          780            2.432528\n",
+       " 736          781            2.418560\n",
+       " 737          782            2.404981\n",
+       " 738          783            2.392640\n",
+       " 739          784            2.382315,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 740          785            2.371929\n",
+       " 741          786            2.360778\n",
+       " 742          787            2.353491\n",
+       " 743          788            2.346534\n",
+       " 744          789            2.338420\n",
+       " 745          790            2.330434\n",
+       " 746          791            2.324452\n",
+       " 747          792            2.316533\n",
+       " 748          793            2.311922\n",
+       " 749          794            2.306107\n",
+       " 750          795            2.299735\n",
+       " 751          796            2.294061\n",
+       " 752          797            2.293107\n",
+       " 753          798            2.289807\n",
+       " 754          799            2.281478\n",
+       " 755          800            2.275785\n",
+       " 756          801            2.271435\n",
+       " 757          802            2.264935\n",
+       " 758          803            2.259853\n",
+       " 759          804            2.256506,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 760          805            2.253333\n",
+       " 761          806            2.247626\n",
+       " 762          807            2.241953\n",
+       " 763          808            2.238524\n",
+       " 764          809            2.231675\n",
+       " 765          810            2.225632\n",
+       " 766          811            2.221538\n",
+       " 767          812            2.218022\n",
+       " 768          813            2.214614\n",
+       " 769          814            2.209432\n",
+       " 770          815            2.204552\n",
+       " 771          816            2.198004\n",
+       " 772          817            2.192654\n",
+       " 773          818            2.189696\n",
+       " 774          819            2.183196\n",
+       " 775          820            2.179089\n",
+       " 776          821            2.173966\n",
+       " 777          822            2.168945\n",
+       " 778          823            2.165181\n",
+       " 779          824            2.159964,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 780          825            2.156523\n",
+       " 781          826            2.150540\n",
+       " 782          827            2.149243\n",
+       " 783          828            2.143173\n",
+       " 784          829            2.138178\n",
+       " 785          830            2.132572\n",
+       " 786          831            2.126112\n",
+       " 787          832            2.122281\n",
+       " 788          833            2.117192\n",
+       " 789          834            2.113636\n",
+       " 790          835            2.109879\n",
+       " 791          836            2.102364\n",
+       " 792          837            2.095030\n",
+       " 793          838            2.091111\n",
+       " 794          839            2.082487\n",
+       " 795          840            2.078662\n",
+       " 796          841            2.071268\n",
+       " 797          842            2.065494\n",
+       " 798          843            2.056984\n",
+       " 799          844            2.051566,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 800          845            2.046006\n",
+       " 801          846            2.039789\n",
+       " 802          847            2.030815\n",
+       " 803          848            2.023857\n",
+       " 804          849            2.015683\n",
+       " 805          850            2.006118\n",
+       " 806          851            1.996250\n",
+       " 807          852            1.989595\n",
+       " 808          853            1.979324\n",
+       " 809          854            1.970068\n",
+       " 810          855            1.961565\n",
+       " 811          856            1.949781\n",
+       " 812          857            1.941439\n",
+       " 813          858            1.928358\n",
+       " 814          859            1.918289\n",
+       " 815          860            1.902922\n",
+       " 816          861            1.891871\n",
+       " 817          862            1.879254\n",
+       " 818          863            1.864210\n",
+       " 819          864            1.848064,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 820          865            1.833054\n",
+       " 821          866            1.820571\n",
+       " 822          867            1.803813\n",
+       " 823          868            1.784595\n",
+       " 824          869            1.767763\n",
+       " 825          870            1.751092\n",
+       " 826          871            1.729185\n",
+       " 827          872            1.711137\n",
+       " 828          873            1.692073\n",
+       " 829          874            1.669487\n",
+       " 830          875            1.648750\n",
+       " 831          881            1.755415\n",
+       " 832          882            1.580387\n",
+       " 833          883            1.540647\n",
+       " 834          884            1.504422\n",
+       " 835          885            1.473467\n",
+       " 836          886            1.441726\n",
+       " 837          887            1.414750\n",
+       " 838          888            1.388353\n",
+       " 839          889            1.363173,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 840          890            1.337642\n",
+       " 841          891            1.316542\n",
+       " 842          892            1.295099\n",
+       " 843          893            1.271928\n",
+       " 844          894            1.253765\n",
+       " 845          895            1.234567\n",
+       " 846          896            1.215585\n",
+       " 847          897            1.194760\n",
+       " 848          898            1.179730\n",
+       " 849          899            1.163563\n",
+       " 850          900            1.147282\n",
+       " 851          901            1.134322\n",
+       " 852          902            1.118989\n",
+       " 853          903            1.103509\n",
+       " 854          904            1.090239\n",
+       " 855          905            1.076621\n",
+       " 856          906            1.066773\n",
+       " 857          907            1.054895\n",
+       " 858          908            1.044617\n",
+       " 859          909            1.035287,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 860          910            1.024928\n",
+       " 861          911            1.015397\n",
+       " 862          912            1.007176\n",
+       " 863          913            0.994330\n",
+       " 864          914            0.987984\n",
+       " 865          915            0.979414\n",
+       " 866          916            0.969156\n",
+       " 867          917            0.961096\n",
+       " 868          918            0.952761\n",
+       " 869          919            0.944298\n",
+       " 870          920            0.934410\n",
+       " 871          921            0.929516\n",
+       " 872          922            0.919588\n",
+       " 873          923            0.913982\n",
+       " 874          924            0.906426\n",
+       " 875          925            0.903852\n",
+       " 876          926            0.893063\n",
+       " 877          927            0.886045\n",
+       " 878          928            0.885440\n",
+       " 879          929            0.875371,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 880          930            0.868629\n",
+       " 881          931            0.860912\n",
+       " 882          932            0.856529\n",
+       " 883          933            0.852059\n",
+       " 884          934            0.843434\n",
+       " 885          935            0.838776\n",
+       " 886          936            0.833446\n",
+       " 887          937            0.828323\n",
+       " 888          938            0.821783\n",
+       " 889          939            0.818039\n",
+       " 890          940            0.813018\n",
+       " 891          941            0.807035\n",
+       " 892          942            0.805018\n",
+       " 893          943            0.799211\n",
+       " 894          944            0.794122\n",
+       " 895          945            0.790210\n",
+       " 896          946            0.785444\n",
+       " 897          947            0.781928\n",
+       " 898          948            0.776994\n",
+       " 899          949            0.774957,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 900          950            0.769056\n",
+       " 901          951            0.766871\n",
+       " 902          952            0.762226\n",
+       " 903          953            0.758509\n",
+       " 904          954            0.754812\n",
+       " 905          955            0.750160\n",
+       " 906          956            0.748090\n",
+       " 907          957            0.743405\n",
+       " 908          958            0.741529\n",
+       " 909          959            0.737671\n",
+       " 910          960            0.734047\n",
+       " 911          961            0.731715\n",
+       " 912          962            0.726768\n",
+       " 913          963            0.724744\n",
+       " 914          964            0.721430\n",
+       " 915          965            0.720207\n",
+       " 916          966            0.715327\n",
+       " 917          967            0.713236\n",
+       " 918          968            0.709942\n",
+       " 919          969            0.706884,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 920          970            0.704000\n",
+       " 921          971            0.700458\n",
+       " 922          972            0.698401\n",
+       " 923          973            0.693978\n",
+       " 924          974            0.692633\n",
+       " 925          975            0.689138\n",
+       " 926          976            0.686530\n",
+       " 927          977            0.683209\n",
+       " 928          978            0.680648\n",
+       " 929          979            0.679310\n",
+       " 930          980            0.675862\n",
+       " 931          986            0.898387\n",
+       " 932          987            0.658613\n",
+       " 933          988            0.644006\n",
+       " 934          989            0.634347\n",
+       " 935          990            0.630004\n",
+       " 936          991            0.625185\n",
+       " 937          992            0.622005\n",
+       " 938          993            0.619222\n",
+       " 939          994            0.614013,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 940          995            0.613025\n",
+       " 941          996            0.609388\n",
+       " 942          997            0.605671\n",
+       " 943          998            0.603836\n",
+       " 944          999            0.601436\n",
+       " 945         1000            0.599816\n",
+       " 946         1001            0.596798\n",
+       " 947         1002            0.594008\n",
+       " 948         1003            0.593269\n",
+       " 949         1004            0.589814\n",
+       " 950         1005            0.586997\n",
+       " 951         1006            0.586110\n",
+       " 952         1007            0.583649\n",
+       " 953         1008            0.581210\n",
+       " 954         1009            0.580121\n",
+       " 955         1010            0.578272\n",
+       " 956         1011            0.576242\n",
+       " 957         1012            0.574723\n",
+       " 958         1013            0.573506\n",
+       " 959         1014            0.571866,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 960         1015            0.569843\n",
+       " 961         1016            0.568626\n",
+       " 962         1017            0.566300\n",
+       " 963         1018            0.564956\n",
+       " 964         1019            0.563692\n",
+       " 965         1020            0.561944\n",
+       " 966         1021            0.560956\n",
+       " 967         1022            0.559329\n",
+       " 968         1023            0.556708\n",
+       " 969         1024            0.556795\n",
+       " 970         1025            0.554684\n",
+       " 971         1026            0.552271\n",
+       " 972         1027            0.552164\n",
+       " 973         1028            0.550510\n",
+       " 974         1029            0.548588\n",
+       " 975         1030            0.547250\n",
+       " 976         1031            0.546678\n",
+       " 977         1032            0.545361\n",
+       " 978         1033            0.543990\n",
+       " 979         1034            0.543802,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 980         1035            0.541933\n",
+       " 981         1036            0.540703\n",
+       " 982         1037            0.539378\n",
+       " 983         1038            0.538968\n",
+       " 984         1039            0.537671\n",
+       " 985         1040            0.535668\n",
+       " 986         1041            0.534801\n",
+       " 987         1042            0.534035\n",
+       " 988         1043            0.534028\n",
+       " 989         1044            0.531520\n",
+       " 990         1045            0.531030\n",
+       " 991         1046            0.528879\n",
+       " 992         1047            0.529316\n",
+       " 993         1048            0.526419\n",
+       " 994         1049            0.525934\n",
+       " 995         1050            0.524805\n",
+       " 996         1051            0.524429\n",
+       " 997         1052            0.522049\n",
+       " 998         1053            0.522338\n",
+       " 999         1054            0.521276,\n",
+       "       cycle_index  discharge_capacity\n",
+       " 1000         1055            0.520651\n",
+       " 1001         1056            0.519528\n",
+       " 1002         1057            0.518513\n",
+       " 1003         1058            0.518796\n",
+       " 1004         1059            0.517243\n",
+       " 1005         1060            0.516920\n",
+       " 1006         1061            0.515872\n",
+       " 1007         1062            0.515199\n",
+       " 1008         1063            0.513983\n",
+       " 1009         1064            0.513788\n",
+       " 1010         1065            0.512255\n",
+       " 1011         1066            0.511529\n",
+       " 1012         1067            0.511590\n",
+       " 1013         1068            0.510124\n",
+       " 1014         1069            0.509802\n",
+       " 1015         1070            0.508935\n",
+       " 1016         1071            0.507671\n",
+       " 1017         1072            0.507039\n",
+       " 1018         1073            0.505372\n",
+       " 1019         1074            0.504767]"
+      ]
+     },
+     "execution_count": 148,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cell_labels[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 145,
+   "id": "b84f84c4",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[[    cycle_index  discharge_capacity\n",
+       "  20           25            3.809959\n",
+       "  21           26            3.807600\n",
+       "  22           27            3.804501\n",
+       "  23           28            3.801214\n",
+       "  24           29            3.798881\n",
+       "  25           30            3.794310\n",
+       "  26           31            3.791211\n",
+       "  27           32            3.789114\n",
+       "  28           33            3.786210\n",
+       "  29           34            3.781344\n",
+       "  30           35            3.780261\n",
+       "  31           41            3.800649\n",
+       "  32           42            3.793537\n",
+       "  33           43            3.788503\n",
+       "  34           44            3.783945\n",
+       "  35           45            3.779441\n",
+       "  36           46            3.774118\n",
+       "  37           47            3.769795\n",
+       "  38           48            3.764975\n",
+       "  39           49            3.760485,\n",
+       "      cycle_index  discharge_capacity\n",
+       "  40           50            3.756755\n",
+       "  41           51            3.752721\n",
+       "  42           52            3.748500\n",
+       "  43           53            3.744379\n",
+       "  44           54            3.740676\n",
+       "  45           55            3.736864\n",
+       "  46           56            3.732623\n",
+       "  47           57            3.728455\n",
+       "  48           58            3.724294\n",
+       "  49           59            3.720187\n",
+       "  50           60            3.716792\n",
+       "  51           61            3.712786\n",
+       "  52           62            3.708961\n",
+       "  53           63            3.703563\n",
+       "  54           64            3.699517\n",
+       "  55           65            3.695847\n",
+       "  56           66            3.691571\n",
+       "  57           67            3.688130\n",
+       "  58           68            3.683243\n",
+       "  59           69            3.679660,\n",
+       "      cycle_index  discharge_capacity\n",
+       "  60           70            3.674135\n",
+       "  61           71            3.670753\n",
+       "  62           72            3.665436\n",
+       "  63           73            3.661188\n",
+       "  64           74            3.657551\n",
+       "  65           75            3.653269\n",
+       "  66           76            3.647220\n",
+       "  67           77            3.643039\n",
+       "  68           78            3.639153\n",
+       "  69           79            3.634918\n",
+       "  70           80            3.630609\n",
+       "  71           81            3.625353\n",
+       "  72           82            3.619780\n",
+       "  73           83            3.614880\n",
+       "  74           84            3.610417\n",
+       "  75           85            3.606189\n",
+       "  76           86            3.601429\n",
+       "  77           87            3.596516\n",
+       "  78           88            3.592422\n",
+       "  79           89            3.587185,\n",
+       "      cycle_index  discharge_capacity\n",
+       "  80           90            3.582561\n",
+       "  81           91            3.577116\n",
+       "  82           92            3.571073\n",
+       "  83           93            3.565675\n",
+       "  84           94            3.560936\n",
+       "  85           95            3.556258\n",
+       "  86           96            3.550490\n",
+       "  87           97            3.546296\n",
+       "  88           98            3.540844\n",
+       "  89           99            3.536072\n",
+       "  90          100            3.530082\n",
+       "  91          101            3.525222\n",
+       "  92          102            3.520664\n",
+       "  93          103            3.514769\n",
+       "  94          104            3.510864\n",
+       "  95          105            3.505459\n",
+       "  96          106            3.500041\n",
+       "  97          107            3.493656\n",
+       "  98          108            3.487949\n",
+       "  99          109            3.483035,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  100          110            3.476904\n",
+       "  101          111            3.470976\n",
+       "  102          112            3.466062\n",
+       "  103          113            3.460395\n",
+       "  104          114            3.454675\n",
+       "  105          115            3.449943\n",
+       "  106          116            3.444236\n",
+       "  107          117            3.438179\n",
+       "  108          118            3.432835\n",
+       "  109          119            3.427982\n",
+       "  110          120            3.422497\n",
+       "  111          121            3.416554\n",
+       "  112          122            3.411432\n",
+       "  113          123            3.404744\n",
+       "  114          124            3.398015\n",
+       "  115          125            3.392449\n",
+       "  116          126            3.386782\n",
+       "  117          127            3.380961\n",
+       "  118          128            3.376451\n",
+       "  119          129            3.370368,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  120          130            3.364385\n",
+       "  121          131            3.357831\n",
+       "  122          132            3.351936\n",
+       "  123          133            3.346760\n",
+       "  124          134            3.340865\n",
+       "  125          135            3.336482\n",
+       "  126          136            3.328375\n",
+       "  127          137            3.323132\n",
+       "  128          138            3.315570\n",
+       "  129          139            3.309890\n",
+       "  130          140            3.304949\n",
+       "  131          146            3.525733\n",
+       "  132          147            3.499732\n",
+       "  133          148            3.482316\n",
+       "  134          149            3.466398\n",
+       "  135          150            3.451220\n",
+       "  136          151            3.437036\n",
+       "  137          152            3.424748\n",
+       "  138          153            3.411701\n",
+       "  139          154            3.399366,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  140          155            3.386447\n",
+       "  141          156            3.375348\n",
+       "  142          157            3.364533\n",
+       "  143          158            3.352474\n",
+       "  144          159            3.342505\n",
+       "  145          160            3.333860\n",
+       "  146          161            3.323677\n",
+       "  147          162            3.313150\n",
+       "  148          163            3.304095\n",
+       "  149          164            3.295242\n",
+       "  150          165            3.284165\n",
+       "  151          166            3.277288\n",
+       "  152          167            3.268785\n",
+       "  153          168            3.260732\n",
+       "  154          169            3.253452\n",
+       "  155          170            3.244653\n",
+       "  156          171            3.236539\n",
+       "  157          172            3.228607\n",
+       "  158          173            3.219916\n",
+       "  159          174            3.212616,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  160          175            3.204469\n",
+       "  161          176            3.198137\n",
+       "  162          177            3.190977\n",
+       "  163          178            3.181271\n",
+       "  164          179            3.175396\n",
+       "  165          180            3.167605\n",
+       "  166          181            3.160211\n",
+       "  167          182            3.153549\n",
+       "  168          183            3.148797\n",
+       "  169          184            3.141477\n",
+       "  170          185            3.134762\n",
+       "  171          186            3.126164\n",
+       "  172          187            3.119193\n",
+       "  173          188            3.113923\n",
+       "  174          189            3.106751\n",
+       "  175          190            3.100096\n",
+       "  176          191            3.094490\n",
+       "  177          192            3.087835\n",
+       "  178          193            3.080643\n",
+       "  179          194            3.075648,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  180          195            3.069087\n",
+       "  181          196            3.063253\n",
+       "  182          197            3.057344\n",
+       "  183          198            3.051826\n",
+       "  184          199            3.046952\n",
+       "  185          200            3.039551\n",
+       "  186          201            3.032876\n",
+       "  187          202            3.026846\n",
+       "  188          203            3.022565\n",
+       "  189          204            3.016360\n",
+       "  190          205            3.012192\n",
+       "  191          206            3.006848\n",
+       "  192          207            3.000873\n",
+       "  193          208            2.995213\n",
+       "  194          209            2.989116\n",
+       "  195          210            2.982965\n",
+       "  196          211            2.977460\n",
+       "  197          212            2.972950\n",
+       "  198          213            2.969488\n",
+       "  199          214            2.963546,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  200          215            2.958652\n",
+       "  201          216            2.953234\n",
+       "  202          217            2.948838\n",
+       "  203          218            2.941632\n",
+       "  204          219            2.936449\n",
+       "  205          220            2.931690\n",
+       "  206          221            2.928376\n",
+       "  207          222            2.923449\n",
+       "  208          223            2.917654\n",
+       "  209          224            2.912566\n",
+       "  210          225            2.908002\n",
+       "  211          226            2.900184\n",
+       "  212          227            2.896117\n",
+       "  213          228            2.892601\n",
+       "  214          229            2.886975\n",
+       "  215          230            2.884058\n",
+       "  216          231            2.877511\n",
+       "  217          232            2.872832\n",
+       "  218          233            2.868866\n",
+       "  219          234            2.864006,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  220          235            2.858575\n",
+       "  221          236            2.855026\n",
+       "  222          237            2.849823\n",
+       "  223          238            2.845809\n",
+       "  224          239            2.841615\n",
+       "  225          240            2.837972\n",
+       "  226          241            2.832850\n",
+       "  227          242            2.827304\n",
+       "  228          243            2.822034\n",
+       "  229          244            2.819359\n",
+       "  230          245            2.817436\n",
+       "  231          251            3.222927\n",
+       "  232          252            3.163155\n",
+       "  233          253            3.124208\n",
+       "  234          254            3.094920\n",
+       "  235          255            3.068483\n",
+       "  236          256            3.045493\n",
+       "  237          257            3.024608\n",
+       "  238          258            3.006755\n",
+       "  239          259            2.989284,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  240          260            2.973682\n",
+       "  241          261            2.958746\n",
+       "  242          262            2.946156\n",
+       "  243          263            2.932530\n",
+       "  244          264            2.920101\n",
+       "  245          265            2.911040\n",
+       "  246          266            2.901474\n",
+       "  247          267            2.890585\n",
+       "  248          268            2.881215\n",
+       "  249          269            2.872321\n",
+       "  250          270            2.863059\n",
+       "  251          271            2.854199\n",
+       "  252          272            2.846630\n",
+       "  253          273            2.839505\n",
+       "  254          274            2.833313\n",
+       "  255          275            2.826793\n",
+       "  256          276            2.818593\n",
+       "  257          277            2.811783\n",
+       "  258          278            2.806453\n",
+       "  259          279            2.799146,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  260          280            2.793156\n",
+       "  261          281            2.787752\n",
+       "  262          282            2.783497\n",
+       "  263          283            2.779269\n",
+       "  264          284            2.771807\n",
+       "  265          285            2.767008\n",
+       "  266          286            2.762148\n",
+       "  267          287            2.757308\n",
+       "  268          288            2.751359\n",
+       "  269          289            2.746687\n",
+       "  270          290            2.743373\n",
+       "  271          291            2.738534\n",
+       "  272          292            2.733620\n",
+       "  273          293            2.728867\n",
+       "  274          294            2.724215\n",
+       "  275          295            2.719517\n",
+       "  276          296            2.713951\n",
+       "  277          297            2.711941\n",
+       "  278          298            2.708035\n",
+       "  279          299            2.705481,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  280          300            2.701018\n",
+       "  281          301            2.696434\n",
+       "  282          302            2.691910\n",
+       "  283          303            2.687594\n",
+       "  284          304            2.684529\n",
+       "  285          305            2.681484\n",
+       "  286          306            2.678990\n",
+       "  287          307            2.674412\n",
+       "  288          308            2.671851\n",
+       "  289          309            2.668033\n",
+       "  290          310            2.664578\n",
+       "  291          311            2.662568\n",
+       "  292          312            2.658481\n",
+       "  293          313            2.655590\n",
+       "  294          314            2.652115\n",
+       "  295          315            2.650926\n",
+       "  296          316            2.647598\n",
+       "  297          317            2.644130\n",
+       "  298          318            2.640560\n",
+       "  299          319            2.636849,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  300          320            2.635909\n",
+       "  301          321            2.633153\n",
+       "  302          322            2.630255\n",
+       "  303          323            2.627372\n",
+       "  304          324            2.625174\n",
+       "  305          325            2.623883\n",
+       "  306          326            2.618364\n",
+       "  307          327            2.616482\n",
+       "  308          328            2.616146\n",
+       "  309          329            2.613914\n",
+       "  310          330            2.613417\n",
+       "  311          331            2.608308\n",
+       "  312          332            2.606386\n",
+       "  313          333            2.605828\n",
+       "  314          334            2.600921\n",
+       "  315          335            2.598138\n",
+       "  316          336            2.596410\n",
+       "  317          337            2.594898\n",
+       "  318          338            2.595241\n",
+       "  319          339            2.590071,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  320          340            2.587860\n",
+       "  321          341            2.584653\n",
+       "  322          342            2.584102\n",
+       "  323          343            2.581326\n",
+       "  324          344            2.580042\n",
+       "  325          345            2.580183\n",
+       "  326          346            2.576748\n",
+       "  327          347            2.573199\n",
+       "  328          348            2.571693\n",
+       "  329          349            2.569650\n",
+       "  330          350            2.567667\n",
+       "  331          356            2.985883\n",
+       "  332          357            2.932012\n",
+       "  333          358            2.891734\n",
+       "  334          359            2.859563\n",
+       "  335          360            2.835283\n",
+       "  336          361            2.807978\n",
+       "  337          362            2.788646\n",
+       "  338          363            2.770684\n",
+       "  339          364            2.754754,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  340          365            2.740086\n",
+       "  341          366            2.726333\n",
+       "  342          367            2.714509\n",
+       "  343          368            2.703902\n",
+       "  344          369            2.694726\n",
+       "  345          370            2.685712\n",
+       "  346          371            2.675259\n",
+       "  347          372            2.666433\n",
+       "  348          373            2.659073\n",
+       "  349          374            2.652384\n",
+       "  350          375            2.646005\n",
+       "  351          376            2.640090\n",
+       "  352          377            2.632675\n",
+       "  353          378            2.626914\n",
+       "  354          379            2.621987\n",
+       "  355          380            2.615964\n",
+       "  356          381            2.610036\n",
+       "  357          382            2.606097\n",
+       "  358          383            2.603542\n",
+       "  359          384            2.598709,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  360          385            2.594340\n",
+       "  361          386            2.590119\n",
+       "  362          387            2.587712\n",
+       "  363          388            2.583497\n",
+       "  364          389            2.580042\n",
+       "  365          390            2.576392\n",
+       "  366          391            2.573643\n",
+       "  367          392            2.572803\n",
+       "  368          393            2.568870\n",
+       "  369          394            2.565872\n",
+       "  370          395            2.562155\n",
+       "  371          396            2.559869\n",
+       "  372          397            2.556650\n",
+       "  373          398            2.556327\n",
+       "  374          399            2.555003\n",
+       "  375          400            2.552677\n",
+       "  376          401            2.549961\n",
+       "  377          402            2.546452\n",
+       "  378          403            2.544698\n",
+       "  379          404            2.542554,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  380          405            2.540860\n",
+       "  381          406            2.538695\n",
+       "  382          407            2.536174\n",
+       "  383          408            2.535348\n",
+       "  384          409            2.533727\n",
+       "  385          410            2.531160\n",
+       "  386          411            2.529291\n",
+       "  387          412            2.526495\n",
+       "  388          413            2.524707\n",
+       "  389          414            2.521245\n",
+       "  390          415            2.519033\n",
+       "  391          416            2.520848\n",
+       "  392          417            2.519450\n",
+       "  393          418            2.518139\n",
+       "  394          419            2.515289\n",
+       "  395          420            2.513615\n",
+       "  396          421            2.511471\n",
+       "  397          422            2.510436\n",
+       "  398          423            2.507572\n",
+       "  399          424            2.505347,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  400          425            2.504951\n",
+       "  401          426            2.504292\n",
+       "  402          427            2.503963\n",
+       "  403          428            2.503069\n",
+       "  404          429            2.501435\n",
+       "  405          430            2.500118\n",
+       "  406          431            2.497415\n",
+       "  407          432            2.496535\n",
+       "  408          433            2.493799\n",
+       "  409          434            2.492454\n",
+       "  410          435            2.492071\n",
+       "  411          436            2.493537\n",
+       "  412          437            2.491386\n",
+       "  413          438            2.489813\n",
+       "  414          439            2.487561\n",
+       "  415          440            2.486627\n",
+       "  416          441            2.487043\n",
+       "  417          442            2.484684\n",
+       "  418          443            2.482896\n",
+       "  419          444            2.482224,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  420          445            2.481767\n",
+       "  421          446            2.481464\n",
+       "  422          447            2.481236\n",
+       "  423          448            2.480651\n",
+       "  424          449            2.478291\n",
+       "  425          450            2.475724\n",
+       "  426          451            2.475152\n",
+       "  427          452            2.472174\n",
+       "  428          453            2.470480\n",
+       "  429          454            2.470440\n",
+       "  430          455            2.469291\n",
+       "  431          461            2.840997\n",
+       "  432          462            2.796100\n",
+       "  433          463            2.762793\n",
+       "  434          464            2.735078\n",
+       "  435          465            2.711027\n",
+       "  436          466            2.692434\n",
+       "  437          467            2.675024\n",
+       "  438          468            2.659738\n",
+       "  439          469            2.645602,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  440          470            2.633159\n",
+       "  441          471            2.627600\n",
+       "  442          472            2.613027\n",
+       "  443          473            2.614412\n",
+       "  444          474            2.598756\n",
+       "  445          475            2.590286\n",
+       "  446          476            2.582617\n",
+       "  447          477            2.575874\n",
+       "  448          478            2.569630\n",
+       "  449          479            2.563399\n",
+       "  450          480            2.560676\n",
+       "  451          481            2.555991\n",
+       "  452          482            2.551548\n",
+       "  453          483            2.546903\n",
+       "  454          484            2.542406\n",
+       "  455          485            2.539650\n",
+       "  456          486            2.534884\n",
+       "  457          487            2.532094\n",
+       "  458          488            2.530266\n",
+       "  459          489            2.527167,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  460          490            2.523699\n",
+       "  461          491            2.519928\n",
+       "  462          492            2.518065\n",
+       "  463          493            2.515323\n",
+       "  464          494            2.512822\n",
+       "  465          495            2.509650\n",
+       "  466          496            2.508346\n",
+       "  467          497            2.506853\n",
+       "  468          498            2.505670\n",
+       "  469          499            2.501731\n",
+       "  470          500            2.498955\n",
+       "  471          501            2.498081\n",
+       "  472          502            2.497503\n",
+       "  473          503            2.494270\n",
+       "  474          504            2.492287\n",
+       "  475          505            2.491016\n",
+       "  476          506            2.489336\n",
+       "  477          507            2.488045\n",
+       "  478          508            2.485786\n",
+       "  479          509            2.485134,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  480          510            2.484731\n",
+       "  481          511            2.482701\n",
+       "  482          512            2.482351\n",
+       "  483          513            2.479105\n",
+       "  484          514            2.476860\n",
+       "  485          515            2.475582\n",
+       "  486          516            2.475320\n",
+       "  487          517            2.472880\n",
+       "  488          518            2.471482\n",
+       "  489          519            2.472040\n",
+       "  490          520            2.470716\n",
+       "  491          521            2.470252\n",
+       "  492          522            2.469102\n",
+       "  493          523            2.467126\n",
+       "  494          524            2.465224\n",
+       "  495          525            2.464014\n",
+       "  496          526            2.461930\n",
+       "  497          527            2.460586\n",
+       "  498          528            2.460223\n",
+       "  499          529            2.461318,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  500          530            2.460364\n",
+       "  501          531            2.459039\n",
+       "  502          532            2.458535\n",
+       "  503          533            2.458804\n",
+       "  504          534            2.456485\n",
+       "  505          535            2.455510\n",
+       "  506          536            2.455618\n",
+       "  507          537            2.453306\n",
+       "  508          538            2.451477\n",
+       "  509          539            2.451134\n",
+       "  510          540            2.450314\n",
+       "  511          541            2.449481\n",
+       "  512          542            2.449803\n",
+       "  513          543            2.447854\n",
+       "  514          544            2.448715\n",
+       "  515          545            2.449044\n",
+       "  516          546            2.447686\n",
+       "  517          547            2.446449\n",
+       "  518          548            2.446785\n",
+       "  519          549            2.446550,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  520          550            2.445663\n",
+       "  521          551            2.444318\n",
+       "  522          552            2.443243\n",
+       "  523          553            2.440621\n",
+       "  524          554            2.439485\n",
+       "  525          555            2.439418\n",
+       "  526          556            2.438833\n",
+       "  527          557            2.438995\n",
+       "  528          558            2.436877\n",
+       "  529          559            2.437482\n",
+       "  530          560            2.436763\n",
+       "  531          566            2.766645\n",
+       "  532          567            2.722595\n",
+       "  533          568            2.692199\n",
+       "  534          569            2.667489\n",
+       "  535          570            2.645831\n",
+       "  536          571            2.628924\n",
+       "  537          572            2.614156\n",
+       "  538          573            2.597526\n",
+       "  539          574            2.583766,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  540          575            2.572372\n",
+       "  541          576            2.563842\n",
+       "  542          577            2.555124\n",
+       "  543          578            2.545175\n",
+       "  544          579            2.538298\n",
+       "  545          580            2.534709\n",
+       "  546          581            2.525486\n",
+       "  547          582            2.522065\n",
+       "  548          583            2.516983\n",
+       "  549          584            2.511465\n",
+       "  550          585            2.507693\n",
+       "  551          586            2.502685\n",
+       "  552          587            2.499936\n",
+       "  553          588            2.495063\n",
+       "  554          589            2.491796\n",
+       "  555          590            2.487776\n",
+       "  556          591            2.485383\n",
+       "  557          592            2.483326\n",
+       "  558          593            2.481236\n",
+       "  559          594            2.476348,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  560          595            2.475630\n",
+       "  561          596            2.472860\n",
+       "  562          597            2.469613\n",
+       "  563          598            2.467623\n",
+       "  564          599            2.465096\n",
+       "  565          600            2.464182\n",
+       "  566          601            2.461870\n",
+       "  567          602            2.461177\n",
+       "  568          603            2.460343\n",
+       "  569          604            2.457675\n",
+       "  570          605            2.455289\n",
+       "  571          606            2.453400\n",
+       "  572          607            2.452237\n",
+       "  573          608            2.451370\n",
+       "  574          609            2.450402\n",
+       "  575          610            2.449978\n",
+       "  576          611            2.449394\n",
+       "  577          612            2.447296\n",
+       "  578          613            2.447229\n",
+       "  579          614            2.443948,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  580          615            2.441979\n",
+       "  581          616            2.440534\n",
+       "  582          617            2.438410\n",
+       "  583          618            2.439593\n",
+       "  584          619            2.438961\n",
+       "  585          620            2.438484\n",
+       "  586          621            2.434679\n",
+       "  587          622            2.433926\n",
+       "  588          623            2.434269\n",
+       "  589          624            2.432011\n",
+       "  590          625            2.430222\n",
+       "  591          626            2.429631\n",
+       "  592          627            2.428367\n",
+       "  593          628            2.428448\n",
+       "  594          629            2.427722\n",
+       "  595          630            2.425954\n",
+       "  596          631            2.424502\n",
+       "  597          632            2.424878\n",
+       "  598          633            2.422210\n",
+       "  599          634            2.421746,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  600          635            2.422714\n",
+       "  601          636            2.422331\n",
+       "  602          637            2.421753\n",
+       "  603          638            2.421537\n",
+       "  604          639            2.420341\n",
+       "  605          640            2.418781\n",
+       "  606          641            2.419023\n",
+       "  607          642            2.417726\n",
+       "  608          643            2.415683\n",
+       "  609          644            2.415992\n",
+       "  610          645            2.415595\n",
+       "  611          646            2.415730\n",
+       "  612          647            2.415441\n",
+       "  613          648            2.413270\n",
+       "  614          649            2.412718\n",
+       "  615          650            2.413330\n",
+       "  616          651            2.413142\n",
+       "  617          652            2.411885\n",
+       "  618          653            2.411663\n",
+       "  619          654            2.411461,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  620          655            2.410957\n",
+       "  621          656            2.410554\n",
+       "  622          657            2.409102\n",
+       "  623          658            2.408645\n",
+       "  624          659            2.407999\n",
+       "  625          660            2.406917\n",
+       "  626          661            2.405788\n",
+       "  627          662            2.402131\n",
+       "  628          663            2.400888\n",
+       "  629          664            2.399745\n",
+       "  630          665            2.398911\n",
+       "  631          671            2.694525\n",
+       "  632          672            2.651537\n",
+       "  633          673            2.628192\n",
+       "  634          674            2.607508\n",
+       "  635          675            2.588875\n",
+       "  636          676            2.570228\n",
+       "  637          677            2.555043\n",
+       "  638          678            2.541942\n",
+       "  639          679            2.529123,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  640          680            2.520089\n",
+       "  641          681            2.509334\n",
+       "  642          682            2.501993\n",
+       "  643          683            2.493886\n",
+       "  644          684            2.485974\n",
+       "  645          685            2.481229\n",
+       "  646          686            2.475206\n",
+       "  647          687            2.469170\n",
+       "  648          688            2.464242\n",
+       "  649          689            2.464195\n",
+       "  650          690            2.462246\n",
+       "  651          691            2.453595\n",
+       "  652          692            2.452620\n",
+       "  653          693            2.449588\n",
+       "  654          694            2.446853\n",
+       "  655          695            2.443747\n",
+       "  656          696            2.440252\n",
+       "  657          697            2.437039\n",
+       "  658          698            2.433489\n",
+       "  659          699            2.432468,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  660          700            2.430646\n",
+       "  661          701            2.428838\n",
+       "  662          702            2.427749\n",
+       "  663          703            2.426061\n",
+       "  664          704            2.425288\n",
+       "  665          705            2.421773\n",
+       "  666          706            2.419702\n",
+       "  667          707            2.418459\n",
+       "  668          708            2.416960\n",
+       "  669          709            2.415474\n",
+       "  670          710            2.414789\n",
+       "  671          711            2.413411\n",
+       "  672          712            2.413901\n",
+       "  673          713            2.412295\n",
+       "  674          714            2.412154\n",
+       "  675          715            2.411044\n",
+       "  676          716            2.409955\n",
+       "  677          717            2.408483\n",
+       "  678          718            2.408456\n",
+       "  679          719            2.406870,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  680          720            2.406467\n",
+       "  681          721            2.406063\n",
+       "  682          722            2.404739\n",
+       "  683          723            2.403005\n",
+       "  684          724            2.401076\n",
+       "  685          725            2.398945\n",
+       "  686          726            2.397963\n",
+       "  687          727            2.397419\n",
+       "  688          728            2.397419\n",
+       "  689          729            2.397345\n",
+       "  690          730            2.396848\n",
+       "  691          731            2.395691\n",
+       "  692          732            2.394421\n",
+       "  693          733            2.392888\n",
+       "  694          734            2.391752\n",
+       "  695          735            2.389467\n",
+       "  696          736            2.389769\n",
+       "  697          737            2.387773\n",
+       "  698          738            2.386012\n",
+       "  699          739            2.386529,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  700          740            2.384956\n",
+       "  701          741            2.383491\n",
+       "  702          742            2.383404\n",
+       "  703          743            2.379680\n",
+       "  704          744            2.378039\n",
+       "  705          745            2.375963\n",
+       "  706          746            2.372870\n",
+       "  707          747            2.372521\n",
+       "  708          748            2.371116\n",
+       "  709          749            2.368588\n",
+       "  710          750            2.367009\n",
+       "  711          751            2.367587\n",
+       "  712          752            2.365543\n",
+       "  713          753            2.363419\n",
+       "  714          754            2.362337\n",
+       "  715          755            2.359440\n",
+       "  716          756            2.357732\n",
+       "  717          757            2.355817\n",
+       "  718          758            2.352765\n",
+       "  719          759            2.350970,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  720          760            2.350096\n",
+       "  721          761            2.346527\n",
+       "  722          762            2.342621\n",
+       "  723          763            2.339717\n",
+       "  724          764            2.335072\n",
+       "  725          765            2.332874\n",
+       "  726          766            2.330932\n",
+       "  727          767            2.328539\n",
+       "  728          768            2.326986\n",
+       "  729          769            2.323114\n",
+       "  730          770            2.321043\n",
+       "  731          776            2.545740\n",
+       "  732          777            2.486385\n",
+       "  733          778            2.465533\n",
+       "  734          779            2.448735\n",
+       "  735          780            2.432528\n",
+       "  736          781            2.418560\n",
+       "  737          782            2.404981\n",
+       "  738          783            2.392640\n",
+       "  739          784            2.382315,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  740          785            2.371929\n",
+       "  741          786            2.360778\n",
+       "  742          787            2.353491\n",
+       "  743          788            2.346534\n",
+       "  744          789            2.338420\n",
+       "  745          790            2.330434\n",
+       "  746          791            2.324452\n",
+       "  747          792            2.316533\n",
+       "  748          793            2.311922\n",
+       "  749          794            2.306107\n",
+       "  750          795            2.299735\n",
+       "  751          796            2.294061\n",
+       "  752          797            2.293107\n",
+       "  753          798            2.289807\n",
+       "  754          799            2.281478\n",
+       "  755          800            2.275785\n",
+       "  756          801            2.271435\n",
+       "  757          802            2.264935\n",
+       "  758          803            2.259853\n",
+       "  759          804            2.256506,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  760          805            2.253333\n",
+       "  761          806            2.247626\n",
+       "  762          807            2.241953\n",
+       "  763          808            2.238524\n",
+       "  764          809            2.231675\n",
+       "  765          810            2.225632\n",
+       "  766          811            2.221538\n",
+       "  767          812            2.218022\n",
+       "  768          813            2.214614\n",
+       "  769          814            2.209432\n",
+       "  770          815            2.204552\n",
+       "  771          816            2.198004\n",
+       "  772          817            2.192654\n",
+       "  773          818            2.189696\n",
+       "  774          819            2.183196\n",
+       "  775          820            2.179089\n",
+       "  776          821            2.173966\n",
+       "  777          822            2.168945\n",
+       "  778          823            2.165181\n",
+       "  779          824            2.159964,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  780          825            2.156523\n",
+       "  781          826            2.150540\n",
+       "  782          827            2.149243\n",
+       "  783          828            2.143173\n",
+       "  784          829            2.138178\n",
+       "  785          830            2.132572\n",
+       "  786          831            2.126112\n",
+       "  787          832            2.122281\n",
+       "  788          833            2.117192\n",
+       "  789          834            2.113636\n",
+       "  790          835            2.109879\n",
+       "  791          836            2.102364\n",
+       "  792          837            2.095030\n",
+       "  793          838            2.091111\n",
+       "  794          839            2.082487\n",
+       "  795          840            2.078662\n",
+       "  796          841            2.071268\n",
+       "  797          842            2.065494\n",
+       "  798          843            2.056984\n",
+       "  799          844            2.051566,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  800          845            2.046006\n",
+       "  801          846            2.039789\n",
+       "  802          847            2.030815\n",
+       "  803          848            2.023857\n",
+       "  804          849            2.015683\n",
+       "  805          850            2.006118\n",
+       "  806          851            1.996250\n",
+       "  807          852            1.989595\n",
+       "  808          853            1.979324\n",
+       "  809          854            1.970068\n",
+       "  810          855            1.961565\n",
+       "  811          856            1.949781\n",
+       "  812          857            1.941439\n",
+       "  813          858            1.928358\n",
+       "  814          859            1.918289\n",
+       "  815          860            1.902922\n",
+       "  816          861            1.891871\n",
+       "  817          862            1.879254\n",
+       "  818          863            1.864210\n",
+       "  819          864            1.848064,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  820          865            1.833054\n",
+       "  821          866            1.820571\n",
+       "  822          867            1.803813\n",
+       "  823          868            1.784595\n",
+       "  824          869            1.767763\n",
+       "  825          870            1.751092\n",
+       "  826          871            1.729185\n",
+       "  827          872            1.711137\n",
+       "  828          873            1.692073\n",
+       "  829          874            1.669487\n",
+       "  830          875            1.648750\n",
+       "  831          881            1.755415\n",
+       "  832          882            1.580387\n",
+       "  833          883            1.540647\n",
+       "  834          884            1.504422\n",
+       "  835          885            1.473467\n",
+       "  836          886            1.441726\n",
+       "  837          887            1.414750\n",
+       "  838          888            1.388353\n",
+       "  839          889            1.363173,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  840          890            1.337642\n",
+       "  841          891            1.316542\n",
+       "  842          892            1.295099\n",
+       "  843          893            1.271928\n",
+       "  844          894            1.253765\n",
+       "  845          895            1.234567\n",
+       "  846          896            1.215585\n",
+       "  847          897            1.194760\n",
+       "  848          898            1.179730\n",
+       "  849          899            1.163563\n",
+       "  850          900            1.147282\n",
+       "  851          901            1.134322\n",
+       "  852          902            1.118989\n",
+       "  853          903            1.103509\n",
+       "  854          904            1.090239\n",
+       "  855          905            1.076621\n",
+       "  856          906            1.066773\n",
+       "  857          907            1.054895\n",
+       "  858          908            1.044617\n",
+       "  859          909            1.035287,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  860          910            1.024928\n",
+       "  861          911            1.015397\n",
+       "  862          912            1.007176\n",
+       "  863          913            0.994330\n",
+       "  864          914            0.987984\n",
+       "  865          915            0.979414\n",
+       "  866          916            0.969156\n",
+       "  867          917            0.961096\n",
+       "  868          918            0.952761\n",
+       "  869          919            0.944298\n",
+       "  870          920            0.934410\n",
+       "  871          921            0.929516\n",
+       "  872          922            0.919588\n",
+       "  873          923            0.913982\n",
+       "  874          924            0.906426\n",
+       "  875          925            0.903852\n",
+       "  876          926            0.893063\n",
+       "  877          927            0.886045\n",
+       "  878          928            0.885440\n",
+       "  879          929            0.875371,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  880          930            0.868629\n",
+       "  881          931            0.860912\n",
+       "  882          932            0.856529\n",
+       "  883          933            0.852059\n",
+       "  884          934            0.843434\n",
+       "  885          935            0.838776\n",
+       "  886          936            0.833446\n",
+       "  887          937            0.828323\n",
+       "  888          938            0.821783\n",
+       "  889          939            0.818039\n",
+       "  890          940            0.813018\n",
+       "  891          941            0.807035\n",
+       "  892          942            0.805018\n",
+       "  893          943            0.799211\n",
+       "  894          944            0.794122\n",
+       "  895          945            0.790210\n",
+       "  896          946            0.785444\n",
+       "  897          947            0.781928\n",
+       "  898          948            0.776994\n",
+       "  899          949            0.774957,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  900          950            0.769056\n",
+       "  901          951            0.766871\n",
+       "  902          952            0.762226\n",
+       "  903          953            0.758509\n",
+       "  904          954            0.754812\n",
+       "  905          955            0.750160\n",
+       "  906          956            0.748090\n",
+       "  907          957            0.743405\n",
+       "  908          958            0.741529\n",
+       "  909          959            0.737671\n",
+       "  910          960            0.734047\n",
+       "  911          961            0.731715\n",
+       "  912          962            0.726768\n",
+       "  913          963            0.724744\n",
+       "  914          964            0.721430\n",
+       "  915          965            0.720207\n",
+       "  916          966            0.715327\n",
+       "  917          967            0.713236\n",
+       "  918          968            0.709942\n",
+       "  919          969            0.706884,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  920          970            0.704000\n",
+       "  921          971            0.700458\n",
+       "  922          972            0.698401\n",
+       "  923          973            0.693978\n",
+       "  924          974            0.692633\n",
+       "  925          975            0.689138\n",
+       "  926          976            0.686530\n",
+       "  927          977            0.683209\n",
+       "  928          978            0.680648\n",
+       "  929          979            0.679310\n",
+       "  930          980            0.675862\n",
+       "  931          986            0.898387\n",
+       "  932          987            0.658613\n",
+       "  933          988            0.644006\n",
+       "  934          989            0.634347\n",
+       "  935          990            0.630004\n",
+       "  936          991            0.625185\n",
+       "  937          992            0.622005\n",
+       "  938          993            0.619222\n",
+       "  939          994            0.614013,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  940          995            0.613025\n",
+       "  941          996            0.609388\n",
+       "  942          997            0.605671\n",
+       "  943          998            0.603836\n",
+       "  944          999            0.601436\n",
+       "  945         1000            0.599816\n",
+       "  946         1001            0.596798\n",
+       "  947         1002            0.594008\n",
+       "  948         1003            0.593269\n",
+       "  949         1004            0.589814\n",
+       "  950         1005            0.586997\n",
+       "  951         1006            0.586110\n",
+       "  952         1007            0.583649\n",
+       "  953         1008            0.581210\n",
+       "  954         1009            0.580121\n",
+       "  955         1010            0.578272\n",
+       "  956         1011            0.576242\n",
+       "  957         1012            0.574723\n",
+       "  958         1013            0.573506\n",
+       "  959         1014            0.571866,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  960         1015            0.569843\n",
+       "  961         1016            0.568626\n",
+       "  962         1017            0.566300\n",
+       "  963         1018            0.564956\n",
+       "  964         1019            0.563692\n",
+       "  965         1020            0.561944\n",
+       "  966         1021            0.560956\n",
+       "  967         1022            0.559329\n",
+       "  968         1023            0.556708\n",
+       "  969         1024            0.556795\n",
+       "  970         1025            0.554684\n",
+       "  971         1026            0.552271\n",
+       "  972         1027            0.552164\n",
+       "  973         1028            0.550510\n",
+       "  974         1029            0.548588\n",
+       "  975         1030            0.547250\n",
+       "  976         1031            0.546678\n",
+       "  977         1032            0.545361\n",
+       "  978         1033            0.543990\n",
+       "  979         1034            0.543802,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  980         1035            0.541933\n",
+       "  981         1036            0.540703\n",
+       "  982         1037            0.539378\n",
+       "  983         1038            0.538968\n",
+       "  984         1039            0.537671\n",
+       "  985         1040            0.535668\n",
+       "  986         1041            0.534801\n",
+       "  987         1042            0.534035\n",
+       "  988         1043            0.534028\n",
+       "  989         1044            0.531520\n",
+       "  990         1045            0.531030\n",
+       "  991         1046            0.528879\n",
+       "  992         1047            0.529316\n",
+       "  993         1048            0.526419\n",
+       "  994         1049            0.525934\n",
+       "  995         1050            0.524805\n",
+       "  996         1051            0.524429\n",
+       "  997         1052            0.522049\n",
+       "  998         1053            0.522338\n",
+       "  999         1054            0.521276,\n",
+       "        cycle_index  discharge_capacity\n",
+       "  1000         1055            0.520651\n",
+       "  1001         1056            0.519528\n",
+       "  1002         1057            0.518513\n",
+       "  1003         1058            0.518796\n",
+       "  1004         1059            0.517243\n",
+       "  1005         1060            0.516920\n",
+       "  1006         1061            0.515872\n",
+       "  1007         1062            0.515199\n",
+       "  1008         1063            0.513983\n",
+       "  1009         1064            0.513788\n",
+       "  1010         1065            0.512255\n",
+       "  1011         1066            0.511529\n",
+       "  1012         1067            0.511590\n",
+       "  1013         1068            0.510124\n",
+       "  1014         1069            0.509802\n",
+       "  1015         1070            0.508935\n",
+       "  1016         1071            0.507671\n",
+       "  1017         1072            0.507039\n",
+       "  1018         1073            0.505372\n",
+       "  1019         1074            0.504767],\n",
+       " [    cycle_index  discharge_capacity\n",
+       "  20           25            4.431603\n",
+       "  21           26            4.426252\n",
+       "  22           27            4.421506\n",
+       "  23           28            4.416095\n",
+       "  24           29            4.410792\n",
+       "  25           30            4.404829\n",
+       "  26           31            4.398080\n",
+       "  27           32            4.392871\n",
+       "  28           33            4.386680\n",
+       "  29           34            4.380966\n",
+       "  30           35            4.374526\n",
+       "  31           41            4.391991\n",
+       "  32           42            4.384300\n",
+       "  33           43            4.378069\n",
+       "  34           44            4.370056\n",
+       "  35           45            4.363489\n",
+       "  36           46            4.355517\n",
+       "  37           47            4.350039\n",
+       "  38           48            4.342839\n",
+       "  39           49            4.336951,\n",
+       "      cycle_index  discharge_capacity\n",
+       "  40           50            4.329207\n",
+       "  41           51            4.322256\n",
+       "  42           52            4.316818\n",
+       "  43           53            4.309027\n",
+       "  44           54            4.304147\n",
+       "  45           55            4.295462\n",
+       "  46           56            4.288720\n",
+       "  47           57            4.282066\n",
+       "  48           58            4.274315\n",
+       "  49           59            4.267788\n",
+       "  50           60            4.259594\n",
+       "  51           61            4.253107\n",
+       "  52           62            4.247084\n",
+       "  53           63            4.239663\n",
+       "  54           64            4.230373\n",
+       "  55           65            4.223046\n",
+       "  56           66            4.216123\n",
+       "  57           67            4.208251\n",
+       "  58           68            4.202800\n",
+       "  59           69            4.193947,\n",
+       "      cycle_index  discharge_capacity\n",
+       "  60           70            4.184395\n",
+       "  61           71            4.177969\n",
+       "  62           72            4.169815\n",
+       "  63           73            4.161748\n",
+       "  64           74            4.154260\n",
+       "  65           75            4.143801\n",
+       "  66           76            4.137636\n",
+       "  67           77            4.129477\n",
+       "  68           78            4.121255\n",
+       "  69           79            4.112134\n",
+       "  70           80            4.104988\n",
+       "  71           81            4.096679\n",
+       "  72           82            4.086805\n",
+       "  73           83            4.077737\n",
+       "  74           84            4.069449\n",
+       "  75           85            4.062485\n",
+       "  76           86            4.055501\n",
+       "  77           87            4.044913\n",
+       "  78           88            4.036403\n",
+       "  79           89            4.026751,\n",
+       "      cycle_index  discharge_capacity\n",
+       "  80           90            4.018993\n",
+       "  81           91            4.009260\n",
+       "  82           92            4.001839\n",
+       "  83           93            3.991642\n",
+       "  84           94            3.981538\n",
+       "  85           95            3.974137\n",
+       "  86           96            3.964929\n",
+       "  87           97            3.955323\n",
+       "  88           98            3.945757\n",
+       "  89           99            3.936064\n",
+       "  90          100            3.928193\n",
+       "  91          101            3.919931\n",
+       "  92          102            3.909835\n",
+       "  93          103            3.900807\n",
+       "  94          104            3.889393\n",
+       "  95          105            3.879586\n",
+       "  96          106            3.870780\n",
+       "  97          107            3.860590\n",
+       "  98          108            3.851448\n",
+       "  99          109            3.841889,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  100          110            3.831389\n",
+       "  101          111            3.823726\n",
+       "  102          112            3.814840\n",
+       "  103          113            3.802895\n",
+       "  104          114            3.793585\n",
+       "  105          115            3.783992\n",
+       "  106          116            3.773997\n",
+       "  107          117            3.766898\n",
+       "  108          118            3.758422\n",
+       "  109          119            3.746134\n",
+       "  110          120            3.735413\n",
+       "  111          121            3.724301\n",
+       "  112          122            3.714850\n",
+       "  113          123            3.705896\n",
+       "  114          124            3.698287\n",
+       "  115          125            3.688493\n",
+       "  116          126            3.677550\n",
+       "  117          127            3.666969\n",
+       "  118          128            3.657531\n",
+       "  119          129            3.648040,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  120          130            3.639442\n",
+       "  121          131            3.630926\n",
+       "  122          132            3.621018\n",
+       "  123          133            3.609900\n",
+       "  124          134            3.599292\n",
+       "  125          135            3.589236\n",
+       "  126          136            3.580020\n",
+       "  127          137            3.572162\n",
+       "  128          138            3.562415\n",
+       "  129          139            3.549980\n",
+       "  130          140            3.540166\n",
+       "  131          146            3.885710\n",
+       "  132          147            3.836141\n",
+       "  133          148            3.807728\n",
+       "  134          149            3.783179\n",
+       "  135          150            3.757931\n",
+       "  136          151            3.737120\n",
+       "  137          152            3.717996\n",
+       "  138          153            3.698576\n",
+       "  139          154            3.680205,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  140          155            3.664677\n",
+       "  141          156            3.646071\n",
+       "  142          157            3.628432\n",
+       "  143          158            3.612837\n",
+       "  144          159            3.595756\n",
+       "  145          160            3.580646\n",
+       "  146          161            3.563390\n",
+       "  147          162            3.548938\n",
+       "  148          163            3.535736\n",
+       "  149          164            3.520517\n",
+       "  150          165            3.503921\n",
+       "  151          166            3.488655\n",
+       "  152          167            3.473947\n",
+       "  153          168            3.460893\n",
+       "  154          169            3.448619\n",
+       "  155          170            3.436029\n",
+       "  156          171            3.420393\n",
+       "  157          172            3.404502\n",
+       "  158          173            3.390272\n",
+       "  159          174            3.377191,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  160          175            3.362389\n",
+       "  161          176            3.349267\n",
+       "  162          177            3.335770\n",
+       "  163          178            3.321815\n",
+       "  164          179            3.306099\n",
+       "  165          180            3.291707\n",
+       "  166          181            3.277873\n",
+       "  167          182            3.262903\n",
+       "  168          183            3.250649\n",
+       "  169          184            3.238704\n",
+       "  170          185            3.225576\n",
+       "  171          186            3.211897\n",
+       "  172          187            3.197781\n",
+       "  173          188            3.184330\n",
+       "  174          189            3.171376\n",
+       "  175          190            3.157462\n",
+       "  176          191            3.146196\n",
+       "  177          192            3.133895\n",
+       "  178          193            3.120074\n",
+       "  179          194            3.106247,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  180          195            3.093825\n",
+       "  181          196            3.083056\n",
+       "  182          197            3.071212\n",
+       "  183          198            3.060880\n",
+       "  184          199            3.051463\n",
+       "  185          200            3.039760\n",
+       "  186          201            3.028937\n",
+       "  187          202            3.015400\n",
+       "  188          203            3.004436\n",
+       "  189          204            2.995119\n",
+       "  190          205            2.984384\n",
+       "  191          206            2.975067\n",
+       "  192          207            2.964574\n",
+       "  193          208            2.954155\n",
+       "  194          209            2.945000\n",
+       "  195          210            2.936187\n",
+       "  196          211            2.925593\n",
+       "  197          212            2.917010\n",
+       "  198          213            2.909077\n",
+       "  199          214            2.900547,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  200          215            2.891506\n",
+       "  201          216            2.882297\n",
+       "  202          217            2.873538\n",
+       "  203          218            2.866353\n",
+       "  204          219            2.855154\n",
+       "  205          220            2.846355\n",
+       "  206          221            2.839464\n",
+       "  207          222            2.832312\n",
+       "  208          223            2.823540\n",
+       "  209          224            2.814661\n",
+       "  210          225            2.808376\n",
+       "  211          226            2.802211\n",
+       "  212          227            2.796477\n",
+       "  213          228            2.787739\n",
+       "  214          229            2.781830\n",
+       "  215          230            2.776842\n",
+       "  216          231            2.770073\n",
+       "  217          232            2.764481\n",
+       "  218          233            2.757638\n",
+       "  219          234            2.753880,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  220          235            2.748281\n",
+       "  221          236            2.740147\n",
+       "  222          237            2.734494\n",
+       "  223          238            2.731973\n",
+       "  224          239            2.725164\n",
+       "  225          240            2.719067\n",
+       "  226          241            2.713568\n",
+       "  227          242            2.708365\n",
+       "  228          243            2.704803\n",
+       "  229          244            2.698437\n",
+       "  230          245            2.692696\n",
+       "  231          251            3.049460\n",
+       "  232          252            3.021543\n",
+       "  233          253            3.001895\n",
+       "  234          254            2.976748\n",
+       "  235          255            2.953678\n",
+       "  236          256            2.933135\n",
+       "  237          257            2.919134\n",
+       "  238          258            2.899411\n",
+       "  239          259            2.883225,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  240          260            2.869297\n",
+       "  241          261            2.855698\n",
+       "  242          262            2.843719\n",
+       "  243          263            2.831116\n",
+       "  244          264            2.819521\n",
+       "  245          265            2.809370\n",
+       "  246          266            2.800699\n",
+       "  247          267            2.790434\n",
+       "  248          268            2.782375\n",
+       "  249          269            2.773770\n",
+       "  250          270            2.766719\n",
+       "  251          271            2.759849\n",
+       "  252          272            2.752825\n",
+       "  253          273            2.747205\n",
+       "  254          274            2.741075\n",
+       "  255          275            2.734286\n",
+       "  256          276            2.728195\n",
+       "  257          277            2.721937\n",
+       "  258          278            2.716291\n",
+       "  259          279            2.712573,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  260          280            2.707115\n",
+       "  261          281            2.701133\n",
+       "  262          282            2.695614\n",
+       "  263          283            2.692898\n",
+       "  264          284            2.688220\n",
+       "  265          285            2.683292\n",
+       "  266          286            2.678896\n",
+       "  267          287            2.674607\n",
+       "  268          288            2.672705\n",
+       "  269          289            2.668847\n",
+       "  270          290            2.665587\n",
+       "  271          291            2.661231\n",
+       "  272          292            2.655672\n",
+       "  273          293            2.655329\n",
+       "  274          294            2.652788\n",
+       "  275          295            2.648345\n",
+       "  276          296            2.644372\n",
+       "  277          297            2.641414\n",
+       "  278          298            2.639694\n",
+       "  279          299            2.636669,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  280          300            2.632481\n",
+       "  281          301            2.629577\n",
+       "  282          302            2.628959\n",
+       "  283          303            2.627305\n",
+       "  284          304            2.624213\n",
+       "  285          305            2.622432\n",
+       "  286          306            2.620395\n",
+       "  287          307            2.617786\n",
+       "  288          308            2.617034\n",
+       "  289          309            2.614372\n",
+       "  290          310            2.611911\n",
+       "  291          311            2.610762\n",
+       "  292          312            2.609243\n",
+       "  293          313            2.607892\n",
+       "  294          314            2.606762\n",
+       "  295          315            2.604947\n",
+       "  296          316            2.602521\n",
+       "  297          317            2.600229\n",
+       "  298          318            2.599812\n",
+       "  299          319            2.599355,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  300          320            2.596821\n",
+       "  301          321            2.595940\n",
+       "  302          322            2.595859\n",
+       "  303          323            2.593708\n",
+       "  304          324            2.591221\n",
+       "  305          325            2.590294\n",
+       "  306          326            2.589292\n",
+       "  307          327            2.590388\n",
+       "  308          328            2.588102\n",
+       "  309          329            2.586866\n",
+       "  310          330            2.586677\n",
+       "  311          331            2.586926\n",
+       "  312          332            2.584082\n",
+       "  313          333            2.582731\n",
+       "  314          334            2.581400\n",
+       "  315          335            2.581064\n",
+       "  316          336            2.580042\n",
+       "  317          337            2.578839\n",
+       "  318          338            2.577165\n",
+       "  319          339            2.577556,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  320          340            2.577891\n",
+       "  321          341            2.576722\n",
+       "  322          342            2.575713\n",
+       "  323          343            2.573757\n",
+       "  324          344            2.574040\n",
+       "  325          345            2.572816\n",
+       "  326          346            2.572084\n",
+       "  327          347            2.571425\n",
+       "  328          348            2.571277\n",
+       "  329          349            2.572305\n",
+       "  330          350            2.572507\n",
+       "  331          356            2.863583\n",
+       "  332          357            2.846106\n",
+       "  333          358            2.837737\n",
+       "  334          359            2.815911\n",
+       "  335          360            2.808738\n",
+       "  336          361            2.794662\n",
+       "  337          362            2.781151\n",
+       "  338          363            2.774053\n",
+       "  339          364            2.764904,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  340          365            2.757268\n",
+       "  341          366            2.749995\n",
+       "  342          367            2.744079\n",
+       "  343          368            2.736733\n",
+       "  344          369            2.731879\n",
+       "  345          370            2.725023\n",
+       "  346          371            2.720599\n",
+       "  347          372            2.716970\n",
+       "  348          373            2.712540\n",
+       "  349          374            2.711518\n",
+       "  350          375            2.707317\n",
+       "  351          376            2.705119\n",
+       "  352          377            2.703465\n",
+       "  353          378            2.700931\n",
+       "  354          379            2.697993\n",
+       "  355          380            2.696703\n",
+       "  356          381            2.694088\n",
+       "  357          382            2.693362\n",
+       "  358          383            2.691937\n",
+       "  359          384            2.689463,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  360          385            2.689658\n",
+       "  361          386            2.690915\n",
+       "  362          387            2.688623\n",
+       "  363          388            2.686351\n",
+       "  364          389            2.685961\n",
+       "  365          390            2.686438\n",
+       "  366          391            2.687857\n",
+       "  367          392            2.686123\n",
+       "  368          393            2.685322\n",
+       "  369          394            2.686041\n",
+       "  370          395            2.687769\n",
+       "  371          396            2.687252\n",
+       "  372          397            2.688394\n",
+       "  373          398            2.688072\n",
+       "  374          399            2.687958\n",
+       "  375          400            2.688690\n",
+       "  376          401            2.687252\n",
+       "  377          402            2.687998\n",
+       "  378          403            2.689651\n",
+       "  379          404            2.690277,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  380          405            2.690740\n",
+       "  381          406            2.690156\n",
+       "  382          407            2.689860\n",
+       "  383          408            2.690619\n",
+       "  384          409            2.690230\n",
+       "  385          410            2.691621\n",
+       "  386          411            2.691964\n",
+       "  387          412            2.692320\n",
+       "  388          413            2.690216\n",
+       "  389          414            2.691325\n",
+       "  390          415            2.692394\n",
+       "  391          416            2.692609\n",
+       "  392          417            2.693564\n",
+       "  393          418            2.691923\n",
+       "  394          419            2.692105\n",
+       "  395          420            2.693698\n",
+       "  396          421            2.693174\n",
+       "  397          422            2.692253\n",
+       "  398          423            2.691836\n",
+       "  399          424            2.691325,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  400          425            2.691554\n",
+       "  401          426            2.692784\n",
+       "  402          427            2.690162\n",
+       "  403          428            2.689429\n",
+       "  404          429            2.689900\n",
+       "  405          430            2.687030\n",
+       "  406          431            2.686600\n",
+       "  407          432            2.685652\n",
+       "  408          433            2.683535\n",
+       "  409          434            2.684402\n",
+       "  410          435            2.680247\n",
+       "  411          436            2.676786\n",
+       "  412          437            2.673734\n",
+       "  413          438            2.671690\n",
+       "  414          439            2.668222\n",
+       "  415          440            2.662642\n",
+       "  416          441            2.656747\n",
+       "  417          442            2.653265\n",
+       "  418          443            2.649629\n",
+       "  419          444            2.641710,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  420          445            2.634686\n",
+       "  421          446            2.626431\n",
+       "  422          447            2.618620\n",
+       "  423          448            2.610184\n",
+       "  424          449            2.600464\n",
+       "  425          450            2.590872\n",
+       "  426          451            2.581757\n",
+       "  427          452            2.570269\n",
+       "  428          453            2.556522\n",
+       "  429          454            2.543448\n",
+       "  430          455            2.528855\n",
+       "  431          461            2.686391\n",
+       "  432          462            2.603791\n",
+       "  433          463            2.577058\n",
+       "  434          464            2.548516\n",
+       "  435          465            2.528418\n",
+       "  436          466            2.484994\n",
+       "  437          467            2.449770\n",
+       "  438          468            2.410749\n",
+       "  439          469            2.370168,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  440          470            2.330226\n",
+       "  441          471            2.287111\n",
+       "  442          472            2.250725\n",
+       "  443          473            2.207093\n",
+       "  444          474            2.163709\n",
+       "  445          475            2.119841\n",
+       "  446          476            2.078017\n",
+       "  447          477            2.031595\n",
+       "  448          478            1.983956\n",
+       "  449          479            1.936075\n",
+       "  450          480            1.886964\n",
+       "  451          481            1.837934\n",
+       "  452          482            1.790315\n",
+       "  453          483            1.743396\n",
+       "  454          484            1.695166\n",
+       "  455          485            1.650700\n",
+       "  456          486            1.609272\n",
+       "  457          487            1.565505\n",
+       "  458          488            1.524104\n",
+       "  459          489            1.483685,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  460          490            1.443696\n",
+       "  461          491            1.409602\n",
+       "  462          492            1.369828\n",
+       "  463          493            1.333919\n",
+       "  464          494            1.300585\n",
+       "  465          495            1.269596\n",
+       "  466          496            1.239441\n",
+       "  467          497            1.212069\n",
+       "  468          498            1.185826\n",
+       "  469          499            1.165224\n",
+       "  470          500            1.144412\n",
+       "  471          501            1.125040\n",
+       "  472          502            1.106561\n",
+       "  473          503            1.088620\n",
+       "  474          504            1.070551\n",
+       "  475          505            1.054398\n",
+       "  476          506            1.037660\n",
+       "  477          507            1.023746\n",
+       "  478          508            1.008359\n",
+       "  479          509            0.996139,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  480          510            0.981592\n",
+       "  481          511            0.970380\n",
+       "  482          512            0.959705\n",
+       "  483          513            0.948641\n",
+       "  484          514            0.939055\n",
+       "  485          515            0.927453\n",
+       "  486          516            0.917955\n",
+       "  487          517            0.909297\n",
+       "  488          518            0.900969\n",
+       "  489          519            0.892136\n",
+       "  490          520            0.885454\n",
+       "  491          521            0.876689\n",
+       "  492          522            0.867984\n",
+       "  493          523            0.861161\n",
+       "  494          524            0.853760\n",
+       "  495          525            0.845774\n",
+       "  496          526            0.837540\n",
+       "  497          527            0.829036\n",
+       "  498          528            0.821884\n",
+       "  499          529            0.814819,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  500          530            0.808662\n",
+       "  501          531            0.801638\n",
+       "  502          532            0.794734\n",
+       "  503          533            0.789276\n",
+       "  504          534            0.782144\n",
+       "  505          535            0.775852\n",
+       "  506          536            0.768908\n",
+       "  507          537            0.762025\n",
+       "  508          538            0.755310\n",
+       "  509          539            0.748554\n",
+       "  510          540            0.743492\n",
+       "  511          541            0.737564\n",
+       "  512          542            0.731762\n",
+       "  513          543            0.726687\n",
+       "  514          544            0.720503\n",
+       "  515          545            0.715542\n",
+       "  516          546            0.709519\n",
+       "  517          547            0.702777\n",
+       "  518          548            0.699040\n",
+       "  519          549            0.693279,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  520          550            0.688963\n",
+       "  521          551            0.683115\n",
+       "  522          552            0.677247\n",
+       "  523          553            0.672394\n",
+       "  524          554            0.668629\n",
+       "  525          555            0.662687\n",
+       "  526          556            0.659756\n",
+       "  527          557            0.654607\n",
+       "  528          558            0.651098\n",
+       "  529          559            0.646769\n",
+       "  530          560            0.641190\n",
+       "  531          566            0.802256\n",
+       "  532          567            0.632068\n",
+       "  533          568            0.618853\n",
+       "  534          569            0.613119\n",
+       "  535          570            0.607795\n",
+       "  536          571            0.603567\n",
+       "  537          572            0.599460\n",
+       "  538          573            0.592967\n",
+       "  539          574            0.589263,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  540          575            0.585263\n",
+       "  541          576            0.578810\n",
+       "  542          577            0.574730\n",
+       "  543          578            0.569231\n",
+       "  544          579            0.564902\n",
+       "  545          580            0.562005\n",
+       "  546          581            0.556843\n",
+       "  547          582            0.552984\n",
+       "  548          583            0.550954\n",
+       "  549          584            0.545664\n",
+       "  550          585            0.541073\n",
+       "  551          586            0.538384\n",
+       "  552          587            0.533443\n",
+       "  553          588            0.529861\n",
+       "  554          589            0.526217\n",
+       "  555          590            0.523064\n",
+       "  556          591            0.520194\n",
+       "  557          592            0.516652\n",
+       "  558          593            0.512343\n",
+       "  559          594            0.510636,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  560          595            0.506448\n",
+       "  561          596            0.502119\n",
+       "  562          597            0.499712\n",
+       "  563          598            0.497198\n",
+       "  564          599            0.492224\n",
+       "  565          600            0.490792\n",
+       "  566          601            0.487935\n",
+       "  567          602            0.485354\n",
+       "  568          603            0.484292\n",
+       "  569          604            0.480326\n",
+       "  570          605            0.477920\n",
+       "  571          606            0.475305\n",
+       "  572          607            0.471614\n",
+       "  573          608            0.467837\n",
+       "  574          609            0.466284\n",
+       "  575          610            0.463138\n",
+       "  576          611            0.460227\n",
+       "  577          612            0.459447\n",
+       "  578          613            0.456335\n",
+       "  579          614            0.454070,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  580          615            0.451838\n",
+       "  581          616            0.449365\n",
+       "  582          617            0.446743\n",
+       "  583          618            0.445190\n",
+       "  584          619            0.442535\n",
+       "  585          620            0.440458\n",
+       "  586          621            0.437325\n",
+       "  587          622            0.435336\n",
+       "  588          623            0.433124\n",
+       "  589          624            0.430321\n",
+       "  590          625            0.428795\n",
+       "  591          626            0.426322\n",
+       "  592          627            0.424554\n",
+       "  593          628            0.422430\n",
+       "  594          629            0.419647\n",
+       "  595          630            0.417496\n",
+       "  596          631            0.415976\n",
+       "  597          632            0.413489\n",
+       "  598          633            0.412582\n",
+       "  599          634            0.411258,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  600          635            0.410989\n",
+       "  601          636            0.408804\n",
+       "  602          637            0.405947\n",
+       "  603          638            0.403689\n",
+       "  604          639            0.402828\n",
+       "  605          640            0.399978\n",
+       "  606          641            0.396725\n",
+       "  607          642            0.395716\n",
+       "  608          643            0.393713\n",
+       "  609          644            0.391851\n",
+       "  610          645            0.390406\n",
+       "  611          646            0.388504\n",
+       "  612          647            0.385586\n",
+       "  613          648            0.384914\n",
+       "  614          649            0.382958\n",
+       "  615          650            0.379160\n",
+       "  616          651            0.379247\n",
+       "  617          652            0.376619\n",
+       "  618          653            0.373998\n",
+       "  619          654            0.372667,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  620          655            0.370939\n",
+       "  621          656            0.368022\n",
+       "  622          657            0.368438\n",
+       "  623          658            0.364372\n",
+       "  624          659            0.361468\n",
+       "  625          660            0.360896\n",
+       "  626          661            0.358349\n",
+       "  627          662            0.356594\n",
+       "  628          663            0.354766\n",
+       "  629          664            0.352326\n",
+       "  630          665            0.351385\n",
+       "  631          671            0.418074\n",
+       "  632          672            0.333498\n",
+       "  633          673            0.331178\n",
+       "  634          674            0.326607\n",
+       "  635          675            0.325330\n",
+       "  636          676            0.323455\n",
+       "  637          677            0.319879\n",
+       "  638          678            0.318635\n",
+       "  639          679            0.317909,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  640          680            0.315738\n",
+       "  641          681            0.314058\n",
+       "  642          682            0.313345\n",
+       "  643          683            0.310777\n",
+       "  644          684            0.309211\n",
+       "  645          685            0.305877\n",
+       "  646          686            0.306354\n",
+       "  647          687            0.302637\n",
+       "  648          688            0.300499\n",
+       "  649          689            0.300116\n",
+       "  650          690            0.295337\n",
+       "  651          691            0.293939\n",
+       "  652          692            0.292292\n",
+       "  653          693            0.290436\n",
+       "  654          694            0.289650\n",
+       "  655          695            0.286746\n",
+       "  656          696            0.284635\n",
+       "  657          697            0.283775\n",
+       "  658          698            0.281496\n",
+       "  659          699            0.279869,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  660          700            0.277013\n",
+       "  661          701            0.275527\n",
+       "  662          702            0.273510\n",
+       "  663          703            0.271783\n",
+       "  664          704            0.269914\n",
+       "  665          705            0.267461\n",
+       "  666          706            0.267064\n",
+       "  667          707            0.265404\n",
+       "  668          708            0.263165\n",
+       "  669          709            0.261807\n",
+       "  670          710            0.259925\n",
+       "  671          711            0.257969\n",
+       "  672          712            0.259280\n",
+       "  673          713            0.256195\n",
+       "  674          714            0.253970\n",
+       "  675          715            0.253472\n",
+       "  676          716            0.251704\n",
+       "  677          717            0.251711\n",
+       "  678          718            0.247543\n",
+       "  679          719            0.246959,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  680          720            0.245829\n",
+       "  681          721            0.244424\n",
+       "  682          722            0.242972\n",
+       "  683          723            0.242166\n",
+       "  684          724            0.240815\n",
+       "  685          725            0.239363\n",
+       "  686          726            0.238408\n",
+       "  687          727            0.239006\n",
+       "  688          728            0.236035\n",
+       "  689          729            0.236358\n",
+       "  690          730            0.236250\n",
+       "  691          731            0.233851\n",
+       "  692          732            0.232036\n",
+       "  693          733            0.231995\n",
+       "  694          734            0.232936\n",
+       "  695          735            0.229340\n",
+       "  696          736            0.228399\n",
+       "  697          737            0.227566\n",
+       "  698          738            0.225973\n",
+       "  699          739            0.224655,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  700          740            0.223989\n",
+       "  701          741            0.222793\n",
+       "  702          742            0.220622\n",
+       "  703          743            0.219378\n",
+       "  704          744            0.219647\n",
+       "  705          745            0.217691\n",
+       "  706          746            0.215506\n",
+       "  707          747            0.215567\n",
+       "  708          748            0.213994\n",
+       "  709          749            0.213839\n",
+       "  710          750            0.211460\n",
+       "  711          751            0.211433\n",
+       "  712          752            0.210861\n",
+       "  713          753            0.209853\n",
+       "  714          754            0.209376\n",
+       "  715          755            0.206613\n",
+       "  716          756            0.207386\n",
+       "  717          757            0.205981\n",
+       "  718          758            0.205033\n",
+       "  719          759            0.203897,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  720          760            0.202647\n",
+       "  721          761            0.203239\n",
+       "  722          762            0.200086\n",
+       "  723          763            0.200456\n",
+       "  724          764            0.199737\n",
+       "  725          765            0.198043\n",
+       "  726          766            0.198984\n",
+       "  727          767            0.195965\n",
+       "  728          768            0.195179\n",
+       "  729          769            0.195004\n",
+       "  730          770            0.193283\n",
+       "  731          776            0.204731\n",
+       "  732          777            0.179080\n",
+       "  733          778            0.179813\n",
+       "  734          779            0.180639\n",
+       "  735          780            0.181157\n",
+       "  736          781            0.183516\n",
+       "  737          782            0.180760\n",
+       "  738          783            0.182468\n",
+       "  739          784            0.182804,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  740          785            0.180175\n",
+       "  741          786            0.179221\n",
+       "  742          787            0.178522\n",
+       "  743          788            0.178145\n",
+       "  744          789            0.176418\n",
+       "  745          790            0.174106\n",
+       "  746          791            0.175053\n",
+       "  747          792            0.171229\n",
+       "  748          793            0.172331\n",
+       "  749          794            0.170476\n",
+       "  750          795            0.168614\n",
+       "  751          796            0.170019\n",
+       "  752          797            0.167397\n",
+       "  753          798            0.168351\n",
+       "  754          799            0.165542\n",
+       "  755          800            0.164802\n",
+       "  756          801            0.164950\n",
+       "  757          802            0.162053\n",
+       "  758          803            0.162779\n",
+       "  759          804            0.161045,\n",
+       "       cycle_index  discharge_capacity\n",
+       "  760          805            0.161650\n",
+       "  761          806            0.159942\n",
+       "  762          807            0.158188\n",
+       "  763          808            0.158463\n",
+       "  764          809            0.156561\n",
+       "  765          810            0.155620\n",
+       "  766          811            0.154968\n",
+       "  767          812            0.156245\n",
+       "  768          813            0.154235\n",
+       "  769          814            0.151795\n",
+       "  770          815            0.153079\n",
+       "  771          816            0.150565\n",
+       "  772          817            0.150693\n",
+       "  773          818            0.150095\n",
+       "  774          819            0.850717\n",
+       "  775          820            0.662370\n",
+       "  776          821            0.801814\n",
+       "  777          822            0.454392\n",
+       "  778          823            0.048896\n",
+       "  779          824            0.022749]]"
+      ]
+     },
+     "execution_count": 145,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cell_labels"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 156,
+   "id": "d66c31ee",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "50"
+      ]
+     },
+     "execution_count": 156,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(cell_labels[0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 167,
+   "id": "a80595ed",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[      voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 118  2.700801 -0.691463            0            4.756813         3.857488\n",
+       " 119  2.702502 -0.691911            0            4.755975         3.857488\n",
+       " 120  2.704204 -0.691374            0            4.755099         3.857488\n",
+       " 121  2.705906 -0.691747            0            4.754218         3.857488\n",
+       " 122  2.707608 -0.691463            0            4.753360         3.857488\n",
+       " ..        ...       ...          ...                 ...              ...\n",
+       " 981  4.169369 -0.691463            0            0.000463         3.857488\n",
+       " 982  4.171071 -0.691463            0            0.000184         3.857488\n",
+       " 983  4.172773 -0.691623            0            0.000051         3.857488\n",
+       " 984  4.174474 -0.693506            0            0.000025         3.857488\n",
+       " 985  4.176176 -0.695775            0            0.000012         3.857488\n",
+       " \n",
+       " [868 rows x 5 columns],\n",
+       "        voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 1118  2.700801 -14.520006            6            4.482246         4.541034\n",
+       " 1119  2.702502 -14.519932            6            4.480342         4.541034\n",
+       " 1120  2.704204 -14.519858            6            4.478439         4.541034\n",
+       " 1121  2.705906 -14.519813            6            4.476541         4.541034\n",
+       " 1122  2.707608 -14.519885            6            4.474664         4.541034\n",
+       " ...        ...        ...          ...                 ...              ...\n",
+       " 1814  3.885185 -14.521509            6            0.000272         4.541034\n",
+       " 1815  3.886887 -14.521586            6            0.000248         4.541034\n",
+       " 1816  3.888589 -14.521664            6            0.000224         4.541034\n",
+       " 1817  3.890290 -14.521741            6            0.000200         4.541034\n",
+       " 1818  3.891992 -14.521818            6            0.000175         4.541034\n",
+       " \n",
+       " [701 rows x 5 columns],\n",
+       "        voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 2118  2.700801 -14.520256            7            4.482755         4.492178\n",
+       " 2119  2.702502 -14.520206            7            4.480971         4.492178\n",
+       " 2120  2.704204 -14.520131            7            4.479066         4.492178\n",
+       " 2121  2.705906 -14.520057            7            4.477161         4.492178\n",
+       " 2122  2.707608 -14.520027            7            4.475281         4.492178\n",
+       " ...        ...        ...          ...                 ...              ...\n",
+       " 2823  3.900501 -14.525382            7            0.000209         4.492178\n",
+       " 2824  3.902202 -14.525579            7            0.000188         4.492178\n",
+       " 2825  3.903904 -14.525777            7            0.000167         4.492178\n",
+       " 2826  3.905606 -14.525975            7            0.000147         4.492178\n",
+       " 2827  3.907307 -14.526173            7            0.000126         4.492178\n",
+       " \n",
+       " [710 rows x 5 columns],\n",
+       "        voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 3118  2.700801 -14.520404            8            4.476952         4.486927\n",
+       " 3119  2.702502 -14.520188            8            4.475152         4.486927\n",
+       " 3120  2.704204 -14.519972            8            4.473353         4.486927\n",
+       " 3121  2.705906 -14.519784            8            4.471549         4.486927\n",
+       " 3122  2.707608 -14.519710            8            4.469724         4.486927\n",
+       " ...        ...        ...          ...                 ...              ...\n",
+       " 3824  3.902202 -14.525090            8            0.000215         4.486927\n",
+       " 3825  3.903904 -14.525285            8            0.000195         4.486927\n",
+       " 3826  3.905606 -14.525479            8            0.000175         4.486927\n",
+       " 3827  3.907307 -14.525674            8            0.000154         4.486927\n",
+       " 3828  3.909009 -14.525868            8            0.000134         4.486927\n",
+       " \n",
+       " [711 rows x 5 columns],\n",
+       "        voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 4118  2.700801 -14.520256            9            4.473556         4.481853\n",
+       " 4119  2.702502 -14.520256            9            4.471739         4.481853\n",
+       " 4120  2.704204 -14.520230            9            4.469918         4.481853\n",
+       " 4121  2.705906 -14.519938            9            4.468041         4.481853\n",
+       " 4122  2.707608 -14.519647            9            4.466165         4.481853\n",
+       " ...        ...        ...          ...                 ...              ...\n",
+       " 4826  3.905606 -14.525805            9            0.000206         4.481853\n",
+       " 4827  3.907307 -14.526012            9            0.000186         4.481853\n",
+       " 4828  3.909009 -14.526221            9            0.000166         4.481853\n",
+       " 4829  3.910711 -14.526429            9            0.000145         4.481853\n",
+       " 4830  3.912412 -14.526637            9            0.000125         4.481853\n",
+       " \n",
+       " [713 rows x 5 columns],\n",
+       "        voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 5118  2.700801 -14.519644           10            4.469127         4.477909\n",
+       " 5119  2.702502 -14.519803           10            4.467328         4.477909\n",
+       " 5120  2.704204 -14.519963           10            4.465528         4.477909\n",
+       " 5121  2.705906 -14.520027           10            4.463714         4.477909\n",
+       " 5122  2.707608 -14.520027           10            4.461888         4.477909\n",
+       " ...        ...        ...          ...                 ...              ...\n",
+       " 5828  3.909009 -14.525447           10            0.000219         4.477909\n",
+       " 5829  3.910711 -14.525658           10            0.000198         4.477909\n",
+       " 5830  3.912412 -14.525868           10            0.000178         4.477909\n",
+       " 5831  3.914114 -14.526079           10            0.000157         4.477909\n",
+       " 5832  3.915816 -14.526290           10            0.000137         4.477909\n",
+       " \n",
+       " [715 rows x 5 columns],\n",
+       "        voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 6118  2.700801 -14.519798           11            4.465600         4.474064\n",
+       " 6119  2.702502 -14.519798           11            4.463848         4.474064\n",
+       " 6120  2.704204 -14.519798           11            4.462096         4.474064\n",
+       " 6121  2.705906 -14.519731           11            4.460230         4.474064\n",
+       " 6122  2.707608 -14.519657           11            4.458352         4.474064\n",
+       " ...        ...        ...          ...                 ...              ...\n",
+       " 6823  3.900501 -14.521245           11            0.000272         4.474064\n",
+       " 6824  3.902202 -14.521278           11            0.000249         4.474064\n",
+       " 6825  3.903904 -14.521311           11            0.000226         4.474064\n",
+       " 6826  3.905606 -14.521344           11            0.000203         4.474064\n",
+       " 6827  3.907307 -14.521377           11            0.000179         4.474064\n",
+       " \n",
+       " [710 rows x 5 columns],\n",
+       "        voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 7118  2.700801 -14.520403           12            4.459919         4.468312\n",
+       " 7119  2.702502 -14.520244           12            4.458176         4.468312\n",
+       " 7120  2.704204 -14.520172           12            4.456402         4.468312\n",
+       " 7121  2.705906 -14.520101           12            4.454628         4.468312\n",
+       " 7122  2.707608 -14.520028           12            4.452855         4.468312\n",
+       " ...        ...        ...          ...                 ...              ...\n",
+       " 7828  3.909009 -14.525272           12            0.000217         4.468312\n",
+       " 7829  3.910711 -14.525464           12            0.000197         4.468312\n",
+       " 7830  3.912412 -14.525657           12            0.000178         4.468312\n",
+       " 7831  3.914114 -14.525848           12            0.000159         4.468312\n",
+       " 7832  3.915816 -14.526040           12            0.000139         4.468312\n",
+       " \n",
+       " [715 rows x 5 columns],\n",
+       "        voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 8118  2.700801 -14.520116           13            4.455410         4.463356\n",
+       " 8119  2.702502 -14.519815           13            4.453691         4.463356\n",
+       " 8120  2.704204 -14.519798           13            4.451859         4.463356\n",
+       " 8121  2.705906 -14.519798           13            4.450021         4.463356\n",
+       " 8122  2.707608 -14.519798           13            4.448183         4.463356\n",
+       " ...        ...        ...          ...                 ...              ...\n",
+       " 8829  3.910711 -14.524277           13            0.000219         4.463356\n",
+       " 8830  3.912412 -14.524436           13            0.000199         4.463356\n",
+       " 8831  3.914114 -14.524594           13            0.000180         4.463356\n",
+       " 8832  3.915816 -14.524754           13            0.000160         4.463356\n",
+       " 8833  3.917517 -14.524912           13            0.000141         4.463356\n",
+       " \n",
+       " [716 rows x 5 columns],\n",
+       "        voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 9118  2.700801 -14.520256           14            4.450332         4.460022\n",
+       " 9119  2.702502 -14.520256           14            4.448533         4.460022\n",
+       " 9120  2.704204 -14.520256           14            4.446733         4.460022\n",
+       " 9121  2.705906 -14.520256           14            4.444934         4.460022\n",
+       " 9122  2.707608 -14.520188           14            4.443135         4.460022\n",
+       " ...        ...        ...          ...                 ...              ...\n",
+       " 9829  3.910711 -14.526074           14            0.000215         4.460022\n",
+       " 9830  3.912412 -14.526288           14            0.000196         4.460022\n",
+       " 9831  3.914114 -14.526503           14            0.000177         4.460022\n",
+       " 9832  3.915816 -14.526716           14            0.000158         4.460022\n",
+       " 9833  3.917517 -14.526930           14            0.000139         4.460022\n",
+       " \n",
+       " [716 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 10118  2.700801 -14.519798           15            4.444081         4.453266\n",
+       " 10119  2.702502 -14.519859           15            4.442332         4.453266\n",
+       " 10120  2.704204 -14.519933           15            4.440546         4.453266\n",
+       " 10121  2.705906 -14.520005           15            4.438759         4.453266\n",
+       " 10122  2.707608 -14.519925           15            4.436973         4.453266\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 10829  3.910711 -14.525947           15            0.000215         4.453266\n",
+       " 10830  3.912412 -14.526138           15            0.000196         4.453266\n",
+       " 10831  3.914114 -14.526329           15            0.000177         4.453266\n",
+       " 10832  3.915816 -14.526521           15            0.000159         4.453266\n",
+       " 10833  3.917517 -14.526712           15            0.000140         4.453266\n",
+       " \n",
+       " [716 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 11118  2.700801 -14.519838           16            4.438663         4.447062\n",
+       " 11119  2.702502 -14.519923           16            4.436924         4.447062\n",
+       " 11120  2.704204 -14.520008           16            4.435184         4.447062\n",
+       " 11121  2.705906 -14.519971           16            4.433379         4.447062\n",
+       " 11122  2.707608 -14.519897           16            4.431554         4.447062\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 11831  3.914114 -14.524817           16            0.000199         4.447062\n",
+       " 11832  3.915816 -14.524992           16            0.000180         4.447062\n",
+       " 11833  3.917517 -14.525167           16            0.000161         4.447062\n",
+       " 11834  3.919219 -14.525342           16            0.000142         4.447062\n",
+       " 11835  3.920921 -14.525517           16            0.000123         4.447062\n",
+       " \n",
+       " [718 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 12118  2.700801 -14.520027           17            4.433584         4.442595\n",
+       " 12119  2.702502 -14.520027           17            4.431851         4.442595\n",
+       " 12120  2.704204 -14.520027           17            4.430115         4.442595\n",
+       " 12121  2.705906 -14.520027           17            4.428290         4.442595\n",
+       " 12122  2.707608 -14.520027           17            4.426465         4.442595\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 12830  3.912412 -14.524177           17            0.000207         4.442595\n",
+       " 12831  3.914114 -14.524319           17            0.000188         4.442595\n",
+       " 12832  3.915816 -14.524461           17            0.000170         4.442595\n",
+       " 12833  3.917517 -14.524603           17            0.000152         4.442595\n",
+       " 12834  3.919219 -14.524746           17            0.000134         4.442595\n",
+       " \n",
+       " [717 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 13118  2.700801 -14.520027           18            4.428654         4.436209\n",
+       " 13119  2.702502 -14.520027           18            4.426897         4.436209\n",
+       " 13120  2.704204 -14.520027           18            4.425140         4.436209\n",
+       " 13121  2.705906 -14.519981           18            4.423372         4.436209\n",
+       " 13122  2.707608 -14.519909           18            4.421598         4.436209\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 13830  3.912412 -14.524445           18            0.000210         4.436209\n",
+       " 13831  3.914114 -14.524573           18            0.000191         4.436209\n",
+       " 13832  3.915816 -14.524702           18            0.000173         4.436209\n",
+       " 13833  3.917517 -14.524831           18            0.000155         4.436209\n",
+       " 13834  3.919219 -14.524960           18            0.000137         4.436209\n",
+       " \n",
+       " [717 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 14118  2.700801 -14.519978           19            4.423285         4.431855\n",
+       " 14119  2.702502 -14.519871           19            4.421524         4.431855\n",
+       " 14120  2.704204 -14.519843           19            4.419746         4.431855\n",
+       " 14121  2.705906 -14.519987           19            4.417934         4.431855\n",
+       " 14122  2.707608 -14.520131           19            4.416122         4.431855\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 14830  3.912412 -14.524783           19            0.000206         4.431855\n",
+       " 14831  3.914114 -14.524943           19            0.000188         4.431855\n",
+       " 14832  3.915816 -14.525103           19            0.000170         4.431855\n",
+       " 14833  3.917517 -14.525262           19            0.000152         4.431855\n",
+       " 14834  3.919219 -14.525422           19            0.000134         4.431855\n",
+       " \n",
+       " [717 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 15118  2.700801 -14.520485           20            4.417915         4.426726\n",
+       " 15119  2.702502 -14.520485           20            4.416142         4.426726\n",
+       " 15120  2.704204 -14.520485           20            4.414369         4.426726\n",
+       " 15121  2.705906 -14.520412           20            4.412608         4.426726\n",
+       " 15122  2.707608 -14.520190           20            4.410874         4.426726\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 15830  3.912412 -14.525632           20            0.000203         4.426726\n",
+       " 15831  3.914114 -14.525807           20            0.000186         4.426726\n",
+       " 15832  3.915816 -14.525984           20            0.000168         4.426726\n",
+       " 15833  3.917517 -14.526159           20            0.000150         4.426726\n",
+       " 15834  3.919219 -14.526335           20            0.000133         4.426726\n",
+       " \n",
+       " [717 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 16118  2.700801 -14.520027           21            4.411853         4.421103\n",
+       " 16119  2.702502 -14.519988           21            4.410088         4.421103\n",
+       " 16120  2.704204 -14.519915           21            4.408276         4.421103\n",
+       " 16121  2.705906 -14.519840           21            4.406464         4.421103\n",
+       " 16122  2.707608 -14.519798           21            4.404684         4.421103\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 16830  3.912412 -14.525681           21            0.000196         4.421103\n",
+       " 16831  3.914114 -14.525862           21            0.000178         4.421103\n",
+       " 16832  3.915816 -14.526043           21            0.000161         4.421103\n",
+       " 16833  3.917517 -14.526224           21            0.000143         4.421103\n",
+       " 16834  3.919219 -14.526405           21            0.000125         4.421103\n",
+       " \n",
+       " [717 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 17118  2.700801 -14.520232           22            4.406054         4.414199\n",
+       " 17119  2.702502 -14.520159           22            4.404281         4.414199\n",
+       " 17120  2.704204 -14.520086           22            4.402507         4.414199\n",
+       " 17121  2.705906 -14.520027           22            4.400736         4.414199\n",
+       " 17122  2.707608 -14.520027           22            4.398976         4.414199\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 17829  3.910711 -14.525145           22            0.000210         4.414199\n",
+       " 17830  3.912412 -14.525311           22            0.000192         4.414199\n",
+       " 17831  3.914114 -14.525478           22            0.000175         4.414199\n",
+       " 17832  3.915816 -14.525645           22            0.000157         4.414199\n",
+       " 17833  3.917517 -14.525812           22            0.000140         4.414199\n",
+       " \n",
+       " [716 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 18118  2.700801 -14.519798           23            4.400772         4.409393\n",
+       " 18119  2.702502 -14.519798           23            4.398999         4.409393\n",
+       " 18120  2.704204 -14.519798           23            4.397226         4.409393\n",
+       " 18121  2.705906 -14.519798           23            4.395434         4.409393\n",
+       " 18122  2.707608 -14.519798           23            4.393596         4.409393\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 18829  3.910711 -14.525597           23            0.000207         4.409393\n",
+       " 18830  3.912412 -14.525769           23            0.000190         4.409393\n",
+       " 18831  3.914114 -14.525942           23            0.000172         4.409393\n",
+       " 18832  3.915816 -14.526115           23            0.000155         4.409393\n",
+       " 18833  3.917517 -14.526288           23            0.000137         4.409393\n",
+       " \n",
+       " [716 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 19118  2.700801 -14.519862           24            4.399586         4.403893\n",
+       " 19119  2.702502 -14.520000           24            4.397860         4.403893\n",
+       " 19120  2.704204 -14.519968           24            4.396044         4.403893\n",
+       " 19121  2.705906 -14.519896           24            4.394206         4.403893\n",
+       " 19122  2.707608 -14.519822           24            4.392368         4.403893\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 19830  3.912412 -14.523899           24            0.000207         4.403893\n",
+       " 19831  3.914114 -14.523996           24            0.000189         4.403893\n",
+       " 19832  3.915816 -14.524095           24            0.000172         4.403893\n",
+       " 19833  3.917517 -14.524192           24            0.000155         4.403893\n",
+       " 19834  3.919219 -14.524289           24            0.000138         4.403893\n",
+       " \n",
+       " [717 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 20118  2.700801 -14.519244           25            4.397271         4.402388\n",
+       " 20119  2.702502 -14.519527           25            4.395597         4.402388\n",
+       " 20120  2.704204 -14.519631           25            4.393860         4.402388\n",
+       " 20121  2.705906 -14.519705           25            4.392112         4.402388\n",
+       " 20122  2.707608 -14.519777           25            4.390364         4.402388\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 20831  3.914114 -14.526211           25            0.000203         4.402388\n",
+       " 20832  3.915816 -14.526405           25            0.000186         4.402388\n",
+       " 20833  3.917517 -14.526599           25            0.000169         4.402388\n",
+       " 20834  3.919219 -14.526793           25            0.000151         4.402388\n",
+       " 20835  3.920921 -14.526988           25            0.000134         4.402388\n",
+       " \n",
+       " [718 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 21118  2.700801 -14.519981           26            4.394260          4.40094\n",
+       " 21119  2.702502 -14.520234           26            4.392518          4.40094\n",
+       " 21120  2.704204 -14.520160           26            4.390744          4.40094\n",
+       " 21121  2.705906 -14.520086           26            4.388971          4.40094\n",
+       " 21122  2.707608 -14.520041           26            4.387195          4.40094\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 21831  3.914114 -14.526452           26            0.000202          4.40094\n",
+       " 21832  3.915816 -14.526644           26            0.000185          4.40094\n",
+       " 21833  3.917517 -14.526835           26            0.000168          4.40094\n",
+       " 21834  3.919219 -14.527027           26            0.000151          4.40094\n",
+       " 21835  3.920921 -14.527219           26            0.000134          4.40094\n",
+       " \n",
+       " [718 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 22118  2.700801 -14.519860           27            4.390422         4.399085\n",
+       " 22119  2.702502 -14.520076           27            4.388711         4.399085\n",
+       " 22120  2.704204 -14.520291           27            4.387001         4.399085\n",
+       " 22121  2.705906 -14.520462           27            4.385277         4.399085\n",
+       " 22122  2.707608 -14.520236           27            4.383438         4.399085\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 22831  3.914114 -14.526466           27            0.000200         4.399085\n",
+       " 22832  3.915816 -14.526656           27            0.000184         4.399085\n",
+       " 22833  3.917517 -14.526847           27            0.000167         4.399085\n",
+       " 22834  3.919219 -14.527038           27            0.000150         4.399085\n",
+       " 22835  3.920921 -14.527227           27            0.000133         4.399085\n",
+       " \n",
+       " [718 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 23118  2.700801 -14.520195           28            4.382787         4.391406\n",
+       " 23119  2.702502 -14.520256           28            4.381002         4.391406\n",
+       " 23120  2.704204 -14.520256           28            4.379190         4.391406\n",
+       " 23121  2.705906 -14.520256           28            4.377378         4.391406\n",
+       " 23122  2.707608 -14.520193           28            4.375621         4.391406\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 23825  3.903904 -14.519860           28            0.000250         4.391406\n",
+       " 23826  3.905606 -14.519846           28            0.000230         4.391406\n",
+       " 23827  3.907307 -14.519833           28            0.000211         4.391406\n",
+       " 23828  3.909009 -14.519819           28            0.000192         4.391406\n",
+       " 23829  3.910711 -14.519805           28            0.000173         4.391406\n",
+       " \n",
+       " [712 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 24118  2.700801 -14.519694           29            4.377563         4.384727\n",
+       " 24119  2.702502 -14.519963           29            4.375835         4.384727\n",
+       " 24120  2.704204 -14.520082           29            4.374092         4.384727\n",
+       " 24121  2.705906 -14.520156           29            4.372344         4.384727\n",
+       " 24122  2.707608 -14.520228           29            4.370596         4.384727\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 24824  3.902202 -14.521212           29            0.000252         4.384727\n",
+       " 24825  3.903904 -14.521252           29            0.000233         4.384727\n",
+       " 24826  3.905606 -14.521292           29            0.000214         4.384727\n",
+       " 24827  3.907307 -14.521332           29            0.000195         4.384727\n",
+       " 24828  3.909009 -14.521372           29            0.000176         4.384727\n",
+       " \n",
+       " [711 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 25118  2.700801 -14.520027           30            4.372911          4.38055\n",
+       " 25119  2.702502 -14.519950           30            4.371221          4.38055\n",
+       " 25120  2.704204 -14.519801           30            4.369434          4.38055\n",
+       " 25121  2.705906 -14.519653           30            4.367648          4.38055\n",
+       " 25122  2.707608 -14.519631           30            4.365873          4.38055\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 25829  3.910711 -14.525270           30            0.000202          4.38055\n",
+       " 25830  3.912412 -14.525416           30            0.000186          4.38055\n",
+       " 25831  3.914114 -14.525562           30            0.000169          4.38055\n",
+       " 25832  3.915816 -14.525707           30            0.000153          4.38055\n",
+       " 25833  3.917517 -14.525853           30            0.000137          4.38055\n",
+       " \n",
+       " [716 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 26118  2.700801 -14.519833           31            4.366767         4.376842\n",
+       " 26119  2.702502 -14.519907           31            4.364981         4.376842\n",
+       " 26120  2.704204 -14.519980           31            4.363195         4.376842\n",
+       " 26121  2.705906 -14.520081           31            4.361413         4.376842\n",
+       " 26122  2.707608 -14.520225           31            4.359640         4.376842\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 26823  3.900501 -14.521403           31            0.000254         4.376842\n",
+       " 26824  3.902202 -14.521450           31            0.000235         4.376842\n",
+       " 26825  3.903904 -14.521496           31            0.000217         4.376842\n",
+       " 26826  3.905606 -14.521542           31            0.000198         4.376842\n",
+       " 26827  3.907307 -14.521588           31            0.000179         4.376842\n",
+       " \n",
+       " [710 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 27118  2.700801 -14.519958           32            4.360590         4.368238\n",
+       " 27119  2.702502 -14.519811           32            4.358791         4.368238\n",
+       " 27120  2.704204 -14.519662           32            4.356992         4.368238\n",
+       " 27121  2.705906 -14.519650           32            4.355207         4.368238\n",
+       " 27122  2.707608 -14.519870           32            4.353446         4.368238\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 27829  3.910711 -14.524078           32            0.000190         4.368238\n",
+       " 27830  3.912412 -14.524205           32            0.000174         4.368238\n",
+       " 27831  3.914114 -14.524333           32            0.000157         4.368238\n",
+       " 27832  3.915816 -14.524460           32            0.000141         4.368238\n",
+       " 27833  3.917517 -14.524587           32            0.000125         4.368238\n",
+       " \n",
+       " [716 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 28118  2.700801 -14.519953           33            4.355965         4.362786\n",
+       " 28119  2.702502 -14.519796           33            4.354195         4.362786\n",
+       " 28120  2.704204 -14.519724           33            4.352447         4.362786\n",
+       " 28121  2.705906 -14.519652           33            4.350698         4.362786\n",
+       " 28122  2.707608 -14.519580           33            4.348949         4.362786\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 28829  3.910711 -14.525503           33            0.000196         4.362786\n",
+       " 28830  3.912412 -14.525660           33            0.000180         4.362786\n",
+       " 28831  3.914114 -14.525816           33            0.000163         4.362786\n",
+       " 28832  3.915816 -14.525972           33            0.000147         4.362786\n",
+       " 28833  3.917517 -14.526129           33            0.000131         4.362786\n",
+       " \n",
+       " [716 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 29118  2.700801 -14.519798           34            4.352950         4.360024\n",
+       " 29119  2.702502 -14.519798           34            4.351199         4.360024\n",
+       " 29120  2.704204 -14.519917           34            4.349420         4.360024\n",
+       " 29121  2.705906 -14.520065           34            4.347634         4.360024\n",
+       " 29122  2.707608 -14.520214           34            4.345848         4.360024\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 29828  3.909009 -14.526061           34            0.000201         4.360024\n",
+       " 29829  3.910711 -14.526232           34            0.000185         4.360024\n",
+       " 29830  3.912412 -14.526403           34            0.000169         4.360024\n",
+       " 29831  3.914114 -14.526574           34            0.000153         4.360024\n",
+       " 29832  3.915816 -14.526745           34            0.000136         4.360024\n",
+       " \n",
+       " [715 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 30118  2.700801 -14.520131           35            4.344505         4.354329\n",
+       " 30119  2.702502 -14.519981           35            4.342771         4.354329\n",
+       " 30120  2.704204 -14.519908           35            4.340959         4.354329\n",
+       " 30121  2.705906 -14.519834           35            4.339146         4.354329\n",
+       " 30122  2.707608 -14.519872           35            4.337348         4.354329\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 30822  3.898799 -14.520857           35            0.000244         4.354329\n",
+       " 30823  3.900501 -14.520876           35            0.000226         4.354329\n",
+       " 30824  3.902202 -14.520895           35            0.000208         4.354329\n",
+       " 30825  3.903904 -14.520914           35            0.000190         4.354329\n",
+       " 30826  3.905606 -14.520933           35            0.000172         4.354329\n",
+       " \n",
+       " [709 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 31118  2.700801 -14.519981           41            4.332470         4.403173\n",
+       " 31119  2.702502 -14.519962           41            4.330622         4.403173\n",
+       " 31120  2.704204 -14.519890           41            4.328759         4.403173\n",
+       " 31121  2.705906 -14.519817           41            4.326895         4.403173\n",
+       " 31122  2.707608 -14.519743           41            4.325031         4.403173\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 31826  3.905606 -14.525601           41            0.000186         4.403173\n",
+       " 31827  3.907307 -14.525746           41            0.000171         4.403173\n",
+       " 31828  3.909009 -14.525891           41            0.000155         4.403173\n",
+       " 31829  3.910711 -14.526036           41            0.000140         4.403173\n",
+       " 31830  3.912412 -14.526181           41            0.000125         4.403173\n",
+       " \n",
+       " [713 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 32118  2.700801 -14.520027           42            4.314476         4.334279\n",
+       " 32119  2.702502 -14.520027           42            4.312562         4.334279\n",
+       " 32120  2.704204 -14.520027           42            4.310627         4.334279\n",
+       " 32121  2.705906 -14.520027           42            4.308684         4.334279\n",
+       " 32122  2.707608 -14.520027           42            4.306742         4.334279\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 32824  3.902202 -14.526319           42            0.000191         4.334279\n",
+       " 32825  3.903904 -14.526496           42            0.000176         4.334279\n",
+       " 32826  3.905606 -14.526674           42            0.000161         4.334279\n",
+       " 32827  3.907307 -14.526852           42            0.000146         4.334279\n",
+       " 32828  3.909009 -14.527030           42            0.000130         4.334279\n",
+       " \n",
+       " [711 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 33118  2.700801 -14.519920           43            4.312320         4.318172\n",
+       " 33119  2.702502 -14.520182           43            4.310451         4.318172\n",
+       " 33120  2.704204 -14.520203           43            4.308595         4.318172\n",
+       " 33121  2.705906 -14.520129           43            4.306744         4.318172\n",
+       " 33122  2.707608 -14.520055           43            4.304892         4.318172\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 33826  3.905606 -14.525371           43            0.000191         4.318172\n",
+       " 33827  3.907307 -14.525507           43            0.000176         4.318172\n",
+       " 33828  3.909009 -14.525643           43            0.000160         4.318172\n",
+       " 33829  3.910711 -14.525780           43            0.000145         4.318172\n",
+       " 33830  3.912412 -14.525917           43            0.000129         4.318172\n",
+       " \n",
+       " [713 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 34118  2.700801 -14.519862           44            4.306965         4.315179\n",
+       " 34119  2.702502 -14.520000           44            4.305117         4.315179\n",
+       " 34120  2.704204 -14.519968           44            4.303288         4.315179\n",
+       " 34121  2.705906 -14.519896           44            4.301463         4.315179\n",
+       " 34122  2.707608 -14.519822           44            4.299638         4.315179\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 34820  3.895395 -14.522270           44            0.000233         4.315179\n",
+       " 34821  3.897097 -14.522337           44            0.000216         4.315179\n",
+       " 34822  3.898799 -14.522404           44            0.000199         4.315179\n",
+       " 34823  3.900501 -14.522470           44            0.000182         4.315179\n",
+       " 34824  3.902202 -14.522536           44            0.000165         4.315179\n",
+       " \n",
+       " [707 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 35118  2.700801 -14.519674           45            4.302002         4.309985\n",
+       " 35119  2.702502 -14.519899           45            4.300150         4.309985\n",
+       " 35120  2.704204 -14.520124           45            4.298298         4.309985\n",
+       " 35121  2.705906 -14.520256           45            4.296434         4.309985\n",
+       " 35122  2.707608 -14.520256           45            4.294556         4.309985\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 35825  3.903904 -14.525907           45            0.000194         4.309985\n",
+       " 35826  3.905606 -14.526067           45            0.000179         4.309985\n",
+       " 35827  3.907307 -14.526227           45            0.000164         4.309985\n",
+       " 35828  3.909009 -14.526387           45            0.000149         4.309985\n",
+       " 35829  3.910711 -14.526547           45            0.000133         4.309985\n",
+       " \n",
+       " [712 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 36118  2.700801 -14.520137           46            4.296241         4.306491\n",
+       " 36119  2.702502 -14.520027           46            4.294418         4.306491\n",
+       " 36120  2.704204 -14.520027           46            4.292476         4.306491\n",
+       " 36121  2.705906 -14.520027           46            4.290533         4.306491\n",
+       " 36122  2.707608 -14.519958           46            4.288635         4.306491\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 36825  3.903904 -14.525807           46            0.000186         4.306491\n",
+       " 36826  3.905606 -14.525956           46            0.000171         4.306491\n",
+       " 36827  3.907307 -14.526104           46            0.000156         4.306491\n",
+       " 36828  3.909009 -14.526252           46            0.000141         4.306491\n",
+       " 36829  3.910711 -14.526401           46            0.000126         4.306491\n",
+       " \n",
+       " [712 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 37118  2.700801 -14.519454           47            4.291701         4.298993\n",
+       " 37119  2.702502 -14.519608           47            4.289862         4.298993\n",
+       " 37120  2.704204 -14.519681           47            4.287985         4.298993\n",
+       " 37121  2.705906 -14.519753           47            4.286109         4.298993\n",
+       " 37122  2.707608 -14.519798           47            4.284243         4.298993\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 37825  3.903904 -14.526272           47            0.000185         4.298993\n",
+       " 37826  3.905606 -14.526420           47            0.000170         4.298993\n",
+       " 37827  3.907307 -14.526568           47            0.000155         4.298993\n",
+       " 37828  3.909009 -14.526716           47            0.000140         4.298993\n",
+       " 37829  3.910711 -14.526865           47            0.000125         4.298993\n",
+       " \n",
+       " [712 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 38118  2.700801 -14.519957           48            4.287521         4.294162\n",
+       " 38119  2.702502 -14.520229           48            4.285738         4.294162\n",
+       " 38120  2.704204 -14.520011           48            4.283862         4.294162\n",
+       " 38121  2.705906 -14.519792           48            4.281986         4.294162\n",
+       " 38122  2.707608 -14.519573           48            4.280109         4.294162\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 38825  3.903904 -14.526563           48            0.000190         4.294162\n",
+       " 38826  3.905606 -14.526739           48            0.000175         4.294162\n",
+       " 38827  3.907307 -14.526917           48            0.000160         4.294162\n",
+       " 38828  3.909009 -14.527093           48            0.000145         4.294162\n",
+       " 38829  3.910711 -14.527269           48            0.000129         4.294162\n",
+       " \n",
+       " [712 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 39118  2.700801 -14.520020           49            4.283262         4.291245\n",
+       " 39119  2.702502 -14.519946           49            4.281373         4.291245\n",
+       " 39120  2.704204 -14.519874           49            4.279484         4.291245\n",
+       " 39121  2.705906 -14.519800           49            4.277595         4.291245\n",
+       " 39122  2.707608 -14.519729           49            4.275805         4.291245\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 39824  3.902202 -14.524950           49            0.000196         4.291245\n",
+       " 39825  3.903904 -14.525066           49            0.000181         4.291245\n",
+       " 39826  3.905606 -14.525182           49            0.000166         4.291245\n",
+       " 39827  3.907307 -14.525297           49            0.000151         4.291245\n",
+       " 39828  3.909009 -14.525414           49            0.000136         4.291245\n",
+       " \n",
+       " [711 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 40118  2.700801 -14.519798           50            4.277275         4.285218\n",
+       " 40119  2.702502 -14.519798           50            4.275503         4.285218\n",
+       " 40120  2.704204 -14.519870           50            4.273602         4.285218\n",
+       " 40121  2.705906 -14.519943           50            4.271700         4.285218\n",
+       " 40122  2.707608 -14.520016           50            4.269798         4.285218\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 40824  3.902202 -14.525525           50            0.000191         4.285218\n",
+       " 40825  3.903904 -14.525673           50            0.000176         4.285218\n",
+       " 40826  3.905606 -14.525821           50            0.000161         4.285218\n",
+       " 40827  3.907307 -14.525969           50            0.000146         4.285218\n",
+       " 40828  3.909009 -14.526116           50            0.000132         4.285218\n",
+       " \n",
+       " [711 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 41118  2.700801 -14.519574           51            4.275562         4.280601\n",
+       " 41119  2.702502 -14.519647           51            4.273673         4.280601\n",
+       " 41120  2.704204 -14.519720           51            4.271784         4.280601\n",
+       " 41121  2.705906 -14.519793           51            4.269895         4.280601\n",
+       " 41122  2.707608 -14.519933           51            4.268018         4.280601\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 41824  3.902202 -14.525789           51            0.000188         4.280601\n",
+       " 41825  3.903904 -14.525937           51            0.000173         4.280601\n",
+       " 41826  3.905606 -14.526084           51            0.000158         4.280601\n",
+       " 41827  3.907307 -14.526232           51            0.000143         4.280601\n",
+       " 41828  3.909009 -14.526379           51            0.000128         4.280601\n",
+       " \n",
+       " [711 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 42118  2.700801 -14.519868           52            4.267179         4.277286\n",
+       " 42119  2.702502 -14.520019           52            4.265379         4.277286\n",
+       " 42120  2.704204 -14.519821           52            4.263508         4.277286\n",
+       " 42121  2.705906 -14.519603           52            4.261631         4.277286\n",
+       " 42122  2.707608 -14.519383           52            4.259755         4.277286\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 42823  3.900501 -14.526369           52            0.000191         4.277286\n",
+       " 42824  3.902202 -14.526530           52            0.000176         4.277286\n",
+       " 42825  3.903904 -14.526692           52            0.000162         4.277286\n",
+       " 42826  3.905606 -14.526854           52            0.000147         4.277286\n",
+       " 42827  3.907307 -14.527015           52            0.000132         4.277286\n",
+       " \n",
+       " [710 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 43118  2.700801 -14.520027           53            4.264802          4.27068\n",
+       " 43119  2.702502 -14.520027           53            4.262920          4.27068\n",
+       " 43120  2.704204 -14.520027           53            4.261044          4.27068\n",
+       " 43121  2.705906 -14.520027           53            4.259168          4.27068\n",
+       " 43122  2.707608 -14.520027           53            4.257291          4.27068\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 43823  3.900501 -14.526529           53            0.000193          4.27068\n",
+       " 43824  3.902202 -14.526700           53            0.000178          4.27068\n",
+       " 43825  3.903904 -14.526872           53            0.000163          4.27068\n",
+       " 43826  3.905606 -14.527042           53            0.000149          4.27068\n",
+       " 43827  3.907307 -14.527214           53            0.000134          4.27068\n",
+       " \n",
+       " [710 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 44118  2.700801 -14.520027           54            4.259737         4.269398\n",
+       " 44119  2.702502 -14.520027           54            4.257895         4.269398\n",
+       " 44120  2.704204 -14.520027           54            4.256053         4.269398\n",
+       " 44121  2.705906 -14.520073           54            4.254198         4.269398\n",
+       " 44122  2.707608 -14.520145           54            4.252336         4.269398\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 44823  3.900501 -14.526402           54            0.000188         4.269398\n",
+       " 44824  3.902202 -14.526561           54            0.000174         4.269398\n",
+       " 44825  3.903904 -14.526719           54            0.000159         4.269398\n",
+       " 44826  3.905606 -14.526878           54            0.000145         4.269398\n",
+       " 44827  3.907307 -14.527038           54            0.000130         4.269398\n",
+       " \n",
+       " [710 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 45118  2.700801 -14.519879           55            4.255193         4.260923\n",
+       " 45119  2.702502 -14.520052           55            4.253378         4.260923\n",
+       " 45120  2.704204 -14.520225           55            4.251564         4.260923\n",
+       " 45121  2.705906 -14.520256           55            4.249656         4.260923\n",
+       " 45122  2.707608 -14.520256           55            4.247728         4.260923\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 45823  3.900501 -14.526405           55            0.000184         4.260923\n",
+       " 45824  3.902202 -14.526575           55            0.000169         4.260923\n",
+       " 45825  3.903904 -14.526746           55            0.000155         4.260923\n",
+       " 45826  3.905606 -14.526916           55            0.000140         4.260923\n",
+       " 45827  3.907307 -14.527085           55            0.000126         4.260923\n",
+       " \n",
+       " [710 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 46118  2.700801 -14.519798           56            4.252473         4.258512\n",
+       " 46119  2.702502 -14.519798           56            4.250623         4.258512\n",
+       " 46120  2.704204 -14.519929           56            4.248807         4.258512\n",
+       " 46121  2.705906 -14.520075           56            4.246995         4.258512\n",
+       " 46122  2.707608 -14.520221           56            4.245183         4.258512\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 46823  3.900501 -14.524491           56            0.000192         4.258512\n",
+       " 46824  3.902202 -14.524611           56            0.000178         4.258512\n",
+       " 46825  3.903904 -14.524730           56            0.000163         4.258512\n",
+       " 46826  3.905606 -14.524848           56            0.000149         4.258512\n",
+       " 46827  3.907307 -14.524967           56            0.000134         4.258512\n",
+       " \n",
+       " [710 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 47118  2.700801 -14.519649           57            4.247389         4.254043\n",
+       " 47119  2.702502 -14.519819           57            4.245620         4.254043\n",
+       " 47120  2.704204 -14.519989           57            4.243851         4.254043\n",
+       " 47121  2.705906 -14.519855           57            4.241977         4.254043\n",
+       " 47122  2.707608 -14.519633           57            4.240074         4.254043\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 47822  3.898799 -14.525588           57            0.000190         4.254043\n",
+       " 47823  3.900501 -14.525722           57            0.000175         4.254043\n",
+       " 47824  3.902202 -14.525855           57            0.000161         4.254043\n",
+       " 47825  3.903904 -14.525989           57            0.000146         4.254043\n",
+       " 47826  3.905606 -14.526122           57            0.000132         4.254043\n",
+       " \n",
+       " [709 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 48118  2.700801 -14.519691           58            4.245105         4.250618\n",
+       " 48119  2.702502 -14.519950           58            4.243366         4.250618\n",
+       " 48120  2.704204 -14.520209           58            4.241628         4.250618\n",
+       " 48121  2.705906 -14.520071           58            4.239786         4.250618\n",
+       " 48122  2.707608 -14.519846           58            4.237920         4.250618\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 48822  3.898799 -14.526070           58            0.000182         4.250618\n",
+       " 48823  3.900501 -14.526212           58            0.000168         4.250618\n",
+       " 48824  3.902202 -14.526354           58            0.000154         4.250618\n",
+       " 48825  3.903904 -14.526496           58            0.000139         4.250618\n",
+       " 48826  3.905606 -14.526638           58            0.000125         4.250618\n",
+       " \n",
+       " [709 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 49118  2.700801 -14.519957           59            4.239147          4.24826\n",
+       " 49119  2.702502 -14.520027           59            4.237288          4.24826\n",
+       " 49120  2.704204 -14.520027           59            4.235414          4.24826\n",
+       " 49121  2.705906 -14.520027           59            4.233540          4.24826\n",
+       " 49122  2.707608 -14.519945           59            4.231665          4.24826\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 49816  3.888589 -14.520256           59            0.000232          4.24826\n",
+       " 49817  3.890290 -14.520256           59            0.000216          4.24826\n",
+       " 49818  3.891992 -14.520256           59            0.000200          4.24826\n",
+       " 49819  3.893694 -14.520256           59            0.000185          4.24826\n",
+       " 49820  3.895395 -14.520256           59            0.000169          4.24826\n",
+       " \n",
+       " [703 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 50118  2.700801 -14.519958           60            4.232832         4.240416\n",
+       " 50119  2.702502 -14.519685           60            4.231030         4.240416\n",
+       " 50120  2.704204 -14.519980           60            4.229166         4.240416\n",
+       " 50121  2.705906 -14.520277           60            4.227302         4.240416\n",
+       " 50122  2.707608 -14.520442           60            4.225434         4.240416\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 50815  3.886887 -14.519853           60            0.000240         4.240416\n",
+       " 50816  3.888589 -14.519842           60            0.000224         4.240416\n",
+       " 50817  3.890290 -14.519831           60            0.000208         4.240416\n",
+       " 50818  3.891992 -14.519819           60            0.000192         4.240416\n",
+       " 50819  3.893694 -14.519808           60            0.000177         4.240416\n",
+       " \n",
+       " [702 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 51118  2.700801 -14.519951           61            4.230160         4.236219\n",
+       " 51119  2.702502 -14.519786           61            4.228375         4.236219\n",
+       " 51120  2.704204 -14.519621           61            4.226590         4.236219\n",
+       " 51121  2.705906 -14.519569           61            4.224778         4.236219\n",
+       " 51122  2.707608 -14.519569           61            4.222954         4.236219\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 51822  3.898799 -14.524978           61            0.000181         4.236219\n",
+       " 51823  3.900501 -14.525110           61            0.000167         4.236219\n",
+       " 51824  3.902202 -14.525243           61            0.000153         4.236219\n",
+       " 51825  3.903904 -14.525374           61            0.000138         4.236219\n",
+       " 51826  3.905606 -14.525507           61            0.000124         4.236219\n",
+       " \n",
+       " [709 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 52118  2.700801 -14.520218           62            4.223598         4.232447\n",
+       " 52119  2.702502 -14.520135           62            4.221756         4.232447\n",
+       " 52120  2.704204 -14.520053           62            4.219913         4.232447\n",
+       " 52121  2.705906 -14.520027           62            4.218040         4.232447\n",
+       " 52122  2.707608 -14.520027           62            4.216151         4.232447\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 52821  3.897097 -14.525002           62            0.000181         4.232447\n",
+       " 52822  3.898799 -14.525126           62            0.000167         4.232447\n",
+       " 52823  3.900501 -14.525251           62            0.000153         4.232447\n",
+       " 52824  3.902202 -14.525375           62            0.000139         4.232447\n",
+       " 52825  3.903904 -14.525500           62            0.000125         4.232447\n",
+       " \n",
+       " [708 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 53118  2.700801 -14.520027           63            4.221117         4.225752\n",
+       " 53119  2.702502 -14.520027           63            4.219228         4.225752\n",
+       " 53120  2.704204 -14.520027           63            4.217353         4.225752\n",
+       " 53121  2.705906 -14.520027           63            4.215528         4.225752\n",
+       " 53122  2.707608 -14.520027           63            4.213704         4.225752\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 53820  3.895395 -14.526582           63            0.000188         4.225752\n",
+       " 53821  3.897097 -14.526747           63            0.000174         4.225752\n",
+       " 53822  3.898799 -14.526912           63            0.000160         4.225752\n",
+       " 53823  3.900501 -14.527077           63            0.000146         4.225752\n",
+       " 53824  3.902202 -14.527242           63            0.000132         4.225752\n",
+       " \n",
+       " [707 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 54118  2.700801 -14.519984           64            4.215772          4.22393\n",
+       " 54119  2.702502 -14.519891           64            4.213923          4.22393\n",
+       " 54120  2.704204 -14.519798           64            4.212075          4.22393\n",
+       " 54121  2.705906 -14.519871           64            4.210147          4.22393\n",
+       " 54122  2.707608 -14.519944           64            4.208220          4.22393\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 54820  3.895395 -14.525586           64            0.000187          4.22393\n",
+       " 54821  3.897097 -14.525721           64            0.000173          4.22393\n",
+       " 54822  3.898799 -14.525855           64            0.000159          4.22393\n",
+       " 54823  3.900501 -14.525990           64            0.000145          4.22393\n",
+       " 54824  3.902202 -14.526124           64            0.000131          4.22393\n",
+       " \n",
+       " [707 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 55118  2.700801 -14.520311           65            4.219345         4.218569\n",
+       " 55119  2.702502 -14.520431           65            4.217462         4.218569\n",
+       " 55120  2.704204 -14.520446           65            4.215569         4.218569\n",
+       " 55121  2.705906 -14.520374           65            4.213669         4.218569\n",
+       " 55122  2.707608 -14.520303           65            4.211769         4.218569\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 55823  3.900501 -14.525520           65            0.000192         4.218569\n",
+       " 55824  3.902202 -14.525661           65            0.000177         4.218569\n",
+       " 55825  3.903904 -14.525801           65            0.000163         4.218569\n",
+       " 55826  3.905606 -14.525942           65            0.000149         4.218569\n",
+       " 55827  3.907307 -14.526082           65            0.000135         4.218569\n",
+       " \n",
+       " [710 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 56118  2.700801 -14.520308           66            4.217141         4.221962\n",
+       " 56119  2.702502 -14.520046           66            4.215366         4.221962\n",
+       " 56120  2.704204 -14.520120           66            4.213567         4.221962\n",
+       " 56121  2.705906 -14.520194           66            4.211768         4.221962\n",
+       " 56122  2.707608 -14.520232           66            4.209956         4.221962\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 56822  3.898799 -14.524929           66            0.000192         4.221962\n",
+       " 56823  3.900501 -14.525047           66            0.000178         4.221962\n",
+       " 56824  3.902202 -14.525166           66            0.000164         4.221962\n",
+       " 56825  3.903904 -14.525284           66            0.000150         4.221962\n",
+       " 56826  3.905606 -14.525402           66            0.000136         4.221962\n",
+       " \n",
+       " [709 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 57118  2.700801 -14.520027           67            4.211847         4.218698\n",
+       " 57119  2.702502 -14.520027           67            4.210061         4.218698\n",
+       " 57120  2.704204 -14.520027           67            4.208274         4.218698\n",
+       " 57121  2.705906 -14.520006           67            4.206473         4.218698\n",
+       " 57122  2.707608 -14.519934           67            4.204636         4.218698\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 57822  3.898799 -14.526453           67            0.000180         4.218698\n",
+       " 57823  3.900501 -14.526616           67            0.000166         4.218698\n",
+       " 57824  3.902202 -14.526780           67            0.000152         4.218698\n",
+       " 57825  3.903904 -14.526943           67            0.000138         4.218698\n",
+       " 57826  3.905606 -14.527106           67            0.000124         4.218698\n",
+       " \n",
+       " [709 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 58118  2.700801 -14.519855           68            4.206508         4.214984\n",
+       " 58119  2.702502 -14.519977           68            4.204687         4.214984\n",
+       " 58120  2.704204 -14.520027           68            4.202864         4.214984\n",
+       " 58121  2.705906 -14.520027           68            4.201038         4.214984\n",
+       " 58122  2.707608 -14.520027           68            4.199213         4.214984\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 58821  3.897097 -14.524782           68            0.000182         4.214984\n",
+       " 58822  3.898799 -14.524899           68            0.000169         4.214984\n",
+       " 58823  3.900501 -14.525017           68            0.000155         4.214984\n",
+       " 58824  3.902202 -14.525134           68            0.000141         4.214984\n",
+       " 58825  3.903904 -14.525251           68            0.000127         4.214984\n",
+       " \n",
+       " [708 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 59118  2.700801 -14.519730           69            4.200329         4.208444\n",
+       " 59119  2.702502 -14.519454           69            4.198512         4.208444\n",
+       " 59120  2.704204 -14.519746           69            4.196726         4.208444\n",
+       " 59121  2.705906 -14.520038           69            4.194940         4.208444\n",
+       " 59122  2.707608 -14.520237           69            4.193127         4.208444\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 59820  3.895395 -14.524738           69            0.000190         4.208444\n",
+       " 59821  3.897097 -14.524851           69            0.000176         4.208444\n",
+       " 59822  3.898799 -14.524964           69            0.000163         4.208444\n",
+       " 59823  3.900501 -14.525078           69            0.000149         4.208444\n",
+       " 59824  3.902202 -14.525190           69            0.000135         4.208444\n",
+       " \n",
+       " [707 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 60118  2.700801 -14.520088           70            4.195876         4.202224\n",
+       " 60119  2.702502 -14.519798           70            4.194042         4.202224\n",
+       " 60120  2.704204 -14.519798           70            4.192139         4.202224\n",
+       " 60121  2.705906 -14.519798           70            4.190235         4.202224\n",
+       " 60122  2.707608 -14.519879           70            4.188376         4.202224\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 60820  3.895395 -14.526443           70            0.000181         4.202224\n",
+       " 60821  3.897097 -14.526604           70            0.000167         4.202224\n",
+       " 60822  3.898799 -14.526765           70            0.000153         4.202224\n",
+       " 60823  3.900501 -14.526926           70            0.000139         4.202224\n",
+       " 60824  3.902202 -14.527087           70            0.000125         4.202224\n",
+       " \n",
+       " [707 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 61118  2.700801 -14.520256           71            4.190989         4.197487\n",
+       " 61119  2.702502 -14.520256           71            4.189190         4.197487\n",
+       " 61120  2.704204 -14.520256           71            4.187391         4.197487\n",
+       " 61121  2.705906 -14.520316           71            4.185507         4.197487\n",
+       " 61122  2.707608 -14.520389           71            4.183605         4.197487\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 61820  3.895395 -14.525482           71            0.000178         4.197487\n",
+       " 61821  3.897097 -14.525603           71            0.000165         4.197487\n",
+       " 61822  3.898799 -14.525725           71            0.000151         4.197487\n",
+       " 61823  3.900501 -14.525846           71            0.000137         4.197487\n",
+       " 61824  3.902202 -14.525969           71            0.000124         4.197487\n",
+       " \n",
+       " [707 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 62118  2.700801 -14.519883           72            4.188012          4.19391\n",
+       " 62119  2.702502 -14.520065           72            4.186229          4.19391\n",
+       " 62120  2.704204 -14.520247           72            4.184446          4.19391\n",
+       " 62121  2.705906 -14.520186           72            4.182611          4.19391\n",
+       " 62122  2.707608 -14.520113           72            4.180773          4.19391\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 62819  3.893694 -14.524319           72            0.000188          4.19391\n",
+       " 62820  3.895395 -14.524426           72            0.000175          4.19391\n",
+       " 62821  3.897097 -14.524532           72            0.000161          4.19391\n",
+       " 62822  3.898799 -14.524640           72            0.000147          4.19391\n",
+       " 62823  3.900501 -14.524747           72            0.000134          4.19391\n",
+       " \n",
+       " [706 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 63118  2.700801 -14.519249           73            4.182278         4.190191\n",
+       " 63119  2.702502 -14.519544           73            4.180478         4.190191\n",
+       " 63120  2.704204 -14.519818           73            4.178674         4.190191\n",
+       " 63121  2.705906 -14.519964           73            4.176836         4.190191\n",
+       " 63122  2.707608 -14.520109           73            4.174998         4.190191\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 63819  3.893694 -14.525612           73            0.000185         4.190191\n",
+       " 63820  3.895395 -14.525743           73            0.000171         4.190191\n",
+       " 63821  3.897097 -14.525874           73            0.000157         4.190191\n",
+       " 63822  3.898799 -14.526005           73            0.000144         4.190191\n",
+       " 63823  3.900501 -14.526135           73            0.000130         4.190191\n",
+       " \n",
+       " [706 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 64118  2.700801 -14.519798           74            4.180536         4.184529\n",
+       " 64119  2.702502 -14.519870           74            4.178668         4.184529\n",
+       " 64120  2.704204 -14.519944           74            4.176790         4.184529\n",
+       " 64121  2.705906 -14.520019           74            4.174913         4.184529\n",
+       " 64122  2.707608 -14.519900           74            4.173082         4.184529\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 64818  3.891992 -14.523471           74            0.000189         4.184529\n",
+       " 64819  3.893694 -14.523562           74            0.000175         4.184529\n",
+       " 64820  3.895395 -14.523654           74            0.000162         4.184529\n",
+       " 64821  3.897097 -14.523746           74            0.000148         4.184529\n",
+       " 64822  3.898799 -14.523838           74            0.000134         4.184529\n",
+       " \n",
+       " [705 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 65118  2.700801 -14.519897           75            4.175357         4.182582\n",
+       " 65119  2.702502 -14.520055           75            4.173566         4.182582\n",
+       " 65120  2.704204 -14.520127           75            4.171729         4.182582\n",
+       " 65121  2.705906 -14.520199           75            4.169892         4.182582\n",
+       " 65122  2.707608 -14.520226           75            4.168052         4.182582\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 65818  3.891992 -14.525539           75            0.000190         4.182582\n",
+       " 65819  3.893694 -14.525676           75            0.000176         4.182582\n",
+       " 65820  3.895395 -14.525811           75            0.000162         4.182582\n",
+       " 65821  3.897097 -14.525947           75            0.000149         4.182582\n",
+       " 65822  3.898799 -14.526083           75            0.000135         4.182582\n",
+       " \n",
+       " [705 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 66118  2.700801 -14.519202           76            4.169430         4.178782\n",
+       " 66119  2.702502 -14.519418           76            4.167580         4.178782\n",
+       " 66120  2.704204 -14.519634           76            4.165730         4.178782\n",
+       " 66121  2.705906 -14.519851           76            4.163887         4.178782\n",
+       " 66122  2.707608 -14.520069           76            4.162062         4.178782\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 66818  3.891992 -14.526480           76            0.000177         4.178782\n",
+       " 66819  3.893694 -14.526638           76            0.000164         4.178782\n",
+       " 66820  3.895395 -14.526796           76            0.000150         4.178782\n",
+       " 66821  3.897097 -14.526955           76            0.000137         4.178782\n",
+       " 66822  3.898799 -14.527112           76            0.000123         4.178782\n",
+       " \n",
+       " [705 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 67118  2.700801 -14.519669           77            4.162191         4.170609\n",
+       " 67119  2.702502 -14.519909           77            4.160373         4.170609\n",
+       " 67120  2.704204 -14.520192           77            4.158524         4.170609\n",
+       " 67121  2.705906 -14.520476           77            4.156674         4.170609\n",
+       " 67122  2.707608 -14.520666           77            4.154814         4.170609\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 67811  3.880080 -14.519389           77            0.000231         4.170609\n",
+       " 67812  3.881782 -14.519379           77            0.000216         4.170609\n",
+       " 67813  3.883483 -14.519368           77            0.000201         4.170609\n",
+       " 67814  3.885185 -14.519357           77            0.000186         4.170609\n",
+       " 67815  3.886887 -14.519346           77            0.000171         4.170609\n",
+       " \n",
+       " [698 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 68118  2.700801 -14.519964           78            4.161858         4.165257\n",
+       " 68119  2.702502 -14.519830           78            4.160035         4.165257\n",
+       " 68120  2.704204 -14.519854           78            4.158181         4.165257\n",
+       " 68121  2.705906 -14.519927           78            4.156318         4.165257\n",
+       " 68122  2.707608 -14.520000           78            4.154454         4.165257\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 68817  3.890290 -14.523924           78            0.000180         4.165257\n",
+       " 68818  3.891992 -14.524030           78            0.000167         4.165257\n",
+       " 68819  3.893694 -14.524135           78            0.000153         4.165257\n",
+       " 68820  3.895395 -14.524240           78            0.000140         4.165257\n",
+       " 68821  3.897097 -14.524344           78            0.000127         4.165257\n",
+       " \n",
+       " [704 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 69118  2.700801 -14.519798           79            4.159587         4.166417\n",
+       " 69119  2.702502 -14.519798           79            4.157900         4.166417\n",
+       " 69120  2.704204 -14.519745           79            4.156085         4.166417\n",
+       " 69121  2.705906 -14.519670           79            4.154220         4.166417\n",
+       " 69122  2.707608 -14.519594           79            4.152354         4.166417\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 69817  3.890290 -14.525969           79            0.000188         4.166417\n",
+       " 69818  3.891992 -14.526112           79            0.000175         4.166417\n",
+       " 69819  3.893694 -14.526254           79            0.000161         4.166417\n",
+       " 69820  3.895395 -14.526396           79            0.000148         4.166417\n",
+       " 69821  3.897097 -14.526539           79            0.000134         4.166417\n",
+       " \n",
+       " [704 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 70118  2.700801 -14.520184           80            4.153414         4.160131\n",
+       " 70119  2.702502 -14.520029           80            4.151560         4.160131\n",
+       " 70120  2.704204 -14.519883           80            4.149760         4.160131\n",
+       " 70121  2.705906 -14.519737           80            4.147961         4.160131\n",
+       " 70122  2.707608 -14.519591           80            4.146162         4.160131\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 70817  3.890290 -14.524586           80            0.000181         4.160131\n",
+       " 70818  3.891992 -14.524695           80            0.000167         4.160131\n",
+       " 70819  3.893694 -14.524805           80            0.000154         4.160131\n",
+       " 70820  3.895395 -14.524915           80            0.000141         4.160131\n",
+       " 70821  3.897097 -14.525024           80            0.000127         4.160131\n",
+       " \n",
+       " [704 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 71118  2.700801 -14.519977           81            4.150172         4.155378\n",
+       " 71119  2.702502 -14.520360           81            4.148373         4.155378\n",
+       " 71120  2.704204 -14.520436           81            4.146539         4.155378\n",
+       " 71121  2.705906 -14.520363           81            4.144689         4.155378\n",
+       " 71122  2.707608 -14.520290           81            4.142838         4.155378\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 71817  3.890290 -14.524822           81            0.000178         4.155378\n",
+       " 71818  3.891992 -14.524938           81            0.000164         4.155378\n",
+       " 71819  3.893694 -14.525052           81            0.000151         4.155378\n",
+       " 71820  3.895395 -14.525167           81            0.000137         4.155378\n",
+       " 71821  3.897097 -14.525283           81            0.000124         4.155378\n",
+       " \n",
+       " [704 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 72118  2.700801 -14.520251           82            4.145774         4.154408\n",
+       " 72119  2.702502 -14.520179           82            4.143950         4.154408\n",
+       " 72120  2.704204 -14.520105           82            4.142125         4.154408\n",
+       " 72121  2.705906 -14.520033           82            4.140299         4.154408\n",
+       " 72122  2.707608 -14.520096           82            4.138426         4.154408\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 72810  3.878378 -14.520816           82            0.000234         4.154408\n",
+       " 72811  3.880080 -14.520842           82            0.000220         4.154408\n",
+       " 72812  3.881782 -14.520867           82            0.000205         4.154408\n",
+       " 72813  3.883483 -14.520894           82            0.000190         4.154408\n",
+       " 72814  3.885185 -14.520920           82            0.000176         4.154408\n",
+       " \n",
+       " [697 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 73118  2.700801 -14.519853           83            4.140250         4.146821\n",
+       " 73119  2.702502 -14.519959           83            4.138451         4.146821\n",
+       " 73120  2.704204 -14.520053           83            4.136638         4.146821\n",
+       " 73121  2.705906 -14.520124           83            4.134801         4.146821\n",
+       " 73122  2.707608 -14.520197           83            4.132964         4.146821\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 73816  3.888589 -14.526519           83            0.000176         4.146821\n",
+       " 73817  3.890290 -14.526670           83            0.000162         4.146821\n",
+       " 73818  3.891992 -14.526820           83            0.000149         4.146821\n",
+       " 73819  3.893694 -14.526971           83            0.000136         4.146821\n",
+       " 73820  3.895395 -14.527122           83            0.000123         4.146821\n",
+       " \n",
+       " [703 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 74118  2.700801 -14.519667           84            4.137724         4.142769\n",
+       " 74119  2.702502 -14.519875           84            4.135870         4.142769\n",
+       " 74120  2.704204 -14.520046           84            4.134003         4.142769\n",
+       " 74121  2.705906 -14.520119           84            4.132102         4.142769\n",
+       " 74122  2.707608 -14.520190           84            4.130202         4.142769\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 74817  3.890290 -14.526439           84            0.000183         4.142769\n",
+       " 74818  3.891992 -14.526591           84            0.000169         4.142769\n",
+       " 74819  3.893694 -14.526744           84            0.000156         4.142769\n",
+       " 74820  3.895395 -14.526896           84            0.000142         4.142769\n",
+       " 74821  3.897097 -14.527049           84            0.000129         4.142769\n",
+       " \n",
+       " [704 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 75118  2.700801 -14.519661           85            4.135265         4.141524\n",
+       " 75119  2.702502 -14.519857           85            4.133501         4.141524\n",
+       " 75120  2.704204 -14.520018           85            4.131721         4.141524\n",
+       " 75121  2.705906 -14.519945           85            4.129846         4.141524\n",
+       " 75122  2.707608 -14.519874           85            4.127970         4.141524\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 75816  3.888589 -14.524120           85            0.000187         4.141524\n",
+       " 75817  3.890290 -14.524219           85            0.000174         4.141524\n",
+       " 75818  3.891992 -14.524317           85            0.000161         4.141524\n",
+       " 75819  3.893694 -14.524414           85            0.000148         4.141524\n",
+       " 75820  3.895395 -14.524512           85            0.000135         4.141524\n",
+       " \n",
+       " [703 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 76118  2.700801 -14.520145           86            4.130782         4.137221\n",
+       " 76119  2.702502 -14.519908           86            4.129004         4.137221\n",
+       " 76120  2.704204 -14.519917           86            4.127165         4.137221\n",
+       " 76121  2.705906 -14.520140           86            4.125274         4.137221\n",
+       " 76122  2.707608 -14.520362           86            4.123384         4.137221\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 76816  3.888589 -14.526525           86            0.000177         4.137221\n",
+       " 76817  3.890290 -14.526669           86            0.000164         4.137221\n",
+       " 76818  3.891992 -14.526814           86            0.000151         4.137221\n",
+       " 76819  3.893694 -14.526958           86            0.000137         4.137221\n",
+       " 76820  3.895395 -14.527102           86            0.000124         4.137221\n",
+       " \n",
+       " [703 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 77118  2.700801 -14.519798           87            4.127692         4.134223\n",
+       " 77119  2.702502 -14.519786           87            4.125858         4.134223\n",
+       " 77120  2.704204 -14.519713           87            4.124008         4.134223\n",
+       " 77121  2.705906 -14.519640           87            4.122157         4.134223\n",
+       " 77122  2.707608 -14.519575           87            4.120306         4.134223\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 77816  3.888589 -14.526725           87            0.000178         4.134223\n",
+       " 77817  3.890290 -14.526875           87            0.000164         4.134223\n",
+       " 77818  3.891992 -14.527024           87            0.000151         4.134223\n",
+       " 77819  3.893694 -14.527174           87            0.000138         4.134223\n",
+       " 77820  3.895395 -14.527324           87            0.000125         4.134223\n",
+       " \n",
+       " [703 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 78118  2.700801 -14.520182           88            4.122301         4.129322\n",
+       " 78119  2.702502 -14.520036           88            4.120579         4.129322\n",
+       " 78120  2.704204 -14.519890           88            4.118724         4.129322\n",
+       " 78121  2.705906 -14.519744           88            4.116860         4.129322\n",
+       " 78122  2.707608 -14.519598           88            4.114997         4.129322\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 78815  3.886887 -14.526233           88            0.000183         4.129322\n",
+       " 78816  3.888589 -14.526378           88            0.000169         4.129322\n",
+       " 78817  3.890290 -14.526524           88            0.000156         4.129322\n",
+       " 78818  3.891992 -14.526669           88            0.000143         4.129322\n",
+       " 78819  3.893694 -14.526814           88            0.000130         4.129322\n",
+       " \n",
+       " [702 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 79118  2.700801 -14.519798           89            4.119896         4.124625\n",
+       " 79119  2.702502 -14.519816           89            4.118117         4.124625\n",
+       " 79120  2.704204 -14.519964           89            4.116265         4.124625\n",
+       " 79121  2.705906 -14.520112           89            4.114414         4.124625\n",
+       " 79122  2.707608 -14.520258           89            4.112559         4.124625\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 79815  3.886887 -14.524347           89            0.000182         4.124625\n",
+       " 79816  3.888589 -14.524455           89            0.000169         4.124625\n",
+       " 79817  3.890290 -14.524563           89            0.000156         4.124625\n",
+       " 79818  3.891992 -14.524671           89            0.000142         4.124625\n",
+       " 79819  3.893694 -14.524778           89            0.000129         4.124625\n",
+       " \n",
+       " [702 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 80118  2.700801 -14.519787           90            4.115797         4.123161\n",
+       " 80119  2.702502 -14.519714           90            4.113920         4.123161\n",
+       " 80120  2.704204 -14.519641           90            4.112044         4.123161\n",
+       " 80121  2.705906 -14.519570           90            4.110168         4.123161\n",
+       " 80122  2.707608 -14.519645           90            4.108277         4.123161\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 80815  3.886887 -14.526713           90            0.000181         4.123161\n",
+       " 80816  3.888589 -14.526856           90            0.000168         4.123161\n",
+       " 80817  3.890290 -14.526999           90            0.000155         4.123161\n",
+       " 80818  3.891992 -14.527142           90            0.000142         4.123161\n",
+       " 80819  3.893694 -14.527285           90            0.000129         4.123161\n",
+       " \n",
+       " [702 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 81118  2.700801 -14.520178           91            4.113960         4.117964\n",
+       " 81119  2.702502 -14.520011           91            4.112175         4.117964\n",
+       " 81120  2.704204 -14.519843           91            4.110391         4.117964\n",
+       " 81121  2.705906 -14.519905           91            4.108568         4.117964\n",
+       " 81122  2.707608 -14.520051           91            4.106730         4.117964\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 81809  3.876677 -14.521657           91            0.000226         4.117964\n",
+       " 81810  3.878378 -14.521703           91            0.000212         4.117964\n",
+       " 81811  3.880080 -14.521749           91            0.000197         4.117964\n",
+       " 81812  3.881782 -14.521795           91            0.000183         4.117964\n",
+       " 81813  3.883483 -14.521841           91            0.000168         4.117964\n",
+       " \n",
+       " [696 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 82118  2.700801 -14.520243           92            4.111567         4.118506\n",
+       " 82119  2.702502 -14.520027           92            4.109666         4.118506\n",
+       " 82120  2.704204 -14.519811           92            4.107766         4.118506\n",
+       " 82121  2.705906 -14.519595           92            4.105865         4.118506\n",
+       " 82122  2.707608 -14.519759           92            4.103976         4.118506\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 82808  3.874975 -14.521255           92            0.000231         4.118506\n",
+       " 82809  3.876677 -14.521285           92            0.000217         4.118506\n",
+       " 82810  3.878378 -14.521316           92            0.000203         4.118506\n",
+       " 82811  3.880080 -14.521346           92            0.000188         4.118506\n",
+       " 82812  3.881782 -14.521377           92            0.000174         4.118506\n",
+       " \n",
+       " [695 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 83118  2.700801 -14.519379           93            4.104495         4.112949\n",
+       " 83119  2.702502 -14.519462           93            4.102652         4.112949\n",
+       " 83120  2.704204 -14.519544           93            4.100809         4.112949\n",
+       " 83121  2.705906 -14.519722           93            4.098960         4.112949\n",
+       " 83122  2.707608 -14.519943           93            4.097109         4.112949\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 83807  3.873273 -14.519434           93            0.000229         4.112949\n",
+       " 83808  3.874975 -14.519414           93            0.000215         4.112949\n",
+       " 83809  3.876677 -14.519394           93            0.000200         4.112949\n",
+       " 83810  3.878378 -14.519373           93            0.000186         4.112949\n",
+       " 83811  3.880080 -14.519353           93            0.000172         4.112949\n",
+       " \n",
+       " [694 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 84118  2.700801 -14.520364           94            4.100104         4.106719\n",
+       " 84119  2.702502 -14.520104           94            4.098275         4.106719\n",
+       " 84120  2.704204 -14.519845           94            4.096445         4.106719\n",
+       " 84121  2.705906 -14.519858           94            4.094577         4.106719\n",
+       " 84122  2.707608 -14.519931           94            4.092701         4.106719\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 84814  3.885185 -14.526079           94            0.000178         4.106719\n",
+       " 84815  3.886887 -14.526218           94            0.000164         4.106719\n",
+       " 84816  3.888589 -14.526358           94            0.000151         4.106719\n",
+       " 84817  3.890290 -14.526497           94            0.000138         4.106719\n",
+       " 84818  3.891992 -14.526636           94            0.000125         4.106719\n",
+       " \n",
+       " [701 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 85118  2.700801 -14.520027           95            4.096791         4.103227\n",
+       " 85119  2.702502 -14.520027           95            4.094948         4.103227\n",
+       " 85120  2.704204 -14.519981           95            4.093100         4.103227\n",
+       " 85121  2.705906 -14.519909           95            4.091249         4.103227\n",
+       " 85122  2.707608 -14.519835           95            4.089399         4.103227\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 85813  3.883483 -14.526690           95            0.000185         4.103227\n",
+       " 85814  3.885185 -14.526828           95            0.000172         4.103227\n",
+       " 85815  3.886887 -14.526966           95            0.000159         4.103227\n",
+       " 85816  3.888589 -14.527103           95            0.000146         4.103227\n",
+       " 85817  3.890290 -14.527241           95            0.000133         4.103227\n",
+       " \n",
+       " [700 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 86118  2.700801 -14.520027           96            4.093601         4.098489\n",
+       " 86119  2.702502 -14.519406           96            4.091810         4.098489\n",
+       " 86120  2.704204 -14.519625           96            4.089960         4.098489\n",
+       " 86121  2.705906 -14.519844           96            4.088109         4.098489\n",
+       " 86122  2.707608 -14.520040           96            4.086248         4.098489\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 86807  3.873273 -14.520279           96            0.000227         4.098489\n",
+       " 86808  3.874975 -14.520274           96            0.000213         4.098489\n",
+       " 86809  3.876677 -14.520268           96            0.000199         4.098489\n",
+       " 86810  3.878378 -14.520264           96            0.000185         4.098489\n",
+       " 86811  3.880080 -14.520259           96            0.000170         4.098489\n",
+       " \n",
+       " [694 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 87118  2.700801 -14.519993           97            4.089441         4.097572\n",
+       " 87119  2.702502 -14.519920           97            4.087577         4.097572\n",
+       " 87120  2.704204 -14.519847           97            4.085714         4.097572\n",
+       " 87121  2.705906 -14.519822           97            4.083838         4.097572\n",
+       " 87122  2.707608 -14.519896           97            4.081936         4.097572\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 87813  3.883483 -14.524434           97            0.000176         4.097572\n",
+       " 87814  3.885185 -14.524530           97            0.000163         4.097572\n",
+       " 87815  3.886887 -14.524626           97            0.000150         4.097572\n",
+       " 87816  3.888589 -14.524721           97            0.000138         4.097572\n",
+       " 87817  3.890290 -14.524817           97            0.000125         4.097572\n",
+       " \n",
+       " [700 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 88118  2.700801 -14.519890           98            4.083857         4.089258\n",
+       " 88119  2.702502 -14.520069           98            4.082041         4.089258\n",
+       " 88120  2.704204 -14.520248           98            4.080226         4.089258\n",
+       " 88121  2.705906 -14.520186           98            4.078341         4.089258\n",
+       " 88122  2.707608 -14.520113           98            4.076451         4.089258\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 88812  3.881782 -14.524603           98            0.000176         4.089258\n",
+       " 88813  3.883483 -14.524712           98            0.000164         4.089258\n",
+       " 88814  3.885185 -14.524820           98            0.000151         4.089258\n",
+       " 88815  3.886887 -14.524928           98            0.000138         4.089258\n",
+       " 88816  3.888589 -14.525037           98            0.000125         4.089258\n",
+       " \n",
+       " [699 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 89118  2.700801 -14.519964           99            4.081496         4.087944\n",
+       " 89119  2.702502 -14.519746           99            4.079594         4.087944\n",
+       " 89120  2.704204 -14.519526           99            4.077692         4.087944\n",
+       " 89121  2.705906 -14.519373           99            4.075795         4.087944\n",
+       " 89122  2.707608 -14.519591           99            4.073932         4.087944\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 89812  3.881782 -14.526224           99            0.000185         4.087944\n",
+       " 89813  3.883483 -14.526361           99            0.000173         4.087944\n",
+       " 89814  3.885185 -14.526497           99            0.000160         4.087944\n",
+       " 89815  3.886887 -14.526633           99            0.000147         4.087944\n",
+       " 89816  3.888589 -14.526770           99            0.000134         4.087944\n",
+       " \n",
+       " [699 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 90118  2.700801 -14.520215          100            4.075736         4.083102\n",
+       " 90119  2.702502 -14.520127          100            4.073890         4.083102\n",
+       " 90120  2.704204 -14.520039          100            4.072044         4.083102\n",
+       " 90121  2.705906 -14.520027          100            4.070094         4.083102\n",
+       " 90122  2.707608 -14.520027          100            4.068128         4.083102\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 90811  3.880080 -14.524772          100            0.000184         4.083102\n",
+       " 90812  3.881782 -14.524880          100            0.000171         4.083102\n",
+       " 90813  3.883483 -14.524989          100            0.000158         4.083102\n",
+       " 90814  3.885185 -14.525098          100            0.000145         4.083102\n",
+       " 90815  3.886887 -14.525206          100            0.000133         4.083102\n",
+       " \n",
+       " [698 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 91118  2.700801 -14.519798          101            4.071812         4.078109\n",
+       " 91119  2.702502 -14.519798          101            4.069941         4.078109\n",
+       " 91120  2.704204 -14.519832          101            4.068071         4.078109\n",
+       " 91121  2.705906 -14.519979          101            4.066206         4.078109\n",
+       " 91122  2.707608 -14.520127          101            4.064342         4.078109\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 91812  3.881782 -14.524696          101            0.000174         4.078109\n",
+       " 91813  3.883483 -14.524788          101            0.000161         4.078109\n",
+       " 91814  3.885185 -14.524879          101            0.000148         4.078109\n",
+       " 91815  3.886887 -14.524970          101            0.000136         4.078109\n",
+       " 91816  3.888589 -14.525062          101            0.000123         4.078109\n",
+       " \n",
+       " [699 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 92118  2.700801 -14.520027          102            4.068388         4.074751\n",
+       " 92119  2.702502 -14.520027          102            4.066612         4.074751\n",
+       " 92120  2.704204 -14.520027          102            4.064760         4.074751\n",
+       " 92121  2.705906 -14.520027          102            4.062883         4.074751\n",
+       " 92122  2.707608 -14.520027          102            4.061007         4.074751\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 92811  3.880080 -14.523542          102            0.000178         4.074751\n",
+       " 92812  3.881782 -14.523627          102            0.000166         4.074751\n",
+       " 92813  3.883483 -14.523712          102            0.000153         4.074751\n",
+       " 92814  3.885185 -14.523797          102            0.000140         4.074751\n",
+       " 92815  3.886887 -14.523882          102            0.000128         4.074751\n",
+       " \n",
+       " [698 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 93118  2.700801 -14.519798          103            4.066670         4.070282\n",
+       " 93119  2.702502 -14.519798          103            4.064806         4.070282\n",
+       " 93120  2.704204 -14.519798          103            4.062943         4.070282\n",
+       " 93121  2.705906 -14.519798          103            4.061075         4.070282\n",
+       " 93122  2.707608 -14.519798          103            4.059132         4.070282\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 93811  3.880080 -14.525431          103            0.000176         4.070282\n",
+       " 93812  3.881782 -14.525560          103            0.000163         4.070282\n",
+       " 93813  3.883483 -14.525691          103            0.000150         4.070282\n",
+       " 93814  3.885185 -14.525821          103            0.000138         4.070282\n",
+       " 93815  3.886887 -14.525951          103            0.000125         4.070282\n",
+       " \n",
+       " [698 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 94118  2.700801 -14.519844          104            4.062052         4.071453\n",
+       " 94119  2.702502 -14.519798          104            4.060144         4.071453\n",
+       " 94120  2.704204 -14.519798          104            4.058231         4.071453\n",
+       " 94121  2.705906 -14.519798          104            4.056318         4.071453\n",
+       " 94122  2.707608 -14.519952          104            4.054403         4.071453\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 94811  3.880080 -14.525514          104            0.000175         4.071453\n",
+       " 94812  3.881782 -14.525625          104            0.000162         4.071453\n",
+       " 94813  3.883483 -14.525737          104            0.000150         4.071453\n",
+       " 94814  3.885185 -14.525848          104            0.000137         4.071453\n",
+       " 94815  3.886887 -14.525960          104            0.000124         4.071453\n",
+       " \n",
+       " [698 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 95118  2.700801 -14.519989          105            4.057794         4.063387\n",
+       " 95119  2.702502 -14.520100          105            4.055918         4.063387\n",
+       " 95120  2.704204 -14.519877          105            4.053988         4.063387\n",
+       " 95121  2.705906 -14.519656          105            4.052059         4.063387\n",
+       " 95122  2.707608 -14.519660          105            4.050138         4.063387\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 95811  3.880080 -14.525941          105            0.000174         4.063387\n",
+       " 95812  3.881782 -14.526061          105            0.000162         4.063387\n",
+       " 95813  3.883483 -14.526181          105            0.000149         4.063387\n",
+       " 95814  3.885185 -14.526301          105            0.000136         4.063387\n",
+       " 95815  3.886887 -14.526422          105            0.000124         4.063387\n",
+       " \n",
+       " [698 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 96118  2.700801 -14.520216          106            4.057915         4.062112\n",
+       " 96119  2.702502 -14.520131          106            4.055995         4.062112\n",
+       " 96120  2.704204 -14.520046          106            4.054076         4.062112\n",
+       " 96121  2.705906 -14.519914          106            4.052170         4.062112\n",
+       " 96122  2.707608 -14.519768          106            4.050268         4.062112\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 96812  3.881782 -14.526070          106            0.000182         4.062112\n",
+       " 96813  3.883483 -14.526194          106            0.000170         4.062112\n",
+       " 96814  3.885185 -14.526319          106            0.000157         4.062112\n",
+       " 96815  3.886887 -14.526443          106            0.000145         4.062112\n",
+       " 96816  3.888589 -14.526568          106            0.000132         4.062112\n",
+       " \n",
+       " [699 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 97118  2.700801 -14.519798          107            4.055706         4.059759\n",
+       " 97119  2.702502 -14.519798          107            4.053893         4.059759\n",
+       " 97120  2.704204 -14.519798          107            4.052080         4.059759\n",
+       " 97121  2.705906 -14.519835          107            4.050234         4.059759\n",
+       " 97122  2.707608 -14.519910          107            4.048357         4.059759\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 97814  3.885185 -14.526317          107            0.000175         4.059759\n",
+       " 97815  3.886887 -14.526456          107            0.000162         4.059759\n",
+       " 97816  3.888589 -14.526594          107            0.000150         4.059759\n",
+       " 97817  3.890290 -14.526732          107            0.000137         4.059759\n",
+       " 97818  3.891992 -14.526871          107            0.000125         4.059759\n",
+       " \n",
+       " [701 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 98118  2.700801 -14.519798          108            4.059221          4.06046\n",
+       " 98119  2.702502 -14.519798          108            4.057372          4.06046\n",
+       " 98120  2.704204 -14.519798          108            4.055427          4.06046\n",
+       " 98121  2.705906 -14.519798          108            4.053482          4.06046\n",
+       " 98122  2.707608 -14.519776          108            4.051535          4.06046\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 98815  3.886887 -14.523807          108            0.000182          4.06046\n",
+       " 98816  3.888589 -14.523878          108            0.000170          4.06046\n",
+       " 98817  3.890290 -14.523949          108            0.000157          4.06046\n",
+       " 98818  3.891992 -14.524020          108            0.000145          4.06046\n",
+       " 98819  3.893694 -14.524092          108            0.000132          4.06046\n",
+       " \n",
+       " [702 rows x 5 columns],\n",
+       "         voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 99118  2.700801 -14.520226          109            4.053569         4.060015\n",
+       " 99119  2.702502 -14.520256          109            4.051739         4.060015\n",
+       " 99120  2.704204 -14.520256          109            4.049901         4.060015\n",
+       " 99121  2.705906 -14.520256          109            4.048064         4.060015\n",
+       " 99122  2.707608 -14.520138          109            4.046225         4.060015\n",
+       " ...         ...        ...          ...                 ...              ...\n",
+       " 99815  3.886887 -14.525037          109            0.000175         4.060015\n",
+       " 99816  3.888589 -14.525152          109            0.000162         4.060015\n",
+       " 99817  3.890290 -14.525268          109            0.000150         4.060015\n",
+       " 99818  3.891992 -14.525382          109            0.000137         4.060015\n",
+       " 99819  3.893694 -14.525497          109            0.000125         4.060015\n",
+       " \n",
+       " [702 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 100118  2.700801 -14.519991          110            4.050096         4.056343\n",
+       " 100119  2.702502 -14.519843          110            4.048258         4.056343\n",
+       " 100120  2.704204 -14.519695          110            4.046420         4.056343\n",
+       " 100121  2.705906 -14.519569          110            4.044583         4.056343\n",
+       " 100122  2.707608 -14.519569          110            4.042758         4.056343\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 100814  3.885185 -14.525671          110            0.000178         4.056343\n",
+       " 100815  3.886887 -14.525791          110            0.000166         4.056343\n",
+       " 100816  3.888589 -14.525910          110            0.000153         4.056343\n",
+       " 100817  3.890290 -14.526031          110            0.000141         4.056343\n",
+       " 100818  3.891992 -14.526150          110            0.000128         4.056343\n",
+       " \n",
+       " [701 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 101118  2.700801 -14.520027          111            4.045145          4.05248\n",
+       " 101119  2.702502 -14.519963          111            4.043290          4.05248\n",
+       " 101120  2.704204 -14.519892          111            4.041427          4.05248\n",
+       " 101121  2.705906 -14.519820          111            4.039564          4.05248\n",
+       " 101122  2.707608 -14.519902          111            4.037710          4.05248\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 101813  3.883483 -14.525689          111            0.000175          4.05248\n",
+       " 101814  3.885185 -14.525813          111            0.000162          4.05248\n",
+       " 101815  3.886887 -14.525937          111            0.000150          4.05248\n",
+       " 101816  3.888589 -14.526061          111            0.000137          4.05248\n",
+       " 101817  3.890290 -14.526185          111            0.000125          4.05248\n",
+       " \n",
+       " [700 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 102118  2.700801 -14.520167          112            4.041419         4.048491\n",
+       " 102119  2.702502 -14.520100          112            4.039598         4.048491\n",
+       " 102120  2.704204 -14.519877          112            4.037747         4.048491\n",
+       " 102121  2.705906 -14.519656          112            4.035895         4.048491\n",
+       " 102122  2.707608 -14.519613          112            4.034029         4.048491\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 102813  3.883483 -14.525080          112            0.000174         4.048491\n",
+       " 102814  3.885185 -14.525187          112            0.000162         4.048491\n",
+       " 102815  3.886887 -14.525293          112            0.000149         4.048491\n",
+       " 102816  3.888589 -14.525399          112            0.000137         4.048491\n",
+       " 102817  3.890290 -14.525506          112            0.000124         4.048491\n",
+       " \n",
+       " [700 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 103118  2.700801 -14.520138          113            4.036231         4.042709\n",
+       " 103119  2.702502 -14.520369          113            4.034391         4.042709\n",
+       " 103120  2.704204 -14.520146          113            4.032513         4.042709\n",
+       " 103121  2.705906 -14.519924          113            4.030636         4.042709\n",
+       " 103122  2.707608 -14.519829          113            4.028787         4.042709\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 103805  3.869870 -14.521688          113            0.000223         4.042709\n",
+       " 103806  3.871572 -14.521727          113            0.000209         4.042709\n",
+       " 103807  3.873273 -14.521765          113            0.000196         4.042709\n",
+       " 103808  3.874975 -14.521804          113            0.000182         4.042709\n",
+       " 103809  3.876677 -14.521842          113            0.000169         4.042709\n",
+       " \n",
+       " [692 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 104118  2.700801 -14.519736          114            4.030949         4.038795\n",
+       " 104119  2.702502 -14.519588          114            4.029059         4.038795\n",
+       " 104120  2.704204 -14.519440          114            4.027168         4.038795\n",
+       " 104121  2.705906 -14.519438          114            4.025278         4.038795\n",
+       " 104122  2.707608 -14.519733          114            4.023387         4.038795\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 104811  3.880080 -14.525122          114            0.000176         4.038795\n",
+       " 104812  3.881782 -14.525214          114            0.000164         4.038795\n",
+       " 104813  3.883483 -14.525308          114            0.000151         4.038795\n",
+       " 104814  3.885185 -14.525400          114            0.000139         4.038795\n",
+       " 104815  3.886887 -14.525493          114            0.000126         4.038795\n",
+       " \n",
+       " [698 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 105118  2.700801 -14.520201          115            4.026259          4.03364\n",
+       " 105119  2.702502 -14.520052          115            4.024434          4.03364\n",
+       " 105120  2.704204 -14.519904          115            4.022608          4.03364\n",
+       " 105121  2.705906 -14.519798          115            4.020761          4.03364\n",
+       " 105122  2.707608 -14.519798          115            4.018856          4.03364\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 105804  3.868168 -14.521279          115            0.000220          4.03364\n",
+       " 105805  3.869870 -14.521308          115            0.000206          4.03364\n",
+       " 105806  3.871572 -14.521337          115            0.000193          4.03364\n",
+       " 105807  3.873273 -14.521365          115            0.000179          4.03364\n",
+       " 105808  3.874975 -14.521395          115            0.000166          4.03364\n",
+       " \n",
+       " [691 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 106118  2.700801 -14.519883          116            4.023562         4.029441\n",
+       " 106119  2.702502 -14.519998          116            4.021684         4.029441\n",
+       " 106120  2.704204 -14.519855          116            4.019872         4.029441\n",
+       " 106121  2.705906 -14.519713          116            4.018060         4.029441\n",
+       " 106122  2.707608 -14.519572          116            4.016249         4.029441\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 106804  3.868168 -14.520216          116            0.000219         4.029441\n",
+       " 106805  3.869870 -14.520226          116            0.000206         4.029441\n",
+       " 106806  3.871572 -14.520235          116            0.000192         4.029441\n",
+       " 106807  3.873273 -14.520246          116            0.000178         4.029441\n",
+       " 106808  3.874975 -14.520255          116            0.000164         4.029441\n",
+       " \n",
+       " [691 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 107118  2.700801 -14.519973          117            4.017642         4.025023\n",
+       " 107119  2.702502 -14.519857          117            4.015679         4.025023\n",
+       " 107120  2.704204 -14.519763          117            4.013791         4.025023\n",
+       " 107121  2.705906 -14.519692          117            4.011979         4.025023\n",
+       " 107122  2.707608 -14.519622          117            4.010168         4.025023\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 107802  3.864765 -14.520645          117            0.000228         4.025023\n",
+       " 107803  3.866467 -14.520659          117            0.000214         4.025023\n",
+       " 107804  3.868168 -14.520674          117            0.000201         4.025023\n",
+       " 107805  3.869870 -14.520688          117            0.000187         4.025023\n",
+       " 107806  3.871572 -14.520702          117            0.000174         4.025023\n",
+       " \n",
+       " [689 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 108118  2.700801 -14.519958          118            4.014197         4.019928\n",
+       " 108119  2.702502 -14.519807          118            4.012371         4.019928\n",
+       " 108120  2.704204 -14.519657          118            4.010545         4.019928\n",
+       " 108121  2.705906 -14.519662          118            4.008682         4.019928\n",
+       " 108122  2.707608 -14.519884          118            4.006765         4.019928\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 108802  3.864765 -14.521306          118            0.000229         4.019928\n",
+       " 108803  3.866467 -14.521325          118            0.000216         4.019928\n",
+       " 108804  3.868168 -14.521344          118            0.000202         4.019928\n",
+       " 108805  3.869870 -14.521364          118            0.000189         4.019928\n",
+       " 108806  3.871572 -14.521383          118            0.000175         4.019928\n",
+       " \n",
+       " [689 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 109118  2.700801 -14.519973          119            4.010026         4.016312\n",
+       " 109119  2.702502 -14.519857          119            4.008166         4.016312\n",
+       " 109120  2.704204 -14.519763          119            4.006310         4.016312\n",
+       " 109121  2.705906 -14.519691          119            4.004460         4.016312\n",
+       " 109122  2.707608 -14.519619          119            4.002611         4.016312\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 109802  3.864765 -14.521667          119            0.000222         4.016312\n",
+       " 109803  3.866467 -14.521711          119            0.000209         4.016312\n",
+       " 109804  3.868168 -14.521754          119            0.000195         4.016312\n",
+       " 109805  3.869870 -14.521797          119            0.000182         4.016312\n",
+       " 109806  3.871572 -14.521840          119            0.000168         4.016312\n",
+       " \n",
+       " [689 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 110118  2.700801 -14.519754          120            4.006707         4.012572\n",
+       " 110119  2.702502 -14.519660          120            4.004908         4.012572\n",
+       " 110120  2.704204 -14.519573          120            4.003101         4.012572\n",
+       " 110121  2.705906 -14.519648          120            4.001130         4.012572\n",
+       " 110122  2.707608 -14.519723          120            3.999159         4.012572\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 110801  3.863063 -14.520668          120            0.000227         4.012572\n",
+       " 110802  3.864765 -14.520678          120            0.000214         4.012572\n",
+       " 110803  3.866467 -14.520687          120            0.000200         4.012572\n",
+       " 110804  3.868168 -14.520697          120            0.000187         4.012572\n",
+       " 110805  3.869870 -14.520706          120            0.000173         4.012572\n",
+       " \n",
+       " [688 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 111118  2.700801 -14.520141          121            4.002855         4.008944\n",
+       " 111119  2.702502 -14.520180          121            4.001049         4.008944\n",
+       " 111120  2.704204 -14.520034          121            3.999199         4.008944\n",
+       " 111121  2.705906 -14.519888          121            3.997348         4.008944\n",
+       " 111122  2.707608 -14.519771          121            3.995478         4.008944\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 111808  3.874975 -14.526779          121            0.000173         4.008944\n",
+       " 111809  3.876677 -14.526917          121            0.000161         4.008944\n",
+       " 111810  3.878378 -14.527055          121            0.000149         4.008944\n",
+       " 111811  3.880080 -14.527192          121            0.000137         4.008944\n",
+       " 111812  3.881782 -14.527329          121            0.000124         4.008944\n",
+       " \n",
+       " [695 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 112118  2.700801 -14.520414          122            3.999721          4.00552\n",
+       " 112119  2.702502 -14.520202          122            3.997897          4.00552\n",
+       " 112120  2.704204 -14.519989          122            3.996073          4.00552\n",
+       " 112121  2.705906 -14.519798          122            3.994241          4.00552\n",
+       " 112122  2.707608 -14.519798          122            3.992340          4.00552\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 112807  3.873273 -14.526682          122            0.000178          4.00552\n",
+       " 112808  3.874975 -14.526829          122            0.000166          4.00552\n",
+       " 112809  3.876677 -14.526975          122            0.000154          4.00552\n",
+       " 112810  3.878378 -14.527122          122            0.000142          4.00552\n",
+       " 112811  3.880080 -14.527267          122            0.000129          4.00552\n",
+       " \n",
+       " [694 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 113118  2.700801 -14.519742          123            3.997866         4.002945\n",
+       " 113119  2.702502 -14.520114          123            3.996051         4.002945\n",
+       " 113120  2.704204 -14.520485          123            3.994235         4.002945\n",
+       " 113121  2.705906 -14.520185          123            3.992264         4.002945\n",
+       " 113122  2.707608 -14.519884          123            3.990293         4.002945\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 113807  3.873273 -14.523754          123            0.000178         4.002945\n",
+       " 113808  3.874975 -14.523840          123            0.000166         4.002945\n",
+       " 113809  3.876677 -14.523926          123            0.000154         4.002945\n",
+       " 113810  3.878378 -14.524012          123            0.000142         4.002945\n",
+       " 113811  3.880080 -14.524097          123            0.000129         4.002945\n",
+       " \n",
+       " [694 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 114118  2.700801 -14.519997          124            3.994884         4.000532\n",
+       " 114119  2.702502 -14.519923          124            3.993072         4.000532\n",
+       " 114120  2.704204 -14.519851          124            3.991260         4.000532\n",
+       " 114121  2.705906 -14.519735          124            3.989418         4.000532\n",
+       " 114122  2.707608 -14.519513          124            3.987502         4.000532\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 114807  3.873273 -14.524649          124            0.000176         4.000532\n",
+       " 114808  3.874975 -14.524742          124            0.000163         4.000532\n",
+       " 114809  3.876677 -14.524837          124            0.000151         4.000532\n",
+       " 114810  3.878378 -14.524931          124            0.000139         4.000532\n",
+       " 114811  3.880080 -14.525025          124            0.000127         4.000532\n",
+       " \n",
+       " [694 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 115118  2.700801 -14.520107          125            3.993102         3.999272\n",
+       " 115119  2.702502 -14.519800          125            3.991274         3.999272\n",
+       " 115120  2.704204 -14.519875          125            3.989422         3.999272\n",
+       " 115121  2.705906 -14.519949          125            3.987571         3.999272\n",
+       " 115122  2.707608 -14.520022          125            3.985719         3.999272\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 115807  3.873273 -14.524024          125            0.000172         3.999272\n",
+       " 115808  3.874975 -14.524110          125            0.000160         3.999272\n",
+       " 115809  3.876677 -14.524195          125            0.000148         3.999272\n",
+       " 115810  3.878378 -14.524280          125            0.000136         3.999272\n",
+       " 115811  3.880080 -14.524365          125            0.000124         3.999272\n",
+       " \n",
+       " [694 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 116118  2.700801 -14.520027          126            3.987412         3.993356\n",
+       " 116119  2.702502 -14.519960          126            3.985557         3.993356\n",
+       " 116120  2.704204 -14.519738          126            3.983654         3.993356\n",
+       " 116121  2.705906 -14.519517          126            3.981750         3.993356\n",
+       " 116122  2.707608 -14.519356          126            3.979844         3.993356\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 116800  3.861361 -14.520401          126            0.000222         3.993356\n",
+       " 116801  3.863063 -14.520420          126            0.000209         3.993356\n",
+       " 116802  3.864765 -14.520439          126            0.000195         3.993356\n",
+       " 116803  3.866467 -14.520457          126            0.000182         3.993356\n",
+       " 116804  3.868168 -14.520476          126            0.000169         3.993356\n",
+       " \n",
+       " [687 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 117118  2.700801 -14.520020          127            3.982207         3.989142\n",
+       " 117119  2.702502 -14.519946          127            3.980241         3.989142\n",
+       " 117120  2.704204 -14.519874          127            3.978274         3.989142\n",
+       " 117121  2.705906 -14.519800          127            3.976308         3.989142\n",
+       " 117122  2.707608 -14.519659          127            3.974467         3.989142\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 117800  3.861361 -14.520864          127            0.000218         3.989142\n",
+       " 117801  3.863063 -14.520884          127            0.000204         3.989142\n",
+       " 117802  3.864765 -14.520903          127            0.000191         3.989142\n",
+       " 117803  3.866467 -14.520922          127            0.000178         3.989142\n",
+       " 117804  3.868168 -14.520940          127            0.000165         3.989142\n",
+       " \n",
+       " [687 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 118118  2.700801 -14.520079          128            3.980975         3.985757\n",
+       " 118119  2.702502 -14.520106          128            3.979105         3.985757\n",
+       " 118120  2.704204 -14.519894          128            3.977206         3.985757\n",
+       " 118121  2.705906 -14.519681          128            3.975307         3.985757\n",
+       " 118122  2.707608 -14.519603          128            3.973425         3.985757\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 118806  3.871572 -14.524024          128            0.000172         3.985757\n",
+       " 118807  3.873273 -14.524109          128            0.000160         3.985757\n",
+       " 118808  3.874975 -14.524194          128            0.000148         3.985757\n",
+       " 118809  3.876677 -14.524279          128            0.000136         3.985757\n",
+       " 118810  3.878378 -14.524364          128            0.000124         3.985757\n",
+       " \n",
+       " [693 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 119118  2.700801 -14.519798          129            3.974371         3.981971\n",
+       " 119119  2.702502 -14.519798          129            3.972508         3.981971\n",
+       " 119120  2.704204 -14.519798          129            3.970646         3.981971\n",
+       " 119121  2.705906 -14.519798          129            3.968735         3.981971\n",
+       " 119122  2.707608 -14.519798          129            3.966818         3.981971\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 119805  3.869870 -14.526347          129            0.000174         3.981971\n",
+       " 119806  3.871572 -14.526475          129            0.000162         3.981971\n",
+       " 119807  3.873273 -14.526602          129            0.000150         3.981971\n",
+       " 119808  3.874975 -14.526730          129            0.000138         3.981971\n",
+       " 119809  3.876677 -14.526857          129            0.000126         3.981971\n",
+       " \n",
+       " [692 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 120118  2.700801 -14.520389          130            3.971180         3.977461\n",
+       " 120119  2.702502 -14.520436          130            3.969346         3.977461\n",
+       " 120120  2.704204 -14.520362          130            3.967443         3.977461\n",
+       " 120121  2.705906 -14.520288          130            3.965539         3.977461\n",
+       " 120122  2.707608 -14.520172          130            3.963621         3.977461\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 120806  3.871572 -14.525963          130            0.000172         3.977461\n",
+       " 120807  3.873273 -14.526078          130            0.000160         3.977461\n",
+       " 120808  3.874975 -14.526194          130            0.000148         3.977461\n",
+       " 120809  3.876677 -14.526309          130            0.000136         3.977461\n",
+       " 120810  3.878378 -14.526425          130            0.000124         3.977461\n",
+       " \n",
+       " [693 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 121118  2.700801 -14.519585          131            3.967235         3.973915\n",
+       " 121119  2.702502 -14.519659          131            3.965304         3.973915\n",
+       " 121120  2.704204 -14.519734          131            3.963372         3.973915\n",
+       " 121121  2.705906 -14.519788          131            3.961447         3.973915\n",
+       " 121122  2.707608 -14.519714          131            3.959558         3.973915\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 121805  3.869870 -14.524691          131            0.000172         3.973915\n",
+       " 121806  3.871572 -14.524779          131            0.000161         3.973915\n",
+       " 121807  3.873273 -14.524868          131            0.000149         3.973915\n",
+       " 121808  3.874975 -14.524957          131            0.000137         3.973915\n",
+       " 121809  3.876677 -14.525045          131            0.000125         3.973915\n",
+       " \n",
+       " [692 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 122118  2.700801 -14.519689          132            3.965364         3.968612\n",
+       " 122119  2.702502 -14.519943          132            3.963475         3.968612\n",
+       " 122120  2.704204 -14.520027          132            3.961602         3.968612\n",
+       " 122121  2.705906 -14.520027          132            3.959738         3.968612\n",
+       " 122122  2.707608 -14.520027          132            3.957874         3.968612\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 122804  3.868168 -14.526417          132            0.000181         3.968612\n",
+       " 122805  3.869870 -14.526560          132            0.000169         3.968612\n",
+       " 122806  3.871572 -14.526703          132            0.000157         3.968612\n",
+       " 122807  3.873273 -14.526846          132            0.000145         3.968612\n",
+       " 122808  3.874975 -14.526990          132            0.000134         3.968612\n",
+       " \n",
+       " [691 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 123118  2.700801 -14.519982          133            3.964164           3.9715\n",
+       " 123119  2.702502 -14.519886          133            3.962381           3.9715\n",
+       " 123120  2.704204 -14.519798          133            3.960581           3.9715\n",
+       " 123121  2.705906 -14.519798          133            3.958599           3.9715\n",
+       " 123122  2.707608 -14.519798          133            3.956618           3.9715\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 123805  3.869870 -14.525878          133            0.000177           3.9715\n",
+       " 123806  3.871572 -14.526000          133            0.000165           3.9715\n",
+       " 123807  3.873273 -14.526123          133            0.000153           3.9715\n",
+       " 123808  3.874975 -14.526245          133            0.000141           3.9715\n",
+       " 123809  3.876677 -14.526368          133            0.000129           3.9715\n",
+       " \n",
+       " [692 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 124118  2.700801 -14.519977          134            3.958428         3.964928\n",
+       " 124119  2.702502 -14.519868          134            3.956629         3.964928\n",
+       " 124120  2.704204 -14.519851          134            3.954784         3.964928\n",
+       " 124121  2.705906 -14.519997          134            3.952856         3.964928\n",
+       " 124122  2.707608 -14.520143          134            3.950928         3.964928\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 124798  3.857958 -14.521276          134            0.000222         3.964928\n",
+       " 124799  3.859660 -14.521303          134            0.000209         3.964928\n",
+       " 124800  3.861361 -14.521331          134            0.000196         3.964928\n",
+       " 124801  3.863063 -14.521358          134            0.000183         3.964928\n",
+       " 124802  3.864765 -14.521386          134            0.000170         3.964928\n",
+       " \n",
+       " [685 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 125118  2.700801 -14.519798          135            3.955766         3.962102\n",
+       " 125119  2.702502 -14.519798          135            3.953967         3.962102\n",
+       " 125120  2.704204 -14.519798          135            3.952037         3.962102\n",
+       " 125121  2.705906 -14.519798          135            3.950093         3.962102\n",
+       " 125122  2.707608 -14.519798          135            3.948148         3.962102\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 125805  3.869870 -14.525063          135            0.000172         3.962102\n",
+       " 125806  3.871572 -14.525171          135            0.000160         3.962102\n",
+       " 125807  3.873273 -14.525281          135            0.000148         3.962102\n",
+       " 125808  3.874975 -14.525390          135            0.000137         3.962102\n",
+       " 125809  3.876677 -14.525498          135            0.000125         3.962102\n",
+       " \n",
+       " [692 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 126118  2.700801 -14.519982          136            3.951225         3.956498\n",
+       " 126119  2.702502 -14.519886          136            3.949375         3.956498\n",
+       " 126120  2.704204 -14.519798          136            3.947521         3.956498\n",
+       " 126121  2.705906 -14.519798          136            3.945632         3.956498\n",
+       " 126122  2.707608 -14.519798          136            3.943743         3.956498\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 126804  3.868168 -14.525067          136            0.000178         3.956498\n",
+       " 126805  3.869870 -14.525164          136            0.000166         3.956498\n",
+       " 126806  3.871572 -14.525260          136            0.000154         3.956498\n",
+       " 126807  3.873273 -14.525356          136            0.000143         3.956498\n",
+       " 126808  3.874975 -14.525453          136            0.000131         3.956498\n",
+       " \n",
+       " [691 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 127118  2.700801 -14.520195          137            3.948829         3.954178\n",
+       " 127119  2.702502 -14.519628          137            3.947030         3.954178\n",
+       " 127120  2.704204 -14.519569          137            3.945160         3.954178\n",
+       " 127121  2.705906 -14.519569          137            3.943283         3.954178\n",
+       " 127122  2.707608 -14.519569          137            3.941406         3.954178\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 127804  3.868168 -14.526057          137            0.000178         3.954178\n",
+       " 127805  3.869870 -14.526187          137            0.000166         3.954178\n",
+       " 127806  3.871572 -14.526318          137            0.000154         3.954178\n",
+       " 127807  3.873273 -14.526448          137            0.000142         3.954178\n",
+       " 127808  3.874975 -14.526579          137            0.000130         3.954178\n",
+       " \n",
+       " [691 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 128118  2.700801 -14.519798          138            3.945358         3.951205\n",
+       " 128119  2.702502 -14.519728          138            3.943449         3.951205\n",
+       " 128120  2.704204 -14.519654          138            3.941534         3.951205\n",
+       " 128121  2.705906 -14.519582          138            3.939619         3.951205\n",
+       " 128122  2.707608 -14.519507          138            3.937703         3.951205\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 128804  3.868168 -14.525043          138            0.000176         3.951205\n",
+       " 128805  3.869870 -14.525147          138            0.000165         3.951205\n",
+       " 128806  3.871572 -14.525251          138            0.000153         3.951205\n",
+       " 128807  3.873273 -14.525356          138            0.000141         3.951205\n",
+       " 128808  3.874975 -14.525461          138            0.000129         3.951205\n",
+       " \n",
+       " [691 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 129118  2.700801 -14.519899          139            3.942125         3.947005\n",
+       " 129119  2.702502 -14.520117          139            3.940306         3.947005\n",
+       " 129120  2.704204 -14.520151          139            3.938481         3.947005\n",
+       " 129121  2.705906 -14.519859          139            3.936643         3.947005\n",
+       " 129122  2.707608 -14.519567          139            3.934806         3.947005\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 129804  3.868168 -14.525068          139            0.000178         3.947005\n",
+       " 129805  3.869870 -14.525165          139            0.000166         3.947005\n",
+       " 129806  3.871572 -14.525262          139            0.000154         3.947005\n",
+       " 129807  3.873273 -14.525359          139            0.000142         3.947005\n",
+       " 129808  3.874975 -14.525456          139            0.000130         3.947005\n",
+       " \n",
+       " [691 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 130118  2.700801 -14.519582          140            3.939342           3.9447\n",
+       " 130119  2.702502 -14.519713          140            3.937437           3.9447\n",
+       " 130120  2.704204 -14.519861          140            3.935521           3.9447\n",
+       " 130121  2.705906 -14.520009          140            3.933604           3.9447\n",
+       " 130122  2.707608 -14.519963          140            3.931723           3.9447\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 130804  3.868168 -14.526375          140            0.000171           3.9447\n",
+       " 130805  3.869870 -14.526501          140            0.000159           3.9447\n",
+       " 130806  3.871572 -14.526627          140            0.000148           3.9447\n",
+       " 130807  3.873273 -14.526752          140            0.000136           3.9447\n",
+       " 130808  3.874975 -14.526878          140            0.000124           3.9447\n",
+       " \n",
+       " [691 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 131118  2.700801 -14.519877          146            3.975067         4.073756\n",
+       " 131119  2.702502 -14.520027          146            3.972948         4.073756\n",
+       " 131120  2.704204 -14.520027          146            3.970679         4.073756\n",
+       " 131121  2.705906 -14.520027          146            3.968410         4.073756\n",
+       " 131122  2.707608 -14.520029          146            3.966141         4.073756\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 131807  3.873273 -14.524435          146            0.000176         4.073756\n",
+       " 131808  3.874975 -14.524520          146            0.000165         4.073756\n",
+       " 131809  3.876677 -14.524605          146            0.000153         4.073756\n",
+       " 131810  3.878378 -14.524689          146            0.000142         4.073756\n",
+       " 131811  3.880080 -14.524774          146            0.000131         4.073756\n",
+       " \n",
+       " [694 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 132118  2.700801 -14.519875          147            3.967717         3.976259\n",
+       " 132119  2.702502 -14.520033          147            3.965594         3.976259\n",
+       " 132120  2.704204 -14.520106          147            3.963403         3.976259\n",
+       " 132121  2.705906 -14.520181          147            3.961213         3.976259\n",
+       " 132122  2.707608 -14.520255          147            3.959023         3.976259\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 132807  3.873273 -14.525972          147            0.000169         3.976259\n",
+       " 132808  3.874975 -14.526086          147            0.000158         3.976259\n",
+       " 132809  3.876677 -14.526199          147            0.000146         3.976259\n",
+       " 132810  3.878378 -14.526313          147            0.000135         3.976259\n",
+       " 132811  3.880080 -14.526426          147            0.000123         3.976259\n",
+       " \n",
+       " [694 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 133118  2.700801 -14.519746          148            3.957532         3.969686\n",
+       " 133119  2.702502 -14.519817          148            3.955319         3.969686\n",
+       " 133120  2.704204 -14.520114          148            3.953063         3.969686\n",
+       " 133121  2.705906 -14.520410          148            3.950808         3.969686\n",
+       " 133122  2.707608 -14.520374          148            3.948552         3.969686\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 133805  3.869870 -14.526469          148            0.000178         3.969686\n",
+       " 133806  3.871572 -14.526604          148            0.000167         3.969686\n",
+       " 133807  3.873273 -14.526737          148            0.000155         3.969686\n",
+       " 133808  3.874975 -14.526872          148            0.000144         3.969686\n",
+       " 133809  3.876677 -14.527006          148            0.000132         3.969686\n",
+       " \n",
+       " [692 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 134118  2.700801 -14.520300          149            3.951081         3.960113\n",
+       " 134119  2.702502 -14.519831          149            3.948940         3.960113\n",
+       " 134120  2.704204 -14.519904          149            3.946711         3.960113\n",
+       " 134121  2.705906 -14.519979          149            3.944481         3.960113\n",
+       " 134122  2.707608 -14.519976          149            3.942236         3.960113\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 134805  3.869870 -14.523935          149            0.000179         3.960113\n",
+       " 134806  3.871572 -14.524025          149            0.000167         3.960113\n",
+       " 134807  3.873273 -14.524115          149            0.000156         3.960113\n",
+       " 134808  3.874975 -14.524204          149            0.000144         3.960113\n",
+       " 134809  3.876677 -14.524294          149            0.000133         3.960113\n",
+       " \n",
+       " [692 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 135118  2.700801 -14.520117          150            3.943113         3.952693\n",
+       " 135119  2.702502 -14.520293          150            3.940942         3.952693\n",
+       " 135120  2.704204 -14.520469          150            3.938770         3.952693\n",
+       " 135121  2.705906 -14.520418          150            3.936493         3.952693\n",
+       " 135122  2.707608 -14.520346          150            3.934206         3.952693\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 135798  3.857958 -14.518978          150            0.000217         3.952693\n",
+       " 135799  3.859660 -14.518956          150            0.000204         3.952693\n",
+       " 135800  3.861361 -14.518933          150            0.000192         3.952693\n",
+       " 135801  3.863063 -14.518911          150            0.000179         3.952693\n",
+       " 135802  3.864765 -14.518889          150            0.000167         3.952693\n",
+       " \n",
+       " [685 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 136118  2.700801 -14.520256          151            3.938946         3.946351\n",
+       " 136119  2.702502 -14.520256          151            3.936712         3.946351\n",
+       " 136120  2.704204 -14.520256          151            3.934478         3.946351\n",
+       " 136121  2.705906 -14.520200          151            3.932243         3.946351\n",
+       " 136122  2.707608 -14.520126          151            3.930006         3.946351\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 136805  3.869870 -14.526812          151            0.000173         3.946351\n",
+       " 136806  3.871572 -14.526934          151            0.000162         3.946351\n",
+       " 136807  3.873273 -14.527056          151            0.000150         3.946351\n",
+       " 136808  3.874975 -14.527178          151            0.000139         3.946351\n",
+       " 136809  3.876677 -14.527300          151            0.000127         3.946351\n",
+       " \n",
+       " [692 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 137118  2.700801 -14.520201          152            3.929239         3.939153\n",
+       " 137119  2.702502 -14.520055          152            3.927041         3.939153\n",
+       " 137120  2.704204 -14.519910          152            3.924843         3.939153\n",
+       " 137121  2.705906 -14.519798          152            3.922630         3.939153\n",
+       " 137122  2.707608 -14.519798          152            3.920368         3.939153\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 137804  3.868168 -14.526515          152            0.000180         3.939153\n",
+       " 137805  3.869870 -14.526637          152            0.000168         3.939153\n",
+       " 137806  3.871572 -14.526759          152            0.000157         3.939153\n",
+       " 137807  3.873273 -14.526881          152            0.000145         3.939153\n",
+       " 137808  3.874975 -14.527003          152            0.000134         3.939153\n",
+       " \n",
+       " [691 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 138118  2.700801 -14.520027          153            3.925565         3.934006\n",
+       " 138119  2.702502 -14.519900          153            3.923348         3.934006\n",
+       " 138120  2.704204 -14.519756          153            3.921131         3.934006\n",
+       " 138121  2.705906 -14.519612          153            3.918913         3.934006\n",
+       " 138122  2.707608 -14.519673          153            3.916660         3.934006\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 138804  3.868168 -14.526157          153            0.000170         3.934006\n",
+       " 138805  3.869870 -14.526278          153            0.000159         3.934006\n",
+       " 138806  3.871572 -14.526398          153            0.000148         3.934006\n",
+       " 138807  3.873273 -14.526519          153            0.000136         3.934006\n",
+       " 138808  3.874975 -14.526639          153            0.000125         3.934006\n",
+       " \n",
+       " [691 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 139118  2.700801 -14.519984          154            3.920842         3.925068\n",
+       " 139119  2.702502 -14.519894          154            3.918705         3.925068\n",
+       " 139120  2.704204 -14.519802          154            3.916569         3.925068\n",
+       " 139121  2.705906 -14.519727          154            3.914299         3.925068\n",
+       " 139122  2.707608 -14.519651          154            3.912024         3.925068\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 139796  3.854555 -14.521049          154            0.000220         3.925068\n",
+       " 139797  3.856256 -14.521076          154            0.000208         3.925068\n",
+       " 139798  3.857958 -14.521102          154            0.000195         3.925068\n",
+       " 139799  3.859660 -14.521129          154            0.000183         3.925068\n",
+       " 139800  3.861361 -14.521154          154            0.000171         3.925068\n",
+       " \n",
+       " [683 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 140118  2.700801 -14.520407          155            3.910630         3.923263\n",
+       " 140119  2.702502 -14.520240          155            3.908477         3.923263\n",
+       " 140120  2.704204 -14.520072          155            3.906324         3.923263\n",
+       " 140121  2.705906 -14.520082          155            3.904077         3.923263\n",
+       " 140122  2.707608 -14.520155          155            3.901795         3.923263\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 140803  3.866467 -14.525119          155            0.000168         3.923263\n",
+       " 140804  3.868168 -14.525220          155            0.000156         3.923263\n",
+       " 140805  3.869870 -14.525320          155            0.000145         3.923263\n",
+       " 140806  3.871572 -14.525420          155            0.000134         3.923263\n",
+       " 140807  3.873273 -14.525520          155            0.000122         3.923263\n",
+       " \n",
+       " [690 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 141118  2.700801 -14.519833          156            3.907088         3.912552\n",
+       " 141119  2.702502 -14.519907          156            3.904949         3.912552\n",
+       " 141120  2.704204 -14.519980          156            3.902811         3.912552\n",
+       " 141121  2.705906 -14.520027          156            3.900646         3.912552\n",
+       " 141122  2.707608 -14.520027          156            3.898437         3.912552\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 141803  3.866467 -14.524074          156            0.000170         3.912552\n",
+       " 141804  3.868168 -14.524147          156            0.000158         3.912552\n",
+       " 141805  3.869870 -14.524220          156            0.000147         3.912552\n",
+       " 141806  3.871572 -14.524293          156            0.000135         3.912552\n",
+       " 141807  3.873273 -14.524366          156            0.000124         3.912552\n",
+       " \n",
+       " [690 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 142118  2.700801 -14.519961          157            3.899760         3.909593\n",
+       " 142119  2.702502 -14.519819          157            3.897736         3.909593\n",
+       " 142120  2.704204 -14.519734          157            3.895497         3.909593\n",
+       " 142121  2.705906 -14.519659          157            3.893222         3.909593\n",
+       " 142122  2.707608 -14.519584          157            3.890946         3.909593\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 142795  3.852853 -14.519173          157            0.000220         3.909593\n",
+       " 142796  3.854555 -14.519159          157            0.000208         3.909593\n",
+       " 142797  3.856256 -14.519146          157            0.000195         3.909593\n",
+       " 142798  3.857958 -14.519134          157            0.000183         3.909593\n",
+       " 142799  3.859660 -14.519120          157            0.000171         3.909593\n",
+       " \n",
+       " [682 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 143118  2.700801 -14.519751          158            3.897954         3.903176\n",
+       " 143119  2.702502 -14.519649          158            3.895777         3.903176\n",
+       " 143120  2.704204 -14.519603          158            3.893591         3.903176\n",
+       " 143121  2.705906 -14.519751          158            3.891375         3.903176\n",
+       " 143122  2.707608 -14.519898          158            3.889158         3.903176\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 143802  3.864765 -14.524656          158            0.000172         3.903176\n",
+       " 143803  3.866467 -14.524749          158            0.000161         3.903176\n",
+       " 143804  3.868168 -14.524840          158            0.000150         3.903176\n",
+       " 143805  3.869870 -14.524932          158            0.000138         3.903176\n",
+       " 143806  3.871572 -14.525024          158            0.000127         3.903176\n",
+       " \n",
+       " [689 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 144118  2.700801 -14.520137          159            3.892298          3.89893\n",
+       " 144119  2.702502 -14.520027          159            3.890224          3.89893\n",
+       " 144120  2.704204 -14.520027          159            3.888112          3.89893\n",
+       " 144121  2.705906 -14.520027          159            3.886000          3.89893\n",
+       " 144122  2.707608 -14.520099          159            3.883816          3.89893\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 144801  3.863063 -14.526549          159            0.000175          3.89893\n",
+       " 144802  3.864765 -14.526673          159            0.000163          3.89893\n",
+       " 144803  3.866467 -14.526798          159            0.000152          3.89893\n",
+       " 144804  3.868168 -14.526922          159            0.000141          3.89893\n",
+       " 144805  3.869870 -14.527046          159            0.000129          3.89893\n",
+       " \n",
+       " [688 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 145118  2.700801 -14.519798          160            3.891174         3.896872\n",
+       " 145119  2.702502 -14.519867          160            3.889014         3.896872\n",
+       " 145120  2.704204 -14.519941          160            3.886850         3.896872\n",
+       " 145121  2.705906 -14.520015          160            3.884686         3.896872\n",
+       " 145122  2.707608 -14.520027          160            3.882548         3.896872\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 145795  3.852853 -14.519588          160            0.000213         3.896872\n",
+       " 145796  3.854555 -14.519583          160            0.000200         3.896872\n",
+       " 145797  3.856256 -14.519578          160            0.000188         3.896872\n",
+       " 145798  3.857958 -14.519574          160            0.000176         3.896872\n",
+       " 145799  3.859660 -14.519569          160            0.000164         3.896872\n",
+       " \n",
+       " [682 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 146118  2.700801 -14.519751          161            3.885631         3.892158\n",
+       " 146119  2.702502 -14.519658          161            3.883603         3.892158\n",
+       " 146120  2.704204 -14.519569          161            3.881568         3.892158\n",
+       " 146121  2.705906 -14.519569          161            3.879390         3.892158\n",
+       " 146122  2.707608 -14.519569          161            3.877213         3.892158\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 146801  3.863063 -14.525480          161            0.000174         3.892158\n",
+       " 146802  3.864765 -14.525588          161            0.000163         3.892158\n",
+       " 146803  3.866467 -14.525696          161            0.000152         3.892158\n",
+       " 146804  3.868168 -14.525805          161            0.000141         3.892158\n",
+       " 146805  3.869870 -14.525912          161            0.000129         3.892158\n",
+       " \n",
+       " [688 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 147118  2.700801 -14.519375          162            3.880030         3.887617\n",
+       " 147119  2.702502 -14.519449          162            3.877905         3.887617\n",
+       " 147120  2.704204 -14.519523          162            3.875780         3.887617\n",
+       " 147121  2.705906 -14.519597          162            3.873635         3.887617\n",
+       " 147122  2.707608 -14.519670          162            3.871458         3.887617\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 147800  3.861361 -14.523793          162            0.000178         3.887617\n",
+       " 147801  3.863063 -14.523865          162            0.000167         3.887617\n",
+       " 147802  3.864765 -14.523936          162            0.000155         3.887617\n",
+       " 147803  3.866467 -14.524008          162            0.000144         3.887617\n",
+       " 147804  3.868168 -14.524080          162            0.000133         3.887617\n",
+       " \n",
+       " [687 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 148118  2.700801 -14.519888          163            3.875941         3.881735\n",
+       " 148119  2.702502 -14.520081          163            3.873871         3.881735\n",
+       " 148120  2.704204 -14.520256          163            3.871784         3.881735\n",
+       " 148121  2.705906 -14.520256          163            3.869542         3.881735\n",
+       " 148122  2.707608 -14.520256          163            3.867299         3.881735\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 148800  3.861361 -14.524451          163            0.000176         3.881735\n",
+       " 148801  3.863063 -14.524531          163            0.000165         3.881735\n",
+       " 148802  3.864765 -14.524611          163            0.000154         3.881735\n",
+       " 148803  3.866467 -14.524691          163            0.000143         3.881735\n",
+       " 148804  3.868168 -14.524770          163            0.000131         3.881735\n",
+       " \n",
+       " [687 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 149118  2.700801 -14.519569          164            3.869945          3.87752\n",
+       " 149119  2.702502 -14.519569          164            3.867903          3.87752\n",
+       " 149120  2.704204 -14.519630          164            3.865811          3.87752\n",
+       " 149121  2.705906 -14.519705          164            3.863707          3.87752\n",
+       " 149122  2.707608 -14.519780          164            3.861604          3.87752\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 149800  3.861361 -14.526591          164            0.000171          3.87752\n",
+       " 149801  3.863063 -14.526714          164            0.000160          3.87752\n",
+       " 149802  3.864765 -14.526837          164            0.000148          3.87752\n",
+       " 149803  3.866467 -14.526961          164            0.000137          3.87752\n",
+       " 149804  3.868168 -14.527084          164            0.000126          3.87752\n",
+       " \n",
+       " [687 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 150118  2.700801 -14.519460          165            3.868447         3.872644\n",
+       " 150119  2.702502 -14.519714          165            3.866393         3.872644\n",
+       " 150120  2.704204 -14.519970          165            3.864339         3.872644\n",
+       " 150121  2.705906 -14.519970          165            3.862230         3.872644\n",
+       " 150122  2.707608 -14.519896          165            3.860105         3.872644\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 150800  3.861361 -14.525517          165            0.000172         3.872644\n",
+       " 150801  3.863063 -14.525621          165            0.000161         3.872644\n",
+       " 150802  3.864765 -14.525725          165            0.000150         3.872644\n",
+       " 150803  3.866467 -14.525828          165            0.000139         3.872644\n",
+       " 150804  3.868168 -14.525932          165            0.000127         3.872644\n",
+       " \n",
+       " [687 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 151118  2.700801 -14.519703          166            3.864698         3.870899\n",
+       " 151119  2.702502 -14.519594          166            3.862642         3.870899\n",
+       " 151120  2.704204 -14.519666          166            3.860576         3.870899\n",
+       " 151121  2.705906 -14.519738          166            3.858511         3.870899\n",
+       " 151122  2.707608 -14.519810          166            3.856439         3.870899\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 151800  3.861361 -14.524898          166            0.000173         3.870899\n",
+       " 151801  3.863063 -14.524985          166            0.000162         3.870899\n",
+       " 151802  3.864765 -14.525073          166            0.000151         3.870899\n",
+       " 151803  3.866467 -14.525161          166            0.000139         3.870899\n",
+       " 151804  3.868168 -14.525249          166            0.000128         3.870899\n",
+       " \n",
+       " [687 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 152118  2.700801 -14.520145          167            3.861327         3.867456\n",
+       " 152119  2.702502 -14.519837          167            3.859286         3.867456\n",
+       " 152120  2.704204 -14.519913          167            3.857143         3.867456\n",
+       " 152121  2.705906 -14.519988          167            3.855000         3.867456\n",
+       " 152122  2.707608 -14.519992          167            3.852878         3.867456\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 152793  3.849449 -14.520890          167            0.000213         3.867456\n",
+       " 152794  3.851151 -14.520903          167            0.000200         3.867456\n",
+       " 152795  3.852853 -14.520916          167            0.000188         3.867456\n",
+       " 152796  3.854555 -14.520929          167            0.000176         3.867456\n",
+       " 152797  3.856256 -14.520942          167            0.000163         3.867456\n",
+       " \n",
+       " [680 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 153118  2.700801 -14.519798          168            3.855897         3.862147\n",
+       " 153119  2.702502 -14.519798          168            3.853841         3.862147\n",
+       " 153120  2.704204 -14.519798          168            3.851784         3.862147\n",
+       " 153121  2.705906 -14.519798          168            3.849718         3.862147\n",
+       " 153122  2.707608 -14.519798          168            3.847610         3.862147\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 153799  3.859660 -14.526613          168            0.000172         3.862147\n",
+       " 153800  3.861361 -14.526729          168            0.000161         3.862147\n",
+       " 153801  3.863063 -14.526844          168            0.000150         3.862147\n",
+       " 153802  3.864765 -14.526959          168            0.000138         3.862147\n",
+       " 153803  3.866467 -14.527075          168            0.000127         3.862147\n",
+       " \n",
+       " [686 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 154118  2.700801 -14.519987          169            3.850115         3.857899\n",
+       " 154119  2.702502 -14.519902          169            3.848016         3.857899\n",
+       " 154120  2.704204 -14.519817          169            3.845917         3.857899\n",
+       " 154121  2.705906 -14.519798          169            3.843797         3.857899\n",
+       " 154122  2.707608 -14.519798          169            3.841672         3.857899\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 154799  3.859660 -14.525556          169            0.000168         3.857899\n",
+       " 154800  3.861361 -14.525659          169            0.000157         3.857899\n",
+       " 154801  3.863063 -14.525762          169            0.000146         3.857899\n",
+       " 154802  3.864765 -14.525865          169            0.000135         3.857899\n",
+       " 154803  3.866467 -14.525968          169            0.000124         3.857899\n",
+       " \n",
+       " [686 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 155118  2.700801 -14.519813          170            3.848703         3.853097\n",
+       " 155119  2.702502 -14.520038          170            3.846600         3.853097\n",
+       " 155120  2.704204 -14.520263          170            3.844496         3.853097\n",
+       " 155121  2.705906 -14.520485          170            3.842392         3.853097\n",
+       " 155122  2.707608 -14.520485          170            3.840262         3.853097\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 155799  3.859660 -14.523181          170            0.000169         3.853097\n",
+       " 155800  3.861361 -14.523249          170            0.000158         3.853097\n",
+       " 155801  3.863063 -14.523315          170            0.000146         3.853097\n",
+       " 155802  3.864765 -14.523383          170            0.000135         3.853097\n",
+       " 155803  3.866467 -14.523451          170            0.000124         3.853097\n",
+       " \n",
+       " [686 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 156118  2.700801 -14.520226          171            3.843612         3.850954\n",
+       " 156119  2.702502 -14.520152          171            3.841556         3.850954\n",
+       " 156120  2.704204 -14.520080          171            3.839500         3.850954\n",
+       " 156121  2.705906 -14.520027          171            3.837419         3.850954\n",
+       " 156122  2.707608 -14.520027          171            3.835276         3.850954\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 156799  3.859660 -14.525798          171            0.000169         3.850954\n",
+       " 156800  3.861361 -14.525897          171            0.000157         3.850954\n",
+       " 156801  3.863063 -14.525995          171            0.000146         3.850954\n",
+       " 156802  3.864765 -14.526094          171            0.000135         3.850954\n",
+       " 156803  3.866467 -14.526193          171            0.000124         3.850954\n",
+       " \n",
+       " [686 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 157118  2.700801 -14.519882          172            3.841861         3.847171\n",
+       " 157119  2.702502 -14.520061          172            3.839794         3.847171\n",
+       " 157120  2.704204 -14.520240          172            3.837726         3.847171\n",
+       " 157121  2.705906 -14.520125          172            3.835580         3.847171\n",
+       " 157122  2.707608 -14.519981          172            3.833426         3.847171\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 157799  3.859660 -14.524510          172            0.000168         3.847171\n",
+       " 157800  3.861361 -14.524590          172            0.000157         3.847171\n",
+       " 157801  3.863063 -14.524668          172            0.000146         3.847171\n",
+       " 157802  3.864765 -14.524747          172            0.000135         3.847171\n",
+       " 157803  3.866467 -14.524826          172            0.000124         3.847171\n",
+       " \n",
+       " [686 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 158118  2.700801 -14.519569          173            3.836352         3.842438\n",
+       " 158119  2.702502 -14.519569          173            3.834320         3.842438\n",
+       " 158120  2.704204 -14.519576          173            3.832283         3.842438\n",
+       " 158121  2.705906 -14.519724          173            3.830158         3.842438\n",
+       " 158122  2.707608 -14.519872          173            3.828033         3.842438\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 158798  3.857958 -14.526739          173            0.000173         3.842438\n",
+       " 158799  3.859660 -14.526874          173            0.000162         3.842438\n",
+       " 158800  3.861361 -14.527007          173            0.000151         3.842438\n",
+       " 158801  3.863063 -14.527142          173            0.000140         3.842438\n",
+       " 158802  3.864765 -14.527276          173            0.000129         3.842438\n",
+       " \n",
+       " [685 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 159118  2.700801 -14.520134          174            3.833269         3.839439\n",
+       " 159119  2.702502 -14.519873          174            3.831285         3.839439\n",
+       " 159120  2.704204 -14.519852          174            3.829225         3.839439\n",
+       " 159121  2.705906 -14.519927          174            3.827135         3.839439\n",
+       " 159122  2.707608 -14.520002          174            3.825045         3.839439\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 159798  3.857958 -14.525740          174            0.000173         3.839439\n",
+       " 159799  3.859660 -14.525842          174            0.000162         3.839439\n",
+       " 159800  3.861361 -14.525945          174            0.000151         3.839439\n",
+       " 159801  3.863063 -14.526047          174            0.000140         3.839439\n",
+       " 159802  3.864765 -14.526150          174            0.000129         3.839439\n",
+       " \n",
+       " [685 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 160118  2.700801 -14.519130          175            3.828938         3.834453\n",
+       " 160119  2.702502 -14.519422          175            3.826805         3.834453\n",
+       " 160120  2.704204 -14.519713          175            3.824671         3.834453\n",
+       " 160121  2.705906 -14.520005          175            3.822538         3.834453\n",
+       " 160122  2.707608 -14.520027          175            3.820479         3.834453\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 160798  3.857958 -14.524249          175            0.000168         3.834453\n",
+       " 160799  3.859660 -14.524336          175            0.000157         3.834453\n",
+       " 160800  3.861361 -14.524423          175            0.000146         3.834453\n",
+       " 160801  3.863063 -14.524508          175            0.000135         3.834453\n",
+       " 160802  3.864765 -14.524595          175            0.000124         3.834453\n",
+       " \n",
+       " [685 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 161118  2.700801 -14.519578          176            3.828580         3.832634\n",
+       " 161119  2.702502 -14.520019          176            3.826643         3.832634\n",
+       " 161120  2.704204 -14.519945          176            3.824574         3.832634\n",
+       " 161121  2.705906 -14.519873          176            3.822505         3.832634\n",
+       " 161122  2.707608 -14.519799          176            3.820436         3.832634\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 161798  3.857958 -14.523182          176            0.000169         3.832634\n",
+       " 161799  3.859660 -14.523249          176            0.000158         3.832634\n",
+       " 161800  3.861361 -14.523315          176            0.000146         3.832634\n",
+       " 161801  3.863063 -14.523383          176            0.000135         3.832634\n",
+       " 161802  3.864765 -14.523450          176            0.000124         3.832634\n",
+       " \n",
+       " [685 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 162118  2.700801 -14.519985          177            3.822025          3.82915\n",
+       " 162119  2.702502 -14.519896          177            3.819973          3.82915\n",
+       " 162120  2.704204 -14.519806          177            3.817921          3.82915\n",
+       " 162121  2.705906 -14.519931          177            3.815807          3.82915\n",
+       " 162122  2.707608 -14.520077          177            3.813687          3.82915\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 162797  3.856256 -14.525938          177            0.000174          3.82915\n",
+       " 162798  3.857958 -14.526044          177            0.000163          3.82915\n",
+       " 162799  3.859660 -14.526150          177            0.000152          3.82915\n",
+       " 162800  3.861361 -14.526256          177            0.000141          3.82915\n",
+       " 162801  3.863063 -14.526361          177            0.000130          3.82915\n",
+       " \n",
+       " [684 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 163118  2.700801 -14.520067          178            3.820384         3.825451\n",
+       " 163119  2.702502 -14.520152          178            3.818360         3.825451\n",
+       " 163120  2.704204 -14.520237          178            3.816336         3.825451\n",
+       " 163121  2.705906 -14.520026          178            3.814254         3.825451\n",
+       " 163122  2.707608 -14.519731          178            3.812154         3.825451\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 163797  3.856256 -14.525079          178            0.000174         3.825451\n",
+       " 163798  3.857958 -14.525172          178            0.000163         3.825451\n",
+       " 163799  3.859660 -14.525266          178            0.000152         3.825451\n",
+       " 163800  3.861361 -14.525360          178            0.000141         3.825451\n",
+       " 163801  3.863063 -14.525454          178            0.000130         3.825451\n",
+       " \n",
+       " [684 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 164118  2.700801 -14.520078          179            3.815923         3.821813\n",
+       " 164119  2.702502 -14.520186          179            3.813932         3.821813\n",
+       " 164120  2.704204 -14.520203          179            3.811907         3.821813\n",
+       " 164121  2.705906 -14.520055          179            3.809821         3.821813\n",
+       " 164122  2.707608 -14.519907          179            3.807735         3.821813\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 164797  3.856256 -14.523876          179            0.000167         3.821813\n",
+       " 164798  3.857958 -14.523943          179            0.000156         3.821813\n",
+       " 164799  3.859660 -14.524009          179            0.000145         3.821813\n",
+       " 164800  3.861361 -14.524076          179            0.000134         3.821813\n",
+       " 164801  3.863063 -14.524141          179            0.000123         3.821813\n",
+       " \n",
+       " [684 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 165118  2.700801 -14.519941          180            3.814472         3.820099\n",
+       " 165119  2.702502 -14.519774          180            3.812422         3.820099\n",
+       " 165120  2.704204 -14.519607          180            3.810372         3.820099\n",
+       " 165121  2.705906 -14.519626          180            3.808317         3.820099\n",
+       " 165122  2.707608 -14.519699          180            3.806261         3.820099\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 165797  3.856256 -14.525552          180            0.000169         3.820099\n",
+       " 165798  3.857958 -14.525653          180            0.000158         3.820099\n",
+       " 165799  3.859660 -14.525754          180            0.000147         3.820099\n",
+       " 165800  3.861361 -14.525855          180            0.000136         3.820099\n",
+       " 165801  3.863063 -14.525956          180            0.000125         3.820099\n",
+       " \n",
+       " [684 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 166118  2.700801 -14.519886          181            3.810951         3.815746\n",
+       " 166119  2.702502 -14.520008          181            3.808863         3.815746\n",
+       " 166120  2.704204 -14.519936          181            3.806807         3.815746\n",
+       " 166121  2.705906 -14.519863          181            3.804751         3.815746\n",
+       " 166122  2.707608 -14.519807          181            3.802694         3.815746\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 166796  3.854555 -14.526361          181            0.000174         3.815746\n",
+       " 166797  3.856256 -14.526474          181            0.000163         3.815746\n",
+       " 166798  3.857958 -14.526587          181            0.000152         3.815746\n",
+       " 166799  3.859660 -14.526700          181            0.000141         3.815746\n",
+       " 166800  3.861361 -14.526813          181            0.000130         3.815746\n",
+       " \n",
+       " [683 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 167118  2.700801 -14.519798          182            3.810354         3.815898\n",
+       " 167119  2.702502 -14.519798          182            3.808357         3.815898\n",
+       " 167120  2.704204 -14.519798          182            3.806327         3.815898\n",
+       " 167121  2.705906 -14.519798          182            3.804296         3.815898\n",
+       " 167122  2.707608 -14.519798          182            3.802265         3.815898\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 167796  3.854555 -14.526332          182            0.000175         3.815898\n",
+       " 167797  3.856256 -14.526447          182            0.000164         3.815898\n",
+       " 167798  3.857958 -14.526564          182            0.000154         3.815898\n",
+       " 167799  3.859660 -14.526679          182            0.000143         3.815898\n",
+       " 167800  3.861361 -14.526794          182            0.000132         3.815898\n",
+       " \n",
+       " [683 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 168118  2.700801 -14.519510          183            3.804261           3.8093\n",
+       " 168119  2.702502 -14.519814          183            3.802196           3.8093\n",
+       " 168120  2.704204 -14.519885          183            3.800220           3.8093\n",
+       " 168121  2.705906 -14.519958          183            3.798243           3.8093\n",
+       " 168122  2.707608 -14.520029          183            3.796264           3.8093\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 168789  3.842643 -14.518571          183            0.000214           3.8093\n",
+       " 168790  3.844344 -14.518538          183            0.000202           3.8093\n",
+       " 168791  3.846046 -14.518503          183            0.000190           3.8093\n",
+       " 168792  3.847748 -14.518470          183            0.000179           3.8093\n",
+       " 168793  3.849449 -14.518436          183            0.000167           3.8093\n",
+       " \n",
+       " [676 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 169118  2.700801 -14.519839          184            3.801101         3.808289\n",
+       " 169119  2.702502 -14.519927          184            3.799069         3.808289\n",
+       " 169120  2.704204 -14.520016          184            3.797037         3.808289\n",
+       " 169121  2.705906 -14.519963          184            3.794959         3.808289\n",
+       " 169122  2.707608 -14.519889          184            3.792873         3.808289\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 169796  3.854555 -14.525968          184            0.000168         3.808289\n",
+       " 169797  3.856256 -14.526079          184            0.000157         3.808289\n",
+       " 169798  3.857958 -14.526191          184            0.000146         3.808289\n",
+       " 169799  3.859660 -14.526303          184            0.000135         3.808289\n",
+       " 169800  3.861361 -14.526415          184            0.000124         3.808289\n",
+       " \n",
+       " [683 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 170118  2.700801 -14.519657          185            3.798640         3.802546\n",
+       " 170119  2.702502 -14.519817          185            3.796618         3.802546\n",
+       " 170120  2.704204 -14.519891          185            3.794623         3.802546\n",
+       " 170121  2.705906 -14.519965          185            3.792628         3.802546\n",
+       " 170122  2.707608 -14.520040          185            3.790623         3.802546\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 170795  3.852853 -14.526609          185            0.000171         3.802546\n",
+       " 170796  3.854555 -14.526728          185            0.000160         3.802546\n",
+       " 170797  3.856256 -14.526846          185            0.000148         3.802546\n",
+       " 170798  3.857958 -14.526964          185            0.000137         3.802546\n",
+       " 170799  3.859660 -14.527083          185            0.000126         3.802546\n",
+       " \n",
+       " [682 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 171118  2.700801 -14.520172          186            3.795134         3.802258\n",
+       " 171119  2.702502 -14.519994          186            3.793192         3.802258\n",
+       " 171120  2.704204 -14.519814          186            3.791251         3.802258\n",
+       " 171121  2.705906 -14.519866          186            3.789190         3.802258\n",
+       " 171122  2.707608 -14.519939          186            3.787117         3.802258\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 171789  3.842643 -14.518936          186            0.000213         3.802258\n",
+       " 171790  3.844344 -14.518924          186            0.000201         3.802258\n",
+       " 171791  3.846046 -14.518911          186            0.000189         3.802258\n",
+       " 171792  3.847748 -14.518898          186            0.000178         3.802258\n",
+       " 171793  3.849449 -14.518886          186            0.000166         3.802258\n",
+       " \n",
+       " [676 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 172118  2.700801 -14.519813          187            3.791891         3.797421\n",
+       " 172119  2.702502 -14.519884          187            3.789876         3.797421\n",
+       " 172120  2.704204 -14.519957          187            3.787861         3.797421\n",
+       " 172121  2.705906 -14.520028          187            3.785847         3.797421\n",
+       " 172122  2.707608 -14.520102          187            3.783894         3.797421\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 172789  3.842643 -14.520426          187            0.000219         3.797421\n",
+       " 172790  3.844344 -14.520438          187            0.000207         3.797421\n",
+       " 172791  3.846046 -14.520451          187            0.000195         3.797421\n",
+       " 172792  3.847748 -14.520464          187            0.000183         3.797421\n",
+       " 172793  3.849449 -14.520476          187            0.000171         3.797421\n",
+       " \n",
+       " [676 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 173118  2.700801 -14.520188          188            3.787581         3.793761\n",
+       " 173119  2.702502 -14.520042          188            3.785705         3.793761\n",
+       " 173120  2.704204 -14.519959          188            3.783708         3.793761\n",
+       " 173121  2.705906 -14.519885          188            3.781697         3.793761\n",
+       " 173122  2.707608 -14.519810          188            3.779686         3.793761\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 173788  3.840941 -14.518329          188            0.000216         3.793761\n",
+       " 173789  3.842643 -14.518299          188            0.000204         3.793761\n",
+       " 173790  3.844344 -14.518270          188            0.000193         3.793761\n",
+       " 173791  3.846046 -14.518241          188            0.000181         3.793761\n",
+       " 173792  3.847748 -14.518211          188            0.000169         3.793761\n",
+       " \n",
+       " [675 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 174118  2.700801 -14.519917          189            3.784367         3.790459\n",
+       " 174119  2.702502 -14.520149          189            3.782363         3.790459\n",
+       " 174120  2.704204 -14.520176          189            3.780364         3.790459\n",
+       " 174121  2.705906 -14.520028          189            3.778370         3.790459\n",
+       " 174122  2.707608 -14.519880          189            3.776375         3.790459\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 174795  3.852853 -14.525048          189            0.000172         3.790459\n",
+       " 174796  3.854555 -14.525151          189            0.000161         3.790459\n",
+       " 174797  3.856256 -14.525255          189            0.000150         3.790459\n",
+       " 174798  3.857958 -14.525359          189            0.000139         3.790459\n",
+       " 174799  3.859660 -14.525462          189            0.000129         3.790459\n",
+       " \n",
+       " [682 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 175118  2.700801 -14.520050          190            3.780521         3.786676\n",
+       " 175119  2.702502 -14.519958          190            3.778547         3.786676\n",
+       " 175120  2.704204 -14.519885          190            3.776570         3.786676\n",
+       " 175121  2.705906 -14.519814          190            3.774594         3.786676\n",
+       " 175122  2.707608 -14.519680          190            3.772569         3.786676\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 175788  3.840941 -14.521317          190            0.000210         3.786676\n",
+       " 175789  3.842643 -14.521338          190            0.000198         3.786676\n",
+       " 175790  3.844344 -14.521358          190            0.000187         3.786676\n",
+       " 175791  3.846046 -14.521379          190            0.000175         3.786676\n",
+       " 175792  3.847748 -14.521399          190            0.000163         3.786676\n",
+       " \n",
+       " [675 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 176118  2.700801 -14.519841          191            3.785244         3.787261\n",
+       " 176119  2.702502 -14.519932          191            3.783283         3.787261\n",
+       " 176120  2.704204 -14.520023          191            3.781324         3.787261\n",
+       " 176121  2.705906 -14.519958          191            3.779370         3.787261\n",
+       " 176122  2.707608 -14.519884          191            3.777416         3.787261\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 176796  3.854555 -14.524693          191            0.000168         3.787261\n",
+       " 176797  3.856256 -14.524781          191            0.000157         3.787261\n",
+       " 176798  3.857958 -14.524870          191            0.000146         3.787261\n",
+       " 176799  3.859660 -14.524958          191            0.000135         3.787261\n",
+       " 176800  3.861361 -14.525046          191            0.000124         3.787261\n",
+       " \n",
+       " [683 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 177118  2.700801 -14.520002          192            3.779716         3.783058\n",
+       " 177119  2.702502 -14.520099          192            3.777773         3.783058\n",
+       " 177120  2.704204 -14.520173          192            3.775831         3.783058\n",
+       " 177121  2.705906 -14.520247          192            3.773888         3.783058\n",
+       " 177122  2.707608 -14.520128          192            3.771959         3.783058\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 177794  3.851151 -14.525057          192            0.000175         3.783058\n",
+       " 177795  3.852853 -14.525153          192            0.000164         3.783058\n",
+       " 177796  3.854555 -14.525249          192            0.000153         3.783058\n",
+       " 177797  3.856256 -14.525344          192            0.000142         3.783058\n",
+       " 177798  3.857958 -14.525440          192            0.000132         3.783058\n",
+       " \n",
+       " [681 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 178118  2.700801 -14.519957          193            3.772614         3.782889\n",
+       " 178119  2.702502 -14.520086          193            3.770586         3.782889\n",
+       " 178120  2.704204 -14.520160          193            3.768501         3.782889\n",
+       " 178121  2.705906 -14.520234          193            3.766414         3.782889\n",
+       " 178122  2.707608 -14.520205          193            3.764396         3.782889\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 178794  3.851151 -14.524000          193            0.000173         3.782889\n",
+       " 178795  3.852853 -14.524080          193            0.000162         3.782889\n",
+       " 178796  3.854555 -14.524161          193            0.000151         3.782889\n",
+       " 178797  3.856256 -14.524241          193            0.000140         3.782889\n",
+       " 178798  3.857958 -14.524323          193            0.000130         3.782889\n",
+       " \n",
+       " [681 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 179118  2.700801 -14.519863          194            3.770256         3.775924\n",
+       " 179119  2.702502 -14.520394          194            3.768339         3.775924\n",
+       " 179120  2.704204 -14.520247          194            3.766318         3.775924\n",
+       " 179121  2.705906 -14.520098          194            3.764297         3.775924\n",
+       " 179122  2.707608 -14.519952          194            3.762286         3.775924\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 179795  3.852853 -14.524895          194            0.000169         3.775924\n",
+       " 179796  3.854555 -14.524986          194            0.000158         3.775924\n",
+       " 179797  3.856256 -14.525078          194            0.000148         3.775924\n",
+       " 179798  3.857958 -14.525169          194            0.000137         3.775924\n",
+       " 179799  3.859660 -14.525261          194            0.000126         3.775924\n",
+       " \n",
+       " [682 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 180118  2.700801 -14.519666          195            3.767497         3.772811\n",
+       " 180119  2.702502 -14.519715          195            3.765578         3.772811\n",
+       " 180120  2.704204 -14.519938          195            3.763544         3.772811\n",
+       " 180121  2.705906 -14.520160          195            3.761510         3.772811\n",
+       " 180122  2.707608 -14.520214          195            3.759506         3.772811\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 180794  3.851151 -14.524038          195            0.000170         3.772811\n",
+       " 180795  3.852853 -14.524115          195            0.000159         3.772811\n",
+       " 180796  3.854555 -14.524191          195            0.000149         3.772811\n",
+       " 180797  3.856256 -14.524266          195            0.000138         3.772811\n",
+       " 180798  3.857958 -14.524343          195            0.000127         3.772811\n",
+       " \n",
+       " [681 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 181118  2.700801 -14.520217          196            3.768276         3.770911\n",
+       " 181119  2.702502 -14.520133          196            3.766344         3.770911\n",
+       " 181120  2.704204 -14.520050          196            3.764412         3.770911\n",
+       " 181121  2.705906 -14.520082          196            3.762415         3.770911\n",
+       " 181122  2.707608 -14.520155          196            3.760395         3.770911\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 181794  3.851151 -14.525530          196            0.000173         3.770911\n",
+       " 181795  3.852853 -14.525625          196            0.000162         3.770911\n",
+       " 181796  3.854555 -14.525721          196            0.000152         3.770911\n",
+       " 181797  3.856256 -14.525816          196            0.000141         3.770911\n",
+       " 181798  3.857958 -14.525911          196            0.000130         3.770911\n",
+       " \n",
+       " [681 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 182118  2.700801 -14.519827          197            3.764352         3.768966\n",
+       " 182119  2.702502 -14.520378          197            3.762479         3.768966\n",
+       " 182120  2.704204 -14.520306          197            3.760540         3.768966\n",
+       " 182121  2.705906 -14.520083          197            3.758584         3.768966\n",
+       " 182122  2.707608 -14.519862          197            3.756629         3.768966\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 182794  3.851151 -14.525771          197            0.000168         3.768966\n",
+       " 182795  3.852853 -14.525873          197            0.000157         3.768966\n",
+       " 182796  3.854555 -14.525976          197            0.000147         3.768966\n",
+       " 182797  3.856256 -14.526078          197            0.000136         3.768966\n",
+       " 182798  3.857958 -14.526180          197            0.000125         3.768966\n",
+       " \n",
+       " [681 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 183118  2.700801 -14.519975          198            3.758925         3.767091\n",
+       " 183119  2.702502 -14.519861          198            3.757006         3.767091\n",
+       " 183120  2.704204 -14.519831          198            3.755042         3.767091\n",
+       " 183121  2.705906 -14.519904          198            3.753025         3.767091\n",
+       " 183122  2.707608 -14.519977          198            3.751007         3.767091\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 183793  3.849449 -14.525698          198            0.000176         3.767091\n",
+       " 183794  3.851151 -14.525800          198            0.000165         3.767091\n",
+       " 183795  3.852853 -14.525902          198            0.000154         3.767091\n",
+       " 183796  3.854555 -14.526004          198            0.000144         3.767091\n",
+       " 183797  3.856256 -14.526106          198            0.000133         3.767091\n",
+       " \n",
+       " [680 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 184118  2.700801 -14.520362          199            3.757331         3.760174\n",
+       " 184119  2.702502 -14.520098          199            3.755455         3.760174\n",
+       " 184120  2.704204 -14.519834          199            3.753578         3.760174\n",
+       " 184121  2.705906 -14.519861          199            3.751557         3.760174\n",
+       " 184122  2.707608 -14.519935          199            3.749513         3.760174\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 184794  3.851151 -14.525756          199            0.000171         3.760174\n",
+       " 184795  3.852853 -14.525856          199            0.000161         3.760174\n",
+       " 184796  3.854555 -14.525955          199            0.000150         3.760174\n",
+       " 184797  3.856256 -14.526054          199            0.000139         3.760174\n",
+       " 184798  3.857958 -14.526155          199            0.000128         3.760174\n",
+       " \n",
+       " [681 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 185118  2.700801 -14.519904          200            3.753228         3.759653\n",
+       " 185119  2.702502 -14.520131          200            3.751289         3.759653\n",
+       " 185120  2.704204 -14.520288          200            3.749345         3.759653\n",
+       " 185121  2.705906 -14.520360          200            3.747394         3.759653\n",
+       " 185122  2.707608 -14.520432          200            3.745442         3.759653\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 185787  3.839239 -14.518986          200            0.000211         3.759653\n",
+       " 185788  3.840941 -14.518961          200            0.000199         3.759653\n",
+       " 185789  3.842643 -14.518936          200            0.000188         3.759653\n",
+       " 185790  3.844344 -14.518910          200            0.000176         3.759653\n",
+       " 185791  3.846046 -14.518886          200            0.000164         3.759653\n",
+       " \n",
+       " [674 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 186118  2.700801 -14.520073          201            3.753955         3.757663\n",
+       " 186119  2.702502 -14.520171          201            3.752017         3.757663\n",
+       " 186120  2.704204 -14.520247          201            3.750071         3.757663\n",
+       " 186121  2.705906 -14.520172          201            3.748063         3.757663\n",
+       " 186122  2.707608 -14.520098          201            3.746055         3.757663\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 186794  3.851151 -14.526188          201            0.000170         3.757663\n",
+       " 186795  3.852853 -14.526295          201            0.000160         3.757663\n",
+       " 186796  3.854555 -14.526401          201            0.000149         3.757663\n",
+       " 186797  3.856256 -14.526507          201            0.000138         3.757663\n",
+       " 186798  3.857958 -14.526613          201            0.000128         3.757663\n",
+       " \n",
+       " [681 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 187118  2.700801 -14.520167          202            3.751658         3.754761\n",
+       " 187119  2.702502 -14.520256          202            3.749849         3.754761\n",
+       " 187120  2.704204 -14.520256          202            3.747947         3.754761\n",
+       " 187121  2.705906 -14.520256          202            3.746045         3.754761\n",
+       " 187122  2.707608 -14.520213          202            3.744112         3.754761\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 187786  3.837538 -14.520862          202            0.000220         3.754761\n",
+       " 187787  3.839239 -14.520878          202            0.000209         3.754761\n",
+       " 187788  3.840941 -14.520894          202            0.000197         3.754761\n",
+       " 187789  3.842643 -14.520910          202            0.000185         3.754761\n",
+       " 187790  3.844344 -14.520927          202            0.000174         3.754761\n",
+       " \n",
+       " [673 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 188118  2.700801 -14.519938          203            3.746034         3.753855\n",
+       " 188119  2.702502 -14.519976          203            3.744117         3.753855\n",
+       " 188120  2.704204 -14.519903          203            3.742151         3.753855\n",
+       " 188121  2.705906 -14.519830          203            3.740184         3.753855\n",
+       " 188122  2.707608 -14.519880          203            3.738218         3.753855\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 188793  3.849449 -14.525516          203            0.000173         3.753855\n",
+       " 188794  3.851151 -14.525614          203            0.000162         3.753855\n",
+       " 188795  3.852853 -14.525712          203            0.000151         3.753855\n",
+       " 188796  3.854555 -14.525809          203            0.000141         3.753855\n",
+       " 188797  3.856256 -14.525908          203            0.000130         3.753855\n",
+       " \n",
+       " [680 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 189118  2.700801 -14.520027          204            3.744144         3.748565\n",
+       " 189119  2.702502 -14.520027          204            3.742198         3.748565\n",
+       " 189120  2.704204 -14.520070          204            3.740256         3.748565\n",
+       " 189121  2.705906 -14.520143          204            3.738315         3.748565\n",
+       " 189122  2.707608 -14.520216          204            3.736374         3.748565\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 189793  3.849449 -14.526097          204            0.000174         3.748565\n",
+       " 189794  3.851151 -14.526214          204            0.000163         3.748565\n",
+       " 189795  3.852853 -14.526331          204            0.000153         3.748565\n",
+       " 189796  3.854555 -14.526448          204            0.000142         3.748565\n",
+       " 189797  3.856256 -14.526565          204            0.000132         3.748565\n",
+       " \n",
+       " [680 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 190118  2.700801 -14.519517          205            3.739549         3.745191\n",
+       " 190119  2.702502 -14.519836          205            3.737661         3.745191\n",
+       " 190120  2.704204 -14.519984          205            3.735705         3.745191\n",
+       " 190121  2.705906 -14.520132          205            3.733749         3.745191\n",
+       " 190122  2.707608 -14.520208          205            3.731796         3.745191\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 190786  3.837538 -14.520632          205            0.000209         3.745191\n",
+       " 190787  3.839239 -14.520653          205            0.000197         3.745191\n",
+       " 190788  3.840941 -14.520673          205            0.000186         3.745191\n",
+       " 190789  3.842643 -14.520693          205            0.000174         3.745191\n",
+       " 190790  3.844344 -14.520714          205            0.000163         3.745191\n",
+       " \n",
+       " [673 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 191118  2.700801 -14.520101          206            3.741363         3.745396\n",
+       " 191119  2.702502 -14.520257          206            3.739495         3.745396\n",
+       " 191120  2.704204 -14.520414          206            3.737626         3.745396\n",
+       " 191121  2.705906 -14.520485          206            3.735718         3.745396\n",
+       " 191122  2.707608 -14.520485          206            3.733778         3.745396\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 191793  3.849449 -14.525948          206            0.000168         3.745396\n",
+       " 191794  3.851151 -14.526059          206            0.000158         3.745396\n",
+       " 191795  3.852853 -14.526172          206            0.000147         3.745396\n",
+       " 191796  3.854555 -14.526283          206            0.000137         3.745396\n",
+       " 191797  3.856256 -14.526396          206            0.000126         3.745396\n",
+       " \n",
+       " [680 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 192118  2.700801 -14.519582          207            3.736392         3.741224\n",
+       " 192119  2.702502 -14.519713          207            3.734430         3.741224\n",
+       " 192120  2.704204 -14.519861          207            3.732461         3.741224\n",
+       " 192121  2.705906 -14.520009          207            3.730493         3.741224\n",
+       " 192122  2.707608 -14.520027          207            3.728617         3.741224\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 192786  3.837538 -14.520638          207            0.000216         3.741224\n",
+       " 192787  3.839239 -14.520655          207            0.000205         3.741224\n",
+       " 192788  3.840941 -14.520671          207            0.000193         3.741224\n",
+       " 192789  3.842643 -14.520687          207            0.000181         3.741224\n",
+       " 192790  3.844344 -14.520704          207            0.000170         3.741224\n",
+       " \n",
+       " [673 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 193118  2.700801 -14.519880          208            3.732471         3.739437\n",
+       " 193119  2.702502 -14.520057          208            3.730564         3.739437\n",
+       " 193120  2.704204 -14.520232          208            3.728656         3.739437\n",
+       " 193121  2.705906 -14.520319          208            3.726664         3.739437\n",
+       " 193122  2.707608 -14.520392          208            3.724659         3.739437\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 193793  3.849449 -14.526788          208            0.000172         3.739437\n",
+       " 193794  3.851151 -14.526907          208            0.000162         3.739437\n",
+       " 193795  3.852853 -14.527026          208            0.000151         3.739437\n",
+       " 193796  3.854555 -14.527146          208            0.000141         3.739437\n",
+       " 193797  3.856256 -14.527266          208            0.000130         3.739437\n",
+       " \n",
+       " [680 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 194118  2.700801 -14.519776          209            3.731819         3.736063\n",
+       " 194119  2.702502 -14.519630          209            3.729904         3.736063\n",
+       " 194120  2.704204 -14.519485          209            3.727989         3.736063\n",
+       " 194121  2.705906 -14.519342          209            3.726074         3.736063\n",
+       " 194122  2.707608 -14.519493          209            3.724129         3.736063\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 194793  3.849449 -14.525960          209            0.000170         3.736063\n",
+       " 194794  3.851151 -14.526065          209            0.000160         3.736063\n",
+       " 194795  3.852853 -14.526170          209            0.000149         3.736063\n",
+       " 194796  3.854555 -14.526275          209            0.000139         3.736063\n",
+       " 194797  3.856256 -14.526380          209            0.000128         3.736063\n",
+       " \n",
+       " [680 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 195118  2.700801 -14.520183          210            3.726179         3.732513\n",
+       " 195119  2.702502 -14.520026          210            3.724269         3.732513\n",
+       " 195120  2.704204 -14.519869          210            3.722359         3.732513\n",
+       " 195121  2.705906 -14.519757          210            3.720438         3.732513\n",
+       " 195122  2.707608 -14.519684          210            3.718508         3.732513\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 195792  3.847748 -14.525698          210            0.000174         3.732513\n",
+       " 195793  3.849449 -14.525803          210            0.000163         3.732513\n",
+       " 195794  3.851151 -14.525907          210            0.000153         3.732513\n",
+       " 195795  3.852853 -14.526011          210            0.000142         3.732513\n",
+       " 195796  3.854555 -14.526116          210            0.000132         3.732513\n",
+       " \n",
+       " [679 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 196118  2.700801 -14.520027          211            3.723890         3.728445\n",
+       " 196119  2.702502 -14.520027          211            3.721914         3.728445\n",
+       " 196120  2.704204 -14.520027          211            3.719990         3.728445\n",
+       " 196121  2.705906 -14.520027          211            3.718142         3.728445\n",
+       " 196122  2.707608 -14.520027          211            3.716293         3.728445\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 196792  3.847748 -14.526148          211            0.000173         3.728445\n",
+       " 196793  3.849449 -14.526256          211            0.000162         3.728445\n",
+       " 196794  3.851151 -14.526364          211            0.000152         3.728445\n",
+       " 196795  3.852853 -14.526472          211            0.000141         3.728445\n",
+       " 196796  3.854555 -14.526581          211            0.000131         3.728445\n",
+       " \n",
+       " [679 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 197118  2.700801 -14.520027          212            3.720906         3.726446\n",
+       " 197119  2.702502 -14.520017          212            3.719022         3.726446\n",
+       " 197120  2.704204 -14.519873          212            3.717159         3.726446\n",
+       " 197121  2.705906 -14.519729          212            3.715297         3.726446\n",
+       " 197122  2.707608 -14.519585          212            3.713434         3.726446\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 197785  3.835836 -14.521062          212            0.000214         3.726446\n",
+       " 197786  3.837538 -14.521087          212            0.000203         3.726446\n",
+       " 197787  3.839239 -14.521111          212            0.000191         3.726446\n",
+       " 197788  3.840941 -14.521135          212            0.000180         3.726446\n",
+       " 197789  3.842643 -14.521160          212            0.000168         3.726446\n",
+       " \n",
+       " [672 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 198118  2.700801 -14.519880          213            3.718189         3.723186\n",
+       " 198119  2.702502 -14.520051          213            3.716345         3.723186\n",
+       " 198120  2.704204 -14.520197          213            3.714430         3.723186\n",
+       " 198121  2.705906 -14.520343          213            3.712515         3.723186\n",
+       " 198122  2.707608 -14.520483          213            3.710601         3.723186\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 198792  3.847748 -14.525766          213            0.000170         3.723186\n",
+       " 198793  3.849449 -14.525863          213            0.000160         3.723186\n",
+       " 198794  3.851151 -14.525960          213            0.000149         3.723186\n",
+       " 198795  3.852853 -14.526056          213            0.000139         3.723186\n",
+       " 198796  3.854555 -14.526154          213            0.000128         3.723186\n",
+       " \n",
+       " [679 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 199118  2.700801 -14.520143          214            3.715098         3.721153\n",
+       " 199119  2.702502 -14.520066          214            3.713224         3.721153\n",
+       " 199120  2.704204 -14.520140          214            3.711281         3.721153\n",
+       " 199121  2.705906 -14.520214          214            3.709338         3.721153\n",
+       " 199122  2.707608 -14.520256          214            3.707397         3.721153\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 199792  3.847748 -14.526602          214            0.000168         3.721153\n",
+       " 199793  3.849449 -14.526721          214            0.000158         3.721153\n",
+       " 199794  3.851151 -14.526840          214            0.000147         3.721153\n",
+       " 199795  3.852853 -14.526958          214            0.000137         3.721153\n",
+       " 199796  3.854555 -14.527078          214            0.000126         3.721153\n",
+       " \n",
+       " [679 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 200118  2.700801 -14.519955          215            3.712566         3.718194\n",
+       " 200119  2.702502 -14.519800          215            3.710699         3.718194\n",
+       " 200120  2.704204 -14.519646          215            3.708831         3.718194\n",
+       " 200121  2.705906 -14.519607          215            3.706959         3.718194\n",
+       " 200122  2.707608 -14.519679          215            3.705083         3.718194\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 200792  3.847748 -14.525538          215            0.000167         3.718194\n",
+       " 200793  3.849449 -14.525642          215            0.000156         3.718194\n",
+       " 200794  3.851151 -14.525746          215            0.000146         3.718194\n",
+       " 200795  3.852853 -14.525849          215            0.000135         3.718194\n",
+       " 200796  3.854555 -14.525953          215            0.000125         3.718194\n",
+       " \n",
+       " [679 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 201118  2.700801 -14.519798          216            3.710495         3.714956\n",
+       " 201119  2.702502 -14.519798          216            3.708606         3.714956\n",
+       " 201120  2.704204 -14.519798          216            3.706716         3.714956\n",
+       " 201121  2.705906 -14.519798          216            3.704827         3.714956\n",
+       " 201122  2.707608 -14.519798          216            3.702913         3.714956\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 201791  3.846046 -14.524701          216            0.000171         3.714956\n",
+       " 201792  3.847748 -14.524779          216            0.000161         3.714956\n",
+       " 201793  3.849449 -14.524857          216            0.000150         3.714956\n",
+       " 201794  3.851151 -14.524934          216            0.000140         3.714956\n",
+       " 201795  3.852853 -14.525012          216            0.000129         3.714956\n",
+       " \n",
+       " [678 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 202118  2.700801 -14.519648          217            3.707293          3.71313\n",
+       " 202119  2.702502 -14.519814          217            3.705450          3.71313\n",
+       " 202120  2.704204 -14.519982          217            3.703606          3.71313\n",
+       " 202121  2.705906 -14.519973          217            3.701681          3.71313\n",
+       " 202122  2.707608 -14.519899          217            3.699725          3.71313\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 202791  3.846046 -14.525111          217            0.000171          3.71313\n",
+       " 202792  3.847748 -14.525200          217            0.000160          3.71313\n",
+       " 202793  3.849449 -14.525289          217            0.000150          3.71313\n",
+       " 202794  3.851151 -14.525377          217            0.000139          3.71313\n",
+       " 202795  3.852853 -14.525466          217            0.000129          3.71313\n",
+       " \n",
+       " [678 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 203118  2.700801 -14.520027          218            3.704694         3.709613\n",
+       " 203119  2.702502 -14.520027          218            3.702811         3.709613\n",
+       " 203120  2.704204 -14.520024          218            3.700927         3.709613\n",
+       " 203121  2.705906 -14.519951          218            3.699013         3.709613\n",
+       " 203122  2.707608 -14.519878          218            3.697098         3.709613\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 203791  3.846046 -14.524672          218            0.000170         3.709613\n",
+       " 203792  3.847748 -14.524756          218            0.000160         3.709613\n",
+       " 203793  3.849449 -14.524841          218            0.000150         3.709613\n",
+       " 203794  3.851151 -14.524926          218            0.000139         3.709613\n",
+       " 203795  3.852853 -14.525011          218            0.000129         3.709613\n",
+       " \n",
+       " [678 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 204118  2.700801 -14.520256          219            3.702406         3.708269\n",
+       " 204119  2.702502 -14.520256          219            3.700633         3.708269\n",
+       " 204120  2.704204 -14.520050          219            3.698775         3.708269\n",
+       " 204121  2.705906 -14.519832          219            3.696911         3.708269\n",
+       " 204122  2.707608 -14.519612          219            3.695048         3.708269\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 204791  3.846046 -14.526383          219            0.000169         3.708269\n",
+       " 204792  3.847748 -14.526497          219            0.000159         3.708269\n",
+       " 204793  3.849449 -14.526611          219            0.000148         3.708269\n",
+       " 204794  3.851151 -14.526725          219            0.000138         3.708269\n",
+       " 204795  3.852853 -14.526839          219            0.000127         3.708269\n",
+       " \n",
+       " [678 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 205118  2.700801 -14.519748          220            3.703303         3.704303\n",
+       " 205119  2.702502 -14.519639          220            3.701466         3.704303\n",
+       " 205120  2.704204 -14.519595          220            3.699628         3.704303\n",
+       " 205121  2.705906 -14.519667          220            3.697791         3.704303\n",
+       " 205122  2.707608 -14.519739          220            3.695954         3.704303\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 205791  3.846046 -14.526422          220            0.000168         3.704303\n",
+       " 205792  3.847748 -14.526528          220            0.000158         3.704303\n",
+       " 205793  3.849449 -14.526634          220            0.000148         3.704303\n",
+       " 205794  3.851151 -14.526741          220            0.000137         3.704303\n",
+       " 205795  3.852853 -14.526848          220            0.000127         3.704303\n",
+       " \n",
+       " [678 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 206118  2.700801 -14.519909          221            3.699550          3.70788\n",
+       " 206119  2.702502 -14.520256          221            3.697657          3.70788\n",
+       " 206120  2.704204 -14.520256          221            3.695719          3.70788\n",
+       " 206121  2.705906 -14.520256          221            3.693780          3.70788\n",
+       " 206122  2.707608 -14.520232          221            3.691851          3.70788\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 206791  3.846046 -14.525130          221            0.000168          3.70788\n",
+       " 206792  3.847748 -14.525218          221            0.000158          3.70788\n",
+       " 206793  3.849449 -14.525307          221            0.000148          3.70788\n",
+       " 206794  3.851151 -14.525394          221            0.000137          3.70788\n",
+       " 206795  3.852853 -14.525482          221            0.000127          3.70788\n",
+       " \n",
+       " [678 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 207118  2.700801 -14.519469          222            3.699328         3.702007\n",
+       " 207119  2.702502 -14.519745          222            3.697529         3.702007\n",
+       " 207120  2.704204 -14.519798          222            3.695667         3.702007\n",
+       " 207121  2.705906 -14.519798          222            3.693791         3.702007\n",
+       " 207122  2.707608 -14.519798          222            3.691915         3.702007\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 207791  3.846046 -14.526186          222            0.000171         3.702007\n",
+       " 207792  3.847748 -14.526289          222            0.000160         3.702007\n",
+       " 207793  3.849449 -14.526391          222            0.000150         3.702007\n",
+       " 207794  3.851151 -14.526494          222            0.000140         3.702007\n",
+       " 207795  3.852853 -14.526597          222            0.000129         3.702007\n",
+       " \n",
+       " [678 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 208118  2.700801 -14.520027          223            3.694400           3.7026\n",
+       " 208119  2.702502 -14.519969          223            3.692627           3.7026\n",
+       " 208120  2.704204 -14.519818          223            3.690669           3.7026\n",
+       " 208121  2.705906 -14.519669          223            3.688711           3.7026\n",
+       " 208122  2.707608 -14.519594          223            3.686754           3.7026\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 208784  3.834134 -14.520665          223            0.000209           3.7026\n",
+       " 208785  3.835836 -14.520677          223            0.000198           3.7026\n",
+       " 208786  3.837538 -14.520689          223            0.000186           3.7026\n",
+       " 208787  3.839239 -14.520700          223            0.000175           3.7026\n",
+       " 208788  3.840941 -14.520713          223            0.000164           3.7026\n",
+       " \n",
+       " [671 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 209118  2.700801 -14.519740          224            3.692582         3.695673\n",
+       " 209119  2.702502 -14.519627          224            3.690682         3.695673\n",
+       " 209120  2.704204 -14.519604          224            3.688833         3.695673\n",
+       " 209121  2.705906 -14.519674          224            3.687033         3.695673\n",
+       " 209122  2.707608 -14.519744          224            3.685234         3.695673\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 209791  3.846046 -14.526128          224            0.000171         3.695673\n",
+       " 209792  3.847748 -14.526241          224            0.000161         3.695673\n",
+       " 209793  3.849449 -14.526356          224            0.000151         3.695673\n",
+       " 209794  3.851151 -14.526470          224            0.000140         3.695673\n",
+       " 209795  3.852853 -14.526585          224            0.000130         3.695673\n",
+       " \n",
+       " [678 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 210118  2.700801 -14.519946          225            3.688097         3.695073\n",
+       " 210119  2.702502 -14.519601          225            3.686265         3.695073\n",
+       " 210120  2.704204 -14.519672          225            3.684440         3.695073\n",
+       " 210121  2.705906 -14.519745          225            3.682616         3.695073\n",
+       " 210122  2.707608 -14.519761          225            3.680762         3.695073\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 210790  3.844344 -14.525959          225            0.000171         3.695073\n",
+       " 210791  3.846046 -14.526061          225            0.000160         3.695073\n",
+       " 210792  3.847748 -14.526163          225            0.000150         3.695073\n",
+       " 210793  3.849449 -14.526265          225            0.000140         3.695073\n",
+       " 210794  3.851151 -14.526367          225            0.000129         3.695073\n",
+       " \n",
+       " [677 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 211118  2.700801 -14.519586          226            3.686815            3.692\n",
+       " 211119  2.702502 -14.519733          226            3.684924            3.692\n",
+       " 211120  2.704204 -14.519881          226            3.683034            3.692\n",
+       " 211121  2.705906 -14.520026          226            3.681144            3.692\n",
+       " 211122  2.707608 -14.519955          226            3.679320            3.692\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 211791  3.846046 -14.526838          226            0.000171            3.692\n",
+       " 211792  3.847748 -14.526948          226            0.000160            3.692\n",
+       " 211793  3.849449 -14.527059          226            0.000150            3.692\n",
+       " 211794  3.851151 -14.527169          226            0.000140            3.692\n",
+       " 211795  3.852853 -14.527279          226            0.000129            3.692\n",
+       " \n",
+       " [678 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 212118  2.700801 -14.519966          227            3.684735         3.689025\n",
+       " 212119  2.702502 -14.519820          227            3.682859         3.689025\n",
+       " 212120  2.704204 -14.519674          227            3.680983         3.689025\n",
+       " 212121  2.705906 -14.519610          227            3.679103         3.689025\n",
+       " 212122  2.707608 -14.519756          227            3.677214         3.689025\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 212790  3.844344 -14.526400          227            0.000171         3.689025\n",
+       " 212791  3.846046 -14.526505          227            0.000160         3.689025\n",
+       " 212792  3.847748 -14.526611          227            0.000150         3.689025\n",
+       " 212793  3.849449 -14.526717          227            0.000140         3.689025\n",
+       " 212794  3.851151 -14.526823          227            0.000129         3.689025\n",
+       " \n",
+       " [677 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 213118  2.700801 -14.519867          228            3.684536         3.689453\n",
+       " 213119  2.702502 -14.520015          228            3.682671         3.689453\n",
+       " 213120  2.704204 -14.520164          228            3.680807         3.689453\n",
+       " 213121  2.705906 -14.520229          228            3.678938         3.689453\n",
+       " 213122  2.707608 -14.520156          228            3.677062         3.689453\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 213783  3.832433 -14.522132          228            0.000215         3.689453\n",
+       " 213784  3.834134 -14.522172          228            0.000204         3.689453\n",
+       " 213785  3.835836 -14.522211          228            0.000192         3.689453\n",
+       " 213786  3.837538 -14.522251          228            0.000181         3.689453\n",
+       " 213787  3.839239 -14.522291          228            0.000170         3.689453\n",
+       " \n",
+       " [670 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 214118  2.700801 -14.520427          229            3.681138         3.684996\n",
+       " 214119  2.702502 -14.520303          229            3.679338         3.684996\n",
+       " 214120  2.704204 -14.520119          229            3.677491         3.684996\n",
+       " 214121  2.705906 -14.519900          229            3.675615         3.684996\n",
+       " 214122  2.707608 -14.519681          229            3.673738         3.684996\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 214790  3.844344 -14.526008          229            0.000167         3.684996\n",
+       " 214791  3.846046 -14.526106          229            0.000157         3.684996\n",
+       " 214792  3.847748 -14.526204          229            0.000147         3.684996\n",
+       " 214793  3.849449 -14.526302          229            0.000136         3.684996\n",
+       " 214794  3.851151 -14.526401          229            0.000126         3.684996\n",
+       " \n",
+       " [677 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 215118  2.700801 -14.519890          230            3.679210         3.685869\n",
+       " 215119  2.702502 -14.520072          230            3.677456         3.685869\n",
+       " 215120  2.704204 -14.520220          230            3.675565         3.685869\n",
+       " 215121  2.705906 -14.520368          230            3.673675         3.685869\n",
+       " 215122  2.707608 -14.520439          230            3.671784         3.685869\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 215790  3.844344 -14.526176          230            0.000168         3.685869\n",
+       " 215791  3.846046 -14.526285          230            0.000158         3.685869\n",
+       " 215792  3.847748 -14.526394          230            0.000148         3.685869\n",
+       " 215793  3.849449 -14.526503          230            0.000138         3.685869\n",
+       " 215794  3.851151 -14.526611          230            0.000128         3.685869\n",
+       " \n",
+       " [677 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 216118  2.700801 -14.519857          231            3.674704         3.680511\n",
+       " 216119  2.702502 -14.519985          231            3.672860         3.680511\n",
+       " 216120  2.704204 -14.520027          231            3.671020         3.680511\n",
+       " 216121  2.705906 -14.520027          231            3.669182         3.680511\n",
+       " 216122  2.707608 -14.520027          231            3.667344         3.680511\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 216790  3.844344 -14.525941          231            0.000171         3.680511\n",
+       " 216791  3.846046 -14.526047          231            0.000160         3.680511\n",
+       " 216792  3.847748 -14.526153          231            0.000150         3.680511\n",
+       " 216793  3.849449 -14.526258          231            0.000140         3.680511\n",
+       " 216794  3.851151 -14.526364          231            0.000129         3.680511\n",
+       " \n",
+       " [677 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 217118  2.700801 -14.519798          232            3.672982         3.678013\n",
+       " 217119  2.702502 -14.519798          232            3.671167         3.678013\n",
+       " 217120  2.704204 -14.519805          232            3.669347         3.678013\n",
+       " 217121  2.705906 -14.519949          232            3.667433         3.678013\n",
+       " 217122  2.707608 -14.520092          232            3.665520         3.678013\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 217790  3.844344 -14.524304          232            0.000167         3.678013\n",
+       " 217791  3.846046 -14.524374          232            0.000157         3.678013\n",
+       " 217792  3.847748 -14.524443          232            0.000147         3.678013\n",
+       " 217793  3.849449 -14.524511          232            0.000136         3.678013\n",
+       " 217794  3.851151 -14.524580          232            0.000126         3.678013\n",
+       " \n",
+       " [677 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 218118  2.700801 -14.519720          233            3.672870         3.677246\n",
+       " 218119  2.702502 -14.519553          233            3.671070         3.677246\n",
+       " 218120  2.704204 -14.519385          233            3.669271         3.677246\n",
+       " 218121  2.705906 -14.519503          233            3.667415         3.677246\n",
+       " 218122  2.707608 -14.519725          233            3.665537         3.677246\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 218790  3.844344 -14.526763          233            0.000170         3.677246\n",
+       " 218791  3.846046 -14.526890          233            0.000160         3.677246\n",
+       " 218792  3.847748 -14.527018          233            0.000149         3.677246\n",
+       " 218793  3.849449 -14.527144          233            0.000139         3.677246\n",
+       " 218794  3.851151 -14.527272          233            0.000129         3.677246\n",
+       " \n",
+       " [677 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 219118  2.700801 -14.520073          234            3.668820         3.673044\n",
+       " 219119  2.702502 -14.519820          234            3.667106         3.673044\n",
+       " 219120  2.704204 -14.519893          234            3.665268         3.673044\n",
+       " 219121  2.705906 -14.519966          234            3.663430         3.673044\n",
+       " 219122  2.707608 -14.520027          234            3.661584         3.673044\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 219782  3.830731 -14.519780          234            0.000214         3.673044\n",
+       " 219783  3.832433 -14.519784          234            0.000203         3.673044\n",
+       " 219784  3.834134 -14.519788          234            0.000192         3.673044\n",
+       " 219785  3.835836 -14.519792          234            0.000181         3.673044\n",
+       " 219786  3.837538 -14.519796          234            0.000170         3.673044\n",
+       " \n",
+       " [669 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 220118  2.700801 -14.519798          235            3.666560         3.673412\n",
+       " 220119  2.702502 -14.519798          235            3.664722         3.673412\n",
+       " 220120  2.704204 -14.519798          235            3.662884         3.673412\n",
+       " 220121  2.705906 -14.519870          235            3.661046         3.673412\n",
+       " 220122  2.707608 -14.520089          235            3.659209         3.673412\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 220790  3.844344 -14.525584          235            0.000164         3.673412\n",
+       " 220791  3.846046 -14.525681          235            0.000153         3.673412\n",
+       " 220792  3.847748 -14.525779          235            0.000143         3.673412\n",
+       " 220793  3.849449 -14.525877          235            0.000133         3.673412\n",
+       " 220794  3.851151 -14.525974          235            0.000123         3.673412\n",
+       " \n",
+       " [677 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 221118  2.700801 -14.519813          236            3.663222         3.668246\n",
+       " 221119  2.702502 -14.519886          236            3.661385         3.668246\n",
+       " 221120  2.704204 -14.519958          236            3.659547         3.668246\n",
+       " 221121  2.705906 -14.520027          236            3.657708         3.668246\n",
+       " 221122  2.707608 -14.520027          236            3.655858         3.668246\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 221790  3.844344 -14.526169          236            0.000166         3.668246\n",
+       " 221791  3.846046 -14.526285          236            0.000156         3.668246\n",
+       " 221792  3.847748 -14.526402          236            0.000146         3.668246\n",
+       " 221793  3.849449 -14.526518          236            0.000135         3.668246\n",
+       " 221794  3.851151 -14.526633          236            0.000125         3.668246\n",
+       " \n",
+       " [677 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 222118  2.700801 -14.519638          237            3.661927         3.666229\n",
+       " 222119  2.702502 -14.519786          237            3.660102         3.666229\n",
+       " 222120  2.704204 -14.519935          237            3.658276         3.666229\n",
+       " 222121  2.705906 -14.520000          237            3.656432         3.666229\n",
+       " 222122  2.707608 -14.519926          237            3.654554         3.666229\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 222782  3.830731 -14.520633          237            0.000209         3.666229\n",
+       " 222783  3.832433 -14.520652          237            0.000198         3.666229\n",
+       " 222784  3.834134 -14.520672          237            0.000187         3.666229\n",
+       " 222785  3.835836 -14.520691          237            0.000176         3.666229\n",
+       " 222786  3.837538 -14.520711          237            0.000165         3.666229\n",
+       " \n",
+       " [669 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 223118  2.700801 -14.520123          238            3.661905         3.666926\n",
+       " 223119  2.702502 -14.519979          238            3.660080         3.666926\n",
+       " 223120  2.704204 -14.519904          238            3.658189         3.666926\n",
+       " 223121  2.705906 -14.519831          238            3.656299         3.666926\n",
+       " 223122  2.707608 -14.519798          238            3.654453         3.666926\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 223782  3.830731 -14.520645          238            0.000211         3.666926\n",
+       " 223783  3.832433 -14.520661          238            0.000200         3.666926\n",
+       " 223784  3.834134 -14.520677          238            0.000189         3.666926\n",
+       " 223785  3.835836 -14.520692          238            0.000178         3.666926\n",
+       " 223786  3.837538 -14.520708          238            0.000167         3.666926\n",
+       " \n",
+       " [669 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 224118  2.700801 -14.520027          239            3.659056         3.662857\n",
+       " 224119  2.702502 -14.519944          239            3.657254         3.662857\n",
+       " 224120  2.704204 -14.519798          239            3.655416         3.662857\n",
+       " 224121  2.705906 -14.519652          239            3.653579         3.662857\n",
+       " 224122  2.707608 -14.519601          239            3.651752         3.662857\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 224789  3.842643 -14.526180          239            0.000170         3.662857\n",
+       " 224790  3.844344 -14.526285          239            0.000159         3.662857\n",
+       " 224791  3.846046 -14.526389          239            0.000149         3.662857\n",
+       " 224792  3.847748 -14.526494          239            0.000139         3.662857\n",
+       " 224793  3.849449 -14.526598          239            0.000129         3.662857\n",
+       " \n",
+       " [676 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 225118  2.700801 -14.519912          240            3.656171         3.661836\n",
+       " 225119  2.702502 -14.519950          240            3.654365         3.661836\n",
+       " 225120  2.704204 -14.519801          240            3.652474         3.661836\n",
+       " 225121  2.705906 -14.519653          240            3.650584         3.661836\n",
+       " 225122  2.707608 -14.519633          240            3.648710         3.661836\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 225781  3.829029 -14.517515          240            0.000218         3.661836\n",
+       " 225782  3.830731 -14.517468          240            0.000207         3.661836\n",
+       " 225783  3.832433 -14.517421          240            0.000196         3.661836\n",
+       " 225784  3.834134 -14.517374          240            0.000185         3.661836\n",
+       " 225785  3.835836 -14.517326          240            0.000174         3.661836\n",
+       " \n",
+       " [668 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 226118  2.700801 -14.519866          241            3.653872         3.659956\n",
+       " 226119  2.702502 -14.520012          241            3.652073         3.659956\n",
+       " 226120  2.704204 -14.520158          241            3.650274         3.659956\n",
+       " 226121  2.705906 -14.520206          241            3.648449         3.659956\n",
+       " 226122  2.707608 -14.520057          241            3.646570         3.659956\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 226789  3.842643 -14.525566          241            0.000167         3.659956\n",
+       " 226790  3.844344 -14.525660          241            0.000157         3.659956\n",
+       " 226791  3.846046 -14.525753          241            0.000147         3.659956\n",
+       " 226792  3.847748 -14.525846          241            0.000137         3.659956\n",
+       " 226793  3.849449 -14.525939          241            0.000127         3.659956\n",
+       " \n",
+       " [676 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 227118  2.700801 -14.519968          242            3.653752         3.655792\n",
+       " 227119  2.702502 -14.520271          242            3.651942         3.655792\n",
+       " 227120  2.704204 -14.520343          242            3.650092         3.655792\n",
+       " 227121  2.705906 -14.520415          242            3.648242         3.655792\n",
+       " 227122  2.707608 -14.520477          242            3.646390         3.655792\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 227788  3.840941 -14.525727          242            0.000173         3.655792\n",
+       " 227789  3.842643 -14.525824          242            0.000163         3.655792\n",
+       " 227790  3.844344 -14.525920          242            0.000152         3.655792\n",
+       " 227791  3.846046 -14.526017          242            0.000142         3.655792\n",
+       " 227792  3.847748 -14.526114          242            0.000132         3.655792\n",
+       " \n",
+       " [675 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 228118  2.700801 -14.519798          243            3.651564         3.658232\n",
+       " 228119  2.702502 -14.519798          243            3.649745         3.658232\n",
+       " 228120  2.704204 -14.519798          243            3.647912         3.658232\n",
+       " 228121  2.705906 -14.519798          243            3.646062         3.658232\n",
+       " 228122  2.707608 -14.519798          243            3.644212         3.658232\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 228789  3.842643 -14.524926          243            0.000169         3.658232\n",
+       " 228790  3.844344 -14.525004          243            0.000159         3.658232\n",
+       " 228791  3.846046 -14.525084          243            0.000149         3.658232\n",
+       " 228792  3.847748 -14.525163          243            0.000139         3.658232\n",
+       " 228793  3.849449 -14.525241          243            0.000129         3.658232\n",
+       " \n",
+       " [676 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 229118  2.700801 -14.519569          244            3.648991         3.654784\n",
+       " 229119  2.702502 -14.519649          244            3.647211         3.654784\n",
+       " 229120  2.704204 -14.519798          244            3.645293         3.654784\n",
+       " 229121  2.705906 -14.519948          244            3.643375         3.654784\n",
+       " 229122  2.707608 -14.520027          244            3.641495         3.654784\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 229789  3.842643 -14.524063          244            0.000167         3.654784\n",
+       " 229790  3.844344 -14.524135          244            0.000157         3.654784\n",
+       " 229791  3.846046 -14.524206          244            0.000146         3.654784\n",
+       " 229792  3.847748 -14.524278          244            0.000136         3.654784\n",
+       " 229793  3.849449 -14.524349          244            0.000126         3.654784\n",
+       " \n",
+       " [676 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 230118  2.700801 -14.519790          245            3.645928         3.649908\n",
+       " 230119  2.702502 -14.519569          245            3.644125         3.649908\n",
+       " 230120  2.704204 -14.519569          245            3.642249         3.649908\n",
+       " 230121  2.705906 -14.519569          245            3.640374         3.649908\n",
+       " 230122  2.707608 -14.519542          245            3.638509         3.649908\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 230788  3.840941 -14.525915          245            0.000171         3.649908\n",
+       " 230789  3.842643 -14.526022          245            0.000161         3.649908\n",
+       " 230790  3.844344 -14.526129          245            0.000151         3.649908\n",
+       " 230791  3.846046 -14.526236          245            0.000141         3.649908\n",
+       " 230792  3.847748 -14.526342          245            0.000131         3.649908\n",
+       " \n",
+       " [675 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 231118  2.700801 -14.519969          251            3.709962         3.808984\n",
+       " 231119  2.702502 -14.519845          251            3.707615         3.808984\n",
+       " 231120  2.704204 -14.519798          251            3.705235         3.808984\n",
+       " 231121  2.705906 -14.519798          251            3.702836         3.808984\n",
+       " 231122  2.707608 -14.519798          251            3.700437         3.808984\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 231793  3.849449 -14.526404          251            0.000170         3.808984\n",
+       " 231794  3.851151 -14.526506          251            0.000160         3.808984\n",
+       " 231795  3.852853 -14.526608          251            0.000150         3.808984\n",
+       " 231796  3.854555 -14.526710          251            0.000140         3.808984\n",
+       " 231797  3.856256 -14.526812          251            0.000130         3.808984\n",
+       " \n",
+       " [680 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 232118  2.700801 -14.519390          252            3.695725         3.710225\n",
+       " 232119  2.702502 -14.519541          252            3.693278         3.710225\n",
+       " 232120  2.704204 -14.519691          252            3.690830         3.710225\n",
+       " 232121  2.705906 -14.519798          252            3.688400         3.710225\n",
+       " 232122  2.707608 -14.519798          252            3.686014         3.710225\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 232792  3.847748 -14.526633          252            0.000168         3.710225\n",
+       " 232793  3.849449 -14.526738          252            0.000159         3.710225\n",
+       " 232794  3.851151 -14.526844          252            0.000149         3.710225\n",
+       " 232795  3.852853 -14.526949          252            0.000139         3.710225\n",
+       " 232796  3.854555 -14.527055          252            0.000129         3.710225\n",
+       " \n",
+       " [679 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 233118  2.700801 -14.520209          253            3.685199         3.698067\n",
+       " 233119  2.702502 -14.520109          253            3.682853         3.698067\n",
+       " 233120  2.704204 -14.520027          253            3.680489         3.698067\n",
+       " 233121  2.705906 -14.520027          253            3.678047         3.698067\n",
+       " 233122  2.707608 -14.520027          253            3.675606         3.698067\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 233784  3.834134 -14.520871          253            0.000213         3.698067\n",
+       " 233785  3.835836 -14.520886          253            0.000202         3.698067\n",
+       " 233786  3.837538 -14.520902          253            0.000192         3.698067\n",
+       " 233787  3.839239 -14.520917          253            0.000181         3.698067\n",
+       " 233788  3.840941 -14.520932          253            0.000170         3.698067\n",
+       " \n",
+       " [671 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 234118  2.700801 -14.520256          254            3.676863         3.687846\n",
+       " 234119  2.702502 -14.520256          254            3.674544         3.687846\n",
+       " 234120  2.704204 -14.520246          254            3.672207         3.687846\n",
+       " 234121  2.705906 -14.520171          254            3.669746         3.687846\n",
+       " 234122  2.707608 -14.520096          254            3.667286         3.687846\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 234791  3.846046 -14.526644          254            0.000168         3.687846\n",
+       " 234792  3.847748 -14.526749          254            0.000158         3.687846\n",
+       " 234793  3.849449 -14.526854          254            0.000148         3.687846\n",
+       " 234794  3.851151 -14.526958          254            0.000138         3.687846\n",
+       " 234795  3.852853 -14.527063          254            0.000128         3.687846\n",
+       " \n",
+       " [678 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 235118  2.700801 -14.520172          255            3.663119         3.675866\n",
+       " 235119  2.702502 -14.519994          255            3.660736         3.675866\n",
+       " 235120  2.704204 -14.519814          255            3.658353         3.675866\n",
+       " 235121  2.705906 -14.519867          255            3.655887         3.675866\n",
+       " 235122  2.707608 -14.519941          255            3.653413         3.675866\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 235790  3.844344 -14.526172          255            0.000169         3.675866\n",
+       " 235791  3.846046 -14.526276          255            0.000159         3.675866\n",
+       " 235792  3.847748 -14.526381          255            0.000149         3.675866\n",
+       " 235793  3.849449 -14.526485          255            0.000139         3.675866\n",
+       " 235794  3.851151 -14.526589          255            0.000130         3.675866\n",
+       " \n",
+       " [677 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 236118  2.700801 -14.519931          256            3.652344         3.663649\n",
+       " 236119  2.702502 -14.520214          256            3.650120         3.663649\n",
+       " 236120  2.704204 -14.520061          256            3.647674         3.663649\n",
+       " 236121  2.705906 -14.519833          256            3.645190         3.663649\n",
+       " 236122  2.707608 -14.519604          256            3.642706         3.663649\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 236790  3.844344 -14.526683          256            0.000164         3.663649\n",
+       " 236791  3.846046 -14.526787          256            0.000154         3.663649\n",
+       " 236792  3.847748 -14.526891          256            0.000144         3.663649\n",
+       " 236793  3.849449 -14.526996          256            0.000134         3.663649\n",
+       " 236794  3.851151 -14.527100          256            0.000125         3.663649\n",
+       " \n",
+       " [677 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 237118  2.700801 -14.519955          257            3.645927         3.653041\n",
+       " 237119  2.702502 -14.519800          257            3.643610         3.653041\n",
+       " 237120  2.704204 -14.519798          257            3.641243         3.653041\n",
+       " 237121  2.705906 -14.519798          257            3.638875         3.653041\n",
+       " 237122  2.707608 -14.519798          257            3.636507         3.653041\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 237789  3.842643 -14.526431          257            0.000167         3.653041\n",
+       " 237790  3.844344 -14.526532          257            0.000158         3.653041\n",
+       " 237791  3.846046 -14.526632          257            0.000148         3.653041\n",
+       " 237792  3.847748 -14.526733          257            0.000138         3.653041\n",
+       " 237793  3.849449 -14.526834          257            0.000128         3.653041\n",
+       " \n",
+       " [676 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 238118  2.700801 -14.519862          258            3.638250          3.64825\n",
+       " 238119  2.702502 -14.520000          258            3.635989          3.64825\n",
+       " 238120  2.704204 -14.519966          258            3.633631          3.64825\n",
+       " 238121  2.705906 -14.519892          258            3.631249          3.64825\n",
+       " 238122  2.707608 -14.519816          258            3.628868          3.64825\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 238789  3.842643 -14.526626          258            0.000165          3.64825\n",
+       " 238790  3.844344 -14.526741          258            0.000155          3.64825\n",
+       " 238791  3.846046 -14.526855          258            0.000145          3.64825\n",
+       " 238792  3.847748 -14.526970          258            0.000135          3.64825\n",
+       " 238793  3.849449 -14.527085          258            0.000126          3.64825\n",
+       " \n",
+       " [676 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 239118  2.700801 -14.520066          259            3.631240         3.640166\n",
+       " 239119  2.702502 -14.520150          259            3.628910         3.640166\n",
+       " 239120  2.704204 -14.520233          259            3.626580         3.640166\n",
+       " 239121  2.705906 -14.520091          259            3.624203         3.640166\n",
+       " 239122  2.707608 -14.519866          259            3.621808         3.640166\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 239781  3.829029 -14.520878          259            0.000208         3.640166\n",
+       " 239782  3.830731 -14.520893          259            0.000198         3.640166\n",
+       " 239783  3.832433 -14.520908          259            0.000187         3.640166\n",
+       " 239784  3.834134 -14.520924          259            0.000176         3.640166\n",
+       " 239785  3.835836 -14.520939          259            0.000166         3.640166\n",
+       " \n",
+       " [668 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 240118  2.700801 -14.519968          260            3.625307         3.634193\n",
+       " 240119  2.702502 -14.519840          260            3.622968         3.634193\n",
+       " 240120  2.704204 -14.519749          260            3.620615         3.634193\n",
+       " 240121  2.705906 -14.519674          260            3.618255         3.634193\n",
+       " 240122  2.707608 -14.519601          260            3.615896         3.634193\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 240788  3.840941 -14.526192          260            0.000167         3.634193\n",
+       " 240789  3.842643 -14.526296          260            0.000157         3.634193\n",
+       " 240790  3.844344 -14.526400          260            0.000147         3.634193\n",
+       " 240791  3.846046 -14.526503          260            0.000138         3.634193\n",
+       " 240792  3.847748 -14.526607          260            0.000128         3.634193\n",
+       " \n",
+       " [675 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 241118  2.700801 -14.519636          261            3.620385         3.627251\n",
+       " 241119  2.702502 -14.519780          261            3.618130         3.627251\n",
+       " 241120  2.704204 -14.519924          261            3.615874         3.627251\n",
+       " 241121  2.705906 -14.520048          261            3.613598         3.627251\n",
+       " 241122  2.707608 -14.520123          261            3.611270         3.627251\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 241788  3.840941 -14.526423          261            0.000165         3.627251\n",
+       " 241789  3.842643 -14.526529          261            0.000156         3.627251\n",
+       " 241790  3.844344 -14.526637          261            0.000146         3.627251\n",
+       " 241791  3.846046 -14.526745          261            0.000136         3.627251\n",
+       " 241792  3.847748 -14.526853          261            0.000126         3.627251\n",
+       " \n",
+       " [675 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 242118  2.700801 -14.520156          262            3.614655         3.622643\n",
+       " 242119  2.702502 -14.520432          262            3.612394         3.622643\n",
+       " 242120  2.704204 -14.520301          262            3.610072         3.622643\n",
+       " 242121  2.705906 -14.520072          262            3.607736         3.622643\n",
+       " 242122  2.707608 -14.519843          262            3.605399         3.622643\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 242788  3.840941 -14.525860          262            0.000162         3.622643\n",
+       " 242789  3.842643 -14.525946          262            0.000152         3.622643\n",
+       " 242790  3.844344 -14.526032          262            0.000142         3.622643\n",
+       " 242791  3.846046 -14.526118          262            0.000132         3.622643\n",
+       " 242792  3.847748 -14.526205          262            0.000123         3.622643\n",
+       " \n",
+       " [675 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 243118  2.700801 -14.519838          263            3.612954         3.618562\n",
+       " 243119  2.702502 -14.519923          263            3.610765         3.618562\n",
+       " 243120  2.704204 -14.520008          263            3.608576         3.618562\n",
+       " 243121  2.705906 -14.520027          263            3.606356         3.618562\n",
+       " 243122  2.707608 -14.520027          263            3.604126         3.618562\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 243788  3.840941 -14.523873          263            0.000163         3.618562\n",
+       " 243789  3.842643 -14.523939          263            0.000153         3.618562\n",
+       " 243790  3.844344 -14.524005          263            0.000144         3.618562\n",
+       " 243791  3.846046 -14.524071          263            0.000134         3.618562\n",
+       " 243792  3.847748 -14.524137          263            0.000124         3.618562\n",
+       " \n",
+       " [675 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 244118  2.700801 -14.519150          264            3.608336         3.614838\n",
+       " 244119  2.702502 -14.519403          264            3.606035         3.614838\n",
+       " 244120  2.704204 -14.519704          264            3.603720         3.614838\n",
+       " 244121  2.705906 -14.520004          264            3.601405         3.614838\n",
+       " 244122  2.707608 -14.520095          264            3.599234         3.614838\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 244787  3.839239 -14.526811          264            0.000169         3.614838\n",
+       " 244788  3.840941 -14.526924          264            0.000159         3.614838\n",
+       " 244789  3.842643 -14.527038          264            0.000149         3.614838\n",
+       " 244790  3.844344 -14.527152          264            0.000140         3.614838\n",
+       " 244791  3.846046 -14.527266          264            0.000130         3.614838\n",
+       " \n",
+       " [674 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 245118  2.700801 -14.520012          265            3.604465         3.612528\n",
+       " 245119  2.702502 -14.519866          265            3.602293         3.612528\n",
+       " 245120  2.704204 -14.519720          265            3.600121         3.612528\n",
+       " 245121  2.705906 -14.519574          265            3.597949         3.612528\n",
+       " 245122  2.707608 -14.519788          265            3.595638         3.612528\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 245787  3.839239 -14.524748          265            0.000167         3.612528\n",
+       " 245788  3.840941 -14.524817          265            0.000157         3.612528\n",
+       " 245789  3.842643 -14.524885          265            0.000147         3.612528\n",
+       " 245790  3.844344 -14.524954          265            0.000138         3.612528\n",
+       " 245791  3.846046 -14.525023          265            0.000128         3.612528\n",
+       " \n",
+       " [674 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 246118  2.700801 -14.520222          266            3.600769         3.605012\n",
+       " 246119  2.702502 -14.520147          266            3.598657         3.605012\n",
+       " 246120  2.704204 -14.520074          266            3.596545         3.605012\n",
+       " 246121  2.705906 -14.520027          266            3.594411         3.605012\n",
+       " 246122  2.707608 -14.520027          266            3.592242         3.605012\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 246787  3.839239 -14.526495          266            0.000163         3.605012\n",
+       " 246788  3.840941 -14.526592          266            0.000153         3.605012\n",
+       " 246789  3.842643 -14.526689          266            0.000143         3.605012\n",
+       " 246790  3.844344 -14.526785          266            0.000133         3.605012\n",
+       " 246791  3.846046 -14.526881          266            0.000124         3.605012\n",
+       " \n",
+       " [674 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 247118  2.700801 -14.519768          267            3.595820          3.60413\n",
+       " 247119  2.702502 -14.520193          267            3.593646          3.60413\n",
+       " 247120  2.704204 -14.520618          267            3.591472          3.60413\n",
+       " 247121  2.705906 -14.520541          267            3.589265          3.60413\n",
+       " 247122  2.707608 -14.520320          267            3.587048          3.60413\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 247786  3.837538 -14.526612          267            0.000170          3.60413\n",
+       " 247787  3.839239 -14.526715          267            0.000161          3.60413\n",
+       " 247788  3.840941 -14.526818          267            0.000151          3.60413\n",
+       " 247789  3.842643 -14.526921          267            0.000141          3.60413\n",
+       " 247790  3.844344 -14.527024          267            0.000132          3.60413\n",
+       " \n",
+       " [673 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 248118  2.700801 -14.520090          268            3.592914         3.600248\n",
+       " 248119  2.702502 -14.520225          268            3.590736         3.600248\n",
+       " 248120  2.704204 -14.520144          268            3.588588         3.600248\n",
+       " 248121  2.705906 -14.519996          268            3.586450         3.600248\n",
+       " 248122  2.707608 -14.519847          268            3.584312         3.600248\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 248786  3.837538 -14.524694          268            0.000170         3.600248\n",
+       " 248787  3.839239 -14.524770          268            0.000160         3.600248\n",
+       " 248788  3.840941 -14.524846          268            0.000150         3.600248\n",
+       " 248789  3.842643 -14.524921          268            0.000141         3.600248\n",
+       " 248790  3.844344 -14.524998          268            0.000131         3.600248\n",
+       " \n",
+       " [673 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 249118  2.700801 -14.520027          269            3.591424         3.594679\n",
+       " 249119  2.702502 -14.520027          269            3.589338         3.594679\n",
+       " 249120  2.704204 -14.520054          269            3.587209         3.594679\n",
+       " 249121  2.705906 -14.520127          269            3.585006         3.594679\n",
+       " 249122  2.707608 -14.520202          269            3.582803         3.594679\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 249778  3.823924 -14.520220          269            0.000214         3.594679\n",
+       " 249779  3.825626 -14.520227          269            0.000203         3.594679\n",
+       " 249780  3.827327 -14.520235          269            0.000193         3.594679\n",
+       " 249781  3.829029 -14.520243          269            0.000182         3.594679\n",
+       " 249782  3.830731 -14.520249          269            0.000172         3.594679\n",
+       " \n",
+       " [665 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 250118  2.700801 -14.519851          270            3.589535         3.596118\n",
+       " 250119  2.702502 -14.520070          270            3.587376         3.596118\n",
+       " 250120  2.704204 -14.520288          270            3.585217         3.596118\n",
+       " 250121  2.705906 -14.520455          270            3.583071         3.596118\n",
+       " 250122  2.707608 -14.520172          270            3.581048         3.596118\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 250786  3.837538 -14.523403          270            0.000167         3.596118\n",
+       " 250787  3.839239 -14.523464          270            0.000158         3.596118\n",
+       " 250788  3.840941 -14.523526          270            0.000148         3.596118\n",
+       " 250789  3.842643 -14.523588          270            0.000138         3.596118\n",
+       " 250790  3.844344 -14.523650          270            0.000129         3.596118\n",
+       " \n",
+       " [673 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 251118  2.700801 -14.519820          271            3.584810         3.590554\n",
+       " 251119  2.702502 -14.519966          271            3.582663         3.590554\n",
+       " 251120  2.704204 -14.520112          271            3.580517         3.590554\n",
+       " 251121  2.705906 -14.520253          271            3.578371         3.590554\n",
+       " 251122  2.707608 -14.520034          271            3.576225         3.590554\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 251787  3.839239 -14.524920          271            0.000163         3.590554\n",
+       " 251788  3.840941 -14.525010          271            0.000153         3.590554\n",
+       " 251789  3.842643 -14.525100          271            0.000143         3.590554\n",
+       " 251790  3.844344 -14.525189          271            0.000134         3.590554\n",
+       " 251791  3.846046 -14.525280          271            0.000124         3.590554\n",
+       " \n",
+       " [674 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 252118  2.700801 -14.519936          272            3.580668         3.587709\n",
+       " 252119  2.702502 -14.519820          272            3.578540         3.587709\n",
+       " 252120  2.704204 -14.519895          272            3.576454         3.587709\n",
+       " 252121  2.705906 -14.519968          272            3.574368         3.587709\n",
+       " 252122  2.707608 -14.520012          272            3.572266         3.587709\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 252786  3.837538 -14.524958          272            0.000163         3.587709\n",
+       " 252787  3.839239 -14.525037          272            0.000154         3.587709\n",
+       " 252788  3.840941 -14.525116          272            0.000144         3.587709\n",
+       " 252789  3.842643 -14.525194          272            0.000134         3.587709\n",
+       " 252790  3.844344 -14.525273          272            0.000125         3.587709\n",
+       " \n",
+       " [673 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 253118  2.700801 -14.519798          273            3.586050         3.591092\n",
+       " 253119  2.702502 -14.519798          273            3.584030         3.591092\n",
+       " 253120  2.704204 -14.519798          273            3.582010         3.591092\n",
+       " 253121  2.705906 -14.519931          273            3.579863         3.591092\n",
+       " 253122  2.707608 -14.520077          273            3.577704         3.591092\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 253779  3.825626 -14.520913          273            0.000205         3.591092\n",
+       " 253780  3.827327 -14.520920          273            0.000194         3.591092\n",
+       " 253781  3.829029 -14.520927          273            0.000184         3.591092\n",
+       " 253782  3.830731 -14.520935          273            0.000173         3.591092\n",
+       " 253783  3.832433 -14.520943          273            0.000163         3.591092\n",
+       " \n",
+       " [666 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 254118  2.700801 -14.520275          274            3.578543         3.582055\n",
+       " 254119  2.702502 -14.519825          274            3.576427         3.582055\n",
+       " 254120  2.704204 -14.519868          274            3.574425         3.582055\n",
+       " 254121  2.705906 -14.519942          274            3.572430         3.582055\n",
+       " 254122  2.707608 -14.520016          274            3.570435         3.582055\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 254787  3.839239 -14.526032          274            0.000163         3.582055\n",
+       " 254788  3.840941 -14.526129          274            0.000153         3.582055\n",
+       " 254789  3.842643 -14.526226          274            0.000144         3.582055\n",
+       " 254790  3.844344 -14.526322          274            0.000134         3.582055\n",
+       " 254791  3.846046 -14.526419          274            0.000124         3.582055\n",
+       " \n",
+       " [674 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 255118  2.700801 -14.520188          275            3.575264         3.581131\n",
+       " 255119  2.702502 -14.520042          275            3.573208         3.581131\n",
+       " 255120  2.704204 -14.519897          275            3.571152         3.581131\n",
+       " 255121  2.705906 -14.519846          275            3.569096         3.581131\n",
+       " 255122  2.707608 -14.519992          275            3.567039         3.581131\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 255786  3.837538 -14.526669          275            0.000164         3.581131\n",
+       " 255787  3.839239 -14.526774          275            0.000154         3.581131\n",
+       " 255788  3.840941 -14.526880          275            0.000144         3.581131\n",
+       " 255789  3.842643 -14.526987          275            0.000135         3.581131\n",
+       " 255790  3.844344 -14.527093          275            0.000125         3.581131\n",
+       " \n",
+       " [673 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 256118  2.700801 -14.520256          276            3.572130         3.578833\n",
+       " 256119  2.702502 -14.520256          276            3.570098         3.578833\n",
+       " 256120  2.704204 -14.520256          276            3.568066         3.578833\n",
+       " 256121  2.705906 -14.520128          276            3.565953         3.578833\n",
+       " 256122  2.707608 -14.519980          276            3.563828         3.578833\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 256785  3.835836 -14.525774          276            0.000169         3.578833\n",
+       " 256786  3.837538 -14.525863          276            0.000160         3.578833\n",
+       " 256787  3.839239 -14.525951          276            0.000150         3.578833\n",
+       " 256788  3.840941 -14.526040          276            0.000141         3.578833\n",
+       " 256789  3.842643 -14.526130          276            0.000131         3.578833\n",
+       " \n",
+       " [672 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 257118  2.700801 -14.519798          277            3.569736         3.573081\n",
+       " 257119  2.702502 -14.519798          277            3.567663         3.573081\n",
+       " 257120  2.704204 -14.519798          277            3.565590         3.573081\n",
+       " 257121  2.705906 -14.519794          277            3.563515         3.573081\n",
+       " 257122  2.707608 -14.519717          277            3.561407         3.573081\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 257786  3.837538 -14.525161          277            0.000165         3.573081\n",
+       " 257787  3.839239 -14.525243          277            0.000155         3.573081\n",
+       " 257788  3.840941 -14.525326          277            0.000145         3.573081\n",
+       " 257789  3.842643 -14.525408          277            0.000136         3.573081\n",
+       " 257790  3.844344 -14.525490          277            0.000126         3.573081\n",
+       " \n",
+       " [673 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 258118  2.700801 -14.520027          278            3.566553         3.572336\n",
+       " 258119  2.702502 -14.520098          278            3.564489         3.572336\n",
+       " 258120  2.704204 -14.520171          278            3.562420         3.572336\n",
+       " 258121  2.705906 -14.520244          278            3.560351         3.572336\n",
+       " 258122  2.707608 -14.520134          278            3.558293         3.572336\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 258785  3.835836 -14.525135          278            0.000168         3.572336\n",
+       " 258786  3.837538 -14.525217          278            0.000158         3.572336\n",
+       " 258787  3.839239 -14.525299          278            0.000148         3.572336\n",
+       " 258788  3.840941 -14.525381          278            0.000139         3.572336\n",
+       " 258789  3.842643 -14.525463          278            0.000129         3.572336\n",
+       " \n",
+       " [672 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 259118  2.700801 -14.519976          279            3.567894         3.572578\n",
+       " 259119  2.702502 -14.519864          279            3.565860         3.572578\n",
+       " 259120  2.704204 -14.519855          279            3.563810         3.572578\n",
+       " 259121  2.705906 -14.519998          279            3.561736         3.572578\n",
+       " 259122  2.707608 -14.520139          279            3.559662         3.572578\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 259785  3.835836 -14.524661          279            0.000170         3.572578\n",
+       " 259786  3.837538 -14.524743          279            0.000160         3.572578\n",
+       " 259787  3.839239 -14.524824          279            0.000150         3.572578\n",
+       " 259788  3.840941 -14.524906          279            0.000141         3.572578\n",
+       " 259789  3.842643 -14.524987          279            0.000131         3.572578\n",
+       " \n",
+       " [672 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 260118  2.700801 -14.520393          280            3.564244         3.567142\n",
+       " 260119  2.702502 -14.520288          280            3.562292         3.567142\n",
+       " 260120  2.704204 -14.520067          280            3.560310         3.567142\n",
+       " 260121  2.705906 -14.519845          280            3.558328         3.567142\n",
+       " 260122  2.707608 -14.519798          280            3.556240         3.567142\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 260785  3.835836 -14.525781          280            0.000169         3.567142\n",
+       " 260786  3.837538 -14.525869          280            0.000159         3.567142\n",
+       " 260787  3.839239 -14.525959          280            0.000149         3.567142\n",
+       " 260788  3.840941 -14.526048          280            0.000140         3.567142\n",
+       " 260789  3.842643 -14.526137          280            0.000130         3.567142\n",
+       " \n",
+       " [672 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 261118  2.700801 -14.519897          281            3.560996         3.566892\n",
+       " 261119  2.702502 -14.520027          281            3.559007         3.566892\n",
+       " 261120  2.704204 -14.520027          281            3.556957         3.566892\n",
+       " 261121  2.705906 -14.520027          281            3.554906         3.566892\n",
+       " 261122  2.707608 -14.520002          281            3.552842         3.566892\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 261785  3.835836 -14.526025          281            0.000164         3.566892\n",
+       " 261786  3.837538 -14.526119          281            0.000154         3.566892\n",
+       " 261787  3.839239 -14.526215          281            0.000145         3.566892\n",
+       " 261788  3.840941 -14.526309          281            0.000135         3.566892\n",
+       " 261789  3.842643 -14.526404          281            0.000126         3.566892\n",
+       " \n",
+       " [672 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 262118  2.700801 -14.519739          282            3.560150         3.565875\n",
+       " 262119  2.702502 -14.520012          282            3.558059         3.565875\n",
+       " 262120  2.704204 -14.519940          282            3.556083         3.565875\n",
+       " 262121  2.705906 -14.519868          282            3.554106         3.565875\n",
+       " 262122  2.707608 -14.519798          282            3.552126         3.565875\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 262785  3.835836 -14.526444          282            0.000166         3.565875\n",
+       " 262786  3.837538 -14.526543          282            0.000157         3.565875\n",
+       " 262787  3.839239 -14.526642          282            0.000147         3.565875\n",
+       " 262788  3.840941 -14.526740          282            0.000137         3.565875\n",
+       " 262789  3.842643 -14.526838          282            0.000128         3.565875\n",
+       " \n",
+       " [672 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 263118  2.700801 -14.520256          283            3.555849         3.560951\n",
+       " 263119  2.702502 -14.520226          283            3.553792         3.560951\n",
+       " 263120  2.704204 -14.520082          283            3.551854         3.560951\n",
+       " 263121  2.705906 -14.519938          283            3.549915         3.560951\n",
+       " 263122  2.707608 -14.519798          283            3.547974         3.560951\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 263785  3.835836 -14.523852          283            0.000166         3.560951\n",
+       " 263786  3.837538 -14.523917          283            0.000157         3.560951\n",
+       " 263787  3.839239 -14.523982          283            0.000147         3.560951\n",
+       " 263788  3.840941 -14.524046          283            0.000137         3.560951\n",
+       " 263789  3.842643 -14.524111          283            0.000128         3.560951\n",
+       " \n",
+       " [672 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 264118  2.700801 -14.519955          284            3.552480         3.557213\n",
+       " 264119  2.702502 -14.519800          284            3.550517         3.557213\n",
+       " 264120  2.704204 -14.519872          284            3.548509         3.557213\n",
+       " 264121  2.705906 -14.519945          284            3.546502         3.557213\n",
+       " 264122  2.707608 -14.520020          284            3.544494         3.557213\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 264777  3.822222 -14.521753          284            0.000212         3.557213\n",
+       " 264778  3.823924 -14.521775          284            0.000202         3.557213\n",
+       " 264779  3.825626 -14.521797          284            0.000192         3.557213\n",
+       " 264780  3.827327 -14.521819          284            0.000181         3.557213\n",
+       " 264781  3.829029 -14.521841          284            0.000171         3.557213\n",
+       " \n",
+       " [664 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 265118  2.700801 -14.519615          285            3.554508         3.557525\n",
+       " 265119  2.702502 -14.520071          285            3.552573         3.557525\n",
+       " 265120  2.704204 -14.520217          285            3.550645         3.557525\n",
+       " 265121  2.705906 -14.520363          285            3.548717         3.557525\n",
+       " 265122  2.707608 -14.520449          285            3.546764         3.557525\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 265785  3.835836 -14.526876          285            0.000164         3.557525\n",
+       " 265786  3.837538 -14.526985          285            0.000155         3.557525\n",
+       " 265787  3.839239 -14.527093          285            0.000145         3.557525\n",
+       " 265788  3.840941 -14.527202          285            0.000136         3.557525\n",
+       " 265789  3.842643 -14.527310          285            0.000126         3.557525\n",
+       " \n",
+       " [672 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 266118  2.700801 -14.520019          286            3.550439         3.556202\n",
+       " 266119  2.702502 -14.519837          286            3.548529         3.556202\n",
+       " 266120  2.704204 -14.519911          286            3.546482         3.556202\n",
+       " 266121  2.705906 -14.519985          286            3.544435         3.556202\n",
+       " 266122  2.707608 -14.520027          286            3.542400         3.556202\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 266785  3.835836 -14.526032          286            0.000163         3.556202\n",
+       " 266786  3.837538 -14.526128          286            0.000154         3.556202\n",
+       " 266787  3.839239 -14.526222          286            0.000144         3.556202\n",
+       " 266788  3.840941 -14.526318          286            0.000134         3.556202\n",
+       " 266789  3.842643 -14.526413          286            0.000125         3.556202\n",
+       " \n",
+       " [672 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 267118  2.700801 -14.520202          287            3.548921         3.551498\n",
+       " 267119  2.702502 -14.520086          287            3.546937         3.551498\n",
+       " 267120  2.704204 -14.520099          287            3.544975         3.551498\n",
+       " 267121  2.705906 -14.520245          287            3.543035         3.551498\n",
+       " 267122  2.707608 -14.520391          287            3.541094         3.551498\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 267776  3.820521 -14.520839          287            0.000212         3.551498\n",
+       " 267777  3.822222 -14.520861          287            0.000201         3.551498\n",
+       " 267778  3.823924 -14.520883          287            0.000191         3.551498\n",
+       " 267779  3.825626 -14.520905          287            0.000181         3.551498\n",
+       " 267780  3.827327 -14.520926          287            0.000170         3.551498\n",
+       " \n",
+       " [663 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 268118  2.700801 -14.519735          288            3.544489         3.551843\n",
+       " 268119  2.702502 -14.519601          288            3.542690         3.551843\n",
+       " 268120  2.704204 -14.519626          288            3.540761         3.551843\n",
+       " 268121  2.705906 -14.519700          288            3.538793         3.551843\n",
+       " 268122  2.707608 -14.519773          288            3.536824         3.551843\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 268776  3.820521 -14.521482          288            0.000209         3.551843\n",
+       " 268777  3.822222 -14.521515          288            0.000199         3.551843\n",
+       " 268778  3.823924 -14.521548          288            0.000188         3.551843\n",
+       " 268779  3.825626 -14.521582          288            0.000178         3.551843\n",
+       " 268780  3.827327 -14.521614          288            0.000168         3.551843\n",
+       " \n",
+       " [663 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 269118  2.700801 -14.519365          289            3.544240          3.54981\n",
+       " 269119  2.702502 -14.519439          289            3.542297          3.54981\n",
+       " 269120  2.704204 -14.519513          289            3.540354          3.54981\n",
+       " 269121  2.705906 -14.519587          289            3.538406          3.54981\n",
+       " 269122  2.707608 -14.519661          289            3.536437          3.54981\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 269785  3.835836 -14.525834          289            0.000163          3.54981\n",
+       " 269786  3.837538 -14.525922          289            0.000153          3.54981\n",
+       " 269787  3.839239 -14.526010          289            0.000144          3.54981\n",
+       " 269788  3.840941 -14.526097          289            0.000134          3.54981\n",
+       " 269789  3.842643 -14.526185          289            0.000125          3.54981\n",
+       " \n",
+       " [672 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 270118  2.700801 -14.519910          290            3.541288          3.54522\n",
+       " 270119  2.702502 -14.519659          290            3.539371          3.54522\n",
+       " 270120  2.704204 -14.519408          290            3.537453          3.54522\n",
+       " 270121  2.705906 -14.519498          290            3.535484          3.54522\n",
+       " 270122  2.707608 -14.519714          290            3.533494          3.54522\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 270785  3.835836 -14.525151          290            0.000164          3.54522\n",
+       " 270786  3.837538 -14.525236          290            0.000155          3.54522\n",
+       " 270787  3.839239 -14.525321          290            0.000145          3.54522\n",
+       " 270788  3.840941 -14.525407          290            0.000135          3.54522\n",
+       " 270789  3.842643 -14.525492          290            0.000126          3.54522\n",
+       " \n",
+       " [672 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 271118  2.700801 -14.520153          291            3.540361         3.544682\n",
+       " 271119  2.702502 -14.519931          291            3.538444         3.544682\n",
+       " 271120  2.704204 -14.519887          291            3.536507         3.544682\n",
+       " 271121  2.705906 -14.520105          291            3.534541         3.544682\n",
+       " 271122  2.707608 -14.520324          291            3.532575         3.544682\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 271784  3.834134 -14.525526          291            0.000166         3.544682\n",
+       " 271785  3.835836 -14.525624          291            0.000157         3.544682\n",
+       " 271786  3.837538 -14.525723          291            0.000147         3.544682\n",
+       " 271787  3.839239 -14.525820          291            0.000138         3.544682\n",
+       " 271788  3.840941 -14.525918          291            0.000128         3.544682\n",
+       " \n",
+       " [671 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 272118  2.700801 -14.519834          292            3.538020         3.544548\n",
+       " 272119  2.702502 -14.519908          292            3.536102         3.544548\n",
+       " 272120  2.704204 -14.519983          292            3.534184         3.544548\n",
+       " 272121  2.705906 -14.519965          292            3.532239         3.544548\n",
+       " 272122  2.707608 -14.519817          292            3.530257         3.544548\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 272784  3.834134 -14.526011          292            0.000167         3.544548\n",
+       " 272785  3.835836 -14.526100          292            0.000158         3.544548\n",
+       " 272786  3.837538 -14.526191          292            0.000148         3.544548\n",
+       " 272787  3.839239 -14.526281          292            0.000139         3.544548\n",
+       " 272788  3.840941 -14.526372          292            0.000129         3.544548\n",
+       " \n",
+       " [671 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 273118  2.700801 -14.519798          293            3.535906         3.540164\n",
+       " 273119  2.702502 -14.519798          293            3.534038         3.540164\n",
+       " 273120  2.704204 -14.519798          293            3.532144         3.540164\n",
+       " 273121  2.705906 -14.519798          293            3.530241         3.540164\n",
+       " 273122  2.707608 -14.519798          293            3.528337         3.540164\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 273784  3.834134 -14.525755          293            0.000166         3.540164\n",
+       " 273785  3.835836 -14.525852          293            0.000157         3.540164\n",
+       " 273786  3.837538 -14.525950          293            0.000147         3.540164\n",
+       " 273787  3.839239 -14.526049          293            0.000138         3.540164\n",
+       " 273788  3.840941 -14.526146          293            0.000128         3.540164\n",
+       " \n",
+       " [671 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 274118  2.700801 -14.520027          294            3.533901         3.537502\n",
+       " 274119  2.702502 -14.520027          294            3.532059         3.537502\n",
+       " 274120  2.704204 -14.520027          294            3.530216         3.537502\n",
+       " 274121  2.705906 -14.520027          294            3.528285         3.537502\n",
+       " 274122  2.707608 -14.520027          294            3.526314         3.537502\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 274776  3.820521 -14.519587          294            0.000211         3.537502\n",
+       " 274777  3.822222 -14.519583          294            0.000201         3.537502\n",
+       " 274778  3.823924 -14.519579          294            0.000191         3.537502\n",
+       " 274779  3.825626 -14.519575          294            0.000180         3.537502\n",
+       " 274780  3.827327 -14.519572          294            0.000170         3.537502\n",
+       " \n",
+       " [663 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 275118  2.700801 -14.520005          295            3.531183         3.536659\n",
+       " 275119  2.702502 -14.520256          295            3.529276         3.536659\n",
+       " 275120  2.704204 -14.520256          295            3.527331         3.536659\n",
+       " 275121  2.705906 -14.520256          295            3.525387         3.536659\n",
+       " 275122  2.707608 -14.520227          295            3.523433         3.536659\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 275776  3.820521 -14.521070          295            0.000210         3.536659\n",
+       " 275777  3.822222 -14.521092          295            0.000200         3.536659\n",
+       " 275778  3.823924 -14.521114          295            0.000190         3.536659\n",
+       " 275779  3.825626 -14.521136          295            0.000179         3.536659\n",
+       " 275780  3.827327 -14.521158          295            0.000169         3.536659\n",
+       " \n",
+       " [663 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 276118  2.700801 -14.519614          296            3.532463         3.536982\n",
+       " 276119  2.702502 -14.519711          296            3.530561         3.536982\n",
+       " 276120  2.704204 -14.519798          296            3.528651         3.536982\n",
+       " 276121  2.705906 -14.519798          296            3.526643         3.536982\n",
+       " 276122  2.707608 -14.519798          296            3.524635         3.536982\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 276785  3.835836 -14.524136          296            0.000162         3.536982\n",
+       " 276786  3.837538 -14.524193          296            0.000153         3.536982\n",
+       " 276787  3.839239 -14.524250          296            0.000143         3.536982\n",
+       " 276788  3.840941 -14.524307          296            0.000134         3.536982\n",
+       " 276789  3.842643 -14.524364          296            0.000124         3.536982\n",
+       " \n",
+       " [672 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 277118  2.700801 -14.519514          297            3.530687         3.534981\n",
+       " 277119  2.702502 -14.519395          297            3.528783         3.534981\n",
+       " 277120  2.704204 -14.519457          297            3.526867         3.534981\n",
+       " 277121  2.705906 -14.519672          297            3.524941         3.534981\n",
+       " 277122  2.707608 -14.519888          297            3.523015         3.534981\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 277785  3.835836 -14.526478          297            0.000163         3.534981\n",
+       " 277786  3.837538 -14.526576          297            0.000153         3.534981\n",
+       " 277787  3.839239 -14.526674          297            0.000144         3.534981\n",
+       " 277788  3.840941 -14.526772          297            0.000134         3.534981\n",
+       " 277789  3.842643 -14.526870          297            0.000125         3.534981\n",
+       " \n",
+       " [672 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 278118  2.700801 -14.519569          298            3.525893         3.531748\n",
+       " 278119  2.702502 -14.519569          298            3.523965         3.531748\n",
+       " 278120  2.704204 -14.519569          298            3.522038         3.531748\n",
+       " 278121  2.705906 -14.519611          298            3.520110         3.531748\n",
+       " 278122  2.707608 -14.519831          298            3.518182         3.531748\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 278784  3.834134 -14.526237          298            0.000163         3.531748\n",
+       " 278785  3.835836 -14.526338          298            0.000153         3.531748\n",
+       " 278786  3.837538 -14.526438          298            0.000144         3.531748\n",
+       " 278787  3.839239 -14.526538          298            0.000134         3.531748\n",
+       " 278788  3.840941 -14.526639          298            0.000125         3.531748\n",
+       " \n",
+       " [671 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 279118  2.700801 -14.519930          299            3.522658         3.528959\n",
+       " 279119  2.702502 -14.519722          299            3.520748         3.528959\n",
+       " 279120  2.704204 -14.519608          299            3.518824         3.528959\n",
+       " 279121  2.705906 -14.519754          299            3.516857         3.528959\n",
+       " 279122  2.707608 -14.519900          299            3.514891         3.528959\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 279775  3.818819 -14.520623          299            0.000214         3.528959\n",
+       " 279776  3.820521 -14.520641          299            0.000203         3.528959\n",
+       " 279777  3.822222 -14.520659          299            0.000193         3.528959\n",
+       " 279778  3.823924 -14.520679          299            0.000183         3.528959\n",
+       " 279779  3.825626 -14.520697          299            0.000173         3.528959\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 280118  2.700801 -14.520016          300            3.520142         3.524802\n",
+       " 280119  2.702502 -14.519940          300            3.518171         3.524802\n",
+       " 280120  2.704204 -14.519866          300            3.516200         3.524802\n",
+       " 280121  2.705906 -14.519806          300            3.514231         3.524802\n",
+       " 280122  2.707608 -14.519878          300            3.512291         3.524802\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 280783  3.832433 -14.525960          300            0.000169         3.524802\n",
+       " 280784  3.834134 -14.526057          300            0.000159         3.524802\n",
+       " 280785  3.835836 -14.526155          300            0.000150         3.524802\n",
+       " 280786  3.837538 -14.526251          300            0.000140         3.524802\n",
+       " 280787  3.839239 -14.526348          300            0.000131         3.524802\n",
+       " \n",
+       " [670 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 281118  2.700801 -14.519381          301            3.522012         3.524746\n",
+       " 281119  2.702502 -14.519756          301            3.520107         3.524746\n",
+       " 281120  2.704204 -14.520131          301            3.518202         3.524746\n",
+       " 281121  2.705906 -14.520476          301            3.516295         3.524746\n",
+       " 281122  2.707608 -14.520326          301            3.514364         3.524746\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 281784  3.834134 -14.525841          301            0.000162         3.524746\n",
+       " 281785  3.835836 -14.525928          301            0.000153         3.524746\n",
+       " 281786  3.837538 -14.526014          301            0.000143         3.524746\n",
+       " 281787  3.839239 -14.526101          301            0.000134         3.524746\n",
+       " 281788  3.840941 -14.526188          301            0.000124         3.524746\n",
+       " \n",
+       " [671 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 282118  2.700801 -14.520018          302            3.520525          3.52495\n",
+       " 282119  2.702502 -14.519870          302            3.518621          3.52495\n",
+       " 282120  2.704204 -14.519722          302            3.516717          3.52495\n",
+       " 282121  2.705906 -14.519574          302            3.514814          3.52495\n",
+       " 282122  2.707608 -14.519499          302            3.512949          3.52495\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 282785  3.835836 -14.526256          302            0.000164          3.52495\n",
+       " 282786  3.837538 -14.526349          302            0.000154          3.52495\n",
+       " 282787  3.839239 -14.526443          302            0.000145          3.52495\n",
+       " 282788  3.840941 -14.526536          302            0.000135          3.52495\n",
+       " 282789  3.842643 -14.526629          302            0.000126          3.52495\n",
+       " \n",
+       " [672 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 283118  2.700801 -14.520096          303            3.519386         3.523405\n",
+       " 283119  2.702502 -14.520201          303            3.517575         3.523405\n",
+       " 283120  2.704204 -14.520126          303            3.515684         3.523405\n",
+       " 283121  2.705906 -14.520053          303            3.513793         3.523405\n",
+       " 283122  2.707608 -14.520076          303            3.511920         3.523405\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 283784  3.834134 -14.526818          303            0.000168         3.523405\n",
+       " 283785  3.835836 -14.526928          303            0.000159         3.523405\n",
+       " 283786  3.837538 -14.527039          303            0.000149         3.523405\n",
+       " 283787  3.839239 -14.527148          303            0.000140         3.523405\n",
+       " 283788  3.840941 -14.527259          303            0.000130         3.523405\n",
+       " \n",
+       " [671 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 284118  2.700801 -14.520071          304            3.517636         3.522604\n",
+       " 284119  2.702502 -14.520165          304            3.515770         3.522604\n",
+       " 284120  2.704204 -14.520249          304            3.513903         3.522604\n",
+       " 284121  2.705906 -14.520103          304            3.512001         3.522604\n",
+       " 284122  2.707608 -14.519958          304            3.510099         3.522604\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 284784  3.834134 -14.526634          304            0.000166         3.522604\n",
+       " 284785  3.835836 -14.526741          304            0.000156         3.522604\n",
+       " 284786  3.837538 -14.526848          304            0.000147         3.522604\n",
+       " 284787  3.839239 -14.526955          304            0.000137         3.522604\n",
+       " 284788  3.840941 -14.527061          304            0.000128         3.522604\n",
+       " \n",
+       " [671 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 285118  2.700801 -14.519977          305            3.513858         3.518498\n",
+       " 285119  2.702502 -14.519868          305            3.512021         3.518498\n",
+       " 285120  2.704204 -14.519850          305            3.510170         3.518498\n",
+       " 285121  2.705906 -14.519994          305            3.508295         3.518498\n",
+       " 285122  2.707608 -14.520138          305            3.506419         3.518498\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 285776  3.820521 -14.521094          305            0.000207         3.518498\n",
+       " 285777  3.822222 -14.521112          305            0.000196         3.518498\n",
+       " 285778  3.823924 -14.521131          305            0.000186         3.518498\n",
+       " 285779  3.825626 -14.521149          305            0.000176         3.518498\n",
+       " 285780  3.827327 -14.521167          305            0.000166         3.518498\n",
+       " \n",
+       " [663 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 286118  2.700801 -14.520454          306            3.510512          3.51615\n",
+       " 286119  2.702502 -14.520383          306            3.508675          3.51615\n",
+       " 286120  2.704204 -14.520310          306            3.506838          3.51615\n",
+       " 286121  2.705906 -14.520239          306            3.504988          3.51615\n",
+       " 286122  2.707608 -14.520164          306            3.503098          3.51615\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 286775  3.818819 -14.520185          306            0.000213          3.51615\n",
+       " 286776  3.820521 -14.520200          306            0.000202          3.51615\n",
+       " 286777  3.822222 -14.520214          306            0.000192          3.51615\n",
+       " 286778  3.823924 -14.520229          306            0.000182          3.51615\n",
+       " 286779  3.825626 -14.520244          306            0.000172          3.51615\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 287118  2.700801 -14.519834          307            3.510451         3.514235\n",
+       " 287119  2.702502 -14.520200          307            3.508507         3.514235\n",
+       " 287120  2.704204 -14.519978          307            3.506630         3.514235\n",
+       " 287121  2.705906 -14.519755          307            3.504753         3.514235\n",
+       " 287122  2.707608 -14.519605          307            3.502867         3.514235\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 287783  3.832433 -14.526796          307            0.000168         3.514235\n",
+       " 287784  3.834134 -14.526910          307            0.000159         3.514235\n",
+       " 287785  3.835836 -14.527023          307            0.000150         3.514235\n",
+       " 287786  3.837538 -14.527136          307            0.000140         3.514235\n",
+       " 287787  3.839239 -14.527249          307            0.000131         3.514235\n",
+       " \n",
+       " [670 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 288118  2.700801 -14.519881          308            3.508820         3.512522\n",
+       " 288119  2.702502 -14.519569          308            3.507076         3.512522\n",
+       " 288120  2.704204 -14.519419          308            3.505292         3.512522\n",
+       " 288121  2.705906 -14.519711          308            3.503403         3.512522\n",
+       " 288122  2.707608 -14.520002          308            3.501514         3.512522\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 288783  3.832433 -14.525590          308            0.000168         3.512522\n",
+       " 288784  3.834134 -14.525670          308            0.000159         3.512522\n",
+       " 288785  3.835836 -14.525750          308            0.000149         3.512522\n",
+       " 288786  3.837538 -14.525830          308            0.000140         3.512522\n",
+       " 288787  3.839239 -14.525909          308            0.000131         3.512522\n",
+       " \n",
+       " [670 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 289118  2.700801 -14.519590          309            3.503962         3.511491\n",
+       " 289119  2.702502 -14.519662          309            3.502048         3.511491\n",
+       " 289120  2.704204 -14.519733          309            3.500135         3.511491\n",
+       " 289121  2.705906 -14.519806          309            3.498220         3.511491\n",
+       " 289122  2.707608 -14.519878          309            3.496293         3.511491\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 289783  3.832433 -14.526062          309            0.000161         3.511491\n",
+       " 289784  3.834134 -14.526152          309            0.000152         3.511491\n",
+       " 289785  3.835836 -14.526241          309            0.000143         3.511491\n",
+       " 289786  3.837538 -14.526330          309            0.000134         3.511491\n",
+       " 289787  3.839239 -14.526420          309            0.000124         3.511491\n",
+       " \n",
+       " [670 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 290118  2.700801 -14.519688          310            3.500666         3.506147\n",
+       " 290119  2.702502 -14.519753          310            3.498759         3.506147\n",
+       " 290120  2.704204 -14.519972          310            3.496805         3.506147\n",
+       " 290121  2.705906 -14.520190          310            3.494852         3.506147\n",
+       " 290122  2.707608 -14.520154          310            3.492952         3.506147\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 290783  3.832433 -14.526062          310            0.000161         3.506147\n",
+       " 290784  3.834134 -14.526152          310            0.000152         3.506147\n",
+       " 290785  3.835836 -14.526241          310            0.000143         3.506147\n",
+       " 290786  3.837538 -14.526330          310            0.000134         3.506147\n",
+       " 290787  3.839239 -14.526420          310            0.000124         3.506147\n",
+       " \n",
+       " [670 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 291118  2.700801 -14.519695          311            3.501100          3.50432\n",
+       " 291119  2.702502 -14.519509          311            3.499317          3.50432\n",
+       " 291120  2.704204 -14.519374          311            3.497516          3.50432\n",
+       " 291121  2.705906 -14.519750          311            3.495531          3.50432\n",
+       " 291122  2.707608 -14.520125          311            3.493547          3.50432\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 291775  3.818819 -14.518316          311            0.000211          3.50432\n",
+       " 291776  3.820521 -14.518291          311            0.000201          3.50432\n",
+       " 291777  3.822222 -14.518266          311            0.000191          3.50432\n",
+       " 291778  3.823924 -14.518240          311            0.000181          3.50432\n",
+       " 291779  3.825626 -14.518215          311            0.000170          3.50432\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 292118  2.700801 -14.519691          312            3.498238         3.504942\n",
+       " 292119  2.702502 -14.519931          312            3.496383         3.504942\n",
+       " 292120  2.704204 -14.520170          312            3.494528         3.504942\n",
+       " 292121  2.705906 -14.520164          312            3.492651         3.504942\n",
+       " 292122  2.707608 -14.520020          312            3.490763         3.504942\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 292783  3.832433 -14.526274          312            0.000160         3.504942\n",
+       " 292784  3.834134 -14.526369          312            0.000151         3.504942\n",
+       " 292785  3.835836 -14.526464          312            0.000142         3.504942\n",
+       " 292786  3.837538 -14.526560          312            0.000133         3.504942\n",
+       " 292787  3.839239 -14.526656          312            0.000123         3.504942\n",
+       " \n",
+       " [670 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 293118  2.700801 -14.520115          313            3.499517         3.502735\n",
+       " 293119  2.702502 -14.519839          313            3.497718         3.502735\n",
+       " 293120  2.704204 -14.519670          313            3.495852         3.502735\n",
+       " 293121  2.705906 -14.519520          313            3.493973         3.502735\n",
+       " 293122  2.707608 -14.519370          313            3.492094         3.502735\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 293783  3.832433 -14.524932          313            0.000167         3.502735\n",
+       " 293784  3.834134 -14.525008          313            0.000157         3.502735\n",
+       " 293785  3.835836 -14.525084          313            0.000148         3.502735\n",
+       " 293786  3.837538 -14.525160          313            0.000139         3.502735\n",
+       " 293787  3.839239 -14.525236          313            0.000129         3.502735\n",
+       " \n",
+       " [670 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 294118  2.700801 -14.519799          314            3.497782         3.500957\n",
+       " 294119  2.702502 -14.519872          314            3.495919         3.500957\n",
+       " 294120  2.704204 -14.519943          314            3.494057         3.500957\n",
+       " 294121  2.705906 -14.520016          314            3.492194         3.500957\n",
+       " 294122  2.707608 -14.519965          314            3.490287         3.500957\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 294783  3.832433 -14.526480          314            0.000161         3.500957\n",
+       " 294784  3.834134 -14.526579          314            0.000152         3.500957\n",
+       " 294785  3.835836 -14.526677          314            0.000143         3.500957\n",
+       " 294786  3.837538 -14.526776          314            0.000133         3.500957\n",
+       " 294787  3.839239 -14.526875          314            0.000124         3.500957\n",
+       " \n",
+       " [670 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 295118  2.700801 -14.520131          315            3.493981         3.501413\n",
+       " 295119  2.702502 -14.519862          315            3.492071         3.501413\n",
+       " 295120  2.704204 -14.519593          315            3.490161         3.501413\n",
+       " 295121  2.705906 -14.519700          315            3.488271         3.501413\n",
+       " 295122  2.707608 -14.519844          315            3.486384         3.501413\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 295783  3.832433 -14.526219          315            0.000164         3.501413\n",
+       " 295784  3.834134 -14.526319          315            0.000155         3.501413\n",
+       " 295785  3.835836 -14.526418          315            0.000146         3.501413\n",
+       " 295786  3.837538 -14.526516          315            0.000136         3.501413\n",
+       " 295787  3.839239 -14.526615          315            0.000127         3.501413\n",
+       " \n",
+       " [670 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 296118  2.700801 -14.519928          316            3.493346         3.497869\n",
+       " 296119  2.702502 -14.519827          316            3.491527         3.497869\n",
+       " 296120  2.704204 -14.519901          316            3.489676         3.497869\n",
+       " 296121  2.705906 -14.519975          316            3.487824         3.497869\n",
+       " 296122  2.707608 -14.520048          316            3.485970         3.497869\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 296783  3.832433 -14.525969          316            0.000168         3.497869\n",
+       " 296784  3.834134 -14.526065          316            0.000159         3.497869\n",
+       " 296785  3.835836 -14.526161          316            0.000149         3.497869\n",
+       " 296786  3.837538 -14.526258          316            0.000140         3.497869\n",
+       " 296787  3.839239 -14.526354          316            0.000130         3.497869\n",
+       " \n",
+       " [670 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 297118  2.700801 -14.520419          317            3.493761         3.496189\n",
+       " 297119  2.702502 -14.520370          317            3.492001         3.496189\n",
+       " 297120  2.704204 -14.520224          317            3.490163         3.496189\n",
+       " 297121  2.705906 -14.520078          317            3.488325         3.496189\n",
+       " 297122  2.707608 -14.519979          317            3.486436         3.496189\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 297783  3.832433 -14.526443          317            0.000165         3.496189\n",
+       " 297784  3.834134 -14.526543          317            0.000155         3.496189\n",
+       " 297785  3.835836 -14.526642          317            0.000146         3.496189\n",
+       " 297786  3.837538 -14.526741          317            0.000137         3.496189\n",
+       " 297787  3.839239 -14.526840          317            0.000128         3.496189\n",
+       " \n",
+       " [670 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 298118  2.700801 -14.520181          318            3.491410         3.497211\n",
+       " 298119  2.702502 -14.520033          318            3.489611         3.497211\n",
+       " 298120  2.704204 -14.519884          318            3.487812         3.497211\n",
+       " 298121  2.705906 -14.519798          318            3.485986         3.497211\n",
+       " 298122  2.707608 -14.519798          318            3.484121         3.497211\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 298783  3.832433 -14.525999          318            0.000165         3.497211\n",
+       " 298784  3.834134 -14.526094          318            0.000156         3.497211\n",
+       " 298785  3.835836 -14.526190          318            0.000146         3.497211\n",
+       " 298786  3.837538 -14.526284          318            0.000137         3.497211\n",
+       " 298787  3.839239 -14.526380          318            0.000128         3.497211\n",
+       " \n",
+       " [670 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 299118  2.700801 -14.519798          319            3.489608         3.494835\n",
+       " 299119  2.702502 -14.519798          319            3.487769         3.494835\n",
+       " 299120  2.704204 -14.519798          319            3.485880         3.494835\n",
+       " 299121  2.705906 -14.519798          319            3.483991         3.494835\n",
+       " 299122  2.707608 -14.519843          319            3.482085         3.494835\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 299783  3.832433 -14.525567          319            0.000165         3.494835\n",
+       " 299784  3.834134 -14.525656          319            0.000156         3.494835\n",
+       " 299785  3.835836 -14.525744          319            0.000147         3.494835\n",
+       " 299786  3.837538 -14.525833          319            0.000138         3.494835\n",
+       " 299787  3.839239 -14.525922          319            0.000128         3.494835\n",
+       " \n",
+       " [670 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 300118  2.700801 -14.519960          320            3.486081         3.490585\n",
+       " 300119  2.702502 -14.519816          320            3.484269         3.490585\n",
+       " 300120  2.704204 -14.519672          320            3.482457         3.490585\n",
+       " 300121  2.705906 -14.519630          320            3.480652         3.490585\n",
+       " 300122  2.707608 -14.519846          320            3.478866         3.490585\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 300775  3.818819 -14.521095          320            0.000206         3.490585\n",
+       " 300776  3.820521 -14.521113          320            0.000196         3.490585\n",
+       " 300777  3.822222 -14.521132          320            0.000185         3.490585\n",
+       " 300778  3.823924 -14.521150          320            0.000175         3.490585\n",
+       " 300779  3.825626 -14.521167          320            0.000165         3.490585\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 301118  2.700801 -14.520027          321            3.482327         3.488533\n",
+       " 301119  2.702502 -14.520027          321            3.480508         3.488533\n",
+       " 301120  2.704204 -14.520027          321            3.478701         3.488533\n",
+       " 301121  2.705906 -14.520027          321            3.476915         3.488533\n",
+       " 301122  2.707608 -14.520027          321            3.475128         3.488533\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 301782  3.830731 -14.525998          321            0.000167         3.488533\n",
+       " 301783  3.832433 -14.526090          321            0.000157         3.488533\n",
+       " 301784  3.834134 -14.526181          321            0.000148         3.488533\n",
+       " 301785  3.835836 -14.526273          321            0.000139         3.488533\n",
+       " 301786  3.837538 -14.526364          321            0.000130         3.488533\n",
+       " \n",
+       " [669 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 302118  2.700801 -14.519648          322            3.485388         3.488224\n",
+       " 302119  2.702502 -14.520245          322            3.483718         3.488224\n",
+       " 302120  2.704204 -14.520097          322            3.481853         3.488224\n",
+       " 302121  2.705906 -14.519949          322            3.479989         3.488224\n",
+       " 302122  2.707608 -14.519801          322            3.478124         3.488224\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 302783  3.832433 -14.525842          322            0.000161         3.488224\n",
+       " 302784  3.834134 -14.525930          322            0.000151         3.488224\n",
+       " 302785  3.835836 -14.526018          322            0.000142         3.488224\n",
+       " 302786  3.837538 -14.526107          322            0.000133         3.488224\n",
+       " 302787  3.839239 -14.526195          322            0.000124         3.488224\n",
+       " \n",
+       " [670 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 303118  2.700801 -14.520098          323            3.482888         3.485709\n",
+       " 303119  2.702502 -14.520250          323            3.481062         3.485709\n",
+       " 303120  2.704204 -14.520403          323            3.479236         3.485709\n",
+       " 303121  2.705906 -14.520316          323            3.477410         3.485709\n",
+       " 303122  2.707608 -14.519952          323            3.475585         3.485709\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 303783  3.832433 -14.526466          323            0.000161         3.485709\n",
+       " 303784  3.834134 -14.526568          323            0.000152         3.485709\n",
+       " 303785  3.835836 -14.526670          323            0.000143         3.485709\n",
+       " 303786  3.837538 -14.526772          323            0.000133         3.485709\n",
+       " 303787  3.839239 -14.526875          323            0.000124         3.485709\n",
+       " \n",
+       " [670 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 304118  2.700801 -14.520205          324            3.480530         3.485136\n",
+       " 304119  2.702502 -14.520093          324            3.478750         3.485136\n",
+       " 304120  2.704204 -14.520027          324            3.476947         3.485136\n",
+       " 304121  2.705906 -14.520027          324            3.475110         3.485136\n",
+       " 304122  2.707608 -14.520027          324            3.473273         3.485136\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 304782  3.830731 -14.525527          324            0.000168         3.485136\n",
+       " 304783  3.832433 -14.525619          324            0.000159         3.485136\n",
+       " 304784  3.834134 -14.525710          324            0.000149         3.485136\n",
+       " 304785  3.835836 -14.525803          324            0.000140         3.485136\n",
+       " 304786  3.837538 -14.525894          324            0.000131         3.485136\n",
+       " \n",
+       " [669 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 305118  2.700801 -14.519341          325            3.478479          3.48452\n",
+       " 305119  2.702502 -14.519341          325            3.476627          3.48452\n",
+       " 305120  2.704204 -14.519353          325            3.474766          3.48452\n",
+       " 305121  2.705906 -14.519424          325            3.472867          3.48452\n",
+       " 305122  2.707608 -14.519495          325            3.470968          3.48452\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 305782  3.830731 -14.526002          325            0.000168          3.48452\n",
+       " 305783  3.832433 -14.526091          325            0.000159          3.48452\n",
+       " 305784  3.834134 -14.526178          325            0.000149          3.48452\n",
+       " 305785  3.835836 -14.526267          325            0.000140          3.48452\n",
+       " 305786  3.837538 -14.526355          325            0.000131          3.48452\n",
+       " \n",
+       " [669 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 306118  2.700801 -14.520106          326            3.475372         3.480936\n",
+       " 306119  2.702502 -14.520239          326            3.473593         3.480936\n",
+       " 306120  2.704204 -14.520095          326            3.471743         3.480936\n",
+       " 306121  2.705906 -14.519951          326            3.469893         3.480936\n",
+       " 306122  2.707608 -14.519807          326            3.468043         3.480936\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 306782  3.830731 -14.525794          326            0.000167         3.480936\n",
+       " 306783  3.832433 -14.525879          326            0.000158         3.480936\n",
+       " 306784  3.834134 -14.525964          326            0.000149         3.480936\n",
+       " 306785  3.835836 -14.526049          326            0.000140         3.480936\n",
+       " 306786  3.837538 -14.526134          326            0.000130         3.480936\n",
+       " \n",
+       " [669 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 307118  2.700801 -14.519779          327            3.477216         3.479596\n",
+       " 307119  2.702502 -14.520229          327            3.475338         3.479596\n",
+       " 307120  2.704204 -14.520053          327            3.473522         3.479596\n",
+       " 307121  2.705906 -14.519837          327            3.471710         3.479596\n",
+       " 307122  2.707608 -14.519622          327            3.469898         3.479596\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 307775  3.818819 -14.520667          327            0.000207         3.479596\n",
+       " 307776  3.820521 -14.520678          327            0.000197         3.479596\n",
+       " 307777  3.822222 -14.520688          327            0.000187         3.479596\n",
+       " 307778  3.823924 -14.520699          327            0.000177         3.479596\n",
+       " 307779  3.825626 -14.520710          327            0.000167         3.479596\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 308118  2.700801 -14.520256          328            3.474463         3.480017\n",
+       " 308119  2.702502 -14.520256          328            3.472612         3.480017\n",
+       " 308120  2.704204 -14.520256          328            3.470762         3.480017\n",
+       " 308121  2.705906 -14.520257          328            3.468911         3.480017\n",
+       " 308122  2.707608 -14.520330          328            3.467073         3.480017\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 308783  3.832433 -14.526690          328            0.000159         3.480017\n",
+       " 308784  3.834134 -14.526798          328            0.000150         3.480017\n",
+       " 308785  3.835836 -14.526906          328            0.000141         3.480017\n",
+       " 308786  3.837538 -14.527015          328            0.000132         3.480017\n",
+       " 308787  3.839239 -14.527122          328            0.000123         3.480017\n",
+       " \n",
+       " [670 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 309118  2.700801 -14.520036          329            3.474433         3.478653\n",
+       " 309119  2.702502 -14.520256          329            3.472697         3.478653\n",
+       " 309120  2.704204 -14.520256          329            3.470871         3.478653\n",
+       " 309121  2.705906 -14.520256          329            3.469046         3.478653\n",
+       " 309122  2.707608 -14.520256          329            3.467196         3.478653\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 309783  3.832433 -14.525831          329            0.000163         3.478653\n",
+       " 309784  3.834134 -14.525915          329            0.000154         3.478653\n",
+       " 309785  3.835836 -14.526000          329            0.000145         3.478653\n",
+       " 309786  3.837538 -14.526084          329            0.000136         3.478653\n",
+       " 309787  3.839239 -14.526169          329            0.000127         3.478653\n",
+       " \n",
+       " [670 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 310118  2.700801 -14.520188          330            3.473284         3.476471\n",
+       " 310119  2.702502 -14.520042          330            3.471537         3.476471\n",
+       " 310120  2.704204 -14.520156          330            3.469731         3.476471\n",
+       " 310121  2.705906 -14.520300          330            3.467920         3.476471\n",
+       " 310122  2.707608 -14.520444          330            3.466108         3.476471\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 310782  3.830731 -14.524674          330            0.000168         3.476471\n",
+       " 310783  3.832433 -14.524753          330            0.000159         3.476471\n",
+       " 310784  3.834134 -14.524831          330            0.000150         3.476471\n",
+       " 310785  3.835836 -14.524909          330            0.000141         3.476471\n",
+       " 310786  3.837538 -14.524987          330            0.000131         3.476471\n",
+       " \n",
+       " [669 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 311118  2.700801 -14.519838          331            3.469208         3.473769\n",
+       " 311119  2.702502 -14.519925          331            3.467455         3.473769\n",
+       " 311120  2.704204 -14.520012          331            3.465701         3.473769\n",
+       " 311121  2.705906 -14.519904          331            3.463758         3.473769\n",
+       " 311122  2.707608 -14.519753          331            3.461774         3.473769\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 311782  3.830731 -14.525581          331            0.000166         3.473769\n",
+       " 311783  3.832433 -14.525665          331            0.000156         3.473769\n",
+       " 311784  3.834134 -14.525750          331            0.000147         3.473769\n",
+       " 311785  3.835836 -14.525835          331            0.000138         3.473769\n",
+       " 311786  3.837538 -14.525920          331            0.000129         3.473769\n",
+       " \n",
+       " [669 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 312118  2.700801 -14.519728          332            3.466618         3.472341\n",
+       " 312119  2.702502 -14.519435          332            3.464854         3.472341\n",
+       " 312120  2.704204 -14.519579          332            3.463004         3.472341\n",
+       " 312121  2.705906 -14.519723          332            3.461154         3.472341\n",
+       " 312122  2.707608 -14.519870          332            3.459278         3.472341\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 312782  3.830731 -14.524094          332            0.000162         3.472341\n",
+       " 312783  3.832433 -14.524158          332            0.000153         3.472341\n",
+       " 312784  3.834134 -14.524224          332            0.000144         3.472341\n",
+       " 312785  3.835836 -14.524289          332            0.000135         3.472341\n",
+       " 312786  3.837538 -14.524354          332            0.000126         3.472341\n",
+       " \n",
+       " [669 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 313118  2.700801 -14.519981          333            3.467840         3.472916\n",
+       " 313119  2.702502 -14.519961          333            3.465999         3.472916\n",
+       " 313120  2.704204 -14.519888          333            3.464135         3.472916\n",
+       " 313121  2.705906 -14.519814          333            3.462270         3.472916\n",
+       " 313122  2.707608 -14.519798          333            3.460427         3.472916\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 313782  3.830731 -14.526216          333            0.000165         3.472916\n",
+       " 313783  3.832433 -14.526314          333            0.000156         3.472916\n",
+       " 313784  3.834134 -14.526411          333            0.000146         3.472916\n",
+       " 313785  3.835836 -14.526508          333            0.000137         3.472916\n",
+       " 313786  3.837538 -14.526607          333            0.000128         3.472916\n",
+       " \n",
+       " [669 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 314118  2.700801 -14.520137          334            3.468161         3.471175\n",
+       " 314119  2.702502 -14.519984          334            3.466420         3.471175\n",
+       " 314120  2.704204 -14.519909          334            3.464621         3.471175\n",
+       " 314121  2.705906 -14.519835          334            3.462821         3.471175\n",
+       " 314122  2.707608 -14.519837          334            3.460988         3.471175\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 314782  3.830731 -14.526823          334            0.000168         3.471175\n",
+       " 314783  3.832433 -14.526930          334            0.000158         3.471175\n",
+       " 314784  3.834134 -14.527038          334            0.000149         3.471175\n",
+       " 314785  3.835836 -14.527145          334            0.000140         3.471175\n",
+       " 314786  3.837538 -14.527253          334            0.000131         3.471175\n",
+       " \n",
+       " [669 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 315118  2.700801 -14.520061          335            3.464867         3.468939\n",
+       " 315119  2.702502 -14.520134          335            3.463145         3.468939\n",
+       " 315120  2.704204 -14.520207          335            3.461423         3.468939\n",
+       " 315121  2.705906 -14.520184          335            3.459675         3.468939\n",
+       " 315122  2.707608 -14.519961          335            3.457876         3.468939\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 315782  3.830731 -14.525573          335            0.000168         3.468939\n",
+       " 315783  3.832433 -14.525654          335            0.000159         3.468939\n",
+       " 315784  3.834134 -14.525736          335            0.000150         3.468939\n",
+       " 315785  3.835836 -14.525818          335            0.000141         3.468939\n",
+       " 315786  3.837538 -14.525900          335            0.000131         3.468939\n",
+       " \n",
+       " [669 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 316118  2.700801 -14.520485          336            3.463305         3.467961\n",
+       " 316119  2.702502 -14.520366          336            3.461527         3.467961\n",
+       " 316120  2.704204 -14.520216          336            3.459662         3.467961\n",
+       " 316121  2.705906 -14.520065          336            3.457797         3.467961\n",
+       " 316122  2.707608 -14.519917          336            3.455913         3.467961\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 316782  3.830731 -14.525162          336            0.000165         3.467961\n",
+       " 316783  3.832433 -14.525239          336            0.000155         3.467961\n",
+       " 316784  3.834134 -14.525317          336            0.000146         3.467961\n",
+       " 316785  3.835836 -14.525395          336            0.000137         3.467961\n",
+       " 316786  3.837538 -14.525474          336            0.000128         3.467961\n",
+       " \n",
+       " [669 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 317118  2.700801 -14.520256          337            3.461173         3.467455\n",
+       " 317119  2.702502 -14.520256          337            3.459399         3.467455\n",
+       " 317120  2.704204 -14.520256          337            3.457626         3.467455\n",
+       " 317121  2.705906 -14.520184          337            3.455831         3.467455\n",
+       " 317122  2.707608 -14.519961          337            3.453993         3.467455\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 317782  3.830731 -14.524697          337            0.000165         3.467455\n",
+       " 317783  3.832433 -14.524776          337            0.000156         3.467455\n",
+       " 317784  3.834134 -14.524854          337            0.000147         3.467455\n",
+       " 317785  3.835836 -14.524931          337            0.000138         3.467455\n",
+       " 317786  3.837538 -14.525009          337            0.000129         3.467455\n",
+       " \n",
+       " [669 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 318118  2.700801 -14.519605          338            3.459657         3.463829\n",
+       " 318119  2.702502 -14.520172          338            3.457833         3.463829\n",
+       " 318120  2.704204 -14.520132          338            3.455986         3.463829\n",
+       " 318121  2.705906 -14.519986          338            3.454135         3.463829\n",
+       " 318122  2.707608 -14.519840          338            3.452285         3.463829\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 318782  3.830731 -14.524299          338            0.000164         3.463829\n",
+       " 318783  3.832433 -14.524366          338            0.000155         3.463829\n",
+       " 318784  3.834134 -14.524434          338            0.000145         3.463829\n",
+       " 318785  3.835836 -14.524502          338            0.000136         3.463829\n",
+       " 318786  3.837538 -14.524570          338            0.000127         3.463829\n",
+       " \n",
+       " [669 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 319118  2.700801 -14.519798          339            3.458998          3.46261\n",
+       " 319119  2.702502 -14.519798          339            3.457233          3.46261\n",
+       " 319120  2.704204 -14.519812          339            3.455459          3.46261\n",
+       " 319121  2.705906 -14.519955          339            3.453597          3.46261\n",
+       " 319122  2.707608 -14.520099          339            3.451734          3.46261\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 319783  3.832433 -14.524975          339            0.000160          3.46261\n",
+       " 319784  3.834134 -14.525053          339            0.000150          3.46261\n",
+       " 319785  3.835836 -14.525131          339            0.000141          3.46261\n",
+       " 319786  3.837538 -14.525209          339            0.000132          3.46261\n",
+       " 319787  3.839239 -14.525288          339            0.000123          3.46261\n",
+       " \n",
+       " [670 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 320118  2.700801 -14.520027          340            3.459118         3.460775\n",
+       " 320119  2.702502 -14.519972          340            3.457375         3.460775\n",
+       " 320120  2.704204 -14.519897          340            3.455563         3.460775\n",
+       " 320121  2.705906 -14.519824          340            3.453751         3.460775\n",
+       " 320122  2.707608 -14.519847          340            3.451896         3.460775\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 320782  3.830731 -14.526914          340            0.000160         3.460775\n",
+       " 320783  3.832433 -14.527020          340            0.000151         3.460775\n",
+       " 320784  3.834134 -14.527127          340            0.000142         3.460775\n",
+       " 320785  3.835836 -14.527233          340            0.000133         3.460775\n",
+       " 320786  3.837538 -14.527340          340            0.000123         3.460775\n",
+       " \n",
+       " [669 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 321118  2.700801 -14.519561          341            3.455343         3.462763\n",
+       " 321119  2.702502 -14.519485          341            3.453449         3.462763\n",
+       " 321120  2.704204 -14.519409          341            3.451556         3.462763\n",
+       " 321121  2.705906 -14.519356          341            3.449670         3.462763\n",
+       " 321122  2.707608 -14.519499          341            3.447846         3.462763\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 321782  3.830731 -14.524696          341            0.000167         3.462763\n",
+       " 321783  3.832433 -14.524771          341            0.000158         3.462763\n",
+       " 321784  3.834134 -14.524845          341            0.000149         3.462763\n",
+       " 321785  3.835836 -14.524920          341            0.000140         3.462763\n",
+       " 321786  3.837538 -14.524995          341            0.000131         3.462763\n",
+       " \n",
+       " [669 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 322118  2.700801 -14.519960          342            3.453376         3.458465\n",
+       " 322119  2.702502 -14.519830          342            3.451577         3.458465\n",
+       " 322120  2.704204 -14.519687          342            3.449758         3.458465\n",
+       " 322121  2.705906 -14.519541          342            3.447933         3.458465\n",
+       " 322122  2.707608 -14.519396          342            3.446109         3.458465\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 322782  3.830731 -14.525189          342            0.000161         3.458465\n",
+       " 322783  3.832433 -14.525267          342            0.000152         3.458465\n",
+       " 322784  3.834134 -14.525344          342            0.000143         3.458465\n",
+       " 322785  3.835836 -14.525421          342            0.000134         3.458465\n",
+       " 322786  3.837538 -14.525498          342            0.000125         3.458465\n",
+       " \n",
+       " [669 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 323118  2.700801 -14.520143          343            3.450563         3.455264\n",
+       " 323119  2.702502 -14.519899          343            3.448785         3.455264\n",
+       " 323120  2.704204 -14.519755          343            3.446949         3.455264\n",
+       " 323121  2.705906 -14.519681          343            3.445072         3.455264\n",
+       " 323122  2.707608 -14.519608          343            3.443194         3.455264\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 323781  3.829029 -14.524700          343            0.000167         3.455264\n",
+       " 323782  3.830731 -14.524775          343            0.000158         3.455264\n",
+       " 323783  3.832433 -14.524849          343            0.000149         3.455264\n",
+       " 323784  3.834134 -14.524922          343            0.000140         3.455264\n",
+       " 323785  3.835836 -14.524997          343            0.000131         3.455264\n",
+       " \n",
+       " [668 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 324118  2.700801 -14.519753          344            3.449779         3.452301\n",
+       " 324119  2.702502 -14.519929          344            3.447930         3.452301\n",
+       " 324120  2.704204 -14.520077          344            3.446065         3.452301\n",
+       " 324121  2.705906 -14.520225          344            3.444201         3.452301\n",
+       " 324122  2.707608 -14.520141          344            3.442378         3.452301\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 324773  3.815415 -14.518282          344            0.000211         3.452301\n",
+       " 324774  3.817117 -14.518265          344            0.000202         3.452301\n",
+       " 324775  3.818819 -14.518248          344            0.000192         3.452301\n",
+       " 324776  3.820521 -14.518229          344            0.000182         3.452301\n",
+       " 324777  3.822222 -14.518212          344            0.000172         3.452301\n",
+       " \n",
+       " [660 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 325118  2.700801 -14.519515          345            3.449028         3.452657\n",
+       " 325119  2.702502 -14.519408          345            3.447322         3.452657\n",
+       " 325120  2.704204 -14.519391          345            3.445592         3.452657\n",
+       " 325121  2.705906 -14.519533          345            3.443818         3.452657\n",
+       " 325122  2.707608 -14.519675          345            3.442044         3.452657\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 325781  3.829029 -14.525573          345            0.000166         3.452657\n",
+       " 325782  3.830731 -14.525657          345            0.000157         3.452657\n",
+       " 325783  3.832433 -14.525740          345            0.000148         3.452657\n",
+       " 325784  3.834134 -14.525824          345            0.000139         3.452657\n",
+       " 325785  3.835836 -14.525908          345            0.000130         3.452657\n",
+       " \n",
+       " [668 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 326118  2.700801 -14.519880          346            3.445255         3.452333\n",
+       " 326119  2.702502 -14.520027          346            3.443428         3.452333\n",
+       " 326120  2.704204 -14.520027          346            3.441616         3.452333\n",
+       " 326121  2.705906 -14.520027          346            3.439804         3.452333\n",
+       " 326122  2.707608 -14.520027          346            3.437992         3.452333\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 326773  3.815415 -14.521094          346            0.000207         3.452333\n",
+       " 326774  3.817117 -14.521111          346            0.000197         3.452333\n",
+       " 326775  3.818819 -14.521129          346            0.000187         3.452333\n",
+       " 326776  3.820521 -14.521146          346            0.000177         3.452333\n",
+       " 326777  3.822222 -14.521164          346            0.000167         3.452333\n",
+       " \n",
+       " [660 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 327118  2.700801 -14.519569          347            3.442804         3.447777\n",
+       " 327119  2.702502 -14.519569          347            3.440953         3.447777\n",
+       " 327120  2.704204 -14.519569          347            3.439102         3.447777\n",
+       " 327121  2.705906 -14.519569          347            3.437252         3.447777\n",
+       " 327122  2.707608 -14.519639          347            3.435476         3.447777\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 327781  3.829029 -14.524966          347            0.000164         3.447777\n",
+       " 327782  3.830731 -14.525037          347            0.000155         3.447777\n",
+       " 327783  3.832433 -14.525107          347            0.000146         3.447777\n",
+       " 327784  3.834134 -14.525178          347            0.000137         3.447777\n",
+       " 327785  3.835836 -14.525249          347            0.000128         3.447777\n",
+       " \n",
+       " [668 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 328118  2.700801 -14.519836          348            3.441437         3.444988\n",
+       " 328119  2.702502 -14.519917          348            3.439724         3.444988\n",
+       " 328120  2.704204 -14.519999          348            3.438010         3.444988\n",
+       " 328121  2.705906 -14.519979          348            3.436148         3.444988\n",
+       " 328122  2.707608 -14.519904          348            3.434204         3.444988\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 328781  3.829029 -14.525989          348            0.000165         3.444988\n",
+       " 328782  3.830731 -14.526084          348            0.000156         3.444988\n",
+       " 328783  3.832433 -14.526180          348            0.000146         3.444988\n",
+       " 328784  3.834134 -14.526277          348            0.000137         3.444988\n",
+       " 328785  3.835836 -14.526373          348            0.000128         3.444988\n",
+       " \n",
+       " [668 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 329118  2.700801 -14.519834          349            3.440116         3.443988\n",
+       " 329119  2.702502 -14.519979          349            3.438355         3.443988\n",
+       " 329120  2.704204 -14.520125          349            3.436595         3.443988\n",
+       " 329121  2.705906 -14.520233          349            3.434822         3.443988\n",
+       " 329122  2.707608 -14.520011          349            3.432945         3.443988\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 329781  3.829029 -14.526611          349            0.000165         3.443988\n",
+       " 329782  3.830731 -14.526720          349            0.000156         3.443988\n",
+       " 329783  3.832433 -14.526829          349            0.000147         3.443988\n",
+       " 329784  3.834134 -14.526937          349            0.000138         3.443988\n",
+       " 329785  3.835836 -14.527046          349            0.000129         3.443988\n",
+       " \n",
+       " [668 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 330118  2.700801 -14.519814          350            3.439055         3.444346\n",
+       " 330119  2.702502 -14.519958          350            3.437231         3.444346\n",
+       " 330120  2.704204 -14.520102          350            3.435406         3.444346\n",
+       " 330121  2.705906 -14.520246          350            3.433582         3.444346\n",
+       " 330122  2.707608 -14.520391          350            3.431769         3.444346\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 330781  3.829029 -14.524753          350            0.000162         3.444346\n",
+       " 330782  3.830731 -14.524823          350            0.000153         3.444346\n",
+       " 330783  3.832433 -14.524894          350            0.000144         3.444346\n",
+       " 330784  3.834134 -14.524964          350            0.000135         3.444346\n",
+       " 330785  3.835836 -14.525035          350            0.000126         3.444346\n",
+       " \n",
+       " [668 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 331118  2.700801 -14.520473          356            3.519612         3.620202\n",
+       " 331119  2.702502 -14.520339          356            3.517032         3.620202\n",
+       " 331120  2.704204 -14.520188          356            3.514439         3.620202\n",
+       " 331121  2.705906 -14.520039          356            3.511846         3.620202\n",
+       " 331122  2.707608 -14.519895          356            3.509354         3.620202\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 331785  3.835836 -14.525813          356            0.000164         3.620202\n",
+       " 331786  3.837538 -14.525899          356            0.000155         3.620202\n",
+       " 331787  3.839239 -14.525984          356            0.000146         3.620202\n",
+       " 331788  3.840941 -14.526070          356            0.000137         3.620202\n",
+       " 331789  3.842643 -14.526155          356            0.000128         3.620202\n",
+       " \n",
+       " [672 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 332118  2.700801 -14.520027          357            3.506982         3.520636\n",
+       " 332119  2.702502 -14.520027          357            3.504583         3.520636\n",
+       " 332120  2.704204 -14.520027          357            3.502184         3.520636\n",
+       " 332121  2.705906 -14.520027          357            3.499651         3.520636\n",
+       " 332122  2.707608 -14.520027          357            3.497044         3.520636\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 332784  3.834134 -14.525604          357            0.000160         3.520636\n",
+       " 332785  3.835836 -14.525693          357            0.000151         3.520636\n",
+       " 332786  3.837538 -14.525782          357            0.000142         3.520636\n",
+       " 332787  3.839239 -14.525870          357            0.000133         3.520636\n",
+       " 332788  3.840941 -14.525959          357            0.000124         3.520636\n",
+       " \n",
+       " [671 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 333118  2.700801 -14.520485          358            3.493244         3.506102\n",
+       " 333119  2.702502 -14.520485          358            3.490707         3.506102\n",
+       " 333120  2.704204 -14.520485          358            3.488169         3.506102\n",
+       " 333121  2.705906 -14.520382          358            3.485659         3.506102\n",
+       " 333122  2.707608 -14.520161          358            3.483182         3.506102\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 333775  3.818819 -14.518930          358            0.000207         3.506102\n",
+       " 333776  3.820521 -14.518920          358            0.000198         3.506102\n",
+       " 333777  3.822222 -14.518909          358            0.000188         3.506102\n",
+       " 333778  3.823924 -14.518899          358            0.000178         3.506102\n",
+       " 333779  3.825626 -14.518889          358            0.000169         3.506102\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 334118  2.700801 -14.519854          359            3.480147         3.492201\n",
+       " 334119  2.702502 -14.519973          359            3.477720         3.492201\n",
+       " 334120  2.704204 -14.519986          359            3.475256         3.492201\n",
+       " 334121  2.705906 -14.519910          359            3.472758         3.492201\n",
+       " 334122  2.707608 -14.519834          359            3.470261         3.492201\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 334783  3.832433 -14.526255          359            0.000162         3.492201\n",
+       " 334784  3.834134 -14.526346          359            0.000153         3.492201\n",
+       " 334785  3.835836 -14.526439          359            0.000144         3.492201\n",
+       " 334786  3.837538 -14.526531          359            0.000135         3.492201\n",
+       " 334787  3.839239 -14.526623          359            0.000127         3.492201\n",
+       " \n",
+       " [670 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 335118  2.700801 -14.519955          360            3.470680           3.4819\n",
+       " 335119  2.702502 -14.519800          360            3.468363           3.4819\n",
+       " 335120  2.704204 -14.519870          360            3.465884           3.4819\n",
+       " 335121  2.705906 -14.519943          360            3.463404           3.4819\n",
+       " 335122  2.707608 -14.520016          360            3.460924           3.4819\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 335782  3.830731 -14.525594          360            0.000164           3.4819\n",
+       " 335783  3.832433 -14.525676          360            0.000155           3.4819\n",
+       " 335784  3.834134 -14.525758          360            0.000146           3.4819\n",
+       " 335785  3.835836 -14.525840          360            0.000138           3.4819\n",
+       " 335786  3.837538 -14.525922          360            0.000129           3.4819\n",
+       " \n",
+       " [669 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 336118  2.700801 -14.519773          361            3.459813         3.473167\n",
+       " 336119  2.702502 -14.519697          361            3.457356         3.473167\n",
+       " 336120  2.704204 -14.519621          361            3.454899         3.473167\n",
+       " 336121  2.705906 -14.519594          361            3.452429         3.473167\n",
+       " 336122  2.707608 -14.519670          361            3.449931         3.473167\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 336782  3.830731 -14.526887          361            0.000162         3.473167\n",
+       " 336783  3.832433 -14.526991          361            0.000153         3.473167\n",
+       " 336784  3.834134 -14.527095          361            0.000144         3.473167\n",
+       " 336785  3.835836 -14.527199          361            0.000136         3.473167\n",
+       " 336786  3.837538 -14.527303          361            0.000127         3.473167\n",
+       " \n",
+       " [669 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 337118  2.700801 -14.519609          362            3.455223         3.463995\n",
+       " 337119  2.702502 -14.519696          362            3.452798         3.463995\n",
+       " 337120  2.704204 -14.519783          362            3.450374         3.463995\n",
+       " 337121  2.705906 -14.519858          362            3.447914         3.463995\n",
+       " 337122  2.707608 -14.519931          362            3.445447         3.463995\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 337782  3.830731 -14.525187          362            0.000160         3.463995\n",
+       " 337783  3.832433 -14.525265          362            0.000151         3.463995\n",
+       " 337784  3.834134 -14.525344          362            0.000142         3.463995\n",
+       " 337785  3.835836 -14.525422          362            0.000134         3.463995\n",
+       " 337786  3.837538 -14.525501          362            0.000125         3.463995\n",
+       " \n",
+       " [669 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 338118  2.700801 -14.520256          363            3.448497         3.455144\n",
+       " 338119  2.702502 -14.520256          363            3.446093         3.455144\n",
+       " 338120  2.704204 -14.520256          363            3.443689         3.455144\n",
+       " 338121  2.705906 -14.520202          363            3.441241         3.455144\n",
+       " 338122  2.707608 -14.520128          363            3.438777         3.455144\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 338781  3.829029 -14.526659          363            0.000166         3.455144\n",
+       " 338782  3.830731 -14.526753          363            0.000157         3.455144\n",
+       " 338783  3.832433 -14.526849          363            0.000148         3.455144\n",
+       " 338784  3.834134 -14.526944          363            0.000139         3.455144\n",
+       " 338785  3.835836 -14.527039          363            0.000130         3.455144\n",
+       " \n",
+       " [668 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 339118  2.700801 -14.520040          364            3.440381          3.45007\n",
+       " 339119  2.702502 -14.519871          364            3.438018          3.45007\n",
+       " 339120  2.704204 -14.520020          364            3.435531          3.45007\n",
+       " 339121  2.705906 -14.520170          364            3.433043          3.45007\n",
+       " 339122  2.707608 -14.520164          364            3.430618          3.45007\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 339782  3.830731 -14.524992          364            0.000161          3.45007\n",
+       " 339783  3.832433 -14.525061          364            0.000152          3.45007\n",
+       " 339784  3.834134 -14.525130          364            0.000143          3.45007\n",
+       " 339785  3.835836 -14.525199          364            0.000134          3.45007\n",
+       " 339786  3.837538 -14.525269          364            0.000125          3.45007\n",
+       " \n",
+       " [669 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 340118  2.700801 -14.519569          365            3.432328         3.442394\n",
+       " 340119  2.702502 -14.519812          365            3.429982         3.442394\n",
+       " 340120  2.704204 -14.520116          365            3.427552         3.442394\n",
+       " 340121  2.705906 -14.520421          365            3.425121         3.442394\n",
+       " 340122  2.707608 -14.520305          365            3.422659         3.442394\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 340772  3.813714 -14.520256          365            0.000207         3.442394\n",
+       " 340773  3.815415 -14.520256          365            0.000198         3.442394\n",
+       " 340774  3.817117 -14.520256          365            0.000188         3.442394\n",
+       " 340775  3.818819 -14.520256          365            0.000179         3.442394\n",
+       " 340776  3.820521 -14.520256          365            0.000169         3.442394\n",
+       " \n",
+       " [659 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 341118  2.700801 -14.519355          366            3.430263         3.437412\n",
+       " 341119  2.702502 -14.519584          366            3.427779         3.437412\n",
+       " 341120  2.704204 -14.519812          366            3.425295         3.437412\n",
+       " 341121  2.705906 -14.520019          366            3.422819         3.437412\n",
+       " 341122  2.707608 -14.519868          366            3.420478         3.437412\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 341780  3.827327 -14.525772          366            0.000165         3.437412\n",
+       " 341781  3.829029 -14.525863          366            0.000156         3.437412\n",
+       " 341782  3.830731 -14.525953          366            0.000147         3.437412\n",
+       " 341783  3.832433 -14.526044          366            0.000138         3.437412\n",
+       " 341784  3.834134 -14.526134          366            0.000130         3.437412\n",
+       " \n",
+       " [667 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 342118  2.700801 -14.520048          367            3.425344         3.432493\n",
+       " 342119  2.702502 -14.520121          367            3.422979         3.432493\n",
+       " 342120  2.704204 -14.520194          367            3.420615         3.432493\n",
+       " 342121  2.705906 -14.520245          367            3.418244         3.432493\n",
+       " 342122  2.707608 -14.520168          367            3.415841         3.432493\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 342780  3.827327 -14.525970          367            0.000166         3.432493\n",
+       " 342781  3.829029 -14.526063          367            0.000157         3.432493\n",
+       " 342782  3.830731 -14.526156          367            0.000149         3.432493\n",
+       " 342783  3.832433 -14.526250          367            0.000140         3.432493\n",
+       " 342784  3.834134 -14.526343          367            0.000131         3.432493\n",
+       " \n",
+       " [667 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 343118  2.700801 -14.519798          368            3.422676         3.427832\n",
+       " 343119  2.702502 -14.519817          368            3.420350         3.427832\n",
+       " 343120  2.704204 -14.519891          368            3.418043         3.427832\n",
+       " 343121  2.705906 -14.519965          368            3.415735         3.427832\n",
+       " 343122  2.707608 -14.520015          368            3.413421         3.427832\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 343781  3.829029 -14.524746          368            0.000161         3.427832\n",
+       " 343782  3.830731 -14.524817          368            0.000152         3.427832\n",
+       " 343783  3.832433 -14.524890          368            0.000144         3.427832\n",
+       " 343784  3.834134 -14.524962          368            0.000135         3.427832\n",
+       " 343785  3.835836 -14.525034          368            0.000126         3.427832\n",
+       " \n",
+       " [668 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 344118  2.700801 -14.520027          369            3.417962         3.424496\n",
+       " 344119  2.702502 -14.519975          369            3.415717         3.424496\n",
+       " 344120  2.704204 -14.519901          369            3.413396         3.424496\n",
+       " 344121  2.705906 -14.519827          369            3.411075         3.424496\n",
+       " 344122  2.707608 -14.519934          369            3.408771         3.424496\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 344780  3.827327 -14.524981          369            0.000164         3.424496\n",
+       " 344781  3.829029 -14.525047          369            0.000155         3.424496\n",
+       " 344782  3.830731 -14.525113          369            0.000146         3.424496\n",
+       " 344783  3.832433 -14.525179          369            0.000138         3.424496\n",
+       " 344784  3.834134 -14.525245          369            0.000129         3.424496\n",
+       " \n",
+       " [667 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 345118  2.700801 -14.519888          370            3.412958         3.421023\n",
+       " 345119  2.702502 -14.520081          370            3.410802         3.421023\n",
+       " 345120  2.704204 -14.520256          370            3.408624         3.421023\n",
+       " 345121  2.705906 -14.520256          370            3.406221         3.421023\n",
+       " 345122  2.707608 -14.520256          370            3.403817         3.421023\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 345780  3.827327 -14.524964          370            0.000163         3.421023\n",
+       " 345781  3.829029 -14.525036          370            0.000154         3.421023\n",
+       " 345782  3.830731 -14.525107          370            0.000145         3.421023\n",
+       " 345783  3.832433 -14.525179          370            0.000136         3.421023\n",
+       " 345784  3.834134 -14.525249          370            0.000128         3.421023\n",
+       " \n",
+       " [667 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 346118  2.700801 -14.519605          371            3.410123         3.415093\n",
+       " 346119  2.702502 -14.520172          371            3.407944         3.415093\n",
+       " 346120  2.704204 -14.520346          371            3.405691         3.415093\n",
+       " 346121  2.705906 -14.520037          371            3.403347         3.415093\n",
+       " 346122  2.707608 -14.519728          371            3.401002         3.415093\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 346780  3.827327 -14.526684          371            0.000160         3.415093\n",
+       " 346781  3.829029 -14.526787          371            0.000151         3.415093\n",
+       " 346782  3.830731 -14.526890          371            0.000142         3.415093\n",
+       " 346783  3.832433 -14.526992          371            0.000134         3.415093\n",
+       " 346784  3.834134 -14.527095          371            0.000125         3.415093\n",
+       " \n",
+       " [667 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 347118  2.700801 -14.519552          372            3.406841         3.414351\n",
+       " 347119  2.702502 -14.520237          372            3.404548         3.414351\n",
+       " 347120  2.704204 -14.520164          372            3.402273         3.414351\n",
+       " 347121  2.705906 -14.520092          372            3.399999         3.414351\n",
+       " 347122  2.707608 -14.520010          372            3.397715         3.414351\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 347780  3.827327 -14.526479          372            0.000161         3.414351\n",
+       " 347781  3.829029 -14.526572          372            0.000153         3.414351\n",
+       " 347782  3.830731 -14.526666          372            0.000144         3.414351\n",
+       " 347783  3.832433 -14.526758          372            0.000135         3.414351\n",
+       " 347784  3.834134 -14.526852          372            0.000126         3.414351\n",
+       " \n",
+       " [667 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 348118  2.700801 -14.520169          373            3.407546         3.410533\n",
+       " 348119  2.702502 -14.519984          373            3.405289         3.410533\n",
+       " 348120  2.704204 -14.519798          373            3.403032         3.410533\n",
+       " 348121  2.705906 -14.519798          373            3.400688         3.410533\n",
+       " 348122  2.707608 -14.519798          373            3.398344         3.410533\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 348780  3.827327 -14.526670          373            0.000162         3.410533\n",
+       " 348781  3.829029 -14.526769          373            0.000154         3.410533\n",
+       " 348782  3.830731 -14.526869          373            0.000145         3.410533\n",
+       " 348783  3.832433 -14.526969          373            0.000136         3.410533\n",
+       " 348784  3.834134 -14.527069          373            0.000127         3.410533\n",
+       " \n",
+       " [667 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 349118  2.700801 -14.519737          374            3.403092         3.408538\n",
+       " 349119  2.702502 -14.519607          374            3.400970         3.408538\n",
+       " 349120  2.704204 -14.519733          374            3.398723         3.408538\n",
+       " 349121  2.705906 -14.519962          374            3.396427         3.408538\n",
+       " 349122  2.707608 -14.520190          374            3.394131         3.408538\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 349772  3.813714 -14.520871          374            0.000203         3.408538\n",
+       " 349773  3.815415 -14.520888          374            0.000193         3.408538\n",
+       " 349774  3.817117 -14.520905          374            0.000184         3.408538\n",
+       " 349775  3.818819 -14.520923          374            0.000174         3.408538\n",
+       " 349776  3.820521 -14.520939          374            0.000165         3.408538\n",
+       " \n",
+       " [659 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 350118  2.700801 -14.519413          375            3.401994         3.405208\n",
+       " 350119  2.702502 -14.519567          375            3.399854         3.405208\n",
+       " 350120  2.704204 -14.519722          375            3.397714         3.405208\n",
+       " 350121  2.705906 -14.519835          375            3.395516         3.405208\n",
+       " 350122  2.707608 -14.519910          375            3.393260         3.405208\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 350771  3.812012 -14.519599          375            0.000205         3.405208\n",
+       " 350772  3.813714 -14.519592          375            0.000195         3.405208\n",
+       " 350773  3.815415 -14.519586          375            0.000186         3.405208\n",
+       " 350774  3.817117 -14.519579          375            0.000176         3.405208\n",
+       " 350775  3.818819 -14.519572          375            0.000167         3.405208\n",
+       " \n",
+       " [658 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 351118  2.700801 -14.520172          376            3.396290         3.405299\n",
+       " 351119  2.702502 -14.519994          376            3.394112         3.405299\n",
+       " 351120  2.704204 -14.519814          376            3.391934         3.405299\n",
+       " 351121  2.705906 -14.519798          376            3.389721         3.405299\n",
+       " 351122  2.707608 -14.519798          376            3.387504         3.405299\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 351780  3.827327 -14.525652          376            0.000158         3.405299\n",
+       " 351781  3.829029 -14.525733          376            0.000149         3.405299\n",
+       " 351782  3.830731 -14.525813          376            0.000140         3.405299\n",
+       " 351783  3.832433 -14.525894          376            0.000132         3.405299\n",
+       " 351784  3.834134 -14.525974          376            0.000123         3.405299\n",
+       " \n",
+       " [667 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 352118  2.700801 -14.519972          377            3.396188         3.402017\n",
+       " 352119  2.702502 -14.519823          377            3.393972         3.402017\n",
+       " 352120  2.704204 -14.519675          377            3.391755         3.402017\n",
+       " 352121  2.705906 -14.519610          377            3.389519         3.402017\n",
+       " 352122  2.707608 -14.519756          377            3.387231         3.402017\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 352779  3.825626 -14.524969          377            0.000166         3.402017\n",
+       " 352780  3.827327 -14.525034          377            0.000157         3.402017\n",
+       " 352781  3.829029 -14.525100          377            0.000148         3.402017\n",
+       " 352782  3.830731 -14.525165          377            0.000140         3.402017\n",
+       " 352783  3.832433 -14.525229          377            0.000131         3.402017\n",
+       " \n",
+       " [666 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 353118  2.700801 -14.520181          378            3.393201         3.398252\n",
+       " 353119  2.702502 -14.520019          378            3.391059         3.398252\n",
+       " 353120  2.704204 -14.519856          378            3.388917         3.398252\n",
+       " 353121  2.705906 -14.519703          378            3.386736         3.398252\n",
+       " 353122  2.707608 -14.519555          378            3.384532         3.398252\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 353779  3.825626 -14.525614          378            0.000165         3.398252\n",
+       " 353780  3.827327 -14.525688          378            0.000157         3.398252\n",
+       " 353781  3.829029 -14.525763          378            0.000148         3.398252\n",
+       " 353782  3.830731 -14.525836          378            0.000139         3.398252\n",
+       " 353783  3.832433 -14.525910          378            0.000130         3.398252\n",
+       " \n",
+       " [666 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 354118  2.700801 -14.520027          379            3.389348         3.395686\n",
+       " 354119  2.702502 -14.520027          379            3.387119         3.395686\n",
+       " 354120  2.704204 -14.520027          379            3.384890         3.395686\n",
+       " 354121  2.705906 -14.519997          379            3.382690         3.395686\n",
+       " 354122  2.707608 -14.519924          379            3.380531         3.395686\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 354779  3.825626 -14.524317          379            0.000163         3.395686\n",
+       " 354780  3.827327 -14.524379          379            0.000154         3.395686\n",
+       " 354781  3.829029 -14.524441          379            0.000146         3.395686\n",
+       " 354782  3.830731 -14.524503          379            0.000137         3.395686\n",
+       " 354783  3.832433 -14.524565          379            0.000128         3.395686\n",
+       " \n",
+       " [666 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 355118  2.700801 -14.519654          380            3.386732         3.391647\n",
+       " 355119  2.702502 -14.519783          380            3.384624         3.391647\n",
+       " 355120  2.704204 -14.519710          380            3.382439         3.391647\n",
+       " 355121  2.705906 -14.519637          380            3.380254         3.391647\n",
+       " 355122  2.707608 -14.519569          380            3.378067         3.391647\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 355780  3.827327 -14.524133          380            0.000159         3.391647\n",
+       " 355781  3.829029 -14.524191          380            0.000150         3.391647\n",
+       " 355782  3.830731 -14.524250          380            0.000141         3.391647\n",
+       " 355783  3.832433 -14.524309          380            0.000132         3.391647\n",
+       " 355784  3.834134 -14.524368          380            0.000124         3.391647\n",
+       " \n",
+       " [667 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 356118  2.700801 -14.519887          381            3.386832         3.389576\n",
+       " 356119  2.702502 -14.519587          381            3.384786         3.389576\n",
+       " 356120  2.704204 -14.519381          381            3.382726         3.389576\n",
+       " 356121  2.705906 -14.519603          381            3.380601         3.389576\n",
+       " 356122  2.707608 -14.519824          381            3.378476         3.389576\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 356779  3.825626 -14.525846          381            0.000160         3.389576\n",
+       " 356780  3.827327 -14.525929          381            0.000151         3.389576\n",
+       " 356781  3.829029 -14.526012          381            0.000143         3.389576\n",
+       " 356782  3.830731 -14.526096          381            0.000134         3.389576\n",
+       " 356783  3.832433 -14.526179          381            0.000125         3.389576\n",
+       " \n",
+       " [666 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 357118  2.700801 -14.519798          382            3.381880         3.390167\n",
+       " 357119  2.702502 -14.519798          382            3.379678         3.390167\n",
+       " 357120  2.704204 -14.519910          382            3.377548         3.390167\n",
+       " 357121  2.705906 -14.520056          382            3.375440         3.390167\n",
+       " 357122  2.707608 -14.520201          382            3.373333         3.390167\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 357779  3.825626 -14.526231          382            0.000163         3.390167\n",
+       " 357780  3.827327 -14.526323          382            0.000155         3.390167\n",
+       " 357781  3.829029 -14.526416          382            0.000146         3.390167\n",
+       " 357782  3.830731 -14.526508          382            0.000137         3.390167\n",
+       " 357783  3.832433 -14.526601          382            0.000128         3.390167\n",
+       " \n",
+       " [666 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 358118  2.700801 -14.519798          383            3.379720         3.385878\n",
+       " 358119  2.702502 -14.519708          383            3.377616         3.385878\n",
+       " 358120  2.704204 -14.519560          383            3.375438         3.385878\n",
+       " 358121  2.705906 -14.519411          383            3.373261         3.385878\n",
+       " 358122  2.707608 -14.519497          383            3.371081         3.385878\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 358779  3.825626 -14.525593          383            0.000164         3.385878\n",
+       " 358780  3.827327 -14.525672          383            0.000156         3.385878\n",
+       " 358781  3.829029 -14.525752          383            0.000147         3.385878\n",
+       " 358782  3.830731 -14.525832          383            0.000138         3.385878\n",
+       " 358783  3.832433 -14.525912          383            0.000130         3.385878\n",
+       " \n",
+       " [666 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 359118  2.700801 -14.519842          384            3.378553         3.383767\n",
+       " 359119  2.702502 -14.519937          384            3.376571         3.383767\n",
+       " 359120  2.704204 -14.520023          384            3.374581         3.383767\n",
+       " 359121  2.705906 -14.519949          384            3.372424         3.383767\n",
+       " 359122  2.707608 -14.519874          384            3.370268         3.383767\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 359779  3.825626 -14.525572          384            0.000162         3.383767\n",
+       " 359780  3.827327 -14.525661          384            0.000153         3.383767\n",
+       " 359781  3.829029 -14.525750          384            0.000145         3.383767\n",
+       " 359782  3.830731 -14.525840          384            0.000136         3.383767\n",
+       " 359783  3.832433 -14.525928          384            0.000127         3.383767\n",
+       " \n",
+       " [666 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 360118  2.700801 -14.519951          385            3.377428         3.380884\n",
+       " 360119  2.702502 -14.519810          385            3.375366         3.380884\n",
+       " 360120  2.704204 -14.519956          385            3.373284         3.380884\n",
+       " 360121  2.705906 -14.520102          385            3.371202         3.380884\n",
+       " 360122  2.707608 -14.520247          385            3.369120         3.380884\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 360770  3.810310 -14.519814          385            0.000210         3.380884\n",
+       " 360771  3.812012 -14.519812          385            0.000200         3.380884\n",
+       " 360772  3.813714 -14.519808          385            0.000191         3.380884\n",
+       " 360773  3.815415 -14.519805          385            0.000182         3.380884\n",
+       " 360774  3.817117 -14.519801          385            0.000172         3.380884\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 361118  2.700801 -14.519978          386            3.373587          3.37961\n",
+       " 361119  2.702502 -14.519871          386            3.371507          3.37961\n",
+       " 361120  2.704204 -14.519868          386            3.369413          3.37961\n",
+       " 361121  2.705906 -14.520090          386            3.367287          3.37961\n",
+       " 361122  2.707608 -14.520312          386            3.365162          3.37961\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 361779  3.825626 -14.526243          386            0.000162          3.37961\n",
+       " 361780  3.827327 -14.526336          386            0.000153          3.37961\n",
+       " 361781  3.829029 -14.526428          386            0.000145          3.37961\n",
+       " 361782  3.830731 -14.526521          386            0.000136          3.37961\n",
+       " 361783  3.832433 -14.526613          386            0.000127          3.37961\n",
+       " \n",
+       " [666 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 362118  2.700801 -14.520354          387            3.371616         3.376292\n",
+       " 362119  2.702502 -14.520100          387            3.369569         3.376292\n",
+       " 362120  2.704204 -14.520027          387            3.367485         3.376292\n",
+       " 362121  2.705906 -14.520027          387            3.365386         3.376292\n",
+       " 362122  2.707608 -14.520027          387            3.363286         3.376292\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 362771  3.812012 -14.521091          387            0.000201         3.376292\n",
+       " 362772  3.813714 -14.521111          387            0.000192         3.376292\n",
+       " 362773  3.815415 -14.521131          387            0.000182         3.376292\n",
+       " 362774  3.817117 -14.521151          387            0.000173         3.376292\n",
+       " 362775  3.818819 -14.521171          387            0.000163         3.376292\n",
+       " \n",
+       " [658 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 363118  2.700801 -14.520024          388            3.369075          3.37483\n",
+       " 363119  2.702502 -14.519878          388            3.366993          3.37483\n",
+       " 363120  2.704204 -14.519732          388            3.364911          3.37483\n",
+       " 363121  2.705906 -14.519587          388            3.362829          3.37483\n",
+       " 363122  2.707608 -14.519768          388            3.360728          3.37483\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 363779  3.825626 -14.526316          388            0.000158          3.37483\n",
+       " 363780  3.827327 -14.526402          388            0.000149          3.37483\n",
+       " 363781  3.829029 -14.526487          388            0.000140          3.37483\n",
+       " 363782  3.830731 -14.526574          388            0.000132          3.37483\n",
+       " 363783  3.832433 -14.526660          388            0.000123          3.37483\n",
+       " \n",
+       " [666 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 364118  2.700801 -14.520058          389            3.368463          3.37186\n",
+       " 364119  2.702502 -14.519632          389            3.366463          3.37186\n",
+       " 364120  2.704204 -14.519697          389            3.364341          3.37186\n",
+       " 364121  2.705906 -14.519848          389            3.362198          3.37186\n",
+       " 364122  2.707608 -14.519998          389            3.360055          3.37186\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 364779  3.825626 -14.524770          389            0.000158          3.37186\n",
+       " 364780  3.827327 -14.524840          389            0.000150          3.37186\n",
+       " 364781  3.829029 -14.524911          389            0.000141          3.37186\n",
+       " 364782  3.830731 -14.524981          389            0.000132          3.37186\n",
+       " 364783  3.832433 -14.525052          389            0.000124          3.37186\n",
+       " \n",
+       " [666 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 365118  2.700801 -14.520027          390            3.368785         3.372458\n",
+       " 365119  2.702502 -14.520027          390            3.366960         3.372458\n",
+       " 365120  2.704204 -14.520097          390            3.364864         3.372458\n",
+       " 365121  2.705906 -14.520171          390            3.362752         3.372458\n",
+       " 365122  2.707608 -14.520245          390            3.360640         3.372458\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 365779  3.825626 -14.526078          390            0.000159         3.372458\n",
+       " 365780  3.827327 -14.526164          390            0.000150         3.372458\n",
+       " 365781  3.829029 -14.526251          390            0.000141         3.372458\n",
+       " 365782  3.830731 -14.526337          390            0.000132         3.372458\n",
+       " 365783  3.832433 -14.526423          390            0.000124         3.372458\n",
+       " \n",
+       " [666 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 366118  2.700801 -14.520256          391            3.366136         3.371439\n",
+       " 366119  2.702502 -14.520112          391            3.363994         3.371439\n",
+       " 366120  2.704204 -14.519964          391            3.361843         3.371439\n",
+       " 366121  2.705906 -14.519816          391            3.359692         3.371439\n",
+       " 366122  2.707608 -14.519862          391            3.357635         3.371439\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 366779  3.825626 -14.526714          391            0.000158         3.371439\n",
+       " 366780  3.827327 -14.526813          391            0.000150         3.371439\n",
+       " 366781  3.829029 -14.526911          391            0.000141         3.371439\n",
+       " 366782  3.830731 -14.527010          391            0.000132         3.371439\n",
+       " 366783  3.832433 -14.527108          391            0.000124         3.371439\n",
+       " \n",
+       " [666 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 367118  2.700801 -14.520030          392            3.361655         3.367607\n",
+       " 367119  2.702502 -14.520178          392            3.359647         3.367607\n",
+       " 367120  2.704204 -14.520326          392            3.357639         3.367607\n",
+       " 367121  2.705906 -14.520473          392            3.355632         3.367607\n",
+       " 367122  2.707608 -14.520277          392            3.353560         3.367607\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 367778  3.823924 -14.526443          392            0.000163         3.367607\n",
+       " 367779  3.825626 -14.526538          392            0.000155         3.367607\n",
+       " 367780  3.827327 -14.526633          392            0.000146         3.367607\n",
+       " 367781  3.829029 -14.526728          392            0.000138         3.367607\n",
+       " 367782  3.830731 -14.526823          392            0.000129         3.367607\n",
+       " \n",
+       " [665 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 368118  2.700801 -14.520247          393            3.361237         3.364335\n",
+       " 368119  2.702502 -14.520094          393            3.359142         3.364335\n",
+       " 368120  2.704204 -14.519941          393            3.357048         3.364335\n",
+       " 368121  2.705906 -14.519798          393            3.354954         3.364335\n",
+       " 368122  2.707608 -14.519798          393            3.352872         3.364335\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 368770  3.810310 -14.521728          393            0.000204         3.364335\n",
+       " 368771  3.812012 -14.521757          393            0.000194         3.364335\n",
+       " 368772  3.813714 -14.521788          393            0.000185         3.364335\n",
+       " 368773  3.815415 -14.521817          393            0.000176         3.364335\n",
+       " 368774  3.817117 -14.521848          393            0.000166         3.364335\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 369118  2.700801 -14.519820          394            3.361003          3.36485\n",
+       " 369119  2.702502 -14.519602          394            3.358985          3.36485\n",
+       " 369120  2.704204 -14.519675          394            3.356938          3.36485\n",
+       " 369121  2.705906 -14.519750          394            3.354892          3.36485\n",
+       " 369122  2.707608 -14.519850          394            3.352825          3.36485\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 369779  3.825626 -14.526058          394            0.000158          3.36485\n",
+       " 369780  3.827327 -14.526151          394            0.000149          3.36485\n",
+       " 369781  3.829029 -14.526242          394            0.000141          3.36485\n",
+       " 369782  3.830731 -14.526335          394            0.000132          3.36485\n",
+       " 369783  3.832433 -14.526426          394            0.000123          3.36485\n",
+       " \n",
+       " [666 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 370118  2.700801 -14.520191          395            3.361437         3.365335\n",
+       " 370119  2.702502 -14.520449          395            3.359426         3.365335\n",
+       " 370120  2.704204 -14.520230          395            3.357447         3.365335\n",
+       " 370121  2.705906 -14.520011          395            3.355468         3.365335\n",
+       " 370122  2.707608 -14.519800          395            3.353487         3.365335\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 370779  3.825626 -14.525633          395            0.000158         3.365335\n",
+       " 370780  3.827327 -14.525717          395            0.000150         3.365335\n",
+       " 370781  3.829029 -14.525800          395            0.000141         3.365335\n",
+       " 370782  3.830731 -14.525883          395            0.000132         3.365335\n",
+       " 370783  3.832433 -14.525966          395            0.000124         3.365335\n",
+       " \n",
+       " [666 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 371118  2.700801 -14.519912          396            3.357666         3.362919\n",
+       " 371119  2.702502 -14.520155          396            3.355696         3.362919\n",
+       " 371120  2.704204 -14.520398          396            3.353725         3.362919\n",
+       " 371121  2.705906 -14.520295          396            3.351689         3.362919\n",
+       " 371122  2.707608 -14.520000          396            3.349616         3.362919\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 371770  3.810310 -14.520869          396            0.000204         3.362919\n",
+       " 371771  3.812012 -14.520885          396            0.000195         3.362919\n",
+       " 371772  3.813714 -14.520902          396            0.000186         3.362919\n",
+       " 371773  3.815415 -14.520919          396            0.000176         3.362919\n",
+       " 371774  3.817117 -14.520935          396            0.000167         3.362919\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 372118  2.700801 -14.519534          397            3.355529         3.360627\n",
+       " 372119  2.702502 -14.519460          397            3.353557         3.360627\n",
+       " 372120  2.704204 -14.519384          397            3.351586         3.360627\n",
+       " 372121  2.705906 -14.519495          397            3.349578         3.360627\n",
+       " 372122  2.707608 -14.519865          397            3.347518         3.360627\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 372779  3.825626 -14.526513          397            0.000157         3.360627\n",
+       " 372780  3.827327 -14.526608          397            0.000148         3.360627\n",
+       " 372781  3.829029 -14.526703          397            0.000140         3.360627\n",
+       " 372782  3.830731 -14.526797          397            0.000131         3.360627\n",
+       " 372783  3.832433 -14.526893          397            0.000123         3.360627\n",
+       " \n",
+       " [666 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 373118  2.700801 -14.520067          398            3.355953         3.358033\n",
+       " 373119  2.702502 -14.520154          398            3.353940         3.358033\n",
+       " 373120  2.704204 -14.520241          398            3.351928         3.358033\n",
+       " 373121  2.705906 -14.520136          398            3.349900         3.358033\n",
+       " 373122  2.707608 -14.519991          398            3.347870         3.358033\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 373779  3.825626 -14.525660          398            0.000157         3.358033\n",
+       " 373780  3.827327 -14.525739          398            0.000148         3.358033\n",
+       " 373781  3.829029 -14.525818          398            0.000140         3.358033\n",
+       " 373782  3.830731 -14.525898          398            0.000131         3.358033\n",
+       " 373783  3.832433 -14.525977          398            0.000123         3.358033\n",
+       " \n",
+       " [666 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 374118  2.700801 -14.520066          399            3.353058          3.35902\n",
+       " 374119  2.702502 -14.520144          399            3.351081          3.35902\n",
+       " 374120  2.704204 -14.520222          399            3.349105          3.35902\n",
+       " 374121  2.705906 -14.520176          399            3.347063          3.35902\n",
+       " 374122  2.707608 -14.520030          399            3.344968          3.35902\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 374770  3.810310 -14.521511          399            0.000205          3.35902\n",
+       " 374771  3.812012 -14.521538          399            0.000195          3.35902\n",
+       " 374772  3.813714 -14.521564          399            0.000186          3.35902\n",
+       " 374773  3.815415 -14.521590          399            0.000176          3.35902\n",
+       " 374774  3.817117 -14.521617          399            0.000167          3.35902\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 375118  2.700801 -14.519942          400            3.351454         3.357277\n",
+       " 375119  2.702502 -14.520252          400            3.349655         3.357277\n",
+       " 375120  2.704204 -14.520108          400            3.347621         3.357277\n",
+       " 375121  2.705906 -14.519958          400            3.345584         3.357277\n",
+       " 375122  2.707608 -14.519808          400            3.343546         3.357277\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 375779  3.825626 -14.526967          400            0.000157         3.357277\n",
+       " 375780  3.827327 -14.527061          400            0.000149         3.357277\n",
+       " 375781  3.829029 -14.527157          400            0.000140         3.357277\n",
+       " 375782  3.830731 -14.527251          400            0.000132         3.357277\n",
+       " 375783  3.832433 -14.527346          400            0.000123         3.357277\n",
+       " \n",
+       " [666 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 376118  2.700801 -14.519569          401            3.352616          3.35549\n",
+       " 376119  2.702502 -14.520189          401            3.350674          3.35549\n",
+       " 376120  2.704204 -14.519967          401            3.348640          3.35549\n",
+       " 376121  2.705906 -14.519746          401            3.346606          3.35549\n",
+       " 376122  2.707608 -14.519585          401            3.344569          3.35549\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 376779  3.825626 -14.524967          401            0.000162          3.35549\n",
+       " 376780  3.827327 -14.525038          401            0.000154          3.35549\n",
+       " 376781  3.829029 -14.525108          401            0.000145          3.35549\n",
+       " 376782  3.830731 -14.525179          401            0.000136          3.35549\n",
+       " 376783  3.832433 -14.525249          401            0.000128          3.35549\n",
+       " \n",
+       " [666 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 377118  2.700801 -14.520120          402            3.350007         3.354176\n",
+       " 377119  2.702502 -14.519829          402            3.348130         3.354176\n",
+       " 377120  2.704204 -14.519798          402            3.346187         3.354176\n",
+       " 377121  2.705906 -14.519798          402            3.344236         3.354176\n",
+       " 377122  2.707608 -14.519798          402            3.342284         3.354176\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 377778  3.823924 -14.524934          402            0.000164         3.354176\n",
+       " 377779  3.825626 -14.525007          402            0.000156         3.354176\n",
+       " 377780  3.827327 -14.525081          402            0.000147         3.354176\n",
+       " 377781  3.829029 -14.525154          402            0.000139         3.354176\n",
+       " 377782  3.830731 -14.525227          402            0.000130         3.354176\n",
+       " \n",
+       " [665 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 378118  2.700801 -14.520170          403            3.349037         3.353866\n",
+       " 378119  2.702502 -14.520003          403            3.347164         3.353866\n",
+       " 378120  2.704204 -14.519835          403            3.345291         3.353866\n",
+       " 378121  2.705906 -14.519739          403            3.343267         3.353866\n",
+       " 378122  2.707608 -14.519663          403            3.341199         3.353866\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 378779  3.825626 -14.524960          403            0.000163         3.353866\n",
+       " 378780  3.827327 -14.525029          403            0.000155         3.353866\n",
+       " 378781  3.829029 -14.525100          403            0.000146         3.353866\n",
+       " 378782  3.830731 -14.525170          403            0.000137         3.353866\n",
+       " 378783  3.832433 -14.525240          403            0.000129         3.353866\n",
+       " \n",
+       " [666 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 379118  2.700801 -14.520210          404            3.345453         3.351584\n",
+       " 379119  2.702502 -14.520112          404            3.343584         3.351584\n",
+       " 379120  2.704204 -14.520038          404            3.341682         3.351584\n",
+       " 379121  2.705906 -14.520112          404            3.339566         3.351584\n",
+       " 379122  2.707608 -14.520187          404            3.337449         3.351584\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 379779  3.825626 -14.526273          404            0.000159         3.351584\n",
+       " 379780  3.827327 -14.526364          404            0.000151         3.351584\n",
+       " 379781  3.829029 -14.526456          404            0.000142         3.351584\n",
+       " 379782  3.830731 -14.526547          404            0.000134         3.351584\n",
+       " 379783  3.832433 -14.526639          404            0.000125         3.351584\n",
+       " \n",
+       " [666 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 380118  2.700801 -14.520148          405            3.343895          3.34805\n",
+       " 380119  2.702502 -14.519916          405            3.341973          3.34805\n",
+       " 380120  2.704204 -14.519870          405            3.340004          3.34805\n",
+       " 380121  2.705906 -14.520016          405            3.337986          3.34805\n",
+       " 380122  2.707608 -14.520162          405            3.335969          3.34805\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 380779  3.825626 -14.526285          405            0.000159          3.34805\n",
+       " 380780  3.827327 -14.526374          405            0.000151          3.34805\n",
+       " 380781  3.829029 -14.526463          405            0.000142          3.34805\n",
+       " 380782  3.830731 -14.526551          405            0.000134          3.34805\n",
+       " 380783  3.832433 -14.526640          405            0.000125          3.34805\n",
+       " \n",
+       " [666 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 381118  2.700801 -14.520302          406            3.345042         3.347249\n",
+       " 381119  2.702502 -14.519909          406            3.343242         3.347249\n",
+       " 381120  2.704204 -14.519798          406            3.341305         3.347249\n",
+       " 381121  2.705906 -14.519798          406            3.339313         3.347249\n",
+       " 381122  2.707608 -14.519798          406            3.337321         3.347249\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 381778  3.823924 -14.525998          406            0.000165         3.347249\n",
+       " 381779  3.825626 -14.526086          406            0.000156         3.347249\n",
+       " 381780  3.827327 -14.526175          406            0.000148         3.347249\n",
+       " 381781  3.829029 -14.526262          406            0.000139         3.347249\n",
+       " 381782  3.830731 -14.526350          406            0.000131         3.347249\n",
+       " \n",
+       " [665 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 382118  2.700801 -14.520256          407            3.344645         3.348605\n",
+       " 382119  2.702502 -14.520256          407            3.342687         3.348605\n",
+       " 382120  2.704204 -14.520053          407            3.340747         3.348605\n",
+       " 382121  2.705906 -14.519837          407            3.338809         3.348605\n",
+       " 382122  2.707608 -14.519622          407            3.336870         3.348605\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 382779  3.825626 -14.526061          407            0.000158         3.348605\n",
+       " 382780  3.827327 -14.526153          407            0.000149         3.348605\n",
+       " 382781  3.829029 -14.526243          407            0.000141         3.348605\n",
+       " 382782  3.830731 -14.526335          407            0.000132         3.348605\n",
+       " 382783  3.832433 -14.526426          407            0.000123         3.348605\n",
+       " \n",
+       " [666 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 383118  2.700801 -14.520070          408            3.343925         3.348857\n",
+       " 383119  2.702502 -14.520161          408            3.341982         3.348857\n",
+       " 383120  2.704204 -14.520252          408            3.340038         3.348857\n",
+       " 383121  2.705906 -14.520044          408            3.337983         3.348857\n",
+       " 383122  2.707608 -14.519822          408            3.335923         3.348857\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 383779  3.825626 -14.526752          408            0.000157         3.348857\n",
+       " 383780  3.827327 -14.526843          408            0.000149         3.348857\n",
+       " 383781  3.829029 -14.526935          408            0.000140         3.348857\n",
+       " 383782  3.830731 -14.527025          408            0.000132         3.348857\n",
+       " 383783  3.832433 -14.527117          408            0.000123         3.348857\n",
+       " \n",
+       " [666 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 384118  2.700801 -14.519798          409            3.341964         3.347035\n",
+       " 384119  2.702502 -14.519856          409            3.340019         3.347035\n",
+       " 384120  2.704204 -14.520007          409            3.338021         3.347035\n",
+       " 384121  2.705906 -14.520157          409            3.336024         3.347035\n",
+       " 384122  2.707608 -14.520206          409            3.334041         3.347035\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 384779  3.825626 -14.525858          409            0.000158         3.347035\n",
+       " 384780  3.827327 -14.525943          409            0.000149         3.347035\n",
+       " 384781  3.829029 -14.526028          409            0.000140         3.347035\n",
+       " 384782  3.830731 -14.526114          409            0.000132         3.347035\n",
+       " 384783  3.832433 -14.526198          409            0.000123         3.347035\n",
+       " \n",
+       " [666 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 385118  2.700801 -14.519798          410            3.338775         3.342911\n",
+       " 385119  2.702502 -14.519810          410            3.336935         3.342911\n",
+       " 385120  2.704204 -14.519958          410            3.334940         3.342911\n",
+       " 385121  2.705906 -14.520105          410            3.332946         3.342911\n",
+       " 385122  2.707608 -14.520253          410            3.330951         3.342911\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 385770  3.810310 -14.521527          410            0.000204         3.342911\n",
+       " 385771  3.812012 -14.521551          410            0.000195         3.342911\n",
+       " 385772  3.813714 -14.521574          410            0.000185         3.342911\n",
+       " 385773  3.815415 -14.521597          410            0.000176         3.342911\n",
+       " 385774  3.817117 -14.521620          410            0.000167         3.342911\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 386118  2.700801 -14.520027          411            3.338429         3.340808\n",
+       " 386119  2.702502 -14.520027          411            3.336513         3.340808\n",
+       " 386120  2.704204 -14.520027          411            3.334560         3.340808\n",
+       " 386121  2.705906 -14.520027          411            3.332606         3.340808\n",
+       " 386122  2.707608 -14.520002          411            3.330649         3.340808\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 386770  3.810310 -14.520661          411            0.000200         3.340808\n",
+       " 386771  3.812012 -14.520675          411            0.000191         3.340808\n",
+       " 386772  3.813714 -14.520687          411            0.000181         3.340808\n",
+       " 386773  3.815415 -14.520700          411            0.000172         3.340808\n",
+       " 386774  3.817117 -14.520714          411            0.000163         3.340808\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 387118  2.700801 -14.519875          412            3.333949         3.341691\n",
+       " 387119  2.702502 -14.520040          412            3.331976         3.341691\n",
+       " 387120  2.704204 -14.520205          412            3.330003         3.341691\n",
+       " 387121  2.705906 -14.520155          412            3.328006         3.341691\n",
+       " 387122  2.707608 -14.520006          412            3.325998         3.341691\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 387769  3.808609 -14.519782          412            0.000208         3.341691\n",
+       " 387770  3.810310 -14.519786          412            0.000198         3.341691\n",
+       " 387771  3.812012 -14.519789          412            0.000189         3.341691\n",
+       " 387772  3.813714 -14.519793          412            0.000180         3.341691\n",
+       " 387773  3.815415 -14.519795          412            0.000170         3.341691\n",
+       " \n",
+       " [656 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 388118  2.700801 -14.519985          413            3.335232          3.33908\n",
+       " 388119  2.702502 -14.519836          413            3.333263          3.33908\n",
+       " 388120  2.704204 -14.519689          413            3.331295          3.33908\n",
+       " 388121  2.705906 -14.519598          413            3.329326          3.33908\n",
+       " 388122  2.707608 -14.519746          413            3.327358          3.33908\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 388778  3.823924 -14.524345          413            0.000163          3.33908\n",
+       " 388779  3.825626 -14.524400          413            0.000155          3.33908\n",
+       " 388780  3.827327 -14.524455          413            0.000146          3.33908\n",
+       " 388781  3.829029 -14.524509          413            0.000137          3.33908\n",
+       " 388782  3.830731 -14.524564          413            0.000129          3.33908\n",
+       " \n",
+       " [665 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 389118  2.700801 -14.520062          414            3.333329         3.337714\n",
+       " 389119  2.702502 -14.520139          414            3.331409         3.337714\n",
+       " 389120  2.704204 -14.520215          414            3.329489         3.337714\n",
+       " 389121  2.705906 -14.520155          414            3.327565         3.337714\n",
+       " 389122  2.707608 -14.519937          414            3.325637         3.337714\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 389778  3.823924 -14.524718          414            0.000163         3.337714\n",
+       " 389779  3.825626 -14.524791          414            0.000154         3.337714\n",
+       " 389780  3.827327 -14.524863          414            0.000146         3.337714\n",
+       " 389781  3.829029 -14.524936          414            0.000137         3.337714\n",
+       " 389782  3.830731 -14.525008          414            0.000129         3.337714\n",
+       " \n",
+       " [665 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 390118  2.700801 -14.520027          415            3.328967         3.334725\n",
+       " 390119  2.702502 -14.520027          415            3.327035         3.334725\n",
+       " 390120  2.704204 -14.520027          415            3.325103         3.334725\n",
+       " 390121  2.705906 -14.519974          415            3.323137         3.334725\n",
+       " 390122  2.707608 -14.519901          415            3.321158         3.334725\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 390778  3.823924 -14.525004          415            0.000159         3.334725\n",
+       " 390779  3.825626 -14.525071          415            0.000151         3.334725\n",
+       " 390780  3.827327 -14.525138          415            0.000142         3.334725\n",
+       " 390781  3.829029 -14.525205          415            0.000134         3.334725\n",
+       " 390782  3.830731 -14.525271          415            0.000125         3.334725\n",
+       " \n",
+       " [665 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 391118  2.700801 -14.519610          416            3.327981         3.331922\n",
+       " 391119  2.702502 -14.519754          416            3.326042         3.331922\n",
+       " 391120  2.704204 -14.519898          416            3.324104         3.331922\n",
+       " 391121  2.705906 -14.520012          416            3.322166         3.331922\n",
+       " 391122  2.707608 -14.519866          416            3.320239         3.331922\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 391778  3.823924 -14.526453          416            0.000164         3.331922\n",
+       " 391779  3.825626 -14.526544          416            0.000155         3.331922\n",
+       " 391780  3.827327 -14.526635          416            0.000147         3.331922\n",
+       " 391781  3.829029 -14.526727          416            0.000138         3.331922\n",
+       " 391782  3.830731 -14.526817          416            0.000130         3.331922\n",
+       " \n",
+       " [665 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 392118  2.700801 -14.520040          417            3.328157         3.329977\n",
+       " 392119  2.702502 -14.519576          417            3.326303         3.329977\n",
+       " 392120  2.704204 -14.519643          417            3.324362         3.329977\n",
+       " 392121  2.705906 -14.519716          417            3.322419         3.329977\n",
+       " 392122  2.707608 -14.519791          417            3.320476         3.329977\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 392778  3.823924 -14.525215          417            0.000158         3.329977\n",
+       " 392779  3.825626 -14.525288          417            0.000150         3.329977\n",
+       " 392780  3.827327 -14.525360          417            0.000141         3.329977\n",
+       " 392781  3.829029 -14.525433          417            0.000133         3.329977\n",
+       " 392782  3.830731 -14.525505          417            0.000124         3.329977\n",
+       " \n",
+       " [665 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 393118  2.700801 -14.519732          418            3.324416         3.330929\n",
+       " 393119  2.702502 -14.520080          418            3.322413         3.330929\n",
+       " 393120  2.704204 -14.520185          418            3.320447         3.330929\n",
+       " 393121  2.705906 -14.520041          418            3.318521         3.330929\n",
+       " 393122  2.707608 -14.519897          418            3.316596         3.330929\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 393769  3.808609 -14.520685          418            0.000203         3.330929\n",
+       " 393770  3.810310 -14.520692          418            0.000194         3.330929\n",
+       " 393771  3.812012 -14.520699          418            0.000185         3.330929\n",
+       " 393772  3.813714 -14.520705          418            0.000176         3.330929\n",
+       " 393773  3.815415 -14.520711          418            0.000166         3.330929\n",
+       " \n",
+       " [656 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 394118  2.700801 -14.519798          419            3.322593         3.328279\n",
+       " 394119  2.702502 -14.519798          419            3.320660         3.328279\n",
+       " 394120  2.704204 -14.519798          419            3.318683         3.328279\n",
+       " 394121  2.705906 -14.519798          419            3.316706         3.328279\n",
+       " 394122  2.707608 -14.519833          419            3.314729         3.328279\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 394769  3.808609 -14.522172          419            0.000204         3.328279\n",
+       " 394770  3.810310 -14.522204          419            0.000194         3.328279\n",
+       " 394771  3.812012 -14.522237          419            0.000185         3.328279\n",
+       " 394772  3.813714 -14.522269          419            0.000176         3.328279\n",
+       " 394773  3.815415 -14.522303          419            0.000167         3.328279\n",
+       " \n",
+       " [656 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 395118  2.700801 -14.519953          420            3.323181         3.326715\n",
+       " 395119  2.702502 -14.519798          420            3.321379         3.326715\n",
+       " 395120  2.704204 -14.519798          420            3.319491         3.326715\n",
+       " 395121  2.705906 -14.519798          420            3.317603         3.326715\n",
+       " 395122  2.707608 -14.519798          420            3.315715         3.326715\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 395778  3.823924 -14.525846          420            0.000160         3.326715\n",
+       " 395779  3.825626 -14.525927          420            0.000152         3.326715\n",
+       " 395780  3.827327 -14.526009          420            0.000143         3.326715\n",
+       " 395781  3.829029 -14.526090          420            0.000135         3.326715\n",
+       " 395782  3.830731 -14.526172          420            0.000126         3.326715\n",
+       " \n",
+       " [665 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 396118  2.700801 -14.520071          421            3.322261         3.327815\n",
+       " 396119  2.702502 -14.519569          421            3.320341         3.327815\n",
+       " 396120  2.704204 -14.519569          421            3.318466         3.327815\n",
+       " 396121  2.705906 -14.519569          421            3.316592         3.327815\n",
+       " 396122  2.707608 -14.519600          421            3.314696         3.327815\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 396778  3.823924 -14.524553          421            0.000160         3.327815\n",
+       " 396779  3.825626 -14.524617          421            0.000152         3.327815\n",
+       " 396780  3.827327 -14.524680          421            0.000143         3.327815\n",
+       " 396781  3.829029 -14.524743          421            0.000135         3.327815\n",
+       " 396782  3.830731 -14.524806          421            0.000126         3.327815\n",
+       " \n",
+       " [665 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 397118  2.700801 -14.520134          422            3.320656         3.323435\n",
+       " 397119  2.702502 -14.519873          422            3.318718         3.323435\n",
+       " 397120  2.704204 -14.519798          422            3.316788         3.323435\n",
+       " 397121  2.705906 -14.519798          422            3.314860         3.323435\n",
+       " 397122  2.707608 -14.519798          422            3.312932         3.323435\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 397778  3.823924 -14.526492          422            0.000159         3.323435\n",
+       " 397779  3.825626 -14.526586          422            0.000151         3.323435\n",
+       " 397780  3.827327 -14.526679          422            0.000142         3.323435\n",
+       " 397781  3.829029 -14.526772          422            0.000134         3.323435\n",
+       " 397782  3.830731 -14.526866          422            0.000125         3.323435\n",
+       " \n",
+       " [665 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 398118  2.700801 -14.520205          423            3.318386         3.323633\n",
+       " 398119  2.702502 -14.520097          423            3.316510         3.323633\n",
+       " 398120  2.704204 -14.520001          423            3.314630         3.323633\n",
+       " 398121  2.705906 -14.519930          423            3.312742         3.323633\n",
+       " 398122  2.707608 -14.519857          423            3.310854         3.323633\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 398778  3.823924 -14.525188          423            0.000160         3.323633\n",
+       " 398779  3.825626 -14.525264          423            0.000151         3.323633\n",
+       " 398780  3.827327 -14.525339          423            0.000143         3.323633\n",
+       " 398781  3.829029 -14.525415          423            0.000134         3.323633\n",
+       " 398782  3.830731 -14.525491          423            0.000126         3.323633\n",
+       " \n",
+       " [665 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 399118  2.700801 -14.520219          424            3.316178          3.32099\n",
+       " 399119  2.702502 -14.520139          424            3.314238          3.32099\n",
+       " 399120  2.704204 -14.520060          424            3.312299          3.32099\n",
+       " 399121  2.705906 -14.519895          424            3.310373          3.32099\n",
+       " 399122  2.707608 -14.519672          424            3.308456          3.32099\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 399778  3.823924 -14.526256          424            0.000162          3.32099\n",
+       " 399779  3.825626 -14.526343          424            0.000154          3.32099\n",
+       " 399780  3.827327 -14.526432          424            0.000145          3.32099\n",
+       " 399781  3.829029 -14.526520          424            0.000137          3.32099\n",
+       " 399782  3.830731 -14.526608          424            0.000128          3.32099\n",
+       " \n",
+       " [665 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 400118  2.700801 -14.519874          425            3.314711         3.317875\n",
+       " 400119  2.702502 -14.520036          425            3.312826         3.317875\n",
+       " 400120  2.704204 -14.520198          425            3.310941         3.317875\n",
+       " 400121  2.705906 -14.520114          425            3.309045         3.317875\n",
+       " 400122  2.707608 -14.519892          425            3.307141         3.317875\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 400769  3.808609 -14.520668          425            0.000206         3.317875\n",
+       " 400770  3.810310 -14.520679          425            0.000196         3.317875\n",
+       " 400771  3.812012 -14.520688          425            0.000187         3.317875\n",
+       " 400772  3.813714 -14.520698          425            0.000178         3.317875\n",
+       " 400773  3.815415 -14.520707          425            0.000169         3.317875\n",
+       " \n",
+       " [656 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 401118  2.700801 -14.520255          426            3.315031         3.317477\n",
+       " 401119  2.702502 -14.520181          426            3.313102         3.317477\n",
+       " 401120  2.704204 -14.520106          426            3.311172         3.317477\n",
+       " 401121  2.705906 -14.520033          426            3.309242         3.317477\n",
+       " 401122  2.707608 -14.519958          426            3.307253         3.317477\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 401778  3.823924 -14.523483          426            0.000157         3.317477\n",
+       " 401779  3.825626 -14.523535          426            0.000148         3.317477\n",
+       " 401780  3.827327 -14.523585          426            0.000140         3.317477\n",
+       " 401781  3.829029 -14.523637          426            0.000131         3.317477\n",
+       " 401782  3.830731 -14.523688          426            0.000123         3.317477\n",
+       " \n",
+       " [665 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 402118  2.700801 -14.520243          427            3.310627         3.318146\n",
+       " 402119  2.702502 -14.520023          427            3.308661         3.318146\n",
+       " 402120  2.704204 -14.519805          427            3.306694         3.318146\n",
+       " 402121  2.705906 -14.519586          427            3.304728         3.318146\n",
+       " 402122  2.707608 -14.519843          427            3.302820         3.318146\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 402778  3.823924 -14.523243          427            0.000158         3.318146\n",
+       " 402779  3.825626 -14.523294          427            0.000150         3.318146\n",
+       " 402780  3.827327 -14.523345          427            0.000142         3.318146\n",
+       " 402781  3.829029 -14.523396          427            0.000133         3.318146\n",
+       " 402782  3.830731 -14.523448          427            0.000125         3.318146\n",
+       " \n",
+       " [665 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 403118  2.700801 -14.519679          428            3.309992         3.313874\n",
+       " 403119  2.702502 -14.519630          428            3.308020         3.313874\n",
+       " 403120  2.704204 -14.519704          428            3.306015         3.313874\n",
+       " 403121  2.705906 -14.519776          428            3.304011         3.313874\n",
+       " 403122  2.707608 -14.519850          428            3.302015         3.313874\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 403769  3.808609 -14.521524          428            0.000205         3.313874\n",
+       " 403770  3.810310 -14.521547          428            0.000196         3.313874\n",
+       " 403771  3.812012 -14.521570          428            0.000187         3.313874\n",
+       " 403772  3.813714 -14.521593          428            0.000177         3.313874\n",
+       " 403773  3.815415 -14.521616          428            0.000168         3.313874\n",
+       " \n",
+       " [656 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 404118  2.700801 -14.520153          429            3.310472         3.314217\n",
+       " 404119  2.702502 -14.519963          429            3.308660         3.314217\n",
+       " 404120  2.704204 -14.519814          429            3.306731         3.314217\n",
+       " 404121  2.705906 -14.519667          429            3.304801         3.314217\n",
+       " 404122  2.707608 -14.519569          429            3.302855         3.314217\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 404778  3.823924 -14.525581          429            0.000161         3.314217\n",
+       " 404779  3.825626 -14.525668          429            0.000153         3.314217\n",
+       " 404780  3.827327 -14.525755          429            0.000144         3.314217\n",
+       " 404781  3.829029 -14.525842          429            0.000136         3.314217\n",
+       " 404782  3.830731 -14.525928          429            0.000127         3.314217\n",
+       " \n",
+       " [665 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 405118  2.700801 -14.519640          430            3.311258         3.314974\n",
+       " 405119  2.702502 -14.519569          430            3.309361         3.314974\n",
+       " 405120  2.704204 -14.519569          430            3.307408         3.314974\n",
+       " 405121  2.705906 -14.519569          430            3.305454         3.314974\n",
+       " 405122  2.707608 -14.519667          430            3.303474         3.314974\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 405778  3.823924 -14.525181          430            0.000162         3.314974\n",
+       " 405779  3.825626 -14.525252          430            0.000154         3.314974\n",
+       " 405780  3.827327 -14.525325          430            0.000145         3.314974\n",
+       " 405781  3.829029 -14.525397          430            0.000137         3.314974\n",
+       " 405782  3.830731 -14.525470          430            0.000128         3.314974\n",
+       " \n",
+       " [665 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 406118  2.700801 -14.519798          431            3.307653         3.313093\n",
+       " 406119  2.702502 -14.519798          431            3.305686         3.313093\n",
+       " 406120  2.704204 -14.519798          431            3.303733         3.313093\n",
+       " 406121  2.705906 -14.519798          431            3.301779         3.313093\n",
+       " 406122  2.707608 -14.519798          431            3.299827         3.313093\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 406778  3.823924 -14.525587          431            0.000159         3.313093\n",
+       " 406779  3.825626 -14.525678          431            0.000151         3.313093\n",
+       " 406780  3.827327 -14.525767          431            0.000142         3.313093\n",
+       " 406781  3.829029 -14.525857          431            0.000134         3.313093\n",
+       " 406782  3.830731 -14.525948          431            0.000125         3.313093\n",
+       " \n",
+       " [665 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 407118  2.700801 -14.520288          432            3.305687         3.309566\n",
+       " 407119  2.702502 -14.520394          432            3.303846         3.309566\n",
+       " 407120  2.704204 -14.520247          432            3.301864         3.309566\n",
+       " 407121  2.705906 -14.520098          432            3.299882         3.309566\n",
+       " 407122  2.707608 -14.520027          432            3.297908         3.309566\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 407778  3.823924 -14.526050          432            0.000159         3.309566\n",
+       " 407779  3.825626 -14.526139          432            0.000150         3.309566\n",
+       " 407780  3.827327 -14.526229          432            0.000142         3.309566\n",
+       " 407781  3.829029 -14.526320          432            0.000133         3.309566\n",
+       " 407782  3.830731 -14.526409          432            0.000125         3.309566\n",
+       " \n",
+       " [665 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 408118  2.700801 -14.519798          433            3.304564         3.308431\n",
+       " 408119  2.702502 -14.519798          433            3.302543         3.308431\n",
+       " 408120  2.704204 -14.519798          433            3.300522         3.308431\n",
+       " 408121  2.705906 -14.519798          433            3.298502         3.308431\n",
+       " 408122  2.707608 -14.519798          433            3.296591         3.308431\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 408778  3.823924 -14.525182          433            0.000159         3.308431\n",
+       " 408779  3.825626 -14.525260          433            0.000151         3.308431\n",
+       " 408780  3.827327 -14.525337          433            0.000142         3.308431\n",
+       " 408781  3.829029 -14.525415          433            0.000134         3.308431\n",
+       " 408782  3.830731 -14.525494          433            0.000125         3.308431\n",
+       " \n",
+       " [665 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 409118  2.700801 -14.519573          434            3.303979         3.308265\n",
+       " 409119  2.702502 -14.519792          434            3.302013         3.308265\n",
+       " 409120  2.704204 -14.520011          434            3.300047         3.308265\n",
+       " 409121  2.705906 -14.520229          434            3.298080         3.308265\n",
+       " 409122  2.707608 -14.520128          434            3.296148         3.308265\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 409778  3.823924 -14.526690          434            0.000161         3.308265\n",
+       " 409779  3.825626 -14.526785          434            0.000152         3.308265\n",
+       " 409780  3.827327 -14.526881          434            0.000144         3.308265\n",
+       " 409781  3.829029 -14.526977          434            0.000135         3.308265\n",
+       " 409782  3.830731 -14.527073          434            0.000127         3.308265\n",
+       " \n",
+       " [665 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 410118  2.700801 -14.520171          435            3.300832         3.305298\n",
+       " 410119  2.702502 -14.519989          435            3.298936         3.305298\n",
+       " 410120  2.704204 -14.519807          435            3.297040         3.305298\n",
+       " 410121  2.705906 -14.519659          435            3.295077         3.305298\n",
+       " 410122  2.707608 -14.519513          435            3.293111         3.305298\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 410777  3.822222 -14.524937          435            0.000164         3.305298\n",
+       " 410778  3.823924 -14.525008          435            0.000156         3.305298\n",
+       " 410779  3.825626 -14.525081          435            0.000147         3.305298\n",
+       " 410780  3.827327 -14.525152          435            0.000139         3.305298\n",
+       " 410781  3.829029 -14.525224          435            0.000130         3.305298\n",
+       " \n",
+       " [664 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 411118  2.700801 -14.520027          436            3.297583         3.302336\n",
+       " 411119  2.702502 -14.520027          436            3.295640         3.302336\n",
+       " 411120  2.704204 -14.520027          436            3.293695         3.302336\n",
+       " 411121  2.705906 -14.520027          436            3.291744         3.302336\n",
+       " 411122  2.707608 -14.520027          436            3.289792         3.302336\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 411777  3.822222 -14.525167          436            0.000162         3.302336\n",
+       " 411778  3.823924 -14.525243          436            0.000154         3.302336\n",
+       " 411779  3.825626 -14.525317          436            0.000145         3.302336\n",
+       " 411780  3.827327 -14.525393          436            0.000137         3.302336\n",
+       " 411781  3.829029 -14.525467          436            0.000128         3.302336\n",
+       " \n",
+       " [664 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 412118  2.700801 -14.519798          437            3.298065         3.301705\n",
+       " 412119  2.702502 -14.519798          437            3.296203         3.301705\n",
+       " 412120  2.704204 -14.519798          437            3.294342         3.301705\n",
+       " 412121  2.705906 -14.519862          437            3.292388         3.301705\n",
+       " 412122  2.707608 -14.519937          437            3.290419         3.301705\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 412777  3.822222 -14.526469          437            0.000164         3.301705\n",
+       " 412778  3.823924 -14.526556          437            0.000155         3.301705\n",
+       " 412779  3.825626 -14.526643          437            0.000147         3.301705\n",
+       " 412780  3.827327 -14.526730          437            0.000138         3.301705\n",
+       " 412781  3.829029 -14.526816          437            0.000130         3.301705\n",
+       " \n",
+       " [664 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 413118  2.700801 -14.519841          438            3.297161         3.301318\n",
+       " 413119  2.702502 -14.519932          438            3.295266         3.301318\n",
+       " 413120  2.704204 -14.520023          438            3.293370         3.301318\n",
+       " 413121  2.705906 -14.519821          438            3.291458         3.301318\n",
+       " 413122  2.707608 -14.519606          438            3.289545         3.301318\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 413777  3.822222 -14.526244          438            0.000163         3.301318\n",
+       " 413778  3.823924 -14.526331          438            0.000155         3.301318\n",
+       " 413779  3.825626 -14.526418          438            0.000147         3.301318\n",
+       " 413780  3.827327 -14.526505          438            0.000138         3.301318\n",
+       " 413781  3.829029 -14.526591          438            0.000130         3.301318\n",
+       " \n",
+       " [664 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 414118  2.700801 -14.520119          439            3.297142         3.300527\n",
+       " 414119  2.702502 -14.520298          439            3.295295         3.300527\n",
+       " 414120  2.704204 -14.520477          439            3.293449         3.300527\n",
+       " 414121  2.705906 -14.520276          439            3.291524         3.300527\n",
+       " 414122  2.707608 -14.520057          439            3.289597         3.300527\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 414769  3.808609 -14.520632          439            0.000202         3.300527\n",
+       " 414770  3.810310 -14.520651          439            0.000192         3.300527\n",
+       " 414771  3.812012 -14.520670          439            0.000183         3.300527\n",
+       " 414772  3.813714 -14.520690          439            0.000174         3.300527\n",
+       " 414773  3.815415 -14.520709          439            0.000165         3.300527\n",
+       " \n",
+       " [656 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 415118  2.700801 -14.519798          440            3.294706          3.29915\n",
+       " 415119  2.702502 -14.519862          440            3.292839          3.29915\n",
+       " 415120  2.704204 -14.519934          440            3.290964          3.29915\n",
+       " 415121  2.705906 -14.520005          440            3.289089          3.29915\n",
+       " 415122  2.707608 -14.519923          440            3.287185          3.29915\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 415769  3.808609 -14.520441          440            0.000204          3.29915\n",
+       " 415770  3.810310 -14.520451          440            0.000195          3.29915\n",
+       " 415771  3.812012 -14.520460          440            0.000186          3.29915\n",
+       " 415772  3.813714 -14.520471          440            0.000177          3.29915\n",
+       " 415773  3.815415 -14.520480          440            0.000167          3.29915\n",
+       " \n",
+       " [656 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 416118  2.700801 -14.520082          441            3.293959         3.297672\n",
+       " 416119  2.702502 -14.519709          441            3.292116         3.297672\n",
+       " 416120  2.704204 -14.519707          441            3.290204         3.297672\n",
+       " 416121  2.705906 -14.519925          441            3.288250         3.297672\n",
+       " 416122  2.707608 -14.520144          441            3.286297         3.297672\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 416769  3.808609 -14.521524          441            0.000200         3.297672\n",
+       " 416770  3.810310 -14.521550          441            0.000191         3.297672\n",
+       " 416771  3.812012 -14.521576          441            0.000182         3.297672\n",
+       " 416772  3.813714 -14.521602          441            0.000173         3.297672\n",
+       " 416773  3.815415 -14.521627          441            0.000163         3.297672\n",
+       " \n",
+       " [656 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 417118  2.700801 -14.520027          442            3.296621         3.299486\n",
+       " 417119  2.702502 -14.520027          442            3.294779         3.299486\n",
+       " 417120  2.704204 -14.520027          442            3.292936         3.299486\n",
+       " 417121  2.705906 -14.520027          442            3.291061         3.299486\n",
+       " 417122  2.707608 -14.520027          442            3.289172         3.299486\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 417778  3.823924 -14.526079          442            0.000158         3.299486\n",
+       " 417779  3.825626 -14.526163          442            0.000150         3.299486\n",
+       " 417780  3.827327 -14.526247          442            0.000142         3.299486\n",
+       " 417781  3.829029 -14.526331          442            0.000133         3.299486\n",
+       " 417782  3.830731 -14.526415          442            0.000125         3.299486\n",
+       " \n",
+       " [665 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 418118  2.700801 -14.520210          443            3.291890         3.297634\n",
+       " 418119  2.702502 -14.520112          443            3.290022         3.297634\n",
+       " 418120  2.704204 -14.520007          443            3.288147         3.297634\n",
+       " 418121  2.705906 -14.519859          443            3.286231         3.297634\n",
+       " 418122  2.707608 -14.519711          443            3.284314         3.297634\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 418769  3.808609 -14.520243          443            0.000201         3.297634\n",
+       " 418770  3.810310 -14.520246          443            0.000192         3.297634\n",
+       " 418771  3.812012 -14.520249          443            0.000183         3.297634\n",
+       " 418772  3.813714 -14.520252          443            0.000174         3.297634\n",
+       " 418773  3.815415 -14.520255          443            0.000165         3.297634\n",
+       " \n",
+       " [656 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 419118  2.700801 -14.520077          444            3.290413          3.29467\n",
+       " 419119  2.702502 -14.520184          444            3.288576          3.29467\n",
+       " 419120  2.704204 -14.520186          444            3.286714          3.29467\n",
+       " 419121  2.705906 -14.519964          444            3.284798          3.29467\n",
+       " 419122  2.707608 -14.519742          444            3.282881          3.29467\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 419777  3.822222 -14.525193          444            0.000164          3.29467\n",
+       " 419778  3.823924 -14.525259          444            0.000156          3.29467\n",
+       " 419779  3.825626 -14.525325          444            0.000148          3.29467\n",
+       " 419780  3.827327 -14.525391          444            0.000139          3.29467\n",
+       " 419781  3.829029 -14.525455          444            0.000131          3.29467\n",
+       " \n",
+       " [664 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 420118  2.700801 -14.519622          445            3.290114         3.293944\n",
+       " 420119  2.702502 -14.519735          445            3.288155         3.293944\n",
+       " 420120  2.704204 -14.519897          445            3.286261         3.293944\n",
+       " 420121  2.705906 -14.520115          445            3.284449         3.293944\n",
+       " 420122  2.707608 -14.520334          445            3.282637         3.293944\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 420769  3.808609 -14.518498          445            0.000204         3.293944\n",
+       " 420770  3.810310 -14.518482          445            0.000195         3.293944\n",
+       " 420771  3.812012 -14.518466          445            0.000186         3.293944\n",
+       " 420772  3.813714 -14.518450          445            0.000177         3.293944\n",
+       " 420773  3.815415 -14.518434          445            0.000168         3.293944\n",
+       " \n",
+       " [656 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 421118  2.700801 -14.520027          446            3.289503         3.293081\n",
+       " 421119  2.702502 -14.520027          446            3.287704         3.293081\n",
+       " 421120  2.704204 -14.520027          446            3.285779         3.293081\n",
+       " 421121  2.705906 -14.520027          446            3.283805         3.293081\n",
+       " 421122  2.707608 -14.520027          446            3.281832         3.293081\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 421777  3.822222 -14.526057          446            0.000162         3.293081\n",
+       " 421778  3.823924 -14.526137          446            0.000154         3.293081\n",
+       " 421779  3.825626 -14.526217          446            0.000145         3.293081\n",
+       " 421780  3.827327 -14.526299          446            0.000137         3.293081\n",
+       " 421781  3.829029 -14.526379          446            0.000128         3.293081\n",
+       " \n",
+       " [664 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 422118  2.700801 -14.519955          447            3.286024         3.291867\n",
+       " 422119  2.702502 -14.519800          447            3.284115         3.291867\n",
+       " 422120  2.704204 -14.519798          447            3.282264         3.291867\n",
+       " 422121  2.705906 -14.519798          447            3.280413         3.291867\n",
+       " 422122  2.707608 -14.519798          447            3.278563         3.291867\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 422768  3.806907 -14.521110          447            0.000207         3.291867\n",
+       " 422769  3.808609 -14.521122          447            0.000198         3.291867\n",
+       " 422770  3.810310 -14.521135          447            0.000189         3.291867\n",
+       " 422771  3.812012 -14.521148          447            0.000180         3.291867\n",
+       " 422772  3.813714 -14.521161          447            0.000170         3.291867\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 423118  2.700801 -14.519577          448            3.288001         3.292521\n",
+       " 423119  2.702502 -14.519649          448            3.286113         3.292521\n",
+       " 423120  2.704204 -14.519721          448            3.284225         3.292521\n",
+       " 423121  2.705906 -14.519793          448            3.282337         3.292521\n",
+       " 423122  2.707608 -14.519798          448            3.280461         3.292521\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 423769  3.808609 -14.519612          448            0.000203         3.292521\n",
+       " 423770  3.810310 -14.519602          448            0.000194         3.292521\n",
+       " 423771  3.812012 -14.519592          448            0.000185         3.292521\n",
+       " 423772  3.813714 -14.519583          448            0.000176         3.292521\n",
+       " 423773  3.815415 -14.519573          448            0.000167         3.292521\n",
+       " \n",
+       " [656 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 424118  2.700801 -14.519996          449            3.283660         3.288791\n",
+       " 424119  2.702502 -14.519844          449            3.281839         3.288791\n",
+       " 424120  2.704204 -14.519917          449            3.279949         3.288791\n",
+       " 424121  2.705906 -14.519992          449            3.278058         3.288791\n",
+       " 424122  2.707608 -14.519950          449            3.276134         3.288791\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 424777  3.822222 -14.526065          449            0.000161         3.288791\n",
+       " 424778  3.823924 -14.526145          449            0.000153         3.288791\n",
+       " 424779  3.825626 -14.526226          449            0.000144         3.288791\n",
+       " 424780  3.827327 -14.526306          449            0.000136         3.288791\n",
+       " 424781  3.829029 -14.526386          449            0.000128         3.288791\n",
+       " \n",
+       " [664 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 425118  2.700801 -14.519787          450            3.282185          3.28558\n",
+       " 425119  2.702502 -14.519713          450            3.280268          3.28558\n",
+       " 425120  2.704204 -14.519639          450            3.278351          3.28558\n",
+       " 425121  2.705906 -14.519573          450            3.276435          3.28558\n",
+       " 425122  2.707608 -14.519646          450            3.274522          3.28558\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 425777  3.822222 -14.526257          450            0.000161          3.28558\n",
+       " 425778  3.823924 -14.526345          450            0.000152          3.28558\n",
+       " 425779  3.825626 -14.526435          450            0.000144          3.28558\n",
+       " 425780  3.827327 -14.526524          450            0.000136          3.28558\n",
+       " 425781  3.829029 -14.526613          450            0.000127          3.28558\n",
+       " \n",
+       " [664 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 426118  2.700801 -14.520103          451            3.281140         3.285459\n",
+       " 426119  2.702502 -14.519820          451            3.279225         3.285459\n",
+       " 426120  2.704204 -14.520112          451            3.277310         3.285459\n",
+       " 426121  2.705906 -14.520404          451            3.275395         3.285459\n",
+       " 426122  2.707608 -14.520696          451            3.273480         3.285459\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 426777  3.822222 -14.525563          451            0.000164         3.285459\n",
+       " 426778  3.823924 -14.525646          451            0.000156         3.285459\n",
+       " 426779  3.825626 -14.525729          451            0.000147         3.285459\n",
+       " 426780  3.827327 -14.525813          451            0.000139         3.285459\n",
+       " 426781  3.829029 -14.525896          451            0.000131         3.285459\n",
+       " \n",
+       " [664 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 427118  2.700801 -14.519916          452            3.281961         3.284921\n",
+       " 427119  2.702502 -14.519676          452            3.280078         3.284921\n",
+       " 427120  2.704204 -14.519437          452            3.278194         3.284921\n",
+       " 427121  2.705906 -14.519517          452            3.276307         3.284921\n",
+       " 427122  2.707608 -14.519813          452            3.274416         3.284921\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 427768  3.806907 -14.519399          452            0.000204         3.284921\n",
+       " 427769  3.808609 -14.519386          452            0.000195         3.284921\n",
+       " 427770  3.810310 -14.519374          452            0.000186         3.284921\n",
+       " 427771  3.812012 -14.519361          452            0.000177         3.284921\n",
+       " 427772  3.813714 -14.519348          452            0.000168         3.284921\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 428118  2.700801 -14.519569          453            3.279652         3.284814\n",
+       " 428119  2.702502 -14.519569          453            3.277698         3.284814\n",
+       " 428120  2.704204 -14.519569          453            3.275745         3.284814\n",
+       " 428121  2.705906 -14.519569          453            3.273791         3.284814\n",
+       " 428122  2.707608 -14.519637          453            3.271921         3.284814\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 428777  3.822222 -14.526473          453            0.000162         3.284814\n",
+       " 428778  3.823924 -14.526562          453            0.000154         3.284814\n",
+       " 428779  3.825626 -14.526651          453            0.000145         3.284814\n",
+       " 428780  3.827327 -14.526741          453            0.000137         3.284814\n",
+       " 428781  3.829029 -14.526830          453            0.000128         3.284814\n",
+       " \n",
+       " [664 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 429118  2.700801 -14.520430          454            3.281845         3.284915\n",
+       " 429119  2.702502 -14.520281          454            3.279955         3.284915\n",
+       " 429120  2.704204 -14.520133          454            3.278064         3.284915\n",
+       " 429121  2.705906 -14.520027          454            3.276189         3.284915\n",
+       " 429122  2.707608 -14.520027          454            3.274352         3.284915\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 429777  3.822222 -14.525186          454            0.000162         3.284915\n",
+       " 429778  3.823924 -14.525257          454            0.000153         3.284915\n",
+       " 429779  3.825626 -14.525328          454            0.000145         3.284915\n",
+       " 429780  3.827327 -14.525399          454            0.000137         3.284915\n",
+       " 429781  3.829029 -14.525470          454            0.000128         3.284915\n",
+       " \n",
+       " [664 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 430118  2.700801 -14.520027          455            3.278477          3.28361\n",
+       " 430119  2.702502 -14.520027          455            3.276633          3.28361\n",
+       " 430120  2.704204 -14.520027          455            3.274718          3.28361\n",
+       " 430121  2.705906 -14.520027          455            3.272803          3.28361\n",
+       " 430122  2.707608 -14.520027          455            3.270887          3.28361\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 430777  3.822222 -14.525860          455            0.000159          3.28361\n",
+       " 430778  3.823924 -14.525940          455            0.000150          3.28361\n",
+       " 430779  3.825626 -14.526019          455            0.000142          3.28361\n",
+       " 430780  3.827327 -14.526099          455            0.000134          3.28361\n",
+       " 430781  3.829029 -14.526178          455            0.000125          3.28361\n",
+       " \n",
+       " [664 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 431118  2.700801 -14.519886          461            3.365999         3.468875\n",
+       " 431119  2.702502 -14.520027          461            3.363317         3.468875\n",
+       " 431120  2.704204 -14.520027          461            3.360684         3.468875\n",
+       " 431121  2.705906 -14.520027          461            3.358052         3.468875\n",
+       " 431122  2.707608 -14.520058          461            3.355416         3.468875\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 431780  3.827327 -14.525835          461            0.000159         3.468875\n",
+       " 431781  3.829029 -14.525920          461            0.000150         3.468875\n",
+       " 431782  3.830731 -14.526006          461            0.000142         3.468875\n",
+       " 431783  3.832433 -14.526091          461            0.000134         3.468875\n",
+       " 431784  3.834134 -14.526176          461            0.000125         3.468875\n",
+       " \n",
+       " [667 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 432118  2.700801 -14.519728          462            3.351107         3.365176\n",
+       " 432119  2.702502 -14.519798          462            3.348488         3.365176\n",
+       " 432120  2.704204 -14.519798          462            3.345829         3.365176\n",
+       " 432121  2.705906 -14.519798          462            3.343169         3.365176\n",
+       " 432122  2.707608 -14.519746          462            3.340528         3.365176\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 432779  3.825626 -14.526443          462            0.000164         3.365176\n",
+       " 432780  3.827327 -14.526533          462            0.000155         3.365176\n",
+       " 432781  3.829029 -14.526625          462            0.000147         3.365176\n",
+       " 432782  3.830731 -14.526715          462            0.000139         3.365176\n",
+       " 432783  3.832433 -14.526807          462            0.000130         3.365176\n",
+       " \n",
+       " [666 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 433118  2.700801 -14.520169          463            3.337446         3.351045\n",
+       " 433119  2.702502 -14.519984          463            3.334927         3.351045\n",
+       " 433120  2.704204 -14.519798          463            3.332408         3.351045\n",
+       " 433121  2.705906 -14.519874          463            3.329736         3.351045\n",
+       " 433122  2.707608 -14.519948          463            3.327063         3.351045\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 433778  3.823924 -14.524513          463            0.000164         3.351045\n",
+       " 433779  3.825626 -14.524577          463            0.000155         3.351045\n",
+       " 433780  3.827327 -14.524642          463            0.000147         3.351045\n",
+       " 433781  3.829029 -14.524707          463            0.000139         3.351045\n",
+       " 433782  3.830731 -14.524771          463            0.000130         3.351045\n",
+       " \n",
+       " [665 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 434118  2.700801 -14.519734          464            3.326429         3.338645\n",
+       " 434119  2.702502 -14.519596          464            3.324071         3.338645\n",
+       " 434120  2.704204 -14.519756          464            3.321404         3.338645\n",
+       " 434121  2.705906 -14.519989          464            3.318665         3.338645\n",
+       " 434122  2.707608 -14.520221          464            3.315925         3.338645\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 434778  3.823924 -14.525677          464            0.000156         3.338645\n",
+       " 434779  3.825626 -14.525750          464            0.000148         3.338645\n",
+       " 434780  3.827327 -14.525823          464            0.000140         3.338645\n",
+       " 434781  3.829029 -14.525896          464            0.000132         3.338645\n",
+       " 434782  3.830731 -14.525970          464            0.000123         3.338645\n",
+       " \n",
+       " [665 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 435118  2.700801 -14.519799          465            3.315260         3.326769\n",
+       " 435119  2.702502 -14.519877          465            3.312575         3.326769\n",
+       " 435120  2.704204 -14.519955          465            3.309890         3.326769\n",
+       " 435121  2.705906 -14.520036          465            3.307210         3.326769\n",
+       " 435122  2.707608 -14.520182          465            3.304627         3.326769\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 435777  3.822222 -14.524728          465            0.000164         3.326769\n",
+       " 435778  3.823924 -14.524795          465            0.000155         3.326769\n",
+       " 435779  3.825626 -14.524862          465            0.000147         3.326769\n",
+       " 435780  3.827327 -14.524929          465            0.000139         3.326769\n",
+       " 435781  3.829029 -14.524997          465            0.000131         3.326769\n",
+       " \n",
+       " [664 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 436118  2.700801 -14.519607          466            3.306660         3.317013\n",
+       " 436119  2.702502 -14.519687          466            3.304116         3.317013\n",
+       " 436120  2.704204 -14.519766          466            3.301572         3.317013\n",
+       " 436121  2.705906 -14.519843          466            3.298927         3.317013\n",
+       " 436122  2.707608 -14.519918          466            3.296215         3.317013\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 436777  3.822222 -14.526057          466            0.000162         3.317013\n",
+       " 436778  3.823924 -14.526136          466            0.000154         3.317013\n",
+       " 436779  3.825626 -14.526215          466            0.000146         3.317013\n",
+       " 436780  3.827327 -14.526294          466            0.000137         3.317013\n",
+       " 436781  3.829029 -14.526373          466            0.000129         3.317013\n",
+       " \n",
+       " [664 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 437118  2.700801 -14.519973          467            3.298482         3.308179\n",
+       " 437119  2.702502 -14.520346          467            3.295959         3.308179\n",
+       " 437120  2.704204 -14.520390          467            3.293342         3.308179\n",
+       " 437121  2.705906 -14.520237          467            3.290670         3.308179\n",
+       " 437122  2.707608 -14.520084          467            3.287998         3.308179\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 437777  3.822222 -14.525625          467            0.000159         3.308179\n",
+       " 437778  3.823924 -14.525704          467            0.000151         3.308179\n",
+       " 437779  3.825626 -14.525783          467            0.000143         3.308179\n",
+       " 437780  3.827327 -14.525861          467            0.000135         3.308179\n",
+       " 437781  3.829029 -14.525940          467            0.000126         3.308179\n",
+       " \n",
+       " [664 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 438118  2.700801 -14.520098          468            3.292825         3.301364\n",
+       " 438119  2.702502 -14.519798          468            3.290360         3.301364\n",
+       " 438120  2.704204 -14.519798          468            3.287854         3.301364\n",
+       " 438121  2.705906 -14.519798          468            3.285348         3.301364\n",
+       " 438122  2.707608 -14.519798          468            3.282842         3.301364\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 438777  3.822222 -14.525260          468            0.000157         3.301364\n",
+       " 438778  3.823924 -14.525321          468            0.000149         3.301364\n",
+       " 438779  3.825626 -14.525382          468            0.000141         3.301364\n",
+       " 438780  3.827327 -14.525443          468            0.000133         3.301364\n",
+       " 438781  3.829029 -14.525504          468            0.000125         3.301364\n",
+       " \n",
+       " [664 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 439118  2.700801 -14.520073          469            3.290030         3.296345\n",
+       " 439119  2.702502 -14.519680          469            3.287631         3.296345\n",
+       " 439120  2.704204 -14.519677          469            3.285140         3.296345\n",
+       " 439121  2.705906 -14.519827          469            3.282613         3.296345\n",
+       " 439122  2.707608 -14.519978          469            3.280087         3.296345\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 439777  3.822222 -14.525660          469            0.000161         3.296345\n",
+       " 439778  3.823924 -14.525726          469            0.000153         3.296345\n",
+       " 439779  3.825626 -14.525794          469            0.000145         3.296345\n",
+       " 439780  3.827327 -14.525861          469            0.000137         3.296345\n",
+       " 439781  3.829029 -14.525928          469            0.000129         3.296345\n",
+       " \n",
+       " [664 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 440118  2.700801 -14.519816          470            3.281086         3.290425\n",
+       " 440119  2.702502 -14.519893          470            3.278508         3.290425\n",
+       " 440120  2.704204 -14.519969          470            3.275930         3.290425\n",
+       " 440121  2.705906 -14.520027          470            3.273373         3.290425\n",
+       " 440122  2.707608 -14.520027          470            3.270880         3.290425\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 440776  3.820521 -14.525625          470            0.000161         3.290425\n",
+       " 440777  3.822222 -14.525701          470            0.000153         3.290425\n",
+       " 440778  3.823924 -14.525776          470            0.000144         3.290425\n",
+       " 440779  3.825626 -14.525851          470            0.000136         3.290425\n",
+       " 440780  3.827327 -14.525927          470            0.000128         3.290425\n",
+       " \n",
+       " [663 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 441118  2.700801 -14.519798          471            3.276974         3.283106\n",
+       " 441119  2.702502 -14.519798          471            3.274428         3.283106\n",
+       " 441120  2.704204 -14.519824          471            3.271901         3.283106\n",
+       " 441121  2.705906 -14.519896          471            3.269404         3.283106\n",
+       " 441122  2.707608 -14.519968          471            3.266908         3.283106\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 441776  3.820521 -14.523896          471            0.000160         3.283106\n",
+       " 441777  3.822222 -14.523952          471            0.000151         3.283106\n",
+       " 441778  3.823924 -14.524007          471            0.000143         3.283106\n",
+       " 441779  3.825626 -14.524062          471            0.000135         3.283106\n",
+       " 441780  3.827327 -14.524117          471            0.000127         3.283106\n",
+       " \n",
+       " [663 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 442118  2.700801 -14.520256          472            3.272523         3.280566\n",
+       " 442119  2.702502 -14.520256          472            3.270204         3.280566\n",
+       " 442120  2.704204 -14.520247          472            3.267852         3.280566\n",
+       " 442121  2.705906 -14.520172          472            3.265284         3.280566\n",
+       " 442122  2.707608 -14.520098          472            3.262716         3.280566\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 442776  3.820521 -14.524354          472            0.000158         3.280566\n",
+       " 442777  3.822222 -14.524412          472            0.000150         3.280566\n",
+       " 442778  3.823924 -14.524470          472            0.000141         3.280566\n",
+       " 442779  3.825626 -14.524528          472            0.000133         3.280566\n",
+       " 442780  3.827327 -14.524586          472            0.000125         3.280566\n",
+       " \n",
+       " [663 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 443118  2.700801 -14.519616          473            3.269775         3.276262\n",
+       " 443119  2.702502 -14.519716          473            3.267447         3.276262\n",
+       " 443120  2.704204 -14.519812          473            3.265080         3.276262\n",
+       " 443121  2.705906 -14.519887          473            3.262540         3.276262\n",
+       " 443122  2.707608 -14.519962          473            3.260000         3.276262\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 443776  3.820521 -14.524775          473            0.000158         3.276262\n",
+       " 443777  3.822222 -14.524841          473            0.000150         3.276262\n",
+       " 443778  3.823924 -14.524908          473            0.000141         3.276262\n",
+       " 443779  3.825626 -14.524975          473            0.000133         3.276262\n",
+       " 443780  3.827327 -14.525041          473            0.000125         3.276262\n",
+       " \n",
+       " [663 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 444118  2.700801 -14.519699          474            3.266641         3.270717\n",
+       " 444119  2.702502 -14.519161          474            3.264241         3.270717\n",
+       " 444120  2.704204 -14.519462          474            3.261780         3.270717\n",
+       " 444121  2.705906 -14.519762          474            3.259320         3.270717\n",
+       " 444122  2.707608 -14.520019          474            3.256854         3.270717\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 444775  3.818819 -14.525805          474            0.000163         3.270717\n",
+       " 444776  3.820521 -14.525887          474            0.000155         3.270717\n",
+       " 444777  3.822222 -14.525967          474            0.000147         3.270717\n",
+       " 444778  3.823924 -14.526048          474            0.000138         3.270717\n",
+       " 444779  3.825626 -14.526129          474            0.000130         3.270717\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 445118  2.700801 -14.519440          475            3.263261         3.269546\n",
+       " 445119  2.702502 -14.519718          475            3.260918         3.269546\n",
+       " 445120  2.704204 -14.520099          475            3.258488         3.269546\n",
+       " 445121  2.705906 -14.520480          475            3.256058         3.269546\n",
+       " 445122  2.707608 -14.520686          475            3.253636         3.269546\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 445767  3.805205 -14.520687          475            0.000200         3.269546\n",
+       " 445768  3.806907 -14.520694          475            0.000191         3.269546\n",
+       " 445769  3.808609 -14.520700          475            0.000182         3.269546\n",
+       " 445770  3.810310 -14.520706          475            0.000174         3.269546\n",
+       " 445771  3.812012 -14.520713          475            0.000165         3.269546\n",
+       " \n",
+       " [654 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 446118  2.700801 -14.519653          476            3.258991         3.265807\n",
+       " 446119  2.702502 -14.519875          476            3.256606         3.265807\n",
+       " 446120  2.704204 -14.520097          476            3.254220         3.265807\n",
+       " 446121  2.705906 -14.520213          476            3.251835         3.265807\n",
+       " 446122  2.707608 -14.520063          476            3.249454         3.265807\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 446775  3.818819 -14.526465          476            0.000161         3.265807\n",
+       " 446776  3.820521 -14.526555          476            0.000153         3.265807\n",
+       " 446777  3.822222 -14.526645          476            0.000145         3.265807\n",
+       " 446778  3.823924 -14.526733          476            0.000137         3.265807\n",
+       " 446779  3.825626 -14.526823          476            0.000129         3.265807\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 447118  2.700801 -14.519971          477            3.257188         3.262037\n",
+       " 447119  2.702502 -14.519859          477            3.254822         3.262037\n",
+       " 447120  2.704204 -14.519766          477            3.252445         3.262037\n",
+       " 447121  2.705906 -14.519692          477            3.250054         3.262037\n",
+       " 447122  2.707608 -14.519620          477            3.247664         3.262037\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 447775  3.818819 -14.526467          477            0.000160         3.262037\n",
+       " 447776  3.820521 -14.526560          477            0.000152         3.262037\n",
+       " 447777  3.822222 -14.526652          477            0.000144         3.262037\n",
+       " 447778  3.823924 -14.526745          477            0.000136         3.262037\n",
+       " 447779  3.825626 -14.526837          477            0.000127         3.262037\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 448118  2.700801 -14.519739          478            3.254916         3.259995\n",
+       " 448119  2.702502 -14.519600          478            3.252587         3.259995\n",
+       " 448120  2.704204 -14.519460          478            3.250257         3.259995\n",
+       " 448121  2.705906 -14.519383          478            3.247927         3.259995\n",
+       " 448122  2.707608 -14.519675          478            3.245588         3.259995\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 448776  3.820521 -14.526305          478            0.000156         3.259995\n",
+       " 448777  3.822222 -14.526392          478            0.000148         3.259995\n",
+       " 448778  3.823924 -14.526479          478            0.000140         3.259995\n",
+       " 448779  3.825626 -14.526566          478            0.000132         3.259995\n",
+       " 448780  3.827327 -14.526652          478            0.000124         3.259995\n",
+       " \n",
+       " [663 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 449118  2.700801 -14.519505          479            3.252881          3.25814\n",
+       " 449119  2.702502 -14.519856          479            3.250476          3.25814\n",
+       " 449120  2.704204 -14.520208          479            3.248072          3.25814\n",
+       " 449121  2.705906 -14.520256          479            3.245691          3.25814\n",
+       " 449122  2.707608 -14.520256          479            3.243314          3.25814\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 449775  3.818819 -14.526471          479            0.000162          3.25814\n",
+       " 449776  3.820521 -14.526558          479            0.000154          3.25814\n",
+       " 449777  3.822222 -14.526645          479            0.000146          3.25814\n",
+       " 449778  3.823924 -14.526731          479            0.000138          3.25814\n",
+       " 449779  3.825626 -14.526817          479            0.000130          3.25814\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 450118  2.700801 -14.519970          480            3.251864         3.255085\n",
+       " 450119  2.702502 -14.519569          480            3.249561         3.255085\n",
+       " 450120  2.704204 -14.519569          480            3.247240         3.255085\n",
+       " 450121  2.705906 -14.519569          480            3.244920         3.255085\n",
+       " 450122  2.707608 -14.519618          480            3.242573         3.255085\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 450766  3.803504 -14.521081          480            0.000206         3.255085\n",
+       " 450767  3.805205 -14.521099          480            0.000197         3.255085\n",
+       " 450768  3.806907 -14.521118          480            0.000188         3.255085\n",
+       " 450769  3.808609 -14.521136          480            0.000179         3.255085\n",
+       " 450770  3.810310 -14.521155          480            0.000170         3.255085\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 451118  2.700801 -14.520352          481            3.248913          3.25449\n",
+       " 451119  2.702502 -14.520208          481            3.246537          3.25449\n",
+       " 451120  2.704204 -14.520135          481            3.244147          3.25449\n",
+       " 451121  2.705906 -14.520062          481            3.241756          3.25449\n",
+       " 451122  2.707608 -14.520027          481            3.239405          3.25449\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 451775  3.818819 -14.525641          481            0.000160          3.25449\n",
+       " 451776  3.820521 -14.525714          481            0.000152          3.25449\n",
+       " 451777  3.822222 -14.525786          481            0.000144          3.25449\n",
+       " 451778  3.823924 -14.525859          481            0.000136          3.25449\n",
+       " 451779  3.825626 -14.525931          481            0.000128          3.25449\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 452118  2.700801 -14.520470          482            3.246293         3.252096\n",
+       " 452119  2.702502 -14.520326          482            3.244000         3.252096\n",
+       " 452120  2.704204 -14.520182          482            3.241706         3.252096\n",
+       " 452121  2.705906 -14.520038          482            3.239413         3.252096\n",
+       " 452122  2.707608 -14.520027          482            3.237125         3.252096\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 452766  3.803504 -14.518960          482            0.000206         3.252096\n",
+       " 452767  3.805205 -14.518944          482            0.000197         3.252096\n",
+       " 452768  3.806907 -14.518929          482            0.000189         3.252096\n",
+       " 452769  3.808609 -14.518913          482            0.000180         3.252096\n",
+       " 452770  3.810310 -14.518898          482            0.000171         3.252096\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 453118  2.700801 -14.520052          483            3.243608         3.247969\n",
+       " 453119  2.702502 -14.519953          483            3.241269         3.247969\n",
+       " 453120  2.704204 -14.519876          483            3.238919         3.247969\n",
+       " 453121  2.705906 -14.519800          483            3.236569         3.247969\n",
+       " 453122  2.707608 -14.519871          483            3.234279         3.247969\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 453775  3.818819 -14.526673          483            0.000162         3.247969\n",
+       " 453776  3.820521 -14.526765          483            0.000154         3.247969\n",
+       " 453777  3.822222 -14.526857          483            0.000146         3.247969\n",
+       " 453778  3.823924 -14.526950          483            0.000138         3.247969\n",
+       " 453779  3.825626 -14.527041          483            0.000130         3.247969\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 454118  2.700801 -14.520403          484            3.242466          3.24893\n",
+       " 454119  2.702502 -14.520226          484            3.240217          3.24893\n",
+       " 454120  2.704204 -14.520051          484            3.237968          3.24893\n",
+       " 454121  2.705906 -14.520092          484            3.235673          3.24893\n",
+       " 454122  2.707608 -14.520167          484            3.233371          3.24893\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 454776  3.820521 -14.526075          484            0.000156          3.24893\n",
+       " 454777  3.822222 -14.526161          484            0.000148          3.24893\n",
+       " 454778  3.823924 -14.526248          484            0.000140          3.24893\n",
+       " 454779  3.825626 -14.526334          484            0.000132          3.24893\n",
+       " 454780  3.827327 -14.526420          484            0.000124          3.24893\n",
+       " \n",
+       " [663 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 455118  2.700801 -14.519968          485            3.242011         3.244132\n",
+       " 455119  2.702502 -14.520153          485            3.239747         3.244132\n",
+       " 455120  2.704204 -14.520303          485            3.237419         3.244132\n",
+       " 455121  2.705906 -14.520453          485            3.235090         3.244132\n",
+       " 455122  2.707608 -14.520426          485            3.232741         3.244132\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 455775  3.818819 -14.525848          485            0.000161         3.244132\n",
+       " 455776  3.820521 -14.525924          485            0.000153         3.244132\n",
+       " 455777  3.822222 -14.525998          485            0.000145         3.244132\n",
+       " 455778  3.823924 -14.526073          485            0.000137         3.244132\n",
+       " 455779  3.825626 -14.526148          485            0.000129         3.244132\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 456118  2.700801 -14.519880          486            3.238637         3.244561\n",
+       " 456119  2.702502 -14.520057          486            3.236482         3.244561\n",
+       " 456120  2.704204 -14.520232          486            3.234326         3.244561\n",
+       " 456121  2.705906 -14.520448          486            3.232004         3.244561\n",
+       " 456122  2.707608 -14.520670          486            3.229658         3.244561\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 456776  3.820521 -14.524366          486            0.000156         3.244561\n",
+       " 456777  3.822222 -14.524424          486            0.000148         3.244561\n",
+       " 456778  3.823924 -14.524482          486            0.000140         3.244561\n",
+       " 456779  3.825626 -14.524539          486            0.000132         3.244561\n",
+       " 456780  3.827327 -14.524596          486            0.000124         3.244561\n",
+       " \n",
+       " [663 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 457118  2.700801 -14.520111          487            3.238433         3.241931\n",
+       " 457119  2.702502 -14.520289          487            3.236271         3.241931\n",
+       " 457120  2.704204 -14.520469          487            3.234109         3.241931\n",
+       " 457121  2.705906 -14.520283          487            3.231838         3.241931\n",
+       " 457122  2.707608 -14.520061          487            3.229556         3.241931\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 457776  3.820521 -14.524808          487            0.000155         3.241931\n",
+       " 457777  3.822222 -14.524871          487            0.000147         3.241931\n",
+       " 457778  3.823924 -14.524935          487            0.000139         3.241931\n",
+       " 457779  3.825626 -14.524999          487            0.000131         3.241931\n",
+       " 457780  3.827327 -14.525062          487            0.000123         3.241931\n",
+       " \n",
+       " [663 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 458118  2.700801 -14.520180          488            3.234857         3.239866\n",
+       " 458119  2.702502 -14.520015          488            3.232637         3.239866\n",
+       " 458120  2.704204 -14.519850          488            3.230417         3.239866\n",
+       " 458121  2.705906 -14.519798          488            3.228172         3.239866\n",
+       " 458122  2.707608 -14.519798          488            3.225917         3.239866\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 458775  3.818819 -14.524953          488            0.000161         3.239866\n",
+       " 458776  3.820521 -14.525025          488            0.000153         3.239866\n",
+       " 458777  3.822222 -14.525097          488            0.000144         3.239866\n",
+       " 458778  3.823924 -14.525169          488            0.000136         3.239866\n",
+       " 458779  3.825626 -14.525241          488            0.000128         3.239866\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 459118  2.700801 -14.519835          489            3.235106         3.239079\n",
+       " 459119  2.702502 -14.519985          489            3.232856         3.239079\n",
+       " 459120  2.704204 -14.520135          489            3.230607         3.239079\n",
+       " 459121  2.705906 -14.520212          489            3.228358         3.239079\n",
+       " 459122  2.707608 -14.519987          489            3.226109         3.239079\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 459775  3.818819 -14.524779          489            0.000157         3.239079\n",
+       " 459776  3.820521 -14.524845          489            0.000149         3.239079\n",
+       " 459777  3.822222 -14.524911          489            0.000141         3.239079\n",
+       " 459778  3.823924 -14.524977          489            0.000133         3.239079\n",
+       " 459779  3.825626 -14.525043          489            0.000125         3.239079\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 460118  2.700801 -14.519746          490            3.228925         3.237157\n",
+       " 460119  2.702502 -14.520009          490            3.226569         3.237157\n",
+       " 460120  2.704204 -14.519937          490            3.224339         3.237157\n",
+       " 460121  2.705906 -14.519865          490            3.222109         3.237157\n",
+       " 460122  2.707608 -14.519804          490            3.219874         3.237157\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 460775  3.818819 -14.526511          490            0.000158         3.237157\n",
+       " 460776  3.820521 -14.526598          490            0.000150         3.237157\n",
+       " 460777  3.822222 -14.526684          490            0.000142         3.237157\n",
+       " 460778  3.823924 -14.526771          490            0.000134         3.237157\n",
+       " 460779  3.825626 -14.526856          490            0.000126         3.237157\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 461118  2.700801 -14.519908          491            3.228493         3.233695\n",
+       " 461119  2.702502 -14.519840          491            3.226276         3.233695\n",
+       " 461120  2.704204 -14.519915          491            3.223982         3.233695\n",
+       " 461121  2.705906 -14.519988          491            3.221687         3.233695\n",
+       " 461122  2.707608 -14.520027          491            3.219402         3.233695\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 461775  3.818819 -14.525207          491            0.000158         3.233695\n",
+       " 461776  3.820521 -14.525278          491            0.000150         3.233695\n",
+       " 461777  3.822222 -14.525350          491            0.000142         3.233695\n",
+       " 461778  3.823924 -14.525421          491            0.000134         3.233695\n",
+       " 461779  3.825626 -14.525493          491            0.000126         3.233695\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 462118  2.700801 -14.519922          492            3.226389         3.230707\n",
+       " 462119  2.702502 -14.519984          492            3.224152         3.230707\n",
+       " 462120  2.704204 -14.519909          492            3.221811         3.230707\n",
+       " 462121  2.705906 -14.519835          492            3.219469         3.230707\n",
+       " 462122  2.707608 -14.519760          492            3.217209         3.230707\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 462775  3.818819 -14.526687          492            0.000160         3.230707\n",
+       " 462776  3.820521 -14.526781          492            0.000152         3.230707\n",
+       " 462777  3.822222 -14.526875          492            0.000144         3.230707\n",
+       " 462778  3.823924 -14.526970          492            0.000135         3.230707\n",
+       " 462779  3.825626 -14.527065          492            0.000127         3.230707\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 463118  2.700801 -14.519798          493            3.226712         3.231366\n",
+       " 463119  2.702502 -14.519798          493            3.224443         3.231366\n",
+       " 463120  2.704204 -14.519798          493            3.222174         3.231366\n",
+       " 463121  2.705906 -14.519776          493            3.219922         3.231366\n",
+       " 463122  2.707608 -14.519630          493            3.217763         3.231366\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 463775  3.818819 -14.525858          493            0.000160         3.231366\n",
+       " 463776  3.820521 -14.525932          493            0.000152         3.231366\n",
+       " 463777  3.822222 -14.526007          493            0.000144         3.231366\n",
+       " 463778  3.823924 -14.526081          493            0.000136         3.231366\n",
+       " 463779  3.825626 -14.526155          493            0.000128         3.231366\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 464118  2.700801 -14.519423          494            3.225384         3.229452\n",
+       " 464119  2.702502 -14.519593          494            3.223109         3.229452\n",
+       " 464120  2.704204 -14.519739          494            3.220937         3.229452\n",
+       " 464121  2.705906 -14.519885          494            3.218765         3.229452\n",
+       " 464122  2.707608 -14.520023          494            3.216588         3.229452\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 464775  3.818819 -14.525632          494            0.000160         3.229452\n",
+       " 464776  3.820521 -14.525706          494            0.000152         3.229452\n",
+       " 464777  3.822222 -14.525781          494            0.000144         3.229452\n",
+       " 464778  3.823924 -14.525855          494            0.000136         3.229452\n",
+       " 464779  3.825626 -14.525929          494            0.000128         3.229452\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 465118  2.700801 -14.520026          495            3.223713         3.228911\n",
+       " 465119  2.702502 -14.519951          495            3.221543         3.228911\n",
+       " 465120  2.704204 -14.519876          495            3.219373         3.228911\n",
+       " 465121  2.705906 -14.519800          495            3.217204         3.228911\n",
+       " 465122  2.707608 -14.519944          495            3.214970         3.228911\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 465775  3.818819 -14.526318          495            0.000157         3.228911\n",
+       " 465776  3.820521 -14.526398          495            0.000149         3.228911\n",
+       " 465777  3.822222 -14.526478          495            0.000141         3.228911\n",
+       " 465778  3.823924 -14.526558          495            0.000133         3.228911\n",
+       " 465779  3.825626 -14.526638          495            0.000125         3.228911\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 466118  2.700801 -14.519619          496            3.220630         3.224943\n",
+       " 466119  2.702502 -14.519770          496            3.218394         3.224943\n",
+       " 466120  2.704204 -14.519919          496            3.216159         3.224943\n",
+       " 466121  2.705906 -14.520048          496            3.213932         3.224943\n",
+       " 466122  2.707608 -14.520123          496            3.211729         3.224943\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 466775  3.818819 -14.524595          496            0.000158         3.224943\n",
+       " 466776  3.820521 -14.524650          496            0.000150         3.224943\n",
+       " 466777  3.822222 -14.524704          496            0.000142         3.224943\n",
+       " 466778  3.823924 -14.524758          496            0.000134         3.224943\n",
+       " 466779  3.825626 -14.524813          496            0.000126         3.224943\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 467118  2.700801 -14.520027          497            3.220180         3.224172\n",
+       " 467119  2.702502 -14.520027          497            3.217969         3.224172\n",
+       " 467120  2.704204 -14.520027          497            3.215758         3.224172\n",
+       " 467121  2.705906 -14.519848          497            3.213505         3.224172\n",
+       " 467122  2.707608 -14.519629          497            3.211243         3.224172\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 467775  3.818819 -14.525646          497            0.000157         3.224172\n",
+       " 467776  3.820521 -14.525723          497            0.000149         3.224172\n",
+       " 467777  3.822222 -14.525801          497            0.000141         3.224172\n",
+       " 467778  3.823924 -14.525878          497            0.000133         3.224172\n",
+       " 467779  3.825626 -14.525955          497            0.000125         3.224172\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 468118  2.700801 -14.520168          498            3.217772         3.222964\n",
+       " 468119  2.702502 -14.519979          498            3.215672         3.222964\n",
+       " 468120  2.704204 -14.519798          498            3.213567         3.222964\n",
+       " 468121  2.705906 -14.519798          498            3.211324         3.222964\n",
+       " 468122  2.707608 -14.519798          498            3.209082         3.222964\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 468775  3.818819 -14.525252          498            0.000155         3.222964\n",
+       " 468776  3.820521 -14.525318          498            0.000147         3.222964\n",
+       " 468777  3.822222 -14.525384          498            0.000139         3.222964\n",
+       " 468778  3.823924 -14.525450          498            0.000131         3.222964\n",
+       " 468779  3.825626 -14.525516          498            0.000123         3.222964\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 469118  2.700801 -14.519878          499            3.215578         3.220571\n",
+       " 469119  2.702502 -14.520036          499            3.213474         3.220571\n",
+       " 469120  2.704204 -14.520193          499            3.211370         3.220571\n",
+       " 469121  2.705906 -14.520082          499            3.209264         3.220571\n",
+       " 469122  2.707608 -14.519791          499            3.207157         3.220571\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 469774  3.817117 -14.524296          499            0.000162         3.220571\n",
+       " 469775  3.818819 -14.524358          499            0.000154         3.220571\n",
+       " 469776  3.820521 -14.524421          499            0.000146         3.220571\n",
+       " 469777  3.822222 -14.524484          499            0.000138         3.220571\n",
+       " 469778  3.823924 -14.524547          499            0.000130         3.220571\n",
+       " \n",
+       " [661 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 470118  2.700801 -14.519211          500            3.216122         3.218969\n",
+       " 470119  2.702502 -14.519511          500            3.213912         3.218969\n",
+       " 470120  2.704204 -14.519812          500            3.211703         3.218969\n",
+       " 470121  2.705906 -14.519985          500            3.209525         3.218969\n",
+       " 470122  2.707608 -14.519837          500            3.207426         3.218969\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 470775  3.818819 -14.524769          500            0.000158         3.218969\n",
+       " 470776  3.820521 -14.524835          500            0.000150         3.218969\n",
+       " 470777  3.822222 -14.524900          500            0.000142         3.218969\n",
+       " 470778  3.823924 -14.524966          500            0.000134         3.218969\n",
+       " 470779  3.825626 -14.525032          500            0.000126         3.218969\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 471118  2.700801 -14.519709          501            3.213582         3.219163\n",
+       " 471119  2.702502 -14.519516          501            3.211579         3.219163\n",
+       " 471120  2.704204 -14.519354          501            3.209558         3.219163\n",
+       " 471121  2.705906 -14.519506          501            3.207356         3.219163\n",
+       " 471122  2.707608 -14.519659          501            3.205154         3.219163\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 471775  3.818819 -14.525198          501            0.000157         3.219163\n",
+       " 471776  3.820521 -14.525272          501            0.000149         3.219163\n",
+       " 471777  3.822222 -14.525347          501            0.000141         3.219163\n",
+       " 471778  3.823924 -14.525421          501            0.000133         3.219163\n",
+       " 471779  3.825626 -14.525496          501            0.000125         3.219163\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 472118  2.700801 -14.519849          502            3.210540         3.215886\n",
+       " 472119  2.702502 -14.519958          502            3.208416         3.215886\n",
+       " 472120  2.704204 -14.519975          502            3.206288         3.215886\n",
+       " 472121  2.705906 -14.519829          502            3.204154         3.215886\n",
+       " 472122  2.707608 -14.519683          502            3.202021         3.215886\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 472766  3.803504 -14.519176          502            0.000199         3.215886\n",
+       " 472767  3.805205 -14.519161          502            0.000191         3.215886\n",
+       " 472768  3.806907 -14.519145          502            0.000182         3.215886\n",
+       " 472769  3.808609 -14.519130          502            0.000173         3.215886\n",
+       " 472770  3.810310 -14.519114          502            0.000164         3.215886\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 473118  2.700801 -14.519853          503            3.209106         3.213289\n",
+       " 473119  2.702502 -14.519968          503            3.207021         3.213289\n",
+       " 473120  2.704204 -14.520027          503            3.204920         3.213289\n",
+       " 473121  2.705906 -14.520027          503            3.202804         3.213289\n",
+       " 473122  2.707608 -14.520027          503            3.200688         3.213289\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 473774  3.817117 -14.526453          503            0.000163         3.213289\n",
+       " 473775  3.818819 -14.526542          503            0.000154         3.213289\n",
+       " 473776  3.820521 -14.526630          503            0.000146         3.213289\n",
+       " 473777  3.822222 -14.526718          503            0.000138         3.213289\n",
+       " 473778  3.823924 -14.526807          503            0.000130         3.213289\n",
+       " \n",
+       " [661 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 474118  2.700801 -14.520027          504            3.207554         3.212433\n",
+       " 474119  2.702502 -14.520027          504            3.205428         3.212433\n",
+       " 474120  2.704204 -14.519956          504            3.203305         3.212433\n",
+       " 474121  2.705906 -14.519810          504            3.201184         3.212433\n",
+       " 474122  2.707608 -14.519664          504            3.199064         3.212433\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 474766  3.803504 -14.519354          504            0.000200         3.212433\n",
+       " 474767  3.805205 -14.519350          504            0.000191         3.212433\n",
+       " 474768  3.806907 -14.519347          504            0.000182         3.212433\n",
+       " 474769  3.808609 -14.519344          504            0.000174         3.212433\n",
+       " 474770  3.810310 -14.519341          504            0.000165         3.212433\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 475118  2.700801 -14.519978          505            3.206657         3.211483\n",
+       " 475119  2.702502 -14.519871          505            3.204595         3.211483\n",
+       " 475120  2.704204 -14.519821          505            3.202505         3.211483\n",
+       " 475121  2.705906 -14.519893          505            3.200351         3.211483\n",
+       " 475122  2.707608 -14.519964          505            3.198197         3.211483\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 475775  3.818819 -14.524967          505            0.000161         3.211483\n",
+       " 475776  3.820521 -14.525036          505            0.000153         3.211483\n",
+       " 475777  3.822222 -14.525104          505            0.000145         3.211483\n",
+       " 475778  3.823924 -14.525172          505            0.000136         3.211483\n",
+       " 475779  3.825626 -14.525241          505            0.000128         3.211483\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 476118  2.700801 -14.519697          506            3.208357         3.211139\n",
+       " 476119  2.702502 -14.519480          506            3.206309         3.211139\n",
+       " 476120  2.704204 -14.519469          506            3.204237         3.211139\n",
+       " 476121  2.705906 -14.519829          506            3.202121         3.211139\n",
+       " 476122  2.707608 -14.520188          506            3.200005         3.211139\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 476775  3.818819 -14.523484          506            0.000161         3.211139\n",
+       " 476776  3.820521 -14.523527          506            0.000153         3.211139\n",
+       " 476777  3.822222 -14.523570          506            0.000145         3.211139\n",
+       " 476778  3.823924 -14.523613          506            0.000137         3.211139\n",
+       " 476779  3.825626 -14.523656          506            0.000129         3.211139\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 477118  2.700801 -14.519843          507            3.206749         3.211027\n",
+       " 477119  2.702502 -14.519939          507            3.204712         3.211027\n",
+       " 477120  2.704204 -14.520041          507            3.202666         3.211027\n",
+       " 477121  2.705906 -14.520186          507            3.200520         3.211027\n",
+       " 477122  2.707608 -14.520332          507            3.198373         3.211027\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 477775  3.818819 -14.526919          507            0.000161         3.211027\n",
+       " 477776  3.820521 -14.527010          507            0.000153         3.211027\n",
+       " 477777  3.822222 -14.527102          507            0.000145         3.211027\n",
+       " 477778  3.823924 -14.527192          507            0.000136         3.211027\n",
+       " 477779  3.825626 -14.527284          507            0.000128         3.211027\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 478118  2.700801 -14.519850          508            3.204003         3.208915\n",
+       " 478119  2.702502 -14.519961          508            3.201871         3.208915\n",
+       " 478120  2.704204 -14.519999          508            3.199773         3.208915\n",
+       " 478121  2.705906 -14.519928          508            3.197723         3.208915\n",
+       " 478122  2.707608 -14.519856          508            3.195674         3.208915\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 478774  3.817117 -14.526524          508            0.000156         3.208915\n",
+       " 478775  3.818819 -14.526613          508            0.000148         3.208915\n",
+       " 478776  3.820521 -14.526703          508            0.000140         3.208915\n",
+       " 478777  3.822222 -14.526793          508            0.000132         3.208915\n",
+       " 478778  3.823924 -14.526882          508            0.000124         3.208915\n",
+       " \n",
+       " [661 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 479118  2.700801 -14.519850          509            3.203102         3.207743\n",
+       " 479119  2.702502 -14.519961          509            3.201029         3.207743\n",
+       " 479120  2.704204 -14.519967          509            3.198951         3.207743\n",
+       " 479121  2.705906 -14.519819          509            3.196865         3.207743\n",
+       " 479122  2.707608 -14.519671          509            3.194779         3.207743\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 479766  3.803504 -14.521309          509            0.000200         3.207743\n",
+       " 479767  3.805205 -14.521331          509            0.000191         3.207743\n",
+       " 479768  3.806907 -14.521353          509            0.000182         3.207743\n",
+       " 479769  3.808609 -14.521374          509            0.000174         3.207743\n",
+       " 479770  3.810310 -14.521396          509            0.000165         3.207743\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 480118  2.700801 -14.519954          510            3.201915         3.206117\n",
+       " 480119  2.702502 -14.520287          510            3.199802         3.206117\n",
+       " 480120  2.704204 -14.520485          510            3.197708         3.206117\n",
+       " 480121  2.705906 -14.520485          510            3.195638         3.206117\n",
+       " 480122  2.707608 -14.520485          510            3.193569         3.206117\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 480775  3.818819 -14.526527          510            0.000157         3.206117\n",
+       " 480776  3.820521 -14.526613          510            0.000149         3.206117\n",
+       " 480777  3.822222 -14.526698          510            0.000141         3.206117\n",
+       " 480778  3.823924 -14.526783          510            0.000133         3.206117\n",
+       " 480779  3.825626 -14.526869          510            0.000125         3.206117\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 481118  2.700801 -14.519587          511            3.201136         3.205135\n",
+       " 481119  2.702502 -14.519660          511            3.199015         3.205135\n",
+       " 481120  2.704204 -14.519732          511            3.196895         3.205135\n",
+       " 481121  2.705906 -14.519806          511            3.194780         3.205135\n",
+       " 481122  2.707608 -14.519880          511            3.192720         3.205135\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 481775  3.818819 -14.526101          511            0.000156         3.205135\n",
+       " 481776  3.820521 -14.526181          511            0.000148         3.205135\n",
+       " 481777  3.822222 -14.526260          511            0.000140         3.205135\n",
+       " 481778  3.823924 -14.526340          511            0.000132         3.205135\n",
+       " 481779  3.825626 -14.526420          511            0.000124         3.205135\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 482118  2.700801 -14.519423          512            3.201190         3.204531\n",
+       " 482119  2.702502 -14.519606          512            3.199092         3.204531\n",
+       " 482120  2.704204 -14.519821          512            3.197052         3.204531\n",
+       " 482121  2.705906 -14.520037          512            3.195012         3.204531\n",
+       " 482122  2.707608 -14.520252          512            3.192972         3.204531\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 482766  3.803504 -14.519584          512            0.000204         3.204531\n",
+       " 482767  3.805205 -14.519581          512            0.000195         3.204531\n",
+       " 482768  3.806907 -14.519578          512            0.000187         3.204531\n",
+       " 482769  3.808609 -14.519575          512            0.000178         3.204531\n",
+       " 482770  3.810310 -14.519571          512            0.000169         3.204531\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 483118  2.700801 -14.519829          513            3.199172         3.203777\n",
+       " 483119  2.702502 -14.519732          513            3.197145         3.203777\n",
+       " 483120  2.704204 -14.519660          513            3.195118         3.203777\n",
+       " 483121  2.705906 -14.519588          513            3.193091         3.203777\n",
+       " 483122  2.707608 -14.519624          513            3.191023         3.203777\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 483775  3.818819 -14.524965          513            0.000161         3.203777\n",
+       " 483776  3.820521 -14.525033          513            0.000153         3.203777\n",
+       " 483777  3.822222 -14.525102          513            0.000145         3.203777\n",
+       " 483778  3.823924 -14.525169          513            0.000137         3.203777\n",
+       " 483779  3.825626 -14.525238          513            0.000129         3.203777\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 484118  2.700801 -14.520232          514            3.196465         3.200392\n",
+       " 484119  2.702502 -14.520006          514            3.194387         3.200392\n",
+       " 484120  2.704204 -14.519781          514            3.192310         3.200392\n",
+       " 484121  2.705906 -14.519569          514            3.190231         3.200392\n",
+       " 484122  2.707608 -14.519569          514            3.188119         3.200392\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 484775  3.818819 -14.526083          514            0.000156         3.200392\n",
+       " 484776  3.820521 -14.526168          514            0.000148         3.200392\n",
+       " 484777  3.822222 -14.526253          514            0.000140         3.200392\n",
+       " 484778  3.823924 -14.526338          514            0.000132         3.200392\n",
+       " 484779  3.825626 -14.526423          514            0.000124         3.200392\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 485118  2.700801 -14.519669          515            3.196372         3.198435\n",
+       " 485119  2.702502 -14.519798          515            3.194328         3.198435\n",
+       " 485120  2.704204 -14.519798          515            3.192310         3.198435\n",
+       " 485121  2.705906 -14.519798          515            3.190292         3.198435\n",
+       " 485122  2.707608 -14.519816          515            3.188265         3.198435\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 485775  3.818819 -14.526729          515            0.000157         3.198435\n",
+       " 485776  3.820521 -14.526819          515            0.000149         3.198435\n",
+       " 485777  3.822222 -14.526910          515            0.000141         3.198435\n",
+       " 485778  3.823924 -14.527001          515            0.000133         3.198435\n",
+       " 485779  3.825626 -14.527092          515            0.000125         3.198435\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 486118  2.700801 -14.519890          516            3.193397          3.19934\n",
+       " 486119  2.702502 -14.519929          516            3.191325          3.19934\n",
+       " 486120  2.704204 -14.520077          516            3.189225          3.19934\n",
+       " 486121  2.705906 -14.520225          516            3.187126          3.19934\n",
+       " 486122  2.707608 -14.520199          516            3.185071          3.19934\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 486775  3.818819 -14.526753          516            0.000155          3.19934\n",
+       " 486776  3.820521 -14.526844          516            0.000147          3.19934\n",
+       " 486777  3.822222 -14.526935          516            0.000139          3.19934\n",
+       " 486778  3.823924 -14.527025          516            0.000131          3.19934\n",
+       " 486779  3.825626 -14.527117          516            0.000123          3.19934\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 487118  2.700801 -14.519798          517            3.191585         3.196146\n",
+       " 487119  2.702502 -14.519798          517            3.189635         3.196146\n",
+       " 487120  2.704204 -14.519798          517            3.187686         3.196146\n",
+       " 487121  2.705906 -14.519971          517            3.185611         3.196146\n",
+       " 487122  2.707608 -14.520192          517            3.183498         3.196146\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 487774  3.817117 -14.525836          517            0.000161         3.196146\n",
+       " 487775  3.818819 -14.525913          517            0.000153         3.196146\n",
+       " 487776  3.820521 -14.525990          517            0.000145         3.196146\n",
+       " 487777  3.822222 -14.526066          517            0.000137         3.196146\n",
+       " 487778  3.823924 -14.526142          517            0.000129         3.196146\n",
+       " \n",
+       " [661 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 488118  2.700801 -14.520116          518            3.192390         3.193979\n",
+       " 488119  2.702502 -14.519815          518            3.190353         3.193979\n",
+       " 488120  2.704204 -14.519868          518            3.188319         3.193979\n",
+       " 488121  2.705906 -14.519942          518            3.186285         3.193979\n",
+       " 488122  2.707608 -14.520016          518            3.184251         3.193979\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 488775  3.818819 -14.525893          518            0.000157         3.193979\n",
+       " 488776  3.820521 -14.525967          518            0.000149         3.193979\n",
+       " 488777  3.822222 -14.526041          518            0.000141         3.193979\n",
+       " 488778  3.823924 -14.526114          518            0.000132         3.193979\n",
+       " 488779  3.825626 -14.526189          518            0.000124         3.193979\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 489118  2.700801 -14.519643          519            3.190772         3.195856\n",
+       " 489119  2.702502 -14.519799          519            3.188724         3.195856\n",
+       " 489120  2.704204 -14.519957          519            3.186675         3.195856\n",
+       " 489121  2.705906 -14.520067          519            3.184653         3.195856\n",
+       " 489122  2.707608 -14.520139          519            3.182651         3.195856\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 489766  3.803504 -14.521541          519            0.000199         3.195856\n",
+       " 489767  3.805205 -14.521562          519            0.000190         3.195856\n",
+       " 489768  3.806907 -14.521584          519            0.000181         3.195856\n",
+       " 489769  3.808609 -14.521605          519            0.000173         3.195856\n",
+       " 489770  3.810310 -14.521626          519            0.000164         3.195856\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 490118  2.700801 -14.519672          520            3.190636         3.192783\n",
+       " 490119  2.702502 -14.519831          520            3.188612         3.192783\n",
+       " 490120  2.704204 -14.519904          520            3.186553         3.192783\n",
+       " 490121  2.705906 -14.519979          520            3.184492         3.192783\n",
+       " 490122  2.707608 -14.520002          520            3.182447         3.192783\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 490775  3.818819 -14.524783          520            0.000155         3.192783\n",
+       " 490776  3.820521 -14.524851          520            0.000147         3.192783\n",
+       " 490777  3.822222 -14.524919          520            0.000139         3.192783\n",
+       " 490778  3.823924 -14.524987          520            0.000131         3.192783\n",
+       " 490779  3.825626 -14.525055          520            0.000123         3.192783\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 491118  2.700801 -14.520061          521            3.188090         3.194155\n",
+       " 491119  2.702502 -14.520134          521            3.186085         3.194155\n",
+       " 491120  2.704204 -14.520207          521            3.184080         3.194155\n",
+       " 491121  2.705906 -14.520207          521            3.182040         3.194155\n",
+       " 491122  2.707608 -14.520060          521            3.179928         3.194155\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 491765  3.801802 -14.519370          521            0.000205         3.194155\n",
+       " 491766  3.803504 -14.519364          521            0.000196         3.194155\n",
+       " 491767  3.805205 -14.519358          521            0.000188         3.194155\n",
+       " 491768  3.806907 -14.519352          521            0.000179         3.194155\n",
+       " 491769  3.808609 -14.519346          521            0.000170         3.194155\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 492118  2.700801 -14.520088          522            3.186921         3.190127\n",
+       " 492119  2.702502 -14.520234          522            3.184801         3.190127\n",
+       " 492120  2.704204 -14.520380          522            3.182680         3.190127\n",
+       " 492121  2.705906 -14.520444          522            3.180600         3.190127\n",
+       " 492122  2.707608 -14.520301          522            3.178624         3.190127\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 492765  3.801802 -14.521297          522            0.000204         3.190127\n",
+       " 492766  3.803504 -14.521319          522            0.000196         3.190127\n",
+       " 492767  3.805205 -14.521340          522            0.000187         3.190127\n",
+       " 492768  3.806907 -14.521362          522            0.000178         3.190127\n",
+       " 492769  3.808609 -14.521383          522            0.000170         3.190127\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 493118  2.700801 -14.519984          523            3.184803         3.189953\n",
+       " 493119  2.702502 -14.519894          523            3.182844         3.189953\n",
+       " 493120  2.704204 -14.519802          523            3.180884         3.189953\n",
+       " 493121  2.705906 -14.519729          523            3.178746         3.189953\n",
+       " 493122  2.707608 -14.519655          523            3.176600         3.189953\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 493766  3.803504 -14.519150          523            0.000199         3.189953\n",
+       " 493767  3.805205 -14.519141          523            0.000190         3.189953\n",
+       " 493768  3.806907 -14.519132          523            0.000182         3.189953\n",
+       " 493769  3.808609 -14.519122          523            0.000173         3.189953\n",
+       " 493770  3.810310 -14.519114          523            0.000164         3.189953\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 494118  2.700801 -14.520153          524            3.184774         3.187816\n",
+       " 494119  2.702502 -14.519931          524            3.182838         3.187816\n",
+       " 494120  2.704204 -14.519798          524            3.180836         3.187816\n",
+       " 494121  2.705906 -14.519798          524            3.178737         3.187816\n",
+       " 494122  2.707608 -14.519798          524            3.176638         3.187816\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 494774  3.817117 -14.526063          524            0.000161         3.187816\n",
+       " 494775  3.818819 -14.526139          524            0.000154         3.187816\n",
+       " 494776  3.820521 -14.526216          524            0.000146         3.187816\n",
+       " 494777  3.822222 -14.526292          524            0.000138         3.187816\n",
+       " 494778  3.823924 -14.526368          524            0.000130         3.187816\n",
+       " \n",
+       " [661 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 495118  2.700801 -14.519853          525            3.183201         3.187395\n",
+       " 495119  2.702502 -14.519968          525            3.181176         3.187395\n",
+       " 495120  2.704204 -14.519991          525            3.179130         3.187395\n",
+       " 495121  2.705906 -14.519918          525            3.177061         3.187395\n",
+       " 495122  2.707608 -14.519845          525            3.174992         3.187395\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 495775  3.818819 -14.526753          525            0.000155         3.187395\n",
+       " 495776  3.820521 -14.526844          525            0.000147         3.187395\n",
+       " 495777  3.822222 -14.526935          525            0.000139         3.187395\n",
+       " 495778  3.823924 -14.527025          525            0.000131         3.187395\n",
+       " 495779  3.825626 -14.527117          525            0.000123         3.187395\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 496118  2.700801 -14.520227          526            3.180802         3.186067\n",
+       " 496119  2.702502 -14.520409          526            3.178741         3.186067\n",
+       " 496120  2.704204 -14.520186          526            3.176641         3.186067\n",
+       " 496121  2.705906 -14.519964          526            3.174542         3.186067\n",
+       " 496122  2.707608 -14.519817          526            3.172453         3.186067\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 496774  3.817117 -14.526746          526            0.000159         3.186067\n",
+       " 496775  3.818819 -14.526827          526            0.000151         3.186067\n",
+       " 496776  3.820521 -14.526909          526            0.000143         3.186067\n",
+       " 496777  3.822222 -14.526990          526            0.000135         3.186067\n",
+       " 496778  3.823924 -14.527072          526            0.000127         3.186067\n",
+       " \n",
+       " [661 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 497118  2.700801 -14.520027          527            3.183072         3.189243\n",
+       " 497119  2.702502 -14.520027          527            3.181119         3.189243\n",
+       " 497120  2.704204 -14.520027          527            3.179062         3.189243\n",
+       " 497121  2.705906 -14.520027          527            3.176992         3.189243\n",
+       " 497122  2.707608 -14.520027          527            3.174923         3.189243\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 497766  3.803504 -14.521312          527            0.000198         3.189243\n",
+       " 497767  3.805205 -14.521334          527            0.000190         3.189243\n",
+       " 497768  3.806907 -14.521355          527            0.000181         3.189243\n",
+       " 497769  3.808609 -14.521376          527            0.000173         3.189243\n",
+       " 497770  3.810310 -14.521398          527            0.000164         3.189243\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 498118  2.700801 -14.520426          528            3.176902         3.180948\n",
+       " 498119  2.702502 -14.520423          528            3.174893         3.180948\n",
+       " 498120  2.704204 -14.520349          528            3.172807         3.180948\n",
+       " 498121  2.705906 -14.520275          528            3.170721         3.180948\n",
+       " 498122  2.707608 -14.520145          528            3.168645         3.180948\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 498774  3.817117 -14.524995          528            0.000157         3.180948\n",
+       " 498775  3.818819 -14.525062          528            0.000149         3.180948\n",
+       " 498776  3.820521 -14.525129          528            0.000142         3.180948\n",
+       " 498777  3.822222 -14.525197          528            0.000134         3.180948\n",
+       " 498778  3.823924 -14.525265          528            0.000126         3.180948\n",
+       " \n",
+       " [661 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 499118  2.700801 -14.519634          529            3.177025         3.179802\n",
+       " 499119  2.702502 -14.519762          529            3.175091         3.179802\n",
+       " 499120  2.704204 -14.519958          529            3.173076         3.179802\n",
+       " 499121  2.705906 -14.520180          529            3.171029         3.179802\n",
+       " 499122  2.707608 -14.520401          529            3.168982         3.179802\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 499775  3.818819 -14.526769          529            0.000155         3.179802\n",
+       " 499776  3.820521 -14.526856          529            0.000147         3.179802\n",
+       " 499777  3.822222 -14.526944          529            0.000139         3.179802\n",
+       " 499778  3.823924 -14.527033          529            0.000131         3.179802\n",
+       " 499779  3.825626 -14.527121          529            0.000123         3.179802\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 500118  2.700801 -14.520361          530            3.178704         3.181753\n",
+       " 500119  2.702502 -14.520118          530            3.176819         3.181753\n",
+       " 500120  2.704204 -14.519979          530            3.174811         3.181753\n",
+       " 500121  2.705906 -14.519903          530            3.172730         3.181753\n",
+       " 500122  2.707608 -14.519827          530            3.170649         3.181753\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 500774  3.817117 -14.526661          530            0.000162         3.181753\n",
+       " 500775  3.818819 -14.526754          530            0.000154         3.181753\n",
+       " 500776  3.820521 -14.526848          530            0.000146         3.181753\n",
+       " 500777  3.822222 -14.526941          530            0.000138         3.181753\n",
+       " 500778  3.823924 -14.527035          530            0.000130         3.181753\n",
+       " \n",
+       " [661 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 501118  2.700801 -14.519702          531            3.177071         3.180551\n",
+       " 501119  2.702502 -14.519751          531            3.175085         3.180551\n",
+       " 501120  2.704204 -14.519677          531            3.173029         3.180551\n",
+       " 501121  2.705906 -14.519605          531            3.170973         3.180551\n",
+       " 501122  2.707608 -14.519646          531            3.168943         3.180551\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 501774  3.817117 -14.526529          531            0.000157         3.180551\n",
+       " 501775  3.818819 -14.526613          531            0.000149         3.180551\n",
+       " 501776  3.820521 -14.526698          531            0.000141         3.180551\n",
+       " 501777  3.822222 -14.526783          531            0.000133         3.180551\n",
+       " 501778  3.823924 -14.526868          531            0.000125         3.180551\n",
+       " \n",
+       " [661 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 502118  2.700801 -14.519798          532            3.176628         3.180612\n",
+       " 502119  2.702502 -14.519798          532            3.174639         3.180612\n",
+       " 502120  2.704204 -14.519798          532            3.172649         3.180612\n",
+       " 502121  2.705906 -14.519810          532            3.170647         3.180612\n",
+       " 502122  2.707608 -14.519883          532            3.168574         3.180612\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 502774  3.817117 -14.524784          532            0.000157         3.180612\n",
+       " 502775  3.818819 -14.524849          532            0.000149         3.180612\n",
+       " 502776  3.820521 -14.524914          532            0.000141         3.180612\n",
+       " 502777  3.822222 -14.524978          532            0.000133         3.180612\n",
+       " 502778  3.823924 -14.525043          532            0.000125         3.180612\n",
+       " \n",
+       " [661 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 503118  2.700801 -14.520112          533            3.175464         3.179737\n",
+       " 503119  2.702502 -14.520294          533            3.173456         3.179737\n",
+       " 503120  2.704204 -14.520476          533            3.171448         3.179737\n",
+       " 503121  2.705906 -14.520273          533            3.169403         3.179737\n",
+       " 503122  2.707608 -14.520051          533            3.167356         3.179737\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 503774  3.817117 -14.525669          533            0.000157         3.179737\n",
+       " 503775  3.818819 -14.525739          533            0.000149         3.179737\n",
+       " 503776  3.820521 -14.525809          533            0.000141         3.179737\n",
+       " 503777  3.822222 -14.525880          533            0.000134         3.179737\n",
+       " 503778  3.823924 -14.525950          533            0.000126         3.179737\n",
+       " \n",
+       " [661 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 504118  2.700801 -14.520013          534            3.173826         3.178546\n",
+       " 504119  2.702502 -14.519938          534            3.171819         3.178546\n",
+       " 504120  2.704204 -14.519865          534            3.169811         3.178546\n",
+       " 504121  2.705906 -14.519806          534            3.167804         3.178546\n",
+       " 504122  2.707608 -14.519880          534            3.165810         3.178546\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 504774  3.817117 -14.526275          534            0.000159         3.178546\n",
+       " 504775  3.818819 -14.526360          534            0.000151         3.178546\n",
+       " 504776  3.820521 -14.526443          534            0.000143         3.178546\n",
+       " 504777  3.822222 -14.526528          534            0.000135         3.178546\n",
+       " 504778  3.823924 -14.526612          534            0.000127         3.178546\n",
+       " \n",
+       " [661 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 505118  2.700801 -14.520027          535            3.171067         3.176968\n",
+       " 505119  2.702502 -14.520027          535            3.169007         3.176968\n",
+       " 505120  2.704204 -14.520027          535            3.166947         3.176968\n",
+       " 505121  2.705906 -14.520027          535            3.164907         3.176968\n",
+       " 505122  2.707608 -14.520027          535            3.162918         3.176968\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 505774  3.817117 -14.526477          535            0.000160         3.176968\n",
+       " 505775  3.818819 -14.526564          535            0.000152         3.176968\n",
+       " 505776  3.820521 -14.526650          535            0.000145         3.176968\n",
+       " 505777  3.822222 -14.526737          535            0.000137         3.176968\n",
+       " 505778  3.823924 -14.526824          535            0.000129         3.176968\n",
+       " \n",
+       " [661 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 506118  2.700801 -14.520213          536            3.171268         3.174928\n",
+       " 506119  2.702502 -14.520120          536            3.169256         3.174928\n",
+       " 506120  2.704204 -14.520027          536            3.167244         3.174928\n",
+       " 506121  2.705906 -14.520173          536            3.165213         3.174928\n",
+       " 506122  2.707608 -14.520319          536            3.163183         3.174928\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 506774  3.817117 -14.526923          536            0.000159         3.174928\n",
+       " 506775  3.818819 -14.527016          536            0.000151         3.174928\n",
+       " 506776  3.820521 -14.527108          536            0.000143         3.174928\n",
+       " 506777  3.822222 -14.527201          536            0.000135         3.174928\n",
+       " 506778  3.823924 -14.527294          536            0.000127         3.174928\n",
+       " \n",
+       " [661 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 507118  2.700801 -14.520027          537            3.170089         3.174849\n",
+       " 507119  2.702502 -14.520027          537            3.168146         3.174849\n",
+       " 507120  2.704204 -14.520027          537            3.166202         3.174849\n",
+       " 507121  2.705906 -14.520027          537            3.164075         3.174849\n",
+       " 507122  2.707608 -14.520027          537            3.161941         3.174849\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 507774  3.817117 -14.525194          537            0.000157         3.174849\n",
+       " 507775  3.818819 -14.525270          537            0.000149         3.174849\n",
+       " 507776  3.820521 -14.525346          537            0.000141         3.174849\n",
+       " 507777  3.822222 -14.525421          537            0.000133         3.174849\n",
+       " 507778  3.823924 -14.525497          537            0.000125         3.174849\n",
+       " \n",
+       " [661 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 508118  2.700801 -14.519569          538            3.167801         3.171987\n",
+       " 508119  2.702502 -14.519569          538            3.165795         3.171987\n",
+       " 508120  2.704204 -14.519569          538            3.163788         3.171987\n",
+       " 508121  2.705906 -14.519609          538            3.161775         3.171987\n",
+       " 508122  2.707608 -14.519683          538            3.159757         3.171987\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 508765  3.801802 -14.520853          538            0.000199         3.171987\n",
+       " 508766  3.803504 -14.520875          538            0.000190         3.171987\n",
+       " 508767  3.805205 -14.520896          538            0.000182         3.171987\n",
+       " 508768  3.806907 -14.520917          538            0.000173         3.171987\n",
+       " 508769  3.808609 -14.520938          538            0.000165         3.171987\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 509118  2.700801 -14.520027          539            3.168016         3.170972\n",
+       " 509119  2.702502 -14.520027          539            3.165999         3.170972\n",
+       " 509120  2.704204 -14.520027          539            3.163981         3.170972\n",
+       " 509121  2.705906 -14.520027          539            3.161968         3.170972\n",
+       " 509122  2.707608 -14.520027          539            3.160027         3.170972\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 509774  3.817117 -14.525233          539            0.000156         3.170972\n",
+       " 509775  3.818819 -14.525301          539            0.000148         3.170972\n",
+       " 509776  3.820521 -14.525368          539            0.000140         3.170972\n",
+       " 509777  3.822222 -14.525435          539            0.000132         3.170972\n",
+       " 509778  3.823924 -14.525503          539            0.000125         3.170972\n",
+       " \n",
+       " [661 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 510118  2.700801 -14.520155          540            3.167616         3.171951\n",
+       " 510119  2.702502 -14.519938          540            3.165645         3.171951\n",
+       " 510120  2.704204 -14.519876          540            3.163647         3.171951\n",
+       " 510121  2.705906 -14.520096          540            3.161604         3.171951\n",
+       " 510122  2.707608 -14.520314          540            3.159561         3.171951\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 510774  3.817117 -14.524809          540            0.000158         3.171951\n",
+       " 510775  3.818819 -14.524864          540            0.000150         3.171951\n",
+       " 510776  3.820521 -14.524920          540            0.000143         3.171951\n",
+       " 510777  3.822222 -14.524977          540            0.000135         3.171951\n",
+       " 510778  3.823924 -14.525033          540            0.000127         3.171951\n",
+       " \n",
+       " [661 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 511118  2.700801 -14.519625          541            3.163858         3.168721\n",
+       " 511119  2.702502 -14.519744          541            3.161870         3.168721\n",
+       " 511120  2.704204 -14.519837          541            3.159887         3.168721\n",
+       " 511121  2.705906 -14.519911          541            3.157908         3.168721\n",
+       " 511122  2.707608 -14.519983          541            3.155929         3.168721\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 511774  3.817117 -14.526536          541            0.000157         3.168721\n",
+       " 511775  3.818819 -14.526618          541            0.000149         3.168721\n",
+       " 511776  3.820521 -14.526699          541            0.000141         3.168721\n",
+       " 511777  3.822222 -14.526780          541            0.000134         3.168721\n",
+       " 511778  3.823924 -14.526861          541            0.000126         3.168721\n",
+       " \n",
+       " [661 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 512118  2.700801 -14.520256          542            3.163212         3.167331\n",
+       " 512119  2.702502 -14.520256          542            3.161222         3.167331\n",
+       " 512120  2.704204 -14.520247          542            3.159227         3.167331\n",
+       " 512121  2.705906 -14.520173          542            3.157196         3.167331\n",
+       " 512122  2.707608 -14.520101          542            3.155166         3.167331\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 512774  3.817117 -14.525203          542            0.000158         3.167331\n",
+       " 512775  3.818819 -14.525272          542            0.000150         3.167331\n",
+       " 512776  3.820521 -14.525343          542            0.000143         3.167331\n",
+       " 512777  3.822222 -14.525413          542            0.000135         3.167331\n",
+       " 512778  3.823924 -14.525483          542            0.000127         3.167331\n",
+       " \n",
+       " [661 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 513118  2.700801 -14.519846          543            3.162009         3.166232\n",
+       " 513119  2.702502 -14.519948          543            3.160210         3.166232\n",
+       " 513120  2.704204 -14.520027          543            3.158346         3.166232\n",
+       " 513121  2.705906 -14.520027          543            3.156255         3.166232\n",
+       " 513122  2.707608 -14.520027          543            3.154165         3.166232\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 513774  3.817117 -14.526283          543            0.000157         3.166232\n",
+       " 513775  3.818819 -14.526370          543            0.000149         3.166232\n",
+       " 513776  3.820521 -14.526457          543            0.000141         3.166232\n",
+       " 513777  3.822222 -14.526544          543            0.000134         3.166232\n",
+       " 513778  3.823924 -14.526630          543            0.000126         3.166232\n",
+       " \n",
+       " [661 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 514118  2.700801 -14.519874          544            3.161116         3.165088\n",
+       " 514119  2.702502 -14.520036          544            3.159132         3.165088\n",
+       " 514120  2.704204 -14.520198          544            3.157147         3.165088\n",
+       " 514121  2.705906 -14.520302          544            3.155167         3.165088\n",
+       " 514122  2.707608 -14.520374          544            3.153190         3.165088\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 514774  3.817117 -14.524529          544            0.000158         3.165088\n",
+       " 514775  3.818819 -14.524596          544            0.000150         3.165088\n",
+       " 514776  3.820521 -14.524664          544            0.000142         3.165088\n",
+       " 514777  3.822222 -14.524731          544            0.000135         3.165088\n",
+       " 514778  3.823924 -14.524798          544            0.000127         3.165088\n",
+       " \n",
+       " [661 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 515118  2.700801 -14.520027          545            3.162051         3.164436\n",
+       " 515119  2.702502 -14.520022          545            3.160165         3.164436\n",
+       " 515120  2.704204 -14.519876          545            3.158198         3.164436\n",
+       " 515121  2.705906 -14.519731          545            3.156232         3.164436\n",
+       " 515122  2.707608 -14.519585          545            3.154266         3.164436\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 515764  3.800100 -14.520683          545            0.000205         3.164436\n",
+       " 515765  3.801802 -14.520690          545            0.000197         3.164436\n",
+       " 515766  3.803504 -14.520696          545            0.000188         3.164436\n",
+       " 515767  3.805205 -14.520701          545            0.000180         3.164436\n",
+       " 515768  3.806907 -14.520708          545            0.000171         3.164436\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 516118  2.700801 -14.519942          546            3.162489         3.165214\n",
+       " 516119  2.702502 -14.519798          546            3.160586         3.165214\n",
+       " 516120  2.704204 -14.519798          546            3.158657         3.165214\n",
+       " 516121  2.705906 -14.519798          546            3.156727         3.165214\n",
+       " 516122  2.707608 -14.519807          546            3.154788         3.165214\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 516774  3.817117 -14.524390          546            0.000156         3.165214\n",
+       " 516775  3.818819 -14.524441          546            0.000148         3.165214\n",
+       " 516776  3.820521 -14.524491          546            0.000140         3.165214\n",
+       " 516777  3.822222 -14.524541          546            0.000132         3.165214\n",
+       " 516778  3.823924 -14.524591          546            0.000125         3.165214\n",
+       " \n",
+       " [661 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 517118  2.700801 -14.520229          547            3.158887         3.164873\n",
+       " 517119  2.702502 -14.520157          547            3.156936         3.164873\n",
+       " 517120  2.704204 -14.520085          547            3.154984         3.164873\n",
+       " 517121  2.705906 -14.520069          547            3.153035         3.164873\n",
+       " 517122  2.707608 -14.520288          547            3.151095         3.164873\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 517773  3.815415 -14.526059          547            0.000160         3.164873\n",
+       " 517774  3.817117 -14.526137          547            0.000153         3.164873\n",
+       " 517775  3.818819 -14.526216          547            0.000145         3.164873\n",
+       " 517776  3.820521 -14.526294          547            0.000137         3.164873\n",
+       " 517777  3.822222 -14.526372          547            0.000129         3.164873\n",
+       " \n",
+       " [660 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 518118  2.700801 -14.519706          548            3.155544         3.161053\n",
+       " 518119  2.702502 -14.519997          548            3.153719         3.161053\n",
+       " 518120  2.704204 -14.520095          548            3.151751         3.161053\n",
+       " 518121  2.705906 -14.520169          548            3.149767         3.161053\n",
+       " 518122  2.707608 -14.520245          548            3.147783         3.161053\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 518774  3.817117 -14.525231          548            0.000156         3.161053\n",
+       " 518775  3.818819 -14.525299          548            0.000149         3.161053\n",
+       " 518776  3.820521 -14.525366          548            0.000141         3.161053\n",
+       " 518777  3.822222 -14.525433          548            0.000133         3.161053\n",
+       " 518778  3.823924 -14.525499          548            0.000125         3.161053\n",
+       " \n",
+       " [661 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 519118  2.700801 -14.520075          549            3.153392         3.158648\n",
+       " 519119  2.702502 -14.520177          549            3.151449         3.158648\n",
+       " 519120  2.704204 -14.520240          549            3.149481         3.158648\n",
+       " 519121  2.705906 -14.520168          549            3.147428         3.158648\n",
+       " 519122  2.707608 -14.520096          549            3.145376         3.158648\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 519774  3.817117 -14.525689          549            0.000155         3.158648\n",
+       " 519775  3.818819 -14.525759          549            0.000147         3.158648\n",
+       " 519776  3.820521 -14.525829          549            0.000139         3.158648\n",
+       " 519777  3.822222 -14.525899          549            0.000131         3.158648\n",
+       " 519778  3.823924 -14.525970          549            0.000123         3.158648\n",
+       " \n",
+       " [661 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 520118  2.700801 -14.519958          550            3.152382         3.157241\n",
+       " 520119  2.702502 -14.519811          550            3.150348         3.157241\n",
+       " 520120  2.704204 -14.519662          550            3.148314         3.157241\n",
+       " 520121  2.705906 -14.519596          550            3.146278         3.157241\n",
+       " 520122  2.707608 -14.519668          550            3.144238         3.157241\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 520773  3.815415 -14.526935          550            0.000162         3.157241\n",
+       " 520774  3.817117 -14.527020          550            0.000154         3.157241\n",
+       " 520775  3.818819 -14.527103          550            0.000146         3.157241\n",
+       " 520776  3.820521 -14.527187          550            0.000138         3.157241\n",
+       " 520777  3.822222 -14.527271          550            0.000130         3.157241\n",
+       " \n",
+       " [660 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 521118  2.700801 -14.519821          551            3.151969         3.156217\n",
+       " 521119  2.702502 -14.519969          551            3.149922         3.156217\n",
+       " 521120  2.704204 -14.520117          551            3.147875         3.156217\n",
+       " 521121  2.705906 -14.520247          551            3.145831         3.156217\n",
+       " 521122  2.707608 -14.520100          551            3.143837         3.156217\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 521773  3.815415 -14.525615          551            0.000162         3.156217\n",
+       " 521774  3.817117 -14.525687          551            0.000154         3.156217\n",
+       " 521775  3.818819 -14.525761          551            0.000146         3.156217\n",
+       " 521776  3.820521 -14.525833          551            0.000138         3.156217\n",
+       " 521777  3.822222 -14.525906          551            0.000130         3.156217\n",
+       " \n",
+       " [660 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 522118  2.700801 -14.519798          552            3.151903         3.153897\n",
+       " 522119  2.702502 -14.519798          552            3.149885         3.153897\n",
+       " 522120  2.704204 -14.519798          552            3.147867         3.153897\n",
+       " 522121  2.705906 -14.519798          552            3.145850         3.153897\n",
+       " 522122  2.707608 -14.519798          552            3.143894         3.153897\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 522773  3.815415 -14.524978          552            0.000161         3.153897\n",
+       " 522774  3.817117 -14.525042          552            0.000153         3.153897\n",
+       " 522775  3.818819 -14.525105          552            0.000145         3.153897\n",
+       " 522776  3.820521 -14.525169          552            0.000137         3.153897\n",
+       " 522777  3.822222 -14.525233          552            0.000130         3.153897\n",
+       " \n",
+       " [660 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 523118  2.700801 -14.520235          553            3.150495         3.156109\n",
+       " 523119  2.702502 -14.520161          553            3.148487         3.156109\n",
+       " 523120  2.704204 -14.520087          553            3.146479         3.156109\n",
+       " 523121  2.705906 -14.520041          553            3.144485         3.156109\n",
+       " 523122  2.707608 -14.520114          553            3.142544         3.156109\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 523773  3.815415 -14.526684          553            0.000161         3.156109\n",
+       " 523774  3.817117 -14.526773          553            0.000153         3.156109\n",
+       " 523775  3.818819 -14.526863          553            0.000145         3.156109\n",
+       " 523776  3.820521 -14.526953          553            0.000137         3.156109\n",
+       " 523777  3.822222 -14.527041          553            0.000130         3.156109\n",
+       " \n",
+       " [660 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 524118  2.700801 -14.519681          554            3.151590         3.154674\n",
+       " 524119  2.702502 -14.519977          554            3.149647         3.154674\n",
+       " 524120  2.704204 -14.520272          554            3.147705         3.154674\n",
+       " 524121  2.705906 -14.520442          554            3.145746         3.154674\n",
+       " 524122  2.707608 -14.520292          554            3.143749         3.154674\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 524774  3.817117 -14.524807          554            0.000155         3.154674\n",
+       " 524775  3.818819 -14.524868          554            0.000147         3.154674\n",
+       " 524776  3.820521 -14.524929          554            0.000140         3.154674\n",
+       " 524777  3.822222 -14.524991          554            0.000132         3.154674\n",
+       " 524778  3.823924 -14.525052          554            0.000124         3.154674\n",
+       " \n",
+       " [661 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 525118  2.700801 -14.519582          555            3.149383         3.153219\n",
+       " 525119  2.702502 -14.519483          555            3.147507         3.153219\n",
+       " 525120  2.704204 -14.519778          555            3.145461         3.153219\n",
+       " 525121  2.705906 -14.520075          555            3.143414         3.153219\n",
+       " 525122  2.707608 -14.520171          555            3.141383         3.153219\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 525774  3.817117 -14.526766          555            0.000156         3.153219\n",
+       " 525775  3.818819 -14.526850          555            0.000148         3.153219\n",
+       " 525776  3.820521 -14.526934          555            0.000140         3.153219\n",
+       " 525777  3.822222 -14.527017          555            0.000132         3.153219\n",
+       " 525778  3.823924 -14.527101          555            0.000125         3.153219\n",
+       " \n",
+       " [661 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 526118  2.700801 -14.520079          556            3.148608         3.151301\n",
+       " 526119  2.702502 -14.520190          556            3.146614         3.151301\n",
+       " 526120  2.704204 -14.520197          556            3.144641         3.151301\n",
+       " 526121  2.705906 -14.520051          556            3.142700         3.151301\n",
+       " 526122  2.707608 -14.519905          556            3.140759         3.151301\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 526764  3.800100 -14.522422          556            0.000202         3.151301\n",
+       " 526765  3.801802 -14.522449          556            0.000193         3.151301\n",
+       " 526766  3.803504 -14.522475          556            0.000185         3.151301\n",
+       " 526767  3.805205 -14.522502          556            0.000176         3.151301\n",
+       " 526768  3.806907 -14.522530          556            0.000168         3.151301\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 527118  2.700801 -14.519899          557            3.147672          3.15191\n",
+       " 527119  2.702502 -14.519627          557            3.145744          3.15191\n",
+       " 527120  2.704204 -14.519353          557            3.143816          3.15191\n",
+       " 527121  2.705906 -14.519482          557            3.141787          3.15191\n",
+       " 527122  2.707608 -14.519629          557            3.139753          3.15191\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 527773  3.815415 -14.524781          557            0.000160          3.15191\n",
+       " 527774  3.817117 -14.524839          557            0.000152          3.15191\n",
+       " 527775  3.818819 -14.524899          557            0.000145          3.15191\n",
+       " 527776  3.820521 -14.524957          557            0.000137          3.15191\n",
+       " 527777  3.822222 -14.525015          557            0.000129          3.15191\n",
+       " \n",
+       " [660 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 528118  2.700801 -14.519798          558            3.144671         3.151625\n",
+       " 528119  2.702502 -14.519869          558            3.142674         3.151625\n",
+       " 528120  2.704204 -14.520018          558            3.140640         3.151625\n",
+       " 528121  2.705906 -14.520165          558            3.138606         3.151625\n",
+       " 528122  2.707608 -14.520228          558            3.136604         3.151625\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 528764  3.800100 -14.520669          558            0.000205         3.151625\n",
+       " 528765  3.801802 -14.520678          558            0.000197         3.151625\n",
+       " 528766  3.803504 -14.520687          558            0.000188         3.151625\n",
+       " 528767  3.805205 -14.520696          558            0.000180         3.151625\n",
+       " 528768  3.806907 -14.520705          558            0.000171         3.151625\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 529118  2.700801 -14.520211          559            3.146120         3.148376\n",
+       " 529119  2.702502 -14.520115          559            3.144151         3.148376\n",
+       " 529120  2.704204 -14.520000          559            3.142182         3.148376\n",
+       " 529121  2.705906 -14.519705          559            3.140213         3.148376\n",
+       " 529122  2.707608 -14.519408          559            3.138245         3.148376\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 529774  3.817117 -14.526133          559            0.000154         3.148376\n",
+       " 529775  3.818819 -14.526208          559            0.000146         3.148376\n",
+       " 529776  3.820521 -14.526282          559            0.000138         3.148376\n",
+       " 529777  3.822222 -14.526358          559            0.000131         3.148376\n",
+       " 529778  3.823924 -14.526433          559            0.000123         3.148376\n",
+       " \n",
+       " [661 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 530118  2.700801 -14.519810          560            3.146420         3.151044\n",
+       " 530119  2.702502 -14.519882          560            3.144479         3.151044\n",
+       " 530120  2.704204 -14.519956          560            3.142538         3.151044\n",
+       " 530121  2.705906 -14.520026          560            3.140597         3.151044\n",
+       " 530122  2.707608 -14.519952          560            3.138576         3.151044\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 530774  3.817117 -14.524151          560            0.000154         3.151044\n",
+       " 530775  3.818819 -14.524207          560            0.000146         3.151044\n",
+       " 530776  3.820521 -14.524262          560            0.000138         3.151044\n",
+       " 530777  3.822222 -14.524318          560            0.000131         3.151044\n",
+       " 530778  3.823924 -14.524374          560            0.000123         3.151044\n",
+       " \n",
+       " [661 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 531118  2.700801 -14.519845          566            3.236779         3.338232\n",
+       " 531119  2.702502 -14.519945          566            3.234098         3.338232\n",
+       " 531120  2.704204 -14.520001          566            3.231425         3.338232\n",
+       " 531121  2.705906 -14.519857          566            3.228790         3.338232\n",
+       " 531122  2.707608 -14.519713          566            3.226154         3.338232\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 531776  3.820521 -14.525857          566            0.000159         3.338232\n",
+       " 531777  3.822222 -14.525932          566            0.000151         3.338232\n",
+       " 531778  3.823924 -14.526008          566            0.000143         3.338232\n",
+       " 531779  3.825626 -14.526083          566            0.000135         3.338232\n",
+       " 531780  3.827327 -14.526159          566            0.000128         3.338232\n",
+       " \n",
+       " [663 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 532118  2.700801 -14.520048          567            3.224077         3.236069\n",
+       " 532119  2.702502 -14.520123          567            3.221418         3.236069\n",
+       " 532120  2.704204 -14.520196          567            3.218758         3.236069\n",
+       " 532121  2.705906 -14.520256          567            3.216096         3.236069\n",
+       " 532122  2.707608 -14.520256          567            3.213423         3.236069\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 532775  3.818819 -14.524794          567            0.000159         3.236069\n",
+       " 532776  3.820521 -14.524852          567            0.000151         3.236069\n",
+       " 532777  3.822222 -14.524910          567            0.000143         3.236069\n",
+       " 532778  3.823924 -14.524969          567            0.000135         3.236069\n",
+       " 532779  3.825626 -14.525027          567            0.000127         3.236069\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 533118  2.700801 -14.519531          568            3.207631         3.224248\n",
+       " 533119  2.702502 -14.519448          568            3.204975         3.224248\n",
+       " 533120  2.704204 -14.519366          568            3.202320         3.224248\n",
+       " 533121  2.705906 -14.519392          568            3.199608         3.224248\n",
+       " 533122  2.707608 -14.519467          568            3.196869         3.224248\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 533775  3.818819 -14.524571          568            0.000155         3.224248\n",
+       " 533776  3.820521 -14.524635          568            0.000147         3.224248\n",
+       " 533777  3.822222 -14.524699          568            0.000139         3.224248\n",
+       " 533778  3.823924 -14.524762          568            0.000131         3.224248\n",
+       " 533779  3.825626 -14.524826          568            0.000123         3.224248\n",
+       " \n",
+       " [662 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 534118  2.700801 -14.519798          569            3.197689         3.208632\n",
+       " 534119  2.702502 -14.519787          569            3.195067         3.208632\n",
+       " 534120  2.704204 -14.519639          569            3.192329         3.208632\n",
+       " 534121  2.705906 -14.519491          569            3.189591         3.208632\n",
+       " 534122  2.707608 -14.519343          569            3.186853         3.208632\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 534774  3.817117 -14.526258          569            0.000160         3.208632\n",
+       " 534775  3.818819 -14.526342          569            0.000152         3.208632\n",
+       " 534776  3.820521 -14.526428          569            0.000144         3.208632\n",
+       " 534777  3.822222 -14.526514          569            0.000136         3.208632\n",
+       " 534778  3.823924 -14.526600          569            0.000128         3.208632\n",
+       " \n",
+       " [661 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 535118  2.700801 -14.519646          570            3.187417          3.19891\n",
+       " 535119  2.702502 -14.519798          570            3.184827          3.19891\n",
+       " 535120  2.704204 -14.519798          570            3.182141          3.19891\n",
+       " 535121  2.705906 -14.519798          570            3.179456          3.19891\n",
+       " 535122  2.707608 -14.519800          570            3.176769          3.19891\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 535774  3.817117 -14.526095          570            0.000157          3.19891\n",
+       " 535775  3.818819 -14.526173          570            0.000149          3.19891\n",
+       " 535776  3.820521 -14.526251          570            0.000141          3.19891\n",
+       " 535777  3.822222 -14.526328          570            0.000133          3.19891\n",
+       " 535778  3.823924 -14.526405          570            0.000126          3.19891\n",
+       " \n",
+       " [661 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 536118  2.700801 -14.520101          571            3.179418         3.187918\n",
+       " 536119  2.702502 -14.519768          571            3.176719         3.187918\n",
+       " 536120  2.704204 -14.519659          571            3.174009         3.187918\n",
+       " 536121  2.705906 -14.519881          571            3.171284         3.187918\n",
+       " 536122  2.707608 -14.520103          571            3.168560         3.187918\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 536774  3.817117 -14.527003          571            0.000154         3.187918\n",
+       " 536775  3.818819 -14.527088          571            0.000146         3.187918\n",
+       " 536776  3.820521 -14.527174          571            0.000139         3.187918\n",
+       " 536777  3.822222 -14.527259          571            0.000131         3.187918\n",
+       " 536778  3.823924 -14.527345          571            0.000123         3.187918\n",
+       " \n",
+       " [661 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 537118  2.700801 -14.519759          572            3.175446         3.182068\n",
+       " 537119  2.702502 -14.519683          572            3.172868         3.182068\n",
+       " 537120  2.704204 -14.519607          572            3.170290         3.182068\n",
+       " 537121  2.705906 -14.519607          572            3.167696         3.182068\n",
+       " 537122  2.707608 -14.519679          572            3.165087         3.182068\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 537773  3.815415 -14.526948          572            0.000159         3.182068\n",
+       " 537774  3.817117 -14.527033          572            0.000151         3.182068\n",
+       " 537775  3.818819 -14.527119          572            0.000144         3.182068\n",
+       " 537776  3.820521 -14.527204          572            0.000136         3.182068\n",
+       " 537777  3.822222 -14.527289          572            0.000128         3.182068\n",
+       " \n",
+       " [660 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 538118  2.700801 -14.519917          573            3.170670         3.177814\n",
+       " 538119  2.702502 -14.520027          573            3.168109         3.177814\n",
+       " 538120  2.704204 -14.520027          573            3.165449         3.177814\n",
+       " 538121  2.705906 -14.520027          573            3.162789         3.177814\n",
+       " 538122  2.707608 -14.520027          573            3.160134         3.177814\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 538773  3.815415 -14.525217          573            0.000157         3.177814\n",
+       " 538774  3.817117 -14.525286          573            0.000149         3.177814\n",
+       " 538775  3.818819 -14.525354          573            0.000141         3.177814\n",
+       " 538776  3.820521 -14.525423          573            0.000133         3.177814\n",
+       " 538777  3.822222 -14.525492          573            0.000126         3.177814\n",
+       " \n",
+       " [660 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 539118  2.700801 -14.519844          574            3.161340         3.170916\n",
+       " 539119  2.702502 -14.520233          574            3.158835         3.170916\n",
+       " 539120  2.704204 -14.520159          574            3.156215         3.170916\n",
+       " 539121  2.705906 -14.520083          574            3.153596         3.170916\n",
+       " 539122  2.707608 -14.520027          574            3.150963         3.170916\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 539772  3.813714 -14.523916          574            0.000161         3.170916\n",
+       " 539773  3.815415 -14.523962          574            0.000153         3.170916\n",
+       " 539774  3.817117 -14.524009          574            0.000145         3.170916\n",
+       " 539775  3.818819 -14.524055          574            0.000138         3.170916\n",
+       " 539776  3.820521 -14.524102          574            0.000130         3.170916\n",
+       " \n",
+       " [659 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 540118  2.700801 -14.519834          575            3.155546         3.164058\n",
+       " 540119  2.702502 -14.520076          575            3.152951         3.164058\n",
+       " 540120  2.704204 -14.520150          575            3.150356         3.164058\n",
+       " 540121  2.705906 -14.520224          575            3.147761         3.164058\n",
+       " 540122  2.707608 -14.520214          575            3.145123         3.164058\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 540764  3.800100 -14.520207          575            0.000197         3.164058\n",
+       " 540765  3.801802 -14.520220          575            0.000189         3.164058\n",
+       " 540766  3.803504 -14.520231          575            0.000180         3.164058\n",
+       " 540767  3.805205 -14.520244          575            0.000172         3.164058\n",
+       " 540768  3.806907 -14.520255          575            0.000164         3.164058\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 541118  2.700801 -14.519914          576            3.151506          3.15923\n",
+       " 541119  2.702502 -14.519670          576            3.148979          3.15923\n",
+       " 541120  2.704204 -14.519427          576            3.146451          3.15923\n",
+       " 541121  2.705906 -14.519481          576            3.143880          3.15923\n",
+       " 541122  2.707608 -14.519700          576            3.141284          3.15923\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 541772  3.813714 -14.523664          576            0.000160          3.15923\n",
+       " 541773  3.815415 -14.523717          576            0.000152          3.15923\n",
+       " 541774  3.817117 -14.523768          576            0.000145          3.15923\n",
+       " 541775  3.818819 -14.523821          576            0.000137          3.15923\n",
+       " 541776  3.820521 -14.523872          576            0.000129          3.15923\n",
+       " \n",
+       " [659 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 542118  2.700801 -14.519798          577            3.147650         3.154124\n",
+       " 542119  2.702502 -14.519798          577            3.145158         3.154124\n",
+       " 542120  2.704204 -14.519775          577            3.142669         3.154124\n",
+       " 542121  2.705906 -14.519703          577            3.140188         3.154124\n",
+       " 542122  2.707608 -14.519629          577            3.137708         3.154124\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 542763  3.798398 -14.519812          577            0.000201         3.154124\n",
+       " 542764  3.800100 -14.519809          577            0.000192         3.154124\n",
+       " 542765  3.801802 -14.519806          577            0.000184         3.154124\n",
+       " 542766  3.803504 -14.519803          577            0.000176         3.154124\n",
+       " 542767  3.805205 -14.519800          577            0.000167         3.154124\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 543118  2.700801 -14.519644          578            3.149592         3.154346\n",
+       " 543119  2.702502 -14.519869          578            3.147078         3.154346\n",
+       " 543120  2.704204 -14.520095          578            3.144565         3.154346\n",
+       " 543121  2.705906 -14.520256          578            3.142044         3.154346\n",
+       " 543122  2.707608 -14.520256          578            3.139503         3.154346\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 543772  3.813714 -14.525181          578            0.000161         3.154346\n",
+       " 543773  3.815415 -14.525249          578            0.000153         3.154346\n",
+       " 543774  3.817117 -14.525317          578            0.000145         3.154346\n",
+       " 543775  3.818819 -14.525386          578            0.000138         3.154346\n",
+       " 543776  3.820521 -14.525455          578            0.000130         3.154346\n",
+       " \n",
+       " [659 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 544118  2.700801 -14.520373          579            3.144103           3.1511\n",
+       " 544119  2.702502 -14.520134          579            3.141615           3.1511\n",
+       " 544120  2.704204 -14.519895          579            3.139127           3.1511\n",
+       " 544121  2.705906 -14.519842          579            3.136677           3.1511\n",
+       " 544122  2.707608 -14.519917          579            3.134252           3.1511\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 544772  3.813714 -14.526296          579            0.000158           3.1511\n",
+       " 544773  3.815415 -14.526376          579            0.000151           3.1511\n",
+       " 544774  3.817117 -14.526455          579            0.000143           3.1511\n",
+       " 544775  3.818819 -14.526534          579            0.000135           3.1511\n",
+       " 544776  3.820521 -14.526613          579            0.000127           3.1511\n",
+       " \n",
+       " [659 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 545118  2.700801 -14.519469          580            3.138419         3.144982\n",
+       " 545119  2.702502 -14.519745          580            3.136109         3.144982\n",
+       " 545120  2.704204 -14.519859          580            3.133592         3.144982\n",
+       " 545121  2.705906 -14.519934          580            3.131025         3.144982\n",
+       " 545122  2.707608 -14.520009          580            3.128459         3.144982\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 545772  3.813714 -14.524989          580            0.000157         3.144982\n",
+       " 545773  3.815415 -14.525058          580            0.000149         3.144982\n",
+       " 545774  3.817117 -14.525126          580            0.000141         3.144982\n",
+       " 545775  3.818819 -14.525194          580            0.000133         3.144982\n",
+       " 545776  3.820521 -14.525263          580            0.000126         3.144982\n",
+       " \n",
+       " [659 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 546118  2.700801 -14.520027          581            3.138355         3.140671\n",
+       " 546119  2.702502 -14.520073          581            3.135973         3.140671\n",
+       " 546120  2.704204 -14.520146          581            3.133522         3.140671\n",
+       " 546121  2.705906 -14.520221          581            3.131071         3.140671\n",
+       " 546122  2.707608 -14.520217          581            3.128587         3.140671\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 546772  3.813714 -14.523906          581            0.000157         3.140671\n",
+       " 546773  3.815415 -14.523960          581            0.000149         3.140671\n",
+       " 546774  3.817117 -14.524014          581            0.000141         3.140671\n",
+       " 546775  3.818819 -14.524069          581            0.000133         3.140671\n",
+       " 546776  3.820521 -14.524124          581            0.000126         3.140671\n",
+       " \n",
+       " [659 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 547118  2.700801 -14.520214          582            3.133295           3.1415\n",
+       " 547119  2.702502 -14.520124          582            3.130896           3.1415\n",
+       " 547120  2.704204 -14.520035          582            3.128497           3.1415\n",
+       " 547121  2.705906 -14.519891          582            3.125946           3.1415\n",
+       " 547122  2.707608 -14.519740          582            3.123379           3.1415\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 547772  3.813714 -14.526495          582            0.000159           3.1415\n",
+       " 547773  3.815415 -14.526580          582            0.000151           3.1415\n",
+       " 547774  3.817117 -14.526665          582            0.000143           3.1415\n",
+       " 547775  3.818819 -14.526750          582            0.000136           3.1415\n",
+       " 547776  3.820521 -14.526834          582            0.000128           3.1415\n",
+       " \n",
+       " [659 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 548118  2.700801 -14.519938          583            3.131056         3.136073\n",
+       " 548119  2.702502 -14.519745          583            3.128612         3.136073\n",
+       " 548120  2.704204 -14.519583          583            3.126160         3.136073\n",
+       " 548121  2.705906 -14.519733          583            3.123633         3.136073\n",
+       " 548122  2.707608 -14.519883          583            3.121106         3.136073\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 548772  3.813714 -14.525263          583            0.000156         3.136073\n",
+       " 548773  3.815415 -14.525323          583            0.000148         3.136073\n",
+       " 548774  3.817117 -14.525383          583            0.000140         3.136073\n",
+       " 548775  3.818819 -14.525443          583            0.000132         3.136073\n",
+       " 548776  3.820521 -14.525503          583            0.000125         3.136073\n",
+       " \n",
+       " [659 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 549118  2.700801 -14.519851          584            3.139348          3.14231\n",
+       " 549119  2.702502 -14.519964          584            3.136869          3.14231\n",
+       " 549120  2.704204 -14.519994          584            3.134420          3.14231\n",
+       " 549121  2.705906 -14.519920          584            3.132008          3.14231\n",
+       " 549122  2.707608 -14.519846          584            3.129596          3.14231\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 549772  3.813714 -14.526060          584            0.000160          3.14231\n",
+       " 549773  3.815415 -14.526136          584            0.000153          3.14231\n",
+       " 549774  3.817117 -14.526213          584            0.000145          3.14231\n",
+       " 549775  3.818819 -14.526289          584            0.000137          3.14231\n",
+       " 549776  3.820521 -14.526366          584            0.000130          3.14231\n",
+       " \n",
+       " [659 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 550118  2.700801 -14.519724          585            3.129870         3.135516\n",
+       " 550119  2.702502 -14.519571          585            3.127559         3.135516\n",
+       " 550120  2.704204 -14.519646          585            3.125069         3.135516\n",
+       " 550121  2.705906 -14.519720          585            3.122579         3.135516\n",
+       " 550122  2.707608 -14.519794          585            3.120088         3.135516\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 550772  3.813714 -14.525234          585            0.000156         3.135516\n",
+       " 550773  3.815415 -14.525299          585            0.000148         3.135516\n",
+       " 550774  3.817117 -14.525365          585            0.000141         3.135516\n",
+       " 550775  3.818819 -14.525430          585            0.000133         3.135516\n",
+       " 550776  3.820521 -14.525496          585            0.000125         3.135516\n",
+       " \n",
+       " [659 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 551118  2.700801 -14.519934          586            3.126294          3.13204\n",
+       " 551119  2.702502 -14.519733          586            3.123930          3.13204\n",
+       " 551120  2.704204 -14.519583          586            3.121547          3.13204\n",
+       " 551121  2.705906 -14.519655          586            3.119080          3.13204\n",
+       " 551122  2.707608 -14.519729          586            3.116612          3.13204\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 551771  3.812012 -14.525182          586            0.000161          3.13204\n",
+       " 551772  3.813714 -14.525250          586            0.000153          3.13204\n",
+       " 551773  3.815415 -14.525318          586            0.000145          3.13204\n",
+       " 551774  3.817117 -14.525386          586            0.000138          3.13204\n",
+       " 551775  3.818819 -14.525455          586            0.000130          3.13204\n",
+       " \n",
+       " [658 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 552118  2.700801 -14.519871          587            3.123690         3.127704\n",
+       " 552119  2.702502 -14.520013          587            3.121491         3.127704\n",
+       " 552120  2.704204 -14.519960          587            3.119113         3.127704\n",
+       " 552121  2.705906 -14.519887          587            3.116714         3.127704\n",
+       " 552122  2.707608 -14.519813          587            3.114315         3.127704\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 552762  3.796697 -14.520456          587            0.000203         3.127704\n",
+       " 552763  3.798398 -14.520462          587            0.000195         3.127704\n",
+       " 552764  3.800100 -14.520468          587            0.000186         3.127704\n",
+       " 552765  3.801802 -14.520474          587            0.000178         3.127704\n",
+       " 552766  3.803504 -14.520480          587            0.000170         3.127704\n",
+       " \n",
+       " [649 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 553118  2.700801 -14.519841          588            3.120908         3.127712\n",
+       " 553119  2.702502 -14.519992          588            3.118540         3.127712\n",
+       " 553120  2.704204 -14.520142          588            3.116172         3.127712\n",
+       " 553121  2.705906 -14.520238          588            3.113786         3.127712\n",
+       " 553122  2.707608 -14.520162          588            3.111342         3.127712\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 553771  3.812012 -14.523903          588            0.000161         3.127712\n",
+       " 553772  3.813714 -14.523952          588            0.000153         3.127712\n",
+       " 553773  3.815415 -14.524001          588            0.000145         3.127712\n",
+       " 553774  3.817117 -14.524050          588            0.000138         3.127712\n",
+       " 553775  3.818819 -14.524099          588            0.000130         3.127712\n",
+       " \n",
+       " [658 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 554118  2.700801 -14.520008          589            3.119192         3.123897\n",
+       " 554119  2.702502 -14.520458          589            3.116996         3.123897\n",
+       " 554120  2.704204 -14.520276          589            3.114646         3.123897\n",
+       " 554121  2.705906 -14.520054          589            3.112286         3.123897\n",
+       " 554122  2.707608 -14.519832          589            3.109926         3.123897\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 554772  3.813714 -14.523923          589            0.000156         3.123897\n",
+       " 554773  3.815415 -14.523974          589            0.000148         3.123897\n",
+       " 554774  3.817117 -14.524026          589            0.000140         3.123897\n",
+       " 554775  3.818819 -14.524078          589            0.000133         3.123897\n",
+       " 554776  3.820521 -14.524130          589            0.000125         3.123897\n",
+       " \n",
+       " [659 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 555118  2.700801 -14.520027          590            3.119148         3.123546\n",
+       " 555119  2.702502 -14.520027          590            3.116769         3.123546\n",
+       " 555120  2.704204 -14.519962          590            3.114417         3.123546\n",
+       " 555121  2.705906 -14.519819          590            3.112098         3.123546\n",
+       " 555122  2.707608 -14.519675          590            3.109779         3.123546\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 555772  3.813714 -14.525261          590            0.000154         3.123546\n",
+       " 555773  3.815415 -14.525323          590            0.000147         3.123546\n",
+       " 555774  3.817117 -14.525386          590            0.000139         3.123546\n",
+       " 555775  3.818819 -14.525448          590            0.000131         3.123546\n",
+       " 555776  3.820521 -14.525511          590            0.000124         3.123546\n",
+       " \n",
+       " [659 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 556118  2.700801 -14.519399          591            3.117296         3.119713\n",
+       " 556119  2.702502 -14.519523          591            3.114927         3.119713\n",
+       " 556120  2.704204 -14.519660          591            3.112597         3.119713\n",
+       " 556121  2.705906 -14.519803          591            3.110291         3.119713\n",
+       " 556122  2.707608 -14.519947          591            3.107985         3.119713\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 556772  3.813714 -14.526093          591            0.000155         3.119713\n",
+       " 556773  3.815415 -14.526175          591            0.000147         3.119713\n",
+       " 556774  3.817117 -14.526257          591            0.000139         3.119713\n",
+       " 556775  3.818819 -14.526338          591            0.000132         3.119713\n",
+       " 556776  3.820521 -14.526420          591            0.000124         3.119713\n",
+       " \n",
+       " [659 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 557118  2.700801 -14.519869          592            3.114822          3.12144\n",
+       " 557119  2.702502 -14.519857          592            3.112517          3.12144\n",
+       " 557120  2.704204 -14.519931          592            3.110235          3.12144\n",
+       " 557121  2.705906 -14.520005          592            3.107953          3.12144\n",
+       " 557122  2.707608 -14.520027          592            3.105596          3.12144\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 557772  3.813714 -14.525890          592            0.000156          3.12144\n",
+       " 557773  3.815415 -14.525965          592            0.000148          3.12144\n",
+       " 557774  3.817117 -14.526038          592            0.000140          3.12144\n",
+       " 557775  3.818819 -14.526112          592            0.000132          3.12144\n",
+       " 557776  3.820521 -14.526186          592            0.000125          3.12144\n",
+       " \n",
+       " [659 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 558118  2.700801 -14.519984          593            3.112296          3.11722\n",
+       " 558119  2.702502 -14.519894          593            3.110015          3.11722\n",
+       " 558120  2.704204 -14.519802          593            3.107734          3.11722\n",
+       " 558121  2.705906 -14.519659          593            3.105348          3.11722\n",
+       " 558122  2.707608 -14.519513          593            3.102958          3.11722\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 558772  3.813714 -14.526116          593            0.000155          3.11722\n",
+       " 558773  3.815415 -14.526193          593            0.000147          3.11722\n",
+       " 558774  3.817117 -14.526269          593            0.000139          3.11722\n",
+       " 558775  3.818819 -14.526344          593            0.000132          3.11722\n",
+       " 558776  3.820521 -14.526421          593            0.000124          3.11722\n",
+       " \n",
+       " [659 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 559118  2.700801 -14.519569          594            3.114468         3.117651\n",
+       " 559119  2.702502 -14.519789          594            3.112130         3.117651\n",
+       " 559120  2.704204 -14.520014          594            3.109788         3.117651\n",
+       " 559121  2.705906 -14.520239          594            3.107446         3.117651\n",
+       " 559122  2.707608 -14.520256          594            3.105100         3.117651\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 559771  3.812012 -14.526717          594            0.000161         3.117651\n",
+       " 559772  3.813714 -14.526799          594            0.000153         3.117651\n",
+       " 559773  3.815415 -14.526880          594            0.000145         3.117651\n",
+       " 559774  3.817117 -14.526961          594            0.000138         3.117651\n",
+       " 559775  3.818819 -14.527043          594            0.000130         3.117651\n",
+       " \n",
+       " [658 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 560118  2.700801 -14.519798          595            3.113157         3.116066\n",
+       " 560119  2.702502 -14.519798          595            3.110817         3.116066\n",
+       " 560120  2.704204 -14.519847          595            3.108548         3.116066\n",
+       " 560121  2.705906 -14.519920          595            3.106312         3.116066\n",
+       " 560122  2.707608 -14.519993          595            3.104075         3.116066\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 560772  3.813714 -14.526562          595            0.000154         3.116066\n",
+       " 560773  3.815415 -14.526643          595            0.000146         3.116066\n",
+       " 560774  3.817117 -14.526725          595            0.000138         3.116066\n",
+       " 560775  3.818819 -14.526807          595            0.000131         3.116066\n",
+       " 560776  3.820521 -14.526888          595            0.000123         3.116066\n",
+       " \n",
+       " [659 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 561118  2.700801 -14.519798          596            3.109566         3.115184\n",
+       " 561119  2.702502 -14.519798          596            3.107398         3.115184\n",
+       " 561120  2.704204 -14.519798          596            3.105230         3.115184\n",
+       " 561121  2.705906 -14.519798          596            3.102919         3.115184\n",
+       " 561122  2.707608 -14.519798          596            3.100556         3.115184\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 561772  3.813714 -14.526051          596            0.000158         3.115184\n",
+       " 561773  3.815415 -14.526135          596            0.000150         3.115184\n",
+       " 561774  3.817117 -14.526219          596            0.000142         3.115184\n",
+       " 561775  3.818819 -14.526304          596            0.000134         3.115184\n",
+       " 561776  3.820521 -14.526389          596            0.000127         3.115184\n",
+       " \n",
+       " [659 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 562118  2.700801 -14.519810          597            3.108453         3.114076\n",
+       " 562119  2.702502 -14.519882          597            3.106166         3.114076\n",
+       " 562120  2.704204 -14.519956          597            3.103878         3.114076\n",
+       " 562121  2.705906 -14.520027          597            3.101591         3.114076\n",
+       " 562122  2.707608 -14.520027          597            3.099336         3.114076\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 562762  3.796697 -14.520445          597            0.000200         3.114076\n",
+       " 562763  3.798398 -14.520453          597            0.000192         3.114076\n",
+       " 562764  3.800100 -14.520462          597            0.000184         3.114076\n",
+       " 562765  3.801802 -14.520472          597            0.000176         3.114076\n",
+       " 562766  3.803504 -14.520480          597            0.000167         3.114076\n",
+       " \n",
+       " [649 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 563118  2.700801 -14.520026          598            3.105776         3.110069\n",
+       " 563119  2.702502 -14.519952          598            3.103442         3.110069\n",
+       " 563120  2.704204 -14.519877          598            3.101108         3.110069\n",
+       " 563121  2.705906 -14.519804          598            3.098774         3.110069\n",
+       " 563122  2.707608 -14.519798          598            3.096555         3.110069\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 563771  3.812012 -14.525642          598            0.000159         3.110069\n",
+       " 563772  3.813714 -14.525713          598            0.000151         3.110069\n",
+       " 563773  3.815415 -14.525784          598            0.000144         3.110069\n",
+       " 563774  3.817117 -14.525854          598            0.000136         3.110069\n",
+       " 563775  3.818819 -14.525925          598            0.000128         3.110069\n",
+       " \n",
+       " [658 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 564118  2.700801 -14.520027          599            3.103353         3.107265\n",
+       " 564119  2.702502 -14.519996          599            3.101029         3.107265\n",
+       " 564120  2.704204 -14.519848          599            3.098786         3.107265\n",
+       " 564121  2.705906 -14.519700          599            3.096544         3.107265\n",
+       " 564122  2.707608 -14.519578          599            3.094301         3.107265\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 564771  3.812012 -14.524789          599            0.000159         3.107265\n",
+       " 564772  3.813714 -14.524846          599            0.000152         3.107265\n",
+       " 564773  3.815415 -14.524903          599            0.000144         3.107265\n",
+       " 564774  3.817117 -14.524961          599            0.000136         3.107265\n",
+       " 564775  3.818819 -14.525017          599            0.000129         3.107265\n",
+       " \n",
+       " [658 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 565118  2.700801 -14.519845          600            3.102490         3.107851\n",
+       " 565119  2.702502 -14.519945          600            3.100286         3.107851\n",
+       " 565120  2.704204 -14.520027          600            3.098077         3.107851\n",
+       " 565121  2.705906 -14.520027          600            3.095854         3.107851\n",
+       " 565122  2.707608 -14.520027          600            3.093631         3.107851\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 565771  3.812012 -14.525201          600            0.000158         3.107851\n",
+       " 565772  3.813714 -14.525269          600            0.000151         3.107851\n",
+       " 565773  3.815415 -14.525337          600            0.000143         3.107851\n",
+       " 565774  3.817117 -14.525405          600            0.000136         3.107851\n",
+       " 565775  3.818819 -14.525473          600            0.000128         3.107851\n",
+       " \n",
+       " [658 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 566118  2.700801 -14.520027          601            3.100680         3.104814\n",
+       " 566119  2.702502 -14.520027          601            3.098508         3.104814\n",
+       " 566120  2.704204 -14.520027          601            3.096336         3.104814\n",
+       " 566121  2.705906 -14.520027          601            3.094164         3.104814\n",
+       " 566122  2.707608 -14.520027          601            3.091927         3.104814\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 566771  3.812012 -14.525643          601            0.000157         3.104814\n",
+       " 566772  3.813714 -14.525717          601            0.000150         3.104814\n",
+       " 566773  3.815415 -14.525789          601            0.000142         3.104814\n",
+       " 566774  3.817117 -14.525863          601            0.000135         3.104814\n",
+       " 566775  3.818819 -14.525936          601            0.000127         3.104814\n",
+       " \n",
+       " [658 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 567118  2.700801 -14.519798          602            3.100937         3.104079\n",
+       " 567119  2.702502 -14.519798          602            3.098821         3.104079\n",
+       " 567120  2.704204 -14.519798          602            3.096610         3.104079\n",
+       " 567121  2.705906 -14.519798          602            3.094400         3.104079\n",
+       " 567122  2.707608 -14.519798          602            3.092181         3.104079\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 567771  3.812012 -14.524539          602            0.000160         3.104079\n",
+       " 567772  3.813714 -14.524599          602            0.000153         3.104079\n",
+       " 567773  3.815415 -14.524658          602            0.000145         3.104079\n",
+       " 567774  3.817117 -14.524718          602            0.000137         3.104079\n",
+       " 567775  3.818819 -14.524778          602            0.000130         3.104079\n",
+       " \n",
+       " [658 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 568118  2.700801 -14.520395          603            3.101739          3.10407\n",
+       " 568119  2.702502 -14.520203          603            3.099566          3.10407\n",
+       " 568120  2.704204 -14.520014          603            3.097387          3.10407\n",
+       " 568121  2.705906 -14.519866          603            3.095145          3.10407\n",
+       " 568122  2.707608 -14.519718          603            3.092902          3.10407\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 568762  3.796697 -14.520850          603            0.000200          3.10407\n",
+       " 568763  3.798398 -14.520871          603            0.000192          3.10407\n",
+       " 568764  3.800100 -14.520891          603            0.000183          3.10407\n",
+       " 568765  3.801802 -14.520912          603            0.000175          3.10407\n",
+       " 568766  3.803504 -14.520932          603            0.000167          3.10407\n",
+       " \n",
+       " [649 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 569118  2.700801 -14.520174          604            3.095672         3.103573\n",
+       " 569119  2.702502 -14.520347          604            3.093521         3.103573\n",
+       " 569120  2.704204 -14.520122          604            3.091299         3.103573\n",
+       " 569121  2.705906 -14.519897          604            3.089076         3.103573\n",
+       " 569122  2.707608 -14.519841          604            3.086839         3.103573\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 569771  3.812012 -14.526311          604            0.000157         3.103573\n",
+       " 569772  3.813714 -14.526389          604            0.000149         3.103573\n",
+       " 569773  3.815415 -14.526467          604            0.000142         3.103573\n",
+       " 569774  3.817117 -14.526546          604            0.000134         3.103573\n",
+       " 569775  3.818819 -14.526624          604            0.000126         3.103573\n",
+       " \n",
+       " [658 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 570118  2.700801 -14.519798          605            3.095536         3.099345\n",
+       " 570119  2.702502 -14.519798          605            3.093379         3.099345\n",
+       " 570120  2.704204 -14.519798          605            3.091224         3.099345\n",
+       " 570121  2.705906 -14.519930          605            3.088970         3.099345\n",
+       " 570122  2.707608 -14.520082          605            3.086700         3.099345\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 570771  3.812012 -14.525649          605            0.000156         3.099345\n",
+       " 570772  3.813714 -14.525724          605            0.000148         3.099345\n",
+       " 570773  3.815415 -14.525801          605            0.000140         3.099345\n",
+       " 570774  3.817117 -14.525876          605            0.000133         3.099345\n",
+       " 570775  3.818819 -14.525951          605            0.000125         3.099345\n",
+       " \n",
+       " [658 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 571118  2.700801 -14.519711          606            3.092006         3.097808\n",
+       " 571119  2.702502 -14.519588          606            3.089829         3.097808\n",
+       " 571120  2.704204 -14.519660          606            3.087713         3.097808\n",
+       " 571121  2.705906 -14.519732          606            3.085597         3.097808\n",
+       " 571122  2.707608 -14.519793          606            3.083467         3.097808\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 571771  3.812012 -14.526087          606            0.000155         3.097808\n",
+       " 571772  3.813714 -14.526168          606            0.000148         3.097808\n",
+       " 571773  3.815415 -14.526249          606            0.000140         3.097808\n",
+       " 571774  3.817117 -14.526330          606            0.000132         3.097808\n",
+       " 571775  3.818819 -14.526411          606            0.000125         3.097808\n",
+       " \n",
+       " [658 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 572118  2.700801 -14.519798          607            3.090461          3.09498\n",
+       " 572119  2.702502 -14.519798          607            3.088320          3.09498\n",
+       " 572120  2.704204 -14.519798          607            3.086180          3.09498\n",
+       " 572121  2.705906 -14.519924          607            3.083879          3.09498\n",
+       " 572122  2.707608 -14.520070          607            3.081553          3.09498\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 572771  3.812012 -14.525001          607            0.000155          3.09498\n",
+       " 572772  3.813714 -14.525068          607            0.000148          3.09498\n",
+       " 572773  3.815415 -14.525136          607            0.000140          3.09498\n",
+       " 572774  3.817117 -14.525204          607            0.000132          3.09498\n",
+       " 572775  3.818819 -14.525271          607            0.000125          3.09498\n",
+       " \n",
+       " [658 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 573118  2.700801 -14.519619          608            3.092488         3.095202\n",
+       " 573119  2.702502 -14.519726          608            3.090370         3.095202\n",
+       " 573120  2.704204 -14.519821          608            3.088223         3.095202\n",
+       " 573121  2.705906 -14.519894          608            3.086013         3.095202\n",
+       " 573122  2.707608 -14.519967          608            3.083802         3.095202\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 573771  3.812012 -14.526975          608            0.000156         3.095202\n",
+       " 573772  3.813714 -14.527061          608            0.000148         3.095202\n",
+       " 573773  3.815415 -14.527148          608            0.000140         3.095202\n",
+       " 573774  3.817117 -14.527235          608            0.000133         3.095202\n",
+       " 573775  3.818819 -14.527321          608            0.000125         3.095202\n",
+       " \n",
+       " [658 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 574118  2.700801 -14.519920          609            3.092747         3.096904\n",
+       " 574119  2.702502 -14.520182          609            3.090579         3.096904\n",
+       " 574120  2.704204 -14.520151          609            3.088389         3.096904\n",
+       " 574121  2.705906 -14.520005          609            3.086191         3.096904\n",
+       " 574122  2.707608 -14.519859          609            3.083994         3.096904\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 574771  3.812012 -14.526928          609            0.000159         3.096904\n",
+       " 574772  3.813714 -14.527017          609            0.000151         3.096904\n",
+       " 574773  3.815415 -14.527106          609            0.000143         3.096904\n",
+       " 574774  3.817117 -14.527195          609            0.000136         3.096904\n",
+       " 574775  3.818819 -14.527285          609            0.000128         3.096904\n",
+       " \n",
+       " [658 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 575118  2.700801 -14.520268          610            3.088913         3.094321\n",
+       " 575119  2.702502 -14.519992          610            3.086774         3.094321\n",
+       " 575120  2.704204 -14.519919          610            3.084577         3.094321\n",
+       " 575121  2.705906 -14.519846          610            3.082379         3.094321\n",
+       " 575122  2.707608 -14.519798          610            3.080193         3.094321\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 575761  3.794995 -14.519813          610            0.000202         3.094321\n",
+       " 575762  3.796697 -14.519810          610            0.000194         3.094321\n",
+       " 575763  3.798398 -14.519807          610            0.000186         3.094321\n",
+       " 575764  3.800100 -14.519803          610            0.000178         3.094321\n",
+       " 575765  3.801802 -14.519800          610            0.000169         3.094321\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 576118  2.700801 -14.519834          611            3.088228         3.092726\n",
+       " 576119  2.702502 -14.519930          611            3.086094         3.092726\n",
+       " 576120  2.704204 -14.519782          611            3.083890         3.092726\n",
+       " 576121  2.705906 -14.519633          611            3.081687         3.092726\n",
+       " 576122  2.707608 -14.519655          611            3.079469         3.092726\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 576771  3.812012 -14.526556          611            0.000153         3.092726\n",
+       " 576772  3.813714 -14.526640          611            0.000146         3.092726\n",
+       " 576773  3.815415 -14.526724          611            0.000138         3.092726\n",
+       " 576774  3.817117 -14.526807          611            0.000130         3.092726\n",
+       " 576775  3.818819 -14.526891          611            0.000123         3.092726\n",
+       " \n",
+       " [658 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 577118  2.700801 -14.520176          612            3.087075         3.092684\n",
+       " 577119  2.702502 -14.520145          612            3.084908         3.092684\n",
+       " 577120  2.704204 -14.519998          612            3.082730         3.092684\n",
+       " 577121  2.705906 -14.519850          612            3.080553         3.092684\n",
+       " 577122  2.707608 -14.519897          612            3.078311         3.092684\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 577771  3.812012 -14.525894          612            0.000155         3.092684\n",
+       " 577772  3.813714 -14.525967          612            0.000148         3.092684\n",
+       " 577773  3.815415 -14.526039          612            0.000140         3.092684\n",
+       " 577774  3.817117 -14.526113          612            0.000132         3.092684\n",
+       " 577775  3.818819 -14.526185          612            0.000125         3.092684\n",
+       " \n",
+       " [658 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 578118  2.700801 -14.519654          613            3.087193         3.092064\n",
+       " 578119  2.702502 -14.519879          613            3.084971         3.092064\n",
+       " 578120  2.704204 -14.520104          613            3.082748         3.092064\n",
+       " 578121  2.705906 -14.520232          613            3.080559         3.092064\n",
+       " 578122  2.707608 -14.520159          613            3.078439         3.092064\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 578771  3.812012 -14.524805          613            0.000155         3.092064\n",
+       " 578772  3.813714 -14.524864          613            0.000148         3.092064\n",
+       " 578773  3.815415 -14.524923          613            0.000140         3.092064\n",
+       " 578774  3.817117 -14.524982          613            0.000133         3.092064\n",
+       " 578775  3.818819 -14.525042          613            0.000125         3.092064\n",
+       " \n",
+       " [658 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 579118  2.700801 -14.520268          614            3.085258         3.088801\n",
+       " 579119  2.702502 -14.520185          614            3.083088         3.088801\n",
+       " 579120  2.704204 -14.520110          614            3.080911         3.088801\n",
+       " 579121  2.705906 -14.520036          614            3.078734         3.088801\n",
+       " 579122  2.707608 -14.520027          614            3.076598         3.088801\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 579762  3.796697 -14.518701          614            0.000196         3.088801\n",
+       " 579763  3.798398 -14.518689          614            0.000188         3.088801\n",
+       " 579764  3.800100 -14.518678          614            0.000179         3.088801\n",
+       " 579765  3.801802 -14.518665          614            0.000171         3.088801\n",
+       " 579766  3.803504 -14.518654          614            0.000163         3.088801\n",
+       " \n",
+       " [649 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 580118  2.700801 -14.519886          615            3.085286         3.087285\n",
+       " 580119  2.702502 -14.520027          615            3.083134         3.087285\n",
+       " 580120  2.704204 -14.520027          615            3.081023         3.087285\n",
+       " 580121  2.705906 -14.520027          615            3.078911         3.087285\n",
+       " 580122  2.707608 -14.520029          615            3.076795         3.087285\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 580771  3.812012 -14.524575          615            0.000156         3.087285\n",
+       " 580772  3.813714 -14.524635          615            0.000148         3.087285\n",
+       " 580773  3.815415 -14.524694          615            0.000140         3.087285\n",
+       " 580774  3.817117 -14.524754          615            0.000133         3.087285\n",
+       " 580775  3.818819 -14.524813          615            0.000125         3.087285\n",
+       " \n",
+       " [658 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 581118  2.700801 -14.520256          616            3.082217          3.08699\n",
+       " 581119  2.702502 -14.520256          616            3.080127          3.08699\n",
+       " 581120  2.704204 -14.520256          616            3.078039          3.08699\n",
+       " 581121  2.705906 -14.520256          616            3.075850          3.08699\n",
+       " 581122  2.707608 -14.520256          616            3.073639          3.08699\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 581761  3.794995 -14.518940          616            0.000203          3.08699\n",
+       " 581762  3.796697 -14.518929          616            0.000195          3.08699\n",
+       " 581763  3.798398 -14.518917          616            0.000187          3.08699\n",
+       " 581764  3.800100 -14.518905          616            0.000179          3.08699\n",
+       " 581765  3.801802 -14.518893          616            0.000170          3.08699\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 582118  2.700801 -14.519820          617            3.078450         3.084785\n",
+       " 582119  2.702502 -14.520073          617            3.076332         3.084785\n",
+       " 582120  2.704204 -14.520148          617            3.074162         3.084785\n",
+       " 582121  2.705906 -14.520224          617            3.071993         3.084785\n",
+       " 582122  2.707608 -14.520171          617            3.069815         3.084785\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 582771  3.812012 -14.526762          617            0.000155         3.084785\n",
+       " 582772  3.813714 -14.526846          617            0.000148         3.084785\n",
+       " 582773  3.815415 -14.526930          617            0.000140         3.084785\n",
+       " 582774  3.817117 -14.527014          617            0.000132         3.084785\n",
+       " 582775  3.818819 -14.527097          617            0.000125         3.084785\n",
+       " \n",
+       " [658 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 583118  2.700801 -14.520373          618            3.078470         3.083165\n",
+       " 583119  2.702502 -14.520134          618            3.076389         3.083165\n",
+       " 583120  2.704204 -14.519895          618            3.074309         3.083165\n",
+       " 583121  2.705906 -14.519754          618            3.072178         3.083165\n",
+       " 583122  2.707608 -14.519680          618            3.070014         3.083165\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 583771  3.812012 -14.526538          618            0.000155         3.083165\n",
+       " 583772  3.813714 -14.526622          618            0.000147         3.083165\n",
+       " 583773  3.815415 -14.526705          618            0.000140         3.083165\n",
+       " 583774  3.817117 -14.526789          618            0.000132         3.083165\n",
+       " 583775  3.818819 -14.526872          618            0.000124         3.083165\n",
+       " \n",
+       " [658 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 584118  2.700801 -14.520027          619            3.078320         3.081999\n",
+       " 584119  2.702502 -14.520027          619            3.076164         3.081999\n",
+       " 584120  2.704204 -14.520027          619            3.074007         3.081999\n",
+       " 584121  2.705906 -14.520019          619            3.071855         3.081999\n",
+       " 584122  2.707608 -14.519873          619            3.069760         3.081999\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 584771  3.812012 -14.523943          619            0.000154         3.081999\n",
+       " 584772  3.813714 -14.523992          619            0.000147         3.081999\n",
+       " 584773  3.815415 -14.524040          619            0.000139         3.081999\n",
+       " 584774  3.817117 -14.524088          619            0.000132         3.081999\n",
+       " 584775  3.818819 -14.524137          619            0.000124         3.081999\n",
+       " \n",
+       " [658 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 585118  2.700801 -14.519116          620            3.077828         3.080784\n",
+       " 585119  2.702502 -14.519404          620            3.075700         3.080784\n",
+       " 585120  2.704204 -14.519692          620            3.073571         3.080784\n",
+       " 585121  2.705906 -14.519979          620            3.071442         3.080784\n",
+       " 585122  2.707608 -14.519965          620            3.069328         3.080784\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 585761  3.794995 -14.519354          620            0.000201         3.080784\n",
+       " 585762  3.796697 -14.519351          620            0.000192         3.080784\n",
+       " 585763  3.798398 -14.519348          620            0.000184         3.080784\n",
+       " 585764  3.800100 -14.519345          620            0.000176         3.080784\n",
+       " 585765  3.801802 -14.519342          620            0.000168         3.080784\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 586118  2.700801 -14.519798          621            3.081409         3.081553\n",
+       " 586119  2.702502 -14.519831          621            3.079394         3.081553\n",
+       " 586120  2.704204 -14.519906          621            3.077251         3.081553\n",
+       " 586121  2.705906 -14.519981          621            3.075108         3.081553\n",
+       " 586122  2.707608 -14.519971          621            3.072984         3.081553\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 586771  3.812012 -14.525895          621            0.000156         3.081553\n",
+       " 586772  3.813714 -14.525966          621            0.000149         3.081553\n",
+       " 586773  3.815415 -14.526036          621            0.000141         3.081553\n",
+       " 586774  3.817117 -14.526106          621            0.000133         3.081553\n",
+       " 586775  3.818819 -14.526176          621            0.000126         3.081553\n",
+       " \n",
+       " [658 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 587118  2.700801 -14.519853          622            3.074313         3.083216\n",
+       " 587119  2.702502 -14.519968          622            3.072227         3.083216\n",
+       " 587120  2.704204 -14.519990          622            3.070166         3.083216\n",
+       " 587121  2.705906 -14.519915          622            3.068128         3.083216\n",
+       " 587122  2.707608 -14.519840          622            3.066091         3.083216\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 587771  3.812012 -14.526767          622            0.000154         3.083216\n",
+       " 587772  3.813714 -14.526853          622            0.000146         3.083216\n",
+       " 587773  3.815415 -14.526939          622            0.000139         3.083216\n",
+       " 587774  3.817117 -14.527025          622            0.000131         3.083216\n",
+       " 587775  3.818819 -14.527112          622            0.000123         3.083216\n",
+       " \n",
+       " [658 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 588118  2.700801 -14.520191          623            3.071998         3.077343\n",
+       " 588119  2.702502 -14.520063          623            3.069906         3.077343\n",
+       " 588120  2.704204 -14.519975          623            3.067803         3.077343\n",
+       " 588121  2.705906 -14.519902          623            3.065696         3.077343\n",
+       " 588122  2.707608 -14.519829          623            3.063588         3.077343\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 588761  3.794995 -14.519582          623            0.000199         3.077343\n",
+       " 588762  3.796697 -14.519579          623            0.000190         3.077343\n",
+       " 588763  3.798398 -14.519576          623            0.000182         3.077343\n",
+       " 588764  3.800100 -14.519573          623            0.000174         3.077343\n",
+       " 588765  3.801802 -14.519570          623            0.000166         3.077343\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 589118  2.700801 -14.519798          624            3.071357         3.075524\n",
+       " 589119  2.702502 -14.519800          624            3.069330         3.075524\n",
+       " 589120  2.704204 -14.519875          624            3.067218         3.075524\n",
+       " 589121  2.705906 -14.519949          624            3.065105         3.075524\n",
+       " 589122  2.707608 -14.520022          624            3.062994         3.075524\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 589770  3.810310 -14.525848          624            0.000160         3.075524\n",
+       " 589771  3.812012 -14.525921          624            0.000152         3.075524\n",
+       " 589772  3.813714 -14.525993          624            0.000145         3.075524\n",
+       " 589773  3.815415 -14.526066          624            0.000137         3.075524\n",
+       " 589774  3.817117 -14.526138          624            0.000130         3.075524\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 590118  2.700801 -14.520092          625            3.073104         3.074411\n",
+       " 590119  2.702502 -14.520220          625            3.071125         3.074411\n",
+       " 590120  2.704204 -14.520203          625            3.069050         3.074411\n",
+       " 590121  2.705906 -14.520129          625            3.066938         3.074411\n",
+       " 590122  2.707608 -14.520055          625            3.064826         3.074411\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 590770  3.810310 -14.525670          625            0.000157         3.074411\n",
+       " 590771  3.812012 -14.525738          625            0.000150         3.074411\n",
+       " 590772  3.813714 -14.525805          625            0.000142         3.074411\n",
+       " 590773  3.815415 -14.525871          625            0.000134         3.074411\n",
+       " 590774  3.817117 -14.525939          625            0.000127         3.074411\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 591118  2.700801 -14.519992          626            3.069337         3.075306\n",
+       " 591119  2.702502 -14.519917          626            3.067220         3.075306\n",
+       " 591120  2.704204 -14.519842          626            3.065104         3.075306\n",
+       " 591121  2.705906 -14.519859          626            3.062996         3.075306\n",
+       " 591122  2.707608 -14.520005          626            3.060901         3.075306\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 591771  3.812012 -14.525873          626            0.000155         3.075306\n",
+       " 591772  3.813714 -14.525951          626            0.000147         3.075306\n",
+       " 591773  3.815415 -14.526030          626            0.000140         3.075306\n",
+       " 591774  3.817117 -14.526109          626            0.000132         3.075306\n",
+       " 591775  3.818819 -14.526187          626            0.000124         3.075306\n",
+       " \n",
+       " [658 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 592118  2.700801 -14.519864          627            3.070607         3.074944\n",
+       " 592119  2.702502 -14.520006          627            3.068533         3.074944\n",
+       " 592120  2.704204 -14.519964          627            3.066382         3.074944\n",
+       " 592121  2.705906 -14.519890          627            3.064218         3.074944\n",
+       " 592122  2.707608 -14.519816          627            3.062054         3.074944\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 592771  3.812012 -14.525941          627            0.000154         3.074944\n",
+       " 592772  3.813714 -14.526006          627            0.000146         3.074944\n",
+       " 592773  3.815415 -14.526070          627            0.000139         3.074944\n",
+       " 592774  3.817117 -14.526134          627            0.000131         3.074944\n",
+       " 592775  3.818819 -14.526199          627            0.000123         3.074944\n",
+       " \n",
+       " [658 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 593118  2.700801 -14.520141          628            3.067752         3.072874\n",
+       " 593119  2.702502 -14.520218          628            3.065743         3.072874\n",
+       " 593120  2.704204 -14.520144          628            3.063699         3.072874\n",
+       " 593121  2.705906 -14.520072          628            3.061656         3.072874\n",
+       " 593122  2.707608 -14.519942          628            3.059568         3.072874\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 593770  3.810310 -14.526294          628            0.000159         3.072874\n",
+       " 593771  3.812012 -14.526371          628            0.000151         3.072874\n",
+       " 593772  3.813714 -14.526449          628            0.000143         3.072874\n",
+       " 593773  3.815415 -14.526527          628            0.000136         3.072874\n",
+       " 593774  3.817117 -14.526606          628            0.000128         3.072874\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 594118  2.700801 -14.520103          629            3.068476         3.070352\n",
+       " 594119  2.702502 -14.520245          629            3.066415         3.070352\n",
+       " 594120  2.704204 -14.520099          629            3.064346         3.070352\n",
+       " 594121  2.705906 -14.519953          629            3.062277         3.070352\n",
+       " 594122  2.707608 -14.519808          629            3.060208         3.070352\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 594770  3.810310 -14.526512          629            0.000157         3.070352\n",
+       " 594771  3.812012 -14.526596          629            0.000150         3.070352\n",
+       " 594772  3.813714 -14.526679          629            0.000142         3.070352\n",
+       " 594773  3.815415 -14.526762          629            0.000134         3.070352\n",
+       " 594774  3.817117 -14.526845          629            0.000127         3.070352\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 595118  2.700801 -14.519661          630            3.063976         3.070646\n",
+       " 595119  2.702502 -14.519820          630            3.061869         3.070646\n",
+       " 595120  2.704204 -14.519895          630            3.059769         3.070646\n",
+       " 595121  2.705906 -14.519968          630            3.057670         3.070646\n",
+       " 595122  2.707608 -14.519997          630            3.055563         3.070646\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 595770  3.810310 -14.524990          630            0.000158         3.070646\n",
+       " 595771  3.812012 -14.525055          630            0.000150         3.070646\n",
+       " 595772  3.813714 -14.525119          630            0.000143         3.070646\n",
+       " 595773  3.815415 -14.525184          630            0.000135         3.070646\n",
+       " 595774  3.817117 -14.525248          630            0.000128         3.070646\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 596118  2.700801 -14.519408          631            3.064054          3.06818\n",
+       " 596119  2.702502 -14.519554          631            3.062023          3.06818\n",
+       " 596120  2.704204 -14.519503          631            3.059931          3.06818\n",
+       " 596121  2.705906 -14.519429          631            3.057832          3.06818\n",
+       " 596122  2.707608 -14.519355          631            3.055733          3.06818\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 596761  3.794995 -14.520243          631            0.000199          3.06818\n",
+       " 596762  3.796697 -14.520246          631            0.000191          3.06818\n",
+       " 596763  3.798398 -14.520248          631            0.000183          3.06818\n",
+       " 596764  3.800100 -14.520252          631            0.000175          3.06818\n",
+       " 596765  3.801802 -14.520255          631            0.000167          3.06818\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 597118  2.700801 -14.519581          632            3.064659         3.066051\n",
+       " 597119  2.702502 -14.519450          632            3.062673         3.066051\n",
+       " 597120  2.704204 -14.519595          632            3.060642         3.066051\n",
+       " 597121  2.705906 -14.519741          632            3.058612         3.066051\n",
+       " 597122  2.707608 -14.519843          632            3.056573         3.066051\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 597770  3.810310 -14.524140          632            0.000157         3.066051\n",
+       " 597771  3.812012 -14.524191          632            0.000150         3.066051\n",
+       " 597772  3.813714 -14.524242          632            0.000142         3.066051\n",
+       " 597773  3.815415 -14.524293          632            0.000135         3.066051\n",
+       " 597774  3.817117 -14.524343          632            0.000127         3.066051\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 598118  2.700801 -14.519605          633            3.062968         3.069371\n",
+       " 598119  2.702502 -14.519848          633            3.060951         3.069371\n",
+       " 598120  2.704204 -14.519923          633            3.058848         3.069371\n",
+       " 598121  2.705906 -14.519998          633            3.056745         3.069371\n",
+       " 598122  2.707608 -14.519982          633            3.054636         3.069371\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 598771  3.812012 -14.524797          633            0.000154         3.069371\n",
+       " 598772  3.813714 -14.524861          633            0.000146         3.069371\n",
+       " 598773  3.815415 -14.524926          633            0.000139         3.069371\n",
+       " 598774  3.817117 -14.524990          633            0.000131         3.069371\n",
+       " 598775  3.818819 -14.525055          633            0.000123         3.069371\n",
+       " \n",
+       " [658 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 599118  2.700801 -14.519797          634            3.063126         3.065959\n",
+       " 599119  2.702502 -14.519357          634            3.061171         3.065959\n",
+       " 599120  2.704204 -14.519576          634            3.059089         3.065959\n",
+       " 599121  2.705906 -14.519794          634            3.057007         3.065959\n",
+       " 599122  2.707608 -14.520014          634            3.054925         3.065959\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 599770  3.810310 -14.525852          634            0.000160         3.065959\n",
+       " 599771  3.812012 -14.525925          634            0.000152         3.065959\n",
+       " 599772  3.813714 -14.525997          634            0.000144         3.065959\n",
+       " 599773  3.815415 -14.526070          634            0.000137         3.065959\n",
+       " 599774  3.817117 -14.526142          634            0.000129         3.065959\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 600118  2.700801 -14.520027          635            3.059693         3.063513\n",
+       " 600119  2.702502 -14.520098          635            3.057660         3.063513\n",
+       " 600120  2.704204 -14.520171          635            3.055629         3.063513\n",
+       " 600121  2.705906 -14.520244          635            3.053599         3.063513\n",
+       " 600122  2.707608 -14.520074          635            3.051579         3.063513\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 600770  3.810310 -14.525638          635            0.000158         3.063513\n",
+       " 600771  3.812012 -14.525709          635            0.000151         3.063513\n",
+       " 600772  3.813714 -14.525782          635            0.000143         3.063513\n",
+       " 600773  3.815415 -14.525854          635            0.000135         3.063513\n",
+       " 600774  3.817117 -14.525927          635            0.000128         3.063513\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 601118  2.700801 -14.519835          636            3.058742         3.063758\n",
+       " 601119  2.702502 -14.519912          636            3.056738         3.063758\n",
+       " 601120  2.704204 -14.519989          636            3.054735         3.063758\n",
+       " 601121  2.705906 -14.519990          636            3.052691         3.063758\n",
+       " 601122  2.707608 -14.519917          636            3.050609         3.063758\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 601770  3.810310 -14.526503          636            0.000159         3.063758\n",
+       " 601771  3.812012 -14.526583          636            0.000152         3.063758\n",
+       " 601772  3.813714 -14.526664          636            0.000144         3.063758\n",
+       " 601773  3.815415 -14.526744          636            0.000137         3.063758\n",
+       " 601774  3.817117 -14.526825          636            0.000129         3.063758\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 602118  2.700801 -14.520397          637            3.057073         3.061976\n",
+       " 602119  2.702502 -14.520207          637            3.055124         3.061976\n",
+       " 602120  2.704204 -14.520020          637            3.053168         3.061976\n",
+       " 602121  2.705906 -14.519870          637            3.051051         3.061976\n",
+       " 602122  2.707608 -14.519720          637            3.048934         3.061976\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 602761  3.794995 -14.519607          637            0.000198         3.061976\n",
+       " 602762  3.796697 -14.519598          637            0.000190         3.061976\n",
+       " 602763  3.798398 -14.519589          637            0.000182         3.061976\n",
+       " 602764  3.800100 -14.519581          637            0.000173         3.061976\n",
+       " 602765  3.801802 -14.519572          637            0.000165         3.061976\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 603118  2.700801 -14.520027          638            3.058797         3.059901\n",
+       " 603119  2.702502 -14.520027          638            3.056834         3.059901\n",
+       " 603120  2.704204 -14.520027          638            3.054816         3.059901\n",
+       " 603121  2.705906 -14.520027          638            3.052799         3.059901\n",
+       " 603122  2.707608 -14.520027          638            3.050742         3.059901\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 603761  3.794995 -14.521321          638            0.000200         3.059901\n",
+       " 603762  3.796697 -14.521338          638            0.000192         3.059901\n",
+       " 603763  3.798398 -14.521356          638            0.000184         3.059901\n",
+       " 603764  3.800100 -14.521373          638            0.000176         3.059901\n",
+       " 603765  3.801802 -14.521391          638            0.000168         3.059901\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 604118  2.700801 -14.519839          639            3.058146         3.063078\n",
+       " 604119  2.702502 -14.519927          639            3.056160         3.063078\n",
+       " 604120  2.704204 -14.520016          639            3.054175         3.063078\n",
+       " 604121  2.705906 -14.520027          639            3.052091         3.063078\n",
+       " 604122  2.707608 -14.520027          639            3.049992         3.063078\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 604771  3.812012 -14.525248          639            0.000153         3.063078\n",
+       " 604772  3.813714 -14.525314          639            0.000146         3.063078\n",
+       " 604773  3.815415 -14.525381          639            0.000138         3.063078\n",
+       " 604774  3.817117 -14.525448          639            0.000131         3.063078\n",
+       " 604775  3.818819 -14.525516          639            0.000123         3.063078\n",
+       " \n",
+       " [658 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 605118  2.700801 -14.520333          640            3.055208         3.059156\n",
+       " 605119  2.702502 -14.520007          640            3.053236         3.059156\n",
+       " 605120  2.704204 -14.519773          640            3.051248         3.059156\n",
+       " 605121  2.705906 -14.519699          640            3.049231         3.059156\n",
+       " 605122  2.707608 -14.519627          640            3.047213         3.059156\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 605770  3.810310 -14.526077          640            0.000157         3.059156\n",
+       " 605771  3.812012 -14.526155          640            0.000150         3.059156\n",
+       " 605772  3.813714 -14.526232          640            0.000142         3.059156\n",
+       " 605773  3.815415 -14.526310          640            0.000135         3.059156\n",
+       " 605774  3.817117 -14.526387          640            0.000127         3.059156\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 606118  2.700801 -14.519346          641            3.055081         3.058945\n",
+       " 606119  2.702502 -14.519642          641            3.052969         3.058945\n",
+       " 606120  2.704204 -14.519938          641            3.050857         3.058945\n",
+       " 606121  2.705906 -14.520233          641            3.048744         3.058945\n",
+       " 606122  2.707608 -14.519982          641            3.046693         3.058945\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 606771  3.812012 -14.526130          641            0.000153         3.058945\n",
+       " 606772  3.813714 -14.526205          641            0.000146         3.058945\n",
+       " 606773  3.815415 -14.526280          641            0.000138         3.058945\n",
+       " 606774  3.817117 -14.526355          641            0.000131         3.058945\n",
+       " 606775  3.818819 -14.526430          641            0.000123         3.058945\n",
+       " \n",
+       " [658 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 607118  2.700801 -14.520256          642            3.052131         3.057464\n",
+       " 607119  2.702502 -14.520256          642            3.050135         3.057464\n",
+       " 607120  2.704204 -14.520256          642            3.048139         3.057464\n",
+       " 607121  2.705906 -14.520211          642            3.046079         3.057464\n",
+       " 607122  2.707608 -14.520136          642            3.043975         3.057464\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 607770  3.810310 -14.526685          642            0.000160         3.057464\n",
+       " 607771  3.812012 -14.526773          642            0.000152         3.057464\n",
+       " 607772  3.813714 -14.526862          642            0.000145         3.057464\n",
+       " 607773  3.815415 -14.526951          642            0.000137         3.057464\n",
+       " 607774  3.817117 -14.527039          642            0.000130         3.057464\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 608118  2.700801 -14.519798          643            3.049975         3.054498\n",
+       " 608119  2.702502 -14.519798          643            3.048026         3.054498\n",
+       " 608120  2.704204 -14.519884          643            3.046050         3.054498\n",
+       " 608121  2.705906 -14.520033          643            3.044055         3.054498\n",
+       " 608122  2.707608 -14.520181          643            3.042060         3.054498\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 608770  3.810310 -14.526525          643            0.000157         3.054498\n",
+       " 608771  3.812012 -14.526606          643            0.000150         3.054498\n",
+       " 608772  3.813714 -14.526687          643            0.000142         3.054498\n",
+       " 608773  3.815415 -14.526767          643            0.000134         3.054498\n",
+       " 608774  3.817117 -14.526847          643            0.000127         3.054498\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 609118  2.700801 -14.519851          644            3.052021         3.054365\n",
+       " 609119  2.702502 -14.519964          644            3.049962         3.054365\n",
+       " 609120  2.704204 -14.519996          644            3.047918         3.054365\n",
+       " 609121  2.705906 -14.519924          644            3.045894         3.054365\n",
+       " 609122  2.707608 -14.519854          644            3.043870         3.054365\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 609770  3.810310 -14.525611          644            0.000159         3.054365\n",
+       " 609771  3.812012 -14.525686          644            0.000152         3.054365\n",
+       " 609772  3.813714 -14.525761          644            0.000144         3.054365\n",
+       " 609773  3.815415 -14.525836          644            0.000137         3.054365\n",
+       " 609774  3.817117 -14.525910          644            0.000129         3.054365\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 610118  2.700801 -14.519609          645            3.052337          3.05579\n",
+       " 610119  2.702502 -14.519696          645            3.050263          3.05579\n",
+       " 610120  2.704204 -14.519783          645            3.048189          3.05579\n",
+       " 610121  2.705906 -14.519798          645            3.046127          3.05579\n",
+       " 610122  2.707608 -14.519798          645            3.044067          3.05579\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 610770  3.810310 -14.525004          645            0.000158          3.05579\n",
+       " 610771  3.812012 -14.525065          645            0.000150          3.05579\n",
+       " 610772  3.813714 -14.525127          645            0.000143          3.05579\n",
+       " 610773  3.815415 -14.525188          645            0.000135          3.05579\n",
+       " 610774  3.817117 -14.525250          645            0.000128          3.05579\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 611118  2.700801 -14.520182          646            3.049535         3.053886\n",
+       " 611119  2.702502 -14.520032          646            3.047672         3.053886\n",
+       " 611120  2.704204 -14.520182          646            3.045595         3.053886\n",
+       " 611121  2.705906 -14.520332          646            3.043518         3.053886\n",
+       " 611122  2.707608 -14.520482          646            3.041441         3.053886\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 611770  3.810310 -14.525606          646            0.000157         3.053886\n",
+       " 611771  3.812012 -14.525686          646            0.000150         3.053886\n",
+       " 611772  3.813714 -14.525767          646            0.000142         3.053886\n",
+       " 611773  3.815415 -14.525847          646            0.000135         3.053886\n",
+       " 611774  3.817117 -14.525928          646            0.000127         3.053886\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 612118  2.700801 -14.519846          647            3.048284         3.052518\n",
+       " 612119  2.702502 -14.519948          647            3.046340         3.052518\n",
+       " 612120  2.704204 -14.520027          647            3.044376         3.052518\n",
+       " 612121  2.705906 -14.520027          647            3.042336         3.052518\n",
+       " 612122  2.707608 -14.520027          647            3.040296         3.052518\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 612770  3.810310 -14.525867          647            0.000158         3.052518\n",
+       " 612771  3.812012 -14.525938          647            0.000151         3.052518\n",
+       " 612772  3.813714 -14.526011          647            0.000143         3.052518\n",
+       " 612773  3.815415 -14.526083          647            0.000135         3.052518\n",
+       " 612774  3.817117 -14.526155          647            0.000128         3.052518\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 613118  2.700801 -14.519502          648            3.047331         3.050253\n",
+       " 613119  2.702502 -14.519848          648            3.045333         3.050253\n",
+       " 613120  2.704204 -14.520194          648            3.043336         3.050253\n",
+       " 613121  2.705906 -14.520195          648            3.041287         3.050253\n",
+       " 613122  2.707608 -14.520122          648            3.039227         3.050253\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 613770  3.810310 -14.526044          648            0.000157         3.050253\n",
+       " 613771  3.812012 -14.526129          648            0.000150         3.050253\n",
+       " 613772  3.813714 -14.526215          648            0.000142         3.050253\n",
+       " 613773  3.815415 -14.526300          648            0.000134         3.050253\n",
+       " 613774  3.817117 -14.526386          648            0.000127         3.050253\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 614118  2.700801 -14.520073          649            3.045890         3.050265\n",
+       " 614119  2.702502 -14.519820          649            3.043900         3.050265\n",
+       " 614120  2.704204 -14.519893          649            3.041870         3.050265\n",
+       " 614121  2.705906 -14.519966          649            3.039840         3.050265\n",
+       " 614122  2.707608 -14.519991          649            3.037811         3.050265\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 614761  3.794995 -14.520436          649            0.000197         3.050265\n",
+       " 614762  3.796697 -14.520448          649            0.000189         3.050265\n",
+       " 614763  3.798398 -14.520459          649            0.000181         3.050265\n",
+       " 614764  3.800100 -14.520471          649            0.000173         3.050265\n",
+       " 614765  3.801802 -14.520482          649            0.000165         3.050265\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 615118  2.700801 -14.520256          650            3.046046         3.049022\n",
+       " 615119  2.702502 -14.520232          650            3.044055         3.049022\n",
+       " 615120  2.704204 -14.520088          650            3.042041         3.049022\n",
+       " 615121  2.705906 -14.519944          650            3.040026         3.049022\n",
+       " 615122  2.707608 -14.519801          650            3.038012         3.049022\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 615770  3.810310 -14.525861          650            0.000157         3.049022\n",
+       " 615771  3.812012 -14.525936          650            0.000150         3.049022\n",
+       " 615772  3.813714 -14.526011          650            0.000142         3.049022\n",
+       " 615773  3.815415 -14.526085          650            0.000135         3.049022\n",
+       " 615774  3.817117 -14.526160          650            0.000127         3.049022\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 616118  2.700801 -14.519960          651            3.045442         3.049355\n",
+       " 616119  2.702502 -14.520308          651            3.043458         3.049355\n",
+       " 616120  2.704204 -14.520378          651            3.041460         3.049355\n",
+       " 616121  2.705906 -14.520163          651            3.039445         3.049355\n",
+       " 616122  2.707608 -14.519947          651            3.037430         3.049355\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 616770  3.810310 -14.525853          651            0.000159         3.049355\n",
+       " 616771  3.812012 -14.525926          651            0.000152         3.049355\n",
+       " 616772  3.813714 -14.525997          651            0.000144         3.049355\n",
+       " 616773  3.815415 -14.526070          651            0.000137         3.049355\n",
+       " 616774  3.817117 -14.526142          651            0.000129         3.049355\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 617118  2.700801 -14.519665          652            3.042668         3.046997\n",
+       " 617119  2.702502 -14.519957          652            3.040690         3.046997\n",
+       " 617120  2.704204 -14.519808          652            3.038695         3.046997\n",
+       " 617121  2.705906 -14.519660          652            3.036700         3.046997\n",
+       " 617122  2.707608 -14.519627          652            3.034691         3.046997\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 617770  3.810310 -14.524132          652            0.000157         3.046997\n",
+       " 617771  3.812012 -14.524185          652            0.000149         3.046997\n",
+       " 617772  3.813714 -14.524239          652            0.000142         3.046997\n",
+       " 617773  3.815415 -14.524291          652            0.000134         3.046997\n",
+       " 617774  3.817117 -14.524344          652            0.000127         3.046997\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 618118  2.700801 -14.520027          653            3.043988         3.047226\n",
+       " 618119  2.702502 -14.519812          653            3.042005         3.047226\n",
+       " 618120  2.704204 -14.519589          653            3.040010         3.047226\n",
+       " 618121  2.705906 -14.519367          653            3.038016         3.047226\n",
+       " 618122  2.707608 -14.519601          653            3.036032         3.047226\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 618770  3.810310 -14.526517          653            0.000156         3.047226\n",
+       " 618771  3.812012 -14.526603          653            0.000148         3.047226\n",
+       " 618772  3.813714 -14.526688          653            0.000141         3.047226\n",
+       " 618773  3.815415 -14.526773          653            0.000133         3.047226\n",
+       " 618774  3.817117 -14.526859          653            0.000126         3.047226\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 619118  2.700801 -14.519780          654            3.045607         3.048894\n",
+       " 619119  2.702502 -14.519707          654            3.043639         3.048894\n",
+       " 619120  2.704204 -14.519632          654            3.041670         3.048894\n",
+       " 619121  2.705906 -14.519569          654            3.039685         3.048894\n",
+       " 619122  2.707608 -14.519569          654            3.037608         3.048894\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 619761  3.794995 -14.519822          654            0.000196         3.048894\n",
+       " 619762  3.796697 -14.519816          654            0.000188         3.048894\n",
+       " 619763  3.798398 -14.519811          654            0.000180         3.048894\n",
+       " 619764  3.800100 -14.519805          654            0.000172         3.048894\n",
+       " 619765  3.801802 -14.519799          654            0.000164         3.048894\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 620118  2.700801 -14.520223          655            3.041573         3.046491\n",
+       " 620119  2.702502 -14.520000          655            3.039500         3.046491\n",
+       " 620120  2.704204 -14.519778          655            3.037427         3.046491\n",
+       " 620121  2.705906 -14.519573          655            3.035361         3.046491\n",
+       " 620122  2.707608 -14.519646          655            3.033397         3.046491\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 620770  3.810310 -14.525664          655            0.000156         3.046491\n",
+       " 620771  3.812012 -14.525734          655            0.000149         3.046491\n",
+       " 620772  3.813714 -14.525803          655            0.000142         3.046491\n",
+       " 620773  3.815415 -14.525871          655            0.000134         3.046491\n",
+       " 620774  3.817117 -14.525941          655            0.000127         3.046491\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 621118  2.700801 -14.519622          656            3.042742         3.043824\n",
+       " 621119  2.702502 -14.519837          656            3.040765         3.043824\n",
+       " 621120  2.704204 -14.520053          656            3.038789         3.043824\n",
+       " 621121  2.705906 -14.520256          656            3.036812         3.043824\n",
+       " 621122  2.707608 -14.520256          656            3.034830         3.043824\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 621761  3.794995 -14.519158          656            0.000196         3.043824\n",
+       " 621762  3.796697 -14.519147          656            0.000188         3.043824\n",
+       " 621763  3.798398 -14.519135          656            0.000180         3.043824\n",
+       " 621764  3.800100 -14.519124          656            0.000172         3.043824\n",
+       " 621765  3.801802 -14.519113          656            0.000163         3.043824\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 622118  2.700801 -14.519875          657            3.041399         3.046928\n",
+       " 622119  2.702502 -14.520027          657            3.039399         3.046928\n",
+       " 622120  2.704204 -14.520027          657            3.037420         3.046928\n",
+       " 622121  2.705906 -14.520027          657            3.035440         3.046928\n",
+       " 622122  2.707608 -14.520027          657            3.033461         3.046928\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 622770  3.810310 -14.523931          657            0.000158         3.046928\n",
+       " 622771  3.812012 -14.523976          657            0.000151         3.046928\n",
+       " 622772  3.813714 -14.524022          657            0.000143         3.046928\n",
+       " 622773  3.815415 -14.524067          657            0.000136         3.046928\n",
+       " 622774  3.817117 -14.524113          657            0.000128         3.046928\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 623118  2.700801 -14.520141          658            3.040426         3.045507\n",
+       " 623119  2.702502 -14.520256          658            3.038427         3.045507\n",
+       " 623120  2.704204 -14.520256          658            3.036363         3.045507\n",
+       " 623121  2.705906 -14.520256          658            3.034299         3.045507\n",
+       " 623122  2.707608 -14.520256          658            3.032269         3.045507\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 623770  3.810310 -14.526556          658            0.000156         3.045507\n",
+       " 623771  3.812012 -14.526630          658            0.000149         3.045507\n",
+       " 623772  3.813714 -14.526705          658            0.000142         3.045507\n",
+       " 623773  3.815415 -14.526779          658            0.000134         3.045507\n",
+       " 623774  3.817117 -14.526854          658            0.000127         3.045507\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 624118  2.700801 -14.519444          659            3.039439         3.042589\n",
+       " 624119  2.702502 -14.519666          659            3.037470         3.042589\n",
+       " 624120  2.704204 -14.519888          659            3.035501         3.042589\n",
+       " 624121  2.705906 -14.520000          659            3.033508         3.042589\n",
+       " 624122  2.707608 -14.519926          659            3.031474         3.042589\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 624770  3.810310 -14.524578          659            0.000155         3.042589\n",
+       " 624771  3.812012 -14.524637          659            0.000148         3.042589\n",
+       " 624772  3.813714 -14.524695          659            0.000140         3.042589\n",
+       " 624773  3.815415 -14.524754          659            0.000133         3.042589\n",
+       " 624774  3.817117 -14.524813          659            0.000125         3.042589\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 625118  2.700801 -14.519992          660            3.039713         3.041995\n",
+       " 625119  2.702502 -14.519847          660            3.037768         3.041995\n",
+       " 625120  2.704204 -14.519921          660            3.035800         3.041995\n",
+       " 625121  2.705906 -14.519995          660            3.033831         3.041995\n",
+       " 625122  2.707608 -14.519984          660            3.031821         3.041995\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 625761  3.794995 -14.518502          660            0.000199         3.041995\n",
+       " 625762  3.796697 -14.518485          660            0.000191         3.041995\n",
+       " 625763  3.798398 -14.518468          660            0.000183         3.041995\n",
+       " 625764  3.800100 -14.518451          660            0.000175         3.041995\n",
+       " 625765  3.801802 -14.518434          660            0.000167         3.041995\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 626118  2.700801 -14.519919          661            3.036433          3.04178\n",
+       " 626119  2.702502 -14.519763          661            3.034513          3.04178\n",
+       " 626120  2.704204 -14.519689          661            3.032505          3.04178\n",
+       " 626121  2.705906 -14.519615          661            3.030497          3.04178\n",
+       " 626122  2.707608 -14.519654          661            3.028485          3.04178\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 626770  3.810310 -14.526736          661            0.000158          3.04178\n",
+       " 626771  3.812012 -14.526819          661            0.000150          3.04178\n",
+       " 626772  3.813714 -14.526901          661            0.000143          3.04178\n",
+       " 626773  3.815415 -14.526984          661            0.000135          3.04178\n",
+       " 626774  3.817117 -14.527067          661            0.000128          3.04178\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 627118  2.700801 -14.519848          662            3.037391         3.040634\n",
+       " 627119  2.702502 -14.519955          662            3.035442         3.040634\n",
+       " 627120  2.704204 -14.519981          662            3.033459         3.040634\n",
+       " 627121  2.705906 -14.519835          662            3.031403         3.040634\n",
+       " 627122  2.707608 -14.519690          662            3.029346         3.040634\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 627770  3.810310 -14.526075          662            0.000158         3.040634\n",
+       " 627771  3.812012 -14.526153          662            0.000150         3.040634\n",
+       " 627772  3.813714 -14.526230          662            0.000143         3.040634\n",
+       " 627773  3.815415 -14.526306          662            0.000135         3.040634\n",
+       " 627774  3.817117 -14.526383          662            0.000128         3.040634\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 628118  2.700801 -14.519976          663            3.036775         3.038514\n",
+       " 628119  2.702502 -14.519798          663            3.034822         3.038514\n",
+       " 628120  2.704204 -14.519798          663            3.032804         3.038514\n",
+       " 628121  2.705906 -14.519798          663            3.030787         3.038514\n",
+       " 628122  2.707608 -14.519798          663            3.028773         3.038514\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 628770  3.810310 -14.523916          663            0.000159         3.038514\n",
+       " 628771  3.812012 -14.523965          663            0.000151         3.038514\n",
+       " 628772  3.813714 -14.524013          663            0.000144         3.038514\n",
+       " 628773  3.815415 -14.524060          663            0.000136         3.038514\n",
+       " 628774  3.817117 -14.524108          663            0.000129         3.038514\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 629118  2.700801 -14.520012          664            3.035177         3.040195\n",
+       " 629119  2.702502 -14.519866          664            3.033147         3.040195\n",
+       " 629120  2.704204 -14.519720          664            3.031116         3.040195\n",
+       " 629121  2.705906 -14.519574          664            3.029086         3.040195\n",
+       " 629122  2.707608 -14.519640          664            3.027117         3.040195\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 629761  3.794995 -14.519170          664            0.000196         3.040195\n",
+       " 629762  3.796697 -14.519156          664            0.000188         3.040195\n",
+       " 629763  3.798398 -14.519141          664            0.000180         3.040195\n",
+       " 629764  3.800100 -14.519127          664            0.000172         3.040195\n",
+       " 629765  3.801802 -14.519113          664            0.000163         3.040195\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 630118  2.700801 -14.519735          665            3.035506         3.039971\n",
+       " 630119  2.702502 -14.519601          665            3.033494         3.039971\n",
+       " 630120  2.704204 -14.519569          665            3.031497         3.039971\n",
+       " 630121  2.705906 -14.519569          665            3.029505         3.039971\n",
+       " 630122  2.707608 -14.519569          665            3.027513         3.039971\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 630770  3.810310 -14.525861          665            0.000156         3.039971\n",
+       " 630771  3.812012 -14.525938          665            0.000149         3.039971\n",
+       " 630772  3.813714 -14.526015          665            0.000141         3.039971\n",
+       " 630773  3.815415 -14.526092          665            0.000134         3.039971\n",
+       " 630774  3.817117 -14.526169          665            0.000126         3.039971\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 631118  2.700801 -14.519655          671            3.123783         3.225361\n",
+       " 631119  2.702502 -14.519956          671            3.121031         3.225361\n",
+       " 631120  2.704204 -14.520256          671            3.118279         3.225361\n",
+       " 631121  2.705906 -14.520450          671            3.115525         3.225361\n",
+       " 631122  2.707608 -14.520299          671            3.112760         3.225361\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 631772  3.813714 -14.526551          671            0.000156         3.225361\n",
+       " 631773  3.815415 -14.526628          671            0.000148         3.225361\n",
+       " 631774  3.817117 -14.526706          671            0.000141         3.225361\n",
+       " 631775  3.818819 -14.526784          671            0.000133         3.225361\n",
+       " 631776  3.820521 -14.526861          671            0.000126         3.225361\n",
+       " \n",
+       " [659 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 632118  2.700801 -14.519972          672            3.111889         3.126136\n",
+       " 632119  2.702502 -14.519853          672            3.109253         3.126136\n",
+       " 632120  2.704204 -14.519718          672            3.106534         3.126136\n",
+       " 632121  2.705906 -14.519570          672            3.103744         3.126136\n",
+       " 632122  2.707608 -14.519423          672            3.100954         3.126136\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 632763  3.798398 -14.520679          672            0.000195         3.126136\n",
+       " 632764  3.800100 -14.520688          672            0.000187         3.126136\n",
+       " 632765  3.801802 -14.520697          672            0.000179         3.126136\n",
+       " 632766  3.803504 -14.520705          672            0.000171         3.126136\n",
+       " 632767  3.805205 -14.520714          672            0.000163         3.126136\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 633118  2.700801 -14.520176          673            3.099640          3.11034\n",
+       " 633119  2.702502 -14.520475          673            3.096859          3.11034\n",
+       " 633120  2.704204 -14.520180          673            3.094160          3.11034\n",
+       " 633121  2.705906 -14.519884          673            3.091461          3.11034\n",
+       " 633122  2.707608 -14.519588          673            3.088763          3.11034\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 633772  3.813714 -14.525255          673            0.000154          3.11034\n",
+       " 633773  3.815415 -14.525319          673            0.000146          3.11034\n",
+       " 633774  3.817117 -14.525383          673            0.000139          3.11034\n",
+       " 633775  3.818819 -14.525447          673            0.000131          3.11034\n",
+       " 633776  3.820521 -14.525511          673            0.000124          3.11034\n",
+       " \n",
+       " [659 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 634118  2.700801 -14.519743          674            3.090210          3.10251\n",
+       " 634119  2.702502 -14.519624          674            3.087532          3.10251\n",
+       " 634120  2.704204 -14.519648          674            3.084816          3.10251\n",
+       " 634121  2.705906 -14.519794          674            3.082065          3.10251\n",
+       " 634122  2.707608 -14.519939          674            3.079315          3.10251\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 634771  3.812012 -14.524561          674            0.000156          3.10251\n",
+       " 634772  3.813714 -14.524622          674            0.000148          3.10251\n",
+       " 634773  3.815415 -14.524683          674            0.000141          3.10251\n",
+       " 634774  3.817117 -14.524743          674            0.000134          3.10251\n",
+       " 634775  3.818819 -14.524804          674            0.000126          3.10251\n",
+       " \n",
+       " [658 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 635118  2.700801 -14.519879          675            3.080905         3.089274\n",
+       " 635119  2.702502 -14.520052          675            3.078252         3.089274\n",
+       " 635120  2.704204 -14.520225          675            3.075599         3.089274\n",
+       " 635121  2.705906 -14.520133          675            3.072789         3.089274\n",
+       " 635122  2.707608 -14.519982          675            3.069944         3.089274\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 635771  3.812012 -14.524379          675            0.000154         3.089274\n",
+       " 635772  3.813714 -14.524432          675            0.000147         3.089274\n",
+       " 635773  3.815415 -14.524485          675            0.000139         3.089274\n",
+       " 635774  3.817117 -14.524538          675            0.000132         3.089274\n",
+       " 635775  3.818819 -14.524591          675            0.000124         3.089274\n",
+       " \n",
+       " [658 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 636118  2.700801 -14.519646          676            3.073650         3.083264\n",
+       " 636119  2.702502 -14.519798          676            3.070926         3.083264\n",
+       " 636120  2.704204 -14.519798          676            3.068240         3.083264\n",
+       " 636121  2.705906 -14.519798          676            3.065553         3.083264\n",
+       " 636122  2.707608 -14.519798          676            3.062867         3.083264\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 636771  3.812012 -14.524142          676            0.000154         3.083264\n",
+       " 636772  3.813714 -14.524198          676            0.000146         3.083264\n",
+       " 636773  3.815415 -14.524253          676            0.000139         3.083264\n",
+       " 636774  3.817117 -14.524308          676            0.000132         3.083264\n",
+       " 636775  3.818819 -14.524364          676            0.000124         3.083264\n",
+       " \n",
+       " [658 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 637118  2.700801 -14.520022          677            3.067611         3.074748\n",
+       " 637119  2.702502 -14.519947          677            3.064859         3.074748\n",
+       " 637120  2.704204 -14.519873          677            3.062107         3.074748\n",
+       " 637121  2.705906 -14.519798          677            3.059356         3.074748\n",
+       " 637122  2.707608 -14.519798          677            3.056684         3.074748\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 637770  3.810310 -14.526776          677            0.000157         3.074748\n",
+       " 637771  3.812012 -14.526851          677            0.000150         3.074748\n",
+       " 637772  3.813714 -14.526924          677            0.000142         3.074748\n",
+       " 637773  3.815415 -14.526999          677            0.000135         3.074748\n",
+       " 637774  3.817117 -14.527073          677            0.000128         3.074748\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 638118  2.700801 -14.519376          678            3.062721         3.069039\n",
+       " 638119  2.702502 -14.519450          678            3.060167         3.069039\n",
+       " 638120  2.704204 -14.519526          678            3.057614         3.069039\n",
+       " 638121  2.705906 -14.519634          678            3.054972         3.069039\n",
+       " 638122  2.707608 -14.519789          678            3.052205         3.069039\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 638770  3.810310 -14.525688          678            0.000157         3.069039\n",
+       " 638771  3.812012 -14.525752          678            0.000149         3.069039\n",
+       " 638772  3.813714 -14.525815          678            0.000142         3.069039\n",
+       " 638773  3.815415 -14.525878          678            0.000134         3.069039\n",
+       " 638774  3.817117 -14.525941          678            0.000127         3.069039\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 639118  2.700801 -14.520333          679            3.055402         3.064496\n",
+       " 639119  2.702502 -14.520007          679            3.052894         3.064496\n",
+       " 639120  2.704204 -14.519824          679            3.050304         3.064496\n",
+       " 639121  2.705906 -14.519897          679            3.047567         3.064496\n",
+       " 639122  2.707608 -14.519970          679            3.044829         3.064496\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 639770  3.810310 -14.526349          679            0.000152         3.064496\n",
+       " 639771  3.812012 -14.526428          679            0.000145         3.064496\n",
+       " 639772  3.813714 -14.526507          679            0.000137         3.064496\n",
+       " 639773  3.815415 -14.526586          679            0.000130         3.064496\n",
+       " 639774  3.817117 -14.526665          679            0.000122         3.064496\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 640118  2.700801 -14.519903          680            3.050668         3.057346\n",
+       " 640119  2.702502 -14.519379          680            3.048231         3.057346\n",
+       " 640120  2.704204 -14.519529          680            3.045585         3.057346\n",
+       " 640121  2.705906 -14.519679          680            3.042939         3.057346\n",
+       " 640122  2.707608 -14.519814          680            3.040296         3.057346\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 640770  3.810310 -14.526579          680            0.000152         3.057346\n",
+       " 640771  3.812012 -14.526657          680            0.000145         3.057346\n",
+       " 640772  3.813714 -14.526736          680            0.000137         3.057346\n",
+       " 640773  3.815415 -14.526814          680            0.000130         3.057346\n",
+       " 640774  3.817117 -14.526894          680            0.000123         3.057346\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 641118  2.700801 -14.519981          681            3.045656         3.053329\n",
+       " 641119  2.702502 -14.519614          681            3.043191         3.053329\n",
+       " 641120  2.704204 -14.519765          681            3.040545         3.053329\n",
+       " 641121  2.705906 -14.519915          681            3.037899         3.053329\n",
+       " 641122  2.707608 -14.520063          681            3.035266         3.053329\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 641769  3.808609 -14.526304          681            0.000158         3.053329\n",
+       " 641770  3.810310 -14.526381          681            0.000150         3.053329\n",
+       " 641771  3.812012 -14.526457          681            0.000143         3.053329\n",
+       " 641772  3.813714 -14.526533          681            0.000135         3.053329\n",
+       " 641773  3.815415 -14.526608          681            0.000128         3.053329\n",
+       " \n",
+       " [656 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 642118  2.700801 -14.519997          682            3.042615          3.04878\n",
+       " 642119  2.702502 -14.520027          682            3.040020          3.04878\n",
+       " 642120  2.704204 -14.520027          682            3.037399          3.04878\n",
+       " 642121  2.705906 -14.520027          682            3.034777          3.04878\n",
+       " 642122  2.707608 -14.520027          682            3.032177          3.04878\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 642769  3.808609 -14.525859          682            0.000157          3.04878\n",
+       " 642770  3.810310 -14.525932          682            0.000150          3.04878\n",
+       " 642771  3.812012 -14.526006          682            0.000143          3.04878\n",
+       " 642772  3.813714 -14.526080          682            0.000135          3.04878\n",
+       " 642773  3.815415 -14.526154          682            0.000128          3.04878\n",
+       " \n",
+       " [656 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 643118  2.700801 -14.519840          683            3.039884         3.043776\n",
+       " 643119  2.702502 -14.519989          683            3.037394         3.043776\n",
+       " 643120  2.704204 -14.520137          683            3.034904         3.043776\n",
+       " 643121  2.705906 -14.520227          683            3.032388         3.043776\n",
+       " 643122  2.707608 -14.520077          683            3.029769         3.043776\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 643769  3.808609 -14.524343          683            0.000156         3.043776\n",
+       " 643770  3.810310 -14.524400          683            0.000149         3.043776\n",
+       " 643771  3.812012 -14.524458          683            0.000141         3.043776\n",
+       " 643772  3.813714 -14.524515          683            0.000134         3.043776\n",
+       " 643773  3.815415 -14.524573          683            0.000127         3.043776\n",
+       " \n",
+       " [656 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 644118  2.700801 -14.519798          684            3.035458         3.042634\n",
+       " 644119  2.702502 -14.519798          684            3.032909         3.042634\n",
+       " 644120  2.704204 -14.519798          684            3.030360         3.042634\n",
+       " 644121  2.705906 -14.519836          684            3.027775         3.042634\n",
+       " 644122  2.707608 -14.519912          684            3.025156         3.042634\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 644769  3.808609 -14.524597          684            0.000156         3.042634\n",
+       " 644770  3.810310 -14.524650          684            0.000148         3.042634\n",
+       " 644771  3.812012 -14.524702          684            0.000141         3.042634\n",
+       " 644772  3.813714 -14.524755          684            0.000134         3.042634\n",
+       " 644773  3.815415 -14.524807          684            0.000126         3.042634\n",
+       " \n",
+       " [656 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 645118  2.700801 -14.520027          685            3.032208         3.037917\n",
+       " 645119  2.702502 -14.520027          685            3.029698         3.037917\n",
+       " 645120  2.704204 -14.519987          685            3.027142         3.037917\n",
+       " 645121  2.705906 -14.519914          685            3.024548         3.037917\n",
+       " 645122  2.707608 -14.519839          685            3.021953         3.037917\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 645759  3.791592 -14.520890          685            0.000200         3.037917\n",
+       " 645760  3.793293 -14.520902          685            0.000192         3.037917\n",
+       " 645761  3.794995 -14.520913          685            0.000184         3.037917\n",
+       " 645762  3.796697 -14.520925          685            0.000176         3.037917\n",
+       " 645763  3.798398 -14.520935          685            0.000168         3.037917\n",
+       " \n",
+       " [646 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 646118  2.700801 -14.519797          686            3.032687         3.036954\n",
+       " 646119  2.702502 -14.519721          686            3.030096         3.036954\n",
+       " 646120  2.704204 -14.519645          686            3.027504         3.036954\n",
+       " 646121  2.705906 -14.519571          686            3.024914         3.036954\n",
+       " 646122  2.707608 -14.519719          686            3.022358         3.036954\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 646769  3.808609 -14.526064          686            0.000159         3.036954\n",
+       " 646770  3.810310 -14.526139          686            0.000151         3.036954\n",
+       " 646771  3.812012 -14.526216          686            0.000144         3.036954\n",
+       " 646772  3.813714 -14.526291          686            0.000137         3.036954\n",
+       " 646773  3.815415 -14.526367          686            0.000129         3.036954\n",
+       " \n",
+       " [656 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 647118  2.700801 -14.519578          687            3.030766         3.034032\n",
+       " 647119  2.702502 -14.520019          687            3.028279         3.034032\n",
+       " 647120  2.704204 -14.519945          687            3.025798         3.034032\n",
+       " 647121  2.705906 -14.519873          687            3.023318         3.034032\n",
+       " 647122  2.707608 -14.519799          687            3.020838         3.034032\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 647769  3.808609 -14.524798          687            0.000156         3.034032\n",
+       " 647770  3.810310 -14.524856          687            0.000149         3.034032\n",
+       " 647771  3.812012 -14.524914          687            0.000142         3.034032\n",
+       " 647772  3.813714 -14.524971          687            0.000134         3.034032\n",
+       " 647773  3.815415 -14.525028          687            0.000127         3.034032\n",
+       " \n",
+       " [656 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 648118  2.700801 -14.519753          688            3.027055          3.03305\n",
+       " 648119  2.702502 -14.519704          688            3.024575          3.03305\n",
+       " 648120  2.704204 -14.519856          688            3.022051          3.03305\n",
+       " 648121  2.705906 -14.520009          688            3.019526          3.03305\n",
+       " 648122  2.707608 -14.520027          688            3.017043          3.03305\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 648769  3.808609 -14.525219          688            0.000156          3.03305\n",
+       " 648770  3.810310 -14.525285          688            0.000149          3.03305\n",
+       " 648771  3.812012 -14.525350          688            0.000142          3.03305\n",
+       " 648772  3.813714 -14.525415          688            0.000134          3.03305\n",
+       " 648773  3.815415 -14.525481          688            0.000127          3.03305\n",
+       " \n",
+       " [656 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 649118  2.700801 -14.520027          689            3.025314         3.029914\n",
+       " 649119  2.702502 -14.520027          689            3.022942         3.029914\n",
+       " 649120  2.704204 -14.520027          689            3.020455         3.029914\n",
+       " 649121  2.705906 -14.520027          689            3.017968         3.029914\n",
+       " 649122  2.707608 -14.519998          689            3.015486         3.029914\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 649769  3.808609 -14.526974          689            0.000154         3.029914\n",
+       " 649770  3.810310 -14.527063          689            0.000146         3.029914\n",
+       " 649771  3.812012 -14.527152          689            0.000139         3.029914\n",
+       " 649772  3.813714 -14.527241          689            0.000132         3.029914\n",
+       " 649773  3.815415 -14.527330          689            0.000124         3.029914\n",
+       " \n",
+       " [656 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 650118  2.700801 -14.519897          690            3.023012          3.02745\n",
+       " 650119  2.702502 -14.520027          690            3.020503          3.02745\n",
+       " 650120  2.704204 -14.520027          690            3.017997          3.02745\n",
+       " 650121  2.705906 -14.520027          690            3.015491          3.02745\n",
+       " 650122  2.707608 -14.520063          690            3.012994          3.02745\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 650769  3.808609 -14.526746          690            0.000154          3.02745\n",
+       " 650770  3.810310 -14.526834          690            0.000146          3.02745\n",
+       " 650771  3.812012 -14.526923          690            0.000139          3.02745\n",
+       " 650772  3.813714 -14.527013          690            0.000132          3.02745\n",
+       " 650773  3.815415 -14.527102          690            0.000124          3.02745\n",
+       " \n",
+       " [656 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 651118  2.700801 -14.519998          691            3.021855         3.025748\n",
+       " 651119  2.702502 -14.519443          691            3.019372         3.025748\n",
+       " 651120  2.704204 -14.519291          691            3.016933         3.025748\n",
+       " 651121  2.705906 -14.519734          691            3.014560         3.025748\n",
+       " 651122  2.707608 -14.520179          691            3.012187         3.025748\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 651769  3.808609 -14.526553          691            0.000154         3.025748\n",
+       " 651770  3.810310 -14.526632          691            0.000147         3.025748\n",
+       " 651771  3.812012 -14.526711          691            0.000140         3.025748\n",
+       " 651772  3.813714 -14.526790          691            0.000132         3.025748\n",
+       " 651773  3.815415 -14.526868          691            0.000125         3.025748\n",
+       " \n",
+       " [656 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 652118  2.700801 -14.519984          692            3.019121         3.025651\n",
+       " 652119  2.702502 -14.519834          692            3.016660         3.025651\n",
+       " 652120  2.704204 -14.519684          692            3.014200         3.025651\n",
+       " 652121  2.705906 -14.519588          692            3.011737         3.025651\n",
+       " 652122  2.707608 -14.519664          692            3.009266         3.025651\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 652769  3.808609 -14.524853          692            0.000152         3.025651\n",
+       " 652770  3.810310 -14.524905          692            0.000145         3.025651\n",
+       " 652771  3.812012 -14.524958          692            0.000137         3.025651\n",
+       " 652772  3.813714 -14.525009          692            0.000130         3.025651\n",
+       " 652773  3.815415 -14.525062          692            0.000123         3.025651\n",
+       " \n",
+       " [656 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 653118  2.700801 -14.520027          693            3.016642         3.020738\n",
+       " 653119  2.702502 -14.520027          693            3.014310         3.020738\n",
+       " 653120  2.704204 -14.520027          693            3.011967         3.020738\n",
+       " 653121  2.705906 -14.520027          693            3.009391         3.020738\n",
+       " 653122  2.707608 -14.520027          693            3.006814         3.020738\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 653768  3.806907 -14.524783          693            0.000158         3.020738\n",
+       " 653769  3.808609 -14.524840          693            0.000151         3.020738\n",
+       " 653770  3.810310 -14.524898          693            0.000144         3.020738\n",
+       " 653771  3.812012 -14.524955          693            0.000136         3.020738\n",
+       " 653772  3.813714 -14.525012          693            0.000129         3.020738\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 654118  2.700801 -14.519988          694            3.014599         3.020962\n",
+       " 654119  2.702502 -14.519904          694            3.012210         3.020962\n",
+       " 654120  2.704204 -14.519821          694            3.009821         3.020962\n",
+       " 654121  2.705906 -14.519744          694            3.007386         3.020962\n",
+       " 654122  2.707608 -14.519670          694            3.004935         3.020962\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 654768  3.806907 -14.526518          694            0.000159         3.020962\n",
+       " 654769  3.808609 -14.526593          694            0.000152         3.020962\n",
+       " 654770  3.810310 -14.526669          694            0.000144         3.020962\n",
+       " 654771  3.812012 -14.526745          694            0.000137         3.020962\n",
+       " 654772  3.813714 -14.526820          694            0.000130         3.020962\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 655118  2.700801 -14.520167          695            3.014000         3.016791\n",
+       " 655119  2.702502 -14.520152          695            3.011639         3.016791\n",
+       " 655120  2.704204 -14.520004          695            3.009175         3.016791\n",
+       " 655121  2.705906 -14.519855          695            3.006711         3.016791\n",
+       " 655122  2.707608 -14.519798          695            3.004302         3.016791\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 655768  3.806907 -14.525628          695            0.000159         3.016791\n",
+       " 655769  3.808609 -14.525699          695            0.000152         3.016791\n",
+       " 655770  3.810310 -14.525768          695            0.000144         3.016791\n",
+       " 655771  3.812012 -14.525839          695            0.000137         3.016791\n",
+       " 655772  3.813714 -14.525909          695            0.000130         3.016791\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 656118  2.700801 -14.519432          696            3.012618         3.017703\n",
+       " 656119  2.702502 -14.519547          696            3.010183         3.017703\n",
+       " 656120  2.704204 -14.519769          696            3.007745         3.017703\n",
+       " 656121  2.705906 -14.519990          696            3.005307         3.017703\n",
+       " 656122  2.707608 -14.519964          696            3.002927         3.017703\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 656759  3.791592 -14.519582          696            0.000199         3.017703\n",
+       " 656760  3.793293 -14.519579          696            0.000191         3.017703\n",
+       " 656761  3.794995 -14.519576          696            0.000183         3.017703\n",
+       " 656762  3.796697 -14.519573          696            0.000175         3.017703\n",
+       " 656763  3.798398 -14.519571          696            0.000167         3.017703\n",
+       " \n",
+       " [646 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 657118  2.700801 -14.519798          697            3.012551         3.016207\n",
+       " 657119  2.702502 -14.519798          697            3.010180         3.016207\n",
+       " 657120  2.704204 -14.519798          697            3.007810         3.016207\n",
+       " 657121  2.705906 -14.519798          697            3.005430         3.016207\n",
+       " 657122  2.707608 -14.519798          697            3.003044         3.016207\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 657769  3.808609 -14.524803          697            0.000153         3.016207\n",
+       " 657770  3.810310 -14.524866          697            0.000146         3.016207\n",
+       " 657771  3.812012 -14.524928          697            0.000138         3.016207\n",
+       " 657772  3.813714 -14.524991          697            0.000131         3.016207\n",
+       " 657773  3.815415 -14.525053          697            0.000124         3.016207\n",
+       " \n",
+       " [656 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 658118  2.700801 -14.519252          698            3.007512         3.014141\n",
+       " 658119  2.702502 -14.519552          698            3.005149         3.014141\n",
+       " 658120  2.704204 -14.519812          698            3.002762         3.014141\n",
+       " 658121  2.705906 -14.519886          698            3.000272         3.014141\n",
+       " 658122  2.707608 -14.519959          698            2.997782         3.014141\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 658769  3.808609 -14.524822          698            0.000152         3.014141\n",
+       " 658770  3.810310 -14.524882          698            0.000145         3.014141\n",
+       " 658771  3.812012 -14.524941          698            0.000137         3.014141\n",
+       " 658772  3.813714 -14.525002          698            0.000130         3.014141\n",
+       " 658773  3.815415 -14.525062          698            0.000123         3.014141\n",
+       " \n",
+       " [656 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 659118  2.700801 -14.519499          699            3.007046         3.010968\n",
+       " 659119  2.702502 -14.519839          699            3.004807         3.010968\n",
+       " 659120  2.704204 -14.519959          699            3.002492         3.010968\n",
+       " 659121  2.705906 -14.519810          699            3.000085         3.010968\n",
+       " 659122  2.707608 -14.519659          699            2.997677         3.010968\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 659759  3.791592 -14.521730          699            0.000196         3.010968\n",
+       " 659760  3.793293 -14.521761          699            0.000188         3.010968\n",
+       " 659761  3.794995 -14.521792          699            0.000180         3.010968\n",
+       " 659762  3.796697 -14.521823          699            0.000172         3.010968\n",
+       " 659763  3.798398 -14.521853          699            0.000164         3.010968\n",
+       " \n",
+       " [646 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 660118  2.700801 -14.520256          700            3.006356         3.010103\n",
+       " 660119  2.702502 -14.520256          700            3.004107         3.010103\n",
+       " 660120  2.704204 -14.520256          700            3.001819         3.010103\n",
+       " 660121  2.705906 -14.520256          700            2.999504         3.010103\n",
+       " 660122  2.707608 -14.520256          700            2.997189         3.010103\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 660768  3.806907 -14.524977          700            0.000158         3.010103\n",
+       " 660769  3.808609 -14.525042          700            0.000151         3.010103\n",
+       " 660770  3.810310 -14.525106          700            0.000143         3.010103\n",
+       " 660771  3.812012 -14.525172          700            0.000136         3.010103\n",
+       " 660772  3.813714 -14.525237          700            0.000129         3.010103\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 661118  2.700801 -14.520182          701            3.007338         3.008929\n",
+       " 661119  2.702502 -14.520027          701            3.005033         3.008929\n",
+       " 661120  2.704204 -14.520027          701            3.002725         3.008929\n",
+       " 661121  2.705906 -14.520027          701            3.000417         3.008929\n",
+       " 661122  2.707608 -14.520027          701            2.998110         3.008929\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 661768  3.806907 -14.526733          701            0.000158         3.008929\n",
+       " 661769  3.808609 -14.526814          701            0.000151         3.008929\n",
+       " 661770  3.810310 -14.526894          701            0.000143         3.008929\n",
+       " 661771  3.812012 -14.526975          701            0.000136         3.008929\n",
+       " 661772  3.813714 -14.527055          701            0.000129         3.008929\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 662118  2.700801 -14.519798          702            3.004944         3.011587\n",
+       " 662119  2.702502 -14.519670          702            3.002627         3.011587\n",
+       " 662120  2.704204 -14.519444          702            3.000259         3.011587\n",
+       " 662121  2.705906 -14.519219          702            2.997891         3.011587\n",
+       " 662122  2.707608 -14.519188          702            2.995578         3.011587\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 662768  3.806907 -14.525870          702            0.000158         3.011587\n",
+       " 662769  3.808609 -14.525941          702            0.000150         3.011587\n",
+       " 662770  3.810310 -14.526011          702            0.000143         3.011587\n",
+       " 662771  3.812012 -14.526081          702            0.000136         3.011587\n",
+       " 662772  3.813714 -14.526152          702            0.000128         3.011587\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 663118  2.700801 -14.520106          703            3.000360         3.005182\n",
+       " 663119  2.702502 -14.520229          703            2.998127         3.005182\n",
+       " 663120  2.704204 -14.520007          703            2.995793         3.005182\n",
+       " 663121  2.705906 -14.519785          703            2.993460         3.005182\n",
+       " 663122  2.707608 -14.519573          703            2.991125         3.005182\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 663768  3.806907 -14.525887          703            0.000157         3.005182\n",
+       " 663769  3.808609 -14.525954          703            0.000150         3.005182\n",
+       " 663770  3.810310 -14.526021          703            0.000143         3.005182\n",
+       " 663771  3.812012 -14.526089          703            0.000135         3.005182\n",
+       " 663772  3.813714 -14.526156          703            0.000128         3.005182\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 664118  2.700801 -14.519906          704            3.001172         3.003131\n",
+       " 664119  2.702502 -14.520063          704            2.998906         3.003131\n",
+       " 664120  2.704204 -14.520138          704            2.996578         3.003131\n",
+       " 664121  2.705906 -14.520213          704            2.994249         3.003131\n",
+       " 664122  2.707608 -14.520193          704            2.991972         3.003131\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 664768  3.806907 -14.524789          704            0.000156         3.003131\n",
+       " 664769  3.808609 -14.524849          704            0.000149         3.003131\n",
+       " 664770  3.810310 -14.524909          704            0.000141         3.003131\n",
+       " 664771  3.812012 -14.524969          704            0.000134         3.003131\n",
+       " 664772  3.813714 -14.525028          704            0.000127         3.003131\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 665118  2.700801 -14.520112          705            3.000709         3.006862\n",
+       " 665119  2.702502 -14.520226          705            2.998457         3.006862\n",
+       " 665120  2.704204 -14.520080          705            2.996196         3.006862\n",
+       " 665121  2.705906 -14.519934          705            2.993934         3.006862\n",
+       " 665122  2.707608 -14.519804          705            2.991663         3.006862\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 665769  3.808609 -14.526567          705            0.000152         3.006862\n",
+       " 665770  3.810310 -14.526647          705            0.000145         3.006862\n",
+       " 665771  3.812012 -14.526728          705            0.000138         3.006862\n",
+       " 665772  3.813714 -14.526808          705            0.000130         3.006862\n",
+       " 665773  3.815415 -14.526889          705            0.000123         3.006862\n",
+       " \n",
+       " [656 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 666118  2.700801 -14.520027          706            2.997639         3.001562\n",
+       " 666119  2.702502 -14.520027          706            2.995381         3.001562\n",
+       " 666120  2.704204 -14.520054          706            2.993105         3.001562\n",
+       " 666121  2.705906 -14.520127          706            2.990797         3.001562\n",
+       " 666122  2.707608 -14.520202          706            2.988489         3.001562\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 666768  3.806907 -14.525233          706            0.000158         3.001562\n",
+       " 666769  3.808609 -14.525293          706            0.000150         3.001562\n",
+       " 666770  3.810310 -14.525353          706            0.000143         3.001562\n",
+       " 666771  3.812012 -14.525413          706            0.000136         3.001562\n",
+       " 666772  3.813714 -14.525473          706            0.000128         3.001562\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 667118  2.700801 -14.520185          707            2.995804          2.99893\n",
+       " 667119  2.702502 -14.520033          707            2.993589          2.99893\n",
+       " 667120  2.704204 -14.519880          707            2.991373          2.99893\n",
+       " 667121  2.705906 -14.519798          707            2.989166          2.99893\n",
+       " 667122  2.707608 -14.519798          707            2.986969          2.99893\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 667758  3.789890 -14.519784          707            0.000202          2.99893\n",
+       " 667759  3.791592 -14.519787          707            0.000194          2.99893\n",
+       " 667760  3.793293 -14.519790          707            0.000186          2.99893\n",
+       " 667761  3.794995 -14.519793          707            0.000178          2.99893\n",
+       " 667762  3.796697 -14.519795          707            0.000171          2.99893\n",
+       " \n",
+       " [645 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 668118  2.700801 -14.519945          708            2.993815         2.998236\n",
+       " 668119  2.702502 -14.520233          708            2.991610         2.998236\n",
+       " 668120  2.704204 -14.520520          708            2.989405         2.998236\n",
+       " 668121  2.705906 -14.520617          708            2.987197         2.998236\n",
+       " 668122  2.707608 -14.520321          708            2.984980         2.998236\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 668768  3.806907 -14.526300          708            0.000155         2.998236\n",
+       " 668769  3.808609 -14.526383          708            0.000147         2.998236\n",
+       " 668770  3.810310 -14.526466          708            0.000140         2.998236\n",
+       " 668771  3.812012 -14.526549          708            0.000133         2.998236\n",
+       " 668772  3.813714 -14.526632          708            0.000125         2.998236\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 669118  2.700801 -14.519625          709            2.994874         2.997334\n",
+       " 669119  2.702502 -14.519733          709            2.992768         2.997334\n",
+       " 669120  2.704204 -14.519828          709            2.990608         2.997334\n",
+       " 669121  2.705906 -14.519902          709            2.988365         2.997334\n",
+       " 669122  2.707608 -14.519976          709            2.986122         2.997334\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 669768  3.806907 -14.525018          709            0.000153         2.997334\n",
+       " 669769  3.808609 -14.525083          709            0.000146         2.997334\n",
+       " 669770  3.810310 -14.525148          709            0.000139         2.997334\n",
+       " 669771  3.812012 -14.525213          709            0.000131         2.997334\n",
+       " 669772  3.813714 -14.525278          709            0.000124         2.997334\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 670118  2.700801 -14.519613          710            2.991572          2.99701\n",
+       " 670119  2.702502 -14.519698          710            2.989398          2.99701\n",
+       " 670120  2.704204 -14.519783          710            2.987224          2.99701\n",
+       " 670121  2.705906 -14.519798          710            2.984912          2.99701\n",
+       " 670122  2.707608 -14.519798          710            2.982570          2.99701\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 670758  3.789890 -14.519811          710            0.000197          2.99701\n",
+       " 670759  3.791592 -14.519808          710            0.000189          2.99701\n",
+       " 670760  3.793293 -14.519805          710            0.000181          2.99701\n",
+       " 670761  3.794995 -14.519802          710            0.000173          2.99701\n",
+       " 670762  3.796697 -14.519799          710            0.000166          2.99701\n",
+       " \n",
+       " [645 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 671118  2.700801 -14.519798          711            2.990537          2.99542\n",
+       " 671119  2.702502 -14.519798          711            2.988357          2.99542\n",
+       " 671120  2.704204 -14.519798          711            2.986176          2.99542\n",
+       " 671121  2.705906 -14.519918          711            2.983950          2.99542\n",
+       " 671122  2.707608 -14.520063          711            2.981714          2.99542\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 671768  3.806907 -14.526530          711            0.000156          2.99542\n",
+       " 671769  3.808609 -14.526610          711            0.000148          2.99542\n",
+       " 671770  3.810310 -14.526691          711            0.000141          2.99542\n",
+       " 671771  3.812012 -14.526772          711            0.000134          2.99542\n",
+       " 671772  3.813714 -14.526852          711            0.000126          2.99542\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 672118  2.700801 -14.519983          712            2.990245         2.994697\n",
+       " 672119  2.702502 -14.519897          712            2.988080         2.994697\n",
+       " 672120  2.704204 -14.519810          712            2.985915         2.994697\n",
+       " 672121  2.705906 -14.519928          712            2.983643         2.994697\n",
+       " 672122  2.707608 -14.520079          712            2.981354         2.994697\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 672768  3.806907 -14.523254          712            0.000157         2.994697\n",
+       " 672769  3.808609 -14.523299          712            0.000149         2.994697\n",
+       " 672770  3.810310 -14.523343          712            0.000142         2.994697\n",
+       " 672771  3.812012 -14.523387          712            0.000135         2.994697\n",
+       " 672772  3.813714 -14.523432          712            0.000127         2.994697\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 673118  2.700801 -14.519803          713            2.992259         2.995588\n",
+       " 673119  2.702502 -14.519876          713            2.990003         2.995588\n",
+       " 673120  2.704204 -14.519951          713            2.987748         2.995588\n",
+       " 673121  2.705906 -14.520025          713            2.985492         2.995588\n",
+       " 673122  2.707608 -14.520027          713            2.983293         2.995588\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 673768  3.806907 -14.525827          713            0.000158         2.995588\n",
+       " 673769  3.808609 -14.525905          713            0.000151         2.995588\n",
+       " 673770  3.810310 -14.525983          713            0.000144         2.995588\n",
+       " 673771  3.812012 -14.526060          713            0.000136         2.995588\n",
+       " 673772  3.813714 -14.526138          713            0.000129         2.995588\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 674118  2.700801 -14.519758          714            2.990383         2.992929\n",
+       " 674119  2.702502 -14.519671          714            2.988218         2.992929\n",
+       " 674120  2.704204 -14.519585          714            2.986052         2.992929\n",
+       " 674121  2.705906 -14.519630          714            2.983824         2.992929\n",
+       " 674122  2.707608 -14.519704          714            2.981581         2.992929\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 674768  3.806907 -14.523494          714            0.000155         2.992929\n",
+       " 674769  3.808609 -14.523539          714            0.000148         2.992929\n",
+       " 674770  3.810310 -14.523582          714            0.000140         2.992929\n",
+       " 674771  3.812012 -14.523626          714            0.000133         2.992929\n",
+       " 674772  3.813714 -14.523670          714            0.000126         2.992929\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 675118  2.700801 -14.520163          715            2.987500          2.99367\n",
+       " 675119  2.702502 -14.519962          715            2.985296          2.99367\n",
+       " 675120  2.704204 -14.519798          715            2.983082          2.99367\n",
+       " 675121  2.705906 -14.519798          715            2.980826          2.99367\n",
+       " 675122  2.707608 -14.519798          715            2.978570          2.99367\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 675768  3.806907 -14.526568          715            0.000155          2.99367\n",
+       " 675769  3.808609 -14.526641          715            0.000148          2.99367\n",
+       " 675770  3.810310 -14.526713          715            0.000141          2.99367\n",
+       " 675771  3.812012 -14.526786          715            0.000133          2.99367\n",
+       " 675772  3.813714 -14.526859          715            0.000126          2.99367\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 676118  2.700801 -14.520256          716            2.984434         2.989777\n",
+       " 676119  2.702502 -14.520256          716            2.982312         2.989777\n",
+       " 676120  2.704204 -14.520243          716            2.980183         2.989777\n",
+       " 676121  2.705906 -14.520097          716            2.977986         2.989777\n",
+       " 676122  2.707608 -14.519951          716            2.975788         2.989777\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 676768  3.806907 -14.525670          716            0.000154         2.989777\n",
+       " 676769  3.808609 -14.525743          716            0.000146         2.989777\n",
+       " 676770  3.810310 -14.525815          716            0.000139         2.989777\n",
+       " 676771  3.812012 -14.525887          716            0.000132         2.989777\n",
+       " 676772  3.813714 -14.525960          716            0.000124         2.989777\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 677118  2.700801 -14.520379          717            2.983669         2.987647\n",
+       " 677119  2.702502 -14.520152          717            2.981550         2.987647\n",
+       " 677120  2.704204 -14.519995          717            2.979420         2.987647\n",
+       " 677121  2.705906 -14.519923          717            2.977279         2.987647\n",
+       " 677122  2.707608 -14.519851          717            2.975138         2.987647\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 677768  3.806907 -14.525002          717            0.000155         2.987647\n",
+       " 677769  3.808609 -14.525066          717            0.000148         2.987647\n",
+       " 677770  3.810310 -14.525131          717            0.000141         2.987647\n",
+       " 677771  3.812012 -14.525196          717            0.000133         2.987647\n",
+       " 677772  3.813714 -14.525261          717            0.000126         2.987647\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 678118  2.700801 -14.520149          718            2.981941         2.985309\n",
+       " 678119  2.702502 -14.520411          718            2.979749         2.985309\n",
+       " 678120  2.704204 -14.520537          718            2.977581         2.985309\n",
+       " 678121  2.705906 -14.520610          718            2.975422         2.985309\n",
+       " 678122  2.707608 -14.520683          718            2.973263         2.985309\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 678768  3.806907 -14.524590          718            0.000155         2.985309\n",
+       " 678769  3.808609 -14.524644          718            0.000148         2.985309\n",
+       " 678770  3.810310 -14.524698          718            0.000141         2.985309\n",
+       " 678771  3.812012 -14.524754          718            0.000133         2.985309\n",
+       " 678772  3.813714 -14.524808          718            0.000126         2.985309\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 679118  2.700801 -14.519657          719            2.982539         2.985631\n",
+       " 679119  2.702502 -14.519798          719            2.980458         2.985631\n",
+       " 679120  2.704204 -14.519798          719            2.978235         2.985631\n",
+       " 679121  2.705906 -14.519798          719            2.976013         2.985631\n",
+       " 679122  2.707608 -14.519814          719            2.973800         2.985631\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 679768  3.806907 -14.526101          719            0.000155         2.985631\n",
+       " 679769  3.808609 -14.526177          719            0.000148         2.985631\n",
+       " 679770  3.810310 -14.526253          719            0.000140         2.985631\n",
+       " 679771  3.812012 -14.526328          719            0.000133         2.985631\n",
+       " 679772  3.813714 -14.526403          719            0.000126         2.985631\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 680118  2.700801 -14.519976          720            2.982251          2.98509\n",
+       " 680119  2.702502 -14.519864          720            2.980119          2.98509\n",
+       " 680120  2.704204 -14.519769          720            2.977977          2.98509\n",
+       " 680121  2.705906 -14.519696          720            2.975817          2.98509\n",
+       " 680122  2.707608 -14.519623          720            2.973659          2.98509\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 680768  3.806907 -14.524806          720            0.000154          2.98509\n",
+       " 680769  3.808609 -14.524866          720            0.000147          2.98509\n",
+       " 680770  3.810310 -14.524925          720            0.000139          2.98509\n",
+       " 680771  3.812012 -14.524985          720            0.000132          2.98509\n",
+       " 680772  3.813714 -14.525044          720            0.000125          2.98509\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 681118  2.700801 -14.519798          721            2.980909         2.984725\n",
+       " 681119  2.702502 -14.519807          721            2.978821         2.984725\n",
+       " 681120  2.704204 -14.519880          721            2.976598         2.984725\n",
+       " 681121  2.705906 -14.519953          721            2.974374         2.984725\n",
+       " 681122  2.707608 -14.520026          721            2.972151         2.984725\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 681768  3.806907 -14.526320          721            0.000154         2.984725\n",
+       " 681769  3.808609 -14.526401          721            0.000147         2.984725\n",
+       " 681770  3.810310 -14.526481          721            0.000139         2.984725\n",
+       " 681771  3.812012 -14.526561          721            0.000132         2.984725\n",
+       " 681772  3.813714 -14.526641          721            0.000125         2.984725\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 682118  2.700801 -14.520096          722            2.979556         2.984275\n",
+       " 682119  2.702502 -14.520200          722            2.977436         2.984275\n",
+       " 682120  2.704204 -14.520124          722            2.975226         2.984275\n",
+       " 682121  2.705906 -14.520050          722            2.973017         2.984275\n",
+       " 682122  2.707608 -14.519976          722            2.970852         2.984275\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 682768  3.806907 -14.525242          722            0.000154         2.984275\n",
+       " 682769  3.808609 -14.525307          722            0.000147         2.984275\n",
+       " 682770  3.810310 -14.525372          722            0.000139         2.984275\n",
+       " 682771  3.812012 -14.525436          722            0.000132         2.984275\n",
+       " 682772  3.813714 -14.525501          722            0.000125         2.984275\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 683118  2.700801 -14.520256          723            2.977640         2.981492\n",
+       " 683119  2.702502 -14.520256          723            2.975457         2.981492\n",
+       " 683120  2.704204 -14.520256          723            2.973274         2.981492\n",
+       " 683121  2.705906 -14.520256          723            2.971091         2.981492\n",
+       " 683122  2.707608 -14.520329          723            2.968960         2.981492\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 683768  3.806907 -14.525702          723            0.000154         2.981492\n",
+       " 683769  3.808609 -14.525767          723            0.000146         2.981492\n",
+       " 683770  3.810310 -14.525832          723            0.000139         2.981492\n",
+       " 683771  3.812012 -14.525897          723            0.000132         2.981492\n",
+       " 683772  3.813714 -14.525962          723            0.000124         2.981492\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 684118  2.700801 -14.519855          724            2.984545         2.987887\n",
+       " 684119  2.702502 -14.519977          724            2.982403         2.987887\n",
+       " 684120  2.704204 -14.520027          724            2.980276         2.987887\n",
+       " 684121  2.705906 -14.520027          724            2.978160         2.987887\n",
+       " 684122  2.707608 -14.520027          724            2.976044         2.987887\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 684768  3.806907 -14.526267          724            0.000157         2.987887\n",
+       " 684769  3.808609 -14.526350          724            0.000150         2.987887\n",
+       " 684770  3.810310 -14.526433          724            0.000143         2.987887\n",
+       " 684771  3.812012 -14.526516          724            0.000136         2.987887\n",
+       " 684772  3.813714 -14.526599          724            0.000128         2.987887\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 685118  2.700801 -14.520123          725            2.979636         2.982147\n",
+       " 685119  2.702502 -14.520180          725            2.977612         2.982147\n",
+       " 685120  2.704204 -14.519958          725            2.975435         2.982147\n",
+       " 685121  2.705906 -14.519735          725            2.973258         2.982147\n",
+       " 685122  2.707608 -14.519624          725            2.971080         2.982147\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 685768  3.806907 -14.525249          725            0.000156         2.982147\n",
+       " 685769  3.808609 -14.525308          725            0.000149         2.982147\n",
+       " 685770  3.810310 -14.525368          725            0.000141         2.982147\n",
+       " 685771  3.812012 -14.525427          725            0.000134         2.982147\n",
+       " 685772  3.813714 -14.525487          725            0.000127         2.982147\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 686118  2.700801 -14.519608          726            2.975964         2.981685\n",
+       " 686119  2.702502 -14.519776          726            2.973874         2.981685\n",
+       " 686120  2.704204 -14.519989          726            2.971787         2.981685\n",
+       " 686121  2.705906 -14.520202          726            2.969701         2.981685\n",
+       " 686122  2.707608 -14.520311          726            2.967566         2.981685\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 686768  3.806907 -14.526117          726            0.000154         2.981685\n",
+       " 686769  3.808609 -14.526192          726            0.000146         2.981685\n",
+       " 686770  3.810310 -14.526267          726            0.000139         2.981685\n",
+       " 686771  3.812012 -14.526341          726            0.000132         2.981685\n",
+       " 686772  3.813714 -14.526417          726            0.000124         2.981685\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 687118  2.700801 -14.520256          727            2.977261          2.97827\n",
+       " 687119  2.702502 -14.520256          727            2.975153          2.97827\n",
+       " 687120  2.704204 -14.520256          727            2.973045          2.97827\n",
+       " 687121  2.705906 -14.520223          727            2.970921          2.97827\n",
+       " 687122  2.707608 -14.520151          727            2.968780          2.97827\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 687758  3.789890 -14.520878          727            0.000199          2.97827\n",
+       " 687759  3.791592 -14.520892          727            0.000192          2.97827\n",
+       " 687760  3.793293 -14.520905          727            0.000184          2.97827\n",
+       " 687761  3.794995 -14.520920          727            0.000176          2.97827\n",
+       " 687762  3.796697 -14.520933          727            0.000168          2.97827\n",
+       " \n",
+       " [645 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 688118  2.700801 -14.519924          728            2.976866         2.982535\n",
+       " 688119  2.702502 -14.519831          728            2.974842         2.982535\n",
+       " 688120  2.704204 -14.519904          728            2.972677         2.982535\n",
+       " 688121  2.705906 -14.519979          728            2.970513         2.982535\n",
+       " 688122  2.707608 -14.519953          728            2.968373         2.982535\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 688768  3.806907 -14.525671          728            0.000155         2.982535\n",
+       " 688769  3.808609 -14.525742          728            0.000147         2.982535\n",
+       " 688770  3.810310 -14.525811          728            0.000140         2.982535\n",
+       " 688771  3.812012 -14.525881          728            0.000133         2.982535\n",
+       " 688772  3.813714 -14.525951          728            0.000125         2.982535\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 689118  2.700801 -14.519951          729            2.976261         2.978909\n",
+       " 689119  2.702502 -14.519810          729            2.974253         2.978909\n",
+       " 689120  2.704204 -14.519959          729            2.972176         2.978909\n",
+       " 689121  2.705906 -14.520110          729            2.970099         2.978909\n",
+       " 689122  2.707608 -14.520252          729            2.968021         2.978909\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 689758  3.789890 -14.520457          729            0.000201         2.978909\n",
+       " 689759  3.791592 -14.520463          729            0.000194         2.978909\n",
+       " 689760  3.793293 -14.520469          729            0.000186         2.978909\n",
+       " 689761  3.794995 -14.520474          729            0.000178         2.978909\n",
+       " 689762  3.796697 -14.520480          729            0.000170         2.978909\n",
+       " \n",
+       " [645 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 690118  2.700801 -14.520027          730            2.975020         2.980299\n",
+       " 690119  2.702502 -14.520027          730            2.972887         2.980299\n",
+       " 690120  2.704204 -14.520027          730            2.970753         2.980299\n",
+       " 690121  2.705906 -14.520027          730            2.968613         2.980299\n",
+       " 690122  2.707608 -14.520027          730            2.966448         2.980299\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 690768  3.806907 -14.524790          730            0.000155         2.980299\n",
+       " 690769  3.808609 -14.524852          730            0.000147         2.980299\n",
+       " 690770  3.810310 -14.524914          730            0.000140         2.980299\n",
+       " 690771  3.812012 -14.524977          730            0.000133         2.980299\n",
+       " 690772  3.813714 -14.525039          730            0.000125         2.980299\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 691118  2.700801 -14.520005          731            2.974490         2.977432\n",
+       " 691119  2.702502 -14.520225          731            2.972430         2.977432\n",
+       " 691120  2.704204 -14.520151          731            2.970283         2.977432\n",
+       " 691121  2.705906 -14.520079          731            2.968137         2.977432\n",
+       " 691122  2.707608 -14.520006          731            2.966011         2.977432\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 691769  3.808609 -14.526796          731            0.000152         2.977432\n",
+       " 691770  3.810310 -14.526876          731            0.000145         2.977432\n",
+       " 691771  3.812012 -14.526958          731            0.000138         2.977432\n",
+       " 691772  3.813714 -14.527038          731            0.000130         2.977432\n",
+       " 691773  3.815415 -14.527118          731            0.000123         2.977432\n",
+       " \n",
+       " [656 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 692118  2.700801 -14.520256          732            2.971833         2.975699\n",
+       " 692119  2.702502 -14.520256          732            2.969784         2.975699\n",
+       " 692120  2.704204 -14.520195          732            2.967709         2.975699\n",
+       " 692121  2.705906 -14.520045          732            2.965592         2.975699\n",
+       " 692122  2.707608 -14.519896          732            2.963475         2.975699\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 692768  3.806907 -14.525010          732            0.000154         2.975699\n",
+       " 692769  3.808609 -14.525075          732            0.000147         2.975699\n",
+       " 692770  3.810310 -14.525140          732            0.000140         2.975699\n",
+       " 692771  3.812012 -14.525205          732            0.000132         2.975699\n",
+       " 692772  3.813714 -14.525270          732            0.000125         2.975699\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 693118  2.700801 -14.520131          733            2.970889         2.974465\n",
+       " 693119  2.702502 -14.519862          733            2.968782         2.974465\n",
+       " 693120  2.704204 -14.519742          733            2.966651         2.974465\n",
+       " 693121  2.705906 -14.519668          733            2.964513         2.974465\n",
+       " 693122  2.707608 -14.519594          733            2.962374         2.974465\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 693768  3.806907 -14.526342          733            0.000153         2.974465\n",
+       " 693769  3.808609 -14.526420          733            0.000146         2.974465\n",
+       " 693770  3.810310 -14.526497          733            0.000138         2.974465\n",
+       " 693771  3.812012 -14.526574          733            0.000131         2.974465\n",
+       " 693772  3.813714 -14.526652          733            0.000124         2.974465\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 694118  2.700801 -14.519917          734            2.969486         2.973412\n",
+       " 694119  2.702502 -14.520172          734            2.967484         2.973412\n",
+       " 694120  2.704204 -14.520154          734            2.965393         2.973412\n",
+       " 694121  2.705906 -14.520001          734            2.963258         2.973412\n",
+       " 694122  2.707608 -14.519849          734            2.961123         2.973412\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 694768  3.806907 -14.524579          734            0.000152         2.973412\n",
+       " 694769  3.808609 -14.524641          734            0.000145         2.973412\n",
+       " 694770  3.810310 -14.524703          734            0.000138         2.973412\n",
+       " 694771  3.812012 -14.524764          734            0.000131         2.973412\n",
+       " 694772  3.813714 -14.524826          734            0.000123         2.973412\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 695118  2.700801 -14.519864          735            2.968150         2.973113\n",
+       " 695119  2.702502 -14.520006          735            2.966226         2.973113\n",
+       " 695120  2.704204 -14.520027          735            2.964168         2.973113\n",
+       " 695121  2.705906 -14.520027          735            2.962086         2.973113\n",
+       " 695122  2.707608 -14.520027          735            2.960004         2.973113\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 695768  3.806907 -14.525920          735            0.000152         2.973113\n",
+       " 695769  3.808609 -14.525990          735            0.000145         2.973113\n",
+       " 695770  3.810310 -14.526059          735            0.000138         2.973113\n",
+       " 695771  3.812012 -14.526129          735            0.000131         2.973113\n",
+       " 695772  3.813714 -14.526198          735            0.000123         2.973113\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 696118  2.700801 -14.519591          736            2.967960         2.970778\n",
+       " 696119  2.702502 -14.519341          736            2.965885         2.970778\n",
+       " 696120  2.704204 -14.519341          736            2.963807         2.970778\n",
+       " 696121  2.705906 -14.519341          736            2.961729         2.970778\n",
+       " 696122  2.707608 -14.519414          736            2.959650         2.970778\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 696767  3.805205 -14.525192          736            0.000158         2.970778\n",
+       " 696768  3.806907 -14.525260          736            0.000151         2.970778\n",
+       " 696769  3.808609 -14.525327          736            0.000144         2.970778\n",
+       " 696770  3.810310 -14.525393          736            0.000136         2.970778\n",
+       " 696771  3.812012 -14.525460          736            0.000129         2.970778\n",
+       " \n",
+       " [654 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 697118  2.700801 -14.520256          737            2.967285          2.97066\n",
+       " 697119  2.702502 -14.520256          737            2.965235          2.97066\n",
+       " 697120  2.704204 -14.520256          737            2.963186          2.97066\n",
+       " 697121  2.705906 -14.520256          737            2.961139          2.97066\n",
+       " 697122  2.707608 -14.520256          737            2.959092          2.97066\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 697768  3.806907 -14.525677          737            0.000152          2.97066\n",
+       " 697769  3.808609 -14.525751          737            0.000145          2.97066\n",
+       " 697770  3.810310 -14.525826          737            0.000137          2.97066\n",
+       " 697771  3.812012 -14.525901          737            0.000130          2.97066\n",
+       " 697772  3.813714 -14.525976          737            0.000123          2.97066\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 698118  2.700801 -14.519613          738            2.966963         2.971392\n",
+       " 698119  2.702502 -14.519708          738            2.964914         2.971392\n",
+       " 698120  2.704204 -14.519798          738            2.962864         2.971392\n",
+       " 698121  2.705906 -14.519798          738            2.960802         2.971392\n",
+       " 698122  2.707608 -14.519798          738            2.958741         2.971392\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 698768  3.806907 -14.524808          738            0.000155         2.971392\n",
+       " 698769  3.808609 -14.524865          738            0.000148         2.971392\n",
+       " 698770  3.810310 -14.524921          738            0.000141         2.971392\n",
+       " 698771  3.812012 -14.524979          738            0.000133         2.971392\n",
+       " 698772  3.813714 -14.525036          738            0.000126         2.971392\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 699118  2.700801 -14.520123          739            2.966122          2.96979\n",
+       " 699119  2.702502 -14.519979          739            2.964077          2.96979\n",
+       " 699120  2.704204 -14.519906          739            2.961982          2.96979\n",
+       " 699121  2.705906 -14.519834          739            2.959887          2.96979\n",
+       " 699122  2.707608 -14.519760          739            2.957790          2.96979\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 699768  3.806907 -14.526765          739            0.000154          2.96979\n",
+       " 699769  3.808609 -14.526847          739            0.000147          2.96979\n",
+       " 699770  3.810310 -14.526929          739            0.000139          2.96979\n",
+       " 699771  3.812012 -14.527012          739            0.000132          2.96979\n",
+       " 699772  3.813714 -14.527094          739            0.000125          2.96979\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 700118  2.700801 -14.519569          740            2.964540         2.969165\n",
+       " 700119  2.702502 -14.519569          740            2.962483         2.969165\n",
+       " 700120  2.704204 -14.519742          740            2.960387         2.969165\n",
+       " 700121  2.705906 -14.520038          740            2.958262         2.969165\n",
+       " 700122  2.707608 -14.520334          740            2.956136         2.969165\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 700768  3.806907 -14.525702          740            0.000154         2.969165\n",
+       " 700769  3.808609 -14.525766          740            0.000146         2.969165\n",
+       " 700770  3.810310 -14.525830          740            0.000139         2.969165\n",
+       " 700771  3.812012 -14.525894          740            0.000132         2.969165\n",
+       " 700772  3.813714 -14.525959          740            0.000125         2.969165\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 701118  2.700801 -14.519683          741            2.967160         2.967901\n",
+       " 701119  2.702502 -14.519759          741            2.965156         2.967901\n",
+       " 701120  2.704204 -14.519686          741            2.963044         2.967901\n",
+       " 701121  2.705906 -14.519611          741            2.960932         2.967901\n",
+       " 701122  2.707608 -14.519601          741            2.958838         2.967901\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 701766  3.803504 -14.525171          741            0.000159         2.967901\n",
+       " 701767  3.805205 -14.525242          741            0.000152         2.967901\n",
+       " 701768  3.806907 -14.525312          741            0.000144         2.967901\n",
+       " 701769  3.808609 -14.525383          741            0.000137         2.967901\n",
+       " 701770  3.810310 -14.525454          741            0.000130         2.967901\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 702118  2.700801 -14.519590          742            2.961347         2.968332\n",
+       " 702119  2.702502 -14.519665          742            2.959248         2.968332\n",
+       " 702120  2.704204 -14.519738          742            2.957149         2.968332\n",
+       " 702121  2.705906 -14.519827          742            2.955068         2.968332\n",
+       " 702122  2.707608 -14.519972          742            2.953063         2.968332\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 702768  3.806907 -14.524624          742            0.000152         2.968332\n",
+       " 702769  3.808609 -14.524675          742            0.000145         2.968332\n",
+       " 702770  3.810310 -14.524727          742            0.000138         2.968332\n",
+       " 702771  3.812012 -14.524778          742            0.000130         2.968332\n",
+       " 702772  3.813714 -14.524830          742            0.000123         2.968332\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 703118  2.700801 -14.520197          743            2.960597         2.964559\n",
+       " 703119  2.702502 -14.520317          743            2.958541         2.964559\n",
+       " 703120  2.704204 -14.520391          743            2.956498         2.964559\n",
+       " 703121  2.705906 -14.520463          743            2.954454         2.964559\n",
+       " 703122  2.707608 -14.520378          743            2.952385         2.964559\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 703768  3.806907 -14.525266          743            0.000154         2.964559\n",
+       " 703769  3.808609 -14.525325          743            0.000146         2.964559\n",
+       " 703770  3.810310 -14.525384          743            0.000139         2.964559\n",
+       " 703771  3.812012 -14.525443          743            0.000132         2.964559\n",
+       " 703772  3.813714 -14.525502          743            0.000125         2.964559\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 704118  2.700801 -14.520027          744            2.959448         2.963113\n",
+       " 704119  2.702502 -14.520027          744            2.957555         2.963113\n",
+       " 704120  2.704204 -14.520087          744            2.955495         2.963113\n",
+       " 704121  2.705906 -14.520161          744            2.953396         2.963113\n",
+       " 704122  2.707608 -14.520235          744            2.951297         2.963113\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 704768  3.806907 -14.526085          744            0.000157         2.963113\n",
+       " 704769  3.808609 -14.526159          744            0.000149         2.963113\n",
+       " 704770  3.810310 -14.526235          744            0.000142         2.963113\n",
+       " 704771  3.812012 -14.526309          744            0.000135         2.963113\n",
+       " 704772  3.813714 -14.526383          744            0.000128         2.963113\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 705118  2.700801 -14.520308          745            2.960297         2.962453\n",
+       " 705119  2.702502 -14.520027          745            2.958366         2.962453\n",
+       " 705120  2.704204 -14.520027          745            2.956342         2.962453\n",
+       " 705121  2.705906 -14.520027          745            2.954318         2.962453\n",
+       " 705122  2.707608 -14.519997          745            2.952276         2.962453\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 705768  3.806907 -14.524591          745            0.000155         2.962453\n",
+       " 705769  3.808609 -14.524645          745            0.000148         2.962453\n",
+       " 705770  3.810310 -14.524699          745            0.000141         2.962453\n",
+       " 705771  3.812012 -14.524754          745            0.000133         2.962453\n",
+       " 705772  3.813714 -14.524808          745            0.000126         2.962453\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 706118  2.700801 -14.519811          746            2.960586         2.963063\n",
+       " 706119  2.702502 -14.519869          746            2.958524         2.963063\n",
+       " 706120  2.704204 -14.519942          746            2.956455         2.963063\n",
+       " 706121  2.705906 -14.520015          746            2.954386         2.963063\n",
+       " 706122  2.707608 -14.519965          746            2.952379         2.963063\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 706768  3.806907 -14.525037          746            0.000152         2.963063\n",
+       " 706769  3.808609 -14.525099          746            0.000145         2.963063\n",
+       " 706770  3.810310 -14.525161          746            0.000138         2.963063\n",
+       " 706771  3.812012 -14.525223          746            0.000131         2.963063\n",
+       " 706772  3.813714 -14.525284          746            0.000123         2.963063\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 707118  2.700801 -14.520278          747            2.959992         2.964274\n",
+       " 707119  2.702502 -14.520059          747            2.957960         2.964274\n",
+       " 707120  2.704204 -14.520132          747            2.955929         2.964274\n",
+       " 707121  2.705906 -14.520205          747            2.953899         2.964274\n",
+       " 707122  2.707608 -14.520211          747            2.951858         2.964274\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 707768  3.806907 -14.525003          747            0.000155         2.964274\n",
+       " 707769  3.808609 -14.525068          747            0.000148         2.964274\n",
+       " 707770  3.810310 -14.525132          747            0.000140         2.964274\n",
+       " 707771  3.812012 -14.525196          747            0.000133         2.964274\n",
+       " 707772  3.813714 -14.525261          747            0.000126         2.964274\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 708118  2.700801 -14.520126          748            2.957039         2.961259\n",
+       " 708119  2.702502 -14.519848          748            2.955158         2.961259\n",
+       " 708120  2.704204 -14.519569          748            2.953276         2.961259\n",
+       " 708121  2.705906 -14.519719          748            2.951133         2.961259\n",
+       " 708122  2.707608 -14.519870          748            2.948990         2.961259\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 708768  3.806907 -14.526569          748            0.000152         2.961259\n",
+       " 708769  3.808609 -14.526649          748            0.000145         2.961259\n",
+       " 708770  3.810310 -14.526729          748            0.000138         2.961259\n",
+       " 708771  3.812012 -14.526808          748            0.000130         2.961259\n",
+       " 708772  3.813714 -14.526888          748            0.000123         2.961259\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 709118  2.700801 -14.520256          749            2.955127         2.959217\n",
+       " 709119  2.702502 -14.520256          749            2.953222         2.959217\n",
+       " 709120  2.704204 -14.520041          749            2.951168         2.959217\n",
+       " 709121  2.705906 -14.519821          749            2.949111         2.959217\n",
+       " 709122  2.707608 -14.519603          749            2.947055         2.959217\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 709768  3.806907 -14.526572          749            0.000152         2.959217\n",
+       " 709769  3.808609 -14.526652          749            0.000144         2.959217\n",
+       " 709770  3.810310 -14.526731          749            0.000137         2.959217\n",
+       " 709771  3.812012 -14.526812          749            0.000130         2.959217\n",
+       " 709772  3.813714 -14.526892          749            0.000123         2.959217\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 710118  2.700801 -14.520027          750            2.954366         2.958385\n",
+       " 710119  2.702502 -14.520027          750            2.952463         2.958385\n",
+       " 710120  2.704204 -14.520017          750            2.950531         2.958385\n",
+       " 710121  2.705906 -14.519940          750            2.948409         2.958385\n",
+       " 710122  2.707608 -14.519864          750            2.946288         2.958385\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 710768  3.806907 -14.525918          750            0.000153         2.958385\n",
+       " 710769  3.808609 -14.525988          750            0.000145         2.958385\n",
+       " 710770  3.810310 -14.526057          750            0.000138         2.958385\n",
+       " 710771  3.812012 -14.526126          750            0.000131         2.958385\n",
+       " 710772  3.813714 -14.526196          750            0.000124         2.958385\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 711118  2.700801 -14.519849          751            2.953380         2.956701\n",
+       " 711119  2.702502 -14.519958          751            2.951351         2.956701\n",
+       " 711120  2.704204 -14.520053          751            2.949333         2.956701\n",
+       " 711121  2.705906 -14.520123          751            2.947334         2.956701\n",
+       " 711122  2.707608 -14.520194          751            2.945335         2.956701\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 711768  3.806907 -14.526995          751            0.000154         2.956701\n",
+       " 711769  3.808609 -14.527077          751            0.000147         2.956701\n",
+       " 711770  3.810310 -14.527159          751            0.000139         2.956701\n",
+       " 711771  3.812012 -14.527241          751            0.000132         2.956701\n",
+       " 711772  3.813714 -14.527323          751            0.000125         2.956701\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 712118  2.700801 -14.519755          752            2.953147         2.956875\n",
+       " 712119  2.702502 -14.519671          752            2.951156         2.956875\n",
+       " 712120  2.704204 -14.519588          752            2.949165         2.956875\n",
+       " 712121  2.705906 -14.519739          752            2.947104         2.956875\n",
+       " 712122  2.707608 -14.519958          752            2.945022         2.956875\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 712758  3.789890 -14.520221          752            0.000196         2.956875\n",
+       " 712759  3.791592 -14.520228          752            0.000189         2.956875\n",
+       " 712760  3.793293 -14.520237          752            0.000181         2.956875\n",
+       " 712761  3.794995 -14.520246          752            0.000173         2.956875\n",
+       " 712762  3.796697 -14.520253          752            0.000165         2.956875\n",
+       " \n",
+       " [645 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 713118  2.700801 -14.520150          753            2.952503         2.955175\n",
+       " 713119  2.702502 -14.519923          753            2.950584         2.955175\n",
+       " 713120  2.704204 -14.519832          753            2.948582         2.955175\n",
+       " 713121  2.705906 -14.519907          753            2.946479         2.955175\n",
+       " 713122  2.707608 -14.519982          753            2.944376         2.955175\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 713768  3.806907 -14.526780          753            0.000153         2.955175\n",
+       " 713769  3.808609 -14.526862          753            0.000145         2.955175\n",
+       " 713770  3.810310 -14.526945          753            0.000138         2.955175\n",
+       " 713771  3.812012 -14.527027          753            0.000131         2.955175\n",
+       " 713772  3.813714 -14.527109          753            0.000124         2.955175\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 714118  2.700801 -14.519946          754            2.952004         2.956117\n",
+       " 714119  2.702502 -14.519773          754            2.950053         2.956117\n",
+       " 714120  2.704204 -14.519601          754            2.948101         2.956117\n",
+       " 714121  2.705906 -14.519629          754            2.946084         2.956117\n",
+       " 714122  2.707608 -14.519702          754            2.944054         2.956117\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 714768  3.806907 -14.525252          754            0.000154         2.956117\n",
+       " 714769  3.808609 -14.525314          754            0.000147         2.956117\n",
+       " 714770  3.810310 -14.525376          754            0.000139         2.956117\n",
+       " 714771  3.812012 -14.525437          754            0.000132         2.956117\n",
+       " 714772  3.813714 -14.525499          754            0.000125         2.956117\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 715118  2.700801 -14.520027          755            2.950056         2.953373\n",
+       " 715119  2.702502 -14.520027          755            2.948076         2.953373\n",
+       " 715120  2.704204 -14.519995          755            2.946086         2.953373\n",
+       " 715121  2.705906 -14.519849          755            2.944055         2.953373\n",
+       " 715122  2.707608 -14.519703          755            2.942025         2.953373\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 715768  3.806907 -14.524173          755            0.000153         2.953373\n",
+       " 715769  3.808609 -14.524221          755            0.000145         2.953373\n",
+       " 715770  3.810310 -14.524270          755            0.000138         2.953373\n",
+       " 715771  3.812012 -14.524319          755            0.000131         2.953373\n",
+       " 715772  3.813714 -14.524368          755            0.000124         2.953373\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 716118  2.700801 -14.519983          756            2.949176         2.952323\n",
+       " 716119  2.702502 -14.519889          756            2.947127         2.952323\n",
+       " 716120  2.704204 -14.519801          756            2.945078         2.952323\n",
+       " 716121  2.705906 -14.519874          756            2.943025         2.952323\n",
+       " 716122  2.707608 -14.519945          756            2.940972         2.952323\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 716767  3.805205 -14.526071          756            0.000158         2.952323\n",
+       " 716768  3.806907 -14.526146          756            0.000151         2.952323\n",
+       " 716769  3.808609 -14.526220          756            0.000143         2.952323\n",
+       " 716770  3.810310 -14.526295          756            0.000136         2.952323\n",
+       " 716771  3.812012 -14.526369          756            0.000129         2.952323\n",
+       " \n",
+       " [654 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 717118  2.700801 -14.519961          757            2.950029         2.952869\n",
+       " 717119  2.702502 -14.519819          757            2.948080         2.952869\n",
+       " 717120  2.704204 -14.519861          757            2.946081         2.952869\n",
+       " 717121  2.705906 -14.519936          757            2.944073         2.952869\n",
+       " 717122  2.707608 -14.520009          757            2.942065         2.952869\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 717768  3.806907 -14.525271          757            0.000153         2.952869\n",
+       " 717769  3.808609 -14.525331          757            0.000146         2.952869\n",
+       " 717770  3.810310 -14.525390          757            0.000138         2.952869\n",
+       " 717771  3.812012 -14.525449          757            0.000131         2.952869\n",
+       " 717772  3.813714 -14.525508          757            0.000124         2.952869\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 718118  2.700801 -14.520256          758            2.947580         2.951812\n",
+       " 718119  2.702502 -14.520256          758            2.945567         2.951812\n",
+       " 718120  2.704204 -14.520144          758            2.943578         2.951812\n",
+       " 718121  2.705906 -14.519996          758            2.941597         2.951812\n",
+       " 718122  2.707608 -14.519847          758            2.939615         2.951812\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 718768  3.806907 -14.526112          758            0.000152         2.951812\n",
+       " 718769  3.808609 -14.526192          758            0.000145         2.951812\n",
+       " 718770  3.810310 -14.526271          758            0.000137         2.951812\n",
+       " 718771  3.812012 -14.526350          758            0.000130         2.951812\n",
+       " 718772  3.813714 -14.526430          758            0.000123         2.951812\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 719118  2.700801 -14.520180          759            2.949413         2.952654\n",
+       " 719119  2.702502 -14.520029          759            2.947535         2.952654\n",
+       " 719120  2.704204 -14.519954          759            2.945464         2.952654\n",
+       " 719121  2.705906 -14.519880          759            2.943391         2.952654\n",
+       " 719122  2.707608 -14.519806          759            2.941318         2.952654\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 719768  3.806907 -14.526574          759            0.000154         2.952654\n",
+       " 719769  3.808609 -14.526649          759            0.000146         2.952654\n",
+       " 719770  3.810310 -14.526723          759            0.000139         2.952654\n",
+       " 719771  3.812012 -14.526797          759            0.000132         2.952654\n",
+       " 719772  3.813714 -14.526872          759            0.000125         2.952654\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 720118  2.700801 -14.519887          760            2.945008         2.949825\n",
+       " 720119  2.702502 -14.519798          760            2.943062         2.949825\n",
+       " 720120  2.704204 -14.519798          760            2.941097         2.949825\n",
+       " 720121  2.705906 -14.519798          760            2.939134         2.949825\n",
+       " 720122  2.707608 -14.519876          760            2.937125         2.949825\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 720767  3.805205 -14.524778          760            0.000157         2.949825\n",
+       " 720768  3.806907 -14.524837          760            0.000150         2.949825\n",
+       " 720769  3.808609 -14.524897          760            0.000143         2.949825\n",
+       " 720770  3.810310 -14.524956          760            0.000136         2.949825\n",
+       " 720771  3.812012 -14.525015          760            0.000128         2.949825\n",
+       " \n",
+       " [654 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 721118  2.700801 -14.519661          761            2.943823          2.94697\n",
+       " 721119  2.702502 -14.519821          761            2.941834          2.94697\n",
+       " 721120  2.704204 -14.519897          761            2.939726          2.94697\n",
+       " 721121  2.705906 -14.519974          761            2.937618          2.94697\n",
+       " 721122  2.707608 -14.520006          761            2.935542          2.94697\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 721767  3.805205 -14.524996          761            0.000157          2.94697\n",
+       " 721768  3.806907 -14.525057          761            0.000150          2.94697\n",
+       " 721769  3.808609 -14.525119          761            0.000143          2.94697\n",
+       " 721770  3.810310 -14.525181          761            0.000136          2.94697\n",
+       " 721771  3.812012 -14.525242          761            0.000128          2.94697\n",
+       " \n",
+       " [654 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 722118  2.700801 -14.520256          762            2.947361         2.950059\n",
+       " 722119  2.702502 -14.520256          762            2.945327         2.950059\n",
+       " 722120  2.704204 -14.520256          762            2.943293         2.950059\n",
+       " 722121  2.705906 -14.520252          762            2.941261         2.950059\n",
+       " 722122  2.707608 -14.520180          762            2.939246         2.950059\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 722769  3.808609 -14.526538          762            0.000154         2.950059\n",
+       " 722770  3.810310 -14.526621          762            0.000146         2.950059\n",
+       " 722771  3.812012 -14.526704          762            0.000139         2.950059\n",
+       " 722772  3.813714 -14.526787          762            0.000132         2.950059\n",
+       " 722773  3.815415 -14.526870          762            0.000125         2.950059\n",
+       " \n",
+       " [656 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 723118  2.700801 -14.519863          763            2.948615         2.950423\n",
+       " 723119  2.702502 -14.519594          763            2.946656         2.950423\n",
+       " 723120  2.704204 -14.519745          763            2.944671         2.950423\n",
+       " 723121  2.705906 -14.519895          763            2.942687         2.950423\n",
+       " 723122  2.707608 -14.520010          763            2.940692         2.950423\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 723768  3.806907 -14.524143          763            0.000155         2.950423\n",
+       " 723769  3.808609 -14.524195          763            0.000148         2.950423\n",
+       " 723770  3.810310 -14.524246          763            0.000141         2.950423\n",
+       " 723771  3.812012 -14.524298          763            0.000134         2.950423\n",
+       " 723772  3.813714 -14.524349          763            0.000126         2.950423\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 724118  2.700801 -14.519851          764            2.944375         2.950563\n",
+       " 724119  2.702502 -14.519626          764            2.942405         2.950563\n",
+       " 724120  2.704204 -14.519844          764            2.940426         2.950563\n",
+       " 724121  2.705906 -14.520062          764            2.938447         2.950563\n",
+       " 724122  2.707608 -14.520221          764            2.936463         2.950563\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 724768  3.806907 -14.523497          764            0.000153         2.950563\n",
+       " 724769  3.808609 -14.523543          764            0.000145         2.950563\n",
+       " 724770  3.810310 -14.523589          764            0.000138         2.950563\n",
+       " 724771  3.812012 -14.523636          764            0.000131         2.950563\n",
+       " 724772  3.813714 -14.523682          764            0.000124         2.950563\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 725118  2.700801 -14.519878          765            2.941622         2.945248\n",
+       " 725119  2.702502 -14.519559          765            2.939636         2.945248\n",
+       " 725120  2.704204 -14.519318          765            2.937643         2.945248\n",
+       " 725121  2.705906 -14.519243          765            2.935635         2.945248\n",
+       " 725122  2.707608 -14.519169          765            2.933627         2.945248\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 725768  3.806907 -14.525928          765            0.000152         2.945248\n",
+       " 725769  3.808609 -14.525997          765            0.000144         2.945248\n",
+       " 725770  3.810310 -14.526067          765            0.000137         2.945248\n",
+       " 725771  3.812012 -14.526135          765            0.000130         2.945248\n",
+       " 725772  3.813714 -14.526205          765            0.000123         2.945248\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 726118  2.700801 -14.519798          766            2.943266         2.945465\n",
+       " 726119  2.702502 -14.519750          766            2.941329         2.945465\n",
+       " 726120  2.704204 -14.519675          766            2.939295         2.945465\n",
+       " 726121  2.705906 -14.519602          766            2.937261         2.945465\n",
+       " 726122  2.707608 -14.519739          766            2.935210         2.945465\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 726768  3.806907 -14.526559          766            0.000153         2.945465\n",
+       " 726769  3.808609 -14.526638          766            0.000146         2.945465\n",
+       " 726770  3.810310 -14.526718          766            0.000138         2.945465\n",
+       " 726771  3.812012 -14.526797          766            0.000131         2.945465\n",
+       " 726772  3.813714 -14.526877          766            0.000124         2.945465\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 727118  2.700801 -14.520002          767            2.939454         2.944345\n",
+       " 727119  2.702502 -14.519929          767            2.937420         2.944345\n",
+       " 727120  2.704204 -14.519855          767            2.935386         2.944345\n",
+       " 727121  2.705906 -14.519815          767            2.933362         2.944345\n",
+       " 727122  2.707608 -14.519890          767            2.931367         2.944345\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 727767  3.805205 -14.524799          767            0.000158         2.944345\n",
+       " 727768  3.806907 -14.524853          767            0.000151         2.944345\n",
+       " 727769  3.808609 -14.524907          767            0.000143         2.944345\n",
+       " 727770  3.810310 -14.524961          767            0.000136         2.944345\n",
+       " 727771  3.812012 -14.525015          767            0.000129         2.944345\n",
+       " \n",
+       " [654 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 728118  2.700801 -14.519843          768            2.938460         2.941854\n",
+       " 728119  2.702502 -14.519939          768            2.936525         2.941854\n",
+       " 728120  2.704204 -14.520034          768            2.934580         2.941854\n",
+       " 728121  2.705906 -14.520108          768            2.932533         2.941854\n",
+       " 728122  2.707608 -14.520182          768            2.930486         2.941854\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 728767  3.805205 -14.526949          768            0.000157         2.941854\n",
+       " 728768  3.806907 -14.527034          768            0.000150         2.941854\n",
+       " 728769  3.808609 -14.527119          768            0.000142         2.941854\n",
+       " 728770  3.810310 -14.527203          768            0.000135         2.941854\n",
+       " 728771  3.812012 -14.527287          768            0.000128         2.941854\n",
+       " \n",
+       " [654 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 729118  2.700801 -14.519835          769            2.938853         2.941796\n",
+       " 729119  2.702502 -14.519912          769            2.936808         2.941796\n",
+       " 729120  2.704204 -14.519989          769            2.934763         2.941796\n",
+       " 729121  2.705906 -14.519990          769            2.932724         2.941796\n",
+       " 729122  2.707608 -14.519916          769            2.930690         2.941796\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 729767  3.805205 -14.524992          769            0.000156         2.941796\n",
+       " 729768  3.806907 -14.525056          769            0.000149         2.941796\n",
+       " 729769  3.808609 -14.525121          769            0.000142         2.941796\n",
+       " 729770  3.810310 -14.525185          769            0.000135         2.941796\n",
+       " 729771  3.812012 -14.525249          769            0.000127         2.941796\n",
+       " \n",
+       " [654 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 730118  2.700801 -14.520003          770            2.939433         2.943276\n",
+       " 730119  2.702502 -14.519785          770            2.937467         2.943276\n",
+       " 730120  2.704204 -14.519567          770            2.935501         2.943276\n",
+       " 730121  2.705906 -14.519347          770            2.933534         2.943276\n",
+       " 730122  2.707608 -14.519411          770            2.931481         2.943276\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 730768  3.806907 -14.526135          770            0.000153         2.943276\n",
+       " 730769  3.808609 -14.526207          770            0.000146         2.943276\n",
+       " 730770  3.810310 -14.526278          770            0.000138         2.943276\n",
+       " 730771  3.812012 -14.526349          770            0.000131         2.943276\n",
+       " 730772  3.813714 -14.526421          770            0.000124         2.943276\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 731118  2.700801 -14.519811          776            3.031269          3.13307\n",
+       " 731119  2.702502 -14.519872          776            3.028549          3.13307\n",
+       " 731120  2.704204 -14.519946          776            3.025824          3.13307\n",
+       " 731121  2.705906 -14.520021          776            3.023098          3.13307\n",
+       " 731122  2.707608 -14.520097          776            3.020324          3.13307\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 731770  3.810310 -14.526547          776            0.000154          3.13307\n",
+       " 731771  3.812012 -14.526628          776            0.000147          3.13307\n",
+       " 731772  3.813714 -14.526708          776            0.000139          3.13307\n",
+       " 731773  3.815415 -14.526788          776            0.000132          3.13307\n",
+       " 731774  3.817117 -14.526868          776            0.000125          3.13307\n",
+       " \n",
+       " [657 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 732118  2.700801 -14.520152          777            3.015207         3.029301\n",
+       " 732119  2.702502 -14.520210          777            3.012523         3.029301\n",
+       " 732120  2.704204 -14.520137          777            3.009759         3.029301\n",
+       " 732121  2.705906 -14.520062          777            3.006995         3.029301\n",
+       " 732122  2.707608 -14.520027          777            3.004203         3.029301\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 732769  3.808609 -14.524373          777            0.000155         3.029301\n",
+       " 732770  3.810310 -14.524425          777            0.000148         3.029301\n",
+       " 732771  3.812012 -14.524476          777            0.000141         3.029301\n",
+       " 732772  3.813714 -14.524528          777            0.000133         3.029301\n",
+       " 732773  3.815415 -14.524579          777            0.000126         3.029301\n",
+       " \n",
+       " [656 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 733118  2.700801 -14.519518          778            3.005213          3.01628\n",
+       " 733119  2.702502 -14.519406          778            3.002417          3.01628\n",
+       " 733120  2.704204 -14.519341          778            2.999670          3.01628\n",
+       " 733121  2.705906 -14.519341          778            2.996997          3.01628\n",
+       " 733122  2.707608 -14.519341          778            2.994325          3.01628\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 733769  3.808609 -14.526759          778            0.000153          3.01628\n",
+       " 733770  3.810310 -14.526844          778            0.000146          3.01628\n",
+       " 733771  3.812012 -14.526929          778            0.000139          3.01628\n",
+       " 733772  3.813714 -14.527014          778            0.000132          3.01628\n",
+       " 733773  3.815415 -14.527099          778            0.000125          3.01628\n",
+       " \n",
+       " [656 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 734118  2.700801 -14.519989          779            2.997021         3.007178\n",
+       " 734119  2.702502 -14.520205          779            2.994278         3.007178\n",
+       " 734120  2.704204 -14.520060          779            2.991656         3.007178\n",
+       " 734121  2.705906 -14.519914          779            2.989035         3.007178\n",
+       " 734122  2.707608 -14.519782          779            2.986377         3.007178\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 734759  3.791592 -14.521099          779            0.000197         3.007178\n",
+       " 734760  3.793293 -14.521116          779            0.000189         3.007178\n",
+       " 734761  3.794995 -14.521132          779            0.000181         3.007178\n",
+       " 734762  3.796697 -14.521149          779            0.000174         3.007178\n",
+       " 734763  3.798398 -14.521165          779            0.000166         3.007178\n",
+       " \n",
+       " [646 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 735118  2.700801 -14.519799          780            2.992272         3.000863\n",
+       " 735119  2.702502 -14.520256          780            2.989576         3.000863\n",
+       " 735120  2.704204 -14.520256          780            2.986915         3.000863\n",
+       " 735121  2.705906 -14.520256          780            2.984254         3.000863\n",
+       " 735122  2.707608 -14.520256          780            2.981593         3.000863\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 735768  3.806907 -14.526489          780            0.000158         3.000863\n",
+       " 735769  3.808609 -14.526571          780            0.000151         3.000863\n",
+       " 735770  3.810310 -14.526653          780            0.000144         3.000863\n",
+       " 735771  3.812012 -14.526735          780            0.000136         3.000863\n",
+       " 735772  3.813714 -14.526817          780            0.000129         3.000863\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 736118  2.700801 -14.520016          781            2.984564         2.993072\n",
+       " 736119  2.702502 -14.519942          781            2.981839         2.993072\n",
+       " 736120  2.704204 -14.519868          781            2.979114         2.993072\n",
+       " 736121  2.705906 -14.519803          781            2.976393         2.993072\n",
+       " 736122  2.707608 -14.519876          781            2.973733         2.993072\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 736768  3.806907 -14.525664          781            0.000157         2.993072\n",
+       " 736769  3.808609 -14.525730          781            0.000149         2.993072\n",
+       " 736770  3.810310 -14.525796          781            0.000142         2.993072\n",
+       " 736771  3.812012 -14.525863          781            0.000135         2.993072\n",
+       " 736772  3.813714 -14.525928          781            0.000128         2.993072\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 737118  2.700801 -14.520256          782            2.979117         2.987271\n",
+       " 737119  2.702502 -14.520256          782            2.976404         2.987271\n",
+       " 737120  2.704204 -14.520256          782            2.973692         2.987271\n",
+       " 737121  2.705906 -14.520144          782            2.971013         2.987271\n",
+       " 737122  2.707608 -14.519921          782            2.968366         2.987271\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 737768  3.806907 -14.525232          782            0.000155         2.987271\n",
+       " 737769  3.808609 -14.525296          782            0.000148         2.987271\n",
+       " 737770  3.810310 -14.525360          782            0.000141         2.987271\n",
+       " 737771  3.812012 -14.525423          782            0.000133         2.987271\n",
+       " 737772  3.813714 -14.525487          782            0.000126         2.987271\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 738118  2.700801 -14.520019          783            2.971165         2.980576\n",
+       " 738119  2.702502 -14.519578          783            2.968527         2.980576\n",
+       " 738120  2.704204 -14.519652          783            2.965893         2.980576\n",
+       " 738121  2.705906 -14.519727          783            2.963259         2.980576\n",
+       " 738122  2.707608 -14.519800          783            2.960621         2.980576\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 738768  3.806907 -14.526121          783            0.000152         2.980576\n",
+       " 738769  3.808609 -14.526197          783            0.000145         2.980576\n",
+       " 738770  3.810310 -14.526274          783            0.000138         2.980576\n",
+       " 738771  3.812012 -14.526350          783            0.000131         2.980576\n",
+       " 738772  3.813714 -14.526426          783            0.000123         2.980576\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 739118  2.700801 -14.520098          784            2.966207         2.973525\n",
+       " 739119  2.702502 -14.519807          784            2.963719         2.973525\n",
+       " 739120  2.704204 -14.519881          784            2.961020         2.973525\n",
+       " 739121  2.705906 -14.519956          784            2.958322         2.973525\n",
+       " 739122  2.707608 -14.520025          784            2.955624         2.973525\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 739767  3.805205 -14.525220          784            0.000158         2.973525\n",
+       " 739768  3.806907 -14.525280          784            0.000151         2.973525\n",
+       " 739769  3.808609 -14.525341          784            0.000144         2.973525\n",
+       " 739770  3.810310 -14.525402          784            0.000136         2.973525\n",
+       " 739771  3.812012 -14.525463          784            0.000129         2.973525\n",
+       " \n",
+       " [654 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 740118  2.700801 -14.519859          785            2.962648         2.968859\n",
+       " 740119  2.702502 -14.519938          785            2.959972         2.968859\n",
+       " 740120  2.704204 -14.520088          785            2.957233         2.968859\n",
+       " 740121  2.705906 -14.520238          785            2.954495         2.968859\n",
+       " 740122  2.707608 -14.520058          785            2.951826         2.968859\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 740757  3.788188 -14.519354          785            0.000200         2.968859\n",
+       " 740758  3.789890 -14.519351          785            0.000193         2.968859\n",
+       " 740759  3.791592 -14.519348          785            0.000185         2.968859\n",
+       " 740760  3.793293 -14.519345          785            0.000177         2.968859\n",
+       " 740761  3.794995 -14.519343          785            0.000170         2.968859\n",
+       " \n",
+       " [644 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 741118  2.700801 -14.520238          786            2.960052         2.965289\n",
+       " 741119  2.702502 -14.520162          786            2.957380         2.965289\n",
+       " 741120  2.704204 -14.520085          786            2.954708         2.965289\n",
+       " 741121  2.705906 -14.520027          786            2.952048         2.965289\n",
+       " 741122  2.707608 -14.520027          786            2.949428         2.965289\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 741768  3.806907 -14.525941          786            0.000151         2.965289\n",
+       " 741769  3.808609 -14.526008          786            0.000144         2.965289\n",
+       " 741770  3.810310 -14.526073          786            0.000137         2.965289\n",
+       " 741771  3.812012 -14.526139          786            0.000130         2.965289\n",
+       " 741772  3.813714 -14.526205          786            0.000123         2.965289\n",
+       " \n",
+       " [655 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 742118  2.700801 -14.519987          787            2.956971         2.963608\n",
+       " 742119  2.702502 -14.519902          787            2.954512         2.963608\n",
+       " 742120  2.704204 -14.519817          787            2.952053         2.963608\n",
+       " 742121  2.705906 -14.519798          787            2.949397         2.963608\n",
+       " 742122  2.707608 -14.519798          787            2.946685         2.963608\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 742757  3.788188 -14.519161          787            0.000198         2.963608\n",
+       " 742758  3.789890 -14.519151          787            0.000190         2.963608\n",
+       " 742759  3.791592 -14.519139          787            0.000183         2.963608\n",
+       " 742760  3.793293 -14.519129          787            0.000175         2.963608\n",
+       " 742761  3.794995 -14.519118          787            0.000167         2.963608\n",
+       " \n",
+       " [644 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 743118  2.700801 -14.519798          788            2.957673         2.958399\n",
+       " 743119  2.702502 -14.519798          788            2.955095         2.958399\n",
+       " 743120  2.704204 -14.519798          788            2.952517         2.958399\n",
+       " 743121  2.705906 -14.519812          788            2.949941         2.958399\n",
+       " 743122  2.707608 -14.520037          788            2.947387         2.958399\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 743767  3.805205 -14.526075          788            0.000156         2.958399\n",
+       " 743768  3.806907 -14.526152          788            0.000149         2.958399\n",
+       " 743769  3.808609 -14.526229          788            0.000142         2.958399\n",
+       " 743770  3.810310 -14.526305          788            0.000135         2.958399\n",
+       " 743771  3.812012 -14.526381          788            0.000128         2.958399\n",
+       " \n",
+       " [654 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 744118  2.700801 -14.520027          789            2.949597         2.961593\n",
+       " 744119  2.702502 -14.520027          789            2.947052         2.961593\n",
+       " 744120  2.704204 -14.520027          789            2.944515         2.961593\n",
+       " 744121  2.705906 -14.520027          789            2.941984         2.961593\n",
+       " 744122  2.707608 -14.520027          789            2.939452         2.961593\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 744757  3.788188 -14.519582          789            0.000197         2.961593\n",
+       " 744758  3.789890 -14.519579          789            0.000190         2.961593\n",
+       " 744759  3.791592 -14.519576          789            0.000182         2.961593\n",
+       " 744760  3.793293 -14.519573          789            0.000174         2.961593\n",
+       " 744761  3.794995 -14.519570          789            0.000167         2.961593\n",
+       " \n",
+       " [644 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 745118  2.700801 -14.520145          790            2.945965         2.952427\n",
+       " 745119  2.702502 -14.519908          790            2.943517         2.952427\n",
+       " 745120  2.704204 -14.519798          790            2.941000         2.952427\n",
+       " 745121  2.705906 -14.519798          790            2.938421         2.952427\n",
+       " 745122  2.707608 -14.519798          790            2.935843         2.952427\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 745757  3.788188 -14.519378          790            0.000198         2.952427\n",
+       " 745758  3.789890 -14.519369          790            0.000190         2.952427\n",
+       " 745759  3.791592 -14.519361          790            0.000182         2.952427\n",
+       " 745760  3.793293 -14.519353          790            0.000175         2.952427\n",
+       " 745761  3.794995 -14.519345          790            0.000167         2.952427\n",
+       " \n",
+       " [644 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 746118  2.700801 -14.520135          791            2.944589         2.949763\n",
+       " 746119  2.702502 -14.520116          791            2.942159         2.949763\n",
+       " 746120  2.704204 -14.519824          791            2.939666         2.949763\n",
+       " 746121  2.705906 -14.519532          791            2.937172         2.949763\n",
+       " 746122  2.707608 -14.519393          791            2.934628         2.949763\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 746767  3.805205 -14.526144          791            0.000153         2.949763\n",
+       " 746768  3.806907 -14.526213          791            0.000146         2.949763\n",
+       " 746769  3.808609 -14.526280          791            0.000139         2.949763\n",
+       " 746770  3.810310 -14.526349          791            0.000132         2.949763\n",
+       " 746771  3.812012 -14.526418          791            0.000124         2.949763\n",
+       " \n",
+       " [654 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 747118  2.700801 -14.519584          792            2.939927         2.947204\n",
+       " 747119  2.702502 -14.519657          792            2.937472         2.947204\n",
+       " 747120  2.704204 -14.519730          792            2.935018         2.947204\n",
+       " 747121  2.705906 -14.519790          792            2.932562         2.947204\n",
+       " 747122  2.707608 -14.519644          792            2.930095         2.947204\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 747767  3.805205 -14.525918          792            0.000152         2.947204\n",
+       " 747768  3.806907 -14.525989          792            0.000144         2.947204\n",
+       " 747769  3.808609 -14.526059          792            0.000137         2.947204\n",
+       " 747770  3.810310 -14.526130          792            0.000130         2.947204\n",
+       " 747771  3.812012 -14.526200          792            0.000123         2.947204\n",
+       " \n",
+       " [654 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 748118  2.700801 -14.519816          793            2.939042         2.944163\n",
+       " 748119  2.702502 -14.519890          793            2.936552         2.944163\n",
+       " 748120  2.704204 -14.519964          793            2.934062         2.944163\n",
+       " 748121  2.705906 -14.520039          793            2.931580         2.944163\n",
+       " 748122  2.707608 -14.520113          793            2.929145         2.944163\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 748767  3.805205 -14.524399          793            0.000152         2.944163\n",
+       " 748768  3.806907 -14.524449          793            0.000144         2.944163\n",
+       " 748769  3.808609 -14.524500          793            0.000137         2.944163\n",
+       " 748770  3.810310 -14.524549          793            0.000130         2.944163\n",
+       " 748771  3.812012 -14.524600          793            0.000123         2.944163\n",
+       " \n",
+       " [654 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 749118  2.700801 -14.519606          794            2.937544         2.941097\n",
+       " 749119  2.702502 -14.519756          794            2.935030         2.941097\n",
+       " 749120  2.704204 -14.519906          794            2.932517         2.941097\n",
+       " 749121  2.705906 -14.520027          794            2.930024         2.941097\n",
+       " 749122  2.707608 -14.520027          794            2.927616         2.941097\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 749766  3.803504 -14.526514          794            0.000158         2.941097\n",
+       " 749767  3.805205 -14.526590          794            0.000151         2.941097\n",
+       " 749768  3.806907 -14.526666          794            0.000144         2.941097\n",
+       " 749769  3.808609 -14.526742          794            0.000137         2.941097\n",
+       " 749770  3.810310 -14.526818          794            0.000130         2.941097\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 750118  2.700801 -14.519834          795            2.933100         2.940401\n",
+       " 750119  2.702502 -14.520027          795            2.930743         2.940401\n",
+       " 750120  2.704204 -14.520027          795            2.928253         2.940401\n",
+       " 750121  2.705906 -14.520027          795            2.925763         2.940401\n",
+       " 750122  2.707608 -14.519985          795            2.923273         2.940401\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 750767  3.805205 -14.525272          795            0.000152         2.940401\n",
+       " 750768  3.806907 -14.525332          795            0.000145         2.940401\n",
+       " 750769  3.808609 -14.525393          795            0.000137         2.940401\n",
+       " 750770  3.810310 -14.525455          795            0.000130         2.940401\n",
+       " 750771  3.812012 -14.525515          795            0.000123         2.940401\n",
+       " \n",
+       " [654 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 751118  2.700801 -14.519872          796            2.932008         2.936484\n",
+       " 751119  2.702502 -14.519539          796            2.929641         2.936484\n",
+       " 751120  2.704204 -14.519402          796            2.927221         2.936484\n",
+       " 751121  2.705906 -14.519551          796            2.924720         2.936484\n",
+       " 751122  2.707608 -14.519701          796            2.922220         2.936484\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 751766  3.803504 -14.525856          796            0.000158         2.936484\n",
+       " 751767  3.805205 -14.525928          796            0.000151         2.936484\n",
+       " 751768  3.806907 -14.525998          796            0.000144         2.936484\n",
+       " 751769  3.808609 -14.526069          796            0.000136         2.936484\n",
+       " 751770  3.810310 -14.526139          796            0.000129         2.936484\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 752118  2.700801 -14.519989          797            2.930803         2.934072\n",
+       " 752119  2.702502 -14.519908          797            2.928361         2.934072\n",
+       " 752120  2.704204 -14.519827          797            2.925919         2.934072\n",
+       " 752121  2.705906 -14.519846          797            2.923480         2.934072\n",
+       " 752122  2.707608 -14.519919          797            2.921041         2.934072\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 752766  3.803504 -14.524772          797            0.000158         2.934072\n",
+       " 752767  3.805205 -14.524830          797            0.000151         2.934072\n",
+       " 752768  3.806907 -14.524888          797            0.000144         2.934072\n",
+       " 752769  3.808609 -14.524946          797            0.000137         2.934072\n",
+       " 752770  3.810310 -14.525004          797            0.000130         2.934072\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 753118  2.700801 -14.520096          798            2.927722         2.933915\n",
+       " 753119  2.702502 -14.520456          798            2.925286         2.933915\n",
+       " 753120  2.704204 -14.520384          798            2.922908         2.933915\n",
+       " 753121  2.705906 -14.520310          798            2.920531         2.933915\n",
+       " 753122  2.707608 -14.520237          798            2.918126         2.933915\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 753766  3.803504 -14.525857          798            0.000156         2.933915\n",
+       " 753767  3.805205 -14.525930          798            0.000149         2.933915\n",
+       " 753768  3.806907 -14.526004          798            0.000142         2.933915\n",
+       " 753769  3.808609 -14.526077          798            0.000135         2.933915\n",
+       " 753770  3.810310 -14.526151          798            0.000128         2.933915\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 754118  2.700801 -14.520027          799            2.926391         2.930438\n",
+       " 754119  2.702502 -14.520027          799            2.924003         2.930438\n",
+       " 754120  2.704204 -14.520027          799            2.921615         2.930438\n",
+       " 754121  2.705906 -14.520027          799            2.919216         2.930438\n",
+       " 754122  2.707608 -14.520027          799            2.916817         2.930438\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 754767  3.805205 -14.526133          799            0.000152         2.930438\n",
+       " 754768  3.806907 -14.526206          799            0.000145         2.930438\n",
+       " 754769  3.808609 -14.526279          799            0.000138         2.930438\n",
+       " 754770  3.810310 -14.526353          799            0.000131         2.930438\n",
+       " 754771  3.812012 -14.526426          799            0.000123         2.930438\n",
+       " \n",
+       " [654 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 755118  2.700801 -14.520268          800            2.923524         2.930117\n",
+       " 755119  2.702502 -14.520256          800            2.921073         2.930117\n",
+       " 755120  2.704204 -14.520256          800            2.918609         2.930117\n",
+       " 755121  2.705906 -14.520256          800            2.916145         2.930117\n",
+       " 755122  2.707608 -14.520063          800            2.913746         2.930117\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 755756  3.786486 -14.520892          800            0.000198         2.930117\n",
+       " 755757  3.788188 -14.520903          800            0.000191         2.930117\n",
+       " 755758  3.789890 -14.520914          800            0.000183         2.930117\n",
+       " 755759  3.791592 -14.520925          800            0.000176         2.930117\n",
+       " 755760  3.793293 -14.520935          800            0.000168         2.930117\n",
+       " \n",
+       " [643 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 756118  2.700801 -14.519786          801            2.924641         2.925982\n",
+       " 756119  2.702502 -14.519954          801            2.922298         2.925982\n",
+       " 756120  2.704204 -14.519802          801            2.919855         2.925982\n",
+       " 756121  2.705906 -14.519650          801            2.917411         2.925982\n",
+       " 756122  2.707608 -14.519676          801            2.915003         2.925982\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 756766  3.803504 -14.525683          801            0.000154         2.925982\n",
+       " 756767  3.805205 -14.525748          801            0.000147         2.925982\n",
+       " 756768  3.806907 -14.525814          801            0.000140         2.925982\n",
+       " 756769  3.808609 -14.525880          801            0.000133         2.925982\n",
+       " 756770  3.810310 -14.525945          801            0.000126         2.925982\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 757118  2.700801 -14.520349          802            2.923821          2.93025\n",
+       " 757119  2.702502 -14.520058          802            2.921456          2.93025\n",
+       " 757120  2.704204 -14.520027          802            2.919131          2.93025\n",
+       " 757121  2.705906 -14.520027          802            2.916810          2.93025\n",
+       " 757122  2.707608 -14.520027          802            2.914489          2.93025\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 757766  3.803504 -14.526757          802            0.000157          2.93025\n",
+       " 757767  3.805205 -14.526833          802            0.000150          2.93025\n",
+       " 757768  3.806907 -14.526909          802            0.000143          2.93025\n",
+       " 757769  3.808609 -14.526984          802            0.000135          2.93025\n",
+       " 757770  3.810310 -14.527061          802            0.000128          2.93025\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 758118  2.700801 -14.519735          803            2.922683         2.927443\n",
+       " 758119  2.702502 -14.519601          803            2.920386         2.927443\n",
+       " 758120  2.704204 -14.519569          803            2.918051         2.927443\n",
+       " 758121  2.705906 -14.519569          803            2.915705         2.927443\n",
+       " 758122  2.707608 -14.519569          803            2.913358         2.927443\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 758766  3.803504 -14.526524          803            0.000156         2.927443\n",
+       " 758767  3.805205 -14.526602          803            0.000149         2.927443\n",
+       " 758768  3.806907 -14.526680          803            0.000142         2.927443\n",
+       " 758769  3.808609 -14.526758          803            0.000135         2.927443\n",
+       " 758770  3.810310 -14.526836          803            0.000128         2.927443\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 759118  2.700801 -14.519803          804            2.920094         2.924507\n",
+       " 759119  2.702502 -14.519876          804            2.917695         2.924507\n",
+       " 759120  2.704204 -14.519951          804            2.915296         2.924507\n",
+       " 759121  2.705906 -14.520025          804            2.912897         2.924507\n",
+       " 759122  2.707608 -14.520027          804            2.910511         2.924507\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 759766  3.803504 -14.525017          804            0.000155         2.924507\n",
+       " 759767  3.805205 -14.525077          804            0.000148         2.924507\n",
+       " 759768  3.806907 -14.525137          804            0.000141         2.924507\n",
+       " 759769  3.808609 -14.525198          804            0.000133         2.924507\n",
+       " 759770  3.810310 -14.525258          804            0.000126         2.924507\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 760118  2.700801 -14.519823          805            2.918050         2.923486\n",
+       " 760119  2.702502 -14.519897          805            2.915690         2.923486\n",
+       " 760120  2.704204 -14.519971          805            2.913330         2.923486\n",
+       " 760121  2.705906 -14.519992          805            2.910956         2.923486\n",
+       " 760122  2.707608 -14.519841          805            2.908535         2.923486\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 760766  3.803504 -14.524570          805            0.000154         2.923486\n",
+       " 760767  3.805205 -14.524630          805            0.000146         2.923486\n",
+       " 760768  3.806907 -14.524691          805            0.000139         2.923486\n",
+       " 760769  3.808609 -14.524751          805            0.000132         2.923486\n",
+       " 760770  3.810310 -14.524811          805            0.000125         2.923486\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 761118  2.700801 -14.520020          806            2.913970         2.918799\n",
+       " 761119  2.702502 -14.520494          806            2.911585         2.918799\n",
+       " 761120  2.704204 -14.520563          806            2.909250         2.918799\n",
+       " 761121  2.705906 -14.520284          806            2.906958         2.918799\n",
+       " 761122  2.707608 -14.520003          806            2.904665         2.918799\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 761756  3.786486 -14.520907          806            0.000196         2.918799\n",
+       " 761757  3.788188 -14.520916          806            0.000188         2.918799\n",
+       " 761758  3.789890 -14.520924          806            0.000181         2.918799\n",
+       " 761759  3.791592 -14.520932          806            0.000173         2.918799\n",
+       " 761760  3.793293 -14.520940          806            0.000165         2.918799\n",
+       " \n",
+       " [643 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 762118  2.700801 -14.519917          807            2.914340         2.917962\n",
+       " 762119  2.702502 -14.519682          807            2.912056         2.917962\n",
+       " 762120  2.704204 -14.519446          807            2.909772         2.917962\n",
+       " 762121  2.705906 -14.519463          807            2.907461         2.917962\n",
+       " 762122  2.707608 -14.519685          807            2.905127         2.917962\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 762766  3.803504 -14.526352          807            0.000152         2.917962\n",
+       " 762767  3.805205 -14.526427          807            0.000145         2.917962\n",
+       " 762768  3.806907 -14.526503          807            0.000138         2.917962\n",
+       " 762769  3.808609 -14.526578          807            0.000131         2.917962\n",
+       " 762770  3.810310 -14.526653          807            0.000124         2.917962\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 763118  2.700801 -14.520256          808            2.916378         2.920144\n",
+       " 763119  2.702502 -14.520256          808            2.914071         2.920144\n",
+       " 763120  2.704204 -14.520256          808            2.911763         2.920144\n",
+       " 763121  2.705906 -14.520223          808            2.909448         2.920144\n",
+       " 763122  2.707608 -14.519998          808            2.907094         2.920144\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 763766  3.803504 -14.526721          808            0.000156         2.920144\n",
+       " 763767  3.805205 -14.526807          808            0.000149         2.920144\n",
+       " 763768  3.806907 -14.526893          808            0.000142         2.920144\n",
+       " 763769  3.808609 -14.526978          808            0.000134         2.920144\n",
+       " 763770  3.810310 -14.527063          808            0.000127         2.920144\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 764118  2.700801 -14.520374          809            2.911992         2.917332\n",
+       " 764119  2.702502 -14.520137          809            2.909691         2.917332\n",
+       " 764120  2.704204 -14.520067          809            2.907411         2.917332\n",
+       " 764121  2.705906 -14.520143          809            2.905148         2.917332\n",
+       " 764122  2.707608 -14.520218          809            2.902886         2.917332\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 764766  3.803504 -14.526993          809            0.000152         2.917332\n",
+       " 764767  3.805205 -14.527079          809            0.000145         2.917332\n",
+       " 764768  3.806907 -14.527164          809            0.000138         2.917332\n",
+       " 764769  3.808609 -14.527249          809            0.000131         2.917332\n",
+       " 764770  3.810310 -14.527335          809            0.000124         2.917332\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 765118  2.700801 -14.519923          810            2.909817         2.914839\n",
+       " 765119  2.702502 -14.520192          810            2.907520         2.914839\n",
+       " 765120  2.704204 -14.520256          810            2.905149         2.914839\n",
+       " 765121  2.705906 -14.520256          810            2.902754         2.914839\n",
+       " 765122  2.707608 -14.520256          810            2.900360         2.914839\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 765766  3.803504 -14.526380          810            0.000151         2.914839\n",
+       " 765767  3.805205 -14.526450          810            0.000144         2.914839\n",
+       " 765768  3.806907 -14.526520          810            0.000137         2.914839\n",
+       " 765769  3.808609 -14.526590          810            0.000130         2.914839\n",
+       " 765770  3.810310 -14.526661          810            0.000123         2.914839\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 766118  2.700801 -14.519844          811            2.909831         2.913394\n",
+       " 766119  2.702502 -14.519942          811            2.907564         2.913394\n",
+       " 766120  2.704204 -14.520027          811            2.905288         2.913394\n",
+       " 766121  2.705906 -14.520027          811            2.902946         2.913394\n",
+       " 766122  2.707608 -14.520027          811            2.900604         2.913394\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 766766  3.803504 -14.525273          811            0.000152         2.913394\n",
+       " 766767  3.805205 -14.525333          811            0.000144         2.913394\n",
+       " 766768  3.806907 -14.525393          811            0.000137         2.913394\n",
+       " 766769  3.808609 -14.525454          811            0.000130         2.913394\n",
+       " 766770  3.810310 -14.525515          811            0.000123         2.913394\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 767118  2.700801 -14.519975          812            2.906719         2.912814\n",
+       " 767119  2.702502 -14.520315          812            2.904359         2.912814\n",
+       " 767120  2.704204 -14.520391          812            2.901977         2.912814\n",
+       " 767121  2.705906 -14.520466          812            2.899596         2.912814\n",
+       " 767122  2.707608 -14.520374          812            2.897289         2.912814\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 767765  3.801802 -14.526971          812            0.000157         2.912814\n",
+       " 767766  3.803504 -14.527049          812            0.000150         2.912814\n",
+       " 767767  3.805205 -14.527127          812            0.000143         2.912814\n",
+       " 767768  3.806907 -14.527205          812            0.000136         2.912814\n",
+       " 767769  3.808609 -14.527283          812            0.000129         2.912814\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 768118  2.700801 -14.520027          813            2.906064         2.909693\n",
+       " 768119  2.702502 -14.520027          813            2.903852         2.909693\n",
+       " 768120  2.704204 -14.520027          813            2.901583         2.909693\n",
+       " 768121  2.705906 -14.520027          813            2.899302         2.909693\n",
+       " 768122  2.707608 -14.520027          813            2.897020         2.909693\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 768765  3.801802 -14.525654          813            0.000158         2.909693\n",
+       " 768766  3.803504 -14.525720          813            0.000151         2.909693\n",
+       " 768767  3.805205 -14.525784          813            0.000143         2.909693\n",
+       " 768768  3.806907 -14.525849          813            0.000136         2.909693\n",
+       " 768769  3.808609 -14.525915          813            0.000129         2.909693\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 769118  2.700801 -14.519902          814            2.905534         2.910155\n",
+       " 769119  2.702502 -14.519844          814            2.903274         2.910155\n",
+       " 769120  2.704204 -14.519917          814            2.900992         2.910155\n",
+       " 769121  2.705906 -14.519992          814            2.898711         2.910155\n",
+       " 769122  2.707608 -14.519949          814            2.896446         2.910155\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 769766  3.803504 -14.524837          814            0.000152         2.910155\n",
+       " 769767  3.805205 -14.524891          814            0.000144         2.910155\n",
+       " 769768  3.806907 -14.524946          814            0.000137         2.910155\n",
+       " 769769  3.808609 -14.525002          814            0.000130         2.910155\n",
+       " 769770  3.810310 -14.525057          814            0.000123         2.910155\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 770118  2.700801 -14.520240          815            2.905760         2.909723\n",
+       " 770119  2.702502 -14.520092          815            2.903466         2.909723\n",
+       " 770120  2.704204 -14.519944          815            2.901171         2.909723\n",
+       " 770121  2.705906 -14.519798          815            2.898877         2.909723\n",
+       " 770122  2.707608 -14.519798          815            2.896634         2.909723\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 770765  3.801802 -14.524596          815            0.000158         2.909723\n",
+       " 770766  3.803504 -14.524644          815            0.000151         2.909723\n",
+       " 770767  3.805205 -14.524692          815            0.000144         2.909723\n",
+       " 770768  3.806907 -14.524740          815            0.000136         2.909723\n",
+       " 770769  3.808609 -14.524788          815            0.000129         2.909723\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 771118  2.700801 -14.519755          816            2.905557          2.90918\n",
+       " 771119  2.702502 -14.519662          816            2.903382          2.90918\n",
+       " 771120  2.704204 -14.519569          816            2.901206          2.90918\n",
+       " 771121  2.705906 -14.519722          816            2.898789          2.90918\n",
+       " 771122  2.707608 -14.519875          816            2.896373          2.90918\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 771766  3.803504 -14.526135          816            0.000153          2.90918\n",
+       " 771767  3.805205 -14.526205          816            0.000146          2.90918\n",
+       " 771768  3.806907 -14.526276          816            0.000139          2.90918\n",
+       " 771769  3.808609 -14.526346          816            0.000132          2.90918\n",
+       " 771770  3.810310 -14.526416          816            0.000124          2.90918\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 772118  2.700801 -14.520027          817            2.904247         2.908876\n",
+       " 772119  2.702502 -14.520027          817            2.902075         2.908876\n",
+       " 772120  2.704204 -14.520027          817            2.899766         2.908876\n",
+       " 772121  2.705906 -14.520027          817            2.897456         2.908876\n",
+       " 772122  2.707608 -14.520061          817            2.895176         2.908876\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 772766  3.803504 -14.525054          817            0.000153         2.908876\n",
+       " 772767  3.805205 -14.525109          817            0.000146         2.908876\n",
+       " 772768  3.806907 -14.525166          817            0.000139         2.908876\n",
+       " 772769  3.808609 -14.525221          817            0.000132         2.908876\n",
+       " 772770  3.810310 -14.525276          817            0.000124         2.908876\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 773118  2.700801 -14.520287          818            2.903731         2.906892\n",
+       " 773119  2.702502 -14.520085          818            2.901469         2.906892\n",
+       " 773120  2.704204 -14.520236          818            2.899247         2.906892\n",
+       " 773121  2.705906 -14.520386          818            2.897024         2.906892\n",
+       " 773122  2.707608 -14.520383          818            2.894770         2.906892\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 773766  3.803504 -14.526591          818            0.000151         2.906892\n",
+       " 773767  3.805205 -14.526667          818            0.000144         2.906892\n",
+       " 773768  3.806907 -14.526742          818            0.000137         2.906892\n",
+       " 773769  3.808609 -14.526817          818            0.000130         2.906892\n",
+       " 773770  3.810310 -14.526893          818            0.000123         2.906892\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 774118  2.700801 -14.520244          819            2.901103         2.907441\n",
+       " 774119  2.702502 -14.520041          819            2.898851         2.907441\n",
+       " 774120  2.704204 -14.519818          819            2.896595         2.907441\n",
+       " 774121  2.705906 -14.519596          819            2.894340         2.907441\n",
+       " 774122  2.707608 -14.519768          819            2.892102         2.907441\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 774756  3.786486 -14.519809          819            0.000194         2.907441\n",
+       " 774757  3.788188 -14.519807          819            0.000186         2.907441\n",
+       " 774758  3.789890 -14.519804          819            0.000178         2.907441\n",
+       " 774759  3.791592 -14.519801          819            0.000171         2.907441\n",
+       " 774760  3.793293 -14.519798          819            0.000163         2.907441\n",
+       " \n",
+       " [643 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 775118  2.700801 -14.519521          820            2.899874         2.903516\n",
+       " 775119  2.702502 -14.519417          820            2.897708         2.903516\n",
+       " 775120  2.704204 -14.519361          820            2.895513         2.903516\n",
+       " 775121  2.705906 -14.519433          820            2.893238         2.903516\n",
+       " 775122  2.707608 -14.519506          820            2.890963         2.903516\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 775766  3.803504 -14.525714          820            0.000151         2.903516\n",
+       " 775767  3.805205 -14.525779          820            0.000144         2.903516\n",
+       " 775768  3.806907 -14.525845          820            0.000137         2.903516\n",
+       " 775769  3.808609 -14.525909          820            0.000130         2.903516\n",
+       " 775770  3.810310 -14.525974          820            0.000123         2.903516\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 776118  2.700801 -14.520204          821            2.900776         2.905131\n",
+       " 776119  2.702502 -14.519988          821            2.898495         2.905131\n",
+       " 776120  2.704204 -14.519773          821            2.896215         2.905131\n",
+       " 776121  2.705906 -14.519578          821            2.893940         2.905131\n",
+       " 776122  2.707608 -14.519724          821            2.891768         2.905131\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 776766  3.803504 -14.526135          821            0.000154         2.905131\n",
+       " 776767  3.805205 -14.526204          821            0.000147         2.905131\n",
+       " 776768  3.806907 -14.526272          821            0.000140         2.905131\n",
+       " 776769  3.808609 -14.526340          821            0.000133         2.905131\n",
+       " 776770  3.810310 -14.526407          821            0.000125         2.905131\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 777118  2.700801 -14.520027          822            2.896590         2.902388\n",
+       " 777119  2.702502 -14.520027          822            2.894348         2.902388\n",
+       " 777120  2.704204 -14.520027          822            2.892105         2.902388\n",
+       " 777121  2.705906 -14.520027          822            2.889866         2.902388\n",
+       " 777122  2.707608 -14.520027          822            2.887675         2.902388\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 777765  3.801802 -14.526082          822            0.000157         2.902388\n",
+       " 777766  3.803504 -14.526155          822            0.000150         2.902388\n",
+       " 777767  3.805205 -14.526227          822            0.000143         2.902388\n",
+       " 777768  3.806907 -14.526299          822            0.000136         2.902388\n",
+       " 777769  3.808609 -14.526372          822            0.000129         2.902388\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 778118  2.700801 -14.519610          823            2.896136         2.899854\n",
+       " 778119  2.702502 -14.519698          823            2.893995         2.899854\n",
+       " 778120  2.704204 -14.519787          823            2.891855         2.899854\n",
+       " 778121  2.705906 -14.519798          823            2.889631         2.899854\n",
+       " 778122  2.707608 -14.519798          823            2.887395         2.899854\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 778765  3.801802 -14.526759          823            0.000157         2.899854\n",
+       " 778766  3.803504 -14.526834          823            0.000150         2.899854\n",
+       " 778767  3.805205 -14.526909          823            0.000143         2.899854\n",
+       " 778768  3.806907 -14.526984          823            0.000135         2.899854\n",
+       " 778769  3.808609 -14.527060          823            0.000128         2.899854\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 779118  2.700801 -14.520027          824            2.897470         2.900541\n",
+       " 779119  2.702502 -14.520027          824            2.895251         2.900541\n",
+       " 779120  2.704204 -14.519961          824            2.893036         2.900541\n",
+       " 779121  2.705906 -14.519815          824            2.890826         2.900541\n",
+       " 779122  2.707608 -14.519670          824            2.888615         2.900541\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 779766  3.803504 -14.525922          824            0.000151         2.900541\n",
+       " 779767  3.805205 -14.525992          824            0.000144         2.900541\n",
+       " 779768  3.806907 -14.526062          824            0.000137         2.900541\n",
+       " 779769  3.808609 -14.526133          824            0.000130         2.900541\n",
+       " 779770  3.810310 -14.526203          824            0.000123         2.900541\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 780118  2.700801 -14.519841          825            2.896795         2.900321\n",
+       " 780119  2.702502 -14.519935          825            2.894685         2.900321\n",
+       " 780120  2.704204 -14.520027          825            2.892575         2.900321\n",
+       " 780121  2.705906 -14.520027          825            2.890286         2.900321\n",
+       " 780122  2.707608 -14.520027          825            2.887998         2.900321\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 780756  3.786486 -14.521323          825            0.000194         2.900321\n",
+       " 780757  3.788188 -14.521342          825            0.000186         2.900321\n",
+       " 780758  3.789890 -14.521360          825            0.000179         2.900321\n",
+       " 780759  3.791592 -14.521379          825            0.000171         2.900321\n",
+       " 780760  3.793293 -14.521399          825            0.000164         2.900321\n",
+       " \n",
+       " [643 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 781118  2.700801 -14.519569          826            2.893858         2.899002\n",
+       " 781119  2.702502 -14.519569          826            2.891764         2.899002\n",
+       " 781120  2.704204 -14.519569          826            2.889670         2.899002\n",
+       " 781121  2.705906 -14.519634          826            2.887465         2.899002\n",
+       " 781122  2.707608 -14.519710          826            2.885243         2.899002\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 781755  3.784785 -14.519367          826            0.000201         2.899002\n",
+       " 781756  3.786486 -14.519361          826            0.000193         2.899002\n",
+       " 781757  3.788188 -14.519357          826            0.000185         2.899002\n",
+       " 781758  3.789890 -14.519351          826            0.000178         2.899002\n",
+       " 781759  3.791592 -14.519345          826            0.000170         2.899002\n",
+       " \n",
+       " [642 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 782118  2.700801 -14.519867          827            2.893710         2.897633\n",
+       " 782119  2.702502 -14.520015          827            2.891559         2.897633\n",
+       " 782120  2.704204 -14.520164          827            2.889408         2.897633\n",
+       " 782121  2.705906 -14.520256          827            2.887252         2.897633\n",
+       " 782122  2.707608 -14.520256          827            2.885087         2.897633\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 782766  3.803504 -14.525685          827            0.000153         2.897633\n",
+       " 782767  3.805205 -14.525753          827            0.000146         2.897633\n",
+       " 782768  3.806907 -14.525821          827            0.000139         2.897633\n",
+       " 782769  3.808609 -14.525888          827            0.000132         2.897633\n",
+       " 782770  3.810310 -14.525956          827            0.000125         2.897633\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 783118  2.700801 -14.519615          828            2.896077         2.897364\n",
+       " 783119  2.702502 -14.519713          828            2.893984         2.897364\n",
+       " 783120  2.704204 -14.519789          828            2.891875         2.897364\n",
+       " 783121  2.705906 -14.519714          828            2.889672         2.897364\n",
+       " 783122  2.707608 -14.519640          828            2.887469         2.897364\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 783766  3.803504 -14.525238          828            0.000153         2.897364\n",
+       " 783767  3.805205 -14.525303          828            0.000146         2.897364\n",
+       " 783768  3.806907 -14.525369          828            0.000139         2.897364\n",
+       " 783769  3.808609 -14.525434          828            0.000132         2.897364\n",
+       " 783770  3.810310 -14.525499          828            0.000125         2.897364\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 784118  2.700801 -14.520083          829            2.891428         2.898586\n",
+       " 784119  2.702502 -14.520458          829            2.889377         2.898586\n",
+       " 784120  2.704204 -14.520383          829            2.887121         2.898586\n",
+       " 784121  2.705906 -14.520307          829            2.884865         2.898586\n",
+       " 784122  2.707608 -14.520231          829            2.882634         2.898586\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 784765  3.801802 -14.525197          829            0.000158         2.898586\n",
+       " 784766  3.803504 -14.525262          829            0.000150         2.898586\n",
+       " 784767  3.805205 -14.525327          829            0.000143         2.898586\n",
+       " 784768  3.806907 -14.525393          829            0.000136         2.898586\n",
+       " 784769  3.808609 -14.525457          829            0.000129         2.898586\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 785118  2.700801 -14.520185          830            2.890192         2.894425\n",
+       " 785119  2.702502 -14.519847          830            2.888032         2.894425\n",
+       " 785120  2.704204 -14.519921          830            2.885790         2.894425\n",
+       " 785121  2.705906 -14.519995          830            2.883547         2.894425\n",
+       " 785122  2.707608 -14.520070          830            2.881331         2.894425\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 785765  3.801802 -14.524355          830            0.000156         2.894425\n",
+       " 785766  3.803504 -14.524408          830            0.000149         2.894425\n",
+       " 785767  3.805205 -14.524461          830            0.000142         2.894425\n",
+       " 785768  3.806907 -14.524513          830            0.000135         2.894425\n",
+       " 785769  3.808609 -14.524566          830            0.000128         2.894425\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 786118  2.700801 -14.519571          831            2.890589         2.894263\n",
+       " 786119  2.702502 -14.519459          831            2.888432         2.894263\n",
+       " 786120  2.704204 -14.519684          831            2.886223         2.894263\n",
+       " 786121  2.705906 -14.519909          831            2.884013         2.894263\n",
+       " 786122  2.707608 -14.519992          831            2.881838         2.894263\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 786765  3.801802 -14.525242          831            0.000155         2.894263\n",
+       " 786766  3.803504 -14.525303          831            0.000148         2.894263\n",
+       " 786767  3.805205 -14.525363          831            0.000141         2.894263\n",
+       " 786768  3.806907 -14.525423          831            0.000134         2.894263\n",
+       " 786769  3.808609 -14.525483          831            0.000127         2.894263\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 787118  2.700801 -14.519798          832            2.890888         2.894825\n",
+       " 787119  2.702502 -14.519798          832            2.888763         2.894825\n",
+       " 787120  2.704204 -14.519798          832            2.886638         2.894825\n",
+       " 787121  2.705906 -14.519840          832            2.884505         2.894825\n",
+       " 787122  2.707608 -14.519988          832            2.882354         2.894825\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 787766  3.803504 -14.525268          832            0.000153         2.894825\n",
+       " 787767  3.805205 -14.525326          832            0.000146         2.894825\n",
+       " 787768  3.806907 -14.525383          832            0.000139         2.894825\n",
+       " 787769  3.808609 -14.525441          832            0.000132         2.894825\n",
+       " 787770  3.810310 -14.525499          832            0.000125         2.894825\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 788118  2.700801 -14.519932          833            2.889492         2.894353\n",
+       " 788119  2.702502 -14.519849          833            2.887487         2.894353\n",
+       " 788120  2.704204 -14.519995          833            2.885367         2.894353\n",
+       " 788121  2.705906 -14.520141          833            2.883246         2.894353\n",
+       " 788122  2.707608 -14.520241          833            2.881123         2.894353\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 788765  3.801802 -14.524776          833            0.000158         2.894353\n",
+       " 788766  3.803504 -14.524834          833            0.000151         2.894353\n",
+       " 788767  3.805205 -14.524892          833            0.000143         2.894353\n",
+       " 788768  3.806907 -14.524949          833            0.000136         2.894353\n",
+       " 788769  3.808609 -14.525007          833            0.000129         2.894353\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 789118  2.700801 -14.519579          834            2.888286         2.893032\n",
+       " 789119  2.702502 -14.519725          834            2.886127         2.893032\n",
+       " 789120  2.704204 -14.519870          834            2.883968         2.893032\n",
+       " 789121  2.705906 -14.520016          834            2.881809         2.893032\n",
+       " 789122  2.707608 -14.519959          834            2.879686         2.893032\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 789766  3.803504 -14.526808          834            0.000151         2.893032\n",
+       " 789767  3.805205 -14.526886          834            0.000144         2.893032\n",
+       " 789768  3.806907 -14.526963          834            0.000137         2.893032\n",
+       " 789769  3.808609 -14.527040          834            0.000130         2.893032\n",
+       " 789770  3.810310 -14.527118          834            0.000123         2.893032\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 790118  2.700801 -14.520042          835            2.888234         2.891945\n",
+       " 790119  2.702502 -14.520188          835            2.886113         2.891945\n",
+       " 790120  2.704204 -14.520334          835            2.883993         2.891945\n",
+       " 790121  2.705906 -14.520480          835            2.881872         2.891945\n",
+       " 790122  2.707608 -14.520342          835            2.879697         2.891945\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 790766  3.803504 -14.525275          835            0.000151         2.891945\n",
+       " 790767  3.805205 -14.525334          835            0.000144         2.891945\n",
+       " 790768  3.806907 -14.525394          835            0.000137         2.891945\n",
+       " 790769  3.808609 -14.525455          835            0.000130         2.891945\n",
+       " 790770  3.810310 -14.525515          835            0.000123         2.891945\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 791118  2.700801 -14.520190          836            2.890002         2.891667\n",
+       " 791119  2.702502 -14.520048          836            2.888028         2.891667\n",
+       " 791120  2.704204 -14.519964          836            2.885914         2.891667\n",
+       " 791121  2.705906 -14.519890          836            2.883775         2.891667\n",
+       " 791122  2.707608 -14.519816          836            2.881637         2.891667\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 791766  3.803504 -14.526568          836            0.000152         2.891667\n",
+       " 791767  3.805205 -14.526646          836            0.000145         2.891667\n",
+       " 791768  3.806907 -14.526724          836            0.000138         2.891667\n",
+       " 791769  3.808609 -14.526801          836            0.000131         2.891667\n",
+       " 791770  3.810310 -14.526878          836            0.000124         2.891667\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 792118  2.700801 -14.520091          837            2.886789         2.892364\n",
+       " 792119  2.702502 -14.520229          837            2.884844         2.892364\n",
+       " 792120  2.704204 -14.520074          837            2.882738         2.892364\n",
+       " 792121  2.705906 -14.519849          837            2.880595         2.892364\n",
+       " 792122  2.707608 -14.519624          837            2.878452         2.892364\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 792766  3.803504 -14.524595          837            0.000153         2.892364\n",
+       " 792767  3.805205 -14.524651          837            0.000146         2.892364\n",
+       " 792768  3.806907 -14.524705          837            0.000139         2.892364\n",
+       " 792769  3.808609 -14.524760          837            0.000132         2.892364\n",
+       " 792770  3.810310 -14.524816          837            0.000125         2.892364\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 793118  2.700801 -14.520123          838            2.886123         2.890675\n",
+       " 793119  2.702502 -14.519840          838            2.884049         2.890675\n",
+       " 793120  2.704204 -14.519735          838            2.881921         2.890675\n",
+       " 793121  2.705906 -14.519661          838            2.879782         2.890675\n",
+       " 793122  2.707608 -14.519588          838            2.877644         2.890675\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 793766  3.803504 -14.524385          838            0.000155         2.890675\n",
+       " 793767  3.805205 -14.524433          838            0.000148         2.890675\n",
+       " 793768  3.806907 -14.524481          838            0.000141         2.890675\n",
+       " 793769  3.808609 -14.524529          838            0.000134         2.890675\n",
+       " 793770  3.810310 -14.524576          838            0.000127         2.890675\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 794118  2.700801 -14.519984          839            2.886598         2.890329\n",
+       " 794119  2.702502 -14.519894          839            2.884590         2.890329\n",
+       " 794120  2.704204 -14.519802          839            2.882582         2.890329\n",
+       " 794121  2.705906 -14.519798          839            2.880474         2.890329\n",
+       " 794122  2.707608 -14.519798          839            2.878362         2.890329\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 794766  3.803504 -14.525227          839            0.000156         2.890329\n",
+       " 794767  3.805205 -14.525289          839            0.000149         2.890329\n",
+       " 794768  3.806907 -14.525352          839            0.000141         2.890329\n",
+       " 794769  3.808609 -14.525414          839            0.000134         2.890329\n",
+       " 794770  3.810310 -14.525477          839            0.000127         2.890329\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 795118  2.700801 -14.519989          840            2.884694         2.890794\n",
+       " 795119  2.702502 -14.519908          840            2.882580         2.890794\n",
+       " 795120  2.704204 -14.519827          840            2.880467         2.890794\n",
+       " 795121  2.705906 -14.519798          840            2.878388         2.890794\n",
+       " 795122  2.707608 -14.519798          840            2.876328         2.890794\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 795766  3.803504 -14.525707          840            0.000151         2.890794\n",
+       " 795767  3.805205 -14.525775          840            0.000144         2.890794\n",
+       " 795768  3.806907 -14.525843          840            0.000137         2.890794\n",
+       " 795769  3.808609 -14.525909          840            0.000130         2.890794\n",
+       " 795770  3.810310 -14.525977          840            0.000123         2.890794\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 796118  2.700801 -14.519833          841            2.882419         2.887163\n",
+       " 796119  2.702502 -14.519975          841            2.880282         2.887163\n",
+       " 796120  2.704204 -14.520116          841            2.878146         2.887163\n",
+       " 796121  2.705906 -14.520253          841            2.876011         2.887163\n",
+       " 796122  2.707608 -14.520038          841            2.873971         2.887163\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 796766  3.803504 -14.523934          841            0.000151         2.887163\n",
+       " 796767  3.805205 -14.523987          841            0.000144         2.887163\n",
+       " 796768  3.806907 -14.524039          841            0.000137         2.887163\n",
+       " 796769  3.808609 -14.524092          841            0.000130         2.887163\n",
+       " 796770  3.810310 -14.524144          841            0.000123         2.887163\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 797118  2.700801 -14.520226          842            2.883243         2.886524\n",
+       " 797119  2.702502 -14.520079          842            2.881118         2.886524\n",
+       " 797120  2.704204 -14.519931          842            2.878993         2.886524\n",
+       " 797121  2.705906 -14.519798          842            2.876870         2.886524\n",
+       " 797122  2.707608 -14.519798          842            2.874766         2.886524\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 797765  3.801802 -14.524753          842            0.000157         2.886524\n",
+       " 797766  3.803504 -14.524815          842            0.000150         2.886524\n",
+       " 797767  3.805205 -14.524878          842            0.000143         2.886524\n",
+       " 797768  3.806907 -14.524940          842            0.000136         2.886524\n",
+       " 797769  3.808609 -14.525002          842            0.000129         2.886524\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 798118  2.700801 -14.520204          843            2.885045         2.887052\n",
+       " 798119  2.702502 -14.519984          843            2.882924         2.887052\n",
+       " 798120  2.704204 -14.519766          843            2.880804         2.887052\n",
+       " 798121  2.705906 -14.519569          843            2.878688         2.887052\n",
+       " 798122  2.707608 -14.519569          843            2.876619         2.887052\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 798766  3.803504 -14.526536          843            0.000154         2.887052\n",
+       " 798767  3.805205 -14.526616          843            0.000147         2.887052\n",
+       " 798768  3.806907 -14.526696          843            0.000140         2.887052\n",
+       " 798769  3.808609 -14.526776          843            0.000133         2.887052\n",
+       " 798770  3.810310 -14.526856          843            0.000126         2.887052\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 799118  2.700801 -14.519702          844            2.880713         2.887836\n",
+       " 799119  2.702502 -14.519985          844            2.878714         2.887836\n",
+       " 799120  2.704204 -14.519964          844            2.876575         2.887836\n",
+       " 799121  2.705906 -14.519890          844            2.874410         2.887836\n",
+       " 799122  2.707608 -14.519816          844            2.872246         2.887836\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 799766  3.803504 -14.526166          844            0.000151         2.887836\n",
+       " 799767  3.805205 -14.526233          844            0.000144         2.887836\n",
+       " 799768  3.806907 -14.526300          844            0.000137         2.887836\n",
+       " 799769  3.808609 -14.526368          844            0.000130         2.887836\n",
+       " 799770  3.810310 -14.526435          844            0.000123         2.887836\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 800118  2.700801 -14.520027          845            2.880034         2.884819\n",
+       " 800119  2.702502 -14.520027          845            2.877961         2.884819\n",
+       " 800120  2.704204 -14.520027          845            2.875880         2.884819\n",
+       " 800121  2.705906 -14.520027          845            2.873790         2.884819\n",
+       " 800122  2.707608 -14.520027          845            2.871699         2.884819\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 800765  3.801802 -14.526097          845            0.000157         2.884819\n",
+       " 800766  3.803504 -14.526168          845            0.000150         2.884819\n",
+       " 800767  3.805205 -14.526237          845            0.000142         2.884819\n",
+       " 800768  3.806907 -14.526307          845            0.000135         2.884819\n",
+       " 800769  3.808609 -14.526378          845            0.000128         2.884819\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 801118  2.700801 -14.520256          846            2.879388         2.884012\n",
+       " 801119  2.702502 -14.520256          846            2.877313         2.884012\n",
+       " 801120  2.704204 -14.520256          846            2.875238         2.884012\n",
+       " 801121  2.705906 -14.520103          846            2.873182         2.884012\n",
+       " 801122  2.707608 -14.519882          846            2.871135         2.884012\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 801766  3.803504 -14.525722          846            0.000151         2.884012\n",
+       " 801767  3.805205 -14.525784          846            0.000144         2.884012\n",
+       " 801768  3.806907 -14.525846          846            0.000137         2.884012\n",
+       " 801769  3.808609 -14.525909          846            0.000130         2.884012\n",
+       " 801770  3.810310 -14.525971          846            0.000123         2.884012\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 802118  2.700801 -14.519991          847            2.876758         2.881643\n",
+       " 802119  2.702502 -14.520405          847            2.874667         2.881643\n",
+       " 802120  2.704204 -14.520308          847            2.872667         2.881643\n",
+       " 802121  2.705906 -14.520089          847            2.870687         2.881643\n",
+       " 802122  2.707608 -14.519871          847            2.868708         2.881643\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 802765  3.801802 -14.526097          847            0.000157         2.881643\n",
+       " 802766  3.803504 -14.526168          847            0.000150         2.881643\n",
+       " 802767  3.805205 -14.526237          847            0.000142         2.881643\n",
+       " 802768  3.806907 -14.526307          847            0.000135         2.881643\n",
+       " 802769  3.808609 -14.526378          847            0.000128         2.881643\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 803118  2.700801 -14.519761          848            2.877965         2.881422\n",
+       " 803119  2.702502 -14.519688          848            2.875973         2.881422\n",
+       " 803120  2.704204 -14.519615          848            2.873981         2.881422\n",
+       " 803121  2.705906 -14.519626          848            2.871948         2.881422\n",
+       " 803122  2.707608 -14.519775          848            2.869844         2.881422\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 803766  3.803504 -14.526364          848            0.000153         2.881422\n",
+       " 803767  3.805205 -14.526435          848            0.000146         2.881422\n",
+       " 803768  3.806907 -14.526505          848            0.000139         2.881422\n",
+       " 803769  3.808609 -14.526575          848            0.000132         2.881422\n",
+       " 803770  3.810310 -14.526645          848            0.000124         2.881422\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 804118  2.700801 -14.519905          849            2.875706         2.880375\n",
+       " 804119  2.702502 -14.519644          849            2.873607         2.880375\n",
+       " 804120  2.704204 -14.519569          849            2.871578         2.880375\n",
+       " 804121  2.705906 -14.519569          849            2.869576         2.880375\n",
+       " 804122  2.707608 -14.519569          849            2.867573         2.880375\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 804765  3.801802 -14.526109          849            0.000157         2.880375\n",
+       " 804766  3.803504 -14.526176          849            0.000150         2.880375\n",
+       " 804767  3.805205 -14.526244          849            0.000143         2.880375\n",
+       " 804768  3.806907 -14.526312          849            0.000135         2.880375\n",
+       " 804769  3.808609 -14.526380          849            0.000128         2.880375\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 805118  2.700801 -14.519966          850            2.875701         2.879106\n",
+       " 805119  2.702502 -14.519399          850            2.873777         2.879106\n",
+       " 805120  2.704204 -14.519477          850            2.871712         2.879106\n",
+       " 805121  2.705906 -14.519629          850            2.869631         2.879106\n",
+       " 805122  2.707608 -14.519782          850            2.867550         2.879106\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 805756  3.786486 -14.520879          850            0.000193         2.879106\n",
+       " 805757  3.788188 -14.520894          850            0.000186         2.879106\n",
+       " 805758  3.789890 -14.520910          850            0.000178         2.879106\n",
+       " 805759  3.791592 -14.520926          850            0.000170         2.879106\n",
+       " 805760  3.793293 -14.520943          850            0.000163         2.879106\n",
+       " \n",
+       " [643 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 806118  2.700801 -14.520372          851            2.874603         2.879776\n",
+       " 806119  2.702502 -14.520621          851            2.872475         2.879776\n",
+       " 806120  2.704204 -14.520622          851            2.870400         2.879776\n",
+       " 806121  2.705906 -14.520476          851            2.868356         2.879776\n",
+       " 806122  2.707608 -14.520330          851            2.866313         2.879776\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 806765  3.801802 -14.524357          851            0.000157         2.879776\n",
+       " 806766  3.803504 -14.524406          851            0.000150         2.879776\n",
+       " 806767  3.805205 -14.524457          851            0.000143         2.879776\n",
+       " 806768  3.806907 -14.524507          851            0.000136         2.879776\n",
+       " 806769  3.808609 -14.524556          851            0.000129         2.879776\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 807118  2.700801 -14.520234          852            2.871258         2.877193\n",
+       " 807119  2.702502 -14.520117          852            2.869186         2.877193\n",
+       " 807120  2.704204 -14.520263          852            2.867091         2.877193\n",
+       " 807121  2.705906 -14.520409          852            2.864997         2.877193\n",
+       " 807122  2.707608 -14.520451          852            2.862920         2.877193\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 807765  3.801802 -14.525015          852            0.000155         2.877193\n",
+       " 807766  3.803504 -14.525075          852            0.000148         2.877193\n",
+       " 807767  3.805205 -14.525135          852            0.000141         2.877193\n",
+       " 807768  3.806907 -14.525195          852            0.000134         2.877193\n",
+       " 807769  3.808609 -14.525255          852            0.000127         2.877193\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 808118  2.700801 -14.520119          853            2.873079          2.87544\n",
+       " 808119  2.702502 -14.519853          853            2.871031          2.87544\n",
+       " 808120  2.704204 -14.519926          853            2.868974          2.87544\n",
+       " 808121  2.705906 -14.519999          853            2.866918          2.87544\n",
+       " 808122  2.707608 -14.519982          853            2.864838          2.87544\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 808755  3.784785 -14.519838          853            0.000200          2.87544\n",
+       " 808756  3.786486 -14.519830          853            0.000193          2.87544\n",
+       " 808757  3.788188 -14.519822          853            0.000185          2.87544\n",
+       " 808758  3.789890 -14.519814          853            0.000178          2.87544\n",
+       " 808759  3.791592 -14.519806          853            0.000170          2.87544\n",
+       " \n",
+       " [642 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 809118  2.700801 -14.520226          854            2.871076         2.876015\n",
+       " 809119  2.702502 -14.520186          854            2.869029         2.876015\n",
+       " 809120  2.704204 -14.520111          854            2.866952         2.876015\n",
+       " 809121  2.705906 -14.520036          854            2.864875         2.876015\n",
+       " 809122  2.707608 -14.520092          854            2.862779         2.876015\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 809755  3.784785 -14.518957          854            0.000198         2.876015\n",
+       " 809756  3.786486 -14.518941          854            0.000190         2.876015\n",
+       " 809757  3.788188 -14.518926          854            0.000183         2.876015\n",
+       " 809758  3.789890 -14.518909          854            0.000175         2.876015\n",
+       " 809759  3.791592 -14.518893          854            0.000168         2.876015\n",
+       " \n",
+       " [642 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 810118  2.700801 -14.519852          855            2.869819         2.873976\n",
+       " 810119  2.702502 -14.520074          855            2.867785         2.873976\n",
+       " 810120  2.704204 -14.520296          855            2.865752         2.873976\n",
+       " 810121  2.705906 -14.520473          855            2.863706         2.873976\n",
+       " 810122  2.707608 -14.520400          855            2.861594         2.873976\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 810755  3.784785 -14.520663          855            0.000199         2.873976\n",
+       " 810756  3.786486 -14.520674          855            0.000191         2.873976\n",
+       " 810757  3.788188 -14.520684          855            0.000184         2.873976\n",
+       " 810758  3.789890 -14.520695          855            0.000176         2.873976\n",
+       " 810759  3.791592 -14.520706          855            0.000168         2.873976\n",
+       " \n",
+       " [642 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 811118  2.700801 -14.519832          856            2.869383         2.873268\n",
+       " 811119  2.702502 -14.520054          856            2.867258         2.873268\n",
+       " 811120  2.704204 -14.520276          856            2.865133         2.873268\n",
+       " 811121  2.705906 -14.520463          856            2.863015         2.873268\n",
+       " 811122  2.707608 -14.520093          856            2.861021         2.873268\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 811765  3.801802 -14.525023          856            0.000156         2.873268\n",
+       " 811766  3.803504 -14.525080          856            0.000148         2.873268\n",
+       " 811767  3.805205 -14.525137          856            0.000141         2.873268\n",
+       " 811768  3.806907 -14.525194          856            0.000134         2.873268\n",
+       " 811769  3.808609 -14.525251          856            0.000127         2.873268\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 812118  2.700801 -14.519791          857            2.869076         2.873531\n",
+       " 812119  2.702502 -14.519716          857            2.866964         2.873531\n",
+       " 812120  2.704204 -14.519643          857            2.864852         2.873531\n",
+       " 812121  2.705906 -14.519569          857            2.862741         2.873531\n",
+       " 812122  2.707608 -14.519569          857            2.860711         2.873531\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 812765  3.801802 -14.525001          857            0.000155         2.873531\n",
+       " 812766  3.803504 -14.525064          857            0.000148         2.873531\n",
+       " 812767  3.805205 -14.525126          857            0.000141         2.873531\n",
+       " 812768  3.806907 -14.525188          857            0.000134         2.873531\n",
+       " 812769  3.808609 -14.525250          857            0.000127         2.873531\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 813118  2.700801 -14.519966          858            2.869749          2.87334\n",
+       " 813119  2.702502 -14.520256          858            2.867763          2.87334\n",
+       " 813120  2.704204 -14.520256          858            2.865733          2.87334\n",
+       " 813121  2.705906 -14.520256          858            2.863702          2.87334\n",
+       " 813122  2.707608 -14.520256          858            2.861675          2.87334\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 813766  3.803504 -14.523957          858            0.000152          2.87334\n",
+       " 813767  3.805205 -14.524002          858            0.000145          2.87334\n",
+       " 813768  3.806907 -14.524047          858            0.000138          2.87334\n",
+       " 813769  3.808609 -14.524092          858            0.000131          2.87334\n",
+       " 813770  3.810310 -14.524137          858            0.000124          2.87334\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 814118  2.700801 -14.520027          859            2.868744         2.871775\n",
+       " 814119  2.702502 -14.520027          859            2.866654         2.871775\n",
+       " 814120  2.704204 -14.520027          859            2.864564         2.871775\n",
+       " 814121  2.705906 -14.520044          859            2.862494         2.871775\n",
+       " 814122  2.707608 -14.520116          859            2.860492         2.871775\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 814766  3.803504 -14.525280          859            0.000152         2.871775\n",
+       " 814767  3.805205 -14.525337          859            0.000145         2.871775\n",
+       " 814768  3.806907 -14.525394          859            0.000138         2.871775\n",
+       " 814769  3.808609 -14.525452          859            0.000131         2.871775\n",
+       " 814770  3.810310 -14.525510          859            0.000124         2.871775\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 815118  2.700801 -14.520135          860            2.868306         2.871732\n",
+       " 815119  2.702502 -14.520220          860            2.866322         2.871732\n",
+       " 815120  2.704204 -14.520144          860            2.864228         2.871732\n",
+       " 815121  2.705906 -14.520067          860            2.862133         2.871732\n",
+       " 815122  2.707608 -14.520027          860            2.860042         2.871732\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 815756  3.786486 -14.520679          860            0.000195         2.871732\n",
+       " 815757  3.788188 -14.520687          860            0.000188         2.871732\n",
+       " 815758  3.789890 -14.520695          860            0.000180         2.871732\n",
+       " 815759  3.791592 -14.520703          860            0.000173         2.871732\n",
+       " 815760  3.793293 -14.520711          860            0.000165         2.871732\n",
+       " \n",
+       " [643 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 816118  2.700801 -14.520027          861            2.867640         2.871758\n",
+       " 816119  2.702502 -14.520027          861            2.865600         2.871758\n",
+       " 816120  2.704204 -14.520027          861            2.863560         2.871758\n",
+       " 816121  2.705906 -14.520027          861            2.861518         2.871758\n",
+       " 816122  2.707608 -14.520027          861            2.859445         2.871758\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 816766  3.803504 -14.525272          861            0.000152         2.871758\n",
+       " 816767  3.805205 -14.525332          861            0.000145         2.871758\n",
+       " 816768  3.806907 -14.525392          861            0.000138         2.871758\n",
+       " 816769  3.808609 -14.525452          861            0.000131         2.871758\n",
+       " 816770  3.810310 -14.525512          861            0.000124         2.871758\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 817118  2.700801 -14.519798          862            2.865763         2.870668\n",
+       " 817119  2.702502 -14.519798          862            2.863794         2.870668\n",
+       " 817120  2.704204 -14.519798          862            2.861824         2.870668\n",
+       " 817121  2.705906 -14.519734          862            2.859753         2.870668\n",
+       " 817122  2.707608 -14.519660          862            2.857667         2.870668\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 817765  3.801802 -14.526521          862            0.000156         2.870668\n",
+       " 817766  3.803504 -14.526598          862            0.000149         2.870668\n",
+       " 817767  3.805205 -14.526675          862            0.000142         2.870668\n",
+       " 817768  3.806907 -14.526752          862            0.000135         2.870668\n",
+       " 817769  3.808609 -14.526830          862            0.000128         2.870668\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 818118  2.700801 -14.519612          863            2.864731         2.868873\n",
+       " 818119  2.702502 -14.519832          863            2.862611         2.868873\n",
+       " 818120  2.704204 -14.520050          863            2.860490         2.868873\n",
+       " 818121  2.705906 -14.520265          863            2.858377         2.868873\n",
+       " 818122  2.707608 -14.520406          863            2.856378         2.868873\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 818765  3.801802 -14.524771          863            0.000157         2.868873\n",
+       " 818766  3.803504 -14.524831          863            0.000150         2.868873\n",
+       " 818767  3.805205 -14.524891          863            0.000143         2.868873\n",
+       " 818768  3.806907 -14.524950          863            0.000136         2.868873\n",
+       " 818769  3.808609 -14.525010          863            0.000129         2.868873\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 819118  2.700801 -14.519649          864            2.869230         2.872517\n",
+       " 819119  2.702502 -14.519798          864            2.867322         2.872517\n",
+       " 819120  2.704204 -14.519798          864            2.865278         2.872517\n",
+       " 819121  2.705906 -14.519798          864            2.863235         2.872517\n",
+       " 819122  2.707608 -14.519798          864            2.861192         2.872517\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 819756  3.786486 -14.519366          864            0.000199         2.872517\n",
+       " 819757  3.788188 -14.519361          864            0.000192         2.872517\n",
+       " 819758  3.789890 -14.519356          864            0.000184         2.872517\n",
+       " 819759  3.791592 -14.519350          864            0.000177         2.872517\n",
+       " 819760  3.793293 -14.519345          864            0.000169         2.872517\n",
+       " \n",
+       " [643 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 820118  2.700801 -14.520141          865            2.864801         2.868595\n",
+       " 820119  2.702502 -14.519894          865            2.862842         2.868595\n",
+       " 820120  2.704204 -14.519647          865            2.860883         2.868595\n",
+       " 820121  2.705906 -14.519621          865            2.858888         2.868595\n",
+       " 820122  2.707608 -14.519696          865            2.856878         2.868595\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 820766  3.803504 -14.526802          865            0.000152         2.868595\n",
+       " 820767  3.805205 -14.526879          865            0.000145         2.868595\n",
+       " 820768  3.806907 -14.526957          865            0.000138         2.868595\n",
+       " 820769  3.808609 -14.527034          865            0.000131         2.868595\n",
+       " 820770  3.810310 -14.527111          865            0.000124         2.868595\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 821118  2.700801 -14.520411          866            2.868145         2.868473\n",
+       " 821119  2.702502 -14.520265          866            2.866114         2.868473\n",
+       " 821120  2.704204 -14.520187          866            2.864132         2.868473\n",
+       " 821121  2.705906 -14.520115          866            2.862153         2.868473\n",
+       " 821122  2.707608 -14.520041          866            2.860174         2.868473\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 821767  3.805205 -14.525284          866            0.000152         2.868473\n",
+       " 821768  3.806907 -14.525342          866            0.000144         2.868473\n",
+       " 821769  3.808609 -14.525399          866            0.000137         2.868473\n",
+       " 821770  3.810310 -14.525457          866            0.000130         2.868473\n",
+       " 821771  3.812012 -14.525516          866            0.000123         2.868473\n",
+       " \n",
+       " [654 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 822118  2.700801 -14.519880          867            2.862820          2.87119\n",
+       " 822119  2.702502 -14.520027          867            2.860698          2.87119\n",
+       " 822120  2.704204 -14.520027          867            2.858668          2.87119\n",
+       " 822121  2.705906 -14.520027          867            2.856637          2.87119\n",
+       " 822122  2.707608 -14.520027          867            2.854604          2.87119\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 822765  3.801802 -14.525012          867            0.000157          2.87119\n",
+       " 822766  3.803504 -14.525069          867            0.000150          2.87119\n",
+       " 822767  3.805205 -14.525126          867            0.000143          2.87119\n",
+       " 822768  3.806907 -14.525184          867            0.000136          2.87119\n",
+       " 822769  3.808609 -14.525241          867            0.000129          2.87119\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 823118  2.700801 -14.520213          868            2.862677         2.866842\n",
+       " 823119  2.702502 -14.520120          868            2.860746         2.866842\n",
+       " 823120  2.704204 -14.520027          868            2.858816         2.866842\n",
+       " 823121  2.705906 -14.520027          868            2.856726         2.866842\n",
+       " 823122  2.707608 -14.520027          868            2.854636         2.866842\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 823765  3.801802 -14.526962          868            0.000157         2.866842\n",
+       " 823766  3.803504 -14.527042          868            0.000150         2.866842\n",
+       " 823767  3.805205 -14.527122          868            0.000143         2.866842\n",
+       " 823768  3.806907 -14.527202          868            0.000136         2.866842\n",
+       " 823769  3.808609 -14.527282          868            0.000129         2.866842\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 824118  2.700801 -14.519609          869            2.860898         2.865723\n",
+       " 824119  2.702502 -14.519694          869            2.858874         2.865723\n",
+       " 824120  2.704204 -14.519779          869            2.856850         2.865723\n",
+       " 824121  2.705906 -14.519798          869            2.854778         2.865723\n",
+       " 824122  2.707608 -14.519798          869            2.852692         2.865723\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 824766  3.803504 -14.526570          869            0.000151         2.865723\n",
+       " 824767  3.805205 -14.526649          869            0.000144         2.865723\n",
+       " 824768  3.806907 -14.526730          869            0.000137         2.865723\n",
+       " 824769  3.808609 -14.526810          869            0.000130         2.865723\n",
+       " 824770  3.810310 -14.526889          869            0.000123         2.865723\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 825118  2.700801 -14.519798          870            2.859560         2.864067\n",
+       " 825119  2.702502 -14.519798          870            2.857606         2.864067\n",
+       " 825120  2.704204 -14.519865          870            2.855616         2.864067\n",
+       " 825121  2.705906 -14.519938          870            2.853621         2.864067\n",
+       " 825122  2.707608 -14.520013          870            2.851626         2.864067\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 825765  3.801802 -14.525620          870            0.000157         2.864067\n",
+       " 825766  3.803504 -14.525691          870            0.000150         2.864067\n",
+       " 825767  3.805205 -14.525764          870            0.000143         2.864067\n",
+       " 825768  3.806907 -14.525836          870            0.000136         2.864067\n",
+       " 825769  3.808609 -14.525908          870            0.000129         2.864067\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 826118  2.700801 -14.519608          871            2.857501         2.861223\n",
+       " 826119  2.702502 -14.519419          871            2.855545         2.861223\n",
+       " 826120  2.704204 -14.519644          871            2.853428         2.861223\n",
+       " 826121  2.705906 -14.519869          871            2.851311         2.861223\n",
+       " 826122  2.707608 -14.519984          871            2.849194         2.861223\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 826765  3.801802 -14.526306          871            0.000155         2.861223\n",
+       " 826766  3.803504 -14.526383          871            0.000148         2.861223\n",
+       " 826767  3.805205 -14.526460          871            0.000141         2.861223\n",
+       " 826768  3.806907 -14.526537          871            0.000134         2.861223\n",
+       " 826769  3.808609 -14.526614          871            0.000127         2.861223\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 827118  2.700801 -14.519533          872            2.856574         2.861281\n",
+       " 827119  2.702502 -14.519947          872            2.854532         2.861281\n",
+       " 827120  2.704204 -14.519967          872            2.852475         2.861281\n",
+       " 827121  2.705906 -14.519894          872            2.850415         2.861281\n",
+       " 827122  2.707608 -14.519819          872            2.848355         2.861281\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 827765  3.801802 -14.526771          872            0.000155         2.861281\n",
+       " 827766  3.803504 -14.526848          872            0.000147         2.861281\n",
+       " 827767  3.805205 -14.526925          872            0.000140         2.861281\n",
+       " 827768  3.806907 -14.527002          872            0.000133         2.861281\n",
+       " 827769  3.808609 -14.527079          872            0.000126         2.861281\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 828118  2.700801 -14.519629          873            2.856078         2.859799\n",
+       " 828119  2.702502 -14.519357          873            2.854152         2.859799\n",
+       " 828120  2.704204 -14.519431          873            2.852115         2.859799\n",
+       " 828121  2.705906 -14.519506          873            2.850078         2.859799\n",
+       " 828122  2.707608 -14.519593          873            2.848046         2.859799\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 828765  3.801802 -14.526129          873            0.000155         2.859799\n",
+       " 828766  3.803504 -14.526196          873            0.000148         2.859799\n",
+       " 828767  3.805205 -14.526263          873            0.000141         2.859799\n",
+       " 828768  3.806907 -14.526331          873            0.000133         2.859799\n",
+       " 828769  3.808609 -14.526398          873            0.000126         2.859799\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 829118  2.700801 -14.520494          874            2.854810         2.859198\n",
+       " 829119  2.702502 -14.520586          874            2.852817         2.859198\n",
+       " 829120  2.704204 -14.520360          874            2.850779         2.859198\n",
+       " 829121  2.705906 -14.520135          874            2.848742         2.859198\n",
+       " 829122  2.707608 -14.520027          874            2.846720         2.859198\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 829765  3.801802 -14.525895          874            0.000154         2.859198\n",
+       " 829766  3.803504 -14.525965          874            0.000147         2.859198\n",
+       " 829767  3.805205 -14.526034          874            0.000140         2.859198\n",
+       " 829768  3.806907 -14.526104          874            0.000133         2.859198\n",
+       " 829769  3.808609 -14.526174          874            0.000126         2.859198\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 830118  2.700801 -14.520015          875            2.854213         2.857915\n",
+       " 830119  2.702502 -14.520186          875            2.852208         2.857915\n",
+       " 830120  2.704204 -14.520041          875            2.850203         2.857915\n",
+       " 830121  2.705906 -14.519895          875            2.848198         2.857915\n",
+       " 830122  2.707608 -14.519847          875            2.846195         2.857915\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 830765  3.801802 -14.526546          875            0.000154         2.857915\n",
+       " 830766  3.803504 -14.526623          875            0.000147         2.857915\n",
+       " 830767  3.805205 -14.526700          875            0.000140         2.857915\n",
+       " 830768  3.806907 -14.526776          875            0.000133         2.857915\n",
+       " 830769  3.808609 -14.526854          875            0.000126         2.857915\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 831118  2.700801 -14.519871          881            2.944570         3.050738\n",
+       " 831119  2.702502 -14.520025          881            2.941899         3.050738\n",
+       " 831120  2.704204 -14.520180          881            2.939227         3.050738\n",
+       " 831121  2.705906 -14.520103          881            2.936501         3.050738\n",
+       " 831122  2.707608 -14.519803          881            2.933723         3.050738\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 831767  3.805205 -14.526330          881            0.000153         3.050738\n",
+       " 831768  3.806907 -14.526407          881            0.000146         3.050738\n",
+       " 831769  3.808609 -14.526485          881            0.000139         3.050738\n",
+       " 831770  3.810310 -14.526563          881            0.000132         3.050738\n",
+       " 831771  3.812012 -14.526641          881            0.000125         3.050738\n",
+       " \n",
+       " [654 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 832118  2.700801 -14.519910          882            2.931235         2.945044\n",
+       " 832119  2.702502 -14.519659          882            2.928595         2.945044\n",
+       " 832120  2.704204 -14.519408          882            2.925955         2.945044\n",
+       " 832121  2.705906 -14.519506          882            2.923195         2.945044\n",
+       " 832122  2.707608 -14.519731          882            2.920390         2.945044\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 832767  3.805205 -14.526344          882            0.000153         2.945044\n",
+       " 832768  3.806907 -14.526419          882            0.000146         2.945044\n",
+       " 832769  3.808609 -14.526494          882            0.000139         2.945044\n",
+       " 832770  3.810310 -14.526569          882            0.000131         2.945044\n",
+       " 832771  3.812012 -14.526645          882            0.000124         2.945044\n",
+       " \n",
+       " [654 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 833118  2.700801 -14.519798          883            2.920115         2.932176\n",
+       " 833119  2.702502 -14.519798          883            2.917417         2.932176\n",
+       " 833120  2.704204 -14.519798          883            2.914718         2.932176\n",
+       " 833121  2.705906 -14.519921          883            2.911943         2.932176\n",
+       " 833122  2.707608 -14.520072          883            2.909152         2.932176\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 833766  3.803504 -14.524367          883            0.000156         2.932176\n",
+       " 833767  3.805205 -14.524417          883            0.000149         2.932176\n",
+       " 833768  3.806907 -14.524467          883            0.000142         2.932176\n",
+       " 833769  3.808609 -14.524516          883            0.000135         2.932176\n",
+       " 833770  3.810310 -14.524567          883            0.000128         2.932176\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 834118  2.700801 -14.520447          884            2.913178         2.924037\n",
+       " 834119  2.702502 -14.520364          884            2.910479         2.924037\n",
+       " 834120  2.704204 -14.520282          884            2.907781         2.924037\n",
+       " 834121  2.705906 -14.520204          884            2.905036         2.924037\n",
+       " 834122  2.707608 -14.520127          884            2.902270         2.924037\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 834766  3.803504 -14.526335          884            0.000156         2.924037\n",
+       " 834767  3.805205 -14.526404          884            0.000149         2.924037\n",
+       " 834768  3.806907 -14.526474          884            0.000142         2.924037\n",
+       " 834769  3.808609 -14.526545          884            0.000135         2.924037\n",
+       " 834770  3.810310 -14.526614          884            0.000128         2.924037\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 835118  2.700801 -14.519798          885            2.905838         2.914944\n",
+       " 835119  2.702502 -14.519798          885            2.903225         2.914944\n",
+       " 835120  2.704204 -14.519829          885            2.900578         2.914944\n",
+       " 835121  2.705906 -14.520058          885            2.897704         2.914944\n",
+       " 835122  2.707608 -14.520287          885            2.894831         2.914944\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 835756  3.786486 -14.520870          885            0.000197         2.914944\n",
+       " 835757  3.788188 -14.520886          885            0.000189         2.914944\n",
+       " 835758  3.789890 -14.520903          885            0.000182         2.914944\n",
+       " 835759  3.791592 -14.520919          885            0.000174         2.914944\n",
+       " 835760  3.793293 -14.520934          885            0.000167         2.914944\n",
+       " \n",
+       " [643 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 836118  2.700801 -14.520138          886            2.899544         2.908658\n",
+       " 836119  2.702502 -14.520445          886            2.896919         2.908658\n",
+       " 836120  2.704204 -14.520369          886            2.894126         2.908658\n",
+       " 836121  2.705906 -14.520292          886            2.891333         2.908658\n",
+       " 836122  2.707608 -14.520179          886            2.888569         2.908658\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 836766  3.803504 -14.525718          886            0.000153         2.908658\n",
+       " 836767  3.805205 -14.525777          886            0.000146         2.908658\n",
+       " 836768  3.806907 -14.525837          886            0.000139         2.908658\n",
+       " 836769  3.808609 -14.525896          886            0.000132         2.908658\n",
+       " 836770  3.810310 -14.525956          886            0.000125         2.908658\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 837118  2.700801 -14.520069          887            2.894918          2.90168\n",
+       " 837119  2.702502 -14.520159          887            2.892330          2.90168\n",
+       " 837120  2.704204 -14.520248          887            2.889742          2.90168\n",
+       " 837121  2.705906 -14.520256          887            2.886978          2.90168\n",
+       " 837122  2.707608 -14.520256          887            2.884198          2.90168\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 837766  3.803504 -14.525926          887            0.000153          2.90168\n",
+       " 837767  3.805205 -14.525990          887            0.000146          2.90168\n",
+       " 837768  3.806907 -14.526054          887            0.000139          2.90168\n",
+       " 837769  3.808609 -14.526118          887            0.000132          2.90168\n",
+       " 837770  3.810310 -14.526183          887            0.000125          2.90168\n",
+       " \n",
+       " [653 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 838118  2.700801 -14.519784          888            2.893140         2.899452\n",
+       " 838119  2.702502 -14.519711          888            2.890480         2.899452\n",
+       " 838120  2.704204 -14.519638          888            2.887820         2.899452\n",
+       " 838121  2.705906 -14.519574          888            2.885158         2.899452\n",
+       " 838122  2.707608 -14.519649          888            2.882473         2.899452\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 838756  3.786486 -14.519123          888            0.000195         2.899452\n",
+       " 838757  3.788188 -14.519120          888            0.000188         2.899452\n",
+       " 838758  3.789890 -14.519117          888            0.000180         2.899452\n",
+       " 838759  3.791592 -14.519115          888            0.000173         2.899452\n",
+       " 838760  3.793293 -14.519113          888            0.000165         2.899452\n",
+       " \n",
+       " [643 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 839118  2.700801 -14.520119          889            2.885413         2.894182\n",
+       " 839119  2.702502 -14.520093          889            2.882707         2.894182\n",
+       " 839120  2.704204 -14.520166          889            2.879982         2.894182\n",
+       " 839121  2.705906 -14.520241          889            2.877257         2.894182\n",
+       " 839122  2.707608 -14.520019          889            2.874564         2.894182\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 839765  3.801802 -14.524365          889            0.000156         2.894182\n",
+       " 839766  3.803504 -14.524415          889            0.000149         2.894182\n",
+       " 839767  3.805205 -14.524465          889            0.000142         2.894182\n",
+       " 839768  3.806907 -14.524514          889            0.000135         2.894182\n",
+       " 839769  3.808609 -14.524564          889            0.000128         2.894182\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 840118  2.700801 -14.519909          890            2.881053         2.888218\n",
+       " 840119  2.702502 -14.520180          890            2.878428         2.888218\n",
+       " 840120  2.704204 -14.520034          890            2.875832         2.888218\n",
+       " 840121  2.705906 -14.519888          890            2.873236         2.888218\n",
+       " 840122  2.707608 -14.519856          890            2.870605         2.888218\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 840765  3.801802 -14.524588          890            0.000156         2.888218\n",
+       " 840766  3.803504 -14.524639          890            0.000149         2.888218\n",
+       " 840767  3.805205 -14.524692          890            0.000142         2.888218\n",
+       " 840768  3.806907 -14.524743          890            0.000135         2.888218\n",
+       " 840769  3.808609 -14.524796          890            0.000128         2.888218\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 841118  2.700801 -14.519829          891            2.881581         2.887158\n",
+       " 841119  2.702502 -14.519798          891            2.878910         2.887158\n",
+       " 841120  2.704204 -14.519798          891            2.876225         2.887158\n",
+       " 841121  2.705906 -14.519798          891            2.873538         2.887158\n",
+       " 841122  2.707608 -14.519857          891            2.870905         2.887158\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 841765  3.801802 -14.524603          891            0.000155         2.887158\n",
+       " 841766  3.803504 -14.524652          891            0.000148         2.887158\n",
+       " 841767  3.805205 -14.524702          891            0.000141         2.887158\n",
+       " 841768  3.806907 -14.524752          891            0.000134         2.887158\n",
+       " 841769  3.808609 -14.524801          891            0.000127         2.887158\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 842118  2.700801 -14.519683          892            2.875386         2.881016\n",
+       " 842119  2.702502 -14.519798          892            2.872802         2.881016\n",
+       " 842120  2.704204 -14.519798          892            2.870244         2.881016\n",
+       " 842121  2.705906 -14.519798          892            2.867687         2.881016\n",
+       " 842122  2.707608 -14.519770          892            2.865105         2.881016\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 842765  3.801802 -14.526311          892            0.000155         2.881016\n",
+       " 842766  3.803504 -14.526387          892            0.000148         2.881016\n",
+       " 842767  3.805205 -14.526464          892            0.000141         2.881016\n",
+       " 842768  3.806907 -14.526541          892            0.000134         2.881016\n",
+       " 842769  3.808609 -14.526618          892            0.000127         2.881016\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 843118  2.700801 -14.519654          893            2.873059          2.87875\n",
+       " 843119  2.702502 -14.519836          893            2.870472          2.87875\n",
+       " 843120  2.704204 -14.520019          893            2.867886          2.87875\n",
+       " 843121  2.705906 -14.520027          893            2.865279          2.87875\n",
+       " 843122  2.707608 -14.520027          893            2.862672          2.87875\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 843765  3.801802 -14.524375          893            0.000153          2.87875\n",
+       " 843766  3.803504 -14.524426          893            0.000146          2.87875\n",
+       " 843767  3.805205 -14.524479          893            0.000139          2.87875\n",
+       " 843768  3.806907 -14.524530          893            0.000132          2.87875\n",
+       " 843769  3.808609 -14.524583          893            0.000125          2.87875\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 844118  2.700801 -14.520089          894            2.869578         2.875498\n",
+       " 844119  2.702502 -14.519731          894            2.867053         2.875498\n",
+       " 844120  2.704204 -14.519373          894            2.864528         2.875498\n",
+       " 844121  2.705906 -14.519477          894            2.861857         2.875498\n",
+       " 844122  2.707608 -14.519628          894            2.859171         2.875498\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 844765  3.801802 -14.526391          894            0.000151         2.875498\n",
+       " 844766  3.803504 -14.526458          894            0.000144         2.875498\n",
+       " 844767  3.805205 -14.526524          894            0.000137         2.875498\n",
+       " 844768  3.806907 -14.526590          894            0.000130         2.875498\n",
+       " 844769  3.808609 -14.526657          894            0.000123         2.875498\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 845118  2.700801 -14.520009          895            2.866144         2.872761\n",
+       " 845119  2.702502 -14.519857          895            2.863574         2.872761\n",
+       " 845120  2.704204 -14.519933          895            2.860928         2.872761\n",
+       " 845121  2.705906 -14.520008          895            2.858282         2.872761\n",
+       " 845122  2.707608 -14.519856          895            2.855706         2.872761\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 845764  3.800100 -14.525667          895            0.000156         2.872761\n",
+       " 845765  3.801802 -14.525732          895            0.000149         2.872761\n",
+       " 845766  3.803504 -14.525796          895            0.000142         2.872761\n",
+       " 845767  3.805205 -14.525860          895            0.000135         2.872761\n",
+       " 845768  3.806907 -14.525924          895            0.000128         2.872761\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 846118  2.700801 -14.519768          896            2.862516         2.869474\n",
+       " 846119  2.702502 -14.520057          896            2.860054         2.869474\n",
+       " 846120  2.704204 -14.520133          896            2.857436         2.869474\n",
+       " 846121  2.705906 -14.520209          896            2.854817         2.869474\n",
+       " 846122  2.707608 -14.520256          896            2.852229         2.869474\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 846764  3.800100 -14.524141          896            0.000156         2.869474\n",
+       " 846765  3.801802 -14.524191          896            0.000149         2.869474\n",
+       " 846766  3.803504 -14.524240          896            0.000142         2.869474\n",
+       " 846767  3.805205 -14.524289          896            0.000135         2.869474\n",
+       " 846768  3.806907 -14.524339          896            0.000128         2.869474\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 847118  2.700801 -14.520027          897            2.862867         2.868143\n",
+       " 847119  2.702502 -14.520027          897            2.860338         2.868143\n",
+       " 847120  2.704204 -14.520027          897            2.857767         2.868143\n",
+       " 847121  2.705906 -14.520027          897            2.855197         2.868143\n",
+       " 847122  2.707608 -14.520027          897            2.852682         2.868143\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 847765  3.801802 -14.526794          897            0.000152         2.868143\n",
+       " 847766  3.803504 -14.526871          897            0.000145         2.868143\n",
+       " 847767  3.805205 -14.526947          897            0.000138         2.868143\n",
+       " 847768  3.806907 -14.527023          897            0.000131         2.868143\n",
+       " 847769  3.808609 -14.527100          897            0.000125         2.868143\n",
+       " \n",
+       " [652 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 848118  2.700801 -14.520027          898            2.860569         2.864749\n",
+       " 848119  2.702502 -14.520070          898            2.858044         2.864749\n",
+       " 848120  2.704204 -14.520145          898            2.855411         2.864749\n",
+       " 848121  2.705906 -14.520220          898            2.852778         2.864749\n",
+       " 848122  2.707608 -14.520179          898            2.850199         2.864749\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 848764  3.800100 -14.525855          898            0.000157         2.864749\n",
+       " 848765  3.801802 -14.525927          898            0.000150         2.864749\n",
+       " 848766  3.803504 -14.525997          898            0.000143         2.864749\n",
+       " 848767  3.805205 -14.526069          898            0.000136         2.864749\n",
+       " 848768  3.806907 -14.526140          898            0.000129         2.864749\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 849118  2.700801 -14.519908          899            2.857285         2.863387\n",
+       " 849119  2.702502 -14.519841          899            2.854900         2.863387\n",
+       " 849120  2.704204 -14.519917          899            2.852413         2.863387\n",
+       " 849121  2.705906 -14.519991          899            2.849926         2.863387\n",
+       " 849122  2.707608 -14.520027          899            2.847445         2.863387\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 849764  3.800100 -14.525887          899            0.000156         2.863387\n",
+       " 849765  3.801802 -14.525953          899            0.000149         2.863387\n",
+       " 849766  3.803504 -14.526020          899            0.000142         2.863387\n",
+       " 849767  3.805205 -14.526087          899            0.000135         2.863387\n",
+       " 849768  3.806907 -14.526154          899            0.000128         2.863387\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 850118  2.700801 -14.519798          900            2.854094         2.860487\n",
+       " 850119  2.702502 -14.519798          900            2.851749         2.860487\n",
+       " 850120  2.704204 -14.519798          900            2.849404         2.860487\n",
+       " 850121  2.705906 -14.519798          900            2.846916         2.860487\n",
+       " 850122  2.707608 -14.519798          900            2.844376         2.860487\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 850764  3.800100 -14.525688          900            0.000154         2.860487\n",
+       " 850765  3.801802 -14.525752          900            0.000147         2.860487\n",
+       " 850766  3.803504 -14.525816          900            0.000140         2.860487\n",
+       " 850767  3.805205 -14.525880          900            0.000133         2.860487\n",
+       " 850768  3.806907 -14.525944          900            0.000126         2.860487\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 851118  2.700801 -14.519639          901            2.853587         2.857837\n",
+       " 851119  2.702502 -14.519790          901            2.851192         2.857837\n",
+       " 851120  2.704204 -14.519939          901            2.848798         2.857837\n",
+       " 851121  2.705906 -14.520027          901            2.846379         2.857837\n",
+       " 851122  2.707608 -14.520027          901            2.843928         2.857837\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 851754  3.783083 -14.520678          901            0.000197         2.857837\n",
+       " 851755  3.784785 -14.520685          901            0.000190         2.857837\n",
+       " 851756  3.786486 -14.520693          901            0.000182         2.857837\n",
+       " 851757  3.788188 -14.520701          901            0.000175         2.857837\n",
+       " 851758  3.789890 -14.520709          901            0.000167         2.857837\n",
+       " \n",
+       " [641 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 852118  2.700801 -14.519958          902            2.851185         2.856602\n",
+       " 852119  2.702502 -14.519807          902            2.848830         2.856602\n",
+       " 852120  2.704204 -14.519866          902            2.846486         2.856602\n",
+       " 852121  2.705906 -14.519938          902            2.844141         2.856602\n",
+       " 852122  2.707608 -14.520010          902            2.841797         2.856602\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 852764  3.800100 -14.522417          902            0.000155         2.856602\n",
+       " 852765  3.801802 -14.522444          902            0.000148         2.856602\n",
+       " 852766  3.803504 -14.522471          902            0.000141         2.856602\n",
+       " 852767  3.805205 -14.522498          902            0.000134         2.856602\n",
+       " 852768  3.806907 -14.522526          902            0.000127         2.856602\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 853118  2.700801 -14.519815          903            2.849294         2.853811\n",
+       " 853119  2.702502 -14.519889          903            2.846942         2.853811\n",
+       " 853120  2.704204 -14.519961          903            2.844590         2.853811\n",
+       " 853121  2.705906 -14.520020          903            2.842223         2.853811\n",
+       " 853122  2.707608 -14.519943          903            2.839726         2.853811\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 853764  3.800100 -14.524574          903            0.000154         2.853811\n",
+       " 853765  3.801802 -14.524632          903            0.000147         2.853811\n",
+       " 853766  3.803504 -14.524688          903            0.000140         2.853811\n",
+       " 853767  3.805205 -14.524744          903            0.000133         2.853811\n",
+       " 853768  3.806907 -14.524801          903            0.000126         2.853811\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 854118  2.700801 -14.520138          904            2.846132         2.851639\n",
+       " 854119  2.702502 -14.520256          904            2.843720         2.851639\n",
+       " 854120  2.704204 -14.520256          904            2.841253         2.851639\n",
+       " 854121  2.705906 -14.520256          904            2.838785         2.851639\n",
+       " 854122  2.707608 -14.520155          904            2.836386         2.851639\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 854764  3.800100 -14.526339          904            0.000154         2.851639\n",
+       " 854765  3.801802 -14.526409          904            0.000147         2.851639\n",
+       " 854766  3.803504 -14.526481          904            0.000140         2.851639\n",
+       " 854767  3.805205 -14.526552          904            0.000133         2.851639\n",
+       " 854768  3.806907 -14.526624          904            0.000126         2.851639\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 855118  2.700801 -14.519978          905            2.844749         2.849765\n",
+       " 855119  2.702502 -14.519827          905            2.842341         2.849765\n",
+       " 855120  2.704204 -14.519677          905            2.839933         2.849765\n",
+       " 855121  2.705906 -14.519632          905            2.837524         2.849765\n",
+       " 855122  2.707608 -14.519855          905            2.835112         2.849765\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 855764  3.800100 -14.524778          905            0.000155         2.849765\n",
+       " 855765  3.801802 -14.524839          905            0.000148         2.849765\n",
+       " 855766  3.803504 -14.524901          905            0.000141         2.849765\n",
+       " 855767  3.805205 -14.524962          905            0.000134         2.849765\n",
+       " 855768  3.806907 -14.525024          905            0.000127         2.849765\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 856118  2.700801 -14.520160          906            2.847611         2.849397\n",
+       " 856119  2.702502 -14.520110          906            2.845237         2.849397\n",
+       " 856120  2.704204 -14.519888          906            2.842746         2.849397\n",
+       " 856121  2.705906 -14.519666          906            2.840256         2.849397\n",
+       " 856122  2.707608 -14.519732          906            2.837849         2.849397\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 856764  3.800100 -14.525662          906            0.000156         2.849397\n",
+       " 856765  3.801802 -14.525728          906            0.000149         2.849397\n",
+       " 856766  3.803504 -14.525795          906            0.000142         2.849397\n",
+       " 856767  3.805205 -14.525862          906            0.000135         2.849397\n",
+       " 856768  3.806907 -14.525928          906            0.000128         2.849397\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 857118  2.700801 -14.519798          907            2.841864         2.850697\n",
+       " 857119  2.702502 -14.519798          907            2.839501         2.850697\n",
+       " 857120  2.704204 -14.519798          907            2.837137         2.850697\n",
+       " 857121  2.705906 -14.519798          907            2.834713         2.850697\n",
+       " 857122  2.707608 -14.519798          907            2.832275         2.850697\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 857764  3.800100 -14.526141          907            0.000153         2.850697\n",
+       " 857765  3.801802 -14.526208          907            0.000146         2.850697\n",
+       " 857766  3.803504 -14.526274          907            0.000139         2.850697\n",
+       " 857767  3.805205 -14.526340          907            0.000132         2.850697\n",
+       " 857768  3.806907 -14.526406          907            0.000126         2.850697\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 858118  2.700801 -14.520334          908            2.840482         2.846133\n",
+       " 858119  2.702502 -14.520501          908            2.838181         2.846133\n",
+       " 858120  2.704204 -14.520669          908            2.835881         2.846133\n",
+       " 858121  2.705906 -14.520549          908            2.833511         2.846133\n",
+       " 858122  2.707608 -14.520324          908            2.831117         2.846133\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 858764  3.800100 -14.523932          908            0.000154         2.846133\n",
+       " 858765  3.801802 -14.523978          908            0.000148         2.846133\n",
+       " 858766  3.803504 -14.524025          908            0.000141         2.846133\n",
+       " 858767  3.805205 -14.524072          908            0.000134         2.846133\n",
+       " 858768  3.806907 -14.524118          908            0.000127         2.846133\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 859118  2.700801 -14.520027          909            2.841606         2.843954\n",
+       " 859119  2.702502 -14.520027          909            2.839207         2.843954\n",
+       " 859120  2.704204 -14.520027          909            2.836808         2.843954\n",
+       " 859121  2.705906 -14.520020          909            2.834417         2.843954\n",
+       " 859122  2.707608 -14.519945          909            2.832096         2.843954\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 859764  3.800100 -14.525879          909            0.000155         2.843954\n",
+       " 859765  3.801802 -14.525949          909            0.000149         2.843954\n",
+       " 859766  3.803504 -14.526017          909            0.000142         2.843954\n",
+       " 859767  3.805205 -14.526086          909            0.000135         2.843954\n",
+       " 859768  3.806907 -14.526155          909            0.000128         2.843954\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 860118  2.700801 -14.519992          910            2.836818         2.844173\n",
+       " 860119  2.702502 -14.519749          910            2.834499         2.844173\n",
+       " 860120  2.704204 -14.519673          910            2.832118         2.844173\n",
+       " 860121  2.705906 -14.519599          910            2.829737         2.844173\n",
+       " 860122  2.707608 -14.519614          910            2.827368         2.844173\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 860764  3.800100 -14.525041          910            0.000152         2.844173\n",
+       " 860765  3.801802 -14.525100          910            0.000145         2.844173\n",
+       " 860766  3.803504 -14.525158          910            0.000138         2.844173\n",
+       " 860767  3.805205 -14.525217          910            0.000131         2.844173\n",
+       " 860768  3.806907 -14.525276          910            0.000124         2.844173\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 861118  2.700801 -14.520027          911            2.835707         2.840836\n",
+       " 861119  2.702502 -14.520027          911            2.833373         2.840836\n",
+       " 861120  2.704204 -14.519966          911            2.830990         2.840836\n",
+       " 861121  2.705906 -14.519892          911            2.828595         2.840836\n",
+       " 861122  2.707608 -14.519816          911            2.826201         2.840836\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 861764  3.800100 -14.526327          911            0.000151         2.840836\n",
+       " 861765  3.801802 -14.526408          911            0.000144         2.840836\n",
+       " 861766  3.803504 -14.526489          911            0.000138         2.840836\n",
+       " 861767  3.805205 -14.526569          911            0.000131         2.840836\n",
+       " 861768  3.806907 -14.526650          911            0.000124         2.840836\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 862118  2.700801 -14.520009          912            2.833735         2.839538\n",
+       " 862119  2.702502 -14.519612          912            2.831504         2.839538\n",
+       " 862120  2.704204 -14.519688          912            2.829083         2.839538\n",
+       " 862121  2.705906 -14.519762          912            2.826662         2.839538\n",
+       " 862122  2.707608 -14.519836          912            2.824232         2.839538\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 862764  3.800100 -14.525041          912            0.000152         2.839538\n",
+       " 862765  3.801802 -14.525100          912            0.000145         2.839538\n",
+       " 862766  3.803504 -14.525158          912            0.000138         2.839538\n",
+       " 862767  3.805205 -14.525217          912            0.000131         2.839538\n",
+       " 862768  3.806907 -14.525276          912            0.000124         2.839538\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 863118  2.700801 -14.519877          913            2.835304         2.838678\n",
+       " 863119  2.702502 -14.520045          913            2.833120         2.838678\n",
+       " 863120  2.704204 -14.520196          913            2.830752         2.838678\n",
+       " 863121  2.705906 -14.520346          913            2.828384         2.838678\n",
+       " 863122  2.707608 -14.520469          913            2.826016         2.838678\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 863754  3.783083 -14.519582          913            0.000197         2.838678\n",
+       " 863755  3.784785 -14.519579          913            0.000190         2.838678\n",
+       " 863756  3.786486 -14.519576          913            0.000182         2.838678\n",
+       " 863757  3.788188 -14.519573          913            0.000175         2.838678\n",
+       " 863758  3.789890 -14.519571          913            0.000167         2.838678\n",
+       " \n",
+       " [641 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 864118  2.700801 -14.519569          914            2.833484         2.838497\n",
+       " 864119  2.702502 -14.519569          914            2.831141         2.838497\n",
+       " 864120  2.704204 -14.519727          914            2.828814         2.838497\n",
+       " 864121  2.705906 -14.520019          914            2.826501         2.838497\n",
+       " 864122  2.707608 -14.520309          914            2.824188         2.838497\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 864764  3.800100 -14.525692          914            0.000155         2.838497\n",
+       " 864765  3.801802 -14.525753          914            0.000148         2.838497\n",
+       " 864766  3.803504 -14.525814          914            0.000141         2.838497\n",
+       " 864767  3.805205 -14.525876          914            0.000134         2.838497\n",
+       " 864768  3.806907 -14.525937          914            0.000127         2.838497\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 865118  2.700801 -14.519857          915            2.832041         2.836185\n",
+       " 865119  2.702502 -14.520387          915            2.829807         2.836185\n",
+       " 865120  2.704204 -14.520162          915            2.827465         2.836185\n",
+       " 865121  2.705906 -14.519937          915            2.825124         2.836185\n",
+       " 865122  2.707608 -14.519798          915            2.822775         2.836185\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 865764  3.800100 -14.525673          915            0.000153         2.836185\n",
+       " 865765  3.801802 -14.525742          915            0.000146         2.836185\n",
+       " 865766  3.803504 -14.525810          915            0.000139         2.836185\n",
+       " 865767  3.805205 -14.525879          915            0.000132         2.836185\n",
+       " 865768  3.806907 -14.525948          915            0.000126         2.836185\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 866118  2.700801 -14.520039          916            2.828780         2.834741\n",
+       " 866119  2.702502 -14.520112          916            2.826473         2.834741\n",
+       " 866120  2.704204 -14.520186          916            2.824165         2.834741\n",
+       " 866121  2.705906 -14.520256          916            2.821856         2.834741\n",
+       " 866122  2.707608 -14.520256          916            2.819541         2.834741\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 866764  3.800100 -14.525698          916            0.000153         2.834741\n",
+       " 866765  3.801802 -14.525762          916            0.000146         2.834741\n",
+       " 866766  3.803504 -14.525826          916            0.000139         2.834741\n",
+       " 866767  3.805205 -14.525889          916            0.000132         2.834741\n",
+       " 866768  3.806907 -14.525952          916            0.000125         2.834741\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 867118  2.700801 -14.520027          917            2.828194         2.832257\n",
+       " 867119  2.702502 -14.520027          917            2.825924         2.832257\n",
+       " 867120  2.704204 -14.519982          917            2.823568         2.832257\n",
+       " 867121  2.705906 -14.519907          917            2.821151         2.832257\n",
+       " 867122  2.707608 -14.519831          917            2.818734         2.832257\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 867763  3.798398 -14.524990          917            0.000156         2.832257\n",
+       " 867764  3.800100 -14.525052          917            0.000150         2.832257\n",
+       " 867765  3.801802 -14.525113          917            0.000143         2.832257\n",
+       " 867766  3.803504 -14.525174          917            0.000136         2.832257\n",
+       " 867767  3.805205 -14.525236          917            0.000129         2.832257\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 868118  2.700801 -14.520020          918            2.826620         2.832703\n",
+       " 868119  2.702502 -14.519944          918            2.824265         2.832703\n",
+       " 868120  2.704204 -14.519869          918            2.821910         2.832703\n",
+       " 868121  2.705906 -14.519807          918            2.819557         2.832703\n",
+       " 868122  2.707608 -14.519953          918            2.817231         2.832703\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 868754  3.783083 -14.518722          918            0.000195         2.832703\n",
+       " 868755  3.784785 -14.518706          918            0.000187         2.832703\n",
+       " 868756  3.786486 -14.518690          918            0.000180         2.832703\n",
+       " 868757  3.788188 -14.518675          918            0.000173         2.832703\n",
+       " 868758  3.789890 -14.518659          918            0.000165         2.832703\n",
+       " \n",
+       " [641 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 869118  2.700801 -14.519798          919            2.826060          2.83054\n",
+       " 869119  2.702502 -14.519798          919            2.823796          2.83054\n",
+       " 869120  2.704204 -14.519798          919            2.821532          2.83054\n",
+       " 869121  2.705906 -14.519798          919            2.819183          2.83054\n",
+       " 869122  2.707608 -14.519798          919            2.816810          2.83054\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 869754  3.783083 -14.519637          919            0.000195          2.83054\n",
+       " 869755  3.784785 -14.519622          919            0.000187          2.83054\n",
+       " 869756  3.786486 -14.519606          919            0.000180          2.83054\n",
+       " 869757  3.788188 -14.519590          919            0.000173          2.83054\n",
+       " 869758  3.789890 -14.519574          919            0.000165          2.83054\n",
+       " \n",
+       " [641 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 870118  2.700801 -14.520027          920            2.822904         2.828392\n",
+       " 870119  2.702502 -14.520027          920            2.820668         2.828392\n",
+       " 870120  2.704204 -14.520027          920            2.818431         2.828392\n",
+       " 870121  2.705906 -14.520035          920            2.816186         2.828392\n",
+       " 870122  2.707608 -14.520107          920            2.813860         2.828392\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 870764  3.800100 -14.524636          920            0.000150         2.828392\n",
+       " 870765  3.801802 -14.524685          920            0.000143         2.828392\n",
+       " 870766  3.803504 -14.524734          920            0.000137         2.828392\n",
+       " 870767  3.805205 -14.524783          920            0.000130         2.828392\n",
+       " 870768  3.806907 -14.524832          920            0.000123         2.828392\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 871118  2.700801 -14.519942          921            2.822685         2.826707\n",
+       " 871119  2.702502 -14.520252          921            2.820450         2.826707\n",
+       " 871120  2.704204 -14.520561          921            2.818214         2.826707\n",
+       " 871121  2.705906 -14.520603          921            2.815939         2.826707\n",
+       " 871122  2.707608 -14.520384          921            2.813626         2.826707\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 871753  3.781381 -14.520447          921            0.000199         2.826707\n",
+       " 871754  3.783083 -14.520454          921            0.000191         2.826707\n",
+       " 871755  3.784785 -14.520462          921            0.000184         2.826707\n",
+       " 871756  3.786486 -14.520471          921            0.000177         2.826707\n",
+       " 871757  3.788188 -14.520478          921            0.000169         2.826707\n",
+       " \n",
+       " [640 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 872118  2.700801 -14.520256          922            2.821442         2.827057\n",
+       " 872119  2.702502 -14.520256          922            2.819223         2.827057\n",
+       " 872120  2.704204 -14.520256          922            2.817004         2.827057\n",
+       " 872121  2.705906 -14.520083          922            2.814716         2.827057\n",
+       " 872122  2.707608 -14.519862          922            2.812409         2.827057\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 872753  3.781381 -14.521551          922            0.000199         2.827057\n",
+       " 872754  3.783083 -14.521567          922            0.000192         2.827057\n",
+       " 872755  3.784785 -14.521583          922            0.000185         2.827057\n",
+       " 872756  3.786486 -14.521599          922            0.000177         2.827057\n",
+       " 872757  3.788188 -14.521614          922            0.000170         2.827057\n",
+       " \n",
+       " [640 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 873118  2.700801 -14.520027          923            2.822140         2.825527\n",
+       " 873119  2.702502 -14.520027          923            2.819946         2.825527\n",
+       " 873120  2.704204 -14.520027          923            2.817752         2.825527\n",
+       " 873121  2.705906 -14.520027          923            2.815484         2.825527\n",
+       " 873122  2.707608 -14.520027          923            2.813208         2.825527\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 873764  3.800100 -14.525695          923            0.000151         2.825527\n",
+       " 873765  3.801802 -14.525764          923            0.000144         2.825527\n",
+       " 873766  3.803504 -14.525832          923            0.000137         2.825527\n",
+       " 873767  3.805205 -14.525901          923            0.000130         2.825527\n",
+       " 873768  3.806907 -14.525970          923            0.000123         2.825527\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 874118  2.700801 -14.519607          924            2.820352         2.825007\n",
+       " 874119  2.702502 -14.519687          924            2.818131         2.825007\n",
+       " 874120  2.704204 -14.519766          924            2.815911         2.825007\n",
+       " 874121  2.705906 -14.519842          924            2.813630         2.825007\n",
+       " 874122  2.707608 -14.519917          924            2.811309         2.825007\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 874763  3.798398 -14.524355          924            0.000156         2.825007\n",
+       " 874764  3.800100 -14.524406          924            0.000149         2.825007\n",
+       " 874765  3.801802 -14.524458          924            0.000142         2.825007\n",
+       " 874766  3.803504 -14.524509          924            0.000135         2.825007\n",
+       " 874767  3.805205 -14.524561          924            0.000128         2.825007\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 875118  2.700801 -14.520411          925            2.821643         2.824235\n",
+       " 875119  2.702502 -14.520251          925            2.819422         2.824235\n",
+       " 875120  2.704204 -14.520091          925            2.817201         2.824235\n",
+       " 875121  2.705906 -14.520071          925            2.814975         2.824235\n",
+       " 875122  2.707608 -14.520145          925            2.812746         2.824235\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 875764  3.800100 -14.526169          925            0.000150         2.824235\n",
+       " 875765  3.801802 -14.526236          925            0.000143         2.824235\n",
+       " 875766  3.803504 -14.526301          925            0.000137         2.824235\n",
+       " 875767  3.805205 -14.526367          925            0.000130         2.824235\n",
+       " 875768  3.806907 -14.526433          925            0.000123         2.824235\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 876118  2.700801 -14.519765          926            2.818555           2.8248\n",
+       " 876119  2.702502 -14.520183          926            2.816372           2.8248\n",
+       " 876120  2.704204 -14.520601          926            2.814190           2.8248\n",
+       " 876121  2.705906 -14.520497          926            2.811973           2.8248\n",
+       " 876122  2.707608 -14.520202          926            2.809743           2.8248\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 876764  3.800100 -14.526569          926            0.000151           2.8248\n",
+       " 876765  3.801802 -14.526649          926            0.000144           2.8248\n",
+       " 876766  3.803504 -14.526727          926            0.000137           2.8248\n",
+       " 876767  3.805205 -14.526805          926            0.000130           2.8248\n",
+       " 876768  3.806907 -14.526883          926            0.000123           2.8248\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 877118  2.700801 -14.519625          927            2.818266         2.823561\n",
+       " 877119  2.702502 -14.519744          927            2.816070         2.823561\n",
+       " 877120  2.704204 -14.519838          927            2.813841         2.823561\n",
+       " 877121  2.705906 -14.519912          927            2.811586         2.823561\n",
+       " 877122  2.707608 -14.519986          927            2.809330         2.823561\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 877763  3.798398 -14.526754          927            0.000156         2.823561\n",
+       " 877764  3.800100 -14.526831          927            0.000149         2.823561\n",
+       " 877765  3.801802 -14.526906          927            0.000142         2.823561\n",
+       " 877766  3.803504 -14.526981          927            0.000135         2.823561\n",
+       " 877767  3.805205 -14.527058          927            0.000128         2.823561\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 878118  2.700801 -14.519919          928            2.814883         2.819642\n",
+       " 878119  2.702502 -14.519687          928            2.812695         2.819642\n",
+       " 878120  2.704204 -14.519607          928            2.810490         2.819642\n",
+       " 878121  2.705906 -14.519682          928            2.808267         2.819642\n",
+       " 878122  2.707608 -14.519756          928            2.806045         2.819642\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 878763  3.798398 -14.526130          928            0.000156         2.819642\n",
+       " 878764  3.800100 -14.526194          928            0.000149         2.819642\n",
+       " 878765  3.801802 -14.526257          928            0.000142         2.819642\n",
+       " 878766  3.803504 -14.526320          928            0.000135         2.819642\n",
+       " 878767  3.805205 -14.526384          928            0.000128         2.819642\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 879118  2.700801 -14.519569          929            2.814472         2.818964\n",
+       " 879119  2.702502 -14.519569          929            2.812270         2.818964\n",
+       " 879120  2.704204 -14.519569          929            2.810067         2.818964\n",
+       " 879121  2.705906 -14.519699          929            2.807801         2.818964\n",
+       " 879122  2.707608 -14.519850          929            2.805526         2.818964\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 879763  3.798398 -14.525024          929            0.000154         2.818964\n",
+       " 879764  3.800100 -14.525084          929            0.000147         2.818964\n",
+       " 879765  3.801802 -14.525142          929            0.000140         2.818964\n",
+       " 879766  3.803504 -14.525201          929            0.000133         2.818964\n",
+       " 879767  3.805205 -14.525259          929            0.000126         2.818964\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 880118  2.700801 -14.520027          930            2.817015         2.819318\n",
+       " 880119  2.702502 -14.520027          930            2.814816         2.819318\n",
+       " 880120  2.704204 -14.520027          930            2.812606         2.819318\n",
+       " 880121  2.705906 -14.520027          930            2.810383         2.819318\n",
+       " 880122  2.707608 -14.520027          930            2.808159         2.819318\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 880753  3.781381 -14.521338          930            0.000198         2.819318\n",
+       " 880754  3.783083 -14.521351          930            0.000191         2.819318\n",
+       " 880755  3.784785 -14.521364          930            0.000183         2.819318\n",
+       " 880756  3.786486 -14.521378          930            0.000176         2.819318\n",
+       " 880757  3.788188 -14.521390          930            0.000169         2.819318\n",
+       " \n",
+       " [640 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 881118  2.700801 -14.519631          931            2.813216         2.820185\n",
+       " 881119  2.702502 -14.519753          931            2.811117         2.820185\n",
+       " 881120  2.704204 -14.519939          931            2.808932         2.820185\n",
+       " 881121  2.705906 -14.520164          931            2.806697         2.820185\n",
+       " 881122  2.707608 -14.520391          931            2.804461         2.820185\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 881763  3.798398 -14.526970          931            0.000155         2.820185\n",
+       " 881764  3.800100 -14.527051          931            0.000148         2.820185\n",
+       " 881765  3.801802 -14.527131          931            0.000141         2.820185\n",
+       " 881766  3.803504 -14.527212          931            0.000134         2.820185\n",
+       " 881767  3.805205 -14.527293          931            0.000127         2.820185\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 882118  2.700801 -14.519699          932            2.813368         2.817982\n",
+       " 882119  2.702502 -14.519599          932            2.811249         2.817982\n",
+       " 882120  2.704204 -14.519673          932            2.809040         2.817982\n",
+       " 882121  2.705906 -14.519749          932            2.806830         2.817982\n",
+       " 882122  2.707608 -14.519874          932            2.804632         2.817982\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 882764  3.800100 -14.525711          932            0.000150         2.817982\n",
+       " 882765  3.801802 -14.525778          932            0.000143         2.817982\n",
+       " 882766  3.803504 -14.525844          932            0.000137         2.817982\n",
+       " 882767  3.805205 -14.525909          932            0.000130         2.817982\n",
+       " 882768  3.806907 -14.525975          932            0.000123         2.817982\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 883118  2.700801 -14.520015          933            2.810472         2.815692\n",
+       " 883119  2.702502 -14.520184          933            2.808336         2.815692\n",
+       " 883120  2.704204 -14.520034          933            2.806100         2.815692\n",
+       " 883121  2.705906 -14.519884          933            2.803864         2.815692\n",
+       " 883122  2.707608 -14.519891          933            2.801658         2.815692\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 883763  3.798398 -14.525899          933            0.000155         2.815692\n",
+       " 883764  3.800100 -14.525965          933            0.000148         2.815692\n",
+       " 883765  3.801802 -14.526031          933            0.000141         2.815692\n",
+       " 883766  3.803504 -14.526096          933            0.000134         2.815692\n",
+       " 883767  3.805205 -14.526162          933            0.000127         2.815692\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 884118  2.700801 -14.519798          934            2.809651         2.813142\n",
+       " 884119  2.702502 -14.519798          934            2.807409         2.813142\n",
+       " 884120  2.704204 -14.519798          934            2.805166         2.813142\n",
+       " 884121  2.705906 -14.519798          934            2.802924         2.813142\n",
+       " 884122  2.707608 -14.519867          934            2.800754         2.813142\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 884763  3.798398 -14.525902          934            0.000153         2.813142\n",
+       " 884764  3.800100 -14.525970          934            0.000146         2.813142\n",
+       " 884765  3.801802 -14.526039          934            0.000139         2.813142\n",
+       " 884766  3.803504 -14.526108          934            0.000133         2.813142\n",
+       " 884767  3.805205 -14.526175          934            0.000126         2.813142\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 885118  2.700801 -14.519578          935            2.808326         2.813369\n",
+       " 885119  2.702502 -14.519841          935            2.806217         2.813369\n",
+       " 885120  2.704204 -14.519917          935            2.803942         2.813369\n",
+       " 885121  2.705906 -14.519991          935            2.801666         2.813369\n",
+       " 885122  2.707608 -14.520027          935            2.799432         2.813369\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 885763  3.798398 -14.527003          935            0.000153         2.813369\n",
+       " 885764  3.800100 -14.527081          935            0.000146         2.813369\n",
+       " 885765  3.801802 -14.527160          935            0.000139         2.813369\n",
+       " 885766  3.803504 -14.527238          935            0.000133         2.813369\n",
+       " 885767  3.805205 -14.527316          935            0.000126         2.813369\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 886118  2.700801 -14.519997          936            2.810977         2.813935\n",
+       " 886119  2.702502 -14.520027          936            2.808781         2.813935\n",
+       " 886120  2.704204 -14.520027          936            2.806583         2.813935\n",
+       " 886121  2.705906 -14.520027          936            2.804385         2.813935\n",
+       " 886122  2.707608 -14.520085          936            2.802214         2.813935\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 886763  3.798398 -14.526532          936            0.000155         2.813935\n",
+       " 886764  3.800100 -14.526608          936            0.000148         2.813935\n",
+       " 886765  3.801802 -14.526684          936            0.000142         2.813935\n",
+       " 886766  3.803504 -14.526759          936            0.000135         2.813935\n",
+       " 886767  3.805205 -14.526835          936            0.000128         2.813935\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 887118  2.700801 -14.519874          937            2.808475         2.813934\n",
+       " 887119  2.702502 -14.519587          937            2.806387         2.813934\n",
+       " 887120  2.704204 -14.519808          937            2.804314         2.813934\n",
+       " 887121  2.705906 -14.520030          937            2.802241         2.813934\n",
+       " 887122  2.707608 -14.520252          937            2.800168         2.813934\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 887764  3.800100 -14.525720          937            0.000152         2.813934\n",
+       " 887765  3.801802 -14.525782          937            0.000145         2.813934\n",
+       " 887766  3.803504 -14.525843          937            0.000138         2.813934\n",
+       " 887767  3.805205 -14.525904          937            0.000131         2.813934\n",
+       " 887768  3.806907 -14.525965          937            0.000124         2.813934\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 888118  2.700801 -14.519906          938            2.809168         2.812145\n",
+       " 888119  2.702502 -14.519669          938            2.807117         2.812145\n",
+       " 888120  2.704204 -14.519613          938            2.804944         2.812145\n",
+       " 888121  2.705906 -14.519689          938            2.802681         2.812145\n",
+       " 888122  2.707608 -14.519763          938            2.800419         2.812145\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 888753  3.781381 -14.521337          938            0.000199         2.812145\n",
+       " 888754  3.783083 -14.521350          938            0.000191         2.812145\n",
+       " 888755  3.784785 -14.521363          938            0.000184         2.812145\n",
+       " 888756  3.786486 -14.521376          938            0.000177         2.812145\n",
+       " 888757  3.788188 -14.521389          938            0.000169         2.812145\n",
+       " \n",
+       " [640 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 889118  2.700801 -14.519919          939            2.808978         2.812546\n",
+       " 889119  2.702502 -14.520670          939            2.806755         2.812546\n",
+       " 889120  2.704204 -14.520505          939            2.804600         2.812546\n",
+       " 889121  2.705906 -14.520283          939            2.802449         2.812546\n",
+       " 889122  2.707608 -14.520061          939            2.800297         2.812546\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 889763  3.798398 -14.526530          939            0.000157         2.812546\n",
+       " 889764  3.800100 -14.526604          939            0.000150         2.812546\n",
+       " 889765  3.801802 -14.526677          939            0.000143         2.812546\n",
+       " 889766  3.803504 -14.526751          939            0.000136         2.812546\n",
+       " 889767  3.805205 -14.526824          939            0.000129         2.812546\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 890118  2.700801 -14.520455          940            2.804921         2.812233\n",
+       " 890119  2.702502 -14.520308          940            2.802822         2.812233\n",
+       " 890120  2.704204 -14.520160          940            2.800723         2.812233\n",
+       " 890121  2.705906 -14.520027          940            2.798619         2.812233\n",
+       " 890122  2.707608 -14.520027          940            2.796476         2.812233\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 890763  3.798398 -14.526518          940            0.000156         2.812233\n",
+       " 890764  3.800100 -14.526595          940            0.000149         2.812233\n",
+       " 890765  3.801802 -14.526673          940            0.000142         2.812233\n",
+       " 890766  3.803504 -14.526752          940            0.000135         2.812233\n",
+       " 890767  3.805205 -14.526830          940            0.000128         2.812233\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 891118  2.700801 -14.519981          941            2.806868         2.809185\n",
+       " 891119  2.702502 -14.520027          941            2.804721         2.809185\n",
+       " 891120  2.704204 -14.520027          941            2.802564         2.809185\n",
+       " 891121  2.705906 -14.520027          941            2.800408         2.809185\n",
+       " 891122  2.707608 -14.519904          941            2.798300         2.809185\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 891753  3.781381 -14.520688          941            0.000199         2.809185\n",
+       " 891754  3.783083 -14.520694          941            0.000191         2.809185\n",
+       " 891755  3.784785 -14.520699          941            0.000184         2.809185\n",
+       " 891756  3.786486 -14.520704          941            0.000177         2.809185\n",
+       " 891757  3.788188 -14.520709          941            0.000169         2.809185\n",
+       " \n",
+       " [640 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 892118  2.700801 -14.519850          942            2.806439         2.810791\n",
+       " 892119  2.702502 -14.520131          942            2.804317         2.810791\n",
+       " 892120  2.704204 -14.520279          942            2.802127         2.810791\n",
+       " 892121  2.705906 -14.520428          942            2.799937         2.810791\n",
+       " 892122  2.707608 -14.520485          942            2.797783         2.810791\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 892764  3.800100 -14.523989          942            0.000150         2.810791\n",
+       " 892765  3.801802 -14.524028          942            0.000143         2.810791\n",
+       " 892766  3.803504 -14.524067          942            0.000137         2.810791\n",
+       " 892767  3.805205 -14.524106          942            0.000130         2.810791\n",
+       " 892768  3.806907 -14.524145          942            0.000123         2.810791\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 893118  2.700801 -14.519848          943            2.809291         2.813784\n",
+       " 893119  2.702502 -14.519955          943            2.807136         2.813784\n",
+       " 893120  2.704204 -14.520050          943            2.805004         2.813784\n",
+       " 893121  2.705906 -14.520123          943            2.802922         2.813784\n",
+       " 893122  2.707608 -14.520196          943            2.800840         2.813784\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 893764  3.800100 -14.526141          943            0.000152         2.813784\n",
+       " 893765  3.801802 -14.526210          943            0.000145         2.813784\n",
+       " 893766  3.803504 -14.526278          943            0.000138         2.813784\n",
+       " 893767  3.805205 -14.526346          943            0.000132         2.813784\n",
+       " 893768  3.806907 -14.526415          943            0.000125         2.813784\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 894118  2.700801 -14.520027          944            2.806136         2.810185\n",
+       " 894119  2.702502 -14.520027          944            2.804044         2.810185\n",
+       " 894120  2.704204 -14.520027          944            2.801932         2.810185\n",
+       " 894121  2.705906 -14.520027          944            2.799820         2.810185\n",
+       " 894122  2.707608 -14.520027          944            2.797708         2.810185\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 894764  3.800100 -14.524392          944            0.000152         2.810185\n",
+       " 894765  3.801802 -14.524442          944            0.000146         2.810185\n",
+       " 894766  3.803504 -14.524490          944            0.000139         2.810185\n",
+       " 894767  3.805205 -14.524539          944            0.000132         2.810185\n",
+       " 894768  3.806907 -14.524588          944            0.000125         2.810185\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 895118  2.700801 -14.519694          945            2.806120         2.809341\n",
+       " 895119  2.702502 -14.519963          945            2.804084         2.809341\n",
+       " 895120  2.704204 -14.519971          945            2.801970         2.809341\n",
+       " 895121  2.705906 -14.519897          945            2.799832         2.809341\n",
+       " 895122  2.707608 -14.519823          945            2.797694         2.809341\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 895764  3.800100 -14.525684          945            0.000153         2.809341\n",
+       " 895765  3.801802 -14.525751          945            0.000146         2.809341\n",
+       " 895766  3.803504 -14.525817          945            0.000139         2.809341\n",
+       " 895767  3.805205 -14.525883          945            0.000132         2.809341\n",
+       " 895768  3.806907 -14.525949          945            0.000126         2.809341\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 896118  2.700801 -14.519948          946            2.802891         2.808884\n",
+       " 896119  2.702502 -14.519790          946            2.800761         2.808884\n",
+       " 896120  2.704204 -14.519715          946            2.798622         2.808884\n",
+       " 896121  2.705906 -14.519641          946            2.796484         2.808884\n",
+       " 896122  2.707608 -14.519578          946            2.794344         2.808884\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 896764  3.800100 -14.524383          946            0.000154         2.808884\n",
+       " 896765  3.801802 -14.524432          946            0.000147         2.808884\n",
+       " 896766  3.803504 -14.524481          946            0.000140         2.808884\n",
+       " 896767  3.805205 -14.524529          946            0.000133         2.808884\n",
+       " 896768  3.806907 -14.524579          946            0.000126         2.808884\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 897118  2.700801 -14.519898          947            2.802107         2.805403\n",
+       " 897119  2.702502 -14.519623          947            2.800113         2.805403\n",
+       " 897120  2.704204 -14.519509          947            2.798024         2.805403\n",
+       " 897121  2.705906 -14.519436          947            2.795912         2.805403\n",
+       " 897122  2.707608 -14.519361          947            2.793799         2.805403\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 897764  3.800100 -14.526587          947            0.000150         2.805403\n",
+       " 897765  3.801802 -14.526663          947            0.000143         2.805403\n",
+       " 897766  3.803504 -14.526739          947            0.000137         2.805403\n",
+       " 897767  3.805205 -14.526814          947            0.000130         2.805403\n",
+       " 897768  3.806907 -14.526891          947            0.000123         2.805403\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 898118  2.700801 -14.519798          948            2.800860         2.805701\n",
+       " 898119  2.702502 -14.519847          948            2.798778         2.805701\n",
+       " 898120  2.704204 -14.519921          948            2.796600         2.805701\n",
+       " 898121  2.705906 -14.519995          948            2.794423         2.805701\n",
+       " 898122  2.707608 -14.520027          948            2.792263         2.805701\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 898763  3.798398 -14.526522          948            0.000156         2.805701\n",
+       " 898764  3.800100 -14.526598          948            0.000149         2.805701\n",
+       " 898765  3.801802 -14.526673          948            0.000143         2.805701\n",
+       " 898766  3.803504 -14.526750          948            0.000136         2.805701\n",
+       " 898767  3.805205 -14.526825          948            0.000129         2.805701\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 899118  2.700801 -14.519626          949            2.800414         2.804686\n",
+       " 899119  2.702502 -14.519776          949            2.798271         2.804686\n",
+       " 899120  2.704204 -14.519926          949            2.796128         2.804686\n",
+       " 899121  2.705906 -14.520003          949            2.794009         2.804686\n",
+       " 899122  2.707608 -14.519930          949            2.791940         2.804686\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 899764  3.800100 -14.526176          949            0.000151         2.804686\n",
+       " 899765  3.801802 -14.526240          949            0.000144         2.804686\n",
+       " 899766  3.803504 -14.526303          949            0.000137         2.804686\n",
+       " 899767  3.805205 -14.526367          949            0.000130         2.804686\n",
+       " 899768  3.806907 -14.526430          949            0.000123         2.804686\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 900118  2.700801 -14.520220          950            2.797383         2.803002\n",
+       " 900119  2.702502 -14.520143          950            2.795379         2.803002\n",
+       " 900120  2.704204 -14.520065          950            2.793376         2.803002\n",
+       " 900121  2.705906 -14.519951          950            2.791281         2.803002\n",
+       " 900122  2.707608 -14.519801          950            2.789098         2.803002\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 900753  3.781381 -14.519389          950            0.000197         2.803002\n",
+       " 900754  3.783083 -14.519379          950            0.000190         2.803002\n",
+       " 900755  3.784785 -14.519368          950            0.000182         2.803002\n",
+       " 900756  3.786486 -14.519358          950            0.000175         2.803002\n",
+       " 900757  3.788188 -14.519347          950            0.000168         2.803002\n",
+       " \n",
+       " [640 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 901118  2.700801 -14.520112          951            2.795963         2.800559\n",
+       " 901119  2.702502 -14.519802          951            2.793769         2.800559\n",
+       " 901120  2.704204 -14.519493          951            2.791574         2.800559\n",
+       " 901121  2.705906 -14.519413          951            2.789458         2.800559\n",
+       " 901122  2.707608 -14.519557          951            2.787418         2.800559\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 901763  3.798398 -14.526775          951            0.000154         2.800559\n",
+       " 901764  3.800100 -14.526851          951            0.000147         2.800559\n",
+       " 901765  3.801802 -14.526927          951            0.000140         2.800559\n",
+       " 901766  3.803504 -14.527002          951            0.000133         2.800559\n",
+       " 901767  3.805205 -14.527078          951            0.000127         2.800559\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 902118  2.700801 -14.519968          952            2.795815         2.800238\n",
+       " 902119  2.702502 -14.520027          952            2.793741         2.800238\n",
+       " 902120  2.704204 -14.520027          952            2.791650         2.800238\n",
+       " 902121  2.705906 -14.520027          952            2.789559         2.800238\n",
+       " 902122  2.707608 -14.520027          952            2.787412         2.800238\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 902753  3.781381 -14.520666          952            0.000197         2.800238\n",
+       " 902754  3.783083 -14.520677          952            0.000189         2.800238\n",
+       " 902755  3.784785 -14.520687          952            0.000182         2.800238\n",
+       " 902756  3.786486 -14.520698          952            0.000175         2.800238\n",
+       " 902757  3.788188 -14.520708          952            0.000167         2.800238\n",
+       " \n",
+       " [640 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 903118  2.700801 -14.520209          953            2.795935         2.799916\n",
+       " 903119  2.702502 -14.520109          953            2.793854         2.799916\n",
+       " 903120  2.704204 -14.520014          953            2.791767         2.799916\n",
+       " 903121  2.705906 -14.519939          953            2.789654         2.799916\n",
+       " 903122  2.707608 -14.519866          953            2.787543         2.799916\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 903763  3.798398 -14.526521          953            0.000155         2.799916\n",
+       " 903764  3.800100 -14.526599          953            0.000148         2.799916\n",
+       " 903765  3.801802 -14.526677          953            0.000142         2.799916\n",
+       " 903766  3.803504 -14.526755          953            0.000135         2.799916\n",
+       " 903767  3.805205 -14.526834          953            0.000128         2.799916\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 904118  2.700801 -14.520027          954            2.795248         2.798398\n",
+       " 904119  2.702502 -14.520027          954            2.793248         2.798398\n",
+       " 904120  2.704204 -14.520060          954            2.791189         2.798398\n",
+       " 904121  2.705906 -14.520133          954            2.789056         2.798398\n",
+       " 904122  2.707608 -14.520205          954            2.786922         2.798398\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 904763  3.798398 -14.526105          954            0.000155         2.798398\n",
+       " 904764  3.800100 -14.526175          954            0.000148         2.798398\n",
+       " 904765  3.801802 -14.526246          954            0.000141         2.798398\n",
+       " 904766  3.803504 -14.526317          954            0.000134         2.798398\n",
+       " 904767  3.805205 -14.526388          954            0.000127         2.798398\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 905118  2.700801 -14.519569          955            2.792463          2.79787\n",
+       " 905119  2.702502 -14.519569          955            2.790373          2.79787\n",
+       " 905120  2.704204 -14.519569          955            2.788283          2.79787\n",
+       " 905121  2.705906 -14.519610          955            2.786166          2.79787\n",
+       " 905122  2.707608 -14.519684          955            2.784028          2.79787\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 905763  3.798398 -14.525201          955            0.000156          2.79787\n",
+       " 905764  3.800100 -14.525267          955            0.000149          2.79787\n",
+       " 905765  3.801802 -14.525332          955            0.000142          2.79787\n",
+       " 905766  3.803504 -14.525398          955            0.000135          2.79787\n",
+       " 905767  3.805205 -14.525464          955            0.000128          2.79787\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 906118  2.700801 -14.519758          956            2.792560         2.796118\n",
+       " 906119  2.702502 -14.519673          956            2.790506         2.796118\n",
+       " 906120  2.704204 -14.519588          956            2.788452         2.796118\n",
+       " 906121  2.705906 -14.519686          956            2.786298         2.796118\n",
+       " 906122  2.707608 -14.519836          956            2.784115         2.796118\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 906763  3.798398 -14.526525          956            0.000156         2.796118\n",
+       " 906764  3.800100 -14.526601          956            0.000149         2.796118\n",
+       " 906765  3.801802 -14.526677          956            0.000142         2.796118\n",
+       " 906766  3.803504 -14.526752          956            0.000135         2.796118\n",
+       " 906767  3.805205 -14.526829          956            0.000128         2.796118\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 907118  2.700801 -14.519968          957            2.793039         2.796351\n",
+       " 907119  2.702502 -14.519840          957            2.791059         2.796351\n",
+       " 907120  2.704204 -14.519899          957            2.788988         2.796351\n",
+       " 907121  2.705906 -14.520049          957            2.786871         2.796351\n",
+       " 907122  2.707608 -14.520200          957            2.784754         2.796351\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 907763  3.798398 -14.525045          957            0.000154         2.796351\n",
+       " 907764  3.800100 -14.525099          957            0.000147         2.796351\n",
+       " 907765  3.801802 -14.525152          957            0.000140         2.796351\n",
+       " 907766  3.803504 -14.525206          957            0.000133         2.796351\n",
+       " 907767  3.805205 -14.525260          957            0.000127         2.796351\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 908118  2.700801 -14.520088          958            2.789675         2.796061\n",
+       " 908119  2.702502 -14.520219          958            2.787576         2.796061\n",
+       " 908120  2.704204 -14.520043          958            2.785486         2.796061\n",
+       " 908121  2.705906 -14.519748          958            2.783400         2.796061\n",
+       " 908122  2.707608 -14.519452          958            2.781314         2.796061\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 908763  3.798398 -14.524161          958            0.000154         2.796061\n",
+       " 908764  3.800100 -14.524207          958            0.000147         2.796061\n",
+       " 908765  3.801802 -14.524254          958            0.000141         2.796061\n",
+       " 908766  3.803504 -14.524301          958            0.000134         2.796061\n",
+       " 908767  3.805205 -14.524346          958            0.000127         2.796061\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 909118  2.700801 -14.519997          959            2.790471         2.794668\n",
+       " 909119  2.702502 -14.520422          959            2.788522         2.794668\n",
+       " 909120  2.704204 -14.520293          959            2.786407         2.794668\n",
+       " 909121  2.705906 -14.520068          959            2.784264         2.794668\n",
+       " 909122  2.707608 -14.519842          959            2.782121         2.794668\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 909753  3.781381 -14.521112          959            0.000196         2.794668\n",
+       " 909754  3.783083 -14.521126          959            0.000189         2.794668\n",
+       " 909755  3.784785 -14.521138          959            0.000182         2.794668\n",
+       " 909756  3.786486 -14.521152          959            0.000174         2.794668\n",
+       " 909757  3.788188 -14.521165          959            0.000167         2.794668\n",
+       " \n",
+       " [640 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 910118  2.700801 -14.519894          960            2.788891         2.792805\n",
+       " 910119  2.702502 -14.520001          960            2.786808         2.792805\n",
+       " 910120  2.704204 -14.519926          960            2.784665         2.792805\n",
+       " 910121  2.705906 -14.519851          960            2.782522         2.792805\n",
+       " 910122  2.707608 -14.519777          960            2.780386         2.792805\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 910763  3.798398 -14.525028          960            0.000153         2.792805\n",
+       " 910764  3.800100 -14.525087          960            0.000147         2.792805\n",
+       " 910765  3.801802 -14.525146          960            0.000140         2.792805\n",
+       " 910766  3.803504 -14.525204          960            0.000133         2.792805\n",
+       " 910767  3.805205 -14.525262          960            0.000126         2.792805\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 911118  2.700801 -14.519798          961            2.785661         2.791559\n",
+       " 911119  2.702502 -14.519798          961            2.783527         2.791559\n",
+       " 911120  2.704204 -14.519798          961            2.781394         2.791559\n",
+       " 911121  2.705906 -14.519775          961            2.779264         2.791559\n",
+       " 911122  2.707608 -14.519557          961            2.777170         2.791559\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 911763  3.798398 -14.525694          961            0.000153         2.791559\n",
+       " 911764  3.800100 -14.525757          961            0.000146         2.791559\n",
+       " 911765  3.801802 -14.525820          961            0.000140         2.791559\n",
+       " 911766  3.803504 -14.525883          961            0.000133         2.791559\n",
+       " 911767  3.805205 -14.525947          961            0.000126         2.791559\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 912118  2.700801 -14.519669          962            2.789582         2.791812\n",
+       " 912119  2.702502 -14.519856          962            2.787384         2.791812\n",
+       " 912120  2.704204 -14.520004          962            2.785207         2.791812\n",
+       " 912121  2.705906 -14.520152          962            2.783030         2.791812\n",
+       " 912122  2.707608 -14.520169          962            2.780892         2.791812\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 912763  3.798398 -14.525027          962            0.000155         2.791812\n",
+       " 912764  3.800100 -14.525084          962            0.000148         2.791812\n",
+       " 912765  3.801802 -14.525139          962            0.000141         2.791812\n",
+       " 912766  3.803504 -14.525195          962            0.000134         2.791812\n",
+       " 912767  3.805205 -14.525250          962            0.000127         2.791812\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 913118  2.700801 -14.519822          963            2.787467         2.792166\n",
+       " 913119  2.702502 -14.519896          963            2.785398         2.792166\n",
+       " 913120  2.704204 -14.519968          963            2.783329         2.792166\n",
+       " 913121  2.705906 -14.520041          963            2.781240         2.792166\n",
+       " 913122  2.707608 -14.520114          963            2.779068         2.792166\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 913753  3.781381 -14.520232          963            0.000197         2.792166\n",
+       " 913754  3.783083 -14.520237          963            0.000189         2.792166\n",
+       " 913755  3.784785 -14.520243          963            0.000182         2.792166\n",
+       " 913756  3.786486 -14.520247          963            0.000175         2.792166\n",
+       " 913757  3.788188 -14.520253          963            0.000167         2.792166\n",
+       " \n",
+       " [640 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 914118  2.700801 -14.519813          964            2.784433          2.78951\n",
+       " 914119  2.702502 -14.520034          964            2.782347          2.78951\n",
+       " 914120  2.704204 -14.520256          964            2.780261          2.78951\n",
+       " 914121  2.705906 -14.520478          964            2.778175          2.78951\n",
+       " 914122  2.707608 -14.520413          964            2.776114          2.78951\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 914752  3.779680 -14.520910          964            0.000193          2.78951\n",
+       " 914753  3.781381 -14.520919          964            0.000186          2.78951\n",
+       " 914754  3.783083 -14.520926          964            0.000178          2.78951\n",
+       " 914755  3.784785 -14.520934          964            0.000171          2.78951\n",
+       " 914756  3.786486 -14.520942          964            0.000163          2.78951\n",
+       " \n",
+       " [639 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 915118  2.700801 -14.519945          965            2.783411         2.787752\n",
+       " 915119  2.702502 -14.519823          965            2.781426         2.787752\n",
+       " 915120  2.704204 -14.519971          965            2.779287         2.787752\n",
+       " 915121  2.705906 -14.520119          965            2.777149         2.787752\n",
+       " 915122  2.707608 -14.520246          965            2.775015         2.787752\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 915753  3.781381 -14.520473          965            0.000196         2.787752\n",
+       " 915754  3.783083 -14.520475          965            0.000189         2.787752\n",
+       " 915755  3.784785 -14.520478          965            0.000182         2.787752\n",
+       " 915756  3.786486 -14.520481          965            0.000174         2.787752\n",
+       " 915757  3.788188 -14.520484          965            0.000167         2.787752\n",
+       " \n",
+       " [640 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 916118  2.700801 -14.519981          966            2.781716         2.786846\n",
+       " 916119  2.702502 -14.519900          966            2.779663         2.786846\n",
+       " 916120  2.704204 -14.519756          966            2.777585         2.786846\n",
+       " 916121  2.705906 -14.519612          966            2.775507         2.786846\n",
+       " 916122  2.707608 -14.519725          966            2.773396         2.786846\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 916753  3.781381 -14.519832          966            0.000194         2.786846\n",
+       " 916754  3.783083 -14.519824          966            0.000187         2.786846\n",
+       " 916755  3.784785 -14.519816          966            0.000180         2.786846\n",
+       " 916756  3.786486 -14.519808          966            0.000172         2.786846\n",
+       " 916757  3.788188 -14.519800          966            0.000165         2.786846\n",
+       " \n",
+       " [640 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 917118  2.700801 -14.519869          967            2.779015         2.784718\n",
+       " 917119  2.702502 -14.519798          967            2.776965         2.784718\n",
+       " 917120  2.704204 -14.519798          967            2.774912         2.784718\n",
+       " 917121  2.705906 -14.519798          967            2.772860         2.784718\n",
+       " 917122  2.707608 -14.519843          967            2.770755         2.784718\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 917763  3.798398 -14.525902          967            0.000151         2.784718\n",
+       " 917764  3.800100 -14.525974          967            0.000144         2.784718\n",
+       " 917765  3.801802 -14.526048          967            0.000137         2.784718\n",
+       " 917766  3.803504 -14.526120          967            0.000131         2.784718\n",
+       " 917767  3.805205 -14.526194          967            0.000124         2.784718\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 918118  2.700801 -14.519341          968            2.778782         2.782868\n",
+       " 918119  2.702502 -14.519341          968            2.776761         2.782868\n",
+       " 918120  2.704204 -14.519341          968            2.774740         2.782868\n",
+       " 918121  2.705906 -14.519504          968            2.772669         2.782868\n",
+       " 918122  2.707608 -14.519800          968            2.770557         2.782868\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 918763  3.798398 -14.524418          968            0.000152         2.782868\n",
+       " 918764  3.800100 -14.524462          968            0.000145         2.782868\n",
+       " 918765  3.801802 -14.524506          968            0.000138         2.782868\n",
+       " 918766  3.803504 -14.524549          968            0.000131         2.782868\n",
+       " 918767  3.805205 -14.524592          968            0.000124         2.782868\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 919118  2.700801 -14.519777          969            2.779401         2.783375\n",
+       " 919119  2.702502 -14.519705          969            2.777293         2.783375\n",
+       " 919120  2.704204 -14.519631          969            2.775186         2.783375\n",
+       " 919121  2.705906 -14.519581          969            2.773079         2.783375\n",
+       " 919122  2.707608 -14.519655          969            2.770975         2.783375\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 919763  3.798398 -14.527004          969            0.000153         2.783375\n",
+       " 919764  3.800100 -14.527082          969            0.000146         2.783375\n",
+       " 919765  3.801802 -14.527160          969            0.000139         2.783375\n",
+       " 919766  3.803504 -14.527238          969            0.000132         2.783375\n",
+       " 919767  3.805205 -14.527316          969            0.000126         2.783375\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 920118  2.700801 -14.519972          970            2.778285         2.782762\n",
+       " 920119  2.702502 -14.519853          970            2.776151         2.782762\n",
+       " 920120  2.704204 -14.519798          970            2.774073         2.782762\n",
+       " 920121  2.705906 -14.519798          970            2.772042         2.782762\n",
+       " 920122  2.707608 -14.519798          970            2.770012         2.782762\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 920763  3.798398 -14.525710          970            0.000153         2.782762\n",
+       " 920764  3.800100 -14.525771          970            0.000146         2.782762\n",
+       " 920765  3.801802 -14.525831          970            0.000139         2.782762\n",
+       " 920766  3.803504 -14.525892          970            0.000132         2.782762\n",
+       " 920767  3.805205 -14.525953          970            0.000125         2.782762\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 921118  2.700801 -14.520143          971            2.777797          2.78162\n",
+       " 921119  2.702502 -14.519899          971            2.775741          2.78162\n",
+       " 921120  2.704204 -14.519656          971            2.773685          2.78162\n",
+       " 921121  2.705906 -14.519616          971            2.771620          2.78162\n",
+       " 921122  2.707608 -14.519690          971            2.769551          2.78162\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 921763  3.798398 -14.525695          971            0.000152          2.78162\n",
+       " 921764  3.800100 -14.525760          971            0.000145          2.78162\n",
+       " 921765  3.801802 -14.525826          971            0.000138          2.78162\n",
+       " 921766  3.803504 -14.525891          971            0.000132          2.78162\n",
+       " 921767  3.805205 -14.525957          971            0.000125          2.78162\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 922118  2.700801 -14.520003          972            2.778528         2.782922\n",
+       " 922119  2.702502 -14.519933          972            2.776504         2.782922\n",
+       " 922120  2.704204 -14.519862          972            2.774480         2.782922\n",
+       " 922121  2.705906 -14.519814          972            2.772447         2.782922\n",
+       " 922122  2.707608 -14.519964          972            2.770344         2.782922\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 922763  3.798398 -14.526107          972            0.000153         2.782922\n",
+       " 922764  3.800100 -14.526180          972            0.000147         2.782922\n",
+       " 922765  3.801802 -14.526253          972            0.000140         2.782922\n",
+       " 922766  3.803504 -14.526326          972            0.000133         2.782922\n",
+       " 922767  3.805205 -14.526400          972            0.000126         2.782922\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 923118  2.700801 -14.520027          973            2.775366         2.780436\n",
+       " 923119  2.702502 -14.520027          973            2.773287         2.780436\n",
+       " 923120  2.704204 -14.519994          973            2.771193         2.780436\n",
+       " 923121  2.705906 -14.519920          973            2.769081         2.780436\n",
+       " 923122  2.707608 -14.519846          973            2.766969         2.780436\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 923763  3.798398 -14.525924          973            0.000152         2.780436\n",
+       " 923764  3.800100 -14.525989          973            0.000145         2.780436\n",
+       " 923765  3.801802 -14.526054          973            0.000138         2.780436\n",
+       " 923766  3.803504 -14.526120          973            0.000132         2.780436\n",
+       " 923767  3.805205 -14.526186          973            0.000125         2.780436\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 924118  2.700801 -14.519699          974            2.773994         2.778148\n",
+       " 924119  2.702502 -14.519978          974            2.771998         2.778148\n",
+       " 924120  2.704204 -14.520256          974            2.770003         2.778148\n",
+       " 924121  2.705906 -14.520106          974            2.767833         2.778148\n",
+       " 924122  2.707608 -14.519956          974            2.765663         2.778148\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 924763  3.798398 -14.526143          974            0.000153         2.778148\n",
+       " 924764  3.800100 -14.526209          974            0.000146         2.778148\n",
+       " 924765  3.801802 -14.526275          974            0.000139         2.778148\n",
+       " 924766  3.803504 -14.526340          974            0.000132         2.778148\n",
+       " 924767  3.805205 -14.526406          974            0.000126         2.778148\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 925118  2.700801 -14.520080          975            2.773995         2.777848\n",
+       " 925119  2.702502 -14.520193          975            2.771916         2.777848\n",
+       " 925120  2.704204 -14.520352          975            2.769860         2.777848\n",
+       " 925121  2.705906 -14.520569          975            2.767833         2.777848\n",
+       " 925122  2.707608 -14.520784          975            2.765805         2.777848\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 925753  3.781381 -14.521983          975            0.000195         2.777848\n",
+       " 925754  3.783083 -14.522006          975            0.000188         2.777848\n",
+       " 925755  3.784785 -14.522030          975            0.000181         2.777848\n",
+       " 925756  3.786486 -14.522053          975            0.000174         2.777848\n",
+       " 925757  3.788188 -14.522077          975            0.000166         2.777848\n",
+       " \n",
+       " [640 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 926118  2.700801 -14.520100          976            2.775489         2.779203\n",
+       " 926119  2.702502 -14.520254          976            2.773499         2.779203\n",
+       " 926120  2.704204 -14.520110          976            2.771504         2.779203\n",
+       " 926121  2.705906 -14.519962          976            2.769509         2.779203\n",
+       " 926122  2.707608 -14.519814          976            2.767514         2.779203\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 926763  3.798398 -14.523290          976            0.000155         2.779203\n",
+       " 926764  3.800100 -14.523326          976            0.000148         2.779203\n",
+       " 926765  3.801802 -14.523363          976            0.000141         2.779203\n",
+       " 926766  3.803504 -14.523399          976            0.000134         2.779203\n",
+       " 926767  3.805205 -14.523436          976            0.000127         2.779203\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 927118  2.700801 -14.519753          977            2.770754         2.775939\n",
+       " 927119  2.702502 -14.519654          977            2.768816         2.775939\n",
+       " 927120  2.704204 -14.519580          977            2.766845         2.775939\n",
+       " 927121  2.705906 -14.519656          977            2.764656         2.775939\n",
+       " 927122  2.707608 -14.519732          977            2.762467         2.775939\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 927763  3.798398 -14.524841          977            0.000151         2.775939\n",
+       " 927764  3.800100 -14.524895          977            0.000144         2.775939\n",
+       " 927765  3.801802 -14.524948          977            0.000137         2.775939\n",
+       " 927766  3.803504 -14.525002          977            0.000130         2.775939\n",
+       " 927767  3.805205 -14.525055          977            0.000123         2.775939\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 928118  2.700801 -14.519968          978            2.769594          2.77491\n",
+       " 928119  2.702502 -14.519840          978            2.767593          2.77491\n",
+       " 928120  2.704204 -14.519798          978            2.765491          2.77491\n",
+       " 928121  2.705906 -14.519798          978            2.763339          2.77491\n",
+       " 928122  2.707608 -14.519798          978            2.761188          2.77491\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 928763  3.798398 -14.524817          978            0.000151          2.77491\n",
+       " 928764  3.800100 -14.524875          978            0.000145          2.77491\n",
+       " 928765  3.801802 -14.524933          978            0.000138          2.77491\n",
+       " 928766  3.803504 -14.524991          978            0.000131          2.77491\n",
+       " 928767  3.805205 -14.525049          978            0.000124          2.77491\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 929118  2.700801 -14.519798          979            2.775080         2.776203\n",
+       " 929119  2.702502 -14.519798          979            2.773079         2.776203\n",
+       " 929120  2.704204 -14.519798          979            2.771079         2.776203\n",
+       " 929121  2.705906 -14.519833          979            2.769057         2.776203\n",
+       " 929122  2.707608 -14.519906          979            2.767010         2.776203\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 929764  3.800100 -14.525723          979            0.000150         2.776203\n",
+       " 929765  3.801802 -14.525785          979            0.000143         2.776203\n",
+       " 929766  3.803504 -14.525849          979            0.000136         2.776203\n",
+       " 929767  3.805205 -14.525912          979            0.000130         2.776203\n",
+       " 929768  3.806907 -14.525975          979            0.000123         2.776203\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 930118  2.700801 -14.520027          980            2.767819         2.775653\n",
+       " 930119  2.702502 -14.520027          980            2.765728         2.775653\n",
+       " 930120  2.704204 -14.519958          980            2.763622         2.775653\n",
+       " 930121  2.705906 -14.519886          980            2.761514         2.775653\n",
+       " 930122  2.707608 -14.519813          980            2.759407         2.775653\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 930763  3.798398 -14.525714          980            0.000151         2.775653\n",
+       " 930764  3.800100 -14.525777          980            0.000144         2.775653\n",
+       " 930765  3.801802 -14.525840          980            0.000137         2.775653\n",
+       " 930766  3.803504 -14.525903          980            0.000131         2.775653\n",
+       " 930767  3.805205 -14.525967          980            0.000124         2.775653\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 931118  2.700801 -14.519917          986            2.861994         2.968891\n",
+       " 931119  2.702502 -14.519735          986            2.859259         2.968891\n",
+       " 931120  2.704204 -14.519660          986            2.856468         2.968891\n",
+       " 931121  2.705906 -14.519586          986            2.853676         2.968891\n",
+       " 931122  2.707608 -14.519745          986            2.850896         2.968891\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 931755  3.784785 -14.520245          986            0.000195         2.968891\n",
+       " 931756  3.786486 -14.520247          986            0.000187         2.968891\n",
+       " 931757  3.788188 -14.520250          986            0.000180         2.968891\n",
+       " 931758  3.789890 -14.520252          986            0.000172         2.968891\n",
+       " 931759  3.791592 -14.520255          986            0.000165         2.968891\n",
+       " \n",
+       " [642 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 932118  2.700801 -14.520200          987            2.847491         2.861189\n",
+       " 932119  2.702502 -14.520572          987            2.844825         2.861189\n",
+       " 932120  2.704204 -14.520943          987            2.842159         2.861189\n",
+       " 932121  2.705906 -14.520638          987            2.839325         2.861189\n",
+       " 932122  2.707608 -14.520333          987            2.836492         2.861189\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 932764  3.800100 -14.525219          987            0.000156         2.861189\n",
+       " 932765  3.801802 -14.525280          987            0.000150         2.861189\n",
+       " 932766  3.803504 -14.525341          987            0.000143         2.861189\n",
+       " 932767  3.805205 -14.525402          987            0.000136         2.861189\n",
+       " 932768  3.806907 -14.525463          987            0.000129         2.861189\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 933118  2.700801 -14.519579          988            2.839161         2.849351\n",
+       " 933119  2.702502 -14.519727          988            2.836371         2.849351\n",
+       " 933120  2.704204 -14.519875          988            2.833581         2.849351\n",
+       " 933121  2.705906 -14.520022          988            2.830791         2.849351\n",
+       " 933122  2.707608 -14.520027          988            2.828051         2.849351\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 933754  3.783083 -14.519603          988            0.000194         2.849351\n",
+       " 933755  3.784785 -14.519594          988            0.000187         2.849351\n",
+       " 933756  3.786486 -14.519587          988            0.000179         2.849351\n",
+       " 933757  3.788188 -14.519579          988            0.000172         2.849351\n",
+       " 933758  3.789890 -14.519571          988            0.000164         2.849351\n",
+       " \n",
+       " [641 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 934118  2.700801 -14.519661          989            2.830269         2.842109\n",
+       " 934119  2.702502 -14.519857          989            2.827605         2.842109\n",
+       " 934120  2.704204 -14.520027          989            2.824913         2.842109\n",
+       " 934121  2.705906 -14.520027          989            2.822042         2.842109\n",
+       " 934122  2.707608 -14.520027          989            2.819171         2.842109\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 934754  3.783083 -14.519394          989            0.000193         2.842109\n",
+       " 934755  3.784785 -14.519381          989            0.000185         2.842109\n",
+       " 934756  3.786486 -14.519367          989            0.000178         2.842109\n",
+       " 934757  3.788188 -14.519355          989            0.000171         2.842109\n",
+       " 934758  3.789890 -14.519341          989            0.000163         2.842109\n",
+       " \n",
+       " [641 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 935118  2.700801 -14.519755          990            2.826308         2.833857\n",
+       " 935119  2.702502 -14.519665          990            2.823625         2.833857\n",
+       " 935120  2.704204 -14.519573          990            2.820943         2.833857\n",
+       " 935121  2.705906 -14.519641          990            2.818055         2.833857\n",
+       " 935122  2.707608 -14.519716          990            2.815158         2.833857\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 935764  3.800100 -14.526344          990            0.000153         2.833857\n",
+       " 935765  3.801802 -14.526417          990            0.000146         2.833857\n",
+       " 935766  3.803504 -14.526490          990            0.000139         2.833857\n",
+       " 935767  3.805205 -14.526563          990            0.000132         2.833857\n",
+       " 935768  3.806907 -14.526636          990            0.000125         2.833857\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 936118  2.700801 -14.520106          991            2.821178         2.829278\n",
+       " 936119  2.702502 -14.520277          991            2.818479         2.829278\n",
+       " 936120  2.704204 -14.520447          991            2.815781         2.829278\n",
+       " 936121  2.705906 -14.520310          991            2.813020         2.829278\n",
+       " 936122  2.707608 -14.520085          991            2.810242         2.829278\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 936763  3.798398 -14.526111          991            0.000155         2.829278\n",
+       " 936764  3.800100 -14.526179          991            0.000148         2.829278\n",
+       " 936765  3.801802 -14.526247          991            0.000141         2.829278\n",
+       " 936766  3.803504 -14.526316          991            0.000135         2.829278\n",
+       " 936767  3.805205 -14.526383          991            0.000128         2.829278\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 937118  2.700801 -14.520121          992            2.814637         2.824481\n",
+       " 937119  2.702502 -14.520180          992            2.811962         2.824481\n",
+       " 937120  2.704204 -14.519879          992            2.809171         2.824481\n",
+       " 937121  2.705906 -14.519579          992            2.806379         2.824481\n",
+       " 937122  2.707608 -14.519341          992            2.803594         2.824481\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 937763  3.798398 -14.526326          992            0.000155         2.824481\n",
+       " 937764  3.800100 -14.526397          992            0.000149         2.824481\n",
+       " 937765  3.801802 -14.526467          992            0.000142         2.824481\n",
+       " 937766  3.803504 -14.526537          992            0.000135         2.824481\n",
+       " 937767  3.805205 -14.526608          992            0.000128         2.824481\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 938118  2.700801 -14.519991          993            2.808036         2.816758\n",
+       " 938119  2.702502 -14.519914          993            2.805351         2.816758\n",
+       " 938120  2.704204 -14.519836          993            2.802666         2.816758\n",
+       " 938121  2.705906 -14.519798          993            2.799953         2.816758\n",
+       " 938122  2.707608 -14.519798          993            2.797215         2.816758\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 938763  3.798398 -14.525683          993            0.000154         2.816758\n",
+       " 938764  3.800100 -14.525746          993            0.000148         2.816758\n",
+       " 938765  3.801802 -14.525809          993            0.000141         2.816758\n",
+       " 938766  3.803504 -14.525872          993            0.000134         2.816758\n",
+       " 938767  3.805205 -14.525935          993            0.000127         2.816758\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 939118  2.700801 -14.519872          994            2.803149         2.811524\n",
+       " 939119  2.702502 -14.520094          994            2.800451         2.811524\n",
+       " 939120  2.704204 -14.520316          994            2.797752         2.811524\n",
+       " 939121  2.705906 -14.520432          994            2.795056         2.811524\n",
+       " 939122  2.707608 -14.520206          994            2.792370         2.811524\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 939763  3.798398 -14.526139          994            0.000151         2.811524\n",
+       " 939764  3.800100 -14.526209          994            0.000145         2.811524\n",
+       " 939765  3.801802 -14.526279          994            0.000138         2.811524\n",
+       " 939766  3.803504 -14.526349          994            0.000131         2.811524\n",
+       " 939767  3.805205 -14.526420          994            0.000124         2.811524\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 940118  2.700801 -14.519607          995            2.798329         2.805817\n",
+       " 940119  2.702502 -14.519687          995            2.795672         2.805817\n",
+       " 940120  2.704204 -14.519766          995            2.793016         2.805817\n",
+       " 940121  2.705906 -14.519798          995            2.790388         2.805817\n",
+       " 940122  2.707608 -14.519798          995            2.787781         2.805817\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 940763  3.798398 -14.527024          995            0.000151         2.805817\n",
+       " 940764  3.800100 -14.527102          995            0.000144         2.805817\n",
+       " 940765  3.801802 -14.527179          995            0.000138         2.805817\n",
+       " 940766  3.803504 -14.527256          995            0.000131         2.805817\n",
+       " 940767  3.805205 -14.527333          995            0.000124         2.805817\n",
+       " \n",
+       " [650 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 941118  2.700801 -14.519922          996            2.796248         2.802304\n",
+       " 941119  2.702502 -14.520027          996            2.793738         2.802304\n",
+       " 941120  2.704204 -14.520027          996            2.791078         2.802304\n",
+       " 941121  2.705906 -14.520027          996            2.788419         2.802304\n",
+       " 941122  2.707608 -14.520027          996            2.785691         2.802304\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 941762  3.796697 -14.524572          996            0.000156         2.802304\n",
+       " 941763  3.798398 -14.524626          996            0.000149         2.802304\n",
+       " 941764  3.800100 -14.524678          996            0.000142         2.802304\n",
+       " 941765  3.801802 -14.524732          996            0.000136         2.802304\n",
+       " 941766  3.803504 -14.524785          996            0.000129         2.802304\n",
+       " \n",
+       " [649 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 942118  2.700801 -14.520027          997            2.794583         2.801079\n",
+       " 942119  2.702502 -14.520027          997            2.792024         2.801079\n",
+       " 942120  2.704204 -14.519959          997            2.789444         2.801079\n",
+       " 942121  2.705906 -14.519810          997            2.786838         2.801079\n",
+       " 942122  2.707608 -14.519659          997            2.784232         2.801079\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 942762  3.796697 -14.526979          997            0.000156         2.801079\n",
+       " 942763  3.798398 -14.527055          997            0.000149         2.801079\n",
+       " 942764  3.800100 -14.527129          997            0.000143         2.801079\n",
+       " 942765  3.801802 -14.527205          997            0.000136         2.801079\n",
+       " 942766  3.803504 -14.527279          997            0.000129         2.801079\n",
+       " \n",
+       " [649 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 943118  2.700801 -14.519951          998            2.788777         2.797581\n",
+       " 943119  2.702502 -14.519786          998            2.786137         2.797581\n",
+       " 943120  2.704204 -14.519621          998            2.783496         2.797581\n",
+       " 943121  2.705906 -14.519775          998            2.780815         2.797581\n",
+       " 943122  2.707608 -14.520076          998            2.778116         2.797581\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 943762  3.796697 -14.526316          998            0.000155         2.797581\n",
+       " 943763  3.798398 -14.526388          998            0.000148         2.797581\n",
+       " 943764  3.800100 -14.526461          998            0.000142         2.797581\n",
+       " 943765  3.801802 -14.526532          998            0.000135         2.797581\n",
+       " 943766  3.803504 -14.526605          998            0.000128         2.797581\n",
+       " \n",
+       " [649 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 944118  2.700801 -14.519689          999            2.789252         2.793087\n",
+       " 944119  2.702502 -14.519453          999            2.786678         2.793087\n",
+       " 944120  2.704204 -14.519217          999            2.784104         2.793087\n",
+       " 944121  2.705906 -14.519279          999            2.781453         2.793087\n",
+       " 944122  2.707608 -14.519585          999            2.778741         2.793087\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 944762  3.796697 -14.526968          999            0.000156         2.793087\n",
+       " 944763  3.798398 -14.527045          999            0.000149         2.793087\n",
+       " 944764  3.800100 -14.527122          999            0.000143         2.793087\n",
+       " 944765  3.801802 -14.527200          999            0.000136         2.793087\n",
+       " 944766  3.803504 -14.527277          999            0.000129         2.793087\n",
+       " \n",
+       " [649 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 945118  2.700801 -14.519399         1000            2.783568         2.792287\n",
+       " 945119  2.702502 -14.519523         1000            2.781001         2.792287\n",
+       " 945120  2.704204 -14.519477         1000            2.778384         2.792287\n",
+       " 945121  2.705906 -14.519328         1000            2.775738         2.792287\n",
+       " 945122  2.707608 -14.519180         1000            2.773091         2.792287\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 945752  3.779680 -14.520425         1000            0.000197         2.792287\n",
+       " 945753  3.781381 -14.520437         1000            0.000190         2.792287\n",
+       " 945754  3.783083 -14.520451         1000            0.000182         2.792287\n",
+       " 945755  3.784785 -14.520463         1000            0.000175         2.792287\n",
+       " 945756  3.786486 -14.520476         1000            0.000168         2.792287\n",
+       " \n",
+       " [639 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 946118  2.700801 -14.519646         1001            2.782983         2.788401\n",
+       " 946119  2.702502 -14.519798         1001            2.780534         2.788401\n",
+       " 946120  2.704204 -14.519798         1001            2.777941         2.788401\n",
+       " 946121  2.705906 -14.519798         1001            2.775348         2.788401\n",
+       " 946122  2.707608 -14.519798         1001            2.772753         2.788401\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 946764  3.800100 -14.525925         1001            0.000150         2.788401\n",
+       " 946765  3.801802 -14.525993         1001            0.000143         2.788401\n",
+       " 946766  3.803504 -14.526063         1001            0.000136         2.788401\n",
+       " 946767  3.805205 -14.526132         1001            0.000130         2.788401\n",
+       " 946768  3.806907 -14.526201         1001            0.000123         2.788401\n",
+       " \n",
+       " [651 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 947118  2.700801 -14.519914         1002            2.780400         2.786368\n",
+       " 947119  2.702502 -14.519869         1002            2.777942         2.786368\n",
+       " 947120  2.704204 -14.520018         1002            2.775321         2.786368\n",
+       " 947121  2.705906 -14.520165         1002            2.772701         2.786368\n",
+       " 947122  2.707608 -14.520201         1002            2.770109         2.786368\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 947762  3.796697 -14.525720         1002            0.000153         2.786368\n",
+       " 947763  3.798398 -14.525778         1002            0.000146         2.786368\n",
+       " 947764  3.800100 -14.525835         1002            0.000139         2.786368\n",
+       " 947765  3.801802 -14.525893         1002            0.000132         2.786368\n",
+       " 947766  3.803504 -14.525951         1002            0.000126         2.786368\n",
+       " \n",
+       " [649 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 948118  2.700801 -14.519803         1003            2.777665          2.78406\n",
+       " 948119  2.702502 -14.519878         1003            2.775072          2.78406\n",
+       " 948120  2.704204 -14.519953         1003            2.772479          2.78406\n",
+       " 948121  2.705906 -14.520027         1003            2.769886          2.78406\n",
+       " 948122  2.707608 -14.520027         1003            2.767305          2.78406\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 948752  3.779680 -14.521573         1003            0.000194          2.78406\n",
+       " 948753  3.781381 -14.521586         1003            0.000187          2.78406\n",
+       " 948754  3.783083 -14.521599         1003            0.000180          2.78406\n",
+       " 948755  3.784785 -14.521612         1003            0.000173          2.78406\n",
+       " 948756  3.786486 -14.521625         1003            0.000165          2.78406\n",
+       " \n",
+       " [639 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 949118  2.700801 -14.520027         1004            2.777339         2.781802\n",
+       " 949119  2.702502 -14.519985         1004            2.774785         2.781802\n",
+       " 949120  2.704204 -14.519911         1004            2.772203         2.781802\n",
+       " 949121  2.705906 -14.519837         1004            2.769622         2.781802\n",
+       " 949122  2.707608 -14.519834         1004            2.767053         2.781802\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 949762  3.796697 -14.526988         1004            0.000154         2.781802\n",
+       " 949763  3.798398 -14.527068         1004            0.000147         2.781802\n",
+       " 949764  3.800100 -14.527147         1004            0.000140         2.781802\n",
+       " 949765  3.801802 -14.527227         1004            0.000133         2.781802\n",
+       " 949766  3.803504 -14.527307         1004            0.000126         2.781802\n",
+       " \n",
+       " [649 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 950118  2.700801 -14.520131         1005            2.777274         2.781791\n",
+       " 950119  2.702502 -14.519862         1005            2.774788         2.781791\n",
+       " 950120  2.704204 -14.519740         1005            2.772273         2.781791\n",
+       " 950121  2.705906 -14.519664         1005            2.769749         2.781791\n",
+       " 950122  2.707608 -14.519588         1005            2.767225         2.781791\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 950762  3.796697 -14.524598         1005            0.000154         2.781791\n",
+       " 950763  3.798398 -14.524649         1005            0.000147         2.781791\n",
+       " 950764  3.800100 -14.524699         1005            0.000141         2.781791\n",
+       " 950765  3.801802 -14.524750         1005            0.000134         2.781791\n",
+       " 950766  3.803504 -14.524800         1005            0.000127         2.781791\n",
+       " \n",
+       " [649 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 951118  2.700801 -14.519414         1006            2.773283         2.779914\n",
+       " 951119  2.702502 -14.519636         1006            2.770766         2.779914\n",
+       " 951120  2.704204 -14.519858         1006            2.768250         2.779914\n",
+       " 951121  2.705906 -14.520010         1006            2.765715         2.779914\n",
+       " 951122  2.707608 -14.519936         1006            2.763121         2.779914\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 951762  3.796697 -14.525030         1006            0.000152         2.779914\n",
+       " 951763  3.798398 -14.525091         1006            0.000145         2.779914\n",
+       " 951764  3.800100 -14.525151         1006            0.000138         2.779914\n",
+       " 951765  3.801802 -14.525211         1006            0.000132         2.779914\n",
+       " 951766  3.803504 -14.525271         1006            0.000125         2.779914\n",
+       " \n",
+       " [649 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 952118  2.700801 -14.519755         1007            2.769142         2.776407\n",
+       " 952119  2.702502 -14.519662         1007            2.766688         2.776407\n",
+       " 952120  2.704204 -14.519569         1007            2.764235         2.776407\n",
+       " 952121  2.705906 -14.519569         1007            2.761697         2.776407\n",
+       " 952122  2.707608 -14.519569         1007            2.759159         2.776407\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 952762  3.796697 -14.526165         1007            0.000150         2.776407\n",
+       " 952763  3.798398 -14.526233         1007            0.000143         2.776407\n",
+       " 952764  3.800100 -14.526299         1007            0.000136         2.776407\n",
+       " 952765  3.801802 -14.526367         1007            0.000129         2.776407\n",
+       " 952766  3.803504 -14.526434         1007            0.000123         2.776407\n",
+       " \n",
+       " [649 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 953118  2.700801 -14.520256         1008            2.769583          2.77277\n",
+       " 953119  2.702502 -14.519891         1008            2.767099          2.77277\n",
+       " 953120  2.704204 -14.519515         1008            2.764612          2.77277\n",
+       " 953121  2.705906 -14.519140         1008            2.762125          2.77277\n",
+       " 953122  2.707608 -14.519459         1008            2.759650          2.77277\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 953752  3.779680 -14.520474         1008            0.000193          2.77277\n",
+       " 953753  3.781381 -14.520476         1008            0.000186          2.77277\n",
+       " 953754  3.783083 -14.520479         1008            0.000179          2.77277\n",
+       " 953755  3.784785 -14.520482         1008            0.000171          2.77277\n",
+       " 953756  3.786486 -14.520485         1008            0.000164          2.77277\n",
+       " \n",
+       " [639 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 954118  2.700801 -14.520027         1009            2.765978         2.774086\n",
+       " 954119  2.702502 -14.520027         1009            2.763487         2.774086\n",
+       " 954120  2.704204 -14.520080         1009            2.760976         2.774086\n",
+       " 954121  2.705906 -14.520152         1009            2.758457         2.774086\n",
+       " 954122  2.707608 -14.520226         1009            2.755938         2.774086\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 954751  3.777978 -14.518730         1009            0.000199         2.774086\n",
+       " 954752  3.779680 -14.518715         1009            0.000192         2.774086\n",
+       " 954753  3.781381 -14.518700         1009            0.000184         2.774086\n",
+       " 954754  3.783083 -14.518684         1009            0.000177         2.774086\n",
+       " 954755  3.784785 -14.518669         1009            0.000170         2.774086\n",
+       " \n",
+       " [638 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 955118  2.700801 -14.519798         1010            2.764953         2.770202\n",
+       " 955119  2.702502 -14.519798         1010            2.762511         2.770202\n",
+       " 955120  2.704204 -14.519798         1010            2.760069         2.770202\n",
+       " 955121  2.705906 -14.519869         1010            2.757593         2.770202\n",
+       " 955122  2.707608 -14.519943         1010            2.755116         2.770202\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 955762  3.796697 -14.526149         1010            0.000150         2.770202\n",
+       " 955763  3.798398 -14.526218         1010            0.000144         2.770202\n",
+       " 955764  3.800100 -14.526288         1010            0.000137         2.770202\n",
+       " 955765  3.801802 -14.526359         1010            0.000130         2.770202\n",
+       " 955766  3.803504 -14.526428         1010            0.000123         2.770202\n",
+       " \n",
+       " [649 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 956118  2.700801 -14.520256         1011            2.763803         2.769624\n",
+       " 956119  2.702502 -14.520256         1011            2.761404         2.769624\n",
+       " 956120  2.704204 -14.520229         1011            2.758986         2.769624\n",
+       " 956121  2.705906 -14.520082         1011            2.756483         2.769624\n",
+       " 956122  2.707608 -14.519934         1011            2.753980         2.769624\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 956761  3.794995 -14.526510         1011            0.000156         2.769624\n",
+       " 956762  3.796697 -14.526587         1011            0.000150         2.769624\n",
+       " 956763  3.798398 -14.526664         1011            0.000143         2.769624\n",
+       " 956764  3.800100 -14.526741         1011            0.000136         2.769624\n",
+       " 956765  3.801802 -14.526818         1011            0.000129         2.769624\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 957118  2.700801 -14.519798         1012            2.763661         2.767539\n",
+       " 957119  2.702502 -14.519798         1012            2.761197         2.767539\n",
+       " 957120  2.704204 -14.519798         1012            2.758755         2.767539\n",
+       " 957121  2.705906 -14.519798         1012            2.756314         2.767539\n",
+       " 957122  2.707608 -14.519798         1012            2.753812         2.767539\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 957762  3.796697 -14.525054         1012            0.000152         2.767539\n",
+       " 957763  3.798398 -14.525109         1012            0.000145         2.767539\n",
+       " 957764  3.800100 -14.525165         1012            0.000138         2.767539\n",
+       " 957765  3.801802 -14.525220         1012            0.000131         2.767539\n",
+       " 957766  3.803504 -14.525275         1012            0.000124         2.767539\n",
+       " \n",
+       " [649 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 958118  2.700801 -14.519626         1013            2.760223         2.767617\n",
+       " 958119  2.702502 -14.519748         1013            2.757846         2.767617\n",
+       " 958120  2.704204 -14.519886         1013            2.755404         2.767617\n",
+       " 958121  2.705906 -14.520036         1013            2.752917         2.767617\n",
+       " 958122  2.707608 -14.520186         1013            2.750430         2.767617\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 958762  3.796697 -14.523485         1013            0.000153         2.767617\n",
+       " 958763  3.798398 -14.523531         1013            0.000146         2.767617\n",
+       " 958764  3.800100 -14.523577         1013            0.000139         2.767617\n",
+       " 958765  3.801802 -14.523623         1013            0.000132         2.767617\n",
+       " 958766  3.803504 -14.523668         1013            0.000126         2.767617\n",
+       " \n",
+       " [649 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 959118  2.700801 -14.520080         1014            2.758262         2.762297\n",
+       " 959119  2.702502 -14.519760         1014            2.755831         2.762297\n",
+       " 959120  2.704204 -14.519612         1014            2.753406         2.762297\n",
+       " 959121  2.705906 -14.519464         1014            2.750981         2.762297\n",
+       " 959122  2.707608 -14.519328         1014            2.748544         2.762297\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 959752  3.779680 -14.520661         1014            0.000193         2.762297\n",
+       " 959753  3.781381 -14.520674         1014            0.000185         2.762297\n",
+       " 959754  3.783083 -14.520687         1014            0.000178         2.762297\n",
+       " 959755  3.784785 -14.520700         1014            0.000171         2.762297\n",
+       " 959756  3.786486 -14.520712         1014            0.000164         2.762297\n",
+       " \n",
+       " [639 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 960118  2.700801 -14.520027         1015            2.757206         2.761957\n",
+       " 960119  2.702502 -14.520105         1015            2.754768         2.761957\n",
+       " 960120  2.704204 -14.520330         1015            2.752347         2.761957\n",
+       " 960121  2.705906 -14.520555         1015            2.749926         2.761957\n",
+       " 960122  2.707608 -14.520647         1015            2.747489         2.761957\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 960762  3.796697 -14.527042         1015            0.000151         2.761957\n",
+       " 960763  3.798398 -14.527117         1015            0.000144         2.761957\n",
+       " 960764  3.800100 -14.527191         1015            0.000137         2.761957\n",
+       " 960765  3.801802 -14.527266         1015            0.000130         2.761957\n",
+       " 960766  3.803504 -14.527340         1015            0.000124         2.761957\n",
+       " \n",
+       " [649 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 961118  2.700801 -14.520027         1016            2.755961         2.761293\n",
+       " 961119  2.702502 -14.520033         1016            2.753688         2.761293\n",
+       " 961120  2.704204 -14.520105         1016            2.751297         2.761293\n",
+       " 961121  2.705906 -14.520179         1016            2.748907         2.761293\n",
+       " 961122  2.707608 -14.520251         1016            2.746516         2.761293\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 961761  3.794995 -14.524137         1016            0.000155         2.761293\n",
+       " 961762  3.796697 -14.524187         1016            0.000148         2.761293\n",
+       " 961763  3.798398 -14.524237         1016            0.000141         2.761293\n",
+       " 961764  3.800100 -14.524287         1016            0.000134         2.761293\n",
+       " 961765  3.801802 -14.524338         1016            0.000128         2.761293\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 962118  2.700801 -14.519989         1017            2.757320         2.761392\n",
+       " 962119  2.702502 -14.520501         1017            2.754952         2.761392\n",
+       " 962120  2.704204 -14.520057         1017            2.752501         2.761392\n",
+       " 962121  2.705906 -14.519613         1017            2.750050         2.761392\n",
+       " 962122  2.707608 -14.519482         1017            2.747623         2.761392\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 962752  3.779680 -14.520693         1017            0.000192         2.761392\n",
+       " 962753  3.781381 -14.520699         1017            0.000185         2.761392\n",
+       " 962754  3.783083 -14.520703         1017            0.000178         2.761392\n",
+       " 962755  3.784785 -14.520708         1017            0.000170         2.761392\n",
+       " 962756  3.786486 -14.520714         1017            0.000163         2.761392\n",
+       " \n",
+       " [639 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 963118  2.700801 -14.519517         1018            2.753258          2.75961\n",
+       " 963119  2.702502 -14.519837         1018            2.750950          2.75961\n",
+       " 963120  2.704204 -14.519990         1018            2.748519          2.75961\n",
+       " 963121  2.705906 -14.520142         1018            2.746089          2.75961\n",
+       " 963122  2.707608 -14.520200         1018            2.743654          2.75961\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 963762  3.796697 -14.524834         1018            0.000152          2.75961\n",
+       " 963763  3.798398 -14.524886         1018            0.000145          2.75961\n",
+       " 963764  3.800100 -14.524940         1018            0.000138          2.75961\n",
+       " 963765  3.801802 -14.524992         1018            0.000132          2.75961\n",
+       " 963766  3.803504 -14.525044         1018            0.000125          2.75961\n",
+       " \n",
+       " [649 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 964118  2.700801 -14.520433         1019            2.751647         2.756854\n",
+       " 964119  2.702502 -14.520322         1019            2.749300         2.756854\n",
+       " 964120  2.704204 -14.520166         1019            2.746922         2.756854\n",
+       " 964121  2.705906 -14.519944         1019            2.744496         2.756854\n",
+       " 964122  2.707608 -14.519723         1019            2.742071         2.756854\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 964762  3.796697 -14.525273         1019            0.000150         2.756854\n",
+       " 964763  3.798398 -14.525333         1019            0.000144         2.756854\n",
+       " 964764  3.800100 -14.525393         1019            0.000137         2.756854\n",
+       " 964765  3.801802 -14.525454         1019            0.000130         2.756854\n",
+       " 964766  3.803504 -14.525514         1019            0.000123         2.756854\n",
+       " \n",
+       " [649 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 965118  2.700801 -14.519710         1020            2.749632         2.755344\n",
+       " 965119  2.702502 -14.519798         1020            2.747271         2.755344\n",
+       " 965120  2.704204 -14.519798         1020            2.744829         2.755344\n",
+       " 965121  2.705906 -14.519798         1020            2.742387         2.755344\n",
+       " 965122  2.707608 -14.519920         1020            2.740001         2.755344\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 965761  3.794995 -14.524807         1020            0.000155         2.755344\n",
+       " 965762  3.796697 -14.524859         1020            0.000149         2.755344\n",
+       " 965763  3.798398 -14.524912         1020            0.000142         2.755344\n",
+       " 965764  3.800100 -14.524965         1020            0.000135         2.755344\n",
+       " 965765  3.801802 -14.525018         1020            0.000128         2.755344\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 966118  2.700801 -14.519569         1021            2.748622         2.753255\n",
+       " 966119  2.702502 -14.519569         1021            2.746210         2.753255\n",
+       " 966120  2.704204 -14.519569         1021            2.743798         2.753255\n",
+       " 966121  2.705906 -14.519578         1021            2.741387         2.753255\n",
+       " 966122  2.707608 -14.519724         1021            2.738984         2.753255\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 966762  3.796697 -14.524870         1021            0.000150         2.753255\n",
+       " 966763  3.798398 -14.524918         1021            0.000143         2.753255\n",
+       " 966764  3.800100 -14.524965         1021            0.000136         2.753255\n",
+       " 966765  3.801802 -14.525014         1021            0.000129         2.753255\n",
+       " 966766  3.803504 -14.525062         1021            0.000123         2.753255\n",
+       " \n",
+       " [649 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 967118  2.700801 -14.520027         1022            2.747762         2.751395\n",
+       " 967119  2.702502 -14.520027         1022            2.745388         2.751395\n",
+       " 967120  2.704204 -14.520027         1022            2.742993         2.751395\n",
+       " 967121  2.705906 -14.520027         1022            2.740594         2.751395\n",
+       " 967122  2.707608 -14.520027         1022            2.738195         2.751395\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 967761  3.794995 -14.524576         1022            0.000156         2.751395\n",
+       " 967762  3.796697 -14.524629         1022            0.000149         2.751395\n",
+       " 967763  3.798398 -14.524681         1022            0.000142         2.751395\n",
+       " 967764  3.800100 -14.524734         1022            0.000135         2.751395\n",
+       " 967765  3.801802 -14.524787         1022            0.000128         2.751395\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 968118  2.700801 -14.519588         1023            2.745589         2.751281\n",
+       " 968119  2.702502 -14.519661         1023            2.743203         2.751281\n",
+       " 968120  2.704204 -14.519735         1023            2.740817         2.751281\n",
+       " 968121  2.705906 -14.519810         1023            2.738445         2.751281\n",
+       " 968122  2.707608 -14.519883         1023            2.736150         2.751281\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 968751  3.777978 -14.518705         1023            0.000199         2.751281\n",
+       " 968752  3.779680 -14.518695         1023            0.000192         2.751281\n",
+       " 968753  3.781381 -14.518684         1023            0.000184         2.751281\n",
+       " 968754  3.783083 -14.518674         1023            0.000177         2.751281\n",
+       " 968755  3.784785 -14.518664         1023            0.000170         2.751281\n",
+       " \n",
+       " [638 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 969118  2.700801 -14.519728         1024            2.747674         2.750402\n",
+       " 969119  2.702502 -14.520027         1024            2.745487         2.750402\n",
+       " 969120  2.704204 -14.520027         1024            2.743122         2.750402\n",
+       " 969121  2.705906 -14.520027         1024            2.740757         2.750402\n",
+       " 969122  2.707608 -14.520027         1024            2.738393         2.750402\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 969762  3.796697 -14.524413         1024            0.000151         2.750402\n",
+       " 969763  3.798398 -14.524459         1024            0.000144         2.750402\n",
+       " 969764  3.800100 -14.524505         1024            0.000137         2.750402\n",
+       " 969765  3.801802 -14.524550         1024            0.000131         2.750402\n",
+       " 969766  3.803504 -14.524595         1024            0.000124         2.750402\n",
+       " \n",
+       " [649 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 970118  2.700801 -14.519665         1025            2.747350         2.751318\n",
+       " 970119  2.702502 -14.519953         1025            2.745082         2.751318\n",
+       " 970120  2.704204 -14.520240         1025            2.742814         2.751318\n",
+       " 970121  2.705906 -14.520452         1025            2.740541         2.751318\n",
+       " 970122  2.707608 -14.520226         1025            2.738239         2.751318\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 970762  3.796697 -14.526796         1025            0.000151         2.751318\n",
+       " 970763  3.798398 -14.526874         1025            0.000144         2.751318\n",
+       " 970764  3.800100 -14.526950         1025            0.000138         2.751318\n",
+       " 970765  3.801802 -14.527027         1025            0.000131         2.751318\n",
+       " 970766  3.803504 -14.527103         1025            0.000124         2.751318\n",
+       " \n",
+       " [649 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 971118  2.700801 -14.519798         1026            2.751280         2.757419\n",
+       " 971119  2.702502 -14.519798         1026            2.749012         2.757419\n",
+       " 971120  2.704204 -14.519845         1026            2.746703         2.757419\n",
+       " 971121  2.705906 -14.519993         1026            2.744304         2.757419\n",
+       " 971122  2.707608 -14.520141         1026            2.741905         2.757419\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 971762  3.796697 -14.524597         1026            0.000156         2.757419\n",
+       " 971763  3.798398 -14.524646         1026            0.000149         2.757419\n",
+       " 971764  3.800100 -14.524693         1026            0.000142         2.757419\n",
+       " 971765  3.801802 -14.524741         1026            0.000135         2.757419\n",
+       " 971766  3.803504 -14.524790         1026            0.000129         2.757419\n",
+       " \n",
+       " [649 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 972118  2.700801 -14.519989         1027            2.741794         2.747107\n",
+       " 972119  2.702502 -14.519908         1027            2.739509         2.747107\n",
+       " 972120  2.704204 -14.519827         1027            2.737225         2.747107\n",
+       " 972121  2.705906 -14.519846         1027            2.734917         2.747107\n",
+       " 972122  2.707608 -14.519919         1027            2.732596         2.747107\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 972751  3.777978 -14.519798         1027            0.000198         2.747107\n",
+       " 972752  3.779680 -14.519798         1027            0.000191         2.747107\n",
+       " 972753  3.781381 -14.519798         1027            0.000184         2.747107\n",
+       " 972754  3.783083 -14.519798         1027            0.000177         2.747107\n",
+       " 972755  3.784785 -14.519798         1027            0.000170         2.747107\n",
+       " \n",
+       " [638 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 973118  2.700801 -14.519885         1028            2.740017         2.744768\n",
+       " 973119  2.702502 -14.520070         1028            2.737727         2.744768\n",
+       " 973120  2.704204 -14.520256         1028            2.735437         2.744768\n",
+       " 973121  2.705906 -14.520031         1028            2.733069         2.744768\n",
+       " 973122  2.707608 -14.519806         1028            2.730701         2.744768\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 973761  3.794995 -14.525007         1028            0.000155         2.744768\n",
+       " 973762  3.796697 -14.525067         1028            0.000148         2.744768\n",
+       " 973763  3.798398 -14.525126         1028            0.000141         2.744768\n",
+       " 973764  3.800100 -14.525187         1028            0.000134         2.744768\n",
+       " 973765  3.801802 -14.525247         1028            0.000128         2.744768\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 974118  2.700801 -14.520256         1029            2.739162         2.744653\n",
+       " 974119  2.702502 -14.520256         1029            2.736942         2.744653\n",
+       " 974120  2.704204 -14.520256         1029            2.734722         2.744653\n",
+       " 974121  2.705906 -14.520153         1029            2.732364         2.744653\n",
+       " 974122  2.707608 -14.520002         1029            2.729943         2.744653\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 974761  3.794995 -14.524183         1029            0.000154         2.744653\n",
+       " 974762  3.796697 -14.524224         1029            0.000148         2.744653\n",
+       " 974763  3.798398 -14.524265         1029            0.000141         2.744653\n",
+       " 974764  3.800100 -14.524306         1029            0.000134         2.744653\n",
+       " 974765  3.801802 -14.524347         1029            0.000127         2.744653\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 975118  2.700801 -14.520027         1030            2.739475         2.744091\n",
+       " 975119  2.702502 -14.520027         1030            2.737233         2.744091\n",
+       " 975120  2.704204 -14.520027         1030            2.734992         2.744091\n",
+       " 975121  2.705906 -14.519966         1030            2.732643         2.744091\n",
+       " 975122  2.707608 -14.519893         1030            2.730270         2.744091\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 975762  3.796697 -14.524831         1030            0.000150         2.744091\n",
+       " 975763  3.798398 -14.524889         1030            0.000143         2.744091\n",
+       " 975764  3.800100 -14.524946         1030            0.000136         2.744091\n",
+       " 975765  3.801802 -14.525003         1030            0.000129         2.744091\n",
+       " 975766  3.803504 -14.525062         1030            0.000123         2.744091\n",
+       " \n",
+       " [649 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 976118  2.700801 -14.520292         1031            2.737805         2.742715\n",
+       " 976119  2.702502 -14.520370         1031            2.735528         2.742715\n",
+       " 976120  2.704204 -14.520447         1031            2.733252         2.742715\n",
+       " 976121  2.705906 -14.520410         1031            2.730927         2.742715\n",
+       " 976122  2.707608 -14.520262         1031            2.728554         2.742715\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 976761  3.794995 -14.526500         1031            0.000156         2.742715\n",
+       " 976762  3.796697 -14.526579         1031            0.000149         2.742715\n",
+       " 976763  3.798398 -14.526658         1031            0.000143         2.742715\n",
+       " 976764  3.800100 -14.526737         1031            0.000136         2.742715\n",
+       " 976765  3.801802 -14.526816         1031            0.000129         2.742715\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 977118  2.700801 -14.519576         1032            2.735547         2.741047\n",
+       " 977119  2.702502 -14.519588         1032            2.733323         2.741047\n",
+       " 977120  2.704204 -14.519885         1032            2.731041         2.741047\n",
+       " 977121  2.705906 -14.520181         1032            2.728760         2.741047\n",
+       " 977122  2.707608 -14.520032         1032            2.726443         2.741047\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 977762  3.796697 -14.526605         1032            0.000151         2.741047\n",
+       " 977763  3.798398 -14.526674         1032            0.000144         2.741047\n",
+       " 977764  3.800100 -14.526744         1032            0.000137         2.741047\n",
+       " 977765  3.801802 -14.526814         1032            0.000130         2.741047\n",
+       " 977766  3.803504 -14.526883         1032            0.000124         2.741047\n",
+       " \n",
+       " [649 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 978118  2.700801 -14.520027         1033            2.735228         2.738471\n",
+       " 978119  2.702502 -14.520027         1033            2.732960         2.738471\n",
+       " 978120  2.704204 -14.520027         1033            2.730675         2.738471\n",
+       " 978121  2.705906 -14.520027         1033            2.728355         2.738471\n",
+       " 978122  2.707608 -14.520027         1033            2.726034         2.738471\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 978761  3.794995 -14.524793         1033            0.000156         2.738471\n",
+       " 978762  3.796697 -14.524848         1033            0.000149         2.738471\n",
+       " 978763  3.798398 -14.524903         1033            0.000142         2.738471\n",
+       " 978764  3.800100 -14.524959         1033            0.000135         2.738471\n",
+       " 978765  3.801802 -14.525014         1033            0.000129         2.738471\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 979118  2.700801 -14.519938         1034            2.731647         2.738572\n",
+       " 979119  2.702502 -14.520239         1034            2.729398         2.738572\n",
+       " 979120  2.704204 -14.520186         1034            2.727155         2.738572\n",
+       " 979121  2.705906 -14.520112         1034            2.724912         2.738572\n",
+       " 979122  2.707608 -14.520039         1034            2.722670         2.738572\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 979761  3.794995 -14.525023         1034            0.000154         2.738572\n",
+       " 979762  3.796697 -14.525081         1034            0.000147         2.738572\n",
+       " 979763  3.798398 -14.525139         1034            0.000140         2.738572\n",
+       " 979764  3.800100 -14.525196         1034            0.000134         2.738572\n",
+       " 979765  3.801802 -14.525253         1034            0.000127         2.738572\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 980118  2.700801 -14.520027         1035            2.728773         2.734433\n",
+       " 980119  2.702502 -14.520027         1035            2.726504         2.734433\n",
+       " 980120  2.704204 -14.520064         1035            2.724218         2.734433\n",
+       " 980121  2.705906 -14.520140         1035            2.721916         2.734433\n",
+       " 980122  2.707608 -14.520214         1035            2.719615         2.734433\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 980761  3.794995 -14.524622         1035            0.000154         2.734433\n",
+       " 980762  3.796697 -14.524667         1035            0.000147         2.734433\n",
+       " 980763  3.798398 -14.524713         1035            0.000140         2.734433\n",
+       " 980764  3.800100 -14.524758         1035            0.000134         2.734433\n",
+       " 980765  3.801802 -14.524803         1035            0.000127         2.734433\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 981118  2.700801 -14.520442         1036            2.728769         2.732651\n",
+       " 981119  2.702502 -14.520349         1036            2.726578         2.732651\n",
+       " 981120  2.704204 -14.520256         1036            2.724386         2.732651\n",
+       " 981121  2.705906 -14.520027         1036            2.721996         2.732651\n",
+       " 981122  2.707608 -14.519799         1036            2.719606         2.732651\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 981761  3.794995 -14.526092         1036            0.000155         2.732651\n",
+       " 981762  3.796697 -14.526163         1036            0.000148         2.732651\n",
+       " 981763  3.798398 -14.526235         1036            0.000141         2.732651\n",
+       " 981764  3.800100 -14.526307         1036            0.000135         2.732651\n",
+       " 981765  3.801802 -14.526379         1036            0.000128         2.732651\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 982118  2.700801 -14.519681         1037            2.728763         2.733165\n",
+       " 982119  2.702502 -14.519920         1037            2.726472         2.733165\n",
+       " 982120  2.704204 -14.520160         1037            2.724181         2.733165\n",
+       " 982121  2.705906 -14.520212         1037            2.721923         2.733165\n",
+       " 982122  2.707608 -14.520140         1037            2.719686         2.733165\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 982761  3.794995 -14.523721         1037            0.000155         2.733165\n",
+       " 982762  3.796697 -14.523762         1037            0.000148         2.733165\n",
+       " 982763  3.798398 -14.523803         1037            0.000142         2.733165\n",
+       " 982764  3.800100 -14.523843         1037            0.000135         2.733165\n",
+       " 982765  3.801802 -14.523884         1037            0.000128         2.733165\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 983118  2.700801 -14.519980         1038            2.728941         2.732986\n",
+       " 983119  2.702502 -14.519880         1038            2.726771         2.732986\n",
+       " 983120  2.704204 -14.519812         1038            2.724581         2.732986\n",
+       " 983121  2.705906 -14.519886         1038            2.722300         2.732986\n",
+       " 983122  2.707608 -14.519959         1038            2.720018         2.732986\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 983761  3.794995 -14.524784         1038            0.000155         2.732986\n",
+       " 983762  3.796697 -14.524841         1038            0.000148         2.732986\n",
+       " 983763  3.798398 -14.524899         1038            0.000142         2.732986\n",
+       " 983764  3.800100 -14.524957         1038            0.000135         2.732986\n",
+       " 983765  3.801802 -14.525014         1038            0.000128         2.732986\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 984118  2.700801 -14.519798         1039            2.728957          2.73329\n",
+       " 984119  2.702502 -14.519798         1039            2.726737          2.73329\n",
+       " 984120  2.704204 -14.519798         1039            2.724516          2.73329\n",
+       " 984121  2.705906 -14.519664         1039            2.722294          2.73329\n",
+       " 984122  2.707608 -14.519439         1039            2.720071          2.73329\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 984761  3.794995 -14.526093         1039            0.000156          2.73329\n",
+       " 984762  3.796697 -14.526162         1039            0.000149          2.73329\n",
+       " 984763  3.798398 -14.526232         1039            0.000142          2.73329\n",
+       " 984764  3.800100 -14.526301         1039            0.000136          2.73329\n",
+       " 984765  3.801802 -14.526371         1039            0.000129          2.73329\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 985118  2.700801 -14.520209         1040            2.727223         2.731218\n",
+       " 985119  2.702502 -14.520109         1040            2.725089         2.731218\n",
+       " 985120  2.704204 -14.519987         1040            2.722939         2.731218\n",
+       " 985121  2.705906 -14.519761         1040            2.720716         2.731218\n",
+       " 985122  2.707608 -14.519536         1040            2.718493         2.731218\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 985762  3.796697 -14.524595         1040            0.000151         2.731218\n",
+       " 985763  3.798398 -14.524652         1040            0.000144         2.731218\n",
+       " 985764  3.800100 -14.524710         1040            0.000137         2.731218\n",
+       " 985765  3.801802 -14.524767         1040            0.000130         2.731218\n",
+       " 985766  3.803504 -14.524825         1040            0.000124         2.731218\n",
+       " \n",
+       " [649 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 986118  2.700801 -14.519753         1041            2.725199         2.729932\n",
+       " 986119  2.702502 -14.520145         1041            2.722961         2.729932\n",
+       " 986120  2.704204 -14.520150         1041            2.720730         2.729932\n",
+       " 986121  2.705906 -14.520002         1041            2.718500         2.729932\n",
+       " 986122  2.707608 -14.519854         1041            2.716270         2.729932\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 986761  3.794995 -14.525855         1041            0.000156         2.729932\n",
+       " 986762  3.796697 -14.525928         1041            0.000149         2.729932\n",
+       " 986763  3.798398 -14.525999         1041            0.000142         2.729932\n",
+       " 986764  3.800100 -14.526072         1041            0.000135         2.729932\n",
+       " 986765  3.801802 -14.526143         1041            0.000128         2.729932\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 987118  2.700801 -14.520256         1042            2.724889         2.729383\n",
+       " 987119  2.702502 -14.520256         1042            2.722715         2.729383\n",
+       " 987120  2.704204 -14.520256         1042            2.720541         2.729383\n",
+       " 987121  2.705906 -14.520071         1042            2.718272         2.729383\n",
+       " 987122  2.707608 -14.519846         1042            2.715984         2.729383\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 987762  3.796697 -14.526366         1042            0.000152         2.729383\n",
+       " 987763  3.798398 -14.526436         1042            0.000145         2.729383\n",
+       " 987764  3.800100 -14.526505         1042            0.000138         2.729383\n",
+       " 987765  3.801802 -14.526575         1042            0.000131         2.729383\n",
+       " 987766  3.803504 -14.526645         1042            0.000124         2.729383\n",
+       " \n",
+       " [649 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 988118  2.700801 -14.519942         1043            2.721710          2.72832\n",
+       " 988119  2.702502 -14.519829         1043            2.719438          2.72832\n",
+       " 988120  2.704204 -14.519975         1043            2.717202          2.72832\n",
+       " 988121  2.705906 -14.520121         1043            2.714966          2.72832\n",
+       " 988122  2.707608 -14.520250         1043            2.712725          2.72832\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 988761  3.794995 -14.525892         1043            0.000155          2.72832\n",
+       " 988762  3.796697 -14.525956         1043            0.000149          2.72832\n",
+       " 988763  3.798398 -14.526021         1043            0.000142          2.72832\n",
+       " 988764  3.800100 -14.526085         1043            0.000135          2.72832\n",
+       " 988765  3.801802 -14.526150         1043            0.000128          2.72832\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 989118  2.700801 -14.519856         1044            2.724725         2.728688\n",
+       " 989119  2.702502 -14.519980         1044            2.722597         2.728688\n",
+       " 989120  2.704204 -14.519935         1044            2.720389         2.728688\n",
+       " 989121  2.705906 -14.519786         1044            2.718133         2.728688\n",
+       " 989122  2.707608 -14.519638         1044            2.715878         2.728688\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 989762  3.796697 -14.525299         1044            0.000150         2.728688\n",
+       " 989763  3.798398 -14.525353         1044            0.000143         2.728688\n",
+       " 989764  3.800100 -14.525409         1044            0.000136         2.728688\n",
+       " 989765  3.801802 -14.525464         1044            0.000129         2.728688\n",
+       " 989766  3.803504 -14.525519         1044            0.000123         2.728688\n",
+       " \n",
+       " [649 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 990118  2.700801 -14.520073         1045            2.719020         2.724783\n",
+       " 990119  2.702502 -14.519680         1045            2.716851         2.724783\n",
+       " 990120  2.704204 -14.519731         1045            2.714616         2.724783\n",
+       " 990121  2.705906 -14.519957         1045            2.712353         2.724783\n",
+       " 990122  2.707608 -14.520182         1045            2.710091         2.724783\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 990761  3.794995 -14.524599         1045            0.000154         2.724783\n",
+       " 990762  3.796697 -14.524650         1045            0.000147         2.724783\n",
+       " 990763  3.798398 -14.524700         1045            0.000140         2.724783\n",
+       " 990764  3.800100 -14.524750         1045            0.000134         2.724783\n",
+       " 990765  3.801802 -14.524800         1045            0.000127         2.724783\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 991118  2.700801 -14.520188         1046            2.718500         2.723012\n",
+       " 991119  2.702502 -14.520042         1046            2.716341         2.723012\n",
+       " 991120  2.704204 -14.519960         1046            2.714130         2.723012\n",
+       " 991121  2.705906 -14.519887         1046            2.711914         2.723012\n",
+       " 991122  2.707608 -14.519813         1046            2.709697         2.723012\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 991761  3.794995 -14.525259         1046            0.000155         2.723012\n",
+       " 991762  3.796697 -14.525314         1046            0.000148         2.723012\n",
+       " 991763  3.798398 -14.525369         1046            0.000141         2.723012\n",
+       " 991764  3.800100 -14.525424         1046            0.000134         2.723012\n",
+       " 991765  3.801802 -14.525479         1046            0.000128         2.723012\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 992118  2.700801 -14.520700         1047            2.719891         2.723061\n",
+       " 992119  2.702502 -14.520481         1047            2.717668         2.723061\n",
+       " 992120  2.704204 -14.520263         1047            2.715444         2.723061\n",
+       " 992121  2.705906 -14.520043         1047            2.713221         2.723061\n",
+       " 992122  2.707608 -14.519891         1047            2.711016         2.723061\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 992761  3.794995 -14.524384         1047            0.000154         2.723061\n",
+       " 992762  3.796697 -14.524431         1047            0.000147         2.723061\n",
+       " 992763  3.798398 -14.524480         1047            0.000140         2.723061\n",
+       " 992764  3.800100 -14.524528         1047            0.000133         2.723061\n",
+       " 992765  3.801802 -14.524575         1047            0.000127         2.723061\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 993118  2.700801 -14.519883         1048            2.717546         2.721736\n",
+       " 993119  2.702502 -14.519798         1048            2.715278         2.721736\n",
+       " 993120  2.704204 -14.519798         1048            2.712957         2.721736\n",
+       " 993121  2.705906 -14.519798         1048            2.710637         2.721736\n",
+       " 993122  2.707608 -14.519798         1048            2.708458         2.721736\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 993761  3.794995 -14.526550         1048            0.000153         2.721736\n",
+       " 993762  3.796697 -14.526627         1048            0.000146         2.721736\n",
+       " 993763  3.798398 -14.526703         1048            0.000139         2.721736\n",
+       " 993764  3.800100 -14.526780         1048            0.000133         2.721736\n",
+       " 993765  3.801802 -14.526856         1048            0.000126         2.721736\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 994118  2.700801 -14.519798         1049            2.714510         2.721154\n",
+       " 994119  2.702502 -14.519798         1049            2.712274         2.721154\n",
+       " 994120  2.704204 -14.519798         1049            2.710037         2.721154\n",
+       " 994121  2.705906 -14.519763         1049            2.707801         2.721154\n",
+       " 994122  2.707608 -14.519612         1049            2.705565         2.721154\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 994761  3.794995 -14.525263         1049            0.000153         2.721154\n",
+       " 994762  3.796697 -14.525320         1049            0.000146         2.721154\n",
+       " 994763  3.798398 -14.525377         1049            0.000139         2.721154\n",
+       " 994764  3.800100 -14.525435         1049            0.000133         2.721154\n",
+       " 994765  3.801802 -14.525493         1049            0.000126         2.721154\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 995118  2.700801 -14.519798         1050            2.713761         2.718013\n",
+       " 995119  2.702502 -14.519798         1050            2.711571         2.718013\n",
+       " 995120  2.704204 -14.519798         1050            2.709380         2.718013\n",
+       " 995121  2.705906 -14.519798         1050            2.707192         2.718013\n",
+       " 995122  2.707608 -14.519798         1050            2.705009         2.718013\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 995761  3.794995 -14.525911         1050            0.000153         2.718013\n",
+       " 995762  3.796697 -14.525976         1050            0.000147         2.718013\n",
+       " 995763  3.798398 -14.526041         1050            0.000140         2.718013\n",
+       " 995764  3.800100 -14.526106         1050            0.000133         2.718013\n",
+       " 995765  3.801802 -14.526170         1050            0.000126         2.718013\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 996118  2.700801 -14.520126         1051            2.710599         2.716505\n",
+       " 996119  2.702502 -14.520227         1051            2.708505         2.716505\n",
+       " 996120  2.704204 -14.520155         1051            2.706359         2.716505\n",
+       " 996121  2.705906 -14.520082         1051            2.704212         2.716505\n",
+       " 996122  2.707608 -14.520046         1051            2.702032         2.716505\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 996761  3.794995 -14.525713         1051            0.000151         2.716505\n",
+       " 996762  3.796697 -14.525775         1051            0.000144         2.716505\n",
+       " 996763  3.798398 -14.525838         1051            0.000138         2.716505\n",
+       " 996764  3.800100 -14.525900         1051            0.000131         2.716505\n",
+       " 996765  3.801802 -14.525962         1051            0.000124         2.716505\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 997118  2.700801 -14.519969         1052            2.709116         2.713913\n",
+       " 997119  2.702502 -14.519845         1052            2.706988         2.713913\n",
+       " 997120  2.704204 -14.519845         1052            2.704796         2.713913\n",
+       " 997121  2.705906 -14.519918         1052            2.702567         2.713913\n",
+       " 997122  2.707608 -14.519993         1052            2.700337         2.713913\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 997761  3.794995 -14.524381         1052            0.000151         2.713913\n",
+       " 997762  3.796697 -14.524433         1052            0.000144         2.713913\n",
+       " 997763  3.798398 -14.524486         1052            0.000138         2.713913\n",
+       " 997764  3.800100 -14.524539         1052            0.000131         2.713913\n",
+       " 997765  3.801802 -14.524591         1052            0.000124         2.713913\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 998118  2.700801 -14.520027         1053            2.709842         2.714408\n",
+       " 998119  2.702502 -14.520027         1053            2.707712         2.714408\n",
+       " 998120  2.704204 -14.520007         1053            2.705536         2.714408\n",
+       " 998121  2.705906 -14.519935         1053            2.703236         2.714408\n",
+       " 998122  2.707608 -14.519861         1053            2.700935         2.714408\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 998761  3.794995 -14.525915         1053            0.000153         2.714408\n",
+       " 998762  3.796697 -14.525979         1053            0.000146         2.714408\n",
+       " 998763  3.798398 -14.526044         1053            0.000140         2.714408\n",
+       " 998764  3.800100 -14.526109         1053            0.000133         2.714408\n",
+       " 998765  3.801802 -14.526173         1053            0.000126         2.714408\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       "          voltage    current  cycle_index  discharge_capacity  charge_capacity\n",
+       " 999118  2.700801 -14.519798         1054            2.707036         2.712567\n",
+       " 999119  2.702502 -14.519798         1054            2.704857         2.712567\n",
+       " 999120  2.704204 -14.519732         1054            2.702667         2.712567\n",
+       " 999121  2.705906 -14.519584         1054            2.700463         2.712567\n",
+       " 999122  2.707608 -14.519436         1054            2.698260         2.712567\n",
+       " ...          ...        ...          ...                 ...              ...\n",
+       " 999761  3.794995 -14.523717         1054            0.000152         2.712567\n",
+       " 999762  3.796697 -14.523762         1054            0.000146         2.712567\n",
+       " 999763  3.798398 -14.523808         1054            0.000139         2.712567\n",
+       " 999764  3.800100 -14.523852         1054            0.000132         2.712567\n",
+       " 999765  3.801802 -14.523898         1054            0.000125         2.712567\n",
+       " \n",
+       " [648 rows x 5 columns],\n",
+       " ...]"
+      ]
+     },
+     "execution_count": 167,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cell"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 165,
+   "id": "257df48e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[    cycle_index  discharge_capacity\n",
+       " 20           25            4.398051\n",
+       " 21           26            4.395067\n",
+       " 22           27            4.391276\n",
+       " 23           28            4.383451\n",
+       " 24           29            4.378369\n",
+       " 25           30            4.373650\n",
+       " 26           31            4.367600\n",
+       " 27           32            4.361429\n",
+       " 28           33            4.356791\n",
+       " 29           34            4.353766\n",
+       " 30           35            4.345255\n",
+       " 31           41            4.333276\n",
+       " 32           42            4.315368\n",
+       " 33           43            4.313190\n",
+       " 34           44            4.307826\n",
+       " 35           45            4.302865\n",
+       " 36           46            4.297017\n",
+       " 37           47            4.292540\n",
+       " 38           48            4.288345\n",
+       " 39           49            4.284191,\n",
+       "     cycle_index  discharge_capacity\n",
+       " 40           50            4.278101\n",
+       " 41           51            4.276286\n",
+       " 42           52            4.268017\n",
+       " 43           53            4.265678\n",
+       " 44           54            4.260596\n",
+       " 45           55            4.256038\n",
+       " 46           56            4.253336\n",
+       " 47           57            4.248214\n",
+       " 48           58            4.245915\n",
+       " 49           59            4.239986\n",
+       " 50           60            4.233653\n",
+       " 51           61            4.230991\n",
+       " 52           62            4.224457\n",
+       " 53           63            4.221997\n",
+       " 54           64            4.216633\n",
+       " 55           65            4.220222\n",
+       " 56           66            4.217964\n",
+       " 57           67            4.212640\n",
+       " 58           68            4.207356\n",
+       " 59           69            4.201185,\n",
+       "     cycle_index  discharge_capacity\n",
+       " 60           70            4.196668\n",
+       " 61           71            4.191828\n",
+       " 62           72            4.188843\n",
+       " 63           73            4.183116\n",
+       " 64           74            4.181261\n",
+       " 65           75            4.176179\n",
+       " 66           76            4.170250\n",
+       " 67           77            4.163030\n",
+       " 68           78            4.162707\n",
+       " 69           79            4.160449\n",
+       " 70           80            4.154278\n",
+       " 71           81            4.151011\n",
+       " 72           82            4.146534\n",
+       " 73           83            4.141169\n",
+       " 74           84            4.138588\n",
+       " 75           85            4.136087\n",
+       " 76           86            4.131611\n",
+       " 77           87            4.128545\n",
+       " 78           88            4.123181\n",
+       " 79           89            4.120721,\n",
+       "     cycle_index  discharge_capacity\n",
+       " 80           90            4.116728\n",
+       " 81           91            4.114792\n",
+       " 82           92            4.112372\n",
+       " 83           93            4.105354\n",
+       " 84           94            4.100957\n",
+       " 85           95            4.097650\n",
+       " 86           96            4.094423\n",
+       " 87           97            4.090309\n",
+       " 88           98            4.084784\n",
+       " 89           99            4.082444\n",
+       " 90          100            4.076596\n",
+       " 91          101            4.072684\n",
+       " 92          102            4.069215\n",
+       " 93          103            4.067561\n",
+       " 94          104            4.062923\n",
+       " 95          105            4.058607\n",
+       " 96          106            4.058809\n",
+       " 97          107            4.056551\n",
+       " 98          108            4.060060\n",
+       " 99          109            4.054373,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 100          110            4.050904\n",
+       " 101          111            4.045983\n",
+       " 102          112            4.042232\n",
+       " 103          113            4.037070\n",
+       " 104          114            4.031826\n",
+       " 105          115            4.027107\n",
+       " 106          116            4.024445\n",
+       " 107          117            4.018557\n",
+       " 108          118            4.015048\n",
+       " 109          119            4.010893\n",
+       " 110          120            4.007546\n",
+       " 111          121            4.003674\n",
+       " 112          122            4.000568\n",
+       " 113          123            3.998713\n",
+       " 114          124            3.995688\n",
+       " 115          125            3.993953\n",
+       " 116          126            3.988266\n",
+       " 117          127            3.983023\n",
+       " 118          128            3.981813\n",
+       " 119          129            3.975239,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 120          130            3.971972\n",
+       " 121          131            3.967938\n",
+       " 122          132            3.966245\n",
+       " 123          133            3.964994\n",
+       " 124          134            3.959267\n",
+       " 125          135            3.956605\n",
+       " 126          136            3.952088\n",
+       " 127          137            3.949748\n",
+       " 128          138            3.946159\n",
+       " 129          139            3.942972\n",
+       " 130          140            3.940028\n",
+       " 131          146            3.976045\n",
+       " 132          147            3.968705\n",
+       " 133          148            3.958460\n",
+       " 134          149            3.952047\n",
+       " 135          150            3.944223\n",
+       " 136          151            3.939988\n",
+       " 137          152            3.930227\n",
+       " 138          153            3.926597\n",
+       " 139          154            3.921838,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 140          155            3.911633\n",
+       " 141          156            3.908084\n",
+       " 142          157            3.900703\n",
+       " 143          158            3.898969\n",
+       " 144          159            3.893242\n",
+       " 145          160            3.892152\n",
+       " 146          161            3.886667\n",
+       " 147          162            3.881021\n",
+       " 148          163            3.876907\n",
+       " 149          164            3.870897\n",
+       " 150          165            3.869405\n",
+       " 151          166            3.865654\n",
+       " 152          167            3.862225\n",
+       " 153          168            3.856861\n",
+       " 154          169            3.851093\n",
+       " 155          170            3.849601\n",
+       " 156          171            3.844519\n",
+       " 157          172            3.842825\n",
+       " 158          173            3.837299\n",
+       " 159          174            3.834194,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 160          175            3.829838\n",
+       " 161          176            3.829475\n",
+       " 162          177            3.822981\n",
+       " 163          178            3.821327\n",
+       " 164          179            3.816850\n",
+       " 165          180            3.815519\n",
+       " 166          181            3.811930\n",
+       " 167          182            3.811285\n",
+       " 168          183            3.805235\n",
+       " 169          184            3.802048\n",
+       " 170          185            3.799588\n",
+       " 171          186            3.796039\n",
+       " 172          187            3.792893\n",
+       " 173          188            3.788456\n",
+       " 174          189            3.785391\n",
+       " 175          190            3.781478\n",
+       " 176          191            3.786157\n",
+       " 177          192            3.780631\n",
+       " 178          193            3.773452\n",
+       " 179          194            3.771072,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 180          195            3.768289\n",
+       " 181          196            3.769177\n",
+       " 182          197            3.765224\n",
+       " 183          198            3.759819\n",
+       " 184          199            3.758206\n",
+       " 185          200            3.754132\n",
+       " 186          201            3.754858\n",
+       " 187          202            3.752398\n",
+       " 188          203            3.746872\n",
+       " 189          204            3.745138\n",
+       " 190          205            3.740419\n",
+       " 191          206            3.742234\n",
+       " 192          207            3.737192\n",
+       " 193          208            3.733361\n",
+       " 194          209            3.732756\n",
+       " 195          210            3.727069\n",
+       " 196          211            3.724810\n",
+       " 197          212            3.721785\n",
+       " 198          213            3.719042\n",
+       " 199          214            3.715937,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 200          215            3.713436\n",
+       " 201          216            3.711339\n",
+       " 202          217            3.708153\n",
+       " 203          218            3.705571\n",
+       " 204          219            3.703232\n",
+       " 205          220            3.704160\n",
+       " 206          221            3.700409\n",
+       " 207          222            3.700167\n",
+       " 208          223            3.695246\n",
+       " 209          224            3.693552\n",
+       " 210          225            3.688954\n",
+       " 211          226            3.687502\n",
+       " 212          227            3.685566\n",
+       " 213          228            3.685405\n",
+       " 214          229            3.681976\n",
+       " 215          230            3.680000\n",
+       " 216          231            3.675563\n",
+       " 217          232            3.673910\n",
+       " 218          233            3.673708\n",
+       " 219          234            3.669594,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 220          235            3.667416\n",
+       " 221          236            3.664109\n",
+       " 222          237            3.662778\n",
+       " 223          238            3.662697\n",
+       " 224          239            3.659874\n",
+       " 225          240            3.656970\n",
+       " 226          241            3.654711\n",
+       " 227          242            3.654590\n",
+       " 228          243            3.652412\n",
+       " 229          244            3.649750\n",
+       " 230          245            3.646725\n",
+       " 231          251            3.711057\n",
+       " 232          252            3.696658\n",
+       " 233          253            3.686292\n",
+       " 234          254            3.677943\n",
+       " 235          255            3.664230\n",
+       " 236          256            3.653380\n",
+       " 237          257            3.647007\n",
+       " 238          258            3.639304\n",
+       " 239          259            3.632326,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 240          260            3.626397\n",
+       " 241          261            3.621436\n",
+       " 242          262            3.615709\n",
+       " 243          263            3.613975\n",
+       " 244          264            3.609175\n",
+       " 245          265            3.605464\n",
+       " 246          266            3.601754\n",
+       " 247          267            3.596833\n",
+       " 248          268            3.593929\n",
+       " 249          269            3.592396\n",
+       " 250          270            3.590460\n",
+       " 251          271            3.585822\n",
+       " 252          272            3.581668\n",
+       " 253          273            3.586992\n",
+       " 254          274            3.579530\n",
+       " 255          275            3.576223\n",
+       " 256          276            3.573077\n",
+       " 257          277            3.570576\n",
+       " 258          278            3.567511\n",
+       " 259          279            3.568842,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 260          280            3.565050\n",
+       " 261          281            3.561904\n",
+       " 262          282            3.561138\n",
+       " 263          283            3.556823\n",
+       " 264          284            3.553394\n",
+       " 265          285            3.555411\n",
+       " 266          286            3.551337\n",
+       " 267          287            3.549845\n",
+       " 268          288            3.545328\n",
+       " 269          289            3.545086\n",
+       " 270          290            3.542182\n",
+       " 271          291            3.541254\n",
+       " 272          292            3.538915\n",
+       " 273          293            3.536777\n",
+       " 274          294            3.534760\n",
+       " 275          295            3.532058\n",
+       " 276          296            3.533349\n",
+       " 277          297            3.531574\n",
+       " 278          298            3.526815\n",
+       " 279          299            3.523548,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 280          300            3.520926\n",
+       " 281          301            3.522701\n",
+       " 282          302            3.521289\n",
+       " 283          303            3.520119\n",
+       " 284          304            3.518506\n",
+       " 285          305            3.514715\n",
+       " 286          306            3.511448\n",
+       " 287          307            3.511367\n",
+       " 288          308            3.509633\n",
+       " 289          309            3.504712\n",
+       " 290          310            3.501445\n",
+       " 291          311            3.502090\n",
+       " 292          312            3.499186\n",
+       " 293          313            3.500437\n",
+       " 294          314            3.498622\n",
+       " 295          315            3.494871\n",
+       " 296          316            3.494185\n",
+       " 297          317            3.494508\n",
+       " 298          318            3.492330\n",
+       " 299          319            3.490394,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 300          320            3.486925\n",
+       " 301          321            3.483174\n",
+       " 302          322            3.486159\n",
+       " 303          323            3.483739\n",
+       " 304          324            3.481359\n",
+       " 305          325            3.479343\n",
+       " 306          326            3.476196\n",
+       " 307          327            3.478092\n",
+       " 308          328            3.475269\n",
+       " 309          329            3.475188\n",
+       " 310          330            3.474099\n",
+       " 311          331            3.470026\n",
+       " 312          332            3.467364\n",
+       " 313          333            3.468614\n",
+       " 314          334            3.468937\n",
+       " 315          335            3.465670\n",
+       " 316          336            3.463976\n",
+       " 317          337            3.461999\n",
+       " 318          338            3.460507\n",
+       " 319          339            3.459821,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 320          340            3.459902\n",
+       " 321          341            3.456030\n",
+       " 322          342            3.454296\n",
+       " 323          343            3.451392\n",
+       " 324          344            3.450585\n",
+       " 325          345            3.449899\n",
+       " 326          346            3.446108\n",
+       " 327          347            3.443648\n",
+       " 328          348            3.442236\n",
+       " 329          349            3.440945\n",
+       " 330          350            3.439897\n",
+       " 331          356            3.520603\n",
+       " 332          357            3.508100\n",
+       " 333          358            3.494427\n",
+       " 334          359            3.481278\n",
+       " 335          360            3.471760\n",
+       " 336          361            3.460789\n",
+       " 337          362            3.456353\n",
+       " 338          363            3.449617\n",
+       " 339          364            3.441429,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 340          365            3.433362\n",
+       " 341          366            3.431144\n",
+       " 342          367            3.426304\n",
+       " 343          368            3.423763\n",
+       " 344          369            3.418923\n",
+       " 345          370            3.413962\n",
+       " 346          371            3.411139\n",
+       " 347          372            3.407912\n",
+       " 348          373            3.408598\n",
+       " 349          374            3.404081\n",
+       " 350          375            3.402992\n",
+       " 351          376            3.397305\n",
+       " 352          377            3.397184\n",
+       " 353          378            3.394199\n",
+       " 354          379            3.390327\n",
+       " 355          380            3.387706\n",
+       " 356          381            3.387786\n",
+       " 357          382            3.382906\n",
+       " 358          383            3.380647\n",
+       " 359          384            3.379477,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 360          385            3.378388\n",
+       " 361          386            3.374557\n",
+       " 362          387            3.372661\n",
+       " 363          388            3.369919\n",
+       " 364          389            3.369394\n",
+       " 365          390            3.369636\n",
+       " 366          391            3.366974\n",
+       " 367          392            3.362538\n",
+       " 368          393            3.361973\n",
+       " 369          394            3.361933\n",
+       " 370          395            3.362376\n",
+       " 371          396            3.358585\n",
+       " 372          397            3.356447\n",
+       " 373          398            3.356891\n",
+       " 374          399            3.354068\n",
+       " 375          400            3.352293\n",
+       " 376          401            3.353503\n",
+       " 377          402            3.350881\n",
+       " 378          403            3.349994\n",
+       " 379          404            3.346324,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 380          405            3.344791\n",
+       " 381          406            3.345880\n",
+       " 382          407            3.345557\n",
+       " 383          408            3.344831\n",
+       " 384          409            3.342855\n",
+       " 385          410            3.339709\n",
+       " 386          411            3.339306\n",
+       " 387          412            3.334869\n",
+       " 388          413            3.335998\n",
+       " 389          414            3.334224\n",
+       " 390          415            3.329868\n",
+       " 391          416            3.328900\n",
+       " 392          417            3.329021\n",
+       " 393          418            3.325350\n",
+       " 394          419            3.323455\n",
+       " 395          420            3.324019\n",
+       " 396          421            3.323172\n",
+       " 397          422            3.321559\n",
+       " 398          423            3.319260\n",
+       " 399          424            3.317082,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 400          425            3.315590\n",
+       " 401          426            3.315791\n",
+       " 402          427            3.311355\n",
+       " 403          428            3.310911\n",
+       " 404          429            3.311274\n",
+       " 405          430            3.312040\n",
+       " 406          431            3.308572\n",
+       " 407          432            3.306515\n",
+       " 408          433            3.305265\n",
+       " 409          434            3.304861\n",
+       " 410          435            3.301715\n",
+       " 411          436            3.298489\n",
+       " 412          437            3.298932\n",
+       " 413          438            3.298045\n",
+       " 414          439            3.298085\n",
+       " 415          440            3.295544\n",
+       " 416          441            3.294818\n",
+       " 417          442            3.297480\n",
+       " 418          443            3.292761\n",
+       " 419          444            3.291269,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 420          445            3.291027\n",
+       " 421          446            3.290341\n",
+       " 422          447            3.286913\n",
+       " 423          448            3.288809\n",
+       " 424          449            3.284533\n",
+       " 425          450            3.283081\n",
+       " 426          451            3.282033\n",
+       " 427          452            3.282839\n",
+       " 428          453            3.280419\n",
+       " 429          454            3.282638\n",
+       " 430          455            3.279330\n",
+       " 431          461            3.367257\n",
+       " 432          462            3.352253\n",
+       " 433          463            3.338620\n",
+       " 434          464            3.327528\n",
+       " 435          465            3.316275\n",
+       " 436          466            3.307846\n",
+       " 437          467            3.299658\n",
+       " 438          468            3.293971\n",
+       " 439          469            3.291148,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 440          470            3.282113\n",
+       " 441          471            3.278161\n",
+       " 442          472            3.273603\n",
+       " 443          473            3.270860\n",
+       " 444          474            3.267755\n",
+       " 445          475            3.264326\n",
+       " 446          476            3.260051\n",
+       " 447          477            3.258397\n",
+       " 448          478            3.255937\n",
+       " 449          479            3.254001\n",
+       " 450          480            3.252912\n",
+       " 451          481            3.250008\n",
+       " 452          482            3.247427\n",
+       " 453          483            3.244523\n",
+       " 454          484            3.243514\n",
+       " 455          485            3.242909\n",
+       " 456          486            3.239642\n",
+       " 457          487            3.239441\n",
+       " 458          488            3.235891\n",
+       " 459          489            3.236012,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 460          490            3.230043\n",
+       " 461          491            3.229479\n",
+       " 462          492            3.227462\n",
+       " 463          493            3.227583\n",
+       " 464          494            3.226453\n",
+       " 465          495            3.224639\n",
+       " 466          496            3.221493\n",
+       " 467          497            3.221210\n",
+       " 468          498            3.218750\n",
+       " 469          499            3.216653\n",
+       " 470          500            3.216935\n",
+       " 471          501            3.214515\n",
+       " 472          502            3.211530\n",
+       " 473          503            3.210078\n",
+       " 474          504            3.208545\n",
+       " 475          505            3.207618\n",
+       " 476          506            3.209312\n",
+       " 477          507            3.207699\n",
+       " 478          508            3.204996\n",
+       " 479          509            3.204069,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 480          510            3.202899\n",
+       " 481          511            3.202012\n",
+       " 482          512            3.202173\n",
+       " 483          513            3.200116\n",
+       " 484          514            3.197293\n",
+       " 485          515            3.197333\n",
+       " 486          516            3.194268\n",
+       " 487          517            3.192493\n",
+       " 488          518            3.193340\n",
+       " 489          519            3.191727\n",
+       " 490          520            3.191565\n",
+       " 491          521            3.189024\n",
+       " 492          522            3.187855\n",
+       " 493          523            3.185717\n",
+       " 494          524            3.185677\n",
+       " 495          525            3.184144\n",
+       " 496          526            3.181845\n",
+       " 497          527            3.183983\n",
+       " 498          528            3.177650\n",
+       " 499          529            3.178013,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 500          530            3.179667\n",
+       " 501          531            3.177933\n",
+       " 502          532            3.177610\n",
+       " 503          533            3.176400\n",
+       " 504          534            3.174545\n",
+       " 505          535            3.171963\n",
+       " 506          536            3.172205\n",
+       " 507          537            3.170995\n",
+       " 508          538            3.168737\n",
+       " 509          539            3.168817\n",
+       " 510          540            3.168535\n",
+       " 511          541            3.164784\n",
+       " 512          542            3.164139\n",
+       " 513          543            3.162848\n",
+       " 514          544            3.162041\n",
+       " 515          545            3.162929\n",
+       " 516          546            3.163372\n",
+       " 517          547            3.159742\n",
+       " 518          548            3.156395\n",
+       " 519          549            3.154297,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 520          550            3.153330\n",
+       " 521          551            3.152765\n",
+       " 522          552            3.152684\n",
+       " 523          553            3.151232\n",
+       " 524          554            3.152523\n",
+       " 525          555            3.150183\n",
+       " 526          556            3.149538\n",
+       " 527          557            3.148570\n",
+       " 528          558            3.145586\n",
+       " 529          559            3.147038\n",
+       " 530          560            3.147239\n",
+       " 531          566            3.238029\n",
+       " 532          567            3.225163\n",
+       " 533          568            3.208868\n",
+       " 534          569            3.198906\n",
+       " 535          570            3.188621\n",
+       " 536          571            3.180675\n",
+       " 537          572            3.176763\n",
+       " 538          573            3.171802\n",
+       " 539          574            3.162485,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 540          575            3.156758\n",
+       " 541          576            3.152684\n",
+       " 542          577            3.148812\n",
+       " 543          578            3.150667\n",
+       " 544          579            3.145263\n",
+       " 545          580            3.139495\n",
+       " 546          581            3.139415\n",
+       " 547          582            3.134413\n",
+       " 548          583            3.132195\n",
+       " 549          584            3.140504\n",
+       " 550          585            3.130945\n",
+       " 551          586            3.127395\n",
+       " 552          587            3.124814\n",
+       " 553          588            3.121870\n",
+       " 554          589            3.120216\n",
+       " 555          590            3.120256\n",
+       " 556          591            3.118401\n",
+       " 557          592            3.115941\n",
+       " 558          593            3.113359\n",
+       " 559          594            3.115497,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 560          595            3.114247\n",
+       " 561          596            3.110576\n",
+       " 562          597            3.109528\n",
+       " 563          598            3.106704\n",
+       " 564          599            3.104446\n",
+       " 565          600            3.103518\n",
+       " 566          601            3.101663\n",
+       " 567          602            3.101905\n",
+       " 568          603            3.102752\n",
+       " 569          604            3.096621\n",
+       " 570          605            3.096540\n",
+       " 571          606            3.093031\n",
+       " 572          607            3.091458\n",
+       " 573          608            3.093475\n",
+       " 574          609            3.093757\n",
+       " 575          610            3.089885\n",
+       " 576          611            3.089159\n",
+       " 577          612            3.088070\n",
+       " 578          613            3.088111\n",
+       " 579          614            3.086134,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 580          615            3.086296\n",
+       " 581          616            3.083190\n",
+       " 582          617            3.079399\n",
+       " 583          618            3.079439\n",
+       " 584          619            3.079157\n",
+       " 585          620            3.078794\n",
+       " 586          621            3.082303\n",
+       " 587          622            3.075285\n",
+       " 588          623            3.073066\n",
+       " 589          624            3.072300\n",
+       " 590          625            3.074115\n",
+       " 591          626            3.070324\n",
+       " 592          627            3.071574\n",
+       " 593          628            3.068670\n",
+       " 594          629            3.069436\n",
+       " 595          630            3.064959\n",
+       " 596          631            3.065000\n",
+       " 597          632            3.065524\n",
+       " 598          633            3.063830\n",
+       " 599          634            3.064032,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 600          635            3.060684\n",
+       " 601          636            3.059676\n",
+       " 602          637            3.057982\n",
+       " 603          638            3.059635\n",
+       " 604          639            3.059071\n",
+       " 605          640            3.056127\n",
+       " 606          641            3.055804\n",
+       " 607          642            3.053061\n",
+       " 608          643            3.050883\n",
+       " 609          644            3.052981\n",
+       " 610          645            3.053303\n",
+       " 611          646            3.050399\n",
+       " 612          647            3.049189\n",
+       " 613          648            3.048262\n",
+       " 614          649            3.046810\n",
+       " 615          650            3.046971\n",
+       " 616          651            3.046366\n",
+       " 617          652            3.043583\n",
+       " 618          653            3.044712\n",
+       " 619          654            3.046527,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 620          655            3.042413\n",
+       " 621          656            3.043583\n",
+       " 622          657            3.042333\n",
+       " 623          658            3.041324\n",
+       " 624          659            3.040356\n",
+       " 625          660            3.040598\n",
+       " 626          661            3.037291\n",
+       " 627          662            3.038299\n",
+       " 628          663            3.037614\n",
+       " 629          664            3.036041\n",
+       " 630          665            3.036444\n",
+       " 631          671            3.124935\n",
+       " 632          672            3.113117\n",
+       " 633          673            3.100937\n",
+       " 634          674            3.091458\n",
+       " 635          675            3.082141\n",
+       " 636          676            3.074922\n",
+       " 637          677            3.068549\n",
+       " 638          678            3.063911\n",
+       " 639          679            3.056570,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 640          680            3.051771\n",
+       " 641          681            3.046769\n",
+       " 642          682            3.043664\n",
+       " 643          683            3.040881\n",
+       " 644          684            3.036646\n",
+       " 645          685            3.033379\n",
+       " 646          686            3.033661\n",
+       " 647          687            3.031927\n",
+       " 648          688            3.028055\n",
+       " 649          689            3.026401\n",
+       " 650          690            3.024183\n",
+       " 651          691            3.023013\n",
+       " 652          692            3.020069\n",
+       " 653          693            3.017729\n",
+       " 654          694            3.015713\n",
+       " 655          695            3.014987\n",
+       " 656          696            3.013736\n",
+       " 657          697            3.013656\n",
+       " 658          698            3.008614\n",
+       " 659          699            3.008090,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 660          700            3.007404\n",
+       " 661          701            3.008412\n",
+       " 662          702            3.005992\n",
+       " 663          703            3.001394\n",
+       " 664          704            3.002201\n",
+       " 665          705            3.001757\n",
+       " 666          706            2.998692\n",
+       " 667          707            2.996837\n",
+       " 668          708            2.994941\n",
+       " 669          709            2.995949\n",
+       " 670          710            2.992682\n",
+       " 671          711            2.991553\n",
+       " 672          712            2.991351\n",
+       " 673          713            2.993166\n",
+       " 674          714            2.991392\n",
+       " 675          715            2.988528\n",
+       " 676          716            2.985422\n",
+       " 677          717            2.984656\n",
+       " 678          718            2.982962\n",
+       " 679          719            2.983486,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 680          720            2.983245\n",
+       " 681          721            2.981873\n",
+       " 682          722            2.980421\n",
+       " 683          723            2.978606\n",
+       " 684          724            2.985543\n",
+       " 685          725            2.980542\n",
+       " 686          726            2.976993\n",
+       " 687          727            2.978243\n",
+       " 688          728            2.977759\n",
+       " 689          729            2.977195\n",
+       " 690          730            2.975944\n",
+       " 691          731            2.975420\n",
+       " 692          732            2.972879\n",
+       " 693          733            2.971871\n",
+       " 694          734            2.970418\n",
+       " 695          735            2.969047\n",
+       " 696          736            2.968926\n",
+       " 697          737            2.968241\n",
+       " 698          738            2.967918\n",
+       " 699          739            2.967031,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 700          740            2.965498\n",
+       " 701          741            2.968039\n",
+       " 702          742            2.962271\n",
+       " 703          743            2.961586\n",
+       " 704          744            2.960416\n",
+       " 705          745            2.961182\n",
+       " 706          746            2.961424\n",
+       " 707          747            2.960940\n",
+       " 708          748            2.957915\n",
+       " 709          749            2.956100\n",
+       " 710          750            2.955253\n",
+       " 711          751            2.954326\n",
+       " 712          752            2.954164\n",
+       " 713          753            2.953398\n",
+       " 714          754            2.952914\n",
+       " 715          755            2.950978\n",
+       " 716          756            2.950131\n",
+       " 717          757            2.950938\n",
+       " 718          758            2.948518\n",
+       " 719          759            2.950373,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 720          760            2.945896\n",
+       " 721          761            2.944726\n",
+       " 722          762            2.948114\n",
+       " 723          763            2.949526\n",
+       " 724          764            2.945291\n",
+       " 725          765            2.942548\n",
+       " 726          766            2.944081\n",
+       " 727          767            2.940411\n",
+       " 728          768            2.939362\n",
+       " 729          769            2.939806\n",
+       " 730          770            2.940411\n",
+       " 731          776            3.032451\n",
+       " 732          777            3.016398\n",
+       " 733          778            3.006517\n",
+       " 734          779            2.998329\n",
+       " 735          780            2.993529\n",
+       " 736          781            2.985705\n",
+       " 737          782            2.980381\n",
+       " 738          783            2.972395\n",
+       " 739          784            2.967353,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 740          785            2.963522\n",
+       " 741          786            2.961182\n",
+       " 742          787            2.958117\n",
+       " 743          788            2.958641\n",
+       " 744          789            2.950897\n",
+       " 745          790            2.947106\n",
+       " 746          791            2.945694\n",
+       " 747          792            2.941137\n",
+       " 748          793            2.940169\n",
+       " 749          794            2.938596\n",
+       " 750          795            2.934078\n",
+       " 751          796            2.933110\n",
+       " 752          797            2.931941\n",
+       " 753          798            2.928875\n",
+       " 754          799            2.927504\n",
+       " 755          800            2.924439\n",
+       " 756          801            2.925689\n",
+       " 757          802            2.924923\n",
+       " 758          803            2.923753\n",
+       " 759          804            2.921131,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 760          805            2.919115\n",
+       " 761          806            2.915081\n",
+       " 762          807            2.915404\n",
+       " 763          808            2.917340\n",
+       " 764          809            2.913065\n",
+       " 765          810            2.910887\n",
+       " 766          811            2.910887\n",
+       " 767          812            2.907781\n",
+       " 768          813            2.907095\n",
+       " 769          814            2.906571\n",
+       " 770          815            2.906612\n",
+       " 771          816            2.906571\n",
+       " 772          817            2.905200\n",
+       " 773          818            2.904796\n",
+       " 774          819            2.902094\n",
+       " 775          820            2.900884\n",
+       " 776          821            2.901812\n",
+       " 777          822            2.897416\n",
+       " 778          823            2.897133\n",
+       " 779          824            2.898505,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 780          825            2.897778\n",
+       " 781          826            2.894834\n",
+       " 782          827            2.894713\n",
+       " 783          828            2.897052\n",
+       " 784          829            2.892334\n",
+       " 785          830            2.891124\n",
+       " 786          831            2.891567\n",
+       " 787          832            2.891809\n",
+       " 788          833            2.890397\n",
+       " 789          834            2.889268\n",
+       " 790          835            2.889268\n",
+       " 791          836            2.890922\n",
+       " 792          837            2.887695\n",
+       " 793          838            2.887090\n",
+       " 794          839            2.887534\n",
+       " 795          840            2.885679\n",
+       " 796          841            2.883380\n",
+       " 797          842            2.884106\n",
+       " 798          843            2.886001\n",
+       " 799          844            2.881645,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 800          845            2.881000\n",
+       " 801          846            2.880355\n",
+       " 802          847            2.877733\n",
+       " 803          848            2.878983\n",
+       " 804          849            2.876684\n",
+       " 805          850            2.876684\n",
+       " 806          851            2.875595\n",
+       " 807          852            2.872207\n",
+       " 808          853            2.874022\n",
+       " 809          854            2.871844\n",
+       " 810          855            2.870674\n",
+       " 811          856            2.870312\n",
+       " 812          857            2.869868\n",
+       " 813          858            2.870634\n",
+       " 814          859            2.869626\n",
+       " 815          860            2.869182\n",
+       " 816          861            2.868618\n",
+       " 817          862            2.866682\n",
+       " 818          863            2.865552\n",
+       " 819          864            2.870110,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 820          865            2.865714\n",
+       " 821          866            2.869182\n",
+       " 822          867            2.863818\n",
+       " 823          868            2.863576\n",
+       " 824          869            2.861842\n",
+       " 825          870            2.860470\n",
+       " 826          871            2.858373\n",
+       " 827          872            2.857526\n",
+       " 828          873            2.856961\n",
+       " 829          874            2.855711\n",
+       " 830          875            2.855146\n",
+       " 831          881            2.945815\n",
+       " 832          882            2.932465\n",
+       " 833          883            2.921373\n",
+       " 834          884            2.914436\n",
+       " 835          885            2.907055\n",
+       " 836          886            2.900683\n",
+       " 837          887            2.896125\n",
+       " 838          888            2.894270\n",
+       " 839          889            2.886606,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 840          890            2.882291\n",
+       " 841          891            2.882734\n",
+       " 842          892            2.876604\n",
+       " 843          893            2.874264\n",
+       " 844          894            2.870755\n",
+       " 845          895            2.867206\n",
+       " 846          896            2.863616\n",
+       " 847          897            2.864020\n",
+       " 848          898            2.861680\n",
+       " 849          899            2.858333\n",
+       " 850          900            2.855187\n",
+       " 851          901            2.854703\n",
+       " 852          902            2.852283\n",
+       " 853          903            2.850266\n",
+       " 854          904            2.847120\n",
+       " 855          905            2.845708\n",
+       " 856          906            2.848612\n",
+       " 857          907            2.842966\n",
+       " 858          908            2.841554\n",
+       " 859          909            2.842643,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 860          910            2.837843\n",
+       " 861          911            2.836795\n",
+       " 862          912            2.834657\n",
+       " 863          913            2.836311\n",
+       " 864          914            2.834576\n",
+       " 865          915            2.833044\n",
+       " 866          916            2.829817\n",
+       " 867          917            2.829253\n",
+       " 868          918            2.827639\n",
+       " 869          919            2.827115\n",
+       " 870          920            2.824050\n",
+       " 871          921            2.823727\n",
+       " 872          922            2.822477\n",
+       " 873          923            2.823162\n",
+       " 874          924            2.821387\n",
+       " 875          925            2.822678\n",
+       " 876          926            2.819572\n",
+       " 877          927            2.819290\n",
+       " 878          928            2.815902\n",
+       " 879          929            2.815499,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 880          930            2.818040\n",
+       " 881          931            2.814289\n",
+       " 882          932            2.814329\n",
+       " 883          933            2.811425\n",
+       " 884          934            2.810578\n",
+       " 885          935            2.809207\n",
+       " 886          936            2.811990\n",
+       " 887          937            2.809449\n",
+       " 888          938            2.810215\n",
+       " 889          939            2.810014\n",
+       " 890          940            2.805859\n",
+       " 891          941            2.807836\n",
+       " 892          942            2.807352\n",
+       " 893          943            2.810296\n",
+       " 894          944            2.807109\n",
+       " 895          945            2.807069\n",
+       " 896          946            2.803883\n",
+       " 897          947            2.803036\n",
+       " 898          948            2.801745\n",
+       " 899          949            2.801382,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 900          950            2.798317\n",
+       " 901          951            2.796986\n",
+       " 902          952            2.796744\n",
+       " 903          953            2.796905\n",
+       " 904          954            2.796179\n",
+       " 905          955            2.793437\n",
+       " 906          956            2.793517\n",
+       " 907          957            2.793961\n",
+       " 908          958            2.790654\n",
+       " 909          959            2.791380\n",
+       " 910          960            2.789847\n",
+       " 911          961            2.786540\n",
+       " 912          962            2.790613\n",
+       " 913          963            2.788395\n",
+       " 914          964            2.785370\n",
+       " 915          965            2.784321\n",
+       " 916          966            2.782587\n",
+       " 917          967            2.779965\n",
+       " 918          968            2.779723\n",
+       " 919          969            2.780328,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 920          970            2.779280\n",
+       " 921          971            2.778755\n",
+       " 922          972            2.779401\n",
+       " 923          973            2.776335\n",
+       " 924          974            2.774924\n",
+       " 925          975            2.774964\n",
+       " 926          976            2.776416\n",
+       " 927          977            2.771657\n",
+       " 928          978            2.770527\n",
+       " 929          979            2.776013\n",
+       " 930          980            2.768793\n",
+       " 931          986            2.863132\n",
+       " 932          987            2.848733\n",
+       " 933          988            2.840384\n",
+       " 934          989            2.831511\n",
+       " 935          990            2.827558\n",
+       " 936          991            2.822436\n",
+       " 937          992            2.815983\n",
+       " 938          993            2.809288\n",
+       " 939          994            2.804327,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 940          995            2.799567\n",
+       " 941          996            2.797430\n",
+       " 942          997            2.795776\n",
+       " 943          998            2.790008\n",
+       " 944          999            2.790452\n",
+       " 945         1000            2.784765\n",
+       " 946         1001            2.784120\n",
+       " 947         1002            2.781579\n",
+       " 948         1003            2.778796\n",
+       " 949         1004            2.778513\n",
+       " 950         1005            2.778433\n",
+       " 951         1006            2.774399\n",
+       " 952         1007            2.770285\n",
+       " 953         1008            2.770689\n",
+       " 954         1009            2.767139\n",
+       " 955         1010            2.766091\n",
+       " 956         1011            2.764921\n",
+       " 957         1012            2.764840\n",
+       " 958         1013            2.761331\n",
+       " 959         1014            2.759395,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 960         1015            2.758347\n",
+       " 961         1016            2.757016\n",
+       " 962         1017            2.758387\n",
+       " 963         1018            2.754313\n",
+       " 964         1019            2.752740\n",
+       " 965         1020            2.750643\n",
+       " 966         1021            2.749594\n",
+       " 967         1022            2.748868\n",
+       " 968         1023            2.746650\n",
+       " 969         1024            2.748788\n",
+       " 970         1025            2.748505\n",
+       " 971         1026            2.752337\n",
+       " 972         1027            2.742859\n",
+       " 973         1028            2.741084\n",
+       " 974         1029            2.740197\n",
+       " 975         1030            2.740519\n",
+       " 976         1031            2.738866\n",
+       " 977         1032            2.736446\n",
+       " 978         1033            2.736284\n",
+       " 979         1034            2.732695,\n",
+       "      cycle_index  discharge_capacity\n",
+       " 980         1035            2.729831\n",
+       " 981         1036            2.729791\n",
+       " 982         1037            2.729831\n",
+       " 983         1038            2.729952\n",
+       " 984         1039            2.729993\n",
+       " 985         1040            2.728218\n",
+       " 986         1041            2.726242\n",
+       " 987         1042            2.725999\n",
+       " 988         1043            2.722773\n",
+       " 989         1044            2.725717\n",
+       " 990         1045            2.720030\n",
+       " 991         1046            2.719506\n",
+       " 992         1047            2.720958\n",
+       " 993         1048            2.718498\n",
+       " 994         1049            2.715473\n",
+       " 995         1050            2.714787\n",
+       " 996         1051            2.711560\n",
+       " 997         1052            2.710108\n",
+       " 998         1053            2.710834\n",
+       " 999         1054            2.708051,\n",
+       "       cycle_index  discharge_capacity\n",
+       " 1000         1055            2.705914\n",
+       " 1001         1056            2.703655\n",
+       " 1002         1057            2.702768\n",
+       " 1003         1058            2.702445\n",
+       " 1004         1059            2.700872\n",
+       " 1005         1060            2.700953\n",
+       " 1006         1061            2.698129\n",
+       " 1007         1062            2.699097\n",
+       " 1008         1063            2.695225\n",
+       " 1009         1064            2.696435\n",
+       " 1010         1065            2.696032\n",
+       " 1011         1066            2.694217\n",
+       " 1012         1067            2.692967\n",
+       " 1013         1068            2.691031\n",
+       " 1014         1069            2.690506\n",
+       " 1015         1070            2.689538\n",
+       " 1016         1071            2.688288\n",
+       " 1017         1072            2.685707\n",
+       " 1018         1073            2.683892\n",
+       " 1019         1074            2.682561,\n",
+       "       cycle_index  discharge_capacity\n",
+       " 1020         1075            2.681956\n",
+       " 1021         1076            2.680302\n",
+       " 1022         1077            2.679415\n",
+       " 1023         1078            2.678971\n",
+       " 1024         1079            2.676107\n",
+       " 1025         1080            2.673728\n",
+       " 1026         1081            2.678406\n",
+       " 1027         1082            2.672518\n",
+       " 1028         1083            2.669130\n",
+       " 1029         1084            2.669452\n",
+       " 1030         1085            2.668283\n",
+       " 1031         1091            2.759476\n",
+       " 1032         1092            2.751329\n",
+       " 1033         1093            2.745480\n",
+       " 1034         1094            2.736405\n",
+       " 1035         1095            2.730436\n",
+       " 1036         1096            2.722450\n",
+       " 1037         1097            2.718457\n",
+       " 1038         1098            2.713496\n",
+       " 1039         1099            2.710391,\n",
+       "       cycle_index  discharge_capacity\n",
+       " 1040         1100            2.703897\n",
+       " 1041         1101            2.701921\n",
+       " 1042         1102            2.700590\n",
+       " 1043         1103            2.695427\n",
+       " 1044         1104            2.690789\n",
+       " 1045         1105            2.688288\n",
+       " 1046         1106            2.687885\n",
+       " 1047         1107            2.684053\n",
+       " 1048         1108            2.682036\n",
+       " 1049         1109            2.681633\n",
+       " 1050         1110            2.675502\n",
+       " 1051         1111            2.671388\n",
+       " 1052         1112            2.668525\n",
+       " 1053         1113            2.668565\n",
+       " 1054         1114            2.666669\n",
+       " 1055         1115            2.663080\n",
+       " 1056         1116            2.662596\n",
+       " 1057         1117            2.658885\n",
+       " 1058         1118            2.655215\n",
+       " 1059         1119            2.652432,\n",
+       "       cycle_index  discharge_capacity\n",
+       " 1060         1120            2.654166\n",
+       " 1061         1121            2.651141\n",
+       " 1062         1122            2.646261\n",
+       " 1063         1123            2.647632\n",
+       " 1064         1124            2.641824\n",
+       " 1065         1125            2.640614\n",
+       " 1066         1126            2.639606\n",
+       " 1067         1127            2.638033\n",
+       " 1068         1128            2.637670\n",
+       " 1069         1129            2.632346\n",
+       " 1070         1130            2.631781\n",
+       " 1071         1131            2.629523\n",
+       " 1072         1132            2.628151\n",
+       " 1073         1133            2.625772\n",
+       " 1074         1134            2.623836\n",
+       " 1075         1135            2.623392\n",
+       " 1076         1136            2.619601\n",
+       " 1077         1137            2.618552\n",
+       " 1078         1138            2.616697\n",
+       " 1079         1139            2.614680,\n",
+       "       cycle_index  discharge_capacity\n",
+       " 1080         1140            2.612784\n",
+       " 1081         1141            2.612421\n",
+       " 1082         1142            2.610122\n",
+       " 1083         1143            2.607904\n",
+       " 1084         1144            2.608307\n",
+       " 1085         1145            2.606896\n",
+       " 1086         1146            2.600926\n",
+       " 1087         1147            2.608227\n",
+       " 1088         1148            2.599071\n",
+       " 1089         1149            2.596288\n",
+       " 1090         1150            2.592456\n",
+       " 1091         1151            2.592214\n",
+       " 1092         1152            2.589916\n",
+       " 1093         1153            2.587979\n",
+       " 1094         1154            2.583744\n",
+       " 1095         1155            2.585156\n",
+       " 1096         1156            2.583018\n",
+       " 1097         1157            2.579429\n",
+       " 1098         1158            2.579429\n",
+       " 1099         1159            2.576404,\n",
+       "       cycle_index  discharge_capacity\n",
+       " 1100         1160            2.573621\n",
+       " 1101         1161            2.571564\n",
+       " 1102         1162            2.568700\n",
+       " 1103         1163            2.568740\n",
+       " 1104         1164            2.565514\n",
+       " 1105         1165            2.567047\n",
+       " 1106         1166            2.559545\n",
+       " 1107         1167            2.556399\n",
+       " 1108         1168            2.554342\n",
+       " 1109         1169            2.551155\n",
+       " 1110         1170            2.549502\n",
+       " 1111         1171            2.548776\n",
+       " 1112         1172            2.545025\n",
+       " 1113         1173            2.542847\n",
+       " 1114         1174            2.539822\n",
+       " 1115         1175            2.538531\n",
+       " 1116         1176            2.533651\n",
+       " 1117         1177            2.532158\n",
+       " 1118         1178            2.531271\n",
+       " 1119         1179            2.529375,\n",
+       "       cycle_index  discharge_capacity\n",
+       " 1120         1180            2.526028\n",
+       " 1121         1181            2.523366\n",
+       " 1122         1182            2.519332\n",
+       " 1123         1183            2.520058\n",
+       " 1124         1184            2.514412\n",
+       " 1125         1185            2.513121\n",
+       " 1126         1186            2.511185\n",
+       " 1127         1187            2.507273\n",
+       " 1128         1188            2.502836\n",
+       " 1129         1189            2.500900\n",
+       " 1130         1190            2.496867\n",
+       " 1131         1196            2.609598\n",
+       " 1132         1197            2.595118\n",
+       " 1133         1198            2.586568\n",
+       " 1134         1199            2.580276\n",
+       " 1135         1200            2.574266\n",
+       " 1136         1201            2.565272\n",
+       " 1137         1202            2.561440\n",
+       " 1138         1203            2.554947\n",
+       " 1139         1204            2.549381,\n",
+       "       cycle_index  discharge_capacity\n",
+       " 1140         1205            2.543855\n",
+       " 1141         1206            2.540991\n",
+       " 1142         1207            2.535950\n",
+       " 1143         1208            2.531755\n",
+       " 1144         1209            2.526431\n",
+       " 1145         1210            2.521228\n",
+       " 1146         1211            2.517437\n",
+       " 1147         1212            2.515380\n",
+       " 1148         1213            2.511427\n",
+       " 1149         1214            2.514452\n",
+       " 1150         1215            2.505095\n",
+       " 1151         1216            2.499287\n",
+       " 1152         1217            2.494528\n",
+       " 1153         1218            2.490817\n",
+       " 1154         1219            2.486904\n",
+       " 1155         1220            2.484323\n",
+       " 1156         1221            2.480814\n",
+       " 1157         1222            2.476862\n",
+       " 1158         1223            2.471820\n",
+       " 1159         1224            2.471659,\n",
+       "       cycle_index  discharge_capacity\n",
+       " 1160         1225            2.468876\n",
+       " 1161         1226            2.464076\n",
+       " 1162         1227            2.464439\n",
+       " 1163         1228            2.458913\n",
+       " 1164         1229            2.456171\n",
+       " 1165         1230            2.453186\n",
+       " 1166         1231            2.450605\n",
+       " 1167         1232            2.444595\n",
+       " 1168         1233            2.440360\n",
+       " 1169         1234            2.443385\n",
+       " 1170         1235            2.434189\n",
+       " 1171         1236            2.430559\n",
+       " 1172         1237            2.428663\n",
+       " 1173         1238            2.426122\n",
+       " 1174         1239            2.421686\n",
+       " 1175         1240            2.417612\n",
+       " 1176         1241            2.414748\n",
+       " 1177         1242            2.410473\n",
+       " 1178         1243            2.408456\n",
+       " 1179         1244            2.406359,\n",
+       "       cycle_index  discharge_capacity\n",
+       " 1180         1245            2.401479\n",
+       " 1181         1246            2.399180\n",
+       " 1182         1247            2.396155\n",
+       " 1183         1248            2.388976\n",
+       " 1184         1249            2.385749\n",
+       " 1185         1250            2.383490\n",
+       " 1186         1251            2.380304\n",
+       " 1187         1252            2.377400\n",
+       " 1188         1253            2.374536\n",
+       " 1189         1254            2.377400\n",
+       " 1190         1255            2.365986\n",
+       " 1191         1256            2.359250\n",
+       " 1192         1257            2.356346\n",
+       " 1193         1258            2.355015\n",
+       " 1194         1259            2.349570\n",
+       " 1195         1260            2.345859\n",
+       " 1196         1261            2.342350\n",
+       " 1197         1262            2.339487\n",
+       " 1198         1263            2.334848\n",
+       " 1199         1264            2.332630,\n",
+       "       cycle_index  discharge_capacity\n",
+       " 1200         1265            2.326862\n",
+       " 1201         1266            2.326056\n",
+       " 1202         1267            2.319804\n",
+       " 1203         1268            2.313996\n",
+       " 1204         1269            2.313351\n",
+       " 1205         1270            2.307624\n",
+       " 1206         1271            2.303671\n",
+       " 1207         1272            2.299113\n",
+       " 1208         1273            2.295120\n",
+       " 1209         1274            2.291571\n",
+       " 1210         1275            2.288385\n",
+       " 1211         1276            2.282778\n",
+       " 1212         1277            2.279189\n",
+       " 1213         1278            2.273623\n",
+       " 1214         1279            2.271485\n",
+       " 1215         1280            2.264991\n",
+       " 1216         1281            2.262007\n",
+       " 1217         1282            2.258014\n",
+       " 1218         1283            2.253859\n",
+       " 1219         1284            2.252004,\n",
+       "       cycle_index  discharge_capacity\n",
+       " 1220         1285            2.246680\n",
+       " 1221         1286            2.242606\n",
+       " 1222         1287            2.234742\n",
+       " 1223         1288            2.230870\n",
+       " 1224         1289            2.226877\n",
+       " 1225         1290            2.225062\n",
+       " 1226         1291            2.221230\n",
+       " 1227         1292            2.215019\n",
+       " 1228         1293            2.210663\n",
+       " 1229         1294            2.204895\n",
+       " 1230         1295            2.210622\n",
+       " 1231         1301            2.326782\n",
+       " 1232         1302            2.317505\n",
+       " 1233         1303            2.306978\n",
+       " 1234         1304            2.297298\n",
+       " 1235         1305            2.290482\n",
+       " 1236         1306            2.283988\n",
+       " 1237         1307            2.275922\n",
+       " 1238         1308            2.270678\n",
+       " 1239         1309            2.261402,\n",
+       "       cycle_index  discharge_capacity\n",
+       " 1240         1310            2.253577\n",
+       " 1241         1311            2.243453\n",
+       " 1242         1312            2.238815\n",
+       " 1243         1313            2.234378\n",
+       " 1244         1314            2.228369\n",
+       " 1245         1315            2.224295\n",
+       " 1246         1316            2.216793\n",
+       " 1247         1317            2.214051\n",
+       " 1248         1318            2.206266\n",
+       " 1249         1319            2.199773\n",
+       " 1250         1320            2.193279\n",
+       " 1251         1321            2.189528\n",
+       " 1252         1322            2.183276\n",
+       " 1253         1323            2.179445\n",
+       " 1254         1324            2.174201\n",
+       " 1255         1325            2.179324\n",
+       " 1256         1326            2.185132\n",
+       " 1257         1327            2.181542\n",
+       " 1258         1328            2.180332\n",
+       " 1259         1329            2.189488,\n",
+       "       cycle_index  discharge_capacity\n",
+       " 1260         1330            2.171378\n",
+       " 1261         1331            2.147259\n",
+       " 1262         1332            2.138789\n",
+       " 1263         1333            2.132134\n",
+       " 1264         1334            2.123180\n",
+       " 1265         1335            2.117695\n",
+       " 1266         1336            2.108579\n",
+       " 1267         1337            2.105635\n",
+       " 1268         1338            2.100916\n",
+       " 1269         1339            2.095915\n",
+       " 1270         1340            2.092527\n",
+       " 1271         1341            2.085186\n",
+       " 1272         1342            2.082161\n",
+       " 1273         1343            2.072037\n",
+       " 1274         1344            2.065262\n",
+       " 1275         1345            2.061632\n",
+       " 1276         1346            2.057639\n",
+       " 1277         1347            2.050540\n",
+       " 1278         1348            2.047757\n",
+       " 1279         1349            2.044006,\n",
+       "       cycle_index  discharge_capacity\n",
+       " 1280         1350            2.039811\n",
+       " 1281         1351            2.031543\n",
+       " 1282         1352            2.023476\n",
+       " 1283         1353            2.016700\n",
+       " 1284         1354            2.008674\n",
+       " 1285         1355            2.006738\n",
+       " 1286         1356            1.999196\n",
+       " 1287         1357            1.994396\n",
+       " 1288         1358            1.986531\n",
+       " 1289         1359            1.982135\n",
+       " 1290         1360            1.972778\n",
+       " 1291         1361            1.965155\n",
+       " 1292         1362            1.960476\n",
+       " 1293         1363            1.954749\n",
+       " 1294         1364            1.952490\n",
+       " 1295         1365            1.943496\n",
+       " 1296         1366            1.941842\n",
+       " 1297         1367            1.933130\n",
+       " 1298         1368            1.928129\n",
+       " 1299         1369            1.920022,\n",
+       "       cycle_index  discharge_capacity\n",
+       " 1300         1370            1.912520\n",
+       " 1301         1371            1.906147\n",
+       " 1302         1372            1.902800\n",
+       " 1303         1373            1.893563\n",
+       " 1304         1374            1.888481\n",
+       " 1305         1375            1.885214\n",
+       " 1306         1376            1.875050\n",
+       " 1307         1377            1.862466\n",
+       " 1308         1378            1.859078\n",
+       " 1309         1379            1.852141\n",
+       " 1310         1380            1.850003\n",
+       " 1311         1381            1.845204\n",
+       " 1312         1382            1.840485\n",
+       " 1313         1383            1.826045\n",
+       " 1314         1384            1.811889\n",
+       " 1315         1385            1.807896\n",
+       " 1316         1386            1.801604\n",
+       " 1317         1387            1.789826\n",
+       " 1318         1388            1.784180\n",
+       " 1319         1389            1.771233,\n",
+       "       cycle_index  discharge_capacity\n",
+       " 1320         1390            1.778775\n",
+       " 1321         1391            1.766675\n",
+       " 1322         1392            1.745944\n",
+       " 1323         1393            1.741104\n",
+       " 1324         1394            1.731787\n",
+       " 1325         1395            1.718558\n",
+       " 1326         1396            1.714928\n",
+       " 1327         1397            1.707869\n",
+       " 1328         1398            1.711741\n",
+       " 1329         1399            1.700246\n",
+       " 1330         1400            1.693914\n",
+       " 1331         1406            1.930791\n",
+       " 1332         1407            1.918973\n",
+       " 1333         1408            1.910503\n",
+       " 1334         1409            1.889772\n",
+       " 1335         1410            1.881181\n",
+       " 1336         1411            1.860692\n",
+       " 1337         1412            1.860167\n",
+       " 1338         1413            1.839557\n",
+       " 1339         1414            1.830643,\n",
+       "       cycle_index  discharge_capacity\n",
+       " 1340         1415            1.814470\n",
+       " 1341         1416            1.799627\n",
+       " 1342         1417            1.776557\n",
+       " 1343         1418            1.770023\n",
+       " 1344         1419            1.763166\n",
+       " 1345         1420            1.744694\n",
+       " 1346         1421            1.728237\n",
+       " 1347         1422            1.721300\n",
+       " 1348         1423            1.710209\n",
+       " 1349         1424            1.693551\n",
+       " 1350         1425            1.675401\n",
+       " 1351         1426            1.665035\n",
+       " 1352         1427            1.650314\n",
+       " 1353         1428            1.628736\n",
+       " 1354         1429            1.619903\n",
+       " 1355         1430            1.600301\n",
+       " 1356         1431            1.570858\n",
+       " 1357         1432            1.564969\n",
+       " 1358         1433            1.560371\n",
+       " 1359         1434            1.536131,\n",
+       "       cycle_index  discharge_capacity\n",
+       " 1360         1435            1.530645\n",
+       " 1361         1436            1.508059\n",
+       " 1362         1437            1.487811\n",
+       " 1363         1438            1.468008\n",
+       " 1364         1439            1.463733\n",
+       " 1365         1440            1.442074\n",
+       " 1366         1441            1.425416\n",
+       " 1367         1442            1.429449\n",
+       " 1368         1443            1.402305\n",
+       " 1369         1444            1.385930\n",
+       " 1370         1445            1.373830\n",
+       " 1371         1446            1.357495\n",
+       " 1372         1447            1.356729\n",
+       " 1373         1448            1.332126\n",
+       " 1374         1449            1.322244\n",
+       " 1375         1450            1.306796\n",
+       " 1376         1451            1.301795\n",
+       " 1377         1452            1.283887\n",
+       " 1378         1453            1.266261\n",
+       " 1379         1454            1.256985,\n",
+       "       cycle_index  discharge_capacity\n",
+       " 1380         1455            1.252871\n",
+       " 1381         1456            1.250814\n",
+       " 1382         1457            1.243070\n",
+       " 1383         1458            1.224396\n",
+       " 1384         1459            1.212901\n",
+       " 1385         1460            1.198703\n",
+       " 1386         1461            1.176278\n",
+       " 1387         1462            1.169220\n",
+       " 1388         1463            1.158773\n",
+       " 1389         1464            1.143568\n",
+       " 1390         1465            1.133928\n",
+       " 1391         1466            1.129492\n",
+       " 1392         1467            1.122232\n",
+       " 1393         1468            1.109728\n",
+       " 1394         1469            1.099605\n",
+       " 1395         1470            1.089078\n",
+       " 1396         1471            1.087666\n",
+       " 1397         1472            1.075365\n",
+       " 1398         1473            1.099887\n",
+       " 1399         1474            1.047172,\n",
+       "       cycle_index  discharge_capacity\n",
+       " 1400         1475            1.036362\n",
+       " 1401         1476            1.020753\n",
+       " 1402         1477            1.013211\n",
+       " 1403         1478            1.001676\n",
+       " 1404         1479            0.993448\n",
+       " 1405         1480            0.990020\n",
+       " 1406         1481            0.981953\n",
+       " 1407         1482            0.969530\n",
+       " 1408         1483            0.957430\n",
+       " 1409         1484            0.959326\n",
+       " 1410         1485            0.946137\n",
+       " 1411         1486            0.930810\n",
+       " 1412         1487            0.922623\n",
+       " 1413         1488            0.912055\n",
+       " 1414         1489            0.910805\n",
+       " 1415         1490            0.895842\n",
+       " 1416         1491            0.888783\n",
+       " 1417         1492            0.882330\n",
+       " 1418         1493            0.867891\n",
+       " 1419         1494            0.863293,\n",
+       "       cycle_index  discharge_capacity\n",
+       " 1420         1495            0.860308\n",
+       " 1421         1496            0.851798\n",
+       " 1422         1497            0.838326\n",
+       " 1423         1498            0.840020\n",
+       " 1424         1499            0.820902\n",
+       " 1425         1500            0.815498\n",
+       " 1426         1501            0.809892\n",
+       " 1427         1502            0.804971\n",
+       " 1428         1503            0.800776\n",
+       " 1429         1504            0.790249\n",
+       " 1430         1505            0.781900\n",
+       " 1431         1511            1.223105\n",
+       " 1432         1512            1.212901\n",
+       " 1433         1513            1.183619\n",
+       " 1434         1514            1.145464\n",
+       " 1435         1515            1.120255\n",
+       " 1436         1516            1.101904\n",
+       " 1437         1517            1.078511\n",
+       " 1438         1518            1.070525\n",
+       " 1439         1519            1.041162,\n",
+       "       cycle_index  discharge_capacity\n",
+       " 1440         1520            1.024666\n",
+       " 1441         1521            1.006233\n",
+       " 1442         1522            0.987196\n",
+       " 1443         1523            0.979977\n",
+       " 1444         1524            0.969288\n",
+       " 1445         1525            0.944524\n",
+       " 1446         1526            0.935812\n",
+       " 1447         1527            0.915161\n",
+       " 1448         1528            0.904675\n",
+       " 1449         1529            0.892212\n",
+       " 1450         1530            0.878216\n",
+       " 1451         1531            0.874384\n",
+       " 1452         1532            0.872166\n",
+       " 1453         1533            0.841674\n",
+       " 1454         1534            0.827557\n",
+       " 1455         1535            0.827194\n",
+       " 1456         1536            0.801906\n",
+       " 1457         1537            0.799203\n",
+       " 1458         1538            0.780973\n",
+       " 1459         1539            0.766735,\n",
+       "       cycle_index  discharge_capacity\n",
+       " 1460         1540            0.758951\n",
+       " 1461         1541            0.752457\n",
+       " 1462         1542            0.743302\n",
+       " 1463         1543            0.730919\n",
+       " 1464         1544            0.724345\n",
+       " 1465         1545            0.716036\n",
+       " 1466         1546            0.707123\n",
+       " 1467         1547            0.694902\n",
+       " 1468         1548            0.683245\n",
+       " 1469         1549            0.674775\n",
+       " 1470         1550            0.669895\n",
+       " 1471         1551            0.656908\n",
+       " 1472         1552            0.646542\n",
+       " 1473         1553            0.639081\n",
+       " 1474         1554            0.628191\n",
+       " 1475         1555            0.619922\n",
+       " 1476         1556            0.608427\n",
+       " 1477         1557            0.603265\n",
+       " 1478         1558            0.596368\n",
+       " 1479         1559            0.587454]"
+      ]
+     },
+     "execution_count": 165,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cycle_window_labels"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 144,
+   "id": "10b24684",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(-0.0057076483299999484, -0.002683982064285725)\n",
+      "(-0.006961283289999986, -0.007294125555555592)\n",
+      "(-0.007940705100000046, -0.008693021755555542)\n",
+      "(-0.009080091300000027, -0.009589287600000032)\n",
+      "(-0.009597658440000023, -0.009708067077777778)\n",
+      "(-0.009927670649999998, 0.010002813928571433)\n",
+      "(-0.016075614869999998, -0.014081120777777765)\n",
+      "(-0.013681280169999966, -0.013258792933333355)\n",
+      "(-0.010944098959999992, -0.009315201233333317)\n",
+      "(-0.008313078060000034, -0.006055044455555553)\n",
+      "(-0.005558454579999994, 0.013609178892857145)\n",
+      "(-0.01025777174, -0.006016181911111109)\n",
+      "(-0.0041528498099999926, -0.003213118022222251)\n",
+      "(-0.0020569396800000027, -0.0013951928333332869)\n",
+      "(-0.001014358169999996, -0.0010135090333333412)\n",
+      "(-0.0005384133200000196, 0.013742624900000016)\n",
+      "(-0.004995112599999985, -0.0019837232888888995)\n",
+      "(-0.00018890318999997824, 0.00027861758888889397)\n",
+      "(0.00016535871000002977, -0.00011874527777777644)\n",
+      "(-0.0011306517500000001, -0.0042818926333333274)\n",
+      "(-0.010583124420000001, -0.011334728578571429)\n",
+      "(-0.04432621187999999, -0.0448088219111111)\n",
+      "(-0.029928353169999998, -0.01647484817777778)\n",
+      "(-0.009613796640000005, -0.00784832002222222)\n",
+      "(-0.00651698074, -0.005579255644444441)\n",
+      "(-0.004777325600000004, -0.0037091047785714243)\n",
+      "(-0.004419045359999996, -0.003381911200000001)\n",
+      "(-0.0028528182099999966, -0.002649960722222227)\n",
+      "(-0.0023042901999999975, -0.0019486405333333358)\n",
+      "(-0.002058281519999999, -0.0019710394333333336)\n",
+      "(-0.0019554360300000017, -0.002391106714285714)\n",
+      "(-0.002040123020000001, -0.001718591566666668)\n",
+      "(-0.0017087456399999979, -0.001440735944444444)\n",
+      "(-0.0009578744200000016, -0.001288395655555555)\n",
+      "(-0.0012529800300000004, -0.0008402461555555543)\n",
+      "(-0.0009363685499999997, -0.0007485437642857144)\n",
+      "(-0.0011561762199999992, -0.0008409978111111111)\n",
+      "(-0.0008570531600000014, -0.014481137099999998)\n"
+     ]
+    }
+   ],
+   "source": [
+    "for i in range(len(cycle_window_labels)):\n",
+    "    print(find_slope(cycle_window_labels[i]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 116,
+   "id": "ab16b749",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[25.   ,  4.432],\n",
+       "       [26.   ,  4.426],\n",
+       "       [27.   ,  4.422],\n",
+       "       [28.   ,  4.416],\n",
+       "       [29.   ,  4.411],\n",
+       "       [30.   ,  4.405],\n",
+       "       [31.   ,  4.398],\n",
+       "       [32.   ,  4.393],\n",
+       "       [33.   ,  4.387],\n",
+       "       [34.   ,  4.381],\n",
+       "       [35.   ,  4.375],\n",
+       "       [41.   ,  4.392],\n",
+       "       [42.   ,  4.384],\n",
+       "       [43.   ,  4.378],\n",
+       "       [44.   ,  4.37 ],\n",
+       "       [45.   ,  4.363],\n",
+       "       [46.   ,  4.356],\n",
+       "       [47.   ,  4.35 ],\n",
+       "       [48.   ,  4.343],\n",
+       "       [49.   ,  4.337]])"
+      ]
+     },
+     "execution_count": 116,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.array(cycle_window_labels[0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 105,
+   "id": "380a6f43",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[[    discharge_capacity  cycle_index\n",
+       "  20            3.809959           25\n",
+       "  21            3.807600           26\n",
+       "  22            3.804501           27\n",
+       "  23            3.801214           28\n",
+       "  24            3.798881           29\n",
+       "  25            3.794310           30\n",
+       "  26            3.791211           31\n",
+       "  27            3.789114           32\n",
+       "  28            3.786210           33\n",
+       "  29            3.781344           34\n",
+       "  30            3.780261           35\n",
+       "  31            3.800649           41\n",
+       "  32            3.793537           42\n",
+       "  33            3.788503           43\n",
+       "  34            3.783945           44\n",
+       "  35            3.779441           45\n",
+       "  36            3.774118           46\n",
+       "  37            3.769795           47\n",
+       "  38            3.764975           48\n",
+       "  39            3.760485           49,\n",
+       "      discharge_capacity  cycle_index\n",
+       "  40            3.756755           50\n",
+       "  41            3.752721           51\n",
+       "  42            3.748500           52\n",
+       "  43            3.744379           53\n",
+       "  44            3.740676           54\n",
+       "  45            3.736864           55\n",
+       "  46            3.732623           56\n",
+       "  47            3.728455           57\n",
+       "  48            3.724294           58\n",
+       "  49            3.720187           59\n",
+       "  50            3.716792           60\n",
+       "  51            3.712786           61\n",
+       "  52            3.708961           62\n",
+       "  53            3.703563           63\n",
+       "  54            3.699517           64\n",
+       "  55            3.695847           65\n",
+       "  56            3.691571           66\n",
+       "  57            3.688130           67\n",
+       "  58            3.683243           68\n",
+       "  59            3.679660           69,\n",
+       "      discharge_capacity  cycle_index\n",
+       "  60            3.674135           70\n",
+       "  61            3.670753           71\n",
+       "  62            3.665436           72\n",
+       "  63            3.661188           73\n",
+       "  64            3.657551           74\n",
+       "  65            3.653269           75\n",
+       "  66            3.647220           76\n",
+       "  67            3.643039           77\n",
+       "  68            3.639153           78\n",
+       "  69            3.634918           79\n",
+       "  70            3.630609           80\n",
+       "  71            3.625353           81\n",
+       "  72            3.619780           82\n",
+       "  73            3.614880           83\n",
+       "  74            3.610417           84\n",
+       "  75            3.606189           85\n",
+       "  76            3.601429           86\n",
+       "  77            3.596516           87\n",
+       "  78            3.592422           88\n",
+       "  79            3.587185           89,\n",
+       "      discharge_capacity  cycle_index\n",
+       "  80            3.582561           90\n",
+       "  81            3.577116           91\n",
+       "  82            3.571073           92\n",
+       "  83            3.565675           93\n",
+       "  84            3.560936           94\n",
+       "  85            3.556258           95\n",
+       "  86            3.550490           96\n",
+       "  87            3.546296           97\n",
+       "  88            3.540844           98\n",
+       "  89            3.536072           99\n",
+       "  90            3.530082          100\n",
+       "  91            3.525222          101\n",
+       "  92            3.520664          102\n",
+       "  93            3.514769          103\n",
+       "  94            3.510864          104\n",
+       "  95            3.505459          105\n",
+       "  96            3.500041          106\n",
+       "  97            3.493656          107\n",
+       "  98            3.487949          108\n",
+       "  99            3.483035          109,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  100            3.476904          110\n",
+       "  101            3.470976          111\n",
+       "  102            3.466062          112\n",
+       "  103            3.460395          113\n",
+       "  104            3.454675          114\n",
+       "  105            3.449943          115\n",
+       "  106            3.444236          116\n",
+       "  107            3.438179          117\n",
+       "  108            3.432835          118\n",
+       "  109            3.427982          119\n",
+       "  110            3.422497          120\n",
+       "  111            3.416554          121\n",
+       "  112            3.411432          122\n",
+       "  113            3.404744          123\n",
+       "  114            3.398015          124\n",
+       "  115            3.392449          125\n",
+       "  116            3.386782          126\n",
+       "  117            3.380961          127\n",
+       "  118            3.376451          128\n",
+       "  119            3.370368          129,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  120            3.364385          130\n",
+       "  121            3.357831          131\n",
+       "  122            3.351936          132\n",
+       "  123            3.346760          133\n",
+       "  124            3.340865          134\n",
+       "  125            3.336482          135\n",
+       "  126            3.328375          136\n",
+       "  127            3.323132          137\n",
+       "  128            3.315570          138\n",
+       "  129            3.309890          139\n",
+       "  130            3.304949          140\n",
+       "  131            3.525733          146\n",
+       "  132            3.499732          147\n",
+       "  133            3.482316          148\n",
+       "  134            3.466398          149\n",
+       "  135            3.451220          150\n",
+       "  136            3.437036          151\n",
+       "  137            3.424748          152\n",
+       "  138            3.411701          153\n",
+       "  139            3.399366          154,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  140            3.386447          155\n",
+       "  141            3.375348          156\n",
+       "  142            3.364533          157\n",
+       "  143            3.352474          158\n",
+       "  144            3.342505          159\n",
+       "  145            3.333860          160\n",
+       "  146            3.323677          161\n",
+       "  147            3.313150          162\n",
+       "  148            3.304095          163\n",
+       "  149            3.295242          164\n",
+       "  150            3.284165          165\n",
+       "  151            3.277288          166\n",
+       "  152            3.268785          167\n",
+       "  153            3.260732          168\n",
+       "  154            3.253452          169\n",
+       "  155            3.244653          170\n",
+       "  156            3.236539          171\n",
+       "  157            3.228607          172\n",
+       "  158            3.219916          173\n",
+       "  159            3.212616          174,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  160            3.204469          175\n",
+       "  161            3.198137          176\n",
+       "  162            3.190977          177\n",
+       "  163            3.181271          178\n",
+       "  164            3.175396          179\n",
+       "  165            3.167605          180\n",
+       "  166            3.160211          181\n",
+       "  167            3.153549          182\n",
+       "  168            3.148797          183\n",
+       "  169            3.141477          184\n",
+       "  170            3.134762          185\n",
+       "  171            3.126164          186\n",
+       "  172            3.119193          187\n",
+       "  173            3.113923          188\n",
+       "  174            3.106751          189\n",
+       "  175            3.100096          190\n",
+       "  176            3.094490          191\n",
+       "  177            3.087835          192\n",
+       "  178            3.080643          193\n",
+       "  179            3.075648          194,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  180            3.069087          195\n",
+       "  181            3.063253          196\n",
+       "  182            3.057344          197\n",
+       "  183            3.051826          198\n",
+       "  184            3.046952          199\n",
+       "  185            3.039551          200\n",
+       "  186            3.032876          201\n",
+       "  187            3.026846          202\n",
+       "  188            3.022565          203\n",
+       "  189            3.016360          204\n",
+       "  190            3.012192          205\n",
+       "  191            3.006848          206\n",
+       "  192            3.000873          207\n",
+       "  193            2.995213          208\n",
+       "  194            2.989116          209\n",
+       "  195            2.982965          210\n",
+       "  196            2.977460          211\n",
+       "  197            2.972950          212\n",
+       "  198            2.969488          213\n",
+       "  199            2.963546          214,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  200            2.958652          215\n",
+       "  201            2.953234          216\n",
+       "  202            2.948838          217\n",
+       "  203            2.941632          218\n",
+       "  204            2.936449          219\n",
+       "  205            2.931690          220\n",
+       "  206            2.928376          221\n",
+       "  207            2.923449          222\n",
+       "  208            2.917654          223\n",
+       "  209            2.912566          224\n",
+       "  210            2.908002          225\n",
+       "  211            2.900184          226\n",
+       "  212            2.896117          227\n",
+       "  213            2.892601          228\n",
+       "  214            2.886975          229\n",
+       "  215            2.884058          230\n",
+       "  216            2.877511          231\n",
+       "  217            2.872832          232\n",
+       "  218            2.868866          233\n",
+       "  219            2.864006          234,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  220            2.858575          235\n",
+       "  221            2.855026          236\n",
+       "  222            2.849823          237\n",
+       "  223            2.845809          238\n",
+       "  224            2.841615          239\n",
+       "  225            2.837972          240\n",
+       "  226            2.832850          241\n",
+       "  227            2.827304          242\n",
+       "  228            2.822034          243\n",
+       "  229            2.819359          244\n",
+       "  230            2.817436          245\n",
+       "  231            3.222927          251\n",
+       "  232            3.163155          252\n",
+       "  233            3.124208          253\n",
+       "  234            3.094920          254\n",
+       "  235            3.068483          255\n",
+       "  236            3.045493          256\n",
+       "  237            3.024608          257\n",
+       "  238            3.006755          258\n",
+       "  239            2.989284          259,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  240            2.973682          260\n",
+       "  241            2.958746          261\n",
+       "  242            2.946156          262\n",
+       "  243            2.932530          263\n",
+       "  244            2.920101          264\n",
+       "  245            2.911040          265\n",
+       "  246            2.901474          266\n",
+       "  247            2.890585          267\n",
+       "  248            2.881215          268\n",
+       "  249            2.872321          269\n",
+       "  250            2.863059          270\n",
+       "  251            2.854199          271\n",
+       "  252            2.846630          272\n",
+       "  253            2.839505          273\n",
+       "  254            2.833313          274\n",
+       "  255            2.826793          275\n",
+       "  256            2.818593          276\n",
+       "  257            2.811783          277\n",
+       "  258            2.806453          278\n",
+       "  259            2.799146          279,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  260            2.793156          280\n",
+       "  261            2.787752          281\n",
+       "  262            2.783497          282\n",
+       "  263            2.779269          283\n",
+       "  264            2.771807          284\n",
+       "  265            2.767008          285\n",
+       "  266            2.762148          286\n",
+       "  267            2.757308          287\n",
+       "  268            2.751359          288\n",
+       "  269            2.746687          289\n",
+       "  270            2.743373          290\n",
+       "  271            2.738534          291\n",
+       "  272            2.733620          292\n",
+       "  273            2.728867          293\n",
+       "  274            2.724215          294\n",
+       "  275            2.719517          295\n",
+       "  276            2.713951          296\n",
+       "  277            2.711941          297\n",
+       "  278            2.708035          298\n",
+       "  279            2.705481          299,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  280            2.701018          300\n",
+       "  281            2.696434          301\n",
+       "  282            2.691910          302\n",
+       "  283            2.687594          303\n",
+       "  284            2.684529          304\n",
+       "  285            2.681484          305\n",
+       "  286            2.678990          306\n",
+       "  287            2.674412          307\n",
+       "  288            2.671851          308\n",
+       "  289            2.668033          309\n",
+       "  290            2.664578          310\n",
+       "  291            2.662568          311\n",
+       "  292            2.658481          312\n",
+       "  293            2.655590          313\n",
+       "  294            2.652115          314\n",
+       "  295            2.650926          315\n",
+       "  296            2.647598          316\n",
+       "  297            2.644130          317\n",
+       "  298            2.640560          318\n",
+       "  299            2.636849          319,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  300            2.635909          320\n",
+       "  301            2.633153          321\n",
+       "  302            2.630255          322\n",
+       "  303            2.627372          323\n",
+       "  304            2.625174          324\n",
+       "  305            2.623883          325\n",
+       "  306            2.618364          326\n",
+       "  307            2.616482          327\n",
+       "  308            2.616146          328\n",
+       "  309            2.613914          329\n",
+       "  310            2.613417          330\n",
+       "  311            2.608308          331\n",
+       "  312            2.606386          332\n",
+       "  313            2.605828          333\n",
+       "  314            2.600921          334\n",
+       "  315            2.598138          335\n",
+       "  316            2.596410          336\n",
+       "  317            2.594898          337\n",
+       "  318            2.595241          338\n",
+       "  319            2.590071          339,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  320            2.587860          340\n",
+       "  321            2.584653          341\n",
+       "  322            2.584102          342\n",
+       "  323            2.581326          343\n",
+       "  324            2.580042          344\n",
+       "  325            2.580183          345\n",
+       "  326            2.576748          346\n",
+       "  327            2.573199          347\n",
+       "  328            2.571693          348\n",
+       "  329            2.569650          349\n",
+       "  330            2.567667          350\n",
+       "  331            2.985883          356\n",
+       "  332            2.932012          357\n",
+       "  333            2.891734          358\n",
+       "  334            2.859563          359\n",
+       "  335            2.835283          360\n",
+       "  336            2.807978          361\n",
+       "  337            2.788646          362\n",
+       "  338            2.770684          363\n",
+       "  339            2.754754          364,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  340            2.740086          365\n",
+       "  341            2.726333          366\n",
+       "  342            2.714509          367\n",
+       "  343            2.703902          368\n",
+       "  344            2.694726          369\n",
+       "  345            2.685712          370\n",
+       "  346            2.675259          371\n",
+       "  347            2.666433          372\n",
+       "  348            2.659073          373\n",
+       "  349            2.652384          374\n",
+       "  350            2.646005          375\n",
+       "  351            2.640090          376\n",
+       "  352            2.632675          377\n",
+       "  353            2.626914          378\n",
+       "  354            2.621987          379\n",
+       "  355            2.615964          380\n",
+       "  356            2.610036          381\n",
+       "  357            2.606097          382\n",
+       "  358            2.603542          383\n",
+       "  359            2.598709          384,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  360            2.594340          385\n",
+       "  361            2.590119          386\n",
+       "  362            2.587712          387\n",
+       "  363            2.583497          388\n",
+       "  364            2.580042          389\n",
+       "  365            2.576392          390\n",
+       "  366            2.573643          391\n",
+       "  367            2.572803          392\n",
+       "  368            2.568870          393\n",
+       "  369            2.565872          394\n",
+       "  370            2.562155          395\n",
+       "  371            2.559869          396\n",
+       "  372            2.556650          397\n",
+       "  373            2.556327          398\n",
+       "  374            2.555003          399\n",
+       "  375            2.552677          400\n",
+       "  376            2.549961          401\n",
+       "  377            2.546452          402\n",
+       "  378            2.544698          403\n",
+       "  379            2.542554          404,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  380            2.540860          405\n",
+       "  381            2.538695          406\n",
+       "  382            2.536174          407\n",
+       "  383            2.535348          408\n",
+       "  384            2.533727          409\n",
+       "  385            2.531160          410\n",
+       "  386            2.529291          411\n",
+       "  387            2.526495          412\n",
+       "  388            2.524707          413\n",
+       "  389            2.521245          414\n",
+       "  390            2.519033          415\n",
+       "  391            2.520848          416\n",
+       "  392            2.519450          417\n",
+       "  393            2.518139          418\n",
+       "  394            2.515289          419\n",
+       "  395            2.513615          420\n",
+       "  396            2.511471          421\n",
+       "  397            2.510436          422\n",
+       "  398            2.507572          423\n",
+       "  399            2.505347          424,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  400            2.504951          425\n",
+       "  401            2.504292          426\n",
+       "  402            2.503963          427\n",
+       "  403            2.503069          428\n",
+       "  404            2.501435          429\n",
+       "  405            2.500118          430\n",
+       "  406            2.497415          431\n",
+       "  407            2.496535          432\n",
+       "  408            2.493799          433\n",
+       "  409            2.492454          434\n",
+       "  410            2.492071          435\n",
+       "  411            2.493537          436\n",
+       "  412            2.491386          437\n",
+       "  413            2.489813          438\n",
+       "  414            2.487561          439\n",
+       "  415            2.486627          440\n",
+       "  416            2.487043          441\n",
+       "  417            2.484684          442\n",
+       "  418            2.482896          443\n",
+       "  419            2.482224          444,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  420            2.481767          445\n",
+       "  421            2.481464          446\n",
+       "  422            2.481236          447\n",
+       "  423            2.480651          448\n",
+       "  424            2.478291          449\n",
+       "  425            2.475724          450\n",
+       "  426            2.475152          451\n",
+       "  427            2.472174          452\n",
+       "  428            2.470480          453\n",
+       "  429            2.470440          454\n",
+       "  430            2.469291          455\n",
+       "  431            2.840997          461\n",
+       "  432            2.796100          462\n",
+       "  433            2.762793          463\n",
+       "  434            2.735078          464\n",
+       "  435            2.711027          465\n",
+       "  436            2.692434          466\n",
+       "  437            2.675024          467\n",
+       "  438            2.659738          468\n",
+       "  439            2.645602          469,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  440            2.633159          470\n",
+       "  441            2.627600          471\n",
+       "  442            2.613027          472\n",
+       "  443            2.614412          473\n",
+       "  444            2.598756          474\n",
+       "  445            2.590286          475\n",
+       "  446            2.582617          476\n",
+       "  447            2.575874          477\n",
+       "  448            2.569630          478\n",
+       "  449            2.563399          479\n",
+       "  450            2.560676          480\n",
+       "  451            2.555991          481\n",
+       "  452            2.551548          482\n",
+       "  453            2.546903          483\n",
+       "  454            2.542406          484\n",
+       "  455            2.539650          485\n",
+       "  456            2.534884          486\n",
+       "  457            2.532094          487\n",
+       "  458            2.530266          488\n",
+       "  459            2.527167          489,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  460            2.523699          490\n",
+       "  461            2.519928          491\n",
+       "  462            2.518065          492\n",
+       "  463            2.515323          493\n",
+       "  464            2.512822          494\n",
+       "  465            2.509650          495\n",
+       "  466            2.508346          496\n",
+       "  467            2.506853          497\n",
+       "  468            2.505670          498\n",
+       "  469            2.501731          499\n",
+       "  470            2.498955          500\n",
+       "  471            2.498081          501\n",
+       "  472            2.497503          502\n",
+       "  473            2.494270          503\n",
+       "  474            2.492287          504\n",
+       "  475            2.491016          505\n",
+       "  476            2.489336          506\n",
+       "  477            2.488045          507\n",
+       "  478            2.485786          508\n",
+       "  479            2.485134          509,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  480            2.484731          510\n",
+       "  481            2.482701          511\n",
+       "  482            2.482351          512\n",
+       "  483            2.479105          513\n",
+       "  484            2.476860          514\n",
+       "  485            2.475582          515\n",
+       "  486            2.475320          516\n",
+       "  487            2.472880          517\n",
+       "  488            2.471482          518\n",
+       "  489            2.472040          519\n",
+       "  490            2.470716          520\n",
+       "  491            2.470252          521\n",
+       "  492            2.469102          522\n",
+       "  493            2.467126          523\n",
+       "  494            2.465224          524\n",
+       "  495            2.464014          525\n",
+       "  496            2.461930          526\n",
+       "  497            2.460586          527\n",
+       "  498            2.460223          528\n",
+       "  499            2.461318          529,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  500            2.460364          530\n",
+       "  501            2.459039          531\n",
+       "  502            2.458535          532\n",
+       "  503            2.458804          533\n",
+       "  504            2.456485          534\n",
+       "  505            2.455510          535\n",
+       "  506            2.455618          536\n",
+       "  507            2.453306          537\n",
+       "  508            2.451477          538\n",
+       "  509            2.451134          539\n",
+       "  510            2.450314          540\n",
+       "  511            2.449481          541\n",
+       "  512            2.449803          542\n",
+       "  513            2.447854          543\n",
+       "  514            2.448715          544\n",
+       "  515            2.449044          545\n",
+       "  516            2.447686          546\n",
+       "  517            2.446449          547\n",
+       "  518            2.446785          548\n",
+       "  519            2.446550          549,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  520            2.445663          550\n",
+       "  521            2.444318          551\n",
+       "  522            2.443243          552\n",
+       "  523            2.440621          553\n",
+       "  524            2.439485          554\n",
+       "  525            2.439418          555\n",
+       "  526            2.438833          556\n",
+       "  527            2.438995          557\n",
+       "  528            2.436877          558\n",
+       "  529            2.437482          559\n",
+       "  530            2.436763          560\n",
+       "  531            2.766645          566\n",
+       "  532            2.722595          567\n",
+       "  533            2.692199          568\n",
+       "  534            2.667489          569\n",
+       "  535            2.645831          570\n",
+       "  536            2.628924          571\n",
+       "  537            2.614156          572\n",
+       "  538            2.597526          573\n",
+       "  539            2.583766          574,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  540            2.572372          575\n",
+       "  541            2.563842          576\n",
+       "  542            2.555124          577\n",
+       "  543            2.545175          578\n",
+       "  544            2.538298          579\n",
+       "  545            2.534709          580\n",
+       "  546            2.525486          581\n",
+       "  547            2.522065          582\n",
+       "  548            2.516983          583\n",
+       "  549            2.511465          584\n",
+       "  550            2.507693          585\n",
+       "  551            2.502685          586\n",
+       "  552            2.499936          587\n",
+       "  553            2.495063          588\n",
+       "  554            2.491796          589\n",
+       "  555            2.487776          590\n",
+       "  556            2.485383          591\n",
+       "  557            2.483326          592\n",
+       "  558            2.481236          593\n",
+       "  559            2.476348          594,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  560            2.475630          595\n",
+       "  561            2.472860          596\n",
+       "  562            2.469613          597\n",
+       "  563            2.467623          598\n",
+       "  564            2.465096          599\n",
+       "  565            2.464182          600\n",
+       "  566            2.461870          601\n",
+       "  567            2.461177          602\n",
+       "  568            2.460343          603\n",
+       "  569            2.457675          604\n",
+       "  570            2.455289          605\n",
+       "  571            2.453400          606\n",
+       "  572            2.452237          607\n",
+       "  573            2.451370          608\n",
+       "  574            2.450402          609\n",
+       "  575            2.449978          610\n",
+       "  576            2.449394          611\n",
+       "  577            2.447296          612\n",
+       "  578            2.447229          613\n",
+       "  579            2.443948          614,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  580            2.441979          615\n",
+       "  581            2.440534          616\n",
+       "  582            2.438410          617\n",
+       "  583            2.439593          618\n",
+       "  584            2.438961          619\n",
+       "  585            2.438484          620\n",
+       "  586            2.434679          621\n",
+       "  587            2.433926          622\n",
+       "  588            2.434269          623\n",
+       "  589            2.432011          624\n",
+       "  590            2.430222          625\n",
+       "  591            2.429631          626\n",
+       "  592            2.428367          627\n",
+       "  593            2.428448          628\n",
+       "  594            2.427722          629\n",
+       "  595            2.425954          630\n",
+       "  596            2.424502          631\n",
+       "  597            2.424878          632\n",
+       "  598            2.422210          633\n",
+       "  599            2.421746          634,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  600            2.422714          635\n",
+       "  601            2.422331          636\n",
+       "  602            2.421753          637\n",
+       "  603            2.421537          638\n",
+       "  604            2.420341          639\n",
+       "  605            2.418781          640\n",
+       "  606            2.419023          641\n",
+       "  607            2.417726          642\n",
+       "  608            2.415683          643\n",
+       "  609            2.415992          644\n",
+       "  610            2.415595          645\n",
+       "  611            2.415730          646\n",
+       "  612            2.415441          647\n",
+       "  613            2.413270          648\n",
+       "  614            2.412718          649\n",
+       "  615            2.413330          650\n",
+       "  616            2.413142          651\n",
+       "  617            2.411885          652\n",
+       "  618            2.411663          653\n",
+       "  619            2.411461          654,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  620            2.410957          655\n",
+       "  621            2.410554          656\n",
+       "  622            2.409102          657\n",
+       "  623            2.408645          658\n",
+       "  624            2.407999          659\n",
+       "  625            2.406917          660\n",
+       "  626            2.405788          661\n",
+       "  627            2.402131          662\n",
+       "  628            2.400888          663\n",
+       "  629            2.399745          664\n",
+       "  630            2.398911          665\n",
+       "  631            2.694525          671\n",
+       "  632            2.651537          672\n",
+       "  633            2.628192          673\n",
+       "  634            2.607508          674\n",
+       "  635            2.588875          675\n",
+       "  636            2.570228          676\n",
+       "  637            2.555043          677\n",
+       "  638            2.541942          678\n",
+       "  639            2.529123          679,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  640            2.520089          680\n",
+       "  641            2.509334          681\n",
+       "  642            2.501993          682\n",
+       "  643            2.493886          683\n",
+       "  644            2.485974          684\n",
+       "  645            2.481229          685\n",
+       "  646            2.475206          686\n",
+       "  647            2.469170          687\n",
+       "  648            2.464242          688\n",
+       "  649            2.464195          689\n",
+       "  650            2.462246          690\n",
+       "  651            2.453595          691\n",
+       "  652            2.452620          692\n",
+       "  653            2.449588          693\n",
+       "  654            2.446853          694\n",
+       "  655            2.443747          695\n",
+       "  656            2.440252          696\n",
+       "  657            2.437039          697\n",
+       "  658            2.433489          698\n",
+       "  659            2.432468          699,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  660            2.430646          700\n",
+       "  661            2.428838          701\n",
+       "  662            2.427749          702\n",
+       "  663            2.426061          703\n",
+       "  664            2.425288          704\n",
+       "  665            2.421773          705\n",
+       "  666            2.419702          706\n",
+       "  667            2.418459          707\n",
+       "  668            2.416960          708\n",
+       "  669            2.415474          709\n",
+       "  670            2.414789          710\n",
+       "  671            2.413411          711\n",
+       "  672            2.413901          712\n",
+       "  673            2.412295          713\n",
+       "  674            2.412154          714\n",
+       "  675            2.411044          715\n",
+       "  676            2.409955          716\n",
+       "  677            2.408483          717\n",
+       "  678            2.408456          718\n",
+       "  679            2.406870          719,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  680            2.406467          720\n",
+       "  681            2.406063          721\n",
+       "  682            2.404739          722\n",
+       "  683            2.403005          723\n",
+       "  684            2.401076          724\n",
+       "  685            2.398945          725\n",
+       "  686            2.397963          726\n",
+       "  687            2.397419          727\n",
+       "  688            2.397419          728\n",
+       "  689            2.397345          729\n",
+       "  690            2.396848          730\n",
+       "  691            2.395691          731\n",
+       "  692            2.394421          732\n",
+       "  693            2.392888          733\n",
+       "  694            2.391752          734\n",
+       "  695            2.389467          735\n",
+       "  696            2.389769          736\n",
+       "  697            2.387773          737\n",
+       "  698            2.386012          738\n",
+       "  699            2.386529          739,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  700            2.384956          740\n",
+       "  701            2.383491          741\n",
+       "  702            2.383404          742\n",
+       "  703            2.379680          743\n",
+       "  704            2.378039          744\n",
+       "  705            2.375963          745\n",
+       "  706            2.372870          746\n",
+       "  707            2.372521          747\n",
+       "  708            2.371116          748\n",
+       "  709            2.368588          749\n",
+       "  710            2.367009          750\n",
+       "  711            2.367587          751\n",
+       "  712            2.365543          752\n",
+       "  713            2.363419          753\n",
+       "  714            2.362337          754\n",
+       "  715            2.359440          755\n",
+       "  716            2.357732          756\n",
+       "  717            2.355817          757\n",
+       "  718            2.352765          758\n",
+       "  719            2.350970          759,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  720            2.350096          760\n",
+       "  721            2.346527          761\n",
+       "  722            2.342621          762\n",
+       "  723            2.339717          763\n",
+       "  724            2.335072          764\n",
+       "  725            2.332874          765\n",
+       "  726            2.330932          766\n",
+       "  727            2.328539          767\n",
+       "  728            2.326986          768\n",
+       "  729            2.323114          769\n",
+       "  730            2.321043          770\n",
+       "  731            2.545740          776\n",
+       "  732            2.486385          777\n",
+       "  733            2.465533          778\n",
+       "  734            2.448735          779\n",
+       "  735            2.432528          780\n",
+       "  736            2.418560          781\n",
+       "  737            2.404981          782\n",
+       "  738            2.392640          783\n",
+       "  739            2.382315          784,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  740            2.371929          785\n",
+       "  741            2.360778          786\n",
+       "  742            2.353491          787\n",
+       "  743            2.346534          788\n",
+       "  744            2.338420          789\n",
+       "  745            2.330434          790\n",
+       "  746            2.324452          791\n",
+       "  747            2.316533          792\n",
+       "  748            2.311922          793\n",
+       "  749            2.306107          794\n",
+       "  750            2.299735          795\n",
+       "  751            2.294061          796\n",
+       "  752            2.293107          797\n",
+       "  753            2.289807          798\n",
+       "  754            2.281478          799\n",
+       "  755            2.275785          800\n",
+       "  756            2.271435          801\n",
+       "  757            2.264935          802\n",
+       "  758            2.259853          803\n",
+       "  759            2.256506          804,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  760            2.253333          805\n",
+       "  761            2.247626          806\n",
+       "  762            2.241953          807\n",
+       "  763            2.238524          808\n",
+       "  764            2.231675          809\n",
+       "  765            2.225632          810\n",
+       "  766            2.221538          811\n",
+       "  767            2.218022          812\n",
+       "  768            2.214614          813\n",
+       "  769            2.209432          814\n",
+       "  770            2.204552          815\n",
+       "  771            2.198004          816\n",
+       "  772            2.192654          817\n",
+       "  773            2.189696          818\n",
+       "  774            2.183196          819\n",
+       "  775            2.179089          820\n",
+       "  776            2.173966          821\n",
+       "  777            2.168945          822\n",
+       "  778            2.165181          823\n",
+       "  779            2.159964          824,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  780            2.156523          825\n",
+       "  781            2.150540          826\n",
+       "  782            2.149243          827\n",
+       "  783            2.143173          828\n",
+       "  784            2.138178          829\n",
+       "  785            2.132572          830\n",
+       "  786            2.126112          831\n",
+       "  787            2.122281          832\n",
+       "  788            2.117192          833\n",
+       "  789            2.113636          834\n",
+       "  790            2.109879          835\n",
+       "  791            2.102364          836\n",
+       "  792            2.095030          837\n",
+       "  793            2.091111          838\n",
+       "  794            2.082487          839\n",
+       "  795            2.078662          840\n",
+       "  796            2.071268          841\n",
+       "  797            2.065494          842\n",
+       "  798            2.056984          843\n",
+       "  799            2.051566          844,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  800            2.046006          845\n",
+       "  801            2.039789          846\n",
+       "  802            2.030815          847\n",
+       "  803            2.023857          848\n",
+       "  804            2.015683          849\n",
+       "  805            2.006118          850\n",
+       "  806            1.996250          851\n",
+       "  807            1.989595          852\n",
+       "  808            1.979324          853\n",
+       "  809            1.970068          854\n",
+       "  810            1.961565          855\n",
+       "  811            1.949781          856\n",
+       "  812            1.941439          857\n",
+       "  813            1.928358          858\n",
+       "  814            1.918289          859\n",
+       "  815            1.902922          860\n",
+       "  816            1.891871          861\n",
+       "  817            1.879254          862\n",
+       "  818            1.864210          863\n",
+       "  819            1.848064          864,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  820            1.833054          865\n",
+       "  821            1.820571          866\n",
+       "  822            1.803813          867\n",
+       "  823            1.784595          868\n",
+       "  824            1.767763          869\n",
+       "  825            1.751092          870\n",
+       "  826            1.729185          871\n",
+       "  827            1.711137          872\n",
+       "  828            1.692073          873\n",
+       "  829            1.669487          874\n",
+       "  830            1.648750          875\n",
+       "  831            1.755415          881\n",
+       "  832            1.580387          882\n",
+       "  833            1.540647          883\n",
+       "  834            1.504422          884\n",
+       "  835            1.473467          885\n",
+       "  836            1.441726          886\n",
+       "  837            1.414750          887\n",
+       "  838            1.388353          888\n",
+       "  839            1.363173          889,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  840            1.337642          890\n",
+       "  841            1.316542          891\n",
+       "  842            1.295099          892\n",
+       "  843            1.271928          893\n",
+       "  844            1.253765          894\n",
+       "  845            1.234567          895\n",
+       "  846            1.215585          896\n",
+       "  847            1.194760          897\n",
+       "  848            1.179730          898\n",
+       "  849            1.163563          899\n",
+       "  850            1.147282          900\n",
+       "  851            1.134322          901\n",
+       "  852            1.118989          902\n",
+       "  853            1.103509          903\n",
+       "  854            1.090239          904\n",
+       "  855            1.076621          905\n",
+       "  856            1.066773          906\n",
+       "  857            1.054895          907\n",
+       "  858            1.044617          908\n",
+       "  859            1.035287          909,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  860            1.024928          910\n",
+       "  861            1.015397          911\n",
+       "  862            1.007176          912\n",
+       "  863            0.994330          913\n",
+       "  864            0.987984          914\n",
+       "  865            0.979414          915\n",
+       "  866            0.969156          916\n",
+       "  867            0.961096          917\n",
+       "  868            0.952761          918\n",
+       "  869            0.944298          919\n",
+       "  870            0.934410          920\n",
+       "  871            0.929516          921\n",
+       "  872            0.919588          922\n",
+       "  873            0.913982          923\n",
+       "  874            0.906426          924\n",
+       "  875            0.903852          925\n",
+       "  876            0.893063          926\n",
+       "  877            0.886045          927\n",
+       "  878            0.885440          928\n",
+       "  879            0.875371          929,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  880            0.868629          930\n",
+       "  881            0.860912          931\n",
+       "  882            0.856529          932\n",
+       "  883            0.852059          933\n",
+       "  884            0.843434          934\n",
+       "  885            0.838776          935\n",
+       "  886            0.833446          936\n",
+       "  887            0.828323          937\n",
+       "  888            0.821783          938\n",
+       "  889            0.818039          939\n",
+       "  890            0.813018          940\n",
+       "  891            0.807035          941\n",
+       "  892            0.805018          942\n",
+       "  893            0.799211          943\n",
+       "  894            0.794122          944\n",
+       "  895            0.790210          945\n",
+       "  896            0.785444          946\n",
+       "  897            0.781928          947\n",
+       "  898            0.776994          948\n",
+       "  899            0.774957          949,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  900            0.769056          950\n",
+       "  901            0.766871          951\n",
+       "  902            0.762226          952\n",
+       "  903            0.758509          953\n",
+       "  904            0.754812          954\n",
+       "  905            0.750160          955\n",
+       "  906            0.748090          956\n",
+       "  907            0.743405          957\n",
+       "  908            0.741529          958\n",
+       "  909            0.737671          959\n",
+       "  910            0.734047          960\n",
+       "  911            0.731715          961\n",
+       "  912            0.726768          962\n",
+       "  913            0.724744          963\n",
+       "  914            0.721430          964\n",
+       "  915            0.720207          965\n",
+       "  916            0.715327          966\n",
+       "  917            0.713236          967\n",
+       "  918            0.709942          968\n",
+       "  919            0.706884          969,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  920            0.704000          970\n",
+       "  921            0.700458          971\n",
+       "  922            0.698401          972\n",
+       "  923            0.693978          973\n",
+       "  924            0.692633          974\n",
+       "  925            0.689138          975\n",
+       "  926            0.686530          976\n",
+       "  927            0.683209          977\n",
+       "  928            0.680648          978\n",
+       "  929            0.679310          979\n",
+       "  930            0.675862          980\n",
+       "  931            0.898387          986\n",
+       "  932            0.658613          987\n",
+       "  933            0.644006          988\n",
+       "  934            0.634347          989\n",
+       "  935            0.630004          990\n",
+       "  936            0.625185          991\n",
+       "  937            0.622005          992\n",
+       "  938            0.619222          993\n",
+       "  939            0.614013          994,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  940            0.613025          995\n",
+       "  941            0.609388          996\n",
+       "  942            0.605671          997\n",
+       "  943            0.603836          998\n",
+       "  944            0.601436          999\n",
+       "  945            0.599816         1000\n",
+       "  946            0.596798         1001\n",
+       "  947            0.594008         1002\n",
+       "  948            0.593269         1003\n",
+       "  949            0.589814         1004\n",
+       "  950            0.586997         1005\n",
+       "  951            0.586110         1006\n",
+       "  952            0.583649         1007\n",
+       "  953            0.581210         1008\n",
+       "  954            0.580121         1009\n",
+       "  955            0.578272         1010\n",
+       "  956            0.576242         1011\n",
+       "  957            0.574723         1012\n",
+       "  958            0.573506         1013\n",
+       "  959            0.571866         1014,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  960            0.569843         1015\n",
+       "  961            0.568626         1016\n",
+       "  962            0.566300         1017\n",
+       "  963            0.564956         1018\n",
+       "  964            0.563692         1019\n",
+       "  965            0.561944         1020\n",
+       "  966            0.560956         1021\n",
+       "  967            0.559329         1022\n",
+       "  968            0.556708         1023\n",
+       "  969            0.556795         1024\n",
+       "  970            0.554684         1025\n",
+       "  971            0.552271         1026\n",
+       "  972            0.552164         1027\n",
+       "  973            0.550510         1028\n",
+       "  974            0.548588         1029\n",
+       "  975            0.547250         1030\n",
+       "  976            0.546678         1031\n",
+       "  977            0.545361         1032\n",
+       "  978            0.543990         1033\n",
+       "  979            0.543802         1034,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  980            0.541933         1035\n",
+       "  981            0.540703         1036\n",
+       "  982            0.539378         1037\n",
+       "  983            0.538968         1038\n",
+       "  984            0.537671         1039\n",
+       "  985            0.535668         1040\n",
+       "  986            0.534801         1041\n",
+       "  987            0.534035         1042\n",
+       "  988            0.534028         1043\n",
+       "  989            0.531520         1044\n",
+       "  990            0.531030         1045\n",
+       "  991            0.528879         1046\n",
+       "  992            0.529316         1047\n",
+       "  993            0.526419         1048\n",
+       "  994            0.525934         1049\n",
+       "  995            0.524805         1050\n",
+       "  996            0.524429         1051\n",
+       "  997            0.522049         1052\n",
+       "  998            0.522338         1053\n",
+       "  999            0.521276         1054,\n",
+       "        discharge_capacity  cycle_index\n",
+       "  1000            0.520651         1055\n",
+       "  1001            0.519528         1056\n",
+       "  1002            0.518513         1057\n",
+       "  1003            0.518796         1058\n",
+       "  1004            0.517243         1059\n",
+       "  1005            0.516920         1060\n",
+       "  1006            0.515872         1061\n",
+       "  1007            0.515199         1062\n",
+       "  1008            0.513983         1063\n",
+       "  1009            0.513788         1064\n",
+       "  1010            0.512255         1065\n",
+       "  1011            0.511529         1066\n",
+       "  1012            0.511590         1067\n",
+       "  1013            0.510124         1068\n",
+       "  1014            0.509802         1069\n",
+       "  1015            0.508935         1070\n",
+       "  1016            0.507671         1071\n",
+       "  1017            0.507039         1072\n",
+       "  1018            0.505372         1073\n",
+       "  1019            0.504767         1074],\n",
+       " [    discharge_capacity  cycle_index\n",
+       "  20            4.431603           25\n",
+       "  21            4.426252           26\n",
+       "  22            4.421506           27\n",
+       "  23            4.416095           28\n",
+       "  24            4.410792           29\n",
+       "  25            4.404829           30\n",
+       "  26            4.398080           31\n",
+       "  27            4.392871           32\n",
+       "  28            4.386680           33\n",
+       "  29            4.380966           34\n",
+       "  30            4.374526           35\n",
+       "  31            4.391991           41\n",
+       "  32            4.384300           42\n",
+       "  33            4.378069           43\n",
+       "  34            4.370056           44\n",
+       "  35            4.363489           45\n",
+       "  36            4.355517           46\n",
+       "  37            4.350039           47\n",
+       "  38            4.342839           48\n",
+       "  39            4.336951           49,\n",
+       "      discharge_capacity  cycle_index\n",
+       "  40            4.329207           50\n",
+       "  41            4.322256           51\n",
+       "  42            4.316818           52\n",
+       "  43            4.309027           53\n",
+       "  44            4.304147           54\n",
+       "  45            4.295462           55\n",
+       "  46            4.288720           56\n",
+       "  47            4.282066           57\n",
+       "  48            4.274315           58\n",
+       "  49            4.267788           59\n",
+       "  50            4.259594           60\n",
+       "  51            4.253107           61\n",
+       "  52            4.247084           62\n",
+       "  53            4.239663           63\n",
+       "  54            4.230373           64\n",
+       "  55            4.223046           65\n",
+       "  56            4.216123           66\n",
+       "  57            4.208251           67\n",
+       "  58            4.202800           68\n",
+       "  59            4.193947           69,\n",
+       "      discharge_capacity  cycle_index\n",
+       "  60            4.184395           70\n",
+       "  61            4.177969           71\n",
+       "  62            4.169815           72\n",
+       "  63            4.161748           73\n",
+       "  64            4.154260           74\n",
+       "  65            4.143801           75\n",
+       "  66            4.137636           76\n",
+       "  67            4.129477           77\n",
+       "  68            4.121255           78\n",
+       "  69            4.112134           79\n",
+       "  70            4.104988           80\n",
+       "  71            4.096679           81\n",
+       "  72            4.086805           82\n",
+       "  73            4.077737           83\n",
+       "  74            4.069449           84\n",
+       "  75            4.062485           85\n",
+       "  76            4.055501           86\n",
+       "  77            4.044913           87\n",
+       "  78            4.036403           88\n",
+       "  79            4.026751           89,\n",
+       "      discharge_capacity  cycle_index\n",
+       "  80            4.018993           90\n",
+       "  81            4.009260           91\n",
+       "  82            4.001839           92\n",
+       "  83            3.991642           93\n",
+       "  84            3.981538           94\n",
+       "  85            3.974137           95\n",
+       "  86            3.964929           96\n",
+       "  87            3.955323           97\n",
+       "  88            3.945757           98\n",
+       "  89            3.936064           99\n",
+       "  90            3.928193          100\n",
+       "  91            3.919931          101\n",
+       "  92            3.909835          102\n",
+       "  93            3.900807          103\n",
+       "  94            3.889393          104\n",
+       "  95            3.879586          105\n",
+       "  96            3.870780          106\n",
+       "  97            3.860590          107\n",
+       "  98            3.851448          108\n",
+       "  99            3.841889          109,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  100            3.831389          110\n",
+       "  101            3.823726          111\n",
+       "  102            3.814840          112\n",
+       "  103            3.802895          113\n",
+       "  104            3.793585          114\n",
+       "  105            3.783992          115\n",
+       "  106            3.773997          116\n",
+       "  107            3.766898          117\n",
+       "  108            3.758422          118\n",
+       "  109            3.746134          119\n",
+       "  110            3.735413          120\n",
+       "  111            3.724301          121\n",
+       "  112            3.714850          122\n",
+       "  113            3.705896          123\n",
+       "  114            3.698287          124\n",
+       "  115            3.688493          125\n",
+       "  116            3.677550          126\n",
+       "  117            3.666969          127\n",
+       "  118            3.657531          128\n",
+       "  119            3.648040          129,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  120            3.639442          130\n",
+       "  121            3.630926          131\n",
+       "  122            3.621018          132\n",
+       "  123            3.609900          133\n",
+       "  124            3.599292          134\n",
+       "  125            3.589236          135\n",
+       "  126            3.580020          136\n",
+       "  127            3.572162          137\n",
+       "  128            3.562415          138\n",
+       "  129            3.549980          139\n",
+       "  130            3.540166          140\n",
+       "  131            3.885710          146\n",
+       "  132            3.836141          147\n",
+       "  133            3.807728          148\n",
+       "  134            3.783179          149\n",
+       "  135            3.757931          150\n",
+       "  136            3.737120          151\n",
+       "  137            3.717996          152\n",
+       "  138            3.698576          153\n",
+       "  139            3.680205          154,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  140            3.664677          155\n",
+       "  141            3.646071          156\n",
+       "  142            3.628432          157\n",
+       "  143            3.612837          158\n",
+       "  144            3.595756          159\n",
+       "  145            3.580646          160\n",
+       "  146            3.563390          161\n",
+       "  147            3.548938          162\n",
+       "  148            3.535736          163\n",
+       "  149            3.520517          164\n",
+       "  150            3.503921          165\n",
+       "  151            3.488655          166\n",
+       "  152            3.473947          167\n",
+       "  153            3.460893          168\n",
+       "  154            3.448619          169\n",
+       "  155            3.436029          170\n",
+       "  156            3.420393          171\n",
+       "  157            3.404502          172\n",
+       "  158            3.390272          173\n",
+       "  159            3.377191          174,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  160            3.362389          175\n",
+       "  161            3.349267          176\n",
+       "  162            3.335770          177\n",
+       "  163            3.321815          178\n",
+       "  164            3.306099          179\n",
+       "  165            3.291707          180\n",
+       "  166            3.277873          181\n",
+       "  167            3.262903          182\n",
+       "  168            3.250649          183\n",
+       "  169            3.238704          184\n",
+       "  170            3.225576          185\n",
+       "  171            3.211897          186\n",
+       "  172            3.197781          187\n",
+       "  173            3.184330          188\n",
+       "  174            3.171376          189\n",
+       "  175            3.157462          190\n",
+       "  176            3.146196          191\n",
+       "  177            3.133895          192\n",
+       "  178            3.120074          193\n",
+       "  179            3.106247          194,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  180            3.093825          195\n",
+       "  181            3.083056          196\n",
+       "  182            3.071212          197\n",
+       "  183            3.060880          198\n",
+       "  184            3.051463          199\n",
+       "  185            3.039760          200\n",
+       "  186            3.028937          201\n",
+       "  187            3.015400          202\n",
+       "  188            3.004436          203\n",
+       "  189            2.995119          204\n",
+       "  190            2.984384          205\n",
+       "  191            2.975067          206\n",
+       "  192            2.964574          207\n",
+       "  193            2.954155          208\n",
+       "  194            2.945000          209\n",
+       "  195            2.936187          210\n",
+       "  196            2.925593          211\n",
+       "  197            2.917010          212\n",
+       "  198            2.909077          213\n",
+       "  199            2.900547          214,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  200            2.891506          215\n",
+       "  201            2.882297          216\n",
+       "  202            2.873538          217\n",
+       "  203            2.866353          218\n",
+       "  204            2.855154          219\n",
+       "  205            2.846355          220\n",
+       "  206            2.839464          221\n",
+       "  207            2.832312          222\n",
+       "  208            2.823540          223\n",
+       "  209            2.814661          224\n",
+       "  210            2.808376          225\n",
+       "  211            2.802211          226\n",
+       "  212            2.796477          227\n",
+       "  213            2.787739          228\n",
+       "  214            2.781830          229\n",
+       "  215            2.776842          230\n",
+       "  216            2.770073          231\n",
+       "  217            2.764481          232\n",
+       "  218            2.757638          233\n",
+       "  219            2.753880          234,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  220            2.748281          235\n",
+       "  221            2.740147          236\n",
+       "  222            2.734494          237\n",
+       "  223            2.731973          238\n",
+       "  224            2.725164          239\n",
+       "  225            2.719067          240\n",
+       "  226            2.713568          241\n",
+       "  227            2.708365          242\n",
+       "  228            2.704803          243\n",
+       "  229            2.698437          244\n",
+       "  230            2.692696          245\n",
+       "  231            3.049460          251\n",
+       "  232            3.021543          252\n",
+       "  233            3.001895          253\n",
+       "  234            2.976748          254\n",
+       "  235            2.953678          255\n",
+       "  236            2.933135          256\n",
+       "  237            2.919134          257\n",
+       "  238            2.899411          258\n",
+       "  239            2.883225          259,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  240            2.869297          260\n",
+       "  241            2.855698          261\n",
+       "  242            2.843719          262\n",
+       "  243            2.831116          263\n",
+       "  244            2.819521          264\n",
+       "  245            2.809370          265\n",
+       "  246            2.800699          266\n",
+       "  247            2.790434          267\n",
+       "  248            2.782375          268\n",
+       "  249            2.773770          269\n",
+       "  250            2.766719          270\n",
+       "  251            2.759849          271\n",
+       "  252            2.752825          272\n",
+       "  253            2.747205          273\n",
+       "  254            2.741075          274\n",
+       "  255            2.734286          275\n",
+       "  256            2.728195          276\n",
+       "  257            2.721937          277\n",
+       "  258            2.716291          278\n",
+       "  259            2.712573          279,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  260            2.707115          280\n",
+       "  261            2.701133          281\n",
+       "  262            2.695614          282\n",
+       "  263            2.692898          283\n",
+       "  264            2.688220          284\n",
+       "  265            2.683292          285\n",
+       "  266            2.678896          286\n",
+       "  267            2.674607          287\n",
+       "  268            2.672705          288\n",
+       "  269            2.668847          289\n",
+       "  270            2.665587          290\n",
+       "  271            2.661231          291\n",
+       "  272            2.655672          292\n",
+       "  273            2.655329          293\n",
+       "  274            2.652788          294\n",
+       "  275            2.648345          295\n",
+       "  276            2.644372          296\n",
+       "  277            2.641414          297\n",
+       "  278            2.639694          298\n",
+       "  279            2.636669          299,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  280            2.632481          300\n",
+       "  281            2.629577          301\n",
+       "  282            2.628959          302\n",
+       "  283            2.627305          303\n",
+       "  284            2.624213          304\n",
+       "  285            2.622432          305\n",
+       "  286            2.620395          306\n",
+       "  287            2.617786          307\n",
+       "  288            2.617034          308\n",
+       "  289            2.614372          309\n",
+       "  290            2.611911          310\n",
+       "  291            2.610762          311\n",
+       "  292            2.609243          312\n",
+       "  293            2.607892          313\n",
+       "  294            2.606762          314\n",
+       "  295            2.604947          315\n",
+       "  296            2.602521          316\n",
+       "  297            2.600229          317\n",
+       "  298            2.599812          318\n",
+       "  299            2.599355          319,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  300            2.596821          320\n",
+       "  301            2.595940          321\n",
+       "  302            2.595859          322\n",
+       "  303            2.593708          323\n",
+       "  304            2.591221          324\n",
+       "  305            2.590294          325\n",
+       "  306            2.589292          326\n",
+       "  307            2.590388          327\n",
+       "  308            2.588102          328\n",
+       "  309            2.586866          329\n",
+       "  310            2.586677          330\n",
+       "  311            2.586926          331\n",
+       "  312            2.584082          332\n",
+       "  313            2.582731          333\n",
+       "  314            2.581400          334\n",
+       "  315            2.581064          335\n",
+       "  316            2.580042          336\n",
+       "  317            2.578839          337\n",
+       "  318            2.577165          338\n",
+       "  319            2.577556          339,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  320            2.577891          340\n",
+       "  321            2.576722          341\n",
+       "  322            2.575713          342\n",
+       "  323            2.573757          343\n",
+       "  324            2.574040          344\n",
+       "  325            2.572816          345\n",
+       "  326            2.572084          346\n",
+       "  327            2.571425          347\n",
+       "  328            2.571277          348\n",
+       "  329            2.572305          349\n",
+       "  330            2.572507          350\n",
+       "  331            2.863583          356\n",
+       "  332            2.846106          357\n",
+       "  333            2.837737          358\n",
+       "  334            2.815911          359\n",
+       "  335            2.808738          360\n",
+       "  336            2.794662          361\n",
+       "  337            2.781151          362\n",
+       "  338            2.774053          363\n",
+       "  339            2.764904          364,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  340            2.757268          365\n",
+       "  341            2.749995          366\n",
+       "  342            2.744079          367\n",
+       "  343            2.736733          368\n",
+       "  344            2.731879          369\n",
+       "  345            2.725023          370\n",
+       "  346            2.720599          371\n",
+       "  347            2.716970          372\n",
+       "  348            2.712540          373\n",
+       "  349            2.711518          374\n",
+       "  350            2.707317          375\n",
+       "  351            2.705119          376\n",
+       "  352            2.703465          377\n",
+       "  353            2.700931          378\n",
+       "  354            2.697993          379\n",
+       "  355            2.696703          380\n",
+       "  356            2.694088          381\n",
+       "  357            2.693362          382\n",
+       "  358            2.691937          383\n",
+       "  359            2.689463          384,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  360            2.689658          385\n",
+       "  361            2.690915          386\n",
+       "  362            2.688623          387\n",
+       "  363            2.686351          388\n",
+       "  364            2.685961          389\n",
+       "  365            2.686438          390\n",
+       "  366            2.687857          391\n",
+       "  367            2.686123          392\n",
+       "  368            2.685322          393\n",
+       "  369            2.686041          394\n",
+       "  370            2.687769          395\n",
+       "  371            2.687252          396\n",
+       "  372            2.688394          397\n",
+       "  373            2.688072          398\n",
+       "  374            2.687958          399\n",
+       "  375            2.688690          400\n",
+       "  376            2.687252          401\n",
+       "  377            2.687998          402\n",
+       "  378            2.689651          403\n",
+       "  379            2.690277          404,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  380            2.690740          405\n",
+       "  381            2.690156          406\n",
+       "  382            2.689860          407\n",
+       "  383            2.690619          408\n",
+       "  384            2.690230          409\n",
+       "  385            2.691621          410\n",
+       "  386            2.691964          411\n",
+       "  387            2.692320          412\n",
+       "  388            2.690216          413\n",
+       "  389            2.691325          414\n",
+       "  390            2.692394          415\n",
+       "  391            2.692609          416\n",
+       "  392            2.693564          417\n",
+       "  393            2.691923          418\n",
+       "  394            2.692105          419\n",
+       "  395            2.693698          420\n",
+       "  396            2.693174          421\n",
+       "  397            2.692253          422\n",
+       "  398            2.691836          423\n",
+       "  399            2.691325          424,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  400            2.691554          425\n",
+       "  401            2.692784          426\n",
+       "  402            2.690162          427\n",
+       "  403            2.689429          428\n",
+       "  404            2.689900          429\n",
+       "  405            2.687030          430\n",
+       "  406            2.686600          431\n",
+       "  407            2.685652          432\n",
+       "  408            2.683535          433\n",
+       "  409            2.684402          434\n",
+       "  410            2.680247          435\n",
+       "  411            2.676786          436\n",
+       "  412            2.673734          437\n",
+       "  413            2.671690          438\n",
+       "  414            2.668222          439\n",
+       "  415            2.662642          440\n",
+       "  416            2.656747          441\n",
+       "  417            2.653265          442\n",
+       "  418            2.649629          443\n",
+       "  419            2.641710          444,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  420            2.634686          445\n",
+       "  421            2.626431          446\n",
+       "  422            2.618620          447\n",
+       "  423            2.610184          448\n",
+       "  424            2.600464          449\n",
+       "  425            2.590872          450\n",
+       "  426            2.581757          451\n",
+       "  427            2.570269          452\n",
+       "  428            2.556522          453\n",
+       "  429            2.543448          454\n",
+       "  430            2.528855          455\n",
+       "  431            2.686391          461\n",
+       "  432            2.603791          462\n",
+       "  433            2.577058          463\n",
+       "  434            2.548516          464\n",
+       "  435            2.528418          465\n",
+       "  436            2.484994          466\n",
+       "  437            2.449770          467\n",
+       "  438            2.410749          468\n",
+       "  439            2.370168          469,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  440            2.330226          470\n",
+       "  441            2.287111          471\n",
+       "  442            2.250725          472\n",
+       "  443            2.207093          473\n",
+       "  444            2.163709          474\n",
+       "  445            2.119841          475\n",
+       "  446            2.078017          476\n",
+       "  447            2.031595          477\n",
+       "  448            1.983956          478\n",
+       "  449            1.936075          479\n",
+       "  450            1.886964          480\n",
+       "  451            1.837934          481\n",
+       "  452            1.790315          482\n",
+       "  453            1.743396          483\n",
+       "  454            1.695166          484\n",
+       "  455            1.650700          485\n",
+       "  456            1.609272          486\n",
+       "  457            1.565505          487\n",
+       "  458            1.524104          488\n",
+       "  459            1.483685          489,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  460            1.443696          490\n",
+       "  461            1.409602          491\n",
+       "  462            1.369828          492\n",
+       "  463            1.333919          493\n",
+       "  464            1.300585          494\n",
+       "  465            1.269596          495\n",
+       "  466            1.239441          496\n",
+       "  467            1.212069          497\n",
+       "  468            1.185826          498\n",
+       "  469            1.165224          499\n",
+       "  470            1.144412          500\n",
+       "  471            1.125040          501\n",
+       "  472            1.106561          502\n",
+       "  473            1.088620          503\n",
+       "  474            1.070551          504\n",
+       "  475            1.054398          505\n",
+       "  476            1.037660          506\n",
+       "  477            1.023746          507\n",
+       "  478            1.008359          508\n",
+       "  479            0.996139          509,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  480            0.981592          510\n",
+       "  481            0.970380          511\n",
+       "  482            0.959705          512\n",
+       "  483            0.948641          513\n",
+       "  484            0.939055          514\n",
+       "  485            0.927453          515\n",
+       "  486            0.917955          516\n",
+       "  487            0.909297          517\n",
+       "  488            0.900969          518\n",
+       "  489            0.892136          519\n",
+       "  490            0.885454          520\n",
+       "  491            0.876689          521\n",
+       "  492            0.867984          522\n",
+       "  493            0.861161          523\n",
+       "  494            0.853760          524\n",
+       "  495            0.845774          525\n",
+       "  496            0.837540          526\n",
+       "  497            0.829036          527\n",
+       "  498            0.821884          528\n",
+       "  499            0.814819          529,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  500            0.808662          530\n",
+       "  501            0.801638          531\n",
+       "  502            0.794734          532\n",
+       "  503            0.789276          533\n",
+       "  504            0.782144          534\n",
+       "  505            0.775852          535\n",
+       "  506            0.768908          536\n",
+       "  507            0.762025          537\n",
+       "  508            0.755310          538\n",
+       "  509            0.748554          539\n",
+       "  510            0.743492          540\n",
+       "  511            0.737564          541\n",
+       "  512            0.731762          542\n",
+       "  513            0.726687          543\n",
+       "  514            0.720503          544\n",
+       "  515            0.715542          545\n",
+       "  516            0.709519          546\n",
+       "  517            0.702777          547\n",
+       "  518            0.699040          548\n",
+       "  519            0.693279          549,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  520            0.688963          550\n",
+       "  521            0.683115          551\n",
+       "  522            0.677247          552\n",
+       "  523            0.672394          553\n",
+       "  524            0.668629          554\n",
+       "  525            0.662687          555\n",
+       "  526            0.659756          556\n",
+       "  527            0.654607          557\n",
+       "  528            0.651098          558\n",
+       "  529            0.646769          559\n",
+       "  530            0.641190          560\n",
+       "  531            0.802256          566\n",
+       "  532            0.632068          567\n",
+       "  533            0.618853          568\n",
+       "  534            0.613119          569\n",
+       "  535            0.607795          570\n",
+       "  536            0.603567          571\n",
+       "  537            0.599460          572\n",
+       "  538            0.592967          573\n",
+       "  539            0.589263          574,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  540            0.585263          575\n",
+       "  541            0.578810          576\n",
+       "  542            0.574730          577\n",
+       "  543            0.569231          578\n",
+       "  544            0.564902          579\n",
+       "  545            0.562005          580\n",
+       "  546            0.556843          581\n",
+       "  547            0.552984          582\n",
+       "  548            0.550954          583\n",
+       "  549            0.545664          584\n",
+       "  550            0.541073          585\n",
+       "  551            0.538384          586\n",
+       "  552            0.533443          587\n",
+       "  553            0.529861          588\n",
+       "  554            0.526217          589\n",
+       "  555            0.523064          590\n",
+       "  556            0.520194          591\n",
+       "  557            0.516652          592\n",
+       "  558            0.512343          593\n",
+       "  559            0.510636          594,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  560            0.506448          595\n",
+       "  561            0.502119          596\n",
+       "  562            0.499712          597\n",
+       "  563            0.497198          598\n",
+       "  564            0.492224          599\n",
+       "  565            0.490792          600\n",
+       "  566            0.487935          601\n",
+       "  567            0.485354          602\n",
+       "  568            0.484292          603\n",
+       "  569            0.480326          604\n",
+       "  570            0.477920          605\n",
+       "  571            0.475305          606\n",
+       "  572            0.471614          607\n",
+       "  573            0.467837          608\n",
+       "  574            0.466284          609\n",
+       "  575            0.463138          610\n",
+       "  576            0.460227          611\n",
+       "  577            0.459447          612\n",
+       "  578            0.456335          613\n",
+       "  579            0.454070          614,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  580            0.451838          615\n",
+       "  581            0.449365          616\n",
+       "  582            0.446743          617\n",
+       "  583            0.445190          618\n",
+       "  584            0.442535          619\n",
+       "  585            0.440458          620\n",
+       "  586            0.437325          621\n",
+       "  587            0.435336          622\n",
+       "  588            0.433124          623\n",
+       "  589            0.430321          624\n",
+       "  590            0.428795          625\n",
+       "  591            0.426322          626\n",
+       "  592            0.424554          627\n",
+       "  593            0.422430          628\n",
+       "  594            0.419647          629\n",
+       "  595            0.417496          630\n",
+       "  596            0.415976          631\n",
+       "  597            0.413489          632\n",
+       "  598            0.412582          633\n",
+       "  599            0.411258          634,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  600            0.410989          635\n",
+       "  601            0.408804          636\n",
+       "  602            0.405947          637\n",
+       "  603            0.403689          638\n",
+       "  604            0.402828          639\n",
+       "  605            0.399978          640\n",
+       "  606            0.396725          641\n",
+       "  607            0.395716          642\n",
+       "  608            0.393713          643\n",
+       "  609            0.391851          644\n",
+       "  610            0.390406          645\n",
+       "  611            0.388504          646\n",
+       "  612            0.385586          647\n",
+       "  613            0.384914          648\n",
+       "  614            0.382958          649\n",
+       "  615            0.379160          650\n",
+       "  616            0.379247          651\n",
+       "  617            0.376619          652\n",
+       "  618            0.373998          653\n",
+       "  619            0.372667          654,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  620            0.370939          655\n",
+       "  621            0.368022          656\n",
+       "  622            0.368438          657\n",
+       "  623            0.364372          658\n",
+       "  624            0.361468          659\n",
+       "  625            0.360896          660\n",
+       "  626            0.358349          661\n",
+       "  627            0.356594          662\n",
+       "  628            0.354766          663\n",
+       "  629            0.352326          664\n",
+       "  630            0.351385          665\n",
+       "  631            0.418074          671\n",
+       "  632            0.333498          672\n",
+       "  633            0.331178          673\n",
+       "  634            0.326607          674\n",
+       "  635            0.325330          675\n",
+       "  636            0.323455          676\n",
+       "  637            0.319879          677\n",
+       "  638            0.318635          678\n",
+       "  639            0.317909          679,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  640            0.315738          680\n",
+       "  641            0.314058          681\n",
+       "  642            0.313345          682\n",
+       "  643            0.310777          683\n",
+       "  644            0.309211          684\n",
+       "  645            0.305877          685\n",
+       "  646            0.306354          686\n",
+       "  647            0.302637          687\n",
+       "  648            0.300499          688\n",
+       "  649            0.300116          689\n",
+       "  650            0.295337          690\n",
+       "  651            0.293939          691\n",
+       "  652            0.292292          692\n",
+       "  653            0.290436          693\n",
+       "  654            0.289650          694\n",
+       "  655            0.286746          695\n",
+       "  656            0.284635          696\n",
+       "  657            0.283775          697\n",
+       "  658            0.281496          698\n",
+       "  659            0.279869          699,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  660            0.277013          700\n",
+       "  661            0.275527          701\n",
+       "  662            0.273510          702\n",
+       "  663            0.271783          703\n",
+       "  664            0.269914          704\n",
+       "  665            0.267461          705\n",
+       "  666            0.267064          706\n",
+       "  667            0.265404          707\n",
+       "  668            0.263165          708\n",
+       "  669            0.261807          709\n",
+       "  670            0.259925          710\n",
+       "  671            0.257969          711\n",
+       "  672            0.259280          712\n",
+       "  673            0.256195          713\n",
+       "  674            0.253970          714\n",
+       "  675            0.253472          715\n",
+       "  676            0.251704          716\n",
+       "  677            0.251711          717\n",
+       "  678            0.247543          718\n",
+       "  679            0.246959          719,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  680            0.245829          720\n",
+       "  681            0.244424          721\n",
+       "  682            0.242972          722\n",
+       "  683            0.242166          723\n",
+       "  684            0.240815          724\n",
+       "  685            0.239363          725\n",
+       "  686            0.238408          726\n",
+       "  687            0.239006          727\n",
+       "  688            0.236035          728\n",
+       "  689            0.236358          729\n",
+       "  690            0.236250          730\n",
+       "  691            0.233851          731\n",
+       "  692            0.232036          732\n",
+       "  693            0.231995          733\n",
+       "  694            0.232936          734\n",
+       "  695            0.229340          735\n",
+       "  696            0.228399          736\n",
+       "  697            0.227566          737\n",
+       "  698            0.225973          738\n",
+       "  699            0.224655          739,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  700            0.223989          740\n",
+       "  701            0.222793          741\n",
+       "  702            0.220622          742\n",
+       "  703            0.219378          743\n",
+       "  704            0.219647          744\n",
+       "  705            0.217691          745\n",
+       "  706            0.215506          746\n",
+       "  707            0.215567          747\n",
+       "  708            0.213994          748\n",
+       "  709            0.213839          749\n",
+       "  710            0.211460          750\n",
+       "  711            0.211433          751\n",
+       "  712            0.210861          752\n",
+       "  713            0.209853          753\n",
+       "  714            0.209376          754\n",
+       "  715            0.206613          755\n",
+       "  716            0.207386          756\n",
+       "  717            0.205981          757\n",
+       "  718            0.205033          758\n",
+       "  719            0.203897          759,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  720            0.202647          760\n",
+       "  721            0.203239          761\n",
+       "  722            0.200086          762\n",
+       "  723            0.200456          763\n",
+       "  724            0.199737          764\n",
+       "  725            0.198043          765\n",
+       "  726            0.198984          766\n",
+       "  727            0.195965          767\n",
+       "  728            0.195179          768\n",
+       "  729            0.195004          769\n",
+       "  730            0.193283          770\n",
+       "  731            0.204731          776\n",
+       "  732            0.179080          777\n",
+       "  733            0.179813          778\n",
+       "  734            0.180639          779\n",
+       "  735            0.181157          780\n",
+       "  736            0.183516          781\n",
+       "  737            0.180760          782\n",
+       "  738            0.182468          783\n",
+       "  739            0.182804          784,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  740            0.180175          785\n",
+       "  741            0.179221          786\n",
+       "  742            0.178522          787\n",
+       "  743            0.178145          788\n",
+       "  744            0.176418          789\n",
+       "  745            0.174106          790\n",
+       "  746            0.175053          791\n",
+       "  747            0.171229          792\n",
+       "  748            0.172331          793\n",
+       "  749            0.170476          794\n",
+       "  750            0.168614          795\n",
+       "  751            0.170019          796\n",
+       "  752            0.167397          797\n",
+       "  753            0.168351          798\n",
+       "  754            0.165542          799\n",
+       "  755            0.164802          800\n",
+       "  756            0.164950          801\n",
+       "  757            0.162053          802\n",
+       "  758            0.162779          803\n",
+       "  759            0.161045          804,\n",
+       "       discharge_capacity  cycle_index\n",
+       "  760            0.161650          805\n",
+       "  761            0.159942          806\n",
+       "  762            0.158188          807\n",
+       "  763            0.158463          808\n",
+       "  764            0.156561          809\n",
+       "  765            0.155620          810\n",
+       "  766            0.154968          811\n",
+       "  767            0.156245          812\n",
+       "  768            0.154235          813\n",
+       "  769            0.151795          814\n",
+       "  770            0.153079          815\n",
+       "  771            0.150565          816\n",
+       "  772            0.150693          817\n",
+       "  773            0.150095          818\n",
+       "  774            0.850717          819\n",
+       "  775            0.662370          820\n",
+       "  776            0.801814          821\n",
+       "  777            0.454392          822\n",
+       "  778            0.048896          823\n",
+       "  779            0.022749          824]]"
+      ]
+     },
+     "execution_count": 105,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cell_labels"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 101,
+   "id": "669554e3",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>discharge_capacity</th>\n",
+       "      <th>cycle_index</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1040</th>\n",
+       "      <td>2.161563</td>\n",
+       "      <td>1100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1041</th>\n",
+       "      <td>2.159156</td>\n",
+       "      <td>1101</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1042</th>\n",
+       "      <td>2.152206</td>\n",
+       "      <td>1102</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1043</th>\n",
+       "      <td>2.148697</td>\n",
+       "      <td>1103</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1044</th>\n",
+       "      <td>2.144045</td>\n",
+       "      <td>1104</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1045</th>\n",
+       "      <td>2.141665</td>\n",
+       "      <td>1105</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1046</th>\n",
+       "      <td>2.140066</td>\n",
+       "      <td>1106</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1047</th>\n",
+       "      <td>2.135535</td>\n",
+       "      <td>1107</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1048</th>\n",
+       "      <td>2.129929</td>\n",
+       "      <td>1108</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1049</th>\n",
+       "      <td>2.127025</td>\n",
+       "      <td>1109</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1050</th>\n",
+       "      <td>2.126138</td>\n",
+       "      <td>1110</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1051</th>\n",
+       "      <td>2.122897</td>\n",
+       "      <td>1111</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1052</th>\n",
+       "      <td>2.121607</td>\n",
+       "      <td>1112</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1053</th>\n",
+       "      <td>2.130466</td>\n",
+       "      <td>1113</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1054</th>\n",
+       "      <td>2.116390</td>\n",
+       "      <td>1114</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1055</th>\n",
+       "      <td>2.115947</td>\n",
+       "      <td>1115</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1056</th>\n",
+       "      <td>2.112048</td>\n",
+       "      <td>1116</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1057</th>\n",
+       "      <td>2.109897</td>\n",
+       "      <td>1117</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1058</th>\n",
+       "      <td>2.108189</td>\n",
+       "      <td>1118</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1059</th>\n",
+       "      <td>2.107463</td>\n",
+       "      <td>1119</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      discharge_capacity  cycle_index\n",
+       "1040            2.161563         1100\n",
+       "1041            2.159156         1101\n",
+       "1042            2.152206         1102\n",
+       "1043            2.148697         1103\n",
+       "1044            2.144045         1104\n",
+       "1045            2.141665         1105\n",
+       "1046            2.140066         1106\n",
+       "1047            2.135535         1107\n",
+       "1048            2.129929         1108\n",
+       "1049            2.127025         1109\n",
+       "1050            2.126138         1110\n",
+       "1051            2.122897         1111\n",
+       "1052            2.121607         1112\n",
+       "1053            2.130466         1113\n",
+       "1054            2.116390         1114\n",
+       "1055            2.115947         1115\n",
+       "1056            2.112048         1116\n",
+       "1057            2.109897         1117\n",
+       "1058            2.108189         1118\n",
+       "1059            2.107463         1119"
+      ]
+     },
+     "execution_count": 101,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cycle_window_labels[-1]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 82,
+   "id": "2d493075",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1071"
+      ]
+     },
+     "execution_count": 82,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(cycle_window_labels[0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "id": "6ca209f4",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[ 2.701e+00, -6.627e-01,  8.250e+02],\n",
+       "       [ 2.703e+00, -1.504e+00,  8.250e+02],\n",
+       "       [ 2.704e+00, -2.345e+00,  8.250e+02],\n",
+       "       ...,\n",
+       "       [ 4.248e+00,  2.420e+00,  8.250e+02],\n",
+       "       [ 4.249e+00,  2.420e+00,  8.250e+02],\n",
+       "       [ 4.249e+00,  2.420e+00,  8.250e+02]])"
+      ]
+     },
+     "execution_count": 48,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cycle_features[-1]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "e7368aa8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "21"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# data_prep\n",
+    "def prep_ml_data(dat, cycle_numbers=20):\n",
+    "    features = np.empty([0, cycle_numbers,100, 3])\n",
+    "    labels = np.empty([0, cycle_numbers])\n",
+    "    print('Generating features and labels. Skipping cells with cycles lower than 50.')\n",
+    "    for j,d in enumerate(tqdm(dat)):\n",
+    "        if not len(d) < 50:\n",
+    "            n = d.shape[0]//cycle_numbers\n",
+    "            cell_features = []\n",
+    "            cell_labels = []\n",
+    "            for i in range(n-1):\n",
+    "                cell_features.append(d[cycle_numbers*i:cycle_numbers*(i+1), :, :3])\n",
+    "                cell_labels.append(d[cycle_numbers*(i+1):cycle_numbers*(i+2), 0, -1])\n",
+    "#             print(np.array(cell_features).shape, j)\n",
+    "            features = np.append(features, np.array(cell_features), axis=0)\n",
+    "            labels = np.append(labels, np.array(cell_labels), axis=0)\n",
+    "        else:\n",
+    "            print(f'Cell {j} has only {len(d)} cycles. Skipping!')\n",
+    "    return features, labels"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "6cb3a8df",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "024ad7da",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>cycle_index</th>\n",
+       "      <th>discharge_capacity</th>\n",
+       "      <th>charge_capacity</th>\n",
+       "      <th>discharge_energy</th>\n",
+       "      <th>charge_energy</th>\n",
+       "      <th>dc_internal_resistance</th>\n",
+       "      <th>temperature_maximum</th>\n",
+       "      <th>temperature_average</th>\n",
+       "      <th>temperature_minimum</th>\n",
+       "      <th>date_time_iso</th>\n",
+       "      <th>energy_efficiency</th>\n",
+       "      <th>charge_throughput</th>\n",
+       "      <th>energy_throughput</th>\n",
+       "      <th>charge_duration</th>\n",
+       "      <th>time_temperature_integrated</th>\n",
+       "      <th>paused</th>\n",
+       "      <th>CV_time</th>\n",
+       "      <th>CV_current</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>4.750399</td>\n",
+       "      <td>3.870380</td>\n",
+       "      <td>17.390939</td>\n",
+       "      <td>15.072334</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2020-12-19T20:19:16+00:00</td>\n",
+       "      <td>1.153832</td>\n",
+       "      <td>3.870380</td>\n",
+       "      <td>15.072334</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2062.030029</td>\n",
+       "      <td>0.138247</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>6</td>\n",
+       "      <td>3.508421</td>\n",
+       "      <td>3.829267</td>\n",
+       "      <td>12.907875</td>\n",
+       "      <td>14.385632</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2020-12-23T06:59:08+00:00</td>\n",
+       "      <td>0.897276</td>\n",
+       "      <td>7.699647</td>\n",
+       "      <td>29.457966</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1799.969971</td>\n",
+       "      <td>0.224308</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>7</td>\n",
+       "      <td>3.498147</td>\n",
+       "      <td>3.513221</td>\n",
+       "      <td>12.869881</td>\n",
+       "      <td>13.314831</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2020-12-23T15:10:20+00:00</td>\n",
+       "      <td>0.966582</td>\n",
+       "      <td>11.212869</td>\n",
+       "      <td>42.772797</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1799.979980</td>\n",
+       "      <td>0.221103</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>8</td>\n",
+       "      <td>3.489705</td>\n",
+       "      <td>3.504323</td>\n",
+       "      <td>12.839340</td>\n",
+       "      <td>13.281834</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2020-12-23T23:01:18+00:00</td>\n",
+       "      <td>0.966684</td>\n",
+       "      <td>14.717191</td>\n",
+       "      <td>56.054630</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1799.979980</td>\n",
+       "      <td>0.222019</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>9</td>\n",
+       "      <td>3.481804</td>\n",
+       "      <td>3.496785</td>\n",
+       "      <td>12.810638</td>\n",
+       "      <td>13.254452</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2020-12-24T06:51:14+00:00</td>\n",
+       "      <td>0.966516</td>\n",
+       "      <td>18.213976</td>\n",
+       "      <td>69.309082</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1799.989990</td>\n",
+       "      <td>0.221332</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1240</th>\n",
+       "      <td>1310</td>\n",
+       "      <td>3.018786</td>\n",
+       "      <td>3.029007</td>\n",
+       "      <td>11.107913</td>\n",
+       "      <td>11.533662</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2022-03-13T21:08:59+00:00</td>\n",
+       "      <td>0.963086</td>\n",
+       "      <td>3917.212891</td>\n",
+       "      <td>14888.087891</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1799.989990</td>\n",
+       "      <td>0.189975</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1241</th>\n",
+       "      <td>1311</td>\n",
+       "      <td>3.016508</td>\n",
+       "      <td>3.025954</td>\n",
+       "      <td>11.100614</td>\n",
+       "      <td>11.522671</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2022-03-14T04:01:08+00:00</td>\n",
+       "      <td>0.963372</td>\n",
+       "      <td>3920.238770</td>\n",
+       "      <td>14899.610352</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1799.989990</td>\n",
+       "      <td>0.189059</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1242</th>\n",
+       "      <td>1312</td>\n",
+       "      <td>3.013734</td>\n",
+       "      <td>3.023249</td>\n",
+       "      <td>11.091372</td>\n",
+       "      <td>11.512824</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2022-03-14T10:52:57+00:00</td>\n",
+       "      <td>0.963393</td>\n",
+       "      <td>3923.261963</td>\n",
+       "      <td>14911.123047</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1799.989990</td>\n",
+       "      <td>0.192950</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1243</th>\n",
+       "      <td>1313</td>\n",
+       "      <td>3.011360</td>\n",
+       "      <td>3.020964</td>\n",
+       "      <td>11.083298</td>\n",
+       "      <td>11.504633</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2022-03-14T17:44:25+00:00</td>\n",
+       "      <td>0.963377</td>\n",
+       "      <td>3926.282959</td>\n",
+       "      <td>14922.627930</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1799.989990</td>\n",
+       "      <td>0.188830</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1244</th>\n",
+       "      <td>1314</td>\n",
+       "      <td>3.008897</td>\n",
+       "      <td>3.018276</td>\n",
+       "      <td>11.074881</td>\n",
+       "      <td>11.494771</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2022-03-15T00:35:37+00:00</td>\n",
+       "      <td>0.963471</td>\n",
+       "      <td>3929.301270</td>\n",
+       "      <td>14934.123047</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>6890.649902</td>\n",
+       "      <td>0.189746</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1245 rows × 18 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      cycle_index  discharge_capacity  charge_capacity  discharge_energy  \\\n",
+       "0               0            4.750399         3.870380         17.390939   \n",
+       "1               6            3.508421         3.829267         12.907875   \n",
+       "2               7            3.498147         3.513221         12.869881   \n",
+       "3               8            3.489705         3.504323         12.839340   \n",
+       "4               9            3.481804         3.496785         12.810638   \n",
+       "...           ...                 ...              ...               ...   \n",
+       "1240         1310            3.018786         3.029007         11.107913   \n",
+       "1241         1311            3.016508         3.025954         11.100614   \n",
+       "1242         1312            3.013734         3.023249         11.091372   \n",
+       "1243         1313            3.011360         3.020964         11.083298   \n",
+       "1244         1314            3.008897         3.018276         11.074881   \n",
+       "\n",
+       "      charge_energy  dc_internal_resistance  temperature_maximum  \\\n",
+       "0         15.072334                     0.0                  NaN   \n",
+       "1         14.385632                     0.0                  NaN   \n",
+       "2         13.314831                     0.0                  NaN   \n",
+       "3         13.281834                     0.0                  NaN   \n",
+       "4         13.254452                     0.0                  NaN   \n",
+       "...             ...                     ...                  ...   \n",
+       "1240      11.533662                     0.0                  NaN   \n",
+       "1241      11.522671                     0.0                  NaN   \n",
+       "1242      11.512824                     0.0                  NaN   \n",
+       "1243      11.504633                     0.0                  NaN   \n",
+       "1244      11.494771                     0.0                  NaN   \n",
+       "\n",
+       "      temperature_average  temperature_minimum              date_time_iso  \\\n",
+       "0                     NaN                  NaN  2020-12-19T20:19:16+00:00   \n",
+       "1                     NaN                  NaN  2020-12-23T06:59:08+00:00   \n",
+       "2                     NaN                  NaN  2020-12-23T15:10:20+00:00   \n",
+       "3                     NaN                  NaN  2020-12-23T23:01:18+00:00   \n",
+       "4                     NaN                  NaN  2020-12-24T06:51:14+00:00   \n",
+       "...                   ...                  ...                        ...   \n",
+       "1240                  NaN                  NaN  2022-03-13T21:08:59+00:00   \n",
+       "1241                  NaN                  NaN  2022-03-14T04:01:08+00:00   \n",
+       "1242                  NaN                  NaN  2022-03-14T10:52:57+00:00   \n",
+       "1243                  NaN                  NaN  2022-03-14T17:44:25+00:00   \n",
+       "1244                  NaN                  NaN  2022-03-15T00:35:37+00:00   \n",
+       "\n",
+       "      energy_efficiency  charge_throughput  energy_throughput  \\\n",
+       "0              1.153832           3.870380          15.072334   \n",
+       "1              0.897276           7.699647          29.457966   \n",
+       "2              0.966582          11.212869          42.772797   \n",
+       "3              0.966684          14.717191          56.054630   \n",
+       "4              0.966516          18.213976          69.309082   \n",
+       "...                 ...                ...                ...   \n",
+       "1240           0.963086        3917.212891       14888.087891   \n",
+       "1241           0.963372        3920.238770       14899.610352   \n",
+       "1242           0.963393        3923.261963       14911.123047   \n",
+       "1243           0.963377        3926.282959       14922.627930   \n",
+       "1244           0.963471        3929.301270       14934.123047   \n",
+       "\n",
+       "      charge_duration  time_temperature_integrated  paused      CV_time  \\\n",
+       "0                 NaN                          NaN       0  2062.030029   \n",
+       "1                 NaN                          NaN       0  1799.969971   \n",
+       "2                 NaN                          NaN       0  1799.979980   \n",
+       "3                 NaN                          NaN       0  1799.979980   \n",
+       "4                 NaN                          NaN       0  1799.989990   \n",
+       "...               ...                          ...     ...          ...   \n",
+       "1240              NaN                          NaN       0  1799.989990   \n",
+       "1241              NaN                          NaN       0  1799.989990   \n",
+       "1242              NaN                          NaN       0  1799.989990   \n",
+       "1243              NaN                          NaN       0  1799.989990   \n",
+       "1244              NaN                          NaN       0  6890.649902   \n",
+       "\n",
+       "      CV_current  \n",
+       "0       0.138247  \n",
+       "1       0.224308  \n",
+       "2       0.221103  \n",
+       "3       0.222019  \n",
+       "4       0.221332  \n",
+       "...          ...  \n",
+       "1240    0.189975  \n",
+       "1241    0.189059  \n",
+       "1242    0.192950  \n",
+       "1243    0.188830  \n",
+       "1244    0.189746  \n",
+       "\n",
+       "[1245 rows x 18 columns]"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cell.structured_summary"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "d94c4ed0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
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+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
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+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>voltage</th>\n",
+       "      <th>current</th>\n",
+       "      <th>cycle_index</th>\n",
+       "      <th>discharge_capacity</th>\n",
+       "      <th>charge_capacity</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1244412</th>\n",
+       "      <td>3.201101</td>\n",
+       "      <td>-0.967737</td>\n",
+       "      <td>1314</td>\n",
+       "      <td>3.007392</td>\n",
+       "      <td>3.018276</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1244413</th>\n",
+       "      <td>3.202803</td>\n",
+       "      <td>-0.967540</td>\n",
+       "      <td>1314</td>\n",
+       "      <td>3.005107</td>\n",
+       "      <td>3.018276</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1244414</th>\n",
+       "      <td>3.204504</td>\n",
+       "      <td>-0.967693</td>\n",
+       "      <td>1314</td>\n",
+       "      <td>3.002765</td>\n",
+       "      <td>3.018276</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1244415</th>\n",
+       "      <td>3.206206</td>\n",
+       "      <td>-0.967845</td>\n",
+       "      <td>1314</td>\n",
+       "      <td>3.000423</td>\n",
+       "      <td>3.018276</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1244416</th>\n",
+       "      <td>3.207908</td>\n",
+       "      <td>-0.967956</td>\n",
+       "      <td>1314</td>\n",
+       "      <td>2.998101</td>\n",
+       "      <td>3.018276</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1244919</th>\n",
+       "      <td>4.063864</td>\n",
+       "      <td>-0.967852</td>\n",
+       "      <td>1314</td>\n",
+       "      <td>0.001188</td>\n",
+       "      <td>3.018276</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1244920</th>\n",
+       "      <td>4.065566</td>\n",
+       "      <td>-0.967927</td>\n",
+       "      <td>1314</td>\n",
+       "      <td>0.000507</td>\n",
+       "      <td>3.018276</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1244921</th>\n",
+       "      <td>4.067267</td>\n",
+       "      <td>-0.969217</td>\n",
+       "      <td>1314</td>\n",
+       "      <td>0.000195</td>\n",
+       "      <td>3.018276</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1244922</th>\n",
+       "      <td>4.068969</td>\n",
+       "      <td>-0.971274</td>\n",
+       "      <td>1314</td>\n",
+       "      <td>0.000116</td>\n",
+       "      <td>3.018276</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1244923</th>\n",
+       "      <td>4.070671</td>\n",
+       "      <td>-0.973332</td>\n",
+       "      <td>1314</td>\n",
+       "      <td>0.000037</td>\n",
+       "      <td>3.018276</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>512 rows × 5 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       "1244412  3.201101 -0.967737         1314            3.007392         3.018276\n",
+       "1244413  3.202803 -0.967540         1314            3.005107         3.018276\n",
+       "1244414  3.204504 -0.967693         1314            3.002765         3.018276\n",
+       "1244415  3.206206 -0.967845         1314            3.000423         3.018276\n",
+       "1244416  3.207908 -0.967956         1314            2.998101         3.018276\n",
+       "...           ...       ...          ...                 ...              ...\n",
+       "1244919  4.063864 -0.967852         1314            0.001188         3.018276\n",
+       "1244920  4.065566 -0.967927         1314            0.000507         3.018276\n",
+       "1244921  4.067267 -0.969217         1314            0.000195         3.018276\n",
+       "1244922  4.068969 -0.971274         1314            0.000116         3.018276\n",
+       "1244923  4.070671 -0.973332         1314            0.000037         3.018276\n",
+       "\n",
+       "[512 rows x 5 columns]"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "structured_data_list[0][-1]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "3961a5c1",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
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+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
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+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
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+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>cycle_index</th>\n",
+       "      <th>discharge_capacity</th>\n",
+       "      <th>charge_capacity</th>\n",
+       "      <th>discharge_energy</th>\n",
+       "      <th>charge_energy</th>\n",
+       "      <th>charge_throughput</th>\n",
+       "      <th>energy_throughput</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>4.750399</td>\n",
+       "      <td>3.870380</td>\n",
+       "      <td>17.390939</td>\n",
+       "      <td>15.072334</td>\n",
+       "      <td>3.870380</td>\n",
+       "      <td>15.072334</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>6</td>\n",
+       "      <td>3.508421</td>\n",
+       "      <td>3.829267</td>\n",
+       "      <td>12.907875</td>\n",
+       "      <td>14.385632</td>\n",
+       "      <td>7.699647</td>\n",
+       "      <td>29.457966</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>7</td>\n",
+       "      <td>3.498147</td>\n",
+       "      <td>3.513221</td>\n",
+       "      <td>12.869881</td>\n",
+       "      <td>13.314831</td>\n",
+       "      <td>11.212869</td>\n",
+       "      <td>42.772797</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>8</td>\n",
+       "      <td>3.489705</td>\n",
+       "      <td>3.504323</td>\n",
+       "      <td>12.839340</td>\n",
+       "      <td>13.281834</td>\n",
+       "      <td>14.717191</td>\n",
+       "      <td>56.054630</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>9</td>\n",
+       "      <td>3.481804</td>\n",
+       "      <td>3.496785</td>\n",
+       "      <td>12.810638</td>\n",
+       "      <td>13.254452</td>\n",
+       "      <td>18.213976</td>\n",
+       "      <td>69.309082</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1240</th>\n",
+       "      <td>1310</td>\n",
+       "      <td>3.018786</td>\n",
+       "      <td>3.029007</td>\n",
+       "      <td>11.107913</td>\n",
+       "      <td>11.533662</td>\n",
+       "      <td>3917.212891</td>\n",
+       "      <td>14888.087891</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1241</th>\n",
+       "      <td>1311</td>\n",
+       "      <td>3.016508</td>\n",
+       "      <td>3.025954</td>\n",
+       "      <td>11.100614</td>\n",
+       "      <td>11.522671</td>\n",
+       "      <td>3920.238770</td>\n",
+       "      <td>14899.610352</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1242</th>\n",
+       "      <td>1312</td>\n",
+       "      <td>3.013734</td>\n",
+       "      <td>3.023249</td>\n",
+       "      <td>11.091372</td>\n",
+       "      <td>11.512824</td>\n",
+       "      <td>3923.261963</td>\n",
+       "      <td>14911.123047</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1243</th>\n",
+       "      <td>1313</td>\n",
+       "      <td>3.011360</td>\n",
+       "      <td>3.020964</td>\n",
+       "      <td>11.083298</td>\n",
+       "      <td>11.504633</td>\n",
+       "      <td>3926.282959</td>\n",
+       "      <td>14922.627930</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1244</th>\n",
+       "      <td>1314</td>\n",
+       "      <td>3.008897</td>\n",
+       "      <td>3.018276</td>\n",
+       "      <td>11.074881</td>\n",
+       "      <td>11.494771</td>\n",
+       "      <td>3929.301270</td>\n",
+       "      <td>14934.123047</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1245 rows × 7 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      cycle_index  discharge_capacity  charge_capacity  discharge_energy  \\\n",
+       "0               0            4.750399         3.870380         17.390939   \n",
+       "1               6            3.508421         3.829267         12.907875   \n",
+       "2               7            3.498147         3.513221         12.869881   \n",
+       "3               8            3.489705         3.504323         12.839340   \n",
+       "4               9            3.481804         3.496785         12.810638   \n",
+       "...           ...                 ...              ...               ...   \n",
+       "1240         1310            3.018786         3.029007         11.107913   \n",
+       "1241         1311            3.016508         3.025954         11.100614   \n",
+       "1242         1312            3.013734         3.023249         11.091372   \n",
+       "1243         1313            3.011360         3.020964         11.083298   \n",
+       "1244         1314            3.008897         3.018276         11.074881   \n",
+       "\n",
+       "      charge_energy  charge_throughput  energy_throughput  \n",
+       "0         15.072334           3.870380          15.072334  \n",
+       "1         14.385632           7.699647          29.457966  \n",
+       "2         13.314831          11.212869          42.772797  \n",
+       "3         13.281834          14.717191          56.054630  \n",
+       "4         13.254452          18.213976          69.309082  \n",
+       "...             ...                ...                ...  \n",
+       "1240      11.533662        3917.212891       14888.087891  \n",
+       "1241      11.522671        3920.238770       14899.610352  \n",
+       "1242      11.512824        3923.261963       14911.123047  \n",
+       "1243      11.504633        3926.282959       14922.627930  \n",
+       "1244      11.494771        3929.301270       14934.123047  \n",
+       "\n",
+       "[1245 rows x 7 columns]"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "summary_data_list[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b161baa2",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "2276d4b9",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "4 1732 1731\n",
+      "7 2307 2306\n",
+      "10 2839 2838\n",
+      "12 707 706\n",
+      "14 2255 2254\n",
+      "15 1477 1476\n",
+      "16 1766 1765\n",
+      "18 944 943\n",
+      "21 1478 1477\n",
+      "23 1876 1875\n",
+      "25 574 573\n",
+      "32 1469 1468\n",
+      "33 90 89\n",
+      "36 79 78\n",
+      "38 1645 1644\n",
+      "40 1494 1493\n",
+      "46 1558 1557\n",
+      "47 1044 1043\n",
+      "48 1832 1831\n",
+      "50 3933 3932\n",
+      "51 81 80\n",
+      "54 2323 2322\n",
+      "58 1680 1679\n",
+      "59 2764 2763\n",
+      "61 3876 3875\n",
+      "66 901 900\n",
+      "67 1563 1562\n",
+      "68 4246 4245\n",
+      "69 1642 1641\n",
+      "72 1466 1465\n",
+      "76 3545 3544\n",
+      "83 1527 1526\n",
+      "85 1320 1319\n",
+      "89 4044 4043\n",
+      "91 1190 1189\n",
+      "93 964 963\n",
+      "94 761 760\n",
+      "97 1505 1504\n",
+      "100 327 326\n",
+      "108 1164 1163\n",
+      "109 2283 2282\n",
+      "113 3982 3981\n",
+      "118 4739 4738\n",
+      "119 2989 2988\n",
+      "121 511 510\n",
+      "124 86 85\n",
+      "126 3410 3409\n",
+      "128 1486 1485\n",
+      "130 2788 2787\n",
+      "131 72 71\n",
+      "132 2824 2823\n",
+      "133 2418 2417\n",
+      "134 1654 1653\n",
+      "137 1071 1070\n",
+      "138 1429 1428\n",
+      "140 2467 2466\n",
+      "141 2268 2267\n",
+      "146 1710 1709\n",
+      "150 1323 1322\n",
+      "152 2177 2176\n",
+      "154 1494 1493\n",
+      "155 1610 1609\n",
+      "156 1468 1467\n",
+      "157 3829 3828\n",
+      "160 84 83\n",
+      "165 1931 1925\n",
+      "168 510 509\n",
+      "169 1591 1590\n",
+      "171 2591 2590\n",
+      "174 1244 1243\n",
+      "176 1808 1807\n",
+      "179 1950 1949\n",
+      "183 1569 1568\n",
+      "184 1931 1925\n",
+      "188 1562 1561\n",
+      "189 1505 1504\n",
+      "192 1244 1243\n",
+      "195 67 66\n",
+      "196 1942 1941\n",
+      "199 3627 3626\n",
+      "202 3161 3160\n",
+      "207 3175 3174\n",
+      "208 3072 3071\n",
+      "215 1314 1313\n",
+      "218 1065 1064\n",
+      "222 3314 3313\n",
+      "225 2779 2778\n",
+      "228 1220 1219\n",
+      "231 1637 1636\n",
+      "234 3590 3589\n",
+      "235 1319 1318\n",
+      "238 664 663\n",
+      "239 820 819\n",
+      "242 1356 1355\n",
+      "245 2290 2289\n",
+      "246 1491 1490\n",
+      "247 1884 1883\n",
+      "250 1835 1834\n",
+      "255 1358 1357\n",
+      "256 1642 1641\n",
+      "261 2809 2808\n",
+      "263 1104 1103\n",
+      "267 1480 1479\n",
+      "268 1067 1066\n",
+      "269 1525 1524\n",
+      "270 821 820\n",
+      "272 889 888\n",
+      "274 1469 1468\n",
+      "275 85 84\n",
+      "279 1472 1471\n",
+      "280 3478 3477\n",
+      "282 1620 1619\n",
+      "283 1132 1126\n",
+      "285 1714 1713\n",
+      "286 65 64\n",
+      "287 1644 1643\n",
+      "288 102 101\n",
+      "289 2467 2466\n",
+      "294 682 681\n",
+      "298 4064 4063\n",
+      "300 1609 1608\n",
+      "301 1456 1455\n",
+      "306 78 77\n",
+      "310 1802 1801\n",
+      "311 3953 3952\n",
+      "320 2800 2799\n",
+      "321 1222 1221\n",
+      "329 513 512\n",
+      "330 617 616\n",
+      "331 848 847\n",
+      "334 77 76\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "for i in range(len(summary_data_list)):\n",
+    "    n_structured_data = np.array(structured_data_list[i][-1]['cycle_index'])[-1]\n",
+    "    n_summary_data = np.array(summary_data_list[i]['cycle_index'])[-1]\n",
+    "    if n_structured_data != n_summary_data:\n",
+    "        print(i, n_structured_data, n_summary_data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 137,
+   "id": "1e61c982",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "structured_data_list = []\n",
+    "summary_data_list = []\n",
+    "for m,n in dat:\n",
+    "    structured_data, summary_data = m,n\n",
+    "    s_list = []\n",
+    "    for s in structured_data:\n",
+    "        if s.shape[0] != 0:\n",
+    "            s_list.append(s)\n",
+    "    structured_data_list.append(s_list)\n",
+    "    summary_data_list.append(summary_data[0].iloc[:-1])\n",
+    "#     summary_data = summary_data.iloc[:-1]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "id": "3a4f69f0",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "AttributeError",
+     "evalue": "'MaccorDatapath' object has no attribute 'summary_data'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
+      "Input \u001b[0;32mIn [57]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mcell\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msummary_data\u001b[49m[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mcycle_index\u001b[39m\u001b[38;5;124m'\u001b[39m]\n",
+      "\u001b[0;31mAttributeError\u001b[0m: 'MaccorDatapath' object has no attribute 'summary_data'"
+     ]
+    }
+   ],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "id": "40cbe41d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Pre-processing data for cell PreDiag_000272_0000C5_structured.\n"
+     ]
+    }
+   ],
+   "source": [
+    "structured_columns = ['voltage', 'current', 'cycle_index', 'discharge_capacity', 'charge_capacity']\n",
+    "summary_columns = ['cycle_index', 'discharge_capacity', 'charge_capacity', 'discharge_energy',\n",
+    "                   'charge_energy', 'charge_throughput', 'energy_throughput']\n",
+    "n = '/home/ec2-user/SageMaker/data_cache/structure/PreDiag_000272_0000C5_structured.json.gz'\n",
+    "structured_data = []\n",
+    "summary_data = []\n",
+    "max_cycle_idx = max(cell.structured_data['cycle_index'])\n",
+    "manufacturding_nominal_discharge_capacity = 4.84\n",
+    "nominal_discharge_capacity_drop = 1- cell.structured_summary['discharge_capacity'][1]/manufacturding_nominal_discharge_capacity\n",
+    "# excluding cells that that have more that 80% drop in discharge capacity within 1st cycle\n",
+    "# excluding cells that that have less than 50 cycles\n",
+    "cycle_idx_threshold = 50\n",
+    "nominal_discharge_capacity_drop_threshold = 0.8\n",
+    "if nominal_discharge_capacity_drop < nominal_discharge_capacity_drop_threshold and not max_cycle_idx < cycle_idx_threshold:\n",
+    "    print(f'Pre-processing data for cell {n[46:-8]}.')\n",
+    "#     for j in tqdm(range(max_cycle_idx)):\n",
+    "    for c in tqdm(cell.structured_summary['cycle_index']):\n",
+    "        clean_cell = bye_cycle.clean_cycle_data(cell, j, columns=structured_columns)\n",
+    "        structured_data.append(clean_cell)\n",
+    "    summary_data.append(cell.structured_summary[summary_columns])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "id": "ccec0383",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>voltage</th>\n",
+       "      <th>current</th>\n",
+       "      <th>cycle_index</th>\n",
+       "      <th>discharge_capacity</th>\n",
+       "      <th>charge_capacity</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>118</th>\n",
+       "      <td>2.700801</td>\n",
+       "      <td>-0.692125</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4.741166</td>\n",
+       "      <td>3.852409</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>119</th>\n",
+       "      <td>2.702502</td>\n",
+       "      <td>-0.691623</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4.740309</td>\n",
+       "      <td>3.852409</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>120</th>\n",
+       "      <td>2.704204</td>\n",
+       "      <td>-0.691216</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4.739393</td>\n",
+       "      <td>3.852409</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>121</th>\n",
+       "      <td>2.705906</td>\n",
+       "      <td>-0.691276</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4.738537</td>\n",
+       "      <td>3.852409</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>122</th>\n",
+       "      <td>2.707608</td>\n",
+       "      <td>-0.691522</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4.737663</td>\n",
+       "      <td>3.852409</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3286096</th>\n",
+       "      <td>3.588057</td>\n",
+       "      <td>2.419597</td>\n",
+       "      <td>1738</td>\n",
+       "      <td>0.000017</td>\n",
+       "      <td>0.461665</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3286097</th>\n",
+       "      <td>3.589617</td>\n",
+       "      <td>2.419683</td>\n",
+       "      <td>1738</td>\n",
+       "      <td>0.000017</td>\n",
+       "      <td>0.466474</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3286098</th>\n",
+       "      <td>3.591153</td>\n",
+       "      <td>2.419893</td>\n",
+       "      <td>1738</td>\n",
+       "      <td>0.000017</td>\n",
+       "      <td>0.471283</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3286099</th>\n",
+       "      <td>3.592690</td>\n",
+       "      <td>2.420102</td>\n",
+       "      <td>1738</td>\n",
+       "      <td>0.000017</td>\n",
+       "      <td>0.476092</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3286100</th>\n",
+       "      <td>3.594243</td>\n",
+       "      <td>2.419981</td>\n",
+       "      <td>1738</td>\n",
+       "      <td>0.000017</td>\n",
+       "      <td>0.480901</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1294884 rows × 5 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       "118      2.700801 -0.692125            0            4.741166         3.852409\n",
+       "119      2.702502 -0.691623            0            4.740309         3.852409\n",
+       "120      2.704204 -0.691216            0            4.739393         3.852409\n",
+       "121      2.705906 -0.691276            0            4.738537         3.852409\n",
+       "122      2.707608 -0.691522            0            4.737663         3.852409\n",
+       "...           ...       ...          ...                 ...              ...\n",
+       "3286096  3.588057  2.419597         1738            0.000017         0.461665\n",
+       "3286097  3.589617  2.419683         1738            0.000017         0.466474\n",
+       "3286098  3.591153  2.419893         1738            0.000017         0.471283\n",
+       "3286099  3.592690  2.420102         1738            0.000017         0.476092\n",
+       "3286100  3.594243  2.419981         1738            0.000017         0.480901\n",
+       "\n",
+       "[1294884 rows x 5 columns]"
+      ]
+     },
+     "execution_count": 70,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cycle_number = 2\n",
+    "selected_cell_data = cell.structured_data[structured_columns].dropna()\n",
+    "selected_cell_data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "id": "5f166523",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
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+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>voltage</th>\n",
+       "      <th>current</th>\n",
+       "      <th>cycle_index</th>\n",
+       "      <th>discharge_capacity</th>\n",
+       "      <th>charge_capacity</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "Empty DataFrame\n",
+       "Columns: [voltage, current, cycle_index, discharge_capacity, charge_capacity]\n",
+       "Index: []"
+      ]
+     },
+     "execution_count": 69,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "clean_cell_data_cycle_number = selected_cell_data.loc[(selected_cell_data['cycle_index'] == cycle_number) \n",
+    "                                          & (selected_cell_data['discharge_capacity']!=0)]\n",
+    "clean_cell_data_cycle_number"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "id": "639365ac",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "\n",
+       "    .dataframe tbody tr th {\n",
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+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>cycle_index</th>\n",
+       "      <th>discharge_capacity</th>\n",
+       "      <th>charge_capacity</th>\n",
+       "      <th>discharge_energy</th>\n",
+       "      <th>charge_energy</th>\n",
+       "      <th>charge_throughput</th>\n",
+       "      <th>energy_throughput</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>4.741486</td>\n",
+       "      <td>3.852409</td>\n",
+       "      <td>17.353089</td>\n",
+       "      <td>15.000720</td>\n",
+       "      <td>3.852409</td>\n",
+       "      <td>15.000720</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>6</td>\n",
+       "      <td>2.642477</td>\n",
+       "      <td>4.523357</td>\n",
+       "      <td>9.959919</td>\n",
+       "      <td>17.299393</td>\n",
+       "      <td>8.375766</td>\n",
+       "      <td>32.300114</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>7</td>\n",
+       "      <td>2.634625</td>\n",
+       "      <td>2.651804</td>\n",
+       "      <td>9.932148</td>\n",
+       "      <td>10.605730</td>\n",
+       "      <td>11.027570</td>\n",
+       "      <td>42.905842</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>8</td>\n",
+       "      <td>2.627890</td>\n",
+       "      <td>2.638572</td>\n",
+       "      <td>9.907780</td>\n",
+       "      <td>10.554319</td>\n",
+       "      <td>13.666142</td>\n",
+       "      <td>53.460163</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>9</td>\n",
+       "      <td>2.624367</td>\n",
+       "      <td>2.630954</td>\n",
+       "      <td>9.895451</td>\n",
+       "      <td>10.525008</td>\n",
+       "      <td>16.297096</td>\n",
+       "      <td>63.985168</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1638</th>\n",
+       "      <td>1728</td>\n",
+       "      <td>1.919406</td>\n",
+       "      <td>1.921610</td>\n",
+       "      <td>7.119877</td>\n",
+       "      <td>7.732109</td>\n",
+       "      <td>3616.476074</td>\n",
+       "      <td>14500.291016</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1639</th>\n",
+       "      <td>1729</td>\n",
+       "      <td>1.916676</td>\n",
+       "      <td>1.920892</td>\n",
+       "      <td>7.109297</td>\n",
+       "      <td>7.728719</td>\n",
+       "      <td>3618.396973</td>\n",
+       "      <td>14508.019531</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1640</th>\n",
+       "      <td>1730</td>\n",
+       "      <td>1.918061</td>\n",
+       "      <td>1.920649</td>\n",
+       "      <td>7.115403</td>\n",
+       "      <td>7.728511</td>\n",
+       "      <td>3620.317627</td>\n",
+       "      <td>14515.748047</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1641</th>\n",
+       "      <td>1731</td>\n",
+       "      <td>1.915628</td>\n",
+       "      <td>1.919130</td>\n",
+       "      <td>7.105213</td>\n",
+       "      <td>7.722100</td>\n",
+       "      <td>3622.236816</td>\n",
+       "      <td>14523.470703</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1642</th>\n",
+       "      <td>1732</td>\n",
+       "      <td>4.077648</td>\n",
+       "      <td>3.616768</td>\n",
+       "      <td>14.945608</td>\n",
+       "      <td>14.627481</td>\n",
+       "      <td>3625.853516</td>\n",
+       "      <td>14538.097656</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1643 rows × 7 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      cycle_index  discharge_capacity  charge_capacity  discharge_energy  \\\n",
+       "0               0            4.741486         3.852409         17.353089   \n",
+       "1               6            2.642477         4.523357          9.959919   \n",
+       "2               7            2.634625         2.651804          9.932148   \n",
+       "3               8            2.627890         2.638572          9.907780   \n",
+       "4               9            2.624367         2.630954          9.895451   \n",
+       "...           ...                 ...              ...               ...   \n",
+       "1638         1728            1.919406         1.921610          7.119877   \n",
+       "1639         1729            1.916676         1.920892          7.109297   \n",
+       "1640         1730            1.918061         1.920649          7.115403   \n",
+       "1641         1731            1.915628         1.919130          7.105213   \n",
+       "1642         1732            4.077648         3.616768         14.945608   \n",
+       "\n",
+       "      charge_energy  charge_throughput  energy_throughput  \n",
+       "0         15.000720           3.852409          15.000720  \n",
+       "1         17.299393           8.375766          32.300114  \n",
+       "2         10.605730          11.027570          42.905842  \n",
+       "3         10.554319          13.666142          53.460163  \n",
+       "4         10.525008          16.297096          63.985168  \n",
+       "...             ...                ...                ...  \n",
+       "1638       7.732109        3616.476074       14500.291016  \n",
+       "1639       7.728719        3618.396973       14508.019531  \n",
+       "1640       7.728511        3620.317627       14515.748047  \n",
+       "1641       7.722100        3622.236816       14523.470703  \n",
+       "1642      14.627481        3625.853516       14538.097656  \n",
+       "\n",
+       "[1643 rows x 7 columns]"
+      ]
+     },
+     "execution_count": 60,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "summary_data[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "id": "46c16de4",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>voltage</th>\n",
+       "      <th>current</th>\n",
+       "      <th>cycle_index</th>\n",
+       "      <th>discharge_capacity</th>\n",
+       "      <th>charge_capacity</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "Empty DataFrame\n",
+       "Columns: [voltage, current, cycle_index, discharge_capacity, charge_capacity]\n",
+       "Index: []"
+      ]
+     },
+     "execution_count": 62,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "structured_data[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "id": "2487f640",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>voltage</th>\n",
+       "      <th>current</th>\n",
+       "      <th>cycle_index</th>\n",
+       "      <th>discharge_capacity</th>\n",
+       "      <th>charge_capacity</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>118</th>\n",
+       "      <td>2.700801</td>\n",
+       "      <td>-0.692125</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4.741166</td>\n",
+       "      <td>3.852409</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>119</th>\n",
+       "      <td>2.702502</td>\n",
+       "      <td>-0.691623</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4.740309</td>\n",
+       "      <td>3.852409</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>120</th>\n",
+       "      <td>2.704204</td>\n",
+       "      <td>-0.691216</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4.739393</td>\n",
+       "      <td>3.852409</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>121</th>\n",
+       "      <td>2.705906</td>\n",
+       "      <td>-0.691276</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4.738537</td>\n",
+       "      <td>3.852409</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>122</th>\n",
+       "      <td>2.707608</td>\n",
+       "      <td>-0.691522</td>\n",
+       "      <td>0</td>\n",
+       "      <td>4.737663</td>\n",
+       "      <td>3.852409</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3286096</th>\n",
+       "      <td>3.588057</td>\n",
+       "      <td>2.419597</td>\n",
+       "      <td>1738</td>\n",
+       "      <td>0.000017</td>\n",
+       "      <td>0.461665</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3286097</th>\n",
+       "      <td>3.589617</td>\n",
+       "      <td>2.419683</td>\n",
+       "      <td>1738</td>\n",
+       "      <td>0.000017</td>\n",
+       "      <td>0.466474</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3286098</th>\n",
+       "      <td>3.591153</td>\n",
+       "      <td>2.419893</td>\n",
+       "      <td>1738</td>\n",
+       "      <td>0.000017</td>\n",
+       "      <td>0.471283</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3286099</th>\n",
+       "      <td>3.592690</td>\n",
+       "      <td>2.420102</td>\n",
+       "      <td>1738</td>\n",
+       "      <td>0.000017</td>\n",
+       "      <td>0.476092</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3286100</th>\n",
+       "      <td>3.594243</td>\n",
+       "      <td>2.419981</td>\n",
+       "      <td>1738</td>\n",
+       "      <td>0.000017</td>\n",
+       "      <td>0.480901</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1294884 rows × 5 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       "118      2.700801 -0.692125            0            4.741166         3.852409\n",
+       "119      2.702502 -0.691623            0            4.740309         3.852409\n",
+       "120      2.704204 -0.691216            0            4.739393         3.852409\n",
+       "121      2.705906 -0.691276            0            4.738537         3.852409\n",
+       "122      2.707608 -0.691522            0            4.737663         3.852409\n",
+       "...           ...       ...          ...                 ...              ...\n",
+       "3286096  3.588057  2.419597         1738            0.000017         0.461665\n",
+       "3286097  3.589617  2.419683         1738            0.000017         0.466474\n",
+       "3286098  3.591153  2.419893         1738            0.000017         0.471283\n",
+       "3286099  3.592690  2.420102         1738            0.000017         0.476092\n",
+       "3286100  3.594243  2.419981         1738            0.000017         0.480901\n",
+       "\n",
+       "[1294884 rows x 5 columns]"
+      ]
+     },
+     "execution_count": 53,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cell.structured_data[structured_columns].dropna()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "id": "1d0b73c7",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
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+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>cycle_index</th>\n",
+       "      <th>discharge_capacity</th>\n",
+       "      <th>charge_capacity</th>\n",
+       "      <th>discharge_energy</th>\n",
+       "      <th>charge_energy</th>\n",
+       "      <th>charge_throughput</th>\n",
+       "      <th>energy_throughput</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>4.741486</td>\n",
+       "      <td>3.852409</td>\n",
+       "      <td>17.353089</td>\n",
+       "      <td>15.000720</td>\n",
+       "      <td>3.852409</td>\n",
+       "      <td>15.000720</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>6</td>\n",
+       "      <td>2.642477</td>\n",
+       "      <td>4.523357</td>\n",
+       "      <td>9.959919</td>\n",
+       "      <td>17.299393</td>\n",
+       "      <td>8.375766</td>\n",
+       "      <td>32.300114</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>7</td>\n",
+       "      <td>2.634625</td>\n",
+       "      <td>2.651804</td>\n",
+       "      <td>9.932148</td>\n",
+       "      <td>10.605730</td>\n",
+       "      <td>11.027570</td>\n",
+       "      <td>42.905842</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>8</td>\n",
+       "      <td>2.627890</td>\n",
+       "      <td>2.638572</td>\n",
+       "      <td>9.907780</td>\n",
+       "      <td>10.554319</td>\n",
+       "      <td>13.666142</td>\n",
+       "      <td>53.460163</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>9</td>\n",
+       "      <td>2.624367</td>\n",
+       "      <td>2.630954</td>\n",
+       "      <td>9.895451</td>\n",
+       "      <td>10.525008</td>\n",
+       "      <td>16.297096</td>\n",
+       "      <td>63.985168</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1638</th>\n",
+       "      <td>1728</td>\n",
+       "      <td>1.919406</td>\n",
+       "      <td>1.921610</td>\n",
+       "      <td>7.119877</td>\n",
+       "      <td>7.732109</td>\n",
+       "      <td>3616.476074</td>\n",
+       "      <td>14500.291016</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1639</th>\n",
+       "      <td>1729</td>\n",
+       "      <td>1.916676</td>\n",
+       "      <td>1.920892</td>\n",
+       "      <td>7.109297</td>\n",
+       "      <td>7.728719</td>\n",
+       "      <td>3618.396973</td>\n",
+       "      <td>14508.019531</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1640</th>\n",
+       "      <td>1730</td>\n",
+       "      <td>1.918061</td>\n",
+       "      <td>1.920649</td>\n",
+       "      <td>7.115403</td>\n",
+       "      <td>7.728511</td>\n",
+       "      <td>3620.317627</td>\n",
+       "      <td>14515.748047</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1641</th>\n",
+       "      <td>1731</td>\n",
+       "      <td>1.915628</td>\n",
+       "      <td>1.919130</td>\n",
+       "      <td>7.105213</td>\n",
+       "      <td>7.722100</td>\n",
+       "      <td>3622.236816</td>\n",
+       "      <td>14523.470703</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1642</th>\n",
+       "      <td>1732</td>\n",
+       "      <td>4.077648</td>\n",
+       "      <td>3.616768</td>\n",
+       "      <td>14.945608</td>\n",
+       "      <td>14.627481</td>\n",
+       "      <td>3625.853516</td>\n",
+       "      <td>14538.097656</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1643 rows × 7 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      cycle_index  discharge_capacity  charge_capacity  discharge_energy  \\\n",
+       "0               0            4.741486         3.852409         17.353089   \n",
+       "1               6            2.642477         4.523357          9.959919   \n",
+       "2               7            2.634625         2.651804          9.932148   \n",
+       "3               8            2.627890         2.638572          9.907780   \n",
+       "4               9            2.624367         2.630954          9.895451   \n",
+       "...           ...                 ...              ...               ...   \n",
+       "1638         1728            1.919406         1.921610          7.119877   \n",
+       "1639         1729            1.916676         1.920892          7.109297   \n",
+       "1640         1730            1.918061         1.920649          7.115403   \n",
+       "1641         1731            1.915628         1.919130          7.105213   \n",
+       "1642         1732            4.077648         3.616768         14.945608   \n",
+       "\n",
+       "      charge_energy  charge_throughput  energy_throughput  \n",
+       "0         15.000720           3.852409          15.000720  \n",
+       "1         17.299393           8.375766          32.300114  \n",
+       "2         10.605730          11.027570          42.905842  \n",
+       "3         10.554319          13.666142          53.460163  \n",
+       "4         10.525008          16.297096          63.985168  \n",
+       "...             ...                ...                ...  \n",
+       "1638       7.732109        3616.476074       14500.291016  \n",
+       "1639       7.728719        3618.396973       14508.019531  \n",
+       "1640       7.728511        3620.317627       14515.748047  \n",
+       "1641       7.722100        3622.236816       14523.470703  \n",
+       "1642      14.627481        3625.853516       14538.097656  \n",
+       "\n",
+       "[1643 rows x 7 columns]"
+      ]
+     },
+     "execution_count": 55,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "summary_data[-1]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "id": "87f44b56",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
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+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>voltage</th>\n",
+       "      <th>current</th>\n",
+       "      <th>cycle_index</th>\n",
+       "      <th>discharge_capacity</th>\n",
+       "      <th>charge_capacity</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "Empty DataFrame\n",
+       "Columns: [voltage, current, cycle_index, discharge_capacity, charge_capacity]\n",
+       "Index: []"
+      ]
+     },
+     "execution_count": 49,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "structured_data[-3]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3a2826c4",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 123,
+   "id": "f01c7392",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "\n",
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+       "\n",
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+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>cycle_index</th>\n",
+       "      <th>discharge_capacity</th>\n",
+       "      <th>charge_capacity</th>\n",
+       "      <th>discharge_energy</th>\n",
+       "      <th>charge_energy</th>\n",
+       "      <th>charge_throughput</th>\n",
+       "      <th>energy_throughput</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>4.739763</td>\n",
+       "      <td>3.845542</td>\n",
+       "      <td>17.344500</td>\n",
+       "      <td>14.976089</td>\n",
+       "      <td>3.845542</td>\n",
+       "      <td>14.976089</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>6</td>\n",
+       "      <td>3.801423</td>\n",
+       "      <td>3.780793</td>\n",
+       "      <td>13.262715</td>\n",
+       "      <td>14.334126</td>\n",
+       "      <td>7.626336</td>\n",
+       "      <td>29.310215</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>7</td>\n",
+       "      <td>3.796112</td>\n",
+       "      <td>3.798094</td>\n",
+       "      <td>13.241635</td>\n",
+       "      <td>14.414895</td>\n",
+       "      <td>11.424430</td>\n",
+       "      <td>43.725109</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>8</td>\n",
+       "      <td>3.791151</td>\n",
+       "      <td>3.794633</td>\n",
+       "      <td>13.218457</td>\n",
+       "      <td>14.402270</td>\n",
+       "      <td>15.219062</td>\n",
+       "      <td>58.127380</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>9</td>\n",
+       "      <td>3.788853</td>\n",
+       "      <td>3.790908</td>\n",
+       "      <td>13.206060</td>\n",
+       "      <td>14.389844</td>\n",
+       "      <td>19.009970</td>\n",
+       "      <td>72.517227</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1978</th>\n",
+       "      <td>2033</td>\n",
+       "      <td>1.730030</td>\n",
+       "      <td>1.730979</td>\n",
+       "      <td>5.712026</td>\n",
+       "      <td>6.869929</td>\n",
+       "      <td>4956.676758</td>\n",
+       "      <td>19291.085938</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1979</th>\n",
+       "      <td>2034</td>\n",
+       "      <td>1.728551</td>\n",
+       "      <td>1.730629</td>\n",
+       "      <td>5.705998</td>\n",
+       "      <td>6.868699</td>\n",
+       "      <td>4958.407227</td>\n",
+       "      <td>19297.955078</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980</th>\n",
+       "      <td>2035</td>\n",
+       "      <td>1.727704</td>\n",
+       "      <td>1.729381</td>\n",
+       "      <td>5.702184</td>\n",
+       "      <td>6.864341</td>\n",
+       "      <td>4960.136719</td>\n",
+       "      <td>19304.818359</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1981</th>\n",
+       "      <td>2036</td>\n",
+       "      <td>1.727099</td>\n",
+       "      <td>1.727993</td>\n",
+       "      <td>5.699559</td>\n",
+       "      <td>6.859002</td>\n",
+       "      <td>4961.864746</td>\n",
+       "      <td>19311.677734</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1982</th>\n",
+       "      <td>2037</td>\n",
+       "      <td>2.962107</td>\n",
+       "      <td>2.082554</td>\n",
+       "      <td>10.841866</td>\n",
+       "      <td>8.391261</td>\n",
+       "      <td>4963.947266</td>\n",
+       "      <td>19320.068359</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1983 rows × 7 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      cycle_index  discharge_capacity  charge_capacity  discharge_energy  \\\n",
+       "0               0            4.739763         3.845542         17.344500   \n",
+       "1               6            3.801423         3.780793         13.262715   \n",
+       "2               7            3.796112         3.798094         13.241635   \n",
+       "3               8            3.791151         3.794633         13.218457   \n",
+       "4               9            3.788853         3.790908         13.206060   \n",
+       "...           ...                 ...              ...               ...   \n",
+       "1978         2033            1.730030         1.730979          5.712026   \n",
+       "1979         2034            1.728551         1.730629          5.705998   \n",
+       "1980         2035            1.727704         1.729381          5.702184   \n",
+       "1981         2036            1.727099         1.727993          5.699559   \n",
+       "1982         2037            2.962107         2.082554         10.841866   \n",
+       "\n",
+       "      charge_energy  charge_throughput  energy_throughput  \n",
+       "0         14.976089           3.845542          14.976089  \n",
+       "1         14.334126           7.626336          29.310215  \n",
+       "2         14.414895          11.424430          43.725109  \n",
+       "3         14.402270          15.219062          58.127380  \n",
+       "4         14.389844          19.009970          72.517227  \n",
+       "...             ...                ...                ...  \n",
+       "1978       6.869929        4956.676758       19291.085938  \n",
+       "1979       6.868699        4958.407227       19297.955078  \n",
+       "1980       6.864341        4960.136719       19304.818359  \n",
+       "1981       6.859002        4961.864746       19311.677734  \n",
+       "1982       8.391261        4963.947266       19320.068359  \n",
+       "\n",
+       "[1983 rows x 7 columns]"
+      ]
+     },
+     "execution_count": 123,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "summary_data[0].iloc[:-1]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "a64b3833",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "\n",
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+       "\n",
+       "    .dataframe thead th {\n",
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+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>cycle_index</th>\n",
+       "      <th>discharge_capacity</th>\n",
+       "      <th>charge_capacity</th>\n",
+       "      <th>discharge_energy</th>\n",
+       "      <th>charge_energy</th>\n",
+       "      <th>charge_throughput</th>\n",
+       "      <th>energy_throughput</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>4.741486</td>\n",
+       "      <td>3.852409</td>\n",
+       "      <td>17.353089</td>\n",
+       "      <td>15.000720</td>\n",
+       "      <td>3.852409</td>\n",
+       "      <td>15.000720</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>6</td>\n",
+       "      <td>2.642477</td>\n",
+       "      <td>4.523357</td>\n",
+       "      <td>9.959919</td>\n",
+       "      <td>17.299393</td>\n",
+       "      <td>8.375766</td>\n",
+       "      <td>32.300114</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>7</td>\n",
+       "      <td>2.634625</td>\n",
+       "      <td>2.651804</td>\n",
+       "      <td>9.932148</td>\n",
+       "      <td>10.605730</td>\n",
+       "      <td>11.027570</td>\n",
+       "      <td>42.905842</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>8</td>\n",
+       "      <td>2.627890</td>\n",
+       "      <td>2.638572</td>\n",
+       "      <td>9.907780</td>\n",
+       "      <td>10.554319</td>\n",
+       "      <td>13.666142</td>\n",
+       "      <td>53.460163</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>9</td>\n",
+       "      <td>2.624367</td>\n",
+       "      <td>2.630954</td>\n",
+       "      <td>9.895451</td>\n",
+       "      <td>10.525008</td>\n",
+       "      <td>16.297096</td>\n",
+       "      <td>63.985168</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1637</th>\n",
+       "      <td>1727</td>\n",
+       "      <td>1.922041</td>\n",
+       "      <td>1.923796</td>\n",
+       "      <td>7.130655</td>\n",
+       "      <td>7.741613</td>\n",
+       "      <td>3614.554443</td>\n",
+       "      <td>14492.559570</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1638</th>\n",
+       "      <td>1728</td>\n",
+       "      <td>1.919406</td>\n",
+       "      <td>1.921610</td>\n",
+       "      <td>7.119877</td>\n",
+       "      <td>7.732109</td>\n",
+       "      <td>3616.476074</td>\n",
+       "      <td>14500.291016</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1639</th>\n",
+       "      <td>1729</td>\n",
+       "      <td>1.916676</td>\n",
+       "      <td>1.920892</td>\n",
+       "      <td>7.109297</td>\n",
+       "      <td>7.728719</td>\n",
+       "      <td>3618.396973</td>\n",
+       "      <td>14508.019531</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1640</th>\n",
+       "      <td>1730</td>\n",
+       "      <td>1.918061</td>\n",
+       "      <td>1.920649</td>\n",
+       "      <td>7.115403</td>\n",
+       "      <td>7.728511</td>\n",
+       "      <td>3620.317627</td>\n",
+       "      <td>14515.748047</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1641</th>\n",
+       "      <td>1731</td>\n",
+       "      <td>1.915628</td>\n",
+       "      <td>1.919130</td>\n",
+       "      <td>7.105213</td>\n",
+       "      <td>7.722100</td>\n",
+       "      <td>3622.236816</td>\n",
+       "      <td>14523.470703</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1642 rows × 7 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      cycle_index  discharge_capacity  charge_capacity  discharge_energy  \\\n",
+       "0               0            4.741486         3.852409         17.353089   \n",
+       "1               6            2.642477         4.523357          9.959919   \n",
+       "2               7            2.634625         2.651804          9.932148   \n",
+       "3               8            2.627890         2.638572          9.907780   \n",
+       "4               9            2.624367         2.630954          9.895451   \n",
+       "...           ...                 ...              ...               ...   \n",
+       "1637         1727            1.922041         1.923796          7.130655   \n",
+       "1638         1728            1.919406         1.921610          7.119877   \n",
+       "1639         1729            1.916676         1.920892          7.109297   \n",
+       "1640         1730            1.918061         1.920649          7.115403   \n",
+       "1641         1731            1.915628         1.919130          7.105213   \n",
+       "\n",
+       "      charge_energy  charge_throughput  energy_throughput  \n",
+       "0         15.000720           3.852409          15.000720  \n",
+       "1         17.299393           8.375766          32.300114  \n",
+       "2         10.605730          11.027570          42.905842  \n",
+       "3         10.554319          13.666142          53.460163  \n",
+       "4         10.525008          16.297096          63.985168  \n",
+       "...             ...                ...                ...  \n",
+       "1637       7.741613        3614.554443       14492.559570  \n",
+       "1638       7.732109        3616.476074       14500.291016  \n",
+       "1639       7.728719        3618.396973       14508.019531  \n",
+       "1640       7.728511        3620.317627       14515.748047  \n",
+       "1641       7.722100        3622.236816       14523.470703  \n",
+       "\n",
+       "[1642 rows x 7 columns]"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "summary_data_list[4]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "id": "2d2a042a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>voltage</th>\n",
+       "      <th>current</th>\n",
+       "      <th>cycle_index</th>\n",
+       "      <th>discharge_capacity</th>\n",
+       "      <th>charge_capacity</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1642118</th>\n",
+       "      <td>2.700801</td>\n",
+       "      <td>-0.691463</td>\n",
+       "      <td>1732</td>\n",
+       "      <td>4.077430</td>\n",
+       "      <td>3.616768</td>\n",
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+       "    <tr>\n",
+       "      <th>1642119</th>\n",
+       "      <td>2.702502</td>\n",
+       "      <td>-0.691681</td>\n",
+       "      <td>1732</td>\n",
+       "      <td>4.076982</td>\n",
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+       "    <tr>\n",
+       "      <th>1642120</th>\n",
+       "      <td>2.704204</td>\n",
+       "      <td>-0.691593</td>\n",
+       "      <td>1732</td>\n",
+       "      <td>4.076527</td>\n",
+       "      <td>3.616768</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1642121</th>\n",
+       "      <td>2.705906</td>\n",
+       "      <td>-0.691656</td>\n",
+       "      <td>1732</td>\n",
+       "      <td>4.076084</td>\n",
+       "      <td>3.616768</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1642122</th>\n",
+       "      <td>2.707608</td>\n",
+       "      <td>-0.691632</td>\n",
+       "      <td>1732</td>\n",
+       "      <td>4.075636</td>\n",
+       "      <td>3.616768</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1642983</th>\n",
+       "      <td>4.172773</td>\n",
+       "      <td>-0.693400</td>\n",
+       "      <td>1732</td>\n",
+       "      <td>0.000024</td>\n",
+       "      <td>3.616768</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1642984</th>\n",
+       "      <td>4.174474</td>\n",
+       "      <td>-0.694370</td>\n",
+       "      <td>1732</td>\n",
+       "      <td>0.000018</td>\n",
+       "      <td>3.616768</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1642985</th>\n",
+       "      <td>4.176176</td>\n",
+       "      <td>-0.695341</td>\n",
+       "      <td>1732</td>\n",
+       "      <td>0.000012</td>\n",
+       "      <td>3.616768</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1642986</th>\n",
+       "      <td>4.177878</td>\n",
+       "      <td>-0.696311</td>\n",
+       "      <td>1732</td>\n",
+       "      <td>0.000007</td>\n",
+       "      <td>3.616768</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3285398</th>\n",
+       "      <td>4.137558</td>\n",
+       "      <td>-0.254747</td>\n",
+       "      <td>1732</td>\n",
+       "      <td>0.136241</td>\n",
+       "      <td>1.913986</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>870 rows × 5 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       "1642118  2.700801 -0.691463         1732            4.077430         3.616768\n",
+       "1642119  2.702502 -0.691681         1732            4.076982         3.616768\n",
+       "1642120  2.704204 -0.691593         1732            4.076527         3.616768\n",
+       "1642121  2.705906 -0.691656         1732            4.076084         3.616768\n",
+       "1642122  2.707608 -0.691632         1732            4.075636         3.616768\n",
+       "...           ...       ...          ...                 ...              ...\n",
+       "1642983  4.172773 -0.693400         1732            0.000024         3.616768\n",
+       "1642984  4.174474 -0.694370         1732            0.000018         3.616768\n",
+       "1642985  4.176176 -0.695341         1732            0.000012         3.616768\n",
+       "1642986  4.177878 -0.696311         1732            0.000007         3.616768\n",
+       "3285398  4.137558 -0.254747         1732            0.136241         1.913986\n",
+       "\n",
+       "[870 rows x 5 columns]"
+      ]
+     },
+     "execution_count": 40,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "structured_data_list[4][-1]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 99,
+   "id": "cfc08466",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>cycle_index</th>\n",
+       "      <th>discharge_capacity</th>\n",
+       "      <th>charge_capacity</th>\n",
+       "      <th>discharge_energy</th>\n",
+       "      <th>charge_energy</th>\n",
+       "      <th>charge_throughput</th>\n",
+       "      <th>energy_throughput</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>4.739763</td>\n",
+       "      <td>3.845542</td>\n",
+       "      <td>17.344500</td>\n",
+       "      <td>14.976089</td>\n",
+       "      <td>3.845542</td>\n",
+       "      <td>14.976089</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>6</td>\n",
+       "      <td>3.801423</td>\n",
+       "      <td>3.780793</td>\n",
+       "      <td>13.262715</td>\n",
+       "      <td>14.334126</td>\n",
+       "      <td>7.626336</td>\n",
+       "      <td>29.310215</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>7</td>\n",
+       "      <td>3.796112</td>\n",
+       "      <td>3.798094</td>\n",
+       "      <td>13.241635</td>\n",
+       "      <td>14.414895</td>\n",
+       "      <td>11.424430</td>\n",
+       "      <td>43.725109</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>8</td>\n",
+       "      <td>3.791151</td>\n",
+       "      <td>3.794633</td>\n",
+       "      <td>13.218457</td>\n",
+       "      <td>14.402270</td>\n",
+       "      <td>15.219062</td>\n",
+       "      <td>58.127380</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>9</td>\n",
+       "      <td>3.788853</td>\n",
+       "      <td>3.790908</td>\n",
+       "      <td>13.206060</td>\n",
+       "      <td>14.389844</td>\n",
+       "      <td>19.009970</td>\n",
+       "      <td>72.517227</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1978</th>\n",
+       "      <td>2033</td>\n",
+       "      <td>1.730030</td>\n",
+       "      <td>1.730979</td>\n",
+       "      <td>5.712026</td>\n",
+       "      <td>6.869929</td>\n",
+       "      <td>4956.676758</td>\n",
+       "      <td>19291.085938</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1979</th>\n",
+       "      <td>2034</td>\n",
+       "      <td>1.728551</td>\n",
+       "      <td>1.730629</td>\n",
+       "      <td>5.705998</td>\n",
+       "      <td>6.868699</td>\n",
+       "      <td>4958.407227</td>\n",
+       "      <td>19297.955078</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1980</th>\n",
+       "      <td>2035</td>\n",
+       "      <td>1.727704</td>\n",
+       "      <td>1.729381</td>\n",
+       "      <td>5.702184</td>\n",
+       "      <td>6.864341</td>\n",
+       "      <td>4960.136719</td>\n",
+       "      <td>19304.818359</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1981</th>\n",
+       "      <td>2036</td>\n",
+       "      <td>1.727099</td>\n",
+       "      <td>1.727993</td>\n",
+       "      <td>5.699559</td>\n",
+       "      <td>6.859002</td>\n",
+       "      <td>4961.864746</td>\n",
+       "      <td>19311.677734</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1982</th>\n",
+       "      <td>2037</td>\n",
+       "      <td>2.962107</td>\n",
+       "      <td>2.082554</td>\n",
+       "      <td>10.841866</td>\n",
+       "      <td>8.391261</td>\n",
+       "      <td>4963.947266</td>\n",
+       "      <td>19320.068359</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1983 rows × 7 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      cycle_index  discharge_capacity  charge_capacity  discharge_energy  \\\n",
+       "0               0            4.739763         3.845542         17.344500   \n",
+       "1               6            3.801423         3.780793         13.262715   \n",
+       "2               7            3.796112         3.798094         13.241635   \n",
+       "3               8            3.791151         3.794633         13.218457   \n",
+       "4               9            3.788853         3.790908         13.206060   \n",
+       "...           ...                 ...              ...               ...   \n",
+       "1978         2033            1.730030         1.730979          5.712026   \n",
+       "1979         2034            1.728551         1.730629          5.705998   \n",
+       "1980         2035            1.727704         1.729381          5.702184   \n",
+       "1981         2036            1.727099         1.727993          5.699559   \n",
+       "1982         2037            2.962107         2.082554         10.841866   \n",
+       "\n",
+       "      charge_energy  charge_throughput  energy_throughput  \n",
+       "0         14.976089           3.845542          14.976089  \n",
+       "1         14.334126           7.626336          29.310215  \n",
+       "2         14.414895          11.424430          43.725109  \n",
+       "3         14.402270          15.219062          58.127380  \n",
+       "4         14.389844          19.009970          72.517227  \n",
+       "...             ...                ...                ...  \n",
+       "1978       6.869929        4956.676758       19291.085938  \n",
+       "1979       6.868699        4958.407227       19297.955078  \n",
+       "1980       6.864341        4960.136719       19304.818359  \n",
+       "1981       6.859002        4961.864746       19311.677734  \n",
+       "1982       8.391261        4963.947266       19320.068359  \n",
+       "\n",
+       "[1983 rows x 7 columns]"
+      ]
+     },
+     "execution_count": 99,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 96,
+   "id": "11ea6a8c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>voltage</th>\n",
+       "      <th>current</th>\n",
+       "      <th>cycle_index</th>\n",
+       "      <th>discharge_capacity</th>\n",
+       "      <th>charge_capacity</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1982118</th>\n",
+       "      <td>2.700801</td>\n",
+       "      <td>-0.691584</td>\n",
+       "      <td>2037</td>\n",
+       "      <td>2.961932</td>\n",
+       "      <td>2.082554</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1982119</th>\n",
+       "      <td>2.702502</td>\n",
+       "      <td>-0.691751</td>\n",
+       "      <td>2037</td>\n",
+       "      <td>2.961543</td>\n",
+       "      <td>2.082554</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1982120</th>\n",
+       "      <td>2.704204</td>\n",
+       "      <td>-0.691762</td>\n",
+       "      <td>2037</td>\n",
+       "      <td>2.961133</td>\n",
+       "      <td>2.082554</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1982121</th>\n",
+       "      <td>2.705906</td>\n",
+       "      <td>-0.691809</td>\n",
+       "      <td>2037</td>\n",
+       "      <td>2.960702</td>\n",
+       "      <td>2.082554</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1982122</th>\n",
+       "      <td>2.707608</td>\n",
+       "      <td>-0.691681</td>\n",
+       "      <td>2037</td>\n",
+       "      <td>2.960321</td>\n",
+       "      <td>2.082554</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1982979</th>\n",
+       "      <td>4.165966</td>\n",
+       "      <td>-0.692822</td>\n",
+       "      <td>2037</td>\n",
+       "      <td>0.000025</td>\n",
+       "      <td>2.082554</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1982980</th>\n",
+       "      <td>4.167668</td>\n",
+       "      <td>-0.693266</td>\n",
+       "      <td>2037</td>\n",
+       "      <td>0.000020</td>\n",
+       "      <td>2.082554</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1982981</th>\n",
+       "      <td>4.169369</td>\n",
+       "      <td>-0.693710</td>\n",
+       "      <td>2037</td>\n",
+       "      <td>0.000015</td>\n",
+       "      <td>2.082554</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1982982</th>\n",
+       "      <td>4.171071</td>\n",
+       "      <td>-0.694154</td>\n",
+       "      <td>2037</td>\n",
+       "      <td>0.000010</td>\n",
+       "      <td>2.082554</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1982983</th>\n",
+       "      <td>4.172773</td>\n",
+       "      <td>-0.694598</td>\n",
+       "      <td>2037</td>\n",
+       "      <td>0.000005</td>\n",
+       "      <td>2.082554</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>866 rows × 5 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       "1982118  2.700801 -0.691584         2037            2.961932         2.082554\n",
+       "1982119  2.702502 -0.691751         2037            2.961543         2.082554\n",
+       "1982120  2.704204 -0.691762         2037            2.961133         2.082554\n",
+       "1982121  2.705906 -0.691809         2037            2.960702         2.082554\n",
+       "1982122  2.707608 -0.691681         2037            2.960321         2.082554\n",
+       "...           ...       ...          ...                 ...              ...\n",
+       "1982979  4.165966 -0.692822         2037            0.000025         2.082554\n",
+       "1982980  4.167668 -0.693266         2037            0.000020         2.082554\n",
+       "1982981  4.169369 -0.693710         2037            0.000015         2.082554\n",
+       "1982982  4.171071 -0.694154         2037            0.000010         2.082554\n",
+       "1982983  4.172773 -0.694598         2037            0.000005         2.082554\n",
+       "\n",
+       "[866 rows x 5 columns]"
+      ]
+     },
+     "execution_count": 96,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "new_structured_data[-1]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 88,
+   "id": "8bef14de",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
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+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>voltage</th>\n",
+       "      <th>current</th>\n",
+       "      <th>cycle_index</th>\n",
+       "      <th>discharge_capacity</th>\n",
+       "      <th>charge_capacity</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1982118</th>\n",
+       "      <td>2.700801</td>\n",
+       "      <td>-0.691584</td>\n",
+       "      <td>2037</td>\n",
+       "      <td>2.961932</td>\n",
+       "      <td>2.082554</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1982119</th>\n",
+       "      <td>2.702502</td>\n",
+       "      <td>-0.691751</td>\n",
+       "      <td>2037</td>\n",
+       "      <td>2.961543</td>\n",
+       "      <td>2.082554</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1982120</th>\n",
+       "      <td>2.704204</td>\n",
+       "      <td>-0.691762</td>\n",
+       "      <td>2037</td>\n",
+       "      <td>2.961133</td>\n",
+       "      <td>2.082554</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1982121</th>\n",
+       "      <td>2.705906</td>\n",
+       "      <td>-0.691809</td>\n",
+       "      <td>2037</td>\n",
+       "      <td>2.960702</td>\n",
+       "      <td>2.082554</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1982122</th>\n",
+       "      <td>2.707608</td>\n",
+       "      <td>-0.691681</td>\n",
+       "      <td>2037</td>\n",
+       "      <td>2.960321</td>\n",
+       "      <td>2.082554</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1982978</th>\n",
+       "      <td>4.164264</td>\n",
+       "      <td>-0.692378</td>\n",
+       "      <td>2037</td>\n",
+       "      <td>0.000030</td>\n",
+       "      <td>2.082554</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1982979</th>\n",
+       "      <td>4.165966</td>\n",
+       "      <td>-0.692822</td>\n",
+       "      <td>2037</td>\n",
+       "      <td>0.000025</td>\n",
+       "      <td>2.082554</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1982980</th>\n",
+       "      <td>4.167668</td>\n",
+       "      <td>-0.693266</td>\n",
+       "      <td>2037</td>\n",
+       "      <td>0.000020</td>\n",
+       "      <td>2.082554</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1982981</th>\n",
+       "      <td>4.169369</td>\n",
+       "      <td>-0.693710</td>\n",
+       "      <td>2037</td>\n",
+       "      <td>0.000015</td>\n",
+       "      <td>2.082554</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1982982</th>\n",
+       "      <td>4.171071</td>\n",
+       "      <td>-0.694154</td>\n",
+       "      <td>2037</td>\n",
+       "      <td>0.000010</td>\n",
+       "      <td>2.082554</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>865 rows × 5 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       "1982118  2.700801 -0.691584         2037            2.961932         2.082554\n",
+       "1982119  2.702502 -0.691751         2037            2.961543         2.082554\n",
+       "1982120  2.704204 -0.691762         2037            2.961133         2.082554\n",
+       "1982121  2.705906 -0.691809         2037            2.960702         2.082554\n",
+       "1982122  2.707608 -0.691681         2037            2.960321         2.082554\n",
+       "...           ...       ...          ...                 ...              ...\n",
+       "1982978  4.164264 -0.692378         2037            0.000030         2.082554\n",
+       "1982979  4.165966 -0.692822         2037            0.000025         2.082554\n",
+       "1982980  4.167668 -0.693266         2037            0.000020         2.082554\n",
+       "1982981  4.169369 -0.693710         2037            0.000015         2.082554\n",
+       "1982982  4.171071 -0.694154         2037            0.000010         2.082554\n",
+       "\n",
+       "[865 rows x 5 columns]"
+      ]
+     },
+     "execution_count": 88,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "new_structured_data[-1]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 91,
+   "id": "55f8339e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2043"
+      ]
+     },
+     "execution_count": 91,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(structured_data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 97,
+   "id": "b31c214e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>voltage</th>\n",
+       "      <th>current</th>\n",
+       "      <th>cycle_index</th>\n",
+       "      <th>discharge_capacity</th>\n",
+       "      <th>charge_capacity</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1982118</th>\n",
+       "      <td>2.700801</td>\n",
+       "      <td>-0.691584</td>\n",
+       "      <td>2037</td>\n",
+       "      <td>2.961932</td>\n",
+       "      <td>2.082554</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1982119</th>\n",
+       "      <td>2.702502</td>\n",
+       "      <td>-0.691751</td>\n",
+       "      <td>2037</td>\n",
+       "      <td>2.961543</td>\n",
+       "      <td>2.082554</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1982120</th>\n",
+       "      <td>2.704204</td>\n",
+       "      <td>-0.691762</td>\n",
+       "      <td>2037</td>\n",
+       "      <td>2.961133</td>\n",
+       "      <td>2.082554</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1982121</th>\n",
+       "      <td>2.705906</td>\n",
+       "      <td>-0.691809</td>\n",
+       "      <td>2037</td>\n",
+       "      <td>2.960702</td>\n",
+       "      <td>2.082554</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1982122</th>\n",
+       "      <td>2.707608</td>\n",
+       "      <td>-0.691681</td>\n",
+       "      <td>2037</td>\n",
+       "      <td>2.960321</td>\n",
+       "      <td>2.082554</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1982979</th>\n",
+       "      <td>4.165966</td>\n",
+       "      <td>-0.692822</td>\n",
+       "      <td>2037</td>\n",
+       "      <td>0.000025</td>\n",
+       "      <td>2.082554</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1982980</th>\n",
+       "      <td>4.167668</td>\n",
+       "      <td>-0.693266</td>\n",
+       "      <td>2037</td>\n",
+       "      <td>0.000020</td>\n",
+       "      <td>2.082554</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1982981</th>\n",
+       "      <td>4.169369</td>\n",
+       "      <td>-0.693710</td>\n",
+       "      <td>2037</td>\n",
+       "      <td>0.000015</td>\n",
+       "      <td>2.082554</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1982982</th>\n",
+       "      <td>4.171071</td>\n",
+       "      <td>-0.694154</td>\n",
+       "      <td>2037</td>\n",
+       "      <td>0.000010</td>\n",
+       "      <td>2.082554</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1982983</th>\n",
+       "      <td>4.172773</td>\n",
+       "      <td>-0.694598</td>\n",
+       "      <td>2037</td>\n",
+       "      <td>0.000005</td>\n",
+       "      <td>2.082554</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>866 rows × 5 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          voltage   current  cycle_index  discharge_capacity  charge_capacity\n",
+       "1982118  2.700801 -0.691584         2037            2.961932         2.082554\n",
+       "1982119  2.702502 -0.691751         2037            2.961543         2.082554\n",
+       "1982120  2.704204 -0.691762         2037            2.961133         2.082554\n",
+       "1982121  2.705906 -0.691809         2037            2.960702         2.082554\n",
+       "1982122  2.707608 -0.691681         2037            2.960321         2.082554\n",
+       "...           ...       ...          ...                 ...              ...\n",
+       "1982979  4.165966 -0.692822         2037            0.000025         2.082554\n",
+       "1982980  4.167668 -0.693266         2037            0.000020         2.082554\n",
+       "1982981  4.169369 -0.693710         2037            0.000015         2.082554\n",
+       "1982982  4.171071 -0.694154         2037            0.000010         2.082554\n",
+       "1982983  4.172773 -0.694598         2037            0.000005         2.082554\n",
+       "\n",
+       "[866 rows x 5 columns]"
+      ]
+     },
+     "execution_count": 97,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "new_structured_data = []\n",
+    "for i,s in enumerate(structured_data):\n",
+    "    if s.shape[0] != 0:\n",
+    "        new_structured_data.append(s)\n",
+    "        summary_data[i].iloc[:-1]\n",
+    "#     print(s.shape)\n",
+    "new_structured_data[-1]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "5b3640a9",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "AttributeError",
+     "evalue": "'str' object has no attribute 'shape'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
+      "Input \u001b[0;32mIn [22]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i,m \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(dat[\u001b[38;5;241m1\u001b[39m][\u001b[38;5;241m0\u001b[39m]):\n\u001b[1;32m      2\u001b[0m \u001b[38;5;66;03m#     if m.shape\u001b[39;00m\n\u001b[1;32m      3\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(m) \u001b[38;5;241m!=\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[0;32m----> 4\u001b[0m         \u001b[38;5;28mprint\u001b[39m(\u001b[43mm\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mshape\u001b[49m)\n",
+      "\u001b[0;31mAttributeError\u001b[0m: 'str' object has no attribute 'shape'"
+     ]
+    }
+   ],
+   "source": [
+    "for i,m in enumerate(dat[1][0]):\n",
+    "#     if m.shape\n",
+    "    if len(m) != 0:\n",
+    "        print(m.shape)\n",
+    "#         break"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "cf44660a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import random\n",
+    "random.seed(0)\n",
+    "indices = list(range(len(dat)))\n",
+    "random.shuffle(indices)\n",
+    "train_size = 0.9\n",
+    "val_size = 0.09\n",
+    "N_train = int(train_size *len(dat))\n",
+    "N_val = int(val_size *len(dat))\n",
+    "train_dat = dat[:N_train]\n",
+    "# train_indices = random.sample(range(len(dat)), N_train)\n",
+    "test_dat = dat[N_train:]\n",
+    "val_dat = test_dat[:N_val]\n",
+    "test_dat = test_dat[N_val:]\n",
+    "\n",
+    "# val_indices = random.sample(list(range(len(dat))).pop(train_indices), N_val)\n",
+    "# N_test = len(dat) - N_train - N_val"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "5273d6db",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "add_txt = 'hi There'\n",
+    "with open('CACHED_DATA/pre_processed_pandas/notes.txt', 'r+') as f:\n",
+    "    for line in f:\n",
+    "#         loglist = f.readlines()\n",
+    "#         print(line)\n",
+    "#         print(loglist)\n",
+    "        if add_txt not in line : \n",
+    "            f.write(add_txt)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "fcb33bf0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# data_prep\n",
+    "def prep_ml_data(dat, cycle_numbers=20):\n",
+    "    features = np.empty([0, cycle_numbers,100, 3])\n",
+    "    labels = np.empty([0, cycle_numbers])\n",
+    "    print('Generating features and labels. Skipping cells with cycles lower than 50.')\n",
+    "    for j,d in enumerate(tqdm(dat)):\n",
+    "        if not len(d) < 50:\n",
+    "            n = d.shape[0]//cycle_numbers\n",
+    "            cell_features = []\n",
+    "            cell_labels = []\n",
+    "            for i in range(n-1):\n",
+    "                cell_features.append(d[cycle_numbers*i:cycle_numbers*(i+1), :, :3])\n",
+    "                cell_labels.append(d[cycle_numbers*(i+1):cycle_numbers*(i+2), 0, -1])\n",
+    "#             print(np.array(cell_features).shape, j)\n",
+    "            features = np.append(features, np.array(cell_features), axis=0)\n",
+    "            labels = np.append(labels, np.array(cell_labels), axis=0)\n",
+    "        else:\n",
+    "            print(f'Cell {j} has only {len(d)} cycles. Skipping!')\n",
+    "    return features, labels"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "2785604c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Generating features and labels. Skipping cells with cycles lower than 50.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "  5%|▍         | 16/339 [00:00<00:02, 159.16it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Cell 8 has only 2 cycles. Skipping!\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 12%|█▏        | 42/339 [00:00<00:07, 40.92it/s] "
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Cell 41 has only 2 cycles. Skipping!\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 39%|███▉      | 133/339 [00:11<00:28,  7.29it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Cell 131 has only 48 cycles. Skipping!\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 56%|█████▋    | 191/339 [00:24<00:39,  3.77it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Cell 191 has only 2 cycles. Skipping!\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████| 339/339 [01:19<00:00,  4.29it/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "train_features, train_labels = prep_ml_data(train_dat)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "234fef64",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(1431, 100, 4)"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dat[0].shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "680a4604",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from beep.structure.cli import auto_load_processed\n",
+    "cell = auto_load_processed('/home/ec2-user/SageMaker/data_cache/structure/PreDiag_000206_000057_structured.json.gz')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "46e1a5de",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>cycle_index</th>\n",
+       "      <th>discharge_capacity</th>\n",
+       "      <th>charge_capacity</th>\n",
+       "      <th>discharge_energy</th>\n",
+       "      <th>charge_energy</th>\n",
+       "      <th>dc_internal_resistance</th>\n",
+       "      <th>temperature_maximum</th>\n",
+       "      <th>temperature_average</th>\n",
+       "      <th>temperature_minimum</th>\n",
+       "      <th>date_time_iso</th>\n",
+       "      <th>energy_efficiency</th>\n",
+       "      <th>charge_throughput</th>\n",
+       "      <th>energy_throughput</th>\n",
+       "      <th>charge_duration</th>\n",
+       "      <th>time_temperature_integrated</th>\n",
+       "      <th>paused</th>\n",
+       "      <th>CV_time</th>\n",
+       "      <th>CV_current</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>4.773268</td>\n",
+       "      <td>3.870386</td>\n",
+       "      <td>17.471176</td>\n",
+       "      <td>15.071790</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2019-12-14T00:58:35+00:00</td>\n",
+       "      <td>1.159197</td>\n",
+       "      <td>3.870386</td>\n",
+       "      <td>15.071790</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>62318</td>\n",
+       "      <td>2084.219971</td>\n",
+       "      <td>0.138476</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>6</td>\n",
+       "      <td>0.000163</td>\n",
+       "      <td>1.751873</td>\n",
+       "      <td>0.000559</td>\n",
+       "      <td>6.227764</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2019-12-17T13:54:56+00:00</td>\n",
+       "      <td>0.000090</td>\n",
+       "      <td>5.622260</td>\n",
+       "      <td>21.299555</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1799.969971</td>\n",
+       "      <td>0.124514</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>7</td>\n",
+       "      <td>0.000122</td>\n",
+       "      <td>0.034658</td>\n",
+       "      <td>0.000421</td>\n",
+       "      <td>0.128238</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2019-12-17T16:21:32+00:00</td>\n",
+       "      <td>0.003282</td>\n",
+       "      <td>5.656918</td>\n",
+       "      <td>21.427792</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1799.979980</td>\n",
+       "      <td>0.028153</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>8</td>\n",
+       "      <td>0.000163</td>\n",
+       "      <td>0.011033</td>\n",
+       "      <td>0.000560</td>\n",
+       "      <td>0.040823</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2019-12-17T17:11:33+00:00</td>\n",
+       "      <td>0.013708</td>\n",
+       "      <td>5.667951</td>\n",
+       "      <td>21.468615</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1799.979980</td>\n",
+       "      <td>0.011215</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>9</td>\n",
+       "      <td>0.000163</td>\n",
+       "      <td>0.005046</td>\n",
+       "      <td>0.000559</td>\n",
+       "      <td>0.018673</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2019-12-17T18:01:34+00:00</td>\n",
+       "      <td>0.029962</td>\n",
+       "      <td>5.672997</td>\n",
+       "      <td>21.487288</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1799.969971</td>\n",
+       "      <td>0.007324</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4437</th>\n",
+       "      <td>4667</td>\n",
+       "      <td>0.000163</td>\n",
+       "      <td>0.001382</td>\n",
+       "      <td>0.000558</td>\n",
+       "      <td>0.005115</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2020-09-02T13:28:15+00:00</td>\n",
+       "      <td>0.109117</td>\n",
+       "      <td>80.722565</td>\n",
+       "      <td>288.610504</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>659.969971</td>\n",
+       "      <td>0.001602</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4438</th>\n",
+       "      <td>4668</td>\n",
+       "      <td>0.000163</td>\n",
+       "      <td>0.001001</td>\n",
+       "      <td>0.000558</td>\n",
+       "      <td>0.003704</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2020-09-02T14:18:16+00:00</td>\n",
+       "      <td>0.150690</td>\n",
+       "      <td>80.723572</td>\n",
+       "      <td>288.614197</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>810.000000</td>\n",
+       "      <td>0.001831</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4439</th>\n",
+       "      <td>4669</td>\n",
+       "      <td>0.000122</td>\n",
+       "      <td>0.000846</td>\n",
+       "      <td>0.000420</td>\n",
+       "      <td>0.003132</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2020-09-02T15:08:17+00:00</td>\n",
+       "      <td>0.134067</td>\n",
+       "      <td>80.724411</td>\n",
+       "      <td>288.617340</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1499.969971</td>\n",
+       "      <td>0.002289</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4440</th>\n",
+       "      <td>4670</td>\n",
+       "      <td>0.000122</td>\n",
+       "      <td>0.000738</td>\n",
+       "      <td>0.000420</td>\n",
+       "      <td>0.002732</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2020-09-02T15:58:18+00:00</td>\n",
+       "      <td>0.153696</td>\n",
+       "      <td>80.725151</td>\n",
+       "      <td>288.620056</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1560.000000</td>\n",
+       "      <td>0.000458</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4441</th>\n",
+       "      <td>4671</td>\n",
+       "      <td>4.274622</td>\n",
+       "      <td>2.573219</td>\n",
+       "      <td>15.777023</td>\n",
+       "      <td>10.290895</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2020-09-02T16:48:20+00:00</td>\n",
+       "      <td>1.533105</td>\n",
+       "      <td>83.298370</td>\n",
+       "      <td>298.910950</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0</td>\n",
+       "      <td>17580.750000</td>\n",
+       "      <td>0.138476</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>4442 rows × 18 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      cycle_index  discharge_capacity  charge_capacity  discharge_energy  \\\n",
+       "0               0            4.773268         3.870386         17.471176   \n",
+       "1               6            0.000163         1.751873          0.000559   \n",
+       "2               7            0.000122         0.034658          0.000421   \n",
+       "3               8            0.000163         0.011033          0.000560   \n",
+       "4               9            0.000163         0.005046          0.000559   \n",
+       "...           ...                 ...              ...               ...   \n",
+       "4437         4667            0.000163         0.001382          0.000558   \n",
+       "4438         4668            0.000163         0.001001          0.000558   \n",
+       "4439         4669            0.000122         0.000846          0.000420   \n",
+       "4440         4670            0.000122         0.000738          0.000420   \n",
+       "4441         4671            4.274622         2.573219         15.777023   \n",
+       "\n",
+       "      charge_energy  dc_internal_resistance  temperature_maximum  \\\n",
+       "0         15.071790                     0.0                  NaN   \n",
+       "1          6.227764                     0.0                  NaN   \n",
+       "2          0.128238                     0.0                  NaN   \n",
+       "3          0.040823                     0.0                  NaN   \n",
+       "4          0.018673                     0.0                  NaN   \n",
+       "...             ...                     ...                  ...   \n",
+       "4437       0.005115                     0.0                  NaN   \n",
+       "4438       0.003704                     0.0                  NaN   \n",
+       "4439       0.003132                     0.0                  NaN   \n",
+       "4440       0.002732                     0.0                  NaN   \n",
+       "4441      10.290895                     0.0                  NaN   \n",
+       "\n",
+       "      temperature_average  temperature_minimum              date_time_iso  \\\n",
+       "0                     NaN                  NaN  2019-12-14T00:58:35+00:00   \n",
+       "1                     NaN                  NaN  2019-12-17T13:54:56+00:00   \n",
+       "2                     NaN                  NaN  2019-12-17T16:21:32+00:00   \n",
+       "3                     NaN                  NaN  2019-12-17T17:11:33+00:00   \n",
+       "4                     NaN                  NaN  2019-12-17T18:01:34+00:00   \n",
+       "...                   ...                  ...                        ...   \n",
+       "4437                  NaN                  NaN  2020-09-02T13:28:15+00:00   \n",
+       "4438                  NaN                  NaN  2020-09-02T14:18:16+00:00   \n",
+       "4439                  NaN                  NaN  2020-09-02T15:08:17+00:00   \n",
+       "4440                  NaN                  NaN  2020-09-02T15:58:18+00:00   \n",
+       "4441                  NaN                  NaN  2020-09-02T16:48:20+00:00   \n",
+       "\n",
+       "      energy_efficiency  charge_throughput  energy_throughput  \\\n",
+       "0              1.159197           3.870386          15.071790   \n",
+       "1              0.000090           5.622260          21.299555   \n",
+       "2              0.003282           5.656918          21.427792   \n",
+       "3              0.013708           5.667951          21.468615   \n",
+       "4              0.029962           5.672997          21.487288   \n",
+       "...                 ...                ...                ...   \n",
+       "4437           0.109117          80.722565         288.610504   \n",
+       "4438           0.150690          80.723572         288.614197   \n",
+       "4439           0.134067          80.724411         288.617340   \n",
+       "4440           0.153696          80.725151         288.620056   \n",
+       "4441           1.533105          83.298370         298.910950   \n",
+       "\n",
+       "      charge_duration  time_temperature_integrated  paused       CV_time  \\\n",
+       "0                 NaN                          NaN   62318   2084.219971   \n",
+       "1                 NaN                          NaN       0   1799.969971   \n",
+       "2                 NaN                          NaN       0   1799.979980   \n",
+       "3                 NaN                          NaN       0   1799.979980   \n",
+       "4                 NaN                          NaN       0   1799.969971   \n",
+       "...               ...                          ...     ...           ...   \n",
+       "4437              NaN                          NaN       0    659.969971   \n",
+       "4438              NaN                          NaN       0    810.000000   \n",
+       "4439              NaN                          NaN       0   1499.969971   \n",
+       "4440              NaN                          NaN       0   1560.000000   \n",
+       "4441              NaN                          NaN       0  17580.750000   \n",
+       "\n",
+       "      CV_current  \n",
+       "0       0.138476  \n",
+       "1       0.124514  \n",
+       "2       0.028153  \n",
+       "3       0.011215  \n",
+       "4       0.007324  \n",
+       "...          ...  \n",
+       "4437    0.001602  \n",
+       "4438    0.001831  \n",
+       "4439    0.002289  \n",
+       "4440    0.000458  \n",
+       "4441    0.138476  \n",
+       "\n",
+       "[4442 rows x 18 columns]"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cell.structured_summary"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "c2c7f684",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "line_exists\n"
+     ]
+    }
+   ],
+   "source": [
+    "add_txt = 'PreDiag_000255_000214_structured'\n",
+    "with open('CACHED_DATA/pre_processed_pandas/notes.txt', 'r+') as f:\n",
+    "    if add_txt in f.read():\n",
+    "        print('line_exists')\n",
+    "    else:\n",
+    "        print('Run')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "83cfdc0b",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "NameError",
+     "evalue": "name 'os' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "Input \u001b[0;32mIn [10]\u001b[0m, in \u001b[0;36m<cell line: 3>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m structure_path \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m/home/ec2-user/SageMaker/data_cache/structure/\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m      2\u001b[0m \u001b[38;5;66;03m#Get all structured files with the correct prefix\u001b[39;00m\n\u001b[0;32m----> 3\u001b[0m names \u001b[38;5;241m=\u001b[39m [os\u001b[38;5;241m.\u001b[39mpath\u001b[38;5;241m.\u001b[39mjoin(structure_path, n) \u001b[38;5;28;01mfor\u001b[39;00m n \u001b[38;5;129;01min\u001b[39;00m \u001b[43mos\u001b[49m\u001b[38;5;241m.\u001b[39mlistdir(structure_path) \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mPreDiag\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01min\u001b[39;00m n \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mPredictionDiagnostics\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01min\u001b[39;00m n]\n\u001b[1;32m      4\u001b[0m \u001b[38;5;66;03m#exclude stitched files\u001b[39;00m\n\u001b[1;32m      5\u001b[0m names \u001b[38;5;241m=\u001b[39m [n \u001b[38;5;28;01mfor\u001b[39;00m n \u001b[38;5;129;01min\u001b[39;00m names \u001b[38;5;28;01mif\u001b[39;00m (\u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mp2_structure\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01min\u001b[39;00m n \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m.gz\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01min\u001b[39;00m n)]\n",
+      "\u001b[0;31mNameError\u001b[0m: name 'os' is not defined"
+     ]
+    }
+   ],
+   "source": [
+    "structure_path = '/home/ec2-user/SageMaker/data_cache/structure/'\n",
+    "#Get all structured files with the correct prefix\n",
+    "names = [os.path.join(structure_path, n) for n in os.listdir(structure_path) if \"PreDiag\" in n or \"PredictionDiagnostics\" in n]\n",
+    "#exclude stitched files\n",
+    "names = [n for n in names if (not \"p2_structure\" in n and \".gz\" in n)]\n",
+    "from beep.structure.cli import auto_load_processed\n",
+    "cell = auto_load_processed(names[275])\n",
+    "clean_cell = bye_cycle.clean_cycle_data(cell, 0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "id": "e0d07793",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>data_point</th>\n",
+       "      <th>cycle_index</th>\n",
+       "      <th>step_index</th>\n",
+       "      <th>test_time</th>\n",
+       "      <th>step_time</th>\n",
+       "      <th>_capacity</th>\n",
+       "      <th>_energy</th>\n",
+       "      <th>current</th>\n",
+       "      <th>voltage</th>\n",
+       "      <th>_state</th>\n",
+       "      <th>...</th>\n",
+       "      <th>_var13</th>\n",
+       "      <th>_var14</th>\n",
+       "      <th>_var15</th>\n",
+       "      <th>charge_capacity</th>\n",
+       "      <th>discharge_capacity</th>\n",
+       "      <th>charge_energy</th>\n",
+       "      <th>discharge_energy</th>\n",
+       "      <th>date_time_iso</th>\n",
+       "      <th>temperature</th>\n",
+       "      <th>time_since_cycle_start</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>4.146105</td>\n",
+       "      <td>R</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2020-12-19T20:18:43+00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>30.0</td>\n",
+       "      <td>30.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>4.146182</td>\n",
+       "      <td>R</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2020-12-19T20:19:16+00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>60.0</td>\n",
+       "      <td>60.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>4.145953</td>\n",
+       "      <td>R</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2020-12-19T20:19:43+00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>4</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>90.0</td>\n",
+       "      <td>90.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>4.145800</td>\n",
+       "      <td>R</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2020-12-19T20:20:13+00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1.50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>5</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>120.0</td>\n",
+       "      <td>120.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>4.145800</td>\n",
+       "      <td>R</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2020-12-19T20:20:43+00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>6</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>150.0</td>\n",
+       "      <td>150.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>4.145724</td>\n",
+       "      <td>R</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2020-12-19T20:21:13+00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>2.50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>7</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>180.0</td>\n",
+       "      <td>180.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>4.145800</td>\n",
+       "      <td>R</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2020-12-19T20:21:43+00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>8</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>210.0</td>\n",
+       "      <td>210.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>4.145648</td>\n",
+       "      <td>R</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2020-12-19T20:22:13+00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>3.50</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>9</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>240.0</td>\n",
+       "      <td>240.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>4.145648</td>\n",
+       "      <td>R</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2020-12-19T20:22:43+00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>4.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>10</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>270.0</td>\n",
+       "      <td>270.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>4.145724</td>\n",
+       "      <td>R</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>2020-12-19T20:23:13+00:00</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>4.50</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>10 rows × 45 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   data_point  cycle_index  step_index  test_time  step_time  _capacity  \\\n",
+       "0           1            0           1        0.0        0.0        0.0   \n",
+       "1           2            0           1       30.0       30.0        0.0   \n",
+       "2           3            0           1       60.0       60.0        0.0   \n",
+       "3           4            0           1       90.0       90.0        0.0   \n",
+       "4           5            0           1      120.0      120.0        0.0   \n",
+       "5           6            0           1      150.0      150.0        0.0   \n",
+       "6           7            0           1      180.0      180.0        0.0   \n",
+       "7           8            0           1      210.0      210.0        0.0   \n",
+       "8           9            0           1      240.0      240.0        0.0   \n",
+       "9          10            0           1      270.0      270.0        0.0   \n",
+       "\n",
+       "   _energy  current   voltage _state  ...  _var13 _var14  _var15  \\\n",
+       "0      0.0      0.0  4.146105      R  ...     0.0    0.0     0.0   \n",
+       "1      0.0      0.0  4.146182      R  ...     0.0    0.0     0.0   \n",
+       "2      0.0      0.0  4.145953      R  ...     0.0    0.0     0.0   \n",
+       "3      0.0      0.0  4.145800      R  ...     0.0    0.0     0.0   \n",
+       "4      0.0      0.0  4.145800      R  ...     0.0    0.0     0.0   \n",
+       "5      0.0      0.0  4.145724      R  ...     0.0    0.0     0.0   \n",
+       "6      0.0      0.0  4.145800      R  ...     0.0    0.0     0.0   \n",
+       "7      0.0      0.0  4.145648      R  ...     0.0    0.0     0.0   \n",
+       "8      0.0      0.0  4.145648      R  ...     0.0    0.0     0.0   \n",
+       "9      0.0      0.0  4.145724      R  ...     0.0    0.0     0.0   \n",
+       "\n",
+       "   charge_capacity  discharge_capacity  charge_energy  discharge_energy  \\\n",
+       "0              0.0                 0.0            0.0               0.0   \n",
+       "1              0.0                 0.0            0.0               0.0   \n",
+       "2              0.0                 0.0            0.0               0.0   \n",
+       "3              0.0                 0.0            0.0               0.0   \n",
+       "4              0.0                 0.0            0.0               0.0   \n",
+       "5              0.0                 0.0            0.0               0.0   \n",
+       "6              0.0                 0.0            0.0               0.0   \n",
+       "7              0.0                 0.0            0.0               0.0   \n",
+       "8              0.0                 0.0            0.0               0.0   \n",
+       "9              0.0                 0.0            0.0               0.0   \n",
+       "\n",
+       "               date_time_iso  temperature  time_since_cycle_start  \n",
+       "0  2020-12-19T20:18:43+00:00          NaN                    0.00  \n",
+       "1  2020-12-19T20:19:16+00:00          NaN                    0.55  \n",
+       "2  2020-12-19T20:19:43+00:00          NaN                    1.00  \n",
+       "3  2020-12-19T20:20:13+00:00          NaN                    1.50  \n",
+       "4  2020-12-19T20:20:43+00:00          NaN                    2.00  \n",
+       "5  2020-12-19T20:21:13+00:00          NaN                    2.50  \n",
+       "6  2020-12-19T20:21:43+00:00          NaN                    3.00  \n",
+       "7  2020-12-19T20:22:13+00:00          NaN                    3.50  \n",
+       "8  2020-12-19T20:22:43+00:00          NaN                    4.00  \n",
+       "9  2020-12-19T20:23:13+00:00          NaN                    4.50  \n",
+       "\n",
+       "[10 rows x 45 columns]"
+      ]
+     },
+     "execution_count": 41,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cell.raw_data.head(10)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "id": "74b01f33",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7fcf68212f70>]"
+      ]
+     },
+     "execution_count": 53,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.plot(cell.raw_data.head(5000)['voltage'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "id": "36de4299",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0             0\n",
+       "1             0\n",
+       "2             0\n",
+       "3             0\n",
+       "4             0\n",
+       "           ... \n",
+       "2863995    1513\n",
+       "2863996    1513\n",
+       "2863997    1513\n",
+       "2863998    1513\n",
+       "2863999    1513\n",
+       "Name: cycle_index, Length: 2864000, dtype: int32"
+      ]
+     },
+     "execution_count": 62,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cell.structured_data['cycle_index']\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "id": "3f7679fc",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cycle_index = []\n",
+    "time_c =[]\n",
+    "for i,c in enumerate(cell.structured_data['cycle_index']):\n",
+    "    if c not in cycle_index:\n",
+    "        cycle_index.append(c)\n",
+    "        time_c.append(i)\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 77,
+   "id": "1a64f1f3",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       " ...]"
+      ]
+     },
+     "execution_count": 77,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "time_c"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 83,
+   "id": "851693d9",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 0, 'Time')"
+      ]
+     },
+     "execution_count": 83,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.plot(cell.structured_data.head(10000)['voltage'])\n",
+    "for t in time_c:\n",
+    "    plt.axvline(t, linestyle='--',color='C3', alpha=0.8)\n",
+    "    if t > 10000:\n",
+    "        break\n",
+    "plt.ylabel('Voltage')\n",
+    "plt.xlabel('Time')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 87,
+   "id": "cb1aef30",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2862001    3.465450\n",
+       "2862002    3.479265\n",
+       "2862003    3.489516\n",
+       "2862004    3.498118\n",
+       "2862005    3.505805\n",
+       "             ...   \n",
+       "2863073    3.782738\n",
+       "2863074    3.785545\n",
+       "2863075    3.788277\n",
+       "2863076    3.791022\n",
+       "2863077    3.793859\n",
+       "Name: voltage, Length: 353, dtype: float32"
+      ]
+     },
+     "execution_count": 87,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cell.structured_data.iloc[-2000:]['voltage'].dropna()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 98,
+   "id": "1126da04",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(1500000.0, 1510000.0)"
+      ]
+     },
+     "execution_count": 98,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.plot(cell.structured_data['voltage'].dropna())\n",
+    "plt.xlim([1.5e6,1.51e6])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 88,
+   "id": "89adf122",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 0, 'Time')"
+      ]
+     },
+     "execution_count": 88,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.plot(cell.structured_data.iloc[-2000:]['voltage'].dropna())\n",
+    "# for t in time_c:\n",
+    "#     if t > t[-2000]:\n",
+    "#         plt.axvline(t, linestyle='--',color='C3', alpha=0.8)\n",
+    "#         break\n",
+    "plt.ylabel('Voltage')\n",
+    "plt.xlabel('Time')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 109,
+   "id": "993491cc",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<beep.structure.maccor.MaccorDatapath at 0x7fc86d154e20>"
+      ]
+     },
+     "execution_count": 109,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cell"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 113,
+   "id": "c2a73440",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7fcf5bcc6640>]"
+      ]
+     },
+     "execution_count": 113,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "max_cycle_index = max(cell.structured_data['cycle_index'])\n",
+    "clean_cell = bye_cycle.clean_cycle_data(cell, max_cycle_index)\n",
+    "plt.plot(clean_cell['voltage'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "id": "6b750fa0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7fcf67f521c0>]"
+      ]
+     },
+     "execution_count": 64,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.plot(cell.structured_data.iloc[4000:5000]['voltage'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "id": "6bc1c3c4",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "for i in range(10):\n",
+    "    clean_cell = bye_cycle.clean_cycle_data(cell, 1500)\n",
+    "    plt.plot(clean_cell['voltage'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 100,
+   "id": "9680794d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(23103, 20, 100, 3)"
+      ]
+     },
+     "execution_count": 100,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_features.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 104,
+   "id": "f8e89fc5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7fcf5bb92d90>]"
+      ]
+     },
+     "execution_count": 104,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "d = train_features[0]\n",
+    "plt.plot(d[0,:,0], label='interpol')\n",
+    "plt.plot(clean_cell['voltage'], label='raw dat')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "c0f19fec",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Generating features and labels. Skipping cells with cycles lower than 50.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████| 33/33 [00:00<00:00, 52.75it/s] \n"
+     ]
+    }
+   ],
+   "source": [
+    "val_features, val_labels = prep_ml_data(val_dat)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "53e92eea",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Generating features and labels. Skipping cells with cycles lower than 50.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████| 5/5 [00:00<00:00, 139.60it/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "test_features, test_labels = prep_ml_data(test_dat)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "4a7b535a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def standardize(inputs):\n",
+    "    fstd = np.std(inputs, axis=0)\n",
+    "    fmean = np.mean(inputs, axis=0)\n",
+    "    std_features = (inputs - fmean) / fstd\n",
+    "    return std_features\n",
+    "std_train_features = standardize(train_features)\n",
+    "std_test_features = standardize(test_features)\n",
+    "std_val_features = standardize(val_features)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "865e9506",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from dataclasses import dataclass\n",
+    "@dataclass\n",
+    "class Config:\n",
+    "    vocab_size: int\n",
+    "    example_number: int\n",
+    "    batch_size: int\n",
+    "    buffer_size: int\n",
+    "    rnn_units: int\n",
+    "    hidden_dim: int\n",
+    "    embedding_dim: int\n",
+    "    reg_strength: float\n",
+    "    lr: float\n",
+    "    drop_rate: float\n",
+    "        \n",
+    "config = Config(vocab_size=21, # include gap\n",
+    "                example_number=len(train_labels), \n",
+    "                batch_size=512, \n",
+    "                buffer_size=10000,\n",
+    "                rnn_units=64,\n",
+    "                hidden_dim=64,\n",
+    "                embedding_dim=32,\n",
+    "                reg_strength=0,\n",
+    "                lr=1e-3,\n",
+    "                drop_rate=0.1\n",
+    "               )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "1b66b129",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2022-06-22 15:06:48.478875: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:48.480503: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:48.482104: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:48.483631: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:48.485203: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:48.486718: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:48.488239: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:48.489784: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:48.496899: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:48.498491: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:48.500028: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:48.501599: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:48.503121: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:48.504654: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:48.506237: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:48.507761: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:48.509313: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:48.510831: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:48.512356: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:48.513904: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:48.515422: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:48.516963: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:48.518481: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:48.519996: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:48.522413: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA\n",
+      "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
+      "2022-06-22 15:06:49.148875: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:49.150488: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:49.152055: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:49.153649: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:49.155201: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:49.156775: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:49.158333: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:49.159884: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:49.161455: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:49.162981: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:49.164508: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:49.166072: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:49.167588: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:49.169154: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:49.170691: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:49.172256: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:49.173824: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:49.175379: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:49.176963: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:49.178502: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:49.180037: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:49.181629: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:49.183197: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:49.184786: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:53.315547: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:53.317278: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:53.318918: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:53.320533: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:53.322168: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:53.323779: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:53.325415: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:53.327017: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:53.328565: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:53.330148: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:53.331708: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:53.333284: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:53.334830: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:53.336375: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:53.337962: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:53.339509: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:53.341091: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:53.342636: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 10645 MB memory:  -> device: 0, name: Tesla K80, pci bus id: 0000:00:17.0, compute capability: 3.7\n",
+      "2022-06-22 15:06:53.343451: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:53.344995: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:1 with 10645 MB memory:  -> device: 1, name: Tesla K80, pci bus id: 0000:00:18.0, compute capability: 3.7\n",
+      "2022-06-22 15:06:53.345688: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:53.347205: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:2 with 10645 MB memory:  -> device: 2, name: Tesla K80, pci bus id: 0000:00:19.0, compute capability: 3.7\n",
+      "2022-06-22 15:06:53.347898: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:53.349451: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:3 with 10645 MB memory:  -> device: 3, name: Tesla K80, pci bus id: 0000:00:1a.0, compute capability: 3.7\n",
+      "2022-06-22 15:06:53.350159: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:53.351679: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:4 with 10645 MB memory:  -> device: 4, name: Tesla K80, pci bus id: 0000:00:1b.0, compute capability: 3.7\n",
+      "2022-06-22 15:06:53.352369: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:53.353921: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:5 with 10645 MB memory:  -> device: 5, name: Tesla K80, pci bus id: 0000:00:1c.0, compute capability: 3.7\n",
+      "2022-06-22 15:06:53.354676: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:53.356188: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:6 with 10645 MB memory:  -> device: 6, name: Tesla K80, pci bus id: 0000:00:1d.0, compute capability: 3.7\n",
+      "2022-06-22 15:06:53.356893: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:975] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
+      "2022-06-22 15:06:53.358406: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1532] Created device /job:localhost/replica:0/task:0/device:GPU:7 with 10645 MB memory:  -> device: 7, name: Tesla K80, pci bus id: 0000:00:1e.0, compute capability: 3.7\n"
+     ]
+    }
+   ],
+   "source": [
+    "# [:,:,:2]\n",
+    "np.random.seed(0)\n",
+    "i = np.arange(len(train_features))\n",
+    "np.random.shuffle(i)\n",
+    "train_data = tf.data.Dataset.from_tensor_slices((std_train_features[i], train_labels[i])).batch(config.batch_size)\n",
+    "i = np.arange(len(val_features))\n",
+    "val_data = tf.data.Dataset.from_tensor_slices((std_val_features[i], val_labels[i])).batch(config.batch_size)\n",
+    "i = np.arange(len(test_features))\n",
+    "test_data = tf.data.Dataset.from_tensor_slices((std_test_features[i], test_labels[i])).batch(config.batch_size)\n",
+    "N = len(dat)\n",
+    "C = std_train_features.shape[1]\n",
+    "T = std_train_features.shape[2]\n",
+    "L = std_train_features.shape[-1]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "7959995d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(23103, 20, 100, 3)"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "std_train_features.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "5fff8d28",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "input: (None, 20, 100, 3)\n",
+      "output CNN 1: (None, 20, 16)\n",
+      "(None, 20, 16)\n",
+      "Model: \"model\"\n",
+      "_________________________________________________________________\n",
+      " Layer (type)                Output Shape              Param #   \n",
+      "=================================================================\n",
+      " input_1 (InputLayer)        [(None, 20, 100, 3)]      0         \n",
+      "                                                                 \n",
+      " time_distributed (TimeDistr  (None, 20, 1, 16)        4816      \n",
+      " ibuted)                                                         \n",
+      "                                                                 \n",
+      " time_distributed_1 (TimeDis  (None, 20, 16)           0         \n",
+      " tributed)                                                       \n",
+      "                                                                 \n",
+      " bidirectional_1 (Bidirectio  (None, 64)               12544     \n",
+      " nal)                                                            \n",
+      "                                                                 \n",
+      " dense (Dense)               (None, 16)                1040      \n",
+      "                                                                 \n",
+      " dense_1 (Dense)             (None, 20)                340       \n",
+      "                                                                 \n",
+      "=================================================================\n",
+      "Total params: 18,740\n",
+      "Trainable params: 18,740\n",
+      "Non-trainable params: 0\n",
+      "_________________________________________________________________\n"
+     ]
+    }
+   ],
+   "source": [
+    "def build_model(C, T, L, cycle_numbers=20):\n",
+    "    inputs = tf.keras.Input(shape=(C, T, L))\n",
+    "    print(f'input: {inputs.shape}')\n",
+    "    conv_1d_layer = tf.keras.layers.Conv1D(16, 100)\n",
+    "    blstm_layer = tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(16))\n",
+    "    x = tf.keras.layers.TimeDistributed(conv_1d_layer, input_shape=(5, 3))(inputs)\n",
+    "    x = tf.keras.layers.TimeDistributed(tf.keras.layers.Flatten())(x)\n",
+    "#     x = tf.keras.layers.Reshape((100, 64))(x)\n",
+    "    print(f'output CNN 1: {x.shape}')\n",
+    "#     conv_1d_layer = tf.keras.layers.Conv1D(64, 5, input_shape=(100,64))\n",
+    "#     x = tf.keras.layers.TimeDistributed(conv_1d_layer, input_shape=(100,))(x)\n",
+    "    print(x.shape)\n",
+    "    x = tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(32, return_sequences=False))(x)\n",
+    "    x = tf.keras.layers.Dense(16, activation='relu')(x)\n",
+    "#     e = tf.keras.layers.Embedding(input_dim=config.vocab_size, \n",
+    "#                                     output_dim=config.embedding_dim,\n",
+    "#                                     mask_zero=True)(inputs)\n",
+    "    yhat = tf.keras.layers.Dense(cycle_numbers)(x)\n",
+    "    model = tf.keras.Model(inputs=[inputs], outputs=yhat)\n",
+    "    return model\n",
+    "tf.keras.backend.clear_session()\n",
+    "model = build_model(C, T, L)\n",
+    "opt = tf.optimizers.Adam(1e-3)\n",
+    "model.compile(\n",
+    "  opt,\n",
+    "  loss='mean_squared_error')\n",
+    "model.summary()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "9dfd9010",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Epoch 1/150\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2022-06-22 15:07:00.677405: I tensorflow/stream_executor/cuda/cuda_dnn.cc:384] Loaded cuDNN version 8100\n",
+      "2022-06-22 15:07:01.122992: W tensorflow/stream_executor/gpu/asm_compiler.cc:111] *** WARNING *** You are using ptxas 10.0.145, which is older than 11.1. ptxas before 11.1 is known to miscompile XLA code, leading to incorrect results or invalid-address errors.\n",
+      "\n",
+      "You may not need to update to CUDA 11.1; cherry-picking the ptxas binary is often sufficient.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "46/46 [==============================] - 8s 58ms/step - loss: 2.9812 - val_loss: 1.9436 - lr: 0.0010\n",
+      "Epoch 2/150\n",
+      "46/46 [==============================] - 1s 22ms/step - loss: 0.8556 - val_loss: 0.8452 - lr: 0.0010\n",
+      "Epoch 3/150\n",
+      "46/46 [==============================] - 1s 22ms/step - loss: 0.3016 - val_loss: 0.5764 - lr: 0.0010\n",
+      "Epoch 4/150\n",
+      "46/46 [==============================] - 1s 22ms/step - loss: 0.1986 - val_loss: 0.5052 - lr: 0.0010\n",
+      "Epoch 5/150\n",
+      "46/46 [==============================] - 1s 22ms/step - loss: 0.1692 - val_loss: 0.5101 - lr: 0.0010\n",
+      "Epoch 6/150\n",
+      "46/46 [==============================] - 1s 22ms/step - loss: 0.1568 - val_loss: 0.5504 - lr: 0.0010\n",
+      "Epoch 7/150\n",
+      "46/46 [==============================] - 1s 22ms/step - loss: 0.1480 - val_loss: 0.5538 - lr: 0.0010\n",
+      "Epoch 8/150\n",
+      "46/46 [==============================] - 1s 22ms/step - loss: 0.1422 - val_loss: 0.5592 - lr: 0.0010\n",
+      "Epoch 9/150\n",
+      "46/46 [==============================] - 1s 22ms/step - loss: 0.1378 - val_loss: 0.5702 - lr: 0.0010\n",
+      "Epoch 10/150\n",
+      "46/46 [==============================] - 1s 22ms/step - loss: 0.1333 - val_loss: 0.5571 - lr: 9.0000e-04\n",
+      "Epoch 11/150\n",
+      "46/46 [==============================] - 1s 22ms/step - loss: 0.1311 - val_loss: 0.5212 - lr: 9.0000e-04\n",
+      "Epoch 12/150\n",
+      "46/46 [==============================] - 1s 22ms/step - loss: 0.1289 - val_loss: 0.4946 - lr: 9.0000e-04\n",
+      "Epoch 13/150\n",
+      "46/46 [==============================] - 1s 22ms/step - loss: 0.1273 - val_loss: 0.5295 - lr: 9.0000e-04\n",
+      "Epoch 14/150\n",
+      "46/46 [==============================] - 1s 22ms/step - loss: 0.1225 - val_loss: 0.4862 - lr: 9.0000e-04\n",
+      "Epoch 15/150\n",
+      "46/46 [==============================] - 1s 22ms/step - loss: 0.1207 - val_loss: 0.5276 - lr: 9.0000e-04\n",
+      "Epoch 16/150\n",
+      "46/46 [==============================] - 1s 22ms/step - loss: 0.1190 - val_loss: 0.5680 - lr: 9.0000e-04\n",
+      "Epoch 17/150\n",
+      "46/46 [==============================] - 1s 22ms/step - loss: 0.1189 - val_loss: 0.5270 - lr: 9.0000e-04\n",
+      "Epoch 18/150\n",
+      "46/46 [==============================] - 1s 22ms/step - loss: 0.1151 - val_loss: 0.5171 - lr: 9.0000e-04\n",
+      "Epoch 19/150\n",
+      "46/46 [==============================] - 1s 22ms/step - loss: 0.1124 - val_loss: 0.5313 - lr: 9.0000e-04\n",
+      "Epoch 20/150\n",
+      "46/46 [==============================] - 1s 22ms/step - loss: 0.1095 - val_loss: 0.5188 - lr: 8.1000e-04\n",
+      "Epoch 21/150\n",
+      "46/46 [==============================] - 1s 22ms/step - loss: 0.1097 - val_loss: 0.5090 - lr: 8.1000e-04\n",
+      "Epoch 22/150\n",
+      "46/46 [==============================] - 1s 22ms/step - loss: 0.1103 - val_loss: 0.5072 - lr: 8.1000e-04\n",
+      "Epoch 23/150\n",
+      "46/46 [==============================] - 1s 22ms/step - loss: 0.1116 - val_loss: 0.5561 - lr: 8.1000e-04\n",
+      "Epoch 24/150\n",
+      "46/46 [==============================] - 1s 22ms/step - loss: 0.1075 - val_loss: 0.5761 - lr: 8.1000e-04\n"
+     ]
+    }
+   ],
+   "source": [
+    "result = model.fit(\n",
+    "    train_data, \n",
+    "    validation_data=val_data, \n",
+    "    callbacks=[tf.keras.callbacks.ReduceLROnPlateau(\n",
+    "            monitor=\"val_loss\", factor=0.9, patience=5, min_lr=1e-5\n",
+    "        ), tf.keras.callbacks.EarlyStopping(monitor='val_loss', mode='min', restore_best_weights=True, patience=10)],\n",
+    "# #         tf.keras.callbacks.LambdaCallback(\n",
+    "# #         on_epoch_begin=lambda epochs,logs: print('lr =',lr_decayed_fn(opt.iterations).numpy())\n",
+    "# #         ),\n",
+    "#         ,\n",
+    "    epochs=150)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "e90f4296",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 0, 'Epochs')"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 600x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(dpi=100)\n",
+    "plt.plot(result.history['loss'], color='C0', label='Train')\n",
+    "plt.plot(result.history['val_loss'], color='C1', label='Validation')\n",
+    "plt.legend()\n",
+    "plt.ylabel('MSE')\n",
+    "plt.xlabel('Epochs')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4bf2cd6d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "conda_beep",
+   "language": "python",
+   "name": "conda_beep"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}