diff --git a/Assignment 1/Utkarsh_251151/Assignment 2.ipynb b/Assignment 1/Utkarsh_251151/Assignment 2.ipynb new file mode 100644 index 00000000..619f76b8 --- /dev/null +++ b/Assignment 1/Utkarsh_251151/Assignment 2.ipynb @@ -0,0 +1,232 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "e7b905ef", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "import yfinance as yf\n", + "import plotly.graph_objects as go\n", + "import plotly.io as pio" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "d73b1be1", + "metadata": {}, + "outputs": [], + "source": [ + "pio.renderers.default = \"notebook_connected\"" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "ab3f991d", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[*********************100%***********************] 1 of 1 completed\n" + ] + } + ], + "source": [ + "df = yf.download(\n", + " \"AAPL\",\n", + " period=\"6mo\",\n", + " interval=\"1d\",\n", + " group_by=\"column\",\n", + " auto_adjust=False\n", + ")\n", + "df.columns = df.columns.get_level_values(0)\n", + "df = df[df[\"Volume\"] > 0]\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "7ea6c016", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Price Open High Low Close\n", + "Date \n", + "2025-06-13 199.729996 200.369995 195.699997 196.449997\n", + "2025-06-16 197.300003 198.690002 196.559998 198.419998\n", + "2025-06-17 197.199997 198.389999 195.210007 195.639999\n", + "2025-06-18 195.940002 197.570007 195.070007 196.580002\n", + "2025-06-20 198.240005 201.699997 196.860001 201.000000\n", + "Price Open High Low Close\n", + "count 127.000000 127.000000 127.000000 127.000000\n", + "mean 240.415472 242.862678 238.368346 240.645827\n", + "std 26.532801 26.803042 26.411420 26.695534\n", + "min 195.940002 197.570007 195.070007 195.639999\n", + "25% 213.519997 215.195000 212.019997 213.654999\n", + "50% 238.970001 240.149994 236.649994 238.470001\n", + "75% 265.740005 270.190002 265.410004 267.449997\n", + "max 286.200012 288.619995 283.299988 286.190002\n", + "Date\n", + "4 26\n", + "1 26\n", + "2 26\n", + "0 25\n", + "3 24\n", + "Name: count, dtype: int64\n" + ] + } + ], + "source": [ + "print(df[[\"Open\", \"High\", \"Low\", \"Close\"]].head())\n", + "print(df[[\"Open\", \"High\", \"Low\", \"Close\"]].describe())\n", + "print(df.index.dayofweek.value_counts())\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "bf5b6031", + "metadata": {}, + "outputs": [], + "source": [ + "x = df.index.astype(str) \n", + "open_ = df[\"Open\"].to_numpy()\n", + "high_ = df[\"High\"].to_numpy()\n", + "low_ = df[\"Low\"].to_numpy()\n", + "close_ = df[\"Close\"].to_numpy()\n", + "ymin = df[\"Low\"].min()\n", + "ymax = df[\"High\"].max()\n", + "padding = 0.02 * (ymax - ymin)\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "e6dc6699", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + " \n", + " \n", + " " + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
\n", + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = go.Figure(\n", + " go.Candlestick(\n", + " x=df.index.astype(str), \n", + " open=df[\"Open\"],\n", + " high=df[\"High\"],\n", + " low=df[\"Low\"],\n", + " close=df[\"Close\"]\n", + " )\n", + ")\n", + "fig.update_layout(\n", + " height=1000\n", + ")\n", + "\n", + "\n", + "fig.update_layout(\n", + " title=\"Apple (AAPL) — Last 6 Months\",\n", + " xaxis_title=\"Date\",\n", + " yaxis_title=\"Price (USD)\",\n", + " xaxis_rangeslider_visible=True,\n", + " xaxis=dict(type=\"category\") \n", + ")\n", + "fig.update_layout(\n", + " yaxis=dict(\n", + " range=[ymin - padding, ymax + padding]\n", + " )\n", + ")\n", + "\n", + "fig.show()\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "567e0d2f", + "metadata": {}, + "source": [ + "on 25-6-25,17-9-2025 Doji was observed #squeezed my eyes for this \n", + "on 26th june price moved downward . \n", + "on 18th september and bit furthur price increased." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.9" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/Assignment 1/Utkarsh_251151/i b/Assignment 1/Utkarsh_251151/i new file mode 100644 index 00000000..8b137891 --- /dev/null +++ b/Assignment 1/Utkarsh_251151/i @@ -0,0 +1 @@ + diff --git a/Assignment 3/bcs-fap-qv.ipynb b/Assignment 3/bcs-fap-qv.ipynb new file mode 100644 index 00000000..580f091f --- /dev/null +++ b/Assignment 3/bcs-fap-qv.ipynb @@ -0,0 +1 @@ +{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.11.13","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":8077192,"sourceType":"datasetVersion","datasetId":4766889}],"dockerImageVersionId":31239,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"import os\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport tensorflow as tf\n\nfrom tensorflow.keras.preprocessing.image import ImageDataGenerator\nfrom tensorflow.keras import layers, models, optimizers\n","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true,"execution":{"iopub.status.busy":"2026-01-04T09:46:20.023694Z","iopub.execute_input":"2026-01-04T09:46:20.024030Z","iopub.status.idle":"2026-01-04T09:46:20.030135Z","shell.execute_reply.started":"2026-01-04T09:46:20.024007Z","shell.execute_reply":"2026-01-04T09:46:20.028669Z"}},"outputs":[],"execution_count":20},{"cell_type":"code","source":"train_ds_path = \"/kaggle/input/candle-image-data/Train\"\ntest_ds_path = \"/kaggle/input/candle-image-data/Test\"\n\nIMG_SIZE = (224, 224)\nBATCH_SIZE = 32\nSEED = 42\n\ntf.random.set_seed(SEED)\nnp.random.seed(SEED)\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-01-04T09:46:20.032440Z","iopub.execute_input":"2026-01-04T09:46:20.032900Z","iopub.status.idle":"2026-01-04T09:46:20.062998Z","shell.execute_reply.started":"2026-01-04T09:46:20.032862Z","shell.execute_reply":"2026-01-04T09:46:20.061925Z"}},"outputs":[],"execution_count":21},{"cell_type":"code","source":"raw_gen = ImageDataGenerator(rescale=1./255).flow_from_directory(\n train_ds_path,\n target_size=IMG_SIZE,\n batch_size=BATCH_SIZE,\n class_mode=\"binary\",\n shuffle=True,\n seed=SEED\n)\n\nimages, labels = next(raw_gen)\n\nplt.figure(figsize=(9, 9))\nfor i in range(9):\n ax = plt.subplot(3, 3, i + 1)\n plt.imshow(images[i])\n plt.title(\"UP\" if labels[i] == 1 else \"DOWN\")\n plt.axis(\"off\")\nplt.show()\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-01-04T09:46:20.064774Z","iopub.execute_input":"2026-01-04T09:46:20.065127Z","iopub.status.idle":"2026-01-04T09:46:21.191568Z","shell.execute_reply.started":"2026-01-04T09:46:20.065071Z","shell.execute_reply":"2026-01-04T09:46:21.190586Z"}},"outputs":[{"name":"stdout","text":"Found 1433 images belonging to 2 classes.\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{}}],"execution_count":22},{"cell_type":"code","source":"raw_gen = ImageDataGenerator(rescale=1./255).flow_from_directory(\n train_ds_path,\n target_size=IMG_SIZE,\n batch_size=BATCH_SIZE,\n class_mode=\"binary\",\n shuffle=True,\n seed=SEED\n)\n\nimages, labels = next(raw_gen)\n\nplt.figure(figsize=(9, 9))\nfor i in range(9):\n ax = plt.subplot(3, 3, i + 1)\n plt.imshow(images[i])\n plt.title(\"UP\" if labels[i] == 1 else \"DOWN\")\n plt.axis(\"off\")\nplt.show()\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-01-04T09:46:21.192881Z","iopub.execute_input":"2026-01-04T09:46:21.193566Z","iopub.status.idle":"2026-01-04T09:46:22.360286Z","shell.execute_reply.started":"2026-01-04T09:46:21.193538Z","shell.execute_reply":"2026-01-04T09:46:22.359266Z"}},"outputs":[{"name":"stdout","text":"Found 1433 images belonging to 2 classes.\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"
","image/png":"iVBORw0KGgoAAAANSUhEUgAAAswAAALfCAYAAAB1k5QvAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8pXeV/AAAACXBIWXMAAA9hAAAPYQGoP6dpAABVJklEQVR4nO3deXxUZZ7v8e+p7AkRkC0JkIDgyiKLKATCNrY40y6j3dpX5vZcZ+5Vb0vr9Dgzeue2iku3dwSXFrtR29u2Dt52tNuelnaZUVFBAi2LKCiLbAkhZCWQhOzLc//ARE5OcVJUKnVq+bxfr3Rbv/NU1S/AqfrWqec8xzLGGAEAAADwy+d1AwAAAEAkIzADAAAALgjMAAAAgAsCMwAAAOCCwAwAAAC4IDADAAAALgjMAAAAgAsCMwAAAOCCwAwAAAC4IDADAAAALgjM/eTFF1+UZVndP6mpqcrJydGiRYu0YsUK1dfX+71fYWGhrrvuOo0YMUIpKSkaM2aMbrvtNh06dMg2btmyZbIsS9u2bbPVjTEaPHiwLMvSwYMHbduam5uVkpKixYsXd9e6+nv88cdP+zts2bIl2D8GIKawXwPw54EHHpBlWaqurva7feLEiZo/f74kqaioyPY6kpCQoNzcXF133XX67LPPwtc0zgiBuZ899NBDWrVqlZ555hndcccdkqQf/ehHmjRpkrZv324b+/TTT6ugoEA7duzQHXfcoZUrV+q73/2uXn31VU2ePFkbNmzoHjtnzhxJ0vr1622P8eWXX+r48eNKTExUYWGhbdvmzZvV2trafd9TLV++XI2NjSH5nYFYx34NoK9uuukmrVq1Si+88IIWL16sDz74QDNnziQ0RyqDfvHrX//aSDKbN292bFuzZo1JS0szeXl5prGx0RhjzPr1643P5zMFBQWmoaHBNn7fvn1mxIgRJjs729TU1BhjjGlpaTGpqanmxhtvtI199tlnzZAhQ8yiRYvMbbfdZtv2yCOPGEnm888/765JMlOmTDGSzOOPPx7w7wDEI/ZrAP4sXbrUSDJVVVV+t0+YMMHMmzfPGGPMwYMHjSSzfPly25jVq1cbSebWW2/t73YRBI4we2DhwoW67777VFxcrJdfflmS9PDDD8uyLL300ktKT0+3jR83bpyWLVumsrIyPffcc5Kk5ORkzZgxw3G0qbCwULNmzdLs2bP9bhs0aJAmTpxoq8+ePVsLFy7UsmXL1NTUFOpfF4gL7NcA+mLhwoWS5Jh2hchAYPbI97//fUnSu+++q8bGRq1Zs0YFBQUaO3as3/Hf+973lJKSojfffLO7NmfOHJWWlqqoqKi7VlhYqPz8fOXn53d/jSudnAO5YcMGzZo1Sz6f86/9gQceUEVFhZ555pnQ/ZJAnGG/BhCs/fv3S5KGDBnicSfwh8DskVGjRmngwIHav3+/9u7dq/b2dl188cWnHZ+SkqLzzz9fu3bt6q71nO9YXl6uAwcOaPbs2brsssvk8/m650fu3LlTx44d8zvPUZIKCgq0YMECLV++nKNRQJDYrwEEqrGxUdXV1aqoqNDatWt18803S5JuuOEGbxuDXwRmDw0YMED19fXdZ9ZnZma6js/MzFRdXV337fz8fPl8vu431sLCQiUlJWnGjBkaMGCAJk+e3P31bdf/n+6NVTp5NKq8vFzPPvtsn34vIJ6xXwMIxNKlSzVs2DBlZWVp/vz52r9/vx599FFdf/31XrcGPwjMHjpx4oQyMzO731BPtyRVl/r6etub76BBgzRhwgTbm+fUqVOVlpYm6eQb76nbkpOTdemll5728efOnasFCxYw5xHoA/ZrAP5YlmW7feutt+q9997TmjVrtHXrVlVWVuruu+/2qDv0hsDskcOHD6u2tlbjx4/X+PHjlZiY6FiO6lQtLS3as2ePLrroIlt9zpw53XMau+Y5dsnPz9emTZvU1tam9evXa/r06UpNTXXta+nSpSovL+8+CQlA4NivgfjUtQ+e7kNpY2OjYz8999xzdfnll2vhwoWaNm2aUlJS+r1PBI/A7JFVq1ZJkhYtWqSMjAwtWLBA69atU3Fxsd/xr732mlpaWnTVVVfZ6nPmzJExRu+//762bdum2bNnd2/Lz89XU1OT3nrrLR04cMD1a9su8+bN0/z58/Xoo49yNAo4Q+zXQHzKy8uTJO3Zs8exrbGxUSUlJd1jEKW8XdUudgWyXuvYsWNNU1OTMcaYtWvXGp/PZ+bPn9+9hmuXAwcOmKysLNt6rV2Ki4uNJDNr1iwjyZSWltq2Z2dnd2974403HL1IMkuWLLHVPvroI9s6rqzXCpzEfg3An4qKCpOcnGyuv/5609HRYdv25JNPGknmD3/4gzHm9OswI7Ilhj+ix5d33nlHu3fvVnt7uyoqKvTBBx/ovffeU15enlavXt39Fc3cuXP12GOP6a677tLkyZN18803Kzs7W7t379bzzz+vzs5Ovf322xo8eLDt8XNzczV69Ght3LhRY8aMUU5Ojm17fn6+Xn/9dVmWZTtK5WbevHmaN2+e1q5dG5o/BCDGsF8DONXw4cN1//33695779XcuXN1zTXXKD09XRs2bNArr7yiK664QldffbXXbaIvvE7ssarrSFTXT3JyssnKyjLf+ta3zFNPPWXq6ur83m/dunXm2muvNUOHDjVJSUkmNzfX3HLLLaaoqOi0z3XTTTcZSWbx4sWObU888YSRZC688EK/95WfI1HGGPPhhx92986RKOAk9msAbl5++WUzc+ZMk5GRYVJSUswFF1xgHnzwQdPc3Nw9hiPM0ckyxpiwp3QAAAAgSnDSHwAAAOCCwAwAAAC4IDADAAAALgjMAAAAgAsCMwAAAOCCwAwAAAC4IDADAAAALgK+0p9lWf3ZBxBTomV5c/ZrIHDs10DsCXS/5ggzAAAA4ILADAAAALggMAMAAAAuCMwAAACACwIzAAAA4ILADAAAALggMAMAAAAuCMwAAACACwIzAAAA4ILAHCdSfVz5CUB4+ZISvG4B6Ff8G48fBOY4UTV7qtctAIgzlz1+m9ctAP1q5mP8G48XBGYAQNSYnJHmdQsA4hCBGQAQNTZMu8jrFoB+NXhCntctwA8CMwAganA2BmLdhbdd5XUL8IPAHIEeGjPS6xYAAADwtUSvG4DTXaNH6P6iUq/bAAAA/WTwhDwNn3mho+5LTND5//1KW61q8x7VbD8YrtbgB4EZABA1jNcNACGSlnW2hl16gd9tPesNh6sJzB5jSgYAIGowhxmAFwjMAAAAgAumZIRAbcF0Dfx4q9dtSJLuHDVCj4/PddQTJLXNn2Gr/e/9JVpeUh6mzgAg8lgJPpmOTq/bAPpNsmWp1TCZqa84whwCiRH0HaElKVGW48fyV7MiqHEAUc2XnKikzDTbj2Q5akmZafIlRc6xmllP/sDrFoB+daxgmtctxITIedWKYnxuAxDvcuZfrDHfKXDUL/Nz6eADr63VkTXbgnoeXm8BeIEjzCHAcVoACA9ebwF4gcAMAAAAuCAwAwAAAC4IzAAAAICLuDzp7/zbr9WelW8Edd9bsofpv4wYYqul+HxaM8V+VZ4Xy6q0quJo0D0CAJw46Q+AF+IyMA8+f2TQ9x2XlqKFgzLV89SThYPOst3+6Fhd0M8BAPHuvwwfrPvHZEvG/lqbZlnaOWOCrfZ0aaWeOVIVzvYAxJmYDszZ8y9W7lUzHadVJyQn6bLH7UsdFb+xQeXrdoSxOwDA6QxOTNKF6Rl+t12YkW67PTQpKRwtAYhjIQ/MNXOm6ez1n4buAX2W1Bncl3C+5EQlDUizB+avHyppQJptbEIELaQPAOh63e9lITljxEQN4KT7x+Tox3k5tlqSZall3iW22v8pLtMDRaXhbC3qhfykvyRfaFfJvOxnt/ftAXq2Y/mpeSjNZ+nsxATbjyVn7ezEBKVwZT4AcCIvA5KkBFlKtny2H8tRs1jxIQgRf1jVF0npth/8w+gsPTy255xqS0fnTHWMXfJVsVYyTw8AACCsIj4wxz5L/g/0+/mgwBFmAACAsOOoPAAAAOCCwAwAAAC4YEoGAABAzOAs2P4QdGD+y6GDdVvOMEc91efTO5PPs9VeKKvWb6tqgn0qAECEq9q6Vw2Hq3sdZyQ1VfB+AHiKU6LOWNCBOS81WVeePcjvtp71D4/VB/SY2fMnK3vuZFstISlB0+7/r7aaMUaH3vxER7ftC7hfAIC7TdMv0qVbdwZ135ajdWo5yhVOAS/9orTCcYBy8/QJmrH1S1utsrUtnG3FhIiakpGUma70nCGO1SDSRw61DzRGiRmpYewMAGLfhIy03gcBiFiVbe2qbGu31Tpl9EVDk0cdxY6ICswAAPQrf8tz+qsZ5oEC+AaB+Qw1dxod7+iw1QYmJKi2R62FF1sAiCij/+JS5V0zy160LM155k7H2P2vfKiytdvD1BmASEdgPkMPFJU6rr/eMHe6Bn/8qUcdAQACFtARZsNJUeh3HU0taq467qinDh2o5upaW629sSVMXeF0Yjowtx4/obp9pT2qls46J0t1B8ps1ZbahvA1BgCIcHxLiP5VsWGnKjY4T7LNX7FEW+59MfwNwVVMB+aqTXtUtWmPoz7rqdu1fflvPegIAAAA0YYr/YXAkyUVXrcAAACAfhLTR5jD5d6Dh71uAQAA9KPBE/I0ePI5tpqVlKBzblrgGFu95SvV7e05JRTRjMAMABHu7IvPUdaciQGNrdiwk4s6Af1gQN4I5cy/2FH3V2s6cpTAHGMIzAAQ4VKHDtTZPY5snU7dviP93A0AxB8CMwDEoX8YnaW/H51lq6X6fDqcP8VWe6qkXMtLysPYGYBItufSyTp/U/ytUR6XgfmTf/yl1y0AgKfOSkjQyORkR91eM8pMSAhfUwAiXk5KktcteCIuV8no7HGddQAAAOB04vIIMwDEu9qODh1qsV89bFRKsg63tDrGAYhPmQk+DUq0R0VLUm5KsuPSPsfb21Xf0RnU8/h77emL5MED1HrsRMgeTyIwRwYuwQogzJ4oKdcTPeYmN8ydrryNn3vUUaThhRmxYUtd8MHxf+YM17JxuY568awpPSpGd+07pCcPB3ddit0zJ2nA2q1B3defSx78b9pw5y9C9ngSgdlzuxub9PuqGlvtmiGDtfroMcfYA01cSx4AgtVYfkzVPZbcG3LxOTr6+QFbzZLUXFUbxs6Abxz9fH9IH2/eZ84rHkcaK7gD02FFYPbY76qO6XdV9nB8omCavvMF66gCQCgd/XSvjn6611bLX7FEu59906OOAKc9v/oPr1uAH3F50h8AAAAQKAJzBPqrnQd6HwQAAICwIDBHoDeOHve6BQAAAHyNwAwAiEABrlJhSbKCX9Gi59JYAOAPJ/0BACKOUaeMOv0kWp+knqfUBx97P/knrvwKeC0aPrgSmAEAEefZI9V67ki1o36iYLoGfGxfr7Uvb7adLW19uDeAUOjLqueWz5KVkOB4QF+SM+J2dnRIncG9YhCYAQCSpLLWyAqPp3tbi4ajUQDCY9SVM5R3bb6jnv/zH9puG9Opfa98qIq1O4J6HuYwA0AYZIwc6nULvRr/p+1etwAA/cKyLPn6cCibwAwAYXDxPd/zuoWYwNFlIPZEw34dUVMyThRVqGyt/QhHVsEklX/sPHzeWHY0XG0BACJEX+Y6AohM0bBfR1RgrtlxUDU7DtpqQy67QPtf+dCjjgAAABDvIn5Kxr6X3vO6BQAAAMSxiA/MNdv2ed0CACBCRMNcRwBnJhr264gPzAAAdImGuY4Azkw07Nd9msNs/HwmsGQ569HwJ4EzciR/inI2fOZ1G0BcKFu7XRUbvuxRtXTpo/9Dm+553lbtbOsIX2MeMO1edwAgHgUdmFccrtDPD1c46rVzp2vgOvtVmHpexBTRb2BiQu+DAISEae9QR7szCG/8u5WSiYYvM0Nn4MatvQ8CgBALOjAbSf6OY5yujuiV4fMpPcE+e8eSpWE9LjvZ2NGphk4+HgFhE2dhWeL9BYA3ImpZOUSmu3OzdP+YnB5VS5Wzp9gqDxcd0f1FR8LWFwAAiB6DExOUk5LsqFuWpQkZabZaZWubqtoiZw4WgRkBsOT//NBTJ6cbMVkdOCl16EClDh9oq1k+S4MuynWMbSqrUcuxE+FqDQA881+GD9HK8/LkLy98MWPSKbeM7j9YqoeLI+cgHIEZoRF/3wwDpzXs0vOVd22+oz7x76531Pb/5gPHFU4BIDYFGBaMIm7KGcvKAQAAAC5CHphv21MU6ocEAAAAPBPywPybiqOhfkgAAADAM8xhBgAAgMOvyqr0x6PHbbWt0yfokq1fOmYjV7S2ha0vLxCYAQAA4FDT3qGaHhdN6pS0q7HZm4Y8RGCOMZ2S2vycWZpoSe09yp0RdgYqAABAJCIwx5inD1foaT+XLK8vmKbMjz/1oCMAAIDoxrJyAAAAgAsCMwD4cdb4kV63AACIEEzJABD3MkYPU0bOEFvt3L/+lvb+63u22onD1WosrQ5nawAQUV6piM/XQAIzgLg37JLzNOrKSyRZtvp5f3ul7Xbx6o0BBea6faUqeesT27JLo6+8RCX/scU2zpJ0orgyyK4BIPxu/arY6xY8QWAGAMeKon1T+1Wpar8qtdVGXT5Nh1ZvDOnzAADCgznMAAAAgAsCMwAAAOCCwAwAAIAwsHof0jXMCnBsmDCHGQAAAP3OqFMdpkM9g7NPljp7nEtiQnxuSV8RmAEgDDqaW71uAQA89eyRaj17xLnSUEPBdGV8vNWDjgJHYAaAMPjk7ue9bgEAYlMgB6Otvh2xJjADAAAgKrXU1Ktur30Zz7PGZ6tuX5mtZqlTbcdOBP08BGYAAABEpco/7VLln3bZavkrlmj7478N6fOwSgYAAAA8E1mn9/lHYAYAAABcEJgBAADgmchacdk/AjMAAAC8EwVzMgjMAAAA8Mz4Tdu9bqFXrJIRJ4YXbvO6BQAAotbh/9ii0vc+tdVmPn6r/vSPv3QcIe3s6AhjZ9GvrLXN6xZ6RWCOE02dUfB9BwAAEcp0dsp0dvYoSp2t7d40hNNqbw59AGdKBgAAAGLGprt/GfLHJDADAAAALgjMAAAAgAsCMwAAAOCCwAwAABCEon8v9LoFhAmBGQAAIAhHPvrc6xYQJgRmAAAAwAWBGQAAAHBBYAYAAABcEJgBAAAAFwRmAAAAwAWBGQAAAHBBYAYAAABcEJgBAAAAFwRmAAAAwAWBGQAAAHBBYAYAAABcEJgBAAAAFwRmAAAAwAWBGQAAAHBBYAYAAABcEJgBAAAAFwRmAAAQFwZdMNrrFhClCMwAACAuXLTkGq9bQJQiMAMAAAAuCMwAAACACwIzAACID8brBhCtCMwAACA+WF43gGhFYAYAAABcJHrdACBJiZbUHuFflUVDjwCAr1mWLNsR5ZM3LJ/9MLMxhqka6BWBGRHh2Jzpyvx4q9dtuDo+Z7oGRHiPAICTxvxlvkYtusRetCzNXnmnrVT8xz+p5K1PwtgZohGBGQgUc98AIIqYr1+3e7x4W7yY48wxhxkAAABwQWAGAAAAXBCYEbNGXTnd6xYAIGLdPTrL6xaAqEFgRswa/e3LvG4BACLWfWNyvG4BiBoEZgAA4lGIT3678AfXhPTxgEjCKhkAAOCMZM+frOy5k2219Owhmnb/f7XVjDE69OYnOrpt3xk/hyVpw7SLNOvTnX1pFQgJAjMAADHsluyhevickeq5vFqGz6fy2VNstZ8UHdHPSyt7fcykzHSl5wxxHKVOHznUPtAYJWakBtO2JGlCelrQ9wVCicAMIDZYlmS4XBfQU3pCgkYkJfvdNiIpyT7Wx0xNwB/2DABRxUpMUEJaco+fFM144geOupXISxxwZrioB+APR5gBRJWchVM09jsFfrfN+tntttsHX1ur0jXbwtEWEOEIwkBfEJgBP0alJCsv1f4VZoJlafbAAfaBRtrf1KzytvYwdgcAAMKJwAz4cXPWUD08dpSjvn7qRfaC6dSSvcVaeaQqTJ0BAIBwY4If0BeWJIsTzaIfX1cDAE6PI8wA4t7Rzw+opabeVjvnxnk68NpaW62+qCKcbQEAIgSBGUDcqz9QpvoDZbba2O8WqGztdo86AgBEEgIzgLCb/I83avtjr3ndhism2gDh89dZQ3TnqCxbzZKUnujTlksm2OpPlJTrNxVHw9gdQGAG4IGM0cO8bqFXW+990esWgLgxIilJ0weky9/5BNMHZPQYS3RB+PGvDgHq5Xgb50whnMJw+Le1tqH/nwQAEBUIzOhVq+nUiQ77OsMZCYlq6FFrNZ3hbAvxrmdotnrU+BAHAAgRAjN69dPiMv202H5CVMPc6cr8mCuoIfzamlrVdLSux5qYllKGDHCsdNHe3BrO1gAAMYrADCCqVH68Q5Uf73DUZz11uzb/+AUPOgIAxDoCM8Lu3LQUTcxIt9USLUvXDx3s+JZ9R0Oj9jW1hK85AACAHgjMCLu/HDpYy8blOuqvTzy3R8Xorn2H9ORhLhYRzTLHZilzbLatZiX4lLNwqmPs8d2H1HiE5aIAAJGFwAygXw2eOEa5357pqJ9z4zxHbe/L7xOYAQARh8AMoP+xYgUAIIr5eh8CAAAAxC8CMwAAAOCCwAwAAAC4YA4zol7W3Ekad9NCR92ypNnP/J2tduiPG1Xy9qZwtQYACEC7MWrs7FTPEx7SfJaaOk2PsWFsDPgagRkxwbK6/sdPvYsxfscgNrTWNnjdAoAgPXm4wrGEqCWpds50nbV+qzdNAacgMCPqWZYVUBA2kozh0ES4tdU1qqGk0lbLGDlMDaVVjrHtDc1BP8/W+18K+r4AALghMAPoV2Vrt6ts7XZbbdZTS7TtJ7/xqCMAAM4MJ/0BAAAALgjMAAAgBnHOCkKHKRkAws7wUR1AP6vavEcNh6tttfNuvkJfvfiurdZQah8D+ENgBhB2X/7s9163ACDGNRyudgTmc79/uao27/GoI0QzjvMg6hljTi4Z14uTK8+F+Cs6I8nwtd+Zqt9f5nULAOIRL9cIEkeYEZScws+8buEbliUjyQrpknFGRvbHsyx/udwiMAMAEOMIzAhKbUeH1y10K1+7XeXrdtiLljRrxQ+08Y5n7PUAQ/VPi8v0f4rtR0Fr507XwHXOBfQ7z6jb6DTzyR/oT3//TO8DASCCmfbIee9CdCEwIzb0DMKm6ye4o85Gkr+X1Xh9qfUlMHsLQPTb+PfPet0CohTvggAAAIALAjMAAIhIa47Xet0CIInADAAAIpCRdN0X+7xuA5BEYAYAAF1Y9Afwi5P+AACIeSbAMBzK5TmB2EFgRsz6csUbXrcAAJ57vapG2080OupvTT5f395uv+rd/qaWcLUFRBUCM2JW3d5Sr1sAAM8dbmnT4ZY2R71DRh8er/egIyD6MIcZAAAAcMERZgDfsCTL6jnR8eRty2evG2OY7ggAiAsEZgDdshdO1Tk3zHXULVnKX3mnrVb0+0KVvrslXK0BAOAZAjOAbu2NzWqqPO44cpw+fNDJeo+xAADEAwIzgG5VG3epauMuRz1/xRJ9uvQlDzoCAMB7BGYgQK+UH/W6BQCICA2Hq1X5yW5bbdiM81W12b5MnYxRc+WxMHYG9A8CMxCgW74q8roFAIgIR7ft09Ft9stWD5l6rr769X961BHQv1hWDgAAAHBBYAYAIA5dt2Ov1y0AUYPADABAHHr/WJ3XLQBRg8AMAAAAuLCMMQFdq8t59S8gOAmSEgP899RujDr6t51+EeBu5blA92srMUGmPRr/JoDQibX9OuTPy+sEolCg+zWBGegHvLECsYf9Gog9ge7XTMkAAAAAXBCYAQAAABcEZgAAAMAFgRkAAABwQWAGAAAAXBCYAQAAABcEZgAAAMAFgRkAAABwQWAGAAAAXAR8pT8AAAAgHnGEGQAAAHBBYAYAAABcEJgBAAAAFwRmAAAAwAWBGQAAAHBBYAYAAABcEJgBAAAAFwRmAAAAwAWBGQAAAHBBYAYAAABcEJgBAAAAFwRmAAAAwAWBGQAAAHBBYAYAAABcEJgBAAAAFwRmAAAAwAWBGQAAAHBBYAYAAABcEJgBAAAAFwTmfvLiiy/Ksqzun9TUVOXk5GjRokVasWKF6uvr/d6vsLBQ1113nUaMGKGUlBSNGTNGt912mw4dOmQbt2zZMlmWpW3bttnqxhgNHjxYlmXp4MGDtm3Nzc1KSUnR4sWLu2td/T3++OOn/R22bNkS7B8DgFM88MADsixL1dXVfrdPnDhR8+fPlyQVFRXZXkMSEhKUm5ur6667Tp999ln4mgZiHO/XCASBuZ899NBDWrVqlZ555hndcccdkqQf/ehHmjRpkrZv324b+/TTT6ugoEA7duzQHXfcoZUrV+q73/2uXn31VU2ePFkbNmzoHjtnzhxJ0vr1622P8eWXX+r48eNKTExUYWGhbdvmzZvV2trafd9TLV++XI2NjSH5nQGEzk033aRVq1bphRde0OLFi/XBBx9o5syZhGYgxHi/hiuDfvHrX//aSDKbN292bFuzZo1JS0szeXl5prGx0RhjzPr1643P5zMFBQWmoaHBNn7fvn1mxIgRJjs729TU1BhjjGlpaTGpqanmxhtvtI199tlnzZAhQ8yiRYvMbbfdZtv2yCOPGEnm888/765JMlOmTDGSzOOPPx7w7wDgzC1dutRIMlVVVX63T5gwwcybN88YY8zBgweNJLN8+XLbmNWrVxtJ5tZbb+3vdoG4wPs1AsERZg8sXLhQ9913n4qLi/Xyyy9Lkh5++GFZlqWXXnpJ6enptvHjxo3TsmXLVFZWpueee06SlJycrBkzZjg+lRYWFmrWrFmaPXu2322DBg3SxIkTbfXZs2dr4cKFWrZsmZqamkL96wIIoYULF0qS4ytcAKHH+zW6EJg98v3vf1+S9O6776qxsVFr1qxRQUGBxo4d63f89773PaWkpOjNN9/srs2ZM0elpaUqKirqrhUWFio/P1/5+fndX/dIJ+dKbdiwQbNmzZLP5/xrf+CBB1RRUaFnnnkmdL8kgJDbv3+/JGnIkCEedwLEB96vIRGYPTNq1CgNHDhQ+/fv1969e9Xe3q6LL774tONTUlJ0/vnna9euXd21nvOiysvLdeDAAc2ePVuXXXaZfD5f9zyqnTt36tixY37nQ0lSQUGBFixYoOXLl/OpFYggjY2Nqq6uVkVFhdauXaubb75ZknTDDTd42xgQJ3i/hkRg9tSAAQNUX1/ffQZuZmam6/jMzEzV1dV1387Pz5fP5+veAQsLC5WUlKQZM2ZowIABmjx5cvfXPF3/f7odUDr5qbW8vFzPPvtsn34vAKGzdOlSDRs2TFlZWZo/f77279+vRx99VNdff73XrQFxg/drEJg9dOLECWVmZnbveKdbuqZLfX29bScdNGiQJkyYYNvJpk6dqrS0NEknd9BTtyUnJ+vSSy897ePPnTtXCxYsYG4U4CHLsmy3b731Vr333ntas2aNtm7dqsrKSt19990edQfEJ96vQWD2yOHDh1VbW6vx48dr/PjxSkxMdCxbc6qWlhbt2bNHF110ka0+Z86c7rlPXfOhuuTn52vTpk1qa2vT+vXrNX36dKWmprr2tXTpUpWXl3efrAAgdLr2v9O9wTU2Njr20XPPPVeXX365Fi5cqGnTpiklJaXf+wTwDd6vIRGYPbNq1SpJ0qJFi5SRkaEFCxZo3bp1Ki4u9jv+tddeU0tLi6666ipbfc6cOTLG6P3339e2bds0e/bs7m35+flqamrSW2+9pQMHDrh+vdNl3rx5mj9/vh599FE+tQIhlpeXJ0nas2ePY1tjY6NKSkq6xwCIDLxfQxLrMPeXQNZ1HDt2rGlqajLGGLN27Vrj8/nM/Pnzu9d67HLgwAGTlZVlW9exS3FxsZFkZs2aZSSZ0tJS2/bs7OzubW+88YajF0lmyZIlttpHH31kW++RdR2B0KioqDDJycnm+uuvNx0dHbZtTz75pJFk/vCHPxhjTr8OM4DQ4v0agUgMf0SPL++88452796t9vZ2VVRU6IMPPtB7772nvLw8rV69uvsrl7lz5+qxxx7TXXfdpcmTJ+vmm29Wdna2du/ereeff16dnZ16++23NXjwYNvj5+bmavTo0dq4caPGjBmjnJwc2/b8/Hy9/vrrsizL9mnWzbx58zRv3jytXbs2NH8IACRJw4cP1/333697771Xc+fO1TXXXKP09HRt2LBBr7zyiq644gpdffXVXrcJxCXer+HK68Qeq7o+sXb9JCcnm6ysLPOtb33LPPXUU6aurs7v/datW2euvfZaM3ToUJOUlGRyc3PNLbfcYoqKik77XDfddJORZBYvXuzY9sQTTxhJ5sILL/R7X/n5xGqMMR9++GF373xiBULr5ZdfNjNnzjQZGRkmJSXFXHDBBebBBx80zc3N3WM4wgyEB+/XCIRljDFhT+kAAABAlOCkPwAAAMAFgRkAAABwQWAGAAAAXBCYAQAAABcEZgAAAMAFgRkAAABwQWAGAAAAXAR8pT/LsvqzDyCmRMvy5uzXQODYr4HYE+h+zRFmAAAAwAWBGQAAAHBBYAYAAABcEJgBAAAAFwRmAAAAwAWBGQAAAHBBYAYAAABcEJgBAAAAFwRmBMWXlOB1CwBCLNXHBS/iCa/jQOAIzAjKzCf+p9ctAAixo3Omed0Cwmjm47yOA4EiMAMAAAAuCMwAAACACwIzAAAA4ILADAAAALggMAMAAAAuCMwAAACACwIzgLCbet/3vW4BAICAEZgBhF3qsIFetwAAQMAIzAAAAIALAjMAAADgItHrBhD5kjLTlJSZbqtZlqX0nCG2Wlt9o9rqm8LZGgAAQL8jMKNX2fMvVu5VMx31aUvtJ26VvPWJildvDFdbAAAAYcGUDAAAAMAFgRkAAABwQWAGAAAAXBCYAUQ9S9Kbk87zug0AQIwiMAOICXMHZnrdAgAgRrFKBgJjvG4AAADAGwRm9Mp0GnW2d9pqvkRLne3GMQ4AEFmyF0zR2O/OldXjyIeV4NPsX9xhqxX9YYNK39sazvaAqEBgRq9K3vpEJW99YqvlP71EG+74hUcdAQACZlmyEnyyLD+bEhPsBZ+fQQAIzAD6V2JGqpIGpNpqlmUpbcQgx9jWukZ1NLWGqTMAAAJDYEZEKBiYoY9rG7xuA/0gZ+EU55UijdH0B/+bbIe8jNHel9eoYv0X4W0QAIBesEoGIsLbk8d73QL6k+kxv92y5Pf7YQAAIhCBGRGCLzsAAEBkIqUAAABJJy8CFIhrhgzSt4cOCmjsy+XV+rj2RNA9AZGAwAwAQAyr+Wyfmspr7GHYki76wdXaufKPtrGNFccCeszpmem6NXuYAonYW+oaCMyIegRmAABiWEtNvVpq6h1102l0bGexBx0B0YfAjLC7feRw3T9mpK2WnuBT+eypPUYaLT1YqueOVIWvOSACjSiYqLxr8gMaW/LWJyr76PN+7ggA4guBGUHZ+PfPBn3fDJ9PI5KSHHVnzSjdx3mpsLPk/BK461oLPf+1GMXGVd0TkpOUfFZ6YGNTnPsWAKBvCMwIimnv8LoFxKl/HJ2lR8eN8rPFUvv8S2yVf9hXoicPV4SnMQBAzCIwA4g61mlPNGJtZwBA6BGYAUQpwjEAIDyYIAoAAAC4IDADAAAALgjMAAAAgAsCMwAAAOCCwAwAAAC4IDADAAAALgjMAAAg4liSyvOnet0GotDMx28L+WMSmAH0K9PRqc6WNnU2t3b/yBjb7c7mVnW0tMl0dHrdLkJo1lO3e91Cr2atWOJ1C3CR7iOm4Mz5kkJ/mREuXAKgX5W8vUklb2+y1Wat+KE2/t1KjzpC2ETBtWWioEUAEYCPbgAAAIALAjMAAADggsAMAAAAuGAOMwAAOCP/UVOn4+0dttq/nDNa/+tAiWPsxroT4WoL6DcEZgCIQ98bdrZuGH62rZbs8+l3E8bbar+rqtG/VdaEszVEgY11JxxB+CdjRurJwxUedQT0LwIzAMShizLS9J1hgx31nrWdjU3hagkAIhZzmAHAj12XTvK6BQBAhOAIMwD4MTo12esW+tVPi4/osZIyGX2zFnH57GnKKvzUNq6l04S9Nzfll05V1qZtXrcBIM4QmAHAj1i/oEWrMWrt6BmGjeoj/GqLmSl8MQog/AjMAOJeZoJPmQkJtpolKSc5yVar6+jQiQgPlECgWmsbvG4BiBoEZgBx78d5ObonN9tRL82fYrt9/8FSPVx8JExdAf1ry30vet0CEDX4bitODJqQ53ULQOQyRjLSyePKbj/wWmTNqAYQLwjMceLC277tdQsA0Gd8bAHgBaZkxAkrgt5m1h6v1z09rgb10JiRWlpU2uPokdHHtfXhbA0AAMCBwIyw21TfoE319pNN7svL0aOHyjzqCEA8GDJlnIZOP9dW8yUm6Pz/fqVjbMWGnTq+61C4WgMQ4QjMAKIUs1njUV/+1tNzhmjYpRc46v5qdfuOEJgBdCMwAwCiRngmlxkmSwdh0pYvg77vLdlDdXdujr1oSRmJPu29bLKt/EjxEf26vDro5wKCQWAGEH5W8GlkxeEK/bKsylbzSTo0a4pGbfzMVm9izWQEjW8wztSB5pag7zsoMVHj01Lk75PK+LTUHmMTHGOA/kZgjjWWJSuh5wvOydtWon1RFNNhTi6nFQEGfbzV6xYQRhvv/HnQ920xRi3tHbaapZP/lGt71AEACAUCc4zJWThF59w4z++22b+403b74O/Xq/Q/t4SjrV4Rc+JMhHxQAwAgEKzDHMeYogcg2vBRC4AXCMwAgKjBB30AXoj4KRnDZl6oqj/t8roNAIh5L7HyAOC5vx4xRP9acdTrNqJGxqhhGpA33FazEnwaMXtCj5FGdQfK1FR2LKjnifjAPG7xnxGYASAMbv+q2OsWgLj3i/PyCMxn4OzJY5V3bb6jfu5ff6tHxWj/Kx8EHZgjfkoGX78hUoz/qz/zugUAAOCBiA/MQKQYfpnzamAAwouT/gB4gcAMAIgafOsIwAsEZgAAAMBFxJ/0B3hh1JUzlHv1TFvNl+BT/i/usNUsSftf/Ujl63aEsTsg9t2WM1Qrzs11zMFIsiy1zJ1mqz1YVKZHDpWFsTsA8YbADPhh+Sz5EhMcdWfNyLL4khgINZ8sJVsJzjkYRkr2JdhuO/dUAAgtAjPQVxanIQH9x3K9yWmAAMKBOcwAAACACwIzgF7dNPxsr1sAAMAzBGYAvfrl+WO8bgEAAM8QmAH0jhMbAQBxjMAMAAAAuCAwAwAAAC4IzAAAAICLyFuH2d9cSX81w9qbAAAA6H8RFZhzr56p3G9f1qNqac4zdzrG7n15jSrWfxGexgAAABC3InNKhmWd8tPzNmfrIzBjU1O8bgEAAMSAiDrCDITSFzMmKuPjrV63AQDwQF5qskalJPc67lBzq0paWsPQEaIZgRlATHi9usbrFgBEkB/kDNc9udk6+VX16d1/8LAeLj4SnqYQtSJzSgYQApwWGj+MpL/ZfdDrNgBEEmN4I0DIcIQZQLcFgzL1nWFnO+oplk8/PzfPVnuj+pjeO1YXrtYAAPAMgRkxi9NDz9zkAelaMnKE320964eaWwnMAIC4QGAGAPTZ8JkXKmfhFFstISlJU3+8WKbHuvml73+qqk17wtgdAPQNgRkA0GfJZ6UrM8/57cSA3OG220ZSUmZ6mLoCgNAgMCPq3ZI9VD8bn+eopyX41FAw3VZ7uPiI/uVQWbhaiz5G6vRzlowl57kzxuJsGtjxLwJArCIwI+olWpbSE3zyN2s5PSHhmxvGKImJza6eKq3QU6UVtpolqW7udGWuY01rAEB8Ylk5xBcOgZ0x/sgAAPGOwAwAAAC4IDADAAAALgjMIbBk5PDeBwEAACAqEZhDYNm40V63AAAAgH7CKhkAAAC9+M6wwbpp+JCAxj5fVqX/rKnt544QTgRmAACAXlyYnqbvDDs7oLEfHK/r524QbkzJAAAAAFwQmEOAdWoBAABiF4E5BLh4HAAAQOwKeWDOSk4K9UMCAAAAngn5SX97Z05W5rqtoX5YAACAwFmW5Ivc74CHJSUqJyXZVrMk+WTp4gHptnpZS6sq29rD2B16YpWMEGAOMwAAkWV3Y7PerD5uq/35kIF656h9ube9Tc1h7Oobi0cM0c/G5/nd9tklE2237zlQomWHysLRFk6DwBwCkfv5FQCA+PRiebVeLK+21RrmTtfVO77yqCNEM076i0APjRnpdQsAAAD4GoE5At01eoTXLQAAAOBrBOYQYA4zgN5M/NF1XrcAxD3erxEsAnMIMIcZQG/OOifb6xaAuMf7NYJFYAaAcODQFgBELQIzAAAA4IJl5TyW7vMpI8H+ucWSpeFJiY4DUic6OtTUyWEqAACAcCIwh0BfIuxdo7P08NhRjnrF7GmO2pK9RVpZWtmHZwMAIH5xyAnBYkpGCHASAQAAkY/3awSLwAwAAAC4IDADAAAALpjDDAAAPPV2Ta0q2toUyKSJzXUn+r8hP1ZXH9OhllZb7ZfnjdGtXxU5xn7iUY/oPwTmEOAkgihhSbKYwQYAkebLhiZ92dDU78/Tl/fr7Q1N2t6jx5Xn5upfy6v71hSiAoE5BCIpglVu3KljXxY56lN/vFjbfvobW62tvv9fnMLhlcoafXi83lH/9JKJmrblC1utqq09XG0BACJMJL1fI7oQmGNMe2OL2htbnBuM1FR+LPwNhcHx9g4db+9w1I0x2t3Y7EFHAAAglhCYz5BPks/PR9TEHrVOI3WGpSOcDlNlQqfd8KcJIPrxSoZgEZjP0CPnjNTdudm2miVLrfMusdWWHizVw8Vl4WwN6DeDP/7U6xYAAPAMgfmMWbJOnj3mqPYcB2/xNwAAONW+Jj9TFmNc6vBBaq487nUb/aa9oTmwKaeWUXtja+/jToPAfKaMOfmdDmkMQJi0HqtX7Z4SR33guSNVu7fUVmupcZ4AC+CkKZu/6H1QjJl2319pwx2/8LqNflO2drvK1m7v9+chMCNmMVcNsaL6032q/nSfo56/Yol2PPG6Bx0BQHwhMCNm9eVLgLp9pSp56xNbbdSVl+jwf2xxPEl9cWUfngkAAEQ6AjNi1g/3Fgd939qvSlX7lf2r7pGXT1Px6o19bQsAAEQZAjNi1q+5+hICZVlffyXBRB4AgJPP6wYAAACASMYRZgBx7yfFR/RESbmtdnDWFI3d+Jmt1tDB5YgAfGPsn/p/dYZ4cMlP/lZb7n3B6zZcEZgBxL0THZ064QjDRpVt7Z70AyA6VPEaERJJmWlet9ArpmQAAAAALjjCDAAhlpieosT0VHvRspQ6dKBjbNuJJnU0B3/1KfQXrk4F4BsEZgAIsez5Fyvv2nxH/ZKf/o2jtv83H4TlKlWQWo7Vq26ffbnIs87JVt2BMsfY1tqGcLUFIAoQmAEAcaFy4y5Vbtxlq+WvWKLty3/rUUcAogWBGQD8YEVmANHmrHE5Omtctq1m+XwadcV0W63uQJnq9h0J6jl+NGqEfna4Iqj7ZowepkEX5jomPPkSnD3W7juiej/f/niFwAwAABADBl2Uq9yrZjrqY75T0P3fxhiVvL0p6MD88NhRQQfmzHOyNfaUXk7XoyQVr94YUYGZVTIAwA9O+eovHLsHvGbYD89Y3B1htiStnXKh5n62q9exAIDAVGzcpeO7S2y1yf90g2N+sJFR67ETATxi10eWAN7Y+XQDoJ/FXWCWpCkD0r1uAQBiSlt9o9rqG201Y4xOHKrs3ye2uv8HAPpNXAZmIDh8hQWEy/NllXqxvNpWsyRVzZ6qoYXbbPU2w74JoH8RmIEAbbhzpdctIIyIYN5qN1K76Xm58pN/L02dzjqA0EuyLCVb9m9wLEkDEnw69XNqmzFqjfEPrgRmAPCDL/kjE38vQPj8bfZQ/e+8HFstLcGnLy+dZKv9qqxKDxUFt+pGtCAwA4AfsX2sJHrx9wKEz3NHqvTckSpbrb5guvI2fu5RR96J6cB8bmqKJmak2Q5JWJISLem6oYNsY3c0NGlfU0tY+wMQufpyJLOx/Jiqt+2z1YZOPkfV2w84xjZX1/bhmeIPR5gBeCGmA/NfDh2sZeNGS1bPYxKWfj9xvK1y174SPRnkQtwAcKqjn+7V0U/32mr5T92u3c++6VFHAIC+iOnALOvrH7/XZ+E4BQAAAHrHlf7OlGVFZdbe/at3vG4BAAAgKsX2Eeb+YoUuMb9QVqV3a+xzGNdOvUDztu12jC1qDn6Odc3nzrmTAAAA6B2B+Qz9y6EyrSy1X7lq92WTdcEn22212vaOgB7vSGubjrS22WrnfbJDJS2tfWsUAAAAIRHTgflnhyv07JFKGX0zi8KSpdL8KcrZsM1Wb+4MbLGi4+0dOt4jDHfK6FAIAy5hGfAey5dFJv5eAHgh6MCcKCnJ13NqgiVLUlqPepsxavfgVa7NGLV12J/YkmSMVN8RuitFReGUZgC9YL+OTM1c5Q+AB4IOzEtyButn43MlX1KPLZYa5063Ve7Zf1jLSsqDfSoAgB+ttQ1etxB2Qwu3ed0CgDgU/JQMX7LkSznNRueRZwBAaG2570WvWwCAuMCyciHAnDog9rBfx4eaL4u8bgEIO4sDmWcspk/6Cxf+2QGxh/06Pux+7i2vWwBC5kRRhco++txWyy6YpLKPd/QY58002cYjRx39nc6J4si6+nJ4AjPvPAAAAP2qZsdB1ew4aKuNyL9I+1/50KOO7Or2lqpub6nXbQSl74GZMAwAAIAYFnRg/m1ljbbWO8/QfvfiC3TF5/ar1PXlCnXRgLmOQOxhvwYAdAk6MPu7Qp0kdchofe2JPjUVbTjIDsQe9msAQBdWyQAAAABcsEpGCLQEeFltAAAASeowUosJ7MqVHYac4TUCcwicvf5Tr1sAAABR5OelFfp5aWQtnYbTY0oGAPjB8RwAQJeIOsLcXHlcx3YW69TTbQZdmKvjuw71GGnUeqw+rL0BiC+c9Nd3x3eVeN0CAIRERAXmyk92q/IT+5J0s1b8UF+u+HePOgIABGvXM3/0ugUACAmmZAAAAAAuCMwAAACACwIzAPjBSX8AgC4EZgDwg5P+AABdCMwAAACAi4gPzKYjsKvgAEAoMSUDANAl4gPzn/5+pdctAAAAII5FfGAGAC8whxkA0IXADAAAgIB8fDw+r7RMYAYAP5jDDABOf7HjK69b8ASBGQD8ePRQmdctAAAiBIEZAPx4uOiI1y0AACJEnAZmvmwFAABAYOIuMBtJMz/d6XUbAAAAiBJxF5glaWdjs9ctAAAAIEpYxpiA5idYVmCrkqZYlloCe0ggZgW4W3ku0P0afWclJsi0d3jdBvqA/RrRiNced4Hu1yEPzAB4YwViEfs1EHsC3a/jckoGAAAAECgCMwAAAOCCwAwAAAC4IDADAAAALgjMAAAAgAsCMwAAAOCCwAwAAAC4IDADAAAALgjMAAAAgIuAr/QHAAAAxCOOMAMAAAAuCMwAAACACwIzAAAA4ILADAAAALggMAMAAAAuCMwAAACACwIzAAAA4ILADAAAALggMAMAAAAuCMwAAACACwIzAAAA4ILADAAAALggMAMAAAAuCMwAAACACwIzAAAA4ILADAAAALggMAMAAAAuCMwAAACACwIzAAAA4ILA3E9efPFFWZbV/ZOamqqcnBwtWrRIK1asUH19vd/7FRYW6rrrrtOIESOUkpKiMWPG6LbbbtOhQ4ds45YtWybLsrRt2zZb3RijwYMHy7IsHTx40LatublZKSkpWrx4cXetq7/HH3/8tL/Dli1bgv1jAGIK+zUAfx544AFZlqXq6mq/2ydOnKj58+dLkoqKimyvIwkJCcrNzdV1112nzz77LHxN44wQmPvZQw89pFWrVumZZ57RHXfcIUn60Y9+pEmTJmn79u22sU8//bQKCgq0Y8cO3XHHHVq5cqW++93v6tVXX9XkyZO1YcOG7rFz5syRJK1fv972GF9++aWOHz+uxMREFRYW2rZt3rxZra2t3fc91fLly9XY2BiS3xmIdezXAPrqpptu0qpVq/TCCy9o8eLF+uCDDzRz5kxCc6Qy6Be//vWvjSSzefNmx7Y1a9aYtLQ0k5eXZxobG40xxqxfv974fD5TUFBgGhoabOP37dtnRowYYbKzs01NTY0xxpiWlhaTmppqbrzxRtvYZ5991gwZMsQsWrTI3HbbbbZtjzzyiJFkPv/88+6aJDNlyhQjyTz++OMB/w5APGK/BuDP0qVLjSRTVVXld/uECRPMvHnzjDHGHDx40Egyy5cvt41ZvXq1kWRuvfXW/m4XQeAIswcWLlyo++67T8XFxXr55ZclSQ8//LAsy9JLL72k9PR02/hx48Zp2bJlKisr03PPPSdJSk5O1owZMxxHmwoLCzVr1izNnj3b77ZBgwZp4sSJtvrs2bO1cOFCLVu2TE1NTaH+dYG4wH4NoC8WLlwoSY5pV4gMBGaPfP/735ckvfvuu2psbNSaNWtUUFCgsWPH+h3/ve99TykpKXrzzTe7a3PmzFFpaamKioq6a4WFhcrPz1d+fn7317jSyTmQGzZs0KxZs+TzOf/aH3jgAVVUVOiZZ54J3S8JxBn2awDB2r9/vyRpyJAhHncCfwjMHhk1apQGDhyo/fv3a+/evWpvb9fFF1982vEpKSk6//zztWvXru5az/mO5eXlOnDggGbPnq3LLrtMPp+ve37kzp07dezYMb/zHCWpoKBACxYs0PLlyzkaBQSJ/RpAoBobG1VdXa2KigqtXbtWN998syTphhtu8LYx+EVg9tCAAQNUX1/ffWZ9Zmam6/jMzEzV1dV1387Pz5fP5+t+Yy0sLFRSUpJmzJihAQMGaPLkyd1f33b9/+neWKWTR6PKy8v17LPP9un3AuIZ+zWAQCxdulTDhg1TVlaW5s+fr/379+vRRx/V9ddf73Vr8IPA7KETJ04oMzOz+w31dEtSdamvr7e9+Q4aNEgTJkywvXlOnTpVaWlpkk6+8Z66LTk5WZdeeulpH3/u3LlasGABcx6BPmC/BuCPZVm227feeqvee+89rVmzRlu3blVlZaXuvvtuj7pDbwjMHjl8+LBqa2s1fvx4jR8/XomJiY7lqE7V0tKiPXv26KKLLrLV58yZ0z2nsWueY5f8/Hxt2rRJbW1tWr9+vaZPn67U1FTXvpYuXary8vLuk5AABI79GohPXfvg6T6UNjY2OvbTc889V5dffrkWLlyoadOmKSUlpd/7RPAIzB5ZtWqVJGnRokXKyMjQggULtG7dOhUXF/sd/9prr6mlpUVXXXWVrT5nzhwZY/T+++9r27Ztmj17dve2/Px8NTU16a233tKBAwdcv7btMm/ePM2fP1+PPvooR6OAM8R+DcSnvLw8SdKePXsc2xobG1VSUtI9BlHK21XtYlcg67WOHTvWNDU1GWOMWbt2rfH5fGb+/Pnda7h2OXDggMnKyrKt19qluLjYSDKzZs0ykkxpaalte3Z2dve2N954w9GLJLNkyRJb7aOPPrKt48p6rcBJ7NcA/KmoqDDJycnm+uuvNx0dHbZtTz75pJFk/vCHPxhjTr8OMyJbYvgjenx55513tHv3brW3t6uiokIffPCB3nvvPeXl5Wn16tXdX9HMnTtXjz32mO666y5NnjxZN998s7Kzs7V79249//zz6uzs1Ntvv63BgwfbHj83N1ejR4/Wxo0bNWbMGOXk5Ni25+fn6/XXX5dlWbajVG7mzZunefPmae3ataH5QwBiDPs1gFMNHz5c999/v+69917NnTtX11xzjdLT07Vhwwa98soruuKKK3T11Vd73Sb6wuvEHqu6jkR1/SQnJ5usrCzzrW99yzz11FOmrq7O7/3WrVtnrr32WjN06FCTlJRkcnNzzS233GKKiopO+1w33XSTkWQWL17s2PbEE08YSebCCy/0e1/5ORJljDEffvhhd+8ciQJOYr8G4Obll182M2fONBkZGSYlJcVccMEF5sEHHzTNzc3dYzjCHJ0sY4wJe0oHAAAAogQn/QEAAAAuCMwAAACACwIzAAAA4ILADAAAALggMAMAAAAuCMwAAACACwIzAAAA4CLgK/1ZltWffQAxJVqWN2e/BgLHfg3EnkD3a44wAwAAAC4IzAAAAIALAjMAAADggsAMAAAAuCAwAwAAAC4IzAAAAIALAjMAAADggsAMAAAAuCAwAwAAAC4CvtJfoFJ9lpo7o+NqSACA+OZLSlBnW4fXbSAKWD5LVkJCQGM7OzqkILMQOSoyhTwwV82Zpsx1W0P9sAAA9IkvJUmJqcm22iU/+RttuffXjrHtTS3qbG0PV2uIAqOunKG8a/MDGrv/Nx+obO32oJ6HHBWZQh6YAQCIRCP/bKrfwHPpslsctb4EHgCxhznMAADYGMnyugcAkSToI8yTM9I0e2Cmo55kWfpBznBbbWPdCX12ojHYpwIAIMyYQwrgG0EH5gWDz9LPxuf53bbyvDG22/ccKCEwAwAAICqFZ0oGH9QBAAAQpZjDDAAAALggMAMAAAAuWFYOAAAgzH6QM1yPnDPKUc/w+XRszjRb7YGiUj11uCJcrcEPjjADAKLG9MecayYD0SjZZ2lQYqLjx5KznuIjrnmNvwEAQNRITknyugUAcYjADAAAALggMAMAAAAuCMwAAACACwIzAAAA4ILADAAAALggMAMAAAAuuHAJACDiDL3kPOVedZksWbZ6QlKSpj/w17bakQ8/U9na7eFsD0CcITADACJOYnqK0rPOlmVZjm3p2Wd3/7eRlDggLYydAYhHBGYAQMTpCsqml3HGGBnT2ygA6JugA3NzZ6eOtrWrx7dlOjsxQTXtHbZak+kM9mk0ODFBx3o8HgAgDvg5ugwAXgg6MD93pErPHaly1OvnTtfQ9Z/2qalTHZ55sTJC+HgAAABnqr2hWU3lx2y1tOGD1FR53Dm2qaXXxzve3qE9TU2O+rlpqdrb1Gyr1bS1n1mzCDmmZAAAAPSibO12x8ml+U/drq1LXwrq8V4qr9ZL5dWOev3c6brgkx1BPSb6D8vKAQAAAC4IzAAAAIALAjMAAADggsAMAAAAuIiok/5uzxmu/5kz3FZLTUzQ9ksm2gdaRg8WHdHrVfazVQN18T3f0+ePvhpsmwAAAIgjERWYRyQnatKANPVc3HnSgPQeI43OTgy+9fScIUHfFwAAAPElSqdksJg9AABAb47OmeZ1CzEhoo4wR6uzEhJU18HVCAEAQGRJ9cX2QUYrMUG+pITeBxqps61dpiO4q08TmEOgbPYUZazb6nUbAIAQMF//AIh8o66Yrrxr83sfaIz2v/KBytYGd1EYAjMAIC60HKtX3b5SW+2sc7JVd6DMVjPGqPV4QzhbA9DPjEyfPggTmAEAcaFy4y5Vbtxlq+WvWKLty3/rUUcItyFTx+votn1et9FvJmak6aKMNFstwbJ04/CzbbWdDU36oqEpnK15zrIsWX2YnUJgDgG+ugMAIPKd/zeLtCHCA/PPSsqDvu8Nwwbr/jEjHfVXLxp3yi2jh4uP6IuD8RWY+ypKV8kAAACIPfcdLO190GkFcAjVWBzpCwJHmEMgts8/BQAgRsTFG3Zvv6QJYAx64ggzAACISJP+8QavWwAkcYQZAOLSyMunKefPer+gwZEPtqn0PZbNhDcGjB7mdQuAJAIzAMSlhLRkpQwe0Msoo8S05LD0A0QnJgPHCwLzGUq2LCWdui7J1/+Z4bPPbmk1Rm2GHQlABOtlGqMxUieBALEkxP+cN/zdM6F9QESskAfmw82toX7IiPLQ2JG6JzdbPd9pTsy9xHb7/oOH9XDxkTB2BgAAXHGuG4IU8pP+LtwU3CUHJUmW9fWPev/xijF8AwMAARiQO9zrFnp14lCF1y0gnHj/RpAiakrGroYm/b6qxla7ZshgrT56zDH2YHNLuNoCAARh0j9+VxvvXOl1G662P/Y7r1tAP0nPGaK04YNsNcvn05Ap42y1xvIaNZU7cwZwqogKzP9WWaN/q7QH5oY50/SdLyL7qjwAACCyDL/sAo26coajfuEPrrbdLl69USVvfRKuthClWIcZAAAAARn9l7O9bsETBGYAAAAEZOSCi71uwRMEZgAAAATE6oeFFybc9d3QP2iIRdQc5lDLKpik0X/unL+UkJKkGY/8ra126K1PVFH4ZbhaAwAAgKSzxkb+ijoxHZgTUpOVcnam349DKUPOst1OTOVqVgAAAHBiSgYAAADgIqaPMAMAgPjU0dyq1uMnbLXkgRlqrW1wjAN6Q2AGAAAxp+SdzSp5Z7Otlv/0Em265/961BGiGYEZAADEBy6NfUZShw5UWvbZtprl8+nsSWN7/FEaNZbVqKW6LpzthRWBGUBM+O/ZQ/Wrsmqv2wAQhIzRw5Q5NttRtxJ8ypo72Var239EjaVB7uv9sCRaLBs6bbzGfqfAUZ/ww2ttt42MDry2TkfWbAtXa2FHYAYQ9SxJT47LjbvAnHfNTBWv/pPXbUiSBp47UoMnjrHVfAkJGnP9HMnYj0XV7Dioun1HwtgdIt2gC3M15npnMJOkcYsX2m4f/O3a4AMzzhgH5U8iMAOIEfF36Gjk5dMiJjBnjs3S6Cud696PXnSJ7baR1FrXSGCGH6bXq2JYisc9PRrE/t8KgRkAolZkvUlxJApBM+H512w6w/AkiEmswwwAAOLCtodXed0CohRHmAEAQFxojuFVHOLV4Xe36siHn9lqly27RZ/c/X/V83uvztb2oJ8n4gPzWes/9boFAAAARCDT3qGO9o4eRamjqSWkzxPxgbmj9yEAAI91tLarra7RVkvKTFNbfZNjbGdb8Ed5AMALER+YAXgvLftsNZXVeN0GIljZR5+r7KPPbbVZK27XJ//0S486AoDQ4aQ/AL2a+s83ed0C4lHPZTeMnxoAhAFHmAEAp2V5tHRdY1mNygu/cNRHzLpQFRt32ccergpXWwDiFIEZAOJQ7Z4SHeq0H64d/e1LVfLWJvu4vaXhbOub5/3qsGq/OuyoD7v0PO1b9b4HHQGIZwRmAIhDtV+VqvYrexgedeUlOvTWJx51BACRi8AMABFuyNTxyp53saPuS0zQxB99x1YrX79D1Vu+CldrABAXCMwAwm7Kj/9Kn/30/3ndRtRIOTtTgy4Y3aN6cjpFz/rxXcVh6goA4geBGUDYpY0Y7HUL0cdx7p03J+MBQDwiMAOIKj5Jvh5ZsWslh8Qe9Q7DKmQAgL4jMAOIKv8wOkuPjus5PeFkaG6dN8M+dt8hPXm4IlytoYf2htBemhYAvEJgBhB1rFP+115nmkIk2fzPv/K6BQAIiZgOzC3H6v2s42lp4Lk5jrVFW46dCPBReUMGAACIJzEdmKu3fOV3eaVZT92uHU+8HtyDWnJOoASAGFC5aY/XLQBARIrpwNwf1hyrU6uxn0b0v3Kz9S+Hymy1j2vrw9kWAPQZV9AD0J8G5A7X4IljHHVfQoJG/8WltlrtV4dVt+9ImDrrHYH5DL13rE7vHauz1f5hdJbuP+jN5WMBAACiQeaYLOVdM0uynN/U512b3/3fxhgdWr0xogKzz+sGAAAAEAcs+Q3L/kTakqAE5hCYsWWn1y0AAACgnxCYQ2BnY5PXLQAAAEDS5h+/EPLHJDADAAAgZrTVh/5AJoEZAAAAcEFgBgAAAFywrByAbskDM5QydKDzepaWpbPG5dhKzUfr1Ho80CtkAgAQvQjMALoNmX6ezrlxnt9VfybffaPtdtHv1+vwf27p9THTc4YoPWeIrWb5LA295DzH2BNFFWqurj2zpgEA6GcEZgBBCXSNzKHTz1XuVTN73Nnogv/x5/b1OI3R3pfXqHk9gRkAEFmYwwwEaOwNc71uIXr1uJy8LCvgxesBAJEu0i4zEnocYY5Av50wTjd8ud/rNtBDdsEkHfztOq/bAOLa7ufe8roFIG5Ub9unxrIaW+2C276t3b98y5GRG8qOhrGz8CMwR6A/P3ug1y0AQEQ69kWx1y0AcaO5qlbNVfZpcqazUzXbD3rUkXcIzB67c9QI3Z2bZaulJSTocP7FjrE/PnBYL5XH9ic4AACASENg9thZCQkamZzsqPurZSQkhKMlILSMZHrOYfY7zjjnOgMAEAEIzAD61aE3/6RDb/7JVpu14ofaeOfPPeoIAIAzQ2COCKwWAAAAEKniclm5E0WVXrcAAACAKBGXgXnHk7/zugUAAABEibgMzAAAAECgCMwAAACACwIzAAAA4IJVMgA/RuRfpKy5k2w1X1KiLv5f33OMPfzuVh39dF+4WgMAAGFGYAb8SB40QJljsx11Z80o+ay08DQFAAA8wZQMAAAAwAWBGQAAAHBBYAYAAABcMIcZgIPxugEAACIIgRnANyxLkiWZACIzqRoAIoslyerlxfnrl3mcGQIzgG6NpdUqW7ddVmenrZ41d6LK131hqzWUVIazNQCxzArsMzg5z93muhNaWWp/bb4le7ieL7PXNtWdCGdbMYHADKBb7e5Dqt19yFEfkX+R9v/bhx50BCAe1H51WEX/Xuio5149S4f+uNE+dt+RcLUVdd48Wqs3j9baajdnDdWSr4pD9hzFqzf2PigGEZgBAICnThRV6ERRhaOe+xeXqvQ/t3jQEU7nyPvbvG7BE6ySAQAAALggMAMAgIj06cMve90CIInADMADm+75pdctAIgCLdV1XrcASCIwA/BAR1Or1y0AABAwAjMAAADggsAMAAD6LC3rbK9bAPoNgRkAAPTZlH++yesWgH5DYAYAAABcEJgBAAAAFwRmAAAAwAWBGQAAAHBBYAYAAABcEJgBAAAAFwRmRISa2RND/piWzwr5YwIAgPhDYEZESPKlhPwxZz71g5A/Zrxqa2j2ugUAADxDYAbQq83//CuvWwAAwDMEZgAAAMAFgRkAAABwQWAGAAAAXBCYAQAAABcEZgAAAMAFgRkAAABwkeh1AwAAILqMumK6Rn5ruq2WkJKoy5bf6hh74HfrVPXJ7nC1BvQLAjOC4pPU6XUTp7L8XNXP8lM3JiztACFljNQZ4B7Hv3GEgS8lSUlnpTvq/mq+JKIGoh//ihGU+oJpyvj4U6/bkCRlzZuscTctkL8LYc955k7b7eI//kklb30SnsaAEDnywWc68sFnXrcBAHGLwBwnUoacpZajdaF7QH9HdAM0MDFBQxLt//R8ksalpqjnsbGjbe2q7ehwf0BjTobl3nriyBsAIM4cbGr2uoWYQGCOE9OXfl8b7vyF121Ikm7NHqZl40Y76vtmTnbU7tp3SE8ernB9PMuyAgrwRpIhNAMA4sjEzV963UJMYJUMeMQK4AeIHUOmjfe6BQBAkAjMABAG5//NlV63AAAIEoEZAMKB6UAAELWYwwz4UbXlKzWUVNlqF972be167i37QEtqKK0OY2cAACDcCMyAH82Vx9VcedxW++xfXlXD4Sr/dwAAADGLKRlAgAjLAGLJJQ/9N69bAKIGR5gBAIhhWQsnaez1cyRjP0aWkJSoWU8vsdWK39ioI+9HxkWpEKOM6dO1HLxCYAYAIIZZSpQvMcVvRklITrKPTeCLZ/SfzvYOdbS0ORaO9aUkqbOlzV7s6AxbX4EgMHustr1Dh1pabLVRKck63NLqGHuivZcr3gEAEAYdTa1qqbFfPTZlcKZajtU7xjqCEOJWReGXqih0Xkhl1tO3a+PfrfSgo8ARmD32dGmFni61X8nuRME05W383KOOAABwV/r+pyrtMXVj1lNLtPmfX/CoI6B/8d0LAAAA4IIjzDEmY/QwDTxvlKNuJfiU82dTbbW6faU6UVwZrtYAAACiEoE5xgw8b5TOuXGe320960W/X09gBgCERNG/r/e6BaDfMCUD3rBM7z+AKxPAT/D+30Xj+tgfEF/KPuLcG8QujjBHoPmf7fa6hX71csVRrT1uP5P6oykXasHnu2R6ZJxDflYLAcLhL4cO8roFAECEIDBHoC31jV630K/KWttU1mpfZqhDRp/UNXjUEaLJc0cq9Wplja1mWdIXMyZpwqYdtvqx9vaAHvOe3Gz9YORwWy3V51PRrItttSdKyrXisH1VGwBA32y9/1+9bqFXBGb06n/n5eie3GxZ+uZL7jSfT7UF023jlh8q00+Kj4S9P8SXuo5O1XXYv3mwdPLiUcF+IzE4MUF5KclfP9I38lJSbLcHJiQE9Hgjr5iu0d++zFbzJSdq5lO3O8Ye/O06Vaz/4swaBoAY0nrshNct9IrAjF6lWJbO8hMUbDVjlByFl7oE+oMvMUGJqcmOur+ajyurAUDE45UaAAAAcEFgBgAAAFwQmAEAAAAXBGYAAADABYEZAAAAcEFgBgAAAFwQmAEAAAAXrMOMABh9c8mS07DU85oPAAAAMYHAjABYjrh86lX/IoIxJ6+PDEQIY+x7iGVZjhoAIDoQmNGrB4pK9VBRqa1WN3e6zlq31VbrDGdTpzhtCOkRoi2dDC1Afyt5e5NK3tlsq+U/dbs2/Gil85MmIRoAIh6BGb0ykjr81P3VvNDZ1qHW+iZHPWlAqtp61Dta2sLVFuKdvyDcSTgGgGhEYEbUq9y4U5Ubdzrqs56+XZv+6ZcedAQAAGIJq2QgZh3fXeJ1CwAAIAYQmBGzdv3ij163gDAxkv61otrrNgAAMYrADCAm/HBvsdctAABiFIEZAAAAcMFJfwgOJ/sjhvzySJX+s6bWVnv74vP1F5/vsdUONrcE/RzsMgAQvQjMMaZy404d+7LIUZ/648Xa9tPf2Go9l1w7E1O3fBn0ff2ZHuLHA87EgeYWHegRhjuN0YfH60P2HJ/12P8AANGDwBxj2htb1N7o5yiYkZrKj4Xseb5qag7ZY/XH4wGRpqkidPsfACC8mMMMAH4whQIA0IXADAAAALggMAOAH5bXDQAAIgaBGQAAAHBBYAYAP5jDDADoQmAGAD+YkgEA6EJgBgAAAFwQmAEAgCS+WQFOh8AMAH4whxkxw5iTPwCCxpX+AMAPjrQhVlSs/0LVW/b0qFqa8dO/0eYfv2CrdrS0ha8xIIpYxgT2sdOyePuIZlZigkx7h9dtxI0AdyvPsV+fXoplqSVK/h4RHrG2X/O+AAS+XxOYgX4Qa2+sANivgVgU6H7NHGYAAADABYEZAAAAcEFgBgAAAFwQmAEAAAAXBGYAAADABYEZAAAAcEFgBgAAAFwQmAEAAAAXBGYAAADARcBX+gMAAADiEUeYAQAAABcEZgAAAMAFgRkAAABwQWAGAAAAXBCYAQAAABcEZgAAAMAFgRkAAABwQWAGAAAAXBCYAQAAABf/H/ME/DA+kwzZAAAAAElFTkSuQmCC\n"},"metadata":{}}],"execution_count":23},{"cell_type":"markdown","source":"## Data Augmentation Strategy\n\nAugmentation is applied to improve generalization while preserving semantic meaning.\n\nApplied:\n- Small rotations\n- Horizontal shifts\n- Vertical shifts\n- Zoom\n- Brightness variation\n\nExcluded:\n- Vertical flip (would invert price-time semantics and destroy trend information)\n","metadata":{}},{"cell_type":"code","source":"augmenter = ImageDataGenerator(\n rescale=1./255,\n rotation_range=10,\n width_shift_range=0.05,\n height_shift_range=0.05,\n zoom_range=0.1,\n brightness_range=(0.9, 1.1),\n horizontal_flip=False\n)\n\naug_gen = augmenter.flow_from_directory(\n train_ds_path,\n target_size=IMG_SIZE,\n batch_size=BATCH_SIZE,\n class_mode=\"binary\",\n shuffle=True,\n seed=SEED\n)\n\naug_images, aug_labels = next(aug_gen)\n\nplt.figure(figsize=(9, 9))\nfor i in range(9):\n ax = plt.subplot(3, 3, i + 1)\n plt.imshow(aug_images[i])\n plt.title(\"UP\" if aug_labels[i] == 1 else \"DOWN\")\n plt.axis(\"off\")\nplt.show()\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-01-04T09:46:22.362641Z","iopub.execute_input":"2026-01-04T09:46:22.362942Z","iopub.status.idle":"2026-01-04T09:46:23.626017Z","shell.execute_reply.started":"2026-01-04T09:46:22.362918Z","shell.execute_reply":"2026-01-04T09:46:23.625067Z"}},"outputs":[{"name":"stdout","text":"Found 1433 images belonging to 2 classes.\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{}}],"execution_count":24},{"cell_type":"markdown","source":"","metadata":{}},{"cell_type":"code","source":"train_gen = augmenter.flow_from_directory(\n train_ds_path,\n target_size=IMG_SIZE,\n batch_size=BATCH_SIZE,\n class_mode=\"binary\",\n shuffle=True\n)\n\nval_gen = ImageDataGenerator(rescale=1./255).flow_from_directory(\n test_ds_path,\n target_size=IMG_SIZE,\n batch_size=BATCH_SIZE,\n class_mode=\"binary\",\n shuffle=False\n)\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-01-04T09:46:23.627384Z","iopub.execute_input":"2026-01-04T09:46:23.627669Z","iopub.status.idle":"2026-01-04T09:46:23.683284Z","shell.execute_reply.started":"2026-01-04T09:46:23.627629Z","shell.execute_reply":"2026-01-04T09:46:23.682392Z"}},"outputs":[{"name":"stdout","text":"Found 1433 images belonging to 2 classes.\nFound 351 images belonging to 2 classes.\n","output_type":"stream"}],"execution_count":25},{"cell_type":"markdown","source":"## CNN Model Architecture\n\nDesign principles:\n- Progressive feature extraction via convolution blocks\n- MaxPooling for spatial downsampling\n- Dropout for regularization\n- Sigmoid output for binary classification\n","metadata":{}},{"cell_type":"code","source":"model = models.Sequential([\n layers.Input(shape=(224, 224, 3)),\n\n layers.Conv2D(32, (3,3), activation=\"relu\"),\n layers.MaxPooling2D(2,2),\n\n layers.Conv2D(64, (3,3), activation=\"relu\"),\n layers.MaxPooling2D(2,2),\n\n layers.Conv2D(128, (3,3), activation=\"relu\"),\n layers.MaxPooling2D(2,2),\n\n layers.Flatten(),\n layers.Dense(128, activation=\"relu\"),\n layers.Dropout(0.5),\n\n layers.Dense(1, activation=\"sigmoid\")\n])\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-01-04T09:46:23.684093Z","iopub.execute_input":"2026-01-04T09:46:23.684384Z","iopub.status.idle":"2026-01-04T09:46:23.825042Z","shell.execute_reply.started":"2026-01-04T09:46:23.684363Z","shell.execute_reply":"2026-01-04T09:46:23.824024Z"}},"outputs":[],"execution_count":26},{"cell_type":"code","source":"model.compile(\n optimizer=optimizers.Adam(learning_rate=1e-4),\n loss=\"binary_crossentropy\",\n metrics=[\"accuracy\"]\n)\n\nmodel.summary()\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-01-04T09:46:23.826047Z","iopub.execute_input":"2026-01-04T09:46:23.826376Z","iopub.status.idle":"2026-01-04T09:46:23.859049Z","shell.execute_reply.started":"2026-01-04T09:46:23.826346Z","shell.execute_reply":"2026-01-04T09:46:23.858085Z"}},"outputs":[{"output_type":"display_data","data":{"text/plain":"\u001b[1mModel: \"sequential_1\"\u001b[0m\n","text/html":"
Model: \"sequential_1\"\n
\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n┃\u001b[1m \u001b[0m\u001b[1mLayer (type) \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m Param #\u001b[0m\u001b[1m \u001b[0m┃\n┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n│ conv2d_3 (\u001b[38;5;33mConv2D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m222\u001b[0m, \u001b[38;5;34m222\u001b[0m, \u001b[38;5;34m32\u001b[0m) │ \u001b[38;5;34m896\u001b[0m │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ max_pooling2d_3 (\u001b[38;5;33mMaxPooling2D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m111\u001b[0m, \u001b[38;5;34m111\u001b[0m, \u001b[38;5;34m32\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ conv2d_4 (\u001b[38;5;33mConv2D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m109\u001b[0m, \u001b[38;5;34m109\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m18,496\u001b[0m │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ max_pooling2d_4 (\u001b[38;5;33mMaxPooling2D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m54\u001b[0m, \u001b[38;5;34m54\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ conv2d_5 (\u001b[38;5;33mConv2D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m52\u001b[0m, \u001b[38;5;34m52\u001b[0m, \u001b[38;5;34m128\u001b[0m) │ \u001b[38;5;34m73,856\u001b[0m │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ max_pooling2d_5 (\u001b[38;5;33mMaxPooling2D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m26\u001b[0m, \u001b[38;5;34m26\u001b[0m, \u001b[38;5;34m128\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ flatten_1 (\u001b[38;5;33mFlatten\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m86528\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ dense_2 (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m) │ \u001b[38;5;34m11,075,712\u001b[0m │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ dropout_1 (\u001b[38;5;33mDropout\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ dense_3 (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m) │ \u001b[38;5;34m129\u001b[0m │\n└─────────────────────────────────┴────────────────────────┴───────────────┘\n","text/html":"
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃\n┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n│ conv2d_3 (Conv2D)               │ (None, 222, 222, 32)   │           896 │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ max_pooling2d_3 (MaxPooling2D)  │ (None, 111, 111, 32)   │             0 │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ conv2d_4 (Conv2D)               │ (None, 109, 109, 64)   │        18,496 │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ max_pooling2d_4 (MaxPooling2D)  │ (None, 54, 54, 64)     │             0 │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ conv2d_5 (Conv2D)               │ (None, 52, 52, 128)    │        73,856 │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ max_pooling2d_5 (MaxPooling2D)  │ (None, 26, 26, 128)    │             0 │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ flatten_1 (Flatten)             │ (None, 86528)          │             0 │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ dense_2 (Dense)                 │ (None, 128)            │    11,075,712 │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ dropout_1 (Dropout)             │ (None, 128)            │             0 │\n├─────────────────────────────────┼────────────────────────┼───────────────┤\n│ dense_3 (Dense)                 │ (None, 1)              │           129 │\n└─────────────────────────────────┴────────────────────────┴───────────────┘\n
\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"\u001b[1m Total params: \u001b[0m\u001b[38;5;34m11,169,089\u001b[0m (42.61 MB)\n","text/html":"
 Total params: 11,169,089 (42.61 MB)\n
\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m11,169,089\u001b[0m (42.61 MB)\n","text/html":"
 Trainable params: 11,169,089 (42.61 MB)\n
\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n","text/html":"
 Non-trainable params: 0 (0.00 B)\n
\n"},"metadata":{}}],"execution_count":27},{"cell_type":"code","source":"EPOCHS = 15\n\nhistory = model.fit(\n train_gen,\n epochs=EPOCHS,\n validation_data=val_gen\n)\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-01-04T09:46:23.860230Z","iopub.execute_input":"2026-01-04T09:46:23.860588Z","iopub.status.idle":"2026-01-04T10:09:27.289153Z","shell.execute_reply.started":"2026-01-04T09:46:23.860564Z","shell.execute_reply":"2026-01-04T10:09:27.288071Z"}},"outputs":[{"name":"stdout","text":"Epoch 1/15\n\u001b[1m45/45\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m89s\u001b[0m 2s/step - accuracy: 0.5424 - loss: 0.6888 - val_accuracy: 0.5413 - val_loss: 0.6915\nEpoch 2/15\n\u001b[1m45/45\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m87s\u001b[0m 2s/step - accuracy: 0.5723 - loss: 0.6877 - val_accuracy: 0.5527 - val_loss: 0.6906\nEpoch 3/15\n\u001b[1m45/45\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m148s\u001b[0m 2s/step - accuracy: 0.5848 - loss: 0.6776 - val_accuracy: 0.5499 - val_loss: 0.6925\nEpoch 4/15\n\u001b[1m45/45\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m87s\u001b[0m 2s/step - accuracy: 0.5776 - loss: 0.6738 - val_accuracy: 0.5613 - val_loss: 0.6973\nEpoch 5/15\n\u001b[1m45/45\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m91s\u001b[0m 2s/step - accuracy: 0.5837 - loss: 0.6755 - val_accuracy: 0.5328 - val_loss: 0.7005\nEpoch 6/15\n\u001b[1m45/45\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m86s\u001b[0m 2s/step - accuracy: 0.6106 - loss: 0.6617 - val_accuracy: 0.5413 - val_loss: 0.7085\nEpoch 7/15\n\u001b[1m45/45\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m90s\u001b[0m 2s/step - accuracy: 0.5950 - loss: 0.6567 - val_accuracy: 0.5271 - val_loss: 0.7055\nEpoch 8/15\n\u001b[1m45/45\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m86s\u001b[0m 2s/step - accuracy: 0.5725 - loss: 0.6780 - val_accuracy: 0.5356 - val_loss: 0.7071\nEpoch 9/15\n\u001b[1m45/45\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m87s\u001b[0m 2s/step - accuracy: 0.5861 - loss: 0.6561 - val_accuracy: 0.5242 - val_loss: 0.6994\nEpoch 10/15\n\u001b[1m45/45\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m92s\u001b[0m 2s/step - accuracy: 0.6107 - loss: 0.6589 - val_accuracy: 0.5214 - val_loss: 0.7019\nEpoch 11/15\n\u001b[1m45/45\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m87s\u001b[0m 2s/step - accuracy: 0.5870 - loss: 0.6698 - val_accuracy: 0.5356 - val_loss: 0.6988\nEpoch 12/15\n\u001b[1m45/45\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m87s\u001b[0m 2s/step - accuracy: 0.5803 - loss: 0.6663 - val_accuracy: 0.5328 - val_loss: 0.7037\nEpoch 13/15\n\u001b[1m45/45\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m87s\u001b[0m 2s/step - accuracy: 0.6111 - loss: 0.6491 - val_accuracy: 0.5185 - val_loss: 0.7089\nEpoch 14/15\n\u001b[1m45/45\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m87s\u001b[0m 2s/step - accuracy: 0.5970 - loss: 0.6664 - val_accuracy: 0.5185 - val_loss: 0.7143\nEpoch 15/15\n\u001b[1m45/45\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m91s\u001b[0m 2s/step - accuracy: 0.6205 - loss: 0.6402 - val_accuracy: 0.5385 - val_loss: 0.7220\n","output_type":"stream"}],"execution_count":28},{"cell_type":"code","source":"plt.figure(figsize=(8,5))\nplt.plot(history.history[\"accuracy\"], label=\"Train Accuracy\")\nplt.plot(history.history[\"val_accuracy\"], label=\"Validation Accuracy\")\nplt.xlabel(\"Epoch\")\nplt.ylabel(\"Accuracy\")\nplt.legend()\nplt.grid(True)\nplt.show()\nplt.figure(figsize=(8,5))\nplt.plot(history.history[\"loss\"], label=\"Train Loss\")\nplt.plot(history.history[\"val_loss\"], label=\"Validation Loss\")\nplt.xlabel(\"Epoch\")\nplt.ylabel(\"Loss\")\nplt.legend()\nplt.grid(True)\nplt.show()\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-01-04T10:09:27.291214Z","iopub.execute_input":"2026-01-04T10:09:27.291600Z","iopub.status.idle":"2026-01-04T10:09:27.736875Z","shell.execute_reply.started":"2026-01-04T10:09:27.291572Z","shell.execute_reply":"2026-01-04T10:09:27.735668Z"}},"outputs":[{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
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\n"},"metadata":{}}],"execution_count":29},{"cell_type":"markdown","source":"## Model Summary\n\nThe proposed model is a convolutional neural network designed to learn hierarchical visual patterns from candlestick chart images for binary market direction prediction. \nConvolutional layers progressively extract local features such as candle shapes, wicks, and short-term trend structures, while max-pooling layers reduce spatial dimensionality and enforce translational invariance. \nReLU activations introduce non-linearity, enabling the model to capture complex market visual patterns beyond linear separability. \nDropout regularization is applied in the fully connected layer to mitigate overfitting, which is critical given the limited size of financial image datasets. \nThe final sigmoid-activated output layer models the probability of an upward market movement, making the architecture suitable for binary classification.\n","metadata":{}}]} \ No newline at end of file diff --git a/MidEval Code/Utkarsh_251151/Quantvision.ipynb b/MidEval Code/Utkarsh_251151/Quantvision.ipynb new file mode 100644 index 00000000..c1e1bfb8 --- /dev/null +++ b/MidEval Code/Utkarsh_251151/Quantvision.ipynb @@ -0,0 +1,652 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "6e1cbda2", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd \n", + "import numpy as np\n", + "import matplotlib.pyplot as plt \n", + "from sklearn.preprocessing import StandardScaler\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.linear_model import LogisticRegression\n", + "from sklearn.metrics import (\n", + " accuracy_score,\n", + " precision_score,\n", + " recall_score,\n", + " f1_score,\n", + " roc_auc_score,\n", + " confusion_matrix,\n", + " classification_report\n", + ")\n", + "\n", + "url=\"https://raw.githubusercontent.com/e-Phi/Data-projects/refs/heads/main/quantvision_financial_dataset_200.csv\"\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "0ece6459", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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lookback_daysasset_typemarket_regimehigh_volatilitytrend_continuationtechnical_scoreedge_densityslope_strengthcandlestick_variancepattern_symmetryfuture_trend
048equitybullish0159.990.5040.2981.5720.7681
138indexbullish1178.540.5590.0370.6920.5381
224equitybullish1056.030.6170.2121.4190.3011
352equitybullish0066.510.3600.3470.6990.4981
417equitybullish1161.210.4920.1442.5200.8281
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" + ], + "text/plain": [ + " lookback_days asset_type market_regime high_volatility \\\n", + "0 48 equity bullish 0 \n", + "1 38 index bullish 1 \n", + "2 24 equity bullish 1 \n", + "3 52 equity bullish 0 \n", + "4 17 equity bullish 1 \n", + "\n", + " trend_continuation technical_score edge_density slope_strength \\\n", + "0 1 59.99 0.504 0.298 \n", + "1 1 78.54 0.559 0.037 \n", + "2 0 56.03 0.617 0.212 \n", + "3 0 66.51 0.360 0.347 \n", + "4 1 61.21 0.492 0.144 \n", + "\n", + " candlestick_variance pattern_symmetry future_trend \n", + "0 1.572 0.768 1 \n", + "1 0.692 0.538 1 \n", + "2 1.419 0.301 1 \n", + "3 0.699 0.498 1 \n", + "4 2.520 0.828 1 " + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df=pd.read_csv(url)\n", + "df.head()\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "69cd0e96", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "\n", + "import seaborn as sns\n", + "\n", + "sns.set(style=\"whitegrid\")\n", + "\n", + "class_counts = df[\"future_trend\"].value_counts().sort_index()\n", + "\n", + "plt.figure(figsize=(6, 6))\n", + "plt.pie(\n", + " class_counts.values,\n", + " labels=[f\"Class {i}\" for i in class_counts.index],\n", + " autopct=\"%1.1f%%\",\n", + " startangle=90,\n", + " wedgeprops={\"edgecolor\": \"black\"}\n", + ")\n", + "plt.title(\"Class Distribution of Target Variable\", fontsize=14)\n", + "plt.tight_layout()\n", + "plt.show()\n", + "plt.figure(figsize=(6, 4))\n", + "sns.countplot(\n", + " x=\"future_trend\",\n", + " data=df\n", + ")\n", + "plt.title(\"Target Class Counts\", fontsize=14)\n", + "plt.xlabel(\"Future Trend\")\n", + "plt.ylabel(\"Count\")\n", + "plt.tight_layout()\n", + "plt.show()\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "7a6bf587", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Class counts:\n", + " future_trend\n", + "0 13\n", + "1 187\n", + "Name: count, dtype: int64\n", + "Class proportions:\n", + " future_trend\n", + "0 0.065\n", + "1 0.935\n", + "Name: proportion, dtype: float64\n", + "Imbalance ratio: 14.384615384615385\n" + ] + } + ], + "source": [ + "counts = df[\"future_trend\"].value_counts().sort_index()\n", + "proportions = df[\"future_trend\"].value_counts(normalize=True).sort_index()\n", + "imbalance_ratio = counts.max() / counts.min()\n", + "\n", + "print(\"Class counts:\\n\", counts)\n", + "print(\"Class proportions:\\n\", proportions)\n", + "print(\"Imbalance ratio:\", imbalance_ratio)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "ae9d5b59", + "metadata": {}, + "outputs": [], + "source": [ + "y = df[\"future_trend\"]\n", + "X = df.drop(columns=[\"future_trend\"])\n", + "X_encoded = pd.get_dummies(\n", + " X,\n", + " columns=[\"market_regime\", \"asset_type\"],\n", + " drop_first=False \n", + ")\n", + "X_train, X_test, y_train, y_test = train_test_split(\n", + " X_encoded,\n", + " y,\n", + " test_size=0.20,\n", + " stratify=y,\n", + " random_state=42\n", + ")\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "4750f6e4", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " lookback_days high_volatility trend_continuation technical_score \\\n", + "31 1.132469 1 0 -0.738531 \n", + "111 -1.159433 1 1 -0.268390 \n", + "148 -1.092024 1 1 0.514276 \n", + "108 -0.957206 1 1 0.351925 \n", + "109 1.739149 0 1 1.668995 \n", + "\n", + " edge_density slope_strength candlestick_variance pattern_symmetry \\\n", + "31 0.366192 -2.371427 -0.169912 -2.317923 \n", + "111 1.419954 1.283782 1.693257 -0.500166 \n", + "148 2.111484 0.247470 1.372197 0.570102 \n", + "108 1.666929 -0.695655 0.683969 1.538439 \n", + "109 0.514377 1.245221 1.271439 -0.143410 \n", + "\n", + " market_regime_bearish market_regime_bullish market_regime_sideways \\\n", + "31 False True False \n", + "111 True False False \n", + "148 False True False \n", + "108 False True False \n", + "109 True False False \n", + "\n", + " asset_type_crypto asset_type_equity asset_type_index future_trend \n", + "31 True False False 1 \n", + "111 False True False 1 \n", + "148 False True False 1 \n", + "108 False True False 1 \n", + "109 True False False 1 \n" + ] + } + ], + "source": [ + "continuous_cols = [\n", + " \"lookback_days\",\n", + " \"technical_score\",\n", + " \"edge_density\",\n", + " \"slope_strength\",\n", + " \"candlestick_variance\",\n", + " \"pattern_symmetry\"\n", + "]\n", + "scaler = StandardScaler()\n", + "\n", + "X_train[continuous_cols] = scaler.fit_transform(\n", + " X_train[continuous_cols]\n", + ")\n", + "\n", + "X_test[continuous_cols] = scaler.transform(\n", + " X_test[continuous_cols]\n", + ")\n", + "train_dataset = X_train.copy()\n", + "train_dataset[\"future_trend\"] = y_train.values\n", + "\n", + "test_dataset = X_test.copy()\n", + "test_dataset[\"future_trend\"] = y_test.values\n", + "print(train_dataset.head())\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "61a2bf34", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy : 0.95\n", + "Precision : 1.0\n", + "Recall : 0.9459459459459459\n", + "F1 score : 0.9722222222222222\n", + "ROC AUC : 0.963963963963964\n", + "[[ 3 0]\n", + " [ 2 35]]\n", + " precision recall f1-score support\n", + "\n", + " class_0 0.6000 1.0000 0.7500 3\n", + " class_1 1.0000 0.9459 0.9722 37\n", + "\n", + " accuracy 0.9500 40\n", + " macro avg 0.8000 0.9730 0.8611 40\n", + "weighted avg 0.9700 0.9500 0.9556 40\n", + "\n" + ] + } + ], + "source": [ + "w0 = 4.0\n", + "model = LogisticRegression(\n", + " max_iter=1000,\n", + " solver=\"lbfgs\",\n", + " class_weight={0: w0, 1: 1.0}\n", + ")\n", + "model.fit(X_train, y_train)\n", + "y_prob = model.predict_proba(X_test)[:, 1]\n", + "threshold = 0.49\n", + "y_pred = (y_prob >= threshold).astype(int)\n", + "\n", + "\n", + "print(\"Accuracy :\", accuracy_score(y_test, y_pred))\n", + "print(\"Precision :\", precision_score(y_test, y_pred))\n", + "print(\"Recall :\", recall_score(y_test, y_pred))\n", + "print(\"F1 score :\", f1_score(y_test, y_pred))\n", + "print(\"ROC AUC :\", roc_auc_score(y_test, y_prob))\n", + "\n", + "print(confusion_matrix(y_test, y_pred))\n", + "\n", + "print(classification_report(\n", + " y_test,\n", + " y_pred,\n", + " labels=[0, 1],\n", + " target_names=[\"class_0\", \"class_1\"],\n", + " digits=4\n", + "))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "ef734338", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "\n", + "numeric_df = df.select_dtypes(include=[np.number])\n", + "corr = numeric_df.corr()\n", + "plt.figure(figsize=(10, 8))\n", + "sns.heatmap(\n", + " corr,\n", + " cmap=\"coolwarm\",\n", + " center=0,\n", + " square=True,\n", + " linewidths=0.5,\n", + " cbar_kws={\"shrink\": 0.8}\n", + ")\n", + "plt.title(\"Feature Correlation Heatmap\", fontsize=14)\n", + "plt.tight_layout()\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "d6cceaf7", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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A1LFjRzl9+rT07t1bYmJipFOnThIYGCgtWrSQzp07O10ebgGl7y4r702aLrt2/i5TI8dJn56dZcykDyQgIMDp0gCk8krWqwkIcMVEClzIFQFJaTjq0qWL7Ny500yHFCtWLEniB27UHQULm0uFylXMvxyHvT5Atm7aaG4DuHWFhoWZa+03SujsmX9GjsLC+J2BiwPS/v37vX/nypXLXJ86dcpcVIECBRyrDenXyRPHZc3qnySieg3Jeds//1+pEqXKmOujRw87WB2AtFCoUGHTjxi9d0+i7Xv37jXXRYuFO1QZ3M4VAUkPEHm1qY6oqKg0rQe3Bp2u1ZGijl17Squ2Hb3b169Zba7D7yrpYHUA0kLmzJml8j1V5LtlS6VNu/be35plS5dIWFiYlC1X3ukS4VKuCEgzZ85MdDsuLs6saps+fbr07dvXsbqQvuXLf7s82rCJzJg6yfS0FS9RWrZu3igfz5xqDhx5J/9yBPxCx05dpFOHdtKnd09p/MSTsnnTJnMk7Z69XpIsWbI4XR5cyhUHirySn376ScaOHStz58696X1xoEj/pMt758yaJou/mS+HDu6XvPnyy2ONm0mLVm0lQwaaM/0NB4r0XzqCNHH8e2ZZf958+aT50y2lTdvnnC4LLj5QpKsDkp6TrUGDBrJ169ab3hcBCQABCUBwYDpt0vY4c+aMREZGSsGCBR2pCQAA+C/XNmnrwFZISIiMGDHCsboAAIB/csUU27p165JsCwoKkhIlSkjW/3+005vFFBsAptgABAems1VsvXr1kvBwVhUBAADnuWIZz5o1a8yxKgAAANzAFQGpSZMmMnLkSNmxY4fExsY6XQ4AAPBzruhBqlevnjns+5WOpu2LI2nTgwSAHiQAwempB0lPUgsAACD+PoJUunRpWblypffktKmNESQAjCABCA50eQ+SC2b2AAAA3NukDQAA4CaO9iAtWrRIQkNDr/m4xo0bp0k9AAAAjvYglSpVKkWP05VtrGID4Av0IAEITg+r2FatWpVmTdoAAACu70G60jGPAAAAnMYqNgAAALcEJD29COdfAwAAbuSKU42kBZq0AdCkDSDY7QeKBAAAcCsCEgAAgIWABAAAYCEgAQAAWAhIAAAAFgISAACAhYAEAABgISABAABYCEgAAAAWAhIAAICFgAQAAGAhIAEAAFgISAAAABYCEgAAgIWABAAAYCEgAQAAWAhIAAAAFgISAACAhYAEAABgISABAABYCEgAAAAWAhIAAICFgAQAAGAhIAEAAFgISAAAABYCEgAAgIWABAAAYCEgAQAAWAhIAAAAFgISAACAhYAEAABgISABAABYCEgAAAAWAhIAAICFgAQAAGAhIAEAAFgISAAAABYCEgAAgCVQUqB169aSUgEBATJjxowUPx4AACBdBqT4+PgU7/B6HgsAAOBGAfF+kmgO/n3R6RIAOCxH1iCnSwDgsOBAH44gJWfXrl2yatUqOXLkiLRq1Uqio6OlVKlSEhoaeqO7BAAAcIXrDkiXL1+WgQMHyrx588x0mvYc1a9fXyZMmCB79uyRjz76SPLnz5861QIAALhxFZsGoQULFsiQIUPMCJJnhq5Pnz7m73fffTc16gQAAHBvQNKRox49esiTTz4pOXLk8G4vXbq02a6hCQAAwK8C0tGjR00YSk6+fPnk1KlTvqgLAAAg/QSkIkWKyIoVK5K9b926deZ+AAAAv2rSbtOmjWnSvnjxotSqVcs0aWtz9tq1a2XatGnSt2/f1KkUAADAzcdBioyMlIkTJ0pMTIy3STsoKEg6dOggPXv2FDfiOEgAOA4SgODAVD5Q5JkzZ2TTpk1y8uRJyZYtm1SoUCFR07bbEJAAEJAABAem8slq9XhInuMgZcqUyYwgAQAA+O2BIocPHy4ff/yx6UPyDEBlyZJFunTpIs8//3xq1AkAAODegDR+/HiZNWuWOb1I3bp1JVeuXGbp/9dffy2jR4+WrFmzSsuWLVOnWgAAgDRw3T1INWvWlKZNm8oLL7yQ5L4RI0bIkiVLZNmyZeI29CABoAcJQHBq9SCdOHFCKlWqlOx9999/vzl5LQAAQHp23QGpevXqsmjRomTvW716tVSuXNkXdQEAADgmRQNNX375pffvihUryrhx4+TYsWPyyCOPSJ48ecxSfz26tk6vDRgwIDXrBQAAcEcPUqlSpVK+w4AAiYqKErehBwkAPUgAglPYg5Sih3333Xc3WQ4AAED6kaKAdMcdd6R4hzd4YG4AAID0exwktXDhQlm3bp3ExsZ6A5Fenzt3TjZv3iw//vijr+sEAABwb0DSBm29hIWFyaVLl8wpRgIDA+X48eOSIUMGadasWepUCgAA4NZl/l988YU0btzYjCC1bdtWatWqZZb3f/bZZ+ZktcWLF0+dSgEAANwakA4dOiQNGzY0q9VKly4tmzZtMtvLli0rnTt3lk8//TQ16gQAAHBvQAoJCTHhSBUpUkT27dsnFy5cMLc1MOltAAAAvwpI5cqV8x44smjRopIxY0b5+eefze1du3ZJpkyZfF8lAACAm5u0dRqtXbt2curUKZk0aZI0atRIXn31VYmIiJCVK1dKnTp1UqdSAAAAtwakqlWrmobs//73v+b2wIEDzeq1X375RerXry99+/ZNjToBAADcdaqRWwGnGgHAqUYABAemUg/StQ4B8PDDD/tylwAAAGnOpwFJ+5L27t3ry10CAACk74AEAABwKyAgAQAAWAhIAAAAFgISAACAJUWL3UqVKuU9vcjV6BEDUvI4JwQFurMuAGknZ9UXnC4BgMPObxrnu4DUrVs31wYfAAAAX0tRQOrevbvPXxgAAMCt6EECAACwEJAAAAAsBCQAAAALAQkAAMBCQAIAALiRVWy248ePy9SpU2X16tVy5MgRmTJliixbtswcL6lOnTo3sksAAID0O4IUHR0tjRo1krlz50q+fPnk2LFjEhcXJ7t375YePXrIDz/8kDqVAgAAuHUE6e2335ZcuXLJrFmzJCQkRMqWLWu2jxo1SmJiYmTSpElSs2bN1KgVAADAnSNIP//8s3Tt2lWyZcuW5OjazZs3lx07dviyPgAAgPTRpB0YmPzAU2xsLKckAQAA/heQqlSpIpGRkXLu3DnvNg1Fly9fltmzZ0vlypV9XSMAAIC7e5Beeuklefrpp6VevXoSERFhwpGuaNu1a5fs2bNHPv7449SpFAAAwK0jSCVKlJB58+aZcLR27VrJmDGjWe5fuHBhmTNnjpQuXTp1KgUAAEgjAfHx8fHiB46dveR0CQAcVrDGi06XAMBh5zeNS50ptv3791/zMQUKFLje3QIAALjGdQek2rVrX3OlWlRU1M3UBAAAkL4C0tChQ5MEJF3RtmHDBtOTpPcDAACkZz7tQRo2bJgcPXrUHFXbbehBAkAPEoDzKexBuqEDRV5t+o1zsQEAgPTOpwFpy5YtVzzKNgAAQHpx3WmmX79+SbbpUbQPHjwo69evl6ZNm/qqNgAAgPQRkLQR26ZN26GhodKxY0fp3Lmzr2oDAABIHwFp8uTJEh4enjrVAAAApMcepGeeeUa+/PLL1KkGAAAgPQakoKAgyZkzZ+pUAwAAkB6n2Hr27CnDhw+X06dPS6lSpSQkJCTJYzjVCAAA8KsDRd59990SFxd31dONuPFUIxwoEgAHigRwPrVOVjtkyJAbqQcAACDdSFFAat26tQwaNMisXmvSpEnqVwUAAOD2Ju1169bJ2bNnU78aAACAW+1UIwAAALcCAhIAAMCNNml369ZNMmXKdM3H6eq2ZcuWpXS3AAAA6TcglSlTRm677bbUrQYAACC9jSCVL18+dasBAABwAXqQAAAALAQkAACAGwlIenBITlALAAD8RYp6kIYNG5b6lQAAALgEU2wAAAAWAhIAAICFgAQAAGAhIAEAAFgISAAAABYCEgAAgIWABAAAYCEgAQAAWAhIAAAAFgISAACAhYAEAABgISABAABYCEgAAAAWAhIAAICFgAQAAGAhIAEAAFgISAAAABYCEgAAgIWABAAAYCEgAQAAWAhIAAAAFgISAACAhYAEAABgISABAABYCEgAAAAWAhIAAICFgAQAAGAhIAEAAFgISAAAABYCEgAAgIWABAAAYCEgAQAAWAhIAAAAFgISAACAhYAEAABgISABAABYCEgAAAAWAhIAAICFgAQAAGAJFIc8++yzEhAQkKLHzpw5M9XrAQAAcDwg1ahRQ8aMGSNFixaV8uXLO1UGAACAewJSp06dJDQ0VEaNGiWRkZFSsGBBp0oBAABwTw9Sy5YtpVq1ajJ8+HAnywAAAHDHCJLH4MGDZfv27U6XAQAA4J6AlDdvXnMBAABwC5b5AwAAWAhIAAAAFgISAACAhYAEAADg9oAUGxvrdAkAAMDPOb6KzWP27NkyefJkOXjwoCxZskSmTJki+fLlk65duzpdGtKxy5cvy1effyqfz50j+/+Klpy35ZL7H6wlHTq/IFlDQ50uD4CP6SmseraqLe2b3id35M0hO/YelnenL5M5izZ4H7Nz8RtyR76cSZ5bsNarcuzk2TSuGG7lioC0YMECc0TtNm3amGCkwsPDZeTIkRIcHCzPPfec0yUinfpwxlSZPGGsPNO6nVSpdq/s3fOnTJ44Vv7YtVNGT5ic4vMBAkgfBnZpIL3b1pE3Jn4jG7bvkfo17pYPhraVy/HxMnfxRsmVI6sJR/3e+UJWb96V6LknT593rG64jysC0rRp02TAgAHSpEkT87dq3bq1hISEmFElAhJudPToo+nT5PEnmkmX7r3MtqoR1SV79hwysN/L8lvUdildpqzTZQLwkSzBQfJCy1oy/uMfZOQHS822H9b9LpVKF5auT9c0Aal8yX9Oa/XV8i2ye99RhyuGm7miB2n37t1SpUqVJNsjIiLkwIEDjtSE9O/s2TPycIOGUu+RBom2Fyla1Fz/FR3tUGUAUkNM7CWp1XaUjJn1XaLtsRcvSeZM/4wHVChRUE6dOU84QvoYQcqdO7cJSYUKFUq0fdOmTRxlGzcsLCyb9H6lf5LtPy7/3lwXDb/LgaoApJbLl+Nl24793tt5bwuT1o/fK7UjSsoLQ+aYbeVL3iEnTp2T2SM7SK1qJSVjxgyy+Kdt0mfkPDl49JSD1cNtXDGC1Lx5c3NOtu+++yf1//HHH6Zp+80335QnnnjC6fJwC9n+n60ya/oUqfFATQm/q7jT5QBIJU/Vv0f2fDdM3ujxuCxe+avMXrjebNcptgJ5csgvv+6VJ3tOkldHfS417iku3055UUKCMzldNlwkID4+Pl5c4J133pEZM2ZITEyMuR0YGCgtWrSQ/v37S4YMN5/jjp295IMqkZ5t3fyL9OnZTXLlzi0Tp86S7DlyOF0S0ljBGi86XQLSSNGCuaVA3uxSrvgdMrDrY7Jtx19Sr8MYiShfVC5dipONv+71PrZ6hWLy/fTe0mPoHJn86UpH60bqO79pXPqZYlO9e/eWLl26yM6dO0UzW7FixSSUZdjwkWVLFsmQ1wZI4cJF5J1x7xOOgFuc9hjpZdUvu+TU2Qsy9Y3Wcl/lcHPb9vOWP+Tk6XNSrsQ/DdyAawLS/v3/mzPOlSuXuT516pS5qAIFCjhWG9K/j2d+IOPHjJJK91SVt0a9J6FhYU6XBCAV5M4ZKvXuKyNLV/0qR06c8W7fHPXPgow778gt4YXyyIZte+TXXf9bAKSH+8gUGChHT5x2pG64kysCUu3ata96PJqoqKg0rQe3ji8/myvjRo+Uh+o9IgPfGCpBQfQYALeqLJmDzEjRv8fOl5HTvvVur1O9tLneuH2PrPrwFZm/fIu0GzDDe/9jD5aTkCyZZMX6HY7UDXdyRUCaOXNmottxcXFmVdv06dOlb9++jtWF9O3Y0SMy5p235fYCd0jT5k/Lf62gfUehQpIz522O1QfAt6IPnpDpX66W/h3ry6WLcbL5v9FyX6W75OV2deWDL1bLb38clJHTv5WBXR6Tw8dPy+KV26XsXQVkQKdHZcHyLbJi/e9OvwW4iGuatJPz008/ydixY2Xu3Lk3vS+atP3P119+LkMH//uK9w94bYg0aNQkTWuCs2jSvvUFBWaUXm3qSKuGEVL49pyy7+BJmfb5Knl35nemv1VnKzo0vU86PfWAFCuYW47/fVbmLNwgQyIXyoWYi06XDxc1abs6IEVHR0uDBg1k69atN70vAhIAAhKA8+lpFVvCJm2PM2fOSGRkpBQsyKoCAACQtlzbpK0DW3outhEjRjhWFwAA8E+ubNJWQUFBUqJECcmaNasjNQEAAP/lmoDUq1cvCQ8Pd7oUAAAAd5yLbc2aNZI5c2anywAAAHBPQGrSpImMHDlSduzYIbGxsU6XAwAA/JwrpthWrFghe/fulSVLliR7P0fSBgAAfheQ9CS1AAAA4u8BqXTp0rJy5UpzclqdYgMAABB/70Fy8QG8AQCAn3NFkzYAAICbONqDtGjRIgkNDb3m4xo3bpwm9QAAADgekIYMGXLNx+gpSAhIAADAbwLSqlWrTJM2AACAmzjWg2SfnBYAAMAtWMUGAADgloCkxz7i/GsAAMCNHOtBGjZsmFMvDQAAcFUcBwkAAMBCQAIAALAQkAAAACwEJAAAAAsBCQAAwEJAAgAAsBCQAAAALAQkAAAACwEJAADAQkACAACwEJAAAAAsBCQAAAALAQkAAMBCQAIAALAQkAAAACwEJAAAAAsBCQAAwEJAAgAAsBCQAAAALAQkAAAACwEJAADAQkACAACwEJAAAAAsBCQAAAALAQkAAMBCQAIAALAQkAAAACwEJAAAAAsBCQAAwEJAAgAAsBCQAAAALAQkAAAACwEJAADAQkACAACwEJAAAAAsBCQAAAALAQkAAMBCQAIAALAQkAAAACwEJAAAAAsBCQAAwEJAAgAAsBCQAAAALAQkAAAACwEJAADAQkACAACwEJAAAAAsBCQAAAALAQkAAMBCQAIAALAQkAAAACwEJAAAAAsBCQAAwEJAAgAAsBCQAAAALAQkAAAACwEJAADAQkACAACwEJAAAAAsBCQAAAALAQkAAMBCQAIAALAQkAAAACwEJAAAAAsBCQAAwEJAAgAAsBCQAAAALAQkAAAACwEJAADAQkACAACwEJAAAAAsBCQAAAALAQkAAMBCQAIAALAQkAAAACwB8fHx8fZGAAAAf8YIEgAAgIWABAAAYCEgAQAAWAhIAAAAFgISAACAhYAEAABgISABAABYCEgAAAAWAhIAAICFgAQAAGAhIAEAAFgISAAAABYCElyndu3aUrJkSe+lVKlSUrlyZWnVqpWsX7/e56+3du1a8zr79u274mOioqLM61esWNHUN3PmTJ/XAcDd3wMeJ06ckBo1apjn4NZFQIIrPffcc7Jy5Upz+fHHH2XOnDkSGhoqHTp0kP3796dpLfpl2K5dOylcuLDMmzdPunXrJiNHjjR/A/CP7wGPQ4cOSfv27eXIkSOOvD7SDgEJrhQSEiJ58uQxl7x580qJEiXk9ddflwsXLsjSpUvTtJa5c+dKUFCQDB48WMLDw+XJJ5+Utm3byvvvv5+mdQD+xk3fA+qzzz6TRo0apfnrwhkEJKQbgYGB5jpTpkzeIfi3335bHn30UYmIiJB169ZJfHy8TJ48WR566CGpUKGCPP744zJ//vxE+9mwYYM0a9ZMypcvb77sfvvtt6u+rj6+WrVq3tdX9957r/z5559y9OjRVHmvANz1PaA0lPXq1UvGjBmTSu8ObvK/b3zAxXRYe+jQoeZflA8++KB3+4cffiiRkZESFhZm+gfeffdd+frrr2XgwIFSrFgx06vw2muvyenTp6Vly5YSHR1thu0bN24sb731luzcudM89moOHjxo/uWakP5rVh04cEBy586dSu8agFu+B5S+hkpJnxLSPwISXEm/iKZNm2b+vnTpksTGxprprdGjR0uBAgW8j9MvyX/961/m73Pnzsn06dPlnXfekZo1a5pt2jf0119/ydSpU80Xo06XaaAZNGiQZMyY0exTQ86wYcOuWIsO53v+teqROXNmcx0TE5Mq7x+Au74H4H8ISHClFi1ayLPPPmv+zpAhg+TIkcP869BWpEgR79/6r0ANLC+99JJ5jofni1WDzu+//y5lypQxX4oeujLmaoKDg83zE/IEI/2XLIBb/3sA/oeABFfKnj17oi+9q4UXD+07UPqvSx1Wt+koUEBAgFy+fDnR9oS9RcnJnz+/HD58ONE2z+18+fJds0YA6f97AP6HJm3cMvTLUL/kdPmvfql6LitWrDBD6/qvST2WyrZt2xKNCOntq6lataps3LhR4uLivNvWrFkjRYsWlVy5cqXqewLgju8B+B8CEm4ZOvSuQ/K6wuSrr74yjZi6LHfEiBHepuqnn35azp8/L/3795ddu3bJ8uXLZezYsVfdry7rP3PmjAwYMMAM33/++eemx6FTp05p9M4AOP09AP/DmCJuKf369ZOcOXOaL0edBrv99tulR48e5sBynimxGTNmmJUwTZo0Mfd36dLFHFvlSnSUaMqUKfLmm2+a5+gxWV555RXzNwD/+B6A/wmI90zYAgAAwGCKDQAAwEJAAgAAsBCQAAAALAQkAAAACwEJAADAQkACAACwEJAAAAAsBCQAtwwO6wbAVwhIAAw9a3rJkiUTXcqWLSs1a9Y0Rxj++++/U+219fQt+nr79u0zt/W0D3o7pQ4ePCjPP/+8/PXXXzddi9agr601Xcn11nczr3U9//30AsA3ONUIAK8yZcrIoEGDvLcvXrwo27dvl3feeUeioqJk9uzZ5kzoqa1Zs2Zy//33p/jxq1evNicjBQBfISAB8AoNDZWKFSsm2la1alU5e/asvPfee7Jly5Yk96eG/PnzmwsAOIUpNgDXpFNtav/+/eZap3JefvllcwJQDUzt2rUz22NiYmT48OHy4IMPmuc0bNhQFi5cmGhfly9flgkTJpipuwoVKkjXrl2TTN8lN4X15ZdfmhOL6nP0uaNGjZLY2FgzPaUnJ1UPPfSQ9O3b1/ucTz/9VBo0aOCdKtT9xsXFJdrvt99+K40aNZLy5cub/f/2228++9zWr18v7du3NyFTa6hdu7apQT+DhA4dOiSdOnUyNehnp2HUrjMl7wWA7zCCBOCadu/eba4LFSrk3bZo0SITLCZOnGh+8LVBulu3bvLLL7+Y4BQeHi5Lly6VXr16mSDTuHFj87wRI0bIzJkzzdnTNezofjTsXM1HH30kgwcPNlNvvXv3lujoaBPENFi9+OKLZl9ax7hx47zBKjIyUt59911p1aqVCVA6Raih4sCBA+Ys7ur77783tWqQ69Onj3mMXvuCBq22bdtK/fr1TR36+SxYsMDUWKxYMRN2PLQu/XzGjx8vmzZtkkmTJsmZM2ekf//+KX4vAHyLgATAS3/EL1265L2tAWTdunUmfFSqVMk7kqSCgoJM83amTJnM7VWrVslPP/1kfsgfffRRs037iM6fPy8jR46Uxx57TM6dOyezZs0yI04vvPCC9zGHDx82z02Ohi8NDnXq1JEhQ4Z4t+t+v/nmGwkLC5PChQubbaVLl5aCBQvK6dOnzShV8+bN5f/+7//MfTVq1JAcOXKY2/r6xYsXN/vVURsNbZ5a1LUCW0oD0r/+9S+z7wwZ/hmsv++++0woW7t2baKApK/rCTr6t4ajjz/+2IyuZcyYMUXvBYBvEZAAJJoSuvvuuxNt0x93/aHXEZyEDdo6CuIJR+rnn3829+sUUcKQpdNK8+fPlx07dsiRI0dM43etWrUSvcYjjzxyxYCko1fHjh2TunXrJtquU1d6SY6Owly4cMG8tl2LJ8zpaJg2oPfs2TNJLb4ISDoipBeddtT3sGfPHjPyo9Ni+hnYr5lQvXr1ZMaMGabnSz/Ta70XAhLgewQkAF4ajnRUSOkPc+bMmeX22283zdu2rFmzJrp98uRJMwJVuXLlZPeto0SnTp0yf+fMmTPRfXny5LliTbpflStXrhS/D89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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "cm = confusion_matrix(y_test, y_pred)\n", + "\n", + "plt.figure(figsize=(6, 5))\n", + "sns.heatmap(\n", + " cm,\n", + " annot=True,\n", + " fmt=\"d\",\n", + " cmap=\"Blues\",\n", + " cbar=False,\n", + " xticklabels=[\"Pred 0\", \"Pred 1\"],\n", + " yticklabels=[\"True 0\", \"True 1\"]\n", + ")\n", + "\n", + "plt.xlabel(\"Predicted Label\")\n", + "plt.ylabel(\"True Label\")\n", + "plt.title(\"Confusion Matrix\")\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "d707c047", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "c:\\Users\\Lenovo\\AppData\\Local\\Programs\\Python\\Python313\\Lib\\site-packages\\keras\\src\\export\\tf2onnx_lib.py:8: FutureWarning: In the future `np.object` will be defined as the corresponding NumPy scalar.\n", + " if not hasattr(np, \"object\"):\n", + "c:\\Users\\Lenovo\\AppData\\Local\\Programs\\Python\\Python313\\Lib\\site-packages\\keras\\src\\layers\\core\\dense.py:106: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead.\n", + " super().__init__(activity_regularizer=activity_regularizer, **kwargs)\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import tensorflow as tf\n", + "from tensorflow.keras.models import Sequential\n", + "from tensorflow.keras.layers import Dense\n", + "from tensorflow.keras.optimizers import Adam\n", + "from sklearn.metrics import (\n", + " accuracy_score,\n", + " precision_score,\n", + " recall_score,\n", + " f1_score,\n", + " roc_auc_score,\n", + " confusion_matrix,\n", + " classification_report\n", + ")\n", + "\n", + "model_nn = Sequential([\n", + " Dense(16, activation=\"relu\", input_shape=(X_train.shape[1],)),\n", + " Dense(8, activation=\"relu\"),\n", + " Dense(1, activation=\"sigmoid\")\n", + "])\n", + "\n", + "model_nn.compile(\n", + " optimizer=Adam(learning_rate=0.001),\n", + " loss=\"binary_crossentropy\"\n", + ")\n", + "\n", + "class_weights = {\n", + " 0: 2.1,\n", + " 1: 1.0\n", + "}\n", + "\n", + "model_nn.fit(\n", + " X_train,\n", + " y_train,\n", + " epochs=25,\n", + " batch_size=7,\n", + " class_weight=class_weights,\n", + " verbose=0\n", + ")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "4bfc4327", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m2/2\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 30ms/step\n" + ] + } + ], + "source": [ + "y_prob_nn = model_nn.predict(X_test).ravel()\n", + "\n", + "threshold = 0.7\n", + "y_pred_nn = (y_prob_nn >= threshold).astype(int)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "37b91769", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy : 0.975\n", + "Precision : 1.0\n", + "Recall : 0.972972972972973\n", + "F1 score : 0.9863013698630136\n", + "ROC AUC : 0.972972972972973\n", + "[[ 3 0]\n", + " [ 1 36]]\n", + " precision recall f1-score support\n", + "\n", + " class_0 0.7500 1.0000 0.8571 3\n", + " class_1 1.0000 0.9730 0.9863 37\n", + "\n", + " accuracy 0.9750 40\n", + " macro avg 0.8750 0.9865 0.9217 40\n", + "weighted avg 0.9812 0.9750 0.9766 40\n", + "\n" + ] + } + ], + "source": [ + "print(\"Accuracy :\", accuracy_score(y_test, y_pred_nn))\n", + "print(\"Precision :\", precision_score(y_test, y_pred_nn))\n", + "print(\"Recall :\", recall_score(y_test, y_pred_nn))\n", + "print(\"F1 score :\", f1_score(y_test, y_pred_nn))\n", + "print(\"ROC AUC :\", roc_auc_score(y_test, y_prob_nn))\n", + "\n", + "print(confusion_matrix(y_test, y_pred_nn))\n", + "\n", + "print(classification_report(\n", + " y_test,\n", + " y_pred_nn,\n", + " labels=[0, 1],\n", + " target_names=[\"class_0\", \"class_1\"],\n", + " digits=4\n", + "))\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.9" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/MidEval Code/Utkarsh_251151/readme.md b/MidEval Code/Utkarsh_251151/readme.md new file mode 100644 index 00000000..8b137891 --- /dev/null +++ b/MidEval Code/Utkarsh_251151/readme.md @@ -0,0 +1 @@ +