02_evaluate_ml_vs_gl.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### RandomForest\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "from baseline.models.random_forest import RandomForest\n",
    "\n",
    "def evaluate_rf(desire, choice_type, num_sample=1000, seed=42):\n",
    "    print(f'Random Forest:disire-{desire} choice_type-{choice_type}')\n",
    "    model = RandomForest(data_dir='baseline/data', choice_type=choice_type,\n",
    "                         desire=desire, sample_num=num_sample, seed=seed)\n",
    "    model.load_dataset()\n",
    "    model.prepare_data()\n",
    "    model.optimize()\n",
    "    model.train()\n",
    "    error, kl_divergence = model.evaluate_with_cv(figsize=(20, 3), plot=False)\n",
    "    _,_,age_error_table = model.get_error_table(x_label='age_group')\n",
    "    _,_,income_error_table = model.get_error_table(x_label='income_group')\n",
    "    print('MAPE:', round(error['mean'],2))\n",
    "    print('KL Divergence:', round(kl_divergence['mean'],2))\n",
    "    print('=='*20)\n",
    "    return age_error_table, income_error_table, error, kl_divergence"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "# evaluate_rf(desire='Recreation', choice_type='amenity')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### XGBoost"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "from baseline.models.xgboost import XGBoost\n",
    "\n",
    "\n",
    "def evaluate_xg(desire, choice_type, num_sample=1000, seed=42):\n",
    "    print(f'XGBoost: disire-{desire} choice_type-{choice_type}')\n",
    "    model = XGBoost(data_dir='baseline/data',choice_type=choice_type,\n",
    "                    desire=desire, sample_num=num_sample, seed=seed)\n",
    "    model.load_dataset()\n",
    "    model.prepare_data()\n",
    "    model.optimize()\n",
    "    model.train()\n",
    "    error, kl_divergence = model.evaluate_with_cv(figsize=(20, 3), plot=False)\n",
    "    _,_,age_error_table = model.get_error_table(x_label='age_group')\n",
    "    _,_,income_error_table = model.get_error_table(x_label='income_group')\n",
    "    print('MAPE:', round(error['mean'],2))\n",
    "    print('KL Divergence:', round(kl_divergence['mean'],2))\n",
    "    print('=='*20)\n",
    "    return age_error_table, income_error_table, error, kl_divergence"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### MLP"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "from baseline.models.multilayer_perceptron import MLP\n",
    "\n",
    "\n",
    "def evaluate_mlp(desire, choice_type, num_sample=1000, seed=42):\n",
    "    print(f'MLP: disire-{desire} choice_type-{choice_type}')\n",
    "    model = MLP(data_dir='baseline/data',choice_type=choice_type,\n",
    "                desire=desire, sample_num=num_sample, seed=seed)\n",
    "    model.load_dataset()\n",
    "    model.prepare_data()\n",
    "    model.optimize()\n",
    "    model.train()\n",
    "    error, kl_divergence = model.evaluate_with_cv(figsize=(20, 3), plot=False)\n",
    "    _,_,age_error_table = model.get_error_table(x_label='age_group')\n",
    "    _,_,income_error_table = model.get_error_table(x_label='income_group')\n",
    "    print('MAPE:', round(error['mean'],2))\n",
    "    print('KL Divergence:', round(kl_divergence['mean'],2))\n",
    "    print('=='*20)\n",
    "    return age_error_table, income_error_table, error, kl_divergence"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Proposed Method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "from model import ChoiceModel\n",
    "\n",
    "def evaluate_gl(desire, choice_type, num_sample=1000, seed=42):\n",
    "    print(f'Graph RAG+LLM: disire-{desire} choice_type-{choice_type}')\n",
    "    choice_model = ChoiceModel(\n",
    "        data_dir='data', desire=desire, choice_type=choice_type,\n",
    "        sample_num=num_sample, skip_init=True, seed=seed)\n",
    "\n",
    "    error, kl_divergence = choice_model.evaluate(figsize=(20, 3), plot=False)\n",
    "\n",
    "    _,_,age_error_table = choice_model._get_error_table(x_label='age_group')\n",
    "    _,_,income_error_table = choice_model._get_error_table(x_label='income_group')\n",
    "\n",
    "    print('MAPE:', round(error['mean'],2))\n",
    "    print('KL Divergence:', round(kl_divergence['mean'],2))\n",
    "    print('=='*20)\n",
    "    return age_error_table, income_error_table, error, kl_divergence"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "# evaluate_gl(desire='Eat',choice_type='mode', num_sample=1000, seed=42)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from tqdm import tqdm\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "# plot predict table\n",
    "\n",
    "def plot_predict_table(desire, choice_type, y_tick=None, x_label='age_group',num_sample=1000, seed=42):\n",
    "    model = RandomForest(data_dir='baseline/data',choice_type=choice_type,\n",
    "                desire=desire, sample_num=num_sample, seed=seed)\n",
    "    \n",
    "    model.load_dataset()\n",
    "    model.prepare_data()\n",
    "    model.optimize()\n",
    "    model.train()\n",
    "\n",
    "    predict_tables = model.get_error_table(x_label=x_label)\n",
    "\n",
    "    choice_model = ChoiceModel(\n",
    "        data_dir='data', desire=desire, choice_type=choice_type,\n",
    "        sample_num=num_sample, skip_init=True, seed=seed)\n",
    "\n",
    "    choice_predict_tables = choice_model._get_error_table(x_label=x_label)\n",
    "\n",
    "    fig, axs = plt.subplots(2, 3, figsize=(20,9), sharex=True, sharey=True)\n",
    "\n",
    "    table_names = ['Ground Truth', 'Prediction', 'Absolute Percentage Error']\n",
    "    for i in range(3):\n",
    "        for j,table in enumerate([predict_tables, choice_predict_tables]):\n",
    "            ax = axs[j,i]\n",
    "            vmax = 60 if i <= 1 else 30\n",
    "            sns.heatmap(table[i].abs(), annot=True, fmt=\".0f\",cbar=False,\n",
    "                        cmap=\"Blues\", vmin=0, vmax=vmax, ax=ax,annot_kws={\"size\": 15})\n",
    "            ax.set_xlabel(\"\")\n",
    "            ax.set_ylabel(\"\")\n",
    "            ax.set_xticklabels(ax.get_xticklabels(), rotation=0,fontsize=15)\n",
    "            if j == 0:\n",
    "                if i ==0 :\n",
    "                    ax.set_ylabel(\"RF\",fontweight='bold',fontsize=25)\n",
    "                ax.set_title(table_names[i],fontweight='bold',fontsize=25)\n",
    "            else:\n",
    "                if i ==0:\n",
    "                    ax.set_ylabel(\"GL\",fontweight='bold',fontsize=25)\n",
    "                # ax.set_title(table_names[i]+' (GL)',fontweight='bold',fontsize=25)\n",
    "            if y_tick:\n",
    "                ax.set_yticklabels(y_tick, fontsize=15)\n",
    "    plt.tight_layout()\n",
    "    plt.savefig(f'results/predict_table({x_label}).png')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
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1XU+L8dM1o8JVUFalv34fZ227ejjrmlFh+ml347brtaPCNKmXn7JLKjX3x72dvu3amZPc+9b+pswDexR7euN72OLXrfewXqOmaupNDe9hi16x3sOGzbxSQ4+9h2Wlycm1c9/DOnOSe+vyX5QSv0vjzr1YgeFH60JFeTn65Nm5Sk/cr0ETTtcldz9Sty9u42ol7tqqsN79Fd67n3764N9K2L6RJPcJsNck988/fqsd27bqsiuvUc/o3nXbs7Oz9MA9tyt+7x6dcfa5+r9/PW/DKFuvKyS53/1soYJDGz80Z6/sOcm9c9sW9e0/UM4mU4Pt3331mf79wr/k6+evz7//TY5G+/uO9pzk3rFti/o1US7ffvWZXn3eWi5f/mB/5WKvSe7j2bZhjZ5/9F75BwbrlY+/l8Fgf3949pjk7uq/9Seb5O4Sa3Ifa9CgQVq6dKn8/Py0fv16eXh4aOHChW2a4LYH+7NLG3USSNKy/bnKLKqQt6uTwrysPxZZJZV6eXlig04CSao2WzR/U6pKK2vk7+6s3gGdtxFuLxJyGnfeSKpN5lXI28VJoV5Hf8S3pxXpy23p2pBSUJvs6+Q9NXYmasx0Db/szgYJbkly8fbT0EusU7Gkbl8rc/XRTv6cA9YHXPqfdUVdgluSnFzd1ff0iyVJeSn72jv0Lm1jSqG+3J7RIMEtSUUVNVqwwzryd3Cop4480+LjYlRsiIdqzBZ9tT29wVTmO9OLteVwoTxMRo3p0Xk71OzBvqzGyTNJWrIvRxlFFfJxdVK499GOwaS8skYJbklKyCnV+qR8ORgMGhjs0a4xd3WDJp+ls264t0GCW5I8fPx1xrV3SpL2bVqlmnr3sOCeMY0S3JIU2nuA+o+dKlksStmztV3jRvuIzypp8hpdvDdb6YXWazTCp+nO++vGhMtkdNB/16e0d5jdRsy4MzT+yrsaJIckyc3bT2Mvv0OSlLR1TYPrM2nzSqXHb1fUiEkadt7VDZJDkuQZENqpk0P2oO+EMzXlmrsbJLglyc3HT5Ou/LMkKXHz6gblgvbXXNv19/25yqhru1rvX1nFlXppWdNt13m1bdcAd2f1tsMOq86kz/gzNPGqpu9h469o+h6WWHsP6zlikoY3dQ8L5B52KoZNPVuzbrmvQYJbkjx9/TXzxnskSXs2rFR1vTLpP2qiZlz3Zw2ZNF3+oRGSHXY+4+Scc95sPfDw/zXo9JakgIBA3feg9QGIFb//pqoq+00WA21l0NDhjRKpknTBJVcoLCJSebk5SjyYYIPIurfBzZTLbMql0zkyinvCaTPsMsFtr/itb8i+HndpRnPra8fExCg3N1d9+vTR/PnzNX/+/EbHGAwGvf/+++0dYqdTUzuAv6mOhGNV1ViUUVShaH83+bh23hG5XcGRAaYnUi5of95hPSVJ5uoqVZYUycXbT5LkYGz5OnB282zP0Lq1I2trOzk6yM3ZUUUVNQqvTdrklFYpr6zxE/f7s0s1MsJbg0I8tPJgXofG210cuW+d6P2r5iSPx8kL7NFLklRTVaWy4kJ5+LQ8TZGDo7VqeCL3OdiXumuuiWGNQ8M8NamXnz7fkqqMou7RCLI1vwjrTAnm6ipVlBTJrbaOEb96kSRpwLTzbRZbd+ZfWy411VWqKC6Sm4+fjSOCdHJ1hqoai9KLKtTL302+rl2iu6NT8qt/rdS/h63iHmYrwVHWTs6aqiqVFRXK09c+p6dE+4rpa13qobKyUgUFBQoICLRxREDnZaxtGzs50TbuTIxGyqWzKC8v06a1KyRJk6afY+NocER3/K3vEq2+Dz/88Lj7t2zZoi1bmp5esjsmucdF+SjY06T0ogplFLfckWmQ5O/uLEkqKLfP6Zrswdge3gr2dFZGUYUy6WDuFEpzMiRJBkejnNyPJq2D+g1X8h9LFPfrZ42mK49fukCSFDXWPqeytAf+tdPfV5stKq2yPhlicrROTFJW1XjUsCSV1o4mDvPuvNMP2rOJ0b4K9TIprbBC6Scw5XqEj4vGRvmousasnWlFLR6P1snPsk7n7+BolIt7yw/eZKUc1N71y+XgaFTP2BHtHR460ORevgr1NimtoFxpx1yjJqODbhoXqcP55fp+Z6aNIux+irKts5I4OBplqn0wzlxTrcyE3TI4OCogqp9yDx1U0paVKi8qkJuPvyKHjJNfRC9bht3lFdYvF/fGM42kxm1TTkqCaqqq5O4boMhBoxQYZX9rZ9qT8T19FOJlUnphhTKKW65jWNuu1roibdf2U5TV9D0so/YeFtjTeg9L3LxSZUUFcvfxV4+h3MPaU17m0XqfqwcPXKNpqYcOSbImiby8mFXBVhb/9I2KCgpkcHBQeEQPjZt8mgKDQ20dFupZ/PMPSklOVHhklMIjbbNUFhr79acflJKUqAjKpVPYuOp3VZSXKap3P4VHUcfrLLrjb32XSHL/97//ZTqE4zi7X4DCvE0yGR0U6mVSuLeL8kqr9O7aFJ3Iiuxjorzl5WJUYXm1ErLtYw1oe3BWX3+FelnLJcSztlzKqvTe+kNMSN5J7F/xvSQpuP8IOdYb1Rg78zrlpyTo4OqflLFno3wiYlRTXancg3vkYHTWqKv/qsA+Q2wVdpc3pZd1pEhcZnHdyJ7iSmsnpm8zs0341SbG3Z0d5exoaDCdOU7euQMCFeHtIpPRQWHeJkX4uCq3tEpvrE5q8ndleLiXRkd6y9HBIH93J/UJcFe1xaL31x9qNCU92s7mX76VJEUPGSWjk3Oj/Qlb1ip+wyqZa6pVmJOl1H275WB01Fk33iuf4K6zRlx3dF5skCJ9rNdouLeLIn1dlVtaqX+vSGx0jV46LFRBnib9c9G+unsq2t+e37+TJIUNHCnH2lEIRdnpqqmqlIuXr3Yv/UZbvv9YFou57pytCz/RgNMu0JhL/mSTmLuDnUus5RIRO1KOTdw3961b0uD1xu8+VvSIiZp2/V/l5OLaITF2dTP6ByjM20UmR2vbNcLH2nZ9e23yCbVdx0b5yNvFSYXl1dpP27Xd7K69h4XXv4dlWe9hrl6+2rX0G23+ruE9bMvCTzTwtAs09lLuYe1h/c/Wh61jho1ust4HSNKXn82TJI0dP0nOzvyd2MoXH7/X4PUHb76sy669RVdcx/3RVj6f/4ESD+xXeXmZkhMPKvHAfvkHBumRJ56V4zFLb6DjfDbvAyUe3K/ysjIl1ZZLAOXSaRyZqpxR3J1Ld/yt7xJJ7uuvv97WIXRqsSEeGhhydCRCdkml3l9/SEl55S2e6+vqpCuGWZ8m/G5nBtPKtqGBwR4aENywXD7ccFjJ+S2XC9pf+u6NSlq/WAZHowaec3WDfS5evpr856e0Yd7zyty7RaW5R0e+hQ0ZIp+I3se+HdrIgCB3jenhrWqzRYvisuu2J+eVq6rGLC8Xo/oHuisuq+EajaPrrcVtMjqosqbpEd84MYNDPTUo9OgIkaziSr29NlmJuWVNHt/D10WTex+d8rWi2qz5Gw9rNVPHt5sD2/7QjhWL5OBo1MSLr2vymMzkA9q1anHda6OzSadfdbtiJ57RUWGinQwN89LgsPrXaIVeX5Wkg8dcoz39XHXOgEAt35+jPRnFHR1mt3Vo5wbtW/OrHByNGj7rmrrtlaXWMqgoLtTm7z5UvykzFXvGRXJycVfK9nX644s3tWfpt/IKDFX/qbNsFX6XlbzjD8Wt/kUOjkaNvuDaBvu8g8I07pKbFTlolDz8g1VRWqT0+J1av+B9Hdy8WhazWWfd8Q8bRd61DArxbNR2fW9dyom1Xd2cNGe4te367Q7aru0lZecGxdfew0acf/QeVlF7DysvLtSmbz9U/ykzNeiMi+Tk6q7k7eu0/vM3tbv2HjZgGvewthS/ZZ02//6zHByNOv2yppfzA9auWqEfv/taRqNRN99+l63D6ZZih4zQmTMv1IBBQ+XrH6DszAytXvabvpj3nv733zfl5u6h8y+50tZhdksb163W5o3r614Hh4Tpocf+pb79Y20YFTasX63NG+qVS2iY5j72L/UbQLnYWl5OtnZt3SgHB0eNn3aWrcNBre76W98lktyDBw/WlClTNGnSJE2ePFkRERFt/hkVFRWqqGg4PVpNVWWTT/h3Ni8tT5QkuTo5KMLbRbNig/Tg6b30zfYMLdyT1ex5zo4G3TEpUp4uRm0+VKjlCSQj2tIrK5MkWcsl3NtFMwcE6m/TovXtzgz9XC95h45XlJGijZ+8KFksGjTrBnmHRzfYX5B6UGvffVwGg4PG3fSI/HvHqqaiQoe3rdbuhR8pa/9OTb3nOXkGtf29qDsL8nDWVSPC5GAw6LudGXVrc0tSebVZqxPzNa23n+aMCNVX29K1L7tUniajZvQPULCHqe5YujtP3bNLD0iS3JwcFOHjqgsHB+uRM2P05dY0fb+r8XTH3+3M1Hc7M+XkYFCwp0nT+/rrpnGRGhHhpVdXJjF6tI3lpCbrp7eelSwWTb3iFgX1aPrBm/EXXKXxF1yl6spK5WUe1rYlP+rXD17R/i1rdcHd/2gwg0V3ZM91v38t3i9JcnNyVA9fF100NET/N6OvPtucqm931C7FYZBundBDJZU1mr/xsC3D7VYK0lO08sPnJYtFIy+8scHUvRazufbfNQqPHaVxV/y5bl+fCWeppqpS6z9/Qzt++YIkdxvLT0vR7+9by2XsJTfJP7LhdHt9xp3e4LWTyUUxY09TWL+h+vKftytx61plHNij4F4DOjLsLumFZQcl1bZdfVx0fmyQHpreW19vT9ePu4/fdr1zYo/atmuBliXkdlTI3Up+eopWfGC9VkZddMw9zNLwHjZ+ztF7WN/ae9i6z97Q9l++IMndhrIOJ+vr156WLBadddWtConigevWaKreV1HpKJPJ1MwZ9iUp8YAe/8eDslgsuuOev6lP3/62DqlbuuqmOxq8Do+M0mXX3KQ+/Qfqsb/doU8/eEtnz7pIJhPLrHW051+zjq4vLirUgYR9mvf+W/rL7Tfoxlvv0lU3MMLeVl6sXy779+nj/76le2+7QTfddpeuplxsau2yX2Q212jIqPHy8QuwdThQ9/6td7B1AG1h165deuutt3T11VcrKipK0dHRuvbaa/Xuu+8qLi6uTT7j6aeflre3d4N/tn37XssndiJlVWbtyy7VqysSlZhbpgsGB6mnX9PT6jkapNsn9FC0n5vis0r07rqUDo62+yirMmt/dqn+sypJSbllOj82SFG+VGhtpSw/R2ve/j9VlRYrZtpsxUw9v8F+c0211n/4jMoKcjX2hrkKHTRWzq4ecvXxV8zU8zXg3GtUVVqkPT9/YqNv0DV5uxj1p3GRcnN21LKEXK1sYgTwwj1Z2ppaKE+TUTeMidBT5/bV3Om9NDjEQ9/szKg7rqzK3OhctE5plVnxWSV64fcDOpBTqouHhii6md8VSaoyW3SooFwfbTisX+OyNDzCW2f1pTLclopys7XghYdVXlKkkTMu1sizL2zxHKOzswIjonXGdXdp+JkX6MDW9dq8+LsOiLZza6rut+fH/9o6rJNSWlWjuMwSPftbghKyS3XZ8FD18neTJJ07IEjR/m7636bDKqpgdouOUJKfrcWvParK0mINnH6hBp4+u8F+o+no/TNm/JmNzo8Zb51loTQ/R4WZqe0aa3dSkpetn/79iCpKizX4zIs0ePrsEz7XzcdP/SZayypl56Z2irB7Kqsya19WqV5ZnqjE3FLNHhx83LbrHROjFO1vbbu+vZa2a3soyc/W4v9Y72Gx0y9U7DH3MKd697A+TdzD+nAPa3OFuVma//SDKi8p0viZl2rcuRfbOiS71VS979UXn7V1WG0iKzNDf73rVhUVFuryq67TZXOuafkkdKjho8crpt9AlRQXKX73TluH0615eHppyLCRevrlN9S3/0B98M5riqNMbM7D00tDho/UM7Xl8t+3KRdbW710kSSmKu8suvtvfZdIci9fvlxPPPGEzjrrLHl6eiopKUnz58/XbbfdptjYWAUFBemiiy7Syy+/rI0bN8psPvkEx9y5c1VQUNDgn6Gzb26Hb9P+aizShuQCORgMGlpvKssjDJJuHBuhwWGeSs4r039WJqmK9WvbndkibTxkLZchoY3LBe2vsqRIq996VKV5meox5gwNOr/xVG+5iXtVkpUqd/9g+UTGNNofPnSiJCk7YVe7x9tduDk56NZxkfJzc9L65PwmRwpLUo3Zoo83puo/q5K0OD5baxPz9XNclp5bdlDxtdOXZxVXMmq4HdRYpPVJ+XIwGDQ8wuuEzllV+6DCiMgTOx4tKysu1FfPz1VhdoYGTT5b0+ac/JPNA2unKk/YvKatw7M7TdX9Bpxnn1OA1liktYl5cjAYNLL2mhsZ6SWzxaIpvf30j7NjGvzj7WodxX/v1Gj94+yYJuuLODkVJUVa/J9HVJKbqZjxZ2rURY3bER7+QUf/2y+40X6js4tcPH0kSeVF+e0VardSXlKkn155WMU5meo74UyNu+Tk23feQWGSpNICRg63hxqL9Edt23VYM23Xm8ZFakiYp5LyyvTqikTaru2goqRIv/77ERXnZqrP+DM1+uIW7mH+x7+HlXEPO2WlxYWa99QDKsjO0LBpM3TW1bfZOiS71lS9756/PmjrsE5ZYUG+/nLnLUpPS9W5sy7Unffeb+uQ0IywiB6SpNyc5mctQccxGp007YwZslgsWrtqma3DQS2j0Umn1ZbLmpXLbB1Ot3U4+aCSEvbKxdVNI8dPs3U43R6/9V1kuvLJkydr8uTJkiSLxaJt27Zp5cqVWrVqlVatWqW0tDR9++23+u4766gkd3d3jRs3ru68adOmtfgZJpOp0TRF9jBdZXOKK6slSZ4mx0b75owI1dgoH6UXVujl5YmMeuxAxbUjqTxNXeLStCvVFWVa887/qSgjRWFDxmvE5XfKYDA0Oq6swDqVvJOLW5Pv4+TqLkmqKmNt07bg7GjQLeMiFeJl0vbUIn2xNb3Fcw7mljVad3ZUbeI1Iae0XeKEVFRh/V3xOsH7F/e7tlVZXqYFLzysnMNJ6jNqks666d4m72EtcfW0XiulhQVtHaLd6Wp1v7pr1OXoNedgMGhgSPMJ7L5B1t+05ftJ3p2KqvIy/fb6oypIS1aPYRM0/qq7m7w+nV3d5eEfouKc9Lq1beuzmM2qrK1f1B/1jdapKi/Tz68+qry0ZPUcPlFTrr2nVffNI2XlxNSi7eZ4dYarRoZpXG3b9aVlB2m7toOq8jL9+tqjyk9LVtSwCZpwdcv3sMoW7mFO3MNOSUV5mT55+iFlHUrSgDGTdf6f/tqq+xeOaqreV1FUbaNo2kZpaYn+evdtSjyQoKmnnaEHH/knfyedWHFRoSTJxZX7Y2fh7eMjSSrIY/nOzqSuXPIpF1tZteRnSdKoidNkcqENZEv81lt1uZ5lg8GgYcOGadiwYbrrLuvi6gcOHNDKlSu1YsUKrV69WvHx8VqyZImWLFkig8Gg6mr7rri2Rt9Aa6dlZnFlg+2zBwXp9D7+yimp1EvLE5m+soP1CbQmTrNKKls4Em2pprpK695/UnnJaPTKAgAAmQtJREFU8QrqP0Kjr7lfBofGD4BIkounrySpKPOwqspLGyW785L3SZLc/IIanYuT4+hg0I1jIhTl66q4zGLN23S41etpT4y2ltu6pPw2iw8NDQjykNT4d6U5/YOb/h3CyauuqtS3rzym9AN71XPwKJ13x1w5NHMPa8mhuB2SJJ/akYnoOgYGW6/RjCLrNff4L/ubPfY/Fw9UoIdJd3y5U7mlVR0SX1dVU1WlpW8/ruzEeIUNHKkpNz543OszcshY7fn9O2Xs267wgSMa7Ms6GCdzdbUcnUzyDo5o79C7tJqqSv3yxj+VlbhXEbEjNf2W45dLcywWixK3WGe+COjReIYftI0jD9wcW2e4cHCwTu/jr+ySSr2w7CBt13ZQU1WlJW9Z72HhA0dq6k3Hv1Z6DBmr3b9/p/T4xvewTO5hbaK6qlKfPf+IDifEqffQ0br47kdaXe/7f/buOy6uKv//+HtoM/TeIUAgpJDemyYmlmg09tXYXcsWddetdt396drdr+6uXVeN3bVr7KZqeq9AQkIIHULvMzC/PwZICEMgCTAMvJ6PRx7KvedePpOTc+fc+7nnHPRfDQ0NuutPt2n3zu2aPG2G/vbwE3J15d9JX1VeVqJd2zdLkhKHDHdwNGixddMGSVJUTKyDI8GRtm5urpdo6sURrFarVi/9VpI0c845Do5mYOO7/rB+MV15ZwYPHqxrr71Wr7zyit577z3de++9CggIkNVqldXaP6cySwrxUkqEj45+b8PVIM0ZEqRpcQGqtzRpfVZF674zkoN1bkqYymrNempZJg81e0BisKdSwtvXi4tBOi0xSFPjAtRgadKGg4yg6y3WpkatX/SEivZsU/DgFE25/i65uLl3WD4ofpiMPgFqbKjT1o9eVKPlcDupLT+k7Z++IunwtOU4MQZJV0+IUnKotzIO1ei19TnqbObJAE83+Xi0/TJ3dzHoF2MiFBfoqXVZZcoqq+u5oPu5IaFeGhXpa/d75YzkEM1ICFS9pan1RQJfo6tmJwbJw7X9G4QjI3x0+bhISdKKDEaInoympkYtfu4RZe3aopihI3X+7+6X6zGuYTUVZdq29CuZ69u3hcwdG7X8vZclSSNPPbPHYkbPSA711pgo+230rGEhOmVwkOotTVq9nzfee0tTU6NW/Pcx5adtVVhSik67+Z5jtk9JGjHnArm4uSl1+Rcq2p/aur2uqlzrPnxJkm1tblf3Y58HHWtqatSPrzym3NStihgyUmf++t5j1kttZZl2Lv1CDXVtZ4Mx19Xqp7f/o8L9afL0C1TCuOk9HXq/lRTipZEd3LvOHRKs6c33ruuOuEc6IzlY5zXfuz65dD/3rj2gqalRy/77mPLStio8KUVzftWFa9hc2zVs9/IvVLjvqGvY/2zXsCFcw05YU1OjPvzXQ9q/c7MGDRuly/74d7l1UicYeBobG/W3e/6ijevXasy4CXr4iWfk7sSzEfUXu3ds0ZqVS9XY2PaFrIK8XD18759UV1uryTNmKSSs/XIP6Bk7tm7WutU/tVvW1GIx65MP3tYP33wpo9Gk2afPc1CEA9P2Y9TLxx+8re+/ttXLaWdQL46QtmOzigvzFBgSphFjJzo6nAGL7/q2+t1I7iPV19dr7dq1rdOWr169WhUVFbJarXJ1ddX48eM1Y0b/TESF+Xjol1NiVFln0YHSWlU1NMrHw1UxASYFeLqrwdKk19Zlq7TW9jAgNsCkS8dGSJKKq82aPyLU7nlX7ivV3mKm+z1RYT5GXTcpWpX1FmW11oubov2NtnppbNLrG3JUWnt4dgE/k5t+M+3w22kRvrYptBaOi1Rd83R82/Or9NVu1u05ERkrFytv+2pJkoe3n7Z++LzdciMX/FJGH3+5unto7C9+q3WvP6aDG5aoaM9WBcYmqdHcoJLMVFnqaxUQk6jkuZf05sfod2YmBLauTV/d0KiLR0XYLffFrkJVN9huEoeEeOsXYyJ0sKxOpbVmubsalBDkJW8PV6UWVunDbQW9Fn9/FOFr1M3TBqmizqLMkhpV1TfKx+im2ACTAr1s3ysvrc5qfchsdHPRDVNjddXEKO0vqVVJjVlGVxdF+BkV7W+bzujr3UW81HOSNn//ufZs/FmS5Onjrx/e+LfdcrMW3iwvX3+Z6+v03WtPa8nbzysiYYh8AkNlrq9TaX62SvIOSpImnHWRkied0mufAd0j0s+o38yMU0WdWfsO1aqq3iJfo5tiAz0V1NxGn//pgA6RCOo1qcu+UNZW2yhfk7e/1rz3nN1yEy+6QSYff0m2dWynXn6rVr39jL75518VmjBM7p7eKtq3W/XVFQqKTdKEC5xzbfi+YufSL1pHX5t8/PTTO8/aLTf1khtl8vWXpb5eP7/7nNZ9/JpC45Pl5R+o2spyFWdlqL66Qh5ePjrj1/fIjenKT1i4r4dumBK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",
      "text/plain": [
       "<Figure size 2000x900 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_predict_table(desire='Eat', choice_type='mode', x_label='income_group', y_tick=['WK','PT','CA'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "# eval\n",
    "def evaluate(desire, choice_type):\n",
    "    columns = ['model', 'desire', 'num_sample', 'choice_type',\n",
    "           'MAPE','KLD']\n",
    "    df = pd.DataFrame(columns=columns)\n",
    "    error_tables = {}\n",
    "    # evaluate_rf \n",
    "    age_error_table, income_error_table, error, kl_divergence = evaluate_rf(desire, choice_type, num_sample=1000, seed=42)\n",
    "    error_tables['RF'] = {'age': age_error_table.abs(), 'income': income_error_table.abs()}\n",
    "    df.loc[len(df)] = ['RF', desire, 1000, choice_type,error['mean'], kl_divergence['mean']]\n",
    "\n",
    "    # evaluate_xg\n",
    "    age_error_table, income_error_table, error, kl_divergence = evaluate_xg(desire, choice_type, num_sample=1000, seed=42)\n",
    "    error_tables['XG'] = {'age': age_error_table.abs(), 'income': income_error_table.abs()}\n",
    "    df.loc[len(df)] = ['XG', desire, 1000, choice_type,error['mean'], kl_divergence['mean']]\n",
    "\n",
    "    # evaluate_mlp\n",
    "    age_error_table, income_error_table, error, kl_divergence = evaluate_mlp(desire, choice_type, num_sample=1000, seed=42)\n",
    "    error_tables['MLP'] = {'age': age_error_table.abs(), 'income': income_error_table.abs()}\n",
    "    df.loc[len(df)] = ['MLP', desire, 1000, choice_type,error['mean'], kl_divergence['mean']]\n",
    "\n",
    "    # evaluate_gl\n",
    "    age_error_table, income_error_table, error, kl_divergence = evaluate_gl(desire, choice_type, num_sample=1000, seed=42)\n",
    "    error_tables['GL'] = {'age': age_error_table.abs(), 'income': income_error_table.abs()}\n",
    "    df.loc[len(df)] = ['GL', desire, 1000, choice_type,error['mean'], kl_divergence['mean']]\n",
    "    df['MAPE'] = df['MAPE'].apply(lambda x: round(x,2))\n",
    "    df['KLD'] = df['KLD'].apply(lambda x: round(x,2))\n",
    "    return df, error_tables\n",
    "\n",
    "# plot\n",
    "\n",
    "# def combined_plot(error_tables_list, desires, y_ticks=None, x_ticks=None, group='age', filename=None):\n",
    "#     n_models = len(error_tables_list[0].keys())  # number of models in each table\n",
    "#     fig, axes = plt.subplots(len(error_tables_list), n_models, figsize=(20, 8))\n",
    "#     for k, (error_tables, desire, y_tick) in enumerate(zip(error_tables_list, desires,y_ticks)):\n",
    "#         for i, model in enumerate(error_tables.keys()):\n",
    "#             ax = axes[k,i]\n",
    "#             # format as int\n",
    "#             sns.heatmap(error_tables[model][group], annot=True, ax=ax, cmap=\"Blues\", fmt=\".0f\",\n",
    "#                         vmin=0, vmax=30, cbar=False, annot_kws={\"size\": 15})\n",
    "#             ax.set_xlabel(\"\")\n",
    "#             ax.set_ylabel(\"\")\n",
    "#             if k == len(error_tables_list)-1:\n",
    "#                 ax.set_xticklabels(ax.get_xticklabels(), rotation=0, fontsize=15)\n",
    "#                 if x_ticks:\n",
    "#                     ax.set_xticklabels(x_ticks, rotation=0, fontsize=15)\n",
    "#             else:\n",
    "#                 ax.set_xticklabels('')\n",
    "#             if k ==0 :\n",
    "#                 ax.set_title(f'{model}', fontsize=20, fontweight='bold')\n",
    "#             if i == 0:\n",
    "#                 ax.set_ylabel(desire, fontsize=20, fontweight='bold')\n",
    "#                 if y_tick:\n",
    "#                     ax.set_yticklabels(y_tick, fontsize=15)\n",
    "#             else:\n",
    "#                 ax.set_yticklabels('')\n",
    "            \n",
    "#     plt.tight_layout()\n",
    "#     if filename:\n",
    "#         plt.savefig(filename)\n",
    "#     plt.show()\n",
    "\n",
    "def combined_plot(error_tables_list, desires, y_ticks=None, x_ticks=None, group='age', filename=None):\n",
    "    n_models = len(error_tables_list[0].keys())  # number of models in each table\n",
    "    fig, axes = plt.subplots( n_models, len(error_tables_list),figsize=(20, 15))\n",
    "    \n",
    "    for k, (error_tables, desire, y_tick) in enumerate(zip(error_tables_list, desires,y_ticks)):\n",
    "        for i, model in enumerate(error_tables.keys()):\n",
    "            ax = axes[i,k]\n",
    "            # format as int\n",
    "            sns.heatmap(error_tables[model][group], annot=True, ax=ax, cmap=\"Blues\", fmt=\".0f\",\n",
    "                        vmin=0, vmax=30, cbar=False, annot_kws={\"size\": 15})\n",
    "            ax.set_xlabel(\"\")\n",
    "            ax.set_ylabel(\"\")\n",
    "            ax.set_xticklabels('')\n",
    "            ax.set_yticklabels('')\n",
    "            if k ==0 :\n",
    "                ax.set_ylabel(f'{model}', fontsize=25, fontweight='bold')\n",
    "                if y_tick:\n",
    "                    ax.set_yticklabels(y_tick, fontsize=15)\n",
    "            if i == 0:\n",
    "                ax.set_title(desire, fontsize=25, fontweight='bold')\n",
    "            if i == n_models-1:\n",
    "                if x_ticks:\n",
    "                    ax.set_xticklabels(x_ticks, rotation=0, fontsize=15)\n",
    "            \n",
    "    plt.tight_layout()\n",
    "    if filename:\n",
    "        plt.savefig(filename)\n",
    "    plt.show()\n",
    "\n",
    "# group df\n",
    "def group_df(df):\n",
    "    # Pivot the data to create a grouped table with 'desire' and 'metrics'\n",
    "    pivot_df = df.melt(id_vars=['desire', 'model'], value_vars=['MAPE', 'KLD'], \n",
    "                    var_name='Metrics', value_name='Value')\n",
    "    pivot_df['desire'] = pd.Categorical(pivot_df['desire'], categories=['Eat', 'Shop', 'Recreation'], ordered=True)\n",
    "    # Reorganize the table to get a grouped format with models as columns\n",
    "    grouped_df = pivot_df.pivot_table(\n",
    "        index=['desire', 'Metrics'], columns='model', values='Value'\n",
    "    ).reset_index()\n",
    "    grouped_df = grouped_df[['desire', 'Metrics', 'RF', 'MLP', 'XG', 'GL']]\n",
    "    return grouped_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Mobility Choice"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Start evaluation: choice_type = mode\n",
      "Random Forest:disire-Eat choice_type-mode\n",
      "MAPE: 10.79\n",
      "KL Divergence: 0.09\n",
      "========================================\n",
      "XGBoost: disire-Eat choice_type-mode\n",
      "MAPE: 15.19\n",
      "KL Divergence: 0.19\n",
      "========================================\n",
      "MLP: disire-Eat choice_type-mode\n",
      "MAPE: 14.96\n",
      "KL Divergence: 0.6\n",
      "========================================\n",
      "Graph RAG+LLM: disire-Eat choice_type-mode\n",
      "MAPE: 5.55\n",
      "KL Divergence: 0.02\n",
      "========================================\n",
      "Random Forest:disire-Shop choice_type-mode\n",
      "MAPE: 7.04\n",
      "KL Divergence: 0.05\n",
      "========================================\n",
      "XGBoost: disire-Shop choice_type-mode\n",
      "MAPE: 10.08\n",
      "KL Divergence: 0.15\n",
      "========================================\n",
      "MLP: disire-Shop choice_type-mode\n",
      "MAPE: 6.97\n",
      "KL Divergence: 0.05\n",
      "========================================\n",
      "Graph RAG+LLM: disire-Shop choice_type-mode\n",
      "MAPE: 5.15\n",
      "KL Divergence: 0.02\n",
      "========================================\n",
      "Random Forest:disire-Recreation choice_type-mode\n",
      "MAPE: 11.74\n",
      "KL Divergence: 0.25\n",
      "========================================\n",
      "XGBoost: disire-Recreation choice_type-mode\n",
      "MAPE: 15.34\n",
      "KL Divergence: 0.32\n",
      "========================================\n",
      "MLP: disire-Recreation choice_type-mode\n",
      "MAPE: 16.15\n",
      "KL Divergence: 0.8\n",
      "========================================\n",
      "Graph RAG+LLM: disire-Recreation choice_type-mode\n",
      "MAPE: 6.96\n",
      "KL Divergence: 0.03\n",
      "========================================\n"
     ]
    }
   ],
   "source": [
    "print(\"Start evaluation: choice_type = mode\")\n",
    "eat_mode_df,eat_mode_error_tables = evaluate(desire='Eat', choice_type='mode')\n",
    "shop_mode_df,shop_mode_error_tables = evaluate(desire='Shop', choice_type='mode')\n",
    "recreation_mode_df,recreation_mode_error_tables = evaluate(desire='Recreation', choice_type='mode')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "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>model</th>\n",
       "      <th>desire</th>\n",
       "      <th>Metrics</th>\n",
       "      <th>RF</th>\n",
       "      <th>MLP</th>\n",
       "      <th>XG</th>\n",
       "      <th>GL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Eat</td>\n",
       "      <td>KLD</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.19</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Eat</td>\n",
       "      <td>MAPE</td>\n",
       "      <td>10.79</td>\n",
       "      <td>14.96</td>\n",
       "      <td>15.19</td>\n",
       "      <td>5.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Shop</td>\n",
       "      <td>KLD</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.15</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Shop</td>\n",
       "      <td>MAPE</td>\n",
       "      <td>7.04</td>\n",
       "      <td>6.97</td>\n",
       "      <td>10.08</td>\n",
       "      <td>5.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Recreation</td>\n",
       "      <td>KLD</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.80</td>\n",
       "      <td>0.32</td>\n",
       "      <td>0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Recreation</td>\n",
       "      <td>MAPE</td>\n",
       "      <td>11.74</td>\n",
       "      <td>16.15</td>\n",
       "      <td>15.34</td>\n",
       "      <td>6.96</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "model      desire Metrics     RF    MLP     XG    GL\n",
       "0             Eat     KLD   0.09   0.60   0.19  0.02\n",
       "1             Eat    MAPE  10.79  14.96  15.19  5.55\n",
       "2            Shop     KLD   0.05   0.05   0.15  0.02\n",
       "3            Shop    MAPE   7.04   6.97  10.08  5.15\n",
       "4      Recreation     KLD   0.25   0.80   0.32  0.03\n",
       "5      Recreation    MAPE  11.74  16.15  15.34  6.96"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mobility_df = pd.concat([eat_mode_df, shop_mode_df, recreation_mode_df])\n",
    "mobility_df = group_df(mobility_df)\n",
    "mobility_df.to_csv('results/mobility_choice.csv', index=False)\n",
    "mobility_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
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t27pF+/fxkAuK9+eeWL225GChhLgknUvN0psXttHqFeone9t/x33u7ph/T/HNhqMFCXFJ2nsyST/vPCUPFwfd1CrAAtGjpNoNHq5Ot96r+q07y83z8uN+njVq6eYJr6p2k9aFVky1c3BUr3sel6OLm5LPxel0FH9DKpvuN92l3sPuV2i7riUa3w1t31UD731ULbr1lW9AbYnx3Spr96bVSk44rxq16uj64fcXlNvY2OiGEQ/Lp0aAInZt1Unu46qEBdtPadbm49oYHV9kpZb/8qvmqC71fZSTm6f3Vh4uSIhL0vrD8VoZeVZeLg4a1PTaWiXAkEnxizO+L7V27Vq1bdtW/fv3N9tm165dSkpKUp06dVSnTh2z59+7d6969+6tuLg4TZw4UW+/zSyI0moYkr/sUlZWlhITE6wbDIDLOhEVIUkKbtpKtraF/1zY2durfmgLSdLerea3pIAxdQ/OT4KtPXzeypHgamVnZerw3h2SpBadiyY9ml8oO1CKLTSA4pw+sF3Hd6xW437DVa06A6FVEf2Ca0NWZobWLf9LTs4u6j1giLXDQQVwcHAoUTs3D88KjgQVaefOHUpOTlZQUB01adK0SH2/6/MfiFi9aqWlQ4NBHLywlZaTva08XRwK/t2ubv794orwM0WOWRGev4dx94Zsp2hE9o5O8vIPlCSlxrNEPlBZnDh8+fu4ehceeN27pWhODVVboxr5D0XGJGUqNjmrSH3YySRJUrfgki/HbgSGWsekY8eOcnJyUkREhM6ePavq1atLkg4fPqxTp07prrvuUmBgoOrWrVtkNvmVlk7fvXu3+vbtq7Nnz2rSpEl69dVXK/bNGNSpEyckSfb29vLgJhuo1LIyMyRJLm7VzNa7untIkmJ4kvCa4evmoMY1qyknN08bj7B0elV35tQx5WRny83DS55m9o4KrN9IknT66GFLhwaDycnM0M4fP5F7jdoK7TPU2uGgjOgXXBuiIg8oPS1VjZu3lqOTs3ZuWa89OzYrKytLAbXrqMt1/eVT3c/aYeIq+PkHqkZAbZ0+cVSbVv1dZPn0jauWyK2ah9p2KfrAHKqOyIj85aybNC2aEM8vb5bfLjLCYjHBWAK9nCVJ2bl5SsrIn6lWx8dFTva2Op+apTgzg+/hscmSpIY13IrUoeoz5eUp+Vz+9kiuV5hxDsBysjIu3MdVM78tnlu1/BzNqSNRFosJluFsbydJSsk0v2JoUnp+eXB1V4vFVBkYKinu5OSkDh06aN26dVq/fr1uvvlmSf8up969e3dJUrdu3fTjjz8qPT1dLi4uhdqYS4qHh4erT58+OnfunF566SVNmzbNEm/HkH5cMEeS1LFLdzk6Olo5GgCXU83DS5KUcCbWbP35uBhJUnwx9TCe7vV9ZGtjox0nE9kDzgASzuYPWHj6mk9uODq7yNmtmtJTk5WZniYnl2urk4zys3/JXKWdj9N1j70qW/uSzVBE5UO/4Npw4sKDUB5e3npz8gRt27C6UP2Crz/W/8a/pG59BlojPJQDWzs7PfDUS3p/6tP64q3J+vvneapZK0hJifE6uC9MAUH19cBTL6maOw+xV2UxMfm/k2vU9DdbX/NCecypUxaLCcZyR4f8ZdI3Hj6v7FyTJMnfIz9RHlfMNlsZ2XlKSs+Wp4uDXB3tlJbFPaWRRG5epfSkBLm4eyqgYRNrhwPggov3cfFnTputL7iPO2u+HlVXYnr+Q2s13Z3M1vt75pd7ujjI2cFWGdfIvuKGWj5dMr+E+sV/d+vWreC/WVlZ2rx5c0GbyyXFN2/erHPnzqljx44kxK/CxvVr9Mdvi2Rvb68H//e4tcMBcAXBTVtJkg7s2KjUpIRCdYnnzihy9zZJUmZG2n8PhUF1b3Bx6XRmiRtBVkb+Hn8OjuY7x5Lk6JQ/sJWZzs85yib++CEdWvOb6nboI7+GLawdDq4C/YJrQ2pK/iy+7RvXaNfWjRo99ll9+cM/+mjO7xoy7B5lZWbq4zen6MghZpdWZY2attKzr30iP/9AHY2K0Ja1yxS+e7tsbGzVrE1H+V1Y/hZVV3pa/u9iF2dns/UXJ4ikpqZaLCYYR9cGPrqplb+yc/P0xZojBeUujvkz0jIvM6h+ccDd9UJbGEPy+TNaO/9zSVKnW+6VnQMToYDKouA+bvtGpfznPi7h3BlF7N4qiXEfIwqPTVFWTp583BzVoa5XkfoBTf6dJOPqcO38XTZsUvzS5dHXrVunkJAQ+fnlf8gXk+MX20RFRSkmJka+vr5q0qTok2ytW7eWm5ubtmzZomeffbai34IhHT1yWNNffk4mk0mPPDFBDUMaWzskAFcQ0qqDAoNDlJmRri//7xkdO7hfmelpOhKxVzP/b6LycvOf6raxsbFypLCEej4uCvJyUUpmjrYfT7R2OACqAFNernZ8/6EcXNzU4qbR1g4HV4l+wbXBlJefrMjNzdWwUQ9rwE3D5OHlLb+aARo55kl1vq6fcnNy9NsPs60cKa7GptVL9cr4B+RTvYZefPsrffrjSs34fKG69btBf/88T28+/5iys4sufQwAdX1cNGVIY9na2OjDFYd1MI4HK6512ZkZ+uujacpISVRwm65q3vsGa4cE4BKhrTuq9sX7uOkTdfSS+7gvpz99yX2c4VKF17zUrFz9uid/BYBn+zdQ92AfuTnaKcjLWS8NbKS63i4FbU0ma0VpeYZaPl2SunbtKltbW+3YsUPp6elKSUlReHi4Ro/+dyCuRYsW8vDwKEiKX5xJ3r17d7ODOK1atdKbb76pG2+8UW+88Ybc3d314osvljimzMxMZWZm/qfMVk5Oxc/MMpIzcbGa+MT/lJyUpOF3j9Kwu+6xdkgASsDGxkajJk7XV68+qxNR4fpg0v8K6ty9fHT98Pu1ZP5MubiZ35MGxtIjOH9PsM1HE5STdw31lAzM0Tm/85udZX55Q+nfPYRZOr10zPX9crKzZH+NzZg4uPo3JZw8rHZ3PiGnaizDW9XRL7g2OF/y+773gJuK1PcaMESb1izTgd07LBkWylHsyWP66t1p8vD01pOT3y74zGsG1tGox59Twrkz2rV1vdb987t6D77NytGirFxc8z/X9Av7iP5Xenr+ikFubuztXB7M9f3ycrJka2+svp9fNUe9d0dLebo4aO7m4/p+28lC9ekXlkN3cig+seJ8oY6l040hNydHSz75P8UdOaiARs10/cNMJgMqGxsbG9038f8089VndDwqXO8/93BBnbuXjwYMH62/5n8p12L2HEfVNnPDMdWo5qSejXw17cbQgvKs3Dx9tOaIxvUOliSlZJnfd9yIDJcU9/T0VMuWLRUWFqZNmzYpISFB0r/7iUuSra2tOnfurI0bNyo3N7cgKW5u6fSL+vXrp4ULF+q2227TSy+9JA8PDz3xxBMlimnGjBmaOnVqobIJz72oiZNeLuW7q3qSEhM14fExOh1zSoOH3KLHxj1t7ZAAlIKPn7/Gv/WV9m5eqyMRe5WdlSn/oPpq26O/9mxeI0nyD6pv5ShR0WxspC71Ly6dft7K0aC8eFWvISl/2WNzsjLSlZGaIhc3d5LipWSu79f97sfVY8RYK0VkHTH7tkg2Njq6dbmObl1RqC4jOX8bhs2zXpOtvYNC+94u/ybtrBEmSoF+gfFVv7DPsJOzszy8vIvU+9WsJUlKTKA/UFVtXrNMuTk5at6uc6GHIC7q0KOfdm1dr4i9YSTFq7CAgABJUlys+f1BYy+UB9SqZbGYjMxc369Wn1Gq3e9+K0VU/jyc7fXBnS1Vy8tZv++K0QcrDhdpczop/yGMGsXsXersYCsPFwclpmeTFDcAU16eln31lo7u2arqdRroxienyv4yW3MBsB6fGv6a8PbX2rN5rY5E7FF2Vpb8g+qpbY/rtWfzaklSzaB61g0SFSI716Spf0WqxS53dajrJS8XB8UlZ2pl5DldnPJ0IiFd2bnXzgQowyXFpfzkdlhYmNatW2c2KS7lL6G+dOlS7d69+7L7iV/qpptu0nfffaeRI0dq3Lhxcnd31/33X7mDO2nSJI0fP75QWUKm8ZejSEtL08Qn/6cj0VG6rnc/TXxhKsspAlWQnZ29WnXtrVZdexcqPxKxV5LUoFlrK0QFS2oR4C4fVwedSclUeCzL4xmFX606sndwUGpSghLPn5Gnj1+h+pPRByVJ/nWDrRFelWau7zd95TErRWNlJpPORu0rtvr80fx9iet27GupiHCV6BcYW/2G+dtcZWVmKjsrSw6OhWc5piTnb6FiLpmKqiH+XJwkycW1mtl6lwszh9Mu7C+PqikkNP9n+cD+/WbrD+zP/9scEhJqth6lY67v1/f9zVaKpvy5ONjq3TtaKNjPTSvDz+jVvyLNtjt2Pl2ZF/Yu9avmqDMphbdhaFwzfxbiIZZcN4Q1cz/Rwc2r5FUzUDeN/z85FfN3BUDlYGdnr9Zde6t1MfdxDZu1sUZYsJA9p5K151Th/n3/xtUlSbtOJFkjJKsxbFL8ww8/1Lp16xQfH6+aNWuqUaNGhdpc3Fd80aJFioyMlJubm9q2bXvFc991111KTU3VQw89pIceekjVqlXTsGHDLnuMk5NTkaXS05OyS/muqpasrCw9P2GsDuzbo46du2ny/70pOzs7a4cFoJwkxZ/T7k2r5OruqRadelo7HFSw7heWTl97ON7KkaA8OTg6Kbh5W0Xu3Kw9G1ep+w2F+zN7N+U/LdykXVdrhFelmev7XWtLp0tSz8dnFFv317QHlBYfp0GTv5GrV3ULRoWKQL/AOKrX8Ffd4BAdPRyp/bt3qFX7zoXqLy6bXr8BibSqytPbV5J05FC42froyAOSpOo1AiwWE8pfmzZt5e7uruPHjyn8wAE1btKkUP2ypX9Lknr26m3ucJSSub6fUZZOd7Cz0Zu3N1fzWh7aePi8Xvz1gIrbTSszJ0/bj8arawNf9W3ipwVbCy+v3ufC4Pu6Q+cqOmxUsE2LZmnPysVy962hm5+eIVcPL2u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9l3+QRlxwuUIiIhUcHqmln7+rpJjoVqwYTVVRZdL8zYf19cZD2pdxPPjydbXX21f3V88gNz10Xnc9+dPxkPRwTrG+Wn9QO4/kKS4lX4+e30OjIrwtUT5OQXllpT5dukPv/bxN8Qeza5YHejnrx+emalA3f73+j7N14+u/1az7x1u/N/hZHi72uuJs80N381bubtnC0SQ1fX+/xNXv+3vyPHPf380jdeNbq+rs9/Ujk471/W3RrO+30vfXxsUdKVBSepF2pxYoPrVA39w85IT9fg+dE6EQT0etT87Wc4vjVVJhHilqbIS3nr8wUk+d30PXzN7coUaJNPyc4iaTSddff71KSkr03HPPadasWXUCcUmytrbWZZddps2bN2vo0KH1PmPOnDmSpI8++kiurq5avny5jh492ir1t2U/bDuiudGHtXF/jrKLG28QV+sbZO7snLc5RbX+tqqorFI/bDsiyTz8A9qO+ZsO6YnvdtQJxCUpPa9Uz/ywQ5J0fv9A2dlY1ayLO5xX7wu2JG3bn6NftqbI2tpKo7qf+tNMaHk/bDiox+ZtrxOIS1JaXqme/Ha7JOn8gcF1z/Oh3HqBuCRt3ZetRZsPy9raSqN7+LZs4ThlX63co7s/XF2nUSxJR7OLdf/H5jc+p43sIrtajajLx4RrfP8QzY9K0kvfbK7TKJakfan5yswvbfHa0TTcm9HSxl9yrc69+hb1HjpGbl4nv5+v/uU7SdLEy6+vCcQlqXNkX42cPFXFhQXatGJJi9WL5vXdF/9Tfm6OZtx2b71AXJK69WQ4fKCtWBqXpteXJdYJxCUps7Bcb/yeKEka18NXttbH2/hXDw2RJH2x/kBNIC5JcSn5WrD9iNwd7XRRv8BWqB6n4sdNh/Xk97F1AnGp+vu6+SGlv39f39nY9/UDOVq87dj39W58X8dxY6deowlX3KTIIaPl6nny0DNy6Gidf8Od6jdmknyCOkmyOuk+sKxfYo7q5SUJdQJxScooKNOspQmSpAk9694v/krI1JvLE/VrbJoOZhXLZKrbX4C25as/duvu91bWCcQl6Wh2ke7/cJUkadroiDp9Qo25bGx3OdrbasOuI0pK6Vhvl7Z1X63co7s/imq47+8T84gf9fr+RnfV+H7Bmh+1Vy99u4W+v3ZgXvRhzV5/UOuSs5XVQJuuNj9Xe40O91ZFZZXeWrG3JhCXpDVJWVqRkCFPZztN6RPQ0mW3KYYPxX/99VfFxsaqU6dOevLJJ0+4rYeHh/r2rduRs2vXLm3ZskXBwcG66KKLdNlll6myslLz5s1rybINqbzq5A2k/EbmtUDbs/Ow+Q1gBzsbebrYn9I+FZXmP7zllR3nyaP2buch83l2tLOR1yme5/JK87VexnluF2KSzUNgOtrbyufYPDSSdNNk8/BpHy6Os0hdaB3cm9GSyktLlRRrHk2m38j6AWq/UcemdWjCkJywnLLSEq3+Y6kcHJ004fyLLV0OgDOQmFYoyTzvuIeTeQBBe1trDQ7zlCStjM+ot8+qY8vG8CZgu7Arpenf1/keB+Dv9hx7ScbB1kaeznYWrgYtISbZfH839wk5nnT7ayaY+4q+5i3xdoW+v46p+iWXI3mlSm3g4YZtB80PtnS09r3hh09fvHixJOmKK66QrW3TD7f6LfFrrrlG1tbWmjFjhr788kvNnTtX999/f7PWanRbD+Zqck8/XTMkuN4QrdMHBkmSlu1Ot2CFaIowX/Mf1bKKKuU28Mbw30UGuemiQcEqq6jS6t31O1nQNnX2Nc8jWVZR1eAbBX/XM9hdU4eEmM/zrrSWLg/NoGuguySprLxSWccaSLY2VhrdK1DlFVXalJCmvp29ddmYcPl5OCkls1C/bNynHfuyLFk2mgn3ZrSk9JQDqigvk4u7pzx96s9BHNLVPOzekf1JrV0aTkNSwi4VFxWqZ9+Bsndw1NaNUYrZvEHlZWUK6hSmUeMmy9vXz9Jlohn9vmSB8vNyZW1lpeDQzho+Zrz8AoIsXRaaQbCnudO7vLJKeccefuvs7SQHW2tlF5YpvaD+MJnxx95G7ubHCDLtQZjP8e9xp/x9fWCQyiqqtKaBhyIAdEwhXk6SzPeL3FMYiQztT0N9Qo0J9XPVmD7BKiuv1A9/7WmN8tBMGu/7CzD3/e1JN/f9je4qPw9HpWQV6ZeN++n7a+cc7WwkSfmlDb/sknvse0DEsf7/jsLwofi2bdskSYMHD27yviaTSV999ZUkacaMGZKkSZMmKSgoSFu2bNHOnf/P3n1HRXXtbRx/Zui9F0WwoFiw95bYo1Fjijemx/T6plfTY3q76fUm0cSYbmKJ0ZjYEntvKCBVRUVBem/vH6MoARQRGDh8P2u5lHPODL9Zx9lzZj9n771bXbp0qbNajW7m+gNq7+eiiV0D1DfEUzFHc2Rva1bnQFcVFZfq9aWx2nGQdauaihvPbytJWrnnSJV3ko8K99eFPVrI1sasll6O6tPWMlXHtO93aF9qbqXj0TjdPCJUkrRid7IKiyuf59HdAjX++NTqLb2d1Ledj4pKSvXo7K1KTOE8NwV3T7TMkLJk64Hyc9w2wF1ODrY6nJareyd103PX9JONzcnJZZ66so8+/G2XHv1yrVVqRt3hsxn1KT3FcnOUh0/VQam9o5OcXFyVl5OlgrxcOTg1ry9iTc2BxDhJkrunl15/5iFtWrOywv7vvvxQdzz0tIaOHGeN8lAPfv7m8wo/f/XJ2/rPdbdqynW3Wqki1JUpvS1rxa+PTysfHRxwfNTQkSoCcUnKLypVZn6R3J3s5Gxno9wi1hVvzE58X/878mi139fHdQ+UrY1ZQV5O6t3Gy/J9/Ue+rwM46ar+luWP1sQeK/+8gLHcPamnJGnJlkQVFp/+s/2K4Z1kNpv0x4ZEHcvKP+2xaFzunhgu6XR9f1313NV9K/b9XdHb0vc3Y71Vasa5Sz9+M1PgKbMDnKqFu2W7h5OdnOzMzWZdccOH4qmplqkh/PzOftTCypUrtW/fPoWHh6tnz56SLOuPX3XVVfrvf/+rWbNm6ZVXXqnLcg0tLa9Ij83fo8dGt1efYA8Fup98M65OOqaYozlWrA5nY3gXf10xMFiFxaX67+9RVR7TOchd/xkQXP5zXmGJnv8lQr9sOtBQZeIcjQwP0JWDW6uwuFRvLNhT5TFdgtw1ZVBI+c95hcV69qedmrNhf0OViXMwtk+wbhjdSYVFJZr+7cby7V6ulvbZx81RL1w/QJ/8HqF35+1QZm6hJvZvo//eOlj3TOqm2EMZ+nTRbmuVjzrAZzPqU0G+pVPd3r76afjsHJyUl5NNKN4E5GRZbpDZvPZvmc02uvmexzRo2GgVFORr8dwfteCnWfrw9efUKqSt2rTvaOVqcS66dO+t0eMvUcfwHvLy8VXqkWSt+fsv/fzNF/p+xsdydnbRxMlXW7tM1NKgtl6a2D1QRSWl+t+qxPLtTvaWkST5pwm784tK5e5omVGGULzxGt7ZT1MGHP++vqia7+st3fWf/hW/r0//NUK/bkpqqDIBNHJD2nvr4l4tVFRSqo9XxFm7HNSDsX1b64YLwi19QrPWnfH4q0ZYrvG/W8bU6U3J2N6tdMOojpbz/N3m8u1erpblVXzcHPXCdf31yaLdenfezuN9f63131sGWfr+Dmfq00VV9wujcYs8nK3C4lJ5u9irf2tPbUhMr7B/XJeTM/o52dk0m1Dc8GuKn4tvvvlGknTddddV2H7i59mzZ6usjLvkaqqNt5M+vLyrWnk66vlF0br8y826btZWfbo6UX2CPfTmJV0U5HHmtUtgXaH+Lnrn2p4ym016Zf4e7almBOEHS2LU5r7f1PGh33XBqyv10/r9evXK7vrfLf1kZ2Nq4KpxtkIDXPXeDX1kNpv00q+7tOf4GvL/9t7iaLW6a65C752vUS8s1Q9r9+n1a3rpyzsGcp4bubAgD315/wiZzSY98dX6ClMimU2Wc2dna9bizfv0wGerlZCcpWNZBfp6aZSe+Mpyl+gjk3tao3TUIT6bAdRUaZnlC3JJSYmm3HC7xl58udw9veQX0ELX3X6fBp4/WiXFxZr/4ywrV4pzddWNd2rYmAkKbNlKDg6OahncWv+55mY9Pv0tSdIPX32qggJGBzVFId5OemZCR5lNJn24Ip6b3wyonb+L3r7m+Pf1Baf5vv5njNo+sFAdH1mksa+t1M8b9uuVK7rrfzf35XscALXxcdYLl3SR2WTSu3/Fam8ynxdGE9bKS18+PNbSJ/TlKu2MP/3SGT1D/dSltY/SsvO1cH18A1WJc2Xp+xtuOc9fbzhN399+PfDZmlP6/qL1xFcbJEmPXNbTGqWjDuQUlmjujsOSpMcvaK+hod5ysbdRsJejnhkfptbeTuXHNqeU0/ChuI+PjyTp6NGzWw8zPz9fP//8s0wmk66+uuJd8D179lR4eLj279+vlStXVvMMJxUUFCgzM7PCn5KiqqckMyobs0lPXtBB3s72evGPvVqfmK6cwhKl5hRp3s5kzdqYJHdHW13XL8japeI0Ajwc9dUdA+TpYq//LY/VjJVnvggqKC5V9KEsPfPzLs1YGa/RXQM09fhUbmicAj0c9c3/DZani70+/StGXyw/8x3BBcWlijqUpad+2KEvl8dqTLdA3Tg8tAGqRW209HbW/GfHy9vNUe/O26EPf9tVYX92/sm1wmYtrTy65MS2IF9XtTu+LhGaHj6b609V135Fhadfn82IHByPr2daWH14VlSQZzmWUeKNnuMp52jE2EmV9o8Yd5EkafeOLQ1WExpWz36DFNqxi3Kys7R3z64zPwCNiq+rvf77n65yd7LTdxsP6KctByvszyu0jPw+sfZgVRztLF1IuYWMEm+MAjwc9NXt/eXpYq/Pl8dp5t8JZ3xMYXGpog9n65k5EZr5d7xGhQdo6nlt6r1Wo+HaD0bi52av96/uLg8nO32zdp++28CMj0bT0sdF86dfbOkT+mWLPpy//YyPuWpEJ0nSL6tizjjNOhqHlt7Omv/MuON9fzv14W8RFfZn559cZ3rWsuhKjz+xLcjXhb6/Jux/qxO1IjpF3i72evGiTlp41wDNmtpbQ9t56/2VCeXHZVez7rgRGT4UPzHt+ZYtZ9c5M3/+fGVkZMjOzk5XXXWVhg4dWuFPSorl7qlZs848EuKVV16Rh4dHhT9xf3x11q+lKevk76IgT0clZxUotop1hv+Jtdyl1LWFW0OXhhrycLbTrDsHqJWPs35ct08vzT37aVN+PT51+piuAXVdHuqIp7OdZt8zWME+zvp+TaJe+OXsOzxPTJ1+QffAui4PdcDL1UELnhuv1v5u+uqvKD0+o/IUWfuOnhxRkngku9L+vMISJadb2nJ/D6dK+9E08Nlcf6q69pvzxfvWLqvBefpapuLKSK365tTC/Dzl5WTLycWNULwJ8PO3fK47ODrK3dOr8v4AyxrFGenHKu2DcbQMsiybk5Z6+tFEaFzcHG31zuVd1cLDUb/tPKwPVlS+uTk5yxLg+R+fSvPfHO3Mcne0U2ZeEVOnN0Ieznb6+o4BauXtrB/X79dL82vzfd0ydTrf189eVdd+82d8aO2ygLPm7mirD6/pqZaeTpq37ZDe/ivW2iWhjnm5OmjBC5eodYC7vloSoce/WHXGx5jNJl1+fgdJTJ3eVHi5OmjBsxda+v6WRunxmZXXBa/Y91d5ZhlL35/lJnZ/ZhBssopKyvTc79G658edmrXhgBbsPKwv1uzTjd9s06bj06kfSMtTUUnzGStu+FB8woQJkqSffvpJxcU1v9vhRNhdWFio1atXV/qTnJwsSfr555+Vn3/6qeOmTZumjIyMCn/ajZ1ay1fUNPke/2KdU80d5TmFlnPj6mD4Ze6bJGd7G311e3+FtXDTou2H9Pj3O2r1PMeyLTMk+FTT0QLrcnaw0ay7B6ljS3f9vvWgHp29tVbPU36e3RzOcCQamoujreY9c6G6hHhr7tp43fXR31Uel5lbpPjDlinzPat4v5pMkqeL5fyeOqocTQufzfWnqmu/yTffY+2yGpxfyxDZ2tkrJzO9ymA8Kd5y53mL1sws0hS0bW8ZHVJYUKCiwsqzXmVnZUiqOKIcxpOdbbk+cHDkprimwsnOrLcmh6utr4tWRKfotT/2Vnlc4rE8FRSXysvFvvwa4VQd/V0liSnXGyFnexvNvK2fwgIt39en/VDL7+s5lrbd25XvcWerqmu/STfebe2ygLPiZGej96/uoVA/Fy3dc0Qv/kb4aTQujnaaN/1idWnto7mrY3TX+8tq9LgRPYLVwsdVicmZWh1x8MwPgFW5ONpq3tNj1SXE63jfX9U3PlTo+3Op/Nlv6fuzXBOeOqocTdPOg1n6Ys0+vbU0TrM2HFBSer7CW1oGwWw7UPWyqUZl+FB83LhxCg8P14EDB/TSSy+d9tjMzExFREQoJSVFf/zxh+zt7XXs2DGVlZVV+Wf48OHKzMzUvHnzTvu8Dg4Ocnd3r/DHxq55hYJpuZbQpJWno5zsKv+3Czv+BfvE3eloPOxtzPrfrf3Us42XVu45onu/2qLSWt44NLC9ZTmDxNTKIxJhXfa2Zn15+0D1auutFRHJuvvLjbU/zx18JUmJdJg1Kva2Zv30xFj1C/PXki37df1bS1V6mpO8cGOiJOn8ri0r7RsQFiAHOxvlFhQrOim9vkpGPeOzuf5Ude1nZ9/8OpjtHBwU2rWXJGnHuhWV9u9ca1mGqHPfwQ1ZFmrJNyBQrUPDVFZWVuUU6Se2tW3fsaFLQwPJSE/Tnh2WmybbhXWycjWoCTsbk169NFzhLd21Lv6Ynl0QWe01fmFxqbbsS5ckjezoW2n/8OPbVscyG0RjYm9j1mc391XP1pbv6/fN2lrr73EDQo9/X0/he9zZ4toPTZ2djUn/vaKbuga5a01Mqp74ZXet2xI0Tva2Nvrp6Ynq1zFQSzYn6vrXF5+2T+hUV42wXN9/t5wbJRo7e1uzfpo25mTf33+Xn6Hvb58k6fyuLSrtGxDmT9+fwV3SwzIb3G+7kq1cScMyfChuMpn0zTffyNHRUc8995ymTZumnJyKF/hlZWWaP3+++vbtq40bN+r7779XUVGRxo4dKy+vylMDnnDVVVdJkr755pt6fQ1GsCc5W2m5RXKys9GdQ9vI1mwq3+ftbKfbBlum4VsdxxfsxsRskt6b2ktDwny1PiZVt3+x6bRTaXi72OvKQSHla82damhHXz0+qbMk6af1++utZpw9s0n68Ka+GtrJT+v2puiWzzac/jy72uvqIa2rXG/wvE5+evLScEnSj2v31VvNODtms0lfPzRKI7oHaVXEIV356hIVFZee9jHvL9ipgqIS3TE+XP3D/Mu3+7g56I2bB0mSvl4apcIzPA8aLz6b0RDOmzhFkrRsziylHDq5HmFi1C6t/2uBnFxc1W/keGuVh7N08ZTrJUmzPn2nwvTZCTFR+u2n2ZKkMRMnW6U21I3IXdu1ftVylZRUnEXkyOGDeu2Zh5Sfn6d+g4fJ14/plRs7s0l6fmIn9W3tqW37M/TE3D0qPkPn9/fHp8+e4q5aWAABAABJREFUOjBErTxPTpMZ3tJNF/doocz8Iv2283C91o2aM5ukd6+3fF/fEJuqO2ZsPvP39YHBVX9fD/PV4xdZbnb5mfWDgWbFbJJevixc/dt6aUtiuh75adcZPy/QtJjNJn392FiN6BmsVbuSdOVLC8/YJ3SCk4OtJg2yzOz1LVOnN2qWvr+RJ/v+XvurBn1/u473/XVR/zC/8u2Wvr+BkqSvl0XT99eE+bvZy9PJrsI2exuzHh4Vqi6BbloUcUSRyZWXzjQyU1lZWbP4lFu9erUmT56s5ORkOTs7a9CgQQoICFBGRoY2bdqk5ORkOTo66rffftMTTzyhDRs26Ntvvy0Pvqty7NgxBQYGqqysTAcPHpSfn1+1x/7b+E821MXLsqp+IR66qk9Q+c9h/i4ym0wV3kTfbU7Sxn2WqRQHtfHUtDHtZWtjVkp2ofYezZG9rVmdA1zlbG+jvUdz9Ni8Pco3SCO7e88Ra5dwzm4c1lbPXmYJOBdvP1TtVCkvzduttJwitfJ20qpnRym3oFg792focEa+nO1t1NbPRe0DLdNxfL48Ti/O3d1gr6G+FRc1/eljbh7RTs9f3l2StGjbQWXlVf2aXvhll9JyCtXK21nrXrxAuQXF2rEvXYfT8+Rkb6t2Aa7qcPw8f7Y0RtPnnP165I1R6sGm/16+e2JXvXmLZSTmvLXxysyrPO2tJE2bsU6pp4wKvn5UR3189/kqLinV+qhkZeQWaWCnAPm6O2pL7FFd8OQC5RhkCqUR43pau4Q6wWfz6f1+R3+r/e65O4wRIuzZvFZL53xd/vOBmD0qKytTcIcu5dtGTb5enfsMKv95/oz3tfr3n2Xn4KgO3fuqpLhIe3dsksqkax96XuH9z2vQ11Bf2nq5WLuEBvHh689p5ZLf5OLqprAu3VVYWKDoiB0qKirUqPGX6vYHn7R2ifXK1mzs+8qXLZ6vD15/Tp7evmrXoZNcXN10NPmQ4qL3qLCwQMFtQvX8W5/K08vb2qXWq9u+rTwbQlNzee+Wun+UpRN7ZXRKtculfLAiThmnXP/fN6KdpvQNUl5hiTYmpsnOxqx+rT0lk0lPzdujf2JSG6L8enfwYNOfJvKG89vo2eM3JC/ecbjaZY1enr9HaTlFCvJy0qpnRiq3oFi7DmToUPrx7+v+rmofYJkh6PMVcXpp3tmvR95Yxb89wWq/+9stxri5IHrLOv3968nBQEmxkVJZmYLady7fdv6l1yqstyU8yUpL1Q//fbZ8X8rBfSrIzZFvUIgcnCzXSh16DdCwy65roFdQv95aWPWSFE3JVf1b6eGxlvWil0UeVU5B1d/x3/kzVul5lnbG19Veb17etXxfG19nuTnaKe5oTvnjV8Wk6vN/Euu5+vq3e91Oa5dwzu6e1ENv3j5MkjRvTYwyc6vpE/pilVIzKy4Te8WwMM18dJw2RR3WeQ/+WO+1Wo19018C6u6J4Xrz+CCWeesSqj/PM9f/q+8vTB/fdZ6l7y/6iDJyCk/p+0vRBU/9Zoi+vwHDupz5oCZgYBsvXT+gVfnPnQJdZTaZtPvQyXXhv15/QOsS0iRJ47r46eFRoYo6kqPkrAI52JjVtaWbPJzstCEhTU8tiFShgdYTX3H/mWcibDaLRA4ZMkQxMTH69NNPtWDBAu3YsUNpaWlydXVVx44ddccdd+iWW25Rbm6uNmzYIGdnZ02aNOm0z+nt7a0LLrhACxcu1Pfff6977mlea0V6ONmp0/EvTqc6dZvHKXehrE1I1/2/7NbknoHq2sJNfUM8VFxapoMZ+fon9pjm7jhsqDegEZx6/sb1qDyNygnvLI5WWk6RUrIK9PK83RrY3kdhgW7qHuIps0k6klmg+ZuT9O2afVpnkE4UI/FwPrmcw4U9K0+VfcJ/F0YqLadQKVkFevGXXRoU5quwFu7q0dpTJpNJRzLyNXfjAc1elaC1e1OqfR40PM9T1gW8eFDbao978fvNFS6Mv14apfjkTD18WU/1C/OXk72N4pOz9PHCXXpn7g7lVvNlGdbDZzPqW05muvbvrXxz26nbcjLTK+ybdOM9atmmvdYs/lV7d2ySra2t2nfro1H/mao2HbsKTctdjzyrjuE99NfCX7R7x2ZJJrXt0EmjJ16m4RdMtHZ5OEdhnbtq7KTLtXfPTsVERSgnK0sOjo5q0z5Mg4eN0dhJ/5GDg+OZnwhW5+Z4srtnWFjl6dBP+GJ1YoVQ/N3lcdp7JFuTe7dUv9ZeKiot1cbEdM1cu0+7DmZV+zxoeBW+r3cPrPa4dxbvVVpOkVKzC/TK/D0a0N5HYYGu6hZ8yvf1LZbv6+uZHh//kpuVrqSYyjdKnLotNyu9/N8lxUVVHp+SdHImOd+WwXVbJM7JqZ8XIztVP+Dr05UJ5aG4nY1Z3Vp5VDqmnd/Jm0QTWDqx0fB0PXntdvHg9tUe9+L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",
      "text/plain": [
       "<Figure size 2000x1500 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Provide the error tables and corresponding desires\n",
    "error_tables_list = [eat_mode_error_tables, shop_mode_error_tables, recreation_mode_error_tables]\n",
    "desires = ['Eat', 'Shop', 'Recreation']\n",
    "x_ticks = ['Young-Adult', 'Adult', 'Mid-Age', 'Senior', 'Elderly']\n",
    "y_ticks = [['WK', 'PT', 'CA'],['WK', 'PT', 'CA'],['WK', 'PT', 'CA']]\n",
    "combined_plot(error_tables_list, desires, y_ticks, x_ticks=x_ticks, group='age',filename='results/mobility_choice(age).png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x1500 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_ticks = ['Debt', 'Low', 'Medium', 'High', 'High+','High++']\n",
    "y_ticks = [['WK', 'PT', 'CA'],['WK', 'PT', 'CA'],['WK', 'PT', 'CA']]\n",
    "combined_plot(error_tables_list, desires, y_ticks=y_ticks, x_ticks=x_ticks, group='income',filename='results/mobility_choice(income).png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Amenity Choice"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Start evaluation: choice_type = amenity\n",
      "Random Forest:disire-Eat choice_type-amenity\n",
      "MAPE: 17.44\n",
      "KL Divergence: 1.79\n",
      "========================================\n",
      "XGBoost: disire-Eat choice_type-amenity\n",
      "MAPE: 21.42\n",
      "KL Divergence: 2.87\n",
      "========================================\n",
      "MLP: disire-Eat choice_type-amenity\n",
      "MAPE: 25.95\n",
      "KL Divergence: 9.89\n",
      "========================================\n",
      "Graph RAG+LLM: disire-Eat choice_type-amenity\n",
      "MAPE: 7.19\n",
      "KL Divergence: 0.07\n",
      "========================================\n",
      "Random Forest:disire-Shop choice_type-amenity\n",
      "MAPE: 9.6\n",
      "KL Divergence: 0.1\n",
      "========================================\n",
      "XGBoost: disire-Shop choice_type-amenity\n",
      "MAPE: 19.7\n",
      "KL Divergence: 0.61\n",
      "========================================\n",
      "MLP: disire-Shop choice_type-amenity\n",
      "MAPE: 28.0\n",
      "KL Divergence: 8.04\n",
      "========================================\n",
      "Graph RAG+LLM: disire-Shop choice_type-amenity\n",
      "MAPE: 7.49\n",
      "KL Divergence: 0.05\n",
      "========================================\n",
      "Random Forest:disire-Recreation choice_type-amenity\n",
      "MAPE: 8.15\n",
      "KL Divergence: 0.09\n",
      "========================================\n",
      "XGBoost: disire-Recreation choice_type-amenity\n",
      "MAPE: 12.41\n",
      "KL Divergence: 0.34\n",
      "========================================\n",
      "MLP: disire-Recreation choice_type-amenity\n",
      "MAPE: 6.51\n",
      "KL Divergence: 0.07\n",
      "========================================\n",
      "Graph RAG+LLM: disire-Recreation choice_type-amenity\n",
      "MAPE: 8.31\n",
      "KL Divergence: 0.1\n",
      "========================================\n"
     ]
    }
   ],
   "source": [
    "print(\"Start evaluation: choice_type = amenity\")\n",
    "eat_amenity_df,eat_amenity_error_tables = evaluate(desire='Eat', choice_type='amenity')\n",
    "shop_amenity_df,shop_amenity_error_tables = evaluate(desire='Shop', choice_type='amenity')\n",
    "recreation_amenity_df,recreation_amenity_error_tables = evaluate(desire='Recreation', choice_type='amenity')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "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>model</th>\n",
       "      <th>desire</th>\n",
       "      <th>Metrics</th>\n",
       "      <th>RF</th>\n",
       "      <th>MLP</th>\n",
       "      <th>XG</th>\n",
       "      <th>GL</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Eat</td>\n",
       "      <td>KLD</td>\n",
       "      <td>1.79</td>\n",
       "      <td>9.89</td>\n",
       "      <td>2.87</td>\n",
       "      <td>0.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Eat</td>\n",
       "      <td>MAPE</td>\n",
       "      <td>17.44</td>\n",
       "      <td>25.95</td>\n",
       "      <td>21.42</td>\n",
       "      <td>7.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Shop</td>\n",
       "      <td>KLD</td>\n",
       "      <td>0.10</td>\n",
       "      <td>8.04</td>\n",
       "      <td>0.61</td>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Shop</td>\n",
       "      <td>MAPE</td>\n",
       "      <td>9.60</td>\n",
       "      <td>28.00</td>\n",
       "      <td>19.70</td>\n",
       "      <td>7.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Recreation</td>\n",
       "      <td>KLD</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.07</td>\n",
       "      <td>0.34</td>\n",
       "      <td>0.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Recreation</td>\n",
       "      <td>MAPE</td>\n",
       "      <td>8.15</td>\n",
       "      <td>6.51</td>\n",
       "      <td>12.41</td>\n",
       "      <td>8.31</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "model      desire Metrics     RF    MLP     XG    GL\n",
       "0             Eat     KLD   1.79   9.89   2.87  0.07\n",
       "1             Eat    MAPE  17.44  25.95  21.42  7.19\n",
       "2            Shop     KLD   0.10   8.04   0.61  0.05\n",
       "3            Shop    MAPE   9.60  28.00  19.70  7.49\n",
       "4      Recreation     KLD   0.09   0.07   0.34  0.10\n",
       "5      Recreation    MAPE   8.15   6.51  12.41  8.31"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "amenity_df = pd.concat([eat_amenity_df, shop_amenity_df, recreation_amenity_df])\n",
    "amenity_df = group_df(amenity_df)\n",
    "amenity_df.to_csv('results/amenity_choice.csv', index=False)\n",
    "amenity_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
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DtLii+AlvvvmmXFxctG3bNq1Z0/AlRyMiIiRJ+/bta6poLY6dnV2D+rm6ezRxEphaaUmx9u7eKknqMaj2P5y6H2+L2bLOpLlw9mztGjZDxsWt9g9BaBk4Z1u20uJiJe7eJqnu83aPwcfP25GctwEAAADUFnckT5LkYGcjT6eG/XwJ82dtYyNJsrFhdZ2WoqS4SP/8vVgOjk4adfFlRsdBE+Far+UqLSlWUlRV7aZbHdcAuw2satuz1bKuAVpsUdzDw0Njx46VJK1YceqH0J8sNzdXkuTgYN5LKJ8J34Bg+QW21uH9KdqwcmmNbQf3JWnDyiVydnVXxODaBx5atvSDqSorLZWLu6c8WvnV2h7ctoMk6XDKXlNHw1ny9Q+Sb2CwDh9I1cb/dzwf2pd8/Hh2Ux+O5xaLc7Zlqzpvl8jF3VOedZ63q54BeCgl0dTRAAAAALQArb2cJEmlZRXKLjTvZYfRMMcOJCkpcrWsbWwV3DXC6DhooMS4GBUW5Ktt+06yd3DUtk1r9dWst/TZezP1x8/f61hGutER0Qi41mu5Mg7uO6l2U/txEEHHazdHLKx2Y9G3bvXu3Vvz5s1TTEzDloaorKzUwoULJUk9e/ZsymgtirWNjaY+/Izee+FRffrGc/pzwffyC2qj3OxMxUdtV2Cbtpr68DNydWPWobnJykiTpDpPqpJk7+gkRxdXFebnqriwQA5OzqaMh7NgbWOjqQ89o/dffEyfvfm8/vxljvyD2ignO1MJx4/nWx76j1w4nlssztmWrSHnbSfO2wAAAADqcf2gNpKktQlHVVrOGumWKGXHBiVvW6uK8jLlHUtXWmKMrG1sNGzyA3L3Pf3zXNE87D9eCHP39NJrzz2iyHWramyf88WHumvaMxp2/hgj4qGRcK3XcmVlHJEkuXtTuzmZxc4UlyQfHx9JUmZm5in7lZeXKz4+XlOnTtX69evl4OCgW265xRQRW4wOXXvp8ZkfyTcgWCmJsdr8z1/as3OLrKys1TVigHwDgo2OiCZQUlQoSbKzr3/lBHsHR0lScWFBvX3QvLTv2kuPzag6nlOPH8+xJ47n3v3lw/Hc4nHOtlzFRVXnYnt7x3r72DlUzfzgvA0AAADgZMM6tNL4iCCVllXow+WWNbMM/zq2P0nx6/9S4qaVOpIQJWtbOw2+9m51GDja6Gg4A/l5VSviblm/Wjs2r9et9z+hz35apg+//V2XXT1ZJcXF+vD155WcEGtwUpwrrvVapurazSlWvbbE2o1FzxSvrKy6m9HKyqrO7XW1u7m56auvvlJ4eHiTZmtpNq76U1+881+Fd+qmOx57UcGh7ZR1NF1LF3yvPxd8r9idWzT9jU9l18BnWAAwzsZVf2r2uy+rXaduuv2xFxQU0k5ZxzL058/f6c9f5mjPrq168vX/cTy3YJyzAQAAAABnIszHWa9c1U3W1lZ6fWl89bPFYXkixl2niHHXqay0RDlpBxWz6g+t+fY9pezYoAvu+o9sbHnWfEtQUVEhqWpC4LW33KOLL7+6etvkOx5U+pFD2rD6L/320zd6YPp/jYqJRsC1XuBfFl0Uz8jIkCR5e3vXuX3KlCmSJGtra7m7u6tHjx666qqr5OXlVe8+i4uLVVxcXKOtpKRY9qeYSdvSHTmQqs/fflHuHl564Lk35Xh8mQX/4BDddN+Tyjqarh2b12rNst816pIJBqdFY7J3PP4cqZLievuUFBdJksUsv9HSHTm4T1++85LcPLx0/7Nv/Hs8B7XR5PueVNaxDO3cvFZrly3UyEuuMjgtzgbnbMvm4Fg13iUlRfX2KS2uupOU8zYAAABQv7quAVaUlcja1vyKCn5uDvroxt7ycLbT1+tS9P2GfUZHQjNga2cv7+AwDb3+XllZWyt6xW+KWvGbel7ItYSWwPGkn/lHXXx5re2jLr5MG1b/peidW00ZC42Ma72Wq7p2U0zt5mQWvXz6tm3bJEldu3atc/vs2bM1e/ZsffHFF3rnnXd06623nrIgLkkzZsyQh4dHjV/fznq70bM3J5tW/6XysjJ17zuoxl+mJ/QbfoEkKW73dhMnQ1Pz9PGTJGUfTa9ze0lRoYry8+Tk4mZRJ9aWbPPqZVXHc596judhVUthxUVtN3EyNBbO2ZatIeftQs7bAAAAwGnVdQ0wbc0co2M1OncnW826qbeCvZz0y9aDenNpgtGR0Ax1GHS+JCl1+waDk6ChfP0DJEkOjo5y96xd8/D1r3o+fHbWMZPmQuPiWq/l8vTxlyTlHKN2czKLLYpnZ2dr6dKlkqRRo0Y12n6nT5+u7OzsGr9uvOvhRtt/c5R5NE2S5OTsWud2ZxcXSVLB8eeUwHz4BoXI1s5O+TlZyq7j5HogKV6SFBDaztTRcJYyM44fzy51H88n2gvyckyWCY2Lc7Zlqzpv21edt+sojB9IipMkBYbymBgAAADgVOq6Bug37DqjYzUqJ3sbfXRjb4X7ueqv6DS98FuM0ZHQTDm6ekiSCvOyDU6ChmrbvrMkqaS4WKUlJbW25+VWjWVdhVS0HFzrtVw+QW2qazd1FcYPHq/d+FtY7cZii+KPPPKI8vPz1b9/fw0ePLjR9uvg4CB3d/cav8x56XRJcvdqJUlKTthT5/akuKp/MLfyCzRZJpiGnb2D2nXvI0natX5lre27N6ySJHXpO8SUsXAOThzPKfF1/6CbHB8tieO5JeOcbdnsHBwU3j1CkrRzw8pa23etP37e7sd5GwAAADiVuq4BmtPS6XY2Vnr3up7q0dpDa+OP6ol5u1VRaXQqNFeH4nZJktx9uZbQUvj4BSi0XUdVVlbWuUT6iba24Z1MHQ2NiGu9lsvO3kFtu1XVbnYfv953sqiNVW2d+1jWNUCLK4rv3btX11xzjT7//HO5uLjo888/NzpSixcxcLgkKW73Nq1YNL/GtsQ9u7Xs1x8kSf2GNd6MfDQfw8ddLUla8fM3yji0v7o9JS5Km/76TY4urup3/iVGxcMZ6j3wPElVS+asXPRzjW2Je3brr19/lCT1Hcrx3FJxzsbwSydJkpbP/3/n7djd2vjX73JycVV/ztsAAACAxbK2kl6d2F0D23lrS3Kmpv24U2XlVMQtWWFulvb8s1hlJUW1tu2P3qpNP1ddY+845EJTR8M5uOKamyRJ3/zvHWUezahuT06I1cJ530mSLryUZ8S3ZFzrtWxDj9duVi34RkdPugaYGhelyL9+l6OLq/pY2DVAq8rKSrP7F42VlZUkacqUKZKkiooK5eTkKC4uTnv27FFlZaU6dOig77//Xv369av3/Y31v2ZNfGaj7Kc5m/vF+1r6c9VflEEh7RQU0lZZx9KVuGe3KisqNGLMlbrpvicNTtm00gpq/6OwJdqzdb2Wz/+6+vX+hKpjpk2HLtVt50+4SZ37/LvCwu+z39e6RfNl5+CoDj36qqy8TAk7I6XKSl0/7QV1GzDcpN+hKfk4mffKD5L00xfv688F30uqOp4D24Qp+1iGEmOrjufzLr5Ck838eLY+/veAueKcXSWjsNjoCI0iZst6/V3jvB1z/Lzdtbpt9ISb1KXvv+ft3758X2sXzas6b/fsp/KyUsXvjJQqpRsfMa/z9pU9Awz77PfXJhn22TCdUi4QWwRPJ1ujI6CJeTuYz+xO1G9x3FGjI8AEPpnYzbDP7vXc34Z9dmO6flAbPTG2oyTp7+g05RWX1dnvrT8TlFVQKknycbXX29f2rN4W5uMsdyc7JablK//4+/+Jz9D/ViU3bXgTuHFUW6MjNIrUXZu07Y/vq1+nJ8dJlZXybfvvzOCIcdcrpMcA5WYc0Y9P3yxbewf5hHSQi5ePSkuKlH3kgLIP75MkdR89XoMm3WHy79FULmrna3QEk/jwtee1atlCubi6qWPXniopKVZc1E6VlpZo9CXjdefDTxsdsUllF5UaHaHJca1XOmwmtZvYreu1cv431a8PJFbVblq3/7d2M3LCZHU6qXazaPYHWr+4qnYT3qOvysvKlLirqnZzzbQX1LX/MJN+h6Y0qXfQafuY9U/2X331lSTJ1tZW7u7uCgoK0k033aQrrrhCl19+uWxsbAxOaD4mTb1f7Tv30MrFC5SSuEdHDqTIwclFnbpH6LyLr9DAERcZHRENlJ+TpX11LKdyclt+TlaNbZfdfL+Cwtpr/ZIFit+1RTa2tmrfo6/On3CTQjt1b+rIaGRXT71f4V16aNXiX5SacOJ4dlbH7hEaftHlHM9mgHO2eak6b0fXaj+57f+fty+/peq8vW7JAsXvjJTt8fP26IlTFMZ5GwAAALBo7o7/XjIe3dWv3n6zViZVF8Xtba3Vs41HrT7hfi7Vv0/KyG/ElDhXRbnZSk+KrdV+clvR8edKO7l7aMBVt+pQ3E5lHkpRekq8VFkhJw9vtes/Qp2HX6KgTj1r7QvN3z2PPadO3Xvpr4U/K3rnFklWatuhsy4Yd5VGXnSp0fHQCLjWaz7yc7K1P6F27ebktvyc7BrbLrn5PgWEtdfGpQuUeLx2E96jr0ZeNVkhFngN0Cxnijc3ljBTHOYzUxynZgkzxWH+M8VRxVxmiuPUmCmOpsZMccvATHHzx0xxy8BMccvATHE0NXOZKY5Ts5SZ4pbOEmaKw3xmiuPUGjJT3OKeKQ4AAAAAAAAAAAAAsBwUxQEAAAAAAAAAAAAAZouiOAAAAAAAAAAAAADAbFEUBwAAAAAAAAAAAACYLYriAAAAAAAAAAAAAACzRVEcAAAAAAAAAAAAAGC2KIoDAAAAAAAAAAAAAMwWRXEAAAAAAAAAAAAAgNmiKA4AAAAAAAAAAAAAMFsUxQEAAAAAAAAAAAAAZouiOAAAAAAAAAAAAADAbFEUBwAAAAAAAAAAAACYLYriAAAAAAAAAAAAAACzRVEcAAAAAAAAAAAAAGC2KIoDAAAAAAAAAAAAAMwWRXEAAAAAAAAAAAAAgNmiKA4AAAAAAAAAAAAAMFsUxQEAAAAAAAAAAAAAZouiOAAAAAAAAAAAAAD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",
      "text/plain": [
       "<Figure size 2000x1500 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Provide the error tables and corresponding desires\n",
    "error_tables_list = [eat_amenity_error_tables, shop_amenity_error_tables, recreation_amenity_error_tables]\n",
    "desires = ['Eat', 'Shop', 'Recreation']\n",
    "# y_ticks = [['Limited-Service Restaurants','Nonalcoholic Bars','Full-Service Restaurants', 'Drinking Places'],\n",
    "#            ['Consumer Goods','Grocery','Durable Goods'],\n",
    "#            ['Leisure & Wellness','Entertainment','Cultural','Hotel']]\n",
    "y_ticks = [['LS','NB','FS', 'DP'],\n",
    "           ['CG','GR','DG'],\n",
    "           ['LW','EN','CU','HO']]\n",
    "x_ticks = ['Young-Adult', 'Adult', 'Mid-Age', 'Senior', 'Elderly']\n",
    "combined_plot(error_tables_list, desires, y_ticks=y_ticks,x_ticks=x_ticks, group='age',filename='results/amenity_choice(age).png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x1500 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_ticks = ['Debt', 'Low', 'Medium', 'High', 'High+','High++']\n",
    "combined_plot(error_tables_list, desires, y_ticks, x_ticks=x_ticks, group='income',filename='results/amenity_choice(income).png')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "pytorch",
   "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": "3.8.18"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}