{
 "metadata": {
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.7-final"
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  "orig_nbformat": 2,
  "kernelspec": {
   "name": "python38764bitsurrogateoptime172a7b2c75d4817b747a7ff436f986e",
   "display_name": "Python 3.8.7 64-bit ('surrogate-optim')"
  }
 },
 "nbformat": 4,
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 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_folder = \"../data\"\n",
    "surrogate_data_folder = os.path.join(data_folder, \"surrogate\", \"data\")\n",
    "surrogate_static_folder = os.path.join(data_folder, \"surrogate\", \"static\")\n",
    "log_folder = os.path.join(data_folder, \"logs\")\n",
    "\n",
    "output_images_folder = 'images'\n",
    "if not os.path.exists(output_images_folder):\n",
    "    os.makedirs(output_images_folder)"
   ]
  },
  {
   "source": [
    "## What to display ?\n",
    "\n",
    "- **1. Curve of performance runs during search process (`surrogate/data`) :**\n",
    "    - best solution score (in means from 5 runs)\n",
    "    - comparisons of different orders\n",
    "    - comparisons of different LS iterations per orders\n",
    "    - extract times of computation (`data/logs`)\n",
    "    - surrogate model performance during training (r²)\n",
    "\n",
    "\n",
    "- **2. From only best last solutions found displays :**\n",
    "    - bar plot of best attribute selected for classification per order\n",
    "    - same for the two orders "
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "source": [
    "### 1. Curve of performances runs during search process (`surrogate/data`)"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fixed parameters\n",
    "ILS = 1000\n",
    "POP = 20\n",
    "N_RUNS = 5\n",
    "SS = 50 # start surrogate training after at least 50 real evaluations\n",
    "SE = 10 # train every 10 real evaluations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def extract_params(filename):\n",
    "    #pop_size = filename.split('-')[2].replace('POP_', '')\n",
    "    ls_iter = filename.split('-')[3].replace('LS_', '')\n",
    "    s_order = filename.split('-')[5].replace('SO_', '')\n",
    "\n",
    "    return int(ls_iter), int(s_order)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "files = os.listdir(surrogate_data_folder)\n",
    "\n",
    "data_results = {}\n",
    "static_results = []\n",
    "\n",
    "# extract static result\n",
    "for f in os.listdir(surrogate_static_folder):\n",
    "    filepath = os.path.join(surrogate_static_folder, f)\n",
    "\n",
    "    with open(filepath, 'r') as ff:\n",
    "\n",
    "        max_score = 0.\n",
    "        scores = []\n",
    "\n",
    "        for line in ff.readlines()[1:ILS+1]:\n",
    "            cscore = float(line.split(';')[-1])\n",
    "\n",
    "            if cscore > max_score:\n",
    "                max_score = cscore\n",
    "\n",
    "            scores.append(max_score)\n",
    "\n",
    "    static_results.append(scores)\n",
    "\n",
    "\n",
    "# extract all other results\n",
    "for i in range(1, N_RUNS + 1):\n",
    "    for run in [ f for f in files if f\"RUN_{i}_performance\" in f ]:\n",
    "        \n",
    "        key = extract_params(run)\n",
    "        if key not in data_results:\n",
    "            data_results[key] = []\n",
    "\n",
    "        # need to extract the 50 first solution found from surrogate data file\n",
    "        data_file = os.path.join(surrogate_data_folder, run.replace('_performance.csv', ''))\n",
    "\n",
    "        max_score = 0.\n",
    "        scores = []\n",
    "        with open(data_file, 'r') as f:\n",
    "            lines = f.readlines()\n",
    "\n",
    "            for line in lines[1:SS + 1]:\n",
    "                cscore = float(line.split(';')[-1])\n",
    "\n",
    "                if cscore > max_score:\n",
    "                    max_score = cscore\n",
    "                scores.append(max_score)\n",
    "        \n",
    "        with open(os.path.join(surrogate_data_folder, run), 'r') as f:\n",
    "            lines = f.readlines()\n",
    "\n",
    "            for index, line in enumerate(lines[:ILS - SS]):\n",
    "                #print(f'{index} => {run}')\n",
    "                #print(line)\n",
    "                cscore = float(line.split(';')[-2])\n",
    "\n",
    "                if cscore > max_score:\n",
    "                    max_score = cscore\n",
    "\n",
    "                scores.append(max_score)\n",
    "\n",
    "        # append run data into dictionnary with its key\n",
    "        data_results[key].append(scores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "(100, 1) has 5 runs\n(100, 2) has 5 runs\n(500, 1) has 5 runs\n(500, 2) has 5 runs\n(1000, 1) has 5 runs\n(1000, 2) has 5 runs\n"
     ]
    }
   ],
   "source": [
    "for k in sorted(data_results.keys()):\n",
    "    print(f'{k} has {len(data_results[k])} runs')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "(2, 1000)\n"
     ]
    }
   ],
   "source": [
    "print(np.array(static_results).shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "display_data",
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135.643832 127.512624 \nL 135.846944 127.512624 \nL 136.050056 127.512624 \nL 136.253169 127.512624 \nL 136.456281 127.512624 \nL 136.659393 127.512624 \nL 136.862505 127.512624 \nL 137.065617 127.512624 \nL 137.26873 127.512624 \nL 137.471842 127.512624 \nL 137.674954 127.512624 \nL 137.878066 127.512624 \nL 138.081178 127.512624 \nL 138.284291 127.512624 \nL 138.487403 127.512624 \nL 138.690515 127.512624 \nL 138.893627 127.512624 \nL 139.096739 127.512624 \nL 139.299852 127.512624 \nL 139.502964 127.512624 \nL 139.706076 127.512624 \nL 139.909188 127.512624 \nL 140.1123 127.512624 \nL 140.315413 127.512624 \nL 140.518525 127.512624 \nL 140.721637 127.512624 \nL 140.924749 127.512624 \nL 141.127861 127.512624 \nL 141.330974 127.512624 \nL 141.534086 127.512624 \nL 141.737198 127.512624 \nL 141.94031 127.512624 \nL 142.143422 127.512624 \nL 142.346535 127.512624 \nL 142.549647 127.512624 \nL 142.752759 127.512624 \nL 142.955871 127.512624 \nL 143.158983 127.512624 \nL 143.362096 127.512624 \nL 143.565208 127.512624 \nL 143.76832 127.512624 \nL 143.971432 127.512624 \nL 144.174544 127.512624 \nL 144.377657 127.512624 \nL 144.580769 127.512624 \nL 144.783881 127.512624 \nL 144.986993 127.512624 \nL 145.190105 127.512624 \nL 145.393218 127.512624 \nL 145.59633 127.512624 \nL 145.799442 127.512624 \nL 146.002554 127.512624 \nL 146.205666 127.512624 \nL 146.408779 127.512624 \nL 146.611891 127.512624 \nL 146.815003 127.512624 \nL 147.018115 127.512624 \nL 147.221227 127.512624 \nL 147.42434 127.512624 \nL 147.627452 127.512624 \nL 147.830564 127.512624 \nL 148.033676 127.512624 \nL 148.236788 127.512624 \nL 148.439901 127.512624 \nL 148.643013 127.512624 \nL 148.846125 127.512624 \nL 149.049237 127.512624 \nL 149.25235 127.512624 \nL 149.455462 127.512624 \nL 149.658574 127.512624 \nL 149.861686 127.512624 \nL 150.064798 127.512624 \nL 150.267911 127.512624 \nL 150.471023 127.512624 \nL 150.674135 127.512624 \nL 150.877247 127.512624 \nL 151.080359 127.512624 \nL 151.283472 127.512624 \nL 151.486584 127.512624 \nL 151.689696 127.512624 \nL 151.892808 127.512624 \nL 152.09592 127.512624 \nL 152.299033 127.512624 \nL 152.502145 127.512624 \nL 152.705257 127.512624 \nL 152.908369 127.512624 \nL 153.111481 127.512624 \nL 153.314594 127.512624 \nL 153.517706 127.512624 \nL 153.720818 127.512624 \nL 153.92393 127.512624 \nL 154.127042 127.512624 \nL 154.330155 127.512624 \nL 154.533267 127.512624 \nL 154.736379 127.512624 \nL 154.939491 127.512624 \nL 155.142603 127.512624 \nL 155.345716 127.512624 \nL 155.548828 127.512624 \nL 155.75194 127.512624 \nL 155.955052 127.512624 \nL 156.158164 127.512624 \nL 156.361277 127.512624 \nL 156.564389 127.512624 \nL 156.767501 127.512624 \nL 156.970613 127.512624 \nL 157.173725 127.512624 \nL 157.376838 127.512624 \nL 157.57995 127.512624 \nL 157.783062 127.512624 \nL 157.986174 127.512624 \nL 158.189286 127.512624 \nL 158.392399 127.512624 \nL 158.595511 127.512624 \nL 158.798623 127.512624 \nL 159.001735 127.512624 \nL 159.204847 127.512624 \nL 159.40796 127.512624 \nL 159.611072 127.512624 \nL 159.814184 127.512624 \nL 160.017296 127.512624 \nL 160.220408 127.512624 \nL 160.423521 127.512624 \nL 160.626633 127.512624 \nL 160.829745 127.512624 \nL 161.032857 127.512624 \nL 161.235969 127.512624 \nL 161.439082 127.512624 \nL 161.642194 127.512624 \nL 161.845306 127.512624 \nL 162.048418 127.512624 \nL 162.251531 127.512624 \nL 162.454643 127.512624 \nL 162.657755 127.512624 \nL 162.860867 127.512624 \nL 163.063979 127.512624 \nL 163.267092 127.512624 \nL 163.470204 127.512624 \nL 163.673316 127.512624 \nL 163.876428 127.512624 \nL 164.07954 127.512624 \nL 164.282653 127.512624 \nL 164.485765 127.512624 \nL 164.688877 127.512624 \nL 164.891989 127.512624 \nL 165.095101 127.512624 \nL 165.298214 127.512624 \nL 165.501326 127.512624 \nL 165.704438 127.512624 \nL 165.90755 127.512624 \nL 166.110662 127.512624 \nL 166.313775 127.512624 \nL 166.516887 127.512624 \nL 166.719999 127.512624 \nL 166.923111 127.512624 \nL 167.126223 127.512624 \nL 167.329336 127.512624 \nL 167.532448 127.512624 \nL 167.73556 127.512624 \nL 167.938672 127.512624 \nL 168.141784 127.512624 \nL 168.344897 127.512624 \nL 168.548009 127.512624 \nL 168.751121 127.512624 \nL 168.954233 127.512624 \nL 169.157345 127.512624 \nL 169.360458 127.512624 \nL 169.56357 127.512624 \nL 169.766682 127.512624 \nL 169.969794 127.512624 \nL 170.172906 127.512624 \nL 170.376019 127.512624 \nL 170.579131 127.512624 \nL 170.782243 127.512624 \nL 170.985355 127.512624 \nL 171.188467 127.512624 \nL 171.39158 127.512624 \nL 171.594692 127.512624 \nL 171.797804 127.512624 \nL 172.000916 127.512624 \nL 172.204028 127.512624 \nL 172.407141 127.512624 \nL 172.610253 127.512624 \nL 172.813365 127.512624 \nL 173.016477 127.512624 \nL 173.219589 127.512624 \nL 173.422702 127.512624 \nL 173.625814 127.512624 \nL 173.828926 127.512624 \nL 174.032038 127.512624 \nL 174.23515 127.512624 \nL 174.438263 127.512624 \nL 174.641375 127.512624 \nL 174.844487 127.512624 \nL 175.047599 127.512624 \nL 175.250712 127.512624 \nL 175.453824 127.512624 \nL 175.656936 127.512624 \nL 175.860048 127.512624 \nL 176.06316 127.512624 \nL 176.266273 127.512624 \nL 176.469385 127.512624 \nL 176.672497 127.512624 \nL 176.875609 127.512624 \nL 177.078721 127.512624 \nL 177.281834 127.512624 \nL 177.484946 127.512624 \nL 177.688058 127.512624 \nL 177.89117 127.512624 \nL 178.094282 127.512624 \nL 178.297395 127.512624 \nL 178.500507 127.512624 \nL 178.703619 127.512624 \nL 178.906731 127.512624 \nL 179.109843 127.512624 \nL 179.312956 127.512624 \nL 179.516068 127.512624 \nL 179.71918 127.512624 \nL 179.922292 127.512624 \nL 180.125404 127.512624 \nL 180.328517 127.512624 \nL 180.531629 127.512624 \nL 180.734741 127.512624 \nL 180.937853 127.512624 \nL 181.140965 127.512624 \nL 181.344078 127.512624 \nL 181.54719 127.512624 \nL 181.750302 127.512624 \nL 181.953414 127.512624 \nL 182.156526 127.512624 \nL 182.359639 127.512624 \nL 182.562751 127.512624 \nL 182.765863 127.512624 \nL 182.968975 127.512624 \nL 183.172087 127.512624 \nL 183.3752 127.512624 \nL 183.578312 127.512624 \nL 183.781424 127.512624 \nL 183.984536 127.512624 \nL 184.187648 127.512624 \nL 184.390761 127.512624 \nL 184.593873 127.512624 \nL 184.796985 127.512624 \nL 185.000097 127.512624 \nL 185.203209 127.512624 \nL 185.406322 127.512624 \nL 185.609434 127.512624 \nL 185.812546 127.512624 \nL 186.015658 127.512624 \nL 186.21877 127.512624 \nL 186.421883 127.512624 \nL 186.624995 127.512624 \nL 186.828107 127.512624 \nL 187.031219 127.512624 \nL 187.234331 127.512624 \nL 187.437444 127.512624 \nL 187.640556 127.512624 \nL 187.843668 127.512624 \nL 188.04678 127.512624 \nL 188.249893 127.512624 \nL 188.453005 127.512624 \nL 188.656117 127.512624 \nL 188.859229 127.512624 \nL 189.062341 127.512624 \nL 189.265454 127.512624 \nL 189.468566 127.512624 \nL 189.671678 127.512624 \nL 189.87479 127.512624 \nL 190.077902 127.512624 \nL 190.281015 127.512624 \nL 190.484127 127.512624 \nL 190.687239 127.512624 \nL 190.890351 127.512624 \nL 191.093463 127.512624 \nL 191.296576 127.512624 \nL 191.499688 127.512624 \nL 191.7028 127.512624 \nL 191.905912 127.512624 \nL 192.109024 127.512624 \nL 192.312137 127.512624 \nL 192.515249 127.512624 \nL 192.718361 127.512624 \nL 192.921473 127.512624 \nL 193.124585 127.512624 \nL 193.327698 127.512624 \nL 193.53081 127.512624 \nL 193.733922 127.512624 \nL 193.937034 127.512624 \nL 194.140146 127.512624 \nL 194.343259 127.512624 \nL 194.546371 127.512624 \nL 194.749483 127.512624 \nL 194.952595 127.512624 \nL 195.155707 127.512624 \nL 195.35882 127.512624 \nL 195.561932 127.512624 \nL 195.765044 127.512624 \nL 195.968156 127.512624 \nL 196.171268 127.512624 \nL 196.374381 127.512624 \nL 196.577493 127.512624 \nL 196.780605 127.512624 \nL 196.983717 127.512624 \nL 197.186829 127.512624 \nL 197.389942 127.512624 \nL 197.593054 127.512624 \nL 197.796166 127.512624 \nL 197.999278 127.512624 \nL 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229.48167 127.512624 \nL 229.684782 127.512624 \nL 229.887894 127.512624 \nL 230.091006 127.512624 \nL 230.294119 127.512624 \nL 230.497231 127.512624 \nL 230.700343 127.512624 \nL 230.903455 127.512624 \nL 231.106567 127.512624 \nL 231.30968 127.512624 \nL 231.512792 127.512624 \nL 231.715904 127.512624 \nL 231.919016 127.512624 \nL 232.122128 127.512624 \nL 232.325241 127.512624 \nL 232.528353 127.512624 \nL 232.731465 127.512624 \nL 232.934577 127.512624 \nL 233.137689 127.512624 \nL 233.340802 127.512624 \nL 233.543914 127.512624 \nL 233.747026 127.512624 \nL 233.950138 127.512624 \nL 234.15325 127.512624 \nL 234.356363 127.512624 \nL 234.559475 127.512624 \nL 234.762587 127.512624 \nL 234.965699 127.512624 \nL 235.168811 127.512624 \nL 235.371924 127.512624 \nL 235.575036 127.512624 \nL 235.778148 127.512624 \nL 235.98126 127.512624 \nL 236.184372 127.512624 \nL 236.387485 127.512624 \nL 236.590597 127.512624 \nL 236.793709 127.512624 \nL 236.996821 127.512624 \nL 237.199933 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43.784039 \nL 207.139327 43.784039 \nL 206.936215 43.784039 \nL 206.733103 43.784039 \nL 206.529991 43.784039 \nL 206.326879 43.784039 \nL 206.123766 43.784039 \nL 205.920654 43.784039 \nL 205.717542 43.784039 \nL 205.51443 43.784039 \nL 205.311318 43.784039 \nL 205.108205 43.784039 \nL 204.905093 43.784039 \nL 204.701981 43.784039 \nL 204.498869 43.784039 \nL 204.295757 43.784039 \nL 204.092644 43.784039 \nL 203.889532 43.784039 \nL 203.68642 43.784039 \nL 203.483308 43.784039 \nL 203.280196 43.784039 \nL 203.077083 43.943184 \nL 202.873971 43.943184 \nL 202.670859 43.943184 \nL 202.467747 43.943184 \nL 202.264635 43.943184 \nL 202.061522 43.943184 \nL 201.85841 43.943184 \nL 201.655298 43.943184 \nL 201.452186 43.943184 \nL 201.249074 43.943184 \nL 201.045961 43.943184 \nL 200.842849 43.943184 \nL 200.639737 43.943184 \nL 200.436625 43.943184 \nL 200.233512 45.197067 \nL 200.0304 45.197067 \nL 199.827288 45.197067 \nL 199.624176 45.197067 \nL 199.421064 45.197067 \nL 199.217951 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125.081997 86.246591 \nL 125.28511 86.246591 \nL 125.488222 82.741947 \nL 125.691334 82.741947 \nL 125.894446 82.741947 \nL 126.097558 82.741947 \nL 126.300671 81.966612 \nL 126.503783 81.966612 \nL 126.706895 81.966612 \nL 126.910007 81.966612 \nL 127.113119 81.231244 \nL 127.316232 72.357547 \nL 127.519344 72.357547 \nL 127.722456 72.357547 \nL 127.925568 72.357547 \nL 128.12868 72.357547 \nL 128.331793 72.357547 \nL 128.534905 72.357547 \nL 128.738017 72.357547 \nL 128.941129 72.357547 \nL 129.144241 72.357547 \nL 129.347354 72.357547 \nL 129.550466 72.357547 \nL 129.753578 72.357547 \nL 129.95669 72.357547 \nL 130.159802 72.357547 \nL 130.362915 72.357547 \nL 130.566027 72.357547 \nL 130.769139 72.357547 \nL 130.972251 68.765221 \nL 131.175363 68.765221 \nL 131.378476 68.765221 \nL 131.581588 68.439834 \nL 131.7847 68.439834 \nL 131.987812 68.439834 \nL 132.190924 65.424321 \nL 132.394037 65.418525 \nL 132.597149 65.418525 \nL 132.800261 65.418525 \nL 133.003373 65.418525 \nL 133.206485 65.408706 \nL 133.409598 65.408706 \nL 133.61271 65.408706 \nL 133.815822 65.408706 \nL 134.018934 65.408706 \nL 134.222046 65.408706 \nL 134.425159 65.408706 \nL 134.628271 65.408706 \nL 134.831383 65.408706 \nL 135.034495 65.408706 \nL 135.237607 65.408706 \nL 135.44072 65.408706 \nL 135.643832 65.408706 \nL 135.846944 64.209831 \nL 136.050056 64.209831 \nL 136.253169 64.209831 \nL 136.456281 64.209831 \nL 136.659393 64.209831 \nL 136.862505 64.14379 \nL 137.065617 64.091879 \nL 137.26873 64.091879 \nL 137.471842 62.484681 \nL 137.674954 62.484681 \nL 137.878066 62.484681 \nL 138.081178 62.484681 \nL 138.284291 62.484681 \nL 138.487403 62.484681 \nL 138.690515 62.484681 \nL 138.893627 62.484681 \nL 139.096739 61.296897 \nL 139.299852 61.296897 \nL 139.502964 61.296897 \nL 139.706076 61.296897 \nL 139.909188 61.296897 \nL 140.1123 61.296897 \nL 140.315413 61.296897 \nL 140.518525 61.296897 \nL 140.721637 61.296897 \nL 140.924749 61.296897 \nL 141.127861 59.692927 \nL 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119.835045 \nL 115.535724 119.835045 \nL 115.738836 120.043253 \nL 115.941948 118.324135 \nL 116.14506 117.702207 \nL 116.348173 116.711024 \nL 116.551285 116.711024 \nL 116.754397 116.711024 \nL 116.957509 116.711024 \nL 117.160621 116.711024 \nL 117.363734 116.412823 \nL 117.566846 116.111187 \nL 117.769958 116.111187 \nL 117.97307 115.488471 \nL 118.176182 115.488471 \nL 118.379295 115.488471 \nL 118.582407 115.488471 \nL 118.785519 115.488471 \nL 118.988631 114.722243 \nL 119.191743 114.722243 \nL 119.394856 115.091069 \nL 119.597968 115.091069 \nL 119.80108 114.060343 \nL 120.004192 114.060343 \nL 120.207304 114.060343 \nL 120.410417 114.060343 \nL 120.613529 114.060343 \nL 120.816641 114.060343 \nL 121.019753 114.060343 \nL 121.222865 114.060343 \nL 121.425978 113.298902 \nL 121.62909 113.298902 \nL 121.832202 113.298902 \nL 122.035314 113.298902 \nL 122.238426 113.298902 \nL 122.441539 113.298902 \nL 122.644651 113.298902 \nL 122.847763 113.298902 \nL 123.050875 113.298902 \nL 123.253988 113.298902 \nL 123.4571 113.298902 \nL 123.660212 113.298902 \nL 123.863324 113.298902 \nL 124.066436 113.298902 \nL 124.269549 113.298902 \nL 124.472661 113.298902 \nL 124.675773 113.298902 \nL 124.878885 113.298902 \nL 125.081997 113.298902 \nL 125.28511 113.298902 \nL 125.488222 113.298902 \nL 125.691334 113.298902 \nL 125.894446 113.298902 \nL 126.097558 113.298902 \nL 126.300671 113.298902 \nL 126.503783 113.298902 \nL 126.706895 113.298902 \nL 126.910007 113.298902 \nL 127.113119 113.298902 \nL 127.316232 113.298902 \nL 127.519344 113.298902 \nL 127.722456 113.298902 \nL 127.925568 113.298902 \nL 128.12868 113.298902 \nL 128.331793 113.298902 \nL 128.534905 113.298902 \nL 128.738017 113.298902 \nL 128.941129 113.298902 \nL 129.144241 113.298902 \nL 129.347354 113.298902 \nL 129.550466 113.298902 \nL 129.753578 113.298902 \nL 129.95669 113.298902 \nL 130.159802 113.298902 \nL 130.362915 113.298902 \nL 130.566027 113.298902 \nL 130.769139 113.298902 \nL 130.972251 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154.533267 110.154456 \nL 154.736379 110.154456 \nL 154.939491 110.154456 \nL 155.142603 110.20223 \nL 155.345716 110.20223 \nL 155.548828 105.857114 \nL 155.75194 105.857114 \nL 155.955052 105.857114 \nL 156.158164 105.857114 \nL 156.361277 105.857114 \nL 156.564389 105.857114 \nL 156.767501 105.857114 \nL 156.970613 105.857114 \nL 157.173725 105.857114 \nL 157.376838 105.857114 \nL 157.57995 105.857114 \nL 157.783062 105.857114 \nL 157.986174 105.857114 \nL 158.189286 105.857114 \nL 158.392399 105.857114 \nL 158.595511 105.857114 \nL 158.798623 105.857114 \nL 159.001735 105.857114 \nL 159.204847 105.857114 \nL 159.40796 105.857114 \nL 159.611072 105.857114 \nL 159.814184 105.857114 \nL 160.017296 105.514095 \nL 160.220408 104.606701 \nL 160.423521 104.606701 \nL 160.626633 104.606701 \nL 160.829745 104.606701 \nL 161.032857 104.425103 \nL 161.235969 104.425103 \nL 161.439082 104.425103 \nL 161.642194 104.425103 \nL 161.845306 104.425103 \nL 162.048418 104.425103 \nL 162.251531 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170.172906 101.571086 \nL 170.376019 101.571086 \nL 170.579131 101.571086 \nL 170.782243 101.571086 \nL 170.985355 101.571086 \nL 171.188467 101.571086 \nL 171.39158 101.571086 \nL 171.594692 101.571086 \nL 171.797804 101.488779 \nL 172.000916 101.488779 \nL 172.204028 101.488779 \nL 172.407141 101.488779 \nL 172.610253 101.488779 \nL 172.813365 101.423942 \nL 173.016477 101.423942 \nL 173.219589 101.423942 \nL 173.422702 101.423942 \nL 173.625814 101.423942 \nL 173.828926 101.423942 \nL 174.032038 101.423942 \nL 174.23515 101.423942 \nL 174.438263 101.415698 \nL 174.641375 101.415698 \nL 174.844487 101.415698 \nL 175.047599 101.415698 \nL 175.250712 101.415698 \nL 175.453824 101.415698 \nL 175.656936 101.415698 \nL 175.860048 101.415698 \nL 176.06316 101.415698 \nL 176.266273 101.415698 \nL 176.469385 101.415698 \nL 176.672497 101.415698 \nL 176.875609 101.415698 \nL 177.078721 101.415698 \nL 177.281834 101.415698 \nL 177.484946 101.415698 \nL 177.688058 101.415698 \nL 177.89117 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185.812546 100.836551 \nL 186.015658 100.836551 \nL 186.21877 100.836551 \nL 186.421883 100.836551 \nL 186.624995 100.836551 \nL 186.828107 100.836551 \nL 187.031219 100.836551 \nL 187.234331 100.836551 \nL 187.437444 100.836551 \nL 187.640556 100.836551 \nL 187.843668 96.846213 \nL 188.04678 96.846213 \nL 188.249893 96.846213 \nL 188.453005 96.846213 \nL 188.656117 96.846213 \nL 188.859229 96.846213 \nL 189.062341 96.846213 \nL 189.265454 96.846213 \nL 189.468566 96.846213 \nL 189.671678 96.846213 \nL 189.87479 96.846213 \nL 190.077902 96.846213 \nL 190.281015 96.846213 \nL 190.484127 96.846213 \nL 190.687239 96.846213 \nL 190.890351 96.846213 \nL 191.093463 96.846213 \nL 191.296576 96.846213 \nL 191.499688 96.846213 \nL 191.7028 96.846213 \nL 191.905912 96.846213 \nL 192.109024 93.228423 \nL 192.312137 93.228423 \nL 192.515249 93.228423 \nL 192.718361 93.228423 \nL 192.921473 93.228423 \nL 193.124585 91.791624 \nL 193.327698 91.791624 \nL 193.53081 91.791624 \nL 193.733922 91.791624 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185.203209 57.584654 \nL 185.000097 57.584654 \nL 184.796985 57.584654 \nL 184.593873 57.584654 \nL 184.390761 57.584654 \nL 184.187648 57.517784 \nL 183.984536 57.517784 \nL 183.781424 57.517784 \nL 183.578312 57.517784 \nL 183.3752 57.517784 \nL 183.172087 57.517784 \nL 182.968975 57.517784 \nL 182.765863 57.517784 \nL 182.562751 57.517784 \nL 182.359639 57.517784 \nL 182.156526 57.517784 \nL 181.953414 57.517784 \nL 181.750302 57.517784 \nL 181.54719 57.517784 \nL 181.344078 57.517784 \nL 181.140965 57.517784 \nL 180.937853 57.517784 \nL 180.734741 57.517784 \nL 180.531629 57.517784 \nL 180.328517 57.517784 \nL 180.125404 57.517784 \nL 179.922292 57.517784 \nL 179.71918 57.517784 \nL 179.516068 57.517784 \nL 179.312956 57.517784 \nL 179.109843 57.517784 \nL 178.906731 57.517784 \nL 178.703619 57.517784 \nL 178.500507 57.517784 \nL 178.297395 57.517784 \nL 178.094282 57.517784 \nL 177.89117 57.517784 \nL 177.688058 57.517784 \nL 177.484946 57.517784 \nL 177.281834 57.517784 \nL 177.078721 57.517784 \nL 176.875609 57.517784 \nL 176.672497 57.517784 \nL 176.469385 57.517784 \nL 176.266273 57.517784 \nL 176.06316 57.517784 \nL 175.860048 57.517784 \nL 175.656936 57.517784 \nL 175.453824 57.517784 \nL 175.250712 57.517784 \nL 175.047599 57.517784 \nL 174.844487 57.517784 \nL 174.641375 57.517784 \nL 174.438263 57.517784 \nL 174.23515 57.823655 \nL 174.032038 57.823655 \nL 173.828926 57.823655 \nL 173.625814 57.823655 \nL 173.422702 57.823655 \nL 173.219589 57.823655 \nL 173.016477 57.823655 \nL 172.813365 57.823655 \nL 172.610253 59.156778 \nL 172.407141 59.156778 \nL 172.204028 59.156778 \nL 172.000916 59.156778 \nL 171.797804 59.156778 \nL 171.594692 60.141697 \nL 171.39158 60.141697 \nL 171.188467 60.141697 \nL 170.985355 60.141697 \nL 170.782243 60.141697 \nL 170.579131 60.141697 \nL 170.376019 60.141697 \nL 170.172906 60.141697 \nL 169.969794 62.330735 \nL 169.766682 62.330735 \nL 169.56357 62.330735 \nL 169.360458 62.330735 \nL 169.157345 62.330735 \nL 168.954233 62.330735 \nL 168.751121 62.330735 \nL 168.548009 62.330735 \nL 168.344897 62.330735 \nL 168.141784 65.168058 \nL 167.938672 65.168058 \nL 167.73556 65.168058 \nL 167.532448 76.51251 \nL 167.329336 76.51251 \nL 167.126223 76.51251 \nL 166.923111 76.51251 \nL 166.719999 76.51251 \nL 166.516887 76.51251 \nL 166.313775 76.51251 \nL 166.110662 76.51251 \nL 165.90755 76.51251 \nL 165.704438 76.51251 \nL 165.501326 76.51251 \nL 165.298214 76.51251 \nL 165.095101 76.51251 \nL 164.891989 76.51251 \nL 164.688877 76.51251 \nL 164.485765 76.51251 \nL 164.282653 76.51251 \nL 164.07954 76.51251 \nL 163.876428 76.51251 \nL 163.673316 76.51251 \nL 163.470204 76.51251 \nL 163.267092 76.51251 \nL 163.063979 76.51251 \nL 162.860867 76.51251 \nL 162.657755 76.51251 \nL 162.454643 76.782047 \nL 162.251531 76.782047 \nL 162.048418 76.782047 \nL 161.845306 76.782047 \nL 161.642194 76.782047 \nL 161.439082 76.782047 \nL 161.235969 76.782047 \nL 161.032857 76.782047 \nL 160.829745 76.972539 \nL 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128.12868 84.813119 \nL 127.925568 84.813119 \nL 127.722456 84.813119 \nL 127.519344 84.813119 \nL 127.316232 84.813119 \nL 127.113119 84.813119 \nL 126.910007 84.813119 \nL 126.706895 84.813119 \nL 126.503783 84.813119 \nL 126.300671 84.813119 \nL 126.097558 84.813119 \nL 125.894446 84.813119 \nL 125.691334 84.813119 \nL 125.488222 84.813119 \nL 125.28511 84.813119 \nL 125.081997 84.813119 \nL 124.878885 84.813119 \nL 124.675773 84.813119 \nL 124.472661 84.813119 \nL 124.269549 84.813119 \nL 124.066436 84.813119 \nL 123.863324 84.813119 \nL 123.660212 84.813119 \nL 123.4571 84.813119 \nL 123.253988 84.813119 \nL 123.050875 84.813119 \nL 122.847763 84.813119 \nL 122.644651 84.813119 \nL 122.441539 84.813119 \nL 122.238426 84.813119 \nL 122.035314 84.813119 \nL 121.832202 84.813119 \nL 121.62909 84.813119 \nL 121.425978 84.813119 \nL 121.222865 85.255408 \nL 121.019753 85.255408 \nL 120.816641 85.255408 \nL 120.613529 85.255408 \nL 120.410417 85.255408 \nL 120.207304 85.255408 \nL 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218.513611 34.227204 \nL 218.310499 34.227204 \nL 218.107386 34.227204 \nL 217.904274 34.227204 \nL 217.701162 34.227204 \nL 217.49805 34.227204 \nL 217.294938 34.227204 \nL 217.091825 34.702817 \nL 216.888713 34.702817 \nL 216.685601 34.702817 \nL 216.482489 34.702817 \nL 216.279377 34.702817 \nL 216.076264 34.702817 \nL 215.873152 34.702817 \nL 215.67004 34.702817 \nL 215.466928 34.702817 \nL 215.263816 35.352392 \nL 215.060703 35.550372 \nL 214.857591 35.550372 \nL 214.654479 35.550372 \nL 214.451367 35.550372 \nL 214.248255 35.550372 \nL 214.045142 35.550372 \nL 213.84203 35.550372 \nL 213.638918 35.720682 \nL 213.435806 36.372914 \nL 213.232693 36.372914 \nL 213.029581 36.372914 \nL 212.826469 36.372914 \nL 212.623357 36.452102 \nL 212.420245 36.452102 \nL 212.217132 36.962524 \nL 212.01402 36.962524 \nL 211.810908 37.185539 \nL 211.607796 37.185539 \nL 211.404684 37.185539 \nL 211.201571 37.185539 \nL 210.998459 37.185539 \nL 210.795347 37.185539 \nL 210.592235 37.185539 \nL 210.389123 37.185539 \nL 210.18601 37.881737 \nL 209.982898 37.881737 \nL 209.779786 37.881737 \nL 209.576674 37.881737 \nL 209.373562 37.881737 \nL 209.170449 37.881737 \nL 208.967337 37.881737 \nL 208.764225 37.881737 \nL 208.561113 37.881737 \nL 208.358001 38.100779 \nL 208.154888 38.100779 \nL 207.951776 38.100779 \nL 207.748664 38.100779 \nL 207.545552 38.100779 \nL 207.34244 38.100779 \nL 207.139327 38.100779 \nL 206.936215 38.100779 \nL 206.733103 38.100779 \nL 206.529991 38.100779 \nL 206.326879 38.100779 \nL 206.123766 38.100779 \nL 205.920654 38.100779 \nL 205.717542 38.100779 \nL 205.51443 38.100779 \nL 205.311318 38.100779 \nL 205.108205 38.100779 \nL 204.905093 38.100779 \nL 204.701981 38.100779 \nL 204.498869 38.100779 \nL 204.295757 38.100779 \nL 204.092644 38.100779 \nL 203.889532 38.100779 \nL 203.68642 38.380254 \nL 203.483308 38.380254 \nL 203.280196 38.380254 \nL 203.077083 38.380254 \nL 202.873971 38.380254 \nL 202.670859 38.380254 \nL 202.467747 38.380254 \nL 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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 400x400 with 0 Axes>"
     },
     "metadata": {}
    }
   ],
   "source": [
    "n_LS = 100\n",
    "\n",
    "for n_LS in [100, 500, 1000]:\n",
    "    fig = plt.figure(dpi=100, figsize=(4, 4))\n",
    "    ax = fig.add_subplot(111)\n",
    "    ax.set_title(f'Surroggate - LS {n_LS}')\n",
    "\n",
    "    # display static results\n",
    "    data = np.array(static_results)\n",
    "\n",
    "    means = data.mean(axis=0)\n",
    "    confidences = (1.9 * data.std(axis=0)) / np.sqrt(data.shape[0])\n",
    "            \n",
    "    ax.plot(means, label=f'classical')\n",
    "    ax.fill_between(np.arange(data.shape[1]), means-confidences, means+confidences, alpha=.25)\n",
    "\n",
    "    for k in sorted(data_results.keys()):\n",
    "        ls_iter, order = k\n",
    "\n",
    "        if ls_iter == n_LS:\n",
    "            \n",
    "            data = np.array(data_results[k])\n",
    "\n",
    "            means = data.mean(axis=0)\n",
    "            confidences = (1.9 * data.std(axis=0)) / np.sqrt(N_RUNS)\n",
    "            \n",
    "            ax.plot(means, label=f'order {order}')\n",
    "            ax.fill_between(np.arange(1000), means-confidences, means+confidences, alpha=.25)\n",
    "\n",
    "    ax.grid()\n",
    "    ax.legend(loc=4)\n",
    "    ax.set_ylabel('AUC ROC')\n",
    "    ax.set_xlabel('Iteration')\n",
    "    # ax.set_yscale('log')\n",
    "    fig.savefig(os.path.join(output_images_folder, f'out_performance_LS-{n_LS}.pdf'), format='pdf', bbox_inches='tight')\n",
    "    #plt.show()\n",
    "fig.clf()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 400x400 with 0 Axes>"
     },
     "metadata": {}
    }
   ],
   "source": [
    "for o in [1, 2]:\n",
    "    fig = plt.figure(dpi=100, figsize=(4, 4))\n",
    "    ax = fig.add_subplot(111)\n",
    "    ax.set_title(f'Surrogate order {o}')\n",
    "\n",
    "    # display static results\n",
    "    data = np.array(static_results)\n",
    "\n",
    "    means = data.mean(axis=0)\n",
    "    confidences = (1.9 * data.std(axis=0)) / np.sqrt(data.shape[0])\n",
    "            \n",
    "    ax.plot(means, label=f'classical')\n",
    "    ax.fill_between(np.arange(data.shape[1]), means-confidences, means+confidences, alpha=.25)\n",
    "\n",
    "    for k in sorted(data_results.keys()):\n",
    "        ls_iter, order = k\n",
    "\n",
    "        if o == order:\n",
    "            \n",
    "            data = np.array(data_results[k])\n",
    "\n",
    "            means = data.mean(axis=0)\n",
    "            confidences = (1.9 * data.std(axis=0)) / np.sqrt(N_RUNS)\n",
    "            \n",
    "            ax.plot(means, label=f'LS {ls_iter}')\n",
    "            ax.fill_between(np.arange(1000), means-confidences, means+confidences, alpha=.25)\n",
    "\n",
    "    ax.grid()\n",
    "    ax.legend(loc=4)\n",
    "    ax.set_ylabel('AUC ROC')\n",
    "    ax.set_xlabel('Iteration')\n",
    "    # ax.set_yscale('log')\n",
    "    fig.savefig(os.path.join(output_images_folder, f'out_performance_SO-{o}.pdf'), format='pdf', bbox_inches='tight')\n",
    "    #plt.show()\n",
    "fig.clf()"
   ]
  },
  {
   "source": [
    "### 2. Curve of model training scores"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "files = os.listdir(surrogate_data_folder)\n",
    "\n",
    "data_results = {}\n",
    "for i in range(1, N_RUNS + 1):\n",
    "    for run in [ f for f in files if f\"RUN_{i}_performance\" in f ]:\n",
    "        \n",
    "        key = extract_params(run)\n",
    "        if key not in data_results:\n",
    "            data_results[key] = []\n",
    "\n",
    "        # need to extract the 50 first solution found from surrogate data file\n",
    "        data_file = os.path.join(surrogate_data_folder, run.replace('_performance.csv', ''))\n",
    "\n",
    "        scores = []\n",
    "        \n",
    "        with open(os.path.join(surrogate_data_folder, run), 'r') as f:\n",
    "            lines = f.readlines()\n",
    "\n",
    "            for index, line in enumerate(lines[:ILS - SS]):\n",
    "                #print(f'{index} => {run}')\n",
    "                #print(line)\n",
    "                scores.append(float(line.split(';')[4]))\n",
    "\n",
    "        # append run data into dictionnary with its key\n",
    "        data_results[key].append(scores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 400x400 with 1 Axes>",
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213.645452 65.444305 \nL 213.859265 65.444305 \nL 214.073079 65.510729 \nL 214.286892 65.510729 \nL 214.500706 65.510729 \nL 214.714519 65.552963 \nL 214.928333 65.882603 \nL 215.142147 68.341494 \nL 215.35596 68.341494 \nL 215.569774 68.341494 \nL 215.783587 68.341494 \nL 215.997401 68.422951 \nL 216.211215 68.422951 \nL 216.425028 68.422951 \nL 216.638842 68.788148 \nL 216.852655 66.125233 \nL 217.066469 66.144694 \nL 217.280282 66.144694 \nL 217.494096 66.144694 \nL 217.70791 66.144694 \nL 217.921723 66.240737 \nL 218.135537 66.240737 \nL 218.34935 66.240737 \nL 218.563164 68.3161 \nL 218.776978 68.238306 \nL 218.990791 68.997922 \nL 219.204605 68.997922 \nL 219.418418 68.997922 \nL 219.632232 68.997922 \nL 219.846045 68.574915 \nL 220.059859 68.574915 \nL 220.273673 65.897082 \nL 220.487486 65.831561 \nL 220.7013 65.899036 \nL 220.915113 65.295599 \nL 221.128927 65.295599 \nL 221.342741 65.295599 \nL 221.556554 68.149013 \nL 221.770368 68.149013 \nL 221.984181 70.829424 \nL 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214.714519 57.446992 \nL 214.500706 57.261405 \nL 214.286892 57.261405 \nL 214.073079 57.261405 \nL 213.859265 57.201945 \nL 213.645452 57.201945 \nL 213.431638 57.201945 \nL 213.217824 56.022839 \nL 213.004011 56.765647 \nL 212.790197 57.211654 \nL 212.576384 57.086755 \nL 212.36257 57.086755 \nL 212.148756 57.086755 \nL 211.934943 57.489442 \nL 211.721129 57.489442 \nL 211.507316 57.608531 \nL 211.293502 57.608531 \nL 211.079689 56.642285 \nL 210.865875 56.58352 \nL 210.652061 57.44019 \nL 210.438248 57.44019 \nL 210.224434 57.44019 \nL 210.010621 57.95195 \nL 209.796807 58.568094 \nL 209.582993 58.568094 \nL 209.36918 58.568094 \nL 209.155366 58.239878 \nL 208.941553 58.327612 \nL 208.727739 57.791393 \nL 208.513926 57.791393 \nL 208.300112 57.791393 \nL 208.086298 56.252768 \nL 207.872485 56.252768 \nL 207.658671 56.252768 \nL 207.444858 56.252768 \nL 207.231044 56.439555 \nL 207.01723 56.822874 \nL 206.803417 56.957966 \nL 206.589603 56.957966 \nL 206.37579 52.652611 \nL 206.161976 52.652611 \nL 205.948163 52.652611 \nL 205.734349 52.652611 \nL 205.520535 52.652611 \nL 205.306722 53.016276 \nL 205.092908 52.849416 \nL 204.879095 52.560461 \nL 204.665281 53.472798 \nL 204.451467 53.932684 \nL 204.237654 53.932684 \nL 204.02384 53.932684 \nL 203.810027 53.932684 \nL 203.596213 53.932684 \nL 203.3824 52.724994 \nL 203.168586 52.869379 \nL 202.954772 53.517122 \nL 202.740959 55.912269 \nL 202.527145 55.14037 \nL 202.313332 55.14037 \nL 202.099518 55.14037 \nL 201.885704 55.14037 \nL 201.671891 55.14037 \nL 201.458077 55.96959 \nL 201.244264 55.96959 \nL 201.03045 55.316861 \nL 200.816637 51.026682 \nL 200.602823 51.513764 \nL 200.389009 51.513764 \nL 200.175196 51.513764 \nL 199.961382 51.513764 \nL 199.747569 51.513764 \nL 199.533755 51.313735 \nL 199.319941 51.313735 \nL 199.106128 51.600214 \nL 198.892314 49.706189 \nL 198.678501 49.595586 \nL 198.464687 49.595586 \nL 198.250874 49.595586 \nL 198.03706 49.595586 \nL 197.823246 49.600052 \nL 197.609433 49.623786 \nL 197.395619 49.623786 \nL 197.181806 49.278832 \nL 196.967992 52.477938 \nL 196.754178 52.844552 \nL 196.540365 52.844552 \nL 196.326551 52.844552 \nL 196.112738 52.844552 \nL 195.898924 52.866153 \nL 195.685111 53.148794 \nL 195.471297 53.148794 \nL 195.257483 53.381427 \nL 195.04367 51.123318 \nL 194.829856 51.473433 \nL 194.616043 51.473433 \nL 194.402229 51.473433 \nL 194.188415 51.473433 \nL 193.974602 51.571193 \nL 193.760788 52.727324 \nL 193.546975 52.727324 \nL 193.333161 50.665509 \nL 193.119348 50.753157 \nL 192.905534 50.703643 \nL 192.69172 50.703643 \nL 192.477907 50.703643 \nL 192.264093 50.703643 \nL 192.05028 50.454033 \nL 191.836466 49.462398 \nL 191.622652 49.462398 \nL 191.408839 49.683529 \nL 191.195025 49.110804 \nL 190.981212 49.117669 \nL 190.767398 49.117669 \nL 190.553585 49.117669 \nL 190.339771 49.117669 \nL 190.125957 49.168395 \nL 189.912144 49.027567 \nL 189.69833 49.027567 \nL 189.484517 49.031037 \nL 189.270703 49.414735 \nL 189.056889 49.432625 \nL 188.843076 49.432625 \nL 188.629262 49.432625 \nL 188.415449 49.432625 \nL 188.201635 49.295414 \nL 187.987822 49.669062 \nL 187.774008 49.669062 \nL 187.560194 49.411082 \nL 187.346381 50.33333 \nL 187.132567 50.32374 \nL 186.918754 50.32374 \nL 186.70494 50.32374 \nL 186.491126 50.32374 \nL 186.277313 50.390635 \nL 186.063499 50.136579 \nL 185.849686 50.136579 \nL 185.635872 51.013393 \nL 185.422059 49.110926 \nL 185.208245 49.10471 \nL 184.994431 49.10471 \nL 184.780618 49.10471 \nL 184.566804 49.10471 \nL 184.352991 48.718539 \nL 184.139177 49.437974 \nL 183.925363 49.437974 \nL 183.71155 48.407202 \nL 183.497736 48.586491 \nL 183.283923 48.264246 \nL 183.070109 48.264246 \nL 182.856296 48.264246 \nL 182.642482 48.264246 \nL 182.428668 48.531922 \nL 182.214855 48.576362 \nL 182.001041 48.576362 \nL 181.787228 49.758735 \nL 181.573414 50.208247 \nL 181.3596 50.772668 \nL 181.145787 50.772668 \nL 180.931973 50.772668 \nL 180.71816 50.772668 \nL 180.504346 51.118022 \nL 180.290532 51.1189 \nL 180.076719 51.1189 \nL 179.862905 50.49196 \nL 179.649092 52.861978 \nL 179.435278 52.501478 \nL 179.221465 52.501478 \nL 179.007651 52.501478 \nL 178.793837 52.501478 \nL 178.580024 52.261169 \nL 178.36621 52.261169 \nL 178.152397 52.261169 \nL 177.938583 51.629247 \nL 177.724769 50.253142 \nL 177.510956 50.191105 \nL 177.297142 50.191105 \nL 177.083329 50.191105 \nL 176.869515 50.024806 \nL 176.655702 50.302192 \nL 176.441888 50.302192 \nL 176.228074 50.302192 \nL 176.014261 48.517796 \nL 175.800447 47.945316 \nL 175.586634 47.970574 \nL 175.37282 47.970574 \nL 175.159006 47.970574 \nL 174.945193 47.989969 \nL 174.731379 48.063372 \nL 174.517566 48.063372 \nL 174.303752 48.063372 \nL 174.089939 49.118287 \nL 173.876125 50.173287 \nL 173.662311 51.030134 \nL 173.448498 51.030134 \nL 173.234684 51.035994 \nL 173.020871 51.035994 \nL 172.807057 51.227508 \nL 172.593243 51.227508 \nL 172.37943 51.227508 \nL 172.165616 51.393276 \nL 171.951803 53.122175 \nL 171.737989 52.552805 \nL 171.524176 52.090596 \nL 171.310362 52.090596 \nL 171.096548 52.090596 \nL 170.882735 52.197143 \nL 170.668921 52.197143 \nL 170.455108 52.197143 \nL 170.241294 51.374228 \nL 170.02748 50.592048 \nL 169.813667 50.01878 \nL 169.599853 50.01878 \nL 169.38604 50.01878 \nL 169.172226 49.962603 \nL 168.958413 49.962603 \nL 168.744599 49.962603 \nL 168.530785 49.962603 \nL 168.316972 53.541108 \nL 168.103158 52.223918 \nL 167.889345 52.631107 \nL 167.675531 52.631107 \nL 167.461717 52.631107 \nL 167.247904 53.265104 \nL 167.03409 53.265104 \nL 166.820277 53.265104 \nL 166.606463 53.265104 \nL 166.39265 52.644217 \nL 166.178836 54.273563 \nL 165.965022 55.553843 \nL 165.751209 55.553843 \nL 165.537395 55.553843 \nL 165.323582 53.828389 \nL 165.109768 53.828389 \nL 164.895954 53.828389 \nL 164.682141 53.828389 \nL 164.468327 54.284058 \nL 164.254514 54.336082 \nL 164.0407 53.625123 \nL 163.826887 53.625123 \nL 163.613073 53.625123 \nL 163.399259 52.538933 \nL 163.185446 52.538933 \nL 162.971632 52.538933 \nL 162.757819 52.538933 \nL 162.544005 52.609294 \nL 162.330191 51.809662 \nL 162.116378 52.44132 \nL 161.902564 52.44132 \nL 161.688751 52.44132 \nL 161.474937 54.523709 \nL 161.261124 54.523709 \nL 161.04731 54.523709 \nL 160.833496 54.523709 \nL 160.619683 54.781126 \nL 160.405869 57.100082 \nL 160.192056 56.622648 \nL 159.978242 56.622648 \nL 159.764428 56.622648 \nL 159.550615 57.022466 \nL 159.336801 57.022466 \nL 159.122988 57.022466 \nL 158.909174 57.022466 \nL 158.695361 56.114614 \nL 158.481547 57.071582 \nL 158.267733 57.463151 \nL 158.05392 57.463151 \nL 157.840106 57.463151 \nL 157.626293 57.01461 \nL 157.412479 57.01461 \nL 157.198665 57.01461 \nL 156.984852 57.01461 \nL 156.771038 55.846363 \nL 156.557225 54.444813 \nL 156.343411 53.851472 \nL 156.129598 53.851472 \nL 155.915784 53.851472 \nL 155.70197 51.12038 \nL 155.488157 51.12038 \nL 155.274343 51.12038 \nL 155.06053 51.212006 \nL 154.846716 50.693075 \nL 154.632902 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128.761459 49.717414 \nL 128.547645 49.717414 \nL 128.333832 49.717414 \nL 128.120018 49.717414 \nL 127.906204 48.082933 \nL 127.692391 47.949678 \nL 127.478577 47.936574 \nL 127.264764 47.936574 \nL 127.05095 48.228495 \nL 126.837137 48.228495 \nL 126.623323 48.228495 \nL 126.409509 48.228495 \nL 126.195696 48.228495 \nL 125.981882 50.32941 \nL 125.768069 51.306563 \nL 125.554255 52.224654 \nL 125.340441 52.224654 \nL 125.126628 52.895113 \nL 124.912814 52.895113 \nL 124.699001 52.895113 \nL 124.485187 52.895113 \nL 124.271374 52.895113 \nL 124.05756 53.1302 \nL 123.843746 52.790401 \nL 123.629933 53.319589 \nL 123.416119 53.319589 \nL 123.202306 50.557018 \nL 122.988492 50.557018 \nL 122.774678 50.557018 \nL 122.560865 50.557018 \nL 122.347051 50.557018 \nL 122.133238 49.121826 \nL 121.919424 49.517907 \nL 121.705611 49.474646 \nL 121.491797 49.474646 \nL 121.277983 50.676195 \nL 121.06417 50.676195 \nL 120.850356 50.676195 \nL 120.636543 50.676195 \nL 120.422729 50.676195 \nL 120.208915 51.446198 \nL 119.995102 51.254662 \nL 119.781288 50.942515 \nL 119.567475 50.942515 \nL 119.353661 50.893819 \nL 119.139848 50.893819 \nL 118.926034 50.893819 \nL 118.71222 50.893819 \nL 118.498407 50.893819 \nL 118.284593 51.482719 \nL 118.07078 51.343992 \nL 117.856966 51.828206 \nL 117.643152 51.828206 \nL 117.429339 54.810796 \nL 117.215525 54.810796 \nL 117.001712 54.810796 \nL 116.787898 54.810796 \nL 116.574085 54.810796 \nL 116.360271 54.728038 \nL 116.146457 53.823446 \nL 115.932644 54.094254 \nL 115.71883 54.094254 \nL 115.505017 53.803977 \nL 115.291203 53.803977 \nL 115.077389 53.803977 \nL 114.863576 53.803977 \nL 114.649762 53.803977 \nL 114.435949 52.760841 \nL 114.222135 51.267904 \nL 114.008322 51.848113 \nL 113.794508 51.848113 \nL 113.580694 53.897741 \nL 113.366881 53.897741 \nL 113.153067 53.897741 \nL 112.939254 53.897741 \nL 112.72544 53.897741 \nL 112.511626 53.825472 \nL 112.297813 52.195971 \nL 112.083999 52.195971 \nL 111.870186 52.195971 \nL 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132.39629 117.818636 \nL 132.610103 118.988793 \nL 132.823917 124.438767 \nL 133.037731 124.481293 \nL 133.251544 124.548599 \nL 133.465358 133.281494 \nL 133.679171 133.281494 \nL 133.892985 133.281494 \nL 134.106798 133.281494 \nL 134.320612 122.942914 \nL 134.534426 117.212878 \nL 134.748239 117.212878 \nL 134.962053 109.363623 \nL 135.175866 109.431632 \nL 135.38968 109.431632 \nL 135.603494 109.431632 \nL 135.817307 109.431632 \nL 136.031121 113.440636 \nL 136.244934 127.149623 \nL 136.458748 127.149623 \nL 136.672561 127.149623 \nL 136.886375 127.471599 \nL 137.100189 127.453655 \nL 137.314002 127.453655 \nL 137.527816 127.453655 \nL 137.741629 123.187096 \nL 137.955443 92.605771 \nL 138.169257 92.605771 \nL 138.38307 92.605771 \nL 138.596884 92.605771 \nL 138.810697 92.470169 \nL 139.024511 92.812725 \nL 139.238324 110.96779 \nL 139.452138 110.96779 \nL 139.665952 106.393462 \nL 139.879765 106.393462 \nL 140.093579 106.393462 \nL 140.307392 106.393462 \nL 140.521206 106.393462 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157.840106 82.391473 \nL 158.05392 82.019363 \nL 158.267733 82.111824 \nL 158.481547 84.977578 \nL 158.695361 84.977578 \nL 158.909174 84.977578 \nL 159.122988 84.977578 \nL 159.336801 84.977578 \nL 159.550615 83.135665 \nL 159.764428 83.135665 \nL 159.978242 82.952035 \nL 160.192056 79.770186 \nL 160.405869 79.770186 \nL 160.619683 79.770186 \nL 160.833496 79.770186 \nL 161.04731 79.770186 \nL 161.261124 84.606684 \nL 161.474937 84.606684 \nL 161.688751 84.606684 \nL 161.902564 79.555564 \nL 162.116378 79.714166 \nL 162.330191 79.714166 \nL 162.544005 79.714166 \nL 162.757819 79.714166 \nL 162.971632 77.746048 \nL 163.185446 77.746048 \nL 163.399259 77.746048 \nL 163.613073 84.341528 \nL 163.826887 84.146363 \nL 164.0407 84.390717 \nL 164.254514 84.390717 \nL 164.468327 84.390717 \nL 164.682141 85.569073 \nL 164.895954 85.569073 \nL 165.109768 85.569073 \nL 165.323582 85.046736 \nL 165.537395 78.320461 \nL 165.751209 78.289085 \nL 165.965022 77.769347 \nL 166.178836 77.769347 \nL 166.39265 72.224443 \nL 166.606463 72.224443 \nL 166.820277 72.224443 \nL 167.03409 69.845079 \nL 167.247904 69.845079 \nL 167.461717 69.22622 \nL 167.675531 69.168851 \nL 167.889345 69.15822 \nL 168.103158 70.040609 \nL 168.316972 70.040609 \nL 168.530785 70.040609 \nL 168.744599 70.332128 \nL 168.958413 70.332128 \nL 169.172226 77.480574 \nL 169.38604 77.480574 \nL 169.599853 77.43829 \nL 169.813667 76.112385 \nL 170.02748 76.112385 \nL 170.241294 76.112385 \nL 170.455108 76.112385 \nL 170.668921 73.024023 \nL 170.882735 71.877829 \nL 171.096548 71.877829 \nL 171.310362 71.877829 \nL 171.524176 72.221009 \nL 171.737989 71.94258 \nL 171.951803 71.94258 \nL 172.165616 71.94258 \nL 172.37943 76.814276 \nL 172.593243 86.500696 \nL 172.807057 86.500696 \nL 173.020871 86.500696 \nL 173.234684 89.791884 \nL 173.448498 89.76094 \nL 173.662311 89.863424 \nL 173.876125 89.863424 \nL 174.089939 98.489194 \nL 174.303752 95.4585 \nL 174.517566 95.4585 \nL 174.731379 95.4585 \nL 174.945193 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235.240624 74.957833 \nL 235.454437 76.15724 \nL 235.668251 76.15724 \nL 235.882064 73.163976 \nL 236.095878 70.33719 \nL 236.309691 70.33719 \nL 236.523505 70.585217 \nL 236.737319 70.585217 \nL 236.951132 70.585217 \nL 237.164946 71.275772 \nL 237.378759 71.275772 \nL 237.592573 71.244286 \nL 237.806387 74.452875 \nL 238.0202 74.452875 \nL 238.234014 74.452875 \nL 238.447827 74.600833 \nL 238.661641 74.600833 \nL 238.875454 73.20094 \nL 239.089268 73.210552 \nL 239.303082 76.149329 \nL 239.516895 77.603113 \nL 239.730709 77.603113 \nL 239.944522 77.603113 \nL 240.158336 77.603113 \nL 240.37215 77.155347 \nL 240.585963 76.99166 \nL 240.799777 76.99166 \nL 241.01359 74.439647 \nL 241.227404 71.408569 \nL 241.441217 71.408569 \nL 241.655031 71.408569 \nL 241.868845 71.408569 \nL 242.082658 71.408569 \nL 242.296472 69.636537 \nL 242.510285 69.636537 \nL 242.724099 75.99289 \nL 242.937913 76.11837 \nL 243.151726 74.268711 \nL 243.36554 74.268711 \nL 243.579353 74.268711 \nL 243.793167 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235.882064 54.441394 \nL 235.668251 55.024281 \nL 235.454437 55.024281 \nL 235.240624 54.729832 \nL 235.02681 54.787056 \nL 234.812996 54.787056 \nL 234.599183 54.787056 \nL 234.385369 54.263221 \nL 234.171556 54.263221 \nL 233.957742 53.65937 \nL 233.743928 53.65937 \nL 233.530115 53.527564 \nL 233.316301 53.527564 \nL 233.102488 51.995004 \nL 232.888674 51.995004 \nL 232.67486 51.995004 \nL 232.461047 54.573977 \nL 232.247233 52.935733 \nL 232.03342 52.935733 \nL 231.819606 52.681223 \nL 231.605793 52.681223 \nL 231.391979 52.681223 \nL 231.178165 57.097744 \nL 230.964352 57.097744 \nL 230.750538 57.097744 \nL 230.536725 58.837248 \nL 230.322911 58.837248 \nL 230.109097 58.055217 \nL 229.895284 58.055217 \nL 229.68147 58.055217 \nL 229.467657 58.055217 \nL 229.253843 59.320901 \nL 229.04003 59.320901 \nL 228.826216 59.12598 \nL 228.612402 55.003799 \nL 228.398589 56.063283 \nL 228.184775 56.063283 \nL 227.970962 56.063283 \nL 227.757148 56.063283 \nL 227.543334 56.063283 \nL 227.329521 50.415469 \nL 227.115707 50.575147 \nL 226.901894 52.506368 \nL 226.68808 49.68621 \nL 226.474267 49.28788 \nL 226.260453 49.28788 \nL 226.046639 49.28788 \nL 225.832826 49.28788 \nL 225.619012 49.28788 \nL 225.405199 53.114175 \nL 225.191385 53.114175 \nL 224.977571 57.024664 \nL 224.763758 57.894148 \nL 224.549944 57.894148 \nL 224.336131 57.894148 \nL 224.122317 57.894148 \nL 223.908504 57.894148 \nL 223.69469 57.976343 \nL 223.480876 53.743005 \nL 223.267063 53.743005 \nL 223.053249 53.273334 \nL 222.839436 52.863174 \nL 222.625622 52.863174 \nL 222.411808 52.863174 \nL 222.197995 52.863174 \nL 221.984181 52.712836 \nL 221.770368 52.712836 \nL 221.556554 53.567065 \nL 221.342741 53.181422 \nL 221.128927 49.425518 \nL 220.915113 49.425518 \nL 220.7013 49.425518 \nL 220.487486 49.425518 \nL 220.273673 49.423384 \nL 220.059859 49.423384 \nL 219.846045 49.423384 \nL 219.632232 50.839683 \nL 219.418418 50.439828 \nL 219.204605 50.90426 \nL 218.990791 50.90426 \nL 218.776978 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210.010621 57.302012 \nL 209.796807 57.302012 \nL 209.582993 57.302012 \nL 209.36918 57.302012 \nL 209.155366 57.302012 \nL 208.941553 56.427635 \nL 208.727739 55.938768 \nL 208.513926 55.938768 \nL 208.300112 57.236435 \nL 208.086298 57.236435 \nL 207.872485 57.236435 \nL 207.658671 57.236435 \nL 207.444858 57.236435 \nL 207.231044 57.236435 \nL 207.01723 57.551801 \nL 206.803417 58.444232 \nL 206.589603 58.336825 \nL 206.37579 57.928703 \nL 206.161976 57.928703 \nL 205.948163 57.928703 \nL 205.734349 57.928703 \nL 205.520535 57.928703 \nL 205.306722 57.92152 \nL 205.092908 56.663928 \nL 204.879095 57.075818 \nL 204.665281 57.075818 \nL 204.451467 58.244295 \nL 204.237654 58.244295 \nL 204.02384 58.244295 \nL 203.810027 58.244295 \nL 203.596213 58.436672 \nL 203.3824 58.436672 \nL 203.168586 59.096423 \nL 202.954772 58.147326 \nL 202.740959 58.147326 \nL 202.527145 57.619732 \nL 202.313332 57.619732 \nL 202.099518 57.619732 \nL 201.885704 57.733922 \nL 201.671891 57.733922 \nL 201.458077 57.077591 \nL 201.244264 57.424456 \nL 201.03045 57.589425 \nL 200.816637 57.589425 \nL 200.602823 58.465634 \nL 200.389009 58.465634 \nL 200.175196 58.75308 \nL 199.961382 58.75308 \nL 199.747569 58.960159 \nL 199.533755 58.960159 \nL 199.319941 58.124691 \nL 199.106128 57.424626 \nL 198.892314 57.424626 \nL 198.678501 56.465501 \nL 198.464687 56.426852 \nL 198.250874 56.426852 \nL 198.03706 56.76061 \nL 197.823246 56.76061 \nL 197.609433 56.76061 \nL 197.395619 54.673282 \nL 197.181806 56.892749 \nL 196.967992 56.892749 \nL 196.754178 58.332658 \nL 196.540365 58.332658 \nL 196.326551 58.197703 \nL 196.112738 58.197703 \nL 195.898924 58.197703 \nL 195.685111 58.197703 \nL 195.471297 58.828432 \nL 195.257483 58.652396 \nL 195.04367 58.177502 \nL 194.829856 58.084085 \nL 194.616043 55.532949 \nL 194.402229 55.532949 \nL 194.188415 55.532949 \nL 193.974602 55.532949 \nL 193.760788 55.532949 \nL 193.546975 55.847404 \nL 193.333161 56.960669 \nL 193.119348 56.960669 \nL 192.905534 57.227026 \nL 192.69172 57.227026 \nL 192.477907 57.227026 \nL 192.264093 57.227026 \nL 192.05028 57.227026 \nL 191.836466 55.238204 \nL 191.622652 54.747633 \nL 191.408839 54.747633 \nL 191.195025 54.740934 \nL 190.981212 56.35002 \nL 190.767398 56.35002 \nL 190.553585 56.35002 \nL 190.339771 56.35002 \nL 190.125957 56.587964 \nL 189.912144 57.387934 \nL 189.69833 59.224277 \nL 189.484517 58.528044 \nL 189.270703 58.528044 \nL 189.056889 58.231935 \nL 188.843076 58.231935 \nL 188.629262 58.231935 \nL 188.415449 58.231935 \nL 188.201635 58.015639 \nL 187.987822 58.015639 \nL 187.774008 56.51456 \nL 187.560194 56.51456 \nL 187.346381 55.90572 \nL 187.132567 55.90572 \nL 186.918754 55.90572 \nL 186.70494 55.90572 \nL 186.491126 56.838615 \nL 186.277313 57.183374 \nL 186.063499 57.25638 \nL 185.849686 57.363832 \nL 185.635872 57.893948 \nL 185.422059 57.893948 \nL 185.208245 57.893948 \nL 184.994431 57.893948 \nL 184.780618 57.885133 \nL 184.566804 57.885133 \nL 184.352991 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163.613073 83.546649 \nL 163.826887 83.546649 \nL 164.0407 85.568039 \nL 164.254514 71.175082 \nL 164.468327 71.175082 \nL 164.682141 71.066428 \nL 164.895954 71.066428 \nL 165.109768 71.066428 \nL 165.323582 71.066428 \nL 165.537395 71.196867 \nL 165.751209 70.75744 \nL 165.965022 75.165484 \nL 166.178836 75.254186 \nL 166.39265 75.254186 \nL 166.606463 72.84683 \nL 166.820277 72.84683 \nL 167.03409 72.84683 \nL 167.247904 72.84683 \nL 167.461717 84.917638 \nL 167.675531 82.988534 \nL 167.889345 82.988534 \nL 168.103158 83.715118 \nL 168.316972 83.715118 \nL 168.530785 86.119441 \nL 168.744599 86.119441 \nL 168.958413 86.119441 \nL 169.172226 77.722133 \nL 169.38604 77.72573 \nL 169.599853 78.948643 \nL 169.813667 78.948643 \nL 170.02748 78.882699 \nL 170.241294 80.468345 \nL 170.455108 80.468345 \nL 170.668921 80.468345 \nL 170.882735 79.225311 \nL 171.096548 79.225311 \nL 171.310362 79.229998 \nL 171.524176 79.101341 \nL 171.737989 79.101341 \nL 171.951803 84.329682 \nL 172.165616 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55.487251 \nL 240.799777 55.565066 \nL 241.01359 55.565066 \nL 241.227404 55.1643 \nL 241.441217 55.1643 \nL 241.655031 55.1643 \nL 241.868845 55.1643 \nL 242.082658 55.1643 \nL 242.296472 55.1643 \nL 242.510285 55.526671 \nL 242.724099 51.743539 \nL 242.937913 51.743539 \nL 243.151726 52.30454 \nL 243.36554 52.30454 \nL 243.579353 52.30454 \nL 243.793167 52.30454 \nL 244.00698 52.30454 \nL 244.220794 52.30454 \nL 244.434608 50.631644 \nL 244.648421 53.025659 \nL 244.862235 53.025659 \nL 245.076048 52.641774 \nL 245.289862 52.641774 \nL 245.503676 52.641774 \nL 245.717489 52.641774 \nL 245.931303 52.641774 \nL 246.145116 52.641774 \nL 246.35893 53.928113 \nL 246.572743 52.076267 \nL 246.786557 52.076267 \nL 247.000371 50.509693 \nL 247.214184 50.509693 \nL 247.427998 50.509693 \nL 247.641811 50.509693 \nL 247.855625 50.509693 \nL 248.069439 50.509693 \nL 248.283252 49.470989 \nL 248.497066 48.745947 \nL 248.710879 48.745947 \nL 248.924693 50.387719 \nL 249.138506 50.387719 \nL 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45.171286 \nL 255.980541 45.431761 \nL 255.766728 45.786665 \nL 255.552914 45.786665 \nL 255.3391 45.786665 \nL 255.125287 45.786665 \nL 254.911473 45.786665 \nL 254.69766 45.786665 \nL 254.483846 44.935857 \nL 254.270032 44.935857 \nL 254.056219 44.414411 \nL 253.842405 44.562309 \nL 253.628592 44.562309 \nL 253.414778 44.562309 \nL 253.200965 44.562309 \nL 252.987151 44.562309 \nL 252.773337 44.562309 \nL 252.559524 45.480286 \nL 252.34571 45.480286 \nL 252.131897 45.717864 \nL 251.918083 44.925493 \nL 251.704269 44.925493 \nL 251.490456 44.925493 \nL 251.276642 44.925493 \nL 251.062829 44.925493 \nL 250.849015 44.925493 \nL 250.635202 43.977038 \nL 250.421388 43.977038 \nL 250.207574 45.032332 \nL 249.993761 45.403201 \nL 249.779947 45.403201 \nL 249.566134 45.403201 \nL 249.35232 45.403201 \nL 249.138506 45.403201 \nL 248.924693 45.403201 \nL 248.710879 45.624253 \nL 248.497066 45.624253 \nL 248.283252 46.171691 \nL 248.069439 46.399229 \nL 247.855625 46.399229 \nL 247.641811 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213.004011 45.461051 \nL 212.790197 45.461051 \nL 212.576384 45.461051 \nL 212.36257 45.461051 \nL 212.148756 44.660664 \nL 211.934943 44.660664 \nL 211.721129 43.947332 \nL 211.507316 43.440081 \nL 211.293502 43.440081 \nL 211.079689 43.440081 \nL 210.865875 43.440081 \nL 210.652061 43.440081 \nL 210.438248 43.440081 \nL 210.224434 43.688545 \nL 210.010621 43.688545 \nL 209.796807 44.234394 \nL 209.582993 45.249061 \nL 209.36918 45.249061 \nL 209.155366 45.249061 \nL 208.941553 45.249061 \nL 208.727739 45.249061 \nL 208.513926 45.249061 \nL 208.300112 45.165234 \nL 208.086298 45.165234 \nL 207.872485 46.311672 \nL 207.658671 45.148075 \nL 207.444858 45.148075 \nL 207.231044 45.148075 \nL 207.01723 45.148075 \nL 206.803417 45.148075 \nL 206.589603 45.148075 \nL 206.37579 46.019308 \nL 206.161976 46.019308 \nL 205.948163 45.437407 \nL 205.734349 44.96498 \nL 205.520535 44.96498 \nL 205.306722 44.96498 \nL 205.092908 44.96498 \nL 204.879095 44.96498 \nL 204.665281 44.96498 \nL 204.451467 45.034606 \nL 204.237654 45.034606 \nL 204.02384 45.344166 \nL 203.810027 44.922286 \nL 203.596213 44.922286 \nL 203.3824 44.922286 \nL 203.168586 44.922286 \nL 202.954772 44.922286 \nL 202.740959 44.922286 \nL 202.527145 45.252107 \nL 202.313332 45.252107 \nL 202.099518 45.475189 \nL 201.885704 45.304157 \nL 201.671891 45.304157 \nL 201.458077 45.304157 \nL 201.244264 45.304157 \nL 201.03045 45.304157 \nL 200.816637 45.304157 \nL 200.602823 45.476589 \nL 200.389009 45.476589 \nL 200.175196 44.809671 \nL 199.961382 45.559511 \nL 199.747569 45.559511 \nL 199.533755 45.559511 \nL 199.319941 45.559511 \nL 199.106128 45.559511 \nL 198.892314 45.677023 \nL 198.678501 45.13249 \nL 198.464687 45.13249 \nL 198.250874 45.386502 \nL 198.03706 45.932276 \nL 197.823246 45.932276 \nL 197.609433 45.932276 \nL 197.395619 45.932276 \nL 197.181806 45.932276 \nL 196.967992 45.289793 \nL 196.754178 46.364381 \nL 196.540365 46.364381 \nL 196.326551 46.978275 \nL 196.112738 46.448096 \nL 195.898924 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170.02748 46.741015 \nL 169.813667 47.100107 \nL 169.599853 47.100107 \nL 169.38604 45.566948 \nL 169.172226 45.512749 \nL 168.958413 43.612251 \nL 168.744599 43.612251 \nL 168.530785 43.612251 \nL 168.316972 40.147516 \nL 168.103158 40.147516 \nL 167.889345 37.627321 \nL 167.675531 37.627321 \nL 167.461717 39.562376 \nL 167.247904 44.937493 \nL 167.03409 44.937493 \nL 166.820277 44.937493 \nL 166.606463 44.937493 \nL 166.39265 48.115387 \nL 166.178836 48.115387 \nL 165.965022 50.242211 \nL 165.751209 50.88004 \nL 165.537395 51.058414 \nL 165.323582 48.971045 \nL 165.109768 48.971045 \nL 164.895954 48.971045 \nL 164.682141 48.971045 \nL 164.468327 49.02796 \nL 164.254514 49.02796 \nL 164.0407 46.584473 \nL 163.826887 44.056588 \nL 163.613073 44.056588 \nL 163.399259 45.088599 \nL 163.185446 45.088599 \nL 162.971632 45.088599 \nL 162.757819 45.088599 \nL 162.544005 45.968046 \nL 162.330191 47.296214 \nL 162.116378 47.250167 \nL 161.902564 47.250167 \nL 161.688751 47.250167 \nL 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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 400x400 with 0 Axes>"
     },
     "metadata": {}
    }
   ],
   "source": [
    "n_LS = 100\n",
    "\n",
    "for n_LS in [100, 500, 1000]:\n",
    "    fig = plt.figure(dpi=100, figsize=(4, 4))\n",
    "    ax = fig.add_subplot(111)\n",
    "    ax.set_title(f'Surrogate model - LS {n_LS}')\n",
    "\n",
    "    for k in sorted(data_results.keys()):\n",
    "        ls_iter, order = k\n",
    "\n",
    "        if ls_iter == n_LS:\n",
    "            \n",
    "            data = np.array(data_results[k])\n",
    "\n",
    "            means = data.mean(axis=0)\n",
    "            confidences = (1.9 * data.std(axis=0)) / np.sqrt(N_RUNS)\n",
    "            \n",
    "            ax.plot(means, label=f'order {order}')\n",
    "            ax.fill_between(np.arange(ILS - SS), means-confidences, means+confidences, alpha=.25)\n",
    "\n",
    "    ax.grid()\n",
    "    ax.legend(loc=4)\n",
    "    ax.set_ylabel('R²')\n",
    "    ax.set_xlabel('Iteration')\n",
    "    ax.set_ylim(0.5, 1)\n",
    "    # ax.set_yscale('log')\n",
    "    fig.savefig(os.path.join(output_images_folder, f'model_scores_LS-{n_LS}.pdf'), format='pdf', bbox_inches='tight')\n",
    "    #plt.show()\n",
    "fig.clf()"
   ]
  },
  {
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   "outputs": [
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213.645452 65.444305 \nL 213.859265 65.444305 \nL 214.073079 65.510729 \nL 214.286892 65.510729 \nL 214.500706 65.510729 \nL 214.714519 65.552963 \nL 214.928333 65.882603 \nL 215.142147 68.341494 \nL 215.35596 68.341494 \nL 215.569774 68.341494 \nL 215.783587 68.341494 \nL 215.997401 68.422951 \nL 216.211215 68.422951 \nL 216.425028 68.422951 \nL 216.638842 68.788148 \nL 216.852655 66.125233 \nL 217.066469 66.144694 \nL 217.280282 66.144694 \nL 217.494096 66.144694 \nL 217.70791 66.144694 \nL 217.921723 66.240737 \nL 218.135537 66.240737 \nL 218.34935 66.240737 \nL 218.563164 68.3161 \nL 218.776978 68.238306 \nL 218.990791 68.997922 \nL 219.204605 68.997922 \nL 219.418418 68.997922 \nL 219.632232 68.997922 \nL 219.846045 68.574915 \nL 220.059859 68.574915 \nL 220.273673 65.897082 \nL 220.487486 65.831561 \nL 220.7013 65.899036 \nL 220.915113 65.295599 \nL 221.128927 65.295599 \nL 221.342741 65.295599 \nL 221.556554 68.149013 \nL 221.770368 68.149013 \nL 221.984181 70.829424 \nL 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214.714519 57.446992 \nL 214.500706 57.261405 \nL 214.286892 57.261405 \nL 214.073079 57.261405 \nL 213.859265 57.201945 \nL 213.645452 57.201945 \nL 213.431638 57.201945 \nL 213.217824 56.022839 \nL 213.004011 56.765647 \nL 212.790197 57.211654 \nL 212.576384 57.086755 \nL 212.36257 57.086755 \nL 212.148756 57.086755 \nL 211.934943 57.489442 \nL 211.721129 57.489442 \nL 211.507316 57.608531 \nL 211.293502 57.608531 \nL 211.079689 56.642285 \nL 210.865875 56.58352 \nL 210.652061 57.44019 \nL 210.438248 57.44019 \nL 210.224434 57.44019 \nL 210.010621 57.95195 \nL 209.796807 58.568094 \nL 209.582993 58.568094 \nL 209.36918 58.568094 \nL 209.155366 58.239878 \nL 208.941553 58.327612 \nL 208.727739 57.791393 \nL 208.513926 57.791393 \nL 208.300112 57.791393 \nL 208.086298 56.252768 \nL 207.872485 56.252768 \nL 207.658671 56.252768 \nL 207.444858 56.252768 \nL 207.231044 56.439555 \nL 207.01723 56.822874 \nL 206.803417 56.957966 \nL 206.589603 56.957966 \nL 206.37579 52.652611 \nL 206.161976 52.652611 \nL 205.948163 52.652611 \nL 205.734349 52.652611 \nL 205.520535 52.652611 \nL 205.306722 53.016276 \nL 205.092908 52.849416 \nL 204.879095 52.560461 \nL 204.665281 53.472798 \nL 204.451467 53.932684 \nL 204.237654 53.932684 \nL 204.02384 53.932684 \nL 203.810027 53.932684 \nL 203.596213 53.932684 \nL 203.3824 52.724994 \nL 203.168586 52.869379 \nL 202.954772 53.517122 \nL 202.740959 55.912269 \nL 202.527145 55.14037 \nL 202.313332 55.14037 \nL 202.099518 55.14037 \nL 201.885704 55.14037 \nL 201.671891 55.14037 \nL 201.458077 55.96959 \nL 201.244264 55.96959 \nL 201.03045 55.316861 \nL 200.816637 51.026682 \nL 200.602823 51.513764 \nL 200.389009 51.513764 \nL 200.175196 51.513764 \nL 199.961382 51.513764 \nL 199.747569 51.513764 \nL 199.533755 51.313735 \nL 199.319941 51.313735 \nL 199.106128 51.600214 \nL 198.892314 49.706189 \nL 198.678501 49.595586 \nL 198.464687 49.595586 \nL 198.250874 49.595586 \nL 198.03706 49.595586 \nL 197.823246 49.600052 \nL 197.609433 49.623786 \nL 197.395619 49.623786 \nL 197.181806 49.278832 \nL 196.967992 52.477938 \nL 196.754178 52.844552 \nL 196.540365 52.844552 \nL 196.326551 52.844552 \nL 196.112738 52.844552 \nL 195.898924 52.866153 \nL 195.685111 53.148794 \nL 195.471297 53.148794 \nL 195.257483 53.381427 \nL 195.04367 51.123318 \nL 194.829856 51.473433 \nL 194.616043 51.473433 \nL 194.402229 51.473433 \nL 194.188415 51.473433 \nL 193.974602 51.571193 \nL 193.760788 52.727324 \nL 193.546975 52.727324 \nL 193.333161 50.665509 \nL 193.119348 50.753157 \nL 192.905534 50.703643 \nL 192.69172 50.703643 \nL 192.477907 50.703643 \nL 192.264093 50.703643 \nL 192.05028 50.454033 \nL 191.836466 49.462398 \nL 191.622652 49.462398 \nL 191.408839 49.683529 \nL 191.195025 49.110804 \nL 190.981212 49.117669 \nL 190.767398 49.117669 \nL 190.553585 49.117669 \nL 190.339771 49.117669 \nL 190.125957 49.168395 \nL 189.912144 49.027567 \nL 189.69833 49.027567 \nL 189.484517 49.031037 \nL 189.270703 49.414735 \nL 189.056889 49.432625 \nL 188.843076 49.432625 \nL 188.629262 49.432625 \nL 188.415449 49.432625 \nL 188.201635 49.295414 \nL 187.987822 49.669062 \nL 187.774008 49.669062 \nL 187.560194 49.411082 \nL 187.346381 50.33333 \nL 187.132567 50.32374 \nL 186.918754 50.32374 \nL 186.70494 50.32374 \nL 186.491126 50.32374 \nL 186.277313 50.390635 \nL 186.063499 50.136579 \nL 185.849686 50.136579 \nL 185.635872 51.013393 \nL 185.422059 49.110926 \nL 185.208245 49.10471 \nL 184.994431 49.10471 \nL 184.780618 49.10471 \nL 184.566804 49.10471 \nL 184.352991 48.718539 \nL 184.139177 49.437974 \nL 183.925363 49.437974 \nL 183.71155 48.407202 \nL 183.497736 48.586491 \nL 183.283923 48.264246 \nL 183.070109 48.264246 \nL 182.856296 48.264246 \nL 182.642482 48.264246 \nL 182.428668 48.531922 \nL 182.214855 48.576362 \nL 182.001041 48.576362 \nL 181.787228 49.758735 \nL 181.573414 50.208247 \nL 181.3596 50.772668 \nL 181.145787 50.772668 \nL 180.931973 50.772668 \nL 180.71816 50.772668 \nL 180.504346 51.118022 \nL 180.290532 51.1189 \nL 180.076719 51.1189 \nL 179.862905 50.49196 \nL 179.649092 52.861978 \nL 179.435278 52.501478 \nL 179.221465 52.501478 \nL 179.007651 52.501478 \nL 178.793837 52.501478 \nL 178.580024 52.261169 \nL 178.36621 52.261169 \nL 178.152397 52.261169 \nL 177.938583 51.629247 \nL 177.724769 50.253142 \nL 177.510956 50.191105 \nL 177.297142 50.191105 \nL 177.083329 50.191105 \nL 176.869515 50.024806 \nL 176.655702 50.302192 \nL 176.441888 50.302192 \nL 176.228074 50.302192 \nL 176.014261 48.517796 \nL 175.800447 47.945316 \nL 175.586634 47.970574 \nL 175.37282 47.970574 \nL 175.159006 47.970574 \nL 174.945193 47.989969 \nL 174.731379 48.063372 \nL 174.517566 48.063372 \nL 174.303752 48.063372 \nL 174.089939 49.118287 \nL 173.876125 50.173287 \nL 173.662311 51.030134 \nL 173.448498 51.030134 \nL 173.234684 51.035994 \nL 173.020871 51.035994 \nL 172.807057 51.227508 \nL 172.593243 51.227508 \nL 172.37943 51.227508 \nL 172.165616 51.393276 \nL 171.951803 53.122175 \nL 171.737989 52.552805 \nL 171.524176 52.090596 \nL 171.310362 52.090596 \nL 171.096548 52.090596 \nL 170.882735 52.197143 \nL 170.668921 52.197143 \nL 170.455108 52.197143 \nL 170.241294 51.374228 \nL 170.02748 50.592048 \nL 169.813667 50.01878 \nL 169.599853 50.01878 \nL 169.38604 50.01878 \nL 169.172226 49.962603 \nL 168.958413 49.962603 \nL 168.744599 49.962603 \nL 168.530785 49.962603 \nL 168.316972 53.541108 \nL 168.103158 52.223918 \nL 167.889345 52.631107 \nL 167.675531 52.631107 \nL 167.461717 52.631107 \nL 167.247904 53.265104 \nL 167.03409 53.265104 \nL 166.820277 53.265104 \nL 166.606463 53.265104 \nL 166.39265 52.644217 \nL 166.178836 54.273563 \nL 165.965022 55.553843 \nL 165.751209 55.553843 \nL 165.537395 55.553843 \nL 165.323582 53.828389 \nL 165.109768 53.828389 \nL 164.895954 53.828389 \nL 164.682141 53.828389 \nL 164.468327 54.284058 \nL 164.254514 54.336082 \nL 164.0407 53.625123 \nL 163.826887 53.625123 \nL 163.613073 53.625123 \nL 163.399259 52.538933 \nL 163.185446 52.538933 \nL 162.971632 52.538933 \nL 162.757819 52.538933 \nL 162.544005 52.609294 \nL 162.330191 51.809662 \nL 162.116378 52.44132 \nL 161.902564 52.44132 \nL 161.688751 52.44132 \nL 161.474937 54.523709 \nL 161.261124 54.523709 \nL 161.04731 54.523709 \nL 160.833496 54.523709 \nL 160.619683 54.781126 \nL 160.405869 57.100082 \nL 160.192056 56.622648 \nL 159.978242 56.622648 \nL 159.764428 56.622648 \nL 159.550615 57.022466 \nL 159.336801 57.022466 \nL 159.122988 57.022466 \nL 158.909174 57.022466 \nL 158.695361 56.114614 \nL 158.481547 57.071582 \nL 158.267733 57.463151 \nL 158.05392 57.463151 \nL 157.840106 57.463151 \nL 157.626293 57.01461 \nL 157.412479 57.01461 \nL 157.198665 57.01461 \nL 156.984852 57.01461 \nL 156.771038 55.846363 \nL 156.557225 54.444813 \nL 156.343411 53.851472 \nL 156.129598 53.851472 \nL 155.915784 53.851472 \nL 155.70197 51.12038 \nL 155.488157 51.12038 \nL 155.274343 51.12038 \nL 155.06053 51.212006 \nL 154.846716 50.693075 \nL 154.632902 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128.761459 49.717414 \nL 128.547645 49.717414 \nL 128.333832 49.717414 \nL 128.120018 49.717414 \nL 127.906204 48.082933 \nL 127.692391 47.949678 \nL 127.478577 47.936574 \nL 127.264764 47.936574 \nL 127.05095 48.228495 \nL 126.837137 48.228495 \nL 126.623323 48.228495 \nL 126.409509 48.228495 \nL 126.195696 48.228495 \nL 125.981882 50.32941 \nL 125.768069 51.306563 \nL 125.554255 52.224654 \nL 125.340441 52.224654 \nL 125.126628 52.895113 \nL 124.912814 52.895113 \nL 124.699001 52.895113 \nL 124.485187 52.895113 \nL 124.271374 52.895113 \nL 124.05756 53.1302 \nL 123.843746 52.790401 \nL 123.629933 53.319589 \nL 123.416119 53.319589 \nL 123.202306 50.557018 \nL 122.988492 50.557018 \nL 122.774678 50.557018 \nL 122.560865 50.557018 \nL 122.347051 50.557018 \nL 122.133238 49.121826 \nL 121.919424 49.517907 \nL 121.705611 49.474646 \nL 121.491797 49.474646 \nL 121.277983 50.676195 \nL 121.06417 50.676195 \nL 120.850356 50.676195 \nL 120.636543 50.676195 \nL 120.422729 50.676195 \nL 120.208915 51.446198 \nL 119.995102 51.254662 \nL 119.781288 50.942515 \nL 119.567475 50.942515 \nL 119.353661 50.893819 \nL 119.139848 50.893819 \nL 118.926034 50.893819 \nL 118.71222 50.893819 \nL 118.498407 50.893819 \nL 118.284593 51.482719 \nL 118.07078 51.343992 \nL 117.856966 51.828206 \nL 117.643152 51.828206 \nL 117.429339 54.810796 \nL 117.215525 54.810796 \nL 117.001712 54.810796 \nL 116.787898 54.810796 \nL 116.574085 54.810796 \nL 116.360271 54.728038 \nL 116.146457 53.823446 \nL 115.932644 54.094254 \nL 115.71883 54.094254 \nL 115.505017 53.803977 \nL 115.291203 53.803977 \nL 115.077389 53.803977 \nL 114.863576 53.803977 \nL 114.649762 53.803977 \nL 114.435949 52.760841 \nL 114.222135 51.267904 \nL 114.008322 51.848113 \nL 113.794508 51.848113 \nL 113.580694 53.897741 \nL 113.366881 53.897741 \nL 113.153067 53.897741 \nL 112.939254 53.897741 \nL 112.72544 53.897741 \nL 112.511626 53.825472 \nL 112.297813 52.195971 \nL 112.083999 52.195971 \nL 111.870186 52.195971 \nL 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131.968663 104.644255 \nL 132.182476 104.658526 \nL 132.39629 104.658526 \nL 132.610103 104.658526 \nL 132.823917 99.892666 \nL 133.037731 99.892666 \nL 133.251544 100.788734 \nL 133.465358 100.788734 \nL 133.679171 93.550907 \nL 133.892985 93.550907 \nL 134.106798 120.151891 \nL 134.320612 120.151891 \nL 134.534426 120.897711 \nL 134.748239 120.897711 \nL 134.962053 123.020283 \nL 135.175866 123.020283 \nL 135.38968 121.858945 \nL 135.603494 121.858945 \nL 135.817307 121.858945 \nL 136.031121 121.886549 \nL 136.244934 121.410607 \nL 136.458748 121.410607 \nL 136.672561 119.576443 \nL 136.886375 119.576443 \nL 137.100189 119.26813 \nL 137.314002 119.26813 \nL 137.527816 119.26813 \nL 137.741629 119.26813 \nL 137.955443 120.725629 \nL 138.169257 108.029501 \nL 138.38307 106.317931 \nL 138.596884 106.317931 \nL 138.810697 106.652812 \nL 139.024511 106.652812 \nL 139.238324 106.652812 \nL 139.452138 117.399805 \nL 139.665952 118.691128 \nL 139.879765 118.467768 \nL 140.093579 117.14472 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148.646122 98.403374 \nL 148.859936 98.230769 \nL 149.073749 96.138341 \nL 149.287563 96.138341 \nL 149.501376 96.237559 \nL 149.71519 96.237559 \nL 149.929004 96.237559 \nL 150.142817 96.237559 \nL 150.356631 97.12611 \nL 150.570444 120.026626 \nL 150.784258 118.227664 \nL 150.998072 118.227664 \nL 151.211885 118.227664 \nL 151.425699 118.20366 \nL 151.639512 118.20366 \nL 151.853326 118.20366 \nL 152.067139 119.712475 \nL 152.280953 120.429411 \nL 152.494767 120.536724 \nL 152.70858 120.536724 \nL 152.922394 120.536724 \nL 153.136207 120.536724 \nL 153.350021 123.703205 \nL 153.563835 123.703205 \nL 153.777648 123.339177 \nL 153.991462 122.599751 \nL 154.205275 122.15155 \nL 154.419089 122.15155 \nL 154.632902 123.012714 \nL 154.846716 123.012714 \nL 155.06053 123.012714 \nL 155.274343 123.030113 \nL 155.488157 122.799024 \nL 155.70197 119.791867 \nL 155.915784 119.638799 \nL 156.129598 112.723029 \nL 156.343411 112.723029 \nL 156.557225 112.723029 \nL 156.771038 112.723029 \nL 156.984852 112.723029 \nL 157.198665 114.156448 \nL 157.412479 113.410629 \nL 157.626293 112.808624 \nL 157.840106 112.808624 \nL 158.05392 112.808624 \nL 158.267733 112.808624 \nL 158.481547 112.808624 \nL 158.695361 112.808624 \nL 158.909174 111.642985 \nL 159.122988 110.041773 \nL 159.336801 109.480527 \nL 159.550615 109.480527 \nL 159.764428 109.480527 \nL 159.978242 109.480527 \nL 160.192056 109.480527 \nL 160.405869 120.9174 \nL 160.619683 120.299526 \nL 160.833496 120.106711 \nL 161.04731 120.341067 \nL 161.261124 120.341067 \nL 161.474937 120.341067 \nL 161.688751 115.25268 \nL 161.902564 115.25268 \nL 162.116378 115.25268 \nL 162.330191 115.459842 \nL 162.544005 115.459842 \nL 162.757819 114.777914 \nL 162.971632 116.480483 \nL 163.185446 116.480483 \nL 163.399259 116.480483 \nL 163.613073 116.480483 \nL 163.826887 116.480483 \nL 164.0407 118.148418 \nL 164.254514 118.148418 \nL 164.468327 109.84396 \nL 164.682141 109.84396 \nL 164.895954 109.772635 \nL 165.109768 109.772635 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173.662311 90.820573 \nL 173.876125 90.820573 \nL 174.089939 90.820573 \nL 174.303752 87.592806 \nL 174.517566 87.900849 \nL 174.731379 87.830812 \nL 174.945193 87.830812 \nL 175.159006 87.830812 \nL 175.37282 87.830812 \nL 175.586634 87.830812 \nL 175.800447 87.830812 \nL 176.014261 87.711113 \nL 176.228074 87.711113 \nL 176.441888 84.895154 \nL 176.655702 84.895154 \nL 176.869515 84.895154 \nL 177.083329 84.895154 \nL 177.297142 84.895154 \nL 177.510956 84.895154 \nL 177.724769 81.198519 \nL 177.938583 81.198519 \nL 178.152397 80.876558 \nL 178.36621 81.697338 \nL 178.580024 81.697338 \nL 178.793837 81.697338 \nL 179.007651 81.697338 \nL 179.221465 81.697338 \nL 179.435278 83.835981 \nL 179.649092 83.835981 \nL 179.862905 83.269207 \nL 180.076719 82.361225 \nL 180.290532 81.662132 \nL 180.504346 81.662132 \nL 180.71816 81.662132 \nL 180.931973 81.662132 \nL 181.145787 82.805355 \nL 181.3596 82.805355 \nL 181.573414 83.054084 \nL 181.787228 83.054084 \nL 182.001041 83.013164 \nL 182.214855 83.313367 \nL 182.428668 83.313367 \nL 182.642482 83.313367 \nL 182.856296 82.502683 \nL 183.070109 82.502683 \nL 183.283923 82.719921 \nL 183.497736 82.719921 \nL 183.71155 82.719921 \nL 183.925363 82.973154 \nL 184.139177 82.873739 \nL 184.352991 82.873739 \nL 184.566804 86.898702 \nL 184.780618 86.898702 \nL 184.994431 86.915273 \nL 185.208245 86.915273 \nL 185.422059 86.915273 \nL 185.635872 86.915273 \nL 185.849686 86.675479 \nL 186.063499 86.679278 \nL 186.277313 87.075061 \nL 186.491126 86.895258 \nL 186.70494 85.465634 \nL 186.918754 85.465634 \nL 187.132567 85.465634 \nL 187.346381 85.465634 \nL 187.560194 85.793335 \nL 187.774008 85.793335 \nL 187.987822 87.851106 \nL 188.201635 87.851106 \nL 188.415449 88.178033 \nL 188.629262 88.178033 \nL 188.843076 88.178033 \nL 189.056889 88.178033 \nL 189.270703 88.32789 \nL 189.484517 88.32789 \nL 189.69833 85.189659 \nL 189.912144 85.20805 \nL 190.125957 84.269332 \nL 190.339771 84.151943 \nL 190.553585 84.151943 \nL 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199.319941 77.233697 \nL 199.533755 77.279344 \nL 199.747569 77.279344 \nL 199.961382 78.599878 \nL 200.175196 78.599878 \nL 200.389009 77.771738 \nL 200.602823 77.771738 \nL 200.816637 77.61398 \nL 201.03045 77.61398 \nL 201.244264 77.546253 \nL 201.458077 77.496222 \nL 201.671891 73.317191 \nL 201.885704 73.317191 \nL 202.099518 72.6972 \nL 202.313332 72.6972 \nL 202.527145 72.6972 \nL 202.740959 72.781914 \nL 202.954772 72.781914 \nL 203.168586 73.351128 \nL 203.3824 73.285002 \nL 203.596213 73.285002 \nL 203.810027 72.703362 \nL 204.02384 72.703362 \nL 204.237654 72.703362 \nL 204.451467 72.703362 \nL 204.665281 72.563124 \nL 204.879095 72.563124 \nL 205.092908 69.784569 \nL 205.306722 69.912511 \nL 205.520535 69.955526 \nL 205.734349 69.955526 \nL 205.948163 69.955526 \nL 206.161976 69.955526 \nL 206.37579 69.955526 \nL 206.589603 69.955973 \nL 206.803417 68.353459 \nL 207.01723 67.950441 \nL 207.231044 67.498017 \nL 207.444858 67.498017 \nL 207.658671 67.498017 \nL 207.872485 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242.296472 67.415778 \nL 242.510285 67.415778 \nL 242.724099 66.966275 \nL 242.937913 64.339924 \nL 243.151726 64.274924 \nL 243.36554 64.236917 \nL 243.579353 64.236917 \nL 243.793167 63.781183 \nL 244.00698 63.781183 \nL 244.220794 63.781183 \nL 244.434608 63.781183 \nL 244.648421 66.579309 \nL 244.862235 66.579309 \nL 245.076048 66.667586 \nL 245.289862 66.650213 \nL 245.503676 66.650213 \nL 245.717489 66.972585 \nL 245.931303 66.972585 \nL 246.145116 66.972585 \nL 246.35893 62.857023 \nL 246.572743 62.428903 \nL 246.786557 62.428903 \nL 247.000371 63.709376 \nL 247.214184 63.77891 \nL 247.427998 63.77891 \nL 247.641811 63.803941 \nL 247.855625 63.803941 \nL 248.069439 64.088852 \nL 248.283252 64.088852 \nL 248.497066 64.401357 \nL 248.710879 64.401357 \nL 248.924693 64.084058 \nL 249.138506 64.120934 \nL 249.35232 64.120934 \nL 249.566134 63.652786 \nL 249.779947 63.652786 \nL 249.993761 62.623561 \nL 250.207574 62.623561 \nL 250.421388 62.885318 \nL 250.635202 62.885318 \nL 250.849015 62.619519 \nL 251.062829 62.541651 \nL 251.276642 62.541651 \nL 251.490456 62.709775 \nL 251.704269 62.709775 \nL 251.918083 62.269723 \nL 252.131897 62.269723 \nL 252.34571 62.869221 \nL 252.559524 62.869221 \nL 252.773337 63.566491 \nL 252.987151 63.462763 \nL 253.200965 63.462763 \nL 253.414778 63.469383 \nL 253.628592 64.945587 \nL 253.842405 64.945587 \nL 254.056219 64.945587 \nL 254.270032 63.672151 \nL 254.483846 63.672151 \nL 254.69766 62.016887 \nL 254.911473 62.028845 \nL 255.125287 62.028845 \nL 255.3391 64.039624 \nL 255.552914 64.039624 \nL 255.766728 64.039624 \nL 255.980541 64.039624 \nL 256.194355 64.418283 \nL 256.408168 64.418283 \nL 256.621982 64.614243 \nL 256.835795 64.639468 \nL 256.835795 49.741774 \nL 256.835795 49.741774 \nL 256.621982 50.429485 \nL 256.408168 50.238311 \nL 256.194355 50.238311 \nL 255.980541 49.758095 \nL 255.766728 49.758095 \nL 255.552914 49.758095 \nL 255.3391 49.758095 \nL 255.125287 50.327753 \nL 254.911473 50.327753 \nL 254.69766 50.742001 \nL 254.483846 51.486521 \nL 254.270032 51.486521 \nL 254.056219 52.796988 \nL 253.842405 52.796988 \nL 253.628592 52.796988 \nL 253.414778 52.807261 \nL 253.200965 52.77434 \nL 252.987151 52.77434 \nL 252.773337 52.076195 \nL 252.559524 51.878541 \nL 252.34571 51.878541 \nL 252.131897 51.631137 \nL 251.918083 51.631137 \nL 251.704269 51.613522 \nL 251.490456 51.613522 \nL 251.276642 50.895704 \nL 251.062829 50.895704 \nL 250.849015 50.208988 \nL 250.635202 50.28639 \nL 250.421388 50.28639 \nL 250.207574 50.130953 \nL 249.993761 50.130953 \nL 249.779947 50.062373 \nL 249.566134 50.062373 \nL 249.35232 51.321242 \nL 249.138506 51.321242 \nL 248.924693 51.547647 \nL 248.710879 51.656147 \nL 248.497066 51.656147 \nL 248.283252 51.304697 \nL 248.069439 51.304697 \nL 247.855625 51.326253 \nL 247.641811 51.326253 \nL 247.427998 51.282325 \nL 247.214184 51.282325 \nL 247.000371 51.767045 \nL 246.786557 51.212851 \nL 246.572743 51.212851 \nL 246.35893 51.589476 \nL 246.145116 50.850611 \nL 245.931303 50.850611 \nL 245.717489 50.850611 \nL 245.503676 50.02564 \nL 245.289862 50.02564 \nL 245.076048 50.749444 \nL 244.862235 50.64852 \nL 244.648421 50.64852 \nL 244.434608 50.558318 \nL 244.220794 50.558318 \nL 244.00698 50.558318 \nL 243.793167 50.558318 \nL 243.579353 51.587862 \nL 243.36554 51.587862 \nL 243.151726 50.794488 \nL 242.937913 50.855715 \nL 242.724099 50.307259 \nL 242.510285 50.924932 \nL 242.296472 50.924932 \nL 242.082658 50.924932 \nL 241.868845 50.924932 \nL 241.655031 50.352653 \nL 241.441217 50.352653 \nL 241.227404 51.599372 \nL 241.01359 51.308028 \nL 240.799777 51.308028 \nL 240.585963 51.848985 \nL 240.37215 51.848985 \nL 240.158336 51.848985 \nL 239.944522 51.848985 \nL 239.730709 52.421087 \nL 239.516895 52.421087 \nL 239.303082 52.307677 \nL 239.089268 51.615635 \nL 238.875454 51.615635 \nL 238.661641 51.049737 \nL 238.447827 51.049737 \nL 238.234014 51.049737 \nL 238.0202 51.049737 \nL 237.806387 50.721739 \nL 237.592573 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211.721129 57.062263 \nL 211.507316 57.062263 \nL 211.293502 57.062263 \nL 211.079689 57.062263 \nL 210.865875 57.160176 \nL 210.652061 56.962237 \nL 210.438248 56.962237 \nL 210.224434 57.437605 \nL 210.010621 57.302012 \nL 209.796807 57.302012 \nL 209.582993 57.302012 \nL 209.36918 57.302012 \nL 209.155366 57.302012 \nL 208.941553 56.427635 \nL 208.727739 55.938768 \nL 208.513926 55.938768 \nL 208.300112 57.236435 \nL 208.086298 57.236435 \nL 207.872485 57.236435 \nL 207.658671 57.236435 \nL 207.444858 57.236435 \nL 207.231044 57.236435 \nL 207.01723 57.551801 \nL 206.803417 58.444232 \nL 206.589603 58.336825 \nL 206.37579 57.928703 \nL 206.161976 57.928703 \nL 205.948163 57.928703 \nL 205.734349 57.928703 \nL 205.520535 57.928703 \nL 205.306722 57.92152 \nL 205.092908 56.663928 \nL 204.879095 57.075818 \nL 204.665281 57.075818 \nL 204.451467 58.244295 \nL 204.237654 58.244295 \nL 204.02384 58.244295 \nL 203.810027 58.244295 \nL 203.596213 58.436672 \nL 203.3824 58.436672 \nL 203.168586 59.096423 \nL 202.954772 58.147326 \nL 202.740959 58.147326 \nL 202.527145 57.619732 \nL 202.313332 57.619732 \nL 202.099518 57.619732 \nL 201.885704 57.733922 \nL 201.671891 57.733922 \nL 201.458077 57.077591 \nL 201.244264 57.424456 \nL 201.03045 57.589425 \nL 200.816637 57.589425 \nL 200.602823 58.465634 \nL 200.389009 58.465634 \nL 200.175196 58.75308 \nL 199.961382 58.75308 \nL 199.747569 58.960159 \nL 199.533755 58.960159 \nL 199.319941 58.124691 \nL 199.106128 57.424626 \nL 198.892314 57.424626 \nL 198.678501 56.465501 \nL 198.464687 56.426852 \nL 198.250874 56.426852 \nL 198.03706 56.76061 \nL 197.823246 56.76061 \nL 197.609433 56.76061 \nL 197.395619 54.673282 \nL 197.181806 56.892749 \nL 196.967992 56.892749 \nL 196.754178 58.332658 \nL 196.540365 58.332658 \nL 196.326551 58.197703 \nL 196.112738 58.197703 \nL 195.898924 58.197703 \nL 195.685111 58.197703 \nL 195.471297 58.828432 \nL 195.257483 58.652396 \nL 195.04367 58.177502 \nL 194.829856 58.084085 \nL 194.616043 55.532949 \nL 194.402229 55.532949 \nL 194.188415 55.532949 \nL 193.974602 55.532949 \nL 193.760788 55.532949 \nL 193.546975 55.847404 \nL 193.333161 56.960669 \nL 193.119348 56.960669 \nL 192.905534 57.227026 \nL 192.69172 57.227026 \nL 192.477907 57.227026 \nL 192.264093 57.227026 \nL 192.05028 57.227026 \nL 191.836466 55.238204 \nL 191.622652 54.747633 \nL 191.408839 54.747633 \nL 191.195025 54.740934 \nL 190.981212 56.35002 \nL 190.767398 56.35002 \nL 190.553585 56.35002 \nL 190.339771 56.35002 \nL 190.125957 56.587964 \nL 189.912144 57.387934 \nL 189.69833 59.224277 \nL 189.484517 58.528044 \nL 189.270703 58.528044 \nL 189.056889 58.231935 \nL 188.843076 58.231935 \nL 188.629262 58.231935 \nL 188.415449 58.231935 \nL 188.201635 58.015639 \nL 187.987822 58.015639 \nL 187.774008 56.51456 \nL 187.560194 56.51456 \nL 187.346381 55.90572 \nL 187.132567 55.90572 \nL 186.918754 55.90572 \nL 186.70494 55.90572 \nL 186.491126 56.838615 \nL 186.277313 57.183374 \nL 186.063499 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76.111057 \nL 102.248574 76.111057 \nL 102.462388 76.111057 \nL 102.676202 77.483141 \nL 102.890015 72.499455 \nL 103.103829 69.428174 \nL 103.317642 69.428174 \nL 103.531456 69.428174 \nL 103.74527 69.346496 \nL 103.959083 69.346496 \nL 104.172897 69.346496 \nL 104.38671 69.346496 \nL 104.600524 68.762592 \nL 104.814337 71.081157 \nL 105.028151 71.081157 \nL 105.241965 71.081157 \nL 105.455778 71.081157 \nL 105.669592 70.975868 \nL 105.883405 70.975868 \nL 106.097219 70.975868 \nL 106.311033 70.716936 \nL 106.524846 70.975139 \nL 106.73866 63.93451 \nL 106.952473 63.93451 \nL 107.166287 63.93451 \nL 107.3801 63.93451 \nL 107.593914 64.229239 \nL 107.807728 64.229239 \nL 108.021541 68.381364 \nL 108.235355 68.381364 \nL 108.449168 68.801821 \nL 108.662982 68.755117 \nL 108.876796 68.755117 \nL 109.090609 68.755117 \nL 109.304423 68.755117 \nL 109.518236 69.382886 \nL 109.73205 75.790286 \nL 109.945863 75.790286 \nL 110.159677 78.243223 \nL 110.373491 76.452343 \nL 110.587304 76.398989 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119.353661 69.090559 \nL 119.567475 69.804895 \nL 119.781288 71.072333 \nL 119.995102 71.072333 \nL 120.208915 65.398013 \nL 120.422729 65.398013 \nL 120.636543 65.398013 \nL 120.850356 65.398013 \nL 121.06417 65.398013 \nL 121.277983 65.398013 \nL 121.491797 65.084551 \nL 121.705611 65.084551 \nL 121.919424 65.084551 \nL 122.133238 65.528307 \nL 122.347051 65.528307 \nL 122.560865 65.528307 \nL 122.774678 65.528307 \nL 122.988492 65.528307 \nL 123.202306 65.528307 \nL 123.416119 62.852961 \nL 123.629933 62.852961 \nL 123.843746 68.714199 \nL 124.05756 67.705172 \nL 124.271374 67.705172 \nL 124.485187 67.705172 \nL 124.699001 67.705172 \nL 124.912814 67.705172 \nL 125.126628 68.609237 \nL 125.340441 69.853893 \nL 125.554255 77.67953 \nL 125.768069 77.67953 \nL 125.981882 77.302037 \nL 126.195696 77.302037 \nL 126.409509 77.302037 \nL 126.623323 77.302037 \nL 126.837137 77.783412 \nL 127.05095 77.783412 \nL 127.264764 81.437066 \nL 127.478577 81.437066 \nL 127.692391 81.437066 \nL 127.906204 81.788121 \nL 128.120018 81.788121 \nL 128.333832 81.788121 \nL 128.547645 81.99022 \nL 128.761459 81.99022 \nL 128.975272 72.059412 \nL 129.189086 71.796801 \nL 129.4029 71.796801 \nL 129.616713 71.796801 \nL 129.830527 71.947031 \nL 130.04434 71.947031 \nL 130.258154 71.947031 \nL 130.471968 69.395907 \nL 130.685781 70.291313 \nL 130.899595 71.900389 \nL 131.113408 71.900389 \nL 131.327222 71.900389 \nL 131.541035 71.900389 \nL 131.754849 72.092109 \nL 131.968663 72.092109 \nL 132.182476 72.092109 \nL 132.39629 68.854612 \nL 132.610103 70.317535 \nL 132.823917 70.317535 \nL 133.037731 70.317535 \nL 133.251544 70.317535 \nL 133.465358 70.317535 \nL 133.679171 70.275838 \nL 133.892985 70.275838 \nL 134.106798 80.769355 \nL 134.320612 80.973477 \nL 134.534426 79.086322 \nL 134.748239 79.086322 \nL 134.962053 79.086322 \nL 135.175866 79.086322 \nL 135.38968 79.086322 \nL 135.603494 79.025613 \nL 135.817307 71.408199 \nL 136.031121 73.671743 \nL 136.244934 74.302608 \nL 136.458748 74.302608 \nL 136.672561 74.302608 \nL 136.886375 74.302608 \nL 137.100189 74.302608 \nL 137.314002 74.302608 \nL 137.527816 70.018388 \nL 137.741629 72.760244 \nL 137.955443 72.760244 \nL 138.169257 72.233736 \nL 138.38307 72.233736 \nL 138.596884 72.233736 \nL 138.810697 72.233736 \nL 139.024511 72.233736 \nL 139.238324 72.233736 \nL 139.452138 71.028044 \nL 139.665952 63.488906 \nL 139.879765 63.488906 \nL 140.093579 61.788474 \nL 140.307392 61.788474 \nL 140.521206 61.788474 \nL 140.73502 61.788474 \nL 140.948833 61.788474 \nL 141.162647 65.079342 \nL 141.37646 73.673944 \nL 141.590274 73.673944 \nL 141.804087 73.673944 \nL 142.017901 73.654387 \nL 142.231715 73.654387 \nL 142.445528 73.654387 \nL 142.659342 73.654387 \nL 142.873155 76.694127 \nL 143.086969 71.700816 \nL 143.300783 71.210598 \nL 143.514596 71.210598 \nL 143.72841 71.210598 \nL 143.942223 71.185103 \nL 144.156037 71.185103 \nL 144.36985 71.185103 \nL 144.583664 66.096935 \nL 144.797478 68.013036 \nL 145.011291 68.013036 \nL 145.225105 67.859518 \nL 145.438918 67.859518 \nL 145.652732 67.859518 \nL 145.866546 67.991772 \nL 146.080359 67.991772 \nL 146.294173 66.874892 \nL 146.507986 66.353937 \nL 146.7218 66.353937 \nL 146.935613 66.353937 \nL 147.149427 66.635702 \nL 147.363241 66.635702 \nL 147.577054 66.635702 \nL 147.790868 66.671961 \nL 148.004681 69.0588 \nL 148.218495 70.664776 \nL 148.432309 70.664776 \nL 148.646122 70.664776 \nL 148.859936 70.664776 \nL 149.073749 70.470663 \nL 149.287563 70.470663 \nL 149.501376 70.470663 \nL 149.71519 70.482871 \nL 149.929004 67.069481 \nL 150.142817 59.188845 \nL 150.356631 59.188845 \nL 150.570444 59.188845 \nL 150.784258 59.188845 \nL 150.998072 59.764792 \nL 151.211885 59.764792 \nL 151.425699 65.465332 \nL 151.639512 66.994976 \nL 151.853326 81.663632 \nL 152.067139 81.663632 \nL 152.280953 81.663632 \nL 152.494767 81.663632 \nL 152.70858 81.663632 \nL 152.922394 81.314522 \nL 153.136207 80.344667 \nL 153.350021 80.344667 \nL 153.563835 72.435932 \nL 153.777648 72.435932 \nL 153.991462 72.435932 \nL 154.205275 72.435932 \nL 154.419089 72.435932 \nL 154.632902 72.435932 \nL 154.846716 72.910366 \nL 155.06053 72.337204 \nL 155.274343 74.330617 \nL 155.488157 74.005489 \nL 155.70197 74.005489 \nL 155.915784 74.005489 \nL 156.129598 74.005489 \nL 156.343411 74.005489 \nL 156.557225 75.333183 \nL 156.771038 75.327666 \nL 156.984852 76.459934 \nL 157.198665 76.459934 \nL 157.412479 76.782253 \nL 157.626293 76.782253 \nL 157.840106 76.782253 \nL 158.05392 76.782253 \nL 158.267733 76.782253 \nL 158.481547 75.342674 \nL 158.695361 71.424552 \nL 158.909174 71.424552 \nL 159.122988 71.932848 \nL 159.336801 71.932848 \nL 159.550615 71.932848 \nL 159.764428 71.932848 \nL 159.978242 71.932848 \nL 160.192056 71.932848 \nL 160.405869 71.379344 \nL 160.619683 77.011499 \nL 160.833496 77.130579 \nL 161.04731 77.130579 \nL 161.261124 71.790373 \nL 161.474937 71.790373 \nL 161.688751 71.790373 \nL 161.902564 71.790373 \nL 162.116378 72.289332 \nL 162.330191 71.654913 \nL 162.544005 71.663981 \nL 162.757819 70.95865 \nL 162.971632 70.843555 \nL 163.185446 76.284301 \nL 163.399259 76.284301 \nL 163.613073 76.284301 \nL 163.826887 71.490557 \nL 164.0407 71.490557 \nL 164.254514 72.247052 \nL 164.468327 72.333207 \nL 164.682141 72.191699 \nL 164.895954 72.191699 \nL 165.109768 72.191699 \nL 165.323582 72.191699 \nL 165.537395 70.952054 \nL 165.751209 71.068742 \nL 165.965022 71.068742 \nL 166.178836 70.223803 \nL 166.39265 74.202228 \nL 166.606463 74.639487 \nL 166.820277 74.639487 \nL 167.03409 74.639487 \nL 167.247904 74.444857 \nL 167.461717 74.444857 \nL 167.675531 74.444857 \nL 167.889345 74.444857 \nL 168.103158 77.779706 \nL 168.316972 77.819609 \nL 168.530785 77.443177 \nL 168.744599 77.443177 \nL 168.958413 77.983077 \nL 169.172226 77.983077 \nL 169.38604 77.983077 \nL 169.599853 77.983077 \nL 169.813667 72.180276 \nL 170.02748 72.180276 \nL 170.241294 72.870906 \nL 170.455108 73.024836 \nL 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187.774008 72.958487 \nL 187.987822 72.958487 \nL 188.201635 72.958487 \nL 188.415449 72.958487 \nL 188.629262 70.534172 \nL 188.843076 70.534172 \nL 189.056889 70.534172 \nL 189.270703 70.841654 \nL 189.484517 70.762133 \nL 189.69833 71.441785 \nL 189.912144 71.441785 \nL 190.125957 71.441785 \nL 190.339771 67.832235 \nL 190.553585 67.896706 \nL 190.767398 67.896706 \nL 190.981212 67.896706 \nL 191.195025 67.343023 \nL 191.408839 67.293137 \nL 191.622652 68.046105 \nL 191.836466 68.046105 \nL 192.05028 70.116169 \nL 192.264093 70.116169 \nL 192.477907 70.112934 \nL 192.69172 70.112934 \nL 192.905534 70.112934 \nL 193.119348 70.439851 \nL 193.333161 70.82836 \nL 193.546975 70.84484 \nL 193.760788 69.879418 \nL 193.974602 69.879418 \nL 194.188415 69.879418 \nL 194.402229 69.810504 \nL 194.616043 69.810504 \nL 194.829856 69.810504 \nL 195.04367 70.277589 \nL 195.257483 70.026079 \nL 195.471297 70.599929 \nL 195.685111 70.599929 \nL 195.898924 70.599929 \nL 196.112738 70.599929 \nL 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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 400x400 with 0 Axes>"
     },
     "metadata": {}
    }
   ],
   "source": [
    "for o in [1, 2]:\n",
    "    fig = plt.figure(dpi=100, figsize=(4, 4))\n",
    "    ax = fig.add_subplot(111)\n",
    "    ax.set_title(f'Surrogate model - order {o}')\n",
    "\n",
    "    for k in sorted(data_results.keys()):\n",
    "        ls_iter, order = k\n",
    "\n",
    "        if o == order:\n",
    "            \n",
    "            data = np.array(data_results[k])\n",
    "\n",
    "            means = data.mean(axis=0)\n",
    "            confidences = (1.9 * data.std(axis=0)) / np.sqrt(N_RUNS)\n",
    "            \n",
    "            ax.plot(means, label=f'LS {ls_iter}')\n",
    "            ax.fill_between(np.arange(ILS - SS), means-confidences, means+confidences, alpha=.25)\n",
    "\n",
    "    ax.grid()\n",
    "    ax.legend(loc=4)\n",
    "    ax.set_ylabel('R²')\n",
    "    ax.set_xlabel('Iteration')\n",
    "    ax.set_ylim(0.5, 1)\n",
    "    # ax.set_yscale('log')\n",
    "    fig.savefig(os.path.join(output_images_folder, f'model_scores_SO-{o}.pdf'), format='pdf', bbox_inches='tight')\n",
    "    #plt.show()\n",
    "fig.clf()"
   ]
  },
  {
   "source": [
    "### 3. Display more selected attributes"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "results_folder = os.path.join(data_folder, 'results')\n",
    "results_file = os.path.join(results_folder, 'optimization_comparisons_attributes.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_solutions = {}\n",
    "with open(results_file, 'r') as f:\n",
    "    for line in f.readlines():\n",
    "        order = line.split(';')[0].split('-')[5].replace('SO_', '')\n",
    "        ls_iter = line.split(';')[0].split('-')[3].replace('LS_', '')\n",
    "        key = (int(ls_iter), int(order))\n",
    "        data_line = line.split(';')[2].replace('[', '').replace(']', '')\n",
    "        binary_sol = list(map(int, data_line.split(' ')))\n",
    "\n",
    "        if key not in all_solutions:\n",
    "            all_solutions[key] = []\n",
    "\n",
    "        all_solutions[key].append(binary_sol)"
   ]
  },
  {
   "source": [
    "#### Global occurences"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "binary_sols = []\n",
    "binary_sol_orders = {}\n",
    "for k in all_solutions:\n",
    "    ls_iter, order = k\n",
    "\n",
    "    if order not in binary_sol_orders:\n",
    "        binary_sol_orders[order] = []\n",
    "\n",
    "    for sol in all_solutions[k]:\n",
    "        binary_sols.append(sol)\n",
    "\n",
    "        binary_sol_orders[order].append(sol)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 800x400 with 0 Axes>"
     },
     "metadata": {}
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 800x400 with 0 Axes>"
     },
     "metadata": {}
    }
   ],
   "source": [
    "binary_sum = np.sum(binary_sols, axis=0)\n",
    "\n",
    "# overall\n",
    "fig = plt.figure(dpi=100, figsize=(8, 4))\n",
    "ax = fig.add_axes([0,0,1,1])\n",
    "ax.set_title('Surrogate - attributes choices')\n",
    "ax.bar(np.arange(1, len(binary_sum) + 1), binary_sum, label='All')\n",
    "ax.set_xticks(np.arange(1, len(binary_sum) + 1))\n",
    "ax.set_ylabel('Occurences')\n",
    "ax.set_xlabel('Attribute index')\n",
    "fig.savefig(os.path.join(output_images_folder, f'attributes_occurences.pdf'), format='pdf', bbox_inches='tight')\n",
    "fig.clf()\n",
    "\n",
    "# for each order\n",
    "fig = plt.figure(dpi=100, figsize=(8, 4))\n",
    "ax = fig.add_axes([0,0,1,1])\n",
    "ax.set_title('Surrogate - attributes choices depending of order')\n",
    "\n",
    "widths = [-0.2, 0.2]\n",
    "for order in [1, 2]:\n",
    "    binary_sum = np.sum(binary_sol_orders[order], axis=0)\n",
    "    ax.bar(np.arange(1, len(binary_sum) + 1) - widths[order - 1], binary_sum, 0.4, label=f'Order {order}')\n",
    "ax.set_xticks(np.arange(1, len(binary_sum) + 1))\n",
    "ax.set_ylabel('Occurences')\n",
    "ax.set_xlabel('Attribute index')\n",
    "ax.legend(loc=2)\n",
    "fig.savefig(os.path.join(output_images_folder, f'attributes_occurences_orders.pdf'), format='pdf', bbox_inches='tight')\n",
    "fig.clf()\n"
   ]
  }
 ]
}