1387 lines (1386 with data), 872.9 kB

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'pd' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[1], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m file \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcovid_analytics_clinical_data.csv\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m----> 2\u001b[0m COVID_data \u001b[38;5;241m=\u001b[39m \u001b[43mpd\u001b[49m\u001b[38;5;241m.\u001b[39mread_csv(file)\n\u001b[1;32m      6\u001b[0m COVID_data\u001b[38;5;241m.\u001b[39mrename(columns\u001b[38;5;241m=\u001b[39m{\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mMean corpuscular hemoglobin concentration (MCHC)\u001b[39m\u001b[38;5;124m'\u001b[39m: \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mMCHC\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mMean corpuscular hemoglobin (MCH)\u001b[39m\u001b[38;5;124m'\u001b[39m: \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mMCH\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mRed blood cell distribution width (RDW)\u001b[39m\u001b[38;5;124m'\u001b[39m:\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mRDW\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mMean corpuscular volume (MCV)\u001b[39m\u001b[38;5;124m'\u001b[39m:\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mMCV\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mProteina C reativa mg/dL\u001b[39m\u001b[38;5;124m'\u001b[39m:\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mCRP\u001b[39m\u001b[38;5;124m'\u001b[39m}, inplace\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n",
      "\u001b[0;31mNameError\u001b[0m: name 'pd' is not defined"
     ]
    }
   ],
   "source": [
    "file = \"covid_analytics_clinical_data.csv\"\n",
    "COVID_data = pd.read_csv(file)\n",
    "\n",
    "\n",
    "\n",
    "COVID_data.rename(columns={'Mean corpuscular hemoglobin concentration (MCHC)': 'MCHC', 'Mean corpuscular hemoglobin (MCH)': 'MCH', 'Red blood cell distribution width (RDW)':'RDW', 'Mean corpuscular volume (MCV)':'MCV', 'Proteina C reativa mg/dL':'CRP'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_variables = [\"Patient age quantile\", \n",
    "                  \"Hemoglobin\", \n",
    "                  \"Platelets\", \n",
    "                  \"Red blood Cells\",\n",
    "                  \"MCHC\",\n",
    "                  \"MCH\",\n",
    "                  \"RDW\",\n",
    "                  \"MCV\",\n",
    "                  \"Lymphocytes\",\n",
    "                  \"Leukocytes\", # <-1\n",
    "                  \"Monocytes\", #\n",
    "                  \"Basophils\", # <-1\n",
    "                  \"Eosinophils\", # <-1\n",
    "                  \"CRP\", # <-1\n",
    "                  \"Hematocrit\", # <-1\n",
    "                  \"Mean platelet volume \", ##\n",
    "                  \"Neutrophils\" # <-1\n",
    "                ]\n",
    "\n",
    "all_variables = [\"Patient age quantile\", \n",
    "                  \"Hemoglobin\", \n",
    "                  \"Platelets\", \n",
    "                  #\"Red blood Cells\",\n",
    "                  #\"MCHC\",\n",
    "                  #\"MCH\",\n",
    "                  #\"RDW\",\n",
    "                  #\"MCV\",\n",
    "                  #\"Lymphocytes\",\n",
    "                  \"Leukocytes\", # <-1\n",
    "                  \"Monocytes\", #\n",
    "                  \"Basophils\", # <-1\n",
    "                  \"Eosinophils\", # <-1\n",
    "                  \"CRP\", # <-1\n",
    "                  \"Hematocrit\", # <-1\n",
    "                  #\"Mean platelet volume \", ##\n",
    "                  \"Neutrophils\" # <-1\n",
    "                ]\n",
    "\n",
    "\n",
    "test_results = [\"result\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create dataset for all variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 601 entries, 1 to 5643\n",
      "Data columns (total 11 columns):\n",
      "Patient age quantile    601 non-null int64\n",
      "Hemoglobin              601 non-null float64\n",
      "Platelets               601 non-null float64\n",
      "Leukocytes              601 non-null float64\n",
      "Monocytes               601 non-null float64\n",
      "Basophils               601 non-null float64\n",
      "Eosinophils             601 non-null float64\n",
      "CRP                     501 non-null float64\n",
      "Hematocrit              601 non-null float64\n",
      "Neutrophils             513 non-null float64\n",
      "result                  601 non-null int64\n",
      "dtypes: float64(9), int64(2)\n",
      "memory usage: 56.3 KB\n"
     ]
    }
   ],
   "source": [
    "COVID_data = COVID_data.dropna(subset=[\"Monocytes\"])\n",
    "\n",
    "COVID_data[\"result\"] = COVID_data[\"SARS-Cov-2 exam result\"].map({'positive': 1, 'negative': 0})\n",
    "COVID_all_variables = COVID_data[all_variables+test_results].copy()\n",
    "COVID_all_variables.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create dataset for my variables"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Correlation matrix for all vaiables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "# corr_matrix_all_variables = COVID_all_variables.corr()\n",
    "# fig, ax = plt.subplots(figsize=(30,25))\n",
    "# sns.set(font_scale=1.5)\n",
    "# sns.heatmap(corr_matrix_all_variables, annot=True, fmt='.2f' , cmap=plt.get_cmap('coolwarm'), cbar=False, ax=ax)\n",
    "# ax.set_yticklabels(ax.get_yticklabels(), rotation=\"horizontal\")\n",
    "# plt.savefig('corr_matrix_all_variables.pdf', bbox_inches='tight', pad_inches=0.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
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l9WNG/kXhzTrLaCwd/Ow8YIy+e2eMdq77Xp0GjFFI2JW7znFtcX2hKqUlH9SKhd+pY4+BGv/Xt0rK69QN13ef/Vtb1i5R935DL7uNh558VQFBITKZzJr+yetKT026ZN1WHXqUW75g1qcyWzzUo9/w33QeqB4GdTLJyyJ9tKBQx085y3YctOvxW8wa3s2kqT9W/IRmp+ZGNahj1MLNRdoU77xZ2ba/SHfHSH3bOEPTnPNjwS0jDGrRwKitiUWat7H0xmbHIbv+dItZQ7uZ9NXPPP1bXZ04tl9xq79Rs/aDdcsfStvH2sENtGLWa4qPXaDoLpdvH5fPelV+AfV191PT5OHpbB8jW/XTtH+P0oaF7+rGe0vbx9CI1vrjvzbIxy9IeblZ+uC5nlV3crjmko4k68f5C9SnVw/98/lnS8rr1aur9z76VCtXr9HA/jGX/L63l5fef+etMuUjht6k0Q89ou9nz1XH9u1Kyu+58/YydUfePEL//eAjzVuwSAmJ+9Uyiv5XTbO8xQ3KO+yc5dkvbp5MvpWbdVXMYDar9Tt/V17KMW3oP1pFZ52z+TKXrFafTbPV4h8TtGv8P0rqNxx3pwK6ttOep15V0nvfSJJSPvtenWb8V82efUxHv5ytvOS0K3R2uF6M7OslH0+D/ufrXB3NcPZ7Nu2x6u8P+eueQd566bMzFW4j+Xihnnk3R7l5DtXyNujNCbUvWddokAZ29lTy8UL9d+ZZFQ/zrtlhVZFD6t7KQw3qmkqOBdVPZtp+bVv5jVp0HKxRj13QB6vTQL/MeE17ty5Q626X74P9/J1zjOL+P5eOUTRp3U9f/GuU1s5/V0PvL+2D9RzyaJltdBnwgJZ++7JiV03XsaRdCmvcrkwd1Ax/HNtYvrXMGjdpmw4cdt7oLV5+XF+/11VP/7G57hu/pcJtfDMrpUzZD/PTlJ1j06jh4Ypu7qd9+51/C01G6c5bGijhwBlN+vtOOc7/Eftx8TEVFTl004BQNWtcq+RYUL3dFuMtH0+DJn9xuqRd2ri7QP/8Q23dO7iW/vlJToXbOHK8UH/+31MlbeSUiZde+aV9c4vaNvXQ6rh8TVtSugrDxt1W/fMPtXX3jbX0zncVt8s1De8grQJvvPGGZsyYUeZfw4YNr+h+7rzzTs2YMeOKbvNqqK7Hfb3at3W+5HCoy8CxLuXt+twli4e39m7+6bLfT9m/Rbk5GWrb646SjqEkhUZEK6JFN8VvW6iiotKnTiJadHMJryTJYDQqquNNkpyBGmoOri9Upc1rF8vhcGjQiNEu5X1vHCUPTy9tWr2gwm0Eh9SXyfTbn/favzdW6alJ6th9gGr5XXqwBdWbxSxFRRiUlO4oCUcl55K3sfvtqlPboPDgip/8btvYIKvNoW0XLae7YZ9dZpNBbSJLu9aN6zm3F3fA9QnMU7lScoZDTesbVbuWUE0lbHO2j536u7aPbXvdJbOHt/ZtuXz7eHT/Fp0tbh89Sy+Eug2i1aB5NyXEuraPHl6+8vELurIngevWitVr5HA4NOoW1wHeYTcNlpenp35Zseo3bTegdm15eFiUm1u5QbXQkBBJ0plK1kf1UhyO/lZB/brKKzxUKf83qyQclaTTO+J1ctVm1b9zmAzm0j5a2D0jVHj2nJI/nemyncP//VJGDw/Vv3PY7zoeXH88LFK7ZhYlphS6BJIFNmndrgKFBpnUqF7Fq04U2FTpGS0mk2SxSDlnHbr4Gzm5zv5bgbVmzo5xF/u2OPtgXS8ao+hwfoxiz6YKxigSnWMU7XuXHaNo2KKb4re69sEuxT/I+UqX/HMVBxionrw8jerdrY7idme7BJJ5+XbNW3pMDRv4KLp52ZWrKut4hnM5IT/f0rbSZDbK08Ook6esJeFosRNZztnv+fnuuQxqTeNhkdo391Bictk2cu2OAtULNimyfiXaSGvl28ioRhZJ0vpdrktZncixa39KoaIjLQr0d7+4kBmkVSAqKkrR0dFVvp969eqpXr16Vb6fK626Hvf16viR3TIYjKrXyPWJNbPFUyENWur4kV2X/36S8/OwJh3LfBYW2UHJCRt1Kj1JdcKaX3Y7Z7KdSzzU8gv+NYeP6xzXF6pS0oE9MhiNimzexqXc4uGpiMgoJR3YU+XHsHbZXElSn0G3Vfm+cO2EBhhkMRmUkln2ZjLlhPNmIryOQaknL31jYZBUP8igY1kOFV60mdQTDtntDpeQ1XT+vsJWWHabtvOTVcPrGJRzlkG66uhy7WPd8JZKT758+1j8ef3Isu1j/cgOSkncqFMZSapT//LtI2qmhMT9MhqNirpo1qaHh4eaNGmsxP0HKrWdoqIi5eaeVZG9SJmZJ/T9nLnKy8tXty6dyq1/7lyebDabzuWd0+69+zTjhzny9/dTdBTXIcoK6OJ8LcGpjXFlPsvetF11BvZUrRaRyt17QDIYVLtjK+XE7ZW9wHV505wtO+UoKirZHmqO8BCTLGaDDqeVna1ZXBZZ36Qjx6/cbE5boXQgpUitG5s1uJun4hJtKrJLLSLM6tfBU5v2WJWZTbhQnR073werH1lOH6xBSx2rYIyi+PPw8sYoGnfQkYSNykpPUshFYxQF+bkqKrTKmndWRw9u08aln8q7VoDCGrf/nWeE61XTSF95ehi1J/50mc/2JDhn2V04+7Mi3t4meVgMquVtVttW/hp9e4SyT9u0N7F0+1arXTv25Kh7pyCNvj1CK9dnqqjIoY5tA3TbsDAtXpGuo8fyrswJ4ppqEGKWxWzQodSyK1kdTnOWRdY3K+nYlWsjzefzVms5z4BYz49bNK5v0qnT7tVOEpBeA1lZWZoyZYpWrFihnJwchYWFadSoUXrkkUdkMpU+GTB9+nR9++23SklJkdFoVL169TRy5Eg9+qhzeYdLLVU7ZswYRUdH6+OPP9axY8fUqFEjTZo0SQMGDHA5jo0bN+rdd9/V7t27JUlt27bVE088oW7dupXUKd7HnDlz9M4772jLli3y8PDQkCFD9Ne//lW1apWd+jB79uzL7rsySwMX/zdas2aNTp48KT8/PzVt2lTPPPOM2ren83Gh3JwMefsGymwpO4XeLyBUaYfiVFRolclc/hT73JwMZ93aZdd69w2oK0k6k51+2QArNztdO9bOUO06EQpv1vm3nAauU1xfqErZWZny9QuQpZzrKyC4rg4m7FChzSazxVIl+887l6tt639WndBwtWzbreIvoNryO79q4JlzZT87c87hUudSvDwlD7OhpP6FiuzSuQLXbWSef5i8cX2j0i8YiLOYnMGoJNX2MUhl5jegOrhc++gbEKq0w5VrH30Dymkfazvbx9zsdAJSN3UyK0v+/n7yKKf9qxMcpL374mWz2WSpoH1MTjmqRydMLPm9Vi0f3XPn7br3rjvKrf/mO//VmvUbSn5vGdVCT4x/VL6+vuXWh3vzCnP+rSpISy/zWX5axvk6ocrde0CWwNoy+XgrP7VsXbvVJuvJbHmF163aA8ZVF+DrfFosO7fsQGtxWXGdK+n/FpzVg8N8dFuMt26Lcb5zzO5waPGGAs1bV/H7AnF9y82+/BhFagVjFGeyL90H8wso7YNdHJAu/PJ5JcQtKfk9rHF7Db7nH/Ly8f/N54LrW51g5zWUebKgzGcnzpfVCfas9PaenxilAb1DSn7fE39aUz7cr9yzrgHYy2/u04uTWmr8g000/sEmkiS73aGvZibr02lJv/Y0cJ2q7eccEzhVXht5pmrayGMnnNday0ZmpWaWXncWs9S4vjMmDPI3Sap4Fn1NQkBaBYqKilRY6Jr+GwwGmUwm5eXl6YEHHlB6eromTpyoxo0ba+3atXrnnXeUkpKiyZMnS5Lmz5+v1157TY899pi6deumoqIiJSUlKSMjo8L9L1u2TDt27NDEiRPl4+OjTz/9VBMmTNDixYsVEREhSdqwYYPGjRun9u3b64033pAkff7553rooYf02WefqUcP1/e0TZgwQTfffLPGjh2rHTt26P3339exY8f08ccf/+p9V8Yzzzyj5ORkTZo0SeHh4crOztaOHTuUnZ1d6W24C5s175IdP5PZ83yd/EvWKbQ6nzwyldO5NFs8z9e59E2EzZqnuR9PkK0gT6PGfyiTqWqCDFwbXF+oStaC/HJvbCWVhKZWa36VBaSb1yyWtSBfvQfeKoOh4uVVUX1Zzvd4C+1lw8jC8/cFlgpWryn+vPASD3AW2iWLufQ62nHIrn5tjRrQ3ihboUMHjznk42nQgPZG+Xi6Hheqn0Lb72sfbcXtYzmfV6Z9RM1WUFBwyfDT43z7eLk6xerVC9Ubr70sm82mtGPHtWzFKp09d05Wm03eprJ/9B64726NGDZE2Tk52rFzlw4lHdHp0+73HiJUjsnHGTwVXTQjVJKK8gvO1/Fy+V+7tWxdSbLnF8h4fnuoOYr7ObZyXvNePGTmYb7yffDCIikz267sM1btOewc5O3QwqJhvbxkK3Jo8cayYQeqD5s1T+ZL9cEslR+jKG8bF37/Yr1HPK6O/e7RudwsHUnYpMzUBOWdZYyyJvPydIZTNlvZe0ir1e5SpzI+//aIflyUpoDaFnVqG6Cmkb7y9y/bl7MV2pV2PE+LlhVoU2yWHA6pf68QPXhPI1ltdn01M/k3nhGuJ8XtX2HRpVec8rBc2TZy026rhvXy1s19fVRgk/Yl2eTrbdDNfb3l62M4v88rustqgWGZKnD77beXKQsICNCmTZs0Z84cHThwQB9++GHJrMo+ffrIbrfryy+/1MMPP6ymTZsqNjZWLVq00MSJpU/89unTp1L7t9ls+uKLL+Tj45zG0Lp1a/Xt21cLFy7UY489JkmaMmWK6tSpoy+++EKens4OQExMjAYNGqS33367zDtChw8frkmTJkmSevfuLbPZrLfeektxcXHq2LHjr9p3ZcTGxuqpp57SyJEjS8puvPHGSn/fnVg8vHXuzMlyPysqLDhfx+uS3zd7nL+xtZW9WS20FZyvU/73C20FmvPh4zp+ZLeGjnldDZp1+VXHjusf1xeqkoenl87kZJX7me38NeNxmevr91q3bK6MRpN6Dby1yvaBq8tgkGpd9BCvraj0BsNsLDtjs3iZGVsFK9cUf26+RJBqNroup5tvlb78uVCj+ph1S8/SLnfScbvW7bErpp1JBe71YGaNYrZ4K6/gt7ePluL2sfDXt4+o+Tw9PZWXU/47zazn28fie7jL8fbyUqcOpavvDLnxBo2f+Ge9nPa6Xn/1pTL1G0dGqvH5nwfG9NP8RUv0wkuv6q3XJ6tNq6p/hQyql6Jz5x/08CwnZPDyPF8n3+V/jR7lBxZGL0/Zz7FkYHVlMEh+Pq6DuFabo6T/Vd4DYcWvp7WW8yqC38Nilp65z1cp6UX6bH7p0iFb421yjJBu7u2luASb0k+51/KBNYnFw1tnLzVGYav8GEVhOX2wy32/bniUFO78uVXXEYpb/Z1mTn1Eo//8jRqw0lW1ZjRKARcFlQVWu/ILnH8nLOWEVB4e45UGcQAAIABJREFUzmC0uE5lHDpyVoeOOH/+ZXWmbh1SX2/+s60mPLddu/Y5l9n19DTqw393VMLBXL30n30l3122JlMv2aM17r5IrViXqZRU2szqotw2srC0/TObyl5fxe2mtZxw/vc4V+DQ29+d0UMjaumBoaWrgiYm27RkY76G9/ZWXoH7rXBFQFoF3nzzTUVGRrqUFT/du2nTJvn5+ZVZ7nbkyJH68ssvtXnzZjVt2lTt2rXT9OnT9Y9//EODBw9W+/bt5edXuRc/9+jRoySglKQ6deooODhYqampkqRz585p165deuCBB1xurL28vDRkyBBNmzZNeXl58vYufYJz+PDhLvsYPny43nrrLW3ZssUlIK1o35XVrl07ffLJJyoqKlLPnj3VokULl+WHUcq3dl2dPHZAhTZrmZlYZ7LT5e0beMkn54q/L0lnctIVXL+py2e555ce8Stn6ZFCW4HmfPQnHUlYryGjX1Pr7gQMNRHXF6pSQFCIjh09JJvNWmaZ3eyTGfL1D6iy2aNHj+xX0oE9atu5rwKDWdKtpqjtI0263fWaiTtg19ZE541recvoFt+slLf87oXyC5w3MeVtw2SUfDylIxetHJiRLX04v1BBfpKft0Fn8hzKOiPd2Ml5Q30ix/1uPmoK39p1lXW8/PYx91e0j7nZ6Qqud1H7eJnld+EegoOClJxyVFabrcwyuydOZqm2v3+Fs0fL4+3trT69emjGrNlKO3ZMYfXrX7b+oAH9NfWDjzR/0WICUpRRvIyuZ1iocuMPuXxWvPxu/vnld22nclR0Lk9e4WX/rhk9LPIIDlDW6i1VfMSoKoF+Rk1+zHWZ0Q27rVqzwxk2lbdE4OWW3/09OkVZFBpk0o9rys4AjE20qUu0h5o2MCv9VPmzmXH98w2oqxO/Y4ziwmV061w0RnG55Xcv1qbHrVr67cuKW/MdAWk1V7eOp2Z95rqS4sJlx/XjomOSpJByltEtXlr3RDnL71bW4hXpevqPzXXr0LCSgHRArxBFhPvow68Ol6m/Yl2mBvWrq3atahOQViNB/kb9a3yAS9n6XQVaE+e8dgLLayP9qqaNlKS0zCJN/vy0QgKMCvAzKvuMXZnZdo3q78yBjp+8cu88rS4ISKtAs2bNFB1d/g1kTk6O6tSpU6Y8JMS5BnnxErIjR46UzWbTrFmzNGvWLBkMBnXu3Fl//vOfK3wHZ0BAQJkyDw8PWc8vZ3P69Gk5HI6SfV6obt26stvtOn36tEtAevExF/9+6tSpX7Xvynr77bf1/vvv66uvvtIbb7yhgIAADRs2TJMmTZK/P+v7X6heozZK2rdWx4/sdJlhV2grUObR+Apn3dWLbCtJSjsUp8iWvVw+S0vaLg8vXwWGRrqUF9qsmvvR40rat0433feq2vYq/z1GqP64vlCVIpu11t7tG5S0f7eat+pUUm6zFiglKcGl7Epb+8scSVKfQbdV2T5w9eXmOWdtXujMOYdyzkq2IociQso+nRlx/n2gqScvH1Y6JB3Lcqh+oEEmo/O9o8XC6xhkNBqUdrL8G5isM1LWmdLtNw83Kt/qUHImAWl1Va9RGx2JL799zEiNV4Oml28fQxs628djSXFqdFH7eKy4fawbecWPG9VDVIvm2ha3XQkJiWrbpnVJudVq1aFDh13Kfq2C88uhnjmTK10+H5Wt0Ca73e6sC1wke+suSVJgj446uXyDy2cB3TvIlnNGZxOTnAUOh3Li9sq/Q7SMHhbZraVLKNTu2k4Gk0nZ23ZfrUPHFXb6rF3/O9P170R2rl2nTttlK3SocVjZh92Ly44cv7IDscXBa3lvzzCeLzNe+dee4iqq36iNDu9dq2NJOxXR/KI+2NF4l7Lyv+/sg6UeilNk9EVjFIe3y9PLV0EXjVGUp8hmlcNhV/7Z8ld8QPWRdcqqp17c4VJ2Isuq9Mx8FVjtat2y7Dh06yjnJKb4A7/9VQQeZqNMJoP8fUvjmeL3npqMZf+IFZeVN+MQ16+cXLve/vZ0mbKs821kk/Cy8VzjMGdZ0rFy1qi/QjKzncFosTZNLMrLt+tgatXt83pFt+AqCwgI0IkTJ8qUZ2Zmlnxe7M4779SMGTO0bds2vffee8rOztbDDz+snEsst1RZ/v7+MhgMJfu8UEZGhoxGY5kQ8uJjLv49MDDwdx3LpQQFBenFF1/UypUrtXLlSo0fP16zZs3Sa6+9ViX7q85adh4mGQzauvxLl/Kda2fKZs1TdNebS8pyczJ08vjBkvdeSVJE866qVTtEu9bPkjX/bEl5xtF4pSRuVlSnIS7vfXSGV3/S4X1rNfjel9Wu951VeHa41ri+UJW69B4sg8GgX+ZPcylf8/NsWQvy1b3fsJKy7KxMHTt6WAUFv/9JSZvNqk2rF8k/IFjtuvT93dvD9aPQLh065nD5l5njXMImMcWhyFCDQi/ouniYpU7NjTpx2qHUE6VhpdEg1fGXatdy3f7uww55WAzq0sK1C90z2qgiu0O7j1T8hGf3lkaFBhq0YZ+93HdyoXpo0cnZPsaudG0fd62fqUJrnlpe1D5mXdQ+NmjeVbX8z7ePBaXtY+bReB3dv1ktOg7hvdturH/f3jIYDJr90zyX8oVLliq/oEAD+/crKTuZlaXklKPKzy+dwZCdkyO7vezfo6xTp7R63Tp5e3upUcOGLuXlmfvTfElSdFSL33U+qP4864WoVlQTGb1Ll53MWr1F+WkZinj4DplqlS6v4NcuSsEx3XTsh8VyFJY2dGkz5stcy0cNH7nbZduNnxwru82mY7MWVf2JoEoUFknxRwpd/h0/aVeBTdp50KYWEWaFh5T2nTwtUu+2nkrPKlLSsdKA1GiUQoOMCvT77YP/x87PfOnRuuwMwh5tnGVHjrnf7JiapGUXZx9sy0VjFNvPj1G06lbBGEWLrvKtHaId61zHKNKPxis5cbOiOrv2wXJzyo6dStLWFV9LksIaX34SC65/VptDW3dku/xLSjmnvHy71m8+qY5tAtQssvTG0NvLqJsH11dK6jntTSwNSE0mgxo28FZoiOuM06CA8vv0d9zsXLN5T0JpeJaU4lzWaMjAsrOYh97gLNu3n/fDVyfltZHHitvIAza1aGhWg7qlDxJ5WqQ+7S/TRvpf+ThvQGdPhdc165etBbK64WuAmEF6lfXo0UOLFi3SihUrXJbZ/emnn2QwGNS9e/cy3/H29lb//v116tQpPfvss0pNTVXt2rV/8zH4+Pioffv2WrJkif7yl7+ULLNbUFCgpUuXqn379i6zRyVpwYIFatmypcvvktS1a9fffByVVb9+fT344INatmyZ4uPjq3x/1U1IeJQ69hutuFXfaO5HE9SkTYxOHj+o2BVfK6J5N7W6YIBu9Y9TtGfjHN391Fdq2MJ5rZlMFt1w5wv66bNJ+nbKaLXrfaes+We1dfkX8vYLUu8RT7rsb8EXf9HhvWvUqGUvmS1e2rPpxzLHU7dBS6Fm4PpCVWrQqLn6D7lLKxbN0Adv/FltOvXW8aOHtWzhd2rRurO69R1aUnfOtKnasGKe/vzKJ4pqU/pUcOKebdq/N1aSdOTAXknSioXfyaeW84nO4Xc+Uma/2zet0Nkz2bpp5IMymegKuYtf4orUuL5ZYwaZtWGf84akc3Oj/HykactdB8r8faQnRlp0+LhdXywt/Wzbfrs6NDXopi5GBdSSMnMcah5uVKtGRq3aWaTsiyZZjR5o0qlcZ0grh9Q0zKDohkYlHLVr9U7efVWdhYRFqUPf0dq++hv99MkENW4do6zjBxW36ms1aNZN0Z1L28e1P03R3s1zdOeTXymieWn7OOCOFzT/80ma8c5ote3pbB9jV34hb98g9Rz2ZJl9blz8viSp0OpcNvBEWkJJWYNmXdWgWdX3y3F1NI6M1C3Dh+rH+Qv10uTX1a1LZyWnpGjuvAVq16a1BsaUBqSfffm1fl62Qm/+61W1b+ecFbN85SrN/nGeevfsoXqhoTKbzUpNTdPS5SuUm5urp594XF5epYN3jzz+pNq0ilazpk1VJzhIOafPKDZuu+J27FTjyEYadestV/2/Aape+Ohb5d0wTJLkERIko4dFzZ4bL0nKS05T6rTSfnjU5KcVMWaUNtzwgLJWb5YkOQoLtefpyeo0/W31XDlNKZ99L7NfLTWe+KAKMrOU+PJ/XfaX/On3ajD2dkX/51l5NwpXbvxB1R0So3q3Ddb+ye8rL+noVTpzXE0/rs5Xy4ZmPXmnr5ZtLVC+1aE+7TwU4GfQez+4vt8gwNeol8b5KzG5UG/PcO1UDe3h/Jvlcf5dgOEhxpKy/UcLdeCos7+262ChDqcVqm1Ti56+x1dxiVYZDAZ1aG5R8wiztsVblZJBQFqd1Q2PUqeY0Ypd+Y1mfzhBTdvE6MTxg9q23DlG0fqCMYqVc6Zo98Y5unfSV2oUVdoHG3TXC5r76SR989Zodeh9pwryz2rLsi/k4xekvheNUXz2ygg1aNZZoQ1byS8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GUdmtadRXOadt90099yyUu9/1Pfzp5uGhZu//UTkJ5/RT74dUkGV7uC9l+QZ13zZXjf70nA6M/1NJ/VpPjFZQh5Y69OJfFPfxTElSwtffq+23H6rBq8/o7LS5yolPukG9w51k+1LbHDby+R8UVhQHa9R2uL6fNFSb572lMa+UP4cd3TFHKWcPqOuwP6h5N9sc1qTTGK2YMUF7136hmPaj5H9VHKxYnjlLm358S027PKgzR1w7H8M7SG8gs9msDz+89V+Ee/fu1eTJk5WRUTm2OIqIiNC3336r3r173+5LqRL2b12swsJCdR0w1q68fe/R8jR6a++WBdc8//TRHbpyOVntet1XkhyVpKjaTVS3SUcd2LZUBfm2VQ85Wek6H39UdWLalyRHi7XtPkKStHvj3BvRLdxh8szZiju8RlH1O5YkRyXJ0+Srpp3uU1pKnJITDpTbzvE9i+Th6a2mncbYlbfsMU7Wgjyd3Le0pCwgpIbDDw9Jqtmoq0w+gbp0/sT/0CPcSfIs2Uo4ukaRdTuWJEcl2/iKaXefMi7G6eLZ8sfXqf2L5eHprUbtR9uVN+s6VtaCPMUeKB1feZZsHf5phmo1uUvV63VSYWGh8swE4qqSlZu2qbCwUPcP7mdXPuzunvIyGbV8w9YKt/X57LkqKCjQMw+MLLPOik3b5GUyatjdPe3K7x/cT/n5BVq9ufwAMyonk9FNHVv56eDx7JLkqCTlmgu1YlOaakSa1LDOtbcTvJbkou1y/XxKX2PQvJGPQoM9tWJTWklyVJJOnzXr4PFs9WgfIHd+6VUJXiaDunUM1d6D6XYJo5xcqxatPK9a0T5q0tDvF7d/Idk2Zv39yn92emg/24PAC6vo6j5XZBtfYdpzMM1hfC1ccU61avioSUP/X9z+eSfjy93DIJPRoNTLFocFuxcvWSRJublVcwW8q1i7YaMKCws1athQu/JBA/rLy2TSqrXrf1G7QYGBMho9lZnp/J49OSVFU2fO0tgHf6UIHkqr8vLM2Tp9aI2iG3QsSY5KkvHqGEV8BWIUuxfJw+itZp3tYxStexXFKPZWPEaRSoyiSihOjv5SIT07yCu6mhL+M6ckOSpJGfuOKnX9dlUfPUhuHqXfi1G/GqL8rGzFf/WdXTunP5wmg9Go6qMH/U/XgztTniVbZ46sUfV6HUuSo5ItDta4w31KvxinlArEwU7utcVZG3e0n8NadLfNYaeuirNebcfy91VozVeHAS/+bx2pAvjZfAP16NFD8+bN06lTp273pZTJarUqL+/2vpPIaDSqdevWCgmputtO3EpnYw/Kzc2gGvXsn6D0NJpUvXZjnT198JrnJxYdr9WgtcOxmvVbyZyTqYvn4yRJ+XmWorYdg3yeJm9JUsKpfdfdB9z5Us8dU0G+RZG1HcdJtdqtJKncBGmh1aqLiYcVFt1EHp727/6rVqul3NwMFUqymnOuKM+cLR//0OvoAe5kl8/bxldErVYOx8KLylISyx9fqUmHFRLlOL7Ca9jG18XE0vnwQtwu5ZmzFBbVTFsX/U0z3mqvGW+11zdvd9XOFf+WtSD/BvQMt9ORk3EyGNzUtGFdu3KT0VMN69TSkVOnK9TOoROxmrNsjV547AH5+ng7rWO1WnUsNl6N6taSyehpd6xpw7oyGNx0+GTFPg+VT50aXjJ6GnQ0Nsfh2LHTtrKGdZyPHWe8TQYF+LqrWpin+nQK0L0DQpWRma/jp0vbL27vaKzjdrPHYnPk6+2u6GrG6+0K7kD16/jKZDTo4DHHh2EPHbOtyGt8HQksb293Bfp7qHo1Lw3oHaEHR9VQWkaeDh+/cs3zqkeY1KZFoPYdSldCouNYR+VUv46fTEaDDjl5n2zx+LqeBKm3t7sCAzwUVc1LA/pE6KF7axaNr9L2LRar9h1KV6e2IXro3pqKru6lyAiT7ulbTSMHRWnZ2gs6e44xVpkdO35CBoNBMTGN7MqNRqPq1aur4ydOVqidgoICpadn6NLlyzp2/ITe+dck5eTkqmP7tk7rf/TJ56peLVKjhg91ehxVy8UKxCguVCBGkXL2sMKvEaMorw3pqhiFHzEKSEHtW0iSLm/d43AsbdteeQb6y7dRHVuBm5sC2zRVxt4jspotdnXTd+xXYUFBSXuoWi4VzWHVnMxhxbGxlArGWUOdzGERNW1zmLMka3LCfh3aMktdhr4mo9cvf9CyqmCL3Rvoqaee0oEDBzRp0iR9/PHHZdYzm8367LPPtHjxYiUlJSkoKEj9+/fXSy+9JD8/26B0tg1tsZiYGD333HOaMGGCPvroI02ebNsDvm/f0hdGr169WjVq1FBMTIzGjh2rGjVqaObMmUpMTNSUKVPUqVMnXbp0SZMmTdLatWuVnp6uqKgojRo1Sk899ZTc3d3truP3v/+9MjIyNGfOHKWnp6tFixaaOHGiWrRwnKRjY2P19ttva/fu3QoICNA999yjl156SUajsdy+Xe2bb77R7NmzlZCQIIPBoMjISI0YMUJPP/10Bf8iruFKWrJ8/IPl4ekYBAsIrqb4E3uUn2+Rh4fzIFnG5eSSuo7nR5TUqVajofwCw+TjH6yEU/uUZ8m1S5TGHt4mSUpP5YnyqigrwzZOfAMdx4lvgK0sK/2Cw7GrmXPSlZ+X67QNdw+jvHyClFlOG5K0a9WnshbkKaZ92Su5ULlkZ9i28fMJcBwbxWXZGckOx65mzk1XQV6ufAMiHI65exhl8glSdkbp+Eq/aEtWHdoyXQZ3T3UY+IpMPkGK3btI+9d/oeyMC+p537u/uE+4/VIupynQ319GT0+HY+EhQTpw7KTy8vLl6Vn27XB+QYHe/WyaOrZspru7diiz3pWsbJktFoWHBDscM3p6KtDPTymX0n5ZR3DHCw20jaHUy44PIaam2cpCgyr+s+uFcdXVrV3pazOOxubos9nnlZVTuqIqpKi91DTHhzmKy0KDPBV/zuJwHJVLWIjtHv5iquPfsni1XXhIxZPhrz3fSL27lq6sOnQsQ5M+P6XMrGu/AH3Q3ZEyGNyq7LshXVVYqG3spKSaHY5dLCoLCzU5HCvLay/EqE+38JL/PnQ0Q5M+O+Ewvv78ryN6/f8aa/yj9TT+0XqSJKu1UNO/i9dXs+Kutxu4w6ReuqSAAOf3YGGhITp85Kjy8vLk6eT41eITzurp514o+W9fXx/9avS9emDMfQ51123YpG07d+n9f7xTEs9C1ZaVXnaMwi+wYjGK3PJiFL5B5bYhSTtX2mIUjTsQo4DkFWWLSZiTHMdOblJyUZ1qyjx8Up7BgXL38VZuomNdqyVPltQ0eUU7xjhQ+ZXEWZ3EwYrnpKyM8uOstjiY8znM5BOk7J/NYdaCfG344Y+q0bCb6re655defpVCgvQGCggI0NNPP61//OMf2rNnj9q0aeNQp6CgQE8//bQOHTqkp59+Wi1atFBsbKw++OADHT9+XNOnT5fBUPGFvaNHj9aVK1c0bdo0TZ48WeHhth8jERGlk+eyZctUrVo1vfzyy/Lx8VGtWrWUk5OjRx55RBcuXNALL7ygunXratOmTXr//feVkJCgt99+2+5zpk2bpjp16ujPf/6zcnJyNHnyZI0bN07z5s1TrVql20tYLBb9+te/1v33368nn3xS27dv16effio/Pz8991zFX7a8aNEi/fWvf9Uzzzyjjh07qqCgQHFxcUpOvnaA3BXlWXLLTH4WJ03zzGXXybPk2NW1P99kV8fNzU3dBozTyjnva9aHz+vuURPk4x+sUwe3aPWPk2Vw91CeJfd/7hPuPPl5Re88czKO3IvGSXGdsuRdo43idspr49S+Zdq7YYpqxnRX4w5lP2CByiU/zzbHuLs7GV8eJrs6ZbZRNPcYnLRR3E7+VfNT8Xa65px0jXx+gYLCbcG5ei3u0ZKvxunknvlq0fNJBUc0uM7e4E5hNltkLCP5WRywy7VYrpkgnTV/mRLOJevd3137Hia36GlfT48yPs/oKbOFRFVVZTLa3guTl+/4TkZLXmFRnYrf389edFFLN1xWoL+HWsT4qE60lwJ87YO9Jk/DNT7TanddqNy8TLa/ffHf9WpmS9Hf2lTxZMCU/57RvGXnFBTgqbYtAlW/jq8C/a8dFjAYpHv6VlNmVr7Wbr54HVePO52XqWguyXMylxSNr+I6FTFl9hnNX5qkoEBPtW0RpPp1/BQQ4JgEy8u3Kul8jpauNmvb7ksqLJR6dw3Xo7+qLUueVdO/i/+FPcKdwGw2l5n8NBbFHa5Vp1hkZDX9/a9/Vl5enpLOndfqteuVlZ0tS16evK9KgmZmZurTL7/WoAH91LRJ4xvXEdzRKhSjKCc+VXy8zBjFz35DOnNy3zLtWT9FtWK6q0lHYhSQ3It2HSowO/7+K8g1F9Xxsvtfaxm/Fa25ZhnK2MUIlVvxHGZwNod5VHAOKy/O6uEYZ9234WulXzyj/o9Mvu5rrqpIkN5gDz/8sGbMmKH33ntPM2fOdDi+ZMkSbd26VV988YV69bK9lL5Lly6qVq2afvOb32jDhg3X9W7OyMhIRUVFSZKaNGmiGjVqONSxWCyaOnVqyepUybY68+TJk/rss8/Up08fSVL37t1ltVo1bdo0Pf7446pfv35JfYPBoK+++qrkBrZdu3bq16+fvvrqK7311lsl9cxms15++WX169evpG+HDh3SwoULrytBunv3bjVq1EgvvFD6tGD37t0rfL4r8TR6yZx7yemxki1xTWW/98rT6G1X1/58s10dSeo55CnlWXK0aelUffqmbX9zo5ePBj3we62c84Gs1ms/fY47m9VaoNxM+/Hk7uklD0/bGCrId3KDVzROiuuUxfMabRS3c602zhxZr5Xf/Fbh0c004JH3y31ROe48VmuBcrPsx5eHp5c8PIt+QBQ4GV/5xePr2j8KPIpWtFudtFHcjsdVq97di8ZaeM1WJcnRYg3aDNf509t1/vQOEqSVmMlkVHa68y0jLUWvG/Aylr3qKuHcBf1nzkI9du8QRVcLL7OeJHmZih5Iyne+NbPFkifTNT4LlYPBTQrwt09EWSyFMltsiQVPD8fvJaOnraw4kVURZ5LMOpNk+/cNOzI0sEeQ3ni+pib+64yOnLI9LGIuSpY5/0xD0Wc6Jjxw5zIYpKCfJZLMFqtyzbZ76+K/69WKE+9mc8Xvv2PPZEtnbFszr96YomEDIvXPPzXXhNf26+MK8iYAACAASURBVICTbVYlqWObYFULM2nesnPXNZZx5yh7fBXNJZ5O5pKi8VVcpyJiz2Qp9ozt31dtSNHwgdX1rzda6LmJe3XgiG18mUwGffaPNjp2KlNv/vNIybmrN6boTWsTPfFgHa3dnMJWzpWYyWRSTnq602OWoriDyVT+ymRvLy+1bV36Co6B/fpq/Asv689J7+rdv7xZUv75f6bKWmjVE4+O/d8uHHckq7VAOZnOfkNWIEbh5PVQdu0Yy4lR/Ow35M/FHV6vFTN/q4gazTRwHDEK2BRkFz0AbnKS+PIyFdXJtftfQxm/FQ1eJlmz+T6szJzGwTxK5zCrszksv4JzWHlx1nz7OGv6xTPaveoTtek7XgGhNSveiSqOBOkNZjKZNGHCBL322mtat26dQ7Jz/fr1CgoKUrdu3ZR/VRCtW7ducnd31/bt268rQVoRnTt3tkuOStK2bdvk7+9fkhwtNmLECE2bNk3bt2+3S5D269fP7um+6tWrq02bNtq+fbvd+e7u7iWJ32IxMTH66aefruuaW7ZsqW+++UZ/+tOf1L9/f7Vq1Ur+/hV/94kr8Q+KUHLiKeXnWRxWgWZcvmDbfreMJ0mkq7fRvaCI6Pp2x0q33y1dkWwwGNTvvhfVa+jTOp9wXCosVGStxpIKNX/qm6pZ3/Edgqg8MtPOaebf7rYri2k/Qs063y/J+RY1xVs+ONuW5mom70B5eHo5baMg36Lc7DRFBTrfwjL+6EYtmzZBIZENNfTpr9kjv5LKSj+v7/9lP74atBlR8jL5bCfbhxSX+TjZOvdqJq9AuXt6lWxTcrWCfIvM2WnyqVs6voq3IPHxC3Oo7+NvS4ZZcpwHilE5hAcHKe5skix5eQ5bvKVcSlNQgN81V49+NO07Bfj5qlfHtko4Vzo2CwqsyssvUMK5C/L2MiksOEj+vj4yGY1KuXTZoR1LXp7SMzPVOqSRwzFULmEhnvr6b/YPTazekqalG23bJ4cGO66ECQ2ylTnbCrei1m5N17MPRuqensElCdJLJdvoeujsefsfxKEl2+86bvmLO1dEmEnff9nRrmzp6guav/ycpNKtUK9WvP1uyqVfvkJ9+dpkvfRMAw0fGFlmgnTw3ZGSxPa6lVhEmElzvu5sV7Zk9XnNX2obX+FOttEt3lr3opPtdytq2doLeunZhhp+T1RJgrRP13DVjPbRZ9Md3829dnOK7u4ZoZZNA0mQVmKhISGKTzjr9B7sYuolBQYElLt61Blvb29179pZ386Zq6Rz5xRVvbpOnDyl5StXa+yDv1JGxhVlZNgejktLsyVoL12+rMSkcwoPD3O65S/ufJlp5zT9r/a/IRt3GKFmXcqOURS/uqe8GIVXeTGKrDRF1XceozhzZKOWTp2g0MiGGvYMMQqUKt5G1xRVTZlHY+2OFW+/m1u0/W7e5XQVZOfIK9pxrBqMnjKGBunShh03+YpxM2WlndPsv9vPYY3ajVCTTkVzmJM4WPGc5Gzr3KuZvIvjYM7nMHN2mnzqlc5hWxf/XSafQNVtdrfSL54pKS8sKJC1wKL0i2fkafQuN/5W1ZAgvQlGjhypKVOm6L333lPPnj3tjqWmpiotLU3NmjVzeu7ly46Btf9V8ba7V0tPT1dYmGNQuLhuWpr9e7Kc1Q0LC9OJEyfsynx8fEreNVrMaDTKcp3byo0YMUJ5eXmaM2eO5syZIzc3N7Vr104vv/yyWrUiAXe1GvWa6+TBzTobu191YtqXlOdZzDp35qjqNG5/jbOl6LrNJUnxJ/eqQfOudscSTu2TydtPYZF1HM4zmnxUq0Hpi6QPbl+uwsJCNWrV06EuKg8f/3ANffo/dmW+ARHyD64udw+jzp/Z63DOhTP7JEkRNZpfs203g0Fh0U11MfGICvItdltAXIjfr8JCq8KdtBF/bKOWTn1OQRH1NOyZ/8jLJ/CXdA13AG+/MA147Gu7Mp+ACPkF2sZXcvw+h3NSisrCossfX6FRTXUpyXF8pZy1ja+w6NLv3vAaLSVJWRmOwd6sdFuZl29IBXuGO1GTBnW0bd8hHT5xWq2bliYnzZY8nYiLV+sm105Ynr+YqouX0vTg//3R6fExE15T17Yt9d5rL8hgMCimXi0dPx3vEAw8fOK0rNZCNalf54b0C7fP5fR8vf7vM3Zll9LzlXIpT5Y8qxrXc1zpHlPXVnYy7pcH+j083eRucJPfVdvsnihqr3E9H+07mm3/mfW8lZVToMQLbOtcmVy6bNGLfzpgV5Z6yaILKbkyW6xqHhPgcE6zGNsDpMdOZv7iz/X0NMjd3U0B/s4TB0GBnurWIUQnT2f+T5+D2+vSZYtefN3+PuviVeOrWeOyx9fRk853Y6gIo0fR+PIrDT0VJ/vdDY4rrYrLPNxZhVWZxTRqqF179urYseNq0bz0/ttisSg29rRd2fUyF21ZeeVKplRdSk5JUWFhoabNmq1ps2Y71P/48y8lSZP//S/FNGRnmMrIxz9cw591jFH4VSRGUbP835DhNZoq5RoxCmdxjjNHN2rJlOcUHFFPw58lRgF7aTtt93PBndsodY39gqGgTq2Vl35FWcfjbAWFhUrfc1gBrZvIYPSU1VL6gGNgh5Zyc3dX2q6Dt+rScRN4+4dr0JNO5rAg2xx2wckcVhwbcxYjvVpxnDXVyRyWnOAYZ828nKTsjGR9P2mI0/a+/ecA1WrcSwMf+7zC/asKSJDeBAaDQf/3f/+nX//611qwYIHdseDgYIWFhemzzz5zem5wcLCk0u1Gfp5Y/CUJVGdbPAQFBengQccJNiUlpeT41S5edHzXzMWLFx3q3UijR4/W6NGjlZOTo23btmnSpEl6/PHHtWbNGgUGcvNRrEWnQVq/8AttWT7dLkG6c933yrPkqHWX0kkvIy1Z5uxMBYZWl9FkC9jVbdxB/kHh2rV+jroNHCeTl68k6Vz8UZ0+sl1te46Uu8e1n7TMvnJZK77/t3z8g9Xxrl/dhF7iVvHwNKlmo65Oj9Vp2kexB1bqYtJRhUXZ3u2SZ87S4W1zFBhWWxG1WpbULSjIU0Zqgjw8veQfHFVS3rDNYJ2P261DW79Vy+6PlJTv3zhNBoOHGvzsBeHxxzZp6ZTnFBReR8OfmSIvn5s35+Dm8/A0KbqB8/FVs3EfnTm0Uqnnjiq0eun4OrZrjgJCa5ckNCXJWpCnjEu28eUXVDq+6rUcpOQzu3Vsx3dq2uXhkvJDW6bLzeChus1Lx5d/SA1F1G6r5Pg9uph4qCR5arUW6NjOOXIzeCi6Ybcb2n/cWn27dtS0uUv07eKVdgnSBas2KNds0YCepStpLl5OU2Z2jiLDQuRVdA/23NgxyszKdmj3X1/OlNHoqefH3a/Q4NL7kX7dOmn/0ZOav3KDRg/qW1L+7eKVcnd3V9+uzp8+R+WRl1/okIwstn1/prq08VedGibFnbWttvIyual/9yAlXjDreFzpu1/cDVL1cKPMFqtSLpeuLA0KcFdahuNWqUPvsj2scSy2NMl68Hi2UtPy1L97kOavTlWu2badbp0aJjVv5KPVW9JVwE6olYolr1C79qU5PbZlR6p6dg5T/Tq+OhVne4e2t5dBQ/pFKiExW4ePlyaw3N3dFB3ppVyzVckXS1f+hQR56pKTVcX3DbF9jx465nz16MA+EfL0NGjRSscn01F5WPIKtbOs8bU9VT27hKlBHV+dvGp8De1f3fn4qu4ls9mqCykVGF9DoyXZj6+4BNs8OvCualqzKcWu/j19bSsljpz45UlZ3H69e3TT7O/maO6ChXbJ0CXLVyjXbNZdvUsfqk69dElZWdmKCA+XV9HWk2np6Qrw95fBYL+1+KXLl7Vh82Z5e3updq1akqSYRo30x1d/53AN+w4c1ILFS3TfyOFqEhOjqOqRN6OruAWuGaNo1kex+1fqYuJRhUXbfkNaimMU4bVV7ecxiosJ8jA6xijOnd6tgz99q1Y9SmMUe9fbYhQNWzvGKJb8pyhGMX6KvHyJUbgyU2S4PAL9lROfJGuO7X7/0oYdyk1KVs3H79PpD6aqoOg3pX/LGIX26qiEaXNVeNWukknfLlJIt3aq9dT9ivu49HV9dZ8fJ2tens7NWXprO4UbysPTpBoNnc9htZr0UdzBlUpNOqrQq+KsR3fY4qzhNX8WByuKs/pdNYc1aDVYF+J268i2b9W8W+kcdmDTNLkZPFSvZekc1mnw75zulLZp3lty9zCpy5Dfu9zqUYkE6U3Tt29ftW3bVh9++KG8vEr3eu7Zs6eWLFkig8FQ5ipSybY602Qy6dixY3blq1evdqhbvGLTbK741jedO3fW0qVLtXbtWrttdhcsWCA3Nzd16tTJrv7KlSv129/+tmQblHPnzmnPnj0aNermv4Dc29tbvXv31uXLl/Xqq68qMTGRBOlVIms2Uqe+D2rrqlma9cEENWrVUylJsfpp5UzVbdxBLa9KkK747t/as2menpg4TfWa2Lbwcvfw1OCHX9O3H7+kL//6iNr3vk/mnCxtXj5NvgEh6jtygt3nHdu3XhuX/EcNmnWVX2CY0lKTtHP9HOVmZejhFz+Wr3/wLe0/bp3Og17S2RNbtfCLJ9Sq5zgZTX46vO17ZWVc0OAnPrN7GCMr/YJm/2OQoup10Ihfzygpb9pptI7umKstC/6uK5cSFVytvs4c2aDTB1eq3d3jFRBa+h7l5IQDWjrlN5IK1bjDKJ05utHhmmLaDbupfcat077//ynp1FYtn/KkmnUbJ6PJV8d2zlF2RrL6jf3Z+MpI1tz3ByuybgcNenJ6SXlM+9E6setHbVv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\n",
      "text/plain": [
       "<Figure size 2160x1800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "l = COVID_all_variables[all_variables+test_results]\n",
    "corr_matrix_pos = l.corr()\n",
    "fig, ax = plt.subplots(figsize=(30,25))\n",
    "sns.set(font_scale=1.5)\n",
    "sns.heatmap(corr_matrix_pos, annot=True, fmt='.2f' , cmap=plt.get_cmap('coolwarm'), cbar=False, ax=ax)\n",
    "ax.set_yticklabels(ax.get_yticklabels(), rotation=\"horizontal\")\n",
    "plt.savefig('corr_matrix.pdf', bbox_inches='tight', pad_inches=0.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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8+WM5u1jUqlPJ4y/YlfkZpG+//bZmzZqlTz75RD169NBnn32mRx55RFZr0avLS3P06FFNnjxZsbGxRV6bPHmyxowZU67tldeCBQs0fXr57p5D+dzo3zEc5YejV8qvW6TcgqrrxBezC8JRSTq/fZ8Sojaq5j0DZXIuvNai1v23K+dCmo5/9r3Ddo5+ME1OFotq3jPwqvYHlcfO9Qtks9nUse8oh+Vtut8jF0sVbV/3c6nrR+/fpJSk02rTbVjBBwZJqhkcqvpN22nnxkXKzSk+HMjKTFN2VubVdwKVmouzFFLHpOh4W0E4KklZOdLWg1ZV8zYpyP/yV0hm5Uhp5Si35Av2cBQojYuz1LSOk46esjlMbZuVI23Zn6sAbyfVrlbG+sy4un1JzZBycqUqrlwxbGS7NiyQbDa17+M4nX2bbvfKxVJFO9b/Uur6xw7Yz+utuw0rCEclqUbdUNULaafdm4o/rycnntTKn/6rHoOfkrdfzYrpDCqVLWsWyWaz6bZBDzgs79xrqCyubtr424LLbsMvoKbM5qt7QpFfgL0+0y6cv6rtoHLZkTcm6tTPcUzUtod9TPTH76WPiY7u26SUc6fVprvjmKhWcKjqh7bTzg2Ox86NK75T+oVk9b/vRZmdXZSVmV7imAnGVlCbl4zX2+aP1y9Xm3nj9bbdixmvhxYdr+fXZj9qE5ex7Xd7bXYd4Fib7W8bJhfXKtq6Zn6p6x/eu1nnz51W+x5DHWozqF6oGoZFavv6XwtqLy01WXHH9qtB0zYF4Wi+tt3ulCRtWj23IrqFSuJ6n9eLE71/s86ePKqwNr25874MyvwJPyQkRKGhoZKkjh07KjExUXPnztW2bdvUpk3FXCURFhZWIdvBzYvf8a3Hp6396uZz67cVeS1pwx+q1rOj3JvUU+qeQ5LJJO/WYUretkfWzCyHtsmbdsiWm1uwPSD26C6ZTE6q3aCFw3IXi6tq1m2q2KO7Sl0/Ju/1uo1aFXmtdsOWOrJ3vc7GR6t6UGOH1xZ+86Z++vwVSZJ/9WC17zVCHfo8yFRnKKK6j0kuZpNOnCl6MdiJs/ZAKqiaSbEJpJm4/mr4muTibNLx00WnzzyeV7NBASbFnK34+jSZpCoWyclJ8nY3qUszs1xdTDpwgqk8jSwueqdMJicF1Xc8rzu7uKpG3aaKO7qz1PVj816v07DoeT2oYUsd3bdeCfHRCrz0vD7jn/INqKMOfUZrx2UuroIxHTu8WyaTk4IbOY5DXCyuql2vqY4f2n1N3jcj/YJysrOUkX5Bh/dt09K5X8rd04e7R+Eg5kgpY6LgpgVjnpLEljImqtOwpY7sWa+zp6JVvbb92Hlg+2q5VvFQRtp5ffjaXTp1fJ9MJifVbdxaA0e8pNoNqE/YXW68ftnaPGJ/vU5Za3NHYW1O/ptjbQ4YTm2i0InD9tqs27DoeT0oOEQnjpRem/mvBzcuWpvBjVrq0O4NOnPqmGrUbqScHPt3my6uVYq0tbi6SZKOHdx+Rf1A5XS9z+vF2Rz1oySpbfdh5d19QyrzHaSXatHC/kuOi7NPlXns2DG9/PLL6t27t1q0aKHu3bvrmWee0bFjxwrWmTNnjp566ilJ0qhRoxQSEqKQkBBt2LBBkn361ZdfftnhfU6dOqXx48erS5cuatasmfr166evvvrKoc2GDRsUEhKihQsXatKkSerSpYsiIiL00EMP6ciRIwXtHnzwQS1fvlyxsbEF792zZ89S+zlz5kyNGDFCHTp0UOvWrTVkyBB98803Re6czcrK0ltvvaXOnTurZcuWGj58uHbs2HHFfSpJSkqKXn31VbVv316tW7fWI488oiNHjigkJEQfflg4ndTLL79cbN8+/PBDhYSEXFEfe/bsqTFjxmjVqlW688471aJFC/Xv31+zZ88uaHMlv+PizJ07V0OHDlXLli3Vpk0bjRkzRtHR0WX6GaFiudUKlCRlxsUXeS0j7nRem+qSJBdfb5mrVlFGbNG21qxsZSUkyS0o8BruLW4l55NOq6qnr5xdLEVe8/StrrSUcwUfRouTcu50QdtLefkGOrSRJCdnZzVt3VP97n1RI5+dqsGjX5dbVS8t/Gaifvr81avtDiohz7wZyVPSir6WkmZzaANcb15V7Rd1nE8rGoCeT3NsU9ECvE16daSrxg931ZjBFjUOctKq7TmK2kFAamQppZ3XfaorLfWccks7ryedLmh7Ka+8ZSnnHD9j7tq4UAd2RGnQg6/L6Srv7kPllZx4Wh5ePnIppja9/QKVmnJOOdkVf5fS11P+ppce7a5/PD1Q0ye/qoCadfX0qx8X+9xSGFdpx06vMoyJzueNd7xKGROdv2hMdOZktKy5ufrq3SdUs25TDR/7vvrf/6LiYw7qszdHKz7m4FX2CJXF1dZm/nm9rLV59qS9NqdNyqvNp99Xv/vstfn5RGoThc4nnZF7KbV5oYzHTW+/ot9PeuUtS060f+b09K4md09fHT+4XdlZjtPuHNqzUZKUlHjqyjqCSul6n9cvlZGeql0bF8s3oLYahHUo7+4b0hWPImNi7NN2+vn5SZJOnz4tPz8/vfTSS/Lx8dHZs2f17bff6t5779XChQvl7++vHj166MUXX9SkSZP097//XeHh4ZKkRo0aFfse8fHxGjZsmNzd3TVu3DjVrFlTa9eu1TvvvKOkpCQ999xzDu0nTZqktm3basKECUpJSdGkSZP05JNPauHChTKbzfrHP/6h119/XdHR0Zo8ebIkyWIpWqwXO3HihIYMGaKgoCCZzWbt2LFD77zzjk6fPu3w/uPHj9eiRYv0+OOPq127djp06JCeeeYZpaamXlWfLma1WvXkk09q+/btGjt2rMLDw7VlyxY9/vjjpfbhcsraR0nas2eP3n33XT3xxBPy9/fX999/r1dffVXBwcGKjIws9++4OB988IE++ugj3X///Xr22WeVmpqqqVOnavjw4Zo3b54CAwnYridzVftVUrmZRQ/euRmZeW3cHP60ZhV/oLdmZMqpatGrrmBM2ZkZcnYu/hic/0GitDbZWen2tsW87uziKknKykwvWBbcOELBz0Y4tGvT/R59/Z8/aduan9Sm21AFN+G5ESjkkvcpKaeY+W5z8nIgFx4Pihskvz5zi8kkc3JtDm0q2rlUm774NUtmJ5P8vUxq1dBJbhaTzGbJyiNIDSs7K0PmEs/rrpdtk/+lU3FfJly8fr6MtPNa/N1ERXS7R3Uatb6qfUfllpVV8ufJ/NA0Kytdzi4V+7y7gff8WV373qvU84k6sGuTYo8f0IXUpAp9D9z6skupz3KNiUo9dhaOibIyLshqzVXLTndo2BMTC5bXqheuzyeO1sq5U3X/0+8V2RaMJ+sqx+tZZRivF1ubHe/Q0Mcda/OLt0Zr5bypuv8pahN5dVfCOdslv7ZKPW7mfeYs5vWL15ckk8mkbgNGadH37+ur955Vv2FPy93TVwd3rdOS2VPkZHYuaAtI1/+8fqkd6xYoOytdbbrdzUx5ZVTmr01yc3OVk5Oj9PR0rVmzRt99952qV6+utm3bSpIiIyMVGRnp0L5Hjx7q1KmT5s+fr9GjR8vPz0/169eXZA/MWrUqeqvwxSZPnqyMjAzNmTOnIBTr1KmTsrOz9fnnn+uhhx6Sj0/hPMohISF65513Cv5uNpv13HPPaceOHWrdurUaNWokLy8vWSyWy753vovvdrRarYqMjFRubq6++uorPfvsszKZTDp48KDmz5+vP//5zxo3bpwkqXPnzqpWrZqef/75q+rTxX777Tdt2rRJf//73zVy5MiC9zGbzfrggw+KXaei+pgvKSlJs2bNUvXq9qsYIiMjtWHDBv3yyy+KjIws9+/4UnFxcfrkk0/08MMP669//WvB8jZt2qhfv3768ssv9dJLL11xX1F+uWn2g67ZteiB2ezmmtcmw+FPpxIuPHByc5U1reSDOIzFxdVNF84nFvtaTnZWQZsS17fYw/birrzKybaH95ZipkG5mJOTk7rd/rgO7VqjAztWE5AalMkkubs6LsvOlbLzgh5nJ5Mkx5DU2VzYDriWTCbJ/ZJDYXZOYX2aiwnpnc2mgnbXQnaOdDjOpvx/F1sO5OqpIS4a2dNFXy3hWVFG5WJxU1ZKSef1zII2pa1vb1vyef3i9Zd8/45sNqt6D33hivcZxmCxuCklo/jazM6rN4ul4i/iDApuUvD/bbsM1G9Lf9CUCWM07o0v1bApoT7sXCxuyiyhPss1Jir12FlY384WV2VlpCmiy50ObRuEtpOPf00d2bepfB1ApWVxdVPqVYzXLWUYrxdXm627Fq1Nb/+aOkptIo+Lq5syk4uZ5klSdn5tlXrczPvMWUxtFrf+bYMfU1ZWuqIWTNMHf7tfkuTqVlV3PPBXLfr+A1lzuUIUha73ef1Sm1f/KCcnsyK63l3mfTa6MgekQ4cOdfh7y5Yt9e9//1uurnl36WRlafr06Zo7d65iY2OVllZ4oLp4mtvyiIqKUseOHeXn56ecnMKDTffu3TVt2jRt375d3bt3L1h+6ZSy+VPJxsXFqXXrKxuA7N69Wx999JH++OMPJSQkOEw7m5CQoGrVqmnjRvst9QMGDHBYt1+/fnJ2dvwRl7dPF8t/nzvuuMNh+eDBg68qIC1LH/OFhYUVhKOS5Orqqnr16ik2NvaK3/9ia9euVU5OjgYPHuzw8/H391dYWJg2beID0fWWP42ua63qSt3n+G85f/rdjLzpd7PPJSs3LV1uQUWnAXCyuMji76PE1fwOYeflE6gzsYeVk51V5MqolHPx9ikpSriiSpI8C6bRjVdgrYYOr50vmH738nec+1YLkiSlpZwr1/6j8vCuKo0b6ngF6rZDVm0+YD8fFjeNrmfe1KXFTb8LVCRvd+kv9zom+FsP5mrjPns6X9w0ul55NVvc9LvXQlaOtPuYVd1bOMvPU0pMuS5vi5uMp0+gzsSVcF5PildVD98S7x7NXz+/bcCl5/WkvGnO8qaaOnlst7at+VE9hoxVemqS0vPuyruQF9CmJp9VYvwxefnVLPbqaxiLt1+gTsYcUXZ2VpFpdpMTT8vD07fC7x4tTvtut2vW/ybotyU/EJCigKdPoE6XMCY6X4YxUeF0e/EKDCp+TOR10ZjI27eGzpw8Ik+farqUp0+A4qL3XnFfULlcbW3mn9fPlzJeL7Y2vYuvzZPUJvJ4+QQoPqbk2nQv43EzOfG0ql963EzMn3638HtNJycnDbj3WfUc/LhOnTgom82mWsEhstls+vHzf6puo5YV1TVUAtf7vH6xUycOKPbIToW07O5QwyhdmQPSSZMmqV69enJ2dlb16tULptbNN3HiRM2aNUtPPPGEIiMj5enpKZPJpCeeeEKZmZlXtHMJCQlasmRJwTStlzp3zvHLbF9fX4e/50+fe6XvHxMTo5EjR6phw4Z66aWXFBQUJBcXFy1btkwff/yxMjLsd8slJydLkkOQKEnOzs5F7gYtb58ulpSUJFdXV3l5OT6z5GqmnC1rH/MVd3erxWJRVglTqpbX2bNnJUlDhgwp9vXatWtXyPug7JI275Qk+XZorYQV6xxe82nfStnJKbpwINq+wGZT8rY98moVKieLi6xZhXeReEe2kMlsVtKW0h9GDeMIqt9Mh3atVcyRHaoX0rZgeXZWpk4e3+ewrDi16zeTJB0/9IcahndyeC3m8Ha5VvFQter1LrsfCfH2Z2W7e/mXsweoLFLTpWlLHa/6TEmzKfmClJ1rU52AogFUnWr2ZbEJ1yeAgnGlpktf/Or4Oet8mpScalN2jk11A50kOd7KXDfASZIUe/b61Wf+dNNVXE1SCv8ujKhWveY6vHutYo/uUHCTwnN4TnamTh3f57CsOEH1m0uSThz+Qw3CHM/rsXnndf+883pywknJZtOquR9o1dyiF4ou+ubfkqTH//aDatVrfjXdQiUQ3DBce7f/rmOHdqpRaOFsIdlZmYqJ3uew7FrKyc6WzWZVWmrydXk/3BpqNyhlTHRsn+o1vdyxs3BM1KiZ47HzRP6YqEa9i96vuc6cPKLkxHhVr93EoX1yYrzcvRy/64NxXe14PaiBvTZPHPpDjcIvX5tBpdTmeWoTF6nTsJkO7Pxdx+VO0doAACAASURBVA/vVIOmjuf12GP7HZYVu35ebR47+IeaNO/o8NqxQ9vlVsVDATWCi6zn6lZVwY0Lw9DtGxbLZrMptFXXq+kOKpnrfV6/2Oao2ZKktj2GXUUPjKfMAWmjRo0UGhpa4uvz58/XkCFDHJ5ZmZWVVRAeXglfX1+FhYVp7Nixxb5+rcOy5cuXKz09XR9++KFq1arlsPxi+aHh2bNnHULSnJwcJSU5PmPkavrk4+OjzMxMnT9/3iEkPX266IN5SwotLw1gy9rH6yU/5J4yZYrDnar5LvfMWFwd1xoBcvb2VPrxOFnT7eF44upNyog7rTqPDNPR979S7gX77VKeLULk372dTkybI9tFd/vGzZovv85tVPfx+xQ9ZUbB8vrPjJY1O1snZy+6vp3CTatZu4FaPf9TrVsy3eFDw5aoH5Sdla4WHW8vWJaSdFoZaany9q9ZMG1uvZBIefoEaMvq2erUb7Rc3dwlSSeP79PRfRsV0fUumZ0L7wZISz2nqh6OF9LkZGdpxdwpkqSmrW+7Zn3FzS3HKh05WXygc+CETaF1TaruK8XnnUItzlJEYyedPW9zCKCcTJKfp33a3eQL12PPYQQ5ufnT2Ra174RV4cFOquFn0qlEexuLs9QmxKyzyVbFnLmkPr1Mys6xXXF9VnWT0jMunXBa8qgiNatvVma2TafPEY4aVXi7Afpt4SfasHSaQxi6ZfX3ys5KV/MOhbPgpCSdVmZ6qrz9asol77we3CRSHt4B2rZ6tjr2GS1L3nn91Il9it6/Ua263F1wXg+q31z3PPnfIvsQvX+jNq34Rh37PqzaDVvKN6DutewybhERnfpp8U+faeWCGQ5h6NrlPyorM0ORXQcVLEs+d0bpaanyq1bjso9qKEnyubPy9i16B9TKRTMlSfWbtLii7aJyat5+oKJ++VS/L3YcE21eZR8TtbpoTHQ+6bQyLxkT1W+aNyaKmq3O/S8ZE+3dqIhujmOiVp0Ha9vaedq4YpaatCj8Un/vtpU6fy5ebXvcc627jFtE8/b28frvl4zXN+eN11teZrxeP2+8vjmqmPH63qLj9VadB+uPtfO0aaVjbe7Lr83u1CbsWnUYoBXz/qffFk13CEM3rJyt7Mx0RXS+6Lh57owy0lLkU62wNhuGtpWXT4A2rPpR3QaOKqjNuGP7dHjPJkV2d6zN4lxISdKiWe/L3dNXHXvddw16iVvV9T6v58vJztL233+Rh3c1hbTqcW07WcmUOSC9HJPJJJdLpqX58ccflZvreEV7fptL70wsTteuXbVu3TrVr19fHh4eFbKfFoulTO8tqeDZmxf3KzMzUz///LNDu/xnry5atEhNmzYtWL548WKHaWKlq+tT+/bt9dlnn+mXX34peAappCL7I9mD1oSEBIfQNisrS2vWrLmiPpZHeX7Hl8p/pmpMTIx69+59xfuAQkEjh6hKXXv4bQnwk5PFRY3GPylJSj8ep9iZ8wrahkx4XnVG3a11vR5U4mr7lM62nBztfn6CIr55Tx1XzdSJz3+Qs6e76j/7kDLPJOrAPx2v2j/+2Q+qPXqoQt99WVWCg5S677AC+3dXjbv66uCEqUqPjrlOPcfNrkadJmrXc4Q2LJ+pbz4cqyYtuulM3BGtXzZD9UIi1aJD4YeGpT+8p21r5+qRl6apfmg7SZLZ2UUDR7yi7z96Xp+9+aDadh+mzPQL+n3JNLl7+qnnXY4Xokz/vyfk6ROoWvXC5OkTqJSk09r++y9KiD+mDr0fUO0GfFmFopZty1X9ms4a1dtZ6/ZalZkttWnsJM+q0swVjp9xvKpKY+900dFTVn21xPG1bs3td/S55H3yqu5rKlh2LN6mY6cLQ6XgQJOCq9vPz7X87X+2a+qkjLzrnlbvLJwKH8a2ZHOOGtay6OF+Llq7O1eZWTa1DTHLq6o0/ZK7or3cpXFDLTpy0qrPFzk+J7RHS/vtn/n1WcPXVLAs+pRV0fH2+mzVwKxO4WbtOZarc6lSbq5N/t4mRTQyy81Vmrsmh+fyGlj12iGKvG2ENq2YqVlTxqpx8246c/KwNi6foeCQSDVvX3heX/7jf7T997ka/Zdpqte0vST7eb3/8Fc1+5Nx+vKtBxTR7R5lZqRq/dJpqurppx5DCs/rnr7VFda2f5F9yMqwX8hXu2HLYl+HMQUFN1G3fvcr6tdv9em74xQe0UWnYo5q1aJv1Disrdp2GVjQdt7M97Uh6mc9+/rnahIeWbD84J7NOrR3qyTp+JHdkqSoX79VFXf7hcsDhj5R0HbCC3erYdPWqlM/VD5+gUpNSdK+Heu0f+cG1arbWLcNeuB6dBu3iBp1mqh9rxFav2ymZr4/Vk1a2sdE65bOUP2mkQ4XjS75/j1tWzNXj46fpgYXjYkGPfCKZk15Xv/794Nq28M+Jlq7eJrcvfzU65IxUaNmndSiwyDtWL9A0yY9oZBWPZSUEKf1S2fK0ydAve56+rr2Hzevi2vzmw/yxusn7bVZ79La/MFem4+8fEltjnxFs6Y+r88m2GszI/2Cfi+pNsMLa3P6/+XV5tk4rV9mr82e1Cby1KzbRJ36DNfaJd/oq/eeVWirroqPPaI1i2eqQWikWncqvPBp4az3tHn1PP35tS/VKKywNoeMGq8ZH76gKf8cpfY9hykzPVWrF34tDy9f9Rv2lMP77d22WqsWfKEmzTrJ06eazp2N04aVPyr9wnk9/MJkuXs5XogPY7ve5/V8e7YsU1pqkroOelRmc4VFfoZQYT+t7t2766efflKDBg0UEhKiLVu26LvvvisyHWyjRo1kMpk0e/ZseXh4yGKxlBgWPvfcc1q7dq2GDx+uBx98UMHBwUpLS9OxY8e0cuVKffHFFzKbzeXaz8aNG2vRokWaNWuWQkND5erqWvCs0kt17txZLi4ueuGFF/TYY4/pwoUL+vLLL4s8V7Rx48a6/fbb9b///U+SPcg8ePCgvvzyy4KphiuiT126dFFkZKTefvttXbhwQeHh4dqyZYvmzZtXpO2AAQP0wQcfaNy4cXrssceUmZmpr7/+ukhgXdY+lkd5fseXqlOnjsaMGaNJkybpxIkT6tSpkzw8PHTmzBlt3bpVDRo00AMPMKAsjzoPD5V/9/YOy0LesN/pnRC1wSEgLcmpH3/V5rsy1OiVJxX69l9lzczS2RXrtO+VScqMc7yD2ZadrQ39HlLIG8+p1n23y8XfR2mHj2vXs2/o2NSZFdcxVAoDR46Xb7UgbYr6Xge2R6mqh6869B6pnneNlZOT02XXb9auv1wsrlr188daPOtdmZ0tahDWQf3ufUFevo53oYe17at9W5dr/bKZykhLkcVSRTWDQ9XzrrFq0WFQCe8Ao0tMkT7/NUd9Iszq0sxJZifpZKJNM5ZbS7zrtDi9Wjue22v5m1TL375s5fZch4C0fk2Tbmvp2L5zeOHfCUiRLzFF+nR+tvq1Natbc7PMZikuwaZpS7JLvOu0OH3aOH7uq1XNSbWq2Y/By7flKDre/vkxOt6qoACTmtY1y6OKZHayTwF8KM6qdXtydfw0d48aXf/hr8inWpC2Rn2vgztWqaqHr9r1HKnb7nxGpjKc18Mj7ef11fM/1pIf3pGzs0X1Qzuo97AXi5zXgfIY9tBf5RdYS2uXztburavl7umrHv2Ha9B9T5XpM+eBXRu18IePHZYt/2V6wf9fHJD2GDBCe7ev0+rF3+lC6nlZLK4KrFVPg0c8ox4DRsjVrZiHm8PQBj0wXr4BQdq08nvt3x6lqp6+6th7pHoNLduYqHm7/nJxsY+Jfv3OPiZqGG4fExX3DLJhf3pLNeuGaMvqOVo48y25VfVUeGRf9Rn2XInPNYMxDRw5Xj7VgrR5VV5t5o3Xe91d9vG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9Tw6nUwt/WP3zTgAtWl1w9ETFnj1QwcmtlP3uzPrgqCSVbdqhoiWr1Wb8xTKYG8ZQJl17iRwVldr/9sde9ex9eaqMVqvajL/4Fx0PWh6rxaC+6cHavtdWHxyVPMHLJeuq1CberI7Jxx+EtDPLOzgqSW63tGar50U0pZX/sb4GgxTMOyYaERxk1JC+Udq8vbw+OCp5gpfzvitUaptgpXf8eQNPjnao0DMbNDzM/yBSg0EKDaYbBr6sZimjvUm7c131wVHJ0/5etd2hxGijUhOPf+3U2KWKZrbXrWZpRC+ztmY564OjQYwRRa35P6yR2+3WtRed61V++bnDFRxk1dffN7+N8vp/58rpcumOq30HKdcJCwlWTOSJZUdB4LLbKrVv+yK16TioPjgqefqTug4cp9LCLBU0oz8pc+MXMltC1HXQ1V7lPYffIpfTrt2bGvqT7LZK/bj8A7XLOFdJnc6S2+2WraZ5KfrR8s1f7ulPuvZi78/gXD56hOfeuWxVs+t6/b9zPPfOaxrPKsa985djBikQIFrHGGQxG7Q/3+mzbH+BpzGUnGBQTuHJT3lrMEghVslolKLCDBrew6Qgi0G7sn2PBYGnOG+nnA6bEtv29lmWUFtWcGCLElJ7NVqH2+VSUe42xSVlyGzxzuefkNJLBoNRhQeaTjNx5HCODu5dpVbt+isqocMJnAlaiu27s2Q0GJSR5n0dBFkt6tw+Vdszs5pVz9af9mjmvEV66t4/KCw0xO86LpdLO/fuV3qHtj4pUzLSOshoMGhbM/cHNEf0AE/68OKVG3yWlazaqPhzhyisS3uVb8uUDAZF9c1Q6YZtctV4p4AsXbNZbqezvj6gTtvWZlktBmVm+6YNrSvrkGzRngMn9k3QmChP4Kms3HemU0ykSW8+3lpBVoNqbC5tybTpk2/LdLCQd054dEgNltVq1PbMCp9l23d7Bo108TP7szEhwUZZzAaFhpjUvUuYrhnbSqVHHNqx23f7+Bir5rzVW8FBRlXXOLV28xG990musg/W/LKTQovQJs5zLe075HtvqytLTTAqO//kzfLs0MaoYKtBOQUuXT7MooFdzQq2GlRe5daq7Q59s9ouF1/ECVjbdu+T0WBQ97T2XuVBVou6tEvR9t37mlXP1swszfzmO/110u8V3kibCDhRhw96+pNatevjs6yuj6kge4sSj9OfVHhgm+KTffuTElM9/UlHB1nz9q6TvaZCCcnd9cPcZ7Rzzaey2yoVHBajroPGa8D5k2Q0EXIJVE3fO1O1fXdWs+rZmrlXM+ct1l8n38a98xTjf+uvKC8vT1OmTNGyZctUUlKi5ORkXXfddZowYUL9OnWpehcuXOiVnnbVqlW6+eab9cEHH2jw4MbT+s2ZM0ePPfaYbrzxRj388MMyGAw6fPiwXnzxRS1evFilpaVKSkrS7373O91+++0ymRpGttbU1OjNN9/Ul19+qZycHIWFhSkjI0MPPvigOnTooJEjR+rCCy/U008/7bXPnTt36rLLLtMzzzwjo9GoRx99VJJ08803169z9HHPnj1bH374oTIzM2U2mzV48GA99NBDat++ff36W7du1ZQpU7RlyxYdOXJEsbGx6tGjh/7+978rKirqhH7/gS4y1DOSvqzSt4VTVum9zsmWEGXQ5N81fHuvqsat7zY5tGQznVWQKss8afZCI1v5LKsrqyzL91l2tJrqUjnt1QqLTPRZZjJbFRQarcoy31RoR9u17lPJ7VYXZo8GvILDJYqKDJfV4juEPiE2Rlt27pbd7pDF0vhrlMPp1P+98YEG9e6u84YObHS9IxWVqrHZlBAb7bPMarEoKiJcBYdLTuxEAD+Ckzz3yZpc33tidW5+7TqtVL4tU5aYKJlCQ1R9wHddl80uW1GJgpN977sIbNERnvZFcZlvJ35dWUxk09/Ea7xuo84ZEKpDhx3atc87AFtQ7NRP+yuUnefp0O+UYtF5g8OU0TFef3u7SDmH+KwDpLhoz7O9sNg3QF942FMWH9P8KXR/vr2tRgyKqf95e2aFXpmarYpK73ZOXoFNW3cd0t7sKrlcUtdOobrs/AT17R6h+/66S1k5vzBFD854kWGetnhphZ/2em1ZVPjJba8nRHtmpJ7dyyKH060vV9pVWe1W384mje5nUVSYQf9dxDdyA1VhcWkTbaJobd61R3aHQxZz022i/33zPxrcq5vOG9L/VB4uAlRFbV9RmJ/+pLCoVrXrNN0XVFNV15/kW0d9f1JpQx0lBXslSVu+/0Amk0WDL35QQaHRytz4uTYuflMVpYd0zjXPnvA54cxWWNxUf1K0Nu/a3bx75xv/0eDeGTpvyIBTebgQAdJfzaFDhzRu3DiFhYXpvvvuU5s2bbR8+XI999xzKikp0b333vuL9/Hvf/9bL7/8sh599FHddJMnX3pVVZVuuukmHTp0SJMnT1aHDh30/fff66WXXlJ2draeeeYZSZLD4dDvf/97bdy4URMnTtSAAQNks9m0bt065eXlKSMjQ1dddZX++9//6qGHHlJ4eHj9fqdNm6aoqChdcsklqqys1J///Gc9//zzeuKJJ9S9e3dJUlpamiTp5Zdf1uuvv65rr71WkydPVnl5uV577TVdd911mjNnjhITE1VRUaGJEycqIyNDf/3rXxUZGan8/HwtX75cNTWMrj1Rdf34Tj8xSYfT7bXOyVZc7ta782wyGQ2KizSoTyfPSFWTSXLRVxXwHHZPejOTyeqzzGQO8lqn0Tpsnk4lo5866uqpW8cfl8upzA2zZQkKV4ceY5p13Gi5amw2Wc3+O0frXnKrbbYmA6TT5n6j7IP5+r8H/9TkvqprZ+VZ/Lw81+2vpoaOKZw8ptrRp04/15WzuqZ2nWCvP102/9egq7pGRkaz4hhWi6cDv+798mh2h6csyPLzO/mtFmnydTEKshr0z2klch4Tf337s1Kvn9dsrdb6HdX6y8Q4XX9hpJ6bevhn7xMtT1CQJyBkt/sG8G21ZUHW5qfA/fCzPH2xqEhREWb1yQhXh9QQRYb7vh+88NZ+r5+XrSnRivWl+sdjnfXHG5L1yLO7f85poAWqe630f+/0XudkqUunGxIkPT+jRgUlnn1v2u3UHy8zaEC6WYs32HWomGmkgai6xiZrIx349W2iGluTnfz/+fxbZefl67kH7mh0HeCXcNhr+4LMTfQnNdEXdHQdJj911NVTt44k2Ws8WShqqko1/r7PFZ3YUZLUqfdF+vyNm/XT+jnqM+p2xbRK+5lng5ag2nYS7p1z5ys775Ce+/MfG10HJw8B0l/JK6+8ourqas2aNUuJiZ6R9kOHDpXdbtc777yjCRMmKDrad/ZIczgcDj311FOaO3eupkyZovPPP79+2WeffabMzEz9+9//1jnnnCNJGj58uFwul6ZOnaqJEyeqU6dO+vzzz7VmzRo9++yzuuKKK+q3P++8hu+vXX/99Xr//fc1e/Zs3XjjjZKk8vJyff7557r22msVHBys4OBgdejgSUmYlpamPn0aUhzk5ubqjTfe0K233qqHHnqovrx///4aM2aM3nvvPT388MPas2ePSkpK9PDDD6tr1671611yySUn9PsJNAaDFBbsXWZ3NDSqTH4G7JtNhvr1TgW7Q9qd65bkaVit2+XUny636IZzLXp//omlV8OZx+VyqrrCu3PSbAmW2VLbWe/001nvqKldr+kOeLO1thPfTx119dSt48+Bn75XRWme0gdeI7OVzv5AF2S1qrK6zO8ym91zzwq2+m88SVL2wUN695PPdetVY5XcKqHJfQUHeeqx2/3fC212u4KCGt8X8HM5K2sHpfi5rkzBQbXrVHv9aWzkejcGB8lV2fQAFrRcBoMUGeYdSLLZ3bLZPe97de+XR7OYPWU19p/X2W4xS5Ovj1WHZIvenFWqXfua9/64a59dO7Js6tbBKov51L3r4vRjNEhRkd7dHTU2l2pqPEFQi8U3CGqtLauxNT+FaVZOdf3sz+9WFmvsOXH624Od9MDfftK2n3zT+B7tx10V2rKjXL27RchqMdT/30HLZjBI4ce2150N9yf/987a9U7yPcxRO3h6/yFXfXC0zrqdDqUlm9QxyaRDxdw8A1FwkFWHy474XVbfJmqinZKdl693P/1Kt/7uouO2iYDj8dufZA6W2VLbF+Rooj+pib4gSfV1OP3UUVdP3Tqe9T1tpsS2veuDo3W69LtcB/es1sE9awiQBqhgq1WHq3/pvfNL3fq7i7l3/koIkP5KlixZoiFDhig2NlYOR8PL5ciRIzV16lRt2rRJI0eO/Nn1VldX684779SWLVv0/vvvq2/fvl7LV61apYiIiPrgaJ0rrrhCU6dO1erVq9WpUyctW7ZMoaGhuvzyxj/6m5qaqlGjRmn69On1AdLPPvtMVVVVuu666457rMuXL5fD4dBll13m9TuIi4tTRkaG1qxZI0lq3769oqKi6lMFDxgwQKmpqc3+nQS6qDDpwau9c+av/8mp1Ts8rR9/aXQjQz1/+ku/eyrYHNLWfS6N7GVWbIR02P9zAy1MRWmePnn+PK+ytL5XqOugqyXJbwrcurJQP6lzjxYUHCWTJbg+vcrRnA6baipLFNqh8TSnu9Z9KklKJ70u5El7kpWTK5vd7pMWpeBwsaIjwpucPfqvDz5RZHiYRg7qp+yDDde10+mS3eFU9sFDCgkOUnxMtCLCQhVktfpNo2uz21V6pFx9MrqcvJNDwKtLoxuU1ErlO/Z4LatLv1tdm37XXlwqZ2WVgpN9000ZrRZZ46J1eOmaU3zEOF3FRZn04gPez+dl6yu1eK3n2w0xkb4BqLqy4rLmf2bBExyNUfeOVr07p1Q/bPp5QfnCEqcyOhoUFmJUyZGT9+0+nN4S4qz68J/dvcrmLyvSl4sKJflPoxsf23j63eZasPyw7p6QqkvOjT9ugFSSDhXa1CfDoPAwkw6XEIQKBNHhBj12o/eAzDU7HFq5zfPvHxXmp71el363/OS210tq6zvi9zM8nrKQIJ9FCBDxMVHam3OwkTZRiadN1MQMqCkffqrI8FCNHNhH2XkN7XSHq7ZNlJevkKAgxcfwGS0cX0XJQU1/1rs/qUv/K9Rt8DWe5X76kypq0+L6S517tKCQuv4k3zrq+5M6NvQnhUW1liSFhsf7rF/Xd1VTVeqzDIEhPib6F947Z9b2Jx1z73Q6ZXc6uHeeAgRIfyVFRUWaP39+fcrZYxUXF59QvYWFhTpw4IBGjRqlXr18PzhdWlqq+HjfG3ZCgmcEQklJSf3+ExMTZTA0ne7q5ptv1oQJE7Rq1SoNHjxY06dP14gRI9S2bdtmHaukRoOwdd9cjYiI0IcffqjXXntN//u//6uysjKlpKTohhtu0K233nrcYwx05VXSu/O8Rz2VVXoaU3aHW20TjZK8O6XaJng6qw4U/nqjli21M1lDggzSEUZLB4KQ8HiNufUdr7LQyESFR7WRyWxV/v5NPtsU1JbFJ/dosm6D0ai4pAwdzt0up8PmlRqlIGez3G6X4pP933+ryouUveM7xbROV3xK0/tBYOjWqb1WbdqqbZl71adbQ3CyxmbXT1nZXmX+5BUUqbC4RNff/4Tf5VdPekxD+/XSC49OktFoVHqHttqVtd/nBXpb5l653G5169T+pJwXIEkla7dIkmLO6quiRSu8lkUP7iN76RFV7MryFLjdKt2wTZF9uslotchlawgaRA3sJYPJpJJ1P/5ah47TTGm5U8++V+RVVnzEpaJSp2x2t9JSfUdG15XtzW1eAMpskiZdF6MenYL03txSLV3/82cst44zy+F0q6KK4GggOVxq18P/l+lVVlRsV36RTTabS93Swny26dbJM2r0p72VJ7xfi9kok9GgiPDmfWc3uVWQHA63jlQ0f9AAzmxHKt16Y653useySreKj3ja6+1a+Q4uqSvLKTi597HsfE99/r5tWldWXkVbPVBldGqnVZu3a2tmlvp261xfXmOza9e+HPXt2vTsuLzCwyooLtV1f37a7/Jx9z6pYX176MWHm/4kCSBJIREJuvi2d73KwiITFR7t6U86tG+jzzZ1fUwJx+nnMRiNik/OUNEB3/6k/GxPf9LRdSSkevrfK0r9BWXzPMcbHtfMM0NL47l3bmvk3pntVeZPXkGRCopLdN0DT/ldPm7y/2hYv5568eG7T+pxBzICpL+SmJgYZWRk6J577vG7vC44GBTkGZ5nO+ZbT40FUFNSUnT//ffrnnvu0f3336/nn3/e6ztm0dHR+vFH346rgoKC+uWSFBsbq40bN8rtdjcZgBwyZIjS0tL00UcfyeVyaffu3V7pcpsSExMjSXr11VfVqpXv6B3rUenb0tPTNWXKFLndbu3cuVPTp0/Xs88+q8jISI0bxwyvpjicdelsfe3Idql7O6NaxxqUd9izjtUs9U83qbDUpZyChu2MBik20iC7w63S4w9+9is0WKqqrkus2yA8ROrRwaQau1v5fM8kYJgtQUpOG+p3WWrXc7Rv67cqOrhDcW08qbXtNRXauW6mIuPaKSGlYQCIy2lX2eFsmS3BCo9Oqi/v2Oti5e9br51rPlbGkBvry7f+8IEMRrM69LjI774zN8yRy2ln9ijqjR46UFM/+0ozvlzgFQydu3CpqmtsGjNicH1ZYXGJyiur1Do+VsG1z/C7bx6v8grfztXn354mq8WiSbdcrbijRvudP3yQNu/M1JwFSzX+otH15TO+XCCTyaTRQwacitNEAAhqnSBzVISq9ufKVeXpjD28dI2qc/OVOnGc9k55X87aazWiV7riRg5S9tRZch+V6SN3xheKHdZfbW+/Rlmv/qe+vMOkW+Sy23Vw5te/7knhtGF3SFv3+E9FtnFntQZkBCu1tVnZeZ7rKchq0Mj+IcordGhPTkOA1GSUEmNNstndKipt6Pw3mzwzR3umBen9z0u1ZF3jwdGQIIOqbW65j3mt7N0lSF3aWbVpVzXpdQOM3e7Whq3+09Ss3FiqYQOi1bFtiPbs91xXwUFGXTgqXjkHq7Vjd8Mz3GSSkhKDVG1zqaCo4bqNiTKruNT3orpijGcg8o7MhgZUaIhR1dUuuY65Pgf1jvz/7N13eFRV/sfxz2Qmk94LLbQQCIHQCaFIBwEFUZqiYtdV17ZYdnXVn2VZd9W194KoFCnSVLo06b0IhBYCgYQkkELqZFJ+fwxJGGYSUEHKvF/Pk0c599w798DJnXPO95xzFRvtqw3bc2Rle12XUVIq7T/mPNC5+3CpWjU2qk6IQaknq/rr8TEmZWSX6Uh61XlublKIv0HWkqqVoL9VZm65DqWWqmFtN9ULNVROmDYYpM4xJpWWlmtfMpNLXFW/Lh01YfZCfTd/qd2A/pylq2x9oms6VaadyMo5o09kG9t77PZhys13/O5+Y/wUmd3d9fiYEayAwnkzuXsooqnz8aQGMb2V9OtinUxJUEjdqvGkhI0zFBDasDKgKZ0eTzp5ejwpqGo8KarN9UpL2qI966cqttuYyvSdq76Wwc2kyNZV40n+wRGq1ai90g5v1Yljuyon45eVlWrPhukyuJkU0bTbBS0/rhz9usZpwuwF+m7ez/bPzp9/Oc9n5wjlFjiOJ73x5RSZ3U16/I6RCg3k2XkhESD9k3Tv3l1r165V48aN5evrW22+evXqSZL27t2ryMiqfcyXLl1a7Tk9e/bUp59+qocffliPPvqo3nvvvcpgY+fOnTV//nwtW7bMbpvduXPnymAwKD4+vvL+fvzxR82ZM8fuHaTO3H777Ro3bpxOnjypiIgI9ejRw+54RYC2qMh+VmS3bt1kNBp19OhRu3eb1sRgMKh58+Z68cUXNWPGDCUkJJzXeXBu0aYSNalr1t0D3LV6V6ksxeXqGG2Uv7f0zWL7Dr6/j/S34WYlppbpy/n2s/x7tbHNiK7YYbJ2kKEyLel4mZLSbB2rtpFGdW1p1O7DpcrKk0pLyxUSYFD7KKM8PaTZq0pkZbI0JHW89m9KObhOC7+6Ty273Smzh4/2bpqhglPp6n/HJ3YTN/JPpWvmO9erduM4XXffN5Xp0R1Hav/mWVo/77/KzTqmwLBIHd23Uod3L1GbXg/KLzjC6Wfv3zxTRpOHmrQdctHLiStDVMMIDR/QWzMWLNU/3vhQXdu3UtLRVE2bv1TtWjTTtddUBUg/njRT81as0YcvPaX2LW2dsU6tWzi97vvfTpe3p4f6nBXwHNq3h35atlrvfj1Nqekn1CiijtZs2akVG7bqruGDVZf3TuAM9W4bKq8Gts68OSxYbmZ3RT37kCSp8EiKjk2aU5k3etxY1b9jmNb2HaPMlRskSeUlJdo1dpzaT35bXZZPUvKX02Xy81Hjx++SJSNT+15+z+7zjnwxXRF3DlfMG/+QV8N6yks4qPCBPVX7pmu1f9xHKkw6+ieVHFeSaYtz1SLSQ8/cGayFa/JVaClXr47eCvIz6q2J9u+PCvI36r+Ph2vPIYteG1917MGRgWrTzFO/HrCo2Cp1bWO/JWXycauS02zt15hIs24d6K+tey3KyCxRaZnUJMJdXdt46VR+qSbNc/5eabim8VNT1LaFn157polmLshQQWGpBvUKUWiQu57/30G7vKFBZn35egtt35Orp/9dtSL1s9ditGtfnvYnFepkVrH8fU1qH+uv9rF+SjxSqJkLMyrztm3hp7/cWk/rtuYoNb1YpWXlah7prT7dgpV9yqqPJx7708qOy9u8dVY1rWfUA4M9tXKHVZZiW3DU38egL+dZ7PIG+Bj099FeOnisVB/PtT/Wt72to252t/Wh6oS4VaYdSi1TYmpV0HPWqmL99UZP/WWIp1btLFF+UbnaRhnVoJZRizZZf3fwFVe+qAb1NOLanpq+cLn+/r9P1bVdSyUdO66pC5apfUxTDehWteXoR1Nm66eV6/TRC39Th5a2CaadWsU4ve77E7+Xl6eH+nZu73Bs/Mx5kqQii20C1oEjxyrT2sU0PefKK7imTgPHKuXAOs378l61uuZOuXv6KmHDdOWfStPAu84aT8pJ07T/Xac6kXEa8pdvK9ObdxqpvZtmau2PtvGkoPAmOpKwUkm7Fqtdn4fkf9Z4UrcbntfcT27XT5/fo5bdbpend6AO7pivjOQdat/3YbvgK1yL3bPzzY/VtV0rJR1L1dQFS9W+RTMN6FYVIP1oyiz9tGKtPnpxrDq0jJYkdWpdw7PTw0N9O3dwODb++58kSUWnF9wdOHy0Mq1dTFO147VNNSJAeoGtWbNGhw8fdkh/4okntHr1ao0ePVpjxoxRw4YNVVBQoMOHD2vZsmUaP368jEajWrVqpcaNG+v1119XaWmp/P39tWTJEm3evLnGz+3SpYvGjx+v+++/Xw8++KA+/PBDeXl56cYbb9SkSZP09NNP6/HHH1dkZKRWrVqlCRMmaNSoUZVB2MGDB2vGjBl6/vnnlZiYqLi4OJWUlGjLli1q3769XXB16NCheuutt7Rx40Y9/fTTcnOz3wImKipKBoNBM2bMkK+vr8xmsxo3bqz69evr4Ycf1ptvvqnk5GR17dpVvr6+ysjI0JYtWxQZGanbb79dy5Yt05QpU9SvXz9FRESotLRUP/zwg0pLS9W9e/cL8K/kujJzpc9+tGpAR6N6tDLKaJRSTpbr60XWaledOtO/g/2jo26om+qG2urBz1tLlJRmi3ompZWpXphBzRsY5etlWyGQVygdSCnT2t2lOpJOZws2/iENNfiBSdq08C3tXPm5SkutCqnbQtfe+Vm1q07PZjSZNfCe8dqy+F0l7vhJloJs+Qc3UOfBzyum861Oz0k7vFXZGQcV2WawPLyYgYUqT9x1i+qEh2jO4pVas2WnAvx8NXJgH91/81CH770/yt3dpPdefFKfTpmlxas3KCc3X/VqhWnsPbdqxMDe574AXEr9u4crpGe8XVr0K09Ikk6uWG8XIK3O8e8XaNNNRYp67iHF/PcZlVmKdWLpWiU896YsKfbvci63WrV+wF2KfuUJ1b15sNxDAlV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\n",
      "text/plain": [
       "<Figure size 2160x1800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "l = COVID_all_variables[all_variables]\n",
    "corr_matrix_neg = l[COVID_all_variables['result']==0].corr()\n",
    "fig, ax = plt.subplots(figsize=(30,25))\n",
    "sns.set(font_scale=1.5)\n",
    "sns.heatmap(corr_matrix_neg, annot=True, fmt='.2f' , cmap=plt.get_cmap('coolwarm'), cbar=False, ax=ax)\n",
    "ax.set_yticklabels(ax.get_yticklabels(), rotation=\"horizontal\")\n",
    "plt.savefig('corr_matrix_neg.pdf', bbox_inches='tight', pad_inches=0.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "# sns.set(font_scale=1.)\n",
    "# axes = COVID_all_variables[COVID_all_variables['result']==0].hist(alpha=0.5, label='Negative', figsize=(20,15), bins = 20, range=[-4, 4])\n",
    "# COVID_all_variables[COVID_all_variables['result']==1].hist(ax=axes.ravel()[:18], alpha=0.5, label='Positive', figsize=(20,15), bins = 20, range=[-4, 4])\n",
    "# plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot all variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "#os.mkdir('Figs')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/cvmfs/sft.cern.ch/lcg/views/LCG_97python3/x86_64-centos7-gcc8-opt/lib/python3.7/site-packages/numpy/lib/histograms.py:824: RuntimeWarning: invalid value encountered in greater_equal\n",
      "  keep = (tmp_a >= first_edge)\n",
      "/cvmfs/sft.cern.ch/lcg/views/LCG_97python3/x86_64-centos7-gcc8-opt/lib/python3.7/site-packages/numpy/lib/histograms.py:825: RuntimeWarning: invalid value encountered in less_equal\n",
      "  keep &= (tmp_a <= last_edge)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#sns.set(style=\"ticks\")\n",
    "COVID_data_pos = COVID_all_variables[COVID_all_variables['result']==1]\n",
    "COVID_data_neg = COVID_all_variables[COVID_all_variables['result']==0]\n",
    "for variable in COVID_all_variables:\n",
    "    maxi = max(COVID_all_variables[variable])\n",
    "    mini = min(COVID_all_variables[variable])\n",
    "\n",
    "    weights1 = np.ones_like(COVID_data_neg[variable])/len(COVID_data_neg[variable])\n",
    "    weights2 = np.ones_like(COVID_data_pos[variable])/len(COVID_data_pos[variable])\n",
    "    \n",
    "    plt.title(variable)\n",
    "    plt.hist(COVID_data_neg[variable], alpha=0.6, label='Negative', bins = 12, range=[mini, maxi], weights=weights1)\n",
    "    plt.hist(COVID_data_pos[variable], alpha=0.5, label='Positive', bins = 12, range=[mini, maxi], weights=weights2)\n",
    "    plt.legend()\n",
    "    plt.savefig('Figs/{}.png'.format(variable.replace(' ', '_').replace('/','')))\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# sns.set(font_scale=2)\n",
    "# g = sns.PairGrid(COVID_all_variables, hue=\"result\", vars=COVID_all_variables[all_variables], height=5.5) \n",
    "# g = g.map_offdiag(plt.scatter)\n",
    "# g.map_diag(plt.hist) \n",
    "# g.add_legend() \n",
    "# g.set(alpha=0.5)\n",
    "\n",
    "# plt.savefig(\"pairplot2.pdf\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Split dataset with all vaiables into train and test datasets "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "420 training events, 181 testing events\n",
      "Training: 61 of which are positive and 359 are negative\n",
      "Testing: 22 of which are positive and 159 are negative\n"
     ]
    }
   ],
   "source": [
    "X_train_all, X_test_all, y_train_all, y_test_all = train_test_split(COVID_all_variables[all_variables], COVID_all_variables[test_results], test_size=0.3, random_state=42)\n",
    "print('{} training events, {} testing events'.format(len(y_train_all), len(y_test_all)))\n",
    "\n",
    "n_train_pos_all = len([i[0] for i in y_train_all.values if i[0]==1])\n",
    "n_test_pos_all = len([i[0] for i in y_test_all.values if i[0]==1])\n",
    "n_train_neg_all = len([i[0] for i in y_train_all.values if i[0]==0])\n",
    "n_test_neg_all = len([i[0] for i in y_test_all.values if i[0]==0])\n",
    "\n",
    "print(\"Training: {} of which are positive and {} are negative\".format(n_train_pos_all, n_train_neg_all))\n",
    "print(\"Testing: {} of which are positive and {} are negative\".format(n_test_pos_all, n_test_neg_all))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Split dataset with my vaiables into train and test datasets "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "def impute_with_median (df):\n",
    "    \"\"\"Iterate through columns of Pandas DataFrame.\n",
    "    Where NaNs exist replace with median\"\"\"\n",
    "    \n",
    "    # Get list of DataFrame column names\n",
    "    cols = list(df)\n",
    "    # Loop through columns\n",
    "    for column in cols:\n",
    "        # Transfer column to independent series\n",
    "        col_data = df[column]\n",
    "        # Look to see if there is any missing numerical data\n",
    "        missing_data = sum(col_data.isna())\n",
    "        if missing_data > 0:\n",
    "            # Get median and replace missing numerical data with median\n",
    "            col_median = col_data.median()\n",
    "            col_data.fillna(col_median, inplace=True)\n",
    "            df[column] = col_data\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 420 entries, 2546 to 619\n",
      "Data columns (total 10 columns):\n",
      "Patient age quantile    420 non-null int64\n",
      "Hemoglobin              420 non-null float64\n",
      "Platelets               420 non-null float64\n",
      "Leukocytes              420 non-null float64\n",
      "Monocytes               420 non-null float64\n",
      "Basophils               420 non-null float64\n",
      "Eosinophils             420 non-null float64\n",
      "CRP                     420 non-null float64\n",
      "Hematocrit              420 non-null float64\n",
      "Neutrophils             420 non-null float64\n",
      "dtypes: float64(9), int64(1)\n",
      "memory usage: 36.1 KB\n"
     ]
    }
   ],
   "source": [
    "X_train_all = impute_with_median(X_train_all)\n",
    "X_train_all.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 181 entries, 693 to 681\n",
      "Data columns (total 10 columns):\n",
      "Patient age quantile    181 non-null int64\n",
      "Hemoglobin              181 non-null float64\n",
      "Platelets               181 non-null float64\n",
      "Leukocytes              181 non-null float64\n",
      "Monocytes               181 non-null float64\n",
      "Basophils               181 non-null float64\n",
      "Eosinophils             181 non-null float64\n",
      "CRP                     181 non-null float64\n",
      "Hematocrit              181 non-null float64\n",
      "Neutrophils             181 non-null float64\n",
      "dtypes: float64(9), int64(1)\n",
      "memory usage: 15.6 KB\n"
     ]
    }
   ],
   "source": [
    "X_test_all = impute_with_median(X_test_all)\n",
    "X_test_all.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_roc_curve(fpr, tpr, label=None):\n",
    "    plt.plot(fpr, tpr, linewidth=2, label=label)\n",
    "    plt.plot([0, 1], [0, 1], 'k--') \n",
    "    plt.axis([0, 1, 0, 1])                       \n",
    "    plt.xlabel('False Positive Rate', fontsize=16)\n",
    "    plt.ylabel('True Positive Rate', fontsize=16)\n",
    "    plt.grid(True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "# param_grid = [\n",
    "#               {\n",
    "#                 'activation' : ['logistic'], #['identity', 'logistic', 'tanh', 'relu'],\n",
    "#                 'solver' : ['lbfgs', 'sgd', 'adam'],\n",
    "#                 'alpha': [0.0001], #[0.05],\n",
    "#                 'random_state':[42],\n",
    "#                 'learning_rate': ['constant','adaptive'],\n",
    "#                 'hidden_layer_sizes': [\n",
    "#                 (1,),(2,),(3,),(4,),(5,),(6,),(7,),(8,),(9,),(10,),(11,),(12,),\n",
    "#                 (1,1),(2,2),(3,3),(4,4),(5,5),(6,6),(7,7),(8,8),(9,9),(10,10),(11,11),(12,12),\n",
    "#                 (2,1),(3,2),(3,1),(4,3),(4,2),(4,1),(7,6),(7,5),(7,4),(8,7),(8,6),(8,5),(9,8),\n",
    "#                 (9,7),(10,9),(10,8)\n",
    "#                 ]\n",
    "#               }\n",
    "#              ]\n",
    "\n",
    "param_grid = [\n",
    "              {\n",
    "                'activation' : ['logistic'], #['identity', 'logistic', 'tanh', 'relu'],\n",
    "                'solver' : ['lbfgs'],\n",
    "                'alpha': [0.0001], #[0.05],\n",
    "                'random_state':[i for i in range(100,3000)],\n",
    "                'learning_rate': ['constant'],\n",
    "                'hidden_layer_sizes': [(12,12)]\n",
    "              }\n",
    "             ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "# from sklearn.neural_network.multilayer_perceptron import MLPClassifier\n",
    "\n",
    "# MLP_clf_best_all = GridSearchCV(MLPClassifier(), param_grid, cv=2, scoring='f1')\n",
    "# MLP_clf_best_all.fit(X_train_all.values, y_train_all.values.ravel())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Best paameters for all variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# print(\"Best parameters set found on development set:\")\n",
    "# print(MLP_clf_best_all.best_params_)\n",
    "# print(MLP_clf_best_all.best_estimator_)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Best parameters for my variables\n",
    "\n",
    "->Best accuracy:\n",
    "(this was the best one)\n",
    "MLPClassifier(activation='identity', alpha=0.0001, batch_size='auto',\n",
    "              beta_1=0.9, beta_2=0.999, early_stopping=False, epsilon=1e-08,\n",
    "              hidden_layer_sizes=(2,), learning_rate='constant',\n",
    "              learning_rate_init=0.001, max_iter=200, momentum=0.9,\n",
    "              n_iter_no_change=10, nesterovs_momentum=True, power_t=0.5,\n",
    "              random_state=None, shuffle=True, solver='lbfgs', tol=0.0001,\n",
    "              validation_fraction=0.1, verbose=False, warm_start=False)\n",
    "              \n",
    "->Best f1:\n",
    "\n",
    " MLPClassifier(activation='logistic', alpha=0.0001, batch_size='auto',\n",
    "              beta_1=0.9, beta_2=0.999, early_stopping=False, epsilon=1e-08,\n",
    "              hidden_layer_sizes=(12, 12), learning_rate='constant',\n",
    "              learning_rate_init=0.001, max_iter=200, momentum=0.9,\n",
    "              n_iter_no_change=10, nesterovs_momentum=True, power_t=0.5,\n",
    "              random_state=42, shuffle=True, solver='lbfgs', tol=0.0001,\n",
    "              validation_fraction=0.1, verbose=False, warm_start=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "# print(\"Best parameters set found on development set:\")\n",
    "# print(MLP_clf_best.best_params_)\n",
    "# print(MLP_clf_best.best_estimator_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/cvmfs/sft.cern.ch/lcg/views/LCG_97python3/x86_64-centos7-gcc8-opt/lib/python3.7/site-packages/sklearn/neural_network/multilayer_perceptron.py:921: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().\n",
      "  y = column_or_1d(y, warn=True)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "0.8769350198639208"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "MLP_clf_noseed = MLPClassifier(activation='logistic', alpha=0.0001, batch_size='auto',\n",
    "              beta_1=0.9, beta_2=0.999, early_stopping=False, epsilon=1e-08,\n",
    "              hidden_layer_sizes=(12, 12), learning_rate='constant',\n",
    "              learning_rate_init=0.001, max_iter=200, momentum=0.9,\n",
    "              n_iter_no_change=10, nesterovs_momentum=True, power_t=0.5,\n",
    "              random_state=42, shuffle=True, solver='lbfgs', tol=0.0001,\n",
    "              validation_fraction=0.1, verbose=False, warm_start=False)\n",
    "\n",
    "\n",
    "MLP_clf_noseed.fit(X_train_all, y_train_all)\n",
    "\n",
    "y_probas_MLP_noseed = cross_val_predict(MLP_clf_noseed, X_train_all.values, y_train_all.values.ravel(), cv=2, method=\"predict_proba\")\n",
    "y_scores_MLP_noseed = y_probas_MLP_noseed[:, 1]\n",
    "fpr_MLP_noseed, tpr_MLP_noseed, thresholds_MLP_noseed = roc_curve(y_train_all, y_scores_MLP_noseed)\n",
    "\n",
    "AOC_all_variables_noseed = 0\n",
    "times = 1\n",
    "for seed in range(times):\n",
    "    AOC_all_variables_noseed += roc_auc_score(y_train_all, y_scores_MLP_noseed)\n",
    "\n",
    "plt.figure(figsize=(8, 6))\n",
    "plot_roc_curve(fpr_MLP_noseed, tpr_MLP_noseed, \"MLP (AUC={0:.5f})\".format(roc_auc_score(y_train_all, y_scores_MLP_noseed)))\n",
    "plt.grid(True)\n",
    "plt.legend(loc=\"lower right\", fontsize=16)\n",
    "plt.savefig('ROC_curve.png')\n",
    "plt.show()\n",
    "\n",
    "AOC_all_variables = roc_auc_score(y_train_all, y_scores_MLP_noseed)\n",
    "AOC_all_variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "var_list = []\n",
    "y_scores_MLP_list = []\n",
    "roc_values = []\n",
    "\n",
    "for i_var, variable in enumerate(all_variables):\n",
    "    this_vars = all_variables[:i_var]+all_variables[i_var+1:]\n",
    "    var_list.append(this_vars)\n",
    "    this_score = cross_val_predict(MLP_clf_noseed, X_train_all[this_vars].values, y_train_all.values.ravel(), cv=2, method=\"predict_proba\")[:, 1]\n",
    "    y_scores_MLP_list.append(this_score)\n",
    "    roc_values.append(roc_curve(y_train_all, this_score))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                      AOC change\n",
      "Basophils               0.774739\n",
      "Neutrophils             0.779282\n",
      "CRP                     0.793096\n",
      "Hematocrit              0.795242\n",
      "Leukocytes              0.805493\n",
      "Patient age quantile    0.805836\n",
      "Hemoglobin              0.820243\n",
      "Monocytes               0.829353\n",
      "Platelets               0.830860\n",
      "Eosinophils             0.845769\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rank_features = {}\n",
    "for i_var, variable in enumerate(all_variables):\n",
    "    rank_features[variable] = 0\n",
    "\n",
    "times = 1\n",
    "for seed in range(times):\n",
    "    for i_var, variable in enumerate(all_variables):\n",
    "        rank_features[variable] = rank_features[variable]+(roc_auc_score(y_train_all, y_scores_MLP_list[i_var]))/times\n",
    "\n",
    "rank_features = pd.DataFrame(data=rank_features.values(), index=rank_features.keys(), columns=['AOC change'])\n",
    "rank_features = rank_features.sort_values(by='AOC change')\n",
    "\n",
    "print(rank_features)\n",
    "\n",
    "plt.figure(figsize=(8, 6))\n",
    "rank_features['AOC change'].plot(kind = \"barh\")\n",
    "plt.vlines(AOC_all_variables_noseed/times,-10,20, colors='r', linestyles='--', label='AOC = {0:.4f}'.format(AOC_all_variables_noseed/times))\n",
    "plt.xlim(0.7,0.93)\n",
    "plt.legend()\n",
    "plt.savefig('features_noseed.png',  bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# times = 10\n",
    "# AOC_all_variables_noseed = 0\n",
    "\n",
    "# rank_features = {}\n",
    "# for i_var, variable in enumerate(all_variables):\n",
    "#     rank_features[variable] = 0\n",
    "\n",
    "# for i in range(times):\n",
    "#     seed = i+40\n",
    "#     MLP_clf_noseed = MLPClassifier(activation='tanh', alpha=0.0001, batch_size='auto', beta_1=0.9, beta_2=0.999, early_stopping=False, epsilon=1e-08, hidden_layer_sizes=(4, 4), learning_rate='constant', learning_rate_init=0.001, max_iter=200, momentum=0.9, n_iter_no_change=10, nesterovs_momentum=True, power_t=0.5, random_state=None, shuffle=True, solver='lbfgs', tol=0.0001, validation_fraction=0.1, verbose=False, warm_start=False)\n",
    "\n",
    "\n",
    "#     y_probas_MLP_noseed = cross_val_predict(MLP_clf_noseed, X_train_all.values, y_train_all.values.ravel(), cv=3, method=\"predict_proba\")\n",
    "#     y_scores_MLP_noseed = y_probas_MLP_noseed[:, 1]\n",
    "#     fpr_MLP_noseed, tpr_MLP_noseed, thresholds_MLP_noseed = roc_curve(y_train_all, y_scores_MLP_noseed)\n",
    "\n",
    "#     AOC_all_variables_noseed += roc_auc_score(y_train_all, y_scores_MLP_noseed)\n",
    "\n",
    "\n",
    "#     var_list = []\n",
    "#     y_scores_MLP_list = []\n",
    "#     roc_values = []\n",
    "\n",
    "#     for i_var, variable in enumerate(all_variables):\n",
    "#         this_vars = all_variables[:i_var]+all_variables[i_var+1:]\n",
    "#         var_list.append(this_vars)\n",
    "#         this_score = cross_val_predict(MLP_clf_noseed, X_train_all[this_vars].values, y_train_all.values.ravel(), cv=3, method=\"predict_proba\")[:, 1]\n",
    "#         y_scores_MLP_list.append(this_score)\n",
    "#         roc_values.append(roc_curve(y_train_all, this_score))\n",
    "\n",
    "    \n",
    "#     for i_var, variable in enumerate(all_variables):\n",
    "#         rank_features[variable] = rank_features[variable]+(roc_auc_score(y_train_all, y_scores_MLP_list[i_var]))/times\n",
    "\n",
    "        \n",
    "        \n",
    "# rank_features = pd.DataFrame(data=rank_features.values(), index=rank_features.keys(), columns=['AOC change'])\n",
    "# rank_features = rank_features.sort_values(by='AOC change')\n",
    "\n",
    "# print(rank_features)\n",
    "\n",
    "# plt.figure(figsize=(8, 6))\n",
    "# rank_features['AOC change'].plot(kind = \"barh\")\n",
    "# plt.vlines(AOC_all_variables_noseed/times,-10,20, colors='r', linestyles='--', label='AOC = {0:.5f}'.format(AOC_all_variables_noseed/times))\n",
    "# plt.xlim(0.6,0.92)\n",
    "# plt.legend()\n",
    "\n",
    "# plt.savefig('features_noseed.png',  bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Confusion Matrix:\n",
      "[[TN  FP]\n",
      " [FN  TP]] = \n",
      "[[315  44]\n",
      " [ 12  49]]\n",
      "\n",
      "Precision: TP/(TP+FP) =  0.5268817204301075\n",
      "Recall: TP/(TP+FN) =  0.8032786885245902\n",
      "F1 score =  0.6363636363636364\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y_probas_MLP_noseed_b_prob = cross_val_predict(MLP_clf_noseed, X_train_all[all_variables].values, y_train_all.values.ravel(), cv=2, method=\"predict_proba\")\n",
    "threshold = 0.03\n",
    "y_probas_MLP_noseed_b = (y_probas_MLP_noseed_b_prob [:,1] >= threshold).astype('int')\n",
    "\n",
    "conf = confusion_matrix(y_train_all, y_probas_MLP_noseed_b)\n",
    "print(\"Confusion Matrix:\")\n",
    "print(\"[[TN  FP]\")\n",
    "print(\" [FN  TP]] = \")\n",
    "print(conf)\n",
    "print()\n",
    "print(\"Precision: TP/(TP+FP) = \", precision_score(y_train_all, y_probas_MLP_noseed_b))\n",
    "print(\"Recall: TP/(TP+FN) = \", recall_score(y_train_all, y_probas_MLP_noseed_b))\n",
    "print(\"F1 score = \", f1_score(y_train_all, y_probas_MLP_noseed_b))\n",
    "\n",
    "precisions, recalls, thresholds = precision_recall_curve(y_train_all, y_probas_MLP_noseed_b)\n",
    "\n",
    "def plot_precision_recall_vs_threshold(precisions, recalls, thresholds):\n",
    "    plt.plot(thresholds, precisions[:-1], \"b--\", label=\"Precision\")\n",
    "    plt.plot(thresholds, recalls[:-1], \"g-\", label=\"Recall\")\n",
    "plot_precision_recall_vs_threshold(precisions, recalls, thresholds)\n",
    "plt.show()\n",
    "\n",
    "plt.plot(recalls[:-1], precisions[:-1])\n",
    "plt.xlabel('Recall')\n",
    "plt.ylabel('Precision')\n",
    "plt.show()\n",
    "\n",
    "\n",
    "\n",
    "#conf = [[330, 29],[34, 27]]\n",
    "ax= plt.subplot()\n",
    "sns.set(font_scale=1.5)\n",
    "sns.heatmap(conf, annot=True, ax = ax, cmap=\"YlGnBu\", fmt='d');\n",
    "ax.set_xlabel('Predicted');\n",
    "ax.set_ylabel('Actual');\n",
    "ax.set_title('Cross-validation');\n",
    "ax.xaxis.set_ticklabels([0, 1]);\n",
    "ax.yaxis.set_ticklabels([0, 1]);\n",
    "plt.tight_layout()\n",
    "plt.savefig('conf_matix.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sig_lllist = [i_val[1] for i, i_val in enumerate(y_probas_MLP_noseed_b_prob) if y_train_all.values.ravel()[i]!=0]\n",
    "bck_lllist = [i_val[1] for i, i_val in enumerate(y_probas_MLP_noseed_b_prob) if y_train_all.values.ravel()[i]!=1]\n",
    "#getPredDist(sig_lllist, bck_lllist)\n",
    "\n",
    "w1 = np.ones_like(bck_lllist)/(len(bck_lllist))\n",
    "w2 = np.ones_like(sig_lllist)/(len(sig_lllist))\n",
    "    \n",
    "#plt.title(variable)\n",
    "plt.hist(bck_lllist, alpha=0.6, label='Negative', bins = 20, range=[mini, maxi], weights=w1)\n",
    "plt.hist(sig_lllist, alpha=0.5, label='Positive', bins = 20, range=[mini, maxi], weights=w2)\n",
    "plt.legend()\n",
    "#plt.savefig('Figs/{}.png'.format(variable.replace(' ', '_').replace('/','')))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\\begin{tabular}{l|l|c|c|c}\n",
      "\\cline{3-4}\n",
      "\\multicolumn{2}{c|}{}& Predicted 0 & Predicted 1 &\\multicolumn{1}{c}{Total}\\\\\n",
      "\\cline{2-4}\n",
      "& Actual 0 & $TN = 315$ & $FP = 44$ & $359$\\\\\n",
      "\\cline{2-4}\n",
      "& Actual 1 & $FN = 12$ & $TP = 49$ & $61$\\\\\n",
      "\\cline{2-4}\n",
      "\\multicolumn{1}{c}{} & \\multicolumn{1}{c}{Total} & \\multicolumn{1}{c}{$327$} & \\multicolumn{    1}{c}{$93$} & \\multicolumn{1}{c}{$420$}\\\\\n",
      "\\end{tabular}\n"
     ]
    }
   ],
   "source": [
    "conf = confusion_matrix(y_train_all, y_probas_MLP_noseed_b)\n",
    "print('\\\\begin{tabular}{l|l|c|c|c}')\n",
    "print('\\\\cline{3-4}')\n",
    "print('\\\\multicolumn{2}{c|}{}& Predicted 0 & Predicted 1 &\\\\multicolumn{1}{c}{Total}\\\\\\\\')\n",
    "print('\\\\cline{2-4}')\n",
    "print('& Actual 0 & $TN = '+str(conf[0][0])+'$ & $FP = '+str(conf[0][1])+'$ & $'+str(conf[0][0]+conf[0][1])+'$\\\\\\\\')\n",
    "print('\\\\cline{2-4}')\n",
    "print('& Actual 1 & $FN = '+str(conf[1][0])+'$ & $TP = '+str(conf[1][1])+'$ & $'+str(conf[1][0]+conf[1][1])+'$\\\\\\\\')\n",
    "print('\\\\cline{2-4}')\n",
    "print('\\\\multicolumn{1}{c}{} & \\\\multicolumn{1}{c}{Total} & \\\\multicolumn{1}{c}{$'+str(conf[1][0]+conf[0][0])+'$} & \\\\multicolumn{    1}{c}{$'+str(conf[0][1]+conf[1][1])+'$} & \\\\multicolumn{1}{c}{$'+str(conf[0][1]+conf[1][1]+conf[0][0]+conf[1][0])+'$}\\\\\\\\')\n",
    "print('\\\\end{tabular}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.4426229508196721\n",
      "0.5901639344262295\n",
      "0.4262295081967213\n",
      "0.5081967213114754\n",
      "0.6229508196721312\n",
      "0.3114754098360656\n",
      "0.36065573770491804\n",
      "0.39344262295081966\n",
      "0.4426229508196721\n",
      "0.5409836065573771\n"
     ]
    }
   ],
   "source": [
    "var_list = []\n",
    "y_scores_MLP_list = []\n",
    "roc_values = []\n",
    "\n",
    "for i_var, variable in enumerate(all_variables):\n",
    "    this_vars = all_variables[:i_var]+all_variables[i_var+1:]\n",
    "    var_list.append(this_vars)\n",
    "    this_score = cross_val_predict(MLP_clf_noseed, X_train_all[this_vars].values, y_train_all.values.ravel(), cv=2)\n",
    "    precisions, recallsles, thresholds = precision_recall_curve(y_train_all, this_score)\n",
    "    print(recallsles[1])\n",
    "    y_scores_MLP_list.append(recallsles[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                        recall\n",
      "Basophils             0.311475\n",
      "Eosinophils           0.360656\n",
      "CRP                   0.393443\n",
      "Platelets             0.426230\n",
      "Patient age quantile  0.442623\n",
      "Hematocrit            0.442623\n",
      "Leukocytes            0.508197\n",
      "Neutrophils           0.540984\n",
      "Hemoglobin            0.590164\n",
      "Monocytes             0.622951\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rank_features = {}\n",
    "for i_var, variable in enumerate(all_variables):\n",
    "    rank_features[variable] = 0\n",
    "\n",
    "times=1\n",
    "for seed in range(times):\n",
    "    for i_var, variable in enumerate(all_variables):\n",
    "        rank_features[variable] = rank_features[variable]+(y_scores_MLP_list[i_var])/times\n",
    "\n",
    "rank_features = pd.DataFrame(data=rank_features.values(), index=rank_features.keys(), columns=['recall'])\n",
    "rank_features = rank_features.sort_values(by='recall')\n",
    "\n",
    "print(rank_features)\n",
    "\n",
    "plt.figure(figsize=(8, 6))\n",
    "rank_features['recall'].plot(kind = \"barh\")\n",
    "plt.vlines(recalls[1],-10,20, colors='r', linestyles='--', label='Recall = {0:.4f}'.format(recalls[1]))\n",
    "#plt.xlim(0.5,0.6)\n",
    "plt.legend()\n",
    "plt.savefig('features_noseed.png',  bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 0 0 0 0 0 1 0 1 1 0 0 1 0 0 0\n",
      " 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 1 0 0 0 0 1 0\n",
      " 1 0 0 0 0 0 1 0 0 0 0 1 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 0 0\n",
      " 1 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 0 0 0 1 0 1 1 1 1 0 0 0 0 0 0 0 0\n",
      " 1 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 0 0 0 0 0 1]\n",
      "Confusion Matrix:\n",
      "[[TN  FP]\n",
      " [FN  TP]] = \n",
      "[[133  26]\n",
      " [  8  14]]\n",
      "\n",
      "Precision: TP/(TP+FP) =  0.35\n",
      "Recall: TP/(TP+FN) =  0.6363636363636364\n",
      "F1 score =  0.45161290322580644\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "y_pred_prob = MLP_clf_noseed.predict_proba(X_test_all)\n",
    "y_pred = (y_pred_prob [:,1] >= threshold).astype('int')\n",
    "print(y_pred)\n",
    "accuracy_score(y_test_all, y_pred)\n",
    "\n",
    "conf = confusion_matrix(y_test_all, y_pred)\n",
    "print(\"Confusion Matrix:\")\n",
    "print(\"[[TN  FP]\")\n",
    "print(\" [FN  TP]] = \")\n",
    "print(conf)\n",
    "print()\n",
    "print(\"Precision: TP/(TP+FP) = \", precision_score(y_test_all, y_pred))\n",
    "print(\"Recall: TP/(TP+FN) = \", recall_score(y_test_all, y_pred))\n",
    "print(\"F1 score = \", f1_score(y_test_all, y_pred))\n",
    "\n",
    "precisions, recalls, thresholds = precision_recall_curve(y_test_all, y_pred)\n",
    "plt.plot(recalls[:-1], precisions[:-1])\n",
    "plt.xlabel('Recall')\n",
    "plt.ylabel('Precision')\n",
    "plt.show()\n",
    "\n",
    "ax= plt.subplot()\n",
    "sns.heatmap(conf, annot=True, ax = ax, cmap=\"YlGnBu\", fmt='d');\n",
    "ax.set_xlabel('Predicted');\n",
    "ax.set_ylabel('Actual');\n",
    "ax.xaxis.set_ticklabels([0, 1]);\n",
    "ax.yaxis.set_ticklabels([0, 1]);\n",
    "plt.tight_layout()\n",
    "plt.savefig('conf_matix.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sig_lllist = [i_val[1] for i, i_val in enumerate(y_pred_prob) if y_test_all.values.ravel()[i]!=0]\n",
    "bck_lllist = [i_val[1] for i, i_val in enumerate(y_pred_prob) if y_test_all.values.ravel()[i]!=1]\n",
    "#getPredDist(sig_lllist, bck_lllist)\n",
    "\n",
    "w3 = np.ones_like(bck_lllist)/(len(bck_lllist))\n",
    "w4 = np.ones_like(sig_lllist)/(len(sig_lllist))\n",
    "    \n",
    "#plt.title(variable)\n",
    "plt.hist(bck_lllist, alpha=0.6, label='Negative (test sample)', bins = 20, range=[mini, maxi], weights=w3)\n",
    "plt.hist(sig_lllist, alpha=0.5, label='Positive (test sample)', bins = 20, range=[mini, maxi], weights=w4)\n",
    "plt.legend()\n",
    "#plt.savefig('Figs/{}.png'.format(variable.replace(' ', '_').replace('/','')))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [],
   "source": [
    "# #best_f1 = ['Hemoglobin', 'Platelets', 'Leukocytes', 'CRP', 'Basophils', 'Lymphocytes', 'Monocytes', 'Neutrophils']\n",
    "# best_f1 = ['Basophils', 'Lymphocytes', 'Leukocytes', 'Platelets']\n",
    "\n",
    "# list1 = [\"Patient age quantile\", \n",
    "#                   \"Hemoglobin\",\n",
    "#                   \"Platelets\", \n",
    "#                   \"Red blood Cells\",\n",
    "#                   \"MCHC\",\n",
    "#                   \"MCH\",\n",
    "#                   \"RDW\",\n",
    "#                   \"MCV\",\n",
    "#                   \"Lymphocytes\",\n",
    "#                   \"Leukocytes\",\n",
    "#                   \"Monocytes\",\n",
    "#                   \"Basophils\",\n",
    "#                   \"Eosinophils\",\n",
    "#                   \"CRP\",\n",
    "#                   \"Hematocrit\",\n",
    "#                   \"Mean platelet volume \",\n",
    "#                   \"Neutrophils\"\n",
    "#                 ]\n",
    "\n",
    "\n",
    "# # a = []\n",
    "# # for i_n, i in enumerate(best_f1):\n",
    "# #     for j_n, j in enumerate(best_f1[i_n:]):\n",
    "# #         for k_n, k in enumerate(best_f1[j_n:]):\n",
    "# #             for l in list1[k_n:]:\n",
    "# #                 if i!=j and i!=k and i!=l and j!=k and j!=l and k!=l:\n",
    "# #                     a.append([i, j, k, l])\n",
    "# #                     print([i, j, k, l])\n",
    "\n",
    "# # print(len(a))                    \n",
    "\n",
    "# a = []\n",
    "# for i_n, i in enumerate(list1):\n",
    "#     if i not in best_f1:\n",
    "#         b = best_f1.copy()\n",
    "#         b.append(i)\n",
    "#         a.append(b)\n",
    "#         print(b)\n",
    "# print()\n",
    "\n",
    "# big_funs = []\n",
    "# for varsvisks in a:\n",
    "#     y_jurema = cross_val_predict(MLP_clf_noseed, X_train_all[varsvisks].values, y_train_all.values.ravel(), cv=2)\n",
    "#     f1 = f1_score(y_train_all, y_jurema)\n",
    "#     if f1>0.4:\n",
    "#         rec = recall_score(y_train_all, y_jurema)\n",
    "#         if rec>0.4:\n",
    "#             print(varsvisks)\n",
    "#     #         conf = confusion_matrix(y_test_all, y_pred)\n",
    "#     #         print(\"Confusion Matrix:\")\n",
    "#     #         print(\"[[TN  FP]\")\n",
    "#     #         print(\" [FN  TP]] = \")\n",
    "#     #         print(conf)\n",
    "#     #         print()\n",
    "#             print(\"Precision: TP/(TP+FP) = \", precision_score(y_train_all, y_jurema))\n",
    "#             print(\"Recall: TP/(TP+FN) = \", rec)\n",
    "#             print(\"F1 score = \", f1)\n",
    "#             print()\n",
    "#             big_funs.append(varsvisks)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1º test\n",
    "\n",
    "['Hemoglobin', 'Platelets', 'Leukocytes']\n",
    "F1 score =  0.43181818181818177\n",
    "\n",
    "['Hemoglobin', 'Leukocytes', 'CRP']\n",
    "F1 score =  0.45360824742268036\n",
    "\n",
    "['Lymphocytes', 'Basophils', 'Leukocytes']\n",
    "F1 score =  0.4719101123595506\n",
    "\n",
    "['Leukocytes', 'Hematocrit', 'Basophils']\n",
    "F1 score =  0.4827586206896552\n",
    "\n",
    "['Basophils', 'CRP', 'Leukocytes']\n",
    "F1 score =  0.441860465116279\n",
    "\n",
    "# 2º test\n",
    "\n",
    "['Basophils', 'Lymphocytes', 'Leukocytes', 'Platelets']\n",
    "Precision: TP/(TP+FP) =  0.42857142857142855\n",
    "Recall: TP/(TP+FN) =  0.6122448979591837\n",
    "F1 score =  0.5042016806722688\n",
    "\n",
    "# 3º test\n",
    "\n",
    "['Basophils', 'Lymphocytes', 'Leukocytes', 'Platelets', 'Red blood Cells']\n",
    "Precision: TP/(TP+FP) =  0.4\n",
    "Recall: TP/(TP+FN) =  0.6122448979591837\n",
    "F1 score =  0.48387096774193544\n",
    "\n",
    "['Basophils', 'Lymphocytes', 'Leukocytes', 'Platelets', 'Eosinophils']\n",
    "Precision: TP/(TP+FP) =  0.4166666666666667\n",
    "Recall: TP/(TP+FN) =  0.5102040816326531\n",
    "F1 score =  0.45871559633027525\n",
    "\n",
    "['Basophils', 'Lymphocytes', 'Leukocytes', 'Platelets', 'Red blood Cells', 'Monocytes']\n",
    "Precision: TP/(TP+FP) =  0.46774193548387094\n",
    "Recall: TP/(TP+FN) =  0.5918367346938775\n",
    "F1 score =  0.5225225225225224\n",
    "\n",
    "# 4º test\n",
    "\n",
    "['Basophils', 'Lymphocytes', 'Leukocytes', 'Platelets', 'Red blood Cells', 'Monocytes', 'Hematocrit', 'Eosinophils', 'Mean platelet volume ']\n",
    "Precision: TP/(TP+FP) =  0.47368421052631576\n",
    "Recall: TP/(TP+FN) =  0.5510204081632653\n",
    "F1 score =  0.5094339622641509"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0]\n"
     ]
    }
   ],
   "source": [
    "my_data = [(23.0-49.0)/15.7, (13.4-13.7)/2.0, (241.0-211.6)/87.4, (4900.0-7048.1)/3350.8, (420.0-570.4)/314.7, (10.0-23.9)/23.5, (250.0-115.5)/179.7, 0, 0, 0]\n",
    "my_data = np.array(my_data).reshape(1, -1)\n",
    "\n",
    "y_pred_prob_my = MLP_clf_noseed.predict_proba(my_data)\n",
    "y_pred_prob_my = (y_pred_prob_my [:,1] >= threshold).astype('int')\n",
    "print(y_pred_prob_my)"
   ]
  }
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