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{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "c07c6518",
   "metadata": {},
   "outputs": [],
   "source": [
    "model_name = 'models/xgboost_third_model_not_2025.json'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "71f7f221",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import xgboost as xgb\n",
    "import sklearn\n",
    "from sklearn.metrics import confusion_matrix, roc_curve, classification_report, auc\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "66144283",
   "metadata": {},
   "outputs": [],
   "source": [
    "xgb_model = xgb.XGBClassifier()\n",
    "xgb_model.load_model(model_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "3063b1bd",
   "metadata": {},
   "outputs": [],
   "source": [
    "table = pd.read_csv('/mnt/d/acoustics-data/scrap_xgb_bird_present/clean-features/combined_features.csv', \n",
    "                    low_memory=False)\n",
    "not_bc = table[table['dataset']!='birdclef']\n",
    "bc = table[table['dataset']=='birdclef']\n",
    "del table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "a4639860",
   "metadata": {},
   "outputs": [],
   "source": [
    "bc['year'] = bc['file_name'].apply(lambda x: int(x.split('-')[1][:4]))\n",
    "bc['bird'] = bc['file_name'].apply(lambda x: x.split('/')[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "ff6ba894",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.05      0.10      0.07      1783\n",
      "           1       0.97      0.94      0.96     59402\n",
      "\n",
      "    accuracy                           0.91     61185\n",
      "   macro avg       0.51      0.52      0.51     61185\n",
      "weighted avg       0.95      0.91      0.93     61185\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# subtable = not_bc[not_bc['dataset'] == 'esc50']\n",
    "subtable = bc[bc['year'] == 2025]\n",
    "X = subtable[[f'feature_{i}' for i in range(24)]].to_numpy()\n",
    "y = subtable['hasbird'].to_numpy()\n",
    "y_pred = xgb_model.predict(X)\n",
    "y_pred_proba = xgb_model.predict_proba(X)[:, 1]\n",
    "print(classification_report(y, y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "0a17bf81",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the confusion matrix\n",
    "cm = confusion_matrix(y, y_pred)\n",
    "plt.figure(figsize=(5, 4))\n",
    "sns.heatmap(cm, annot=True, fmt='d', cmap='Blues', cbar=False)\n",
    "plt.xlabel('Predicted')\n",
    "plt.ylabel('Actual')\n",
    "plt.title('Freefield')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "bbe26523",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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tDYlEgm7dumHgwIE4cOCASvsLCAhAv3790LBhQzg4OGDGjBmYOHGi4v0PI03/8ssvaNCgAfT09NCqVSssXbpU3R+NiIi+glwusPXSE4zffUOpvZKzFfYNrgc9vcy7IKxduxZjx47FH3/88dn+rtomETl5LCcfi4+Ph7W1NeLi4mBlZaX0XkpKCiIiIuDq6qr0aDflTfz3IiJSTUq6DIdvvcSQreGZvh8xu02GfpNhYWEICQnBmDFjcqPEz8rq+/tT+apDMREREakuMVWKSpMPffb93ztXxQ8exZTahBBYtmwZRo4cibS0NFSqVAnt2rXTdKlqwXBDRESko/6Nisea0xHYHvYsw3utKztiUVd3GBvoZ3jv7du38PX1xe7duwEAHTp0QL169TRer7ow3BAREemQNKkcAzeH4cjtjMOSWJoY4MqkFtD/TH8aALhw4QK6du2KR48ewcjICAsWLMDgwYOzHAYkr2G4ISIi0hHDg65g1+XnGdorOFnhx9ol0KNWySy39/f3x5AhQyCVSlGqVCkEBQXBw8NDU+VqDMNNJgpYH+t8i/9ORFTQCSGw8uRD/H74DqTyjL8Tt/vVgWfJQtm+6mJvbw+pVIrOnTvjr7/+grW1tbpLzhUMNx/5MEJuUlKS0tgtlDd9mL9L06NTExHlRW8T01Btekim7x0a2gDlHC0zfe9TiYmJigFlf/jhB5w6dQr16tXLV7ehPsVw8xF9fX3Y2Ngopk8wMzPL1/+4ukoIgaSkJERHR8PGxibD9BdERLpMJhf4eWNohj41v7Ush/buzihWyCxb+5HL5Zg3bx6WLFmC0NBQODs7AwDq16+v9ppzG8PNJxwdHQFkPT8U5Q02NjaKfy8iooJgWOAV7A5X7lPzffWiWNjFXaX9vHr1Cr169cLBgwcBABs2bND6ODbqxHDzCYlEAicnJ9jb2yM9PV3b5dBnGBoa8ooNERUIQghs+ucxJv59M8N7B4fWR3nHrAe0+9SpU6fQrVs3vHjxAiYmJli2bBn69u2rrnLzBIabz9DX1+eXJxERac2zt0moN/d4pu+dGd0427efPpDJZJg9ezYmT54MuVyOChUqICgoCJUrV1ZHuXkKww0REVEes+H8I0zK5ErNlv614FW6cI72uWjRIsVcgL1798by5csVHYl1DcMNERFRHjJxzw1s/OexYrlFRQcs7loNpkZfdzfBz88PgYGBGDRoEHr37v21ZeZpDDdERER5xLR9t5SCzddcqZHJZNi8eTN+/PFH6OnpwdzcHP/88w/09PTUVW6exXBDRESkRSnpMvzvWiRGbr+q1L5roBeqlyiUo32+ePEC3bt3x8mTJxEVFYVRo0YBQIEINgDDDRERkdZM3XcTAWcfZWjPyVNQHxw6dAg//vgjYmJiYGFhgeLFi39llfkPww0REVEuEULgxvN4BJyLyHQOqG41S2BGh8pZTmz5OVKpFBMnTsScOXMAAFWrVkVQUBDc3Ny+uu78huGGiIhIw96lSuE+9XCm8z8BwJrenmhawSHH+3/27Bm6deuGM2fOAAAGDBiAhQsXwsTEJMf7zM8YboiIiDQkJV2GKlMOI00mz/BeRScr9Kvviu+rF/vq40RFReHChQuwsrLCX3/9hS5dunz1PvMzhhsiIiINuPcyAc3/OJWh/diIhihVxOKr9y+EUMx/6OnpiU2bNsHDwwOlS5f+6n3ndww3REREavQqIRVbLz7BwpC7Su3Xp7SApYmhWo7x6NEj+Pj44I8//kC1atUAoMBfrfkYww0REdFXuvI0FgM2hSEyLiXDe03K22OtTw21HWvPnj3o06cPYmNj8fPPP+PChQuKKzj0HsMNERFRDsQmpWHQlss4e//1Z9cZ0qQMhrcop5bjpaWlYdSoUVi8eDEAoFatWti2bRuDTSYYboiIiFTwLlWKYYFXEHLrZYb3qha3wayOlVHJ2Vqtx3z48CG8vb0RGhoKABgxYgRmzZoFIyMjtR5HVzDcEBERZUN0QgraLD6DmHepSu0OVsZY2MUdXqXtNHIV5fbt26hduzbi4+Nha2uL9evX49tvv1X7cXQJww0REVEWXr9LRec/z+Phq0Sl9sIWRtjQtxYqOudsJOHsKleuHGrXro3ExERs3bq1QI44rCqGGyIiokysOvUAs4L/zfS9bT/VRu1Sdho79v379+Hs7AwzMzPo6ekhMDAQ5ubmMDRUz9NWuo7hhoiI6CMvYpPhNedYpu9dndQC1maaDRhbt27FTz/9BG9vb6xevRoAYGNjo9Fj6hqGGyIiIgByuYDPuks4dfeVUvuUdhXhU9dV48dPTk7GkCFDFIHm3r17SE5OhqmpqcaPrWsYboiIqMBLSpOi4qRDSm3VS9hg18C6uXL827dvo0uXLrhx4wYkEgkmTJiASZMmwcCAX9M5wbNGREQFVmKqFB4zQpCSrjz3042pLWFhnDtfkRs2bMCAAQOQlJQEBwcHbNq0Cc2aNcuVY+sqhhsiIipwUtJl+GbKIaTLMs7SfW9maxjq6+VKHW/fvsXw4cORlJSEpk2bYtOmTXB0dMyVY+syhhsiIiowHr56hya/n8z0PXVNaKmKQoUKYcOGDQgLC8O4ceOgr6+fq8fXVRIhRMbYqsPi4+NhbW2NuLg4WFlpdmwCIiLKGy49eoPeay8iKU2W4b2wCc1gZ2GcK3UIIbB27VoULlwY7du3z5Vj6gpVvr955YaIiHRWqlSG9svO4t+oBKX2OqXssLibO+wtTXKtloSEBAwYMACbN2+GjY0Nbt68CWdn51w7fkHCcENERDopNikN7tNClNq+reKE6e0ro5B57s7JdPXqVXTp0gV3796Fvr4+Ro8ezb41GsRwQ0REOuVRTCKO34nG1H23lNpvT2sFU6Pc7dMihMCff/6JoUOHIjU1FcWKFcPWrVtRr169XK2joGG4ISIinTEi6Cp2Xn6Wof3hrDbQ01P/pJZZkUql6NGjB4KCggAAbdu2xfr162Fnp7lpG+g9hhsiIsr3Hr56h/bLziIhVapoq1rcBoMbl0Hzig5aqcnAwACFCxeGgYEB5syZg2HDhkFPL3ceMS/o+LQUERHlWynpMiw5eg8rTjxQaj8+shFcC5vnej1CCCQmJsLC4v0j5SkpKbh58yY8PDxyvRZdw6eliIhIpwkhsP7cI0z5pF9Ny0oO+L2Le66NLvyxt2/fwtfXF7GxsQgJCYG+vj5MTEwYbLSA4YaIiPKVcw9i0P2vC0ptRvp6WNLNHa0qO2mlposXL8Lb2xuPHj2CoaEhLl26hNq1a2ulFmK4ISKifEIuFyg1LjhD++Ku7mjvXlQLFb2/gvTHH39g9OjRkEqlKFWqFAIDA+Hp6amVeug9hhsiIsrzXsQmw2vOMaW2mR0ro0etklqqCHjz5g18fHywb98+AECnTp2wevVqWFtba60meo/hhoiI8rTd4c8wLPCqUtudGa1gbKDdeZi6d++OQ4cOwdjYGH/88Qf8/PwgkeTu4+aUOYYbIiLKk1LSZSg/8aBSm3txG+wZVFdLFSmbP38+oqKisG7dOri7u2u7HPoIww0REeUpz94mocPyc4h5l6rUvqRbNXxXVXtzMb169QqnT5/G999/DwD45ptvcPnyZY5dkwcx3BARUZ5x80Uc2i45o9TmZG2C82Obaqmi906dOoVu3bohOjoap0+fVjwJxWCTNzHcEBGR1gWcjcgwF1RJOzNs7FsLJezMtFQVIJPJMHv2bEyePBlyuRzly5dXDNBHeRfDDRERac396AQ0W3gqQ/vIFm4Y3KSsFir6z8uXL9GjRw8cPXoUANCrVy8sX76c4SYfYLghIqJcJYTA/uuRGLfrOuJTpErv/dayHHzrucLEULtPQh07dgzdu3fHy5cvYWZmhuXLl8PHx0erNVH2MdwQEVGueRmfggbzjiNVKldq71azBGZ//42Wqsro+vXrePnyJSpVqoSgoCBUrFhR2yWRChhuiIgoV8w7+G+GCS7bVnHCzA6VYWNmpKWq/iOEUIxTM2TIEBgaGsLHxwdmZtrr80M5w3BDREQaI5MLbLnwGBP/vqnU3qhcESztVg2WJoZaqkzZ4cOHMX36dAQHB8PS0hISiQQDBw7UdlmUQww3RESkEZkNwgcAW/rVgleZwlqoKCOpVIpJkyZh9uzZAIA5c+Zg5syZWq6KvhbDDRERqZVMLjBu13UEhj5Vah/SpAyGtyinpaoyevbsGbp164YzZ96Pq+Pn54eJEydquSpSB62PPrRixQq4urrCxMQEHh4eOH36dJbrb968GVWrVoWZmRmcnJzQp08fvH79OpeqJSKirDx7m4TS44IzBJsHs9rkqWCzf/9+uLu748yZM7C0tERgYCD8/f1hYmKi7dJIDbQabgIDAzF06FCMHz8e4eHhqF+/Plq3bo0nT55kuv6ZM2fQq1cv+Pr64ubNm9i+fTsuXbqEfv365XLlRET0MSEEWi06hXpzjyu1T29fCY/mtIW+Xt6ZUHLt2rX49ttv8fr1a1SvXh3h4eHo0qWLtssiNZIIIYS2Dl6rVi1Ur14d/v7+irYKFSqgQ4cOivufH1uwYAH8/f3x4MF/ve2XLl2KefPm4enTpxnWz0x8fDysra0RFxcHKyurr/8QREQF3PPYZNSdc0ypraFbEazvW1NLFWXt5cuXqFatGjp16oT58+fD2NhY2yVRNqjy/a21PjdpaWkICwvDmDFjlNpbtGiBc+fOZbqNl5cXxo8fj+DgYLRu3RrR0dHYsWMH2rZt+9njpKamIjX1v8nX4uPj1fMBiIgKuHSZHGXHH8jQHj6xOQqZa//R7o9duXJFMXO3g4MDbty4AVtbW+0WRRqjtdtSMTExkMlkcHBwUGp3cHBAVFRUptt4eXlh8+bN8Pb2hpGRERwdHWFjY4OlS5d+9jizZ8+GtbW14lW8eHG1fg4iooLoeWxyhmDTsVpRPJrTNk8Fm7S0NAwdOhTVqlXD1q1bFe0MNrpN6x2KPwyY9MHHgyh96tatWxgyZAgmTZqEsLAwHDx4EBEREfDz8/vs/seOHYu4uDjFK7u3r4iIKHNCiAy3oW5Na4k/vN21U9BnPHz4EHXr1sXixYsBALdv39ZyRZRbtHZbqnDhwtDX189wlSY6OjrD1ZwPZs+ejbp16+K3334DAFSpUgXm5uaoX78+ZsyYAScnpwzbGBsb834qEZGaRCekoObMo4rlxuWKYK1Pjc/+UaotO3bsgK+vL+Lj41GoUCGsX78e7dq103ZZlEu0duXGyMgIHh4eCAkJUWoPCQmBl5dXptskJSVBT0+5ZH3995OrabFfNBGRzktJl2HQ5stKwQYAAvrUzFPBJiUlBYMGDULnzp0RHx8PLy8vXLlyhcGmgNHqIH7Dhw9Hz5494enpiTp16mDVqlV48uSJ4jbT2LFj8fz5c2zYsAEA0K5dO/Tv3x/+/v5o2bIlIiMjMXToUNSsWRPOzs7a/ChERDor5l0qPGccUWpzLWyOI8Mbaqmizzt37hxWrFgBABg9ejSmT58OQ8O8McUD5R6thhtvb2+8fv0a06ZNQ2RkJCpXrozg4GCULFkSABAZGak05o2Pjw8SEhKwbNkyjBgxAjY2NmjSpAnmzp2rrY9ARKTzZvzvluJnIwM9HB3eEMVt8+Zkkk2aNMGMGTNQvXp1tG7dWtvlkJZodZwbbeA4N0RE2Td+93VsvvD+j0xnaxOcG9tUyxUpS05Oxrhx4zB06FDFH8akm/LFODdERJS3PX2TpAg2ALCyp4cWq8no33//RZcuXXD9+nVcunQJp0+fzlP9f0h7tP4oOBER5U1d/jyv+PniuKaoUsxGe8V8YsOGDfDw8MD169dhb2+PKVOmMNiQAsMNERFlkCqVITIuBQBQ1MYU9lZ5Y0LJxMRE9OnTB71790ZSUhKaNGmCK1euoFmzZtoujfIQ3pYiIiKFqLgU1J6t/Lj34q7u2inmE48fP0abNm1w69Yt6OnpYfLkyRg/frxiSBCiDxhuiIgIQgisOPEA8w/dUWp3LWwOj5KFtFSVMgcHBxgaGsLJyQlbtmxBo0aNtF0S5VEMN0REBZwQAq5jg5Xa7C2N8b8h9WBvqd3bUe/evYOpqSn09fVhYmKCXbt2wcLCAvb29lqti/I29rkhIirgXsanKi1v6FsTF8c303qwuXr1Kjw8PDBjxgxFW6lSpRhs6IsYboiICrDYpDTUmfNfH5tHc9qigVsRLVb0/krSn3/+iVq1auHu3btYu3YtEhMTtVoT5S8MN0REBdTbxDS4TwvBh6Fcy9hbaLcgvB+orVu3bvDz80NqairatGmDsLAwmJuba7s0ykcYboiICqC45HRUm648cfH+IfW0VM17ly9fRvXq1REYGAgDAwPMnz8f+/btQ+HChbVaF+U/7FBMRFTA9Fj9D87ef61YtjY1xJVJzbU6CF58fDyaNGmCuLg4lChRAoGBgahdu7bW6qH8jeGGiKiAyOypqLpl7LC5n/ZDhJWVFebPn4/9+/dj7dq1sLW11XZJlI9x4kwiIh33LlWKMTuv4X/XIpXaQ4Y1QFkHSy1VBVy8eBESiQQ1atQA8D58AeA0CpQpTpxJREQAgBvP4/Dt0jMZ2u/PbA0Dfe10uxRC4I8//sDo0aNRtGhRhIeHo1ChQgw1pDYMN0REOurCw9fwXvWPYtlQX4I1vWto9VHvN2/ewMfHB/v27QMAeHp6Qk+Pz7aQejHcEBHpoGdvk5SCzZjW5eHXsLQWKwLOnTuHrl274unTpzAyMsIff/yBAQMG8IoNqR3DDRGRjmmz+DRuRcYrlie0rYB+9UtprR65XI4FCxZg3LhxkMlkKFOmDIKCglCtWjWt1US6jdcCiYh0hFwuMGjzZaVg07FaUa0GG+B9B+GzZ89CJpOha9euCAsLY7AhjeKVGyIiHbH/eiT2X//viai7M1rDyEB7f8MKISCRSCCRSBAQEIB9+/ahV69evA1FGscrN0REOiAuKR2/bA1XLO8a6KW1YCOXyzFz5kz06dNH8Xi3ra0tevfuzWBDuYJXboiI8rm/rzzHr9uuKJanta+E6iUKaaWWly9fomfPnggJeT+1Q+/evdG4cWOt1EIFF8MNEVE+9u3S07jx/L8+Nu7FbdCrjotWajl27Bh69OiBqKgomJqaYvny5WjUqJFWaqGCjeGGiCif+nVbuFKwGd2qPAY0yv3HvWUyGaZPn45p06ZBCIGKFSti+/btqFixYq7XQgQw3BAR5UtBl57i7ysvFMuhE5qhsIWxVmrp2bMntm7dCgDo27cvli5dCjMzM63UQgSwQzERUb7z88ZQjNp5TbF8YmQjrQUbAPD19YWVlRU2btyINWvWMNiQ1vHKDRFRPrLlwhMcuvlSsTy4cRm4FDbP1RqkUilu3ryJqlWrAgCaNm2KR48eoVAh7XRiJvoUww0RUT4w58C/WHnygVLbhXFN4WBlkqt1PHv2DN27d8eVK1dw+fJllClTBgAYbChP4W0pIqI8buDmsAzBZodfnVwPNsHBwXB3d8fp06cBAPfv38/V4xNlF6/cEBHlUdeexeK7ZWeV2gJ/qo1apexytY709HSMHz8e8+fPBwBUr14dgYGBiqs2RHkNww0RUR40LPAKdoc/V2o7PaoxitvmbmfdJ0+eoGvXrjh//jwAYPDgwViwYAGMjbXXgZnoSxhuiIjykBFBV7Hz8jOlNq/Sdtjcr5ZWpi5YtWoVzp8/D2tra6xZswY//PBDrtdApCqGGyKiPOD1u1R4zDiSof2fsU3haJ27fWs+NmnSJMTExGD06NFwdXXVWh1EqmC4ISLSIiEEyk88iFSpXKl9TW9PNClvn+tXayIiIjBv3jwsWbIEhoaGMDIywsqVK3O1BqKvlaNwI5VKceLECTx48ADdu3eHpaUlXrx4ASsrK1hYWKi7RiIinZQuk6PvuktKwaa8oyX2DKoLE0P9XK9n586d8PX1RVxcHOzt7TF16tRcr4FIHVQON48fP0arVq3w5MkTpKamonnz5rC0tMS8efOQkpLChE9ElA1yuUDZ8QeU2h7MagN9vdzvV5OSkoKRI0di+fLlAIA6derA19c31+sgUheVx7n59ddf4enpibdv38LU1FTR3rFjRxw9elStxRER6aItF56g1LhgpbZzY5poJdjcv38fXl5eimAzatQonDx5EiVKlMj1WojUReUrN2fOnMHZs2dhZGSk1F6yZEk8f/78M1sREVFKugw/bwzDybuvlNojZrfRypNQwcHB6Nq1KxISEmBnZ4cNGzagTZs2uV4HkbqpHG7kcjlkMlmG9mfPnsHS0lItRRER6ZoPHYc/NveHb+BdQ3tXSEqXLg25XI769etjy5YtKFasmNZqIVInlW9LNW/eHIsWLVIsSyQSvHv3DpMnT2biJyL6hFwuMHL7VbiOVb4NdWFcU60Em9jYWMXP5cqVw+nTp3Hs2DEGG9IpEiGEUGWDFy9eoHHjxtDX18e9e/fg6emJe/fuoXDhwjh16hTs7e01VataxMfHw9raGnFxcbCystJ2OUSko4QQWHTkHhYfvafUbmlsgOtTW2qlpk2bNmHQoEHYu3cvGjZsqJUaiHJKle9vlW9LOTs748qVK9i2bRvCwsIgl8vh6+uLHj16KHUwJiIqyPw2heHQzZdKbWETmsHOIvenLUhKSsLgwYMREBAA4P2owww3pMtUvnJz6tQpeHl5wcBAORdJpVKcO3cODRo0UGuB6sYrN0SkSclpMlSYpNy35n+/1EPlotZaqefmzZvo0qULbt26BYlEgsmTJ2PChAnQ18/9cXSIvoYq398q97lp3Lgx3rx5k6E9Li4OjRs3VnV3REQ6I00qzxBsTv3WWCvBRgiBgIAA1KhRA7du3YKjoyOOHj2KyZMnM9iQzlP5tpQQItNHFl+/fg1zc3O1FEVElB+5TVAelE9bj3gDwPHjx9G3b18A7x8E2bRpU57vE0mkLtkON99//z2A909H+fj4KE13L5PJcO3aNXh5eam/QiKifKD9sjNKy/9Ob6W1YAO8v8reo0cPVKxYEWPGjIGensoX6onyrWyHG2vr95dVhRCwtLRU6jxsZGSE2rVro3///uqvkIgojzt97xWuPotTLN+d0RpGBrkbJoQQ2LhxI9q1a4dChQpBIpFg48aNWg1YRNqS7XDzoZe9i4sLRo4cyVtQRET/b/LfNxU/X5vSIteDTXx8PH7++Wds27YNHTt2xM6dOyGRSBhsqMBSuc/N5MmTNVEHEVG+8+u2cPx95YViub27M6xMDHO1hvDwcHTp0gX379+Hvr4+6tSp89m+kUQFhcrhBgB27NiBoKAgPHnyBGlpaUrvXb58WS2FERHlZevORigFGwCY+0OVXDu+EAIrVqzA8OHDkZaWhhIlSmDbtm2oU6dOrtVAlFepfO10yZIl6NOnD+zt7REeHo6aNWvCzs4ODx8+ROvWrTVRIxFRnjNl3y3FzwF9auDujNYwMcydR6xjY2PRuXNnDB48GGlpafjuu+8QHh7OYEP0/1QONytWrMCqVauwbNkyGBkZYdSoUQgJCcGQIUMQFxf35R0QEeVj96MT4DJmv2K5b11XNC5nn6v9bGQyGS5evAhDQ0P88ccf2LNnD2xtbXPt+ER5ncq3pZ48eaJ45NvU1BQJCQkAgJ49e6J27dpYtmyZeiskIsoj0mVyNFt4SqltdOtyuXLsD4PJSyQS2NnZYfv27dDT00ONGjVy5fhE+YnKf2o4Ojri9evXAICSJUvin3/+AQBERERAxZkciIjyjZR0GcqO/2+QPq/Sdrg7ozWMDTR/K+rNmzfo0KGD4qlVAKhVqxaDDdFnqBxumjRpgn379gEAfH19MWzYMDRv3hze3t7o2LGj2gskItI2IQTKT/xvWoUaLoWwpX/tXLkVdf78eVSrVg179+7FiBEjEB8fr/FjEuV3Kt+WWrVqFeRyOQDAz88Ptra2OHPmDNq1awc/Pz+1F0hEpG19111S/GxrboTtfpofjV0ul+P333/HuHHjIJVKUbp0aQQFBXHCX6JsUHlW8Kw8f/4cRYsWVdfuNIKzghORKsbuuoatF58qlh/NaavxY8bExKB3794IDg4GAHh7e2PVqlX8nUUFmkZnBc9MVFQUfvnlF5QpU0blbVesWAFXV1eYmJjAw8MDp0+fznL91NRUjB8/HiVLloSxsTFKly6NtWvX5rR0IqLPGrXjqlKwuTdT88NdvHv3Dh4eHggODoaxsTH+/PNPbN26lcGGSAXZDjexsbHo0aMHihQpAmdnZyxZsgRyuRyTJk1CqVKl8M8//6gcMgIDAzF06FCMHz8e4eHhqF+/Plq3bo0nT558dpsuXbrg6NGjWLNmDe7cuYOtW7eifPnyKh2XiOhL7r5MQFDoM8XyhXFNYaiv+T42FhYW6N27N8qVK4eLFy/ip59+4mjDRCrK9m2pgQMHYt++ffD29sbBgwdx+/ZttGzZEikpKZg8eTIaNmyo8sFr1aqF6tWrw9/fX9FWoUIFdOjQAbNnz86w/sGDB9G1a1c8fPgwx2M68LYUEWXlVUIqGsw7juR0maLtf7/UQ+Wi1ho7ZnR0NJKSkuDi4gIAkEqlSElJgYWFhcaOSZTfaOS21P79+xEQEIAFCxZg7969EELAzc0Nx44dy1GwSUtLQ1hYGFq0aKHU3qJFC5w7dy7Tbfbu3QtPT0/MmzcPRYsWhZubG0aOHInk5OTPHic1NRXx8fFKLyKizMjkAjVmHlEKNmNbl9dosDl+/DiqVq2KH374AampqQAAAwMDBhuir5Dtp6VevHiBihUrAgBKlSoFExMT9OvXL8cHjomJgUwmg4ODg1K7g4MDoqKiMt3m4cOHOHPmDExMTLB7927ExMRg4MCBePPmzWdvic2ePRtTp07NcZ1EVHDMDr6t+NnO3AiXxjeDnp5mbgnJZDLMmDED06ZNg1wuh62tLaKjo1G8eHGNHI+oIMn2lRu5XA5Dw/9mu9XX14e5uflXF/DpveSsZrOVy+WQSCTYvHkzatasiTZt2mDhwoVYt27dZ6/ejB07FnFxcYrX06dPM12PiAq2FSfuY/WZCMVy6ATNBZvIyEi0aNECU6ZMgVwuR58+fXDx4kUGGyI1yfaVGyEEfHx8YGxsDABISUmBn59fhoCza9eubO2vcOHC0NfXz3CVJjo6OsPVnA+cnJxQtGhRWFv/d4m4QoUKEELg2bNnKFu2bIZtjI2NFTUTEWXm2L8vMe/gHcXykm7VNNaJNyQkBD/++COio6Nhbm4Of39/9OzZUyPHIiqosh1uevfurbT8448/ftWBjYyM4OHhgZCQEKWRjUNCQtC+fftMt6lbty62b9+Od+/eKe5H3717F3p6eihWrNhX1UNEBdPiI/fwx5G7iuW9g+uiSjEbjRxLCIFJkyYhOjoa33zzDYKCgvi0J5EGqHUQP1UFBgaiZ8+eWLlyJerUqYNVq1bhr7/+ws2bN1GyZEmMHTsWz58/x4YNGwC8H/+hQoUKqF27NqZOnYqYmBj069cPDRs2xF9//ZWtY/JpKSICgPiUdFSZclipbUaHyvixdkmNHjciIgKLFy/G7NmzYWpqqtFjEekSVb6/VZ5+QZ28vb3x+vVrTJs2DZGRkahcuTKCg4NRsuT7Xy6RkZFKY95YWFggJCQEv/zyCzw9PWFnZ4cuXbpgxowZ2voIRJQP7b36AkO2hiu1/T2oLqoWt1H7sQ4cOICrV69izJgxAABXV1csWrRI7cchov9o9cqNNvDKDVHBdvzfaPT5aK4oALg1rSXMjNT7t156ejomTJiAefPmAQBOnDiRo2EziOi9fHPlhogoN/mfeIC5B/9VLE/6tiL61nNV+3GePHmCrl274vz58wCAQYMGoVatWmo/DhFljuGGiHRemlQOtwkHlNqmflcJvb1c1H6svXv3wsfHB2/fvoW1tTXWrFmDH374Qe3HIaLPY7ghIp326dUaAAjoUwONy9mr/VgTJkzAzJkzAQA1atTAtm3bUKpUKbUfh4iylqNZ4DZu3Ii6devC2dkZjx8/BgAsWrQIf//9t1qLIyL6Gjeex2UINvdnttZIsAGAcuXKAQCGDh2KM2fOMNgQaYnK4cbf3x/Dhw9HmzZtEBsbC5ns/RwsNjY2fAKAiPKM+JR0fLv0jGJ510AvPJrTFgZqntn77du3ip979uyJsLAw/PHHHzAyMlLrcYgo+1T+v3zp0qX466+/MH78eOjr6yvaPT09cf36dbUWR0SkqpR0GQ7djFIaw2ZIkzKoXqKQWo+TmpqKX375Bd988w1evXqlaK9evbpaj0NEqlO5z01ERASqVauWod3Y2BiJiYlqKYqISFUPXr3D9yvOIS45Xam9aXl7DG9RTq3Hun//Pry9vXH58mUAwP79++Hj46PWYxBRzqkcblxdXXHlyhXFQHsfHDhwQDFrOBFRbvLbGIaDN6MytA9oVBqjW6l3eoOgoCD069cPCQkJsLOzw/r169G2bVu1HoOIvo7K4ea3337DoEGDkJKSAiEELl68iK1bt2L27NlYvXq1JmokIvqsxFSpUrD5pqg1AvrUQGEL9U6Ym5ycjGHDhuHPP/8EANSrVw9bt27lvHZEeZDK4aZPnz6QSqUYNWoUkpKS0L17dxQtWhSLFy9G165dNVEjEVGm0mVyeMwIUSyHTmim9lDzwbRp0/Dnn39CIpFg7NixmDp1KgwMOJoGUV70VdMvxMTEQC6Xw95eM49VagKnXyDSDS/jU1Br1lGltkdzNHd7KC4uDq1bt8aUKVPQokULjR2HiDKnyve3yk9LTZ06FQ8ePAAAFC5cOF8FGyLSDQ9evcsQbEInNFPrMZKSkuDv748Pf/9ZW1vj7NmzDDZE+YDK4Wbnzp1wc3ND7dq1sWzZMqVHIImINOldqhSeM0LQ9PeTirYaLoXwaE5btd6OunXrFmrWrImBAwdixYoVinaJRKK2YxCR5qgcbq5du4Zr166hSZMmWLhwIYoWLYo2bdpgy5YtSEpK0kSNRESIiElE5cmHEPMuTdFWqog5tvt5qfU469atQ40aNXDz5k04OjqiQoUKat0/EWneV/W5AYCzZ89iy5Yt2L59O1JSUhAfH6+u2jSCfW6I8heZXKD0uOAM7SdGNoJLYXO1Hefdu3cYNGgQNmzYAABo1qwZNm3aBAcHB7Udg4hyTqN9bj5lbm4OU1NTGBkZIT09/csbEBGpoNfaC0rL/eu74tGctmoNNtevX0eNGjWwYcMG6OnpYcaMGTh06BCDDVE+laPnGCMiIrBlyxZs3rwZd+/eRYMGDTBlyhR07txZ3fURUQEkhEDnlecRGZeC57HJivaI2W000u8lLi4O9+7dg7OzM7Zu3YoGDRqo/RhElHtUDjd16tTBxYsX8c0336BPnz6KcW6IiNQhMVWKSpMPZWgPGdZArcFGCKHYX7169bBt2zY0bNgQRYoUUdsxiEg7VA43jRs3xurVq1GpUiVN1ENEBVzbJaeVlgP61EAtV1uYGalvwLzw8HD07dsXmzdvVkwb06lTJ7Xtn4i066s7FOc37FBMlDdFxiWj4/JziIpPUbSpe1A+IQT8/f0xbNgwpKWloVWrVjhw4IBaj0FEmqHK93e2/hQaPnw4pk+fDnNzcwwfPjzLdRcuXJj9SomI/l/gpadKwebf6a3Uuv+4uDj069cPO3bsAAC0a9cOAQEBaj0GEeUN2Qo34eHhiiehwsPDNVoQERUsd6IS0HLRKcVyCVszHBvREAb6X/0wp0JoaCi6dOmCiIgIGBoaYu7cuRg6dCgH5SPSUdkKN8ePH8/0ZyKir1F3zjGlp6EAYGbHymoNNufPn0fDhg2Rnp4OFxcXBAYGombNmmrbPxHlPSr/Bunbty8SEhIytCcmJqJv375qKYqIdFtSmhS/bb+qFGxK2pkhbEIz1C+r3qeVatSogdq1a+P7779HeHg4gw1RAaByh2J9fX1ERkZmmDAzJiYGjo6OkEqlai1Q3dihmEi7fvA/h7DHb5XaHs5qAz099d0iunz5MipVqgRj4/fzTSUkJMDCwoK3oYjyMY2MUBwfH4+4uDgIIZCQkID4+HjF6+3btwgODuYM4UT0Wa8SUuEyZr9SsDE20MPewXXVFmzkcjkWLFiAWrVqYdSoUYp2S0tLBhuiAiTbA0fY2NhAIpFAIpHAzc0tw/sSiQRTp05Va3FEpBtS0mWoMfOIUtudGa1gbKCvtmPExMTAx8cH+/fvBwC8fPkSMpkM+vrqOwYR5Q/ZDjfHjx+HEAJNmjTBzp07YWtrq3jPyMgIJUuWhLOzs0aKJKL8a/OFxxi/+4ZiuZCZIcImNFfrbagzZ86ga9eueP78OYyNjbF48WL89NNPvFpDVEBlO9w0bNgQwPt5pUqUKMFfGkSUpeexyWi+8CSS0mSKtnplCmNTv1pqO4ZcLsfcuXMxceJEyGQyuLm5ISgoCFWrVlXbMYgo/8lWuLl27RoqV64MPT09xMXF4fr1659dt0qVKmorjojyp0uP3qDzyvNKbcu6V8O3VdR7dffFixeYM2cOZDIZevToAX9/f1haWqr1GESU/2TraSk9PT1ERUXB3t4eenp6kEgkyGwziUQCmUyWyR7yDj4tRaQ5D169Q4dlZ5GQ+t9Tk7bmRjg+ohGszQw1cszdu3fj7du36NOnD68oE+kwtU+/EBERoZgpNyIi4usrJCKdk5QmRdPfTyq1NSpXBAE+NdQWOmQyGWbNmoWaNWuiZcuWAICOHTuqZd9EpDuyFW5KliyZ6c9ERABw9PZL+K4PVSwXtTHF0RENYWKovieVoqKi0KNHDxw7dgyFCxfG3bt3UahQIbXtn4h0h8ojFK9fv17xqCUAjBo1CjY2NvDy8sLjx4/VWhwR5W1RcSlwGbNfKdgAUHuwOXLkCKpWrYpjx47B3NwcCxcuZLAhos9SOdzMmjULpqamAN7P2bJs2TLMmzcPhQsXxrBhw9ReIBHlTQeuR6L27KNKbYMal8ajOW3VFmykUikmTpyIFi1aIDo6Gt988w1CQ0PRs2dPteyfiHRTth8F/+Dp06coU6YMAGDPnj3o1KkTfvrpJ9StWxeNGjVSd31ElMfI5QKlxwfj42cK+tR1weR2ldR6nKSkJLRu3RqnTr2fMfynn37CokWLFH9cERF9jspXbiwsLPD69WsAwOHDh9GsWTMAgImJCZKTk7PalIjyucBLT1BqnHKwWdqtmtqDDQCYmZnB1dUVFhYW2Lp1K/78808GGyLKFpWv3DRv3hz9+vVDtWrVcPfuXbRt2xYAcPPmTbi4uKi7PiLKIxYcuoNlx+8rtal7wsv09HQkJSXB2toaALB8+XJMmDBBcbWYiCg7VL5ys3z5ctSpUwevXr3Czp07YWdnBwAICwtDt27d1F4gEWnf7ODbSsFmYZeqeDSnrVqDzdOnT9GoUSN069YNcrkcAGBubs5gQ0Qqy9YgfrqEg/gRZY9UJse3S8/g36gEpfY9g+rCvbiNWo+1b98++Pj44M2bN7CyssKFCxdQvnx5tR6DiPI3tQ/i96nY2FisWbMGt2/fhkQiQYUKFeDr66u4lExE+ZtMLlBm/AGlNmMDPZz8rTEcrU3Udpy0tDSMHTsWCxcuBAB4enoiMDAQpUqVUtsxiKjgUfnKTWhoKFq2bAlTU1PUrFkTQgiEhoYiOTkZhw8fRvXq1TVVq1rwyg1R5lLSZdh68Qn+efgah26+VHrvwrimcLBSX6gBgEePHsHb2xsXL14EAAwdOhRz5syBsbGxWo9DRLpBle9vlcNN/fr1UaZMGfz1118wMHh/4UcqlaJfv354+PCh4rHNvIrhhkhZcpoMs4JvY+M/GQfhNDXUx+3prdR+TCEEatSogbCwMNjY2GDdunVo37692o9DRLpDo+HG1NQU4eHhGe6H37p1C56enkhKSlK94lzEcEP0nz3hzzE08EqG9i6exdCrjgsqF9XcrebQ0FCMGDECGzZs4LQuRPRFGu1zY2VlhSdPnmQIN0+fPoWlpaWquyMiLYmOT1EKNi52ZvizpyfKOWrm/+MHDx4gPDwcnTp1AvC+f82JEyc4kzcRqZ3K4cbb2xu+vr5YsGABvLy8IJFIcObMGfz22298FJwon/BddwlH/41WLK/vWxMN3Ypo7Hjbt29Hv379kJKSgtKlS6NatWoAwGBDRBqhcrhZsGABJBIJevXqBalUCgAwNDTEgAEDMGfOHLUXSETqE5+SjipTDiu1lbG30FiwSUlJwfDhw+Hv7w8AqFevHooU0VyIIiICvmKcm6SkJDx48ABCCJQpUwZmZmbqrk0j2OeGCqqnb5JQf95xpbZrU1rAysRQI8e7e/cuunTpgqtXr0IikWDs2LGYOnWq4kEEIiJVqPL9ne0RipOSkjBo0CAULVoU9vb26NevH5ycnFClSpV8E2yICiohhFKwKWRmiEdz2mos2GzZsgXVq1fH1atXUaRIERw8eBAzZ85ksCGiXJHtcDN58mSsW7cObdu2RdeuXRESEoIBAwZosjYiUpPlH02dULeMHS6Ma6bR4z169AiJiYlo1KgRrly5ghYtWmj0eEREH8v2n1G7du3CmjVr0LVrVwDAjz/+iLp160Imk0FfX19jBRJRzkXEJKLxghNKbZv71dbIseRyOfT03v+9NGbMGDg7O6Nnz578/UBEuS7bV26ePn2K+vXrK5Zr1qwJAwMDvHjxQiOFEVHORcYlo/r0kAzBZmGXqho53vr16+Hl5aUY50pPTw8+Pj4MNkSkFdkONzKZDEZGRkptBgYGiiemiChvuPI0FnVmH8ObxDRFm72lMa5NaYHvqxdT67ESExPRu3dv+Pj44MKFC/jzzz/Vun8iopzI9m0pIQR8fHyU5n1JSUmBn58fzM3NFW27du1Sb4VElG2rTz/EjP23Fctl7S2wa6AXLDXQcfj69evo0qUL/v33X+jp6WHatGkYMmSI2o9DRKSqbIeb3r17Z2j78ccf1VoMEeXcvZcJSsHm16ZlMay5m9qPI4TAmjVr8MsvvyAlJQXOzs7YunUrGjRooPZjERHlRLbDTUBAgCbrIKKvkCqVofkf/01a+79f6mlsXqg5c+Zg3LhxAIDWrVtj/fr1HJiPiPKUbPe50ZQVK1bA1dUVJiYm8PDwwOnTp7O13dmzZ2FgYAB3d3fNFkiUxwkhUG7CQcVyt5rFNTrhZc+ePeHo6Ii5c+fif//7H4MNEeU5Wg03gYGBGDp0KMaPH4/w8HDUr18frVu3xpMnT7LcLi4uDr169ULTpk1zqVKivCso9KniZxszQ8z+vopa9y+EwNmzZxXLxYoVw7179zBq1CjFo99ERHmJVn8zLVy4EL6+vujXrx8qVKiARYsWoXjx4op5aD7n559/Rvfu3VGnTp1cqpQob4pLTsfondcVy5cnNFfv/uPi0KVLF9SrVw9///23ot3CwkKtxyEiUiethZu0tDSEhYVlGLm0RYsWOHfu3Ge3CwgIwIMHDzB58mRNl0iU540Iuqr4+ffOVaGnp75ZtkNDQ1G9enXs2LEDhoaGiIyMVNu+iYg0SWsTvcTExEAmk8HBwUGp3cHBAVFRUZluc+/ePYwZMwanT5/O9hw1qampSE1NVSzHx8fnvGiiPOQH/3MIe/wWAGCoL8EPHuoZw0YIgSVLluC3335Deno6XFxcEBgYiJo1a6pl/0REmpajKzcbN25E3bp14ezsjMePHwMAFi1apHTZOrskEuW/NIUQGdqA94MIdu/eHVOnToWbW/Yfb509ezasra0Vr+LFi6tcI1FeU3fOMUWwAYADv6rnMey3b9/i+++/x9ChQ5Geno7vv/8e4eHhDDZElK+oHG78/f0xfPhwtGnTBrGxsZDJZAAAGxsbLFq0KNv7KVy4MPT19TNcpYmOjs5wNQcAEhISEBoaisGDB8PAwAAGBgaYNm0arl69CgMDAxw7dizT44wdOxZxcXGK19OnTzNdjyi/mH3gNp7HJiuWb0xtiTL26ukDc+rUKezZswdGRkZYunQpduzYARsbG7Xsm4got6gcbpYuXYq//voL48ePV5o3xtPTE9evX89iS2VGRkbw8PBASEiIUntISAi8vLwyrG9lZYXr16/jypUripefnx/KlSuHK1euoFatWpkex9jYGFZWVkovovzq7P0Y/HnyoWL5yqTmsDBW393l9u3bY8aMGTh37hwGDx6c6VVUIqK8TuXfihEREahWrVqGdmNjYyQmJqq0r+HDh6Nnz57w9PREnTp1sGrVKjx58gR+fn4A3l91ef78OTZs2AA9PT1UrlxZaXt7e3uYmJhkaCfSRdP23cLasxGK5aMjGsLGzCiLLb7s9evXGDFiBGbPng0nJycAwPjx479qn0RE2qZyuHF1dcWVK1dQsmRJpfYDBw6gYsWKKu3L29sbr1+/xrRp0xAZGYnKlSsjODhYse/IyMgvjnlDpOui41NQc9ZRpbaVP3qgdJGvuxV19uxZdO3aFc+ePUN0dDSCg4O/an9ERHmFRAghVNkgICAAEydOxO+//w5fX1+sXr0aDx48wOzZs7F69Wp07dpVU7WqRXx8PKytrREXF8dbVJTnxbxLheeMI0ptZ0Y3RrFCZjnep1wux7x58zBhwgTIZDK4ubkhKCgIVatW/dpyiYg0RpXvb5Wv3PTp0wdSqRSjRo1CUlISunfvjqJFi2Lx4sV5PtgQ5RcPX73D8uMPsPPyM0Vb43JFENDn655aevXqFXr16oWDB99P19CjRw/4+/vD0tLyq/ZLRJSXqHzl5mMxMTGQy+Wwt7dXZ00axSs3lNe9TUxDtenKHe39GpbGmNblv2q/N27cQMuWLfHixQuYmppi2bJl6NOnDzsNE1G+oNErNx8rXLjw12xORJ+4HRmP1ov/mzy2opMV+tZzRSc1DNDn4uICKysrWFtbIygoiB3xiUhn5ahDcVZ/6T18+PCz7xHR50llcqVgU6qIOYJ/rf9V+3z9+jUKFSoEPT09WFhYIDg4GPb29jA3N//acomI8iyVw83QoUOVltPT0xEeHo6DBw/it99+U1ddRAWO36Ywxc9967piUjvVnj781NGjR9GjRw+MHDkSI0eOBPD+jxMiIl33VX1uPrZ8+XKEhoYiICBAHbvTGPa5obwmOU2GRguO42X8f3OgPZrTNsf7k8lkmDp1KmbMmAEhBKpVq4aLFy9mez42IqK8SJXvb7XNCt66dWvs3LlTXbsjKhDWn3uECpMOKgWbvYPr5nh/L168QNOmTTF9+nQIIdC/f3+cPXuWwYaIChS1/cbbsWMHbG1t1bU7Ip0Wm5QG92nKT0QZ6evh6uQWMDXS/8xWWTt06BB+/PFHxMTEwMLCAqtWrUK3bt3UUS4RUb6icripVq2aUodiIQSioqLw6tUrrFixQq3FEemiO1EJaLnolFJbQJ8aaFwu50MqREZGon379khNTYW7uzsCAwPh5ub2taUSEeVLKoebDh06KC3r6emhSJEiaNSoEcqX/7pxOIh03f+uvcDgLeGKZa/SdtjkWwt6el831oyTkxPmzp2Lu3fv4vfff4eJicnXlkpElG+pFG6kUilcXFzQsmVLODo6aqomIp3016mHmBl8W7E8oFFpjG6V8z8I9u/fj6JFi8Ld3R0A8Ouvv35tiUREOkGlDsUGBgYYMGAAUlNTv7wyESk8fZOkFGw296uV42CTlpaGkSNH4ttvv0WXLl2QkJCgrjKJiHSCyrelatWqhfDw8AyzghNR5j7tY7PWxxN1y+RsdO9Hjx6ha9euuHDhAgCgbdu2MDIyUkudRES6QuVwM3DgQIwYMQLPnj2Dh4dHhpFOq1SporbiiPKruOR0bPrnMeYfuqPU/nODUmhS3iFH+9yzZw/69OmD2NhY2NjYYN26dWjfvr06yiUi0inZHsSvb9++WLRoEWxsbDLuRCKBEAISiQQymUzdNaoVB/EjTUtJl6H8xIMZ2ie0rYB+9UupvL/09HSMHDkSS5YsAQDUrl0b27Zt49VTIipQNDJx5vr16zFnzhxERER8dYFEuir00Rt0WnlesWxiqIeRLcqhT11X6OfwiSg9PT3cunULADBy5EjMmjULhoaGaqmXiEgXZTvcfLjAw78WiT7v42BjbqSPG1NbZjnRbFbkcjn09PSgr6+PTZs2ISwsDG3atFFXqUREOkulp6Vy+kuaSNelpMtQffp/Iw53rFY0x8EmJSUFAwcOxIABAxRtDg4ODDZERNmkUodiNze3L/6yfvPmzVcVRJTfRMWloPbso0ptv3eumqNgc+/ePXTp0gVXrlwBAAwaNIid9ImIVKRSuJk6dSqsra01VQtRvvTjmguKn/X1JLg5tWWORhzeunUrfvrpJ7x79w5FihTBxo0bGWyIiHJApXDTtWtX2NvnfP4bIl0TnZCC+9HvAABuDhYIHlIfBvoq3e1FcnIyhgwZgtWrVwMAGjVqhM2bN8PZ2Vnt9RIRFQTZDjfsb0OU0cbzjxU/7xpYV+VgI4RAmzZtcOLECUgkEkycOBGTJk2Cvn7OZgYnIqIcPC1FRO+FPnqDpcfuK5YtjFUeExMSiQQjR47EnTt3sGnTJjRp0kSdJRIRFUjZ/m0sl8s1WQdRvpKSLlN67HtL/1rZ3jYxMRG3b9+Gp6cngPdTKNy7dy/DaN9ERJQzql1DJyrg0qRybLv4RGkE4iXdqsGrdPbmirpx4wZq1KiBFi1a4PHj/25pMdgQEamP6tfRiQqwWrOO4G1SumK5jL0Fvqv65Y6/QgisXbsWv/zyC5KTk+Hs7IyXL19yUEwiIg1guCHKJpcx+5WWf21aFgMalf7idgkJCRgwYAA2b94MAGjVqhU2bNiAIkWKaKROIqKCjuGG6AvkcoFS44KV2u7PbJ2tJ6OuXLkCb29v3L17F/r6+pg5cyZ+++036OnxjjARkaYw3BB9we7w50rLj+a0zfa2a9aswd27d1GsWDFs27YNdevWVXd5RET0CYYbos+QywX+PPUQcw/+q2h7OEu1+Z3mz58PQ0NDjB8/HnZ2duoukYiIMsFr40SZEOL9raiPg83CLlW/OK1CWFgYfH19IZPJAAAmJiZYuHAhgw0RUS7ilRuiTySmSlFp8iGltt0DvVCtRKHPbiOEwLJlyzBy5EikpaWhUqVKGD58uKZLJSKiTDDcEH3k8etENJx/QqntS31s3r59C19fX+zevRsA0KFDB/Tp00dTJRIR0RfwthTR//v7ynOlYONiZ4aI2Vn3sbl48SKqV6+O3bt3w8jICEuWLMGuXbtQqNDnr/IQEZFm8coNEYATd6Lx67YriuWuNYpjZsdvspwwdsOGDfD19YVUKkWpUqUQFBQEDw+PXKiWiIiywnBDBVp8SjqqTj2Mj+eF3TnACx4lv3zlxd3dHQYGBvj++++xatUqWFtba7BSIiLKLoYbKpBkcoG2S07j36gEpfaZHStnGWyio6Nhb28PAKhSpQouX76M8uXLZ3mFh4iIchf73FCBVHpcsFKw6VWnJB7NaYsetTKf60kul2Pu3LlwcXHBhQsXFO0VKlRgsCEiymN45YYKnBn/u6X42dHKBOfGNMly/JpXr16hV69eOHjw/UzgO3bsQK1atTReJxER5QzDDRUYD1+9Q9slZ5CcLlO0/TOuaZbbnDp1Ct26dcOLFy9gYmKCZcuWoW/fvpoulYiIvgJvS1GB8C5Viia/n1QKNmETmn12fZlMhhkzZqBx48Z48eIFKlSogEuXLsHX15e3oYiI8jiGG9J5CSnpqPzRiMM+Xi54OKsN7CyMP7vNzp07MXHiRMjlcvTu3RuXLl1C5cqVc6NcIiL6SrwtRTpLCIFBWy4j+HqUou3H2iUw5btKX9y2c+fO2LNnD1q2bInevXtrskwiIlIzhhvSWb0DLuHU3VeK5V+blsWw5m6ZriuTybBkyRL069cPlpaWkEgk2LJlS26VSkREasRwQzpnwaE7WHb8vlLb1UktYG1mmOn6L168QPfu3XHy5EmEhYVh06ZNuVEmERFpCPvckE4JvPQkQ7A5M7rxZ4PNoUOH4O7ujpMnT8LCwgJt2mQ9lxQREeV9vHJDOuPIrZcYvfO6YnmHXx14uthmuq5UKsXEiRMxZ84cAEDVqlURFBQEN7fMb1sREVH+wXBDOkEIgX4bQhXLR0c0ROkiFpmu+/z5c3h7e+Ps2bMAgIEDB+L333+HiYlJrtRKRESaxXBDOuHmi3jFz5t8a3022ACAvr4+7t+/DysrK6xevRqdO3fOjRKJiCiXsM8N6YSZ+28DAEwM9VCvbOEM78tk/w3e5+joiF27duHy5csMNpQnLVmyBBKJ5LNjKz169AgSiQQLFizI9P0FCxZAIpHg0aNHirZGjRpBIpEoXiYmJqhYsSJmzJiBtLS0TPfz9OlTDB48GKVLl4aJiQkKFSqERo0aYfPmzRBCZLrNy5cvMWbMGHzzzTewsLCAiYkJypYti19//RX37t1T7USowdKlS1G+fHkYGxvD1dUVU6dORXp6+he3+3COM3tt27Yty21//PFHSCQSfPvtt0rtJ06c+Ow+JRIJ/Pz8vuqz0n945YbyveiEFJx/+BoAYG+Z8dbSo0eP0LVrVwwbNgze3t4AAC8vr1ytkUgVa9euBQDcvHkTFy5cUNtcZqVKlcLmzZsBvJ8zbfXq1Zg4cSKePHmCVatWKa179uxZfPvtt7CwsMBvv/2GKlWqIC4uDkFBQfjxxx+xb98+bNmyBXp6//2NfPHiRXz77bcQQmDw4MGoU6cOjIyMcOfOHWzatAk1a9bE27dv1fJZsmPmzJmYOHEixowZgxYtWuDSpUuYMGECnj9/nuHzfs4vv/yC7t27K7WVLVv2s+vv378fe/bsgZWVVYb3qlevjvPnz2do9/f3x4YNG9CxY8ds1UTZIAqYuLg4AUDExcVpuxRSg/jkNFFy9P8Ur9jENKX3d+/eLWxsbAQAUaJECZGamqqlSomy59KlSwKAaNu2rQAg+vfvn2GdiIgIAUDMnz8/033Mnz9fABARERGKtoYNG4pKlSoprZeeni7Kli0rjIyMRHJysqL97du3wt7eXpQsWVJERUVl2P+cOXMEADF79mxFW1xcnHB0dBTFixcXT58+zbSu7du3Z/nZ1SkmJkaYmJiIn376Sal95syZQiKRiJs3b2a5/ZfOcWZiY2NF0aJFxcKFC0XJkiVF27Ztv7iNXC4XpUqVEiVLlhQymSzbxyqIVPn+5m0pyrfiktLxzZTDiuVRrcopHvlOS0vD0KFD0bFjR8TGxqJmzZo4efIkjIyMtFUuUbasWbMGADBnzhx4eXlh27ZtSEpK0sixDAwM4O7ujrS0NMTGxiraV69ejejoaMyZMwcODg4Zths1ahTKly+P+fPnK27x/PXXX4iKisK8efNQrFixTI/XqVMnjXyOzBw8eBApKSno06ePUnufPn0ghMCePXvUfswRI0bAyckJQ4YMyfY2x48fx8OHD9GnTx+lq2D0dXgmKd9qtfiU4ueGbkUwsFEZAMDDhw9Rt25dLF68GMD7XzinT5+Gi4uLNsokyrbk5GRs3boVNWrUQOXKldG3b18kJCRg+/btGjtmREQEbGxsUKRIEUVbSEgI9PX10a5du0y3kUgk+O677/DmzRuEhYUBAA4fPpzlNtkllUqz9RKf6fPzwY0bNwAA33zzjVK7k5MTChcurHj/S+bMmQMjIyOYmZmhXr162Lt3b6brHTlyBBs2bMDq1auhr6+frX0D78Osnp5ehhBGX4fhhvKVdJkcM/ffgsuY/YiMS1G0r+tTAwAQHR2N6tWrIzQ0FLa2tti7dy8WLFjAKzaUL+zYsQNxcXHw9fUFAHh7e8PCwkJxNUcdPoSDqKgoTJ48GaGhoZgzZ47SF/KTJ09QpEgRmJubf3Y/rq6uinWzu82XPHr0CIaGhtl6nTx5Mst9vX79GsbGxpnWY2tri9evX2e5vbGxMfr37w9/f38cO3YMq1evhkwmQ/v27bF69Wqldd+9e4f+/ftj5MiRqFq1arY/b2xsLHbt2oXmzZujRIkS2d6Ovowdiilf+fPkA/x1OkKpLXRCM0gkEgCAvb09fH198c8//2Dbtm0oXry4NsokypE1a9bA1NQUXbt2BQBYWFigc+fOCAgIwL1797LsyJodN2/ehKGh8mjdY8eOxc8//6zyvj5cOfnw/546ODs749KlS9lat1y5cl9cJ6vavlS3k5NThk7HnTt3Rq1atTBmzBj4+PjAwOD9V+iYMWNgaGiISZMmZaPy/2zevBkpKSno16+fStvRl2n9ys2KFSvg6uoKExMTeHh44PTp059d90PCLVKkCKysrFCnTh0cOnQoF6slbYpPSceCw3cVy4u83fFwVhu8jXyi+OsReH8Z+cSJEww2lK/cv38fp06dQtu2bSGEQGxsLGJjYxX9VD48QQVA8aX68RAHH5NKpQCQIciULl0aly5dwsWLF7F9+3ZUrVoVs2fPzvBoc4kSJfDq1SskJiZ+tt4Pj5l/+P8sO9t8iZGREdzd3bP1srD4/FhWAGBnZ4eUlJRM+yu9efMGtraZj16eFUNDQ3h7e+P169eKx9ovXryIFStWYN68eUhJSVH8u8nlckilUsTGxiI1NTXT/a1ZswZFihRB+/btVa6FsqbVcBMYGIihQ4di/PjxCA8PR/369dG6dWulL6qPnTp1Cs2bN0dwcDDCwsLQuHFjtGvXDuHh4blcOeW2hJR0VPmo8/DvnauiQ7WiCAzchurVq6Nbt26Kjo0fLlsT5Sdr166FEAI7duxAoUKFFK+2bdsCANavX68IM4ULF4a+vj6eP3+e6b6eP38OfX192NnZKbWbmJjA09MTNWrUQKdOnXD06FE4ODhg6NChePfunWK95s2bQyaTYd++fZnuXwiBvXv3wtbWFh4eHgCAli1bZrlNdqjzttSHvjbXr19Xao+KikJMTMxnxxD6kg9XrD50/r116xaEEOjYsaPSv9vTp09x6NAhFCpUCP7+/hn2Ex4ejvDwcPTq1Yu/rzRBg09tfVHNmjWFn5+fUlv58uXFmDFjsr2PihUriqlTp2Z7fT4Knv/I5XJRceIBxePerRadEklJSaJ///4CgAAgGjZsKF6/fq3tUolyRCqVCmdnZ1G6dGlx/PjxDK8RI0YIAGLfvn2KbRo0aCBKliyp9Ai3EEIkJyeLEiVKiIYNGyq1Z/YouBBCBAQECABi1qxZirYPj4K7uLiIly9fZtjmw6Pgc+bMUbTFxsYqHgV/9uxZpp9z586dWZ6H1NRUcenSpWy94uPjs9zX69evhYmJSYbvmNmzZ2frUfDMpKWlCXd3d1G4cGEhlUqFEEJERkZm+m/m4OAgateuLY4fP57po/GDBg0SAMStW7dUrqOgUuX7W2vhJjU1Vejr64tdu3YptQ8ZMkQ0aNAgW/uQyWSiePHiYunSpdk+LsNN/hHx6p3o5H9WaRybqlMPidu3b4vKlSsLAEIikYiJEyeK9PR0bZdLlGP79u0TAMTcuXMzff/Vq1fC2NhYdOjQQdF27tw5YWxsLNzd3cW6devEsWPHxLp164S7u7swNjYW586dU9rH58KNTCYT33zzjbC1tVX6vXjmzBlhY2MjihUrJhYvXixOnDgh9u7dK3r06CEACG9v7wzjsly4cEEUKVJEFClSREydOlUcPnxYnDhxQvz111+iYcOGwsbG5mtOk8pmzJghJBKJGDdunDhx4oSYP3++MDY2zjB20Pr164W+vr5Yv369om3YsGFi8ODBYuvWreL48eNiw4YNokaNGgKACAgI+OKxsxrnJjk5WRQqVEh4eXl91ecraPJFuHn+/LkAIM6ePavUPnPmTOHm5patfcybN0/Y2tpm+pfFBykpKSIuLk7xevr0KcNNHieTyUWfgItKoeZDsFm9JkCYmZkJAMLBwUGEhIRou1yir9ahQwdhZGQkoqOjP7tO165dhYGBgdKgeqGhoaJjx46icOHCQl9fXxQuXFh07NhRhIWFZdj+c+FGCCH2798vAGS4Cv7kyRMxaNAgUapUKWFkZCSsra1FgwYNxKZNm4RcLs90X1FRUWL06NGiUqVKwszMTBgbG4syZcqIn3/+WVy/fj07p0OtFi9eLNzc3ISRkZEoUaKEmDx5skhLUx7s88PVq49Dy5o1a0TNmjWFra2tMDAwEIUKFRItW7YUhw4dytZxswo3mzdvFgDE2rVrc/y5CiJVwo1EiC8MFqAhL168QNGiRXHu3DnUqVNH0T5z5kxs3LgR//77b5bbb926Ff369cPff/+NZs2afXa9KVOmYOrUqRna4+LiMh0em7TrwsPX8F71j1JbZ49iGNK0LBwsDFCjRg1cu3YNTZs2xaZNm+Do6KilSomIKDfFx8fD2to6W9/fWnsU/EOHuKioKKX26OjoTEfE/FhgYCB8fX2xffv2LIMN8P4xx+HDhyuW4+Pj+RRNHjVxzw1s/OexUtu1KS1gZfJfZ7ugoCDs3LkTo0ePVmmgLCIiKji09rSUkZERPDw8EBISotQeEhKS5aSGW7duhY+PD7Zs2aJ4iiArxsbGsLKyUnpR3jNhz3WlYDOiuRsezmqN7Zs3YN68eYr2cuXKYdy4cQw2RET0WVodxG/48OHo2bMnPD09UadOHaxatQpPnjxRTPs+duxYPH/+HBs2bADwPtj06tULixcvRu3atRVXfUxNTWFtba21z0FfJ+ZdKjb989/j/6dHNYaNoQy9evXC5s2boaenh2bNmqF69eparJKIiPILrYabD4MhTZs2DZGRkahcuTKCg4NRsmRJAEBkZKTSmDd//vknpFIpBg0ahEGDBinae/fujXXr1uV2+aQGz2OTUXfOMcVy8JD6ePP0Hpp16YK7d+9CX18fM2bMgLu7u/aKJCKifEVrHYq1RZUOSaRZcrlAqXHBiuURzcvC6P5x/Prrr0hNTUWxYsWwdetW1KtXT4tVEhFRXpAvOhRTwfbpU1Htqjrj8qbZiitw3377LdatW5dhhFUiIqIv0frcUlQwfRxs3BwssKSrO2rXrg0DAwMsWLAAe/fuZbAhIqIc4ZUbynW/bb8K4P0cLb3drTGtW30AwE8//YRGjRpla7ZfIiKiz2GfG8o1i47cxaIj72fSlaW8w+sDi+GQFonw8HDY2NhotzgiIsrT2OeG8pR9V1/gl63/zdye+uIOYvbOgzTuJZ4bGuLs2bPZGrOIiIgoOxhuSGO2XHiCcbuvK5aFEEi4tAcJp9dDKpWiVKlSCAwMhKenpxarJCIiXcNwQ2qXKpWh9qyjeJuUrmiTJcfD4p9VeHLxBACgU6dOWL16NQdfJCIitePTUqR2zRaeVAo2W/vXRqukY/j34gkYGxtjxYoVCAoKYrAhIiKN4JUbUps0qRxuEw4otd2b2RqG+npwmzMHERERWLBgAUcbJiIijWK4IbWQyYVSsJElxeHXklEw0GsDALCzs8ORI0e0VR4RERUgDDekFh1XnFX8nPL0BvRPLMFvL17AtpAN+vbtq73CiIiowGG4oa8W+ugNrj2Lg5DLEPfPdiSc3QK5XI7y5cujRo0a2i6PiIgKGIYb+irDA69gV/hzyBLfImbf70h5fAUA0KtXLyxfvhwWFhbaLZCIiAochhvKkVsv4rHl4mPsCn+OlCfX8GrvPMgTY2FmZobly5fDx8dH2yUSEVEBxXBDKhFCoOuqf3Ah4s1/bXI5RFIcKlWqhKCgIFSsWFGLFRIRUUHHcEPZIpXJ0WfdJZy+FwMAEHIZJHr6+KF6Mfz6W2OEd6uM5s2bw8zMTMuVEhFRQcdwQ190PzoBzRaeUiwnPwxDwvFVCD97HOXcygIASrRvr63yiIiIlHCEYspSyK2XimAj5DIYXt6G6O2TkRzzHLNmztBydURERBnxyg1lSggB3/WhOPZvNABAGh8D83PLcPdqKADAz88PCxcu1GaJREREmWK4oUwN2XZFEWySHlxC+tGleP72DSwtLbF69Wp06dJFyxUSERFljuGGlKSkyzBu13Xsu/oCAJB0/yJe7ZwGAKhevToCAwNRpkwZbZZIRESUJYYbUpi27xbWno1Qaru9dhTaPD2IWrVqYf78+TA2NtZSdURERNnDcEM4fDMKP20MUyynPL6Glk0aYlnPGrA0McTJkydhYmKixQqJiIiyj09LFXD/PHytCDZClo7443/h5bZxKBrxP1iaGAIAgw0REeUrvHJTQKWky9Bs4Uk8e5sMAEiPjYLJqSV4e/va++X0dAghIJFItFkmERGRyhhuCpg0qRyzgm9j3blHirbEf88g8cgyJCe+g62tLdatW4d27dppr0giIqKvwHBTgKSky1B+4kHFspCmQfyzATFn9wAAvLy8sHXrVpQoUUJLFRIREX099rkpIGLepSoFG0crE6zt7Io3V0IAAKNHj8aJEycYbIiIKN/jlZsCov2ys4qfu9UsjtnfVwEArF27FpaWlmjdurW2SiMiIlIrhhsdJ4TAoC2X8Tw2GfL0VBhc3IDWbYYr3udIw0REpGsYbnTYi9hkeM05BgBIf/0Ur/6ei/RXj9CjRxju3bvHR7yJiEgnMdzosNaLTwMA3t04ijeHV0Ckp8Le3h5r165lsCEiIp3FcKOD7kQl4KeNoXgbl4A3ISuReOMIAKBJkybYtGkTnJyctFwhERGR5jDc6JjIuGS0XHQKsuQEvNw8Gumvn0BPTw+TJ0/G+PHjoa+vr+0SiYiINIrhRsesPfN+4ks9EwuULV8Bbx6mY+uWLWjUqJF2CyMiIsolDDc65PStp/jzyA3oGZvD0doEh/cHIjX1fT8bIiKigoKD+OmIpdtD0KR+HbwOXgwhBDb61oK1tTWDDRERFTi8cpPPCSGw3H8lhgz5FZClQ6SlYHxjR7g5WGq7NCIiIq1guMnH4uPj0b9/fwQFBQEATEvXwJaN69GhTgUtV0ZERKQ9DDf51OXLl9GlSxc8ePAA0NOHTYPeKOL1PYMNEREVeAw3+ZBUKkWH7zvh6eMI6FsVQZHvRsOuVGWETmim7dKIiIi0juEmH9oZ/gJp9fxgZvw3bFv9Ajs7W1yZ1ELbZREREeUJDDf5xMWLF3H51j08ta6CzReewKRYJZgUq4Sxrcvj54altV0eERFRnsFwk8cJITBl1jxMnzwB0NOHY68/YFS4BABg10AvVC9RSMsVEhER5S0MN3nY7Ucv0Pr7rngc/n4CTLPSNWFgYYsetUqgW80SqFzUWssVEhER5T0MN3nUuXPn0Kh1B6THvwL0DWDbpD96+fbH7O+rwMSQ80MRERF9DsNNHtRr6ARsXDIbEHIYFHJC6a4TETSuG6oUs9F2aURERHkew00eEp2QAr+NYTh68T4g5DCr0AB2LQfj+oIfYKjPmTKIiIiyg+Emj5BKpag/9zhSpXLY1OsOY8fS2DZrCJqUd9B2aURERPkKLwdomVwux8yZM1G0fDWkpKQCAOqWtcfDrVMZbIiIiHKAV2606OXLl/jxxx9x5MgRAIDdnTOwqNQYm3xrQU9PouXqiIiI8ieGGy05duwYevTogaioKEgMjGHb3A/mFRvh5tSWDDZERERfgbelcplMJsOUKVPQrFkzREVFwdCuBBx7/4Fitdvg0Zy2MDdm3iQiIvoa/CbNZcOHD8eSJUsAAObfNIdt859hamqG0PHNIJHwig0REdHXYrjJZenlW0HfYjNsGvnAolJjAMCdGa21XBUREZHuYLjRMKlUiv2HQnBFXgKHbkThRZwcRX9eDYmBIZpXdMDoVuW1XSIREZFOYbjRoGfPnsGjSTtE37sK+y5TYepaHQAgMTDElUnNYWNmpOUKiYiIdI/WOxSvWLECrq6uMDExgYeHB06fPp3l+idPnoSHhwdMTExQqlQprFy5MpcqVc3va7ahpFslRN+7AomRCUR6Cio4WWFr/9qImN2GwYaIiEhDtBpuAgMDMXToUIwfPx7h4eGoX78+WrdujSdPnmS6fkREBNq0aYP69esjPDwc48aNw5AhQ7Bz585crvzz/I/dgXWtHzCyXzfIk+Nh5FAaTj6L8XLnDBz4tT7qlLZjx2EiIiINkgghhLYOXqtWLVSvXh3+/v6KtgoVKqBDhw6YPXt2hvVHjx6NvXv34vbt24o2Pz8/XL16FefPn8/WMePj42FtbY24uDhYWVl9/Yf4SLEBAXi1dy7SXtwBAFh6tMNvk6Zj3LdVoM+xa4iIiHJMle9vrV25SUtLQ1hYGFq0aKHU3qJFC5w7dy7Tbc6fP59h/ZYtWyI0NBTp6emZbpOamor4+HillyYkpKQj5ekNpL24A4mxOQbP9Ed86F5M/K4qgw0REVEu0lq4iYmJgUwmg4OD8vxJDg4OiIqKynSbqKioTNeXSqWIiYnJdJvZs2fD2tpa8SpevLh6PsAnktNlsHVvBpsGvXD/1jUsHeenkeMQERFR1rTeofjT/idCiCz7pGS2fmbtH4wdOxZxcXGK19OnT7+y4szZW5rg7ozWeHtyPUqVKqWRYxAREdGXae1R8MKFC0NfXz/DVZro6OgMV2c+cHR0zHR9AwMD2NnZZbqNsbExjI2N1VM0ERER5Xlau3JjZGQEDw8PhISEKLWHhITAy8sr023q1KmTYf3Dhw/D09MThoaGGquViIiI8g+t3pYaPnw4Vq9ejbVr1+L27dsYNmwYnjx5Aj+/9/1Vxo4di169einW9/Pzw+PHjzF8+HDcvn0ba9euxZo1azBy5EhtfQQiIiLKY7Q6QrG3tzdev36NadOmITIyEpUrV0ZwcDBKliwJAIiMjFQa88bV1RXBwcEYNmwYli9fDmdnZyxZsgQ//PCDtj4CERER5TFaHedGGzQ5zg0RERFpRr4Y54aIiIhIExhuiIiISKcw3BAREZFOYbghIiIincJwQ0RERDqF4YaIiIh0CsMNERER6RSGGyIiItIpDDdERESkU7Q6/YI2fBiQOT4+XsuVEBERUXZ9+N7OzsQKBS7cJCQkAACKFy+u5UqIiIhIVQkJCbC2ts5ynQI3t5RcLseLFy9gaWkJiUSi1n3Hx8ejePHiePr0Keet0iCe59zB85w7eJ5zD8917tDUeRZCICEhAc7OztDTy7pXTYG7cqOnp4dixYpp9BhWVlb8HycX8DznDp7n3MHznHt4rnOHJs7zl67YfMAOxURERKRTGG6IiIhIpzDcqJGxsTEmT54MY2NjbZei03iecwfPc+7gec49PNe5Iy+c5wLXoZiIiIh0G6/cEBERkU5huCEiIiKdwnBDREREOoXhhoiIiHQKw42KVqxYAVdXV5iYmMDDwwOnT5/Ocv2TJ0/Cw8MDJiYmKFWqFFauXJlLleZvqpznXbt2oXnz5ihSpAisrKxQp04dHDp0KBerzb9U/e/5g7Nnz8LAwADu7u6aLVBHqHqeU1NTMX78eJQsWRLGxsYoXbo01q5dm0vV5l+qnufNmzejatWqMDMzg5OTE/r06YPXr1/nUrX506lTp9CuXTs4OztDIpFgz549X9xGK9+DgrJt27ZtwtDQUPz111/i1q1b4tdffxXm5ubi8ePHma7/8OFDYWZmJn799Vdx69Yt8ddffwlDQ0OxY8eOXK48f1H1PP/6669i7ty54uLFi+Lu3bti7NixwtDQUFy+fDmXK89fVD3PH8TGxopSpUqJFi1aiKpVq+ZOsflYTs7zd999J2rVqiVCQkJERESEuHDhgjh79mwuVp3/qHqeT58+LfT09MTixYvFw4cPxenTp0WlSpVEhw4dcrny/CU4OFiMHz9e7Ny5UwAQu3fvznJ9bX0PMtyooGbNmsLPz0+prXz58mLMmDGZrj9q1ChRvnx5pbaff/5Z1K5dW2M16gJVz3NmKlasKKZOnaru0nRKTs+zt7e3mDBhgpg8eTLDTTaoep4PHDggrK2txevXr3OjPJ2h6nmeP3++KFWqlFLbkiVLRLFixTRWo67JTrjR1vcgb0tlU1paGsLCwtCiRQul9hYtWuDcuXOZbnP+/PkM67ds2RKhoaFIT0/XWK35WU7O86fkcjkSEhJga2uriRJ1Qk7Pc0BAAB48eIDJkydrukSdkJPzvHfvXnh6emLevHkoWrQo3NzcMHLkSCQnJ+dGyflSTs6zl5cXnj17huDgYAgh8PLlS+zYsQNt27bNjZILDG19Dxa4iTNzKiYmBjKZDA4ODkrtDg4OiIqKynSbqKioTNeXSqWIiYmBk5OTxurNr3Jynj/1+++/IzExEV26dNFEiTohJ+f53r17GDNmDE6fPg0DA/7qyI6cnOeHDx/izJkzMDExwe7duxETE4OBAwfizZs37HfzGTk5z15eXti8eTO8vb2RkpICqVSK7777DkuXLs2NkgsMbX0P8sqNiiQSidKyECJD25fWz6ydlKl6nj/YunUrpkyZgsDAQNjb22uqPJ2R3fMsk8nQvXt3TJ06FW5ubrlVns5Q5b9nuVwOiUSCzZs3o2bNmmjTpg0WLlyIdevW8erNF6hynm/duoUhQ4Zg0qRJCAsLw8GDBxEREQE/P7/cKLVA0cb3IP/8yqbChQtDX18/w18B0dHRGVLpB46Ojpmub2BgADs7O43Vmp/l5Dx/EBgYCF9fX2zfvh3NmjXTZJn5nqrnOSEhAaGhoQgPD8fgwYMBvP8SFkLAwMAAhw8fRpMmTXKl9vwkJ/89Ozk5oWjRorC2tla0VahQAUIIPHv2DGXLltVozflRTs7z7NmzUbduXfz2228AgCpVqsDc3Bz169fHjBkzeGVdTbT1PcgrN9lkZGQEDw8PhISEKLWHhITAy8sr023q1KmTYf3Dhw/D09MThoaGGqs1P8vJeQbeX7Hx8fHBli1beM88G1Q9z1ZWVrh+/TquXLmiePn5+aFcuXK4cuUKatWqlVul5ys5+e+5bt26ePHiBd69e6dou3v3LvT09FCsWDGN1ptf5eQ8JyUlQU9P+StQX18fwH9XFujrae17UKPdlXXMh0cN16xZI27duiWGDh0qzM3NxaNHj4QQQowZM0b07NlTsf6HR+CGDRsmbt26JdasWcNHwbNB1fO8ZcsWYWBgIJYvXy4iIyMVr9jYWG19hHxB1fP8KT4tlT2qnueEhARRrFgx0alTJ3Hz5k1x8uRJUbZsWdGvXz9tfYR8QdXzHBAQIAwMDMSKFSvEgwcPxJkzZ4Snp6eoWbOmtj5CvpCQkCDCw8NFeHi4ACAWLlwowsPDFY/c55XvQYYbFS1fvlyULFlSGBkZierVq4uTJ08q3uvdu7do2LCh0vonTpwQ1apVE0ZGRsLFxUX4+/vncsX5kyrnuWHDhgJAhlfv3r1zv/B8RtX/nj/GcJN9qp7n27dvi2bNmglTU1NRrFgxMXz4cJGUlJTLVec/qp7nJUuWiIoVKwpTU1Ph5OQkevToIZ49e5bLVecvx48fz/L3bV75HpQIwetvREREpDvY54aIiIh0CsMNERER6RSGGyIiItIpDDdERESkUxhuiIiISKcw3BAREZFOYbghIiIincJwQ0RK1q1bBxsbG22XkWMuLi5YtGhRlutMmTIF7u7uuVIPEeU+hhsiHeTj4wOJRJLhdf/+fW2XhnXr1inV5OTkhC5duiAiIkIt+7906RJ++uknxbJEIsGePXuU1hk5ciSOHj2qluN9zqef08HBAe3atcPNmzdV3k9+DptE2sBwQ6SjWrVqhcjISKWXq6urtssC8H4izsjISLx48QJbtmzBlStX8N1330Emk331vosUKQIzM7Ms17GwsNDojMQffPw59+/fj8TERLRt2xZpaWkaPzZRQcZwQ6SjjI2N4ejoqPTS19fHwoUL8c0338Dc3BzFixfHwIEDlWag/tTVq1fRuHFjWFpawsrKCh4eHggNDVW8f+7cOTRo0ACmpqYoXrw4hgwZgsTExCxrk0gkcHR0hJOTExo3bozJkyfjxo0biitL/v7+KF26NIyMjFCuXDls3LhRafspU6agRIkSMDY2hrOzM4YMGaJ47+PbUi4uLgCAjh07QiKRKJY/vi116NAhmJiYIDY2VukYQ4YMQcOGDdX2OT09PTFs2DA8fvwYd+7cUayT1b/HiRMn0KdPH8TFxSmuAE2ZMgUAkJaWhlGjRqFo0aIwNzdHrVq1cOLEiSzrISooGG6IChg9PT0sWbIEN27cwPr163Hs2DGMGjXqs+v36NEDxYoVw6VLlxAWFoYxY8bA0NAQAHD9+nW0bNkS33//Pa5du4bAwECcOXMGgwcPVqkmU1NTAEB6ejp2796NX3/9FSNGjMCNGzfw888/o0+fPjh+/DgAYMeOHfjjjz/w559/4t69e9izZw+++eabTPd76dIlAEBAQAAiIyMVyx9r1qwZbGxssHPnTkWbTCZDUFAQevToobbPGRsbiy1btgCA4vwBWf97eHl5YdGiRYorQJGRkRg5ciQAoE+fPjh79iy2bduGa9euoXPnzmjVqhXu3buX7ZqIdJbGp+YkolzXu3dvoa+vL8zNzRWvTp06ZbpuUFCQsLOzUywHBAQIa2trxbKlpaVYt25dptv27NlT/PTTT0ptp0+fFnp6eiI5OTnTbT7d/9OnT0Xt2rVFsWLFRGpqqvDy8hL9+/dX2qZz586iTZs2Qgghfv/9d+Hm5ibS0tIy3X/JkiXFH3/8oVgGIHbv3q20zqczmg8ZMkQ0adJEsXzo0CFhZGQk3rx581WfE4AwNzcXZmZmitmTv/vuu0zX/+BL/x5CCHH//n0hkUjE8+fPldqbNm0qxo4dm+X+iQoCA+1GKyLSlMaNG8Pf31+xbG5uDgA4fvw4Zs2ahVu3biE+Ph5SqRQpKSlITExUrPOx4cOHo1+/fti4cSOaNWuGzp07o3Tp0gCAsLAw3L9/H5s3b1asL4SAXC5HREQEKlSokGltcXFxsLCwgBACSUlJqF69Onbt2gUjIyPcvn1bqUMwANStWxeLFy8GAHTu3BmLFi1CqVKl0KpVK7Rp0wbt2rWDgUHOf5316NEDderUwYsXL+Ds7IzNmzejTZs2KFSo0Fd9TktLS1y+fBlSqRQnT57E/PnzsXLlSqV1VP33AIDLly9DCAE3Nzel9tTU1FzpS0SU1zHcEOkoc3NzlClTRqnt8ePHaNOmDfz8/DB9+nTY2trizJkz8PX1RXp6eqb7mTJlCrp37479+/fjwIEDmDx5MrZt24aOHTtCLpfj559/Vurz8kGJEiU+W9uHL309PT04ODhk+BKXSCRKy0IIRVvx4sVx584dhISE4MiRIxg4cCDmz5+PkydPKt3uUUXNmjVRunRpbNu2DQMGDMDu3bsREBCgeD+nn1NPT0/xb1C+fHlERUXB29sbp06dApCzf48P9ejr6yMsLAz6+vpK71lYWKj02Yl0EcMNUQESGhoKqVSK33//HXp677vcBQUFfXE7Nzc3uLm5YdiwYejWrRsCAgLQsWNHVK9eHTdv3swQor7k4y/9T1WoUAFnzpxBr169FG3nzp1TujpiamqK7777Dt999x0GDRqE8uXL4/r166hevXqG/RkaGmbrKazu3btj8+bNKFasGPT09NC2bVvFezn9nJ8aNmwYFi5ciN27d6Njx47Z+vcwMjLKUH+1atUgk8kQHR2N+vXrf1VNRLqIHYqJCpDSpUtDKpVi6dKlePjwITZu3JjhNsnHkpOTMXjwYJw4cQKPHz/G2bNncenSJUXQGD16NM6fP49BgwbhypUruHfvHvbu3YtffvklxzX+9ttvWLduHVauXIl79+5h4cKF2LVrl6Ij7bp167BmzRrcuHFD8RlMTU1RsmTJTPfn4uKCo0ePIioqCm/fvv3scXv06IHLly9j5syZ6NSpE0xMTBTvqetzWllZoV+/fpg8eTKEENn693BxccG7d+9w9OhRxMTEICkpCW5ubujRowd69eqFXbt2ISIiApcuXcLcuXMRHBysUk1EOkmbHX6ISDN69+4t2rdvn+l7CxcuFE5OTsLU1FS0bNlSbNiwQQAQb9++FUIod2BNTU0VXbt2FcWLFxdGRkbC2dlZDB48WKkT7cWLF0Xz5s2FhYWFMDc3F1WqVBEzZ878bG2ZdZD91IoVK0SpUqWEoaGhcHNzExs2bFC8t3v3blGrVi1hZWUlzM3NRe3atcWRI0cU73/aoXjv3r2iTJkywsDAQJQsWVIIkbFD8Qc1atQQAMSxY8cyvKeuz/n48WNhYGAgAgMDhRBf/vcQQgg/Pz9hZ2cnAIjJkycLIYRIS0sTkyZNEi4uLsLQ0FA4OjqKjh07imvXrn22JqKCQiKEENqNV0RERETqw9tSREREpFMYboiIiEinMNwQERGRTmG4ISIiIp3CcENEREQ6heGGiIiIdArDDREREekUhhsiIiLSKQw3REREpFMYboiIiEinMNwQERGRTmG4ISIiIp3yfznW/WmsnD8DAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "# plot the roc curve\n",
    "fpr_proba, tpr_proba, _ = roc_curve(y, y_pred_proba)\n",
    "plt.plot(fpr_proba, tpr_proba,)\n",
    "plt.plot([0, 1], [0, 1], 'k--', label='Random')\n",
    "plt.xlabel('False Positive Rate')\n",
    "plt.ylabel('True Positive Rate')\n",
    "plt.title('Freefield')\n",
    "auroc = auc(fpr_proba, tpr_proba)\n",
    "plt.text(0.6, 0.2, f'AUROC = {auroc:.3f}', fontsize=12)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "birdclef",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}