From 858d1d2111d7767a10b85d67d381084bf885f54b Mon Sep 17 00:00:00 2001
From: frodrigue-ensae <fanta.rodrigue@ensae.fr>
Date: Sun, 10 Mar 2024 18:49:34 +0000
Subject: [PATCH] stat

---
 Spectacle/Stat_desc.ipynb | 305 +++++++++++++++++++++++++++++++++-----
 1 file changed, 270 insertions(+), 35 deletions(-)

diff --git a/Spectacle/Stat_desc.ipynb b/Spectacle/Stat_desc.ipynb
index 06b1fa0..47e83f4 100644
--- a/Spectacle/Stat_desc.ipynb
+++ b/Spectacle/Stat_desc.ipynb
@@ -1788,7 +1788,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 101,
    "id": "5b460061-f8b5-4a6b-ba59-539446d8487f",
    "metadata": {},
    "outputs": [],
@@ -1829,7 +1829,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 69,
+   "execution_count": 102,
    "id": "cccee90c-67d1-4e14-8410-1210a5ef97d9",
    "metadata": {},
    "outputs": [],
@@ -7230,7 +7230,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 95,
+   "execution_count": 97,
    "id": "86fa4d7f-9b5f-4487-beb8-eb23771f724c",
    "metadata": {},
    "outputs": [
@@ -7256,6 +7256,7 @@
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>number_company</th>\n",
+       "      <th>y_has_purchased</th>\n",
        "      <th>nb_tickets</th>\n",
        "      <th>nb_tickets_internet</th>\n",
        "      <th>Taux_ticket_internet</th>\n",
@@ -7265,35 +7266,80 @@
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>10</td>\n",
-       "      <td>17898.0</td>\n",
-       "      <td>8874.0</td>\n",
-       "      <td>49.580959</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>9957.0</td>\n",
+       "      <td>5450.0</td>\n",
+       "      <td>54.735362</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
-       "      <td>11</td>\n",
-       "      <td>19999.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>0.025001</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>7941.0</td>\n",
+       "      <td>3424.0</td>\n",
+       "      <td>43.117995</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
-       "      <td>12</td>\n",
-       "      <td>47120.0</td>\n",
+       "      <td>11</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>10361.0</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>0.048258</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>11</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>9638.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>13</td>\n",
-       "      <td>1135835.0</td>\n",
-       "      <td>119308.0</td>\n",
-       "      <td>10.503990</td>\n",
+       "      <th>4</th>\n",
+       "      <td>12</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>35600.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>4</th>\n",
+       "      <th>5</th>\n",
+       "      <td>12</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>11520.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>13</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>131759.0</td>\n",
+       "      <td>105406.0</td>\n",
+       "      <td>79.999089</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>13</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1004076.0</td>\n",
+       "      <td>13902.0</td>\n",
+       "      <td>1.384557</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
        "      <td>14</td>\n",
-       "      <td>61290.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>44596.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>14</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>16694.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.000000</td>\n",
        "    </tr>\n",
@@ -7302,38 +7348,81 @@
        "</div>"
       ],
       "text/plain": [
-       "   number_company  nb_tickets  nb_tickets_internet  Taux_ticket_internet\n",
-       "0              10     17898.0               8874.0             49.580959\n",
-       "1              11     19999.0                  5.0              0.025001\n",
-       "2              12     47120.0                  0.0              0.000000\n",
-       "3              13   1135835.0             119308.0             10.503990\n",
-       "4              14     61290.0                  0.0              0.000000"
+       "   number_company  y_has_purchased  nb_tickets  nb_tickets_internet  \\\n",
+       "0              10              0.0      9957.0               5450.0   \n",
+       "1              10              1.0      7941.0               3424.0   \n",
+       "2              11              0.0     10361.0                  5.0   \n",
+       "3              11              1.0      9638.0                  0.0   \n",
+       "4              12              0.0     35600.0                  0.0   \n",
+       "5              12              1.0     11520.0                  0.0   \n",
+       "6              13              0.0    131759.0             105406.0   \n",
+       "7              13              1.0   1004076.0              13902.0   \n",
+       "8              14              0.0     44596.0                  0.0   \n",
+       "9              14              1.0     16694.0                  0.0   \n",
+       "\n",
+       "   Taux_ticket_internet  \n",
+       "0             54.735362  \n",
+       "1             43.117995  \n",
+       "2              0.048258  \n",
+       "3              0.000000  \n",
+       "4              0.000000  \n",
+       "5              0.000000  \n",
+       "6             79.999089  \n",
+       "7              1.384557  \n",
+       "8              0.000000  \n",
+       "9              0.000000  "
       ]
      },
-     "execution_count": 95,
+     "execution_count": 97,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "#Taux de ticket payé par internet selon les compagnies avec la base de train\n",
+    "#Taux de ticket payé par en ligne selon y_has_purchase par  compagnies avec la base de train\n",
     "\n",
-    "purchase_spectacle_train = train_set_spectacle.groupby(\"number_company\")[[\"nb_tickets\", \"nb_tickets_internet\"]].sum().reset_index()\n",
+    "purchase_spectacle_train = train_set_spectacle.groupby([\"number_company\", \"y_has_purchased\"])[[\"nb_tickets\", \"nb_tickets_internet\"]].sum().reset_index()\n",
     "purchase_spectacle_train[\"Taux_ticket_internet\"] = purchase_spectacle_train[\"nb_tickets_internet\"]*100 / purchase_spectacle_train[\"nb_tickets\"]\n",
     "purchase_spectacle_train"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 106,
    "id": "d11335b7-e35a-44c7-8ce4-661216978151",
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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bN0yDBg3Mk08+aS2fO3eukWRmzpx51/klmYCAAOvFlDG3vjBy5Mhhxo4d69LtceZznD9/vpFkvvrqK5vylPW9//771rKQkBDj6elpjhw5Yi27evWqKVCggOnRo8dd9sYt90qqkpKSTGBgoKlevbrNfEeOHDG5cuVKM6mqWLGiNeE2xpiff/7ZSLJJcJ3ZP2n58ssvjSSza9eudOtkZL/eefxPnz7dSDKff/65zbzjxo0zkmz+sWJvO0vL4cOHTY4cOcykSZOsZVevXjV+fn6p/iF0L47GcfPmTZOYmGjCw8NNv379rOVPPPGEqVy5coZiuFNKGwkODjZXr161lickJJgCBQqYhg0bWssymlT5+vranNuNMaZ+/fomX7585tSpU+nGlHJuvP2fScYYM378eCPJnDx5Ms35kpOTzY0bN8z69euNJPPLL78YY4z5+++/jSQzefLkdNd59OhR4+bmZl555RWb8osXL5rAwEDTrl07Y8yt4y84ONhUrVrV5jwdFxeX6vhLT0hIiLFYLKmOjUaNGpm8efOay5cvpzlfyvn2+eefN1WqVLGZlt7+zogSJUqYEiVK2LSDO9WoUcP4+/ubixcv2sRVoUIFU6RIEes+SfkM79yfrVu3NpLMxIkTbcorV65sqlatan2fkXZ5p/SOl4EDBxqLxWJzAW/Mre+XtJIqSWbr1q02dcuVK2ciIyNTxXn7d46931eOHr+DBw9Ot/3cvh2XL182BQoUMC1atLCpl5SUZB566CHz6KOP3nU99sSXcuzfvp+NMeazzz4zksynn35qjLH/+DLGvnY4YcKEVMlOWtI7J9i7njuv05zdp1u3bjWSbP4BkaJ8+fKprnGN+b9rgMcff/yuyzYm/WsyY9JPqjJ6njXGtedUY4zp3bt3qu+Q2x08eNBIMtOmTUu3zp3+9bf/7dy5Uy1btpSfn59y5sypXLlyqXPnzkpKStLvv//u0DJLliypmTNnasmSJXriiSdUp04du0Y3Wbt2rfLkyaOWLVvalHfs2NHm/aFDh7R//349++yzkm6NPJfyatasmU6ePKkDBw44FPudNm3apISEBPXq1SvVrTR3MsaoR48eGj58uObNm6dBgwZZp127dk0//PCDnnzySXl7e6eK+dq1a2ne+mWv6dOnq2rVqvL09JSbm5ty5cqlH374Qfv27bPW+f777+Xp6alu3brdc3n16tVTnjx5rO8DAgLk7+9vHRXHFdvj7Oe4dOlS5cuXTy1atLCZt3LlygoMDEx1a17lypVVrFgx63tPT0+VKlXKZqQfRx04cMB668ztihUrptq1a6c5T/PmzZUzZ07r+0qVKkmSNZ770c4rV64sd3d3vfjii5ozZ47++OOPVHUyul9vt2bNGvn4+Kht27Y25Sm31955K8a92ll6ihcvrieeeELvv/++9daDefPm6cyZMw6N5GdPHDdv3tSYMWNUrlw5ubu7y83NTe7u7jp48KDNcfboo4/ql19+Ua9evbRixQolJCRkOJ4Ubdq0kaenp/V9njx51KJFC/34449KSkpyaJn169dX/vz5re+vXLmi9evXq127dnY9T3rn+fnOdivdugWlY8eOCgwMtH6vRERESJJ1XxUoUEAlSpTQhAkTNHHiRO3cudPmFi5JWrFihW7evKnOnTvbtEVPT09FRERY2+KBAwf0559/qmPHjjbn6ZCQENWqVcvufVO+fHk99NBDNmUdO3ZUQkKCduzYYS374osvVLt2beXOndt6vv3oo49s2kGKO/d3Rvz+++86fPiwnn/+eZt2cLvLly9r69atatu2rc0ItDlz5lSnTp10/PjxVOeJJ554wuZ92bJlJSnVwA5ly5ZN81i0p13ae7ysX79eFSpUULly5WzW8cwzz6S5vYGBgXr00UdtyipVqnTXc0ZGvq8cPX7Xrl2bbvu53aZNm3T27Fl16dLFJo7k5GQ1adJEMTExad4SlyIj8aV8d6Ro166d3NzctHbtWkn2H1/2tMN7seec4Oh6nN2nKbfV+fv7Z3i7nnrqqTTL7bkmuxt7zrN3cuU51R4p++vEiRN2z/OvTqqOHj2qOnXq6MSJE3r33Xe1YcMGxcTEWO+jvHr1qsPLbt68uQICAnTt2jX179/f5uIxPWfOnFFAQECq8sDAQJv3f/31lyTp1VdfVa5cuWxevXr1kiT9/fffDsd+u5T7j4sUKXLPuomJiVq4cKHKly+vpk2b2kw7c+aMbt68qSlTpqSKuVmzZk7FPHHiRL300kuqXr26vvrqK23ZskUxMTFq0qSJzWd4+vRpBQcHK0eOezdrPz+/VGUeHh7W5blie5z9HP/66y+dP39e7u7uqeaPj49PNe+9tskZKSPgpNV+0ypLKx4PDw9J/3fc3Y92XqJECa1evVr+/v7q3bu3SpQooRIlStjcj5/R/Xq7M2fOKDAwMNU/IPz9/eXm5pZqpCBnPpP//Oc/OnjwoFatWiXp1vOhNWvWdGhERnvi6N+/v4YNG6bWrVvr22+/1datWxUTE6OHHnrIpt6QIUP09ttva8uWLWratKn8/PzUoEEDh4Yiv/Pcl1KWmJioS5cuZXh5klKNbHru3DklJSXZdY6T7t1uL126pDp16mjr1q0aNWqU1q1bp5iYGC1atMimnsVi0Q8//KDIyEiNHz9eVatWVaFChdSnTx/rcygpx8AjjzySqi0uXLjQ2hZT2lV6+8ted5s/ZR2LFi1Su3btVLhwYX366afavHmzYmJi1K1bN127di3V/M6MJGvP98+5c+dkjElzPcHBwTaxpyhQoIDNe3d393TL09ome9qlvcdLet/79p43pXufMzLyfeXo8Zty7rtTetcvbdu2TRXLuHHjZIzR2bNn011PRuK7c91ubm7y8/Oztgd7j6+MXAelxd5zgqPrcXafpqzfkYQxrePO3muyu7nXeTYtrjyn2iNlf2XkGipbj/53L0uWLNHly5e1aNEimyEk0xr62tPTM9UDy9KtE1HBggVTlac8oFm+fHn16dNHderUued/6/z8/PTzzz+nKr9zoIqU9Q0ZMkRt2rRJc1m3P2zojJT/3B4/fvyedT08PLR27VpFRkaqYcOGWr58uXWb8+fPb/3PYe/evdOcPywszKEYP/30U9WtW1fTpk2zKb/zAdlChQpp48aNSk5OtiuxuhtXbI+zn2PKA5zLly9Pc/rtPQ/3W8oJMOWEdbv0Blq5l/vVzuvUqaM6deooKSlJ27Zt05QpU9S3b18FBASoQ4cOTu1XPz8/bd26VcYYm8Tq1KlTunnzZprnCkfVr19fFSpU0NSpU5U7d27t2LFDn376qcuWf6dPP/1UnTt31pgxY2zK//77b+XLl8/63s3NTf3791f//v11/vx5rV69Wv/9738VGRmpY8eOydvb2+51ptV24uPj5e7ubu2VuNu5OS13JrwFChRQzpw57TrH2WPNmjX6888/tW7dOut/oiWlOcxySEiIPvroI0m3/kv9+eefKzo6WomJiZo+fbq1vXz55Zc231F3Sjn+0ttf9rrb/Cnr+PTTTxUWFqaFCxfa7Mu0PgMp9f7OCHu+f/Lnz68cOXKkOQhUyn/gXXncSfa1S3uPFz8/P5eeN9OSke8rR49fPz8/u9pfymcxZcqUdEd+Sy+hzGh88fHxKly4sPX9zZs3debMGWtbtvf4ysh1UFrsPSc4uh5n92nK/HdLvNKT1vFt7zXZ/eCqc6o9UvZXRs4v/+qkKqUxpGTA0q1b2GbOnJmqbmhoqHbv3m1T9vvvv+vAgQOpduiHH36oTz/9VB9//LEiIiJUtWpVde3aVUuWLLlrPPXq1dPnn3+ub775xqbr884hLkuXLq3w8HD98ssvqU7Y9rAn409Rq1Yt+fr6avr06erQocM9vyCrVKmi9evXq2HDhqpbt65WrVolf39/eXt7q169etq5c6cqVapk/c+gs/FJtz7H2z9DSdq9e7c2b96sokWLWsuaNm2q+fPna/bs2XbdAng3rtgeZz/HJ554QgsWLFBSUpKqV6+e4fldqXTp0goMDNTnn3+u/v37W8uPHj2qTZs2Wf9jnNFlOrN/7iVnzpyqXr26ypQpo88++0w7duxQhw4dnNqvDRo00Oeff64lS5boySeftJanjMLWoEEDl25Dnz591LNnT124cEEBAQF6+umnXbr826V1nH333Xc6ceKESpYsmeY8+fLlU9u2bXXixAn17dtXcXFxqW5zuptFixZpwoQJ1v8IXrx4Ud9++63q1Klj7f0PDQ3VqVOn9Ndff1kvHBITE7VixQq71uHl5aWIiAh98cUXGj16tNMX4Gl9r0jSBx98cNf5SpUqpddff11fffWV9Va7yMhIubm56fDhw+neZiPdOlaCgoI0f/589e/f3xrDkSNHMnT87dmzR7/88ovNLVzz5s1Tnjx5rD2gFotF7u7uNt8F8fHxaY7+56xSpUqpRIkS+vjjj9W/f/9U+1SSfHx8VL16dS1atEhvv/22dbj25ORkffrppypSpIhKlSrl0rjsaZf2Hi8RERF6++23tXfvXptjY8GCBS6LNyPfV7fLyPFbr149jR8/Ps32c7vatWsrX7582rt3r9M/On6v+D777DM9/PDD1veff/65bt68aR2x2d7jy552KKX/XW/vOcHe9dzJ2X2acvvr4cOHU01z5G4We6/J7jdnzqmS7eeZ1s9ApDw+kJHvtH91UtWoUSO5u7vrmWee0aBBg3Tt2jVNmzZN586dS1W3U6dOeu6559SrVy899dRTOnLkiMaPH5/qHvxff/1Vffr0UZcuXdS1a1dJ0kcffaS2bdtq8uTJdx0Ws3Pnzpo0aZI6d+6s0aNHKzw8XMuWLUvz4uCDDz5Q06ZNFRkZqaioKBUuXFhnz57Vvn37tGPHDn3xxRfpridPnjwKCQnR119/rQYNGqhAgQIqWLBgmsMS586dW++8845eeOEFNWzYUN27d1dAQIAOHTqkX375RVOnTk01T9myZbVhwwY1bNhQjz/+uFavXq0iRYro3Xff1WOPPaY6deropZdeUmhoqC5evKhDhw7p22+/1Zo1ayTdukXLy8tLn332mcqWLavcuXMrODg43QuDJ554Qm+++aaGDx+uiIgIHThwQCNHjlRYWJhu3rxprffMM89o1qxZ6tmzpw4cOKB69eopOTlZW7duVdmyZdWhQ4d091laXLE9znyOHTp00GeffaZmzZrpP//5jx599FHlypVLx48f19q1a9WqVSubC/v7KUeOHBoxYoR69Oihtm3bqlu3bjp//rxGjBihoKAgh3sGndk/aZk+fbrWrFmj5s2bq1ixYrp27Zp1WPmGDRtKcm6/du7cWf/73//UpUsXxcXFqWLFitq4caPGjBmjZs2aWdfhKs8995yGDBmiH3/8Ua+//rrdF0uOeOKJJzR79myVKVNGlSpV0vbt2zVhwoRUt6q0aNFCFSpUULVq1VSoUCEdOXJEkydPVkhIiMLDwzO0zpw5c6pRo0bq37+/kpOTNW7cOCUkJNj8IGP79u31xhtvqEOHDho4cKCuXbum9957L0PPXE2cOFGPPfaYqlevrtdee00lS5bUX3/9pW+++UYffPBBhnp9a9Wqpfz586tnz54aPny4cuXKpc8++0y//PKLTb3du3fr5Zdf1tNPP63w8HC5u7trzZo12r17t1577TVJtxLGkSNHaujQofrjjz/UpEkT5c+fX3/99Zd+/vln+fj4aMSIEcqRI4fefPNNvfDCC3ryySfVvXt3nT9/XtHR0Rm6/S84OFgtW7ZUdHS0goKC9Omnn2rVqlUaN26ctQfgiSee0KJFi9SrVy+1bdtWx44d05tvvqmgoCAdPHjQ7nXZ63//+59atGihGjVqqF+/fipWrJiOHj2qFStW6LPPPpMkjR07Vo0aNVK9evX06quvyt3dXe+//75+++03zZ8/36nesrTY0y7tPV769u2rjz/+WE2bNtXIkSMVEBCgefPmaf/+/ZLk9F0VKez9vnL0+E3ZjubNm2vUqFEKCAjQZ599Zt2OFLlz59aUKVPUpUsXnT17Vm3btpW/v79Onz6tX375RadPn07Vw3G7jMS3aNEiubm5qVGjRtqzZ4+GDRumhx56yPrsr73Hl2RfO6xYsaJ1X3fp0kW5cuVS6dKl7T4n2LueOzm7T4sUKaLixYtry5Yt6tOnj820ihUrasGCBVq4cKGKFy8uT09P63amx95rMldz5Tk1Zdslady4cWratKly5sxp80+JLVu2KGfOnHr88cftD9LuIS2ygbRG//v222/NQw89ZDw9PU3hwoXNwIEDzffff59q1J3k5GQzfvx4U7x4cePp6WmqVatm1qxZYzP616VLl0yZMmVMuXLlUo2U1Lt3b5MrV65Uo/bc6fjx4+app54yuXPnNnny5DFPPfWU2bRpU5qjx/3yyy+mXbt2xt/f3+TKlcsEBgaa+vXrm+nTp99zX6xevdpUqVLFeHh4GEnWkQ3TGqrTGGOWLVtmIiIijI+Pj/H29jblypWzGd0vrX17/PhxU6ZMGRMaGmodmjk2NtZ069bNFC5c2OTKlcsUKlTI1KpVy4waNcpm3vnz55syZcqYXLlypTtSYYrr16+bV1991RQuXNh4enqaqlWrmiVLlqQ5KtjVq1fNG2+8YcLDw427u7vx8/Mz9evXtxkKV5Lp3bt3qvWkNQKkK7bHmc/xxo0b5u2337a24dy5c5syZcqYHj16mIMHD9rE3rx581TzpzV6ZVrujDmtIdWNMWbGjBmmZMmSxt3d3ZQqVcp8/PHHplWrVjajgqWMTHX7MM3prccY5/bPnTZv3myefPJJExISYjw8PIyfn5+JiIgw33zzjU09e/drWvvvzJkzpmfPniYoKMi4ubmZkJAQM2TIEJuhWFO21d52djdRUVHGzc3NHD9+3O55HInj3Llz5vnnnzf+/v7G29vbPPbYY2bDhg2p9sE777xjatWqZQoWLGjc3d1NsWLFzPPPP2/i4uLsjimljYwbN86MGDHCFClSxLi7u5sqVaqYFStWpKq/bNkyU7lyZePl5WWKFy9upk6dmu7of2ltqzHG7N271zz99NPGz8/PGndUVJT1c0s5N8bExNjMl9axsGnTJlOzZk3j7e1tChUqZF544QWzY8cOm/P4X3/9ZaKiokyZMmWMj4+PyZ07t6lUqZKZNGmSzaiYxhizZMkSU69ePZM3b17j4eFhQkJCTNu2bVMNlfzhhx9az20px196oyPeKeUc8eWXX5ry5csbd3d3ExoammpEPGNujfAaGhpqPDw8TNmyZc3MmTMzvL8zYvPmzaZp06bG19fXeHh4mBIlSqQa2W3Dhg2mfv36xsfHx3h5eZkaNWqYb7/91qZOep9hSuynT5+2Kb/zey0j7dLe48UYY3777TfTsGFD4+npaQoUKGCef/55M2fOnFQjw0VERJjy5cun2j93fsZpjf6XUn6v7ytnjt+9e/eaRo0a2WzH119/neZ3xfr1603z5s1NgQIFTK5cuUzhwoVN8+bNzRdffHHXddgTX8rnuX37dtOiRQvr9dQzzzxj/vrrr1TLtPf4sqcdDhkyxAQHB5scOXLYbLc95wR715PedZqj+9QYY4YNG2by58+f6nsqLi7ONG7c2OTJk8c6TL0x/3feS2vZGbkmu/M7PyPn2Tu5+px6/fp188ILL5hChQoZi8WSap/XqVMn1YiL92L5/xsNABl2/vx5lSpVSq1bt9aMGTMyO5x/ncTERIWGhuqxxx5z6geRs5q4uDiFhYVpwoQJevXVVzM7nAdCaGioKlSocM8fn36Q/ZPt8sUXX9T8+fN15syZ+9oD/W8UHR2tESNG6PTp0y5/nu7f6s8//1RYWJjmzp2r9u3bZ3Y4Wd7hw4cVHh6uFStWqFGjRnbP96++/Q+A68THx2v06NGqV6+e/Pz8dOTIEU2aNEkXL17Uf/7zn8wO71/l9OnTOnDggGbNmqW//vrLemsDgOxn5MiRCg4OVvHixXXp0iUtXbpUH3744X2/pRdIERwcrL59+2r06NF6+umnXXbb6b/VqFGj1KBBgwwlVBJJFQA7eXh4KC4uTr169dLZs2fl7e2tGjVqaPr06Spfvnxmh/ev8t1336lr164KCgrS+++/n+Yw6ve6dz1HjhyZ8sVpT1zAgyRXrlyaMGGCjh8/rps3byo8PFwTJ07kn1H4R73++uvy9vbWiRMn/tEBJbKbmzdvqkSJEhoyZEiG5+X2PwDIhu71cH6XLl00e/bsfyaY/y/l9qm7GT58uF0/lg4AQHZCTxUAZEMxMTF3nZ4ZzxoEBwffMy5Hht8HACCro6cKAAAAAJzAze0AAAAA4IQH4va/5ORk/fnnn8qTJ4/LfyQQAAAAQPZhjNHFixcVHBzssgGUHoik6s8//2SkEwAAAABWx44dU5EiRVyyrAciqcqTJ4+kWzsub968mRwNAAAAgMySkJCgokWLWnMEV3ggkqqUW/7y5s1LUgUAAADApY8FMVAFAAAAADiBpAoAAAAAnEBSBQAAAABOeCCeqbJHUlKSbty4kdlhAHgA5cqVSzlz5szsMAAAgIMe+KTKGKP4+HidP38+s0MB8ADLly+fAgMD+S09AACyoQc+qUpJqPz9/eXt7c0FDYB/lDFGV65c0alTpyRJQUFBmRwRAADIqAc6qUpKSrImVH5+fpkdDoAHlJeXlyTp1KlT8vf351ZAAACymQd6oIqUZ6i8vb0zORIAD7qU8xDPdgIAkP080ElVCm75A5DZOA8BAJB9kVQByDTr1q3TtGnTMjsMAAAAp5BU/QvFxcXJYrFo165dkm5duFosFkY4hF3ubD/3S2xsrJ577jk98sgj93U9AAAA99sDPVDF3YS+9t0/ur64t5rft2XXqlVLJ0+elK+vr8uWGRcXp7CwMO3cuVOVK1d22XLvtG7dOkVFRSkuLu6+rcMR69atU7169XTu3Dnly5cvs8PJkkJDQ9W3b1/17ds31bTExEQ988wzmjlzpqpVq/bPBwcAAOBCJFUPAHd3dwUGBmZ2GICVu7u7tmzZktlhAAAAuAS3/2VTycnJGjdunEqWLCkPDw8VK1ZMo0ePTrNuWrf/bdq0SY8//ri8vLxUtGhR9enTR5cvX7ZODw0N1ZgxY9StWzflyZNHxYoV04wZM6zTw8LCJElVqlSRxWJR3bp1ret69NFH5ePjo3z58ql27do6cuRImnGl3Ga2aNEi1atXT97e3nrooYe0efPmdLf78OHDatWqlQICApQ7d2498sgjWr16tXX6yJEjVbFixVTzPfzww3rjjTckSTExMWrUqJEKFiwoX19fRUREaMeOHTb1LRaLPvzwQz355JPy9vZWeHi4vvnmG2vc9erVkyTlz59fFotFUVFRacY7e/Zs5cuXT0uWLFGpUqXk6empRo0a6dixY3ZvkyS9//77Cg8Pl6enpwICAtS2bdt099GZM2f0zDPPqEiRIvL29lbFihU1f/58mzr2tJ8//vjjrp/L3dpQ3bp1deTIEfXr108Wi8VmEIZ7tT0AAIDshqQqmxoyZIjGjRunYcOGae/evZo3b54CAgLsmvfXX39VZGSk2rRpo927d2vhwoXauHGjXn75ZZt677zzjqpVq6adO3eqV69eeumll7R//35J0s8//yxJWr16tU6ePKlFixbp5s2bat26tSIiIrR7925t3rxZL7744j1HNRs6dKheffVV7dq1S6VKldIzzzyjmzdvpln30qVLatasmVavXq2dO3cqMjJSLVq00NGjRyVJ3bp10969exUTE2OdZ/fu3dq5c6c18bl48aK6dOmiDRs2aMuWLQoPD1ezZs108eJFm3WNGDFC7dq10+7du9WsWTM9++yzOnv2rIoWLaqvvvpKknTgwAGdPHlS7777brrbd+XKFY0ePVpz5szRTz/9pISEBHXo0MHubdq2bZv69OmjkSNH6sCBA1q+fLkef/zxdNd37do1Pfzww1q6dKl+++03vfjii+rUqZO2bt1qrWNP+7nb53KvNrRo0SIVKVJEI0eO1MmTJ3Xy5Em75gMAAMiWTCa6ceOGGTp0qAkNDTWenp4mLCzMjBgxwiQlJVnrJCcnm+HDh5ugoCDj6elpIiIizG+//Zah9Vy4cMFIMhcuXLApv3r1qtm7d6+5evVqqnlCBi/9R18ZkZCQYDw8PMzMmTPTnB4bG2skmZ07dxpjjFm7dq2RZM6dO2eMMaZTp07mxRdftJlnw4YNJkeOHNZ9ERISYp577jnr9OTkZOPv72+mTZuW5jqMMebMmTNGklm3bp1d25GyjA8//NBatmfPHiPJ7Nu3z65lGGNMuXLlzJQpU6zvmzZtal566SXr+759+5q6deumO//NmzdNnjx5zLfffmstk2Ref/116/tLly4Zi8Vivv/+e2NM6n2anlmzZhlJZsuWLdayffv2GUlm69atdm3TV199ZfLmzWsSEhLuuq67adasmRkwYIAxxv72c7fPxd42NGnSJJs69sz3oLrb+QgAALhOermBMzK1p2rcuHGaPn26pk6dqn379mn8+PGaMGGCpkyZYq0zfvx4TZw4UVOnTlVMTIwCAwPVqFGjVL0KD5J9+/bp+vXratCggUPzb9++XbNnz1bu3Lmtr8jISCUnJys2NtZar1KlSta/LRaLAgMDderUqXSXW6BAAUVFRVl7Wt59911rD8Xd3L6eoKAgSUp3PZcvX9agQYNUrlw55cuXT7lz59b+/futvTqS1L17d82fP1/Xrl3TjRs39Nlnn6lbt27W6adOnVLPnj1VqlQp+fr6ytfXV5cuXbJZxp1x+fj4KE+ePHfd/vS4ubnZDMZQpkwZ5cuXT/v27bNrmxo1aqSQkBAVL15cnTp10meffaYrV66ku76kpCSNHj1alSpVkp+fn3Lnzq2VK1dal2dv+7nb52JvG7qTo/MBAABkZZk6UMXmzZvVqlUrNW9+a+S70NBQzZ8/X9u2bZMkGWM0efJkDR06VG3atJEkzZkzRwEBAZo3b5569OiRabFnJi8vL6fmT05OVo8ePdSnT59U04oVK2b9O1euXDbTLBaLkpOT77rsWbNmqU+fPlq+fLkWLlyo119/XatWrVKNGjXSnef29aTcKpjeegYOHKgVK1bo7bffVsmSJeXl5aW2bdsqMTHRWqdFixby8PDQ4sWL5eHhoevXr+upp56yTo+KitLp06c1efJkhYSEyMPDQzVr1rRZhqPbn560boFMKbvXNuXJk0c7duzQunXrtHLlSr3xxhuKjo5WTExMmiMPvvPOO5o0aZImT56sihUrysfHR3379rUuz972c7fPxd42dCdH5wMAAMjKMjWpeuyxxzR9+nT9/vvvKlWqlH755Rdt3LhRkydPlnTrd2zi4+PVuHFj6zweHh6KiIjQpk2b0k2qrl+/ruvXr1vfJyQk3Nft+KeFh4fLy8tLP/zwg1544YUMz1+1alXt2bNHJUuWdDgGd3d3Sbd6Re5UpUoVValSRUOGDFHNmjU1b968uyZVGbFhwwZFRUXpySeflHTreaQ7h1t3c3NTly5dNGvWLHl4eKhDhw7y9va2Wcb777+vZs2aSZKOHTumv//+O0Nx3G3773Tz5k1t27ZNjz76qKRbz2GdP39eZcqUydA2NWzYUA0bNtTw4cOVL18+rVmzxvrPhttt2LBBrVq10nPPPSfpViJz8OBBlS1bVpLz7Ueyrw25u7un2j+uaHsAAABZTaYmVYMHD9aFCxdUpkwZ5cyZ03rb0jPPPCNJio+Pl6RUD9AHBASkO6KcJI0dO1YjRoy4f4FnMk9PTw0ePFiDBg2Su7u7ateurdOnT2vPnj16/vnn7zn/4MGDVaNGDfXu3Vvdu3eXj4+P9u3bp1WrVtncenk3/v7+8vLy0vLly1WkSBF5enrq7NmzmjFjhlq2bKng4GAdOHBAv//+uzp37uzsJluVLFlSixYtUosWLWSxWDRs2LA0e49eeOEFaxLx008/pVrGJ598omrVqikhIUEDBw7McO9fSEiILBaLli5dqmbNmsnLy0u5c+dOs26uXLn0yiuv6L333lOuXLn08ssvq0aNGtYk617btHTpUv3xxx96/PHHlT9/fi1btkzJyckqXbp0uvvoq6++0qZNm5Q/f35NnDhR8fHx1v3hbPuR7GtDoaGh+vHHH9WhQwd5eHioYMGCLml7ALK3f/p3IP8J9/O3JgFkD5n6TNXChQv16aefat68edqxY4fmzJmjt99+W3PmzLGpd+etU8aYu44oN2TIEF24cMH6un346n+LYcOGacCAAXrjjTdUtmxZtW/f3u7nfSpVqqT169fr4MGDqlOnjqpUqaJhw4ZZn5uxh5ubm9577z198MEHCg4OVqtWreTt7a39+/frqaeeUqlSpfTiiy/q5ZdfdultmpMmTVL+/PlVq1YttWjRQpGRkapatWqqeuHh4apVq5ZKly6t6tWr20z7+OOPde7cOVWpUkWdOnVSnz595O/vn6E4ChcurBEjRui1115TQEDAXUev8/b21uDBg9WxY0fVrFlTXl5eWrBggd3blC9fPi1atEj169dX2bJlNX36dM2fP1/ly5dPc33Dhg1T1apVFRkZqbp16yowMFCtW7dOVcfR9iPZ14ZGjhypuLg4lShRQoUKFbJ7PgAAgOzGYowxmbXyokWL6rXXXlPv3r2tZaNGjdKnn36q/fv3648//lCJEiW0Y8cOValSxVqnVatWypcvX6rkKz0JCQny9fXVhQsXlDdvXmv5tWvXFBsbq7CwMHl6erpuw5DpjDEqU6aMevToof79+2daHLNnz1bfvn1tfiMMSAvnIzwo6KkCkNnSyw2ckak9VVeuXFGOHLYh5MyZ03rrU1hYmAIDA7Vq1Srr9MTERK1fv161atX6R2NF9nHq1ClNnDhRJ06cUNeuXTM7HAAAAPzLZeozVS1atNDo0aNVrFgxlS9fXjt37tTEiROtw19bLBb17dtXY8aMUXh4uMLDwzVmzBh5e3urY8eOmRk6srCAgAAVLFhQM2bMUP78+TM7HAAAAPzLZWpSNWXKFA0bNky9evXSqVOnFBwcrB49euiNN96w1hk0aJCuXr2qXr166dy5c6pevbpWrlypPHnyZGLkyMoy8Y7WVKKiohQVFZXZYQAAAOA+ytRnqv4pPFMFIKvjfIQHBc9UAchs/7pnqgAAAAAguyOpAgAAAAAnkFQBAAAAgBNIqgAAAADACSRVAAAAAOAEkirgX+j8+fMaMWKETp48mdmhZJp169Zp2rRpmR0GAAB4AJBU/QvFxcXJYrFo165dkm5dXFosFp0/fz5T44JUt25d9e3b976vJyoqSlevXlVQUNB9X9e93Nke/wmxsbF67rnn9Mgjj9yzrqvi+6c+WwAAkPVk6o//ZmnRvv/w+i7ct0XXqlVLJ0+elK+v67YpLi5OYWFh2rlzpypXruyy5WaW0NBQ9e3bN1tcFEdHR2vJkiXpJgHvvPOOcufOrbFjx/6zgWURiYmJeuaZZzRz5kxVq1btnvWLFi2qkydPqmDBgv9AdAAA4N+IpOoB4O7ursDAwMwOA/+QAQMGZMp6jTFKSkqSm1vmnlbc3d21ZcsWu+omJiZyfAAAAKdx+182lZycrHHjxqlkyZLy8PBQsWLFNHr06DTrpnX736ZNm/T444/Ly8tLRYsWVZ8+fXT58mXr9NDQUI0ZM0bdunVTnjx5VKxYMc2YMcM6PSwsTJJUpUoVWSwW1a1b17quRx99VD4+PsqXL59q166tI0eOpLsdgwcPVqlSpeTt7a3ixYtr2LBhunHjhqRbvWE5cuTQtm3bbOaZMmWKQkJCrBfxzz//vMLCwuTl5aXSpUvr3XfftakfFRWl1q1b6+2331ZQUJD8/PzUu3dv63rq1q2rI0eOqF+/frJYLLJYLOnGO3HiRFWsWFE+Pj4qWrSoevXqpUuXLtnU+emnnxQRESFvb2/lz59fkZGROnfunHV6cnKyBg0apAIFCigwMFDR0dE281+4cEEvvvii/P39lTdvXtWvX1+//PKLJGn27NkaMWKEfvnlF2uss2fPvud8aUlMTNTLL7+soKAgeXp6KjQ01Nq7ldYtcefPn5fFYtG6desk/V+7WrFihapVqyYPDw9t2LAh3fWlsOczu1PKur777js99NBD8vT0VPXq1fXrr7/a1LOnXY8aNUpRUVHy9fVV9+7d09zW9evX69FHH5WHh4eCgoL02muv6ebNm9bply9fVufOnZU7d24FBQXpnXfeSXP/Dho0SIULF5aPj4+qV69u3XcAAODfhaQqmxoyZIjGjRunYcOGae/evZo3b54CAgLsmvfXX39VZGSk2rRpo927d2vhwoXauHGjXn75ZZt677zzjqpVq6adO3eqV69eeumll7R//35J0s8//yxJWr16tU6ePKlFixbp5s2bat26tSIiIrR7925t3rxZL7744l2TlDx58mj27Nnau3ev3n33Xc2cOVOTJk2SdOsCuGHDhpo1a5bNPLNmzVJUVJQsFouSk5NVpEgRff7559q7d6/eeOMN/fe//9Xnn39uM8/atWt1+PBhrV27VnPmzNHs2bOtyciiRYtUpEgRjRw5UidPnrzr4A45cuTQe++9p99++01z5szRmjVrNGjQIOv0Xbt2qUGDBipfvrw2b96sjRs3qkWLFkpKSrLWmTNnjnx8fLR161aNHz9eI0eO1KpVqyTd6u1p3ry54uPjtWzZMm3fvl1Vq1ZVgwYNdPbsWbVv314DBgxQ+fLlrbG2b9/+nvOl5b333tM333yjzz//XAcOHNCnn36q0NDQdLc9PYMGDdLYsWO1b98+VapU6Z717f3M0jJw4EC9/fbbiomJkb+/v1q2bGlNju1t1xMmTFCFChW0fft2DRs2LNU6Tpw4oWbNmumRRx7RL7/8omnTpumjjz7SqFGjbOJYu3atFi9erJUrV2rdunXavn27zXK6du2qn376SQsWLNDu3bv19NNPq0mTJjp48OA9txMAAGQvFmOMyewg7reEhAT5+vrqwoULyps3r7X82rVrio2NVVhYmDw9PW1nysLPVF28eFGFChXS1KlT9cILL6SafufzTuvWrVO9evV07tw55cuXT507d5aXl5c++OAD6zwbN25URESELl++bO21qFOnjj755BNJty72AwMDNWLECPXs2TPNZ6rOnj0rPz8/rVu3ThEREQ7thgkTJmjhwoXW3qnPP/9cPXv21MmTJ+Xh4aFffvlFVapU0R9//JFuAtC7d2/99ddf+vLLLyXd6qlat26dDh8+rJw5c0qS2rVrpxw5cmjBggWSHH+m6osvvtBLL72kv//+W5LUsWNHHT16VBs3bkyzft26dZWUlGTTo/Poo4+qfv36euutt7RmzRo9+eSTOnXqlDw8PKx1SpYsqUGDBunFF19M85kqe+a7U58+fbRnzx6tXr06VeKb1ud7/vx55c+fX2vXrlXdunWt7WrJkiVq1apVuvvInufv7vzM7pSyrgULFqh9+/aSbrW3IkWKaPbs2WrXrp3d7bpKlSpavHhxuvENHTpUX331lfbt22fdL++//74GDx6sCxcu6MqVK/Lz89PcuXNTxfLiiy9q8uTJOnz4sMLDw3X8+HEFBwdb19WwYUM9+uijGjNmTKptvOv5CPgXCX3tu8wOweXi3mqe2SEAyID0cgNn8ExVNrRv3z5dv35dDRo0cGj+7du369ChQ/rss8+sZcYYJScnKzY2VmXLlpUkm14Hi8WiwMBAnTp1Kt3lFihQQFFRUYqMjFSjRo3UsGFDtWvX7q4j0H355ZeaPHmyDh06pEuXLunmzZs2jbt169Z6+eWXtXjxYnXo0EEff/yx6tWrZ5NQTZ8+XR9++KGOHDmiq1evKjExMdXFe/ny5a0JlSQFBQWlunXMHmvXrtWYMWO0d+9eJSQk6ObNm7p27ZouX74sHx8f7dq1S08//fRdl3Fnb05QUJB1v27fvl2XLl2Sn5+fTZ2rV6/q8OHD6S7TkfmioqLUqFEjlS5dWk2aNNETTzyhxo0b3zX2tNgzGMSd7PnM0lKzZk3r3wUKFFDp0qW1b98+Sfa363vFu2/fPtWsWdMm0axdu7YuXbqk48eP69y5c0pMTEwzlhQ7duyQMUalSpWyWfb169dTfUYAACD7I6nKhry8vJyaPzk5WT169FCfPn1STStWrJj171y5ctlMS7nd7m5mzZqlPn36aPny5Vq4cKFef/11rVq1SjVq1EhVd8uWLerQoYNGjBihyMhI+fr6asGCBTbPp7i7u6tTp06aNWuW2rRpo3nz5mny5MnW6Z9//rn69eund955RzVr1lSePHk0YcIEbd261WZdjmzLnY4cOaJmzZqpZ8+eevPNN1WgQAFt3LhRzz//vPUWNHs+m7vFkpycrKCgoDSfvcmXL1+6y3RkvqpVqyo2Nlbff/+9Vq9erXbt2qlhw4b68ssvlSPHrTuDb+/ITtnGO/n4+KQbV1rs/czslZL82Nuu7xWvMSZVz13KfrBYLLKncz85OVk5c+bU9u3bbZJ5ScqdO/c95wcAANkLSVU2FB4eLi8vL/3www9p3v53L1WrVtWePXtUsmRJh2Nwd3eXJJtnhVJUqVJFVapU0ZAhQ1SzZk3NmzcvzaTqp59+UkhIiIYOHWotS2tQixdeeEEVKlTQ+++/rxs3bqhNmzbWaRs2bFCtWrXUq1cva9ndenTutj1pbcvttm3bpps3b+qdd96xJh13PgdUqVIl/fDDDxoxYkSGY5BufTbx8fFyc3NL9/bGtGK1Z7605M2bV+3bt1f79u3Vtm1bNWnSRGfPnlWhQoUkSSdPnlSVKlUkyWW/M+XMZ7ZlyxZrgnTu3Dn9/vvvKlOmjCTXtGtJKleunL766iub5GrTpk3KkyePChcurPz58ytXrlxpxpJy22uVKlWUlJSkU6dOqU6dOk7FAwAAsj4GqsiGPD09NXjwYA0aNEhz587V4cOHtWXLFn300Ud2zT948GBt3rxZvXv31q5du3Tw4EF98803euWVV+yOwd/fX15eXlq+fLn++usvXbhwQbGxsRoyZIg2b96sI0eOaOXKlfr999+tt13dqWTJkjp69KgWLFigw4cP67333rN51iVF2bJlVaNGDQ0ePFjPPPOMTW9QyZIltW3bNq1YsUK///67hg0bppiYGLu3I0VoaKh+/PFHnThxwvp81J1KlCihmzdvasqUKfrjjz/0ySefaPr06TZ1hgwZopiYGPXq1Uu7d+/W/v37NW3atHSXeaeGDRuqZs2aat26tVasWKG4uDht2rRJr7/+uvU5s9DQUMXGxmrXrl36+++/df36dbvmu9OkSZO0YMEC7d+/X7///ru++OILBQYGKl++fPLy8lKNGjX01ltvae/evfrxxx/1+uuvZ2CPps+Zz2zkyJH64Ycf9NtvvykqKkoFCxZU69atJbmmXUtSr169dOzYMb3yyivav3+/vv76aw0fPlz9+/dXjhw5lDt3bj3//PMaOHCgTSwpibYklSpVSs8++6w6d+6sRYsWKTY2VjExMRo3bpyWLVuWoXgAAEDWR1KVTQ0bNkwDBgzQG2+8obJly6p9+/Z3fd7pdpUqVdL69et18OBB1alTR1WqVNGwYcPu+uzTndzc3PTee+/pgw8+UHBwsFq1aiVvb2/t379fTz31lEqVKqUXX3xRL7/8snr06JHmMlq1aqV+/frp5ZdfVuXKlbVp06Y0R2OTpOeff16JiYnq1q2bTXnPnj3Vpk0btW/fXtWrV9eZM2dsekDsNXLkSMXFxalEiRLWXpo7Va5cWRMnTtS4ceNUoUIFffbZZ6l+YLdUqVJauXKlfvnlFz366KOqWbOmvv76a7t/u8lisWjZsmV6/PHH1a1bN5UqVUodOnRQXFycdXTHp556Sk2aNFG9evVUqFAhzZ8/36757pQ7d26NGzdO1apV0yOPPKK4uDgtW7bMmhx8/PHHunHjhqpVq6b//Oc/NqPfOcOZz+ytt97Sf/7zHz388MM6efKkvvnmG2uvqSvatSQVLlxYy5Yt088//6yHHnpIPXv21PPPP2+TVE6YMEGPP/64WrZsqYYNG+qxxx7Tww8/bLOcWbNmqXPnzhowYIBKly6tli1bauvWrSpatGiG4gEAAFkfo/8x2la2MHr0aC1YsMChwSWQ/d05guW/EecjPCgY/Q9AZrsfo//RU4Us7dKlS4qJidGUKVPSHIAAAAAAyGwkVcjSXn75ZT322GOKiIhIdesfAAAAkBUw+h+ytNmzZ2v27NmZHQYyWd26de0ayhwAACAz0FMFAAAAAE4gqZL4DziATMd5CACA7OuBTqpy5colSbpy5UomRwLgQZdyHko5LwEAgOzjgX6mKmfOnMqXL5/19528vb1lsVgyOSoADxJjjK5cuaJTp04pX758ypkzZ2aHBAAAMuiBTqokKTAwUJLs/uFcALgf8uXLZz0fAQCA7OWBT6osFouCgoLk7++vGzduZHY4AB5AuXLloocKAIBs7IFPqlLkzJmTixoAAAAAGfZAD1QBAAAAAM4iqQIAAAAAJ5BUAQAAAIATSKoAAAAAwAkkVQAAAADgBJIqAAAAAHACSRUAAAAAOIGkCgAAAACcQFIFAAAAAE4gqQIAAAAAJ5BUAQAAAIATSKoAAAAAwAkkVQAAAADgBJIqAAAAAHACSRUAAAAAOIGkCgAAAACckKlJVWhoqCwWS6pX7969JUnGGEVHRys4OFheXl6qW7eu9uzZk5khAwAAAICNTE2qYmJidPLkSetr1apVkqSnn35akjR+/HhNnDhRU6dOVUxMjAIDA9WoUSNdvHgxM8MGAAAAAKtMTaoKFSqkwMBA62vp0qUqUaKEIiIiZIzR5MmTNXToULVp00YVKlTQnDlzdOXKFc2bNy8zwwYAAAAAqyzzTFViYqI+/fRTdevWTRaLRbGxsYqPj1fjxo2tdTw8PBQREaFNmzbddVnXr19XQkKCzQsAAAAA7ocsk1QtWbJE58+fV1RUlCQpPj5ekhQQEGBTLyAgwDotPWPHjpWvr6/1VbRo0fsSMwAAAABkmaTqo48+UtOmTRUcHGxTbrFYbN4bY1KV3WnIkCG6cOGC9XXs2DGXxwsAAAAAkuSW2QFI0pEjR7R69WotWrTIWhYYGCjpVo9VUFCQtfzUqVOpeq/u5OHhIQ8Pj/sTLAAAAADcJkv0VM2aNUv+/v5q3ry5tSwsLEyBgYHWEQGlW89drV+/XrVq1cqMMAEAAAAglUzvqUpOTtasWbPUpUsXubn9XzgWi0V9+/bVmDFjFB4ervDwcI0ZM0be3t7q2LFjJkYMAAAAAP8n05Oq1atX6+jRo+rWrVuqaYMGDdLVq1fVq1cvnTt3TtWrV9fKlSuVJ0+eTIgUAAAAAFKzGGNMZgdxvyUkJMjX11cXLlxQ3rx5MzscAAAeWKGvfZfZIbhc3FvN710JQJZxP3KDLPFMFQAAAABkVyRVAAAAAOAEkioAAAAAcAJJFQAAAAA4gaQKAAAAAJxAUgUAAAAATiCpAgAAAAAnkFQBAAAAgBNIqgAAAADACSRVAAAAAOAEkioAAAAAcAJJFQAAAAA4gaQKAAAAAJxAUgUAAAAATiCpAgAAAAAnkFQBAAAAgBNIqgAAAADACW4ZncEYo/Xr12vDhg2Ki4vTlStXVKhQIVWpUkUNGzZU0aJF70ecAAAAAJAl2d1TdfXqVY0ZM0ZFixZV06ZN9d133+n8+fPKmTOnDh06pOHDhyssLEzNmjXTli1b7mfMAAAAAJBl2N1TVapUKVWvXl3Tp09XZGSkcuXKlarOkSNHNG/ePLVv316vv/66unfv7tJgAQAAACCrsTup+v7771WhQoW71gkJCdGQIUM0YMAAHTlyxOngAAAAACCrs/v2v3slVLdzd3dXeHi4QwEBAAAAQHaS4YEqbnfz5k198MEHWrdunZKSklS7dm317t1bnp6erooPAAAAALI0p5KqPn366Pfff1ebNm1048YNzZ07V9u2bdP8+fNdFR8AAAAAZGkZSqoWL16sJ5980vp+5cqVOnDggHLmzClJioyMVI0aNVwbIQAAAABkYRn68d+PPvpIrVu31okTJyRJVatWVc+ePbV8+XJ9++23GjRokB555JH7EigAAAAAZEUZSqqWLl2qDh06qG7dupoyZYpmzJihvHnzaujQoRo2bJiKFi2qefPm3a9YAQAAACDLyfAzVR06dFCTJk00cOBARUZG6oMPPtA777xzP2IDAAAAgCwvQz1VKfLly6eZM2dqwoQJ6tSpkwYOHKirV6+6OjYAAAAAyPIylFQdO3ZM7du3V8WKFfXss88qPDxc27dvl5eXlypXrqzvv//+fsUJAAAAAFlShpKqzp07y2KxaMKECfL391ePHj3k7u6ukSNHasmSJRo7dqzatWt3v2IFAAAAgCwnQ89Ubdu2Tbt27VKJEiUUGRmpsLAw67SyZcvqxx9/1IwZM1weJAAAAABkVRlKqqpWrao33nhDXbp00erVq1WxYsVUdV588UWXBQcAAAAAWV2Gbv+bO3eurl+/rn79+unEiRP64IMP7ldcAAAAAJAtZKinKiQkRF9++eX9igUAAAAAsh27e6ouX76coQVntD4AAAAAZEd2J1UlS5bUmDFj9Oeff6ZbxxijVatWqWnTpnrvvfdcEiAAAAAAZGV23/63bt06vf766xoxYoQqV66satWqKTg4WJ6enjp37pz27t2rzZs3K1euXBoyZAgDVgAAAAB4INidVJUuXVpffPGFjh8/ri+++EI//vijNm3apKtXr6pgwYKqUqWKZs6cqWbNmilHjgyNfwEAAAAA2VaGBqqQpCJFiqhfv37q16/f/YgHAAAAALIVupQAAAAAwAkkVQAAAADgBJIqAAAAAHACSRUAAAAAOMGhpOro0aMyxqQqN8bo6NGjGVrWiRMn9Nxzz8nPz0/e3t6qXLmytm/fbrPM6OhoBQcHy8vLS3Xr1tWePXscCRsAAAAAXM6hpCosLEynT59OVX727FmFhYXZvZxz586pdu3aypUrl77//nvt3btX77zzjvLly2etM378eE2cOFFTp05VTEyMAgMD1ahRI128eNGR0AEAAADApTI8pLp0q/fIYrGkKr906ZI8PT3tXs64ceNUtGhRzZo1y1oWGhpqs57Jkydr6NChatOmjSRpzpw5CggI0Lx589SjRw9HwgcAAAAAl8lQUtW/f39JksVi0bBhw+Tt7W2dlpSUpK1bt6py5cp2L++bb75RZGSknn76aa1fv16FCxdWr1691L17d0lSbGys4uPj1bhxY+s8Hh4eioiI0KZNm9JNqq5fv67r169b3yckJGRkMwEAAADAbhlKqnbu3CnpVg/Sr7/+Knd3d+s0d3d3PfTQQ3r11VftXt4ff/yhadOmqX///vrvf/+rn3/+WX369JGHh4c6d+6s+Ph4SVJAQIDNfAEBATpy5Ei6yx07dqxGjBiRkU0DAAAAAIdkKKlau3atJKlr16569913lTdvXqdWnpycrGrVqmnMmDGSpCpVqmjPnj2aNm2aOnfubK13562G6d1+mGLIkCHWXjXpVk9V0aJFnYoVAAAAANLi0EAVs2bNUt68eXXo0CGtWLFCV69elaQ0RwS8m6CgIJUrV86mrGzZstYRBAMDAyXJ2mOV4tSpU6l6r27n4eGhvHnz2rwAAAAA4H5wKKk6e/asGjRooFKlSqlZs2Y6efKkJOmFF17QgAED7F5O7dq1deDAAZuy33//XSEhIZJujTIYGBioVatWWacnJiZq/fr1qlWrliOhAwAAAIBLOZRU9e3bV7ly5dLRo0dtBqto3769li9fbvdy+vXrpy1btmjMmDE6dOiQ5s2bpxkzZqh3796Sbt3217dvX40ZM0aLFy/Wb7/9pqioKHl7e6tjx46OhA4AAAAALuXQkOorV67UihUrVKRIEZvy8PDwuw4gcadHHnlEixcv1pAhQzRy5EiFhYVp8uTJevbZZ611Bg0apKtXr6pXr146d+6cqlevrpUrVypPnjyOhA4AAAAALuVQUnX58mWbHqoUf//9tzw8PDK0rCeeeEJPPPFEutMtFouio6MVHR2d0TABAAAA4L5z6Pa/xx9/XHPnzrW+t1gsSk5O1oQJE1SvXj2XBQcAAAAAWZ1DPVUTJkxQ3bp1tW3bNiUmJmrQoEHas2ePzp49q59++snVMQIAAABAluVQT1W5cuW0e/duPfroo2rUqJEuX76sNm3aaOfOnSpRooSrYwQAAACALMuhnirp1m9IjRgxwpWxAAAAAEC243BSdf78ef388886deqUkpOTbaZ17tzZ6cAAAAAAIDtwKKn69ttv9eyzz+ry5cvKkyePLBaLdZrFYiGpAgAAAPDAcOiZqgEDBqhbt266ePGizp8/r3PnzllfZ8+edXWMAAAAAJBlOZRUnThxQn369Enzt6oAAAAA4EHiUFIVGRmpbdu2uToWAAAAAMh2HHqmqnnz5ho4cKD27t2rihUrKleuXDbTW7Zs6ZLgAAAAACCrcyip6t69uyRp5MiRqaZZLBYlJSU5FxUAAAAAZBMOJVV3DqEOAAAAAA+qDD9TdfPmTbm5uem33367H/EAAAAAQLaS4aTKzc1NISEh3OIHAAAAAHJw9L/XX39dQ4YM4TepAAAAADzwHHqm6r333tOhQ4cUHByskJAQ+fj42EzfsWOHS4IDAAAAgKzOoaSqdevWLg4DAAAAALInh5Kq4cOHuzoOAAAAAMiWHHqmSpLOnz+vDz/80ObZqh07dujEiRMuCw4AAAAAsjqHeqp2796thg0bytfXV3FxcerevbsKFCigxYsX68iRI5o7d66r4wQAAACALMmhnqr+/fsrKipKBw8elKenp7W8adOm+vHHH10WHAAAAABkdQ4lVTExMerRo0eq8sKFCys+Pt7poAAAAAAgu3Do9j9PT08lJCSkKj9w4IAKFSrkdFD/dqGvfZfZIbhU3FvNMzsEAAAAINM41FPVqlUrjRw5Ujdu3JAkWSwWHT16VK+99pqeeuoplwYIAAAAAFmZQ0nV22+/rdOnT8vf319Xr15VRESESpYsqTx58mj06NGujhEAAAAAsiyHbv/LmzevNm7cqDVr1mjHjh1KTk5W1apV1bBhQ1fHBwAAAABZmkNJ1dy5c9W+fXvVr19f9evXt5YnJiZqwYIF6ty5s8sCBAAAAICszKHb/7p27aoLFy6kKr948aK6du3qdFAAAAAAkF04lFQZY2SxWFKVHz9+XL6+vk4HBQAAAADZRYZu/6tSpYosFossFosaNGggN7f/mz0pKUmxsbFq0qSJy4MEAAAAgKwqQ0lV69atJUm7du1SZGSkcufObZ3m7u6u0NBQhlQHAAAA8EDJUFI1fPhwSVJoaKjat28vT0/P+xIUAAAAAGQXDo3+16VLF0m3Rvs7deqUkpOTbaYXK1bM+cgAAAAAIBtwKKk6ePCgunXrpk2bNtmUpwxgkZSU5JLgAAAAACCrcyipioqKkpubm5YuXaqgoKA0RwIEAAAAgAeBQ0nVrl27tH37dpUpU8bV8QAAAABAtuLQ71SVK1dOf//9t6tjAQAAAIBsx6Gkaty4cRo0aJDWrVunM2fOKCEhweYFAAAAAA8Kh27/a9iwoSSpQYMGNuUMVAEAAADgQeNQUrV27VpXxwEAAAAA2ZJDSVVERISr4wAAAACAbMnupGr37t2qUKGCcuTIod27d9+1bqVKlZwODAAAAACyA7uTqsqVKys+Pl7+/v6qXLmyLBaLjDGp6vFMFQAAAIAHid1JVWxsrAoVKmT9GwAAAACQgSHVQ0JCZLFYrH/f7WWv6OhoWSwWm1dgYKB1ujFG0dHRCg4OlpeXl+rWras9e/ZkYPMAAAAA4P5y6HeqXKl8+fI6efKk9fXrr79ap40fP14TJ07U1KlTFRMTo8DAQDVq1EgXL17MxIgBAAAA4P9kelLl5uamwMBA6yvlFkNjjCZPnqyhQ4eqTZs2qlChgubMmaMrV65o3rx5mRw1AAAAANyS6UnVwYMHFRwcrLCwMHXo0EF//PGHpFvPbcXHx6tx48bWuh4eHoqIiNCmTZvuuszr168rISHB5gUAAAAA90OGk6qkpCStX79e586dc3rl1atX19y5c7VixQrNnDlT8fHxqlWrls6cOaP4+HhJUkBAgM08AQEB1mnpGTt2rHx9fa2vokWLOh0rAAAAAKQlw0lVzpw5FRkZqfPnzzu98qZNm+qpp55SxYoV1bBhQ3333XeSpDlz5ljrpAyOkcIYk6rsTkOGDNGFCxesr2PHjjkdKwAAAACkxaHb/ypWrGi9Tc+VfHx8VLFiRR08eNA6CuCdvVKnTp1K1Xt1Jw8PD+XNm9fmBQAAAAD3g0NJ1ejRo/Xqq69q6dKlOnnypMueX7p+/br27dunoKAghYWFKTAwUKtWrbJOT0xM1Pr161WrVi2H1wEAAAAArmT3j//erkmTJpKkli1b2tyKl3JrXlJSkl3LefXVV9WiRQsVK1ZMp06d0qhRo5SQkKAuXbrIYrGob9++GjNmjMLDwxUeHq4xY8bI29tbHTt2dCRsAAAAAHA5h5KqtWvXumTlx48f1zPPPKO///5bhQoVUo0aNbRlyxbrDwgPGjRIV69eVa9evXTu3DlVr15dK1euVJ48eVyyfgAAAABwlkNJVUREhEtWvmDBgrtOt1gsio6OVnR0tEvWBwAAAACu5lBSleLKlSs6evSoEhMTbcorVarkVFAAAAAAkF04lFSdPn1aXbt21ffff5/mdHufqQIAAACA7M6h0f/69u2rc+fOacuWLfLy8tLy5cs1Z84chYeH65tvvnF1jAAAAACQZTnUU7VmzRp9/fXXeuSRR5QjRw6FhISoUaNGyps3r8aOHavmzZu7Ok4AAAAAyJIc6qm6fPmy/P39JUkFChTQ6dOnJd36UeAdO3a4LjoAAAAAyOIcSqpKly6tAwcOSJIqV66sDz74QCdOnND06dMVFBTk0gABAAAAICtz6Pa/vn376uTJk5Kk4cOHKzIyUp999pnc3d01e/ZsV8YHAAAAAFmaQ0nVs88+a/27SpUqiouL0/79+1WsWDEVLFjQZcEBAAAAQFbn1O9USZIxRl5eXqpataor4gEAAACAbMWhZ6ok6aOPPlKFChXk6ekpT09PVahQQR9++KErYwMAAACALM+hnqphw4Zp0qRJeuWVV1SzZk1J0ubNm9WvXz/FxcVp1KhRLg0SAAAAALIqh5KqadOmaebMmXrmmWesZS1btlSlSpX0yiuvkFQBAAAAeGA4dPtfUlKSqlWrlqr84Ycf1s2bN50OCgAAAACyC4eSqueee07Tpk1LVT5jxgybkQEBAAAA4N/O4dH/PvroI61cuVI1atSQJG3ZskXHjh1T586d1b9/f2u9iRMnOh8lAAAAAGRRDiVVv/32m3UI9cOHD0uSChUqpEKFCum3336z1rNYLC4IEQAAAACyLoeSqrVr17o6DgAAAADIlhz+nSoAAAAAAEkVAAAAADiFpAoAAAAAnEBSBQAAAABOIKkCAAAAACc4nFR98sknql27toKDg3XkyBFJ0uTJk/X111+7LDgAAAAAyOrsSqpWrFihCxcuWN9PmzZN/fv3V7NmzXT+/HklJSVJkvLly6fJkyffl0ABAAAAICuyK6mKj49X7dq1dfz4cUnSlClTNHPmTA0dOlQ5c+a01qtWrZp+/fXX+xMpAAAAAGRBdv34b5cuXZQnTx41adJEv/32m2JjY1WlSpVU9Tw8PHT58mWXBwkAAAAAWZXdz1S1adNG3377rSQpLCxMu3btSlXn+++/V7ly5VwWHAAAAABkdXb1VKUICwuTJA0cOFC9e/fWtWvXZIzRzz//rPnz52vs2LH68MMP70ugAAAAAJAVZSipStG1a1fdvHlTgwYN0pUrV9SxY0cVLlxY7777rjp06ODqGAEAAAAgy3IoqZKk7t27q3v37vr777+VnJwsf39/V8YFAAAAANmCQ79TVb9+fZ0/f16SVLBgQWtClZCQoPr167ssOAAAAADI6hzqqVq3bp0SExNTlV+7dk0bNmxwOihkM9G+mR2B60VfuHcdAAAAQBlMqnbv3m39e+/evYqPj7e+T0pK0vLly1W4cGHXRQcAAAAAWVyGkqrKlSvLYrHIYrGkeZufl5eXpkyZ4rLgAAAAACCry1BSFRsbK2OMihcvrp9//lmFChWyTnN3d5e/v79y5szp8iABAAAAIKvKUFIVEhIiSUpOTr4vwQAAAABAduPQ6H+S9Mknn6h27doKDg7WkSNHJEmTJk3S119/7bLgAAAAACCrcyipmjZtmvr3769mzZrp/PnzSkpKkiTlz59fkydPdmV8AAAAAJClOZRUTZkyRTNnztTQoUNtnqGqVq2afv31V5cFBwAAAABZnUNJVWxsrKpUqZKq3MPDQ5cvX3Y6KAAAAADILhxKqsLCwrRr165U5d9//73KlSvnbEwAAAAAkG1kaPS/FAMHDlTv3r117do1GWP0888/a/78+Ro7dqw+/PBDV8cIAAAAAFmWQ0lV165ddfPmTQ0aNEhXrlxRx44dVbhwYb377rvq0KGDq2MEAAAAgCzLoaRKkrp3767u3bvr77//VnJysvz9/V0ZFwAAAABkCw7/TlWKggULuiyhGjt2rCwWi/r27WstM8YoOjpawcHB8vLyUt26dbVnzx6XrA8AAAAAnOVQUvXXX3+pU6dOCg4Olpubm3LmzGnzckRMTIxmzJihSpUq2ZSPHz9eEydO1NSpUxUTE6PAwEA1atRIFy9edGg9AAAAAOBKDt3+FxUVpaNHj2rYsGEKCgqSxWJxKohLly7p2Wef1cyZMzVq1ChruTFGkydP1tChQ9WmTRtJ0pw5cxQQEKB58+apR48eTq0XAAAAAJzlUFK1ceNGbdiwQZUrV3ZJEL1791bz5s3VsGFDm6QqNjZW8fHxaty4sbXMw8NDERER2rRpU7pJ1fXr13X9+nXr+4SEBJfECQAAAAB3ciipKlq0qIwxLglgwYIF2rFjh2JiYlJNi4+PlyQFBATYlAcEBOjIkSPpLnPs2LEaMWKES+IDAAAAgLtx6JmqyZMn67XXXlNcXJxTKz927Jj+85//6NNPP5Wnp2e69e68vdAYc9dbDocMGaILFy5YX8eOHXMqTgAAAABIj909Vfnz57dJZC5fvqwSJUrI29tbuXLlsql79uxZu5a5fft2nTp1Sg8//LC1LCkpST/++KOmTp2qAwcOSLrVYxUUFGStc+rUqVS9V7fz8PCQh4eHXTEAAAAAgDPsTqomT57s8pU3aNBAv/76q01Z165dVaZMGQ0ePFjFixdXYGCgVq1apSpVqkiSEhMTtX79eo0bN87l8QAAAABARtmdVHXp0sXlK8+TJ48qVKhgU+bj4yM/Pz9red++fTVmzBiFh4crPDxcY8aMkbe3tzp27OjyeAAAAAAgoxwaqGLZsmXKmTOnIiMjbcpXrlyppKQkNW3a1CXBSdKgQYN09epV9erVS+fOnVP16tW1cuVK5cmTx2XrAAAAAABHOTRQxWuvvaakpKRU5cnJyXrttdecCmjdunU2txpaLBZFR0fr5MmTunbtmtavX5+qdwsAAAAAMotDSdXBgwdVrly5VOVlypTRoUOHnA4KAAAAALILh5IqX19f/fHHH6nKDx06JB8fH6eDAgAAAIDswqGkqmXLlurbt68OHz5sLTt06JAGDBigli1buiw4AAAAAMjqHEqqJkyYIB8fH5UpU0ZhYWEKCwtT2bJl5efnp7ffftvVMQIAAABAluXQ6H++vr7atGmTVq1apV9++UVeXl6qVKmSHn/8cVfHBwAAAABZmkNJlXRrVL7GjRurcePGrowHAAAAALIVh5Oqy5cva/369Tp69KgSExNtpvXp08fpwAAAAAAgO3Aoqdq5c6eaNWumK1eu6PLlyypQoID+/vtveXt7y9/fn6QKAAAAwAPDoYEq+vXrpxYtWujs2bPy8vLSli1bdOTIET388MMMVAEAAADggeJQUrVr1y4NGDBAOXPmVM6cOXX9+nUVLVpU48eP13//+19XxwgAAAAAWZZDSVWuXLlksVgkSQEBATp69KikW6MCpvwNAAAAAA8Ch56pqlKlirZt26ZSpUqpXr16euONN/T333/rk08+UcWKFV0dIwAAAABkWQ71VI0ZM0ZBQUGSpDfffFN+fn566aWXdOrUKc2YMcOlAQIAAABAVuZQT1W1atWsfxcqVEjLli1zWUAAAAAAkJ041FMFAAAAALiFpAoAAAAAnEBSBQAAAABOIKkCAAAAACc4lFTNnTtX169fT1WemJiouXPnOh0UAAAAAGQXDiVVXbt21YULF1KVX7x4UV27dnU6KAAAAADILhxKqowxslgsqcqPHz8uX19fp4MCAAAAgOwiQ79TVaVKFVksFlksFjVo0EBubv83e1JSkmJjY9WkSROXBwkAAAAAWVWGkqrWrVtLknbt2qXIyEjlzp3bOs3d3V2hoaF66qmnXBogAAAAAGRlGUqqhg8fLkkKDQ1V+/bt5enpeV+CAgAAAIDswqFnqrp06aJr167pww8/1JAhQ3T27FlJ0o4dO3TixAmXBggAAAAAWVmGeqpS7N69Ww0bNpSvr6/i4uLUvXt3FShQQIsXL9aRI0cYVh0AAADAA8Ohnqp+/fopKipKBw8etLkFsGnTpvrxxx9dFhwAAAAAZHUO9VRt27ZNM2bMSFVeuHBhxcfHOx0UAAAAAGQXDvVUeXp6KiEhIVX5gQMHVKhQIaeDAgAAAIDswqGkqlWrVho5cqRu3LghSbJYLDp69Khee+01hlQHAAAA8EBxKKl6++23dfr0afn7++vq1auKiIhQyZIllSdPHo0ePdrVMQIAAABAluXQM1V58+bVxo0btWbNGu3YsUPJycmqWrWqGjZsKGOMq2MEAAAAgCzLoaRq7NixGjJkiOrXr6/69etby5OSkvTcc89p/vz5LgsQAAAAALIyh27/mzx5cqrR/5KSktShQwft2rXLFXEBAAAAQLbgUE/VsmXL1LBhQ+XLl0/t2rXTjRs31L59e+3fv19r1651dYwAAAAAkGU5lFQ9/PDDWrx4sVq1aiUPDw999NFHOnz4sNauXauAgABXxwgAAAAAWZZDt/9JUt26dfXJJ5+obdu2iouL0/r160moAAAAADxw7O6patOmTZrlhQoVUr58+fTiiy9ayxYtWuR8ZAAAAACQDdidVPn6+qZZHhkZ6bJgAAAAACC7sTupmjVr1v2MAwAAAACyJYeeqYqNjdXBgwdTlR88eFBxcXHOxgQAAAAA2YZDSVVUVJQ2bdqUqnzr1q2KiopyNiYAAAAAyDYcSqp27typ2rVrpyqvUaMGP/4LAAAA4IHiUFJlsVh08eLFVOUXLlxQUlKS00EBAAAAQHbhUFJVp04djR071iaBSkpK0tixY/XYY4/ZvZxp06apUqVKyps3r/LmzauaNWvq+++/t043xig6OlrBwcHy8vJS3bp1tWfPHkdCBgAAAID7wu7R/243fvx4Pf744ypdurTq1KkjSdqwYYMSEhK0Zs0au5dTpEgRvfXWWypZsqQkac6cOWrVqpV27typ8uXLa/z48Zo4caJmz56tUqVKadSoUWrUqJEOHDigPHnyOBI6AAAAALiUQz1V5cqV0+7du9WuXTudOnVKFy9eVOfOnbV//35VqFDB7uW0aNFCzZo1U6lSpVSqVCmNHj1auXPn1pYtW2SM0eTJkzV06FC1adNGFSpU0Jw5c3TlyhXNmzfPkbABAAAAwOUc6qmSpODgYI0ZM8ZlgSQlJemLL77Q5cuXVbNmTcXGxio+Pl6NGze21vHw8FBERIQ2bdqkHj16pLus69ev6/r169b3CQkJLosTAAAAAG5nd1K1e/duVahQQTly5NDu3bvvWrdSpUp2B/Drr7+qZs2aunbtmnLnzq3FixerXLly1iHbAwICbOoHBAToyJEjd13m2LFjNWLECLtjAAAAAABH2Z1UVa5cWfHx8fL391flypVlsVhkjElVz2KxZGgEwNKlS2vXrl06f/68vvrqK3Xp0kXr16+3Wd7tjDGpyu40ZMgQ9e/f3/o+ISFBRYsWtTsmAAAAALCX3UlVbGysChUqZP3bVdzd3a0DVVSrVk0xMTF69913NXjwYElSfHy8goKCrPVPnTqVqvfqTh4eHvLw8HBZjAAAAACQHrsHqggJCbH2EB05ckSFCxdWSEiIzatw4cL3vDXvXowxun79usLCwhQYGKhVq1ZZpyUmJmr9+vWqVauWU+sAAAAAAFdxaKCKevXq6eTJk/L397cpv3DhgurVq2f37X///e9/1bRpUxUtWlQXL17UggULtG7dOi1fvlwWi0V9+/bVmDFjFB4ervDwcI0ZM0be3t7q2LGjI2EDAAAAgMs5lFSl91zTmTNn5OPjY/dy/vrrL3Xq1EknT56Ur6+vKlWqpOXLl6tRo0aSpEGDBunq1avq1auXzp07p+rVq2vlypX8RhUAAACALCNDSVWbNm0k3Ro8Iioqyua5paSkJO3evTtDt+Z99NFHd51usVgUHR2t6OjojIQJAAAAAP+YDCVVvr6+km71VOXJk0deXl7Wae7u7qpRo4a6d+/u2ggBAAAAIAvLUFI1a9YsSVJoaKheffXVDN3qBwAAAAD/Rg49UzV8+HBXxwEAAAAA2ZLdQ6oDAAAAAFIjqQIAAAAAJ5BUAQAAAIATnE6qrl275oo4AAAAACBbciipSk5O1ptvvqnChQsrd+7c+uOPPyRJw4YNu+dvTwEAAADAv4lDSdWoUaM0e/ZsjR8/Xu7u7tbyihUr6sMPP3RZcAAAAACQ1TmUVM2dO1czZszQs88+q5w5c1rLK1WqpP3797ssOAAAAADI6hxKqk6cOKGSJUumKk9OTtaNGzecDgoAAAAAsguHkqry5ctrw4YNqcq/+OILValSxemgAAAAACC7cHNkpuHDh6tTp046ceKEkpOTtWjRIh04cEBz587V0qVLXR0jAAAAAGRZDvVUtWjRQgsXLtSyZctksVj0xhtvaN++ffr222/VqFEjV8cIAAAAAFmWQz1VkhQZGanIyEhXxgIAAAAA2Y7TP/4LAAAAAA8yu3uq8ufPL4vFYlfds2fPOhwQAAAAAGQndidVkydPtv595swZjRo1SpGRkapZs6YkafPmzVqxYoWGDRvm8iABAAAAIKuyO6nq0qWL9e+nnnpKI0eO1Msvv2wt69Onj6ZOnarVq1erX79+ro0SAAAAALIoh56pWrFihZo0aZKqPDIyUqtXr3Y6KAAAAADILhxKqvz8/LR48eJU5UuWLJGfn5/TQQEAAABAduHQkOojRozQ888/r3Xr1lmfqdqyZYuWL1+uDz/80KUBAgAAAEBW5lBSFRUVpbJly+q9997TokWLZIxRuXLl9NNPP6l69equjhEAAAAAsiyHf/y3evXq+uyzz1wZCwAAAABkO/z4LwAAAAA4gaQKAAAAAJxAUgUAAAAATiCpAgAAAAAnOJRU/fXXX+lO2717t8PBAAAAAEB241BSVbFiRX3zzTepyt9++22GVAcAAADwQHEoqRo8eLDat2+vnj176urVqzpx4oTq16+vCRMmaOHCha6OEQAAAACyLIeSqgEDBmjLli366aefVKlSJVWqVEleXl7avXu3WrZs6eoYAQAAACDLcnigiuLFi6t8+fKKi4tTQkKC2rVrp4CAAFfGBgAAAABZnkNJVUoP1aFDh7R7925NmzZNr7zyitq1a6dz5865OkYAAAAAyLIcSqrq16+v9u3ba/PmzSpbtqxeeOEF7dy5U8ePH1fFihVdHSMAAAAAZFlujsy0cuVKRURE2JSVKFFCGzdu1OjRo10SGAAAAABkBw71VN2ZUFkXliOHhg0b5lRAAAAAAJCdONRTNXLkyLtOf+ONNxwKBgAAAACyG4eSqsWLF9u8v3HjhmJjY+Xm5qYSJUqQVAEAAAB4YDiUVO3cuTNVWUJCgqKiovTkk086HRQAAAAAZBcO/07VnfLmzauRI0fyTBUAAACAB4rLkipJOn/+vC5cuODKRQIAAABAlubQ7X/vvfeezXtjjE6ePKlPPvlETZo0cUlgAAAAAJAdOJRUTZo0yeZ9jhw5VKhQIXXp0kVDhgxxSWAAAAAAkB04lFTFxsa6ZOVjx47VokWLtH//fnl5ealWrVoaN26cSpcuba1jjNGIESM0Y8YMnTt3TtWrV9f//vc/lS9f3iUxAAAAAIAzXPpMVUatX79evXv31pYtW7Rq1SrdvHlTjRs31uXLl611xo8fr4kTJ2rq1KmKiYlRYGCgGjVqpIsXL2Zi5AAAAABwi0M9VZIUExOjL774QkePHlViYqLNtEWLFtm1jOXLl9u8nzVrlvz9/bV9+3Y9/vjjMsZo8uTJGjp0qNq0aSNJmjNnjgICAjRv3jz16NHD0fABAAAAwCUc6qlasGCBateurb1792rx4sW6ceOG9u7dqzVr1sjX19fhYFJGDixQoICkW7cZxsfHq3HjxtY6Hh4eioiI0KZNm9JdzvXr15WQkGDzAgAAAID7waGkasyYMZo0aZKWLl0qd3d3vfvuu9q3b5/atWunYsWKORSIMUb9+/fXY489pgoVKkiS4uPjJUkBAQE2dQMCAqzT0jJ27Fj5+vpaX0WLFnUoJgAAAAC4F4eSqsOHD6t58+aSbvUcXb58WRaLRf369dOMGTMcCuTll1/W7t27NX/+/FTTLBaLzXtjTKqy2w0ZMkQXLlywvo4dO+ZQTAAAAABwLw4lVQUKFLAOFFG4cGH99ttvkm79+O+VK1cyvLxXXnlF33zzjdauXasiRYpYywMDAyUpVa/UqVOnUvVe3c7Dw0N58+a1eQEAAADA/ZChpKpbt266ePGi6tSpo1WrVkmS2rVrp//85z/q3r27nnnmGTVo0MDu5Rlj9PLLL2vRokVas2aNwsLCbKaHhYUpMDDQui5JSkxM1Pr161WrVq2MhA4AAAAA90WGRv+bM2eO3nrrLU2dOlXXrl2TdOtWu1y5cmnjxo1q06aNhg0bZvfyevfurXnz5unrr79Wnjx5rD1Svr6+8vLyksViUd++fTVmzBiFh4crPDxcY8aMkbe3tzp27JiR0AEAAADgvshQUmWMkfR/o/NJUo4cOTRo0CANGjQowyufNm2aJKlu3bo25bNmzVJUVJQkadCgQbp69ap69epl/fHflStXKk+ePBleHwAAAAC4WoZ/p+puA0RkVEqSdq/1RUdHKzo62mXrBQAAAABXyXBSVapUqXsmVmfPnnU4IAAAAADITjKcVI0YMcKpH/gFAAAAgH+TDCdVHTp0kL+///2IBQAAAACynQwNqe7K56kAAAAA4N8gQ0mVPQNLAAAAAMCDJEO3/yUnJ9+vOAAAAAAgW8pQTxUAAAAAwBZJFQAAAAA4gaQKAAAAAJxAUgUAAAAATiCpAgAAAAAnkFQBAAAAgBNIqgAAAADACSRVAAAAAOAEkioAAAAAcAJJFQAAAAA4gaQKAAAAAJxAUgUAAAAATiCpAgAAAAAnkFQBAAAAgBNIqgAAAADACSRVAAAAAOAEkioAAAAAcAJJFQAAAAA4gaQKAAAAAJxAUgUAAAAATiCpAgAAAAAnkFQBAAAAgBNIqgAAAADACSRVAAAAAOAEkioAAAAAcAJJFQAAAAA4gaQKAAAAAJxAUgUAAAAATiCpAgAAAAAnkFQBAAAAgBNIqgAAAADACSRVAAAAAOAEkioAAAAAcAJJFQAAAAA4gaQKAAAAAJxAUgUAAAAATiCpAgAAAAAnkFQBAAAAgBMyPan68ccf1aJFCwUHB8tisWjJkiU2040xio6OVnBwsLy8vFS3bl3t2bMnc4IFAAAAgDtkelJ1+fJlPfTQQ5o6dWqa08ePH6+JEydq6tSpiomJUWBgoBo1aqSLFy/+w5ECAAAAQGpumR1A06ZN1bRp0zSnGWM0efJkDR06VG3atJEkzZkzRwEBAZo3b5569OjxT4YKAAAAAKlkek/V3cTGxio+Pl6NGze2lnl4eCgiIkKbNm1Kd77r168rISHB5gUAAAAA90OWTqri4+MlSQEBATblAQEB1mlpGTt2rHx9fa2vokWL3tc4AQAAADy4snRSlcJisdi8N8akKrvdkCFDdOHCBevr2LFj9ztEAAAAAA+oTH+m6m4CAwMl3eqxCgoKspafOnUqVe/V7Tw8POTh4XHf4wMAAACALN1TFRYWpsDAQK1atcpalpiYqPXr16tWrVqZGBkAAAAA3JLpPVWXLl3SoUOHrO9jY2O1a9cuFShQQMWKFVPfvn01ZswYhYeHKzw8XGPGjJG3t7c6duyYiVEDAAAAwC2ZnlRt27ZN9erVs77v37+/JKlLly6aPXu2Bg0apKtXr6pXr146d+6cqlevrpUrVypPnjyZFTIAAAAAWGV6UlW3bl0ZY9KdbrFYFB0drejo6H8uKAAAAACwU5Z+pgoAAAAAsjqSKgAAAABwAkkVAAAAADiBpAoAAAAAnEBSBQAAAABOIKkCAAAAACeQVAEAAACAE0iqAAAAAMAJJFUAAAAA4ASSKgAAAABwAkkVAAAAADiBpAoAAAAAnEBSBQAAAABOIKkCAAAAACeQVAEAAACAE0iqAAAAAMAJJFUAAAAA4ASSKgAAAABwAkkVAAAAADiBpAoAAAAAnEBSBQAAAABOIKkCAAAAACeQVAEAAACAE0iqAAAAAMAJJFUAAAAA4ASSKgAAAABwAkkVAAAAADiBpAoAAAAAnEBSBQAAAABOIKkCAAAAACeQVAEAAACAE0iqAAAAAMAJJFUAAAAA4ASSKgAAAABwAkkVAAAAADiBpAoAAAAAnEBSBQAAAABOIKkCAAAAACeQVAEAAACAE0iqAAAAAMAJJFUAAAAA4AS3zA4AAAAgW4v2zewIXCv6QmZHAGQ79FQBAAAAgBNIqgAAAADACdkmqXr//fcVFhYmT09PPfzww9qwYUNmhwQAAAAA2SOpWrhwofr27auhQ4dq586dqlOnjpo2baqjR49mdmgAAAAAHnDZIqmaOHGinn/+eb3wwgsqW7asJk+erKJFi2ratGmZHRoAAACAB1yWH/0vMTFR27dv12uvvWZT3rhxY23atCnNea5fv67r169b31+4cGsUm4SEhPsXaAYkX7+S2SG4VILFZHYIrpdF2goA/Nv8274DpX/h9yDfgfiXS8kJjHHdsZvlk6q///5bSUlJCggIsCkPCAhQfHx8mvOMHTtWI0aMSFVetGjR+xLjg+5fNpDsLW/9K7cKAHAf/Ou+MfgOxAPi4sWL8vV1TXvP8klVCovFYvPeGJOqLMWQIUPUv39/6/vk5GSdPXtWfn5+6c4DxyQkJKho0aI6duyY8ubNm9nh4F+CdoX7gXaF+4F2hfuBdnV/GWN08eJFBQcHu2yZWT6pKliwoHLmzJmqV+rUqVOpeq9SeHh4yMPDw6YsX7589ytESMqbNy8HPVyOdoX7gXaF+4F2hfuBdnX/uKqHKkWWH6jC3d1dDz/8sFatWmVTvmrVKtWqVSuTogIAAACAW7J8T5Uk9e/fX506dVK1atVUs2ZNzZgxQ0ePHlXPnj0zOzQAAAAAD7hskVS1b99eZ86c0ciRI3Xy5ElVqFBBy5YtU0hISGaH9sDz8PDQ8OHDU91uCTiDdoX7gXaF+4F2hfuBdpX9WIwrxxIEAAAAgAdMln+mCgAAAACyMpIqAAAAAHACSRUAAAAAOIGkCgAAAACcQFIFu/z4449q0aKFgoODZbFYtGTJEpvpxhhFR0crODhYXl5eqlu3rvbs2ZM5wSLbuFe7WrRokSIjI1WwYEFZLBbt2rUrU+JE9nK3dnXjxg0NHjxYFStWlI+Pj4KDg9W5c2f9+eefmRcwsoV7na+io6NVpkwZ+fj4KH/+/GrYsKG2bt2aOcEi27hXu7pdjx49ZLFYNHny5H8sPtiPpAp2uXz5sh566CFNnTo1zenjx4/XxIkTNXXqVMXExCgwMFCNGjXSxYsX/+FIkZ3cq11dvnxZtWvX1ltvvfUPR4bs7G7t6sqVK9qxY4eGDRumHTt2aNGiRfr999/VsmXLTIgU2cm9zlelSpXS1KlT9euvv2rjxo0KDQ1V48aNdfr06X84UmQn92pXKZYsWaKtW7cqODj4H4oMGcWQ6sgwi8WixYsXq3Xr1pJu9VIFBwerb9++Gjx4sCTp+vXrCggI0Lhx49SjR49MjBbZxZ3t6nZxcXEKCwvTzp07Vbly5X88NmRfd2tXKWJiYvToo4/qyJEjKlas2D8XHLIte9pVQkKCfH19tXr1ajVo0OCfCw7ZVnrt6sSJE6pevbpWrFih5s2bq2/fvurbt2+mxIj00VMFp8XGxio+Pl6NGze2lnl4eCgiIkKbNm3KxMgA4N4uXLggi8WifPnyZXYo+JdITEzUjBkz5Ovrq4ceeiizw0E2lpycrE6dOmngwIEqX758ZoeDu3DL7ACQ/cXHx0uSAgICbMoDAgJ05MiRzAgJAOxy7do1vfbaa+rYsaPy5s2b2eEgm1u6dKk6dOigK1euKCgoSKtWrVLBggUzOyxkY+PGjZObm5v69OmT2aHgHuipgstYLBab98aYVGUAkFXcuHFDHTp0UHJyst5///3MDgf/AvXq1dOuXbu0adMmNWnSRO3atdOpU6cyOyxkU9u3b9e7776r2bNncz2VDZBUwWmBgYGS/q/HKsWpU6dS9V4BQFZw48YNtWvXTrGxsVq1ahW9VHAJHx8flSxZUjVq1NBHH30kNzc3ffTRR5kdFrKpDRs26NSpUypWrJjc3Nzk5uamI0eOaMCAAQoNDc3s8HAHkio4LSwsTIGBgVq1apW1LDExUevXr1etWrUyMTIASC0loTp48KBWr14tPz+/zA4J/1LGGF2/fj2zw0A21alTJ+3evVu7du2yvoKDgzVw4ECtWLEis8PDHXimCna5dOmSDh06ZH0fGxurXbt2qUCBAipWrJj69u2rMWPGKDw8XOHh4RozZoy8vb3VsWPHTIwaWd292tXZs2d19OhR628IHThwQNKt3tGUHlLgTndrV8HBwWrbtq127NihpUuXKikpydrLXqBAAbm7u2dW2Mji7tau/Pz8NHr0aLVs2VJBQUE6c+aM3n//fR0/flxPP/10JkaNrO5e34N3/tMnV65cCgwMVOnSpf/pUHEvBrDD2rVrjaRUry5duhhjjElOTjbDhw83gYGBxsPDwzz++OPm119/zdygkeXdq13NmjUrzenDhw/P1LiRtd2tXcXGxqY5TZJZu3ZtZoeOLOxu7erq1avmySefNMHBwcbd3d0EBQWZli1bmp9//jmzw0YWd6/vwTuFhISYSZMm/aMxwj78ThUAAAAAOIFnqgAAAADACSRVAAAAAOAEkioAAAAAcAJJFQAAAAA4gaQKAAAAAJxAUgUAAAAATiCpAgAAAAAnkFQBAJwWFxenUaNG6dKlS5kdCgAA/ziSKgCAUxITE9WuXTv5+fkpd+7c/8g6161bJ4vFovPnz/8j6/u3qlu3rvr27ZvZYQBAtkdSBQDZUFRUlCwWi9566y2b8iVLlshisfyjsQwYMECNGjXSSy+99I+uF85btGiR3nzzzcwOAwCyPbfMDgAA4BhPT0+NGzdOPXr0UP78+TMtjilTpthVLzExUe7u7vc5GmREgQIFMjsEAPhXoKcKALKphg0bKjAwUGPHjk23TnR0tCpXrmxTNnnyZIWGhlrfR0VFqXXr1hozZowCAgKUL18+jRgxQjdv3tTAgQNVoEABFSlSRB9//LHNck6cOKH27dsrf/788vPzU6tWrRQXF5dquWPHjlVwcLBKlSolSfr1119Vv359eXl5yc/PTy+++OI9n8VatmyZSpUqJS8vL9WrV89mPSk2bdqkxx9/XF5eXipatKj69Omjy5cv33W533zzjapVqyZPT08VLFhQbdq0sU47d+6cOnfurPz588vb21tNmzbVwYMHrdNnz56tfPnyaenSpSpdurS8vb3Vtm1bXb58WXPmzFFoaKjy58+vV155RUlJSdb5QkND9eabb6pjx47KnTu3goODUyWmEydOVMWKFeXj46OiRYuqV69eqfbRzJkzVbRoUXl7e+vJJ5/UxIkTlS9fPuv0lM/+k08+UWhoqHx9fdWhQwddvHjRWufO2/8SExM1aNAgFS5cWD4+PqpevbrWrVt3130IACCpAoBsK2fOnBozZoymTJmi48ePO7WsNWvW6M8//9SPP/6oiRMnKjo6Wk888YTy58+vrVu3qmfPnurZs6eOHTsmSbpy5Yrq1aun3Llz68cff9TGjRuVO3duNWnSRImJidbl/vDDD9q3b59WrVqlpUuX6sqVK2rSpIny58+vmJgYffHFF1q9erVefvnldGM7duyY2rRpo2bNmmnXrl164YUX9Nprr9nU+fXXXxUZGak2bdpo9+7dWrhwoTZu3HjX5X733Xdq06aNmjdvrp07d+qHH35QtWrVrNOjoqK0bds2ffPNN9q8ebOMMWrWrJlu3LhhrXPlyhW99957WrBggZYvX65169apTZs2WrZsmZYtW6ZPPvlEM2bM0Jdffmmz7gkTJqhSpUrasWOHhgwZon79+mnVqlXW6Tly5NB7772n3377TXPmzNGaNWs0aNAg6/SffvpJPXv21H/+8x/t2rVLjRo10ujRo1Nt4+HDh7VkyRItXbpUS5cu1fr161PdMnq7rl276qefftKCBQu0e/duPf3002rSpIlNMgkASIMBAGQ7Xbp0Ma1atTLGGFOjRg3TrVs3Y4wxixcvNref2ocPH24eeughm3knTZpkQkJCbJYVEhJikpKSrGWlS5c2derUsb6/efOm8fHxMfPnzzfGGPPRRx+Z0qVLm+TkZGud69evGy8vL7NixQrrcgMCAsz169etdWbMmGHy589vLl26ZC377rvvTI4cOUx8fHya2zpkyBBTtmxZm3UNHjzYSDLnzp0zxhjTqVMn8+KLL9rMt2HDBpMjRw5z9erVNJdbs2ZN8+yzz6Y57ffffzeSzE8//WQt+/vvv42Xl5f5/PPPjTHGzJo1y0gyhw4dstbp0aOH8fb2NhcvXrSWRUZGmh49eljfh4SEmCZNmtisr3379qZp06ZpxmKMMZ9//rnx8/Ozqd+8eXObOs8++6zx9f1/7d1fSJNrHAfwr67A5tYBzYZIQ7LUVbotKVtiSUMGEQ2iu9X6KwmxVllEQexiEG2kF5WyrnSERUkRBltdhCyV3HJh9GfNaaOLIAy7KKIu1vuei0M7vW7r1HnjHLTv58rned/n9/x8drH9eJ89+yPddrlcolKpFN+/f5/uO378uFhfX59ub9y4UXQ6naIoiuLExISYl5cnvn79WhLXbDaLJ0+ezJkbERGJIp9UERHNch6PB36/H8+fP//XMVauXIn8/L/fEjQaDWpqatJthUKB4uJiTE1NAQCi0SgmJiagVquhUqmgUqlQVFSEz58/Y3JyMj2upqZG8j2qWCwGvV6PwsLCdF9DQwMEQUA8Hs+aWywWw7p16yQHcJhMJsk90WgUPT096VxUKhUsFgsEQUAymcwad2xsDGazOeec8+bNQ319fbqvuLgYVVVViMVi6T6lUomKigrJupWXl0tOQdRoNOl1y5W/yWSSxB0YGEBzczPKysqgVqtht9sxPT2d3s4Yj8exdu1aSYyZbeCvrYZqtTrdLi0tzcjlq0ePHkEURVRWVkrWMRQKSV5TIiLKxIMqiIhmuQ0bNsBiseDUqVPYvXu35Fp+fj5EUZT0fbt97av58+dL2nl5eVn7BEEAAAiCgLq6OvT29mbEKikpSf/9bfEEAKIo5jydMFf/zPyzEQQBBw4cwKFDhzKuabXarGMWLFiQM16uOWfm/7Pr9j1f47569QqbN29Ga2sr3G43ioqKMDQ0hH379qVfu2zrmC3nn8lFEAQoFApEo1EoFArJtf/qqHwiotmKRRUR0Rxw9uxZGAyG9GEQX5WUlODNmzeSD+FjY2Oy51u9ejWuXbuGxYsXY+HChT88bsWKFfD7/fj48WO64BoeHkZ+fn5G7t+OuXXrlqRvZGQkI59nz55h2bJlP5xLbW0t7t27hz179mSdM5VKIRwOY/369QCA6elpjI+PQ6fT/fAcuczMf2RkBNXV1QCA0dFRpFIptLe3p58eXr9+XXJ/dXU1IpGIpG90dFRWTkajEV++fMHU1BQaGxtlxSIi+t1w+x8R0RxQU1MDm82WcYpcU1MT3r59C6/Xi8nJSXR2diIYDMqez2azYdGiRbBarRgcHEQymUQoFILT6fzuoRk2mw0FBQXYtWsXnj59ioGBATgcDuzcuRMajSbrmNbWVkxOTuLo0aOIx+O4cuUKenp6JPecOHECDx48wMGDBzE2NoZEIoH+/n44HI6cubhcLly9ehUulwuxWAxPnjyB1+sFACxfvhxWqxUtLS0YGhrC48ePsWPHDpSVlcFqtf78gs0wPDwMr9eL8fFxdHZ2oq+vD06nEwBQUVGBVCqFCxcu4OXLl7h8+TJ8Pp9kvMPhQCAQQEdHBxKJBC5duoRgMCjrN8oqKyths9lgt9tx8+ZNJJNJPHz4EB6PB4FAQNb/S0Q017GoIiKaI9xud8YWMJ1Oh66uLnR2dkKv1yMSieDYsWOy51Iqlbh//z60Wi22bdsGnU6HvXv34tOnT999cqVUKnH37l28e/cOa9aswfbt22E2m3Hx4sWcY7RaLW7cuIHbt29Dr9fD5/PhzJkzkntqa2sRCoWQSCTQ2NgIo9GI06dPo7S0NGfcpqYm9PX1ob+/HwaDAZs2bUI4HE5f7+7uRl1dHbZs2QKTyQRRFBEIBDK21P0bbW1tiEajMBqNcLvdaG9vh8ViAQAYDAZ0dHTA4/Fg1apV6O3tzTg2v6GhAT6fDx0dHdDr9bhz5w6OHDmCgoICWXl1d3fDbrejra0NVVVV2Lp1K8LhMJYsWSIrLhHRXJcn/shmdSIiIvolysvLcfjwYcnvQ/0KLS0tePHiBQYHB39pXCIi+mf8ThUREdEsdO7cOTQ3N6OwsBDBYBB+vx9dXV3/d1pERL8lFlVERESzUCQSgdfrxYcPH7B06VKcP38e+/fv/7/TIiL6LXH7HxERERERkQw8qIKIiIiIiEgGFlVEREREREQysKgiIiIiIiKSgUUVERERERGRDCyqiIiIiIiIZGBRRUREREREJAOLKiIiIiIiIhlYVBEREREREcnAooqIiIiIiEiGPwHgGeQ3ZZh2zgAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "multiple_barplot(purchase_spectacle_train, x=\"number_company\", y=\"Taux_ticket_internet\", var_labels=\"y_has_purchased\",\n",
+    "                dico_labels = {0 : \"clients n'ayant pas acheté\", 1 : \"clients ayant acheté sur la période\"},\n",
+    "                xlabel = \"Numéro de compagnie\", ylabel = \"Taux de ticket acheté par internet (%)\", \n",
+    "                title = \"Taux de ticket achété en ligne  selon y_has_purchased par  compagnies de spectacle (train set)\")"
+   ]
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": 107,
+   "id": "9ba02de7-3087-4b0c-884a-dc4a6ca92c3b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#stat sur la variable temps ecoulé entre le premier et le dernier achat"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 108,
    "id": "59a95248-0261-4970-9e91-e43d50cf4d69",
    "metadata": {},
    "outputs": [
@@ -7343,7 +7432,7 @@
        "Text(0.5, 1.0, 'Boite à moustache du temps ecoulés entre le premier et le dernier achat selon les compagnies de spectacles')"
       ]
      },
-     "execution_count": 66,
+     "execution_count": 108,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -7359,7 +7448,7 @@
     }
    ],
    "source": [
-    "#repartition Chiffre d'affaire selon le numero de la compagnie\n",
+    "#repartition des client selon le temps ecoulés entre le premier et le denier achat par  compagnie\n",
     "\n",
     "sns.boxplot(data=products_purchased_reduced_spectacle, y=\"time_between_purchase\",x=\"number_compagny\",showfliers=False,showmeans=True)\n",
     "plt.title(\"Boite à moustache du temps ecoulés entre le premier et le dernier achat selon les compagnies de spectacles\")"
@@ -7367,7 +7456,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 109,
    "id": "e2c51e28-6197-48f0-ab6d-9fc7b3b0de74",
    "metadata": {},
    "outputs": [
@@ -7424,6 +7513,152 @@
     "    print(\"Il n'y a pas de différences significatives entre les entreprises .\")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 111,
+   "id": "75a003ab-f42a-4b2d-a0a8-284e673e71f7",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>number_company</th>\n",
+       "      <th>y_has_purchased</th>\n",
+       "      <th>time_between_purchase</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>10</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>45.791114</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>10</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>193.080793</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>11</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>27.640469</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>11</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>129.853892</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>12</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>16.418446</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>12</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>58.548598</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>13</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>10.012525</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>13</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>93.545373</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>14</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>3.879196</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>14</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>10.745213</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   number_company  y_has_purchased  time_between_purchase\n",
+       "0              10              0.0              45.791114\n",
+       "1              10              1.0             193.080793\n",
+       "2              11              0.0              27.640469\n",
+       "3              11              1.0             129.853892\n",
+       "4              12              0.0              16.418446\n",
+       "5              12              1.0              58.548598\n",
+       "6              13              0.0              10.012525\n",
+       "7              13              1.0              93.545373\n",
+       "8              14              0.0               3.879196\n",
+       "9              14              1.0              10.745213"
+      ]
+     },
+     "execution_count": 111,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#repartition des client selon le temps ecoulés entre le premier et le denier achat par  compagnie\n",
+    "purchase_train_time= train_set_spectacle.groupby([\"number_company\", \"y_has_purchased\"])[\"time_between_purchase\"].mean().reset_index()\n",
+    "purchase_train_time"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 113,
+   "id": "f27921a9-1253-4c02-9bff-8cd3c4a9a5d9",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "multiple_barplot(purchase_train_time, x=\"number_company\", y=\"time_between_purchase\", var_labels=\"y_has_purchased\",\n",
+    "                dico_labels = {0 : \"clients n'ayant pas acheté\", 1 : \"clients ayant acheté sur la période\"},\n",
+    "                xlabel = \"Numéro de compagnie\", ylabel = \"Taux de ticket acheté par internet (%)\", \n",
+    "                title = \"temps moyen entre le premier et le dernier achat selon y_has_purchased par  compagnies de spectacle (train set)\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 33,