IP Profiling- Anomaly Detection.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import datetime as dt\n",
    "import random\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "# Set some parameters to get good visuals - style to ggplot and size to 15,10\n",
    "plt.style.use('ggplot')\n",
    "import matplotlib.style as style\n",
    "style.use('fivethirtyeight')\n",
    "plt.rcParams['figure.figsize'] = (15, 8)\n",
    "\n",
    "import seaborn as sns\n",
    "from sklearn.manifold import TSNE\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "\n",
    "from sklearn import preprocessing\n",
    "from sklearn.decomposition import PCA\n",
    "\n",
    "from sklearn.cluster import KMeans\n",
    "from sklearn.ensemble import IsolationForest\n",
    "from sklearn.svm import OneClassSVM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv('final_ip_mapped_data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>@timestamp</th>\n",
       "      <th>_id</th>\n",
       "      <th>ip_address</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>July 8th 2019, 14:43:03.000</td>\n",
       "      <td>XswJ0msBoTGddM7vxMDB</td>\n",
       "      <td>10.1.1.285</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>July 8th 2019, 14:43:01.000</td>\n",
       "      <td>dKQJ0msB7mP0GwVzvJjz</td>\n",
       "      <td>10.1.2.389</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>July 8th 2019, 14:42:59.000</td>\n",
       "      <td>CcwJ0msBoTGddM7vtb8y</td>\n",
       "      <td>10.1.1.415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>July 8th 2019, 14:42:57.000</td>\n",
       "      <td>bKQJ0msB7mP0GwVzrZdT</td>\n",
       "      <td>10.1.1.79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>July 8th 2019, 14:42:55.000</td>\n",
       "      <td>L6QJ0msB7mP0GwVzpZeI</td>\n",
       "      <td>10.1.1.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>July 8th 2019, 14:42:53.000</td>\n",
       "      <td>O8wJ0msBoTGddM7vnb2w</td>\n",
       "      <td>10.1.2.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>July 8th 2019, 14:42:51.000</td>\n",
       "      <td>Z8wJ0msBoTGddM7vlbze</td>\n",
       "      <td>10.1.2.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>July 8th 2019, 14:42:49.000</td>\n",
       "      <td>J6QJ0msB7mP0GwVzjpUY</td>\n",
       "      <td>10.1.2.247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>July 8th 2019, 14:42:46.000</td>\n",
       "      <td>#NAME?</td>\n",
       "      <td>10.1.1.199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>July 8th 2019, 14:42:46.000</td>\n",
       "      <td>#NAME?</td>\n",
       "      <td>10.1.1.387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>July 8th 2019, 14:42:30.000</td>\n",
       "      <td>36QJ0msB7mP0GwVzQ4_c</td>\n",
       "      <td>10.1.2.128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>July 8th 2019, 14:12:45.000</td>\n",
       "      <td>W8ru0WsBoTGddM7vB6Mx</td>\n",
       "      <td>10.1.1.243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>July 8th 2019, 14:12:40.000</td>\n",
       "      <td>2qLt0WsB7mP0GwVz84Cr</td>\n",
       "      <td>10.1.2.106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>July 8th 2019, 14:12:36.000</td>\n",
       "      <td>Ycrt0WsBoTGddM7v5KAI</td>\n",
       "      <td>10.1.2.500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>July 8th 2019, 14:12:32.000</td>\n",
       "      <td>BKLt0WsB7mP0GwVz1H9p</td>\n",
       "      <td>10.1.2.100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>July 8th 2019, 14:12:28.000</td>\n",
       "      <td>t8rt0WsBoTGddM7vxJ3J</td>\n",
       "      <td>10.1.2.314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>July 8th 2019, 14:12:23.000</td>\n",
       "      <td>rcrt0WsBoTGddM7vsZw_</td>\n",
       "      <td>10.1.1.383</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>July 8th 2019, 14:12:20.000</td>\n",
       "      <td>uqLt0WsB7mP0GwVzpXuJ</td>\n",
       "      <td>10.1.2.279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>July 8th 2019, 14:12:17.000</td>\n",
       "      <td>9qLt0WsB7mP0GwVzmXrT</td>\n",
       "      <td>10.1.2.264</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>July 8th 2019, 14:12:15.000</td>\n",
       "      <td>b8rt0WsBoTGddM7vkpoB</td>\n",
       "      <td>10.1.2.468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>July 8th 2019, 14:12:12.000</td>\n",
       "      <td>Vsrt0WsBoTGddM7vhplI</td>\n",
       "      <td>10.1.2.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>July 8th 2019, 14:12:09.000</td>\n",
       "      <td>UaLt0WsB7mP0GwVzeniX</td>\n",
       "      <td>10.1.2.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>July 8th 2019, 14:12:06.000</td>\n",
       "      <td>pcrt0WsBoTGddM7vbpXY</td>\n",
       "      <td>10.1.1.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>July 8th 2019, 14:12:03.000</td>\n",
       "      <td>eKLt0WsB7mP0GwVzY3Ij</td>\n",
       "      <td>10.1.2.412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>July 8th 2019, 14:12:00.000</td>\n",
       "      <td>kMrt0WsBoTGddM7vV5Np</td>\n",
       "      <td>10.1.2.313</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>July 8th 2019, 14:12:00.000</td>\n",
       "      <td>pqLt0WsB7mP0GwVzV3Fs</td>\n",
       "      <td>10.1.2.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>July 8th 2019, 14:10:59.000</td>\n",
       "      <td>7crs0WsBoTGddM7vaYAk</td>\n",
       "      <td>10.1.2.89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>July 8th 2019, 14:09:12.000</td>\n",
       "      <td>w6Lq0WsB7mP0GwVzx0Ir</td>\n",
       "      <td>10.1.1.170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>July 8th 2019, 14:08:28.000</td>\n",
       "      <td>hcrq0WsBoTGddM7vG05I</td>\n",
       "      <td>10.1.1.446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>July 8th 2019, 14:08:26.000</td>\n",
       "      <td>WaLq0WsB7mP0GwVzExd7</td>\n",
       "      <td>10.1.1.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>721517</th>\n",
       "      <td>June 9th 2019, 00:02:29.000</td>\n",
       "      <td>cBuLOWsB7mP0GwVzKX30</td>\n",
       "      <td>10.1.2.465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>721518</th>\n",
       "      <td>June 9th 2019, 00:02:25.000</td>\n",
       "      <td>sUWLOWsBoTGddM7vGlVT</td>\n",
       "      <td>10.1.1.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>721519</th>\n",
       "      <td>June 9th 2019, 00:02:19.000</td>\n",
       "      <td>6kWLOWsBoTGddM7vAlTj</td>\n",
       "      <td>10.1.1.499</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>721520</th>\n",
       "      <td>June 9th 2019, 00:02:15.000</td>\n",
       "      <td>MUWKOWsBoTGddM7v81RC</td>\n",
       "      <td>10.1.2.179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>721521</th>\n",
       "      <td>June 9th 2019, 00:02:09.000</td>\n",
       "      <td>CBuKOWsB7mP0GwVz23vY</td>\n",
       "      <td>10.1.2.500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>721522</th>\n",
       "      <td>June 9th 2019, 00:02:05.000</td>\n",
       "      <td>mUWKOWsBoTGddM7vzFIx</td>\n",
       "      <td>10.1.2.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>721523</th>\n",
       "      <td>June 9th 2019, 00:01:59.000</td>\n",
       "      <td>kUWKOWsBoTGddM7vtFHB</td>\n",
       "      <td>10.1.2.225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>721524</th>\n",
       "      <td>June 9th 2019, 00:01:55.000</td>\n",
       "      <td>_0WKOWsBoTGddM7vpVAg</td>\n",
       "      <td>10.1.1.295</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>721525</th>\n",
       "      <td>June 9th 2019, 00:01:49.000</td>\n",
       "      <td>UEWKOWsBoTGddM7vjVCz</td>\n",
       "      <td>10.1.2.428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>721526</th>\n",
       "      <td>June 9th 2019, 00:01:45.000</td>\n",
       "      <td>oUWKOWsBoTGddM7vfk8R</td>\n",
       "      <td>10.1.2.446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>721527</th>\n",
       "      <td>June 9th 2019, 00:01:39.000</td>\n",
       "      <td>m0WKOWsBoTGddM7vZk6h</td>\n",
       "      <td>10.1.1.459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>721528</th>\n",
       "      <td>June 9th 2019, 00:01:35.000</td>\n",
       "      <td>mRuKOWsB7mP0GwVzV3UD</td>\n",
       "      <td>10.1.1.313</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>721529</th>\n",
       "      <td>June 9th 2019, 00:01:29.000</td>\n",
       "      <td>1EWKOWsBoTGddM7vP0yR</td>\n",
       "      <td>10.1.2.149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>721530</th>\n",
       "      <td>June 9th 2019, 00:01:25.000</td>\n",
       "      <td>JhuKOWsB7mP0GwVzL3T0</td>\n",
       "      <td>10.1.1.249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>721531</th>\n",
       "      <td>June 9th 2019, 00:01:19.000</td>\n",
       "      <td>dhuKOWsB7mP0GwVzGHOF</td>\n",
       "      <td>10.1.1.386</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>721532</th>\n",
       "      <td>June 9th 2019, 00:01:15.000</td>\n",
       "      <td>nhuKOWsB7mP0GwVzCHLl</td>\n",
       "      <td>10.1.1.211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>721533</th>\n",
       "      <td>June 9th 2019, 00:01:09.000</td>\n",
       "      <td>qUWJOWsBoTGddM7v8Ulx</td>\n",
       "      <td>10.1.2.347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>721534</th>\n",
       "      <td>June 9th 2019, 00:01:05.000</td>\n",
       "      <td>QRuJOWsB7mP0GwVz4XHU</td>\n",
       "      <td>10.1.1.175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>721535</th>\n",
       "      <td>June 9th 2019, 00:00:59.000</td>\n",
       "      <td>SxuJOWsB7mP0GwVzynBl</td>\n",
       "      <td>10.1.1.191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>721536</th>\n",
       "      <td>June 9th 2019, 00:00:55.000</td>\n",
       "      <td>okWJOWsBoTGddM7vukfB</td>\n",
       "      <td>10.1.2.398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>721537</th>\n",
       "      <td>June 9th 2019, 00:00:49.000</td>\n",
       "      <td>1UWJOWsBoTGddM7vo0ZS</td>\n",
       "      <td>10.1.2.343</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>721538</th>\n",
       "      <td>June 9th 2019, 00:00:45.000</td>\n",
       "      <td>ERuJOWsB7mP0GwVzk260</td>\n",
       "      <td>10.1.1.486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>721539</th>\n",
       "      <td>June 9th 2019, 00:00:39.000</td>\n",
       "      <td>NEWJOWsBoTGddM7vfEVB</td>\n",
       "      <td>10.1.2.382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>721540</th>\n",
       "      <td>June 9th 2019, 00:00:35.000</td>\n",
       "      <td>dxuJOWsB7mP0GwVzaGy9</td>\n",
       "      <td>10.1.2.191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>721541</th>\n",
       "      <td>June 9th 2019, 00:00:29.000</td>\n",
       "      <td>jhuJOWsB7mP0GwVzVWs1</td>\n",
       "      <td>10.1.1.350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>721542</th>\n",
       "      <td>June 9th 2019, 00:00:25.000</td>\n",
       "      <td>dkWJOWsBoTGddM7vRUOR</td>\n",
       "      <td>10.1.2.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>721543</th>\n",
       "      <td>June 9th 2019, 00:00:19.000</td>\n",
       "      <td>TBuJOWsB7mP0GwVzLmol</td>\n",
       "      <td>10.1.1.249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>721544</th>\n",
       "      <td>June 9th 2019, 00:00:15.000</td>\n",
       "      <td>vUWJOWsBoTGddM7vHkGD</td>\n",
       "      <td>10.1.1.200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>721545</th>\n",
       "      <td>June 9th 2019, 00:00:09.000</td>\n",
       "      <td>aUWJOWsBoTGddM7vB0AR</td>\n",
       "      <td>10.1.2.432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>721546</th>\n",
       "      <td>June 9th 2019, 00:00:05.000</td>\n",
       "      <td>AEWIOWsBoTGddM7v90Bw</td>\n",
       "      <td>10.1.2.156</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>721547 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                         @timestamp                   _id  ip_address\n",
       "0       July 8th 2019, 14:43:03.000  XswJ0msBoTGddM7vxMDB  10.1.1.285\n",
       "1       July 8th 2019, 14:43:01.000  dKQJ0msB7mP0GwVzvJjz  10.1.2.389\n",
       "2       July 8th 2019, 14:42:59.000  CcwJ0msBoTGddM7vtb8y  10.1.1.415\n",
       "3       July 8th 2019, 14:42:57.000  bKQJ0msB7mP0GwVzrZdT   10.1.1.79\n",
       "4       July 8th 2019, 14:42:55.000  L6QJ0msB7mP0GwVzpZeI   10.1.1.60\n",
       "5       July 8th 2019, 14:42:53.000  O8wJ0msBoTGddM7vnb2w   10.1.2.66\n",
       "6       July 8th 2019, 14:42:51.000  Z8wJ0msBoTGddM7vlbze   10.1.2.25\n",
       "7       July 8th 2019, 14:42:49.000  J6QJ0msB7mP0GwVzjpUY  10.1.2.247\n",
       "8       July 8th 2019, 14:42:46.000                #NAME?  10.1.1.199\n",
       "9       July 8th 2019, 14:42:46.000                #NAME?  10.1.1.387\n",
       "10      July 8th 2019, 14:42:30.000  36QJ0msB7mP0GwVzQ4_c  10.1.2.128\n",
       "11      July 8th 2019, 14:12:45.000  W8ru0WsBoTGddM7vB6Mx  10.1.1.243\n",
       "12      July 8th 2019, 14:12:40.000  2qLt0WsB7mP0GwVz84Cr  10.1.2.106\n",
       "13      July 8th 2019, 14:12:36.000  Ycrt0WsBoTGddM7v5KAI  10.1.2.500\n",
       "14      July 8th 2019, 14:12:32.000  BKLt0WsB7mP0GwVz1H9p  10.1.2.100\n",
       "15      July 8th 2019, 14:12:28.000  t8rt0WsBoTGddM7vxJ3J  10.1.2.314\n",
       "16      July 8th 2019, 14:12:23.000  rcrt0WsBoTGddM7vsZw_  10.1.1.383\n",
       "17      July 8th 2019, 14:12:20.000  uqLt0WsB7mP0GwVzpXuJ  10.1.2.279\n",
       "18      July 8th 2019, 14:12:17.000  9qLt0WsB7mP0GwVzmXrT  10.1.2.264\n",
       "19      July 8th 2019, 14:12:15.000  b8rt0WsBoTGddM7vkpoB  10.1.2.468\n",
       "20      July 8th 2019, 14:12:12.000  Vsrt0WsBoTGddM7vhplI   10.1.2.95\n",
       "21      July 8th 2019, 14:12:09.000  UaLt0WsB7mP0GwVzeniX   10.1.2.47\n",
       "22      July 8th 2019, 14:12:06.000  pcrt0WsBoTGddM7vbpXY   10.1.1.64\n",
       "23      July 8th 2019, 14:12:03.000  eKLt0WsB7mP0GwVzY3Ij  10.1.2.412\n",
       "24      July 8th 2019, 14:12:00.000  kMrt0WsBoTGddM7vV5Np  10.1.2.313\n",
       "25      July 8th 2019, 14:12:00.000  pqLt0WsB7mP0GwVzV3Fs    10.1.2.1\n",
       "26      July 8th 2019, 14:10:59.000  7crs0WsBoTGddM7vaYAk   10.1.2.89\n",
       "27      July 8th 2019, 14:09:12.000  w6Lq0WsB7mP0GwVzx0Ir  10.1.1.170\n",
       "28      July 8th 2019, 14:08:28.000  hcrq0WsBoTGddM7vG05I  10.1.1.446\n",
       "29      July 8th 2019, 14:08:26.000  WaLq0WsB7mP0GwVzExd7   10.1.1.63\n",
       "...                             ...                   ...         ...\n",
       "721517  June 9th 2019, 00:02:29.000  cBuLOWsB7mP0GwVzKX30  10.1.2.465\n",
       "721518  June 9th 2019, 00:02:25.000  sUWLOWsBoTGddM7vGlVT   10.1.1.34\n",
       "721519  June 9th 2019, 00:02:19.000  6kWLOWsBoTGddM7vAlTj  10.1.1.499\n",
       "721520  June 9th 2019, 00:02:15.000  MUWKOWsBoTGddM7v81RC  10.1.2.179\n",
       "721521  June 9th 2019, 00:02:09.000  CBuKOWsB7mP0GwVz23vY  10.1.2.500\n",
       "721522  June 9th 2019, 00:02:05.000  mUWKOWsBoTGddM7vzFIx    10.1.2.3\n",
       "721523  June 9th 2019, 00:01:59.000  kUWKOWsBoTGddM7vtFHB  10.1.2.225\n",
       "721524  June 9th 2019, 00:01:55.000  _0WKOWsBoTGddM7vpVAg  10.1.1.295\n",
       "721525  June 9th 2019, 00:01:49.000  UEWKOWsBoTGddM7vjVCz  10.1.2.428\n",
       "721526  June 9th 2019, 00:01:45.000  oUWKOWsBoTGddM7vfk8R  10.1.2.446\n",
       "721527  June 9th 2019, 00:01:39.000  m0WKOWsBoTGddM7vZk6h  10.1.1.459\n",
       "721528  June 9th 2019, 00:01:35.000  mRuKOWsB7mP0GwVzV3UD  10.1.1.313\n",
       "721529  June 9th 2019, 00:01:29.000  1EWKOWsBoTGddM7vP0yR  10.1.2.149\n",
       "721530  June 9th 2019, 00:01:25.000  JhuKOWsB7mP0GwVzL3T0  10.1.1.249\n",
       "721531  June 9th 2019, 00:01:19.000  dhuKOWsB7mP0GwVzGHOF  10.1.1.386\n",
       "721532  June 9th 2019, 00:01:15.000  nhuKOWsB7mP0GwVzCHLl  10.1.1.211\n",
       "721533  June 9th 2019, 00:01:09.000  qUWJOWsBoTGddM7v8Ulx  10.1.2.347\n",
       "721534  June 9th 2019, 00:01:05.000  QRuJOWsB7mP0GwVz4XHU  10.1.1.175\n",
       "721535  June 9th 2019, 00:00:59.000  SxuJOWsB7mP0GwVzynBl  10.1.1.191\n",
       "721536  June 9th 2019, 00:00:55.000  okWJOWsBoTGddM7vukfB  10.1.2.398\n",
       "721537  June 9th 2019, 00:00:49.000  1UWJOWsBoTGddM7vo0ZS  10.1.2.343\n",
       "721538  June 9th 2019, 00:00:45.000  ERuJOWsB7mP0GwVzk260  10.1.1.486\n",
       "721539  June 9th 2019, 00:00:39.000  NEWJOWsBoTGddM7vfEVB  10.1.2.382\n",
       "721540  June 9th 2019, 00:00:35.000  dxuJOWsB7mP0GwVzaGy9  10.1.2.191\n",
       "721541  June 9th 2019, 00:00:29.000  jhuJOWsB7mP0GwVzVWs1  10.1.1.350\n",
       "721542  June 9th 2019, 00:00:25.000  dkWJOWsBoTGddM7vRUOR   10.1.2.66\n",
       "721543  June 9th 2019, 00:00:19.000  TBuJOWsB7mP0GwVzLmol  10.1.1.249\n",
       "721544  June 9th 2019, 00:00:15.000  vUWJOWsBoTGddM7vHkGD  10.1.1.200\n",
       "721545  June 9th 2019, 00:00:09.000  aUWJOWsBoTGddM7vB0AR  10.1.2.432\n",
       "721546  June 9th 2019, 00:00:05.000  AEWIOWsBoTGddM7v90Bw  10.1.2.156\n",
       "\n",
       "[721547 rows x 3 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Feature Building"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['@timestamp'] = pd.to_datetime(data['@timestamp'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "data.sort_values(['ip_address', '@timestamp'], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['shift_time'] = data.groupby(['ip_address'])['@timestamp'].shift(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['time_diff'] = (data['@timestamp'] - data['shift_time']).dt.seconds//60"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['date'] = data['@timestamp'].dt.date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['dow'] = data['@timestamp'].dt.weekday"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['hour'] = data['@timestamp'].dt.hour"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['is_weekend'] = ((data['dow']==5)|(data['dow']==6)).astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['hour_bucket'] = data['hour']//4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>@timestamp</th>\n",
       "      <th>_id</th>\n",
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       "  </thead>\n",
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       "      <th>721473</th>\n",
       "      <td>2019-06-09 00:06:09</td>\n",
       "      <td>DBuOOWsB7mP0GwVzhZ9U</td>\n",
       "      <td>10.1.1.1</td>\n",
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       "      <td>2019-06-09 01:28:39</td>\n",
       "      <td>bB7aOWsB7mP0GwVzDY5G</td>\n",
       "      <td>10.1.1.1</td>\n",
       "      <td>2019-06-09 00:06:09</td>\n",
       "      <td>82.0</td>\n",
       "      <td>2019-06-09</td>\n",
       "      <td>6</td>\n",
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       "      <td>R0w5OmsBoTGddM7vayZT</td>\n",
       "      <td>10.1.1.1</td>\n",
       "      <td>2019-06-09 01:28:39</td>\n",
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       "      <th>719222</th>\n",
       "      <td>2019-06-09 03:13:45</td>\n",
       "      <td>U0w6OmsBoTGddM7vRi8R</td>\n",
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       "    <tr>\n",
       "      <th>718730</th>\n",
       "      <td>2019-06-09 03:54:45</td>\n",
       "      <td>x01fOmsBoTGddM7vz6d3</td>\n",
       "      <td>10.1.1.1</td>\n",
       "      <td>2019-06-09 03:42:39</td>\n",
       "      <td>12.0</td>\n",
       "      <td>2019-06-09</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>718240</th>\n",
       "      <td>2019-06-09 04:35:35</td>\n",
       "      <td>nk-FOmsBoTGddM7vLRjb</td>\n",
       "      <td>10.1.1.1</td>\n",
       "      <td>2019-06-09 03:54:45</td>\n",
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       "      <td>2019-06-09</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <td>2019-06-09 05:21:49</td>\n",
       "      <td>N1CvOmsBoTGddM7vhbSz</td>\n",
       "      <td>10.1.1.1</td>\n",
       "      <td>2019-06-09 04:35:35</td>\n",
       "      <td>46.0</td>\n",
       "      <td>2019-06-09</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>717521</th>\n",
       "      <td>2019-06-09 05:35:29</td>\n",
       "      <td>tlG8OmsBoTGddM7vCDDU</td>\n",
       "      <td>10.1.1.1</td>\n",
       "      <td>2019-06-09 05:21:49</td>\n",
       "      <td>13.0</td>\n",
       "      <td>2019-06-09</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>717169</th>\n",
       "      <td>2019-06-09 06:04:49</td>\n",
       "      <td>uFLWOmsBoTGddM7v4zfT</td>\n",
       "      <td>10.1.1.1</td>\n",
       "      <td>2019-06-09 05:35:29</td>\n",
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       "      <td>2019-06-09</td>\n",
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       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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      ],
      "text/plain": [
       "                @timestamp                   _id ip_address  \\\n",
       "721473 2019-06-09 00:06:09  DBuOOWsB7mP0GwVzhZ9U   10.1.1.1   \n",
       "720483 2019-06-09 01:28:39  bB7aOWsB7mP0GwVzDY5G   10.1.1.1   \n",
       "719233 2019-06-09 03:12:49  R0w5OmsBoTGddM7vayZT   10.1.1.1   \n",
       "719222 2019-06-09 03:13:45  U0w6OmsBoTGddM7vRi8R   10.1.1.1   \n",
       "718875 2019-06-09 03:42:39  z01UOmsBoTGddM7vuzyC   10.1.1.1   \n",
       "718730 2019-06-09 03:54:45  x01fOmsBoTGddM7vz6d3   10.1.1.1   \n",
       "718240 2019-06-09 04:35:35  nk-FOmsBoTGddM7vLRjb   10.1.1.1   \n",
       "717685 2019-06-09 05:21:49  N1CvOmsBoTGddM7vhbSz   10.1.1.1   \n",
       "717521 2019-06-09 05:35:29  tlG8OmsBoTGddM7vCDDU   10.1.1.1   \n",
       "717169 2019-06-09 06:04:49  uFLWOmsBoTGddM7v4zfT   10.1.1.1   \n",
       "\n",
       "                shift_time  time_diff        date  dow  hour  is_weekend  \\\n",
       "721473                 NaT        NaN  2019-06-09    6     0           1   \n",
       "720483 2019-06-09 00:06:09       82.0  2019-06-09    6     1           1   \n",
       "719233 2019-06-09 01:28:39      104.0  2019-06-09    6     3           1   \n",
       "719222 2019-06-09 03:12:49        0.0  2019-06-09    6     3           1   \n",
       "718875 2019-06-09 03:13:45       28.0  2019-06-09    6     3           1   \n",
       "718730 2019-06-09 03:42:39       12.0  2019-06-09    6     3           1   \n",
       "718240 2019-06-09 03:54:45       40.0  2019-06-09    6     4           1   \n",
       "717685 2019-06-09 04:35:35       46.0  2019-06-09    6     5           1   \n",
       "717521 2019-06-09 05:21:49       13.0  2019-06-09    6     5           1   \n",
       "717169 2019-06-09 05:35:29       29.0  2019-06-09    6     6           1   \n",
       "\n",
       "        hour_bucket  \n",
       "721473            0  \n",
       "720483            0  \n",
       "719233            0  \n",
       "719222            0  \n",
       "718875            0  \n",
       "718730            0  \n",
       "718240            1  \n",
       "717685            1  \n",
       "717521            1  \n",
       "717169            1  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# IP Profile Building"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "ip_col = 'ip_address'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "ip_counts = data.groupby(ip_col)['@timestamp'].count().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "ip_counts = ip_counts.rename(columns={'@timestamp':'total_count'})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Daily counts average"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "daily_counts = data.groupby([ip_col, 'date'])['@timestamp'].count().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "daily_counts = daily_counts.rename(columns={'@timestamp':'daily_counts'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "daily_counts_agg = daily_counts.groupby(ip_col).daily_counts.median().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>0</th>\n",
       "      <td>10.1.1.1</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.1.1.100</td>\n",
       "      <td>78.0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10.1.1.101</td>\n",
       "      <td>40.0</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10.1.1.106</td>\n",
       "      <td>35.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10.1.1.109</td>\n",
       "      <td>42.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>10.1.1.110</td>\n",
       "      <td>41.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>10.1.1.114</td>\n",
       "      <td>37.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>10.1.1.118</td>\n",
       "      <td>42.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>10.1.1.119</td>\n",
       "      <td>42.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10.1.1.12</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10.1.1.121</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>10.1.1.128</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>10.1.1.129</td>\n",
       "      <td>42.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>10.1.1.135</td>\n",
       "      <td>37.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>10.1.1.138</td>\n",
       "      <td>39.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>10.1.1.139</td>\n",
       "      <td>79.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>10.1.1.147</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>10.1.1.149</td>\n",
       "      <td>41.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>10.1.1.15</td>\n",
       "      <td>76.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>10.1.1.152</td>\n",
       "      <td>38.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    ip_address  daily_counts\n",
       "0     10.1.1.1          40.0\n",
       "1   10.1.1.100          78.0\n",
       "2   10.1.1.101          40.0\n",
       "3   10.1.1.106          35.5\n",
       "4   10.1.1.109          42.5\n",
       "5   10.1.1.110          41.0\n",
       "6   10.1.1.114          37.0\n",
       "7   10.1.1.118          42.0\n",
       "8   10.1.1.119          42.0\n",
       "9    10.1.1.12          40.0\n",
       "10  10.1.1.121          40.0\n",
       "11  10.1.1.128          40.0\n",
       "12  10.1.1.129          42.0\n",
       "13  10.1.1.135          37.0\n",
       "14  10.1.1.138          39.5\n",
       "15  10.1.1.139          79.5\n",
       "16  10.1.1.147          40.0\n",
       "17  10.1.1.149          41.0\n",
       "18   10.1.1.15          76.5\n",
       "19  10.1.1.152          38.5"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "daily_counts_agg.head(20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## weekday weekend counts average"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "weekend_counts = data.groupby([ip_col, 'is_weekend'])['@timestamp'].count().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "weekend_counts = weekend_counts.rename(columns={'@timestamp':'weekend_counts'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "weekend_counts_agg = weekend_counts.pivot_table(index=ip_col, columns='is_weekend').reset_index([0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "weekend_counts_agg.columns = weekend_counts_agg.columns.droplevel()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "weekend_counts_agg.columns = [ip_col, 'week_day', 'weekend']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "weekend_counts_agg['is_weekend_ratio'] = weekend_counts_agg['week_day']/ weekend_counts_agg['weekend']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "lean_weekend_counts_agg = weekend_counts_agg[[ip_col, 'is_weekend_ratio']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## avg login time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "avg_timedelta_data = data.groupby(ip_col).agg({'time_diff':['mean','max']}).reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "avg_timedelta_data.columns = avg_timedelta_data.columns.droplevel()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "avg_timedelta_data.columns = [ip_col, 'td_mean', 'td_max']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ip_address</th>\n",
       "      <th>td_mean</th>\n",
       "      <th>td_max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10.1.1.1</td>\n",
       "      <td>28.999308</td>\n",
       "      <td>362.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.1.1.100</td>\n",
       "      <td>14.427072</td>\n",
       "      <td>185.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10.1.1.101</td>\n",
       "      <td>28.520492</td>\n",
       "      <td>211.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10.1.1.106</td>\n",
       "      <td>29.771144</td>\n",
       "      <td>319.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10.1.1.109</td>\n",
       "      <td>28.711934</td>\n",
       "      <td>278.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>10.1.1.110</td>\n",
       "      <td>28.249831</td>\n",
       "      <td>240.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>10.1.1.114</td>\n",
       "      <td>29.827169</td>\n",
       "      <td>300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>10.1.1.118</td>\n",
       "      <td>28.976471</td>\n",
       "      <td>267.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>10.1.1.119</td>\n",
       "      <td>29.087561</td>\n",
       "      <td>232.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10.1.1.12</td>\n",
       "      <td>30.152408</td>\n",
       "      <td>250.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ip_address    td_mean  td_max\n",
       "0    10.1.1.1  28.999308   362.0\n",
       "1  10.1.1.100  14.427072   185.0\n",
       "2  10.1.1.101  28.520492   211.0\n",
       "3  10.1.1.106  29.771144   319.0\n",
       "4  10.1.1.109  28.711934   278.0\n",
       "5  10.1.1.110  28.249831   240.0\n",
       "6  10.1.1.114  29.827169   300.0\n",
       "7  10.1.1.118  28.976471   267.0\n",
       "8  10.1.1.119  29.087561   232.0\n",
       "9   10.1.1.12  30.152408   250.0"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "avg_timedelta_data.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Full Feature Set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "merge_1 = ip_counts.merge(daily_counts_agg, on=ip_col, how='left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "merge_2 = merge_1.merge(lean_weekend_counts_agg, on=ip_col, how='left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "final_data = merge_2.merge(avg_timedelta_data, on=ip_col, how='left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    .dataframe tbody tr th {\n",
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       "    }\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>ip_address</th>\n",
       "      <th>total_count</th>\n",
       "      <th>daily_counts</th>\n",
       "      <th>is_weekend_ratio</th>\n",
       "      <th>td_mean</th>\n",
       "      <th>td_max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10.1.1.1</td>\n",
       "      <td>1446</td>\n",
       "      <td>40.0</td>\n",
       "      <td>2.070064</td>\n",
       "      <td>28.999308</td>\n",
       "      <td>362.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.1.1.100</td>\n",
       "      <td>2860</td>\n",
       "      <td>78.0</td>\n",
       "      <td>2.177778</td>\n",
       "      <td>14.427072</td>\n",
       "      <td>185.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10.1.1.101</td>\n",
       "      <td>1465</td>\n",
       "      <td>40.0</td>\n",
       "      <td>2.191721</td>\n",
       "      <td>28.520492</td>\n",
       "      <td>211.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10.1.1.106</td>\n",
       "      <td>1408</td>\n",
       "      <td>35.5</td>\n",
       "      <td>2.229358</td>\n",
       "      <td>29.771144</td>\n",
       "      <td>319.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10.1.1.109</td>\n",
       "      <td>1459</td>\n",
       "      <td>42.5</td>\n",
       "      <td>2.206593</td>\n",
       "      <td>28.711934</td>\n",
       "      <td>278.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>10.1.1.110</td>\n",
       "      <td>1482</td>\n",
       "      <td>41.0</td>\n",
       "      <td>2.242888</td>\n",
       "      <td>28.249831</td>\n",
       "      <td>240.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>10.1.1.114</td>\n",
       "      <td>1407</td>\n",
       "      <td>37.0</td>\n",
       "      <td>2.140625</td>\n",
       "      <td>29.827169</td>\n",
       "      <td>300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>10.1.1.118</td>\n",
       "      <td>1446</td>\n",
       "      <td>42.0</td>\n",
       "      <td>2.308924</td>\n",
       "      <td>28.976471</td>\n",
       "      <td>267.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>10.1.1.119</td>\n",
       "      <td>1440</td>\n",
       "      <td>42.0</td>\n",
       "      <td>2.257919</td>\n",
       "      <td>29.087561</td>\n",
       "      <td>232.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10.1.1.12</td>\n",
       "      <td>1392</td>\n",
       "      <td>40.0</td>\n",
       "      <td>2.200000</td>\n",
       "      <td>30.152408</td>\n",
       "      <td>250.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ip_address  total_count  daily_counts  is_weekend_ratio    td_mean  td_max\n",
       "0    10.1.1.1         1446          40.0          2.070064  28.999308   362.0\n",
       "1  10.1.1.100         2860          78.0          2.177778  14.427072   185.0\n",
       "2  10.1.1.101         1465          40.0          2.191721  28.520492   211.0\n",
       "3  10.1.1.106         1408          35.5          2.229358  29.771144   319.0\n",
       "4  10.1.1.109         1459          42.5          2.206593  28.711934   278.0\n",
       "5  10.1.1.110         1482          41.0          2.242888  28.249831   240.0\n",
       "6  10.1.1.114         1407          37.0          2.140625  29.827169   300.0\n",
       "7  10.1.1.118         1446          42.0          2.308924  28.976471   267.0\n",
       "8  10.1.1.119         1440          42.0          2.257919  29.087561   232.0\n",
       "9   10.1.1.12         1392          40.0          2.200000  30.152408   250.0"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_data.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "ip_map = final_data[ip_col].to_dict()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "RANDOM_STATE = 123"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## KMEANS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['ip_address', 'total_count', 'daily_counts', 'is_weekend_ratio',\n",
       "       'td_mean', 'td_max', 'cluster', 'tsne-2d-one', 'tsne-2d-two', 'ssd',\n",
       "       'anomaly_kmeans', 'anomaly_isolated', 'anomaly_svm', 'anomaly_manual'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 167,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {},
   "outputs": [],
   "source": [
    "feature_cols = ['total_count', 'daily_counts', 'is_weekend_ratio', 'td_mean', 'td_max']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_new = final_data[feature_cols]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {},
   "outputs": [],
   "source": [
    "min_max_scaler = preprocessing.MinMaxScaler()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/sanganichaitanya/anaconda3/lib/python3.6/site-packages/sklearn/preprocessing/data.py:323: DataConversionWarning: Data with input dtype int64, float64 were all converted to float64 by MinMaxScaler.\n",
      "  return self.partial_fit(X, y)\n"
     ]
    }
   ],
   "source": [
    "np_scaled = min_max_scaler.fit_transform(data_new)\n",
    "data_new = pd.DataFrame(np_scaled, columns=feature_cols)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x1a24324cf8>"
      ]
     },
     "execution_count": 172,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x900 with 30 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(final_data[feature_cols])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x11af9bba8>"
      ]
     },
     "execution_count": 173,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x900 with 30 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(data_new)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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du2a2HPv7Gzti7bLMIo4UAAAoJ8ahiQxOFuP7RybimTcm4unD43Hw9IXfet6ZScW717fHrk3L4hc2dcT2lVm3ngMAQJ2IcWhg+WISf/PWVDw9s+r5j9+cjMKFT37HjjVtM899d8TPXdkRy7LiGwAAGoEYhwbz2nA+nnljIr77xng8e2QiBicvvL7XLUvPbDm2LHZt7Iirutx6DgAAjUiMQ50NTxXjfx+diO++MX37+atD+Qv+3vZ0xP99VUfcvqkjbt+0LG5enY20W88BAKDhiXGosSRJ4rmBqXj68PTs918en4yp4oV//9tWZWPXzJZjP7++Pbqy9vwGAIBmI8ahRl4+NRWP7x+Lr+wfjQMXsfDa6o5U7Nq4LG7f1BG7Ni6LTcvdeg4AAM1OjMMi+tlwPr56YCy+vH8sek9MXdD3ZFMR77qyPX5h03SA37qmLTJpt54DAEArEeOwwN4aL8TXDozFVw6Mxf85NnlB39PTnYnbZ2a/37OhI3Jtbj0HAIBWJsZhAZyeKsY3D43H4/tH45nDE+fdfqw9HXHH5mXxi5uXxd/f2BHX5fyrCAAAS4kCgEs0UUjiO6+Px+P7x+JbPxuL8fM8Bp5ORbxvQ0d86PrO+JVrOmNVh9lvAABYqsQ4XIRCMYkfHJ2Ix/ePxdcPjcXQBewB/s51bXHP9V3xq9d12vcbAACICDEO55UkSfz1W1Px+P7ReOLAWBwbO/8+ZDeuysY913fFh67vdAs6AAAwj0qAs3j51FQ83j8Wjx8YjYMXsBXZ1Ssycc+Wzrjn+q64eU1bDUYIAAA0KzEOZV4bzsdX94/Fl/ePxgsn8+d9/xXL0vFrWzrjni2d8a4r2yOVsgUZAABwfmKcJW92K7LH94/FD4+ffyuyXFsqfuXazrjn+s5434aOyNoDHAAAuEhinCVpaLIY33xtPL5ygVuRdWQifnHzsrjn+q74xc3LojMrwAEAgEsnxlkyxvNJfOeN6b3Av/2z8Qveiuye6zvjV67tjJXttiIDAAAWhhinpc1uRfbl/WPxjQvciuxd69rjQ9d3xq9t6YwrO21FBgAALDwxTstJkiR+/ObMVmQHx+K4rcgAAIAGozpoGS+dnA7wrxwYu+CtyD58fWd8aIutyAAAgNoS4zS1Q6fz8dUDY/H4RW5F9uHrO+Od62xFBgAA1IcYp+m8OVaIrx2c3orsRxexFdmHr++M99qKDAAAaABinKYwuxXZ4/tH43u2IgMAAJqcGKdhjeeTeOr18fjKgQvfiuzvb+iID9mKDAAAaHBinIaSLybxgyMT8fiBsfjGwbEYmrIVGQAA0HpqGuMjIyPxZ3/2Z/HSSy/FwMBArFixIm699db41V/91VixYkXF+x577LF47rnnIiJi586dce+990ZXV1cth0uNzG5F9uX9o/G1C9yK7KZV2binpys+uMVWZAAAQPOpacWcOnUqTp06FR/60Idi48aNcfLkyfjTP/3TeOihh+KTn/xk6X0PP/xwDAwMxJ49eyKVSsWXvvSleOSRR+ITn/hELYfLInvx5FR8Zf9oPL5/LA4Nn38rsmtWZOIeW5EBAAAtoKYxvmnTpvhn/+yflY6vvPLK+PCHPxxf/OIXY2xsLDo7O+PIkSPR29sbn/70p2Pr1q0REXH//ffHZz/72Th69GisX7++lkNmgb0xUoj/92fZeOaFY/HiBWxFtm5ZOn7VVmQAAECLqfv9vWNjY5HNZqO9vT0iIvr7+6OjoyN6enpK79m6dWt0dHREf3+/GG9izx6eiHu/OxCj+faIOHuI59pS8f9c2xn32IoMAABoUXWN8dHR0fizP/uz+Ht/7+9FJjO98Nbg4GDkcrmKGdBUKhW5XC4GBwfP+Xl9fX2LOl4uz3/q7YjR/JkXWGtPJfGeNYW4a10hfn51IZZlRiJGIw7013iQ1IV/d5nlWmCWa4FyrgdmuRYo1+jXw7Zt2875+oLE+BNPPBFPPvnkOd/zwAMPxPbt20vHExMT8cUvfjFWrVoV99xzT8V7z3QrcpIk571F+Xx/WOonSZJ4+S+PRMTc6uizW5Hdc31nfMBWZEtWX1+ff3eJCNcCc1wLlHM9MMu1QLlWuB4WJMbvuOOOuO222875njVr1pS+Hh8fjy984QsREfGJT3wi2trmFuNauXJlDA0NVcR3kiQxPDwc3d3dCzFc6uC14UIMTc6FeK4tFX/9oatsRQYAACxJCxLjuVwucrncBb13fHw8Pv/5z0eSJPEv/sW/iGXLllW83tPTExMTE9Hf319awK2/vz8mJiYqniOnuew7MVVxvGNNmxAHAACWrJreFzw+Ph6f+9znYmRkJP7RP/pHMTExEYODgzE4OBj5/PSCXhs2bIgdO3bE3r17o7+/P/r7+2Pv3r1x6623WrytifWeIcYBAACWqpou4Hbo0KHYv39/RER85jOfqXit/Jny3bt3x6OPPhoPPvhgRETs3Lkz7rvvvloOlQVWPTN+ixgHAACWsJrG+Pbt2+Ohhx467/uWL18eu3fvrsGIqBUxDgAAMMfy1Sy6UxPFeG24UDrORBJvWyXGAQCApUuMs+heOFk5K35tVxKd2XNvUwcAANDKxDiLrvoW9W3Li3UaCQAAQGMQ4yy66hjfLsYBAIAlToyz6PYNVMb4DWIcAABY4sQ4i2qqmMTLp9ymDgAAUE6Ms6heOZWPybL2Xt+ZjjXt9RsPAABAIxDjLCr7iwMAAMwnxllU82J8rRgHAAAQ4yyqXjPjAAAA84hxFk2SJPNmxneIcQAAADHO4jk8WowTE3Ort3VlU3F9LlvHEQEAADQGMc6iqb5F/ebV2cikU3UaDQAAQOMQ4yya+Sup29MMAAAgQoyziPadmKw49rw4AADANDHOotk3YCV1AACAMxHjLIrTU8U4cLpQOk5FxE2rLd4GAAAQIcZZJC+emIqk7Hjrymwsb3O5AQAARIhxFsm8/cVXu0UdAABglhhnUcxbSX2tGAcAAJglxlkU1XuMW7wNAABgjhhnweWLSbxwUowDAACcjRhnwfUP5WN8biH1uGJZOq7qdKkBAADMUkgsuHnPi69pi1QqVafRAAAANB4xzoLzvDgAAMC5iXEW3JlmxgEAAJgjxllw8/YYF+MAAAAVxDgL6thoIY6PFUvHHZmIbSuzdRwRAABA4xHjLKjeqi3NblrdFtm0xdsAAADKiXEW1L6BqlvUV7tFHQAAoJoYZ0FZvA0AAOD8xDgLal6MrxXjAAAA1cQ4C2Y0X4xXh/IV5252mzoAAMA8YpwF89LJfBSTuePrcpnobneJAQAAVFNKLBjPiwMAAFwYMc6C6RXjAAAAF0SMs2DMjAMAAFwYMc6CKCbJvJnxHWIcAADgjMQ4C+LAUCFG8nOrt61qT8Xm5Zk6jggAAKBxiXEWRO/J+beop1KpOo0GAACgsYlxFsS+gaoYX+sWdQAAgLMR4yyIfScmK453rBbjAAAAZyPGWRDzVlJf216nkQAAADQ+Mc5lGxgvxOHRYum4LR2xfWW2jiMCAABobGKcy1a9pdnbVrVFe8bibQAAAGcjxrlsz9tfHAAA4KKIcS7bvOfFxTgAAMA5iXEuW/Vt6mIcAADg3MQ4l2U8n8Qrp/IV58Q4AADAuYlxLsvLp6Yin8wdb16eiVUdLisAAIBzUU1cFs+LAwAAXDwxzmWZ97z4WjEOAABwPmKcy2JmHAAA4OKJcS5ZkiRWUgcAALgEYpxLdmi4EENTc6u3dbel4poVmTqOCAAAoDmIcS5Z9az4zWvaIp1K1Wk0AAAAzUOMc8mqnxff4RZ1AACACyLGuWQWbwMAALg0YpxLVn2b+q1iHAAA4IKIcS7JqYlivDZcKB1nUhFvWyXGAQAALoQY55L0nqycFb9hZTaWZS3eBgAAcCHEOJdk34DnxQEAAC6VGOeSVM+Mi3EAAIALJ8a5JPNmxteKcQAAgAslxrlok4UkXj5lj3EAAIBLJca5aK8M5mOyOHe8oSsdVyzL1G9AAAAATUaMc9Gq9xf3vDgAAMDFEeNctH1iHAAA4LKIcS5adYx7XhwAAODiiHEuSpIkse/EZMU5M+MAAAAXR4xzUQ6PFuPkRFI6Xp5NxZZcto4jAgAAaD5inItSPSt+8+q2yKRTdRoNAABAcxLjXJR9A54XBwAAuFxinItiJXUAAIDLV7eHfZMkic9//vPxwgsvxD/5J/8k3vGOd5ReGxkZicceeyyee+65iIjYuXNn3HvvvdHV1VWv4TJj3h7ja8U4AADAxarbzPhTTz0V6fSZf/zDDz8chw4dij179sTv/M7vxKFDh+KRRx6p8QipdnqqGPtPF0rH6VTETast3gYAAHCx6hLjBw8ejO9+97vx0Y9+dN5rR44cid7e3viN3/iN2Lp1a/T09MT9998fzz//fBw9erT2g6XkhapZ8Z7ubHRlPekAAABwsWpeUuPj4/HQQw/F/fffH93d3fNe7+/vj46Ojujp6Smd27p1a3R0dER/f38th0oVz4sDAAAsjJrfY/wnf/IncfPNN8ctt9xyxtcHBwcjl8tFKjW3XVYqlYpcLheDg4Pn/Oy+vr4FHSuV/uJAe5RfMhuKg9HXN3BJn+V3RTnXA7NcC8xyLVDO9cAs1wLlGv162LZt2zlfX5AYf+KJJ+LJJ58853seeOCBOHHiRLz++uvxmc985pzvLQ/xWUmSnPF8ufP9Ybk8r718PCLmZsd33bAhtm1edtGf09fX53dFieuBWa4FZrkWKOd6YJZrgXKtcD0sSIzfcccdcdttt53zPWvWrIm/+Iu/iCNHjsQ//+f/vOK1P/qjP4qenp749Kc/HStXroyhoaGK+E6SJIaHh894Wzu1kS8m8eJJe4wDAAAshAWJ8VwuF7lc7rzv+7Vf+7W46667Ks79+3//7+PDH/5wvP3tb4+IiJ6enpiYmIj+/v7YunVrREw/Rz4xMVHxHDm19epQPsbnFlKPdcvScVWnxdsAAAAuRU2fGV+9enWsXr163vk1a9bEunXrIiJiw4YNsWPHjti7d2/cf//9ERGxd+/euPXWW2P9+vW1HC5l5u0vvqbtvI8NAAAAcGYNuUn07t2749FHH40HH3wwIiJ27twZ9913X51HtbTtG3CLOgAAwEKpe4w/9NBD884tX748du/eXYfRcDa2NQMAAFg4HvrlgvRWLd52y1oxDgAAcKnEOOd1bLQQx8eKpeNlmYit3XW/qQIAAKBpiXHOq/oW9RtXt0U2bfE2AACASyXGOS/PiwMAACwsMc55nWlbMwAAAC6dGOe8zIwDAAAsLDHOOY1MFaNvMF9x7mYxDgAAcFnEOOf00ql8JGXHW3KZyLW5bAAAAC6HquKcPC8OAACw8MQ45+R5cQAAgIUnxjmnfQOVMb5DjAMAAFw2Mc5ZFZMkXjhpZhwAAGChiXHO6sBQIUbyc8u3re5IxablmTqOCAAAoDWIcc5q/vPi7ZFKpeo0GgAAgNYhxjmrfScmK453rMnWaSQAAACtRYxzVmeaGQcAAODyiXHOyh7jAAAAi0OMc0ZvjRfi8GixdNyejrhhpdvUAQAAFoIY54yqZ8W3r2qL9ozF2wAAABaCGOeM9g24RR0AAGCxiHHOaN9JMQ4AALBYxDhn1Fs9M75WjAMAACwUMc484/kkfjqYrzi3Y7UYBwAAWChinHlePjUVhWTu+OoVmVjV4VIBAABYKAqLefbZXxwAAGBRiXHmqY7xHWIcAABgQYlx5jEzDgAAsLjEOBWSJIkXxDgAAMCiEuNUODRciKGpudXbuttSce2KTB1HBAAA0HrEOBWqb1G/eU1bpFKpOo0GAACgNYlxKnheHAAAYPGJcSr0inEAAIBFJ8apYGYcAABg8YlxSk5NFONnw4XScSYV8bZVYhwAAGChiXFKqmfFt6/MxrKsxdsAAAAWmhinpPp58R1rzYoDAAAsBjFOiefFAQAAakOMUyLGAQAAakOMExERk4UkXj5VdZu6GAcAAFgUYpyIiHhlMB9TxbnjjV3puGJZpn4DAgAAaGFinIhwizoAAEAtiXEiImLficmKY7eoAwAALB4xTkRE7Buonhlvr9NIAAAAWp8YJ5Ikid6TblMHAACoFTFOvDFSiJMTSel4eTYVW7ot3gYAALBYxDjTVB8KAAAfE0lEQVTzFm+7eXVbpFOpOo0GAACg9Ylx5q+kvtYt6gAAAItJjBO9tjUDAACoKTHOvJlx25oBAAAsLjG+xA1NFuPA6ULpOJ2KuGl1to4jAgAAaH1ifIl7sWpLs63d2ejKuiwAAAAWk+pa4uYt3uYWdQAAgEUnxpc4z4sDAADUnhhf4syMAwAA1J4YX8LyxSReOinGAQAAak2ML2GvDuVjfG4h9biyMx1XdWXqNyAAAIAlQowvYfsGqp4XX21WHAAAoBbE+BLmeXEAAID6EONLWG91jK8V4wAAALUgxpeoJEnieTPjAAAAdSHGl6hjY8V4a7xYOl6WiejpztZxRAAAAEuHGF+iqp8Xv2l1W2TTqTqNBgAAYGkR40vUvOfF3aIOAABQM2J8ibKSOgAAQP2I8SWqOsZ3iHEAAICaEeNL0MhUMV4dzFecu1mMAwAA1IwYX4JeOpWPpOz4+lwmcm0uBQAAgFpRYEvQvoGq58XXmhUHAACoJTG+BM17Xny1GAcAAKglMb4E7TsxWXFsZhwAAKC2xPgSUygm8eLJysXbblnTXqfRAAAALE1ifIk5cDofI/m55dvWdKRjY5fLAAAAoJZU2BJzpv3FU6lUnUYDAACwNInxJaa3KsZvsb84AABAzWXr8UMPHDgQTzzxROzfvz8iIjZv3hwf//jHI5fLRUTEyMhIPPbYY/Hcc89FRMTOnTvj3nvvja6urnoMt6VUz4yLcQAAgNqreYzv378/Hnzwwbjrrrvi13/91yOTycThw4cjk8mU3vPwww/HwMBA7NmzJ1KpVHzpS1+KRx55JD7xiU/Uergt50y3qQMAAFBbNY/x//W//lfs2rUrPvCBD5TOrV+/vvT1kSNHore3Nz796U/H1q1bIyLi/vvvj89+9rNx9OjRivdycd4aL8SR0WLpuD0dccPKutwcAQAAsKTVtMSGhoaiv78/3vWud8Uf/uEfxrFjx+Kqq66Ku+++O2688caIiOjv74+Ojo7o6ekpfd/WrVujo6Mj+vv7xfhlqH5e/G2r2qI9Y/E2AACAWqtpjL/55psREfH1r3897rnnnrjmmmvixz/+cTz44IPxmc98Jq6++uoYHByMXC5XscJ3KpWKXC4Xg4OD5/z8vr6+RR1/s3v69WxEzO0pfm12rG7/zPyuKOd6YJZrgVmuBcq5HpjlWqBco18P27ZtO+frCxLjTzzxRDz55JPnfM8DDzxQei78ve99b7znPe+JiIhrrrkmXnnllXj22WfjH/7DfxgRccattpIkOe8WXOf7wy51Rw+fiIix0vHPX7c2tm1bUfNx9PX1+V1R4npglmuBWa4FyrkemOVaoFwrXA8LEuN33HFH3Hbbbed8z5o1a2JoaCgiIjZu3Fjx2vr16+PEiRMREbFy5coYGhqqiO8kSWJ4eDi6u7sXYrhL1ryV1NdavA0AAKAeFiTGc7lcaVuyc7niiiti1apVcfTo0Yrzx44di82bN0dERE9PT0xMTER/f39pAbf+/v6YmJioeI6cizOeT+KVwXzFuR2rxTgAAEA9pGv5w1KpVNx1113x9NNPx49//OM4fvx4fPOb34wDBw7Ee9/73oiI2LBhQ+zYsSP27t0b/f390d/fH3v37o1bb73V4m2X4eVTU1FI5o6vWZGJVR01/fUDAAAwo+b7Wt1xxx2Rz+fjy1/+cgwPD8fGjRtjz549cfXVV5fes3v37nj00UfjwQcfjIiInTt3xn333VfrobaU5+0vDgAA0DDqssn0+9///nj/+99/1teXL18eu3fvruGIWt+858XFOAAAQN24T3mJqN5jXIwDAADUjxhfAopJIsYBAAAaiBhfAl4bLsTpqbnV27rbU3HNikwdRwQAALC0ifEl4PmBqsXbVreV9nAHAACg9sT4EtB70i3qAAAAjUSMLwH7qmbGb1krxgEAAOpJjC8B1dua7VgtxgEAAOpJjLe4kxPFeH2kUDrOpiLetkqMAwAA1JMYb3HVW5rdsCoby7IWbwMAAKgnMd7iqm9Rt3gbAABA/YnxFjfveXExDgAAUHdivMVV36Z+qxgHAACoOzHewiYLSbx8ysw4AABAoxHjLeyng/mYKs4db+rKxNplmfoNCAAAgIgQ4y1t38BkxfGONdk6jQQAAIByYryF9Z6sXkm9vU4jAQAAoJwYb2H7BqpifK3nxQEAABqBGG9RSZLM39ZstRgHAABoBGK8Rb0+UohTk0npeHk2FVu6Ld4GAADQCMR4i6reX3zHmrZIp1J1Gg0AAADlxHiLqr5F/Rb7iwMAADQMMd6i5j0vLsYBAAAahhhvUWbGAQAAGpcYb0FDk8U4eLpQOk6nIm5cna3jiAAAACgnxlvQCycrZ8W3dWejK+tXDQAA0CgUWgvaN+B5cQAAgEYmxluQ58UBAAAamxhvQb1Vt6nfslaMAwAANBIx3mLyxSRerI5xM+MAAAANRYy3mL7BfEzMLaQeV3am48rOTP0GBAAAwDxivMV4XhwAAKDxifEW0yvGAQAAGp4YbzFmxgEAABqfGG8hSZLMi3F7jAMAADQeMd5Cjo4V463xYum4M5OKrd3ZOo4IAACAMxHjLaT6efGbVmcjk07VaTQAAACcjRhvIZ4XBwAAaA5ivIXsG/C8OAAAQDMQ4y2k96SZcQAAgGYgxlvEyFQxXh3Ml45TEXGTGAcAAGhIYrxFvHgyH0nZ8fXdmci1+fUCAAA0IrXWIuwvDgAA0DzEeIuo3tbsljXtdRoJAAAA5yPGW8S+E5MVxxZvAwAAaFxivAUUikm8cDJfcc5t6gAAAI1LjLeA/afzMZqfW75tTUc6Nnb51QIAADQqxdYC5j8v3hapVKpOowEAAOB8xHgLqF5J3fPiAAAAjU2Mt4B9A7Y1AwAAaCZivAWYGQcAAGguYrzJvTlWiKNjxdJxezrihlXZOo4IAACA8xHjTa568bYbV7dFW9ribQAAAI1MjDe56lvUPS8OAADQ+MR4k/O8OAAAQPMR403uTHuMAwAA0NjEeBMbyyfxymC+4pzb1AEAABqfGG9iL5+aikIyd3zNikysbPcrBQAAaHTKrYl5XhwAAKA5ifEmJsYBAACakxhvYhZvAwAAaE5ivEkVk2RejFu8DQAAoDmI8Sb12nAhTk/Nrd7W3Z6Ka1Zk6jgiAAAALpQYb1LPD8y/RT2VStVpNAAAAFwMMd6kLN4GAADQvMR4k6qOcc+LAwAANA8x3qSspA4AANC8xHgTOjlRjNdHCqXjbCribavEOAAAQLMQ402o+hb17auy0ZGxeBsAAECzEONNyPPiAAAAzU2MNyHPiwMAADQ3Md6E5m9r1l6nkQAAAHApxHiTmSwk8dNT1TGerdNoAAAAuBRivMm8fGoqpopzx5u6MrFmWaZ+AwIAAOCiifEmU/28+I61nhcHAABoNjW/v3lwcDAef/zxePHFF2N8fDyuvPLKuOuuu+K2224rvWdkZCQee+yxeO655yIiYufOnXHvvfdGV1dXrYfbcOY/Ly7GAQAAmk3NY/yP//iPY2RkJD7+8Y9HLpeLv/mbv4k//uM/jjVr1sQNN9wQEREPP/xwDAwMxJ49eyKVSsWXvvSleOSRR+ITn/hErYfbcMQ4AABA86v5ber9/f2xa9euuP7662PdunXxi7/4i7F69eo4cOBAREQcOXIkent74zd+4zdi69at0dPTE/fff388//zzcfTo0VoPt6EkSSLGAQAAWkDNY3zr1q3x4x//OIaHh6NYLMbf/u3fxvDwcNx4440RMR3rHR0d0dPTU/E9HR0d0d/fX+vhNpTXRwoxOJmUjldkU3FdzuJtAAAAzabmt6n/43/8j+O//tf/Gp/85Ccjk8lENpuN3/7t345rrrkmIqafKc/lcpFKpUrfk0qlIpfLxeDg4Dk/u6+vb1HHXm/PDmQioqN03NOVj/5XX63fgC5Dq/+uuDiuB2a5FpjlWqCc64FZrgXKNfr1sG3btnO+viAx/sQTT8STTz55zvc88MADsX379vja174Ww8PD8alPfSpWrFhRemb8X/2rfxVXX311RERFiM9KkuSM58ud7w/b7L46MhQRp0vH79zYHdu2rarfgC5RX19fy/+uuHCuB2a5FpjlWqCc64FZrgXKtcL1sCAxfscdd1Sshn4ma9asiePHj8fTTz8dv/d7v1cK76uvvjpeffXVePrpp+M3f/M3Y+XKlTE0NFQR30mSxPDwcHR3dy/EcJvWvgHPiwMAALSCBYnxXC4XuVzuvO+bnJyMiIh0uvJR9VQqFUky/Sx0T09PTExMRH9/f2zdujUipp8jn5iYqHiOfCnqPSnGAQAAWkFNF3Bbv359XHnllfGnf/qnceDAgTh+/Hg89dRT8dJLL8Xf+Tt/JyIiNmzYEDt27Ii9e/dGf39/9Pf3x969e+PWW2+N9evX13K4DWVwshgHTxdKx+lUxI2rxTgAAEAzqukCbtlsNvbs2RNf/epX44tf/GJMTEzElVdeGR/96Edj586dpfft3r07Hn300XjwwQcjImLnzp1x33331XKoDeeFqi3NtnVnozN77mfoAQAAaEw1X039qquuin/6T//pOd+zfPny2L17d41G1Bx6q/cXX2tWHAAAoFnVfJ9xLs2+6hj3vDgAAEDTEuNNQowDAAC0DjHeBPLFJF46VRnjO8Q4AABA0xLjTaBvMB8Tcwupx1Wd6biyM1O/AQEAAHBZxHgTcIs6AABAaxHjTUCMAwAAtBYx3gSqY9zz4gAAAM1NjDe4JEnm7zEuxgEAAJqaGG9wR8eK8dZ4sXTcmUlFT3e2jiMCAADgconxBrdvoHJW/OY12cikU3UaDQAAAAtBjDe4ec+Lr3aLOgAAQLMT4w1u3vPia8U4AABAsxPjDc62ZgAAAK1HjDew4ali9A/lS8epiLjJbeoAAABNT4w3sBdPTkVSdnx9dyZWtPmVAQAANDtl18B6T+Qrjm9Z016nkQAAALCQxHgD23disuLY8+IAAACtQYw3sHnbmolxAACAliDGG1ShmMQL825TF+MAAACtQIw3qP2n8zFWmFu+bW1HOjZ0+XUBAAC0AnXXoPYNVO0vvrYtUqlUnUYDAADAQhLjDWre8+L2FwcAAGgZYrxBVcf4LWvFOAAAQKsQ4w2qtzrGLd4GAADQMsR4Azo+VoijY8XScUcmYtvKbB1HBAAAwEIS4w2oelb8bavaoi1t8TYAAIBWIcYbkFvUAQAAWpsYb0DzFm8T4wAAAC1FjDcgMQ4AANDaxHiDGcsn8cpgvuLczWIcAACgpYjxBvPyqakoJnPH167IxMp2vyYAAIBWovIajFvUAQAAWp8YbzD7BqpifK0YBwAAaDVivMFUz4zvWC3GAQAAWo0YbyDFJIkXTpoZBwAAaHVivIEcOl2I01Nzq7etbE/F1cszdRwRAAAAi0GMN5Dnz7B4WyqVqtNoAAAAWCxivIHMe17cSuoAAAAtSYw3kF7bmgEAACwJYryBiHEAAIClQYw3iBPjhXh9pFA6zqYitq8S4wAAAK1IjDeIfSfyFcfbV2WjI2PxNgAAgFYkxhtEb/X+4m5RBwAAaFlivEHsG5isOL5lbXudRgIAAMBiE+MNYt62ZqvNjAMAALQqMd4AJgpJ/PRU5TPjt6zJ1mk0AAAALDYx3gB+emoq8snc8eblmVizLFO/AQEAALCoxHgDmHeLusXbAAAAWpoYbwBiHAAAYGkR4w2g94RtzQAAAJYSMV5nSZLMmxm/VYwDAAC0NDFeZz8bKcTg5Nzqbbm2VFybs3gbAABAKxPjdbZvoHJW/ObVbZFOpeo0GgAAAGpBjNdZ70nPiwMAACw1YrzOqmfGb1krxgEAAFqdGK+z6sXbzIwDAAC0PjFeR4OTxTg0XCgdp1MRb1slxgEAAFqdGK+jF6pmxW9YmY3OrMXbAAAAWp0YryO3qAMAACxNYryOxDgAAMDSJMbrqDrGd4hxAACAJUGM18lUMYmXT4lxAACApUiM10nfYD4m5hZSj/Wd6biyM1O/AQEAAFAzYrxO3KIOAACwdInxOtk3YPE2AACApUqM10nvSTEOAACwVInxOkiSZP7M+FoxDgAAsFSI8To4MlqMgYli6bgzk4rrc9k6jggAAIBaEuN1UL14281rspFJp+o0GgAAAGpNjNdB7wnPiwMAACxlYrwOqmfGb1nTXqeRAAAAUA9ivA72nZisON6xxvPiAAAAS4kYr7HhqWLsHyqUjlMRcdNqt6kDAAAsJWK8xl48ORVJ2XFPdzZWtPk1AAAALCULfn/097///fjLv/zLeO2112JsbCz+83/+z3HFFVdUvGdkZCQee+yxeO655yIiYufOnXHvvfdGV1dX6T2vv/56PProo3HgwIFYvnx5vPe9741f+ZVfiVSquVcdn/+8uFlxAACApWbBp2QnJyfjpptuirvvvvus73n44Yfj0KFDsWfPnvid3/mdOHToUDzyyCOl18fGxuJzn/tc5HK5+N3f/d34yEc+Et/+9rfjO9/5zkIPt+b2DVTG+A4xDgAAsOQs+Mz4HXfcERERBw8ePOPrR44cid7e3vj0pz8dW7dujYiI+++/Pz772c/G0aNHY/369fGjH/0oJicn47d+67eivb09Nm3aFEeOHInvfOc7ceeddzb17HjvSTPjAAAAS13NH1bu7++Pjo6O6OnpKZ3bunVrdHR0RH9/f+k927Zti/b2uS2/br755jh16lS89dZbtR7ygikUk3jhRL7i3C1rxTgAAMBSU/M9tQYHByOXy1XMbqdSqcjlcjE4OBgREUNDQ7F69eqK7+vu7i69tm7dujN+dl9f3yKNemEcHE3FWKGzdLy6LYnTr++P4ead6L9kjf67orZcD8xyLTDLtUA51wOzXAuUa/TrYdu2bed8/YJi/Iknnognn3zynO954IEHYvv27Rc0qDPdZp4kyWXffn6+P2y9Pb9/NCJOlo53rlsWN9ywuX4DqpO+vr6G/11RO64HZrkWmOVaoJzrgVmuBcq1wvVwQTF+xx13xG233XbO96xZs+aCfuDKlStjaGioIr6TJInh4eHS7Hd3d3cMDQ1VfN/s8ex7mlGvldQBAACIC4zxXC4XuVxuQX5gT09PTExMRH9/f2kBt/7+/piYmCg9R97T0xNf+cpXYmpqKtrapoP1xRdfjFWrVs3bJq2Z2NYMAACAiEVYwG1wcDBee+21OHbsWERMr57+2muvxcjISEREbNiwIXbs2BF79+6N/v7+6O/vj71798att94a69evj4iId73rXdHe3h7/7b/9t3jjjTfiJz/5SXzrW99q+pXUxTgAAAARi7CA27PPPhvf+MY3Ssdf+MIXIiLiox/9aLz73e+OiIjdu3fHo48+Gg8++GBEROzcuTPuu+++0vd0dXXFJz/5yfgf/+N/xB/8wR/E8uXL484774w777xzoYdbM8fHCnFsrFg67shEbFtZ8/XzAAAAaAALXoN333133H333ed8z/Lly2P37t3nfM/mzZvjX//rf72QQ6ur6ufFb1zVFtl0887yAwAAcOlqvs/4UuUWdQAAAGaJ8RoR4wAAAMwS4zWyb6AyxneIcQAAgCVLjNfAWD6JvqF8xbmbxTgAAMCSJcZr4KWTU1FM5o6vy2ViZbt/9AAAAEuVIqyBgYlirO+c+0e9Y7VZcQAAgKXMRtc1cOfmZfHyRzbE8bFC9J6Yiq6sLc0AAACWMjFeQ1d2ZuL2TZl6DwMAAIA6c5s6AAAA1JgYBwAAgBoT4wAAAFBjYhwAAABqTIwDAABAjYlxAAAAqDExDgAAADUmxgEAAKDGxDgAAADUmBgHAACAGhPjAAAAUGNiHAAAAGpMjAMAAECNiXEAAACoMTEOAAAANSbGAQAAoMbEOAAAANSYGAcAAIAaS506dSqp9yAAAABgKTEzDgAAADUmxgEAAKDGxDgAAADUmBgHAACAGhPjAAAAUGPZeg+ApeHJJ5+Mn/zkJ3Hs2LHIZrNx/fXXxwc/+MHYtGlTvYdGnX3zm9+Mr33ta7Fr166477776j0c6uDUqVPx1a9+Nfbt2xfj4+Oxbt26+Af/4B/E9u3b6z00aqhYLMbXv/71+OEPfxiDg4OxcuXK+Lmf+7m4++67I5PJ1Ht4LLJXXnklnnrqqTh06FCcOnUqPvrRj8a73/3u0utJksQ3vvGN+P73vx+jo6OxZcuWuO+++/x3RAs617WQz+fja1/7WvT29sabb74ZnZ2dsX379vjgBz8Ya9eurfPIWWjn+9+Fcv/9v//3+MEPfhD33HNP3HXXXTUe6aUzM05N/PSnP41du3bFv/k3/yb+5b/8l5FOp+O//Jf/EiMjI/UeGnXU398fP/jBD2Lz5s31Hgp1Mjo6Gn/4h38YSZLEnj174j/+x/8Y9957b3R3d9d7aNTYn//5n8czzzwT9957b/z+7/9+fOQjH4nvfe978ed//uf1Hho1MDExERs3boyPfOQj0d7ePu/1b33rW/HUU0/FvffeG7/7u78buVwuPve5z8X4+HgdRstiOte1MDk5Ga+99lp84AMfiH/7b/9tfPzjH48TJ07E5z//+SgUCnUaMYvlfP+7MOuv//qv4+DBg7Fq1aoajm5hiHFq4pOf/GS8+93vjk2bNsXmzZvjYx/7WJw+fTpeffXVeg+NOhkdHY1HHnkkfvM3fzO6urrqPRzq5Fvf+lasXLkyPvaxj8WWLVti3bp1ceONN8aGDRvqPTRqrL+/P3bu3Bk7d+6MK664It7+9rfHzp07Y//+/fUeGjVwyy23xAc/+MF4xzveEalUquK1JEniu9/9bvzSL/1SvOMd74hNmzbFb/3Wb8X4+Hj86Ec/qtOIWSznuha6urriU5/6VLzzne+M9evXx5YtW+L++++PI0eOxJEjR+o0YhbLua6FWQMDA/HYY4/Fb//2bzflXVRinLoYHx+PJElE2BL2J3/yJ/F3/+7fjRtvvLHeQ6GO/vZv/za2bNkSf/RHfxSf+tSn4j/8h/8QTz/9dCRJUu+hUWPbtm2Ln/70p6X/oD58+HC8/PLLccstt9R5ZNTbW2+9FYODg3HTTTeVzrW3t8cNN9wQ/f39dRwZjWBsbCwiwn9TLkGFQiEeeuih+MAHPtC0/ye+Z8api8ceeyyuvvrq6OnpqfdQqIPvf//7cfz48fjYxz5W76FQZ2+++WZ873vfizvvvDN+6Zd+KX72s5/Fo48+GhERt99+e51HRy29//3vj/Hx8fh3/+7fRTqdjkKhEL/8y78cu3btqvfQqLPBwcGIiHmPr3R3d8fJkyf///buHrSpNgzj+NWqpCZiJKbERJFUnBWRpBQR0lhaEBJQnDJJaZeSzdSPRVwlDg5dCkInIUElUokZ+kUdVJqh4CCEKEikkAiWSlSCjck7iOWt7asvfjxHzf833nDgGg6Hcz/nfp5jRST8Jur1um7duqXDhw/L5XJZHQeGTU5OyuFwKBQKWR3lu9GMw7h0Oq1nz57pwoULam9nOKPVlMtlZTIZnT9/Xlu38ghqdc1mU36/X6dPn5Yk7d+/X5VKRXNzczTjLSafz+vRo0caGhqSz+fTy5cvlUql5Ha7dfz4cavj4Tew2fj6f42u4u/38eNH3bhxQ+/fv1c8Hrc6DgwrFAp6+PChLl++bHWUH8KbMIxKp9PK5/M6d+6cOjs7rY4DCzx//lxv377VlStX1mqNRkPFYlHz8/MaGxvTtm3brAsIo5xO54bRMq/Xq5mZGYsSwSq3b99Wf3+/gsGgJGnfvn16/fq1crkczXiLczqdkj59If/3189qtcphjy3q83jy0tKSEomEduzYYXUkGFYoFPTmzRslEom1WqPR0J07dzQ9Pa1kMmlhuv+PZhzGpFIpLSwsaHR09I/d14Efd+TIEfn9/nW1iYkJeTwenTx5kq/lLebgwYMql8vrapVKhV/UtKAPHz5smJZqb2/n/ADI7XbL6XTq6dOn6urqkiStrq6qWCzqzJkzFqeDafV6fV0j/nmxBq0lFArp6NGj62rXr19XMBj8oxZweeuFETdv3tTjx481MjIiu92+tv/LZrOpo6PD4nQwyW63bzhkxWazyeFw8L/YFtTX16erV68qm80qEAioVCppdnZWp06dsjoaDDt06JByuZzcbrd8Pp9KpZKmpqbU09NjdTQYUKvV9OrVK0mfxs+Xl5dVKpXkcDi0e/dunThxQvfv35fX65XH41E2m5XNZlN3d7fFyfGzfe1e2LVrl8bHx/XixQvF43G1tbWtvVNu3779q7+/wp/nW8+FLydjtmzZop07d2rPnj1WxP0ubSsrKyw545cbHh7etB6JRBSNRg2nwe8mmUxq7969isViVkeBBZ48eaJMJqNyuSyXy6VwOKxwOMxe0BZTq9V09+5dLS4uqlqtyul0KhAIKBKJsHWlBRQKBV27dm1DvaenR4ODg2o2m7p3754ePHigd+/e6cCBA4rFYizi/oW+di9Eo1FdunRp0+vOnj2rY8eO/ep4MOhbz4UvXbx4Ub29vRoYGDAR76egGQcAAAAAwDCOsgYAAAAAwDCacQAAAAAADKMZBwAAAADAMJpxAAAAAAAMoxkHAAAAAMAwmnEAAAAAAAyjGQcAAAAAwDCacQAAAAAADKMZBwAAAADAsH8AQqM4f7QPDCYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "n_cluster = range(1, 15)\n",
    "kmeans = [KMeans(n_clusters=i, random_state=RANDOM_STATE).fit(data_new) for i in n_cluster]\n",
    "scores = [kmeans[i].score(data_new) for i in range(len(kmeans))]\n",
    "fig, ax = plt.subplots()\n",
    "ax.plot(n_cluster, scores)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {},
   "outputs": [],
   "source": [
    "cluster_model = kmeans[5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1    103\n",
       "2     94\n",
       "4     73\n",
       "3     60\n",
       "5     46\n",
       "0     10\n",
       "Name: cluster, dtype: int64"
      ]
     },
     "execution_count": 176,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_data['cluster'] = cluster_model.predict(data_new)\n",
    "final_data['cluster'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {},
   "outputs": [],
   "source": [
    "tsne = TSNE(n_components=2, verbose=1, perplexity=40, n_iter=300, random_state=RANDOM_STATE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[t-SNE] Computing 121 nearest neighbors...\n",
      "[t-SNE] Indexed 386 samples in 0.000s...\n",
      "[t-SNE] Computed neighbors for 386 samples in 0.008s...\n",
      "[t-SNE] Computed conditional probabilities for sample 386 / 386\n",
      "[t-SNE] Mean sigma: 0.077308\n",
      "[t-SNE] KL divergence after 250 iterations with early exaggeration: 56.693813\n",
      "[t-SNE] KL divergence after 300 iterations: 0.342785\n"
     ]
    }
   ],
   "source": [
    "tsne_results = tsne.fit_transform(data_new)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {},
   "outputs": [],
   "source": [
    "final_data['tsne-2d-one'] = tsne_results[:,0]\n",
    "final_data['tsne-2d-two'] = tsne_results[:,1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {},
   "outputs": [],
   "source": [
    "tsne_cluster = final_data.groupby('cluster').agg({'tsne-2d-one':'mean', 'tsne-2d-two':'mean'}).reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16,10))\n",
    "\n",
    "sns.scatterplot(\n",
    "    x=\"tsne-2d-one\", y=\"tsne-2d-two\",\n",
    "    hue=\"cluster\",\n",
    "    palette=sns.color_palette(\"hls\", 6),\n",
    "    data=final_data,\n",
    "    legend=\"full\",\n",
    "    alpha=1\n",
    ")\n",
    "\n",
    "plt.scatter(x=\"tsne-2d-one\", y=\"tsne-2d-two\", data=tsne_cluster, s=100, c='b')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {},
   "outputs": [],
   "source": [
    "centers = cluster_model.cluster_centers_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {},
   "outputs": [],
   "source": [
    "points = np.asarray(data_new)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {},
   "outputs": [],
   "source": [
    "total_distance = pd.Series()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_sum_square_distance(data, cluster_model):\n",
    "    centers = cluster_model.cluster_centers_\n",
    "    points = np.asarray(data[feature_cols])\n",
    "    total_distance = pd.Series()\n",
    "    for i in range(len(points)):\n",
    "        distance = 0\n",
    "        for j in range(len(centers)):\n",
    "            a = np.linalg.norm(points[i] - centers[j])\n",
    "            distance += a**2\n",
    "        total_distance.set_value(i, distance)\n",
    "    \n",
    "    return total_distance    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/sanganichaitanya/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:10: FutureWarning: set_value is deprecated and will be removed in a future release. Please use .at[] or .iat[] accessors instead\n",
      "  # Remove the CWD from sys.path while we load stuff.\n"
     ]
    }
   ],
   "source": [
    "final_data['ssd'] = get_sum_square_distance(data_new, cluster_model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 7., 12.,  9., 33., 35., 22., 29., 29., 17., 16., 24., 10., 13.,\n",
       "        20., 21., 17., 17.,  9., 11.,  8.,  4.,  3.,  3.,  2.,  1.,  1.,\n",
       "         0.,  0.,  1.,  0.,  0.,  0.,  1.,  0.,  1.,  0.,  0.,  0.,  0.,\n",
       "         0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,\n",
       "         0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,\n",
       "         0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,\n",
       "         0.,  0.,  0.,  0.,  0.,  0.,  0.,  2.,  0.,  0.,  1.,  0.,  0.,\n",
       "         2.,  1.,  0.,  1.,  1.,  1.,  0.,  0.,  1.]),\n",
       " array([ 3.36474279,  3.45164257,  3.53854235,  3.62544212,  3.7123419 ,\n",
       "         3.79924167,  3.88614145,  3.97304122,  4.059941  ,  4.14684077,\n",
       "         4.23374055,  4.32064032,  4.4075401 ,  4.49443987,  4.58133965,\n",
       "         4.66823942,  4.7551392 ,  4.84203897,  4.92893875,  5.01583852,\n",
       "         5.1027383 ,  5.18963808,  5.27653785,  5.36343763,  5.4503374 ,\n",
       "         5.53723718,  5.62413695,  5.71103673,  5.7979365 ,  5.88483628,\n",
       "         5.97173605,  6.05863583,  6.1455356 ,  6.23243538,  6.31933515,\n",
       "         6.40623493,  6.4931347 ,  6.58003448,  6.66693426,  6.75383403,\n",
       "         6.84073381,  6.92763358,  7.01453336,  7.10143313,  7.18833291,\n",
       "         7.27523268,  7.36213246,  7.44903223,  7.53593201,  7.62283178,\n",
       "         7.70973156,  7.79663133,  7.88353111,  7.97043088,  8.05733066,\n",
       "         8.14423043,  8.23113021,  8.31802999,  8.40492976,  8.49182954,\n",
       "         8.57872931,  8.66562909,  8.75252886,  8.83942864,  8.92632841,\n",
       "         9.01322819,  9.10012796,  9.18702774,  9.27392751,  9.36082729,\n",
       "         9.44772706,  9.53462684,  9.62152661,  9.70842639,  9.79532617,\n",
       "         9.88222594,  9.96912572, 10.05602549, 10.14292527, 10.22982504,\n",
       "        10.31672482, 10.40362459, 10.49052437, 10.57742414, 10.66432392,\n",
       "        10.75122369, 10.83812347, 10.92502324, 11.01192302, 11.09882279,\n",
       "        11.18572257, 11.27262234, 11.35952212, 11.4464219 , 11.53332167,\n",
       "        11.62022145, 11.70712122, 11.794021  , 11.88092077, 11.96782055,\n",
       "        12.05472032]),\n",
       " <a list of 100 Patch objects>)"
      ]
     },
     "execution_count": 187,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(final_data['ssd'], bins=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "metadata": {},
   "outputs": [],
   "source": [
    "cutoff = 6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {},
   "outputs": [],
   "source": [
    "final_data['anomaly_kmeans'] = (final_data['ssd'] >= cutoff).astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a2950f1d0>"
      ]
     },
     "execution_count": 190,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(\n",
    "    x=\"tsne-2d-one\", y=\"tsne-2d-two\",\n",
    "    hue=\"anomaly_kmeans\",\n",
    "#     palette=sns.color_palette(\"hls\", 10),\n",
    "    data=final_data,\n",
    "    legend=\"full\",\n",
    "    alpha=1\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "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>ip_address</th>\n",
       "      <th>total_count</th>\n",
       "      <th>daily_counts</th>\n",
       "      <th>is_weekend_ratio</th>\n",
       "      <th>td_mean</th>\n",
       "      <th>td_max</th>\n",
       "      <th>cluster</th>\n",
       "      <th>tsne-2d-one</th>\n",
       "      <th>tsne-2d-two</th>\n",
       "      <th>ssd</th>\n",
       "      <th>anomaly_kmeans</th>\n",
       "      <th>anomaly_isolated</th>\n",
       "      <th>anomaly_svm</th>\n",
       "      <th>anomaly_manual</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>10.1.1.199</td>\n",
       "      <td>1365</td>\n",
       "      <td>40.5</td>\n",
       "      <td>2.123570</td>\n",
       "      <td>30.801320</td>\n",
       "      <td>455.0</td>\n",
       "      <td>5</td>\n",
       "      <td>-11.512229</td>\n",
       "      <td>6.081614</td>\n",
       "      <td>6.164888</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>10.1.1.249</td>\n",
       "      <td>4301</td>\n",
       "      <td>116.5</td>\n",
       "      <td>2.236268</td>\n",
       "      <td>9.459535</td>\n",
       "      <td>101.0</td>\n",
       "      <td>0</td>\n",
       "      <td>15.251910</td>\n",
       "      <td>-2.014084</td>\n",
       "      <td>11.541074</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>10.1.1.386</td>\n",
       "      <td>4300</td>\n",
       "      <td>118.5</td>\n",
       "      <td>2.127273</td>\n",
       "      <td>9.453361</td>\n",
       "      <td>104.0</td>\n",
       "      <td>0</td>\n",
       "      <td>15.528737</td>\n",
       "      <td>-2.041709</td>\n",
       "      <td>11.779482</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>10.1.1.486</td>\n",
       "      <td>4317</td>\n",
       "      <td>117.0</td>\n",
       "      <td>2.315668</td>\n",
       "      <td>9.417285</td>\n",
       "      <td>108.0</td>\n",
       "      <td>0</td>\n",
       "      <td>14.781444</td>\n",
       "      <td>-2.334249</td>\n",
       "      <td>11.659370</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>10.1.1.63</td>\n",
       "      <td>4339</td>\n",
       "      <td>112.0</td>\n",
       "      <td>2.148766</td>\n",
       "      <td>9.368142</td>\n",
       "      <td>101.0</td>\n",
       "      <td>0</td>\n",
       "      <td>15.287605</td>\n",
       "      <td>-2.182364</td>\n",
       "      <td>11.319226</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>10.1.1.86</td>\n",
       "      <td>4293</td>\n",
       "      <td>113.0</td>\n",
       "      <td>2.203731</td>\n",
       "      <td>9.456897</td>\n",
       "      <td>110.0</td>\n",
       "      <td>0</td>\n",
       "      <td>15.423254</td>\n",
       "      <td>-2.342858</td>\n",
       "      <td>11.090154</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>255</th>\n",
       "      <td>10.1.2.249</td>\n",
       "      <td>4353</td>\n",
       "      <td>112.0</td>\n",
       "      <td>2.250934</td>\n",
       "      <td>9.332721</td>\n",
       "      <td>102.0</td>\n",
       "      <td>0</td>\n",
       "      <td>14.986474</td>\n",
       "      <td>-2.238024</td>\n",
       "      <td>11.318310</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>311</th>\n",
       "      <td>10.1.2.386</td>\n",
       "      <td>4326</td>\n",
       "      <td>108.0</td>\n",
       "      <td>2.250188</td>\n",
       "      <td>9.392370</td>\n",
       "      <td>110.0</td>\n",
       "      <td>0</td>\n",
       "      <td>15.119220</td>\n",
       "      <td>-2.613225</td>\n",
       "      <td>10.791042</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>331</th>\n",
       "      <td>10.1.2.432</td>\n",
       "      <td>1437</td>\n",
       "      <td>40.5</td>\n",
       "      <td>2.413302</td>\n",
       "      <td>29.176880</td>\n",
       "      <td>466.0</td>\n",
       "      <td>5</td>\n",
       "      <td>-12.583876</td>\n",
       "      <td>1.878566</td>\n",
       "      <td>6.357696</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>357</th>\n",
       "      <td>10.1.2.486</td>\n",
       "      <td>4251</td>\n",
       "      <td>114.0</td>\n",
       "      <td>2.056075</td>\n",
       "      <td>9.571059</td>\n",
       "      <td>99.0</td>\n",
       "      <td>0</td>\n",
       "      <td>15.041411</td>\n",
       "      <td>-2.061416</td>\n",
       "      <td>11.438757</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>370</th>\n",
       "      <td>10.1.2.63</td>\n",
       "      <td>4372</td>\n",
       "      <td>121.0</td>\n",
       "      <td>2.184268</td>\n",
       "      <td>9.268588</td>\n",
       "      <td>118.0</td>\n",
       "      <td>0</td>\n",
       "      <td>15.395945</td>\n",
       "      <td>-2.032638</td>\n",
       "      <td>12.054720</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>381</th>\n",
       "      <td>10.1.2.86</td>\n",
       "      <td>4307</td>\n",
       "      <td>111.0</td>\n",
       "      <td>2.209389</td>\n",
       "      <td>9.441013</td>\n",
       "      <td>122.0</td>\n",
       "      <td>0</td>\n",
       "      <td>15.335781</td>\n",
       "      <td>-2.458637</td>\n",
       "      <td>10.825228</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     ip_address  total_count  daily_counts  is_weekend_ratio    td_mean  \\\n",
       "42   10.1.1.199         1365          40.5          2.123570  30.801320   \n",
       "62   10.1.1.249         4301         116.5          2.236268   9.459535   \n",
       "118  10.1.1.386         4300         118.5          2.127273   9.453361   \n",
       "164  10.1.1.486         4317         117.0          2.315668   9.417285   \n",
       "177   10.1.1.63         4339         112.0          2.148766   9.368142   \n",
       "188   10.1.1.86         4293         113.0          2.203731   9.456897   \n",
       "255  10.1.2.249         4353         112.0          2.250934   9.332721   \n",
       "311  10.1.2.386         4326         108.0          2.250188   9.392370   \n",
       "331  10.1.2.432         1437          40.5          2.413302  29.176880   \n",
       "357  10.1.2.486         4251         114.0          2.056075   9.571059   \n",
       "370   10.1.2.63         4372         121.0          2.184268   9.268588   \n",
       "381   10.1.2.86         4307         111.0          2.209389   9.441013   \n",
       "\n",
       "     td_max  cluster  tsne-2d-one  tsne-2d-two        ssd  anomaly_kmeans  \\\n",
       "42    455.0        5   -11.512229     6.081614   6.164888               1   \n",
       "62    101.0        0    15.251910    -2.014084  11.541074               1   \n",
       "118   104.0        0    15.528737    -2.041709  11.779482               1   \n",
       "164   108.0        0    14.781444    -2.334249  11.659370               1   \n",
       "177   101.0        0    15.287605    -2.182364  11.319226               1   \n",
       "188   110.0        0    15.423254    -2.342858  11.090154               1   \n",
       "255   102.0        0    14.986474    -2.238024  11.318310               1   \n",
       "311   110.0        0    15.119220    -2.613225  10.791042               1   \n",
       "331   466.0        5   -12.583876     1.878566   6.357696               1   \n",
       "357    99.0        0    15.041411    -2.061416  11.438757               1   \n",
       "370   118.0        0    15.395945    -2.032638  12.054720               1   \n",
       "381   122.0        0    15.335781    -2.458637  10.825228               1   \n",
       "\n",
       "     anomaly_isolated  anomaly_svm  anomaly_manual  \n",
       "42                  0            1               0  \n",
       "62                  1            1               1  \n",
       "118                 1            1               1  \n",
       "164                 1            1               1  \n",
       "177                 1            1               1  \n",
       "188                 1            1               1  \n",
       "255                 1            1               1  \n",
       "311                 1            1               1  \n",
       "331                 0            1               0  \n",
       "357                 1            1               1  \n",
       "370                 1            1               1  \n",
       "381                 1            1               1  "
      ]
     },
     "execution_count": 191,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_data.loc[final_data['anomaly_kmeans']==1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Isolated Forests"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 257,
   "metadata": {},
   "outputs": [],
   "source": [
    "outlier_fraction = 0.028"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 258,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ip_address</th>\n",
       "      <th>total_count</th>\n",
       "      <th>daily_counts</th>\n",
       "      <th>is_weekend_ratio</th>\n",
       "      <th>td_mean</th>\n",
       "      <th>td_max</th>\n",
       "      <th>cluster</th>\n",
       "      <th>tsne-2d-one</th>\n",
       "      <th>tsne-2d-two</th>\n",
       "      <th>ssd</th>\n",
       "      <th>anomaly_kmeans</th>\n",
       "      <th>anomaly_isolated</th>\n",
       "      <th>anomaly_svm</th>\n",
       "      <th>anomaly_manual</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10.1.1.1</td>\n",
       "      <td>1446</td>\n",
       "      <td>40.0</td>\n",
       "      <td>2.070064</td>\n",
       "      <td>28.999308</td>\n",
       "      <td>362.0</td>\n",
       "      <td>5</td>\n",
       "      <td>-4.352579</td>\n",
       "      <td>11.806170</td>\n",
       "      <td>4.570390</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.1.1.100</td>\n",
       "      <td>2860</td>\n",
       "      <td>78.0</td>\n",
       "      <td>2.177778</td>\n",
       "      <td>14.427072</td>\n",
       "      <td>185.0</td>\n",
       "      <td>2</td>\n",
       "      <td>9.245516</td>\n",
       "      <td>-8.002912</td>\n",
       "      <td>4.393522</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10.1.1.101</td>\n",
       "      <td>1465</td>\n",
       "      <td>40.0</td>\n",
       "      <td>2.191721</td>\n",
       "      <td>28.520492</td>\n",
       "      <td>211.0</td>\n",
       "      <td>1</td>\n",
       "      <td>4.270270</td>\n",
       "      <td>2.411105</td>\n",
       "      <td>3.658624</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10.1.1.106</td>\n",
       "      <td>1408</td>\n",
       "      <td>35.5</td>\n",
       "      <td>2.229358</td>\n",
       "      <td>29.771144</td>\n",
       "      <td>319.0</td>\n",
       "      <td>5</td>\n",
       "      <td>-7.361582</td>\n",
       "      <td>4.483963</td>\n",
       "      <td>4.265576</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10.1.1.109</td>\n",
       "      <td>1459</td>\n",
       "      <td>42.5</td>\n",
       "      <td>2.206593</td>\n",
       "      <td>28.711934</td>\n",
       "      <td>278.0</td>\n",
       "      <td>1</td>\n",
       "      <td>-2.134053</td>\n",
       "      <td>3.368442</td>\n",
       "      <td>3.626661</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ip_address  total_count  daily_counts  is_weekend_ratio    td_mean  td_max  \\\n",
       "0    10.1.1.1         1446          40.0          2.070064  28.999308   362.0   \n",
       "1  10.1.1.100         2860          78.0          2.177778  14.427072   185.0   \n",
       "2  10.1.1.101         1465          40.0          2.191721  28.520492   211.0   \n",
       "3  10.1.1.106         1408          35.5          2.229358  29.771144   319.0   \n",
       "4  10.1.1.109         1459          42.5          2.206593  28.711934   278.0   \n",
       "\n",
       "   cluster  tsne-2d-one  tsne-2d-two       ssd  anomaly_kmeans  \\\n",
       "0        5    -4.352579    11.806170  4.570390               0   \n",
       "1        2     9.245516    -8.002912  4.393522               0   \n",
       "2        1     4.270270     2.411105  3.658624               0   \n",
       "3        5    -7.361582     4.483963  4.265576               0   \n",
       "4        1    -2.134053     3.368442  3.626661               0   \n",
       "\n",
       "   anomaly_isolated  anomaly_svm  anomaly_manual  \n",
       "0                 0            0               0  \n",
       "1                 0            0               0  \n",
       "2                 0            0               0  \n",
       "3                 0            0               0  \n",
       "4                 0            0               0  "
      ]
     },
     "execution_count": 258,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 259,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['ip_address', 'total_count', 'daily_counts', 'is_weekend_ratio',\n",
       "       'td_mean', 'td_max', 'cluster', 'tsne-2d-one', 'tsne-2d-two', 'ssd',\n",
       "       'anomaly_kmeans', 'anomaly_isolated', 'anomaly_svm', 'anomaly_manual'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 259,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 260,
   "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>total_count</th>\n",
       "      <th>daily_counts</th>\n",
       "      <th>is_weekend_ratio</th>\n",
       "      <th>td_mean</th>\n",
       "      <th>td_max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.038133</td>\n",
       "      <td>0.052632</td>\n",
       "      <td>0.264803</td>\n",
       "      <td>0.884954</td>\n",
       "      <td>0.716621</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.502959</td>\n",
       "      <td>0.497076</td>\n",
       "      <td>0.408397</td>\n",
       "      <td>0.231366</td>\n",
       "      <td>0.234332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.044379</td>\n",
       "      <td>0.052632</td>\n",
       "      <td>0.426985</td>\n",
       "      <td>0.863479</td>\n",
       "      <td>0.305177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.025641</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.477159</td>\n",
       "      <td>0.919573</td>\n",
       "      <td>0.599455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.042406</td>\n",
       "      <td>0.081871</td>\n",
       "      <td>0.446812</td>\n",
       "      <td>0.872065</td>\n",
       "      <td>0.487738</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   total_count  daily_counts  is_weekend_ratio   td_mean    td_max\n",
       "0     0.038133      0.052632          0.264803  0.884954  0.716621\n",
       "1     0.502959      0.497076          0.408397  0.231366  0.234332\n",
       "2     0.044379      0.052632          0.426985  0.863479  0.305177\n",
       "3     0.025641      0.000000          0.477159  0.919573  0.599455\n",
       "4     0.042406      0.081871          0.446812  0.872065  0.487738"
      ]
     },
     "execution_count": 260,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_new.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 261,
   "metadata": {},
   "outputs": [],
   "source": [
    "model =  IsolationForest(n_jobs=-1, n_estimators=200, max_features=3, random_state=RANDOM_STATE, contamination=outlier_fraction)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 262,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/sanganichaitanya/anaconda3/lib/python3.6/site-packages/sklearn/ensemble/iforest.py:223: FutureWarning: behaviour=\"old\" is deprecated and will be removed in version 0.22. Please use behaviour=\"new\", which makes the decision_function change to match other anomaly detection algorithm API.\n",
      "  FutureWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "IsolationForest(behaviour='old', bootstrap=False, contamination=0.028,\n",
       "        max_features=3, max_samples='auto', n_estimators=200, n_jobs=-1,\n",
       "        random_state=123, verbose=0)"
      ]
     },
     "execution_count": 262,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(data_new)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 263,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/sanganichaitanya/anaconda3/lib/python3.6/site-packages/sklearn/ensemble/iforest.py:417: DeprecationWarning: threshold_ attribute is deprecated in 0.20 and will be removed in 0.22.\n",
      "  \" be removed in 0.22.\", DeprecationWarning)\n"
     ]
    }
   ],
   "source": [
    "# add the data to the main  \n",
    "final_data['anomaly_isolated'] = pd.Series(model.predict(data_new))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 264,
   "metadata": {},
   "outputs": [],
   "source": [
    "final_data['anomaly_isolated'] = final_data['anomaly_isolated'].map( {1: 0, -1: 1} )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 265,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    375\n",
       "1     11\n",
       "Name: anomaly_isolated, dtype: int64"
      ]
     },
     "execution_count": 265,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_data['anomaly_isolated'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 266,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a366f84e0>"
      ]
     },
     "execution_count": 266,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(\n",
    "    x=\"tsne-2d-one\", y=\"tsne-2d-two\",\n",
    "    hue=\"anomaly_isolated\",\n",
    "#     palette=sns.color_palette(\"hls\", 10),\n",
    "    data=final_data,\n",
    "    legend=\"full\",\n",
    "    alpha=1\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 267,
   "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>ip_address</th>\n",
       "      <th>total_count</th>\n",
       "      <th>daily_counts</th>\n",
       "      <th>is_weekend_ratio</th>\n",
       "      <th>td_mean</th>\n",
       "      <th>td_max</th>\n",
       "      <th>cluster</th>\n",
       "      <th>tsne-2d-one</th>\n",
       "      <th>tsne-2d-two</th>\n",
       "      <th>ssd</th>\n",
       "      <th>anomaly_kmeans</th>\n",
       "      <th>anomaly_isolated</th>\n",
       "      <th>anomaly_svm</th>\n",
       "      <th>anomaly_manual</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>10.1.1.249</td>\n",
       "      <td>4301</td>\n",
       "      <td>116.5</td>\n",
       "      <td>2.236268</td>\n",
       "      <td>9.459535</td>\n",
       "      <td>101.0</td>\n",
       "      <td>0</td>\n",
       "      <td>15.251910</td>\n",
       "      <td>-2.014084</td>\n",
       "      <td>11.541074</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>10.1.1.386</td>\n",
       "      <td>4300</td>\n",
       "      <td>118.5</td>\n",
       "      <td>2.127273</td>\n",
       "      <td>9.453361</td>\n",
       "      <td>104.0</td>\n",
       "      <td>0</td>\n",
       "      <td>15.528737</td>\n",
       "      <td>-2.041709</td>\n",
       "      <td>11.779482</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>10.1.1.486</td>\n",
       "      <td>4317</td>\n",
       "      <td>117.0</td>\n",
       "      <td>2.315668</td>\n",
       "      <td>9.417285</td>\n",
       "      <td>108.0</td>\n",
       "      <td>0</td>\n",
       "      <td>14.781444</td>\n",
       "      <td>-2.334249</td>\n",
       "      <td>11.659370</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>10.1.1.63</td>\n",
       "      <td>4339</td>\n",
       "      <td>112.0</td>\n",
       "      <td>2.148766</td>\n",
       "      <td>9.368142</td>\n",
       "      <td>101.0</td>\n",
       "      <td>0</td>\n",
       "      <td>15.287605</td>\n",
       "      <td>-2.182364</td>\n",
       "      <td>11.319226</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>10.1.1.86</td>\n",
       "      <td>4293</td>\n",
       "      <td>113.0</td>\n",
       "      <td>2.203731</td>\n",
       "      <td>9.456897</td>\n",
       "      <td>110.0</td>\n",
       "      <td>0</td>\n",
       "      <td>15.423254</td>\n",
       "      <td>-2.342858</td>\n",
       "      <td>11.090154</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>255</th>\n",
       "      <td>10.1.2.249</td>\n",
       "      <td>4353</td>\n",
       "      <td>112.0</td>\n",
       "      <td>2.250934</td>\n",
       "      <td>9.332721</td>\n",
       "      <td>102.0</td>\n",
       "      <td>0</td>\n",
       "      <td>14.986474</td>\n",
       "      <td>-2.238024</td>\n",
       "      <td>11.318310</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>311</th>\n",
       "      <td>10.1.2.386</td>\n",
       "      <td>4326</td>\n",
       "      <td>108.0</td>\n",
       "      <td>2.250188</td>\n",
       "      <td>9.392370</td>\n",
       "      <td>110.0</td>\n",
       "      <td>0</td>\n",
       "      <td>15.119220</td>\n",
       "      <td>-2.613225</td>\n",
       "      <td>10.791042</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>357</th>\n",
       "      <td>10.1.2.486</td>\n",
       "      <td>4251</td>\n",
       "      <td>114.0</td>\n",
       "      <td>2.056075</td>\n",
       "      <td>9.571059</td>\n",
       "      <td>99.0</td>\n",
       "      <td>0</td>\n",
       "      <td>15.041411</td>\n",
       "      <td>-2.061416</td>\n",
       "      <td>11.438757</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361</th>\n",
       "      <td>10.1.2.497</td>\n",
       "      <td>2973</td>\n",
       "      <td>83.5</td>\n",
       "      <td>2.440972</td>\n",
       "      <td>13.869785</td>\n",
       "      <td>165.0</td>\n",
       "      <td>2</td>\n",
       "      <td>4.914829</td>\n",
       "      <td>-13.606808</td>\n",
       "      <td>5.452700</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>370</th>\n",
       "      <td>10.1.2.63</td>\n",
       "      <td>4372</td>\n",
       "      <td>121.0</td>\n",
       "      <td>2.184268</td>\n",
       "      <td>9.268588</td>\n",
       "      <td>118.0</td>\n",
       "      <td>0</td>\n",
       "      <td>15.395945</td>\n",
       "      <td>-2.032638</td>\n",
       "      <td>12.054720</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>381</th>\n",
       "      <td>10.1.2.86</td>\n",
       "      <td>4307</td>\n",
       "      <td>111.0</td>\n",
       "      <td>2.209389</td>\n",
       "      <td>9.441013</td>\n",
       "      <td>122.0</td>\n",
       "      <td>0</td>\n",
       "      <td>15.335781</td>\n",
       "      <td>-2.458637</td>\n",
       "      <td>10.825228</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     ip_address  total_count  daily_counts  is_weekend_ratio    td_mean  \\\n",
       "62   10.1.1.249         4301         116.5          2.236268   9.459535   \n",
       "118  10.1.1.386         4300         118.5          2.127273   9.453361   \n",
       "164  10.1.1.486         4317         117.0          2.315668   9.417285   \n",
       "177   10.1.1.63         4339         112.0          2.148766   9.368142   \n",
       "188   10.1.1.86         4293         113.0          2.203731   9.456897   \n",
       "255  10.1.2.249         4353         112.0          2.250934   9.332721   \n",
       "311  10.1.2.386         4326         108.0          2.250188   9.392370   \n",
       "357  10.1.2.486         4251         114.0          2.056075   9.571059   \n",
       "361  10.1.2.497         2973          83.5          2.440972  13.869785   \n",
       "370   10.1.2.63         4372         121.0          2.184268   9.268588   \n",
       "381   10.1.2.86         4307         111.0          2.209389   9.441013   \n",
       "\n",
       "     td_max  cluster  tsne-2d-one  tsne-2d-two        ssd  anomaly_kmeans  \\\n",
       "62    101.0        0    15.251910    -2.014084  11.541074               1   \n",
       "118   104.0        0    15.528737    -2.041709  11.779482               1   \n",
       "164   108.0        0    14.781444    -2.334249  11.659370               1   \n",
       "177   101.0        0    15.287605    -2.182364  11.319226               1   \n",
       "188   110.0        0    15.423254    -2.342858  11.090154               1   \n",
       "255   102.0        0    14.986474    -2.238024  11.318310               1   \n",
       "311   110.0        0    15.119220    -2.613225  10.791042               1   \n",
       "357    99.0        0    15.041411    -2.061416  11.438757               1   \n",
       "361   165.0        2     4.914829   -13.606808   5.452700               0   \n",
       "370   118.0        0    15.395945    -2.032638  12.054720               1   \n",
       "381   122.0        0    15.335781    -2.458637  10.825228               1   \n",
       "\n",
       "     anomaly_isolated  anomaly_svm  anomaly_manual  \n",
       "62                  1            1               1  \n",
       "118                 1            1               1  \n",
       "164                 1            1               1  \n",
       "177                 1            1               1  \n",
       "188                 1            1               1  \n",
       "255                 1            1               1  \n",
       "311                 1            1               1  \n",
       "357                 1            1               1  \n",
       "361                 1            1               0  \n",
       "370                 1            1               1  \n",
       "381                 1            1               1  "
      ]
     },
     "execution_count": 267,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_data.loc[final_data['anomaly_isolated']==1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# One Class SVM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 268,
   "metadata": {},
   "outputs": [],
   "source": [
    "model =  OneClassSVM(nu=outlier_fraction, random_state=RANDOM_STATE, degree=2, kernel='rbf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 269,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_new_clean = data_new.loc[data_new.total_count <=data_new.total_count.quantile(1-outlier_fraction)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 270,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/sanganichaitanya/anaconda3/lib/python3.6/site-packages/sklearn/svm/classes.py:1175: DeprecationWarning: The random_state parameter is deprecated and will be removed in version 0.22.\n",
      "  \" be removed in version 0.22.\", DeprecationWarning)\n",
      "/Users/sanganichaitanya/anaconda3/lib/python3.6/site-packages/sklearn/svm/base.py:196: FutureWarning: The default value of gamma will change from 'auto' to 'scale' in version 0.22 to account better for unscaled features. Set gamma explicitly to 'auto' or 'scale' to avoid this warning.\n",
      "  \"avoid this warning.\", FutureWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "OneClassSVM(cache_size=200, coef0=0.0, degree=2, gamma='auto_deprecated',\n",
       "      kernel='rbf', max_iter=-1, nu=0.028, random_state=123,\n",
       "      shrinking=True, tol=0.001, verbose=False)"
      ]
     },
     "execution_count": 270,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(data_new_clean)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 271,
   "metadata": {},
   "outputs": [],
   "source": [
    "final_data['anomaly_svm'] = pd.Series(model.predict(data_new))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 272,
   "metadata": {},
   "outputs": [],
   "source": [
    "final_data['anomaly_svm'] = final_data['anomaly_svm'].map( {1: 0, -1: 1} )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 273,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    365\n",
       "1     21\n",
       "Name: anomaly_svm, dtype: int64"
      ]
     },
     "execution_count": 273,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_data['anomaly_svm'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 274,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a36749c18>"
      ]
     },
     "execution_count": 274,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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ReCGEEH1KvcdP8LJbseL14Lq4oSzqvQHopACzq2itqTFeXBReXEJ0XlDd2bTWLN6caNY2bXCYd9fXc/tH6RT3etvhvFc38Nk5wxniU8SUjx++Wsa8NelVC0IexfszhzHY57b7fcoyCZ47oZiYA5ZSBLUh6PbOyvxCCCE6j4zECyGE6FOMMdR7/NRm9aM2mkvM4++1wWwjV3lYXK055Mk1DJm9nDNe2Ug1/l5bYM1xHKYMCjVrG18Y4KVVsRb3fX11em37tXVOUwAPUG8brnlnM/HdGO8wxhAyCfJ1gv4qTtAkdv0gIYQQYhckiBdCCCF6uRgejntuNaU16SXfFqyr56dvbiSuem9CXp7X5aGjB5AftPBbihE5XiYWBVrc74D8dHp7ebzldIqyehvb9M4LHUIIIXqu3nv0FkIIIQQAVUmXWKp5tsEba2IkTQH+LupTpvlNipMH+zjizKGAIqAcEnh4cWUdH2xMp7Sfv0c2o7I9uG6CcbkBoj5NTXLbfPWfjMshajnsqlyC1hqtNY7j9PqsDiGEEF1PgnghhBCil8vxaXyWIulsCzAPLAjioZcHnK5N1tbq+RjwKptnTyimwQGPVgSUS2BrintEpXh/5jBueG8z6+tsfjwuh2MGB3GcHafANxbDe39jnM8r4pxckkWBz+Azqc54dUIIIfooSacXQgiRcZZl4fHIdeOuEsTmb0cXk+VNH/ZLsr3cd0QRYdW31io3xhA2CfJ0ghziBMy2de1xHQZ4ktwzJZcnjy1kxhAvAXfnc9hj+Djz5Q1Mf2Ed17+7mXGPrGRRuY3H4yGuvNTix9beDL8qIYRovfvuu4999tmHwsJCpk6dyrvvvtvVXRLtIEG8EEIIsDzU4qdW+VFWxwXbWmtiOsBjK5Pc+VmMTY4fuxfPw+6uPMbmyGIPX547nGXnlbDg1MEUeVPdbqkz1/JQg4+48nZJ0T1jDF43RYgUTiuWHKxMwVvrthXDM8C172xmk+3hR/PLmfjEaq5eWElMB3ttEUEhRM/x9NNPc8011/CLX/yCBQsWMGHCBE477TTWrFnT1V0TbSRBvBBC9HENysdDyxo46PFSJjy+mn+sSBBXvg557lp8HPbkai6aV8ZNC8vZ85EVlDYotJbDT2ezXJuIiZOvE2SZRLcL4Ot1gFs+rOGwp9Zy/rzNlNk+VDffT1JOy+kIDbbLhxvjvLiyjvUxm/s/r+bStzaSkBmMQogu9qc//YmzzjqL8847jzFjxnD77bdTWFjI7Nmzu7proo2699FRCCFERmmt+aLK5j/f2sTGeocNMZuL3yhjea272yOHWmsWlydYUb1tfrDtws0Ly0lg7W7XRS/iaC83Lizn94srKa1J8XJpjKlPrqbWdMzFpEzJCyhG92vexysOzOXvX9c0a3t2eS1JJfu8EGKb0toUF71VwYn/3MxFb1VQWpvZWhrJZJLFixczbdq0Zu3Tpk1j0aJFGd226HhyWVgIIfowy7J49KuqFu2PL6thvwnZpFKtP6lQShHDS8JoLAVh5ZJyki3ul3ANbi+vpybapt5onlhW26ytrN6mOumS1Y2nlEdVijdmDOG+f1fx74oEs/bMZlxegJ+/WdbsfsOiXmhD1Xqpdi9E71Zam2L6K1tYWbtt2s6Hm5M8e0wuQyOZ+dHbsmULjuOQn5/frD0/P59NmzZlZJsic2QkXgghuhmlOi/d3HXd7a6dPaEw0OZ065jy88PXNjH8geWUPLicOxbXcGBhkMJQ8xHI68fnElS7nm8s+g6NSQe636KALF/3Pk1xXZcst4HLx4W5d2ouh+YpAibFnYcV0JjH4rcUs48cQFS17oJYvQ4wf6PL/35ax9J6T4dNbRFCdB+3flzbLIAHWFnrcOvHtTt4RMf5bpadMUZqdvRAMhIvhBDdRONyVStrbKqSDvvmBYiYJMa0PphWSlGHj/JEevQuP6AIm+QOR/Mcx+H7w8P8rTjI2+sbADhicIhpg0I4Trz127U83Pfval5fEwPSafO3fbiFs8dG+WDmMP7y7yrW19n8dN9+DAmC68oSXGKbqHb4yxFFTHtqNQ12el+9cWIeAXrGxR7XsVGAC3hxOWNEiO+XjGBDzGZwlocQrSsi2KD8/McbG3lhZR0A/+/9Lcw+cgCnDvNhnL61koAQvdmG+u3/tpXtoL0j5ObmYllWi1H38vLyFqPzovuTIF4IIbqJOuVnxovrWVSWDqb7Byw+mDmMPJ1odUptnfJz/PNr+XRzemms/fMDvHjSQEJmxwF52CR4/NgB1Dvp0c+QlW5rSxJv3FW8ta6hRfuCdfWcO8LPNftmYVAYx5b0YNGC4ziMCXtY+sMSVtWkGBD2kGW5+Hvoeut+k8JPiv5ZCmNaH3w3uKopgG90w3ubOWrwECJIEC9EbzEgtP0aGUU7aO8IPp+P/fbbj/nz5zN9+vSm9vnz53PSSSdlbLsiM7p3npoQQvQRWmv+vSXZFMADVMQdfv1BOY5u3fVWy7J4dkVdUwAP8MnmOC+uimFZOz4xaFw7O1+n188OmdZfNGgU1C4nDAu3aD+kOITruji2jWunJIDvo5RSxHSAbxq8LI97ialAi/RNbdLV8/eJuuTpBIEeGsB/W1v3d2c79084BiTTVYhe5YYDIgyPND8uD49Y3HBAJKPb/elPf8rf//53Hn74Yb7++muuvvpqysrKuOCCCzK6XdHxZCReCCG6AaUU6+paFoFbU2dju9CaWbFa62YBfKMlWxKcNSLQqnWv28t1HM4cHeHjzXH+8XUNIa/mV5PzKfS3PZARvU+dCnDkM6v5siK9j++b7+elkwYR3k6GSF/eX8IWTCoKsvBbF/OuOLA/Ee3SQ2YWCCFaYWjEy7PH5HLrx7WU1TsUhdIBfKaK2jWaMWMGFRUV3H777WzcuJE99tiDJ554giFDhmR0u6LjSRAvhBDdgOM4TBscxm+p9MjbVj/dpx9B7dKa+Nu2bS7YM5u//rt5tflzx2Zj25lPxQ26cX57SC63HZyeWxdWNtpteWFC9C0ej4cnvq5pCuABPt2c4J+lMc4Y5svoxaWeJkySp08o5vFltSzaGOfs0VEOKvCB0/LinBCiZxsa8XLv1P6dvt0LL7yQCy+8sNO3KzqWBPFCCNFNRHWKRWcM47p3N1ORcLhsv35MzPfibGeZtu0xxlCSpfn7scX896JylIKbJ+YzJNR5o5s+N7kta6DvDqiKb1FK8XlFy334y4okuiSzGSI9jTGGkIlz4egAF4wOoY2D60oAL4QQojkJ4oUQopvQrkNJ0PDAtDwcFBHttDqAb+Q3SU4c5GHKgIEAZFsOjtPz5xaLnsu2bWbtmc1938kQOXtMtFMyRHqi9IUNh7Yt8iiEEKKvkMJ2QgjRjbhuuiJ3yCTbPULpOg5ZJMmi7c/RWevTi74jnSGieOL4gYzL87NffoDnvj+IgcG+Pf9dCCGEaC8ZiRdCCEGD8rE5AatqUuyTFyBLp/C4kubcVtqyiBtNQBncLlrXWymFZVm4rtuqtck7Q8CkOK7Y4uDvF4PS+DRYxpEpF0IIIUQ7SBAvhBB9XFz5uPmDSv7yWTrd2avhjVOHsl+2JfOV26DBCvDo17W8UhrjqCEhzhkTJeS2rL6eSXHlZX0DPL+ijv0L/IwvCHR6H3bEdV2M8nLTonLeWd/AtMFhbhifS5aJy4i8EEII0QYSxAshRB8Xc3VTAA+QcuFnb5bx0onFhGVdq1ZJKB+XvrmJJ7+pBeC11THeWd/AXw7PJ2A6p0K/sixeW5Pg3Fc2NLUdPyzMfdMKCHVSH3Ymho9TX1rP+1uXT/u6MsnyqiQPHVlAkK7vnxBCCNFTyORHIYToZrTWxJSfLcZPrQrg6Mxeb42lWqZcb4jZuKiMbrc3SaB5amsA3+i5FXUkTOcdZmsdD9e/W96s7aVVMerd7nGoTxjVFMA3enV1jGQnvkc9ReOUCCGEEGJ75MgphBBdRClFvfJTbgJsdv3UKz9aaypcH8fPXceIB1ewx99W8s+1KVIqc4F8f79mYFbz5z9/j2zClozCt5YCAp7mFz38lkJ14nUQoyDhtLwg47jdI1XdoyD0nfeof8BCq+7Rv+6iXvtZXK15enWKSgI4WoJ5IYQQzUkQL4QQXSSm/PzwtTJGPricUQ+tYOYrZdQqP/+1YCOfbk6vDV2Xcjnv1fXETOaC+KhKsuAHQzlzTJR98/3cdnA+l+3XD91Fhdl6oqByuHFCXrO268bnElKd9x5GlMMvDsht1nZAQYCsbjJxLqRsfjulsOlvBfzpe4VkKblY1Khe+fnhq2VMfWo15726gTEPr+CbOi2rRgghhGimmxzahRCib7Esi/lrGnh9TX1T24J19ZTVOywqa16IzDGwPmaTE85MX1zXJU8n+OOh/Ym7ELEMxukexdB6Co+b4vyxWRw9NMy7GxqYVBRkUEjhcTtxrrdrc+6YLMb28/HI1zWML/Bz1pjsdOG4zuvFDlmuzSnDAhx1fglLK5OM7e8nrGyUKxeLGm2Km2a/CUnHcMXbm3jimAKCsmq8EEKIreTSrhBCdAGtNYs2NrRoX1qZ5PBBoWZtXg2DMjycaozB46bIIoWREfh2CZokI4M254/0MzpkE+yCYnJBN8HhBYq/TunPxWODhN2GblX53W9S5KoEB+dCP+L4jI3WmjoV4JsGL+ttPw3K39Xd7BJKKWqSLbMSKuIOjpH6FEKI3ffOO+8wc+ZM9thjD3Jycnj00Ue7ukuinSSIF0KI3aCUIqG91OInrnyoVk6Ctm2b00dFW7QPDFv85pACpgxMB/IFIYunTxxEEAmsewJjDI7jdGng7LouOKndXh4wXbPBR4UJUGECHRpcf/v9qTQ+Dp6zmoMeW8Wef1vBBfM2Uq/7XiBvjKEk20tBqPkc+J/t24+o1KcQQnSAWCzGnnvuyf/8z/8QDAa7ujtiN0g6vRBCtJNSikrj52fzN/LWunomFAb5y7RCCjypdCC1E8YYRkY093yviFsWleNiuG58LqOyLUImzuPHFJI0Gq0gqmV0XHS+mPIz6/UyXi6NAXDc0DD3H1nUoevOG8vDnR9UsLo21dT2cmmMLyttxvfTO/weWZZFzNV4FHiN3a2yDXZHlCQLTx/Grz8oZ3l1igv3yuGIQQFcJ9HVXRNC9AJHH300Rx99NAA/+clPurg3YndIEC+EEO0Uw8vMl9ezcEM6LX7emhgnPr+W108ZRBa7PukOmCRnjfBz4vAhAES0A04SAwRJEgQwYGQQTnQyy7J4bXV9UwAP8M/SGG+srefkwd7dHuVvlHQVX1W1nHawrCrJhP6+7T4mrnws2pjid5+Ukxe0+O9J+Qzw2Si3539RXNclVyf4zaR+JA2EtYsjAbwQvZLatB7f07NRleWYfnkkZ8zCFBR3dbdEDyFBvBBCtFPK6KYAvtFXlUkSLmRtJ6tea00KC61Au+nRQ+PYRBpT5Xt+DCJ6Ca0176xvWbPhnQ0NnDLU32FBfEi7XLBHNq9+62KBpeCIwaHtBq+WZfHhphQnz13b1PbSyjq+/GEJ2R30BVJKEcNL0mgsBVmdXHzPGIM2KQJAB73NQohuRm1aT/D2K9Cb1je1Wcu/oOHKOySQF60ic+KFEKKdtDIMCDe/Fprt1/h0ywg+qTx8WWfx47e28It3K9no+DCy/rPophzH4fTRkRbtp4+KdlgA37id7w0McNfUAkZkezmgIMDrM4bQbwdzwOtdze8XVzZvsw1vra3HsrZ9nxztpU4FqFMB0K0fr1BKUYOf01/eyLAHlrPPoyt5db1NSsmYhxCi4/ient0sgAfQW0fmhWgNCeKFEKKdosrmb8cMIOhJB+0+S/HAkQMIq1Sz+2mtKa1XTHp8FU9+U8vsL6rZ79GVVLverui2ELvkui579fNy+2EF5Pg1/fyaOw4rYGy2tct6D20VcBNcMCrImzMG8fwJAzioH3jM9ke+PQqKQi0vfhWGPE3z4ht0gP9dXMOoh1ewz99X8Y8VCeJq+6n535VSHm54bzNvr08v81aZcDnz5XXEjATxQoiOoyrLt99etaWTeyJ6KjkqCSFEOxnXYf8ci6U/LKEy4dLPrwlio7+Teusoizs+rmi2Vne9bXhhZR3njey41GQhOlIjE7PWAAAgAElEQVTQTXDhmCAzRw1HAWFto5zMLJuXnlaStrOvg8fY/HJiHs+tqKMmmb6YsH9+gL1zfbhuHMuymLemgd98VAFAg+1wyfwyJhQNY2RQ7bIAXr2reGtd82kEroGVNSkOyN7144UQojVMv7ztt+fkdnJPRE8lQbwQQuwGyzhEcIj4gB2c3yugn79l4lP2dtqE6E5UN6vZYIyhwGPz+TnDWVgWp3/AYmw/L1kmgQFSaJ78prbF414ujfGfe4Ww7Z3PbQ9pw6HFQVbVbMum0QqGR70Y03FV+YUQfVtyxiys5V80S6l3C4pJzpiV0e3W1dWxYsWK9PZcl7Vr17JkyRL69evH4MGDM7pt0bHkDFIIITJMuTZXHJhLlnfbT+6wqJdpg8IyCi9EW7kOERPnmAGag3Jcwm68aYTci8uhxS3XPp5YGGjVNACvsfn1wflMLEo/R9SneejoAYSULPEohOg4pqCYhivvIDX5SOw99ic1+chOKWr3ySefMGXKFKZMmUJDQwO33XYbU6ZM4de//nVGtys6nozECyFEhhljyLNSfH7ucF5ZFSPi00wZGCJCgo6dXSxE37G9oNxxHM4aE+X5FXUsWJee137eHlH27OfFdXe9VJsxhmyV4Jnji0iY9Dr0YdVyiowQQuwuU1BM4uIbOnWbhx12GFVVVZ26TZEZEsQLIURncB2ycTizJF1gy3EaJIAXIgPCbpzHjimiwVVYCgLKJWBav9a6MYYQSUKQniIj0+CFEEJ0MxLECyFEJ5L0eSEyKx2EJwg1rvQoQbgQQoheRoJ4IYQQohdSSlGPl6TRaAVZykZJWrgQQgjR40kQL4QQQvRCNfg5+5UNLFhXT45fc8/3ijii2ItvB2uwt5rlJWXSaeqSWSKEEEJ0PqlOL4QQQvQytvZy48LypuJuVQmXs19ZT71p/7V77fFRpYLc9GE1580rZ16ZS1z7O6rLQgghhGglGYkXQgghepl6V/HW1gC+kWtgeXWSg3JU05JsrZVQXioTmiOeXsW6uvRI/kur6rjviCLOGO7rmhF5bVFrPDhG4VWGiEq1ahm53aGUIo6XFBowRDthm0KI7skYg1Jq13cUYgfaeiz+NhmJF0II0SdorfvMCVdIGw77znrpCijJ9rXrpKHO1XxZmWgK4Bv9bnEl1Y61O11tF1tZLNxiOOAfpQx7YDknvbCeCteX0c9XKUWtCnDhm5sZPHs5U55aw+Jqhas7//ULIbpWIBCgvr5+13cUYgeMMVRVVREOh9v1eBmJF0II0au52qLOePloY5zBES/FQU2oDUuO9UReY3Pr5Hy+qkyxqKyBiE/zx6mFhJXT5mrtWms+LUsQ9rUMVqM+3SWjAQ14mT53BXEn/WI+2hTnJ/M3MntaPgGSGdlmUnm45p1NzF1RB8CK6hTHPLuGpT8sIYLUBhCiL/H7/di2TXV1dVd3pc+pqakhGo12dTc6RCQSweNpXzguQbwQQoheS2vNspjm0DkrSGwN+E4bFeH3h+URMpkJ9roDYwxRleCZ44tIGI2lIKxsLDfV5udyXZcx/Xx8XpHi0OIQb69Pjz5ZCn5zaAFZ2qazM8orEm5TAN/oX+vrSRlFIEPbbHA1r5TGmrfZhrJ6h0hwBw8SQvRa7R1BFbtn06ZNDB48uKu70eUkiBdCCNFr1RkP/7WgrCmAB5izrJb/npRPqJcfAdPrpScJQXr0fTfWS8/1wdq6JNeOz6UinsP6mM2MkRH6abtL5oT392v8lmr2uU4uCuJVJmPrwvuUYb/8AK+t3hbIawX5IQ+Ytl8cEUIIIdpL5sQLIUQP4movtfiwtbfPzO/eHY6BjfUtU50rEo68f20QMEnOHRViXK6PwwcGmbVHhAKdwLO7y9W1UxCbJ08YSP9AOsV/nzw/f55WRJDMBdNBUvzpe0UMi3oB8FuK/z20kK8qEiirl18REkII0a3IUUcIIXoApRR1KsBtH27h1dUxJhUFuHVyPjk6KdWxdyJquVy4VzbXvLO5qS0/aDE0y4PpogC0p/K6KbyNQbKdsQHvVvEYm0PzPXx61jBSrsGvIaKSuG5me1XZYPOHw4vI8VtoBY98Vc3szyt59eSBRDK6ZSGEEGIbCeKFEKIHaMDLj98o44WV6aJaSyuTLClP8uL3iwnTu4u07Q7j2Jw3NkLYq3noy2pGRL3cenA+EZVkN1Z2Ed2Acm0i2Omy+ya9hF4mGWMIeTUnPVHarP2IweGMpvELIYQQ39WjgvilS5fy6quvUlpaSlVVFeeffz6HHHJI0+3GGObOncuCBQuor69n+PDhnHXWWQwcOLALey2EELsviebFrQF8o8Wb4yRcCEtW+E4F3QTnjfQzY/gA/NrgNUlMpiM+0Svl+hU/GBnhyW9qAQh7Fb+dUkBI2Rm/iCCEEEI06lFz4hOJBMXFxcycOROfz9fi9pdffplXX32VM888k+uvv55IJMLvfvc74vF4F/RWCCF2Tns8YHnRetc/xQpDXrD5El8BS+HREsG3hus4hEnicVPtWiddCICQSfCHKfl8ctYwXjp5EF+dW8KQgCNTWoQQQnSqHhXEjxs3jhkzZnDggQe2KEhkjGHevHkcd9xxHHjggQwcOJBZs2YRj8dZtGhRF/VYCCFa0lpTrQL86uNaLvlXBZ/VaBLKu9PHRJTDn6cV8e2Y/fZDC8iyDLXKT60KkNQtL26KvsOyLBztRVst13MXHSdkEpQEbA7JhYiJo1xZI14IIUTn6lHp9DtTXl5OdXU1e+65Z1Obz+dj9OjRLF++nKlTp3Zh74QQYpta/Ex8bBVl9enCav/4uoaXpw/mkDwLx9lBQODaTCn0sOL8EXxdmWREtpeQBa+siXPpWxupjDucPirKbw/LJ+hK9lFf06ADvLAyxtyVdUwbFOKM0VGCTkNXd6vXkmwOIYQQXanXBPHV1dUARKPRZu3RaJTKysodPm7ZsmUZ7ZfoWvL5ikxqz/7l9/spDQ5qCuAb/fqDLdw7KUDNxrU7fbxSiiKvl5pKB3vwaM58eX3Tbf9YWsPIbA/nFNVTU1nR5r6J7qW1+1d2QTG3fVnLA1/WAPD8ijreWBPjjgMDVJetyWQXW83v9xPMLwaPH+U6JCs3Equt6epu9WlyfBSZJPuXyKS+sH+NGjVqp7f3miC+0fbS7He2FvCu3iDRcy1btkw+X5Ex7d2/lFKUV7WcyRT0KHKyoxRGW/ecWmv+ub7lmtj/XF3PxXsXUZiX2+a+ie6jLftXjQrw8FfLm7U9vzLGHw4vYlQkkInutYlSinLXzykvrGVJeYKikIdHjy1m/+JidA9PRbcsi4TReJXBOD1nyUI5PopMkv1LZJLsX2k9ak78zmRnZwPbRuQb1dbWthidF0KIrmKMYUw/L3v03zZ/3aPh/03OJ6haH9C4rsteuf4W7ZOLggQtSfXtSxTgt5pfrLYUdJeah/V4mfX6BpaUp5dCLKu3OXnuWmJm53Uguru49vPiOpvz3ijn9iV11OkAWmuU1tQpPxUmQJ3yt6pwpRBCCNEWvebIkpeXR3Z2Nl988UVTWyqVYtmyZYwYMaILeyaEEM1lmQSvnzKYR44ZwG0H5/PFuSWUhEybK1zn+eDmiXl4tv6SH1gQ4OqD+qN70Iig2H0hZXPDhLxmbf+5X38CbbgolEkOmnfX1zdrq0u51KYyd7FJKUVc+ahTGQqktYcHv6pl5j/X8+LKOm59fwtHPbOGWnwsb7A49Mk1lDy4nMOeXMOKBo8E8kIIITpUj0qnj8fjbNq0CUiPZlVUVLB69WrC4TC5ubkcccQRvPTSSwwYMIDCwkJefPFF/H4/EydO7OKeCyHENsYYwibOyYO9KOXDthPQjngmYJL8ZK8sZu2VTco1BHT6AoGMw/ctlmtzwdgsjhwSZt6aGIcOCDIy6sHnJrq6awBYuEwsCvH2twL5sFcR8ap27fe7opSiVgW4ZH4ZL6yoY3i2lwePKmbvbNVh6fu1rsXvFzevt/NlRZLKpOG0F9exqiY91WVlTYoZL65lwamDyaJ7fB5CCCF6vh4VxJeWlnLHHXc0/f3888/z/PPPM3nyZGbNmsWxxx5LKpXi73//O7FYjJKSEi677DICga6fEyi6v8baCVJ1WHSWHVaibwOfSeEjlc6pNhmJiUQ352gvtgslYdhzzxCO42BM9wkYw8rmgaOKOHnuOr6oSJAXtHj0mGJCtKzp0BFSysM172xi7oo6AFZUpzjm2dUs/WEJETomiFdAlrfl6LpXq6YAvtGK6hRJV6UfJIQQQnSAHhXEjxkzhnvvvXeHtyulOOmkkzjppJM6sVeip1NKEVM+1sVcqpMOY/v5iZDEtDG1WQghOpNSijoV4OaF5cxbG2NSUZDbDsmnn3K71cVI13Up9KR4bfpAEm460I2oFGSoqF2Dq3mlNNa8zTaU1TtEgh2zjahlc/uh+ZzywrqmC2cnlWQR9CiKszysqd02pWV41ItPyxU2IYQQHadHBfFCZEJM+Zn58gYWrEuneuYFLd4/Yxi5OtGtToSFEOLbGvBywWsbeHV1OmBdUZ3iy4okL3y/mHA3S912XZcwCcJbM0YyGdB6lWG//ACvrd4WyGsFBSELTMeM/ruOw8EFXj4/t4RXSuvYK9fP3v29hEnw7ImDOOWFdayuTTE06uXpEwcRVSlcOZwIIYToIBLEiz5NKcWXlammAB6gvMHh1x+U85tJ/dAddMInhBAdLYluCuAbfbI5TtxV6WC5jwqS4k/fK+ToZ9awqiaF31L8fmohwQ5KpW/kMymKPXDh6ADGGFw3XY9iZAjePW0wSRd8GiIq1eailUIIIcTOSBAv+jStNWtqWwbqK2tsUgZaLuAlhBDdgwLygxabG7YFpyGPwqvpkanbKe0lbiwAsrSNaucqC8YYijwp3v7BYOptCHgUIWXjcTNzUfa7tS2M66aL2DXWqWjnZyF1WoQQQuyIrHki+jTHcZg6KITvO2ss/3hcNiEtIydCiO4rolL85YgiGn++FPC7qYWEVM9bYjBuBfjl+1WUPLicvR5ZySPfxIkrX7ufz3VdskyCAitB1MTxuD3nPVFKEdMBPq+zWFyjiW1df14IIYRoJCPxos+LqhTvnj6Uq97eTGXc4ef79WPKgACO073mlAohRDOuw2EFHlacP4JvqpMMj/rI0k7GRpwzxbIsnl0R48+fVQGQSrpc+uZGDi0eTklA9bmR6Drl59jn1vJZefoYNCTi5Z3ThhKhoYt7JoQQoruQIF70eZZxGB0y/P2oAmwDUcvBlQBeCNEDeI1NNjYH5SiMiffINPq40Ty3dTm4b5u/NsbI0YEOWYqxp7AsizdW1zcF8ACra1Pc/3kVv9gnjGP3nIwCIYQQmSP5WUKQTr0MmCRZJHH70AmjaL9o/gBqVIBqAsSVt6u706G01tTip04FSCpv09xc0X11xmi1UooG5aNOBahTfizL6pDn9SvDlOKWa79NLAx2aUE4ZXmow4utO+87oJRieXXLTIplVUlc07o+JJSXagJUEqBe+eT7K4QQvZAE8UII0UYN2s8flytKHlzO8AeXc+W7FTToQFd3q0M4yuLjKsXhT69h2IPLufRfW6hTUuKxr1NKUWn8nPnqRgbNXs5Rz65laUyD3v1A3nVsztszm2mDQkB6Obif79ePkojVZan0DVaAu7+o54QXNnDp2xWUu/5OmZfuOA5njI6ivxN3X7JPP5TZ9QXmeuXnpg+qGPbAcoY/sJzzXt9ETL6/QgjR60g6vRBCtIHWmiVbUty9pKqp7W9f1XDUkDCnDPH2+NTfGF6OeXYFCScdPD2+rJb+QQ+3js/G6mFzrUXHaVyT/s216eU4v6xIcsyza/jkzGFEOmDptrAb55GjC4m7GktBQDn4TddMa3ItD3d+XMkdH1cA8OnmBP9aV8/C04eSRTyj2zbGkOd1eGPGEG54r5yE43Lt+FxGRdQusxK01nxdZTfVFgB4bXWMx5bWctGYvjUtQQghejsZiRdCiDbQWjNvTaxF+8ulMYzq2T+pSilW1aSaAvhGL66sI+ZKSm5vElc+KkyA1cl0evyuRpltpZsC+EblDQ4xu2NGyo0xhEyS/ipONnH8pusuGMVci4e+rG7WtrbOpjKRudR+pRSWZaGUwmtsDsgxzDmmgGePH8BRRVar3g+tNQs3tCx+99b6BpKmZ/82CSGEaE5+1YUQog1c1+XoIeEW7ScOz0KZnr0soTGGgVkt5/fvm+/Hr3pgxTSxXQ3Kx20fp5dz2+fRlYx/vJRN9s7nfStjGJfXPC075FGEPL3v4o42hgHhlomKYW9mTpniysuqhJfZy+L8u9aiXvlxXZcgKcIkWz2C7jgOR27nt+mUkix8qmf/NgkhhGhOgnghhGgD13XZq5+XKw/oh89SWAou2iuH7w0M9op01SztcPuhBXi2Hh2GRb387rACAkhV7N6iMqX4/eLKpr83xGyufHszCbXjGXYRleKRY4opCqXvE/YqHjmmmHAPXJN+V6KWw92HF/LtmP2ScTmEdAYCYe3h+dI4+z66kv98axOHzCnlVx9WkmhHsUxjDINDirumFBD1aXyW4tJ9+3HMkFCv+G0SQgixjcyJF0KINgqaBBcOsfn5fiUY0vN3fW775soqpUgqD3FXEdImo/POlVI04CFldrwtv0lx/ugQZ4weQYNtCHsgqlK4rozE9wZKKVbXJlu0f1WZIOkqfDt4nOu6DPXbfDhzCDF76yi8srHcrgniLY8HgwLX6fAK9o7jsGe2h2/OH8GnmxMMi3rJ90PAtHzfdled8XDNO2ubtd3zWSVXHdQfP23/LQiYJOeNDvKDkcMxQFA5eNr52ySEEKL7kiBeCCHaoaZ8I4X9ouk/2hnfaq2pcH1c8/YmPtgY5+ihWdwwPpcsE+/wqtxKa8pSXi59cyNfViY4uSTCdeNzCTkt59B6TQovKaIWYKA7xO+Nqd5dVa28tzDGsGf/AH5LNat9cPqoKBHLZWcF0I1xySJB1tb9oivWpNdaU4Of+z+r4puqFD8el8PIiEWgg+fQe1ybbGwOL9C4bjKjr7Uu1fwihGvAcYF2zlRQjk1WY+aMfF2EEKJXkiBeCCG6SI3xcvxza/miIl2F+54llayvS/HXw/Px07GjfrXGx9QnSymrT5/c3/1pJfW2y28m9cPTjavOK6WIKR9rYy6xlMuobC9RlezS9cN7ujAp5p86hJ/M38jauhTnjs3m4r2zMU73H7Gtxcchc0oprUnvs3/7qppnvz+IIwqtjKSMZ3o/CyiHi/bO4U+fbpvecGhxkIA2EoALIYTYIQnihRCii8QdmgL4RnNX1pE8vJCOXtm5JmWaAvhGTyyt5ZaJeUTakbbbWWLKz4wX17OwLJ0xUBTysPCMoeRkeKmv3swyDuOiFi9+fwCuUYS1i+4BKddKKb6pTjUF8I1+/cEWxh9XRLgDlrrrbB43xQ3j+zMu188zy2s5ZECQC/fOIezGJYYXQgixQxLECyFEF/FZCp+lSH4rrTldOKzjT9/DXoVWzVPjh2d70XTfEW2tNYvLE00BPEBZvc1vP67gv8dng9N9Lz50d47jbAt6M7QLJJSXBBbGNK77vvufl1e3zDH3atA9OOQNOnHOLvExY1g+fm0wTkOzVyNTSYQQQnyXVKcXQohOopQiobzU4MPRXkLY3H5oftPtHg1/PaKI7AxU/A7gcMukvKa/Qx7FX48oIqq77+ilUoqV1S0Dv+U1KVISz3RrDdrPjR9UMeyB5Qx/cDlXvldBgw7s1nMaYxga8bB37rY8Fa3g1sn5hLvxftwajuPgMymM0/y7X6/8fNPg4d0tUKsCoK0u6qEQQojuREbihRCiE2it2ez4uHzBRj4tT3D8sCyuH9+fM0eEOHF4CatqUozM8RHGxs1AxW+/SXHRHlmcNSZKWcxhSMRDGLtbLz3lOA7HDsvCozdif2u0+JJxOfhxunEOQd+mtebDTUn+8llVU9vDX9Zw3NAsThzk2a19LsskeGX6IF5fU8/y6iQzR0fJ97q4bvfdj9urXvv5jzc28cLKOgAiPs3C04cyyOfKqLwQQvRxEsQLIUQnqDFejnpmNSu2jiz/35JKtjTY/HFKHrkqQV6OwpjMzksOmBQBBXkRhTE9Y33vbG3zrx8M5Zp3N1OTcPnFAf05KN+brhguuiXLsnhtTXWL9pdXxzhpSL/dCuKNMYRNnBlDvCjlw3FSvTKgVUqxod5tCuABapMu17y7mfsOz2vX8nNCCCF6D0mnF0KITlBv0xTAN3rym1qSJv0z3JmBSE8KejzGZq+Iy+NHFzL3xAGcPNhDQAL4bs1xHI4fltWi/eThWR1W7d1xHGzbbvW+3DivvKdQSrGxvuWFtrW1NrbpWa9FCCFEx5MgXgghOkHAo/B85xd3SMSLrCO1a67rEjBJskh26/R/kea6LvvmernywP74LIVXw6X79mNykb/TP7+48rLZ9fNhlaJaBXB0z0hAdF2Xcbl+srzNfzT+Y1wOEUu+A0II0df1jKOZEEL0cEEcbju4gCvf3gSkK9Pfd+QAsrWNxKWitwm6Ca7eL8ql+/ZL/60cvG5iF4/qWEnl5d4v6/jle+VAuor9y9OHML6fzvj679+mtcay0uvYt2W7EZVi0RlDuertzayL2Vy0dzanDA/hOp37PgohhOh+JIgXQohO4DUpzh0dYsbIEaytTTE820tIpXrFyLLSmhrjJemCT0NUpTCdGCSJzqeUwlYeDOBj+8Gpx00RbZy73QUJJw1Y3LywvOnvlAv/MW8Db506mCw6JxBu0H4+2pzkhZVVHDM0zKTCAEG3lbUvXIdBPpfZ0/KwjSJiORLACyGEACSIF0KITpMuLJciL3trEbtekEmvtGZ5g8XJc1ezptZmYJaHZ08cxOgwEsj3UrbyUNqg+NX7WwC4fkIuQ4MaTzcrlhi3Dc53vmOra1PA7s0pt7WXemNhDPiVS5DtF9dLaS//81Elv19cCcCfP6vior1y+NWkfvhaWdfBGIOfFH6gFxbgF0II0U4yJ14IITpZJgrLaa3RHi+W1bnrSNcaLzNeWMea2nQAt67OZvoLa6kx3k7th+ic4m1KKTalLCY8toqnl9fy9PJaJjy2ik0pq9sVjwt7YHi0+X44c3QUv2p/NNygfNz97zpGPrSCoQ8s56L5m4kp/3bvGzcW/7ekslnb7C+qiLty6iWEEGL3yJFECLFblFK42ktcdX4AKdIatJ83Nxku+Vclj6xI0GAFdhhQaa2pVz5q8WM6oMhXyihW1TSvur+uziYpg/CdxlUWtSrAx9WajY6fBuXL2LY8Hg/3f17VbITbMXDvv6vweLpXcl9UpZg3Ywg/GBlhZI6Py/fvz/8eko/Xbd/ybEop1tYbbl5UTnLrGzB3ZR0Pf1mDtlq+9u1dqjM7aBdCCCHaonsdcYUQ3YayPNS4FgpFQDl4tnPiq7Vmi+vjV4vKWV6dYtZeORw1KECgkwtY9WWu5eEv/65pmvv76FfVPPVNHQ8fWUCI5im7rvawNKa49M0y1talOG+PbC7dJ6f1c3S3w6sMI3N8fFO1bVtDIl78GolWOoHWmqUxzdQnV9Bgp9/wyw/oz1X7ZRMwHb8UnzGGgmDLi3UFQavbLV3oui65OsH/Tc0l4SrClot22r+va61ZWNbQon3e2nouGBvmu+PxQeVw8bh+/PHTbaPxF+yZQ0A58t0QQgixW2QkXgjRQlJ5eWldioMeK2X4g8u5ZmElDTrQ4n41+Jj8eCn3fV7N/LX1nPvKep5cHtvuqJTIjHrXw50fVzRre311jIbtpOzWGQ9T5pSyqKyBdXU2v/5gC/d/UYPajc8rqlI8c+JARuakR39Lsr089/1BRFT7RjtF29QaDz+ZX9YUwAP89uMK6jOUsm3bNmeNzWZAeNs+UxTycM7YbGy7e82Jh/RFB5+bIkIS7exe/1zX5ZABwRbtxw4NE9QtU0+8borrDurHcycO5KK9c3jyhIH8v0m5+E3Hfze0ltM5IYToS+RMWwjRjGVZVCYtzvzn+qa2+z6vZnQ/HxePDeFuPRFWSrGqxqasvvmJ8d2fVjJ9+ECyvvO8Sim01r2iGnt349lO5rz+TptSii8qEsS/U+nr71/XcP7YrBafV2u5rstQv82bMwZhG4VHGaIqlfElvJRS3W7ktyu4RlFa0zIorEm69N/+VO3dlk2CD2YO5Z31DRjg0OIQURK4vfzjMMZQHFT85tACbl64mbhj+MHICGeNieDuYIQ/6Cb4XqHmyOIcXNfF2Y1MgO1JKC+1jubLLUn26O8not2MXCQQQgjRvUgQL4Ro4iiLVQ0WC9bWtbjtuRV1nDsqTOM4lDGGqK/l6E//gIWlaJYuWq/8LK+xWVKeYNrgMP29cqLZUcLK5qZJefzXW5ua2k4dGSGgXDBgtIc6k/6pH5TVMsoa3c+LTxvYjZjbdd1tS3YZMhrMNSgftY5ic73DkIgnPeLfh8t2h7TL2WOyuWvxtmyMgpBFXkDvPGVbW9QaD7ZR+JQh0oYLL+nPO85xxdbWvxt2Z/fpVFprlFLtvpgYMEl+NCbImaNLMIAfF/8uAnPXdTNyUcvVHuaWxrnw9bKmttlHDmD6UB/a7X5ZEUIIITqOBPFCiCYxvJzwbCn3H13c4raJhUECloFvnfvm+RXHDA3/f/buPLDOqkz8+Pec9737vdmaJmnSvdCytIUCpVBWQQqyy7AviusIjo7ghriMoz91VNSZ0WFUVAZFdlEB2ZF9k7W0FEqhpVvaZt/v9r7n/P64Tdo0aZu0We5Nns9/OW2Sk3vf973nOec5z+GhtZ0ABDT85JgKYsrrCeRSKshXn2vgD2+39XzfXafVsGSSg5FV+b2mjMeFs2IcXjmNv7zXzpGTIj1nUadVgEc2ZPjcE+tpThvuPn0y/zyvhF8tawFywd6PjqogZDMFsUU3qYJ875UWfrF1j3FxSOOY5sYAACAASURBVPPMedOYFrLDvvKfrxyT5auHlhJxFXe+286c0iA/PaaChMqws0QFox1ea4aLH1zLli6fgyaGuPu0yZTr9KCyGwrpNVdK0aFCPFObZHOXxxkzEhTrLI4d/DPIMR4JRj9I7rAuX3hyfa+2Lzy1hZMunZEX/RNCCDF8JIgXIk/kVkwdLIoQ/oivVCuleKspw8ZOj9WtGf7loFKuf6MZY2HBxDBXH1KG8nsXdYraNDeeWMm7bR5r2rIcUx2l2PF6De67jO4VwAN86ek6njl3CnEKL4h3HAcfTSJRNNpd6RG2GQ6MK+Yfkti66pdbGewwDpc9VNsToF/4wEbuOWMyXzpkAi1pn0lRJxfsFUgedJunegJ4gNa04fNPbOHWJZWEGfoiboUiYlJ85eA4V84rIqgsYXb9nnbaAGfdu4aObO4+XVqf5uOPbuK2JZVExujr2KFCnHj3et5uzv19X36mnpcunM70kCnYbRnG0vMedmvLmDG/rUEIIYQUthMiL6RVgHvWZ5j/x/eZfuN7XPlUI11O3wJKw8lay5RE7kzlzz+xmbKwwzPnT+fli2Zwz5k1JGz/KaNRm+agIsM5UwOUqRTODmmc2X5GlC1pvyBWfneU1GH+ut7jk0828nBnKUmnb7G/0WKtxfO2TaBorVnRlO71Omd8yxefriOiDftGssRtClsgq6lKKeqTfSd91rRlyRbixTTElO+RIEPIZncblHZkbZ/g77naLvwxOiTQWrOsMdMTwEPuXvj2Cw1kVOGuZQSV4diaaK+24ydHCarCuKeFEELsubH5iS3EAGRUgDYVptGG6FShfs/VdhyHQCAw7JV/W33NRx/eRHM6t4ryp3fbuf6NZhiCc7wHozRguergUjwD33mxgX+6bwMlQUWR3XWarbV2p3tM4y7MndC7wtZn55cS04W1Cu/pAD94uYlLH6rlrlXtfP6pej712JZhPZN7bxhj2K+0b9+OnhQhogsv6rXWMj3h9qnDcPGcIuKOBC2DEQ8oYoHez7sjJkVxCmZn++B1Zvv+bYW+ah0jyy2nVPOZeSUcUBbiyvml3HxyNVGk3ogQQox1hTsFLcReSKog1y9v4wcvN+IZOKwyzF9On0zcbksXT+owz29K8cDaNk6bHmNRZYjIMJx/rrXmtc19V7kfXNvJFQcmiA35b9y5iM1wzSElfH5BGR0ZQ2lIU6QymL0Y6cbJ8ODZk/n50mZerUtz4ewEp06L7dV5zaMhaR1+ubylV9t9azpIHV/JyOZMDFyRY/jF8ZV8+Zk6kp7liEkRvrFoAs5enAs/muIqyzPnTePzT27h/bYsF88p4nMHlaAK7FoabVGy3H36ZC55sJaGpM8BZSFu/GAVMZUt6KB2Z4wxHF4VoSzs0JTaNnn41cPKiCh/SP5mpRQpAmTRwMic0GCtJW6TfO/wEpKmlIi2OCZZkFlOQgghBkeCeDHuKKWoT8N3/9HY0/bylhQ/ebWJbx2SQBmPtArwzRca+c2buaDthuUtfO6gUr51WDEBM7SrHMaYPivVAEd1r5iO8OJYyGYIAaVBhqTSeG6gmeLagxOkTBFRPfTHLI2UoFZktjuiTav8TmcK2SwXzgxz5syZ+BZCyhCz6cId5Buf6WHLbUsqyVhIOEYC+D3gWJ9FZQ6vXTSNrIGQZlDV6QtRkU3zykXT+emrTdR2evzrwWXMKVKYIXieK6VoV2H++e+buX9NB7NKgtx00iT2Tyj0HhTOGyzHZHNHRI7dt08IIcQO8nn8KcSwUEqxrKHvivpzm5IkTS7FNI3D71b0XnX95bJmktYZlj5NCML3F08k6OR+/xGTInzl0Alj6pgg63uEbLZgz4mPaY+vHz6hV9un5pYQVvn997jWo8imKCVF1GYKtohXN2MMYZuhiAzKHzv3x4gzPgmbpkylidn0mA7gAaw1lJLiuwuLueH4CRxcPHTHXKaVy5ee3sLf1nRggXdbMiz5yzo6CQzJzxdCCCF2JCvxYtwxxrCwqm9BstNnxIg5lu6Fk7475IdP2Gb41P5RLt1v+xXTVOGumI5B2ve4fE6c42uiPLi2k8WVQeaVhwnZod9iIYQYJn4u4X0opyzSRvccs9mtM2tpSPkk+iZZCSGEEHtNVuLFuFTiGP54cjXlEQdXw2X7FfHJA4uxW1f2wsrwiQNLen3PFfNKiQzjqmvAjK0V07EoYjMcEPf58vwYkzrXE5UAXohxz1WWgyb2nhh2FEwID0/mlhBCCCEr8WJcCtosp00OcOxF01AogsonuN3e2qDJ8O+LyvjQ9BgPre3ktOlxDqsIEhiGwnaisHQf5ZZOy7UgxgbHcWj3NQENQevJBOIgxZTHr06o4oN/Xsf6do+Qo/jF8ZVEkO0eQgghhocE8WL8Mh6J7kFWP2PWiElzYqVmSXUJvu9jhiCA11rTZgNkDbgaipSHNfm9p1qIfmmHdhsg7VvCDiNSjVsMvZQO8ej6FL94o5mqqMP3jpxITciH8f5c0g7t1iVrFEG962rzxhgmBbI8f95UujwIu4ooHq6VIF4IIcTwkCBejBhfu3RZt6AG/caYQfXR14Gtxe8sMe33KryltaY2G+CsezewsjlDVdTljlNrmFfsoMb7gFkUFKscXm2G8+9/n8aUz/SiAH87czJTQl7e39NiG8dxeGx9iksfqu1pe2RdJ29dNpMixvEzSTssb1Ocd/86NnV6zC4N8tfTJ1MT3HUgHydNPPf4F0IIIYaV7IkXI8JTLg9vzLL/H9awz02rOfHPG6jzAig1kuXjBk5rjesObo4rqUNc90Y7s3+/mgP/+D7/906SlAr2/Hu7dbnkwVpWNmcA2Nzlcea96+mw47eCsdaatArQSRDHkf2jhaKDAOf8bQONW8/cfr8ty8UP1dI+jq/lQtTua65f1tyrrTNreWlLCq3H7/Cg3QY4894NbOrMTcK+05zhogdrabey7iGEECI/jN9PaTGiunC57OFaOrK5VYyVzRmufHwLyTw7gkcpRacO82Ct4fq3uqgzITy1+4Gb4zg8tznND15qpMuztKYNVz1Vx5pO0zNRYdC8Utf7TOuWtKHLG5/LNkY7vJd0uOyxej78wGbuWe+R0sHdf6MYdd3X+PaW1qcxI3qmg9hbAQ2TYn2fb5VRZ1zti1eOS7sK0a5CKMcl6VmaUr0zEV6vT+HLkEkIIUSekE8kMSIakj7eDlmIL21JkrH5NejvUEFOvWcD5z+wka88U8/+v1/Nqg52uypl0Nyxqr1P+32rO3pWmDWGQyt6VzAuDWmibn69BiOlzQQ44va1PLy2k39sTnLJQ7U8vyUrK/IFIOoqyiO936eFlWGcIT24Swy3oPX47hETSQS3Pd+OrYkys8gdN0F8SgW55b00i25fx6Lb1/HH99KEXU3ZDpXlF0yU61sIIUT+kCBejIiJEYew0ztY/cCUGCGVP4MipRTvt/ssrd9WwM63cO1z9XTtJo3SUZZjqiN92hdXR3r2UCaUxx9PqWa/0txq86SYyz1nTCGuskP4VxQGx3F4fEMXab93oHD9G810GXks5buEynLfmVOYXpTLpDloYohbTqkmrqSQVyGx1jIp6LHi0hn89fTJPHf+NG47pYqYzQz571KOSwdBUiqYN6n6WmtWtvlc8fhmajs9ajs9rnx8M40pj3vPmEz11iyFOaVBbv1QNQm5voUQQuQJ2eAlRkSULPedNZmPPryJjR0ex02O8p/HVhAmnVc1gFI7pguQSx02u+mk53mcMyvOX1d38Mi6TgAunlPEgvIQxuRS6I0xVAeyPPrhyWSMIqBtblA4DovaWWupifd9/ExNuAQUUhgq3xmf/eOWZ86dgmcVAWVJFEChStEP45PA5wOVGmt9rPGG/PZL6hC3vtPBDctbqIq6/PTYCqaHFcqO7rPPcRxuXdnSp/1Xy1q4bnEpL14wdUDV6ccLpRQdBOnyIaAVYWUID8OEjxBCiN2TIF6MCMf6LCx1eOG8qVilCGCIks6rlE1rLXNKQ1THXGo7t624fPXQMhKOj7+b8WbMprnpgxWkjUYpcgMc03sPfHcFY7oD1fz580eUMYa5ZWGOnBTh+U1JAMrCDtcuLMex+TWxI/pnu69lAMtuJ7pEfhuuANVxHP78XidXP1UHwFtNGRbfsZaVHxn9CvjGGA6vivDLZb0D+UVVEazvk7B+z7Narm9oV2HOuGcDr9XnPtc+cWAx3z1iAtEhOH5VCCHE4EgQL3bJdRy07+E7Lv7uotjdsFtXfLojtHwcExWR4YULpvGLpc2sbsty5fxSDih28P3drzZYa4mSIdq9ayAf/8A8ErNp/nTqJNa2+7RkfOZNCJEgg5XRshBjRpvv8LsVrb3akp7l1boUJ1TqUV3d9n2fU6ZGOa4mypMbu4BcTYCTp0bx/dRuvnt8UY7L/y5t7gngAX77ZisfO6CYeQmVVxPyQggxHkgQL3Yq5mdRzz0Er78Ahx6NPexYOp38qiY/1IwxFJHiG4ck8K3CsT7G9A3gtdZ0WZeMVcS0wTHjb1/73rLWErVpDogrlFIYk5J5DyHGmKC2TEsEeHlL76C4Jh7A2tHfYx6zaW49uYrOrXPUMSfXJs+i3lJG8Y8tfSc2ltanOag4tNeT/EIIIQZHgnjRr7CfRd3wH/D8Y7mGFx9HnXAG4cv+lZQe+5eN8TwU9FuLWCnNhkyAzz6+mZXNGc7ZJ8G1h5URNbJysyestbKKI8QYFbQeP1g8kcc3dPUc23bWzDg1UZ0X930ugypNtLvWnpUkqv5EteG8fRM9NV+6fWBKDN+XdHohhBhpYz8aE3vE9bPwwt97Nz5xP+5FV0JwfF827QQ57q73qU/mBqS/WNpMxrf8YFGJrMgLIcR2rLVUBrK8ccl03m3JUhZ2KA8polYCv3xitUuHdfEtBJUhRrbXJIvv+5wxPcaXDy3j+jeaKQ46/OSYCiYEjMx6CCHEKBjf0ZjYBQXaAX+7dEfXBTU+zzTfXlPa9ATw3e5c1cY3FpZRNEp9EmIouW7uo8HzRj/dWRS+XBHEFAuKFdb6EvTlmaxyeWKTx6cfW09z2nBUdYTbTqmmSPUuPhsxKa45uIh/PagUsCS0h/Vl4loIIUZDfhzWKvJO1g3CGRf3bjzncjKB0Oh0KI8UBzU7TmXMLA7iyMhU5CnluPg6gOM4u/5/StOmwvz8zS5+sLSDBhvG6F1/jxADlQ/p86KvTuty4QMbaU7nNpA9W5vkmmfryai+6zyOyRK3KeI2jZV98EIIMWpkJV70EXA01tGYsz+CPvw4ePNVmLcQf2I1mT7h6/gTVj7/tqicb7/YAEA8oPnViVUktMc4P0ZY5BmtNa02yK/eaGFZY4bL9y/iyMoQ4Z0cCdVKkINveb9n7/J1rzTxxiUzqHJNwQZg2nFp9XMTEUWOj/Ulu2AoaK1pswEMChdDXHnj/hz1QqSUYl1bFn+H2/up2i6SppyxXcpWCCEKlwTxooejFdGuDuz9t0FbC+qMi8lUT8efNgff9wt2ED/UQjbLZw6Mc9n+xdQnPSbHXWJkZQAr8k67DXLC3etZ1ZI7YeGv77Xzi+MruWyfcJ9g1nEc7nm3oyeAB0j7lp++1sSPjigBr/DSZlMqyP1rU3z7hQY8Y7l24QTOnRklbHd/ZKTYBe3wTqfmggfW815rlsMqw9z+oRomOplRfQ4qJUedDZa1lqmJAFrB9qd7Hl0dJaJN/9VdhRBCjDpJpxc9Iuku7Bcvgr/+AR6/F/vFiwnW1WJM4a7CDZewzTJBpdgv6hE3KZSRtEKRf+pTpieA7/aTV5to8/tPke/vLt9xha5QKKV4v9Pw8Uc2sa49S22nx788sYU3Wzy0lo++vdFuA3zor7kAHuDlLSkufrCWDjs66wJJFWJDNsiKDocOFZb3d5BiyuMPJ1dTFMy9bodXRfjhURMJ5sERgEIIIfonn3QCyK3Csexl6Gjb1mgt9u4bcSX9VIiCFHT6bn+JBTSqn3Dd933OnBmnJLTtYyGg4eoFZb0LXBYIx3G4c1V7n/bfv92G3k1tALFrXZ7tU9zzxc1J/J0NKRyXDoJkdQA1xMVRu1SITz9ex9yb13DkHWs57La1NPjBIf89Y1nAenyoxmX5pTNY87FZ/OXUKopJy+S9EELkMQniBbC14FCwn6J1gaBUpBeiQJUE4INToj1fK+BHR1dQ7PSfOVKsMrx+8Qy+cfgErlpQxvJLZ1IZ8ApyMG+t5ZCKcJ/2hRVhKMC/J59EXdWzatttXnkIbfvmXiedMD9/s5NT7qnls0810mBCQ7ZSrpRidbvHvWs6eto2d3l876UGvH6Ksomd08anyKYoJUXUZgrynhdCiPFEPuUEQG4f434HwcRJUL8p1xgIos7/FFmlZdArRAGKkeH3SybxekOaNxsznD4jzoSAj7+zlXVjKCHFNQfFUUrheYU7mPd9nw/URPjA5CiPb+gCYFFVhHNmxfG81Cj3rrDFlMddp9Vwwf25iuZTEi63nFLdp7in0QF+9EozP3utCYDljWme3ZTkxfOnEWfv3wOlFGva+tZqWNWSJWMgste/YXQ5jtOz9aXI8fGlGrwQQoitJIgXPbqCEaL/8X/wyjPQ0YpafBLJSKxgB/FCjHfWWqI2xdHlmmMrInheekBndI+V8+FjNs0tS6ro8HNFuxJurq37JdBao7XGGCOFKQdBG4+FpQ5vXDKDlG+JOJBQfYt7dhrN799q7fm6POLww6Mrafegk1Du/WDPJ4qMMRw9KUpAQ3a7X335AUXEHUMhx7xpFeCVep9vPL8Jz1i+eXg5x1QFpSijEEIIQIJ4sR1jDB1uCGfxkq2rcGNjIC/EeDdeg1RrLRHSRLqzt+22OYykDvFGY5YnNnRw8rQYc0qCRIwESAOlrE8Cn4Qm97r2E4drZamOuzRuPfHg9lMn82/P1/NMbS4zYvGkCHedWk3U7vmqfJHj8dS507jq6Toakz5Xzi/h1KlRfL//YxQLgVKKzWnFqX9d39N23v0befa8acwr0nl1LyulUErlVZ+EEGI8kD3xog/f9yWAF2IMSKsArSrMFj9Ehxq6vciFLqODfOcfTZz8l/X84OVGjv/TOq5f1oav5VTsoVSkfa7/QBVBR3F0dZQ3GlI9ATzAc5uS3L+2M1dYdQ85xuPAhOHuD1Xx9w/X8PHZEcKmcAN4yKXR3/J2a5/2G95sQen8KcrYpUO80aa5d6NPC2F8lT99E0KIsU5W4sWY0qVCtGYh5VsmTJ+N1qO/QuA4DtbaUe9HIVFK0UWAtNVolduD6xiZWBqMpArys6Wt/PiVJiwwszjA38+ZSqmSqtNJo/nV8pZebT9+pYlPzy0hQd891mLP+L7PAQmHVR+dSVPS54Y3+wam/9ic4qKZ4b3a722MIUoui8IWcAp9N2st+5X1LTR7QFmw35MlRkOXCnH5I1t4eF0nACFH8ez505gdlc86IYQYCWMqiL/nnnu49957e7UVFRXxk5/8ZJR6JEZSlw7xyce2cP/7uUHFjKIAT547laIhKKC0J6x2aLcBnljXRWnI4ZCKMHErAdRAdKgwlzxUyxMbuogHND89toKzpoUJWQmwANAu7dYBFGHlEzB9X5emLPzolaaer1e3Zvnm8/X87Kgy3Dx8HbXj0mUUYQ34w9s/S9/0b1/uy2HhWJ9ifMpiDhfPKeL6N5p7/fsl+xVJwbYd+L7PyVOjHDQxxNL6XFbB7NIgl8wpxvOSI9YPrTWO42CM6fMe1aVsTwAPkPYtX3q6jluXVBJBtqUIIcRwG1NBPEBVVRVf+tKXer6W9NHxQWvNW81eTwAPsKYty3++1sy3Di0a9qBgR0optmRdDr11DR1bKy4dUBbikQ9PJrYX+z/HA+O4/OClRp7YWlG8I2v49GOb+cBHZzJRbmfSKsAjGzJ84akNtKR9LplTzH8sLiditl1XWmtWt/a95l9vSJMyivhIdngAkk6YW1e28+fVHSyqCnPVwWXEbWrYJrzCynDevgnu2O4c+U/NLSWs/AEV/hOD5/s++ySC/PrEKr77jwasha8vLGdOkYORWgR9xGya+8+YzOakj28sNXGXBGm617h97dJlXTLGEtb9FxbcGykdZGWrz81vt7CwIszpM2K5opDWopSiJd134qUh6ePL/SOEECNizAXxWmuKi4tHuxtihCmleKe57z7IN5vSZCwER7g/vnb53ksNPQE8wIqmNK/WpTmuIr8KE+WbLl/3BPDbW9GY5gOV8tq1eJpLH6rt+fqmt1rZrzTIlQdEsVuPjjPGMG9CGFeDt93Ldc6sBHFtII9eQk8H+LcXGvn11vT2pzd28fj6Lu45vZoYw7O3OWwz/NdxFZwyLc4j6zs5c0ac42siBIxMsA2nsM1wwYwQH5o6FVRuz7z1JYDvj7WWGClmhXOfb9Z4PbdtVrk8uCHDZ/6+js6sZU5pkPvPmkK5HppML+W4/HVNkn9+bDMANwBHVEW4+9RJRMn9jn1KApRHHBqS24L5z84vpcjxMZJYIYQQw27MrWs1NDTw5S9/mWuuuYZf//rX1NfXj3aXxAjwfZ8Tp8bQqnf75fsXE1EjH7H4FhqSfX9vY8pHKdXPd4huUcfwgcnRPu0HTAiN+wBea82Lm/um096zpoNOv/d1FVceD5w1hX1KgkRdxT/PK+Ezc4thBGsLDORaT1mH/3ur917pV+pSJM3w3icRP8V50wP88tgyTp/s9spkEMPH+h4J0iRsumfSSezajoF5EpfLH95EZzbXvrI5w+ee2EJyiNZl2nyH//ePhl5tL2xO0rbd25Ugw4sXTOej+xdzbE2UP5xczYdnRjGyNUIIIUaEamlpGTPJT8uWLSOVSjFp0iTa2tr429/+xubNm/n3f/934vH+E0hXrVo1wr0UwyVeNpF1qoSvPNdAa9rwL/OL+fBkl6YNq0e8L5FIhNroZJb8dWNPWyygWHbRVJrWvC374ndBa82E6XP4+N/r+fuGLhJBzXVHlXNccZr2hk2j3b1R5boufuUsDrt9fa/2qw4u5ar9Q2TdIBYwqS466jYSiURxSibiuC5eRysdTfUjMhESKy4lPKGKFU0ZpiYChL1O2jZv6Pe6L526L0f+eTP1263oaQWrLp1G05q3hr2vYvTFi0sIlExEaQe/q52Ohs2yT34ntNZkK/bhiLs29Govjzg8d3YFrevf2+vfUTx5Jifd38jatt5bclZcMo3OtdvuSdd1iZWUYXQAkm20t7fv+KOEEELsoX333XeX/z6mgvgdpVIprr32Wk455RSWLFky2t0RI8BxHFp9B4uiq34jlRPLR60vaRVgeYvhulebKA9rvnF4OZUBj1HNNdQOHTZA0reEHUVcZVF5mPu4fXV6Z2t1ep1n1elXrVq12wfscEiqIP/9Rhs/eqUR38JhlWH+fPpkfrO8me+/1EjWwKnT4/zmxEqio7C67DgOS1sVJ9y9jszWDbJXLyjjKwuKCPdXUE+73Lch22uLwNULyvjqgqJxXchwtK6vkZZRLn/flOVfnthCY9LnrFlxrj9+dK7dQtGuwuxz02rS221AP3/fBP9z7IR+i1z2Z1fXl3Zc7nw/zSce3dzTdtSkCHd+aBJRW9jH94mRMV6eX2J0yPWVM+b2xG8vHA5TXV1NXV3daHdFjBDf94mTC0o3tzSPahAfslkWlmpuOrEcB3BtBmtGb85Mac3bHZoz7n2fui6f8ojDX06fzLwiB5tngby1lggZIrC1lPgodyiPRGyGqw5K8Jn5JXgGItqypcvj319s7Pk/97/fwR/ejnDF/lHMCKcstxmHKx6v7QngAX76WhOfO7iUcH/HtxmPk2qCrPzITJ6r7WLexDA1EU1IgoVxod04XPTA2p5b/C/vdbBvSZBrD06g8mziLl9EyXLfmZO5/JFNbOzw+MDkKD85poKgTQ/Jo9L4HqdNjfDc+dO4ZWUbh1WEWTI1mitsNwQ/XwghxN4b00F8Nptl8+bNzJkzZ7S7Mup85dBFgJaMoTioieLhWhkgDTdjDMGt5YhGe/DTZgOcd/966rpyAXtD0ufcv23kpQunkiC/gnixa0GTJUgWFDja4Y6NfVct/76hi4/NiY14UUdjFRva+wbrnVlDaaD/7wnZLJUOnDs9iDGebDcZJ7TWLN/SNzB8cG0n/zq/OO9OUcgXjvU5vMzhhfOmYpUigOkpODdUwjbDgXHFDxcVbz1iLjXqn2FCCCG2GVNB/J133sn8+fMpKyujvb2d++67j3Q6zeLFi0e7a6NKaYfXm+GMe1bT5VlCjuL2U2s4tsLNuxRlMXw8q1i3Q3C1ucsjYwCptVewjDEcW9O3EOCp0+NEtGGktxZHHcNl+xXz30u3nQdeE3cpCerdzmRZa3EcB9/3JZAfB4wx7FcW6tO+uCpCRNu8OkUh31jj5yZft94mw3G3WGvJZsfvlhYhhMhnYyqIb25u5oYbbqCjo4NEIsHMmTP52te+xoQJE0a7a6Oqzbpc+tA6urzcx3zat1z+cC3LLplBAgnix4uAsuxfFuStpm1HOs0oChDS9BoBWu3QaQO0Zi1FAUVEsjbymrWW6ojix8dU8O0X6kl6lotmF3H+PnF8fxT2xPtZvnZYGSVhh7tWtXNAWZD/OGoiRSrDrnaTdOkQr9ZneKWukzNmxKmO0P8eejGmFLuGHx9dwdefryfjWw6tCPONwyfgyJ54IYQQYqfGVBD/6U9/erS7kJeMVWzq7B2EtaQNGWNlBXYMUEphtYNB4Vp/p9XHi1SWu0+bzAUPbOSNhjQHTghx+4eqKVLZnuDKcRxWtGuW/GUNrWlD0FHc+MFJnFwTkEA+j4Vtho/PjnDhvjOxQAif0CgGQRGT4uq5MT51QIKwtgRtBrOLCD6pgnz2iTr+/F4HAP/2QgP/d9IkzpkWHPE9/YXCaJdO66KAqPbQBfo6hW2Wj82OcMHsmXjGEtKWOLL3WgghhNiVMRXERrYasgAAIABJREFUi/4FlOHwqgj/2O586f1Kg31WYEUB0g71foAfv9RIU8rn6gVlzIo7BPtZwTTGUBPM8sCZ1fhoNDYXwG8X9Lcal8se3kBrOteW8S2ffGwTKz8ykyLJ2shrjvHyK7PGeCQAzO4fM0mjewL4btc+V8+JU6bm19+UJ5I6xI1vtfODlxuxFr5yaBmfOrCIiCnMYoCu9XLPFwVY+VgSQgghdkePdgfE8IuR5Y4PVXPKtBixgOL4yVHuO3MyRUpSVQtdmw2w4JY1/GpZC3euaufIO9bybodF6/5vbWMMMZuhyKaI23SfVXuL4p3mTK+2pGdJejKsFsPH72f/e8q3kijUD601K5qzXPtcPe0ZQ0fW8K0XGljamN3pfS+EEEKIsUU+8ccBay2lKs1NJ1bw9mUzuHVJJROdzE7TrkVhcByHR9Z10p7p/T7+6JUmsjh79DOj2nLzydV8bWE5UxK5RJ2auEvMlXBKDJ+YAwsrw73arl5QRkzLqQk7chynT9YCwB3vtOM4e3bfj1VaazpUiEYbol2FQMvrI4QQYmyQdPpxwlpLiAzddYBlXbXwWWspCvYdlJaENGoPYu6UDvHY+hT/80YzFVGXm0+p4U+r2vjMvFISKsNAi4UrpdBaY4yRCuNiQGJk+Mvpk7llZSsvbklx0ewiFleFUH5hpocPJ2MMR1dH+MV21f8BjpsckYnZ7Wit2ZwNcMa9G1jZnKE84nDrKdUcWuagjUwOCSGEKGwSxAtRoIwxLJ4UZlZxgPdac1sjoq7ia4dNwDGZQU3UOI7D4xtSXPJQbU/bo+s6WHHZLEpV37T7nUmqEGs6fF6tS3H85CjlQSsVxsVuWWuJ2SSf2S/CJ/eL4WLwx2AA7zgOKasJKMDfs/vC932Oq45wzj5x7n43tyJ/+ow4J02JjsppBPmqw7p85JFNrNy6Pagh6fPh+zby1mUzckezCSGEEAVMgnghhplSCk+5WCDIzqvH74kEGZ46dypP1SZpTvmcOj1Osc5id3WWVz86fM3/vNHSq60za3l5S5KTqga26yalAnz3pSauX7bt5/zupEn807QgtkArZ4uR5fs+Cn9MhlgpHeKp2hQ3rmhj/9IgX1hQSonas21NEZPif46dyE+OqQQgrAwROZKtF4PmxU3JXm0dWUOnZ0lIVr0QQogCJ0G8EMPI0w4bUw7/7x8NpHzLtYdNYJ+4JjBEx7UZY4iR4vQaF62DGJPF9wcfArkaqmJ9R7YVEQdrBxZkpKzD/y7rPRHwlWfqWDJlGnGpMJ4XjOPS6Tu5kwkcf4+uFTF42nG5c1Unn3tyCwAPvA9/eq+d586dSow9C74jNkOk+wvZtdKHg2FxdYRna7cF8kVBTdxV8noJIYQoeFLYThQUrTVZFcDXAdSebPweYc2ey2G3ruHOVe3cu7qDxXesZUNKDWnflVK02QCPb/a4e22WVhXGDrKAU9B6fPeIiSSC2x4Jx9REmFXsDnhfu9/P0VC5onv5/z6NB0knzA9fa+fQ29dy6n21vN6i8LTM446EVl/zXzvsYV/blmVTl0yiDJeY8rhpSTXzy3OVYKpjLveeOZkYsr1HCCFE4ZMRnCgYGRXgnTbLD15uIOIqvnV4OTUhH8fm50DYdV1uW95GdruFbAv8fGkz/7m4FOsNzWCyQ4U4+S8bWN6Y20McCyheuWgGk9yBF5az1jIp6LHi0hm8UpdiYsRlRsIhZge+tz6iLYuqIry4edvK16fmlhBW/oivfDmui0VhfW9Yi+tp7dBmXUARxCfE8P6+PaUcl9+/1cYPX2kCoK7L54S71/Lu5bMoliyJYafJrQLvKCynPgwbYwwVToYHzqwhYxWushQpDztCRe26t1GljCLhGIxsKRJCCDGEZCVeFASlFGu74Og71/K3NR3ctaqdw257nxYTGO2u7ZS1lomRvivilVEXNURRrdaapQ3pngAecnvZv/NiA54a5Byd8UnYFCdUauYmfKI2PaiANEaGu0+r4VuLyjlpaoz/PaGSry8swzUjt/KltaZVhfn+6x3867PNvJt0yQz2dRigWGk5TzdYFt2xjqk3vseVTzfSoUK7/8ZR0OFrbnunvVdb1sDrdSk5W3wEFDk+Pz66Ar1dzL5kaoyyoATxw8kYQ8ymKSVFwqZHLIDXWtNoQnzh2SbOun8TN6xMknTCu/9GIYQQYoBkJV4UBKtd/vv13umoGd/yp3fbuHL/KJ6Xf6scvu9z+owEUxNNrGvPBbLlEYfPzCvB94amCJVSiqZU37+9MeXjW/botPg9LbzXXWH8i/NipOfGCSuDGeFq2W2EOOzWNdQnc4P1/1vRyjPnTWNekR7y47eCJRM58+a1+FvnOe5a1c7kmMu3DitC59mqW0hb9i8L8lp97/djenEQYzKj1Kvxw/d95pe4rPzITB5a28mc0iAHlgWJSjG6ManNBjn2rrVs6Mg9B17ekqIp5fOl+XGUya9ngxBCiMIkSzCiIGhlqYj2DUknRga+Z3s0FJHm+fOn8qfTarj1lGpev3g6JWrogibf9zm2Jko80PtW/uKCslwa+yiwvkfQZDEjXDRNa83zm5I9ATzksvi/91Ij6T2aztg5pRTvtGR6Avhu96/tpNPLv8dqwHp898iJ1MS3zdt+em4JFaE9XwlWSqHdAI5buHPBSikcxxmRbISA9Zio03x0nxCLysj7AF45LhkdQDtSyn2wGtOmJ4Dv9ts3W+kw8loKIYQYGoU7+hLjivE8PndQKTeuaKUplQvSZhYHWDI1hu8nd/Pdo6e7enz3MW3GpIZ8e3iRyvLKRdP53ksN1CcNVy8oZV6pgxnBNPYddQdGxpgRrYAecvoGpcF+2vaWtZaZxcE+7YdVhAk7FoZ20X+vWWuZ6GR48fxpNKUN8YAmog0Ru2dnsWeVy/qk4hdvNFMRcblifgklKoMd4myH4ZRWARqymvvXdDB3QpCDysMjEljn+4kASik6VJjfLG/hmdokZ86Mc+4+cSJyBv2AxfqpdVAZy50KIYQQQgwFCeJFwShVGZZeMp1nNiaJuorDKsMkSOdbvNSvoU7l7v3Dfapcw8+OKsO3EMYf1QA+qcM8XZvivjWtnDY9zrHV4RE5w9oYw6EVYaYXBXi/Lff3BzR8e1E5Ibwhv05UVys/PrqCa5+rI2tg/7Ig3188kaBN5+VQ3RhDnBTx7rmHPeyk1pr3OuDI29/v+RE3LG9h6SXTiW93XFpSBekymqRnKAlqivbwTPTh4DgOL2zxOOveDT1tp0yLceOJlXs8sTFWdBLgwgdqebq2C4BH1nWyrCHN9xaVEBjF50ohiTmWjx1QzI0rWoHcc+jnx1VuPdZxlDsnhBBiTJAgXhQMaw0Jm+K0mlxKojGpggjgR4K1FsfP4jA0i8BWu3QZTdQxqEHs787oIP/2YiO/Xp47L/73b7XyqQNL+N4RpQRHYO91ggzPnjeNv73fweZOjwvnFFHm+MMSPLbV1XL5nP25YPYsMr4l4kBCZTAmH0P4bazj0ulrwtoSsIOvpp/B4XsvNfSaA2hM+Ty9MclpNQ7GGLpUiGuea+D3b7cBML0owBP/NJWSPTwTfai1+g5ffWZzr7YH13bS5kE/tSjHlZTRPQF8txtXtPDNwycQGMbj2dIqQBoHRe54OF3Ae8cjNsP3jijj8weXsro1y6EVYeLKw8+zWhlCCCEKV/5t3hRiN4wxebOiN9YopejUEb7zajtn/m0TP3y9nS4dHvC59imr+e2bLb3afreihZQdmUeNMYaYSXLRjCBXz4tRodO4dvgGzgHjUWRTlOs0MZvO++uyS4f58dIOTr6nls8/00STDe3RfvDwLrYtKKXY0GV6AniA99uy/OClRoze9WkSRju0qzB1JkSHCqGGaa+6RdHp9X2vMnk+ATMSHEWvKvrA1pobw/faJJ0In3+6kek3vscBN6/httVpUip/Tx4ZiKjNMDPscVKVpoTUsD6HhBBCjD8SxAshenQS4IIHavnZa028UpfiP15u4jOPbyHJwAfUO8b7A4z/h5Tv+3l5YsFo8nSAb77QwPdfauTNxjS3rGzjg3evo80OLlgKWI9vHl7O9rUUpyYCHFEVxhiDUoqVzX1T0pc3pUmbnV8MRju80GA54OY1zL5pNYfdto41SXdYis4VOT5XHVzWq22/0iBl/ZzlPt6Elc/nDirt1fYfR1WQGKZCmcpx+b8Vrdy+qh1joT1juPLxzTRk1IAnD/OVtTbvJ/aEEEIUJkmnF0L0SFvNMzuk0t67uoPM8ZUM5JRjRyk+eWApv1y27TjATx5YQkAxnAt5YgBS1uGP262OA7zXmqXTg/ggUsittdSEfN76yCxuXdlKRcTltBnxnvoUxhgWT4riKHpV779odhHxXewJ7rQBLnhgDe2ZXNCzucvjogc38sjZk4kztPvUre9x0ew404oC/P7tNg4qD/HpuSW5v2GcX6chm+Wrh5Rw0ZwiXtqS4riaKBUhC8O0Hz5pFA+s7ezT/sLmJNOmB/O+EKAQQggxGiSIF3lFOy6tvsZREFeerGKMMEflUqVT20VfRSHNQNfDurKG46dEWVwd4flNSY6cFCHoqD5HsYlRYC3VcZfVrduCMa0g7KpBT7A41qdc+Vw1N4a1Ft9P9qrFUKw9Hjp7Cp9/so6GlMen5pbwT/vE8XdR4Tzp2Z4AvttbTRnsgK++wYmYNEsmORxfNYGAspgd/obxLGoz7B9THLhPCGOyw3qMZ1hbjq2J8tTG3pOHh1aEMQW8L14IIYQYTnsUxNfV1bFs2TIaGxsBmDBhAvPmzaOiomJIOyfGl5QOcde7nfx8aTNlYYfrjqlgTlzLXsIRFFU+/2/xRL70dF1P20+PqSSuvAEFeiFXcflDtcwqCXLghBA/fLmRjG95/JzJw9jr4aOUGtYAZiQVOx6/PKGKU/+6nu7t4F89dAJh9nylc2dbFlzrsWiCw8NnVWNRxLWP2s0RZVEXqqIum7u2/cwjJ0VwhjG09n0fB1+C937kJmdGYBXc97hiXgnP1Xbx9w1dBDRcu7AcRyuabIi48gjIZ4AQQgjRy6CD+DvuuIPHHnusz8D2jjvu4MQTT+T8888fss6J8cNxHB5dn+JfntjS03bcXWt55yOzKFMygBsprsly6b5RTp0+k+UNKQ6aGKbENagBptJGyQWKn3xsE282pkkENQ+dPYUilS2sNGXt0EGAt5oyTIwEqAgrogV+9Jjv+ywodXn3o7NY3phmZnGQsoAlZIfn1ADf94l3TxAMIEpOqCwPnD2Fix/cyFtNGY6cFOGPJ1cTV5nCunbEoMVtipuXVJKymqRn+e2bLRz8xzUA3HlqDR+c5GAlrV4IIYToMagg/pFHHuHRRx9lwYIFLFmyhOrqagBqa2t5+OGHefTRRykrK+ODH/zgsHRWjF2dRvO7rWfqdvMMPLmhk3NlX+SICtss1S5MrnYwJj2oVGvXepw2Jcjqy2fRkjaUhjQxsgW1LUIpxaasy6Lb19CazvX7jBlxfvWBioIP5APWowSPY8oV1g7uvR1u1hhmRTweOXsyFoWDyQXwBXTtiD1jrSVKBk+FWXDLGjLb7b+54vHNvHLhNBJ7kTEihBBCjDWDKsX79NNPM3fuXK644gpmzZpFJBIhEokwa9YsrrjiCubOncuTTz45XH0VY1hQw77FfatkzywOyiB+lOzp6x6wuWPXpgYzJGwKbQtr8J1WLtc8W9cTwAPcu6aD2qQp+GrZ3fJ1i4AxhrhNk7ApolYC+PEma2yvAB6gvssftroIQgghRKEaVBBfX1/P/Pnzd/rv8+bNo6GhYa87JcYf7We5ZuEEJsW2JYecPC3GvsVu3gYcojA5jkNGB7CO229QnjWK9e19t3Bs6vDGTBAvRD4Kazh4Yu9zMM6aFScoq/BCCCFEL4NKp4/FYmzevHmn/75lyxZisdhed0qMTxN0hpcumMa6Do94QFMeKvx9yCK/pHSQFzZn+d9ljUxLBLjmsAlMcDLY7VZ8ixyfT84t4ZW/b3vWxQKKgyeGMGbXxdkgN0nQ6ufObCt2fNkKIsYVpRRKu7mdGsYb1CRsnAz3nFHD9W+0MDnuMqskyMKJIQJ+Kp92fgghhBCjblBB/MEHH8wTTzzBlClTWLx4cc+qlLWW559/nieffJKjjz56WDoqxj5jDHFSHBhXWDuwauhCDFSueGKaSx+q7Wm7+712ll48gxjJnjbf9zl7RhT/+Ep+tbyF6pjLj4+uIK6yu70m0yrAS3Ue33y+Dt9avnF4OcdWBQkPU/E4IfKJ1Q71nsvPXm4i5VmuPqSMqqAZ8Akj1loS2uPC2UV85dk6mlI+nzuolJOnRAjLhK4QQgjRY1BB/Ic//GHee+89brrpJv70pz9RWVkJ5I6ca29vZ/LkyZx99tnD0lExfkj6vBgObb7Dz16r69XWkPRZ0ZTm8NLeR8lFTJqP7BPi7BnVuMoSVd5u92crpdiUUpx+z4aetvPv38iz501jXpGW/d1izGsxAQ7642q6vNy99Pu3W1l68QwmBwd+VGObdTni9tWktu6N/+jDm7jjQ9V8qMYd91ktSRWk3Vd0ZAyVUYcEUjdCCCHGq0Gn03/961/nqaeeYtmyZT3736dOncr8+fM5+uijCQT6FicTQojR5ihLScjp014U1NDPnlvTfUSaZUBHnDmOw60rW/u0/+bNFv77qFKQwbYYw1zX5Y4VbT0BPOROGPmvpc1cd0QJ1tv9MZVaa57ekOwJ4Lv977IWjp1UQXiM7Y1XSuE4Dr7v73aSo0uF+NKz9dyysh2AmrjLM+dNo0ylZeJbCCHGoUGfE++6LieccAInnHDCcPRHCDEKlBr4SlmhiiqfHx49kcV3dPVUwD5yUoQpcQdrBpbuuyvWWuaUhvq0HzghhJK9IWKMs9YSDfStlRt19YCvf2stNfG+w5KpiQABxZjaYpVUQdZ2Gp7Y0MUx1VFmJjSRnWy7UUqxocv0BPAAGzs8/v3FBn5yZCmO3f0EiRBCiLFlUNXpn3rqKTZt2jRcfRFCjDClNR0qzFudDpv9EEkVHO0uDRtjDDMihpUfmclvTqziobOncNep1cSGaL+67/ucMi3aq7r2nNIgF80uwvP2fpJAjA6jXdpVmHYVJqsl02xnfN/n7JkJKqLbsl3iAc3nDirFH+D1b61lTkmAY2uiPW1lYYdvLiof8L76QuDrADesaOeI29dyzbP1HHXnWv77jbY+15fjODiOg1KKNa19n1NvN2dIS4KPEEKMS4Naib/55psBiMfj7LPPPsyePZt9992XKVOmoPWg5gOEEKNMKcWWbIDFd75PQzKXpnrZfsX8cHEZ0TFaiM2xPqX4XDAjiLUWY4a26nXMprn/zBo2dfn4FmqiDgnSyDi7MKVUkFtXdfKtFxpIeYbLDyjmO4vKiQzglIJC4DgObb6DAYodg/H3LlAuVmlevWgG961pJ+lZzpmVoGgABSG3F7Npbju5ivWdPs1pn7kTQiRsZkxlCnVZh++/1Nir7bpXG7lifgkBsiilaSXIPe92YIGzZsZZVAUBDdntHiaXzCki4RjGeakAIYQYlwYVxF933XWsXLmSVatWsWrVKl5//XUAwuEws2bN6hXYC7GnlFJkcMlYRdEwHNFldIBOk0vxHM9HgKWVyzXP1fcE8AB/eLuVLx1axrQxtCDfPcG4fQGo4XrPrbVEbYpZ4e4tCtkB7acX+SeXwmy56qltxRBvWN7KwooIF80MFvxzI6tcXmwwfOXZWjqzlqsWlPJPM2OEzeCrwHdvx8mdMJLkkpkhlFJ4XmrQKfDWWqKk2S+mIAZ2iCfa8oEFMjs8GDwD3fMULQRZcMv7NKVy19g3n69n2SUzeeycqXzhqTrqujw+NbeEc2fF8f2xMaEkhBBicAYVxBcVFbFw4UIWLlwIQFdXF6tWreKdd95h6dKlvPnmmyil+NWvfjUsnRVjn9KaTdkA1z5Xz7r2LB8/oJhz9nBg2Z+kE+YnrzbzuxWtVEVdfnF8JfNL3DGVqjlQGaN4r58UzfXtWWZMLPxq6lpr2gjy8pYUjlIcUhHeq2rOng6Qsg5gSejdB3BjaeVwKCil6CRIyihcnatR4Jr83curtebxDV192v+6poNzZpTjFniRtUbP4ZS/rO0JkD/7+BZqYpM5scoZ0ASFUopOFaQ+ZUl5hpqYS5HK3V9DMcExlu+fED4Xzyni5rfbetrO2SdBSBlcx+UPy9t6AniAlrThN2+28NWDE9x72iQMioTjgwTwQggxbg26sF23lpaWnhX5d955h7q6OhzHYdq0aUPZPzHOtBPkiNvX0LJ1o9/LW1JkTSUf2ze816meynG56a02rnu1CYCmlM+Sv6zj3Y/OooTxF8QnHMOlc4pZWr9tpTHsKOaXhzBjIF241QY5/Pa1bOrMvbfTigI8d960XmfCD1RSh/nOP5r47YoWSkOa/zy2kgXlVUPd5TGtXYU49/5aXtiUJOwovr94IhfvGyU8xEW5HMchaTS5Qwf2/GcbYzhyUrhP+wcmRwkqU9BbJBzH4W9bU7W397sVLRxdObAJik4V4vwHanmmNnc/TS8K8PS500jswf013oRslh8fNZGjqiPc/34nJ02Ncd6sOGGTAlw6s32vro6swVpLjK3XdGHPIQkhhNhLgwrin3322Z7Avb6+nmAwyMyZMzn00EO58MILmTVrlhwxJ/aYUoqVzZmeAL7br5e38E8zq4nv5c/v8DV3rGrv1eYZeLUuxQerCn/lebCs73HpnARJz/C7Fa1Ux1z+67hK4sor6CrQSikCgQC/W9raE8ADrG3Lcvd77Vy+T2hQK4XacbhtZTv/u6wZgC1dPhc9WMvyi6ciI+mB8XWA773UxAubcgFeyrdc/XQdp82YSbjvqX97LKlDPLwuyc1vtzFvQoirFpRRrNJ7dG9ba5lV5PKvB5fyi6XN+BZOnhbj4tkJTIGvgFpr2b+s756ZA8tCBJTd7e2vtealulRPAA/wfluW699o5msL4hgp5LhbEZPi0pkhzp8RIaBMzzXleR6fmFvCT19rIr31FI2go/jnuSVks0OTkSaEEKLwDSqIv+mmm9Bac8ghh/Dxj3+c6dOn4zhDOAIT45q1lvJI30mgSTEXV9m9DizD2nJgWZBX63oPwGeVBLHj9IieiEnx+QNjfGz/IhxliSuvoCczkirE+i5D2vep7egbSGzq9FCq7+rqrnQZzZ9Xd/Rpf35TigtnhQt+b/RISBp4trZvavpbTWkmVQ7RBJp2ufGtdq59rh6AR9Z1cs+aDp44ZzJx9iz4iZg01x5SzNULyjBAWBmiNl3Ic1xALsvg4PIwJ06J8tj63PsyszjAlfNLsf7uV9K11qxq7vuavtWcIWsUMioYGN/3cfD7ZHWUOVmWXjKDn77ahAG+uKCMCW5hT64KIYQYWoMK4hctWsSqVat4+eWXWb58ObNmzWL27NnMnj2badOm4bp7nJ0vBAAVIcWZM+PcszVoirqK646uIKq8vS4Q5lqP7xw5kadqk6xtywXtV8wroSI0tvdf7pbxSJAbIBZyEbaUCvKNFxv57Zu5rILfn1zDr5e39Ix7HQUf2b8Y3x9c5f2whsOrwjy1sXcQOq88WNATHiMppi0nTY3xRkPvwG9ueQgzRPUu2o3DL5Y292p7tyVDc8YS34sEsZDNEupOYd77ucS8EbNp/rCkiqa0Je1bKiMORSq902eAUgqtcxMunudxxsw4X3m2rtf//9TcYgL9BKVDRW/dKhFSFszYXe3XxmeSa7juyJLc9eaPrer8Qggh9t6gou5PfOITADQ1NfHOO++watUqnn/+ef785z8TCASYMWMGs2fP5swzzxyWzo5HSilg/ASZEZvml8dX8M3Dy6nt9FgwMUSc7JAES9ZaJugMz547ldaMIRrQRJQhPEaPUxtvklbz2zdbAajt9LhndTv3nTWFny9txlHw7UXllLv+4O8lP8sXDi7jsXVdvFafQgGfO7iUqpCljTBpYwk7UKSG5jodi5Tx+OKCMt5pyXDf6g5Kww7/dVwFRdoMWVSssBSHNLWdvdvDjhqaXzDG5E5SSBMNAAFgFycpdGe4vLIlxTE1EcqDljLX59EPT+Wrz9bRkTV86ZAyDi0PYMzwPE+TOszd73Xwp3c7WFgZ4nMHlZGwqTH72WitxXrjM0NMCCHE7qmWlpa9+gRMJpO89tprPPDAA2zZsgWAX//610PSufFMa000k4QNqyEYxlZU0xUIj9kBy46UUiil9iooWrVqlRx3OI5s8kLs/4fVvdqOrApz52k1BPEJ4+/x9aSUooMgXT4EtCKoLQ+t7eSzT9TR5VnmlAa5/6wplOv0uLlHB0spRZIAGTSK/8/efQdIVZ2NH/+ec++dPttZlrKwVBUUVFAQFUSsGLtijZqY8iZ5Y2Jikp+via8xpqnR9GY0iYmJJr4xsSMaIyi2KBoVlSYdadt36r33/P4YGFgXgd2d7c/nL/bM7Oxh9s7sPOc853kgplxUAXdTtdY8tw1Oe3BdPhg9Z0yMn82qJGy69iyxUoq0ckgbhY0hWoBjKb3l/SujHL7/WiM/2FEQFODXc6qYVxPEUibfZ76kC9t1etrhplcbuX3JrjlMHhTk0dOHEe3i321/1VuuL9E/yfUlupJcXzntzn9vbm7O78IvW7aMDRs24Ps+juMwbtw4xo8f3xXzHHCiqRbMVy+Dutz5TlUznug3fkqzvasYkbIcfED7br8LHIwx/e7/JLpWkaMYVxJgef2uncCZwyJElIv23E6l+OaqQqeJ5lrO02BCfOKpzeyoO8W7dRk+/6/N3HV8BSEKs3umLZtmTxHSoHtxK7Y9SatcO76sbwhbECOXDhwiQ74iQYFf3r7vM6Xc5p3LRvPPdQkOKg0wrsQmXKB0/Q+jlKKRIF94ZgsL1rYwuSLEHXOqGBrIYvpBZkbSWPxwt+AZ4GvPbmE/es0KAAAgAElEQVTuyBpifprojuKOXVkaImksfvVG66MSr29Nk/DIvyaFEEKIgaRdQfz111/P+++/D0AoFGLMmDFMmTKF8ePHU1NTI2fiC8TRGvPIvfkAHoDVy+Cd19CTpuOj2O453P5SLXUZj6sPK2NE2BAYgL3OhdgprjI8eU41N/+7lte2pbhwXBHnjYuhu6CS+OaEmw/gd3p5c5KM0bSvbN6eJa0Q977bxF9WNDG5Isj/HFFOiep4j/vulFQBfvifBm59pRbPwOGVIR48fRgx0/UV3QPGpVK7XDI6V6/AdHEAD5DE4ZNPvc/ja3J5/M9uTHDS39fy/PkjOlxQrzfxDG2u9aasj6E7jykYSoIWiQ9UvQ9oOSohhBBiYGpX1D1kyBBmzpzJ+PHjGT58OFrLEnhXUMaHLRva3rBlI1pr6j2bw/70Ho2Z3Af6P73TyIsX1HBgbOC1SRNiJ9/3KSbFt44sIu0VE7X8LmsFNiRiE7RUvgUUwJzqCGHt09mqXr52+MGrddy6I335+U1JnlqX4OlOVFnfF601lmXh+36nUqKVUmxJw/f/vWvn9tUtKW59pZb/nVJU0PT5venOjgFZNPPXtD6Iv67JJeFCrB+UaQ9pn2OHRli0W3eByw8qJqS8bqvyF9cut82s5MLHNubHPnlwCUFVuJoKQgghRF/SriB+3rx5xONxAoG2/WUBMpkMTU1NlJeXF2RyA5WrNMFT52EWP7lr0LJR02ZjjOHJtS35AB5yn2G+/8p2fj2rHKvL6gIL0TdozyUM+F0Yx0XI8o/ThnLlPzezodnl+OootxxTSaAA7cdajOY3b9W3Glten6F5P4JC37Jp9nLVu0Ps3zGbpA7y+vYsD66q5/jqKEdXhQj7HVv8UErxxra23/vC5hRJv5hIhx61d1MYxpQEWLHbMY6QpQjZql8EmFGy3HvqUH79Zj2LNiY5Y1SUC8bFcTp4jXSE8TxmDwnw9kdHs3BDgkMqgtTELEJyHl4IIcQA1a6t9GuvvZYlS5Z86O2vv/461157bacnNdD5vk922Ci49jY4YBJMOhK+cxepcCxXUdhp+2uLORolmYVCdAvLeIzIbuaFeSNY+/Ex3HNiJUUUpqidAirCbddXg/uosp7QYW54uZFZ/7eeT/1rG1u9wD6zpTzt8KPXGzjl7+v4+X/qOe+RDXxt8VbSas8Ltfvi+z5HVoXbjJ8xKkbU6gcR7R4UqSx/OGkI8UDuubY1/PL4KiL0j+NNxhiifpIvHRLlzycO4uPjO77I0xlBk2Wok+HMURGGx2w8A0r3g1QHIYQQogMKeojd87x8SzTROSnLwZp4BM7YiaA0GSeYS5X3fY4ZGmZkkZPvdR62FdceUY7lZ/rDxo8QfUJLUyNDq3btBBbqtVesXX5y3GBO+8euKuufOriE8F5Sh7Pa4WvPbeEP7zQC8F5jlte2pXnuvOq9puAn9lC07A9vN/Kt6YMIdnT+ls+fTx3KF57ZTF3K49IDi/nYhCJMFx1t6Gm+73NATLH00lHUpX1KgpowLnY/q1FiPHfHNWHRTG6Rp7gLK9J/kFKKJhXi4ws28cTaFoZEbe46cQhHlNn97rkWQggh9qVgQXwikeDNN98kHo8X6iEHPM/z8OwdH6V3O+teRIbF549gwdoEtSmPs8fGKVFZqeYuRD/geR5Ty2yWXz6GF95PckBpgKFhRch8eP/ttLH4y/KmVmNrGrO07EcKfqHfNYImy9xhDsdeOBKDIqQ8nH4awO+kjUccj3iAfpFC/2HSKsA/N6T51oub0QpunF7B0YMdgqbruydklc11i7fwxNpc/YFNLS5nPLiOlVeMoaifZD0IIYQQ+2ufQfyDDz7Iww8/nP/6zjvv5M477/zQ+8+ZM6cwMxMfyvd9oqQ4d6QDOHheql9/cBRioHGMS7lyOX2YhTH7c7bdMLLIYVndrkDfUuzzXHZYeVx1aCm3vLJrN/7iA4s6XTDMeC6xnYGVvDf1C1prVjb5XLRbcblzHtnAvy+qYVxYdfkictJXPLku0Wos68PaJpdD4nv++RnlkMYCDEXaxXRjwUMhhBCiK+0ziK+pqWHmzJkYY1i0aBEHHngglZWVre6jlCIQCFBTU8OUKVO6bLKite6swCyE6H77222iSGX59fFVnPz3dfmK+d+cPogwe3+PsP0sXzq0hOOGRXhgVTMnVEeYNTRMqB1nnrXWNBmHhAcBSxHC65adWdEx2rJp9DSOMoSVt9/XmGVZ3LW0vs34Pe80ctMRRWSzXfs7D2qYWhliQ3NzfkwrGB6zMXtIp09YYb74zGbuX9HEoLDFz46rYmaVLa1YhRBC9Av7DOInTZrEpEmTAHBdl1mzZjF69Ogun5joGKVUvlWUtJsTYmDwfZ9Dii2WXz6alQ1ZqmM2McsnsB/BdNhPc+wgzXFVJTtazLUv9b3eBDjl7+tZWptGK7jm8DK+NLl4r+n/omekdJA/LWvmrrcaGBazufXYSoYHPdR+tHIwxnBIedtKCQeXB7rlb03QZPnhrMEsr8+ytDZN2Fb8ZNZgIntodWcsmx+9Vps/YrI54XH+oxtYecUYypQE8UIIIfq+dp2J/9jHPtZV8xAFkNIB3mvyeXxNC0cPDXNwWZCILy14hBgILONRhMfhxQpj0u1KY+/oop+nHW56cTtLa3PvM76Bm1+p5aMHFlPdsQL3ootoy+a+5c18aeEWAN7cnua5jWt4+6OjiO8jYwNyi/jnjY3z6zfreWt77vd96KAQp46MtnvhpyOMMZTrDAvOGkbKB0crIsrF9tsuVLV4msdWt7T+fuCNbSlmD9aywC2EEKLP61Rhu8bGRq655hquvvpqDjrooELNSXSAr23ufreFrz67JT/2yYNL+NaRJYQktVWIAePDziZrrTHGFPTscspX/HtL2wDu3boMI4dIsNSbNHqaO99qaDXWnPV5qzbNUWX7d6Y9ZlI8ceZwNic9tFIMCimiJt1tZQ9y9WDSRBW5qPxDfnBYG6YNDvOfba0XsceXBvFlYVsIIUQ/0K4+8aL3ajE2N764rdXYb96s31HURwgxUPnapkGFWPC+zzstFgnV0eZxbUUtn7NGx1qNaQWHV4YkgO9lHGWojjltxqsizn4v7BhjiJoUo0NZaoKZXADfC7uiWH6W66dVMHlQ7lp3NHxnxiBKnd43VyGEEKIjCtonXvSsjN/6A4oBfPnMIsSApbVmZUJx9F9WkdpR8O70UTF+NbuSiCnAjqTn8smJxaxtynL3O41Uhi1+NruKuHalKn0vE8LllmMrWbQxQWMmt8By7tgYg0N772DQVxWR4tHTd6Xeh5WH40udBiGEEP2DBPH9RFh5fOaQEn70Wl1+7LSaGKFOtooSQvRdCWPz5UWb8wE8wEPvNfPtGYMYUaAz62E/xfeml3LDtArAUKRcfF+Kh/U2xhiGBlzeunQU79RlqIzYDAoqwoVYzOmFjDH7lXovhBBC9EWdCuLD4TBXXHEFw4YNK9R8RDsopUgrm5SvCGO4dmoZ0waH+duqJmYPi3DO2BgRv/vOKwqxO19ZtOCQcA1RWxEngzGSYt2dsga2JNoWLatLeYwMFq63t+1niZGrvSHZP72Y7xHH48hShTEZCWyFEEKIPqpTQbzjOMyYMaNQcxHtoLWm1g/w5YVbeH5TkuOGR/j+0YM4Y4TDqdXl2ORaRclntN5Ja00WC0sZlO/1ynOlneFpi0WbPS6dv57mrM+QqM38s6qpCblyVrobFVs+nz6kmC88s6vgZVnIYkyJg2lHL3jRv/S39xshhBBioNlrEL9s2bIOPej48eM79H1i/zUZhzMfXs/rW3OpkH96t5H1zS73njyYiMnsR8Mg0VNSymFpnc8PX9vG0KjNV6aUU2FlMP0ouG0xDhc/vo6EmwsWNrW4XDp/I4+dMYwo/TN9tzfyPZd5Y2OELM1dSxsYVeTwraMqclkRPT05IXoZrXO1fmWhUQghRG+31yD+1ltv7dCD/vrXv+7Q94n9l/ZVPoDfaeGGBFkjDQd6M8uyWLLV49R/rMuP3beskf9cOoo4/WdnNOGafAC/03+2pTGqfxbR6s3CfpqLRgf4yMjBBDU4JoORnPc+QSlFEocsigA+IVzZRe8CSimaVZBXt6RpzPocOzRMkcqCL8vhQggheqe9BvFf/vKXW33teR73338/6XSamTNnUlVVhTGGzZs3s3DhQkKhEOeee26XTljkOBpijqY5u2vHYFDYQisjQVIv1uJrbnl1a6uxurTPi++nOKmq//TVjtqKirDFtuSuD8Gzhkew5Ex8j/A9jygeSJ3LPiMUCrHVC/Bf/9zMS5uTzBoe4afHDaZE9c62bn1Zswpy/N/W8W5drnp9cVDz6kWjqNC+PNdCCCF6pb0G8QcccECrr++//3601txwww04Tut+s8cddxw333wzS5cuZcKECYWfqWglolx+cfxgLn9iE74BW8MdJwwhrqS1U29mKSgOtM2W2NNYXxZXWeafVc0lj2/knboMxw6L8PsThxBBCi0KsT9Cg4Zx2oPr84HlQ6ua2Z70+L9TqwgjrdIKRWvN4k2p/PMM0JD2ufmV7XxvWjHKk04LQgghep92FbZ74YUXOPXUU9sE8ADBYJCjjjqKxx9/nPPOO69gExR7ZvkuJw8LsOqKMWxodqmO20RwQVo79WoB4/LN6RU8urqZ9I62XweXB5lQFsDvT4XGfI/xUXjy7OEYFDZ+LoCXXS0h9ounnVaBJcDiTUkyRhPuoTn1R0optiXb/t3ckvDwjcLqgTkJIYQQ+9KuID6ZTNLS0vKht7e0tJBMJjs9KbF/AsYlgEtpXGGMBO99gTGG4SGPdy8bzWOrm6mK2hw5OETM9L8das/ziO1WYrG//f+E6EqOMsQDmqbMriMoQ6N2vz4yZVkWLb7GUWCb7jn/73kep9bECNtbSO5Wx+NLh5fh4CEHgIQQQvRG7crhHTt2LE8++SQrVqxoc9uKFSt46qmnGDt2bMEmJ/ZPf9/dVErlqwb3BpZldWo+2vcoIcWlY4LMGayJ+ql+/zsUQrRPpm4Lvz1hCM6Ot5qwrbj75CEUqf65YJvSAR7f6HHRE1v4wnO1bPECoLtnH7xIZXnlolFcML6IU2tiPH3uCMbHVb+pUSKEEKL/addO/EUXXcQtt9zCzTffzIgRI6iqqkIpxaZNm1i7di2xWIyLLrqoq+YqBpidFYOX1WfJeIaJ5SGKyPTcBytt0Wgc5r/XQszRzBwWIU66w/PxPKl8LITYs+aGOo4bX8XKK8ZQl/YpC2oiZDH9sGK6ZVn8c32aix/fmB976L1m3rxkFPFuaJiqjccwx+fnx5bhASE8fD/b5T9XCCGE6Kh2BfFVVVXccMMNPPbYY7zxxhu8+uqrAJSXl3PCCSdwyimnUFRU1CUTFQPPBysGD4vZvDBvZI+0YlNKsc1zOPRP7+XTW2uKHJ47fyRR5AiJEKLwbONShEtRgH6bQg/Q5Gl+/Hpdq7GGtM9rW9PMquyerh3GGCyTxQJJoRdCCNHrtSuIB4jH48ybN4958+Z1xXyEAHI7M/NXJ1oVdtrQ7HLHW/V8dVIM1+3elFKjbW799/ZW51NXN2Z5al0LZ49wZFddCCE6yNZQEWqbOl8WtjBG3luFEEKID2p3EN8XPP3008yfP5+GhgaGDh3KBRdcwPjx43t6Wt1K677dc1wpxdqmtumMqxtdfFS3z8cAdam2z2d9uu8+x0II0RsEjct3ZgziqXUt+eJyRw0JMypuYaTjihBCCNHGflXnMsbw+uuv8/jjj/Pss8/S1NS0x/utX7+ehx56qKATbK+XX36Z++67j7lz53L99dczZswYfvzjH7N9+/YenVd3ySqbWhNi4VbDFj9ISrVtB9gXuK7LhQcUoT8Qr392UgmmB/r2at/ly4eXtVo+iNiKM0bHOrQLb1kWjuP0qoJ9QgjRE4wxVAc93rlsNPecMpSnzx3B/XOHEjWZfX+zEEIIMQDtcyc+m81y++23t6pIHwgEOPfcc5k9e3ar++4M4k8//fTCz3Q/LViwgBkzZjBz5kwALr74Yt566y2eeeYZzjnnnB6bV3dQlsUzm1zmPboGf8f5yVuPreSKcWHsPtiCrtz2ePb8kXzj+W1kfMPXjyhnVFT1SCV3YwwjI4YXLhjJLa/UEg9o/t/UcopUtt1nVZM6xOJNKR5b08hpNVGmDw4S9tNdM3EhhOgDlPEoxuP0YRbG+Bg/1Z/LAAghhBCdss8g/oknnmDlypWcc845HH744dTV1fHoo4/y5z//mQ0bNnDJJZegVPenN++J67qsWbOGk046qdX4hAkTWLlyZQ/Nqvs0+jaffXpDPoAH+J/FW5k3bjRF9L0g3jEuB8c195w4CIMipj08r+cqBgeMy0Exza9mlaMVaD/T7gWFtHL4xgvb+c1b9QD85s16Pj+5lOunFuNINWQhxADXl4+BCSGEEN1ln0H8yy+/zIwZMzjllFMAqKys5IADDuCxxx7jgQceoKWlhSuvvBLb7vnj9c3Nzfi+36ZCflFREW+//fYev2f58uXdMbVuUT7qQLYlW6d2ZzxDMuOyeXX/+X+2R2/7/ZaNOpC7lta3GvvlG3V8cVKc2vd611zFvvW260v0L3J9ia4k15foSnJ9ia40EK6vcePG7fX2fUbe27ZtY86cOW3GTz31VEpLS/nd737HT37yEz772c92fJZdzBjzodkC+3qC+pK00pw5Os4DK3fVLDh0UIhYwGJwAf6fO89v95WdkuXLl/e632+jcvZYls9xnF43V7F3vfH6Ev2HXF+iK8n1JbqSXF+iK8n1lbPPqlrhcJhEIrHH26ZPn85nPvMZli9fzu23305LS0vBJ9gesVgMrTWNjY2txpuamgZE//oQLj89rpIvHVbGhLIgH59YzIOnDyNG54oDaa1p1iHmb/J58n2fZh2SgmwdFFI+V04saTX22UmlhJW0URJCtKa1xtUOrpYimEIIIYTYZZ878cOHD2fp0qWcfPLJe7x98uTJfP7zn+dnP/sZa9euLfgE28O2bUaOHMnSpUuZOnVqfnzp0qVMmTKlB2fWPYwxRE2Krx8e50uHFhPWBtukO10Irt4EmHrvarYkcoFmddzm+Xk1xEgWYtoDSsDP8M1pZcytiTJ/bQun1cSYMiiAI4XtRAf1tQyZgSCrbJLYbEl4DI5YRMhitbPfebS0nBUJi2+9tB3fGK47soJREY3TB4uUCiGEEKKw9rm0P3nyZN5++202bdr0ofc56KCDuPrqq3Gcnm9nduKJJ7J48WIWLVrEpk2buPfee2loaGDWrFk9PbVuo32XGBksP9vpAN62bX7zZn0+gAdY1+TywMomLMvq7FQHpLCf5vjBmlunlzBzkJLK9KJDchkyYR7e4PHoRk8yZHoJT9vM35Bh1G9XMvXe1Yz7/SqW1BmU3v/3S6UUfrySI+5dzQMrm/jHqmam37ea99O61xSSFUIIIUTP2edO/IwZMxg3bhzxeHyv9xszZgzXX38927ZtK9jkOuKII46gubmZRx55hIaGBoYOHcpVV11FeXl5j86rz1KKzYm2O0ibEy5KhXpgQv2D7/uycyo6JZch815+gW1I1OalC2qIS4ZMj2oxNp/+51q8HeunKc9w+YJNvDBvBHH2bzfesiz+uKyJr06t4LRRMQDe3J7mnnca+caUONmsdLIQQgghBrJ9BvGBQIBhw4bt14OVl5f3imB59uzZbXrYi47xXJfPTi7l12/W53v22ho+emAxris7yEL0BNu2+d0bDa0yZDa1uNy3vJH/OjCM60rKdU/JeIaWbOsMqA3NLmaPJS0/3Bmj49y7rIlZf12NZ2DW8Ai/OH4IRtLphRBCiAGvU7mXyWSS3/3ud3tNtRd9mzGGoUGf5y8YyUdGxThrTJyXL6yh3JZCbEL0FKUUW5JtX4MfbDEpul/IggNKA63GZg+P4LD/mTee52FpxY9fq83v6D+zPsFflzXkvxZCCCHEwNWpID6bzbJ48WLq6+v3fWfRZznGZULM57fHV/Cb48oZHXKxe/FukFJKzo2Kfs11Xf7rkBKs3S5zW8MVE4plF76HFaksj5w5nFNGRikPWZw/Ls7dJw0hwv6nwGuteXlT224vCzckSfny3iaEEEIMdPtMpxcCcme4d+4k9daNIK01jQRY1ZAl4mjKRoxFKdXp4n5CtJfWmkbjYFDY+ETofJHJ3RljqAr4vHRhDd9+aTuWhuuOqKDC9nrvC3SA8H2fQTrD7+ZUkjGKkPYJtrNLiO/7HD2kbc2Rj4yKEtY+viRcCCGEEAOaBPGi36g3AY76yxo2NOd2Io8aEuL/5g4jYlI9PDMxkBhtsbRZc+n89ayozzBzWIQ/nDyEEtX5do+7s43LuIjmjuPKd3zdsYUCy7Jo8TVBZVC+7OIXgjGGEBlCAH7711WMMYSzLfx8dhXXLt5Cc8bn0gOLuXB8HN+T9zMhhBBioOtUEG9ZFuPHjycajRZqPkJ0iLIcfvRqXT6AB3h+U4pXt6aZOUhLJXjRbZqNw8l/f4+GdO6aW7ghwaeeep/fz6kkRKagP8v3faxOZMgkdZBHVie4551GDi4P8pUpZZSojLxeeoGmzRu46MCDOH3UKACCyiMgAbwQQggh6GQQH41Gueaaawo1FyE6zDWwvL5tgLSyIcOsSmmFJ7pPc9bkA/id/rmuBbdzJUgKz3L4zVtNfOP5rQA8vT7BI6ubWXjuCGJIsNgbKM8lzo6FSTkmIYQQQogdOvSpcvv27Tz//PM88cQT1NbWArlquo2NjXieHNYT3c/B49MHl7QasxTMrYnJNSm6VcxRhKzWxccOrwyj21GdvDs0eZqf/6eu1diqhix1md41T7GL1hrbtqVwpxBCCDHAtXsn/r777uPpp5/Op1tWV1dTVlZGJpPhuuuu44wzzuDEE08s+ERF39OdReV832fKoAB3nzSEHyypJeZovjO9nFLrA4W+LJtmTxPSBse4UvROFFwYlz+ePJTLF2ykJWuojtv89sQhxFQWvxddbgpDadBiU0vrc/AfXIAQvUNSBXm33uXZjS2cMCJKTUwT8gt7PEMIIYQQfUO7duLnz5/PU089xQknnMDVV1/d6rZwOMxhhx3GkiVLCjpB0fcorWnWIV5v1KzNBEioYLf83JCf4ewRDo9+ZCj3n1JFedO6Vq3wklaIn7zVwtyHNvL5Z2vZ7gfRupelOIs+zzYus4fYvP3R0Sy7fDTPnz+CYYFsrztnXmx53D6rEr1bzD5vfJyY1YtWGgQAGeXwnVfqOO7/1vL157cx/b41/PadZjwttWmFEEKIgahdnwAWLlzItGnTOO+882hubm5z+7Bhw3jrrbcKNjnR9yil2OoFOOq+1WxN5tLY59ZE+c3xg4mYdJf/fM/ziJLbfU8mk7vGtcPNr9Rx+5Lc8Y//bEvz7MYEz58/Us7/ioKzfJciXIo0YKA3Jnx4nsfhpTbLLhvNMxsSHFAaYHTcJtwNr1PRPimsNkcfbnppG5ceMHrXmXkhhBBCDBjt2oasra1l3LhxH3p7OBwmkUh0elKi73KVzQ0vbM0H8ACPrm5hdbOXP8epLYtmFaRJhUiqQLec70wYze/fbmg1tq7JpUHO/4oBzDEuFTrNvJoAh8T9blloE+3nG/A+sBCU+eBAN9E7Mq3WZgLUESKtAj0yDyGEEGIga1cQH4vFaGho+NDb169fT2lpaacnJfqujJ8rjvVB65qyKKXwtcWrdTDjr+uovmslFz+xmQaCbQJ5rTWO42BZVkHmpTAMibZNPIk4kk4vhOd5Uh+iFwsqn9NHxVqNfXxCCSHVvUU7lVJsdh2OuHcNk+55j1G/Xcn3ltSTlEBeCCGE6FbtimAOOeQQFi5cSFNTU5vb1q5dy3PPPcehhx5asMmJvidm+Vw5sbjVWNBSTKsK4/s+CRzm/mMda5tygf7T6xN8ceEW0srJ3z+pgzy92eczi+p4YG2WhN5zizilFLZtY9v7PhVSrD1+Pnswu8fsn59cSljJTrzoGkZZNKkQG90gjSqEq+T8suiYsMnwq+MH8+PjBnPWmDi/PXEIN0wrx/HbLph2pbSy+cqzW1oVQ7x9SR11WSmGKIQQQnSndn2qPPPMM3nrrbf45je/yaRJkwB47rnnWLRoEUuWLKGsrIzTTjutSyYq+gbP8zhtZIQfzxrML96oY1DY5rZjKynSWfBhW9In4bbe8XtqXQspfxABcmfXb3+tnptfyZ1dv/vtBs4bG+enMysImV2VmNPKYUMSfvVGPTXFDh89sJgi0h9aPMzzPCYW2Sy/fAxvbEtTU+RQEaTVYxaSUiqXedDLipmJ7mFZFu80a0584D3q0z6OhjtPGMLc4YFWxRZF/+EqmwQ2KdcQsRVxlcEU8PUf8VN8bGyQS8eGcfDxvO6v5ZH2Fe/Utn3PXN+UZVhZ93UjEUIIIQa6dgXxxcXFfP3rX+eBBx7g1VdfBeCll14iFAoxffp0zjnnHKLRaJdMVPQdIT/NFeNCnDN6GJYyRJWXD2bLQhpbg7vbZ9spg0I4ygcDCWPx49daF3C6f0UTtx5byc79eK01b9b5zPnb2vx9fvGfehbPG7HXInW2cSnBZValxvczrVvPFVBSBdicguX1aaZUhinSrgRuA0yDZ3PZE+upT+cu9KwPn3rqfZZfLoXI+iNX2zy5McvHFqwl6eaO7iw4u5oRQbegC3me56Hx6N4k+l1i2uf8cXG+9dL2/FjQUhxYFsCYXe+9lmWhlJJjGkIIIUQXaXd+Zzwe57LLLuOyyy6jqakJYwyxWExadYlWfM8lBmBo1Rs7olx+d+IQPvXU+yRcw+hih1/OqSJCJh9T6w9kZipAKfJBd8LY3PjS5lb3WduUZen2DNP2YzeoK3fH0yrAt1+p56ev5xYiLAWPnlnNjAoLz+upj96i2+m2O5Ypz5BwDfHClHkQu+npzMqIDP4AACAASURBVJeEsbn8ibWkdxSb29TicsWCTfxj7hCi9J9e7sp3+ewhJTRmfP74TiPVcYefzx5MlFxav1KKZhXk8dUtrGrIctEBRQwO+DiyiCmEEEIUVKcOacbj8ULNQwwQtu9y6vAA7142mpRnCFtQpLL4OyL9iPL4ypRyvvnitvz3XHpgEaEdO/U5Zo/FHKxesI6UNDofwEOuovR//2szT589nFiP7Z+J7mYbn5NHRnl8TUt+bEjUJmqrLssAGagSKsj6hM+WhMvkihBxlQW/e19rCdfkA/idXt+awijdK37ftm1jjCnIQmLYT3H9lGKuOawUjaHI8vKP26yCnPjAepbW5rocfOfl7fzz3BFMLZVFTCGEEKKQ2h3EJxIJXnrpJbZu3UpLS8se73PFFVd0dl6iH7N8lzgu8R09tHffqbf8LP81sYiZw8I89F4Ls4aFmTY4SNDf1foqojy+Ob2Cf92/Nv/5eEyxw4GlAYzfsz3fU3to+7Q54WKUBG8DSZgsd8yp4nP/2swTa1qYNCjEb0+oIr5bxonovIQOcvmCzSxYm/tbVBTQvHhBDUMdv1vTuGOOoixkUZvaFaieMCKaPybUU7LKpta1uP/dJkbGbWYPjxAz6U4/N5afZecS/s7YXCnF6kY3H8BD7r/+9ee3cv8pgwnLIqYQQghRMO0K4t9++21+8YtfkEqlCIVCRCKRNvfpjp7fon8LmzRHlGqmVxTheR6+37p3te/7HFRk88alo7j77QZGxh3OGhMnTpqeLiMXs2FsSYAV9btSaD82oZiI8iSILxRt0WQcUp4hZKke2XndF2MMRSrNHbMryJjBWPjEVGHPRw90SinWNnv5AB6gMeNz3fNb+dWschzTfZXbY2SZf1Y1H52/kXfqMpxQHeWXx1cRMukee9lrrVnWCDPvX5XvMX9weZAnzhpOxHTNYqe7h8UB1wdj5HOBEEIIUUjtCuL/8pe/EI1G+cpXvkJ1dXVXzUkIfN/fa8DjGJfqgOL6w+M70kSTPR7AQ+5owJNnV/Otl7bx+rY054+Nc9mBRVg9nCHQb2iLpU2KMx9azdakx+CIxcNnVDM+agpaCbwQjDEETZbgjvPC/odFczsWJeozPsUBTQiPQDcGoH2VUor3W9qetd7Q7JI1CmcP39NlfI8DY/Dk2cMBhYVPhM7veHdGwthc9/xmdk8OenN7mlWNWQ6JF76SvDGGscUONUUOqxt3Xb9fP7KcuOUh2fRCCCFE4bQriH///fc577zzJIAXvYIxBtftXQWTfN+nVKW5eXopKV8Rs3xMD7SC6q+ajM25j6xlazIXEWxOeJz36AaeO6+aGOl9fHfvo7XmvZTF7P9bTW3Kw1Jw28xKLhoT2WMgL1W/d/F9n8MrQ0QdRUt213Px6YOLievuDxo9z2tV96Knfzs+ez7e88Gz+4UUJ8Oz54/k9283sLw+w6cPLmF0TOF5siglhBCiazlKYacT+HaAjJWrBWPbuVB3Z7zQ04VwC6ldQXxFRQWZTP+ptCtEVzDGYJksUcDI7lNBZfxc5e/drWnMku2j6bpNxuYTT27Kn6X2DHxp4RbOGjOGALsCH601TQT5x8om1jRmuWxCMZWOVP0uUlleuqCG/7d4K5taXD59SAlzR0bwvL63oFNoce1x7dRyznxofX5sWMzmgC6sHeL7PjGSfGFiBEMU33MH/GKTEEKIwnEwTBxaSSDVjG87JJ0Qxhiifhb16H2w+Ems4aNwPvFVlFKYfz0BbhZ1zCkYJwDrVkIqCWMnkAyE8fpwMN+uIH7u3Lk8+OCDzJw5U/rBC7EXRtu0GAtQxLQHshNVEEENo4oc3tstXfeA0gCOMj2/9dkBPop36lovjHomd7a7eLd88CYCzLx/DSsbcv/vW16tZeF5I5lUpPvFanKH+R7DAz53HldB1ijilocvATyQywyYNshh0fkj+fl/6hhd5PDpQ0ooItPlR496W4aUEEKIvi/ouzivPw+/+h4kW9BjJxD92g/IBMOo/7sLHv5z7o7bN6MbavG/+TloqgfA/PU36JvuwL/5GmhphuJSIrfcQ1OwbX23vqJdQXxDQwPRaJTrrruOqVOnUlZW1qY/vFKKk08+uaCTFKIvSaogdy1t4vuvbEcr+MaRFVw8LkrYSBZLZxWpLA+eMZzzH9nAO3UZJpYH+evcYbk2hX0wiA8pnzNGxbjn3cb8WFnIojSo2RlpKaV4uzaTD+Ahd77+f1/Yxj0nDiLUK6pB9BxjDAGyBOh19Q17XMhkmVyk+eWxZWgMnpfqk68TIYQQIpBNY378v7Bz82LFUrj7RwSuuBqeeQzGTURf+nmIF2PeeDkfwAOQSmKeehB1xCzMvx6BhjrMI3/COe9TZPvoZki7gvi//e1v+X8vXLjwQ+8nQbwoJMuyaPJyi0Vxy+/V/Ya11ry+Pct1z2/Nj3150RamDh7BYcUDfNe0AHzfZ2TQ5cmzh+MZha0McZXts89rwLjcfEwlSsGDq5o5sCzIHXOqiO2WSq+UYk/HmD1jgL55jOCDUipAymi0Qgr7FVjuteFLgzchhBB9VtB4qM0b2xYxfud18FwYcxD6gk/h3/xVGH0AasyEtg/iubDb5rPatgVl+ubnR2hnEP/d7363q+YhxB5llMPr2z1ueHEzAN+cNohJpU6v/ZBvWRb3LatrM/63Fc1MPbKo08Gm1hqt9T6r9/dnuXO3O1KmzV6qvnehtApQOuogGrAJKZ9gB7MsjDHESHH70WV8d0YF2hjiunUrOt/3mVgeojpus65pV5ryN46sIKLcPr+zmtQhPv/MFu5f0YSl4LOTSrl2SikR0/m0+IQK0OgqElmfyrBFkcr0y9eN1hpjjJw/F0II0adprQlmUmjj4Vq5AnWWUjhvvQql5aCt1ml3B0/BDUVwPvEV/N//COq2whtNqAs+hXnwj5BK5O5n26g5Z+J/+4v5bzWnXYirNPTRQL5dQXx5eXlXzUOINpRSbEjBiQ+sy4+d8MBaXru4hlGhwrdIKgTf9zl2aITfLm1oNT5jSLjTwUNSh1j8forFm1o4c3SMccUBwv7AStHXWtPoO3hK4fRQ7/WkDnH1oi3ct6wJgMsnFPPdoyoId7BYmDEGx2TzLdH29N8pIsPz82q4++0GVjdm+fQhJVSHwfd752LW/rIsi3+sauH+Fbnn0jPwk9frOGtMjCNKO5e5klBB/utfW3hwVTMAI4scFp43gmL6T7cIX9k0YfPCxiTDYjaji2yiJtMr3xuFEEKIvbGUIlK7GfOzG2HtSpwpR+N8/Jrc37Q7voeZOhP12a9jfv9DaGqAiVPgkv8mjcYKhlAbVuceKJPC//Mv0TffjVnwAGTSqDlnYsIR1Jkfxbz2PJzzMdwhI/r0wn67gvhMJkM6nSYej+fHmpqaWLRoEYlEgilTpjBq1KiCT1IMTLZtc9cHgmGAO5c28L0ji8lme18A43kep4yMcMrIKI+vaQHgjNExjh0awutEq7mkCuR3KwF+8GottxxbyScOCKO8AVJESlu826K54LF1rGrIMnVwiPtOHcYgq/t2Vy3L4p/rkty7I4AH+N3SBs4eHWP24K47LrGz6vdVEyMopXDd/lH120Xz5LqWNuPPbEgyrTza4edTKcXyRjcfwEOui8Gtr9Ry4xFFXfqa8bVN0tdELL9Lf47WmjUpzfT7VpF0c9fCnOoIfzipqiBZDEIIIUR3CmeSmOs/DQ21uYHnFoDnoT/xVUxDHWb+/dBYh7762xAKYyqqaA6EMcaQCUYJzjgB7r8Tph+PPu1CsCw46FB482X8m66CRDPqZw/gzj6dbCDUq4/n7g+977vs8sc//pEf/vCH+a/T6TTf+c53+Pvf/84TTzzB97//fVasWFHwSYqByRjDmCKnzfjY4kCvDmCiJs1dcypZdcUY3vvYGH513CAinWzplDI6H8DvdNNL22jx27UO16c1GYdT/5EL4AH+vTnFJfM30mz2/BxorUkrhyQOlmUVZA5aaxbsIej85/pkwX7G3riuSzab7dXXf3vY+Jw+KtZm/MQRkU79cdVas7yubZbK0toMGb9r6ggopWjRYb71ahOnP7KJby9pokWHUaprfl7SWHzt2S35AB7gqXUJNrT4XfYz90ZrTUY5eNrpkZ8vhBCib1Op5K4Afqd/L8qdY599eu7r55/Cv/G/8X/1XfwdveABssZg5l6I+vJ3UVOPxb/la/j/fQ7mmUdQx5ySayvnZjGvv9gvAnhoZxC/YsUKJk+enP/6xRdfZPv27Vx11VXceuutDBkyhEceeaTgkxS9g7Ys0spBWd0TOLquy/njihizW6+tMcUO542N9+oWRsYYIiZDmUpRSqogVen3FLO5PXQY2rdsmgiSVIE23Sm6UsI1bEu2ftN9YVMSfw9vY562ebfF4tInt3Lu45t58n2flAp0eg6e53HW6LZB50dGRfvFH4Tu5nkeJ42I8KmDS7A1hG3F/06rYGyR3amFCs/zmDU8gvWBWPLyg4qI6K7JlmjB4eL5G7l9SS2vbklx6yu1fPKp90nQdiGyEFyj2JJse83Vprr/OkypAM9th48+tZWrF9ey2Qvkzi0KIYQQ+8mEQmB/IMYYPgrPgLnoM3Dpf8O4gzGnzIOv/4R0KEoAg23lPge2WA6MOySXjt9Yl/vw/OK/MM89gZp5au7xygf3o42QdmhoaKCsrCz/9X/+8x9Gjx7NwQcfDMDRRx/NY489VtgZil4hqUPc+24Tj6xpYfbwCB+bUEzUT3X5CyFOmoXnjWB5fRYFjC1xiJMecE21wtrn1JFRHluzaxf4msPLiWiX7iw7nbRC3PJKHfcua2RUscPPjqtiZNhDdUNvr4itiAc0TZldv/1JFUHUHq6Ges9mxl9Wkt1x09kPr+fJc6o5spPnrH3fZ9rgIF8+vIyfvl6HAr58eBkHlzn4vqQwd0TYS3HTtBK+fmQ5CogoD6sAz2WJ5bHg7BF8adEW6tIen5tUyknVYbwu6iOfMZpn1idajT26upmMGUy4C35e3PL43KQSrnzy/fxYaVAzsTyA2Uvmj9aaFmPhGk1Meyi/cwuilmXxytYsp/1jfX7sgZXNvHXpKIqkJr4QQoj9lLEDBD75Nfj193OV5KNx1OdvIBUI4fs+zsnzsI47nc0NjQyxbEKvPQeL5sO4iTD7dJKBMGbtijY7X+bNV1AnnYMZfwjUjO/T5+B3164gPhgMkkjkPqR4nseyZcs44YQT8rcHAgFSqf5TNEjkZHSArzy3lT++k+tl/eTaFhZuSPC7OZWE6drCar7vEyXFYcW5LTXjpwZcAA8QIctdJ1TxyJoWntmQZN64OFMHBdBdFJDsia9tbltSx21LcqlOG1tcjr1/DW9fOopYN3xYjyqX++cO44LHNlCf9qmO29xzylDiH6jQblkWDy9vygfwO/309XruPK4cq5NXUNhPc+1hRXx2YpSAEyhY0DmQBfwsgZ1t9Qq0LugYlyPKLB75yBB8oMjyMV34erFULpNg9/T2okCubV5n/09KKZRSrbsWeB6njYzwx5OH8ss36qmO2dx4VAVxMh/+47TF6pTF55/ZzHsNWS46IM4XJ5d2uCgjQIuvue3V7a3GmjI+z29KcupQq998WBJCCNG1MsqCI48ncPgxkGiGaJzkjgAeIOv7ZJ0gxhj0kw/An36e+8YX/gmLnyL4Pz9EDatp8zdQjZsIk6fD9DkknOCe01v7oHYF8SNHjmTRokUceOCBvPbaa6RSKSZNmpS/fcuWLRQVFRV8kqJnpYzmz+82thqbv6aFlNFdssO0J/0l9aWjjDGETYoLagJcODqE73ndvvPb4lv5iuw7NWV81jS7HBzr+m4B2nc5sszijUtGkfIMYYs99og3xlAda5vCXBN32qRXd5TtZ6l9bznjxo0rWNApCs/zPKI7FphMF68zhXH53tGD+MIzW/Jjtx5bSVS5nbpGkirIhqTPyvoMR1aFiSsX2+R2z0N+mjOrbeYMHYyjDY7JYPZyzKbJOBzz1/do3JHN8v1/16JQfO3QWIeL8NkKykJtj7SUhiSdXgghRPtktEUmEIbAjghjD3/SykMBeOie1oMrl2JlUmTDUezLvwj3/AzcLIw5CC78r3wBvP4SwEM7g/izzz6b2267jZtuugmAww8/nJqamvztS5YsYezYsQWdoOh5CgjbmubdtjYdndt5kgDmw2mtyWChANsUppq453nQQ2evHWUYU+ywtql1V4DKsIUxbQMApRS2beP7fsHOiyvjEccjroEPeS/2fZ/pVSEmDwry+tbcQkdlxOKLh5VCJzoECLE3tnG5YEyEk0eO5o1tKSYPClFs+ehOtAFMqgBfW7ydu9/JdemwNTx1zggOL7HyrynP8wjjgb/3t2OlFGua3HwAv9OflzXyuUOKidOxIN4xLjdOH8Qj7zWT2JGFMHlQkIllAfxOFvQUQgghPsgYA4Fg2xu0JmU5BGafTuCYk8Fz8Z0ASSfULzcD2xXEp1IpbrzxRlatWkU4HOaAAw7I35ZIJJg5c2a3VGgW3SuqXG6aUcEXd9th+sqUcsLKG7BBvGVZ+Gg0ew5Q08phWYPP91/ZRlFA8/UjK6hyPPQegt2+IqJcfnLcYI796xrq0rlA4EuHlxG3TJvrIKUc1rTAn99tZPKgICePiBA16W57E42aNI+eMZxVDVmaXZ9J5aFcLQXJ7BVdKGSyVFkwdIiVy5Tp5OXe4ql8AA/g+nDVM5t59CND8xkG+8sYQ2Wk7d/nUUUOjmr7Gm7P41YFXN6+bDTPrE8wKGwxuSKYe7137CGFEEKID7U5mWHUR6+CH3591+BRc3CdXAHjjNqxm79TPwzgoZ1B/K233sqVV17JtGnT2twWiUQoKyvjjjvuaHVOXvR92ne5cEyU2cNH8eyGBEdUhamOKBx/13l4pRRa6wFRoTupQzy1LsHDq1s4eUSUU0ZEWp0p1Vqzqslw7P1r82N/W9HE25eNprSDu129ge/7DA96vHHJKDYmXMpCFjFtCH2g+r62LJ5al+GS+RvzY9Orwvxt7hAidM8RAGMMUZNiUtHOs8TJAVlLQfSMQpwDV0rR4rb94LG5xcNn/86FaK1pMjY+GgufUgeumlzKj1+vA6A4qPnJcYOJfKCuRLvn6nsU43H2CAdjDL6fkgBeCCFEl6hvbMSdNA379vtyLejGHIQZOY6k1fkuRH1JQXuFua7brS2nRPcJmQw1QcXosUF8v3VqeFIHWdXo8cb2NMcNj1Bq+wRNx1NIe7OMcvjGC9v4zVu53bF7323k4gOKuO3o8nww6yqL25a0LvSU8gwPv9fMFWODfXuhw/eI4TE+DLDns74NnsUNL77fauyF95PUZSHSzW3tjTF9MoXK0w4tvkZjKLa8vn3NiA4xxlAe1FTHbdY17Vr8++TBxcQsb59dKbTWbMg4XPz4RpZsTTGlMsSfThnKN44o5fOHlrI16TEiZhPbQ12JjpLrVAghRHdIWQ6qvApr7oX4vj8gi6ju8yN1MpnMV6QHaG5uZvv27W3ul0gkeOmllygpKSnsDEWvYYzJf0jL7fAE2JjwyPg+a5td/mfxVupSHn89bRgnVVn43dB2rLulsPjt0oZWY39+t5HvzhhEaMfXFlARbpu2Wh6yQNtY9PcPuwp/D4FzXwyme0LSCvG9f9fyh3caGRq1+fnswUwotrD74etJ7F2RyrDwvJHc+OI2ltZmuPiAIuaNjaH2o7ZDo3E446H1LK/PLS6+siXFWQ+vZ8FZwxmk01TGVK6WhbwshRBC9EHGGFy372a4dtY+g/gFCxbw8MMP57++7777uO+++z70/meddVZhZiZ6tQYT5Nj717C6MbfjfuywCH84eSin/WMdX1q4hcXnV3dL27GeYGmF55ndvga1e5E/3+Waw8v507uNNOw4Oz6m2GHq4DCf+NdWThwR4bSR0U61dULbNJncyzeofAJ+17b6a49iy+W6Iyv4+IJN+bHDBoUoC6huCRj21I6rz7BsfvVGAz96LZfuXJvymPO3tay4YgzF/fT1JD6c7/uUqTS3HlVK2oeY5ePvZ3HGjE8+gN/p7doMWbOjXed+LKpprXP1PwpYnFIIIYQQnbfPIH7ChAk4Tq5d0wMPPMDUqVOprq5udR+lFMFgkJEjRzJ69OiumanoNZRl89PXavMBPMCiDQmunFjChLIg65uzsJ9nNvuaiPL40mFlfO/fu7JRPjeplNBuRf6MMZRbWd68ZDRPr28hHtCMKg4y9x/rWFGf4b5ljcwbF+fHx1a0OU++P9LKYcH6DF94Zj31aY8Lxhdx6zGDiPSSStC+5zG3OsSi80bw+3caObQiyDljYt1S6CqpAmxOwbt1aY4YHCauXZw+VEyw2dPcv6J1G7+sD29uS3NMRde38RO9jzEGy2SJAO1JxnC0oipi835i1/U/LGZj72cRu6QO8srWDA+tqueEEVGOGRLq3MKjEEIIIQpmn0H82LFj823jstksU6ZMYdiwYV0+MdF7uUbxdm3b4PO9xixVUZuPjIoS0fs+s9kX2X6WL0wq5uSRURasbWH28AgHlzkEPtiz3feIk+TsEQ7NBKi+awXubhvDf13exM3HVOZT8NujwdNculvRuD+928j4kgBfPCQKHez1XGghk2FyseZHM0p2pDt1faGrlArwnVfq+cmOol1awSNnVnNMhdVndhGD2jChLMCb21tfTzVFDqYDCz5i4CpSWf4ydyhnPrSeurRPWcjiL6cOo0i5+yzU62qHHyyp59ZXawH41Zv1XHFQEd8/qqzf1jsRQggh+pJ2lZk644wzumoeog8JKJ8rJ5bw4Krm/JhWcGpNlJExm1NrIuh+3I87bNJMKdEcURbbUUzjwyuue56Hqwy2Uri7hbFadSxXQWvNK5vaPrePrmnhkxNiRDvwmLtTSuXTZzubjt7dhUZSRucDeADfwH8//T7/OqeaeB9ZUQoYl+8eXcniTUnWN+cWZL5waCllAeTssmgX43scUmzxxiWjaHENEVsRU1nMfmznJ42Vr2C/093vNPLN6YMIIkG8EEII0dO6uVa06A88z2NaZZBfHl/FbUtqqYrY3Hx0JTVRzcSYg9ePA/id2hOgRpTHV6eWceOLu1LwP31I6xT89vzcQyqCbcZnVIUIa0Nn+qillMP7KcXD7zVxeGWIQyuCRPayQNHbpLw9tONKeCjVPWfxC8EYwyArwwvzRtKQ8Yk4mojyCcouvOgAtaObRMwi9xroI68DIYQQQuydBPGiQ0J+motHBzitpprGrOHVzUnigRAENKE+suvpK4sEDg1ZQ5GjCONid8H5acvP8pmJRcypjjJ/za4U/GAHA+SKANwwrYJvv7yNrA9HVoW5Zko52k92eI7KslmwLs1H5+8qRnf2mBg/nzWIcB8JIGO2YlxJoFUxr49PKCbcgcWSnuT7PjFSxJwdA31o7oXiaoeEyXV4COERkBTugrMsiwbPQgFFH2hjGFYeV00uzafTA1x2YFGHFh6FEEIIUXgSxIsOyxrF31Y28YVntuTHbp9ZyWXjwlh+7zib/WG01ixtUpz89/doyvgELMXvTxrCSUOdLpl72GQ4rFgz5dB9p+DvS8hk+NzEGB+fWIzrQ0gboqZzZ86bfItrn9vaauyBlc384NjBhPtIjcIileHJc6q56cXtvLYtxblj41x+UBHWAMgM6W2UUjQTIOXnCqyF2f8Cg0kV5LbX6vnRa3V4vuHjE0q4cXq5FFUroLRyeG5Tlhtf2oICvjm9gmmDnPx5d9vP8uXDSpg9PMKDq5o5aWSUGVUhgvI7EEIIIXoFCeJFhyWM3Sbwu27xVs4bO5o4vTuIb/AdLp2/jqZMLv884xmuXLCJdy/rurkX8oy4Y7I4ZHMH6/ev2PQ+Jd22j+IZ02caDfi+TzEpvje9hJQPMctgJIDvEY0EOeOhDSzZmiJgKb591CA+Oj5CaB876lpr3qrNcssru3aA73irntnVEU4fbveZAoW9mVKK1S2Gcx7ZkB8746H1vHpRDWPCuzoghP00xw7SHFdVsqPFnLyWhBBCiN5C9/QERN/lG0h8IPBLuAa/L6RbKsWqhtYBRcI1ezxXPRBEtcfVh5W1GptSGSJi9dCEOsHys0TJYnpJpf6BxtMON764nSVbc0FfxjN85dktNLj7/nOjteaJtS1txh9+rxmj5M9VIdi2zZ1vNbQZv/vtRmy79bq+7/tks1lZPBFCCCF6GflUJDosoHxOrWldD/2UkVECqvsqkneUjc/s4ZFWYyPiDuE+GLQWgvJcrpwQ5/7ThnHO2DjfnTGIB08fToy+cR6+r0qqALUmxHYTJPH/2bvv6Liqa/Hj33PuvdNn1Fwkd8uNZhuIAYfeIYQSWhJaIAkhDVJISHmP9xLyCoHk/dLeSyeEhBAgCRAgJHQw1dTQi5EbtiVbtupI0+495/fH2LKFXCR51PdnLdZCR1OuZq7k2Xfvs7cKF5vwjXAZo3iqoWd/hrea82i9839yjDEcM7XnjIUTp8dRdvj/XRkJrLXsXdWzOeaelaFBnSYhhBBCiP6TIF70W0IH/OzoGr68XyWLa6J8ab9Kvn/4RLQaftlspRTWcTGOh9aaGAVuOL6GU2oTRF3FwTVR7jt9Kik1dhtoRU2OE2ocfn1kFZfuHSNuMl2ltaL0OnWES5dspPa3dcz67XLOubeBDtUzuBpp4tpw4vTugbgC9qkK7zJINMawoMrjsoUVuLo4ivGCPVIcNy0m2eAS8X2fs2Yn2bMy1LW2T1WYk2fG5TUWQgghRgjZEy/6rd04nPv3tdSWhTitNsnrTTkW3bSC1y+oJTyMgmGjHBp9l2ue30Q6b7nifZXMiFnKyPGrI8dRYAIOloQqjLpMlFKqT4F4EARoghEyX2Dk0lrz3IYcf3mnvWvt0bWd/LkuzSfmRPD9kbsVQBmfy/erYHlbgTvq2qmKOPz0qGqS2u9VzhbcEAAAIABJREFU84aoyfFvi8q44n2VWAsRHRCW/dgllbBZHjh9Kms7AhQwKeaQsDlpPC+EEEKMEBLEi34LrGJZS54n67uXzrblDZXDKKHYZj32u2l51/79Py1r47lzZjA7ChFbILL5diNiL38vZZVHe6BZ3lpgXkWYhBqY8Xmif7TWPN2Q7rH+ZH2GC2dHh+CISituc/z08Cp+dPgEwJJUAfRh6kPIFAix+ULg6LquNixYW5xoMS+mNn9dkABeCCGEGEGknF70W0wbzpmb6rY2PuowLjJ8TivHcfjr8vZuDfgs8P9ebMLo0XkNq6A8bni7gzk3LOeEO95l1m/rWLrJoPUY3fA/DAVBwGm1yR7rH52TRI+CqNVaS8QWSNosSZvrUwAvBo+1VrbMCCGEECPQ8Im2xIjjmALfPKCSry2qZGbK48TpcR47ezpJNbyaoZWFegav5SFn1J78GRyufHLr6L/AwiUP1tNmh8dFC+04tBOigxCOMzYvLFhrmR5X/PSoaqoiDsmQ5tuLx3HQxPCo25estUY5Ho47PM4/IYQQQoiRTj5Vid0SDbJ8c2GSy+aX4SlLlDx2GNWlB0HAsdNiTEt6rG4vlucmQ5rL968ctTPEc4Gl8J5kbn2Hjx0GA9+zOswdyzv5wYtNJDzN9w6dwPxyF28MlvpHbJ5za8OcOnM6oIgpH21yQ31YJZXVIV5p8rnu9SbmV4W5aM8yEjYr2V8hhBBCiN0gQbzYbcr4JAFsr/pWDboUeZ768DQeWZuhI284YUacMlUYtXttYw7sURHizeatFRFnzE4SVmZI3yDHcXi6Ic9nHmroWjv29tW8eUEtE5yxF8QDYHwSbP7Zh+Mvz27QjsPfVmb45APF9/tm4PdvtPLgGVOI29F1sUIIIYQQYjCN1opiIboYY4ibLKdOcTmnNkSZzYIZXSXL20qqAv/40FTOnZdibkWIL+1bwY8On0DYDu3EgJzVXPd6S7c1Y+FvK9Njtqx+NGsNHK55vqnb2pvNeTZkRtnVCiGEEEKIQSaZeDFmjLa9xjtijKFC5fjRoZVkjSLuGHSQHfJEr6cse1SEuOs96/MqQmitsdaOuhF/Y5kCQrrnFg5XLh0LIYQQQuwW+TglxChkrcUzBZLk0cHwKFW3gc8XFlYwPeV1rR05Jcbs8jDfeaGNF1oUGT2MZhOK3VLmBPz3weO7rR1cE6UqNPS9GYQQQgghRjLJxAuxHUop0njkrcZRkFA+WsZk7bYyleeJs6axrjMg4iiac4bFt6ykKRtwzXNNfHvxOC7bO4Fjhrb0X+y+IAg4aLzHK+fN5M/vtLN3ZZhDJ0WI29yQV4UIIYQQQoxkEsQL8R5KKVoJc9Y963imIUMypPm/Iydy4pQQoTHYRb2UjDEkyDI3Cm1E2PemFWw7zOCa5zbxyb3KSCJB/GgQtgWmhRVXLIhjrSUYBts6hBBCCCFGOimnF+I98srlX55s5JmGDADtecOF99XTOUzmrI8WBnjvNMJAIrxRx1qL7/tjpieFEEIIIcRAkyBe9JpSCuN4FLSH1qP31MkYxePrMt3WLLCirYBSsp+3VCLKcObsZLe1z84vJ6ok2BNCCCGEEGJHJLUoekc7NAYeVy/dSH1HwJf2rWBhVYiwye/6viNMTFuOmBxlZdvWkm6tYGbKw9rsEB7Z6BKxef73iAmcNCPBA+92cPqsJIfVRHCNvMZCCCGEEELsiATxolfarceiP66gJVccAXbPyjR3nzqFIyY4o65M1rM+//n+8Sxv83lsbScVYc0vjqkhrnxkQ29pRU2WD8/wOHtmJcoagkACeCGEEEIIIXZGgnixS1prljZkuwL4Lf7nhSYWHT+BCKMriLfWklI5bjlhIgWr0Zu70yvpTj8giheBRtc5JIQQQgghxEAZVUH89773Pd5+++1uawcccACXXHLJEB3R6GCtpTzUcw98RcTBUYzK7LS1lhibtwpYRuXPKIQQQgghhBh5RlUQD3DIIYdw+umnd33ted4QHs3oYK1lz8owC8eHeakxB0DEUVy1eBwhW5D4VgghhBBCCCEGyagL4kOhEGVlZUN9GKNOwua459QpvNiYo6HT57ipcVLKx1oJ4YUQQgghhBBisIy6IP7ZZ5/l2WefJZlMMn/+fE455RQikchQH9aIZ60lbrMcPl6jVKjYgEzidyGEEEIIIYQYVKqlpWXUhGJLliyhsrKS8vJy1q1bx2233caECRO4/PLLd3ifZcuWDeIRjk6u66K1Jp8ffePmhBBCCCGEEGIwzZkzZ6ffH/ZB/O23384999yz09t89atfZd68eT3WV6xYwX//939z5ZVXMn369IE6xDFLKUWHCrEmHdCWN+xRGSJFHmPMru88CJYtW7bLX4Bhy3FpDxwAyhwfM8rG+I0GI/r8EsOenF9iIMn5JQaSnF9iIMn5VTTsy+mPPfZYFi9evNPbVFZWbnd9+vTpaK3ZsGGDBPEDoEOFOeuedTxZnwFgfNRh6UdmUKVzI2qvvNaaLA7WQlQFvboIUdAeWaNxlCWh/JJeuMjoMH98K83/vNhE1NVcffB4Dq/2CNtCyZ5DCCGEEEIIMTIN+yA+mUySTCb7dd+1a9dijJFGdwNAa82rTfmuAB6gMRPw3ec2cc3iMlQwMmaq+8plZafi209vJBdY/uWAKvYu8wjtJGDu0FG+/sQG7lyeZo/KML86ppqpUegwGguEMEQp9OtChuM4PLM+z+WPbehaO/uetbx83kymh9WIujgihBBCCCGEKL1hH8T31oYNG1i6dCnz588nkUhQX1/PrbfeyrRp05g9e/ZQH96oo5RidVvPPfCr2gsUrCI0BMfUH02+w+JbluNvTqTfv7qDZz86g7mx7QfMBe3xtcc38Ie32gB4piHDncvTVMddvrJkPe15w8m1CX5x1ERiNtvn4ymg+d0bzT3W71qR5ot7x/D9kXFxRAghhBBCCDEwRk0Q77oub775Jg8++CC5XI6KigoWLFjAKaecgtZ6qA9v1AmCgGOmxQk5inywNdj9zPxyosqwWzu4tUu7dbCo3cpq74rrutz8RltXAL/F/73czI8PqcD6PbPxWau5c0W66+u4pzhySpzD/rSya+2u5Wn2rgzxjX1TEPStBN7Fst/4CH95p73b+oKq8LDpNSCEEEIIIYQYOqMmiK+srOSKK64Y6sMYU1KqwBNnT+frTzTSkgv40r6VvH9iiCDI42pFOJdBAQXHI6edXj1mXrk8vM7ncw+voSkbcNLMBL88upq4zez6zn1krWVSouevwOS4i9rB/DyNZV5FiOfWF7PsM1IhXt7YM+N+/+pOLptfRryPx2QCn4/vVcbNb7fx6qYcACdMj/O+CWGM6Xtm33EcrLVyAUAIIYQQQohRYtQE8WLwOTZgXtxy03HjCawi5QQEQZ6wCQi99gL2V9dAWwveESfhnn8ZHY63y8dMG5eP/n1VVwj9txVprnluE98+IIUu8T77IAj4wPQEs8o86lqLGfOJMYdPzy8n8LcfMCeVz6+PqeGov6yiOWdYky6wuCba43ZHTI4R0wb6ETsnbJZ7T5tMawFcDUkHon0M4APt0hK4/P2dNFOTLosmREjYnTccdBwHY4zsuxdCCCGEEGIYkyBe7BZjDJHNkeqWKWhetgP7va/BlmDwoTtR1VPwPvARCmbHAaJSijeacj1y4Pe/28EV+5fTv/aGO5ckx5KzpvHyxhy5wLJoYqQ4Jm8Hh2mMYUY04JXzZtKUM5SFNZ6y/M9hE/jXJxvJBpbDJ8f4yv6VKNO/6gFrLXFyxLf8dvYxptZas6xDcfCtdRQ2X0TYf0KEu06ZTHw7+/SzymNjXvHU6gz7T4gwKaqI2p79DoQQQgghhBBDT4J4UVJaa6h7fWsAv8Wzj+IefRoFL7zD+1prmVve8/uH1MSIaduvrPauGGOIk+WQcRpQGJPd9dOYgAQBiRDFANvChXNjnD2nlsBCWBniNtvX2LtXtNa0WY+CVbjKklI+1nTvQNBpHb7xRGNXAA/wwoYsK9t99kl0b9hntcudK7Nc8mBD19q/HFDFl+Ynd9qhXwghhBBCCDE0pOObKCljDEyt7fmN2XsTeLvuWZ9yDD8+YiIRRwGwaGKEbx1UhWMGNqA0xuzWvnHXFEjZLBVkidn8gJSka63Z4Ht84M61zLy+jgNuXs3zzWBU934DxirShZ4/S0e+51raunzt8Q3d1q59fhNZetfDQAghhBBCCDG4JIgXJecnK+DMT8CWZnYz5sKZnyCP2uV9w7bAubMjvH1hLcsvmsVfPziJFLkBPuKhox2HdsK0qzDW2XlhTNq6XHh/Pa9sLL4eDZ0+p929hg669xpIOgFf2b+y29qEmMNeVaHtXlxof09w7xsIpA+eEEIIIYQQw5KU04uSyzoe4ZPPxTvxbPALmFCYjBfpWWK/A67xSeGDAmyft4SPGDnl8Vh9ga8+Vk973nDZvhV8eu8UUbP9ixZGaZ6q777Pvj1vSBcsyW1+k4Mg4PDqEP/40FT+7+VmZiY9Lt+/srjX/z2PGVaGc+el+P2bbV1rh0+OEdZm9L7wQgghhBBCjGASxIsBkdMuuZALoc2d26XjOUopjC6Or1MmYGNBc9bf1nZ9/9tPb2R2WYjTproEQdDj/toaFldHeXKbQD7haRKe6hFwR2yeg6s0Bxw1DkcBQZbt7RYImTzXHjqeBePC3L2yg8Mmxfjc/PIB29MvhBBCCNFbSqni5ycZlStEN1JOL8Qg8JXLqpzHZY83cfmTLbQQ4f5V6R63+8NbbWTt9n8tE8rnt8fXsGdlsbfA+KjD7SdPJq6K/QJ87dFOmE4VQmuNMabYSyDYeT+BaJDl03vEuOX4CXx1QZyYyciYOSGEEEIMGqUUgfbIKA/HcVBK0anD/LNN87e1Aa0qglXSrwfAcV0c10OpXW9TFaOXZOKFGGBKKTYUHPb/43L8zReSn6rP8JOjqnvc9n0TwoSU3W4W3BhDtVvg/g9NIW/A08W59ZiATh3h35/eyO11aeZUhPjF0dVMjwRgemb0t8cEPhEgZ0LkiKAURFWAO8ANBYUQQggxtqnNjXuvWrqRVe0+n96nnCOnxDj3H+tYsrYTgKirWPqRGcyI2DGblVda02xC/OyFZppyhssWVlATNnjWH+pDE0NAMvFC9JHjOBS0h9pFI7ptb/9/LzV3BfAAbzTnSYU0Z89Jdq3tUxXmM/MrsMGO/xgbY0jYHJUqR9LmwAT42uPfn97Ir19rZVM24On6DEf8eRVp6+3wcbYnoyN8+tFGpl9fx9zfLee6tzrIql1PFBBCCCGE6K92Qhx480pufLONx9Z2cvlj63mntdAVwANkfMs3n2gkO4bzj202zL43reCa55v41ast7HvTCtZklWTkxygJ4oXog4wOc/vqAh97cCPff7mDtI726o9nWbjnr9rS+k5+cvh4ll80izc/Vsu9p00mabN9PqZOo7m9rntpfkvO0JjtXRYeQDsuN7zRxh11aSzFfyy//ngjDVnkHwchhBBCDAilFK835WnObc10JD3NmnTPSsDGbMB2JugOGqUUnSpMowmzPgjTocKD9hnJcRzuXZ2mZZvXyVi45rkmAj12L2yMZRLEC9FLRrv89JVWPnZfPX9fmeY/ntnIB+98lzQ7z1b7vs8l+5RTsU0gPyHm8KFZKSImR6XKUu3kiNtcv/aiu8oyt6L7MSigItz7vWOdRnHfu5091p+qz6C1/JkQQgghRDGQLWiPDCEcpzR71N/7eWV5a4G9KiOUvycBcumCClJO7xMUpdahwlxwfwNzbljOvN8t58x76ulQkUF7/rDuecEgtJ01MTbIp3MheqnDOvzvS83d1l5qzNHRi61IFTrPy+fN5BdHV3PdsdU8f84MytT2R8n1VUL5/Pzo6q6LBAr4r4PHE1W9/4cuqi3HTo31WF9cExmze8+EEEIIsQ3tsLYQ4jOPbuLse9fz97U+Wb172+6stUyOa46esvUzSNhRxBx49qMzOG9eiiOmxLj5A5M4fmpku9N7BoPjOCxZl+HBbRIeTzdkuK2uHdcd+Ex4EAQcNTXOpPjW5wo7im8cUIVjZE/8WCT1F0L0kgISId2t5AvA7cVVUGsMSbKcW1v8xy4Isj1mtveXMYbpkYBXzp/JxoyhPKyJqoCw7X1TOhv4XLRniqcbMty5PE3EUfz7QeOojijpVC+EEEII2qzHATcvp6NQ/Fzw+LpO/nTSZE6c5OxWcB23eW48oZq6Vp+1HT7vr4mSVD6ODfjxoZUULMS1IQhKk/zoD6UUz63vueXxmfVZLpoT3eX9tda0WxdjFXEnQO+k/9GOJG2WZz46gzvq2mnJGc6Zl6LCKWCNfE4biySIF6KXUtrn+4dO5CN/3zrb/Zx5SaLa9JjTviMDdgXZBCQISIQ3f92Pv+dxm+OXR47nJ0dMRCmIqQDX5Et6mEIIIYQYebTWPF2f6Qrgt/jfl5s5tHoCUfr/+cZaS8zmWJBSLCxzMCYLtvhRxrEFHGCIEvBdgiDg7Dkpvv9CU7f18/dIYXYxCchoh7fSms8/Us+adp/z90jxlf0riAZ964NkrSVhM1w4u7gX3/ezlCwjJEYcCeKF6CUTBBxZ4/HaBbXcvyrNwvER5pW5RO3QXRkuJWstEfJEoPgvp1zYFUIIIQTFzwgToz3DholRB09Rks8M1tphW/1nrWV6XPGbY2v41tJG5pWH+c+DxzM54dJpA6KqsMNjT1uPI/68nGxQ/P73X2gi4Wm+ND8O/cjID9WWAjG8SBAvRB+EbYEpnuKTcyNYazFmdATwQgghhBA7Yq1lTrnH+2uiPFWfASAZ0nzn/ePxbH5MXPeP2DxnzQjxgenTacgYLrp/Ha9tynHC9AQ/P2oiKdWzQbFSijea8l0B/Ba3LGvj4r2SJHbyfI7jkLMaT9mdjh8WY5ME8UL0kbVWroIKIYQQYkyJ2xx/OWkS77QWaMwEHDgxQlKNrT3ZJvAJlMtxt69mY6b4WfBvK9J8FrjuqPGE6b4N0VrLlKTX43HmVYQIabvDcviMDvFUfZ7fvN7E3lUhLl1QSZnKDUqz4RAGL5/DaIdcSBocD1fSnV4Me0opwiYgUcgSK2RLNtJECCGEEEL0jrWWmMmyMGU4rlqTtFnYxX7w0Sjt264Afot/rEpT2EFYVenB5xdUdH09IeZw7aETCNvtZ9e14/KXuk7O+Nta7l6R5prnmjjiL6tos7s3CaA3EkGe0O9/jLr8HJxrryC2qQFHptgNS5KJF8NevJCD678PTz+Mrp5C9NJvka2Zjo/8VdmWclzagmLZVUwFcuVUCCGEECU3nPeuD4a4qwg7itw2JfL7VEVQO0irR22ef1tUzuX7V9KaC5gQdUiq/A4rGFoDzQ9e7N5Ab3lrgfWZgMQAjqUPYeCmn8IDdxQX3mqBf/sU0R/cQtobwCcW/SKZeDGshTBw88/g8fvAL8CaFfCtzxApyF70bWV0hF++meH4v67lYw80sirngpaKBSGEEEKIUori86tjqglvTlGPjzr89rgakmrH+9YjNk+VylIbKZCwWexOEi2a4kjj9woPcErcy+dg6cPdF9tbi/+JYUeCeDGsufkcPPd498VcFjZtGJoDGoaU4/KHt9u54vENvNGU577VHRx86yraGfiyKyGEEEKIscS1PidNCbHswlreuKCWF86ZwYxo6SogU07A9w6dgN4mZj92aozK0MAG8UY7UDOt+6JSqHhyQJ9X9I+U04thzTguevosaG7cuqgUqrxq6A5qiGmtabMemaB4VdYxlutf736VtD1veLMpx4EVakyXvAkhhBBClJprfVL4pFxKPpY3CAL2q3B5/YJa/r4yzZ6VYRZUhYjbXJ+eJqtCZK3GAhFliLHjMXgAuVCE+GevxF55MXS0g1Jw3qXkPUkKDUcSxIthLeeG8D71Dey/X1LMvjsufOwL5L3wUB/akFBK0RiEOPGOd1nWkifiKH585EQuXVjBZx9q6HbbiTEXa/M7eCQhhBBCCDEcedan2vG5uGukcbZPAXynjvC1Jxq58c02AE6aEefXx1QTs9kd3scYQ2dVNdEf/RnamlCJFHkvRE5LuDgcybsihjVrLZ2pSiLX/A6dzWDDEQquN2b/oGRx+eKj61nWUgzOs4HlMw81sOyi2VSENc25YinXR+cmGRempFeGhRBCCCHE4OnPSGOtNS805roCeIB7VnZw14oOzq0N7fQxA2tJe2GoqunX8YrBMzYjITGiBMbQ4UVAOmOSs5rnN3S/imosbOgs8Mp5M3mrJc/EmEtlCGKShRdCCCGEGDJWu6StS2AhpAzxXZS0l4LWmsfXpXusP7K2k3NmRYCxNxZwNJLGdkKMIDFtOHZqrNta2FFMibskbJZF5ZYpXl4CeCGEEEKIIZRTHne+m2fvG1cw4/o6PnLvetrVwCekgiDg5JmJHutnzU6irIwfHi0kiBdiBPGsz9WHTOADMxIoYGrS5W+nTiFKAUCa2AkhhBBCDAMdxuGi++ppyxcD58fWdnLV0xsJtDegz2utZVZSc+2hE0iGNFFX8fVFlRxcHe5Xeb4YnqScXogRxFpLkizXHz2eAhNRWFLax8gfZSGEEEKI3eI4DtC/vejbUkrxdnPPbvKPruuk01Qw0EPbojbPp+ZFOXfuTCwQUwGOyQ3ws4rBJEG8ECOMtZYIebYUZBmJ34UQQggh+k9r2myIO99JoxWcPDNJmcph+zn73VrL3PIIiu49hg+fFCOmLQxCVbsyPgn8zQc08M8nBpeU0wshhBBCCCHGrBYTYsEfVnDpI+v53MPr2e+mFbTa3ZuPntAB1x9XQzJUDLcOnRTj24urcEyhFIcsxjjJxAshhBBCCCHGJNd1+fVLLbTktqbHN2UD/vBmG1/YJ0Gh0L9mwSFb4NRpIY45f+bW7vQ2B0qhtcYYI72MRL9JJl4IIYQQQggxJimlSBd61rdvzAYs7wCj+5/z1MYnabOUkyVm82TwWJ71+PmbWV5s1XSq8O4cuhjDJIgXQgghhBCihPLKo4UIb3a6tKsIgXKG+pDEDvi+z2fnV+BtExWFHcWZc1Icf/u7dNjSFC5b7XL7igz73bSCKx7fwJF/Wc23n2kipwa2W70YnaScXgghhBBCiBIpKJdb6jJ84dH1WCDiKO47fSr7lhVLqMXwYq2lyvX553m1fO/5TSgUn9i7nP95fhP1nT7pgiVZgogpbV3+5cl3u6396tUW/vWAKsLIPnnRN5KJF0IIIYQQokQyuFz+2PquhuDZwPLx++tps5JxHa5cG1AVsuxREcbRcMbd7/KXd9qJuYqEp0ryHAro9LvvgbdAINviRT9IEC+EEEIIIUSJZHzLe7dYr2grgCpNMLg7sipECxHWB2E6VBitJRTYIobPmbMTPL62k8ZMQFXE4baTpxArUZY8ogI+M7+829oRk2NEdP+rM5RSuK6L60px9Vgj77gQQgghhBAlEndhespjVdvW4O+02iSeDYbwqKBThfiPZ5v52SstAMytCHH/6VMpIzukxzVcGGOY6BZ4+IwpWKVxFXgmjzKled9cU+Ab76tk4bgIt9W1c9ikKBfskSJuc/0a415QLg05zf+93ExV1OGSfcopV/l+z7YXI4sE8UIIIYQQQpRIShV44PSpXPrIel5qzPGBGXH+8/3jiPQzWCsFpRT1GdsVwAO83Zznu8818V8HptCBP0RHVjpKadoJ0ZQzpEKaqAoI275l0XNWU58x/OifmxgXdbh0YQWV2pYsMI6aLGfP8Dh1+jhCymKCbL/OCaUUqzOKA25egdn8AD9/uYV/njuDpFyUGRMkiBdCCCGEEKJEjDFMcPLccMx48lYT0wbX9C9YKxWlFG809Zx3/s/GLNmgjNgQHFMpaa1Zm/c4/M8racwEKODfDhrH5/ZOEOllIK+1pi4N779lZdd79ZvXWnj5vFqSZPp9XB3WxUcRVoaw9QmCAJeA3bks4CuXq5/d1BXAQ3G2/cNrOjl9mkcQDG3Vhxh4shFGCCGEEEKIErLWErEFUuRwzdB3HjfGsLgmgn7PtvyzZidJOCO/s1qndbnskfU0ZorBqwW+s3QjHab3o/3yOHz3uaZuF1uac4aH13SAG6ZdRWhTEfK6dw0KtdasK3h85N717POHlXx+ySbaVBhVgt4ISoH73jeT4pq1238/XdfF87ySPL8YehLECyGEEEIIMcqV6YA7T5lCbZlHMqT50r6VnDs3iRkFpfR5C28253qsN3T6vQ5aFRB1e9424mpuretk7u+WM/P6Or7xdDMZJ7LLx2uzIY69bTVL1nbSmjP8aVk7n35wPdkSzIV3jM+/HFDVbbb9pLjL4ZOjPcYYaq1J6wg/fzPDN55pZWXOI6+kGHukk3dQCCGEEEKIUc6zPodPcHj0jKkopYjqACcYHfunE9pyxqwkP36puWst7immJVys7d1FCtf6XHlAFbe9005u89y3aUmPRROj1F7/TtftfvNaK4fUxPjwjJ2XrXf4ljXp7s/995VpCnYi4b78cNthrWVSJOD1C2r5/ZutVEVczpydJEWuR5l+OyEO+dPqrkaL//vPZh49axr7lukeAb8YOSSIF0IIIYQQYphQSoHjogDjl7YU3wQB5Q7krcbD7ta+7OFEmwLfWFRJzlhufbuNmWUhfnF0NQlVoLfNCKy1VIeKgfGfl7VRGXE4aUaCvy5v73Hbu1ekOX1GFZodB/FRVxF2VNcFAYDZ5SF6fUC74JqA8TrgawsSAPh+psf7qbXmlU35bpMSLHDV0k384bjxREbNGTD2SBAvhBBCCCFEiSmlyOBRQONgSCh/l5nPLWPDfvjPJuKu5ov7VVKpC6gSjafL6Ah3r+jgr8vTHD45yvnzyojb7A73UQ9HSm1/33fMZPnvA8v510WVOFiSetev93v5aDwN5+1RRkhbYhTYq7Jn3vy4aTE8zE5C+OLc+Z8dVc3Lj9woAAAgAElEQVQlD9XjG0h4mt8eX0NKFbo1pNtdvt/37RBKFbcPiJFLgnghhBBCCCFKSGvNxiDEpx5s4LF1nRw4Mcpvjqum2i3sMLBUSlGf0+x30wq2JG9/83orr54/k/Kdhou942uP/3i2iZ++XCw5v3tFmntXdfD74yYSo2fn+qG2ZS/7loA9o8Ksz1rWdRTYpypCkp4XNxxTILX5//taKZ5RIX74civfe74JY2FeRYj7Tp/KHmWWL+9XyU9easI3cMasJKfPShDsYiuCa31OmRai7qJZtOQMlWFNnB2//wPBGMP8qggzUh4rN2fjFfDtg8YRVUFJLyaIwSVBvBBCCCGEECXUbl3Ovmctz28oBnqPr+vklDvX8ODpU0jQswEbANrlBy82sU31NemC4fa6di6eG9ntsWEZ6/Dr11q6rT34bic5q4fViDmtNW2EeG1TnpirqC3z0Fi+9Fgjt7xdLG2PuoonPzydWVFbsqB4Ux6uea6p6+u3mvNctXQj31tcwTf3S/Hl/SqwFsLKEOllLwHP+pThU1a6Kvo+S5Ln8bOn86dlbaxu9/nEXmVUh43shx/hJIgXQgghhBCihHyruwL4Ld5qzpMzkNhBHfOOuqNvb60/FBBxFPltrhJoNfxGVTXbEAfevJL1ncWLFgdOjPCb4yd1BfAAGd/ypSUbuOX4iURKUEWgtebt5p6P88KGHBmjSJAnxOZ95SMse22MIUGGT82LopTC9wsjavuE2L7h9nsrhBBCCCHEiOYoy6R491xZZcQhtJ3Z3ltY4/Pl/SqJbRO0T4w5fHBGYrez8ABx7fOf7x/fbe1z8yuIqNLsty8F5bj85J/NXQE8wMr2Ag0dPfd9r0v7FEoUixpj2Hd8hPe+PR+qTZBwepex1lqTJky7CmN6OUt+MPm+T6EgAfxoIZl4IYQQQgghSiipfP5w4iROuXMN6YIh6ip+d3wNCXbchMxayzjX5/ULavnTsjYSnuaU2s1jw0oQd6nA58OzYhwyaQYPvdvJQdURZqdcwnYH5f1DIECxoq17R/4NnQGTEi4VYU1zbmtA/cm9y0g5hhL1/COpfe46dSqfe7iBhg6fj+2Z4pJ9yqAXpfO+cnm+yXDZI2vY0Onzib3KuWL/CqJmdIzwE8OPBPFCCCGEEEKUkDUBC8td3rhgJumCJeEpYhRQu5hZrkxAOQGf3TOGtZYg6Dk2bHdEbJ7ZUcXcPSIYY7DDKIAHcG3A5xdW8Jd3tpbOuxrijuKpj8zgG09sYEVbgQv3LOPcOUlsCefce9bnsPEOT5w5FZQiogLcXgbhbcblpDvquvoZ/L8Xm5iUcLlkXhQT9L17/C45LjmjiGqDKUGVhhh5JIgXQgghhBBiF5RS5JRHdnPwFLL+TkuTtfFJ4pN06fM+6v6MDeut4sWB4Rn4GWPYuyzEHSdP4drnNxHzNP/1/vHElU+5G/DLI8eRN4qUYzAlDOC7nj8ISBAU369evmdaa55dl+nWkBDg1mXtnD83jlEhClajlSWlfKzp/2uvlCKtIvzs5RaeWNfJqTMTfHRuUjL+Y5AE8UIIIYQQQuyE1pomE+KLj6zn6YYMh0+O8T+HTaBM5QZ1j7HWGrSDxg5ooD+UwjbPMdUOB544Ea0gpoJi1QAQsgVCwG7EwSVnrWVOeajH+hGTo2SM5sP3rOXZ9VkmxV3+cOIkFpa7aNO/964Dj4/8fS2Pr8sA8PCaTl5tyvHdxRV4prCLe4vRRBrbCSGEEEKIYUspRYcK0UyEdhXB6MHPQbVbj9PuXsNfl6dZ3xnwp2XtnPOPdXQweA3MsirEs83wucea+cWbGTp0tGuW+mgTBAExCkTs4M5V7w9rLdVRxWfnl3etzSrzuGxhJZ96oIFn1xez5Os6fE65cw0dtv/nb9borgB+ixveaCVrnWJjPRWmXUXoVKFRe26IIsnECyGEEEKIYUkpRSthzr5nHUsbMqRCmp8eVc0Jkz28XewvL6WcgZcau+8ff2JdhnwvZ6wH2qXTumQCS8xRJFUe24fgVDkud63I8KkHGwC48U347Rut/OPUycR3NHdeDJqYzfOtAyr42qIqsr4l6YHF8ti6zm63SxcM7QVb3GKxmeM4m/sT7Lqiw9HgKLqV7ic9jaPgjbTDuf94l7rWAgfXRLnpxElUDHKliBg8kokXQgghhBDDUl65fPOJRpY2FLOPbXnDx+5bt1vZzP7wtCIV6v6xeXzUwVG7DpB85fJwvc8ev1/O3BuWc9Ctq1ib94ql8b3UFjhc/dymbmuvbMzRlJcAbbiI2DwVZKlxcyRsDhfDgdXRbreJuoqkV8yQ55XLBhPm5hV5XmnXdKrwLp8jSsCX96/stva9wyYQWMWJd6ymrrVYUv9kfYaP319P5yBWiojBJUG8EEIIIYQYljJG8Xh99/JhY2FlW2FQy4XjqsCvjqnB3fzJ2dNw3bE1JNWuqwE6cTn/3nV0bB5qvjbtc+F960j34UKEwuJtZ8a8lpLpYSuufK47tpp5FcX98hVhza0nTSaqfBzH4dlNhnk3LOdTDzZw6J9Wc/njjWRUz7312wrZAl9ZWM6zH53BL46u5tXzZ3LytAgdvuk2fg/gkTWdBEpCvdFKyumFEEIIIcSwFNOWwyZFWbXN7HCtYEbKw9rB68itTcDRNS51F82ivsNnUtwlhg+9aFDWUbBk39O6/MXGLKYPubSUE/Af7x/Ph+9Z27V2SE2Uco8+d74Xg8MYQ7Vb4MHTp5AzENKKhPJRxqeVEF9esrbbW3fz2+3818ETiO7iukzU5pgbU+xRG8KYAtZaYm6EmKvo9Lc+4n4TIig7vPsJiP6TIF4IIYQQQgxLnvW5+uDxrGzzeXxdJxVhzc+PriGu/EEPXj3rU4ZPRUKjVKHXY9oSnqIirLtlSo+ZGsftwwR4EwQcUe3x4rkzuOXtdhaOC3PE5Chxm5MYfhgzxpAgR0LRbWydRdGS63n+5ALbq+jsvWMC46rAHz8wmfPvXUd73jA16fL744uVIuY9J4hSSvbJjwISxAshhBBCiGHJWktK5bj1xInkbbGB15Zs5mArzugO88KGHM05nyOnxEipwi7nnSVUgX98aBrn37uOZS15jpwS45fHVBOlbwF42BaojSiu3C+xOYjLSgA/QiWcgM/Or+CqpRu71uaUh0j1s7LCMQGHTXB4/fyZZANL1IGk6t7ZPxoUcDvasC2boGYa2VAUX4L5EUuCeCGEEEIIMWxZa4mRL3aB3yabOdjSKswxt73Lm815AJIhzQvnzGCCs/PO4soE7JWEh8+YgkXhYojRv67h1nafD6+UwnVdjDG9rgwQQ08FPp/Zp4ypSZeb3ipWVly+XyUpleuROe8tbQKSBCQ1YGHb0ysa5HFu/F/sQ3cWFyIxIt/9LZ1V1cN+hJ/YPul2IIQQQgghxE5orVnakO0K4AHa84arn93Uq7n1QRCQsDmSNkvU5ktSzpxVIV5LO3zzmVZuW12gU0dG3GxwX3u0qwhtKkJej61O6lGT5SMzQtx03Hj+/X1JkjYzYAG125mGLQE8QLYTfvN9QoXB6yshSksy8UIIIYQQQuyEUoqmbM9M98ZswHu3MSulCLSLBTwbDEhgph2Xv63M8MkHGrrWDp8c4+YTqomNkLnxGR3mRy+18v9ebMJYyyf3KufbB1URNWMnsAyCgAgBDGARhVIK29rc8xuNDeggAGfgnlsMHMnECyGEEEIIsRNBEHDc9Dgxt3um+/L9KgltE4FZ7dDgh7j8yWY++fAmXm3X5FXpM8ytgcNVS7vPjV+ytpP04LcK6BetNW80+3z3uU3kA4tv4BevtvDI2gyOMzajSsdxSKswaR0hp0Ilq6qw1sLEyRBPdP/GUR+kEImV5DnE4JMgXgghhBBCiF1IqQIvnDuT8/dIcdKMBA+dOY09y3S3THub9djvphX89vVW7qhr5+BbV7G8w6J16T9ym+2U5I+UNmVaa+5dle6xfueKNHYMzja32uG1ds3Rt69h6nV1fPyhRtpUuGSBfCYUQV39W9jvYJg0Hc79PPbYMyj0dwO+GHJj77dECCGEEEKIPlImoMbN86NDKrnh6HEsKreE7db59Y7jcM+KdLdZ3QDff76JQolrllNOwL8eMK7b2uLqKMkRslHWGMPRU+M91k+cHh+Ts83T1uO421fzdnMeC9yzMs3lSzaQK9HO58BCR8UE/MuuIrjqF+Q+8GE6nLHVg2C0GSG/6rBkyRKeeeYZVq9eTSaT4eqrr2bcuO5/vDo6Orj55pt56aWXAFi4cCHnnHMOsZiUigghhBBCiN1jrcWxxZB8e0nMikjPYL0y4uCo0mY8beBz+swoe1ZO48a32lg0IcKpM+MjZm68MYYFVWEuW1jBT19uxlg4Z16K46fGCIKxsyd+i+acoT3f/eLFvas6yB06nlCJnsMYQ9bxwPG2f/KKEWXEBPH5fJ699tqLfffdl1tuuWW7t/n1r3/Npk2b+MIXvoBSihtuuIHrrruOyy67bJCPVgghhBBCjCVBEHDYpCizyjzqWosZ+mRI87X3VaFM6YPriM2zf7nmgIPLN4+YK83c+C0l3KXooL8zUZPj3xaVccX7KrEWwsoQGUNN7bZVHta4Gvxt4vgF4yK4yo6cPRJiUI2YIP7YY48FYOXKldv9fn19Pa+++ipf//rXmT17NgAXXHAB1157LQ0NDVRXVw/WoQohhBBCiDEoSZ4lZ03jifosbfmA46bFSVEYsIDYGFOy7vdKKTpUmNVpn86CZW6FR4r8gM4RD5kCITZvSRjDwWoUn18eXcNnH24gF1gmJ1x+dUw1cVWQpLnYrhETxO9KXV0d4XCYWbNmda3Nnj2bcDhMXV2dBPFCCCGEEGOQUmrAs8pbGGOIk+XEGo1SzogqDe9QYU67ey3Pri8ec3XMZelHp1PGyPkZhpLrFsMq3+/7iADP+pw6LcSxF9aS8S0xV5FSA3sBRYxsoyaIb21tJZlMduviqJQimUzS2tq6w/stW7ZsMA5PDBF5f8VAkvNLDCQ5v8RAGu3nl1KKVPVUCqEYmzIBUxMOnRvW0pluH+pDG5ai0ShvezVdATxAQ6fPD15o4nPTsrQ2bdrJvXsa7efXtmLJMkLjJnHdK8Vz65N7JslvXEtne1u/H7MNaCjR8Y1GY+H8mjNnzk6/P6RB/O23384999yz09t89atfZd68eb16vO2NYbDW7nQ8w65eIDFyLVu2TN5fMWDk/BIDSc4vMZDGwvmVUSGuXNrEda+tBqAirHniwzOYOynf76y8dl2MVWgbjLoMqeM4PLisZ8Z9RbtP5fiJTKiq7PVjDcb5pbXGWjtoFRY7s8lGmH/j8q6pBD95qZlXzq9lcrVUMAyEsfD3qzeGNIg/9thjWbx48U5vU1nZuz8aZWVltLW1dQvarbWk02lSqdRuH6sQQgghhBgZmguK617bWonZnDN85bEN/PbocYQp7OSePSmtaTYhfvxcM/WdPl9YWEFtwuk2Xm53aa1psyHSviXqKiIEJX38XQmCgA/OSPCVxzZ0a672ufnlhAgYLpcsAuXQbj2eXpdhatJjZtIhZnJDdjyu63LdP1u6jRXsKFiue62Fby5M9Ku0XojeGNIgPplMkkwmS/JYs2bNIpfLUVdX19XYrq6ujlwu122fvBBCCCGEGL2UUtR39AyAl7fmyVtFuI+P106YRTevYGMmAOCPb7Xx0JnTWFSuS5KRV0rRGIQ46i+rWd1eQCu48sBxfG7vJBGb3+3H761yJ+Cxs6bzzScbSRcMX92/koVVLsYM3jHsjNaadzo1h9y6nFxQDJo/MD3OdcdMJGaHLpDfHj3UByBGvRFzjrW2trJ69WrWr18PFLvRr169mo6ODgBqamrYZ599uPHGG6mrq6Ouro4bb7yRBQsWSFM7IYQQQogxwlrL3PIQca/7dsoL9igj6fQt6NZas7Qh0xXAb3H1s5vI2J4z4fsjp1y++tgGVrcXLzwYC99ZupG2YMfbQQeCa332ThpuPn4ifz2phg9OdokMkwAeoMM6fOWxDV0BPMDfV3XQmBu6knrf97l47/Ju51rC03xi73LJwosBNWIa2z366KPcddddXV//+Mc/BuCiiy7ikEMOAeDiiy/mj3/8Iz/84Q8BWLhwIeeee+7gH6wQQgghhBgyCVXgibNn8MUl61ndVuBje5bxyb1S0I9u8TG3ZzAdcxVaUZKxaDmjeHVTz0zy6rYCEysGr7M+FLvrRygG7kGwixsPssAqGjt7HlRLNmBGuLSvk3Yc2gIHBaScgGAnL0aFU+DV82u57rUWNPDxvcsp1wWGzR4EMSqNmCD+1FNP5dRTT93pbeLxOBdffPEgHZEQQgghhBiOlAmojVpuPn4CvlUktEGZvgfwxhgWjIswtyLE283F4DbkKK5aPJ6QLZRktHlCG06rTfD9F5q61kKOYm5FCGulOdoWKcfwuQXlXPrI+q61cVGHWeUeth/v7Y5kdYh7V2W59oX1RBzF1YeMZ78KF89uP7OuTEAFAd9YmADA97MSwIsBN2KCeCGEEEIIIXrLGEN0SzS1G0FVkjwPnzGVh97tpKHT54zZKcp1oWSZX2V8Lt+vgqZcwB/famNa0uMXR1cT62MDvtHOBD5nzYoT92r49Wst1KY8vrV4PEnyJbmYAsXtEy83+Vx4f33X2gm3v8vrF9QyyQt2+p5L+bwYTBLECyGEEEIIsQPGGOJk+dA0D6VCxUxriSvcYybLtYsruOqgcShrKXP8nZZwj1URk+Os6R4nTJlIWINrc1hTujcjUA6/erWp25oFbqtr54v7JGkvGGKOxQYSsIuhNWIa2wkhhBBCCDFUgiAY0GyrawokbZYEuWERwLuui+u6XaObh4sgCIhRwDGlq4bYwsWyZ6XXY31uRZjr3+rgzH+s54evdtCpIyV9XiH6SoJ4IYQQQgghBFAsKU/rKD95rZOvPNVKXcYlr3oGtkPFcZwBu7gQBD6X7FNBbdnWn3dxdZQpCZfLHl3Pk/UZvvX0Rj7/yAZyKlTy5xeit6ScXgghhBBCjHpbgr7B7PY+ErUR4uBbV3WNvPvFqy08dMY0FlVojBm6jm1KKdIqzAOrO6lrzfOROSkmhMwOG871V4ocj501jTVpn7CjqYw4LLp5Rbfb3FHXzo+OmEC4pM8sRO9JJl4IIYQQQoxaWmvaVZSNNsI6P0zOjaK0fATeHqUUr2/KdwXwW1z1zEY67dDm/tIqzAl3rOHC++r5ztJN7HPjCl5ttTiOU9LnMcYQN1n2iAfMCOcBS2uu+8WLREgzvDYZiLFG/oIJIYQQQgi04xBor+RB0VDSWrMhCHHmPWuZdf07nHbXu7y8KU+bDQ/ZXm/HcbDO8H2d9XZeFkcpSt7Nrw+UUqxq93l1U65rzQJXPtVIOhiYcGZLxUYMn28dNK7b9645ZAJxJc3txNCRcnohhBBCiDFMKUWHCvPHt9p5eE0np9UmOHlmnGgw8meUp63L+feu45mGDABvN+c57x9rufvUqcTiLo4d3DFuGR3msXU5/vxOC4dNinLmrARxmxs2Jf7WWvasDDOrzKOutfjaaAVXLR5HTAWUsBF8nxW28+QFA2aAc+Ku9fnEHglOnpngxcYsB0yMUukZtJERgGLoSBAvhBBCCDGGdeLx8QcauHdVBwB3r0jz6X3K+c+DyvFGeKBi0Dxdn+m2tqEzILBQsDBQuXClFFrrbl3mA+3xw3+2cM3zxRFmt77dxl+Xp/ndsROIkR+gI+m7JHmWnDWdO+raWdVe4GN7ljExZIZ0P7y1ltllHtNTHqvatp6T/3pAFSknoK/N/B3HwRjT64snEZtnelgxY6qLMbmhLEoQApAgXgghhBBiTMta3RXAb/Gb11u48sAqPEZ2EA+WvSrDvN60tQw7FdJUhB3iutDn4K83MjrMmg7DS41ZDp0co8I1hG2BTuvw45eau932gdUdZI0mNow2WBtjiJPhY7PDKBUhCEo/ym1XfO2RsQ6BhbAyxCiQJM8TZ0/nN6+1sKylwGfmlzM7qQiC3p+jvnJpDhweXt3J3PIQc8tcYja36ztSvJAwXComhJAgXgghhBBiDNMUS6a3rVaOuKOjbVJKFbjpA5M46Y53WdfhUxbW/P6ESVSE2O4sdqUUvip+PHat3+egLac8rn2+mR/8c2uw/vsTajhlSghlLSFHkfG7P+b29qAPB32ZVa+UogOPnNVUztyDvNKE+rlVIatC3PBWmm89tZFsYDlhepzrj6shFmRIkOHy+fFiCb0J+lQd4DgOLzZbjr1tOcHmt+CkGXF+ffTEXgfyQgwXo+MvtBBCCCGE6JeICrh0YUW3tW8fNI7EKGjcZYxhZtjnmY9M560LZ/HyebUcNtElvJ39/r5yWZ51+eySTXz+sSZW5byugL63sjj86D3Z9suXbCBtHeI64NvvaZB2wR4pImroytRLpUOFOf++9cy8vo55f1jN919qI6P6PoBNKUVjDr7+eCPZzZH2vas6+OnLLeAU3wvf9zF+oc/l/W2Bw89faeaWk6bw6FnTue/0abha0TrSi03EmCSZeCGEEEKIMSxsC3zzfRWcPSfJU+uyHD01xpSYQpnhs097d1hrSJAloSnuZd7OtQmlFOsLmkV/XNGVpf3LO228dn4tE5zeX8woGHo0f2vNG0ChAp9zZsd5f8107lnZwcE1URZUeUTMyMkCO45Da1DsJJByAkwQoByX615r5aE1nQD4Bq59vokzZyfZI676VM2glOL5DT0vsDy8poPP75MguhvHrrXmi/tW8bH71vFOS56KsOanR9cgs+LESCSZeCGEEEKIMWrLmLWoybEgafjsnhHmxHwidnQE8L2hlMINhXlhQ47KyNZWdwUD17/eiuv2PucV1ZZFEyPd1j6xVxkRVSxNj9g8e8YDvrYgzsFVEBtBAXxeeTzWaDnl7npOuHMdd73rk9MhskaxZG2mx+2fW59F676FGsaYHq8fwHHT4kT17u1Htxa+tGQ977QUz+3mnOHiB9YRHyVbR8TYImetEEIIIcQIs7szzgvKpU1FeLXdoZUIBeVirSUIgjHVvMtohwY/xBVPbmLJ2k5uO3kqZ89JdX2/Ktq3/vUJ8txx8hS+vqiSI6bE+MHhE/jWQVW423T5t9YWS8KHsNt7XymlWJ9TnPTXd3mxMctrm3Kcd+863mwNiDlw8sxEj/scOjnWr59xXMjyoyMmEvcUCji1NsHF+1Sg7e69XgZ4tqH7xYaOgqXTHznvgxBbSDm9EEIIIcQIkVMeHcZheUue2eVh4srHs33bu55IlfH0xoDT716Fb4qN1a4/roaTp4ZwzK4fSzku7cYBFDEd8P/bu/fwqMpz7+PfteaYSSYJCQFCgEDCwYIcDHIWPIAHVDygBWVjpdq6bfdud7eFXaUH22q1vtbq667uvlotVq2FWkCiqKBF4wYF1CJalEPkJCZAgjlOMpmZtd4/YkaGBEhCyDDh97kuL80zK2vuGRbj3Ou5n/sx29Ad/FRzKOJixLOfEvyyhv6pjytZc00uq/fU4HWYzB6cSjjcfJb5aGzbJsWu4/aRfupHpJJsWlhN6+9NB9W2k4ht4DIs/EbiJPIOh4PF26ubjT/2USW/n5zBrEEpbDpYz9OfVOJzmtwzMYueHtp1Q8hrh7h2kJ+RWV4chsE7pXVcsmw3r1zVlxSal9q3+jVgcU6Oj7f2BaJjaR6TZKehLeMk4SiJFxEREUkAEdPJC7vq+dfXS7FpTL6XTM9hWrYTWpF8N3Gl9+Dm5SU0TUBaNvzbmv2cf8MAUltaMH6YoOHilT1BfvS/B6kNW3xvZDe+NyKNpAQqC2/idDp5clNFNIEHaIjYPL+9ihev6Ev/VBepBGlPmm1YYZIA68sG7xHDwXuHbG54dTf7AxFG9/Dy/GU5ZBjBTql8sE0HtbaLypBNqssgiTDONtz8sW2bId3czcYHprmwDIOkcD33TejGL8d3p6GhcVmCEWnfkgyn08kjm77gno3lMePLi2u4caCnTV3zD+cjxKILs/n6yn28f6Cevn4nz12SQ4oRUhIvCUfl9CIiIiIJIGA7+cGb+6P5hmXDv/69lGq75ZJvh8OBy+Vqvi7ZdHAgEJsI1YQsQkd2ZDtCU0n1jatKKA2EqW6wuGdjOa9/Vo/D0bay8yZhw0m14WVn0EW14W1zN/gTlexq/lU4xWVQkGGSYtV12Ex5ABdXFn7G/i/f9/cO1HPr30upw9Uh5z8W0zT5pNpg6DM7Gfb0p+Q/9SmrPg+16b22LItJvX2M7vHVevVB6W4uy/NT2dB43bitEH67nkO7tmFE2r+zgY1BWV3zRL2sLnJCy0hs2ybL0UDh5dns+mY+677ejxFpNobVvpsCIvGkJF5EREQkAYQsCByxx3h5fQT7iPbahmEQML0s2xNi/jsVvF9hUG98NYtqBQOc18cX8zsjunvwHudboWmarNpT22z8L9uqCNpt/0ppmw7eLosw8KlPOevPuxj41Ke8UxbBNtt3Q6CtwuEwc89IpZvnq9jTPCY3D0unoaFjG/tVNFjN9odf+3kdoU5ojV5lubhhVQlVDY03JBoiNje/VkKgDQW5tm3jMmx+PLY7r17dj5eu7MvD5/Xi6S0VeB0dO41tRcL8+8humIe9NS4T/uWMVMLhE9v20LIsku0G0qnHbwex2jmrLxJvKqcXERERSQAe06Kgh5f3D9uC68J+ybiOKPiuxcWNq0tZ/WXC/T+bK3jo3B7MG5gEVphAWQlPX3QGd6w7yN/3BhjXK4kHp/TAbzQ02x7tcLZtc1ZW887h43p5cRt2m8vOa2wX81btipazByM281aX8I/rc/HTOclVOg188C8DWFZcg23bzBzoJ9UI0a4a+mM9j9vE4zBiSvfH9UrC1Rl13IYR7cjepC5sUx+xSW3DvRcPYSqDEf5tTQl1YZv+qW5emJGDxw526KuwbZtsj8X62QhvHhcAACAASURBVP25Z2M5bofBj8dkkuEMd/ifi0iiUhIvIiIikgBSCLH88hx+vO4g60rqmNo3mZ+N647Pro9JouosM5rAN/nVhnKuzc8lhTChUIhUgjw4KYM6KxOvYeMhiHWccnrLsvhauoe5Z6TyzCdVAJzd08tNQ9OxIq1v/tYkbDdWEhyurC5C2O68jbtt2yKVem4a5MEwDMLh+pOyPjqJMM9flsM3Xv2cL4IWwzI9PDa1F0l0bALcEicW0/om89rer66Jvn4nPgdteq1uO8wV/dxM69ufkAUe02688XOc66Y9XHaYIckmfzgvEwCnHcI+Cc8jkqiUxIuIiIgkANu2STOakm8Dn2njsOpalYcdeYxt27jsUOOKbLv1uZzPDvKbiZncNSGLiGXjc0DyETcRWsuNxagsL5sOflVZUNCjcVa/sxuNtbdZWms57TDnZDnZ/C8DCFk2HpOTlgAfKYkQT17Yi39/Yz+r99RyVpaXJ6Zl4zdCtLWnnsMK4ycMBmBzzMqNE2VZFo4vp96P9jRO51dbI4qcTpTEi4iIiCQI27Zx2iH8cNTSYp9pM61fMq8dNhv/4zGZpJgROqJK3Ws34IXGzkrHybct00WNZeA1wWOHYjqx+80wyy7P4btrSllXUsekbB+PnN/zuGX9icroxAT4cE03fx4/rzsN9MBh26SYoYTZ3q4lYcPJoYiDv/2zmj4pTi7o6yPF7pxO/yKnAiXxIiIiIqcAFzaeUBCjvg7bm0S9y3ucDd9a5qOBP13Yi9V7A6z9vI7rh6RyRroD2rnlV3sFzCR+/W45hTtrGNHdwwOTe9DD+VXyaFkWGUaQP17QgwbbwG1YJB1R1m8YhhKzDmDbNh5CeL78OYHzd0zTZGetwYQln0a3STyjm5vXZ/Yl2W7bPvIuA9wN9RjYhB0u6k2lRpIYdKWKiIiIxJkTG8+Oj+D+/8Kur4NkP96f/jd1OXlE2phx2baNz65nZj8X1/Zv3Ffbsjo3gQ+ZLv5r7YHo2vmdVSE2lQVZe21fUvhqT3nbtvHy5cz+YbP6QcNFreVgT1WIvDQXvjbuay6Jz+FwYJrml9fvV38H6mwHP3n7YDSBB/jkiwY++SLE2emtv+njiYRxbVoHf3wAamtwTrqIlG/eRo3j5G/7J3KitMWciIiISJx5Q0H47UKo/7JBXG01/PYOvPWBdp8zEokQCsWnbDpoO1iyvTpmbHdViNpW5OFh08VfP60jf1Ex5/1tD/mLinn3kIXRSVvPdUWmw4nlcGGaifHVP2B6WbkvwsINVbxfYVB32BaJNlAfaZ6o14WtNu0j766rgYd/BtWVYEXgrZfhtWW4zM5rrCjSXonxN1lERESkKws1NCbuhztQgpGoe2rZNv38sTOaDgO8zuMnSAHbwQ/fOhCdlQ9ZcPNrJVTZKiBtK9M0qTGT+M2HNdy8ppyigzb1puf4v3gchmFQb7ipNjzUGe42Jc/HU2e4+bc39jP75X38302HOO9ve3hmey22o/HPP9m0WHh2Zszv9PQ5OCvL2+obVqZpYm//Z/MH3vtfHA1tK8kXiQcl8SIiIiJxZrvc0DMndnDQMCIJukY31Qzxh6m9cDu+Su7umpBFUis66wUjdsx+6gCf14Rp7AgnbVFtuznvb3v45fpylhVXc/mKz1i+M4DpaP91ZZomh2wPN7x2gMF/2sn1q/ZzMOLusFn+ettkWXFNzNjdG8qotRpjjkQijMpwsG5WLnOGpPKjszPYcF1//Ict0zge27ah/6DmD5wxkojrxG9yiJxsSuJFRERE4qzO48P46X/DoGFgmnDmaIz59xF0e+MdWjOmaR535tWyLIanwY4b83jjmn7suDGPm85Ixm2Hjnt+n6OxUdnhZuSl4E7UqoQ42l8XYUdFbD+EB94/RGWk/SlAje3i2pf2sXpPLXVhmzc+C3BF4T6q7Y5ZS97SkvYjO/l77BBn+i0enZzBj0f5SbPr27RsxLZtwqnpMPtfwfnlDY0hI+CKuYTUR1ESQGLe3hURERHpQizLojatO57bf4sDCGMQdHmwT6U24qaDatvFhtJ6Mr0OBqW7jrmtl8OOkEqEs9IMbDvY6r3f/UaIl6/qy/y3DvDugXou7pfMneO6423nfvSns8MrIZr4XMYJzeI12AbvHYgtOd9yKEjQguQOKJZIMi2m5ybz8u6vtkj8r9GZ+IxwzDXUmLRb7b61U+9w45k+C9e0q8CKYDnd1Lk8Ld9FEDnFKIkXEREROQVYlkWd87BS3pOcTBiGQS1u6i0DpwlJRgSX1fJMuWEYHAg7OfsvO6kMNqZNo3t4WTEj57jberV1i7imref+59xM6i2DZNPGYdUpgW+HDLfBuTk+3tzX2CDRAH49sQepjgiR469saJHDsOnlc1Ia+KpLYYbX0dgQrgP+kNxYPD4tm1d31/LW5wFmD0plVHcXptX6cvnWChoOgu6krwaUwEuCUBIvIiIichqqNrzMfGkfG0rrcJrw4zHd+c4wP167+XZ0YcPJXRvKogk8wHsH6vnnoQbGZ5gd3gHftm3cdgg3cLKr6BtMF0G7sfN9ihHGsFq3lZ1pmlTbLsqCNm7TIM0FyTScUvvaJ9PAc5dk8+6BIB8fCjIjz093l0UkcvxlDUeTaoR55uJsrij8jEDYxusw+NNF2aRw4lsAhg0nKz9r4Fuv72FcryRGZHrol+okmZAWU4gcRkm8iIiIyGnGNp385r1yNpQ2bmkXtuAX68u4ZqCffu7mx4dtKKltPnVbWhvGyEzcfbXrTC8/WneQZz+pIsVtct+kHlzV34u3FWv3q/Awddketn7ReNNjWl8ff7ooG99xKhM6k23b+Ox6zuthckEvH5HIid9ksK0IZ3VzsPUbeVQ2WKS6TXxtuPlxLHU4+fbre2iI2Ly1L8Bb+wIUfR7g5Rm9SaH5zSWR05Ua24mIiIicZuosg3WlzZPNj8qDLXYZ95kW3x/ZLXbMaXBuHx+R9tZlH4XD4cDlOvl7mpsOJ89uq+ZPH1cRsaEyaHHr30spazCO27jPdDh5/KOKaAIP8NreAO8daPn9izfLsgiHwx1WJeCwI/jtevq4Gki163F2QAIPEAg335ngn+VBME6991QknvQ3QkRERCTBmA4HNYaHGsNL2Gz7THiyw+ay/snNxgt6JFHfQqFmJBJhbJaLZZf34dw+PmYO9LPxuv74aX9Z9pEMwyBgJvF0cZD/WFfBPyoN6s0WygI6SJ1l8NLOmmbj60rqjpuIW4bJpN4+ir7enzeuzeWmYekA/PPQqZnEJ4pkp0FPnyNmbHr/FFwqpheJoXJ6ERERkQQSMpy8X2Zx69/38nltmLlnpHLX+O74rNaXcduRMLecmca2Lxr4y7Yq0j0O7pqQxR+3VHAgEOaeid1JisSez2M3MK2XgwkX9cBhgNsOdej67xrcXPniZ7y7v/F5//BRBY9P7cXsAR6sSMfM9B7Oa9qc09vHms8CMeMFWV6sY8wsG4bBFxGT+W99zuayID6nwd0Te/DDgkxm5PmJRFT23V5+o4HVV/fjm6tL+LA8yMW5yTx6Xk+8BNXYUOQwSuJFREREEkit7eTSF4ppqjp+4p+VZCc7+eHwlDatS06K1PPgOZn8cmIPPjkU5I9bKnh+ezUAE7OTuG6Au1mpfCQSwUsE7A5pRB6jKkQ0gW/yq43lXNKvD/4Ofi5ovJHxneHpvLkvQNG+AE4T5hdkkOMzjnlzImg4WVB0gM1ljd3SA2GbHxbt55Mb8+nmiJxSje0SjW1Z9PeGWXF5NjYmLiOC9xjbGIqcrpTEi4iIiCQI0zT56GCQI5YNs7y4hluHpZLSxvP5TIvHP67hx+sOxoy/uKuWmf29OOjY9e5tZRrQuDHayZFs1/OXi3sStEwcJniJ4G6hO//hgpbJ+iP6CdhAaW2IXqmWZoxPkGVZJDc1sTsJN4tEugIt2hERERFJEJZlkZfWfJ34qCwPXrPt6U4kEmFy76Rm49P6+nAZnbsOOc3VWAFwuDvHdSfN0fGl9E0au7c30M2oJ9Wux32UrvS26aTa8FJteHE5jGb9BJwmDEh1acZYRDqFZuJFREREEkiGy2bhmEx+/W45lg0D093cPSELl932dcO2bZOf5mJ+QSYPbSonbMHMfD/X5qdgRTp3q7RkGnj+0t6s2hNg08Eg1w3x0z/ZxIrzGvN6w8XynfX8aO1eahosrhucyv+Z3JOdVSFe2V1LD5+DP0zNxtcB+6SLiLSGkngRERGRBOK1G/iP4X5uOTOdYMQm2QmpRgOW1fZZYNPh4JNDDbgdsOaa/hgGhC0Lp935ZfRNe5pfk+vi6wM8X26JFv/EuKzB4Na/l0Z/fnZrFSO6e3jmol4EImBg4zfDcBKa74mItERJvIiIiEiC8dghPITAAdjQjvwdgCrLybde28vOqhD3bCwHGkvDP52Xj6sDt49ri0gk0uF7z7eXw+Hgnb11zcZX7q7lG0OSSW0qvz81whWR04TWxIuIiIicrgyDvTWxyXrYgvqw1nZDYw+Cgixvs/HJvX0ktaMHgYhIR1ASLyIiInKachPh2oGpMWP5aS58qtUEGkv8s5MMfjI2E+eX35rPzfHx3eHpKp8XkbjRR7SIiIhIF2YYBg6HA8uysKzYjvNuK8RvJ2fRI8nBS7tqGJXl5f5zejSusddEMwBJh/UgiNjgMSyS7XptfSYicaMkXkRERKSL8kZCuL44iP2PdTDoTKy+eRhG7L7rPquen49JY0FBOh7TxmMH29UkrytzWaGvegRo73IRiTMl8SIiIiJdkMsA5/o12P/vnuiYOfVK+l5+Q7NjzUgIP4ClBFVE5FSnNfEiIiIiXZC7oR6e/V3s4N9XkOZxxScgERHpEEriRURERLogA6AhGDto2xhHrIsXEZHEoiReREREpAtqcHlg+uyYMXvYaGq13l1EJKFpTbyIiIhIF9SAgfPKGzAHDIa3X4evjcKYMp3de/YxIC0j3uGJiEg7KYkXERER6aICDheOs8/FcdYkLIeTcCRCOKz9zUVEEpmSeBEREZEuLBKJEMGASCTeoYiISAfQmngRERERERGRBKEkXkRERERERCRBKIkXERERERERSRBK4kVEREREREQShJJ4ERERERERkQShJF5EREREREQkQSiJFxEREREREUkQSuJFREREREREEoSSeBEREREREZEEoSReREREREREJEEoiRcRERERERFJEEriRURERERERBKEM94BtFZRUREbNmxgz5491NXVce+999K9e/eYY26//XbKy8tjxi655BKuueaazgxVRERERERE5KRImCS+oaGBoUOHMmrUKBYvXnzU4y6//HLOO++86M8ej6cTohMRERERERE5+RImiZ82bRoAu3btOuZxXq+XtLS0TohIREREREREpHMlTBLfWqtWreLll1+mW7dunH322Vx88cU4nV3uZUorDBo0KN4hSBem60tOJl1fcjLp+pKTSdeXnEy6vhp1qez2ggsuoF+/fqSkpLBz506WLl1KWVkZN954Y7xDExERERERETlhcU3ily1bxsqVK495zPz58xkyZEirznfRRRdF/7tPnz54vV4ee+wxrrnmGlJSUk4oVhEREREREZF4i2sSP23aNMaPH3/MYzIyMtp9/ry8PAAOHDigJF5EREREREQSXlyTeL/fj9/vP2nn37t3L4Aa3YmIiIiIiEiXkDBr4isrK6msrGT//v0AlJSUEAgEyMzMJDk5meLiYj799FOGDBlCUlISu3btYsmSJYwcOZLMzMw4Ry8iIiIiIiJy4oyKigo73kG0xooVKygsLGw2Pm/ePCZNmsTu3bt59tlnKS0tJRwOk5mZyZgxY7j44ou1V/xppqioiA0bNrBnzx7q6uq499576d69e8wxtbW1/OUvf+GDDz4AYOTIkVx//fX4fL54hCwJ7v7772fbtm0xY2PGjOGWW26JU0SSyNasWcOrr75KZWUlvXv3Zvbs2QwePDjeYUmCa+l7VGpqKg888ECcIpJEtm3bNlatWsXu3bupqKiIfh9vYts2hYWFFBUVEQgEGDBgAHPmzCEnJyeOUUuiON719eSTT/L222/H/M6AAQNYuHBhZ4caNwkzE3/FFVdwxRVXHPXx3Nzc0+oPTo6uoaGBoUOHMmrUKBYvXtziMX/4wx8oLy/n+9//PoZh8NRTT/HEE0/wve99r5Ojla5i0qRJXH311dGfXS5XHKORRLVx40YWL17MnDlzGDRoEGvWrOHhhx/mF7/4harK5IT16tWL+fPnR382TTOO0UgiCwaD9O7dmwkTJvDkk082e/yVV15h1apVfPOb36RXr14UFhby4IMPcvfdd+P1euMQsSSS411fAF/72te4+eaboz+fbluK69Nbupxp06Zx6aWXMnDgwBYfLykp4aOPPuIb3/gGAwcOJD8/nxtuuIHNmzdTWlraydFKV+F2u0lLS4v+o6oOaY/Vq1czceJEpkyZQnZ2NnPmzCEtLY0333wz3qFJF2CaZszn1MnsSyRd2/Dhw5k5cyajR4/GMIyYx2zb5vXXX2f69OmMHj2anJwcbrrpJurr61m/fn2cIpZEcqzrq4nT6Yz5PEtOTu7kKOPr9LplIQIUFxfj8XjIz8+Pjg0cOBCPx0NxcTG9evWKY3SSqDZu3MjGjRvx+/0MHz6cGTNmaLZB2iQcDrN79+6Y7VIBhg4dSnFxcZyikq6krKyMBQsW4HA4yMvL4+qrryYrKyveYUkXU1ZWRmVlJUOHDo2Oud1uBg8eTHFxMeeee24co5OuYseOHdx2220kJSUxZMgQrrrqKlJTU+MdVqdREi+nncrKSvx+f8ydPcMw8Pv9VFZWxjEySVTjxo0jIyOD9PR0Pv/8c5YuXcrevXu57bbb4h2aJJCamhosy2r2JSQ1NZWPP/44TlFJVzFgwADmzZtHdnY2VVVVvPTSS/z617/mF7/4hbbhlQ7V9F2qpc+yL774Ih4hSRdz5plnUlBQQPfu3SkvL2f58uU88MAD/OQnPzltljMqiZeEsGzZMlauXHnMY+bPn8+QIUNadb6WSnNs2z5qyY6cftpyzU2ZMiU61qdPH7KysrjnnnvYvXs3ubm5JztU6eL02SQdYfjw4TE/5+XlsXDhQtatW9es+kOkI7RUZq/PMukIY8eOjf53nz59yM3N5fbbb+fDDz+koKAgjpF1HiXxkhCmTZvG+PHjj3lMRkZGq86VlpZGVVVVzP9MbNumpqbmtCrDkWM7kWsuNzcX0zQ5cOCAknhptZSUFEzTpKqqKma8urpan03S4bxeL7179+bAgQPxDkW6mLS0NKBxRv7w/0/qs0xOlvT0dNLT06NbkZ8OlMRLQvD7/R3WgCc/P59gMEhxcXG0+V1xcTHBYDBmnbyc3k7kmtu3bx+WZUW/yIi0htPpJDc3ly1btnD22WdHx7ds2cLo0aPjGJl0RaFQiNLS0lZXsIm0Vvfu3UlLS2PLli0MGDAAaLzetm/fzrXXXhvn6KQrqq6upqKi4rT63qUkXrqcyspKKisro3fjSkpKCAQCZGZmkpycTHZ2NmeeeSbPPPMMN9xwAwDPPPMMI0aMUFM7abMDBw6wfv16hg8fTkpKCiUlJSxZsoR+/foddYcEkaO58MILeeKJJxgwYAADBw7kzTffpLKyUo2g5IT99a9/ZcSIEWRkZFBdXc2LL75IMBhk4sSJ8Q5NElB9fX20isO2bQ4dOsSePXtITk4mMzOTqVOnsnLlSrKzs+nZsycvvfQSHo+HcePGxTlySQTHur6Sk5MpLCykoKCAtLQ0ysvLWbp0KX6//7QppQcwKioq7HgHIdKRVqxYQWFhYbPxefPmMWnSJABqa2t57rnn+OCDDwAYOXIkc+bM0bZg0maHDh3iiSeeYN++fQSDQbp168aIESOYMWPGabfdiXSMNWvW8Oqrr1JZWUnv3r2ZPXs2gwcPjndYkuAee+wxtm3bRk1NDX6/n7y8PK688kp69+4d79AkAW3dupXf/OY3zcYnTJjATTfdhG3bFBYWUlRURG1tLXl5ecyZM4ecnJw4RCuJ5ljX19y5c3nkkUfYu3cvgUCAtLS0aHf61i6t7QqUxIuIiIiIiIgkCDPeAYiIiIiIiIhI6yiJFxEREREREUkQSuJFREREREREEoSSeBEREREREZEEoSReREREREREJEEoiRcRERERERFJEEriRUREpFNs3bqVb3/722zdujXeoYiIiCQsZ7wDEBEROd1t376djz/+mGnTpuHz+eIdTouCwSBvv/02mzZtYt++fQQCAbKyshgzZgwXXnghbrc73iGKiIicFjQTLyIiEmc7duygsLCQQCAQ71COqqysjD//+c9YlsXUqVOZPXs2/fv354UXXuDBBx/Esqx4hygiInJa0Ey8iIiIHFdqaip33nknOTk50bEpU6bQs2dPli5dyubNmxk1alQcIxQRETk9KIkXERGJoxUrVlBYWAjAHXfcER2fP38+Xq+X5cuXs2vXLoLBIGlpaQwcOJC5c+fi8XgoKyvjjjvuYObMmaSlpfHyyy9TVlZGz549mTVrFkOHDo15roqKClasWMHmzZupra0lIyODyZMnc/HFF2MYxjHj9Pv9+P3+ZuMFBQUsXbqUkpKSmCS+tLSU5557jh07duD1ehk/fnyzeI5n+/btvPDCC+zatQuAvLw8rrrqKvLy8qLHrF27lkWLFrFgwQI++ugj1q1bRyAQYNCgQcydO5esrKyYc+7atYsVK1awY8cOwuEwOTk5XH755YwcObJNsYmIiMSLkngREZE4KigooLS0lI0bNzJ79mxSUlIAyM7O5mc/+xkpKSlccskl+Hw+Dh06xAcffEAwGMTj8UTP8d5771FTU8OUKVNwu9289tprPProo9x3330kJycDUFVVxb333kskEmHKlCmkpaWxfft2/va3v1FRUcF1113XrvgrKioAonE3Pdf9999PQ0MDF154ISkpKbz99tts2bKl1efdtm0bDz74IN26deOyyy7DsiyKioq4//77WbBgQUwiD7BkyRJcLhfTp0+npqaGVatW8cQTT3D77bdHj9m6dSsPPfQQOTk5XHbZZTidTt59910eeeQRbr31VgoKCtr1HoiIiHQmJfEiIiJx1KdPH/r27cvGjRsZNWoU3bt3B2DTpk3U1tbygx/8gP79+0ePv/LKK5ud4+DBg9x9993RmfLBgwdz1113sWHDBs4//3wAli9fTigU4uc//zmpqakAnHvuuaSnp7Nq1SqmTZsWfe62WLlyJW63O2Ym+5VXXqGqqooFCxYwePBgACZPnswvf/nLVp93yZIleDwe7rjjjujrmjhxIj/96U/561//yo9+9KOY4z0eDz/84Q8xzcZ2P8nJySxevJh9+/aRk5ODbds888wz5Ofnc9ttt0WPO//887nvvvt4/vnnlcSLiEhCUGM7ERGRU5DX6wVg8+bNhMPhYx47evTomFL3fv36kZSUxMGDBwGwbZv33nuPESNGYBgG1dXV0X+GDRuGbdts27atzTG+/PLLbNmyhZkzZ0ZvDDTF3K9fv2gCD41J9pQpU1p13srKSnbv3s2ECRNiXle3bt0YN24cxcXF1NbWxvzOlClTook5EH3usrIyAPbu3UtpaSnjx4+ntrY2+vpra2s588wzOXjwIOXl5W1+D0RERDqbZuJFREROQUOGDKGgoIDCwkJWr17N4MGDGTlyJGPHjo0m+E0yMzOb/b7P54smutXV1QQCAdauXcvatWtbfL7q6moAamtrY24auFyuFre9e+edd1i2bBmTJ09m6tSpMY+Vl5e3OKvds2fPmJ8bGhqoq6uLGUtLS4sm3tnZ2c3OkZ2djW3bHDp0KLpUAJq/B00xN70H+/fvB+Cpp55qds4mVVVVLb6XIiIipxIl8SIiIqcgwzD4zne+w86dO9m8eTNbtmzh6aefZuXKlSxcuDBm5vvwGejD2bYd8++xY8cyadKkFo9tSrAfffTRmFn5CRMmcNNNN8Uc+8EHH7Bo0SLOOuss5s6d2+7XuHHjRhYtWhQz9vjjj7frXEdrzHfkezBz5kxyc3NbPLZXr17tem4REZHOpCReRETkFDZgwAAGDBjAlVdeyYcffsjDDz/MW2+9xWWXXdbqc/j9fpKSkohEIsftED9r1qyYUvX09PSYxz/++GN+//vfM3jwYL71rW+1eAMhMzOT0tLSZuNNs+FNhg0bxn/+5382O65pbX5JSUmzx0pKSjAMg4yMjGO+jiM1dan3er1t7pIvIiJyKlESLyIiEmdNneYDgUB0rLa2Fp/PFzPD3DSDfPhxrWGaJgUFBbzzzjvs3r272Ux0IBDA7XbjdDqPOksNUFxczCOPPELfvn357ne/i8vlavG44cOH89prr7Ft27bo2vRgMEhRUVHMcenp6c1uEkBjSX1ubi7vvPMOl156aXRdfEVFBevXryc/Pz+mlL41cnNz6dGjB6tWrWLcuHHNlghUV1e3uIWeiIjIqUZJvIiISJw1Jc7Lli1jzJgxOJ1ODh06xFtvvcVZZ51FVlYWoVCItWvXRhPytrrmmmvYtm0b9913H+eccw45OTnU19ezb98+3n//fX71q1+RlpZ21N8vLy/n4YcfJhKJMHbsWDZt2hTzeJ8+fejTpw8A06dPZ/369fzud7/jggsuiG4x53a7Wx3vrFmz+O1vf8u9997L5MmTAXjjjTeIRCJce+21bX79pmkyb948HnroIe68804mTZpEZmYmlZWVFBcXU15e3qbu+SIiIvGiJF5ERCTO8vPzueqqqygqKmLRokXYts2sWbPo378/7777LpWVlSQlJdG3b1+uv/568vPz2/wcfr+fhQsX8tJLL/GPf/yDoqIifD4fPXv2ZMaMGced2S4rK4tWACxevLjZ4zNmzIgm8ampqSxYsIDnnnuOVatW4fV6mTBhAkOHDuWhhx5qVbyDZncc7AAAAL5JREFUBw/mtttuY8WKFbz44osYhkFeXh633HJLu14/wKBBg1i4cCEvvvgiRUVF1NXV4ff76du3b4tb94mIiJyKjIqKCjveQYiIiIiIiIjI8WmfeBEREREREZEEoSReREREREREJEEoiRcRERERERFJEEriRURERERERBKEkngRERERERGRBKEkXkRERERERCRBKIkXERERERERSRBK4kVEREREREQShJJ4ERERERERkQShJF5EREREREQkQfx/l2xmyr6gUFMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(\n",
    "    x=\"tsne-2d-one\", y=\"tsne-2d-two\",\n",
    "    hue=\"anomaly_svm\",\n",
    "#     palette=sns.color_palette(\"hls\", 10),\n",
    "    data=final_data,\n",
    "    legend=\"full\",\n",
    "    alpha=1\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 275,
   "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>ip_address</th>\n",
       "      <th>total_count</th>\n",
       "      <th>daily_counts</th>\n",
       "      <th>is_weekend_ratio</th>\n",
       "      <th>td_mean</th>\n",
       "      <th>td_max</th>\n",
       "      <th>cluster</th>\n",
       "      <th>tsne-2d-one</th>\n",
       "      <th>tsne-2d-two</th>\n",
       "      <th>ssd</th>\n",
       "      <th>anomaly_kmeans</th>\n",
       "      <th>anomaly_isolated</th>\n",
       "      <th>anomaly_svm</th>\n",
       "      <th>anomaly_manual</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>10.1.1.138</td>\n",
       "      <td>1383</td>\n",
       "      <td>39.5</td>\n",
       "      <td>2.546154</td>\n",
       "      <td>30.306078</td>\n",
       "      <td>297.0</td>\n",
       "      <td>3</td>\n",
       "      <td>-11.028182</td>\n",
       "      <td>-5.598881</td>\n",
       "      <td>5.249748</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>10.1.1.199</td>\n",
       "      <td>1365</td>\n",
       "      <td>40.5</td>\n",
       "      <td>2.123570</td>\n",
       "      <td>30.801320</td>\n",
       "      <td>455.0</td>\n",
       "      <td>5</td>\n",
       "      <td>-11.512229</td>\n",
       "      <td>6.081614</td>\n",
       "      <td>6.164888</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>10.1.1.249</td>\n",
       "      <td>4301</td>\n",
       "      <td>116.5</td>\n",
       "      <td>2.236268</td>\n",
       "      <td>9.459535</td>\n",
       "      <td>101.0</td>\n",
       "      <td>0</td>\n",
       "      <td>15.251910</td>\n",
       "      <td>-2.014084</td>\n",
       "      <td>11.541074</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>10.1.1.264</td>\n",
       "      <td>1445</td>\n",
       "      <td>42.5</td>\n",
       "      <td>2.621554</td>\n",
       "      <td>29.042936</td>\n",
       "      <td>241.0</td>\n",
       "      <td>3</td>\n",
       "      <td>-10.385866</td>\n",
       "      <td>-6.843124</td>\n",
       "      <td>5.357686</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>10.1.1.386</td>\n",
       "      <td>4300</td>\n",
       "      <td>118.5</td>\n",
       "      <td>2.127273</td>\n",
       "      <td>9.453361</td>\n",
       "      <td>104.0</td>\n",
       "      <td>0</td>\n",
       "      <td>15.528737</td>\n",
       "      <td>-2.041709</td>\n",
       "      <td>11.779482</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>10.1.1.424</td>\n",
       "      <td>2990</td>\n",
       "      <td>80.0</td>\n",
       "      <td>2.225458</td>\n",
       "      <td>13.777852</td>\n",
       "      <td>117.0</td>\n",
       "      <td>2</td>\n",
       "      <td>11.483550</td>\n",
       "      <td>-12.199755</td>\n",
       "      <td>5.263552</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>10.1.1.486</td>\n",
       "      <td>4317</td>\n",
       "      <td>117.0</td>\n",
       "      <td>2.315668</td>\n",
       "      <td>9.417285</td>\n",
       "      <td>108.0</td>\n",
       "      <td>0</td>\n",
       "      <td>14.781444</td>\n",
       "      <td>-2.334249</td>\n",
       "      <td>11.659370</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>10.1.1.500</td>\n",
       "      <td>2946</td>\n",
       "      <td>80.0</td>\n",
       "      <td>2.147436</td>\n",
       "      <td>13.989134</td>\n",
       "      <td>120.0</td>\n",
       "      <td>2</td>\n",
       "      <td>13.428407</td>\n",
       "      <td>-9.499339</td>\n",
       "      <td>5.189349</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>10.1.1.63</td>\n",
       "      <td>4339</td>\n",
       "      <td>112.0</td>\n",
       "      <td>2.148766</td>\n",
       "      <td>9.368142</td>\n",
       "      <td>101.0</td>\n",
       "      <td>0</td>\n",
       "      <td>15.287605</td>\n",
       "      <td>-2.182364</td>\n",
       "      <td>11.319226</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>10.1.1.86</td>\n",
       "      <td>4293</td>\n",
       "      <td>113.0</td>\n",
       "      <td>2.203731</td>\n",
       "      <td>9.456897</td>\n",
       "      <td>110.0</td>\n",
       "      <td>0</td>\n",
       "      <td>15.423254</td>\n",
       "      <td>-2.342858</td>\n",
       "      <td>11.090154</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>10.1.1.89</td>\n",
       "      <td>2895</td>\n",
       "      <td>83.0</td>\n",
       "      <td>2.028243</td>\n",
       "      <td>14.259157</td>\n",
       "      <td>137.0</td>\n",
       "      <td>2</td>\n",
       "      <td>13.737984</td>\n",
       "      <td>-6.781340</td>\n",
       "      <td>5.349382</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208</th>\n",
       "      <td>10.1.2.139</td>\n",
       "      <td>2898</td>\n",
       "      <td>76.0</td>\n",
       "      <td>2.393443</td>\n",
       "      <td>14.231619</td>\n",
       "      <td>115.0</td>\n",
       "      <td>2</td>\n",
       "      <td>4.219205</td>\n",
       "      <td>-12.188558</td>\n",
       "      <td>5.293503</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253</th>\n",
       "      <td>10.1.2.243</td>\n",
       "      <td>1407</td>\n",
       "      <td>39.5</td>\n",
       "      <td>1.871429</td>\n",
       "      <td>29.747511</td>\n",
       "      <td>343.0</td>\n",
       "      <td>4</td>\n",
       "      <td>-1.257572</td>\n",
       "      <td>13.681190</td>\n",
       "      <td>5.593116</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>255</th>\n",
       "      <td>10.1.2.249</td>\n",
       "      <td>4353</td>\n",
       "      <td>112.0</td>\n",
       "      <td>2.250934</td>\n",
       "      <td>9.332721</td>\n",
       "      <td>102.0</td>\n",
       "      <td>0</td>\n",
       "      <td>14.986474</td>\n",
       "      <td>-2.238024</td>\n",
       "      <td>11.318310</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>286</th>\n",
       "      <td>10.1.2.323</td>\n",
       "      <td>1408</td>\n",
       "      <td>43.5</td>\n",
       "      <td>2.192744</td>\n",
       "      <td>29.719261</td>\n",
       "      <td>458.0</td>\n",
       "      <td>5</td>\n",
       "      <td>-11.622698</td>\n",
       "      <td>5.688149</td>\n",
       "      <td>5.825046</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>311</th>\n",
       "      <td>10.1.2.386</td>\n",
       "      <td>4326</td>\n",
       "      <td>108.0</td>\n",
       "      <td>2.250188</td>\n",
       "      <td>9.392370</td>\n",
       "      <td>110.0</td>\n",
       "      <td>0</td>\n",
       "      <td>15.119220</td>\n",
       "      <td>-2.613225</td>\n",
       "      <td>10.791042</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>331</th>\n",
       "      <td>10.1.2.432</td>\n",
       "      <td>1437</td>\n",
       "      <td>40.5</td>\n",
       "      <td>2.413302</td>\n",
       "      <td>29.176880</td>\n",
       "      <td>466.0</td>\n",
       "      <td>5</td>\n",
       "      <td>-12.583876</td>\n",
       "      <td>1.878566</td>\n",
       "      <td>6.357696</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>357</th>\n",
       "      <td>10.1.2.486</td>\n",
       "      <td>4251</td>\n",
       "      <td>114.0</td>\n",
       "      <td>2.056075</td>\n",
       "      <td>9.571059</td>\n",
       "      <td>99.0</td>\n",
       "      <td>0</td>\n",
       "      <td>15.041411</td>\n",
       "      <td>-2.061416</td>\n",
       "      <td>11.438757</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361</th>\n",
       "      <td>10.1.2.497</td>\n",
       "      <td>2973</td>\n",
       "      <td>83.5</td>\n",
       "      <td>2.440972</td>\n",
       "      <td>13.869785</td>\n",
       "      <td>165.0</td>\n",
       "      <td>2</td>\n",
       "      <td>4.914829</td>\n",
       "      <td>-13.606808</td>\n",
       "      <td>5.452700</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>370</th>\n",
       "      <td>10.1.2.63</td>\n",
       "      <td>4372</td>\n",
       "      <td>121.0</td>\n",
       "      <td>2.184268</td>\n",
       "      <td>9.268588</td>\n",
       "      <td>118.0</td>\n",
       "      <td>0</td>\n",
       "      <td>15.395945</td>\n",
       "      <td>-2.032638</td>\n",
       "      <td>12.054720</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>381</th>\n",
       "      <td>10.1.2.86</td>\n",
       "      <td>4307</td>\n",
       "      <td>111.0</td>\n",
       "      <td>2.209389</td>\n",
       "      <td>9.441013</td>\n",
       "      <td>122.0</td>\n",
       "      <td>0</td>\n",
       "      <td>15.335781</td>\n",
       "      <td>-2.458637</td>\n",
       "      <td>10.825228</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     ip_address  total_count  daily_counts  is_weekend_ratio    td_mean  \\\n",
       "14   10.1.1.138         1383          39.5          2.546154  30.306078   \n",
       "42   10.1.1.199         1365          40.5          2.123570  30.801320   \n",
       "62   10.1.1.249         4301         116.5          2.236268   9.459535   \n",
       "70   10.1.1.264         1445          42.5          2.621554  29.042936   \n",
       "118  10.1.1.386         4300         118.5          2.127273   9.453361   \n",
       "134  10.1.1.424         2990          80.0          2.225458  13.777852   \n",
       "164  10.1.1.486         4317         117.0          2.315668   9.417285   \n",
       "171  10.1.1.500         2946          80.0          2.147436  13.989134   \n",
       "177   10.1.1.63         4339         112.0          2.148766   9.368142   \n",
       "188   10.1.1.86         4293         113.0          2.203731   9.456897   \n",
       "189   10.1.1.89         2895          83.0          2.028243  14.259157   \n",
       "208  10.1.2.139         2898          76.0          2.393443  14.231619   \n",
       "253  10.1.2.243         1407          39.5          1.871429  29.747511   \n",
       "255  10.1.2.249         4353         112.0          2.250934   9.332721   \n",
       "286  10.1.2.323         1408          43.5          2.192744  29.719261   \n",
       "311  10.1.2.386         4326         108.0          2.250188   9.392370   \n",
       "331  10.1.2.432         1437          40.5          2.413302  29.176880   \n",
       "357  10.1.2.486         4251         114.0          2.056075   9.571059   \n",
       "361  10.1.2.497         2973          83.5          2.440972  13.869785   \n",
       "370   10.1.2.63         4372         121.0          2.184268   9.268588   \n",
       "381   10.1.2.86         4307         111.0          2.209389   9.441013   \n",
       "\n",
       "     td_max  cluster  tsne-2d-one  tsne-2d-two        ssd  anomaly_kmeans  \\\n",
       "14    297.0        3   -11.028182    -5.598881   5.249748               0   \n",
       "42    455.0        5   -11.512229     6.081614   6.164888               1   \n",
       "62    101.0        0    15.251910    -2.014084  11.541074               1   \n",
       "70    241.0        3   -10.385866    -6.843124   5.357686               0   \n",
       "118   104.0        0    15.528737    -2.041709  11.779482               1   \n",
       "134   117.0        2    11.483550   -12.199755   5.263552               0   \n",
       "164   108.0        0    14.781444    -2.334249  11.659370               1   \n",
       "171   120.0        2    13.428407    -9.499339   5.189349               0   \n",
       "177   101.0        0    15.287605    -2.182364  11.319226               1   \n",
       "188   110.0        0    15.423254    -2.342858  11.090154               1   \n",
       "189   137.0        2    13.737984    -6.781340   5.349382               0   \n",
       "208   115.0        2     4.219205   -12.188558   5.293503               0   \n",
       "253   343.0        4    -1.257572    13.681190   5.593116               0   \n",
       "255   102.0        0    14.986474    -2.238024  11.318310               1   \n",
       "286   458.0        5   -11.622698     5.688149   5.825046               0   \n",
       "311   110.0        0    15.119220    -2.613225  10.791042               1   \n",
       "331   466.0        5   -12.583876     1.878566   6.357696               1   \n",
       "357    99.0        0    15.041411    -2.061416  11.438757               1   \n",
       "361   165.0        2     4.914829   -13.606808   5.452700               0   \n",
       "370   118.0        0    15.395945    -2.032638  12.054720               1   \n",
       "381   122.0        0    15.335781    -2.458637  10.825228               1   \n",
       "\n",
       "     anomaly_isolated  anomaly_svm  anomaly_manual  \n",
       "14                  0            1               0  \n",
       "42                  0            1               0  \n",
       "62                  1            1               1  \n",
       "70                  0            1               0  \n",
       "118                 1            1               1  \n",
       "134                 0            1               0  \n",
       "164                 1            1               1  \n",
       "171                 0            1               0  \n",
       "177                 1            1               1  \n",
       "188                 1            1               1  \n",
       "189                 0            1               0  \n",
       "208                 0            1               0  \n",
       "253                 0            1               0  \n",
       "255                 1            1               1  \n",
       "286                 0            1               0  \n",
       "311                 1            1               1  \n",
       "331                 0            1               0  \n",
       "357                 1            1               1  \n",
       "361                 1            1               0  \n",
       "370                 1            1               1  \n",
       "381                 1            1               1  "
      ]
     },
     "execution_count": 275,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_data.loc[final_data['anomaly_svm']==1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Performance of Algo"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since it is unsupervised we need to manually label the data and see the performance of the individual algos\n",
    "\n",
    "- Criteria for manual labels is strictly based on counts as we want the algos to be robust on count anomalies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 276,
   "metadata": {},
   "outputs": [],
   "source": [
    "total_counts_condition = (final_data['total_count'] >= final_data['total_count'].quantile(0.98)) \n",
    "daily_counts_condition =  (final_data['daily_counts'] >= final_data['daily_counts'].quantile(0.98))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 277,
   "metadata": {},
   "outputs": [],
   "source": [
    "final_data['anomaly_manual'] = (total_counts_condition | daily_counts_condition).astype(np.int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 278,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ip_address</th>\n",
       "      <th>total_count</th>\n",
       "      <th>daily_counts</th>\n",
       "      <th>is_weekend_ratio</th>\n",
       "      <th>td_mean</th>\n",
       "      <th>td_max</th>\n",
       "      <th>cluster</th>\n",
       "      <th>tsne-2d-one</th>\n",
       "      <th>tsne-2d-two</th>\n",
       "      <th>ssd</th>\n",
       "      <th>anomaly_kmeans</th>\n",
       "      <th>anomaly_isolated</th>\n",
       "      <th>anomaly_svm</th>\n",
       "      <th>anomaly_manual</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10.1.1.1</td>\n",
       "      <td>1446</td>\n",
       "      <td>40.0</td>\n",
       "      <td>2.070064</td>\n",
       "      <td>28.999308</td>\n",
       "      <td>362.0</td>\n",
       "      <td>5</td>\n",
       "      <td>-4.352579</td>\n",
       "      <td>11.806170</td>\n",
       "      <td>4.570390</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.1.1.100</td>\n",
       "      <td>2860</td>\n",
       "      <td>78.0</td>\n",
       "      <td>2.177778</td>\n",
       "      <td>14.427072</td>\n",
       "      <td>185.0</td>\n",
       "      <td>2</td>\n",
       "      <td>9.245516</td>\n",
       "      <td>-8.002912</td>\n",
       "      <td>4.393522</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10.1.1.101</td>\n",
       "      <td>1465</td>\n",
       "      <td>40.0</td>\n",
       "      <td>2.191721</td>\n",
       "      <td>28.520492</td>\n",
       "      <td>211.0</td>\n",
       "      <td>1</td>\n",
       "      <td>4.270270</td>\n",
       "      <td>2.411105</td>\n",
       "      <td>3.658624</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10.1.1.106</td>\n",
       "      <td>1408</td>\n",
       "      <td>35.5</td>\n",
       "      <td>2.229358</td>\n",
       "      <td>29.771144</td>\n",
       "      <td>319.0</td>\n",
       "      <td>5</td>\n",
       "      <td>-7.361582</td>\n",
       "      <td>4.483963</td>\n",
       "      <td>4.265576</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10.1.1.109</td>\n",
       "      <td>1459</td>\n",
       "      <td>42.5</td>\n",
       "      <td>2.206593</td>\n",
       "      <td>28.711934</td>\n",
       "      <td>278.0</td>\n",
       "      <td>1</td>\n",
       "      <td>-2.134053</td>\n",
       "      <td>3.368442</td>\n",
       "      <td>3.626661</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ip_address  total_count  daily_counts  is_weekend_ratio    td_mean  td_max  \\\n",
       "0    10.1.1.1         1446          40.0          2.070064  28.999308   362.0   \n",
       "1  10.1.1.100         2860          78.0          2.177778  14.427072   185.0   \n",
       "2  10.1.1.101         1465          40.0          2.191721  28.520492   211.0   \n",
       "3  10.1.1.106         1408          35.5          2.229358  29.771144   319.0   \n",
       "4  10.1.1.109         1459          42.5          2.206593  28.711934   278.0   \n",
       "\n",
       "   cluster  tsne-2d-one  tsne-2d-two       ssd  anomaly_kmeans  \\\n",
       "0        5    -4.352579    11.806170  4.570390               0   \n",
       "1        2     9.245516    -8.002912  4.393522               0   \n",
       "2        1     4.270270     2.411105  3.658624               0   \n",
       "3        5    -7.361582     4.483963  4.265576               0   \n",
       "4        1    -2.134053     3.368442  3.626661               0   \n",
       "\n",
       "   anomaly_isolated  anomaly_svm  anomaly_manual  \n",
       "0                 0            0               0  \n",
       "1                 0            0               0  \n",
       "2                 0            0               0  \n",
       "3                 0            0               0  \n",
       "4                 0            0               0  "
      ]
     },
     "execution_count": 278,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 279,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import f1_score, roc_auc_score, accuracy_score, confusion_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 280,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_sensitivity_specificity(y_true, y_pred):\n",
    "    cf = confusion_matrix(y_true, y_pred)\n",
    "    sensitivity = cf[0,0]/(cf[:,0].sum())\n",
    "    specificity = cf[1,1]/(cf[:,1].sum())\n",
    "    return sensitivity, specificity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 281,
   "metadata": {},
   "outputs": [],
   "source": [
    "f1_iso = f1_score(final_data['anomaly_manual'],final_data['anomaly_isolated'])\n",
    "acc_iso = accuracy_score(final_data['anomaly_manual'],final_data['anomaly_isolated'])\n",
    "roc_iso = roc_auc_score(final_data['anomaly_manual'],final_data['anomaly_isolated'])\n",
    "sen_iso, spec_iso = get_sensitivity_specificity(final_data['anomaly_manual'],final_data['anomaly_isolated'])\n",
    "met_iso = {\n",
    "           'f1_score': f1_iso,\n",
    "           'accuracy': acc_iso,\n",
    "           'roc_score': roc_iso,\n",
    "           'sensitivity': sen_iso,\n",
    "           'specificity': spec_iso\n",
    "          }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 282,
   "metadata": {},
   "outputs": [],
   "source": [
    "f1_kmeans = f1_score(final_data['anomaly_manual'],final_data['anomaly_kmeans'])\n",
    "acc_kmeans = accuracy_score(final_data['anomaly_manual'],final_data['anomaly_kmeans'])\n",
    "roc_kmeans = roc_auc_score(final_data['anomaly_manual'],final_data['anomaly_kmeans'])\n",
    "sen_kmeans, spec_kmeans = get_sensitivity_specificity(final_data['anomaly_manual'],final_data['anomaly_kmeans'])\n",
    "met_kmeans = {\n",
    "           'f1_score': f1_kmeans,\n",
    "           'accuracy': acc_kmeans,\n",
    "           'roc_score': roc_kmeans,\n",
    "           'sensitivity': sen_kmeans,\n",
    "           'specificity': spec_kmeans\n",
    "          }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 283,
   "metadata": {},
   "outputs": [],
   "source": [
    "f1_svm = f1_score(final_data['anomaly_manual'],final_data['anomaly_svm'])\n",
    "acc_svm = accuracy_score(final_data['anomaly_manual'],final_data['anomaly_svm'])\n",
    "roc_svm = roc_auc_score(final_data['anomaly_manual'],final_data['anomaly_svm'])\n",
    "sen_svm, spec_svm = get_sensitivity_specificity(final_data['anomaly_manual'],final_data['anomaly_svm'])\n",
    "met_svm = {\n",
    "           'f1_score': f1_svm,\n",
    "           'accuracy': acc_svm,\n",
    "           'roc_score': roc_svm,\n",
    "           'sensitivity': sen_svm,\n",
    "           'specificity': spec_svm\n",
    "          }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 284,
   "metadata": {},
   "outputs": [],
   "source": [
    "metrics = {'isolated_forest': met_iso,\n",
    "           'kmeans': met_kmeans,\n",
    "           'svm': met_svm\n",
    "          }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 285,
   "metadata": {},
   "outputs": [],
   "source": [
    "metrics_df = pd.DataFrame.from_dict(metrics)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 286,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>isolated_forest</th>\n",
       "      <th>kmeans</th>\n",
       "      <th>svm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>accuracy</th>\n",
       "      <td>0.997409</td>\n",
       "      <td>0.994819</td>\n",
       "      <td>0.971503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f1_score</th>\n",
       "      <td>0.952381</td>\n",
       "      <td>0.909091</td>\n",
       "      <td>0.645161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>roc_score</th>\n",
       "      <td>0.998670</td>\n",
       "      <td>0.997340</td>\n",
       "      <td>0.985372</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sensitivity</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>specificity</th>\n",
       "      <td>0.909091</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>0.476190</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             isolated_forest    kmeans       svm\n",
       "accuracy            0.997409  0.994819  0.971503\n",
       "f1_score            0.952381  0.909091  0.645161\n",
       "roc_score           0.998670  0.997340  0.985372\n",
       "sensitivity         1.000000  1.000000  1.000000\n",
       "specificity         0.909091  0.833333  0.476190"
      ]
     },
     "execution_count": 286,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metrics_df"
   ]
  }
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