AIM-PIbd-31-Belianin-N-N/laboratory_7/lab7.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Приступаем к работе..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 625,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['id', 'date', 'price', 'bedrooms', 'bathrooms', 'sqft_living',\n",
       "       'sqft_lot', 'floors', 'waterfront', 'view', 'condition', 'grade',\n",
       "       'sqft_above', 'sqft_basement', 'yr_built', 'yr_renovated', 'zipcode',\n",
       "       'lat', 'long', 'sqft_living15', 'sqft_lot15'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 625,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import skfuzzy as fuzz\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "\n",
    "df_house = pd.read_csv(\".//static//csv//kc_house_data.csv\")\n",
    "df_house.columns\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 626,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>date</th>\n",
       "      <th>price</th>\n",
       "      <th>bedrooms</th>\n",
       "      <th>bathrooms</th>\n",
       "      <th>sqft_living</th>\n",
       "      <th>sqft_lot</th>\n",
       "      <th>floors</th>\n",
       "      <th>waterfront</th>\n",
       "      <th>view</th>\n",
       "      <th>...</th>\n",
       "      <th>grade</th>\n",
       "      <th>sqft_above</th>\n",
       "      <th>sqft_basement</th>\n",
       "      <th>yr_built</th>\n",
       "      <th>yr_renovated</th>\n",
       "      <th>zipcode</th>\n",
       "      <th>lat</th>\n",
       "      <th>long</th>\n",
       "      <th>sqft_living15</th>\n",
       "      <th>sqft_lot15</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7129300520</td>\n",
       "      <td>20141013T000000</td>\n",
       "      <td>221900.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1180</td>\n",
       "      <td>5650</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>7</td>\n",
       "      <td>1180</td>\n",
       "      <td>0</td>\n",
       "      <td>1955</td>\n",
       "      <td>0</td>\n",
       "      <td>98178</td>\n",
       "      <td>47.5112</td>\n",
       "      <td>-122.257</td>\n",
       "      <td>1340</td>\n",
       "      <td>5650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>6414100192</td>\n",
       "      <td>20141209T000000</td>\n",
       "      <td>538000.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2.25</td>\n",
       "      <td>2570</td>\n",
       "      <td>7242</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>7</td>\n",
       "      <td>2170</td>\n",
       "      <td>400</td>\n",
       "      <td>1951</td>\n",
       "      <td>1991</td>\n",
       "      <td>98125</td>\n",
       "      <td>47.7210</td>\n",
       "      <td>-122.319</td>\n",
       "      <td>1690</td>\n",
       "      <td>7639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5631500400</td>\n",
       "      <td>20150225T000000</td>\n",
       "      <td>180000.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1.00</td>\n",
       "      <td>770</td>\n",
       "      <td>10000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>6</td>\n",
       "      <td>770</td>\n",
       "      <td>0</td>\n",
       "      <td>1933</td>\n",
       "      <td>0</td>\n",
       "      <td>98028</td>\n",
       "      <td>47.7379</td>\n",
       "      <td>-122.233</td>\n",
       "      <td>2720</td>\n",
       "      <td>8062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2487200875</td>\n",
       "      <td>20141209T000000</td>\n",
       "      <td>604000.0</td>\n",
       "      <td>4</td>\n",
       "      <td>3.00</td>\n",
       "      <td>1960</td>\n",
       "      <td>5000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>7</td>\n",
       "      <td>1050</td>\n",
       "      <td>910</td>\n",
       "      <td>1965</td>\n",
       "      <td>0</td>\n",
       "      <td>98136</td>\n",
       "      <td>47.5208</td>\n",
       "      <td>-122.393</td>\n",
       "      <td>1360</td>\n",
       "      <td>5000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1954400510</td>\n",
       "      <td>20150218T000000</td>\n",
       "      <td>510000.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2.00</td>\n",
       "      <td>1680</td>\n",
       "      <td>8080</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>8</td>\n",
       "      <td>1680</td>\n",
       "      <td>0</td>\n",
       "      <td>1987</td>\n",
       "      <td>0</td>\n",
       "      <td>98074</td>\n",
       "      <td>47.6168</td>\n",
       "      <td>-122.045</td>\n",
       "      <td>1800</td>\n",
       "      <td>7503</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           id             date     price  bedrooms  bathrooms  sqft_living  \\\n",
       "0  7129300520  20141013T000000  221900.0         3       1.00         1180   \n",
       "1  6414100192  20141209T000000  538000.0         3       2.25         2570   \n",
       "2  5631500400  20150225T000000  180000.0         2       1.00          770   \n",
       "3  2487200875  20141209T000000  604000.0         4       3.00         1960   \n",
       "4  1954400510  20150218T000000  510000.0         3       2.00         1680   \n",
       "\n",
       "   sqft_lot  floors  waterfront  view  ...  grade  sqft_above  sqft_basement  \\\n",
       "0      5650     1.0           0     0  ...      7        1180              0   \n",
       "1      7242     2.0           0     0  ...      7        2170            400   \n",
       "2     10000     1.0           0     0  ...      6         770              0   \n",
       "3      5000     1.0           0     0  ...      7        1050            910   \n",
       "4      8080     1.0           0     0  ...      8        1680              0   \n",
       "\n",
       "   yr_built  yr_renovated  zipcode      lat     long  sqft_living15  \\\n",
       "0      1955             0    98178  47.5112 -122.257           1340   \n",
       "1      1951          1991    98125  47.7210 -122.319           1690   \n",
       "2      1933             0    98028  47.7379 -122.233           2720   \n",
       "3      1965             0    98136  47.5208 -122.393           1360   \n",
       "4      1987             0    98074  47.6168 -122.045           1800   \n",
       "\n",
       "   sqft_lot15  \n",
       "0        5650  \n",
       "1        7639  \n",
       "2        8062  \n",
       "3        5000  \n",
       "4        7503  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 626,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_house.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 627,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\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>id</th>\n",
       "      <th>price</th>\n",
       "      <th>bedrooms</th>\n",
       "      <th>bathrooms</th>\n",
       "      <th>sqft_living</th>\n",
       "      <th>sqft_lot</th>\n",
       "      <th>floors</th>\n",
       "      <th>waterfront</th>\n",
       "      <th>view</th>\n",
       "      <th>condition</th>\n",
       "      <th>grade</th>\n",
       "      <th>sqft_above</th>\n",
       "      <th>sqft_basement</th>\n",
       "      <th>yr_built</th>\n",
       "      <th>yr_renovated</th>\n",
       "      <th>zipcode</th>\n",
       "      <th>lat</th>\n",
       "      <th>long</th>\n",
       "      <th>sqft_living15</th>\n",
       "      <th>sqft_lot15</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2.161300e+04</td>\n",
       "      <td>2.161300e+04</td>\n",
       "      <td>21613.000000</td>\n",
       "      <td>21613.000000</td>\n",
       "      <td>21613.000000</td>\n",
       "      <td>2.161300e+04</td>\n",
       "      <td>21613.000000</td>\n",
       "      <td>21613.000000</td>\n",
       "      <td>21613.000000</td>\n",
       "      <td>21613.000000</td>\n",
       "      <td>21613.000000</td>\n",
       "      <td>21613.000000</td>\n",
       "      <td>21613.000000</td>\n",
       "      <td>21613.000000</td>\n",
       "      <td>21613.000000</td>\n",
       "      <td>21613.000000</td>\n",
       "      <td>21613.000000</td>\n",
       "      <td>21613.000000</td>\n",
       "      <td>21613.000000</td>\n",
       "      <td>21613.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>4.580302e+09</td>\n",
       "      <td>5.400881e+05</td>\n",
       "      <td>3.370842</td>\n",
       "      <td>2.114757</td>\n",
       "      <td>2079.899736</td>\n",
       "      <td>1.510697e+04</td>\n",
       "      <td>1.494309</td>\n",
       "      <td>0.007542</td>\n",
       "      <td>0.234303</td>\n",
       "      <td>3.409430</td>\n",
       "      <td>7.656873</td>\n",
       "      <td>1788.390691</td>\n",
       "      <td>291.509045</td>\n",
       "      <td>1971.005136</td>\n",
       "      <td>84.402258</td>\n",
       "      <td>98077.939805</td>\n",
       "      <td>47.560053</td>\n",
       "      <td>-122.213896</td>\n",
       "      <td>1986.552492</td>\n",
       "      <td>12768.455652</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>2.876566e+09</td>\n",
       "      <td>3.671272e+05</td>\n",
       "      <td>0.930062</td>\n",
       "      <td>0.770163</td>\n",
       "      <td>918.440897</td>\n",
       "      <td>4.142051e+04</td>\n",
       "      <td>0.539989</td>\n",
       "      <td>0.086517</td>\n",
       "      <td>0.766318</td>\n",
       "      <td>0.650743</td>\n",
       "      <td>1.175459</td>\n",
       "      <td>828.090978</td>\n",
       "      <td>442.575043</td>\n",
       "      <td>29.373411</td>\n",
       "      <td>401.679240</td>\n",
       "      <td>53.505026</td>\n",
       "      <td>0.138564</td>\n",
       "      <td>0.140828</td>\n",
       "      <td>685.391304</td>\n",
       "      <td>27304.179631</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000102e+06</td>\n",
       "      <td>7.500000e+04</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>290.000000</td>\n",
       "      <td>5.200000e+02</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>290.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1900.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>98001.000000</td>\n",
       "      <td>47.155900</td>\n",
       "      <td>-122.519000</td>\n",
       "      <td>399.000000</td>\n",
       "      <td>651.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2.123049e+09</td>\n",
       "      <td>3.219500e+05</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.750000</td>\n",
       "      <td>1427.000000</td>\n",
       "      <td>5.040000e+03</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>1190.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1951.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>98033.000000</td>\n",
       "      <td>47.471000</td>\n",
       "      <td>-122.328000</td>\n",
       "      <td>1490.000000</td>\n",
       "      <td>5100.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.904930e+09</td>\n",
       "      <td>4.500000e+05</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.250000</td>\n",
       "      <td>1910.000000</td>\n",
       "      <td>7.618000e+03</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>1560.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1975.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>98065.000000</td>\n",
       "      <td>47.571800</td>\n",
       "      <td>-122.230000</td>\n",
       "      <td>1840.000000</td>\n",
       "      <td>7620.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>7.308900e+09</td>\n",
       "      <td>6.450000e+05</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>2.500000</td>\n",
       "      <td>2550.000000</td>\n",
       "      <td>1.068800e+04</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>2210.000000</td>\n",
       "      <td>560.000000</td>\n",
       "      <td>1997.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>98118.000000</td>\n",
       "      <td>47.678000</td>\n",
       "      <td>-122.125000</td>\n",
       "      <td>2360.000000</td>\n",
       "      <td>10083.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>9.900000e+09</td>\n",
       "      <td>7.700000e+06</td>\n",
       "      <td>33.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>13540.000000</td>\n",
       "      <td>1.651359e+06</td>\n",
       "      <td>3.500000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>9410.000000</td>\n",
       "      <td>4820.000000</td>\n",
       "      <td>2015.000000</td>\n",
       "      <td>2015.000000</td>\n",
       "      <td>98199.000000</td>\n",
       "      <td>47.777600</td>\n",
       "      <td>-121.315000</td>\n",
       "      <td>6210.000000</td>\n",
       "      <td>871200.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 id         price      bedrooms     bathrooms   sqft_living  \\\n",
       "count  2.161300e+04  2.161300e+04  21613.000000  21613.000000  21613.000000   \n",
       "mean   4.580302e+09  5.400881e+05      3.370842      2.114757   2079.899736   \n",
       "std    2.876566e+09  3.671272e+05      0.930062      0.770163    918.440897   \n",
       "min    1.000102e+06  7.500000e+04      0.000000      0.000000    290.000000   \n",
       "25%    2.123049e+09  3.219500e+05      3.000000      1.750000   1427.000000   \n",
       "50%    3.904930e+09  4.500000e+05      3.000000      2.250000   1910.000000   \n",
       "75%    7.308900e+09  6.450000e+05      4.000000      2.500000   2550.000000   \n",
       "max    9.900000e+09  7.700000e+06     33.000000      8.000000  13540.000000   \n",
       "\n",
       "           sqft_lot        floors    waterfront          view     condition  \\\n",
       "count  2.161300e+04  21613.000000  21613.000000  21613.000000  21613.000000   \n",
       "mean   1.510697e+04      1.494309      0.007542      0.234303      3.409430   \n",
       "std    4.142051e+04      0.539989      0.086517      0.766318      0.650743   \n",
       "min    5.200000e+02      1.000000      0.000000      0.000000      1.000000   \n",
       "25%    5.040000e+03      1.000000      0.000000      0.000000      3.000000   \n",
       "50%    7.618000e+03      1.500000      0.000000      0.000000      3.000000   \n",
       "75%    1.068800e+04      2.000000      0.000000      0.000000      4.000000   \n",
       "max    1.651359e+06      3.500000      1.000000      4.000000      5.000000   \n",
       "\n",
       "              grade    sqft_above  sqft_basement      yr_built  yr_renovated  \\\n",
       "count  21613.000000  21613.000000   21613.000000  21613.000000  21613.000000   \n",
       "mean       7.656873   1788.390691     291.509045   1971.005136     84.402258   \n",
       "std        1.175459    828.090978     442.575043     29.373411    401.679240   \n",
       "min        1.000000    290.000000       0.000000   1900.000000      0.000000   \n",
       "25%        7.000000   1190.000000       0.000000   1951.000000      0.000000   \n",
       "50%        7.000000   1560.000000       0.000000   1975.000000      0.000000   \n",
       "75%        8.000000   2210.000000     560.000000   1997.000000      0.000000   \n",
       "max       13.000000   9410.000000    4820.000000   2015.000000   2015.000000   \n",
       "\n",
       "            zipcode           lat          long  sqft_living15     sqft_lot15  \n",
       "count  21613.000000  21613.000000  21613.000000   21613.000000   21613.000000  \n",
       "mean   98077.939805     47.560053   -122.213896    1986.552492   12768.455652  \n",
       "std       53.505026      0.138564      0.140828     685.391304   27304.179631  \n",
       "min    98001.000000     47.155900   -122.519000     399.000000     651.000000  \n",
       "25%    98033.000000     47.471000   -122.328000    1490.000000    5100.000000  \n",
       "50%    98065.000000     47.571800   -122.230000    1840.000000    7620.000000  \n",
       "75%    98118.000000     47.678000   -122.125000    2360.000000   10083.000000  \n",
       "max    98199.000000     47.777600   -121.315000    6210.000000  871200.000000  "
      ]
     },
     "execution_count": 627,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_house.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 628,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "id               0\n",
      "date             0\n",
      "price            0\n",
      "bedrooms         0\n",
      "bathrooms        0\n",
      "sqft_living      0\n",
      "sqft_lot         0\n",
      "floors           0\n",
      "waterfront       0\n",
      "view             0\n",
      "condition        0\n",
      "grade            0\n",
      "sqft_above       0\n",
      "sqft_basement    0\n",
      "yr_built         0\n",
      "yr_renovated     0\n",
      "zipcode          0\n",
      "lat              0\n",
      "long             0\n",
      "sqft_living15    0\n",
      "sqft_lot15       0\n",
      "dtype: int64\n",
      "id               False\n",
      "date             False\n",
      "price            False\n",
      "bedrooms         False\n",
      "bathrooms        False\n",
      "sqft_living      False\n",
      "sqft_lot         False\n",
      "floors           False\n",
      "waterfront       False\n",
      "view             False\n",
      "condition        False\n",
      "grade            False\n",
      "sqft_above       False\n",
      "sqft_basement    False\n",
      "yr_built         False\n",
      "yr_renovated     False\n",
      "zipcode          False\n",
      "lat              False\n",
      "long             False\n",
      "sqft_living15    False\n",
      "sqft_lot15       False\n",
      "dtype: bool\n"
     ]
    }
   ],
   "source": [
    "# Процент пропущенных значений признаков\n",
    "for i in df_house.columns:\n",
    "    null_rate = df_house[i].isnull().sum() / len(df_house) * 100\n",
    "    if null_rate > 0:\n",
    "        print(f'{i} Процент пустых значений: %{null_rate:.2f}')\n",
    "\n",
    "print(df_house.isnull().sum())\n",
    "\n",
    "print(df_house.isnull().any())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 629,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                 int64\n",
       "date              object\n",
       "price            float64\n",
       "bedrooms           int64\n",
       "bathrooms        float64\n",
       "sqft_living        int64\n",
       "sqft_lot           int64\n",
       "floors           float64\n",
       "waterfront         int64\n",
       "view               int64\n",
       "condition          int64\n",
       "grade              int64\n",
       "sqft_above         int64\n",
       "sqft_basement      int64\n",
       "yr_built           int64\n",
       "yr_renovated       int64\n",
       "zipcode            int64\n",
       "lat              float64\n",
       "long             float64\n",
       "sqft_living15      int64\n",
       "sqft_lot15         int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 629,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Проверка типов столбцов\n",
    "df_house.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Определим входные и выходные переменные (данные)  \n",
    "\n",
    "Перед построением нечёткой системы, нужно определить, какие переменные будут входными, а какие - выходными.\n",
    "\n",
    "**Входные переменные (fuzzy inputs)**  \n",
    "Входные X: bathrooms - ванные, sqft_living - площадь  \n",
    "\n",
    "**Выходные переменные (fuzzy output)**  \n",
    "Выходные Y: price - цены.  \n",
    "\n",
    "## Настройка лингвистических переменных  \n",
    "Заключается в определении термов, которые будут соответствовать переменным, ну и их тип. (Какие-то будут функциями принадлежности, другие треугольными).\n",
    "\n",
    "Всем параметрам присваиваются значения low, medium, high\n",
    "\n",
    "**Создадим лингвистические переменные**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 630,
   "metadata": {},
   "outputs": [],
   "source": [
    "from skfuzzy import control as ctrl\n",
    "\n",
    "# Определим входные и выходные переменные\n",
    "sqft_living = ctrl.Antecedent(df_house['sqft_living'].sort_values(), \"sqft_living\")\n",
    "bathrooms = ctrl.Antecedent(df_house['bathrooms'].sort_values(), \"bathrooms\")\n",
    "price = ctrl.Consequent(df_house['price'].sort_values(), \"price\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Формирование нечётких переменных для лингвистических переменных  \n",
    "Определение функций принадлежности"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 631,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "e:\\MII\\laboratory\\mai\\Lib\\site-packages\\skfuzzy\\control\\fuzzyvariable.py:125: UserWarning: FigureCanvasAgg is non-interactive, and thus cannot be shown\n",
      "  fig.show()\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sqft_living['low'] = fuzz.zmf(sqft_living.universe, 0, 5000)\n",
    "sqft_living['medium'] = fuzz.trapmf(sqft_living.universe, [3400, 5700, 7800, 9900])\n",
    "sqft_living['high'] = fuzz.trimf(sqft_living.universe, [8000, 13580, 13580])\n",
    "sqft_living.view()\n",
    "\n",
    "bathrooms['low'] = fuzz.zmf(bathrooms.universe, 0, 3)\n",
    "bathrooms['medium'] = fuzz.trapmf(bathrooms.universe, [1, 3, 4, 6])\n",
    "bathrooms['high'] = fuzz.trimf(bathrooms.universe, [5, 8, 8])\n",
    "bathrooms.view()\n",
    "\n",
    "#price['low'] = fuzz.zmf(price.universe, 0, 2500000)\n",
    "#price['medium'] = fuzz.trapmf(price.universe, [1500000, 3000000, 4000000, 5500000])\n",
    "#price['high'] = fuzz.trimf(price.universe, [4000000, 9000000, 11000000])\n",
    "\n",
    "# Для более точного определения цены \n",
    "price.automf(5, variable_type=\"quant\")\n",
    "price.view()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Формирование и визуализация базы нечётких правил  \n",
    "Определение правил: установим логические зависимости между входными и выходными переменными.  \n",
    "\n",
    "**Правила:**  \n",
    "&nbsp;&nbsp; 1. Если количество ванн маленькое и площадь маленькая, то цена очень дешёвая  \n",
    "&nbsp;&nbsp; 2. Если количество ванн маленькое и площадь средняя, то цена дешёвая  \n",
    "&nbsp;&nbsp; 3. Если количество ванн маленькое и площадь большая, то цена средняя  \n",
    "&nbsp;&nbsp; 4. Если количество ванн среднее и площадь маленькая, то цена очень дешёвая  \n",
    "&nbsp;&nbsp; 5. Если количество ванн среднее и площадь средняя, то цена средняя  \n",
    "&nbsp;&nbsp; 6. Если количество ванн среднее и площадь большая, то цена высокая  \n",
    "&nbsp;&nbsp; 7. Если количество ванн большое и площадь маленькая, то цена дешёвая  \n",
    "&nbsp;&nbsp; 8. Если количество ванн большое и площадь средняя, то цена высокая  \n",
    "&nbsp;&nbsp; 9. Если количество ванн большое и площадь большая, то цена очень высокая  \n",
    "\n",
    "В случае ошибки необходимо в файле  \n",
    "\n",
    ".venv/lib/python3.13/site-packages/skfuzzy/control/visualization.py  \n",
    "удалить лишний отступ на 182 строке, должно быть:  \n",
    "\n",
    "if not matplotlib_present:  \n",
    "&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;    raise ImportError(\"`ControlSystemVisualizer` can only be used \"  \n",
    "&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;  \"with `matplotlib` present in the system.\")  \n",
    "\n",
    "self.ctrl = control_system  \n",
    "\n",
    "self.fig, self.ax = plt.subplots()  \n",
    "\n",
    "После этого обязательно перезапустить ядро!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 632,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<Figure size 640x480 with 1 Axes>, <Axes: >)"
      ]
     },
     "execution_count": 632,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Для сформированных нечётких переменных поработаем с нечёткими правилами (bathrooms, sqft_living, price)\n",
    "rule1 = ctrl.Rule(bathrooms['low'] & sqft_living['low'], price['lower'])\n",
    "rule2 = ctrl.Rule(bathrooms['low'] & sqft_living['medium'], price['low'])\n",
    "rule3 = ctrl.Rule(bathrooms['low'] & sqft_living['high'], price['average'])\n",
    "rule4 = ctrl.Rule(bathrooms['medium'] & sqft_living['low'], price['lower'])\n",
    "rule5 = ctrl.Rule(bathrooms['medium'] & sqft_living['medium'], price['average'])\n",
    "rule6 = ctrl.Rule(bathrooms['medium'] & sqft_living['high'], price['high'])\n",
    "rule7 = ctrl.Rule(bathrooms['high'] & sqft_living['low'], price['average'])\n",
    "rule8 = ctrl.Rule(bathrooms['high'] & sqft_living['medium'], price['high'])\n",
    "rule9 = ctrl.Rule(bathrooms['high'] & sqft_living['high'], price['higher'])\n",
    "\n",
    "\n",
    "rule1.view()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Создание нечёткой системы и добавление нечётких правил в базу знаний нечёткой системы"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 633,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "e:\\MII\\laboratory\\mai\\Lib\\site-packages\\skfuzzy\\control\\controlsystem.py:135: UserWarning: FigureCanvasAgg is non-interactive, and thus cannot be shown\n",
      "  fig.show()\n"
     ]
    },
    {
     "data": {
      "image/png": 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jcu8Dvz4lCpIPNypnzenxTXGra8/w4cNTnKNSqTh27Bg9evQgPDxcK3bmJVQqFUuWLKFevXrI5XJu3LjBhAkT9NbkycvLC0tLS5ycPh4TYmdnp9kmAIR3QGBwCDEgyHESExM5cOAAXbp0oUSJEkycOJHSpUuzf/9+Xrx4wcqVK6lbt26qPdgCBQrwzz//4Orq+tHxx7hU5OduTpgZy7P1VP+tSwVKW5mzZWh9PMY1oX/9MpSxNk9V00AGlLE2J9HvDC/WjmZIuXhNjECnTp1S3YdMJmPt2rWavWRBxggODqZ58+ZMnTqV77//nmvXrn1yEdY1yfECn6pfkOwZKFeuHObm5kIMCAwOmSRJhhVtJfgskSSJGzdusGnTJnbs2EFkZCS1a9dmwIAB9OnTh6JFi2p9zqeR8cw44Mv5R68/2d44+bhzBRsWdnX6aMBfnEJJUEQciUo1psZyHKwtsDAzxtbWllevXmFsbMyePXvo0qULAI0aNeLKlSsk/6o1aNCACxcu6KwAzueGJEls3bqVMWPGYGlpyaZNm2jWrJm+zSIxMRFLS0vmz5/PxIkTP3ruoEGDCAgI4OLFi9SvX58qVaqwadOmHLJUIPg0wjMg0CnPnz9n8eLFODo6Uq9ePfbv38/QoUPx9fXlxo0bfPfddzoRAkCmnur71y/D6fFN2DK0/icj/y3MjHEsUZia9kVwLFEYCzNjJEkiOjoaeF9+tlu3bmzcuBGAHj16IEkSRkZGTJgwgevXrzN06NBUbW8FqYmIiMDNzY0BAwbQuXNn7ty5YxBCAODGjRu8e/eOJk2afPLcZM8AIIIIBYaJJBBombi4OGnr1q1Sq1atJLlcLuXLl0/q3bu3dPz4cSkpKUmvtsUmJEl3n7+VbgZHSnefv5ViE7Rjz9u3byUg1eu3336Tnj59KlWrVk06cOCAJEmStG3bNkkmk0kjRoyQ1Gq1Vub/HDl58qRUvHhxqUiRItLu3bv1bU4qFi5cKBUsWDBDn+klS5ZIBQsWlCRJklasWCGZmprq/XdBIPgQIQYEWkGlUkleXl7SkCFDpIIFC0qA9NVXX0lr1qyR3r59q2/zdI6fn1+aYgCQXrx4ker8DRs2SIA0duxYIQj+Q3x8vDR27FgJkFxdXaVnz57p26Q0adOmjdSmTZsMnbt582YJkOLj46Vz585JgOTn56djCwWCjCOKDgmyRWBgIFu2bGHz5s08efIEBwcHxo8fz4ABAyhfvry+zcsxQkNDgffBgZIkIZPJ6NmzJ8OHD6dYsWKpzh80aBCJiYmMHDkSMzMzfvnll3SL1uQlbt68Sd++fQkKCmLFihV8++23essU+BhKpZILFy4wc+bMDJ2fHCya3LAI3mcUpFe1UCDIaYQYEGSaqKgo9uzZw6ZNm7hw4QIFCxakZ8+ebNiwAWdnZ4P88tY1SqUSgJo1a1K2bFkOHz7M6tWrsbKySveaESNGoFAo+O677zAzM2PBggU5Za7BoVKpWLx4MXPmzMHJyQkfHx+DXihv3bpFbGzsR+sLfEhyf4Lw8HDKlClDqVKluHPnDr1799almQJBhhFiQJAhVCoVHh4ebN68mQMHDqBQKGjZsiVbt26la9eumJvn7XK7rVq1Ijw8nKJFixIeHs6hQ4fYsWMH33777UevGzt2LAqFgsmTJ5MvXz5mzZqVQxYbDo8fP2bAgAFcvnyZqVOnMnfuXExNTfVt1kfx8vLC3Nyc2rVrZ+j8Dz0DIIIIBYaHEAOCj+Ln58emTZvYunUrL168oEqVKsyZM4d+/fpRqlQpfZtnMMjlck1WhK2tLe3bt2fjxo2fFAMAkyZNQqFQMGvWLMzMzJg8ebKuzTUIJEliw4YNfP/99xQtWhQvLy+++uorfZuVIby8vGjYsGGGRUvyZyO58mD16tXZtm2bzuwTCDJL3vPnCj7J69evWblyJXXq1OGLL75g3bp1dOvWjWvXrnHv3j2mTZsmhMAnGDRoEDdu3ODu3bsZOn/mzJnMmjWLKVOmsGLFCh1bp39evXpFt27dGDp0KD179uT27du5RgioVCrOnz+f4S0CABMTE6ysrFJ4Bp4+fcqbN290ZaZAkCmEZ0AAvC+g8s8//7Bp0yb++ecfANq1a8eMGTNo3749ZmZmerYwd9G+fXuKFi3Kxo0bWbp0aYau+fHHH1EoFHz//feYmZkxcuRIHVupH44dO8aQIUNQKpXs27ePbt266dukTHHnzh2ioqIyJQbgfyWJAU1ZYl9f3wzVKRAIdI3wDORhpP+vCjh27FhKlChBt27dePr0Kb/++iuhoaEcOnSIbt26CSGQBUxMTOjbty9btmwhKSkpQ9fIZDIWL17Md999xzfffMOGDRt0bGXOEhcXx6hRo2jfvj21atXC19c31wkBAG9vb8zMzKhXr16mrvuw8FClSpUwNTUVcQMCg0F4BvIgz58/Z+vWrWzevJl79+5RrFgxBg8ezMCBA/niiy/0bd5nw6BBg1i2bBknTpygY8eOGbpGJpOxbNkyFAoFQ4cOxczMLMfb8uqCa9eu0a9fP549e8aff/7JN998k2tTKb28vGjQoAH58uXL1HW2trYaz4CJiQlVq1YVYkBgMAjPQB4hPj6e7du307p1a+zt7Zk7dy7Vq1fn+PHjPH36lCVLlgghoGVq1KhBzZo1NWWJM4pMJuPPP/9k4MCBDBgwgL179+rGwBxAqVTy448/0qhRIywtLbl16xajRo3KtUJArVbj7e2d6S0CeL9N8GGnSpFRIDAkhGfgM0aSJM6fP8/mzZvZvXs3MTExNG7cmL/++otevXpRuHBhfZv42TNo0CAmTZrE69evsbGxyfB1crmctWvXkpiYSJ8+fTA1NaVTp046tFT7BAQE0L9/f65fv86sWbOYNWsWJiYm+jYrW9y7d4+IiIgs7fN/uE0A78XAvn37UKvVebI2h8CwEJ/Az5DHjx8zd+5cypcvT9OmTTlz5gzjx4/n0aNHXLhwgeHDhwshkEMku/i3b9+e6WuNjIzYtGkTXbp0oWfPnpw4cULb5ukESZJwd3fnyy+/5PXr11y8eJF58+bleiEA77cITExMaNiwYaavtbOz49WrV6hUKuC9GIiPj+fx48faNlMgyDRCDHwmREVFsW7dOpo0aUL58uX59ddfadasGefOnSMwMJB58+blqfLAhoKNjQ0dO3bM9FZBMsbGxmzfvp02bdrQpUsXzpw5o10DtUxYWBidOnVi5MiR9OvXj9u3b9OgQQN9m6U1vLy8qFu3bpaKbNna2qJWq4mMjAT+l1EgtgoEhoAQA7kYlUrFyZMn+frrrylWrBjDhw8nX758bN26lZcvX7J+/XqaNm0qXJB6ZtCgQdy6dYt///03S9ebmJiwe/duXFxc6NixI97e3lq2UDscPnwYJycnrl69yuHDh/n7778pUKCAvs3SGpIkZTleAP5Xkjg5iNDOzo6iRYvi6+urNRsFgqwiVolcyL1795g6dSr29va0adOGW7duMWfOHEJCQjh16hR9+/bFwsJC32YK/p82bdpga2ubZe8AgJmZGfv376dhw4a0b9+ey5cva8/AbBIbG8uwYcPo3LkzDRo04O7duxnOnshN+Pv7ExYWlmUx8N+SxDKZTAQRCgwGIQZyCR9WBXR0dGTt2rV07dqVq1eviqqABo6JiQn9+/dn69atJCYmZnmc/Pnzc/jwYWrWrEmbNm24ceOGFq3MGpcvX6ZGjRrs3LmTNWvWcOjQIc2i97nh5eWFkZERjRo1ytL1yT+XZM8AiIwCgeEgxIABk5iYyMGDB+natSslSpRgwoQJlCxZkn379hEaGsoff/xBvXr1cm2aVl5i4MCBvH79mmPHjmVrHAsLC/755x+qVatGq1atsrz1kF2SkpL44Ycf+Oqrr7C1teX27dsMGzbss/4senl5UatWLQoWLJil6wsUKED+/PlTZRQEBgYSHhmFX2gUt0Le4BcaRZxCqS2zBYIMIVILDQxJkvDx8WHTpk3s2LGDiIgIatasyZIlS+jTp89n+9T1uePk5ETt2rXZuHEjXbp0ydZYBQsW5Pjx47Rs2ZKWLVty7tw5HB0dtWNoBnjw4IEmOHDu3LlMnz4dY+PP+6tEkiS8vLzo06dPlseQyWQp0gsDwmL417gS9t+up/6SC0gfngvYW5njUtmWvvXtqWiXNQEiEGQUmSRJ0qdPE+ia0NBQtm7dyqZNmzRVAfv168eAAQNwcnLSt3kCLbBq1SrGjRvH8+fPtSLqIiMjcXFxISwsDG9vbypVqqQFK9NHkiT+/PNPJk+ejL29PVu2bKFu3bo6ndNQCAwMpEKFChw5coQOHTpkeZz69etToUZ95PX7cv7Ra4zkMlTq9L+Ck487V7BhYVcnSlvl7VbhAt0htgn0SHx8PDt27KBNmzaULl2a2bNn4+TkxLFjxzRVAYUQ+Hzo3bs3crlca61rraysOH36NNbW1jRv3pzAwECtjJsWoaGhtG3bljFjxjB48GBu3ryZZ4QAvO9HIJPJst1Z0bhyEy4VacGlxxEAHxUCHx6/9DiClr97sfN6SLbmFwjSQ3gGchhJkrhw4QKbNm1iz549REdH07hxYwYOHEjPnj2xtLTUt4kCHdKzZ08ePnzIv//+q7X99ZcvX9K0aVMSEhLw9vamTJkyWhk3mX379jFixAhMTU1Zv349bdu21er4uYFBgwZx584dbt68meUx/vAMYOkpf5AkyMb//aRWlRjjUjHL1wsEaSE8AznEkydPmDdvHhUqVKBJkyacPn2a77//noCAAE1VQCEEPn8GDx6Mr68vt27d0tqYxYoV48yZMxgbG9O8eXOeP3+ulXGjo6MZNGgQPXr0oFmzZvj6+uZJIQDvgwezmlIIsPN6yHshANkSAgBLT/mzS3gIBFpGeAZ0SHR0NHv27GHTpk2cP3+eAgUK0LNnTwYMGECTJk1EMaA8iFKppHTp0vTs2ZMVK1Zodezg4GCaNGlCvnz58PLyolixYlke6/z58wwYMICIiAhWrFjBwIEDP+tMgY8REhJCmTJl2L9/P127ds309U8j42n5uxcKpVprNpkZyzk9vqmIIRBojc9qNYpTKPWenqNSqTSFf5KrApqZmbFlyxZNVcBmzZoJIZBHMTY2pn///mzbtg2FQqHVscuUKcPZs2eJjY2lRYsWvHr1KtNjJCYmMn36dJo2bUqpUqX4999/GTRoUJ4VAvDeKwDg7OycpetnHPBF+YnYgMyiVEvMOCAqFwq0R673DASExbDtagieD8MJiYzXW3rOvXv32LRpE1u3biU0NJQqVaowcOBA+vbtS+nSpXU2ryD3ce/ePRwdHdm7dy/du3fX+vgPHz6kadOmFCtWjLNnz2JlZZWh6/z8/OjXrx9+fn78+OOPTJ48GSMjI63bl9sYNmwYV69ezVLZ4ICwGFyX6a589OnxTahgK9IOBdkn14qBp5HxzDjgq9f0nIiICHbs2MGmTZu4ceMGRYoUoU+fPgwcOJC6devm6acpwcepX78+tra2HDlyRCfj+/n50axZMxwcHDh9+vRHu1Sq1WpWrlzJ1KlTKVeuHNu2baNmzZo6sSs3UqlSJVq1asUff/yR6WvnHvZjy9XgT2YNZAUjuYz+9cswt1PO1ZgQfL7kSl/1zushtPzdSy/pOclVAbt160bx4sUZP348JUqUYO/evbx48YJVq1aJqoCCTzJo0CCOHz/Oy5cvdTK+o6MjHh4eBAYG0rZtW2JiYtI879mzZ7Ru3Zpx48bxzTff4OPjI4TAB7x48YKAgIAsBw96PgzXiRCA999rnv7hnz5RIMgAuU4M/OEZwLT9viiU6kz/kqnUEgqlmmn7ffnDMyDD1yVXBfzuu+8oWbIkXbt2JSgoiCVLlvD8+XMOHTpE9+7dMTMzy+ztCPIovXv3xtjYmK1bt+psji+//JJTp07h5+dHhw4diIuLS3F8165dODk5ce/ePU6dOsWyZcvInz+/zuzJjSTHCzRp0iTT18YqlIRExmvbpBSERMSL0sUCrZCrxECK9JxskpH0nNDQUH755RecnJyoU6cOe/bsYeDAgZp84++//16UBxZkiSJFitClSxc2btyILnfq6tSpw4kTJ/Dx8aFz5868e/eOt2/f0rdvX3r37k2rVq3w9fXF1dVVZzbkZry8vKhSpYqm/XBmCI6IQ9d7sBIQFBH3yfMEgk+RawqKP42MZ85hP62OOfuwH43K26SIIXj37h0HDx5k06ZNeHh4YGJiQpcuXViyZAmurq6ffQ12Qc4xaNAg2rZty40bN3Raza9hw4YcO3aMNm3a0KxZM0JDQ4mJiWHr1q18/fXXYkvrI3h5eWXJKwCQqMVUQkOYR/B5k2s8A7pMz5EkifPnzzN8+HCKFSvG119/TUxMDKtXr+bly5fs3LmTtm3bCiEg0Cqurq6UKFGCjRs36nyuevXq0b59e65du0ZCQgI+Pj707dtXCIGPEB4ezv3797McL2BqnDNfrzk1j+DzJld8igLCYjj/6LXWA3FUaonzj15TvmZjmjRpgoeHh6Yq4MWLFxkxYoSoCijQGUZGRgwYMIAdO3aQkJCgs3nu3LlDvXr1OHz4MMOGDePt27dMnz4dpVLsNX8Mb+/3KYFZFQMO1hboWmrJ/n8egSC75AoxsO1qCEZy3fxaSWoVxZv0wtPTk8ePH/Pjjz9SoUIFncwlEPyXQYMG8ebNGw4fPqz1sdVqNUuXLtVsQVy/fp01a9awd+9eDhw4wKBBg1CpVFqf93PB29ub8uXLU7JkySxdb2FmjL2OKwTaW5tjYSY8loLskyvEgC7Tc2RyI4zta4iqgAK9ULlyZRo2bKj1rYLg4GBatGjBlClT+O6777h27RrVq1cHoHPnzmzfvp0dO3YwfPhw1Gqx55wW2e1HAOBS2VZnDzJGchkulUQAs0A7GPzqJ9JzBJ87gwYN4uTJk1ppMCRJElu3bqV69eoEBgZy9uxZlixZQr58+VKc17NnTzZv3szGjRv59ttvdZrRkBuJjIzE19c322Kgb317ndYZ6NfAXidjC/IeBi8GRHqO4HPHzc0NU1PTbNcciIyMpHfv3vTv35+OHTty584dmjVrlu75ffv2Ze3atfz111+MHz9eCIIPOH/+PJIkZTmTIJmKdgVxrmCjde+AkVyGcwUbUYpYoDUMXgyI9BzB507hwoXp1q1btmoOeHh44OTkhIeHBzt37mTr1q0ZCn4dMmQIq1evZvny5UybNk0Igv/Hy8sLe3t7HBwcsj3Wwq5OGGtZDBjLZSzs6qTVMQV5G4MXA/pIzwkNDWX79u0MHz6cwYMH58j8grzNoEGDePDgAVevXs3Ude/eveP777+nVatWVKtWDV9fX9zc3DI1xjfffMOyZcv45ZdfmDt3bqau/VzRRrxAMqWtzJmn5f4BP3ZyFO2LBVrF4MNQk9NzdPm8IgP2b/qbXwMecO7cOZ48eaI5Zm1tjSRJIh9boFOaN29O6dKl2bhxIw0aNMjQNbdu3aJfv34EBgaybNkyxo4dm+Ug2O+//x6FQsHUqVMxMzNjxowZWRrncyAqKorbt28zevRorY3Zu649r2MVWqmgOrlVZdzqilgBgXYxeDGQnJ4TrMMgwkJGicyeMTXV+3K5nMaNGwshINA5yTUH/vjjD37//feP9ghQqVT88ssvzJkzB0dHR27evEm1atWybcOUKVNQKBTMnDkTMzMzJk6cmO0xcyMXL15ErVZrzTPg6+vL0KFDiYuL4+eNx5lz2I+ExCRk8oy3hzaSyzCWy/ixk6MQAgKdYPDbBKD79Jwu9Sry3XffpTqmVqvx8PCgffv2LFiwgNOnTxMdHa0TOwSCgQMHEhUVxcGDB9M958mTJzRr1oyZM2cyceJErl69qhUhkMysWbOYMWMGkyZNylLL3s8BLy8vSpQoQfny5bM1zoULF2jXrh3Vq1fn+vXrREdH07uuPafHN0UW/r5R2qe+15KPNypnzenxTYUQEOgMg/cMwPv0nI2Xg3Qytkot0b9BGSp0Wo6rqytubm4oFApNMRY3NzdCQ0NZunQpUVFRyGQyHB0dadiwIQ0aNKBhw4ZUrlxZ1CgQZJuKFSvy1VdfsXHjRvr06ZPimCRJbNq0ie+++w5ra2u8vLxwdnbWug0ymYwFCxagUCgYO3YsZmZmDB8+XOvzGDLJ/Qiy6hE8deoUc+bM4cqVKxgZvX/6l8lk9OzZE3gfQ1DSfz8ljGrh2OkbPP3DCYmIT7EVKuN9QSGXSrb0a2AvsgYEOidXiIHk9JxLjyO0mrNrJJfRqJy15hetQ4cO+Pj40L59ex4/foxcLmfVqlWYm5ujVqt58OABV65c4fLly1y+fJm1a9ciSRKWlpbUr19fIw7q1atHkSJFtGanIHcSp1ASFBFHolKNqbEcB2uLT1aLGzRoEMOHD+fZs2eUKlUKgNevXzNixAhN1cDly5dTqFAhndktk8lYsmQJCoWCkSNHYmpqysCBA3U2nyERGxvLjRs3GDRoUJauT0hIoFOnTigUCgDNQ4UkSdSvX19znq2tLXGhgczt5MhcHLP0WREItIlMyiW5RE8j42n5uxcKLaYAmhnLOT2+aaqo3Ldv39K/f3+USiXHjx9P9/qoqCiuX7/O5cuXuXLlCleuXCEyMhKAqlWrasRBgwYNqFatmuYpQfD5EhAWw7arIXg+DCckMo2nPStzXCrb0re+PRXtUj/tRUdHU6xYMY27/vjx4wwZMoSkpCTc3d3p1q1bjt2LWq3mm2++Yd26dWzbto3evXvn2Nz64tSpU7Ru3Zp79+5RtWrVLI1x/Phx3NzciI2NTZGqGRgYSLly5YD3GRzXr1/Hx8dHK3YLBNkl14gBgJ3XQ5i231dr4y3u5qTVPThJkggICNB4D65cucKdO3dQq9UULFiQevXqacRBgwYNsLa21trcAv3yNDKeGQd8Of/oNUZy2Uc9WMnHnSvYsLCrUyoxOmDAAC5dukSrVq1YvXo1bdq0Yf369RQvXlzXt5EKtVrNkCFD2Lp1K7t3785RMaIPZs6cydq1a3n58mW2AocXLFjADz/8gEwmQ5IkChcuzJs3bzRjzp49mw0bNvD06VNtmS4QZItcJQYA/vAM0Fp6zrcuum9IlOx2TBYHly9f5tWrV8D7PeIPYw+++OIL0SY5F7LzeghzDvuhVEuZ2sZKjhCf18mR3h+I0j///JNvv/0WMzMzfvvtN0aNGqXXjBaVSkW/fv3Yt28f+/fvp0OHDnqzRdc4OztTrFgx9uzZk+Uxrly5QpMmTRg8eDDR0dHs3LkTV1dXTp06pTln1apVTJgwgYSEBJGtJDAIct3KM8alIjYFzLL15Vs0xJOaZkUA3YuBAgUK0KxZM01ZWEmSePLkSQpxsH37dpRKJRYWFtStWzfF9oKtrWhEYshkR5yq/v/zO22/L69jFXzjXJZFixbx448/YmpqSseOHbWa655VjIyM2Lx5M4mJiXTv3p3Dhw/TunVrfZuldd69e8e1a9f49ddfszxGWFgY3bt3p27duqxcuRITExM6duyYKjPB1taWxMREoqKiRJt0gUGQ6zwDyWTVLTv4i3y0aPAlAK6ursyYMYOmTZvqVZ3Hx8fj4+OjiTu4fPkyL168AKBcuXIpxEGNGjUwMTHRm62C/6HtbavCD45y97A7M2fORK1Ws2LFCl6+fIm5uWFUmksWA6dPn+bYsWO4uLjo2ySt4unpSfPmzblz5w5OTpkv9ZuUlETLli3x9/fHx8eHEiVKpHuut7c3TZs25cGDB1SuXDk7ZgsEWiHXioFkNAFbGUzPkSSJAgUKEB8fr9nPq1WrFrNmzaJz584GkSIoSRJPnz5N4T24efMmSUlJ5MuXjzp16qTYXtDHXnJeR/sBrRKolCxvZUPnll8RGBhIhQoV2LJlC/369dPSHNknISGBzp07c+HCBU6ePMlXX32lb5O0xty5c1m5ciWvXr3K0vfA+PHj+eOPP/D09Pzkz+XBgwdUrVoVb29vnaSICgSZJdeLgQ/JaHpO69atU+zfyeVy1Go1/fv3Z/PmzTlpcoZJSEjg1q1bKYITk4OP7O3tU4iDL7/8EjMzMz1b/HnTf91VnaW6bhn6PgWtadOmmJiYcPr0aa3NoQ3i4+Pp0KEDN27cwMPDI0XKXG7GxcWFwoULf7ToU3ps376dvn37snLlSsaMGfPJ8yMjI7G2tmbPnj306NEjC9YKBNpF/4/BWsTCzBjHEoWpaV8ExxKF083TbdiwYYpAPZlMRr58+Qz6lzJfvnw0bNiQ8ePHs3v3bkJCQnj27Bl79+6lZ8+ePHv2jGnTptGgQQMKFSpEo0aNmDBhAnv27BERy1omICyG849ea71PvUotcf7Rax6FxwAwePBgzp49S3BwsFbnyS7m5uYcPnyY6tWr07p1a27evKlvk7KNQqHgypUrWSpBfOfOHYYNG0b//v359ttvM3RNkSJFMDY2Jjw8PNPzCQS64LMSAxmlXr16KJVKzb/lcjnnzp2jU6dOerQq85QsWZLu3buzdOlSLly4QHR0NNeuXWPJkiU4ODhw4MABevXqhb29PaVKlaJHjx4sXbqUixcv8u7dO32bn2vZdjVEp+Wxt14JAaBHjx6Ym5sbpLeqQIECHDt2jCpVquDq6sqdO3f0bVK2uHbtGgkJCZkWA2/evKFr165UrlyZv/76K8OxRzKZDFtbWyEGBAZDnhQDdevW1fy9cePGmJqa8ttvv+X6Xu6mpqbUrVuX7777ju3bt/PkyRNevHjBgQMH6NevH69fv2bOnDl89dVXFC5cmHr16vHdd9+xY8cOnjx5kuvvP6fwfBiuda9AMiq1hKf/+wWiQIEC9OjRg40bNxrk/02hQoU4ceIEDg4OtGzZknv37unbpCzj7e1N4cKFqVGjRoavUavV9O3blzdv3rB///5MB3ra2dkRFhaWWVMFAp3wWcUMZIZevXpRtWpVZs+ezcGDB+nRowe//PILkydP1rdpOkWpVOLr65siOPHRo0fA+y+nDzMX6tSpg4WFhZ4tNixiFUqc5p7UeUvtu3NbY2FmjJeXF82aNTPoQLOIiAhcXFx49eoV3t7eVKxYUd8mZZpWrVphamrK0aNHM3zNnDlzmD9/PsePH89SqmWbNm2wsLBg3759mb5WINA2eVYM/JcZM2awePFiTp48ScuWLfVtTo7y+vXrFGmN165dIzY2FiMjI6pXr54iOLF8+fJ5ukiKX2gU7Vde0Pk8/4z9CscShVGr1VSoUIFmzZqxfv16nc+bVcLDw2nWrBkxMTF4e3tTtmxZfZuUYZKSkihSpAizZ89mypQpGbrmyJEjdOrUiZ9++okZM2Zkad6BAwcSGBjIhQu6/zwJBJ9CiIH/R6VS0b59e65fv86NGzdy1ZeZtlGpVPj5+aXIXHjw4AEANjY2mnLKDRs2pG7duhQs+Hl1VPvxxx95+PAhHTp0oHXr1lhZWWmO3Qp5Q9fVl3Ruw4FRjahp/77Z1bx581iyZAkvX76kQIECOp87q7x48YImTZqQlJSEt7c39va5o93ulStXaNiwIVeuXMlQZkRAQAB16tShefPm7Nu3L8vpyJMnT+bQoUP4+2e/oqpAkF2EGPiAyMhI6tatS6FChbh48aLBFHsxBCIjI7l27ZpGHFy9epWoqCjkcjlffPFFiu2FSpUqGUS9hqzSrFkzvLy8gPeBXg0bNqRTp060bdsWI+sytP8j5zwDAEFBQZQtW5ZNmzYxYMAAnc+dHZ4+fUrTpk2Ry+V4e3t/tPCOobB48WLmz5/PmzdvPlnQKzY2lgYNGpCUlMT169ez1T1y6dKlzJ8/n6ioqCyPIRBoCyEG/sOdO3do2LAhXbt2ZcuWLXnaJf4x/tvS+cqVK/j5+SFJEkWKFEnV0jk3lVz9/vvv+fPPP1NknCQz+rvxHDNvkWMxA8k0b94cSZLw9PTU4czaISgoiCZNmmBhYcG5c+ews7PTt0kfpV27dqhUKk6ePPnR8yRJonfv3hw7doyrV69SrVq1bM27efNmBg4cyLt378iXL1+2xhIIsosQA2mwc+dO+vTpw7Jly/j+++/1bU6uIb2WzjKZLM2WzobgPYiLi8PPz487d+5w584dfH19uX79OnFxcanOrVChAh4eHgzc84TgyHid2VTG2hyvSSlL/SYvHI8fP84VW1iPHj2iSZMmWFtb4+npiY2Njb5NShOlUomVlRXTpk375N7/r7/+yqRJk9i7dy/du3fP9twnTpygbdu2BAcH55otFcHnixAD6TBp0iSWLVvG6dOnNU2GBJkjuaXzh5kLvr6+qNVqChUqlKql84d789pGrVbz5MkTzaKf/AoMDESSJORyORUrVqR69epYW1vz119/Ae9rUEiSxA8//MDs2bMxMjJi7mE/tlwN1kl6oZFcRv/6ZZjbyTHF+3FxcRQrVoxJkyYxZ84crc+rCx48eEDTpk0pUaIEZ8+epUiRIvo2KRU+Pj7UqVOHCxcu0Lhx43TPO3v2LK6urkyePJmff/5ZK3PfunWLWrVqcf36derUqaOVMQWCrCLEQDoolUpat26Nr68vPj4+lC5dWt8mfRbExsZy/fp1jTi4fPkyr1+/BqBSpUopMhccHR2z1NI5MjISX19ffH19NYv+3bt3NU/7NjY2VK9ePcWrWrVq5M+fH3hfbrdgwYKo1WpsbGzYtWsXzZs314wfEBaD6zJvLfw00ub0+CZUsE0dlDl06FDOnj1LYGCgQXhVMsLdu3dp1qwZ5cqVw8PDg8KFC+vbpBT89ttvzJw5k6ioKExNTdM85+nTp9SqVYsvv/yS48ePa63N+PPnzylVqhRHjx6lffv2WhlTIMgqQgx8hNevX1OnTh2KFi3K+fPnxb6eDpAkicePH6eIPbh9+zYqlQoLCwvq1aunEQf169dP0dI5KSmJhw8fpnDx37lzh2fPngHvizBVq1YNJyenFAu/nZ3dJ2NBGjdujLm5OVu3bk1zzzsnehP8lwsXLuDs7Iynp2eu8lbdunWL5s2bU61aNU6cOGFQ2SedO3cmJiaGs2fPpnk8ISGBJk2aEBYWho+Pj1a3OxITEzEzM2P9+vUMHjxYa+MKBFlBiIFPcPPmTRo3bkyfPn1Yt26dCCjMAZJbOieLg0uXLmkqtVlZWVGoUCESExMJDw/XBPmVLl1as9gnL/6VKlXKcrtnSZI++n+t/a6FYGokZ3XfWjQoZ51mXw1JkqhYsSJfffUVGzdu1Nq8OcG1a9do2bIltWrV4tixYwaRqZPs+fn+++/T3XoZPnw4W7Zs4eLFi9SuXVvrNlhZWTF16lSmTp2q9bEFgsygHX/XZ0ytWrVwd3dnwIAB1K1bl1GjRunbpM+a+Ph4/Pz8CAgIIDQ0lLdv36aI6o+JiUGhUPDu3TvUajWmpqbUqlULZ2dnzRaDNlo6f0r0lbYyZ14nR6bt9832XMkkqtQM3XzjfettK3NcKtvSt749Fe0KamwaNGgQixYtYuXKlQb1hP0p6tWrp6nU16VLFw4fPqx3T5uvry9v3rxJtx/BmjVrWLt2LRs2bNCJEABRklhgOAjPQAZJTjfLSK9ywadRq9UEBQWlcvEHBARonsorVqyYysXv4OCAXC4nISGBmzdvptheSN4eKFOmTIrMhZo1a6a7H5xd/vAMYOkp3RSNMZLLUKklnCvYsLCrE6WtzAkJCcHBwYF169blStfyuXPnaNeuHS4uLuzfv1+vrbZXrFjB5MmTefv2rSZeJJmrV6/SpEkThg4dyp9//qkzG5o2bUrp0qXZunWrzuYQCDKCEAMZJCkpiZYtW/Lw4UN8fHwoWbJkhq6LUygJiogjUanG1FiOg7VFuq2VP1fevn2bIpgvOaAvNjYWeO8qrVGjRgoXv6OjY6Zdyc+ePUshDnx8fFAoFJiZmVGrVq0UmQvaDAjdeT2EOYf9UKolnWUYGMtlzOvkSO+69ri6uqJQKPD21l0Qoy7x8PCgY8eOtG3blt27d2d5Kye79OjRg/Dw8FQ/x7CwMGrXrk3p0qXx8vLSmZCE9z1S3rx5g4eHh87mEAgyghADmeDDL4lz586l+1QTEBbDtqsheD4MJyQyPkWBmvRcwJ8DSUlJ+Pv7p1r4nz59CoCJiQlVq1ZN8aTv5ORE8eLFdRKLkZiYyO3bt1OkNgYHBwPv2z9/6D2oXbt2ttzWTyPjmXHAl/OPXmue6HXBpFaVKBJ6jX79+hEQEECFChV0Mo+u+eeff+jatStdu3Zl27ZtWovQzyiSJGFnZ8fIkSOZP3++5n2lUknLli158OBBpkR/VhkzZgznz5/n33//1ek8AsGnEGIgk1y7dg1nZ2cGDx6syUVPJjMLQlou4NyCJEmEhYWlcvHfu3ePxMREAEqVKqV5yndycqJGjRpUqlRJp09ZGeHFixcpmjLduHGDd+/eYWJiwpdffpkitbFMmTKZFikaIegfTkhEvE4qFc7vUJkx7Wrz/fff8+OPP+pghpzhwIED9OzZkz59+rBx40aMjIxybO579+7h6OjIqVOncHV11bw/ceJEVqxYwdmzZ3OkS+T8+fNZtWoVL1++1PlcAsHHEGIgC6xbt45hw4bh7u7O8OHDgay7iv/rAjY03r17x71791I86fv6+vLq1SsAzM3NUyz6yX/qsoCQNklKSkrV0jkwMBCAYsWKpWjKVLt27Uy1dI5TKLn6OIKR23xIUmnv18zMWE7dVyc5f/wAT548yTU1B9Ji165dfP311wwePBh3d3ed3ct/t+tOH9jBpHFjefv2reb/NLny6PLly/nuu+90Ysd/+fvvvxk9ejRJSUm5+v9RkPsRYiCLjBo1ivXr1+Pt7c31eCutBJFNalWJMS766QUvSRJBQUGpXPwBAQGo1WpkMhnly5dP5eIvV67cZ/cl9urVq1QtnePi4jAyMqJGjRopthc+1dJZV/UIqlkZcXRSG06fPk2LFi20NrY+2LJlCwMHDuSbb75h1apVWtsy+th2HUiYKKLo2+xL+ta3JyE8iAYNGuR4T5IDBw7QrVs3wsPDKVq0aI7MKRCkhRADWSQxMREXFxdCTEph1FB7neQWd3PCTccegqioKM2i/+GfMTExABQpUiRVhT5HR8dMPRV/TqhUKu7evZsiOPHhw4fA/1o6J4uDD1s667pSoYnHzzSo6sCWLVt0NkdOkextGzduHL/99lu2FuOsbNfx8gEFHxzl6pl/crQGwqVLl2jcuDF3797F0dHx0xcIBDpCiIFscOP+E7qvv43MyAS09CRhZizn9PimWokhUCqVBAQEpNrbTw6iMzY21gT0fZjCV6JECVFc6RNERESkaukcHR2doqVzdMXWXHuTT2cZBlWNX3F2yShevHhhcGV+s8Kff/7Jt99+y9SpU1m0aFGWPoNZ3a6T1CrMTIz5sfMXObpd9+jRIypWrMjZs2dxcXH59AUCgY7IWzluWmb5pXCMTEzR5ne9Ui0x44BvuiVp0yM8PDxVE5579+6hUCgAKFGiBNWrV8fNzU2z8FepUkXvAX25FWtra9q2bUvbtm2B996DBw8eaMTBhQsXiJLXw9iymE7mV6kl3uQvgUKhYM+ePQwbNkwn8+Qko0ePRqFQMGHCBPLly8fcuXMzdX12aj7I5EYkqiSm7ffldawix7brkktdi8JDAn0jPANZRF/NahISErh3716qvf3w8HAA8ufPzxdffJFqb9/a2lpntgpSE6tQ4jT3pE6yCZKRARX//Yv46DdcuHBBhzPlLD///DPTp09n4cKFTJ8+PUPX7LweotVqkDmxXQfvY3XMzc1ZvHhxjgUtCgRpITwDWWTb1RCd5ZMbyWVsuRLMkBoFU7n4/f39UalUAJqAvm+++Uaz8JcrVy5HU7QEaRMcEadTIQAgAW169mfiEDf8/f2pVKmSjmfMGaZNm4ZCoWDGjBmYmZkxYcKEj57/NDKeOYf9tGrD7MN+NCpvo/OUX5lMJkoSCwwCIQayiOfDcJ0VllGpJdYfv8qPnd+7fi0tLalevTotWrRg3LhxVK9enS+++IICBQroZH5B9knUYgOjj6FGToECBfjzzz/57bffPpvMjtmzZ5OQkMDEiRMxMzPj22+/TffcGQd8UWr5dzGr23VZwdbWVuPZEwj0hRADWSBWoSQkMl6ncxhZ2rHv8FHqflmdUqVKAe/rpa9Zs4aYmBgaNGig0/kF2cPUOGcW5RnTppAUG8vy5cv5888/KVWq1EdfdnZ2ucJzJJPJWLhwIQqFgjFjxmBqaqqp6fEhAWExnH/0Wuvzq9QS5x+95lF4TJrbddpEeAYEhoAQA1kgJ1zAIKNy7a8oaC6xatUq/vzzT+7fvw9As2bNmDhxos4tEGQdB2sLZKDzmIEH18/jfdaDwYMHM3z4cAoWLMizZ8949uwZ165d49mzZ5ogUgAjIyNKlCjxUcFQvHhxvfUL+BCZTMavv/6KQqFg5MiRmJmZMWBAyjReXW/Xbb0SwtxOuk35s7W1xc9Pu9scAkFmEWIgC+SUC/jrfgO4d/5Yiha+crlcKy16BbrFwswYeytzgnXoQbK3NqecfUnKDhzI4sWLefPmDatWrUpxjiRJREREaATCf1/JvSPi4/9np1wup1ixYh8VDCVKlMiRjoMymYyVK1eSmJjI4MGDMTMzw83NTXNc19t1nv7hzEX3YuDs2bM6nUMg+BRCDGSBnHIB3/fzTSEE4H3r3127duHt7Y2tra3mVbRo0RT//vD9nCyiIvgfLpVt2XI1WGdPrS6VbIH3C+bgwYOZM2cOb9++xdLS8j/ld02oWPULvvzyyzTHkiSJt2/fpisYTp8+zbNnz4iOjk5xna2t7UcFQ8mSJbXy2ZPL5fz1118oFAr69u2LiYkJ3bp1y5HtupCIeOIUylSdRt++fcv169dp0aJFtuM07OzsRMyAQO8IMZAFcsoFfO3MP4wfO5pz584hk8mQJAkjIyPatWtHzZo1CQ8PJzw8nKCgIK5du0Z4eDhv3rxJNZaFhUW6QuG/79nY2BiEi/hzoG99ezZeDtLJ2Cq1RL8G/0t9GzBgAJsOnmLe0fvcfJGQqW6ZMpmMIkWKUKRIEZycnNKdMzo6mufPn6cpGC5cuMDTp09Tff6sra0/GceQkUBYIyMj1q9fj0KhoHfv3uzfv5+ytZxzJGMjKCIOxxKFUalUnD59Gnd3dw4dOoRKpeLy5cvZjt+xtbUlPj6e2NhYERQs0BuizkAWabrEU6cu4DLW5nhNckGSJHbt2sXYsWOJjIxErVazZs2adIvMJCYm8vr1a41QePXqlebvab0+dA8nY2Vl9VFPw4f/LlKkyGcTwa4LdNGbQCapqedgya5v3nfVM6RumXFxcekKhuRXcpOrZAoXLvxJwVC4cGFkMhlJSUm4ubnxzz//sHzrIX6+qdKq/WmxyMUKz70b2LVrVyrvyPHjx2nTpk22xj9z5gwtW7YkMDCQcuXKZWssgSCrCDGQReYe9tOpC7h//TIpApeioqL44YcfWLVqFV5eXnz11VdamSsuLi5dwZDW+//dtjAyMtIIhIwIiAIFCuSpUsdPI+Np+bsXCi3GmUjKRJIOzWHTql+JsKyc67plJiQkEBoamq5YePr0KWFhYXz41VSgQIEU8QqXLl3ieZwM24G/69ze0PVjSQp/kuax6dOnU7FiRUqWLKl5JQuXjOLr60v16tW14mUQCLKKEANZRJ8VCPPly6ezeT9G8t7ypzwOycciIiL478crX758GY51KFq0qN7uVZtouzre9Ob27FsykauxRSjSNPtNsvTZLTM9EhMTefHixUcFQ2h4BKUn7NGpuJQB77aMJux5SJrHTUxMSEpKSvFe/vz5U4iDtF7FihXTlAIPDw/Hzs6OgwcP0rlzZ53di0A7/LcdtoO1RaqYktxI7r8DPVHRriDOFWx00p62UTnrdHOb9bk4fri3XLly5U+er1QqiYiI+Ki3wd/fnwsXLhAeHq7pmvghhQoVylCsg62tLdbW1gaZQ9+7rj2vYxVaaXM9uVVlRrpUoFChNfgfvKsF62DpKX+KFjDLkfK7GcXU1JQyZcpQpkyZdM+Jjo6m5uxDqPJb6cwOe2tzPEOesGzZMqZMmaKp/gnvG321b98ef39/AgMDNSmcCoWCV69eERsbi7+/P4mJiURFRaXwqslkMooWLUrJkiUpUaIEAOvXryciIkLzXsmSJSlSpEie8qR9iCEtuh9rh/2xeJzchPAMZANduIC12bUwt5GQkJCmxyEsLIxXr16lOvZh/jy8/4K1sbFJVyz8V0hk1p2bXbLaUS/Zpf9jJ0fc6tqLz90HzNh3m+3XnoIu4lbUKuyi/WmcP1RT+GvFihWarp+lS5cmJOS9x0CtVvP8+XMCAgJ49OhRij8DAwNJSEgA/retZm1tjYWFBUZGRiiVSm7evImZmVmqGJ78+fNrhEHyK61/fy4Nxwxt0TWkeBxdI8RANsmtDVJyO5IkERMT88lAyeT3X716hVqdcvE0MTHJkMdBmymaWflysVG+Ys+UbpQtWgjQTVBiskcqJ8rvahNdb9fZ+24iLOBfnj17lmqhtrCwwNHR8ZO1GJKFQrI4SE8oyGQyHBwcKFWqFEWLFqVgwYKYmpqiVquJjY3l5cuXPH/+nOfPn/Pu3bsUtiR7GdISC8kvKysrg/UyGOKim13xro94nOwgxIAWyE7r1A+Z3Koy37pU0IJFgv+iVquJjIz8ZIBk8uvt27epxkgvRTMtIfGpFE3NE5B/OCERaTwBWZvjUsmWRyc2sG31r9SqVYtjx44RjbleYlUMmf7rrnIp8DUqLX6T/Vcc/bcWw927d4mKikoV15DZWgzFixfnzZs3dO7cGblcTvPmzTVi4dGjRxqhIJfLKVOmDBUrVqRChQqULFkSS0tLjdgICwvTCIXnz58TGhqaKggzX758lChRIl2xkCwkcqKY1IcY4qKrre90Q4zHSQ8hBrREdj7QamUS5d/cYN+SSRQuXFiHVgoyyn9TND8lINJL0fyUx8HW1haLwlZEqUxJUkup9kaXLFnClClTNFsgXeZv40xIUo5lseQGDGnb5GO1GJ4+fcqzZ89S1WKwsrJCrVYjl8vp2bNnCs+Cqakp8fHxPHv2LMX2w8eEQvKfDg4O5M+fn1evXqUQCR+KhufPnxMXF5fCHmtr64+KhZIlS2JjY6MVL4MhLrp51dsrxIAWyYyrC0kNMjk1i+fn6h/jeBHgi4WFBTNmzGDs2LEULJi7ns7yOtpM0fzwdf/+fU6dOoUkSchkMoqPcMekiO7KUSfXt8htrPd6wI8nArU2ni6/wNOqxbBz506ePHlCxYoVM1SLoWTJklhYWCBJEu/evSMyMpJnz55pxMKnhELFihUpW7YsJiYmGgGTllBIfoWFhaXYZjM1NU3Tw/DheyVKlCB//vzp/hwMcdE1JGGZ0wgxoAMy4gJuXNaSA79MQIp6QcOGDdm4cSPw/pe3UKFCTJ8+nW+//RYLCwt93IJAh2QkRTP5/aCgII3XQWaan9Ljd+s8le7u3Na5KlVKrVbTpUsXrsYWIX/9XtkeTx/bdYsWLeLXX3/l9ev3HRg/VYvh2bNnvHz5MsU2gIWFhUYoWFtbY2ZmphELb9++5cWLFzx58iSVUPivSKhQoQLlypVLEZSoVCpTbUX89xUaGpoqI8jKyirNOAYz65IsvCUjUYttXrSx6ObleBwhBnTMx9Jj/P39qVu3Lg4ODty5cyfVtfb29gQGBmJsnHu+mAXaZf78+fz4448olUpMbMtSYshKnc9pfHoJ+d69xtTUNM2XiYlJuseycl5GzjU2Nk5XBM2fP5/Zs2dz9OhRYmyd3m/XqdSZiiH4b8ZGTrNu3TqGDRtGUlJShn/fk5KSPikYQkNDUzzRm5mZUbx4cQoXLqxJU05ISODt27e8fPlSk6Ejl8uxt7dP16OQXlxBTEwMO3bsYMmSJXTv3p3ChQun2qJ48eIFNj3nks++OjIj7X23ZXfR1VftGENBrDI6xsLMGMcSaccBVKpUiW3bttGxY8c0j7u5uQkhkMdRqVSoVCrkcjkyo5zpGdHUpQUFEyNITExM8xUfH09iYiJJSUnpnpP8SkpKSlWUJ6ukJRySkpJ4+fIldnZ2zJs3D1NTU2wL2hBRrjXxheyR1Cpk8vRrT8iQkJBRwiiW1laRRN16yka/7AkcExOTTJfotrOzA+DVq1cZ7kpqYmLyyVoMyU/0HxMMz58/T/F/ZGRkhKWlJUlJSdy/f59bt24RFRWlOSdZKCSLg/8KhcDAQB49esTixYsZMmQIS5cupUiRIprxH7yIos2KC5n6+WQElVri/KPXPAqPSXPRvX37NjKZjBo1aqR5/efQDjs7CM+AATBt2jQWL14MoGlI9NdffzFy5Eg9WybQN+7u7kyaNInvv/+eGOPCHEyoqvM5/xn7VboCNitIkvRJ4ZBRYfHhv1++fMnatWspUaIEbdu21RxP/jMac56bl+Nt/hIYWRZP6VmQJIh9heqZLwl3PVCEB5OYmJiqdkVWMTY2zpRnJC4ujkuXLtGqVStsbW1zzCtjYmKCTCbj1atXHxUMT58+JTExUXN/MpmMfPnyIZPJUCgUmmJMMpkMMzOzFOmSBQoUYMGCBYwcORIzMzOdlnKX1Crw96b4iwup4hnmzZvHo0eP6Ny5M4sXL05VOC2n+s0YKkIMGABqtRpzc3MUCgVOTk5ER0dTtGhRLl68+NkUExFkneTgwfA3UdRdfF7EDPA+CK9hw4bEx8dz48YNLC0t0z333r17NGvZGrsKXzBsxDdMnjiev5cuYHD/r1OdK0kSKpUqWyIlK+e9efMGDw8PatWqRcGCBTM83n8DUbOCTCbLsGiQJAmlUolSqdSIp3fv3hEXF0d8fHyKCo1pYW1tjc3gVSQY6647Y0HeUeflPyniGaKiolKdZ2lpiZOTE+XKlcO2RGl2S7rtC2Hov1tCDBgIyQFEtra2/PXXX7Rs2ZIxY8bw22+/6ds0gQFRfcZ+oiXd5YEb+tMLvF+w+/Xrx8GDB7ly5cpH2y4nc+fOHVxcXJDJZERERGBnZ0dQUFC65b1zuhTuu3fvMDc3Z8uWLfTr1y/D16nVaq14XbR1XkJCAv7+/ql6kiSTE0GwSBLFLy4ln/H/RI5cLufUqVMaj8WHWFpaUtC+KvJ2M3Vn0/+jba+bNjFMiZIHmT59Ol26dKFevXqsXLmSX375hfHjx9O8eXM6dOigb/MEBkKHWmXZdv3pR/fBs4qRDFwq2Wp9XG2zYsUKtm/fzo4dOzIkBACqV6/OkSNHaNy4MfC+OdCiRYuYN2+e5hx9lsLNnz8/BQsWJCwsLFPXyeVyzMzMcrxQUHooFIoUAsvExIQOHTowceJEGjZsiO+zN3RefUW3RshklKpaE7P4VymEyn8rkCaTmJjIgUNH6P63ju0CErWYsqhtRCN6A6Jq1aps2rSJvXv3kpCQQKdOnRg4cCDPnj3Tt2kCA2GwcwWdCAEAlQSFX6XOajEkvL29mTRpEhMmTKB3796ZuvbJk/+1IZYkiZ9++okHDx7wNDKe/uuu4rrMmy1Xgwn+jxAAkIDgyHi2XA3GdZk3/ddd5amW95dtbW0JDw/X6pg5jbGxcYrgSZVKxYEDB+jevTt9+/YlSZtlIj/CjFmz2bp1K7t37+bgwYMcO3ZMU7sluZlZ5cqV2bJlC2/fviWfac48F5saG+6Sa7iW5VG6devGzJkzmTlzJv3798fc3Jw+ffpoZW9QkPupaFeQBmUKvw+U0iJGMrBMeMGEYV/Tt2/fNMsx65vnz5/Tq1cvvvrqK03AbWZwd3dPsVCp1WrcZqyg5e9eXHocAfDJoLbk45ceR9Dydy92Xk+7tXFWsLW1zbRnQJ8olUpCQkI4f/48W7ZsYcGCBXzzzTcpaqMkP42HhYWxa9cuYt6+SW84rZLWoptsS61atTh8+DD37t2jX79+mJiY4GBtga67NsgAB2vDrRsjtgkMkHnz5uHj48OIESP466+/+Prrr5k3bx7z58/Xt2kCA2BJr1o0++U0yv8PLNQGxkZyjvzwNefrmjNq1CguXLjA1q1bcXZ21sr42UWhUNCjRw+MjY3ZtWtXplNuAwMD8fZOmUNesEFPoiq3B6UKMrkUqP6/7Pi0/b68jlVopRSuTbGShESruRXyRu8te+H9zzwkJITg4GCCg4MJCgrS/D04OJhnz56lCBi0sbGhTJkyFCpUiNjY2BRxA87OzmzevJmixUshwz+V50WbpLfobtiwAUtLS5o0aZLq98bCzBh7K3OdZhPYW5sbbPAgiABCg+XNmzfUqVOHAgUK0KVLF+bPn4+HhwctWrTQt2kCA8D9jB8LTwdpbbwPS7kGBQXRv39/Ll26xPTp05kzZ85Hmy7lBKNHj2bdunV4e3tTv37mi8ocPXqUjh07YmRkhImJCeZOrhRsob3U3ayWwv0wTuG/C5Gu4xRiYmJSLO7/XfRfvnz5P1tkMooXL46Dg4OmtsF/X8kegSlTpvDrr78il8sxNTVl+fLlDB06VLMAG2oKny5THnND3w8hBgwYX19fGjRoQMeOHXn9+jV+fn7cvn1bU6BEkLdpO2k5902yXzY3rfK7KpWKxYsXM2fOHGrWrMm2bduoWFE/3dc2bNjAkCFDcHd3Z/jw4VkeJzo6mgIFCjB2+jz+kb4EI+2l7Wa2FK6uW/ZKkkRkZGSaT/TJr8jISM35xsbGlC5dWrOw/3fRL126dIbTnN3d3Rk5ciQtW7Zk3bp12NunFEmGuujm9QqEQgwYOLt378bNzY25c+fy559/8uWXX3L8+PFMVzgTfH48f/4cx04jsG71DciNstT+9VPld69du0bfvn158eIFy5cvZ8iQISlcrDExMTptquXj40Pjxo3p378/a9as0cqYTWbvJliRT6uBmJkphauNlr29apfi5cuX6brwg4ODU3QjzJ8/f6on+Q8X/OLFi2sC67JLQkICV69eTdMdD4a96IreBAKDZsqUKfz2228sXLiQadOmsWjRIqZOnapvswQGwKhRo9h34hwtp6/j0pM3n3zKlMtALZGpp8zY2FjGjRvHunXr6NatG+7u7lhbW7Ns2TKmTp2Kj48PX3zxhTZvC4DXr19Tu3Zt7Ozs8Pb2TrcmQGbQ90KU7Za9kgQyGTEXthF5YYfmbUtLy3Td9w4ODlprOawtDHXRFV0LBQaNUqmkbdu23L59Gzc3N/766y+8vb1p1KiRvk0T6JmgoCAqVKjA0qVLad9n6Ee7ZZomRvPqzjmmdW/MlG8GZHqu/fv3M3z4cPLly8fs2bMZM2YMSqWSDh06cOTIkQyNkdFiPkqlkjZt2nDnzh18fHwoXbp0pu1Ni7mH/dh8JQgdeKg/6aLWdsver8ur6V3v/YJfuLBhFrJJD0NedA2xtXJOIMRALiEiIoLatWtjbW2NqakpoaGh3Lp1CysrK32bJtAzgwcP5tSpUwQGBmqentNadPv17snBgweRyWRs3rw5U5Xuknn+/Dn9+vXj3LlzmvK0ABcvXkxXnGalmM+0adNYsmQJp0+fxsVFexURcyp47e3btylc9veCwzhhVBdJZgRaekLPLU+c6WGoi+6jR4/4J0jF72ceZXssfbTDzipi4zmXYG1tzYEDB7h37x4lSpQgJiaGoUOHplv2U5B3mD59Oi9evGDjxo2a95K7Zda0L4JjicJYmBnz4sUL4H1w2YABA1Kcn1FKlixJ1apVUwgBIyMjJk+enOqzmNViPu7b97N48WJ++eUXrQqBWIWSEB0KAYDg13EUtralSJEifPnll3Tu3JlJkyZxIqIIkkyuNSEAoFRLzDigvcU0p+ld155JrSppZazJrSpnSwjExsayceNGqlevTsWKFfE/sIKfuzlhZizHSJ65/zMjuQwzYzmLuznlGiEAwjOQ69i6dSv9+/dn2LBhrF27lpUrVzJmzBh9myXQM3369OHy5csEBASkmwZoY2NDRESE5t8ymQx3d3eGDRuW4Xk8PT1p3rx5mseOHj1K+/btgewFyamVSZR748Ppv+dpdZ/bLzSK9iu13zr3v/QqGEjt8naaPftomTmtl+tuXkOPUv8U2Q2o/FQQbHpIksSlS5dYt24dO3bsSNG34Ny5czRt2lTnWR+GhBADuZBx48axatUqOnfuzJEjR7hy5Qo1a9bUt1kCPeLr60v16tVZv349gwcPTnU8Pj4+RWW4D7l582aGPz8XLlxg5MiRBAYGpmr3a2lpyZs3b7IfJPf/TGpVSSvFfJK5FfKGrqsvaW289DgwqhE17Yto/m2oqXSGhD4W3SlTprBkyRKMjY1TVHgtVKgQkZGRKbIrNFtd6cTj2Fub41LJln4N7HOtMBNiIBeSlJSEq6sr9+7dw87ODoVCgY+Pj05TvASGT7du3fD19eXBgwep0sT8/PxSRfzb29vTv39/Zs2alelIfbVazdOnT3nw4AEPHz7k5MmTREVFMeb37Qa5Dww55xn4b2c6Qy2yY4jk5KJ74cIFWrduTUJCgqZUsZGREW5ubmzbti3d63K6o2VOIcRALiU8PFwTUBgYGEjnzp3ZsmWLQaUPCXIWHx8f6tSpw/bt2+nTp0+KY5cvX6ZRo0YUK1aMatWq4eXlxcuXL7GxsdHa/IYcIQ7vv8S/mHtS56VwP+xZH6tQ4pTDc34u5MSi6+3tTfPmzVOUVd66dSt9+/bV6jy5ARFAmEuxtbVl//79PHjwgLp167Jt27YsBYQJPh9q165N27Zt+emnn1K1a61fvz6PHj3i+fPnbN++HUmSOHDggFbnn3HAF6WWXeHaDJJLrj+vS/5bfz44Ik6nQgDeB2EGRcR98rzcRlpBsNpEoVAwf/588uXLh63t+9bdMpmM1q1ba3We3IIQA7mYunXrsnr1ajw9PWncuDFjxozh/v37+jZLoEdmzZqFn58fhw4dSvG+XC6nfPnyyOVy7OzscHFxYefOnVqbNyAshvOPXmt9X1ylljj/6DWPwmO0Mp5LZdtMR4dnFCO5DJdKtiney6n+9Tk1z+eCSqWif//+nD9/nn/++YebN29SuXJlGjdurFVvWW5CiIFczuDBgxk9ejRXr17F1taWXr168e7dO32bJdATjRo1wsXFhfnz53807bR37954enpq0g2zy7arITpdZLde0U6r4L717XUSyAfvhUu/BinjG3Kqf31OzfM5IEkSY8aMYd++fezcuZOmTZtSsmRJ7t69y8mTJ/Vtnt4Qn6DPgN9//5369esTGxvLo0ePGD9+vL5NEuiRWbNmcevWLY4fP57uOd26dcPIyIi9e/dqZU7Ph+E6XWQ9/cO1MlZFu4I4V7BBrmXnvZFchnMFm1RBbQ7WFplsjpx50mvZK0ibOXPm8Ndff7FmzRq6dOmied/Y2Bhz89yVDqhNhBj4DDA1NWXPnj2YmJhQsmRJ/v77b3bv3q1vswR6wsXFhUaNGn3UO2BlZUXr1q3ZtWtXtufLiWI+IRHxxCmUnz4xAyzs6oSxXKbVgl3GchkLuzqlel8fcQqC9FmxYgXz589n8eLFDBkyRN/mGBRCDHwmFC9enH379hEcHEyFChUYPnw4jx8/1rdZAj0gk8mYNWsWV65cwdPTM93zevfuzcWLFwkJyZ4LPrcFyZW2Mmd809JazbwZ09A23YyHnI5TEKTN9u3b+f7775k4cSKTJ0/WtzkGhxADnxENGzbkjz/+4NGjR5iZmeHm5kZiYqK+zRLogTZt2lCrVi0WLFiQ7jmdOnUiX7582fYi5bYgucjISB6d3MQbr81aGc/I7x8WDeuIn59fmsdzOk5BkJoTJ04wcOBABg4cyJIlS0QKdhoIMfCZMWLECIYNG8bbt2+5ffs206dP17dJAj2Q7B3w9PTk4sWLaZ5TqFAh2rdvn+2sgtwQJJeQkMDevXvp3LkzRYsW5bfffiP++n6czUKyXX/+0po5FC1alKZNm3Ljxo1U5ybHKWjbO5BenIIgJZcvX6Z79+60bduWtWvXCiGQDkIMfGbIZDL++OMPatWqhYWFBb/99htHjx7Vt1kCPdC5c2ccHR0/6h1wc3PDx8eHR4+y3qHNkIPkQkJCGDJkCDY2NvTs2ZOjR49qajCUKlUKy4h7nB7flEblrAE+uWAnH29UzprT45viVtceOzs7zp07R8WKFWnevDne3t6prkuOU9Am6cUpCP6Hn58f7du3p3bt2uzatQtjYxFbkR5CDHyGmJmZsXfvXkxNTbG2tmbgwIE8e/ZM32YJchi5XM7MmTM5ceJEmk+sAO3bt8fCwiJbgYT6CpKTJImYmBiSkpLSve7o0aNs2LCBuLj38QbJQiB//vyUL1+ely9fUtrKnC1D6+Mxrgn965ehjLV5KnEj433Z3/71y3B6fBO2DK2fIkagSJEieHh4ULduXVq3bs2JEydSXF/aypx5Wu4f8GMnx1zXDCcnCQ4OpnXr1tjb23P48GHy58+vb5MMGlGO+DMmudRm/vz5qVmzJmfPnhXKOI+hUqmoWrUqjo6O6VYc7Nu3L3fu3MHXN+uV/nTdjKec6hmhR5aTP39+oqKiiIyMJDo6GqVSSceOHTl8+HCa16rVakaPHs3ff//9v/GMjOjSpQsWFhYEBgZy4ULqfgVZLYWbkJBAr169OHHiBNu3b6dHjx4pjhtqE6fPjVevXvHVV1+hVCq5ePEixYoV07dJBo/wDHzGNGnShGXLlhEbG8uFCxf48ccf9W2SIIcxMjJixowZHDx4MN3Fvnfv3ty9e5e7d+9meR5dB8mpHpzj3r17mi2NyMhITae5GjVqpHutXC5n2LBhKdo6q1QqunTpQrFixXj58mWa12W1FG6+fPnYt28fPXr0wM3NjQ0bNqQ4PsalIj93c8pWnELEseX89HUTduzYkaLbnuA9MTExtG3blqioKE6dOiWEQAYRYuAz59tvv2XAgAEYGRmxYMECzp49q2+TBDlM3759KVOmDAsXLkzzeKtWrbC0tMzWVoGug+RO7d2Mi4tLquAvmUzG119/ne71vr6+tG7dmpo1azJt2jTgvUBo164dxYoV48WLF1qtNwBgYmLCli1bGDZsGEOGDGHFihUpjveua5/lOAWPcU1IeujNy5cv+frrrylbtiwrV67UbIPkdRQKBV26dCEgIIATJ05Qvnx5fZuUaxDbBHmAd+/e0bhxY+7fv0+hQoXw9fXVNOYQ5A3++usvRo8ezf3796lcuXKq40OHDsXb2xt/f/8sR1vrumthTEwMjRo14v79+6hUKmSy94WDChYsyIABAxg1ahSOjv/bl/f396dJkyYUL16cs2fPUqRIEVatWsWLFy9YsGABO3fupE+fPkRHR+uk/bckSUyZMoWlS5cyf/58Zs6cmepnm5WWvW3btk0RkyCTyShUqBA///wz33zzjdbvI7egUqlwc3Pjn3/+4eTJkzRp0kTfJuUqhBjIIwQHB1OrVi1iY2Np2rQpJ06cQC4XjqG8QkJCAuXLl8fV1TXN7panTp2idevW+Pj4UKtWrSzPs/N6CNP2a6fLIMDibk641f1fHn1oaCi1a9cmPDwctVrN1q1befjwIWvWrOHly5c0adKEUaNGUatWLVq0aEHBggXx8vKiaNGiqcY+d+4cLi4uPHz4kEqVKmnN5g+RJImffvqJH374gUmTJvHLL7+kK7aS4xRW/70G97/+ZOPKJXzdq3uq8+bPn8+8efNStN0FaNeuHf/8849O7sPQkSSJb775hnXr1rF//346deqkb5NyHWI1yCOUKVOGPXv2kJSUhIeHB0uWLNG3SYIcJF++fEyePJmtW7fy5MmTVMebN2+OjY1NtmsO9K5rz6RW2llYJ7eqnEIIAJQoUYJTp06RL18+ypQpQ58+ffjxxx8JDg5m165dyOVy+vTpQ9WqVYmLi2PTpk1pCgF4X7UTSDduQBsk13tYvnw5S5cuZdSoUakW8WSS4xQuHNpKUvgTJo//joSEhFTn1a9fP9UYgwcPZv/+/Tq5h9zADz/8gLu7O2vXrhVCIIsIMZCHaN68OUuXLgVgxowZXL58Wc8WCXKSESNGYGVlxc8//5zqmLGxMT179mTXrl2a9Lusoo0gucXdnPjWpUKa5zg5OXH9+nWOHTum8W6ZmprSq1cvdu3aRbly5TA3NycpKYkGDRrQuXNnTp48meq+kgPLdCkGkvnuu+9Yv349a9asYcCAAemmQz569Ih///0XgBcvXrBo0aJU59StWxd4LzSS779atWqYmZnpyHrDZvny5fz0008sWbKEQYMG6ducXIsQA3mM8ePH4+bmBkD37t158+aNni0S5BTm5uZMnDiRjRs3pll3onfv3oSEhHDlypVsz5WdILnkYj4fo1q1alSrVi3Fe5GRkbi6uhIfH8/Nmzd58eIFq1evJjg4mDZt2lCpUiWWLl1KREQE8L4CY758+bTWxvlTDB48mJ07d7Jnzx66d++e5lP/+vXrMTIyAt67vhcuXMiDBw9SnFOkSBEqV66MlZUVXl5eTJ06lalTp3L69OkcuQ9DYtu2bYwbN47JkyczadIkfZuTu5EEeY64uDipSpUqklwulzp06CCp1Wp9myTIIaKioqQiRYpI33//fapjKpVKKlGihDR27Fitzun/Mlqac+iu1GTJWclh2lGpzAcvh2lHpSZLzkpzDt2VAsKiszxHVFSUVLduXcna2lq6e/duimNqtVq6dOmS1K9fP8nU1FQyMzOTBgwYIF25ckUqW7asNG3atOzeYqY4duyYlC9fPql58+ZSTEyM5v2kpCSpaNGiEu/7MkmAZGRkJDVu3DjV72hISIj0+vVrSZIkSalUSq1atZKsrKykx48f5+i96JNjx45JxsbG0uDBg8V3mBYQYiCPEhgYKFlYWEiAtHz58nTPi01Iku4+fyvdDI6U7j5/K8UmJOWglQJdMHfuXCl//vzSy5cvUx0bP368VKxYMUmpVOpkbl18nmJjYyVnZ2epcOHC0s2bNz96bnh4uLR48WKpbNmyEiBZWFhIDRs2lGJjY7NtR2bw8vKSChYsKDVo0ECKjIyUJEmSjh49mkIIyGQyycjISAKkM2fOfHS8iIgIqVy5clKNGjWkuLi4nLgFvXLx4kUpf/78UufOnaWkJPGdpA1ENkEeJjmC3MjIiOvXr1OzZk3gg3Snh+GERKaR7mRljktlW/rWt6einWiSktuIjIzEwcGBUaNGsXjx4hTHrl69SoMGDTh79iwuLi56sjDjJCQk0KlTJy5duoSHhwcNGzbM0HUqlYqTJ08ydOhQXr58SeHChRk4cCCjRo2iSpUqOrb6PTdu3KB169aUKlWKU6dOceHCBUaPHo2NjQ1hYWFYWFjQt29fSpcuzYABA7Cw+HhvBl9fX02MxLZt2z7bhjx3797F2dmZ6tWrc+LECVFmWEsIMZDHWbBgAT/88APFixfnzNXbLDz1hPOPXmMkl320olzycecKNizs6iRqpOcypk+fzh9//EFQUBDW1taa9yVJoly5crRq1SpFCV9DJCkpie7du+Ph4cHx48dp1qxZpsf49ttv8fT0pHPnzqxbt45Xr17RvHlzRo0aRefOnVNULtQFfn5+uLq6UrBgQTw8PLC3fx8rMXjwYB48eJDpIN/du3fj5ubG0qVLmThxoi5M1itBQUE0btwYW1tbzp07R+HChfVt0meDCCDM48ycOZPWrVsTU9SJDn9e5dLj98FVnyotm3z80uMIWv7uxc7rITq3VaA9JkyYgEqlSlUdTyaT0bt3b/bu3fvRBkD6RqVS0b9/f06cOMGBAweyJATgfUZBREQEixYt4unTp2zbto3ExER69uxJmTJlmDNnjk6bfDk6OnL+/HkSExNxdnYmICBAY1dWshx69erF1KlTmTJlymcXUBgeHo6rqyv58+fnxIkTQghoGSEG8jgymQzXcb9i3e47VMgzXV9epZZQKNVM2+/LH54BOrJSoG2KFi3KN998w4oVK4iKikpxrHfv3kRGRhrsYqJWqxk2bBh79+5l165dtGnTJstjFS9enFevXqFUKjEzM+Prr7/m/Pnz/Pvvv3Tu3JnffvsNBwcHunfvzunTp7VeuhigfPnynD9/HnNzc5ydnblz5w7FixfPcqnkn376iZYtW+Lm5pZmTYncSHR0NG3btiU2NpZTp05hZ2enb5M+O4QYyOPsvB7CSq8grYy19JQ/u4SHINcwadIk4uPj+fPPP1O8X716dapUqZLtAkS6QJIkxo4dy6ZNm9i8eTNdu3bN1njFihVDkiTCw8NTvF+9enVWr17N8+fPWbFiBQ8fPsTV1ZUqVaqwbNkyrafklipVCm9vb0qUKEGzZs2IiYlBoVCkEmoZwcjIiB07dmBpaUnXrl2Jj4/Xqq05TUJCAl26dCEwMJCTJ09Srlw5fZv0WSLEQB7maWQ8cw77aXXM2Yf9eBqZu7988golSpRg6NCh/Pbbbyka3SRvFRw8eDDNXHh9If1/rf8///wTd3f3jzYoyiifqkJYqFAhRo8eja+vL15eXtSqVYspU6ZQsmRJhg4dio+PT7ZtSKZo0aKcPXuWatWq8dNPPwFkuQaClZUVBw8eJCAggGHDhunEo5ETqFQq+vbty+XLlzly5AjVq1fXt0mfLUIM5GFmHPBFqeW2s0q1xIwD2qtNL9AtU6ZM4e3bt6mCBd3c3IiOjk7REEffzJs3j6VLl7J8+XKGDRumlTGTqxB+atGVyWQ0afK+bfDTp0+ZNWsWHh4e1KlTh3r16rFx40bevXuXbXssLS05efKkpj/EgQMHsjyWk5MTGzZsYMeOHfz222/Zti2nkf6/38ChQ4fYs2cPzs7O+jbps0aIgTxKQFgM5x+91noPepVa4vyj1zwKj9HquALd4ODgQP/+/VmyZEkKL0CVKlWoUaOGwWwVLFmyhHnz5rFw4UK+++47rY1ra2uLTCbLVLCenZ0dM2bM4MmTJxw6dAhra2sGDx5MyZIlmThxoiYIMKtYWFhw6NAhAGbPnp2t1tK5OaBw5syZrF27lvXr19OhQwd9m/PZI8RAHmXb1RCt955PxkguY+sVETuQW5g+fTrh4eGsX78+xfu9e/fmyJEjKbYQ9MGqVauYMmUKM2fOZPr06Vod28TEBBsbmyxF7hsZGdGpUyeOHz9OQEAAQ4cOZePGjVSqVInWrVtz8OBBlEplluyytrbG3NycL7/8kj59+rB27dosjQO5M6Dw999/Z9GiRfz6668MGDBA3+bkCYQYyKN4PgzXulcgGZVawtM//NMnCgyCihUr0rt3bxYvXkxiYqLmfTc3N+Lj4zly5IjebNuwYQNjxoxh3LhxzJ8/XydzFCtWLNv9CSpUqMCSJUt49uwZmzZtIjo6mq5du1K2bFnmz5+fpfGTgwlHjx7N8OHDs+zqz20BhVu2bGHChAlMnTqVCRMm6NucPIMQA3mQWIWSEB0H+YVExBOnyNpTkSDnmTFjBiEhIWzdulXzXtmyZalfv3623NTZYdeuXQwbNowRI0bw22+/6ayiXvHixbXWuTB//vwMGDCAy5cv4+PjQ5s2bVi0aBH29va4ubnh5eWV4WC+4sWLExYWxsqVK5k+fToTJ05k7ty5WQoGzC0Bhf/88w+DBw9m6NChaXZsFOgOIQbyIMERcej6q0ACgiL0614WZBxHR0e6devGwoULU7i23dzcOHbsWJZS3LLD4cOH6devH3379mX16tU6La2rDc9AWtSqVYs1a9YQGhrKr7/+yr///kuzZs344osv+OOPPz75M022SyaTsXDhQhYtWsS8efOYOHFilhZzQw8ovHjxIj179qRjx4789ddfn205ZUNFiIE8SKIye/3qDW0egXaYOXMmgYGBKTwBvXr1IikpiYMHD+aYHadOnaJnz5506dKF9evXI5fr9msqq9X+MoqlpSXfffcd9+/f16QOjhs3jpIlSzJy5Ehu376d5nX/9VhMmzaNVatW8fvvvzN8+HBUKlWmbenVqxdTpkwxuIBCX19fOnToQP369dmxYwfGxsb6NinPIcRAHsTUOGf+23NqHoF2qFWrFu3ateOnn35CrX4v5EqWLImzs3OOZRV4e3vTpUsXXF1d2bZtW44sCsmLrq5d5zKZDBcXF/bs2UNISAhTpkzh6NGj1KxZk0aNGrF169YUGR1peSxGjx7N5s2b2bhxI19//XWKGI+MsnDhQoMKKHzy5AmtW7embNmyHDp0iHz58unbpDyJ+LbOgzhYW6BrB5zs/+cR5C5mzZrF/fv3U+S39+7dGw8PD16/fq3Tua9du0b79u1p2LAhe/fuxdTUVKfzJVOsWDHi4+OJicm5dNgSJUowe/ZsgoOD2b9/PxYWFvTv359SpUoxdepUHj9+TPHixYmMjEShUKS4tn///uzZs4eDBw/StWvXTNc3+DCgsFu3bnoNKAwLC8PV1RULCwuOHz9OoUKF9GZLXkeIgTyIhZkx9jruMpgYGUrDurWYOHEix48f13t6miBjNGzYkBYtWrBgwQLNk3L37t0B2Ldvn87m/ffff2ndujXVq1fP8afDT1Uh1CXGxsZ07doVDw8PHj58yIABA3B3d6dChQqaMtGhoaGpruvatStHjx7l3LlztG3blujo6EzNa2VlxYEDB/D399dbQGFUVBRt2rQhPj5e9BswAIQYyKO4VLbVXZ0BGZQxiUUul+Pu7k67du0oWLAgBQoUoEiRIvz+++9Z2u8U5AyzZs3i9u3bHDt2DHhfmKd58+Y62yq4f/8+rq6ulC9fnmPHjlGgQAGdzJMeGa1CqGsqVarEb7/9xvPnz1m7di2xsbEANGrUiEWLFqXqn+Dq6sqpU6e4desWLVu2JCIiIlPzVa9eXW8BhQkJCXTu3JmgoCBOnjxJ2bJlc3R+QWpkkqHmmAh0SkBYDK7LvHU2fujaUSS9fgq83yv978fM0tISFxcXXF1dadmyJRUqVBDRwwaCJEk4OzujVCq5fPkyMpmM9evXM2zYMJ4/f655ktYGgYGBNGnSBCsrK86dO4e1tbXWxs4o0dHRFC5cmJ07d+Lm5pbj86dHWFgYxYoVo3nz5ly6dAmVSkXPnj0ZNWoUjRs31vy+3Lp1i1atWlGsWDFOnTqV6f+fqVOnsnTpUk6ePEnLli11cSspUCqV9OzZk5MnT+Lh4UHjxo11Pqfg0wjPQB6lol1BnCvYaN07YCSX4VzBhu2r/5cX/qEQsLOzw9vbm3HjxvHq1Su+++47KlWqRNmyZRk2bBi7du3i1atXWrVJkDlkMhmzZs3i6tWrnDlzBnjvljY2NmbPnj1am+fp06e0aNECCwsLPDw89CIEAAoWLEj+/Pn17hn4LzY2NhgZGdGzZ0+eP3/Ozz//zLVr13B2dqZGjRqsXr2amJgYatasyfnz53nz5g3Ozs4EBQVlap6cDChM7jdw5MgR9uzZI4SAASHEQB5mYVcnjLUsBozlMhZ2daJHjx5s2LAh1fHw8HB+/fVX6taty7lz54iMjOTIkSN07tyZy5cv07t3b2xtbTXd4Tw8PLTSAEaQOVq3bk2dOnVYsGABAEWKFKFNmzZa2yp4+fIlLVq0AODMmTMaV70+kMlkOk8vzApGRkbY2try8uVLrKysmDBhAg8fPuTUqVOUL1+eMWPGUKJECb799luUSiUXLlzQeHUePnyYqXlyKqBw+vTprFu3jo0bN9K+fXudzSPIPEIM5GFKW5kzr5OjVsf8sZMjpf8/OHHgwIGaVqwAcrmcBQsW8OTJE9q3b0/ZsmX5/fff+fLLL1m+fDl+fn6acq6Ojo5s2bKFVq1aUaRIEVq2bMnPP/+Mj4+PJu1NoDuSvQNeXl6cP38eeJ9VcPny5Uw/ef6X169f07JlS+Li4jh79iylS5fWgsXZQ5tVCLVJ8eLFU3gs5HI5rq6uHDhwgKCgIMaPH8/+/ftxcnJiwIABTJw4kUKFCuHs7Jxu/YK0yEpAYZxCiV9oFLdC3uAXGvXJiqO//vorixcv5vfff6dfv34Ztk2QM4iYAQF/eAaw9JR/tseZ3Koy37pUSPGeJEmMHj2av/76i44dO3L48GEkSeL69eu4u7uzY8cOEhISaN++PSNGjKBt27YYGRlprvXz8+P06dN4eHjg5eVFXFwcVlZWtGjRgpYtW+Lq6iqCj3SEWq3myy+/pESJEpw4cYKYmBhsbW2ZN28eU6ZMydKYb9++pUWLFjx9+hRvb2+qVKmiZauzRvfu3YmNjeXkyZP6NiUFHTp0wMjISNPFMC2Si0L9+eefnDt3DhsbG0xMTIiNjeXEiRM0atQow/Pt3r0bNzc3li5dysSJE1MdDwiLYdvVEDwfhhMSGZ+ikqkMsLcyx6WyLX3r21PRrqDm2KZNmxg0aBAzZsxI8YAgMByEGBAAsPN6CHMO+6FUS5lqYGQkl2Esl/FjJ0fc6tqneY5KpWLRokV069aNatWqpTgWHR3N9u3b+fvvv7l9+zalSpVi2LBhDBkyJNUTY2JiIleuXNGIg2vXrqFWqylXrpwmELF58+ZYWVll/gcgSJNdu3bRu3dvrl69Sr169ejZsyeBgYHcvHkz02PFxsbSqlUrHjx4gKenJzVq1NCBxVljzJgxnD9/nn///VffpqRg2LBh3Llzh2vXrmXo/Hv37vHXX3+xceNGYmJiMDIyYv78+UydOjXDlRzTCih8GhnPjAO+nH/0GiO57KPfEcnHnSvYsLCrE7cvnqFr164MGTKEv//+WwQKGyhCDAg0ZOcXvnQ26xZIkoSPjw/u7u5s376dd+/e0a5dO423IK1KdG/fvuXcuXMaceDv749MJqNOnToar0GjRo0wMzPLlm15GZVKRbVq1ahSpQqHDh1i37599OjRg4cPH1KpUqUMj/Pu3Tvat2/PjRs3OH36NPXq1dOh1ZlnwYIFrFixIlX6nr754Ycf2LRpEyEhmWsJHhsby8aNG5kxYwYxMTHY2dkxceJEBg8ejI2NzUevValUtGvXDh8fH27cuMGVV/IsPyjIkYg4uRqXMmbs3r1b4/UTGB5CDAhSoXEF+ocTEpGGK9DaHJdKtvRrYE8F24LpDZNlYmJi2LFjB+7u7vj4+FCyZEmGDh3K0KFDsbdP2/sAEBISwunTpzWvV69ekT9/fpydnTWeg+rVq+u81v3nRrKL9/bt21SqVAlbW1umTJnCDz/8kKHrExMT6dq1K56enpw8eRJnZ2cdW5x51q5dy4gRI1AoFJiYmOjbHA2rVq1i/PjxKBSKLD1RKxQK2rVrh6enJ3K5HGNjY3r16sXo0aOpX79+umNGRkZSp04dTGt2IqGSazbuQAJkjHMpx7hWVbMxjkDXCDEg+ChxCiVBEXEkKtWYGstxsLbAwiznmoj4+PiwZs0atm3bRlxcHG3btmXEiBG0b9/+o3Xr1Wo1vr6+eHh4cPr0aby9vXn37h1FixalRYsWuLq64urqahDBa4ZOUlISlSpVol69euzatYv+/fvj4+ODn5/fJxcopVJJ7969OXLkCEePHsXVNTsLi+74559/6NChA8+ePaNkyZL6NkfD/v376d69O69fv85y6qVKpWL48OFs3LiRLl26cPv2bZ48eULNmjUZNWoUX3/9NRYWqUuHLz1wiT+uvcnuLWhY3M0p3a1Egf4RYkCQK4iNjWXnzp38/fff3LhxgxIlSjBkyBCGDh2Kg4PDJ69PSEjg8uXLGnFw48YNJEmiUqVKGq+Bi4sLhQsX1v3N5ELc3d355ptvuHfvHo8ePaJjx47cuXMHJyendK9Rq9UMHDiQnTt3sm/fPjp16pSDFmcOHx8f6tSpw40bN6hdu7a+zdFw6dIlGjdujK+vL1988UWWx1Gr1UyYMIHly5fz888/U716dVavXs3Ro0cpVKgQAwcO5JtvvqFq1fdP708j42n5uxcKpQq01MnEzFjO6fFNs72lKNANQgwIch03b97UeAtiY2Np3bo1I0aMoEOHDhl28UZGRuLp6akRB4GBgcjlcurVq6cRBw0aNMixZjmGjkKhoHz58rRo0YI1a9ZgZ2fH6NGj040MTy4us3btWrZv325Qlf3SIjQ0lJIlS3L06FGDyn9/8uQJ5cqV49SpU9n2qkiSxJw5c5g/fz4zZ85k/vz5hISE4O7uzpo1a3j16hUuLi6MGjWKQ1GlufwkMlMxAp/CSC6jUTlrtgytr7UxBdpDiAFBriU2NpZdu3bh7u7OtWvXKFasGEOGDGHYsGGZTjd88uSJJhDxzJkzREZGYmFhQdOmTTXiwNHRMU9HQq9YsYIJEybg7+/PwoUL8fT05NGjR6l+JpIkMWHCBJYtW8aGDRsYNGiQfgzOBEqlElNTU9zd3Rk2bJi+zdHw7t07zM3N2bx5M/3799fKmEuXLmXy5MmMHTuWZcuWIZfLUSgU7N+/n9WrV3PlXhAlhq/WylxpcXp8E53EGgmyhxADgs+C27dvs2bNGrZu3UpMTAytWrVixIgRdOzYMdMBYWq1mlu3bmnEwYULF1AoFBQrVkyTpdCiRQuD2lvOCeLj4ylbtiydO3emV69euLq6cu3aNerWrZvivFmzZvHTTz+xatUqRo8erSdrM4+dnR1jx45l1qxZ+jYlBZaWlsyYMSPLtR3SInnbZ8CAAaxduzZF/M3E7Vc4eDcSlQ6WBiO5jP71yzBXy8XOBNlHhFULPgu+/PJLVq1aRWhoKOvWrSMqKoru3btTunRpZsyYwePHjzM8llwup3bt2kydOpXTp0/z5s0bPDw8GDBgAPfu3WPgwIGUKlUKR0dHvv/+e44ePUpMTIwO784wMDc3Z+LEiWzcuJHy5ctja2vLrl27UpyzaNEifvrpJ5YsWZKrhAC8715oaP0JAJ2USh4xYgTbtm1j27Zt9O7dG4VCoTl24/k7nQgBAJVawtPfsNI3Be8RngHBZ8udO3dYs2YNW7ZsISoqCldXV0aMGEGnTp2yFQvw+vVrzpw5o/EcBAcHY2xsTIMGDTSeg7p16xpUipq2iImJoUyZMvTr1w+1Ws2hQ4cIDg5GLpezfPlyxo0bx9y5c5kzZ46+Tc00rVu3pkCBAuzbt0/fpqTAxcWFYsWKsWPHDq2PfeTIEXr27EmzZs3Yv38/aiNTnOaeRJeLggy4O7d1jmYlCT6N8AwIPluqV6/OypUrCQ0NZePGjcTFxdGzZ09Kly7NtGnTePToUZbGtbGxwc3NjTVr1vDkyRMCAgJYsWIFtra2LFu2jMaNG2NtbU3nzp1ZuXIlDx48yFCt99xAwYIFGTduHGvWrKFly5Y8e/aMS5cusXbtWsaNG8fkyZOZPXu2vs3MEoban0DbnoFnz56RmJgIQMeOHTl27BgXLlygdevW+AWH6VQIwPvKA0ERcTqeRZBZhGdAkKe4e/cua9asYfPmzZo6+SNGjKBLly5ayRxQqVT4+PhoshQuXrxIUlISpUqVomXLlpqXnZ2dFu5GP7x9+5YyZcowYsQIduzYQbVq1Th9+jSjR49m5cqVuTbIctq0aezevTtTW0o5wYQJEzh27BgPHjzI9lixsbFYWlqSL18+OnToQJcuXWjbti3379+nbdu2lK7ZhOj6I7Rg9cc5MKoRNe2L6HweQcYRYkCQJ4mPj2fv3r24u7tz8eJFihYtyqBBgxg+fDgVK1bU2jxxcXGcP39es6Vw584dAJycnDRZCk2aNEmz6IshM3PmTJYvX85XX33FyZMnGTBgABs2bMjV1R2XL1/O9OnTiYuLMyhBs2TJEn766Sfevn2b7bHUajUWFhYkJCRgbGyMUqnEyMiIWrVqUblyZTxu3Cdfl3nZN/oT/DP2KxxLiJoehoQQA4I8j5+fn8Zb8ObNG1xcXBg5ciRdunTRel+DsLCwFPEGz549w8TEhEaNGmnEQZ06dQy+hvurV68oXbo0iYmJSJLEiRMnaN26td4rVmaH5KZMb9++NajiU1u2bGHAgAHExcVhbp71gj2RkZHcu3ePPn368OzZszTPOfTPCcZ6J+lUDImYAcNEiAGB4P959+4d+/btw93dnfPnz2NjY6PxFmSmKU9GkSQJf39/PDw88PDwwNPTk5iYGCwtLXFxcdGIgwoVKhjUkyrAuXPnNB3tSlWrQ4U2g0kqWilTbW0NDS8vL5o1a8aDBw+oXLmyvs3RcPr0aVxdXXn8+PEn62dIksSrV6+4d+9eqldYWFia18jlcuzs7Ni5cydNmjSh0SIPQqMTdXErAJSxNsdrkovOxhdkDSEGBII0uH//PmvWrGHTpk1ERkbSrFkzRowYQbdu3XTWBVGpVHLt2jVNo6XLly+jVCopU6aMJkuhefPmFC1aVCfzZ5TLly/j6upK9UbNeVm6GWrbyshl8LFiddrucqkL/P39qVy5Mp6enjRr1kzf5mi4e/cuTk5OXLx4kUaNGgHvF/3Q0NA0F/3IyEgATExMqFSpEtWqVUvxOnjwIHPnzkWlUgHQt29fVq9eTcGC74Xa3MN+bLkShEoHK4OoM2C4CDEgEHyEhIQE9u/fj7u7O15eXlhbWzNw4ECGDx9OlSpVdDp3TEwM3t7emmBEPz8/AGrWrKkRB1999RX58+fXqR0fcvPmTZo3b045137EVWmfpba2xnIZ8zo50tvAmtZER0dTuHBhduzYQe/evfVtDvB+j//ff/+lVq1aDBgwACMjI+7fv8+9e/eIjo4GIF++fFSpUiXVol+uXLk001sPHz5M586dMTc3x93dnb59+6Y4HhAWg+syb53dk6hAaJgIMSAQZJAHDx6wdu1aNm7cSEREBE2aNGHEiBF0796dfPny6Xz+0NBQzpw5oxEHL168wMzMjK+++kojDmrWrKmzID4/Pz+aNm2KXfOBxJVvnu3xJrWqxBgX7QVrZhdJkihQoAA//fQT48aNy9G5VSoVjx8/1iz0ya/79+8THx8PgKmpKTVq1KBatWpUrVpVs+g7ODhkKsYkLi6OefPmMXLkSMqXL5/mOf3XXeXS4wjRmyAPIcSAQJBJFAoFBw4cwN3dHU9PT6ysrDTeguSub7pGkiTu3bunCUQ8d+4ccXFxWFlZ0aJFC404yGyPhvQICAjA2dmZIrXb8656N62MCYbX1rZ8+fL06NGDxYsX62T8pKQkHj16lMq1//DhQ00VwMKFC6d6yh8yZAiDBw9OtzGUtvlf10K11sYUXQsNGyEGBIJs4O/vz9q1a9mwYQOvX7/G2dlZ4y3ISfd9YmIiV69e1YiDa9euoVKpKFeunCYQsXnz5lhZWWV67ODgYJydnclftDS0nYlCi5vJhrZAfPXVV5QvX55NmzZla5yEhAT8/f1TPeX7+/ujVCoBsLa2xtHRMcWiX7VqVYoXL54qYLRevXpUr16dtWvXZsuuzLDzegjT9vtqbTxDE36ClAgxIBBoAYVCwaFDh/j77785e/YsRYoUYcCAAQwfPhxHx5wPloqKiuLcuXMacfDw4UNkMhm1a9fWiIPGjRt/MhgyNDQUZ2dnAGpN3MDN57Gfteu4R48eREdHc+rUqQydHxcXx4MHD1K59wMDA1Gr3z9VFytWLNWTfrVq1TIVCNq5c2eUSiX//PNPlu4rq/zhGcDSU/7ZHmdyq8p861JBCxYJdIUQAwKBlgkICNB4C169ekXjxo0ZMWIEPXv2zFFvwYc8ffpUIwxOnz7Nq1evyJ8/P87OzhpxUL169RTxBq9evaJp06bExMSw5bAHg3YH6sw+QwkqGzNmDN7e3priUMlER0enWvDv3btHUFCQ5pzSpUunWvCrVq1KkSLZr7Q3cuRIbty4gY+PT7bHyiy/H77GMu9nGJmYoibjKa6SWoWZiTHzO38hPAK5ACEGBAIdkZiYyKFDh3B3d+f06dNYWlrSv39/RowYwRdffKE3u9RqNb6+vhpx4O3tzbt37yhatCgtWrTQNFrq378/L1++xNvbm+0PkthyNVirXoFkDCndbObMmfz5558sXrw4xaL//PlzAGQyGWXLlk2x2FerVo0qVapQqFAhndk1d+5c3N3dCQ0N1dkcaSFJEq1atSIw7C0Nxq7g0uNITZpoemiOv7xPoYfHuHL6aLaKJQlyBiEGBIIcIDAwkLVr17J+/XrCw8Np2LAhI0aMoFevXjnyRfmxyoAKhYLLly9rvAY3btxArVYjl8vp2bMnvXv3ZunDgjx7m6Az+3KyEI0kSYSHh2v28dMqzCOXy6lQoUKqJ/3KlSvrZWH766+/GDNmDAqFIkerU+7du5eePXty9OhR2rdvT0BYDNuuhuDpH05wRBx84CmQAfbW5rhUsqVfA3viXz6hYcOGdO7cmW3bthlc4SxBSoQYEAhykMTERI4cOYK7uzunTp2icOHC9OvXjxEjRlC9enWtzqX54n4YnuHKgPHx8bRs2ZLbt2/Trl07bt++zeOnoZQevzvXlajNSmEehULBzz//TGBgIOXKldOaLdnl0KFDdOnShZcvX+ZYk6vY2FiqVq1KrVq1OHToUKrjcQoly9dvZ/5Pi2jt2oKNK5dgWSDlNtju3btxc3Pj119/ZcKECTlityBrCDEgEOiJx48fs27dOtavX8/Lly+pX78+I0eOpFevXtlqXPQ0Mp4ZB3w5/+h1hl26zhVsmNO+Mt8OdOPChQucOnWKxo0bA+Bx/T7D9+u+k19Wm9eo1WpCQkJSLfj3799PVZjnw/z8atWqUb58+RSFeW7evEnt2rW5fv06derU0dq9ZZdr165Rv359bt++TY0aNXJkzmnTprF8+XLu3bv30RTVPXv20LdvX9q1a8fOnTtT1dyYOnUqS5cu5dSpU7Ro0ULXZguyiBADAoGeSUpK4ujRo7i7u3Py5EkKFiyo8RZk9ot/5/UQ5hz2y1JlQEml5M3pv9m7eEKKL+1bIW/ouvpSpuzICp9qa5uRwjwWFhapFvzMFOYJDQ2lZMmSHDlyhA4dOmjt3rJLSEgIZcqU4fjx47Rp00bn8z148IDq1asza9YsZs+e/cnzjx8/Trdu3WjcuDEHDx6kQIECmmMqlYp27drh4+PDjRs3cHBw0KHlgqwixIBAYEAEBQWxbt061q1bx4sXL6hXrx4jRozAzc0txRdsWmQ/DUwCZKkqA/qFRtF+5YVsjJsxkj0DWSnMkywASpcuna0KjEqlElNTU/7++2+GDx+urVvLNgqFgnz58rFhwwYGDRqk07mSgwYfP36Mn59fhqtrenl50bFjR7744guOHTuGpaWl5lhkZCR16tShcOHCXLx4UQQUGiBCDAgEBkhyTrm7uzvHjx+nQIEC9O3blxEjRlCzZs1U5+uyQEycQskXc0+i2y8KiVqB23jodydVYZ60cvTTKsyjLexK2tN35Dj6DxpsUG2Yra2tmTRpEtOnT9fpPHv27KFXr16aoMHMcOPGDVq3bk3p0qU5deoUtra2mmN37twRAYUGjBADAoGBExwcrPEWhIaGUqdOHUaMGEHv3r0pWLBgjpSObbrEk+DIeK2N/1/U0WFUfLAtW4V5ssOHwZbBkWlEyRtAG+YvvviC5s2bs2LFCp3N8amgwYxw9+5dXF1dKVy4MB4eHpQuXVpzTAQUGi5CDAgEuQSlUsmxY8c03gJzc3NGjBhBWLWeXH4cqdPKgHMP++mszoCkVlHq3WNG1y9Ky5YtcyxaHrIebKmPNswtW7bEysqK3bt362yOjAYNforAwEBatmyJWq3mzJkzVKjwv+qDIqDQMBFiQCDIhYSEhLB+/XquPXzKPQftNQ76L8mVAXXd1raA1+/4XT4DgJOTk6YqYpMmTbKVWfExshNsqY82zP379ycoKIjz58/rZPwHDx7g5OTEDz/8kKGgwU/x7NkzXF1defv2LadOncLJyQkQAYWGihADAkEuRpdP7EYycCltTC0pkHv37nFGVZX4QqWRybVX9OZDD0RYWBhnzpzRVEZ89uwZJiYmNGrUSNOFsXbt2hgbp79///LlS3x8fD65162tmvs52YZ58uTJHDx4kICAAK2PndWgwU8RHh5O69atCQ4O5sSJE9SrVw8QAYWGiG4anwsEghzB82G4ToQAgEqC47dDGDduHJ6enlR8ewNjuQy0GEpoLJexsOv7J0Y7Ozu+/vpr1q9fT0hICA8ePOC3337D0tKSJUuW0KBBA2xsbOjWrRt//vknAQEB/PdZZs6cOXTo0IHx48drGgX9l53XQ7QiBACWnvJn1/UQrYz1KYoXL86LFy90MvbevXs5ffo0K1as0JoQALC1tcXT05OqVavSokULzp07B4CVlRUHDx7E39+fYcOGpfp/FOQ8wjMgEORSYhVKnHQe5Q+3ZzbXVJbTdtbCyC8LMN2t6SfPUyqVXL9+XVMy+fLlyyiVSuzt7TVbCi1atKBOnTqEhLxfnHv06MGWLVtSLG45EWypK7Zv307fvn2JiYn5ZJppZoiNjaVKlSrUrl07y0GDnyIuLo6uXbty/vx59u7dq/HciIBCw0F4BgSCXEpwRJzOhQDA8+hEzd9717VnUqtKWhm3UNA5Fgxpx/Hjxz95rrGxMQ0bNmT27Nl4e3sTGRnJ0aNH6dq1K1euXKFPnz7Y2tpqhADA/v37admyJW/evNG8N+OAL0ote1KUaokZB7QnkNKjePHiAFr3DixYsICIiAiWLVum1XE/xMLCgiNHjtCmTRu6dOnCrl27AOjVqxdTpkxh8uTJnDlzRmfzCz6NEAMCQS4lUYtPt5mZZ4xLRX7u5oSZsRwjeeZyxY3kMsyM5Szu5sTV9T/SsmVLOnbsyObNmzM1TsGCBWnfvj3Lli3j7t27PH/+nMGDB6c4R61Wc/HiRSpVqoSfnx8BYTGcf/Ra69sqKrXE+UeveRQeo9Vx/0uxYsWA93ER2uL+/fv8+uuvzJgxI1vZAxnBzMyMPXv20KdPH/r06cO6desAWLhwIS1btsTNzS1FS2hBziLEgECQSzE1zplf37Tm6V3XntPjm9KonDXAJ0VB8vFG5aw5Pb4pbnXtyZ8/P/v27WPQoEEMHDiQpUuXZtnGEiVKEBsbm6KQTXIlwtevX7Ns2TK2XQ3JtHjJKEZyGVuv6DZ2QNueAUmSGDt2LGXKlGHy5MlaGfNTGBsbs3HjRkaNGsWwYcP4/fffMTIyYseOHRQqVIiuXbtqSksLchb9l9USCARZwsHaAu2G86VG9v/zpEVpK3O2DK2foq1tSEQa3RE/aGtbwTZlwR5jY2PWrFlDsWLFmDx5Mi9fvuSXX37JUknh27dvI0kSFhYW1K5dmwYNGlCnTh1q165N2bJlabb0nO6CLdUSnv7hzMVRJ+PD+xLM+fLl05pnYO/evZw5c4ajR49qNWjwU8jlcv744w8KFSrEhAkTiI6OZvbs2Rw8eJCGDRsybNgwUaFQDwgxIBDkUizMjLG3MtdpZUB7a/NPluKtaFeQuZ0cmYsjcQolQRFxJCrVGS7lK5PJWLBgAXZ2dnz//feEhYWxfv36FN0EM8Lx48dRKpVUrFgxlZiIVSgJ0eHPCSAkIp44hVJnpYtlMhnFihXTimcgNjaW8ePH06lTp0yXHNYGMpmMRYsWUbhwYaZPn050dDRLly5l9erVDBw4kMTERPbu3ZvjduVlhBgQCHIxLpVtdVdnQC7DpZLtp0/8AAsz4yy1IQYYO3Ystra29O/fn9evX7Nnz55MRc2XL18+3WM5EWwpAUERcVm+/4xQvHhxrXgG5s+fT0REBMuXL9eCVVln2rRpFCr0f+3deVRT19oG8CckAhVoKyhg+4leRbQi2qoFCUJACzh8oliVi3WsQ3GmVtS6HOqwbJ3LvXqLWi4ITrcOKFBFHBCEaKW0Uqc6VkG9oAxaBUVC8v3hBxUVCHASEvL8/rI55+yzg2vZh332ed83MXXqVBQUFODGjeetsvfu3YsjR47A29u7QednSLhngEiPfeJip9Gl75E9tVdhDwACAgJw8OBBpKamok+fPsjLyxNk3IbabCk0IVYGLl26hHXr1mH+/Pk6Uf1vypQpCA8PR2RkJFJS/qpyOXToUG4o1CKGASI91t7GAu72zQXfGCc2EsHdvvkrz/i14aOPPkJycjJu3ryJXr164datW/UesyE3WwqpvoWHGmLTYE3KysqQmJhYaY+AWCyGUqmscUNhUYkCF+4+xK9Zhbhw9yGKShTamHKjxMcERHpuhb8TPlqfLOgKwYuVARtCt27dkJaWBl9fX0ilUiQkJFTUtq+Lht5sKRRbW9t6PSbYvXs3jh07hoMHD2p102B1QkNDK+oOlCsrK0NpaWlFhcIXNxS+2GEyq+A1G1Z1oMOkPuLKAJGea2XZFEv8hN3FvtTPUetd+V5mb2+PtLQ0WFtbw93dvV4Neso3W2qSOpst66tly5a4f/8+FIra/wb8+PFjzJo1C4MGDUK/fv00MLu68fb2xtChQyv6E4jFz3tflJSUYOTIkdi5cyfWr1+P7IJijAr/Cd7fpiD6p1u49VIQAJ6HvVsFxYj+6Ra8v03BqPCfkK3hjaONBcMAUSMgZGXAEJ8OCNBiN77q2NraIjk5Gd26dYOPj0+9yuV6dbDWaJ2B2m62rAtbW1uoVCrcu3ev1teWbxrUZKXBunBycsLu3btRWFiII0eOYMqUKbC2fv6zTE1NxZw5c/D1f5Lx0fpkyG/kA0CNq2Dlx+U38vHR+mTs0lL/CH3G3gREjUh92/Iu9XPUmSDwovLfEvft24dNmzZhwoQJtR5D022Yy9s9a1JGRgZ69OiBn3/+Gd27d1f7ukuXLqFLly5YvHgxFixYoMEZCkOlUiEtLQ1WVlY4+l8J1h7Rrw6T+ogrA0SNiBCVAXWRiYkJdu3ahaCgIEycOBHLly+vdae7xrDZsi4liVUqFaZNm4bWrVtj9uzZmpqaoEQiEXr16oXMx2aCBAFAux0m9RE3EBI1MkJUBtRFYrEYGzZsgK2tLRYuXIicnByEhoZWPGNWh75vtrSxsYFIJKrxjYLt27ejoKAAQUFBiImJwfHjx3Vq06A6sguKsTj2gqBjLoq9AGm75g2+H0YX8TEBkQGoS2VAXbZ582ZMnjwZQ4cORVRUFExMTNS+Vug2zCuHOGl1RcXGxgbTp0+vdrnf0dERFy9ehL29PQoLC+Hu7o6YmBitzVEIo8J/gvxGvqDBTWwkgrStFaLHuwg2ZmPBxwREBqC8MuAHds3g+M5beh0EAGDSpEnYs2cPDhw4gP79++PPP/9U+1p932ypTuGh8mJN169fR35+PhQKBe7evauN6QlC3ztM6iOGASLSS/7+/khMTERGRgY8PT2Rm5ur9rX1bcMsUiowvE0ppnrZ13ba9VZTSWKVSoXCwsKKPwPP+za0b98e58+f18oc60vfO0zqI4YBItJbHh4eSElJQU5ODtzc3HD9+nW1r63rZsuef7PE7U2fYXWQPwYPHoxr167V/QvUQU0rA8XFxSgtLa30mVKpRLt27Spe2dN1SZfvabzDJFXGMEBEeq1Lly6Qy+UQi8WQSqX49ddf1b62fLPlkWAPjHJpjdZWTfFyJBABaG3VFKNcWuPo5x7YPqEnLIyeAQDi4uLw3nvvYebMmSgoKBDuS1WjppWBF/s5GBkZwcTEBKtWrcIvv/yiF2FAmx0m6S/6/eCQiAhAmzZtkJqaigEDBkAmk2H//v3o3bu32tfXtg2zo6MjUlNToVQqoVQqsXHjRkRERCAyMhJDhgwR+utVYmndEnllpvg1q/C188vOzq74s6enJ7Zs2YK2bdtqdE5CaiwdJvUNwwARNQotWrTA8ePH8fHHH6Nfv36Ijo7G8OHDaz2OOm2YHRwccPr06YqywEqlEo8ePcLvv/9ep7nXpHI9/nawHLEa/t/JAbxaj9/CwgLm5uZYunQpgoODKzUA0geNpcOkvmEYIKJGw9zcHHFxcRg3bhz+/ve/4/79+5g6darg92nXrl2l/zY1NcWOHTswePBgQe+TXVCM+THncPJaHsRGotc+R3+xHn/kqZtwt2+Oi7dy9fZd+sbSYVLf8KdBRI2KsbExoqOjERwcjGnTpmHhwoW1rlZYk7Zt21asCjg4OODZs2do3bq1oPfYlZ5lkPX4yztMapI2OkzqG4YBImp0jIyMsHbtWqxcuRLLly/HpEmT6tTprypSqRRdunRBdHQ0fvvtN3Tu3BmjR49GSUmJIONvSLqKefvOoUShrPWu+jKlCiUKJebtO4cNSVcFmY82NZYOk/qGYYCIGiWRSIQ5c+YgIiICERERGDZsGJ48eSLI2HZ2dsjMzMTIkSNhYmKCqKgoXL58GYsXL6732LvSs7Am0bDr8TeGDpP6hmGAiBq1sWPH4sCBAzh8+DB8fX3x4MEDwe/RpUsXLFmyBKtXr4ZcLq/zOJqqx5+t4Vf1hPaJi51G6wyM7KmbDbkaEsMAETV6AwYMwLFjx3D+/Hm4u7trpDRvSEgInJ2dMWbMGBQVFdVpjPkx56AQ+H+CCqUK82OE68WgDY2hw6S+YRggIoPg6uqK1NRUPHjwAFKpFJcvXxZ0fIlEgq1bt+LOnTuYO3dura9nPf7KVvg7QSJwGNBmh0l9wzBARAajU6dOkMvlMDMzg5ubG86cOSPo+A4ODli5ciU2btyIo0eP1upa1uOvrJVlUyzxcxR0zKV+jnr7yqWmMQwQkUFp1aoVTp48iQ4dOsDLywsJCQmCjj916lT07t0b48aNw8OHD9W+jvX4X9UOufhfO2F+Jg3RYVKfMAwQkcGxtLTEkSNH0Lt3bwwcOBDbtm0TbGwjIyNERETg4cOHmDlzplrXsB7/X1QqFRITE+Ht7Q1nZ2dEz/ukXh0mTSRGWDnEqUE6TOoThgEiMkhNmzZFTEwMRo0ahVGjRmHdunWCjW1nZ4fQ0FBs3boVBw4cqPF8bdbj11XFxcXYtGkTOnbsCF9fXxw7dgwA4OvrW+cOk9K2Vjj6uYwrAmpg1QUiMlgSiQTh4eGwsbHBF198gZycHHzzzTcwMqr/70ljx45FTEwMJk2aBKlUihYtWlR5rqHX479//z46duyIwsLCis/Kq0YOHDgQwF8dJiv6NFy5h6z84kohSoTnBYW8HKwxsqcd3xqoBZFK6DqdRER66Ntvv8Xnn3+O0aNH4/vvv0eTJk3qPWZOTg46d+4MT09P7N69u8qmQRfuPsSAf6bW+341+XF6L53s1KdQKNC3b18cP378ldLRf/zxB9q0afPa69TpMEnq4WMCIiIAwcHB2LFjB3bu3InBgwfXuVbAi2xtbfHdd99h79692LlzZ5XnGXo9folEgoSEBPj5+VX63MbGptqeD+UdJj+wawbHd95iEKgHhgEiov8XGBiI+Ph4JCcno0+fPsjPz6/3mMOGDUNgYCCmTp2KO3fuvPYc1uMHbty4gZSUFHTs2LHiMY2Xl5fetWDWVwwDREQv8PHxwYkTJ3D9+nX06tULWVn1fz9/w4YNeOONNzBhwoQqOygacj3+wsJCDBw4EDY2Njh16hQSEhJgaWkpeEtoqhrDABHRS3r06IG0tDQ8ffoUUqkU58+fr9d4lpaW+P7775GQkIAtW7a89hxDrcdfWlqKYcOGIS8vD3FxcXj77bfh7e2NvLw8BAQENPT0DAbDABHRazg4OEAul8PKygru7u5ITa3fBr/+/ftj4sSJmDVrFm7cuPHKcUOsx69SqTBjxgwkJydj3759sLf/qxYAHw9oF8MAEVEVWrZsiZSUFHTt2hXe3t6Ii4ur13hr165FixYtMHbsWJSVlb1y3NDq8W/YsAFhYWEICwuDTCZr6OkYNIYBIqJqvPXWW0hISED//v3h7++Pf//733Uey8LCApGRkUhNTUVoaOgrxw2pHn9CQgKCg4PxxRdfYPz48Q09HYPHOgNERGooKyvD1KlTsWnTJqxYsQLz5s2r81L2rFmz8K9//Qu//PILOnXq9MrxDUlXsSbxSn2njBCfDjpZhvfixYtwdXWFh4cH9u/fD7FY3NBTMngMA0REalKpVFiyZAmWLFmCGTNmYP369XWqVvjkyRN069YNZmZmOHXq1GsLHO1Kz8Li2AtQKFW12lgoNhJBYiTCUj9HnSzDm5eXB2dnZ5ibmyMtLQ0WFrq3l8EQMQwQEdVSWFgYpkyZgoCAAERGRsLExKTWY6Snp8PV1RWLFi3CokWLXntOdkEx5secw8lreRAbiaoNBeXH3e2bY4W/k04+GigpKYG3tzcuX76MM2fOVFtQiLSLYYCIqA727t2LESNGwMPDA/v27avTb7iLFi3C119/jdOnT6N79+5VnldTPf4mJQ/Qq50V5g9z08m3BoDnqyqffvopduzYgaSkJEil0oaeEr2AYYCIqI5OnDiBQYMGoX379jh48CCsrWtX2OfZs2fo2bMnSkpKkJGRAVNT0xqvebkev6goD44O9jAzM8OVK1fwzjvv1PXraNTq1asxZ84cREdHY+TIkQ09HXoJ3yYgIqojT09PJCcn486dO3Bzc3tt/YDqGBsbIyoqCteuXavyUcHLXq7Hfzb9JwBAUVER+vfvL0hPBaHFxsZi7ty5mD9/PoOAjmIYICKqh/fffx9paWkAADc3N5w9e7ZW13fu3BnLli3DmjVr6lTYSC6XV2xiPHfuHEaMGAGlUndaFZ89exYjRozAkCFDsGzZsoaeDlWBjwmIiARw79499O/fH1evXsWBAwfg6emp9rVlZWXw8PBATk4OMjMzYW5urva1Tk5Or5RLDgkJwapVq9QeQ1NycnLg7OyMFi1aICUlBWZmutk1kbgyQEQkCGtrayQlJcHZ2Rm+vr7Ys2eP2teKxWJs3boVOTk5mDNnjtrXPX78GBcvXnzl89WrVyM5OVntcTThyZMnGDx4MBQKBWJjYxkEdBzDABGRQCwsLPDjjz9iyJAhGD58OMLCwtS+1t7eHqtXr8Z3332HxMREta45c+YMlEplpVoHH3zwAWbPno2uXbvWev5CUalUGD9+PH777TfExsbi3XffbbC5kHp0t7k1EZEeMjY2xvbt22FtbY3JkycjJycHixcvVqtaYVBQEGJiYvDpp5/i/PnzePvtt6s9v2XLlvDx8UG3bt2Qn5+PqKgonDp1qk51D4S0fPly7Ny5Ez/88AN69OjRoHMh9XDPABGRBqhUKqxcuRJffvklPvvsM2zcuFGtsrvZ2dlwcnKCn58foqKi1L5fRkYGevTogZSUFLi7u9dn6vXyww8/ICAgAEuXLsXChQsbbB5UO3xMQESkASKRCPPmzUN4eDi2bNmC4cOH4+nTpzVe16pVK/zjH/9AdHQ0YmJi1L7f+++/jzfffBMpKSn1mXa9pKenY8yYMQgMDMSCBQsabB5Ue1wZICLSsNjYWAQEBMDFxQX79++vcflfpVLB398fcrkc58+fV7uY0YABA1BaWqr2ngMh3b59G87OzrCzs0NSUhLeeOMNrc+B6o4rA0REGubn54ejR48iMzMTMpkM//3vf6s9XyQSYfPmzVCpVAgKCoK6v7PJZDLI5XKUlpYKMW21FRUVwc/PDxKJBPv372cQ0EMMA0REWuDm5obU1FTk5+dDKpXiypXqWxRbW1tj06ZNiImJwbZt29S6h0wmQ1FRETIyMoSYslqUSiVGjx6NK1euIC4uDra2tlq7NwmHYYCISEscHR0hl8thamoKNzc3pKenV3v+kCFD8Mknn2D69Om4fft2jeOXt0XWZo2BhQsXIiYmBjt27GjQ1xmpfhgGiIi0yM7ODqmpqWjXrh28vLxw5MiRas//5z//CXNzc4wfP77GxwVNmjSBVCrVWhjYtm0bVqxYgZUrV8LPz08r9yTNYBggItIyKysrHDt2DDKZDAMGDMDOnTurPLdZs2YIDw9HYmKiWkWMZDIZUlNToVAohJzyK+RyOcaPH49x48Zh9uzZGr0XaR7DABFRAzAzM8P+/fsRGBiIESNGIDQ0tMpzfX198dlnn2H27Nm4fv16tePKZDI8evQImZmZQk+5ws2bNzF48GC4uLggLCxMrYJKpNsYBoiIGkiTJk0QGRmJkJAQBAcH48svv6zyUcCaNWtga2uLMWPGoKysrMoxP/zwQ5iammrsUcGjR48wcOBAmJubY9++fTA2NtbIfUi7GAaIiBqQSCTCqlWrsHbtWnzzzTcYP378a5f4zc3NERkZCblcjnXr1lU5nomJCVxdXTUSBsrKyhAYGIisrCzEx8ejefPmgt+DGgbDABGRDpg1axaio6MRHR0Nf39/FBcXv3KOu7s7Zs2ahQULFuDChQtVjiWTyXDy5EkolUpB5zh37lwcOnQI//nPf9CpUydBx6aGxQqEREQ6JCEhAR9//DG6du2K+Ph4WFpaVjr+9OlTdO/eHaampjh9+jSaNGnyyhhJSUno3bs3zp49K9jrfuHh4ZgwYQJCQ0MxY8YMQcYk3cGVASIiHdK3b18cP34cV65cQa9evZCdnV3puKmpKaKiopCZmYnly5e/doyePXvC2NhYsD4FJ06cQFBQEIKCgjB9+nRBxiTdwpUBIiIddPnyZfj4+ECpVCIxMRHvvfdepeNfffUVli9fjtOnT7+2TbC7uztsbGywZ8+ees3j2rVrcHFxwQcffIBDhw69diWC9B/DABGRjrpz5w769u2Lu3fvIj4+Hq6urhXHSktL4erqiuLiYmRkZLzSD2DBggXYvHkzcnNz6/zq34MHD+Dq6gqlUonTp0+jWbNm9fo+pLv4mICISEe9++67SElJgaOjI/r06YMff/wRwPOuhmFhYZg4cSJu3Ljx2nbBMpkM9+/fx6VLl+p0b4VCgeHDhyM3Nxfx8fEMAo2cpKEnQEREVWvWrBkOHz6MwMBADBo0COHh4cjNzcXcuXPRpk0bLFu2DHPnzsWgQYPg4eFRcZ1UKoVEIkFycnKddv4HBwcjKSkJhw8fRvv27YX8SqSD+JiAiEgPKBQKTJkyBVu2bKn0+bFjx/DVV1/h9u3byMzMhIWFRcUxV1dXtG7dGrt27arVvTZu3Ihp06Zh06ZNmDRpkiDzJ93GxwRERHpAIpHAz8+v0vN/iUSCiIgIRERE4N69ewgJCal0jUwmQ0pKCh4/LcWFuw/xa1YhLtx9iKKSqvsWJCYmYubMmQgODmYQMCBcGSAi0gOZmZlwcXFBSUlJpc+NjY2Rm5uLXbt2YfLkyTh06BD69u2Lq7mPsD7+Zxz+7TaUTS3x4j/0IgB2lk3h1cEan7jYob3N89WE33//HT179oRUKkVcXBzEYrH2viA1KIYBIiI9cPz4cfj7++PPP/+EWCyu1J9g/fr1mDlzJvr164dzf9yFZ8hmpF3Ph9hIhDJl1f/Elx93t2+OEM//wRBfGUxMTHDq1Cm8+eab2vhapCMYBoiI9ERZWRnS09Nx+PBhxMfHIyMjAyqVCs2bN8f9+/cRduQ3rDp2EyKxpNoQ8DKxkQiqMgWepG6FPHoN/va3v2nwW5AuYhggItJTBQUFiIiIgFKpxBs9BmNN4pV6jznbxwHTvPj2gKFhGCAi0nO70rMwb985wcZbOcQJAR/aCTYe6T6+TUBEpMeyC4qxOLbqDoZ1sSj2ArILXu2aSI0XwwARkR6bH3MOilrsD1CHQqnC/BjhVhpI9zEMEBHpqau5j3DyWl6tNguqo0ypwslrebh275Gg45LuYhggItJT23/Kgtiobk2IaiI2EmHb6SyNjE26h2GAiEhPJV2+J/iqQLkypQpJV+5pZGzSPQwDRER66HGJAlka3uSXlV9cbeliajwYBoiI9NCt/CJo+r1wFYCb+UUavgvpAoYBIiI99EyhbFT3oYbFMEBEpIeMJdr551tb96GGxb9lIiI91MbKDJp5j+Avov+/DzV+DANERHrIzEQCO8umGr2HnVVTmJlINHoP0g0MA0REesqrg7VG6wx4OVhrZGzSPQwDRER66hMXO43WGRjZk82KDAXDABGRnmpvYwF3++aCrw6IjURwt28Oe2sLQccl3cUwQESkx1b4O0EicBiQGImwwt9J0DFJtzEMEBHpsVaWTbHEz1HQMZf6OaKVhjcnkm5hGCAi0nN//9AOs30cBBkrxKcDAj7kXgFDI1KpVJquaElERFqwKz0Li2MvQKFU1WpjodhIBImRCEv9HBkEDBTDABFRI5JdUIz5Medw8loexEaiakNB+XF3++ZY4e/ERwMGjGGAiKgRupr7CNt/ykLSlXvIyi+u1NRIhOcFhbwcrDGypx3fGiCGASKixq6oRIGb+UV4plDCWGKENlZmrCxIlTAMEBERGTi+TUBERGTgGAaIiIgMHMMAERGRgWMYICIiMnAMA0RERAaOYYCIiMjAMQwQEREZOIYBIiIiA8cwQEREZOAYBoiIiAwcwwAREZGBYxggIiIycAwDREREBo5hgIiIyMAxDBARERk4hgEiIiIDxzBARERk4BgGiIiIDBzDABERkYFjGCAiIjJwDANEREQGjmGAiIjIwDEMEBERGTiGASIiIgPHMEBERGTgGAaIiIgMHMMAERGRgfs/evMR8fmo8tAAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "price_ctrl = ctrl.ControlSystem(\n",
    "    [\n",
    "        rule1,\n",
    "        rule2,\n",
    "        rule3,\n",
    "        rule4,\n",
    "        rule5,\n",
    "        rule6,\n",
    "        rule7,\n",
    "        rule8,\n",
    "        rule9,\n",
    "    ]\n",
    ")\n",
    "\n",
    "prices = ctrl.ControlSystemSimulation(price_ctrl)\n",
    "price_ctrl.view()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Пример расчёта выходной переменной price на основе входных переменных"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 634,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=============\n",
      " Antecedents \n",
      "=============\n",
      "Antecedent: bathrooms               = 1\n",
      "  - low                             : 0.7777777777777778\n",
      "  - medium                          : 0.0\n",
      "  - high                            : 0.0\n",
      "Antecedent: sqft_living             = 3420\n",
      "  - low                             : 0.199712\n",
      "  - medium                          : 0.008695652173913044\n",
      "  - high                            : 0.0\n",
      "\n",
      "=======\n",
      " Rules \n",
      "=======\n",
      "RULE #0:\n",
      "  IF bathrooms[low] AND sqft_living[low] THEN price[lower]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - bathrooms[low]                                         : 0.7777777777777778\n",
      "  - sqft_living[low]                                       : 0.199712\n",
      "                       bathrooms[low] AND sqft_living[low] = 0.199712\n",
      "  Activation (THEN-clause):\n",
      "                                              price[lower] : 0.199712\n",
      "\n",
      "RULE #1:\n",
      "  IF bathrooms[low] AND sqft_living[medium] THEN price[low]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - bathrooms[low]                                         : 0.7777777777777778\n",
      "  - sqft_living[medium]                                    : 0.008695652173913044\n",
      "                    bathrooms[low] AND sqft_living[medium] = 0.008695652173913044\n",
      "  Activation (THEN-clause):\n",
      "                                                price[low] : 0.008695652173913044\n",
      "\n",
      "RULE #2:\n",
      "  IF bathrooms[low] AND sqft_living[high] THEN price[average]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - bathrooms[low]                                         : 0.7777777777777778\n",
      "  - sqft_living[high]                                      : 0.0\n",
      "                      bathrooms[low] AND sqft_living[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                            price[average] : 0.0\n",
      "\n",
      "RULE #3:\n",
      "  IF bathrooms[medium] AND sqft_living[low] THEN price[lower]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - bathrooms[medium]                                      : 0.0\n",
      "  - sqft_living[low]                                       : 0.199712\n",
      "                    bathrooms[medium] AND sqft_living[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                              price[lower] : 0.0\n",
      "\n",
      "RULE #4:\n",
      "  IF bathrooms[medium] AND sqft_living[medium] THEN price[average]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - bathrooms[medium]                                      : 0.0\n",
      "  - sqft_living[medium]                                    : 0.008695652173913044\n",
      "                 bathrooms[medium] AND sqft_living[medium] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                            price[average] : 0.0\n",
      "\n",
      "RULE #5:\n",
      "  IF bathrooms[medium] AND sqft_living[high] THEN price[high]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - bathrooms[medium]                                      : 0.0\n",
      "  - sqft_living[high]                                      : 0.0\n",
      "                   bathrooms[medium] AND sqft_living[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                               price[high] : 0.0\n",
      "\n",
      "RULE #6:\n",
      "  IF bathrooms[high] AND sqft_living[low] THEN price[average]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - bathrooms[high]                                        : 0.0\n",
      "  - sqft_living[low]                                       : 0.199712\n",
      "                      bathrooms[high] AND sqft_living[low] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                            price[average] : 0.0\n",
      "\n",
      "RULE #7:\n",
      "  IF bathrooms[high] AND sqft_living[medium] THEN price[high]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - bathrooms[high]                                        : 0.0\n",
      "  - sqft_living[medium]                                    : 0.008695652173913044\n",
      "                   bathrooms[high] AND sqft_living[medium] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                               price[high] : 0.0\n",
      "\n",
      "RULE #8:\n",
      "  IF bathrooms[high] AND sqft_living[high] THEN price[higher]\n",
      "\tAND aggregation function : fmin\n",
      "\tOR aggregation function  : fmax\n",
      "\n",
      "  Aggregation (IF-clause):\n",
      "  - bathrooms[high]                                        : 0.0\n",
      "  - sqft_living[high]                                      : 0.0\n",
      "                     bathrooms[high] AND sqft_living[high] = 0.0\n",
      "  Activation (THEN-clause):\n",
      "                                             price[higher] : 0.0\n",
      "\n",
      "\n",
      "==============================\n",
      " Intermediaries and Conquests \n",
      "==============================\n",
      "Consequent: price                    = 1034401.1147602632\n",
      "  lower:\n",
      "    Accumulate using accumulation_max : 0.199712\n",
      "  low:\n",
      "    Accumulate using accumulation_max : 0.008695652173913044\n",
      "  average:\n",
      "    Accumulate using accumulation_max : 0.0\n",
      "  high:\n",
      "    Accumulate using accumulation_max : 0.0\n",
      "  higher:\n",
      "    Accumulate using accumulation_max : 0.0\n",
      "\n",
      "1034401.1147602632\n"
     ]
    }
   ],
   "source": [
    "prices.input['bathrooms'] = 1\n",
    "prices.input['sqft_living'] = 3420\n",
    "\n",
    "prices.compute()\n",
    "prices.print_state()\n",
    "print(prices.output['price'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Визуализация функции принадлежности для выходной переменной price  \n",
    "\n",
    "Функция получена в процессе аккумуляции и используется для дефаззификации значения выходной переменной price"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 635,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "price.view(sim=prices)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Тестирование нечёткой системы"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 636,
   "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>bathrooms</th>\n",
       "      <th>sqft_living</th>\n",
       "      <th>price</th>\n",
       "      <th>Pred</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.00</td>\n",
       "      <td>1180</td>\n",
       "      <td>221900.0</td>\n",
       "      <td>7.360929e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2.25</td>\n",
       "      <td>2570</td>\n",
       "      <td>538000.0</td>\n",
       "      <td>8.262097e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.00</td>\n",
       "      <td>770</td>\n",
       "      <td>180000.0</td>\n",
       "      <td>7.360929e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3.00</td>\n",
       "      <td>1960</td>\n",
       "      <td>604000.0</td>\n",
       "      <td>7.563265e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2.00</td>\n",
       "      <td>1680</td>\n",
       "      <td>510000.0</td>\n",
       "      <td>8.163228e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>4.50</td>\n",
       "      <td>5420</td>\n",
       "      <td>1225000.0</td>\n",
       "      <td>3.963452e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2.25</td>\n",
       "      <td>1715</td>\n",
       "      <td>257500.0</td>\n",
       "      <td>7.754055e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1.50</td>\n",
       "      <td>1060</td>\n",
       "      <td>291850.0</td>\n",
       "      <td>8.163228e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1.00</td>\n",
       "      <td>1780</td>\n",
       "      <td>229500.0</td>\n",
       "      <td>7.429885e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2.50</td>\n",
       "      <td>1890</td>\n",
       "      <td>323000.0</td>\n",
       "      <td>7.507770e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2.50</td>\n",
       "      <td>3560</td>\n",
       "      <td>662500.0</td>\n",
       "      <td>2.661365e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1.00</td>\n",
       "      <td>1160</td>\n",
       "      <td>468000.0</td>\n",
       "      <td>7.360929e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1.00</td>\n",
       "      <td>1430</td>\n",
       "      <td>310000.0</td>\n",
       "      <td>7.360929e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1.75</td>\n",
       "      <td>1370</td>\n",
       "      <td>400000.0</td>\n",
       "      <td>8.631650e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2.00</td>\n",
       "      <td>1810</td>\n",
       "      <td>530000.0</td>\n",
       "      <td>8.163228e+05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    bathrooms  sqft_living      price          Pred\n",
       "0        1.00         1180   221900.0  7.360929e+05\n",
       "1        2.25         2570   538000.0  8.262097e+05\n",
       "2        1.00          770   180000.0  7.360929e+05\n",
       "3        3.00         1960   604000.0  7.563265e+05\n",
       "4        2.00         1680   510000.0  8.163228e+05\n",
       "5        4.50         5420  1225000.0  3.963452e+06\n",
       "6        2.25         1715   257500.0  7.754055e+05\n",
       "7        1.50         1060   291850.0  8.163228e+05\n",
       "8        1.00         1780   229500.0  7.429885e+05\n",
       "9        2.50         1890   323000.0  7.507770e+05\n",
       "10       2.50         3560   662500.0  2.661365e+06\n",
       "11       1.00         1160   468000.0  7.360929e+05\n",
       "12       1.00         1430   310000.0  7.360929e+05\n",
       "13       1.75         1370   400000.0  8.631650e+05\n",
       "14       2.00         1810   530000.0  8.163228e+05"
      ]
     },
     "execution_count": 636,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Функция для автоматизации вычисления целевой переменной Y на основе вектора признаков X\n",
    "def fuzzy_pred(row):\n",
    "    prices.input['bathrooms'] = row['bathrooms']\n",
    "    prices.input['sqft_living'] = row['sqft_living']\n",
    "    prices.compute()\n",
    "    return prices.output['price']\n",
    "\n",
    "res = df_house[['bathrooms', 'sqft_living', 'price']].head(100)\n",
    "\n",
    "res['Pred'] = res.apply(fuzzy_pred, axis=1)\n",
    "\n",
    "res.head(15)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Успешно выполнилось заполнение данными и предсказание"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Оценка результатов на основе метрик для задачи регрессии"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 637,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'RMSE': 712719.1570778367,\n",
       " 'RMAE': 706.4876249018378,\n",
       " 'R2': -4.533784587058265}"
      ]
     },
     "execution_count": 637,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import math\n",
    "from sklearn import metrics\n",
    "\n",
    "rmetrics = {}\n",
    "rmetrics[\"RMSE\"] = math.sqrt(metrics.mean_squared_error(res['price'], res['Pred']))\n",
    "rmetrics[\"RMAE\"] = math.sqrt(metrics.mean_absolute_error(res['price'], res['Pred']))\n",
    "rmetrics[\"R2\"] = metrics.r2_score(res['price'], res['Pred'])\n",
    "\n",
    "rmetrics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Визуализация оценки качества нечёткой системы и проверка системы  \n",
    "\n",
    "Тестирование работы модели, проводилось также. После того, как подали тестовые данные, система определила цену."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 638,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    bathrooms  sqft_living      price  Predicted Price\n",
      "14       1.00         1140   160000.0     7.360929e+05\n",
      "12       1.00         1410   175000.0     7.360929e+05\n",
      "5        2.00         1710   211000.0     8.163228e+05\n",
      "18       1.00         1440   355000.0     7.360929e+05\n",
      "13       2.25         1960   365000.0     7.754055e+05\n",
      "0        2.25         2070   365000.0     7.754055e+05\n",
      "8        2.50         1600   384500.0     7.421903e+05\n",
      "11       1.75         1930   385000.0     8.631650e+05\n",
      "19       2.25         1960   474000.0     7.754055e+05\n",
      "9        1.00          910   605000.0     7.360929e+05\n",
      "10       1.00         1830   638000.0     7.463906e+05\n",
      "7        2.50         1800   680000.0     7.443222e+05\n",
      "4        2.50         2550   711000.0     8.233853e+05\n",
      "6        2.50         2690   790000.0     8.430919e+05\n",
      "17       3.25         4360   795127.0     3.861472e+06\n",
      "16       1.00         1430   800000.0     7.360929e+05\n",
      "1        3.00         2900   865000.0     8.720014e+05\n",
      "2        2.50         3770  1038000.0     3.296596e+06\n",
      "15       3.75         4130  1070000.0     3.734520e+06\n",
      "3        3.50         4560  1490000.0     3.924471e+06\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Берём случайно записи из фрейма\n",
    "df_random = df_house[['bathrooms', 'sqft_living', 'price']].sample(20, random_state=42)\n",
    "df_random = df_random.reset_index(drop=True)\n",
    "\n",
    "\n",
    "predicted_prices = []\n",
    "\n",
    "for i in range(len(df_random)):\n",
    "    prices.input['bathrooms'] = df_random.loc[i, 'bathrooms']\n",
    "    prices.input['sqft_living'] = df_random.loc[i, 'sqft_living']\n",
    "    prices.compute()\n",
    "    # a = prices.print_state()\n",
    "    predicted_prices.append(prices.output['price'])\n",
    "\n",
    "\n",
    "df_random['Predicted Price'] = predicted_prices\n",
    "df_random_sorted = df_random.sort_values(by='price')\n",
    "\n",
    "\n",
    "# Вывод результатов\n",
    "print(df_random_sorted[['bathrooms', 'sqft_living', 'price', 'Predicted Price']])\n",
    "\n",
    "# Визуализация графиком\n",
    "plt.figure(figsize=(10, 5))\n",
    "plt.plot(df_random.index, df_random_sorted['price'], marker='o', label='Real Price', color='red')\n",
    "plt.plot(df_random.index, df_random_sorted['Predicted Price'], marker='s', label='Predicted Price', color='green')\n",
    "plt.xlabel(\"Index\")\n",
    "plt.ylabel(\"Price\")\n",
    "plt.legend()\n",
    "plt.title(\"Сравнение реальных цен с предсказанными\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Вывод... Стало более лучше. Результаты предсказанных цен стали точнее, а некоторые цены почти совпали.  \n",
    "\n",
    "Система лучше предсказывает цену, по входным характеристикам. По крайней мере предсказание стало лучше предыдущего.  \n",
    "\n",
    "Как-то так ^_^"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "mai",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
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