Solar Radiation Prediction.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <center><font size = '10' color = 'crimson'>Solar Radiation Prediction<font/><center/>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <i>Table of Content<i/>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. [**Importing Libraries**](#import)\n",
    "2. [**Reading Data**](#load_data)\n",
    "3. [**Data Wrangling**](#data_wrangling)\n",
    "4. [**Feature Selection using Correlation Matrix**](#correlation_matrix)\n",
    "5. [**Feature Selection using SelectKBest Method**](#kbest_method)\n",
    "6. [**Feature Selection using Extra Tree Classifier**](#extra_tree)\n",
    "7. [**Feature Engineering with BoxCox, Log, Min-Max and Standard transformation**](#feature_engg)\n",
    "8. [**Preparing data - Standardisation and Splitting**](#data_prep)\n",
    "9. [**Prediction with XGBoost**](#xgboost)\n",
    "10. [**Prediction with MultiLayer Perceptron**](#perceptron)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <font color = 'green'>Importing Libraries<font/><a class = 'anchor' id = 'import'/>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "import re\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import xgboost as xgb\n",
    "from scipy import stats\n",
    "from collections import Counter\n",
    "from xgboost import XGBRegressor\n",
    "from sklearn.preprocessing import StandardScaler, MinMaxScaler, LabelEncoder\n",
    "from sklearn.ensemble import ExtraTreesClassifier\n",
    "from sklearn.feature_selection import SelectKBest\n",
    "from sklearn.feature_selection import chi2\n",
    "from sklearn.model_selection import train_test_split\n",
    "from tensorflow.keras.layers import Dense, Dropout, Activation\n",
    "from tensorflow.keras.optimizers import SGD, Adam\n",
    "from tensorflow.keras.models import Sequential\n",
    "from sklearn.metrics import mean_squared_error, r2_score, mean_absolute_error"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams['figure.figsize'] = (12,6)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <font color = 'violet'>Loading Data<font/><a class = 'anchor' id = 'load_data'/>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv(\"SolarPrediction.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>UNIXTime</th>\n",
       "      <th>Data</th>\n",
       "      <th>Time</th>\n",
       "      <th>Radiation</th>\n",
       "      <th>Temperature</th>\n",
       "      <th>Pressure</th>\n",
       "      <th>Humidity</th>\n",
       "      <th>WindDirection(Degrees)</th>\n",
       "      <th>Speed</th>\n",
       "      <th>TimeSunRise</th>\n",
       "      <th>TimeSunSet</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1475229326</td>\n",
       "      <td>9/29/2016 12:00:00 AM</td>\n",
       "      <td>23:55:26</td>\n",
       "      <td>1.21</td>\n",
       "      <td>48</td>\n",
       "      <td>30.46</td>\n",
       "      <td>59</td>\n",
       "      <td>177.39</td>\n",
       "      <td>5.62</td>\n",
       "      <td>06:13:00</td>\n",
       "      <td>18:13:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1475229023</td>\n",
       "      <td>9/29/2016 12:00:00 AM</td>\n",
       "      <td>23:50:23</td>\n",
       "      <td>1.21</td>\n",
       "      <td>48</td>\n",
       "      <td>30.46</td>\n",
       "      <td>58</td>\n",
       "      <td>176.78</td>\n",
       "      <td>3.37</td>\n",
       "      <td>06:13:00</td>\n",
       "      <td>18:13:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1475228726</td>\n",
       "      <td>9/29/2016 12:00:00 AM</td>\n",
       "      <td>23:45:26</td>\n",
       "      <td>1.23</td>\n",
       "      <td>48</td>\n",
       "      <td>30.46</td>\n",
       "      <td>57</td>\n",
       "      <td>158.75</td>\n",
       "      <td>3.37</td>\n",
       "      <td>06:13:00</td>\n",
       "      <td>18:13:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1475228421</td>\n",
       "      <td>9/29/2016 12:00:00 AM</td>\n",
       "      <td>23:40:21</td>\n",
       "      <td>1.21</td>\n",
       "      <td>48</td>\n",
       "      <td>30.46</td>\n",
       "      <td>60</td>\n",
       "      <td>137.71</td>\n",
       "      <td>3.37</td>\n",
       "      <td>06:13:00</td>\n",
       "      <td>18:13:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1475228124</td>\n",
       "      <td>9/29/2016 12:00:00 AM</td>\n",
       "      <td>23:35:24</td>\n",
       "      <td>1.17</td>\n",
       "      <td>48</td>\n",
       "      <td>30.46</td>\n",
       "      <td>62</td>\n",
       "      <td>104.95</td>\n",
       "      <td>5.62</td>\n",
       "      <td>06:13:00</td>\n",
       "      <td>18:13:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     UNIXTime                   Data      Time  Radiation  Temperature  \\\n",
       "0  1475229326  9/29/2016 12:00:00 AM  23:55:26       1.21           48   \n",
       "1  1475229023  9/29/2016 12:00:00 AM  23:50:23       1.21           48   \n",
       "2  1475228726  9/29/2016 12:00:00 AM  23:45:26       1.23           48   \n",
       "3  1475228421  9/29/2016 12:00:00 AM  23:40:21       1.21           48   \n",
       "4  1475228124  9/29/2016 12:00:00 AM  23:35:24       1.17           48   \n",
       "\n",
       "   Pressure  Humidity  WindDirection(Degrees)  Speed TimeSunRise TimeSunSet  \n",
       "0     30.46        59                  177.39   5.62    06:13:00   18:13:00  \n",
       "1     30.46        58                  176.78   3.37    06:13:00   18:13:00  \n",
       "2     30.46        57                  158.75   3.37    06:13:00   18:13:00  \n",
       "3     30.46        60                  137.71   3.37    06:13:00   18:13:00  \n",
       "4     30.46        62                  104.95   5.62    06:13:00   18:13:00  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(32686, 11)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 32686 entries, 0 to 32685\n",
      "Data columns (total 11 columns):\n",
      " #   Column                  Non-Null Count  Dtype  \n",
      "---  ------                  --------------  -----  \n",
      " 0   UNIXTime                32686 non-null  int64  \n",
      " 1   Data                    32686 non-null  object \n",
      " 2   Time                    32686 non-null  object \n",
      " 3   Radiation               32686 non-null  float64\n",
      " 4   Temperature             32686 non-null  int64  \n",
      " 5   Pressure                32686 non-null  float64\n",
      " 6   Humidity                32686 non-null  int64  \n",
      " 7   WindDirection(Degrees)  32686 non-null  float64\n",
      " 8   Speed                   32686 non-null  float64\n",
      " 9   TimeSunRise             32686 non-null  object \n",
      " 10  TimeSunSet              32686 non-null  object \n",
      "dtypes: float64(4), int64(3), object(4)\n",
      "memory usage: 2.7+ MB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <font color = 'blue'>Data Wrangling<font/><a class = 'anchor' id = 'data_wrangling'/>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = data.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# extract the date from the date_time format of the 'Data' parameter\n",
    "\n",
    "df['Data'] = df['Data'].apply(lambda x : x.split()[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# extract the date time features from the given parameter using date time python methods\n",
    "\n",
    "df['Month'] = pd.to_datetime(df['Data']).dt.month\n",
    "df['Day'] = pd.to_datetime(df['Data']).dt.day\n",
    "\n",
    "df['Hour'] = pd.to_datetime(df['Time']).dt.hour\n",
    "df['Minute'] = pd.to_datetime(df['Time']).dt.minute\n",
    "df['Second'] = pd.to_datetime(df['Time']).dt.second"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "      <th>Radiation</th>\n",
       "      <th>Temperature</th>\n",
       "      <th>Pressure</th>\n",
       "      <th>Humidity</th>\n",
       "      <th>WindDirection(Degrees)</th>\n",
       "      <th>Speed</th>\n",
       "      <th>TimeSunRise</th>\n",
       "      <th>TimeSunSet</th>\n",
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       "      <th>0</th>\n",
       "      <td>1475229326</td>\n",
       "      <td>9/29/2016</td>\n",
       "      <td>23:55:26</td>\n",
       "      <td>1.21</td>\n",
       "      <td>48</td>\n",
       "      <td>30.46</td>\n",
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       "      <td>177.39</td>\n",
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       "      <td>06:13:00</td>\n",
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       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>23</td>\n",
       "      <td>55</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1475229023</td>\n",
       "      <td>9/29/2016</td>\n",
       "      <td>23:50:23</td>\n",
       "      <td>1.21</td>\n",
       "      <td>48</td>\n",
       "      <td>30.46</td>\n",
       "      <td>58</td>\n",
       "      <td>176.78</td>\n",
       "      <td>3.37</td>\n",
       "      <td>06:13:00</td>\n",
       "      <td>18:13:00</td>\n",
       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>23</td>\n",
       "      <td>50</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1475228726</td>\n",
       "      <td>9/29/2016</td>\n",
       "      <td>23:45:26</td>\n",
       "      <td>1.23</td>\n",
       "      <td>48</td>\n",
       "      <td>30.46</td>\n",
       "      <td>57</td>\n",
       "      <td>158.75</td>\n",
       "      <td>3.37</td>\n",
       "      <td>06:13:00</td>\n",
       "      <td>18:13:00</td>\n",
       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>23</td>\n",
       "      <td>45</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1475228421</td>\n",
       "      <td>9/29/2016</td>\n",
       "      <td>23:40:21</td>\n",
       "      <td>1.21</td>\n",
       "      <td>48</td>\n",
       "      <td>30.46</td>\n",
       "      <td>60</td>\n",
       "      <td>137.71</td>\n",
       "      <td>3.37</td>\n",
       "      <td>06:13:00</td>\n",
       "      <td>18:13:00</td>\n",
       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>23</td>\n",
       "      <td>40</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1475228124</td>\n",
       "      <td>9/29/2016</td>\n",
       "      <td>23:35:24</td>\n",
       "      <td>1.17</td>\n",
       "      <td>48</td>\n",
       "      <td>30.46</td>\n",
       "      <td>62</td>\n",
       "      <td>104.95</td>\n",
       "      <td>5.62</td>\n",
       "      <td>06:13:00</td>\n",
       "      <td>18:13:00</td>\n",
       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>23</td>\n",
       "      <td>35</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      "text/plain": [
       "     UNIXTime       Data      Time  Radiation  Temperature  Pressure  \\\n",
       "0  1475229326  9/29/2016  23:55:26       1.21           48     30.46   \n",
       "1  1475229023  9/29/2016  23:50:23       1.21           48     30.46   \n",
       "2  1475228726  9/29/2016  23:45:26       1.23           48     30.46   \n",
       "3  1475228421  9/29/2016  23:40:21       1.21           48     30.46   \n",
       "4  1475228124  9/29/2016  23:35:24       1.17           48     30.46   \n",
       "\n",
       "   Humidity  WindDirection(Degrees)  Speed TimeSunRise TimeSunSet  Month  Day  \\\n",
       "0        59                  177.39   5.62    06:13:00   18:13:00      9   29   \n",
       "1        58                  176.78   3.37    06:13:00   18:13:00      9   29   \n",
       "2        57                  158.75   3.37    06:13:00   18:13:00      9   29   \n",
       "3        60                  137.71   3.37    06:13:00   18:13:00      9   29   \n",
       "4        62                  104.95   5.62    06:13:00   18:13:00      9   29   \n",
       "\n",
       "   Hour  Minute  Second  \n",
       "0    23      55      26  \n",
       "1    23      50      23  \n",
       "2    23      45      26  \n",
       "3    23      40      21  \n",
       "4    23      35      24  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# extract the sunrise and sunset information using regular expression\n",
    "\n",
    "df['risehour'] = df['TimeSunRise'].apply(lambda x : re.search(r'^\\d+', x).group(0)).astype(int)\n",
    "df['riseminute'] = df['TimeSunRise'].apply(lambda x : re.search(r'(?<=\\:)\\d+(?=\\:)', x).group(0)).astype(int)\n",
    "\n",
    "df['sethour'] = df['TimeSunSet'].apply(lambda x : re.search(r'^\\d+', x).group(0)).astype(int)\n",
    "df['setminute'] = df['TimeSunSet'].apply(lambda x : re.search(r'(?<=\\:)\\d+(?=\\:)', x).group(0)).astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "      <th>Pressure</th>\n",
       "      <th>Humidity</th>\n",
       "      <th>WindDirection(Degrees)</th>\n",
       "      <th>Speed</th>\n",
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       "      <th>TimeSunSet</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day</th>\n",
       "      <th>Hour</th>\n",
       "      <th>Minute</th>\n",
       "      <th>Second</th>\n",
       "      <th>risehour</th>\n",
       "      <th>riseminute</th>\n",
       "      <th>sethour</th>\n",
       "      <th>setminute</th>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1475229326</td>\n",
       "      <td>9/29/2016</td>\n",
       "      <td>23:55:26</td>\n",
       "      <td>1.21</td>\n",
       "      <td>48</td>\n",
       "      <td>30.46</td>\n",
       "      <td>59</td>\n",
       "      <td>177.39</td>\n",
       "      <td>5.62</td>\n",
       "      <td>06:13:00</td>\n",
       "      <td>18:13:00</td>\n",
       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>23</td>\n",
       "      <td>55</td>\n",
       "      <td>26</td>\n",
       "      <td>6</td>\n",
       "      <td>13</td>\n",
       "      <td>18</td>\n",
       "      <td>13</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1475229023</td>\n",
       "      <td>9/29/2016</td>\n",
       "      <td>23:50:23</td>\n",
       "      <td>1.21</td>\n",
       "      <td>48</td>\n",
       "      <td>30.46</td>\n",
       "      <td>58</td>\n",
       "      <td>176.78</td>\n",
       "      <td>3.37</td>\n",
       "      <td>06:13:00</td>\n",
       "      <td>18:13:00</td>\n",
       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>23</td>\n",
       "      <td>50</td>\n",
       "      <td>23</td>\n",
       "      <td>6</td>\n",
       "      <td>13</td>\n",
       "      <td>18</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1475228726</td>\n",
       "      <td>9/29/2016</td>\n",
       "      <td>23:45:26</td>\n",
       "      <td>1.23</td>\n",
       "      <td>48</td>\n",
       "      <td>30.46</td>\n",
       "      <td>57</td>\n",
       "      <td>158.75</td>\n",
       "      <td>3.37</td>\n",
       "      <td>06:13:00</td>\n",
       "      <td>18:13:00</td>\n",
       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>23</td>\n",
       "      <td>45</td>\n",
       "      <td>26</td>\n",
       "      <td>6</td>\n",
       "      <td>13</td>\n",
       "      <td>18</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1475228421</td>\n",
       "      <td>9/29/2016</td>\n",
       "      <td>23:40:21</td>\n",
       "      <td>1.21</td>\n",
       "      <td>48</td>\n",
       "      <td>30.46</td>\n",
       "      <td>60</td>\n",
       "      <td>137.71</td>\n",
       "      <td>3.37</td>\n",
       "      <td>06:13:00</td>\n",
       "      <td>18:13:00</td>\n",
       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>23</td>\n",
       "      <td>40</td>\n",
       "      <td>21</td>\n",
       "      <td>6</td>\n",
       "      <td>13</td>\n",
       "      <td>18</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1475228124</td>\n",
       "      <td>9/29/2016</td>\n",
       "      <td>23:35:24</td>\n",
       "      <td>1.17</td>\n",
       "      <td>48</td>\n",
       "      <td>30.46</td>\n",
       "      <td>62</td>\n",
       "      <td>104.95</td>\n",
       "      <td>5.62</td>\n",
       "      <td>06:13:00</td>\n",
       "      <td>18:13:00</td>\n",
       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>23</td>\n",
       "      <td>35</td>\n",
       "      <td>24</td>\n",
       "      <td>6</td>\n",
       "      <td>13</td>\n",
       "      <td>18</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     UNIXTime       Data      Time  Radiation  Temperature  Pressure  \\\n",
       "0  1475229326  9/29/2016  23:55:26       1.21           48     30.46   \n",
       "1  1475229023  9/29/2016  23:50:23       1.21           48     30.46   \n",
       "2  1475228726  9/29/2016  23:45:26       1.23           48     30.46   \n",
       "3  1475228421  9/29/2016  23:40:21       1.21           48     30.46   \n",
       "4  1475228124  9/29/2016  23:35:24       1.17           48     30.46   \n",
       "\n",
       "   Humidity  WindDirection(Degrees)  Speed TimeSunRise TimeSunSet  Month  Day  \\\n",
       "0        59                  177.39   5.62    06:13:00   18:13:00      9   29   \n",
       "1        58                  176.78   3.37    06:13:00   18:13:00      9   29   \n",
       "2        57                  158.75   3.37    06:13:00   18:13:00      9   29   \n",
       "3        60                  137.71   3.37    06:13:00   18:13:00      9   29   \n",
       "4        62                  104.95   5.62    06:13:00   18:13:00      9   29   \n",
       "\n",
       "   Hour  Minute  Second  risehour  riseminute  sethour  setminute  \n",
       "0    23      55      26         6          13       18         13  \n",
       "1    23      50      23         6          13       18         13  \n",
       "2    23      45      26         6          13       18         13  \n",
       "3    23      40      21         6          13       18         13  \n",
       "4    23      35      24         6          13       18         13  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# drop the parameters that are not required after extracting the relevant information\n",
    "\n",
    "df.drop(['UNIXTime', 'Data', 'Time', 'TimeSunRise', 'TimeSunSet'], axis = 1, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(32686, 15)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\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>Radiation</th>\n",
       "      <th>Temperature</th>\n",
       "      <th>Pressure</th>\n",
       "      <th>Humidity</th>\n",
       "      <th>WindDirection(Degrees)</th>\n",
       "      <th>Speed</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day</th>\n",
       "      <th>Hour</th>\n",
       "      <th>Minute</th>\n",
       "      <th>Second</th>\n",
       "      <th>risehour</th>\n",
       "      <th>riseminute</th>\n",
       "      <th>sethour</th>\n",
       "      <th>setminute</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.21</td>\n",
       "      <td>48</td>\n",
       "      <td>30.46</td>\n",
       "      <td>59</td>\n",
       "      <td>177.39</td>\n",
       "      <td>5.62</td>\n",
       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>23</td>\n",
       "      <td>55</td>\n",
       "      <td>26</td>\n",
       "      <td>6</td>\n",
       "      <td>13</td>\n",
       "      <td>18</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.21</td>\n",
       "      <td>48</td>\n",
       "      <td>30.46</td>\n",
       "      <td>58</td>\n",
       "      <td>176.78</td>\n",
       "      <td>3.37</td>\n",
       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>23</td>\n",
       "      <td>50</td>\n",
       "      <td>23</td>\n",
       "      <td>6</td>\n",
       "      <td>13</td>\n",
       "      <td>18</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.23</td>\n",
       "      <td>48</td>\n",
       "      <td>30.46</td>\n",
       "      <td>57</td>\n",
       "      <td>158.75</td>\n",
       "      <td>3.37</td>\n",
       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>23</td>\n",
       "      <td>45</td>\n",
       "      <td>26</td>\n",
       "      <td>6</td>\n",
       "      <td>13</td>\n",
       "      <td>18</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.21</td>\n",
       "      <td>48</td>\n",
       "      <td>30.46</td>\n",
       "      <td>60</td>\n",
       "      <td>137.71</td>\n",
       "      <td>3.37</td>\n",
       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>23</td>\n",
       "      <td>40</td>\n",
       "      <td>21</td>\n",
       "      <td>6</td>\n",
       "      <td>13</td>\n",
       "      <td>18</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.17</td>\n",
       "      <td>48</td>\n",
       "      <td>30.46</td>\n",
       "      <td>62</td>\n",
       "      <td>104.95</td>\n",
       "      <td>5.62</td>\n",
       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>23</td>\n",
       "      <td>35</td>\n",
       "      <td>24</td>\n",
       "      <td>6</td>\n",
       "      <td>13</td>\n",
       "      <td>18</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Radiation  Temperature  Pressure  Humidity  WindDirection(Degrees)  Speed  \\\n",
       "0       1.21           48     30.46        59                  177.39   5.62   \n",
       "1       1.21           48     30.46        58                  176.78   3.37   \n",
       "2       1.23           48     30.46        57                  158.75   3.37   \n",
       "3       1.21           48     30.46        60                  137.71   3.37   \n",
       "4       1.17           48     30.46        62                  104.95   5.62   \n",
       "\n",
       "   Month  Day  Hour  Minute  Second  risehour  riseminute  sethour  setminute  \n",
       "0      9   29    23      55      26         6          13       18         13  \n",
       "1      9   29    23      50      23         6          13       18         13  \n",
       "2      9   29    23      45      26         6          13       18         13  \n",
       "3      9   29    23      40      21         6          13       18         13  \n",
       "4      9   29    23      35      24         6          13       18         13  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1.21, 1.21, 1.23, ..., 1.2 , 1.23, 1.2 ])"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.array(df['Radiation'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "input_features = df.drop('Radiation', axis = 1)\n",
    "target = df['Radiation']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <font color = 'pink'>Feature Selection using Correlation Matrix<font/><a class = 'anchor' id = 'correlation_matrix'/>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$$\n",
    "r=\\frac{\\sum\\left(x_i-\\bar{x}\\right)\\left(y_i-\\bar{y}\\right)}{\\sqrt{\\sum\\left(x_i-\\bar{x}\\right)^2 \\sum\\left(y_i-\\bar{y}\\right)^2}}\n",
    "$$\n",
    "- $r=$ correlation coefficient\n",
    "- $x_i=$ values of the $\\mathrm{x}$-variable in a sample\n",
    "- $\\bar{x}=$ mean of the values of the $\\mathrm{x}$-variable\n",
    "- $y_i=$ values of the $y$-variable in a sample\n",
    "- $\\bar{y}=$ mean of the values of the $y$-variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": true
   },
   "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>Radiation</th>\n",
       "      <th>Temperature</th>\n",
       "      <th>Pressure</th>\n",
       "      <th>Humidity</th>\n",
       "      <th>WindDirection(Degrees)</th>\n",
       "      <th>Speed</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day</th>\n",
       "      <th>Hour</th>\n",
       "      <th>Minute</th>\n",
       "      <th>Second</th>\n",
       "      <th>risehour</th>\n",
       "      <th>riseminute</th>\n",
       "      <th>sethour</th>\n",
       "      <th>setminute</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Radiation</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.734955</td>\n",
       "      <td>0.119016</td>\n",
       "      <td>-0.226171</td>\n",
       "      <td>-0.230324</td>\n",
       "      <td>0.073627</td>\n",
       "      <td>-0.095450</td>\n",
       "      <td>0.039978</td>\n",
       "      <td>0.004398</td>\n",
       "      <td>-0.000730</td>\n",
       "      <td>-0.031270</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.092850</td>\n",
       "      <td>0.048719</td>\n",
       "      <td>-0.039816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Temperature</th>\n",
       "      <td>0.734955</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.311173</td>\n",
       "      <td>-0.285055</td>\n",
       "      <td>-0.259421</td>\n",
       "      <td>-0.031458</td>\n",
       "      <td>-0.354560</td>\n",
       "      <td>-0.123705</td>\n",
       "      <td>0.197464</td>\n",
       "      <td>-0.001934</td>\n",
       "      <td>-0.036147</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.380968</td>\n",
       "      <td>0.300920</td>\n",
       "      <td>-0.242881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pressure</th>\n",
       "      <td>0.119016</td>\n",
       "      <td>0.311173</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.223973</td>\n",
       "      <td>-0.229010</td>\n",
       "      <td>-0.083639</td>\n",
       "      <td>-0.341759</td>\n",
       "      <td>-0.024633</td>\n",
       "      <td>0.091069</td>\n",
       "      <td>0.001860</td>\n",
       "      <td>-0.031102</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.380399</td>\n",
       "      <td>0.151939</td>\n",
       "      <td>-0.119599</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Humidity</th>\n",
       "      <td>-0.226171</td>\n",
       "      <td>-0.285055</td>\n",
       "      <td>-0.223973</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.001833</td>\n",
       "      <td>-0.211624</td>\n",
       "      <td>-0.068854</td>\n",
       "      <td>0.014637</td>\n",
       "      <td>0.077899</td>\n",
       "      <td>0.000499</td>\n",
       "      <td>-0.027682</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.023955</td>\n",
       "      <td>0.145143</td>\n",
       "      <td>-0.119526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WindDirection(Degrees)</th>\n",
       "      <td>-0.230324</td>\n",
       "      <td>-0.259421</td>\n",
       "      <td>-0.229010</td>\n",
       "      <td>-0.001833</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.073092</td>\n",
       "      <td>0.181485</td>\n",
       "      <td>-0.082354</td>\n",
       "      <td>-0.077969</td>\n",
       "      <td>-0.000602</td>\n",
       "      <td>-0.032568</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.176929</td>\n",
       "      <td>-0.078540</td>\n",
       "      <td>0.070030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Speed</th>\n",
       "      <td>0.073627</td>\n",
       "      <td>-0.031458</td>\n",
       "      <td>-0.083639</td>\n",
       "      <td>-0.211624</td>\n",
       "      <td>0.073092</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.150822</td>\n",
       "      <td>0.117337</td>\n",
       "      <td>-0.057939</td>\n",
       "      <td>0.000192</td>\n",
       "      <td>-0.032934</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.167075</td>\n",
       "      <td>-0.159384</td>\n",
       "      <td>0.119926</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Month</th>\n",
       "      <td>-0.095450</td>\n",
       "      <td>-0.354560</td>\n",
       "      <td>-0.341759</td>\n",
       "      <td>-0.068854</td>\n",
       "      <td>0.181485</td>\n",
       "      <td>0.150822</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.038027</td>\n",
       "      <td>-0.005396</td>\n",
       "      <td>0.000168</td>\n",
       "      <td>0.220563</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.952472</td>\n",
       "      <td>-0.784783</td>\n",
       "      <td>0.541883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Day</th>\n",
       "      <td>0.039978</td>\n",
       "      <td>-0.123705</td>\n",
       "      <td>-0.024633</td>\n",
       "      <td>0.014637</td>\n",
       "      <td>-0.082354</td>\n",
       "      <td>0.117337</td>\n",
       "      <td>0.038027</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.008010</td>\n",
       "      <td>-0.000196</td>\n",
       "      <td>0.089078</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.274522</td>\n",
       "      <td>-0.263575</td>\n",
       "      <td>0.265662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hour</th>\n",
       "      <td>0.004398</td>\n",
       "      <td>0.197464</td>\n",
       "      <td>0.091069</td>\n",
       "      <td>0.077899</td>\n",
       "      <td>-0.077969</td>\n",
       "      <td>-0.057939</td>\n",
       "      <td>-0.005396</td>\n",
       "      <td>-0.008010</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.004052</td>\n",
       "      <td>0.004199</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.006772</td>\n",
       "      <td>0.008629</td>\n",
       "      <td>-0.007056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Minute</th>\n",
       "      <td>-0.000730</td>\n",
       "      <td>-0.001934</td>\n",
       "      <td>0.001860</td>\n",
       "      <td>0.000499</td>\n",
       "      <td>-0.000602</td>\n",
       "      <td>0.000192</td>\n",
       "      <td>0.000168</td>\n",
       "      <td>-0.000196</td>\n",
       "      <td>-0.004052</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.002517</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.000158</td>\n",
       "      <td>0.001052</td>\n",
       "      <td>-0.002215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Second</th>\n",
       "      <td>-0.031270</td>\n",
       "      <td>-0.036147</td>\n",
       "      <td>-0.031102</td>\n",
       "      <td>-0.027682</td>\n",
       "      <td>-0.032568</td>\n",
       "      <td>-0.032934</td>\n",
       "      <td>0.220563</td>\n",
       "      <td>0.089078</td>\n",
       "      <td>0.004199</td>\n",
       "      <td>0.002517</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.258917</td>\n",
       "      <td>-0.037743</td>\n",
       "      <td>0.003571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>risehour</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>riseminute</th>\n",
       "      <td>-0.092850</td>\n",
       "      <td>-0.380968</td>\n",
       "      <td>-0.380399</td>\n",
       "      <td>-0.023955</td>\n",
       "      <td>0.176929</td>\n",
       "      <td>0.167075</td>\n",
       "      <td>0.952472</td>\n",
       "      <td>0.274522</td>\n",
       "      <td>-0.006772</td>\n",
       "      <td>-0.000158</td>\n",
       "      <td>0.258917</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.742329</td>\n",
       "      <td>0.562851</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sethour</th>\n",
       "      <td>0.048719</td>\n",
       "      <td>0.300920</td>\n",
       "      <td>0.151939</td>\n",
       "      <td>0.145143</td>\n",
       "      <td>-0.078540</td>\n",
       "      <td>-0.159384</td>\n",
       "      <td>-0.784783</td>\n",
       "      <td>-0.263575</td>\n",
       "      <td>0.008629</td>\n",
       "      <td>0.001052</td>\n",
       "      <td>-0.037743</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.742329</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.873471</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>setminute</th>\n",
       "      <td>-0.039816</td>\n",
       "      <td>-0.242881</td>\n",
       "      <td>-0.119599</td>\n",
       "      <td>-0.119526</td>\n",
       "      <td>0.070030</td>\n",
       "      <td>0.119926</td>\n",
       "      <td>0.541883</td>\n",
       "      <td>0.265662</td>\n",
       "      <td>-0.007056</td>\n",
       "      <td>-0.002215</td>\n",
       "      <td>0.003571</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.562851</td>\n",
       "      <td>-0.873471</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        Radiation  Temperature  Pressure  Humidity  \\\n",
       "Radiation                1.000000     0.734955  0.119016 -0.226171   \n",
       "Temperature              0.734955     1.000000  0.311173 -0.285055   \n",
       "Pressure                 0.119016     0.311173  1.000000 -0.223973   \n",
       "Humidity                -0.226171    -0.285055 -0.223973  1.000000   \n",
       "WindDirection(Degrees)  -0.230324    -0.259421 -0.229010 -0.001833   \n",
       "Speed                    0.073627    -0.031458 -0.083639 -0.211624   \n",
       "Month                   -0.095450    -0.354560 -0.341759 -0.068854   \n",
       "Day                      0.039978    -0.123705 -0.024633  0.014637   \n",
       "Hour                     0.004398     0.197464  0.091069  0.077899   \n",
       "Minute                  -0.000730    -0.001934  0.001860  0.000499   \n",
       "Second                  -0.031270    -0.036147 -0.031102 -0.027682   \n",
       "risehour                      NaN          NaN       NaN       NaN   \n",
       "riseminute              -0.092850    -0.380968 -0.380399 -0.023955   \n",
       "sethour                  0.048719     0.300920  0.151939  0.145143   \n",
       "setminute               -0.039816    -0.242881 -0.119599 -0.119526   \n",
       "\n",
       "                        WindDirection(Degrees)     Speed     Month       Day  \\\n",
       "Radiation                            -0.230324  0.073627 -0.095450  0.039978   \n",
       "Temperature                          -0.259421 -0.031458 -0.354560 -0.123705   \n",
       "Pressure                             -0.229010 -0.083639 -0.341759 -0.024633   \n",
       "Humidity                             -0.001833 -0.211624 -0.068854  0.014637   \n",
       "WindDirection(Degrees)                1.000000  0.073092  0.181485 -0.082354   \n",
       "Speed                                 0.073092  1.000000  0.150822  0.117337   \n",
       "Month                                 0.181485  0.150822  1.000000  0.038027   \n",
       "Day                                  -0.082354  0.117337  0.038027  1.000000   \n",
       "Hour                                 -0.077969 -0.057939 -0.005396 -0.008010   \n",
       "Minute                               -0.000602  0.000192  0.000168 -0.000196   \n",
       "Second                               -0.032568 -0.032934  0.220563  0.089078   \n",
       "risehour                                   NaN       NaN       NaN       NaN   \n",
       "riseminute                            0.176929  0.167075  0.952472  0.274522   \n",
       "sethour                              -0.078540 -0.159384 -0.784783 -0.263575   \n",
       "setminute                             0.070030  0.119926  0.541883  0.265662   \n",
       "\n",
       "                            Hour    Minute    Second  risehour  riseminute  \\\n",
       "Radiation               0.004398 -0.000730 -0.031270       NaN   -0.092850   \n",
       "Temperature             0.197464 -0.001934 -0.036147       NaN   -0.380968   \n",
       "Pressure                0.091069  0.001860 -0.031102       NaN   -0.380399   \n",
       "Humidity                0.077899  0.000499 -0.027682       NaN   -0.023955   \n",
       "WindDirection(Degrees) -0.077969 -0.000602 -0.032568       NaN    0.176929   \n",
       "Speed                  -0.057939  0.000192 -0.032934       NaN    0.167075   \n",
       "Month                  -0.005396  0.000168  0.220563       NaN    0.952472   \n",
       "Day                    -0.008010 -0.000196  0.089078       NaN    0.274522   \n",
       "Hour                    1.000000 -0.004052  0.004199       NaN   -0.006772   \n",
       "Minute                 -0.004052  1.000000  0.002517       NaN   -0.000158   \n",
       "Second                  0.004199  0.002517  1.000000       NaN    0.258917   \n",
       "risehour                     NaN       NaN       NaN       NaN         NaN   \n",
       "riseminute             -0.006772 -0.000158  0.258917       NaN    1.000000   \n",
       "sethour                 0.008629  0.001052 -0.037743       NaN   -0.742329   \n",
       "setminute              -0.007056 -0.002215  0.003571       NaN    0.562851   \n",
       "\n",
       "                         sethour  setminute  \n",
       "Radiation               0.048719  -0.039816  \n",
       "Temperature             0.300920  -0.242881  \n",
       "Pressure                0.151939  -0.119599  \n",
       "Humidity                0.145143  -0.119526  \n",
       "WindDirection(Degrees) -0.078540   0.070030  \n",
       "Speed                  -0.159384   0.119926  \n",
       "Month                  -0.784783   0.541883  \n",
       "Day                    -0.263575   0.265662  \n",
       "Hour                    0.008629  -0.007056  \n",
       "Minute                  0.001052  -0.002215  \n",
       "Second                 -0.037743   0.003571  \n",
       "risehour                     NaN        NaN  \n",
       "riseminute             -0.742329   0.562851  \n",
       "sethour                 1.000000  -0.873471  \n",
       "setminute              -0.873471   1.000000  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# extract the correlation between the data features\n",
    "\n",
    "df.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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5t8XSzrTtlt++z77POLrgO9l7uurSv+erqKBQJns7HZ77qeK+Lb6zgKO/l8zuLqo/4UYdnveZDs1ZIt+e7dXqvUe09eZZSl1rO0Wv04w+7pRWZ9BVKjiZrfif1lf4PoCahWIN/rWrr75ab7xhfauOdevW6c4775Qk7dmzRwMHDrR6/4orrtD8+fNVUFAge/vKF1E6dz73vcfnzp2rWbNmWU0b7tpSI9wrOfKiUsrcSN6ksz/0u8x7JpOp/PSys5tMKjr1vlNdPzV9aqS2Dnq63MiG0zzaNlK9Mf21ofeUCt+vVcrlSpV66LrrtVfLa+xwxT/8hAqTU6ojMttSbr3T2Z+BcI71NHrm26o/b7xa/L5QKpJyjsQo8cvf5Hdb7yoM2gZVlJfz2N5lOsN0SX6Deytrb6Qyt1oPTfe5oZt8b+6hyAdeUlbEUbm2bKR6M+9SXmySkr6qGVdMhd7cVZ2eu8vy91/Dni/+RwX7unNuvxXl9AzzNBzaQyd+36bs2BSr6U3uulZ+HcP19/AXlBmdIP/Lm6vD3JHKjk1W3J+7zt0hA9W7+Qq1e74kl//c+ZykClJgkuW4cUbnWJ/jfi+5MjJ9b5SSNu1X739eVv1B3XXwreIHZYfd3Ve+HcP1z7AXlBUdL78uLdRu3ijlxKYo/s+dF9DD6hF0y5Vq/vwYy9/b7phX/I9y69OFrIOmcrku0jly+33J7SEz9kYpbeshXbHpdfn37qj4Zevlf20n+VzZSut72f5x3NZyG3p3P3l2aqJtw55VdnSCvC9voWbP3qWcuJRKX6GPmsWW1kGPto0UOqaf1vd+rPIdsHm2913HalazvVq9NVEmO5P2TXnnnO1Rs9jS9n36orT45RsVdeo86OSuI/K6pKlCRlxjKdY0njpEZm83bb51jvIS0xXQ7xK1fuchbRr4pDL2RJ2ry8Y67+82p7fvs7WxnhZ4Y1cF3dJNe+57RRn7ouXeqqHC54xUzolkxX6xSrIrXmbC8o2KfusnSdLJXZHyvKSZ6o64xiaKNTa1XpZR9/YeOvHNX5Xaf8I4NexxlDAQxRr8a25ubgoPt36OQnR0yfD/oqKikhP2UtNKM1VwcMrLK3+gcXNzO2c8U6dO1aRJk6ymrQkfdc75KiMvKU2F+QVyLDM6wdHf64y3Kzl9tUlpDv6eKszLt1ylXFEbR38v5Z1apke7MDkGeKvzr/Ms79uZ7eXdpYVCRvfVytCh8rq8hRz9PdV180KrNk1mDlfomP5ae8n4C+y17ShISVVRfoHs/axHNdj7+KggMfkMcxVzvaaHfGc8ooQps5WzfnN1hmm4guQ0FeUXyKHM6A+zn5fyy4z6OC0/PkUOZdZrs5+XivLylZ9c/LyKgqQ0HR77jExODjJ7eygvNknBj41QTpTtXDFWlfKTivNoDiyfx7Kjlk7Li08pn3d/b6s8nmZydpTvDd10/MVPyi0nZPpInVj4tZKXFo+kyd57RI71AlTn/ltrTLEm5pfN+nXzQcvf9o7FpxzOgV7KjkuxTHf28yw32qa07PgUOQdaj6Jx9vdUdgX3r3at56+gbq215q75VtPtnB3UeupgrRn9sk6s2CpJSt0TJe9WDdT0vgE2X6w58csmJW8+YPnbzqkklzmlcunk76mchLPkMi7FctXeaY7nmKcgM0dpe6LkFlan+LOdHdRy6mCtH/2SYn/bKklK2xMlr1YN1Pi+ATZVrElYvlHrS92j287JQdKpKxpL5c3R3/Ostxyr+BhdMs/pcwOncucG515udnS8XE/l1ufK1nJpGKTu+9+3atf23YeV8s8ebb559hmXdbHZUm7tnB3UeNrt2j7qBSX+Vnw7z5O7j8q9dUM1uO86ijW1lC2tg96nzsGv2Px6STxmezWZOUyhY/ppzSUPXEgXDWHL33VUWPxd0WS2V+u3H5Jz/QBtuWU2o2pqIVvavvOS0lSYl6+MiGNWbTIijsn7suLbIrs0CFLoXX31T/eHLbdBPLn7iLwvb656o67Vvsm2UVDMS0pX0QVt3z7l2hdv3+ml2px9mWFPDNPRBd8p7rs1kqSMPUflHOqvBhNuUuwXq5SXlK7CvHxlRlgXtjIjouV1WcW3n77YbGm9LM37suZyaxKinWNfOc8eAbBVtfPeNbApLVu21F9//WU1bc2aNWratKllVE1AQIBiYmIs7+/fv1+ZmRd272EnJyd5enpavariFmiSVJRXoPTth+R7VVur6b7d2yp1Y8W32kjduF++3cu079FO6dsOqSi/+HZxqZsi5NO9jXWbq9oqdWPx7XmSV+/Quqse1oZeky2vtC0HFPv1X9rQa7JUWKQTX67W+qsftWqTE5OkowuXatuQp6uk/4bLz1fu3gg5X9bJarLzZZ2Us/3MP7a6Xnu1fJ+crMTpzyj773XVHaXhivLylbnjgDy6tbea7tGtvTI27a1wnozNeyto30GZOw5I+QVW04ty8pQXmySZ7eXdr6vS/lc7c1qcx4Py7NbOarpHt/bK2HiGPG4qn0fP7u2Vsb18Hn2uv1ImRwclfVP+lnx2Lo5SYaF1PAWFlqvOaoL8jGxlRMZaXmkRx5QVm6zAUvs6k4O9/Ls0V+LGMz/0MnHjAat5JCnoqrZK3FD+9mUNB3dXdkKqTvxm/fwlO7NZdo7mclejFRUWylQDbuNXNpfp+44pOzZZAVeVzWULJVWQl9OSN+1X4FXWuQzs0UZJG86cfztHszya1FV2bHFB/HQuiwrL5LKgUCYbWz8LMrKVFRlreWXsi1ZObLLVMdzkYC/vLi2Vepa8pW6KKH8cL3WMPvu5wZmXa/Zxl1NdP+WcGgV25NXvtO7qyVrfa4rlJUkRTyzW7olvnHE5RrCl3JpOb99l1knVsH0mzo8trYMxX64ut+1mxyTpyMKl2jrkmarq8kVhy991pJJCjUtYHW29bY7yTxWDULvY0vZdlFegtK0H5do42KqNa+NgZUfHS5LsXB2L29r4uVFRXr7Stx+ST5n++pxl+07bGCGfMjn0KbN9p22qoM1V7ayWae/iVO44Xfq7TVFevtK3HpRL4xCrNi6N6yo7OuE8ell9bGm9LC146NVK23pQJ3cf+TfdA2BDbP8XCtR4Dz/8sFasWKE5c+YoIiJCixcv1muvvaZHHnnE0qZnz5567bXXtHnzZm3cuFH33nuvHBwcDIz6zKLe/FF17+il4NuvlmuTEIXPHiGnev46vvhXSVLY9NvVYsH9lvbHPvyfnEP9FT5ruFybhCj49qtVd2hPHV34Q8kyFy2Tb492qj9+oFzD66r++IHy6d5GUYuKhwAXZGQrY2+U1asgM0d5yenK2Ft89Ul+8slybQrz8pUTl6LMgzGqLdKXfCX3G/vL7Ya+MjesL+9J98m+TqBOfl2cT6/775LfrJJbyLhee7X8Zj2mlPlvKmfnbtn5+cjOz0emSozSqsni3/levoOvke+g3nIKr6e6M+6SQ90AJSwpvpd68OThqv/SREv7xCXL5RASqLozRsspvJ58B/WW7+Deilv0raWNa/um8urbRY6hQXK7pKUafzhTsjMp7q1vLG3sXJ3l0rKRXFo2kiQ5hgbJpWUjOdQ983M0bFnc29/Lb8g18hvcS87h9RTy5F1yDPFXwsfLJUl1pwxTg5cnWtonfLxcjvUCFPLEaDmH15Pf4F7yG9xbcW99V27Z/kN6K+V/61SQkl7uvdTfNqjOA7fJs2cnOdYLlFffyxU4ZqBSlv9TXV29KA68vVzNJ9yguv06y7NZPV0y/14VZOUq6ps1ljaXvHqvWk8bXDLPO8sVdFUbNbv/OnmEB6vZ/dcpsFsrHXh7ufXCTSY1GHKVjnzxZ/GXv1LyT2Ypfs1utZlxuwK6tJBraIAaDOquBrd207FlG6q1z9Xl4NvL1XTCQAX36yyP5vXU8ZXiXB4rlcuOC+5Ti1K5PPj2cgVc1Ubh46+Xe3hdhY+/XgHdWuvQopJnLLR6cqj8ujSXa/0A+XRorEvemSizh4uivige5ZV/MksJa3ar1RND5de1hVzrByh0cHeF3tZNMT/b/nNWohYtU8MHb1RAv0vk1jxULV8dp8KsHJ34puSikpYL7lfj6beXmudn+fZoqwbjb5BreF01GH+DfLu3UdSiZZY2R9/8SXXv6Kng23vItUmImsweLqd6/jp26tzA3tVJ4U/eKc/OTeQcGiDvri3V7qPJyktKV/yy4vuL58anljuOS1L2sQRlH42/GOn5V4zKbcHJLCX/vUvhT94p764t5Vw/QMGDr1Kd27orvoZu3xcqMzNLeyMOam9E8ajGY8djtTfioGJOxBkc2cVh1DpY0Tl4UV6+cuNSrc7BHQO85N6qgVwbFY+mc29RX+6tGhQ/kNyG2Op3HZO9nVq/O0ke7cK0+74FMtnZyTHAS44BXjI5VM2FebBdRm3fknT09R8UNLCr6t7ZUy4Ng1Rv9LXy79NJ0e//T5KUuf+4Mg/FqPnzY+TZobFcGgSp/r3XyfeqNor/2baOQ1Fv/qjgO3qpzqntu/HsEXKu56/ji4v70mj6UDVfUHJHjuMf/irnUH81njVCrk1CVOf2qxU8tKeiFi61tIle9JN8e7RT6KntO/TU9h19avuWpMT/bVKDiTfLt3dHOYcGyL/fpap3z/VKWFbyjJWo15cqcGBXBd/ZSy4N6yhkdF/59+mk4+//chEyc2GMXC8lyd7dRUE3XK7jS36vML6actwBYI3boKHadezYUV988YWeeOIJzZkzR8HBwZo9e7ZGjhxpafPiiy9q1KhR6t69u+rWratXXnlFmzZtMi7os4j7fq0cfDzUcNItcgry0cm9Udo+dK7lig+nQB85h5T8MJ19NF7bhs5Vk9kjVG/UtcqJTVbE9PcV/1PJaIS0jRHadc98hT02RGFTBisr8oR2jZ2vtFK3vUGxzF9Xys7LU153D5O9v6/yDkYq/sGpKjj1Q4S9v5/s6wRa2rvffJ1MZrN8H3tQvo89aJl+8odflDTruYse/8WS8uN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\n",
      "text/plain": [
       "<Figure size 2000x2000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the correlation matrix using heatmap for clear understanding\n",
    "\n",
    "plt.figure(figsize=(20,20))\n",
    "sns.heatmap(df.corr(), annot = True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <font color = 'yellow'>Feature Selection using SelectKBest Method<font/><a class = 'anchor' id = 'kbest_method'/>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        1.21\n",
       "1        1.21\n",
       "2        1.23\n",
       "3        1.21\n",
       "4        1.17\n",
       "         ... \n",
       "32681    1.22\n",
       "32682    1.17\n",
       "32683    1.20\n",
       "32684    1.23\n",
       "32685    1.20\n",
       "Name: Radiation, Length: 32686, dtype: float64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "target"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It works on the target label but instead we are passsing continuous float values to it. So, we need to convert our data to label form and there are two methods as follows:\n",
    "- using LabelEncoder\n",
    "- multiplying the data by 100 and converting it to int which can be treated as labels by the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# using LabelEncoder\n",
    "\n",
    "label_encoder = LabelEncoder()\n",
    "train_Y = label_encoder.fit_transform(target)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 9,  9, 11, ...,  8, 11,  8], dtype=int64)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_Y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# multiplying the data by 100 and converting it to int which can be treated as labels by the model\n",
    "\n",
    "target_cont = df['Radiation'].apply(lambda x : int(x*100))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        121\n",
       "1        121\n",
       "2        123\n",
       "3        121\n",
       "4        117\n",
       "        ... \n",
       "32681    122\n",
       "32682    117\n",
       "32683    120\n",
       "32684    123\n",
       "32685    120\n",
       "Name: Radiation, Length: 32686, dtype: int64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "target_cont"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# scaling input features\n",
    "\n",
    "scaled_input_features = MinMaxScaler().fit_transform(input_features)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# performing SelectKBest() method\n",
    "\n",
    "bestfeatures = SelectKBest(score_func = chi2, k = 10)\n",
    "fit = bestfeatures.fit(scaled_input_features, target_cont)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "scores = pd.DataFrame(fit.scores_)\n",
    "column = pd.DataFrame(input_features.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# contatinating data_features with the scores\n",
    "featureScores = pd.concat([column, scores], axis=1)\n",
    "\n",
    "#naming the dataframe columns\n",
    "featureScores.columns = ['Features', 'feature_imp'] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "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>Features</th>\n",
       "      <th>feature_imp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>sethour</td>\n",
       "      <td>12207.531454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Month</td>\n",
       "      <td>4684.579610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>riseminute</td>\n",
       "      <td>4015.062771</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>WindDirection(Degrees)</td>\n",
       "      <td>3271.827277</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Day</td>\n",
       "      <td>2841.926850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Minute</td>\n",
       "      <td>2702.449333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Second</td>\n",
       "      <td>2288.673032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>setminute</td>\n",
       "      <td>1863.712087</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Temperature</td>\n",
       "      <td>1651.685632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Humidity</td>\n",
       "      <td>1588.087433</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Speed</td>\n",
       "      <td>765.859779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Hour</td>\n",
       "      <td>691.185393</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Pressure</td>\n",
       "      <td>523.791060</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>risehour</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Features   feature_imp\n",
       "12                 sethour  12207.531454\n",
       "5                    Month   4684.579610\n",
       "11              riseminute   4015.062771\n",
       "3   WindDirection(Degrees)   3271.827277\n",
       "6                      Day   2841.926850\n",
       "8                   Minute   2702.449333\n",
       "9                   Second   2288.673032\n",
       "13               setminute   1863.712087\n",
       "0              Temperature   1651.685632\n",
       "2                 Humidity   1588.087433\n",
       "4                    Speed    765.859779\n",
       "7                     Hour    691.185393\n",
       "1                 Pressure    523.791060\n",
       "10                risehour           NaN"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# best features\n",
    "\n",
    "featureScores.sort_values(by = 'feature_imp', ascending=False, inplace=True)\n",
    "featureScores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualise the feature importance\n",
    "\n",
    "plt.figure(figsize = (12, 4))\n",
    "plt.bar(featureScores.Features, featureScores.feature_imp)\n",
    "plt.xticks(rotation = 50)\n",
    "plt.xlabel(\"Features\")\n",
    "plt.ylabel(\"Importance\")\n",
    "plt.title(\"Feature Importance using SelectKBest method\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <font color = 'green'>Feature Selection using Extra Tree Classifier<font/><a class = 'anchor' id = 'extra_tree'/>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "model = ExtraTreesClassifier(verbose = 2, n_estimators = 10)\n",
    "model.fit(scaled_input_features, target_cont)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "feature_importances = pd.DataFrame(model.feature_importances_, index = input_features.columns, columns = [\"feature_imp\"])\n",
    "feature_importances.sort_values(by = 'feature_imp', ascending=False, inplace = True)\n",
    "feature_importances"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.figure(figsize = (10, 6))\n",
    "plt.bar(feature_importances.index, feature_importances[\"feature_imp\"])\n",
    "plt.xticks(rotation = 50)\n",
    "plt.xlabel(\"Features\")\n",
    "plt.ylabel(\"Importance\")\n",
    "plt.title(\"Feature Importance using Extra Tree Classifier\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <font color = 'red'>Feature Engineering with BoxCox, Log, Min-Max and Standard transformation<font/><a class = 'anchor' id = 'feature_engg'/>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x800 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x800 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x800 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x800 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x800 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Looking for transformation\n",
    "\n",
    "features_to_transform = ['Temperature', 'Pressure', 'Humidity', 'Speed', 'WindDirection(Degrees)']\n",
    "\n",
    "for i in features_to_transform:\n",
    "    \n",
    "    fig, (ax1, ax2, ax3, ax4, ax5) = plt.subplots(5, 1, figsize=(12, 8))\n",
    "    \n",
    "    pd.DataFrame(input_features[i]).hist(ax = ax1, bins = 50)\n",
    "    pd.DataFrame((input_features[i]+1).transform(np.log)).hist(ax = ax2, bins = 50)\n",
    "    pd.DataFrame(stats.boxcox(input_features[i]+1)[0]).hist(ax = ax3, bins = 50)    \n",
    "    pd.DataFrame(StandardScaler().fit_transform(np.array(input_features[i]).reshape(-1, 1))).hist(ax = ax4, bins = 50)\n",
    "    pd.DataFrame(MinMaxScaler().fit_transform(np.array(input_features[i]).reshape(-1, 1))).hist(ax = ax5, bins = 50)\n",
    "    \n",
    "    ax1.set_ylabel('Normal')\n",
    "    ax2.set_ylabel('Log')\n",
    "    ax3.set_ylabel('Box Cox')\n",
    "    ax4.set_ylabel('Standard')\n",
    "    ax5.set_ylabel('MinMax')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "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>Temperature</th>\n",
       "      <th>Pressure</th>\n",
       "      <th>Humidity</th>\n",
       "      <th>WindDirection(Degrees)</th>\n",
       "      <th>Speed</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day</th>\n",
       "      <th>Hour</th>\n",
       "      <th>Minute</th>\n",
       "      <th>Second</th>\n",
       "      <th>risehour</th>\n",
       "      <th>riseminute</th>\n",
       "      <th>sethour</th>\n",
       "      <th>setminute</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>48</td>\n",
       "      <td>30.46</td>\n",
       "      <td>59</td>\n",
       "      <td>177.39</td>\n",
       "      <td>5.62</td>\n",
       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>23</td>\n",
       "      <td>55</td>\n",
       "      <td>26</td>\n",
       "      <td>6</td>\n",
       "      <td>13</td>\n",
       "      <td>18</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>48</td>\n",
       "      <td>30.46</td>\n",
       "      <td>58</td>\n",
       "      <td>176.78</td>\n",
       "      <td>3.37</td>\n",
       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>23</td>\n",
       "      <td>50</td>\n",
       "      <td>23</td>\n",
       "      <td>6</td>\n",
       "      <td>13</td>\n",
       "      <td>18</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>48</td>\n",
       "      <td>30.46</td>\n",
       "      <td>57</td>\n",
       "      <td>158.75</td>\n",
       "      <td>3.37</td>\n",
       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>23</td>\n",
       "      <td>45</td>\n",
       "      <td>26</td>\n",
       "      <td>6</td>\n",
       "      <td>13</td>\n",
       "      <td>18</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>48</td>\n",
       "      <td>30.46</td>\n",
       "      <td>60</td>\n",
       "      <td>137.71</td>\n",
       "      <td>3.37</td>\n",
       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>23</td>\n",
       "      <td>40</td>\n",
       "      <td>21</td>\n",
       "      <td>6</td>\n",
       "      <td>13</td>\n",
       "      <td>18</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>48</td>\n",
       "      <td>30.46</td>\n",
       "      <td>62</td>\n",
       "      <td>104.95</td>\n",
       "      <td>5.62</td>\n",
       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>23</td>\n",
       "      <td>35</td>\n",
       "      <td>24</td>\n",
       "      <td>6</td>\n",
       "      <td>13</td>\n",
       "      <td>18</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Temperature  Pressure  Humidity  WindDirection(Degrees)  Speed  Month  Day  \\\n",
       "0           48     30.46        59                  177.39   5.62      9   29   \n",
       "1           48     30.46        58                  176.78   3.37      9   29   \n",
       "2           48     30.46        57                  158.75   3.37      9   29   \n",
       "3           48     30.46        60                  137.71   3.37      9   29   \n",
       "4           48     30.46        62                  104.95   5.62      9   29   \n",
       "\n",
       "   Hour  Minute  Second  risehour  riseminute  sethour  setminute  \n",
       "0    23      55      26         6          13       18         13  \n",
       "1    23      50      23         6          13       18         13  \n",
       "2    23      45      26         6          13       18         13  \n",
       "3    23      40      21         6          13       18         13  \n",
       "4    23      35      24         6          13       18         13  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "input_features.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# set the transformations required\n",
    "\n",
    "transform = {'Temperature' : (input_features['Temperature']+1).transform(np.log), \n",
    "             'Pressure': stats.boxcox(input_features['Pressure']+1)[0], \n",
    "             'Humidity' : stats.boxcox(input_features['Humidity']+1)[0], \n",
    "             'Speed' : (input_features['Speed']+1).transform(np.log), \n",
    "             'WindDirection(Degrees)' : MinMaxScaler().fit_transform(\n",
    "                 np.array(input_features['WindDirection(Degrees)']).reshape(-1, 1))}\n",
    "\n",
    "for i in transform:\n",
    "    input_features[i] = transform[i]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "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>Temperature</th>\n",
       "      <th>Pressure</th>\n",
       "      <th>Humidity</th>\n",
       "      <th>WindDirection(Degrees)</th>\n",
       "      <th>Speed</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day</th>\n",
       "      <th>Hour</th>\n",
       "      <th>Minute</th>\n",
       "      <th>Second</th>\n",
       "      <th>risehour</th>\n",
       "      <th>riseminute</th>\n",
       "      <th>sethour</th>\n",
       "      <th>setminute</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3.89182</td>\n",
       "      <td>5.044903e+152</td>\n",
       "      <td>1139.358665</td>\n",
       "      <td>0.492692</td>\n",
       "      <td>1.890095</td>\n",
       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>23</td>\n",
       "      <td>55</td>\n",
       "      <td>26</td>\n",
       "      <td>6</td>\n",
       "      <td>13</td>\n",
       "      <td>18</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3.89182</td>\n",
       "      <td>5.044903e+152</td>\n",
       "      <td>1104.046980</td>\n",
       "      <td>0.490996</td>\n",
       "      <td>1.474763</td>\n",
       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>23</td>\n",
       "      <td>50</td>\n",
       "      <td>23</td>\n",
       "      <td>6</td>\n",
       "      <td>13</td>\n",
       "      <td>18</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.89182</td>\n",
       "      <td>5.044903e+152</td>\n",
       "      <td>1069.253545</td>\n",
       "      <td>0.440894</td>\n",
       "      <td>1.474763</td>\n",
       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>23</td>\n",
       "      <td>45</td>\n",
       "      <td>26</td>\n",
       "      <td>6</td>\n",
       "      <td>13</td>\n",
       "      <td>18</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3.89182</td>\n",
       "      <td>5.044903e+152</td>\n",
       "      <td>1175.187489</td>\n",
       "      <td>0.382426</td>\n",
       "      <td>1.474763</td>\n",
       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>23</td>\n",
       "      <td>40</td>\n",
       "      <td>21</td>\n",
       "      <td>6</td>\n",
       "      <td>13</td>\n",
       "      <td>18</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3.89182</td>\n",
       "      <td>5.044903e+152</td>\n",
       "      <td>1248.392213</td>\n",
       "      <td>0.291391</td>\n",
       "      <td>1.890095</td>\n",
       "      <td>9</td>\n",
       "      <td>29</td>\n",
       "      <td>23</td>\n",
       "      <td>35</td>\n",
       "      <td>24</td>\n",
       "      <td>6</td>\n",
       "      <td>13</td>\n",
       "      <td>18</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Temperature       Pressure     Humidity  WindDirection(Degrees)     Speed  \\\n",
       "0      3.89182  5.044903e+152  1139.358665                0.492692  1.890095   \n",
       "1      3.89182  5.044903e+152  1104.046980                0.490996  1.474763   \n",
       "2      3.89182  5.044903e+152  1069.253545                0.440894  1.474763   \n",
       "3      3.89182  5.044903e+152  1175.187489                0.382426  1.474763   \n",
       "4      3.89182  5.044903e+152  1248.392213                0.291391  1.890095   \n",
       "\n",
       "   Month  Day  Hour  Minute  Second  risehour  riseminute  sethour  setminute  \n",
       "0      9   29    23      55      26         6          13       18         13  \n",
       "1      9   29    23      50      23         6          13       18         13  \n",
       "2      9   29    23      45      26         6          13       18         13  \n",
       "3      9   29    23      40      21         6          13       18         13  \n",
       "4      9   29    23      35      24         6          13       18         13  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "input_features.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <font color = 'pink'>Preparing data - Standardisation and Splitting<font/><a class = 'anchor' id = 'data_prep'/>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "xtrain, xtest, ytrain, ytest = train_test_split(input_features, target, test_size=0.2, random_state=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "scaler = StandardScaler()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "xtrain = scaler.fit_transform(xtrain)\n",
    "xtest = scaler.transform(xtest)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((26148, 14), (6538, 14))"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xtrain.shape, xtest.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <font color = 'yellow'>Prediction with XGBoost<font/><a class = 'anchor' id = 'xgboost'/>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "params = {\n",
    "    'learning_rate': 0.1,\n",
    "    'max_depth': 8}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = XGBRegressor(**params)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "XGBRegressor(base_score=0.5, booster='gbtree', callbacks=None,\n",
       "             colsample_bylevel=1, colsample_bynode=1, colsample_bytree=1,\n",
       "             early_stopping_rounds=None, enable_categorical=False,\n",
       "             eval_metric=None, feature_types=None, gamma=0, gpu_id=-1,\n",
       "             grow_policy='depthwise', importance_type=None,\n",
       "             interaction_constraints='', learning_rate=0.1, max_bin=256,\n",
       "             max_cat_threshold=64, max_cat_to_onehot=4, max_delta_step=0,\n",
       "             max_depth=8, max_leaves=0, min_child_weight=1, missing=nan,\n",
       "             monotone_constraints='()', n_estimators=100, n_jobs=0,\n",
       "             num_parallel_tree=1, predictor='auto', random_state=0, ...)"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# train the model\n",
    "\n",
    "model.fit(xtrain, ytrain)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred = model.predict(xtest)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Testing performance ~\n",
      "RMSE: 81.45\n",
      "R2: 0.93\n"
     ]
    }
   ],
   "source": [
    "rmse = np.sqrt(mean_squared_error(ytest, y_pred))\n",
    "r2 = r2_score(ytest, y_pred)\n",
    "\n",
    "print(\"Testing performance ~\")\n",
    "\n",
    "print(\"RMSE: {:.2f}\".format(rmse))\n",
    "print(\"R2: {:.2f}\".format(r2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <font color = 'cyan'>Prediction with MultiLayer Perceptron<font/><a class = 'anchor' id = 'perceptron'/>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential\"\n",
      "_________________________________________________________________\n",
      " Layer (type)                Output Shape              Param #   \n",
      "=================================================================\n",
      " dense (Dense)               (None, 128)               1920      \n",
      "                                                                 \n",
      " dropout (Dropout)           (None, 128)               0         \n",
      "                                                                 \n",
      " dense_1 (Dense)             (None, 64)                8256      \n",
      "                                                                 \n",
      " dropout_1 (Dropout)         (None, 64)                0         \n",
      "                                                                 \n",
      " dense_2 (Dense)             (None, 32)                2080      \n",
      "                                                                 \n",
      " dropout_2 (Dropout)         (None, 32)                0         \n",
      "                                                                 \n",
      " dense_3 (Dense)             (None, 1)                 33        \n",
      "                                                                 \n",
      "=================================================================\n",
      "Total params: 12,289\n",
      "Trainable params: 12,289\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "model = None\n",
    "model = Sequential()\n",
    "    \n",
    "model.add(Dense(128, activation='relu', input_dim=14))\n",
    "model.add(Dropout(0.33))\n",
    "    \n",
    "model.add(Dense(64, activation='relu'))\n",
    "model.add(Dropout(0.33))\n",
    "\n",
    "model.add(Dense(32, activation='relu'))\n",
    "model.add(Dropout(0.33))\n",
    "\n",
    "model.add(Dense(1, activation='linear'))\n",
    "    \n",
    "model.compile(metrics='mse', loss='mae', optimizer=Adam(learning_rate=0.001))\n",
    "print(model.summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/50\n",
      "736/736 [==============================] - 3s 3ms/step - loss: 121.2143 - mse: 54720.1602 - val_loss: 77.9992 - val_mse: 23352.9414\n",
      "Epoch 2/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 85.5568 - mse: 27472.1426 - val_loss: 69.7563 - val_mse: 18878.2988\n",
      "Epoch 3/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 81.8897 - mse: 25478.7441 - val_loss: 65.8575 - val_mse: 16900.4199\n",
      "Epoch 4/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 78.2825 - mse: 23696.9160 - val_loss: 63.6074 - val_mse: 16116.0869\n",
      "Epoch 5/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 76.4330 - mse: 22594.1367 - val_loss: 65.5880 - val_mse: 16850.6016\n",
      "Epoch 6/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 73.9627 - mse: 21334.0391 - val_loss: 58.7555 - val_mse: 14217.9258\n",
      "Epoch 7/50\n",
      "736/736 [==============================] - 2s 3ms/step - loss: 72.2974 - mse: 20547.8184 - val_loss: 56.0419 - val_mse: 13251.4863\n",
      "Epoch 8/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 70.8947 - mse: 19744.6328 - val_loss: 56.0517 - val_mse: 13277.9775\n",
      "Epoch 9/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 70.6903 - mse: 19624.0723 - val_loss: 53.5533 - val_mse: 12365.9355\n",
      "Epoch 10/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 69.2477 - mse: 19123.9219 - val_loss: 51.7638 - val_mse: 11619.1230\n",
      "Epoch 11/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 67.8168 - mse: 18320.9766 - val_loss: 54.8172 - val_mse: 12751.3359\n",
      "Epoch 12/50\n",
      "736/736 [==============================] - 2s 3ms/step - loss: 67.0946 - mse: 17912.3301 - val_loss: 50.7062 - val_mse: 11569.1631\n",
      "Epoch 13/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 66.6194 - mse: 17847.1211 - val_loss: 48.6653 - val_mse: 10879.1953\n",
      "Epoch 14/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 66.4846 - mse: 17898.5547 - val_loss: 49.8315 - val_mse: 11319.6719\n",
      "Epoch 15/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 66.4791 - mse: 17925.1543 - val_loss: 49.6373 - val_mse: 11259.8066\n",
      "Epoch 16/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 65.1458 - mse: 17238.2480 - val_loss: 50.4680 - val_mse: 11696.2314\n",
      "Epoch 17/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 65.5086 - mse: 17337.3398 - val_loss: 47.9840 - val_mse: 10845.4443\n",
      "Epoch 18/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 65.1542 - mse: 17200.8398 - val_loss: 48.0480 - val_mse: 10696.6611\n",
      "Epoch 19/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 65.1956 - mse: 17370.8047 - val_loss: 48.3991 - val_mse: 10931.3311\n",
      "Epoch 20/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 64.1069 - mse: 16940.1406 - val_loss: 49.7123 - val_mse: 11034.4795\n",
      "Epoch 21/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 64.2270 - mse: 17087.8242 - val_loss: 51.0479 - val_mse: 11324.3008\n",
      "Epoch 22/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 63.7719 - mse: 16695.5000 - val_loss: 48.3763 - val_mse: 10898.0527\n",
      "Epoch 23/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 63.2434 - mse: 16733.4941 - val_loss: 48.9740 - val_mse: 11074.5205\n",
      "Epoch 24/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 63.0742 - mse: 16402.9492 - val_loss: 48.0850 - val_mse: 11000.6670\n",
      "Epoch 25/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 63.6125 - mse: 16897.7129 - val_loss: 46.3944 - val_mse: 10443.4395\n",
      "Epoch 26/50\n",
      "736/736 [==============================] - 2s 3ms/step - loss: 62.3684 - mse: 16148.5713 - val_loss: 49.4222 - val_mse: 11529.3828\n",
      "Epoch 27/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 62.7308 - mse: 16296.7090 - val_loss: 47.9482 - val_mse: 10945.4062\n",
      "Epoch 28/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 62.6190 - mse: 16527.7949 - val_loss: 45.3593 - val_mse: 10384.5273\n",
      "Epoch 29/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 61.3250 - mse: 15915.7197 - val_loss: 46.2909 - val_mse: 10711.5273\n",
      "Epoch 30/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 61.4905 - mse: 15924.5068 - val_loss: 44.4366 - val_mse: 9851.5508\n",
      "Epoch 31/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 61.8364 - mse: 16121.0156 - val_loss: 44.9051 - val_mse: 10134.0352\n",
      "Epoch 32/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 60.7931 - mse: 15531.7910 - val_loss: 48.4710 - val_mse: 10880.1602\n",
      "Epoch 33/50\n",
      "736/736 [==============================] - 2s 3ms/step - loss: 60.6753 - mse: 15590.7539 - val_loss: 43.9160 - val_mse: 9830.2441\n",
      "Epoch 34/50\n",
      "736/736 [==============================] - 2s 3ms/step - loss: 61.1870 - mse: 15971.5752 - val_loss: 44.1572 - val_mse: 9748.6045\n",
      "Epoch 35/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 60.6887 - mse: 15812.7051 - val_loss: 46.4281 - val_mse: 10189.9863\n",
      "Epoch 36/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 60.8478 - mse: 15729.7402 - val_loss: 44.0361 - val_mse: 10070.7920\n",
      "Epoch 37/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 60.3991 - mse: 15533.9131 - val_loss: 48.1886 - val_mse: 10928.3672\n",
      "Epoch 38/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 59.9898 - mse: 15453.1113 - val_loss: 47.3518 - val_mse: 10631.0918\n",
      "Epoch 39/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 60.0870 - mse: 15564.5537 - val_loss: 43.8503 - val_mse: 9785.2236\n",
      "Epoch 40/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 60.7968 - mse: 15776.9971 - val_loss: 48.1902 - val_mse: 11075.8320\n",
      "Epoch 41/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 60.2016 - mse: 15429.5088 - val_loss: 44.3404 - val_mse: 9923.3770\n",
      "Epoch 42/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 59.7223 - mse: 15303.3154 - val_loss: 43.6503 - val_mse: 9817.0850\n",
      "Epoch 43/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 59.9602 - mse: 15449.5098 - val_loss: 44.0751 - val_mse: 9713.6240\n",
      "Epoch 44/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 59.5368 - mse: 15173.0215 - val_loss: 47.8370 - val_mse: 10813.2432\n",
      "Epoch 45/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 59.9774 - mse: 15438.9072 - val_loss: 44.9831 - val_mse: 10161.8252\n",
      "Epoch 46/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 59.2922 - mse: 15307.6748 - val_loss: 43.6202 - val_mse: 9983.7764\n",
      "Epoch 47/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 59.3783 - mse: 15219.5049 - val_loss: 44.2049 - val_mse: 9998.5742\n",
      "Epoch 48/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 59.5154 - mse: 15285.2754 - val_loss: 43.4484 - val_mse: 9773.3262\n",
      "Epoch 49/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 58.3597 - mse: 14844.2412 - val_loss: 43.4161 - val_mse: 9703.8848\n",
      "Epoch 50/50\n",
      "736/736 [==============================] - 2s 2ms/step - loss: 58.7561 - mse: 14862.4990 - val_loss: 43.5988 - val_mse: 9711.0049\n"
     ]
    }
   ],
   "source": [
    "history = model.fit(xtrain, ytrain, validation_split=0.1, epochs=50, batch_size=32)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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09PRmrb2pxEXWtrQ76B4PAAAAAC1CQIT26upqXXLJJfJ4PHr++ecPer5hGDKZTAc8fv/998vhcHi3rVu3NmW5zYaWdgAAAABoWfw+tFdXV2v06NHKycnRrFmzvK3skpSamiqXy6WioqIGrykoKFBKSsoBr2mz2RQTE9NgCwT1Y9pLqqrl9hg+rgYAAAAA0Nz8OrTXB/bs7GzNnj1bCQkJDY737t1boaGhDSasy8vL08qVK9WvX7+jXW6zs9e1tBuGVMJkdAAAAAAQ9Hw6e3xZWZnWr1/vfZ6Tk6Ply5crPj5eaWlpuvDCC/XLL7/o888/l9vt9o5Tj4+Pl9Vqld1u1zXXXKM777xTCQkJio+P11133aXu3bt7Z5MPJtYQs6JsISpz1qi4sto7xh0AAAAAEJx8GtqXLl2qIUOGeJ9PnDhRknTllVdq0qRJ+uyzzyRJxx13XIPXzZkzR4MHD5YkPfXUUwoJCdHo0aNVWVmp0047TW+88YYsFstReQ9HW2xEqMqcNSqqcClTkb4uBwAAAADQjHwa2gcPHizDOPDY7L86Vi8sLEzPPfecnnvuuaYszW/FRoQqt6hSDiajAwAAAICg59dj2rGvuLrJ6IpY9g0AAAAAgh6hPcDUT0ZXTEs7AAAAAAQ9QnuAqW9pL6alHQAAAACCHqE9wMRG1La0F9HSDgAAAABBj9AeYGLrW9pZpx0AAAAAgh6hPcDEese00z0eAAAAAIIdoT3AxEUyER0AAAAAtBSE9gBjD2fJNwAAAABoKQjtASaubiI6By3tAAAAABD0CO0Bpn4iulJnjardHh9XAwAAAABoToT2AGOvm4hOkhzMIA8AAAAAQY3QHmAsZpNiwkIkMYM8AAAAAAQ7QnsAiousW6udce0AAAAAENQI7QGoflx7EaEdAAAAAIIaoT0AxYbXr9VO93gAAAAACGaE9gBUv+wb3eMBAAAAILgR2gPQnu7xtLQDAAAAQDAjtAeg2PqWdpZ8AwAAAICgRmgPQIxpBwAAAICWgdAegFjyDQAAAABaBkJ7ALLXtbSz5BsAAAAABDdCewCKq5uIzkH3eAAAAAAIaoT2AFQ/ER0t7QAAAAAQ3AjtAah+ybfKareqqt0+rgYAAAAA0FwI7QEo2hYis6n2awfLvgEAAABA0CK0ByCz2eRtbWcGeQAAAAAIXoT2ALVnXDuT0QEAAABAsCK0B6jYumXfaGkHAAAAgOBFaA9Qcd7u8bS0AwAAAECwIrQHKDvLvgEAAABA0CO0ByhvS3slLe0AAAAAEKwI7QHKO6a9nJZ2AAAAAAhWhPYAFRtJSzsAAAAABDtCe4Cqb2lnTDsAAAAABC9Ce4CqH9PuILQDAAAAQNAitAeoWO/s8XSPBwAAAIBgRWgPUPWhvbiyWoZh+LgaAAAAAEBzILQHqNi67vGuGo8qq90+rgYAAAAA0BwI7QEq0mpRqMUkSSpmXDsAAAAABCVCe4AymUze1nbGtQMAAABAcCK0B7D6Zd+YQR4AAAAAghOhPYDFeVvaCe0AAAAAEIwI7QHMzrJvAAAAABDUCO0BLK4utDsqaWkHAAAAgGBEaA9g3onoymlpBwAAAIBgRGgPYLF1Le3FtLQDAAAAQFAitAew2PDalvZixrQDAAAAQFAitAew+jHtxcweDwAAAABBidAewJg9HgAAAACCG6E9gNWv087s8QAAAAAQnAjtASx2r+7xhmH4uBoAAAAAQFMjtAew+pb2Go+hMmeNj6sBAAAAADQ1QnsACwu1KCy09lfIZHQAAAAAEHwI7QFuz7JvhHYAAAAACDaE9gAXywzyAAAAABC0CO0BjtAOAAAAAMHLp6F9/vz5Ouuss5SWliaTyaRPPvmkwfGPPvpII0aMUGJiokwmk5YvX77PNZxOp2699VYlJiYqMjJSZ599tnJzc4/OG/ADLPsGAAAAAMHLp6G9vLxcPXv21PTp0w94vH///nrssccOeI0JEybo448/1rvvvqsFCxaorKxMZ555ptxud3OV7Ve8Le3lhHYAAAAACDYhvvzmI0eO1MiRIw94/PLLL5ckbdq0ab/HHQ6HXn31Vb399tsaOnSoJGnmzJlKT0/X7NmzNWLEiCav2d/E1rW0F1fSPR4AAAAAgk1Aj2lftmyZqqurNXz4cO++tLQ0devWTQsXLjzg65xOp0pKShpsgSo2vLalndnjAQAAACD4BHRoz8/Pl9VqVVxcXIP9KSkpys/PP+Drpk6dKrvd7t3S09Obu9RmUz+mvZiJ6AAAAAAg6AR0aD8QwzBkMpkOePz++++Xw+Hwblu3bj2K1TUtu3f2eFraAQAAACDYBHRoT01NlcvlUlFRUYP9BQUFSklJOeDrbDabYmJiGmyBitnjAQAAACB4BXRo7927t0JDQzVr1izvvry8PK1cuVL9+vXzYWVHD+u0AwAAAEDw8uns8WVlZVq/fr33eU5OjpYvX674+Hi1bdtWu3fv1pYtW7R9+3ZJ0tq1ayXVtrCnpqbKbrfrmmuu0Z133qmEhATFx8frrrvuUvfu3b2zyQe7+tDuqKyWx2PIbD7wsAAAAAAAQGDxaUv70qVL1atXL/Xq1UuSNHHiRPXq1Uv/+Mc/JEmfffaZevXqpVGjRkmSLrnkEvXq1Usvvvii9xpPPfWUzj33XI0ePVr9+/dXRESE/ve//8lisRz9N+QDseG13eMNQyqpoos8AAAAAAQTk2EYhq+L8LWSkhLZ7XY5HI6AHN9+7D++VrnLrbl3DVa7xEhflwMAAAAAOIhDzaEBPaYdtWLrJqNjXDsAAAAABBdCexCoH9dezLJvAAAAABBUCO1BoH7Zt+JKWtoBAAAAIJgQ2oOAvX7Zt3Ja2gEAAAAgmBDag0Bcfff4SkI7AAAAAAQTQnsQqF/2rZiJ6AAAAAAgqBDagwAT0QEAAABAcCK0BwGWfAMAAACA4ERoDwL1Y9odjGkHAAAAgKBCaA8C9d3jaWkHAAAAgOBCaA8C9d3jGdMOAAAAAMGF0B4EYsNrW9pLq2pU4/b4uBoAAAAAQFMhtAcBe11olxjXDgAAAADBhNAeBEIsZsWEhUiSiugiDwAAAABBg9AeJPaMa2cyOgAAAAAIFoT2IFG/7BuT0QEAAABA8CC0Bwl7XUs7y74BAAAAQPAgtAeJ+pZ2JqIDAAAAgOBBaA8S9cu+0dIOAAAAAMGD0B4k9kxER0s7AAAAAAQLQnuQiGUiOgAAAAAIOoT2IBFX39JeSfd4AAAAAAgWhPYgYa9raS8qp6UdAAAAAIIFoT1I1Le0M3s8AAAAAAQPQnuQYPZ4AAAAAAg+hPYgUd/SXuFyy1nj9nE1AAAAAICmQGgPEtFhITKbar92MIM8AAAAAAQFQnuQMJtNsnu7yBPaAQAAACAYENqDiHfZN8a1AwAAAEBQILQHEe+yb7S0AwAAAEBQILQHkT3LvtHSDgAAAADBgNAeRGIZ0w4AAAAAQYXQHkRivWPaCe0AAAAAEAwI7UEktm5MOxPRAQAAAEBwILQHkThvaKelHQAAAACCAaE9iNjruscX0dIOAAAAAEGB0B5E6lvaHZW0tAMAAABAMCC0B5HYcFraAQAAACCYENqDSCxj2gEAAAAgqBDag0hcZG1Lu7PGo0qX28fVAAAAAACOFKE9iERaLQoxmyTRRR4AAAAAggGhPYiYTCbF1s0gTxd5AAAAAAh8hPYgs2dcOy3tAAAAABDoCO1Bpn7Zt2KWfQMAAACAgEdoDzJ2ln0DAAAAgKBBaA8ycSz7BgAAAABBg9AeZBjTDgAAAADBg9AeZJg9HgAAAACCB6E9yNS3tBcR2gEAAAAg4BHag0xcXUu7o5Lu8QAAAAAQ6AjtQSY2nJZ2AAAAAAgWhPYgw5h2AAAAAAgehPYgs/fs8YZh+LgaAAAAAMCRILQHmfox7TUeQ2XOGh9XAwAAAAA4EoT2IBNutcgWUvtrpYs8AAAAAAQ2QnsQ2tNFntAOAAAAAIHMp6F9/vz5Ouuss5SWliaTyaRPPvmkwXHDMDRp0iSlpaUpPDxcgwcP1qpVqxqc43Q6deuttyoxMVGRkZE6++yzlZubexTfhf+p7yJfzLJvAAAAABDQfBray8vL1bNnT02fPn2/x6dNm6Ynn3xS06dP15IlS5Samqphw4aptLTUe86ECRP08ccf691339WCBQtUVlamM888U263+2i9Db9jZ9k3AAAAAAgKIb785iNHjtTIkSP3e8wwDD399NN68MEHdf7550uS3nzzTaWkpOidd97RDTfcIIfDoVdffVVvv/22hg4dKkmaOXOm0tPTNXv2bI0YMWK/13Y6nXI6nd7nJSUlTfzOfKu+pd1RQUs7AAAAAAQyvx3TnpOTo/z8fA0fPty7z2azadCgQVq4cKEkadmyZaqurm5wTlpamrp16+Y9Z3+mTp0qu93u3dLT05vvjfhA/Zh2WtoBAAAAILD5bWjPz8+XJKWkpDTYn5KS4j2Wn58vq9WquLi4A56zP/fff78cDod327p1axNX71ux9WPaCe0AAAAAENB82j3+UJhMpgbPDcPYZ9+fHewcm80mm83WJPX5oz2zx9M9HgAAAAACmd+2tKempkrSPi3mBQUF3tb31NRUuVwuFRUVHfCcliiuPrRX0tIOAAAAAIHMb0N7ZmamUlNTNWvWLO8+l8ulefPmqV+/fpKk3r17KzQ0tME5eXl5WrlypfeclsgeXts9voiWdgAAAAAIaD7tHl9WVqb169d7n+fk5Gj58uWKj49X27ZtNWHCBE2ZMkVZWVnKysrSlClTFBERobFjx0qS7Ha7rrnmGt15551KSEhQfHy87rrrLnXv3t07m3xLVN/S7mBMOwAAAAAENJ+G9qVLl2rIkCHe5xMnTpQkXXnllXrjjTd0zz33qLKyUuPHj1dRUZH69Omjb7/9VtHR0d7XPPXUUwoJCdHo0aNVWVmp0047TW+88YYsFstRfz/+on4iOlraAQAAACCwmQzDMHxdhK+VlJTIbrfL4XAoJibG1+UcsYKSKp005TuZTdL6R8+Q2fzXE/cBAAAAAI6uQ82hfjumHYfPXtc93mNIpVU1Pq4GAAAAAHC4CO1ByBZiUYS1dngAXeQBAAAAIHAR2oNUXN24dpZ9AwAAAIDARWgPUvbw2i7ytLQDAAAAQOAitAepuEiWfQMAAACAQEdoD1Kx4Sz7BgAAAACBjtAepGLrZpAvpqUdAAAAAAIWoT1I7QnttLQDAAAAQKAitAcpZo8HAAAAgMBHaA9Se2aPJ7QDAAAAQKAitAep+pZ2B93jAQAAACBgEdqDVP2YdlraAQAAACBwEdqDVGwES74BAAAAQKAjtAepuLqW9tKqGtW4PT6uBgAAAABwOAjtQap+IjpJcjCDPAAAAAAEJEJ7kAqxmBUdFiKJZd8AAAAAIFAR2oNY/WR0xYxrBwAAAICARGgPYvXLvhUzgzwAAAAABCRCexCrH9fOsm8AAAAAEJgI7UFsT0s73eMBAAAAIBAR2oPYnjHttLQDAAAAQCAitAex2PqW9kpa2gEAAAAgEBHag1gsY9oBAAAAIKAR2oNYXGRtaHcQ2gEAAAAgIBHag1hseG33+CImogMAAACAgERoD2JMRAcAAAAAgY3QHsRY8g0AAAAAAhuhPYjVt7SXu9xy1Xh8XA0AAAAAoLEI7UEsJixUJlPt1yz7BgAAAACBh9AexMxmk+zhjGsHAAAAgEBFaA9ye8a1E9oBAAAAINAQ2oNcfUs7y74BAAAAQOAhtAe5uLrJ6By0tAMAAABAwCG0B7nYuu7xtLQDAAAAQOAhtAe5+mXfiitpaQcAAACAQENoD3Kx4fUT0dHSDgAAAACBhtAe5OIiWfINAAAAAAIVoT3IMXs8AAAAAAQuQnuQY512AAAAAAhchPYg552IjtAOAAAAAAGH0B7k4ljyDQAAAAACFqE9yNW3tDtrPKqqdvu4GgAAAABAYxDag1yULUQhZpMkWtsBAAAAINAQ2oOcyWRiXDsAAAAABChCewvAsm8AAAAAEJgI7S1A/WR0DlraAQAAACCgENpbgPru8UWEdgAAAAAIKIT2FiC2rqW9uJLu8QAAAAAQSAjtLUBsOBPRAQAAAEAgIrS3AHGRdS3tTEQHAAAAAAGF0N4C7Jk9npZ2AAAAAAgkhPYWoH72eFraAQAAACCwHFZof/PNN/XFF194n99zzz2KjY1Vv379tHnz5iYrDk2jfvZ4xrQDAAAAQGA5rNA+ZcoUhYeHS5IWLVqk6dOna9q0aUpMTNQdd9zRpAXiyLHkGwAAAAAEppDDedHWrVvVoUMHSdInn3yiCy+8UNdff7369++vwYMHN2V9aAL13eMdlS4ZhiGTyeTjigAAAAAAh+KwWtqjoqK0a9cuSdK3336roUOHSpLCwsJUWVnZdNVJKi0t1YQJE5SRkaHw8HD169dPS5Ys8R43DEOTJk1SWlqawsPDNXjwYK1atapJawh09S3t1W5D5S63j6sBAAAAAByqwwrtw4YN07XXXqtrr71W69at06hRoyRJq1atUrt27ZqyPl177bWaNWuW3n77ba1YsULDhw/X0KFDtW3bNknStGnT9OSTT2r69OlasmSJUlNTNWzYMJWWljZpHYEsPNQia0jtr5rJ6AAAAAAgcBxWaJ8xY4b69u2rnTt36sMPP1RCQoIkadmyZRozZkyTFVdZWakPP/xQ06ZN0ymnnKIOHTpo0qRJyszM1AsvvCDDMPT000/rwQcf1Pnnn69u3brpzTffVEVFhd55550mqyPQmUwmxYYzGR0AAAAABJrDGtMeGxur6dOn77N/8uTJR1zQ3mpqauR2uxUWFtZgf3h4uBYsWKCcnBzl5+dr+PDh3mM2m02DBg3SwoULdcMNN+z3uk6nU06n0/u8pKSkSev2R3ERVhWUOgntAAAAABBADqul/euvv9aCBQu8z2fMmKHjjjtOY8eOVVFRUZMVFx0drb59++rhhx/W9u3b5Xa7NXPmTP3000/Ky8tTfn6+JCklJaXB61JSUrzH9mfq1Kmy2+3eLT09vclq9ld27wzydI8HAAAAgEBxWKH97rvv9rZOr1ixQnfeeafOOOMMbdy4URMnTmzSAt9++20ZhqHWrVvLZrPp2Wef1dixY2WxWLzn/Hk29IPNkH7//ffL4XB4t61btzZpzf4orn6t9kpa2gEAAAAgUBxW9/icnBx17dpVkvThhx/qzDPP1JQpU/TLL7/ojDPOaNIC27dvr3nz5qm8vFwlJSVq1aqVLr74YmVmZio1NVWSlJ+fr1atWnlfU1BQsE/r+95sNptsNluT1unvYsNrl30rLqelHQAAAAACxWG1tFutVlVUVEiSZs+e7R1THh8f32zjwyMjI9WqVSsVFRXpm2++0TnnnOMN7rNmzfKe53K5NG/ePPXr169Z6ghUsZG0tAMAAABAoDmslvYBAwZo4sSJ6t+/v37++We99957kqR169apTZs2TVrgN998I8Mw1KlTJ61fv1533323OnXqpKuuukomk0kTJkzQlClTlJWVpaysLE2ZMkUREREaO3Zsk9YR6Opb2hnTDgAAAACB47BC+/Tp0zV+/Hh98MEHeuGFF9S6dWtJ0ldffaXTTz+9SQt0OBy6//77lZubq/j4eF1wwQV69NFHFRpa23J8zz33qLKyUuPHj1dRUZH69Omjb7/9VtHR0U1aR6Dzjmln9ngAAAAACBgmwzAMXxfhayUlJbLb7XI4HIqJifF1Oc3i65V5unHmLzq+baw+Gt/f1+UAAAAAQIt2qDn0sFraJcntduuTTz7RmjVrZDKZ1KVLF51zzjkNZnWH/4iNqJuIjpZ2AAAAAAgYhxXa169frzPOOEPbtm1Tp06dZBiG1q1bp/T0dH3xxRdq3759U9eJIxRXH9qZiA4AAAAAAsZhzR5/2223qX379tq6dat++eUX/frrr9qyZYsyMzN12223NXWNaAKx3jHtLnk8LX5EBAAAAAAEhMNqaZ83b54WL16s+Ph4776EhAQ99thj6t+f8dL+yB5eG9o9hlTqrPE+BwAAAAD4r8NqabfZbCotLd1nf1lZmaxW6xEXhaYXFmpReGjtfAPFLPsGAAAAAAHhsEL7mWeeqeuvv14//fSTDMOQYRhavHixbrzxRp199tlNXSOaCMu+AQAAAEBgOazQ/uyzz6p9+/bq27evwsLCFBYWpn79+qlDhw56+umnm7hENBV73WR0RbS0AwAAAEBAOKwx7bGxsfr000+1fv16rVmzRoZhqGvXrurQoUNT14cmVN/S7mAGeQAAAAAICIcc2idOnPiXx+fOnev9+sknnzzsgtB86meQLyqnpR0AAAAAAsEhh/Zff/31kM4zmUyHXQyaVyxrtQMAAABAQDnk0D5nzpzmrANHQWw4E9EBAAAAQCA5rInoEJjimIgOAAAAAAIKob0FsbPkGwAAAAAEFEJ7C1Lf0l5MSzsAAAAABARCewtSv+QbE9EBAAAAQGAgtLcgLPkGAAAAAIGF0N6C1C/5VlJVI7fH8HE1AAAAAICDIbS3IPa6Jd8kyUEXeQAAAADwe4T2FiTUYla0LUQSk9EBAAAAQCAgtLcw9cu+FbHsGwAAAAD4PUJ7C1O/7JujkpZ2AAAAAPB3hPYWZs8M8rS0AwAAAIC/I7S3MPUzyG8vrvRxJQAAAACAgyG0tzC928ZKkl6ev1Fbd1f4thgAAAAAwF8itLcwl52cod4ZcSp11ujO939jvXYAAAAA8GOE9hYmxGLWU6OPU6TVop837daL8zb4uiQAAAAAwAEQ2lugtgkRmnT2sZKkp2at04pch48rAgAAAADsD6G9hbqwdxuN7JaqGo+h29/7VZUut69LAgAAAAD8CaG9hTKZTJpyXnelxNi0cWe5Hv1yta9LAgAAAAD8CaG9BYuLtOpfF/WUJM1cvEXf/7HDxxUBAAAAAPZGaG/hBmYl6er+mZKkez74XYVlTh9XBAAAAACoR2iH7jm9kzqlRKuwzKX7PvxdhsEycAAAAADgDwjtUFioRU9fcpysFrNmrynQOz9v8XVJAAAAAAAR2lGnS6sY3XN6J0nSw5+v1oadZT6uCAAAAABAaIfX1f0z1b9DgqqqPbrjveWqdnt8XRIAAAAAtGiEdniZzSb966KesoeH6vdch579LtvXJQEAAABAi0ZoRwOt7OGacl53SdKMOeu1ZNNuH1cEAAAAAC0XoR37GNWjlc4/vrU8hnTHe8tVWlXt65IAAAAAoEUitGO/Jp99rNrEhSu3qFKTPlvt63IAAAAAoEUitGO/osNC9dTFx8lskj78JVdf/J7n65IAAAAAoMUhtOOATmwXr/GDO0iSHvh4hfIclT6uCAAAAABaFkI7/tLtQ7PUo41djspq3fXf3+TxGL4uCQAAAABaDEI7/lKoxaynLz5O4aEW/bh+l177McfXJQEAAABAi0Fox0EdkxSlv53ZRZI07eu1+iO/xMcVAQAAAEDLQGjHIRl7UlsN7ZIsl9uj2/+zXFXVbl+XBAAAAABBj9COQ2IymfTYBT2UGGXV2h2leuKbtb4uCQAAAACCHqEdhywxyqZpF/aQJL26IEc/ZO/0cUUAAAAAENwI7WiUUzun6LKT20qS7nz/N+0ud/m4IgAAAAAIXoR2NNqDZ3RVh+QoFZQ6de+Hv8swWAYOAAAAAJoDoR2NFm616JlLjpPVYtas1Tv0zs9bfF0SAAAAAAQlQjsOy7Fpdt1zeidJ0sOfr9b6glIfVwQAAAAAwYfQjsN2df9MDcxKVFW1R7f9Z7mcNSwDBwAAAABNidCOw2Y2m/Tvi3oqPtKq1XkleuJrloEDAAAAgKZEaMcRSY4J07QLapeBe2VBjuavYxk4AAAAAGgqhHYcsaFdU3T5yRmSpDv/+5t2lTl9XBEAAAAABAdCO5rEg6O6KCs5SjtZBg4AAAAAmoxfh/aamhr97W9/U2ZmpsLDw3XMMcfooYceksfj8Z5jGIYmTZqktLQ0hYeHa/DgwVq1apUPq26ZwkItenZML1ktZs1eU6CZP7EMHAAAAAAcKb8O7Y8//rhefPFFTZ8+XWvWrNG0adP0xBNP6LnnnvOeM23aND355JOaPn26lixZotTUVA0bNkylpSxBdrR1aRWje0d2liQ98vlqrdvB7wAAAAAAjoRfh/ZFixbpnHPO0ahRo9SuXTtdeOGFGj58uJYuXSqptpX96aef1oMPPqjzzz9f3bp105tvvqmKigq98847Pq6+ZbqqXzsN6pgkZ41Ht/3nV1VVswwcAAAAABwuvw7tAwYM0Hfffad169ZJkn777TctWLBAZ5xxhiQpJydH+fn5Gj58uPc1NptNgwYN0sKFCw94XafTqZKSkgYbmobZbNK/LuqphEir/sgv1TSWgQMAAACAw+bXof3ee+/VmDFj1LlzZ4WGhqpXr16aMGGCxowZI0nKz8+XJKWkpDR4XUpKivfY/kydOlV2u927paenN9+baIGSom164qLaZeBe+zFHc9cW+LgiAAAAAAhMfh3a33vvPc2cOVPvvPOOfvnlF7355pv617/+pTfffLPBeSaTqcFzwzD22be3+++/Xw6Hw7tt3bq1WepvyU7tnKIr+9YuA3fXf39XIcvAAQAAAECj+XVov/vuu3XffffpkksuUffu3XX55Zfrjjvu0NSpUyVJqampkrRPq3pBQcE+re97s9lsiomJabCh6d1/Rhd1SolWYZlTd//3N5aBAwAAAIBG8uvQXlFRIbO5YYkWi8W75FtmZqZSU1M1a9Ys73GXy6V58+apX79+R7VW7Css1KJnxhwna4hZc9bu1FuLNvu6JAAAAAAIKH4d2s866yw9+uij+uKLL7Rp0yZ9/PHHevLJJ3XeeedJqu0WP2HCBE2ZMkUff/yxVq5cqXHjxikiIkJjx471cfWQpM6pMXqgbhm4R79co7X5LAMHAAAAAIfKZPhxn+XS0lL9/e9/18cff6yCggKlpaVpzJgx+sc//iGr1Sqpdvz65MmT9dJLL6moqEh9+vTRjBkz1K1bt0P+PiUlJbLb7XI4HHSVbwaGYejqN5Zoztqd6pQSrU9v6a+wUIuvywIAAAAAnznUHOrXof1oIbQ3v8Iyp05/er4Ky1wa16+dJp19rK9LAgAAAACfOdQc6tfd4xE8EqNseuKinpKkNxZu0pw/WAYOAAAAAA6G0I6jZkinZF3Vv50k6e4PftPOUpaBAwAAAIC/QmjHUXXv6Z3VOTVahWUu3f0By8ABAAAAwF8htOOoCgu16NkxvWQLMWvu2p16dUGOr0sCAAAAAL9FaMdR1zElWg+O6iJJeuSLNZr02SpVVbt9XBUAAAAA+B9CO3zi8pMzdO2ATEm1E9OdO+NHrdvBGu4AAAAAsDdCO3zCZDLpb2d21evjTlRilFV/5JfqrOcW6K1FmxjnDgAAAAB1CO3wqSGdk/XV7adocKckOWs8+senq3Ttm0u1q4yZ5QEAAACA0A6fS4q26fVxJ+qfZ3WV1WLWd38U6PRnftD8dTt9XRoAAAAA+BShHX7BZDLpqv6Z+vSW/spKjtLOUqeueO1nPfL5ajlrmKQOAAAAQMtEaIdf6dIqRv+7dYCu6JshSXplQY7Om7FQ6wuYpA4AAABAy0Noh98JC7XooXO66ZUrTlB8pFWr80p05nML9H8/bWaSOgAAAAAtCqEdfmto1xR9fftADcxKVFW1Rw9+vFLXv71Mu8tdvi4NAAAAAI4KQjv8WnJMmN686iT9bVQXWS1mzVq9QyOfma8f1xf6ujQAAAAAaHaEdvg9s9mkawceo49v7qf2SZHaUeLUZa/+pKlfrpGrxuPr8gAAAACg2RDaETCOTbPr81sH6tI+bWUY0kvzN+qCFxZq484yX5cGAAAAAM2C0I6AEm616NHzuuuly3srLiJUK7Y5dOZzC/RDNmu6AwAAAAg+hHYEpBHHpurrCaeo7zEJqnC5dc0bSzV79Q5flwUAAAAATYrQjoCVEhOmN64+UacfmyqX26MbZy7T579v93VZAAAAANBkCO0IaLYQi6aP7aVzj0tTjcfQbf/5VR8sy/V1WQAAAADQJAjtCHghFrP+Pfo4jTkpXR5Duuu/v+ntRZt8XRYAAAAAHDFCO4KCxWzSlPO666r+7SRJf/90lV6ev8G3RQEAAADAESK0I2iYTCb948yuunlIe0nSlC//0NOz18kwDB9XBgAAAACHh9COoGIymXT3iM66e0QnSdLTs7P12Fd/ENwBAAAABCRCO4LSzUM66B9ndpUkvTR/o/7x6Sp5PAR3AAAAAIGF0I6gdfWATE09v7tMJuntxZt1z4e/y01wBwAAABBACO0IamNOaqunRh8ni9mkD5bl6vZ3f1W12+PrsgAAAADgkBDaEfTO7dVaM8b2UqjFpM9/z9NNM5epqtrt67IAAAAA4KAI7WgRTu/WSi9fcYJsIWbNXlOg695aqkoXwR0AAACAfyO0o8UY0ilZr191oiKsFv2QXagrX/tZpVXVvi4LAAAAAA6I0I4WpV/7RL19TR9Fh4Xo5027ddkrP6m4wuXrsgAAAABgvwjtaHF6Z8TpP9edrLiIUP2W69AlLy9WYZnT12UBAAAAwD4I7WiRurW2670b+iop2qY/8ks1+qVF2lRY7uuyAAAAAKABQjtarI4p0Xr/hr5Ks4dp485ynf7MfL08f4NqWBIOAAAAgJ8gtKNFy0yM1Ac39VP/DgmqqvZoypd/6LznF2r19hJflwYAAAAAhHYgLTZcM6/po2kX9lBMWIhWbHPo7OkL9MQ3f7CeOwAAAACfIrQDkkwmk0afkK7Zdw7SGd1TVeMxNGPOBp3x7A/6OWe3r8sDAAAA0EIR2oG9JEeH6flLe+vFy3orOdqmjTvLNfqlRfrbJytY0x0AAADAUUdoB/bj9G6pmjVxkC45MV2SNHPxFg1/ar6+W7PDx5UBAAAAaEkI7cAB2MND9dgFPfTOdX2UkRChPEeVrnlzqW79z6+s6w4AAADgqCC0AwfRr32ivr79FN1wyjEym6T//bZdw56cp49+yZVhGL4uDwAAAEAQI7QDhyDcatH9Z3TRpzcPUJdWMSqqqNbE93/TuNeXKLeowtflAQAAAAhShHagEbq3seuzW/rr7hGdZA0xa966nRr+1Hy98WOO3B5a3QEAAAA0LUI70EihFrNuHtJBX90+UCe2i1OFy61J/1uti15cqD/yS3xdHgAAAIAgYjIYlKuSkhLZ7XY5HA7FxMT4uhwEEI/H0P/9vEWPf/WHypw1MpmkC45vo4nDOiotNtzX5QEAAADwU4eaQwntIrTjyG0vrtSjX6zRFyvyJEm2ELPG9W+n8YM7yB4e6uPqAAAAAPgbQnsjENrRVH7dUqSpX/2hn3N2S6pdNu6WIR10ed8MhYVafFwdAAAAAH9BaG8EQjuakmEYmrO2QI999YfW7SiTJLWODdedwzvq3ONay2w2+bhCAAAAAL5GaG8EQjuag9tj6MNluXpy1jrll1RJkrq0itH9IzvrlI5JPq4OAAAAgC8R2huB0I7mVOly6/WFOXphzgaVOmskSQM6JOq+kZ3VrbXdx9UBAAAA8AVCeyMQ2nE0FJW7NH3Oer29aLNcbo8k6Zzj0nTX8E5Kj4/wcXUAAAAAjiZCeyMQ2nE0bd1doX99u1afLt8uSQq1mHT5ye10y6kdFB9p9XF1AAAAAI4GQnsjENrhCyu3OfTYV39owfpCSVK0LUQ3Dm6vy/tmKCaMZeIAAACAYEZobwRCO3xp/rqdmvrVH1qTV+LdFxZqVnyEVXGRVsXXbXERdY+RViU0eB6quAirQi1mH74LAAAAAI1xqDk05CjWBGA/TumYpAEdEvXpb9v01Kxsbdldoapqj7Y7qrTdUXXI14kJC/GG+szESN00qL2yUqKbsXIAAAAAzY2WdtHSDv9hGIYqXG7tLnfVbhUuFdV/Xe5SUcWer2ufV6uowqX9/VdsMZt0yYnpumNYRyVG2Y7+mwEAAABwQEHTPb5du3bavHnzPvvHjx+vGTNmyDAMTZ48WS+//LKKiorUp08fzZgxQ8cee+whfw9COwKZ22PIUVntDfW7ypz66Jdt+nb1DklSlC1ENw1ur2sGZCos1OLjagEAAABIQRTad+7cKbfb7X2+cuVKDRs2THPmzNHgwYP1+OOP69FHH9Ubb7yhjh076pFHHtH8+fO1du1aRUcfWtdgQjuC0eKNu/ToF2u0YptDktQ6Nlz3nN5JZ/VIk9ls8nF1AAAAQMsWNKH9zyZMmKDPP/9c2dnZkqS0tDRNmDBB9957ryTJ6XQqJSVFjz/+uG644YZDuiahHcHK4zH06W/bNO3rtcqrGx/fs41dfzuzq05sF+/j6gAAAICW61BzaEBNN+1yuTRz5kxdffXVMplMysnJUX5+voYPH+49x2azadCgQVq4cOEBr+N0OlVSUtJgA4KR2WzSeb3aaM5dg3X3iE6KtFr0W65DF724SDe+vUybCst9XSIAAACAvxBQof2TTz5RcXGxxo0bJ0nKz8+XJKWkpDQ4LyUlxXtsf6ZOnSq73e7d0tPTm61mwB+EhVp085AOmnv3EI05qa3MJunrVfka9tQ8PfS/1SqucPm6RAAAAAD7EVCh/dVXX9XIkSOVlpbWYL/J1HB8rmEY++zb2/333y+Hw+Hdtm7d2iz1Av4mKdqmqed311e3n6JBHZNU7Tb02o85GvTEXL3yw0a5ajy+LhEAAADAXgImtG/evFmzZ8/Wtdde692XmpoqSfu0qhcUFOzT+r43m82mmJiYBhvQknRKjdabV5+kt64+SZ1To+WorNYjX6zRsKfm6asVeQqwqS4AAACAoBUwof31119XcnKyRo0a5d2XmZmp1NRUzZo1y7vP5XJp3rx56tevny/KBALKKR2T9MVtA/XY+d2VFG3T5l0Vuun/ftHolxZp+dZiX5cHAAAAtHgBEdo9Ho9ef/11XXnllQoJCfHuN5lMmjBhgqZMmaKPP/5YK1eu1Lhx4xQREaGxY8f6sGIgcFjMJl1yUlvNvWuwbju1g8JCzVqyqUjnzvhRt/3nV23dXeHrEgEAAIAWKyCWfPv22281YsQIrV27Vh07dmxwzDAMTZ48WS+99JKKiorUp08fzZgxQ926dTvk67PkG7BHnqNS//pmnT76NVeGIVktZo3r3043D+4ge0Sor8sDAAAAgkLQrtPeHAjtwL5WbnNoypdrtHDDLklSbESobjs1S5ednCFrSEB00gEAAAD8FqG9EQjtwP4ZhqG5a3dqypdrlF1QJknKSIjQfad31undUv9ylQYAAAAAB0ZobwRCO/DXatwevb80V0/OWqfCMqckqXdGnB4c1UXHt43zcXUAAABA4CG0NwKhHTg0Zc4avTx/o16ev0FV1bVruo/q3kr3nN5JGQmRPq4OAAAACByE9kYgtAONk++o0pOz1uq/y2onqwu1mHRF33a69dQOio2w+ro8AAAAwO8R2huB0A4cnjV5JZry5Rr9kF0oSYoJC9Ftp2Xp8r4ZsoVYfFwdAAAA4L8I7Y1AaAeOzLx1OzX1yzX6I79UkpQeH657T++sUd1bMVkdAAAAsB+E9kYgtANHzu0x9OGyXP3r27UqKK2drO649FhdMyBTA7MS6TYPAAAA7IXQ3giEdqDpVLhq9P/m5+il+RtU4XJLkswmqWd6rAZ1TNIpHZPUs02sLGZa4AEAANByEdobgdAONL2Ckiq9+mOO5vxRoHU7yhoci40I1YAOiTqlY5IGdUxSSkyYj6oEAAAAfIPQ3giEdqB5bS+u1A/ZOzVv3U79kF2o0qqaBsc7p0ZrUF2A790ujknsAAAAEPQI7Y1AaAeOnhq3R7/lFmve2p2al12o33OLtfdfoQirRX2PSdCgTkk6JStJ7RJZ/x0AAADBh9DeCIR2wHd2l7v0Q/ZOzV9XqHnrdqqwzNngeEZChE7OTFCXVtHq0ipGnVvFyB4e6qNqAQAAgKZBaG8EQjvgHzweQ2vyS+oCfIGWbS5StXvfP1GtY8PVpVWMuraKVte0GHVpFaP0uAiZmdwOAAAAAYLQ3giEdsA/lTlrtGjDLv2eW6w1eSVak1eqbcWV+z030mpR51Yx3hb5Lq1i1Dk1WhHWkKNcNQAAAHBwhPZGILQDgcNRUa01+SVavb2kNsjnl2jdjjK5ajz7nGsySe0SItWlVbTaJ0UpJixUkbYQRdosig4LUaQ1RFFhIYqyhSjSVvtoCzHLZKLFHgAAAM2L0N4IhHYgsNW4PdpYWK41eSVaXdcivyavRDtLnQd/8Z+EmE2Kqg/0ttpQH2kLUbQtRBFWi8x1gb4+1+/J93/a3+DrPcfMJpP6d0jU0C7JfDgAAADQghHaG4HQDgSnnaXOum71Jdqyu0LlzhqVOd11jzXexzJnjSpc7qNaW482dt05vJNOyUokvAMAALRAhPZGILQDcHsMlbtqg3y5s0alVTUqd7q9ob7cWaNyV02D5enq/3zW7zMafL3vMUkqrnDpg2W53g8JTmoXrzuHd1SfYxKa+R0CAADAnxDaG4HQDuBo2lXm1AtzN+itxZu9Y/EHZiVq4rCO6tU2zsfVAQAA4GggtDcCoR2AL+Q7qjRjznq9u2SLd2m7oV2SNXFYJ3VN428RAABAMCO0NwKhHYAvbd1doWe/y9aHv+TKU/cXeVSPVrpjaJY6JEf7tjgAAAA0C0J7IxDaAfiDjTvL9PTsbP3v9+0yDMlsks7t1VoTTuuotgkRTfq9atweVVa7FR0W2qTXBQAAwKEhtDcCoR2AP/kjv0RPzVqnb1btkFS7DN1FJ6Tr1lM7KC02/JCv46xxK7eoUpt3lWtTYUXt467ax9yiStV4DNnDQ5WREKGMhEhlxEeobUKEMuJrnydH22Q2M7M9AABAcyC0NwKhHYA/+j23WE/OWqe5a3dKkqwWsy49ua3GD+6gpGibJKmq2q0tuyu0qbBcm3dVaNOuPY/biyu93e0Phy3ErLbxEcpIiFDb+Ei1S4yoex6p1rHhsoaYm+JtAgAAtEiE9kYgtAPwZ0s37da/vl2rxRt3S5LCQy3q3tqurUUVynNU/eVrI60WZSTUBu6MhEi1S6h/jFR0WIi2FlVo864KbakL+lt21z7fVlwp918kfrNJSosNV+vYcFnMJtV4DNW4PXJ7DNV4jD89euR2739/jduQxzDUq22cruiboZHdWvFhAAAAaBEI7Y1AaAfg7wzD0MINu/TEN2u1fGtxg2PRYSHKTIz8UyivfUyMsspkanwX92q3R9uLK7V5V4U2767Qlrqu9Vt2VWjL7gpVVrub6J01lBhl09g+bXVpn7ZKiQlrlu8BAADgDwjtjUBoBxAoDMPQoo27VFDiVEZChNolRCo2IvSwgvmR1LCz1KnNuyu0vbhSJpNJIWaTLOa9H821j5Y9+0PM5gbP689z1rj1ya/b9X8/bVZBqVNS7Tj+Ed1SdcXJGTopM/6ovj8AAICjgdDeCIR2APC9ardH36zK11uLNuvnnN3e/Z1To3VF33Y6t1eaIqwhPqwQAACg6RDaG4HQDgD+ZU1eid5atFmf/LrN2xU/OixEo09I1+UnZ6hdYqSPKwQAADgyhPZGILQDgH9yVFTrv8u26u3Fm7V5V4V3/+BOSbqybzsN6pjEsnQAACAgEdobgdAOAP7N4zE0P3un3lq0WXPWFqj+/1wZCRG6/OQMXdQ7XfaI0H1eZxiGXG6PKpxulbtqVOFyq9xZo0qXW+UutypcNSp37nk0maSs5Ch1So1WRkKkLHwgAAAAmgmhvREI7QAQODbvKtfMxZv13pKtKqmqkSSFhZrVo3WsqmpqQ3l9OK9wuVVzmIvVh4WalZUcrU6p0eqcGq3OqTHqlBqtpGhbU74dAADQQhHaG4HQDgCBp9Ll1qfLt+nNRZu1Jq/koOfbQsyKtIUowmpRpDVEEbbax3CrRZFWiyJsIXLVeLRuR6nW7ShVVbVnv9dJiLSqU+qeMN8pNUYdU6KYJA8AADQKob0RCO0AELgMw9CvW4u1rahSUXWhPGKvUB5hsygi1KIQi/mQr+n2GNqyu0Jr80u0Jq9Ua/NLtXZHqTbtKtf+/q9pMkkZ8RF1YT5G3Vvb1aONnbXmAQDAARHaG4HQDgA4FJUut7ILSvVHfm2Q/yO/RGvzS1VY5trv+SkxNnVvHauebezq3sauHm1iFR9pPcpVH57d5S79llusCqdbp3ZOVrjV4uuSAAAIKoT2RiC0AwCORGGZsy7El2pNXolW5DqUXVCq/Q2nbxMXrh5t7N4w362NXTFh+06idzSVO2u0cptDv+c6tDy3WL/nFmvr7krv8cQoq64ZcIwuO7mton1cKwAAwYLQ3giEdgBAU6tw1Wj19hL9luvQitxi/Z7r0MbC8v2ee0xipLq3sat7a7t6psfq2LSYZhsj76rxaG1+qX7LLdZvW2vrOtAHDMckRspZ49G24toAHxMWoqv6Z+qq/u0UGxEYPQYAAPBXhPZGILQDAI6Gkqpqb4v2ilyHfsstVm5R5T7nmU1SfKRVMeGhsoeHKias9nHvLSY8pO5xr3MiQhVtC5HJVLtUncdjaGNhuX6vC+i/5Tq0Oq9Erpp9J9lLjQlTz/TaLvw928Sqexu77OGhqnZ79Ony7Xp+7npt3Fn7oUOk1aLLTs7QNQMzlRzNuH0AAA4Hob0RCO0AAF/ZXe7Sim0O/b61WL9vqw3z+SVVh309s0neIL+7zKVSZ80+59jDQ9WjjV0928SqZ3ptN/3kg0ya5/YY+mplnmbM2eCdrd8WYtYlJ6br+kHt1To2/LBrBgCgJSK0NwKhHQDgT3aWOlVY5pSjstq7ldRt3udVNfscd+6nBT0s1KxuaXUt6Om1QT0jIcLbGt9YhmHo+z8K9Nz367V8a7EkKdRi0vm92uimwe3VLjHySN46AAAtBqG9EQjtAIBgUFXtbhDsI20hykqOatRyd4fKMAwt3LBL079fr0Ubd0mqbeU/s0eabh7SQZ1So4/4+kUV1dq0q1ybd5Vry65KuQ1DkVaLIqwWhVtD6h5rl/SLsIbUfu09bpHVYj7sDycAAGhuhPZGILQDAHD4lm3erenfr9ectTu9+4Z3TdEtp3ZQjzaxB3ydYRjaWerUpl0V2ryrXJt3VdSF9NrH0qp9u/Y3hsVsUkRobYCPtIUoPNSirJQo3Tiovbq04v/3AADfIrQ3AqEdAIAjt3KbQ8/PXa+vVuar/l8XA7MSdf0px8hiNu0J5YW1j1t2V6jC5f7La6bZw9Q2IUIZ8ZEKDTGpwuVWhdOtimq3Kl01qnC5Vely1+531aiy2q1q98H/aTOyW6puOy2L8A4A8BlCeyMQ2gEAaDrrC0r1/JwN+vS37XLvby25vZhNUuu4cLVLiFRGQkTdY6TaJUQoPT5CYaGWRn//arfHG+L3DvVlzmp99Ms2fbEiz/uhwhnda8N751T+/w8AOLoI7Y1AaAcAoOlt2VWhF+Zt0Fcr8xQXYd0rlO95bBMXIWtI04+5/ytr80v17PfZ+pLwDgDwIUJ7IxDaAQBoedbml+rZ77L1xYo8775R3VvpttOyjngiPQAADobQ3giEdgAAWq4/8kv03HfrveHdZJLO6N5Kt5+WpY4p/hPe3R5DeY5KbdldoS27KrStuFIdkqM04tjUwxpGAADwLUJ7IxDaAQDAH/kleva7bH25Il+Sb8J7mbNGW3ZV1Abz3eV1j5XaurtCuUUV+51kLy4iVBf2bqMxJ7XVMUlRR6VOAMCRI7Q3AqEdAADU2194r+82f7jh3TAMVbjcclRWq6SqWkXl1dpaVKGtuyu0uS6kb91doV3lrr+8TqjFpPS42kn6UmJs+iG7UHmOKu/xfu0TdGmfDA3rmnLU5woAADQOob0RCO0AAODP1uTVhvevVjYM71f1z5TZJJVU1dSG8MpqbxgvqaxRSd3XDY/VHHQm/XrxkValx0eobXyEMuoe0+Mj1DYhQqkxYbKYTd5za9wezV27U//302bNXbfTO7FeYpRVo09I15iT2io9PqLJfzYAgCNHaG8EQjsAADiQNXklemZ2tr5elX/E1woxm2QPD5U9IlStY8PVtj6c1y1xlx4foZiw0MO6dm5Rhd5bslXvLtmqnaVOSbUfNAzMStKlfdrqtM7JCrH4Z+t7pcutzbvLlRYbftjvHwACDaG9EQjtAADgYFZvr215X5yzS5HWEMWEh8oeHqKYsFDZw0PrnocqJixkz9fefbWPYaFmmUymg3+zI1Dt9ui7NTv0fz9t0Q/Zhd79KTE2XXxiW11yYrrSYsObtYa/Uu6s0eq8Eq3c5tCKbQ6t3ObQ+oIy1XdEyEiIULc0u7qmxejYtBh1a21XYpTNZ/UCQHMhtDcCoR0AAASjTYXl+s+SLfpgaa53vLzZJJ3aOVlj+7TVoI7JDbrbN7UyZ41W1YXzVdtLtGKbQxt2lml///qMtoWo1Fmz3+ukxNjULc2uY9Ni1DXNrm6tY9Q6NrzZPwABgOZEaG8EQjsAAAhmzhq3vl21Q//302Yt3rjbu791bLhO65KsmLBQhVstirRaFGELUYTVokhr7WOENUQRttrn9efsr5t9SVW1Vm3bqwV9u0M5heX7DegpMTZ1b21Xt9Z2dUuzq3sbu1JiwlRU7vK2wq/aXvKX17CHh6pb6xgdWxfmj02zKzMxUhazSYZhqNzlVklltUqraurmG6ida6C0qn7egZoD7rOGmNUxJVqdUqPVqe6xQ3JUi1taz+0xtHKbQz9k71S5y61e6bHqnRGnBHo+AE2C0N4IhHYAANBSrC8o039+3qIPluXKUVl9WNewhpgbBHuX26PNuyr2e26aPUzHtrare912bOsYJUeHHfL3KnfWaE1eSW2Irwvz2QWl+13+LjzUIluoWSWV1TrEef8OmdkktUuIVKfUaHVMiVbn1Gh1TI1Wu4TIZu2tcLTlOSr1w7pCzcveqR/XF6q4Yt975JjESPXOiNMJ7eLUOyNe7ZMi6fUAHAZCeyMQ2gEAQEtTVe3W1yvztXZHqSpdbpU7a1RR7VaFs0blLnftPleNKpxuVbhq9x1sBvzWseF1Lei1Y9Gbazy6s8at7B1lWrXdoZXbSrRqu0Nr8kpVWe1ucF6oxaSYsNq5BWLCQhQdFqqYunkIYsJDFW2rnX+gfl/98bKqGq3dUap1+aX6I79Ua3eU7je8SpItxKwOyVENWuU7pUYrNSYsIIJspcutxTm79MO6Qs3P3qn1BWUNjkfbQtSvQ4LiIqxatrlI2X86LklxEaHqnVEb4E9oF6fure0trlcCcDiCJrRv27ZN9957r7766itVVlaqY8eOevXVV9W7d29JteueTp48WS+//LKKiorUp08fzZgxQ8cee+whfw9COwAAwF8zDEMut6cuzNeG+4q6YC9JnVNjFB9p9Vl9bo+hTbvKZRiGN5TbQppm4j/DMLSz1Km1O0q1Nr92W7ejVOt2lO3zQUG96LAQdUiOUoekKLXf6zE9Ltyns/gbhqE1eaWan71TP2Tv1JKcIrncHu9xs0nqmR6rU7KSdErHRPVsE9ug3uIKl37ZUqSlm4q0dHORfttaLGeNp8H3sFrM6tY6Rie0i69tkadLPbBfQRHai4qK1KtXLw0ZMkQ33XSTkpOTtWHDBrVr107t27eXJD3++ON69NFH9cYbb6hjx4565JFHNH/+fK1du1bR0dGH9H0I7QAAAGgsj8fQ1qIK/ZFf1ypf1zq/sbD8gL0SrBazMhMj1T450hvk2yfVbuHW5mmd3lnq1IL1OzV/XaF+yC5UYZmzwfHWseE6pWOiBmYlqX/7RNkjDn3ZPVeNR6u2O7Rs854g/+frS1JmYqSObxtXN5lgjLq0ipE9nOX90LIFRWi/77779OOPP+qHH37Y73HDMJSWlqYJEybo3nvvlSQ5nU6lpKTo8ccf1w033HBI34fQDgAAgKbirHErp7BcGwrKtb6gTOt3lmlDQZk2FpapqtpzwNe1jg1Xh7oQ3yE5Su0SI2SSSVXVblVVu1VZ7VZVtafusW6fa8/+vc+r31furNGW3Q3nG4iwWtT3mAQNzErUwI5JOiax6cakG4ahLbsrvAF+2ebdWrdj3y719e+3S6vaEN+1VbS6trKrTVy4zM08R0B9/PH18AVXjUelVdX0QmjBgiK0d+3aVSNGjFBubq7mzZun1q1ba/z48bruuuskSRs3blT79u31yy+/qFevXt7XnXPOOYqNjdWbb7653+s6nU45nXs+ASwpKVF6ejqhHQAAAM3G4zG0rbjSG+I37CyrDfUFZSo6wJj5ptKtdYxOyUrSwKwkHZ8RK1vI0Rtz7qio1i9bivTr1mKtySvRmrwS5RZV7vfcKFuIurSKrg3zrWpb5DulRh90jLxhGCqprNHOsirtLHVpZ5lThaVO7SxzamepU4V7Pe4qcyk6LERZydHqkBKlrOQoZSVHKyslSsnRtiYP826Poc27yrVuR1ndsIrabePOctV4DLWNj1D/Doka0CFRfdsn+HSYCY6uoAjtYWG1M4tOnDhRF110kX7++WdNmDBBL730kq644gotXLhQ/fv317Zt25SWluZ93fXXX6/Nmzfrm2++2e91J02apMmTJ++zn9AOAAAAX9hd7tL6PwX5LbsrZDGbFBZqVnioRWF1W3jdFhZqVpjVorAQi8Kte+3b67ywUIuOSYpslgkBj4Sjslp/5JVodV6JVm8v0Zr8Eq3LL2swvr6e2SQdkxSlrq1i1DElSlXVHm8Irw/nhWWu/b62sWrD/J4Q3z65NtSn2Q/eA6D+Q5nsglKtzd8T0NcXlO0z7v9ATCbp2LQYb4g/sV08k/oFsaAI7VarVSeccIIWLlzo3XfbbbdpyZIlWrRokTe0b9++Xa1atfKec91112nr1q36+uuv93tdWtoBAAAA/1Lt9mjjznKtzqtdDWD19tpQv7vcdcjXiAkLUWK0TUlRNu9j0l6PiVE2JURZVVRR+yFJ9o4yZReUKrugTJt3VRxwLoIIq6V2YsH6QJ8cJWuIWet2lCp7R5nW7ihV9o5Slbv2PzFhWKhZWcm1ywV2So1SVkrtagMx4aFakrNbC9YX6sf1hfojv7TB66whZp2QEaf+HRLVv0Oiure2++0SgzVuj8wmU7MPbwgmhxraQ45iTY3WqlUrde3atcG+Ll266MMPP5QkpaamSpLy8/MbhPaCggKlpKQc8Lo2m002m3992ggAAAC0ZKEWs3fJvPPqRr4ahqGCUqe3RX7DzjJFWkNqg3hdCK99tCoxynbIrdJpseE6Ns3eYJ+zxq1NhRW1IX5HbW+H7IJS5RSWq8Ll1u+5Dv2e6zjIezCpfVKUOqZEq2NKVF1Ij1abuIgDhu0hnZM1pHOyJKmgtEqLNuzSguxCLVhfqDxHlRZu2KWFG3bpiW/WKiYsRH3bJ2hAXYjPPIL5CGrcHlXVeOSsdquqxqMKZ43K6reqPV+XO2tUWve49/7aY26VVtUeq6x2KzYiVGNOaqtx/dopJSbssOrCvvw6tPfv319r165tsG/dunXKyMiQJGVmZio1NVWzZs3yjml3uVyaN2+eHn/88aNeLwAAAICmYzKZlBITppSYMA3plNys38sWYvF+aLC3ardHm3dVaH1dmM8uqO36Xu32qGNKtLfVvFNqlDISIhV6BEv6JUeH6ZzjWuuc41rLMAzlFJbrx/W1AX7hhl0qqarRN6t26JtVOyRJafYwndw+QZHWEFVVu+WsqZuQcK8w7qzb7/zT/gP1KjgSxRXVemHuBr3yw0ad1TNN1w44Rl3T6Ml8pPy6e/ySJUvUr18/TZ48WaNHj9bPP/+s6667Ti+//LIuvfRSSbVLvk2dOlWvv/66srKyNGXKFM2dO5cl3wAAAAAEjRq3Ryu3l9SG+OxCLdtc1CTj+KXapQgjbBZF2UL2bGEhirSFKNpW+7j3/gbnWEMUXXfukk279eoPOfp5027vtft3SNC1A47RoI5JdJ3/k6AY0y5Jn3/+ue6//35lZ2crMzNTEydO9M4eL9V2mZk8ebJeeuklFRUVqU+fPpoxY4a6det2yN+D0A4AAAAgkFS63FqyabeWbS6Sodpx82EhFtn29xhqkS1k/49Wi7nJw/TyrcV65YeN+mplvrdFv0NylK4ZkKnzerVmcr06QRPajwZCOwAAAAA0rdyiCr25cJP+8/NWlTlrJEkJkVZd3jdDl52c0WyrGng8hpw1HoVb/fvDAUJ7IxDaAQAAAKB5lFZV670lW/X6j5u0rbhSUu3M+Bcc31rXDMhUh+RDG9b8Z+XOGuUUlmvDzjJt2FmujTvLtHFnuTYWlun849toynndm/JtNDlCeyMQ2gEAAACgedW4PfpqZb5e+WGjfttrJv7BnZJ03cBj1K99wj6z4Xs8hrYVV2pj4Z5QvqHuMb+k6oDfq1/7BL1z3cnN9l6aAqG9EQjtAAAAAHB0GIahpZuL9MoPG/Xt6h2qT6RdWsXowt5t5KhwaUNdON+0q1xV1QeecC8h0qpjkiLVPilKxyRF6pjEKLVPjlJ6XLhCjmAm/6OB0N4IhHYAAAAAOPo2FZbr9R9z9P7SXFVWu/d7TqjFpIyESLVPitQxSVE6JjFS7ZOj1D4xSvaI0KNccdMhtDcCoR0AAAAAfKe4wqX/+2mLfs7ZrbTYsLoW89qW8zYB0Gp+OAjtjUBoBwAAAAAcTYeaQ4Pv4woAAAAAAIIEoR0AAAAAAD9FaAcAAAAAwE8R2gEAAAAA8FOEdgAAAAAA/BShHQAAAAAAP0VoBwAAAADATxHaAQAAAADwU4R2AAAAAAD8FKEdAAAAAAA/RWgHAAAAAMBPEdoBAAAAAPBThHYAAAAAAPwUoR0AAAAAAD9FaAcAAAAAwE8R2gEAAAAA8FOEdgAAAAAA/BShHQAAAAAAPxXi6wL8gWEYkqSSkhIfVwIAAAAAaAnq82d9Hj0QQruk0tJSSVJ6erqPKwEAAAAAtCSlpaWy2+0HPG4yDhbrWwCPx6Pt27crOjpaJpPJ1+UcUElJidLT07V161bFxMT4uhzgoLhnEUi4XxFouGcRSLhfEWiOxj1rGIZKS0uVlpYms/nAI9dpaZdkNpvVpk0bX5dxyGJiYvhjh4DCPYtAwv2KQMM9i0DC/YpA09z37F+1sNdjIjoAAAAAAPwUoR0AAAAAAD9FaA8gNptN//znP2Wz2XxdCnBIuGcRSLhfEWi4ZxFIuF8RaPzpnmUiOgAAAAAA/BQt7QAAAAAA+ClCOwAAAAAAforQDgAAAACAnyK0AwAAAADgpwjtAeT5559XZmamwsLC1Lt3b/3www++LgnQ/PnzddZZZyktLU0mk0mffPJJg+OGYWjSpElKS0tTeHi4Bg8erFWrVvmmWLR4U6dO1Yknnqjo6GglJyfr3HPP1dq1axucwz0Lf/LCCy+oR48eiomJUUxMjPr27auvvvrKe5z7Ff5s6tSpMplMmjBhgncf9yz8yaRJk2QymRpsqamp3uP+cr8S2gPEe++9pwkTJujBBx/Ur7/+qoEDB2rkyJHasmWLr0tDC1deXq6ePXtq+vTp+z0+bdo0Pfnkk5o+fbqWLFmi1NRUDRs2TKWlpUe5UkCaN2+ebr75Zi1evFizZs1STU2Nhg8frvLycu853LPwJ23atNFjjz2mpUuXaunSpTr11FN1zjnneP/RyP0Kf7VkyRK9/PLL6tGjR4P93LPwN8cee6zy8vK824oVK7zH/OZ+NRAQTjrpJOPGG29ssK9z587Gfffd56OKgH1JMj7++GPvc4/HY6SmphqPPfaYd19VVZVht9uNF1980QcVAg0VFBQYkox58+YZhsE9i8AQFxdnvPLKK9yv8FulpaVGVlaWMWvWLGPQoEHG7bffbhgGf2Phf/75z38aPXv23O8xf7pfaWkPAC6XS8uWLdPw4cMb7B8+fLgWLlzoo6qAg8vJyVF+fn6De9dms2nQoEHcu/ALDodDkhQfHy+Jexb+ze12691331V5ebn69u3L/Qq/dfPNN2vUqFEaOnRog/3cs/BH2dnZSktLU2Zmpi655BJt3LhRkn/dryFH9bvhsBQWFsrtdislJaXB/pSUFOXn5/uoKuDg6u/P/d27mzdv9kVJgJdhGJo4caIGDBigbt26SeKehX9asWKF+vbtq6qqKkVFRenjjz9W165dvf9o5H6FP3n33Xe1bNkyLV26dJ9j/I2Fv+nTp4/eeustdezYUTt27NAjjzyifv36adWqVX51vxLaA4jJZGrw3DCMffYB/oh7F/7olltu0e+//64FCxbsc4x7Fv6kU6dOWr58uYqLi/Xhhx/qyiuv1Lx587zHuV/hL7Zu3arbb79d3377rcLCwg54Hvcs/MXIkSO9X3fv3l19+/ZV+/bt9eabb+rkk0+W5B/3K93jA0BiYqIsFss+reoFBQX7fPID+JP62Te5d+Fvbr31Vn322WeaM2eO2rRp493PPQt/ZLVa1aFDB51wwgmaOnWqevbsqWeeeYb7FX5n2bJlKigoUO/evRUSEqKQkBDNmzdPzz77rEJCQrz3Jfcs/FVkZKS6d++u7Oxsv/obS2gPAFarVb1799asWbMa7J81a5b69evno6qAg8vMzFRqamqDe9flcmnevHncu/AJwzB0yy236KOPPtL333+vzMzMBse5ZxEIDMOQ0+nkfoXfOe2007RixQotX77cu51wwgm69NJLtXz5ch1zzDHcs/BrTqdTa9asUatWrfzqbyzd4wPExIkTdfnll+uEE05Q37599fLLL2vLli268cYbfV0aWriysjKtX7/e+zwnJ0fLly9XfHy82rZtqwkTJmjKlCnKyspSVlaWpkyZooiICI0dO9aHVaOluvnmm/XOO+/o008/VXR0tPfTc7vdrvDwcO96wtyz8BcPPPCARo4cqfT0dJWWlurdd9/V3Llz9fXXX3O/wu9ER0d75wipFxkZqYSEBO9+7ln4k7vuuktnnXWW2rZtq4KCAj3yyCMqKSnRlVde6Vd/YwntAeLiiy/Wrl279NBDDykvL0/dunXTl19+qYyMDF+XhhZu6dKlGjJkiPf5xIkTJUlXXnml3njjDd1zzz2qrKzU+PHjVVRUpD59+ujbb79VdHS0r0pGC/bCCy9IkgYPHtxg/+uvv65x48ZJEvcs/MqOHTt0+eWXKy8vT3a7XT169NDXX3+tYcOGSeJ+ReDhnoU/yc3N1ZgxY1RYWKikpCSdfPLJWrx4sTdj+cv9ajIMwziq3xEAAAAAABwSxrQDAAAAAOCnCO0AAAAAAPgpQjsAAAAAAH6K0A4AAAAAgJ8itAMAAAAA4KcI7QAAAAAA+ClCOwAAAAAAforQDgAAAACAnyK0AwCAZjd37lyZTCYVFxf7uhQAAAIKoR0AAAAAAD9FaAcAAAAAwE8R2gEAaAEMw9C0adN0zDHHKDw8XD179tQHH3wgaU/X9S+++EI9e/ZUWFiY+vTpoxUrVjS4xocffqhjjz1WNptN7dq107///e8Gx51Op+655x6lp6fLZrMpKytLr776aoNzli1bphNOOEERERHq16+f1q5d6z3222+/aciQIYqOjlZMTIx69+6tpUuXNtNPBACAwBDi6wIAAEDz+9vf/qaPPvpIL7zwgrKysjR//nxddtllSkpK8p5z991365lnnlFqaqoeeOABnX322Vq3bp1CQ0O1bNkyjR49WpMmTdLFF1+shQsXavz48UpISNC4ceMkSVdccYUWLVqkZ599Vj179lROTo4KCwsb1PHggw/q3//+t5KSknTjjTfq6quv1o8//ihJuvTSS9WrVy+98MILslgsWr58uUJDQ4/azwgAAH9kMgzD8HURAACg+ZSXlysxMVHff/+9+vbt691/7bXXqqKiQtdff72GDBmid999VxdffLEkaffu3WrTpo3eeOMNjR49Wpdeeql27typb7/91vv6e+65R1988YVWrVqldevWqVOnTpo1a5aGDh26Tw1z587VkCFDNHv2bJ122mmSpC+//FKjRo1SZWWlwsLCFBMTo+eee05XXnllM/9EAAAIHHSPBwAgyK1evVpVVVUaNmyYoqKivNtbb72lDRs2eM/bO9DHx8erU6dOWrNmjSRpzZo16t+/f4Pr9u/fX9nZ2XK73Vq+fLksFosGDRr0l7X06NHD+3WrVq0kSQUFBZKkiRMn6tprr9XQoUP12GOPNagNAICWitAOAECQ83g8kqQvvvhCy5cv926rV6/2jms/EJPJJKl2THz91/X27qwXHh5+SLXs3d29/nr19U2aNEmrVq3SqFGj9P3336tr1676+OOPD+m6AAAEK0I7AABBrmvXrrLZbNqyZYs6dOjQYEtPT/eet3jxYu/XRUVFWrdunTp37uy9xoIFCxpcd+HCherYsaMsFou6d+8uj8ejefPmHVGtHTt21B133KFvv/1W559/vl5//fUjuh4AAIGOiegAAAhy0dHRuuuuu3THHXfI4/FowIABKikp0cKFCxUVFaWMjAxJ0kMPPaSEhASlpKTowQcfVGJios4991xJ0p133qkTTzxRDz/8sC6++GItWrRI06dP1/PPPy9Jateuna688kpdffXV3onoNm/erIKCAo0ePfqgNVZWVuruu+/WhRdeqMzMTOXm5mrJkiW64IILmu3nAgBAICC0AwDQAjz88MNKTk7W1KlTtXHjRsXGxur444/XAw884O2e/thjj+n2229Xdna2evbsqc8++0xWq1WSdPzxx+v999/XP/7xDz388MNq1aqVHnroIe/M8ZL0wgsv6IEHHtD48eO1a9cutW3bVg888MAh1WexWLRr1y5dccUV2rFjhxITE3X++edr8uTJTf6zAAAgkDB7PAAALVz9zO5FRUWKjY31dTkAAGAvjGkHAAAAAMBPEdoBAAAAAPBTdI8HAAAAAMBP0dIOAAAAAICfIrQDAAAAAOCnCO0AAAAAAPgpQjsAAAAAAH6K0A4AAAAAgJ8itAMAAAAA4KcI7QAAAAAA+ClCOwAAAAAAfur/A0uoVfRHvKepAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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3796aPn26SkpKzH15eXlqaGjQyJEjzW3JyclKT0/X2rVrJUnr1q2Ty+Uyg78kDR48WC6Xy6dNenq6GfwladSoUXK73crLyztu391ut6qqqnweAAAAAAB0NH4N/4MGDdLf//53vfPOO3r++edVVFSkIUOGqLS0VJI0ZswYvfzyy1q5cqUef/xxbdy4Uddee63cbrckqaioSFarVdHR0T7HTUhIUFFRkdkmPj6+zWfHx8f7tElISPDZHx0dLavVarY5lvnz55vrCLhcLqWkpJz6jwEAAAAAwBni12H/Y8aMMZ/369dPmZmZ6tmzp1566SXNnj1bkydPNvenp6dr4MCBSk1N1bJly3TDDTcc97iGYchisZivj3z+bdoc7YEHHtDs2bPN11VVVR3+AkCtu1G5X5fK09ikMf2S/N0dAAAAAMBZ4Pdh/0eKiopSv379tGPHjmPuT0pKUmpqqrk/MTFRHo9H5eXlPu1KSkrMSn5iYqKKi4vbHOvAgQM+bY6u8JeXl6uhoaHNiIAj2Ww2OZ1On0dHV1rj0Z0vbdKc//vE310BAAAAAJwlHSr8u91ubdu2TUlJx65Il5aWqqCgwNyfkZGh8PBwrVixwmxTWFioLVu2aMiQIZKkzMxMVVZWasOGDWab9evXq7Ky0qfNli1bVFhYaLZZvny5bDabMjIyTvv39CdHRPNgj0Merxq8TX7uDQAAAADgbPBr+J87d65Wr16tnTt3av369brppptUVVWlqVOnqqamRnPnztW6deu0a9curVq1SuPHj1dcXJyuv/56SZLL5dKdd96pOXPm6L333tPHH3+s73//++rXr5+5+n+fPn00evRoTZ8+Xbm5ucrNzdX06dM1btw4paWlSZJGjhypvn37KisrSx9//LHee+89zZ07V9OnTw+Iav7JaA3/klRT3+jHngAAAAAAzha/zvnfu3evbrnlFh08eFDdunXT4MGDlZubq9TUVNXV1Wnz5s36+9//roqKCiUlJemaa67Rq6++KofDYR7jySefVFhYmCZNmqS6ujoNGzZML774okJDQ802L7/8smbOnGneFWDChAlauHChuT80NFTLli3TjBkzNHToUNntdk2ZMkWPPfbY2fsxzpKw0BBFWkN1yONVVX2DoqOs/u4SAAAAAOAMsxiGYfi7E8GiqqpKLpdLlZWVHXrEwKCH31VxlVv/ue8KpZ/j8nd3AAAAAACnqL05tEPN+cfZ4YwIlyRV1Tf4uScAAAAAgLOB8N8Jtc77r6pjzj8AAAAAdAaE/07IaW+u/FdT+QcAAACAToHw3wk5IlrDP5V/AAAAAOgMCP+dkDnsn8o/AAAAAHQKhP9OyEnlHwAAAAA6FcJ/J3R4wT8q/wAAAADQGRD+OyFnS/in8g8AAAAAnQPhvxMyV/t3U/kHAAAAgM6A8N8JHR72T+UfAAAAADoDwn8ndHjBPyr/AAAAANAZEP47IUdL+K9izj8AAAAAdAqE/07IYS741yDDMPzcGwAAAADAmUb474RaF/xr8BpyNzb5uTcAAAAAgDON8N8JRVlDFWJpfl5Vx7x/AAAAAAh2hP9OyGKxMO8fAAAAADoRwn8nZd7ujxX/AQAAACDoEf47KYd5uz8q/wAAAAAQ7Aj/nZTziBX/AQAAAADBjfDfSZlz/uuo/AMAAABAsCP8d1JOO5V/AAAAAOgsCP+dlNNc7Z/wDwAAAADBjvDfSTnMOf8M+wcAAACAYEf476ScrPYPAAAAAJ0G4b+Taq38V9Ux7B8AAAAAgh3hv5Ny2qn8AwAAAEBnQfjvpMzKPwv+AQAAAEDQI/x3Ug7m/AMAAABAp0H476ScVP4BAAAAoNMg/HdSrZX/GnejmpoMP/cGAAAAAHAmEf47qdY5/4Yh1XgY+g8AAAAAwYzw30lFhIfKGtb8Pz/z/gEAAAAguBH+OzFz3n8d8/4BAAAAIJgR/jsxJyv+AwAAAECnQPjvxBxU/gEAAACgUyD8d2KtK/5Xuwn/AAAAABDMCP+dmNPeXPln2D8AAAAABDfCfyfmsDVX/hn2DwAAAADBjfDfiVH5BwAAAIDOgfDfibXO+a+qp/IPAAAAAMGM8N+Jmav9U/kHAAAAgKBG+O/EnK2r/RP+AQAAACCo+TX8z5s3TxaLxeeRmJho7jcMQ/PmzVNycrLsdruuvvpqbd261ecYbrdb9913n+Li4hQVFaUJEyZo7969Pm3Ky8uVlZUll8sll8ulrKwsVVRU+LTZs2ePxo8fr6ioKMXFxWnmzJnyeDxn7Lt3BGblnwX/AAAAACCo+b3yf9FFF6mwsNB8bN682dy3YMECPfHEE1q4cKE2btyoxMREjRgxQtXV1WabWbNmaenSpcrOztaaNWtUU1OjcePGyev1mm2mTJmi/Px85eTkKCcnR/n5+crKyjL3e71ejR07VrW1tVqzZo2ys7O1ZMkSzZkz5+z8CH7itLdW/gn/AAAAABDMwvzegbAwn2p/K8Mw9Ic//EG/+MUvdMMNN0iSXnrpJSUkJOiVV17RD3/4Q1VWVuqvf/2rFi9erOHDh0uS/vGPfyglJUXvvvuuRo0apW3btiknJ0e5ubkaNGiQJOn5559XZmamtm/frrS0NC1fvlyfffaZCgoKlJycLEl6/PHHNW3aND300ENyOp3H7Lvb7Zbb7TZfV1VVndbf5kxjzj8AAAAAdA5+r/zv2LFDycnJ6tGjh773ve/p66+/liTt3LlTRUVFGjlypNnWZrPpqquu0tq1ayVJeXl5amho8GmTnJys9PR0s826devkcrnM4C9JgwcPlsvl8mmTnp5uBn9JGjVqlNxut/Ly8o7b9/nz55tTCVwul1JSUk7DL3L2HJ7zT+UfAAAAAIKZX8P/oEGD9Pe//13vvPOOnn/+eRUVFWnIkCEqLS1VUVGRJCkhIcHnPQkJCea+oqIiWa1WRUdHn7BNfHx8m8+Oj4/3aXP050RHR8tqtZptjuWBBx5QZWWl+SgoKDjJX8C/WsN/fUOTPI1Nfu4NAAAAAOBM8euw/zFjxpjP+/Xrp8zMTPXs2VMvvfSSBg8eLEmyWCw+7zEMo822ox3d5ljtT6XN0Ww2m2w22wn70pF1iTj8P391fYNiuwTudwEAAAAAHJ/fh/0fKSoqSv369dOOHTvMdQCOrryXlJSYVfrExER5PB6Vl5efsE1xcXGbzzpw4IBPm6M/p7y8XA0NDW1GBAST0BCLutiaLwBwuz8AAAAACF4dKvy73W5t27ZNSUlJ6tGjhxITE7VixQpzv8fj0erVqzVkyBBJUkZGhsLDw33aFBYWasuWLWabzMxMVVZWasOGDWab9evXq7Ky0qfNli1bVFhYaLZZvny5bDabMjIyzuh39rfWRf8I/wAAAAAQvPw67H/u3LkaP368zj33XJWUlOh3v/udqqqqNHXqVFksFs2aNUsPP/ywevXqpV69eunhhx9WZGSkpkyZIklyuVy68847NWfOHMXGxiomJkZz585Vv379zNX/+/Tpo9GjR2v69OlatGiRJOmuu+7SuHHjlJaWJkkaOXKk+vbtq6ysLD366KMqKyvT3LlzNX369OOu9B8sHBFhKqyUqlj0DwAAAACCll/D/969e3XLLbfo4MGD6tatmwYPHqzc3FylpqZKku6//37V1dVpxowZKi8v16BBg7R8+XI5HA7zGE8++aTCwsI0adIk1dXVadiwYXrxxRcVGhpqtnn55Zc1c+ZM864AEyZM0MKFC839oaGhWrZsmWbMmKGhQ4fKbrdrypQpeuyxx87SL+E/rPgPAAAAAMHPYhiG4e9OBIuqqiq5XC5VVlYGzIiB21/YoPe3H9CCG/tr0mWBdatCAAAAAOjs2ptDO9Scf5x9jpbKP8P+AQAAACB4Ef47OaedBf8AAAAAINgR/js5Kv8AAAAAEPwI/53c4QX/qPwDAAAAQLAi/HdyjojmYf9VdVT+AQAAACBYEf47udbwT+UfAAAAAIIX4b+Tc9pbhv27qfwDAAAAQLAi/HdyTnPYP5V/AAAAAAhWhP9O7vCCf1T+AQAAACBYEf47ucO3+muUYRh+7g0AAAAA4Ewg/HdyrQv+eZsM1TV4/dwbAAAAAMCZQPjv5CKtoQoNsUhixX8AAAAACFaE/07OYrGY1f+qOub9AwAAAEAwIvzDXPSviso/AAAAAAQlwj8OV/5Z8R8AAAAAghLhH2b4Z84/AAAAAAQnwj/MYf/VVP4BAAAAICgR/iFH65z/Oir/AAAAABCMCP84Ytg/lX8AAAAACEaEf8hpbx32T+UfAAAAAIIR4R9ysto/AAAAAAQ1wj+OWPCPyj8AAAAABCPCP8w5/1V1VP4BAAAAIBgR/mGu9k/lHwAAAACCE+EfctpZ7R8AAAAAghnhH2blv4rKPwAAAAAEJcI/zNX+a9yN8jYZfu4NAAAAAOB0I/zDrPxLUg3VfwAAAAAIOoR/yBoWIltY86lQxbx/AAAAAAg6hH9Ikpx2VvwHAAAAgGBF+IckydEy75/KPwAAAAAEH8I/JEnOCCr/AAAAABCsCP+QdETlv47KPwAAAAAEG8I/JB1Z+Sf8AwAAAECwIfxDkuS0N1f+GfYPAAAAAMGH8A9JkqOl8s+CfwAAAAAQfAj/kCQ5I6j8AwAAAECwIvxDEpV/AAAAAAhmhH9IOrzaP5V/AAAAAAg+hH9IOrzafxXhHwAAAACCDuEfko6o/Ncx7B8AAAAAgk2HCf/z58+XxWLRrFmzzG3Tpk2TxWLxeQwePNjnfW63W/fdd5/i4uIUFRWlCRMmaO/evT5tysvLlZWVJZfLJZfLpaysLFVUVPi02bNnj8aPH6+oqCjFxcVp5syZ8ng8Z+rrdjgOKv8AAAAAELQ6RPjfuHGj/vznP6t///5t9o0ePVqFhYXm46233vLZP2vWLC1dulTZ2dlas2aNampqNG7cOHm9XrPNlClTlJ+fr5ycHOXk5Cg/P19ZWVnmfq/Xq7Fjx6q2tlZr1qxRdna2lixZojlz5py5L93BOO2tc/6p/AMAAABAsAnzdwdqamp066236vnnn9fvfve7NvttNpsSExOP+d7Kykr99a9/1eLFizV8+HBJ0j/+8Q+lpKTo3Xff1ahRo7Rt2zbl5OQoNzdXgwYNkiQ9//zzyszM1Pbt25WWlqbly5frs88+U0FBgZKTkyVJjz/+uKZNm6aHHnpITqfzDH37jqO18u9ubJK70StbWKifewQAAAAAOF38Xvm/5557NHbsWDO8H23VqlWKj49X7969NX36dJWUlJj78vLy1NDQoJEjR5rbkpOTlZ6errVr10qS1q1bJ5fLZQZ/SRo8eLBcLpdPm/T0dDP4S9KoUaPkdruVl5d33L673W5VVVX5PAKVwxYmi6X5OSv+AwAAAEBw8Wv4z87OVl5enubPn3/M/WPGjNHLL7+slStX6vHHH9fGjRt17bXXyu12S5KKiopktVoVHR3t876EhAQVFRWZbeLj49scOz4+3qdNQkKCz/7o6GhZrVazzbHMnz/fXEfA5XIpJSWl/V++gwkJsaiLtXkgSBWL/gEAAABAUPHbsP+CggL9+Mc/1vLlyxUREXHMNpMnTzafp6ena+DAgUpNTdWyZct0ww03HPfYhmHI0lrGlnyef5s2R3vggQc0e/Zs83VVVVVAXwBwRISp2t1I5R8AAAAAgozfKv95eXkqKSlRRkaGwsLCFBYWptWrV+vpp59WWFiYz4J9rZKSkpSamqodO3ZIkhITE+XxeFReXu7TrqSkxKzkJyYmqri4uM2xDhw44NPm6Ap/eXm5Ghoa2owIOJLNZpPT6fR5BDKnvXneP+EfAAAAAIKL38L/sGHDtHnzZuXn55uPgQMH6tZbb1V+fr5CQ9suOFdaWqqCggIlJSVJkjIyMhQeHq4VK1aYbQoLC7VlyxYNGTJEkpSZmanKykpt2LDBbLN+/XpVVlb6tNmyZYsKCwvNNsuXL5fNZlNGRsYZ+f4dkSOiZdg/K/4DAAAAQFDx27B/h8Oh9PR0n21RUVGKjY1Venq6ampqNG/ePN14441KSkrSrl279OCDDyouLk7XX3+9JMnlcunOO+/UnDlzFBsbq5iYGM2dO1f9+vUzFxDs06ePRo8erenTp2vRokWSpLvuukvjxo1TWlqaJGnkyJHq27evsrKy9Oijj6qsrExz587V9OnTA76afzKcEa2Vf8I/AAAAAAQTv6/2fzyhoaHavHmzrrvuOvXu3VtTp05V7969tW7dOjkcDrPdk08+qYkTJ2rSpEkaOnSoIiMj9eabb/qMHHj55ZfVr18/jRw5UiNHjlT//v21ePFin89atmyZIiIiNHToUE2aNEkTJ07UY489dla/s7+Zlf86hv0DAAAAQDCxGIZh+LsTwaKqqkoul0uVlZUBOWLgf17fosW5uzXz2gs0e2Sav7sDAAAAAPgG7c2hHbbyj7PPaW+d80/lHwAAAACCCeEfJkfLnH8W/AMAAACA4EL4h+nwgn9U/gEAAAAgmBD+YTq84B+VfwAAAAAIJoR/mFrDP5V/AAAAAAguhH+YnPaWYf9uKv8AAAAAEEwI/zA5zWH/VP4BAAAAIJgQ/mE6vOBfgwzD8HNvAAAAAACnC+EfptZb/TUZUq3H6+feAAAAAABOF8I/TBHhIQoLsUhqrv4DAAAAAIID4R8mi8VyeNE/VvwHAAAAgKBB+IcPh7noH5V/AAAAAAgWhH/4aA3/VP4BAAAAIHgQ/uGjdcX/Kub8AwAAAEDQIPzDhznsn8o/AAAAAAQNwj98tFb+We0fAAAAAIIH4R8+HK3D/uuo/AMAAABAsCD8w8fhBf+o/AMAAABAsCD8w4fT3jrsn8o/AAAAAAQLwj98HF7wj8o/AAAAAAQLwj98HF7wj8o/AAAAAAQLwj98OFsr/3VU/gEAAAAgWBD+4cNB5R8AAAAAgg7hHz6cdlb7BwAAAIBgQ/iHj9bKf63Hq0Zvk597AwAAAAA4HQj/8NG62r8k1bgZ+g8AAAAAwYDwDx/hoSGyh4dKkqrqCP8AAAAAEAwI/2ijtfpfxbx/AAAAAAgKhH+04bSz4j8AAAAABBPCP9qg8g8AAAAAwYXwjzZaV/yn8g8AAAAAwYHwjzacrZX/Oir/AAAAABAMCP9og8o/AAAAAAQXwj/acNqbK//VzPkHAAAAgKBA+EcbzpbKPwv+AQAAAEBwIPyjjdbV/hn2DwAAAADBgfCPNpzM+QcAAACAoEL4RxutlX+G/QMAAABAcCD8ow2nnco/AAAAAAQTwj/aMCv/dVT+AQAAACAYEP7RhoM5/wAAAAAQVAj/aMPZUvn3eJtU3+D1c28AAAAAAN9Whwn/8+fPl8Vi0axZs8xthmFo3rx5Sk5Olt1u19VXX62tW7f6vM/tduu+++5TXFycoqKiNGHCBO3du9enTXl5ubKysuRyueRyuZSVlaWKigqfNnv27NH48eMVFRWluLg4zZw5Ux6P50x93Q4tyhomi6X5OYv+AQAAAEDg6xDhf+PGjfrzn/+s/v37+2xfsGCBnnjiCS1cuFAbN25UYmKiRowYoerqarPNrFmztHTpUmVnZ2vNmjWqqanRuHHj5PUerlhPmTJF+fn5ysnJUU5OjvLz85WVlWXu93q9Gjt2rGpra7VmzRplZ2dryZIlmjNnzpn/8h1QSIhFDltz9Z+h/wAAAAAQ+Pwe/mtqanTrrbfq+eefV3R0tLndMAz94Q9/0C9+8QvdcMMNSk9P10svvaRDhw7plVdekSRVVlbqr3/9qx5//HENHz5cl1xyif7xj39o8+bNevfddyVJ27ZtU05Ojv7yl78oMzNTmZmZev755/Wf//xH27dvlyQtX75cn332mf7xj3/okksu0fDhw/X444/r+eefV1VV1dn/UTqA1nn/LPoHAAAAAIHP7+H/nnvu0dixYzV8+HCf7Tt37lRRUZFGjhxpbrPZbLrqqqu0du1aSVJeXp4aGhp82iQnJys9Pd1ss27dOrlcLg0aNMhsM3jwYLlcLp826enpSk5ONtuMGjVKbrdbeXl5x+272+1WVVWVzyNYtK74T+UfAAAAAAJfmD8/PDs7W3l5edq0aVObfUVFRZKkhIQEn+0JCQnavXu32cZqtfqMGGht0/r+oqIixcfHtzl+fHy8T5ujPyc6OlpWq9Vscyzz58/Xr3/962/6mgHJaWfFfwAAAAAIFn6r/BcUFOjHP/6xXn75ZUVERBy3naV15bkWhmG02Xa0o9scq/2ptDnaAw88oMrKSvNRUFBwwn4FktYV/1nwDwAAAAACn9/Cf15enkpKSpSRkaGwsDCFhYVp9erVevrppxUWFmZW4o+uvJeUlJj7EhMT5fF4VF5efsI2xcXFbT7/wIEDPm2O/pzy8nI1NDS0GRFwJJvNJqfT6fMIFs6I1so/4R8AAAAAAp3fwv+wYcO0efNm5efnm4+BAwfq1ltvVX5+vs4//3wlJiZqxYoV5ns8Ho9Wr16tIUOGSJIyMjIUHh7u06awsFBbtmwx22RmZqqyslIbNmww26xfv16VlZU+bbZs2aLCwkKzzfLly2Wz2ZSRkXFGf4eOqnXOf1Udw/4BAAAAIND5bc6/w+FQenq6z7aoqCjFxsaa22fNmqWHH35YvXr1Uq9evfTwww8rMjJSU6ZMkSS5XC7deeedmjNnjmJjYxUTE6O5c+eqX79+5gKCffr00ejRozV9+nQtWrRIknTXXXdp3LhxSktLkySNHDlSffv2VVZWlh599FGVlZVp7ty5mj59elBV80+Gg8o/AAAAAAQNvy74903uv/9+1dXVacaMGSovL9egQYO0fPlyORwOs82TTz6psLAwTZo0SXV1dRo2bJhefPFFhYaGmm1efvllzZw507wrwIQJE7Rw4UJzf2hoqJYtW6YZM2Zo6NChstvtmjJlih577LGz92U7GKed1f4BAAAAIFhYDMMw/N2JYFFVVSWXy6XKysqAHzHwzw179MBrmzW8T7z+MvUyf3cHAAAAAHAM7c2hfpvzj47NnPNP5R8AAAAAAh7hH8fUutp/VR1z/gEAAAAg0BH+cUytlX/m/AMAAABA4CP845icdlb7BwAAAIBgQfjHMZmVf3ejmppYExIAAAAAAhnhH8fUOuffMKRaD0P/AQAAACCQEf5xTLawEFlDm08P5v0DAAAAQGAj/OOYLBbLEbf7Y94/AAAAAAQywj+O6/Cif1T+AQAAACCQEf5xXGblv47KPwAAAAAEMsI/jstc8Z/KPwAAAAAENMI/jqt1xf9q5vwDAAAAQEAj/OO4Di/4R+UfAAAAAAIZ4R/H1Vr5Z7V/AAAAAAhshH8cl6M1/NdR+QcAAACAQEb4x3EdXvCPyj8AAAAABDLCP47LaW9d8I/KPwAAAAAEMsI/juvwgn9U/gEAAAAgkBH+cVyHb/VH5R8AAAAAAhnhH8dlVv7rqPwDAAAAQCAj/OO4qPwDAAAAQHAg/OO4nPbmyn9dg1cN3iY/9wYAAAAAcKoI/ziuLrYw8znVfwAAAAAIXIR/HFdYaIgiraGSpGpW/AcAAACAgEX4xwm1zvuvqqPyDwAAAACBivCPE2pd8Z/KPwAAAAAELsI/Tshpb6n8M+cfAAAAAAIW4R8n1Fr5r6LyDwAAAAABi/CPE3K0zPlntX8AAAAACFyEf5yQkzn/AAAAABDwCP84IQer/QMAAABAwCP844Scdir/AAAAABDoCP84IbPyT/gHAAAAgIBF+McJHZ7zz7B/AAAAAAhUhH+ckJPV/gEAAAAg4BH+cUKOlso/w/4BAAAAIHAR/nFCTjuVfwAAAAAIdKcc/hsbG/Xuu+9q0aJFqq6uliTt379fNTU1p61z8D+z8l/XIMMw/NwbAAAAAMCpCDuVN+3evVujR4/Wnj175Ha7NWLECDkcDi1YsED19fX605/+dLr7CT9pXe2/sclQfUOT7NZQP/cIAAAAAHCyTqny/+Mf/1gDBw5UeXm57Ha7uf3666/Xe++9d9o6B/+LsoYqxNL8vJp5/wAAAAAQkE6p8r9mzRp99NFHslqtPttTU1O1b9++09IxdAwWi0WOiHBV1jWoqr5B8c4If3cJAAAAAHCSTqny39TUJK/X22b73r175XA4vnWn0LEcXvGfRf8AAAAAIBCdUvgfMWKE/vCHP5ivLRaLampq9Ktf/Urf/e53232c5557Tv3795fT6ZTT6VRmZqbefvttc/+0adNksVh8HoMHD/Y5htvt1n333ae4uDhFRUVpwoQJ2rt3r0+b8vJyZWVlyeVyyeVyKSsrSxUVFT5t9uzZo/HjxysqKkpxcXGaOXOmPB5P+3+UIOZsmfdfVcewfwAAAAAIRKcU/p988kmtXr1affv2VX19vaZMmaLzzjtP+/bt0yOPPNLu43Tv3l2///3vtWnTJm3atEnXXnutrrvuOm3dutVsM3r0aBUWFpqPt956y+cYs2bN0tKlS5Wdna01a9aopqZG48aN8xmZMGXKFOXn5ysnJ0c5OTnKz89XVlaWud/r9Wrs2LGqra3VmjVrlJ2drSVLlmjOnDmn8vMEndbKP7f7AwAAAIDAZDFO8f5tdXV1ys7OVl5enpqamnTppZfq1ltv9VkA8FTExMTo0Ucf1Z133qlp06apoqJCr7/++jHbVlZWqlu3blq8eLEmT54sqfl2gykpKXrrrbc0atQobdu2TX379lVubq4GDRokScrNzVVmZqY+//xzpaWl6e2339a4ceNUUFCg5ORkSVJ2dramTZumkpISOZ3OY36+2+2W2+02X1dVVSklJUWVlZXHfU8gmv73TVrxWbEevr6fpgw619/dAQAAAAC0qKqqksvl+sYcekqVf0my2+26/fbbtXDhQj377LP6wQ9+8K2Cv9frVXZ2tmpra5WZmWluX7VqleLj49W7d29Nnz5dJSUl5r68vDw1NDRo5MiR5rbk5GSlp6dr7dq1kqR169bJ5XKZwV+SBg8eLJfL5dMmPT3dDP6SNGrUKLndbuXl5R23z/PnzzenErhcLqWkpJzy9+/IDs/5Z9g/AAAAAASiUwr/L730kpYtW2a+vv/++9W1a1cNGTJEu3fvPqljbd68WV26dJHNZtOPfvQjLV26VH379pUkjRkzRi+//LJWrlypxx9/XBs3btS1115rVtuLiopktVoVHR3tc8yEhAQVFRWZbeLj49t8bnx8vE+bhIQEn/3R0dGyWq1mm2N54IEHVFlZaT4KCgpO6rsHitY5/9zqDwAAAAAC0ymF/4cfftis8q9bt04LFy7UggULFBcXp5/85Ccnday0tDTl5+crNzdXd999t6ZOnarPPvtMkjR58mSNHTtW6enpGj9+vN5++2198cUXPhcejsUwDFksFvP1kc+/TZuj2Ww2c7HC1kcwcrZW/uuY8w8AAAAAgeiUwn9BQYEuuOACSdLrr7+um266SXfddZfmz5+vDz/88KSOZbVadcEFF2jgwIGaP3++BgwYoKeeeuqYbZOSkpSamqodO3ZIkhITE+XxeFReXu7TrqSkxKzkJyYmqri4uM2xDhw44NPm6Ap/eXm5Ghoa2owI6IwcVP4BAAAAIKCdUvjv0qWLSktLJUnLly/X8OHDJUkRERGqq6v7Vh0yDMNnEb0jlZaWqqCgQElJSZKkjIwMhYeHa8WKFWabwsJCbdmyRUOGDJEkZWZmqrKyUhs2bDDbrF+/XpWVlT5ttmzZosLCQrPN8uXLZbPZlJGR8a2+TzBw2lntHwAAAAACWdipvGnEiBH6wQ9+oEsuuURffPGFxo4dK0naunWrUlNT232cBx98UGPGjFFKSoqqq6uVnZ2tVatWKScnRzU1NZo3b55uvPFGJSUladeuXXrwwQcVFxen66+/XpLkcrl05513as6cOYqNjVVMTIzmzp2rfv36mRck+vTpo9GjR2v69OlatGiRJOmuu+7SuHHjlJaWJkkaOXKk+vbtq6ysLD366KMqKyvT3LlzNX369KAdyn8yWiv/LPgHAAAAAIHplCr/f/zjH5WZmakDBw5oyZIlio2NldS8+v6UKVPafZzi4mJlZWUpLS1Nw4YN0/r165WTk6MRI0YoNDRUmzdv1nXXXafevXtr6tSp6t27t9atWyeHw2Ee48knn9TEiRM1adIkDR06VJGRkXrzzTcVGhpqtnn55ZfVr18/jRw5UiNHjlT//v21ePFic39oaKiWLVumiIgIDR06VJMmTdLEiRP12GOPncrPE3RaV/un8g8AAAAAgcliGIZxKm+sr6/Xp59+qpKSEjU1NfnsmzBhwmnpXKBp7/0VA80nBRW67o8f6Zyudn3082v93R0AAAAAQIv25tBTGvafk5Oj2267TaWlpTr62oHFYpHX6z2Vw6KDcpir/TPsHwAAAAAC0SkN+7/33nt18803a//+/WpqavJ5EPyDj9PePOe/xtOopqZTGigCAAAAAPCjUwr/JSUlmj17NrfB6yRaK/+GIVW7mfcPAAAAAIHmlML/TTfdpFWrVp3mrqCjsoWFyhrWfKpUs+I/AAAAAAScU5rzv3DhQt1888368MMP1a9fP4WHh/vsnzlz5mnpHDoOZ0S4Dta4WfEfAAAAAALQKYX/V155Re+8847sdrtWrVoli8Vi7rNYLIT/IOSMCNPBGjeL/gEAAABAADql8P/LX/5Sv/nNb/Tzn/9cISGnNHMAAcbRsugflX8AAAAACDynlNw9Ho8mT55M8O9EnK23+2POPwAAAAAEnFNK71OnTtWrr756uvuCDqx1xX8q/wAAAAAQeE5p2L/X69WCBQv0zjvvqH///m0W/HviiSdOS+fQcTgjWof9U/kHAAAAgEBzSuF/8+bNuuSSSyRJW7Zs8dl35OJ/CB4Oc9g/lX8AAAAACDSnFP7ff//9090PdHAOKv8AAAAAELBYsQ/tYi74V0flHwAAAAACDeEf7dJa+We1fwAAAAAIPIR/tIvT3jrsn8o/AAAAAAQawj/a5fCCf1T+AQAAACDQEP7RLq3hn8o/AAAAAAQewj/axdk657+Oyj8AAAAABBrCP9qlNfy7G5vkaWzyc28AAAAAACeD8I926dIy7F+Sqpn3DwAAAAABhfCPdgkNsaiLrXXRP+b9AwAAAEAgIfyj3Q4v+kflHwAAAAACCeEf7dY6758V/wEAAAAgsBD+0W6tlX9W/AcAAACAwEL4R7s57VT+AQAAACAQEf7Rbmblnzn/AAAAABBQCP9ot8Phn8o/AAAAAAQSwj/a7fCCf1T+AQAAACCQEP7Rbo6W8F9VR+UfAAAAAAIJ4R/t5rQ3D/un8g8AAAAAgYXwj3YzK/+EfwAAAAAIKIR/tFvrgn/c6g8AAAAAAgvhH+12eME/wj8AAAAABBLCP9rNad7qj2H/AAAAABBICP9oN8cRlX/DMPzcGwAAAABAexH+0W6tq/17mwwd8nj93BsAAAAAQHsR/tFu9vBQhYZYJDHvHwAAAAACCeEf7WaxWMx5/9XM+wcAAACAgEH4x0lpnffPon8AAAAAEDgI/zgpDnPFf4b9AwAAAECgIPzjpDhbK/91VP4BAAAAIFD4Nfw/99xz6t+/v5xOp5xOpzIzM/X222+b+w3D0Lx585ScnCy73a6rr75aW7du9TmG2+3Wfffdp7i4OEVFRWnChAnau3evT5vy8nJlZWXJ5XLJ5XIpKytLFRUVPm327Nmj8ePHKyoqSnFxcZo5c6Y8Hs8Z++6BymHO+afyDwAAAACBwq/hv3v37vr973+vTZs2adOmTbr22mt13XXXmQF/wYIFeuKJJ7Rw4UJt3LhRiYmJGjFihKqrq81jzJo1S0uXLlV2drbWrFmjmpoajRs3Tl7v4VvRTZkyRfn5+crJyVFOTo7y8/OVlZVl7vd6vRo7dqxqa2u1Zs0aZWdna8mSJZozZ87Z+zEChNPeXPkn/AMAAABA4LAYhmH4uxNHiomJ0aOPPqo77rhDycnJmjVrln72s59Jaq7yJyQk6JFHHtEPf/hDVVZWqlu3blq8eLEmT54sSdq/f79SUlL01ltvadSoUdq2bZv69u2r3NxcDRo0SJKUm5urzMxMff7550pLS9Pbb7+tcePGqaCgQMnJyZKk7OxsTZs2TSUlJXI6ne3qe1VVlVwulyorK9v9nkDz6ze36oWPdunuq3vqZ6Mv9Hd3AAAAAKBTa28O7TBz/r1er7Kzs1VbW6vMzEzt3LlTRUVFGjlypNnGZrPpqquu0tq1ayVJeXl5amho8GmTnJys9PR0s826devkcrnM4C9JgwcPlsvl8mmTnp5uBn9JGjVqlNxut/Ly8o7bZ7fbraqqKp9HsGtd7Z9b/QEAAABA4PB7+N+8ebO6dOkim82mH/3oR1q6dKn69u2roqIiSVJCQoJP+4SEBHNfUVGRrFaroqOjT9gmPj6+zefGx8f7tDn6c6Kjo2W1Ws02xzJ//nxzHQGXy6WUlJST/PaBx8mcfwAAAAAIOH4P/2lpacrPz1dubq7uvvtuTZ06VZ999pm532Kx+LQ3DKPNtqMd3eZY7U+lzdEeeOABVVZWmo+CgoIT9isYsNo/AAAAAAQev4d/q9WqCy64QAMHDtT8+fM1YMAAPfXUU0pMTJSkNpX3kpISs0qfmJgoj8ej8vLyE7YpLi5u87kHDhzwaXP055SXl6uhoaHNiIAj2Ww2804FrY9g57RT+QcAAACAQOP38H80wzDkdrvVo0cPJSYmasWKFeY+j8ej1atXa8iQIZKkjIwMhYeH+7QpLCzUli1bzDaZmZmqrKzUhg0bzDbr169XZWWlT5stW7aosLDQbLN8+XLZbDZlZGSc0e8baFrn/Fcx5x8AAAAAAkaYPz/8wQcf1JgxY5SSkqLq6mplZ2dr1apVysnJkcVi0axZs/Twww+rV69e6tWrlx5++GFFRkZqypQpkiSXy6U777xTc+bMUWxsrGJiYjR37lz169dPw4cPlyT16dNHo0eP1vTp07Vo0SJJ0l133aVx48YpLS1NkjRy5Ej17dtXWVlZevTRR1VWVqa5c+dq+vTpnaKafzIczPkHAAAAgIDj1/BfXFysrKwsFRYWyuVyqX///srJydGIESMkSffff7/q6uo0Y8YMlZeXa9CgQVq+fLkcDod5jCeffFJhYWGaNGmS6urqNGzYML344osKDQ0127z88suaOXOmeVeACRMmaOHCheb+0NBQLVu2TDNmzNDQoUNlt9s1ZcoUPfbYY2fplwgcTnO1f8I/AAAAAAQKi2EYhr87ESzae3/FQFZa41bG796VJH318HcVGnLixRcBAAAAAGdOe3Noh5vzj46tdc6/JNVQ/QcAAACAgED4x0mxhoUoIrz5tGHRPwAAAAAIDIR/nDRW/AcAAACAwEL4x0lzsuI/AAAAAAQUwj9Omln5r6PyDwAAAACBgPCPk+ag8g8AAAAAAYXwj5PmtDPnHwAAAAACCeEfJ405/wAAAAAQWAj/OGnOljn/1VT+AQAAACAgEP5x0lrn/FfVUfkHAAAAgEBA+MdJa13tv9pN5R8AAAAAAgHhHyfNaWfOPwAAAAAEEsI/TprD1rLafx2VfwAAAAAIBIR/nLTWW/1R+QcAAACAwED4x0kzF/xjtX8AAAAACAiEf5y0w+Gfyj8AAAAABALCP05a67B/T2OT6hu8fu4NAAAAAOCbEP5x0rpYw2SxND9n3j8AAAAAdHyEf5y0kBCLuthab/fHvH8AAAAA6OgI/zglrpah/xt2lvm5JwAAAACAb0L4xym5KaO7JOlXb2zVJwUV/u0MAAAAAOCECP84Jfdd20vDLoyXu7FJdy3epOKqen93CQAAAABwHIR/nJLQEIv+8L2L1Su+i4qr3LprcR4r/wMAAABAB0X4xylzRITrL1MHymUP1ycFFXrgtc0yDMPf3QIAAAAAHIXwj28lNTZKz916qUJDLFr68T79+YOv/d0lAAAAAMBRCP/41oZcEKdfje8rSfp9zuda+Xmxn3sEAAAAADgS4R+nRdbgVN1y+bkyDGnmP/P1ZUm1v7sEAAAAAGhB+MdpYbFY9OsJF+nyHjGqcTfqBy9tUsUhj7+7BQAAAAAQ4R+nkTUsRM/deqm6R9u1q/SQ7n3lYzV6m/zdLQAAAADo9Aj/OK1iu9j0/G0DFWkN1ZovD+p3y7b5u0sAAAAA0OkR/nHa9Uly6olJF0uSXly7S9kb9vi3QwAAAADQyRH+cUaMTk/U7BG9JUn/8+8t2rirzM89AgAAAIDOi/CPM+a+ay/Q2H5JavAa+tHiPO0tP+TvLgEAAABAp0T4xxljsVj02M0DdFGyU6W1Hk3/e55q3Y3+7hYAAAAAdDqEf5xRdmuonr9toOK6WLWtsEpz/+8TNTUZ/u4WAAAAAHQqhH+cccld7VqUlaHwUIve3lKkp1fu8HeXAAAAAKBTIfzjrMhIjdFD1/eTJP3h3R16e3Ohn3sEAAAAAJ0H4R9nzaSBKbrzih6SpNn/+kRb91f6uUcAAAAA0DkQ/nFWPTDmQl3Zu5vqGry66+95Oljj9neXAAAAACDoEf5xVoWFhuiZWy7R+XFR2ldRp7v/kSdPY5O/uwUAAAAAQY3wj7POZQ/X81MHyhERpo27yrkDAAAAAACcYYR/+EXPbl30xymXKizEojc+2a9fv7lVhsEFAAAAAAA4E/wa/ufPn6/LLrtMDodD8fHxmjhxorZv3+7TZtq0abJYLD6PwYMH+7Rxu9267777FBcXp6ioKE2YMEF79+71aVNeXq6srCy5XC65XC5lZWWpoqLCp82ePXs0fvx4RUVFKS4uTjNnzpTH4zkj3x3Slb276fFJA2SxSC+t262n3/vS310CAAAAgKDk1/C/evVq3XPPPcrNzdWKFSvU2NiokSNHqra21qfd6NGjVVhYaD7eeustn/2zZs3S0qVLlZ2drTVr1qimpkbjxo2T1+s120yZMkX5+fnKyclRTk6O8vPzlZWVZe73er0aO3asamtrtWbNGmVnZ2vJkiWaM2fOmf0ROrnrLj5H88ZfJEl68t0vtHjdLv92CAAAAACCkMXoQGOtDxw4oPj4eK1evVpXXnmlpObKf0VFhV5//fVjvqeyslLdunXT4sWLNXnyZEnS/v37lZKSorfeekujRo3Stm3b1LdvX+Xm5mrQoEGSpNzcXGVmZurzzz9XWlqa3n77bY0bN04FBQVKTk6WJGVnZ2vatGkqKSmR0+n8xv5XVVXJ5XKpsrKyXe1x2JMrvtBT7+2QxSI99b1LNGFAsr+7BAAAAAAdXntzaIea819Z2Xzf95iYGJ/tq1atUnx8vHr37q3p06erpKTE3JeXl6eGhgaNHDnS3JacnKz09HStXbtWkrRu3Tq5XC4z+EvS4MGD5XK5fNqkp6ebwV+SRo0aJbfbrby8vGP21+12q6qqyueBUzNreC/dlpkqw5Dm/CtfH3xxwN9dAgAAAICg0WHCv2EYmj17tq644gqlp6eb28eMGaOXX35ZK1eu1OOPP66NGzfq2muvldvdfH/4oqIiWa1WRUdH+xwvISFBRUVFZpv4+Pg2nxkfH+/TJiEhwWd/dHS0rFar2eZo8+fPN9cQcLlcSklJOfUfoJOzWCyaN/4ijR+QrAavoR8uztN/95T7u1sAAAAAEBQ6TPi/99579emnn+qf//ynz/bJkydr7NixSk9P1/jx4/X222/riy++0LJly054PMMwZLFYzNdHPv82bY70wAMPqLKy0nwUFBScsE84sZAQix6/eYCu7N1NdQ1e3fHiRu0orvZ3twAAAAAg4HWI8H/ffffpjTfe0Pvvv6/u3bufsG1SUpJSU1O1Y8cOSVJiYqI8Ho/Ky32rxCUlJWYlPzExUcXFxW2OdeDAAZ82R1f4y8vL1dDQ0GZEQCubzSan0+nzwLdjDQvRn75/qS5O6aqKQw3K+usG7S0/5O9uAQAAAEBA82v4NwxD9957r1577TWtXLlSPXr0+Mb3lJaWqqCgQElJSZKkjIwMhYeHa8WKFWabwsJCbdmyRUOGDJEkZWZmqrKyUhs2bDDbrF+/XpWVlT5ttmzZosLCQrPN8uXLZbPZlJGRcVq+L9on0hqmF6Zdpl7xXVRUVa/b/rpBpTVuf3cLAAAAAAKWX1f7nzFjhl555RX9+9//Vlpamrnd5XLJbrerpqZG8+bN04033qikpCTt2rVLDz74oPbs2aNt27bJ4XBIku6++2795z//0YsvvqiYmBjNnTtXpaWlysvLU2hoqKTmtQP279+vRYsWSZLuuusupaam6s0335TUfKu/iy++WAkJCXr00UdVVlamadOmaeLEiXrmmWfa9X1Y7f/0Kqys003PrdO+ijr1O8elf941WF1sYf7uFgAAAAB0GO3NoX4N/8ebS//CCy9o2rRpqqur08SJE/Xxxx+roqJCSUlJuuaaa/Tb3/7WZ3G9+vp6/fSnP9Urr7yiuro6DRs2TM8++6xPm7KyMs2cOVNvvPGGJGnChAlauHChunbtarbZs2ePZsyYoZUrV8put2vKlCl67LHHZLPZ2vV9CP+n39cHanTTn9aprNajIT1j9bdplykiPNTf3QIAAACADiEgwn+wIfyfGZv3Vup7f16nWo9Xoy9K1B9vvVShIce+cAQAAAAAnUl7c2iHWPAPOJF+3V16fupAWUNDlLO1SL9YullcswIAAACA9iP8IyAM6Rmnp2+5WCEWKXtjgR59Z7u/uwQAAAAAAYPwj4AxOj1JD1/fT5L07Kqv9JcPv/ZzjwAAAAAgMBD+EVC+d/m5un90850hfrdsm5bk7fVzjwAAAACg4yP8I+DcfVVPTf9OD0nS/Us+1bufFfu5RwAAAADQsRH+EXAsFose/G4f3Xhpd3mbDN3zyn/14Y4D/u4WAAAAAHRYhH8EJIvFokdu7KfhfeLlbmzSbX/boN+8+ZnqPF5/dw0AAAAAOhzCPwJWWGiIFk65VJMHpsgwpL99tFNjn/5QebvL/d01AAAAAOhQCP8IaBHhoXrkpv564fbLlOC06euDtbr5T2s1/61tqm9gFAAAAAAASIR/BIlr0uK1fNZVuuHSc9RkSIs++FrjnlmjTwoq/N01AAAAAPA7wj+ChisyXE9MuljP3zZQcV1s+rKkRjc8t1aPvvO53I2MAgAAAADQeRH+EXRG9E3Qip9cqQkDkuVtMvTH97/SdQs/0pZ9lf7uGgAAAAD4BeEfQSk6yqqnb7lEz916qWKirPq8qFoT//iR/vDuF2rwNvm7ewAAAABwVhH+EdTG9EvS8p9cqTHpiWpsMvSHd3do4h8/0rbCKn93DQAAAADOGsI/gl5cF5uevfVSPXPLJeoaGa6t+6s0YeEaLVy5Q42MAgAAAADQCRD+0SlYLBaNH5Cs5T+5UsP7JKjBa+ix5V/ohufWakdxtb+7BwAAAABnFOEfnUq8I0LP35ahJyYNkDMiTJ/urdTYZ9Zo0eqv5G0y/N09AAAAADgjCP/odCwWi264tLuW/+QqXZPWTZ7GJs1/+3NNXrROhZV1/u4eAAAAAJx2hH90WomuCP1t2mVacFN/OWxh2rS7XOOeXqM1Ow76u2sAAAAAcFoR/tGpWSwWTRqYov/MvEJ9k5wqrfUo62/r9cx7O9TENAAAAAAAQYLwD0hKjY3SazOGaPLAFBmG9PiKL3TnSxtVccjj764BAAAAwLdG+AdaRISH6pGb+mvBTf1lCwvR+9sPaOzTa/Tp3gp/dw0AAAAAvhXCP3CUSQNT9NqMIUqNjdS+ijrd9Nw6/SN3twyDaQAAAAAAAhPhHziGi5JdevO+KzSyb4I83ib98vUtmv2vT3TI0+jvrgEAAADASSP8A8fhjAjXoqwMPfjdCxUaYtHSj/dp4h8/0lcHavzdNQAAAAA4KYR/4AQsFovuurKnXvnBIHVz2PRFcY0mPLNGyz4t9HfXAAAAAKDdCP9AOww6P1bLZl6hQT1iVOvx6p5X/qvfvPmZGrxN/u4aAAAAAHwjwj/QTvGOCL38g0H60VU9JUl/+2invvfnXBVW1vm5ZwAAAABwYoR/4CSEhYbo52Mu1PO3DZQjIkx5u8s17uk1WrPjoL+7BgAAAADHRfgHTsGIvgn6z31XqG+SU6W1HmX9bb2eeW+Hmpq4HSAAAACAjofwD5yi1NgovTZjiL53WYoMQ3p8xRea9uJGbS+q9nfXAAAAAMCHxTAMSpWnSVVVlVwulyorK+V0Ov3dHZxF/7epQL98fYvcjc0LAI7sm6B7r71A/bt39W/HAAAAAAS19uZQwv9pRPjv3HYUV+vJd7/Q21uK1PpP1Xd6xemeay7QoB4xslgs/u0gAAAAgKBD+PcDwj8k6cuSaj236mu9nr9P3pY1AAamRuueay/Q1b27cREAAAAAwGlD+PcDwj+OVFB2SIs++Er/2rRXnpbpAOnnOHXP1Rdo1EWJCgnhIgAAAACAb4fw7weEfxxLSVW9nv/wa728fo8OebySpJ7dojTj6gs04eJkhYey7iYAAACAU0P49wPCP06kvNajFz7aqRfX7lJVfaMkqXu0XT+6qqduyuiuiPBQP/cQAAAAQKAh/PsB4R/tUV3foMW5u/XXD3eqtNYjSYp32HTXledryqBzFWkN83MPAQAAAAQKwr8fEP5xMuo8Xr26cY8WffC1CivrJUnRkeG6fWgPTR1ynlz2cD/3EAAAAEBHR/j3A8I/ToWnsUlLP96r51Z9pV2lhyRJDluYpg09T3cM7aHoKKufewgAAACgoyL8+wHhH99Go7dJyzYX6o/vf6kvimskSVHWUGVlnqfp3+mh2C42P/cQAAAAQEdD+PcDwj9Oh6YmQ+9sLdLTK7/UtsIqSZI9PFTfH3yupl95vuIdEX7uIQAAAICOor051K/3GJs/f74uu+wyORwOxcfHa+LEidq+fbtPG8MwNG/ePCUnJ8tut+vqq6/W1q1bfdq43W7dd999iouLU1RUlCZMmKC9e/f6tCkvL1dWVpZcLpdcLpeysrJUUVHh02bPnj0aP368oqKiFBcXp5kzZ8rj8ZyR7w4cT0iIRWP6JemtmVfo+dsGqn93l+oavHr+w536ziPva94bW1XUskYAAAAAALSHX8P/6tWrdc899yg3N1crVqxQY2OjRo4cqdraWrPNggUL9MQTT2jhwoXauHGjEhMTNWLECFVXV5ttZs2apaVLlyo7O1tr1qxRTU2Nxo0bJ6/Xa7aZMmWK8vPzlZOTo5ycHOXn5ysrK8vc7/V6NXbsWNXW1mrNmjXKzs7WkiVLNGfOnLPzYwBHsVgsGtE3Qf++Z6heuP0yXXJuV7kbm/Ti2l26csH7+uXrm7W3/JC/uwkAAAAgAHSoYf8HDhxQfHy8Vq9erSuvvFKGYSg5OVmzZs3Sz372M0nNVf6EhAQ98sgj+uEPf6jKykp169ZNixcv1uTJkyVJ+/fvV0pKit566y2NGjVK27ZtU9++fZWbm6tBgwZJknJzc5WZmanPP/9caWlpevvttzVu3DgVFBQoOTlZkpSdna1p06appKTkmMMn3G633G63+bqqqkopKSkM+8cZYRiGPvqyVE+/t0MbdpVJksJCLLopo7tmXH2Bzo2N9HMPAQAAAJxtATHs/2iVlZWSpJiYGEnSzp07VVRUpJEjR5ptbDabrrrqKq1du1aSlJeXp4aGBp82ycnJSk9PN9usW7dOLpfLDP6SNHjwYLlcLp826enpZvCXpFGjRsntdisvL++Y/Z0/f745jcDlciklJeV0/AzAMVksFl3RK07/+lGmsu8arKEXxKqxyVD2xgJd8/gqzfnXJ/r6QI2/uwkAAACgA+ow4d8wDM2ePVtXXHGF0tPTJUlFRUWSpISEBJ+2CQkJ5r6ioiJZrVZFR0efsE18fHybz4yPj/dpc/TnREdHy2q1mm2O9sADD6iystJ8FBQUnOzXBk7J4PNj9fIPBmvJ3Zm6qnc3eZsMLfnvXg1/YrVm/vNj7Siu/uaDAAAAAOg0wvzdgVb33nuvPv30U61Zs6bNPovF4vPaMIw22452dJtjtT+VNkey2Wyy2bj9GvwnIzVGL91xufILKrRw5Q69u61Eb3yyX29+ul9Jzgh1jbQqOipcXSOt6moPV3SkVV0jm/+2bo+OtCo6MlzOiHCFhJz4nysAAAAAgalDhP/77rtPb7zxhj744AN1797d3J6YmCipuSqflJRkbi8pKTGr9ImJifJ4PCovL/ep/peUlGjIkCFmm+Li4jafe+DAAZ/jrF+/3md/eXm5Ghoa2owIADqai1O66i9TL9OWfZVauPJL5Wwt0v7Keu0/ibsCWCyS66gLBBfEd9GwC+OVkRqtsNAOM1AIAAAAwEnya/g3DEP33Xefli5dqlWrVqlHjx4++3v06KHExEStWLFCl1xyiSTJ4/Fo9erVeuSRRyRJGRkZCg8P14oVKzRp0iRJUmFhobZs2aIFCxZIkjIzM1VZWakNGzbo8ssvlyStX79elZWV5gWCzMxMPfTQQyosLDQvNCxfvlw2m00ZGRln/scAToP0c1z6U1aGiqvqVVhZr/JDHlUc8qi8tkEVdQ3Nzw+1/vWo4lCDKg41qMbdKMOQ+brVys9L9OcPvlZ0ZLiuuTBeI/ok6Du9u6mLrUNcNwQAAADQTn5d7X/GjBl65ZVX9O9//1tpaWnmdpfLJbvdLkl65JFHNH/+fL3wwgvq1auXHn74Ya1atUrbt2+Xw+GQJN199936z3/+oxdffFExMTGaO3euSktLlZeXp9DQUEnSmDFjtH//fi1atEiSdNdddyk1NVVvvvmmpOZb/V188cVKSEjQo48+qrKyMk2bNk0TJ07UM888067v095VFoGOxtPYpIq6wxcDyg95VFbr0cZdZVr5eYnPBQFraIgye8ZqeN8EDe8TrySX3Y89BwAAADq39uZQv4b/482lf+GFFzRt2jRJzaMDfv3rX2vRokUqLy/XoEGD9Mc//tFcFFCS6uvr9dOf/lSvvPKK6urqNGzYMD377LM+q++XlZVp5syZeuONNyRJEyZM0MKFC9W1a1ezzZ49ezRjxgytXLlSdrtdU6ZM0WOPPdbuef2EfwSjRm+T8naX691txVrxWbF2lR7y2Z9+jlPD+yRoRN8E9U1yfuN6HAAAAABOn4AI/8GG8I9gZxiGvjpQq3e3Fevdz4qVt6dcR/4bJNkV0TIiIEGDzo+RLSzUf50FAAAAOgHCvx8Q/tHZHKxxa+XnJXr3s2J9uOOg6hq85r4utjBd1bubRqUnakx6osJZMBAAAAA47Qj/fkD4R2dW3+DV2q8OasVnxXp3W4kOVLvNfd2j7brnmgt046XdZQ3jIgAAAABwuhD+/YDwDzRrajL06b5KrfisSK9uLNDBGo+k5mkBd1/dUzcPTFFEOFMCAAAAgG+L8O8HhH+grTqPV69s2KNFq79SSctogASnTT+8sqduufxc2a1cBAAAAABOFeHfDwj/wPHVN3j1r00Fem7VVyqsrJckxXWx6q4rz9etg1IVZQvzcw8BAACAwEP49wPCP/DN3I1eLcnbp2dXfam95XWSpOjIcP3gO+frtsxUOSLC/dxDAAAAIHAQ/v2A8A+0X4O3SUs/3qdn3/9Su0oPSZKcEWG644oeun1ID7kiuQgAAAAAfBPCvx8Q/oGT1+ht0puf7tfClV/qqwO1kiSHLUxTh5ynO6/ooegoq597CAAAAHRchH8/IPwDp87bZOitzYVauPJLbS+uliRFWkOVlZmq6d85X3FdbH7uIQAAANDxEP79gPAPfHtNTYaWf1akp9/7Up8VVkmSbGEhGnR+rAafH6PB58eq3zkuhYeG+LmnAAAAgP8R/v2A8A+cPoZh6L1tJXpm5Q59srfSZ1+kNVQDz4vhYgAAAAA6PcK/HxD+gdPPMAxtK6xW7telyv26VOt3lqmyrsGnDRcDAAAA0FkR/v2A8A+ceU1NhrYX+14MqDjU9mJARmq0Bp8fq8Hnx6p/dy4GAAAAIDgR/v2A8A+cfUdfDNiws0zlx7kYcE5XuyLCQ2W3hsoe3vKw+v6NCA9VpNX3devz0BCLpObRCO7GppaHV+6GI543NrW89h5u0+D1ae9pbJK3yVBjkyFvk6EG7xGvva3bm9Rw1OvW9o1eQ6EhFo3om6CbBnaXM4LbIgIAAHRWhH8/IPwD/tfUZOiLkmrlflWq3K/LtH5naZuLAafKGtY8esDT2HRajnc6RFpDNfGSc3RbZqouTOTfOwAAAJ0N4d8PCP9Ax9N6MWDTrnJVHPKorsGrOk9Ty9/G5r8NTar3eFXX4NUhT6PqG1r3N287EYul+W4EtrDQ5r/hRzxv3R4e4tPGGhai8NAQhYZYFBZiOeJviMJCj9oWGqKwludhoS1tQiwqqarXKxv26IviGrMvl/eI0W2ZqRp1USLTHAAAADoJwr8fEP6B4NM6xP+Qp/nCgMVi8Qn24aEWWSwWv/Vt/c4y/X3dLr2ztVjepuZ/ncc7bJoy6FxNufxcxTsj/NI3AAAAnB2Efz8g/APwl6LK5pEAr6zfo4M1bklSWIhFo9ITddvgVF3eI8ZvFykAAABw5hD+/YDwD8DfPI1NytlapMXrdmnjrnJz+4WJDmVlpmrixecoyhbmxx4CAADgdCL8+wHhH0BH8tn+Ki3O3aXXP95vrl3giAjTTRndlTU4Ved363LC9zd6m1TjblR1faMq6xpUXd+oqvoGVR3xvLq+UaEhFsVGWRUTZVVsF6tio2zm80jr6bnQ0Oht0oEat4oq61Vc5VZxVb2Kq+pVVFWvkiq3iqrqVVnXoPRkp4ZeEKchPeN0YaJDISGMdgAAAMGN8O8HhH8AHVHloQb9X16B/pG7W7tKD5nbv9MrTqmxkc1B/qhAX1XXoFrPiRc7bA97eOgRFwWsiomyHfH88MUCa1iISqrdKq5sDvTF5qM52B+scetk/98qNsqqzJ6xGnpBnK64IE4pMZHf+vsAAAB0NIR/PyD8A+jImpoMfbDjgBav262V20vaHaYjwkPkjAiXIyJMTnu4HBHhckaEmX+9TYbKaj06WOtRWa1bZTXNz0/3LRHDQiyKd9gU74xQojNCCU6bElwRSnBEKNEVoYjwUOXtLtNHX5Zqw86yNndqSImx64qWUQFDesYqtovttPYPAADAHwj/fkD4BxAoCsoO6d/5++TxGnJGhMkZES6nvTXQNwd9R0vAt4ad/G0DDcNQrcershqPSmvdKq3xqKzWo9Jaj0pr3ObzspbX7sYmdXPYlHCcYB/vtCkuytbuYfyexiZ9vKdcH31VqrVfHlR+QYUam3z/765PklNDW0YGXN4j5hvXQmjwNqms1qMD1W4drHHrYI2n+e/Rr2vcirKFaWBqjC7vEa3Le8TqvNhIFlwEAABnBOHfDwj/ANAx1bgbtWFnqT76slQffXlQnxdV++wPC7HoknO7KrNnnCLCQ3Sw+nCQP1jj1oFqt8oPNZzy58d1senyHtG67LwYXd4jRhcmOhXKegQAAOA0IPz7AeEfAALDwRq31raMCvjoq4MqKKtr1/tCLFJsF5viutgU18Wqbl1sinM0P48zt9tUUl2vjbvKtHFnufILKuTx+k6BcNjClHFetC7vEaPLz4tRv+4u2cJCz8RX9Rtvk6H/7inXu58Va9X2A7KGhShrcKquuyQ56L4rAAD+RPj3A8I/AASmgrJD+ujLg9qws0wWi0VxjpZg3/pwNIf76EjrSVfs6xu8+nRvpTbuKtP6nWX67+5y1bgbfdrYwkJ0cUpXXd4jRpedF6NLU6PV5RumIXibDDV4m+TxNqmhsUkN3iNee5vU0GjIkKEecVFyRISf9G9yKqrrG/ThjoN697Nivb+95JijJeIdNt0+tIemDDpXLvvZ6RcAAMGM8O8HhH8AwDdp9Dbp86Jqrd9Zpo07y7RxV5lKaz0+bUJDLEqNjZQMHQ7zXkMNjYfDfVM7/9/bYpF6xEWp/zku9eveVf3OcemiZOc3rnHQXnvLD+m9bSV6d1uxcr8uVYP3cMdc9nBdk9ZNw/okqLCyTn9bs0tFVfWSpChrqG65/FzdcUUPJXe1n5a+AADQGRH+/YDwDwA4WYZh6KsDtS3TBJpHB+yraN80hCOFhVgUHhqi8FCLrGEhCg8NUWOToQPV7jZtLRapZ7cuLRcEXOp3jkt9k52KtH7zBYGmJkOf7K0wA//R6yecHxelYX3iNbxPgjJSoxUWenjBSE9jk974ZL+e/+BrbS+uNvs9fkCy7rryfPVJCoz/72z0Nik0xMIijgCADoHw7weEfwDA6bC/ok67DtYqvCXEh4daZA0NUdgRz8NDQ1r2WxQeEnLcOyEcrHFr875Kbd5baf5trb4fKcQi9Yp3KP0cl/p3b74o0DfJqYjwUB3yNGrNjoN6d1uxVn5+QAdr3D7vG3hejIb3idewPgnq2a3LN34/wzC06osD+vPqr7Xu61Jz+3d6xemHV/bU0Ati/R6sD3katafskHYdrNWu0kPaXVqrXQeb/xZW1Ss1JlI3XtpdN2R01zmMXAAA+BHh3w8I/wCAQFBSXa8t+yr16d5K82/JMUYIhIZY1CMuSnvKDsnTeHjRQoctTFemddPwPvG6une8oqOsp9yXT/dW6M8ffK23NheaUxkuSnbqrivP19h+ST4jB063GnejGep3ldY2P28J+sVVbX+PY7FYpCE9Y3Xjpd01Oj2xXaMnAAA4nQj/fkD4BwAEquKqem3eW6lP97VeEKjQwZrDaxGkxNg17MIEDe+ToMt7xMgadnpDeUHZIf11zU69urFAdQ1eSdI5Xe2644oe+t5lKSe1RkFTk6GKuobmWzVWu3Wg5XaNB2s8Kqmu157SQ9pVeshnBMOxdI0MV2pslM6LjfT5m+SK0LqvSvX/8vb6jFyIsoZqbP8k3Xhpd13eI8bvoxcAAJ0D4d8PCP8AgGBhGIaKqur1eWG1krva1Tuhy1kJs+W1Hv0jd7deWrfLvPjgjAhTVmaqbs5IUX2jVwerPc3BvsY32B+sbt5WWuuRt50rIsZGWZUaG6nzYqN0XlyU+Tw1NlJdI795RENB2SEt/Xif/l/eXu0pO2RuP7d1WsCl5yglJvLUfgwAANqB8O8HhH8AAE6P+gavXvvvPv3lw6/19cHaUzpGdGT4EbdrtCmui1XdHDadG9Mc8M+NjZTzNN0G0TAMbdpdrv+3aa+WbS70uZ3j4PNjdOOl3fXdfkmn7S4Lp6K6vkH7K+q1r+KQ9pXXaW9FnfZX1Kus1q3LzovR9Zeco9TYKL/1DwBwagj/fkD4BwDg9GpqMrRiW7H+/MHX+nhPuVz25kDfzWE7Ithb1a0l4Hdr2RbbxarwM7hewInUebx6Z2uR/l/eXn301UG1/pdWpDVUY9KTdGPGORrcI/a4izSeCsMwdLDGo30VddpXXmcG/H0V9S3bDqmqvvEbj3PpuV11/SXnaGz/ZMV8i7Uc/KXG3aj9FXWKibIqJtJ6Wn9jAOioCP9+QPgHAODMaWoyAi7M7a+oM6cF7DxiBMM5Xe3K7BkriyRDkmE0B/jm54aaDJnPDUMy1Py3yXzdvK+uwdtSza/zWZTxeFz2cJ3T1a7krnZ1j7brnK52RVhDtXxrkT768qC56GJYiEVXp3XTxEvO0fA+CYoIDz0Dv863V1hZp027ypW3u1wbd5VpW2GVz3eI62JTvLP5olC806ZujgjFO2zND2eEurVcMDrda1gAwNlE+PcDwj8AADgWwzD03z3l+n95+/SfT/ar2v3NVfiTZbFICY4IndMS6pO72nVOtF3dW/4md7WrywmmHZRU1euNT/Zr6cf7tHV/lbm9iy1MY9ITdf2lp3/EwsloajL0RUm1Nu4qV96uMm3cVa59FXVt2jkiwlTdjlEOR4qODFe8I6LlAkHzwxkRrihrqKJsYepiC1NUy6P5eaiirM2vuXDQPt4mQweq3XLaw7grBnCaEf79gPAPAAC+SX2DV+9uK9bu0kOyWCSLLAqxyHxusUgWi0UWqWW77zaLRQppeW4NC1GSq7mKn+iKOG1THb4ortbrH+/Tv/P3+wTsJFeEJlycrOsvOUcXJp7Z/9ap83j1yd4KbdpVpk27m6v7R4f6EIvUJ8mpy86LUUZqtAaeF60kl10N3qbmBSGr3Sqpcquk2q2S6vrmv1UtC0VW1etAjVsN3m/3n8LW0JDmiwFtLhKEKq6Lrc2FmLgutoAbwdIehmGo/FCDCsoOqaD8kArK6lr+Nj/2VdSpwWsoxCL1TnDo4pSuGpDSVRendFWv+C5n9LaeQLAj/PsB4R8AAASTpiZDG3eV6fX8ffrPp4U+4fvCRIeuv+QcTbg4WUku+0kd1zAMNXgN1Td6Vd/gVb2nSfWNXn19oNYM+1v2VarxqLs2RFpDdcm5XTUwNUYDz4vWJedGn3A0Q3u+X0VdQ/OFgaqWiwXVzX9r3A2qdXtV425Urbux+a+n0dzWnmkWx2INDVFS14jDFwVaHy0jNpK6RsgW1jGnWRzyNGpveZ0Z6PccEfD3ltf5LHR5LCEW6Vg34rCHh6rfOS5dfG5XDejeVQNSXDqnq53bZQLtRPj3A8I/AAAIVvUNXq3aXqKlH+/Tys9LzIq5xSJlnh+rHnFRqm9oDvH1Hm9LsG9SfYNXdQ1euVuet75uz90Y4x02XXZec9AfmBqjPkmODlMhbvA26ZDbqxrPERcHzAsFXtXUN6ik2q19FXXa37IQY1FVfbu+dzeHrXldhq52dXPYzJEFrVMNuthCFWk9PA0h0hpqjjpozzQET2OTKusaWh4eVdY1qOJQg8/fqroGVdS1bvOo4lCDSms933jseIdNKTGRSom269yYSHWPiVRKdKRSYuxKdEboYI1Hn+ytUH5BhT4pqNCneyuPedEgrotNF6e4Wi4GNF8UcEWenrtzAMGG8O8HhH8AANAZVBzy6K3NRXr9433asKvsWx8vIjxE9vBQxTsilHFetAamRuuy82LUPTq4qr8N3iYVV9VrX3md9le23pmh5a4M5c1D4+sbTm1EQavwUMsRFwqaLxqEh4aoygz7DTrk8Z7y8R0RYTr3iECfYj6PVPdo+0kvDtnUZOirAzXNFwNaLgp8XljdZtSHJJ0fF6UBKV3VO8Gh2CiroqOsiokKV9fI5rs7uOzhp/0uGpV1DS1TSDwqrXXrYLVbB2s8OljjVsWhBiV1jVBagkO9EhzqldDltN0+9Ju4G73aebBWO4pr9GVJjWrcjc13uYiyKjrSqtguzX9joqzqepp/F3Q8hH8/IPwDAIDOpqDskN7ZWqQad6MiwkMVERYiuzVUEeGhsoWFKiI8pHl7eKjs4Ue8DguVLTxEtrCQoAr430brvPnDFwXqVFbrVq3b2zyqwNM8quDQEdMQDrVMQ3Cf5DQEi0Vy2MLUtSU0d40Ml9Me3vy89W9k81+X3WreKeJsVN/rG7zaur/KHB3wyd4K7S499I3vC7E039EiuuVWj9FRVkVHHvE68vAFg4jwUJXXNgf7gzXN60AcrG4O9c0hvznsn+yaEEmuCPVOcKh3Qhf1SnCod4JDveK7KOoUp6fUuhv11YHmgL+jpEY7imv01YEa7S6tbdcoEqn5d+naciEgpuVvdJTVvIBiXkiJtKpLRPNoEkdEGP9sBpCACP8ffPCBHn30UeXl5amwsFBLly7VxIkTzf3Tpk3TSy+95POeQYMGKTc313ztdrs1d+5c/fOf/1RdXZ2GDRumZ599Vt27dzfblJeXa+bMmXrjjTckSRMmTNAzzzyjrl27mm327Nmje+65RytXrpTdbteUKVP02GOPyWpt/z1uCf8AAADwh0Zvk2o9zRcJDh11kcDjbZIz4nCY72pvDnmhAVQNLqttmS6wp0J7yg6p/JBH5bUelR9qUHmt54zcQaOVIyJM3brYFNvFqrguNvPhtIepoKxOO0qq9UVxtYqr3Mc9Rvdoe/OFgIQu6h3ffFHggvguslubR0pUHmrQjpJqM+R/2fI41h0tjuxXr/guuiC+i6IjrSo/5FFZre+j6iTvfHGk0BCLutgOXwxonVrSJSJMjpbtrRcLWp9HWcPk8bZM9/F4dcjTPM3HfN3QPC2oruEY+zyHpwWd09WuoRfE6Tu94jTo/NhvtbZHZ9DeHOrXX7G2tlYDBgzQ7bffrhtvvPGYbUaPHq0XXnjBfH10GJ81a5befPNNZWdnKzY2VnPmzNG4ceOUl5en0NDmf5imTJmivXv3KicnR5J01113KSsrS2+++aYkyev1auzYserWrZvWrFmj0tJSTZ06VYZh6JlnnjkTXx0AAAA4bcJCQ+Syh8hlD8558TFRVl2TFq9r0uKPud/T2KSKQ80XA8pqPc0XB1ouEJTVNq9bUNb6+pBHdR6voiNbwrzDpriWYO8T8h02xUZZ2z2VoTXAf1Fcoy+Kq1seNTpY49be8jrtLa/Tys9LzPYWi5QSHam6Bq8OVB//wkFcF6t6duuiXglddEG35hEFF8R3UbzD9o2V+QZvU5uLAuW1HpUe+feQR6U1zes61LobVeNplGE0356xdarI2baj5SLIi2t3KSzEokvPjdYVveJ0Ra849T/H1WHW/gg0HWbYv8ViOWblv6KiQq+//vox31NZWalu3bpp8eLFmjx5siRp//79SklJ0VtvvaVRo0Zp27Zt6tu3r3JzczVo0CBJUm5urjIzM/X5558rLS1Nb7/9tsaNG6eCggIlJydLkrKzszVt2jSVlJS0u4pP5R8AAADAkcprPc0XAkpqtKO4WtuLqrWjpEZlRy2gmOSK0AUtlfxe8Q4z7EdHtX8k8unQ1GToUINXNfXNI0dq3I0tzxtUXX94gcvqlu3m6/rmqSjW0OapP/bwUNmtYbK3rOkRYQ1VZHiY7NaW1+HNC1farSHmtKBIa/OilZ8XVunDLw9qzY6D2lPmO+XDERGmzPNj9Z1ecbqiVzedFxvZ6acnBETlvz1WrVql+Ph4de3aVVdddZUeeughxcc3X/HLy8tTQ0ODRo4cabZPTk5Wenq61q5dq1GjRmndunVyuVxm8JekwYMHy+Vyae3atUpLS9O6deuUnp5uBn9JGjVqlNxut/Ly8nTNNdccs29ut1tu9+GrdFVVVaf76wMAAAAIYNFRVg06P1aDzo/12X6wxq0vS2oUER6qnt2i5DhLiwV+k5Ajhvv7S4+4KI3plyRJ2lN6SB9+eUBrdhzUR18eVFV9o5Z/VqzlnxVLks7pam+5EBCnoT3jzvrFkkDSocP/mDFjdPPNNys1NVU7d+7U//zP/+jaa69VXl6ebDabioqKZLVaFR0d7fO+hIQEFRUVSZKKiorMiwVHio+P92mTkJDgsz86OlpWq9Vscyzz58/Xr3/962/7NQEAAAB0Mq1rB+DEzo2N1K2xqbp1UKq8TYY276vUmh0HtObLg8rbXa59FXXK3lig7I0Fslik9GSXrugVp4uSmyvg3iZDTYYhb1PzqAavYZjbml8ftb3leVPL9mv7xOvSc6O/oZeBoUOH/9ah/JKUnp6ugQMHKjU1VcuWLdMNN9xw3PcZhuEz9ONYw0BOpc3RHnjgAc2ePdt8XVVVpZSUlON/IQAAAADAKQkNsejilK66OKWr7r22lw55GrV+Z5nW7GieIrC9uFqb91Vq877K0/aZ3Rw2wr8/JCUlKTU1VTt27JAkJSYmyuPxqLy83Kf6X1JSoiFDhphtiouL2xzrwIEDZrU/MTFR69ev99lfXl6uhoaGNiMCjmSz2WSzcbUOAAAAAM62SGuYz0KQJVX1WtOyVkBB+SGFWCwKDWl+tD4Psejw8xCLQi1H7pf5vLXNhYkOP3/L0yegwn9paakKCgqUlNQ8/yMjI0Ph4eFasWKFJk2aJEkqLCzUli1btGDBAklSZmamKisrtWHDBl1++eWSpPXr16uystK8QJCZmamHHnpIhYWF5rGXL18um82mjIyMs/01AQAAAAAnKd4ZoRsu7a4bLu3+zY07Ib+G/5qaGn355Zfm6507dyo/P18xMTGKiYnRvHnzdOONNyopKUm7du3Sgw8+qLi4OF1//fWSJJfLpTvvvFNz5sxRbGysYmJiNHfuXPXr10/Dhw+XJPXp00ejR4/W9OnTtWjRIknNt/obN26c0tLSJEkjR45U3759lZWVpUcffVRlZWWaO3eupk+fzqr9AAAAAICA59fwv2nTJp+V9Fvnz0+dOlXPPfecNm/erL///e+qqKhQUlKSrrnmGr366qtyOA4PvXjyyScVFhamSZMmqa6uTsOGDdOLL76o0NDD9+N8+eWXNXPmTPOuABMmTNDChQvN/aGhoVq2bJlmzJihoUOHym63a8qUKXrsscfO9E8AAAAAAMAZZzEMw/B3J4JFe++vCAAAAADA6dDeHBpyFvsEAAAAAAD8gPAPAAAAAECQI/wDAAAAABDkCP8AAAAAAAQ5wj8AAAAAAEGO8A8AAAAAQJAj/AMAAAAAEOQI/wAAAAAABDnCPwAAAAAAQY7wDwAAAABAkCP8AwAAAAAQ5Aj/AAAAAAAEOcI/AAAAAABBjvAPAAAAAECQI/wDAAAAABDkwvzdgWBiGIYkqaqqys89AQAAAAB0Bq35szWPHg/h/zSqrq6WJKWkpPi5JwAAAACAzqS6uloul+u4+y3GN10eQLs1NTVp//79cjgcslgs/u7OcVVVVSklJUUFBQVyOp3+7g5wQpyvCDScswg0nLMIJJyvCDRn45w1DEPV1dVKTk5WSMjxZ/ZT+T+NQkJC1L17d393o92cTif/0kTA4HxFoOGcRaDhnEUg4XxFoDnT5+yJKv6tWPAPAAAAAIAgR/gHAAAAACDIEf47IZvNpl/96ley2Wz+7grwjThfEWg4ZxFoOGcRSDhfEWg60jnLgn8AAAAAAAQ5Kv8AAAAAAAQ5wj8AAAAAAEGO8A8AAAAAQJAj/AMAAAAAEOQI/53Ms88+qx49eigiIkIZGRn68MMP/d0lQJL0wQcfaPz48UpOTpbFYtHrr7/us98wDM2bN0/Jycmy2+26+uqrtXXrVv90Fp3e/Pnzddlll8nhcCg+Pl4TJ07U9u3bfdpwzqIjee6559S/f385nU45nU5lZmbq7bffNvdzvqIjmz9/viwWi2bNmmVu45xFRzJv3jxZLBafR2Jiorm/o5yvhP9O5NVXX9WsWbP0i1/8Qh9//LG+853vaMyYMdqzZ4+/uwaotrZWAwYM0MKFC4+5f8GCBXriiSe0cOFCbdy4UYmJiRoxYoSqq6vPck8BafXq1brnnnuUm5urFStWqLGxUSNHjlRtba3ZhnMWHUn37t31+9//Xps2bdKmTZt07bXX6rrrrjP/45PzFR3Vxo0b9ec//1n9+/f32c45i47moosuUmFhofnYvHmzua/DnK8GOo3LL7/c+NGPfuSz7cILLzR+/vOf+6lHwLFJMpYuXWq+bmpqMhITE43f//735rb6+nrD5XIZf/rTn/zQQ8BXSUmJIclYvXq1YRicswgM0dHRxl/+8hfOV3RY1dXVRq9evYwVK1YYV111lfHjH//YMAz+HYuO51e/+pUxYMCAY+7rSOcrlf9OwuPxKC8vTyNHjvTZPnLkSK1du9ZPvQLaZ+fOnSoqKvI5f202m6666irOX3QIlZWVkqSYmBhJnLPo2Lxer7Kzs1VbW6vMzEzOV3RY99xzj8aOHavhw4f7bOecRUe0Y8cOJScnq0ePHvre976nr7/+WlLHOl/DzuqnwW8OHjwor9erhIQEn+0JCQkqKiryU6+A9mk9R491/u7evdsfXQJMhmFo9uzZuuKKK5Seni6JcxYd0+bNm5WZman6+np16dJFS5cuVd++fc3/+OR8RUeSnZ2tvLw8bdq0qc0+/h2LjmbQoEH6+9//rt69e6u4uFi/+93vNGTIEG3durVDna+E/07GYrH4vDYMo802oKPi/EVHdO+99+rTTz/VmjVr2uzjnEVHkpaWpvz8fFVUVGjJkiWaOnWqVq9ebe7nfEVHUVBQoB//+Mdavny5IiIijtuOcxYdxZgxY8zn/fr1U2Zmpnr27KmXXnpJgwcPltQxzleG/XcScXFxCg0NbVPlLykpaXMVCuhoWldL5fxFR3PffffpjTfe0Pvvv6/u3bub2zln0RFZrVZdcMEFGjhwoObPn68BAwboqaee4nxFh5OXl6eSkhJlZGQoLCxMYWFhWr16tZ5++mmFhYWZ5yXnLDqqqKgo9evXTzt27OhQ/44l/HcSVqtVGRkZWrFihc/2FStWaMiQIX7qFdA+PXr0UGJios/56/F4tHr1as5f+IVhGLr33nv12muvaeXKlerRo4fPfs5ZBALDMOR2uzlf0eEMGzZMmzdvVn5+vvkYOHCgbr31VuXn5+v888/nnEWH5na7tW3bNiUlJXWof8cy7L8TmT17trKysjRw4EBlZmbqz3/+s/bs2aMf/ehH/u4aoJqaGn355Zfm6507dyo/P18xMTE699xzNWvWLD388MPq1auXevXqpYcffliRkZGaMmWKH3uNzuqee+7RK6+8on//+99yOBzm1XyXyyW73W7ej5pzFh3Fgw8+qDFjxiglJUXV1dXKzs7WqlWrlJOTw/mKDsfhcJhrqLSKiopSbGysuZ1zFh3J3LlzNX78eJ177rkqKSnR7373O1VVVWnq1Kkd6t+xhP9OZPLkySotLdVvfvMbFRYWKj09XW+99ZZSU1P93TVAmzZt0jXXXGO+nj17tiRp6tSpevHFF3X//ferrq5OM2bMUHl5uQYNGqTly5fL4XD4q8voxJ577jlJ0tVXX+2z/YUXXtC0adMkiXMWHUpxcbGysrJUWFgol8ul/v37KycnRyNGjJDE+YrAwzmLjmTv3r265ZZbdPDgQXXr1k2DBw9Wbm6umbM6yvlqMQzDOKufCAAAAAAAzirm/AMAAAAAEOQI/wAAAAAABDnCPwAAAAAAQY7wDwAAAABAkCP8AwAAAAAQ5Aj/AAAAAAAEOcI/AAAAAABBjvAPAAAAAECQI/wDAICAsWrVKlksFlVUVPi7KwAABBTCPwAAAAAAQY7wDwAAAABAkCP8AwCAdjMMQwsWLND5558vu92uAQMG6P/9v/8n6fCQ/GXLlmnAgAGKiIjQoEGDtHnzZp9jLFmyRBdddJFsNpvOO+88Pf744z773W637r//fqWkpMhms6lXr17661//6tMmLy9PAwcOVGRkpIYMGaLt27eb+z755BNdc801cjgccjqdysjI0KZNm87QLwIAQGAI83cHAABA4PjlL3+p1157Tc8995x69eqlDz74QN///vfVrVs3s81Pf/pTPfXUU0pMTNSDDz6oCRMm6IsvvlB4eLjy8vI0adIkzZs3T5MnT9batWs1Y8YMxcbGatq0aZKk2267TevWrdPTTz+tAQMGaOfOnTp48KBPP37xi1/o8ccfV7du3fSjH/1Id9xxhz766CNJ0q233qpLLrlEzz33nEJDQ5Wfn6/w8PCz9hsBANARWQzDMPzdCQAA0PHV1tYqLi5OK1euVGZmprn9Bz/4gQ4dOqS77rpL11xzjbKzszV58mRJUllZmbp3764XX3xRkyZN0q233qoDBw5o+fLl5vvvv/9+LVu2TFu3btUXX3yhtLQ0rVixQsOHD2/Th1WrVumaa67Ru+++q2HDhkmS3nrrLY0dO1Z1dXWKiIiQ0+nUM888o6lTp57hXwQAgMDBsH8AANAun332merr6zVixAh16dLFfPz973/XV199ZbY78sJATEyM0tLStG3bNknStm3bNHToUJ/jDh06VDt27JDX61V+fr5CQ0N11VVXnbAv/fv3N58nJSVJkkpKSiRJs2fP1g9+8AMNHz5cv//97336BgBAZ0X4BwAA7dLU1CRJWrZsmfLz883HZ599Zs77Px6LxSKpec2A1uetjhyEaLfb29WXI4fxtx6vtX/z5s3T1q1bNXbsWK1cuVJ9+/bV0qVL23VcAACCFeEfAAC0S9++fWWz2bRnzx5dcMEFPo+UlBSzXW5urvm8vLxcX3zxhS688ELzGGvWrPE57tq1a9W7d2+FhoaqX79+ampq0urVq79VX3v37q2f/OQnWr58uW644Qa98MIL3+p4AAAEOhb8AwAA7eJwODR37lz95Cc/UVNTk6644gpVVVVp7dq16tKli1JTUyVJv/nNbxQbG6uEhAT94he/UFxcnCZOnChJmjNnji677DL99re/1eTJk7Vu3TotXLhQzz77rCTpvPPO09SpU3XHHXeYC/7t3r1bJSUlmjRp0jf2sa6uTj/96U910003qUePHtq7d682btyoG2+88Yz9LgAABALCPwAAaLff/va3io+P1/z58/X111+ra9euuvTSS/Xggw+aw+5///vf68c//rF27NihAQMG6I033pDVapUkXXrppfrXv/6l//3f/9Vvf/tbJSUl6Te/+Y250r8kPffcc3rwwQc1Y8YMlZaW6txzz9WDDz7Yrv6FhoaqtLRUt912m4qLixUXF6cbbrhBv/71r0/7bwEAQCBhtX8AAHBatK7EX15erq5du/q7OwAA4AjM+QcAAAAAIMgR/gEAAAAACHIM+wcAAAAAIMhR+QcAAAAAIMgR/gEAAAAACHKEfwAAAAAAghzhHwAAAACAIEf4BwAAAAAgyBH+AQAAAAAIcoR/AAAAAACCHOEfAAAAAIAg9/8BU30PLOvGgkgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fit = history.history\n",
    "for i in fit:\n",
    "    plt.plot(fit[i])\n",
    "    plt.title(i + ' over epochs')\n",
    "    plt.ylabel(i)\n",
    "    plt.xlabel('epochs')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "205/205 [==============================] - 0s 2ms/step - loss: 42.4172 - mse: 9873.8340\n"
     ]
    }
   ],
   "source": [
    "scores = model.evaluate(xtest, ytest)\n",
    "mae = scores[0]\n",
    "mse = scores[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean absolute error:  42.41722869873047\n",
      "Mean squared error:  9873.833984375\n"
     ]
    }
   ],
   "source": [
    "print('Mean absolute error: ', mae)\n",
    "print('Mean squared error: ', mse)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "205/205 [==============================] - 0s 1ms/step\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "42.417228300732624"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mean_absolute_error(ytest, model.predict(xtest))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}