Corelation Between Features.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('final.csv', sep= ',')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Collision_Type_val_Driver-autorickshaw ', 'Collision_Type_val_Drowned',\n",
       "       'Collision_Type_val_Head on', 'Collision_Type_val_Hit and Run',\n",
       "       'Collision_Type_val_Hit animal', 'Collision_Type_val_Hit bicyclist',\n",
       "       'Collision_Type_val_Hit fixed object',\n",
       "       'Collision_Type_val_Hit parked vehicle',\n",
       "       'Collision_Type_val_Hit pedal cyclist',\n",
       "       'Collision_Type_val_Hit pedestrian',\n",
       "       ...\n",
       "       'Vehicle_Sub_Type_ROAD ROLLER', 'Vehicle_Sub_Type_SCOOTER',\n",
       "       'Vehicle_Sub_Type_STATION WAGON', 'Vehicle_Sub_Type_TANKER',\n",
       "       'Vehicle_Sub_Type_TEMPO', 'Vehicle_Sub_Type_TRACTOR',\n",
       "       'Vehicle_Sub_Type_TRAIN', 'Vehicle_Sub_Type_Unknown',\n",
       "       'Vehicle_Sub_Type_VAN', 'Vehicle_Sub_Type_accussed/summons'],\n",
       "      dtype='object', length=302)"
      ]
     },
     "execution_count": 157,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [],
   "source": [
    "del df['Unnamed: 0']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "metadata": {},
   "outputs": [],
   "source": [
    "y = pd.read_csv('severity.csv', sep= ',')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "metadata": {},
   "outputs": [],
   "source": [
    "y= y.iloc[:,1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(152784,)"
      ]
     },
     "execution_count": 221,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(152785, 302)"
      ]
     },
     "execution_count": 158,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = df\n",
    "X = df  #independent columnst\n",
    "#get correlations of each features in dataset\n",
    "corrmat = data.corr()\n",
    "#"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "metadata": {},
   "outputs": [],
   "source": [
    "alpha = corrmat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_right_col_names(alpha):\n",
    "    col_names = alpha.columns\n",
    "    valid_columns=[]\n",
    "    index = -1\n",
    "    for col_name in col_names:\n",
    "        index+=1\n",
    "        if (\"unknown\" in col_name.lower()) or (\"applicable\" in col_name.lower()):\n",
    "            print(col_name)\n",
    "        else:\n",
    "            valid_columns.append(index)\n",
    "    return valid_columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collision_Type_val_Not Applicable\n",
      "Accident_Spot_val_Not Applicable\n",
      "Accident_Location_val_Not Applicable\n",
      "Accident_Location_val_Unknown\n",
      "Junction_Control_val_Not Applicable\n",
      "Road_Character_val_Not Applicable\n",
      "Road_Type_val_Not Applicable\n",
      "Road_Classification_val_Unknown\n",
      "Seperation_val_Not Applicable\n",
      "Seperation_val_Unknown\n",
      "Surface_Type_val_Not Applicable\n",
      "Surface_Type_val_Unknown\n",
      "Surface_Condition_val_Not Applicable\n",
      "Surface_Condition_val_Unknown\n",
      "Road_Condition_val_Not Applicable\n",
      "Road_Condition_val_Unknown\n",
      "weather_val_Not Applicable\n",
      "Main_Cause_val_Not Applicable\n",
      "Main_Cause_val_Unknown\n",
      "Hit_Run_val_Not Applicable\n",
      "Hit_Run_val_Unknown\n",
      "Lane_Type_val_Unknown\n",
      "Road_Markings_val_Unknown\n",
      "Spot_Conditions_val_Unknown\n",
      "Accident_Location_id_val_Unknown\n",
      "RoadJunction_val_Not Applicable\n",
      "RoadJunction_val_Unknown\n",
      "Accident_spotb_val_Unknown\n",
      "Vehicle_Type_Unknown\n",
      "Vehicle_Vanoeuvre_Not Applicable\n",
      "Vehicle_Vanoeuvre_Unknown\n",
      "Vehicle_Load_Unknown\n",
      "Fuel_Type_Unknown\n",
      "Vehicle_Sub_Type_Unknown\n"
     ]
    }
   ],
   "source": [
    "rc = get_right_col_names(alpha)\n",
    "beta = alpha.iloc[rc,rc]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "268"
      ]
     },
     "execution_count": 189,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(rc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "metadata": {},
   "outputs": [],
   "source": [
    "def filter_df(matrix, threshold, max_features):\n",
    "    num_rows = matrix.shape[0]\n",
    "    most_correlated_rc= set()\n",
    "    for index in range(num_rows):\n",
    "        #print(index)\n",
    "        #print(\"-----\")\n",
    "        count = 0\n",
    "        r =0\n",
    "        c = 0\n",
    "        for col in range(num_rows):\n",
    "            if(matrix.iloc[index][col]>threshold and matrix.iloc[index][col]<0.99):\n",
    "                count+=1\n",
    "                r = index\n",
    "                c = col\n",
    "                print(matrix.iloc[index][col])\n",
    "                print(\"$$$\")\n",
    "                print(index)\n",
    "                print(col)\n",
    "                \n",
    "                most_correlated_rc.add(index)\n",
    "                most_correlated_rc.add(col)\n",
    "        if(len(most_correlated_rc)>=max_features):\n",
    "            break\n",
    "    return most_correlated_rc\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.5028439986334079\n",
      "$$$\n",
      "3\n",
      "138\n",
      "0.39255300409198746\n",
      "$$$\n",
      "20\n",
      "181\n",
      "0.47823990551613793\n",
      "$$$\n",
      "20\n",
      "184\n",
      "0.35942585944566574\n",
      "$$$\n",
      "21\n",
      "62\n",
      "0.3367625572936984\n",
      "$$$\n",
      "21\n",
      "74\n",
      "0.31721899552976585\n",
      "$$$\n",
      "21\n",
      "91\n",
      "0.3052470917910932\n",
      "$$$\n",
      "22\n",
      "160\n",
      "0.4344051879835977\n",
      "$$$\n",
      "26\n",
      "63\n",
      "0.4174597372441684\n",
      "$$$\n",
      "41\n",
      "75\n"
     ]
    }
   ],
   "source": [
    "imp_f = filter_df(beta,0.3,15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{3, 20, 21, 22, 26, 41, 62, 63, 74, 75, 91, 138, 160, 181, 184}"
      ]
     },
     "execution_count": 201,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "imp_f"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = list(imp_f)\n",
    "b = beta.iloc[a,a]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,20))\n",
    "g=sns.heatmap(b,annot=True,cmap=\"RdYlGn\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Unnamed: 0                                                 0.046710\n",
       "Collision_Type_val_Brown                                  -0.000646\n",
       "Collision_Type_val_Driver-autorickshaw                    -0.000646\n",
       "Collision_Type_val_Drowned                                -0.034640\n",
       "Collision_Type_val_Head on                                -0.097838\n",
       "Collision_Type_val_Hit and Run                             1.000000\n",
       "Collision_Type_val_Hit animal                             -0.019349\n",
       "Collision_Type_val_Hit bicyclist                          -0.047941\n",
       "Collision_Type_val_Hit fixed object                       -0.030075\n",
       "Collision_Type_val_Hit parked vehicle                     -0.024212\n",
       "Collision_Type_val_Hit pedal cyclist                      -0.015724\n",
       "Collision_Type_val_Hit pedestrian                         -0.095169\n",
       "Collision_Type_val_Hit puchcart                           -0.016107\n",
       "Collision_Type_val_Medium                                 -0.000646\n",
       "Collision_Type_val_Not Applicable                         -0.088655\n",
       "Collision_Type_val_Others                                 -0.226799\n",
       "Collision_Type_val_Overturning                            -0.036712\n",
       "Collision_Type_val_Rear end                               -0.067168\n",
       "Collision_Type_val_Right Turn Collision                   -0.024671\n",
       "Collision_Type_val_Run Off Road                           -0.018752\n",
       "Collision_Type_val_Side impact or Right angle             -0.026713\n",
       "Collision_Type_val_Side swipe                             -0.036894\n",
       "Collision_Type_val_Skidding or Self accident              -0.070362\n",
       "Collision_Type_val_Vehicle to Vehicle                     -0.018673\n",
       "Accident_Spot_val_Bottleneck                              -0.009289\n",
       "Accident_Spot_val_Bridge                                   0.010670\n",
       "Accident_Spot_val_Circle                                   0.042349\n",
       "Accident_Spot_val_Cross roads                              0.026814\n",
       "Accident_Spot_val_Culvert                                  0.008007\n",
       "Accident_Spot_val_Curves                                  -0.016908\n",
       "                                                             ...   \n",
       "Accident_Location_id_val_In bazaar                         0.025755\n",
       "Accident_Location_id_val_Narrow bridge or culverts         0.011647\n",
       "Accident_Location_id_val_Near Bus stop                     0.047408\n",
       "Accident_Location_id_val_Near Hospital                     0.024553\n",
       "Accident_Location_id_val_Near Petrol Pump                  0.017000\n",
       "Accident_Location_id_val_Near School or College            0.024270\n",
       "Accident_Location_id_val_Near a factory industrial area    0.019983\n",
       "Accident_Location_id_val_Near a recreation place/cinema    0.017323\n",
       "Accident_Location_id_val_Near a religious place            0.019041\n",
       "Accident_Location_id_val_Near office complex               0.032156\n",
       "Accident_Location_id_val_Near or inside a village          0.005414\n",
       "Accident_Location_id_val_Open area                        -0.020205\n",
       "Accident_Location_id_val_Residential area                  0.030322\n",
       "Accident_Location_id_val_Unknown                          -0.116395\n",
       "RoadJunction_val_More than four arms                      -0.006133\n",
       "RoadJunction_val_Not Applicable                           -0.023147\n",
       "RoadJunction_val_Round about or Circle                    -0.007540\n",
       "RoadJunction_val_Staggered junction                       -0.005890\n",
       "RoadJunction_val_T Junction                               -0.008076\n",
       "RoadJunction_val_Unknown                                   0.027466\n",
       "RoadJunction_val_Y Junction                               -0.004571\n",
       "Accident_spotb_val_Bridge                                 -0.003985\n",
       "Accident_spotb_val_Construction Work / Material           -0.001710\n",
       "Accident_spotb_val_Culvert                                -0.001828\n",
       "Accident_spotb_val_Curve                                  -0.010429\n",
       "Accident_spotb_val_Other                                  -0.017925\n",
       "Accident_spotb_val_Pot holed                              -0.002239\n",
       "Accident_spotb_val_Steep Incline or Climb                 -0.001583\n",
       "Accident_spotb_val_Straight and flat                      -0.017034\n",
       "Accident_spotb_val_Unknown                                 0.027466\n",
       "Name: Collision_Type_val_Hit and Run, Length: 230, dtype: float64"
      ]
     },
     "execution_count": 136,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "alpha.iloc[5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_specific_rc(df, most_correlated_rc):\n",
    "    new_df = pd.DataFrame()\n",
    "    for index in most_correlated_rc:\n",
    "        print(index)\n",
    "        new_df.add(df.iloc[:index:])\n",
    "        \n",
    "    new_df2 = pd.DataFrame()\n",
    "    for index in most_correlated_rc:\n",
    "        new_df2.add(new_df.iloc[:,index])\n",
    "    \n",
    "    return new_df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "229\n",
      "5\n",
      "106\n",
      "107\n",
      "45\n",
      "46\n",
      "47\n",
      "50\n",
      "84\n",
      "23\n"
     ]
    },
    {
     "ename": "IndexError",
     "evalue": "single positional indexer is out-of-bounds",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-124-449dc6a27031>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mcm\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_specific_rc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0malpha\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mimp_f\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m<ipython-input-123-ffc46f53c3c6>\u001b[0m in \u001b[0;36mget_specific_rc\u001b[0;34m(df, most_correlated_rc)\u001b[0m\n\u001b[1;32m      7\u001b[0m     \u001b[0mnew_df2\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mDataFrame\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      8\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mindex\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mmost_correlated_rc\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m         \u001b[0mnew_df2\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnew_df\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0miloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     10\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     11\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mnew_df2\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   1492\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mKeyError\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mIndexError\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mAttributeError\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1493\u001b[0m                 \u001b[0;32mpass\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1494\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_tuple\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1495\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1496\u001b[0m             \u001b[0;31m# we by definition only have the 0th axis\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_getitem_tuple\u001b[0;34m(self, tup)\u001b[0m\n\u001b[1;32m   2141\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_getitem_tuple\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtup\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2142\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2143\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_has_valid_tuple\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtup\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2144\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2145\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_lowerdim\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtup\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_has_valid_tuple\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m    221\u001b[0m                 \u001b[0;32mraise\u001b[0m \u001b[0mIndexingError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Too many indexers'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    222\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 223\u001b[0;31m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_validate_key\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    224\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    225\u001b[0m                 raise ValueError(\"Location based indexing can only have \"\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_validate_key\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m   2068\u001b[0m             \u001b[0;32mreturn\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2069\u001b[0m         \u001b[0;32melif\u001b[0m \u001b[0mis_integer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2070\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_validate_integer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2071\u001b[0m         \u001b[0;32melif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtuple\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2072\u001b[0m             \u001b[0;31m# a tuple should already have been caught by this point\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/anaconda3/lib/python3.6/site-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_validate_integer\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m   2137\u001b[0m         \u001b[0mlen_axis\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_axis\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2138\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mkey\u001b[0m \u001b[0;34m>=\u001b[0m \u001b[0mlen_axis\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0mkey\u001b[0m \u001b[0;34m<\u001b[0m \u001b[0;34m-\u001b[0m\u001b[0mlen_axis\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2139\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mIndexError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"single positional indexer is out-of-bounds\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2140\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2141\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_getitem_tuple\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtup\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mIndexError\u001b[0m: single positional indexer is out-of-bounds"
     ]
    }
   ],
   "source": [
    "cm = get_specific_rc(alpha,imp_f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "def colnames():\n",
    "    col_names = df.columns\n",
    "    count =0\n",
    "    for cn in col_names:\n",
    "        count+=1\n",
    "        print(count)\n",
    "        print(cn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1\n",
      "Unnamed: 0\n",
      "2\n",
      "Collision_Type_val_Brown \n",
      "3\n",
      "Collision_Type_val_Driver-autorickshaw \n",
      "4\n",
      "Collision_Type_val_Drowned\n",
      "5\n",
      "Collision_Type_val_Head on\n",
      "6\n",
      "Collision_Type_val_Hit and Run\n",
      "7\n",
      "Collision_Type_val_Hit animal\n",
      "8\n",
      "Collision_Type_val_Hit bicyclist\n",
      "9\n",
      "Collision_Type_val_Hit fixed object\n",
      "10\n",
      "Collision_Type_val_Hit parked vehicle\n",
      "11\n",
      "Collision_Type_val_Hit pedal cyclist\n",
      "12\n",
      "Collision_Type_val_Hit pedestrian\n",
      "13\n",
      "Collision_Type_val_Hit puchcart\n",
      "14\n",
      "Collision_Type_val_Medium\n",
      "15\n",
      "Collision_Type_val_Not Applicable\n",
      "16\n",
      "Collision_Type_val_Others\n",
      "17\n",
      "Collision_Type_val_Overturning\n",
      "18\n",
      "Collision_Type_val_Rear end\n",
      "19\n",
      "Collision_Type_val_Right Turn Collision\n",
      "20\n",
      "Collision_Type_val_Run Off Road\n",
      "21\n",
      "Collision_Type_val_Side impact or Right angle\n",
      "22\n",
      "Collision_Type_val_Side swipe\n",
      "23\n",
      "Collision_Type_val_Skidding or Self accident\n",
      "24\n",
      "Collision_Type_val_Vehicle to Vehicle\n",
      "25\n",
      "Accident_Spot_val_Bottleneck\n",
      "26\n",
      "Accident_Spot_val_Bridge\n",
      "27\n",
      "Accident_Spot_val_Circle\n",
      "28\n",
      "Accident_Spot_val_Cross roads\n",
      "29\n",
      "Accident_Spot_val_Culvert\n",
      "30\n",
      "Accident_Spot_val_Curves\n",
      "31\n",
      "Accident_Spot_val_Junction\n",
      "32\n",
      "Accident_Spot_val_More than four arms\n",
      "33\n",
      "Accident_Spot_val_Narrow road\n",
      "34\n",
      "Accident_Spot_val_Not Applicable\n",
      "35\n",
      "Accident_Spot_val_Offset\n",
      "36\n",
      "Accident_Spot_val_Other\n",
      "37\n",
      "Accident_Spot_val_Rail Crossing Unmanned\n",
      "38\n",
      "Accident_Spot_val_Rail Crossing manned\n",
      "39\n",
      "Accident_Spot_val_Railway crossing\n",
      "40\n",
      "Accident_Spot_val_Road hump or Rumble strips\n",
      "41\n",
      "Accident_Spot_val_Round about or Circle\n",
      "42\n",
      "Accident_Spot_val_Staggered junction\n",
      "43\n",
      "Accident_Spot_val_T Junction\n",
      "44\n",
      "Accident_Spot_val_Y Junction\n",
      "45\n",
      "Accident_Location_val_Belonging to a gang \n",
      "46\n",
      "Accident_Location_val_City/Town\n",
      "47\n",
      "Accident_Location_val_Not Applicable\n",
      "48\n",
      "Accident_Location_val_Rural Areas\n",
      "49\n",
      "Accident_Location_val_Special features \n",
      "50\n",
      "Accident_Location_val_Unknown\n",
      "51\n",
      "Accident_Location_val_Villages settlement\n",
      "52\n",
      "Junction_Control_val_Controlled\n",
      "53\n",
      "Junction_Control_val_Give way sign\n",
      "54\n",
      "Junction_Control_val_Hindu \n",
      "55\n",
      "Junction_Control_val_No signal lights\n",
      "56\n",
      "Junction_Control_val_Not Applicable\n",
      "57\n",
      "Junction_Control_val_Not at  Junction\n",
      "58\n",
      "Junction_Control_val_Police / Manual\n",
      "59\n",
      "Junction_Control_val_Signal lights Automatic\n",
      "60\n",
      "Junction_Control_val_Signal lights Blinking\n",
      "61\n",
      "Junction_Control_val_Signal lights Manual\n",
      "62\n",
      "Junction_Control_val_Signal lights Not working\n",
      "63\n",
      "Junction_Control_val_Signals (Not working)\n",
      "64\n",
      "Junction_Control_val_Signals (Working)\n",
      "65\n",
      "Junction_Control_val_Stop Sign\n",
      "66\n",
      "Junction_Control_val_Stop sign\n",
      "67\n",
      "Junction_Control_val_T Junction\n",
      "68\n",
      "Junction_Control_val_Uncontrolled\n",
      "69\n",
      "Junction_Control_val_VIR\n",
      "70\n",
      "Road_Character_val_AGER\n",
      "71\n",
      "Road_Character_val_Crest of hill\n",
      "72\n",
      "Road_Character_val_Curve\n",
      "73\n",
      "Road_Character_val_Curve and Incline\n",
      "74\n",
      "Road_Character_val_Dip or trough\n",
      "75\n",
      "Road_Character_val_Gentle Incline or Climb\n",
      "76\n",
      "Road_Character_val_Hump\n",
      "77\n",
      "Road_Character_val_Incline\n",
      "78\n",
      "Road_Character_val_Not Applicable\n",
      "79\n",
      "Road_Character_val_Others\n",
      "80\n",
      "Road_Character_val_Sharp Curve\n",
      "81\n",
      "Road_Character_val_Slight Curve\n",
      "82\n",
      "Road_Character_val_Steep Incline or Climb\n",
      "83\n",
      "Road_Character_val_Straight and flat\n",
      "84\n",
      "Road_Type_val_Arterial\n",
      "85\n",
      "Road_Type_val_City or Town Road\n",
      "86\n",
      "Road_Type_val_Expressway\n",
      "87\n",
      "Road_Type_val_Feeder Road\n",
      "88\n",
      "Road_Type_val_Forest Road\n",
      "89\n",
      "Road_Type_val_Major District Road\n",
      "90\n",
      "Road_Type_val_Minor District Road\n",
      "91\n",
      "Road_Type_val_Mixed\n",
      "92\n",
      "Road_Type_val_NH\n",
      "93\n",
      "Road_Type_val_Not Applicable\n",
      "94\n",
      "Road_Type_val_One way\n",
      "95\n",
      "Road_Type_val_Others\n",
      "96\n",
      "Road_Type_val_Residential Street\n",
      "97\n",
      "Road_Type_val_Service Road\n",
      "98\n",
      "Road_Type_val_State Highway\n",
      "99\n",
      "Road_Type_val_Sub Arterial\n",
      "100\n",
      "Road_Type_val_Two way\n",
      "101\n",
      "Road_Type_val_Village Road\n",
      "102\n",
      "Road_Classification_val_Unknown\n",
      "103\n",
      "Seperation_val_Asphalted\n",
      "104\n",
      "Seperation_val_Concrete\n",
      "105\n",
      "Seperation_val_Divider\n",
      "106\n",
      "Seperation_val_Metalled\n",
      "107\n",
      "Seperation_val_No Divider\n",
      "108\n",
      "Seperation_val_Not Applicable\n",
      "109\n",
      "Seperation_val_Paved\n",
      "110\n",
      "Seperation_val_Unknown\n",
      "111\n",
      "Surface_Type_val_BUDDHISTS\n",
      "112\n",
      "Surface_Type_val_Bitumen(Tar)\n",
      "113\n",
      "Surface_Type_val_Concrete\n",
      "114\n",
      "Surface_Type_val_Gravel\n",
      "115\n",
      "Surface_Type_val_Kutcha\n",
      "116\n",
      "Surface_Type_val_Metalled\n",
      "117\n",
      "Surface_Type_val_Not Applicable\n",
      "118\n",
      "Surface_Type_val_Surfaced\n",
      "119\n",
      "Surface_Type_val_Unknown\n",
      "120\n",
      "Surface_Condition_val_Ditch or Potholed\n",
      "121\n",
      "Surface_Condition_val_Dry\n",
      "122\n",
      "Surface_Condition_val_Flooded\n",
      "123\n",
      "Surface_Condition_val_Muddy\n",
      "124\n",
      "Surface_Condition_val_Not Applicable\n",
      "125\n",
      "Surface_Condition_val_Others\n",
      "126\n",
      "Surface_Condition_val_Unknown\n",
      "127\n",
      "Surface_Condition_val_Wet\n",
      "128\n",
      "Road_Condition_val_Construction Work / Material\n",
      "129\n",
      "Road_Condition_val_Drainage Ditch\n",
      "130\n",
      "Road_Condition_val_EICHER\n",
      "131\n",
      "Road_Condition_val_Engineering Defect of Road\n",
      "132\n",
      "Road_Condition_val_No influence on accident\n",
      "133\n",
      "Road_Condition_val_Not Applicable\n",
      "134\n",
      "Road_Condition_val_Pot holed\n",
      "135\n",
      "Road_Condition_val_Unknown\n",
      "136\n",
      "weather_val_Clear\n",
      "137\n",
      "weather_val_Cloudy\n",
      "138\n",
      "weather_val_Dust Storn\n",
      "139\n",
      "weather_val_Fine\n",
      "140\n",
      "weather_val_Flooding of Slipways/Rivulets\n",
      "141\n",
      "weather_val_Fog / Mist\n",
      "142\n",
      "weather_val_Hail or Sleet\n",
      "143\n",
      "weather_val_Heavy Rain\n",
      "144\n",
      "weather_val_Light Rain\n",
      "145\n",
      "weather_val_Mist or Fog\n",
      "146\n",
      "weather_val_Not Applicable\n",
      "147\n",
      "weather_val_Others\n",
      "148\n",
      "weather_val_Snow\n",
      "149\n",
      "weather_val_Strong Wind\n",
      "150\n",
      "weather_val_Unknown\n",
      "151\n",
      "weather_val_Very Cold\n",
      "152\n",
      "weather_val_Very Hot\n",
      "153\n",
      "weather_val_Wind\n",
      "154\n",
      "Location_Type_val_BAVAJI\n",
      "155\n",
      "Location_Type_val_City/Town\n",
      "156\n",
      "Location_Type_val_Not Applicable\n",
      "157\n",
      "Location_Type_val_Rural Areas\n",
      "158\n",
      "Location_Type_val_Unknown\n",
      "159\n",
      "Location_Type_val_Villages settlement\n",
      "160\n",
      "Main_Cause_val_Accident\n",
      "161\n",
      "Main_Cause_val_BUDDHISTS\n",
      "162\n",
      "Main_Cause_val_Human Error\n",
      "163\n",
      "Main_Cause_val_Not Applicable\n",
      "164\n",
      "Main_Cause_val_Road Environment Defect\n",
      "165\n",
      "Main_Cause_val_Unknown\n",
      "166\n",
      "Main_Cause_val_Vehicle Defect\n",
      "167\n",
      "Hit_Run_val_No\n",
      "168\n",
      "Hit_Run_val_Not Applicable\n",
      "169\n",
      "Hit_Run_val_Unknown\n",
      "170\n",
      "Hit_Run_val_Yes\n",
      "171\n",
      "Lane_Type_val_DualLane\n",
      "172\n",
      "Lane_Type_val_FourLane\n",
      "173\n",
      "Lane_Type_val_Intermediate\n",
      "174\n",
      "Lane_Type_val_Others\n",
      "175\n",
      "Lane_Type_val_SingleLane\n",
      "176\n",
      "Lane_Type_val_SixLane\n",
      "177\n",
      "Lane_Type_val_Unknown\n",
      "178\n",
      "Road_Markings_val_ACHARI\n",
      "179\n",
      "Road_Markings_val_Centre Broken Line\n",
      "180\n",
      "Road_Markings_val_Centre White Line\n",
      "181\n",
      "Road_Markings_val_Centre Yellow Line\n",
      "182\n",
      "Road_Markings_val_Directional Marking\n",
      "183\n",
      "Road_Markings_val_Kerb Line\n",
      "184\n",
      "Road_Markings_val_Unknown\n",
      "185\n",
      "Road_Markings_val_Zebra Crossing\n",
      "186\n",
      "Spot_Conditions_val_Construction Work or Materials\n",
      "187\n",
      "Spot_Conditions_val_Electric or Telephone or Pole or Cable\n",
      "188\n",
      "Spot_Conditions_val_Father\n",
      "189\n",
      "Spot_Conditions_val_Others\n",
      "190\n",
      "Spot_Conditions_val_Tree or Branches\n",
      "191\n",
      "Spot_Conditions_val_Unknown\n",
      "192\n",
      "Side_Walk_val_Asphalted\n",
      "193\n",
      "Side_Walk_val_Concrete\n",
      "194\n",
      "Side_Walk_val_Metalled\n",
      "195\n",
      "Side_Walk_val_No Side Walk\n",
      "196\n",
      "Side_Walk_val_Not Applicable\n",
      "197\n",
      "Side_Walk_val_Paved\n",
      "198\n",
      "Side_Walk_val_Unknown\n",
      "199\n",
      "Accident_Location_id_val_Affected by encroachments\n",
      "200\n",
      "Accident_Location_id_val_At pedestrian Crossing\n",
      "201\n",
      "Accident_Location_id_val_In bazaar\n",
      "202\n",
      "Accident_Location_id_val_Narrow bridge or culverts\n",
      "203\n",
      "Accident_Location_id_val_Near Bus stop\n",
      "204\n",
      "Accident_Location_id_val_Near Hospital\n",
      "205\n",
      "Accident_Location_id_val_Near Petrol Pump\n",
      "206\n",
      "Accident_Location_id_val_Near School or College\n",
      "207\n",
      "Accident_Location_id_val_Near a factory industrial area\n",
      "208\n",
      "Accident_Location_id_val_Near a recreation place/cinema\n",
      "209\n",
      "Accident_Location_id_val_Near a religious place\n",
      "210\n",
      "Accident_Location_id_val_Near office complex\n",
      "211\n",
      "Accident_Location_id_val_Near or inside a village\n",
      "212\n",
      "Accident_Location_id_val_Open area\n",
      "213\n",
      "Accident_Location_id_val_Residential area\n",
      "214\n",
      "Accident_Location_id_val_Unknown\n",
      "215\n",
      "RoadJunction_val_More than four arms\n",
      "216\n",
      "RoadJunction_val_Not Applicable\n",
      "217\n",
      "RoadJunction_val_Round about or Circle\n",
      "218\n",
      "RoadJunction_val_Staggered junction\n",
      "219\n",
      "RoadJunction_val_T Junction\n",
      "220\n",
      "RoadJunction_val_Unknown\n",
      "221\n",
      "RoadJunction_val_Y Junction\n",
      "222\n",
      "Accident_spotb_val_Bridge\n",
      "223\n",
      "Accident_spotb_val_Construction Work / Material\n",
      "224\n",
      "Accident_spotb_val_Culvert\n",
      "225\n",
      "Accident_spotb_val_Curve\n",
      "226\n",
      "Accident_spotb_val_Other\n",
      "227\n",
      "Accident_spotb_val_Pot holed\n",
      "228\n",
      "Accident_spotb_val_Steep Incline or Climb\n",
      "229\n",
      "Accident_spotb_val_Straight and flat\n",
      "230\n",
      "Accident_spotb_val_Unknown\n"
     ]
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_index_with_df_val(df, val):\n",
    "    col_names = df.columns\n",
    "    for col in col_names:\n",
    "        x = df.loc[df[col] == some_value]\n",
    "        print(x)\n",
    "        break\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(152784, 2)"
      ]
     },
     "execution_count": 208,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 227,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ubuntu/anaconda3/lib/python3.6/site-packages/sklearn/ensemble/forest.py:245: FutureWarning: The default value of n_estimators will change from 10 in version 0.20 to 100 in 0.22.\n",
      "  \"10 in version 0.20 to 100 in 0.22.\", FutureWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
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     ]
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    {
     "data": {
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U1XRAuuNS3x9I2glXHQXXlugvqas8VPNbzQz5S+DS0o5D+E7sj0et9Cj5JAD70fzLdwyxUyDPi7JKhTa1NCtaS5dkOH4ktTdukED151U35plxnySeaewuvCnXa4GFn1HFdcZz3gFY28x6mFkP3OAsHskMLPz30UL5PnLNkHWAL+LfUTUeJI7P4m+nO/4M3gwDZENcFr7EUjQJ4n2PRdVon8ET9m0bfS4jaZMa4ydJkiRtSJv9+jezJ+LYYBC+NV5JB2QYcKc8ymQSkbXVzKZIGh7tXwEmNjPc5bhmxURJH+Ahur8ODY8DcX2JLtHPFTX6AffpuFHSLFxc7B8V2kwH5seRwFDgiULdEFpBl8TMZoUB9qKZvRTFFZ9XCzizbM4H4P4Zy+NHJAdG+dAofw/feSj5hQwARplL3pf4E/ArheMvsEo8g3ksbJz8AzdAVwIOi++o2jyPBa6Ua6vMxw2Se4HDJD2FGxWPFdq/C/SVdCr+d7NQIsTQMylpk3TH//4voMnXJEmSJGlHWlUnJElgYW2VsvKhtFCvo6NInZAkSZLGUZ06Ie0p296qyEN4Z0VY6VR5/phG7r8x7v1BW80xxukm6beS/hZhoaMbnWuVfntImhnXfRQhvZJ2LIWyxufD4miqQ4j53NVMm/7xXTwlD+vtX6gbLGnNwufnJa3alnNOkiRJ2ofOkkW3LiRdCnwJzyWyFi7xfQEeJrpsjVuLfXTB85FsZWbrNte+FbgKVytdzzzlfCmtPRFa+mCFe3aJcOG6MLNJwCR5Nt+b8KOiV6N6npktttHTCOEjUql8cHlZRP+cB+xqZrPj+dwv6Tkzm07zgml1I6mLmf2vkXtSrCz5qJKiZUlnYInaCTGzI0P34iTcJ6GnmV1jZq+Z2b+Kv5Jjd2B0XA+RdL2kcXj47Eg8edpUSTtIOkTSRLkg1m3hG1FLLOv7chGuqbHLUa67QbRbB09Ad6pFXhkzmx2hv+C+GF3i39BYW3/gEUm/i52ekQqhMLnQ1rTwRTmyME5pt+E/ZVM4GrhHLmlfUZQsykdLOifW9GzBSbXSmh4rOnPGvX0k9ZX0qFwYbryk5gTmShyPZ7ydXXo+uKPxCaoimAYcrYLIXMxjBbkY3ISYw55RPlguBjcKeFDSGpLGRH8za601SZIkaVuWKCOkwEjgc/HCvEzSV5q9w3cf+pnZIDxF/N9ChGss8Ecz2ypEsZ7Cs9ZCBbEsSRvhDo9fCqNhPk3J5crZBJhqZvPLK+SCbAfiRso2wCGStozq9YBLQ3TrLWCvKL8GODrmswjmieauAM4vrK3IIqJkhbouZtYXTyj4M6ozHBdPQy44t0bsxDwN7GBmWwKn4aHA9bAJrtNSZBKwSQ3BtIVE5qLsFNww7YsLuZ0raYWo64ULlH0Fj5q5L767nsDU8gkpxcqSJEnahSXSCDGzOUBv4FDgVTwr7eBmbrujXPWzwKaSxsqjTvbFX4xQWSxrlxh7olzwahc81LRRtscF2d6N9fwRD3sFF1grvRwn42HGK+OiYmOi/PpGBlPzomSVhNsqcTNNYbDfwTVHwENnbwk/lfNpeoZtQaW57gacFN/JaFw7ZO2ou9/M3ojricCB8qSIm5lZ+e5RipUlSZK0E0uUT0iR2F0YDYwO4+EA4H80GVblAlbv1uhuKJ6yfloYMzvWaCvgWjP7SR3TnAX0lLR0pd2QGpSLmnWt1rAVqUu4zcxelPS6PCfOQOCwqDoDV1AdIM/aO7rOcZ/EjbpphbLe1A6brTRXAXuZ2UK6I3In4AXfvZmNkfRlXDZ+qKTfWI1syylWliRJ0nYskTshkjaQtF6haAvg78Dz+AsMmo4w6mFF4CV5bpHi0UolsawHgb0lfTrKPympomiYmf0NP044XXIxDHlUyzdwUbP+kpaPY4MBUVYRM3sLeEtSSYq82hFQRYGxZkTJGmU4cCLQPZxHwXdCXozrwQ30dR7wkzBciP+eDPw66msJwxW5D/cVKT3nLSs1iu/qZTP7He403KuBuSZJkiStyBJphODCZNdKelIuiLUxLhJ2OnChpEn4r+R6+SmeU2UcCwuAHQvsFDstk4GNzexJPOfIyBj7fqBWJtaD8fwuf42jiqG46umUuJ4QY18VOWNqcSCuDDsV/+VfiTuBASWn27K6A3Bfiem44fbzZsarxq24muvNhbJfAb+U9AQN7LDFsdOPcRG2p2P+JxaOo4bigmlFx9RKnIEnG5wuF5o7o0q7HYFpMc+BeBbgJEmSpANIsbIkqUGKlSVJkjSO6hQrW2J9QhpF0hwz61b4PBhX9TxK0mHAXDO7LspHmllVXQp56O8awPvAf4FDCr/c2504wrjLzDatUr8j8BCwh5ndGWV3AeeZ2ega/R4HXBm5gCrVrwq8hEfsNCeHX2v+g6nwXTTYRw+qPIP4vo6PKJ6GSJ2Q5ONIaogk7cXHxgipRdkLdDD1iWPta2aT5LlpzpUndVuurM1+Zjaj9Wa6WLyAh7HeWU9jSbvjRywHSSodbc02swGFZvvguVsG0UxOnnhOx5YVjzOzI4sFi2PMJEmSJEsWS6pPSKsiFzM7voY4Vi0eBdYys61De2Ld0LTYAthAni8FSUMlXRRCXs/FWNXmc1M4r1K4d+9wah0bQl1TVJBnr4NpwNuSdq0w3i4h8DUjBL+WA4piY2/GmgaU3ToI+BEu/PbZQn9zJJ0vF1t7UNJqZnYNrnlScobtgocJl89liJrE1daV9IBcoG2KpHXkMvgPqkmsbM/C7V0kDZPLv9+qEJ0r6383uajaFEm3SOpWoU3qhCRJkrQDHycjpGsYFlPDsXMRp8wa4li1+Cpwe51zWAPXB/kmcHaNdkVBsGVxLZK78cywu4ZQ10BcTK0RzsSdahcg6RO48+dAM9sMNw4ON7OL8N2gncxsp/KOJH0OFyqbgDuoFjPWrgBMCrG1h1lY/Gz5MNCOAK5uZr7DcNG2nsB2+NHP+8CAeAY7Ab8uRcTghtNlZrYR8E6MUZzzqrH+fnH/JOCH5YOmTkiSJEn78HEyQt4r7VDES/C0xexvmKTZ+BHHpXXec7uZfRgRNqvXaHcPHpWzHPA1YEwYRMsAv4tonVuIHDT1UhI6K4T5gr+4Z5vZs/G5XMSsGgNpio65Cd8VKfEhbkgB3IAbXiVuLMxlJbkI2yJIWhHfYRoR7d8P3xQBZ0WEzwN4DqHSs/ynmY2rMi64Mu3GwLgwRA8AKoZXJ0mSJG1P+oS0nH3xsN1zgYuBb0d5MdyoXDCtKEJWLcQWM3s/nCl3x1/2N0XVD4CXcbnxpfBdgUYp7YY0lMitAoOAz0gq6ZWsKWk9M/tLhbZW5brS5+bYF1gN6G1mH0h6nqbn3FzfwtVTB1EnKVaWJEnSdnycdkLqpV5xLMzjm38KbKNIpAa8LGkjSUvhAmQtZTiuC7IDcG+UdQdeMk+Gtx9QMXFeM3MeCawCbB5Fz+Cy8KWMwkURs4rPQtL6QDczW8vMephnzf0lTbshS9Ek7f494JHC7QOjj+2Bt0NErdI8/wO8IKl/tF8ufDy64zorH0jaiYV3MtaWtG2VccGdaL9UWqs86d36lcZPkiRJ2p40QhZlKPWJYwEQxyS/Bk6IopOAu4DxuA9DSxkJfAV4wMz+G2WXAQfIs+huSG0p+lqcCXwOfNcFN3ZuiWOeD2mKdLkSuFfSQ2X3DwJGlJXdRpMR8i7QN8TZdmZh/5v3QyjsCpoSBVZjP+CYOHoZD3wG9xPpE3Pdn4XF5Z4BjpT0FG5oXV7szMxexaOfbow+H8WfY5IkSdIBdEqxsnJNj1bo72QzO6vwebyZNRJZ0lz/y+AKnXvhuwfzgJ+b2T0t6Ks/8Gz4jTRy3xBgjpmd1+iYVfobiutu3Fqlvuqaq31/1fQ6WmPNzc23wr09qKGtUiLFypIkSRpHKVa2ECdTSC3fmgZIcAYe+bKpmc2TtDq+i9ES+uM7KYu8kCV1MbPF9eVoLT4Wa06xsuTjSIqVJe1Fpz2OkbSjXNWz9PkSubImkp6XdHpBK2LDKO8m6Zoomy5pL0ln0xSeOyzazYn/StK5kmbGPQMLY4+W9KKk9yW9UQjv3b1snssDh+CqofMAzOxlM7s56gdF3zMlnVO4b46kKyW9J+ndqH8W+D4ufjZVrosxWtIF8nw4x8q1QkbF+h6UtHZhOusXw5Dj3whJG0qaUBi7RxxnIOk0SRNj/CslVXWYrXfNwCGV1oxrsAyQ6348Jml1udbJHoux5krz6y3pYUmTJd0naY1C+bQ4zjqyVh9JkiRJ29NpjZA6eC20Hi4Hjo+yn+LOjpuZ2ebAKDM7iabw3PLMs9/GE7n1BPrhL8JSMrotga2B5XFfg6Oij/vK+lgX+IeZvVM+QUlrAufgfhFbAFvF0QO4lsadZtYVD/G9yczWx0NLT4ix/hZtlw3dil/jkTjXxvqGsbBWyLPFMOSSwJiZPQ0sK+kL0W4gTSG0l5jZVnEs0RXXMGmOxVnzY6H7MQaXux8P3LEYay4ff5lov7eZ9ca1SM6M6mtww6lnrcUpxcqSJEnahSXZCPlj/Hcy0COu+1HQ7DCzN5vpY3vgRjObb2Yv41EhW0XdBDN7ISJRphbGaIStgNFm9mocKQyjSYPjv/gRRPkaKjG8cL0t8Ie4vp5FtTCqURQUKxohO0l6PHZGdgY2qbO/anT0mjcANgXul2uBnAp8Vq5HsnJJKyX6qUiKlSVJkrQPndkn5H8sbCRV09yYT9uso6jpUWuMv+KhoStV2hmowQfW5BXc3BpaGgVTZDgeAfNHPLr4L3K11Mvw5HH/DEfP8udcic68ZgGzzGzbhQqriKI1R+qEJEmStB2deSfk78DGcn2IlXHp8ua4n8JZv6RV4vKD2KYvZywwUNLSklbDf7FPqNCuKqHi+XvgQrnEOpJWk7RP9PUVSatKWhoPYX24em9A8zol44HvxvW+sYZ65vk3/MX/U5p2GUoGx2vyHCpV89mU9dWZ1/wMsJpCL0TSMpI2MbO3gLfUpBZbfjSXJEmStDOdzgiR1AWYZ2b/xI8QZsZ/n6jj9l8Aq4RD5DQ8twi43sX0kmNqgRHAdDy52yjgRDP7dwumfSrwKvCkXBvjLuAdM3sJ1w15KMaYbGZ/aqavm4AT5Anl1qlQfzRwoFznYj8WzUxbi+G44+vNAPFi/h3+jO8DJjbQV6dcc2iq7A2cE38DU/G8M+B6KJfGMU2zDrhJkiRJ29LpdEIk9QR+Z2Z9O3ouSZI6IUmSJI2jOnVCOtVOiKTD8ARnpzbXNlkYSYMjMqX0+Xl51tiOnFOP2CWp1WZ7SRMkPR3/Di3U9Ze0ceHzaEnN/lEnSZIkSwadyjHVzK6gSTK80yFpBPCFsuIfVwjb7QgGAzMlnQJ8CVgTeEjSfOBCM7um3o5UEAhryzVL+gwe9dLfzKaE0XSfpBfN7G5qiJi1YKwWiZ6lWFnycSTFypL2olPthHR2QnOjXIejRS9jSSdIOiauz5c0Kq53ljRM0m6SHpULst0SjqMVxcUk7Y0LgQ3DDZBtgX/hYcwfAj9Uk6DbCpKujt2HJyTtGeWDJd0R83iw0prxPC2nlNYsaaikvWPHY2zMdYpcgKwejgSGmtmUGOs14ETgJFUQMYt79om5Pytph5jH0nLRuYlyQbP/F+U7xrzuwH1XVpB0t1ywbKZCnC5JkiTpGNII6TjG4hlywQ2IbhHBswPuLHsq0C8E2SYBP4y2i4iLRb6UScC+YTC8F20rCbqdgou49cUdd8+VtELU9cJFvqrJrw8HvgMQUTG7AHcDrwC7xlgDqSEmVsYmuF5IkUnAJjVEzLrE3I8DfhZlB+EidVvhOiWHqEmYrRdwbAjBfRX4l5n1jOdXyk68EEqxsiRJknYhjZCOYzLQW9JKuCbJo7gxsgPwHrAxMC4iOQ6gKWX9TqpfXKySoNtu+E7DVGA0HqZbkkG/38zeqNHfPTH+csDXgDFh8CwD/C7mdEvMva2otqb9Y02PA58C1ou6CWY2O65nALtKOkfSDmZW0cJIsbIkSZL2oVP5hHycMLMPJM3GfTnG47sfO+GS6LNxg2BQ8R41Li5WSdBNwF5m9kxZ31vTjECYmb0vz4S7O77jcVNU/QB4GZe/Xwp4v1bLkjnsAAAgAElEQVQ/BZ4EegPFEN7ewKwa91Rb09HlR2OSdqSwJjN7VlIv4OvALyQ9aGY/rzXBFCtLkiRpO3InpGMZix+TjInrw3A9lMeAL0laFxb4caxPbXGx5gS/StwHHC15ojpJWzY45+G43sYONB1ndAdeCon7/YCl6+zrUmCwpC1iLp/C8878KuobWdPhcZyFpPULR0wLiOihuWZ2A3AuflSTJEmSdBBphHQsY4E1gEcjd837wFgzexXfIbkxBLoeBTZsRlxsKHBFOHF2rTHmGfjxyXRJs+JzI4wEvgI8EMJg4LszB4Q42IbUKbkewmbfx49ynsZ3hK42szujSXMiZiWuwndVpkRI8G+pvMu3GTAhjm1+hovbJUmSJB1EpxMrS5LORIqVJUmSNI7qFCvrtD4h8vTvI4CNIhV9o/evCVxkZovkQwm/huPNrOG3S/gZ/DeiN6q12QD/Nb4ysBy+u3FotfY1+lkZ+J6ZXdbovTX67AHcFdEhlep3xCXX9yjtSEi6CzjPzEa31jw6A5IG4/41R1VrkzohSVIfqS2StITOfBwzCHgk/tswZvavSgZIK7AjTblIqnERcH6Elm4EXNzCsVYGjmjhvYvDy8BNcbQzFff/qNsQkuf/KX7+Wqmvwr8RizPB8jGSJEmSJY9OaYSE0+X2uP7Dd8vqfixpRghOnR1l60p6IMqmSFpHBclwSV0l3STpqXj5dS30V00U7HlJp0f5DEkbxi7CYcAP4kW6A5VZA3ih9MHMZkSfgyX9SS4//hdJJZ0LJP0wBLRmSjouis8G1omxzq3yrG6S9I3C58UVEAPX6niE0OjAfVeOiP4XEUuL8tGSLpA0CTg25nGFpMeBXfFw4udpip75Wdw3Q9LKcl6XtH+UXydp17K1LiQ+VuO5Iel2SZMlzdLCUvAHyoXOJuDCbkmSJEkH0Vl/Te4J3Bshla9L6m1mkyV9Leq2NrO5kj4Z7YcBZ5vZCHkY61LApwv9HY5HRWwkaXNgCoBcJrwkCvaupB/jomClsM3XzKyXpCPw45uDJV0BzDGz82rM/3xglKTxuCPnNeFUCtAX2BSYC0yUdDdgeMTJ1ni46eOSHsaz0W4ahkA1SgJid6tJQOzw6GfXCKtdD8/J00jelTNxp9X7y8ovKYW1Sroe+CZQciRdtnQGKGko8FlgOzObL+li4Akz6y9pZ+A6YAtgHG4M/B14Dt91uQ5XfT28wrx64c9ktqTeVHhuZvYE8H9m9obcSXeipNuAZYHT8TDgt/Fjp0WyM4fRcijA0iut1sAjS5IkSRqhU+6E4EcwJQ2Km2g6kumHv9DnAsRLZkVgLTMbEWXvl+oLfBm4Ieqn45ocANtQXRQMKgtjNUvkadkIF+7aEXhMLvAFrv/xeoh8/RHf8dkeGGFm75rZnCivtstSTpsIiJnZGPAEc2VVO6m6WNrwsra3mNn8uN4euD76HgV8Si7UNhb/fr6MK7tuJmkt4E0zqxRlUxQfq/XcjpFH6zwGfA4XL9saGG1mr0ZkT/l8S2tPsbIkSZJ2oNPthMTuxs74y8hwzQmTdEJbDEcFUbAClYSx6sLM/gVcDVwdx0IlR9DycKTFCk9qAwGxImfiO0WlZHbNiaWVGw31hOqOwXPIrI1Lyg/A9U/GVmnfbJ9y59p+wLaxYzaa2qJuVUmxsiRJkrajM+6E7A1cb2afN7MeZvY5XEF0B/xo4EBJy4MbLGb2H+AFeTQNkpYr1RcYA3wv6jcFNo/yaqJgtWhWQEvSV9UknPUZXEb8xajeVdIn45igP34cMRboL2l5ucjWgCirV6yrNQXEFmBmI4FVaHpetcTSmmMssC8sMBJeM7N3zOyfwKrAemb2HO6LUhJwq6fPSs+tO76TMleeuG+baP848BVJn4rvZ58G5p8kSZK0Mp3RCBmEh+YWuQ0YZGb34knNJsXxSSkp23749vt0XPDqM2X3X44niHsK9/eYDFBNFKyZ+d0JDFBtx9TdgJlxHHAf7uD576ibEOuZDtxmZpMii+zQqHscuMrMnjCz1/GjopnVHFODVhMQq8CZ+HEGzYilNccQPFfOdNzh9oBC3ePAs3E9FlgLN0ZqUu254YZYl/i+z8aNzZI42hD8ex4HPNXA/JMkSZJWJsXK2hHVoUuRdC5SrCxJkqRxtKSLlbUWcRxyAZ7i/S3cT+I4M3u2SvsehJhXHBscb2bflLQHsLGZnV3lvj7A/mZ2TCvM+VPAg/HxM7hPyqvxuW9ht6PDkfQIcJSZTa1S/wIezfJWfO4X7fu3wtg3ALea2e2L21c1UqwsSVpGipcl9fCRNkJCw2IEcK2ZfTfKegKr07T9Xxdmdgd+FFTs/xTK/AoknWJmZ1bpYyh+fNDcWK/j4auE8+cc/Pjjejz3SanpPDPbuoFlFOe5O54srshsMxvQkv6SJEmSpFE6o09Ia7IT8IGZXVEqMLNpZjY2xLHODX+LGZIG1upILjR2SVzvExEv3wHeCR2P44AXzOzMcDy9XdJ0SY+FNgmShki6Wi7s9ZykundNzGxGjPNn3PdhCzPbWtI5ko6U1E/SQ5LukfSMpEvDCCsplpYE2YZLWsHM7os+FvwDfi/pxsKa+0m6Pa6vlDRJLv51Wr3zbuaZdpOLmk2QJ6n7VpSvIxcle0IuOLZ1lC8l6TJJT0u6H3dordRvrwgjni7pNkndo/wRSWfHeM+oioCbpENjrZPmz327NZaaJEmSVOCjboRsSjihVuDb+G5DTzyc81xJa9TZ72nA7mbWE9ijQv3puDDX5sDJuPhWiQ3xcNq+wM9KUTQNcDXh1ClpaXwn5g9RtzUu8LUxrlOyp6RP46Jnu5hZL9wh9tgqfY8EtldTFt5iyO9Jcb7XE4/waUR3ZKyaJOCvKJSfhovS9cXDsn8tDwN+CRda2xKPqLko2u8NfCHWdyDV5fNvAH4Yz/8Z4KeFOsV4J8T4i5A6IUmSJO3DR/o4phm2B24MMa2X5QqlW9EkZFaLccBQSTfTJGhW3vde4MJcERK6UtTdbWbzgHmSXsGPhl6o0EdFzOyvkv4jaTNcWG2Cmb0Zmx6Pmdnz4HLuMQ/wl/b4aLMsVSJPzOy/scPwDUl/Ar6K7/AADJJ0EP43s2b0+WSd096h3CckyncDvibppPj8CVwv5FXgkjg6+x+wTtR/Gf/OPsTDskeXDxT+NJ8ws3FRdC0hkhY0JECXOiFJkiRtx0fdCJlFY1oWdWFmh8URwTeAyXL58HqZV7huWAQt+D0eWtwDz9a7YGpl7QwXZLvXzPars++bgINxWflHQ85+PXz3pK+ZvRUOoS0S/ypDQH8z+9tChdIvgH8C38eVX+e0wlglWixAlyRJkrQuH/XjmFHAclo4gdnmcn2PscBASUtLWg3/lT2hnk4lrWNmj5vZafiv9s+VNakozLXYq2niNuBb+HHSA4XybSStHcc038F3PMbjAl1fjPmsEEZFNUbhxzoH0XQUsxIunPZOHFnt3krruA84uvRB0pZxWRJaM/zoqeSJOwb/zpaSS7t/pbzDcOp9r+DvsR/wcCvNN0mSJGlFPtK/BM3MJA0ALpAnp3sfz+R6HP6C3haYhu8YnGhm/5aH6DbHufEiFx5KO42FX4hDcLn26fiOwgGL9LAYhFT7GODfcTRRYgLuc7EObpzcEc/gIGC4PMEduJ/KX6r0/T9J9+AKs/tG8RT86OVpPNHcuEr3toDT8e9mBm4Q/xVPUHgJcKuk/wPupmn34lbc2fhJ4B+46Fgl9gMuD9+Wv+L+I0mSJEknI8XKOhmS5gMzcANxNrCfNWXgLbVZCpiKH2U8F2U19TcUob5WIfuvpEvxTLbL4o6fz0TVL8zs1tZYV2sg6WBcc+S4KvW/wA3MHmb2WpTNMbNukrrgO1Ir19sfpFhZkiRJS1CKlS2xvBfhski6Fk/utkB3JBxS78Az1D7XGgOa2ZHRdw9cqG2L1ui3g3gDT953Smt0lmJlSdL6pJBZUuKj7hPS6YnImamFENaucf0p/LhhrWgnef6YG3FHzclR3k3Sg8CvgHUk7Vno+xRJz8pVTTcoG/eO4rgx9pfK2mwgaWLh80aSJsT1C3KNkhkFTY6pct2VtyTNjbJtqED44vy9FDUU63tO0qqS9ow+n5A0MsKM6+UqYF+FNkiSJEnSecmdkA6mqI4KC44Ptgjn0l3wSBhYWNdkVWBi+IW8Cgwws3ckrQo8JukOoBfw3binC+7XsUAzxcwW0Tcp94cxs2ckvSdpUzObiftWXFNo8oaZbRa+G3uYWX9Jw4GDzeyx0s4KrtdSvu75ku7CfUCuxzU/njWz12JdJX+Ww4AfAT9u9mE67+C6LMcAZ5TVrRjGVolPUiHEOhyZDwVYeqXV6hw2SZIkaZQ0QjofXeNFuRae5fX+KK+ma3IPcJakLwMfxn2rAzsAI8xsLvjORwvn83vgwHDs3QfYslBXUlcdhmerBRd+20BN0vKrSOpqZu9V6Hs4cCJuhHw3PoNrhdwsz/uzHA1K7OO5gqZIOr+s/D/Fo6aST0j5zWZ2JXAlwHJrrJdOU0mSJG1EGiGdj/diJ2R5PIT1SJoUQyuxL7Aa0NvMPpD0PK2j4VHiFjyaZhyuG1J0kq30ghb1J9kbi4u+fQpXni0pm14KnGVmfw6H25OqdVAJM3tDLiR3WCP3VSLFypIkSdqO9AnppMQOxjHAjyKyo5quSXfglTBAdsJVVME1NfpL6ippRVxXpKXzGIWHzV5TVl3KtzOIprDdB3DDCQBJVZ1cQwfkT/jOxbSCgdMdeFG+ndLS8OZfA0eQf+NJkiSdlvwfdCfGzJ7AZeQH4dmAp+OaJKMIXRP8KKRPaG3sj2t5YGZT8OONafiRzcRFBqifYcAHuCZKkVVDC+Vw3G8D3AD5UjilPgkc0kzfw3Fl1OGFsiH4eicCL7dkwmb2Mu6PsmxzbZMkSZKOIXVCkmaR53ZZzsxOL5S9gGtsvFX9ziWf1AlJkiRpnHp1QprdCZE0vxB6eaeklZu7p84JDpF0fDNtjpenbZ8qaaKk/aP8+YgEaRck9VdjWWNbc+zBki6pUb+BpNHxjJ6SdGWUbyHp6y0Yb01JtxY+34k7jV5c1nTNKve32bOq9jcjabVCSO8O9fx9SDq5LeaYJEmS1E89jqk1xbPaigjN3BV3cnwn9CQGtEK/Xczsfw3e1h/f2q83a2xLx2kJFwHnm9mfYtzNonwLoA/w57J5ldRRi1xoZtcAmNm/KCT9M7NqviRzq+yCLPKsIgrlqLJ2Y8zsmBrrqoqk0/CQ5RIr434xW0Z9Pd2cDJzVXKMUK0uStiNFy5JGfUIWEc+KHZIZkgZGeTdJD0qaEuV1iWdV4GTg8FLiNzN7x8yuLdQfXRhjw+i/r6RH4xfxeEkbRPlguTjXKODBZua4f/gzTJN0vTwR2h54vpipktaJf/dKmixpbGH8oZKukPQ4Lh62EPLEa88Xd5Mk/UXS6pK+Vfg1/4Ck1ev8TtYAXih9MLMZ8hwxP8cdWadKGhi7CNfjxslTuLHwHzys9+hYJ5J6SJoZ18tLulnSk5JGxPwWbK9JOjOe02OxhkWeVczpqjBkf4rngTFg49IaY25Xx47Oc5KOKYyxyN+Mmf3czLaIPgfjf8dfiDG7lj3z2+N7mqVIZCjpbJpE4YbV+ZyTJEmSVqbuEF21sXhW2VgrASs2I0v+mpn1knQEcDyefv5pYIdIwtYP/6W7V7TvBWwe4ZtdqsxxY+BUYLsQzfpktL8DlzO/Neb3IHCYmf1F0tbAZcDOMc5n4/755RM2sw8l/Qnf0bkm7v27mb0cL9ltQqDrYFw/40flfVTgfGCUpPHASOAaM3srdgv6mNlRMechsb7tzew9eQjwrpEMbz1c86P8/O4I4E0z21jSpni+mhIrAI+Z2SmSfgUcYma/KH9WZdRa44Z4croVgWckXQ5sTjN/M2Y2tcJai03+L77Drvjf6G1mdpKko6rJ0yvFypIkSdqFeoyQziaeVaKkdDmZpq357sC18VI1YJlC+/vN7I24VpU57oznZHkNXG+ifFBJ3XB1z1sKL7vlCk1uqWSAFBgOnIaHuxYFuj6LZ7pdA4/omF2jjwWY2TWS7gO+iquP/j9JPas0v6MgGrYMcIk8hHY+sH6F9tsDF8Y4M+WRMCX+ix+7gH8Hu9Yx3VprvNvM5gHzJL1C6/3NHCPPpAzwOWA94PVaN6RYWZIkSftQt0+I2lE8K3Yo5kj6Yo3dkFJ69/k0reMM4CEzGyCXDB9daP9uK81xKeCtGkne3q1SXuJRYF251kd/4BdRfjHwGzO7Q9KOeJhqXYQfx9XA1XGUsogKaIW5/QAPf+2Jr+n9escLPrCm0Krid1CLWmucV7iut7+axBj9gG3NbK6k0TT4t5hiZUmSJG1H3T4hHSCe9UvgUjUlOOumiI6pQXfgxbge3Ey7SnMcBewjV/BE0iej/D/4MQHhozJb0j7RRjV2HhYhXtwjgN8AT0XumPK51y3QJemrkpaJ688An4p+Fsy5Ct2Bl8zsQ2A/YOkKbcYB34m+NwY2q9CmnFrjNrrGxRVc644fJ82V++0Uk+l9UHpuSZIkScfQkGNqO4tnXQ48hJ/jz8SNng+buedXwC8lPUHtX9LV5jgLj/x5WNI03FAAuAk4Qe40ug6+k3JQtJmFH4M0QjWBrlskTQZea6Cv3YCZMZf7gBPie3gId/6cqnAaLuMy4IC4b0Mq7+BcBqwmFx37Bb7Wt5uZT/mzKjKEBtbYCoJr9wJdJD2F57Z5rFB3JTA9HVOTJEk6jhQrS6oSzsjLhPPqOrgk+wZ15oX5SJBiZUmSJI2jOsXKMoHdxwRJg4GR4T9C+MH0KTnhVmF54KE4thBwRGsaIOG3c5eZVfNhQVJf4DzcUXUu7gR7DH5MtCAipq1InZAk6ThSR+SjT4cbIWpGPGtJRdKBwLFlxePM7MhK7evo7xRgn7LiW8ysXuG4wcBM4F/1jmlm/2HRsN12E2KT64jcAnzXzB6Nsr2p7evS6BjtJSqXJEmSlNHhRkhLX8qdnTCiWmxISToBmGdmF0k6H+gZUUo7AwcB1wKnS9oL+BtwoJnNCc2MbwFdgfHA/8O1UvoAwyS9B2wbwxwt6Vt4uO4+Zva0pBXwKJZNo3yImf0pdlK+DXTDnVi/UmHONwHXm9nd8XkoHsY7Cbge1xYBOMrMxtfxGI4Eri0ZIAAFrZbiuKsBVwBrR9FxZjYudlEuxCNi3otn9Exza0mdkCRJkvYhs+h2XsbiOhngBkS3OBbZAXcIPhXoZ2a98Jf8D6PtJWa2VRxxdAW+GS/uScC+oTRa0gp5Le6/HBd8AzgFGGVmfXHxsHPDMAEXfNvbzBYxQILhNEXTLIuL290NvIILo/UCBlI7xLvIplQRtCvjQly6fivc4LoqykvidVvi2ixFmfaqazGzK82sj5n1WXr57nVONUmSJGmUDt8JSaoyGegdIcrzcLXQPrgRUlJ3HRc7Asvi+iMAO0k6Effn+CQe0XJnlTEqCb7tBuyhpkRxn6Bph6Eo+FaJe4ALJS2Hi6eNCXXW7jQvjLY49MMjgUqfVwpRuXrF65IkSZIOII2QTkpomMzGfTnG47sfOwHr4kqj95vZoOI9kj6Bh9X2MbN/yqXaa4lzVRJ8E7CXmT1T1vfWNCPEFlE0o4Hd8R2Pm6KqpcJos4DewJ+aabcULge/UL/y7MP1iNdVJcXKkiRJ2o48juncjMWPScbE9WHAE7jexZckrQsgaQVJ69NkcLwWOwF7F/pqTrysxH24r4ii7y0bnPNw4EB8x+beKKtHGK0Sl+BaJluXCiR9W4sm9xsJHF1oU1KzrVe8LkmSJOkA0gjp3IzFs+Q+amYv4zsIY83sVfylemPkc3kU2NDM3gJ+h0fB3MfC4l5DgStUIdNsGWfgxxbTJc2Kz40wEnf0fKAQzluPMNoixJq/C5wn6ZkQHdsdN6iKHIOLz00PYbXDorxe8bokSZKkA1hixMokzQdm4C+T2cB+8dJd3H6HAHPM7LwKdaXw4WWBLwClI4pfVMkS2yHIM9JuambHVanfCI8e6Y4n2xttZodL6gV82szurXRf4f662pXdsy5wazHHjqRf4M6wF0g6EzdUHqrRx4L29Y7b2qRYWZIkSeN8FMXK3iu90CRdi4dv1quR0SJK4cMFUa1qSes6O5cAvzKzu+OYpSQO1iuumzMu6m1XN2Z2Smv11ZakWFmSdA5SuOyjyZJ6HPMosBYsSCB3rqSZkmaU8qTIE949KGlKlC/I7yLpFEnPSnoE2KDRwSVtIGli4fNGkibE9QuSzokxH5f0xShfXdIfJU2SNEHSNlX6XlrS39WUuE+SnpO0qqQ9o88nJI2U9Ok6p7wG8AJ4Aj0zmxFHMqcB+8YRzd6StpH0aPQ/TtJ6Vdr1lfSGpHclzY35Pd7gM7xBUv+4/pmk96OvVyW9LWlENN1M0sMxRsko/ImkI+L6Ykkj43q3MFCRdGU861ly7ZRS/a2FOXxN0i2NzDtJkiRpPZY4I0Sez2QXPEwVPLR0Czzyoh+ua7EG7j8xILQpdgJ+HS/03rifwRbA14GtGp1DRI68J6m0o3AgCwuTvWFmmwG/pSkJ3kX4bkQfXEvjKipgZvNxga+S0bQd8GzIq4/Bo0C2xMNrf1TnlH8DjJH0Z0nHSeoeWiE/B4aFdsitwFM06WqcgR87VWq3Ny7hvgJuDP6PCuJlwAZhuEyVNBU4uLyBpOWBQ3BjcAU8guUhMxsQTdYHdsUz4P48vv+ihkovYOUo3yGeEcBJ8ax7ArvKswA/AGyuyJKMf29XV5jToWHATJo/t7l8fUmSJElLWZKMkK7xIvs3nkfk/ijfHrjRzOaHI+PDuGEh4Cy54+YD+MtydfxFNcLM5prZOzQZM43ye+BASV1wOfUbC3Wl62G4EQFuIF0Ra7gdWEXVHUSH4yGu4AZTKdvu2sBIefbfHwKb1DNRM7sK1xW5FTfgHpWLiZWzMnCbPGvxeTX63w04JdbyEAtriRR5JgyXLeIoq5LhtXG0+7u5g9KNZfV3mdl/zewV4A1gNdzhditJKwNz4nMv/LsdG/cNkjQF11fZCNg4onOGAd+T9Ek8/Hdk+YRSrCxJkqR9WOJ8QuKX8324T0gt5c198RdW79DceJ7amhmNcgtwMjAOj14pOslW8vYV0LfOBHBjgaHxi30P4KdRfilwlpn9WVI/4KR6J2tmL+K/+q+W9DT+Yi7nTOA+M7tM7lhazQdEQH8z+1u94y8G8wrX84EuZjZP0ovA/vjzfxY3rj5vZs/KxcmOxZ/3W5JuoOm7vxq4La6Hx85TVVInJEmSpO1YknZCADCzuXhI5o9iF2IsMDB8KVYDvgxMwCNBXgkDZCfg89HFGKC/pK6SVsTzrLR0HqNwp8/yHDGlXYxB+EsSfDdmQZ4cNWlZVOrbcIGuC4BpBQOnO/CiJAEH1DtXSV+NZ4WkNYFV8ER25doh1XQ1ytvdx8K6HI1qiRR5Ej+2+Vysa2BzNwTlGipH4tL0ACvFnN+Jo7ndSzeZ2T+B13ADbuhizDtJkiRZTJY4IwTAzJ7AFUQHASPiehpuFJxoZv/Gt937xNHF/ngeEcxsCn68MQ2XGZ+4yAD1Mwz4AHiwrHzVOAY6nCa/jSNxgbGSlsUhzfQ9HPg+TUcxAEPw9U7EFUjr5WvALLlOx5/xBG+v4s+rZzii7g2cg/vUTMF3O0qUtzsdWEHufDsr5tUiwpg7CjfSJgFvAfU4YozFj9cei12eD2g6ipmCGzdPA9fRZAiW+AMw28yebem8kyRJksVnidEJ6YxIOglYzsxOL5S9gGt2LLaGyccFSd3MMwALd+adYWYXt+F4V+BHaNc21zZ1QpIkSRpHdeqELJE7IYuLPER3VuxKTFVBFrzO+2+U9A5+JNGWL8tukn4r6W+SJksa3ehcq/TbI5xPkdRH0kVxvaOk7QrtDpO0/+KOVweHh5Prk3jm398V5nNXtZskDY6Q3ick/UXSfcX5V7lnKh6JU+4AmyRJkrQzS5JjaqsgaVvgm0CvcHBcFVhWTeqoRS40s2sK93YBVgW2MrOVKvVvZp9tYC4H40cRRcaY2TFxfRWuDruemX0o6Qt4NEm1/k6jKRtuiZvM7Oxq95jZJJp8KXbEo03GR90VdS5lsTCzc4FzW3j7cDM7CiB8f/4oaScze6rYSFIXM/tfo4JzKVaWJJ2HFCz76PFx3AlZA5cCnwdgZq+Z2b+AbwD94iV1MPCWmV0jaYik6yWNA67HQzrXih2UHSQdImmipGmSbovonZI42Ygon1b6hS7p+3Kxsql4KHHvYhhryQCRtA6wNXBqhJZiZrPN7O6o/6FcoG2mpJJc+3W4LPtEPP/LK8CF0b53aS4s7CC7o6S75KqwhwE/KKxtiKTjo90Wkh6L3aMRklaJ8tFycbYJcgG4kn7HIsT9mxQ+j46dmL5qEkkbL6lhAbl4Pg8BVwKHFvq/QNIkPKR4tqRlom6l4uckSZKk/fk4GiEjgc/FC/MySZVEtsrZGDdQBuEhs38Lg2Es8Ecz28rMeuJiXwfFPRcBD0d5L9wxdCM8+uNLYezMx0OJK7EJMLVSCKlccO1A3EjZBjhETREq6wGXmtkmuJPnXlF+DXB0zGcRzOx5PL/M+YW1FbkO+LGZbY7n8PlZoa6LmfUFjisrL2c4LtRGRK2sETsxT9MkknYacFaNPppjCp4kr8SyoflxOi6EVvop9V38u/ugvAOlWFmSJEm78LEzQsxsDi5SdSjwKjBc0uBmbrsjlEMrsamksfIonH1pEvjaGbg8xpxvZm/jWha9gYmxE7IL8MUWLGN7XHDt3VjPH2lSEJ1tZlPjejLQQy7qtbKZldREr29kMEnd4/6Ho+haPBS6xB+L49Xo6mZcbRXcGClJqHcHbgk/lfOpU4St2nTLPheji67CjTdYVOV2ASlWliRJ0j587BDRFFsAACAASURBVHxCYIE0+mhgdBgPB+DS4yWjrFzUrFbq+aG4cNe0MGZ2rNFWwLVm9pM6pjkLD4tdujlBrTLKxb2qqbK2JqUx51Pjb8rMXpT0uqTN8R2hw6LqDEKqPY6FRi/GXLbEd6RKLPjuzGxcOOXuCCxtZjOb6yzFypIkSdqOj91OiDz53HqFoi2AvwPP47sU0HSEUQ8rAi+Fb0HxaOVBXCeklJSue5TtrUg8J+mTkj5f3iFAqJFOAk6XpGjfQ9I3cD2M/pKWl7QCMIAmjYxKfb0FvCVp+yiqdgRULkpWuv9t4M2Cv8d+uDx+SxgOnAh0N7PpUVZNJK0h4mjtUCK6pgrX4TohFXdBkiRJkvbjY2eEAN2AayU9KRcU2xgX2zoduDCcGBvZefgp8DguiPV0ofxYYKfYaZmM5y55EjgVz/8yHc9/s0aNvg/GBbn+GkcVQ3EV2ClxPSHGvioE3GpxIHBpHAOVH1mUuBMYUHJMLas7ABcym44bbj9vZrxq3Ir7Y9xcKPsV8EtJT9D47tzAmO+zuIz+XuWRMWUMwxVjM0Q3SZKkg0mxsuRjhVzxdU8z26+e9ilWliRJ0jiqU6ysXXxCJM0xs26t2N/JZnZW4fN4M6spUtVg/8vgfgp74UcU84Cfm9k9LeirP/Bs7II0ct8QYI6ZndfomFX6G4pnpL21Sv3zQB8zey0+7wgcb2bfbI3xm5lbD2A7M/tDC+67y8w2rWe+ki7GJey/Hp9Hxz1VrYzUCUmSJZ/UF+m8LKmOqSdTCONsTQMkOAM/Jtk0BM1WB+oJ5a1Ef+AuXA10IRQCWpIex/U9iozHhcOWOCTtjuehKTLbzAZUuaUH8D3cV6O8ry64D8qxZVXjaFDgzMyObr5VkiRJ0l60m0+IyiS4JV1SCo2V9Lyk0yVNkSdF2zDKu0m6JsqmS9pL0tlA1/ADGBbt5sR/JelcuYDXDEkDC2OPlnSrpKclDSs5e1aY5/J4crmjC4JmL5vZzVE/KPqeKemcwn1zJJ0pFwR7TC5Wth2uK3JuzHcdLSygdWz8mn8X/y5eB/YIDZFXajzLDSVNKHzuEb4nSDpNLp42U9KV1dbZCHLRsqtj7s9JOqZQt398N9MklUJ/nwHeKFvTAElDJV0kFyR7Lo5GAM4Gdohn9AO5HPsdkkbhzrxDcf+ZLsDSwC/NbIHgWoX5rhDznSAXQNszyrtKuknSU5JGUCVySKkTkiRJ0i50JsfU18ysF66tcXyU/RR428w2C5GsUWZ2EvBeCGqVR3l8G3ea7An0w1/+JcfPLXExrY1xbY5yifYS6wL/MLN3yiskrYn/wt85xtkqjlsAVsAzuvbE08sfYmbjgTuAE2K+f4u2JQGtX+O5Z66N9Q3DRc5qYmZP41LzX4iigTTpYVwS4mmb4i/Z1jpO2RDYHegL/EzSMnL101OBnWPdpd2KWmtaA9c5+SZufACcBIyNZ3R+lPUC9jazr1D7e63EKfjfSl9gp2i/Ah6tNNfMNsJF1XpXujl1QpIkSdqHzmSEVBK86gdcWmpgZm8208f2wI0hDvYyHka6VdRNMLMXQgJ9KrVFtaqxFTDazF41s//hL9iSaNd/8WOX8jVUoiigtS1NxxDXxxrq4Wbc+ICFjZCdJD0eOyM7U7/wVyUP5WLZ3WY2L3xGXsGjdnYGbin5kZjZG9G21ppuN7MPw0dm9Rrzub/QX63vtRK7ASfJI4FG47ova+Pf1Q0x1+nA9GodJEmSJG1Pe/qEFMXAYFFBsLoErxaDchGvamP8FVhb0kqVdkNq8P/bO+9wu4rqf78fEoJAKNIUKUaKSGgBQhFDlSIWCApCRDFIkSKICsgPFKOAUhRRaYI0EUlokQhfCDUSSCA9oUgVEBCBoJSQUIT1+2Otnbtz7mn35t6Ttt7nuU/OmT17Zs2cA3vOzFqf9Z61hRo1GkM98bNmGYarjN4AmJk9IelDwPm4g+lz4dxaOc+1eBUPXZ0e71covYbm568R5XbqHRXNzRwJD9V9bI7CTpxMpVhZkiRJ99HKnZBngb6SlpDLiH+2iXtuZ85kax+Ol++peuKx0bhuRA9JK+O/fMdVqVcTM5sJXIJrhvSKfleWtE+0tb2klST1AAbRWLSrqgBYiTG4bga4iFhN0bEKO5/CFwM/pm0XpFhwTJfUmzaJ9GYYhTuAEmP7OnB3g3vuAvaRtGLct0KUd3RMjeaoo5/rSOCowh9GbXl17sEdYJG0IbBxA7uSJEmSbqTbFyHy6IZ3zOw5/Ajhofi3kbgWwKnAh8PJcip+vg+eKXVa4ZhaYji+xT4Vf0Aeb2b/7oTZP8LzyjwiFwm7CXjDzF7E/Rfujj4mmtmNDdoaChwXDpJrV7l+FHCgXASsWhRIPYbhi4VrYLYy6sX4HI/Es+k2yynAOjHPk/EdoT/Vu8HMHgZOA/4W950dlzo6pmnA++Hc+r0q1zv6uZ6CZxGeJunheA/ub9Rb0t9xsbWJDexKkiRJupFOiZWFM+ZwYP1wkqxXdxPg4nASLMo+BvzWzNr9UlcT2g11+toBeDccQmvVGUIX6m/U61/SYbgj5B+7qP3+wAFmdnSVa89Q0vnogr7qaruEU+rvgNXwxewfgVOtM1+o+ZgUK0uSJOk46maxskHAvfFvzdTt8RA+Go9KmY2Z/YuOHRU0yw64tkbNRUg3M0f/ZnZhVzYeC7N5/kSUtCQe9XO4md0mD2u+HjiCkiPxPLKtZzgNdwkpVpYkCwcpWDZ/0uHjmPA1GAAcRNu5f3Hth3INjamSTo+H8B7A8VE2KbQy+sQxR13tBkm7Shob910bfVfVFZHrbRwGfE/Vc59UG8vwqDtF0guSZkXbx5TqtNPBkPSliECZLOkOuSZIu/7l+hrHxj395Poh06LfD0f5KElnyDUtHq+0W9J5JRuflPS6pAMlrSjpNkkPS/oDdZw8JZ0u6cjSmP8d450m6U1JT8Q87tlozoKvAfeZ2W0w24/mO/hRVaErcmV8dk9IOqRky3FyHZNpkn4aZX3i8784xnNbLHQqx9Fu3iv6uw+4Uu47clapn29Hvd6S7ix9b5odb5IkSdINdMYnZE/gVjN7HHhV0uYAknaPa1uFZsSZUf8q4Lwo2wZ4saK9qtoNklbCfTN2Dv2QCcD3S/fNoStiZs8AFwK/Dr2Jhg6eZrZXCIMdhItrrQRsCBwiaVPV1sG4F9jazDbFfT6Ob6L/PwI/DO2MB5lzB6lnHFcdU1GOmR0Z7fXDE9qNNrPLot69ZrYBfjS2Zp2hDgO+Wow5xro1rsWxmpmti/vb/EpqKoRkAyr8KcJRtrekZaNoYzyE99PAyZI+JmlXYF1ca6QfsLmkIsR5Xfx7sgHwGtUzGbeb99K1vvh3ZRD+eb5uZlvgobyHyDVV3gb2iu9NzfEqxcqSJElaQmeOYwYBv4nXQ+P9RFzT47L4VYyZ/UfSMvhDbniUvQ3tQiW3I8SszGya3JkR/CHZF7gv6vcCxpbuK+uKfLkT4ygzABhuZm+FfTcA2+I6GdV0MFYHhskFs3oBT9drXNJywPJmVkTSXAFcW2MsfZq0eTti3GZ2s6SaGipmNlnSKnJfnJWB/0YI7+LAz2Mh8AHu3/ERoDPOvJXcaGazgFmS7sYXHgNwDY/CKbk3vvj4Jy7rPiXKa81DvXkfEf0RfWysNkXW5aKf52livGZ2Ee78zBKrrrtQ+bgkSZLMT3RoESIPwdwJ2EiS4RLaJum4brBNuGDVoBrXu1tXpB6/A842sxFyZ9Qhc9leK8ZyLe6H81HaQnr3xxclm5vZe3Ln1mZ0RR6hTaQNAElr4Q6/b8SisfLhbfhn+gsz+33FvX1or0NSTVK93ryXdUWEy+6PrOhnMB0cb+qEJEmSdB8dPY7ZG7jSzD5uZn3MbA381+i2uKbHgXInRSStYGZvAs8rpM3lGiFLVbRZS7vhfuAzktaJa0tL+mQD+xrpTdRiNDBQ0lJyee+9oqyWDsZywAvx+puN+jez14H/lvw9vkFjfZFGlOdtd1xorB7DcB+evWnbhVkOeDkeyDsCH2+y76uAAZJ2jv6XxHezzizV2VPSh2LudsDDhUcC31Kbb89qklZpss/C3mrzXslI4PDY6UHSJ+Nz7ex4kyRJkm6go4uQQbj/QZnrgUFmdiseMTFBLpdd5H/5BnB0HLOMwX+Jl6mq3WBmrwCDgavj3rF4/pJ6/BXYS40dU38k6fniz8wm4UnSxgEPAH8ws8l1dDCG4GqlE5lTVbRe/9/Ec5hMw/0hftZgLI34KbCdXAfjy/iRRk1iLMsAL4TeCfhior9c4v0AoG64damtWbj/z48kPYb7uIwHzi1Vm4brqdwPnGJm/wpH1j8DY6PP6+jYonEI1ee9kj/guzWT5A7Qv8d3mDo13iRJkqR76JROSJLUQ92oxdJqUickSZKk46hJnZAO7YRImtF5k6q2d2LF+y7V95Bnej1dHiY6SR4yunsn2xooqW8n7psdptsVSLq85HBZ7fooSRNK7/vLBeDqtdlP0uc7aEcfSV9rsm6Xfm+izW797iRJkiTdT6sdOis5Efh58cbMtumqhiWdhAulLQ48hy+47qZzPiMAA3H59keq9NWlAlmSdgPOqCh+OsJr6923ItAf6CXpKdxHZUlcgr4e/eK+/6tobyM8C26Zd8xsKzx65Wu0ZcudjZkNadBfV9Bt350yKVaWJAsHKVY2f9IZsbIdJN1Uen9uRB1UFRGL8t6SLouyaZK+Iul0YMnwn7gq6s2IfyUXm3oo7tm31PcoSddJelTSVVJNXYtf44usPma2SWhtnGhm10Rbg6LthyTNfuBLmiHpNLk42f1yIbJtcNG1s8LetcOOc2LX4buxM3BXjO9OSfV0O4q+PiVpXOl9H0kPRlTHDcB7MYZxNBGGbGav4noqPwBeDG2R/fEMxoSjaPE5TJa0ozxJ38/wBHFTirmO9h7EF19v4iGtHwBFbpfTgW3jnmr5XqqNd0H57iRJkiQtoDsS2M0hIhZlP8bFozYKsa67zOwEYFYsDvavaOPL+K/zTXD9kbPk2hAAm+KiXn2BtYDP1LBjHeCfZvZG5QW5XsYZeLhxP2ALRQQPsDRwf4iT3QMcErlgRgDHhb1PRd1eZtbfzH6Fh49eEeO7itA+qYd53p1eciEtgH1pC58918y2MLMN8d2MLzZqr8RY4F15BEiZI71b2wh3Mr4C/w6cDAyLsQ2ruOdlYJf4TPctjesEXDitn5n9ugO21WO++O4oxcqSJElaQncsQqoJb+1MKaeImdUU1goGAFeb2ftm9hIezrpFXBtnZs+b2QfAFJoX9yqzBTDKzF6JY5SraNO9eBc/dqkcQzXKD+xP03Y0cWWMoRmuwR/uMOciZEe5RPmD+GJpgybbKzgVV3stM4DIjBsLoGeBRmHPiwMXhx3X4g/w7mK++O6Y2UWxuOzfY6nlOjWQJEmSpDGd8Qn5H3MuXirFnrpbeKtS1KpWH08Ca0pattpuSB3es7aQoUZjeKvOtWYZhoed3oDvUjwh6UPA+XhW3Ofk0SbNiIjNxszuknQqrjw7N3wPeAnfWVgMlz7vLAvKd2c2KVaWJEnSfXRmJ+RZoK9ceGx54LNN3HM7fhQAgCJ5G/CeQlCqgtG4j0IPSSvjuxTjqtSrScjHXwL8JvwekLSypH2ire0lrSSpB3400Ug8rJEQ2hjaEvrtH2Noxs6n8Afij2nbBSkeztPlwl6dzTh8KnPmVxkdtiEXflsTeIz6Y1sO9y/5ANd86RHlnRGGWyC+O0mSJElraHoRIqknHhnxHH6E8FD8O7nujc6pwIfDWXAqnjwMPD/HtMK5sMRwXOxqKq5aeryZdSafyY/wyJBH5KJVNwFvhFjXCXi0zFRgopnd2KCtocBx4dC5dpXrR+GKsdPwh/V3q9SpxTDg6/h8YmavARfjczwSFwLrMGb2f8wZGXM+sFgcrQwDBpvZO/g89K10TC3d88343D5F2+7PNOD9cOCt6ZhafG/CngXpu5MkSZJ0M02LlUnaBLjYPNtrkjTFgv69SbGyJEmSjqMmxcqaOneXdBiuuXHM3Bq2IBERM8OB9cORsyP3fgz4rZm1O0qRi4cda2YdfrrJE7e9GxE7teqsh0uVLw8sgUexHNqJvpYHvmZm53f03ri/3fdGnqzupoj6qXXfAFwif9koOjsy2xafyeNm9ki8H0Un57IZUickSRYtUk+ktTR1HGNmF5pZ38j9Md8haXgcJZT/duuCpgcB98a/HSJypcxegEg6r7ANFwa7StKBnbBpB2CbBmP+LfDrCGFdHw8f7gzLA0d08t5OfW8kfRSPMjrMzD6FR7t8W1Lxf4aBdFGEThwVJUmSJPOI7gjRbTlmtlc8cMt/IxvfWZtwCB0AHESbwymSfhgiWFNDNAtJ60i6I8omycXM+oQfSpFldkV8V+Jp4GFgfzO7TNKucjn5SZKuVVuG2XbiXbGLcBgesfIJPF19tTGvCjxfmp8Ho83Bkm4M0a4nJP2kNK7vh9/FQ5KKnYvTgbVjgXNWjXkaWlogzJaVj/GPDvsnyQXfmuFI4PJIKoiZTceda09QFdG4uGcfSeMkPa5IHBiOqWdJGi8XOft2lO8Qdo2givptkiRJ0jryl2Bt9gRuNbPHJb0qaXNglSjfysxmSloh6l4FnG5mw+XhtYtF3YLDgZlmtr6kjYFJAJJWwp1ndzaztyT9EPg+bRl2p5vZZpKOwI8cDpZ0IY2Tw/0auEueT+U24LJwdgXYEtgQmAmMl3QzYMCBwFaAgAck/Q133t0wlFdrMQz4KnCzPArpszFe4SJnb0taF7ga3wFqxAa4iFqZCcAGZjYmFg83mdl1AHLR055mtqU8/81PcG2Rg3CRsy0kLQHcJ6nYkdksxvV0NQMkHQocCtBj2ZWbMDlJkiTpDLkIqc0g4Dfxemi8F/5AnwlgZv+RtAywmpkNj7K3YfbDsWA7QmnUzKZFBA24hkdf/AEJ0AtXOy0oi3c1lG0viB2WkcDn8EXTt8NBFOB2c3l35NokA/BFyHAze6tUvi2uEtuIW/Aw6CWiv3vMbJak5YBzJfXDQ5AbiaLNDdVEznYFNlZbsr/lgHVxMbpxtRYg4GJlePQNS6y6bqaZTpIk6SZyEVKF2OHYCdhIkuHaGIYrhnZpV/iioJbPSafFu8zsX8ClwKVxLFQ4glY+VOfqIRs7HaOA3XDF16FxqbMiZ48AmwPlkOnN8SOsWlSbJ+HHVXMcy4Vjb9MicylWliRJ0n0sFD4h3cDewJVm9nEz62Nma+C+HK/jWiBLgS9WzOxN4PmI2kAuxLVURXv34BlnkbQhsHGU3w98RtI6cW1puYhYPRqKhEn6nELIKxw9VwReiMu7SFoh/FQGAvfhAl8DJS0laWlgryhrVpBsGH6csy1wa5TVEjlrxHnA4NhBKTIDnwGcGdebtWkkcHhpHj4ZY0uSJEnmE3IRUp1BeGhumetxh88RwAR5lEuRZO0bwNFxzDIG+GjFvRcAvSX9Hff3mAhgZq8Ag4Gr496xuCBYPf4K7BWOmdvWqLMrUIh7jcQT7xWCXeNiLNOA681sQjiBXh7XHgD+YGaT49jmvnBWreqYGtwGbA/cYWbvRlktkbO6hJDc1/F8NY/i83mpmf01qjQSjSv4A76rMil2gn5P7vwlSZLMVzQtVpYs+EgajOej+c68tmVBIcXKkiRJOo66UqwsWTiJRclt4T+CpGfwRcr0eWhTH+qImYVPx4348Rh4BNHOcmG0mWb2x660J8XKkmTRJEXLWkMuQhZgJJ0E7FNRfK2ZnVatvpldjh+7FAzG87j8q4m+NgKurCh+x8y2ius9zex/TRnu9XfDfT3KPI07tDZitJl9sVxgZhc223eSJEkyf5A+IQsQko6TdHS8/jXw2dDw+D4ePXI88EW1Fz47OUS7HpJ0kZy9aVNunRKOqgBHqSSQFvcvjS8O3sWjaX4S/V4gaYSku4A7a9hcVcyMtuy9H8TfEWa211zMzRBJx8brUZLOaFbArEpbh0qaIGnC+zNf76xJSZIkSQNyEbJgMRqPQAFfQPSO6I9tcUfTQvhsM1zg6/tR91wz2yKOOJYEvhhiXxNw5dZ+ZjYr6k6P+y+gzfH2JOCuSEK3I65YWkSabAbsbWbb17C5EDOjJGZ2M/AyLma2GR7a+9sOzMO2apOqP6lGnZ5h7zG4gBmUBMyALYBDJH2i8kYzu8jM+ptZ/x5LLdcBs5IkSZKOkMcxCxYTgc0lLYtrY0zCFyOFsFgt4bMdJR0PLAWsgO+a/JXqVBNI2xXYo9hpAD4ErBmvbzez/9SxuTvEzNodxzQYR5/SOKoJmNUULkudkCRJku4jFyELEGb2nqSncV+OMfjux47AOviDtJ3wmVxG/nzc4fQ5SUPwRUQtagl/fcXMHqtoeysahN52g5hZszQtYJYkSZLMG/I4ZsFjNH5Mck+8PgyYTG3hs2LBMT18RPYutdUR4a+jFFsskjbtoM1dKWY2N6SAWZIkyXxELkIWPEbjomljzewlfAdhdC3hs0hcdzEeBTMSGF9q63LgwgrH1GqcAiwOTJP0cLzvCF0mZjaXpIBZkiTJfESXiJVJeh94EP8f+tPAN0pZW+em3SE0yBgbfgoH4w/j94DfmdkfW615EbLtj5tZy9PDNxIhi3k8HuhjZi9H2Qwz612nzeWBr5nZ+XXqDMSVZdc3s0fnwv7Licy4kv4AnN3Reaw3B43GWo8UK0uSJOk4rRYrm1Wke5d0BXAkUFWroisJgapdgC3N7I1w2Ox0mGep3Q5pXgQDgZvwX9rd2U9nmQ78APhhk/WXB47AdyxqMQi4N/79SZ16TWNmB3dFO11FipUlyaJLCpZ1P91xHDMWWA0g9CjOCn2KByXtG+W9Jd1Z0qPYs7hZ0kmh7XAvsF6Dvk4EDjezNwDM7A0zu6J0vZrmxZaSxspzj4yRtF6UDy5rXjSw8YDQmZgq6UpJ2wB74KGrUyStHX+3SpooaXSp/8slXSjpAdqSslFqezFJz8RORFH2hKSPSPqSpAfC9jskfaTpT8Uz6u4rzxBc2ef34zN6SNIxUXw6sHaMp13emPAvGYCHve4naaOo+6SkGZJelzQrxrpY3DND0q8lPRxzu3KVdkdJ6i9pN0lPSZoZ7bwpaXitzy9YI+5/QlLVRZFca6XQCflpB+YvSZIk6WK69DxcUg9cB+KSKPoy0A+PgFgJGC/pHuAVYK/YvVgJuF/SCFxzYr+4pycegjqxRl/LAsuY2T/qmDTdzDaTdATuzHkw8CiwrZn9T9LOwM+Br0T9zYCNzew/knrWsLEvrsexjZlNl2fS/U9cuyn0N5B0J3CYmT0hjyI5H9gp+lk97n+/0mAz+0DSjfiOzmVx77Nm9lIszLY2M5N0MH7E8oM64y8zA1+IfJfSroWkzXGn0a3w6JEHJP0NOAHYsNjhqsKewK1m9rikV4FeZtZPLqt+K54p+Nl4/WXgOmBpYIKZfU/SyWFHrTw2k/Aw4w3M7OnSPC9L7c9vS2BDYCb+XbvZzGafpUjaFQ/J3TLGOkLSdmZ2T7ljSYcChwL0WLbdOilJkiTpIrpqEbKkPKvsasDfgdujfABwdTxsX4qH2xa4dsTPJW2Hq2WuBnwEj54YbmYzAeLBPjdU07xYDrhC0rq4+ufipfplzQvVsHEnXBp9OkA1jYzYJdgGuFYeUAKwRKnKtdUWICWGAScDl+GLsmFRvjowTNKq+AO6pr5FDX4LTJFU9rEZgM/5W2H7DbTpjtRjEPCbeD003hcLxnHF4lDS1dHHdfg8FmP5E22fTzW2xjVFnoY55rnR5/dqaRwDcEG2gl3jb3K8740vSuZYhJjZRcBFAEusum5meEySJOkmutQnRNJSeATGkdRXwNwfWBnYPLQvnqG+dkU7YodihqS16uyGVNOKOAW428z2kidLG1WqX47QmBsbFwNeq7OL0CgSZCywThxXDAROjfLf4U6bI2LHYUiT9gBgZq9J+jP++XSaONLZCdhIkuHhtSbpuKKryq5rmdSJ7ut9fo36FfALM/t9s52lWFmSJEn30aU+IbGDcTTwgzjOGI37IfSIB+p2wDj81+zL8XDfEfh4NHEPMFDSkpKWAb7UoMtfAOfFFn3ha3JAg3uWA16I14Mb1Ktm413APpJWjD4LH4vZmhvho/K0pH2ijiRt0sCu2ZiHLA0Hzgb+Xvy6r7D9m822V8HZwLdpW5SNxud8Kblmxl5RVk9DZG/gSjP7uJn1MbM18F2ZQlJ+S0mfCF+QfXHnVfDvW6FT8rVSeTXuB7ZTyKqX5rne57eLpBXk4cYDgfsqro8EvqW2nDqrSVqljg1JkiRJN9LljqlmNhlX8hyEP0inAVPxh/fxZvZv4Cqgv6QHgQNwPw3MbBK+XT8VP7IZ366DObkAuBs//38If3h+0OCeM4FfSJpM/Z2gWjY+jEf+/E2ucXF21B8KHBcOk2vjOykHRZ2HcR+KjjAM+DptxxfgOx/XSpqIR7t0mDhGGk4cD8WcX44vDh8A/mBmk2Phc5/cWbXSMbX4bMtcH+Xgn9u5+NHc06W6b+ELlIfwnZSf1bHzFdwv44aYw2Ie6n1+48KOacD1ZX+QaPM24M/A2Phcr6M5sbYkSZKkG+gSnZAkKYhjomOr5XbRXOh1zCtSJyRJkqTjqMU6Icl8ROXDXiUhL7m2yswQdBsM3GZm/6rT1ihcofVt4F3gEDOb0p321yP8QG4yzwhc7foO+O7YHmb21yi7CfilmY3qaH+pE5Ikiy6pE9L9LBCLEEnnAZ+pKP6NmV02L+zpKiQdiIfMlrnPzDrlOCpPa78PbdFKANfS5kOBmV1YumUwLudecxES7G9mE8Les3CBuKrEg35UjWut2gV5HjiJ2pmCkyRJkvmABWIR0tmH8vxOLKK6bCFlZqcBp8VOyOzInNjxKF4PwTVDngH6A1dJmgV82sxmcEodXgAAHb1JREFUNehiLFBEwMyx4yJpb+CLZjZYLsP+RrT/UdwX6LpqDUoaiju53hzvL8eVZycAV+LaIgDfMbMxjWcBcJ+ixSXtYma3ly9I+izwS/y7Px4Xu3unShtJkiRJN5MJ7BZOlpSrl06JHZF2DqCxKJiA73L0a2IBAvA54C9N2rAqrtPxRVx9tRbDgK8CSOqFi93dDLwM7GJmm+ERNvVCvqtxGi4qNxtJH8KdcPc1s43whcjhlTdKOlTSBEkT3p/5ege7TZIkSZplgdgJSTrMrCo7IQ0dhOpwVSwQeuNqts3wFzP7AHhE9eXlbwF+I2kJfJFzj5nNkrQccK6kfrjOyyc7YrCZ3SMJSQNKxesBT5vZ4/G+yHN0TsW9KVaWJEnSAnIRkjTD/rga6lm4YFqhPlt+QFcKuZWPOEQNzOztcH7dDd/xGBqXvge8hEv+L4Y7xnaUYjek00kCU6wsSZKk+8jjmEWbeoJkcxACaj8GtlYk48Ol+NcPUbK5yV48DM9fsy2eawZclOzF2E35Bq7K2iFCF+TDeB4bgMeAPpLWifffAP42F3YnSZIkc0EuQhZtLgcuDN+RJRtVDr+RX9HmnHoC7kQ6BnhxLuy4DdgeuMPM3o2y84FvhlDZp2gsdV+L04A1wHdd8MXOtSFW9gFwYZ17kyRJkm4kxcqSpA4pVpYkSdJxWiZW1tUqmJJONLOfl96PMbNturD9xfEkaF/BjyPeAX5mZrd0oq2BwONm9kgH7xsCzDCzXzaq22R7l+MCXrXCYEcBvYsvhKT+uHjXDnXa7Ad8zMz+r06dc3BdkjXi2KSz9j+Di6lN7+znXWsO6im4NkOKlSVJ0h2kEJozPzqmngjMXoR05QIkOAUPH93QzN6JyI3tO9nWQPw4ot0iRFJPM+u0Q2Q3sIqk3WsttiQNBz5RKloBT3lfdRFS8gN5Dp+/u+t1LmkjXPejzDtmtlW5oNnPW9JuwBmlojWB9fF8MEmSJMkCQJf4hEjaIaSxi/fnFgJZkp6R9FNJkyQ9WDg1Rsbby6JsmqSvSDqdNo2Lq6LejPhXks6KhGoPStq31PcoSddJelTSVZKqRmNIWgo4BDiqEKgys5fM7Jq4PijafkjSGaX7Zkg6TdJUSfdL+oikbYA9gLPC3rXDjnMkTQC+K6mPpLtifHdKWrOJufyUpHGl933CfwFJJ0saH/ZdVGucNTgLVxGt7O9Dki4D1sGjXb4HbBmXt4mx7VulvR3wxHwX0Ja4DklDJF0paaykJyQdEpdWxAXMXgCWxLPkfrqKPTNKr38Yn8fU+G4g6RBJ4/FEdk8B20Q48ghgcuh7PC6pWu6apSVdKmmcPNFg1aSCSp2QJEmSltAqx9TpITp1AXBslP0YeN3MNjKzjYG7zOwEQuPCzPavaOPLuEbFJsDO+MN/1bi2KXAM0BdYi/YS7wXrAP80szcqL0j6GP7LeqfoZ4s4bgFX7bzfzDYB7sHzp4zBH3zHhb1PRd1eZtbfzH6Fh7NeEeO7iiYEt8zsUaCXIoU9HrZaZJA918y2iLwpS+JCYM0yFnhX0o4V5Ud6t7YRvpi4Av9enAwMi7ENoz2DgKvxDLlfiGOugo3xefw0cHLMLfji5ij8c1qbtlDfdkjaHc88vFXM+5lx6YaYg03wLL0HlW7rE318AXe4rQwbPgn/nm0J7Ih/h5auqIOZXRSfYf8eSy1Xy8QkSZJkLmnVIuSG+Hci/qAAX0icV1Qws/82aGMAcLWZvW9mL+GhlVvEtXFm9nz4JUwp9dERtgBGmdkrcYxyFbBdXHsXP3apHEM1yg/sT+Op48GPIga0r16Va/DFB8y5CNlR0gOxM7ITsEGT7RWcSoWKaNj0J5i9AHqWBsJgcuGyz+OCZG8AD+A6HwU3mtksM5uOH9MUOyvjzOwfZvY+voCpNx87A5eZ2cyw7T9RvqGk0TEH+zPnHFxjZh+Y2RPAP/ComjK7AifIVWRH4domDXenkiRJku6hq3xC/secC5pawlXvd2Gf1dpv1MeTwJqSlq22G1KH96wtjKjRGDobSlpmGB5GegO+S/FE/Ko/H3fgfE7u3Fo5z3Uxs7sknQpsPZf27QYsDzwYJ0JLAbNoW6hVhlxZg/KOcDkw0MymxpHfDnXaq3wv4Ctm9liznaVYWZIkSffRVTshzwJ9JS0haXk8/0cjbsePAgCQ9OF4+V7F1n7BaGBfST0krYzvUoyrUq8m8av6ElwmvFf0u7KkfaKt7SWtJKkHftzQSMiqkdjXGGC/eL1/jKEZO5/CFzs/pm0XpFhwTJfUG9i7mbaqcCpwfOn96LANSZ/EdwYeo/7YBgEHm1kfM+uDO7TuEj43AHuGr8mK+CJhfJRvKekTcqfWfYF769h5O3Bg0aakFaJ8GeDF+I5UHtntI2kxSWvjx3KVi42RwFGFL42kTev0nyRJknQzc7UIkdQTj3B4Dj9CeCj+ndzE7acCHw4ny6n4GT14zo5pCsfUEsOBaXiG1LvwzKz/7oTZPwJewXOaPIT/en/DzF7Exbfujj4mmtmNDdoaChwXTo5rV7l+FP4gnYarc363A3YOA76Ozydm9hpwMT7HI2l7sHeICLl9pVR0PrBYHG8MAwaH0+7d+MJyDsfUWBR8Dk8yV7T5Fr6g+FIUTYv77wdOMbN/Rfl44Fzcl+Np/DOtZeetuM/NhDg+KfsSPQDcBzxacds/8cXkLcBhIU5W5hRgcfz79XC8T5IkSeYRcyVWJmkT4OJw9JuvkXQ3cLqZjSyVHQOsZ2btMqnG9T649sSGVa79DE+2dkeNe3egE/oU8ZC/GHfuFPAa8Dkzm1HnnlHRV11VLUkH0rYQ6ovvFLwP3BpOwXONqmigyGXSH8bzvzwDzMAXO0802eaDwCAzeyh2QN4ADjSzoXF9KvANM5tW4/6dge+Y2cA4jppuZudUq1tJipUlSZJ0HHW3WJmkw4Cj8aiUBYGr8aORkaWy/ZjzaKJpzOzkrjCqCt8FXopoFSStB7zXFQ2b2WXAZdHuM8CO4TzaCp4DHjWzL0o6Et91OqjBPQX3Advgu0Cb4Tsp2wBDJS2Dy7I/1PUmp1hZkiTzjkVB0KzTxzFmdqGZ9Y0kYfMdkobHUcKU2M4/Ctir5AvSB/gY4ach6bjQ4Jgm6aelpnpIuljSw5JuU+RYkXS5pL3j9RaSxoSexbh4MJZtqapPIem8so1h5064lgYAZvZYiKr1ieOjos1jY9eh4BuSXpM0S66TUbRZjlqpNVeLSXqy8LsIv5t/SFpB0p8kXSBpYrS7e9TpKensGNM0SQeHvUNqKMHOKO0KLQv8N9oZI2n2TpNch6Uy6mcMvugg/j0fX4yAO9mON7MPJG0t1yeZLOk+Ses2GPfhkm5W+1DeJEmSpAXMj4qpXYKZtcvqKhdU2x24Ed8FucbMTNKuwLp4KKmAEZK2w30M1sWPAg6RdA0u9/6nUpu9cF+Kfc1svKRl8UiRMoU+xbfkjrvjJN1hZkdW1Cvk0m+LBc6duM5IM8cWS5nZ8mH3+SHg1RTxAL8a+Brus7Eb/mD/T/hwroGHMK8L3BHHKwcBL5vZlpKWAO6XdJuZ/bNGN+vFImtZYAmgUEq9BBgMHCupL35E+HDFvffRFlq8DfD/gAPi6GobfJECvkOyrZn9T9LncL+jakJrxVHc9sBe1pY0r7h2KHAoQI9lV64xnCRJkmRuWdSy6BZHMsS/V8frXeNvMjAJ15cofkU/bWZT4nU1jZD18JTz4wHM7A1rL9fetD5F9LUWrnC6AjBe0vpNjg0zuwdYNhY7HeES4Jvx+lvEsU1Q6G88hh+rrBtjOjDG9AAesltv5+GxED5bCz8CK7LXDsOjaXpW6ZcY01MxppWAdczsSWACvmjcBl+kEDZcHztGv6S2jsqB+I7TPpULkOgvxcqSJElawEK7E1KDG4FfS9oM3zmYGOUCfmFmvy9XjiObSg2Shinvq9AhfYpwQr0BuEHSB7gw2DDqa7HMlQaHmT0j6b9yRdVNgfIxW7W2BRxhZnd2pJ9gBK6ei5nNCMfaPfBdplo7OGPw0ODn4v39uNhZf3wRBHAaMNLMzo/dmltrtPUgPsbV8PDymqROSJIkSfexSO2ExMP9buBS2nZBwJ1VvyXX30DSapJWabLZx4BVJW0R9y4Tv+rLNK1PIekzCs2UOOrpiz8oX8KT0K0Yxx+VUTdFLp0BuBx+Z5KeXIIrxQ61ObPi7iPnk/jRzBMxpiOKsUpar/CXaYIBeN6Xgj/gx0Bj6tg9BneCHhvvx+I7Gv80szejbDna/GkG1+l/AnAE8FdJH23S5iRJkqSLWdR2QqAt30lxLIOZ3RZHHmNjnTAD1+h4v1FjZvauXEfjd/EQnoVLjpc5BTgH16dYDNfIqBW6uzZwQSxYFsP1OK4P35Wf4ToYL9BeI+NtSZNxHYxvNbK7BsPxBdrlFeUv4A/u3sChMebf40dKU2LOXsZzvdSi8AkRvrt0aHHBzB6QNJMqRzEl7sOPqMbGPc/FYmxMqc4ZwKWSfoJrhdTEzP4m6QTgZkm7lGThkyRJkhYxVzohycKFpK3xY6kdS2V/Aq4zs790Y79r4Aqp69t89oVMnZAkSZKOoyZ1Qhb64xhJ70eo6kOS/toJh81a7Q6RdGyDOsdKejT6Hy/pgCh/JpwsW4KkgRF5Uq/OSbjfyYld3PdgSefWuX4grlDbG/h7hPwOKF0/Rm1y8EiqKdqWJEmSLFgsCscxs4pwVUlX4PlqTuvuTuVibrsAW5rZGxG6Ww4b3jEe/GWerhZaXNFuzyrRN9XqldVR1wRel/R/1cKCAczsNErzUvRjZl9v1Ffpnn60P8pZmjkF4ip5BT+e2s3MpofT8F8kbRmy/MfgIdEzm7Wjjn1NzV2ZFCtLkmRhYX4UP1vod0IqGItHRBCOlmfFDsmD4deBpN6S7pQ0Kcpn+zlIOkku2HUvHppbjxOBwy2y9Ubo7hWl6xsCHwA9gP1iofQLtYltjZGrpRa7CSMk3QXc2cDGA+S5ao7Bo0COKPX5GUlrx9+tcgGy0ZI+FfdeLulCSQ8AZ1YOSC5q9kx5N0nSE5I+IulLwO/xyJnp+KKiH40XfD8EjiuUW81sEnAFcKSko3FBubvlsvtFn6fJheHul/SRKFtZ0vWx4zRe0meifIikKyXdB1wpaYPYbZkiF1mrK2iWJEmSdB+Lwk4I4CqgeHbfS6Loy3g46CbASrgexz34L/O9YvdiJVyEawSu0Llf3NMT1xOZSBVi12MZM/tHHZOmm9lmko7Ak7MdjDubFmJbOwM/x8NWif43DgGxnjVs7IuLem0TuworRP0ReA6c68K+O/EEb09I2gpXIN0p+lk97m/nlBuiZjfiOzqXxb3PmtlLsTDbOhxoD8a1QH5QZ/wFG1SZxwnAN83sy5K+z5zy8ksD95vZSZLOBA7BRcl+A/zazO6VtCa++1Loq/QFBpjZLEm/A35jZlfJo496VBqkFCtLkiRpCYvCImRJeVTGarii5u1RPgC4Oh62L0n6G64Kegvwc7ny6Adx30eAbYHhZjYTIB7sc8MN8e9EfEEEHmJ6Rfw6NzzSpeD2UgSHati4E3BtaVehXcSHPAx5G+BaeVQLuIJpwbXVFiAlhgEn45Es+8V78MXLMEmrAr3wI5bu4F088zH43O0Sr3fGs/4W9ZaNsQKMMLNCxXYscJKk1YEbqqnRmtlFeDZnllh13fnKUTZJkmRhYlFYhMwys37h3DgS9wn5bZ36+wMrA5ub2XvyRG8dyi0SOxQzJK1VZzekEEF7n7bP4RTgbjPbSy6UNqpU/60usnEx4LU6su5v1SgvGAusI2llYCC+CwHwO+BsMxshzyA8pEl7HgE2B+4qlW2OZ92txnulCJry3C2G78S8Xa4ci5LZYzKzP8dx0xeA/5P0bTMr9z0HKVaWJEnSfSwyPiGxg3E08IM4zhgN7CtP1rYysB2uwbEcnhPlPbl66MejiXuAgZKWlCeo+1KDLn8BnBdHM4WvyQEN7mlWbKuWjXfhwmIrRp8rRPmbwDIxD28AT0vaJ+pI0iYN7JpNLACGA2cDfzezV6vY/s1q99bgTOCMks398LGfX2l7A27DkxRSaqcdktYC/mFmv8UVdDfugK1JkiRJF7LILEIAzGwyMA2X/x4er6fiD+/jIxrjKqC/pAeBAwhRsHCYHBb1bwHGN+juAlyddbw8l8lo/OikHmfizqmTqb9LVcvGh3FH0L9JmoovFACGAseFw+va+E7KQVHnYeqLjFVjGC7mNqxUNgQ/4pmIO6Y2hZmNwAXSxkh6FLgY+LqZvRhVLgJuLTum1uBofE6mSXoEOKxGva8CD8UR3YbAH5u1NUmSJOlaUqwsSeqQYmVJkiQdR02KlS0KPiENkecPOQd3TH0Nz9NyjJk9XqVuHzzSZMPwfTjWzL4oaQ+gr5mdXqOP/sABZnZ0F9i7IlAkjvso7hvxSrzfslpm2HlFRM18x9oyEVde/zDuT7I17nA7Gjg6/GrWwsczNOoeDGxoZse0xvrUCUmSZNGkVZoii/wiRO65OBy4wsz2i7JN8GiTdouQKmwYW/tFe/vhIaBz5EExswl46OlcE34YhQDbEGCGmf2yK9ou0JxiZwX31RI7a6K9k4B9KoqvxRd+EwpRNEmn4nojg4C18AicoZ3ps4oNHRYrS5IkSbqPRconpAY74hEXFxYFZjYVuFdVxMyq8FBEmpwD3BuvZ8R9U0N7BEk7SLopXq8g6S/hv3C/pI2jfIikSyWNkvQPuVhXh5D0c0nfKb0/Q9KRknaWdLekWyQ9Jum8WIAhaXe5SNokScMkLW1ml5lZv/IfcIukq0tt7yzpL/H6IkkTJD0s6eRKu8zstCrtXYf7Zfy8VHUILqrWBzgdV5adUpqL1SWNlIuk/aJkS7sxRPnzkk4PP5u9JH1P0iMx93+qMYeHxlgmvD+zM8mIkyRJkmbIRYg/BKuJjpXFzHYGzpJrYDTDybhi6CbAHlWu/xSYbGYb48qqZefITwG7AVsCP5G0eJX763EpEZ0iF2jbB/hzXNsKOBwX71of2FPSKsAJwGfNbDPcWbdyB6TgNmCAPFswwL607VKcEOd/mwC7qEGummADfB5mO+zGTsXUsPEEPGS5X0SzEO3vg0e1fF3Sx5oYw8tmtqmZXYuLqPWLuf8OVTCzi8ysv5n177HUck0MI0mSJOkMi/xxTB1qiZlNa+Le+4DLJV1DmyhZZdtfATCzuyStWITyAjeb2TvAO5Jexo+Fnm/WaDN7UtKbkjbCQ3fHmdl/Y9PjfjN7BkDS0LAD/IE/Jur0Au6t0fa7km4HviBXTv0cLg8PMEjSQfh36mPR5iPN2t0B7iik8COaZk3cL6beGMpRPA8Dfwr7uy0zcJIkSdKYXIT4Q2nvrmzQzA6TS5p/AZgoafMO3P5O6XVZjKsjXIJrbfTB/Stmm1ZRz3Bn0FvN7BtNtj0Ul5ifCYw1s7fkCq/fxZ1IX4tjjmbE0x4BNpWkQoAsdm82jmvrVLmn2vw0GkNZgG03YHt8h+pESRvXU4hNsbIkSZLuI49jXCNkCXm+EADCR+M1qouZNUTS2mb2gJmdjEetrFFRZTSu1UFE2Ewvft13EdfjYmr9gDtK5VtLWjMe9F/FdwvGANtHJAqSllb9pG534cc6B9F2FLMsLir2RhxZ7daMkWb2KL7Y+H+l4p/QtmPTrFBZU2OIca8eCqnH4zmDlmrG1iRJkqTrWeR3QiLh2l7AOZJ+CLwNPIMfM/TG/ROMEDMLh8lGnBUPQeGhtFPxX98FQ4BL5dluZ9IxhdGGmNnb4RD777K/Bb6IuhBYG1+cjIjxH4TnfekV9U4E2uVUibb/J+kW4GvEQgpP5vcILpr2LH4c1SyDgXMlPRXv7yOSxwGTgR5yUbVL8LmqZtNLTY6hJ/BnueLtYsAvzezNesZNnDhxhqTHOjCeVrISHRCGazFpW+dI2zrP/GzfomjbxxtXSbGyhRJJiwFTgIFF7hp5Vt7vmNnAeWrcAoakCc0I7swL0rbOkbZ1jvnZNpi/7UvbapPHMQsZ4ZD6FO4jUSt5XpIkSZLMcxb545j5Hc2pjlrms6XkcbMxsweBT1Qpv4M5/UMa9TsCjzwpc2y002EkTaD99+1rZtYdETRJkiTJAkAuQuZzyuqoLe63mr7J3LQ3X25FNsFF89qAOqRtnSNt6xzzs20wf9uXttUgfUKSJEmSJJknpE9IkiRJkiTzhFyEJAs9kj4X+XKelHRCletLRL6ZJyU9UA7DlvT/ovwxSbs1alPSJ6KNJ6PNXtShq22TtIY8R9Aj8jw+3y3VHyLpBXkunimSPj8P5u0ZeS6mKeEnVJSvIOl2eU6g2+XZlVs5b+uV5mWKpDckHdPKeZMrJ98taYakcyvu2Tzm7UlJv5Vm531qybzVsk3SUpJulvRofN9OL10bLOmV0rwdPA/mbVS0WdiwSr22Wjhvy1R836ZLOqfF87aLpInxvZooaafSPV3yfWsKM8u//Fto/4AeeLTQWric+1Sgb0WdI4AL4/V+wLB43TfqL4E7+z4V7dVsE7gG2C9eXwgc3mLbVgU2izrL4JmgC9uG4M7F82Te4tozwEpV+jsTzz8EngfojFbbVtH+v4GPt3jelsZTKRwGnFtxzzhga1x76BZg9xbPW1XbcLG/HeN1L1yIsbBtcOU45sG8jQL6V+mvaluttK3i/onAdi2et02Bj8XrDYEXuvL71uxf7oQkCztbAk+a2T/M7F1c5XXPijp7AlfE6+uAz8bKf09gqJm9Y2ZPA09Ge1XbjHt2ijaINuvpsnS5bWb2oplNAjAXYvs7sFoT89TttjXor9xWy+et4t7PAk+Z2bMNbO5S28zsLTO7FxdMnI1chXhZM7vf/P/+f6Rtfloyb7VsM7OZZnZ3vH4XFy5cvY4NLbOtAbW+Hy23TdIngVXwBVxHmRvbJpvZv6L8YWDJ2DXpqu9bU+QiJFnYWQ14rvT+edo/lGfXMc/i+zqwYp17a5WvCLwWbdTqq7ttm01su24KPFAq/o6kaZIubbCV2l22GXBbbP8eWqrzETN7MV7/G0/c2GrbCvYDrq4oa8W81WuznMSy3Gar5q0hkpbH00WUJQW+EvN2naTK9BWtsu2yONb4cWmh0ZG2unXeaNudKEeJtHrevgJMMk+e2lXft6bIRUiSLIRI6o3nEDrG2vISXYBL9vcDXgR+NQ9MG2BmmwG7A0dK2q6yQvzPeJ6E7cl9ePYAri0Vzw/z1pB5PG898YXbb61NJPGvQB8z2xi4nbZf0K1kfzPbCNg2/ppN1NlKKhe9LZ03SRsAZwDf7sh9XfV9y0VIsrDzAnMmEFw9yqrWif+ZLge8WufeWuWvAstHG7X66m7bkLQ4vgC5ysxuKCqY2Utm9r55PqGLqX9E0i22mVnx78vA8JINL8U2cHH88HKrbQt2x38RvlQUtHDe6rVZPuIot9mqeWvERcATZnZOUWBmr8Yva4A/APWyiXeLbaXv25vAn2n77DrSVrfNm6RNgJ5mNrFkc8vmTdLq+H+HB5jZU6X6XfF9a4pchCQLO+OBdeVRK73wXx0jKuqMoC2J4N7AXbHKHwHsF+eknwDWxR22qrYZ99wdbRBt3thK22K7+RLg72Z2drmh4n8ewV7AQy22bWl58kAkLQ3sWrKh3FbL56103yAqjmJaOG9Vie3vNyRtHZ/vAbTNT6vmrSaSTsUfbMdUlJfnbQ/cP6lltknqKWmleL048EWqf98atdUt8xY0+r5127zF8dnNuKPp7KSjXfh9aw6bS8/W/Mu/+f0P+DweJfIUcFKU/QzYI15/CN9+fxJ/IK1VuvekuO8xwkO8VptRvla08WS0uUQrbcM98Q2YhicxnAJ8Pq5dCTwY10YAq7bYtrVw7/2puCNced6K9ARP4OkFVpgHn+nS+C/E5Sr6auW8PQP8B5iBn8UXkU398QfoU8C5tAlNtnLe2tmG/0o2/EFZfN8Ojvq/iM95Kr44/1SLbVsajzqZFnb8hrYorZptteozjWv/qJyXVs0b8CPgrdLnNgVYpSu/b838pWJqkiRJkiTzhDyOSZIkSZJknpCLkCRJkiRJ5gm5CEmSJEmSZJ6Qi5AkSZIkSeYJuQhJkiRJkmSekIuQJEmSJEnmCbkISZIkSZJknpCLkCRJkiRJ5gn/H2oij8T7VIKkAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "from sklearn.ensemble import ExtraTreesClassifier\n",
    "import matplotlib.pyplot as plt\n",
    "model = ExtraTreesClassifier()\n",
    "model.fit(X,y)\n",
    "print(model.feature_importances_) #use inbuilt class feature_importances of tree based classifiers\n",
    "#plot graph of feature importances for better visualization\n",
    "feat_importances = pd.Series(model.feature_importances_, index=X.columns)\n",
    "feat_importances.nlargest(25).plot(kind='barh')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "metadata": {},
   "outputs": [],
   "source": [
    "X= X.iloc[1:,:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 226,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.631778777046409e-06"
      ]
     },
     "execution_count": 226,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.feature_importances_[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Collision_Type_val_Others                                  0.020410\n",
       "Road_Character_val_Others                                  0.019726\n",
       "Vehicle_Sub_Type_By Walk                                   0.018411\n",
       "Junction_Control_val_Not Applicable                        0.017832\n",
       "Hit_Run_val_No                                             0.016392\n",
       "Road_Character_val_Not Applicable                          0.016348\n",
       "weather_val_Fine                                           0.016341\n",
       "Accident_Spot_val_Other                                    0.016179\n",
       "Junction_Control_val_Not at  Junction                      0.015567\n",
       "Accident_Location_id_val_Open area                         0.015513\n",
       "Junction_Control_val_Uncontrolled                          0.015447\n",
       "Surface_Condition_val_Dry                                  0.014578\n",
       "Road_Type_val_State Highway                                0.014518\n",
       "weather_val_Clear                                          0.014346\n",
       "Road_Character_val_Straight and flat                       0.013786\n",
       "Road_Type_val_NH                                           0.013701\n",
       "Collision_Type_val_Head on                                 0.013216\n",
       "Accident_Spot_val_Narrow road                              0.012964\n",
       "weather_val_Others                                         0.012167\n",
       "Junction_Control_val_Controlled                            0.012158\n",
       "Hit_Run_val_Not Applicable                                 0.012118\n",
       "Surface_Condition_val_Others                               0.011690\n",
       "Road_Condition_val_Not Applicable                          0.011551\n",
       "Collision_Type_val_Hit pedestrian                          0.011399\n",
       "Hit_Run_val_Yes                                            0.011393\n",
       "Road_Type_val_Others                                       0.011106\n",
       "Road_Type_val_Village Road                                 0.011104\n",
       "Surface_Type_val_Bitumen(Tar)                              0.010664\n",
       "Accident_Location_id_val_Near Bus stop                     0.010643\n",
       "Road_Character_val_Curve                                   0.010138\n",
       "                                                             ...   \n",
       "Accident_Location_id_val_Near Petrol Pump                  0.005363\n",
       "Vehicle_Type_3-Wheeler                                     0.005068\n",
       "Accident_Location_id_val_Near office complex               0.005023\n",
       "Seperation_val_No Divider                                  0.004964\n",
       "Road_Type_val_Two way                                      0.004785\n",
       "Surface_Type_val_Concrete                                  0.004658\n",
       "Accident_Location_id_val_Near a religious place            0.004645\n",
       "Vehicle_Vanoeuvre_Going Straight                           0.004452\n",
       "Accident_Location_val_Not Applicable                       0.004406\n",
       "Lane_Type_val_DualLane                                     0.004385\n",
       "Accident_Spot_val_Bridge                                   0.004243\n",
       "Vehicle_Sub_Type_Bike                                      0.004206\n",
       "Vehicle_Load_Half Load                                     0.003987\n",
       "Accident_Location_id_val_Near Hospital                     0.003949\n",
       "Accident_Location_val_Unknown                              0.003770\n",
       "Accident_Location_id_val_Near a factory industrial area    0.003743\n",
       "Lane_Type_val_Others                                       0.003739\n",
       "Road_Markings_val_Unknown                                  0.003699\n",
       "Surface_Type_val_Kutcha                                    0.003689\n",
       "Vehicle_Load_Empty                                         0.003660\n",
       "weather_val_Cloudy                                         0.003652\n",
       "Road_Character_val_Incline                                 0.003635\n",
       "Vehicle_Load_Fully Loaded                                  0.003626\n",
       "Seperation_val_Divider                                     0.003574\n",
       "Lane_Type_val_SingleLane                                   0.003484\n",
       "Collision_Type_val_Side swipe                              0.003378\n",
       "Accident_Location_id_val_Unknown                           0.003367\n",
       "Vehicle_Sub_Type_SCOOTER                                   0.003355\n",
       "Accident_Location_id_val_In bazaar                         0.003298\n",
       "Main_Cause_val_Vehicle Defect                              0.003113\n",
       "Length: 100, dtype: float64"
      ]
     },
     "execution_count": 229,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feat_importances.nlargest(100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
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