DarkMatterDistributions.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from selenium import webdriver\n",
    "from selenium.webdriver.common.by import By"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[['CamB', '10', '3.36', '0.26', '2', '65.0', '5.0', '0.075', '0.003', '1.21', '7.89', '0.47', '66.20', '0.012', '1.21', '0.0', '0.0', '2', 'Bm03'], ['D512-2', '10', '15.20', '4.56', '1', '56.0', '10.0', '0.325', '0.022', '2.37', '9.22', '1.24', '93.94', '0.081', '0.00', '0.0', '0.0', '2', 'Tr09'], ['D564-8', '10', '8.79', '0.28', '2', '63.0', '7.0', '0.033', '0.004', '0.72', '10.11', '0.61', '21.13', '0.029', '0.00', '0.0', '0.0', '2', 'Tr09'], ['D631-7', '10', '7.72', '0.18', '2', '59.0', '3.0', '0.196', '0.009', '1.22', '20.93', '0.70', '115.04', '0.290', '0.00', '57.7', '2.7', '1', 'Tr09;dB01'], ['DDO064', '10', '6.80', '2.04', '1', '60.0', '5.0', '0.157', '0.007', '1.20', '17.41', '0.69', '151.65', '0.211', '3.49', '46.1', '3.9', '1', 'dB02;Sw02'], ['DDO154', '10', '4.04', '0.20', '2', '64.0', '3.0', '0.053', '0.002', '0.65', '19.99', '0.37', '71.26', '0.275', '4.96', '47.0', '1.0', '2', 'Be91;CB89'], ['DDO161', '10', '7.50', '2.25', '1', '70.0', '10.0', '0.548', '0.015', '2.04', '20.74', '1.22', '169.37', '1.378', '10.69', '66.3', '1.9', '1', 'Co00'], ['DDO168', '10', '4.25', '0.21', '2', '63.0', '6.0', '0.191', '0.005', '1.29', '18.23', '1.02', '92.22', '0.413', '4.30', '53.4', '1.9', '2', 'Sa96;Br92'], ['DDO170', '10', '15.40', '4.62', '1', '66.0', '7.0', '0.543', '0.030', '3.03', '9.39', '1.95', '73.93', '0.735', '9.14', '60.0', '1.6', '2', 'Be91;La90'], ['ESO079-G014', '4', '28.70', '7.17', '1', '79.0', '5.0', '51.733', '0.524', '7.23', '157.34', '5.08', '2295.25', '3.140', '17.67', '175.0', '3.5', '1', 'Ge04'], ['ESO116-G012', '7', '13.00', '3.90', '1', '74.0', '3.0', '4.292', '0.071', '2.75', '90.54', '1.51', '1320.78', '1.083', '9.58', '109.1', '3.1', '1', 'Ge04'], ['ESO444-G084', '10', '4.83', '0.48', '2', '32.0', '6.0', '0.071', '0.003', '0.75', '19.81', '0.46', '66.81', '0.135', '2.95', '0.0', '0.0', '2', 'Co00'], ['ESO563-G021', '4', '60.80', '9.10', '1', '83.0', '3.0', '311.177', '2.579', '10.59', '429.37', '5.45', '6558.89', '24.298', '55.71', '314.6', '11.7', '1', 'SG06'], ['F561-1', '9', '66.40', '10.00', '1', '24.0', '10.0', '4.077', '0.327', '5.39', '22.12', '2.79', '93.07', '1.622', '10.69', '50.0', '2.9', '3', 'dB97;dB96'], ['F563-1', '9', '48.90', '9.80', '1', '25.0', '5.0', '1.903', '0.170', '4.61', '14.22', '3.52', '41.77', '3.200', '23.47', '109.9', '12.5', '1', 'KN08;dB96'], ['F563-V1', '10', '54.00', '10.80', '1', '60.0', '10.0', '1.540', '0.165', '5.01', '9.75', '3.79', '40.63', '0.610', '6.83', '0.0', '0.0', '3', 'dB97;dB96'], ['F563-V2', '10', '59.70', '11.90', '1', '29.0', '10.0', '2.986', '0.267', '4.49', '23.60', '2.43', '146.16', '2.169', '11.37', '116.6', '9.4', '1', 'dB01;dB96'], ['F565-V2', '10', '51.80', '10.40', '1', '60.0', '10.0', '0.559', '0.098', '3.57', '6.93', '2.17', '40.26', '0.699', '7.31', '0.0', '0.0', '2', 'dB97;dB96'], ['F567-2', '9', '79.00', '11.80', '1', '20.0', '10.0', '2.134', '0.305', '5.43', '11.50', '3.08', '46.65', '2.449', '14.94', '0.0', '0.0', '3', 'dB97;dB96'], 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'1.34', '52.10', '0.115', '2.90', '33.7', '1.6', '2', 'BC04'], ['NGC0024', '5', '7.30', '0.36', '2', '64.0', '3.0', '3.889', '0.036', '2.01', '151.65', '1.34', '1182.58', '0.676', '7.29', '106.3', '7.9', '1', 'Di08;Ch06'], ['NGC0055', '9', '2.11', '0.11', '2', '77.0', '3.0', '4.628', '0.013', '3.67', '54.55', '6.11', '391.59', '1.565', '10.24', '85.6', '5.0', '2', 'Sa96;Pu91'], ['NGC0100', '6', '13.50', '4.05', '1', '89.0', '1.0', '3.232', '0.063', '2.81', '64.99', '1.66', '1193.52', '1.990', '16.36', '88.1', '6.4', '1', 'dB02;Rh96'], ['NGC0247', '7', '3.70', '0.19', '2', '74.0', '3.0', '7.332', '0.027', '5.87', '33.79', '3.74', '506.79', '1.746', '12.79', '104.9', '8.0', '2', 'Sa96;Ca90'], ['NGC0289', '4', '20.80', '5.20', '1', '46.0', '5.0', '72.065', '0.465', '2.69', '1587.93', '6.74', '69.96', '27.469', '49.51', '163.0', '8.0', '2', 'Wa97'], ['NGC0300', '7', '2.08', '0.10', '2', '42.0', '10.0', '2.922', '0.008', '1.77', '147.51', '1.75', '437.35', '0.936', '9.20', '93.3', '7.0', '2', 'Sa96;CP90'], ['NGC0801', '5', '80.70', '8.07', '1', '80.0', '1.0', '312.570', '3.455', '7.76', '818.14', '8.72', '1558.94', '23.201', '44.99', '220.1', '6.2', '1', 'Sa96;Br92'], ['NGC0891', '3', '9.91', '0.50', '2', '90.0', '1.0', '138.340', '0.255', '3.68', '1617.45', '2.55', '5067.92', '4.462', '18.16', '216.1', '5.7', '1', 'Fr11'], ['NGC1003', '6', '11.40', '3.42', '1', '67.0', '5.0', '6.820', '0.075', '2.76', '140.87', '1.61', '1345.33', '5.880', '33.33', '109.8', '4.2', '1', 'Sa96;Br92'], ['NGC1090', '4', '37.00', '9.25', '1', '64.0', '3.0', '72.045', '0.796', '6.36', '283.68', '3.53', '2055.09', '8.783', '30.49', '164.4', '3.7', '1', 'Ge04'], ['NGC1705', '11', '5.73', '0.29', '2', '80.0', '10.0', '0.533', '0.010', '0.49', '347.40', '0.39', '587.26', '0.139', '2.36', '71.9', '4.3', '3', 'Le14'], ['NGC2366', '10', '3.27', '0.16', '2', '68.0', '5.0', '0.236', '0.005', '1.08', '31.98', '0.65', '113.98', '0.647', '6.94', '50.2', '3.2', '3', 'Le14'], ['NGC2403', '6', '3.16', 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'42.94', '0.20', '143.49', '0.182', '4.20', '50.1', '2.1', '1', 'Ge07;Bm05'], ['NGC3769', '3', '18.00', '2.50', '4', '70.0', '2.0', '18.679', '0.189', '2.18', '626.37', '3.38', '160.26', '5.529', '22.57', '118.6', '8.4', '2', 'VS01;SV98'], ['NGC3877', '5', '18.00', '2.50', '4', '76.0', '1.0', '72.535', '0.401', '4.39', '598.18', '2.53', '3410.59', '1.483', '11.47', '168.4', '5.1', '2', 'VS01;SV98'], ['NGC3893', '5', '18.00', '2.50', '4', '49.0', '2.0', '58.525', '0.377', '2.43', '1573.37', '2.38', '2055.09', '5.799', '20.84', '174.0', '8.9', '1', 'VS01;SV98'], ['NGC3917', '6', '18.00', '2.50', '4', '79.0', '2.0', '21.966', '0.202', '5.56', '112.94', '2.63', '1226.96', '1.888', '14.08', '135.9', '4.1', '1', 'VS01;SV98'], ['NGC3949', '4', '18.00', '2.50', '4', '55.0', '2.0', '38.067', '0.280', '2.39', '1058.84', '3.59', '185.71', '3.371', '13.72', '163.0', '7.1', '2', 'VS01;SV98'], ['NGC3953', '4', '18.00', '2.50', '4', '62.0', '1.0', '141.301', '0.521', '6.17', '587.26', '4.89', 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'5.90', '1', '90.0', '3.0', '2.712', '0.080', '3.92', '28.11', '3.38', '103.00', '4.629', '23.04', '65.2', '2.1', '1', 'Sw09;Sw02'], ['UGC07151', '6', '6.87', '0.34', '2', '90.0', '3.0', '2.284', '0.025', '2.17', '76.71', '1.25', '965.67', '0.616', '6.39', '73.5', '2.8', '1', 'Sw09;Sw02'], ['UGC07232', '10', '2.83', '0.17', '2', '59.0', '5.0', '0.113', '0.002', '0.46', '83.34', '0.29', '227.42', '0.046', '1.54', '0.0', '0.0', '2', 'Sw09;Sw02'], ['UGC07261', '8', '13.10', '3.93', '1', '30.0', '10.0', '1.753', '0.048', '2.66', '39.16', '1.20', '566.02', '1.388', '10.10', '74.7', '3.4', '2', 'Sw09;Sw02'], ['UGC07323', '8', '8.00', '2.40', '1', '47.0', '3.0', '4.109', '0.042', '3.26', '61.49', '2.26', '283.68', '0.722', '7.14', '0.0', '0.0', '1', 'Sw09;Sw02'], ['UGC07399', '8', '8.43', '2.53', '1', '55.0', '3.0', '1.156', '0.024', '1.27', '113.98', '1.64', '135.78', '0.745', '7.85', '103.0', '3.3', '1', 'Sw09;Sw02'], ['UGC07524', '9', '4.74', '0.24', '2', '46.0', '3.0', '2.436', '0.025', '3.61', '29.71', '3.46', '106.86', '1.779', '12.11', '79.5', '3.6', '1', 'Sw09;Sw02'], ['UGC07559', '10', '4.97', '0.25', '2', '61.0', '3.0', '0.109', '0.004', '0.98', '17.90', '0.58', '55.06', '0.169', '3.76', '0.0', '0.0', '2', 'Sw09;Sw02'], ['UGC07577', '10', '2.59', '0.13', '2', '63.0', '3.0', '0.045', '0.002', '0.77', '11.94', '0.90', '54.55', '0.044', '2.07', '0.0', '0.0', '2', 'Sw09;Sw02'], ['UGC07603', '7', '4.70', '1.41', '1', '78.0', '3.0', '0.376', '0.008', '0.85', '81.81', '0.53', '520.99', '0.258', '4.37', '61.6', '2.8', '1', 'Sw09;Sw02'], ['UGC07608', '10', '8.21', '2.46', '1', '25.0', '10.0', '0.264', '0.012', '1.60', '16.48', '1.50', '46.65', '0.535', '6.73', '0.0', '0.0', '1', 'Sw09;Sw02'], ['UGC07690', '10', '8.11', '2.43', '1', '41.0', '5.0', '0.858', '0.018', '0.86', '184.01', '0.57', '395.21', '0.390', '5.50', '57.4', '3.2', '2', 'Sw09;Sw02'], ['UGC07866', '10', '4.57', '0.23', '2', '44.0', '5.0', '0.124', '0.004', '0.95', '21.92', '0.61', '97.46', '0.118', '3.30', '0.0', '0.0', '2', 'Sw09;Sw02'], ['UGC08286', '6', '6.50', '0.21', '2', '90.0', '3.0', '1.255', '0.018', '2.25', '39.52', '1.05', '1488.78', '0.642', '8.07', '82.4', '2.3', '1', 'Sw09;Sw02'], ['UGC08490', '9', '4.65', '0.53', '2', '50.0', '3.0', '1.017', '0.012', '1.14', '124.98', '0.67', '576.54', '0.720', '7.80', '78.6', '3.8', '1', 'Sw09;Sw02'], ['UGC08550', '7', '6.70', '2.00', '1', '90.0', '3.0', '0.289', '0.009', '1.01', '45.38', '0.45', '1284.78', '0.288', '5.59', '56.9', '1.9', '1', 'Sw09;Sw02'], ['UGC08699', '2', '39.30', '9.82', '1', '73.0', '9.0', '50.302', '0.695', '1.91', '2191.95', '3.09', '1370.35', '3.738', '19.05', '182.4', '6.9', '2', 'No07;No05'], ['UGC08837', '10', '7.21', '0.36', '2', '80.0', '5.0', '0.501', '0.015', '2.25', '15.73', '1.72', '77.42', '0.320', '4.75', '0.0', '0.0', '2', 'Sw09;Sw02'], ['UGC09037', '6', '83.60', '8.40', '1', '65.0', '5.0', '68.614', '1.769', '5.69', '334.83', '4.28', '841.07', '19.078', '39.72', '152.3', '9.6', '2', 'Ha14'], ['UGC09133', '2', '57.10', '11.40', '1', '53.0', '6.0', '282.926', '2.345', '5.92', '1284.78', '6.97', '864.63', '33.428', '60.35', '226.8', '4.2', '1', 'No07;No05'], ['UGC09992', '10', '10.70', '3.21', '1', '30.0', '10.0', '0.336', '0.017', '1.62', '20.18', '1.04', '73.25', '0.318', '5.45', '33.6', '3.3', '2', 'Sw09;Sw02'], ['UGC10310', '9', '15.20', '4.60', '1', '34.0', '6.0', '1.741', '0.053', '3.12', '28.37', '1.80', '158.79', '1.196', '9.58', '71.4', '3.9', '1', 'Sw09;Sw02'], ['UGC11455', '6', '78.60', '11.80', '1', '90.0', '1.0', '374.322', '3.792', '10.06', '571.26', '5.93', '9568.20', '13.335', '43.44', '269.4', '7.4', '1', 'SG06'], ['UGC11557', '8', '24.20', '6.05', '1', '30.0', '10.0', '12.101', '0.212', '4.18', '106.86', '2.75', '337.93', '2.605', '16.66', '0.0', '0.0', '2', 'Sw02;dB01'], ['UGC11820', '9', '18.10', '5.43', '1', '45.0', '10.0', '0.970', '0.047', '2.74', '20.18', '2.08', '34.11', '1.977', '12.99', '0.0', '0.0', '1', 'KN08;vZ97'], ['UGC11914', '2', '16.90', '5.10', '1', '31.0', '5.0', '150.028', '0.553', '3.12', '2425.66', '2.44', '3168.33', '0.888', '9.26', '288.1', '10.5', '1', 'No07;No05'], ['UGC12506', '6', '100.60', '10.10', '1', '86.0', '4.0', '139.571', '3.214', '12.36', '144.82', '7.38', '5608.28', '35.556', '59.01', '234.0', '16.8', '2', 'Ha14'], ['UGC12632', '9', '9.77', '2.93', '1', '46.0', '3.0', '1.301', '0.030', '3.94', '13.09', '2.42', '66.81', '1.744', '12.60', '71.7', '2.8', '1', 'Sw09;Sw02'], ['UGC12732', '9', '13.20', '4.00', '1', '39.0', '6.0', '1.667', '0.048', '3.12', '26.84', '1.98', '120.46', '3.660', '17.41', '0.0', '0.0', '1', 'Sw09;Sw02'], ['UGCA281', '11', '5.68', '0.28', '2', '67.0', '3.0', '0.194', '0.007', '1.57', '12.50', '1.72', '12.05', '0.062', '1.83', '0.0', '0.0', '3', 'Le14'], ['UGCA442', '9', '4.35', '0.22', '2', '64.0', '7.0', '0.140', '0.005', '1.71', '7.60', '1.18', '116.10', '0.263', '4.37', '56.4', '2.1', '1', 'Co00'], ['UGCA444', '10', '0.98', '0.05', '2', '78.0', '4.0', '0.012', '0.000', '0.41', '11.94', '0.83', '22.74', '0.067', '2.08', '37.0', '4.8', '2', 'Ke07']]\n"
     ]
    }
   ],
   "source": [
    "# Read in the data\n",
    "data = []\n",
    "fin = open(\"Data/Galaxy Data/SPARC_Lelli2016c.mrt\")\n",
    "lines = fin.read().split(\"\\n\")[98:-1]\n",
    "for line in lines:\n",
    "    data.append(line.strip().replace(\",\", \";\").split())\n",
    "print(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "fout = open(\"Data/Galaxy Data/SPARC_Lelli2016c.csv\", \"w\")\n",
    "headers = \",\".join(open(\"Data/Galaxy Data/SPARC_Lelli2016c-headers.txt\").read().split(\"\\n\"))\n",
    "fout.write(headers + \"\\n\")\n",
    "for line in data:\n",
    "    fout.write(\",\".join(line))\n",
    "    if line != data[-1]:\n",
    "        fout.write(\"\\n\")\n",
    "fout.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>Galaxy</th>\n",
       "      <th>T</th>\n",
       "      <th>D</th>\n",
       "      <th>e_D</th>\n",
       "      <th>f_D</th>\n",
       "      <th>Inc</th>\n",
       "      <th>e_Inc</th>\n",
       "      <th>L[3.6]</th>\n",
       "      <th>e_L[3.6]</th>\n",
       "      <th>Reff</th>\n",
       "      <th>SBeff</th>\n",
       "      <th>Rdisk</th>\n",
       "      <th>SBdisk</th>\n",
       "      <th>MHI</th>\n",
       "      <th>RHI</th>\n",
       "      <th>Vflat</th>\n",
       "      <th>e_Vflat</th>\n",
       "      <th>Q</th>\n",
       "      <th>Ref.</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CamB</td>\n",
       "      <td>10</td>\n",
       "      <td>3.36</td>\n",
       "      <td>0.26</td>\n",
       "      <td>2</td>\n",
       "      <td>65.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.075</td>\n",
       "      <td>0.003</td>\n",
       "      <td>1.21</td>\n",
       "      <td>7.89</td>\n",
       "      <td>0.47</td>\n",
       "      <td>66.20</td>\n",
       "      <td>0.012</td>\n",
       "      <td>1.21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>Bm03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>D512-2</td>\n",
       "      <td>10</td>\n",
       "      <td>15.20</td>\n",
       "      <td>4.56</td>\n",
       "      <td>1</td>\n",
       "      <td>56.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.325</td>\n",
       "      <td>0.022</td>\n",
       "      <td>2.37</td>\n",
       "      <td>9.22</td>\n",
       "      <td>1.24</td>\n",
       "      <td>93.94</td>\n",
       "      <td>0.081</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>Tr09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>D564-8</td>\n",
       "      <td>10</td>\n",
       "      <td>8.79</td>\n",
       "      <td>0.28</td>\n",
       "      <td>2</td>\n",
       "      <td>63.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.033</td>\n",
       "      <td>0.004</td>\n",
       "      <td>0.72</td>\n",
       "      <td>10.11</td>\n",
       "      <td>0.61</td>\n",
       "      <td>21.13</td>\n",
       "      <td>0.029</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>Tr09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>D631-7</td>\n",
       "      <td>10</td>\n",
       "      <td>7.72</td>\n",
       "      <td>0.18</td>\n",
       "      <td>2</td>\n",
       "      <td>59.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.196</td>\n",
       "      <td>0.009</td>\n",
       "      <td>1.22</td>\n",
       "      <td>20.93</td>\n",
       "      <td>0.70</td>\n",
       "      <td>115.04</td>\n",
       "      <td>0.290</td>\n",
       "      <td>0.00</td>\n",
       "      <td>57.7</td>\n",
       "      <td>2.7</td>\n",
       "      <td>1</td>\n",
       "      <td>Tr09;dB01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>DDO064</td>\n",
       "      <td>10</td>\n",
       "      <td>6.80</td>\n",
       "      <td>2.04</td>\n",
       "      <td>1</td>\n",
       "      <td>60.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.157</td>\n",
       "      <td>0.007</td>\n",
       "      <td>1.20</td>\n",
       "      <td>17.41</td>\n",
       "      <td>0.69</td>\n",
       "      <td>151.65</td>\n",
       "      <td>0.211</td>\n",
       "      <td>3.49</td>\n",
       "      <td>46.1</td>\n",
       "      <td>3.9</td>\n",
       "      <td>1</td>\n",
       "      <td>dB02;Sw02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>UGC12632</td>\n",
       "      <td>9</td>\n",
       "      <td>9.77</td>\n",
       "      <td>2.93</td>\n",
       "      <td>1</td>\n",
       "      <td>46.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.301</td>\n",
       "      <td>0.030</td>\n",
       "      <td>3.94</td>\n",
       "      <td>13.09</td>\n",
       "      <td>2.42</td>\n",
       "      <td>66.81</td>\n",
       "      <td>1.744</td>\n",
       "      <td>12.60</td>\n",
       "      <td>71.7</td>\n",
       "      <td>2.8</td>\n",
       "      <td>1</td>\n",
       "      <td>Sw09;Sw02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>UGC12732</td>\n",
       "      <td>9</td>\n",
       "      <td>13.20</td>\n",
       "      <td>4.00</td>\n",
       "      <td>1</td>\n",
       "      <td>39.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.667</td>\n",
       "      <td>0.048</td>\n",
       "      <td>3.12</td>\n",
       "      <td>26.84</td>\n",
       "      <td>1.98</td>\n",
       "      <td>120.46</td>\n",
       "      <td>3.660</td>\n",
       "      <td>17.41</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>Sw09;Sw02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>UGCA281</td>\n",
       "      <td>11</td>\n",
       "      <td>5.68</td>\n",
       "      <td>0.28</td>\n",
       "      <td>2</td>\n",
       "      <td>67.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.194</td>\n",
       "      <td>0.007</td>\n",
       "      <td>1.57</td>\n",
       "      <td>12.50</td>\n",
       "      <td>1.72</td>\n",
       "      <td>12.05</td>\n",
       "      <td>0.062</td>\n",
       "      <td>1.83</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>Le14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>UGCA442</td>\n",
       "      <td>9</td>\n",
       "      <td>4.35</td>\n",
       "      <td>0.22</td>\n",
       "      <td>2</td>\n",
       "      <td>64.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.140</td>\n",
       "      <td>0.005</td>\n",
       "      <td>1.71</td>\n",
       "      <td>7.60</td>\n",
       "      <td>1.18</td>\n",
       "      <td>116.10</td>\n",
       "      <td>0.263</td>\n",
       "      <td>4.37</td>\n",
       "      <td>56.4</td>\n",
       "      <td>2.1</td>\n",
       "      <td>1</td>\n",
       "      <td>Co00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>UGCA444</td>\n",
       "      <td>10</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.05</td>\n",
       "      <td>2</td>\n",
       "      <td>78.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.012</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.41</td>\n",
       "      <td>11.94</td>\n",
       "      <td>0.83</td>\n",
       "      <td>22.74</td>\n",
       "      <td>0.067</td>\n",
       "      <td>2.08</td>\n",
       "      <td>37.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>2</td>\n",
       "      <td>Ke07</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>175 rows × 19 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Galaxy   T      D   e_D  f_D   Inc  e_Inc  L[3.6]  e_L[3.6]  Reff  \\\n",
       "0        CamB  10   3.36  0.26    2  65.0    5.0   0.075     0.003  1.21   \n",
       "1      D512-2  10  15.20  4.56    1  56.0   10.0   0.325     0.022  2.37   \n",
       "2      D564-8  10   8.79  0.28    2  63.0    7.0   0.033     0.004  0.72   \n",
       "3      D631-7  10   7.72  0.18    2  59.0    3.0   0.196     0.009  1.22   \n",
       "4      DDO064  10   6.80  2.04    1  60.0    5.0   0.157     0.007  1.20   \n",
       "..        ...  ..    ...   ...  ...   ...    ...     ...       ...   ...   \n",
       "170  UGC12632   9   9.77  2.93    1  46.0    3.0   1.301     0.030  3.94   \n",
       "171  UGC12732   9  13.20  4.00    1  39.0    6.0   1.667     0.048  3.12   \n",
       "172   UGCA281  11   5.68  0.28    2  67.0    3.0   0.194     0.007  1.57   \n",
       "173   UGCA442   9   4.35  0.22    2  64.0    7.0   0.140     0.005  1.71   \n",
       "174   UGCA444  10   0.98  0.05    2  78.0    4.0   0.012     0.000  0.41   \n",
       "\n",
       "     SBeff  Rdisk  SBdisk    MHI    RHI  Vflat  e_Vflat  Q       Ref.  \n",
       "0     7.89   0.47   66.20  0.012   1.21    0.0      0.0  2       Bm03  \n",
       "1     9.22   1.24   93.94  0.081   0.00    0.0      0.0  2       Tr09  \n",
       "2    10.11   0.61   21.13  0.029   0.00    0.0      0.0  2       Tr09  \n",
       "3    20.93   0.70  115.04  0.290   0.00   57.7      2.7  1  Tr09;dB01  \n",
       "4    17.41   0.69  151.65  0.211   3.49   46.1      3.9  1  dB02;Sw02  \n",
       "..     ...    ...     ...    ...    ...    ...      ... ..        ...  \n",
       "170  13.09   2.42   66.81  1.744  12.60   71.7      2.8  1  Sw09;Sw02  \n",
       "171  26.84   1.98  120.46  3.660  17.41    0.0      0.0  1  Sw09;Sw02  \n",
       "172  12.50   1.72   12.05  0.062   1.83    0.0      0.0  3       Le14  \n",
       "173   7.60   1.18  116.10  0.263   4.37   56.4      2.1  1       Co00  \n",
       "174  11.94   0.83   22.74  0.067   2.08   37.0      4.8  2       Ke07  \n",
       "\n",
       "[175 rows x 19 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"Data/Galaxy Data/SPARC_Lelli2016c.csv\")\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "489.955"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max(df[\"L[3.6]\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      0.074995\n",
       "1      0.325000\n",
       "2      0.032977\n",
       "3      0.196000\n",
       "4      0.157000\n",
       "         ...   \n",
       "170    1.301000\n",
       "171    1.667000\n",
       "172    0.194000\n",
       "173    0.140000\n",
       "174    0.011911\n",
       "Name: LumCalc, Length: 175, dtype: float64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['LumCalc'] = df['Reff'] ** 2 * 2 * np.pi * df['SBeff'] / (10 ** 3)\n",
    "df['LumCalc'] = df[\"L[3.6]\"] / ((1 + np.e ** ((-1 * df['Reff'] * df['SBeff']))))\n",
    "df[\"LumCalc\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Formula: $L=\\frac{\\pi R_{eff}^2 S}{500}$<br>\n",
    "Where $L$ is luminosity in $L_\\odot$, $R_{eff}$ is the effective radius in kpc, and $S$ is the effective surface brightness in $L_\\odot/pc^2$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['LumPercentError'] = np.abs(df['L[3.6]'] - df['LumCalc']) / df['L[3.6]']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.38929826293771e-08 0.0001373111494456027 6.177779124625207e-10\n",
      "5.0235865046479024e-05\n"
     ]
    }
   ],
   "source": [
    "q1_avg = np.mean(df[df['Q'] == 1]['LumPercentError'])\n",
    "q2_avg = np.mean(df[df['Q'] == 2]['LumPercentError'])\n",
    "q3_avg = np.mean(df[df['Q'] == 3]['LumPercentError'])\n",
    "print(q1_avg, q2_avg, q3_avg)\n",
    "print(np.mean(df['LumPercentError']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>Galaxy</th>\n",
       "      <th>T</th>\n",
       "      <th>D</th>\n",
       "      <th>e_D</th>\n",
       "      <th>f_D</th>\n",
       "      <th>Inc</th>\n",
       "      <th>e_Inc</th>\n",
       "      <th>L[3.6]</th>\n",
       "      <th>e_L[3.6]</th>\n",
       "      <th>Reff</th>\n",
       "      <th>...</th>\n",
       "      <th>Rdisk</th>\n",
       "      <th>SBdisk</th>\n",
       "      <th>MHI</th>\n",
       "      <th>RHI</th>\n",
       "      <th>Vflat</th>\n",
       "      <th>e_Vflat</th>\n",
       "      <th>Q</th>\n",
       "      <th>Ref.</th>\n",
       "      <th>LumCalc</th>\n",
       "      <th>LumPercentError</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CamB</td>\n",
       "      <td>10</td>\n",
       "      <td>3.36</td>\n",
       "      <td>0.26</td>\n",
       "      <td>2</td>\n",
       "      <td>65.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.075</td>\n",
       "      <td>0.003</td>\n",
       "      <td>1.21</td>\n",
       "      <td>...</td>\n",
       "      <td>0.47</td>\n",
       "      <td>66.20</td>\n",
       "      <td>0.012</td>\n",
       "      <td>1.21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>Bm03</td>\n",
       "      <td>0.074995</td>\n",
       "      <td>7.141723e-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>D512-2</td>\n",
       "      <td>10</td>\n",
       "      <td>15.20</td>\n",
       "      <td>4.56</td>\n",
       "      <td>1</td>\n",
       "      <td>56.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.325</td>\n",
       "      <td>0.022</td>\n",
       "      <td>2.37</td>\n",
       "      <td>...</td>\n",
       "      <td>1.24</td>\n",
       "      <td>93.94</td>\n",
       "      <td>0.081</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>Tr09</td>\n",
       "      <td>0.325000</td>\n",
       "      <td>3.236365e-10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>D564-8</td>\n",
       "      <td>10</td>\n",
       "      <td>8.79</td>\n",
       "      <td>0.28</td>\n",
       "      <td>2</td>\n",
       "      <td>63.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.033</td>\n",
       "      <td>0.004</td>\n",
       "      <td>0.72</td>\n",
       "      <td>...</td>\n",
       "      <td>0.61</td>\n",
       "      <td>21.13</td>\n",
       "      <td>0.029</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>Tr09</td>\n",
       "      <td>0.032977</td>\n",
       "      <td>6.892617e-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>D631-7</td>\n",
       "      <td>10</td>\n",
       "      <td>7.72</td>\n",
       "      <td>0.18</td>\n",
       "      <td>2</td>\n",
       "      <td>59.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.196</td>\n",
       "      <td>0.009</td>\n",
       "      <td>1.22</td>\n",
       "      <td>...</td>\n",
       "      <td>0.70</td>\n",
       "      <td>115.04</td>\n",
       "      <td>0.290</td>\n",
       "      <td>0.00</td>\n",
       "      <td>57.7</td>\n",
       "      <td>2.7</td>\n",
       "      <td>1</td>\n",
       "      <td>Tr09;dB01</td>\n",
       "      <td>0.196000</td>\n",
       "      <td>8.137057e-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>DDO064</td>\n",
       "      <td>10</td>\n",
       "      <td>6.80</td>\n",
       "      <td>2.04</td>\n",
       "      <td>1</td>\n",
       "      <td>60.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.157</td>\n",
       "      <td>0.007</td>\n",
       "      <td>1.20</td>\n",
       "      <td>...</td>\n",
       "      <td>0.69</td>\n",
       "      <td>151.65</td>\n",
       "      <td>0.211</td>\n",
       "      <td>3.49</td>\n",
       "      <td>46.1</td>\n",
       "      <td>3.9</td>\n",
       "      <td>1</td>\n",
       "      <td>dB02;Sw02</td>\n",
       "      <td>0.157000</td>\n",
       "      <td>8.447333e-10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>UGC12632</td>\n",
       "      <td>9</td>\n",
       "      <td>9.77</td>\n",
       "      <td>2.93</td>\n",
       "      <td>1</td>\n",
       "      <td>46.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.301</td>\n",
       "      <td>0.030</td>\n",
       "      <td>3.94</td>\n",
       "      <td>...</td>\n",
       "      <td>2.42</td>\n",
       "      <td>66.81</td>\n",
       "      <td>1.744</td>\n",
       "      <td>12.60</td>\n",
       "      <td>71.7</td>\n",
       "      <td>2.8</td>\n",
       "      <td>1</td>\n",
       "      <td>Sw09;Sw02</td>\n",
       "      <td>1.301000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>UGC12732</td>\n",
       "      <td>9</td>\n",
       "      <td>13.20</td>\n",
       "      <td>4.00</td>\n",
       "      <td>1</td>\n",
       "      <td>39.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.667</td>\n",
       "      <td>0.048</td>\n",
       "      <td>3.12</td>\n",
       "      <td>...</td>\n",
       "      <td>1.98</td>\n",
       "      <td>120.46</td>\n",
       "      <td>3.660</td>\n",
       "      <td>17.41</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>Sw09;Sw02</td>\n",
       "      <td>1.667000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>UGCA281</td>\n",
       "      <td>11</td>\n",
       "      <td>5.68</td>\n",
       "      <td>0.28</td>\n",
       "      <td>2</td>\n",
       "      <td>67.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.194</td>\n",
       "      <td>0.007</td>\n",
       "      <td>1.57</td>\n",
       "      <td>...</td>\n",
       "      <td>1.72</td>\n",
       "      <td>12.05</td>\n",
       "      <td>0.062</td>\n",
       "      <td>1.83</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>Le14</td>\n",
       "      <td>0.194000</td>\n",
       "      <td>2.998961e-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>UGCA442</td>\n",
       "      <td>9</td>\n",
       "      <td>4.35</td>\n",
       "      <td>0.22</td>\n",
       "      <td>2</td>\n",
       "      <td>64.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.140</td>\n",
       "      <td>0.005</td>\n",
       "      <td>1.71</td>\n",
       "      <td>...</td>\n",
       "      <td>1.18</td>\n",
       "      <td>116.10</td>\n",
       "      <td>0.263</td>\n",
       "      <td>4.37</td>\n",
       "      <td>56.4</td>\n",
       "      <td>2.1</td>\n",
       "      <td>1</td>\n",
       "      <td>Co00</td>\n",
       "      <td>0.140000</td>\n",
       "      <td>2.269384e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>UGCA444</td>\n",
       "      <td>10</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.05</td>\n",
       "      <td>2</td>\n",
       "      <td>78.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.012</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.41</td>\n",
       "      <td>...</td>\n",
       "      <td>0.83</td>\n",
       "      <td>22.74</td>\n",
       "      <td>0.067</td>\n",
       "      <td>2.08</td>\n",
       "      <td>37.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>2</td>\n",
       "      <td>Ke07</td>\n",
       "      <td>0.011911</td>\n",
       "      <td>7.425368e-03</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>175 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Galaxy   T      D   e_D  f_D   Inc  e_Inc  L[3.6]  e_L[3.6]  Reff  ...  \\\n",
       "0        CamB  10   3.36  0.26    2  65.0    5.0   0.075     0.003  1.21  ...   \n",
       "1      D512-2  10  15.20  4.56    1  56.0   10.0   0.325     0.022  2.37  ...   \n",
       "2      D564-8  10   8.79  0.28    2  63.0    7.0   0.033     0.004  0.72  ...   \n",
       "3      D631-7  10   7.72  0.18    2  59.0    3.0   0.196     0.009  1.22  ...   \n",
       "4      DDO064  10   6.80  2.04    1  60.0    5.0   0.157     0.007  1.20  ...   \n",
       "..        ...  ..    ...   ...  ...   ...    ...     ...       ...   ...  ...   \n",
       "170  UGC12632   9   9.77  2.93    1  46.0    3.0   1.301     0.030  3.94  ...   \n",
       "171  UGC12732   9  13.20  4.00    1  39.0    6.0   1.667     0.048  3.12  ...   \n",
       "172   UGCA281  11   5.68  0.28    2  67.0    3.0   0.194     0.007  1.57  ...   \n",
       "173   UGCA442   9   4.35  0.22    2  64.0    7.0   0.140     0.005  1.71  ...   \n",
       "174   UGCA444  10   0.98  0.05    2  78.0    4.0   0.012     0.000  0.41  ...   \n",
       "\n",
       "     Rdisk  SBdisk    MHI    RHI  Vflat  e_Vflat  Q       Ref.   LumCalc  \\\n",
       "0     0.47   66.20  0.012   1.21    0.0      0.0  2       Bm03  0.074995   \n",
       "1     1.24   93.94  0.081   0.00    0.0      0.0  2       Tr09  0.325000   \n",
       "2     0.61   21.13  0.029   0.00    0.0      0.0  2       Tr09  0.032977   \n",
       "3     0.70  115.04  0.290   0.00   57.7      2.7  1  Tr09;dB01  0.196000   \n",
       "4     0.69  151.65  0.211   3.49   46.1      3.9  1  dB02;Sw02  0.157000   \n",
       "..     ...     ...    ...    ...    ...      ... ..        ...       ...   \n",
       "170   2.42   66.81  1.744  12.60   71.7      2.8  1  Sw09;Sw02  1.301000   \n",
       "171   1.98  120.46  3.660  17.41    0.0      0.0  1  Sw09;Sw02  1.667000   \n",
       "172   1.72   12.05  0.062   1.83    0.0      0.0  3       Le14  0.194000   \n",
       "173   1.18  116.10  0.263   4.37   56.4      2.1  1       Co00  0.140000   \n",
       "174   0.83   22.74  0.067   2.08   37.0      4.8  2       Ke07  0.011911   \n",
       "\n",
       "     LumPercentError  \n",
       "0       7.141723e-05  \n",
       "1       3.236365e-10  \n",
       "2       6.892617e-04  \n",
       "3       8.137057e-12  \n",
       "4       8.447333e-10  \n",
       "..               ...  \n",
       "170     0.000000e+00  \n",
       "171     0.000000e+00  \n",
       "172     2.998961e-09  \n",
       "173     2.269384e-06  \n",
       "174     7.425368e-03  \n",
       "\n",
       "[175 rows x 21 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[['NGC2685', '16.10', '4.80', '1', '65.0', '4.0', '30.037', '0.277', '1.92', '1284.78', '3.19', '413.84', '-8.56', '0.16', '-10.57', '0.14', '-8.44', '0.11', '-11.25', '0.11'], ['NGC2824', '39.60', '9.90', '1', '65.0', '8.0', '39.572', '0.729', '1.09', '5209.91', '5.00', '84.11', '-8.17', '0.14', '-9.96', '0.12', '-8.43', '0.11', '-10.13', '0.11'], ['NGC2859', '26.20', '6.50', '1', '35.0', '5.0', '89.085', '0.820', '1.59', '5608.28', '2.51', '603.71', '-8.44', '0.14', '-9.99', '0.20', '-8.44', '0.11', '-10.31', '0.11'], ['NGC2974', '22.10', '2.80', '2', '60.0', '2.0', '116.946', '1.077', '3.02', '2017.58', '3.44', '1530.49', '-8.36', '0.10', '-9.59', '0.06', '-8.52', '0.11', '-10.01', '0.11'], ['NGC3522', '25.20', '3.20', '2', '41.0', '2.0', '13.183', '0.243', '1.42', '1039.51', '2.47', '254.00', '-8.43', '0.10', '-10.34', '0.08', '-8.73', '0.11', '-10.85', '0.11'], ['NGC3626', '22.90', '2.50', '2', '54.0', '1.0', '74.623', '0.687', '2.43', '2017.58', '2.52', '1891.60', '-8.26', '0.10', '-10.16', '0.06', '-8.09', '0.11', '-10.29', '0.11'], ['NGC3838', '23.10', '5.80', '1', '66.0', '8.0', '22.492', '0.207', '1.03', '3410.59', '1.99', '417.67', '-8.36', '0.14', '-10.31', '0.13', '-8.44', '0.11', '-11.04', '0.11'], ['NGC3941', '12.40', '1.60', '2', '57.0', '1.0', '43.656', '0.402', '1.42', '3474.00', '1.30', '4373.51', '-8.28', '0.10', '-10.22', '0.07', '-8.12', '0.11', '-10.43', '0.11'], ['NGC3945', '22.80', '5.70', '1', '57.0', '5.0', '126.319', '1.163', '2.50', '3197.64', '7.22', '209.33', '-8.42', '0.14', '-9.90', '0.12', '-8.52', '0.11', '-10.14', '0.11'], ['NGC3998', '14.20', '1.80', '2', '66.0', '2.0', '56.205', '0.518', '1.01', '8807.04', '1.46', '2997.99', '-7.91', '0.10', '-9.84', '0.09', '-8.17', '0.11', '-10.44', '0.11'], ['NGC4203', '15.30', '2.00', '2', '30.0', '3.0', '61.685', '0.568', '1.85', '2093.29', '1.85', '2132.21', '-8.46', '0.10', '-10.06', '0.16', '-8.29', '0.11', '-10.45', '0.11'], ['NGC4262', '16.60', '1.80', '2', '67.0', '8.0', '28.988', '0.267', '0.69', '9480.47', '2.90', '43.74', '-7.85', '0.10', '-9.88', '0.06', '-8.17', '0.11', '-10.45', '0.11'], ['NGC4278', '15.40', '2.00', '2', '45.0', '5.0', '82.612', '0.000', '1.63', '4884.61', '2.57', '992.73', '-8.30', '0.10', '-9.72', '0.10', '-8.48', '0.11', '-10.10', '0.11'], ['NGC5582', '28.10', '3.60', '2', '50.0', '2.0', '55.235', '0.509', '3.07', '930.74', '3.86', '686.80', '-8.49', '0.10', '-10.12', '0.07', '-8.68', '0.11', '-11.09', '0.11'], ['NGC6798', '37.30', '9.30', '1', '52.0', '2.0', '69.090', '0.636', '3.30', '992.73', '3.29', '974.61', '-8.75', '0.14', '-10.37', '0.11', '-9.29', '0.11', '-10.95', '0.11'], ['UGC6176', '39.30', '9.80', '1', '47.0', '6.0', '28.972', '0.534', '1.18', '3317.65', '1.80', '1049.13', '-8.08', '0.14', '-10.23', '0.14', '-8.61', '0.11', '-10.57', '0.11']]\n"
     ]
    }
   ],
   "source": [
    "# Read in the data\n",
    "data = []\n",
    "fin = open(\"Data/Galaxy Data/ETG_Lelli2017.mrt\")\n",
    "lines = fin.read().split(\"\\n\")[2:-1]\n",
    "for line in lines:\n",
    "    data.append(line.strip().replace(\",\", \";\").split())\n",
    "print(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "fout = open(\"Data/Galaxy Data/ETG_Lelli2017.csv\", \"w\")\n",
    "headers = \",\".join(open(\"Data/Galaxy Data/ETG_Lelli2017-headers.txt\").read().split(\"\\n\"))\n",
    "fout.write(headers + \"\\n\")\n",
    "for line in data:\n",
    "    fout.write(\",\".join(line))\n",
    "    if line != data[-1]:\n",
    "        fout.write(\"\\n\")\n",
    "fout.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>Galaxy</th>\n",
       "      <th>Dist</th>\n",
       "      <th>errD</th>\n",
       "      <th>M</th>\n",
       "      <th>Inc</th>\n",
       "      <th>erI</th>\n",
       "      <th>L[3.6]</th>\n",
       "      <th>errL</th>\n",
       "      <th>Reff</th>\n",
       "      <th>SBeff</th>\n",
       "      <th>Rexp</th>\n",
       "      <th>SBexp</th>\n",
       "      <th>Aobs1</th>\n",
       "      <th>eAobs1</th>\n",
       "      <th>Aobs2</th>\n",
       "      <th>eAobs2</th>\n",
       "      <th>Abar1</th>\n",
       "      <th>eAbar1</th>\n",
       "      <th>Abar2</th>\n",
       "      <th>eAbar2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NGC2685</td>\n",
       "      <td>16.1</td>\n",
       "      <td>4.8</td>\n",
       "      <td>1</td>\n",
       "      <td>65.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>30.037</td>\n",
       "      <td>0.277</td>\n",
       "      <td>1.92</td>\n",
       "      <td>1284.78</td>\n",
       "      <td>3.19</td>\n",
       "      <td>413.84</td>\n",
       "      <td>-8.56</td>\n",
       "      <td>0.16</td>\n",
       "      <td>-10.57</td>\n",
       "      <td>0.14</td>\n",
       "      <td>-8.44</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-11.25</td>\n",
       "      <td>0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NGC2824</td>\n",
       "      <td>39.6</td>\n",
       "      <td>9.9</td>\n",
       "      <td>1</td>\n",
       "      <td>65.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>39.572</td>\n",
       "      <td>0.729</td>\n",
       "      <td>1.09</td>\n",
       "      <td>5209.91</td>\n",
       "      <td>5.00</td>\n",
       "      <td>84.11</td>\n",
       "      <td>-8.17</td>\n",
       "      <td>0.14</td>\n",
       "      <td>-9.96</td>\n",
       "      <td>0.12</td>\n",
       "      <td>-8.43</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.13</td>\n",
       "      <td>0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NGC2859</td>\n",
       "      <td>26.2</td>\n",
       "      <td>6.5</td>\n",
       "      <td>1</td>\n",
       "      <td>35.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>89.085</td>\n",
       "      <td>0.820</td>\n",
       "      <td>1.59</td>\n",
       "      <td>5608.28</td>\n",
       "      <td>2.51</td>\n",
       "      <td>603.71</td>\n",
       "      <td>-8.44</td>\n",
       "      <td>0.14</td>\n",
       "      <td>-9.99</td>\n",
       "      <td>0.20</td>\n",
       "      <td>-8.44</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.31</td>\n",
       "      <td>0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NGC2974</td>\n",
       "      <td>22.1</td>\n",
       "      <td>2.8</td>\n",
       "      <td>2</td>\n",
       "      <td>60.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>116.946</td>\n",
       "      <td>1.077</td>\n",
       "      <td>3.02</td>\n",
       "      <td>2017.58</td>\n",
       "      <td>3.44</td>\n",
       "      <td>1530.49</td>\n",
       "      <td>-8.36</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-9.59</td>\n",
       "      <td>0.06</td>\n",
       "      <td>-8.52</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.01</td>\n",
       "      <td>0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NGC3522</td>\n",
       "      <td>25.2</td>\n",
       "      <td>3.2</td>\n",
       "      <td>2</td>\n",
       "      <td>41.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>13.183</td>\n",
       "      <td>0.243</td>\n",
       "      <td>1.42</td>\n",
       "      <td>1039.51</td>\n",
       "      <td>2.47</td>\n",
       "      <td>254.00</td>\n",
       "      <td>-8.43</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-10.34</td>\n",
       "      <td>0.08</td>\n",
       "      <td>-8.73</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.85</td>\n",
       "      <td>0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>NGC3626</td>\n",
       "      <td>22.9</td>\n",
       "      <td>2.5</td>\n",
       "      <td>2</td>\n",
       "      <td>54.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>74.623</td>\n",
       "      <td>0.687</td>\n",
       "      <td>2.43</td>\n",
       "      <td>2017.58</td>\n",
       "      <td>2.52</td>\n",
       "      <td>1891.60</td>\n",
       "      <td>-8.26</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-10.16</td>\n",
       "      <td>0.06</td>\n",
       "      <td>-8.09</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.29</td>\n",
       "      <td>0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>NGC3838</td>\n",
       "      <td>23.1</td>\n",
       "      <td>5.8</td>\n",
       "      <td>1</td>\n",
       "      <td>66.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>22.492</td>\n",
       "      <td>0.207</td>\n",
       "      <td>1.03</td>\n",
       "      <td>3410.59</td>\n",
       "      <td>1.99</td>\n",
       "      <td>417.67</td>\n",
       "      <td>-8.36</td>\n",
       "      <td>0.14</td>\n",
       "      <td>-10.31</td>\n",
       "      <td>0.13</td>\n",
       "      <td>-8.44</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-11.04</td>\n",
       "      <td>0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>NGC3941</td>\n",
       "      <td>12.4</td>\n",
       "      <td>1.6</td>\n",
       "      <td>2</td>\n",
       "      <td>57.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>43.656</td>\n",
       "      <td>0.402</td>\n",
       "      <td>1.42</td>\n",
       "      <td>3474.00</td>\n",
       "      <td>1.30</td>\n",
       "      <td>4373.51</td>\n",
       "      <td>-8.28</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-10.22</td>\n",
       "      <td>0.07</td>\n",
       "      <td>-8.12</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.43</td>\n",
       "      <td>0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>NGC3945</td>\n",
       "      <td>22.8</td>\n",
       "      <td>5.7</td>\n",
       "      <td>1</td>\n",
       "      <td>57.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>126.319</td>\n",
       "      <td>1.163</td>\n",
       "      <td>2.50</td>\n",
       "      <td>3197.64</td>\n",
       "      <td>7.22</td>\n",
       "      <td>209.33</td>\n",
       "      <td>-8.42</td>\n",
       "      <td>0.14</td>\n",
       "      <td>-9.90</td>\n",
       "      <td>0.12</td>\n",
       "      <td>-8.52</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.14</td>\n",
       "      <td>0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>NGC3998</td>\n",
       "      <td>14.2</td>\n",
       "      <td>1.8</td>\n",
       "      <td>2</td>\n",
       "      <td>66.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>56.205</td>\n",
       "      <td>0.518</td>\n",
       "      <td>1.01</td>\n",
       "      <td>8807.04</td>\n",
       "      <td>1.46</td>\n",
       "      <td>2997.99</td>\n",
       "      <td>-7.91</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-9.84</td>\n",
       "      <td>0.09</td>\n",
       "      <td>-8.17</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.44</td>\n",
       "      <td>0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>NGC4203</td>\n",
       "      <td>15.3</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>30.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>61.685</td>\n",
       "      <td>0.568</td>\n",
       "      <td>1.85</td>\n",
       "      <td>2093.29</td>\n",
       "      <td>1.85</td>\n",
       "      <td>2132.21</td>\n",
       "      <td>-8.46</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-10.06</td>\n",
       "      <td>0.16</td>\n",
       "      <td>-8.29</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.45</td>\n",
       "      <td>0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>NGC4262</td>\n",
       "      <td>16.6</td>\n",
       "      <td>1.8</td>\n",
       "      <td>2</td>\n",
       "      <td>67.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>28.988</td>\n",
       "      <td>0.267</td>\n",
       "      <td>0.69</td>\n",
       "      <td>9480.47</td>\n",
       "      <td>2.90</td>\n",
       "      <td>43.74</td>\n",
       "      <td>-7.85</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-9.88</td>\n",
       "      <td>0.06</td>\n",
       "      <td>-8.17</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.45</td>\n",
       "      <td>0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>NGC4278</td>\n",
       "      <td>15.4</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>45.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>82.612</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.63</td>\n",
       "      <td>4884.61</td>\n",
       "      <td>2.57</td>\n",
       "      <td>992.73</td>\n",
       "      <td>-8.30</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-9.72</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-8.48</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.10</td>\n",
       "      <td>0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>NGC5582</td>\n",
       "      <td>28.1</td>\n",
       "      <td>3.6</td>\n",
       "      <td>2</td>\n",
       "      <td>50.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>55.235</td>\n",
       "      <td>0.509</td>\n",
       "      <td>3.07</td>\n",
       "      <td>930.74</td>\n",
       "      <td>3.86</td>\n",
       "      <td>686.80</td>\n",
       "      <td>-8.49</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-10.12</td>\n",
       "      <td>0.07</td>\n",
       "      <td>-8.68</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-11.09</td>\n",
       "      <td>0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>NGC6798</td>\n",
       "      <td>37.3</td>\n",
       "      <td>9.3</td>\n",
       "      <td>1</td>\n",
       "      <td>52.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>69.090</td>\n",
       "      <td>0.636</td>\n",
       "      <td>3.30</td>\n",
       "      <td>992.73</td>\n",
       "      <td>3.29</td>\n",
       "      <td>974.61</td>\n",
       "      <td>-8.75</td>\n",
       "      <td>0.14</td>\n",
       "      <td>-10.37</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-9.29</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.95</td>\n",
       "      <td>0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>UGC6176</td>\n",
       "      <td>39.3</td>\n",
       "      <td>9.8</td>\n",
       "      <td>1</td>\n",
       "      <td>47.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>28.972</td>\n",
       "      <td>0.534</td>\n",
       "      <td>1.18</td>\n",
       "      <td>3317.65</td>\n",
       "      <td>1.80</td>\n",
       "      <td>1049.13</td>\n",
       "      <td>-8.08</td>\n",
       "      <td>0.14</td>\n",
       "      <td>-10.23</td>\n",
       "      <td>0.14</td>\n",
       "      <td>-8.61</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.57</td>\n",
       "      <td>0.11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Galaxy  Dist  errD  M   Inc  erI   L[3.6]   errL  Reff    SBeff  Rexp  \\\n",
       "0   NGC2685  16.1   4.8  1  65.0  4.0   30.037  0.277  1.92  1284.78  3.19   \n",
       "1   NGC2824  39.6   9.9  1  65.0  8.0   39.572  0.729  1.09  5209.91  5.00   \n",
       "2   NGC2859  26.2   6.5  1  35.0  5.0   89.085  0.820  1.59  5608.28  2.51   \n",
       "3   NGC2974  22.1   2.8  2  60.0  2.0  116.946  1.077  3.02  2017.58  3.44   \n",
       "4   NGC3522  25.2   3.2  2  41.0  2.0   13.183  0.243  1.42  1039.51  2.47   \n",
       "5   NGC3626  22.9   2.5  2  54.0  1.0   74.623  0.687  2.43  2017.58  2.52   \n",
       "6   NGC3838  23.1   5.8  1  66.0  8.0   22.492  0.207  1.03  3410.59  1.99   \n",
       "7   NGC3941  12.4   1.6  2  57.0  1.0   43.656  0.402  1.42  3474.00  1.30   \n",
       "8   NGC3945  22.8   5.7  1  57.0  5.0  126.319  1.163  2.50  3197.64  7.22   \n",
       "9   NGC3998  14.2   1.8  2  66.0  2.0   56.205  0.518  1.01  8807.04  1.46   \n",
       "10  NGC4203  15.3   2.0  2  30.0  3.0   61.685  0.568  1.85  2093.29  1.85   \n",
       "11  NGC4262  16.6   1.8  2  67.0  8.0   28.988  0.267  0.69  9480.47  2.90   \n",
       "12  NGC4278  15.4   2.0  2  45.0  5.0   82.612  0.000  1.63  4884.61  2.57   \n",
       "13  NGC5582  28.1   3.6  2  50.0  2.0   55.235  0.509  3.07   930.74  3.86   \n",
       "14  NGC6798  37.3   9.3  1  52.0  2.0   69.090  0.636  3.30   992.73  3.29   \n",
       "15  UGC6176  39.3   9.8  1  47.0  6.0   28.972  0.534  1.18  3317.65  1.80   \n",
       "\n",
       "      SBexp  Aobs1  eAobs1  Aobs2  eAobs2  Abar1  eAbar1  Abar2  eAbar2  \n",
       "0    413.84  -8.56    0.16 -10.57    0.14  -8.44    0.11 -11.25    0.11  \n",
       "1     84.11  -8.17    0.14  -9.96    0.12  -8.43    0.11 -10.13    0.11  \n",
       "2    603.71  -8.44    0.14  -9.99    0.20  -8.44    0.11 -10.31    0.11  \n",
       "3   1530.49  -8.36    0.10  -9.59    0.06  -8.52    0.11 -10.01    0.11  \n",
       "4    254.00  -8.43    0.10 -10.34    0.08  -8.73    0.11 -10.85    0.11  \n",
       "5   1891.60  -8.26    0.10 -10.16    0.06  -8.09    0.11 -10.29    0.11  \n",
       "6    417.67  -8.36    0.14 -10.31    0.13  -8.44    0.11 -11.04    0.11  \n",
       "7   4373.51  -8.28    0.10 -10.22    0.07  -8.12    0.11 -10.43    0.11  \n",
       "8    209.33  -8.42    0.14  -9.90    0.12  -8.52    0.11 -10.14    0.11  \n",
       "9   2997.99  -7.91    0.10  -9.84    0.09  -8.17    0.11 -10.44    0.11  \n",
       "10  2132.21  -8.46    0.10 -10.06    0.16  -8.29    0.11 -10.45    0.11  \n",
       "11    43.74  -7.85    0.10  -9.88    0.06  -8.17    0.11 -10.45    0.11  \n",
       "12   992.73  -8.30    0.10  -9.72    0.10  -8.48    0.11 -10.10    0.11  \n",
       "13   686.80  -8.49    0.10 -10.12    0.07  -8.68    0.11 -11.09    0.11  \n",
       "14   974.61  -8.75    0.14 -10.37    0.11  -9.29    0.11 -10.95    0.11  \n",
       "15  1049.13  -8.08    0.14 -10.23    0.14  -8.61    0.11 -10.57    0.11  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = pd.read_csv(\"Data/Galaxy Data/ETG_Lelli2017.csv\")\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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>Galaxy</th>\n",
       "      <th>Dist</th>\n",
       "      <th>errD</th>\n",
       "      <th>M</th>\n",
       "      <th>Inc</th>\n",
       "      <th>erI</th>\n",
       "      <th>L[3.6]</th>\n",
       "      <th>errL</th>\n",
       "      <th>Reff</th>\n",
       "      <th>SBeff</th>\n",
       "      <th>...</th>\n",
       "      <th>SBexp</th>\n",
       "      <th>Aobs1</th>\n",
       "      <th>eAobs1</th>\n",
       "      <th>Aobs2</th>\n",
       "      <th>eAobs2</th>\n",
       "      <th>Abar1</th>\n",
       "      <th>eAbar1</th>\n",
       "      <th>Abar2</th>\n",
       "      <th>eAbar2</th>\n",
       "      <th>LumCalc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NGC2685</td>\n",
       "      <td>16.1</td>\n",
       "      <td>4.8</td>\n",
       "      <td>1</td>\n",
       "      <td>65.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>30.037</td>\n",
       "      <td>0.277</td>\n",
       "      <td>1.92</td>\n",
       "      <td>1284.78</td>\n",
       "      <td>...</td>\n",
       "      <td>413.84</td>\n",
       "      <td>-8.56</td>\n",
       "      <td>0.16</td>\n",
       "      <td>-10.57</td>\n",
       "      <td>0.14</td>\n",
       "      <td>-8.44</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-11.25</td>\n",
       "      <td>0.11</td>\n",
       "      <td>29.758504</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NGC2824</td>\n",
       "      <td>39.6</td>\n",
       "      <td>9.9</td>\n",
       "      <td>1</td>\n",
       "      <td>65.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>39.572</td>\n",
       "      <td>0.729</td>\n",
       "      <td>1.09</td>\n",
       "      <td>5209.91</td>\n",
       "      <td>...</td>\n",
       "      <td>84.11</td>\n",
       "      <td>-8.17</td>\n",
       "      <td>0.14</td>\n",
       "      <td>-9.96</td>\n",
       "      <td>0.12</td>\n",
       "      <td>-8.43</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.13</td>\n",
       "      <td>0.11</td>\n",
       "      <td>38.892251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NGC2859</td>\n",
       "      <td>26.2</td>\n",
       "      <td>6.5</td>\n",
       "      <td>1</td>\n",
       "      <td>35.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>89.085</td>\n",
       "      <td>0.820</td>\n",
       "      <td>1.59</td>\n",
       "      <td>5608.28</td>\n",
       "      <td>...</td>\n",
       "      <td>603.71</td>\n",
       "      <td>-8.44</td>\n",
       "      <td>0.14</td>\n",
       "      <td>-9.99</td>\n",
       "      <td>0.20</td>\n",
       "      <td>-8.44</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.31</td>\n",
       "      <td>0.11</td>\n",
       "      <td>89.084840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NGC2974</td>\n",
       "      <td>22.1</td>\n",
       "      <td>2.8</td>\n",
       "      <td>2</td>\n",
       "      <td>60.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>116.946</td>\n",
       "      <td>1.077</td>\n",
       "      <td>3.02</td>\n",
       "      <td>2017.58</td>\n",
       "      <td>...</td>\n",
       "      <td>1530.49</td>\n",
       "      <td>-8.36</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-9.59</td>\n",
       "      <td>0.06</td>\n",
       "      <td>-8.52</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.01</td>\n",
       "      <td>0.11</td>\n",
       "      <td>115.617751</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NGC3522</td>\n",
       "      <td>25.2</td>\n",
       "      <td>3.2</td>\n",
       "      <td>2</td>\n",
       "      <td>41.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>13.183</td>\n",
       "      <td>0.243</td>\n",
       "      <td>1.42</td>\n",
       "      <td>1039.51</td>\n",
       "      <td>...</td>\n",
       "      <td>254.00</td>\n",
       "      <td>-8.43</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-10.34</td>\n",
       "      <td>0.08</td>\n",
       "      <td>-8.73</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.85</td>\n",
       "      <td>0.11</td>\n",
       "      <td>13.169983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>NGC3626</td>\n",
       "      <td>22.9</td>\n",
       "      <td>2.5</td>\n",
       "      <td>2</td>\n",
       "      <td>54.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>74.623</td>\n",
       "      <td>0.687</td>\n",
       "      <td>2.43</td>\n",
       "      <td>2017.58</td>\n",
       "      <td>...</td>\n",
       "      <td>1891.60</td>\n",
       "      <td>-8.26</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-10.16</td>\n",
       "      <td>0.06</td>\n",
       "      <td>-8.09</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.29</td>\n",
       "      <td>0.11</td>\n",
       "      <td>74.855408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>NGC3838</td>\n",
       "      <td>23.1</td>\n",
       "      <td>5.8</td>\n",
       "      <td>1</td>\n",
       "      <td>66.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>22.492</td>\n",
       "      <td>0.207</td>\n",
       "      <td>1.03</td>\n",
       "      <td>3410.59</td>\n",
       "      <td>...</td>\n",
       "      <td>417.67</td>\n",
       "      <td>-8.36</td>\n",
       "      <td>0.14</td>\n",
       "      <td>-10.31</td>\n",
       "      <td>0.13</td>\n",
       "      <td>-8.44</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-11.04</td>\n",
       "      <td>0.11</td>\n",
       "      <td>22.734418</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>NGC3941</td>\n",
       "      <td>12.4</td>\n",
       "      <td>1.6</td>\n",
       "      <td>2</td>\n",
       "      <td>57.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>43.656</td>\n",
       "      <td>0.402</td>\n",
       "      <td>1.42</td>\n",
       "      <td>3474.00</td>\n",
       "      <td>...</td>\n",
       "      <td>4373.51</td>\n",
       "      <td>-8.28</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-10.22</td>\n",
       "      <td>0.07</td>\n",
       "      <td>-8.12</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.43</td>\n",
       "      <td>0.11</td>\n",
       "      <td>44.013547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>NGC3945</td>\n",
       "      <td>22.8</td>\n",
       "      <td>5.7</td>\n",
       "      <td>1</td>\n",
       "      <td>57.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>126.319</td>\n",
       "      <td>1.163</td>\n",
       "      <td>2.50</td>\n",
       "      <td>3197.64</td>\n",
       "      <td>...</td>\n",
       "      <td>209.33</td>\n",
       "      <td>-8.42</td>\n",
       "      <td>0.14</td>\n",
       "      <td>-9.90</td>\n",
       "      <td>0.12</td>\n",
       "      <td>-8.52</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.14</td>\n",
       "      <td>0.11</td>\n",
       "      <td>125.571029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>NGC3998</td>\n",
       "      <td>14.2</td>\n",
       "      <td>1.8</td>\n",
       "      <td>2</td>\n",
       "      <td>66.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>56.205</td>\n",
       "      <td>0.518</td>\n",
       "      <td>1.01</td>\n",
       "      <td>8807.04</td>\n",
       "      <td>...</td>\n",
       "      <td>2997.99</td>\n",
       "      <td>-7.91</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-9.84</td>\n",
       "      <td>0.09</td>\n",
       "      <td>-8.17</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.44</td>\n",
       "      <td>0.11</td>\n",
       "      <td>56.448523</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>NGC4203</td>\n",
       "      <td>15.3</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>30.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>61.685</td>\n",
       "      <td>0.568</td>\n",
       "      <td>1.85</td>\n",
       "      <td>2093.29</td>\n",
       "      <td>...</td>\n",
       "      <td>2132.21</td>\n",
       "      <td>-8.46</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-10.06</td>\n",
       "      <td>0.16</td>\n",
       "      <td>-8.29</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.45</td>\n",
       "      <td>0.11</td>\n",
       "      <td>45.014530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>NGC4262</td>\n",
       "      <td>16.6</td>\n",
       "      <td>1.8</td>\n",
       "      <td>2</td>\n",
       "      <td>67.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>28.988</td>\n",
       "      <td>0.267</td>\n",
       "      <td>0.69</td>\n",
       "      <td>9480.47</td>\n",
       "      <td>...</td>\n",
       "      <td>43.74</td>\n",
       "      <td>-7.85</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-9.88</td>\n",
       "      <td>0.06</td>\n",
       "      <td>-8.17</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.45</td>\n",
       "      <td>0.11</td>\n",
       "      <td>28.360110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>NGC4278</td>\n",
       "      <td>15.4</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>45.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>82.612</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.63</td>\n",
       "      <td>4884.61</td>\n",
       "      <td>...</td>\n",
       "      <td>992.73</td>\n",
       "      <td>-8.30</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-9.72</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-8.48</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.10</td>\n",
       "      <td>0.11</td>\n",
       "      <td>81.542678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>NGC5582</td>\n",
       "      <td>28.1</td>\n",
       "      <td>3.6</td>\n",
       "      <td>2</td>\n",
       "      <td>50.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>55.235</td>\n",
       "      <td>0.509</td>\n",
       "      <td>3.07</td>\n",
       "      <td>930.74</td>\n",
       "      <td>...</td>\n",
       "      <td>686.80</td>\n",
       "      <td>-8.49</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-10.12</td>\n",
       "      <td>0.07</td>\n",
       "      <td>-8.68</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-11.09</td>\n",
       "      <td>0.11</td>\n",
       "      <td>55.116927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>NGC6798</td>\n",
       "      <td>37.3</td>\n",
       "      <td>9.3</td>\n",
       "      <td>1</td>\n",
       "      <td>52.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>69.090</td>\n",
       "      <td>0.636</td>\n",
       "      <td>3.30</td>\n",
       "      <td>992.73</td>\n",
       "      <td>...</td>\n",
       "      <td>974.61</td>\n",
       "      <td>-8.75</td>\n",
       "      <td>0.14</td>\n",
       "      <td>-10.37</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-9.29</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.95</td>\n",
       "      <td>0.11</td>\n",
       "      <td>67.926446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>UGC6176</td>\n",
       "      <td>39.3</td>\n",
       "      <td>9.8</td>\n",
       "      <td>1</td>\n",
       "      <td>47.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>28.972</td>\n",
       "      <td>0.534</td>\n",
       "      <td>1.18</td>\n",
       "      <td>3317.65</td>\n",
       "      <td>...</td>\n",
       "      <td>1049.13</td>\n",
       "      <td>-8.08</td>\n",
       "      <td>0.14</td>\n",
       "      <td>-10.23</td>\n",
       "      <td>0.14</td>\n",
       "      <td>-8.61</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.57</td>\n",
       "      <td>0.11</td>\n",
       "      <td>29.025149</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Galaxy  Dist  errD  M   Inc  erI   L[3.6]   errL  Reff    SBeff  ...  \\\n",
       "0   NGC2685  16.1   4.8  1  65.0  4.0   30.037  0.277  1.92  1284.78  ...   \n",
       "1   NGC2824  39.6   9.9  1  65.0  8.0   39.572  0.729  1.09  5209.91  ...   \n",
       "2   NGC2859  26.2   6.5  1  35.0  5.0   89.085  0.820  1.59  5608.28  ...   \n",
       "3   NGC2974  22.1   2.8  2  60.0  2.0  116.946  1.077  3.02  2017.58  ...   \n",
       "4   NGC3522  25.2   3.2  2  41.0  2.0   13.183  0.243  1.42  1039.51  ...   \n",
       "5   NGC3626  22.9   2.5  2  54.0  1.0   74.623  0.687  2.43  2017.58  ...   \n",
       "6   NGC3838  23.1   5.8  1  66.0  8.0   22.492  0.207  1.03  3410.59  ...   \n",
       "7   NGC3941  12.4   1.6  2  57.0  1.0   43.656  0.402  1.42  3474.00  ...   \n",
       "8   NGC3945  22.8   5.7  1  57.0  5.0  126.319  1.163  2.50  3197.64  ...   \n",
       "9   NGC3998  14.2   1.8  2  66.0  2.0   56.205  0.518  1.01  8807.04  ...   \n",
       "10  NGC4203  15.3   2.0  2  30.0  3.0   61.685  0.568  1.85  2093.29  ...   \n",
       "11  NGC4262  16.6   1.8  2  67.0  8.0   28.988  0.267  0.69  9480.47  ...   \n",
       "12  NGC4278  15.4   2.0  2  45.0  5.0   82.612  0.000  1.63  4884.61  ...   \n",
       "13  NGC5582  28.1   3.6  2  50.0  2.0   55.235  0.509  3.07   930.74  ...   \n",
       "14  NGC6798  37.3   9.3  1  52.0  2.0   69.090  0.636  3.30   992.73  ...   \n",
       "15  UGC6176  39.3   9.8  1  47.0  6.0   28.972  0.534  1.18  3317.65  ...   \n",
       "\n",
       "      SBexp  Aobs1  eAobs1  Aobs2  eAobs2  Abar1  eAbar1  Abar2  eAbar2  \\\n",
       "0    413.84  -8.56    0.16 -10.57    0.14  -8.44    0.11 -11.25    0.11   \n",
       "1     84.11  -8.17    0.14  -9.96    0.12  -8.43    0.11 -10.13    0.11   \n",
       "2    603.71  -8.44    0.14  -9.99    0.20  -8.44    0.11 -10.31    0.11   \n",
       "3   1530.49  -8.36    0.10  -9.59    0.06  -8.52    0.11 -10.01    0.11   \n",
       "4    254.00  -8.43    0.10 -10.34    0.08  -8.73    0.11 -10.85    0.11   \n",
       "5   1891.60  -8.26    0.10 -10.16    0.06  -8.09    0.11 -10.29    0.11   \n",
       "6    417.67  -8.36    0.14 -10.31    0.13  -8.44    0.11 -11.04    0.11   \n",
       "7   4373.51  -8.28    0.10 -10.22    0.07  -8.12    0.11 -10.43    0.11   \n",
       "8    209.33  -8.42    0.14  -9.90    0.12  -8.52    0.11 -10.14    0.11   \n",
       "9   2997.99  -7.91    0.10  -9.84    0.09  -8.17    0.11 -10.44    0.11   \n",
       "10  2132.21  -8.46    0.10 -10.06    0.16  -8.29    0.11 -10.45    0.11   \n",
       "11    43.74  -7.85    0.10  -9.88    0.06  -8.17    0.11 -10.45    0.11   \n",
       "12   992.73  -8.30    0.10  -9.72    0.10  -8.48    0.11 -10.10    0.11   \n",
       "13   686.80  -8.49    0.10 -10.12    0.07  -8.68    0.11 -11.09    0.11   \n",
       "14   974.61  -8.75    0.14 -10.37    0.11  -9.29    0.11 -10.95    0.11   \n",
       "15  1049.13  -8.08    0.14 -10.23    0.14  -8.61    0.11 -10.57    0.11   \n",
       "\n",
       "       LumCalc  \n",
       "0    29.758504  \n",
       "1    38.892251  \n",
       "2    89.084840  \n",
       "3   115.617751  \n",
       "4    13.169983  \n",
       "5    74.855408  \n",
       "6    22.734418  \n",
       "7    44.013547  \n",
       "8   125.571029  \n",
       "9    56.448523  \n",
       "10   45.014530  \n",
       "11   28.360110  \n",
       "12   81.542678  \n",
       "13   55.116927  \n",
       "14   67.926446  \n",
       "15   29.025149  \n",
       "\n",
       "[16 rows x 21 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2['LumCalc'] = df2['Reff'] ** 2 * 2 * np.pi * df2['SBeff'] / 10 ** 3\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2['LumPercentError'] = np.abs(df2['L[3.6]'] - df2['LumCalc']) / df2['L[3.6]']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.024800115518449347\n"
     ]
    }
   ],
   "source": [
    "etg_error_avg = np.mean(df2['LumPercentError'])\n",
    "print(etg_error_avg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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>Galaxy</th>\n",
       "      <th>T</th>\n",
       "      <th>D</th>\n",
       "      <th>e_D</th>\n",
       "      <th>f_D</th>\n",
       "      <th>Inc</th>\n",
       "      <th>e_Inc</th>\n",
       "      <th>L[3.6]</th>\n",
       "      <th>e_L[3.6]</th>\n",
       "      <th>Reff</th>\n",
       "      <th>...</th>\n",
       "      <th>Rdisk</th>\n",
       "      <th>SBdisk</th>\n",
       "      <th>MHI</th>\n",
       "      <th>RHI</th>\n",
       "      <th>Vflat</th>\n",
       "      <th>e_Vflat</th>\n",
       "      <th>Q</th>\n",
       "      <th>Ref.</th>\n",
       "      <th>LumCalc</th>\n",
       "      <th>LumPercentError</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CamB</td>\n",
       "      <td>10</td>\n",
       "      <td>3.36</td>\n",
       "      <td>0.26</td>\n",
       "      <td>2</td>\n",
       "      <td>65.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.075</td>\n",
       "      <td>0.003</td>\n",
       "      <td>1.21</td>\n",
       "      <td>...</td>\n",
       "      <td>0.47</td>\n",
       "      <td>66.20</td>\n",
       "      <td>0.012</td>\n",
       "      <td>1.21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>Bm03</td>\n",
       "      <td>0.074995</td>\n",
       "      <td>7.141723e-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>D512-2</td>\n",
       "      <td>10</td>\n",
       "      <td>15.20</td>\n",
       "      <td>4.56</td>\n",
       "      <td>1</td>\n",
       "      <td>56.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.325</td>\n",
       "      <td>0.022</td>\n",
       "      <td>2.37</td>\n",
       "      <td>...</td>\n",
       "      <td>1.24</td>\n",
       "      <td>93.94</td>\n",
       "      <td>0.081</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>Tr09</td>\n",
       "      <td>0.325000</td>\n",
       "      <td>3.236365e-10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>D564-8</td>\n",
       "      <td>10</td>\n",
       "      <td>8.79</td>\n",
       "      <td>0.28</td>\n",
       "      <td>2</td>\n",
       "      <td>63.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.033</td>\n",
       "      <td>0.004</td>\n",
       "      <td>0.72</td>\n",
       "      <td>...</td>\n",
       "      <td>0.61</td>\n",
       "      <td>21.13</td>\n",
       "      <td>0.029</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>Tr09</td>\n",
       "      <td>0.032977</td>\n",
       "      <td>6.892617e-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>D631-7</td>\n",
       "      <td>10</td>\n",
       "      <td>7.72</td>\n",
       "      <td>0.18</td>\n",
       "      <td>2</td>\n",
       "      <td>59.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.196</td>\n",
       "      <td>0.009</td>\n",
       "      <td>1.22</td>\n",
       "      <td>...</td>\n",
       "      <td>0.70</td>\n",
       "      <td>115.04</td>\n",
       "      <td>0.290</td>\n",
       "      <td>0.00</td>\n",
       "      <td>57.7</td>\n",
       "      <td>2.7</td>\n",
       "      <td>1</td>\n",
       "      <td>Tr09;dB01</td>\n",
       "      <td>0.196000</td>\n",
       "      <td>8.137057e-12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>DDO064</td>\n",
       "      <td>10</td>\n",
       "      <td>6.80</td>\n",
       "      <td>2.04</td>\n",
       "      <td>1</td>\n",
       "      <td>60.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.157</td>\n",
       "      <td>0.007</td>\n",
       "      <td>1.20</td>\n",
       "      <td>...</td>\n",
       "      <td>0.69</td>\n",
       "      <td>151.65</td>\n",
       "      <td>0.211</td>\n",
       "      <td>3.49</td>\n",
       "      <td>46.1</td>\n",
       "      <td>3.9</td>\n",
       "      <td>1</td>\n",
       "      <td>dB02;Sw02</td>\n",
       "      <td>0.157000</td>\n",
       "      <td>8.447333e-10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>UGC12632</td>\n",
       "      <td>9</td>\n",
       "      <td>9.77</td>\n",
       "      <td>2.93</td>\n",
       "      <td>1</td>\n",
       "      <td>46.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.301</td>\n",
       "      <td>0.030</td>\n",
       "      <td>3.94</td>\n",
       "      <td>...</td>\n",
       "      <td>2.42</td>\n",
       "      <td>66.81</td>\n",
       "      <td>1.744</td>\n",
       "      <td>12.60</td>\n",
       "      <td>71.7</td>\n",
       "      <td>2.8</td>\n",
       "      <td>1</td>\n",
       "      <td>Sw09;Sw02</td>\n",
       "      <td>1.301000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>UGC12732</td>\n",
       "      <td>9</td>\n",
       "      <td>13.20</td>\n",
       "      <td>4.00</td>\n",
       "      <td>1</td>\n",
       "      <td>39.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.667</td>\n",
       "      <td>0.048</td>\n",
       "      <td>3.12</td>\n",
       "      <td>...</td>\n",
       "      <td>1.98</td>\n",
       "      <td>120.46</td>\n",
       "      <td>3.660</td>\n",
       "      <td>17.41</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>Sw09;Sw02</td>\n",
       "      <td>1.667000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>UGCA281</td>\n",
       "      <td>11</td>\n",
       "      <td>5.68</td>\n",
       "      <td>0.28</td>\n",
       "      <td>2</td>\n",
       "      <td>67.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.194</td>\n",
       "      <td>0.007</td>\n",
       "      <td>1.57</td>\n",
       "      <td>...</td>\n",
       "      <td>1.72</td>\n",
       "      <td>12.05</td>\n",
       "      <td>0.062</td>\n",
       "      <td>1.83</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>Le14</td>\n",
       "      <td>0.194000</td>\n",
       "      <td>2.998961e-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>UGCA442</td>\n",
       "      <td>9</td>\n",
       "      <td>4.35</td>\n",
       "      <td>0.22</td>\n",
       "      <td>2</td>\n",
       "      <td>64.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.140</td>\n",
       "      <td>0.005</td>\n",
       "      <td>1.71</td>\n",
       "      <td>...</td>\n",
       "      <td>1.18</td>\n",
       "      <td>116.10</td>\n",
       "      <td>0.263</td>\n",
       "      <td>4.37</td>\n",
       "      <td>56.4</td>\n",
       "      <td>2.1</td>\n",
       "      <td>1</td>\n",
       "      <td>Co00</td>\n",
       "      <td>0.140000</td>\n",
       "      <td>2.269384e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>UGCA444</td>\n",
       "      <td>10</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.05</td>\n",
       "      <td>2</td>\n",
       "      <td>78.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.012</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.41</td>\n",
       "      <td>...</td>\n",
       "      <td>0.83</td>\n",
       "      <td>22.74</td>\n",
       "      <td>0.067</td>\n",
       "      <td>2.08</td>\n",
       "      <td>37.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>2</td>\n",
       "      <td>Ke07</td>\n",
       "      <td>0.011911</td>\n",
       "      <td>7.425368e-03</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>175 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Galaxy   T      D   e_D  f_D   Inc  e_Inc  L[3.6]  e_L[3.6]  Reff  ...  \\\n",
       "0        CamB  10   3.36  0.26    2  65.0    5.0   0.075     0.003  1.21  ...   \n",
       "1      D512-2  10  15.20  4.56    1  56.0   10.0   0.325     0.022  2.37  ...   \n",
       "2      D564-8  10   8.79  0.28    2  63.0    7.0   0.033     0.004  0.72  ...   \n",
       "3      D631-7  10   7.72  0.18    2  59.0    3.0   0.196     0.009  1.22  ...   \n",
       "4      DDO064  10   6.80  2.04    1  60.0    5.0   0.157     0.007  1.20  ...   \n",
       "..        ...  ..    ...   ...  ...   ...    ...     ...       ...   ...  ...   \n",
       "170  UGC12632   9   9.77  2.93    1  46.0    3.0   1.301     0.030  3.94  ...   \n",
       "171  UGC12732   9  13.20  4.00    1  39.0    6.0   1.667     0.048  3.12  ...   \n",
       "172   UGCA281  11   5.68  0.28    2  67.0    3.0   0.194     0.007  1.57  ...   \n",
       "173   UGCA442   9   4.35  0.22    2  64.0    7.0   0.140     0.005  1.71  ...   \n",
       "174   UGCA444  10   0.98  0.05    2  78.0    4.0   0.012     0.000  0.41  ...   \n",
       "\n",
       "     Rdisk  SBdisk    MHI    RHI  Vflat  e_Vflat  Q       Ref.   LumCalc  \\\n",
       "0     0.47   66.20  0.012   1.21    0.0      0.0  2       Bm03  0.074995   \n",
       "1     1.24   93.94  0.081   0.00    0.0      0.0  2       Tr09  0.325000   \n",
       "2     0.61   21.13  0.029   0.00    0.0      0.0  2       Tr09  0.032977   \n",
       "3     0.70  115.04  0.290   0.00   57.7      2.7  1  Tr09;dB01  0.196000   \n",
       "4     0.69  151.65  0.211   3.49   46.1      3.9  1  dB02;Sw02  0.157000   \n",
       "..     ...     ...    ...    ...    ...      ... ..        ...       ...   \n",
       "170   2.42   66.81  1.744  12.60   71.7      2.8  1  Sw09;Sw02  1.301000   \n",
       "171   1.98  120.46  3.660  17.41    0.0      0.0  1  Sw09;Sw02  1.667000   \n",
       "172   1.72   12.05  0.062   1.83    0.0      0.0  3       Le14  0.194000   \n",
       "173   1.18  116.10  0.263   4.37   56.4      2.1  1       Co00  0.140000   \n",
       "174   0.83   22.74  0.067   2.08   37.0      4.8  2       Ke07  0.011911   \n",
       "\n",
       "     LumPercentError  \n",
       "0       7.141723e-05  \n",
       "1       3.236365e-10  \n",
       "2       6.892617e-04  \n",
       "3       8.137057e-12  \n",
       "4       8.447333e-10  \n",
       "..               ...  \n",
       "170     0.000000e+00  \n",
       "171     0.000000e+00  \n",
       "172     2.998961e-09  \n",
       "173     2.269384e-06  \n",
       "174     7.425368e-03  \n",
       "\n",
       "[175 rows x 21 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>Galaxy</th>\n",
       "      <th>Dist</th>\n",
       "      <th>errD</th>\n",
       "      <th>M</th>\n",
       "      <th>Inc</th>\n",
       "      <th>erI</th>\n",
       "      <th>L[3.6]</th>\n",
       "      <th>errL</th>\n",
       "      <th>Reff</th>\n",
       "      <th>SBeff</th>\n",
       "      <th>...</th>\n",
       "      <th>Aobs1</th>\n",
       "      <th>eAobs1</th>\n",
       "      <th>Aobs2</th>\n",
       "      <th>eAobs2</th>\n",
       "      <th>Abar1</th>\n",
       "      <th>eAbar1</th>\n",
       "      <th>Abar2</th>\n",
       "      <th>eAbar2</th>\n",
       "      <th>LumCalc</th>\n",
       "      <th>LumPercentError</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NGC2685</td>\n",
       "      <td>16.1</td>\n",
       "      <td>4.8</td>\n",
       "      <td>1</td>\n",
       "      <td>65.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>30.037</td>\n",
       "      <td>0.277</td>\n",
       "      <td>1.92</td>\n",
       "      <td>1284.78</td>\n",
       "      <td>...</td>\n",
       "      <td>-8.56</td>\n",
       "      <td>0.16</td>\n",
       "      <td>-10.57</td>\n",
       "      <td>0.14</td>\n",
       "      <td>-8.44</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-11.25</td>\n",
       "      <td>0.11</td>\n",
       "      <td>29.758504</td>\n",
       "      <td>0.009272</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NGC2824</td>\n",
       "      <td>39.6</td>\n",
       "      <td>9.9</td>\n",
       "      <td>1</td>\n",
       "      <td>65.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>39.572</td>\n",
       "      <td>0.729</td>\n",
       "      <td>1.09</td>\n",
       "      <td>5209.91</td>\n",
       "      <td>...</td>\n",
       "      <td>-8.17</td>\n",
       "      <td>0.14</td>\n",
       "      <td>-9.96</td>\n",
       "      <td>0.12</td>\n",
       "      <td>-8.43</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.13</td>\n",
       "      <td>0.11</td>\n",
       "      <td>38.892251</td>\n",
       "      <td>0.017178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NGC2859</td>\n",
       "      <td>26.2</td>\n",
       "      <td>6.5</td>\n",
       "      <td>1</td>\n",
       "      <td>35.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>89.085</td>\n",
       "      <td>0.820</td>\n",
       "      <td>1.59</td>\n",
       "      <td>5608.28</td>\n",
       "      <td>...</td>\n",
       "      <td>-8.44</td>\n",
       "      <td>0.14</td>\n",
       "      <td>-9.99</td>\n",
       "      <td>0.20</td>\n",
       "      <td>-8.44</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.31</td>\n",
       "      <td>0.11</td>\n",
       "      <td>89.084840</td>\n",
       "      <td>0.000002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NGC2974</td>\n",
       "      <td>22.1</td>\n",
       "      <td>2.8</td>\n",
       "      <td>2</td>\n",
       "      <td>60.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>116.946</td>\n",
       "      <td>1.077</td>\n",
       "      <td>3.02</td>\n",
       "      <td>2017.58</td>\n",
       "      <td>...</td>\n",
       "      <td>-8.36</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-9.59</td>\n",
       "      <td>0.06</td>\n",
       "      <td>-8.52</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.01</td>\n",
       "      <td>0.11</td>\n",
       "      <td>115.617751</td>\n",
       "      <td>0.011358</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NGC3522</td>\n",
       "      <td>25.2</td>\n",
       "      <td>3.2</td>\n",
       "      <td>2</td>\n",
       "      <td>41.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>13.183</td>\n",
       "      <td>0.243</td>\n",
       "      <td>1.42</td>\n",
       "      <td>1039.51</td>\n",
       "      <td>...</td>\n",
       "      <td>-8.43</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-10.34</td>\n",
       "      <td>0.08</td>\n",
       "      <td>-8.73</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.85</td>\n",
       "      <td>0.11</td>\n",
       "      <td>13.169983</td>\n",
       "      <td>0.000987</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>NGC3626</td>\n",
       "      <td>22.9</td>\n",
       "      <td>2.5</td>\n",
       "      <td>2</td>\n",
       "      <td>54.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>74.623</td>\n",
       "      <td>0.687</td>\n",
       "      <td>2.43</td>\n",
       "      <td>2017.58</td>\n",
       "      <td>...</td>\n",
       "      <td>-8.26</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-10.16</td>\n",
       "      <td>0.06</td>\n",
       "      <td>-8.09</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.29</td>\n",
       "      <td>0.11</td>\n",
       "      <td>74.855408</td>\n",
       "      <td>0.003114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>NGC3838</td>\n",
       "      <td>23.1</td>\n",
       "      <td>5.8</td>\n",
       "      <td>1</td>\n",
       "      <td>66.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>22.492</td>\n",
       "      <td>0.207</td>\n",
       "      <td>1.03</td>\n",
       "      <td>3410.59</td>\n",
       "      <td>...</td>\n",
       "      <td>-8.36</td>\n",
       "      <td>0.14</td>\n",
       "      <td>-10.31</td>\n",
       "      <td>0.13</td>\n",
       "      <td>-8.44</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-11.04</td>\n",
       "      <td>0.11</td>\n",
       "      <td>22.734418</td>\n",
       "      <td>0.010778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>NGC3941</td>\n",
       "      <td>12.4</td>\n",
       "      <td>1.6</td>\n",
       "      <td>2</td>\n",
       "      <td>57.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>43.656</td>\n",
       "      <td>0.402</td>\n",
       "      <td>1.42</td>\n",
       "      <td>3474.00</td>\n",
       "      <td>...</td>\n",
       "      <td>-8.28</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-10.22</td>\n",
       "      <td>0.07</td>\n",
       "      <td>-8.12</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.43</td>\n",
       "      <td>0.11</td>\n",
       "      <td>44.013547</td>\n",
       "      <td>0.008190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>NGC3945</td>\n",
       "      <td>22.8</td>\n",
       "      <td>5.7</td>\n",
       "      <td>1</td>\n",
       "      <td>57.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>126.319</td>\n",
       "      <td>1.163</td>\n",
       "      <td>2.50</td>\n",
       "      <td>3197.64</td>\n",
       "      <td>...</td>\n",
       "      <td>-8.42</td>\n",
       "      <td>0.14</td>\n",
       "      <td>-9.90</td>\n",
       "      <td>0.12</td>\n",
       "      <td>-8.52</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.14</td>\n",
       "      <td>0.11</td>\n",
       "      <td>125.571029</td>\n",
       "      <td>0.005921</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>NGC3998</td>\n",
       "      <td>14.2</td>\n",
       "      <td>1.8</td>\n",
       "      <td>2</td>\n",
       "      <td>66.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>56.205</td>\n",
       "      <td>0.518</td>\n",
       "      <td>1.01</td>\n",
       "      <td>8807.04</td>\n",
       "      <td>...</td>\n",
       "      <td>-7.91</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-9.84</td>\n",
       "      <td>0.09</td>\n",
       "      <td>-8.17</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.44</td>\n",
       "      <td>0.11</td>\n",
       "      <td>56.448523</td>\n",
       "      <td>0.004333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>NGC4203</td>\n",
       "      <td>15.3</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>30.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>61.685</td>\n",
       "      <td>0.568</td>\n",
       "      <td>1.85</td>\n",
       "      <td>2093.29</td>\n",
       "      <td>...</td>\n",
       "      <td>-8.46</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-10.06</td>\n",
       "      <td>0.16</td>\n",
       "      <td>-8.29</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.45</td>\n",
       "      <td>0.11</td>\n",
       "      <td>45.014530</td>\n",
       "      <td>0.270252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>NGC4262</td>\n",
       "      <td>16.6</td>\n",
       "      <td>1.8</td>\n",
       "      <td>2</td>\n",
       "      <td>67.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>28.988</td>\n",
       "      <td>0.267</td>\n",
       "      <td>0.69</td>\n",
       "      <td>9480.47</td>\n",
       "      <td>...</td>\n",
       "      <td>-7.85</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-9.88</td>\n",
       "      <td>0.06</td>\n",
       "      <td>-8.17</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.45</td>\n",
       "      <td>0.11</td>\n",
       "      <td>28.360110</td>\n",
       "      <td>0.021660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>NGC4278</td>\n",
       "      <td>15.4</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2</td>\n",
       "      <td>45.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>82.612</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.63</td>\n",
       "      <td>4884.61</td>\n",
       "      <td>...</td>\n",
       "      <td>-8.30</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-9.72</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-8.48</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.10</td>\n",
       "      <td>0.11</td>\n",
       "      <td>81.542678</td>\n",
       "      <td>0.012944</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>NGC5582</td>\n",
       "      <td>28.1</td>\n",
       "      <td>3.6</td>\n",
       "      <td>2</td>\n",
       "      <td>50.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>55.235</td>\n",
       "      <td>0.509</td>\n",
       "      <td>3.07</td>\n",
       "      <td>930.74</td>\n",
       "      <td>...</td>\n",
       "      <td>-8.49</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-10.12</td>\n",
       "      <td>0.07</td>\n",
       "      <td>-8.68</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-11.09</td>\n",
       "      <td>0.11</td>\n",
       "      <td>55.116927</td>\n",
       "      <td>0.002138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>NGC6798</td>\n",
       "      <td>37.3</td>\n",
       "      <td>9.3</td>\n",
       "      <td>1</td>\n",
       "      <td>52.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>69.090</td>\n",
       "      <td>0.636</td>\n",
       "      <td>3.30</td>\n",
       "      <td>992.73</td>\n",
       "      <td>...</td>\n",
       "      <td>-8.75</td>\n",
       "      <td>0.14</td>\n",
       "      <td>-10.37</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-9.29</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.95</td>\n",
       "      <td>0.11</td>\n",
       "      <td>67.926446</td>\n",
       "      <td>0.016841</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>UGC6176</td>\n",
       "      <td>39.3</td>\n",
       "      <td>9.8</td>\n",
       "      <td>1</td>\n",
       "      <td>47.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>28.972</td>\n",
       "      <td>0.534</td>\n",
       "      <td>1.18</td>\n",
       "      <td>3317.65</td>\n",
       "      <td>...</td>\n",
       "      <td>-8.08</td>\n",
       "      <td>0.14</td>\n",
       "      <td>-10.23</td>\n",
       "      <td>0.14</td>\n",
       "      <td>-8.61</td>\n",
       "      <td>0.11</td>\n",
       "      <td>-10.57</td>\n",
       "      <td>0.11</td>\n",
       "      <td>29.025149</td>\n",
       "      <td>0.001834</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Galaxy  Dist  errD  M   Inc  erI   L[3.6]   errL  Reff    SBeff  ...  \\\n",
       "0   NGC2685  16.1   4.8  1  65.0  4.0   30.037  0.277  1.92  1284.78  ...   \n",
       "1   NGC2824  39.6   9.9  1  65.0  8.0   39.572  0.729  1.09  5209.91  ...   \n",
       "2   NGC2859  26.2   6.5  1  35.0  5.0   89.085  0.820  1.59  5608.28  ...   \n",
       "3   NGC2974  22.1   2.8  2  60.0  2.0  116.946  1.077  3.02  2017.58  ...   \n",
       "4   NGC3522  25.2   3.2  2  41.0  2.0   13.183  0.243  1.42  1039.51  ...   \n",
       "5   NGC3626  22.9   2.5  2  54.0  1.0   74.623  0.687  2.43  2017.58  ...   \n",
       "6   NGC3838  23.1   5.8  1  66.0  8.0   22.492  0.207  1.03  3410.59  ...   \n",
       "7   NGC3941  12.4   1.6  2  57.0  1.0   43.656  0.402  1.42  3474.00  ...   \n",
       "8   NGC3945  22.8   5.7  1  57.0  5.0  126.319  1.163  2.50  3197.64  ...   \n",
       "9   NGC3998  14.2   1.8  2  66.0  2.0   56.205  0.518  1.01  8807.04  ...   \n",
       "10  NGC4203  15.3   2.0  2  30.0  3.0   61.685  0.568  1.85  2093.29  ...   \n",
       "11  NGC4262  16.6   1.8  2  67.0  8.0   28.988  0.267  0.69  9480.47  ...   \n",
       "12  NGC4278  15.4   2.0  2  45.0  5.0   82.612  0.000  1.63  4884.61  ...   \n",
       "13  NGC5582  28.1   3.6  2  50.0  2.0   55.235  0.509  3.07   930.74  ...   \n",
       "14  NGC6798  37.3   9.3  1  52.0  2.0   69.090  0.636  3.30   992.73  ...   \n",
       "15  UGC6176  39.3   9.8  1  47.0  6.0   28.972  0.534  1.18  3317.65  ...   \n",
       "\n",
       "    Aobs1  eAobs1  Aobs2  eAobs2  Abar1  eAbar1  Abar2  eAbar2     LumCalc  \\\n",
       "0   -8.56    0.16 -10.57    0.14  -8.44    0.11 -11.25    0.11   29.758504   \n",
       "1   -8.17    0.14  -9.96    0.12  -8.43    0.11 -10.13    0.11   38.892251   \n",
       "2   -8.44    0.14  -9.99    0.20  -8.44    0.11 -10.31    0.11   89.084840   \n",
       "3   -8.36    0.10  -9.59    0.06  -8.52    0.11 -10.01    0.11  115.617751   \n",
       "4   -8.43    0.10 -10.34    0.08  -8.73    0.11 -10.85    0.11   13.169983   \n",
       "5   -8.26    0.10 -10.16    0.06  -8.09    0.11 -10.29    0.11   74.855408   \n",
       "6   -8.36    0.14 -10.31    0.13  -8.44    0.11 -11.04    0.11   22.734418   \n",
       "7   -8.28    0.10 -10.22    0.07  -8.12    0.11 -10.43    0.11   44.013547   \n",
       "8   -8.42    0.14  -9.90    0.12  -8.52    0.11 -10.14    0.11  125.571029   \n",
       "9   -7.91    0.10  -9.84    0.09  -8.17    0.11 -10.44    0.11   56.448523   \n",
       "10  -8.46    0.10 -10.06    0.16  -8.29    0.11 -10.45    0.11   45.014530   \n",
       "11  -7.85    0.10  -9.88    0.06  -8.17    0.11 -10.45    0.11   28.360110   \n",
       "12  -8.30    0.10  -9.72    0.10  -8.48    0.11 -10.10    0.11   81.542678   \n",
       "13  -8.49    0.10 -10.12    0.07  -8.68    0.11 -11.09    0.11   55.116927   \n",
       "14  -8.75    0.14 -10.37    0.11  -9.29    0.11 -10.95    0.11   67.926446   \n",
       "15  -8.08    0.14 -10.23    0.14  -8.61    0.11 -10.57    0.11   29.025149   \n",
       "\n",
       "    LumPercentError  \n",
       "0          0.009272  \n",
       "1          0.017178  \n",
       "2          0.000002  \n",
       "3          0.011358  \n",
       "4          0.000987  \n",
       "5          0.003114  \n",
       "6          0.010778  \n",
       "7          0.008190  \n",
       "8          0.005921  \n",
       "9          0.004333  \n",
       "10         0.270252  \n",
       "11         0.021660  \n",
       "12         0.012944  \n",
       "13         0.002138  \n",
       "14         0.016841  \n",
       "15         0.001834  \n",
       "\n",
       "[16 rows x 22 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>galaxy</th>\n",
       "      <th>radius</th>\n",
       "      <th>mu</th>\n",
       "      <th>kill</th>\n",
       "      <th>error</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NGC0289</td>\n",
       "      <td>0.65</td>\n",
       "      <td>14.084</td>\n",
       "      <td>1</td>\n",
       "      <td>0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NGC0289</td>\n",
       "      <td>0.72</td>\n",
       "      <td>14.104</td>\n",
       "      <td>1</td>\n",
       "      <td>0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NGC0289</td>\n",
       "      <td>0.79</td>\n",
       "      <td>14.128</td>\n",
       "      <td>1</td>\n",
       "      <td>0.002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NGC0289</td>\n",
       "      <td>0.87</td>\n",
       "      <td>14.158</td>\n",
       "      <td>1</td>\n",
       "      <td>0.002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NGC0289</td>\n",
       "      <td>0.96</td>\n",
       "      <td>14.192</td>\n",
       "      <td>1</td>\n",
       "      <td>0.002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12538</th>\n",
       "      <td>NGC3941</td>\n",
       "      <td>180.72</td>\n",
       "      <td>23.486</td>\n",
       "      <td>1</td>\n",
       "      <td>0.609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12539</th>\n",
       "      <td>NGC3941</td>\n",
       "      <td>198.79</td>\n",
       "      <td>23.691</td>\n",
       "      <td>1</td>\n",
       "      <td>0.704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12540</th>\n",
       "      <td>NGC3941</td>\n",
       "      <td>218.67</td>\n",
       "      <td>23.655</td>\n",
       "      <td>1</td>\n",
       "      <td>0.686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12541</th>\n",
       "      <td>NGC3941</td>\n",
       "      <td>240.54</td>\n",
       "      <td>24.499</td>\n",
       "      <td>0</td>\n",
       "      <td>1.164</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12542</th>\n",
       "      <td>NGC3941</td>\n",
       "      <td>264.59</td>\n",
       "      <td>25.157</td>\n",
       "      <td>0</td>\n",
       "      <td>1.638</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>12543 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        galaxy  radius      mu  kill  error\n",
       "0      NGC0289    0.65  14.084     1  0.001\n",
       "1      NGC0289    0.72  14.104     1  0.001\n",
       "2      NGC0289    0.79  14.128     1  0.002\n",
       "3      NGC0289    0.87  14.158     1  0.002\n",
       "4      NGC0289    0.96  14.192     1  0.002\n",
       "...        ...     ...     ...   ...    ...\n",
       "12538  NGC3941  180.72  23.486     1  0.609\n",
       "12539  NGC3941  198.79  23.691     1  0.704\n",
       "12540  NGC3941  218.67  23.655     1  0.686\n",
       "12541  NGC3941  240.54  24.499     0  1.164\n",
       "12542  NGC3941  264.59  25.157     0  1.638\n",
       "\n",
       "[12543 rows x 5 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sfb = pd.read_csv(\"Data/Galaxy Data/sfb.csv\")\n",
    "sfb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "\n",
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       "        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>Galaxy</th>\n",
       "      <th>Reff</th>\n",
       "      <th>LumCalc</th>\n",
       "      <th>LumPercentError</th>\n",
       "      <th>SBeff</th>\n",
       "      <th>L[3.6]</th>\n",
       "      <th>Dist</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CamB</td>\n",
       "      <td>1.21</td>\n",
       "      <td>0.074995</td>\n",
       "      <td>7.141723e-05</td>\n",
       "      <td>7.89</td>\n",
       "      <td>0.075</td>\n",
       "      <td>3360000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>D512-2</td>\n",
       "      <td>2.37</td>\n",
       "      <td>0.325000</td>\n",
       "      <td>3.236365e-10</td>\n",
       "      <td>9.22</td>\n",
       "      <td>0.325</td>\n",
       "      <td>15200000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>D564-8</td>\n",
       "      <td>0.72</td>\n",
       "      <td>0.032977</td>\n",
       "      <td>6.892617e-04</td>\n",
       "      <td>10.11</td>\n",
       "      <td>0.033</td>\n",
       "      <td>8790000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>D631-7</td>\n",
       "      <td>1.22</td>\n",
       "      <td>0.196000</td>\n",
       "      <td>8.137057e-12</td>\n",
       "      <td>20.93</td>\n",
       "      <td>0.196</td>\n",
       "      <td>7720000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>DDO064</td>\n",
       "      <td>1.20</td>\n",
       "      <td>0.157000</td>\n",
       "      <td>8.447333e-10</td>\n",
       "      <td>17.41</td>\n",
       "      <td>0.157</td>\n",
       "      <td>6800000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>NGC4262</td>\n",
       "      <td>0.69</td>\n",
       "      <td>28.360110</td>\n",
       "      <td>2.166033e-02</td>\n",
       "      <td>9480.47</td>\n",
       "      <td>28.988</td>\n",
       "      <td>16600000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>NGC4278</td>\n",
       "      <td>1.63</td>\n",
       "      <td>81.542678</td>\n",
       "      <td>1.294390e-02</td>\n",
       "      <td>4884.61</td>\n",
       "      <td>82.612</td>\n",
       "      <td>15400000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>NGC5582</td>\n",
       "      <td>3.07</td>\n",
       "      <td>55.116927</td>\n",
       "      <td>2.137643e-03</td>\n",
       "      <td>930.74</td>\n",
       "      <td>55.235</td>\n",
       "      <td>28100000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>NGC6798</td>\n",
       "      <td>3.30</td>\n",
       "      <td>67.926446</td>\n",
       "      <td>1.684113e-02</td>\n",
       "      <td>992.73</td>\n",
       "      <td>69.090</td>\n",
       "      <td>37300000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>UGC6176</td>\n",
       "      <td>1.18</td>\n",
       "      <td>29.025149</td>\n",
       "      <td>1.834479e-03</td>\n",
       "      <td>3317.65</td>\n",
       "      <td>28.972</td>\n",
       "      <td>39300000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>191 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Galaxy  Reff    LumCalc  LumPercentError    SBeff  L[3.6]        Dist\n",
       "0       CamB  1.21   0.074995     7.141723e-05     7.89   0.075   3360000.0\n",
       "1     D512-2  2.37   0.325000     3.236365e-10     9.22   0.325  15200000.0\n",
       "2     D564-8  0.72   0.032977     6.892617e-04    10.11   0.033   8790000.0\n",
       "3     D631-7  1.22   0.196000     8.137057e-12    20.93   0.196   7720000.0\n",
       "4     DDO064  1.20   0.157000     8.447333e-10    17.41   0.157   6800000.0\n",
       "..       ...   ...        ...              ...      ...     ...         ...\n",
       "186  NGC4262  0.69  28.360110     2.166033e-02  9480.47  28.988  16600000.0\n",
       "187  NGC4278  1.63  81.542678     1.294390e-02  4884.61  82.612  15400000.0\n",
       "188  NGC5582  3.07  55.116927     2.137643e-03   930.74  55.235  28100000.0\n",
       "189  NGC6798  3.30  67.926446     1.684113e-02   992.73  69.090  37300000.0\n",
       "190  UGC6176  1.18  29.025149     1.834479e-03  3317.65  28.972  39300000.0\n",
       "\n",
       "[191 rows x 7 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "galaxy_names = list(df[\"Galaxy\"])\n",
    "galaxy_names.extend(list(df2[\"Galaxy\"]))\n",
    "r_eff = list(df[\"Reff\"])\n",
    "r_eff.extend(list(df2[\"Reff\"]))\n",
    "lum = list(df[\"LumCalc\"])\n",
    "lum.extend(list(df2[\"LumCalc\"]))\n",
    "err = list(df[\"LumPercentError\"])\n",
    "err.extend(list(df2[\"LumPercentError\"]))\n",
    "sbeff = list(df[\"SBeff\"])\n",
    "sbeff.extend(list(df2[\"SBeff\"]))\n",
    "tlum = list(df[\"L[3.6]\"])\n",
    "tlum.extend(list(df2[\"L[3.6]\"]))\n",
    "dis = list(df[\"D\"] * 10 ** 6)\n",
    "dis.extend(list(df2[\"Dist\"] * 10 ** 6))\n",
    "df3 = pd.DataFrame({\"Galaxy\": galaxy_names, \"Reff\": r_eff, \"LumCalc\": lum, \"LumPercentError\": err, \"SBeff\": sbeff, \"L[3.6]\": tlum, \"Dist\": dis})\n",
    "df3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>Galaxy</th>\n",
       "      <th>Reff</th>\n",
       "      <th>LumCalc</th>\n",
       "      <th>LumPercentError</th>\n",
       "      <th>SBeff</th>\n",
       "      <th>L[3.6]</th>\n",
       "      <th>Dist</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>48</td>\n",
       "      <td>NGC2915</td>\n",
       "      <td>0.53</td>\n",
       "      <td>0.641000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>347.40</td>\n",
       "      <td>0.641</td>\n",
       "      <td>4060000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>51</td>\n",
       "      <td>NGC2998</td>\n",
       "      <td>7.06</td>\n",
       "      <td>150.902000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>479.55</td>\n",
       "      <td>150.902</td>\n",
       "      <td>68100000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>56</td>\n",
       "      <td>NGC3741</td>\n",
       "      <td>0.32</td>\n",
       "      <td>0.028000</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>42.94</td>\n",
       "      <td>0.028</td>\n",
       "      <td>3210000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>72</td>\n",
       "      <td>NGC4138</td>\n",
       "      <td>1.91</td>\n",
       "      <td>44.111000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1909.11</td>\n",
       "      <td>44.111</td>\n",
       "      <td>18000000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>97</td>\n",
       "      <td>UGC00191</td>\n",
       "      <td>2.50</td>\n",
       "      <td>2.004000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>50.21</td>\n",
       "      <td>2.004</td>\n",
       "      <td>17100000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>131</td>\n",
       "      <td>UGC06614</td>\n",
       "      <td>3.68</td>\n",
       "      <td>124.350000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1461.61</td>\n",
       "      <td>124.350</td>\n",
       "      <td>88700000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>187</td>\n",
       "      <td>NGC4278</td>\n",
       "      <td>1.63</td>\n",
       "      <td>81.542678</td>\n",
       "      <td>0.012944</td>\n",
       "      <td>4884.61</td>\n",
       "      <td>82.612</td>\n",
       "      <td>15400000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   index    Galaxy  Reff     LumCalc  LumPercentError    SBeff   L[3.6]  \\\n",
       "0     48   NGC2915  0.53    0.641000         0.000000   347.40    0.641   \n",
       "1     51   NGC2998  7.06  150.902000         0.000000   479.55  150.902   \n",
       "2     56   NGC3741  0.32    0.028000         0.000001    42.94    0.028   \n",
       "3     72   NGC4138  1.91   44.111000         0.000000  1909.11   44.111   \n",
       "4     97  UGC00191  2.50    2.004000         0.000000    50.21    2.004   \n",
       "5    131  UGC06614  3.68  124.350000         0.000000  1461.61  124.350   \n",
       "6    187   NGC4278  1.63   81.542678         0.012944  4884.61   82.612   \n",
       "\n",
       "         Dist  \n",
       "0   4060000.0  \n",
       "1  68100000.0  \n",
       "2   3210000.0  \n",
       "3  18000000.0  \n",
       "4  17100000.0  \n",
       "5  88700000.0  \n",
       "6  15400000.0  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get only the rows with these galaxies: NGC3741, NGC4138, UGC06614, NGC2915, NGC4278\n",
    "galaxies = [\"NGC2915\", \"NGC2998\", \"NGC3741\", \"NGC4138\", \"UGC00191\", \"UGC06614\", \"NGC4278\"]\n",
    "galaxy_legend = [\"NGC2915 (Irregular)\", \"NGC2998 (Middle Spiral)\", \"NGC3741 (Irregular)\", \"NGC4138 (Lenticular)\", \"UGC00191 (Irregular)\", \"UGC06614 (Tight Spiral)\", \"NGC4278 (Elliptical)\"]\n",
    "df3 = df3[df3[\"Galaxy\"].isin(galaxies)]\n",
    "df3 = df3.reset_index()\n",
    "df3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'NGC2915': [[], []], 'NGC2998': [[], []], 'NGC3741': [[], []], 'NGC4138': [[], []], 'UGC00191': [[], []], 'UGC06614': [[], []], 'NGC4278': [[], []]}\n",
      "NGC2915\n",
      "NGC2998\n",
      "NGC3741\n",
      "NGC4138\n",
      "UGC00191\n",
      "UGC06614\n",
      "NGC4278\n",
      "[]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'NGC2915': [[0.34,\n",
       "   0.67,\n",
       "   1.0,\n",
       "   1.34,\n",
       "   1.68,\n",
       "   2.01,\n",
       "   2.34,\n",
       "   2.67,\n",
       "   3.01,\n",
       "   3.35,\n",
       "   3.68,\n",
       "   4.02,\n",
       "   4.35,\n",
       "   4.68,\n",
       "   5.02,\n",
       "   5.35,\n",
       "   5.69,\n",
       "   6.03,\n",
       "   6.36,\n",
       "   6.69,\n",
       "   7.02,\n",
       "   7.36,\n",
       "   7.7,\n",
       "   8.03,\n",
       "   8.37,\n",
       "   8.7,\n",
       "   9.03,\n",
       "   9.37,\n",
       "   9.7,\n",
       "   10.04],\n",
       "  [13.5,\n",
       "   31.3,\n",
       "   35.3,\n",
       "   50.5,\n",
       "   61.0,\n",
       "   66.5,\n",
       "   74.4,\n",
       "   83.0,\n",
       "   86.4,\n",
       "   83.6,\n",
       "   79.8,\n",
       "   82.8,\n",
       "   83.5,\n",
       "   80.4,\n",
       "   80.3,\n",
       "   82.1,\n",
       "   82.4,\n",
       "   80.9,\n",
       "   79.0,\n",
       "   81.4,\n",
       "   79.7,\n",
       "   77.5,\n",
       "   79.9,\n",
       "   81.5,\n",
       "   82.2,\n",
       "   82.0,\n",
       "   84.7,\n",
       "   86.1,\n",
       "   85.3,\n",
       "   86.5]],\n",
       " 'NGC2998': [[0.33,\n",
       "   0.99,\n",
       "   1.98,\n",
       "   2.64,\n",
       "   3.63,\n",
       "   7.59,\n",
       "   12.5,\n",
       "   17.48,\n",
       "   22.46,\n",
       "   27.44,\n",
       "   32.32,\n",
       "   37.3,\n",
       "   42.28],\n",
       "  [90.0,\n",
       "   125.0,\n",
       "   148.0,\n",
       "   180.0,\n",
       "   201.0,\n",
       "   206.0,\n",
       "   214.0,\n",
       "   212.0,\n",
       "   213.0,\n",
       "   214.0,\n",
       "   213.0,\n",
       "   213.0,\n",
       "   203.0]],\n",
       " 'NGC3741': [[0.23,\n",
       "   0.47,\n",
       "   0.7,\n",
       "   0.93,\n",
       "   1.17,\n",
       "   1.4,\n",
       "   1.64,\n",
       "   1.87,\n",
       "   2.1,\n",
       "   2.33,\n",
       "   2.57,\n",
       "   2.8,\n",
       "   3.26,\n",
       "   3.73,\n",
       "   4.21,\n",
       "   4.67,\n",
       "   5.14,\n",
       "   5.61,\n",
       "   6.07,\n",
       "   6.54,\n",
       "   7.0],\n",
       "  [13.1,\n",
       "   17.3,\n",
       "   23.6,\n",
       "   26.2,\n",
       "   27.4,\n",
       "   26.9,\n",
       "   27.4,\n",
       "   31.0,\n",
       "   32.5,\n",
       "   33.0,\n",
       "   36.5,\n",
       "   38.9,\n",
       "   41.5,\n",
       "   42.7,\n",
       "   44.7,\n",
       "   46.7,\n",
       "   48.5,\n",
       "   50.0,\n",
       "   50.2,\n",
       "   50.1,\n",
       "   51.6]],\n",
       " 'NGC4138': [[2.61, 5.24, 7.85, 10.65, 13.47, 16.03, 18.58],\n",
       "  [179.0, 195.0, 181.0, 162.0, 145.0, 147.0, 150.0]],\n",
       " 'UGC00191': [[0.62, 0.87, 1.12, 1.37, 1.62, 2.3, 4.97, 7.45, 9.98],\n",
       "  [29.9, 34.4, 46.3, 49.8, 57.6, 71.3, 76.65, 81.0, 83.85]],\n",
       " 'UGC06614': [[3.23,\n",
       "   9.18,\n",
       "   10.64,\n",
       "   11.58,\n",
       "   12.52,\n",
       "   13.57,\n",
       "   15.76,\n",
       "   24.94,\n",
       "   26.3,\n",
       "   34.96,\n",
       "   36.84,\n",
       "   47.38,\n",
       "   64.59],\n",
       "  [194.0,\n",
       "   172.0,\n",
       "   170.0,\n",
       "   170.0,\n",
       "   171.0,\n",
       "   172.0,\n",
       "   174.0,\n",
       "   193.0,\n",
       "   194.0,\n",
       "   201.0,\n",
       "   202.0,\n",
       "   205.0,\n",
       "   204.0]],\n",
       " 'NGC4278': [[0.85, 11.2], [364.0, 256.0]]}"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = []\n",
    "new_data = {galaxy: [[], []] for galaxy in galaxies}\n",
    "print(new_data)\n",
    "for galaxy in galaxies:\n",
    "    print(galaxy)\n",
    "    fin = open(\"Data/Galaxy Data/Rotmod_Undivided/\" + galaxy + \"_rotmod.dat\")\n",
    "    lines = fin.read().split(\"\\n\")[3:-1]\n",
    "    for line in lines:\n",
    "        data.append(line.strip().replace(\",\", \";\").split())\n",
    "    for line in data:\n",
    "        new_data[galaxy][0].append(float(line[0]))\n",
    "        new_data[galaxy][1].append(float(line[1]))\n",
    "    data.clear()\n",
    "print(data)\n",
    "new_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.34, 0.67, 1.0, 1.34, 1.68, 2.01, 2.34, 2.67, 3.01, 3.35, 3.68, 4.02, 4.35, 4.68, 5.02, 5.35, 5.69, 6.03, 6.36, 6.69, 7.02, 7.36, 7.7, 8.03, 8.37, 8.7, 9.03, 9.37, 9.7, 10.04]\n",
      "[0.33, 0.99, 1.98, 2.64, 3.63, 7.59, 12.5, 17.48, 22.46, 27.44, 32.32, 37.3, 42.28]\n",
      "[0.23, 0.47, 0.7, 0.93, 1.17, 1.4, 1.64, 1.87, 2.1, 2.33, 2.57, 2.8, 3.26, 3.73, 4.21, 4.67, 5.14, 5.61, 6.07, 6.54, 7.0]\n",
      "[2.61, 5.24, 7.85, 10.65, 13.47, 16.03, 18.58]\n",
      "[0.62, 0.87, 1.12, 1.37, 1.62, 2.3, 4.97, 7.45, 9.98]\n",
      "[3.23, 9.18, 10.64, 11.58, 12.52, 13.57, 15.76, 24.94, 26.3, 34.96, 36.84, 47.38, 64.59]\n",
      "[0.85, 11.2]\n"
     ]
    },
    {
     "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>index</th>\n",
       "      <th>Galaxy</th>\n",
       "      <th>Reff</th>\n",
       "      <th>LumCalc</th>\n",
       "      <th>LumPercentError</th>\n",
       "      <th>SBeff</th>\n",
       "      <th>L[3.6]</th>\n",
       "      <th>Dist</th>\n",
       "      <th>Radius</th>\n",
       "      <th>Velocity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>48</td>\n",
       "      <td>NGC2915</td>\n",
       "      <td>0.53</td>\n",
       "      <td>0.641000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>347.40</td>\n",
       "      <td>0.641</td>\n",
       "      <td>4060000.0</td>\n",
       "      <td>[0.34, 0.67, 1.0, 1.34, 1.68, 2.01, 2.34, 2.67...</td>\n",
       "      <td>[13.5, 31.3, 35.3, 50.5, 61.0, 66.5, 74.4, 83....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>51</td>\n",
       "      <td>NGC2998</td>\n",
       "      <td>7.06</td>\n",
       "      <td>150.902000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>479.55</td>\n",
       "      <td>150.902</td>\n",
       "      <td>68100000.0</td>\n",
       "      <td>[0.33, 0.99, 1.98, 2.64, 3.63, 7.59, 12.5, 17....</td>\n",
       "      <td>[90.0, 125.0, 148.0, 180.0, 201.0, 206.0, 214....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>56</td>\n",
       "      <td>NGC3741</td>\n",
       "      <td>0.32</td>\n",
       "      <td>0.028000</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>42.94</td>\n",
       "      <td>0.028</td>\n",
       "      <td>3210000.0</td>\n",
       "      <td>[0.23, 0.47, 0.7, 0.93, 1.17, 1.4, 1.64, 1.87,...</td>\n",
       "      <td>[13.1, 17.3, 23.6, 26.2, 27.4, 26.9, 27.4, 31....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>72</td>\n",
       "      <td>NGC4138</td>\n",
       "      <td>1.91</td>\n",
       "      <td>44.111000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1909.11</td>\n",
       "      <td>44.111</td>\n",
       "      <td>18000000.0</td>\n",
       "      <td>[2.61, 5.24, 7.85, 10.65, 13.47, 16.03, 18.58]</td>\n",
       "      <td>[179.0, 195.0, 181.0, 162.0, 145.0, 147.0, 150.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>97</td>\n",
       "      <td>UGC00191</td>\n",
       "      <td>2.50</td>\n",
       "      <td>2.004000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>50.21</td>\n",
       "      <td>2.004</td>\n",
       "      <td>17100000.0</td>\n",
       "      <td>[0.62, 0.87, 1.12, 1.37, 1.62, 2.3, 4.97, 7.45...</td>\n",
       "      <td>[29.9, 34.4, 46.3, 49.8, 57.6, 71.3, 76.65, 81...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>131</td>\n",
       "      <td>UGC06614</td>\n",
       "      <td>3.68</td>\n",
       "      <td>124.350000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1461.61</td>\n",
       "      <td>124.350</td>\n",
       "      <td>88700000.0</td>\n",
       "      <td>[3.23, 9.18, 10.64, 11.58, 12.52, 13.57, 15.76...</td>\n",
       "      <td>[194.0, 172.0, 170.0, 170.0, 171.0, 172.0, 174...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>187</td>\n",
       "      <td>NGC4278</td>\n",
       "      <td>1.63</td>\n",
       "      <td>81.542678</td>\n",
       "      <td>0.012944</td>\n",
       "      <td>4884.61</td>\n",
       "      <td>82.612</td>\n",
       "      <td>15400000.0</td>\n",
       "      <td>[0.85, 11.2]</td>\n",
       "      <td>[364.0, 256.0]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   index    Galaxy  Reff     LumCalc  LumPercentError    SBeff   L[3.6]  \\\n",
       "0     48   NGC2915  0.53    0.641000         0.000000   347.40    0.641   \n",
       "1     51   NGC2998  7.06  150.902000         0.000000   479.55  150.902   \n",
       "2     56   NGC3741  0.32    0.028000         0.000001    42.94    0.028   \n",
       "3     72   NGC4138  1.91   44.111000         0.000000  1909.11   44.111   \n",
       "4     97  UGC00191  2.50    2.004000         0.000000    50.21    2.004   \n",
       "5    131  UGC06614  3.68  124.350000         0.000000  1461.61  124.350   \n",
       "6    187   NGC4278  1.63   81.542678         0.012944  4884.61   82.612   \n",
       "\n",
       "         Dist                                             Radius  \\\n",
       "0   4060000.0  [0.34, 0.67, 1.0, 1.34, 1.68, 2.01, 2.34, 2.67...   \n",
       "1  68100000.0  [0.33, 0.99, 1.98, 2.64, 3.63, 7.59, 12.5, 17....   \n",
       "2   3210000.0  [0.23, 0.47, 0.7, 0.93, 1.17, 1.4, 1.64, 1.87,...   \n",
       "3  18000000.0     [2.61, 5.24, 7.85, 10.65, 13.47, 16.03, 18.58]   \n",
       "4  17100000.0  [0.62, 0.87, 1.12, 1.37, 1.62, 2.3, 4.97, 7.45...   \n",
       "5  88700000.0  [3.23, 9.18, 10.64, 11.58, 12.52, 13.57, 15.76...   \n",
       "6  15400000.0                                       [0.85, 11.2]   \n",
       "\n",
       "                                            Velocity  \n",
       "0  [13.5, 31.3, 35.3, 50.5, 61.0, 66.5, 74.4, 83....  \n",
       "1  [90.0, 125.0, 148.0, 180.0, 201.0, 206.0, 214....  \n",
       "2  [13.1, 17.3, 23.6, 26.2, 27.4, 26.9, 27.4, 31....  \n",
       "3  [179.0, 195.0, 181.0, 162.0, 145.0, 147.0, 150.0]  \n",
       "4  [29.9, 34.4, 46.3, 49.8, 57.6, 71.3, 76.65, 81...  \n",
       "5  [194.0, 172.0, 170.0, 170.0, 171.0, 172.0, 174...  \n",
       "6                                     [364.0, 256.0]  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# append the data as two new columns to the dataframe in a column called radius and vrot for each galaxy (for the row with NGC3741 there should be a list under radius and velocity)\n",
    "r = []\n",
    "v = []\n",
    "for galaxy in galaxies:\n",
    "    # print(new_data)\n",
    "    print(new_data[galaxy][0])\n",
    "    r.append(new_data[galaxy][0])\n",
    "    v.append(new_data[galaxy][1])\n",
    "rad = pd.Series(r, name=\"Radius\")\n",
    "vel = pd.Series(v, name=\"Velocity\")\n",
    "df3 = pd.concat([df3, rad, vel], axis=1)\n",
    "df3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['0.65', '0.72', '0.79', '0.87', '0.96', '1.05', '1.16', '1.27', '1.40', '1.54', '1.69', '1.86', '2.05', '2.25', '2.48', '2.73', '3.00', '3.30', '3.63', '3.99', '4.39', '4.83', '5.31', '5.85', '6.43', '7.07', '7.78', '8.56', '9.42', '10.36', '11.39', '12.53', '13.78', '15.16', '16.68', '18.35', '20.18', '22.20', '24.42', '26.86', '29.55', '32.50', '35.75', '39.33', '43.26', '47.59', '52.35', '57.58', '63.34', '69.68', '76.64', '84.31', '92.74', '102.01', '112.21', '123.43', '135.78', '149.36', '164.29']\n",
      "['0.65', '0.72', '0.79', '0.87', '0.96', '1.05', '1.16', '1.27', '1.40', '1.54', '1.69', '1.86', '2.05', '2.25', '2.48', '2.73', '3.00', '3.30', '3.63', '3.99', '4.39', '4.83', '5.31', '5.85', '6.43', '7.07', '7.78', '8.56', '9.42', '10.36', '11.39', '12.53', '13.78', '15.16', '16.68', '18.35', '20.18', '22.20', '24.42', '26.86', '29.55', '32.50', '35.75', '39.33', '43.26', '47.59', '52.35', '57.58', '63.34', '69.68', '76.64', '84.31', '92.74', '102.01', '112.21', '123.43', '135.78']\n",
      "['0.65', '0.72', '0.79', '0.87', '0.96', '1.05', '1.16', '1.27', '1.40', '1.54', '1.69', '1.86', '2.05', '2.25', '2.48', '2.73', '3.00', '3.30', '3.63', '3.99', '4.39', '4.83', '5.31', '5.85', '6.43', '7.07', '7.78', '8.56', '9.42', '10.36', '11.39', '12.53', '13.78', '15.16', '16.68', '18.35', '20.18', '22.20', '24.42', '26.86', '29.55', '32.50', '35.75', '39.33', '43.26', '47.59', '52.35', '57.58', '63.34', '69.68', '76.64', '84.31', '92.74', '102.01', '112.21']\n",
      "['0.65', '0.72', '0.79', '0.87', '0.96', '1.05', '1.16', '1.27', '1.40', '1.54', '1.69', '1.86', '2.05', '2.25', '2.48', '2.73', '3.00', '3.30', '3.63', '3.99', '4.39', '4.83', '5.31', '5.85', '6.43', '7.07', '7.78', '8.56', '9.42', '10.36', '11.39', '12.53', '13.78', '15.16', '16.68', '18.35', '20.18', '22.20', '24.42', '26.86', '29.55', '32.50', '35.75', '39.33', '43.26', '47.59', '52.35', '57.58', '63.34', '69.68', '76.64', '84.31', '92.74', '102.01', '112.21', '123.43', '135.78', '149.36', '164.29', '180.72', '320.16', '352.17']\n",
      "['0.65', '0.72', '0.79', '0.87', '0.96', '1.05', '1.16', '1.27', '1.40', '1.54', '1.69', '1.86', '2.05', '2.25', '2.48', '2.73', '3.00', '3.30', '3.63', '3.99', '4.39', '4.83', '5.31', '5.85', '6.43', '7.07', '7.78', '8.56', '9.42', '10.36', '11.39', '12.53', '13.78', '15.16', '16.68', '18.35', '20.18', '22.20', '24.42', '26.86', '29.55', '32.50', '35.75', '39.33', '43.26', '47.59', '52.35', '57.58', '63.34', '69.68', '76.64', '84.31', '102.01', '123.43', '135.78', '149.36']\n",
      "['0.65', '0.72', '0.79', '0.87', '0.96', '1.05', '1.16', '1.27', '1.40', '1.54', '1.69', '1.86', '2.05', '2.25', '2.48', '2.73', '3.00', '3.30', '3.63', '3.99', '4.39', '4.83', '5.31', '5.85', '6.43', '7.07', '7.78', '8.56', '9.42', '10.36', '11.39', '12.53', '13.78', '15.16', '16.68', '18.35', '20.18', '22.20', '24.42', '26.86', '29.55', '32.50', '35.75', '39.33', '43.26', '47.59', '52.35', '57.58', '63.34', '69.68', '76.64']\n",
      "['0.65', '0.72', '0.79', '0.87', '0.96', '1.05', '1.16', '1.27', '1.40', '1.54', '1.69', '1.86', '2.05', '2.25', '2.48', '2.73', '3.00', '3.30', '3.63', '3.99', '4.39', '4.83', '5.31', '5.85', '6.43', '7.07', '7.78', '8.56', '9.42', '10.36', '11.39', '12.53', '13.78', '15.16', '16.68', '18.35', '20.18', '22.20', '24.42', '26.86', '29.55', '32.50', '35.75', '39.33', '43.26', '47.59', '52.35', '57.58', '63.34', '69.68', '76.64', '84.31', '92.74', '102.01', '112.21', '123.43', '135.78', '149.36', '164.29', '180.72', '198.79', '218.67', '240.54']\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
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       "        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>index</th>\n",
       "      <th>Galaxy</th>\n",
       "      <th>Reff</th>\n",
       "      <th>LumCalc</th>\n",
       "      <th>LumPercentError</th>\n",
       "      <th>SBeff</th>\n",
       "      <th>L[3.6]</th>\n",
       "      <th>Dist</th>\n",
       "      <th>Radius</th>\n",
       "      <th>Velocity</th>\n",
       "      <th>Original Radius (1)</th>\n",
       "      <th>Radius2</th>\n",
       "      <th>SB</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>48</td>\n",
       "      <td>NGC2915</td>\n",
       "      <td>0.53</td>\n",
       "      <td>0.641000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>347.40</td>\n",
       "      <td>0.641</td>\n",
       "      <td>4060000.0</td>\n",
       "      <td>[0.34, 0.67, 1.0, 1.34, 1.68, 2.01, 2.34, 2.67...</td>\n",
       "      <td>[13.5, 31.3, 35.3, 50.5, 61.0, 66.5, 74.4, 83....</td>\n",
       "      <td>[0.65, 0.72, 0.79, 0.87, 0.96, 1.05, 1.16, 1.2...</td>\n",
       "      <td>[0.012782663458497988, 0.014159257984797769, 0...</td>\n",
       "      <td>[16.455, 16.469, 16.484, 16.5, 16.518, 16.542,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>51</td>\n",
       "      <td>NGC2998</td>\n",
       "      <td>7.06</td>\n",
       "      <td>150.902000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>479.55</td>\n",
       "      <td>150.902</td>\n",
       "      <td>68100000.0</td>\n",
       "      <td>[0.33, 0.99, 1.98, 2.64, 3.63, 7.59, 12.5, 17....</td>\n",
       "      <td>[90.0, 125.0, 148.0, 180.0, 201.0, 206.0, 214....</td>\n",
       "      <td>[0.65, 0.72, 0.79, 0.87, 0.96, 1.05, 1.16, 1.2...</td>\n",
       "      <td>[0.21135938576561064, 0.23412116577113792, 0.2...</td>\n",
       "      <td>[15.762, 15.776, 15.79, 15.808, 15.831, 15.86,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>56</td>\n",
       "      <td>NGC3741</td>\n",
       "      <td>0.32</td>\n",
       "      <td>0.028000</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>42.94</td>\n",
       "      <td>0.028</td>\n",
       "      <td>3210000.0</td>\n",
       "      <td>[0.23, 0.47, 0.7, 0.93, 1.17, 1.4, 1.64, 1.87,...</td>\n",
       "      <td>[13.1, 17.3, 23.6, 26.2, 27.4, 26.9, 27.4, 31....</td>\n",
       "      <td>[0.65, 0.72, 0.79, 0.87, 0.96, 1.05, 1.16, 1.2...</td>\n",
       "      <td>[0.01010841899028594, 0.011197017958470579, 0....</td>\n",
       "      <td>[18.985, 19.01, 19.028, 19.054, 19.079, 19.101...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>72</td>\n",
       "      <td>NGC4138</td>\n",
       "      <td>1.91</td>\n",
       "      <td>44.111000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1909.11</td>\n",
       "      <td>44.111</td>\n",
       "      <td>18000000.0</td>\n",
       "      <td>[2.61, 5.24, 7.85, 10.65, 13.47, 16.03, 18.58]</td>\n",
       "      <td>[179.0, 195.0, 181.0, 162.0, 145.0, 147.0, 150.0]</td>\n",
       "      <td>[0.65, 0.72, 0.79, 0.87, 0.96, 1.05, 1.16, 1.2...</td>\n",
       "      <td>[0.0564947186677653, 0.06257876529352463, 0.06...</td>\n",
       "      <td>[12.968, 12.987, 13.01, 13.043, 13.079, 13.126...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>97</td>\n",
       "      <td>UGC00191</td>\n",
       "      <td>2.50</td>\n",
       "      <td>2.004000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>50.21</td>\n",
       "      <td>2.004</td>\n",
       "      <td>17100000.0</td>\n",
       "      <td>[0.62, 0.87, 1.12, 1.37, 1.62, 2.3, 4.97, 7.45...</td>\n",
       "      <td>[29.9, 34.4, 46.3, 49.8, 57.6, 71.3, 76.65, 81...</td>\n",
       "      <td>[0.65, 0.72, 0.79, 0.87, 0.96, 1.05, 1.16, 1.2...</td>\n",
       "      <td>[0.05368081051021463, 0.05946182087285312, 0.0...</td>\n",
       "      <td>[18.884, 18.903, 18.904, 18.905, 18.906, 18.90...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>131</td>\n",
       "      <td>UGC06614</td>\n",
       "      <td>3.68</td>\n",
       "      <td>124.350000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1461.61</td>\n",
       "      <td>124.350</td>\n",
       "      <td>88700000.0</td>\n",
       "      <td>[3.23, 9.18, 10.64, 11.58, 12.52, 13.57, 15.76...</td>\n",
       "      <td>[194.0, 172.0, 170.0, 170.0, 171.0, 172.0, 174...</td>\n",
       "      <td>[0.65, 0.72, 0.79, 0.87, 0.96, 1.05, 1.16, 1.2...</td>\n",
       "      <td>[0.27403592109072017, 0.30354748182356694, 0.3...</td>\n",
       "      <td>[14.441, 14.473, 14.51, 14.56, 14.624, 14.692,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>187</td>\n",
       "      <td>NGC4278</td>\n",
       "      <td>1.63</td>\n",
       "      <td>81.542678</td>\n",
       "      <td>0.012944</td>\n",
       "      <td>4884.61</td>\n",
       "      <td>82.612</td>\n",
       "      <td>15400000.0</td>\n",
       "      <td>[0.85, 11.2]</td>\n",
       "      <td>[364.0, 256.0]</td>\n",
       "      <td>[0.65, 0.72, 0.79, 0.87, 0.96, 1.05, 1.16, 1.2...</td>\n",
       "      <td>[0.04836252076642912, 0.05357079223358301, 0.0...</td>\n",
       "      <td>[12.659, 12.674, 12.691, 12.714, 12.743, 12.77...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   index    Galaxy  Reff     LumCalc  LumPercentError    SBeff   L[3.6]  \\\n",
       "0     48   NGC2915  0.53    0.641000         0.000000   347.40    0.641   \n",
       "1     51   NGC2998  7.06  150.902000         0.000000   479.55  150.902   \n",
       "2     56   NGC3741  0.32    0.028000         0.000001    42.94    0.028   \n",
       "3     72   NGC4138  1.91   44.111000         0.000000  1909.11   44.111   \n",
       "4     97  UGC00191  2.50    2.004000         0.000000    50.21    2.004   \n",
       "5    131  UGC06614  3.68  124.350000         0.000000  1461.61  124.350   \n",
       "6    187   NGC4278  1.63   81.542678         0.012944  4884.61   82.612   \n",
       "\n",
       "         Dist                                             Radius  \\\n",
       "0   4060000.0  [0.34, 0.67, 1.0, 1.34, 1.68, 2.01, 2.34, 2.67...   \n",
       "1  68100000.0  [0.33, 0.99, 1.98, 2.64, 3.63, 7.59, 12.5, 17....   \n",
       "2   3210000.0  [0.23, 0.47, 0.7, 0.93, 1.17, 1.4, 1.64, 1.87,...   \n",
       "3  18000000.0     [2.61, 5.24, 7.85, 10.65, 13.47, 16.03, 18.58]   \n",
       "4  17100000.0  [0.62, 0.87, 1.12, 1.37, 1.62, 2.3, 4.97, 7.45...   \n",
       "5  88700000.0  [3.23, 9.18, 10.64, 11.58, 12.52, 13.57, 15.76...   \n",
       "6  15400000.0                                       [0.85, 11.2]   \n",
       "\n",
       "                                            Velocity  \\\n",
       "0  [13.5, 31.3, 35.3, 50.5, 61.0, 66.5, 74.4, 83....   \n",
       "1  [90.0, 125.0, 148.0, 180.0, 201.0, 206.0, 214....   \n",
       "2  [13.1, 17.3, 23.6, 26.2, 27.4, 26.9, 27.4, 31....   \n",
       "3  [179.0, 195.0, 181.0, 162.0, 145.0, 147.0, 150.0]   \n",
       "4  [29.9, 34.4, 46.3, 49.8, 57.6, 71.3, 76.65, 81...   \n",
       "5  [194.0, 172.0, 170.0, 170.0, 171.0, 172.0, 174...   \n",
       "6                                     [364.0, 256.0]   \n",
       "\n",
       "                                 Original Radius (1)  \\\n",
       "0  [0.65, 0.72, 0.79, 0.87, 0.96, 1.05, 1.16, 1.2...   \n",
       "1  [0.65, 0.72, 0.79, 0.87, 0.96, 1.05, 1.16, 1.2...   \n",
       "2  [0.65, 0.72, 0.79, 0.87, 0.96, 1.05, 1.16, 1.2...   \n",
       "3  [0.65, 0.72, 0.79, 0.87, 0.96, 1.05, 1.16, 1.2...   \n",
       "4  [0.65, 0.72, 0.79, 0.87, 0.96, 1.05, 1.16, 1.2...   \n",
       "5  [0.65, 0.72, 0.79, 0.87, 0.96, 1.05, 1.16, 1.2...   \n",
       "6  [0.65, 0.72, 0.79, 0.87, 0.96, 1.05, 1.16, 1.2...   \n",
       "\n",
       "                                             Radius2  \\\n",
       "0  [0.012782663458497988, 0.014159257984797769, 0...   \n",
       "1  [0.21135938576561064, 0.23412116577113792, 0.2...   \n",
       "2  [0.01010841899028594, 0.011197017958470579, 0....   \n",
       "3  [0.0564947186677653, 0.06257876529352463, 0.06...   \n",
       "4  [0.05368081051021463, 0.05946182087285312, 0.0...   \n",
       "5  [0.27403592109072017, 0.30354748182356694, 0.3...   \n",
       "6  [0.04836252076642912, 0.05357079223358301, 0.0...   \n",
       "\n",
       "                                                  SB  \n",
       "0  [16.455, 16.469, 16.484, 16.5, 16.518, 16.542,...  \n",
       "1  [15.762, 15.776, 15.79, 15.808, 15.831, 15.86,...  \n",
       "2  [18.985, 19.01, 19.028, 19.054, 19.079, 19.101...  \n",
       "3  [12.968, 12.987, 13.01, 13.043, 13.079, 13.126...  \n",
       "4  [18.884, 18.903, 18.904, 18.905, 18.906, 18.90...  \n",
       "5  [14.441, 14.473, 14.51, 14.56, 14.624, 14.692,...  \n",
       "6  [12.659, 12.674, 12.691, 12.714, 12.743, 12.77...  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Convert radii from arcseconds to parsecs\n",
    "\n",
    "driver = webdriver.Chrome()\n",
    "driver.get(\"http://arcsec2parsec.joseonorbe.com/index.html\")\n",
    "\n",
    "driver.find_element(By.NAME, \"ASunits\").send_keys(\"arcsec\")\n",
    "driver.find_element(By.NAME, \"Dunits\").send_keys(\"pc\")\n",
    "\n",
    "def convertarcsectopc(r, dis):\n",
    "    angsize = driver.find_element(By.NAME, \"txtAngsize\")\n",
    "    angsize.clear()\n",
    "    angsize.send_keys(r)\n",
    "\n",
    "    distance = driver.find_element(By.NAME, \"txtDistance\")\n",
    "    distance.clear()\n",
    "    distance.send_keys(dis)\n",
    "\n",
    "    # br[\"ASunits\"] = [\"arcsec\"]\n",
    "    # br[\"Dunits\"] = [\"pc\"]\n",
    "    # br[\"LSunits\"] = [\"kpc\"]\n",
    "\n",
    "    driver.find_element(By.ID, \"btn-convert\").click()\n",
    "\n",
    "    return driver.find_element(By.NAME, \"txtLinsize\").get_attribute(\"value\")\n",
    "\n",
    "# append the data as two new columns to the dataframe in a column called radius and vrot for each galaxy (for the row with NGC3741 there should be a list under radius and velocity)\n",
    "r = []\n",
    "r2 = []\n",
    "mu = []\n",
    "for galaxy in galaxies:\n",
    "    new_df = sfb[sfb[\"galaxy\"] == galaxy]\n",
    "    rad2 = list(new_df[\"radius\"])\n",
    "    for i in range(len(rad2)):\n",
    "        rad2[i] = convertarcsectopc(rad2[i], list(df3[df3[\"Galaxy\"] == galaxy][\"Dist\"])[0])\n",
    "    r.append(list(map(float, list(new_df[\"radius\"]))))\n",
    "    r2.append(list(map(float, rad2)))\n",
    "    mu.append(list(map(float, list(new_df[\"mu\"]))))\n",
    "    print(list(new_df[\"radius\"]))\n",
    "driver.quit()\n",
    "origrad = pd.Series(r, name=\"Original Radius (1)\")\n",
    "rad = pd.Series(r2, name=\"Radius2\")\n",
    "sb2 = pd.Series(mu, name=\"SB\")\n",
    "df3 = pd.concat([df3, origrad, rad, sb2], axis=1)\n",
    "df3 = df3.head(7)\n",
    "df3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.65, 0.72, 0.79, 0.87, 0.96, 1.05, 1.16, 1.27, 1.4, 1.54, 1.69, 1.86, 2.05, 2.25, 2.48, 2.73, 3.0, 3.3, 3.63, 3.99, 4.39, 4.83, 5.31, 5.85, 6.43, 7.07, 7.78, 8.56, 9.42, 10.36, 11.39, 12.53, 13.78, 15.16, 16.68, 18.35, 20.18, 22.2, 24.42, 26.86, 29.55, 32.5, 35.75, 39.33, 43.26, 47.59, 52.35, 57.58, 63.34, 69.68, 76.64, 84.31, 92.74, 102.01, 112.21, 123.43, 135.78, 149.36, 164.29]\n",
      "[0.012782663458497988, 0.014159257984797769, 0.015535852511097552, 0.017109103398297305, 0.018879010646397028, 0.020648917894496747, 0.02281213786439641, 0.024975357834296066, 0.027531890525995664, 0.03028507957859523, 0.033234924992094766, 0.036578083127394245, 0.04031455398449365, 0.04424768120249303, 0.048770777503192315, 0.05368718652569155, 0.05899690826999071, 0.06489659909698978, 0.07138625900668874, 0.07846588799908764, 0.08633214243508638, 0.09498502231468506, 0.10442452763788354, 0.11504397112648188, 0.12645004005868007, 0.1390360471562781, 0.1529986487801759, 0.16833784493037351, 0.18525029196777082, 0.2037359898923679, 0.22399159506506472, 0.24641042020766116, 0.27099246532015736, 0.29813104312435307, 0.3280228099811483, 0.3608644222514433, 0.39685253629613754, 0.43657712119793124, 0.48023483331772443, 0.5282189853773168, 0.5811195464594084, 0.6391331729248994, 0.7030464902173893, 0.7734494674195781, 0.850735417253266, 0.9358876215229526, 1.0294960493113376, 1.1323473260620216, 1.2456213899404038, 1.3703015227509845, 1.5071743499373627, 1.658009778747639, 1.8237910909863129, 2.006091537540584, 2.2066810256585523, 2.4273294625883177, 2.6702000682997795, 2.937259406401938, 3.230867353225591]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Graph converted radii\n",
    "print(df3[\"Original Radius (1)\"][0])\n",
    "print(df3[\"Radius2\"][0])\n",
    "for i in range(len(galaxies)):\n",
    "    plt.plot(df3[\"Original Radius (1)\"][i], df3[\"Radius2\"][i])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [], [], [], [], [], []]\n",
      "[[14413908.430400183, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [], [], [], [], [], []]\n",
      "[[14413908.430400183, 152685846.95585844, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [], [], [], [], [], []]\n",
      "[[14413908.430400183, 152685846.95585844, 289857615.68687755, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [], [], [], [], [], []]\n",
      "[[14413908.430400183, 152685846.95585844, 289857615.68687755, 794918966.6102092, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [], [], [], [], [], []]\n",
      "[[14413908.430400183, 152685846.95585844, 289857615.68687755, 794918966.6102092, 1454133421.9767945, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [], [], [], [], [], []]\n",
      "[[14413908.430400183, 152685846.95585844, 289857615.68687755, 794918966.6102092, 1454133421.9767945, 2067638702.1421416, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [], [], [], [], [], []]\n",
      "[[14413908.430400183, 152685846.95585844, 289857615.68687755, 794918966.6102092, 1454133421.9767945, 2067638702.1421416, 3012985441.396949, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [], [], [], [], [], []]\n",
      "[[14413908.430400183, 152685846.95585844, 289857615.68687755, 794918966.6102092, 1454133421.9767945, 2067638702.1421416, 3012985441.396949, 4278610482.0892725, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [], [], [], [], [], []]\n",
      "[[14413908.430400183, 152685846.95585844, 289857615.68687755, 794918966.6102092, 1454133421.9767945, 2067638702.1421416, 3012985441.396949, 4278610482.0892725, 5226720602.413726, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [], [], [], [], [], []]\n",
      "[[14413908.430400183, 152685846.95585844, 289857615.68687755, 794918966.6102092, 1454133421.9767945, 2067638702.1421416, 3012985441.396949, 4278610482.0892725, 5226720602.413726, 5446188472.581205, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [], [], [], [], [], []]\n",
      "[[14413908.430400183, 152685846.95585844, 289857615.68687755, 794918966.6102092, 1454133421.9767945, 2067638702.1421416, 3012985441.396949, 4278610482.0892725, 5226720602.413726, 5446188472.581205, 5451159706.662506, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [], [], [], [], [], []]\n",
      "[[14413908.430400183, 152685846.95585844, 289857615.68687755, 794918966.6102092, 1454133421.9767945, 2067638702.1421416, 3012985441.396949, 4278610482.0892725, 5226720602.413726, 5446188472.581205, 5451159706.662506, 6410944709.002964, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [], [], [], [], [], []]\n",
      "[[14413908.430400183, 152685846.95585844, 289857615.68687755, 794918966.6102092, 1454133421.9767945, 2067638702.1421416, 3012985441.396949, 4278610482.0892725, 5226720602.413726, 5446188472.581205, 5451159706.662506, 6410944709.002964, 7055008033.31366, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [], [], [], [], [], []]\n",
      "[[14413908.430400183, 152685846.95585844, 289857615.68687755, 794918966.6102092, 1454133421.9767945, 2067638702.1421416, 3012985441.396949, 4278610482.0892725, 5226720602.413726, 5446188472.581205, 5451159706.662506, 6410944709.002964, 7055008033.31366, 7037092427.903695, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [], [], [], [], [], []]\n",
      "[[14413908.430400183, 152685846.95585844, 289857615.68687755, 794918966.6102092, 1454133421.9767945, 2067638702.1421416, 3012985441.396949, 4278610482.0892725, 5226720602.413726, 5446188472.581205, 5451159706.662506, 6410944709.002964, 7055008033.31366, 7037092427.903695, 7529568911.984431, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [], [], [], [], [], []]\n",
      "[[14413908.430400183, 152685846.95585844, 289857615.68687755, 794918966.6102092, 1454133421.9767945, 2067638702.1421416, 3012985441.396949, 4278610482.0892725, 5226720602.413726, 5446188472.581205, 5451159706.662506, 6410944709.002964, 7055008033.31366, 7037092427.903695, 7529568911.984431, 8388327943.192808, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [], [], [], [], [], []]\n",
      "[[14413908.430400183, 152685846.95585844, 289857615.68687755, 794918966.6102092, 1454133421.9767945, 2067638702.1421416, 3012985441.396949, 4278610482.0892725, 5226720602.413726, 5446188472.581205, 5451159706.662506, 6410944709.002964, 7055008033.31366, 7037092427.903695, 7529568911.984431, 8388327943.192808, 8986736221.51217, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [], [], [], [], [], []]\n",
      "[[14413908.430400183, 152685846.95585844, 289857615.68687755, 794918966.6102092, 1454133421.9767945, 2067638702.1421416, 3012985441.396949, 4278610482.0892725, 5226720602.413726, 5446188472.581205, 5451159706.662506, 6410944709.002964, 7055008033.31366, 7037092427.903695, 7529568911.984431, 8388327943.192808, 8986736221.51217, 9180147518.231834, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [], [], [], [], [], []]\n",
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      "[[14413908.430400183, 152685846.95585844, 289857615.68687755, 794918966.6102092, 1454133421.9767945, 2067638702.1421416, 3012985441.396949, 4278610482.0892725, 5226720602.413726, 5446188472.581205, 5451159706.662506, 6410944709.002964, 7055008033.31366, 7037092427.903695, 7529568911.984431, 8388327943.192808, 8986736221.51217, 9180147518.231834, 9233080093.437445, 10311224254.117287, 10372634133.521475, 10282921585.964184, 11434563443.919067, 12406979579.968687, 13155410301.546059, 13607622794.937372, 15069188852.949091, 16157761690.96447, 16417427280.175901, 17474358140.688328], [621776442.0956943, 3598243299.164898, 10088437916.788212, 19896846147.062218, 34114109926.93699, 74922372497.00941, 133159717275.60051, 182746241986.09595, 237030516841.127, 292312211363.39825, 341087546941.4614, 393643734558.0603, 405286706625.57117], [9181332.847904857, 32720909.665830735, 90689571.65459505, 148498079.10524377, 204325369.08016583, 235650247.57606116, 286404790.84741193, 418023116.6468048, 515966281.56509984, 590227044.8486164, 796442004.8648376, 985581490.4011042, 1306017806.3306208, 1581975985.3255877, 1956736953.1976094, 2369113930.350059, 2812431159.2318473, 3262407257.909507, 3558208805.160014, 3818462278.9962482, 4335435684.872497], [19452788904.190437, 46348513978.30496, 59822162907.987946, 65015205790.76978, 65877772312.93857, 80575590426.50623, 97244160725.06734], [128934568.40207349, 239481209.2596236, 558489881.8162563, 790341082.3095242, 1250245459.713582, 2719832759.487526, 6792286743.200798, 11370030120.686264, 16321947622.365288], [28277517958.969234, 63173491408.14209, 71527784825.53596, 77846968823.28067, 85159255177.84096, 93383908323.36473, 110991575054.10191, 216095822764.33432, 230247282452.2882, 328548011858.3243, 349669429610.98645, 463167505764.4632, 625260399953.8693], [0, 0]]\n",
      "[[14413908.430400183, 152685846.95585844, 289857615.68687755, 794918966.6102092, 1454133421.9767945, 2067638702.1421416, 3012985441.396949, 4278610482.0892725, 5226720602.413726, 5446188472.581205, 5451159706.662506, 6410944709.002964, 7055008033.31366, 7037092427.903695, 7529568911.984431, 8388327943.192808, 8986736221.51217, 9180147518.231834, 9233080093.437445, 10311224254.117287, 10372634133.521475, 10282921585.964184, 11434563443.919067, 12406979579.968687, 13155410301.546059, 13607622794.937372, 15069188852.949091, 16157761690.96447, 16417427280.175901, 17474358140.688328], [621776442.0956943, 3598243299.164898, 10088437916.788212, 19896846147.062218, 34114109926.93699, 74922372497.00941, 133159717275.60051, 182746241986.09595, 237030516841.127, 292312211363.39825, 341087546941.4614, 393643734558.0603, 405286706625.57117], [9181332.847904857, 32720909.665830735, 90689571.65459505, 148498079.10524377, 204325369.08016583, 235650247.57606116, 286404790.84741193, 418023116.6468048, 515966281.56509984, 590227044.8486164, 796442004.8648376, 985581490.4011042, 1306017806.3306208, 1581975985.3255877, 1956736953.1976094, 2369113930.350059, 2812431159.2318473, 3262407257.909507, 3558208805.160014, 3818462278.9962482, 4335435684.872497], [19452788904.190437, 46348513978.30496, 59822162907.987946, 65015205790.76978, 65877772312.93857, 80575590426.50623, 97244160725.06734], [128934568.40207349, 239481209.2596236, 558489881.8162563, 790341082.3095242, 1250245459.713582, 2719832759.487526, 6792286743.200798, 11370030120.686264, 16321947622.365288], [28277517958.969234, 63173491408.14209, 71527784825.53596, 77846968823.28067, 85159255177.84096, 93383908323.36473, 110991575054.10191, 216095822764.33432, 230247282452.2882, 328548011858.3243, 349669429610.98645, 463167505764.4632, 625260399953.8693], [26197328002.665333, 0]]\n"
     ]
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>Galaxy</th>\n",
       "      <th>Reff</th>\n",
       "      <th>LumCalc</th>\n",
       "      <th>LumPercentError</th>\n",
       "      <th>SBeff</th>\n",
       "      <th>L[3.6]</th>\n",
       "      <th>Dist</th>\n",
       "      <th>Radius</th>\n",
       "      <th>Velocity</th>\n",
       "      <th>Original Radius (1)</th>\n",
       "      <th>Radius2</th>\n",
       "      <th>SB</th>\n",
       "      <th>MaxRadius</th>\n",
       "      <th>Mass</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>48</td>\n",
       "      <td>NGC2915</td>\n",
       "      <td>0.53</td>\n",
       "      <td>0.641000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>347.40</td>\n",
       "      <td>0.641</td>\n",
       "      <td>4060000.0</td>\n",
       "      <td>[0.34, 0.67, 1.0, 1.34, 1.68, 2.01, 2.34, 2.67...</td>\n",
       "      <td>[13.5, 31.3, 35.3, 50.5, 61.0, 66.5, 74.4, 83....</td>\n",
       "      <td>[0.65, 0.72, 0.79, 0.87, 0.96, 1.05, 1.16, 1.2...</td>\n",
       "      <td>[0.012782663458497988, 0.014159257984797769, 0...</td>\n",
       "      <td>[16.455, 16.469, 16.484, 16.5, 16.518, 16.542,...</td>\n",
       "      <td>10.04</td>\n",
       "      <td>[14413908.430400183, 152685846.95585844, 28985...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>51</td>\n",
       "      <td>NGC2998</td>\n",
       "      <td>7.06</td>\n",
       "      <td>150.902000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>479.55</td>\n",
       "      <td>150.902</td>\n",
       "      <td>68100000.0</td>\n",
       "      <td>[0.33, 0.99, 1.98, 2.64, 3.63, 7.59, 12.5, 17....</td>\n",
       "      <td>[90.0, 125.0, 148.0, 180.0, 201.0, 206.0, 214....</td>\n",
       "      <td>[0.65, 0.72, 0.79, 0.87, 0.96, 1.05, 1.16, 1.2...</td>\n",
       "      <td>[0.21135938576561064, 0.23412116577113792, 0.2...</td>\n",
       "      <td>[15.762, 15.776, 15.79, 15.808, 15.831, 15.86,...</td>\n",
       "      <td>42.28</td>\n",
       "      <td>[621776442.0956943, 3598243299.164898, 1008843...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>56</td>\n",
       "      <td>NGC3741</td>\n",
       "      <td>0.32</td>\n",
       "      <td>0.028000</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>42.94</td>\n",
       "      <td>0.028</td>\n",
       "      <td>3210000.0</td>\n",
       "      <td>[0.23, 0.47, 0.7, 0.93, 1.17, 1.4, 1.64, 1.87,...</td>\n",
       "      <td>[13.1, 17.3, 23.6, 26.2, 27.4, 26.9, 27.4, 31....</td>\n",
       "      <td>[0.65, 0.72, 0.79, 0.87, 0.96, 1.05, 1.16, 1.2...</td>\n",
       "      <td>[0.01010841899028594, 0.011197017958470579, 0....</td>\n",
       "      <td>[18.985, 19.01, 19.028, 19.054, 19.079, 19.101...</td>\n",
       "      <td>7.00</td>\n",
       "      <td>[9181332.847904857, 32720909.665830735, 906895...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>72</td>\n",
       "      <td>NGC4138</td>\n",
       "      <td>1.91</td>\n",
       "      <td>44.111000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1909.11</td>\n",
       "      <td>44.111</td>\n",
       "      <td>18000000.0</td>\n",
       "      <td>[2.61, 5.24, 7.85, 10.65, 13.47, 16.03, 18.58]</td>\n",
       "      <td>[179.0, 195.0, 181.0, 162.0, 145.0, 147.0, 150.0]</td>\n",
       "      <td>[0.65, 0.72, 0.79, 0.87, 0.96, 1.05, 1.16, 1.2...</td>\n",
       "      <td>[0.0564947186677653, 0.06257876529352463, 0.06...</td>\n",
       "      <td>[12.968, 12.987, 13.01, 13.043, 13.079, 13.126...</td>\n",
       "      <td>18.58</td>\n",
       "      <td>[19452788904.190437, 46348513978.30496, 598221...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>97</td>\n",
       "      <td>UGC00191</td>\n",
       "      <td>2.50</td>\n",
       "      <td>2.004000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>50.21</td>\n",
       "      <td>2.004</td>\n",
       "      <td>17100000.0</td>\n",
       "      <td>[0.62, 0.87, 1.12, 1.37, 1.62, 2.3, 4.97, 7.45...</td>\n",
       "      <td>[29.9, 34.4, 46.3, 49.8, 57.6, 71.3, 76.65, 81...</td>\n",
       "      <td>[0.65, 0.72, 0.79, 0.87, 0.96, 1.05, 1.16, 1.2...</td>\n",
       "      <td>[0.05368081051021463, 0.05946182087285312, 0.0...</td>\n",
       "      <td>[18.884, 18.903, 18.904, 18.905, 18.906, 18.90...</td>\n",
       "      <td>9.98</td>\n",
       "      <td>[128934568.40207349, 239481209.2596236, 558489...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>131</td>\n",
       "      <td>UGC06614</td>\n",
       "      <td>3.68</td>\n",
       "      <td>124.350000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1461.61</td>\n",
       "      <td>124.350</td>\n",
       "      <td>88700000.0</td>\n",
       "      <td>[3.23, 9.18, 10.64, 11.58, 12.52, 13.57, 15.76...</td>\n",
       "      <td>[194.0, 172.0, 170.0, 170.0, 171.0, 172.0, 174...</td>\n",
       "      <td>[0.65, 0.72, 0.79, 0.87, 0.96, 1.05, 1.16, 1.2...</td>\n",
       "      <td>[0.27403592109072017, 0.30354748182356694, 0.3...</td>\n",
       "      <td>[14.441, 14.473, 14.51, 14.56, 14.624, 14.692,...</td>\n",
       "      <td>64.59</td>\n",
       "      <td>[28277517958.969234, 63173491408.14209, 715277...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>187</td>\n",
       "      <td>NGC4278</td>\n",
       "      <td>1.63</td>\n",
       "      <td>81.542678</td>\n",
       "      <td>0.012944</td>\n",
       "      <td>4884.61</td>\n",
       "      <td>82.612</td>\n",
       "      <td>15400000.0</td>\n",
       "      <td>[0.85, 11.2]</td>\n",
       "      <td>[364.0, 256.0]</td>\n",
       "      <td>[0.65, 0.72, 0.79, 0.87, 0.96, 1.05, 1.16, 1.2...</td>\n",
       "      <td>[0.04836252076642912, 0.05357079223358301, 0.0...</td>\n",
       "      <td>[12.659, 12.674, 12.691, 12.714, 12.743, 12.77...</td>\n",
       "      <td>11.20</td>\n",
       "      <td>[26197328002.665333, 170739206203.83627]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   index    Galaxy  Reff     LumCalc  LumPercentError    SBeff   L[3.6]  \\\n",
       "0     48   NGC2915  0.53    0.641000         0.000000   347.40    0.641   \n",
       "1     51   NGC2998  7.06  150.902000         0.000000   479.55  150.902   \n",
       "2     56   NGC3741  0.32    0.028000         0.000001    42.94    0.028   \n",
       "3     72   NGC4138  1.91   44.111000         0.000000  1909.11   44.111   \n",
       "4     97  UGC00191  2.50    2.004000         0.000000    50.21    2.004   \n",
       "5    131  UGC06614  3.68  124.350000         0.000000  1461.61  124.350   \n",
       "6    187   NGC4278  1.63   81.542678         0.012944  4884.61   82.612   \n",
       "\n",
       "         Dist                                             Radius  \\\n",
       "0   4060000.0  [0.34, 0.67, 1.0, 1.34, 1.68, 2.01, 2.34, 2.67...   \n",
       "1  68100000.0  [0.33, 0.99, 1.98, 2.64, 3.63, 7.59, 12.5, 17....   \n",
       "2   3210000.0  [0.23, 0.47, 0.7, 0.93, 1.17, 1.4, 1.64, 1.87,...   \n",
       "3  18000000.0     [2.61, 5.24, 7.85, 10.65, 13.47, 16.03, 18.58]   \n",
       "4  17100000.0  [0.62, 0.87, 1.12, 1.37, 1.62, 2.3, 4.97, 7.45...   \n",
       "5  88700000.0  [3.23, 9.18, 10.64, 11.58, 12.52, 13.57, 15.76...   \n",
       "6  15400000.0                                       [0.85, 11.2]   \n",
       "\n",
       "                                            Velocity  \\\n",
       "0  [13.5, 31.3, 35.3, 50.5, 61.0, 66.5, 74.4, 83....   \n",
       "1  [90.0, 125.0, 148.0, 180.0, 201.0, 206.0, 214....   \n",
       "2  [13.1, 17.3, 23.6, 26.2, 27.4, 26.9, 27.4, 31....   \n",
       "3  [179.0, 195.0, 181.0, 162.0, 145.0, 147.0, 150.0]   \n",
       "4  [29.9, 34.4, 46.3, 49.8, 57.6, 71.3, 76.65, 81...   \n",
       "5  [194.0, 172.0, 170.0, 170.0, 171.0, 172.0, 174...   \n",
       "6                                     [364.0, 256.0]   \n",
       "\n",
       "                                 Original Radius (1)  \\\n",
       "0  [0.65, 0.72, 0.79, 0.87, 0.96, 1.05, 1.16, 1.2...   \n",
       "1  [0.65, 0.72, 0.79, 0.87, 0.96, 1.05, 1.16, 1.2...   \n",
       "2  [0.65, 0.72, 0.79, 0.87, 0.96, 1.05, 1.16, 1.2...   \n",
       "3  [0.65, 0.72, 0.79, 0.87, 0.96, 1.05, 1.16, 1.2...   \n",
       "4  [0.65, 0.72, 0.79, 0.87, 0.96, 1.05, 1.16, 1.2...   \n",
       "5  [0.65, 0.72, 0.79, 0.87, 0.96, 1.05, 1.16, 1.2...   \n",
       "6  [0.65, 0.72, 0.79, 0.87, 0.96, 1.05, 1.16, 1.2...   \n",
       "\n",
       "                                             Radius2  \\\n",
       "0  [0.012782663458497988, 0.014159257984797769, 0...   \n",
       "1  [0.21135938576561064, 0.23412116577113792, 0.2...   \n",
       "2  [0.01010841899028594, 0.011197017958470579, 0....   \n",
       "3  [0.0564947186677653, 0.06257876529352463, 0.06...   \n",
       "4  [0.05368081051021463, 0.05946182087285312, 0.0...   \n",
       "5  [0.27403592109072017, 0.30354748182356694, 0.3...   \n",
       "6  [0.04836252076642912, 0.05357079223358301, 0.0...   \n",
       "\n",
       "                                                  SB  MaxRadius  \\\n",
       "0  [16.455, 16.469, 16.484, 16.5, 16.518, 16.542,...      10.04   \n",
       "1  [15.762, 15.776, 15.79, 15.808, 15.831, 15.86,...      42.28   \n",
       "2  [18.985, 19.01, 19.028, 19.054, 19.079, 19.101...       7.00   \n",
       "3  [12.968, 12.987, 13.01, 13.043, 13.079, 13.126...      18.58   \n",
       "4  [18.884, 18.903, 18.904, 18.905, 18.906, 18.90...       9.98   \n",
       "5  [14.441, 14.473, 14.51, 14.56, 14.624, 14.692,...      64.59   \n",
       "6  [12.659, 12.674, 12.691, 12.714, 12.743, 12.77...      11.20   \n",
       "\n",
       "                                                Mass  \n",
       "0  [14413908.430400183, 152685846.95585844, 28985...  \n",
       "1  [621776442.0956943, 3598243299.164898, 1008843...  \n",
       "2  [9181332.847904857, 32720909.665830735, 906895...  \n",
       "3  [19452788904.190437, 46348513978.30496, 598221...  \n",
       "4  [128934568.40207349, 239481209.2596236, 558489...  \n",
       "5  [28277517958.969234, 63173491408.14209, 715277...  \n",
       "6           [26197328002.665333, 170739206203.83627]  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate the mass of the galaxy at each radius\n",
    "G = 6.67 * 10 ** -11\n",
    "mass = [[]] * 7\n",
    "prev_masses = [0] * 7\n",
    "r = df3[\"Radius\"].tolist()\n",
    "v = df3[\"Velocity\"].tolist()\n",
    "max_radius = [max(r[i]) for i in range(len(r))]\n",
    "df3[\"MaxRadius\"] = max_radius\n",
    "# do mass calculations for each galaxy\n",
    "for i in range(len(galaxies)):\n",
    "    mass[i] = [0] * len(r[i])\n",
    "    for j in range(len(r[i])):\n",
    "        print(mass)\n",
    "        mass[i][j] = ((r[i][j] * 3.086e+19) * (v[i][j] * 10 ** 3) ** 2 / G) / (1.989e+30)\n",
    "df3[\"Mass\"] = mass\n",
    "df3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Rotation Curves\n",
    "for i in range(len(galaxies)):\n",
    "    vel = [df3[\"Velocity\"].tolist()[i][j] ** 2 for j in range(len(df3[\"Velocity\"].tolist()[i]))]\n",
    "    plt.plot(r[i], vel, label=galaxy_legend[i])\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot mass vs radius for each galaxy\n",
    "for i in range(len(galaxies)):\n",
    "    plt.plot(df3[\"Radius\"].tolist()[i], mass[i], label=galaxy_legend[i])\n",
    "plt.rcParams['text.usetex'] = True\n",
    "plt.xlabel(r\"Radius (kpc)\")\n",
    "plt.ylabel(r\"Mass ($M_{\\odot}$)\")\n",
    "plt.rcParams['text.usetex'] = False\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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SK1q0KHZ2dqxatYqSJUsSEhKimVeUGadPn8bU1FQzj+edk+NrpnLJ8OHDRfny5bWWAWZELrHOpxLihJhmL8QUayEeXUn7vCW1lHPuHs272KRCqaAvsU6+HFcIZcmtiYmJePtXfGJiolixYoWoX7++sLCwECYmJqJcuXJi0KBBwt/fX+vcsLAwMX78eFGxYkVhYmIiSpQoIVq1aiV27NghkpKSNMt6U7sdOnRI006vXr1EsWLFhImJiahRo4bYuHFjitfQvHnzVNsJDAwUQgixfv16UblyZVGkSBFhbW0t6tWrl2Jpc2r27NkjSpUqpbXEO7Ul1sOHD9d6nnqJtXpZtFpSUpJYvHixcHNzE8bGxsLBwUF4eXmJI0eOaM55e4n18uXLBaD1f2v58uXC2dlZWFhYiN69e4sZM2aku8R6//79onLlysLU1FTUqFFDHD58WABix44dQoj0l6APHjxYfP755xm+V/qQE0usVUJkYxZXHouLi8PJyYmvv/6ab775JtPPi4iIwMbGhvDw8DSzXEkPnt6AH+uDiSWMvwdpTfD7qSPcOQgfL4XavfM2RqlQiYmJITAwkLJly2ZqIqhUMAghqF+/PiNHjqR79+56iWHGjBmsWLGCe/fu5fm1nz17phniKlu2bJ5fPyPp/dxl9vM73w4nJbdz507CwsJS3eUxudjYWGJjYzXfR0RE5HJkUrY8fT1G7eCedgIDb+bFyBVKkiRlg0qlYtWqVVy5ciXPrvnjjz9St25d7OzsOHHiBPPmzePLL7/Ms+snFxQUxI8//pgvE5icUiCSmLVr1/LBBx9kuN5/1qxZfPfdd3kUlZRtT18v/yxRJf3zir3+wQuVK5QkScqeWrVqpVqPKbfcunWL6dOnExoaSpkyZRg1ahQTJkzIs+snV6dOnUxt9leQ5fskJjg4mAMHDrB9+/YMz50wYQJff/215vuIiAjNrHEpH1H3xBTPIImRPTGSJBUwixYtYtGiRfoOo9DI90mMj48PxYsX58MPP8zwXFNT0yyt15f0RJPEVE7/vKKve2LkXjGSJElSKvLtPjGg1PDw8fGhT58+adbqkAqYuKg3w0PFq6Z/btHXlWejX0B0WK6GJUmSJBU8+TqJOXDgACEhIfTv31/foUg55b8bgIAi9mCZwQ6SplZg8focOaQkSZIkvSVfd2+0adMmW3U8pHxMPak3o6EktaKu8Oo/JYlxqpVLQUmSJEkFUb7uiZHeQer5MCUyGEpSk/NiJEmSpDTIJEbKW5md1KsmVyhJkiRJaZBJjJS3NMNJGSyvVpN7xUiSpIO1a9fSpk2bbD+/b9++GdZeatGiBSNGjEj3HFdXVxYvXqz5XqVSsXPnzmzHlVMy8/oyY/369Vr1sFasWEH79u11bjcjMomR8k5UKLx8pNx3cM/cc2RPjCSlq2/fvqhUKmbPnq11fOfOnSkqYgshWL16NQ0bNsTa2hpLS0uqVq3K8OHDuX37tta5ERERTJw4EXd3d8zMzHB0dKRVq1Zs374dIQTx8fGMGzeO6tWrY2FhgZOTE717905R+drX15fWrVtja2uLnZ0dgwcPJjIyUuucgwcP0qhRI6ysrHB0dGTcuHGaStlq+/bto0GDBlhZWeHg4MBnn31GUFBQuu9NTEwMkyZNYsqUKZpjU6dORaVS0bZt2xTnz5s3D5VKRYsWLTTHlixZoinimN/s2LGDBg0aYGNjg5WVFVWrVs0wmXpbbr2+/v374+vry7Fjx3K87eRkEiPlHXUvjE0ZMMtkLSv1nJjw+5AYnztxSVIBZ2Zmxpw5c3jx4kWa5wgh6NGjB8OGDaNdu3b8888/+Pv7s3btWszMzJg+fbrm3LCwMBo1asTGjRuZMGECvr6+HD16lK5duzJ27FjCw8OJiorC19eXSZMm4evry/bt2wkICODjjz/WtPPw4UNatWpFhQoVOHPmDH///TfXrl3TKiFz6dIl2rVrR9u2bbl48SJbt25l9+7dWpWaAwMD6dChA++//z5+fn7s27ePZ8+e0bFjx3Tfl99++w1ra2saN26sdbxkyZIcOnSI+/fvax1ft24dZcqU0TpmY2Oj1cOQXxw8eJCuXbvy2WefcfbsWS5cuMCMGTOIj8/a78mMXl9cXFy24jMxMaFHjx4pqqnnuBwvS5mPyCrW+cyZVUpV6p87Z/45iYlCfF9ced7zO7kXm1SoFfQq1h999JFwd3cXY8aM0RzfsWOHVhXrzZs3C0Ds2rUr1XaSkpI094cOHSosLCzEgwcPUpz38uVLER8fn2obZ8+eFYAIDg4WQgixcuVKUbx4ca0q0pcvXxaAuHXrlhBCiAkTJog6depotbN7925hZmYmIiIihBBCbNu2TRgZGWm1s3v3bqFSqURcXFzqb4wQ4sMPPxSjR4/WOjZlyhRRs2ZN8dFHH4np06drjp84cULY29uLoUOHiubNm2uOv11ROjIyUvTq1UtYWFgIR0dHMX/+/BSVsJ88eSI++ugjYWZmJlxdXcXPP/8sXFxcxKJFizTnkKwKtRBChISEiM6dOwsbGxtRtGhR8fHHH2uqeKdm+PDhokWLFmk+nvy1rlixQpQuXVqYm5uLzp07i7CwsDRfX/PmzcUXX3whhg8fLuzs7DTXWLBggahWrZooUqSIKF26tBg6dKh4+fKl5nk+Pj7CxsZG6/pHjhwRJiYmIioqKtX4cqKKteyJkfJOZmsmJWdg8GZISc6LkfKSEBD3Ku9v2dhWwtDQkJkzZ7J06dIUvQtqmzdvxs3NTaunJDn10FNSUhJbtmzB29s71Xp1lpaWaW4+Gh4ejkql0vxlHxsbi4mJCQbJCr2am5sDcPz4cc05b1cwNjc3JyYmhgsXLgDg6emJgYEBPj4+JCYmEh4ezk8//USrVq0wNjZO623h+PHjadYO6t+/v9Ywyrp16/D29sbExCTN9gDGjBnDkSNH2LVrF//88w+HDx/G19dX65y+ffty7949Dh06xG+//caPP/7I06dP02wzPj4eLy8vrKysOHbsGCdOnMDS0pK2bdum2RPi6OjItWvXuHr1arrx3r59m19//ZU//viDv//+m4sXL/J///d/6T5nw4YNmJiYcOLECVasWAGAgYEBP/zwA9euXWPDhg38+++/jB07Nt126tSpQ0JCAmfOnEn3PF3k631ipHdMZmsmva2oq7JJnpwXI+Wl+CiYmX7R2VzxzUMwscjy0z799FNq1arFlClTWLt2bYrHb968iZubm9axESNGsGbNGgBsbW25f/8+z54948WLF7i7Z3Le2msxMTGMGzeO7t27Y22tDBe///77fP3118ybN4/hw4fz6tUrzTDRo0fK/DgvLy8WL17M5s2b6dKlC48fP2batGla55QtW5Z//vmHLl268Pnnn5OYmEjDhg3Zs2dPmvGEhYURHh6eZuHgjz76iCFDhnD06FE8PT359ddfOX78OOvWrUuzzcjISNauXcvPP/9My5YtAeUDv3Tp0ppzbt68yd69ezl79ix169YFlMnFlSunvSJz69atJCUlsWbNGk0y6ePjg62tLYcPH051YvJXX33FsWPHqF69Oi4uLjRo0IA2bdrg7e2tVX4nJiaGjRs3UqpUKQCWLl3Khx9+yIIFC3B0dEw1nooVKzJ37lytY8nn2ri6ujJ9+nSGDBnCjz/+mObrKlKkCDY2NgQHB6d5jq5ypCcmPj6ee/fuERAQQGhoaE40Kb1rhMj68mo1uVeMJGXKnDlz2LBhA9evX8/U+RMnTsTPz4/JkydrJtuKbPQExcfH06VLF4QQLF++XHO8atWqbNiwgQULFlCkSBEcHR0pW7YsJUqU0PTOtGnThnnz5jFkyBBMTU2pVKkS7dq1A9Cc8/jxYwYNGkSfPn04d+4cR44cwcTEhE6dOqUZb3R0NECKXh41Y2NjevbsiY+PD9u2baNSpUrUqFEj3dd5584d4uLiqF+/vuZYsWLFtJLD69evY2RkhKenp+aYu7t7uvNOLl26xO3bt7GyssLS0hJLS0uKFStGTEwMd+7cSfU5FhYW/PXXX9y+fZtvv/0WS0tLRo0aRb169YiKitKcV6ZMGU0CA9CwYUOSkpIICAhIM57ksasdOHCAli1bUqpUKaysrOjVqxfPnz/XulZqzM3NMzxHF9nuiXn58iU///wzW7Zs4ezZs8TFxSGEQKVSUbp0adq0acPgwYM1mahUyL18BDHhoDIE+0pZe65coSTpg3ERpVdEH9fNpmbNmuHl5cWECRO0Js+C8tf12x9cDg4OODg4ULx4ca1jtra23LhxI1PXVCcwwcHB/Pvvv5peGLUePXrQo0cPnjx5goWFBSqVioULF1KuXDnNOV9//TUjR47k0aNHFC1alKCgICZMmKA553//+x82NjZavQM///wzzs7OnDlzhgYNGqSIy87ODpVKle5k5/79+1O/fn2uXr2q1/I2kZGReHp6smnTphSPOTikX56lfPnylC9fnoEDBzJx4kQqVarE1q1b6devX7bjsbDQ7gkMCgrio48+YujQocyYMYNixYpx/PhxBgwYQFxcHEWKpP1/NjQ0NMPXoIts9cQsXLgQV1dXfHx8aNWqFTt37sTPz4+bN29y6tQppkyZQkJCAm3atKFt27bcunUrp+OWCponr3th7CqAURYrjav3ipFJjJSXVCplWCevb28ti86q2bNn88cff3Dq1Cmt4927dycgIIBdu3al+3wDAwO6devGpk2bUiyXBuUDV738WZ3A3Lp1iwMHDmBnZ5dmuyVKlMDS0pKtW7diZmZG69attR5XqVQ4OTlhbm7O5s2bcXZ2pnbt2gBERUVpzasBZR4QKHN4UmNiYkKVKlXw9/dPM6aqVatStWpVrl69So8ePdI8T618+fIYGxtrzfF48eIFN2/e1Hzv7u5OQkKCZj4PQEBAAGFhYWm2W7t2bW7dukXx4sWpUKGC1s3GxibDuNRcXV0pUqQIr1690hwLCQnR+nc8ffo0BgYGKYYW03PhwgWSkpJYsGABDRo0oFKlSqn+33jbnTt3iImJwcPDI9PXyqps9cScO3eOo0ePUrVq6lvH16tXj/79+7NixQp8fHw4duwYFStW1ClQqYDL7lASJJvYG6QMS+n4S16S3mXVq1fH29s7xdLWbt26sX37drp168aECRPw8vKiRIkSBAcHs3XrVk1SADBjxgwOHz5M/fr1mTFjBnXq1MHY2Jhjx44xa9Yszp07h4WFBZ06dcLX15c///yTxMREHj9+DChDLOoJssuWLaNRo0ZYWlqyf/9+xowZw+zZs7WGV+bNm0fbtm0xMDBg+/btzJ49m19//VUT04cffsiiRYuYNm0a3bt35+XLl3zzzTe4uLik+wHp5eXF8ePH09075d9//yU+Pj5Ty6gtLS0ZMGAAY8aMwc7OjuLFizNx4kStBMvNzY22bdvy+eefs3z5coyMjBgxYoRmQnNqvL29mTdvHh06dGDatGmULl2a4OBgtm/fztixY7Xm3KhNnTqVqKgo2rVrh4uLC2FhYfzwww/Ex8drJYhmZmb06dOH+fPnExERwbBhw+jSpUua82FSU6FCBeLj41m6dCnt27fXmvCbnmPHjlGuXDnKly+f6WtlVbZ6YjZv3pxmApOcqakpQ4YMkVWopWQrkzJZMyk5Wxfla9xLZcM8SZLSNW3atBQ9FCqViq1bt7J48WL27NlDy5YtcXNzo3///jg7O2tWC4GShJw+fZqePXsyffp0PDw8aNq0KZs3b2bevHnY2Njw4MEDdu/ezf3796lVqxYlS5bU3E6ePKlp6+zZs7Ru3Zrq1auzatUqVq5cybBhw7Ri27t3L02bNqVOnTr89ddf7Nq1S2sX2ffff59ffvmFnTt34uHhQdu2bTE1NeXvv/9ONzkYMGAAe/bsITw8PM1zLCwssrQPzLx582jatCnt27enVatWNGnSJMUcEh8fH5ycnGjevDkdO3Zk8ODBWkN2bytSpAhHjx6lTJkydOzYkcqVKzNgwABiYmJSDM+pNW/enLt379K7d2/c3d354IMPePz4Mf/8849WL0uFChXo2LEj7dq1o02bNtSoUSPdybipqVmzJgsXLmTOnDlUq1aNTZs2MWvWrAyft3nzZgYNGpSla2WVSmRnFlcBERERgY2NDeHh4Wn+R5DyyMpm8OgSdP0ZKmdjK+oFleHlQxh4EEqnvmRSkrIrJiaGwMBAypYtm+ZEUKlg6ty5M7Vr12bChAn6DiXPTZ06VTPdI69du3aN999/n5s3b6Y5JJbez11mP7+z3BMTHR3NgwcPUg1YklKVlAj/vZ5QmNXl1WpyXowkSdkwb948LC0t9R1GofPo0SM2btyYpTk92ZGlJOa3336jYsWKfPjhh9SoUUNrclOvXr1yPDjpHfEiCBJiwMj8zfyWrJIb3kmSlA2urq589dVX+g6j0GnVqhVeXl65fp0sJTHTp0/nwoUL+Pn54ePjw4ABA/jll1+A7O0tIBUST1730jm4gYFh+uempajsiZEkScqKqVOn6mUoKS9laXVSfHw8JUqUAJTNcI4ePcqnn37K7du3U1RLlSQN9aTe7A4lQbK9YmRPjCRJkqTIUk9M8eLFuXz5sub7YsWKsX//fq5fv651XJK06LK8Wk3OiZEkSZLekqUk5qeffkqxTMzExITNmzdz5MiRHA1Meodkp/Dj29Q9MREPIT5G55AkSZKkgi9Lw0mpbbhz8uRJrK2tady4cY4FJb1DEmLh+W3lvi7DSUXswMRK2SsmLAQcsli6QJIkSXrn6FwA8osvvki1zPadO3d4+fKlrs1LBd2zmyASwcwGrEpmvx2VSs6LkSRJkrTonMQEBATQokWLFMcPHDhA9+7ddW1eKug0k3qr6l4uoJir8lXOi5EkSZLIgSTG2to61SqhTZs25fTp07o2LxV06uXVukzqVZN7xUiSlEW9evVi5syZ+g4jS1q0aJFuvafMWrFiBe3bZ2OH9AJE5ySmbdu2zJ8/P2XDBgbExcXp2rxU0Gl6YnIiiZErlCTpbX379kWlUjF79myt4zt37kyx9YUQgtWrV9OwYUOsra2xtLSkatWqDB8+nNu3b2udGxERwcSJE3F3d8fMzAxHR0datWrF9u3bNfuCTZ06FXd3dywsLChatCitWrXSml5w+PBhVCpVqrdz586leC23b9/GysoqRS2ja9eu8dlnn+Hq6opKpWLx4sWZem8uXbrEnj17tGo15VSCUBD0798fX19fjh07pu9Qco3OScz333/PkSNH+Oyzz7hy5Qqg1EOYM2cONWrU0DlAqYDTpfDj2+ScGElKlZmZGXPmzEm1V1xNCEGPHj0YNmwY7dq1459//sHf35+1a9diZmbG9OnTNeeGhYXRqFEjNm7cyIQJE/D19eXo0aN07dqVsWPHagoqVqpUiWXLlnHlyhWOHz+Oq6srbdq04b///gOgUaNGPHr0SOs2cOBAypYtS5062jXQ4uPj6d69O02bNk0Re1RUFOXKlWP27NlZqr68dOlSOnfunKWyA6n98Z2YmJiioGZ+JoQgISEBExMTevTokaKi+TtF5ICgoCDxwQcfCJVKJczMzISRkZGws7MTJ0+ezInmsy08PFwAIjw8XK9xFFrR4UJMsVZur57r3t7zO0pb3xcXIilJ9/Yk6bXo6Gjh7+8voqOj9R1KlvXp00d89NFHwt3dXYwZM0ZzfMeOHSL5r/jNmzcLQOzatSvVdpKS/UwNHTpUWFhYiAcPHqQ47+XLlyI+Pj7VNtS/cw8cOJDq43FxccLBwUFMmzYtxWNjx44VPXv2FD4+PsLGxibV5wshhIuLi1i0aFGaj6slJCQIGxsb8eeff2odb968uRg+fLhWe9OmTRO9evUSVlZWok+fPpoYdu3aJSpXriwMDQ1FYGCgiImJEaNGjRJOTk6iSJEiol69euLQoUNa7a9atUqULl1amJubi08++UQsWLBA6/X06dNHdOjQQes5w4cPF82bN08zxo0bNwpPT09haWkpSpQoIbp37y6ePHmiefzQoUMCEHv27BG1a9cWxsbGmriOHDkiTExMRFRUVIbvWV5L7+cus5/fOvfEALi4uLBnzx4CAwPZunUru3fv5ubNmzRs2DAnmpeyIyoUfu4EV3/XXwz/3VC+WpWEIsV0b8/GGVSGSh2ml491b0+S0iGEICo+Ks9vIhslXAwNDZk5cyZLly7l/v37qZ6zefNm3Nzc+Pjjj1N9XD30lJSUxJYtW/D29sbJySnFeZaWlhgZpdydIy4ujlWrVmFjY0PNmjVTvcbu3bt5/vw5/fr10zr+77//sm3bNv73v/+l+zqz4vLly4SHh6fo8UnN/PnzqVmzJhcvXmTSpEmA0vszZ84c1qxZw7Vr1yhevDhffvklp06dYsuWLVy+fJnOnTvTtm1bbt26BcCJEycYMmQIw4cPx8/Pj9atWzNjxgydX0t8fDzff/89ly5dYufOnQQFBdG3b98U540fP57Zs2dz/fp1zUhInTp1SEhISHUV8bsgS/vEZMTFxQUXF5ecbFLKrlv74fZ+iI2Aap/pJwbNTr067A+TnKEx2JSGsGBlXoy1Dku2JSkD0QnR1P+lfp5f90yPMxQxLpLl53366afUqlWLKVOmsHbt2hSP37x5Ezc3N61jI0aMYM2aNQDY2tpy//59nj17xosXL3B3d8/Udf/880+6detGVFQUJUuWZP/+/djb26d67tq1a/Hy8tLac+z58+f07duXn3/+GWtr68y+3AwFBwdjaGiYYoPW1Lz//vuMGjVK8/2xY8eIj4/nxx9/1CRkISEh+Pj4EBISoknuRo8ezd9//42Pj48mifzggw8YPXo0oAy3nTx5kj///FOn19K/f3/N/XLlyvHDDz9Qt25dIiMjtYbKpk2bRuvWrbWeW6RIEWxsbAgODtYphvxK556Y8PBwBg8eTIUKFahcuTKPHj3KibgkXUU8UL7GROgvhic5UG7gbXJejCSlac6cOWzYsIHr169n6vyJEyfi5+fH5MmTiYyMBLJezPe9997Dz8+PkydP0rZtW7p06cLTp09TnHf//n327dvHgAEDtI4PGjSIHj160KxZsyxdNyPR0dGYmppmqq5far01JiYmWvM6r1y5QmJiIpUqVcLS0lJzO3LkCHfu3AGULUfq1aun1c7b32fHhQsXaN++PWXKlMHKyormzZsDSmKV0esAMDc3JyoqSuc48iOde2K++OIL7ty5w9y5c+nZsyfR0dEAjBw5kvLly/Pll1/qHKSUDS9fJ5OxekxicronBpQaSoFH5AolKdeZG5lzpkfed8GbG5ln+7nNmjXDy8uLCRMmpBhuqFixIgEBAVrHHBwccHBw0OqtcHBwwNbWlhs3bmTqmhYWFlSoUIEKFSrQoEEDKlasyNq1a5kwYYLWeT4+PtjZ2aUYzvr333/ZvXu3ZpWrEIKkpCSMjIxYtWqVVi9EVtjb2xMVFUVcXBwmJiYZvoa3mZubayVAkZGRGBoacuHCBQwNDbXOzcrEYQMDgxSJYnx8fJrnv3r1Ci8vL7y8vNi0aRMODg6EhITg5eWVYhJyaq8DIDQ0FAcHh0zHWJDonMTs3buXAwcO4OHhofUP6+XlxaRJk2QSoy+aJEaPuybnRM2kt8m9YqQ8olKpsjWso2+zZ8+mVq1aKYaOunfvTo8ePdi1axcdOnRI8/kGBgZ069aNn376iSlTpqSYFxMZGYmZmVmq82JAmVMTGxurdUwIgY+PD71798bY2FjrsVOnTpGYmKj5fteuXcyZM4eTJ09SqlSpTL3m1NSqVQsAf39/zX1deHh4kJiYyNOnT1NdQQXg5uaWYun42987ODhw9epVrWN+fn4p3he1Gzdu8Pz5c2bPno2zszMA58+fz3Tcd+7cISYmBg8Pj0w/pyDReThJCIGVlVWK4xUrVtRMdpL0ICJZEqOPpYGRTyHqGaACe7cMT880uVeMJKWrevXqeHt7p1hW261bNzp16kS3bt2YNm0aZ86cISgoiCNHjrB161atP0JnzJiBs7Mz9evXZ+PGjfj7+3Pr1i3WrVuHh4cHkZGRvHr1im+++YbTp08THBzMhQsX6N+/Pw8ePKBz585a1/73338JDAxk4MCBKeKtXLky1apV09xKlSqFgYEB1apVo2jRooAyadjPzw8/Pz/i4uJ48OABfn5+Kfa2Sc7BwYHatWtz/PhxXd5OjUqVKuHt7U3v3r3Zvn07gYGBnD17llmzZvHXX38B8NVXX7Fnzx4WLlzIrVu3WLlyJXv37tXq0Xn//fc5f/48Gzdu5NatW0yZMiVFUpNcmTJlMDExYenSpdy9e5fdu3fz/fffZzruY8eOUa5cOcqXL5/9F5+P6ZzEfPDBB2zatCnF8VevXmVqLFLKJZrVOwLiIvP++o8uKV/tyoNJDv41K+fESFKGpk2blmJfE5VKxdatW1m8eDF79uyhZcuWuLm50b9/f5ydnbU+7IsVK8bp06fp2bMn06dPx8PDg6ZNm7J582bmzZuHjY0NhoaG3Lhxg88++4xKlSrRvn17nj9/zrFjx6haVXtfqLVr19KoUaNMTxZ+28OHD/Hw8MDDw4NHjx4xf/58PDw8Uk2Kkhs4cGCqn0/Zpe5NGjVqFG5ubnzyySecO3eOMmXKANC4cWNWrFjBwoULqVmzJn///TcjR47EzMxM04Z6lGLs2LHUrVuXly9f0rt37zSv6eDgwPr169m2bRtVqlRh9uzZqW4wm5bNmzczaNCg7L/ofE4lsrOeL5mQkBDq1KnDF198wbx587hy5QolS5akV69ehIaGcvDgwZyKNcsiIiKwsbEhPDw8R2e953tJSTDdAZISlO9H+oNN9rtls+Xg93BsPtTsAZ8uz7l2Y8JhtvILgwkPwDTzY9GSlJaYmBgCAwMpW7as1geOVLBFR0fj5ubG1q1b9bblx6BBg7hx44Zeds29du0a77//Pjdv3sTGxibPr5+R9H7uMvv5rfOcmDJlynDy5Em++OILoqKiqFevHi9fvsTa2po9e/bo2ryUHa/+e5PAwOvJvXmcxNx7PSGyTA4vUTWzAfOiEP1CWWqdEzsBS5L0TjI3N2fjxo08e/Ysz645f/58WrdujYWFBXv37mXDhg38+OOPeXb95B49esTGjRvzZQKTU3Jkn5gKFSqwb98+QkJCuHTpEsbGxtSvX18znpldDx48YNy4cezdu5eoqCgqVKiAj49PpjYvKtRevrXMPa8n9ybGw/3XE8+cG+R8+0XLKklMaKBMYiRJSleLFi3y9Hpnz55l7ty5vHz5UrOnS0bDXrmlVatWerluXtI5ienfvz/NmjWjb9++lClTBiEE/v7+GBjoNt3mxYsXNG7cmPfee4+9e/fi4ODArVu3dE6MCoW3k5i83ivm8WVIiFZ6Tewr5Xz7RV3hoa+c3CtJUr7z66+/6juEQkXnJGbPnj0MHjwYUIqGeXp68vLlS+zt7fn3339TLPPLrDlz5uDs7IyPj4/mWNmyZXUNt3CIeKj9fV7vFRPyeijJuT7omMymqph6hZKc3CtJklSY5ciOveq1/L///juOjo5ERETQtWvXFJsdZcXu3bupU6cOnTt3pnjx4nh4eLB69Wpdwy0c3q4rlNdJzL1kSUxu0KxQCsqd9iVJkqQCQeckxtnZmcBA5S/ibdu20bdvX0xNTRkyZAgnTpzIdrt3795l+fLlVKxYkX379jF06FCGDRvGhg0b0nxObGwsERERWrdC6eXbPTF5OCdGiGSTenNhPgy82StGbngnSZJUqOk8nNS3b1+GDRtG+/btOXjwIMuWLQOUXRvVtTiyIykpiTp16jBz5kxA2S3x6tWrrFixgj59+qT6nFmzZvHdd99l+5rvDPVGd8ZFID4qb5OYsBBlTo6BETjVzp1rqHtiwkIgKREMDNM9XZIkSXo36dwTM2HCBDp37szRo0eZPXs2FSpUANDaACg7SpYsSZUq2tvVV65cOUXBq7djCQ8P19zu3buX7esXaOrhJPuKyte8nNir7oUpWTNnN7lLztoJDE0gKf5NoUtJkiSp0NG5J+bUqVN06NCBiRMnah1//PgxPXr0yHa7jRs3TlGs7ObNm7i4uKT5HFNTU0xNTbN9zXeGejjJ3k3ZOTcve2JCTitfc2NptZqBIdiWgee3lXkxttlPliVJkqSCS+eemC+++IIzZ1JWev30008ZMWJEttsdOXIkp0+fZubMmdy+fZtffvmFVatW8cUXX+gQbSEQH63soQLg8HplWGx43l1fM6lX9/Lz6ZLzYiRJyoRJkyZpVtDq09SpU3OkEKXa4cOHUalUhIWF6dROXFwcrq6uWSoqmZ/onMQEBASkupnQwYMH6d69e7bbrVu3Ljt27GDz5s1Uq1aN77//nsWLF+Pt7a1DtIWAeijJyBxslIqnedYTExMBT64p93NrUq+aXKEkSYAyL1GlUjF79myt4zt37kxRv04IwerVq2nYsCHW1tZYWlpStWpVhg8fnqKYYkREBBMnTsTd3R0zMzMcHR1p1aoV27dvJ7VqNUOGDEGlUrF48WKt4zNmzKBRo0YUKVIEW1vbFM97/vw5bdu2xcnJCVNTU5ydnfnyyy9TLMzYtGkTNWvWpEiRIpQsWZL+/fvz/PnzdN+bx48fs2TJEq2Rgr59+/LJJ5+k+zxdqVQqdu7cqXVs9OjRei3DkxYTExNGjx7NuHHj9B1KtuicxFhbW/PixYsUx5s2bcrp06d1avujjz7iypUrxMTEcP369Xe6iFWOUW90Z+UIZq/rTeTVnJj75wABti7K9XOT3CtGkjTMzMyYM2dOqr+L1YQQ9OjRg2HDhtGuXTv++ecf/P39Wbt2LWZmZkyfPl1zblhYGI0aNWLjxo1MmDABX19fjh49SteuXRk7dizh4dq9uzt27OD06dM4OTmluG5cXBydO3dm6NChqcZlYGBAhw4d2L17Nzdv3mT9+vUcOHCAIUOGaM45ceIEvXv3ZsCAAVy7do1t27Zx9uzZDD8T1qxZQ6NGjdKdhpBXLC0tsbOz03cYWuLi4gDw9vbm+PHjXLt2Tc8RZZ3OSUzbtm1TrahpYGCgeYOkPKTe6M7aCUxfJzF51ROT20urkyuoPTFCwI2/4PkdfUcivUNatWqFo6Mjs2bNSvOcrVu3smXLFrZu3cqkSZNo0KABZcqUoUGDBsyZM0drY9FvvvmGoKAgzpw5Q58+fahSpQqVKlVi0KBB+Pn5YWn5pvDqgwcP+Oqrr9i0aRPGxsYprvvdd98xcuRIqlevnmpcRYsWZejQodSpUwcXFxdatmzJ//3f/2kVTDx16hSurq4MGzaMsmXL0qRJEz7//HPOnj2b7vuyZcsW2rdvn+45b7t69SoffPABlpaWlChRgl69emnVXmrRogXDhg1j7NixFCtWDEdHR6ZOnap53NXVFVCmVKhUKs33qQ0nrVu3jqpVq2JqakrJkiX58ssvAQgKCkKlUuHn56c5NywsDJVKxeHDh1ON+/nz53Tv3p1SpUpRpEgRqlevzubNm7XOadGiBV9++SUjRozA3t4eLy8vQPk3aNy4MVu2bMnSe5Uf6JzEfP/99xw5coTPPvuMK1euAEplyjlz5lCjRg2dA5SySD2cZOUIplbK/bza7E4zqTeXNrlLrqDOiTm3Brb0gK299B2JlAEhBElRUXl+S22oJiOGhobMnDmTpUuXcv/+/VTP2bx5M25ubnz88cepPq4eekpKSmLLli14e3un2rNiaWmJkZGR5txevXoxZswYqlbNmTpmDx8+ZPv27TRv3lxzrGHDhty7d489e/YghODJkyf89ttvtGvXLs12QkND8ff3z1KtvbCwMN5//308PDw4f/48f//9N0+ePKFLly5a523YsAELCwvOnDnD3LlzmTZtGvv37weUlbkAPj4+PHr0SPP925YvX84XX3zB4MGDuXLlCrt379as7s2OmJgYPD09+euvv7h69SqDBw+mV69eKRK9DRs2YGJiwokTJ1ixYoXmeL169fRSaVtXOq9OcnZ25syZMwwZMoSaNWtiampKQkICNjY2/PHHHzkRo5QVmuGkkm+Gk/KiJyYx4U3RxzzpiXndPRwTpkxkNi8ANbWe3YJ/Jin3n16DsHtg66zfmKQ0iehoAmp75vl13XwvoCqS9e0JPv30U2rVqsWUKVNYu3Ztisdv3ryZogzMiBEjWLNmDQC2trbcv3+fZ8+e8eLFC9zd3TO85pw5czAyMmLYsGFZjvdt3bt3Z9euXURHR9O+fXtNXKCsVt20aRNdu3YlJiaGhIQE2rdvz//+97802wsJCUEIkWoilpZly5bh4eGh2Z8MlN4SZ2dnbt68SaVKSi24GjVqMGXKFAAqVqzIsmXLOHjwIK1bt8bBwQFQ3k9Hx7SH1adPn86oUaMYPny45ljdunUzHevbSpUqxejRozXff/XVV+zbt49ff/2VevXeLLSoWLEic+fOTfF8JycngoODs319fdGpJyYxMZGdO3dStGhR9uzZQ1BQEFu3btWMbTZs2DCn4pQyK7XhpPgoJcnITU+uQvwr5ZoOGf/y05mJBViWUO4XhCGlxHjYPlgpjKl295D+4pHeSXPmzGHDhg1cv349U+dPnDgRPz8/Jk+erNmcNLM9QRcuXGDJkiWsX78+xQTi7Fi0aBG+vr7s2rWLO3fu8PXXX2se8/f3Z/jw4UyePJkLFy7w999/ExQUpDVv5m3R0crPmpmZWaZjuHTpEocOHcLS0lJzUydzd+68GQJ+e5ShZMmSPH36NNPXefr0KQ8fPqRly5aZfk5GEhMT+f7776levTrFihXD0tKSffv2pdhbzdMz9cTc3NycqKioHIsnr+jUE2NoaEj37t25du0aVlZWlClTRqcN7qQckNpwEihDSkWK5d51773usixdN+920C1eGSKfwLUd4OSRN9fMrmMLlMrbZjZQ+WO4+BPcOQS1e+s7MikNKnNz3Hwv6OW62dWsWTO8vLyYMGECffv21XqsYsWKKfbecnBwwMHBgeLFi2sds7W15caNG+le69ixYzx9+lTrd35iYiKjRo1i8eLFBAUFZSl2R0dHHB0dcXd3p1ixYjRt2pRJkyZRsmRJZs2aRePGjRkzZgygJBEWFhY0bdqU6dOnU7JkyRTt2dvbA/DixQtN70hGIiMjad++PXPmzEnxWPJrvD33R6VSkZSUlOnXap7Bv7HB68K5yRPK+Pj4dJ8zb948lixZwuLFi6levToWFhaMGDEixdxUCwuLVJ8fGhqa6fcpP9F5TkzdunU1tZOkfEC90Z2VExgaK0utIfeHlO69ng+TF0NJag3+T/l6djW8epb+ufp0/wIced19++FC8Oip3L97GLLwi0/KWyqVCoMiRfL8pmuvxuzZs/njjz84deqU1vHu3bsTEBDArl270n2+gYEB3bp1Y9OmTTx8+DDF45GRkSQkJNCrVy8uX76Mn5+f5ubk5MSYMWPYt2+fTq9BnRDExsYCEBUVpflgVzM0VP5YSqvnqHz58lhbW+Pv75/p69auXZtr167h6upKhQoVtG5pffinxtjYmMTExDQft7KywtXVNc0l1+pk4tGjR5pjySf5pubEiRN06NCBnj17UrNmTcqVK8fNmzczHfPVq1fx8MjnfwymQuck5quvvuKbb74pvFv85ydCvKmbZP36r4a8mtwbksuVq1NTsY3SAxMfBSeX5t11syIuCnYMBpEI1T6D6p2glCeYWEF0KDy+pO8IpXdM9erV8fb25ocfftA63q1bNzp16kS3bt2YNm0aZ86cISgoiCNHjrB161ZNUgDK3i7Ozs7Ur1+fjRs34u/vz61bt1i3bh0eHh5ERkZiZ2dHtWrVtG7GxsY4Ojpqzb0JCQnBz8+PkJAQEhMTNQmPevhqz549+Pj4cPXqVYKCgvjrr78YMmQIjRs31qzsad++Pdu3b2f58uXcvXuXEydOMGzYMOrVq5fmnBcDAwNatWrF8ePHUzwWHh6ulXz5+flx7949vvjiC0JDQ+nevTvnzp3jzp077Nu3j379+qWblLxNnaA8fvw4zWXvU6dOZcGCBfzwww/cunULX19fli5Vfo+Zm5vToEEDZs+ezfXr1zly5AjffvttutesWLEi+/fv5+TJk1y/fp3PP/+cJ0+eZDrmY8eO0aZNm0yfn1/onMR07dqVc+fOUbVqVXr27MmaNWu4cOGCXF6tD9EvIFH5ywXL1xPK8mJyb/h9iLgPKkMonfmVADpTqaD56w2azq6GV+lvfKUX+ycr5RGsSkK711sRGBpD2WbK/Tv/6i826Z01bdq0FMMbKpWKrVu3snjxYvbs2UPLli1xc3Ojf//+ODs7a33YFytWjNOnT9OzZ0+mT5+Oh4cHTZs2ZfPmzcybNw8bG5tMxzJ58mQ8PDyYMmUKkZGReHh4aFb/gPKBvXr1apo0aULlypUZOXIkH3/8MX/++aemjb59+7Jw4UKWLVtGtWrV6Ny5M25ubmzfvj3daw8cOJAtW7akeC8OHz6siUN9++6773BycuLEiRMkJibSpk0bqlevzogRI7C1tU3RE5SeBQsWsH//fpydndPs3ejTpw+LFy/mxx9/pGrVqnz00UfcunVL8/i6detISEjA09OTESNGaO3jk5pvv/2W2rVr4+XlRYsWLXB0dMz0pn6nTp0iPDycTp06Zfo15hcqkZ31fMkEBwdz6dIl/Pz8NF+DgoIwMjLCzc2Ny5cv51SsWRYREYGNjQ3h4eFYW1vrLY488+QaLG8E5sVg3OshvlUt4OFF6L4V3NrmznWv/Aa/D4CSteDzI7lzjbQIAauaKzWimoyEVlPz9vrpuX0Afv5Mud9zO1RINonv7GrYMxpcm0LfP1N/vpRnYmJiCAwMpGzZslmaCCrlb0II6tevz8iRI3XaQf5d17VrV2rWrMk333yTp9dN7+cus5/fOi+xdnFxwcXFRWvvgZcvX+Ln56fXBKZQUi+vtk7WvZoXG97l5SZ3b1OpoPl42NJdSQwaDcvdCcyZFRUKO1/X+ao3WDuBASj/vvI15DTEvVJWW0mSlKNUKhWrVq3S7GEmpRQXF0f16tUZOXKkvkPJFp2Hk1JjZWVF06ZNZbHGvBaRrOSAmmZOTC4WgdRscpfLRR/T4vYBONaAuEg4tUw/Mbztr1EQ+RjsKkKr71I+Xqwc2JSBpHgIPpn38UlSIVGrVi169ZKbS6bFxMSEb7/9NsMVU/mVzklMYmIiK1eu5Ouvv2bhwoUcPHgww6JcUi5JvtGdmtnrsevc6omJjVT2iAFw1kNPDCi9MS3GK/fPrFR6QfTpym9wbbsyR6jjSjBJZeMylQrKv6fcl/NiJEmSsiVHVidNnjyZJ0+eMH78eNq1a0fx4sUpU6ZMmttbS7kk1eGk1z0xuVUE8sF5EElKxWybUrlzjcxwaweO1V/3xqS9i2euC38Af73epKv5WGUlUlo0SYzc9E6SJCk7dE5itm/fzsaNG9m0aROmpqacP3+eJUuWEBMTky8qhxYq6Q4n5VJPjD6WVqcm+UolffXGJCXBzqEQE64kL01HpX9+2eaACv67/manZUmSJCnTdE5iIiMjqVKlCqBs8GNkZMSXX37JhAkT5Cz/vJZ8ozu13J7Yq49N7tLi9iGUqA5xL+H0j3l//bOrIPCIssHgp6uUpdTpKVLszU7Ddw/neniSJEnvGp2TmHLlyml2dSxVqhQPHjwAlM2Jfv75Z12bl7IieckBtdzc7C7uVf7piQEwMFCGcEDpjYlOfZOpXPFfABxQCsLR5nuwz2Q1WvUqJTkvRpIkKct0TmI6duzI3r17AWjevDnr1q0DlIJd6gJcUh5IjIfI1wXIks+Jyc3N7q7/qRR9LFpWmY+SH7h/BMWrKknb6eV5c01NcccYKN8S6g7M/HPV82JkCQJJkqQs0zmJmTp1KlOnTgVg7NixHDx4EAcHBzp37kyPHj10bV7KrJePAAEGRlDE/s1x9XBSTC4ssb68Rflas5syJyU/MDCAFq/nxpxenje9MUfmwiM/MLOFDv/L2ntRuh4YW8Cr/96s8pIkKc/ExcVRoUIFTp4sWFsdqFQqdu7cqXM73bp1Y8GCBboHpCfZTmLUJdGTK1OmDNeuXWPu3Lls27aN//1Pj6tECptnr7erLlZO+SBXy605MRGP3szjqNElZ9vWlXt7KF7ldW/Mity91r1zSoVqgI8WvalZlVlGJuDaRLl/V65SkrKuRYsWjBgxIsXx9evXY2trq3UsIiKCSZMmUbVqVczNzbGzs6Nu3brMnTs3RY2f27dv069fP0qXLo2pqSlly5ale/fumnIBoFQ+9vb2xtraGltbWwYMGKCpiaR2+fJlmjZtipmZGc7OzsydO1fr8WvXrvHZZ5/h6uqKSqVi8eLFKV7Ly5cvGTFiBC4uLpibm9OoUSPOnTundc727dtp06YNdnZ2qFSqDAsmqq1YsYKyZcvSqFEjzbGcShAKgm+//ZYZM2YQHp6Le4nlomwnMffv3+eDDz6gdOnSDB06lL179xIXF4e9vT39+vXj448/1rkaq5QF/wUoXx3ctI/n1pyYK9uUpdXO9ZXEKT9JPjfm9HKIDsud68S9gh2fK8Udq3eGah2z146cFyPlgdDQUBo0aICPjw+jR4/mzJkz+Pr6MmPGDC5evMgvv/yiOff8+fN4enpy8+ZNVq5cib+/Pzt27MDd3Z1Ro96suvP29ubatWvs37+fP//8k6NHjzJ48GDN4xEREbRp0wYXFxcuXLjAvHnzmDp1KqtWrdKcExUVRbly5Zg9ezaOjsnm8yUzcOBA9u/fz08//cSVK1do06YNrVq10szBBHj16hVNmjRhzpw5mX5PhBAsW7aMAQMGZPo5APHx8SmOFbR6gep4q1WrRvny5QvuHFahg8TERHH06FExZswYUalSJWFlZSU6duwoNmzYIJ4/f65L0zkiPDxcACI8PFzfoeS+3cOEmGItxIFp2sfD7inHp9nn7PV+bKS0e25tzrabUxIThVhWX4nx0KzcucbB6Ur7CyoLERWa/Xae3nj9b+QgRFxUzsUnZVp0dLTw9/cX0dHR+g4ly5o3by6GDx+e4riPj4+wsbHRfP/5558LCwsL8eDBg1TbSUpK0nytWrWq8PT0FImJiSnOe/HihRBCCH9/fwGIc+fOaR7bu3evUKlUmmv8+OOPomjRoiI2NlZzzrhx44Sbm1uqMbi4uIhFixZpHYuKihKGhobizz//1Dpeu3ZtMXHixBRtBAYGCkBcvHgx1Wskd+7cOWFgYCAiIiK0jgNix44dWu1t2bJFNGvWTJiamgofHx/Rp08f0aFDBzF9+nRRsmRJ4erqKoQQIiQkRHTu3FnY2NiIokWLio8//lgEBgZq2o6PjxdfffWVsLGxEcWKFRNjx44VvXv3Fh06dEj3fahZs6aYMmVKqjEKIcTYsWNFxYoVhbm5uShbtqz49ttvRVxcnObxKVOmiJo1a4rVq1cLV1dXoVKpNI999913okmTJhm+XzktvZ+7zH5+6zQnxsDAgKZNmzJ37lwCAgI4c+YM9evXZ+XKlTg5OdGsWTPmz5+vlS1LueS/m8rXtHpiEuMgPiZnrvX4ijJ/w9AEqn6aM23mNK3emB9zfk5Q+AM4uVS57zUTzItmvy37SmBdSqlALksQSLkgKSmJrVu30rNnT5ycnFI9R91z7ufnx7Vr1xg1alSqlZvVQ1SnTp3C1taWOnXeVK5v1aoVBgYGnDlzRnNOs2bNMDEx0Zzj5eVFQEBAiuGrtCQkJJCYmJhiyw5zc3OtytvZcezYMSpVqoSVlVWG544fP57hw4dz/fp1vLy8ADh48CABAQGanqj4+Hi8vLywsrLi2LFjnDhxAktLS9q2bavp+ZgzZw6bNm3Cx8eHEydOEBERkSNDV1ZWVqxfvx5/f3+WLFnC6tWrWbRokdY5t2/f5vfff2f79u1aw2316tXj7NmzxMbG6hxHXsvR2kmVK1dm7NixnDhxgnv37tGnTx+OHTvG5s2bc/IyUmr+u6F8ta+kfdzE8s39nJoXc+n1hN5KXrp9eOe2Kp+Ag7uSwJxZmbNt/zsdEqKVUgtVOujWlkoF5dSrlOS8mPxCCEF8bGKe34QQOf5a/vvvP8LCwnBz0/4jx9PTE0tLSywtLTVVnm/dUubXubu7p9vm48ePKV68uNYxIyMjihUrxuPHjzXnlChRQusc9ffqczJiZWVFw4YN+f7773n48CGJiYn8/PPPnDp1ikePHmWqjbQEBwenmdS9bcSIEXTs2JGyZctSsqQy983CwoI1a9ZQtWpVqlatytatW0lKSmLNmjVUr16dypUr4+PjQ0hICIcPHwZg6dKlTJgwgU8//RR3d3eWLVuWYu5Sdnz77bc0atQIV1dX2rdvz+jRo/n111+1zomLi2Pjxo14eHhQo0YNzXEnJyfi4uIy/W+Sn+hcxdrf3x93d/cUGbuDgwMDBgzI8lijlA2vnkF0KKBKmcQYGIKJlbIBXGwEWDrodq2kRKU2EEDNfF7aXt0b81t/pTBk3YE5U+H60SW49Dox95qRMyuzyr8Hfj/LEgT5SEJcEquGH8nz6w5e0hxjU8M8udaOHTuIi4tj3Lhxmi0xciOJ0tVPP/1E//79KVWqFIaGhtSuXZvu3bunWFySVdHR0ZnelDV5j5Na9erVtXqZLl26xO3bt1P07MTExHDnzh3Cw8N58uQJ9eq9KZZraGiIp6cnSTpusbB161Z++OEH7ty5Q2RkJAkJCVhbW2ud4+LigoNDys8AdfHHqKgonWLQB52TmGrVqmFmZkaVKlWoWbOm1i0nskspE9STem2dUy82aJosidHV3cNKdWbzYlChte7t5bYqn0CJhcrw14Gp8PEPurUnBOybCAio9hmUTvmLLVvKtVC+PrkKL5+AVYl0T5ckNWtr61RXloSFhWFjoxSAdXBwwNbWloCAAK1zypQpAyi9HWFhYQBUqqT8IXTjxg08PDzSvK6joyNPnz7VOpaQkEBoaKhmgq6joyNPnjzROkf9fVqTeFNTvnx5jhw5wqtXr4iIiKBkyZJ07dqVcuV0W1Rgb2/PlStXMnWuhYVFhsciIyPx9PRk06ZNKc5NLXlIi4GBQYpkMrXJxGqnTp3C29ub7777Di8vL2xsbNiyZUuKpdOpvQZQJn1nNcb8Quck5siRI3Tu3JlSpUrx8uVLVq9ezbVr11CpVFSoUIEuXbowatQomdDkpmevfzHZu6X+uJm1UpIgJ4aT1ENJ1Toqy4PzOwNDaDcffNqC70bw6AXOdbPf3s2/IegYGJpCyyk5F6eFPZSsqfTy3D0MNbvmXNtSthiZGDB4SXO9XDcr3Nzc+Oeff1Ic9/X11SQkBgYGdOnShZ9//pnJkyenO4RSq1YtqlSpwoIFC+jatWuKXvawsDBsbW1p2LAhYWFhXLhwAU9PpdDpv//+S1JSEvXrKzt4N2zYkIkTJxIfH4+xsVKGY//+/bi5uVG0aNaHoi0sLLCwsODFixfs27cvxXLtrPLw8GD58uUIIXJkNW3t2rXZunUrxYsXT9ELolaiRAnOnTtHs2bNAEhMTMTX15datWppznFwcNAaKouIiCAwMDDN6548eRIXFxcmTpyoORYcHJzpuK9evUrp0qWxt7fP+OR8Ruc5McOHD2f58uXs2rWLX3/9lStXrrB//37Kli1Lz549OXr0KB4eHvz33385Ea+UmrSWV6vlVCXr2Ei48adyP78PJSXn0hBqeQNCqTCdlJi9dhLj4Z9Jyv0GQ6BoDhc4lfNi8hWVSoWxqWGe37L6YTp06FBu3rzJsGHDuHz5MgEBASxcuJDNmzdrLYeeOXMmpUqVol69eqxbt47Lly9z584dduzYwalTpzA0NNS8bh8fH27evEnTpk3Zs2cPd+/e5fLly8yYMYMOHZQ5YJUrV6Zt27YMGjSIs2fPcuLECb788ku6deumSZJ69OiBiYkJAwYM4Nq1a2zdupUlS5bw9ddfa+KKi4vDz88PPz8/4uLiePDgAX5+fty+fVtzzr59+/j7778JDAxk//79vPfee7i7u9OvXz/NOaGhofj5+eHv7w9AQEAAfn5+6c7zeO+994iMjOTatWtZes/T4u3tjb29PR06dODYsWMEBgZy+PBhhg0bxv379wH46quvmDVrFrt27SIgIIDhw4fz4sULrX/3999/n59++oljx45x5coV+vTpo/n3SU3FihUJCQlhy5Yt3Llzhx9++IEdO3ZkOu5jx47Rpk2b7L9wfdJ1iZS5ubkICAhIcXz37t3is88+E0lJSaJTp05i4MCBul4qywrNEusNHZQluhc2pP74xk+Vxy/+ott1Lv6itLPEQ4jXyzELjJdPhZjlrMR/emX22jizSnn+nLJCRIflbHxCCHHnsNL+vIoF7/0t4AryEmshhDh79qxo3bq1cHBwEDY2NqJ+/fpay2/VwsLCxIQJE4S7u7swNTUV5ubmokaNGmLSpEkptsUICAgQvXv3Fk5OTsLExES4uLiI7t27C19fX805z58/F927dxeWlpbC2tpa9OvXT7x8+VKrnUuXLokmTZoIU1NTUapUKTF79mytx9VLmN++NW/eXHPO1q1bRbly5YSJiYlwdHQUX3zxhQgL0/4Z9PHxSbWd5MuSU9OlSxcxfvx4rWOkssT67SXb6iXWb3v06JHo3bu3sLe3F6ampqJcuXJi0KBBms+h+Ph48eWXXwpra2tRtGhRMW7cONG5c2fRrVs3TRvh4eGia9euwtraWjg7O4v169dnuMR6zJgxws7OTlhaWoquXbuKRYsWaS2xVy+xflt0dLSwsbERp06dSvd9yg05scRa5ySmSZMmYvLkySmO3717V1hZWQkhhDhz5oxmDX1eKjRJzILKyodf8OnUH9/a+/WH9wrdrrO+vdLO4Tm6taMvZ9co8c8sLUTE46w9NzpMSV6mWCvJTG6IjxHi+xLKNR5fzZ1rSKkq6EmMlH2XLl0SxYsXT5F85ZXExERRqVIl8e233+rl+j/++KNo3bq1Xq6t931iAObPn8/ChQvp1asXN24oy3zj4uJYtGgRxYopK0EcHBxSTO6SckhMBES83ofHoVLq52iKQOownBT+AAKPKvfzW5mBzPLsC04eyvvwz7dZe+6xBRD1HOwqKu3kBiNTcG2s3JerlCQpT9SoUYM5c+akO+ckJwUHB7N69Wpu3rzJlStXGDp0KIGBgXqrNWhsbMzSpUv1cu2coHMSU79+fU6dOsXDhw+pUqUK5ubmWFhYsHr1ambPng3AxYsXM70WX8oidc0ki+Jp79miKQKpQxJzZRsgoEwjKOqa/Xb0ycAQPlwIqODKrxB4LHPPexH8piJ2m+/B0DjXQtTMi5ElCCQpz/Tt25fq1avnybUMDAxYv349devWpXHjxly5coUDBw5QuXLlPLn+2wYOHJhi/6CCROfVSaAssz548CDBwcFcunRJs+5dvYTOwcFBk9BIOexZBpN6IVn9pGyuThLizaqkgr5qplRtqNMfzq+Fv0bBkOMZr7I6+J2y47FrU6jUNnfjU9dRCj6p7LBsnLk9LCRJKhicnZ05ceKEvsN4Z+RIEqPm4uKCi0vKFRtNmzbNyctIyWW0Mgl0r2QddBz+uw5G5sq+KwVdy0ngv0tJAE//CE1GpH3u/fNw9XdAlXMb26WneGWwdFT24rl3+s3+MZIkSVIKOg8nJSYmsnLlSr7++msWLlzIwYMHef78eU7EJmXGs9c1k9LaIwZ0r2R9apnytVYPMLfNXhv5iXlRaDNduX9kDoTdS/08zcZ2KEvKS9bM/dhUKmX3XpDzYiRJkjKgcxLz1VdfMXnyZJ48ecL48eNp164dxYsXp0yZMnz88cc5EaOUHnXNpLQm9UKyib3Z6Il5dkvZ4A0VNPi/rD8/v6rZTZnfEx8F+yakfs713UpviJG50nuTV+S8GEmSpEzROYnZvn07GzduZNOmTZiamnL+/HmWLFlCTExMqkNLUg6Kj4EXQcp9h3SKtemy2d2p/ylf3T4A+wpZf35+pVLBhwtAZQjX/4Cbb+14mhAH+1/vyNvoK7DOw4np6iGkx5eVuliSJElSqnROYiIjI6lSpQqgLNUyMjLiyy+/ZMKECZkurJWaqVOnolKptG4ZVVUtdELvgEgCUxuwTKfWjqlSPyXLPTGvnr8pdNjwy+zFmJ+VqAINhir3946B+Og3j51bDS8Clfe18fC8jcuqBJSopty/ezhvry1JklSA6JzElCtXjocPHwJQqlQpHjxQ9ixp3749P//8s05tV61alUePHmlux48f1zXcd0vyoaT0Jpxq5sSkLBKXrvNrISEGStYCl0bZCjHfazEerJyUHq3ji5VjUaFw5HVNlvcmgqll3scl58VIkiRlSOckpmPHjuzduxeA5s2bs27dOgD8/f01pd2zy8jICEdHR82tIBanylXqPWLSm9QL2nNi3qqMmqb4GDi7Srnf6KvcX5WjL6ZW0Hamcv/4Inh+B47Og5gwKF4VPHrqJ67k82Iy+28mSVKWxcXFUaFCBU6ePJnp56hUKnbu3Jnp8w8fPoxKpdJUCs8Psvoa0tKiRQtGjBih+b5Bgwb8/vvvOrebWTonMVOnTmXq1KkAjB07loMHD+Lg4EDnzp113oHw1q1bODk5Ua5cOby9vQkJCUn3/NjYWCIiIrRu77QIpQcM2zLpn6fuiRFJEPcqc21f2Qav/gPrUlClQ/ZjLAiqfKLsz5IYC9sHwdnVyvE23ysb5OmDSyOlUvbLh29WoElSKt7+EFFbv349tra2WsciIiKYNGkSVatWxdzcHDs7O+rWrcvcuXN58eKF1rm3b9+mX79+lC5dGlNTU8qWLUv37t05f/685pzQ0FC8vb2xtrbG1taWAQMGEBkZqdWOEIL58+dTqVIlTE1NKVWqFDNmzNA6JzY2lokTJ+Li4oKpqSmurq6aP4gBrl27xmeffYarqysqlYrFixen+57Mnj0blUqV6vvythUrVlC2bFkaNWrE+vXrU0xjePsWFBTEo0eP+OCDDzJsOyumTp2qVck6LVFRUUyYMIHy5ctjZmaGg4MDzZs3Z9euXVm6Xm68BoBvv/2W8ePHk5SUlONtpyZH94kpU6YM165dY/fu3djb29O+fftst1W/fn3Wr1+Pm5sbjx494rvvvqNp06ZcvXoVKyurVJ8za9Ysvvvuu2xfs8B59boyuEUGPVTGRZQJrCJR6Y3JaHhEiDcTeusPyd0davMDlQrazYcfG8CDC8qxCq2gQkv9xWRsrlTfvntY6Y1Jbx8gScqE0NBQmjRpQkREBN9//z2enp7Y2NgQEBCAj48Pv/zyC1988QUA58+fp2XLllSrVo2VK1fi7u7Oy5cv2bVrF6NGjeLIkSOAUrX50aNH7N+/n/j4ePr168fgwYP55ZdfNNcdPnw4//zzD/Pnz6d69eqEhoYSGhqqFVuXLl148uQJa9eupUKFCjx69EjrQzAqKopy5crRuXNnRo4cme7rPHfuHCtXrqRGjRoZvidCCJYtW8a0adMA6Nq1K23bvtnQsmPHjlSrVk3zOCibt6ZXUTq3DRkyhDNnzrB06VKqVKnC8+fPOXnyZJa3NlFvRpuW+Ph4jI2z/rv/gw8+YODAgezdu5cPP/wwy8/PMl0LOIWHh4vFixeL8ePHi5UrV4ozZ86IV69e6dpsCi9evBDW1tZizZo1aZ4TExMjwsPDNbd79+692wUgV72vFAv0353xubPKKOc+vZHxubf2K+fOcBIi6oXOYRYYB6crr3uqrRBP/PUdjRDHFyvx/NxZ35G88wpyAcjmzZuL4cOHpzju4+OjVcX4888/FxYWFuLBgweptpP0unJ6UlKSqFq1qvD09BSJiYkpznvx4oUQQgh/f38BiHPnzmke27t3r1CpVJpr+Pv7CyMjI3HjRtq/d/bu3StsbGxSVNFOi4uLi1i0aFGqj718+VJUrFhR7N+/P833Jblz584JAwMDERERkerjabXBWxWkT5w4IWrWrClMTU2Fp6en2LFjh1bl60OHDglAHDhwQHh6egpzc3PRsGFDzfuSWgVuHx+fVGOysbER69evT/d1ubi4iGnTpolu3bqJIkWKCCcnJ7Fs2bI0X4O6UveWLVtEs2bNhKmpqfDx8RHPnj0T3bp1E05OTsLc3FxUq1ZN/PLLLxm+R/369RM9e/ZMN0Yh8kkByI4dOzJ9+nQuXbrEDz/8QOPGjbGxscHd3Z2uXXNui3pbW1sqVarE7du30zzH1NQUa2trrds77dVT5atF8YzPzcquvepeGI9e78bmdpnV9Gvw7Aft5ik75+qbel5M0HFlybeUp4QQxMfE5PlN5MIcqKSkJLZu3UrPnj3TrGOnej3vzc/Pj2vXrjFq1CgMDFJ+RKiHqE6dOoWtrS116tTRPNaqVSsMDAw4c+YMAH/88QflypXjzz//pGzZsri6ujJw4ECtnpjdu3dTp04d5s6dS6lSpahUqRKjR4/O1pzKL774gg8//JBWrVpl6vxjx45RqVKlNHv3MyMiIoL27dtTvXp1fH19+f777xk3blyq506cOJEFCxZw/vx5jIyM6N+/P6D0AI0aNUprMUtan5+Ojo7s2bOHly/T/10+b948atasycWLFxk/fjzDhw9n//796T5Hfd7169fx8vIiJiYGT09P/vrrL65evcrgwYPp1asXZ8+eTbedevXqcexYJmvT6Ujn4aRTp05x+PBh6tatCyhjm1euXMHPz49Lly7pHKBaZGQkd+7coVevXjnWZoEmBES+Hk6ydMj4fDNrCCfjXXufXFOGL1QG0GCIzmEWKMbm0H6xvqN4o0Q1sHBQhg3vnwXXJvqOqFBJiI3lhz6d8vy6wzb8hrEO21Ok5r///iMsLCxFoT9PT08CApTSJe3bt2fz5s3cuqUsGMhoS4vHjx9TvLj2H1BGRkYUK1aMx48fA3D37l2Cg4PZtm0bGzduJDExkZEjR9KpUyf+/fdfzTnHjx/HzMyMHTt28OzZM/7v//6P58+f4+Pjk+nXuGXLFnx9fTl37lymnxMcHKxzceJffvkFlUrF6tWrMTMzo0qVKjx48IBBgwalOHfGjBk0b94cUBKGDz/8kJiYGMzNzbG0tNQsZknPqlWr8Pb2xs7Ojpo1a9KkSRM6depE48aNtc5r3Lgx48ePB6BSpUqcOHGCRYsW0bp16zTbHjFiBB07dtQ6Nnr0aM39r776in379vHrr79Sr169NNtxcnLi3r17JCUlpZoI5ySdW69RowZGRm9yIVNTU+rUqcPAgQN1Ku89evRojhw5QlBQECdPnuTTTz/F0NCQ7t276xryuyEuEhJe/6WSqZ6YTGx4JwT8861yv3L7glut+l1hYCB375Vy1Y4dO/Dz88PLy0vT85GTPUFJSUnExsayceNGmjZtSosWLVi7di2HDh3SJE9JSUmoVCo2bdpEvXr1aNeuHQsXLmTDhg2Z7o25d+8ew4cPZ9OmTVnanyw6Olqn/cwAAgICqFGjhlY7aX3AJ5+nU7JkSQCePn2apes1a9aMu3fvcvDgQTp16sS1a9do2rQp33//vdZ5DRs2TPH99evX0207ea8aKGWFvv/+e6pXr06xYsWwtLRk3759GS6yMTc31/zb5zade2Lmzp3L5MmT+e233zA1Nc2JmAC4f/8+3bt35/nz5zg4ONCkSRNOnz6Ng0Mmeh0Kg8jX//GNi2RuH5PMDCedX6t8WBqZwXvf6h6jpLvy78GVX5X9YlpO1nc0hYqRqSnDNvyml+tmhbW1NeHhKfeACgsLw8ZG2ejSwcEBW1tbTeKgVqaMsrLRyspKs/y3UiWlhMmNGzfw8PBI87qOjo4pPoATEhIIDQ3V9CaULFkSIyMjTZsAlSsrQ7UhISG4ublRsmRJSpUqpYlVfY4Qgvv371OxYsUM34MLFy7w9OlTateurTmWmJjI0aNHWbZsGbGxsalOxrW3t+fKlSsZtp9Tkk+UVQ/fZWcVj7GxMU2bNqVp06aMGzeO6dOnM23aNMaNG4eJiUm247OwsND6ft68eSxZsoTFixdTvXp1LCwsGDFiBHFx6Q9vh4aGYmFhgbm5ebZjySyde2JcXV2JiIigSpUqfPPNN+zevZt799IoqJcFW7Zs4eHDh8TGxnL//n22bNlC+fLldW73naFZmZTJpC6jIpDP78A/r+sDtZqafi0mKe+oe2IeXlQ24ZPyjEqlwtjMLM9vqizuyeTm5oavr2+K476+vprkwcDAgC5duvDzzz9rNidNS61atahSpQoLFixI9QNWnew0bNiQsLAwLly4oHns33//JSkpifr16wPKkEZCQgJ37tzRnHPzprJlgLosTePGjXn48KHW0uybN29iYGBA6dKlM/MW0LJlS800BvWtTp06eHt74+fnl+ZqIg8PD27cuKFT75ObmxtXrlzR6nXIypCWmomJCYmJidmKoUqVKiQkJBATE6M5dvr0aa1zTp8+rUkgM+vEiRN06NCBnj17UrNmTcqVK6f590vP1atX002Ac5LOScxnn31GUFAQjRs35uTJk/Tp0wdXV1ccHBxo06ZNTsQopUadxFhmYigJ0i8CmZQIO/9PKYbo2hTqfZ4zMUq6sy4JDpUBAYFH9B2NlA8NHTqUmzdvMmzYMC5fvkxAQAALFy5k8+bNjBo1SnPezJkzKVWqFPXq1WPdunVcvnyZO3fusGPHDk6dOqX5oFepVPj4+HDz5k2aNm3Knj17uHv3LpcvX2bGjBl06KDsG1W5cmXatm3LoEGDOHv2LCdOnODLL7+kW7dumnkmrVq1onbt2vTv35+LFy9y4cIFPv/8c1q3bq1JsHr06IGdnR39+vXD39+fo0ePMmbMGPr376/5Sz4uLk6TnMTFxfHgwQP8/Pw0Cz2srKyoVq2a1s3CwgI7OzuqVauW5nv33nvvERkZybVr17L9/vfo0YOkpCQGDx7M9evX2bdvH/Pnz9e8l5nl6upKYGAgfn5+PHv2LM2hmBYtWrBy5UouXLhAUFAQe/bs4ZtvvuG9997TWsxy4sQJ5s6dy82bN/nf//7Htm3bGD48ayVUKlasyP79+zl58iTXr1/n888/58mTJxk+79ixY3n3+Z/hGqgMmJubCz8/P61jgYGBYvv27WLq1Km6Nq+TzC7RKpDOrlGW3/7SPXPn/zNJOX/vhJSPHVv0ekl1KSFeBOdomFIO2DtB+ffZ9aW+I3lnFeQl1kIIcfbsWdG6dWvh4OAgbGxsRP369bWWAKuFhYWJCRMmCHd3d2FqairMzc1FjRo1xKRJk1IscQ4ICBC9e/cWTk5OwsTERLi4uIju3bsLX19fzTnPnz8X3bt3F5aWlsLa2lr069dPvHz5UqudBw8eiI4dOwpLS0tRokQJ0bdv3xTXun79umjVqpUwNzcXpUuXFl9//bWIiorSPK5eAvz2rXnz5mm+J5lZYi2EEF26dBHjx4/PUhukssS6Ro0awsTERHh6eopffvlFAJol1Ool1url6UIIcfHiRQGIwMBAIYSyRchnn30mbG1t011iPXPmTNGwYUNRrFgxYWZmJsqVKyeGDRsmnj17pjnHxcVFfPfdd6Jz586iSJEiwtHRUSxZsiTN16B+f9VLwtWeP38uOnToICwtLUXx4sXFt99+K3r37i06dOiQ5nt0//59YWxsLO7du5dq/MnlxBJr1esXk23Nmzdn1qxZNGqU/2rrREREYGNjQ3h4+Lu33PrwbDg8Czz7QvslGZ9/dB78O11ZNt1h2ZvjT67BqhaQGAcfL4PacvVXvnNrP2zqBDZlYMTld7cEhB7FxMQQGBhI2bJldZ7oKRUsly9fpnXr1ty5cwdLy5ypk7Zp0yb69etHeHh4nswLeZurqysjRozI1I7FOW3cuHG8ePGCVatWZXhuej93mf381nk4afjw4UydOjVf1YQoFCKzsEcMJKtknWxOTEIc7PhcSWAqfaC/OkFS+lwagaEJhIcoc5ckScoxNWrUYM6cOQQGBma7jY0bN3L8+HECAwPZuXMn48aNo0uXLnpJYPStePHiKVZK5SadVyd16qTso1CxYkU+/fRT6tevj4eHB9WqVdNplrSUAc1Gd1md2Pt6TkzYPfjra3h8BcyLKb058i/8/MnEApzrQ9AxuHsI7CvoOyJJeqf07dtXp+c/fvyYyZMn8/jxY0qWLEnnzp1T1IcqLJLPw8oLOicxgYGBXLp0SbO53cyZMwkKCsLIyAg3NzcuX76cE3FKb8vKRnfwZmJvdBic+lEZWop/BQbG0OF/YFUiV8KUckj595Uk5s6/UC/lJlqSJOnP2LFjGTt2rL7D0AgKCtJ3CHlG5yTGxcUFFxcXPv74Y82xly9f4ufnJxOY3JSVkgPwpifmoa9yAyjTED5aDMXT35lTygfKvwcHv4PAY5AY/+4X5ZQkScqEbM+JmTx5stb+AMlZWVnRtGlTTUVUKRdEZnGJtWmyiVGmNsrwUd89MoEpKBxrKsN+cS/hQco9QSRJkgqjbCcx9+/f54MPPqB06dIMHTqUvXv3ZriLn5RD4qOVDzPI/JyYElWhYhuo2QO+PKusasrlmhZSDjIwUHrOAO6d0W8skiRJ+US2P8XWrVvH48eP2bx5M1ZWVowYMQJ7e3s+++wzNm7cqFWlVMph6o3uDE3AzCb9c9UMjcF7G3y6HKzSLzAm5VPOr+ux3E+/gqwkSVJhodOf4gYGBjRt2pS5c+cSEBDAmTNnqF+/PitXrsTJyYlmzZoxf/58Hjx4kFPxSvBmKMmiuFxRVJg4K1u5c++sUqxTkiSpkMvR8YTKlSszduxYTpw4QUhICH379uXYsWNs3rw5Jy8jqSf1ZnZlkvRucKqlrCaLfAJhwfqORpIkSe9ybVKEhYUFHh4erF27ltGjR+fWZQqnrG50J70bjM2hZE3l/j05pCRJmdGrVy9mzpyZ6fODgoJQqVT4+fkBcPjwYVQqlWZD1/Xr12Nra6tzXG9fJyeoVCp27twJwLNnzyhevDj379/Psfbzo1xJYmbOnEnHjh3Zvn07//d//0f//v2Jjo7OjUsVTrInpvDSDCnJyb2Som/fvqhUKmbPnq11fOfOnSkKEAohWL16NQ0bNsTa2hpLS0uqVq3K8OHDNcUU1SIiIpg4cSLu7u6YmZnh6OhIq1at2L59e6pVn4cMGYJKpWLx4sWaY0FBQQwYMICyZctibm5O+fLlmTJlitYikKlTp6JSqVLcLCwstNpfvHgxbm5umJub4+zszMiRI7WqNqfm0qVL7Nmzh2HDhmmOtWjRItXrDRkyJN221Lp27ZqpSs7J9e3bl08++UTrmLOzM48ePUq3QKUu7O3t6d27N1OmTMmV9vMLnfeJeZuPjw+hoaHs27dPc2zbtm2MGDGClStX5vTlCqfkc2KkwsW5LpxGJjGSFjMzM+bMmcPnn39O0aJFUz1HCEGPHj3YuXMn33zzDYsWLcLJyYmHDx+yY8cOpk+fzvr16wEICwujSZMmhIeHM336dOrWrYuRkRFHjhxh7NixvP/++1q9ETt27OD06dOa6tVqN27cICkpiZUrV1KhQgWuXr3KoEGDePXqlabS8+jRo1MkEC1btqRu3bqa73/55RfGjx/PunXraNSoETdv3tQkbwsXLkzzfVm6dCmdO3dOURNp0KBBTJs2TetYkSJF0mwnOXNz8xwpJ2BoaIijY+4usujXrx+enp7MmzePYsWK5eq19CbDMpNZ5OXlJf777z8hhBD9+vUTjx8/FkII4eHhkdOXytA7W8X61z5KVeNTP+o7Eimvhd1X/u2n2goRE6HvaN4ZBbmKdZ8+fcRHH30k3N3dxZgxYzTHd+zYIZL/it+8ebMAxK5du1JtJykpSXN/6NChwsLCQjx48CDFeS9fvhTx8fGa7+/fvy9KlSolrl69KlxcXMSiRYvSjXfu3LmibNmyaT7u5+cnAHH06FHNsS+++EK8//77Wud9/fXXonHjxmm2k5CQIGxsbMSff/6pdTyj6tZvV3R+uwK1j4+PsLGx0Zw/ZcoUUbNmTbFixQpRunRpYW5uLjp37izCwsI0j/NW9e1Dhw6lWjn66tWr4sMPPxRWVlbC0tJSNGnSRNy+fVsIoVQqb9WqlbCzsxPW1taiWbNm4sKFC1qx81Z1bSGEKFu2rFizZk2ar1efcqKKdY4PJxkbG2u6Chs3bqzJbpOSknL6UoWXpidGDicVOjalwMYZRJLc9C6XCSFIikvM85vIxsozQ0NDZs6cydKlS9OcA7F582bc3Ny0dldPTj30lJSUxJYtW/D29k7RswJgaWmJkZGR5txevXoxZswYqlatmqlYw8PD0+0VWLNmDZUqVaJp06aaY40aNeLChQucPavMBbt79y579uyhXbt2abZz+fJlwsPDqVOnTqbi0sXt27f59ddf+eOPP/j777+5ePEi//d//wcoPU1dunShbdu2PHr0iEePHtGoUaMUbTx48IBmzZphamrKv//+y4ULF+jfvz8JCQmAshN+nz59OH78OKdPn6ZixYq0a9eOly9fphtbvXr1OHbsWM6/6Hwix4eTBg4cyNixY9mwYQMDBgwAYNGiRXzwwQc5fanCK6vFH6V3i3M9CL+nTO4t11zf0byzRHwSDyefzPPrOk1rhMrEMMvP+/TTT6lVqxZTpkxh7dq1KR6/efMmbm5uWsdGjBjBmjVrALC1teX+/fs8e/aMFy9e4O6e8W7ec+bMwcjISGvOSXpu377N0qVLNUNJb4uJiWHTpk2MHz9e63iPHj149uwZTZo0QQhBQkICQ4YM4ZtvvknzWsHBwRgaGlK8eMph9x9//FHzutVWrlyJt7d3pl5HanFv3LiRUqVKAcow1ocffsiCBQtwdHTE3Nyc2NjYdIeP/ve//2FjY8OWLVswNlbKilSqVEnz+Pvvv691/qpVq7C1teXIkSN89NFHabbr5OTExYsXs/W6CoIc74np0KED7dq1o2XLlvTp04c2bdpoxlWlHPIqiyUHpHeLnNwrpWHOnDls2LCB69evZ+r8iRMn4ufnx+TJk4mMjATIdE/QhQsXWLJkCevXr08xgTg1Dx48oG3btnTu3JlBg1IvYrpjxw5Nj0Nyhw8fZubMmfz444/4+vqyfft2/vrrL77//vs0rxcdHY2pqWmqsXl7e+Pn56d1S6uHKjPKlCmjSWAAGjZsSFJSEgEBAZluw8/Pj6ZNm2oSmLc9efKEQYMGUbFiRWxsbLC2tiYyMpKQkJB02zU3NycqKirTcRQ0Od4TA0rW3KNHD0JDQylatGim/oNLmZQYD9EvlPtyYm/hlHzn3qQkWT4il6iMDXCalrLbPy+um13NmjXDy8uLCRMm0LdvX63HKlasmOJD1cHBAQcHB63eCgcHB2xtbblx40a61zp27BhPnz6lTJkymmOJiYmMGjWKxYsXa1VSfvjwIe+99x6NGjVi1apVaba5Zs0aPvroI0qUKKF1fNKkSfTq1YuBAwcCUL16dV69esXgwYOZOHEiBqn8DNjb2xMVFUVcXBwmJiZaj9nY2FChQoV0X19ey2iycJ8+fXj+/DlLlizBxcUFU1NTGjZsmGG5n9DQUBwc3t1e+1z97VesWDGZwOQ0dS+MyhDMU1+FIL3jSlQD4yIQEw7PsrbUU8o8lUqFgYlhnt90/Z05e/Zs/vjjD06dOqV1vHv37gQEBLBr1650n29gYEC3bt3YtGkTDx8+TPF4ZGQkCQkJ9OrVi8uXL2v1Zjg5OTFmzBit1akPHjygRYsWeHp64uPjk2rCARAYGMihQ4c00xCSi4qKSvE8Q0NlyC2tnqNatWoB4O/vn+7rzQkhISFa79Xp06cxMDDQDN+ZmJiQmJiYbhs1atTg2LFjxMfHp/r4iRMnGDZsGO3ataNq1aqYmpry7NmzDGO7evUqHh4eWXg1BUuuJTG3bt2ieXM5Xp/jIpPNh5F/gRdOhsbgVFu5L4eUpLdUr14db29vfvjhB63j3bp1o1OnTnTr1o1p06Zx5swZgoKCOHLkCFu3btUkBQAzZszA2dmZ+vXrs3HjRvz9/bl16xbr1q3Dw8ODyMhI7OzsqFatmtbN2NgYR0dHzYe3OoEpU6YM8+fP57///uPx48c8fvw4Rdzr1q2jZMmSqc6fbN++PcuXL2fLli0EBgayf/9+Jk2aRPv27bXiTs7BwYHatWtz/PjxFI9FRUVp4lDfXrx4kaX3OTkzMzP69OnDpUuXOHbsGMOGDaNLly6aOTCurq5cvnyZgIAAnj17lmqi8uWXXxIREUG3bt04f/48t27d4qefftL0nlWsWJGffvqJ69evc+bMGby9vTPsvYmKiuLChQu0adMm268tv8u1T8G4uLhU//NIOtLMh3l3uwelTFAPKcmde6VUTJs2LcWKUJVKxdatW1m8eDF79uyhZcuWuLm50b9/f5ydnbV+XxcrVozTp0/Ts2dPpk+fjoeHB02bNmXz5s3MmzcPG5vMFZ7dv38/t2/f5uDBg5QuXZqSJUtqbsklJSWxfv16+vbtm2pS8u233zJq1Ci+/fZbqlSpwoABA/Dy8spw77GBAweyadOmFMdXr16tFUvJkiXp3r17pl5TaipUqEDHjh1p164dbdq0oUaNGvz444+axwcNGoSbmxt16tTBwcGBEydOpGjDzs6Of//9l8jISJo3b46npyerV6/WzJFZu3YtL168oHbt2vTq1Ythw4alOmk5uV27dlGmTBmtlV7vGpXIznq+TLh27Ro1atTIsAstN0VERGBjY0N4eDjW1tZ6iyNHXdwEu/4PyreEXtv1HY2kLwF/w+auYF8Jvjyn72gKvJiYGAIDAylbtixmZmb6DkfKIdHR0bi5ubF161YaNmyYK9eYOnUqO3fuzNHyATmlQYMGDBs2jB49eug7lFSl93OX2c/vbPfEDBkyhNWrV3P+/PkMJxZJOUhTckBO6i3USr/ezfTZTYgK1W8skpRPmZubs3HjxkzNHXnXPHv2jI4dO+rUw1QQZHt10pUrV9i0aROvXr3C2NiYKlWqULt2bTw9Paldu3aak7ckHcmN7iQACzuwqwjPb8H9c1DJS98RSVK+1KJFC32HoBf29vaMHTtW32HkumwnMSdOnEAIQUBAAL6+vprbjh07NNU+5cqkXPBKJjHSa871lSTm3hmZxEiSnkydOpWpU6fqO4xCS6d9YlQqFe7u7ri7u2uNud29e5cLFy6807sE6o3c6E5Sc64Hfj/Lyb2SJBVa2UpiQkJCtDY4elu5cuUoV64cnTt3BpRldsl3M5R08Or12G4Re/3GIemfeufeBxeUTRANU9/pU5Ik6V2VrYkrdevW5fPPP+fcubRXRYSHh7N69WqqVavG77//nu0ApbdEvU5iLGQSU+jZVwIzG4iPgidX9R3NOyGXFmtKkpSKnPh5y1ZPjL+/PzNmzKB169aYmZnh6emJk5MTZmZmvHjxAn9/f65du0bt2rWZO3duupVGpSwQ4k1PjExiJAMDZZXS7QNw7xw4vbu7cuY29V4cUVFRGW4gJklSzlDXdEqrXlRmZCuJsbOzY+HChcyYMYO//vqL48ePExwcTHR0NPb29nh7e+Pl5UW1atWyHZiUiphwSHq906McTpJAGVK6fUCZ3Ft/sL6jKbAMDQ2xtbXl6VNlC4MiRYrIhQmSlEuEEERFRfH06VNsbW3T3HU5M3Sa2Gtubk6nTp3o1KmTLs1ImaXuhTGxAmO5IZeE3Lk3B6m3iFcnMpIk5S5bW1vNz1125UoVaymXyPkw0ttKeYLKAMJDIOIhWDvpO6ICS6VSUbJkSYoXL55mET5JknKGsbGxTj0wajKJKUg0e8TIJEZ6zdQKSlSFx1eU3piqn+g7ogLP0NAwR365SpKU++S2ugWJZlKv3OhOSka91FoOKUmSVMgUmCRm9uzZqFQqRowYoe9Q9EezR4ydfuOQ8pfS6nkxZ/QbhyRJUh4rEEnMuXPnWLlyJTVq1NB3KPoVJXtipFSoJ/c+ugTxMfqNRZIkKQ/lSBJz7NgxevbsScOGDXnw4AEAP/30E8ePH9e57cjISLy9vVm9ejVFixbVub0CTc6JkVJT1BUsiivL7x/56TsaSZKkPKNzEvP777/j5eWFubk5Fy9eJDY2FlB27J05c6bOAX7xxRd8+OGHtGrVKsNzY2NjiYiI0Lq9U+ScGCk1KlWypdZySEmSpMJD5yRm+vTprFixgtWrV2vtute4cWN8fX11anvLli34+voya9asTJ0/a9YsbGxsNDdnZ2edrp/vyDkxUlrk5F5JkgohnZOYgIAAmjVrluK4jY0NYWFh2W733r17DB8+nE2bNmFmlrmN3SZMmEB4eLjmdu/evWxfP1+Sc2KktGiSmDNKeQpJkqRCQOd9YhwdHbl9+zaurq5ax48fP065cuWy3e6FCxd4+vQptWvX1hxLTEzk6NGjLFu2jNjY2BR7OZiammJqaprta+ZrSUmybpKUtpI1wdBEmTf1IhCKZf9nT5IkqaDQOYkZNGgQw4cPZ926dahUKh4+fMipU6cYPXo0kyZNyna7LVu25MqVK1rH+vXrh7u7O+PGjSt8m1HFhIFIVO7LuknS24zNoGQtuH9WGVKSSYwkSYWAzknM+PHjSUpKomXLlkRFRdGsWTNMTU0ZPXo0X331VbbbtbKySlFA0sLCAjs7u8JZWFLdC2NqA0Ym+o1Fyp+c671JYmp203c0kiRJuU7nJEalUjFx4kTGjBnD7du3iYyMpEqVKlhaWuZEfJKaXF4tZcS5HpxCTu6VJKnQ0DmJCQkJwdnZGRMTE6pUqZLisTJlyuh6CY3Dhw/nWFsFjiz+KGVEvXPv02sQEwFm1vqNR5IkKZfpvDqpbNmy/PfffymOP3/+nLJly+ravKSm6YmRK5OkNFiXBNsyIJLgwQV9RyNJkpTrdE5ihBCoVKoUxyMjIzO9NFrKhFfPla+yJ0ZKj9wvRpKkQiTbw0lff/01oMyJmTRpEkWKFNE8lpiYyJkzZ6hVq5bOAUqvqXti5MokKT3O9eHKNrlzryRJhUK2k5iLFy8CSk/MlStXMDF5s2LGxMSEmjVrMnr0aN0jlBRyozspM9TlB+6fU/YWMigQNV4lSZKyJdtJzKFDhwBl75YlS5ZgbS0nEeYqudGdlBnFq4KxBcRGwH83oESVjJ8jSZJUQOm8OsnHx4ewsDAWLFjA9evXAahatSr9+/fHxsZG5wCl12QSI2WGoRGUqg1Bx5Q9Y2QSI0nSO0znvubz589Tvnx5Fi1aRGhoKKGhoSxcuJDy5cvrXABSSkbOiZEyS07ulSSpkNC5J2bkyJF8/PHHrF69GiMjpbmEhAQGDhzIiBEjOHr0qM5BFnpJiRAdqtyXc2KkjCQvBilJkvQO0zmJOX/+vFYCA2BkZMTYsWOpU6eOrs1LANEvlL0/AIoU028sUv5X+vXP3fPbytJ8Czv9xiNJkpRLdB5Osra2JiQkJMXxe/fuYWVlpWvzEryZD2NeFAyN9RuLlP8VKQb2bsr9+3JISZKkd5fOSUzXrl0ZMGAAW7du5d69e9y7d48tW7YwcOBAunfvnhMxSnI+jJRV6qXWckhJkqR3mM7DSfPnz0elUtG7d28SEhIAMDY2ZujQocyePVvnACXkHjFS1jnXh4s/ycm9kiS903ROYkxMTFiyZAmzZs3izp07AJQvX15rB19JR5rl1XJug5RJ6p6YB76QGC+HIaVME3FxxD14gEmZMqgMDfUdjiSlK8e28yxSpAjVq1enevXqMoHJaXI4Scoqu4pgZgsJ0fD4ir6jkQqQmIAA7n7QjjtebfUdiiRlSOeeGICDBw9y8OBBnj59SlJSktZj69aty4lLFG4vHylfrUrqNw6p4DAwUHpjbv2jDCmVqq3viKQCIubGDQBMypTRcySSlDGde2K+++472rRpw8GDB3n27BkvXrzQukk5IOJ1EmMtkxgpC+TkXikbYm8EAGDq7q7nSCQpYzr3xKxYsYL169fTq1evnIhHSo2mJ8ZJv3FIBYvcuVfKhpgApSfGzN1Nz5FIUsZ07omJi4ujUaNGORGLlJaIh8pXK0f9xiEVLE61QWUIEfch/L6+o5EKACHEm54YN9kTI+V/OicxAwcO5JdffsmJWKTUJMS+KTlgLXtipCwwtQTHasp92RsjZUL8gwckRUaiMjbGtFxZfYcjSRnK1nDS119/rbmflJTEqlWrOHDgADVq1MDYWHsp58KFC3WLsLBTDyUZmio79kpSVpSuB48uwf1zUK2jvqOR8rlY9aTeChVQGctl+VL+l60k5uLFi1rf16pVC4CrV69qHVepVNmLSnoj+aRe+X5KWeVcH86tlpN7pUyJeT2UZOYm58NIBUO2kphDhw7ldBxSWl6q58PIoSQpG9QrlB5dgvhoMDbXbzxSvhb7elKvqZzUKxUQObbZHSiTwoQQOdmkJJdXS7qwLQOWjpCUAA8vZny+VKhpemLk8mqpgMiRJGbt2rVUq1YNMzMzzMzMqFatGmvWrMmJpiW50Z2kC5VK7hcjZUpiZCTx9+4BYCqHk6QCQud9YiZPnszChQv56quvaNiwIQCnTp1i5MiRhISEMG3aNJ2DLNTUy6vlyiQpu5zrw/XdcoWSlK7YmzcBMCpRAqOichGBVDDonMQsX76c1atX0717d82xjz/+mBo1avDVV1/JJEZXsidG0pVm07szIIScIC6lSl1uQM6HkQoSnYeT4uPjqVOnTorjnp6eJCQk6Nq8JHtiJF2VrKEs0Y96DqF39R2NlE/FalYmyfkwUsGhcxLTq1cvli9fnuL4qlWr8Pb21rX5wk0IePlYuS9365Wyy8gUnGop9+WQkpQGWW5AKohypIr12rVr+eeff2jQoAEAZ86cISQkhN69e2ttjCc3vsui6BeQGKvcl8NJki6c6ynDSffOQK3uGZ8vFSoiMZHYm7cAMHWvrOdoJCnzdE5irl69Su3atQG4c+cOAPb29tjb22ttfic3vssG9VBSETvlr2lJyi7n+sBSuHMQrv4Oti7KzcJezpGRiAsJQURHozIzw8SljL7DkaRM0zmJkRvf5SJZvVrKKc71ARWEhcBv/d8cN7ZQ9pKxLQNFXyc2ye+b2+orYikPxQa8LvpYqRIqQ0M9RyNJmZcjw0lhYWGsXbuW69evA1C1alX69++PjY1NTjRfeGkm9cqhJElHlsXhszVwaz+EBSvJTMRDiH8F/11XbqkxtYGiZd703BR1gaKuULwK2JSWvTjvCPXKJFluQCpodE5izp8/j5eXF+bm5tSrp2yqtXDhQmbMmME///yjGWqSskEur5ZyUvVOyk0tIRbC78OLICWpCQuGF8Fv7r/6D2LD4fEV5fY2MxsoUe31rapSMduhMpgUybOXJOWM2OtyebVUMOmcxIwcOZKPP/6Y1atXY2SkNJeQkMDAgQMZMWIER48e1TnIQksur5Zyk5Ep2JVXbqmJewVh95IlN69vz+/As5sQEw7BJ5SbmsoAipV/k9Sok5yc7LVJSlSWi0c+hVdPIfK/11+fKolXYhzU+xzK1M+Z6xUCMQGy3IBUMOVIT0zyBAbAyMiIsWPHprp/jJQFsidG0icTCyjurtzelhCrJDKPr8KT17fHVyHqGTy/pdz8d745P6Nem8R4JQFRJyJpJSiRT5UEhgxqtN34C7r8BJXa5NS78c5KDAsj4bGylYMsNyAVNDonMdbW1oSEhOD+VgZ/7949rKysst3u8uXLWb58OUFBQYAyz2by5Ml88MEHuoRbsGiKP8qeGCmfMTIFx+rKLbmXT94kNU+uKYnNs4C0e22sS0PcS2U7gSxRKav2LIuDhcPrr8XB0gGCTsDt/bClO3RcBdU+0/nlvsvURR+NS5fG0NJSz9FIUtbonMR07dqVAQMGMH/+fBo1agTAiRMnGDNmjFYpgqwqXbo0s2fPpmLFiggh2LBhAx06dODixYtUrVpV17ALBk1PjNzoTiogrEootwot3xxLiFMSmdR6bcJD3pynMnydkDi8TkheJyiaJCVZslLEDgzT+PXV8EvYORSubIPfBkDsS/Dsm6svuyCLDZDzYaSCS+ckZv78+ahUKnr37q0pM2BsbMzQoUOZPXt2tttt37691vczZsxg+fLlnD59unAkMQmxyi95kEuspYLNyCTtXpsXgcpQk0VxMC8KBjpvIg6GxvDpKjC1gvPr4I/hEBMBjYfp3vY7KEaWG5AKMJ2TGBMTE5YsWcKsWbM0m92VL1+eIkVyboVCYmIi27Zt49WrV5pK2e88dS+MoSkUKabfWCQpN6h7bXKDgQF8uBBMreHEYtg/CWIj4L2Jcln4W2JkT4xUgOXIPjEARYoUoXr16hmfmAVXrlyhYcOGxMTEYGlpyY4dO6hSpUqa58fGxhIbG6v5PiIiIkfjyVPhD5SvNqXkL11Jyg6VClp/p/T0HPwOjs5T5ua0nZMzPT7vABEfT9yt24BcmSQVTDr/JEdHRxMVFaX5Pjg4mMWLF7Nv3z5dm8bNzQ0/Pz/OnDnD0KFD6dOnD/7+/mmeP2vWLGxsbDQ3Z2dnnWPQm/D7ylfrUvqNQ5IKuqZfw4cLABWcXQW7/g8SE/QdVb4QGxiIiI/HwMIC41Lyd41U8OicxHTo0IGNGzcCys699erVY8GCBXzyySepVrfOChMTEypUqICnpyezZs2iZs2aLFmyJM3zJ0yYQHh4uOZ27949na6vVxGvkxibApyISVJ+UXegslJJZQiXNsO2Psq8s0JOU27AzQ2V7J2SCiCd/9f6+vrStGlTAH777TccHR0JDg5m48aN/PDDDzoHmFxSUpLWcNHbTE1Nsba21roVWMmHkyRJ0l2NLtD1Z2We2Y0/4ZcuEBup76j0SlNuQM6HkQoonZOYqKgozX4w//zzDx07dsTAwIAGDRoQHByc7XYnTJjA0aNHCQoK4sqVK0yYMIHDhw/j7e2ta8gFg3o4yaa0fuOQpHeJezvw3qYUvrx7GH76NBt71Lw7Ym+oe2LkfBipYNI5ialQoQI7d+7k3r177Nu3jzZtlB0ynz59qlNPyNOnT+nduzdubm60bNmSc+fOsW/fPlq3bq1ryAVDxOueGGuZxEhSjirXHPrsBjNbuH8W1n+k7ARcCL0pNyB7YqSCSefVSZMnT6ZHjx6MHDmSli1bapZA//PPP3h4eGS73bVr1+oaWsEW/no+j+yJkaScV7oO9Nuj9MQ8uQrr2kLvnWBbRt+R5ZmEZ89IfPYMVCpMK1bUdziSlC0698R06tSJkJAQzp8/z99//6053rJlSxYtWqRr84VT7EtlKSjIOTGSlFtKVIV+e8GmDITegXUfwLNb+o4qz6g3uTNxdcUgB/f1kqS8lCPT0R0dHfHw8MAg2ez2evXqpainJGWSelKvmY2y66gkSbnDrjz0/xvsKykrAte1hUeX9R1Vnoi9cR2Qm9xJBVu2h5M6duyYqfO2b9+e3UsUXurl1XI+jCTlPptSSo/Mzx3h0SVljoz3r1Cmgb4jy1Wy3ID0Lsh2EmNjY5OTcUjJaVYmyaEkScoTFvbQ5w/4pSuEnFLmynT9WbuQ5TtGFn6U3gXZTmJ8fHxyMg4pOc0eMbInRpLyjJkN9NwOv/aC2wdgczf4bC1U+VjfkeW4pNhYYu8GArLcgFSwyS0a8yPN8mrZEyNJecqkCHTbDFU+gcQ4ZWffi5v0HVWOi719GxITMbSxwahELhXhlKQ8IJOY/EizvFqWHJCkPGdkAp3WgUcvEElKraXTK/QdVY7SbHLn7o5KFpiVCjCZxORHsuSAJOmXgSF8vBQafKF8//c4ODIXhNBvXDkkJkCWG5DeDTKJyW+EeDOcJOfESJL+qFTgNQPem6h8f2gG/PPtO5HIyHID0rtCpyQmPj6eli1bcutW4dkgKtdFPYeEGEAFVk76jkaSCjeVCpqPhbazle9PLYPf+kNMhH7j0oEQQpYbkN4ZOiUxxsbGXL5cODaGyjPq+TCWJZSxeUmS9K/BUOjwI6gM4dp2WNkUHlzQd1TZkvD4MUnh4WBkhEmFCvoOR5J0ovNwUs+ePWWdo5wk58Pka8/vh3D0l/Wc2/07108c4b7/VcKePCYhPl7foUm5zcMb+u9T6iu9CIK1beDED5CUpO/IsiTmxuv9YcqWxcBE/qEkFWw6F4BMSEhg3bp1HDhwAE9PTywsLLQeX7hwoa6XKFzUG93J5dX5TlJSIn8sms3z+yGpPm5ubYNlMTusitlhZWePZVE7LO3ssSpmT/Fy5TG3lCUkCjznuvD5MfhjOPjvhP2T4O5h+HQFWBbXd3SZEhvwZmWSJBV0OicxV69epXbt2gDcvHlT6zG5dC8bwl5/QBaiaroFxY0TR3l+PwRTCwvK1a5H5PNnRL54zsvnz0mIiyU6IpzoiHD+C7qb4rlmFpZ0mzYXu9Ly37XAM7eFzuvBdwPsHQ93DsLyxtBxJZR/X9/RZUhTbkDOh5HeATonMYcOHcqJOCS1F0HK16Ku+oxCektiQgIntymbntX9uBP1P+mseUwIQcyrSCKfP+Nl6DMiQ5XEJjL0GS+fP+P5/RAiQ5+ze+EsvGcuxMTMXF8vQ8opKhV49gXnBvBbP3jqr5QqaDwC3v8WDI31HWGaYtXDSXJlkvQO0DmJATh27BgrV67k7t27bNu2jVKlSvHTTz9RtmxZmjRpkhOXKDw0SUxZvYYhabt6aD/hTx5TxMaW2m3baz2mUqkwt7TC3NIKB5eU/25R4WH8NG4YoQ/u8c/KpXw4bIzspXxXFHeHQf/Cvm/g/Do4sRiCjkOntfnyD5GkqCjigoMB2RMjvRt0ntj7+++/4+Xlhbm5Ob6+vsTGxgIQHh7OzJkzdQ6wUBECwpRfMPnxF2BhFR8Xy+nfNwNQ/9OuGJuZZen5RWxs+WjEeAwMDQk4eRS/fX/mRpiSvhibw0eLoMtGpf7Sg/Owoilc/V3fkaUQe/MmCIGhvT1G9vb6DkeSdKZzEjN9+nRWrFjB6tWrMTZ+04XauHFjfH19dW2+cIl6DnGRgApsZcmB/OLSP3uIfBGKlb0DNVq1zVYbpdyr0My7HwCHN67l4c0bORmilB9U6QBDjitDTLERyn4yu76EuFf6jkzjzXwYOZQkvRt0TmICAgJo1qxZiuM2NjaEhYXp2nzhoh5KsnYCI1O9hiIp4qKjOLtzGwANO3XHyDj7cx1qt+tApfqNSUpM4I/Fs4mKCM+pMKX8wrYM9P0Lmo0BVHDxJ1jVAh5f1XdkgCw3IL17dE5iHB0duX37dorjx48fp1y5cro2X7jISb35zoU9u4h+GUHRkqWo2qylTm2pVCraDBlO0ZKliHz+jD1L55OUlJhDkUr5hqGRMrm3z26wKgnPbsLq9+Hsar2XLJDlBqR3jc5JzKBBgxg+fDhnzpxBpVLx8OFDNm3axOjRoxk6dGhOxFh4vAhUvsokJl+IjnzJ+T92ANCoizcGhoY6t2lapAgffz0BI1NTgi9f5NRvW3RuU8qnyjZThpcqekFiLOwZDVt7QlSoXsIRSUmaPWJkT4z0rtA5iRk/fjw9evSgZcuWREZG0qxZMwYOHMjnn3/OV199lRMxFh4v5KTe/OTc7t+Ji47CwaUsbg1ybpWdfRlX2gz6EoDTv28m8OL5HGtbymcs7KHHVvCaBQbGcONPZdJv8Mk8DyX+/n2SoqJQmZhgUlaufpTeDTonMSqViokTJxIaGsrVq1c5ffo0//33H99//31OxFe4yOGkfCPyRSgX9/4BwP+3d9/xTZVtA8d/2aN7D9oyy957CCggCIogDvRRxL2AV8W9cD6CC1yICxUfBwgKKDJly15FZtl07zZtmmaf94+0gcpu0yZt7+/HfEjPOTnnqqdtrtzr6jd2HDK5Zwu+t+l/DZ2uHQHA0k8/oDg3x6PnF3yITAZ9HoMH/oLQ5lCcBt9dD+vegVrsTnSXG2jRApnSI6trCILXeewvs1qtpk2bNvTo0QN/f39PnbZhqWiJCW7s3TgEti38BbvVQkzL1jTr2qNGrnH1+AeJbp6I2VjC79OnivpL9V1sZ3h4PXS6AyQnrHsb5tx4pl5aDXOPhxEzk4R6xCNJzOzZs2nfvj1arRatVkv79u35+uuvPXHqhsNudX1CA9ES42WGnGz++Ws5AFeNvbvGFqZTqlSMfPIFtP4BZJ84yro5X9XIdQQfoglw1Vm66UtQ+8Ppv+HzqyB5WY1f2izGwwj1ULWTmClTpvD4448zcuRI5s+fz/z58xk5ciRPPvkkU6ZM8USMDYMh1fXpTKmrM4Xk6qstv/6M02EnoUNnEtp3rNFrBUZEMmLS0yCTsXfVUg5uFGU8GoROY+HhDRDTCcoK4OfbYdlzYLfU2CVFuQGhPqp2EjNr1iy++uorpk6dyo033siNN97I1KlT+fLLL/nss888EWPDcPZ4GLEkvdfkp6dycP0aAK66fVytXLNp5270HnM7AKu+/JS8lFO1cl3By8Kaw/2roPcE19fbPoevB0PeUY9fylFSgi3d1W0lWmKE+qTaSYzNZqN79+7nbO/WrRt2u726p284RLkBn7B5/k9IkpPm3XsT06L2/tj3ueV2Gnfsgt1q4ffpU7GYTLV2bcGLlBq47m34z3zQh0HWPvhiIOz50aNrylRMrVbGxKAICvLYeQXB26qdxIwbN45Zs2ads/3LL7/kzjvvrO7pGw53S4wY1Ost2SePc2TLRpDJ6Df2rlq9tlyuYMSkp/EPC6cwM52Vn3+E5OWF0YRa1HIoPLLJtbaMrRQWP+ZaU8aY65HTu8sNtBKtMEL94tGBvQ888AAPPPAAHTp04KuvvkIulzN58mT3Q7iIArHQnbdt/uUHAFr3HUBEQpNav74+MIiRTzyPXKHkyLZN7F66uNZjELwoMAbGLYLBU86sKfNZbzj0R7VPbSkvN6ARXUlCPVPtxQL2799P165dATh+/DgA4eHhhIeHs3//mXohNTXDo95wr9YrFqHyhvTkQ5zYvQOZXE7f27zXghjbsjVX330/a779gg0/fkt085Y0at3Wa/EItUyugP5PQYtrYeEjkHPA1SLTcSwMfwd0IVU6rSj8KNRX1U5i1q4VsymqTZKg4JTreahIYmqbJEn8PXcOAO2vuZaQ6FivxtN52A2kJx8iefMGlnw4jXHvfoI+UIxjaFBiOsJDa2HdNNj0IfwzD05uhFGfQIshV3QqyW7HcuQIABrRnSTUM55dhlSoGlM+WEsAmVjozgtO70si7eB+FEqle5aQN8lkMoY+PInQ2DiMhQWs+vITMT6mIVJqYMircN9KCGsBJRnww83wxxNgMV72aaynTyNZLMh0OtQJCTUXryB4gUhifEHFeJjAWFBpvRtLAyNJEpvmfg9Ap6HXExge4eWIXNRaHdc//ixyhZJjO7ayb81Kb4ckeEt8D3h4I/R6xPX1rm9hVl84temyXu4uN9AyEZkHipgKgi8RSYwvEONhvCZp5Z9kHT+KSqOl1+hbvR1OJZFNmrnXqlk750sKMmpneXrBB6n1rjEx4/+AoHjXkgzfXQ8rXgKb+aIvtbhnJonxMEL9I5IYX1DREiPGw9SqtMMH3Ev99xs7Dn1QsHcDOo/uN9xEQvuO2C0Wln36Pg6x9lLD1nQAPLoZuowDJNjyKXwxANJ3X/Al5vKZSdo2IokR6h+fTWKmTp1Kjx49CAgIIDIyktGjR5NcvmBTvVMokpjaZizIZ8mMaTgdDlr1HUDXETd6O6TzksnlXPfYZLR+/mQdP8qWBT97OyTB27SBMOpTuGMe+EdBXjJ8PQTWvu2qwfYv7sKPoiVGqIeqncSMHz+eDRs2eCKWStavX8+ECRPYunUrq1atwmazMXToUEpLSz1+La8rEN1Jtclht/H7jKmUFhUSntCEYQ//n08vARAQFs6QBycCsG3RL6Qd2n+JVwgNQqvr4LGt0P5mkByw/h1X2YLsg+5D7IWF2HNyANC0bOmtSAWhxlQ7iTEYDAwZMoTExETefvtt0tM902+/fPly7rnnHtq1a0enTp347rvvSElJYdeuXR45v08pOOH6V7TE1Iq1331F5pHDaPz8GPXUS6i0vj+YulWfq2g3cAhIEks//QBz6eXPThHqMX0o3PIN3PKtaw2ZrH/gy4Hw94fgdLiLPqoSElD4+3k3VkGoAdVOYhYtWkR6ejqPPvoo8+bNo0mTJgwfPpwFCxZgs9k8ESPgSpYAQkNDL3iMxWKhuLi40sPnWYxQ6vqkJFpiat7+tavYu2opyGRcP+kZgqNjvB3SZRt070MERUVTkpfL6tnnlvoQGrD2Y+CxbdDyOnBY4a9X4dvhmHe7ZjCJcgNCfeWRMTERERFMnjyZvXv3sm3bNlq0aMG4ceOIjY3lySef5OjR6lVldTqdPPHEE/Tr14/27dtf8LipU6cSFBTkfsTHx1frurWiomaSLgR0wd6MpN7LOn6Uv2a7Kqv3u/VOmnY5t3CpL1Pr9IyY+BQyuZzDm9Zz6O913g5J8CUBUXDHXBg1E9QBkLoNy5+uZFfTSnQlCfWTRwf2ZmZmsmrVKlatWoVCoWDEiBHs27ePtm3bMmPGjCqfd8KECezfv5+5c+de9LgXXngBg8HgfqSmplb5mrVGTK+uFSZDEb9/8DYOm43m3XvR66bbvB1SlcS2bONekO+vrz/DkJPt5YgEnyKTQZe74LHN0HQA5gLXWC9t1kIoqgN/DwXhClU7ibHZbPz666/ccMMNNG7cmPnz5/PEE0+QkZHBnDlz+Ouvv/jll1944403qnT+iRMnsmTJEtauXUtcXNxFj9VoNAQGBlZ6+DwxvbrGOR0Olnz0LiX5uYTENGL4hMnI5D47Me+Seo8ZS0zL1ljLTCybOR2n0+HtkARfE5yANHY+lhINABrzHtcCeXt+dJU5EYR6otp/yWNiYnjwwQdp3Lgx27dvZ+fOnTzyyCOVEohrrrmG4ODgKzqvJElMnDiRhQsXsmbNGpo2radv8qIlpsZt+Ok7Ug/8g0qrY9TTL6PR1+0BjnKFghETn0at05F++AA7Fv/q7ZAEH2Q5fRocTuT+fqhadQFLMSx+DOb+B0pEC55QP1Q7iXn88cdJS0tj5syZdO7c2b1dkiRSUlIACA4O5uTJk1d03gkTJvDDDz/w008/ERAQQFZWFllZWZSVlVU3ZN9SMTMprLl346inDm9az64lCwEY/tiThMXVgXFSlyE4KppB97qWod88/0eyjh3xckSCr6mYmaRp3RrZ/SthyGugUEPyUvisNxxY6N0ABcEDqp3EvPbaaxiN5073LCgoqFbryaxZszAYDFx99dXExMS4H/PmzatOuL7HPb26mXfjqIdyT59kxRcfA9Bz1C0k9urr5Yg8q+2AQbTs0x+nw8HST9/Haq5nCb5QLeazyw3IFXDVk/DQOojuAGUFMP8eWHA/mAq8GqcgVEe1k5gLVdc1Go1oq7H+hiRJ533cc889VT6nz7FbwJDmei6SGI8yG40s/uC/2C0WGnfsQr/yGkT1iUwm49oHJuAfFk5hZgbrvv/a2yEJPsR8+BAAmtZnTa+OagcPrIEBz4JMAfsXwGd94IgoMCrUTcqqvnDy5MmA6w/plClT0Ov17n0Oh4Nt27ZV6l4SzqMoBSQnqP3BzzeqJ9cHkiSx7LPpGLKzCIyI4vr/ewa5vH5W79X6+zP8scnMf+sl9q1eQdPO3UjsWb9anIQrJ0nSmcKPrf9VbkCphkEvudaUWfQI5B2Bn26FEe9Dzwe9EK0gVF2Vk5g9e/YArl+Wffv2oVar3fvUajWdOnXi6aefrn6E9dnZK/X68LL3dc0/fy3nxK7tKFQqbnzqRXQBdWCWWjUktO9Ij5Fj2PH7r6z88lNiWrTCPzTM22EJXmTPycVRWAhyOZrExPMfFNcNHt4Ay1+AXd/C0qddrcN9J9ZusIJQDVVOYtauXQvAvffey0cffVQ3pjP7GjEexuMKMtLc3Sr97xhPVNOGMWC639i7OP1PEjmnjrN81ofc/MLrdXoauVA9lvLK1eomTZBfrFtfpYMbZrgW2/x7Oqx8CexlMOCZWopUEKqn2n/lvv32W5HAVJVIYjzKYbez9JMPsFstJLTvRNfhvlmZuiYolCpGTHoapVrD6X/2sHvZH94OSfAi96De1pdRbkAmg8FT4JqXXF+veQtWvynWkxHqhCq1xEyePJk333wTPz8/99iYC5k+fXqVAmsQRBLjUVt//ZnsE0fR+vlz3WNPNriWiLC4eAaOu5/Vsz9j40/fktC+IxGNxfpDDZF7enWr1pc4spxMBgOfBaUGVk2Bje+D3QxD3xJd3YJPq1ISs2fPHndxx4qxMecjEz/8FyeSGI9JP3yQbQvnAzDkwYkEhIV7OSLv6HTtcE7u2cGJ3TtY+sn7XPfYk+iDg9EHBqFQqrwdnlBLzMlX0BJztn6Pg1IHy56BLZ+6Epnh70ED+0Ag1B0y6UJzpOuB4uJigoKCMBgMvtfl5bDBf6ORHHYMLT7AuOsA5kMHCbj6GiKff04kgFfAYjLxv+cmYcjJpu2AQQyfcPHWwfrOZChizjMTMRmKKm3X+PmhDwpBHxiEPijorOfB+AUFowsKQh8YjF9wMGqdXvwM1lFOs5nkrt3A6aTF+vWooiKv/CS75sAfjwOSqxbTyI9da80IQi253PfvKg/srVBWVoYkSe4p1qdPn2bhwoW0bduWoUOHVvf09ZchFZx2TPkBZM77wL25YM4c5EGBRDz2mBeDq1vWfvclhpxsAiOi3KvYNmT6oGBufOol1v/va4rzcjEZipCcTiylpVhKSynMSLvkORRKJbqgYEKiYrjmnodEt1QdYjl6DJxOFCEhKCOruHRDt/Gg1LqmYO/5wTVrafTnoKj2W4YgeFS1fyJHjRrFmDFjeOSRRygqKqJnz56o1Wry8vKYPn06jz76qCfirH/Ku5KMeWGAFX3v3ui7dSNv5kzyPv4EZUgIwbffLj4NX8KRrX9zYP1fyGRyhk94Es1Z6xU1ZI1ateE/b7mSY8npxGwqxVRUhKm4CJPBgMlQiKnYgMlQVP4of15chLWsDIfdjjE/D2N+Hr++PYX/vPUBgRFV+EQv1LqKmUma1q2q9/ej01jXmjK/PgD75rsSmZtnu7YJgo+odhKze/duZsyYAcCCBQuIjo5mz549/Prrr0yZMkUkMReSdwwAY4rrj4xy5PVor7maMKuF/K++Juv1Nyj86WfCHrifwOHDkanFH45/KynIY9VXMwHoOfoW4tq093JEvkkml6PzD0DnH0AYl64dZbNaKDMYKC0qZOWXn5CXcopf357C7W++h84/oBYiFqqjUrmB6mp3Eyg0MH88HPod5t0Ft30Pqqqvxi4InlTt0Vomk4mAANcftpUrVzJmzBjkcjm9e/fm9OnT1Q6w3so/hrVEgbXAQkGQP/N/+4EvH72HNYZs8seMxB7gj+XoUTKee55jg4eQ9/nn2AsLvR21z5CcTlbM+gizsYSoZi3oc8sd3g6p3lCpNQRGRBKT2Ioxz7+Gf1g4BRlpLH7vTexWq7fDEy7hTOHHKxzUeyGtR8AdP7u6l46ugJ9vB6vJM+cWhGqqdhLTokULFi1aRGpqKitWrHCPg8nJyfG9wbS+JP8oxgwtJpWS3U2icdjtAKQnH2Tb8YOsbhnHvsH9ONginoNyOwdnf8mxG2/Emprq5cB9w54VSzj9zx6Uag3DJz4lZt7UkICwcG5+/jU0ej/SDx9k6afv43Q6vB2WcAGSJJ01M8kDLTEVWgyBOxeAyg9OrIUfbwFLiefOLwhVVO0kZsqUKTz99NM0adKEXr160adPH8DVKtOlS5dqB1hv5R2jMFPPrqbRWJGIataC+z78goHj7icioQkOu43UvCxO+ak5Fh3Kjmax/BXhx7KJD5G2czuS0+nt78Br8lJPs+HHbwEYOO5+whpduotEqLrwhCaMevolFEolR7dtZt33X1+w8KvgXfaMDJwlJaBSoWnm4aUbmvaHcQtBEwinN8H/boKyIs9eQxCukEemWGdlZZGZmUmnTp2Ql68nsH37dgIDA2ntyU8DV8hnp1hbS7G+3ogfk7pS4K9HHxDIXe987F7bRJIkck4eJ+3QAcpKijEW5nN8x1bMpUb3KfyCQ2jRozeNWrUlokkzQmPjkCvq/xRIu9XKTy8/Re7pkzTt0p2bnntVDH6uJYc3refPj98DYMBd99Fj5BgvRyT8W8maNaQ9NgFNq1Y0W7yoZi6SvtuVwJiLIKYTjFsE+tCauZbQYNXaFGuA6OhooqOjK23r2bOnJ05dP+UfZ3V6IgX+epROiTEvvlFpcTaZTEZUsxZENWvh3uZ40MbRFcvY8/mnZGuUlBYVsnfVMvauWgaAQqUitmUbWvcbSMve/dD6+df6t1XTbFYLv3/wNrmnT6ILCGTYI4+LBKYWte43EGNBPut/+IYNP3yDf2gYbfoN9HZYwlnM5eNhrniRuyvRqCvcswS+Hw2Ze+G76+HuxeAvZq8Jtc8jSUxRURGzZ8/m0KFDALRr14777ruPoKAgT5y+3ik5mcShMtcvfB9dcKVk5UIUShWtr7+Rxo2bc+LuceQpZBj796UkQEfOqZPYzGWkHviH1AP/sOabWTTt0oO2A66hWdce9WK8iM1sZtF7b5Kyfy9KjYaRTz6PX3CIt8NqcLrdcBMl+XnsXvY7y2fOwC8ohIT2Hb0dllDOcugKyw1UVXQHuOdP+H4U5ByEb0fA+N8hMLZmrysI/1LtMTE7d+6kefPmzJgxg4KCAgoKCpg+fTrNmzdn9+7dnoix3tm9fjMSMkKNZTRu3/mKXqtr345GL79CZImJZsvXcOONY5n07TzunfE5/f9zD+EJTXDY7RzbsYXfP3ibzx8Zz+pvPifr+NE6O47BWmbit2mvkbJ/LyqtjptfeJ34duKN0xtkMhlX3/0ALXv1w+mws/j9t8hNOeXtsIRyVS43UBWRreHepRAYB/lH4dvhUJRS89cVhLNUe0xM//79adGiBV999RVKpathx26388ADD3DixAk2bNjgkUCrwhfHxFjLTHz54FgsNoluJzLpMuU1gkaOvKJzSJJExnPPUfz7Hyijo2m68DeUIWdaJXJTTnFo41oOblxLaWGBe3tEQhM6Db2eNv2vRq3Veex7qkkWUym/Tn2VzCOHUev03Pzi68S2bOPtsBo8u9XKgv++QvrhA/iHhnHHm+8TGF7F1WEFj3AYSznSvTsAiZs3oQytpXEqhafh+xuh8BQExbu6lsKa1861hXrrct+/q53E6HQ69uzZc84A3oMHD9K9e3dMJu+tJ+CLSczWX+ey6Zcf8LNYGXA4leZ//I4mMfGKz+MwlnLqlluwnjqF/zXXEPfZzHPGhzgdDk7vS+LA+tUc37EVu821xodap6PtgEF0Hno9YXEJHvm+aoLZaOTXt18h67irMvXNL71JdPMr/38l1IwyYwlzpzxLQXoqYXEJ3P7Gu/VyLFZdYdq9h9P/+Q/KiAgSN9byh8fiDJgzEvKPgX+0q2spohZag4R663Lfv6vdnRQYGEhKyrlNiKmpqe5F8AQXU7GBHX/8CkBiViFytRp106rVpFH4+9FoxnRkajXGtWspXvLnOcfIFQqadu7GDY8/y0Ofz+Hqux8gJCYWa1kZSSv+5LunHmPhO6+Tfvhgtb6vmmAqNvDLmy+SdfwouoBAbp3ytkhgfIzOP4CbX3wdv5BQ8tNS+P39/2Ivr24v1L4z5Qa8MCM0MBbuWQoRbcCY5Rojk7W/9uMQGpxqJzFjx47l/vvvZ968eaSmppKamsrcuXN54IEHuOMOsYrq2bYvXoC1rIwweSkxRUY0LRORKas+tlrbpg3hj7oKHmZPm4bDYLjgsTr/ALpdP5p7p3/OzS+9SYsevUEm48TuHcx99VnmvvosJ3bv8IlxM6VFhcx/40VyT51AHxTMbVPeJrKJh9e8EDwiMDySMc+/hlqnI/XgPpZ/NqNBr2HkTe5yA7UxHuZ8AqJcg32jO4IpD+bcABl7vBOL0GBUO4l5//33GTNmDHfffTdNmjShSZMm3HPPPdxyyy288847noixXrCYTOxbvRyATtYsZIC2Tdtqnzf0/vtRN2uGIz+fnOkzLnm8TC6nSccujHr6Ze6d/jkdBg1FoVSSfvggC995nTlPT2DvqqVYzWXVjq0qjAX5/PL6C+SlnsYvJJTbXp1KeEITr8QiXJ7IJs0YOflF5AoFyZs3sOGn77wdUoPkLjdQ0zOTLsYvDMb/AY26Q1khzLkRUrd7Lx6h3vPIYnfgqqF0/PhxAJo3b47eB6oJ+9KYmN3L/mDtd18QGhrA4OStlGZoiXrlZULvvLPa5y7dvp2Uu8cD0Pjnn9Bf4UrJxoJ8di1dzN5Vy7CVJy9qnZ52Vw+m89DrCY2Nq3aMFyM5naQnHyR5y0aSN2+krKQY/7Bwbnvlv4TENKrRawuec3DDGpbNnA7ANfc8RNfhN3o5ooZDcjpJ7t4DyWSi2ZI/0LS49LINNcpSAj/eBimbXaUK/jPPteKvIFymWhvY68t8IYmRJIndSxezbdF8yooNDO4bj//3f2ErVZLw/Rz8PLQoYMYLL2JYuBBNq1Y0XTAfmerK14Yxlxo5uH41SSv/pDAzw709oX1HGrVuR1hcY8LjGxMcHYOiGt1g4Pr/knk0meQtGzmy9W+MBfnufcHRMdzy0psERUZf5AyCL9q28Bf+nvs9yGSMfPJ5Wvbq5+2QGgTrqVMcv244Mo2GVrt2Vqub2nNBlcLc/8CJda7ikbf/BC0GezsqoY6o1RV7V69ezerVq8nJycH5r/7wb775xhOXqLMOb97Auu+/BiAoKprW/gWcLHX9b6/KrKQKkkNCsjuQyWUgkxHxzNMY167FkpxMwfffE3b//Vd8Tq2fP11HjKLLdSM5vS+JpJV/cmLXDlL2/0PK/n/cxymUSkJi4wiPb0x080Sim7cksmkzVBrtheN1OinJz6MgI43T+5I4svVvinNz3PvVOj0tevSmVd/+NO7QuV4s0NcQ9Rx9KyX5eexdtZSln7yPPjCIuDbtvR1WvVcxHkaTWL1xdh6l9oM75sEv4+DoSlf169u+h1bDvR2ZUI9U+6f99ddf54033qB79+7ExMSIZeDP4rDb2fzLDwB0HnYD/cbehTTtagAUIYGV1na5FMkpYU0pxnKsCMupYqyni5FsZxJGmVZJ0B2vUvD1S+R+OpPA665D1ahqXTEyuZwmnbrSpFNXDDnZHNuxhbzU0+SnppCXehqbxUxeyinyUk5xeNN692vC4xsT3aIl0c0TkSuUFGamU5iRTmFmOkVZme4p3hVUWh3Nu/WkVd8BNOnUFWUVWo8E3yKTyRh038MYCws4vnMri997i9vfeI+wOFGksyaZ3TOTfGxas0oLY3+EX++DQ3/AvLvg5tnQbrS3IxPqiWp3J8XExPDuu+8ybtw4T8XkMd7uTtq9dDFr53yFLiCQBz75GrVGQ9F9jcncGoC+e2ca//DzJc9hyyujdEcWZUm5OAyWSx4vOa1Yj6xEHV1G3KyPPJ5USk4nxXm55KWeJvf0SbKOHyXrWDKlRYWXfK1coSQ4OoaIxk1p2bsfTbt0R6XWeDQ+wTfYLGbmv/kSmUeTCQiP4D9vvo9/aJi3w6q3Uh99DOPatUS99BKh4+7ydjjncthh4cOwfwHI5HDTF9DxNm9HJfiwWutOslqt9O3bt7qnqXdKiwrZ9MsPqOU6Bl11L2XrsjEZizApxqCISEPd+uJN7La8MkpWp2BKyoHyNFOmUaBtFYKmWRCaJkEoQrUgSeCQsJwwUPzXaWxZoGl9A05LCflz1hA2fpBHExmZXE5QZBRBkVE07+YazyNJEsaCfLKOHSHr+BGyjh8FICQ2jtCYWEJiGhES04jAiMgGUWlbAJVGy+hnpzB3yjMUZmbw27TXGPvaO2h8YMB/fVTREuO16dWXolDCmC9dY2OSfoDfHgK7Gbre7e3IhDqu2i0xzz33HP7+/rzyyiueisljvNkSs2XBz2Qs20v3iOtQcO4bt0xrJ2RMe3QdwislGU6TjeK/UjBuzYDy3iJt61D8ukehbRWKTHXhWfGSU6LsQD6F83Yj2V1lBdQJ/oTc0gpVpHjzEGpfUXYWP7/yNCZDEQntOzH6uSmi9c3DHAYDR3r1BqDl9m0ofGR18vNyOmHp07BztuvrEe9Dzwe9G5Pgk2ptdtLjjz/O999/T8eOHenYsSOqf41rmD59enVOXy3eSmIcdjvrnvqEVjpXHRNVrB+aJkHI8v6hcN1RFOEdkKldy7OrEwLw6xGNIliDObkQ0+5snCY7ANpWIQRe2xh13JWtfOwwlZHy8Dsoo/ojU6pBIcO/Vwz6HtGoY/w8+80KwiVknzjGvNeex2YxE9e2PaOfmSJaZDyoYokFVWwsLdas9nY4lyZJsOIl2DrT9fXVL0L/yaAQY+KEM2otibnmmmsuun/t2rXVOX21eCuJOfnD36j2u/63+vWPJXhEM2QyGY4Fj3Pk5ZWg1BLzzi+Ubs2pNDi3gjJST/DIZmgTL3/g77+Vbt5M6sRn0Xa8A2X0mYrPqlg/9N2i0HeOROEn/mgItSPt8AEWTnsda5mJqGaJ3Pzi6+gCfLjFoA4p+P57st+eiv+gQcR/NtPb4VweSYI1b8LGD1xfh7WAa9+AViNATA4RqMUxMd5MUnyRo8SKYr8DkJMfk0/c9WcWeKqobaIMVhN8fSIB/RMwbsnEmlKMPd+Mukkg+g4RaFuHIFNUbzFlv759CRjcl+I/PkXb7ToCrnsA8+FCbBmlGDJOYFh6En3nSPz7xaKOFUX7hJoV17odt015m1/fnkL2iaPMe+15bnnpTTHY1wO8Xm6gKmQyGDwFQprAX6+7CkfO/Q806Q9D34LYzt6OUKgjqtQSM3nyZN588038/PyYPHnyhU8uk/HBBx9UK8Dq8EZLTNGG0xiXppBvziD+uasIPWvF2YL725G9yYl/787Ef3fpmUnVZc/P58SI63EYDEQ+8wzBt4+jbG8upbuysaUb3cdpmgfhf1Uj15gbufgUJNSc/LRUFvz3ZYwF+QRFRXPry2+JRQ2r6eSYmzEfPEijjz4icNhQb4dz5czF8Pd02PIZOCyADDrdAYNfcRWWFBqkGq1ivWfPHmzl1Wr37Nlz0UdDU7IrHYAc0iolMNjKsGS6EgdNu47ne6nHKcPCiHz2WQByP/0UR2E2/n1jiZrUhYjHOqHrGA5ysBw3kD/nINnTd2HcmoHT6qiV+ISGJywunttff5fgqBgM2VnMnfIs+Wkp3g6rzpLsdizHjgF1rCXmbNpAGPIaTNoJ7W8BJNj7E3zcFda+DRbjpc4gNGCi7IAHOUqsZPx3KzJkHIzYzdCnHj+zM/sgJ28aiblATaMZ0wkcXjurVkqSRMr4ezBt345f//7Ef/lFpdlQ9iIzxs2ZlG7PRDK7kheZTol/r2j8+8SiCBIzSQTPMxYWsOCtl8lPS0EbEMgtL75BVDMv1/upgyxHj3Ji5I3I9Xpa7tyBTF7tmr7el7bTNfA3davra/9oGPQydP4PyMUSDQ1FjbbECOdXdjAfGTLyLRlEtGtWaZ+UcwSLobzcQC1WmZXJZES/9hoylYrSjRspXrq00n5lsJbgEU2JeaEXwTc2RxGmRSqzU7Iujcx3dlAwLxl7gbnW4hUaBv+QUMa+No3o5omYS4r55Y0XSDu439th1TnucgMtW9aPBAYgrjvctxxuneMaM2PMgt8nwhcDXXWYBOEsHvmpN5vNbN++nSVLlvD7779XelTHhg0bGDlyJLGxschkMhYtWuSJcGuM+Zhr1dpM0wkatW5XaZ/18C4khxyZSo66cUKtxqVp1pSwRx8BIPvtqTgMhnOOkWsU+PeNJfqp7oSNa4O6aSA4JUx7csiesYuS9WlIjnNnUglCVekCArn1lf8S37YD1rIyfn17Cif37PR2WHWKxVfLDVSXTOYqTTBhu2ugryYIsvfB96Pgp7GQe8TbEQo+otpJzPLly0lISKB3797ceOONjB492v246aabqnXu0tJSOnXqxMyZvj9tUJIkzMddSUyhlEN4QuNK+y2HDgGgaRSKzAur1oY/8ADq5s1x5OeT/fbbFzxOJpehaxdO5MOdiJzYGXXTQCSbE8Oyk+R8sgfL6eJajFqo79Q6PTe98BrNuvbAbrOy6L03Sd6y0dth1RlnZibVXuturVJqoO8k+L890PNhkCvhyHL4rDf8+RSU5nk7QsHLqp3ETJo0iVtvvZXMzEycTmelh8NRvQGiw4cP56233qp2MlQbHAYLmJw4JQfqOH/k/+q7NR87BYC2RZPaDw6QqdXEvPkmyOUYFv+OYcmfl3yNOi6AiIc6EnJLInK9EluWidzP91K48CjOMnstRC00BCq1hhufeolWfQfgdDj486P32LdmpbfDqhPchR9b1bOWmH/zC4MR78JjW11ryUgO2PE1fNwFNn0ENtHl3VBVO4nJzs5m8uTJREVFeSKearFYLBQXF1d61BZbeikAxdZ8AmP+9f/C6aQsxdWFo+3Ss9Zi+jd91y6EP/ooAFmvvYY1Lf2Sr5HJZPh1jybqqe7ou0WBBKXbssj6YCelO7KQnPV2XLhQixRKJSMmPUXHwdchSU5WfvExu/5c5O2wfJo9Px9Hbh7IZGhbtvR2OLUjPBHu+BnG/wHRHcFSDKumwMwesP9X1yJ6QoNS7STmlltuYd26dR4IpfqmTp1KUFCQ+xEfH19r17aVT58utGYTHBVTaZ+Ufxxznut/ta73oFqL6XzCH30EXZcuOI1GMp55Bsl+eS0qCj8Vobe2JOKhDigjdDiNNgp/PUrOzCQsp84dYyMIV0ouVzDkwQl0HzkGgHXff83m+T9SjydQVov5sKsVRpUQj9yvgZUTaToAHloPo2dBQAwUpcCC+2D2UEjd7u3ohFpU7SnWJpOJW2+9lYiICDp06HBO7aT/+7//q1aAFWQyGQsXLmT06NEXPMZisWCxWNxfFxcXEx8fXytTrPP+dxDzgXz25K+m9QNDSex1prK3ZdVsTkx6H5kSWiXtQ6as9kLJ1WJNS+fk6NE4jUbCJ0wgYtLEK3q9ZHdi3JJB8V8pSBZXl6GuYzhBI5qiDNbWRMhCAyJJEtsXzefvud8D0HX4jVx99wP1Z/aNh+TP/oac994jYNgw4j760NvheI+1FDZ/Cps+BJvJta3dGNfaMyGNL/ZKwYfVWtmBn3/+mZUrV6LValm3bl2lNUhkMpnHkpjLodFo0Gi8s66JLcvVnVRkzSEoqvIKpGU7XOsdaOMCvZ7AAKjjGhH92mtkPP00ebNm4de3D/pu3S779TKlnID+cei7RFK88jSlO7Io+yePsoMFBAxoRMDV8cjVYj0HoWpkMhm9broNtU7Hmm+/YPey37GUmRj68KRzxpo1ZBXjYersIneeovaDq5+DrnfD2rdgz49w4Dc4/Cf0fgT6PwXaIG9HKdSQan+0eemll3j99dcxGAycOnWKkydPuh8nTpzwRIw+z2l14Mh3DSwzWHMJjq7cnVR2yDUdUNeqaa3HdiFBN1xP0KhR4HSS/swz5512fSkKfzUhYxKJnNQFddMgsDspWZNK9vRdlB0uqIGohYaky3Ujue6xJ5HJ5BxY9xd/fvguDrvN22H5DEvFGjG1uO6UTwuMgVEz4eEN0HSgq4TBpo9cg3+3fwUOMRmhPqp2EmO1Whk7dizyGmjqNRqNJCUlkZSUBMDJkydJSkoiJcW3lim357iaMMvsRhQBGtRaXaX9pqOuaYC6rt1rPbaLiXrlFVTx8dgzMsl4/gUkZ9XWgVHH+hPxUAdC72yDIkiDo8hC/ncHyP/xEI5iy6VPIPgMe5HZp8agtBs4mJGTn0ehVHJk2yYWvfcWNouYieK0WrGUf0hs8C0x/xbTEe5eDP/5BcJbgikflj4Ns/rCkRVi8G89U+3MY/z48cybN88TsZxj586ddOnShS5dugCuwpNdunRhypQpNXK9qrKVJzHFtnyCoysXLLOeOIK1yAkyCb8ho7wR3gUp/P1o9OEMZGo1xrVrKfjmmyqfSyaToe8QTtTkbvj3bwRyKNuXR9YHuzBuShezmOoAp9VB9kd7yPlkj2vJAB+R2LMvo597FaVGw6mkXfz69hQsplJvh+VV1mPHwG5HHhiIMibm0i9oaGQyaDkMHt0MI94HfRjkJcNPt8H/RkPWPm9HKHhItQdoOBwO3n33XVasWEHHjh3PGdg7ffr0Kp/76quv9qlPhRdizykDoMSWT/C/xsMYl/0KgD4KFI0Saz22S9G1a0fUSy+R9eqr5Mz4EG3Hjvj1rPo0cLlGQfD1zdB3iaRo4TGsqSUU/XGC0j05hNyUiLqRvwejFzzJtCcHqcyOU6dEHqD2djiVNOnYhVteeouF014j/fBBfnnjRW5+8Q30gQ1zrIN7kbtWrSqNQxT+RaGCng9Cx9tg4wewdZardMHn/aHLnTDoFQgQVdTrsmq3xOzbt48uXbogl8vZv39/pQrWFd1A9Z29oCKJKTxnenXpRtfqo35tffcXJfi2WwkadSM4HKQ/9RT23Nxqn1Md60/Eo50IHt0cmVaBLc1Izqd7KJiXjDVdVKX1NZIkYdzkWjfIv28sMrnvvTE2atWG216dii4wiJyTx5n36nNkHDlUJz7oeNqZcgNiPMxl0QbBtW/AxB2umUtIsOcHV6Xsde+4ZjgJdVK1W2LWrl3riTjqNHv5oF6jvYgWZw3qlRwOTIdc43f8el3+7J/aJpPJiH71VcwHD2I5eoz0p54m4ZvZ1Z5JJZPL8O8di65dOEVLTlC2NxfTnhxMe3JQNwkk4KpGaNuG+eQbZkNjOVqEPacMmUaBX3fvL1x5IZFNmnH76+8w/62XKchI4+dXniEgPIJWffrTqk9/opq1aBAtE2fKDYjxMFckpAnc+i30fhRWvAhpO2Dd27DrOxjwNHS63TXbSagzxMIL1SRJEvY8V0uM8V8tMZajR3FaHMiVTrTdB3orxMsi1+tp9NHHyPV6TNu3k/vxJx47tyJATdgdrYmc0Bld5wiQy7CeKib/h0NkvbeDkg1pooyBl1W0wvh1j0Ku9f4yABcTGhvHHW+8S5v+16DS6ijJy2XnH7/x44tPMvvxB9n48xxyTp2oty00kiRhOVxRbkC0xFRJfE+4fxXc8g0EJ0BJBvw5Gaa3gRUvQcFJb0coXKZqL3b3xhtvXHS/NwfhXu5iOdXhKLaS+fY2nJKTX09N5+Ev56APCgag4PvvyH77HfyizSQs/huCGtVIDJ5UvHQp6ZOfAiDymWcIve9ej3+ydRgsGLdmUrotE6fJlbzI1HL03aLw7xuLKkLv0esJF2fLMZE9fRfIIPrp7ijDdJd+kY+wWS2c2rOLw1s2cmL3duxnLXYZEhtHqz5X0apPf8Lj68+iZ7asLI5dfQ0oFLTavQu5l9bGqjdsZtj1LWz7AgorkhcZJA6FXg9Bs0EgFlqsdZf7/l3tJKZi5lAFm83GyZMnUSqVNG/enN27d1fn9NVSG0mM+XgReV/to8RWyIrsb3n8f7+53/TTH72H4rXbCO/mJOKHw64R83VA9jvvUvDttwAEXHcdMW+9hcLf802sks2BaU8uJZvSsWeb3Nu1rULw7xuLJjFEdDXVgsJFxyjdmom2TSjh49t5O5wqs5nNHN+9nSNb/ubEnh04bGfWlAmLS6BV3/606jOA0Fjf/zBxMSXr1pH2yKOoWzSn+ZIl3g6n/nA64dhfsP0L178VwlpAz4eg0x2grdmV34Uzam3F3j179pz34vfcc0+dqD5dXRVdSSW2AgJCw90JjORwULrLNY1P3zaxziQwAJHPPoMqrhHZU6dRsnw5lqNHifvkYzTNmnn0OjKVAr+e0eh7RGE5XoRxUwbmwwWYkwsxJxeijNDh3zcWfddI5Brf7uKoq5wmG6Zd2QD496vbb+4qrZbWfQfQuu8ArGUmju/cxuEtGzmVtJv8tBQ2//Ijm3/5kYgmzdxjaP49m7AusLhnJomuJI+Sy6HlUNcj7xjs+Mq1+m/+MVj2LKx+w5XI9HwIIhpIwc06oNotMReyb98+Ro4cyalTp2ri9JelNlpiipaexLghjSOGneRF53Dbq1MBMO3axek770KuctLyo3uRDXq+Rq5fk0y795D+xBPYc3KQ6/XETJ1K4LChNXpNe34Zxs0ZlO7MdtdlkmkU+PWIxr9PTJ3q6qgLSjakYVh6ElW0nsjHu9bLQbHmUiPHdmwlectGUvYl4XQ43PuimiWWt9BcRWB4pBejvHxpTz5JybLlRDw1mfAHH/R2OPWbpQT2znWt+JuXfGZ7s2ug18OuLidRCqNG1FpLzIUYDAYMVVjKvq5xFJ6ZmRQQFu7eXrLK1RzpH2tGFu9bK/VeLn3XLjT97VfSn5yMaccO0h9/nNKxYwkdf7fHW2UqKMN0BI9sTuDQxph25WDcnIE9rwzj3+kYN6WjSQxB3ykCXbswnx+A6uskh4RxcwbgaoWpjwkMgNbPn/ZXD6H91UMoKynm6PYtJG/ZSOr+f8g+cZTsE0fZ8MM3xLRsTes+/WnZ+yr8Q8O8HfYFuVtixPTqmqcJcK0z0+MB1/oy27+C5KVwYq3rEdzYta/LXaAP9Xa0DVK1W2I+/vjjSl9LkkRmZib/+9//GDhwID/99FO1AqyO2miJyf50D7Y0I39n/0ajoZ3pf8d4AI4PHYo1JZVG/QoI/Pgg+PnuH8VLkex2cj6Y7h4nA6Dr3o2QW28lYNgw5Nqaq1wtOSXMRwsxbsrAcqTwzA6lHF2bUPSdItC2CkWmEgPvrpRpXx4FPx5C7qck5vmeyFQN6xOlyVDEkW2bSd6ygbRDB84sRy+TEdW0OeHxTQiLiycsLoGwuHgCwyO9XknbWVZGcrfu4HTSYsN6VJF1o/WoXik8DTu+ht3fg7nItU2pcy2o1/MhiG7v1fDqi1ob2Nu0aeWihnK5nIiICAYNGsSLL76Iv7/3VmitjSQm462tOI02VqZ/R5e7bqLLsBuwnjrF8euGg1yi5b1qFM/8UyPXrm2lmzdT8L8fMK5f7xoEB8gDAwkaOZKQ28eiSazZFYlteWWUJeVg2puLPbfMvV2mUaBrF4a+cySa5sHIFPWzRcHTcj7fi/VUMQGD4gka2sTb4XiVsSCfI9s2kbx5IxlHDp33GKVaQ2hsnDuxCY2LJ6xRAsFR0cgVtZMAlv3zD6duG4siNJTETX/X29azOsFqgv0LYNuXkH1WGYPG/VzJTOsbQCFai6uq1rqTTp48/3z6tLQ0Jk+ezJdfflndS/gsyebAaXTNgCi1G9xN0MYNGwDQh1tRNO3ntfg8za9vX/z69sWWnY3ht98omr8AW0YGhT/+SOHPPxN2/32ET5qEXF0zS9arwnWohjQmYHACtoxSTHtzKdubi8NgwbQ7B9PuHOR+KnQdwwkYEIcypOZaiOo6a1oJ1lPFIJfh31vU3vEPDaPr8BvpOvxGivNyyTqWTH56KvlpqRSkpVCQkYbdaiHn1HFyTh2v9FqFUklIbBxhjc602oTFJRAcHYNCqbrAFavGXL4+jLa1KDfgdWo9dL0buoyDlC2uKdqH/oDTm1yPwEbQ/V7odi/4hV/6fEKV1NjA3r1799K1a1ccZw2iq2013RJTsb6GTbLy26kZ3Pn2DKKbJ3Lqrrso27mLyM4Gwh5/Gfo85vFr+wLJ6aR08xYKf/4Z4+rVAGhatiT23Xdqrb9eckpYTxe7Epp9uThLyxfNU8jw7xVDwKB4FP6+VQfIFxTMS8a0Jwd95whCbxdjKy7F6XBgyMkiPy2V/LSU8gSnPLmxnL9YplyhIDg6tjy5iSc0LoGwRvGExsahPE+iL0kSDrsdm8WMzWzGZjFjt1jcz20WM7nzfqF4+zY0PXui6dO7/JiK4y3u46zmytv1QcEMuPNeWvToXdP/qxq24gzY+Y1rBeDS8vItCjW0v9nVOtOoq1fDq0tqrTvpQhpCElN2KJ/8OQcptGazMv07Hp41B43VxrFrBoEk0WJkFqpJyyGhl8ev7WuKV60i69XXcBQUgEpFxMSJhN1/X7VLF1wJyeHEcqyIkg1pWI67BpXL1HL8r2pEwIA4MRC4nKPYSuY728EhETmhM+r4AG+HVGdJTifFebnkp6e4E5yCtFTy01OwlpWd9zUymZygqChUWl2lRMNqLkMq76atKa369GfQvQ+7F+QUaojdAgcWulpnMs5aK61Rd9esprajQSk+XF2MSGKo+SSm5O90DEtOkFqazJbc33nip4UU/e8HsqdOQxduocmwEng+FVQNo1vDnp9P5pRX3a0yus6diZ02FXWTJrUei/loIYYVp7CluYpNyvVKAgbG4983psENYP03w6rTlKxOQd04kMhHO3k7nHpJkiSMBfmupKa8Wyo/PYX81BTMpZcugCpXKFFpNai0OlQaLSqNBpVGg3XXHhQ2G0FXX402IhKVVuvaX/GvRvOv5zpUGg0H1v3Fjj9+Q3I60foHcM09D9HmqqtFl1RtSNvlWkBv/2/gLF+A0S/yTFdToOjOPR+RxFDzSUzRnycwbkwn2bCdo9JeHvn8e06NvZ2yvXuJ6mogdHAHuH+Fx6/ryyRJwrBoMdn//S9OoxGZTkfkU08RcsftyGpp8OPZsZgP5GNYeQp7jutTsTxQTeCgBPx6RCFTNLwZTZLNSea07ThLbYT+pzX6jhHeDqlBkSQJk6GI/LRUHHbbWQmH1pW0lD9XnKcF05qayvFrhyJTqWi1excy1ZWNt8k+cYwVX3xM7qkTADTt0p0hD0wgMFz8DNQKYw7smgM7Z0NJpmubXAltbnS1zsT3qlOLota0Gk9ixowZc9H9RUVFrF+/vl4nMfk/HaLsnzz25K/GEG5g7P896+pKkkGLG7NQDZnkKv/eANkyMsh48SVMW7cCoGnbhuhXXkH/rzIVtUFySpj25FC86jSOItf4BUWYlqBrG6PrGNGgShuU7symcMERFEEaop/tIWZy1SHFq1aRPun/0LRpQ7OFv1XpHA67nZ1//MaWBT/hsNtR63QMuPNeOg6+zuvTxxsMh801AHj7l64BwRWiO7qSmfY3g0os6nm5799V/qkNCgq66KNx48bcfffdVT19nVAxM6nMUYpfSAglf5V3o0TLUemckNDXm+F5lSo2loRvZhM15RXkgYFYDh7i9B3/IeOFF7Hn59dqLDK5DL9uUUQ/3Z3gkc2Q+6tw5JspmJtM5rTtFC05gTXdWG+rHleQJOlMteo+MSKBqWPOlBtoVeVzKJRKet10G+Pe/YTYlm2wlpXx19ef8cubL1KYme6pUIWLUaig/Ri4bzk8vNE1u0mphax/YPEEmN4WVr0KRSnejrROqLHuJF9Q0y0xWdN3Ys8pY23mz0T3a0vLDdsw7dzpmpXUpgyeOwXaII9ft66x5+eTM306hl9dnx7lAQFE/N//ubqYanHgbwWnxYFxczrGjenuKtoAyggd+s6R6DtH1MvyBpYTReR+uQ+ZSk7MCz2R6z07/VeoWakTJ2L8azWRzz9H2D33VPt8TqeDpBVL+fvnOdgsZpQqNX1vu5Nu14+utXVvhHKmAtjzP9j+NRjKkxeZHFpcCy2HQeK1EJzg3RhrmdfHxPiCmk5iMt7YgtNkZ1nabFoP6Uv4Ox+Wz0rKRpXYER5a5/Fr1mVlSUlkvfEm5oMHAdC0akX0Ky+j7+6dsgyS3Yn5SCGmpBzKDhaA/czMEHV8APrOEeg6RqAIqB+zCPK+P4j5YD5+vaIJualmFyYUPO/YkGuxpaWR8N23+PX23FRpQ042q776lNP/uIr5RjVLZNgj/0dE46aXeKXgcU4HHFnumtV0cn3lfeGtXMlMiyHQuC8oNd6JsZaIJIaaTWIku5P0lzcBsPD0R3Tv2IngOT+hjQ+gab9k6Pd4gx0PczGSw0HR/PnkzPgQZ3ltrZA77yTy2WeQa7z3S+k02yk7kI8pKQfLsSKo+K2Qg6ZFiCuhaRdWZ6tp2/PLyHp/J0gQNbkbqki9t0MSroDDaORI9x4AJG7ZjDIkxKPnlySJA+tXs+77r7CUliJXKOg5+lZ63TQW5RUOIBY8JDfZNXbm2F+Quh2ks8aXqvTQdIAroUm8FkKaeC3MmiKSGGo2ibEXWciath0nTuaffI9+2mCCtu0ioodEePNMGLcIml/j0WvWJ/bCQnKnz6Bo/nzA1SrTaPoHaJo393Jk4CixYvonF1NSLrbUEvd2mVqOrmMEfj2iUScE1KnpqUVLTmD8Ox1NyxAi7hO1Xeoa065dnL7zLpRRUSSuX1dj1zEWFrB69iyO7XANOA2LS2Dow/9HbEuxIKJXlRW5Ck4e/cuV1BizKu8PSzyrlaZfvVjWQyQx1GwSY00rIefTJMqcRn4/PZO+x9IJLjXT/Pps1CEqeO50vfhBqmnG9evJeOFFHAUFyHQ6ol96kaCbb/aZBMGeV4YpKQdTUi72vDOLlykj9fj1iELfJdLnVwR2Wuxkvr0dyeIg7N526FqJart1TcGPP5L95lv4DRxAwhdf1Pj1jmz9m9XffI7JUAQyGd1G3Ei/28ahqsFir8JlkiTI2gfHVrmSmtRt57bSNOl/JqkJrZvdgrVWO6mhclTMTLK5Fq7SWmzoEmNQB2RA44EigblM/gMH0nTRQjKff57SzVvIfPkVjJs2EfP66yhqqGjnlVCG6wgsr9dkPV1M6Y5syv7JxZ5jwvDnSQzLT6FrG4Zfj2g0LYJ9crq2aWc2ksWBMkKHNtGz3RBC7TgzM6l2WkRa9r6K+HYdWff91xzcsIZdfy7m2I6tXPvQJBp36FwrMQgXIJNBTEfXo/9T5a0061wtNMf+cq1Bc3SF6wEQ1sI1QDhxCDS+qt69N4kkpoqcJVYAzI5SkCTUdgdhXcvHdDS72nuB1UGqyEjiv/6a/Nmzyf3oY0qWLcf8zz5i33/PK+vKnI9MJkPTJAhNkyCcI5th2ptL6Y4sbGlGyvblUbYvD0WwBr/uUei7R6MM9o1Bd5JTwrg5AwD/vrE+mWQJl2ZOLk9iWld9evWV0gUEMnzCZFr3G8iqrz7FkJPNgrdepsOgoQy46z60fv61FotwEbpgaDfa9ZAkyD5wVivNVsg/5npsmwVKHTTt72qhaTEEwrzffV9dojupqudel0rx8lOcLNnH3szfuV4ZSJNOm5DZjPDwBogRy7lXRdnevaQ/9TS2tDRQKIiYNImwBx+o9dV+L5c1w0jpjixMe3KRzOXTtWWgSQzBr3sU6saBKALVXuseq6jvJdMqXdOqNb75/1G4MMnhILlbdySzmWZL/0TTrFmtx2AtM7Hx5zkkrfgTAL+QUIbc/5goKOnrzAY4sf5MUlOSUXl/aLPyVpproclVPrXInhgTQ80mMUVLT2LckEZZ1hYKkn6k7fMPEXD4RfCLgKeOgFj9ssocJSVkvfY6xX+6/mAqY2MIHD6cwBEj0LZt6zPjZc4m2RyUHcindHsWlhOGSvtkGgWqKD3KSD2qKD/X8yh9rSQ3uV/vw3KsCP8BjQgeUftvfkL1WU6c5MSIEci0Wlrt2unVhD7t0H5WfvExhZmuN0NRULIOkSTIOQhHV7m6nVK2gPPMOlkota5EpiKp8XIrjUhiqNkkpmDBEUw7s7EcXIj12ApavXcT8h2fQIfb4OavPHqthkiSJAwLF5E9dSrOkjMzhNSNGxN4/QgCR4xA06KFFyO8MHteGaU7syk7mIc9zwzO8/+KVU5u9Kgi9Sij/FAEeSa5sWWVkv3hbpBB9LM9UIbUr77whqJ42TLSn5yMtkMHms7/xdvhYLNa2LrgZ1FQsq4zF7vWojn2l6uVpjit8v6QpuWDg8tbadS1uyyDSGKo2SSmYuEwc9IPyEih+agSyN4HY76Cjrd59FoNmdNsxrhhA8VLl2FcuxbJYnHv07RsSeCIEQSOGI46wTdXs5TsTuz5ZdiyTdiyTdhzTNiySy+a3MgD1QRd1wR9l8hqvSkU/nqU0h1Z6DqEE3ZnmyqfR6gdktOJs6QER1GR62Ew4CgqonjZcoxr1xJ86y3EvPmmt8N0yz5xjBWff0Tu6ZOAKChZp0kS5B4ub6VZBae3nKm4DaDQQJN+Z7XStKjxYpUiiaFmk5icz/diPVVM2fYvCBzUgij7DEAGzxwDv3CPXktwcRhLMa5dS/HSpRj//htsZ37JtJ06Ejx6NIHDh6MIDvZekJfp/MmNyTWNuzy5UTcNJGRUC1TRfld8fkepjcyp28HuJOKRjmiaiPIXtUWSJJylpvJExJWQOA0G7EVnnrsSFUPlhKW4GJzOC543+tUphNxxRy1+J5cmCkrWU5YSOLnhTNeTIbXy/uDGZ1ppmvYH9ZX/jboUkcRQs0lM5nvbcORbMf09nYRn+6Pd/TrEdoWH1nr0OsL5OQwGSv76i+I/l1K6dav7j79MpcL/mmsIGj0a//5XIatjq41Kdiclf6dTsjoFyeYEuQz/q2IJHNz4igblFq9NoXjFaVSN/Imc2Fk081eR02x2t4ick3S4k5R/PTcYKiXYV0qu1yMPDkIRHIwiyPWvOi6O8EceQe7n+TcLT8hPS2XFFx+ReeQwAHFt2zP0oUmExDTycmRCtUmSa/XgY6tcSc3pzee20oxb6Gqp8SCRxFCzSUz6K+uRbHJsKT/RdLQJDi6Cgc/BNS969DrCpdlzczEs+RPDokVYyqeiAihCQwm84XqCR49G06ZNnXojtxeZKfrjBOYDrorfikA1QTc0Q9ch/JLfh+RwkvnODpzFVkJua4lf16jaCNmnSTabK/FwJx8GHIX/TkjOTVIks7nK15Sp1ZUSEdcj6Nxt5c/lFf+qfXvxxAtxFZT8k40/z8FusYiCkvWVxehqpTl7xtOzJzxe7FgkMdRcEiNJEukvbADkKAN3Es0HYC2BB1ZDnHeKGQou5sOHMSxchGHJEhz5+e7tmsREgkaPxq9vH9TNm9eZN4qywwUU/X4cR4HrzVSTGEzwqBaowi88FdKUlEPB3GTkASpinuuJTFl/mvUlpxNncfEFk47zt5YYcBqNVb+oQnHepONSyYlMq61TibOnGHKyWPnlp6TsSwLguseepN3Awd4NSqgZkgSGNAiO9/ipRRJDzSUxTouDjFc3AxDQcgdBKa+DfxRMPiymVvsIyWbDuGkThkWLMa5ejXR2875SiaZpUzQtW6Jp1QptK9e/yqgon3zTkWwOitelUbI+FewSKGQEDIwj8Jp4ZKpzP+Fmz0zCllpC4JAEAoc09kLEl+YaN1L6r6Tj3wnJmefOiuOKi11/OKtCJkMeGOhKOIKCz/r3X88rEpEQ13O5v79P/lz4MkmSOLDuL45s/ZvRz01BLhctMcKVEUkMNZfE2ArKyH53J5LDRkSbeWhT5kLXu+HGTzx2DcFzHAYDxcuWU7x8OeaDB3EWF5/3OHlQENryxEbTqiX+/fujio6u5WgvzJ5XRuHvx7EcKQRAEaoleGQzdG3C3MdYUorJ/WwvKGTEvNCzVuo6Oc3mM0lH0YW7Zv69Dbv90ie/ALlef24rSHmXjPKsrpmznysCA3120cT6SpIkkQAKVSJqJ9Uge7brTUSyGlHnrHNtbD3SY+e3mu0YcsrIzzCSm1JCQUYpVrMDu9WB5JTQBajRBajRB6rR+inR+qvQ+auJaBxAUIRO/NH4F0VQECG3jyXk9rFIkoQ9KwtzcjKW5CNYkpMxH0nGevIUToMB044dmHbscL1QJkPfuxfBo0cTMGSI1wdVKsN1hN/bDvOBfIr+cHUx5c85iLZtGMEjm6EM0WL8Ox0AfecrL0wpWa3njhu5jOTk7GnvV0qm0VxRF40iKAhFUBCyOtId2NCJv0VCTfP5lpiZM2fy3nvvkZWVRadOnfjkk0/o2bPnZb22plpiilfvo3hVEc6SdBIiHgZNEDxzFJRXXi+npMBMzqlick6XkJdaQl6aEVOxtcqx+QVraNQqmMjGgajUCuQKGXKlDIVSjlKlQKmWo1QrUKrkWEw2TMU2TMUWTAYrZpMdpVKOSqtApVWg1ipRaRQEReiIiA9Aoaq/XWVOiwXr8eOYk49gOXKEsqQkyvbsce+X6fUEXnstQaNHoe/Vy+vTR50WB8VrUjBuTAenhEwlx79fI0o2pIITwu5pjlxjOWdqr73SFN/KyYmztLTqASmV509ELpGcyHW+s8y5IAi+o160xMybN4/Jkyfz+eef06tXLz788EOGDRtGcnIykZGRXovLll0IyMBRvpJs25EXTWAkScJYaKEkvwxDrpmi7FIMuWZyU4opzjv/7AddgIrgKD2RCYGExfmh9VOh1CiQAWUlNkzFVspKrJhLbZhLbZQWWcg5XUJpkYUj27I5si3bo9+zXCkjIj6A6GZB5Y9A/II19eaTllyjQdu2Ldq2bd3brGlpGH7/HcPixdhOp2BYvBjD4sUoY2IIGjmSoNGjarSOjdNicSUXxcU4iotdz0tKcBiKcRQbcBS5umQkRxsgmpJ1rrUc7LnJnBr9UNUuKpOhCAw8M8X3QolIUOWERO7nV29+FgRBqDt8uiWmV69e9OjRg08//RQAp9NJfHw8kyZN4vnnn7/k62uqJSb7oz+xZQYi5W8mvtHbmMYtpTi8G3qNgmKDhfzjxRRmlFJWZKEkp4yibBM2i+O855LJZYQ18iOySSAR8QGEx/kTEuOHRnfl+aXN6iD7hIH0I0UUZpXisEs4HU6cDgmHzYnd5sRudWCzOnDYnKh1SvSBrm4pfYAarb8Kh13CarZjMzuwmu1Yy+zkZ5RiNp677oVKo8A/RINfsAb/EA3+IVr8gjXoA9WotQpUWqXrX03Fv4o6V0VZckqYTTaKtv9D/qoNFO78h9C0Xcgl13gObYcOBI0eReCIEShDQpAkCclsxmkynXmUVjwvdW+Tyv91lBhxFhvKExNXcuIsf34l3TTKuJ5o2t+KTBNA2ZZPcOQcQO7nd24iconkRB4QIMaNCILgdXV+YK/VakWv17NgwQJGjx7t3j5+/HiKiopYvHjxJc9RU0lM8urtlO5I46iljCRnFieMjQlzqAi3q4mwq5Fz7hu1EwmjykmZyolZJ2HRgUUPlhAI0Ufjp1GiUshRKmSoFDLUCgUalRytUo5GpUClkKNSyNCUf60rf7SKDkB7nhkqniRJEobcMrJPGMg6UUzWSQP5acYqTRJRahSoNZW7q1Taim1KlGo5MpkMmVyGTObqU5fJOPN1+b9U2n7Wse7X4V4Wu2JfxW1xbXYdJ0lgLbNTZrRSZrRhLn+4W7mMtnO+z5uGWnGsXIxx40ZwlCenSiVyjQanyVT12TPnUzGjpuIRFIg8MMj1/F/Jidw/CJkqAHVCmGvcSB1b6E8QBKFCne9OysvLw+FwEBVVeaGuqKgoDh8+fN7XWCwWLGd9ei2+wCyU6npt2wKuSrkOCCaOGOL+tb9Ql0VmwHFKtAUUaXMp0mVh0ObhlJ/bGiM5VRj3VL0eyuqnBtI8wr/Kr78cMpmM4Eg9wZF6WvWOAcBudWAstGAsNGMssmAstFBaaMFYZMFUbMVmtmOzOLCaHdjMdvf7ut3iwG5xQM3cmhqj1lUMoFahv6otwWOuw56fT/Gff2JYtNg16+lfs21kOp1r9dULPfz0yP38yxOTQBSBQWeeB7kSFbm/v9fH3wiCIPgqn01iqmLq1Km8/vrrNX4dp8KJTW7FpjBj0hRTqiuk2D+XIn0OuQEpmNSud2gJCafkRJIkNGjKv5aQkCj/D6VSzaThrSm12LE7JexOCavdicXuxGp3YrY7sNic2J1ObA4nZpsTs81R/nCiV3un6V+pVhAcpSc46tKVTSXJ1Z1lNTuwWezliY2ru8pmqfzcbnX9/5Ik1+twUulryXnWcwko/9rplED6176Kc1DeOCJJSFRsL38CaHRKtP5qdAEqtH4qV7ISoEbn73qu9VOhOM+CccqwMELvvpvQu+/Glp6OZLMh0+uR6/2Q67SiW0YQBKGG+WwSEx4ejkKhIDu78gDV7Oxsoi+wdscLL7zA5MmT3V8XFxcTH+/5lQR/euY9FHVsbIc3yWQy14wotQKon1NjVY1EjRhBEITa5rPt1Gq1mm7durF69Wr3NqfTyerVq+nTp895X6PRaAgMDKz0qAkigREEQRAE7/PZlhiAyZMnM378eLp3707Pnj358MMPKS0t5d577/V2aIIgCIIgeJlPJzFjx44lNzeXKVOmkJWVRefOnVm+fPk5g30FQRAEQWh4fHaKtSfU1BRrQRAEQRBqzuW+f/vsmBhBEARBEISLEUmMIAiCIAh1kkhiBEEQBEGok0QSIwiCIAhCnSSSGEEQBEEQ6iSRxAiCIAiCUCeJJEYQBEEQhDpJJDGCIAiCINRJIokRBEEQBKFOEkmMIAiCIAh1kk/XTqquiooKxcXFXo5EEARBEITLVfG+fanKSPU6iSkpKQEgPj7ey5EIgiAIgnClSkpKCAoKuuD+el0A0ul0kpGRQUBAADKZzGPnLS4uJj4+ntTUVFFY0oeI++KbxH3xXeLe+CZxX1wtMCUlJcTGxiKXX3jkS71uiZHL5cTFxdXY+QMDAxvsD5gvE/fFN4n74rvEvfFNDf2+XKwFpoIY2CsIgiAIQp0kkhhBEARBEOokkcRUgUaj4dVXX0Wj0Xg7FOEs4r74JnFffJe4N75J3JfLV68H9gqCIAiCUH+JlhhBEARBEOokkcQIgiAIglAniSRGEARBEIQ6SSQxVTBz5kyaNGmCVqulV69ebN++3dshNSgbNmxg5MiRxMbGIpPJWLRoUaX9kiQxZcoUYmJi0Ol0DBkyhKNHj3on2AZk6tSp9OjRg4CAACIjIxk9ejTJycmVjjGbzUyYMIGwsDD8/f25+eabyc7O9lLEDcOsWbPo2LGje82RPn36sGzZMvd+cU98w7Rp05DJZDzxxBPubeLeXJpIYq7QvHnzmDx5Mq+++iq7d++mU6dODBs2jJycHG+H1mCUlpbSqVMnZs6ced797777Lh9//DGff/4527Ztw8/Pj2HDhmE2m2s50oZl/fr1TJgwga1bt7Jq1SpsNhtDhw6ltLTUfcyTTz7JH3/8wfz581m/fj0ZGRmMGTPGi1HXf3FxcUybNo1du3axc+dOBg0axKhRozhw4AAg7okv2LFjB1988QUdO3astF3cm8sgCVekZ8+e0oQJE9xfOxwOKTY2Vpo6daoXo2q4AGnhwoXur51OpxQdHS2999577m1FRUWSRqORfv75Zy9E2HDl5ORIgLR+/XpJklz3QaVSSfPnz3cfc+jQIQmQtmzZ4q0wG6SQkBDp66+/FvfEB5SUlEiJiYnSqlWrpIEDB0qPP/64JEni9+VyiZaYK2C1Wtm1axdDhgxxb5PL5QwZMoQtW7Z4MTKhwsmTJ8nKyqp0j4KCgujVq5e4R7XMYDAAEBoaCsCuXbuw2WyV7k3r1q1JSEgQ96aWOBwO5s6dS2lpKX369BH3xAdMmDCB66+/vtI9APH7crnqde0kT8vLy8PhcBAVFVVpe1RUFIcPH/ZSVMLZsrKyAM57jyr2CTXP6XTyxBNP0K9fP9q3bw+47o1arSY4OLjSseLe1Lx9+/bRp08fzGYz/v7+LFy4kLZt25KUlCTuiRfNnTuX3bt3s2PHjnP2id+XyyOSGEEQPG7ChAns37+fv//+29uhCECrVq1ISkrCYDCwYMECxo8fz/r1670dVoOWmprK448/zqpVq9Bqtd4Op84S3UlXIDw8HIVCcc7o8OzsbKKjo70UlXC2ivsg7pH3TJw4kSVLlrB27dpKVeSjo6OxWq0UFRVVOl7cm5qnVqtp0aIF3bp1Y+rUqXTq1ImPPvpI3BMv2rVrFzk5OXTt2hWlUolSqWT9+vV8/PHHKJVKoqKixL25DCKJuQJqtZpu3bqxevVq9zan08nq1avp06ePFyMTKjRt2pTo6OhK96i4uJht27aJe1TDJEli4sSJLFy4kDVr1tC0adNK+7t164ZKpap0b5KTk0lJSRH3ppY5nU4sFou4J140ePBg9u3bR1JSkvvRvXt37rzzTvdzcW8uTXQnXaHJkyczfvx4unfvTs+ePfnwww8pLS3l3nvv9XZoDYbRaOTYsWPur0+ePElSUhKhoaEkJCTwxBNP8NZbb5GYmEjTpk155ZVXiI2NZfTo0d4LugGYMGECP/30E4sXLyYgIMDdbx8UFIROpyMoKIj777+fyZMnExoaSmBgIJMmTaJPnz707t3by9HXXy+88ALDhw8nISGBkpISfvrpJ9atW8eKFSvEPfGigIAA93ixCn5+foSFhbm3i3tzGbw9Paou+uSTT6SEhARJrVZLPXv2lLZu3ertkBqUtWvXSsA5j/Hjx0uS5Jpm/corr0hRUVGSRqORBg8eLCUnJ3s36AbgfPcEkL799lv3MWVlZdJjjz0mhYSESHq9XrrpppukzMxM7wXdANx3331S48aNJbVaLUVEREiDBw+WVq5c6d4v7onvOHuKtSSJe3M5RBVrQRAEQRDqJDEmRhAEQRCEOkkkMYIgCIIg1EkiiREEQRAEoU4SSYwgCIIgCHWSSGIEQRAEQaiTRBIjCIIgCEKdJJIYQRAEQRDqJJHECIIgCIJQJ4kkRhCEWnP11VfzxBNPuL9u0qQJH374YY1eMz8/n8jISE6dOgXAunXrkMlk5xTW86Tnn3+eSZMm1dj5BUFwEUmMIAiV3HPPPchkMmQyGSqViqZNm/Lss89iNps9fq0dO3bw0EMPefy8Z/vvf//LqFGjaNKkSY1e52xPP/00c+bM4cSJE7V2TUFoiEQSIwjCOa677joyMzM5ceIEM2bM4IsvvuDVV1/1+HUiIiLQ6/UeP28Fk8nE7Nmzuf/++2vsGucTHh7OsGHDmDVrVq1eVxAaGpHECIJwDo1GQ3R0NPHx8YwePZohQ4awatUq9/78/HzuuOMOGjVqhF6vp0OHDvz888+VzlFaWsrdd9+Nv78/MTExfPDBB+dc5+zupFOnTiGTyUhKSnLvLyoqQiaTsW7dOgAKCwu58847iYiIQKfTkZiYyLfffnvB72Pp0qVoNJqLVv01mUwMHz6cfv36UVRU5I5j7ty59O3bF61WS/v27Vm/fn2l1x04cIAbbriBwMBAAgIC6N+/P8ePH3fvHzlyJHPnzr3gdQVBqD6RxAiCcFH79+9n8+bNqNVq9zaz2Uy3bt34888/2b9/Pw899BDjxo1j+/bt7mOeeeYZ1q9fz+LFi1m5ciXr1q1j9+7d1YrllVde4eDBgyxbtoxDhw4xa9YswsPDL3j8xo0b6dat2wX3FxUVce211+J0Olm1ahXBwcGV4n/qqafYs2cPffr0YeTIkeTn5wOQnp7OgAED0Gg0rFmzhl27dnHfffdht9vdr+/ZsydpaWnusTiCIHie0tsBCILge5YsWYK/vz92ux2LxYJcLufTTz9172/UqBFPP/20++tJkyaxYsUKfvnlF3r27InRaGT27Nn88MMPDB48GIA5c+YQFxdXrbhSUlLo0qUL3bt3B7jkOJfTp08TGxt73n1ZWVmMHTuWxMREfvrpp0pJGsDEiRO5+eabAZg1axbLly9n9uzZPPvss8ycOZOgoCDmzp2LSqUCoGXLlpVeX3Hd06dP1+p4HEFoSEQSIwjCOa655hpmzZpFaWkpM2bMQKlUut/QARwOB2+//Ta//PIL6enpWK1WLBaLe3zL8ePHsVqt9OrVy/2a0NBQWrVqVa24Hn30UW6++WZ2797N0KFDGT16NH379r3g8WVlZWi12vPuu/baa+nZsyfz5s1DoVCcs79Pnz7u50qlku7du3Po0CEAkpKS6N+/vzuBOR+dTge4uqsEQagZojtJEIRz+Pn50aJFCzp16sQ333zDtm3bmD17tnv/e++9x0cffcRzzz3H2rVrSUpKYtiwYVit1ipfUy53/TmSJMm9zWazVTpm+PDhnD59mieffJKMjAwGDx5cqUXo38LDwyksLDzvvuuvv54NGzZw8ODBK461IkG5mIKCAsA1eFkQhJohkhhBEC5KLpfz4osv8vLLL1NWVgbApk2bGDVqFHfddRedOnWiWbNmHDlyxP2a5s2bo1Kp2LZtm3tbYWFhpWP+reLNPjMz073t7EG+Zx83fvx4fvjhBz788EO+/PLLC56zS5cuF0xSpk2bxvjx4xk8ePB5j9m6dav7ud1uZ9euXbRp0waAjh07snHjxnOSrLPt378flUpFu3btLniMIAjVI5IYQRAu6dZbb0WhUDBz5kwAEhMTWbVqFZs3b+bQoUM8/PDDZGdnu4/39/fn/vvv55lnnmHNmjXs37+fe+65x93acj46nY7evXszbdo0Dh06xPr163n55ZcrHTNlyhQWL17MsWPHOHDgAEuWLHEnFuczbNgwDhw4cMHWmPfff58777yTQYMGcfjw4Ur7Zs6cycKFCzl8+DATJkygsLCQ++67D3CNlykuLub2229n586dHD16lP/9738kJye7X79x40b69+9/Wa02giBUjUhiBEG4JKVSycSJE3n33XcpLS3l5ZdfpmvXrgwbNoyrr76a6OhoRo8eXek17733Hv3792fkyJEMGTKEq6666qIzhQC++eYb7HY73bp144knnuCtt96qtF+tVvPCCy/QsWNHBgwYgEKhuOg05g4dOtC1a1d++eWXCx4zY8YMbrvtNgYNGlSppWjatGlMmzaNTp068ffff/P777+7Z0KFhYWxZs0ajEYjAwcOpFu3bnz11VeVxsjMnTuXBx988KLfryAI1SOTzu6AFgRBqGf+/PNPnnnmGfbv33/RlqAKp06domnTpuzZs4fOnTtX6ZrLli3jqaee4p9//kGpFPMnBKGmiN8uQRDqteuvv56jR4+Snp5OfHx8rVyztLSUb7/9ViQwglDDREuMIAjCWTzREiMIQu0QSYwgCIIgCHWSGNgrCIIgCEKdJJIYQRAEQRDqJJHECIIgCIJQJ4kkRhAEQRCEOkkkMYIgCIIg1EkiiREEQRAEoU4SSYwgCIIgCHWSSGIEQRAEQaiTRBIjCIIgCEKd9P8mESCQ+or4JwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot luminosity per isophote vs radius for each galaxy\n",
    "def calcLum(r, sb, dis, totallum, i):\n",
    "    return (206265 ** 2) * 10 ** (0.4 * (3.26 - sb - 5)) * np.pi * (r * 1000) ** 2\n",
    "\n",
    "def logistic_curve(x, L, k, x0):\n",
    "    return L / (1 + np.exp(-k * (x - x0)))\n",
    "\n",
    "for i in range(len(galaxies)):\n",
    "    radius = df3[\"Radius2\"].tolist()[i]\n",
    "    sb = df3[\"SB\"].tolist()[i]\n",
    "    dis = df3[\"Dist\"].tolist()[i]\n",
    "    totallum = df3[\"L[3.6]\"].tolist()[i]\n",
    "    reff = df3[\"Reff\"].tolist()[i]\n",
    "    lum = [calcLum(radius[j], sb[j], dis, totallum, i) for j in range(len(radius))]\n",
    "    plt.plot(radius, lum, label=galaxy_legend[i])\n",
    "plt.legend()\n",
    "plt.xlabel(\"Radius (kpc)\")\n",
    "plt.rcParams['text.usetex'] = True\n",
    "plt.ylabel(\"Luminosity per Isophote ($L_{\\odot}/mag/arcsec^2$)\")\n",
    "plt.rcParams['text.usetex'] = False\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[5510963104.078839, 0, 0, 0, 0, 0, 0]\n",
      "[5510963104.078839, 1456974213199.5332, 0, 0, 0, 0, 0]\n",
      "[5510963104.078839, 1456974213199.5332, 202445775.71710795, 0, 0, 0, 0]\n",
      "[5510963104.078839, 1456974213199.5332, 202445775.71710795, 396629770330.2939, 0, 0, 0]\n",
      "[5510963104.078839, 1456974213199.5332, 202445775.71710795, 396629770330.2939, 16767131547.94067, 0, 0]\n",
      "[5510963104.078839, 1456974213199.5332, 202445775.71710795, 396629770330.2939, 16767131547.94067, 652730227690.3295, 0]\n",
      "[5510963104.078839, 1456974213199.5332, 202445775.71710795, 396629770330.2939, 16767131547.94067, 652730227690.3295, 483011769811.8597]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot luminosity vs radius for each galaxy\n",
    "added_luminosities = [0] * 7\n",
    "def calcLum(r, sb, dis, totallum, i):\n",
    "    global added_luminosities\n",
    "    added_luminosities[i] += (206265 ** 2) * 10 ** (0.4 * (3.26 - sb - 5)) * np.pi * (r * 1000) ** 2\n",
    "    return added_luminosities[i]\n",
    "\n",
    "def logistic_curve(x, L, k, x0):\n",
    "    return L / (1 + np.exp(-k * (x - x0)))\n",
    "\n",
    "l = []\n",
    "\n",
    "for i in range(len(galaxies)):\n",
    "    radius = df3[\"Radius2\"].tolist()[i]\n",
    "    sb = df3[\"SB\"].tolist()[i]\n",
    "    dis = df3[\"Dist\"].tolist()[i]\n",
    "    totallum = df3[\"L[3.6]\"].tolist()[i]\n",
    "    reff = df3[\"Reff\"].tolist()[i]\n",
    "    lum = [calcLum(radius[j], sb[j], dis, totallum, i) for j in range(len(radius))]\n",
    "    print(added_luminosities)\n",
    "    l.append(lum)\n",
    "    plt.plot(radius, lum, label=galaxy_legend[i])\n",
    "df3[\"Lum2\"] = l\n",
    "plt.legend()\n",
    "plt.xlabel(\"Radius (kpc)\")\n",
    "plt.rcParams['text.usetex'] = True\n",
    "plt.ylabel(\"Luminosity ($L_{\\odot}$)\")\n",
    "plt.rcParams['text.usetex'] = False\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ku0z4ewK3E29jbmzOp+0+pUv1LoYOS5IkZFIkSZJUZgKiA5h0aBIJmQk4WTixqvMq6trXNXRYkiT9SyZFkiRJZeDXW78y7595qLVq6tnXY2XnlThZOD35iZIklRmZFEmSJJUirdCy6sIqvr38LQBdq3dlUbtFmBubGzgySZIeJ5MiSZKkUpKlyWLO8Tnsu7MPgFENRjGx2USUCrnDkiQ9j+Q7U5IKsWHDBl5++eWnfv7w4cOfuE1Ix44dmTx5cqFlPDw8+OKLL3RfKxQKfvnll6eOq6QU5f6KYtOmTXpbt6xdu5ZevXo9c72GlJyVzLt/vcu+O/swVhozv818JvtMlgmRJD3H5LvzBTd8+HAUCgWLFy/WO/7LL7/o9tvKJYTg22+/pXXr1tjY2GBlZUX9+vWZNGkSN2/e1CublJTEnDlz8Pb2xszMDBcXF7p27crOnTsRQqBWq5k5cyYNGzbE0tISV1dXhg4dmmcT2YCAALp164adnR329vaMHTtWt+N8rr///ps2bdpgbW2Ni4sLM2fO1G06m+vPP/+kVatWWFtb4+joyJtvvsmdO3cKfW0yMjKYO3cu8+bN0x37+OOPUSgUdO/ePU/5pUuXolAo6Nixo+7Yl19+qdu/7Hmza9cuWrVqha2tLdbW1tSvX/+JydnjSuv+Ro4cSUBAAMeOHSvxusvCg7QHjNg3gjNRZ7AwtmBNlzW8Xvt1Q4clSdITyKRIwszMjCVLlhS6e7oQgkGDBjFx4kReeeUV9u/fT1BQEBs2bMDMzIwFCxboyiYkJNCmTRu2bNnC7NmzCQgI4OjRo/Tv358ZM2aQmJhIWloaAQEBzJ07l4CAAHbu3ElwcDC9e/fW1XP//n26du1KrVq1OH36NPv27ePq1asMHz5cV+bixYu88sordO/enQsXLrBjxw727Nmjt+lpaGgoffr0oXPnzgQGBvLnn3/y8OFD3njjjUJfl59//hkbGxvatm2rd7xKlSocOnSIe/fu6R3fuHEj1atX1ztma2ur1wLyvPj777/p378/b775JmfOnOH8+fMsXLgQtVpdrHqedH9ZWVlPFZ9KpWLQoEF5NiYuD+4k3mHIH0MIjg/G3swe/+7+tHaVG+pKUrlQqruwVSAVeUPYnj17Cm9vbzF9+nTd8V27dultCLtt2zYBiN27d+dbj1ar1f3/3XffFZaWliIiIiJPueTkZKFW57+p5ZkzZwQgwsLChBBCrFu3Tjg5OeltyHrp0iUBiBs3bgghhJg9e7Zo3ry5Xj179uwRZmZmIikpSQghxE8//SSMjY316tmzZ49QKBQiKysr/xdGCPHqq6+KadOm6R2bN2+eaNy4sejZs6dYsGCB7viJEyeEg4ODePfdd0WHDh10xx/fnDUlJUUMGTJEWFpaChcXF/H555/n2VQ2Ojpa9OzZU5iZmQkPDw/x/fffC3d3d7FixQpdGR7Z0FUIIcLDw0Xfvn2Fra2tqFSpkujdu7duQ9z8TJo0SXTs2LHA84/e69q1a0XVqlWFubm56Nu3r0hISCjw/jp06CDGjx8vJk2aJOzt7XXXWLZsmWjQoIGwsLAQVatWFe+++65ITk7WPc/f31/Y2trqXf/IkSNCpVKJtLS0fON7Ht93l2IuiXbb2okGmxqIV/77ighPCjd0SJL0wivOhrCypai0CAFZqWX/eIr9fY2MjFi0aBErV67M0/qRa9u2bXh5eem15Dwqt6tNq9Wyfft2Bg8ejKura55yVlZWGBvnP74/MTERhUKha3nIzMxEpVKhVP7vx9TcPGfGzvHjx3VlHt8M1NzcnIyMDM6fPw+Aj48PSqUSf39/NBoNiYmJfPfdd3Tt2hUTE5OCXhaOHz9e4DYXI0eO1Os22rhxI4MHD0alUhVYH8D06dM5cuQIu3fvZv/+/Rw+fJiAgAC9MsOHD+fu3bscOnSIn3/+mTVr1hATE1NgnWq1Gj8/P6ytrTl27BgnTpzAysqK7t27F9hS4+LiwtWrV7ly5Uqh8d68eZMff/yRX3/9lX379nHhwgX+85//FPqczZs3o1KpOHHiBGvXrgVAqVTy1VdfcfXqVTZv3szBgweZMWNGofU0b96c7OxsTp8+XWi558Wxe8cYtX8U8Znx1LOvx5YeW6hmXc3QYUmSVAwv1Oyz119/ncOHD9OlSxd+/vnn0r2YOg0W5U0KSt0H90FlWeynvf766zRp0oR58+axYcOGPOdDQkLw8tLfgmDy5MmsX78eADs7O+7du8fDhw+Jj4/H27t4u3pnZGQwc+ZMBg4cqNvFuHPnzkyZMoWlS5cyadIkUlNTdd1ikZGRAPj5+fHFF1+wbds2+vXrR1RUFPPnz9crU6NGDfbv30+/fv1455130Gg0tG7dmr179xYYT0JCAomJifkmdgA9e/Zk3LhxHD16FB8fH3788UeOHz/Oxo0bC6wzJSWFDRs28P3339OlS84Kxps3b6Zq1aq6MiEhIfzxxx+cOXOGFi1aADmDvevWLXiBvx07dqDValm/fr0uOfX398fOzo7Dhw/nO1D8vffe49ixYzRs2BB3d3datWrFyy+/zODBgzE1NdWVy8jIYMuWLbi5uQGwcuVKXn31VZYtW4aLi0u+8dSuXZvPPvtM79ijY5U8PDxYsGAB48aNY82aNQXel4WFBba2toSFhRVY5nmx++Zu5v0zD43Q0Ma1DSs6rsDCxMLQYUmSVEwvVEvRpEmT2LJli6HDeG4tWbKEzZs3c+3atSKVnzNnDoGBgXz00Ue6wc/iKVqq1Go1/fr1QwjB119/rTtev359Nm/ezLJly7CwsMDFxYUaNWrg7Oysaz16+eWXWbp0KePGjcPU1JQ6derwyiuvAOjKREVFMWbMGIYNG8bZs2c5cuQIKpWKt956q8B409PTAfK0QuUyMTHh7bffxt/fn59++ok6derQqFGjQu/z1q1bZGVl4evrqztWuXJlvWTz2rVrGBsb4+Pjozvm7e1d6LidixcvcvPmTaytrbGyssLKyorKlSuTkZHBrVu38n2OpaUlv//+Ozdv3uTDDz/EysqKqVOn0rJlS9LS0nTlqlevrkuIAFq3bo1WqyU4OLjAeB6NPddff/1Fly5dcHNzw9ramiFDhhAbG6t3rfyYm5s/sYyhbbqyiQ9PfIhGaOjp2ZNVnVfJhEiSyqkXqqWoY8eOHD58uGwuZmKR02pT1p7hl3H79u3x8/Nj9uzZeoOZIeev/8c/CB0dHXF0dMTJyUnvmJ2dHdevXy/SNXMTorCwMA4ePKhrJco1aNAgBg0aRHR0NJaWligUCpYvX46np6euzJQpU3j//feJjIykUqVK3Llzh9mzZ+vKrF69GltbW73Wi++//55q1apx+vRpWrVqlScue3t7FApFoYPPR44cia+vL1euXGHkyJFFut/SkJKSgo+PD1u3bs1zztHRsdDn1qxZk5o1azJ69GjmzJlDnTp12LFjByNGjHjqeCwt9Vsq79y5Q8+ePXn33XdZuHAhlStX5vjx44waNYqsrCwsLAr+mY2Li3viPRiKEIKVF1bqFmUcXn847/u8L6fcS1I5Vm7evUePHqVXr164uroWuEbL6tWr8fDwwMzMDF9fX86cOVP2geZSKHK6scr68dg0+uJavHgxv/76KydPntQ7PnDgQIKDg9m9e3ehz1cqlQwYMICtW7fmmV4POR/gudPlcxOiGzdu8Ndff2Fvb19gvc7OzlhZWbFjxw7MzMzo1q2b3nmFQoGrqyvm5uZs27aNatWq0axZMwDS0tL0xiVBzjgqyBkDlR+VSkW9evUICgoqMKb69etTv359rly5wqBBgwosl6tmzZqYmJjojZGJj48nJCRE97W3tzfZ2dm68VAAwcHBJCQkFFhvs2bNuHHjBk5OTtSqVUvvYWtr+8S4cnl4eGBhYUFqaqruWHh4uN738dSpUyiVyjxdqYU5f/48Wq2WZcuW0apVK+rUqZPvz8bjbt26RUZGBk2bNi3ytcqKVmhZeHqhLiGa1GwSU5tPlQmRJJVz5eYdnJqaSuPGjVm9enW+53fs2MGUKVOYN28eAQEBNG7cGD8/v0IHqEp5NWzYkMGDB+eZCj1gwADeeustBgwYwPz58zl9+jR37tzhyJEj7NixQ5dkACxcuJBq1arh6+vLli1bCAoK4saNG2zcuJGmTZuSkpKCWq3mrbfe4ty5c2zduhWNRkNUVBRRUVF6g4NXrVpFQEAAISEhrF69mgkTJvDpp5/qdSctXbqUy5cvc/XqVT755BMWL17MV199pYvp1Vdf5ezZs8yfP58bN24QEBDAiBEjcHd3L/QD18/PTzeguyAHDx4kMjKySNPuraysGDVqFNOnT+fgwYNcuXKF4cOH6yVsXl5edO/enXfeeYfTp09z/vx5Ro8erRtgnp/Bgwfj4OBAnz59OHbsGKGhoRw+fJiJEycWOHD+448/ZsaMGRw+fJjQ0FAuXLjAyJEjUavVegmnmZkZw4YN4+LFixw7doyJEyfSr1+/AscT5adWrVqo1WpWrlzJ7du3+e6773QDsAtz7NgxPD09qVmzZpGvVRbUWjUfHP+AHcE7UKBgbqu5jG442tBhSZJUEkp5Jlyp4LHpyEII0bJlSzF+/Hjd1xqNRri6uopPP/1Ur9yhQ4fEm2+++cRrZGRkiMTERN3j7t27FXZK/qNTqoUQIjQ0VKhUKvH4j4dGoxFr164Vvr6+wtLSUqhUKuHp6SnGjBkjgoKC9MomJCSIWbNmidq1awuVSiWcnZ1F165dxa5du4RWqxWhoaECyPdx6NAhXT1DhgwRlStXFiqVSjRq1Ehs2bIlzz106tRJ2NraCjMzM+Hr6yv27t2bp8y2bdtE06ZNhaWlpXB0dBS9e/cW165dK/S1uXr1qjA3N9ebgp47Tb0gkyZNKnRKfnJysnj77beFhYWFcHZ2Fp999lmeKfmRkZHi1VdfFaampqJ69epiy5YtT5ySHxkZKYYOHSocHByEqamp7vtS0BTUgwcPijfffFNUq1ZN9/3p3r27OHbsWJ57XbNmjXB1dRVmZmbirbfeEnFxcQXe3+P3kmv58uWiSpUqwtzcXPj5+YktW7YIQMTHxwsh8p+S//LLL+d5/z7KEO+7jOwMMeGvCaLBpgaiyeYm4vdbv5fZtSVJejrFmZJfIZKizMxMYWRklCdRGjp0qOjdu7fesaImRfPmzcv3A7uiJUVS4d566y2xaNEiQ4dhEE9KAEvTlStXhJOTk15C+riyft+lZKWIkftGigabGgif73zE4fDDZXJdSZKezQu3TtHDhw/RaDQ4OzvrHXd2diYqKkr3ddeuXenbty979+6latWqecbNPGr27NkkJibqHnfv3i21+KXn19KlS7GysjJ0GC+cyMhItmzZUqwxUaUpISOB0X+O5kzUGSxNLPm669d0qNbB0GFJklTCXqjZZ3/99VeRy5qamuqt1yK9mDw8PHjvvfcMHcYLp2vXroYOQScmLYax+8dyK/EWdqZ2rO26lvoO9Q0dliRJpaBCtBQ5ODhgZGREdHS03vHo6OhiDQiVJOl/Pv74YwIDAw0dhkGFJoYy9I+h3Eq8hZO5E5u6b5IJkSRVYBUiKVKpVPj4+PD333/rjmm1Wv7++29at362jRhXr15NvXr1dKsLS5L0Yrj44CJD/xhKREoE1a2rs7nHZmraPV8z4SRJKlnlpvssJSWFmzdv6r4ODQ0lMDCQypUrU716daZMmcKwYcNo3rw5LVu25IsvviA1NfWZFqEDGD9+POPHjycpKem5Gd8gSVLpOnz3MNOPTCdDk0ED+was6rIKe/OC19GSJKliKDdJ0blz5+jUqZPu6ylTpgAwbNgwNm3aRP/+/Xnw4AEfffQRUVFRNGnShH379uUZfC1JklSY/4b8l/mn5qMVWl5ye4llHZbJbTsk6QVRbpKijh07PnFfrQkTJjBhwoQyikiSpIpECMHai2tZczFnk9rXar3GR60/wkRpYuDIJEkqK+UmKZIkSSot2dpsFpxawH9v/BeAMQ3H8F7T91A847Y5kiSVLzIpeoLVq1ezevVqNBqNoUORJKkUpGenM+PIDA7fO4xSoeSDlh/Q37u/ocOSJMkAKsTss9I0fvx4goKCOHv2rKFDkQxgyJAhLFq0yNBhFEvHjh2ZPHnyM9ezdu1aevXq9ewBPcfiM+IZvX80h+8dxtTIlOUdl8uESJJeYDIpesENHz4chULB4sWL9Y7/8ssveboOhBB8++23tG7dGhsbG6ysrKhfvz6TJk3SmxkIkJSUxJw5c/D29sbMzAwXFxe6du3Kzp07dWPDPv74Y7y9vbG0tKRSpUp07dpVbwf5w4cPo1Ao8n3kl6TevHkTa2vrPJuzXr16lTfffBMPDw8UCgVffPFFkV6bixcvsnfvXiZOnKg7VlIJR3kwcuRIAgICOHbsmKFDKRVhSWEM/WMolx5cwkZlw7cvf0uX6l0MHZYkSQYkkyIJMzMzlixZQnx8fIFlhBAMGjSIiRMn8sorr7B//36CgoLYsGEDZmZmLFiwQFc2ISGBNm3asGXLFmbPnk1AQABHjx6lf//+zJgxg8TERADq1KnDqlWruHz5MsePH8fDw4OXX36ZBw8eANCmTRsiIyP1HqNHj6ZGjRo0b95cLz61Ws3AgQNp165dntjT0tLw9PRk8eLFxVrMc+XKlfTt27dY23xkZWXlOabRaNBqtUWuw9CEEGRnZ6NSqRg0aBBfffWVoUMqUUIIdt/cTd9f+3In6Q4uli5s6bGFpk5NDR2aJEmGVpqbsFUkhW0oV543hB02bJjo2bOn8Pb2FtOnT9cd37Vrl3j0x2Pbtm0CELt37863Hq1Wq/v/u+++KywtLUVERESecsnJyUKtVudbR+5r/Ndff+V7PisrSzg6Oor58+fnOTdjxgzx9ttv57vb+qMe322+INnZ2cLW1lb89ttvescf3wXe3d1dzJ8/XwwZMkRYW1uLYcOG6WLYvXu3qFu3rjAyMhKhoaEiIyNDTJ06Vbi6ugoLCwvRsmVLcejQIb36v/nmG1G1alVhbm4uXnvtNbFs2TK9+3l8V3ohhJg0aZLo0KFDgTFu2bJF+Pj4CCsrK+Hs7CwGDhwooqOjdecPHTokALF3717RrFkzYWJioovryJEjQqVSibS0tCe+ZmXtad53iZmJYvrh6aLBpgaiwaYGYsS+ESI6NfrJT5Qkqdx64TaEfR4JIUhTp5X5Qzxh2YL8GBkZsWjRIlauXMm9e/fyLbNt2za8vLzo3bt3vudzu9q0Wi3bt29n8ODBuLq65ilnZWWFsXHe8f1ZWVl888032Nra0rhx43yvsWfPHmJjY/MsyHnw4EF++uknVq9eXeh9FselS5dITEzM0yKVn88//5zGjRtz4cIF5s6dC+S0Ti1ZsoT169dz9epVnJycmDBhAidPnmT79u1cunSJvn370r17d27cuAHAiRMnGDduHJMmTSIwMJBu3bqxcOHCZ74XtVrNJ598wsWLF/nll1+4c+cOw4cPz1Nu1qxZLF68mGvXrtGoUSMAmjdvTnZ2tl63ZnkVGBNI3z19+ePOHxgpjJjUbBLfdvsWJwsnQ4cmSdJzQs4+e4KnnX2Wnp2O7w++pRRVwU4POv1UC829/vrrNGnShHnz5rFhw4Y850NCQvDy8tI7NnnyZNavXw+AnZ0d9+7d4+HDh8THx+Pt7V2k6/72228MGDCAtLQ0qlSpwoEDB3BwcMi37IYNG/Dz86Nq1aq6Y7GxsQwfPpzvv/8eGxubot7uE4WFhWFkZIST05M/MDt37szUqVN1Xx87dgy1Ws2aNWt0CV54eDj+/v6Eh4frksVp06axb98+/P39dUlpjx49mDZtGpDTvfjPP//w22+/PdO9jBw5Uvd/T09PvvrqK1q0aEFKSope1+D8+fPp1q2b3nMtLCywtbUlLCzsmWIwpGxtNt9e/pZ1F9ehERqqWlVlSfslNHJsZOjQJEl6zsiWoid4kWafLVmyhM2bN3Pt2rUilZ8zZw6BgYF89NFHpKSkABS7papTp04EBgbyzz//0L17d/r160dMTEyecvfu3ePPP/9k1KhResfHjBnDoEGDaN++fbGu+yTp6emYmpoWaZ2a/FqTVCqVrrUF4PLly2g0GurUqYOVlZXuceTIEW7dugVAcHAwLVu21Kvn8a+fxvnz5+nVqxfVq1fH2tqaDh06ADmJ2pPuA8Dc3Jy0tLRnjsMQIlMiGfXnKNYErkEjNPT07MlPvX6SCZEkSfmSLUWlxNzYnNODyr7LwdzY/Kmf2759e/z8/Jg9e3ae7pXatWsTHBysd8zR0RFHR0e91hRHR0fs7Oy4fv16ka5paWlJrVq1qFWrFq1ataJ27dps2LCB2bNn65Xz9/fH3t4+T/fdwYMH2bNnD59//jmQk5RptVqMjY355ptv9FpJisPBwYG0tDSysrJQqVRPvIfHmZub6yVUKSkpGBkZcf78eYyMjPTKFmcgt1KpzJN4qtXqAsunpqbi5+eHn58fW7duxdHRkfDwcPz8/PIMCs/vPgDi4uJwdHQscozPi/139vPxyY9JzkrG0sSSOb5z6FWzYi8xIEnSs5FJUSlRKBTlcr+kxYsX06RJkzxdZQMHDmTQoEHs3r2bPn36FPh8pVLJgAED+O6775g3b16ecUUpKSmYmZnlO64IcsYkZWZm6h0TQuDv78/QoUMxMdHfcuHkyZN6XZu7d+9myZIl/PPPP7i5uRXpnvPTpEkTAIKCgnT/fxZNmzZFo9EQExOT7ww5AC8vrzwtko9/7ejoyJUrV/SOBQYG5nldcl2/fp3Y2FgWL15MtWrVgJx9BIvq1q1bZGRk0LRp+ZmZlaZOY8nZJey8sROARg6NWNx+MdWsqxk4MkmSnney+0zS07BhQwYPHpxnGvaAAQN46623GDBgAPPnz+f06dPcuXOHI0eOsGPHDr3Wj4ULF1KtWjV8fX3ZsmULQUFB3Lhxg40bN9K0aVNSUlJITU3lgw8+4NSpU4SFhXH+/HlGjhxJREQEffv21bv2wYMHCQ0NZfTo0XnirVu3Lg0aNNA93NzcUCqVNGjQgEqVKgE5g7gDAwMJDAwkKyuLiIgIAgMD86yt9ChHR0eaNWvG8ePHn+Xl1KlTpw6DBw9m6NCh7Ny5k9DQUM6cOcOnn37K77//DsB7773H3r17Wb58OTdu3GDdunX88ccfei1OnTt35ty5c2zZsoUbN24wb968PEnSo6pXr45KpWLlypXcvn2bPXv28MknnxQ57mPHjuHp6UnNmjWf/ubL0N2ku/T/rT87b+xEgYIxDcewqccmmRBJklQkMimS8pg/f36edXUUCgU7duzgiy++YO/evXTp0gUvLy9GjhxJtWrV9JKHypUrc+rUKd5++20WLFhA06ZNadeuHdu2bWPp0qXY2tpiZGTE9evXefPNN6lTpw69evUiNjaWY8eOUb9+fb1rb9iwgTZt2hR58Pbj7t+/T9OmTWnatCmRkZF8/vnnNG3aNN8k61GjR49m69atT3XN/OS2dk2dOhUvLy9ee+01zp49S/Xq1QFo27Yta9euZfny5TRu3Jh9+/bx/vvvY2ZmpqvDz8+PuXPnMmPGDFq0aEFycjJDhw4t8JqOjo5s2rSJn376iXr16rF48WJdV2NRbNu2jTFjxjz9TZehWwm3GLZvGHeS7uBk4cQGvw1MbDZRbugqSVKRKcTTzOF+ASUlJWFra0tiYmKeWU4ZGRmEhoZSo0YNvQ8wqXxLT0/Hy8uLHTt20Lp1a4PEMGbMGK5fv26QVaWvXr1K586dCQkJwdbWtsyv/ySPvu/upN1h7P6xxGfGU8uuFt++/C0O5vnPYpQk6cVS2Of34+SYoieQG8K+uMzNzdmyZQsPHz4ss2t+/vnndOvWDUtLS/744w82b97MmjVryuz6j4qMjGTLli3PZUL0qOC4YN498i7JWcnUs6/Huq7rsDOzM3RYkiSVQ7KlqIhkS5FUFvr168fhw4dJTk7G09OT9957j3Hjxhk6rOdSRkYG129e56NrHxGaFkoTxyas6boGa5W1oUOTJOk5IluKJKmc+vHHHw0dQrmRmpVKXHocGdkZ+Fbx5atOX5XLGZ+SJD0/5EBrSZLKnaTMJCJTIxEImrs0Z3WX1TIhkiTpmcmWIkmSypWEzAQikiMQCMyMzZjdcjamRqaGDkuSpApAJkWSJJUb8Rnx3E+5D4CNygYjUyNMjOSUe0mSSobsPpMkqVyITY/VJUSVzCrhZOFUpL3pJEmSikomRZIkPfcepD0gKjUKAHtze6pYVpEJkSRJJU4mRU+wevVq6tWrR4sWLQwdiiS9cIQQRKdGE5MWA4CjhSPOFs4yIZIkqVTIpOgJxo8fT1BQUJ6NOSVJKn2xGbE8TM9ZPNPZ0ll2mUmSVKpkUiRJhZg7dy5jx441dBh8/PHHNGnSpMTqO3z4MAqFgoSEhGeqJysrCw8PD86dO1cygT0iVZ1KdGo0kJMQyW07JEkqbTIpesENHz4chULB4sWL9Y7/8ssvef4iF0Lw7bff0rp1a2xsbLCysqJ+/fpMmjQpz47zSUlJzJkzB29vb8zMzHBxcaFr167s3LmT/BZRHzduHAqFgi+++ELv+MKFC2nTpg0WFhbY2dnleV5sbCzdu3fH1dUVU1NTqlWrxoQJE0hKStIrt3XrVho3boyFhQVVqlRh5MiRxMbGFvraREVF8eWXXzJnzhy91+u1114r9HnPSqFQ8Msvv+gdmzZtGn///XepXvdpqFQqpk2bxsyZM0u0XrVWzb3kewDYmtpib2ZfovVLkiTlRyZFEmZmZixZsoT4+PgCywghGDRoEBMnTuSVV15h//79BAUFsWHDBszMzFiwYIGubEJCAm3atGHLli3Mnj2bgIAAjh49Sv/+/ZkxYwaJiYl6de/atYtTp07h6uqa57pZWVn07duXd999N9+4lEolffr0Yc+ePYSEhLBp0yb++usvva0xTpw4wdChQxk1ahRXr17lp59+4syZM0/c/X39+vW0adMGd3f3QsuVBSsrK+ztn6/EICsrC4DBgwdz/Phxrl69WiL1CiG4l3yPbG02psamclC1JEllR0hFkpiYKACRmJiY51x6eroICgoS6enpumNarVZoUlPL/KHVaot1X8OGDRM9e/YU3t7eYvr06brju3btEo/+eGzbtk0AYvfu3fnW8+h13333XWFpaSkiIiLylEtOThZqtVr39b1794Sbm5u4cuWKcHd3FytWrMi3fn9/f2Fra1uke/ryyy9F1apVdV8vXbpUeHp66pX56quvhJubW6H11K9fX6xatUrv2LBhw0SfPn0KfM7ly5dF9+7dhaWlpXBychJvv/22ePDgge58hw4dxHvvvSemT58uKlWqJJydncW8efN0593d3QWge7i7uwshhJg3b55o3Lix3rU2bNgg6tWrJ1QqlXBxcRHjx48XQggRGhoqAHHhwgVd2fj4eAGIQ4cOCSGEOHTokABEfHy8EEKIhw8figEDBghXV1dhbm4uGjRoIH744Qe963Xo0EGMHz9eTJo0Sdjb24uOHTvqznXq1El8+OGHhbyaRReVEiWuPLgigh4GiQx1RoHl8nvfSZIkPa6wz+/HycUbS4lITye4mU+ZX9cr4DwKi+Jtd2BkZMSiRYt0LUFVq1bNU2bbtm14eXnRu3fvfOvI/Uteq9Wyfft2Bg8enG/Lj5WVle7/Wq2WIUOGMH36dOrXr1+smAty//59du7cSYcOHXTHWrduzQcffMDevXvp0aMHMTEx/Pzzz7zyyisF1hMXF0dQUBDNmzcv8rUTEhLo3Lkzo0ePZsWKFaSnpzNz5kz69evHwYMHdeU2b97MlClTOH36NCdPnmT48OG0bduWbt26cfbsWZycnPD396d79+4YGRnle62vv/6aKVOmsHjxYnr06EFiYiInTpwocqyPy8jIwMfHh5kzZ2JjY8Pvv//OkCFDqFmzJi1bttSL/d13381zrZYtW3Ls2LGnvn6upMwk3cBqVytXTI3lStWSJJUd2X0mAfD666/TpEkT5s2bl+/5kJAQvLy89I5NnjwZKysrrKysdInUw4cPiY+Px9vb+4nXXLJkCcbGxkycOPGZ4x84cCAWFha4ublhY2PD+vXrdefatm3L1q1b6d+/PyqVChcXF2xtbVm9enWB9YWHhyOEyDexK8iqVato2rQpixYtwtvbm6ZNm7Jx40YOHTpESEiIrlyjRo2YN28etWvXZujQoTRv3lw3XsjR0REAOzs7XFxcdF8/bsGCBUydOpVJkyZRp04dWrRoweTJk4sc6+Pc3NyYNm0aTZo0wdPTk/fee4/u3bvn2aC2du3afPbZZ3h5een9PLi6uhIWFvbU1wfI0mQRkRIBQGXzytia2j5TfZIkScUlW4pKicLcHK+A8wa57tNasmQJnTt3Ztq0aUUqP2fOHCZMmMDOnTtZtGgRQL6DqPNz/vx5vvzySwICAkpkvMiKFSuYN28eISEhzJ49mylTprBmzRoAgoKCmDRpEh999BF+fn5ERkYyffp0xo0bx4YNG/KtLz09HcgZb1VUFy9e5NChQ3qtYblu3bpFnTp1gJyk6FFVqlQhJiamyNeJiYnh/v37dOnSpcjPeRKNRsOiRYv48ccfiYiIICsri8zMTCwea3X08cm/9dPc3Jy0tLSnvr5WaLmbfBet0GJuYo6zhfNT1yVJkvS0ZFL0BKtXr2b16tVoNJpiPU+hUBS7G8vQ2rdvj5+fH7Nnz2b48OF652rXrk1wcLDeMUdHRxwdHXFyctI7Zmdnx/Xr1wu91rFjx4iJiaF69eq6YxqNhqlTp/LFF19w586dYsXu4uKCi4sL3t7eVK5cmXbt2jF37lyqVKnCp59+Stu2bZk+fTqQk5RYWlrSrl07FixYQJUqVfLU5+CQM/07Pj6+wNaax6WkpNCrVy+WLFmS59yj1zAx0d+rS6FQoNVqi3yv5k9IfJXKnAbgRxNUtVpd6HOWLl3Kl19+yRdffEHDhg2xtLRk8uTJusHUuSwtLfN9flxcXJFfp/xEpUaRkZ2BkdKIalbVUCpkI7YkSWVP/uZ5ghdt8cbFixfz66+/cvLkSb3jAwcOJDg4mN27dxf6fKVSyYABA9i6dSv379/Pcz4lJYXs7GyGDBnCpUuXCAwM1D1cXV2ZPn06f/755zPdQ26CkZmZCUBaWpouUciVO1anoJatmjVrYmNjQ1BQUJGv26xZM65evYqHhwe1atXSexSUTOTHxMSk0CTc2toaDw+PAqfo5yYnkZGRumOBgYGFXvPEiRP06dOHt99+m8aNG+Pp6anX5fckV65coWnTpkUu/6ikzCTiM3JmPla1qio3eJUkyWBkS5Gkp2HDhgwePJivvvpK7/iAAQPYuXMnAwYMYPbs2fj5+eHs7ExYWBg7duzQGxC8cOFCDh8+jK+vLwsXLqR58+aYmJhw7NgxPv30U86ePYu9vX2eKeYmJia4uLjojVUJDw8nLi6O8PBwNBqN7sO9Vq1aWFlZsXfvXqKjo2nRogVWVlZcvXqV6dOn07ZtWzw8PADo1asXY8aM4euvv9Z1n02ePJmWLVsWOGZIqVTStWtXjh8/nmddosTExDxJhr29PePHj+fbb79l4MCBzJgxg8qVK3Pz5k22b9/O+vXrCxw0/bjchKdt27aYmppSqVKlPGU+/vhjxo0bh5OTEz169CA5OZkTJ07w3nvvYW5uTqtWrVi8eDE1atQgJiaGDz/8sNBr1q5dm59//pl//vmHSpUqsXz5cqKjo6lXr16RYj527BiffPJJkco+SqPVEJmak7w5mDtgpcrb9ShJklRmSnkmXIVR3Cn55UV+U8xDQ0OFSqUSj/94aDQasXbtWuHr6yssLS2FSqUSnp6eYsyYMSIoKEivbEJCgpg1a5aoXbu2UKlUwtnZWXTt2lXs2rWrwGUD8puSP2zYML0p6rmP3KnlBw8eFK1btxa2trbCzMxM1K5dW8ycOVM31TzXV199JerVqyfMzc1FlSpVxODBg8W9e/cKfW327t0r3NzchEajeWI8o0aNEkIIERISIl5//XVhZ2cnzM3Nhbe3t5g8ebLunjt06CAmTZqkd50+ffqIYcOG6b7es2ePqFWrljA2Ni50Sv7atWuFl5eXMDExEVWqVBHvvfee7lxQUJBo3bq1MDc3F02aNBH79+8vdEp+bGys6NOnj7CyshJOTk7iww8/FEOHDtX72cgvdiGE+Oeff4SdnZ1IS0sr9PXMz/2U++LKgysiJC5EaLSaJz/hEeX5fSdJUtkpzpR8hRBFHBn7gktKSsLW1pbExERsbGz0zmVkZBAaGkqNGjWKNTBXer4JIfD19eX9999n4MCBhg7nudW/f38aN27MBx98UKznpWenczvhNgDuNu7FbiWS7ztJkoqisM/vx8kxRZJUAIVCwTfffEN2drahQ3luZWVl0bBhQ95///1iPU8Iwf2UnDFntqa2sttMkqTnghxTJEmFaNKkSYluxFrRqFSqJ45Xyk9cRhwZ2RkoFUqcLeX0e0mSng+ypUiSpDKl1qiJSctZl8nZwhkTpZxtJknS80EmRZIklamotKicRRqNzalklndmnSRJkqHIpEiSpDKTnJVMUmYSkLO3WUmsZi5JklRSZFIkSVKZ0Aqtbk0ie3N7zIzljDFJkp4vMimSJKlMPEh7gFqjxkRpgqP5028JIkmSVFpkUiRJUqnLyM4gNj0WABdLF4yURVvdW3p+7bsSSVxq1pMLSlI5IpOiJ1i9ejX16tWjRYsWhg5Feg5lZWVRq1Yt/vnnH0OHUiwKhYJffvnlmesZMGAAy5YtK7SMRqvhfup9BAJrlTU2poUvniY9/9Yfu8247wMYueks6VnF2yxbkp5nMil6goq+IWzHjh2ZPHlynuObNm3Czs5O71hSUhJz586lfv36mJubY29vT4sWLfjss8+Ij4/XK3vz5k1GjBhB1apVMTU1pUaNGgwcOJBz587pysTFxTF48GBsbGyws7Nj1KhRpKSk6NVz6dIl2rVrh5mZGdWqVeOzzz7TO3/16lXefPNNPDw8UCgUfPHFF3nuJTk5mcmTJ+Pu7o65uTlt2rTJ8/3cuXMnL7/8Mvb29igUiiduoJpr7dq11KhRgzZt2uiOlVTCUR58+OGHLFy4kMTExHzPp2SlcCvhFunqdJQKJVUsq5RxhFJJEkLw6d5rLPj9GgDN3Sthaiw/RqSKQ/40S0USFxdHq1at8Pf3Z9q0aZw+fZqAgAAWLlzIhQsX+OGHH3Rlz507h4+PDyEhIaxbt46goCB27dqFt7c3U6dO1ZUbPHgwV69e5cCBA/z2228cPXqUsWPH6s4nJSXx8ssv4+7uzvnz51m6dCkff/wx33zzja5MWloanp6eLF68GBcXl3xjHz16NAcOHOC7777j8uXLvPzyy3Tt2pWIiAhdmdTUVF566SWWLFlS5NdECMGqVasYNWpUkZ8DoFar8xzLyipf3RC58TZo0ICaNWvy/fff653XaDXcT7lPWFIYaq0aEyMTqttUx8RIrklU3mRlazl5K5aNx0MZseks647mbM0yq4c3c16ti1IpZxBKFUip7sJWgVTUDWEL2uTT399f2Nra6r5+5513hKWlpYiIiMi3ntwNT7Varahfv77w8fHR20g1V+4GpEFBQQIQZ8+e1Z37448/hEKh0F1jzZo1olKlSiIzM1NXZubMmcLLyyvfGPLbUDYtLU0YGRmJ3377Te94s2bNxJw5c/LUERoaKgBx4cKFfK/xqLNnzwqlUimSkpL0jgNi165devVt375dtG/fXpiamgp/f3/dRrwLFiwQVapUER4eHkIIIcLDw0Xfvn2Fra2tqFSpkujdu7cIDQ3V1a1Wq8V7770nbG1tReXKlcWMGTPybNya3+vQuHFjMW/evHxjFEKIGTNmiNq1awtzc3NRo0YN8eGHH4qsrCzd+dwNab/99lvh4eEhFAqF7tz//d//iZdeekn3dXJmsgiODRZXHlwRVx5cERHJESJbk/3E17O4yvP7rryITkoXfiuOCPeZv+keNWb9JnacCTd0aJJUZMXZEFa2FJUSIQTqTE2ZP0Qp7O+r1WrZsWMHb7/9Nq6urvmWyV1vJjAwkKtXrzJ16lSUyrw/XrldcidPnsTOzo7mzZvrznXt2hWlUsnp06d1Zdq3b49KpdKV8fPzIzg4OE93XUGys7PRaDR5Ngw1Nzfn+PHjRaqjIMeOHaNOnTpYW1s/seysWbOYNGkS165dw8/PD4C///6b4OBgXUuZWq3Gz88Pa2trjh07xokTJ7CysqJ79+66lpklS5awdetW/P39OXHiBElJSSXSVWdtbc2mTZsICgriyy+/5Ntvv2XFihV6ZW7evMl///tfdu7cqde92LJlS86cOUNaelqe1iEPGw9crVzlwOpy6H5COv3XneJ6VDK25iZ0q+fMpC612fWftvRrUc3Q4UlSqZB7n5WS7Cwt30w6UubXHftlB0xMS/YD6MGDByQkJODl5aV33MfHh+DgYAB69erFtm3buHHjBgDe3t6F1hkVFYWTk5PeMWNjYypXrkxUVJSuTI0aNfTKODs7685VqvTk1ZCtra1p3bo1n3zyCXXr1sXZ2Zlt27Zx8uRJatWq9cTnFyYsLKzAJPFxkydP5o033tA7Zmlpyfr163VJ3/fff49Wq2X9+vW6JNPf3x87OzsOHz7Myy+/zMqVK5k9ezavv/46AKtWrWLv3r3PdB+A3v5lHh4eTJs2je3btzNjxgzd8aysLLZs2YKjo/50eldXV7Kysjgdchont5zvaSWzSjhbOMtkqJwKi01l0LeniUhIp2olc34Y3Yrq9haGDkuSSp1MiqSntmvXLrKyspg5cybp6ekApdJS9ay+++47Ro4ciZubG0ZGRjRr1oyBAwdy/vz5Z6o3PT09TwtUQR5tEcvVsGFDvVawixcvcvPmzTwtTxkZGdy6dYvExESio6Np2bKl7pyRkRE+Pj5otdqnvIscO3bs4KuvvuLWrVukpKSQnZ2NjY3+LDF3d/c8CRFAOjnf++TUZNyM3HCzdMNSZflM8UiGk5aVzQj/s0QkpOPpYMn3o31xtTM3dFiSVCZkUlRKjFVKxn7ZwSDXLQ4bG5t8Zw4lJCRga2sLgKOjI3Z2drpWoVzVq1cHclpjEhISAKhTpw4A169fp2nTpgVe18XFhZiYGL1j2dnZxMXF6QZMu7i4EB0drVcm9+uCBlXnp2bNmhw5coTU1FSSkpKoUqUK/fv3x9PTs8h15MfBwYHLly8XqaylZd4k4fFjKSkp+Pj4sHXr1jxl80tGCqJUKvMkp/kN7s518uRJBg8ezP/93//h5+eHra0t27dvzzPV/vF4hRDEpMVwOzJn4K2nqyc1bWvK1qFy7pPfrnH7YSouNmZsf6cVTtZy5XHpxSHHFJUShUKBialRmT+Ku5eUl5cXAQEBeY4HBAToEhylUkm/fv34/vvvuX//fqH1NWnShHr16rFs2bJ8Wy9yk6fWrVuTkJCg11pz8OBBtFotvr6+ujJHjx7V+0A/cOAAXl5eReo6e5ylpSVVqlQhPj6eP//8kz59+hS7jkc1bdqU69evl1jrWLNmzbhx4wZOTk7UqlVL72Fra4utrS3Ozs56ywloNJo83z9HR0ciIyN1XyclJREaGlrgdf/55x/c3d2ZM2cOzZs3p3bt2oSFhRUaqxCCqNQoHqY/5Ma1G7i6udLAo4FMiMq5/Vej2HYmHIUClvdrLBMi6YUjk6IX3LvvvktISAgTJ07k0qVLBAcHs3z5crZt26Y3fX7RokW4ubnRsmVLNm7cyKVLl7h16xa7du3i5MmTGBnlfBgqFAr8/f0JCQmhXbt27N27l9u3b3Pp0iUWLlyoS0Tq1q1L9+7dGTNmDGfOnOHEiRNMmDCBAQMG6MbpDBo0CJVKxahRo7h69So7duzgyy+/ZMqUKbq4srKyCAwMJDAwkKysLCIiIggMDOTmzZu6Mn/++Sf79u0jNDSUAwcO0KlTJ7y9vRkxYoSuTFxcHIGBgQQFBQEQHBxMYGCgbnxTfjp16kRKSgpXr14tge9EzhIFDg4O9OnTh2PHjhEaGsrhw4eZOHEi9+7dA+C9997j008/Zffu3QQHBzNp0iTi4+P1kuHOnTvz3XffcezYMS5fvsywYcN035/81K5dm/DwcLZv386tW7f46quv2LVrV4HlhRDcT7lPXEYcANfOX6O7X/cSeQ0kw4lJzmDWzpyWzzHtPGlTy8HAEUmSAZTiLLgKpaJOyRdCiDNnzohu3boJR0dHYWtrK3x9ffWma+dKSEgQs2fPFt7e3sLU1FSYm5uLRo0aiblz54rY2Fi9ssHBwWLo0KHC1dVVqFQq4e7uLgYOHCgCAgJ0ZWJjY8XAgQOFlZWVsLGxESNGjBDJycl69Vy8eFG89NJLwtTUVLi5uYnFixfrnc+d8v74o0OHDroyO3bsEJ6enkKlUgkXFxcxfvx4kZCQoFePv79/vvU8Oo09P/369ROzZs3SO0Y+U/Ifn+KfOyX/cZGRkWLo0KHCwcFBmJqaCk9PTzFmzBjdz51arRYTJkwQNjY2olKlSmLmzJmib9++YsCAAbo6EhMTRf/+/YWNjY2oVq2a2LRp0xOn5E+fPl3Y29sLKysr0b9/f7FixQq9JRlyp+RrtBoRnhSum24fGR8pbG1txcmTJwt9nUpDeX/fPS+iE9PFl3+FCN+Ffwn3mb+JHl8cFRnqkl9CQZIMpThT8hVCPIcjY59DSUlJ2NrakpiYmGcAakZGBqGhodSoUaPIA2+liuHSpUt069aNW7duYWVlVebX12q11K1bl379+vHJJ5+U7rWElrvJd0nJSkGhUFDVqipbN25l165d7N+/v1SvnR/5vns2KZnZLPz9Gj+du0u2NudjwNnGlK2jfanl9ORlJiSpvCjs8/txcqC1JD2DRo0asWTJEkJDQ2nYsGGpXy8sLIz9+/fToUMHMjMzWbVqFaGhoQwaNKhUr6vRaribfJdUdSoKhYJq1tWwVlljYmLCypUrS/XaUskLCI/n/R2BhMWmAdDCoxJvt3KnewMXTI3luDDpxSWTIkl6RsOHDy+zaymVSjZt2sS0adMQQtCgQQP++usv6tatW2rXzNZmE54crtu/rLpNdSxNcmaijR49utSuK5U8IQRf/X2Trw7eQKMVuNmZ83nfxrSuaW/o0CTpuSCTIkkqR6pVq8aJEyfK7HrZ2mzCksLIyM7ASGGEu4075iZyzZrySKsVfLTnCt+fCgegTxNX5vdpgK253I9OknLJpEiSpHwJIbibfJeM7AyMlca427hjZizH7pRHWq1g7u4rbD2dM91+0esNGdiyuqHDkqTnjkyKJEnKV1xGHGnqNJQKJR42Hpgamxo6JOkpaLWCOb9c0a0/9PlbjXnTp6qhw5Kk55Jcp+gJVq9eTb169WjRooWhQ5GkMpOlySImLWfFcWcLZ5kQlWNL9l1n25lwlP8uyCgTIkkqmEyKnmD8+PEEBQXprSIsSRWZ+HdxRq3QYmFiQSWz4q8eLj0ffj5/j3VHc7ZhWfpWY15vKhMiSSqMTIokSdITnxmvm3rvauVa7K1jpOfD+bB4Pvh3heqJnWvJFiJJKgI5pkiSJB21Rk10as6mu04WTpgayW6z51GGWsOZ0Dgys7Vka7SotQIzYyU1HCypbm9BbEoW73x3niyNFr/6zkzuWsfQIUtSuSCTIkl6BllZWdSrV48tW7bQpk2bIj1HoVCwa9cuXnvttSKVP3z4MJ06dSI+Ph47O7unD/YJhBDcT83pNjM3McferOC1a4p7DwXp2LEjTZo04YsvvgCgVatWTJ8+nTfffPOZ6q3IEtPU9F33DyHRKfmeVyrAzMSItCwN3i7WLO/XBKVStvZJUlHI7rMXXMeOHZk8eXKe45s2bcrzAZyUlMTcuXOpX78+5ubm2Nvb06JFCz777DPi4+P1yt68eZMRI0ZQtWpVTE1NqVGjBgMHDuTcuXO6MnFxcQwePBgbGxvs7OwYNWoUKSn6v+iFEHz++efUqVMHU1NT3NzcWLhwoV6ZzMxM5syZg7u7O6ampnh4eLBx40bd+atXr/Lmm2/i4eGBQqHQfQAXZPHixSgUinxfl8etXbuWGjVq0KZNGzZt2oRCoSj0cefOHSIjI+nRo8cT6y6Ojz/+mCZNmjyxXFpaGrNnz6ZmzZqYmZnh6OhIhw4d2L17N4mZibotPFwtC+82K417APjwww+ZNWsWWq22xOuuCDLUGsZ8d46Q6BRszU1oUs2OFh6VaO1pT0M3W6xMjdEKSMvSYG+p4tuhzbE0lX/7SlJRyXeLVCRxcXG89NJLJCUl8cknn+Dj44OtrS3BwcH4+/vzww8/MH78eADOnTtHly5daNCgAevWrcPb25vk5GR2797N1KlTOXLkCJCzK3xkZCQHDhxArVYzYsQIxo4dyw8//KC77qRJk9i/fz+ff/45DRs2JC4ujri4OL3Y+vXrR3R0NBs2bKBWrVpERkbqfaimpaXh6elJ3759ef/99wu9z7Nnz7Ju3ToaNWr0xNdECMGqVauYP38+AP3796d79//tFv/GG2/QoEED3XkAR0fHQnesL23jxo3j9OnTrFy5knr16hEbG8s///xDzIMYolKjcmI0d3ziekQuLi6Fnler1ZiYFH9RwB49ejB69Gj++OMPXn311WI/vyLTagVTf7rImdA4rE2N2T62FXWr6O/jJITgYUoWd2JTca9sgZONXFdKkoql1LalrWAK22W3PO/W3aFDBzFp0qQ8x/39/fV2SX/nnXeEpaWliIiIyLcerVar+7d+/frCx8dHaDSaPOXi4+OFEEIEBQUJQJw9e1Z37o8//hAKhUJ3jaCgIGFsbCyuX79eYPx//PGHsLW1FbGxsU+6VSGEEO7u7mLFihX5nktOTha1a9cWBw4cKPB1edTZs2eFUqkUSUlJ+Z4vqA4e26H+xIkTonHjxsLU1FT4+PiIXbt2CUBcuHBBCCHEoUOHBCD++usv4ePjI8zNzUXr1q11r4u/v78A9B7+/v75xmRrays2bdqU53juzvc3428Kd3d3MX/+fDFgwABhYWEhXF1dxapVqwq8h9DQUAGI7du3i/bt2wtTU1Ph7+8vHj58KAYMGCBcXV2Fubm5aNCggfjhhx+e+BqNGDFCvP322/nG/6jy/L57Gp/8elW4z/xN1Prgd3HixgNDhyNJ5UZhn9+Pk91npUQIgTojo8wfQogSvxetVsuOHTt4++23cXV1zbdMbldLYGAgV69eZerUqSiVeX+8crvkTp48iZ2dHc2bN9ed69q1K0qlktOnTwPw66+/4unpyW+//UaNGjXw8PBg9OjRei1Fe/bsoXnz5nz22We4ublRp04dpk2bRnp6erHvc/z48bz66qt07dq1SOWPHTtGnTp1sLZ++h3Fk5KS6NWrFw0bNiQgIIBPPvmEmTNn5lt2zpw5LFu2jHPnzmFsbMzIkSOBnBaqqVOnUr9+fSIjI4mMjKR///751uHi4sLevXtJTk7WHUvMTCQpMwkFObPNAJYuXUrjxo25cOECs2bNYtKkSRw4cKDQe8ktd+3aNfz8/MjIyMDHx4fff/+dK1euMHbsWIYMGcKZM2cKradly5YcO3as0DIVjRCCyMR0jt94yOZ/7vDR7itM3HaB8VsDeOe7cwxef4r1x0OBnKn1bWo5GDhiSaqYZPdZKcnOzOSrYW+V+XUnbv4ZE7OSbTJ/8OABCQkJeHl56R338fEhODgYgF69erFt2zZu3LgBgLe3d6F1RkVF4eTkpHfM2NiYypUrExWV041z+/ZtwsLC+Omnn9iyZQsajYb333+ft956i4MHD+rKHD9+HDMzM3bt2sXDhw/5z3/+Q2xsLP7+/kW+x+3btxMQEFCs9ajCwsIKTBKL6ocffkChUPDtt99iZmZGvXr1iIiIYMyYMXnKLly4kA4dOgA5Ccirr75KRkYG5ubmWFlZYWxs/MRurW+++YbBgwdjb29P48aNadO2Db5+vjRu0Rh7C3vMjXP2NWvbti2zZs0CoE6dOpw4cYIVK1bQrVu3AuuePHkyb7zxht6xadOm6f7/3nvv8eeff/Ljjz/SsmXLAutxdXXl7t27aLXafBPriiQmOYMVB0L49WIkKZnZTyw/s7s3rzV1K4PIJOnFJJMi6ant2rWLrKwsZs6cqWuZKcmWKq1WS2ZmJlu2bKFOnZwpxRs2bNAlY15eXmi1WhQKBVu3bsXW1haA5cuX89Zbb7FmzRrMzZ+8eendu3d1LSFmxUgo09PTi1U+P8HBwTRq1EivnoIShkfHOVWpUgWAmJgYqlcv+h5W7du35/bt25w6dYp//vmH3//8nZVfrWTirIksX7hcV65169Z6z2vduvUTB6g/2uoHoNFoWLRoET/++CMRERFkZWWRmZmJhYVFofWYm5vrvvdF+f6VRxlqDRuOh7Lm0E1SszQAGCkVuNtbUNPRipqOVjhYqTAxUmKkVGCsVODhYIlvjcoGjlySKjaZFJUSY1NTJm7+2SDXLQ4bGxsSExPzHE9ISNAlGY6OjtjZ2elahXLlfhhbW1uTkJAAoEterl+/TtOmTQu8rouLCzExMXrHsrOziYuL07V2VKlSBWNjY12dAHXr1gUgPDwcLy8vqlSpgpubmy7W3DJCCO7du0ft2rWf+BqcP3+emJgYmjVrpjum0Wg4evQoq1atIjMzM9/B0Q4ODly+fPmJ9ZeURwcu53ZXPs0sLRMTE9q1a0cT3yb0HNWTdcvWsebzNXz28WeoVKqnjs/S0lLv66VLl/Lll1/yxRdf0LBhQywtLZk8eTJZWVmF1hMXF4elpWWFTIiEEOy5eJ/P9gUTkZDzh0TjqrbM7OFNc/fKqIwrdsuYJD3v5DuwlCgUCkzMzMr8UdzVh728vAgICMhzPCAgQJeMKJVK+vXrx/fff8/9+/cLra9JkybUq1ePZcuW5fuBnZs8tW7dmoSEBM6fP687d/DgQbRaLb6+vkBOF052dja3bt3SlQkJCQHA3d1dV+b+/ft6U/lDQkJQKpVUrVq0FXy7dOnC5cuXCQwM1D2aN2/O4MGDCQwMLHC2WNOmTbl+/foztY55eXlx+fJlMjMzdceeZksZlUqFRqMpcnmNVsP9lJzvZeOGjcnOziYjI0N3/tSpU3rlT506pUtIi+rEiRP06dOHt99+m8aNG+Pp6an7/hXmypUrhSbU5VV6loax351n0vZAIhLScbU148sBTdj1n7a0qekgEyJJeg7Id+EL7t133yUkJISJEydy6dIlgoODWb58Odu2bWPq1Km6cosWLcLNzY2WLVuyceNGLl26xK1bt9i1axcnT57UJQ4KhQJ/f39CQkJo164de/fu5fbt21y6dImFCxfSp08fIKc1p3v37owZM4YzZ85w4sQJJkyYwIABA3TjdLp27UqzZs0YOXIkFy5c4Pz587zzzjt069ZNl7ANGjQIe3t7RowYQVBQEEePHmX69OmMHDlS19KQlZWlS3aysrKIiIggMDCQmzdvAjktXQ0aNNB7WFpaYm9vT4MGDQp87Tp16kRKSgpXr1596td/0KBBaLVaxo4dy7Vr1/jzzz/5/PPPda9lUXl4eBAaGkpgYCAPHz7US7Ie1bFjR9atW8eBEwcIuxPGPwf/Yen8pXTq1Akbm/9N7z5x4gSfffYZISEhrF69mp9++olJkyYV695q167NgQMH+Oeff7h27RrvvPMO0dHRT3zesWPHePnll4t1refdw5RMBnx7igNB0aiMlUx7uQ5/T+1InyZucmFFSXqelOY0uIqkok7JF0KIM2fOiG7duglHR0dha2srfH199aaM50pISBCzZ88W3t7ewtTUVJibm4tGjRqJuXPn5pkSHxwcLIYOHSpcXV2FSqUS7u7uYuDAgSIgIEBXJjY2VgwcOFBYWVkJGxsbMWLECJGcnKxXT0REhHjjjTeElZWVcHZ2FsOHD89zrWvXromuXbsKc3NzUbVqVTFlyhSRlpamO587ZfzxR4cOHQp8TYoyJV8IIfr16ydmzZpVrDrIZ0p+o0aNhEqlEj4+PuKHH34QgG7Kfe6U/NzlDIQQ4sKFCwIQoaGhQgghMjIyxJtvvins7OwKnZK/YOEC4dPSR9hWshWmZqaihmcNMXHiRPHw4UNdGXd3d/F///d/om/fvsLCwkK4uLiIL7/8ssB7yH19c5cQyBUbGyv69OkjrKyshJOTk/jwww/F0KFDRZ8+fQp8je7duydMTEzE3bt3843/UeXlfXcrJlm0W3JQuM/8TTT+vz/FmdCiLR8hSVLJKM6UfIUQpTCHuwJKSkrC1taWxMREvb+oATIyMggNDaVGjRrPPPBWKl8uXbpEt27duHXrFlZWViVS59atWxkxYgSJiYklNq5GCEFSVhKRqZFotDndbE4WTjhaOOYp6+HhweTJk4u0ondJmzlzJvHx8XzzzTdPLFse3nfnw+IYvfkc8WlqqlU2Z9OIltR0LJmfE0mSiqawz+/HyYHWkvQMGjVqxJIlSwgNDaVhw4ZPVceWLVvw9PTEzc2NixcvMnPmTPr161diCZFaoyYyNZLkrJy1iUyNTXG1dMXCpPBZYIbg5OTElClTDB3GM8vM1vDjuXss+C2IzGwtjavasn5YCxyt5Qa7kvQ8k0mRJD2j4cOHP9Pzo6Ki+Oijj4iKiqJKlSr07ds3z/5uT0MIQXxGPNFp0WhFztIFDuYOOJg7oFQ8n8MJHx3HVh5lqDVsPxPOuqO3iUzMGbjeta4TXw1sioVK/rqVpOedfJdKkoHNmDGDGTNmlGidmdmZ3E+9T5o6DQBzE3NcLV2fuKcZwJ07d0o0lorkblwacalZWJoaY2VqjKWpEZYqY9LVGraeDuObo6E8TMkZ5O5sY8o77WsytLU7xkbPZxIqSZI+mRRJUgWiFVpi02N5kP4AIQRKhRInCycqm1Uu9nIN0v8kpqlZ8ud1fjgdnu95I6UCjTZneKabnTnvdqzJWz5VMTMx3Oa/kiQVn0yKJKmCSFenE5EaQWZ2TkuFlcqKKpZVUBk9/YKMLzohBL9eimT+r0G6FqAqtmakZmaTmqXRJUIarcDD3oL/dKrF603dMJEtQ5JULsmkSJLKOa3QEpMWQ2x6LABGSiNcLFywNbWVrUPPIDw2jQ93X+FoyAMAPB0tWfhaQ1rXtAdyEqbMbC2pmdlkZGtxsTHDSK45JEnlmkyKJKkcEkKQlp1GYmYiiZmJaEXO6uG2pra4WLpgrJRv7ael1mj59thtvvzrBpnZWlRGSsZ3qsW4jp6YGv+vO0yhUGBmYiS7yCSpApG/OSWpHMnIziAhM4HEzESytf/bVd3EyIQqllWwVlkbMLryL0OtYfzWAP6+nrMvX5ua9ix4rQGecm0hSXohvFBJ0W+//cbUqVPRarXMnDmT0aNHGzokSXqiLE1WTotQVqJuvBCAUqHExtQGW5UtliaWsqvsGaVlZTN2y3mO33yIqbGSha835M1mbvJ1laQXyAszGjA7O5spU6Zw8OBBLly4wNKlS4mNjTV0WNJzbsiQISxatKjI5e/cuYNCoSAwMBCAw4cPo1AodBvhbtq0CTs7uyfWk63NJi4jjtDEUG7E3yAmLYbM7EwUCgXWKmu0sVrqOdTjwc0HWKmsSuSDW6FQ8MsvvwDw8OFDnJycuHfv3jPXWx4kZ6gZvvEsx28+xEJlxKYRLXnLp6pMiCTpBfPCJEVnzpyhfv36uLm5YWVlRY8ePdi/f7+hwzK44cOHo1AoWLx4sd7xX375Jc8HghCCb7/9ltatW2NjY4OVlRX169dn0qRJus1VcyUlJTFnzhy8vb0xMzPDxcWFrl27snPnznx3lR83bhwKhYIvvvhCd+zOnTuMGjWKGjVqYG5uTs2aNZk3bx5ZWVm6Mh9//DEKhSLPw9LSUq/+L774Ai8vL8zNzalWrRrvv/++3q7w+bl48SJ79+5l4sSJumMdO3bM93rjxo0rtK5c/fv3L3CneK3QkpiZSHhSOCHxIUSmRJKmTmPOhDm8P+x9XK1cqVOpDtVtqlOvVj0iIyML3bD2WTg4ODB06FDmzZtXKvU/TxLSsnh7wxnO3InD2syY70b56gZTS5L0Yik3SdHRo0fp1asXrq6uen/RPmr16tV4eHhgZmaGr68vZ86c0Z27f/8+bm5uuq/d3NyIiIgoi9Cfe2ZmZixZsoT4+PgCywghGDRoEBMnTuSVV15h//79BAUFsWHDBszMzFiwYIGubEJCAm3atGHLli3Mnj2bgIAAjh49Sv/+/ZkxYwaJiYl6de/atYtTp07h6uqqd/z69etotVrWrVvH1atXWbFiBWvXruWDDz7QlZk2bRqRkZF6j3r16tG3b19dmR9++IFZs2Yxb948rl27xoYNG9ixY4dePflZuXIlffv2zbOn2ZgxY/Jc87PPPiu0rlzm5uY4OTnleW3jM+IJiQ/hXvI9krOSEUJgZmyGs6UzNqY2WJhYUMmskm4AtZGRES4uLhgbl14P+IgRI9i6dStxcXGldg1Di03JZOC3p7l4N4FKFiZsG9MKH/dKhg5LkiRDKZ09aUve3r17xZw5c8TOnTvz7DIuhBDbt28XKpVKbNy4UVy9elWMGTNG2NnZiejoaCGEED/99JMYP368rvxnn30mli5dWuTrF7bLbnnZrTs/w4YNEz179hTe3t5i+vTpuuO7du0Sj/54bNu2TQBi9+7d+daj1Wp1/3/33XeFpaWliIiIyFMuOTlZqNVq3df37t0Tbm5u4sqVK8Ld3V2sWLGi0Hg/++wzUaNGjQLPBwYGCkAcPXpUd2z8+PGic+fOeuWmTJki2rZtW2A92dnZwtbWVvz22296xx/f1f1xj+8Y//gO9/7+/sLW1lZX/sO5H4q6DeqKjz7/SDi7OgszczPR6/VeIuphlBBCiHnz5glA73Ho0KF8d6a/cuWKePXVV4W1tbWwsrISL730krh586YQQogzZ86Irl27Cnt7e2FjYyPat28vzp8/rxd7fu+rGjVqiPXr1xd4v4b0rO+76MR00WXZYeE+8zfh88kBcT0yqYQjrNhSEzMNHYIkFUlhn9+PKzcDrXv06EGPHj0KPL98+XLGjBnDiBEjAFi7di2///47GzduZNasWbi6uuq1DEVERNCyZcsC68vMzCQz83+DWpOSkooVrxACodYW6zklQWGiLPY4CCMjIxYtWqRrCapatWqeMtu2bcPLy4vevXvnf91/r6nVatm+fTuDBw/O0/ID6LW6aLVahgwZwvTp06lfv36RYk1MTKRy5coFnl+/fj116tShXbt2umNt2rTh+++/58yZM7Rs2ZLbt2+zd+9ehgwZUmA9ly5dIjExkebNmxcpruISQhCbEUtcRhx3bt/hz91/su2/21BmKhk9ejRTJk5h69atTJs2jWvXrpGUlIS/vz8AlStX5v79+3r1RURE0L59ezp27MjBgwexsbHhxIkTZGfnzFBLTk5m2LBhrFy5EiEEy5Yt45VXXuHGjRtYWxc8Y61ly5YcO3aMUaNGlcrrUNJSMrO5HpnEtcgkrkUlk5yRjYlSgbGRAmMj5b//V2JspGDflSjCYtOoYmvG1tG+coZZEWWlZ/PPzpuEnI1mwNyW2NiXzMbFkvQ8KDdJUWGysrI4f/48s2fP1h1TKpV07dqVkydPAjm/3K9cuUJERAS2trb88ccfzJ07t8A6P/30U/7v//7vqWMSai33P/rnqZ//tFznt0GhKv66Ka+//jpNmjRh3rx5bNiwIc/5kJAQvLy89I5NnjyZ9evXA2BnZ8e9e/d4+PAh8fHxeHt7P/GaS5YswdjYWG/MTmFu3rzJypUr+fzzz/M9n5GRwdatW5k1a5be8UGDBvHw4UNeeuklhBBkZ2czbty4QrvPwsLCMDIyytPVBbBmzRrdfedat24dgwcPLtJ9AIQmhpKenY5AkJWZxQ/f/4BndU8gp9vu1VdfZdmyZbi4uGBubk5mZiYuLi4F1rd69WpsbW3Zvn07JiYmANSpU0d3vnPnznrlv/nmG+zs7Dhy5Ag9e/YssF5XV1cuXLhQ5PsqS1nZGtLVGjb/E0pARCrXIpMJj0srVh3VKpvzw+hWVKtsUUpRVix3Lj/kyA/BpMTn/MEYfiWWBh3y/hElSeVVhUiKHj58iEajwdnZWe+4s7Mz169fB8DY2Jhly5bRqVMntFotM2bMwN6+4MGUs2fPZsqUKbqvk5KSqFatWuncwHNiyZIldO7cmWnTphWp/Jw5c5gwYQI7d+7UzdAS+Qyizs/58+f58ssvCQgIKFLLVkREBN27d6dv376MGTMm3zK7du3StYg86vDhwyxatIg1a9bg6+vLzZs3mTRpEp988kmBiXF6ejqmpqb5xjZ48GDmzJmjd+zxn7385A6k1got6dnpKBVKrFXWVK9eXZcQAbRu3RqtVktwcHChidCjAgMDadeunS4helx0dDQffvghhw8fJiYmBo1GQ1paGuHh+e/llcvc3Jy0tOIlGqVNqxXcS0gnPimV2JQstpyMISJZozvvYmNG3SrW1K1ig4OVKdlaLWqNIFsjHvm/FguVEYNbueNs8+RNcl90GSlqjv0YQsiZaABsHM3p/LY3bl5y/JVUch6EhWJha4elneF+ripEUlRUvXv3LrD753GmpqaYmpo+9bUUJkpc57d56uc/y3WfVvv27fHz82P27NkMHz5c71zt2rUJDg7WO+bo6Iijo6Nea4qjoyN2dna6ZLQgx44dIyYmhurVq+uOaTQapk6dyhdffKG3U/v9+/fp1KkTbdq04ZtvvimwzvXr19OzZ888CcrcuXMZMmSIbl2qhg0bkpqaytixY5kzZw5KZd7XzMHBgbS0NLKyslCp9PcOs7W1pVatWoXe3+PS1Gk8THhISlYKANYqa6pYVsHcuGS6HszNC69n2LBhxMbG8uWXX+Lu7o6pqSmtW7fWm8mXn7i4OBwdHUskxpKQrdFyJzaNtKxsFIDKSEG3es5UdbClbhUb6laxobKl3OutpAghuBXwgKPbg0lPVqNQQOMu1WjZ2xOTp2iRlqT8RIfe4tR/t3Pz7Ema9ehNp+FjDRbLMyVFarWaqKgo0tLScHR0LHSsR2lycHDAyMiI6OhovePR0dFF/ku7pCkUiqfqxjK0xYsX06RJkzxdZQMHDmTQoEHs3r2bPn36FPh8pVLJgAED+O6775g3b16ecUUpKSmYmZkxZMgQunbtqnfOz8+PIUOG6MaFQU4LUadOnfDx8cHf3z/fBAYgNDSUQ4cOsWfPnjzn0tLS8jzPyCjne1NQy1aTJk0ACAoK0v3/aWi0OS0YYUlh2NjaoFTkjPmqZl1N1woVHh7O/fv3da/VqVOnUCqVuu+BSqVCo9Hkf4F/NWrUiM2bN6NWq/NtLTpx4gRr1qzhlVdeAeDu3bs8fPjwifFfuXKFjh07Fvl+S1OGWsOd2FSysrUYKRW4VDLHJN2MWY1rYGYmW3tKWmpiJke3hXA7MGfvt8qulnQa4o1LDVsDRyZVFFG3bnBq53ZunTudc0ChIDMtDSGEwdYIK3ZSlJyczPfff8/27ds5c+YMWVlZuhuoWrUqL7/8MmPHjqVFixalEW++VCoVPj4+/P3337z22mtAziDev//+mwkTJjxT3atXr2b16tVP/FCqKBo2bMjgwYP56quv9I4PGDCAnTt3MmDAAGbPno2fnx/Ozs6EhYWxY8cOXZIBsHDhQg4fPoyvry8LFy6kefPmmJiYcOzYMT799FPOnj2Lvb19nu5LExMTXFxcdMlAREQEHTt2xN3dnc8//5wHDx7oyj6e7G7cuJEqVarkOxi/V69eLF++nKZNm+q6z+bOnUuvXr304n6Uo6MjzZo14/jx43mSorS0NKKiovSOmZqaUqmSfpNvclYy91P+NyDazswOJwsnFCj03vBmZmYMGzaMzz//nKSkJCZOnEi/fv109+jh4cGff/5JcHAw9vb22Nrm/VCaMGECK1eu1H1/bG1tOXXqFC1btsTLy4vatWvz3Xff0bx5c5KSkpg+ffoTW5fS0tI4f/58sRavLC0pGWrC4tLQaAUqYyUe9pagURs6rApJCMH1k1Gc+PkGmWnZKJUKmvVwp3l3D4yeoSVaknJF3gzm5M/bCL1wDgCFQolXm3a0eqM/9lWrP+HZpaw409qWLVsmKleuLFq0aCHmz58v9u3bJy5duiRu3LghTp8+LTZs2CCGDx8u7OzshJ+fnwgJCSnmxLmCJScniwsXLogLFy4IQCxfvlxcuHBBhIWFCSFypuSbmpqKTZs2iaCgIDF27FhhZ2cnoqKiSuT6FXlKfp8+ffSOhYaGCpVKJR7/8dBoNGLt2rXC19dXWFpaCpVKJTw9PcWYMWNEUFCQXtmEhAQxa9YsUbt2baFSqYSzs7Po2rWr2LVrl970/Uc9PiXf398/z3T03MfjcVWtWlV88MEH+darVqvFxx9/LGrWrCnMzMxEtWrVxH/+8x/dNPmCrFmzRrRq1UrvWIcOHfKNx8/PT/faAWLf8X3iyoMrYuMvGwUg7kbf1d3To1Py582bJxo3bizWrFkjXF1dhZmZmXjrrbdEXFycrkxMTIzo1q2bsLKyKnRK/sWLF8XLL78sLCwshLW1tWjXrp24deuWEEKIgIAA0bx5c2FmZiZq164tfvrppzyvN49Nyf/hhx+El5dXoa9RWYhNyRSX7iaIi3fjxY3oZKHO1gghyvf77nmV+DBN7Pnyglj1zt9i1Tt/ix0Lz4gHd5MNHZZUQUQEB4mfF84Vn/d7VXze71WxrH8vsXfl5yI24m6pXrc4U/IVQhRxZCw5XSgffvjhE6dPZ2Zm4u/vj0qlYuTIkcVK0gpy+PBhOnXqlOf4sGHD2LRpEwCrVq1i6dKlREVF0aRJE7766it8fX1L5PpJSUnY2tqSmJiIjY2N3rmMjAxCQ0OpUUM241ck6enpeHl5sWPHDlq3bv3E8kIIErMSiUqN0nWb2Zvb42juiJEy/xapjz/+mF9++UW3LcjzpFWrVkycOJFBgwYZ5PpCCKKTMohJzpnpZGduQtVKFiiVOa1s8n1XcoRWcOVoBP/sukV2pgYjYyUte9WgSddqKI1k65D0bO5du8LJ/24n/HIgAAqlknrtO+P7ej8queRduqWkFfb5/bhidZ9t27atSOVMTU2LvO1BUXXs2PGJM5smTJjwzN1lkpTL3NycLVu2FGnsjVqj5n7qfd1AalNjU1wtXbEwKZ9TvR8+fMgbb7zBwIEDDXJ9rVZwNz6NxPScLjInazOcbfKfDSg9m4ToNA5+d43ImzkrzVepZUvnIXWxcy6fP7vS8+Pu1Uuc/Hkbd4MuA6A0MqJ+hy60fK0fds6GGe/7JCU6+yw1NZWQkBCqVauGg4NDSVYtSQbxpEHGQgjiMuKISYtBK7QoFAoczR2xN7dHqSi/f2E7ODgwY8YMg1xbb4aZQoGbnbmcUVYKtBotgX/d5cxvoWjUWoxNjWjzek0atHdDoZTJp/R0hBCEX7nIqf9u5961KwAojYxp0KkrLfv0xdbpycuXGFKJJUWLFi3iyJEjtGzZkuDgYKysrFi9evUTB3M+7160gdZS0WVrs4lIidC1DpmbmONm6YapcdGXcvj444/5+OOPSynC8ket0XLrQYpuhpl7ZUuszF6olUPKxMN7KRzcco0H4ckAVKtXmY6DveTq1NJTE0IQdukCJ3/exv2QawAYGRvToLMfLfu8hY3D87O0R2FK5LeNv78/cXFx/Pnnn7pjP/30E5MnT2bdunUlcQmDGT9+POPHj9f1SUoS5Kw7dDf5LtnanNYMZwtnKptVlt07z0AIwd24NLKytboZZmYm5W9Zi+eZJlvLuT/uEPBHGFqtwNTCmLZv1ca7tYv82ZWeihCC0MBznPp5O5E3c9ayMzIxoVGX7rTo8ybWlctXr1GJJEU7duzg+++/B2DkyJF8+umn9O3bl08//bQkqi83ijFmXSqncrvLolOjEQhURiqqWVfDzFgO9H1WD1IyScnMRqlQFCkhku+34okOTeLgd9eIu58KgGcTR9oPrIOl7dMvUiu9uIQQ3A44w8mftxN9+wYAxiYqGnXrQYveb2JVyTDrFj6rEkmKTExMdCvjtm3bFguLnAF6Wm3Zb4hqCLmL5aWlpZX77kKpYBqthvup90nKzNkc2MbUBldL1wJnlklFl5qZTXRiziwzVzvzIrUQ5W4/UtDWJlIOdZaGM3tuc/HvuwgB5tYmtB/gRc1mjrJ1SCo2odVy8/xpTv28nZg7twAwNjWlycuv0rzn6wbdoqMklEhSNHr0aGbMmMHmzZt1u2mvWLGi0F3tKxIjIyPs7OyIiYkBwMLCQv6yqWAyszOJTI1ErVWjQIG9uT12xnaos9SokYsIPotsjZbw2DS0Wi3WZiaYKzVkZGQUWF4IQVpaGjExMdjZ2RW4AKcEESHxHPruOokP0gGo4+tMu751MLOSiaRUPEKr5caZfzj13+08CL8DgImpGU2696T5q69hYWtn0PhKSokkRX369CE1NZUuXbrg7u5OZGQkbdq0YcGCBSVRfbmQu/pwbmIkVRxp6jQSMxMRCIyURlQyrUSCUQIJJBg6tAohNiWLdLUGY6UCYxtT7sQX7Q8KOzs7g23j87xLS8rizK+3uXosZ0V1q0qmdBjkhUfD8jW+Q3o+hF0K5PB363n4bzKkMjenafdeNHulDxY2FWusbbEWbyyKuLg4KlWqVGFaSh6dfRYSEvLExZ80Gg1qtWw5qAgysjNYd2kdf4f9DUAz52ZM8ZmCjWnhi39JRbcnMIIv/76BsVLBVwOb4uVStNfWxMREthDlIzM9m8AD4QT+fZfszJwZs/XbudLmjVqozOUsPql4EqIiOfzdBm6dOwWAytyCZq/0ptkrfTC3sjZwdEVXnMUbSzwpqqiK86JK5V9YUhhTDk8hJD4EpULJ+CbjGd1wdLlee+h5cz0qid6rTpCVreXDV+syup2noUMqt7LVGq4cieD8H2FkpP674KW7NW3erIVbnfI9xkMqe1npaZze9SPnf/8FTXY2CqWSJn6v0vqtQeUqGcpVaitaF8WNGzcYPXo0R44cKemqJalM7L+zn4/++YhUdSqVzSrzWfvP8K1SMtvFSDnSsrKZ8MMFsrK1dPJyZGTbGoYOqVzSarRcPxXF2d9CSYn/dzsUZwta9fHEs6kcSC0Vj9BqCTp2iGPbNpMaHwdA9YZN6DRsDA7V3A0cXdko8aQoKyuL48ePl3S1klTq1Bo1y88v5/trOctLNHNqxtIOS3GycDJwZBXP/F+DuBmTgpO1KZ/3bazbz0wqGiEEty884NTu2yRE58zCs6pkSoueNfBu5SL3K5OKLfJmMIf8v9GtNWTnXIUOQ0dT06flC5Vcy05mSQKiUqOYemQqlx5cAmBkg5G81/Q9jJXyLVLS9ly8z/azd1Eo4IsBTbC3kuvkFMfd63Gc2nWLmLCc1ajNLE3w6eFOgw5uGMvFLqViSomP4/i2zVw9kjN20sTMnFZv9KfZK30wfgGXuyj2b/xx48bh4+ND06ZNadSoESqV3JNIKt9ORJxg1rFZJGQmYK2yZmHbhXSq3snQYVVI4bFpfLAzZ3PI9zrVok1NORuqqKLvJHHql1vcux4PgLGpEU26VKNJt+qYykHUUjFlq9UE7N3NqZ07UGfkLNlQr31n2g0chlVlewNHZzjFfiddvnyZrVu3kpqaiomJCfXq1aNZs2b4+PjQrFkzlErZbCuVDxqthrWX1rLu4joEgrqV67K843KqWlc1dGgVUla2lve2BZCSmU0Lj0pM7FLb0CGVC/FRqZzefZtbFx4AoDRS0KC9Gz49PLCwkX+USsUjhODW+TMc2bKehOhIAFxq1aHz8HeoUtvLwNEZXrGTohMnTiCEIDg4mICAAN1j165dJCQkAFSo/ke5IWzFFJsey6xjszgVmTPVtF+dfsxoOQNTI9mVU1o+3x/MxXuJ2Jqb8OWAphjLcS+FSo7L4OzvoVz/JxIhAAV4+brQsmcNbBzkyvlS8cXeC+fQ5m8Ju3QBAEu7SrQbNJx67TqhkA0aQAlPyb99+zbnz5/nwoULLFq0qKSqfS7IKfkVx4WYC0w7PI2Y9BjMjc35qPVH9PTsaeiwKrRDwTGM8D8LwLohPvjVl4suFiQ9JYvz+8K4cjgCTXbOVkk1Gjvg29sTezcrA0cnlUcZKSmc/PkHLvz5G0KrxcjYGJ9XX8P39X6ozC0MHV6pK9Up+R999BF9+vTBx8cnzzlPT088PT3p27dvcauVpFInhGBL0BZWnF+BRmioYVuDFR1XUNOupqFDq9DuxqXx/o5AAIa1dpcJUQGyMrK5+PddLhwIR52R0zLtWtuO1q/XxMWzYq0aLJUNrVbD5b/3c2LHd6Qn5+zZWLN5KzoMGUklF1cDR/d8KnZSdO/ePXr06IFKpaJXr1707t2bLl26yAHX0nMtKSuJj058xN/hOTMsetTowcetP8bCpOL/lWRIaVnZjNlyjoQ0NY2r2jL7lbqGDum5o1FruXo8gnN775CenLPwokM1K1q9VpPq9SpXqOEIUtm5F3SFg5vW8SAsFIDKbtXoNHwsHo2aGjiy51uxk6KNGzei1Wo5ceIEv/76K5MnTyYyMpJu3brRp08fevbsSeXKlUsjVkl6KveS7zH2wFjuJt/FRGnCzBYz6efVT37YlDIhBNN/vsT1qGQcrExZO8QHMzllXEerFYScieLMnlCS43I2wLV1NMe3jye1mjmhkGs3SU8hLTGBw99t4NqxQwCYWlrSpu9gGnd7BSNjOUvxSUpkTNG1a9f49ddf2b17N+fPn6dly5b07t2bgQMH4ubmVhJxGpwcU1Q+xabHMvSPoYQnh+Nq6cqyjsto4NDA0GG9EL4+fIsl+65jYqRg25hWNPeQfyxBTrIYevEhp/fcJu5+KgAWtipavFqDum2rYCQHoEtPQWi1XD50gGNb/clITQGFgkZd/Gjbf0iF27S1uMp8m4+6detSt25dZsyYwYMHD9izZw979uwBYNq0aSVxCUkqtpSsFN79613Ck8Nxs3JjS48tcnXqMnI4OIbP/rwOwMe968uE6F8RIfGc3HWL6NCc8R2mFsY083OnYaeqmKhkK5r0dGLvhbP/m1XcDw4CwNHDk25jxlOllpxiX1wl2paWmprKvXv36NOnD6NGjSrJqiWpWDI1mUw6NIlrcdeobFaZdd3WyYSojIQ+TGXitgsIAQNbVmew74uxZ1JhHoQnc2r3LcKv5uwnZWyipFGXajTtVh0zyxdv1WCpZGSr1Zz55SdO7/oRrSYbE1Mz2vQbTLMevVEayST7aZRYUrRo0SKOHDlCy5YtCQ4OxsrKitWrV2NuXr7X05DrFJU/Gq2G2cdmcybqDBbGFqzpugZ3G/nBXBZSMrMZu+UcSRnZ+LhX4uPe9QwdkkElxKRxZs9tbpyLAUCpVFCvnSvNX/HA0lauiSU9vfsh19i/biWx98IB8GzWgi6j3sXGQf7x9yxKZEyRv78/V69e5fPPP9cd+/HHH/n7779Zt27ds1b/XJBjisoHIQSfnPqEn0J+wkRpwtddv5Y73JcRrVYw7vvz7A+KxtnGlF8nvISTjZmhwypzGSlqYsKTuH3hAddORKLV5vyKrd3CGd/eNbB1lDMepaeXlZ7G8e3fceHP30AIzG1s6TziHbxat5OTRwpQ5mOKduzYwfff5+wsPnLkSD799FP69evH4sWLS6J6SSqyNRfX8FPITyhQsLjdYpkQlaGVB2+yPygalZGStW/7vBAJUXpyFjHhyTwIS+ZBeDIx4UmkxGXqlXFvaE+rPp44VLU2UJRSRRF64RwH1q8m+WHOli/1O3Shw5BRmFvLP9RLSokkRSYmJmRlZQHQtm1bLCxy/hLSarUlUb0kFcm269tYe3EtAHN85/Cyx8sGjujFcSAomhV/hQCw4PUGNK1eycARlby0pCwehCfzIDyJmH+ToJT4zHzL2jqZ4+RuQ4P2brjWtivbQKUKJy0pkUObvuH6iSMA2Dg6023sBLnmUCkokaRo9OjRzJgxg82bN+sGWK9YsYIePXqURPWS9ET7Qvfx6elPAfhP4//Q37u/gSN6cdyMSdZbsbpf82qGDagEpCVlEROW9G8SVHgCZOdsgWN1axyrW+NU3RqH6tZy13qpRAghuHb8MIc2f0tGchIKhZJmr/Smbb+3MTGr+C2xhlAi79w+ffqQmppKly5dcHd3JzIykjZt2rBgwYKSqF6SCvXP/X+YfXw2AkF/r/6MazzO0CG9MBLT1YzZcp6UzGxa1qjMhz3L38Dq1MRMXeKT2wKUmpBPAqQAO6ecBMjJPScJcqxmjUomQFIpSHoQw4H1q7kTeB4Ax+oevPzORFxq1TFwZBVbiW4ICxAXF0elSpUq3IAvOdD6+XTl4RVG/jmS9Ox0/Dz8WNJuCUZKORW1LGi0gtGbz3Io+AGutmbsee8lHKye7xlVqYmZPAhLzhkHFJ7Mg7AkUhOz8hZUQKVHW4DcrXGoZo3KTCZAUunSajUE7vuN49u/Q52ZgZGJCa3fHEjzXm/IFamfUqkOtF6wYAHNmjXDx8cHZ2fnPOflFh9SWQlNDOU/f/2H9Ox0fKv4suilRTIhKkMrDoRwKPgBpsZK1g1p/twlRKkJmf8Ogk76dxB0MmmFJUDu1jhVt8GxujUO1axkAiSVuYfhd9i/biWRN4MBcPOuz8vvvEdl16oGjuzFUex3/UcffaRrBXJxcdElSLn/VpRtPaTnW3RqNOMOjCM+M5569vX4stOXqIzkpsRl5Y/Lkaw6dBOAxW82pGFVw20jIIQgNSErZwC0rgUombSkvAmQQgF2LpY4/dsC5OhujUNVmQBJhpWtVnN61w7O/PIzWk02KnML2g8eQaMufiiUctuXslTs3wQtWrQgMjKSESNG4ODgQEBAADt37mTRokVoNBocHR1p1qwZe/fuLY14y5xcvPH5k5iZyLi/xnE/9T7uNu583fVrLE0sDR3WC+NAUDST/h1YPfqlGrzetOz+is1JgDJ1Y39yW4DSC0iAKlWx1B8EXc0aE1PZmig9PyKuB7F/3VfE3b8HQM3mregyahzWlR0MHNmL6anGFG3atIkPPviAFi1asHz5cmrWrElmZiaBgYEEBARw4cIFvvnmm9KI12DkmKLnQ3p2OmP3jyXwQSCO5o5898p3uFnJ1smy8suFCKb+dBGNVuBX35nVg5phXEobmAohSIl/fBB0EunJ6jxlcxMgp39bfxyr2+BQ1UomQNJzKzMtjWPbNnNx/+8AWNja0WXkOGr7tq1wY3INrTif30890DolJYX58+ezbt06/vOf/zB37lzd+kQVkUyKDE+tVTP50GSO3juKtcqaTd03UaeSnIlRVr47eYeP9lxFCHijmRufvdmoxBIiXQIUlrMAYm4ilG8CpFRQuUruIGgbnNytsa9qJTdUfc5oszRkR6ehtDbB2E5OH3/UrfNn+GvDGlJiHwLQoFM32r89EnMrucBnaSiTpCjXjRs3mDJlCufPn2fx4sUMHTr0Wap7bsmkyLCEEHx44kP23NqDqZEp33T7hmbOzQwd1gtj9aGbLP0zZ/Dn8DYefNSzHkrl0/01K4QgOS5DN/bnQXgyD+4WlgBZ/jsIOqcbzKGqFcYyAXpuCK0gOzYddVQa6qhU1FGpZEelkh2XAQJs/Dyw6VT+164qCWmJCRzc9A3B/xwFwNbZhW5jJuDesIlhA6vgymybj+zsbDIzMxk4cCDR0dGMGDGCnj17yhloUolbcX4Fe27twUhhxOcdPpcJURkRQrBkXzBrj9wC4L3OtZjSrU6xmvdTEzOJupX4v0HQ4clkpORNgJRKBZVcHxsE7SYToOeFEAJtilqX+OQmQdkxaQh1/rsXKC1NoGRXfSmXtFoNl//+k+PbvyMjJRmFQolPz9do03cQJqayFe15UuykaPHixVy+fJnLly9z/fp1zMzMaNSoES1btuSdd97B1tZws1Ckisn/ij/+V/0B+LjNx3Ss1tGwAb0gtFrB3N1X2Ho6ZxfuD17xZmz7mkV+fmpiJud+v0PQ8fu6TVFzKZUKKrtZ6gZAO1a3wb6qJcYmMgF6HuR2ff0vAcp5aFOz83+CsRITZwtMXCwxccn91xIjazkjNCL4Ggc3riXmTs4fFo4envi9MxFnz1oGjkzKT7GTog8++AAPDw+GDRvGwIEDqVNHjumQSs/um7tZfn45AFN8pvBardcMG9ALQq3RMu2ni+wOvI9CAYteb8jAltWL9NzM9Gwu7A/j4t93yc7KaUGwr2qFs7s1ju456wDZu8kE6HkgNLldX4+0/kSnovm36ysPBRjbm2PibIHxv4mPiYsFxvbmKJ6yO7WiSktK5Oj3G7l65G8ATC0sadPvbZq8/ApKI/mz/7wq9piiDh06EBgYSHJyMpaWljRq1IhmzZrpHg0aNMCoAn7D5Ziisnfk7hEmHZqERmgYXn84U5tPNXRIL4QMtYbxWwP4+3oMxkoFK/o3oVdj1yc+L1ut4cqRCM7/EUZGak73mHMNG1q/XhO3OhVvg9jyRAiBNlmt3/ITnYY6Og2yC+j6sjLJSXpyW4CqWGLsZIFSdmc+UcjpE/y1fg3pSYkANOj0Mu0GDsXC1s6wgb2gSnVM0ZEjObv03rhxg/PnzxMQEEBAQABbt24lISEBU1NTGjZsyJkzZ54uekkCAqIDmHpkKhqhoXfN3rzv876hQ3ohpGRmM3rzWU7djsPUWMnat33o5O1U6HO0WkHI6ShO/3qblLicPcMquVjQqk9NajRxkNOLy5g2U4M6OnfA8/+6wLRp+Xd9KUyUGDv/r8srt/vLyEp2fRVXekoyBzeu1e1m71Ddg5fHvkeV2l4GjkwqqqceaF27dm1q167NgAEDdMdCQ0M5d+4cFy5cKJHgpBdTSHwIEw5OIFOTSfuq7fm4zccoFXJV19IWn5rFcP8zXLyXiJWpMRuGNcfX077A8kII7lyO5dQvt4i7nwqApZ0pLXvWwLu1C8pSWr9IypFv11fUv11f+cnt+npkzI+xiyXGlc1k11cJuB1wlv3frCQ1Pg6FQknL196i1ZsDMTYxMXRoUjGU+IawFZXsPisbESkRDN07lJj0GJo4NuGbl7/B3Njc0GFVeNFJGQzZcJqQ6BQqWZiwZaRvoVt3RN5M4OSuW0TeyukeMLUwppmfO406VZWzxUpYTtdXVk7SE/lI99eDNMjO/9e3ruvr0dYfZwsUchxXictMS+XQ5m+5evgvACq7VqX7+PepUku2Dj0vSq37LDw8nOrVizbYEiAiIkLuhSYVWVxGHOMOjCMmPYZadrVY1WWVTIjKwN24NAavP014XBrONqZ8P8qX2s75LyIXez+FU7/c5s6lnEXnjEyUNO5claYvu2NmKf8iflbazGy99X7UUWlkRz+h6+vRcT//JkCy66ts3Ll0gf1rvyI59gEoFPi8+hpt+7+Nier52hxZKrpiJUUtWrTgtddeY/To0bRo0SLfMomJifz44498+eWXjB07lokTJ5ZIoFLFlqpO5T9//Yc7SXeoYlmFtV3XYmsql3cobTeik3l7w2mikzKpXtmCraN9qVY578r0yXEZnPn1NsGnohAiZ1uNum1dafFqDawqyQ+A4hIaQfbDtMcSoFQ08Zn5P0EBxg7m/xv4XOXfKe+VZNeXIWRlpHP0+41cPPAHAHbOVfD7z2Sqetc3cGTSsypWUhQUFMTChQvp1q0bZmZm+Pj44OrqipmZGfHx8QQFBXH16lWaNWvGZ599xiuvvFJacZcZuSFs6cvSZDHp0CSuxl6lkmkl1nVbh7Ols6HDqvBuPUih37qTxKepqeNsxfejfHGy0V9ILiNFzbl9d7hyOALNv7OUPJs60qqPJ5Vc5Ca8TyKEQJOUpVvlWZcExaSBpoCuL2uV3rgfExdLTJzMZdfXc+Ju0GX+/PoLEmOiAWji15P2g4ZjYiYXYawInmpMUXp6Or///jvHjx8nLCyM9PR0HBwcaNq0KX5+fjRo0KA0YjUoOaaodGi0GmYem8mfd/7E3NicjX4baeBQ8X5+njepmdm8tvoEN2JSaFTVls0jWlLJ8n9dLupMDRf/vsuF/WFkZeT8QeBWx45Wr9fEpYZswcuPNiM7Z5p7bstPZM60d5FeQNeXSomJc+6A50cWPJTdkM8ldWYGx7d/R8Afe0AIbByd8Bs3ieoNGhs6tKcnBKTFQlIEoIAqjQwdUako073PXhQyKSp5QggWnV7E9uDtGCuNWd1lNW1c2xg6rApPCMF72y7w26VInG1M+e29djha53SBaTRarp2I5OxvoaQlZQE5Cy+2fr0m1etVltPrAaHRkv0gXW/GlzoqFU1CAV1fyke7vh4Z9yO7vgxOm5mJJj4eExeXQsvdD7nGvjVfEB8ZAUDDLn50eHsUps/7JugZiRB/B5LuQ+K9nH+TIvS/1vz7c1ujAwzbY9BwS0uZ7X0mSc9i7aW1bA/ejgIFn770qUyIysiG46H8dikSY6WCNYOb4WhtihCCm+djOL3nNokx6QDYOJjRspcndVo4v5Af3kIINIlZepucqqPScmZ9FdT1ZaN6ZLZXbteXBQoTuTzB8yb9ylXuz5qJQqWixo4dKPKZOp+tVvPPT1s5t2cnQmixqmzPy+9MpEYTHwNEXAzxd+DoUgjcBqIIQz8sncBMtgCDTIokA/kx+EfWBK4BYFbLWXSv0d3AEb0YTt+O5dM/rgMwt2c9fNwrc/d6HKd23SImLBkAc2sTmr/iQf12bhgZvxgf5tqM7Dzr/aij0hAZBXV9GT027scCY2fZ9VUeiKwsHq5dx8N160CjwcjenqywMExr6e9FFn37Jn+sXk7svZy9/+q170ynYWMxs7IyRNhFkxD+bzL0A2j//dm1dAQbt5yHrRvYuIJN1f/939oVjOVsxVwyKZLK3P47+1lwagEA7zR6h0F1Bxk4ohdDdFIG43+4gEYreK2JKz3cKrPnywvcvRYPgImpEU26VadJ12qozCrmrwaRrSX7YT4LHhba9WWRZ+Cz0f+3d+dxVdZ5/8dfZ+OwI8gmmwoipiYoClpZrpm5l6XOki13dbfd4zjV1NxNzczdVL9pKnNkWiatZpoJtEwrW9xySS0VxV1UcGFH9p2zXb8/LjxAuIAC5wCf5+NxHsJ1rnOdD3U458137WXska1nXV1dejq5zzxL/bFjAHhNvY3g559H79u4DY3VYuaH1Sv58bMUFJsNd59eTH7wcQaMGu2osq+sPBu2/RX2fwQ2dYsdoibAuGchPMGxtXUx3fOdTzitH/N+5Jntz6CgcNfAu3gs7jFHl9QjmCw2Hv33Poqq6hnh58mtFXpWvbwXAK1Ow5CbQxk5tR/u3t3jL0a166u+xYKHlqLaS3Z96bxdGjc57dMw9T3QHU0PaS3rzhSLheL33uN80t/BbEbXqxfBLzyP99Spzc47f+4MXye9zvkzmQDEjBnLhPv/G3dvJ+1aqsiF7a/Dvg/Bqo4BpP8tMP53EOHEIc6JtXsoys7O5k9/+hPvvvtue19adHFHio/wP5v/B7PNzOS+k/nfxP+Vgbud5KWvjpF6tpSRNgMTz9o4nXkeNDBwVBAJMyLxCei6i2Taai3N1vq5sNO7UnfxsRQao67ZHl/q2B93tO7S9dUd1WdkkPvMs9QdOgSA58SJ9PnDC+gDAuzn2KxW9nz+KTtX/Qeb1YKrlzeTHniEmDFjHVX25VXmw/dvwN73GwdK9xurtgz1u9GxtXVx7R6KiouLWb58uYQi0czZirM8uvFRaiw1JAQn8PLYl9FpZd2VzrA2LYcPd5xhfJ2BkfV6bCiEDfLlhjsHEBB+8ZWrnZFisWE+X9sw4LnJgoflpos/QKtBH+DWPABd6PqSMN7tKVYrJR/+k/NLlqCYTGi9vAh+7n/xnjmz2f//4uwsvnnrDfJPnQAgauRoJj/4GB69fC91acepzIcdS2HvcrA07HHX90Y1DPV30gDXxUj3mehQlaZKPs/4nBWHV1BSV8J1ftfx5vg3MepkFeTOcDy/ghdWHWJutQv9LGoIHTmtHwnT+jvtmBhFUbCW1quhp6Bx3I/lfC3YLtH15WNssdGpIcBNur56KNPZs+Q++ztq9+0DwGPsWPq8+H8YghoXhbXZrOxbt5bvU/6F1WzG6O7BhPse5rqx450vNOcfhh/+DodWNXaThY+G8c+q3WXOVm8XJqFIdIj0knSS05NZl7mOWos6xbuvd1/+PunveLo48eyNbqSizsxTy/cyt1SPr02L3kXLxIWDGRAf6OjS7Gw1Znt3V9OBz0p9K7u+Gra9kK4vAaDYbJT+52MKX3sNpbYWrbs7gc/8ll533dUs6JTm5/LtW0vIOX4UgH5x8dz68BN4+fk7qvSWbDY4tRF2LYPTWxuPh4+GW55WB1JLGGp3EopEuzFZTWw4u4GU9BT2F+63H4/yiWLeoHnMjJqJh0G2hugMNpvCH97ey/gsBSNa3H2NTH90mMO6yxSLDXNhTbPgY8mvxlpx6a4vQ6Bb48DnCwse+kjXl7i4+owM8v/wR2r27AHAPTGRPn/+My5hjZuSKzYbaevXse0/H2Cpr8fFzY1bfvlfXD/hVud5XZlr4UCy2jJUpHbpodHB4Fkw5jEIG+nY+rq5NoeiO+6447L3l5WVXW0toovKrcpl1YlVrD65mpK6EgD0Gj0T+05kXsw8RgaNdJ43nB5AURTeensfkcdr0KDBO8KTuU/E4ebV8TPLFJuCtay+xcBnS1EN2C7+GF0vY4vWH72/dH2J1rHV1lL09jsUr1gBZjMaNzcCn/wNvgsWoNE2voYqzhfy7dtLOHf4IAARQ4cx5b8X4R3gJC2nlQWw5z11vFBNsXrM6A3xCyHhYegV7tj6eog2hyIfn8tPTfTx8eGee+656oJE12BTbOzK3UVyejLbsrdhU9RPvEC3QObGzOXO6DsJdHeSN5sexGyykpKUBunlaNBgHOTNzx4f0SGLMKpdX417fNkXPDRdouvLVddsrZ8LIUjbTddEEh2vautW8v/vRczZ2QB4jhtH0HPPNW8dUhQObV7P1n+9h6m2Fr3RyM0/v4+4ybc3C00OU3AEdv0dDq1sHC/UKwJGPwrDfwHGrjMZojto87vR+++/3xF1iC6ivL6cNafWkJKeQlZllv14Yp9E5sfM55bwWzBoZXyHI1SW1LF22QHKc6uxolA+yJPfL7r2pnbF3KTrq8nAZ9ulur50GgwB6oKHTbu/dD4u0mIo2oU5P5+Cl16mcv16APTBwQQ/9794TpzY7DVWWVLEhnf+xum0VABCBw1myiOL8A0OcUjddooCGZtg5zLI/K7xeHii2kUWMw108seCI7T5v/rzzz/PrFmziI938r1fRLs6UnSE5PRkvj79NfUN62J4GjyZNWAWd8fcTaRPpIMr7NnyMsr5+u2D1FaaqdEoHOpr4N3H2haIFJuCtbSu2San5vxqLMW1V+766tPY8qP3d0Ojc4K/wEW3o1gslHz0EUVL/4atpgZ0OvwWLiTgsUfRejSOV1QUhWPbv2PzB+9QX12NzmDgpvn3MOL2mWgduRSI1QxH1sCON6FAXTcJjVYdLzT6MQgf5bjaBHAVoSg7O5upU6fi4uLCjBkzmDlzJhMnTsTFpXushCsa1Vnq+ObMN6QcT+Fw8WH78RjfGOYPms/t/W/H3eDku0T3AEd35LL1P+nYrAqFWhub/G0kPzwGV8Ol3/yt1eYmG502tgIppounH42bvsVWF4Ygd+n6Ep2mNi2NvD/8kfrj6t59bnFxBP/xD7jGxDQ7r7qslA3/SCJj7w8ABA8YyG2P/preoQ4ck2Oqhn3/gl1JUK7upYbBQx0vlPjf4NvXcbWJZtr8jrZixQpsNhs7duzgiy++YNGiReTl5TF58mRmzZrF9OnT8fPz64haHSIpKYmkpCSs1lbsNNxNZFVksfLESj479Rnl9eUAGLQGpvSbwryYecQGxEo3iBMwm6z88FkGB79Tx1OkG6x842HivV8kEOarhlXFbMVcWPuTgc/V2CrNF7+oToMh0N0+5kcf7IFLsAdab+n6Eo5hLS+n8PU3KFu5EhQFrY8PgU/+hl533tliTFD6ru1sXP4WdZUVaHV6brjrZ4yaeSdanYNah6rOw+53Yc8/oFbdYxCPADUIjXoA3JxwgcgeTqMoysVXQ2uDY8eO8cUXX7B27Vr27t1LYmIiM2fOZMGCBYSGhl75Al1ARUUFPj4+lJeX4+3t7ehy2p3VZmV7znaS05PZkbPDfjzEI4S7Yu5izoA59Hbr7cAKRXVZPXkZ5eRnlJOXUUZRVhW2hsUMf3S3kGGwsDgunMkB3vaBz5aiWrjEb7jOz1Xd36vpTu/S9SWchKIoVHz+OQX/7y9YS9RZrT5z5hD41JPof/KHd+GZTH5cncKJH9X3rsB+Udz22K8JiOjX2WWrSjLV8UJp/25cedovEm54AmJ/BgZXx9TVQ7Xl87tdQlFT58+ftweksWPH8uSTT7bn5R2mu4aikroSVp9czar0VeRW59qP3xh6IwtiFnBT6E2yHYcD2GwKJblV5J0qJz+znLyMciqL1TdXFw146zR4azX4ueuwaGwEKhrcuHhLjtZdjz7oJwseBrujNUrXl2hfisWCYjKp/1osKGYLitkMFnOTY2b1uMUMLY6pxxWzmYovvqRm924AXKKiCH7heTwSGnd8t5jNnPzhe/avX0feCbVLTaPVMvqOeSTOmYdO74DXd84+2LkUjq6Fhhm5hIyAmxbBoOkg76UO0ZbP7za/au6///5Wnbd27dq2Xlp0EkVROHD+AMnpyaw/sx6zTe1K8TH6MGfAHO4eeDfh3rImRmcy1VkoOF2htgRlllOQWY61zoqXToO3DiK0Gnw8dPi4aHH56Z8xSkPLTtOurz5Nwo+XdH2Ja6MoCrbycswFhVgKCzDn52MpKMRSkI+5oED9Oj8fa3l5uz6vxtUV/0cfpfe9C9E0jFutKCrkwIavObR5PbUV6vNpdTqiE28kYdZcAvt18qSPCzPJdrwJp7c1Hh8wWQ1DfW+Ulae7kDaHog8++IC+ffsyfPhwLtXIJG/AzqnGXMNXp78iJT2F4yXH7ceH9h7K/EHzmdJvCq56adbtLKX51RzakkPeqVLq8qrx0qqtP8E6DQMNGjyM+pa/Sw2/cjo/V85qbWwsqiRLp7D4Z7EMHBSARie/e6JtFIsFS3ExlvyGgJNfoAafhqBjLlRDj1JX1/aL63Ro9Hr1ZjCAQY9Gb7B/f+E++/Emx/SBgfR+6EFcwsJQbDbOHNhH2vp1ZKbuQWlohfH0682wSbcxbOJtnb+B68Vmkmn1MHSu2k0WPLRz6xHtos2h6JFHHuHjjz/m9OnT3HffffziF7/oVgOru6PT5adJSU/h81OfU2muBMCoMzK1/1TmxcxjqL/88nYWa5UJc3415emlnN6aja9NIUKnQe918bWdtO76ZjO+9MHuGII82JxRxH/9cy8Ab8yNJWaILJQpLs1SWkrt/v3UZ2Q0aeFRQ4+lqEjdZ6sVdL16oQ8KQh8chCEwCH1QEIZg9V99YBD6wAC0Li5wIdxc4+KIdVVVpK5bw4ENX1Ga19i9HzF0GHG3TidqZGLnD6KuLoLUD2DvCqjIUY9dmEk2+lFZebqLu6oxRfX19axevZoVK1awc+dOpk2bxgMPPMCttzrR/jHtrKuNKbLYLGzJ2kJyejI/5v1oPx7hFcHdMXcze8BsfIyXX51cXD2byYqloMl6Pw1f26ouMetLr8EQ5PGTgc8eaL0MLX6nskpquH3pdirrLCwc05c/zpJQK5oz5+VRszeVmtS91KamUn/y1OUfoNOhDwjAENQQcC6EncCmoScQrWvHtyTbbFayjx7m2PdbOL5jGxaTui6ai5s7Q26ZSOzk2+kd5oDgkbMPdv8DDn8KDWu14e4Po/8bRj4A7tI44Kw6daD12bNn+eCDD/jnP/+JxWLhyJEjeHp2v13Qu0ooOl9znk9OfsInJz6hsKYQAK1Gy81hNzM/Zj5jQsag1cjsovai2BQsxbXNFjy05FdjKam75KyvGqDcZMPiaWDwjEjc+3mj7+2GRnvlPygUReHe9/ew9cR5hkf0IuWhMbjIHmE9mqIomE6fpmavGoBq9uzFnJvb4jyXyEhchwzBEBzcvIUnKAh9795oHDVtHfVnyM84wfEd20jftZ3q0hL7ff7hfYmbMo3rxo7HxdWtcwuzmNRB07vfgew9jcdDhqv7kQ2ZIzPJuoAOHWj9U1qtFo1Gg6IoPWotH2eiKAp7C/aSkp7CprObsCgWAPxc/bgz+k7mDpxLiKeDl7Xv4hRFwVZlbrbJqTm/GkthDYr54l0PWo/mXV8mdz3r/p1OeUk9vn08mLN4eJs3af32SD5bT5zHRafltbtiJRD1QIrFQt3xdGpT9za0BqXap6zbabW4Dh6Me3w8biPjcY+PbzGN3RkUZZ0lfec2ju/YRllBnv240cOD6IQbGXLLBEIHDen8HojKfLV7bO/7UK3+cYnWoIagxIchNF4GT3dTVxWKmnafff/990yfPp1ly5Zx2223oXWGDfZ6iCpTFV9kfkHK8RQyyjPsx4cHDmdezDwm952Mi05WGr9WxR8dpf50ObZqy8VP0GubdHs1dn9pPRu7vqrL61n3132Ul9TjE+jGrEVt37W+ut7CH784CsDDt0QSGdD9WmRFS7b6euoOHqSmoRWodv9+dYuLJjRGI27DhjUEoJG4xcWh8/S4xBUdqzj7HOm7vufED99TnH3OflzvYiRqZCKDbryFfrEj0Bs6eQ9FRYGs3Wqr0NG1YGv4ffcMhpH3Q/y94BXUuTWJTtfmUPToo4+SnJxMeHg4999/Px9//DH+/v4dUZu4hBOlJ1iZvpIvMr6gxqK+Obrp3ZgeOZ15MfOI8Yu5whVEW1irzWog0oC+txuGoKYbnbpfseurttLE2iVplJ+vxau3K7MWDcfDx9jmOpZuOkleeR3hfm48Nn7AtfxIwolZKyup3b+fmj17qUlNpe7QIXWtnya0Xl64jRiOe/xI3EfG4zp0qDrA2QkpikJx1llO7tnFiV3fU5R11n6fTq+n77DhDLrxFqJGJnZ+9xiAuU4dJ7T7Hcg70Hg8fDQkPgSDZoDeOf/bivbX5jFFWq2WiIgIhg8fftkmzdWrV19zcc7E0WOKzFYzG89tJPl4MvsK99mP9/fpz7yYecyMmomXi1en19UT1J+rQKPRoA9yR+vStnEXddVm1i7ZT1FWFR69jMz5zQh8Atr+xp+eX8m0pdux2BSWLxzJxOvkL9buwnL+vNoK1NAVVp+e3mI2mC7AXw1A8fG4jxqJMTraoWOArqS+poZzh9I4nbaX0wf2UVVcZL9Pq9PTL3Y4A0ffRNTIRFw9HNTiWZYFe5dD6odQ29D9qDPC9XepYahPrGPqEu2uQ8cU3XPPPd12hpkzyq/OZ9WJVXx64lOK64oB0Gl0TIiYwPyY+YwKHiX/PzqYMeLqQrCp1sIXfztAUVYVbt4uzFoUd1WBSFEUnltzCItN4dbBQRKIujBFUTBnZze0Au2ldm8qprNnW5xniIhQA9BItSXIEBHh1L/nVouZwtOZnDtykDNpqeSeOIatyRhTvcGF8KHDGDj6JgaMHI2roybjKAqc2a7uR3Z8XeOq0z7h6l5kw+8BD9nOqCe7qsUbRceyKTZ+yPuBlOMpbMnegq3hFzfALYC7Bt7FHdF3EOQhH4zOzFxv5cukAxSeqcDVw8CsX8XhG3x1Yzw+3ZfDnjOluBl0PD9jcDtXKjqaoijU/PADZas/o+bHH7EUFjY/QaPBOHCgvRXIbUQ8hiDnXneqrrqKvBPHyUk/Sk76UfJPnsBiNjU7x7dPCP3i4ukfN5KwwUMxuLS9y7jdlGRC+jew/19QeLTxeP+bIeEhGDgVdLLtjWiH2Wei/ZTXl/N5xuesTF/JmYoz9uMJwQnMi5nH+IjxGLSdPPhQtJnFbOWrtw6Sd6ocFzc9M38VR+/Qq/vLuKzGxMtfHQPgfyZGE+br3p6lig5kLS+nfM0aSpNTMJ0+3XiHwYDbkCFqAIqPx334cHQ+zrtmmKIoVJwvJLchAOWkH1PHBf1k5IWrpxehgwbTd9hw+sfG0yu4j4MqRl1t+twuOPGteis+2XifwR1i56thKPA6x9UonJKEIidwtPgoKekpfJX5FXVWdSl9T4MnM6NmcnfM3UT1inJwhaK1rBYb37x7mOzjpRiMOmY8EUtAxNWP9Xr123SKq01EB3rywE3927FS0VFqDx+hNPljKr5cZ98aQ+vujs/sWXhNuQ23YdejdXPAgOJWMtXWUHA6g4KMk+RlnCQ3/ShVJcUtzusV3IfQmMGExAwmNGYwfiGh17yC9TWpOg+nNqghKGMz1Fc03qfVQ8QYdVPW2Png1sthZQrnJqHIwT44/AGvpb5m/z7aN5r5MfOZHjkdd4O0CnQlNquN9cuPcPZQMXqDlmmPDSM48upbANKyyvjPbnXK8v/NHiprEjkxW10dFV99TWlyMnUHD9qPGwcOxPdnC/CePsMpp8ib6+soPHOagsyTFGScJD/jJCV5OS1agbQ6HYH9owhtCEAhMdd1/l5jP6Uo6myxk+vVIJSTSrMVU939IfpWGDgFosaDq/O2xgnnIaHIwW4Ou5ml+5cyqe8kFgxaQFxAnFMPqBQXZ7MpbPzgGJn7z6PVa5j6yPWEDrz6Dw2rTR1crShwx/BQRkfK4E9nZDp7ltLkFMpWr8Z2YYd4gwHvKVPwXTAftxEjnOb32WI2U3TuDPkZJ+0hqCj7HMpF9j3z8g8gODKaoMgBhAwcRPCAgRiMTrByc30VZG6Bk9/CyQ1Qmdf8/j6xED1FDUIhI0DWzRNtJKHIwSJ7RfLd3d/JPmRdmGJT2PLv45zcU4BWq+G2h64nYvC1hZh//3iWwzkVeLnqefZ2GffgTBSLhaotWyj9OJnqHTvsxw0hIfSaP59ed96BvrdjQ6zVYqE4+xwFmacoyFRbgM6fPYPN2nIBUnefXgRHRRMcNZCgqAEE9R/g+Fagpkoy4cR6NQid+R6sTQZ0GzzUVqDoW9WbtwPHMYluQUKRE5BA1HUpisL2lBMc25GHRgOTHxhC/2HXtphpYWUdr36bDsDTU2II8HLgrB1hZy4spOyTTyhbuQpLfr56UKPB4+ax+C5YgOfYsQ5ZO8hms1Kam0t+xgkKMk+Rn3mS86czW8wGA3UwdHBUNEGR0QRFDSA4KhpP395O05oFNAyS/gFOfKN2jRWdaH6/bz8YeJsagvrdBHr5/RDtR0KREFdJURR2rs7g0NYc0MDEewczIP7ap1K/tO4YlXUWrg/14WeJfduhUnG1FEWhZvceSj/+mMqNG8GitrTofH3pNfdOes2bh0tYWKfWU1aQp47/yTxFQcZJCk5nYK6rbXGui5s7QZED7CEoOGoA3gFBzhWALqguUrvDTn4LpzZDfXnjfRcGSQ+conaN+UfLvmOiw0go6omqi6AiBwKHyNoc12D3l6dJ26AOhB73sxhiEoOv+Zo7M4pYk5aLRgN/njMU3WW2DxEdx1pZSfmatZQmJ2PKaNxX0G3ECHwXzMdrypQO31ZDURQqi8+rY4AuhKDMk9RXV7c4V280EtQ/qiH8qCHIN7iPY2eDXY7VArn71VlipzZA9l6aD5Lu3dglFjVBZouJTiOfiD3Rsc/hy1+r/fGhIyBsJIQlQNgo8AxwdHVdQuo3Z9i77gwAY+dFM2Rs6DVf02Sx8fs1hwH4RWJfhoX1uuZrirapO3qU0o+TKf/yS5RatfVF4+6Oz8wZ+C5YgGtMx+0rWFVaYh//cyEE1VaUtzhPZzAQ2DdSHf8TGU1w5AD8wsLRap132w8ASs+oIShjM2Rua94aBBA8rLE1KHQEOPvPI7olCUU9UX0VGH3UN6Uz29XbBb79GgNS+CgIGgo6WTCyqQObsvhhTSYAY+ZEMWx8eLtc973vM8k4X42/pwtP3iqb+nYWW309ld98Q+l/Pqb2QOOGoMboAfSaPx+fWbPQtfO2FDUV5eog6IyT5DfMBKsqLWlxnlanwz+8n338T1BkNP7hEej0XeB3sq5CfW+5EIRKMpvf7+oDkePUlqDoW8E7xCFlCtFUjwpFc+bMYcuWLUycOJFPPvnE0eU4zo3/A2MeVwcwZu+G7D2QtQfOH1f/mis9A4dWqufq3SBkuBqQwkapgcmr524xcmR7Dt+vUlfHHTWtHyOmtM+Yn+zSGpZuUq/7u9uvw8e9C3zodXGmc+coTUmh/NPVWMvK1IMGA96TJ6vT6UeObJfxN3XVVRSezmjWAlRxvqDFeRqNFr/QMPsssODIaAL69kffwd107aZpl1jGZvV9RWnc/wytXn3/iJqg3kLipDVIOB2Novxkla5ubMuWLVRWVvLhhx+2ORS1ZZfdLquuXF0ALWuP+oaWvQfqylqe1yuiMSCFjYLg60HfRd64W0GxKdTXWKitMlFbZaau0kxtlYmywlrSNp4DBYbfGsGYOVHtNmj1wX/uZcPRAhL6+5Hy0GjnHAzbDShWK1Vbt6rT6bc3tpDqQ/rge/c8es29E73/1c8eNNXVUng6Q50F1rAeUGle7kXP9e0T2jAQWg1Bgf0icXF13pWuL6r0DGR8p4ag01vV95Cm/KIaQ1C/m8C1m753CqfWls/vHtVSNG7cOLZs2eLoMpyXq0/jGxiAzQbFpxoC0m51MGThUSg7p94Of6qep3eFPnHq2KTwhqDkRE3hNqtNDTdVZmorTS2+rq00U1d14WsTddUWFNul/1a4fnxYuwaijUcL2HC0AL1Ww4uzh0og6gCWoiLKPvmE0pUrseQ2LPin0eBx003qdPpbbm7zdHqLyUThmUx1IcSGEFSck9ViNWgAn8AgdRq8fTbYAIzuzrfC9RW1pUsscjz4yuxJ0bU4TSjatm0br776KqmpqeTl5fHZZ58xe/bsZuckJSXx6quvkp+fT2xsLH/7299ISEhwTME9gVYLAQPV2/Cfq8fqK9XWpAtdbtl7oLYEsn5Qb7saHusd1rzLrc+wdl9PxGqxkZNeepGQY1K/b/i6vqblgnWt4eKmx83TgJuXAVdPF9w8DQT192bwjSHtFlxqTVb+8MURAB4Y25+BQVe/T5poTlEUavfupfTjj6nYsBHMZgB0vXrhc+cd+M6bh0tERKuuZbWYKTp3tiH8nCA/8xTFWWexWa0tzvX0622fBRYcOYDAyAG4e3fRtchs1uZdYlm7m3eJaXTqH0L2LrHh0iUmujSnCUXV1dXExsZy//33c8cdd7S4PyUlhcWLF/P222+TmJjIkiVLmDJlCunp6QQGqmvDxMXFYbG0/ABcv349ISHO03LRpRm91L8EI8ep3yuK+tdi1u7GFqWCI1CRDUey4chn6nk6F3UJ/rCGoBSeAN6h17TeiNVi44u/HbjyiQAacPUwNIQcNeC4Xvi3Ifi4ebrY/3X1NKDrhL3Gkr47RXZpLSE+rvzPhOgOf76ewFpVRfnatZQlJ1N/8pT9uFtcnDqd/rbb0BovHdBtVivFOVlN1gI6wfmzp7Fe5L3FzdunyTpAaguQp69fh/xcnab0bGMIki4x0cM4TSiaOnUqU6dOveT9r7/+Og8++CD33XcfAG+//Tbr1q1jxYoVPPPMMwCkpaW1Wz319fXU19fbv6+oqLjM2T2YRgO9o9Rb3AL1WH2V+tflhS63rN1QU9Q4TukCrz7NQ1KfODC0fn8lg1FHYF8ve4vOhZDj1jTsNAQdo4cBrZOt+XOqsIp3tqlr4LwwcwgeRqf5deyS6o4fV6fTf/EFSk0NABo3N3xmzMB3wXxcr2u5XYpis1Gan9tsEHThmQwsTX73LzB6eDRpAVJXhPbqHdD1uzvrKtTtM+xdYhnN73f1gf63NASh8eoMVSG6qS7xLmwymUhNTeXZZ5+1H9NqtUyaNIldu3Zd5pFX7+WXX+aPf/xjh1y72zN6Qv+x6g3U1qTS040BKXsP5B9SN3M89rl6A9Aa1EHbF8YlhY1SB3Vf4kNHo9Fw17OjOumHal+KovD82sOYrQoTBgVy6+CeO6PvWthMJiq//VadTr9/v/24S1QUvvPn4zN7FjovtUtSURTKCwuarQVUcPoUptqWq0EbXN0IioyyrwMUHDUQn6Dgrh+AoGWXWPYesDVpBWvaJRY5Xu0Sk0VeRQ/RJV7pRUVFWK1WgoKaf3AEBQVx/PjxVl9n0qRJHDhwgOrqasLCwli1ahVjxoy56LnPPvssixcvtn9fUVFBeHj7rEfT42g04Bep3obdrR4z1UBeWmNIytoN1YWQu0+9/fi2ep5nUGNAChulvkG7uDvsR2kvnx/IZWdGMUa9lj/MGNI9Pmw7kSk7m7KUFMo++RRraal6UK/Ha/IkfOcvwG3USKpLS8g8dqjJTLBT1FVVtriW3sVIYL9I+zT4oMho/EJCnXc16KtRehYyG2aJZW5tOavUL/InXWJddAyUENeoS4Si9rJx48ZWn2s0GjFeZtyBuEYu7tD3BvUGamtS2bnGLras3ZB/EKoK4PiX6g3UtU6ChjZ2uYWNBN/+XWovpIo6My+uOwbA4+MHENG764e8zqBYrVRt20ZpcjLV27bbZ3npg4PxnXc3xqm3cWjPLvZs+Zr85UupKS9rcQ2tTk9A3/4ERw0gqKEbrHdYBFoHbOTags0Gljr1Zq5t5b81YK4DS+0l/q1Tt/T56Swxow9E3qJ2h0WOB7/+jvmZhXAyXSIU+fv7o9PpKChovuBZQUEBwcHXvt+UcAIajTp917cvXD9XPWauhbwDjSEpe4/a5ZaXpt72/EM9zyOgoSWpYbuSkOFqF56Ten39Cc5X1tPf34OHbol0dDlOz1JcTNmnqylLTsac27jmj8eNN+L7swV43nILGr0eU10tP3yajKLYANBotfiH97VvhhoUGY1/RD/0hlYujGk1tyGcXOrfywWWn/xrbTmOqd1odOrvSNNZYtIlJkQLXeK3wsXFhfj4eDZt2mSfpm+z2di0aROPP/54hz53UlISSUlJWC8y9VZ0MIMbRIxWb6C2DFTkNJnptkcNTdXnIf0r9Qag0ULQkCbblSSo3QNO0Jp0OKecf+46A8CfZg3BqHeCFgonpCgKtfv2UfpxMhXffts4nd7HB5/Zs/CdMw2XEH+1G/b8UTDX4mKuYeSNsXh6uBAc4EmArxED9WCuAvNOOL4JDtU2tK7UXqSV5SehRnHg77zWoL7+9a7q5AO9Wxv/dW18vGsvdXkM6RIT4oqcZkXrqqoqTp1Sp88OHz6c119/nfHjx+Pn50dERAQpKSksXLiQd955h4SEBJYsWcLKlSs5fvx4i7FGHaFHrGjdFVnqIe+gOtMtq2G2W0V2y/Pc/Br3cwsbBaHx6vICnchmU7jjrZ2kZZUxfVgflv1sRKc+v9PLTcO6630qvj9E6d5i6s+b7He5BtjwHViPd0g5Wp2t82vT/yRoXPLftgYYt5bX0LtKK44Q7agtn99OE4q2bNnC+PHjWxxfuHAhH3zwAQDLli2zL94YFxfH0qVLSUxM7JT6JBR1IRW5zbvcctMu0jWhgcDBzReY7D1AXbCyg3y8+xzPrj6Ep1HPpt/cQpB365cf6LbMdXDkM8yb36F4cyblZ9ywWdT/BxqdDe++tfgOqMHNz9zysVoDGNwbg8VPv3Zxv8T97g0hxP3KrSwX/nWCVkYhxNXpkqHI2Uko6sIsJnUJgAuLS2btgfJzLc9z7dU4LilspHprpy6H4qp6Jry2lfJaM89PH8z9N/Xwga2lZ2DvCtj3L6gtwVyj5dQXQaBocAnpje+U0fhMvhGdb+9LBxudbJorhLgy2ftMiKb0LhAWr974b/VYZX6TmW571HVb6srg1Eb1BoAGAgY139PNP+aqWpNe+fo45bVmruvjzT1jeuh+UDYrnNqkDpA/uQFo+HvMOwzDhPsIjDTiGjcK98REWaJACOEQ0lJ0BU0HWp84cUJairorqxkKDjfu55a9W23N+CmjT0PAauhyC4sHN9/LXnrPmRLueltdZPTTR24gvu/lz+92qoth/7/UlqGys43HoybAqAch+lYZQyOE6DDSfdYBpPusB6oqVAduX9iuJCdVnbH0U/4DG7vcwhPU1qWGTTHNVhvTl35PekEl80eF88qdwzr5h3AQRVH/e+15Dw6vbhzT5eoDw38JI+9Xt4YRQogOJqGoA0goElgtUHikscste0/LfaIAXLwgJA48AjhWpuW7syZMBm8enDwcD5/e6tglVx9w69X4dXfZWdxUA4c/UcNQXpPNevvEqq1CQ+/sFiuSCyG6DglFHUBCkbio6uLGsUnZuyFnH5iq2n4dF6+GkORz8dB00fsavje4OX52VHEG7FkOaR817qquM8LQO2DUf6lLIDi6RiFEjyQDrYXoLB69IeY29QbqYOLCY1BwmFXbD5KTn8cALyvTot3Q1FdAbZk6oLuuXP3aXK0+zlSp3sqz2l6DzuXSgemS3184dg2tVFYLnPxWbRXK2Nx4vFdfGPUAxP1C/e8jhBBdhIQiIdqTVgfBQ/muPJCnsr3QaTV8ec9NaPpc4q8Tq1kNSBdCUl1Z89BUV65+3/TrpvcpVrCa1FW9q89fXc1G79YFqAv3uXjAiW9g7wdNFsrUqAOmR/0XDJjYfboDhRA9ioSiK5BtPkRblFSbeHPjCf79o7oO0r039OO6SwUiUNfa8fBXb22lKGpXXWsD1E+/v9BKVV+h3srbXgJufjCiYeC0b7+ruIAQQjgPGVPUSjKmSFxOvcXKhzvP8LfNp6isswBw6+Ag3pgXh4fRSf/2sJjUMNS0haq1gar3ADUIDZmjrgIthBBOSsYUCdFJFEXhq0P5vPLNMbJKagEY3Meb56Zdxw0DrqL1pzPpXUB/la1UQgjRDUkoEuIq7TtXyp/XHSP1bCkAgV5GnpoSwx0jwtBpZaaVEEJ0NRKKhGijrJIa/vJtOl8cyAXAzaDj4VsieejmSNxd5FdKCCG6KnkHF6KVKurM/P27DFbsOI3JYkOjgbkjwnhySozseC+EEN2AhCIhrsBitfHx7nO8sfEkJdUmAG6I6s3/TruOISE+Dq5OCCFEe5FQdAUyJb/nUhSF79ILeemr45wqVFepjgrw4He3X8eEQYGyk7sQQnQzMiW/lWRKfs9yNLeCl746xvenigDw83Bh0aRoFiREYNBpHVydEEKI1pIp+UJcpcKKOl5bf4KVqVkoCrjotNx3Yz8eHT8AHzeDo8sTQgjRgSQUCQHUmqz8Y3smb2/NoMakdpVOH9aH3942iHA/2dVdCCF6AglFokez2RQ+25/Dq9+mk19RB8DwiF48N20w8X19HVydEEKIziShSPRYuzKK+fNXRzmcUwFAmK8bv71tENOH9ZFB1EII0QNJKBI9Tub5Kl7++jgbjhYA4GXU89iEAdx7Qz9cDbK7uxBC9FQSikSPUVpt4s1NJ/noh7NYbAo6rYafJUSwaFI0vT2Nji5PCCGEg0kougJZp6jrq7dY+efOs/xt80kqGnawnzAokN/dPogBgV4Ork4IIYSzkHWKWknWKep6FEXh68P5vPL1cc6V1ABwXcMO9jc6+w72Qggh2oWsUyR6vOP5FTz32WH2NtnB/slbY7gzXnawF0IIcXESikS3U1RVzy/e+5GiKhOuBi0P3RzFwzdH4mGUl7sQQohLk08J0a0oisLTnxykqMpETJAXH96fQLCP7GAvhBDiymQTJ9GtfPTjOTYfL8RFr+XNBXESiIQQQrSahCLRbZwqrOLP644C8NvbBjEoWAbECyGEaD0JRaJbMFlsLErZT53Zxthof+67oZ+jSxJCCNHFSCgS3cLrG05wOKcCX3cDf70rFq3MMBNCCNFGEoquICkpicGDBzNq1ChHlyIuYVdGMe9sywDg5TuGEeQt44iEEEK0nSze2EqyeKNzKq8xM/XNbeSW1zFvZDj/b+4wR5ckhBDCibTl81taikSXpSgKz609TG55Hf16u/P8jMGOLkkIIUQXJqFIdFlr0nL44kAuOq2GN+bFyeKMQgghromEItElZZXU8PyaIwD8amI0wyN8HVyREEKIrk5CkehyrDaFxSvTqKy3EN/Xl0fHRTm6JCGEEN2AhCLR5by15RR7zpTiadSzZF4cep28jIUQQlw7+TQRXcqBrDKWbDwJwB9nDiHcz93BFQkhhOguJBSJLqO63sKilDQsNoVpw/pwx4hQR5ckhBCiG5FQJLqMF9cd5XRRNX18XHlp9vVoNLJqtRBCiPYjoUh0Cd8eyefj3VloNPDa3bH4uBscXZIQQohuRkKRcHqFFXU88+lBAB4aG8kNUf4OrkgIIUR3JKFIODWbTeHJTw5SWmNmcB9vFt860NElCSGE6KYkFF2BbAjrWB/uOsO2E+cx6rUsXRCHUa9zdElCCCG6KdkQtpVkQ9jOl55fyYxl32Oy2PjTrCHcM6afo0sSQgjRxciGsKLLq7dY+VXyfkwWG+NjAvjl6L6OLkkIIUQ3J6FIOKVXv0nneH4lvT1c+MvcWJl+L4QQosNJKBJO5/uTRbz3/WkA/jJ3GAFeRgdXJIQQoieQUCScSmm1id+sSgPg54kRTLwuyLEFCSGE6DEkFAmnoSgKv/vsEAUV9UQGePDctMGOLkkIIUQPIqFIOI1Vqdl8fTgfvVbDm/OG4+Yi0++FEEJ0HglFwimcLa7mj58fAWDxrQO5PszHwRUJIYToaSQUCYezWG0sSkmj2mQlob8fD98c5eiShBBC9EASioTD/W3zKfafK8PLVc8b8+LQaWX6vRBCiM4noUg4VOrZUv62+SQAL84eSmgvNwdXJIQQoqeSUCQcpqrewq9T0rApMDsuhFlxoY4uSQghRA8moUg4zB8+P8K5khpCe7nxp9lDHV2OEEKIHk5CkXCIrw7l8UlqNloNvDEvDm9Xg6NLEkII0cNJKBKdLq+8lmdXHwLgkXFRJPT3c3BFQgghhIQi0clsNoUnVx2gvNbMsDAfFk0a6OiShBBCCEBC0RUlJSUxePBgRo0a5ehSuoXl359mx6li3Aw6lsyLw6CTl6AQQgjnoFEURXF0EV1BRUUFPj4+lJeX4+3t7ehyuqSjuRXMTtqByWrjpTnX87PECEeXJIQQoptry+e3/JkuOkWd2cqvkvdjstqYPDiIBQnhji5JCCGEaEZCkegUr3x9nJOFVQR4GXnljuvRaGTVaiGEEM5FQpHocFvSC/lg5xkAXp07jN6eRscWJIQQQlyEhCLRoYqr6nly1UEA7r2hH+NiAh1ckRBCCHFxEopEh1EUhd9+eoiiqnoGBnnyzNRBji5JCCGEuCQJRaLDfLw7i43HCnDRaVkybziuBp2jSxJCCCEuSUKR6BCZ56v4vy+PAvDUlBgGh8gyBkIIIZybhCLR7sxWG4tS0qg1W7lxQG8euKm/o0sSQgghrkhCkWh3Szae4GB2OT5uBv56VyxarUy/F0II4fwkFIl2tft0CX/fkgHAy3dcTx8fNwdXJIQQQrSOhCLRbirqzPw6JQ1FgbnxYdx+fR9HlySEEEK0moQi0W6eX3OYnLJaIvzc+cPMIY4uRwghhGgTCUWiXaxNy2FNWi46rYY35sXhadQ7uiQhhBCiTSQUiWuWXVrDc2sOA/D4+AHE9/V1cEVCCCFE20koEtfEalNYvPIAlXUWhkf04okJAxxdkhBCCHFVJBSJa/LOtgx2ny7Bw0XHknlx6HXykhJCCNE1ySeYuGqHsst5ff0JAF6YOYS+vT0cXJEQQghx9SQUiatSa7Lyq5T9WGwKU4cGc1d8mKNLEkIIIa6JhCJxVV5cd5TM89UEeRt5ac71aDSyarUQQoiuTUKRaLONRwv494/nAHjtrjh8PVwcXJEQQghx7SQUiTY5X1nPbz89CMB/3dSfm6L9HVyREEII0T4kFIlWUxSFpz85QHG1iUHBXjx1W4yjSxJCCCHaTY8JRVlZWYwbN47BgwczbNgwVq1a5eiSupx//XCW79LP46LXsnTBcIx6naNLEkIIIdpNj9mLQa/Xs2TJEuLi4sjPzyc+Pp7bb78dDw+ZRt4aJwsq+fO6YwA8O3UQA4O8HFyREEII0b56TCjq06cPffqou7YHBwfj7+9PSUmJhKJWqLdY+VVyGvUWGzcPDODeG/o5uiQhhBCi3TlN99m2bduYMWMGISEhaDQa1qxZ0+KcpKQk+vXrh6urK4mJiezevfuqnis1NRWr1Up4ePg1Vt0zvL7+BEfzKvDzcOGvc4fJ9HshhBDdktOEourqamJjY0lKSrro/SkpKSxevJgXXniBffv2ERsby5QpUygsLLSfExcXx9ChQ1vccnNz7eeUlJRwzz338O6773b4z9Qd7Mwo4t3tmQC8csf1BHq7OrgiIYQQomNoFEVRHF3ET2k0Gj777DNmz55tP5aYmMioUaNYtmwZADabjfDwcJ544gmeeeaZVl23vr6eyZMn8+CDD/LLX/7yiufW19fbv6+oqCA8PJzy8nK8vb3b/kN1QeU1Zm57cxt55XUsSAjn5TuGObokIYQQok0qKirw8fFp1ee307QUXY7JZCI1NZVJkybZj2m1WiZNmsSuXbtadQ1FUbj33nuZMGHCFQMRwMsvv4yPj4/91tO62hRF4XdrDpFXXkd/fw9+P32wo0sSQgghOlSXCEVFRUVYrVaCgoKaHQ8KCiI/P79V19ixYwcpKSmsWbOGuLg44uLiOHTo0CXPf/bZZykvL7ffsrKyruln6GpW78th3cE89FoNS+bF4e7SY8bkCyGE6KF6zCfdTTfdhM1ma/X5RqMRo9HYgRU5r6ySGl74/AgAiyZFExvey7EFCSGEEJ2gS7QU+fv7o9PpKCgoaHa8oKCA4OBgB1XVPVmsNhalpFFVb2FUP18eGTfA0SUJIYQQnaJLhCIXFxfi4+PZtGmT/ZjNZmPTpk2MGTPGgZV1P3/fkkHq2VK8jHpevzsOnVam3wshhOgZnKb7rKqqilOnTtm/P336NGlpafj5+REREcHixYtZuHAhI0eOJCEhgSVLllBdXc19993XoXUlJSWRlJSE1Wrt0OdxBvvPlfLmppMA/Gn2EML93B1ckRBCCNF5nGZK/pYtWxg/fnyL4wsXLuSDDz4AYNmyZbz66qvk5+cTFxfH0qVLSUxM7JT62jKlryuqrrcwbel2zhTXMCM2hKXz42SRRiGEEF1eWz6/nSYUObvuHop++8lBUvZmEeLjyteLbsbHzeDokoQQQohr1u3WKRId65vD+aTszUKjgdfnxUkgEkII0SNJKOrhCirqeGb1QQAevjmK0ZG9HVyREEII4RgSiq4gKSmJwYMHM2rUKEeX0u5sNoUnVx2grMbM0FBvFk8e6OiShBBCCIeRMUWt1B3HFP2QWcz8d3/A1aDlyyfGMiDQ09ElCSGEEO2qLZ/fTjMlX3S+0ZG9+ef9CRRV1UsgEkII0eNJKOrhbh4Y4OgShBBCCKcgY4qEEEIIIZBQdEXdeaC1EEIIIRrJQOtW6o4DrYUQQojuThZvFEIIIYRoIwlFQgghhBBIKBJCCCGEACQUCSGEEEIAEoqEEEIIIQAJRVckU/KFEEKInkGm5LeSTMkXQgghuh6Zki+EEEII0UYSioQQQgghkFAkhBBCCAGA3tEFdBUXhl5VVFQ4uBIhhBBCtNaFz+3WDKGWUNRKlZWVAISHhzu4EiGEEEK0VWVlJT4+Ppc9R2aftZLNZiM3NxcvLy80Gk2rHjNq1Cj27NnTwZU55vnb69pXe52reVxrH9Me51VUVBAeHk5WVla3na0or++OvU5bH9uW81tzrry+5fXdkdfpzNe3oihUVlYSEhKCVnv5UUPSUtRKWq2WsLCwNj1Gp9M59A2jI5+/va59tde5mse19jHteZ63t3e3/dCQ13fHXqetj23L+a05V17f8vruyOt09uv7Si1EF8hA6w702GOPddvnb69rX+11ruZxrX1Me5/XXTn65+/Or++reWxbzm/NuY7+/+tojv755fV99edfS13SfSZEB5DFPkV3Jq9v0V1JS5EQHcBoNPLCCy9gNBodXYoQ7U5e36K7kpYiIYQQQgikpUgIIYQQApBQJIQQQggBSCgSQgghhAAkFAkhhBBCABKKhBBCCCEACUVCOMSXX35JTEwM0dHRvPfee44uR4h2NWfOHHx9fZk7d66jSxGiTWRKvhCdzGKxMHjwYL777jt8fHyIj49n586d9O7d29GlCdEutmzZQmVlJR9++CGffPKJo8sRotWkpUiITrZ7926GDBlCaGgonp6eTJ06lfXr1zu6LCHazbhx4/Dy8nJ0GUK0mYQiIdpo27ZtzJgxg5CQEDQaDWvWrGlxTlJSEv369cPV1ZXExER2795tvy83N5fQ0FD796GhoeTk5HRG6UJc0bW+voXoyiQUCdFG1dXVxMbGkpSUdNH7U1JSWLx4MS+88AL79u0jNjaWKVOmUFhY2MmVCtF28voWPZmEIiHaaOrUqbz44ovMmTPnove//vrrPPjgg9x3330MHjyYt99+G3d3d1asWAFASEhIs5ahnJwcQkJCOqV2Ia7kWl/fQnRlEoqEaEcmk4nU1FQmTZpkP6bVapk0aRK7du0CICEhgcOHD5OTk0NVVRVff/01U6ZMcVTJQrRaa17fQnRlekcXIER3UlRUhNVqJSgoqNnxoKAgjh8/DoBer+e1115j/Pjx2Gw2nn76aZl5JrqE1ry+ASZNmsSBAweorq4mLCyMVatWMWbMmM4uV4g2k1AkhAPMnDmTmTNnOroMITrExo0bHV2CEFdFus+EaEf+/v7odDoKCgqaHS8oKCA4ONhBVQnRPuT1Lbo7CUVCtCMXFxfi4+PZtGmT/ZjNZmPTpk3SfSC6PHl9i+5Ous+EaKOqqipOnTpl//706dOkpaXh5+dHREQEixcvZuHChYwcOZKEhASWLFlCdXU19913nwOrFqJ15PUtejLZ5kOINtqyZQvjx49vcXzhwoV88MEHACxbtoxXX32V/Px84uLiWLp0KYmJiZ1cqRBtJ69v0ZNJKBJCCCGEQMYUCSGEEEIAEoqEEEIIIQAJRUIIIYQQgIQiIYQQQghAQpEQQgghBCChSAghhBACkFAkhBBCCAFIKBJCCCGEACQUCSG6sHHjxrFo0SL79/369WPJkiUd+pzFxcUEBgZy5swZQF0BWqPRUFZW1mHP+cwzz/DEE0902PWFECoJRUKIDnXvvfei0WjQaDQYDAb69+/P008/TV1dXbs/1549e3jooYfa/bpN/fnPf2bWrFn069evQ5+nqSeffJIPP/yQzMzMTntOIXoiCUVCiA532223kZeXR2ZmJm+88QbvvPMOL7zwQrs/T0BAAO7u7u1+3QtqampYvnw5DzzwQIc9x8X4+/szZcoU3nrrrU59XiF6GglFQogOZzQaCQ4OJjw8nNmzZzNp0iQ2bNhgv7+4uJgFCxYQGhqKu7s7119/PR9//HGza1RXV3PPPffg6elJnz59eO2111o8T9PuszNnzqDRaEhLS7PfX1ZWhkajYcuWLQCUlpby85//nICAANzc3IiOjub999+/5M/x1VdfYTQaGT169CXPqampYerUqdx4442UlZXZ60hOTuaGG27A1dWVoUOHsnXr1maPO3LkCNOnT8fb2xsvLy/Gjh1LRkaG/f4ZM2aQnJx8yecVQlw7CUVCiE51+PBhdu7ciYuLi/1YXV0d8fHxrFu3jsOHD/PQQw/xy1/+kt27d9vPeeqpp9i6dStr165l/fr1bNmyhX379l1TLb///e85evQoX3/9NceOHeOtt97C39//kudv376d+Pj4S95fVlbG5MmTsdlsbNiwgV69ejWr/ze/+Q379+9nzJgxzJgxg+LiYgBycnK4+eabMRqNbN68mdTUVO6//34sFov98QkJCWRnZ9vHMgkh2p/e0QUIIbq/L7/8Ek9PTywWC/X19Wi1WpYtW2a/PzQ0lCeffNL+/RNPPMG3337LypUrSUhIoKqqiuXLl/PRRx8xceJEAD788EPCwsKuqa5z584xfPhwRo4cCXDFcUJnz54lJCTkovfl5+czb948oqOj+c9//tMs9AE8/vjj3HnnnQC89dZbfPPNNyxfvpynn36apKQkfHx8SE5OxmAwADBw4MBmj7/wvGfPnu3U8UxC9CQSioQQHW78+PG89dZbVFdX88Ybb6DX6+0BAcBqtfLSSy+xcuVKcnJyMJlM1NfX28cHZWRkYDKZSExMtD/Gz8+PmJiYa6rrkUce4c4772Tfvn3ceuutzJ49mxtuuOGS59fW1uLq6nrR+yZPnkxCQgIpKSnodLoW948ZM8b+tV6vZ+TIkRw7dgyAtLQ0xo4daw9EF+Pm5gao3XNCiI4h3WdCiA7n4eHBgAEDiI2NZcWKFfz4448sX77cfv+rr77Km2++yW9/+1u+++470tLSmDJlCiaT6aqfU6tV394URbEfM5vNzc6ZOnUqZ8+e5de//jW5ublMnDixWYvVT/n7+1NaWnrR+6ZNm8a2bds4evRom2u9EHgup6SkBFAHkwshOoaEIiFEp9Jqtfzud7/jueeeo7a2FoAdO3Ywa9YsfvGLXxAbG0tkZCQnTpywPyYqKgqDwcCPP/5oP1ZaWtrsnJ+6EB7y8vLsx5oOum563sKFC/noo49YsmQJ77777iWvOXz48EuGnldeeYWFCxcyceLEi57zww8/2L+2WCykpqZy3XXXATBs2DC2b9/eIrQ1dfjwYQwGA0OGDLnkOUKIayOhSAjR6e666y50Oh1JSUkAREdHs2HDBnbu3MmxY8d4+OGHKSgosJ/v6enJAw88wFNPPcXmzZs5fPgw9957r7016GLc3NwYPXo0r7zyCseOHWPr1q0899xzzc55/vnnWbt2LadOneLIkSN8+eWX9qByMVOmTOHIkSOXbC3661//ys9//nMmTJjA8ePHm92XlJTEZ599xvHjx3nssccoLS3l/vvvB9TxRhUVFcyfP5+9e/dy8uRJ/vWvf5Genm5//Pbt2xk7dmyrWpWEEFdHQpEQotPp9Xoef/xx/vKXv1BdXc1zzz3HiBEjmDJlCuPGjSM4OJjZs2c3e8yrr77K2LFjmTFjBpMmTeKmm2667EwwgBUrVmCxWIiPj2fRokW8+OKLze53cXHh2WefZdiwYdx8883odLrLTnu//vrrGTFiBCtXrrzkOW+88QZ33303EyZMaNaS9corr/DKK68QGxvL999/z+eff26f6da7d282b95MVVUVt9xyC/Hx8fzjH/9oNsYoOTmZBx988LI/rxDi2miUph3uQgghLmvdunU89dRTHD58+LItVRecOXOG/v37s3//fuLi4q7qOb/++mt+85vfcPDgQfR6mR8jREeR3y4hhGiDadOmcfLkSXJycggPD++U56yurub999+XQCREB5OWIiGE6EDt0VIkhOgcEoqEEEIIIZCB1kIIIYQQgIQiIYQQQghAQpEQQgghBCChSAghhBACkFAkhBBCCAFIKBJCCCGEACQUCSGEEEIAEoqEEEIIIQAJRUIIIYQQAPx/stGcYLrPfcgAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i in range(len(galaxies)):\n",
    "    radius = df3[\"Radius\"].tolist()[i]\n",
    "    mass = df3[\"Mass\"].tolist()[i]\n",
    "    def lum_function(r):\n",
    "        global i\n",
    "        current_r = df3[\"Radius2\"][i]\n",
    "        current_lum = df3[\"Lum2\"][i]\n",
    "        # find two closest points to r in current_r\n",
    "        def find_closest_numbers(numbers, target):\n",
    "            numbers2 = sorted(numbers, key=lambda x:abs(x-target))\n",
    "            return [numbers.index(numbers2[0]), numbers.index(numbers2[1])]\n",
    "\n",
    "        closest_index = find_closest_numbers(current_r, r)\n",
    "        # Interpolate a data value for the two points\n",
    "        x1 = current_r[closest_index[0]]\n",
    "        x2 = current_r[closest_index[1]]\n",
    "        y1 = current_lum[closest_index[0]]\n",
    "        y2 = current_lum[closest_index[1]]\n",
    "        m = (y2 - y1) / (x2 - x1)\n",
    "        b = y1 - m * x1\n",
    "        return m * r + b\n",
    "    ml = [mass[j] / (lum_function(radius[j])) for j in range(len(radius))]\n",
    "    plt.plot(radius, ml, label=galaxy_legend[i])\n",
    "plt.legend()\n",
    "plt.xlabel(\"Radius (kpc)\")\n",
    "plt.rcParams['text.usetex'] = True\n",
    "plt.ylabel(r\"M/L ($M_{\\odot}/L_{\\odot}$)\")\n",
    "plt.rcParams['text.usetex'] = False\n",
    "plt.yscale(\"log\")\n",
    "plt.xscale(\"log\")\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.11.4"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}