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wrighter/aapl_zipline.ipynb

Last active December 9, 2019 00:06
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Shows a few simple zipline backtests
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aapl_zipline.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt\n",
"import pandas as pd\n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"%load_ext zipline"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"A simple model that buys 10 shares of Apple each period."
]
},
{
"cell_type": "code",
"execution_count": 3,
"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>AAPL</th>\n",
" <th>algo_volatility</th>\n",
" <th>algorithm_period_return</th>\n",
" <th>alpha</th>\n",
" <th>benchmark_period_return</th>\n",
" <th>benchmark_volatility</th>\n",
" <th>beta</th>\n",
" <th>capital_used</th>\n",
" <th>ending_cash</th>\n",
" <th>ending_exposure</th>\n",
" <th>...</th>\n",
" <th>short_exposure</th>\n",
" <th>short_value</th>\n",
" <th>shorts_count</th>\n",
" <th>sortino</th>\n",
" <th>starting_cash</th>\n",
" <th>starting_exposure</th>\n",
" <th>starting_value</th>\n",
" <th>trading_days</th>\n",
" <th>transactions</th>\n",
" <th>treasury_period_return</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2015-01-02 21:00:00+00:00</th>\n",
" <td>109.330</td>\n",
" <td>NaN</td>\n",
" <td>0.000000e+00</td>\n",
" <td>NaN</td>\n",
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" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-05 21:00:00+00:00</th>\n",
" <td>106.250</td>\n",
" <td>6.075516e-07</td>\n",
" <td>-5.412500e-08</td>\n",
" <td>4.165327e-07</td>\n",
" <td>-0.018585</td>\n",
" <td>0.196712</td>\n",
" <td>0.000003</td>\n",
" <td>-1063.04125</td>\n",
" <td>9.998937e+06</td>\n",
" <td>1062.50</td>\n",
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" <td>-11.224972</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.00</td>\n",
" <td>0.00</td>\n",
" <td>2</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-06 21:00:00+00:00</th>\n",
" <td>106.260</td>\n",
" <td>4.571965e-07</td>\n",
" <td>-9.825500e-08</td>\n",
" <td>-9.648674e-07</td>\n",
" <td>-0.027829</td>\n",
" <td>0.139101</td>\n",
" <td>0.000003</td>\n",
" <td>-1063.14130</td>\n",
" <td>9.997874e+06</td>\n",
" <td>2125.20</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
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" <td>1062.50</td>\n",
" <td>3</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-07 21:00:00+00:00</th>\n",
" <td>107.750</td>\n",
" <td>2.348039e-05</td>\n",
" <td>2.826870e-06</td>\n",
" <td>2.719581e-04</td>\n",
" <td>-0.015715</td>\n",
" <td>0.206972</td>\n",
" <td>0.000096</td>\n",
" <td>-1078.04875</td>\n",
" <td>9.996796e+06</td>\n",
" <td>3232.50</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
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" <td>321.292799</td>\n",
" <td>9.997874e+06</td>\n",
" <td>2125.20</td>\n",
" <td>2125.20</td>\n",
" <td>4</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-08 21:00:00+00:00</th>\n",
" <td>111.890</td>\n",
" <td>8.521334e-05</td>\n",
" <td>1.518993e-05</td>\n",
" <td>7.345319e-04</td>\n",
" <td>0.001751</td>\n",
" <td>0.236040</td>\n",
" <td>0.000283</td>\n",
" <td>-1119.46945</td>\n",
" <td>9.995676e+06</td>\n",
" <td>4475.60</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
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" <td>9.996796e+06</td>\n",
" <td>3232.50</td>\n",
" <td>3232.50</td>\n",
" <td>5</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-09 21:00:00+00:00</th>\n",
" <td>112.010</td>\n",
" <td>7.807851e-05</td>\n",
" <td>1.561292e-05</td>\n",
" <td>7.256760e-04</td>\n",
" <td>-0.006276</td>\n",
" <td>0.218111</td>\n",
" <td>0.000285</td>\n",
" <td>-1120.67005</td>\n",
" <td>9.994556e+06</td>\n",
" <td>5600.50</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1448.880183</td>\n",
" <td>9.995676e+06</td>\n",
" <td>4475.60</td>\n",
" <td>4475.60</td>\n",
" <td>6</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-12 21:00:00+00:00</th>\n",
" <td>109.250</td>\n",
" <td>1.217820e-04</td>\n",
" <td>1.757295e-06</td>\n",
" <td>2.459898e-04</td>\n",
" <td>-0.014061</td>\n",
" <td>0.203321</td>\n",
" <td>0.000372</td>\n",
" <td>-1093.05625</td>\n",
" <td>9.993463e+06</td>\n",
" <td>6555.00</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0.761052</td>\n",
" <td>9.994556e+06</td>\n",
" <td>5600.50</td>\n",
" <td>5600.50</td>\n",
" <td>7</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-13 21:00:00+00:00</th>\n",
" <td>110.220</td>\n",
" <td>1.169165e-04</td>\n",
" <td>7.521185e-06</td>\n",
" <td>4.274790e-04</td>\n",
" <td>-0.016834</td>\n",
" <td>0.188301</td>\n",
" <td>0.000367</td>\n",
" <td>-1102.76110</td>\n",
" <td>9.992360e+06</td>\n",
" <td>7715.40</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>3.046676</td>\n",
" <td>9.993463e+06</td>\n",
" <td>6555.00</td>\n",
" <td>6555.00</td>\n",
" <td>8</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-14 21:00:00+00:00</th>\n",
" <td>109.800</td>\n",
" <td>1.113310e-04</td>\n",
" <td>4.525285e-06</td>\n",
" <td>3.636721e-04</td>\n",
" <td>-0.022769</td>\n",
" <td>0.177393</td>\n",
" <td>0.000376</td>\n",
" <td>-1098.55900</td>\n",
" <td>9.991261e+06</td>\n",
" <td>8784.00</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.689259</td>\n",
" <td>9.992360e+06</td>\n",
" <td>7715.40</td>\n",
" <td>7715.40</td>\n",
" <td>9</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-15 21:00:00+00:00</th>\n",
" <td>106.820</td>\n",
" <td>1.612977e-04</td>\n",
" <td>-1.936912e-05</td>\n",
" <td>-8.730670e-05</td>\n",
" <td>-0.031721</td>\n",
" <td>0.170557</td>\n",
" <td>0.000502</td>\n",
" <td>-1068.74410</td>\n",
" <td>9.990193e+06</td>\n",
" <td>9613.80</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>-3.499660</td>\n",
" <td>9.991261e+06</td>\n",
" <td>8784.00</td>\n",
" <td>8784.00</td>\n",
" <td>10</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-16 21:00:00+00:00</th>\n",
" <td>105.990</td>\n",
" <td>1.553397e-04</td>\n",
" <td>-2.689312e-05</td>\n",
" <td>-4.701771e-04</td>\n",
" <td>-0.019023</td>\n",
" <td>0.179591</td>\n",
" <td>0.000343</td>\n",
" <td>-1060.43995</td>\n",
" <td>9.989132e+06</td>\n",
" <td>10599.00</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>-4.471937</td>\n",
" <td>9.990193e+06</td>\n",
" <td>9613.80</td>\n",
" <td>9613.80</td>\n",
" <td>11</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-20 21:00:00+00:00</th>\n",
" <td>108.720</td>\n",
" <td>2.011179e-04</td>\n",
" <td>3.515200e-07</td>\n",
" <td>1.521907e-04</td>\n",
" <td>-0.016931</td>\n",
" <td>0.172126</td>\n",
" <td>0.000420</td>\n",
" <td>-1087.75360</td>\n",
" <td>9.988044e+06</td>\n",
" <td>11959.20</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0.056105</td>\n",
" <td>9.989132e+06</td>\n",
" <td>10599.00</td>\n",
" <td>10599.00</td>\n",
" <td>12</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-21 21:00:00+00:00</th>\n",
" <td>109.550</td>\n",
" <td>1.966305e-04</td>\n",
" <td>9.425745e-06</td>\n",
" <td>2.815507e-04</td>\n",
" <td>-0.011968</td>\n",
" <td>0.167201</td>\n",
" <td>0.000448</td>\n",
" <td>-1096.05775</td>\n",
" <td>9.986948e+06</td>\n",
" <td>13146.00</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.441909</td>\n",
" <td>9.988044e+06</td>\n",
" <td>11959.20</td>\n",
" <td>11959.20</td>\n",
" <td>13</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-22 21:00:00+00:00</th>\n",
" <td>112.400</td>\n",
" <td>2.361999e-04</td>\n",
" <td>4.356854e-05</td>\n",
" <td>7.407250e-04</td>\n",
" <td>0.002725</td>\n",
" <td>0.173978</td>\n",
" <td>0.000695</td>\n",
" <td>-1124.57200</td>\n",
" <td>9.985824e+06</td>\n",
" <td>14612.00</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>6.421964</td>\n",
" <td>9.986948e+06</td>\n",
" <td>13146.00</td>\n",
" <td>13146.00</td>\n",
" <td>14</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-23 21:00:00+00:00</th>\n",
" <td>112.980</td>\n",
" <td>2.283116e-04</td>\n",
" <td>5.105106e-05</td>\n",
" <td>8.802561e-04</td>\n",
" <td>-0.002773</td>\n",
" <td>0.169288</td>\n",
" <td>0.000667</td>\n",
" <td>-1130.37490</td>\n",
" <td>9.984693e+06</td>\n",
" <td>15817.20</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>7.269664</td>\n",
" <td>9.985824e+06</td>\n",
" <td>14612.00</td>\n",
" <td>14612.00</td>\n",
" <td>15</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-26 21:00:00+00:00</th>\n",
" <td>113.100</td>\n",
" <td>2.206832e-04</td>\n",
" <td>5.267351e-05</td>\n",
" <td>8.262006e-04</td>\n",
" <td>-0.000438</td>\n",
" <td>0.163843</td>\n",
" <td>0.000662</td>\n",
" <td>-1131.57550</td>\n",
" <td>9.983562e+06</td>\n",
" <td>16965.00</td>\n",
" <td>...</td>\n",
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" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>7.262510</td>\n",
" <td>9.984693e+06</td>\n",
" <td>15817.20</td>\n",
" <td>15817.20</td>\n",
" <td>16</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-27 21:00:00+00:00</th>\n",
" <td>109.140</td>\n",
" <td>3.225146e-04</td>\n",
" <td>-6.782065e-06</td>\n",
" <td>9.789820e-05</td>\n",
" <td>-0.013623</td>\n",
" <td>0.166597</td>\n",
" <td>0.001043</td>\n",
" <td>-1091.95570</td>\n",
" <td>9.982470e+06</td>\n",
" <td>17462.40</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>-0.395121</td>\n",
" <td>9.983562e+06</td>\n",
" <td>16965.00</td>\n",
" <td>16965.00</td>\n",
" <td>17</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-28 21:00:00+00:00</th>\n",
" <td>115.310</td>\n",
" <td>4.850563e-04</td>\n",
" <td>9.187928e-05</td>\n",
" <td>1.421373e-03</td>\n",
" <td>-0.026272</td>\n",
" <td>0.167814</td>\n",
" <td>0.000373</td>\n",
" <td>-1153.68655</td>\n",
" <td>9.981316e+06</td>\n",
" <td>19602.70</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>5.204787</td>\n",
" <td>9.982470e+06</td>\n",
" <td>17462.40</td>\n",
" <td>17462.40</td>\n",
" <td>18</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-29 21:00:00+00:00</th>\n",
" <td>118.900</td>\n",
" <td>5.134132e-04</td>\n",
" <td>1.528488e-04</td>\n",
" <td>2.167635e-03</td>\n",
" <td>-0.017272</td>\n",
" <td>0.167650</td>\n",
" <td>0.000634</td>\n",
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" <td>9.980126e+06</td>\n",
" <td>21402.00</td>\n",
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" <td>0.0</td>\n",
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" <td>0</td>\n",
" <td>8.427205</td>\n",
" <td>9.981316e+06</td>\n",
" <td>19602.70</td>\n",
" <td>19602.70</td>\n",
" <td>19</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-30 21:00:00+00:00</th>\n",
" <td>117.160</td>\n",
" <td>5.189400e-04</td>\n",
" <td>1.214693e-04</td>\n",
" <td>1.824668e-03</td>\n",
" <td>-0.029629</td>\n",
" <td>0.168390</td>\n",
" <td>0.000801</td>\n",
" <td>-1172.19580</td>\n",
" <td>9.978954e+06</td>\n",
" <td>22260.40</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>5.896422</td>\n",
" <td>9.980126e+06</td>\n",
" <td>21402.00</td>\n",
" <td>21402.00</td>\n",
" <td>20</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-02-02 21:00:00+00:00</th>\n",
" <td>118.630</td>\n",
" <td>5.114028e-04</td>\n",
" <td>1.493389e-04</td>\n",
" <td>1.965643e-03</td>\n",
" <td>-0.017612</td>\n",
" <td>0.170979</td>\n",
" <td>0.000862</td>\n",
" <td>-1186.90315</td>\n",
" <td>9.977767e+06</td>\n",
" <td>23726.00</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>7.074385</td>\n",
" <td>9.978954e+06</td>\n",
" <td>22260.40</td>\n",
" <td>22260.40</td>\n",
" <td>21</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-02-03 21:00:00+00:00</th>\n",
" <td>118.650</td>\n",
" <td>4.996040e-04</td>\n",
" <td>1.496786e-04</td>\n",
" <td>1.734330e-03</td>\n",
" <td>-0.003406</td>\n",
" <td>0.174661</td>\n",
" <td>0.000748</td>\n",
" <td>-1187.10325</td>\n",
" <td>9.976580e+06</td>\n",
" <td>24916.50</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>6.927452</td>\n",
" <td>9.977767e+06</td>\n",
" <td>23726.00</td>\n",
" <td>23726.00</td>\n",
" <td>22</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-02-04 21:00:00+00:00</th>\n",
" <td>119.560</td>\n",
" <td>4.897966e-04</td>\n",
" <td>1.687278e-04</td>\n",
" <td>1.897796e-03</td>\n",
" <td>-0.007201</td>\n",
" <td>0.171086</td>\n",
" <td>0.000727</td>\n",
" <td>-1196.20780</td>\n",
" <td>9.975384e+06</td>\n",
" <td>26303.20</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>7.637315</td>\n",
" <td>9.976580e+06</td>\n",
" <td>24916.50</td>\n",
" <td>24916.50</td>\n",
" <td>23</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-02-05 21:00:00+00:00</th>\n",
" <td>119.940</td>\n",
" <td>4.790407e-04</td>\n",
" <td>1.770269e-04</td>\n",
" <td>1.829832e-03</td>\n",
" <td>0.002822</td>\n",
" <td>0.170656</td>\n",
" <td>0.000702</td>\n",
" <td>-1200.00970</td>\n",
" <td>9.974184e+06</td>\n",
" <td>27586.20</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>7.844195</td>\n",
" <td>9.975384e+06</td>\n",
" <td>26303.20</td>\n",
" <td>26303.20</td>\n",
" <td>24</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-02-06 21:00:00+00:00</th>\n",
" <td>118.930</td>\n",
" <td>4.789523e-04</td>\n",
" <td>1.537364e-04</td>\n",
" <td>1.540647e-03</td>\n",
" <td>0.000049</td>\n",
" <td>0.167323</td>\n",
" <td>0.000732</td>\n",
" <td>-1189.90465</td>\n",
" <td>9.972994e+06</td>\n",
" <td>28543.20</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>6.360016</td>\n",
" <td>9.974184e+06</td>\n",
" <td>27586.20</td>\n",
" <td>27586.20</td>\n",
" <td>25</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-02-09 21:00:00+00:00</th>\n",
" <td>119.720</td>\n",
" <td>4.709504e-04</td>\n",
" <td>1.726355e-04</td>\n",
" <td>1.695828e-03</td>\n",
" <td>-0.004427</td>\n",
" <td>0.164548</td>\n",
" <td>0.000706</td>\n",
" <td>-1197.80860</td>\n",
" <td>9.971796e+06</td>\n",
" <td>29930.00</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>7.003060</td>\n",
" <td>9.972994e+06</td>\n",
" <td>28543.20</td>\n",
" <td>28543.20</td>\n",
" <td>26</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-02-10 21:00:00+00:00</th>\n",
" <td>122.020</td>\n",
" <td>4.871742e-04</td>\n",
" <td>2.300735e-04</td>\n",
" <td>2.088274e-03</td>\n",
" <td>0.006179</td>\n",
" <td>0.164675</td>\n",
" <td>0.000866</td>\n",
" <td>-1220.82010</td>\n",
" <td>9.970576e+06</td>\n",
" <td>31725.20</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>9.158250</td>\n",
" <td>9.971796e+06</td>\n",
" <td>29930.00</td>\n",
" <td>29930.00</td>\n",
" <td>27</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-02-11 21:00:00+00:00</th>\n",
" <td>124.880</td>\n",
" <td>5.171714e-04</td>\n",
" <td>3.043701e-04</td>\n",
" <td>2.678662e-03</td>\n",
" <td>0.006763</td>\n",
" <td>0.161599</td>\n",
" <td>0.000873</td>\n",
" <td>-1249.43440</td>\n",
" <td>9.969326e+06</td>\n",
" <td>33717.60</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>11.896861</td>\n",
" <td>9.970576e+06</td>\n",
" <td>31725.20</td>\n",
" <td>31725.20</td>\n",
" <td>28</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-02-12 21:00:00+00:00</th>\n",
" <td>126.460</td>\n",
" <td>5.163850e-04</td>\n",
" <td>3.469659e-04</td>\n",
" <td>2.872644e-03</td>\n",
" <td>0.016444</td>\n",
" <td>0.161051</td>\n",
" <td>0.000947</td>\n",
" <td>-1265.24230</td>\n",
" <td>9.968061e+06</td>\n",
" <td>35408.80</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>13.325585</td>\n",
" <td>9.969326e+06</td>\n",
" <td>33717.60</td>\n",
" <td>33717.60</td>\n",
" <td>29</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-02-13 21:00:00+00:00</th>\n",
" <td>127.080</td>\n",
" <td>5.076385e-04</td>\n",
" <td>3.642613e-04</td>\n",
" <td>2.889130e-03</td>\n",
" <td>0.020629</td>\n",
" <td>0.158575</td>\n",
" <td>0.000949</td>\n",
" <td>-1271.44540</td>\n",
" <td>9.966789e+06</td>\n",
" <td>36853.20</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>13.754550</td>\n",
" <td>9.968061e+06</td>\n",
" <td>35408.80</td>\n",
" <td>35408.80</td>\n",
" <td>30</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</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",
" <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>2017-11-16 21:00:00+00:00</th>\n",
" <td>171.100</td>\n",
" <td>1.086985e-02</td>\n",
" <td>3.470210e-02</td>\n",
" <td>8.986113e-03</td>\n",
" <td>0.258247</td>\n",
" <td>0.125812</td>\n",
" <td>0.033698</td>\n",
" <td>-1711.86550</td>\n",
" <td>9.106546e+06</td>\n",
" <td>1240475.00</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.701983</td>\n",
" <td>9.108258e+06</td>\n",
" <td>1224139.20</td>\n",
" <td>1224139.20</td>\n",
" <td>726</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-11-17 21:00:00+00:00</th>\n",
" <td>170.150</td>\n",
" <td>1.087047e-02</td>\n",
" <td>3.401326e-02</td>\n",
" <td>8.771735e-03</td>\n",
" <td>0.254549</td>\n",
" <td>0.125740</td>\n",
" <td>0.033741</td>\n",
" <td>-1702.36075</td>\n",
" <td>9.104844e+06</td>\n",
" <td>1235289.00</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.665168</td>\n",
" <td>9.106546e+06</td>\n",
" <td>1240475.00</td>\n",
" <td>1240475.00</td>\n",
" <td>727</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-11-20 21:00:00+00:00</th>\n",
" <td>169.980</td>\n",
" <td>1.086343e-02</td>\n",
" <td>3.388976e-02</td>\n",
" <td>8.698381e-03</td>\n",
" <td>0.256690</td>\n",
" <td>0.125656</td>\n",
" <td>0.033735</td>\n",
" <td>-1700.65990</td>\n",
" <td>9.103143e+06</td>\n",
" <td>1235754.60</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.658028</td>\n",
" <td>9.104844e+06</td>\n",
" <td>1235289.00</td>\n",
" <td>1235289.00</td>\n",
" <td>728</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-11-21 21:00:00+00:00</th>\n",
" <td>173.140</td>\n",
" <td>1.093108e-02</td>\n",
" <td>3.618699e-02</td>\n",
" <td>9.360376e-03</td>\n",
" <td>0.264912</td>\n",
" <td>0.125622</td>\n",
" <td>0.034002</td>\n",
" <td>-1732.27570</td>\n",
" <td>9.101411e+06</td>\n",
" <td>1260459.20</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.766789</td>\n",
" <td>9.103143e+06</td>\n",
" <td>1235754.60</td>\n",
" <td>1235754.60</td>\n",
" <td>729</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-11-22 21:00:00+00:00</th>\n",
" <td>174.960</td>\n",
" <td>1.094745e-02</td>\n",
" <td>3.751186e-02</td>\n",
" <td>9.806658e-03</td>\n",
" <td>0.263793</td>\n",
" <td>0.125538</td>\n",
" <td>0.033967</td>\n",
" <td>-1750.48480</td>\n",
" <td>9.099660e+06</td>\n",
" <td>1275458.40</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.828776</td>\n",
" <td>9.101411e+06</td>\n",
" <td>1260459.20</td>\n",
" <td>1260459.20</td>\n",
" <td>730</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-11-24 18:00:00+00:00</th>\n",
" <td>174.970</td>\n",
" <td>1.093998e-02</td>\n",
" <td>3.751906e-02</td>\n",
" <td>9.768709e-03</td>\n",
" <td>0.266712</td>\n",
" <td>0.125458</td>\n",
" <td>0.033962</td>\n",
" <td>-1750.58485</td>\n",
" <td>9.097910e+06</td>\n",
" <td>1277281.00</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.827867</td>\n",
" <td>9.099660e+06</td>\n",
" <td>1275458.40</td>\n",
" <td>1275458.40</td>\n",
" <td>731</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-11-27 21:00:00+00:00</th>\n",
" <td>174.090</td>\n",
" <td>1.093955e-02</td>\n",
" <td>3.687658e-02</td>\n",
" <td>9.544880e-03</td>\n",
" <td>0.266080</td>\n",
" <td>0.125373</td>\n",
" <td>0.033974</td>\n",
" <td>-1741.78045</td>\n",
" <td>9.096168e+06</td>\n",
" <td>1272597.90</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.793620</td>\n",
" <td>9.097910e+06</td>\n",
" <td>1277281.00</td>\n",
" <td>1277281.00</td>\n",
" <td>732</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-11-28 21:00:00+00:00</th>\n",
" <td>173.070</td>\n",
" <td>1.094137e-02</td>\n",
" <td>3.613087e-02</td>\n",
" <td>9.184643e-03</td>\n",
" <td>0.278924</td>\n",
" <td>0.125419</td>\n",
" <td>0.033739</td>\n",
" <td>-1731.57535</td>\n",
" <td>9.094436e+06</td>\n",
" <td>1266872.40</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.753772</td>\n",
" <td>9.096168e+06</td>\n",
" <td>1272597.90</td>\n",
" <td>1272597.90</td>\n",
" <td>733</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-11-29 21:00:00+00:00</th>\n",
" <td>169.480</td>\n",
" <td>1.103832e-02</td>\n",
" <td>3.350290e-02</td>\n",
" <td>8.295771e-03</td>\n",
" <td>0.278145</td>\n",
" <td>0.125334</td>\n",
" <td>0.033793</td>\n",
" <td>-1695.65740</td>\n",
" <td>9.092741e+06</td>\n",
" <td>1242288.40</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.592335</td>\n",
" <td>9.094436e+06</td>\n",
" <td>1266872.40</td>\n",
" <td>1266872.40</td>\n",
" <td>734</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-11-30 21:00:00+00:00</th>\n",
" <td>171.850</td>\n",
" <td>1.107230e-02</td>\n",
" <td>3.524003e-02</td>\n",
" <td>8.739588e-03</td>\n",
" <td>0.289335</td>\n",
" <td>0.125345</td>\n",
" <td>0.034041</td>\n",
" <td>-1719.36925</td>\n",
" <td>9.091021e+06</td>\n",
" <td>1261379.00</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.671977</td>\n",
" <td>9.092741e+06</td>\n",
" <td>1242288.40</td>\n",
" <td>1242288.40</td>\n",
" <td>735</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-01 21:00:00+00:00</th>\n",
" <td>171.050</td>\n",
" <td>1.107061e-02</td>\n",
" <td>3.465274e-02</td>\n",
" <td>8.553451e-03</td>\n",
" <td>0.286660</td>\n",
" <td>0.125268</td>\n",
" <td>0.034069</td>\n",
" <td>-1711.36525</td>\n",
" <td>9.089310e+06</td>\n",
" <td>1257217.50</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.641837</td>\n",
" <td>9.091021e+06</td>\n",
" <td>1261379.00</td>\n",
" <td>1261379.00</td>\n",
" <td>736</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-04 21:00:00+00:00</th>\n",
" <td>169.800</td>\n",
" <td>1.107657e-02</td>\n",
" <td>3.373390e-02</td>\n",
" <td>8.246946e-03</td>\n",
" <td>0.285103</td>\n",
" <td>0.125186</td>\n",
" <td>0.034099</td>\n",
" <td>-1698.85900</td>\n",
" <td>9.087611e+06</td>\n",
" <td>1249728.00</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.593961</td>\n",
" <td>9.089310e+06</td>\n",
" <td>1257217.50</td>\n",
" <td>1257217.50</td>\n",
" <td>737</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-05 21:00:00+00:00</th>\n",
" <td>169.640</td>\n",
" <td>1.106945e-02</td>\n",
" <td>3.361606e-02</td>\n",
" <td>8.238508e-03</td>\n",
" <td>0.280481</td>\n",
" <td>0.125123</td>\n",
" <td>0.034102</td>\n",
" <td>-1697.25820</td>\n",
" <td>9.085914e+06</td>\n",
" <td>1250246.80</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.587368</td>\n",
" <td>9.087611e+06</td>\n",
" <td>1249728.00</td>\n",
" <td>1249728.00</td>\n",
" <td>738</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-06 21:00:00+00:00</th>\n",
" <td>169.010</td>\n",
" <td>1.106571e-02</td>\n",
" <td>3.315166e-02</td>\n",
" <td>8.070460e-03</td>\n",
" <td>0.280724</td>\n",
" <td>0.125038</td>\n",
" <td>0.034103</td>\n",
" <td>-1690.95505</td>\n",
" <td>9.084223e+06</td>\n",
" <td>1247293.80</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.563801</td>\n",
" <td>9.085914e+06</td>\n",
" <td>1250246.80</td>\n",
" <td>1250246.80</td>\n",
" <td>739</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-07 21:00:00+00:00</th>\n",
" <td>169.452</td>\n",
" <td>1.105935e-02</td>\n",
" <td>3.347777e-02</td>\n",
" <td>8.129948e-03</td>\n",
" <td>0.284762</td>\n",
" <td>0.124964</td>\n",
" <td>0.034114</td>\n",
" <td>-1695.37726</td>\n",
" <td>9.082527e+06</td>\n",
" <td>1252250.28</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.577785</td>\n",
" <td>9.084223e+06</td>\n",
" <td>1247293.80</td>\n",
" <td>1247293.80</td>\n",
" <td>740</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-08 21:00:00+00:00</th>\n",
" <td>169.370</td>\n",
" <td>1.105204e-02</td>\n",
" <td>3.341709e-02</td>\n",
" <td>8.037963e-03</td>\n",
" <td>0.291768</td>\n",
" <td>0.124915</td>\n",
" <td>0.034083</td>\n",
" <td>-1694.55685</td>\n",
" <td>9.080833e+06</td>\n",
" <td>1253338.00</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.573906</td>\n",
" <td>9.082527e+06</td>\n",
" <td>1252250.28</td>\n",
" <td>1252250.28</td>\n",
" <td>741</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-11 21:00:00+00:00</th>\n",
" <td>172.670</td>\n",
" <td>1.112691e-02</td>\n",
" <td>3.585900e-02</td>\n",
" <td>8.788783e-03</td>\n",
" <td>0.295660</td>\n",
" <td>0.124840</td>\n",
" <td>0.034211</td>\n",
" <td>-1727.57335</td>\n",
" <td>9.079105e+06</td>\n",
" <td>1279484.70</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.685294</td>\n",
" <td>9.080833e+06</td>\n",
" <td>1253338.00</td>\n",
" <td>1253338.00</td>\n",
" <td>742</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-12 21:00:00+00:00</th>\n",
" <td>171.700</td>\n",
" <td>1.112780e-02</td>\n",
" <td>3.514014e-02</td>\n",
" <td>8.521161e-03</td>\n",
" <td>0.297947</td>\n",
" <td>0.124758</td>\n",
" <td>0.034188</td>\n",
" <td>-1717.86850</td>\n",
" <td>9.077387e+06</td>\n",
" <td>1274014.00</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.648512</td>\n",
" <td>9.079105e+06</td>\n",
" <td>1279484.70</td>\n",
" <td>1279484.70</td>\n",
" <td>743</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-13 21:00:00+00:00</th>\n",
" <td>172.270</td>\n",
" <td>1.112230e-02</td>\n",
" <td>3.556300e-02</td>\n",
" <td>8.650913e-03</td>\n",
" <td>0.297801</td>\n",
" <td>0.124675</td>\n",
" <td>0.034184</td>\n",
" <td>-1723.57135</td>\n",
" <td>9.075664e+06</td>\n",
" <td>1279966.10</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.666786</td>\n",
" <td>9.077387e+06</td>\n",
" <td>1274014.00</td>\n",
" <td>1274014.00</td>\n",
" <td>744</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-14 21:00:00+00:00</th>\n",
" <td>172.220</td>\n",
" <td>1.111493e-02</td>\n",
" <td>3.552576e-02</td>\n",
" <td>8.675284e-03</td>\n",
" <td>0.292498</td>\n",
" <td>0.124618</td>\n",
" <td>0.034177</td>\n",
" <td>-1723.07110</td>\n",
" <td>9.073941e+06</td>\n",
" <td>1281316.80</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.663955</td>\n",
" <td>9.075664e+06</td>\n",
" <td>1279966.10</td>\n",
" <td>1279966.10</td>\n",
" <td>745</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-15 21:00:00+00:00</th>\n",
" <td>173.870</td>\n",
" <td>1.112715e-02</td>\n",
" <td>3.675327e-02</td>\n",
" <td>9.024123e-03</td>\n",
" <td>0.296633</td>\n",
" <td>0.124545</td>\n",
" <td>0.034241</td>\n",
" <td>-1739.57935</td>\n",
" <td>9.072201e+06</td>\n",
" <td>1295331.50</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.719009</td>\n",
" <td>9.073941e+06</td>\n",
" <td>1281316.80</td>\n",
" <td>1281316.80</td>\n",
" <td>746</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-18 21:00:00+00:00</th>\n",
" <td>176.420</td>\n",
" <td>1.116785e-02</td>\n",
" <td>3.865293e-02</td>\n",
" <td>9.541732e-03</td>\n",
" <td>0.304856</td>\n",
" <td>0.124510</td>\n",
" <td>0.034446</td>\n",
" <td>-1765.09210</td>\n",
" <td>9.070436e+06</td>\n",
" <td>1316093.20</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.804624</td>\n",
" <td>9.072201e+06</td>\n",
" <td>1295331.50</td>\n",
" <td>1295331.50</td>\n",
" <td>747</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-19 21:00:00+00:00</th>\n",
" <td>174.540</td>\n",
" <td>1.118997e-02</td>\n",
" <td>3.725037e-02</td>\n",
" <td>9.103535e-03</td>\n",
" <td>0.299844</td>\n",
" <td>0.124451</td>\n",
" <td>0.034561</td>\n",
" <td>-1746.28270</td>\n",
" <td>9.068690e+06</td>\n",
" <td>1303813.80</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.729069</td>\n",
" <td>9.070436e+06</td>\n",
" <td>1316093.20</td>\n",
" <td>1316093.20</td>\n",
" <td>748</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-20 21:00:00+00:00</th>\n",
" <td>174.350</td>\n",
" <td>1.118301e-02</td>\n",
" <td>3.710835e-02</td>\n",
" <td>9.050697e-03</td>\n",
" <td>0.299163</td>\n",
" <td>0.124369</td>\n",
" <td>0.034564</td>\n",
" <td>-1744.38175</td>\n",
" <td>9.066945e+06</td>\n",
" <td>1304138.00</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.721372</td>\n",
" <td>9.068690e+06</td>\n",
" <td>1303813.80</td>\n",
" <td>1303813.80</td>\n",
" <td>749</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-21 21:00:00+00:00</th>\n",
" <td>175.010</td>\n",
" <td>1.117828e-02</td>\n",
" <td>3.760194e-02</td>\n",
" <td>9.174490e-03</td>\n",
" <td>0.301839</td>\n",
" <td>0.124289</td>\n",
" <td>0.034578</td>\n",
" <td>-1750.98505</td>\n",
" <td>9.065194e+06</td>\n",
" <td>1310824.90</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.742579</td>\n",
" <td>9.066945e+06</td>\n",
" <td>1304138.00</td>\n",
" <td>1304138.00</td>\n",
" <td>750</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-22 21:00:00+00:00</th>\n",
" <td>175.010</td>\n",
" <td>1.117087e-02</td>\n",
" <td>3.760185e-02</td>\n",
" <td>9.165215e-03</td>\n",
" <td>0.301498</td>\n",
" <td>0.124207</td>\n",
" <td>0.034578</td>\n",
" <td>-1750.98505</td>\n",
" <td>9.063443e+06</td>\n",
" <td>1312575.00</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.741415</td>\n",
" <td>9.065194e+06</td>\n",
" <td>1310824.90</td>\n",
" <td>1310824.90</td>\n",
" <td>751</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-26 21:00:00+00:00</th>\n",
" <td>170.570</td>\n",
" <td>1.132170e-02</td>\n",
" <td>3.427176e-02</td>\n",
" <td>8.071629e-03</td>\n",
" <td>0.299942</td>\n",
" <td>0.124128</td>\n",
" <td>0.034688</td>\n",
" <td>-1706.56285</td>\n",
" <td>9.061737e+06</td>\n",
" <td>1280980.70</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.538529</td>\n",
" <td>9.063443e+06</td>\n",
" <td>1312575.00</td>\n",
" <td>1312575.00</td>\n",
" <td>752</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-27 21:00:00+00:00</th>\n",
" <td>170.600</td>\n",
" <td>1.131418e-02</td>\n",
" <td>3.429421e-02</td>\n",
" <td>8.062500e-03</td>\n",
" <td>0.300574</td>\n",
" <td>0.124045</td>\n",
" <td>0.034688</td>\n",
" <td>-1706.86300</td>\n",
" <td>9.060030e+06</td>\n",
" <td>1282912.00</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.538491</td>\n",
" <td>9.061737e+06</td>\n",
" <td>1280980.70</td>\n",
" <td>1280980.70</td>\n",
" <td>753</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-28 21:00:00+00:00</th>\n",
" <td>171.080</td>\n",
" <td>1.130803e-02</td>\n",
" <td>3.465508e-02</td>\n",
" <td>8.144401e-03</td>\n",
" <td>0.303250</td>\n",
" <td>0.123966</td>\n",
" <td>0.034697</td>\n",
" <td>-1711.66540</td>\n",
" <td>9.058318e+06</td>\n",
" <td>1288232.40</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.553289</td>\n",
" <td>9.060030e+06</td>\n",
" <td>1282912.00</td>\n",
" <td>1282912.00</td>\n",
" <td>754</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-29 21:00:00+00:00</th>\n",
" <td>169.230</td>\n",
" <td>1.132910e-02</td>\n",
" <td>3.326195e-02</td>\n",
" <td>7.713847e-03</td>\n",
" <td>0.298336</td>\n",
" <td>0.123907</td>\n",
" <td>0.034810</td>\n",
" <td>-1693.15615</td>\n",
" <td>9.056625e+06</td>\n",
" <td>1275994.20</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.483009</td>\n",
" <td>9.058318e+06</td>\n",
" <td>1288232.40</td>\n",
" <td>1288232.40</td>\n",
" <td>755</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>755 rows × 38 columns</p>\n",
"</div>"
],
"text/plain": [
" AAPL algo_volatility algorithm_period_return \\\n",
"2015-01-02 21:00:00+00:00 109.330 NaN 0.000000e+00 \n",
"2015-01-05 21:00:00+00:00 106.250 6.075516e-07 -5.412500e-08 \n",
"2015-01-06 21:00:00+00:00 106.260 4.571965e-07 -9.825500e-08 \n",
"2015-01-07 21:00:00+00:00 107.750 2.348039e-05 2.826870e-06 \n",
"2015-01-08 21:00:00+00:00 111.890 8.521334e-05 1.518993e-05 \n",
"2015-01-09 21:00:00+00:00 112.010 7.807851e-05 1.561292e-05 \n",
"2015-01-12 21:00:00+00:00 109.250 1.217820e-04 1.757295e-06 \n",
"2015-01-13 21:00:00+00:00 110.220 1.169165e-04 7.521185e-06 \n",
"2015-01-14 21:00:00+00:00 109.800 1.113310e-04 4.525285e-06 \n",
"2015-01-15 21:00:00+00:00 106.820 1.612977e-04 -1.936912e-05 \n",
"2015-01-16 21:00:00+00:00 105.990 1.553397e-04 -2.689312e-05 \n",
"2015-01-20 21:00:00+00:00 108.720 2.011179e-04 3.515200e-07 \n",
"2015-01-21 21:00:00+00:00 109.550 1.966305e-04 9.425745e-06 \n",
"2015-01-22 21:00:00+00:00 112.400 2.361999e-04 4.356854e-05 \n",
"2015-01-23 21:00:00+00:00 112.980 2.283116e-04 5.105106e-05 \n",
"2015-01-26 21:00:00+00:00 113.100 2.206832e-04 5.267351e-05 \n",
"2015-01-27 21:00:00+00:00 109.140 3.225146e-04 -6.782065e-06 \n",
"2015-01-28 21:00:00+00:00 115.310 4.850563e-04 9.187928e-05 \n",
"2015-01-29 21:00:00+00:00 118.900 5.134132e-04 1.528488e-04 \n",
"2015-01-30 21:00:00+00:00 117.160 5.189400e-04 1.214693e-04 \n",
"2015-02-02 21:00:00+00:00 118.630 5.114028e-04 1.493389e-04 \n",
"2015-02-03 21:00:00+00:00 118.650 4.996040e-04 1.496786e-04 \n",
"2015-02-04 21:00:00+00:00 119.560 4.897966e-04 1.687278e-04 \n",
"2015-02-05 21:00:00+00:00 119.940 4.790407e-04 1.770269e-04 \n",
"2015-02-06 21:00:00+00:00 118.930 4.789523e-04 1.537364e-04 \n",
"2015-02-09 21:00:00+00:00 119.720 4.709504e-04 1.726355e-04 \n",
"2015-02-10 21:00:00+00:00 122.020 4.871742e-04 2.300735e-04 \n",
"2015-02-11 21:00:00+00:00 124.880 5.171714e-04 3.043701e-04 \n",
"2015-02-12 21:00:00+00:00 126.460 5.163850e-04 3.469659e-04 \n",
"2015-02-13 21:00:00+00:00 127.080 5.076385e-04 3.642613e-04 \n",
"... ... ... ... \n",
"2017-11-16 21:00:00+00:00 171.100 1.086985e-02 3.470210e-02 \n",
"2017-11-17 21:00:00+00:00 170.150 1.087047e-02 3.401326e-02 \n",
"2017-11-20 21:00:00+00:00 169.980 1.086343e-02 3.388976e-02 \n",
"2017-11-21 21:00:00+00:00 173.140 1.093108e-02 3.618699e-02 \n",
"2017-11-22 21:00:00+00:00 174.960 1.094745e-02 3.751186e-02 \n",
"2017-11-24 18:00:00+00:00 174.970 1.093998e-02 3.751906e-02 \n",
"2017-11-27 21:00:00+00:00 174.090 1.093955e-02 3.687658e-02 \n",
"2017-11-28 21:00:00+00:00 173.070 1.094137e-02 3.613087e-02 \n",
"2017-11-29 21:00:00+00:00 169.480 1.103832e-02 3.350290e-02 \n",
"2017-11-30 21:00:00+00:00 171.850 1.107230e-02 3.524003e-02 \n",
"2017-12-01 21:00:00+00:00 171.050 1.107061e-02 3.465274e-02 \n",
"2017-12-04 21:00:00+00:00 169.800 1.107657e-02 3.373390e-02 \n",
"2017-12-05 21:00:00+00:00 169.640 1.106945e-02 3.361606e-02 \n",
"2017-12-06 21:00:00+00:00 169.010 1.106571e-02 3.315166e-02 \n",
"2017-12-07 21:00:00+00:00 169.452 1.105935e-02 3.347777e-02 \n",
"2017-12-08 21:00:00+00:00 169.370 1.105204e-02 3.341709e-02 \n",
"2017-12-11 21:00:00+00:00 172.670 1.112691e-02 3.585900e-02 \n",
"2017-12-12 21:00:00+00:00 171.700 1.112780e-02 3.514014e-02 \n",
"2017-12-13 21:00:00+00:00 172.270 1.112230e-02 3.556300e-02 \n",
"2017-12-14 21:00:00+00:00 172.220 1.111493e-02 3.552576e-02 \n",
"2017-12-15 21:00:00+00:00 173.870 1.112715e-02 3.675327e-02 \n",
"2017-12-18 21:00:00+00:00 176.420 1.116785e-02 3.865293e-02 \n",
"2017-12-19 21:00:00+00:00 174.540 1.118997e-02 3.725037e-02 \n",
"2017-12-20 21:00:00+00:00 174.350 1.118301e-02 3.710835e-02 \n",
"2017-12-21 21:00:00+00:00 175.010 1.117828e-02 3.760194e-02 \n",
"2017-12-22 21:00:00+00:00 175.010 1.117087e-02 3.760185e-02 \n",
"2017-12-26 21:00:00+00:00 170.570 1.132170e-02 3.427176e-02 \n",
"2017-12-27 21:00:00+00:00 170.600 1.131418e-02 3.429421e-02 \n",
"2017-12-28 21:00:00+00:00 171.080 1.130803e-02 3.465508e-02 \n",
"2017-12-29 21:00:00+00:00 169.230 1.132910e-02 3.326195e-02 \n",
"\n",
" alpha benchmark_period_return \\\n",
"2015-01-02 21:00:00+00:00 NaN -0.000535 \n",
"2015-01-05 21:00:00+00:00 4.165327e-07 -0.018585 \n",
"2015-01-06 21:00:00+00:00 -9.648674e-07 -0.027829 \n",
"2015-01-07 21:00:00+00:00 2.719581e-04 -0.015715 \n",
"2015-01-08 21:00:00+00:00 7.345319e-04 0.001751 \n",
"2015-01-09 21:00:00+00:00 7.256760e-04 -0.006276 \n",
"2015-01-12 21:00:00+00:00 2.459898e-04 -0.014061 \n",
"2015-01-13 21:00:00+00:00 4.274790e-04 -0.016834 \n",
"2015-01-14 21:00:00+00:00 3.636721e-04 -0.022769 \n",
"2015-01-15 21:00:00+00:00 -8.730670e-05 -0.031721 \n",
"2015-01-16 21:00:00+00:00 -4.701771e-04 -0.019023 \n",
"2015-01-20 21:00:00+00:00 1.521907e-04 -0.016931 \n",
"2015-01-21 21:00:00+00:00 2.815507e-04 -0.011968 \n",
"2015-01-22 21:00:00+00:00 7.407250e-04 0.002725 \n",
"2015-01-23 21:00:00+00:00 8.802561e-04 -0.002773 \n",
"2015-01-26 21:00:00+00:00 8.262006e-04 -0.000438 \n",
"2015-01-27 21:00:00+00:00 9.789820e-05 -0.013623 \n",
"2015-01-28 21:00:00+00:00 1.421373e-03 -0.026272 \n",
"2015-01-29 21:00:00+00:00 2.167635e-03 -0.017272 \n",
"2015-01-30 21:00:00+00:00 1.824668e-03 -0.029629 \n",
"2015-02-02 21:00:00+00:00 1.965643e-03 -0.017612 \n",
"2015-02-03 21:00:00+00:00 1.734330e-03 -0.003406 \n",
"2015-02-04 21:00:00+00:00 1.897796e-03 -0.007201 \n",
"2015-02-05 21:00:00+00:00 1.829832e-03 0.002822 \n",
"2015-02-06 21:00:00+00:00 1.540647e-03 0.000049 \n",
"2015-02-09 21:00:00+00:00 1.695828e-03 -0.004427 \n",
"2015-02-10 21:00:00+00:00 2.088274e-03 0.006179 \n",
"2015-02-11 21:00:00+00:00 2.678662e-03 0.006763 \n",
"2015-02-12 21:00:00+00:00 2.872644e-03 0.016444 \n",
"2015-02-13 21:00:00+00:00 2.889130e-03 0.020629 \n",
"... ... ... \n",
"2017-11-16 21:00:00+00:00 8.986113e-03 0.258247 \n",
"2017-11-17 21:00:00+00:00 8.771735e-03 0.254549 \n",
"2017-11-20 21:00:00+00:00 8.698381e-03 0.256690 \n",
"2017-11-21 21:00:00+00:00 9.360376e-03 0.264912 \n",
"2017-11-22 21:00:00+00:00 9.806658e-03 0.263793 \n",
"2017-11-24 18:00:00+00:00 9.768709e-03 0.266712 \n",
"2017-11-27 21:00:00+00:00 9.544880e-03 0.266080 \n",
"2017-11-28 21:00:00+00:00 9.184643e-03 0.278924 \n",
"2017-11-29 21:00:00+00:00 8.295771e-03 0.278145 \n",
"2017-11-30 21:00:00+00:00 8.739588e-03 0.289335 \n",
"2017-12-01 21:00:00+00:00 8.553451e-03 0.286660 \n",
"2017-12-04 21:00:00+00:00 8.246946e-03 0.285103 \n",
"2017-12-05 21:00:00+00:00 8.238508e-03 0.280481 \n",
"2017-12-06 21:00:00+00:00 8.070460e-03 0.280724 \n",
"2017-12-07 21:00:00+00:00 8.129948e-03 0.284762 \n",
"2017-12-08 21:00:00+00:00 8.037963e-03 0.291768 \n",
"2017-12-11 21:00:00+00:00 8.788783e-03 0.295660 \n",
"2017-12-12 21:00:00+00:00 8.521161e-03 0.297947 \n",
"2017-12-13 21:00:00+00:00 8.650913e-03 0.297801 \n",
"2017-12-14 21:00:00+00:00 8.675284e-03 0.292498 \n",
"2017-12-15 21:00:00+00:00 9.024123e-03 0.296633 \n",
"2017-12-18 21:00:00+00:00 9.541732e-03 0.304856 \n",
"2017-12-19 21:00:00+00:00 9.103535e-03 0.299844 \n",
"2017-12-20 21:00:00+00:00 9.050697e-03 0.299163 \n",
"2017-12-21 21:00:00+00:00 9.174490e-03 0.301839 \n",
"2017-12-22 21:00:00+00:00 9.165215e-03 0.301498 \n",
"2017-12-26 21:00:00+00:00 8.071629e-03 0.299942 \n",
"2017-12-27 21:00:00+00:00 8.062500e-03 0.300574 \n",
"2017-12-28 21:00:00+00:00 8.144401e-03 0.303250 \n",
"2017-12-29 21:00:00+00:00 7.713847e-03 0.298336 \n",
"\n",
" benchmark_volatility beta capital_used \\\n",
"2015-01-02 21:00:00+00:00 NaN NaN 0.00000 \n",
"2015-01-05 21:00:00+00:00 0.196712 0.000003 -1063.04125 \n",
"2015-01-06 21:00:00+00:00 0.139101 0.000003 -1063.14130 \n",
"2015-01-07 21:00:00+00:00 0.206972 0.000096 -1078.04875 \n",
"2015-01-08 21:00:00+00:00 0.236040 0.000283 -1119.46945 \n",
"2015-01-09 21:00:00+00:00 0.218111 0.000285 -1120.67005 \n",
"2015-01-12 21:00:00+00:00 0.203321 0.000372 -1093.05625 \n",
"2015-01-13 21:00:00+00:00 0.188301 0.000367 -1102.76110 \n",
"2015-01-14 21:00:00+00:00 0.177393 0.000376 -1098.55900 \n",
"2015-01-15 21:00:00+00:00 0.170557 0.000502 -1068.74410 \n",
"2015-01-16 21:00:00+00:00 0.179591 0.000343 -1060.43995 \n",
"2015-01-20 21:00:00+00:00 0.172126 0.000420 -1087.75360 \n",
"2015-01-21 21:00:00+00:00 0.167201 0.000448 -1096.05775 \n",
"2015-01-22 21:00:00+00:00 0.173978 0.000695 -1124.57200 \n",
"2015-01-23 21:00:00+00:00 0.169288 0.000667 -1130.37490 \n",
"2015-01-26 21:00:00+00:00 0.163843 0.000662 -1131.57550 \n",
"2015-01-27 21:00:00+00:00 0.166597 0.001043 -1091.95570 \n",
"2015-01-28 21:00:00+00:00 0.167814 0.000373 -1153.68655 \n",
"2015-01-29 21:00:00+00:00 0.167650 0.000634 -1189.60450 \n",
"2015-01-30 21:00:00+00:00 0.168390 0.000801 -1172.19580 \n",
"2015-02-02 21:00:00+00:00 0.170979 0.000862 -1186.90315 \n",
"2015-02-03 21:00:00+00:00 0.174661 0.000748 -1187.10325 \n",
"2015-02-04 21:00:00+00:00 0.171086 0.000727 -1196.20780 \n",
"2015-02-05 21:00:00+00:00 0.170656 0.000702 -1200.00970 \n",
"2015-02-06 21:00:00+00:00 0.167323 0.000732 -1189.90465 \n",
"2015-02-09 21:00:00+00:00 0.164548 0.000706 -1197.80860 \n",
"2015-02-10 21:00:00+00:00 0.164675 0.000866 -1220.82010 \n",
"2015-02-11 21:00:00+00:00 0.161599 0.000873 -1249.43440 \n",
"2015-02-12 21:00:00+00:00 0.161051 0.000947 -1265.24230 \n",
"2015-02-13 21:00:00+00:00 0.158575 0.000949 -1271.44540 \n",
"... ... ... ... \n",
"2017-11-16 21:00:00+00:00 0.125812 0.033698 -1711.86550 \n",
"2017-11-17 21:00:00+00:00 0.125740 0.033741 -1702.36075 \n",
"2017-11-20 21:00:00+00:00 0.125656 0.033735 -1700.65990 \n",
"2017-11-21 21:00:00+00:00 0.125622 0.034002 -1732.27570 \n",
"2017-11-22 21:00:00+00:00 0.125538 0.033967 -1750.48480 \n",
"2017-11-24 18:00:00+00:00 0.125458 0.033962 -1750.58485 \n",
"2017-11-27 21:00:00+00:00 0.125373 0.033974 -1741.78045 \n",
"2017-11-28 21:00:00+00:00 0.125419 0.033739 -1731.57535 \n",
"2017-11-29 21:00:00+00:00 0.125334 0.033793 -1695.65740 \n",
"2017-11-30 21:00:00+00:00 0.125345 0.034041 -1719.36925 \n",
"2017-12-01 21:00:00+00:00 0.125268 0.034069 -1711.36525 \n",
"2017-12-04 21:00:00+00:00 0.125186 0.034099 -1698.85900 \n",
"2017-12-05 21:00:00+00:00 0.125123 0.034102 -1697.25820 \n",
"2017-12-06 21:00:00+00:00 0.125038 0.034103 -1690.95505 \n",
"2017-12-07 21:00:00+00:00 0.124964 0.034114 -1695.37726 \n",
"2017-12-08 21:00:00+00:00 0.124915 0.034083 -1694.55685 \n",
"2017-12-11 21:00:00+00:00 0.124840 0.034211 -1727.57335 \n",
"2017-12-12 21:00:00+00:00 0.124758 0.034188 -1717.86850 \n",
"2017-12-13 21:00:00+00:00 0.124675 0.034184 -1723.57135 \n",
"2017-12-14 21:00:00+00:00 0.124618 0.034177 -1723.07110 \n",
"2017-12-15 21:00:00+00:00 0.124545 0.034241 -1739.57935 \n",
"2017-12-18 21:00:00+00:00 0.124510 0.034446 -1765.09210 \n",
"2017-12-19 21:00:00+00:00 0.124451 0.034561 -1746.28270 \n",
"2017-12-20 21:00:00+00:00 0.124369 0.034564 -1744.38175 \n",
"2017-12-21 21:00:00+00:00 0.124289 0.034578 -1750.98505 \n",
"2017-12-22 21:00:00+00:00 0.124207 0.034578 -1750.98505 \n",
"2017-12-26 21:00:00+00:00 0.124128 0.034688 -1706.56285 \n",
"2017-12-27 21:00:00+00:00 0.124045 0.034688 -1706.86300 \n",
"2017-12-28 21:00:00+00:00 0.123966 0.034697 -1711.66540 \n",
"2017-12-29 21:00:00+00:00 0.123907 0.034810 -1693.15615 \n",
"\n",
" ending_cash ending_exposure \\\n",
"2015-01-02 21:00:00+00:00 1.000000e+07 0.00 \n",
"2015-01-05 21:00:00+00:00 9.998937e+06 1062.50 \n",
"2015-01-06 21:00:00+00:00 9.997874e+06 2125.20 \n",
"2015-01-07 21:00:00+00:00 9.996796e+06 3232.50 \n",
"2015-01-08 21:00:00+00:00 9.995676e+06 4475.60 \n",
"2015-01-09 21:00:00+00:00 9.994556e+06 5600.50 \n",
"2015-01-12 21:00:00+00:00 9.993463e+06 6555.00 \n",
"2015-01-13 21:00:00+00:00 9.992360e+06 7715.40 \n",
"2015-01-14 21:00:00+00:00 9.991261e+06 8784.00 \n",
"2015-01-15 21:00:00+00:00 9.990193e+06 9613.80 \n",
"2015-01-16 21:00:00+00:00 9.989132e+06 10599.00 \n",
"2015-01-20 21:00:00+00:00 9.988044e+06 11959.20 \n",
"2015-01-21 21:00:00+00:00 9.986948e+06 13146.00 \n",
"2015-01-22 21:00:00+00:00 9.985824e+06 14612.00 \n",
"2015-01-23 21:00:00+00:00 9.984693e+06 15817.20 \n",
"2015-01-26 21:00:00+00:00 9.983562e+06 16965.00 \n",
"2015-01-27 21:00:00+00:00 9.982470e+06 17462.40 \n",
"2015-01-28 21:00:00+00:00 9.981316e+06 19602.70 \n",
"2015-01-29 21:00:00+00:00 9.980126e+06 21402.00 \n",
"2015-01-30 21:00:00+00:00 9.978954e+06 22260.40 \n",
"2015-02-02 21:00:00+00:00 9.977767e+06 23726.00 \n",
"2015-02-03 21:00:00+00:00 9.976580e+06 24916.50 \n",
"2015-02-04 21:00:00+00:00 9.975384e+06 26303.20 \n",
"2015-02-05 21:00:00+00:00 9.974184e+06 27586.20 \n",
"2015-02-06 21:00:00+00:00 9.972994e+06 28543.20 \n",
"2015-02-09 21:00:00+00:00 9.971796e+06 29930.00 \n",
"2015-02-10 21:00:00+00:00 9.970576e+06 31725.20 \n",
"2015-02-11 21:00:00+00:00 9.969326e+06 33717.60 \n",
"2015-02-12 21:00:00+00:00 9.968061e+06 35408.80 \n",
"2015-02-13 21:00:00+00:00 9.966789e+06 36853.20 \n",
"... ... ... \n",
"2017-11-16 21:00:00+00:00 9.106546e+06 1240475.00 \n",
"2017-11-17 21:00:00+00:00 9.104844e+06 1235289.00 \n",
"2017-11-20 21:00:00+00:00 9.103143e+06 1235754.60 \n",
"2017-11-21 21:00:00+00:00 9.101411e+06 1260459.20 \n",
"2017-11-22 21:00:00+00:00 9.099660e+06 1275458.40 \n",
"2017-11-24 18:00:00+00:00 9.097910e+06 1277281.00 \n",
"2017-11-27 21:00:00+00:00 9.096168e+06 1272597.90 \n",
"2017-11-28 21:00:00+00:00 9.094436e+06 1266872.40 \n",
"2017-11-29 21:00:00+00:00 9.092741e+06 1242288.40 \n",
"2017-11-30 21:00:00+00:00 9.091021e+06 1261379.00 \n",
"2017-12-01 21:00:00+00:00 9.089310e+06 1257217.50 \n",
"2017-12-04 21:00:00+00:00 9.087611e+06 1249728.00 \n",
"2017-12-05 21:00:00+00:00 9.085914e+06 1250246.80 \n",
"2017-12-06 21:00:00+00:00 9.084223e+06 1247293.80 \n",
"2017-12-07 21:00:00+00:00 9.082527e+06 1252250.28 \n",
"2017-12-08 21:00:00+00:00 9.080833e+06 1253338.00 \n",
"2017-12-11 21:00:00+00:00 9.079105e+06 1279484.70 \n",
"2017-12-12 21:00:00+00:00 9.077387e+06 1274014.00 \n",
"2017-12-13 21:00:00+00:00 9.075664e+06 1279966.10 \n",
"2017-12-14 21:00:00+00:00 9.073941e+06 1281316.80 \n",
"2017-12-15 21:00:00+00:00 9.072201e+06 1295331.50 \n",
"2017-12-18 21:00:00+00:00 9.070436e+06 1316093.20 \n",
"2017-12-19 21:00:00+00:00 9.068690e+06 1303813.80 \n",
"2017-12-20 21:00:00+00:00 9.066945e+06 1304138.00 \n",
"2017-12-21 21:00:00+00:00 9.065194e+06 1310824.90 \n",
"2017-12-22 21:00:00+00:00 9.063443e+06 1312575.00 \n",
"2017-12-26 21:00:00+00:00 9.061737e+06 1280980.70 \n",
"2017-12-27 21:00:00+00:00 9.060030e+06 1282912.00 \n",
"2017-12-28 21:00:00+00:00 9.058318e+06 1288232.40 \n",
"2017-12-29 21:00:00+00:00 9.056625e+06 1275994.20 \n",
"\n",
" ... short_exposure short_value \\\n",
"2015-01-02 21:00:00+00:00 ... 0.0 0.0 \n",
"2015-01-05 21:00:00+00:00 ... 0.0 0.0 \n",
"2015-01-06 21:00:00+00:00 ... 0.0 0.0 \n",
"2015-01-07 21:00:00+00:00 ... 0.0 0.0 \n",
"2015-01-08 21:00:00+00:00 ... 0.0 0.0 \n",
"2015-01-09 21:00:00+00:00 ... 0.0 0.0 \n",
"2015-01-12 21:00:00+00:00 ... 0.0 0.0 \n",
"2015-01-13 21:00:00+00:00 ... 0.0 0.0 \n",
"2015-01-14 21:00:00+00:00 ... 0.0 0.0 \n",
"2015-01-15 21:00:00+00:00 ... 0.0 0.0 \n",
"2015-01-16 21:00:00+00:00 ... 0.0 0.0 \n",
"2015-01-20 21:00:00+00:00 ... 0.0 0.0 \n",
"2015-01-21 21:00:00+00:00 ... 0.0 0.0 \n",
"2015-01-22 21:00:00+00:00 ... 0.0 0.0 \n",
"2015-01-23 21:00:00+00:00 ... 0.0 0.0 \n",
"2015-01-26 21:00:00+00:00 ... 0.0 0.0 \n",
"2015-01-27 21:00:00+00:00 ... 0.0 0.0 \n",
"2015-01-28 21:00:00+00:00 ... 0.0 0.0 \n",
"2015-01-29 21:00:00+00:00 ... 0.0 0.0 \n",
"2015-01-30 21:00:00+00:00 ... 0.0 0.0 \n",
"2015-02-02 21:00:00+00:00 ... 0.0 0.0 \n",
"2015-02-03 21:00:00+00:00 ... 0.0 0.0 \n",
"2015-02-04 21:00:00+00:00 ... 0.0 0.0 \n",
"2015-02-05 21:00:00+00:00 ... 0.0 0.0 \n",
"2015-02-06 21:00:00+00:00 ... 0.0 0.0 \n",
"2015-02-09 21:00:00+00:00 ... 0.0 0.0 \n",
"2015-02-10 21:00:00+00:00 ... 0.0 0.0 \n",
"2015-02-11 21:00:00+00:00 ... 0.0 0.0 \n",
"2015-02-12 21:00:00+00:00 ... 0.0 0.0 \n",
"2015-02-13 21:00:00+00:00 ... 0.0 0.0 \n",
"... ... ... ... \n",
"2017-11-16 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-11-17 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-11-20 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-11-21 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-11-22 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-11-24 18:00:00+00:00 ... 0.0 0.0 \n",
"2017-11-27 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-11-28 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-11-29 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-11-30 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-01 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-04 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-05 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-06 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-07 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-08 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-11 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-12 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-13 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-14 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-15 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-18 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-19 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-20 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-21 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-22 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-26 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-27 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-28 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-29 21:00:00+00:00 ... 0.0 0.0 \n",
"\n",
" shorts_count sortino starting_cash \\\n",
"2015-01-02 21:00:00+00:00 0 NaN 1.000000e+07 \n",
"2015-01-05 21:00:00+00:00 0 -11.224972 1.000000e+07 \n",
"2015-01-06 21:00:00+00:00 0 -12.894935 9.998937e+06 \n",
"2015-01-07 21:00:00+00:00 0 321.292799 9.997874e+06 \n",
"2015-01-08 21:00:00+00:00 0 1544.168691 9.996796e+06 \n",
"2015-01-09 21:00:00+00:00 0 1448.880183 9.995676e+06 \n",
"2015-01-12 21:00:00+00:00 0 0.761052 9.994556e+06 \n",
"2015-01-13 21:00:00+00:00 0 3.046676 9.993463e+06 \n",
"2015-01-14 21:00:00+00:00 0 1.689259 9.992360e+06 \n",
"2015-01-15 21:00:00+00:00 0 -3.499660 9.991261e+06 \n",
"2015-01-16 21:00:00+00:00 0 -4.471937 9.990193e+06 \n",
"2015-01-20 21:00:00+00:00 0 0.056105 9.989132e+06 \n",
"2015-01-21 21:00:00+00:00 0 1.441909 9.988044e+06 \n",
"2015-01-22 21:00:00+00:00 0 6.421964 9.986948e+06 \n",
"2015-01-23 21:00:00+00:00 0 7.269664 9.985824e+06 \n",
"2015-01-26 21:00:00+00:00 0 7.262510 9.984693e+06 \n",
"2015-01-27 21:00:00+00:00 0 -0.395121 9.983562e+06 \n",
"2015-01-28 21:00:00+00:00 0 5.204787 9.982470e+06 \n",
"2015-01-29 21:00:00+00:00 0 8.427205 9.981316e+06 \n",
"2015-01-30 21:00:00+00:00 0 5.896422 9.980126e+06 \n",
"2015-02-02 21:00:00+00:00 0 7.074385 9.978954e+06 \n",
"2015-02-03 21:00:00+00:00 0 6.927452 9.977767e+06 \n",
"2015-02-04 21:00:00+00:00 0 7.637315 9.976580e+06 \n",
"2015-02-05 21:00:00+00:00 0 7.844195 9.975384e+06 \n",
"2015-02-06 21:00:00+00:00 0 6.360016 9.974184e+06 \n",
"2015-02-09 21:00:00+00:00 0 7.003060 9.972994e+06 \n",
"2015-02-10 21:00:00+00:00 0 9.158250 9.971796e+06 \n",
"2015-02-11 21:00:00+00:00 0 11.896861 9.970576e+06 \n",
"2015-02-12 21:00:00+00:00 0 13.325585 9.969326e+06 \n",
"2015-02-13 21:00:00+00:00 0 13.754550 9.968061e+06 \n",
"... ... ... ... \n",
"2017-11-16 21:00:00+00:00 0 1.701983 9.108258e+06 \n",
"2017-11-17 21:00:00+00:00 0 1.665168 9.106546e+06 \n",
"2017-11-20 21:00:00+00:00 0 1.658028 9.104844e+06 \n",
"2017-11-21 21:00:00+00:00 0 1.766789 9.103143e+06 \n",
"2017-11-22 21:00:00+00:00 0 1.828776 9.101411e+06 \n",
"2017-11-24 18:00:00+00:00 0 1.827867 9.099660e+06 \n",
"2017-11-27 21:00:00+00:00 0 1.793620 9.097910e+06 \n",
"2017-11-28 21:00:00+00:00 0 1.753772 9.096168e+06 \n",
"2017-11-29 21:00:00+00:00 0 1.592335 9.094436e+06 \n",
"2017-11-30 21:00:00+00:00 0 1.671977 9.092741e+06 \n",
"2017-12-01 21:00:00+00:00 0 1.641837 9.091021e+06 \n",
"2017-12-04 21:00:00+00:00 0 1.593961 9.089310e+06 \n",
"2017-12-05 21:00:00+00:00 0 1.587368 9.087611e+06 \n",
"2017-12-06 21:00:00+00:00 0 1.563801 9.085914e+06 \n",
"2017-12-07 21:00:00+00:00 0 1.577785 9.084223e+06 \n",
"2017-12-08 21:00:00+00:00 0 1.573906 9.082527e+06 \n",
"2017-12-11 21:00:00+00:00 0 1.685294 9.080833e+06 \n",
"2017-12-12 21:00:00+00:00 0 1.648512 9.079105e+06 \n",
"2017-12-13 21:00:00+00:00 0 1.666786 9.077387e+06 \n",
"2017-12-14 21:00:00+00:00 0 1.663955 9.075664e+06 \n",
"2017-12-15 21:00:00+00:00 0 1.719009 9.073941e+06 \n",
"2017-12-18 21:00:00+00:00 0 1.804624 9.072201e+06 \n",
"2017-12-19 21:00:00+00:00 0 1.729069 9.070436e+06 \n",
"2017-12-20 21:00:00+00:00 0 1.721372 9.068690e+06 \n",
"2017-12-21 21:00:00+00:00 0 1.742579 9.066945e+06 \n",
"2017-12-22 21:00:00+00:00 0 1.741415 9.065194e+06 \n",
"2017-12-26 21:00:00+00:00 0 1.538529 9.063443e+06 \n",
"2017-12-27 21:00:00+00:00 0 1.538491 9.061737e+06 \n",
"2017-12-28 21:00:00+00:00 0 1.553289 9.060030e+06 \n",
"2017-12-29 21:00:00+00:00 0 1.483009 9.058318e+06 \n",
"\n",
" starting_exposure starting_value trading_days \\\n",
"2015-01-02 21:00:00+00:00 0.00 0.00 1 \n",
"2015-01-05 21:00:00+00:00 0.00 0.00 2 \n",
"2015-01-06 21:00:00+00:00 1062.50 1062.50 3 \n",
"2015-01-07 21:00:00+00:00 2125.20 2125.20 4 \n",
"2015-01-08 21:00:00+00:00 3232.50 3232.50 5 \n",
"2015-01-09 21:00:00+00:00 4475.60 4475.60 6 \n",
"2015-01-12 21:00:00+00:00 5600.50 5600.50 7 \n",
"2015-01-13 21:00:00+00:00 6555.00 6555.00 8 \n",
"2015-01-14 21:00:00+00:00 7715.40 7715.40 9 \n",
"2015-01-15 21:00:00+00:00 8784.00 8784.00 10 \n",
"2015-01-16 21:00:00+00:00 9613.80 9613.80 11 \n",
"2015-01-20 21:00:00+00:00 10599.00 10599.00 12 \n",
"2015-01-21 21:00:00+00:00 11959.20 11959.20 13 \n",
"2015-01-22 21:00:00+00:00 13146.00 13146.00 14 \n",
"2015-01-23 21:00:00+00:00 14612.00 14612.00 15 \n",
"2015-01-26 21:00:00+00:00 15817.20 15817.20 16 \n",
"2015-01-27 21:00:00+00:00 16965.00 16965.00 17 \n",
"2015-01-28 21:00:00+00:00 17462.40 17462.40 18 \n",
"2015-01-29 21:00:00+00:00 19602.70 19602.70 19 \n",
"2015-01-30 21:00:00+00:00 21402.00 21402.00 20 \n",
"2015-02-02 21:00:00+00:00 22260.40 22260.40 21 \n",
"2015-02-03 21:00:00+00:00 23726.00 23726.00 22 \n",
"2015-02-04 21:00:00+00:00 24916.50 24916.50 23 \n",
"2015-02-05 21:00:00+00:00 26303.20 26303.20 24 \n",
"2015-02-06 21:00:00+00:00 27586.20 27586.20 25 \n",
"2015-02-09 21:00:00+00:00 28543.20 28543.20 26 \n",
"2015-02-10 21:00:00+00:00 29930.00 29930.00 27 \n",
"2015-02-11 21:00:00+00:00 31725.20 31725.20 28 \n",
"2015-02-12 21:00:00+00:00 33717.60 33717.60 29 \n",
"2015-02-13 21:00:00+00:00 35408.80 35408.80 30 \n",
"... ... ... ... \n",
"2017-11-16 21:00:00+00:00 1224139.20 1224139.20 726 \n",
"2017-11-17 21:00:00+00:00 1240475.00 1240475.00 727 \n",
"2017-11-20 21:00:00+00:00 1235289.00 1235289.00 728 \n",
"2017-11-21 21:00:00+00:00 1235754.60 1235754.60 729 \n",
"2017-11-22 21:00:00+00:00 1260459.20 1260459.20 730 \n",
"2017-11-24 18:00:00+00:00 1275458.40 1275458.40 731 \n",
"2017-11-27 21:00:00+00:00 1277281.00 1277281.00 732 \n",
"2017-11-28 21:00:00+00:00 1272597.90 1272597.90 733 \n",
"2017-11-29 21:00:00+00:00 1266872.40 1266872.40 734 \n",
"2017-11-30 21:00:00+00:00 1242288.40 1242288.40 735 \n",
"2017-12-01 21:00:00+00:00 1261379.00 1261379.00 736 \n",
"2017-12-04 21:00:00+00:00 1257217.50 1257217.50 737 \n",
"2017-12-05 21:00:00+00:00 1249728.00 1249728.00 738 \n",
"2017-12-06 21:00:00+00:00 1250246.80 1250246.80 739 \n",
"2017-12-07 21:00:00+00:00 1247293.80 1247293.80 740 \n",
"2017-12-08 21:00:00+00:00 1252250.28 1252250.28 741 \n",
"2017-12-11 21:00:00+00:00 1253338.00 1253338.00 742 \n",
"2017-12-12 21:00:00+00:00 1279484.70 1279484.70 743 \n",
"2017-12-13 21:00:00+00:00 1274014.00 1274014.00 744 \n",
"2017-12-14 21:00:00+00:00 1279966.10 1279966.10 745 \n",
"2017-12-15 21:00:00+00:00 1281316.80 1281316.80 746 \n",
"2017-12-18 21:00:00+00:00 1295331.50 1295331.50 747 \n",
"2017-12-19 21:00:00+00:00 1316093.20 1316093.20 748 \n",
"2017-12-20 21:00:00+00:00 1303813.80 1303813.80 749 \n",
"2017-12-21 21:00:00+00:00 1304138.00 1304138.00 750 \n",
"2017-12-22 21:00:00+00:00 1310824.90 1310824.90 751 \n",
"2017-12-26 21:00:00+00:00 1312575.00 1312575.00 752 \n",
"2017-12-27 21:00:00+00:00 1280980.70 1280980.70 753 \n",
"2017-12-28 21:00:00+00:00 1282912.00 1282912.00 754 \n",
"2017-12-29 21:00:00+00:00 1288232.40 1288232.40 755 \n",
"\n",
" transactions \\\n",
"2015-01-02 21:00:00+00:00 [] \n",
"2015-01-05 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2015-01-06 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2015-01-07 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2015-01-08 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2015-01-09 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2015-01-12 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2015-01-13 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2015-01-14 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2015-01-15 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2015-01-16 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2015-01-20 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2015-01-21 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2015-01-22 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2015-01-23 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2015-01-26 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2015-01-27 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2015-01-28 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2015-01-29 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2015-01-30 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2015-02-02 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2015-02-03 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2015-02-04 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2015-02-05 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2015-02-06 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2015-02-09 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2015-02-10 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2015-02-11 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2015-02-12 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2015-02-13 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"... ... \n",
"2017-11-16 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-11-17 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-11-20 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-11-21 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-11-22 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-11-24 18:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-11-27 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-11-28 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-11-29 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-11-30 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-01 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-04 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-05 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-06 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-07 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-08 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-11 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-12 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-13 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-14 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-15 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-18 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-19 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-20 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-21 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-22 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-26 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-27 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-28 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-29 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"\n",
" treasury_period_return \n",
"2015-01-02 21:00:00+00:00 0.0 \n",
"2015-01-05 21:00:00+00:00 0.0 \n",
"2015-01-06 21:00:00+00:00 0.0 \n",
"2015-01-07 21:00:00+00:00 0.0 \n",
"2015-01-08 21:00:00+00:00 0.0 \n",
"2015-01-09 21:00:00+00:00 0.0 \n",
"2015-01-12 21:00:00+00:00 0.0 \n",
"2015-01-13 21:00:00+00:00 0.0 \n",
"2015-01-14 21:00:00+00:00 0.0 \n",
"2015-01-15 21:00:00+00:00 0.0 \n",
"2015-01-16 21:00:00+00:00 0.0 \n",
"2015-01-20 21:00:00+00:00 0.0 \n",
"2015-01-21 21:00:00+00:00 0.0 \n",
"2015-01-22 21:00:00+00:00 0.0 \n",
"2015-01-23 21:00:00+00:00 0.0 \n",
"2015-01-26 21:00:00+00:00 0.0 \n",
"2015-01-27 21:00:00+00:00 0.0 \n",
"2015-01-28 21:00:00+00:00 0.0 \n",
"2015-01-29 21:00:00+00:00 0.0 \n",
"2015-01-30 21:00:00+00:00 0.0 \n",
"2015-02-02 21:00:00+00:00 0.0 \n",
"2015-02-03 21:00:00+00:00 0.0 \n",
"2015-02-04 21:00:00+00:00 0.0 \n",
"2015-02-05 21:00:00+00:00 0.0 \n",
"2015-02-06 21:00:00+00:00 0.0 \n",
"2015-02-09 21:00:00+00:00 0.0 \n",
"2015-02-10 21:00:00+00:00 0.0 \n",
"2015-02-11 21:00:00+00:00 0.0 \n",
"2015-02-12 21:00:00+00:00 0.0 \n",
"2015-02-13 21:00:00+00:00 0.0 \n",
"... ... \n",
"2017-11-16 21:00:00+00:00 0.0 \n",
"2017-11-17 21:00:00+00:00 0.0 \n",
"2017-11-20 21:00:00+00:00 0.0 \n",
"2017-11-21 21:00:00+00:00 0.0 \n",
"2017-11-22 21:00:00+00:00 0.0 \n",
"2017-11-24 18:00:00+00:00 0.0 \n",
"2017-11-27 21:00:00+00:00 0.0 \n",
"2017-11-28 21:00:00+00:00 0.0 \n",
"2017-11-29 21:00:00+00:00 0.0 \n",
"2017-11-30 21:00:00+00:00 0.0 \n",
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"2017-12-04 21:00:00+00:00 0.0 \n",
"2017-12-05 21:00:00+00:00 0.0 \n",
"2017-12-06 21:00:00+00:00 0.0 \n",
"2017-12-07 21:00:00+00:00 0.0 \n",
"2017-12-08 21:00:00+00:00 0.0 \n",
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"2017-12-18 21:00:00+00:00 0.0 \n",
"2017-12-19 21:00:00+00:00 0.0 \n",
"2017-12-20 21:00:00+00:00 0.0 \n",
"2017-12-21 21:00:00+00:00 0.0 \n",
"2017-12-22 21:00:00+00:00 0.0 \n",
"2017-12-26 21:00:00+00:00 0.0 \n",
"2017-12-27 21:00:00+00:00 0.0 \n",
"2017-12-28 21:00:00+00:00 0.0 \n",
"2017-12-29 21:00:00+00:00 0.0 \n",
"\n",
"[755 rows x 38 columns]"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"%%zipline --start 2015-1-1 --end 2018-1-1\n",
"from zipline.api import order, record, symbol\n",
"def initialize(context):\n",
" pass\n",
"\n",
"def handle_data(context, data):\n",
" order(symbol('AAPL'), 10)\n",
" record(AAPL=data.current(symbol('AAPL'), 'price'))"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"# the %zipline magic returns a dataframe of results\n",
"perf = _"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
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\" width=\"640\">"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"Text(0, 0.5, 'AAPL Stock Price')"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"%matplotlib notebook\n",
"\n",
"ax1 = plt.subplot(211)\n",
"perf.portfolio_value.plot(ax=ax1)\n",
"ax1.set_ylabel('Portfolio Value')\n",
"ax2 = plt.subplot(212, sharex=ax1)\n",
"perf.AAPL.plot(ax=ax2)\n",
"ax2.set_ylabel('AAPL Stock Price')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's see what happens to the data if we go back far enough to see the 2014 7-for-1 split of AAPL. Dealing with splits, dividends, and corporate actions is another area to explore."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"application/javascript": [
"/* Put everything inside the global mpl namespace */\n",
"window.mpl = {};\n",
"\n",
"\n",
"mpl.get_websocket_type = function() {\n",
" if (typeof(WebSocket) !== 'undefined') {\n",
" return WebSocket;\n",
" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
" 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
" 'Firefox 4 and 5 are also supported but you ' +\n",
" 'have to enable WebSockets in about:config.');\n",
" };\n",
"}\n",
"\n",
"mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
" this.id = figure_id;\n",
"\n",
" this.ws = websocket;\n",
"\n",
" this.supports_binary = (this.ws.binaryType != undefined);\n",
"\n",
" if (!this.supports_binary) {\n",
" var warnings = document.getElementById(\"mpl-warnings\");\n",
" if (warnings) {\n",
" warnings.style.display = 'block';\n",
" warnings.textContent = (\n",
" \"This browser does not support binary websocket messages. \" +\n",
" \"Performance may be slow.\");\n",
" }\n",
" }\n",
"\n",
" this.imageObj = new Image();\n",
"\n",
" this.context = undefined;\n",
" this.message = undefined;\n",
" this.canvas = undefined;\n",
" this.rubberband_canvas = undefined;\n",
" this.rubberband_context = undefined;\n",
" this.format_dropdown = undefined;\n",
"\n",
" this.image_mode = 'full';\n",
"\n",
" this.root = $('<div/>');\n",
" this._root_extra_style(this.root)\n",
" this.root.attr('style', 'display: inline-block');\n",
"\n",
" $(parent_element).append(this.root);\n",
"\n",
" this._init_header(this);\n",
" this._init_canvas(this);\n",
" this._init_toolbar(this);\n",
"\n",
" var fig = this;\n",
"\n",
" this.waiting = false;\n",
"\n",
" this.ws.onopen = function () {\n",
" fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
" fig.send_message(\"send_image_mode\", {});\n",
" if (mpl.ratio != 1) {\n",
" fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
" }\n",
" fig.send_message(\"refresh\", {});\n",
" }\n",
"\n",
" this.imageObj.onload = function() {\n",
" if (fig.image_mode == 'full') {\n",
" // Full images could contain transparency (where diff images\n",
" // almost always do), so we need to clear the canvas so that\n",
" // there is no ghosting.\n",
" fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
" }\n",
" fig.context.drawImage(fig.imageObj, 0, 0);\n",
" };\n",
"\n",
" this.imageObj.onunload = function() {\n",
" fig.ws.close();\n",
" }\n",
"\n",
" this.ws.onmessage = this._make_on_message_function(this);\n",
"\n",
" this.ondownload = ondownload;\n",
"}\n",
"\n",
"mpl.figure.prototype._init_header = function() {\n",
" var titlebar = $(\n",
" '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
" 'ui-helper-clearfix\"/>');\n",
" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
" 'text-align: center; padding: 3px;\"/>');\n",
" titlebar.append(titletext)\n",
" this.root.append(titlebar);\n",
" this.header = titletext[0];\n",
"}\n",
"\n",
"\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._init_canvas = function() {\n",
" var fig = this;\n",
"\n",
" var canvas_div = $('<div/>');\n",
"\n",
" canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
"\n",
" function canvas_keyboard_event(event) {\n",
" return fig.key_event(event, event['data']);\n",
" }\n",
"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
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" <th>algorithm_period_return</th>\n",
" <th>alpha</th>\n",
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" <th>beta</th>\n",
" <th>capital_used</th>\n",
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" <th>2014-01-02 21:00:00+00:00</th>\n",
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" <td>[{'amount': 10, 'commission': None, 'price': 5...</td>\n",
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" <tr>\n",
" <th>2014-01-06 21:00:00+00:00</th>\n",
" <td>543.930</td>\n",
" <td>0.000026</td>\n",
" <td>2.405545e-06</td>\n",
" <td>NaN</td>\n",
" <td>-0.002031</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>-5442.029650</td>\n",
" <td>9.989145e+06</td>\n",
" <td>10878.60</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>81.208114</td>\n",
" <td>9.994587e+06</td>\n",
" <td>5409.80</td>\n",
" <td>5409.80</td>\n",
" <td>3</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 5...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-01-07 21:00:00+00:00</th>\n",
" <td>540.037</td>\n",
" <td>0.000073</td>\n",
" <td>-5.651473e-06</td>\n",
" <td>NaN</td>\n",
" <td>-0.002708</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>-5403.080185</td>\n",
" <td>9.983742e+06</td>\n",
" <td>16201.11</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>-5.564302</td>\n",
" <td>9.989145e+06</td>\n",
" <td>10878.60</td>\n",
" <td>10878.60</td>\n",
" <td>4</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 5...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-01-08 21:00:00+00:00</th>\n",
" <td>543.460</td>\n",
" <td>0.000103</td>\n",
" <td>4.344797e-06</td>\n",
" <td>NaN</td>\n",
" <td>-0.003383</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>-5437.327300</td>\n",
" <td>9.978305e+06</td>\n",
" <td>21738.40</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>3.826244</td>\n",
" <td>9.983742e+06</td>\n",
" <td>16201.11</td>\n",
" <td>16201.11</td>\n",
" <td>5</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 5...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-01-09 21:00:00+00:00</th>\n",
" <td>536.519</td>\n",
" <td>0.000209</td>\n",
" <td>-2.368846e-05</td>\n",
" <td>NaN</td>\n",
" <td>-0.004059</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>-5367.882595</td>\n",
" <td>9.972937e+06</td>\n",
" <td>26825.95</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>-5.262989</td>\n",
" <td>9.978305e+06</td>\n",
" <td>21738.40</td>\n",
" <td>21738.40</td>\n",
" <td>6</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 5...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-01-10 21:00:00+00:00</th>\n",
" <td>532.940</td>\n",
" <td>0.000209</td>\n",
" <td>-4.185093e-05</td>\n",
" <td>NaN</td>\n",
" <td>-0.004734</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>-5332.074700</td>\n",
" <td>9.967605e+06</td>\n",
" <td>31976.40</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>-7.307726</td>\n",
" <td>9.972937e+06</td>\n",
" <td>26825.95</td>\n",
" <td>26825.95</td>\n",
" <td>7</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 5...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-01-13 21:00:00+00:00</th>\n",
" <td>535.730</td>\n",
" <td>0.000231</td>\n",
" <td>-2.537980e-05</td>\n",
" <td>NaN</td>\n",
" <td>-0.005408</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>-5359.988650</td>\n",
" <td>9.962245e+06</td>\n",
" <td>37501.10</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>-4.145330</td>\n",
" <td>9.967605e+06</td>\n",
" <td>31976.40</td>\n",
" <td>31976.40</td>\n",
" <td>8</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 5...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-01-14 21:00:00+00:00</th>\n",
" <td>546.390</td>\n",
" <td>0.000464</td>\n",
" <td>4.896601e-05</td>\n",
" <td>NaN</td>\n",
" <td>-0.006082</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>-5466.641950</td>\n",
" <td>9.956778e+06</td>\n",
" <td>43711.20</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>7.540809</td>\n",
" <td>9.962245e+06</td>\n",
" <td>37501.10</td>\n",
" <td>37501.10</td>\n",
" <td>9</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 5...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-01-15 21:00:00+00:00</th>\n",
" <td>557.360</td>\n",
" <td>0.000600</td>\n",
" <td>1.364463e-04</td>\n",
" <td>NaN</td>\n",
" <td>-0.006755</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>-5576.396800</td>\n",
" <td>9.951202e+06</td>\n",
" <td>50162.40</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>19.933310</td>\n",
" <td>9.956778e+06</td>\n",
" <td>43711.20</td>\n",
" <td>43711.20</td>\n",
" <td>10</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 5...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-01-16 21:00:00+00:00</th>\n",
" <td>554.250</td>\n",
" <td>0.000604</td>\n",
" <td>1.081782e-04</td>\n",
" <td>NaN</td>\n",
" <td>-0.007428</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>-5545.281250</td>\n",
" <td>9.945657e+06</td>\n",
" <td>55425.00</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>11.637563</td>\n",
" <td>9.951202e+06</td>\n",
" <td>50162.40</td>\n",
" <td>50162.40</td>\n",
" <td>11</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 5...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-01-17 21:00:00+00:00</th>\n",
" <td>540.670</td>\n",
" <td>0.000882</td>\n",
" <td>-2.789313e-05</td>\n",
" <td>NaN</td>\n",
" <td>-0.008101</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>-5409.413350</td>\n",
" <td>9.940247e+06</td>\n",
" <td>59473.70</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>-0.892414</td>\n",
" <td>9.945657e+06</td>\n",
" <td>55425.00</td>\n",
" <td>55425.00</td>\n",
" <td>12</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 5...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-01-21 21:00:00+00:00</th>\n",
" <td>549.070</td>\n",
" <td>0.000942</td>\n",
" <td>6.423133e-05</td>\n",
" <td>NaN</td>\n",
" <td>-0.008773</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>-5493.455350</td>\n",
" <td>9.934754e+06</td>\n",
" <td>65888.40</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.976167</td>\n",
" <td>9.940247e+06</td>\n",
" <td>59473.70</td>\n",
" <td>59473.70</td>\n",
" <td>13</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 5...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-01-22 21:00:00+00:00</th>\n",
" <td>551.510</td>\n",
" <td>0.000910</td>\n",
" <td>9.323458e-05</td>\n",
" <td>NaN</td>\n",
" <td>-0.009445</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>-5517.867550</td>\n",
" <td>9.929236e+06</td>\n",
" <td>71696.30</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>2.763837</td>\n",
" <td>9.934754e+06</td>\n",
" <td>65888.40</td>\n",
" <td>65888.40</td>\n",
" <td>14</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 5...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-01-23 21:00:00+00:00</th>\n",
" <td>556.180</td>\n",
" <td>0.000905</td>\n",
" <td>1.536655e-04</td>\n",
" <td>NaN</td>\n",
" <td>-0.010116</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>-5564.590900</td>\n",
" <td>9.923671e+06</td>\n",
" <td>77865.20</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>4.400301</td>\n",
" <td>9.929236e+06</td>\n",
" <td>71696.30</td>\n",
" <td>71696.30</td>\n",
" <td>15</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 5...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-01-24 21:00:00+00:00</th>\n",
" <td>546.070</td>\n",
" <td>0.001062</td>\n",
" <td>1.185145e-05</td>\n",
" <td>NaN</td>\n",
" <td>-0.010787</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>-5463.440350</td>\n",
" <td>9.918208e+06</td>\n",
" <td>81910.50</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0.234097</td>\n",
" <td>9.923671e+06</td>\n",
" <td>77865.20</td>\n",
" <td>77865.20</td>\n",
" <td>16</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 5...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-01-27 21:00:00+00:00</th>\n",
" <td>550.500</td>\n",
" <td>0.001059</td>\n",
" <td>7.802520e-05</td>\n",
" <td>NaN</td>\n",
" <td>-0.011457</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>-5507.762500</td>\n",
" <td>9.912700e+06</td>\n",
" <td>88080.00</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.491595</td>\n",
" <td>9.918208e+06</td>\n",
" <td>81910.50</td>\n",
" <td>81910.50</td>\n",
" <td>17</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 5...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-01-28 21:00:00+00:00</th>\n",
" <td>506.500</td>\n",
" <td>0.002844</td>\n",
" <td>-6.262290e-04</td>\n",
" <td>NaN</td>\n",
" <td>-0.012127</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>-5067.542500</td>\n",
" <td>9.907633e+06</td>\n",
" <td>86105.00</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>-3.198560</td>\n",
" <td>9.912700e+06</td>\n",
" <td>88080.00</td>\n",
" <td>88080.00</td>\n",
" <td>18</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 5...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-01-29 21:00:00+00:00</th>\n",
" <td>500.750</td>\n",
" <td>0.002773</td>\n",
" <td>-7.242304e-04</td>\n",
" <td>NaN</td>\n",
" <td>-0.012796</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>-5010.013750</td>\n",
" <td>9.902623e+06</td>\n",
" <td>90135.00</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>-3.568986</td>\n",
" <td>9.907633e+06</td>\n",
" <td>86105.00</td>\n",
" <td>86105.00</td>\n",
" <td>19</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 5...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-01-30 21:00:00+00:00</th>\n",
" <td>499.782</td>\n",
" <td>0.002700</td>\n",
" <td>-7.419053e-04</td>\n",
" <td>NaN</td>\n",
" <td>-0.013465</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>-5000.328910</td>\n",
" <td>9.897622e+06</td>\n",
" <td>94958.58</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>-3.562557</td>\n",
" <td>9.902623e+06</td>\n",
" <td>90135.00</td>\n",
" <td>90135.00</td>\n",
" <td>20</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 5...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-01-31 21:00:00+00:00</th>\n",
" <td>500.600</td>\n",
" <td>0.002638</td>\n",
" <td>-7.266146e-04</td>\n",
" <td>NaN</td>\n",
" <td>-0.014134</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>-5008.513000</td>\n",
" <td>9.892614e+06</td>\n",
" <td>100120.00</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>-3.404990</td>\n",
" <td>9.897622e+06</td>\n",
" <td>94958.58</td>\n",
" <td>94958.58</td>\n",
" <td>21</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 5...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-02-03 21:00:00+00:00</th>\n",
" <td>501.530</td>\n",
" <td>0.002581</td>\n",
" <td>-7.082664e-04</td>\n",
" <td>NaN</td>\n",
" <td>-0.014802</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>-5017.817650</td>\n",
" <td>9.887596e+06</td>\n",
" <td>105321.30</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>-3.242636</td>\n",
" <td>9.892614e+06</td>\n",
" <td>100120.00</td>\n",
" <td>100120.00</td>\n",
" <td>22</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 5...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-02-04 21:00:00+00:00</th>\n",
" <td>508.790</td>\n",
" <td>0.002595</td>\n",
" <td>-5.560618e-04</td>\n",
" <td>NaN</td>\n",
" <td>-0.015469</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>-5090.453950</td>\n",
" <td>9.882506e+06</td>\n",
" <td>111933.80</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>-2.489323</td>\n",
" <td>9.887596e+06</td>\n",
" <td>105321.30</td>\n",
" <td>105321.30</td>\n",
" <td>23</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 5...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-02-05 21:00:00+00:00</th>\n",
" <td>512.590</td>\n",
" <td>0.002561</td>\n",
" <td>-4.727191e-04</td>\n",
" <td>NaN</td>\n",
" <td>-0.016136</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>-5128.472950</td>\n",
" <td>9.877377e+06</td>\n",
" <td>117895.70</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>-2.071367</td>\n",
" <td>9.882506e+06</td>\n",
" <td>111933.80</td>\n",
" <td>111933.80</td>\n",
" <td>24</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 5...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-02-06 21:00:00+00:00</th>\n",
" <td>512.510</td>\n",
" <td>0.002508</td>\n",
" <td>-4.748163e-04</td>\n",
" <td>NaN</td>\n",
" <td>-0.016803</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>-5127.672550</td>\n",
" <td>9.872249e+06</td>\n",
" <td>123002.40</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>-2.038520</td>\n",
" <td>9.877377e+06</td>\n",
" <td>117895.70</td>\n",
" <td>117895.70</td>\n",
" <td>25</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 5...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-02-07 21:00:00+00:00</th>\n",
" <td>519.679</td>\n",
" <td>0.002528</td>\n",
" <td>-3.030212e-04</td>\n",
" <td>NaN</td>\n",
" <td>-0.017469</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>-5199.398395</td>\n",
" <td>9.867050e+06</td>\n",
" <td>129919.75</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>-1.275056</td>\n",
" <td>9.872249e+06</td>\n",
" <td>123002.40</td>\n",
" <td>123002.40</td>\n",
" <td>26</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 5...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-02-10 21:00:00+00:00</th>\n",
" <td>528.990</td>\n",
" <td>0.002589</td>\n",
" <td>-7.051166e-05</td>\n",
" <td>NaN</td>\n",
" <td>-0.018135</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>-5292.554950</td>\n",
" <td>9.861757e+06</td>\n",
" <td>137537.40</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>-0.289997</td>\n",
" <td>9.867050e+06</td>\n",
" <td>129919.75</td>\n",
" <td>129919.75</td>\n",
" <td>27</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 5...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-02-11 21:00:00+00:00</th>\n",
" <td>535.960</td>\n",
" <td>0.002600</td>\n",
" <td>1.104394e-04</td>\n",
" <td>NaN</td>\n",
" <td>-0.018800</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>-5362.289800</td>\n",
" <td>9.856395e+06</td>\n",
" <td>144709.20</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0.449653</td>\n",
" <td>9.861757e+06</td>\n",
" <td>137537.40</td>\n",
" <td>137537.40</td>\n",
" <td>28</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 5...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-02-12 21:00:00+00:00</th>\n",
" <td>535.920</td>\n",
" <td>0.002553</td>\n",
" <td>1.090904e-04</td>\n",
" <td>NaN</td>\n",
" <td>-0.019465</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>-5361.889600</td>\n",
" <td>9.851033e+06</td>\n",
" <td>150057.60</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>0.436453</td>\n",
" <td>9.856395e+06</td>\n",
" <td>144709.20</td>\n",
" <td>144709.20</td>\n",
" <td>29</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 5...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014-02-13 21:00:00+00:00</th>\n",
" <td>544.430</td>\n",
" <td>0.002599</td>\n",
" <td>3.470972e-04</td>\n",
" <td>NaN</td>\n",
" <td>-0.020130</td>\n",
" <td>0.000000</td>\n",
" <td>NaN</td>\n",
" <td>-5447.032150</td>\n",
" <td>9.845586e+06</td>\n",
" <td>157884.70</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.362189</td>\n",
" <td>9.851033e+06</td>\n",
" <td>150057.60</td>\n",
" <td>150057.60</td>\n",
" <td>30</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 5...</td>\n",
" <td>0.0</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",
" <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>2017-11-16 21:00:00+00:00</th>\n",
" <td>171.100</td>\n",
" <td>0.029146</td>\n",
" <td>1.140948e-01</td>\n",
" <td>0.025302</td>\n",
" <td>0.068134</td>\n",
" <td>0.110736</td>\n",
" <td>0.141713</td>\n",
" <td>-1711.865500</td>\n",
" <td>8.360573e+06</td>\n",
" <td>2780375.00</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.441294</td>\n",
" <td>8.362285e+06</td>\n",
" <td>2745859.20</td>\n",
" <td>2745859.20</td>\n",
" <td>978</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-11-17 21:00:00+00:00</th>\n",
" <td>170.150</td>\n",
" <td>0.029141</td>\n",
" <td>1.125510e-01</td>\n",
" <td>0.025019</td>\n",
" <td>0.064995</td>\n",
" <td>0.110690</td>\n",
" <td>0.141781</td>\n",
" <td>-1702.360750</td>\n",
" <td>8.358871e+06</td>\n",
" <td>2766639.00</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.421445</td>\n",
" <td>8.360573e+06</td>\n",
" <td>2780375.00</td>\n",
" <td>2780375.00</td>\n",
" <td>979</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-11-20 21:00:00+00:00</th>\n",
" <td>169.980</td>\n",
" <td>0.029127</td>\n",
" <td>1.122745e-01</td>\n",
" <td>0.024864</td>\n",
" <td>0.066813</td>\n",
" <td>0.110637</td>\n",
" <td>0.141761</td>\n",
" <td>-1700.659900</td>\n",
" <td>8.357170e+06</td>\n",
" <td>2765574.60</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.417430</td>\n",
" <td>8.358871e+06</td>\n",
" <td>2766639.00</td>\n",
" <td>2766639.00</td>\n",
" <td>980</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-11-21 21:00:00+00:00</th>\n",
" <td>173.140</td>\n",
" <td>0.029202</td>\n",
" <td>1.174157e-01</td>\n",
" <td>0.025799</td>\n",
" <td>0.073793</td>\n",
" <td>0.110628</td>\n",
" <td>0.142248</td>\n",
" <td>-1732.275700</td>\n",
" <td>8.355438e+06</td>\n",
" <td>2818719.20</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.477307</td>\n",
" <td>8.357170e+06</td>\n",
" <td>2765574.60</td>\n",
" <td>2765574.60</td>\n",
" <td>981</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-11-22 21:00:00+00:00</th>\n",
" <td>174.960</td>\n",
" <td>0.029215</td>\n",
" <td>1.203786e-01</td>\n",
" <td>0.026505</td>\n",
" <td>0.072843</td>\n",
" <td>0.110573</td>\n",
" <td>0.142193</td>\n",
" <td>-1750.484800</td>\n",
" <td>8.353687e+06</td>\n",
" <td>2850098.40</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.511300</td>\n",
" <td>8.355438e+06</td>\n",
" <td>2818719.20</td>\n",
" <td>2818719.20</td>\n",
" <td>982</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-11-24 18:00:00+00:00</th>\n",
" <td>174.970</td>\n",
" <td>0.029200</td>\n",
" <td>1.203948e-01</td>\n",
" <td>0.026396</td>\n",
" <td>0.075321</td>\n",
" <td>0.110522</td>\n",
" <td>0.142173</td>\n",
" <td>-1750.584850</td>\n",
" <td>8.351937e+06</td>\n",
" <td>2852011.00</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.510720</td>\n",
" <td>8.353687e+06</td>\n",
" <td>2850098.40</td>\n",
" <td>2850098.40</td>\n",
" <td>983</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-11-27 21:00:00+00:00</th>\n",
" <td>174.090</td>\n",
" <td>0.029194</td>\n",
" <td>1.189603e-01</td>\n",
" <td>0.026051</td>\n",
" <td>0.074784</td>\n",
" <td>0.110467</td>\n",
" <td>0.142190</td>\n",
" <td>-1741.780450</td>\n",
" <td>8.350195e+06</td>\n",
" <td>2839407.90</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.492374</td>\n",
" <td>8.351937e+06</td>\n",
" <td>2852011.00</td>\n",
" <td>2852011.00</td>\n",
" <td>984</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-11-28 21:00:00+00:00</th>\n",
" <td>173.070</td>\n",
" <td>0.029191</td>\n",
" <td>1.172966e-01</td>\n",
" <td>0.025273</td>\n",
" <td>0.085687</td>\n",
" <td>0.110527</td>\n",
" <td>0.141552</td>\n",
" <td>-1731.575350</td>\n",
" <td>8.348463e+06</td>\n",
" <td>2824502.40</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.471087</td>\n",
" <td>8.350195e+06</td>\n",
" <td>2839407.90</td>\n",
" <td>2839407.90</td>\n",
" <td>985</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-11-29 21:00:00+00:00</th>\n",
" <td>169.480</td>\n",
" <td>0.029301</td>\n",
" <td>1.114376e-01</td>\n",
" <td>0.023894</td>\n",
" <td>0.085027</td>\n",
" <td>0.110472</td>\n",
" <td>0.141631</td>\n",
" <td>-1695.657400</td>\n",
" <td>8.346768e+06</td>\n",
" <td>2767608.40</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.389166</td>\n",
" <td>8.348463e+06</td>\n",
" <td>2824502.40</td>\n",
" <td>2824502.40</td>\n",
" <td>986</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-11-30 21:00:00+00:00</th>\n",
" <td>171.850</td>\n",
" <td>0.029336</td>\n",
" <td>1.153077e-01</td>\n",
" <td>0.024445</td>\n",
" <td>0.094526</td>\n",
" <td>0.110502</td>\n",
" <td>0.142019</td>\n",
" <td>-1719.369250</td>\n",
" <td>8.345048e+06</td>\n",
" <td>2808029.00</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.433504</td>\n",
" <td>8.346768e+06</td>\n",
" <td>2767608.40</td>\n",
" <td>2767608.40</td>\n",
" <td>987</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-01 21:00:00+00:00</th>\n",
" <td>171.050</td>\n",
" <td>0.029328</td>\n",
" <td>1.140004e-01</td>\n",
" <td>0.024189</td>\n",
" <td>0.092254</td>\n",
" <td>0.110452</td>\n",
" <td>0.142064</td>\n",
" <td>-1711.365250</td>\n",
" <td>8.343337e+06</td>\n",
" <td>2796667.50</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.416986</td>\n",
" <td>8.345048e+06</td>\n",
" <td>2808029.00</td>\n",
" <td>2808029.00</td>\n",
" <td>988</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-04 21:00:00+00:00</th>\n",
" <td>169.800</td>\n",
" <td>0.029330</td>\n",
" <td>1.119566e-01</td>\n",
" <td>0.023729</td>\n",
" <td>0.090933</td>\n",
" <td>0.110398</td>\n",
" <td>0.142112</td>\n",
" <td>-1698.859000</td>\n",
" <td>8.341638e+06</td>\n",
" <td>2777928.00</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.391040</td>\n",
" <td>8.343337e+06</td>\n",
" <td>2796667.50</td>\n",
" <td>2796667.50</td>\n",
" <td>989</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-05 21:00:00+00:00</th>\n",
" <td>169.640</td>\n",
" <td>0.029316</td>\n",
" <td>1.116948e-01</td>\n",
" <td>0.023777</td>\n",
" <td>0.087009</td>\n",
" <td>0.110358</td>\n",
" <td>0.142098</td>\n",
" <td>-1697.258200</td>\n",
" <td>8.339941e+06</td>\n",
" <td>2777006.80</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.387275</td>\n",
" <td>8.341638e+06</td>\n",
" <td>2777928.00</td>\n",
" <td>2777928.00</td>\n",
" <td>990</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-06 21:00:00+00:00</th>\n",
" <td>169.010</td>\n",
" <td>0.029305</td>\n",
" <td>1.106634e-01</td>\n",
" <td>0.023504</td>\n",
" <td>0.087216</td>\n",
" <td>0.110302</td>\n",
" <td>0.142096</td>\n",
" <td>-1690.955050</td>\n",
" <td>8.338250e+06</td>\n",
" <td>2768383.80</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.374231</td>\n",
" <td>8.339941e+06</td>\n",
" <td>2777006.80</td>\n",
" <td>2777006.80</td>\n",
" <td>991</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-07 21:00:00+00:00</th>\n",
" <td>169.452</td>\n",
" <td>0.029292</td>\n",
" <td>1.113873e-01</td>\n",
" <td>0.023533</td>\n",
" <td>0.090644</td>\n",
" <td>0.110257</td>\n",
" <td>0.142104</td>\n",
" <td>-1695.377260</td>\n",
" <td>8.336554e+06</td>\n",
" <td>2777318.28</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.381932</td>\n",
" <td>8.338250e+06</td>\n",
" <td>2768383.80</td>\n",
" <td>2768383.80</td>\n",
" <td>992</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-08 21:00:00+00:00</th>\n",
" <td>169.370</td>\n",
" <td>0.029277</td>\n",
" <td>1.112528e-01</td>\n",
" <td>0.023280</td>\n",
" <td>0.096591</td>\n",
" <td>0.110235</td>\n",
" <td>0.141993</td>\n",
" <td>-1694.556850</td>\n",
" <td>8.334860e+06</td>\n",
" <td>2777668.00</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.379672</td>\n",
" <td>8.336554e+06</td>\n",
" <td>2777318.28</td>\n",
" <td>2777318.28</td>\n",
" <td>993</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-11 21:00:00+00:00</th>\n",
" <td>172.670</td>\n",
" <td>0.029361</td>\n",
" <td>1.166647e-01</td>\n",
" <td>0.024401</td>\n",
" <td>0.099895</td>\n",
" <td>0.110189</td>\n",
" <td>0.142256</td>\n",
" <td>-1727.573350</td>\n",
" <td>8.333132e+06</td>\n",
" <td>2833514.70</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.441636</td>\n",
" <td>8.334860e+06</td>\n",
" <td>2777668.00</td>\n",
" <td>2777668.00</td>\n",
" <td>994</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-12 21:00:00+00:00</th>\n",
" <td>171.700</td>\n",
" <td>0.029356</td>\n",
" <td>1.150728e-01</td>\n",
" <td>0.023943</td>\n",
" <td>0.101836</td>\n",
" <td>0.110136</td>\n",
" <td>0.142196</td>\n",
" <td>-1717.868500</td>\n",
" <td>8.331414e+06</td>\n",
" <td>2819314.00</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.421637</td>\n",
" <td>8.333132e+06</td>\n",
" <td>2833514.70</td>\n",
" <td>2833514.70</td>\n",
" <td>995</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-13 21:00:00+00:00</th>\n",
" <td>172.270</td>\n",
" <td>0.029344</td>\n",
" <td>1.160087e-01</td>\n",
" <td>0.024141</td>\n",
" <td>0.101712</td>\n",
" <td>0.110081</td>\n",
" <td>0.142192</td>\n",
" <td>-1723.571350</td>\n",
" <td>8.329691e+06</td>\n",
" <td>2830396.10</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.431703</td>\n",
" <td>8.331414e+06</td>\n",
" <td>2819314.00</td>\n",
" <td>2819314.00</td>\n",
" <td>996</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-14 21:00:00+00:00</th>\n",
" <td>172.220</td>\n",
" <td>0.029329</td>\n",
" <td>1.159265e-01</td>\n",
" <td>0.024248</td>\n",
" <td>0.097210</td>\n",
" <td>0.110046</td>\n",
" <td>0.142156</td>\n",
" <td>-1723.071100</td>\n",
" <td>8.327968e+06</td>\n",
" <td>2831296.80</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.430037</td>\n",
" <td>8.329691e+06</td>\n",
" <td>2830396.10</td>\n",
" <td>2830396.10</td>\n",
" <td>997</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-15 21:00:00+00:00</th>\n",
" <td>173.870</td>\n",
" <td>0.029338</td>\n",
" <td>1.186390e-01</td>\n",
" <td>0.024731</td>\n",
" <td>0.100721</td>\n",
" <td>0.110002</td>\n",
" <td>0.142277</td>\n",
" <td>-1739.579350</td>\n",
" <td>8.326228e+06</td>\n",
" <td>2860161.50</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.460510</td>\n",
" <td>8.327968e+06</td>\n",
" <td>2831296.80</td>\n",
" <td>2831296.80</td>\n",
" <td>998</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-18 21:00:00+00:00</th>\n",
" <td>176.420</td>\n",
" <td>0.029380</td>\n",
" <td>1.228336e-01</td>\n",
" <td>0.025431</td>\n",
" <td>0.107701</td>\n",
" <td>0.109991</td>\n",
" <td>0.142633</td>\n",
" <td>-1765.092100</td>\n",
" <td>8.324463e+06</td>\n",
" <td>2903873.20</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.507871</td>\n",
" <td>8.326228e+06</td>\n",
" <td>2860161.50</td>\n",
" <td>2860161.50</td>\n",
" <td>999</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-19 21:00:00+00:00</th>\n",
" <td>174.540</td>\n",
" <td>0.029400</td>\n",
" <td>1.197391e-01</td>\n",
" <td>0.024829</td>\n",
" <td>0.103447</td>\n",
" <td>0.109954</td>\n",
" <td>0.142824</td>\n",
" <td>-1746.282700</td>\n",
" <td>8.322717e+06</td>\n",
" <td>2874673.80</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.468156</td>\n",
" <td>8.324463e+06</td>\n",
" <td>2903873.20</td>\n",
" <td>2903873.20</td>\n",
" <td>1000</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-20 21:00:00+00:00</th>\n",
" <td>174.350</td>\n",
" <td>0.029386</td>\n",
" <td>1.194260e-01</td>\n",
" <td>0.024751</td>\n",
" <td>0.102869</td>\n",
" <td>0.109899</td>\n",
" <td>0.142828</td>\n",
" <td>-1744.381750</td>\n",
" <td>8.320972e+06</td>\n",
" <td>2873288.00</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.463813</td>\n",
" <td>8.322717e+06</td>\n",
" <td>2874673.80</td>\n",
" <td>2874673.80</td>\n",
" <td>1001</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-21 21:00:00+00:00</th>\n",
" <td>175.010</td>\n",
" <td>0.029375</td>\n",
" <td>1.205136e-01</td>\n",
" <td>0.024899</td>\n",
" <td>0.105140</td>\n",
" <td>0.109849</td>\n",
" <td>0.142852</td>\n",
" <td>-1750.985050</td>\n",
" <td>8.319222e+06</td>\n",
" <td>2885914.90</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.475493</td>\n",
" <td>8.320972e+06</td>\n",
" <td>2873288.00</td>\n",
" <td>2873288.00</td>\n",
" <td>1002</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-22 21:00:00+00:00</th>\n",
" <td>175.010</td>\n",
" <td>0.029360</td>\n",
" <td>1.205136e-01</td>\n",
" <td>0.024884</td>\n",
" <td>0.104851</td>\n",
" <td>0.109794</td>\n",
" <td>0.142852</td>\n",
" <td>-1750.985050</td>\n",
" <td>8.317471e+06</td>\n",
" <td>2887665.00</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.474756</td>\n",
" <td>8.319222e+06</td>\n",
" <td>2885914.90</td>\n",
" <td>2885914.90</td>\n",
" <td>1003</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-26 21:00:00+00:00</th>\n",
" <td>170.570</td>\n",
" <td>0.029534</td>\n",
" <td>1.131875e-01</td>\n",
" <td>0.023217</td>\n",
" <td>0.103530</td>\n",
" <td>0.109741</td>\n",
" <td>0.143030</td>\n",
" <td>-1706.562850</td>\n",
" <td>8.315764e+06</td>\n",
" <td>2816110.70</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.371694</td>\n",
" <td>8.317471e+06</td>\n",
" <td>2887665.00</td>\n",
" <td>2887665.00</td>\n",
" <td>1004</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-27 21:00:00+00:00</th>\n",
" <td>170.600</td>\n",
" <td>0.029520</td>\n",
" <td>1.132369e-01</td>\n",
" <td>0.023187</td>\n",
" <td>0.104066</td>\n",
" <td>0.109687</td>\n",
" <td>0.143029</td>\n",
" <td>-1706.863000</td>\n",
" <td>8.314057e+06</td>\n",
" <td>2818312.00</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.371570</td>\n",
" <td>8.315764e+06</td>\n",
" <td>2816110.70</td>\n",
" <td>2816110.70</td>\n",
" <td>1005</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-28 21:00:00+00:00</th>\n",
" <td>171.080</td>\n",
" <td>0.029506</td>\n",
" <td>1.140298e-01</td>\n",
" <td>0.023270</td>\n",
" <td>0.106338</td>\n",
" <td>0.109637</td>\n",
" <td>0.143042</td>\n",
" <td>-1711.665400</td>\n",
" <td>8.312345e+06</td>\n",
" <td>2827952.40</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.379845</td>\n",
" <td>8.314057e+06</td>\n",
" <td>2818312.00</td>\n",
" <td>2818312.00</td>\n",
" <td>1006</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-29 21:00:00+00:00</th>\n",
" <td>169.230</td>\n",
" <td>0.029526</td>\n",
" <td>1.109716e-01</td>\n",
" <td>0.022677</td>\n",
" <td>0.102167</td>\n",
" <td>0.109599</td>\n",
" <td>0.143229</td>\n",
" <td>-1693.156150</td>\n",
" <td>8.310652e+06</td>\n",
" <td>2799064.20</td>\n",
" <td>...</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.341469</td>\n",
" <td>8.312345e+06</td>\n",
" <td>2827952.40</td>\n",
" <td>2827952.40</td>\n",
" <td>1007</td>\n",
" <td>[{'amount': 10, 'commission': None, 'price': 1...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>1007 rows × 38 columns</p>\n",
"</div>"
],
"text/plain": [
" AAPL algo_volatility algorithm_period_return \\\n",
"2014-01-02 21:00:00+00:00 553.130 NaN 0.000000e+00 \n",
"2014-01-03 21:00:00+00:00 540.980 0.000003 -2.714900e-07 \n",
"2014-01-06 21:00:00+00:00 543.930 0.000026 2.405545e-06 \n",
"2014-01-07 21:00:00+00:00 540.037 0.000073 -5.651473e-06 \n",
"2014-01-08 21:00:00+00:00 543.460 0.000103 4.344797e-06 \n",
"2014-01-09 21:00:00+00:00 536.519 0.000209 -2.368846e-05 \n",
"2014-01-10 21:00:00+00:00 532.940 0.000209 -4.185093e-05 \n",
"2014-01-13 21:00:00+00:00 535.730 0.000231 -2.537980e-05 \n",
"2014-01-14 21:00:00+00:00 546.390 0.000464 4.896601e-05 \n",
"2014-01-15 21:00:00+00:00 557.360 0.000600 1.364463e-04 \n",
"2014-01-16 21:00:00+00:00 554.250 0.000604 1.081782e-04 \n",
"2014-01-17 21:00:00+00:00 540.670 0.000882 -2.789313e-05 \n",
"2014-01-21 21:00:00+00:00 549.070 0.000942 6.423133e-05 \n",
"2014-01-22 21:00:00+00:00 551.510 0.000910 9.323458e-05 \n",
"2014-01-23 21:00:00+00:00 556.180 0.000905 1.536655e-04 \n",
"2014-01-24 21:00:00+00:00 546.070 0.001062 1.185145e-05 \n",
"2014-01-27 21:00:00+00:00 550.500 0.001059 7.802520e-05 \n",
"2014-01-28 21:00:00+00:00 506.500 0.002844 -6.262290e-04 \n",
"2014-01-29 21:00:00+00:00 500.750 0.002773 -7.242304e-04 \n",
"2014-01-30 21:00:00+00:00 499.782 0.002700 -7.419053e-04 \n",
"2014-01-31 21:00:00+00:00 500.600 0.002638 -7.266146e-04 \n",
"2014-02-03 21:00:00+00:00 501.530 0.002581 -7.082664e-04 \n",
"2014-02-04 21:00:00+00:00 508.790 0.002595 -5.560618e-04 \n",
"2014-02-05 21:00:00+00:00 512.590 0.002561 -4.727191e-04 \n",
"2014-02-06 21:00:00+00:00 512.510 0.002508 -4.748163e-04 \n",
"2014-02-07 21:00:00+00:00 519.679 0.002528 -3.030212e-04 \n",
"2014-02-10 21:00:00+00:00 528.990 0.002589 -7.051166e-05 \n",
"2014-02-11 21:00:00+00:00 535.960 0.002600 1.104394e-04 \n",
"2014-02-12 21:00:00+00:00 535.920 0.002553 1.090904e-04 \n",
"2014-02-13 21:00:00+00:00 544.430 0.002599 3.470972e-04 \n",
"... ... ... ... \n",
"2017-11-16 21:00:00+00:00 171.100 0.029146 1.140948e-01 \n",
"2017-11-17 21:00:00+00:00 170.150 0.029141 1.125510e-01 \n",
"2017-11-20 21:00:00+00:00 169.980 0.029127 1.122745e-01 \n",
"2017-11-21 21:00:00+00:00 173.140 0.029202 1.174157e-01 \n",
"2017-11-22 21:00:00+00:00 174.960 0.029215 1.203786e-01 \n",
"2017-11-24 18:00:00+00:00 174.970 0.029200 1.203948e-01 \n",
"2017-11-27 21:00:00+00:00 174.090 0.029194 1.189603e-01 \n",
"2017-11-28 21:00:00+00:00 173.070 0.029191 1.172966e-01 \n",
"2017-11-29 21:00:00+00:00 169.480 0.029301 1.114376e-01 \n",
"2017-11-30 21:00:00+00:00 171.850 0.029336 1.153077e-01 \n",
"2017-12-01 21:00:00+00:00 171.050 0.029328 1.140004e-01 \n",
"2017-12-04 21:00:00+00:00 169.800 0.029330 1.119566e-01 \n",
"2017-12-05 21:00:00+00:00 169.640 0.029316 1.116948e-01 \n",
"2017-12-06 21:00:00+00:00 169.010 0.029305 1.106634e-01 \n",
"2017-12-07 21:00:00+00:00 169.452 0.029292 1.113873e-01 \n",
"2017-12-08 21:00:00+00:00 169.370 0.029277 1.112528e-01 \n",
"2017-12-11 21:00:00+00:00 172.670 0.029361 1.166647e-01 \n",
"2017-12-12 21:00:00+00:00 171.700 0.029356 1.150728e-01 \n",
"2017-12-13 21:00:00+00:00 172.270 0.029344 1.160087e-01 \n",
"2017-12-14 21:00:00+00:00 172.220 0.029329 1.159265e-01 \n",
"2017-12-15 21:00:00+00:00 173.870 0.029338 1.186390e-01 \n",
"2017-12-18 21:00:00+00:00 176.420 0.029380 1.228336e-01 \n",
"2017-12-19 21:00:00+00:00 174.540 0.029400 1.197391e-01 \n",
"2017-12-20 21:00:00+00:00 174.350 0.029386 1.194260e-01 \n",
"2017-12-21 21:00:00+00:00 175.010 0.029375 1.205136e-01 \n",
"2017-12-22 21:00:00+00:00 175.010 0.029360 1.205136e-01 \n",
"2017-12-26 21:00:00+00:00 170.570 0.029534 1.131875e-01 \n",
"2017-12-27 21:00:00+00:00 170.600 0.029520 1.132369e-01 \n",
"2017-12-28 21:00:00+00:00 171.080 0.029506 1.140298e-01 \n",
"2017-12-29 21:00:00+00:00 169.230 0.029526 1.109716e-01 \n",
"\n",
" alpha benchmark_period_return \\\n",
"2014-01-02 21:00:00+00:00 NaN -0.000678 \n",
"2014-01-03 21:00:00+00:00 NaN -0.001355 \n",
"2014-01-06 21:00:00+00:00 NaN -0.002031 \n",
"2014-01-07 21:00:00+00:00 NaN -0.002708 \n",
"2014-01-08 21:00:00+00:00 NaN -0.003383 \n",
"2014-01-09 21:00:00+00:00 NaN -0.004059 \n",
"2014-01-10 21:00:00+00:00 NaN -0.004734 \n",
"2014-01-13 21:00:00+00:00 NaN -0.005408 \n",
"2014-01-14 21:00:00+00:00 NaN -0.006082 \n",
"2014-01-15 21:00:00+00:00 NaN -0.006755 \n",
"2014-01-16 21:00:00+00:00 NaN -0.007428 \n",
"2014-01-17 21:00:00+00:00 NaN -0.008101 \n",
"2014-01-21 21:00:00+00:00 NaN -0.008773 \n",
"2014-01-22 21:00:00+00:00 NaN -0.009445 \n",
"2014-01-23 21:00:00+00:00 NaN -0.010116 \n",
"2014-01-24 21:00:00+00:00 NaN -0.010787 \n",
"2014-01-27 21:00:00+00:00 NaN -0.011457 \n",
"2014-01-28 21:00:00+00:00 NaN -0.012127 \n",
"2014-01-29 21:00:00+00:00 NaN -0.012796 \n",
"2014-01-30 21:00:00+00:00 NaN -0.013465 \n",
"2014-01-31 21:00:00+00:00 NaN -0.014134 \n",
"2014-02-03 21:00:00+00:00 NaN -0.014802 \n",
"2014-02-04 21:00:00+00:00 NaN -0.015469 \n",
"2014-02-05 21:00:00+00:00 NaN -0.016136 \n",
"2014-02-06 21:00:00+00:00 NaN -0.016803 \n",
"2014-02-07 21:00:00+00:00 NaN -0.017469 \n",
"2014-02-10 21:00:00+00:00 NaN -0.018135 \n",
"2014-02-11 21:00:00+00:00 NaN -0.018800 \n",
"2014-02-12 21:00:00+00:00 NaN -0.019465 \n",
"2014-02-13 21:00:00+00:00 NaN -0.020130 \n",
"... ... ... \n",
"2017-11-16 21:00:00+00:00 0.025302 0.068134 \n",
"2017-11-17 21:00:00+00:00 0.025019 0.064995 \n",
"2017-11-20 21:00:00+00:00 0.024864 0.066813 \n",
"2017-11-21 21:00:00+00:00 0.025799 0.073793 \n",
"2017-11-22 21:00:00+00:00 0.026505 0.072843 \n",
"2017-11-24 18:00:00+00:00 0.026396 0.075321 \n",
"2017-11-27 21:00:00+00:00 0.026051 0.074784 \n",
"2017-11-28 21:00:00+00:00 0.025273 0.085687 \n",
"2017-11-29 21:00:00+00:00 0.023894 0.085027 \n",
"2017-11-30 21:00:00+00:00 0.024445 0.094526 \n",
"2017-12-01 21:00:00+00:00 0.024189 0.092254 \n",
"2017-12-04 21:00:00+00:00 0.023729 0.090933 \n",
"2017-12-05 21:00:00+00:00 0.023777 0.087009 \n",
"2017-12-06 21:00:00+00:00 0.023504 0.087216 \n",
"2017-12-07 21:00:00+00:00 0.023533 0.090644 \n",
"2017-12-08 21:00:00+00:00 0.023280 0.096591 \n",
"2017-12-11 21:00:00+00:00 0.024401 0.099895 \n",
"2017-12-12 21:00:00+00:00 0.023943 0.101836 \n",
"2017-12-13 21:00:00+00:00 0.024141 0.101712 \n",
"2017-12-14 21:00:00+00:00 0.024248 0.097210 \n",
"2017-12-15 21:00:00+00:00 0.024731 0.100721 \n",
"2017-12-18 21:00:00+00:00 0.025431 0.107701 \n",
"2017-12-19 21:00:00+00:00 0.024829 0.103447 \n",
"2017-12-20 21:00:00+00:00 0.024751 0.102869 \n",
"2017-12-21 21:00:00+00:00 0.024899 0.105140 \n",
"2017-12-22 21:00:00+00:00 0.024884 0.104851 \n",
"2017-12-26 21:00:00+00:00 0.023217 0.103530 \n",
"2017-12-27 21:00:00+00:00 0.023187 0.104066 \n",
"2017-12-28 21:00:00+00:00 0.023270 0.106338 \n",
"2017-12-29 21:00:00+00:00 0.022677 0.102167 \n",
"\n",
" benchmark_volatility beta capital_used \\\n",
"2014-01-02 21:00:00+00:00 NaN NaN 0.000000 \n",
"2014-01-03 21:00:00+00:00 0.000000 NaN -5412.514900 \n",
"2014-01-06 21:00:00+00:00 0.000000 NaN -5442.029650 \n",
"2014-01-07 21:00:00+00:00 0.000000 NaN -5403.080185 \n",
"2014-01-08 21:00:00+00:00 0.000000 NaN -5437.327300 \n",
"2014-01-09 21:00:00+00:00 0.000000 NaN -5367.882595 \n",
"2014-01-10 21:00:00+00:00 0.000000 NaN -5332.074700 \n",
"2014-01-13 21:00:00+00:00 0.000000 NaN -5359.988650 \n",
"2014-01-14 21:00:00+00:00 0.000000 NaN -5466.641950 \n",
"2014-01-15 21:00:00+00:00 0.000000 NaN -5576.396800 \n",
"2014-01-16 21:00:00+00:00 0.000000 NaN -5545.281250 \n",
"2014-01-17 21:00:00+00:00 0.000000 NaN -5409.413350 \n",
"2014-01-21 21:00:00+00:00 0.000000 NaN -5493.455350 \n",
"2014-01-22 21:00:00+00:00 0.000000 NaN -5517.867550 \n",
"2014-01-23 21:00:00+00:00 0.000000 NaN -5564.590900 \n",
"2014-01-24 21:00:00+00:00 0.000000 NaN -5463.440350 \n",
"2014-01-27 21:00:00+00:00 0.000000 NaN -5507.762500 \n",
"2014-01-28 21:00:00+00:00 0.000000 NaN -5067.542500 \n",
"2014-01-29 21:00:00+00:00 0.000000 NaN -5010.013750 \n",
"2014-01-30 21:00:00+00:00 0.000000 NaN -5000.328910 \n",
"2014-01-31 21:00:00+00:00 0.000000 NaN -5008.513000 \n",
"2014-02-03 21:00:00+00:00 0.000000 NaN -5017.817650 \n",
"2014-02-04 21:00:00+00:00 0.000000 NaN -5090.453950 \n",
"2014-02-05 21:00:00+00:00 0.000000 NaN -5128.472950 \n",
"2014-02-06 21:00:00+00:00 0.000000 NaN -5127.672550 \n",
"2014-02-07 21:00:00+00:00 0.000000 NaN -5199.398395 \n",
"2014-02-10 21:00:00+00:00 0.000000 NaN -5292.554950 \n",
"2014-02-11 21:00:00+00:00 0.000000 NaN -5362.289800 \n",
"2014-02-12 21:00:00+00:00 0.000000 NaN -5361.889600 \n",
"2014-02-13 21:00:00+00:00 0.000000 NaN -5447.032150 \n",
"... ... ... ... \n",
"2017-11-16 21:00:00+00:00 0.110736 0.141713 -1711.865500 \n",
"2017-11-17 21:00:00+00:00 0.110690 0.141781 -1702.360750 \n",
"2017-11-20 21:00:00+00:00 0.110637 0.141761 -1700.659900 \n",
"2017-11-21 21:00:00+00:00 0.110628 0.142248 -1732.275700 \n",
"2017-11-22 21:00:00+00:00 0.110573 0.142193 -1750.484800 \n",
"2017-11-24 18:00:00+00:00 0.110522 0.142173 -1750.584850 \n",
"2017-11-27 21:00:00+00:00 0.110467 0.142190 -1741.780450 \n",
"2017-11-28 21:00:00+00:00 0.110527 0.141552 -1731.575350 \n",
"2017-11-29 21:00:00+00:00 0.110472 0.141631 -1695.657400 \n",
"2017-11-30 21:00:00+00:00 0.110502 0.142019 -1719.369250 \n",
"2017-12-01 21:00:00+00:00 0.110452 0.142064 -1711.365250 \n",
"2017-12-04 21:00:00+00:00 0.110398 0.142112 -1698.859000 \n",
"2017-12-05 21:00:00+00:00 0.110358 0.142098 -1697.258200 \n",
"2017-12-06 21:00:00+00:00 0.110302 0.142096 -1690.955050 \n",
"2017-12-07 21:00:00+00:00 0.110257 0.142104 -1695.377260 \n",
"2017-12-08 21:00:00+00:00 0.110235 0.141993 -1694.556850 \n",
"2017-12-11 21:00:00+00:00 0.110189 0.142256 -1727.573350 \n",
"2017-12-12 21:00:00+00:00 0.110136 0.142196 -1717.868500 \n",
"2017-12-13 21:00:00+00:00 0.110081 0.142192 -1723.571350 \n",
"2017-12-14 21:00:00+00:00 0.110046 0.142156 -1723.071100 \n",
"2017-12-15 21:00:00+00:00 0.110002 0.142277 -1739.579350 \n",
"2017-12-18 21:00:00+00:00 0.109991 0.142633 -1765.092100 \n",
"2017-12-19 21:00:00+00:00 0.109954 0.142824 -1746.282700 \n",
"2017-12-20 21:00:00+00:00 0.109899 0.142828 -1744.381750 \n",
"2017-12-21 21:00:00+00:00 0.109849 0.142852 -1750.985050 \n",
"2017-12-22 21:00:00+00:00 0.109794 0.142852 -1750.985050 \n",
"2017-12-26 21:00:00+00:00 0.109741 0.143030 -1706.562850 \n",
"2017-12-27 21:00:00+00:00 0.109687 0.143029 -1706.863000 \n",
"2017-12-28 21:00:00+00:00 0.109637 0.143042 -1711.665400 \n",
"2017-12-29 21:00:00+00:00 0.109599 0.143229 -1693.156150 \n",
"\n",
" ending_cash ending_exposure \\\n",
"2014-01-02 21:00:00+00:00 1.000000e+07 0.00 \n",
"2014-01-03 21:00:00+00:00 9.994587e+06 5409.80 \n",
"2014-01-06 21:00:00+00:00 9.989145e+06 10878.60 \n",
"2014-01-07 21:00:00+00:00 9.983742e+06 16201.11 \n",
"2014-01-08 21:00:00+00:00 9.978305e+06 21738.40 \n",
"2014-01-09 21:00:00+00:00 9.972937e+06 26825.95 \n",
"2014-01-10 21:00:00+00:00 9.967605e+06 31976.40 \n",
"2014-01-13 21:00:00+00:00 9.962245e+06 37501.10 \n",
"2014-01-14 21:00:00+00:00 9.956778e+06 43711.20 \n",
"2014-01-15 21:00:00+00:00 9.951202e+06 50162.40 \n",
"2014-01-16 21:00:00+00:00 9.945657e+06 55425.00 \n",
"2014-01-17 21:00:00+00:00 9.940247e+06 59473.70 \n",
"2014-01-21 21:00:00+00:00 9.934754e+06 65888.40 \n",
"2014-01-22 21:00:00+00:00 9.929236e+06 71696.30 \n",
"2014-01-23 21:00:00+00:00 9.923671e+06 77865.20 \n",
"2014-01-24 21:00:00+00:00 9.918208e+06 81910.50 \n",
"2014-01-27 21:00:00+00:00 9.912700e+06 88080.00 \n",
"2014-01-28 21:00:00+00:00 9.907633e+06 86105.00 \n",
"2014-01-29 21:00:00+00:00 9.902623e+06 90135.00 \n",
"2014-01-30 21:00:00+00:00 9.897622e+06 94958.58 \n",
"2014-01-31 21:00:00+00:00 9.892614e+06 100120.00 \n",
"2014-02-03 21:00:00+00:00 9.887596e+06 105321.30 \n",
"2014-02-04 21:00:00+00:00 9.882506e+06 111933.80 \n",
"2014-02-05 21:00:00+00:00 9.877377e+06 117895.70 \n",
"2014-02-06 21:00:00+00:00 9.872249e+06 123002.40 \n",
"2014-02-07 21:00:00+00:00 9.867050e+06 129919.75 \n",
"2014-02-10 21:00:00+00:00 9.861757e+06 137537.40 \n",
"2014-02-11 21:00:00+00:00 9.856395e+06 144709.20 \n",
"2014-02-12 21:00:00+00:00 9.851033e+06 150057.60 \n",
"2014-02-13 21:00:00+00:00 9.845586e+06 157884.70 \n",
"... ... ... \n",
"2017-11-16 21:00:00+00:00 8.360573e+06 2780375.00 \n",
"2017-11-17 21:00:00+00:00 8.358871e+06 2766639.00 \n",
"2017-11-20 21:00:00+00:00 8.357170e+06 2765574.60 \n",
"2017-11-21 21:00:00+00:00 8.355438e+06 2818719.20 \n",
"2017-11-22 21:00:00+00:00 8.353687e+06 2850098.40 \n",
"2017-11-24 18:00:00+00:00 8.351937e+06 2852011.00 \n",
"2017-11-27 21:00:00+00:00 8.350195e+06 2839407.90 \n",
"2017-11-28 21:00:00+00:00 8.348463e+06 2824502.40 \n",
"2017-11-29 21:00:00+00:00 8.346768e+06 2767608.40 \n",
"2017-11-30 21:00:00+00:00 8.345048e+06 2808029.00 \n",
"2017-12-01 21:00:00+00:00 8.343337e+06 2796667.50 \n",
"2017-12-04 21:00:00+00:00 8.341638e+06 2777928.00 \n",
"2017-12-05 21:00:00+00:00 8.339941e+06 2777006.80 \n",
"2017-12-06 21:00:00+00:00 8.338250e+06 2768383.80 \n",
"2017-12-07 21:00:00+00:00 8.336554e+06 2777318.28 \n",
"2017-12-08 21:00:00+00:00 8.334860e+06 2777668.00 \n",
"2017-12-11 21:00:00+00:00 8.333132e+06 2833514.70 \n",
"2017-12-12 21:00:00+00:00 8.331414e+06 2819314.00 \n",
"2017-12-13 21:00:00+00:00 8.329691e+06 2830396.10 \n",
"2017-12-14 21:00:00+00:00 8.327968e+06 2831296.80 \n",
"2017-12-15 21:00:00+00:00 8.326228e+06 2860161.50 \n",
"2017-12-18 21:00:00+00:00 8.324463e+06 2903873.20 \n",
"2017-12-19 21:00:00+00:00 8.322717e+06 2874673.80 \n",
"2017-12-20 21:00:00+00:00 8.320972e+06 2873288.00 \n",
"2017-12-21 21:00:00+00:00 8.319222e+06 2885914.90 \n",
"2017-12-22 21:00:00+00:00 8.317471e+06 2887665.00 \n",
"2017-12-26 21:00:00+00:00 8.315764e+06 2816110.70 \n",
"2017-12-27 21:00:00+00:00 8.314057e+06 2818312.00 \n",
"2017-12-28 21:00:00+00:00 8.312345e+06 2827952.40 \n",
"2017-12-29 21:00:00+00:00 8.310652e+06 2799064.20 \n",
"\n",
" ... short_exposure short_value \\\n",
"2014-01-02 21:00:00+00:00 ... 0.0 0.0 \n",
"2014-01-03 21:00:00+00:00 ... 0.0 0.0 \n",
"2014-01-06 21:00:00+00:00 ... 0.0 0.0 \n",
"2014-01-07 21:00:00+00:00 ... 0.0 0.0 \n",
"2014-01-08 21:00:00+00:00 ... 0.0 0.0 \n",
"2014-01-09 21:00:00+00:00 ... 0.0 0.0 \n",
"2014-01-10 21:00:00+00:00 ... 0.0 0.0 \n",
"2014-01-13 21:00:00+00:00 ... 0.0 0.0 \n",
"2014-01-14 21:00:00+00:00 ... 0.0 0.0 \n",
"2014-01-15 21:00:00+00:00 ... 0.0 0.0 \n",
"2014-01-16 21:00:00+00:00 ... 0.0 0.0 \n",
"2014-01-17 21:00:00+00:00 ... 0.0 0.0 \n",
"2014-01-21 21:00:00+00:00 ... 0.0 0.0 \n",
"2014-01-22 21:00:00+00:00 ... 0.0 0.0 \n",
"2014-01-23 21:00:00+00:00 ... 0.0 0.0 \n",
"2014-01-24 21:00:00+00:00 ... 0.0 0.0 \n",
"2014-01-27 21:00:00+00:00 ... 0.0 0.0 \n",
"2014-01-28 21:00:00+00:00 ... 0.0 0.0 \n",
"2014-01-29 21:00:00+00:00 ... 0.0 0.0 \n",
"2014-01-30 21:00:00+00:00 ... 0.0 0.0 \n",
"2014-01-31 21:00:00+00:00 ... 0.0 0.0 \n",
"2014-02-03 21:00:00+00:00 ... 0.0 0.0 \n",
"2014-02-04 21:00:00+00:00 ... 0.0 0.0 \n",
"2014-02-05 21:00:00+00:00 ... 0.0 0.0 \n",
"2014-02-06 21:00:00+00:00 ... 0.0 0.0 \n",
"2014-02-07 21:00:00+00:00 ... 0.0 0.0 \n",
"2014-02-10 21:00:00+00:00 ... 0.0 0.0 \n",
"2014-02-11 21:00:00+00:00 ... 0.0 0.0 \n",
"2014-02-12 21:00:00+00:00 ... 0.0 0.0 \n",
"2014-02-13 21:00:00+00:00 ... 0.0 0.0 \n",
"... ... ... ... \n",
"2017-11-16 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-11-17 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-11-20 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-11-21 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-11-22 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-11-24 18:00:00+00:00 ... 0.0 0.0 \n",
"2017-11-27 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-11-28 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-11-29 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-11-30 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-01 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-04 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-05 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-06 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-07 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-08 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-11 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-12 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-13 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-14 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-15 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-18 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-19 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-20 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-21 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-22 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-26 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-27 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-28 21:00:00+00:00 ... 0.0 0.0 \n",
"2017-12-29 21:00:00+00:00 ... 0.0 0.0 \n",
"\n",
" shorts_count sortino starting_cash \\\n",
"2014-01-02 21:00:00+00:00 0 NaN 1.000000e+07 \n",
"2014-01-03 21:00:00+00:00 0 -11.224972 1.000000e+07 \n",
"2014-01-06 21:00:00+00:00 0 81.208114 9.994587e+06 \n",
"2014-01-07 21:00:00+00:00 0 -5.564302 9.989145e+06 \n",
"2014-01-08 21:00:00+00:00 0 3.826244 9.983742e+06 \n",
"2014-01-09 21:00:00+00:00 0 -5.262989 9.978305e+06 \n",
"2014-01-10 21:00:00+00:00 0 -7.307726 9.972937e+06 \n",
"2014-01-13 21:00:00+00:00 0 -4.145330 9.967605e+06 \n",
"2014-01-14 21:00:00+00:00 0 7.540809 9.962245e+06 \n",
"2014-01-15 21:00:00+00:00 0 19.933310 9.956778e+06 \n",
"2014-01-16 21:00:00+00:00 0 11.637563 9.951202e+06 \n",
"2014-01-17 21:00:00+00:00 0 -0.892414 9.945657e+06 \n",
"2014-01-21 21:00:00+00:00 0 1.976167 9.940247e+06 \n",
"2014-01-22 21:00:00+00:00 0 2.763837 9.934754e+06 \n",
"2014-01-23 21:00:00+00:00 0 4.400301 9.929236e+06 \n",
"2014-01-24 21:00:00+00:00 0 0.234097 9.923671e+06 \n",
"2014-01-27 21:00:00+00:00 0 1.491595 9.918208e+06 \n",
"2014-01-28 21:00:00+00:00 0 -3.198560 9.912700e+06 \n",
"2014-01-29 21:00:00+00:00 0 -3.568986 9.907633e+06 \n",
"2014-01-30 21:00:00+00:00 0 -3.562557 9.902623e+06 \n",
"2014-01-31 21:00:00+00:00 0 -3.404990 9.897622e+06 \n",
"2014-02-03 21:00:00+00:00 0 -3.242636 9.892614e+06 \n",
"2014-02-04 21:00:00+00:00 0 -2.489323 9.887596e+06 \n",
"2014-02-05 21:00:00+00:00 0 -2.071367 9.882506e+06 \n",
"2014-02-06 21:00:00+00:00 0 -2.038520 9.877377e+06 \n",
"2014-02-07 21:00:00+00:00 0 -1.275056 9.872249e+06 \n",
"2014-02-10 21:00:00+00:00 0 -0.289997 9.867050e+06 \n",
"2014-02-11 21:00:00+00:00 0 0.449653 9.861757e+06 \n",
"2014-02-12 21:00:00+00:00 0 0.436453 9.856395e+06 \n",
"2014-02-13 21:00:00+00:00 0 1.362189 9.851033e+06 \n",
"... ... ... ... \n",
"2017-11-16 21:00:00+00:00 0 1.441294 8.362285e+06 \n",
"2017-11-17 21:00:00+00:00 0 1.421445 8.360573e+06 \n",
"2017-11-20 21:00:00+00:00 0 1.417430 8.358871e+06 \n",
"2017-11-21 21:00:00+00:00 0 1.477307 8.357170e+06 \n",
"2017-11-22 21:00:00+00:00 0 1.511300 8.355438e+06 \n",
"2017-11-24 18:00:00+00:00 0 1.510720 8.353687e+06 \n",
"2017-11-27 21:00:00+00:00 0 1.492374 8.351937e+06 \n",
"2017-11-28 21:00:00+00:00 0 1.471087 8.350195e+06 \n",
"2017-11-29 21:00:00+00:00 0 1.389166 8.348463e+06 \n",
"2017-11-30 21:00:00+00:00 0 1.433504 8.346768e+06 \n",
"2017-12-01 21:00:00+00:00 0 1.416986 8.345048e+06 \n",
"2017-12-04 21:00:00+00:00 0 1.391040 8.343337e+06 \n",
"2017-12-05 21:00:00+00:00 0 1.387275 8.341638e+06 \n",
"2017-12-06 21:00:00+00:00 0 1.374231 8.339941e+06 \n",
"2017-12-07 21:00:00+00:00 0 1.381932 8.338250e+06 \n",
"2017-12-08 21:00:00+00:00 0 1.379672 8.336554e+06 \n",
"2017-12-11 21:00:00+00:00 0 1.441636 8.334860e+06 \n",
"2017-12-12 21:00:00+00:00 0 1.421637 8.333132e+06 \n",
"2017-12-13 21:00:00+00:00 0 1.431703 8.331414e+06 \n",
"2017-12-14 21:00:00+00:00 0 1.430037 8.329691e+06 \n",
"2017-12-15 21:00:00+00:00 0 1.460510 8.327968e+06 \n",
"2017-12-18 21:00:00+00:00 0 1.507871 8.326228e+06 \n",
"2017-12-19 21:00:00+00:00 0 1.468156 8.324463e+06 \n",
"2017-12-20 21:00:00+00:00 0 1.463813 8.322717e+06 \n",
"2017-12-21 21:00:00+00:00 0 1.475493 8.320972e+06 \n",
"2017-12-22 21:00:00+00:00 0 1.474756 8.319222e+06 \n",
"2017-12-26 21:00:00+00:00 0 1.371694 8.317471e+06 \n",
"2017-12-27 21:00:00+00:00 0 1.371570 8.315764e+06 \n",
"2017-12-28 21:00:00+00:00 0 1.379845 8.314057e+06 \n",
"2017-12-29 21:00:00+00:00 0 1.341469 8.312345e+06 \n",
"\n",
" starting_exposure starting_value trading_days \\\n",
"2014-01-02 21:00:00+00:00 0.00 0.00 1 \n",
"2014-01-03 21:00:00+00:00 0.00 0.00 2 \n",
"2014-01-06 21:00:00+00:00 5409.80 5409.80 3 \n",
"2014-01-07 21:00:00+00:00 10878.60 10878.60 4 \n",
"2014-01-08 21:00:00+00:00 16201.11 16201.11 5 \n",
"2014-01-09 21:00:00+00:00 21738.40 21738.40 6 \n",
"2014-01-10 21:00:00+00:00 26825.95 26825.95 7 \n",
"2014-01-13 21:00:00+00:00 31976.40 31976.40 8 \n",
"2014-01-14 21:00:00+00:00 37501.10 37501.10 9 \n",
"2014-01-15 21:00:00+00:00 43711.20 43711.20 10 \n",
"2014-01-16 21:00:00+00:00 50162.40 50162.40 11 \n",
"2014-01-17 21:00:00+00:00 55425.00 55425.00 12 \n",
"2014-01-21 21:00:00+00:00 59473.70 59473.70 13 \n",
"2014-01-22 21:00:00+00:00 65888.40 65888.40 14 \n",
"2014-01-23 21:00:00+00:00 71696.30 71696.30 15 \n",
"2014-01-24 21:00:00+00:00 77865.20 77865.20 16 \n",
"2014-01-27 21:00:00+00:00 81910.50 81910.50 17 \n",
"2014-01-28 21:00:00+00:00 88080.00 88080.00 18 \n",
"2014-01-29 21:00:00+00:00 86105.00 86105.00 19 \n",
"2014-01-30 21:00:00+00:00 90135.00 90135.00 20 \n",
"2014-01-31 21:00:00+00:00 94958.58 94958.58 21 \n",
"2014-02-03 21:00:00+00:00 100120.00 100120.00 22 \n",
"2014-02-04 21:00:00+00:00 105321.30 105321.30 23 \n",
"2014-02-05 21:00:00+00:00 111933.80 111933.80 24 \n",
"2014-02-06 21:00:00+00:00 117895.70 117895.70 25 \n",
"2014-02-07 21:00:00+00:00 123002.40 123002.40 26 \n",
"2014-02-10 21:00:00+00:00 129919.75 129919.75 27 \n",
"2014-02-11 21:00:00+00:00 137537.40 137537.40 28 \n",
"2014-02-12 21:00:00+00:00 144709.20 144709.20 29 \n",
"2014-02-13 21:00:00+00:00 150057.60 150057.60 30 \n",
"... ... ... ... \n",
"2017-11-16 21:00:00+00:00 2745859.20 2745859.20 978 \n",
"2017-11-17 21:00:00+00:00 2780375.00 2780375.00 979 \n",
"2017-11-20 21:00:00+00:00 2766639.00 2766639.00 980 \n",
"2017-11-21 21:00:00+00:00 2765574.60 2765574.60 981 \n",
"2017-11-22 21:00:00+00:00 2818719.20 2818719.20 982 \n",
"2017-11-24 18:00:00+00:00 2850098.40 2850098.40 983 \n",
"2017-11-27 21:00:00+00:00 2852011.00 2852011.00 984 \n",
"2017-11-28 21:00:00+00:00 2839407.90 2839407.90 985 \n",
"2017-11-29 21:00:00+00:00 2824502.40 2824502.40 986 \n",
"2017-11-30 21:00:00+00:00 2767608.40 2767608.40 987 \n",
"2017-12-01 21:00:00+00:00 2808029.00 2808029.00 988 \n",
"2017-12-04 21:00:00+00:00 2796667.50 2796667.50 989 \n",
"2017-12-05 21:00:00+00:00 2777928.00 2777928.00 990 \n",
"2017-12-06 21:00:00+00:00 2777006.80 2777006.80 991 \n",
"2017-12-07 21:00:00+00:00 2768383.80 2768383.80 992 \n",
"2017-12-08 21:00:00+00:00 2777318.28 2777318.28 993 \n",
"2017-12-11 21:00:00+00:00 2777668.00 2777668.00 994 \n",
"2017-12-12 21:00:00+00:00 2833514.70 2833514.70 995 \n",
"2017-12-13 21:00:00+00:00 2819314.00 2819314.00 996 \n",
"2017-12-14 21:00:00+00:00 2830396.10 2830396.10 997 \n",
"2017-12-15 21:00:00+00:00 2831296.80 2831296.80 998 \n",
"2017-12-18 21:00:00+00:00 2860161.50 2860161.50 999 \n",
"2017-12-19 21:00:00+00:00 2903873.20 2903873.20 1000 \n",
"2017-12-20 21:00:00+00:00 2874673.80 2874673.80 1001 \n",
"2017-12-21 21:00:00+00:00 2873288.00 2873288.00 1002 \n",
"2017-12-22 21:00:00+00:00 2885914.90 2885914.90 1003 \n",
"2017-12-26 21:00:00+00:00 2887665.00 2887665.00 1004 \n",
"2017-12-27 21:00:00+00:00 2816110.70 2816110.70 1005 \n",
"2017-12-28 21:00:00+00:00 2818312.00 2818312.00 1006 \n",
"2017-12-29 21:00:00+00:00 2827952.40 2827952.40 1007 \n",
"\n",
" transactions \\\n",
"2014-01-02 21:00:00+00:00 [] \n",
"2014-01-03 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 5... \n",
"2014-01-06 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 5... \n",
"2014-01-07 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 5... \n",
"2014-01-08 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 5... \n",
"2014-01-09 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 5... \n",
"2014-01-10 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 5... \n",
"2014-01-13 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 5... \n",
"2014-01-14 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 5... \n",
"2014-01-15 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 5... \n",
"2014-01-16 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 5... \n",
"2014-01-17 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 5... \n",
"2014-01-21 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 5... \n",
"2014-01-22 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 5... \n",
"2014-01-23 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 5... \n",
"2014-01-24 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 5... \n",
"2014-01-27 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 5... \n",
"2014-01-28 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 5... \n",
"2014-01-29 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 5... \n",
"2014-01-30 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 5... \n",
"2014-01-31 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 5... \n",
"2014-02-03 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 5... \n",
"2014-02-04 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 5... \n",
"2014-02-05 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 5... \n",
"2014-02-06 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 5... \n",
"2014-02-07 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 5... \n",
"2014-02-10 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 5... \n",
"2014-02-11 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 5... \n",
"2014-02-12 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 5... \n",
"2014-02-13 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 5... \n",
"... ... \n",
"2017-11-16 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-11-17 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-11-20 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-11-21 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-11-22 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-11-24 18:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-11-27 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-11-28 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-11-29 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-11-30 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-01 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-04 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-05 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-06 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-07 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-08 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-11 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-12 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-13 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-14 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-15 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-18 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-19 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-20 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-21 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-22 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-26 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-27 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-28 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"2017-12-29 21:00:00+00:00 [{'amount': 10, 'commission': None, 'price': 1... \n",
"\n",
" treasury_period_return \n",
"2014-01-02 21:00:00+00:00 0.0 \n",
"2014-01-03 21:00:00+00:00 0.0 \n",
"2014-01-06 21:00:00+00:00 0.0 \n",
"2014-01-07 21:00:00+00:00 0.0 \n",
"2014-01-08 21:00:00+00:00 0.0 \n",
"2014-01-09 21:00:00+00:00 0.0 \n",
"2014-01-10 21:00:00+00:00 0.0 \n",
"2014-01-13 21:00:00+00:00 0.0 \n",
"2014-01-14 21:00:00+00:00 0.0 \n",
"2014-01-15 21:00:00+00:00 0.0 \n",
"2014-01-16 21:00:00+00:00 0.0 \n",
"2014-01-17 21:00:00+00:00 0.0 \n",
"2014-01-21 21:00:00+00:00 0.0 \n",
"2014-01-22 21:00:00+00:00 0.0 \n",
"2014-01-23 21:00:00+00:00 0.0 \n",
"2014-01-24 21:00:00+00:00 0.0 \n",
"2014-01-27 21:00:00+00:00 0.0 \n",
"2014-01-28 21:00:00+00:00 0.0 \n",
"2014-01-29 21:00:00+00:00 0.0 \n",
"2014-01-30 21:00:00+00:00 0.0 \n",
"2014-01-31 21:00:00+00:00 0.0 \n",
"2014-02-03 21:00:00+00:00 0.0 \n",
"2014-02-04 21:00:00+00:00 0.0 \n",
"2014-02-05 21:00:00+00:00 0.0 \n",
"2014-02-06 21:00:00+00:00 0.0 \n",
"2014-02-07 21:00:00+00:00 0.0 \n",
"2014-02-10 21:00:00+00:00 0.0 \n",
"2014-02-11 21:00:00+00:00 0.0 \n",
"2014-02-12 21:00:00+00:00 0.0 \n",
"2014-02-13 21:00:00+00:00 0.0 \n",
"... ... \n",
"2017-11-16 21:00:00+00:00 0.0 \n",
"2017-11-17 21:00:00+00:00 0.0 \n",
"2017-11-20 21:00:00+00:00 0.0 \n",
"2017-11-21 21:00:00+00:00 0.0 \n",
"2017-11-22 21:00:00+00:00 0.0 \n",
"2017-11-24 18:00:00+00:00 0.0 \n",
"2017-11-27 21:00:00+00:00 0.0 \n",
"2017-11-28 21:00:00+00:00 0.0 \n",
"2017-11-29 21:00:00+00:00 0.0 \n",
"2017-11-30 21:00:00+00:00 0.0 \n",
"2017-12-01 21:00:00+00:00 0.0 \n",
"2017-12-04 21:00:00+00:00 0.0 \n",
"2017-12-05 21:00:00+00:00 0.0 \n",
"2017-12-06 21:00:00+00:00 0.0 \n",
"2017-12-07 21:00:00+00:00 0.0 \n",
"2017-12-08 21:00:00+00:00 0.0 \n",
"2017-12-11 21:00:00+00:00 0.0 \n",
"2017-12-12 21:00:00+00:00 0.0 \n",
"2017-12-13 21:00:00+00:00 0.0 \n",
"2017-12-14 21:00:00+00:00 0.0 \n",
"2017-12-15 21:00:00+00:00 0.0 \n",
"2017-12-18 21:00:00+00:00 0.0 \n",
"2017-12-19 21:00:00+00:00 0.0 \n",
"2017-12-20 21:00:00+00:00 0.0 \n",
"2017-12-21 21:00:00+00:00 0.0 \n",
"2017-12-22 21:00:00+00:00 0.0 \n",
"2017-12-26 21:00:00+00:00 0.0 \n",
"2017-12-27 21:00:00+00:00 0.0 \n",
"2017-12-28 21:00:00+00:00 0.0 \n",
"2017-12-29 21:00:00+00:00 0.0 \n",
"\n",
"[1007 rows x 38 columns]"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"%%zipline --start 2014-1-1 --end 2018-1-1\n",
"from zipline.api import order, record, symbol\n",
"import matplotlib.pyplot as plt\n",
"\n",
"def initialize(context):\n",
" pass\n",
"\n",
"def handle_data(context, data):\n",
" order(symbol('AAPL'), 10)\n",
" record(AAPL=data.current(symbol('AAPL'), 'price'))\n",
" \n",
"\n",
"def analyze(context, perf):\n",
" fig = plt.figure()\n",
"\n",
" ax1 = fig.add_subplot(111)\n",
" perf['AAPL'].plot(ax=ax1)\n",
"\n",
" plt.legend(loc=0)\n",
" plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"scrolled": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/mcw/.pyenv/versions/3.5.8/envs/zipline/lib/python3.5/site-packages/empyrical/stats.py:711: RuntimeWarning: invalid value encountered in true_divide\n",
" out=out,\n",
"/Users/mcw/.pyenv/versions/3.5.8/envs/zipline/lib/python3.5/site-packages/empyrical/stats.py:797: RuntimeWarning: invalid value encountered in true_divide\n",
" np.divide(average_annual_return, annualized_downside_risk, out=out)\n"
]
},
{
"data": {
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" } else if (typeof(MozWebSocket) !== 'undefined') {\n",
" return MozWebSocket;\n",
" } else {\n",
" alert('Your browser does not have WebSocket support.' +\n",
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" 'Firefox 4 and 5 are also supported but you ' +\n",
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" var titletext = $(\n",
" '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
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"\n",
" canvas_div.keydown('key_press', canvas_keyboard_event);\n",
" canvas_div.keyup('key_release', canvas_keyboard_event);\n",
" this.canvas_div = canvas_div\n",
" this._canvas_extra_style(canvas_div)\n",
" this.root.append(canvas_div);\n",
"\n",
" var canvas = $('<canvas/>');\n",
" canvas.addClass('mpl-canvas');\n",
" canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
"\n",
" this.canvas = canvas[0];\n",
" this.context = canvas[0].getContext(\"2d\");\n",
"\n",
" var backingStore = this.context.backingStorePixelRatio ||\n",
"\tthis.context.webkitBackingStorePixelRatio ||\n",
"\tthis.context.mozBackingStorePixelRatio ||\n",
"\tthis.context.msBackingStorePixelRatio ||\n",
"\tthis.context.oBackingStorePixelRatio ||\n",
"\tthis.context.backingStorePixelRatio || 1;\n",
"\n",
" mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
"\n",
" var rubberband = $('<canvas/>');\n",
" rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
"\n",
" var pass_mouse_events = true;\n",
"\n",
" canvas_div.resizable({\n",
" start: function(event, ui) {\n",
" pass_mouse_events = false;\n",
" },\n",
" resize: function(event, ui) {\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" stop: function(event, ui) {\n",
" pass_mouse_events = true;\n",
" fig.request_resize(ui.size.width, ui.size.height);\n",
" },\n",
" });\n",
"\n",
" function mouse_event_fn(event) {\n",
" if (pass_mouse_events)\n",
" return fig.mouse_event(event, event['data']);\n",
" }\n",
"\n",
" rubberband.mousedown('button_press', mouse_event_fn);\n",
" rubberband.mouseup('button_release', mouse_event_fn);\n",
" // Throttle sequential mouse events to 1 every 20ms.\n",
" rubberband.mousemove('motion_notify', mouse_event_fn);\n",
"\n",
" rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
" rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
"\n",
" canvas_div.on(\"wheel\", function (event) {\n",
" event = event.originalEvent;\n",
" event['data'] = 'scroll'\n",
" if (event.deltaY < 0) {\n",
" event.step = 1;\n",
" } else {\n",
" event.step = -1;\n",
" }\n",
" mouse_event_fn(event);\n",
" });\n",
"\n",
" canvas_div.append(canvas);\n",
" canvas_div.append(rubberband);\n",
"\n",
" this.rubberband = rubberband;\n",
" this.rubberband_canvas = rubberband[0];\n",
" this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
" this.rubberband_context.strokeStyle = \"#000000\";\n",
"\n",
" this._resize_canvas = function(width, height) {\n",
" // Keep the size of the canvas, canvas container, and rubber band\n",
" // canvas in synch.\n",
" canvas_div.css('width', width)\n",
" canvas_div.css('height', height)\n",
"\n",
" canvas.attr('width', width * mpl.ratio);\n",
" canvas.attr('height', height * mpl.ratio);\n",
" canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
"\n",
" rubberband.attr('width', width);\n",
" rubberband.attr('height', height);\n",
" }\n",
"\n",
" // Set the figure to an initial 600x600px, this will subsequently be updated\n",
" // upon first draw.\n",
" this._resize_canvas(600, 600);\n",
"\n",
" // Disable right mouse context menu.\n",
" $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
" return false;\n",
" });\n",
"\n",
" function set_focus () {\n",
" canvas.focus();\n",
" canvas_div.focus();\n",
" }\n",
"\n",
" window.setTimeout(set_focus, 100);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items) {\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) {\n",
" // put a spacer in here.\n",
" continue;\n",
" }\n",
" var button = $('<button/>');\n",
" button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
" 'ui-button-icon-only');\n",
" button.attr('role', 'button');\n",
" button.attr('aria-disabled', 'false');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
"\n",
" var icon_img = $('<span/>');\n",
" icon_img.addClass('ui-button-icon-primary ui-icon');\n",
" icon_img.addClass(image);\n",
" icon_img.addClass('ui-corner-all');\n",
"\n",
" var tooltip_span = $('<span/>');\n",
" tooltip_span.addClass('ui-button-text');\n",
" tooltip_span.html(tooltip);\n",
"\n",
" button.append(icon_img);\n",
" button.append(tooltip_span);\n",
"\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" var fmt_picker_span = $('<span/>');\n",
"\n",
" var fmt_picker = $('<select/>');\n",
" fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
" fmt_picker_span.append(fmt_picker);\n",
" nav_element.append(fmt_picker_span);\n",
" this.format_dropdown = fmt_picker[0];\n",
"\n",
" for (var ind in mpl.extensions) {\n",
" var fmt = mpl.extensions[ind];\n",
" var option = $(\n",
" '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
" fmt_picker.append(option)\n",
" }\n",
"\n",
" // Add hover states to the ui-buttons\n",
" $( \".ui-button\" ).hover(\n",
" function() { $(this).addClass(\"ui-state-hover\");},\n",
" function() { $(this).removeClass(\"ui-state-hover\");}\n",
" );\n",
"\n",
" var status_bar = $('<span class=\"mpl-message\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"}\n",
"\n",
"mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
" // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
" // which will in turn request a refresh of the image.\n",
" this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
"}\n",
"\n",
"mpl.figure.prototype.send_message = function(type, properties) {\n",
" properties['type'] = type;\n",
" properties['figure_id'] = this.id;\n",
" this.ws.send(JSON.stringify(properties));\n",
"}\n",
"\n",
"mpl.figure.prototype.send_draw_message = function() {\n",
" if (!this.waiting) {\n",
" this.waiting = true;\n",
" this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
" }\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" var format_dropdown = fig.format_dropdown;\n",
" var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
" fig.ondownload(fig, format);\n",
"}\n",
"\n",
"\n",
"mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
" var size = msg['size'];\n",
" if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
" fig._resize_canvas(size[0], size[1]);\n",
" fig.send_message(\"refresh\", {});\n",
" };\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
" var x0 = msg['x0'] / mpl.ratio;\n",
" var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
" var x1 = msg['x1'] / mpl.ratio;\n",
" var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
" x0 = Math.floor(x0) + 0.5;\n",
" y0 = Math.floor(y0) + 0.5;\n",
" x1 = Math.floor(x1) + 0.5;\n",
" y1 = Math.floor(y1) + 0.5;\n",
" var min_x = Math.min(x0, x1);\n",
" var min_y = Math.min(y0, y1);\n",
" var width = Math.abs(x1 - x0);\n",
" var height = Math.abs(y1 - y0);\n",
"\n",
" fig.rubberband_context.clearRect(\n",
" 0, 0, fig.canvas.width, fig.canvas.height);\n",
"\n",
" fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
" // Updates the figure title.\n",
" fig.header.textContent = msg['label'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
" var cursor = msg['cursor'];\n",
" switch(cursor)\n",
" {\n",
" case 0:\n",
" cursor = 'pointer';\n",
" break;\n",
" case 1:\n",
" cursor = 'default';\n",
" break;\n",
" case 2:\n",
" cursor = 'crosshair';\n",
" break;\n",
" case 3:\n",
" cursor = 'move';\n",
" break;\n",
" }\n",
" fig.rubberband_canvas.style.cursor = cursor;\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_message = function(fig, msg) {\n",
" fig.message.textContent = msg['message'];\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
" // Request the server to send over a new figure.\n",
" fig.send_draw_message();\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
" fig.image_mode = msg['mode'];\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Called whenever the canvas gets updated.\n",
" this.send_message(\"ack\", {});\n",
"}\n",
"\n",
"// A function to construct a web socket function for onmessage handling.\n",
"// Called in the figure constructor.\n",
"mpl.figure.prototype._make_on_message_function = function(fig) {\n",
" return function socket_on_message(evt) {\n",
" if (evt.data instanceof Blob) {\n",
" /* FIXME: We get \"Resource interpreted as Image but\n",
" * transferred with MIME type text/plain:\" errors on\n",
" * Chrome. But how to set the MIME type? It doesn't seem\n",
" * to be part of the websocket stream */\n",
" evt.data.type = \"image/png\";\n",
"\n",
" /* Free the memory for the previous frames */\n",
" if (fig.imageObj.src) {\n",
" (window.URL || window.webkitURL).revokeObjectURL(\n",
" fig.imageObj.src);\n",
" }\n",
"\n",
" fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
" evt.data);\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
" else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
" fig.imageObj.src = evt.data;\n",
" fig.updated_canvas_event();\n",
" fig.waiting = false;\n",
" return;\n",
" }\n",
"\n",
" var msg = JSON.parse(evt.data);\n",
" var msg_type = msg['type'];\n",
"\n",
" // Call the \"handle_{type}\" callback, which takes\n",
" // the figure and JSON message as its only arguments.\n",
" try {\n",
" var callback = fig[\"handle_\" + msg_type];\n",
" } catch (e) {\n",
" console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
" return;\n",
" }\n",
"\n",
" if (callback) {\n",
" try {\n",
" // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
" callback(fig, msg);\n",
" } catch (e) {\n",
" console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
" }\n",
" }\n",
" };\n",
"}\n",
"\n",
"// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
"mpl.findpos = function(e) {\n",
" //this section is from http://www.quirksmode.org/js/events_properties.html\n",
" var targ;\n",
" if (!e)\n",
" e = window.event;\n",
" if (e.target)\n",
" targ = e.target;\n",
" else if (e.srcElement)\n",
" targ = e.srcElement;\n",
" if (targ.nodeType == 3) // defeat Safari bug\n",
" targ = targ.parentNode;\n",
"\n",
" // jQuery normalizes the pageX and pageY\n",
" // pageX,Y are the mouse positions relative to the document\n",
" // offset() returns the position of the element relative to the document\n",
" var x = e.pageX - $(targ).offset().left;\n",
" var y = e.pageY - $(targ).offset().top;\n",
"\n",
" return {\"x\": x, \"y\": y};\n",
"};\n",
"\n",
"/*\n",
" * return a copy of an object with only non-object keys\n",
" * we need this to avoid circular references\n",
" * http://stackoverflow.com/a/24161582/3208463\n",
" */\n",
"function simpleKeys (original) {\n",
" return Object.keys(original).reduce(function (obj, key) {\n",
" if (typeof original[key] !== 'object')\n",
" obj[key] = original[key]\n",
" return obj;\n",
" }, {});\n",
"}\n",
"\n",
"mpl.figure.prototype.mouse_event = function(event, name) {\n",
" var canvas_pos = mpl.findpos(event)\n",
"\n",
" if (name === 'button_press')\n",
" {\n",
" this.canvas.focus();\n",
" this.canvas_div.focus();\n",
" }\n",
"\n",
" var x = canvas_pos.x * mpl.ratio;\n",
" var y = canvas_pos.y * mpl.ratio;\n",
"\n",
" this.send_message(name, {x: x, y: y, button: event.button,\n",
" step: event.step,\n",
" guiEvent: simpleKeys(event)});\n",
"\n",
" /* This prevents the web browser from automatically changing to\n",
" * the text insertion cursor when the button is pressed. We want\n",
" * to control all of the cursor setting manually through the\n",
" * 'cursor' event from matplotlib */\n",
" event.preventDefault();\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" // Handle any extra behaviour associated with a key event\n",
"}\n",
"\n",
"mpl.figure.prototype.key_event = function(event, name) {\n",
"\n",
" // Prevent repeat events\n",
" if (name == 'key_press')\n",
" {\n",
" if (event.which === this._key)\n",
" return;\n",
" else\n",
" this._key = event.which;\n",
" }\n",
" if (name == 'key_release')\n",
" this._key = null;\n",
"\n",
" var value = '';\n",
" if (event.ctrlKey && event.which != 17)\n",
" value += \"ctrl+\";\n",
" if (event.altKey && event.which != 18)\n",
" value += \"alt+\";\n",
" if (event.shiftKey && event.which != 16)\n",
" value += \"shift+\";\n",
"\n",
" value += 'k';\n",
" value += event.which.toString();\n",
"\n",
" this._key_event_extra(event, name);\n",
"\n",
" this.send_message(name, {key: value,\n",
" guiEvent: simpleKeys(event)});\n",
" return false;\n",
"}\n",
"\n",
"mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
" if (name == 'download') {\n",
" this.handle_save(this, null);\n",
" } else {\n",
" this.send_message(\"toolbar_button\", {name: name});\n",
" }\n",
"};\n",
"\n",
"mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
" this.message.textContent = tooltip;\n",
"};\n",
"mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
"\n",
"mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
"\n",
"mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
" // Create a \"websocket\"-like object which calls the given IPython comm\n",
" // object with the appropriate methods. Currently this is a non binary\n",
" // socket, so there is still some room for performance tuning.\n",
" var ws = {};\n",
"\n",
" ws.close = function() {\n",
" comm.close()\n",
" };\n",
" ws.send = function(m) {\n",
" //console.log('sending', m);\n",
" comm.send(m);\n",
" };\n",
" // Register the callback with on_msg.\n",
" comm.on_msg(function(msg) {\n",
" //console.log('receiving', msg['content']['data'], msg);\n",
" // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
" ws.onmessage(msg['content']['data'])\n",
" });\n",
" return ws;\n",
"}\n",
"\n",
"mpl.mpl_figure_comm = function(comm, msg) {\n",
" // This is the function which gets called when the mpl process\n",
" // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
"\n",
" var id = msg.content.data.id;\n",
" // Get hold of the div created by the display call when the Comm\n",
" // socket was opened in Python.\n",
" var element = $(\"#\" + id);\n",
" var ws_proxy = comm_websocket_adapter(comm)\n",
"\n",
" function ondownload(figure, format) {\n",
" window.open(figure.imageObj.src);\n",
" }\n",
"\n",
" var fig = new mpl.figure(id, ws_proxy,\n",
" ondownload,\n",
" element.get(0));\n",
"\n",
" // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
" // web socket which is closed, not our websocket->open comm proxy.\n",
" ws_proxy.onopen();\n",
"\n",
" fig.parent_element = element.get(0);\n",
" fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
" if (!fig.cell_info) {\n",
" console.error(\"Failed to find cell for figure\", id, fig);\n",
" return;\n",
" }\n",
"\n",
" var output_index = fig.cell_info[2]\n",
" var cell = fig.cell_info[0];\n",
"\n",
"};\n",
"\n",
"mpl.figure.prototype.handle_close = function(fig, msg) {\n",
" var width = fig.canvas.width/mpl.ratio\n",
" fig.root.unbind('remove')\n",
"\n",
" // Update the output cell to use the data from the current canvas.\n",
" fig.push_to_output();\n",
" var dataURL = fig.canvas.toDataURL();\n",
" // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
" // the notebook keyboard shortcuts fail.\n",
" IPython.keyboard_manager.enable()\n",
" $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
" fig.close_ws(fig, msg);\n",
"}\n",
"\n",
"mpl.figure.prototype.close_ws = function(fig, msg){\n",
" fig.send_message('closing', msg);\n",
" // fig.ws.close()\n",
"}\n",
"\n",
"mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
" // Turn the data on the canvas into data in the output cell.\n",
" var width = this.canvas.width/mpl.ratio\n",
" var dataURL = this.canvas.toDataURL();\n",
" this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
"}\n",
"\n",
"mpl.figure.prototype.updated_canvas_event = function() {\n",
" // Tell IPython that the notebook contents must change.\n",
" IPython.notebook.set_dirty(true);\n",
" this.send_message(\"ack\", {});\n",
" var fig = this;\n",
" // Wait a second, then push the new image to the DOM so\n",
" // that it is saved nicely (might be nice to debounce this).\n",
" setTimeout(function () { fig.push_to_output() }, 1000);\n",
"}\n",
"\n",
"mpl.figure.prototype._init_toolbar = function() {\n",
" var fig = this;\n",
"\n",
" var nav_element = $('<div/>')\n",
" nav_element.attr('style', 'width: 100%');\n",
" this.root.append(nav_element);\n",
"\n",
" // Define a callback function for later on.\n",
" function toolbar_event(event) {\n",
" return fig.toolbar_button_onclick(event['data']);\n",
" }\n",
" function toolbar_mouse_event(event) {\n",
" return fig.toolbar_button_onmouseover(event['data']);\n",
" }\n",
"\n",
" for(var toolbar_ind in mpl.toolbar_items){\n",
" var name = mpl.toolbar_items[toolbar_ind][0];\n",
" var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
" var image = mpl.toolbar_items[toolbar_ind][2];\n",
" var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
"\n",
" if (!name) { continue; };\n",
"\n",
" var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
" button.click(method_name, toolbar_event);\n",
" button.mouseover(tooltip, toolbar_mouse_event);\n",
" nav_element.append(button);\n",
" }\n",
"\n",
" // Add the status bar.\n",
" var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
" nav_element.append(status_bar);\n",
" this.message = status_bar[0];\n",
"\n",
" // Add the close button to the window.\n",
" var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
" var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
" button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
" button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
" buttongrp.append(button);\n",
" var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
" titlebar.prepend(buttongrp);\n",
"}\n",
"\n",
"mpl.figure.prototype._root_extra_style = function(el){\n",
" var fig = this\n",
" el.on(\"remove\", function(){\n",
"\tfig.close_ws(fig, {});\n",
" });\n",
"}\n",
"\n",
"mpl.figure.prototype._canvas_extra_style = function(el){\n",
" // this is important to make the div 'focusable\n",
" el.attr('tabindex', 0)\n",
" // reach out to IPython and tell the keyboard manager to turn it's self\n",
" // off when our div gets focus\n",
"\n",
" // location in version 3\n",
" if (IPython.notebook.keyboard_manager) {\n",
" IPython.notebook.keyboard_manager.register_events(el);\n",
" }\n",
" else {\n",
" // location in version 2\n",
" IPython.keyboard_manager.register_events(el);\n",
" }\n",
"\n",
"}\n",
"\n",
"mpl.figure.prototype._key_event_extra = function(event, name) {\n",
" var manager = IPython.notebook.keyboard_manager;\n",
" if (!manager)\n",
" manager = IPython.keyboard_manager;\n",
"\n",
" // Check for shift+enter\n",
" if (event.shiftKey && event.which == 13) {\n",
" this.canvas_div.blur();\n",
" event.shiftKey = false;\n",
" // Send a \"J\" for go to next cell\n",
" event.which = 74;\n",
" event.keyCode = 74;\n",
" manager.command_mode();\n",
" manager.handle_keydown(event);\n",
" }\n",
"}\n",
"\n",
"mpl.figure.prototype.handle_save = function(fig, msg) {\n",
" fig.ondownload(fig, null);\n",
"}\n",
"\n",
"\n",
"mpl.find_output_cell = function(html_output) {\n",
" // Return the cell and output element which can be found *uniquely* in the notebook.\n",
" // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
" // IPython event is triggered only after the cells have been serialised, which for\n",
" // our purposes (turning an active figure into a static one), is too late.\n",
" var cells = IPython.notebook.get_cells();\n",
" var ncells = cells.length;\n",
" for (var i=0; i<ncells; i++) {\n",
" var cell = cells[i];\n",
" if (cell.cell_type === 'code'){\n",
" for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
" var data = cell.output_area.outputs[j];\n",
" if (data.data) {\n",
" // IPython >= 3 moved mimebundle to data attribute of output\n",
" data = data.data;\n",
" }\n",
" if (data['text/html'] == html_output) {\n",
" return [cell, data, j];\n",
" }\n",
" }\n",
" }\n",
" }\n",
"}\n",
"\n",
"// Register the function which deals with the matplotlib target/channel.\n",
"// The kernel may be null if the page has been refreshed.\n",
"if (IPython.notebook.kernel != null) {\n",
" IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
"}\n"
],
"text/plain": [
"<IPython.core.display.Javascript object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
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f5MnT5a+fftal5TbVoOl1srCutKwtTJxud2AihBAAAEEEEAAAQQQQAABBKqFwF+NYN5bP9vn4NOGf3LbSdKrVb2AZ3j2qxXyyvS1tvxGKfEy9e5+klor3pYfzsETU5ZJqEU/omtEyeyHzpRGKQnhVOe5Mvz+7blXUiUNogdgCdh18YylS5fKY489Jscff7ykpKRIQkKC6CIfOuT3119/DRr809tor7zXX39dpk6das4JqAuD6HBh3eqcf//73/9k3LhxIYN/Wk9qaqrMnj3b7Hmobapfv77ZjrZt25oBRm1HccE/rUcDe4sXLzaHLnfp0kVq1aplfrp27WrmLVmypEKCf3pvEgIIIIAAAggggAACCCCAAALr0jNdg38q8/VS9843v6zbHQC340CO3PPBAsl368oXUNqe8fPawPr8S2id8zdU7qIk/vdnH4HyEKAHYHkoUkeJBfgLRInJuAABBBBAAAEEEEAAAQQQiDiBfxq9+cY4evP5P+QTl3SWISe19s+Svk9/Jxrwc0t3ntFO7j+3o9sp17y9B3Ol55PfGnP9uZ72Zd52+jHy4HmdfMfVaYffv6vT26q4tla7HoA6DPfqq68W7bHWvXt3c4GKWbNmVZwQNSOAAAIIIIAAAggggAACCCCAQLkLaM+6T3/bGrLev36+VL5aUrQgSG5egezMcA/+aUUvTVsjCzaF31tvzvrdxQb/tN4lW/frhoRAtRXwTADw22+/leuvv16GDRsmBw8GLr+twjo89vTTTxddoXbZsmWyaNEiee+99+S0006T559/vtq+BBqOAAIIIIAAAggggAACCCCAwNEm8NOaXZJ2INv22Nf0aWE71p55//pmpW813rT92cUG7D76dYutjlAHxQ3/ta5duu2Arw1WHlsEqpOAZwKAb731lrz77ruyZ88eqVmzZoDh2rVr5c477zRX4Y2NjZWzzz5bzj//fElMTDT/EY4cOVJ0JVwSAggggAACCCCAAAIIIIAAAgh4X+Cj+ZttjezcNEWeGdRN7j27vS1fV/g9ZKz8q2nrvizbuVrxMaLDfv3T75v2+R+G3NfAnn+6/5wO8t8hvaR/hwb+2bLHGCq83Qg+khCorgKeCQBOnz7dNLzqqqtcLV944QXJzc01V7idOXOmfPPNN+ZiGrrghS6KoYsZv/zyy67XkokAAggggAACCCCAAAIIIIAAAt4R2H/osHyzzL7IxxW9mpsNHHFqm4CGagBOkzMA2KxOovRrn2orv3JHhmT9ETC0nXA52LTnkC23Y+MUObdzY5kwvLckJ8TYzjEM2MbBQTUT8EQA8PDhw7J165Fx/yeddJIr4aeffipRUVHmKrd9+vTxlenYsaP8+c9/NgOAOj8gCQEEEEAAAQQQQAABBBBAAAEEvC3w+cKtovP5WSkuuoZc0r2Zeai9+vTYP+3+IwC4zdEDsGmdBOnSrLbUiCoqrXMLLtkWes6+AqPMwZy8gPkEW9RLNCvS+EOXprWLKjX2ljh6C9pOcoCAxwXs/6KqqLFpaUUTerZoYR/vr03auHGjWGUGDhwY0MoBAwaYedu3bw84RwYCCCCAAAIIIIAAAggggAACCHhLwDlP39nHNZS6NePMRmrwrd4f+1ard2ceWfgj3bEASOPaCVLTCBh2aJRsFTW3Omw4WPpy8XY5/m/fSOfHvg4o0qJuki+vS7MU377uLGUhEJsHB9VLwN6ftRLbXqNGDbNHn3VL/Qeuw3gTEhKsrICtnte5/4KlnJwciY6Otp3Ozz8yT4AtkwMEEEAAAQQQQAABBBBAAAEEEKgSgZVpGbJoi72H3hW97J2B6teKsy0QYvUA3Jd12NbmuklHgoYNUxJkhVGvlQ44yln5h/ML5C+Tl0iG0fvPmVKNe2ow0Uras9A/Fder0L8s+wh4TaDom13JLXvjjTd8AUDtuafDeDUo+Oqrr4ou8mElDfq9//77oqsEt2vXTh555BHrlG+rZUaMGGFerysFkxBAAAEEEEAAAQQQQAABBBBAwJsCs9fusjWsYXJ8wDx+zh6A1hyA+w4dmQvQqqB24pH4gXO+vozswACfXrN6R6ZYwUSrDmvb3K/3n+Z1dgwB3nEgxxgynC0Nk4N3XLLqYouA1wSqLAA4bNgwn0V6erpvHr9u3bqJ/xx/WkiDetpD8IwzzpChQ4f6rrN2MjMz5YYbbpDk5GTX81Y5tggggAACCCCAAAIIIIAAAgggULUCe40FQPxTr1Z1JcYx5199xxBgKwDo7NlXJ+lIADAloagjkdb90rQ1cpqxkm+fNvX8bxVybsAW9YqG/+pFbVJrSlJctG8FYs3TVYMbdiQAqBak6iXgiTkAGzRoII0aNTLlnn76aZvgzz//LLNnzzbzLrjgAts562Dp0qXmbuvWra0stggggAACCCCAAAIIIIAAAggg4EEBXXzDP/kPu7Xy69WMt3bN7e7MIz3/nEOArR6AKY4Ve/Wiez9YIHnGkF//FGoevzM7NfAvKtHGyiLHNWEeQBsKB9VWwBMBQNUbPHiwOQfgF198Yc7zN3r0aHn00UfFCvo1a9ZMLrzwQlfo7777zszv1auX63kyEUAAAQQQQAABBBBAAAEEEEDAGwKHcu0BQF3115l0DkD/tONAtnm43zG3X+3EI+VS/hgK7H/Ntv3Z8vvmff5ZsjjIQh6DejaTi48/sgqx/wXOeQC1ByAJgeoo4JkA4GOPPWbO8afz+U2bNk3uvfde0d6A+/fvNxf2eOmllyQmJvCHQkFBgVjzCZ577rnV8R3QZgQQQAABBBBAAAEEEEAAAQSOGoHMHPtinTrM1pmccwD+tGaX3PjmPNnnGD5s9QB0zgFo1TdrzW5rV/ILCmXZ9sAAXr/2qfL8ld3NHn++wn/sdG5q7wH45ZI06fv0d/LZ71udRTlGwNMCngkApqSkyKxZs+T666+XpKQkszegBgO7dOkikydPlosvvtgVcsKECbJ+/XqpXbu2DBgwwLUMmQgggAACCCCAAAIIIIAAAggg4A2BcIYAO+cA1JZ/t3xnwANYcwAGCwB+syzNjC/ohevSMyX7sH1I8EXdmsh/ru4RUK+V4ewBqPm6GMhfJhkrCWfb5zK0rmGLgBcFPBMAVBydC1ADevv27ZNt27bJ3r17ZdGiRUGH/uo1GvTTAODy5cslPt4+R4CeJyGAAAIIIIAAAggggAACCCCAgHcEnAFAtyHADVPCW2jD6gHoXATEelodsmsFDp3Df5vUTpCXBvcUZ29D61rdtmtYS+JiAkMnGcY8hivTMvyLso+ApwUCv8UeaG50dLQ0btzY7NVXXHM0aNiqVSvfIiLFlec8AggggAACCCCAAAIIIIAAAghUncBBxxyAbkOAGyQX38EnNjrKXKVXnyTZsQqw/9P9+5uVUmAM/12y1T781613n/91uh9rrE7cqXGyM9s83rovyzWfTAS8KODJAKAXoWgTAggggAACCCCAAAIIIIAAAgiUXeCQYw5Atx6AqY5FQNzuqr3/oqKizFMpiYFrBljXrDB66k1ZvF2WbNtvZZnbLk1r246DHfRtU8/11LZ9RxYmcT1JJgIeEyAA6LEXQnMQQAABBBBAAAEEEEAAAQQQiGSBTGP4rH9KclkFOD4mcGEQ/2t03xr+q/uhegDq+b9/sVTmrt+ju77Utbl9gQ/fCcfOTf3ayvHNA4OF2+gB6JDi0MsCBAC9/HZoGwIIIIAAAggggAACCCCAAAIRJhA4B2DxwT43gmZ1k3zZKQnBewBqoV2Zub6y1k64PQB1PsLP7jxVbu1/jHWpuSUAaOPgwOMCBAA9/oJoHgIIIIAAAggggAACCCCAAAKRIrAzI1sO5ubbHqemSw9AWwGXg3hjYY7hp7T2nakZFzoA6Cv4x47OMRjuQiPWtW0b1LR2zS1zANo4OPC4QMn+hXj8YWgeAggggAACCCCAAAIIIIAAAgh4U+CLhdvkrvcXBDSuJMG7uX8+S9akZ0oLo/dfi3pFPQBr1IiS1vWTZMPuQ776xw/rLcMnzPMd++90aRre8F//a5rVSfQ/lO37mQPQBsKBpwXoAejp10PjEEAAAQQQQAABBBBAAAEEEIgMgRe+XeX6IMF6APZuXddWXtf70F57Jx+Tagv+WYXuPbuDxBmr9moa3LelnNGpoTx4XifrtG17Wa/mtuNwDpo6AoD7sw6Lcz7DcOqhDAJVIUAPwKpQ554IIIAAAggggAACCCCAAAIIHEUCh/MLZN2ug65PnBTnPgfgff/XQQa/Nsd3zdMDu/r23XYu7dFMTm5XX7KMIcat6h8Zrntpj6aigcdc4/5WemZQV7mwaxPrMOxtk9oJAWXTjF6A7RrWCsgnAwGvCRAA9NoboT0IIIAAAggggAACCCCAAAIIRJjAnoOBi3DoI8YYQ3d1Pj+3dFLb+vKvK46Xb5amSa9WdeWKMHrtNUy2B+ma1E6UpwZ2kX98uUKS4qPl31d0lz5t6rndrti8hNhoefGq7qLzB2pvQA0Iah4JgeogQACwOrwl2ogAAggggAACCCCAAAIIIIBANRZIz8hxbb0O/43Ssb0uSfMvN4J++ilLuuKEFnJZz+ai8wSWNWkvQxIC1VHAPcxeHZ+ENiOAAAIIIIAAAggggAACCCCAgCcF0jPdA4DJCZXTL6k8gn+ehKVRCIQpQAAwTCiKIYAAAggggAACCCCAAAIIIIBA6QSC9QBs24D580onylUIlEygckLtJWuTr3RBQYEsW7ZM1q1bJxkZGZKfn+87F2zn+uuvD3aKfAQQQAABBBBAAAEEEEAAAQQQqAKBYAHATo2Tq6A13BKBo0/AkwHArKwsefLJJ+W1116T3bt3h/1WdH4AAoBhc1EQAQQQQAABBBBAAAEEEEAAgUoRIABYKczcBIGgAp4LAGrw78wzz5S5c+dKYWFh0IZzAgEEEEAAAQQQQAABBBBAAAEEqodAsDkA2zekB2D1eIO0sroLeC4A+MILL8icOXNM1y5dusidd94pvXr1knr16hkr9jBlYXX/wtF+BBBAAAEEEEAAAQQQQACBo08gbX92wEPXToyVDo2ZAzAAhgwEKkDAcwHADz/80HzMk08+WX744QeJi4urgMemSgQQQAABBBBAAAEEEEAAAQQQqAwBHd23akdGwK0ev/g4iY+JDsgnAwEEyl/AcwHAtWvXis7lN3LkSIJ/5f++qREBBBBAAAEEEEAAAQQQQACBShXYbvT+y8jOs93zh//XX1gB2EbCAQIVKuC5MbVWj7+WLVtW6INTOQIIIIAAAggggAACCCCAAAIIVLzAirQDtpskx8dIm9SatjwOEECgYgU8FwDs1KmT+cRpaWkV++TUjgACCCCAAAIIIIAAAggggAACFS6wIs0+/Ldj42Rz5F+F35gbIICAT8BzAcBhw4aZq/9+9NFHvkaygwACCCCAAAIIIIAAAggggAAC1VNgpUsAsHo+Ca1GoPoKeC4AeNNNN8mZZ54pb731lrz//vvVV5aWI4AAAggggAACCCCAAAIIIICAOAOAnZqkoIIAApUs4LlFQDZv3iyjR48WDQRed911MmnSJBk8eLDo0OCkpKRieZg7sFgiCiCAAAIIIIAAAggggAACCCBQKQK5eQWyZmem7V6djCHAJAQQqFwBzwUAW7du7ZsLQJcK/+STT8xPOCy6enBenn1loXCuowwCCCCAAAIIIIAAAggggAACXhbIPpwvW/dlSbM6iZIQG+3lptratm5XpuQVFNryOjQiAGgD4QCBShDwXABQn1kDf1by37fy2CKAAAIIIIAAAggggAACCCBwtAi8PG2NjPp+teQYvekaJMfLBzefKMc0qFUtHt85/FcDmLUTY6tF22kkApEk4LkA4Pjx4yPJl2dBAAEEEEAAAQQQQAABBBBAoNQCv2/eJ899vdJ3fXpGjjwxZZlMGN7Hl+flneXbA1cA9nJ7aRsCkSrguQDg0KFDI9Wa50IAAQQQQAABBBBAAAEEEECgRAKTF2wNKD99Zbo5r167ht7vBbgy7YCt/R2Z/8/mwQEClSXguVWAK+vBuQ8CCCCAAAIIIIAAAggggAACXhbIN+bO+3LJdtcmTpi93jXfa5nOIcAsAOK1N0R7jhYBAoBHy5vmORFAAAEEEEAAAQQQQAABBKqVwJRF22THgRzXNn/y61bZdyjX9ZxXMvdnHZZt+7NtzenUOMV2zAECCFSOAAHAynHmLggggAACCCCAAAIIIIAAAgiUSOC1H9cFLZ9lrAr8/tzNQc974cS69ExbM2Kjo6Rtg5q2PA4QQKByBKpsDsC///3vvif861//6tv3z/dllmDHv64SXEZRBBBAAAEEEEAAAQQQQAABBDwjkG0E+JZstc+fpwG0w/mFvja+OXuD3NivjcRGe7NvT2ZOnq+tulM3Kc6zbbU1lAMEIlCgygKAjz/+uERFRZmk/kE7//zSePvXVZrruQYBBBBAAAEEEEAAAQQQQACBqhZYv+tgQBPevKGPDH5tji8/7UC26DDhgT2a+/K8tJOVm29rTmJctO2YAwQQqDyBKv0zQWFhoejHmaz80myddXGMAAIIIIAAAggggAACCCCAQHUTcAYAm9ROkJOPSZVereraHuXPny6RjbsDg4W2QlV0oMOU/VNiLAFAfw/2EahMgSoLABYUFIj18X9gK6+0W/+62EcAAQQQQAABBBBAAAEEEEDAKwLayWWcMa/fZa/Mln9+tcL4nTiwQ4zVVuf8edbceSNObWMVMbcaZHv0s6VyKDdPJi/YKj+t3iW6erAXkg5j9k8JBAD9OdhHoFIFqmwIcKU+JTdDAAEEEEAAAQQQQAABBBBAoIoFZhrBuSenLjdb8evGvVKvZpwxh19b11atcwwBbpN6ZPGMc45rJN2a15ZFW/b7rpu5Kl3OfXGmbN6TZebde3Z7uffsDr7zVbXjHAKcEFtlfZCqioD7IuAZAf71eeZV0BAEEEAAAQQQQAABBBBAAIFIEpg4b7MMeX2OPP/NSmPxjgL5zOih5580GOg2LZb2DJy/Ya9/UWmbWss8jjEW/Bg75ATbOT2wgn+6P2b6WjnoWIBD8ys7ZR0usN2SIcA2Dg4QqFQBAoCVys3NEEAAAQQQQAABBBBAAAEEjgaBOet2y8hPFsmPRq+/UT+skQmzNsgMo6eeM61Iy3Bmyey1u2XTnkO2/J5+c/81NuYDHHB8U9t5/4PcvALXe/mXqYx95xBgFgGpDHXugYC7AAFAdxdyEUAAAQQQQAABBBBAAAEEECi1wP0fL7RdO2H2BqlfK86Wpwez1uwKyHt3zkZbXsdGyXK8MezXP3VpmuJ/GLD/zdK0gLyKyFiRdkBeMXoczl2/J6B6ZwCQOQADiMhAoNIEmAOw0qi5EQIIIIAAAggggAACCCCAwNEi4D8kV595674sqRkXuAru7oO5NpKdGdny7bIdtrxrT2wpUVFRtjydPzBUWrB5X6jT5XJu9Y4MGfjybLFW+x0/vLec0bGhr24r38pgCLAlwRaByhegB2Dlm3NHBBBAAAEEEEAAAQQQQACBCBZwLn5hPerBXPuquJq/79Bh83RG9mEZO3Ot9Hnqe8nzW8VXg2aX9mhmVeHbuvUm9J00djbuPiS/bdpboSsC/3fmOl/wT++tPQH9k9OBAKC/DvsIVK4AAcAyeD/44IPmX2H0LzH6mT59erG1ffnllzJw4EBp3ry5xMfHm1s91vxwU15enrz66qvSr18/adCggSQmJsoxxxwjt9xyiyxdujTcamTXrl3y17/+Vbp16yYpKSnmR/c1b/fu3WHXQ0EEEEAAAQQQQAABBBBAAIEigSXbilboLcp139uflSu7M3Pksldmy9P/WxFQaMDxTSQlITYgv17N+IA8Z8agMbPl7vcXVEgQ8FBunnz86xbbLXUY8F6/Ho3OHoAMAbZxcYBApQoQACwl9++//y7PP/982FcXFBTIjTfeKBdccIFMnjxZtm7dKrm5ueZWjzX/pptuEi0XKmnQ7uSTT5bbbrtNfvrpJzOIl52dLevWrZOxY8dKr169ZNy4caGqMM/NmTNHunbtKk888YQsXrxYMjIyzI/ua56emzt3brH1UAABBBBAAAEEEEAAAQQQQMAukLY/254R4kh7AL7w3SpZtSPTtdS1fVu55tcvZgiwddHUxdtlkmP1YetcWbaz1rh3GvFf6MQ5ByCLgJRFnGsRKJsAAcBS+GmQ7uabbxbtidewYdH8BqGqeuSRR+T11183i/To0UPef/99M8CmWz3WpIG7v/zlL+a+23/y8/PN3oPz5s0zTw8aNMjsOajBvFGjRpltycnJMXsChupRuHnzZhkwYICkpaVJTEyMjBw5UmbOnGl+dF/ztm/fbpbZssX+Fx23dpGHAAIIIIAAAggggAACCCBQJJCRnVd0UMyeBgCXbD3gWuq4JinSzbH4h1WwuDkArXK6vf+jheIMxvmfL83+/I2Bi35oPWvTiwKZ2YftHVzoAVgaaa5BoHwECACWwlGDbRqE69Spk4wYMaLYGlatWiX/+te/zHInnHCCzJo1S66++mrp3bu3udWefJqv6bnnnpM1a9aY+87/vPnmm2avP82//fbb5ZNPPpHzzjtP+vTpI3fddZdZrw7l1QDl3XffbQYonXXosQYj09OPLD//3nvvybPPPmsOJ9Yhxbr/7rvvmpft3LkzZEDSrW7yEEAAAQQQQAABBBBAAIGjXUDn8ws37c86LHv8hs36X3d5r+YBi39Y55NcFhSxzrlt3/nFvrKwW5mS5C3Y6L7IiH/w0zkEmDkASyJMWQTKV4AAYAk9N23aJI8++qh5lc7DFxcXeuUlLfjiiy/6gnGjR4825+zzv21SUpJovibtVfjCCy/4n/btW0HEevXqmYFC34k/dtq1aycPP/yweaRBxEmTJjmLmL3+rADfueeeK1dccUVAmSuvvFL0nKa3337bvCagEBkIIIAAAggggAACCCCAAAKuAv5BMNcCfpn7Dh2ZA9Avy9yNqRElA45v6sz2HTtXBfadCLLz5NTl8sikxXI4394rL0jxkNlax6Kt7gHAA37Bz4BFQOIIQYSE5SQCFSjAv74S4t5xxx2SmZkpQ4cOlf79+xd7dWFhoXz22WdmOe0xeOKJJ7peo/kdO3Y0z2l5vc4/aS/C5cuXm1kaoNOgoVsaNmyYL9stAPj555/75hkcPny4r6xzx6pHexPqNSQEEEAAAQQQQAABBBBAAIHwBErSA1BXBnZbHfixAcdJg+TiF/oIr0VHSr07Z5N8uSStJJe4ll2+/YAxpNg9kJjpN/zZOeyYHoCunGQiUCkCng4Afv/99zJkyBDRnm21atUy56ZbtmyZDUbnrhszZoy88847tvyKOJg4caJMmTJFtAee1RuvuPusX79etm3bZhYrLmBondcFQjZs2GCrWocJW8kqZx37bxs3biwdOnQws3SosTOFW4//PdzqcdbLMQIIIIAAAggggAACCCCAwBGBkvQAdDOb9dCZMuSk1m6nbHndW9SxHZ/RsYHt2O1gnrFSb1nTbxv3Bq3C/9mdQ4DjY6ODXscJBBCoWAFPBgAPHTpkDk0955xzROeo0xVuNc/ZK05poqOj5c477zR75K1evbrCtPbt2yf33HOPWb/Ok5eamhrWvfwDltoDMFTyP2/19rPKl6YeXezj4MGDVhXm1qqndu3aosHCYKlJE2OpeWM+QU3OtgS7hnwEEEAAAQQQQAABBBBAAAGRA3694ErqoUN/m9ZOCOuya/q08JWLNq575MJjfcfBdoLNNxisvFv+b5vch/9q2YycovkPnQFAegC6aZKHQOUIeDIAqENcP/30UzPgpwtl3H///UE1TjnlFOnSpYt5XhfFqKikq+Pqqrl6v3AW/rDa4b+KbvPmza1s122LFkU/vDV4559KU48GTP2v0/qs4+LaomWt9jjboueKS3qfUB9dZZiEAAIIIIAAAggggAACCESiQEmGADufX1f3DXd+vytPaCH/ubq73HBKG5l4y4nSrmGyXHdiS1uVXZod6dhhZe4+mGPtlnr7a5g9ABkCXGpiLkSg3AViyr3GMlaoQbz//e9/5g+8sWPHyo033mjWGGrI7aBBg2TJkiUyY8YMeeihh8rYgsDLf/zxRxk3bpw5BFkX/gj3h7HWlJGR4atQhzGHSjVr1vSd1nkG/VN511NcW/TeVnucbfFvV7B9K3gY7Dz5CCCAAAIIIIAAAggggECkCvgPg3U+43FNUow5//Jk4+5DzlPmcf1a4c/7p7+bXtK9mfmxKrv7zPaydW+WrEjLEF1FuG2DmnLfhwut07L3YFEPPV9mCXZ2HsiWrfuygl5hzQFYUFAYME9gYglXLg56E04ggECJBTwXAHzzzTfNh7juuut8wb/inqpXr15mkYoYqpqbmys333yz2Rvxvvvu8/U2LK5N1vns7Gxrt9gVg+Pji37QZ2XZf6CWdz3hrF5stcfZFt8DsYMAAggggAACCCCAAAIIICA/rk6XV6avNRftePj8Y23DYJ08/TqkyuG8Qnlj1nrnKfM4tVaca364mQ1TEmT88D6+4jNWpfv2dWf3wVzbcUkPftsUfP4/rUuDnxr8e/PnDXpoSwwBtnFwgEClCnguADh//nyzh91VV10VNoTOV6cpPd3+gy3sCkIUfPrpp2XFihXSsmVLeeyxx0KUdD+VkFA0d4MGE0OlnJyirtiJiYm2os56/I9tBY2D4urR+RSLa4vWadXjbIvzfm7HxQ0b1iHAffoU/U/JrQ7yEEAAAQQQQAABBBBAAAGvCxzIPiwjJsyX3Pwjq+LqsNdQPQBPaFVPerWqK5/8tkX2ZwX2xtMhwOWZ6iXZ69t7KNcM0NUw5gwsTXLO/9esTqKtR6A6TJi9Qf4+xb6Ap94rOcFzIYjSEHANAtVSwHP/+nbv3m1CNm3aNGzQGjWOTGVYUOC+DHnYFTkKauDvmWeeMXNHjx7tGxLrKBbyMDk52Xe+uKG0/gt2OIfoOusJFQAsrh4NABbXFm20VY+zLb4HCrETzhyDIS7nFAIIIIAAAggggAACCCBQLQS+XbrDF/zTBn9tHIeKrTUxFvjQIN/bI/rIrW//Ktv2F40a0+u7Nbev7Kt5ZUn1HD0K843eeRq0rOMIDIZzjyVb98vYmetsRfsbKw+/N2eTLe+1H+1l9KQGCktzT1vFHCCAQKkFPBcA1NVpNQi4bds26d69e1gPtn79ka7T4a7MG1alRqEXXnjB7CnXtm1bcxXiDz74IOBSnXvQSj/88IO5UIgeDxgwwAwY+gfCrAU4rPLOrX+vOecces56Qj2rVY/OB+F/nd5Pj3fs2OFbDMTZBv9jqx5nW/zLsI8AAggggAACCCCAAAIIHM0CzpVu1cKIsQVNDZOPTP2kgb4ZI8+QqYu2y3ijx9zKtAPSr30DueKE0ItHBq04yIn6Lj0KdSXgkgbj1qVnyqUvzwq4y+kdAgOA2x1BTb2oe4vyDWwGNIQMBBAIKeC5AGCHDh3k559/loULF8oFF1wQsvHWycmTJ5u7PXr0sLLKZWsNgV23bp1cc801xdb5xBNP+MpoUFIX0TjuuON8edqjMFTyP3/ssfbl2531hAqOWvVo4M5ayMO6r9bz66+/yv79+81gZePGja1Ttq0O0T1w4ICZ52yLrSAHCCCAAAIIIIAAAgggcNQJaDDo2a9WyKHcfLn4+KZyWc/mUtohpdUdr3ZibIkewX+Rj9joGnJpj2bmp7CwsEQLToZ704TYaEkyFt/Qd2UlDQC2bWAdhbd96+eNkucS2ezbpr7ERkfJ4fwQUU/jFh0aFY2OC++OlEIAgfIUODJ2tjxrLGNdF154obnghg659V/4Ili1ukKv9szT3m7a685rqU2bNmINZ9ZVikOlmTNnmqebNWsmrVu3thU99dRTfceh6klLS5NVq1aZZU855RTfNdZOuPX438OtHqs+tggggAACCCCAAAIIIHD0Cfxl8hJzqOuPq3fJAx8vkiv/+7PRgy3j6IMwnvjwH3P/hfvw0UHGB+vvtBWVnPMKlnQhkOkrd5rz+rm1r3ZSrNSKL75v0TmdG7ldTh4CCFSSgOcCbTD4YAAAQABJREFUgHfccYfUq1fPHKZ6+eWXy549e1wp8vLy5LXXXpOLLrrImMC0QLS327Bhw1zLljZzwoQJZjBS/xIT7OO/MMi0adN85awAnrks+yWXmE3Qnnm//PKLa3M03+q5d4lR3vnDX3tGWj3xJk6caA5JdqtI22ylgQMHWru+7cUXX2z8Ze7Iax8/frwv37lj1aNl9RoSAggggAACCCCAAAIIIKACOXn5MnvtkbnbLZH5G/fKgNE/yXfLdlhZYW3TM3LMa3Rrpdy88p3b3aq3orbVob3OAODeMFcC3p2ZI2Omr5Fh4+e58l35x3Dl4oYT33HGMXJskxTXOshEAIHKEfBcADAlJUU+/PBDiYmJkS+//NIM7PkPBR45cqScc8450rBhQ7n11lslIyND4uPjRYNisbEl63pdOcQi9957r0RHR5u3u+uuuyQrK8t2az3WfE363FreLd1///1mtgZF1cGZ1q5d61u0pF27duIWANQhv9dee6156ddffy0ff/yxsxr56KOPRM9pGjJkiAQbJhxwIRkIIIAAAggggAACCCAQ8QL+wTr/h9XVX29/7zdZawwPDict335A+j83TW58a75cMOpHWb/roNxk7Hd89EsZOGaW7DKCT9Uh5QQJWE66/WTPNN8ZACyuB6AuFHKz8S56Pfmd/POrlUGf46reLcxzp7SrH1BGhwWfa/T6++3R/5MHzu0UcJ4MBBCoXIHi++lWbnvMu5111lmiC2pcd911snHjRvnqq698PeI0KKhJe+Rp0p5/Gvzr06ePeezF/2jvvQceeED+8Y9/yPz580WH1D744INyzDHHiAbtnn32WVmwYIHZdC3Xvn1718cYOnSovPHGGzJr1ix5+eWXzTn8brrpJqlbt67MnTtXdA5CnbdPe+2NGjXKDCa6VfTUU0+Zpunp6ebchtom7UmpacqUKfLvf//b3G/QoIE8+eST5j7/QQABBBBAAAEEEEAAAQRUYMeB4IE57Q339dI0uf30dsVivTtno29eOg0qnvGv6b5rFmzaJw99skjGDe3ty/PqjvaIdKZ+7VOlR8u6zuwqO3YGAHUOwFBpxqqd8k2I3pzdmteWP/1fB+nVqp5ZzV8uPM4YBhwrm/ceMueEPM1YzCTGCADqHIckBBDwhoAnA4BKo0Gy1atXm/P7ff7552bgbOfOnZKfny/169cXXfBDh6ZqUCwuLs4bmiFaoUE3bb8G8DTYd/XVVweUHjFiRMiAm/Yi1AVPtEfkvHnz5JNPPjE//hVpb8iXXnpJzj//fP9s274GTb/44gu59NJLzSCiBiD145+015/ey7mKsH8Z9hFAAAEEEEAAAQQQQODoE9h5IDvkQx/Iygt53jo5xVj9NlT6bvlO+W3TXunpoUCaW3tzDgcOWb737COdOk4zVsiduSrdd9mgns18+5W541wJuLgA4NKtRxaEdLZRn+vOM9oZwT17YE8XGnnofHr5Ob04RsBLAp4NACqSDofVXoD6qe5Je+W9/vrrctlll8nYsWPNAN6uXbskNTVVevfuLbfcckvIoJ31/Fp+9uzZ5vyH7733nixfvlwOHjxoLjSiPSfvuece6dy5s1U86LZv376yePFi+c9//mMG+jZs2GCW1UVLdA5CHYasgVYSAggggAACCCCAAAIIIOAvsKOYAGBWbngBwDhHEMn/Htb+z8Zcg54PADqGAJ/Ytp6vZ5wGy34xnkGHR+tCGfed3cF6tErd1qsZb7tfqACgBnj//e2RhSX9L3r1ul5yXpfG/lnsI4BANRLwdACwOjg+/vjjop9wk/be85/TMNzr/MtpYPS2224zP/75Jd3XYKIOG9YPCQEEEEAAAQQQQAABBBAIR2Cn34IdbuWzDgcOiXUrp/PMFZcO5oQXTCyunoo8r8E9/9SsTpLvsE+bejLl7lNl8Zb9crIxT16T2om+c5W5U6+mfb58KwCowdxR368Wde7btr6c2i5V/jTx94Cm3dSvDcG/ABUyEKheAgQAq9f7orUIIIAAAggggAACCCCAQJUJzDCGs46Zvjbk/Q/l5psrBT9nLB6xeOt+uaBrE2mdWlN0GGqXZrXNaw8bQbPiFqLQguEGE0M2qIJP5jgCnvGx9uGxHRoli36qMgXrAXjX+wtk7vo9ZtMm/74taBOruv1BG8YJBBAIW4AAYNhUFEQAAQQQQAABBBBAAAEEjl6BlWkZcsOEeQEAyQkxkpFd1FMvywgAPjJpiXz86xaz7Jw/Akx6oEHAwX1bitYVTsp2mV8vnOsqs4xzFeD4GHsAsDLbEuxezkVAdh/MEV14xQr+BbvOym9ap2p6Llr3Z4sAAmUX8FwAUBe6KG2KioqSvLyi//GUth6uQwABBBBAAAEEEEAAAQQQsAt8NH+zuA3bbWv07ltoDHG10vcrdlq7AVvt9Tf6hzUB+cEynL3rgpWrrPy16ZnyvDE/3mFj3r//d05H6dg42ejtaB8CHB9T+t9pK+o5nIuAaGB1/oYjPf/CuWeT2gnhFKMMAgh4WMBzAcDCwuLngfCwJ01DAAEEEEAAAQQQQAABBCJS4K2fN7o+V7/2DWwBQNdCpczMzgtvPsFSVl+iywqMOQvvePc3WfFH78UlxvDmnx480xzu7F9RnBd7ANaK82+iuT9zddHqxAEnHRlVNXehoxkcIoBAGQQ8FwB87LHHin0cXfV21apV8u2330p2draceOKJcs455xR7HQUQQAABBBBAAAEEEEAAAQRKLpATJBCnwa72jWqVvELHFc3rJsrwU9rIWz9vkI27D/nOemkI8CIj4GcF/7SB2/Zny4bdByU3oAeg94YAJxsrEMdGR8nh/KION98vD95T0/cCjJ1GKfGSGOe9Xo3+bWQfAQSKF6iWAUDrsXbv3i0jRoyQKVOmyODBg+WOO+6wTrFFAAEEEEAAAQQQQAABBBAoJ4Fl2w6Ic7Vbrfqes9pLQmz4waETWtWVbfuyzOCZf9M6N02REae2kRpRIn/7YpnvlM4n6JX0g8vQ5r2HDrsMAfZeAFCny2peN0nW7zro43Rbzbl1/ST54f+dLle/9otvfsAbjMAsCQEEqr+A5wKAJSGtX7++fPzxx9K3b1+577775IQTTjD3S1IHZRFAAAEEEEAAAQQQQAABBEILrNoRuGjHqe1SzaDdvCBzycUY0bxR1/SQqYu2m3MH3nN2ezm2SYr8d8ZaeebLFbYbntelsXnsDCZ6aQjwt8t22NqsB/sO5UqOY6GS+BIERAMqrMCMVkZwzz8A6Har5644XmoY7+3dG/vKTGPFZ108pEfLum5FyUMAgWom4L0/TZQQMCYmRu6++25z8Y/nn3++hFdTHAEEEEAAAQQQQAABBBBAoDiB1TsybUX6tU+Vd4wgkQbskoIMDx16cmu5oGsTefnanvLqkF5m8E8rOaNTQzE6pPnSMQ1qysXHNzOPE2Ltv6J6ZQjwaiMAunz7AV+brZ09xqImzuHRXlwFWNvbun5Nq9mu22/uO016t65nnouNriFnHduI4J+rFJkIVE8B+0/X6vkM0qVLF7Pls2bNqqZPQLMRQAABBBBAAAEEEEAAAe8KrDFWv/VPxzev4zt09tqzTgw5sZW1a9t2aJQsfz7/WKmdGCudjFV0/zvkBInWsb9GSnCsoOuVVYA/X7jN9gzWwb5qMgRY29vGWK05VNLefiQEEIhcgWo9BNh6LboQiKZdu3ZZWWwRQAABBBBAAAEEEEAAAQTKSWDNTnsAsF3DooU/kuLcf61sWS8p6N1vOq2t3NivjdET0K8roFE6wdGbMOtw1c8BWFhYKJ/97h4A3GsMAa4Oi4Doi2gdIgCor6FuEgHAoF9YTiAQAQIR0QPw008/NV9FgwYNIuCV8AgIIIAAAggggAACCCCAgHcEdCGOrcbCHf7JPwCY6DLnnQ6D1bnkQiVn8E/LOnsAZnsgALhwy37ZtKdoZWL/Z3JfBCT8RVH866roff935ryXBv+sXpjOcxwjgEBkCLj/qaaaPNvBgwdl9OjR8p///Mf8y9FZZ51VTVpOMxFAAAEEEEAAAQQQQACB6iGw1hj+a3SC8yXtLXZMg6IegImOXntaMDmhdL9qemUOQO31N2/DXtFnn7Um+EgzcxGQPHsvRa/OAdisTqIxp18dWbBpn+9dWjsM/7Uk2CIQuQKl+6lcgR5nnnlmsbUXFBTI3r17ZdWqVZKbm2v8z6hQatWqJY888kix11IAAQQQQAABBBBAAAEEEEAgfAENgvknDST5B/3cFgGpFV+6XzWd8wnqKsD6+55bb0H/NpX3/sT5m+XBTxYXW60OAQ5cBdi7A+3uOrOd3DBhfsBz1Wf+vwATMhCINIHS/VSuQIXp06ebP9z1h3y4qVWrVvLOO+9I+/btw72EcggggAACCCCAAAIIIIAAAmEIhJr/Ty/XFWOdqWYpA4DO4cT6a2FufoHEOxYHcd6vvI9fmb42rCrdFgGJi/bmEGB9oDM6NpTjmqTIMseKxvQADOt1UwiBai3guQDgaaedVuxfd2rUqCHJycnSpk0b6d+/v1x44YUSGxtbrV8EjUcAAQQQQAABBBBAAAEEvCgQEAD0G/4brL3l1QNQ68/OrdwAYHpGjmzY7T7nn/N59xw0FgExApT+KT42MCDqf74q97UnpfYCvO3d32zNKEH/G9t1HCCAQPUR8FwAUHsAkhBAAAEEEEAAAQQQQAABBLwhEBAA9FsBOFgLSx8ADAye6TDg2lJ5HT5+3bgn2GPJgOObyhcLi1YE3mkEC53Jq3MAWu08t3NjqZMUK9p70UrHt6hj7bJFAIEIFQj86RqhD8pjIYAAAggggAACCCCAAAIIlEwgz+jdtmH3QdtFoVaTtQqe2La+tVuirXMOQL24slcC/mWdewBQFz+57+z2UszixpU+XLlEwEZhXZ15zOCeEvfH0O2axiIuA3s0K2k1lEcAgWom4LkegNXMj+YigAACCCCAAAIIIIAAAhErsHHPITmcb5+f3S0AeLcxrHTUD2tMh9qJsTK4b8tSmbj1nss+bB9iW6qKw7xov9ErThcAcUsDuzeTtsbw5w6NkmVFWoZbETMvKd67cwBajT65Xap8cdepsnjrfunfoYE0SI63TrFFAIEIFSAAGKEvlsdCAAEEEEAAAQQQQAABBMoqsHqHfQXg1FpxxvDRuIBq7z27gzSvmyRb9h6SK05oIaVdBETnqEsw5tDzD/pVVg/AbfuyjBVy58mh3Hzb811/Uivp2qy2XNy9qZnfrXntoAHARinxkpJQecOVbQ0t4UHHxsmiHxICCBwdAlUWAJw5c2aFCOsiIiQEEEAAAQQQQAABBBBAAIGyC6xNtwcAjwmyAIgOK72yd4uy39CoQYcB+wcAsw7bA3LlchNHJYu37Jdh4+fKbmNRD//Ur32q/P2SLv5Z0q15HaOX4BZbnnXQqXGKtcsWAQQQ8JRAlQUATz/99GJX+y2plP61KC8vr6SXUR4BBBBAAAEEEEAAAQQQQMBFwLkASPtGtVxKlW9WQowOoS1aoKIyegCO/GRRQPBP58Z79KLjAh7uEqMn4AvfrgoorwWPbUIAMACMDAQQ8IRAlS4CUmisNV7eH0+o0ggEEEAAAQQQQAABBBBAIAIENjoWAAnWA7A8H7WmYw69XZn2XnnleS+tKzMnT5ZvP2Crtk1qTZl8xynmfH+2E8ZBsjHEd/zw3sY2sD/NsU0YUuv04hgBBLwhEPgTq5LaNW3atEq6E7dBAAEEEEAAAQQQQAABBBAojYAz+NY4JaE01ZTomjaptWRtetHKw6t2BF9wo0QVBym82lG/rvI76faTXec6tKrQYcDv3thXrh03RzKyj4xCizEu7NOmnlWELQIIIOApgSoLAPbv399TEDQGAQQQQAABBBBAAAEEEEDALrArM8eWkVoJq8VqL7rvlu/w3dfZO893opx2nAHG1kbvP7eFTpy30yDghzefJI9/vlTU6Y4z2kmT2onOYhwjgAACnhCosgCgJ56eRiCAAAIIIIAAAggggAACCLgK7DUWxHCuiJtaK961bHlmOlemXZlWsT0AVzlWOu7YKPxhvMc1TZGJt55Uno9PXQgggECFCFTpHIAV8kRUigACCCCAAAIIIIAAAgggUCaBl35YLT2e+DagjtRacQF55Z3hXEl3Z0aO7HGszlue93T2AOxQggBgebaDuhBAAIGKFCAAWJG61I0AAggggAACCCCAAAIIVDOBdemZ8m9jlVtnio+pIbXiK34QWev6SRJn3Ms/rUizL9Lhf66s+1v3ZtmqaNugpu2YAwQQQCASBCr+p3cZlDIyMuS7776ThQsXyq5duyQrK8tcNThYlVFRUfL6668HO00+AggggAACCCCAAAIIIIBAMQKz1u42fu8KLKTDf/V3ropOMdE1pH3DWrJ0W1HQT4cBn3xMarnfutB40LQD2bZ6mcfPxsEBAghEiIAnA4AFBQXyxBNPyL///W85eLBo9adQ5vqDmwBgKCHOIYAAAggggAACCCCAAALFCyzYuNe1UP1KGP5r3ViHAfsHAP/2xTJpZwQF+7VvYBUpl21GTl7APIeVsdJxuTSeShBAAIESCHgyADhs2DB59913zd5+0dHRUr9+fdm5c6cZ4GvevLns3btXMjMzzcfUoF9qaqokJSWV4LEpigACCCCAAAIIIIAAAggg4Cbw6yb3AODG3YfcildIXqfGgQtxDHl9rrx5Qx/p36GBfLdsh8xau0tOMwKCjVISZOL8zdK8bqJc1buFJCfEht2mtP323n96YcOUil/oJOwGUhABBBAoJwHPBQC//vpreeedd8xgnwYCtRfg1q1bpVu3buYjb9y40dyuXLlSXnnlFXn55Zelbt26MnnyZOnUqVM5sVANAggggAACCCCAAAIIIHD0CezKzJFggb7zOjeuNJBOTQIDgHrzsTPXmh1FbnxrvtmW8bM2mFvrP+/P3STjhvaWNqnhzePnDADWTYqVhNhoqzq2CCCAQMQIeC4AOH78eBO3c+fO8sYbb5j727ZtCwDv2LGjvPjii3LWWWfJoEGD5IILLpAFCxZI7dq1A8qSgQACCCCAAAIIIIAAAgggULzAb0GG/+qVZx/XqPgKyqlER5cegFr1rDW7JTevIOhd1qYflDP+NV10IY//M9p7e/92UtsI6gVLzvn/tDchCQEEEIhEAfvSSh54wl9++cXs/XfHHXeE1ZoBAwbI0KFDRXsGjho1KqxrKIQAAggggAACCCCAAAIIIBAo8NumfQGZZ3ZqKE9c0lnOMraVlRoYC47Uqxnnert5G9yHKPsXXmcEAv87Y53c8+EC/+yA/VlrdtnymtQmAGgD4QABBCJGwHMBQJ3rT1OHDh18yDoPoJVycnKsXd/28ssvN7uBT5o0yZfHDgIIIIAAAggggAACCCCAQMkEfnPM/3fHGcfIG8N6y5CTWkuNGhW/ArDVWp3rPVgA0CoTznb6ynTJPpzvWnRdeqZ89rt9tFljAoCuVmQigED1F/BcANAirVevnrUryclF8z9YAULfSWOnYcMjf4nasGGDfzb7CCCAAAIIIIAAAggggAACYQoczi+QRVvsPQB7taob5tXlXyymnAKO6RmBnUi0tS9PWxvQ6F6tin4PDThJBgIIIFCNBTwXAGzU6Mi8Env27PGxal5c3JHu34sWLfLlWzvWwiDZ2YErOFll2CKAAAIIIIAAAggggAACkSSwbNsBeWLKMtGFL/ILCsv8aMu3HzB6y9nn1+vRouoCgDf1a1vmZ9IKdmYE/p64dNt+o/ffVlv953ZuJIN6NLPlcYAAAghEioDnAoBdu3Y1bZctW+YzjomJkR49epjH1iIhvpPGjq4GrKlVq1bmlv8ggAACCCCAAAIIIIAAApEsoKv1XjX2Z3n9p/Xy8KeL5dUZgb3Zwnn+rfuy5NHJS+RPE383A4n+1+hCGnWDzMPnX66i9i/o2kSa100Mq/pBPZvJ3We2cy2784C9B+DBnDy5670FkucXNE2IrSFPD+xaqcOcXRtLJgIIIFBBAp4LAJ5++unmfH7fffed7ZGvu+463zx/uujH1KlTZeLEiXLhhReKltU5Ii655BLbNRwggAACCCCAAAIIIIAAApEgUFhYKHsO5kpW7pH57KYu2i4Z2Xm+R3vu65VS4BfQ8p0IsaN1/unD3+XtXzbKp79tNQKAm22le7asut5/2pDEuGj56t7T5JR29W3tch4kxkbLyHM7ScMgK/juOGDvAagBz3W7DtqqGX5KG6lvLDxCQgABBCJVwHMBwIEDB5rWX331lezYscPnfsstt0jPnj3NIOA777wjF198sVxzzTWi5TS1bNlSHnzwQV95dhBAAAEEEEAAAQQQQACBSBDIM+bm+9PEhdLziW/l5H98bw5d1QCgMy01hgSXJG3ZmyVz1hdNveS8tqoDgNqeWvEx8vdLujib5juONuYJ/OzOU0QX72gcJAD4+BfLRHv9PfbZEmn90FT5dIF96O/xzWvLfWcXLULpq5wdBBBAIIIEPBcAbNOmjaxbt06WLFkiKSkpPmodBvztt9/KtddeK7qvf63SjybtBfjjjz9K3bpV+xcqX2PZQQABBBBAAAEEEEAAAQTKSeC/M9fJpD+CVnsPHZZ7Pvhd5m4IDNx9vtAe2Cru9nNDBP/02qpcAMS/7W1Ta0r9IEORX7m2p3RodGTRyFAr+HZ+7Gt58+eN/tWa+8lGgHH0NT0lLsZzvxoHtJUMBBBAoCwCMWW5uKKubd26tWvVGuB7++23ZcyYMbJ69WrJy8uTdu3aif+Kwa4XkokAAggggAACCCCAAAIIVEOB7MP58ur08Ob3Gz9rg1zWq7l0alzUkSLUI89zCSJa5TUw1r5hLeuwSrc63VOLekmy2xgC7Uzt/NrYMKXkQ3hHnt9JWtZPclbLMQIIIBBxAp4MABannJycbA4HLq4c5xFAAAEEEEAAAQQQQACB6iyw3pirLsMYvhpO0kUtrnz1Zzm1fapcbgQCz+zUKOhlOpfgN8uKplxyFuzeso6nFsRoYgzx/d0+RaHERkdJSyMwaKXUmiUPAPaq4nkOrbazRQABBCpawHP9nFesWFHRz0z9CCCAAAIIIIAAAggggEC1ENh7KLDXW6iGHzAWBvnf4jS5YcJ8+XDepqBFPzDO6aIiwdKl3ZsFO1Ul+Y1c5vdrXb+mxEQX/Upbw5gP8JbT2paofa1TiwKIJbqQwggggEA1E/BcD8DOnTtLjx49zLn+rr76amnSpEk1I6W5CCCAAAIIIIAAAggggED5COwz5vxzptM7NpA4I/CVkhgrXZqmiM4RuH2/faVbvWbi/C1yVe+WzsslN69AXjOucUst6iXK0JNay6Ce3goAus3v5z/813qWh4whvae0S5XfNu2V9IwcqZMUKzrX4bwNe60itm1SnOd+Jba1jwMEEECgvAQ899NOF/ZYsGCB+Rk5cqT0799frrvuOhk0aJBtUZDyAqAeBBBAAAEEEEAAAQQQQMCrAs4egN1b1JEJw/vYmnuyEfC611gYZNl2+yrAOnzYmVbvyJD/e2GmM1s+uvUk6d26XkC+VzJ0CLAzuQUAdb7A0zo0MD9Wef0dUwOAV/73ZyuLLQIIIHDUCRT1l/bIoz/11FOivQD1h3R+fr5MmzZNRowYIY0bN5YrrrhCJk+eLIcPB/4VzCPNpxkIIIAAAggggAACCCCAQLkJOHsA1jV6tDmTroL7v3v6ySe3nWQ7pUN892cV/e6Ul18g170+x1ZGD3q3ruvp4J+20W0IsFsAUMs6kwYF+7SpJ3ef2c52asSpbWzHHCCAAAKRLOC5AODDDz8sixYtkoULF8qDDz4oLVq0MIOB2dnZ8umnn8pll10mjRo1kltuuUVmzJgRye+GZ0MAAQQQQAABBBBAAIGjXGCvY56+uklxQUW6NKstxjR4trQuPdM83r4/S577ZqXsOJBjO68Ht59uD4wFFPBARsPkwAU+mtct2fx9g/u2kqZ/9CRsYNR3/UmtPPBkNAEBBBCoHAHPBQCtx+7atas888wzsmHDBpk5c6bceuutUq9ePTMYuG/fPhk3bpyceeaZ0rJlS3nooYfMoKF1LVsEEEAAAQQQQAABBBBAoDoK6Ego/7TXMQdgnRABwPiYaGlaJ9H/chk4ZrZMmLVeTn12mvx3RuC8f8c1SRGdU9DrqYWx2m9qraLgp87t19mY/7AkSecR/OZP/WXyHafId8a2lbGICAkBBBA4WgQ8GwD0fwGnnnqqjBkzRrZv3y5ffPGFXHPNNZKYmGgGA7ds2SLPPfecuXBIt27d/C9jHwEEEEAAAQQQQAABBBCoFgI6XFfnqGvz8P+k9UNTZfj4ubIyLUP2OVYBdhsC7P+AujKuMz3+xTLJL7AHFq0yLw3uITpE1usp1lj05MlLu5pBwPr/n737gJOiSBs4/AKbiEtmyRmRJIigIhIUUEE9DKh4CqIih1kRlcOAeoZTUc9wJ3xmT8UAYlYEA4oRRUFAUIKSc84L/dVbXA+Tdmd2d2and+bf/tbprq5OT+0WM+9UKJ8hd5v1rPQyBb7tCplpouMoZpsJVFgQQACBVBLw3CQg+eGnpaVJv3797M/OnTvteIAvv/yyfPzxx3ZcwLlz5+Z3OPsQQAABBBBAAAEEEEAAAU8K3DRxtp2t1r25Txesk19NALCqCXb5L5WDtv336XqTGuXly9/XByeH3f5L+zomf4Ww+7yYeHKbHNEfFgQQQACBgguUiBaA4R4rKytLqlWrJlWqVJGMjMB/FMPlJw0BBBBAAAEEEEAAAQQQ8JrAAdMyT2fm/XjempBbW7Vlt8xdGTizb6QWgGcdWS/kPHkl1KsS2F04r3ykI4AAAgiUfIES1QJQub/99lt56aWX5LXXXpN169bZEnDHyahdu3bJLxGeAAEEEEAAAQQQQAABBFJC4PWZy+QO0z13+57cqJ83v0lA9CRHmO6trw071nYnjnTSupULNolGpPOxHwEEEEDAuwIlIgC4YMECG/TT7r5Lliyxmm7Qr1KlSnLmmWfKX//6VzspiHepuTMEEEAAAQQQQAABBBBA4KDAVNPib+QbswvMUTdoko9wJ+jcuKpoS8CJPy63uzPSSku35jVk6vzAVoZ1aQEYjo80BBBAICkFPBsA1Ak/XnnlFRv4++mnnyy+G/TTLr+nnHKKDfqddtppkpkZOiV8UpYWD4UAAggggAACCCCAAAJJIfDoJ78V+DlOal1LGlUPneQj3InGnN7Kjge4Zutu+evRDc2Mt+Wky32fiE42okuGmVRDZwBmQQABBBBIDQHPBQCffvpp0ZZ+06dPlwMHDtiZfrUodGaqbt262aDfgAEDpHLlysVWQjNnzpT3339fvvzyS5k3b57tepyeni516tSR4447Ti655BLRmYqjXT744AMZP368fP/99/ZcNWrUkE6dOslll11mA5vRnCc3N1eeeuopGyD99ddfZfv27fZ+evXqJVdffbW0bt06mtPI+vXr5dFHH7UTqixdutQe06hRI+nfv79cc801dpzFqE5EJgQQQAABBBBAAAEEUlxg1p+bZPKsFfLb2u3Spm62nGImrOjQoEqISu7+AzIvaGy/kEz/SyhtJujtalrvnd2xnpzaNvohjypmpcsVPZsFnFZn/L3ipR9l1779ckOfw6RGRRpSBACxgQACCCSxQCnTqi78fPAJeujSpUvbYJ97W23btrVBv4EDB0r9+vWL/a406PjFF19EvO6gQYPk//7v//KdkEQDmhrk0yBnXsull14q48aNE3XIa9GgXd++fW0AMVwebRH5+OOPi54rv0XHU9RA3+rVq8Nm0zEVJ0+eLJ07dw67vyiJy5cv95XnsmXLpF696AcrLsp1ORYBBBBAAAEEEEAAgXgILN+0U3o88Jnkmkk9/Je2JhB4RP1sObpxNTntiDp219L1O6THg5/5Zwu73uvwWvLPs9pKtQqxC9Tp56w9uQckK71M2GuSiAACySfA5+/kK9PCPJHnWgDqQ2igTwN+Oq5fmzZtCvNcMTtm5cqV9lza2k9bHh5//PHSoEED2b9/v3z99dcyduxYWbFihbzwwguyb98+23oxr4uPHj3aF/zr0KGD3HjjjdK0aVNZtGiR3H///TJr1izbqk9bBN5zzz1hT6PXPeOMM3zBPx3/cOjQoVK1alU7Qco//vEPWbt2rQwbNkzq1q2bZ4tCDbpp92mdSCUtLU2uv/56OfXUU+013333XXnooYdEu2Frnh9++IEAXdjSIBEBBBBAAAEEEEAAgYMCOotvcPBP98xZscX+/PebP2XVll3SsWFV0ck/olmu7dU8psE/vab2rCL4F40+eRBAAIHkEvBcC0BtbadBNq8sGhTT1n1nnXWWlCkT+i2ZtsbTbsALFy60t/z555/brsrB96/7tVuudt096qijbBfnsmXL+rLt3LlTunfvLtrdWANy8+fPl2bNApvsa+ZnnnnGdjnW9csvv1yeeOIJXfUtv//+u3Ts2FG2bt1qj9fz6PmCF32mF1980SbrjMoa3PRfNO3cc8+1SYMHD5bnnnvOf3eR1/kGosiEnAABBBBAAAEEEEDAQwKXPj8zZJKNgtzeJV0bS06lLLn3g/mijQh7HV5T/m/QUTZgV5DzkBcBBBAIFuDzd7BIam7n3c80QR5eCv4pgbaGO+ecc8IG/3R/9erVbStAXdfljTfeOLgS9P9HHnnEBv80+bHHHhP/4J+mlStXzqbrugYJH374YV0NWR588EGbpi3+HnjggZD9GjQcNWqUTddg4JtvvhmSR7v8vvTSSzb9pJNOCgn+6Q59Zt2niwYK8+ombDPwPwQQQAABBBBAAAEEUlwgJ7vw3XTPPLKu3HpqKxnarYlMG9FD3ry8i4y/kOBfiv9K8fgIIIBATAU8FwCM6dMV08l69uzpu5J25w1edJyNt956yya3bNlSjjnmmOAsdlvTDzvsMLuu+d1xEN3M2opQW/TpogE6DRqGWy666CJfcrgA4Ntvv20nWNFMQ4YM8eUNXnHPo2MX6jEsCCCAAAIIIIAAAgggEF5gy67c8DuiSG1ao4IvV2Mzy69OHFJaZ/9gQQABBBBAIEYCBABjALlnzx7fWcJ1E16yZIm4YwlqN9/8Fne/jivozsrr5tdZiN3Fzedu+7/m5ORIixYtbNKMGTP8d9n1aM/jf41w5wk5MQkIIIAAAggggAACCKSowOade0Oe/MVLOssdp7cOSfdPyChTWk5rd3ByEP901hFAAAEEEIilQOjgcLE8e4qcS8f9c5fDDz/cXfW9zps3z7euLQDzW/z3a2u/xo0b+7IX9DzaYlAn+9ixY4eUL18+5DzZ2dmiwcK8Fp0FuFKlSnY8QbflYV55SUcAAQQQQAABBBBAIJUFNu4IDAD2blVLjm9eQ7o2qy7fLd0o781eZXnSy5SSt67oKmu37ZZfzAQhvVvlSINq4Xv2pLInz44AAgggEFsBAoBF9NTusffdd5/vLNo1N3jRATfdpV69eu5q2FedAdldNHjnvxTmPNqNWI9zuxbr+dzzRLoXzav3M3fuXBtI1O1oF/caeeXXGYZZEEAAAQQQQAABBBBIFoFNQQHA8zodfF+vs+4+dM4R0sR07V28boecY9Jb1akkraSS9DisZrI8Ps+BAAIIIOBxAQKARSwgnazju+++s2c588wz7Qy8wafctm2bL6lChUPje/gS/Vb8W+pt377db49IrM8T6V704u79BN9LwI2F2fAPZIbZTRICCCCAAAIIIIAAAkklsDGoC3CV8hm+58tMKyMj+hwc69uXyAoCCCCAAALFKEAAsAjY2vX35ptvtmeoWbOm/Oc//wl7tt27d/vSMzIOvRHwJfqtZGZm+rZ27drlW9eVWJ8n0r3oNd37Cb4X3ceCAAIIIIAAAggggEAqCuzau1+++G2dVMhMk2OaVJM9uQdk974DARRVyuX/vj8gMxsIIIAAAgjEWYAAYCGBtVvsGWecIbm5uZKVlSWvv/66aBAw3KL73WXv3sCxQdx099V/QpGyZcu6yfY1+Dz+2wEZzUak8+zcuVMi3Yue0z1P8L0EXy94O7j7cvB+7QLcuXPn4GS2EUAAAQQQQAABBBDwtEDu/gNyyfPfy1eLNtj7HNa9iQ0CBt90VQKAwSRsI4AAAggkUIAAYCHwdVbfPn36yKZNm0Rn/Z0wYYJ069YtzzNVrFjRty9SV1qdsMNdgrvoBp8nvwBgpPNoADDSveh9uOcJvhf3HvN6jWZ8wbyOJR0BBBBAAAEEEEAAAa8KTJq1whf803sc9/li++N/v2VKl5KKWXzU8jdhHQEEEEAgsQKlE3v5knf1lStXSq9evURfdUDfZ555Rv7yl7/k+yD+wbBIk2P4t5wLHkevMOfRe/Q/Tm/U3Y50L5rXvZ/ge9F9LAgggAACCCCAAAIIpJLAonXb5e735kd85MZmwo/SJgjIggACCCCAgFcESsTXUmvWrJFffvlFNm7caN2qVq0qbdq0kVq1ahWr4/r166V3796yePFie93HHntMBg0aFPEeWrVq5cvz66+/+tbDrfjvP/zwwwOyBJ+nffv2Afv9N9zzaODOncjD3a/n+eGHH2TLli2yevVqycnJcXcFvGo33a1bt9q04HsJyMgGAggggAACCCCAAAJJLrB2224Z/Mx3smXXvnyfNCu9tIw8iQk/8kViJwIIIIBAsQt4tgWg4zgybtw4adu2rdSpU8d2uT3vvPNEf7T7rabpvvHjx4vmjfeiwbKTTjpJ5s2bZy913333yRVXXBHVZRs3bmzvVzPrxCH5LdOnT7e769atK40aNQrI2rVrV992fufRoN7ChQtt3uOOO853jLsS7Xn8rxHuPO75eEUAAQQQQAABBBBAIJkFduzJlYuf+16WbwqcpM//mbXVnwb+Pruhp5zUOvwX7P75WUcAAQQQQKA4BTwZANSx9XRMvcsvv9wG3DTAF+5Hg3HDhw+3eTdv3hw3Nx0vr1+/fvLjjz/aa4wePVpuuummqK+n3XDdbsLaMu+bb74Je6ymuy33NL8e57+0aNFC3JZ4r732muh9hVuee+45X7JOVBK8nH766aZLwsGif/bZZ4N3+7bd82hePYYFAQQQQAABBBBAAIFUE1hsuv12u/9T+WXFwZ4x/s9fo2KmdGtRQ1669Gj5ZER3uaJnM8nJPjQBoH9e1hFAAAEEEEikQCkTWIt/87kCPKHeTvfu3eXLL7+0R1WrVk3OOeccOfroo31dVbWF23fffScaBNNuuRoo01Zt/i3WCnDJfLPqTLmnnXaaTJkyxea75ppr5JFHHsn3mHA7tUWedr3dv3+/HHXUUaIt/fxn1t21a5cNZM6cOVPS0tJs4LN58+Yhp9IxBy+55BKbri0QH3/88YA8ixYtkiOPPNJ23W3WrJnMnz/fni8gk9nQrssvvviiTdYZjM8+++yALJqm7roMHjxY3GBgQKYibOj4g+64gjrOoDsuYRFOyaEIIIAAAggggAACCMRU4NkZS+SOdw72API/cYOq5WTS5V2keoVM/2TWEUAAAU8K8Pnbk8VS7DfluQDgSy+9JBdeeKEN6p1//vny73//W/xnv/UX0llsNQimgSwNAv73v/+VgQMH+mcp8vpZZ50lkyZNsuc54YQTbPAvuGWe/0UyMjJEW+qFW0aNGiXadViXDh062FaETZs2FQ3a/fOf/5RZs2bZfZrvnnvusevB/9MAogZIZ8yYYXfp/Q0dOlSqVKlig6J33XWXrF271rbwe/fdd+WUU04JPoXd1qBbx44dZd26dTZAOGLECDn11FPtPj1u7NixkpubKzVq1LAtH2MdoKMCClssJCKAAAIIIIAAAgh4RGD99j3S5b5PZG/ugYA7qlIu3QT/jhPt8suCAAIIlAQBPn+XhFKK/z16LgCoXW0/+OAD6dGjh3zyySdRCfTs2dO2/tNg13vvvRfVMdFmyi/YF+4cDRs2lKVLl4bbJQcOHLDBOm3Fl9eirft0XEO3i264fNrqsW/fvvL999+H2y2ZmZm2ZeCll14adr+b+O2330r//v3tRCBumv+rTg4yefJk2/rSPz0W61RAsVDkHAgggAACCCCAAALxEnh02m/y0McHx9X2v8azF3WSni1r+iexjgACCHhagM/fni6eYrs5z40BqOPsadDtyiuvjBrhqquusnndFnRRH1jMGTWo9/TTT9sgpY7xpxOZaItBfdXt999/X5566ql8g396y9WrV5evvvrKto7Urs/aTTorK0uaNGliA4w6w2+k4J+eR7tVz5kzR2655RY7q3KFChVEf3RyFU3TmZc1DwsCCCCAAAIIIIAAAqkmMO3XtSGPfOaRdQn+haiQgAACCCBQEgQ81wJQW69p11MdC0+7yUazaOBPu7NqMG337t3RHEKeBAvwDUSCC4DLI4AAAggggAACCOQr0OHOKbJp5z5fnnOPqi/3nNlWypQOnKjPl4EVBBBAwKMCfP72aMEU8215rgVgdna2JVi5cmXUFKtWrbJ5K1WqFPUxZEQAAQQQQAABBBBAAAEEwgls35MbEPzTPEO7NSH4Fw6LNAQQQACBEiHguQBgmzZtLNyzzz4bNaCb1z026gPJiAACCCCAAAIIIIAAAggECazYtCsoRaRelbIhaSQggAACCCBQUgQ8FwA8++yzxXEcefPNN2XMmDF2PT9MnfV24sSJdtzAAQMG5JeVfQgggAACCCCAAAIIIIBARIHlm3YG5KlRMVOy0ssEpLGBAAIIIIBASRJI89rNDh06VB577DFZsGCBaHBv0qRJctFFF9nJKGrWrGkDfWvWrBGdwfb555+3E1XoM7Rs2dJOgOG15+F+EEAAAQQQQAABBBBAoGQJrNgc2AKQ1n8lq/y4WwQQQACBUAHPBQDT09Plgw8+kBNPPFGWLFkic+fOlZEjR4be+f9StLWgzn6rx6Slee5x8rxvdiCAAAIIIIAAAggggIA3BRau2RZwY/WqlAvYZgMBBBBAAIGSJuC5LsAK2KhRI5k9e7aMGDFCdFIQDfKF+9F9N9xwg/z000/SoEGDkmbP/SKAAAIIIIAAAggggIDHBFZt2SWvz1wecFeNq5cP2GYDAQQQQACBkibg2SZz5cuXlwceeEDuvvtu+eGHH2xX340bN1rfqlWrik740bFjR8nIyChp5twvAggggAACCCCAAAIIeExAGxy8O3uVXPXKrIA7K1O6lPylfZ2ANDYQQAABBBAoaQKeDQC6kBrgO/bYY+2Pm8YrAggggAACCCCAAAIIIBBLgTvemSfPfbU05JQDO9eXpjUqhKSTgAACCCCAQEkS8GQX4JIEyL0igAACCCCAAAIIIIBAyRb48c9NYYN/FTLT5NpeLUr2w3H3CCCAAAIIGAECgPwaIIAAAggggAACCCCAQEoLPDL1t7DPP7xHU6leITPsPhIRQAABBBAoSQIJ6wL8wgsv+JwGDRrkW/dP9yUWYMX/XAU4jKwIIIAAAggggAACCCCQggKL1m2X6QvXhTx5w2rl5JKujUPSSUAAAQQQQKAkCpQyg906ibjx0qVLS6lSpexPbm6u7xbcdF9CAVb0fP7nKsChZC1mgeXLl0v9+vXtVZctWyb16tUr5jvgcggggAACCCCAAAIIiDw0ZYE8+snvARSnH1FHRvc7XGpVygpIZwMBBBAoiQJ8/i6JpRb7e05YC0B9lLxij3mlx/7xOSMCCCCAAAIIIIAAAgikssCcFVsCHv+iLo1kzOmtA9LYQAABBBBAoKQLJCwAuGTJkrB2eaWHzUwiAggggAACCCCAAAIIIFAEgYVrtgcc3b5+5YBtNhBAAAEEEEgGgYQFABs2bBjWL6/0sJlJRAABBBBAAAEEEEAAAQQKKbB19z5ZsXlXwNGH5VQM2GYDAQQQQACBZBBgFuBkKEWeAQEEEEAAAQQQQAABBAos8NuabQHHpJUuJU1rVAhIYwMBBBBAAIFkECAAmAylyDMggAACCCCAAAIIIIBAgQUm/bgi4JjG1ctLRhofkQJQ2EAAAQQQSAoB/nVLimLkIRBAAAEEEEAAAQQQQKAgAovXbZcJ3y8LOOS4ZtUDttlAAAEEEEAgWQQSNgbgxRdfHHPDUqVKydNPPx3z83JCBBBAAAEEEEAAAQQQSC6BsVMWyv4Dju+hMk3Lv791b+rbZgUBBBBAAIFkEkhYAPC5554TDdjFanEcx56PAGCsRDkPAggggAACCCCAAALJKfDzss3y3pxVAQ835LjGkpOdFZDGBgIIIIAAAskikLAAYIMGDWIaAEyWAuE5EEAAAQQQQAABBBBAIH4C81Zulb88MSPgAtll02U4rf8CTNhAAAEEEEgugYQFAJcuXZpckjwNAggggAACCCCAAAIIeFpg/qqt0vfRL0Lu8fIeTSW7XHpIOgkIIIAAAggkiwCTgCRLSfIcCCCAAAIIIIAAAgggkK/AR3NXh+yvlJUmg45tFJJOAgIIIIAAAskkQAAwmUqTZ0EAAQQQQAABBBBAAIE8Bbbuyg3Zd0aHulI2o0xIOgkIIIAAAggkkwABwGQqTZ4FAQQQQAABBBBAAAEE8hTYk7s/ZN8wxv4LMSEBAQQQQCD5BBI2BmA0lBs3bpRnn31Wpk6dKr/88ovoti5Vq1aVNm3aSK9evWTIkCF2O5rzkQcBBBBAAAEEEEAAAQRSV2Bv7oGAh+/XtrbUqVw2II0NBBBAAAEEklHAswHAcePGyQ033CA7d+607o7j+PxXrFghK1eulClTpsiYMWNk7Nixctlll/n2s4IAAggggAACCCCAAAIIBAvsCQoANqxWLjgL2wgggAACCCSlgCcDgPfdd5+MHj1a3KBfdna2dOjQQXJycmwhrF69WmbNmiVbtmyRHTt2yPDhw2Xz5s1y4403JmUh8VAIIIAAAggggAACCCBQdIHgFoCZaYz9V3RVzoAAAgggUBIEPBcA1K6+t956qw3+1a5dWx544AEZMGCApKenB3jm5ubK66+/LiNHjrStAW+55Rbp16+ftG7dOiAfGwgggAACCCCAAAIIIICACgSPAZiRxpDo/GYggAACCKSGgOf+xXv88cdl//79UqNGDfn666/l/PPPDwn+adGkpaXJwIEDbZ6aNWvaY/RYFgQQQAABBBBAAAEEEEAgnMDe/YFjAGYSAAzHRBoCCCCAQBIKeC4A+Mknn0ipUqVk1KhR0qBBg4jk9evXl5tuusm2GJw2bVrE/GRAAAEEEEAAAQQQQACB1BTYsy8wAEgLwNT8PeCpEUAAgVQU8FwAUCf40KVLly5Rl8dxxx1n8+rEICwIIIAAAggggAACCCCAQDgBWgCGUyENAQQQQCAVBDwXACxT5uBAvDrGX7SLdhnWpXRpzz1OtI9APgQQQAABBBBAAAEEEIizAC0A4wzM6RFAAAEEPCvguYiZ2+23IN153bzusZ7V5sYQQAABBBBAAAEEEEAgYQKhLQCZBThhhcGFEUAAAQSKVcBzAcDevXvb8fwefPBBmTNnTkQMnTVYZwrWcQP79OkTMT8ZEEAAAQQQQAABBBBAIDUF9uw72HPIfXomAXEleEUAAQQQSHYBzwUAr732WsnMzJTt27dL165dRQOBGzZsCCkHTdN9xx9/vGzbts0eo8eyIIAAAggggAACCCCAAALhBEJbAHru41C42yYNAQQQQACBIgukFfkMMT5Bw4YNZdy4cTJkyBAbBNQZfm+++WZp3Lix1KxZ07b0W7NmjSxZssS2FHQcx6bpMXQBjnFhcDoEEEAAAQQQQAABBJJIgDEAk6gweRQEEEAAgQIJeC4AqHc/aNAgqVatmgwbNkx0Zl8N8i1atEgWL15sH0633aVOnToyfvx46du3r5vEKwIIIIAAAggggAACCCAQIrBn/4GAtMw0xgAMAGEDAQQQQCBpBTwZAFTtfv36ydKlS+XNN9+UqVOnio71t3HjRlsQVatWlTZt2kivXr2kf//+kp6enrQFxIMhgAACCCCAAAIIIIBA0QW0EcHe3MAAYEYaXYCLLssZEEAAAQRKgkDCAoCzZ8+2Pi1btpSMjIywVmlpaTJgwAD7EzYDiQgggAACCCCAAAIIIIBAFALB4//pIUwCEgUcWRBAAAEEkkIgYQHA9u3bS+nSpUUDga1atfJh3nnnnXb98ssvl+rVq/vSWUEAAQQQQAABBBBAAAEECisQ3PpPz0MLwMJqchwCCCCAQEkTSFgAUKH8x/Jz4caMGWMn9Tj77LMJALoovCKAAAIIIIAAAggggECRBPYEdf/VkxEALBIpByOAAAIIlCCBhA164Y7bt2vXrhLExa0igAACCCCAAAIIIIBASRQI1wKQLsAlsSS5ZwQQQACBwggkLABYq1Yte78//PBDYe6bYxBAAAEEEEAAAQQQQACBqAVoARg1FRkRQAABBJJQIGFdgLt16yYvv/yy3HTTTbJo0SJp0aJFwGy+b731lsycObPA5IMGDSrwMRyAAAIIIIAAAggggAACyS0QrgVgRpmEtYdIbmyeDgEEEEDAcwKlzDh8TiLuau7cudK5c2fRLsClSpXy3YJ7O/5pvp0RVvSY3NzcCLnY7QWB5cuXS/369e2tLFu2TOrVq+eF2+IeEEAAAQQQQAABBJJUYPbyzXL64zN8T6fj/y38xym+bVYQQACBZBXg83eylmzBnithLQBbt24t06dPl1GjRtnXvXv3Bty5GwgMSGQDAQQQQAABBBBAAAEEEIhCYP8BRz6au1pm/bnJ5k4Pau3H+H9RIJIFAQQQQCBpBBIWAFTBjh07ypQpU2yrvfXr18vu3bulSZMmtkXgRx99JM2bN08aaB4EAQQQQAABBBBAAAEEikfggAn+nTf+a/l+6cHgX7irEgAMp0IaAggggECyCiQ0AOiipqWlSU5OjrtpX+vUqSMNGzYMSGMDAQQQQAABBBBAAAEEEIgk8M2SDfkG//T4zLQykU7DfgQQQAABBJJGwBMBQH/N22+/3W7WrFnTP5l1BBBAAAEEEEAAAQQQQCAqgUXrdkTMt277noh5yIAAAggggECyCHguANizZ09rW758+aiNtevwd999Z/Pr7MIsCCCAAAIIIIAAAgggkLoCqzbvivjwTapH/3kj4snIgAACCCCAgMcFPBcA7NGjh5QuXVpmz54trVq1iopvxYoV4h7HLMBRkZEJAQQQQAABBBBAAIGkFVi1ZXfAs13UpZHUqJgpD3y0wJfeqVFV3zorCCCAAAIIJLuA5wKACl7YGYALe1yyFzLPhwACCCCAAAIIIIBAKgmsDGoBWK9KWbn0+CbSoGo5efHrP6RhtXJyQ5/DUomEZ0UAAQQQSHEBTwYAC1omBw4csIeUKcNAvgW1Iz8CCCCAAAIIIIAAAiVZYPe+/bLatPirWSlT1m3bI4vX75Bvl2wMeKTa2WXt9mlH1BH9YUEAAQQQQCDVBJIiAPjHH3/YcsvOzk618uN5EUAAAQQQQAABBBBIGYFde/fL1t37pFalLPvM781eJSPf+Fl2mvT8ltqVD+bPLw/7EEAAAQQQSGaBhAcA//zzz7C+q1atkgoVKoTd5ybu2bNHFi1aJLfeequUKlVKWrdu7e7itQACGkB99NFH5b333pNly5ZJZmamNG3aVM455xy54oorpFy5cgU4G1kRQAABBBBAAAEEEIi9wFe/r5ehL8yUHSbYd2aHunJa+zpyzYRZknvAiXixOv9rARgxIxkQQAABBBBIUoGEBwAbN24cQqtj+fXp0yckPVLCoEGDImVhf5DAO++8IxdccIFs3brVt2fnzp0yc+ZM+/PUU0/ZwGCzZs18+1lBAAEEEEAAAQQQQKA4BfTzwejJv9jgn1530qwV9ieae8gxrQV1AhAWBBBAAAEEUlmgdKIfXv8x9/9x78c/LdK6tlgbOXKkXHzxxZrCGl8AAEAASURBVO7hvEYhMGvWLDn33HNt8E9bW959993y1VdfybRp02To0KH2DAsXLpR+/frJtm3bojgjWRBAAAEEEEAAAQQQiL3A9N/WyxIztl+0S/UKGVKmdCmpXC5dbjutlV2P9ljyIYAAAgggkIwCCW8B+Oyzzwa4DhkyxHbnveuuu6Ru3boB+/w3tMtvVlaW1K5dWzp06BCxu7D/sawfFLjmmmtk165dkpaWJlOmTJFjjz3WR3PCCSdI8+bN5cYbbxQNAo4dO1bGjBnj288KAggggAACCCCAAALFIbDCzOh78XPf53upzLTSckS9ynYikJtPaSn1qpSTA6Zr8N79ByQrnYkC88VjJwIIIIBASgiUMq3rIg+aUYwUpUuXtgHAOXPmSKtWrYrxyql1qe+++06OPvpo+9DDhg2TJ598MgRAZ1du06aNzJ8/XypXrixr166V9PT0kHyFSVi+fLnUr1/fHqrjDtarV68wp+EYBBBAAAEEEEAAgSQW0I8qGvz7dMG6PJ/y+ObV5enBnSTDBAFZEEAAAQRCBfj8HWqSiime+1fy008/Ff0JNzZgKhZQvJ558uTJvlNrq8twiwZj3XEVN2/ebMslXD7SEEAAAQQQQAABBOIvsHHHXnn52z/li9/yDobF/y6K9wpT56/NN/jXtm62/OeCjgT/irdYuBoCCCCAQAkUSHgX4GAzNxh1/fXXy5VXXhm8m+0YCXz55Zf2TOXLl5eOHTvmedbu3bv79s2YMaNQk7P4TsAKAggggAACCCCAQKEEtu/Jlb888aUs27jLHn/bqa3k4q6hk+kV6uQePWiXme13zNtzA+6uYmaaPHJeexMEXW/H9xt6fBMpb9JYEEAAAQQQQCB/Ac/9a6lNU/fv3y/t27fP/87ZWyQB7dari87uq2MA5rW0bNnSt8s9xpeQYivPf7U0xZ6Yx0UAAQQQQAABLwiYuSzkJdPyzw3+6T29NnNZ0gcA//PZ76Lj//kvd/VvIyceXsv++KezjgACCCCAAAL5C+Qd+cn/uLjtzcnJkRUrVkjZsmXjdo1UP/Hu3btl/fr1liHS2HtVqlQRbSW4Y8cO0bH6ol00kJvfsmrVqvx2e3LfmHfmmhmrPXlr3BQCCCCAAAIIpJjAr6u3JfUT6wQez3/9R8Azdm5cVf7Svk5AGhsIIIAAAgggEJ2A5wKAOjHFpEmTZO7cufl2TY3u8cgVTmDbtkNvGCtUqBAuS0CaGwDcvn17QHp+G+4EH/nlYR8CCCCAAAIIIIBA4QVyzQy3aWU8N6R31A/0y4otpmXjH1KzYpb8rXtTKZtxaLbe5Zt2yZZd+wLONea01naywIBENhBAAAEEEEAgKgHPBQCHDx8uEydOlIcfflgGDhwYs1lno9JIkUzaAtBdMjIy3NU8XzMzM+2+XbsCu2DkeQA7EEAAAQQQQAABBOIusGnnPqlR8eD7tLhfrAgX2JO7X/796SL58JfVUqlsmmg33tnLtsjf35wjuaalny5L1u+QRwd28F1l4ZpDX1hrYnbZdDm8dkXfflYQQAABBBBAoGACngsAnnDCCTJq1Ci599575dRTT5WnnnpKaE1WsEKNlDsrK8uXZe/evb71vFb27NljdxWkW3ak7sLaBbhz5855XdKT6cc0riaO+Y8FAQQQQAABBBAoToHc/Y6s2bY7YAxAvb7OCuz1AOB+E+C79PmZdtIO1+zkR75wV32vb/+8UlqaAN/lPZrZtN/WBvY8aVGrAq3/fFqsIIAAAgggUHABzwUA77zzTtEWZ23btpWPP/5YmjRpIscdd5y0a9dOdDy6MmUOdQ0I97i33XZbuGTS/AQqVjz07Wk03Xp1/D9douku7F4m0tiCbr6S9PrKZceUpNvlXhFAAAEEEEAgyQTajflItu7O9T2VBgC9vvxr2m8Bwb/87vf+DxdI+3qVpUuz6vJbUAvA5rUOvX/N7xzsQwABBBBAAIHwAp4LAI4ZM8b37V6pUqXsjMBffPGF6E80CwHAyEraArBatWqyYcMGiTRZx6ZNm+wEIHpWWmJGtiUHAggggAACCCAQL4FqFTJLVABw/PRF8qgJABZkedXMblwxK10mzVoRcFjzmpHHrQ44gA0EEEAAAQQQCBDw5KjBjplq1f3Ru3XXo3kNeDo28hRo1aqV3ff7779Lbu6hb5KDD/j11199SYcffrhvnRUEEEAAAQQQQACB4hWoWj5w7OaNOw4O01K8dxH5avqe/akvFss97x96Hxn5qIM5tCvwaY9/GZK9nWkZyIIAAggggAAChRfwXADwwIEDUpSfwlOk1pFdu3a1D6zde3/44Yc8H/7zzz/37dOu2CwIIIAAAggggAACiREIDgBu8GgX4Ac+WiD/eG9+vkjlzYy/L17SWd68vEtAPhM7DFnqVy0rHeoTAAyBIQEBBBBAAIECCHguAFiAeydrEQT69+/vO/rZZ5/1rfuvaCD2hRdesEmVK1eWnj17+u9mHQEEEEAAAQQQQKAYBaqFtAD03hiAv6/dJv/+bFGIyt/7tpSTWtey6bUqZcozF3WS45vXkCNMy77K5dJD8vsnnNmhnpQuXco/iXUEEEAAAQQQKKCA58YALOD9k72QAjoD7/HHH2/HVnz66adl8ODBcuyxxwacbezYsTJ//sFvb6+55hpJT8//zVnAwWwggAACCCCAAAIIxFSgSlAAcO1Wb3UB3rZ7n/R6aHrIM4886TC5rFtTm75h+x6pkJUmmWkHJ/bTwF6vw2vJGz8sDzlOE9rVy5Zh3ZuE3UciAggggAACCEQvQAAwequky/mvf/3LzrC8a9cu6dOnj/z973+3rfx0e8KECTJ+/Hj7zC1atJARI0Yk3fPzQAgggAACCCCAQEkSaFi1XMDt/rp6a8B2ojfuDtPt9+TWOXJFz2a+W9OJTIIXDRBqYHDx+h3S3nT1Peeo+nJ046qydtseqZ2d5ZsgMPg4thFAAAEEEEAgegFPBwA3btwo2j116tSp8ssvv4hu61K1alVp06aN9OrVS4YMGWK3o39kcroCHTp0kFdffVUuuOAC2bp1qw0AuvvcVw3+vffee1KxYkU3iVcEEEAAAQQQQACBBAi0qZsdcNWlG3aaWYH3SSUza64Xlq8Xbwi5jWha79WqlCXPDukccmydymVD0khAAAEEEEAAgcIJeHYMwHHjxknDhg3lxhtvlClTpsiKFStEW6bpj65rmu7TPG5LtcIRpPZRp512msyePVuuu+460WBfuXLlRMf7O+qoo+Sf//ynzJo1S5o1O/StbWpr8fQIIIAAAggggEDiBJrXqiDpZQLHwpu30hutAA8ccGTV5t0BODp5h7boY0EAAQQQQACBxAt4sgXgfffdJ6NHjxbnf9OAZWdni7ZWy8nJsWKrV6+2gaktW7aIzmI7fPhw2bx5sw0IJp605N2BBlEfeugh+1Py7p47RgABBBBAAAEEUkNAx81rUauizPUL+s1evlmOaVItoQD6nn2d6cK7d/+BgPt49bJj6b4bIMIGAggggAACiRPwXABQu/reeuutNvhXu3ZteeCBB2TAgAEhE1Dk5ubK66+/LiNHjpSVK1fKLbfcIv369ZPWrVsnTpMrI4AAAggggAACCCAQR4F2ZtZc/wDgF7+t902wEcfL5nnq12cuk9vfnis79+4PyJNmJvfQrr0sCCCAAAIIIOANAc91AX788cdl//79UqNGDfn666/l/PPPDwn+KV1aWpoMHDjQ5qlZs6Y9Ro9lQQABBBBAAAEEEEAgWQW6Na8e8GhfL9ogV778o3y2YG1AenFs7NiTK2PCBP/02hr8K2OCgCwIIIAAAggg4A0BzwUAP/nkE9tVYNSoUdKgQYOISvXr15ebbrrJthicNm1axPxkQAABBBBAAAEEEECgpAocZwKA2rrOXXLN2Hvvzl4lFz37vbz87Z9ucrG8Ll63Q3YEtfxzL1ynMq3/XAteEUAAAQQQ8IKA5wKAOsGHLl26dIna57jjjrN5tSswCwIIIIAAAggggAACySqgM/4eH9QK0H3WV0133OJcVmzeleflamczg2+eOOxAAAEEEEAgAQKeCwCWKVPGMugYf9Eu2mVYl9KlPfc40T4C+RBAAAEEEEAAAQQQiEpgzOmtpWPDKiF5V2zaGZIWz4T8AoD1qhAAjKc950YAAQQQQKCgAp6LmLndfgvSndfN6x5bUATyI4AAAggggAACCCBQUgQaVisvE4d3kVcvOybgltdv3yt7cwNn4g3IEOONlXm0ANQuyqe2qxPjq3E6BBBAAAEEECiKgOcCgL1797bj+T344IMyZ86ciM+mswbrTMGlSpWSPn36RMxPBgQQQAABBBBAAAEEkkHgsJyKIY+xdtvukLR4JQQHANvXrywjereQSZd3kVZ1KsXrspwXAQQQQAABBAoh4LkA4LXXXiuZmZmyfft26dq1q2ggcMOGDSGPpmm67/jjj5dt27bZY/RYFgQQQAABBBBAAAEEUkEgu2y6ZKYFvp1fszVxAcCzO9aTq05sLu3qVU4Ffp4RAQQQQACBEiWQ5rW7bdiwoYwbN06GDBlig4A6w+/NN98sjRs3lpo1a9qWfmvWrJElS5bYloKO49g0PYYuwF4rTe4HAQQQQAABBBBAIF4C2gMmJztL/thwaOy/VVsKHgDcvidXnvpisXy2YJ3oBMNpZUpLeplSclitStK3bY4c2aCKGWv70MzD7vMs3xQ4CUjdyoz759rwigACCCCAgNcEPBcAVKBBgwZJtWrVZNiwYaIz+2qQb9GiRbJ48WLrp9vuUqdOHRk/frz07dvXTeIVAQQQQAABBBBAAIGUEKhVKTAAeOXLs6Rvm9phA3Z5gVw74SeZOn9NyO4Zv2+QZ2YskdomyHh5z2ZywdEN7BfvmnGtaWm4YcfegGPqVy0XsM0GAggggAACCHhHwJMBQOXp16+fLF26VN58802ZOnWq6Fh/GzdutHJVq1aVNm3aSK9evaR///6Snp7uHVHuBAEEEEAAAQQQQACBYhLIMQHA4EWDeX1a59jk/QccKROm9Z57zO9rt4cN/rn79VVbFd46+RfZaVoKDuve1O6as2KLfxYpn1FGmlQvH5DGBgIIIIAAAgh4R8CzAUAlSktLkwEDBtgf75BxJwgggAACCCCAAAIIeEOgQZhWd7OWbZajGlWVy16YKXNXbjXdeGvLbae1Eh0zMHh5beay4KQ8t1//YXmeAcDWdbIL1Oowz4uwAwEEEEAAAQTiIhA4anBcLsFJEUAAAQQQQAABBBBAIB4COvFG8KJj8/3j3Xky849Nsmvffpn443K58OlvZd/+AwFZ9+YekIkmqBduMcMLmu6+gXu0teCWXfts4i9BLQDb1M0OzMwWAggggAACCHhKoMQEAHNzc2XdunX2R9dZEEAAAQQQQAABBBBIdYFGptvtsG5NAhg0UPfBL6sD0mYv3yL647988uuakHH83P039DlMFtx1irvpe/3ZtC7UJbgLcNt6lXx5WEEAAQQQQAAB7wl4OgA4b948ufrqq6VVq1aSlZUlOTk59kfXDz/8cLnqqqvs2IDeY+WOEEAAAQQQQAABBBAoHoFOpruv/zJ/1Vbb8s8/Tdd14g7/ZcL3gd1/m9WsIPef3U4mXHaMXGEm/chIK21mAK7sf4jM+nOzrN22W9Zs3ROQ3pYWgAEebCCAAAIIIOA1AU+OAXjgwAEZOXKkPProo6Lr/rP+KqBuL1iwQBYuXChPPvmkXHnllTJ27Fgz7oin45leK3vuBwEEEEAAAQQQQCAJBOpWKRvVU2z+X/fdT39dK9e99pNs3nmwO697sLYkHHBUfXfTvnZoUEV+NEE/d3l46kKpUTHT3bSv5cwEII2rVwhIYwMBBBBAAAEEvCXgyQDg+eefL6+//rov8Ne6dWvp3Lmz1KpVy+qtWbNGvv/+e9v6b//+/TZQuHLlSnn11Ve9pcvdIIAAAggggAACCCAQZ4GoA4Am4Kfj/l0fJvhXITNN+rWrHXKnHYJaAGqGv785JyBf6zqV8p1pOCAzGwgggAACCCCQEAHPBQAnTJggr732mhl0uJQcccQRMn78eOnUqVNYHA0C/u1vf5NZs2bJG2+8IXrseeedFzYviQgggAACCCCAAAIIJKNApax0qZSVJlt35z9O9uZde+XPjTtlU1DLPzU5o0NdKZcR+tHgSNMCMNLCBCCRhNiPAAIIIIBA4gU812dWA366tGjRQr788ss8g3+aRwOD06dPl8MOO8y2Fhw3bpwmsyCAAAIIIIAAAgggkFICzWtVjPi8W0zgb/POvSH5ehxWQ0b0aRGSrgm1s7NscDHszv8lHt24Wn672YcAAggggAACHhDwXADw559/tq3/brrpJilfvnxEIs2jeXXRY1kQQAABBBBAAAEEEEg1gQ71AyfrCPf8Oubfxh2hAcDnhnSWyuUywh1i35f3bpUTdp+beEyTwElI3HReEUAAAQQQQMA7Ap4LAO7de/BNSbt27aJWcvPu2xc4kHHUJyAjAggggAACCCCAAAIlWEAn64i0aBfg4Ik/2tStFOkwua53czm8dvh8Ov5fXsHDiCcmAwIIIIAAAggUm4DnAoANGza0D79ly5aoEbZu3WrzusdGfSAZEUAAAQQQQAABBBBIAoFwk3X0b18n4Mm+WbxRZixaH5BWJY+Wf/6Z6lUpJ+9f3VUW/ONkmTi8i2SlH/oIMbhLI/+srCOAAAIIIICARwUO/evtkRs866yz7Hh+EydOjPqOdAIQnTTkjDPOiPoYMiKAAAIIIIAAAgggkCwCdSqXlV6H1/I9jnbLPe2IwACg7nzrp5W+PLoSTQBQ8+l77cy0MtKxYRV57+rj5caTD5NnL+okAzrW090sCCCAAAIIIOBxgdCpvhJ8w9dff7289NJLohN6dOvWTc4555x870iDf5q3cePGcsMNN+Sbl50IIIAAAggggAACCCSrwCPntZeJPyy3j9e/fV1ZtH57xEetUi49Yp7gDE1rVJDLezQLTmYbAQQQQAABBDws4LkWgNnZ2TJ16lQ58sgjZeDAgdK/f3+ZPHmyrFixQnSMv9zcXLuuadri79xzz7V5p02bJnosCwIIIIAAAggggAACqShQITNNtEuu/mSbwF7lspGDe4zfl4q/KTwzAggggEAqCniuBWCZMmV85eA4jrzzzjv2x5cYtKJ5Zs6cKU2aNAnac2hTuyxo4JAFAQQQQAABBBBAAIFUEahWPjPio1YtH37234gHkgEBBBBAAAEESpSA51oAakDP/VFJdz2v12jy6LEsCCCAAAIIIIAAAgikkoC2AuzarHq+j1y5EF2A8z0hOxFAAAEEEEDAkwKeawF4++23exKKm0IAAQQQQAABBBBAoKQJjLuwo1z9yiyZ9uvasLce7SQgYQ8mEQEEEEAAAQRKjAABwBJTVNwoAggggAACCCCAAAIFEyhvxgV84q9HStsxH8m+/aG9YqpXiNxNuGBXJDcCCCCAAAIIeFHAc12AvYjEPSGAAAIIIIAAAgggUFIFstLLSNu64SfLa1y9fEl9LO4bAQQQQAABBAogQACwAFhkRQABBBBAAAEEEECgJAp0blwt5LbrVi4rZTMOTcAXkoEEBBBAAAEEEEgaAQKASVOUPAgCCCCAAAIIIIAAAuEFOjeuErKjftWyIWkkIIAAAggggEByChAATM5y5akQQAABBBBAAAEEEPAJdGxY1bfuruzad8Bd5RUBBBBAAAEEklyAAGCSFzCPhwACCCCAAAIIIIBAdtl0yamUFQAxoGO9gG02EEAAAQQQQCB5BQgAJm/Z8mQIIIAAAggggAACCPgEruvd3LdeMStN+rat7dtmBQEEEEAAAQSSWyAtuR+Pp0MAAQQQQAABBBBAAAEVOOeo+lI7u6wsXLNNTjHBv6rlM4BBAAEEEEAAgRQRIACYIgXNYyKAAAIIIIAAAgiktkCpUqWkW4sa9ie1JXh6BBBAAAEEUk+ALsCpV+Y8MQIIIIAAAggggAACCCCAAAIIIIBACgkQAEyhwuZREUAAAQQQQAABBBBAAAEEEEAAAQRST4AAYOqVOU+MAAIIIIAAAggggAACCCCAAAIIIJBCAgQAU6iweVQEEEAAAQQQQAABBBBAAAEEEEAAgdQTIACYemXOEyOAAAIIIIAAAggggAACCCCAAAIIpJAAAcAUKmweFQEEEEAAAQQQQAABBBBAAAEEEEAg9QQIAKZemfPECCCAAAIIIIAAAggggAACCCCAAAIpJEAAMIUKm0dFAAEEEEAAAQQQQAABBBBAAAEEEEg9gbTUe2Se2AsCubm5vttYtWqVb50VBBBAAAEEEEAAAQQQQAABBBCInYD/Z27/z+KxuwJnKgkCBABLQikl4T2uW7fO91SdO3f2rbOCAAIIIIAAAggggAACCCCAAALxEdDP4o0aNYrPyTmrpwXoAuzp4uHmEEAAAQQQQAABBBBAAAEEEEAAAQQQKJpAKccsRTsFRyNQcIHdu3fLnDlz7IE1atSQtDRvN0bVJtNuS8XvvvtOateuXfCH5oiYCFAWMWGM6Ukok5hyxuRklElMGGN2EsojZpQxOxFlEjPKmJ2IMokZZZFPRFkUmTAuJ6Bc4sJapJOWpDLRbr9uL7y2bdtKVlZWkZ6dg0umgLejLiXTlLuOQkArnE6dOkWR03tZNPhXr149791YCt4RZeG9QqdMKBPvCXjrjvgb8VZ56N1QJpSJ9wS8c0f8fXinLPzvhHLx1/DGekkoE7r9euN3JZF3QRfgROpzbQQQQAABBBBAAAEEEEAAAQQQQAABBOIsQAAwzsCcHgEEEEAAAQQQQAABBBBAAAEEEEAAgUQKEABMpD7XRgABBBBAAAEEEEAAAQQQQAABBBBAIM4CBADjDMzpEUAAAQQQQAABBBBAAAEEEEAAAQQQSKQAAcBE6nNtBBBAAAEEEEAAAQQQQAABBBBAAAEE4ixAADDOwJweAQQQQAABBBBAAAEEEEAAAQQQQACBRAoQAEykPtdGAAEEEEAAAQQQQAABBBBAAAEEEEAgzgKlHLPE+RqcHgEEEEAAAQQQQAABBBBAAAEEEEAAAQQSJEALwATBc1kEEEAAAQQQQAABBBBAAAEEEEAAAQSKQ4AAYHEocw0EEEAAAQQQQAABBBBAAAEEEEAAAQQSJEAAMEHwXBYBBBBAAAEEEEAAAQQQQAABBBBAAIHiECAAWBzKXAMBBBBAAAEEEEAAAQQQQAABBBBAAIEECRAATBA8l0UAAQQQQAABBBBAAAEEEEAAAQQQQKA4BAgAFocy10AAAQQQQAABBBBAAAEEEEAAAQQQQCBBAgQAEwTPZRFAAAEEEEAAAQQQQAABBBBAAAEEECgOAQKAxaHMNRBAAAEEEEAAAQQQQAABBBBAAAEEEEiQAAHABMFzWQQQQAABBBBAAAEEEEAAAQQQQAABBIpDgABgcShzDQQQQAABBBBAAAEEEEAAAQQQQAABBBIkQAAwQfBcFgEEEEAAAQQQQAABBBBAAAEEEEAAgeIQIABYHMpcAwEEfAJ79uzxrbOCAAIIlAQB6q2SUErcIwII+AtQb/lrsI4AAgggoAIEAPk9SHoBx3GS/hlLwgNu3rxZzj//fPtTEu6Xe0QgkQLUW4nUP3Rt6q1DFqwhEEmAeiuSUPHsp94qHmeuUvIFqLNKfhnyBAUXSCv4IRyBQMkQmDx5svTv379k3GyS3+XDDz8so0ePlt27d9snnTdvnrRq1SrJn9r7j/fOO+/IunXrZMeOHdKmTRtbJrVq1bI3fuDAASldmu+IirsUqbeKWzzv61Fv5W2TyD3UW4nUD39t6q3wLolIpd5KhHr+16TOyt8nEXupsxKhzjU9I2Ai3ywIJJWA+YfWadasmVOqVClnypQp9tn27duXVM9YUh7m/fffdw477DBbFloeJ598svPWW285e/fuLSmPkJT3+eGHHzpHHXWULZdy5crZVxPsc1q2bOnccccdTm5ublI+t5cfinrLO6VDveWdsvC/E+otfw1vrFNveaMc9C6ot7xTFu6dUGe5Et55pc7yTllwJ4kTkMRdmisjEFsB05LJuf76633BJg04tWvXzncR06LJt85KfAV+/fVXp1+/fr6y0CDg+PHjnY0bN8b3wpw9X4H169c7V155pa9cGjZs6HTr1s1p27atk5WV5Uu/9NJLnZ9//tmei7+bfEmLvJN6q8iEMTsB9VbMKGN6IuqtmHLG5GTUWzFhjMlJqLdiwhjTk1BnxZQzJiejzooJIydJEgECgElSkKn6GG5wYtmyZc6NN97o1KhRwylTpoxTuXJlJzMz0wY0/v3vf1seWgHG/7fEdCV1hg8f7gskVaxY0TFdf53FixfH/+JcIaLAY4895lSqVMkpW7asM3LkSOeXX35xVq1aZY/74IMPnHPOOceWXXp6unPqqac6ixYtsvv2798f8dxkiF6Aeit6q+LISb1VHMqFvwb1VuHtYnkk9VYsNYt+LuqtohvG6wzUWfGSLdh5qbMK5kXu1BEgAJg6ZZ20T6rdFbXln9uCSVubXXXVVU69evVsMEMDHvpGSRcCGfH7Ndi2bZtz9tln+4J/GkCaP3++Y8b9C7io+w+y+xqwk424CXzzzTdO1apVbflcfPHFjn5DHbz8/vvvTo8ePWyejIwM56yzzgrOwnaMBKi3YgRZxNNQbxURMM6HU2/FGbiAp6feKiBYnLJTb8UJNganpc6KAWIMT0GdFUNMTpU0Aozw7pnRGLmRwgqYcU/EtPKTPXv2iOnOKLr96KOPSq9evcSMbybmjZKMGjWqsKfnuCgFKlSoIKeccoo0b97cHpGWliZmTDkxLTHttgn4if6Yrtl2232N8vRkK6LAV199JZs2bZKcnBw7IUu1atV8ZzT/otn1pk2byi233GLXTYtZmTRpkjz//PN2283jO4iVIglQbxWJL2YHU2/FjDIuJ6LeigtroU9KvVVoupgeSL0VU86Ynow6K6acRT4ZdVaRCTlBEgqUGWOWJHwuHimFBDSgYVozSceOHeX++++XJk2a2KevXbu2fPrpp7Jhwwb57rvv5NxzzxXTRVhMK0BmN43x74cGhzSgZyZfkTlz5ogZk0bmzp0r7du3t0HAXbt2iWlRZvOYcThk+vTpsnz5cvnpp5/EdDcV0zItxnfE6fwFNPCqfxsLFiywAcDLLrtM9AOEu/gHY033eZk9e7aY1oB2t/k2WwYOHCimJa2bndcYCFBvxQCxiKeg3ioiYJwPp96KM3AhTk+9VQi0GB9CvRVj0BiejjorhpgxOhV1VowgOU1yCZh/SFgQ8LSA+QfV3l+47rvuPh0E+bfffgt5Dh1/TscDNAEO56STTgrZT0LBBFzv/MpCZ14+4ogjrLkJyvq6XZsWms7dd9/tmBaCvu7ZWi76M2DAAN+MzQW7I3KrQDTlMnjwYGutXeSDu2X7K+7cudM3gYs7juaIESNslnDl7n8s64cEoikT6q1DXvFci6YsqLfiWQLhzx1NuVBvhbeLV2o0ZUK9FS/9wPNGUxbUW4Fm8d6Kpkyos+JdCoHnj6ZMqLMCzdhCgBaAyRXPTcqnMZW7bbHn30rJ/Ona1mRuWvXq1QNakekxus8EO2TatGmyevVq26JJWwm2aNFCzJgQtAIsxG9LNGWh3UiXLl0qZoIJ+6pdTc3ELGLGlrNdSs1MwLYrsJaBmSRE9u7dK/PmzZOPPvpIzKy0thWhdh9miV4gUrmo9ddff21bXK5Zs0bMrL/SunXrsK1htUXmCy+8IGYCEPs3ZQKC9lgzM7BkZ2fruLH2byv6u0vNnJHKRFWot4rndyOasqDeKp6y8L9KpHKh3vLXKp71SGWid0G95Z2yoN4qnrJwrxLp74M6y5UqvtdIZaJ3Qp1VfOXBlUqGAAHAklFOKXmXP//8szz44IPy7rvvyosvvihmpl/RwFDdunUjBiA0+KeBCu22qF1+tRujBjK0K/DVV19tg38EMqL/tYq2LPQfYrWvWbOmzJo1S/744w/59ttvZcKECbJixQrp0KGD3HzzzXLhhRfKDTfcIJ06dbJdtLds2SIaGNTAoXbTbtWqVfQ3l8I5oykXLRMNwGo3eR0LRQOuprWsDBs2zPd3oH8L7pso7Z592223Sffu3aVNmzY2cK5/Q5rHtKKN+LeXwsVhHz2aMsnLiHorL5nCpUdbFtRbhfMt7FHRlAv1VmF1C3dcNGWS15mpt/KSKVx6tGVBvVU438IcFU2ZUGcVRrbwx0RTJnmdnTorLxnSU0bAfKhjQcBTAmbMPseMUWa7K5pKOuBVZ/R9+OGHHRMosvdsvm3L897NP8Z2n3Z31Blp3VmCTVAx4rF5njTFdhSlLLSczNgbtvxMyzFn5MiRzp9//unrEuxSmsCgc8899/jKWbsDm2Cvu5vXMAIFKRcT8POdwUyS43O+7rrrnLVr1/r26Yr+XfXr18/mMa0AHZ0VWP8GS5cu7XTp0sUx4zYG5GfjkEBByoR665BbPNaKUhbUW/EokYPnLEi5UG/Frxz8z1yQMqHe8peL/XpRyoJ6K/bloWcsSJlQZ8WnDILPWpAyoc4K1mMbgYMC2qqDBQHPCOg4DT179vQFKTQYdOaZZzp9+vRxNPinwQh9PfHEEx3Taizifbtjlr333nuO6V5qj9dxzUxrM3usuz/iiVIwQ2HLwv0HVwN7Z5xxhlO2bFnnpptuckzX0wBFf/utW7faIK2Wr5nExXn11VcD8rJxSKAw5WJm9LUnmDp1qh2D0Q2smxaYzh133OGYWbQdM1O2Y1oK2r8R00XYmT9/vj1G//40v+ky7JhJRA7dCGs+gcKUie/gMCvu3wb1VhicCEmFLQvqrQiwRdxdmHKh3ioieoTDC1Mm+Z2Seis/nfz3FbYsqLfydy3K3sKUCXVWUcQjH1uYMsnvrNRZ+emwL5kFCAAmc+mWwGe7/fbbHTMGmdO4cWNn4sSJzubNm31PYWb0ddq1a2eDERqQ+Otf/xpVENA9wdChQx0z86k93oxnZpPdyt/Nw+shgaKUhdv68plnnnH+/ve/R1VOH3zwgW1ppmV733332Rtxz3PorlgrSrmonpaJBv7cIKC+upN96Hr//v0d03XbB2263/vKZcaMGb50Vg4JFLVMDp0pdI16K9Qkv5SilIVb31Bv5SdcuH1FKRe9IvVW4dzzO6qoZZLfuam38tMJ3VeUsqDeCvWMRUpRykSvT50Vi1IIPEdRyyTwbIFb1FmBHmwltwABwOQu3xL1dPrNjhmo1QYmrrjiCmfHjh2++3cDdT/88INjxibzBS/uvfdex4xtZvO5b4J8B/1vxf2G1IwXYVsxuYGPH3/80ebwb7bvXif4HKm2XdSycL8Fde3VL6/ycW21PHSGYC2fXr16ucm8+glEUy7qmNffiJ5Kf8d1xuzzzz/ftoqtV6+eU79+fadr167OpEmTHJ0FWBe37F566SXHjL1pW3LqjIMsgQLRlAn1VqBZvLaKWhbUW/EpmWjKhXorPvZ5nTWaMqHeyksvtulFLQvqrdiWh54tmjKhzoq9e35njKZMqLPyE2QfAocECAAesmAtQQJuYOjDDz+0rf+0G6K29strMZOC2GCFBorMDGjOK6+8klfWkPS77rrLqVq1qg0yacDDXTTYMXfuXEfvQbuupupSnGXhGrvXNDM1O2YCEFs2F1xwgd3t7nPzpuqr6xCLvxH3w4Jarlu3zgbQ58yZE0LrBsPNJC6+rsEzZ84MyZeqCbEsk0iG1Fv5CxVnWbh34l6TessVCX11jai3Qm0SlRLLMon0DNRb+QsVZ1m4d+Jek3rLFQl8dX2oswJdErkVyzKJ9BzUWZGE2J8sAqVTZrYTHtSzAiaQZ+9NZ/k1gTipVq2anQnW/JEF3LO7bVqHyfDhw6VixYqyePFiee2110Rng9LFzRNwoNkw/4DYJJ35VGeY1dmETXdGe6xe04w5J6arqpx33nliWjzJnj17gk+REtvFURbBkO41582b55th1gR2bTZ3X/AxqbbtOphJVIr8N6IzAruL/q3pj872q4sJ+tlX/TsyE3/YdTNuoP37MWNo2r9Lm8j/fL+r1FuJ/2Vw/z7iWRbBT+lek3orWObQtmtEvXXIJNFrbpnE82+F91vRlXJxlEXwnbjXpN4Kljm47fpQZ4X3SUSqWybUWYnQ55rJKkAAMFlLtgQ+l+mGKGbCCDGtksR0UbQfsN03kvo47j8CZrwy6d27twwePNg+5SeffCIapDBdeX15gh9fgxka3DAtzESDgKarsc1iuhrLtddeKzfccIO8/fbbYiYWETMhhS/4EXyeVNmOZ1mEM9Qyf+SRR2zZ634zE224bCmf1qBBg5j+jbh/Uy6sGxx0082swPLGG2/Y3T169BC9PkugQDz/Vqi3Aq0jbcWzLMJdm3ornEpoGvVWqEmiU+L5t0K9VbDSjWdZhLsT6q1wKoFp1FmBHl7YiuffCXWWF0qYeyhOAQKAxanNtfIV0FZ32vJIW+d9/PHHdl0r5XCLBvIGDRok2lJMA3YfffSRmPEhwmW1aXpeN7hhZqaVli1bSkZGhpjZgMXMgCqmO4RtBWXGOBPTBFzMRCR5nisVdsSzLPyDumq5adMmef755+Wzzz6T7OxsMeM6ipmkIhWYC/yM8SwXt/Wfe1Nm1mZ58skn5aeffrKB84svvtjdxaufQDzLhHrLDzqK1XiWBfVWFAWQR5Z4lgv1Vh7oEZLjWSbUWxHwg3bHsyyot4Kwo9yMZ5lQZ0VZCEHZ4lkm1FlB2Gwmv4D5pWdBwBMCOg6f+YbHjgF38skn2zH58ruxbdu2OXfeeafNr+MG6myl+S3mjZAd2FfzdezY0R5nWjo55cuXdx5//PH8Dk25fcVRFibA5EyfPt3R8f60HPRHZ3ZetGhRynlH+8DxLhfzxtRZvny58/nnn9tJQrRMdFbue+65J9pbTLl88S4T6q3of6WKoyyot6IvDzdnvMuFesuVjv413mVCveWtsqDeir48NGe8/z6oswpWHsVRJtRZBS8Tjii5AkwCUnLLLqnuXP8x1EWneNegQ6VKlZwJEybYGUvze9AvvvjCadu2rT3mtNNOs1m1Eg9eTCtBO1mIBps04OcGnC6//HJH97EcEohXWaizBveee+455+abb3bOPvtsp0KFCr6yGD16tG8G2kN3w5orEK9y0fO7fx+nnnqq07dv34By+cc//uHs3r3bvQ1e/QTiWSZ6GbdcqLf80PNYjVdZUG/lAR5lcrzKRS/v/n1Qb0VZGP/LFs8y8S8X6q3I5RKvsqDeimyfV454lYn/3wZ1Vl764dPjWSb+5UKdFd6f1OQTIACYfGVaop/IjOXnNGnSxAaFNEAUaUbetWvXOqYrsM1vugs7v/zyi33+4CCgGdDXOfroo33BppNOOiliC8MSDRmDm491WWzfvt3RGbbc4Ku+asvNAQMGOPPnz4/BHafGKWJdLqqmMwNfdtllvrIpV64c5VKAX6d4lIlennqrAIXwv6yxLgvqrYKXQbgjYl0ueo1Ur7fM8BnhqKNOi0eZ6MVTsd7yWllQbzmO18pE/zZSvc5Sg6Is1FlF0eNYBA4JhB9gLfl7PvOEMRbQMfR+//13e1bzTU2hz64z9Pbp08ceP3HiRNEJPsw/mHmeT8cC1GN00fHjZs2aZddNcMm+uv/TST+6detmxzKbPHmyfPjhh77j3DzJ8urVsjAtL6VLly5iWmqKaWVmJ1/Rcf90FmcdkzHZF6+WiwmW23E3dUKcsWPH2jEYp02blhLlYj4k2ZnEdSxQXcw/jYX6NaTeKhRbwEFeLYtUr7e8Wi6pXG/pbJinnHKKndBM329RbwVUJcW64dWySOV6y6tlksp1lv8fpToUduG9VmHlOA6BIIFDsUDWECi4gDbLvu222xxtfdezZ8+CnyDMEZMmTXJat25tWyMde+yxzs8//xwml+PrHmwm//C1XDLBJJvX/AMTckxRvw0MOaHHErxcFm556OuqVavsOHMe44vb7Xi5XIIf2sykHZyUlNv6e/if//zHMR+ineOPP94ZMWKEs2PHjiI9K/VW4fi8XBapXG95uVyCf9NSpd7Sf0tuvfVW3/udrKws+++peri/q8E2kbaptyIJhd/v5bJwfxf0NZXeb3m5TIJ/i1KlztLfwdmzZzumgYhjJpQLYNDyKsxCnVUYNY5BIFCAFoBBAVE2oxd45ZVXRKdl11lzza+VNGrUSDZs2BD9CYJy6jl06d69u5x++umiMwB/8803doZY06XE7nPz6IY7Q7AZ60SqVatm92srK12CWwBqWuXKlfUlKRevl4VbHvqak5MjdevWTcpyCH4or5dL8P2mwuzX5s2jnT3cjP9pWwLPmDFDzGQ0YrqhB3NEte3WSdRbUXEFZPJ6WaRqveX1cgn4JTIbqVBvuf+WmDFZ7eOnpaVJ2bJl5euvv7bb7u9qsE1e29RbeclETvd6Wbi/C6n0fsvrZRL8W5UKdZb24jrhhBNk4MCBYsZqlx49etgeQM8884zlcD/DBdvktU2dlZcM6QgUQsD8QbEgUCCBmTNn2lYz5s2F/SZaZ9R96aWXYjqZxvfff+/opB56jVq1atnZfnVWLl3cV/emP/74Y8e8EXbMG2Lnyy+/dJNT4pWy8GYxUy7eKxfz5YRz7bXX+lrPtGvXzrn33nvtZEMLFy6MyQ1Tb0XHSFlE51TcuSiX4haPfL1w/5a447Xqe57XX3/dnqSwrWn0YOqtyOWgOSiL6JyKMxdlUpza0V1LW/ydeOKJvvda2lLZ/bzovprgYKFbLetdUGdFVxbkQiAvASYByUuG9BCBdevWORdffLGvIq9Zs6b9AB1poo6QE4VJ0Obw2pV3y5Ytdq8G+XSw19q1a9vr6bXuueeekCO1e4POWqr/qGi34eXLlxfpH5WQC3g0gbLwZsFQLt4sF72r//73v44ZM9SpWLGiM2rUKOePP/6wA3K7d+x2m3K3o3ml3opGKTQPZRFq4oUUysULpXDwHvL7t+TTTz91TCt6+77nyiuvLPBNU28VjIyyKJhXceSmTIpDOfpr6Psn/ZkwYYJTr149Wzfp+63rr7/eGT9+vGNa/Tk683GFChXsviOOOMJOFhTtFaizopUiHwLRCRAAjM4p5XPpB2ZtZed+ezN8+PA8x+YrKJbOAKtvYjMyMpynnnoq4EO5/mOi4wu6173kkkucL774wo4l8dVXXzl6HzqTrAYITReAgl66ROanLLxZbJSLN8tF70q/ka5ataqtR8xkJ44ZKiDgZoNbFQfszGODeisPmAjJlEUEoATtplwSBB/msv/85z/t+yH3fc/f/vY3W4e5rfy07jGTPNj3Rv3793c2b94c5izhk6i3wrvklUpZ5CWTuHTKJHH2+V1ZW5Bryz/9zNa1a1fHDK3i7Ny503eI7tfPbOXKlbPvxfTzni5uvebLGLRCnRUEwiYCMRAgABgDxFQ4hQbZ9M2ofrPz6KOPhjxycAUeTWsa/RD+8MMP+74t0vOb8QRDuvhqHu1m7L4ZNrP9OpUqVfJ9oNf00aNHO2a2wpD7SsYEysKbpUq5eLNc9K7+/e9/2/rjqKOOcrZt2+a7Ua2nClp3UW/5+Aq1QlkUii3uB1EucSeOeIF9+/Y5Zrws33sdnaRoypQpzp49e0KO7datm81nxh61+yO956LeCiHMN4GyyJcnITspk4SwR33RG264wVd3aXBPW+25i5adLp999pmjw6/o57bBgwfbtLz+R52VlwzpCBRdgABg0Q2jPsOaNWucd955x87idvLJJztm4gqd9cL+RKoIgy+yZMkS58Ybb3SOPPJIRwNiOhZMlSpVHJ0194477nD0WtEsOvOlfpumH4z1eP1m5rDDDrPNtpcuXeprjffGG2/YClv3a7DN/RCtlbpbsev1wr0JDf6AvWvXLttaT2ffdIN6en39tsh/cY/T10WLFtk3xo0bN7bHaDc+M6mH/bYpVcb9c50pC//fksSvUy6JL4P87kDL56yzzrL1hpn4w2bVOsi/rtIZ6nRMGq2D5s6d6wsK+ueh3spPObp9lEV0TsWdi3IpbvHQ67l1zf/93//Z1jNPP/20s2nTptCMJkW/7HSHY9H3fu4Ypu45/A+i3vLXiG7ddaQsovMqjlyUSXEoF+4a+hlNv6TQVn/a+q9Bgwa+Ly3ccvN/dQOAd999d9gLUmeFZSERgZgKEACMKWf+J3ODfeFeCxIAfOGFF2x33HDncdO0u5t+c5zf8ttvvznNmzf3BSHdY91XbWWnAUt3MTM42Q/RnTp1ct5991032b7qG9Jx48Y5ZoY6Z+jQoc4111zjPPfcc44GGN3FDejNmjXLF/jTIKi+0XUX/UfCzeemudvaTc/MBux89NFHjo6BY2bvdLOk3Ctl4c0ip1y8WS7ulw233HJLwA1qXaR1r34RoV8q6KuOW9O7d29H97l1jx5EvRVAV+gNyqLQdHE9kHKJK2/Ek7sfkDWjjm8WadH3WFpf6fAnZtbmPLNTb+VJk+cOyiJPmoTtoEwSRh/1hbVBitZJ2mNLP6v5v39yT6LDFejnTm1wohM4hluos8KpkIZAbAUIAMbWM9+zuYE1fdVvSPr06eMLvkUbANTWbvoNi55DX4cMGeJMnjzZ+e677xxtGaYz57rX0TH7tOVcuGXr1q1OixYtfHk1aDdt2jRHx9XTb2V0oFY9j7b409mWdPnpp59s5a4VvM5C5wb3tOuQO+irfhut+90fMwW8HddPj/f/B7xXr152LIjdu3frLru4LancbV5DBVwjyiLUJpEplEsi9fO/tr7hbNiwoa0v/ScSevLJJwPGNdU3pOnp6b66S7+l1sGr/RfqLX+Ngq9TFgU3K44jKJfiUI7NNdwP1fpFqPs+6+WXX7Ynd/cFX4l6K1gkNtuuN2URG89YnIUyiYViwc+hvcKGDRvmq5Pef//9gM98ekad5PHee++1Pdauvvpq29ti7dq1YYdvos4qeBlwBAIFESAAWBCtIua97bbbbIs6HddAF+3G6wbrog0A9uvXz3fME088EfaOdNYl97w64H245dZbb/Xluf/++20W/wCdtq7TYJ6eR8eYcf9R1cCfvunUb3A0UHjGGWf4KvyWLVva7sPt27f3DfLqvkF9++237TXcwfbdgIkm+q/bTPwv5B9OfxLKwl+jeNf9/0aCr0y5BIsUz3Z+ZeLu0y9GtC7SL1100dbRmZmZNk336Rcrn3/+ufPWW285+sbTHc+xWbNmAa2d/esq//XieVLvX8X1Dnen7j7KIpxOfNNc+3BXcfdRLuF04pfmuhf2Ch9++KHvi9dBgwaFPY1bR7mvmsl/PexBKZhIWXiv0CmTklcm2gusSZMm9n1Vly5dfD3I9Asm/bz7wAMP+GYv1y9cGzVq5OTk5NgeFzoEizu0lD65fz3lv+49Fe4IgZIpQAAwgeVWmACgVpoalNOus3ktWtm6AUBtkh286MCsOm6g5tFWgg8++KDNElzJ6rc57nm++eYbm0fHpHFnA9auJ/qhWlvXPPLII7aLnDb71kWbcGvrRJ2pTvPouILz5s2z+/R/+o+7/rhBE9+OFF3RMcj0H8yHHnrICgSXhT+La0ZZ+KvEZ51yiY9rUc5akDLR6+h4Mvpts9s6WYN91157ra2X7rvvvpBb0W+p//73v9v92sr66KOP9g1mrV9gUG8dIqMsDll4aY1y8VJpHLyXgpZJXk/gBkb0i2QdpkXfX5199tl5jhfonod6y5VwHMrikIVX1igTr5TEofuItkzcOknHnr/uuutsbwutl7Kysuy4gPrF6zHHHGPrKvczY9u2bW0AULf1R4etGjFihC/wx3utQ+XAGgLxECilJzVBHpYECJhJNsRMamGvbFoAihkzL+JdmK65Yrreipk0Q0zX3Dzzm3GsZP369dKmTRuZM2dOQL4PPvhA+vbt60szk2nIypUrxQT2xFTkYj702n0m6CdmUhG7PmrUKLnzzjvFfIiWsWPHysiRI8W0oBEzVpaY1oT2fkwl7junrphuxqLHvfjii2LGCJSbbrpJTPNvDTqLGTDWd196r3reVFzMP3JiZlUWM9OxfXzzhl5mzpwZUhbBNnqcmplv3MSMu2jLwozhJGZcIDniiCMkuCzMN2tigh1ivmWzvz9mMgRbNloWwXmDr5WK25SL90q9sGWiT/LMM8/ImDFj7N9J586dRete80WIvPbaa7YONkF1Ma3+bN3k/j2YFlFiutrbY26//Xa58MILA/Z7T6j47oiyKD7rglyJcimIVvHkLUqZ5HWH7vu0Sy+9VEz3UzG9L8SMp5VXdtL/J0BZeO9XgTJJrjLRz6f//e9/5c0335T58+eL6RFmP+uZRg32c42ZvFLMpGyi5W4ChPLqq6+KGUZKzLinUrt2bdH95gsN3mvF8ddC7dVbFxOIteUQx8txaq8KaACQJTEChWkBqC36zO9Svi0AtQWL5tEfnf3Sf9FvdNxz6H4d48984LWTdmg+t3WZrmsrNN2v+bp16xbQLVUHytcZeXXMQPfbHz3GXdzz6PiB+u2PXkNn7XUHt/7222999+jeK68HywwHHPgd4HeA3wF+B/gd4HeA3wF+B/gd4HeA3wF+B+LxO6DzB7CkpsDBpl7mt4qlZAj87W9/sze6YcMGMYPYh73pu+66y5fu5tcEbRGo37TMnTvXt19bnOmirdAWLFhgW/9paxhdtIWZGQPLrus3OdoyRr850EW/3dGWfdpC0G0xY3f8739uK0JtqajfMGhrQROYFDNhic0R7hj/41lHAAEEEEAAAQQQQAABBBBAAAEEEIiNQGr2u4yNXULOcvHFF4sZw0peeOEFMRN8yA8//CCnn366bTptxt+zQTk3yDZ69GgxA9rb+9TubhoYfOyxx2zTak3ULr9mnD/517/+ZYNzZlws0e7B2hXOXerXry+zZ8+2zYW1264G8nQ57rjj7KuJm9vX4IDe8uXLfd2JtRuyme3Xnnfjxo2i+7Q5uLuYbyDs/bvbvCKAAAIIIIAAAggggAACCCCAQGwEVq1aJToUji46BBdLagoQACxh5a7Bueeff150fKp77rlHnnrqKfvj/xg9e/YUM4i9L/in+zIyMsQMhi9uiz9tjafrOoaMBv1+/PFHO5bMe++9J2amYdvST1sAmkk8fKfWcfzcAKCbGBz4c9M1cBi8aMtCHQdQf/wXHfehXr16/kmsI4AAAggggAACCCCAAAIIIIBAjAVSdfz9GDOWyNPRBbgEFpt2x9UWgMGTe7iP8vXXX8vTTz8tK1assEk6YLQu2sJPB8J3g4AaFNTAm5mtV8wMTDaPmcHJvmqloK37/AN+GkBkQQABBBBAAAEEEEAAAQQQQAABBBAoWQIEAEtWeckXX3xhx9175513pG7durbL7+rVq+2MlsuWLZMnnnhCzMQdMmHCBNvEV8f7c8fja9WqlVx22WVSsWJF+9TaLVgXDQB26tTJBvvMJCHy0EMP2XQNHGq3X3fRLsPRLnovZpITez9ul+KTTz5ZFi5cKH/88Ydot18WBBBAAAEEEEAAAQQQQAABBBBAAIH4CxAAjL9xzK6gwbiBAwfa8fpycnLkm2++kQsuuMAG/GbOnCk6MYiOzTd9+nQ7rffKlStl8ODBAdfX4KAbANQuvRrk01Z+l19+udSqVcvm1e7DmzZtsmP2aR53qVChgrsa8upODuLu0HEFtKWiTgev1zjhhBPsBCTNmzeXBg0aMOafC8UrAggggAACCCCAAAIIIIAAAgggEGcBAoBxBo7l6T/88ENft96rrrpKNAiok3ocffTRct5558mRRx5pA20awNPZeXXRSUJ+/vnngNtwx9vbsWOHbN261e7r27ev9OnTRzTIpy0D3XH6dMIOXTSg598d2Cb6/c/VUCdXAABAAElEQVQdR0BbEE6dOlVGjBgh/fv3t0HKpk2b2glLGjdu7HcEqwgggAACCCCAAAIIIIAAAggggAACxSHAJCDFoRyja2iLOnfRcfx69OhhW/tpWvXq1W1XX225p92D3dl5dd+vv/4qbdu2DegKPHHiRN1l92n3X+2me+WVV8pXX30l8+bNsxOLDB06VBYtWmTzHX744fY13P80SKhjDmqLRG0xqPeps/3qcv7558v9998vderUCXcoaQgggAACCCCAAAIIIIAAAggggAACcRagBWCcgWN5ereVnZ5Tx/jTrr7aqk5bAb7++uvy7bffyvXXXy861p//omMAuuMAanrXrl19uz///HMb/NOEdu3aybnnnitVqlSx+3W8QG0lqIt2Lc5r0RaFH3/8sZ1FWGcT1tl+dZbiL7/80nYBJviXlxzpCCCAAAIIIIAAAggggAACCCCAQPwFaAEYf+OYXaFhw4a+c82YMUM0IHjnnXfaoJ224CtVqpTtBnzxxRfbbsHu+H3Tpk2zXYOrVatmj9eWg9nZ2XYsweeff15uvPFG22JQg4TDhg2zgTydpOOnn37yXU8DetqqUK/hv+jYf3ofDz/8sOi5NCDZsWNH0WuwIIAAAggggAACCCCAAAIIIIAAAggkXoAWgIkvg6jvoHfv3nbCD/eAzp07y1//+lcbgHMDczrhhs6yu3PnTjebvPHGGzJ58mTZt2+fTcvIyJCrr77armt33QcffNC2ENRja9asKZdeeqlvohDN1L17dzumoHsN7d67efNme7zbKlG7Eet5tAUiwT9Lw/8QQAABBBBAAAEEEEAAAQQQQAABTwjQArAYi0G7xOokGe6yfv16d9WmP/fcc75tXbnooosCtitXrmwn03jggQdsurbS0wk/TjzxRNHWfWvWrLGBvqeeesrOvKuZNF0Ddi+//PL/s3ce8FEUbRh/CemB0ELovUtHmnQEUUDAhoiKiF0UO/aK+tkVxYINC1JEQVQUkN5774TeAqGHJKQRvnkm7GVvby+5hJRL8ry/37G7M7Ozs/9Njtxzb5G6detKx44d9bnDhw+XX3/9VXbu3Kk9ALEuhP+iSvDhw4cdxUEwuGHDhvocVBlGQZE//vhDateuLXfddZcjXBgDAgMD9Tj+QwIkQAIkQAIkQAIkQAIkQAIkQAL5jUBKykXZGhktpUP8pWLJoPy2fK6XBNIlUESFdV5MdwQ7s40ABD2EyXpqdo8G+fVQkRfFPtIzPz8/eeWVV3TI7quvvqq3TzzxhLz00ktSunRpHc6LAh+o/hsREWE7FTz+sAaEBk+fPl02bdqkhcR169ZJSEiIzvvXtm1b23MzakThkCpVquhhBw8eFKMycUbnsZ8ESIAESIAESIAESIAESIAESIAEspsAPvs+MHaNzNp6THx9isiH/ZvKDc0rZfdl8mQ+fv7OE+xed1F6AHrdI0l/QRD+kGNv9uzZAo9AFNiAgIaQ32LFimnPPITsIpcfPP4g7mEsCoZgizDi6667TguC8OKDmPfFF1/oIiLwAkxMTNTCHIRBePxNmTJFFwJBWDDeNGDw9IOomFXxL/07zFxvfHy8DkfG/UMcpZEACRQuAsh/Cs9lvB/SC7lwPXveLQmQAAmQAAmQQMEjsO7AaZmx+ag0r1pKrm1YziUHfU7e8aKIE1r8wzWSlSfgZ3MiCowAmJPcOHf+IUABMBefFUJ8rWG+xuWRiw/59CC6oYovPOxg+BbCyL2H47CwMB12izZ4Ar733nty/fXXo8vWUJRjyJAhWgCEB9/8+fN1Rd/ixYvr8bgOioDgZTYIawglhucf9g3xD5WB3333Xf1h2zw+t/fBJTIyUhcyye1r83okQALeQwCFiBISErRXNIobVahQwek903tWypWQAAmQAAmQAAmQAAmkR2DP8Ri57ZvlkpCcooeNGthc+jStmN4p2dr3xby0dF2YeM+JWIlPuiCBfkWz9TqcjATyigAFwLwif+m6q1at0iLe1q1bda6+48ePa8+9Zs2aydtvv62r6mIoBC8U6YC3CwQ9FPaAx97atWula9euDsHQejsQFZH3r3fv3vLPP//In3/+qQuAGAKgdfy5c+d09d+//vpLe/8ZeQoxx6effipYlzcYhNKzZ886LcUoSOLUyAMSIIECTQACoGF4T0CRI3xRQiMBEiABEiABEiABEshfBMYs2esQ/7DybxbuyTUBELn/tqncf1Y7cCpO6pZLdZ6x9vGYBPIbAQqAefTEIGChgMe3336rVxAUFCTnz58X5O7bsWOHfkVFRcmwYcPkhhtu0GMg/sEaN24sHTp0EBQV+ffff+Wmm26SRo0a6T67f5Brr1OnTtr7D3PPmjVLBg8erENmjTlxHqoEQ/iD8Lh9+3Y9FXLzobrvrbfeajd1nrQhTBlCqWGoXIzwP/O9GH3ckgAJFGwCCP1HVXK8X8Lw3hAaGqqFwIJ957w7EiABEiABEiABEihYBH5ZfsDphjYdPitJF1LEr6iPUzsO0A6PvRV7Tkmi2q9SKkieubaeVC4V7DLWkwZcKzo+7Ytl45wenyxU4cglZdjVteXq+uWMZm5JIF8ScP1Nype3kb8WvWDBAunbt68W/xDKi/x6Y8aM0dV1P/nkE0elXgh88LpD+C3GGTnuUMSjZ8+eujgHKgHDsw/ioZ3BcxCiIvIGoiIwbOrUqdqj0CqY4Rhehob499Zbb8mBAwe8SvzD+mNiYrDRhnvCy3ovRj+3JEACBZsAfveN9wHjTs3vEUYbtyRAAiRAAiRAAiRAAt5L4MU/NtkubsfRc7btX87bLSNnR8iyPSdlzf7TMnX9Eek/epkcOh1nOz6jRhT+cGfrDpyRxyeul1Oxie6GsJ0E8gUBCoC5/Jj27NkjI0eOlOXLl0uTJk1kwoQJWuSDh12/fv1k6NChOkwXxTrgkbdlyxaZOHGiXqUhciHhfZcuXbQXIDrgRYhiHnZm5A+8+uqrtVcMxiBUFkIfxEGzodpv9+7dHaIjPBS90WJjYx3LgqcPjQRIgATM7wXm9wiSIQESIAESIAESIAES8G4Cm5X33fgVB2wX+eF/OyQu0dUzb/7O1OgP80mRZ+Nl0Pcr5fi5BHOzR/v/bT2a7rhzyjtw8a4T6Y5hJwl4OwEKgLn4hJBf7/7779cCH0J+n3rqKe0JiH0IdRDk4OWHcNb3339frww5+Hbv3q0LcaDBEO3g0YdqvhgLUfGHH36Qffv26XOs/xg5soyqvRAVMY8hDprHI4E+wo5RXdhbDSHAMKw/ICDAW5fJdZEACeQiAbwXGO9pxntELl6elyIBEiABEiABEiABEsgiga9Vrj93Nn/HcRmoCoOciHEW9fapAh12tle1D/p+hZxPvGDXbduGuXYeS4sysx2kGlftPeWui+0kkC8IUADMxccEzz0U7sB21KhRctddd0lgYKBjBfjwCi8/iHO1a6scA8prD7Z+/XrHOIxBPxLdIzdgr1699Bh4Eo4fP95RGAMefoYZxTEiIiJ0E+bGHOYxxtj8sDXWDVbGB/78sG6ukQRIIOcIGO+fuILxHpFzV+PMJEACJEACJEACJEAC2UHgoCqy8c/GI+lOteHQWXny1/WOMWfjkuS0ermz7Sps+Jfl+911u7SnF/5rHrxqHwVAMw/u5z8CFABz8ZlBsBo7dqz06NFDBg4cqK8MIc5qxgdZJLbHPkKBzRVvDdGrfv36upgHCoDExcXJTz/9JKNHj7ZOp8W+jRs3avERnbVq1dJ5ARHySyMBEiABEiABEiABEiABEiABEiCBvCDw3aI9ogrwOizYv6iMubullAz2c7RhB+G3icmpTi57T7p6/1UskeZYg/FztrvP6Yd+sy2yhPb6+/pIkF9qAU7zuB3HzgnERxoJ5FcCVIBy+cmhGu93333n5NFnXQLCgOEZiGIfEAixX6JECadhhnCIXIAjRozQffDwQ96+b775xlERMz4+Xg4fPizff/+9HDlyRHsWougIjQRIgARIgARIgARIgARIgARIgATyigCKavy6+qDT5Qe2rqqr7U58oK1TO/xmjl8KA957wjlct3qZYHmjXyOn8Wv3n5H4JM/CgCOUsGe2D/s3lZUvdZOf7mltblafzUXWHKAXoBMUHuQrAr75arUFZLEQ9hCi5s4DD56CyP1nVONt2rSpvnOIfob3n7FFhV+EAkMEhPCHisHPPPOMLjTSvn17KV68uC44gqIjuB7Ev3r16mlh0ZijgGDlbZAACZAACZAACZAACZAACZAACeQTAj8v26dEOlPqKp8ick+HGnr19coVF3jiGV5/aDwWHS+VSgbJvhPOlX6rh4VIm5qlRZ3u8CZMvJCiqwO3rx2m57P+E5uQLNNU6DFCiVE8xGx1wotJ8UA/6Vy3rLSuUVpWmnL/rdx7WguU5vHcJ4H8QoACYB49KXfin7GcmJgYMYp3INQXZifYGULic889JygM8vTTT2vhEOIhXjgHwmGZMmXk448/lkGDBhmX4JYESIAESIAESIAESIAESIAESIAEcp0AinT8tHSf03X7Nq2oBT404nNsudAAOXjqvGNMlBIAYRACzValVLCEKsHuioqhsvlwtKNrz/EYcScAvjBlk/y1wTX3IETEGkpQNKx1dWcBkHkADTLc5kcCFAC99Kmhou/Ro6mlyFu2bKlXafYANJZtCInwBOzZs6dALFy8eLFMnTpVVxQOCQmRZs2aySOPPKKLjxjncUsCJEACJEACJEACJEACJEACJEACeUHgv61HXQp5PNC5ptNSwosHOguA51IrAZ9UocNmK1PMXx+WDw10EgDdFQqBkGgn/mGSKqWDJdCU/6+V8gCUeWlX23goNbTYPCatl3sk4N0EmAPQS5/P9OnT9cpQsRcvmJ0HoO4w/VOjRg3t5ffbb79pERD5BocPH07xz8SIu5dPYMGCBfrnET+TeC1dujRLk2Z1nvnz5ztd31gHtqiyXa1aNR0aj8rYhietdYGvv/66Yw7MRyMBEiABEiABEiABEiABEsgdAtYwXoTa1i8f6nRxeACazfD8Q+5As5UpljquZHCqEGj0fTxrpyyOOGEcOrYr06nmW7tsMcc47LSoWlKHFhuNSRcuyoaDZ4xDbkkgXxGgAOhljwshvfD0W7dunV5Zw4YNdfhuZpcJz0DMExQUlNlTOZ4EMiSAitNm+/nnn82HHu9n1zzmC54/f14OHDggf/75p9xxxx3Srl07hzeteRz3SYAESIAESIAESIAESIAE8obAuXjnaroI47UaPADNFhV9yQPwUjEQo69MSKrwV8pSORj9T/y6XhKSnYuBmHP6GXMYWwiRZkMuQIQWm41hwGYa3M9PBCgAetnTggcTKvfu3r1br6xFixa6eAeEQauhUAjMrg/tmItGAtlNAALb77//rqctViz1G7JJkyZJQkLqf8ieXi+75nn44Ydl06ZNjteyZctk1KhRUr16db2UVatWSb9+/bQg7unaOI4ESIAESIAESIAESIAESCDnCJyLT3aavHiga3aycIsH4G9rDsnS3SfEGgJc+pIAaPUAxAVOKLHQ6gXoTgCsqsJ/72hbzWldOGhZzVkU/PC/nfLV/N1yVhUQoZFAfiJAAdDLnhZEu7Vr18revXv1ylq3Ti09bhbzUOn37bfflm7dusnBgwe1QAhvPxoJ5AaBP/74Q86dO6cv9dlnn+nt6dOn5e+//87U5bNrnvDwcGnUqJHj1bZtW3n00Uf175ERPr9y5UqZNm1aptbHwSRAAiRAAiRAAiRAAiRAAjlDINriARhqIwCWs3gAYiW3f7tCrOJh2KUcgCVtPABxzrSNkdhog2i341jqZxmjDdvrm1SQhc92lWIBrkKk1SsQ49+bsV3u+H45nQwAg5ZvCFAA9MJHNXPmTL2qqlWrSt26dfU+BMDo6GgZN26c9OnTR1555RXt8TRlyhRHvxfeCpdUAAkY4b5NmjSRIUOGSL169fRdGu2e3rIx/nLncXe9UqVKyQsvvODonjFjhmOfOyRAAiRAAiRAAiRAAiRAAnlHwCrihQb5uSymQgnnEGCXAZcaSoek5gAsZckBaIz/c/1hR96+1ftPKdHO6EndPntdPfmwf1PnRtNRK1UJ2M5QcXhbpKuYaDeWbSTgDQQoAHrDU7i0BqNYwebNm3ULvJdQ1APtKFIwaNAg/dqwYYNUrlxZfv31V3n88ce96A64lIJOIDIyUmbPnq1v884773TaQmA7fvy4Rwiya56MLmZ40GLc/v37MxrOfhIgARIgARIgARIgARIggVwgYPUAtAsBrlgy43z2PirrVclL4qE7D8AUJfg9P2WTJF1IEWsBEHj3De1S26nyr/X2yxYPkBphIdZmfbzvZKxtOxtJwBsJUAD0oqfi6+srFy5ckI0bN+pVtWnTRhDu+9hjj0n37t0dIZYjRozQRQ769+/vRavnUgoDAXig4mcURWZuv/12fcsotAEP1aSkJJkwYYJHGLJrnowu5ueX9k0i1k0jARIgARIgARIgARIgARLIewJWD0AU27BaeQ88AJH/zwcqoDJ3HoDo2xYZLaNV3j5r/r82lqIfGGtn7WqVsWuWvScoANqCYaNXEqAA6GWPZcWKFdpTCcLFokWLpH379jJ69Ghd6GPgwIFaEHz55Ze9bNVcTmEhMHbsWH2rXbp0kUqVKul9eKmi0i7MCOvVB+n8k13zpHMJ3YXiIIZVrFjR2OWWBEiABEiABEiABEiABEggDwlYqwCH2giAgX5FM1yhUQAEA915ABqTfDRrp6w7cMY41Ft34b1Og9TBQ51rCYqEWG0/PQCtSHjsxQQoAHrZw1m9erUW++BhtXjxYl3ko2XLlnofXlMUMbzsgRWi5axfv97hnWqE/xq3bxyvWbNGtm7dajTbbrNrHtvJTY0Inf/oo48cLRAtaSRAAiRAAiRAAiRAAiRAAnlLAOG/J2ISnRZhFwLsNMDNQaNKJRw96XkAOgaZduA42KJaKVOL+90qSvyb83RnGWSpErzvRJz7k9hDAl5GwLXEjZctsLAt5+qrr9aVhBISEgRFDD744AO55557ChuGy77fFJXo4XSc838qlz2pl0+A//AM9/ecWKrh3RcUFCQ333yz0yVuvfVWnY8yMTFRewG+++67Tv3mg+yaxzyneT82NlYgpL/++uuyfPly3VWtWjXBGmkkQAIkQAIkQAIkQAIkQAJ5R2DmlqMydNxalwVkRgBsUCFUDijPuzrlisuT3VOLZmJCO4/B2uHFZFdUjMv10ADx0K7qr+1g1ehX1Ec61AmTscvTcoszB6A7Wmz3RgIUAL3sqTRq1EjgqdSgQQP5+OOPJSAgtaKRly3T65cD8e/Kt1KLVXj9YrNpgWte7i5liuXMzwu86caPH69XiirUoaGhTqsuXbq09OrVS6ZOnaorVf/vf//TeQKdBqmD7JrHPO8bb7wheLmz8PBwvS7+LrkjxHYSIAESIAESIAESIAESyB0C78/YLhdQlcNidlWAMaRplZKOCr7GKdMf72jsumwHtq4qE1Ye0O3VywTLDDX29m9XuBT/wIDuDcq5nJ9Rg7UYSNS5BIlNSJaQAEorGbFjf94T8Mn7JXAFVgKzZs2SL774guKfFQyP84zAzJkz5dixY/r6RrivdTFGOwrXzJs3z9qtj7NrHtvJLY3ITTh8+HBBHsBmzZpZenlIAiRAAiRAAiRAAiRAAiSQmwQSki/I7uP2RTPceQA+0b2O0xJf63OF07H14M1+DeXNGxrJMz3qyuSH24mv8tr7oH8TKXqpUIgxvlPdsnJvhxrGocdb+zyADAP2GCAH5ikBytR5it/+4kWLZpzs1P5MtpJAzhAwwnbLlCkj1113ne1Frr/+eilZsqScOXNGhwF369bNZVx2zWOe+OGHH5ahQ4fqJlQjDgwMlLCwMClRIi0fiHk890mABEiABEiABEiABEiABHKfwNGz8bYX9ff1kQBf+8/AneuUlZd7N5D/thzT+frg4ZeeQfCz5umrViZERihh8N3p23WY8Me3NpWOat6sGMKMH+xcU8qo6sOYt7p6Wb0CszIvzyGB3CBAATA3KPMaJJCPCZw9e1b++usvfQcnT54Uf3//DO9mypQp8uWXX0pISIhjbHbN45jw0g5CfBE6TyMBEiABEiABEiABEiABEvBeAkfO2AuAoYHuZQnkOL+vY039upw7u6NNNRnQsor2BITTwOXYCz0bXM7pPJcE8oyA+9+0PFsSL0wCl08ABTGQE68wWWarXnnKZtKkSRIfb/+ftbs5YmJiBCLgoEGDHEOyax7HhNwhARIgARIgARIgARIgARLINwQiz563XWvlUsG27dndCO9AGgkUZgIUAAvz0y/A945vinKqIEYBxmZ7a0bYboUKFXRhGttBpkbk3UMeQJxnFgCzax7TpbhLAiRAAiRAAiRAAiRAAiSQTwhEugkBbqYKfdBIgARyngAFwJxnzCuQQL4lsHfvXlmyZIle/8033yy33XZbhveyfPly+fTTT2Xu3Lly+PBhqVSpkmTXPBlenANIgARIgARIgARIgARIgAS8ksCRM/YegM2rUgD0ygfGRRU4AvSBLXCPlDdEAtlHAF57Fy9e1BPecsstHk1sjEtJSZFffvlFn5Nd83i0AA4iARIgARIgARIgARIgARLwOgLuPACbVqYA6HUPiwsqkAToAVggHytvigSyh8DYsWP1RCi00bFjR48mbdeunSBcODIyUnD+c889p7c4+XLn8WgBWRg0Y8YM2bdvX4Zn3n777R4VQclwIg4gARIgARIgARIgARIggUJGYHtktMsdw/uvWpncyQHocnE2kEAhI0ABsJA9cN4uCXhKAKG/u3fv1sNvvPFG8fHxzGEY4zAeVYC3bNmiQ4izY541a9bIlVde6enyMzXuvffe82j8DTfcQAHQI1IcRAIkQAIkQAIkQAIkQAJpBI5Fx8sRSw7AjnXC5MP+TeVyq/KmXYV7JEAC6RHw7BN9ejOwjwRIoEASMIp24OaQ/y8zZh6fE/NkZi0cSwIkQAIkQAIkQAIkQAIkkLcE1h0447SA4gG+8tOQ1lIuNNCpnQckQAI5R6CIyu+VmuAr567BmUnAhQCqxFapUkW3Hzx4UCpXruwyxl1DRESEJCcni6+vr9SpU8fdMLaTAAkUMgJ8byhkD5y3SwIkQAIkQAIkkG8IvDt9u4xekBpdhEW3r11Gxt3XNt+sP78v9HI+f+f3e+f60wjQAzCNBfdIgARIgARIgARIgARIgARIgARIgASymcD6g6edZmxWhYU/nIDwgARygQAFwFyAzEuQAAmQAAmQAAmQAAmQAAmQAAmQQGEkcCHlomw8dNbp1ptVKeV0zAMSIIGcJ0ABMOcZ8wokQAIkQAIkQAIkQAIkQAIkQAIkkGUC5xMvyO9rDsnncyNkya4TWZ4nL07ceeycxKn1my1fewDGq2rGa38WGdNTZNs0821xnwS8mgCrAHv14+HiSIAESIAESIAESIAESIAESIAECjOB+KQLcsMXS2SHEtJgRYqIjBzQTPo1q5QvsKw/6FwApHKpIClbPCBfrN1pkXGnRFaMFln6uUhSbGpXkPJkbHC90zAekIC3EqAA6K1PhusiARIgARIgARIgARIgARIgARIo9AQmrz3kEP8AA2U835y2Tbo3KCchqpqut9t6SwXgfOP9F3tSZOU3IgeWiZxUBUyiD7mijpgpEqs8MkPCXPvYQgJeRoAhwF72QLgcEiABEiABEiABEiABEiABEiABEgCBi0rt+2X5ARcYJ2ISZMzivS7t3thg9QDMFwLg4bUiX7UTWfCuyN4F9uIfYKcki2ye4o3YuSYScCFAAdAFCRtIgARIgARIgARIgARIgARIgARIIO8J/LXhiGyLVDnnbOzrhXvkVGyiTY/3NMUkJMvOqNTQZWNVzat6eQXggytFfu4nEnPUWLLrtoiSUur1Erl1rMiVg1372UICXkiAAmAuPpSoqCiZNm2avPrqq9KzZ08JCwtT+RuK6Nfdd9+dpZXMnj1bcG7t2rUlJCRESpQoIXXr1pVbbrlFvvrqK4mJiUl33ri4OHn//felVatWUrp0aT1H/fr15emnn5b9+/eney47SYAESIAESIAESIAESIAESIAEco7AqLm73E4Oce2Lee773Z6Yix0oAIKQZcN8fYpIw4oljEPv2ibGiWycJDL2RpEEe9FVIPzV6SHy0BKRgRNErugr4psP8xl6F3muJpcIeH/CgFwCkRuXKVeuXLZd5vTp0zJkyBD5888/XeaMjo6WiIgImTx5slx11VXSrFkzlzFo2LVrl/Tq1UuPNQ/YsWOH4PXdd9/JuHHj5PrrmdTUzIf7JEACJEACJEACJEACJEACJJDTBM7EJcquKGeHDv+iPpJ4IcVx6bHL9suQ9tWlcqlgR5s37USfT3JaTlixAAn0K+rUlucHKO4x61UVyjtZFfdQIqDVKrUUafOQSHh9kdI1RfxDrCN4TAL5ggA9APPoMVWtWlV69FDfHGTBzp49K9dcc41D/Lvxxhu1ULd8+XJZtWqVTJkyRR5//HGpXLmy29nPnTsnvXv3doh/999/v8yZM0eWLl0qb7/9thQrVkwgJA4YMEDWr1/vdh52kAAJkAAJkAAJkAAJkAAJkAAJZD+BrZbQX4h/M5/sJH5FVRngSwYxcPCYlQJvQG+0uMQLTssKDvAy8e/oJpFvuoisG2sv/tW5VuTuf0Sa9Bcp35jin9PT5EF+I0APwFx8Ygj9RagtXvAG3Ldvn9SoUSPTKxg2bJisWbNGAgICZNKkSdK3r3I7NlnLli0FouAnn3wiFy44v+Eawz744APZuXOnPkQI8PDhw40u7TXYpUsX6dy5syBE+IknnpD58+c7+rlDAiRAAiRAAiRAAiRAAiRAAiSQeQIo6vHl/N0yY/NRaVOjtLzQq4EUVWGxdrYt0jl3Xt3yxaRGWIjc0aaa/Lh0n+OU3cdj5eU/NsmLvRvI1HWHpUxIgPRpWlH8ffPe3yfWIkyG+HuRBLHpd5E/HxVJPu9g6bRTX0XC3fKDCvH1d2rmAQnkVwJe9NuXXxF6vu433njD88FuRi5evFjGjlXfTih76623XMQ/82nIL+jr6/qIk5KS5LPPPtNDGzRooPP9mc/Dfrt27eTee++Vr7/+WhYsWKA9CyFc0kiABEiABEiABEiABEiABEiABDwjAMEv8my8IPQVgtycbVHywcwd+uRNh89KaJCfPNatju1k1uIfDcqH6nGPXl1b/lBC31lTeO3U9Udk3o7jjrYNh87IiH6NbOfNzUYXD0D/PPYAjNqe6u0XMUvkROpzcOKBHH/VO4o0u12k8a0iPnkvojqtjwckcBkE+NN8GfDy4tTPP/9cXxbFPh59VH1bkQWbN2+eIIwYNnjwYPWeZv9jYC5M8scff2ThSjyFBEiABEiABEiABEiABEiABAongfikC9J/9DJp9+5c6frhfNlzPEZmbT3mBOPjWTslMTktp5/RiZDe2ducxzaokCoAQkz89i6Vl85iZkHwl+X75Vh0vGVE7h/GJjqHJocEuDqo5MqqUhTjRR+JfNVOZJn6TG0n/lVuLfKECgke/JdI09so/uXKg+FFcpOAvfKTmyvgtTwmkJiY6Mj7hxyAgYGB+lyE+R48eFCHFMfHZ/wmDy9CwxDm684QShwcnJpMdskSVeWIRgIkQAIkQAIkQAIkQAIkQAIk4BGBiSsPyOr9p/XYw2fO67DdOdudRT10zt8R5TIfinuciXMuoNGxTphjXGsVPjygZRXHsXUnRVXe/X3NIWtzjhxDrFwccUJOxya6zB+X4JySKjgvPADPq2cwQQl6c0aIXHRej2PBLe9JzfVXwn0efcdY7pBAPiVAATAfPbgNGzaIIfA1btxYF+lAfr6wsDBBURHkE4RnIMTB9HL2bd261XHX9eurSkZuDOHDtWvX1r3btm1zM4rNJEACJEACJEACJEACJEACJEACVgKv/532uQt9PytRzy7f35Yj0U6nximvue8W7XFqu+aKclKnXHGntoaVUj0CnRpNB/9ZvA1NXdm2G3UuXq79ZKHc+f0KafvOHNlquRcXD8DcygGoQq9lzwKRmS+JfKm8/iJm2t9zsXIi/b4Uuf4T5vqzJ8TWAkQgj/xvCxDBXLwVs3CXolyY4aEXERHhtAJ4Cc6ePVtX9H3nnXfkueeec+rHwaFDqd8EhYSESMmSJV36zQ1VqlSRjRs3yvHjxyUhIUEXHjH3u9s3ruGuPzIy0l0X20mABEiABEiABEiABEiABEggXxNISLb3NDsWneByX6cuec4dOBknoxfulvErDriMeexq1zyB4cVTI8JcBl9q2HDwjIxVocA3NKsoxQP93A27rPbP5kQIvBthCSqU+Z3p22TsvW0cc7p4AOZGFeB4le7q1ztF9i50rMNpB3n+Wt2nKvsqr8CKzRnq6wSHBwWZAAXAfPR0T5065Vjte++9p70Br7vuOhkxYoQ0adJEewROnjxZnn/+eZ3jD1t4+PXr189xHnbOnUutJlWsWDGndrsDiISGxcTEeCwAQjikkQAJkAAJkAAJkAAJkAAJkEBhJLDxUGrOdU/u/WRsgmw5clZu+2a5nIt3zpmH87vWKyuNK5dwmSo8NMClzdrwytTNMnbZPpn8cLtsFwHPxCXKL8udxcpFKhT4qCp6Ur5EqjiZ6x6AEP/G3iRyeLUVRepxsAqjvmWMSE33qbDsT2QrCeR/Akr6puUXArGxsY6lIhQYob7Tpk0TVOcNCAiQsmXLykMPPaTbjMIeL7zwgqDylNmMMGJ//4zLmWNew86fT/1mxzjmlgRIgARIgARIgARIgARIgARIwJXAkUteca49ri0nYhLly3m7bcU/jB7mpkpwudD0PQCNK+08FiP/+3ebcZht29mqorGd/bf1qKPZpQpwTnoAJihHl19ucS/+VWsv8tAiin+Op8OdwkaAHoD56IkbRT+MJcMLsGhR1zLqHTp0kJtuukl+//13Qe6+TZs2aQ9B4zxjHoQLZ2QI+zUsKCjI2M1wi6Ik6RlCgFu3VlWWaCRAAiRAAiRAAiRAAiRAAiRQwAhYC3ikd3snYxIk+rxzwQ9jfIfaYdKiainj0GlbVlUD9tQmrDwofZtWkqtqlfH0lAzHLYo4bjvm8Ok0xxHkMzRbSE7kAExR4da756pqKu+6in8hZUVa3itSp4dIpRYiRYqYl8N9EihUBCgA5qPHXbx4WtJXePs1b67yFbixa6+9VguA6F61apWTAGjMg5DejMzsdehJyLAxX+XKrJ5ksCis2yKX/nN97bXX5PXXXy+sGHjfJEACJEACJEACJEAChZBApgRAlQPQx40wdX+nmm7p+ftmLqBv4LfL5d4ONeSFnvXFt2jmzrUuIkWVGV6y64S1WR+fNYmZLh6A2VkFWOXFl3U/iyx4XyT6sOtaQsJTK/uWrevaxxYSKIQELu+3vhACy8tbNufVy0hgM49FAQ+zGedC3Dtz5oy5y2Xf8OSD4GgOB3YZyAYSIAESIAESIAESIAESIAESIAFN4Mz5jKOtDFQQC41CIEYbtu2Ut16nOipnXTba94v3yvTNaSG6WZ1629FoQeiynZnFz9gEiwdgQDb5IMUq8fGnPiJ/P24v/iHX3+C/RSj+2T0ithVSAhQA89GDb9iwoWO1Fy7YV5UyBpj7fX2d32SvuOIKY5hs377dsW/dSU5Olt27d+vmBg0aWLt5TAIFkkD16tVVZEARufvuuwvk/fGmSIAESIAESIAESIAEcp6AWQTLytWe7F5XvrrzSv13aXrno0CI2bo3KGc+tN1fvuekbXtmGlHsw52Zxc8c8QBMUiHG428V2b/YfgnFK4rcNVUkvL59P1tJoJASoACYjx58tWrVpGrVqnrF+/btcynuYb4VQ7hDW6VKlcxdghyBhi1YsMDYddmuXr1ajBDg9u1VwlQaCZAACZAACZAACZAACZAACZBAhgRQITerFujnI491qy0lgvwynKJPUyV2XTK/okXkhV4Zi15R59LyvBvnZna7OD0BUHk0Gmb1AAy+nByACSqF1cbfRH6+QeX6W2NcIm1boZlI749EHlkhUr5xWjv3SIAENAEKgPnsB+Hmm2/WK46OjpY5c+a4Xf2UKVMcfWbBD41dunSREiVSy8j/9NNPboXEH3/80THHjTfe6NjnDgmQAAmQAAmQAAmQAAmQAAmQgHsCZ0x58KyjgvyKSnA6ufBQ3dfIp20913p8U4vK8vWgK+XRrrXlj6HtpVbZYvK8yvFnmI+qeWEWCdF+uQJgfNIFWbnvlHEJl62RA/DixYuSbR6AO6aLjFSi3pT7RA4ud74mcv3dOVnkQeXc0kr1B4Y69/OIBEhAE6AAmM9+EJ544gkxqvg+9dRTAiHQar/88ovMnz9fN/fu3VvM+QDR6O/vL4899pjuR5XgDz/8UO+b/1m2bJl8//33uqlz587SqlUrczf3SYAESIAESIAESIAESIAESIAELhGYvilSrh+1SIb8sFL2n1S51k1ecFZI3RqES5sapa3NjuNyxQMd+57sXNuwvDxzbT1pVCnVyeM+VejjtT5XyICWVWT8/W2lT5MKTtNERcc7HWf2YOXeU5KYrApwuDHce9KFFPnov52SrIqFmC0kKzkANyvnll/vFDlvIzoGqHtGrr/a3c2X4T4JkIANAQqANlByqmnx4sUCrzrj9fvvvzsutWvXLke70e/oNO0gBHjEiBG6ZdOmTdK6dWv54YcfZM2aNTJv3jwZNmyYI3dZaGiofPLJJ6az03aHDx8udeumVkN69tln5cEHH9TnL1++XN555x3p0aOHIAdgUFCQjBw5Mu1E7hVKAkeOHJHnn39eWrRoob1H/fz8pFy5ctK4cWMZOHCg/tm1E6PNsFCNGmNRhAYFZRCaPmjQIIEInZGlqApfELZ79eol5cuX1yI2CtN07dpVvvzyS0lMdB9igQrE+AbV+Bb17Nmz8uabb+oq2iVLltTt+J2DZyzG7N+/Xy8H3rHGecYWYy7XIM4b82Ef34xCbIenbpkyZQS/t/i9Hjt2rNOlcI+jR4+Wtm3bSunSpQXVvBGaP2nSJKdx1oPTp0/r94g777xTkP8T1bzxJQA4olr4N99845bfPffco9eK94Fz585Zp3Y5rlevnh6P9dvZ5s2b5a677tI/A/giA+9nWNfatWv1cORdBJvq1avbnc42EiABEiABEiABEvBKAijgMWzCOtl8OFrm7Tgur/21RQmA7v8+7aEEu2Hd6khRuOfZWLkSmRMArVOgwu+Q9jXkvVuaSNuaZQQehWY7rkKAUcU3qzZf3aPZSgU7hyqfVx6CX87bLZ/P22UepvdDA31d2tJt2PCryOR7RVKci4noc0JU/sOB45nrL12A7CSBNAKZ/O1LO5F7mSfw3XffCUQFO1uyZIngZTZ3RQgg3p06dUree+892bFjh+BDutXCw8Nl6tSpUqdOHWuXPoZ48M8//2hBJSIiQosAEALMBiFi3Lhx0qyZyqVAK7QEFi1aJNdff72Lt2lUVJTgBVFn4sSJEhYWpsfZgYJI9/jjj2tR2eiHqAhRD+Hq06dPl06dOhldTlv8rPft29fl9+PEiRMCAQ2vzz//XM+BPJnpGX7WIW4jh6Y3WFJSkvTr10/+/lt9a2kyiKUQypCH89NPPxWIeDfccIMsXLjQNEpk6dKl+oUvEF588UWnPuOgefPmDlHTaMP22LFj8t9//+kXhMV///1Xi4LmMXfccYcWD+Pj4/VzGjx4sLnbaR9r3blzp27DeVbDs8Z7Fe7ZMFQZx3sMRMxvv/3WaOaWBEiABEiABEiABPIVgXnbo5w83awCmfVmapUNkYYVS8gHSqB7YcomSbB40zWtnOrJZz0vq8fhoQFOp8Ir77QSKMsUc253GmRzANHwuckb5bc1h5x6r29SUcYuT/0S3ej4ZmFqMUnjGNsqpYM8u6b6glyObhJZP05kxdfqTItYWb2jSLPbRer3VuG+2cvKvF7uk0BBI0ABMJ8+UXjpQRT56quvBAJNZGSkDg2GVx/a4Qlo5Plzd4u1a9eWdevWyRdffCG//fabQESAlxFChuFpBcEmI0HF3dxsLxgEEhIS5LbbbtPiH0Tjhx9+WHvdQWDGz8revXu1APXHH3+4veGZM2fKypUrtbcgfqbgNXj+/HnBORC34uLitCcgxDl4ppkN1awhPiIkHYZw9EcffVRq1KghEBDHjBmjhW54EXbr1k3Wr1+vPdzMc5j3b7nlFjl8+LD+/cDvSalSpQTXxc85PGlR9AZecZgbwtxbb71lPl1CQkKcji/34JVXXpEVK1YIBLPbb79dC3AQ0eC1CHH/s88+kz59+sioUaM0Z/BHPk54CuJecT7W+uqrr+r1miuFG2sDwzZt2miOEAPhuWk8O4hyM2bM0O8DeM4QU80GD8uKFSvqa0CoS08AHD9+vD61aNGi+mfGPA+ESnyhgbUEBwcL0hdAiIUnKIRDvJ898MADYrd+8zzcJwESIAESIAES8B4CKO4A0Qc53q5RlWcbZ7No5T13mvFKLmTSm65SySA9KfL3daxTVv7acET+WHdI9h6PlatqhcmtrapkfNFMjAhTQp8KslCRJ2knIQ9gZgXASasPuoh/mPF6FWJsFQBj1c+F1VpVcx/27Bh77lhqnr+9zl98O/pbPyBy3XsiPj6OJu6QAAl4RqCICj8zvQ14dhJHkcDlEjh06JAjNyG8gBAW6qlBsEF4sq+vr1sPR+XTbp8jwtOL5MdxQeo/1Gz+j3Du3LlaWAMOeKlBjLMzPA8IefAaNQyhnIZBUIbgZxX43n77bXn55Zf1MHgCWovNQJyG4AeDRxxCdc3zov2ll16S//3vf9gVhLPDM9ZsENPeeOMN3eSj+MDbEOKTO0P4KcKAIXbhetltENkgrBmGEHsIo2Y7evSoDtFH2C1CneHtCD7wAjTbxo0bdSgzQqSR1xOCqtXw++LOExhjIXwaXsSzZ892PG9jnqefflo+/vhjgbAH8RQCotVwfXxxADESbCH6mg3CIwRLCH6oPA5B0mzwJL3qqqtkz549uhmCbFa8ND16bzBfmPskQAIkQAIkQAJZJvDExHUydf0Rx/nXXFFOnrqmrjSokPb3oKOzgO/8uf6wPD5xvcd3ufedXi5/03p8chYHtnxrlpyISXSc/eOQVtKlniqe4aEt2XVC7vhuhe3oXW/3lGYjZkmMEoXTs88GNpe+pqrFLmMTY9Ufp71EIt2wvEp9LuihvqA3fc5wmYMNtgQu5/O37YRszJcEfPPlqrloEsiIABLEflAro1EFq3+4crMPCcvWe4IQZZi7EF30Q4w1i3/GOdgi1xtEJqv4hz6IVshpCY80eLLaCYAYBxEMYb5W8Q99EPcgjm3fvl2HkWI+CE12Bi+09MQ/u3Nysg1CmFX8w/WQnw8sfv75Zzl+/LgMGDDARfzDuCZNmujcgQgNBj87S0/8w/ghQ4ZoT0MIdEgbAE9Ks8E7EQIgvPcQ6m23XuQfhfgHs4b/wsMRc8PgmWwV/9AOj1LkK4XXJY0ESIAESIAESMD7CaDAw7SNkU4LnbX1mMxVobBv9mskt7ep6tSX3sHiiBOyfM9J6VS3rLRWhTEgIq1WFWbrlS8uFUoEpXeq1/ShKm5mzO5v2sycn5WxZVVhEbMA6Ekl4Oj4JJmx+ah8v2iv7Dhmnw+6hxJ+kXOwRJBfugJgtTLB2lPU7dpTFMPJ99mLf0WUt1/n51JfFP/cImQHCWREgH6zGRFiPwkUYgIVKqRVDIOIlxW75pprtMBjdy7Cig2ByvD+MsZBUDIKhNx666266IXRZ95CfISIBUOuPKOghHmMsW8Vp4z2vNoi7NadNW3a1NHlyTgrP8fJph04fEPURZgxcjcaLxRkgW3YsME0OnUXhV/q16+vD4wwX+sgox3FQqwiLrwKDUPRF3eGiuUIbaaRAAmQAAmQAAl4P4GjZ+Odct4ZK0Yo7It/bJI1+08bTelu5+2Ikju/X6GLRdzx3XL5W4XCdvlgntz9wyq55uOFskIJg/nBztuEu2LdPRuV95rlhxd3/oIchUDSMwixPdQzePb3jW7FP5x/Y/PUvyObVy3pdrrBV1WTXx+4SoL8i7odI7NeFdnxr3M/inx0fFrkkZUiXZ6n558zHR6RQKYJ0AMw08h4AgkUHgKoTFuzZk0dmvnEE0/ogg0QeOAN2KpVK1uvPisdQzyythvHqGgLs1aZhThlmJ3XmNGHrbkf5yGc1M7gMedNZlTitlsTKhQb5sk4Kz/jXGxR8Af5QuEpmN44hBrbGYRT5BtELkfkCkX+UMOQJxIemDDkVYSoazbjOcIrM70cfwgxRsGhOXPmmE/nPgmQAAmQAAmQgBcSOHT6fLqrQrjoldVKpTsGnVPXHXaMSbpwUVfSNRogQCGsdtZTnaR4oJ/R7JXbeEsRDyyye4Nw+erOK6X68/94xZqtAmBUdHy66/pXeXgezWDMS70ayHWXRM5X+1whiYrDQfWz0bp6KV19uJiq+NuqemkJ9HMj/F1QxeF2TBdZ94tIhHMKGQlUfwsPUX1hddJdJztJgAQ8J0AB0HNWHEkChY6An5+fzv2H4hnwxkN1Wrxg8PaCEIjcfAhRhYBjZyj6kJ4hLx8MIaZmQ/VfwxAimp4hZNYw83lGm7FF0Q9vsvTYGFywXk/GIQ+f1eDxd//998v3339v7bI9RnEWO0OBEgiAMBQDee211xzDIC6eOXNGH9t5WMIrEwah193PiB6g/kGoN40ESIAESIAESMD7CRw+Y/83g7Hycyp01BPLqFouBKiZW47JLVd6ni/ck+tm9xg7D8DX+jTUl3m0a23t4Whc892bGhu7ubotFxrodL1j0e49ACG+vjltq9N4HAT6+cjT19TTId4hAc5SQrgKMf7mrpYu57htOKdSDY3rr6r9bnQd4qME39vGU/xzJcMWErgsAs6/tZc1FU8mAS8igIIYyIlXmAz3nAN2xRVXyKZNm7QQiEIg8CKDFxjEIhR7wAs54v7991+3ob6Xu6zsypOSkQB1uev0tvNRJdkQ/+BdBy9OeEsi5BeiosEDIu7YsWNVZTj7mlDwAoVXJaoxI9zXLAAa4b8I373uuuu8DQHXQwIkQAIkQAIkkAMEDp2OS3fWmIS0L3bx94W7v+UCfDPOSLX/ZGy61/KGzvjktPvFem5oVlGqlE79EvzOttVk/s4o2Xw4Wuc57NcsNWQ2t9cdHuocAhx1LtUDEM/yy/m7BR6BNcsWk84qF+N3i/bIOSUCWm36452kRliItTnzxyfV57TxA0RORtif23eUSPX29n1sJQESyDIBCoBZRscTvZoAvMqyuSCGV99vDi8OQhEq0BpVaCMjI2XGjBmCKr1r1qzRrwcffFBX+s2upRihwZjv2LFj6U5rLlZiPi/dkwpB57fffqvvEiG7S5cu1V6bdredntekMR7efRAAkT9w9erV0rJlS4mOjtbhxRjTv39/gceo1QyvS1wDXp6G6Ggdh2MUPKGRAAmQAAmQAAl4N4FPZ0fISPVKz2KVeAQvwccmrFPC11mpryoD1y9XXGqFhwgEsWB/Xx0ueiLGvReaMX+sSUw02rxtG2/JARik7s+w8iUC5e9HO0iCCo+F4OlODDXG59TWJQT4Ug7ApyZtkJV7L0XebIuSbxbusV3CO8pz8bLFv/izInsXivypqvnGp0aQOF3MT4mL174l0mygUzMPSIAEsodA2jtT9szHWUiABAoBARQHQeGNO++8U9q2basLb0ybNk17BSI0ODusUaNGjmlQSTa9AhLITWeY+TyjLTPbvPqjLDNr9HTsli1b9FDk5nP3XPCtfHqFU4xroRALPAiTk5O1FyAEwMmTJ0t8fOq3x3bhvzjXyPuHXIFYj7s8jBAHjWrBxjW5JQESIAESIAES8C4Cc7cfk09m73RZVKjK9RYdn+YxdjI2Qe77abVsi4zWYzccPCN4wf7373YdShqf5Jq+RA+w/HM+KW1eS1eeHKaoQifbjkYLwn6R5xB/O1rvBaGyZsMYt3nwzANzcD/cEgIcpUKAD56KSxP/Mrh2tUsejW6Hqb8pJVblkz69TyRGfXkPge+8SgVzXm3PHhTZt1gk+rD96Sj20U2lmGl4o0hAMfsxbCUBErhsAs7vTJc9HScgARIoTATg8dW5c2d9yxCGjFxw2cGgYsWK0qBBAz3VpEmTJCYmxnZaCEc//vij7oO3GarWXo4FBqbmR4Fgld8NzwQWG+s+dObPP/8UeHRmZMjP16NHDz1s4sSJgpyDRvhvtWrVpH17+zCNbt26OaZGmLE7Qy7BkyfzR6U/d/fAdhIgARIgARIo6AR+W33I9hYbVizh1L5k10mH+OfUcenAKpjZjTHa4izedUZ7Xm1HKgG092eL5ZbRy3TFY6zjfJJzCHCQu6IXebVodV2rB2DihRSZtTX9KBvzco2QZkk4p/L2qWJ92/4WWT5aZM4Ikcn3i3x8hciHtUW+7y7y6x3Ky+8Rkf9eFln0ocjGX92Lf+XUl/4PzBdpMYjinxk490kgBwj45sCcnJIESKCAEFi0aJHA289c9dV8a4mJibJgwQLdVKxYsWwv4vDII4/Io48+qkNDH3vsMUFOO6u98cYbsnVrapJiFLxAtdnLMdzv9u3bZfdulZskn1udOnUc+Rv/97//6UIc5lvCPYKxpwYvP+R6hGAI8W/evHn6VBQJcec5idyB8PrbuHGjjBo1SlBQxly1GRMg9PfJJ5/0dBkcRwIkQAIkQAIkkAcEEDUwfbMq3GBjqAS7bE/OfJHnTQLgERXW/NncXQ4Ck5Qg+kyPesoD0FkAzGtvP8cCTTtli5v/Rr4oxeS8LFm7Qdr57JCrfLZKxSInJUASJVC9grAtkihF5KIkXPQX3yLJUvkXJeadU4Jhkvsvlk2X82y3QR+VMFGJiPT684wXR5HAZRKgAHiZAHk6CRRkAnPmzJE333xTOnbsKL1799ZCDjzBUAAEueBGjx7tCB+99957xdc3e99SHnroIV11FrnnfvjhB9m/f78MHTpUatSooUUoCIJTpkzRj6BWrVqOSrWX80zatWunhS1UO3733XelZ8+eEhKi8pEoQxgtCmjkF0Nxj+HDh8uRI0d0EY/nnntOECKNsN25c+fKyJEjBZ6O8Jr0JAy4X79+mgU8CocNG+ao3Owu/NfghFyR8BTFta6++mp56qmn5Nprr9ViLfIJvvPOO4I8jihUgjBgd2KiMR+3JEACJEACJEACuU9gxzHl+WVjqNBr9S6zGZZhU/vaZeT56xrI+JUHZIJ6GWZXYdfoy+3t1PXOIawXVDjwodPn84UHYIAky0PB86VN0gpppUS/YkVUGhek/vP3kOKlNIEejnY/rEjR1Oq+Le8RaaU8B5G7nUYCJJArBLL303quLPnyL4LQtf/++082b96sBYvGjRtL165d1XsP33wuny5nKGgE8PsCLz/D08/u/iAMQcTJbkPBCOQWRA67JUuWaNEKwpXVECo8ffp0gRfi5drDDz8sX331laBoxQsvvKBfxpwQsebPn28cev328ccfl1mzZun3Owi2EGnNBkHz559/1oU8PBEAIYSiEMy4ceMc4d5NmzZ15Pkzz23e79Chg/behIdmXFycvPXWW/pljIFwDOaoMA0B0AjDNvq5JQESIAESIAESyHsC6w+4Fm1A7r9hV9eW/SfdVwVuXaO0rNl/WiCWdalXVoa0ryH/bTkq41akiXy4u671wqVx5RLS+HAJmWC63djE1JQmpqY82UXuv99tQqBRyCTBks/QmgMwTxaMi8arHIyHV4scUq91Y+X5FMVc6W85aj5+IqEV1DfnpdWrpEigegWXUaJfXZEanUTK1Bbx9VR1BTkD8wAAQABJREFUzNGVcnISKHQECpQAiEqhRtJ7ePHYfYjctWuXQKxAiJ/Z6tevL7///rsj55i5j/skUFgJPPPMM9rrb/bs2bJu3TrtSRYVFaVxlC9fXlq3bi3wMoN3YE4ZqvpCGILohLBTrAPiXGhoqEC8R0gphCV//+z5QwIefigqAkETouehQ4cchS5y6h5zal7kaERuPYhrEPoQKo3wHdxj9+7dBQIh3vswxlODtx+ehWEZef8Z4wYPHizNmzeX999/X3tYnjhxQoeMI3cgPAIRFgyxF1aihHMeIWMObkmABEiABEiABPKOwOYjqoKrxWY/1VlQXOJETKKlJ/VwYOuqguqxqAp8Qf0NEhqoxCFlFVRlXHj5KU1NG6rLojowLNjfWaHyFg/ARbtOyJ4TruGvEACtOQDzPAQ4SXn3Lf5EZMmnIsnnNdds/6e4EvlKqmdWvJxISLhI2XppAp+P8zPM9mtzQhIggSwRKKI+DF56283S+V510rPPPisfffSRIO+VVeDDQhH2hhCziIgI/SHYungUHdi0aZOgkAAtZwlAVKlSpYq+yMGDB6Vy5coeXxDPD8UN4DWEZ00jARIoGASQaxJ5CVFdOr2CIe7ulu8N7siwnQRIgARIgAQun8ANXyyR9Zcq+WK2566rLw93qaUn3nH0nFw7cqHLRVa82E3KWarPGoN+WrpPvpy/S4mBQfLxrU2lZtnUSA54Bz4wdo0xTKqq6rMLn+3qOM6rnXt+XCVzt6d+EW5ewzM96srU9UdkV1RawbpRA5tLn6YVzcNyb//wWpEp94ucTMtVmN7Fky/6yOaL1WVdSh25vVMjCQhSqW/8gpWXniqMp6oXS7IqjFdERcqFhIkUU2IfXqHq3vyC0puWfV5G4HI+f3vZrXA5l0GgQHkAwksJBk8TO/vuu+903jLkl0JBAQiG8JBBHrPXX39d5xRDkvpXX33V7nS2kQAJkAAJ5BAB5Fw0Cq+0bds2h67CaUmABEiABEiABLJCIFlVjN0WqcJJTdaoUqjjKCTA1ePLR2lH7sQ/nDi4XXX9ckxyaSfY3/kjqjcUAdmnPP/m7XAV/7BkeD9ai4DkehXgWFWAZed09Zopsl1FVFxMsWJ1HK9MqSc/JV8rGy/WkLMXQyRGgiVFfLTn5d3XXJsq+jlGc4cESKAgEXB+d83nd4acfrBrrrnG9k4QAgfr1KmTTn5vDHrllVf0B0/0//333xQADTDckgAJkEA2EUD6BXfVpE+ePKnDuHEpVHEeMGBANl2V05AACZAACZAACWQHgd3HYyUh2VlUalgxLWVHsQDXj5WhQanhvpm9fpBLCHDe5ACEqPf94r2yR937TlUAxV3c3HEVAmwVAHMtBBiLWvODyMyXVHVe93kYpWILkcotJblmN3n096ISlegasg2xloXYMvvTyvEkkL8IuL5T56/1O1aLfFIIC8WbVr16Kv+AxaKjo2XNmjW635oIH0ORQwwCIELIaCRAAiRAAtlLAF/MoHrzjTfeqPNKIs/f6dOndXGXL7/8Untg44ovv/yyhIWpEBMaCZAACZAACZCA1xDYdNg5/1+lkkFSOiQt/7LVaw8LL5FFAdDqTRinhDhkrcptcerjWTvlm4V7MnwGJ85BAHQWR4P8VchsThqEvzP7ReaMENk82f2VKl0p0kflASzfWI/Bh/9nrjsoz/6+0eWc7Kjk7DIpG0iABLyKQL4WAO+55x4HTAh8hiG81/ofBIoGGP9xTJ48WVcTNcZjm3jpW5Bz586JeV70jRkzBhsaCZAACeg0Asb7RWZwhIeHC16F1fD+O2/ePP1yx2Do0KHy4osvuutmOwmQAAmQAAmQQB4R2GwRAM3hv1iSv6+r4GUU/MjskoP9nD+iQuuCwGb1DMzsvJkZj5DnX1cd9OgUeABai4AE+LqGRHs0WUaDImaJrPpe5IjK8xdzzP1oH8Ww/eMiXV5QVX+dPTFvaVFZxqsKzOZ8jpiouKroTCMBEijYBPL1b/nevXsdTycuLtXlGcLfvn37HO3GjjE2JCREzpw5o19Gn7E1RENjrNHOLQmQAAkYBHr06CH796tvXDNpr732ms41msnTCszwn376SadYQEXnyMhIOX78uC7kg2rSHTp0kAceeEBQvZ1GAiRAAiRAAiTgfQS2WCoANzKF/7pbbWhQ1j5q2gl9cYnJuSoAbjh0Vs6eT7K9NYQ7x6iqxoYdOn1eLhjljC812t2DMT5L2xTlYTj3TVXZ9+P0T6+tUmE1uF6kTo/UQh02o31UcsY3+jaUfqqoi9lQiZlGAiRQsAlk7V3ZS5jAm8QwfCBHeBm8TPBBs2rVqkaX3vbv318OHDgg3bt3lylTpjj14QAePYGBgRIcHJyuh4rLiWwgARIgARLIkEDnzp0FLxoJkAAJkAAJkED+IpCixK0tR9KirbD6RpXS8v+5u5t65dKKhLgbY9cebMkBiDEoBFLGbnAOtc3e5t677nUlnj3z2wbHlRMtuRHRka05AONV+PWUB1SBjxmOa7rs+Cnx7sbRIlf0demya2hapaTc1qqKTDR5OV5VKzcJ262KbSRAAjlNIF8LgGY4lSpV0gJeQkKCTJgwQZ577jlHN8J/Z82apcOCu3Tp4mg37xw8mOriDW8UGgmQAAm4I2DnYexuLNtJgARIgARIgARIIL8T2HsyVgtw5vtoaKoAbLTfrEJLJ689pA+LKi+z+zvVMLoytbWroGsNsc3UhJkcvGb/afl6wW7bsxpWDJWbW1SSUXMjZP9J90U3QmxETNsJ3TUmnRfZ8a/IPuWlh8q+0alcXYYHKCG2RkeRq18RCa/v0p1eA4RMRMCtVffbs3F56VK38KaqSY8T+0igIBEoMAKgr6+vQNybMWOGvPXWWwJBsF+/fhIVFSWPPvqoIEegv7+/wBPQzpYsSXWBbtiwoV0320iABEiABEiABEiABEiABEig0BGw5v9DsYjw4oEuHF7q3UBHYyEk9p4O1aVCiSCXMZ40IEQVIqBZ9Is1hdx6MkdWxiSpvH8jZ++U0Qv2iCWiV1D0pGX1UvJMj3paNGtbo4xbAbC8qqZbMjitQEqm17Jrtsi0J1WRjwP2pxZR+QWvekTkyrtFSimR1cc1/6L9ic6t8FJ856bU4iDOPTwiARIoqAQKjACIB4QcW/D0Qz7AwYMHOz0zfLvx8MMPS4UKFZzajYPx48frN/OuXbsaTdySAAmQAAmQAAmQAAmQAAmQQKEm4Gn4L6oCfzygWbawQhiwWQA8r0KAc9pe+2uLLo5hvc71TSrI57e3cGruWDdMfl2dGkHm1KEOWlQraW3K+BiVTs6q+ea+LbJxovvxwSpMt/9PqV5/7kexhwRIgARsCWTt6wLbqfK+sU2bNgIhr0SJEvrbJ+QDNF633HKLvPfee7aL3LBhgyNE+KabbrIdw0YSIAESIAESIAESIAESIAESKGwEtlrz/6kw2Jy24ADl5WYydwU5TEMuaxfef5PXuIbZIuT3rRsauczdq1EFaVOjtEs7GppXKWXbbtu4d5HIuFtF3q8pMlJ546Un/lW6UuSB+RT/bEGykQRIwBMCBcoDEDeMEF9U6UQoMKr5BgUFSceOHaVFC+dvbcxwDh06JK+++qqEh4e7FA8xj+M+CZAACZAACZAACZAACZAACRQmAkfOqHx0JqsVXsx0lDO7lUsGy8FTadfdrKoQ92xsH8mVHSvYcfScJFiKeTzRvY4M7VJb/H1dfWYQpvzjkNYy/PcNMm1jpNMSWrkRBp0GJSeK/PeyyMqvnZpdDiq3EqmvqvpWayeCfRXVRiMBEiCBrBIocAIgQMADcMCAAR4z6d27t+BFIwESIAESIAESIAESIAESIAESSCWAaKrIs/FOOCqqfHg5bc2qlpRle046LrP+4BnHfk7sbDjkPH+1MsHyRPe66V4qSIUpjxrYXBpUCJVPZ0dIovIi7Nu0ojStbKmQfHSzKugxXQl4yoOvRheRY+r4n6dFDq10Pz+Ke/R4U7kTDspyjj/3k7OHBEigsBIokAJgYX2YvG8SIAESIAESIAESIAESIAESyA4CW5TX3UglbJlz8WFeFLnIaWtWxTmP3oaDZ+WCqsyB6sI5YRvV/GZrUtn5+uY+8z7yzD/StbYMaFVFos8nSY2wEOWkd2mNSUo4XfSRyMIP1Ckqx58n5q+8Kxv0Fen+mkjx8p6cwTEkQAIk4DEBCoAeo+JAEiABEiABEiABEiABEiABEij4BKLjk2TwmFVyIibB5WbDQwNc2rK7oblFAIxRVYB3H4+RuuWKZ/el9Hzbj0Y7zevixefU63oQVixA8BKE9iKsd/MUkcj1SvdLcR1sbfFVgmrXF1OFv5LV6PFn5cNjEiCBbCNAATDbUHIiEiABEiABEiABEiABEiABEsj/BOZui7IV/8KK+UuAb9Ecv8Fw5WVYSYUaHzblH1x/4EyOCYAHTsU53VPtrOQ5PLpJ5I+HVYiv2npqEPwGjBWp0NTTMziOBEiABLJMgAJgltHxRBIgARIgARIgARIgARIgARIoeAQWRhy3vSnt5Wbbk/2NCAM2C4DPTt4o+0/FyuPd6toW5khIviD+RX3SQnA9XNI55e14Oi7JaXSV0sFOx7YHcadEds8VObVHJGqryLZpIinO89ieh8aSVVVxjz4inZ4RCbavJuz2XHaQAAmQQBYJUADMIjieRgIkQAIkQAIkQAIkQAIkQAIFjQAKfyyOOGF7W6or1wwC4D+bnCvsfjFvt6AISR9VbOORcWtl6e6T0rFOmNQMKybjVuyXssUDdPGOm1tU8lgINFcbNm4O3odu7exhldvvQ5F140QuuIZIu5wXVk/kvBILEepb62qRdo+JhNV2GcYGEiABEshpAhQAc5ow5ycBEiABEiABEiABEiABEiCBfEJg57EYiTpnL2xdVatMrt1Fc1UJ2M6+mLtLziiPvUWXRMr5O44LXrBDp8/LM79tkD/XH5bOdctK9TIh0q1BeLpi4MHTzuG/5VSOw0A/U5gz8vrtmady+m1Unn5bRLb/m7HwF95Q5JoRIlVaiQRaqgLb3RTbSIAESCAXCFAAzAXIvAQJkAAJkAAJkAAJkAAJkAAJ5AcCi9yE/6ICb/+WlXPtFhpVKiG+6prJqvqv2Y6cjZcPZu4wN7nsQxw0BMK721WX1/sqQc6Nzdse5dRT1Qj/TVEFPLaoYh5z3xQ5vc9pjNsDHz+R9srDr/NzyuMv54uluF0HO0iABEjAhgAFQBsobCIBEiABEiABEiABEiABEiCBwkhgoSX8t6kKxb2peSXpoEJta5UtlmtI4IVXoWSg2IXoZmYRPy7dJy/1biB+Kj+g1faoysITVx10NIdKjFztf1RkhSrksX58aiVfR6/NTlF/kWrtRUrXVGG9dUWu6CsSWtFmIJtIgARIIO8JUADM+2fAFZCAVxP48ccfZciQIXqNe/fulerVq3v1erk4EiABEiABEiABEihMBKJVEYviAb7phrl6yiM+6YKs2HPSafiDnWpKr8YVnNpy66BMSMBlC4BY61HlNWgt7IFch29OU8U7lNUrckDuKTpDbiy6SPwPXBA5oJvd/wNPvysHi3R8moKfe0rsIQES8DICFAC97IFwOSRAAiRAAiRAAiRAAiRAAiSQEQEIWM+pyri/rzkk5UIDZey9raV2ePGMTnPpT1EhtmsOnJa4xAuSouZMSFahr5dMReBKu1zM+2dc19gOaV9dHp+43jjM8ha5AZ0EwKhtMnfmVGmze7M85L9L2vhsz3ju8k1EqrYVKVtfpO51IiUqZXwOR5AACZCAFxGgAOhFD4NLIQESIAESIAESIAESIAESIAF3BOChh1BW5ONDqO6k1Yf00Ejl4fbClE3y20Pt3J3qtv29mdvl6wV7bPubVC4pJYNVmGseWc9GFeTbSntk8+HoDFfwYOeaEhroZ5sf8MRR5dKXsk65AqpCHhGzlIffUummZuzmyadhhPZ2e02kfm9RbpYZroMDSIAESMBbCXjylueta+e6SIAESIAESIAESIAESIAESKDAE7igvPRe+2uz/LL8gJRX3n7IaTdvh3PxilX7TsuBk3FStUywxzxOxybKtwvtxT9M0knl/ctL8/f1kalD28soVfn30zkRbpfSslopeaZHPfl3U6RjTEk5J8N8p0qfosskfNYZR3uGO0VUBeDyjVI9/WopmbDRzSJF+bE5Q26FbEDKxRQ5EH1AqpeoXsjunLebnwkU6Heybdu2yTfffCOLFi2SPXv2yLlz5yQF1ZzSsSLqW53k5OR0RrCLBEiABEiABEiABEiABEiABHKPwMjZO7X4hysejY6XYROUN5uNfb1wt7x9Y2ObHvumharir6XIrtPAjnXLOh3nxYGv8ngc2rWWfLtojw5Ttq5haJdaMvzaejoHIsJ8fSRFBhadK8/4TpJSRWKsw90fh6h7bXmPet0rUryc+3HsKfQEjsUek1eWvCJbTm6RKX2nSLkQ/rwU+h+KfAKgwAqAH3/8sbzwwgtazEN+DBoJkAAJkAAJkAAJkAAJkAAJ5DcCMQnJ8t2ivR4te9yKA1ImxF+61g+XRpVK2Fa+NU/039Zj5kOn/WKqsEgzVQHYGyzAt6jULVdc1h909eS7qUVlKZKiHDi2/S31IxbKLP8ZUssnzRPQ3fqjLpaUlSn1pHTlutKu/dWpIb6+Ae6Gs50ENIEZe2fIm8vflOjE1LB0CIGjrxktPkV8SIgEvJ5AgRQAZ8yYIc8884yGD4++tm3bypVXXimlS5cWHx/+Ynr9TyUXmO8IHD9+XD799FP5559/BJWC4+PjpXz58tKxY0d58MEHpUOHDm7vCVWF9+/fL4MHDxZUHN6xY4d8+OGHMmvWLImMjJSSJUtKu3bt5LnnntO/y24nUh3w3v3yyy/ll19+ke3bt+vf99q1a8sdd9whjzzyiBw5ckRq1Kihp/jhhx/k7rvvTm86j/u6dOkiCxYskM6dO8v8+fNl165d+h7+++8/fQ/lypWTbt26yauvvirVqlVzzLt582b56KOP9LlYW9myZeX666+XN954Q8LDwx3jrDvLly+XadOmyeLFi/V9njp1SgIDA6Vy5cp6DcOGDZMrrrjCeprmjPvHlyIvvviivP322y5jzA0TJkyQ22+/XTfh2fbq1cvcnWe8nRbBAxIgARIgARIo4AT2Ho+V8yr3n6f2mQqXxatmWIh8c9eVbguDbDly1ilk1jp/25plMhQQrefk5DG8+6wCYLB/Uanhr0TBr/uLRG0VBD/XcvNxL/ZigGy7WE22plST5SkNZFZKS0kSX5l9YyeRLBRPycl75dzeQyAyJlLWRq2ViNMRsvnEZllxdIXT4pZFLpMJ2yfIHQ3ucGrnAQl4I4ECKQCOHDlSsy5VqpT89ddf0r59e29kzzWRQIEgAJGrf//+Eh3tnJwZoh5eEOMgvn322WcZCvB//PGH3HnnnRIXF+dgExUVJVOnTpW///5bxo0bJwMGDHD0mXdw/WuvvVYgjpltzZo1gtfEiRPl66+/NnflyP7s2bPlpptu0ikHjAuAw5gxY7RoB6Gwfv36AnENAmRiYqIxTA4dOiSjR4+W6dOny9KlS6VixYqOPmMHIumQIUOMQ8c2KSlJkPYAr2+//VbzHjp0qKMfOxAf8X4I4RDXz0gABG8YhMkePXrofeMfb+FtrIdbEiABEiABEiioBE7EJGTp1vaciFV583bJqIHNXc7Hl4Fv/L1VfSno0uVouL9j6pemjoY83qlaOshlBV3LxkjRH3uKnDng0mc0TLvQRj5Nvll2XawoF1WAsNWqlwmxNvGYBCTpQpKMXDtSftn2iwqTd59GLDw4XGqVrEViJJAvCLi+A+aLZae/yNWrV+scEPC28SbxD0IGvHawrp49e0pYWJheJ7wUL9cTCYJJzZo1HfPBq8oTw3nvv/++tGrVSntIhoSEaHHi6aef1uKNJ3NwTOElsH79eunTp48W//z8/OTJJ5+UefPmycqVK7XYZnjbffHFFzokPz1SmzZt0t5m8Jb7/PPPtZC3bNkyef3117V324ULF+SBBx4QeBva2W233eYQ//B7D8EP7wUQ0+ABiDU99NBDdqdmWxu8+G699VbttThq1ChZsWKFzkH6xBNP6N9NvAfcd999smrVKrnrrrukVq1a8t133+m1gdugQYP0WiAYPvXUU7brgpcjvtzAewZEReQ4Xbt2rX5vGTFihH5fAatHH31U5s6d6zIHWMDgqQmR0Z2dPHlSIO7CcE++vs7fF3kDb3drZzsJkAAJkAAJFCQCx20EQOS8e7FXfZXvr5H8+1hHubNtVdtbXrPvlEv7BhVGW+OFf2XlXue+8OIBckebqvJYtzry5yPtpY3yAPQmq1IK/n1pVrvIIXnn7LNuxb/4UnVlSfsxUuG+iXJrz2skPNRVQMRsyDFIIwEzAXj93T3jbvl568/pin89q/fUOQDbVmhrPp37JOC1BJw/0XntMjO3MMN7KL2ww8zNmD2jIWzklEFUxAf6zBjCFBHSFxER4XQaQjDxgjABDyCEJOY3w7c0ZxJcc4Tkt/vIzHpLBpTM9dwTEOTgwVa0aFEtQJm9xCAqwzMQv4dbt27VIbEQvRo2bGh7WxCxEKoP0So0NNQxBiH8COOFZyC8zuBRCKHRbH/++acW+tAG77vffvvNydvwuuuuk+bNmztSA5jPzc59/C7VqVNHlixZor3mjLnBAAIaQpvR17t3b2ndurUOcw4OTvtjFqHECJ/G+idPnqzFTnjfmQ1fHiAs13we+nF/mPexxx6TTp06ycaNG+W1116Tq6++2ny6fiYYA4/B8ePH6/BqpwGXDrAGjIEZouGlLvEW3sZ6uCUBEiABEiCBgkzA6gHYWRXmeKRrbadbHtG3kbSqXlpmb4uSvzcccfQdORsv0fFJEhrop9sSk1Nk6Li1jn5jp3KpIJn9VGcJ9CtqNHndFiHAReWC9PZZrir7LpdOPhslIDn1bxXHYksrT6wW6gvVKm0lsEobaX8p/dOV1UrL/Z1qypvTtsr3i9M+Mw1sXcVxKncKN4FklUcSIb7LI5drr7+zCWfdAinuX1xebvOy9KrZy+0YdpCANxIokAJgpUqVdNVfc2idt8GvWrWq9rQzPGwuZ33r1q0ThD0jBxi8sFDtOCPDGIgFhvh3//33Czx6goKCtAfXO++8o8UWhFtCsGjWrFlGU3pVP8S/zr929qo15fRiFgxYIKUDS+f0ZRzzw6MOnmww/PyYxT9jEDzVUIkbAhgqcCM/H7wB3Rk82szinzEOgtezzz6rc/jB480qACJsFoafX+zb5fqERx0ELwiNOWkIdbaKdrgewnEhAMJOnDih8/5ZRTz0Pfzww1oAhKcfPCD79u2LZofh/S09K1GihMAT8IYbbtChvvDkK1Mm7Rt87EMQRUj1pEmT9HuH1bsP8xvhv/Asvuqqq5wu6U28nRbGAxIgARIgARIogASOn3MOAQ4r5lqowseniPRrVkl6Nqog0zdFSrKptO+707fLk93ryoczd8ivqw/aEnqxVwOvFv+w6GpBCTLe/21p47Pd9h6kvKp+PGiqSEiYfb9qhYfjhJUHdDXhQD8f5TlZze1YdhQeAquOrtJVfQ/HHLa9aX8ff2lbsa3UKVlH6pSqI50qdxKIgDQSyG8ECqQAiJBEFCSAcGX94JqXDwheevCKwgvegPv27XMUJMjquhDqB/EFW3j7fP/99x4JgB988IHs3LlTXxYhwMOHD3csAczgiYSCBvCmRPgiChvQSMBMALnuDLv33nuNXZctwnEbNGigc9OZz7EObNy4sTRp0sTarI8RJg8PN4TY7tmzx2kMhDLk1YNB2LIT39CHORBim5MCIAqWIA+hnSEcunjx4vr3E/cJJnbWtGlTR7P1Xh0dpp3Y2FjtKYitUfEcXwQYtmHDBhcvQHj0QQBEODWKrcCr0GwHDhzQ759oM4qAGP3exNtYE7ckQAIkQAIkUBAIJF9IkVGqeMey3SclLilZelxRXga3qy4nYtLyBeM+w4r7u71df18fqaGKf0RExTjGjFeVgfFyZ1epUN+ejcq76/aO9rhTUunv26SyO/Gvciul7v2uvg0ume56a5YtJnOe7iyr953WFY7hVUgrvAQQNTZm8xgZtW6U21DfqsWrykddPpL6pesXXlC88wJDwKfA3InpRlABGBV/UV3z6NGjpp683UVlT4TTZmcoMIROFDioV6+erpLqyR0irA9eSjCIEMj3ZzVUXTVEHYgrhqeXdRyPCy8BVLCF+fv7Z+gh2qZNGz0WHqfuPHNRGCM9w+80zOrhunv3bjl//rzuQwhxetayZcv0ui+7D+G/EBrdGQRCWN26dd0N0fkDjU7rvRrt8CBEFV/83kNUhLjYqFEjgYiKF7x7DcNYq8GrEOfBDE8/8xgUCDHERGv4rzfxNq+Z+yRAAiRAAiSQ3wm89c82VbQjQlaqvH2bD0fLx7N2yuAxK+VYdLzTrZW18QA0D6hbPnOeSV/e0SLdv1/Mc+fJvhL/5Od+UuToRtfL+yh/lmZ3pnr+ZSD+GSdXKBEkfZpWFIp/BpHCt01KSZJ1Uevk8XmPy6drP3Ur/l1T7RqZeP1Ein+F70ekwN5xgfQAROVM5KhCCByELBQUQK67gmYoFACvQhhC8iDEeGIoNnD2bGpOg8GDB9uGS2IeFBkwqqaiOis8F2kkYBA4dUr9MaYMwpxdCKkxDtvy5VO/VYaodPr0aVsR3C4c1jyHEdYLb1ezYT7D3Hn/edpvjMvq1tN7SG+ccZ9Yg/Ve0QbBH16GCO31xAxx1DwWodI33nij/Pzzz7rCMjx9zWsyRMEWLVroVAXmc72Jt3ld3CcBEiABEiCB/Epgy5Gzsvt4rPy4dJ/LLaxXBTusZhcCbB7T44py8s/GSHOT2/17O9SQUiGefYZwO0lOdRxaI7JurMi2v0TiLH/3hJQVufoVkStUqpSgUjm1As5bwAjEJcXpyr5/7vpT4pLjbO+uRoka0r5ie+lapau0Kt/Ku8Vx2ztgIwm4J1AgBUAj6T2ECYS5IiQYnjfwzjF/yLXDAu+dOXPm2HV5XRtyiiHsD2GNCNn11BYvXuwYijBfdwZvKfCCOIBw6vxkKIiBnHiFyXDPeWHpebzlxXoK8jXhPYmKvBD/EOY7bNgw6devn/YoRL7FgIDUnEAIHUaFYZjhyWflAs8+CIB4D8EXJgMHDtRDtmzZIqjIDLN6/+lG/kMCJEACJEACJJAtBM4nXpAnf10vM7ZkLmIpIwGwT5OKusLvuHTCfo0bQLiwV9ry0SIznldLu+i6vFCVD/nuaepb6JqufWwhATcEtp3cJsMXDpf90fttRxSRIjK02VB5oMkDuV5Y0XZBbCSBHCBQIAVA5KszixKG1xGKFrgzjMc483nuxnpD+8SJE+Xff/8VfOhHqHNmDBVZDUsv7BJeXai+imqi27ZtM07JF1ufIj65WhAjX0DJ5kUaIbkQo5AXLj0vQCMUH79f+JnNTjPPh5x26VlG/emd6w19qJBs5AVEQZX77rvPdlmGd6Zt56XGbt26aU/MY8eO6TBgQwA0vP/giYjCQFYrTLyt985jEiABEiABEshOAp/Pi8i0+IdMIzXLpi/aoSDI2zc21oUu/liXWtTAV7XVKVdctkVGO91CRnM5Dc6tg72LRGa+oK5G8S+3kBfk6xyLPSb/7v1X5/lD6K+dwZHivU7vSbuK7ey62UYCBYZAgRQAO3XqlG+EvKz8JCEED4U5YO+++67bogfu5j506JDuCgkJcco3Zje+SpUqWgCEcJKQkODwMLIba24zrmFuM+9HRnoWlmA+h/veRQA552DwSlu/fr2kl1/PEN/hhetpqLqndwtPN1TAjo+P1+Gx6Z23evXq9Lq9vg/eeYahQrc78+Q+ixYtqgU+5BFFNXIIuRB1kf8P1rVrV0E6BasVJt7We+cxCZAACZAACWREYP/JWJmpPPrOnk+ScqGB0qF2mBLsirmcBseD9ApzuJxwqeHe9jWkYskgd91O7W/e0EhqhxcTVBHu37Ky1C8fKr0/WyTbj57T40qr0N9mVfImgsRpoeaDmCiRyfcq7S/F3Jq6X72jSL/PRUpVd+1jCwmYCOD3a0rEFPlxy4+yL3qfqcd5FxV9O1TsIIOuGCRlg1VYOY0ECjiBAikAFvSKtajYC68dVOtFBeDMmlFYoFgx1z9GrHNBJDQsJibGYwEQwiGtYBPo3r27vPTSS/omx4wZ41YAXLZsmRhepzgnuw2ehxD9IWLNmDFDV7a1ywWIPwTGjlV5ZPKxwdPSMITuGoU8jDZsU1JS5Nv/s3cd8FFUX/dIeg8khIQWCKH33qsCShFRKUovAkpRsXx28W/BgoIKKgKKUgQUUBGV3qtARJDeQwkpkEZ64vfuC7OZnZ3dbHqyey+/ZWZem/fObHZ3zpx774IF6iKz++TiSwQgJQZatWqVzMJM2cnJzLn/2hPeEgj+jxFgBBgBRoARsBIBItr6fbYbCak539dCeAdy2W1UxQfd61bE8HbBUqgQKdreTtJXI2lP16SqD3rUC5BZgRtU9tZWmz32dHHE5O6hRvXfjW2D//12AvGCoJzaQ4RHci5Ft4NZmdnkX+JNozmjlSAEO0xhl19jVPjIDAIJaQmYsXcGNl7eaKYF0MivkVT8VfeubrYNVzACtoiATWYBtsULpaxp586dILKFbsIp8Ud+XJZJKUVmjRJLiSlG7fWSCVA5m30i0KZNGwPpR4STXuxMSjYzceJECRC5lD755JNFApZyDnqPTpo0SZJg2hN98sknOHLkiLa4TB2TglKxxYsXK7tG25dfftnqdVJiH2VMcv1dvny5HIsUlY888ojRuOoDe8FbvWbeZwQYAUaAEWAEckNgy8mbRuQftc8SXqxE9m09FYnXf/kXfQRBOPOPk0LItie34WT98vFt8euUTnjmvjrIC/lnbnBSJc57vAWWjGuLNjUrmGtW/OW3LwE/i9+JF3canztUPDzuM4vJP2NU+EgHgSyhGj1y8wiG/jbUIvk3uuFofP/A92DyTwdELrJ5BErRIx+bx7rACyQX3AkTJshYhU8//bRU6+RnULq5JyPXzdyMzqkYZQ611sLDwy02JRdgIpDYyjYCRPy1bdtWvpco0zYlpaCkO6QcDQsLky7qSsy6559/HorbcGGv+uGHH0avXr2kCnDNmjVSETht2jQZw5Lc15cuXSpf9J5T3JHzQ54X9rzzOh5l/w0ICEBkZCRee+01kFqPsvn6+/vj3LlzUvlHRGzHjh2tTtxDSr8ZM2Zg7969OH78uJxSv3794O1tXmFgL3jn9fpwe0aAEWAEGAH7RmD3uehcAaAYfNo4fEqneoFeqF7BHRtPZCvg6gd5o12In1Jtm9t0IUz48/+AI9+buv16iVAkA78GxENkNkZAD4FMoRrdcXUH1p1fh4MRBxGfZhzjUunj5eyFVpVaYXj94WgTxPegCi68tT8EmAAsQ9f83XffxenTp0HutW+99Va+Z664DZJLb25GboaKWeMyrLStWrWqsstbG0agWbNmWLduHQYNGoT4+HiZkEYvKc3kyZMxc+bMIkVi5cqVIIKMCD7KWq3NXN28eXNQ4gwlVqFChBfppAp5cCJWKXPvQw89JGMezp8/H/RSG2UEnzt3rtVkq0IAkos0KTbJzLn/qs9jD3ir18v7jAAjwAgwAoxAbgh4ueb/1urxttXxnkjcQd/H209HIToxFX2bBAnuS/gQ27Ktfw74e6npCu9xAAZ9C3jYOAFqunIusRKBY1HH8PLul81m9aVhvJ298b+O/0O3qt3gUE68p9gYATtHIP/fUqUAuCtXrhhmUb16jv++utzQIA876rHy0K3Im37wwQfyHBRHjUgXPVMIO9pSpmAyUgz16NHD0JzIuQMHDoDaxMbGWkwEoij5KKaa2h3YMBjv2D0CpLwj9dmcOXNkZmpS/JFytFKlSujcubN0ye3UqVOR4+Tr64vdu3dj3rx5Uu1HZDmp/ChpBSXMoMQ5p06dMszDx8fHsF+WdojkpCQflACIsgKTwpHW3qBBA0ncjRs3Dnn5DKRM32plJGX5JTVnbmYveOeGA9czAowAI8AIMAIKAlEJuXvXKG212xbVy8si+u3SXcT7swv7d60++VfOCej/KVC9nV3AwIu0HoH0zHT8HfU3tlzZgpWnVyIjKyfepnaUJv5N8FHXj1DZUyhJ2RgBRkAicI94yqSTX71soENZLMnoi1IdHF8pz88qtGPlZwxr+5D7Xs2aNWXzUaNGwVxML2U8mlt+rGvXrlAnRnnjjTfw9ttvy6EoQUO7dvpfroQp3eQTUUhJFnbs2JGf0+v2oSzBSqIQIhnzohg8e/asvN4UB1GJX6Z7Ei5kBDQIkCvwiBEjZCmRlkQOshUdAsWNN382FN215JEZAUaAEWAEckdgwLw9OBoea9TwyOs9kZKeiQfn7haqPmOC0NWpnKjLQufa/lgwshVcnexIoRQbDnzVEUjJ9j6QoDmKMEWU8KOdiAXoywkFjd5IfIAd4Tvwv33/Q2SyyBRtwap5VcOAWgMwttFYODkIMplNIlCQ+2+G0HYQKNMKQHPcpbly27lsBVuJWo1FpJ45ApBURoqikGKKsTECZR2BH374QS6BFK0hISFlfTmlfv6Md6m/RDxBRoARYAQYgUJEIFok+1DbV8NbooKHsyz6dnQbPLMyDBej7+CxNtXxvwGNZHliSga83RzzldhPfa4ysU9Zfi9sA44KL6WTvwEZycbT7jcHaPaYcRkf2T0CdG///Ynv8fGhj/Gf+KdndcvXxdB6Q9GpSicEegTqNeEyRoAREAiUaQLw229FXAgdM1eu07RMFVlDbNaoUQOXL19GcHCwTBCgt0CKEUbujxTv67vvvsOLL76o+6NDrUikRANsjEBpRuDatWuoUKECzCWrWbhwoXRRpjWMHDlS9z1fmtdX2ubGeJe2K8LzYQQYAUaAEShuBJLTMsXvCUjlHv1Oj9IQgIE+2Yn3aF6Nq/pg47NdQf486rh+Pu52olBKFbHHVwkvjPNb9S9To0eApkP167jUbhFIyUjB+wffx+qzq81iMLLBSDzb8lk4livT1IbZ9XEFI1CYCJTpvxJym9Uzc+V6be2xzNnZGZQhldyAT548iVmzZuGFF14wgoJcgxctWiTLyIW4devWRvV8wAiUNgQ2bdokyeyhQ4eCSG4iwbOysnD+/HlQwoqff/5ZTpliE7788sulbfplbj6Md5m7ZDxhRoARYAQYgUJE4NPNZ/HpljPwcHbErMFNEeLvgbTMLKMzBHi5GB072HpCD6PVag42vGKe/PMRsdz7fkJxnTSd+NAeESAyfeuVrVhzbg0O3jiIlMwUExhI8dexSkf0qtELDf0amtRzASPACOgjUKYJQP0lld5SSlBAcccUi46OVnZluVpxRxWjR4821Bf2DhF+RIqcOXNGkiY0LyJOSD21bds2vPfeezLOHh1Tcgc2RqAsIEAJMT7//HP50ptvUFAQ1q9fDz+/nIxylAiHYmLkxxo1ynbfyU9fW+iTH7xtYd28BkaAEWAEGAH7RmDLyZuYvfmMBCEhNQMTlxzWBcTPM9v9V7fSngrPbACOfGe6YlJs1bkf6DMLcPM1recSu0MgU7iJzzw4Uyb4MLf4ac2nYXzj8ezNYw4gLmcELCDABKAFcAq7ilwQyeVWz/bs2QN6qa0oCUAvLy9JhFC2Twqc//XXX8uX+vze3t5YtmwZmjVrpi7mfUagVCLQr18/fPnll9iwYQNOnDghs+MmJCTIRDb169dH//79ZUZieu+rjZSBY8aMURdZvW+NW77Vg5WxhvnFu4wtk6fLCDACjAAjwAgYIbD3fDSm/RBmVKZ3EOjtChdHO0rqoQcCld2JAX6ZYlzr5AHc+4bwi34U8PA3ruMju0WA3H3/b+f/YWu4vpu4q4Mr3u30rlT92S1IvHBGoIAIMAFYQADLcvfQ0FCEhYVh3rx5+PHHH6UKMS0tTWbnJWLw6aeflm6UZXmNPHf7QcDf318SfJMmTbKfRZfgShnvEgSfT80IMAKMACNQIghs/DcCUwT5l5Zh7OqrN5kxHWvoFdtXmXDlxPpnBQmoydp6/3tAy9H2hQWv1iwCRPwdunkIXx39Ckejjpq0K3dPObSq1ArPt3oe9f3qm9RzASPACFiPwD1CwaKfSsf6MbglI5BnBAqShpwUixkZGXB0dETt2rXzfG7uwAgwAraJAH822OZ15VUxAowAI1DSCGSI2H4rD4XjjV/+RWaW+Vun8iKhx331K2Fg8yroEGrHyja6vbywHdj1MXBpl/Hlq90beHwlx/szRsUuj4j4+/TIp/jpzE+6cf6cyjnhhdYv4IEaD8DXlV3EC/omKcj9d0HPzf1LDwKsACw914JnwggwAowAI8AIMAKMACPACDACpQiBbaciMWbxX2Zn1ERk960pEoAMaV0NbWpUgKNDObNt7aKCyL/fngEOLzZdrlsF4MHPmfwzRcbuSm4k3sAz25/BiZgTumv3cvLCpz0+RetATkSpCxAXMgL5RIAJwHwCx90YAUaAEWAEGAFGgBFgBBgBRsB2EYhNSsO0Ffrx/oYKwu/dgY1h15l99S79Xwv1yT9q238O4FVJrxeX2QkC5Hy478Y+vLzrZdxKuaW76gD3AHx131eoXZ49vXQB4kJGoAAIMAFYAPC4KyPACDACjAAjwAgwAowAI8AI2CYCC3ddREJKhsnixnasidf71ecspFpkok4DG1/TlgrSLwjo9Q7QYIBpHZfYBQLHo49jyYklOHDjAGJSRGIYjVGcv6YVm6JL1S4YVGcQfFx8NC34kBFgBAoDASYACwNFHoMRYAQYAUaAEWAEGAFGgBFgBGwKgc0nb5qsp0MtP7zal8k/E2AyUoHV4wAR183Ies8EWotyRxejYj6wDwSS0pPwedjnWHZyGf4T//SshncNzOk+B7V8a+lVcxkjwAgUIgJMABYimDwUI8AIMAKMACPACDACjAAjwAiUfQSyRLKPi9F3jBbSs0ElfP5Yc3b7NUJFHFDcvy3/AyKOGde0mQC0f8q4jI9sHoHMrExcjLuIf6L/wdf/fI1ridfMrpkUf+93fh9ezl5m23AFI8AIFB4CTAAWHpY8EiPACDACjAAjwAgwAowAI8AI2AAC12KTkZqRZbSSdwc2gquTg1GZ3R9Qtt+t7wJXDxpDUbEe0FOQgmx2g0DWfyJb9umVmH90vq6brxqIQI9ADKs3DCMbjgS5/7IxAoxA8SDABGDx4MxnYQQYAUaAEWAEGAFGgBFgBBiBMoLABY36z8vFERU92Y3VcPmuHACWDwZSYg1Fhh0HZ+CRRYCTm6GId2wbgcvxl/HGnjdwJPKI2YU6l3PGE02eQN+afVHVqyrH0DSLFFcwAkWHgM0TgFlZWdi2bRv27duHiIgIJCUl4d1330VQkAhGe9fS0tKQkZEBBwcHuLjwF7uCC2/LNgLpmdlPrZ0c+Kla2b6SPHtGgBFgBBgBRoARKG4ELkQlGp0ypKIHExYKIid+AVaNVI5Mt72EIjCwkWk5l9gUAlcTrmL3td34O+pvbL68GamZIg6kGWtZqSVmtJ+BGj41zLTgYkaAESgOBGyaAPztt98wbdo0XL582QjL559/3ogAXLhwIaZOnQpPT09cv34dHh4eRu35gBHICwKJRxPh2dQzL10KvW10QipuxCXLULuVvF1Br7JuWSK+zH/i5VCOCc2yfi15/owAI8AIMAKMQGlGIFPE/1v/zw2jKYZULNnfdkaTKcmDhAjg12n6M/ANBu57E2j0iH49l9oEAiki0cvcsLlYcnIJyO3XnJGbb0O/hugZ3BMP1HyAXX3NAcXljEAxImCzd9ILFizAgAEDcOnSJUka+Pn5ya0etuPHj4ePjw8SExOxdu1avSZcxghYhUBqRCr+7vE3aFtSRj9aI+JTDHm2bor9tIzMkppOoZz3dlIaTlyPx8kbCYhJLBxsY8WY9HSfiFIiF9kYAUaAEWAEGAFGgBHYfyEGj361F4cu3zYCo0V1X6NjuzyIOJ6t/NNz+202HJh6mMk/G39jhEWGYdC6QfjuxHdmyb8qnlWwoNcCbHp0k8zu2zekL5N/Nv6+4OWVHQRskgA8e/YsJk+eLK9Cjx49cOLECURGRpq9Ks7OznjkkUckQbhx40az7biCEcgNgfAPw5FxKwPhH4Xn1rTI6pPTMkwIrbjkjCI7X1EPnCnc+K/dzibpiKiLiEsBkZwFseT0TITfSkJiagaihFqSSFJSF6aIcsV1uiDjF1ffDOHmnZiSbnK9i+v8fB5GgBFgBBgBRsCWEPjwz1MY+vV+hF0xjmtXrYIbHm5R1ZaWmre1pAp36NVPAF91BMJF7D+tNR4E9J8DODhpa/jYBhDYe20vXt39Kvqv7Y+Rf4zEpfhLuqu6B/dgeP3hWPPgGrQLaqfbhgsZAUagZBGwSRfg2bNny5h+jRo1wu+//w4i+HKzzp07Y9GiRQgLC8utKdczAroIkOrv+pfXZR1tq71QDS6BxR9TMinNVO0XL0iiil7FPxddoPJYSOSlWqGXKYi6VKFodHfO/8dXXFK6QSFJ07mVmCbIvywkCJzuueceVPZxhV8pD/RNJOb5yESJjbOI81i7kie7R+fxvcXNGQFGgBFgBBgBBYGdZ6LwxfbzyqFhK34WYNajTeEhkoDYpYkHsfhpDHBWRyTh7g+M3wRUCLFLaGx90bFC6fnegffwx6U/zC6VEnv0qtELzQOao33l9qjmVc1sW65gBBiBkkfAJr/Jtm7dKm/in3nmGavIP7oMoaGh8mqEh5eccqvk3w48g4IgQOq/rJTsOBhZyVlSBRj6cfb7qiDj5rXvHR0CMFmnLK/jllT7+OR0k1OnZWQJAtCk2OoCIs/URqQikX9kpAS8FpsMZ8dy8HItvU+ySQmpEKNpQgl4606aIHnLfqxH9XXhfUaAEWAEGAFGoDgQIM+Ct387oXuqMR1qom2In26dXRTu/8I8+ffYCib/bPBNQL+Fd1zdgbf3vY3IZPNedI39G+Odju8gxJcJYBt8G/CSbBQBmyQAr169Ki9X06ZNrb5sSuIPyhLMxgjkFQG1+k/pWxIqQPrCThIuwFojoihL/LgtV048xi4mIyUd2ZtvvokZM2bI/bz+R+6/CcJNV2tEeOXXzGGkHS9GqAJLKwGYQbjcJSyVeTMBqCDBW0aAEWAEGAFGIG8I/Hk8AmeFql5rtQM88ULvutpi+zm+LjyjNs/QrFf8vuv+KtB2IuDqranjw7KMwKGIQ1h+ajloezvVOAamel1ezl4Y33g8RjYYCcdyNkknqJfL+4yATSFgk3+xCvGQFzIvJiZGXlhKBsLGCOQVAbX6T+lbEirAVKGMMxcfL0MQgM7FSAAqOBRkGy/cf4mw0xopAPNr1NccRuoxtSpBdV1J7yekmJKidH3ZGAFGgBFgBBgBRiDvCGw+edOk01PdamFil1pwc3YwqbOLAor799M4IEvtiSHIvxFrgFo97AICe1lkWmYa5hyZgyUnlphdsreztyT8OlbpiLrl68KJ4z2axYorGIHSjIBNJgGpUqWKxPzChQtWY797927ZNiSEJcxWg8YNJQJ66j8FGlIBFmdGYL34f8pcSDVW1ixOx/2X1lAQAjBJ4/6rxeSB9k3QtFp5vDRtksymfOtOqlRPatuV5DHFMNQakZqUFISNEWAEGAFGgBFgBPKGwNFw46Qfbz3YEC/eXw8+7qU3FEjeVpiH1vR78dR6YHEfESRZExOx49NM/uUBytLelB6y/xvzLx5f/7hF8q9D5Q5YO2AtJjadiEb+jZj8K+0XlufHCFhAwCYVgN26dcOZM2fw3XffYdSoURaWn10VFxeHr776SsYNpKzBbIxAXhDQU/8p/YtbBZik4y6rzOWccG2pH+QtvrTLBu9vzv2X1pNfF2DKkEwZha21SJEdmCxauAOHCjegcnfdmq3tXxTtiOij7MV6RlmMPcvI9dWbP5cxAowAI8AIMALFjQA9VLsQfcfotM2r+xod281BsnD7XDEMuLzHdMmVWwA9XjMt55Iyh8CxqGNYdHwRDt08hLjUOLPzr+JZBaMajsKQukPEb+Cycf9gdjFcwQgwAhIBm/xLnjhxoiTzduzYgcWLF1u81OT6+9BDDyEiIgKOjo6YNGmSxfZcyQioEbCk/lPaFacK0JICkOZDceLKilH2Xz33X5p/esZ/ZuvMrS8uOU3G91ESZ5hrp1dOxNrxa3FCeWicPESvbVGXJYrYf+bWwG7ARY0+j88IMAKMACNgawjsOR9ttCRKAlYv0A5j25Hyb/UT+uSfsyfw6CKA3T6N3itl7SDrvyws+GcBRvwxAluubNEl/yir77Mtn8Wfj/wpX4/Ve4zJv7J2oXm+jIAFBGySAGzevDmefvppSRCMGzcOQ4YMwapVqwww7N27F8uXL8fkyZNl9t+dO3dKwvD1119HcHCwoR3vMAK5IWBJ/af0VVSAynFRbcn9MyUXgurmXUVbUc2hMMe1RFYK+g/peXB3JdXc9dhsNV9B5nhDZN4taSNi1JyZIwbNtedyRoARYAQYAUbAnhEgRf27608aQdCosjeIBLQ72zULOLfJdNnlawDDRdy/CiGmdVxSZhC4lXILU7ZMwWdhnyHzP/0H2qG+oVjRbwXGNhoLUv+xMQKMgO0hYLPfbh9//DGefPJJSQL+9NNPeOyxxyTJR5eQFIIjRoyQbr/k/ksqIyIMX3uNZe229xYvuhVZo/5Tzl4cKsDcYtspc4lOTAW5A1+7nWRVMgzqd/36dbz00kto0aIFKFGOk5MTKlWqhMaNG8u/LVLaxsfHK6fQ3f7111+ybdWqVeHi4gKK1Ul/hydPGv/wps6UyVidzThLPJX+bc1KTB45CD1a1EXLkABUDgpE9+7d8cUXXyAtzbyykTIQOwq32AaVsxP8JMTHYf6cjzD4/i7o1DBYxvv7ZdVyjBvUT+5fvxou5//rTz/IY4oHqLwe7dcbBY2luH37dvlZRMmKaJ8+fxYtWoROnTrBz88P3t7eaNOmDZYsMQ7ETGv84ssv0b9nV3RuVBPt61XDqIG9sWHdWgPeemEeb9++jW+//RbDhw9HgwYN4OnpCWdnZwQGBqJ37974+uuvzeI3duxYOVc3NzckJCQYzmNup27durI9zV/Pjh8/jpEjR4LeA66urqhevbqc15EjR2Tz0aNHy/41atTQ685ljAAjwAgwAoxAoSLw4Z+ncC3WODTI0NbVC/UcZWKwc1uAbe8ZT9XdHxj4NTDlMFC9rXEdH5UJBJIzkvHt8W8x7Pdh6L6qO3Zd26U77wC3ADzR+AlJ/tUuX1u3DRcyAoyAbSBgkzEA6dLQzfW8efOke+/7778PcgcmEkFt1KZ9+/aS+HvggQfUVbzPCOSKgDXqP2UQRQUY+nGoUlTo26RU/ad52hNdv/tDN0lwZuVEVuAgHzdtE6PjXbt2oV+/fiYEX2RkJOhFpM6KFSvg7+8v2xl1vntAJB2R7BkZOeo1IhWXLl2KNWvW4I8//kCXLl0MXdVZbuMEgfXMuMdx5K/9hnraiYmOlgQakWhz586VY2gVvKSIS1RlzL188TwmDXsY18OvGI2Vl4N4kZikgoeLTESSKhSX7s6OcMhnduX09HQMGDAA69atM5oCkaVElB06dAiffvopiMSjUAWkVlbb34cOgl7hly5g/NTndF2DSRF9+fJldTe5f/PmTWzcuFG+KAbq77//LklBdcNhw4ZJ8jAlJUVeJ0sxVWmuFHuVjPppja41EYq0ZsXCw8OxbNkyqdBesGCBUsxbRoARYAQYAUagyBE4ePEWvt9n/P3YLqQCHm1ZtcjPXWpOQPdG5wX5tybVoxEAAEAASURBVGaCmNJ/OdO6xwEYtBio2TmnjPfKFAI3Em9g6tapOH37tO68Kabf6IajMbjuYFT2qCzvnXUbciEjwAjYFAI2SwAqV6lnz56gF6lXwsLCJGGRmZkplTbNmjWTpIXSlreMgLUI5EX9p4xJKsBqL1SDS6CLUlRo2zvChSUyIe/uqbfvpCPQ29Xsl35qaiqGDh0qyT8vLy+pqiXVXUBAgFSNXbx4EeRSv3ZtjgpNu6gNGzbg4MGDUi1IJCCpBpOTk2UfIreSkpKkEvDs2bNSmUb9aT1k9Lc6dcwQHD38lzxu1a4jho5+AlWqBSPy5g38vHIZtm1YL1WE9957L/7++2+pcJONxX/ht5JwR6gJFXt+4ihERtzAxCcn4+GHBojPgQqStHIpXwktP56H5KQ7mDziUdwUbYiYm/HW/3A+KlHpDjd3D9wWwcJdHB1wUQQMJ4LRWagLa/p7wMVJ/FjOo1HYgQMHDkjC7PHHH5cEHJFopFo8ffo0PvvsM/Tv3x+ff/65xHn0uAlo1+N++JavgFP/HsO8We8hSuDwxccz0a1XH1Rs1cxkBoRh27ZtJTlLZCApN0lNSNeOSLk///xTfjbSdSYyVW10rStXriwVoETUWSIAKawCmYODg3zPqMeh9wip+2gu7u7umD59Onr16iWVoEQczpw5ExMmTEDDhg3V3XifEWAEGAFGgBEodAQohMjM30/hmz0XjcZ2dSqHDx5pIh+OGlXY6sHJ34ANrwCxxiSoXO59bzL5V4av+9Goo3h669OISYnRXUUF1wr4sMuHaBvEyk5dgLiQEbBhBGyeAFSuHZEXaoWRUs5bRiA/CORF/aeMX1QqQMqWS2SU1hyEwjVTEFSWjNxZKXGIh4v+R8GePXsk+UNjfDB3IYYNGghvNyfDkO3atZNuvbNnz5ZEnqFCtbN//3706dNHEn7keqpY586dJRFPrvdXrlzB+vXrMXDgQEmqKclMflzyjYH8e3ToMLz24ecGsrIBmqFbzwfw+QdvY+HcT3D+/Hm8/fbb+OCDD+QpiJyL18TLO3f6JL5ftRbDHnlQmQZatmwp1MH/IUEk1yC0XF2y5+jr64tmTZugppBKXhZEomJETl6OySb/qIwyEl+KSUKdSp6GuSltc9sS+TdnzhypjlTakps1ZTKvU6eOfHBBxGC0UDuSUrJpJ/EwQ8yTrH7jpmjYtBmG3N9VEmurl3+Hti1NCcCtW7eidm1Td44OHTpI4pHcg0mZRyrpLVu2gIhUxcqVKyfJvE8++QQ0DqkGiUDUGqmrV65cKYupv7YNxVsl8o9cv2kcIiQVI3fhRx99VKqx6SENGyPACDACjAAjUJQI/HE8woT8o/M936sugv08ivLUpWfsf8WD2x9H68+nXj+gwzT9Oi4ttQikZ6bjSOQR7Ly6EytOrUBalnD10Rgl+OhevTtebP0iAtwDNLV8yAgwAvaAgM3GALSHi8drLBkE8qP+U2ZaFLEAyV1Wm/zhHtyDqhXcldNa3KrdbbUNr1+/YShq2rodwkXcQCLLtEYZtCl2nZ5RrDcimdTkn9Ju2rRphnJyNSajjLvKelZ+v0iWVaxYER99MkeXYHvyuZdRM7SObEdupKRaJMvIpFQhxnN9cNDjGPyQ+GGrMXKF9nF3hq94ac3L1cnExVebbZdcgSmQuGJErFJSFsXiBWl39maCVBNSW8WICCNVpNYoPh+RoWRRUVEYPHiwVCSq4yJSXaNGTdBcXBeyIwf36V4bPfJPdrj735gxY0BqaLKff/75bmnORnHnJQKPXL31bNu2bQaiWGmvtCOSk5SZZFOnTjUi/5Q2pCglEpmNEWAEGAFGgBEoagSOXY01OUVIRQ+M6VjTpNwmC8IPCpffifpLCxK/Bx76gmIp6ddzaalE4O/Iv9H/5/4Yv3E8vj/xvQn5V8O7Br6870vsfmw3ZnWdxeRfqbyKPClGoHgQsEkCkNwLv//+e/mim+fcjNoo7dXxqXLrx/X2iUB+1H8KUooKUDku6JYSSMSJmHRac3dxgLerI8rrEFratmkZOUSVts6vYo7aixJlUDbdRJVLrba93jG54BPBo2ekzFUIqgsXLsgmCpFGrroXzmbHLSECzNdHn2Ak8nHA4MdlX4qVt2vfQUkg6iXrGDNyOJyEy25ejMhBPxHzLzdLFsQlYUlqzBPX43EyIgExIuFKkiAGL4kyqif14E1VJmFyuzVnTZs2NVRROyI0CX+1eQrlZp0GjWTRtSuXDMSpuo16n94vERER0u2ZYjcqL0rIQnb06FF1c7lPisR69erJfcXNV9tIKadkIQpxqbTZvHmzsitdvQ0Hmp2+fftKRaimmA8ZAUaAEWAEGIFCRSAl3fR3z9QeoSYP+wr1pKVlsFvit9YP4rdHZvbDUsO0KjUG+okHcWM3CFcIH0Mx75R+BDZc2oBxG8bhWuI13cm2C2qHpX2WolOVTnBztBz3W3cALmQEGAGbQkDf76+ML3HVqlUgVQvd1JL7XG5Wvnx5vPrqq1LBQiolSzfluY3F9baNQEHUfwoyhRULkBRmV28ng9RlWlPi+lUTKkB/LxdJQFHMG1KzuYkYN5EJOT/8yIXVnDVv0w5Vq9fAVUEufTjjZaxf+yP6PzgAfXv1QKtWrUUm19yJsdq16yBKxCd0FTHyiLCi5Dtqq1ChgjykOJ2UYCPiLkFG7rqKkVLOURBx5qxxs1aGql0Hj6BWoxYiUYepmq9Dm5aGdnnZCfB2kcpEPayVcaIFpsrcqYzINm1mQSpPV5F45OZrzsgFWTFqp1YOUnk5gaOLuJZe3tk/1O8kJgoCUOlhvCX36i9FBmFKImIpmy+5GusZqfooXiHFcjx37hxCQ0MNzUhxSe7JZA8++CCI1FUbkYxk5P5rKcYfxQ4kJSK5IbMxAowAI8AIMAJFhQB5GmjtoWbZD8K05TZxLH6P4Oa/wOk/hLvAd0CSJi5cyzHZ5J/m95lNrN0GF5GRlYEDNw4gLDIMpPw7EHHA7Cofq/cYXmj9ApzKOZltwxWMACNgXwjkTQpTRrBRMmoOGTIEpA7KzagNkX50w67nApdbf663HwQKov5TUCoMFSCp5M7cTNQl/+pW8jKK6ecmiLd6gV5oEOQtk1VQ1lq10Q/hGyIz8BnhonpN4+KbiXL47NsfEFK7ruzy79EjeP/tN0Hx+4g473FfL5D6i9xDzVkKnHBDkHqkjIuIT8EVES+PYujF3EkFkZIUZ46MxqB2isXF3lZ2pYLQUqZdf5XCkPpRnLyb4lxaoznnx4hsqy7IVHOxEmlMrVuwNeehhBjmTMGF6qldikap6eJYTpKASjuKw6dVCNJn2vjx42UCECIBLZF/dB5ST+uZ+kEKJQNRG40bG5vtTqV1/6V2pMokI6KXSD5LRq7ebIwAI8AIMAKMQFEioP0+ndy9lsnDyaI8f7GOfUMo+7/qJF4dgW3vAHHhxqcPvQ/oM4tdfo1RKbVHF2IvYOAvAzFp8yTM/2e+LvlXu3xtTGo6CT/1/wmvtH2Fyb9SezV5YoxAySBgkwTgkSNH5Bd5XpJ+KG0PHz5cMleCz1rqESgM9Z+yyILEAiQ308uCTNNzca3s66abjZZUd453XV+dBHGkNoq3FyVcVYkIjLmTJok5pT5ZuMnUqlMPP23ag9kLluKhIcNRvUaIrE5JSca2LZtkIglS6EVGRirdjLZKPD8qjBIqudjkNOm2fE2oF0/eiDdk/CUCTatyUwai+TvcJQqVsty2ek/4cyOgLI1JrsA1/NxlBmBL7fJaR9eTiLrcLFVLAApil+akNjXWVP7NN99g0aJFsgmp6xYvXiwzJsfHxyMjI0Oel849YsQI2cbcPEJCQmSSDmqkuPvKDqpjPz8/3H///UoxbxkBRoARYAQYgVKJgPb3gauj5YdTpXIR1kzq1kXg+4eE+i9biW/Shdx+By0GHIwfDJu044JSgQAp/kb8MQKX4i+Znc/gOoOxqt8qTG42GXUrZD+8N9uYKxgBRsAuEbDJT/wbN27Ii1mtWjWrL2rVqlVl2+vXr1vdhxvaFwKFof5TEFNUgKEfhypFVm9JOafN7usoyLGq5d2MMvSaG9DZwZg00ra7k5qJine9OBVCjoizHvf3lS9qH3UzAnu2b8HK7xbixLG/QcT5hAkT8c2ylYKog4g/mHdXg1SNS46Pb45aj7LPWnIBjlaRj+p+2rUV9JhIyOoV3ISaMUmXgM3r+BFxyTgVEQ/K2Eyu2n7CbVkharVjafFRFIDqdloCkJKikJHL7t69e0Ex+vTs1q1besVGZaTu27dvn4wfeOjQIeEC3gpEJJICkGzQoEFwcjK97orqks5BKk9LJKw1MVuNJsUHjAAjwAgwAoxAHhEwIQDFAzWbs7QkYKV4uJds5vudkn0MXS7ic9z9wWdzANjOgujh7OYrm/HyrpeRqo3deHeZrg6umNJ8CkY2GGm7albbuaS8EkagRBEwlgKV6FQK7+TKDaaSDdSakdPSslOlm1PAWDMGt7FdBApT/aeglB8VIBE8t4RKT2305Lp2JU+ryD/qRySWJXdaRVlIW61LqXLeipUChRpwGL7/ZSPqN24qi9ev/w3nrscI994kI1depU9et6F16xu6UCZZrdrNUCl2jh/NUe6q+6nbWLuvjVGo7ecmXKgJ72A/DwR4uYp8y5YJVW1/9fGdtEx5SIQuuSxT4pDwW0nQZvulzyVKIqI2V6Hk1HK54pIZ2b//ipg/wig2nznyj8Ym1XRuRolYlJAKigpw9erVSEnJdrXWc/+lMZW4f/R5rMxH71xEDirZgvXquYwRYAQYAUaAESgMBFI1SUBcRTxdm7KECJHl9wmh/DtmvCyKA9dmIjDyF2D8FsDHhuMeGq+8TB6FJ4TjvQPv4YE1D2D69ukm5F9Nn5oY02gMPu3+KTYP2oxRDUcx+VcmrzRPmhEoXgRs7BsvG7xKlbIzlyrB562B9Nix7C9JjkFlDVr216Yw1X8KeooKUDm2ZksqMC0pFyzcUvOa2dbZQibcdJFtlixd43KqNz9SfLVsK+LKCCOX0oT4OLkfLVyKC2oBgUGoezf7LCX2SRRJLvSMiKNffvxBVnn7+KJ+o2xCUq+tNWWurq6ymaUHCIS3j5sTAn1cUVfEV6zs4ybjA1K5hybGIqkziSikBCi5GZFxt5PScC7SOL4juQlrrzsRkRSbUG1aBSBdE7I7d+6omxnt//LLL1BU00YVmgP6bOzVq5csXbFiBSjmoEIEBgcHo2PH7PeBphvuvfdeQ9GSJUsM+9odUhLGxMRoi/mYEWAEGAFGgBEoVAS0D9RcbEUBSKq/P/4PmNMEOPWbMWb+IunYiyIDcJ8PgZBu7PZrjE6pO9p2ZRse/fVR/HDqB93svl2rdsWKviswveV09KjeAz4uPqVuDTwhRoARKJ0I2CQB2KFDBxnbSnF/swb6+fPny6cm7dq1s6Y5t7EjBIpC/afAl1cVYIrmqbWzUIHl54err7uzMgWTbYYgAImIShPbIwf24spF8YPRjKUL5ezhA3tkrbuHJ8r7+ZtpaVxMpFhubsL1RdKSqVOmyI7kGjpt2jTjQe4efTX7A1w4c0oePfz4SDiLbLMFsaCgINn9/PnzVg1D14Dcd2tV9ATNuVaAJ6qIWIxEshIZGFLRQxKFNf098kTUxiWlG85/QcR8VBsRjU5C/qdVRRIBSNdOsdq1a8tdSoyk5+ZLa5w8ebLSPNetovIjwpDIv23btsk+lCTEnHKyffv2aNJE3IwI+/zzz0FqTq3R9X322We1xXzMCDACjAAjwAgUOgI26QKcJbwEVjwOHPhKZFXTPIR1Fm6+5O7r6l3oWPKAhYsA/YZbeGwhnt72NJIyBKGrY4/UfgRzus+Bu5P5RHI63biIEWAEGAGJgE0SgErGSopT9fTTTxvdEGuvO33QUhsl+YfSV9uOj+0XgaJQ/ylo5lUFmJKhdQPNX9waf09nBIustpW8XREiiCm1CQpJZrQl1dmBPTsxoFtrjBvUD4u/+kzG/Tt57CjC/tqPn1cuw+hH+oCOyQYOHW5wEVWPp7fv5eooYxaSik7PXMXTeCK5Jk2aZEg+8e233+KJoQOw+fdf5Tl3btmA6RNG4utPP5JDVAuuiYlPv6A3XJ7K6AEC2V9//YX3338fR48exblz5+Tr2rVrVo3l5+mCenfJQFoLGRFkvu7667VqUFUjd2cHOZ4mB4hsQZmVFRs5cqTcpdimRMRRUpCDBw9i586dmDFjBlq2bCmJwRYtWihdLG4HDBgAD4/s98vUqVMN2Z8VYtBc53nz5slsz6Sq7NGjB15//XXs3r1bYvzll1/KeYSHh4MSlZCZIxPNjc/ljAAjwAgwAoyAtQiY/paygduhnSKT74Xsh3JGODiK2L+PLgL8sx8IGtXxQalBgNx9V5xagQmbJuDTI5+KX+I5D3OVSVZyr4SX27yMN9u/KeJi5+5VovTjLSPACDACagRs8tPjgQcekDeZW7duxdy5c2XgelIPde7cGYq6hxQsdBNMihQi/+iGkzIB0w0uGyOgIFCU6j/lHKQCrPZCNbgE5q5c08atccln3Bp6v/sIFSA5DKgVY8qcMgSJpBBJ5Op5aP8e+VLqtdvuvfpg2v+9oS2Wx+Sm6iLiFCoJRaiQCEBKdkFx9LQqNqWethTP87fffpMx7Pbs2YODgpCkl9ZCatfFvO9XgVSIZOXF2uJT0qXbrNZNVttXe/zkk0+CSClSzL388svypbTp2rUrtm/frhzmeWtOeUmOvORKfOVWskn8P72TeNx1J9ZbG8VgrF0pO6g3PdzYtGkTNm7cKJN3jBs3zmg4igv4/fffy0Qe1sQBJPLvoYcewrJlyxAbGyvHatq0qSHOn9HgqoNOnTpJ8vGJJ55AUlIS3nnnHflSmlBsQcKcPpMpDqDihq3U85YRYAQYAUaAESgsBLTeFG7ioVqZtgvbge0zjZdA8f6aCUVgp2eACiHGdXxUahBIz0zHx4c/xvKTy3VJP5po35C+GNtoLGr71uYHpKXmyvFEGIGyi4BNEoB0OShmWLdu3UBxAIngGzVqlNmrRARI48aNQQHt2RgBNQJFqf5TzqOoAK3JCGz61LrgP1qJDCQyjkg/xaIT00AuMqMmTkHt+g1xYNd2nD91XGb/jRQZd+m5pF/FADRq2hL9Hx2CLvf2VrqabD3ED+saIk7hJUFMEQlI5Jxa+VdOJ4mGlypeXoUKFSQxRKTTosVLcFwoDuNib8PT0wv1GjTEfX0HiIQkI+DknOPWTONXFm64dD5SO+bFqlSpIlVyM2fOxI4dO3D16lVDoou8jKPX1k2oAfXiL1I8P2dBklbydhEZhrPj9un1pzIi/SrcdeGmZC7i0MgothFdO6miFDEaKbYekWtE9J04cUISvrTG++67T6qf64k4i0omX6OBzByQ2o+uhWK5qf+UdvQZ3Lx5c3z44YfSdTg6OhoUV5BiB06fPh1t27aVZC+19/HhWDYKbrxlBBgBRoARKFwEbMoFmBJ+rB4vAFIpxu4Rvw0p0UcN/di8hYsmj5ZfBKKSovDcjucQFhmmOwQlmaMYf5zcQxceLmQEGIF8InCPIL9U3xj5HKWUdktOTsarr76Kr7/+WqpO9KZJipaJEyfi7bffNpslU68flxUMASJVqlWrJgch17+qVataPeDZs2dlwglSDSkxzqzunIeGpP47UPMAslJyiLE8dM9T03Ju5dD2QluLKkD6Uz1+Ld7oCWGoiDfnLsijgtrZmwkmWWa1Y1YXLsOKgu1yzB3EJefEqNO2VR/XE8o2IrfIsrL+M1H8xYiEIddik9Vd0KiKj0mCC2pA2XHPR92RJBYRl7VEfL3ElAxEiAy6ipE6juLt6anjlDYluY1MSEFEXM58aS7kik0vWh8lADFnjoLwoziDtHbFosR4NzTj+QsXZCJAy5qFhoaC4hIOHz4clhKGmFtXcX02mDs/lzMCjAAjwAiUfgTqvPqHiHOc89tu3ZROaFy1jD14uiOSZh3+VsQrWQgk3DAG/b4ZQvnHcXWNQSnZI/oNfy3xGiq6V0RCWgL2Xd+H2YdnIyo5SndiXiJu4/ud30eXql1067mQEcgPAgW5/87P+bhP6USg4MxB6VyXnBW5t33yySd48803Qe7AYWFhINUJmb+/PyjuVffu3VltIhHh/7QIFIf6TzmnNSpAygKrjQlCcfIKw2gcbVY89bikWlMn7SDlmTWWnawiZ4567r7eQq1HhFjm3WcRfh7OZsk7IjuJ9ExKzZDEJ7ntkKqOfsgnijKaIxFppZX8I8x83ZxNCEBv4RJNRslRLBlhpSb/qG1FkWH4TmqmdHlW+t66k4YAoSbMbTylfWnYUsxFJfEKJ2MqDVeE58AIMAKMgO0hQL+l1OQfrdA1n+FUSgyda0eA5YOBOzrkUe1eQIenS2xqfGJTBC7GXcSLO1/EqVunTCtVJS4OLugZ3BPtgtqhe/Xu8HbmpC0qeHiXEWAECgkBmyYAFYzInWzgwIHypZTxlhGwhEBxxP7Tnj+3WIDp4ker1qwl4rT9tMeUUdaSBfoIUk1F+llLLHkKNZ6WsNKeh0jCYKHYuyWUgKQUrCgy6loyIvzopRiNX7V82cmE5iyyBlOSEFI+khFpqSQKIYWfJfM1kzSlsq8rEiLSDQ5AlA04RrhxBwgsc8Pf0vkKs44SqZDCT89iYmJA8QHJXEQW5yFDhug14zJGgBFgBBgBRqBACKjjESsDKd/BynGp3t4RQoaVw/XJP2/hTTNwvogVYvlhYqlen41M7k76Hey6tgv7r+/HuvPrkJaVZnFllT0qY3b32Wjg18BiO65kBBgBRqCgCNgFAVhQkLi//SFQnOo/Bd3cVIDqGH3Uh0i4wlK6WVISkkutOmYfndsa4aGDIOZIhWaNEVFIL3uxIEGokuqPOF1KiKKQdESyEm6KGlKNB11vJfmHupz2iTgldaDaLfumcIuOFK8qghytIFSVJW09e/ZEzZo15YOYJk2aSOX17du3QcldvvjiC1BiJrLXXntNKrRLer58fkaAEWAEGAHbQ0CbAIRWmN+EasWOTlZmdry/+Gump67eHnjoC8C9gmkdlxQrApsub8Jb+95CXGqcVedtH9QeH3b5EL6uvla150aMACPACBQEAfu54y4IStzXrhAoCfWfArAlFWCGRgHomItqTxnTmq2TUKXpGenRKvu4GQgqpY1CWCnH6m2jyj5IEkkoSKVXWApF9fglvX/mzBmkpVl+kqs3x4CAANCLjIhbL6H80zMHcV0zM0zVnt5uOUShXj9STqoJQGpDo1y7nQRXcX3dS5hgpfg327Ztky+9+VPZU089hVdeecVcNZczAowAI8AIMAIFQkCbAIQGKzMKwB0fABe2Ga+/amvggQ+BKi2My/mo2BFIyUjBrEOzsPL0ylzPTe6+5OpLLr/9QvqJ38s5ni25duYGjAAjwAgUAIEyTQDu3LnTsPQuXXKCpKrLDQ3ysKMeKw/duKmNIBCxOAKOfiX3p0HnD34p2ARNUwWgZXdRkwEsFOhlpqXmASKeHsXZ05o5tR6RUKRiM1evHacsHvfq1QuXL1/O89QpFumMGTNy7UdKvzTkBCdXOmhVmEq5sqX4iKQQvCNiIapNkoBxyQit6GlC5KrbFfX+d999h3Xr1smMzqT2i4qKAiXyCQwMRKdOnTBhwgR06NChqKdh9fgJKen46fBVkDr24RZVCiXZjtUn54aMACPACDACRYKAXrxj17uJyorkhIUxaKSIHXd0ObDnM+PRPAOBoaLcM/vhonElHxUHAhlZGTgYcRBHbh4BKf8uxF2weNqaPjVxX/X7ML7xeLg7lZ3wNRYXxZWMACNQphAoOZajEGDq1q2bvKElNVJGRs5Nr1Ken1Nox8rPGOb6REZG4uDBg/JFAe/pRbGvyEaNGoXFixfLfUv/JSUl4c8//8SmTZtw6NAhUFytxMREeHt7o06dOujduzcmTZokb6otjaPU0Xhz587Fjz/+KAPwp6amyuy8ffv2xbRp0xAcbEpEKX1tdUvkmx4BV9LrNVUA6qv28jNPvRiALuIHMSXU0DN6Wh4gkk9QRlvFyHXVz8M6l1+lD29NETAXB9DFjEpTPUJFEVtQSwBSfXJapsgwnGnWhVg9RlHtd+3aFfQqC0ZqxYlLDmPv+ezP5y0nb+Kb0a1LlEAtC7jxHBkBRoARKO0IaBWAFHpX7zdQqVhH2h1g7STg5K+m07lHPJwdtJjJP1Nkiq3kzO0zeHHHizgfd97sOVsHtkaHyh3QsXJH1Perb7YdVzACjAAjUFwIlGkCkECiGzU9M1eu17a4yipVqlSgU/3zzz/o2LGjJPy0A926dQv79++Xr9mzZ+Prr7/ONZA+kYd9+vTB2bNnjYY7ffo06LVw4UIsW7YM/fr1M6rng5JBICPT+L1ujijKz+wcdYL6ueso/9RjU2KQSiLGX2pGliSXKJadpViC6r5lef/SpUtFOn1zrt0OQhmYm9E1IHJWe4ND/SgzsLkYgrmNa2/1l2KSDOQfrX3b6Sh53DHU396g4PUyAowAI1CmEaCkH7+EXcexa3Ei7u5/JqFJ6DvTUliTElt8unjA+sNjwMUd+lPo+T8gWMT9Yyt2BOgec83ZNZh5cCZSM1N1z+/q4IpX2r6Ch0IfKp3vL91ZcyEjwAjYAwJlmgCkeFJ6Zq5cr21JlVWvXh316tXDxo0brZ5CfHy8gfwjIpCIuVatWsHPz0+6061ZswYLFiwAtRs2bJhUBT7wwAO64yckJIBUfgr5Rxk4hw4dCjc3Nxmja+bMmXIcysZJQfqbNWumOw4XFh8C6ZnGbqGF+cRaL5mIh4up6692tfSjmX4804utcBDQy7BM1yeXBMHy5HQ9giu4I/x2siBlc1TRVJkoXIPpR2upvNEpHOgKbZTj4kZRa4t2XwQTgFpU+JgRYAQYgdKLAIVOGTB3D05FJJidJMUrLnWWngysGmme/Gv7JNB+cqmbtq1PKDo5Gvtv7MeGSxuwPXy72eXWLl8bs7rMQohviNk2XMEIMAKMQEkhUKYJQHPuZObKSwpk5bxvvPEGWrduLV+kBiQlEWXFtNbKCQXQ4MGDQbHEGjQwTRNPscmI8Bs4cCAyMzMxdepUSfDp3fB/9NFHoGQGZB9++CFeeOEFwzTat28PcqMmHMlF+JlnnsH27dsN9bxTMgiYKgBzV4TlZaYUvy8qIftJJiXv8HEr+cyxeZm/rbTVI3bpeuj9Heut2UXczIQGeEoV4JmbOTc9RCCniRe5drNZRuDEjXiTBnvORQu1aybjZ4IMFzACjAAjUDoR2C0+ty2RfzRrUgWWGktLAs5vBfaKWH/hB4yn5eIDtBgBNB0KBDY2ruOjIkWAVH6fHPpEJvfI/E9kYtYxiu3XrWo3tApsJV1+HcuV6VtsnRVyESPACNgKAvzpVIxX8q233irQ2ShAfm5B8gcMGICHH34Yq1evljH9wsLC0KJFC6Pzpqen47PPxI8LYfXr18dzzz1nVE8HdJ5x48Zh/vz52LFjh4xXSOQlW8kgQMotIm/UVtjutoEi3h+NSURRBQ9nEzcZ9bl5v+gQ0Luu+XH3ppiBpCbMyMp531B8QCYAc792/143JQDJ1X30N39hwahWNp3kJnd0uAUjwAgwAmUDgXORiblOtLz4vVPiRiTk3s+B7e8D6SLun9ZcvEWw8F+Ays21NXxcxAiEJ4Tjue3P4eStk2bPNKz+MExvOR3ODqXgvWR2llzBCDACjEA2AoUrISolqJJSjrJLkrLNHq179+6GZZ8/bxqYllyk4+KyXdwo+QjhpWejR482FK9du9awzzvFj0Cm+HGofUrt5HhPoU6EFGb+IolEkI8bk0SFimzeBjOnAMzbKJCKQa0bd2KK/pPrvI5tq+0pTmJsUhrCLt/WXeK+CzHo+ckO/Hk8wmz8Wd2OXMgIMAKMACNQ7AhcFvFcczP/kk5eliW+l39/Htj0uj755yqUf8NXM/mX24UsxHp66H4+9jyWnliKIeuGmCX/vJy8MLvbbLzU5iUm/woRfx6KEWAEihYBm1QAOjs7g1RunTt3Llr0SunolMlXMQcHU3e/3bt3K9UWs3JSfEF3d3fpBkxxANlKDoF0TQIQmomeUqzkZshnLiwE9BKy5HdsTxdHxCWnG7pzHEADFCY7M379F9/vuySIdpMqo4IbcSmYtPQwnu9VB1N61Daq4wNGgBFgBBiB0oPApRhjNd30nnXQpU5FTF52BNdik8WDMmBYu+olN+EM8Xt9zQTgxM/6c/AUyQOH/QQENdGv59JCR2DjpY345PAnuJZ4TXdsFwcXtK/cHu2C2uGBmg+ggmsF3XZcyAgwAoxAaUXAJgnAypUr4/Lly1IFWFqBL8p5kcuuYuTiq7UTJ04YiigRiTkjFWVoaCgo+/DJk+al7+b6c3nBEUhNzxQunP8hU8NKkGunXuKOgp+RRyhpBPTcfck7KD9GWYHVRu7AyeI95e5sXK5uY4/7lPRj8d5LeVr6/B0X8FS3UKGgLlwlbp4mwY0ZAUaAEWAE5G+kdUev40L0HRGiwQEJKRmIEA9rdp2NNkIn2M8dzar5YtP0LtgusrtXF0mzGlURCrvitqjTwMl1wL/Cu+bmcdOzB3cEGgzIjvdHCkC2IkcgIS0BMw/MxLoL4rqYsRreNfBJt09AST7YGAFGgBEoqwjY5F1gly5dsGTJEhw+fFgm3CirFyc/8z569CjWr18vuzZu3FjG+NOOc/XqVVnk4eEBX19fbbXRcbVq1SQBGBUVBVIWuri4GNWbO1DOYa7+xo0b5qq4/C4C0YmpuC6eUOtZYbv/6p2Dy0oGAb1kH/8hfwygs0j4QTH/KHmFYonixkhNAKYIQpBcXylmIMV+1Du/0tdWt+uPmf88mtS1lriJjII2LmCCiKdILx83J1uFhdfFCDACjECpQ4CU7F9sOwdSYw9vF4z6QV54cukR7DgTletcg/08ZBv6DuzTOCjX9oXegGLybn5DxPubK4bW+V4vJ75PHv4aaPRwoZ+aBzRFID0zHceij+Fo1FH8cOoH3Lhj/rdAn5p98Gb7N+Hu5G46EJcwAowAI1CGELBJApCy3y5fvhyzZs3C448/Dm9vETzXDowIuvHjx8sMwLTcd999V3fVCQkJstzT01O3Xl1IJKFiiYmJVhOARByy5R+BpLQM3IhNMTuAs0jWwWa7CDgLMi5NJJ1QrLx7/gNLewoVYGpiDgFIpFXA3YEzRMKX8yJIOsWYJEsXSlNKBmNvdsVMnKjOtf3x0gP15Iv+Jhu8scEImrikdBMCkGIHnbyRIG7t/kODIG+7JFSNQOIDRoARYAQKEYHXfz6OtWHX5Ii0pQdX9BDLGgsWir8Ss3Txm24tufuKZB565ix+kw9dBoR006vlskJEgL6nf7vwm3T1jU42VomqTxPoEYjWlVqjd43e6FK1C3+fq8HhfUaAESizCNgkAdiyZUt8/vnnmDJlioxxN2/evFyz55bZK6iaOK330KFDsoSSe/Tv319Vm7ObkpJNLFGsxNxMrfhLTtZXo+U2BtdbhwD9IFHUV5HxqZJAMNeTCUBzyNhGeZAg4a7cSpL6AIr16FsAAtBLxAGMEWpSxZJSM6W7lINwXY0S5Qr5R/VRCal2QQCSsnbJ/sso7+6EEe1q4JhwAdazyd1DDcVuTg4i7uY9Ikt2jmojNjkN1WF8Q/nu+pNYuPui7De6Qw3MeLChTBii/G0bBry7c0m4rO09H4MWwb6oF2gfD6u0GPAxI8AIMALWIHA0PNZA/intrSX/2tasgBLL+JsQAawaBYTvV6ZtvPUNBgZ/LxJ9NDMu56NCQSA1MxVhkWE4c+sMTt06hQMRBxCZFGl2bE8nT7zS9hX0C+ln+F1utjFXMAKMACNQxhCwSQJw7Nix8jLUrVsX5BJLyUBIkdakSROUL18eeokxlOtGN2mLFi1SDsvMdubMmVi4cKGcb+vWrUGkpzlzdc1W+KSl5f7EVJ1QxM3NzdyQJuXh4eEmZeoCcgFu06aNushu99OF0uuyIHuShcLIRxA9VXzdEJ+Sk7hBD5gS+xGrNxkuK3QE6H0QKlSAqeK9QQo+Iuvyax6CAKTPNSKYyUiZdkeoAL2F6yop2NSmtFGX2dp+ulA9PvzFXkTEZz8ICbsSK8lW7TpbBZcH3TAqRhj6uDmDXPMVUydYobJjV+MM5B8dU1zBnw5fle7Vw9pWx/RedanYYBcF+dfvs124k5at0Hytb32M7xxiqOcdRoARYAQYgWwEzkUmYOAXe6yGo6X4DG9do4J8sOXu7CCSNuU80LF6kII0JHffo8uBI0sE8XdAjJT9HWwYspy4BWs5GqjzAFCzM+DoYqjincJBgIi/VadXYeGxhbiVcsuqQVsHtsa7Hd9FkGeQVe25ESPACDACZQ0BmyQAFy9ebHhio9z4XrlyBbmRUooCq6wRgPPnz8crr7wi33uU1OP333+H2nVX+6b08vKSReTSm5vduZOTQc0al2FlvKpVqyq7ZW77/vvvY+5cis9SPEYKLPqdqNjQ0eMxbvKzyqHJtmp5d7gKNRKbbSPgJmIUCb6pwEbkoYe4+aG4SYpRgHQiANMEGWZvdujSbQP5R2v/47hQZmiM8Hr/kcaG7xGl2lcoBtUEYKyGQJ0n4lJpjXAnzvCzrefQUtyMdhUZKMn1Oka4rP0uYg8q5B/1e0eoB+PFtXn2vtom59aOy8eMACNg3wgov1ntAQWKVTt5WZjFLO2VfVzx7Zg24rM1FRU9XVC7UvZv3RLBJ0s81PllsiAAf9A/vYtQew8RxGBIN/16Ls03AuTSS0q/E7dO4IeTPyAy2bzSTzlJiE8IiPjrULkDulXrJpLscZgdBRveMgKMgO0hYJMEYPXq1e3m5umHH37AU089Jd+ZwcHB2LRpE/z9/S2+U4mcO3DgAIjci42NtZgIRCFNK1asaHX8P4snLwOVo0ePxltvvQXFVbo4p+zq6oYBgx43e0oi/yjeDRsjkBcESEVoRACmpgtFYLYSOC/j2ELb8NtJuS7j7zd7CXdf0xsAX03Cj9jkHAVlloifSMlCLNmHf57CP8KFbf7OC0bXQ93nsy1n8ds/1/HZ0OYlk51SPRneZwQYgVKHwBfbz+EbEWaAvAU+HtwUoQElSHQVEzpv/3YCp29mx6/WO2XtAE98P64NgnzIU6WE8ZDk3xTz5J9XZWD4T0ClhnpL4bJ8IEBkOLn1Ljq2CPtvmHGz1hm3mlc1vNDqBXSv3l2nlosYAUaAEbBNBGySALx06ZJtXi3Nqn799VeMHDlSqMeyEBQUhC1btsAa5V2DBg2wevVqOdqpU6fQrl07zcjZhxkZGTh//rw8qF+/vm4bWywMDAzEk08+idmzZxf78gaNGAv/gEom56WYf0Hi6Ta5hrIxAnlFgOIAqnVulGCEFBV6ZuuqElqfJaO4gHrkH/XRZvyNS8oJo3BNxBVUq/n0zkGZhLXZhPXaXYi6gzd//Rern+ygV81ljAAjYMMIKAmgKBmU1nafjcaHf56WxdGJaZi14Qy+GtFS28ymjv88fgPLDlwxWhORn/8b0BC7z0XDV0jlx3SqAW9XJ6M2JXJgIP+E66/WnERSvfr9gfveBLwFCchWIATiUuNw+tZpnI0VD83O/4bjMcdzHa9+hfqoV6GefJHir5ZvLVb75YoaN2AEGAFbQ8AmCUBbu0h66yGyb/DgwSCSzs/PTyr/atWqpdfUpKxTp06Gsh07dpglACmhiOIC3LFjR0Mfe9h58cUX8eWXXxarCpDUf6MnTTWCl37QBvu5l0lFK7nfk7355puYMWOG3Of/SgYBvRtJtSJQPSshZIPIdWGzdlvjtqtdqJeFm0gfQQ6qTR0D8OSNeHVVgfePXLktEo5kmSUjC3wCHoARYARKFQK3RViA10SG200nbsrwDKT2r1reDT3qBWBS11oy9MczK8OM5vznv+pHO0ZVNnFAD2xm/nHKaC2UkOm7sa2l8vHe+qYPTI0aF9fBzRPAwa+BU+uBOxqXUwfx4LbXu0CLkYCTfSrvC/MynLl9Rir9NlzaIJKY6T/I1J6vbVBbTGk2Bc0COMmKFhs+ZgQYAftDgAnAMnjN9+7diwEDBoASdPj4+GDDhg1o2NB6V4Ju3brJfnFxcfjuu+9AZJdC1qjhoFiKig0cOFDZtYttSagAteq/8kLtV62Cu13gzYssWgTKCTKW/lECEMUSRTZgPctWyN2DBJGIhmIFegr1IMULtBW7rVLt6a2J1mvOSGmiNnUMwNMR5t3T1H2s3SehIsUbzHZps7YXt2MEGIGyiMCyA5fx6lpjBRNlt6XXPyK50NL9VzCmYw3xmZBmsrxM8dSmIImiTAYswgJ6qHHqRgK8RFiKGv4eMiP9t3suYuVf4ajo5YIPHmli9LuHlNWXY4zDNrwlMquXKrfnoyuBn58UOT50vlOJ/BuyTCT66FWEqNr20EnpSTgRcwIX4y9i59Wd2B6+PdcFuzm6IdQ3FHXK15GZfFsFtsq1DzdgBBgBRsBeEDB/p2ODCJBa7vbt23JllA3Y0bHsLf/vv/9G3759pTKPEn2sX78eLVvmzf3D2dkZ06ZNw9tvv42TJ09i1qxZeOGFF4yu+L59+wzZkLt27QrKLGxvVpwqQD31XyVvzghXEu+5GjVq4PLlyxg1ahTUJHhJzKWwzkkEP90gZpC8766ZVwD+J7IDp8nM1NSUSKgafh42QwLG3smJ26dgod5SvERzRklA1KaOAaiNT0XuwmqFoLqftfs345kAtBYrbscIlFUEKCv7uyIBkCWjz+GPNmS7/mrbxYi6AO/Sryzbez4az606ihtxKeKhMzCxSy0cuXwbBy9lZ2c9G5mIzh9uw6m37zckOqPM6mqjz+BBrUpRkrmDC4Dfn1dPMWefyb8cLPKxRxl8Fx9fjEXHFyE5I9mqEap4VsGYhmMwIHQAXB1L/9+EVYviRowAI8AIFDIC5u90CvlEJTXciRMn8NVXX2Hz5s04c+aMCHyffQNMN8S1a9fGfffdh4kTJ6JRo0ZFPsXdu3fj3LmcLJHR0dGGc1K5lmygZBRqo3h8vXv3lok7qPydd96RSr7jx42fGqv7BAQEgF5aI8Jv5cqVEhMiuuj8Q4cOhZubG7Zt24b33ntPuhfT8Zw5c7Td7eK4OFWAWvUfuf44OzrYBc68yOJBIJsAzDmX8lmYU5K9l5bxH67FphgVRyakFgkBmCHil6Zn/id+qJfTVSEbTaKQDnJTAFK8RHOmJQDjVO7EEeKmVm3Te9YBtd8lYnZ1rxuAkIoe2CPiVRGZ+uyqv6W6Ut1eb/9mvPGYem24jBFgBMo2AocECZaUpqMes3JZ9KCgtBOAhy/fwtjFf4nYs9mZ5+mn+Fc7zuuusN7rf+Lwa/fBT2Ty/eeaMQHYuIpPsX1X6E4uTagRj4sY2pf3AFf2A7cv6jZDYGPg/g+AGvYVPkcfjLyVZv2XJZV+Hxz8AFcTr1rs7FzOWcbxo1h+Xap2Qc/gnnAsZ/473OJgXMkIMAKMgJ0gYLOfkpQYg0iuzz77TCbJ0N7s0vHp06clAUYE4ZQpU/Dxxx+jXDnToMuF9V5YuHChdLnVG2/Pnj2gl9q0BOCuXbsQGZkTW+TZZ59VN9fdNxd/zcvLS6oH+/Tpg7Nnz+Lrr7+WL/Ug3t7eWLZsGZo1s9+YGcWhAtSq/yjhR2AZeJqvfq/wfulHwFoXsauxSUIpmH2TpqwqKS0DySJpCMVeKgzLEp+/pAK5JdzZyC3ZQ5BuIcIdTC8UQWGcTz2G2m1XXa7sk2uaOdMmAbkQnWiI06clFssLEv/BppUxoFkVw3D1g7zlfvsQP2wUcb605upUznCDTHVEGPZuGKhtxseMACNgQwjsOK2fPZySXFAyoLvPrc2uODKBHhT4mK0v6Yp1R6/juR+PQkluYs18vtx+Hv3E5ydt1UYEYIlZpFBpLh8MxBonJDGaT8sxQHuRAdg/1KiYDywjkJGVgTVn12DT5U04Hn0ciemJFjt4O3tjeP3heLz+4/BxKcH3hMVZciUjwAgwAqUTAfN3OqVzvlbP6vHHH8ePP/5oUPxRjLw2bdqgUqXsgME3b97EX3/9BVLPZWZmSqLw+vXrUhVn9UnKeMPQ0FCEhYVh3rx5EitSAaalpaFatWogYvDpp59GcHBwGV9lwaZfHCpArfqvVkVPOAoSkI0RKEwErCUAzd2kJYqYgIVFAMYI4o/c1hQjFziKN1gcsQa1RJ0yB2VryQVYe/NJ8bgoYH+fxkEm7r6UTdicdQz11yUA61TykvG+lH7f77uMh1tURbNqvkoRbxkBRsCGELgYfQffiBh4Wls6ri061fZH82rl0X/ubm210TEptEujUab5T7ecNSHxrJnrwt0XQS+tNS2pz8KLO4EVwwGRedasdX8V6CLC6ZB/M5vVCFB8vxl7Z+DkLfNu8OXuKSeVfjW9a6JlpZbSxdeDsiqzMQKMACPACOQZAZtkGVasWIFVq1ZJMJo2bYoDBw7g2LFjMqYdubbSa9GiRfjnn39kXfPmzSVR+NNPP4H6FpWRiy8pD619aedBikBr+yrtcsu+SnEESeVGZCjFR6Ssv6dOncInn3xi9+Sfgj/h4+paNLFEyMVanfnXRbhCOolXaTMix1966SW0aNFCup07OTlJMr1x48Z47LHHpPt6fLzlLKj0HqO2VatWhYuLC6pUqYIRI0bIOJS5rZcUvUuXLpXENJGyFMeyYsWK6N69O7744gtJXJsbg/4GSFmmqMso+Q3Fv6S/e19fX1lOf5uUHIfaUPw/MkqQo/RTttSmoLZ9+3bDuLRPf6v0eUTZuSmjNylv6WHFkiVLjE5F5Dypldu1a4cKFSqAVLyUnVv5rDNqrDqgv+tvv/0W058ch4E92qFd3apoGRKAHi3qYtKwR/DTssVIF2Pr2RvPTUFTcQPaJjQI0bcs3Pjc7Vy3bl25Npq/ntEDl5EjR6Jx3RC0Dg1E77aN8PK0CTh57ChSMjJBn3GEdY0aNfS6F0qZOm6f3oCeLuaJuxBBzrcKLm/UjWJ3EYGpVRZSEh9z1qGWn24VEYBa+/FQuLaIjxkBRqCEECDCbuYfJ0XSiivys7ug03jvd1PSY8m4NpL8o7EbV/XBpme7QIkJXMPPXYYTUJ+3NIYKyBLxZp9eEWYV+feIeMjxcIscpbR6bep9eqjStU5FdVHR7KfdAaJEvMXMDJHRN0Zk910ALHnYPPnn7g88OBfo+iLEF1jRzMmGRiXCj9x7n9j4BO798V4M+W2IRfKveUBzrOy3EmseXIOPu30sVX9M/tnQG4KXwggwAsWOgE0qAMmdlaxOnTqguHtEcpkzSm6xc+dOtGrVSroEz58/X8bCM9eey+0PgaJUAY4eNwH+AdmqVELWoQhd0PN75cj1vF+/ftASfOSOTi8idYg49/f3l+30zkMkHSlKKRGPYkQqEqm3Zs0a/PHHH+jSpYtSZbS9desWHnzwQRMXeYqhSQQavebOnSvHyE2xSu7uvXr1wqVLl4zOUVIH6enpMqP3unXrjKZAZCkRZYcOHcKnn34qyfmHHnpIflapG1JGcHqReveVV15RVxn2iehUSE1DodiJiYrEvqit2LdzK35c+i3mfbfK6L1IbfsOHIRfVi0TGcdT8Osva1F/2iT1EEb7NFeKs0o2bNgwozo6oGs9duxY0JoVi7h+Db+v/REbf/sZH306z8T1WGlXWFsiW2NzyQJsyQWY5jG8XTAoZpdilKXyp8NXjRKsUJ3WXVhpT9vQAE/1oWE/yMf0QcPOs/rugYZOdr4TnRyN+LR4ONzjAFKJ6G7F56q6nDJiZ4l/mVmZ0gU9U2TvpIcM8p+IP6WU0/uFzMPZA55OnnJ8O4fbrpcfL1TQ/T7bhTt34/VR7L1p99bONyYUN3TLSeNQAJ2F6q+TUAirrbZ4MLDxma4Iv50kyb93xEOHC1GCpLprpVEBOHvzGWz413htNN2hrauBEiaFXYmVGeZf71cfQ1pXF39//4FcoWNE1mNzNkJ89roWUhgK3XPQ3/uR74CNrwuyz/IDTQSJ0DjNhSKwejsgoAFQzkF3SC7MQeBO+h18euRTrDi1Qn7u5tTo7wV7B2Nik4kyiy89GGRjBBgBRoARKBwEbJIAPHr0qFSR/N///Z9F8k+BkAhCaks3p9SXjRHQIlAUsQBJ/ffUtGfETWeOWeummdOjaPdSU1MlIU7kHynOnnzySam6o8QypEi7ePGiJKDWrl1rdiIbNmzAwYMHQWpBIgFpm5ycDOpD5FZSUpJUAhI5R8o+tZF7PpGPlJWajDJSU7zOmjVrggjEb775Bj///LNUEd57772gLNmenvrkCvV/9NFHce3aNUydOlWSipQNnM5LxCGp5EgBS4l2aOwBAwbIRDvUTzFLDxOUNnnZvv7661KFTIQZhS0gsplINFItUoxSimHav39/fP755xJnwn/gwIFSKUhrpf401zfeeEPOl0IdaI0wbNu2Lbr2vB/VQuvDzz9AkHBpuBZ+GevXrMKe7Vtw6vg/+L/J47Dox9+Murfu0BkVKwUh6uYN/LJ6FV6YOlGQIPo/xJcvXy77Ojg4mDxEIZKS1H00F3d3dwwb/xQ6dOkOJ2cXnPgnDIvmzcaLz0xBrTr15BjpmVk4FREvkoM4IFCQYoV10xcv3Iwp6Ygly40ApLh+c8TN7aUYEQz+rilZLJVj2lIMQHNGNzN0HnJ7VpsSI1BdZkmRqG5nr/sLjy3EspPLimX5Lg4ucHN0ky93R3f4uvrCx9kHXs5e8lXZszJCfELkK9AjUP4OKZaJ8UmKBYFtpyIN5B+d8JNNZzC2U01JZOVnAquEuleVmF18zpXDnCHNdN83PkL95uOeHetMGyP43M3E/Jy+yPosP3AFn289ZzL+6/0aYGzHGkI5CVDG3yrl3QzYlRNZ6h8V2X3n77hg0o8KiBR9sluobl2BC2/+C/z7M3DyV6H8O5X7cPX6AY8sBJzccm/LLRCTHIP9N/ZjzpE5iLgTYRGRUN9QTGo6CaT6C3APsNiWKxkBRoARYATyh4BNEoBETJA1adLEalSUtmp1itWduaHNI1AUKkAic/yE+i9KFb+ntBGAlJiGCCYyIniIjFMbuaOSW+/s2bMlkaeuU/b3798vXXeJ8FMTfJ07d5ZE1muvvYYrV67IpDREbqmNXF4V8o8UceSqqzwJbtmypSTHXn31VenWT1myybX3gw8+UA9htE9qRVIbkgpQMRpHbeTeTEbuwUWdHZzCE1CWbSJGFSM3a3I1JgVzQkKCJAZJ7UhKSVIBKkbtSLlMCj8i1kj5TISq1rZu3SoznkeL99n1uGRDdbNWbYXCbzB+XrkMbz4/BYf278GB3TvQtlNX2cZfZGCMFnH67n/wYSxZMA8H9+xE+LUbCK5a2TCGskPqKcoqTkZErBJrVamfPHmynCO5fi9Y8SsaNc/BvLHYv6/vAIwc0EsSkUofikVIL8qOWSvAAy6FkBX7knDfy808LWQBpr50o9pNZPVdvPeSYSi1GocKnRzuEaoxy4oQcntTj0Hnvbe+6Q1PfHKOYtJwQt4xIEBqveKy1MxU0Cs2NTb7lHHmz0xEYU2fmqjlUwvtK7eX2SldHU0VnuZH4JrShsBlFemvzO0nQeKN7lgTG/+NAKl1O4VWxP2Nck/ckymYv5V/Gbv3D2xeRWa+VcY2t9XGIv37aixSRQiFwviMNHfOvJQv3X/ZpDkpJccJspSMniHVDTQNd/DMvXXgIuIfn4tKRMPKPjIBEqmlE4Ty0ss1+3vZZOCCFBATue09YOdHYhTLD4YMp2n3FNDrHVb8GQDR3yH19C/nf8G3x7/FhTh9Ulfd08vJC6MajsLYRmPF92cRXGsh8jfoAABAAElEQVT1yXifEWAEGAE7R6D0BRsrhAuiuAFSrC9rTXFvVPpa24/b2Q8ChRkLkNR/lKVa/fSfkBTcQqmyiIicp7XmXHRpwo6OjjJ2nd7kKX4iqevU5J/Sbtq0aYZycjXWGiWoIaN4f+Tmq5B/6nZvvfUW6tXLVo4tWLBAuKuaD4hOKjQ1+acepyT2SZmnJv+UORDhrJChUVFRGDx4sBH5p7SjBxcUO5BMDz8qr127Nm3EXVf2Rvv/Q0OGoW7DxrJ464b1hmo/oWCjZDTkBkxGJKO5GKnbtm0zEMVa918iOUmtSDZ83EQj8k8Wiv/8/CvihTffVQ6NtpSR+EYsZbksuFHW3tzMGrWhNr7feXHDqjYfN2fd96q6zVPdasFdRRIOa1td3sCvnCBcylRGJKziiqoq5t27CGQJl93SaMkZyaBYV+surMMru19Bjx97yED3pFbcd30fqJ6tbCGQof3CFtP/TCjdKMvthCWHsXT/FUxaehikFMzNdgmykMIHqO2xNtXVh2b3W4g4pGohNj0oOXbV+t+7ZgcuhAr6rNL7nJ3YJSTX0d3E5+H0XnXxxbCWmNw91BAqoUjIP/G9gt9fEOTfh2JeuZB/gsxHrXuBIUuB+2cy+ZfLlYxKisLUrVPx+p7XzZJ/rg6uGNNoDGZ1nSVj+20fsh0Tm05k8i8XbLmaEWAEGIHCQMAmCcBHHnlE3jCtXr3aaowoAQiRC8pNt9UduaHdIKCoAAtjwaT+o/Eo7o3azLlXqtsU535QUJDhdETi5cd69uwJchnWM3IrVgiqCxeMnxKT8vDkyZOyGxFg1FbPiHwcM2aMrKKEF0eOHNFrJsu05JTZhsVUMXToULNnogRGilnTTouf0lfZuorkMnRzFh15E5cunMPZUycQE34O1y+eQUBg9nU+c+K4bB7g5QoXEWvJWRCA9Rs3Rc3QOrJ81coVynBGW8X9l4ht7Wfo5s2bDW3vfyibTDQUqHY639sbvuUrqEpydslVNkO4BRfUtEq9ujpJNypYcN1Vzl/Bw1ihoM2cbCkDsDJGgLcrfnhCKGjbVMP/3V8Pz/euK6uCfIzdylLFzX2iSDLCpo8Axe0rC5aQloDVZ1fj/YPvY8KmCbh31b346K+PEGcpq2hZWJgdzVFPjXtLxKyb+kOYEQrk2kt2WMQK/WL7OZyOSDCqp+/9jzeeMSprEOQNrbLPqIHqgOKLaj+7dp2NVrUo/l36jFoksvbO2ngaKenGf5OU0dgjF2V1scyY1MLXxcOoMEHkLRffRX+J5B6WrGJ9oLcg/F66DIxYA9Tvb6m1XdYR2bcjfAcoFuu/Mf9i8fHFGPjrQOy4usMsHm2D2krSb3rL6ehdozdql68tfms4m23PFYwAI8AIMAKFi4BNugBPnz4dy5YtAyX0INUSkQeWjMg/aktxxZ5//nlLTbnOzhEojFiAivqPoMwiFxSVlTYCkNRlISEhIHLpmWeekX9XRPDQ3xUl0NFT9amWI3cVdZ62XDmmjLZk5O6qNnLXVYyUcpZMXU/92rdvr9tccfXXrSyBQnLzNWfkgqyYNe20+Cl9abt+/Xp88eWX2LFjJ+4kGuOsbhd7+5Y8rOjlIrfkykrWRxB382a9iyOH/pIJR0JDQ2U5/UeKS3JPJqNkLVqiVrmOzsL9t1YdcUN118jdndzgFKPYgaREJDdkrYnc6YgTrrB+wi05v0ZKOm1cqk4i4H5Nfw/8P3vnAR9Fmf7xJ733HpLQAoReAwhI8RCliPUQPT05xYaKZz/Phn/PcufpeRY8ezt7gUMUOwLSi2DoHQJJSCW9J//nmTCb2dmSTbK72U1+j59x2jvvvPOdzbD7m6d8w+F7YpKXb1hyM3dL57KW30+OCbTxx+5QPpdMWosOMf0hVFBW45gQOO2J3XT54bEP0wNjHuBnKRfvkGIe6pw9fIzW1e08FyFcioLISz9DcRBO4i/FQZR1Lhqi/MdFRaQ/KTJSUVuheO1V1Vcp87KaMiqsKqTS2lISca+oqoiOlRxTPF4k2X1LJse9u/td2pSziT6a+REXgPJq6RDs72ACLRUQUoe3YmcObTpSSHNfXc+fH6J/fruPvv3zRJJiHmJSxCPjpLHH3hXsAWzOw13tUz8/iyuJ79UIi1KISHLqTeH0BOrzW3+Mo9bl7+maNzcpgqf+HJLX0FLVc31bh63L96yMz4h+fJSouEmcNT0X/1s35kYiye8nhT0QhmqKSLOltqGW3t31Lr20/SWS5ZZMUiIMiR5CF/e5mGb0nNGqz3pLfWM/CIAACIBA6wh0SgEwLCyMxOvk8ssvV/KTiXeKhP6JYCGeSPIl69SpUySVNt955x1atmyZkkvrk08+ITkWBgKWCKhegJLzrq2mev/J8Rr9Q+mOf3e6lEk+PKlQK8UzxBtP/mZkEhMhU4RAyc0nf2si4JgzKfpgzTzPXLSEmGpNqv+qZsmDUN0v90U17XHqNnUuRT9cyayxUbnIeG1pJ3n49CY/zK6//np644039LvMrldVNYWkqbkofdgDUGzGRZcpAqAsy8uVRx55RBapuraePvxsKZ0+fVpZN+dhKV6ZYmFhEUafkR5RQRwqVm4U3hoRGaW0Nfe/0xXtEwBfWnnQpNteMUF0K4eapUQFknjyXMu5vGwJAY4MNBXptJ0L97ZaoK83BbD3ZSWzVU3Eyx4sVMJMCci/594ejv0qE+wbbHpiC1vk3udW5CpCoOS+Wn1itRLyKyK2OdtbuJe25W6j9Ph0c7uxzYUInG5FPs7Hlu82/Psu/85/sOk4PXLBQCrm59i7648aXZX8vV84zDS3qlEj3cqsIQn01trmfiSc+N7PflOKarx69Ugap6skrDvcrqvHCyvMin9ykpTIQCVvql1PaGtn4vF3chtX9X2QKHOD5aM82aP7kleJBl1iuQ32cKX7Olp2aBn9ePxH2pKzhSrqKlqkEuUfRQ+NfYgmJU8ib0/HPqdbHAwagAAIgAAIKAQ65dNYK0TIl3ERMGSyZNJmy5YtiqeTpTbyI6OuDmFYlvh0pe3t8QIU0eyWhXdQFn9Zl9A+SW6tNVfzAJSxDRgwgDIyMgx/R6tXr1a8wKSSr1T4lenZZ5+lr7/+2mKor/Ya27LcGs8Ia/1rnw3W2nWWfVIlWRX/hg0bpnhxirdkt27dFFFReEh42t23Xk/LP/+YUyEZixSqAJjUvQcNHZlOO7ZuVorBiABYWVNHElL7/pnqvyLeTT13mk3o5H5K/jsplGFreGs5n09CbX05lLkt9uvxJpFSe6wkmhdvvr/OaPZM1O63tNySB+CIlPYJzeIFmFnYnB9MBECYexCQz3ZcUJwySfGPP/T/A50oPUHfHfuO9hftp8OnD9OewqbUBuoVXfvttXT7iNupZ2hPpWBIoI/1lybqcZg7l4B4Idtqeg8/EetmDm4S7fS5BBfNHkChrSxyIc+YbuEBJnkE5Xm6+OdDThUA9akVtIy684sep1o1e7hv5hdeu/9HlMt/Zy3l2vTnl/6XvsnJcqc6dZjudjJ5bj249kHKyM+weejTuk+jB8c+SBH+7fv30OYToiEIgAAIgIBNBDqlAKj3vtCvmyNjSxtzx2Fb1yPQHi/A666/kcq8gqnMwg96VxQA5Q6LUCQVaNUqtNnZ2fTNN9+QFOnYunWrMt14440klX7tZWposPQnHrvWTFusRHuctWO6wj4piiImIbvr1q1TvDb11x0b6kfFp5u89GSf5P9TTQ0BlnUJAxYBcP/+/YoXaGhyGhWXFNOaH79Tmk+dMZuOFFazN52X4oWi9qF6XRYXFymFROSz5MciniKUcB68Mk0BjaLCAvUws/PiyhoOb2sen9lGFjaeKDL2VhDxcWgS//hrg1nLEyjePHNGJbeh1+ZDooL8jATAJ1fspbT4UHgBNiNyq6WkkCSluqU66EXrFin5ANV1mf9727+V1WCfYLow9UKa028O9QrrpW2C5Q4mIN577bHL/rPe5PDhKeF0eXqKyfaWNsjz8/4ZabSQ8w/qIwm0ocEt9WOP/UesVFfvwd7VDjN5YVVwiKjwMFHJSZ7zsuT3q2z+98zsucO7EyUMIUoaTTT8KnaxN5971uyxXWyj5Pb78tCX9OKvL1JNQ02LV58ckqx4M5/b/Vwanzgeob4tEkMDEAABEHA+gU4pAKrhac7HiTN2FQJt8QIU77+582+xiojTormFSXEQKbxx1VVX0dixY5XCG8uXLyfxCpTrtIcNGjTI0I1Ukr366qsN6/qFTZs2GTZpjzNsbMWC/LDqLLZr1y7lUiQ3n6X7Esr56vbt/E1pJ9ceHdwc3qp6AMrOaRdcTE8/+lfFE/qd/75PN9yziH74+kvOAVilHDuDqwVLxd7DLOhJeG8oJ6oX699/gDKv4VyBh/bvob79BykCoGyUxPDxLALmlFRxQZwG2r+72btAPAT9vL2oqKL5R4eEAbdFAKxg78F8zqOntaW3tP3HSXigcREQtd9JfWPoqUsHk76Qh7rf1nnfuGDantnssXisoIIueXkdSTL9AYmhtnaDdi5KYN7AeSYCoDrUstoykkrBMnUL7qZMIgROSZlCo+NHI4xOBdUBc30I8FOXcM5SzvV3MLfMJKefrcO7og3in9r3rCGJJF7Mr6w6RB9tbs5tJx7DlTX1JFV1nWFHCyznvJzOXo92N/Hy++0Toi3suXeqOVdwi+eJ6NFU1KPfdGJlqsXmXbWB5Dt9PeN1+vrI13SyjIVVK9Y7rLfi7RwdEE3Te06nCd0mWGmNXSAAAiAAAq5AAAKgK9wFjMHtCLTFC1C8/0Iioq1eq6t6AFoatOQInDRpkiIASoi85IKzJDRZ6sPS9sTERBaP+iu5ByU/51NPPUXBwaa5uCR34Ntvv610I95mI0aMsNSlTdv9/Zs8zKS4hbubmragvNzyD7Qvv1xGuadylEv1ZgXa+0zeP9mgFQAjo6LprIlTaM1P39NnfD/m3/UwrfjfZ8pxiUnJNDydE6efMflBmMjhaVINt++I5oIsEmZ854MiADb/MJVquFEsOn7JuViLzuR99Oa8kL1j2FOWw9m0AqDkxZO8g1KhWGtSTCS7uJIq+EdvTW0dhXFlaNXEu/tEUXM4rbo9KaLtnina8av9yfw/V420y4/uP0/tS+sOFRiNW3IUPrA0g5YsGK89JZadTCCT851JtVPJuTamZ6SSN9KzlW9ueoT1oAVDF9DiHYutjl5+fMukFArZ9xFF+EUoQqD86I4NiqW+EX2VsOHO9NLCKpAO3CnPEX0I8KBuYTR3dJP33hWvbqD1h617MOuHnxjmT7NbmftP34cUMXr4ggFGAqC0EY9nteiI/hh7r+s9AFNjg5XCH1P7x1F70yEoYz19nGjv1xzSyy+0io415fXjwjs2W2g3ovT5RGMX8D9qbfMgt/lcbt7wp+M/0ZObnqSc8qbvBOYup0doD7pp6E3KC4mYwBhzTbANBEAABEDAhQk0/0py4UFiaCDgigRa4wUootgNt95uIQ1889W18ndk84EOWlqzZg2Jt5+26qv2VDU1NVxZdpWyScS5mBj7fhm85ZZb6NZbb6W8vDxauHAhSU47vT366KO0e/duZbMUvPDjarPtMbnevXv30qFDHE7k5tanTx9D/sYnnniC9OHRco3C2JKpxUDU/RIGLALgqZxs+nrpp7R53Rpl1/QLLzMJ9ZE8lyLMDRg2ir3+BtL+Pbvow7dfo6kzL6SZ50xUu1TmhQUFdNdddxm2iXOGiBrB7CEoYqB4FqpWxXkA9QKgeBCKQCbnEy/B7SdKadob+5VDojjHn/wg1Vo0VxNur3eMhLYdZc881S7iH/Lt7VPtS8TTLxaMoz+9tZl2ZZWom2nXyRLlGvX3xdAACw4lICGgM55fw7lbm/IBf7/7lOLp2paQ75uH3Uwze82klZkr6WjJUSU34K+5v/K/EcZ5OLUXVFRdRF8c+EK7ibqHdqcpyVNoXOI4ig2MpTC/MAr3C4enoBGl9q/Iywht1XLpUesJPHd0cqsEQHnZ8v2dk2wqOtTS6KVwkHhua72cM9sgAMo1vr32iPLyQZ4xkqpB8hX25erF47moyOgekWafcXoPwNvOSeWiJiy6tdbqOcT62FqiHPYEL8/jiQXVvL0s+G1pbU9E/Way6HctUfxQomD7fi9p/WBc9wipci55/bbnbqe1J9fS+mzTMHV19FIl/aoBV9Ftw28jqeoLAwEQAAEQcE8CEADd875h1C5AIC4ujub88Tp699WXWhyNVP6NjI6lAhYprFlrPUms9WWPfT/++CM99thjdPbZZ9PMmTNpyJAhisgnob6SC+4///mP4v0n57ruuuvIW+N5ZY/z33TTTUrV2fXr19Nbb71Fx44dowULFlDPnj1J8hCKIPjFF00/iHv37k0PPfRQu087btw4WrlypZLnTrwOp0+fTkFBQUq/IuRKAQ13ManQfM8991BWVhadddZZdN9995GESFdVVdFPP/1Ezz33HIfwVitek9u2bTO5LL0gPfm8GQoL8Sh86uH7lJx+cpCE/5qzUyzMid3/t6fput/PIgkDvv7yC2nh7bfTBTNnKGKtFGB68kn2OMjJISlUsn37doOYKCKgFP2oq2kWALVioHjlVLFH4GlNmLB+HPI3V8BhelpLjmz/jxcJv3vxTGVh+fF9fysLiWjHY25ZcjG+cU06jX3yR8Pumnr+sXaymIYlhxu2YcF5BL7ZlW0Q/9Szrtyb2+acjymhKXTNwGvUrpRiIZ/u/1QR+U5XN4eAGxqYWThWcoze3vW2Mqm7vTy8aHD0YKXy5qi4USTheTL5e8P7SWXU2rm8WNBbuKYauAheks5gT3aJUlV8aFI4/XVJBn2765TRYfJyYxCH7b4xb5SSAsFoZztWurFHs1YAvPbtLXTg8elGXtwtdX875xP8kT/Pevt5Xx69uvqwUrjp8vRkuve8NIMQKC9etAWL5Nhe0cYvXPT9Keu17JWdvYPodCbn7ztBlH+AaN8Kzt9n/Kw2e6x+YwDn8IvgvH7i6RfZk2jI5Sz8Dda3wrqOQEZeBj224TGTokS6ZorYNyJ2BF0/5HoaGTdSvxvrIAACIAACbkYAAqCb3TAM13UIiDfANTfeRh+/84YhD5q50YloJCJMNbdvyVwxBFhys4mXn+rpZ+4aLrzwQkXEMbevPdukYITkFpQcdmvXrlVEKxGu9CahwitWrDAbIqxv29K6iLUvv/wyFXI46v33369M6jES7vzzzz+rqy4/v52Ftu+//56++44rkLJgKyKt1uSz+e6779JXX31lEHK1+0WAk0ktkhQYGEQX8L346MMPqbS4WGnab8AgSu3XX3uYyfKI0WfRo/98kR6973aqqqygfzz1pDKpDUU4FuZSYVoEQDUMW/brvd1ULxwZk+TGK9FV0lb7tDZPiWx7+K/a7+1T+1Ach/DlcOix/PiP4x//9rY4LtAiRUUk9Fm1i17iv4O7JlEvDpGG2Z+AfL7e5BDfQ5zLUkIY0znMN+xMPss92aZhh1nFTSK3PUYixULuGHkH3TrsVtpXtI9OlJ2go8VH6efMn2lXwS6bT1HfWE/b87Yrk3qQeO8MjBpIZyedTROTJlJaZBq8BFU4Nsz14b/yXJJCQlob0yuKZFLtjnP7siBYqoTjXjS8Gz3z+6FUzR7M/roUBmr79syTIwJohyZvqPT1dUa28mzaeqyQdrL38OR+MWSpKu/WY0VmxT/tmCTFglQzlu8pD80aoOzafNRYsJPnVb/4EO1hxssV3H7Dy0SbXiWqsk3kNu7gzJqHJ1Hf84lG8b9pvc8hYk9xmG0EiqqKaPH2xfTxvo+tehyPiR+jPI/kWeHlafxZt+1MaAUCIAACIOCKBCAAuuJdwZjcgoD8UIyOjaPfX30t/ff1xRbHLIKS5AyUROEtmd7jqqX2jt5/9913K15/P/zwA/3666+KJ1lubpOHgFzT6NGjSbzMxDvQUSZhqyIMvf/++/TBBx8o4xBxLjQ0lAYPHkyXXXYZSeivr29z8Yr2jEU8/KSoiHilieh54sQJxWOuPX121LGSo1HEPRHXROiTUGkRzuQap06dSiIQpqWlKW0sjVE+k/Ua7XrO3CsVAVBtb8n7T92vzmf//gpKGzSY3nr5edq+cS3l5+cr3qTjx4+nO++8k8aMGaOIvdI+LKy5Oq+Eymmt/sxgxNulLeKf9DXTDonpJT/i1WPZ68SBJuKriJX7ThkLT59uPUH3nZ/mwDN33a7/8vlvJHzF1MIK/7h0CM1hz6d9Ocb3QdpIqLu9zcfLhwZFD1Im6VvybWWWZtKPx35UvHVyK3KVsGGp0GmrSWjxzoKdyvTyjpdZxPGkmIAYEi/Eid0m0rQe0ygxONHW7rpcO70AGM6isPx9WjOp3L3y7slUzkWIQv19lKaOEP+k434cprucso2GI4WE5Dm14P1tynZ5li6aPZCuMvPcevnng0bHWltZtiOLHpzZX7n+jYeNBcAR3cMVr23D8fzvDeVwkSkJ6xWPv+0fENW0/F3IcLy64M9ezyL4xfTl2Gt+7qZwbtkw9/HGVy+jI+YFlQVKUaEdeTvocPFhaum5EekfSXePuptm9ZrV4me8I64H5wQBEAABEGgfAQ/+Maj5ade+znA0CNhKQESV5ORkpXlmZiYlJSXZeigdOHBAqUQqXkOS46yjTCqLiqiXn3uKZowbZtYLUDysDh8+rAiAe3NKqIbf/luz/gmhrQrZsdYX9oGAPQhISFsth56qJknnT5VUc8GNpjxo6vbWzIdweJw5k1yTkpdQqku/9957ShMRWKSqpWpSOdiXf9Rqi4Oo++qKsqmgtJKOFlbR478UqZsNc9ES5QfwH8/qYdjm6gvz3tpEEoKnNfFI2/HINO0mLNuBwFe/ZdMtHzSJJdruIjmP5OYHptLox38wm8Zh39/ONypsoz3WUcvy1W13wW768fiPtObkGjpZepJKa00FytacX8KGB0QNoISgBOoT0YfGJozlvzX7vFhpzThcsa3+s9ErJog9cSe7zFBzOd3C6Cea0wXIwCZyVfLjXJBJm6tUtq/9yznUjfOMqibfTc5/bo26atP82z9PVDz9Zr2wRvEuVA+6gwsYiXe0Yqd2Ey27lXP4bVV32zZP4Lx9UalEgVw0LYjz9yUOJ+o5kcgbn0XbADa1qm+op8/2f0b//vXfVNpC0RSpOC5/70NjhtLU7lMpxNeKF2drBoG2IAACLkWgPb+/XepCMJh2EYAHYLvw4eCuTEANRbTmBah6/8mPtTqtG5UFcK4YAmxhqNjcRQjonVwkkl2bh89eGDZv3mwovDJ27FhDt3oPwHJOVF9u2Gu6oB+v2sLfx5NeuGIEnTsgTt3kFnP1OaMdrITZwexLIIdDeSVnmzmTPGcihFvK4SrHWgqtNNefPbaJ99nA6IHKtHDEQqXLWi6iILkD9xbupVUnVtGG7A2UXZZNNQ3Wc8+q45FiADKpJiLAtO7T6Lwe51G/yH5KFeKWvN7UYzvb/HSlMUPxAOxIK9tRRsFDm9MASDX1Jy8ZTPd/0Xz/Vu83fnGgjnc3FxZSBUDJofrwUvPh5eJ9/PRlQ2g0h8EPf+x7pcCS2seaA3mUEO5P0pfWxvTifHz1/HJo3b+Jfn6Kl425adsqy5G92KMvhfP38UvgWE4l0X8W5/PrYdIMG2wjIELfh3s/pPVZ65W0AZV11j2U/b38FQ/jPw78I/l4duxn2rYrRCsQAAEQAIH2EoAA2F6COL7LEtD+MP/TzQvp0/feNPIC9PcPoFtuv0Ph08ACoExakxxC2j5kn3gowUDAlQjoRWkRs9UwXHWcUqijJe/W40cOU0pP/rFnxgq4CrCEcYtJFefLL7/c0EqfA9Cww8KClwUF8MtbJ1AfDpNzN5s2MJ7WHLA91NPdrs8Vxiuf6Xs+20H6ME/t2FZZEFOkzUn2UnW2AKgdm7osocMxgTHKJLn+xOTaymrLFDFgzYk1irfgkeIj6iFW5yImfH7gc2WShkE+QTQsZhhdlHoRnZNyTpfyDtR/NtS8kFYBOmhndU41bT9nO6XvSie/+Oaq9wMTQ206Y8EZj2rJdfl/y9lLT2d/Zg++BZPZA49Nnu1i5w2Ip4+3ZCrL8r+/fbVHyZOppjaOpBK63GcNpW/8gGjp9qbCHobWugXJ3zfoUqKz72bRD6kMdHTavCopAp7Y+ATlVpoWctF36u3hTVNSptCdI+8kyT0KAwEQAAEQ6DoEIAB2nXuNK7UDgQb+tiuhj+LMV68R9Mx5AUpuwHq/plxm5rz/JDePhGhorat6V2gZYNm1COgFQBGttZ99Ga2E5LYkAN74h4upW3J3mjFrNhWNS1fy/BUVFSnFXRYvXqxUdZa+HnzwQYqO5tCvM+bt1TpVXIR2qcaptb9MT3NL8U+uQfIVPrR0p/ZyKLe0ij2KG8ibucPaR0BYXvv2ZqMwRnM9rtKFYWvbnCyy7mWjbevsZfk3RTz5JLxPpnvS7yEpApBdnq1UHf7l5C9KGHFJjbEnl7lxlteW09qstcoU7heuhAqmhKRQXGCckj9QioyICNkRJs+fz7edULzUpqTFKJVopTp4dLAf14do3TPE3PiLdVWAtRWAzbV35LbMf2RSXWEdZT6dSanPNAl1cj5Jz2CLiSereFL//Zu9Js0DubDJvHE9DMKf2mB8n2gjAVC2f7gpkyJY+PuT9zc0z+tbCvXgv4N96hG6eUgCUbeRTdV5B11GFN08bl1LrNpIQMT9UxWnFHF/2cFl9FPmT1aPnN5juuLN2zOsJyWHJHfY36rVQWInCIAACICAwwlAAHQ4YpygMxCQL8unOMdOOVfBky9dft5eFBlk/ENH6wUo3n/zbrpNqd4pP9Rr1dfkZ2CIl1JrPZs6A8fOcA1STbempoWwJjMXGhsbSzK5m+kd6mo0+QDVa1G8RJrT9Kmbjef8d7N53RpletR4j2FtwYIF9Ne//tWwLgteVqo7SuJ7fYEM+VNLigygEH9vKq2qo0Su1Pv7ke7r4SD55yTf1nnPrTZwkWvMLa2mRE0eL8NOLLSKwKNf7m5R/JMON+mqnWpPsulIIf1+VFNOW+12V12O8I8gmSTfnxT/eOish2hT9ib6Le83yirPosOnD9Nv+Vy4wYpJqLHkF9NahF8ETe85nSYlTVIEwYTgBPLzavZQ07a19/Ldn+4gKU4hphW2hiaH06tXj2x3le7TOgGwozwAxfsv6+Wm65R58j3JBi/AEC40EhPiR3n8bLBmklP1eGGFUpFY307yo5oTN8f3jlKa+lENXeC1noZ7HKQeHjk03PMgBXpYOZ94+427jWgyP9d9jF/M6M+NddsJbM7ZTE9vflopCtTSUf0j+9Ndo+6iMQljWmqK/SAAAiAAAl2AAATALnCTcYntJyAOBGUsAqpWXVdPVbXGebi0XoDi/SfrYrXsLqgvmCCeO+33SVBHg7kzCUybNo2OHTvW6lM+8sgjtGjRolYf19EH6D0ALXmzWhunhN4ufu0NWvntClq39hfF2y8vL4+kkE98fDxNmDCBbrjhBho3bpxJN/ocgGqDQF9v8uNceJIPr5LzWKkW7OdFwVwoRBL0H8oro0HdwpR1db87zvvGBfNLB0+jH+zZxZUWBcAi9vCRkMXuUYGo4mjlhos36/e7TllpYduu73afoidYGBevbnc0yf01vtt4ZVLHL7kDVxxdQd8e/Zb2F+3nvJ/N//6pbfTzouoi+mDvB8ok+7w8vGhU3CjFU/B3Kb9TQpP1x7RlXV7CrT9UQHksZElOT1lWxT99fzu4Eu6kp1fSlaO709DkMJo1JLFNL9/0IcDhgcYvAPXnddS6eP81VDUVZWqobDDxAhyREk7ftvCZlpyW5kRC8fyT8F9zFsXXe0vkVrqi/B1K8rAxJUEM5/Sb/QJRcrq5LrGtDQQKqwrpmS3P0LJDy6wePT5xPF2RdoWSIzQ6oNmj3upB2AkCIAACINAlCEAA7BK3GRfZXgL+LDLoc/bpfxDIOcQL8MvPPlS8/9RzSsGEkkrjH08iUkh/WlFRbY85CLgSAX30XJ3Om1VCDK15s8ZxOK6IdBeef64ytfbaLPWthvkmsIff4fzmsiAiDIqJJ4xMncGEsVyntppn1ukqSo2ppX/9sF+5/j+MSaHzOF/gyn25dMv72/ilQz1NHxRPi/8wAiKghQ9BDnt1m/No/c9VI+nOT7YrDC0carRZ/i1YezCfJvdzPw9fowvRrIj33rWDrlUmSVWRU5FDv+b+Sl8c+ILE+8gWq2+sp405G5Xp8Y2PU0xADMUGxlL30O4kOQonJk2kUF/b8tZpz/fcDwfo3z8eUDb15mq88lm3ZlW1DfTm2qa8hyc4XPuWKanWmhv2idCopuXQFwHpCA9ArfefOki9F+CE1OgWBcADp8qMKqtLX6mxwUqFdLVfZV7JldQz+V5nc06/PcvonooMavHNZRoX8eg3nUN9hzSF++pdyI1OgBVbCOwq2EUrDq+g3YXsrZy/k6wV9oj0j6R70++lGT1nGD67tpwDbUAABEAABLoOAQiAXede40rbQUB+BIhXkVb00xf1kP0ecfH02sf/M3j/ySkr+ceJ3gMwlCsIiiiSV1ajhBRLu9gQhMcIB1e3o0ePuvoQ7To+vQdgPQvaWhOB0FLhDRHOJQdXe0w8APVFRtLiQ3hbkwduMIe99Y4J5vD8Oios96JG4+G159QudawIqVoBUEKAn/1+H72zvskbdf2hfFrGhU6e+36/QRBZsTOHJDx1TK+m8D2XuiAXGMyxgmbhWB2O5ECbwPnO7p7Wz2yBBGknn8ckDr/WCs9f/ZbdqQRAlYfMvTy9qFtwN2Wa1WsWHSs5pngGylxykOWU5yjbtMeYW86rzCOZRND4+sjXJIUIRsaPpD7hfSghKIH6R/WnEbEjlPOZO162ZZwophd+ahL/ZP1Qnuk9lO2W7C0WAm+a1NvqS4udJ4tp4Ue/KvkE7zu/H12enmJUAVf67ggPQK33n3p9ei/A8SwA6m0MV/HdyM8B1XZzRWv1uaFuU1+oKOtHf+Eqvuy5d/AHIhs8P+saPWlf7Pk08PePoKiHCtQO86yyLHpu23O04sgKq72F+IQo4fwj40YqXn/h/uFW22MnCIAACIBA1yYAAbBr339cfSsIBOkEQP2hwZxzLCUykMsuDiZO0WUw+aGuNfFokr5EWEll7wUJxxExIzrYV9sMyyDgEgT0Dhz6EGAR//RtZODd+W9BhG7Vg6atFyPHJ0cEUnZxlSKWx7MnnCr+qX3K35Py98l/W1wLoFNatM6bUfJ4LWfRSTVJNfDUir20gwUSrf1343EIgFogmuVjBRWatabFRbMHKi97kiICTPbJBil4s+iCgcpLHamEqpq7hwGr12HLXDz4bhhyg1HT4yXHafnh5bTqxCqluIgtRUXqGutoYzZ7CPKkmngJSoVhCWFMDE5UCoyEcTEteQ7k8DPghve2kM4JWT1UmUte0N/1j6Uvtp0k8fDUWz6/dNvC+Rz1orgU+CrjlwjywuHG97YqlZ3l2EeW7aJpXAG3hL08tRYe4Nx/r815/6nj0XoBSiGQs1nAViuHD+YUCDdM7GUkAMpxEhqtte7+/Lew7xtWWD8l2mmc21HbzrCcNJr2hI6jlXlcWT1lDF17Pqdv4Bc+sPYREFFdcnFuz91OSw8upZqGGosdBvsE063Db6W5/eZaFc0tdoAdIAACIAACXZIABMAuedtx0W0hIB5+1kyEEMntJ6FBpzU/FvSegpJgW/WqCuBwxW5nQhat9Y19INBRBNTPqnp+cyHA6j7tXAS59op/an/Sl4SodWWL0XlS7mEvHqnmqbVV+/O0q8pyAQuFMPMEjuo8AEU4mXOmmMfEvjFGBRVC+QXPVWO7KxVSY9kb8+TpStIKgJ0xDNg8NfNbU0JTaMGwBcokLUQAFGHv+2Pf0+oTq0kqCNti4iH48b6PlUltnxiUyBWMJ9DarQP5RYBlj2J5ufb8FcOpH3sI33t+Gh3MLaU5r2xQXrKpfcn8o82ZRgLgNzuzadGy3WYFQwkfFo857b/p0oe83HCmmfP+U8+v9QKUZ+4LzOCDTceV3Vew96J8Vi1ZN8qjRT7v0LkHt7HHn6VWmu0xaUTn/h9Rn2nUn8/FWf5gdiCwu2A3Pbf1OVqfvb7F3viVG53f43ylondMYEyL7dEABEAABEAABLQErCsa2pZYBoEuTkCS8HtzRVLJ6WfO1FxlIgJas8gOSh5ubUzYBwKWCPBvaiPTC9qWivR66g806gUrrSWg9xD+eZ+p2GeuT3PJ/s2164rbjuUbewAOSGzORyfh618vPJs+33aCRHw9j/Mpal8CdeMQ4OFccOHX482eVK+sOkwSgumuxUDs+RmQ3H7ndj9XmWrra+lQ8SE6VX6KTpSdoPVZ65XJmneTdixSmfiLg59QQxC/BPC6g6g+SLvbsDz/7J6K+KduSI0Noa8WTqCznvxJ3aTMl/x6kq4d35MGJ4VRORf3uvez36iEK4ZbspOcN1CfZzDCif+OW/P+U8es9QKUl4wLJqequ4yKJBk2cpzCXK+V9ID3+xTiYVkgJKni3G0EUeJw9vQ7i/P7zeB7gJ8OzRzbtiR/E+Ltd7j4sOI5uzJzpdWOJMz38rTLaWjMUBoYNdBuBXWsnhQ7QQAEQAAEOiUB/CveKW8rLsoRBOTNuvwA1CcDV8+l/uizVLVU2kneP/H6g4GAuxDQewDqxy37lfyXPJek+WKSI62l4/T9YN06gbbmUpQ8dVVcJVkELZgxAb1nlJLCQdNEishIvjhLNnNwgpEAuP5wAY1/6idazqITcro2U/Px8qG0yDRlkq1/6P8HxSNwXdY62lOwh0TgO1B0QKk23HyU6ZKndxkFdHufqnNnUGNdCE8i2Da9oZg5JEHJ26g/KiEsgLY8OJWmPP0zlbLYp9oFL/5C7103WinQZU38k/Y7s4zD6mWb5OR0llnz/lPHoPUCVLepc8nv14vTjfjm76FLvVZTH4+TNMDzGMV6NIvXalvD3JfF1ikPEA2/isi/WRg37MdCmwgcLT6qVMmWKr62eMVKnsw5/ebQTUNvogj/iDadEweBAAiAAAiAgJYAlAgtDSyDQAsEgvy9WAA030g8BMW8vXQuU5rmEUHOzRukOTUWQaBNBFoK41VD3+VHpuToEsc/+dENsy+BKF0IsK2913NuM8l1J2GRXdVEmH6Wi6N8t+sUh35G0sOzBijpGvQ54qTScmtsBguAT3y9xygnneR8fXvtUSUEtTV9dbW2QT5BBg9B9drFG+qn4z/RmhNr6GjJUSqqKmI/NW1GXf73Negwefd8UTkk1Dec4n1ZWIwYTL9LDaC9hbsUz6iogCjy8WwO0RXx/KbJvenpb/epp1LmV7+xyWjd0koGFwXRWgi/CJS0BM4wW7z/1HEoXoB3dSO/YBb2QuJZG236LuJZkUefxv+Xoko5v5818+Ecxons7ZcylmjUn4jCkqy1xj4bCEghD8nnd6z0GO3I3UFrs9a2eJR4+42KH6UU9pjec7pSNbvFg9AABEAABEAABGwk4JxvMDYOBs1AwBYCnmdiDuvr6xWPo5YEClv6tLWNNgRMe4x4/6mhvxImbM5knOFOzhtkbhzYBgKtIdBSJK+6X7ylos4UsukI7z8ReeSZIKY+I1pzna7eVh8CrB+v5Kiz5Ml0oqgTC4A7vyDa+J8mwSMkkZOzJRBF9SHqNZldUVnQYFu6/SRXjj2oLO87Vao8h2/7XR+SQipaa61XVyKHAU9nEVAqAGtNPAFhrSfQK6wX9Rrci+YPnq8cXNtQS0sOLKHHNjxmtrOSmtOca3AD7S/bQMsym5uI+Ncnog/1j+yvVC6ODoimXikR5OtfRDVV4dywSRhrPqJ56boJPWlfTin9cjDfsFGqAmstNtRyHkJtO3ss2+L9p55H8QKc+3+Ues5i9toLI5p4L1HRUaLfPqao6hK1mdl5cf8rKOzCvzcdZ7YFNtpKQP4t2pizkd7f8z6tylxlImJb6keK3cwbOI+uTLuSAkWMhYEACIAACICAAwhAAHQAVHTpWAK+vr5UU1OjiH/V1dXk7986r432jE4qQIrYV1tvnAdQG16negLqzxPm72MQCfX7sA4CrkqgJTFPu1+77OzrkWeBIQSZnxGdzayFAL9z7Wga2T2Crnh1A+m9lYRDZqFxrrtOxSZ/P19gcxVZ9dpqPf3paNREyk2eRi+vr6dQiqASktxxXCiCxcDZwxL586K2bpq3xXN14Tl9TARAEYwQdm3Mti1rn23Jpm92dae6yp7s+XfE5i5EOJSiCjJpza8nF6qtC6SGKr739cE88XJNDNVXJvM2Fo7Ji2YMjif5W9MKgFJhW2tSidwZ1hrvP3U8WesnU/LoD8iP2AvwOw7hbcEON8TTE43z6JXf/4XfnFgWRlvopkvvrqqrUqpfb87ZTOLxd6T4iJLr0hYosYGx1DOsp1L1WkJ9xTMWBgIgAAIgAAKOJAAB0JF00bdDCAQFBVFZWZnSd0lJiVMFQDUPYFGFcfVNf59mrz81/5m+WEJkUHNIkkPAoFMQcACBln4TukqxD3kWqCbPiM5mlgTANfdOoeTIJm+Rt/+UTg8v22UiSGVyEYNOa6XG3nfqdfo0VFGfvO+U6bszDlunGsPpm/p0eq1+Ft396W9qU2Uuz+22FHaQ0GrhPu+tzYb+RDD6ckcW/f5MRWHDDizYTGBFRjbd/0WG0t7D6yryiVzNIuBB8vApIW/vCmqgJm9fmzs809CTj/UMbvIG1R7b2MAv6OoT6LX9X1JxuQ/5xfELBc4xKOJgPQuG1CBpDZoEstZ6imrP05rl1nj/qf021PlR5tqLKfW8t9RNRvNar0B6r3oi7WjoRUcaE2hnY08a2C2C1CJmRo272EpdQx0VVhVyKPleqq6vplFxo4zy7tU31Cv7tudtpzwOqy6uKaaCygKl2nVFne0vWaRAzqV9L6W5/eZSYjB/tmAgAAIgAAIg4EQCEACdCBunsg+B4OBgOnXqlNJZQUEBeXl5UXh4uDK3zxms9xLO1f/0AmAoe/epJiKhhEJqq2/Kj0tn5QxSx4E5CNiDQEsh9i0JhPYYg7U+JOz39OnTJM8C1eQZ0dkswNeLPZN8OWy1+eXDQg5jVcU/uV7JE/jSlSOoe+ReWvzzIQOCNQfy6NEvd1EQFyC6PD3Z6BhDI3ddKDEvAJq7nDguenCN9/fKlHkqhk74xFBmYwz90jCIMkImccq0tnlATe4XS/0TQmlPdrMI/cDSnewp3khXjE5uc7/mrqErbBNP3js/2WG41Eau+luTN52npk1LFoyj6Igy2pG3Q8mvJoVEcitzKb8yn0TEaYt5eNZSvedxztF2XDncN9K4l8YGb0UQbKwLpl31kXTPKq4KzYUygn2aJinQEB8Ur0wJQQkU4tu+nJtt8f5TR5y1ZTolj1/SlAtQ3SjzoVdS4ej76P9e2KXdyoXJOneBICm2IZ55Mp2qOEWVdZUkXnvldeV0vOS4UolXKlSbE/H+OOCP5Ovlq3j1bcrZRKU1pUbsbFmRz8jQ2KGUEpKiVPCV6tgI8bWFHNqAAAiAAAg4ggAEQEdQRZ8OJSAhwDExMZSX1/RrIDc3l2QSIbCtP+BaO2BvDgGuk7Ag/r0oIcFZlWd+mZzpiPPuU31NnSHEzJs9BA+WNomWrT0X2oNARxKQIhJ1NZa9bQpKPak0t9kD1plj1eb9U88rzwZ5RnRGmzeuB/3zu/3KpY3uGUm3TDFfoVYrCkrj/afKlEmWP96SSeI1qE1bINvd1sbdSpQ6lUg8AXnavzeDelftIi8P47BN/fUle+ZRMuXRWbxjDq2iouoPiFbdQjTsSs4jyF45rRQDLxuZRI8tbw45ralroL8uyaDNRwvp6cuGIP2D/gZYWd92vIgquXK1OfPmNw4itvr7RFBySDLN6jXL0EyeB6erTysVhSX891DxIcrjf5vzK/Ipuzyb8wU2C7SGg2xc8PCsIw/fQs4rWUhZNccp66j1AyWUMz6QBcFgnngeExhjEAuDfIMMy96e3lRTX0MStixzEadEsPJ93JeCqoKsn8TCXvEC/O+vV9IfZywln+TRXLJ4IFG/6UTxgymOj0mLP057Oc+hahcP76YuOmwu90auTUQ28ZrLrWgSbOW6ZRLhVr8s29TtRvN6bt/I7bVzacvbhKF47xmmumqqaWh+adLaC3x397utPcTQvkdoD7qy/5U0u/dshPYaqGABBEAABECgowlAAOzoO4Dzt4lAVFSUkgewuLg5ObdaAKBNHbbyIPETMUT9clgI/9YzMS8OUqqqq1cEQvktWmeukclR2AACrkVAfrgVlVUZVTrVjlAK23hyAQpXsLCwMJJnQ2e1Wznf3OieUVRcWUsT+0aTn7d5z53kCMsJ5MUzeeuxIhqfGt05MPWcSCTTGbv6iR+orjqXzvPaQtM9N9IAz2MU5dEsdqjt9POIhiKilX9rmrw4ZjiiOwuL5/J0DlESiyj+ofpDjNavOas7beTiH9/tNn7Rs+TXk9QrOoik6AjMNgJvrT1qseG/5w63KF7LC0DxxBudMFqZtJ3IcyyrPIsy8jPoZOlJKq4upgOFJ2ln3k46XZelbWqXZRHxRICUqbUWcjqEFn2wqLWHGbVP/mUKXTp3F10+eJqyvTZ/K1WdWsvP8QYaMqiCDted5O0eJNELBd7H6WXV4VKjm2srMBstM0vVtNvFq66stkwRMOX6K2orFEFWRNiymjKbi2GofbvT3NPDk9Lj02lk7EhKCE4gKWgzKHoQp1X0dKfLwFhBAARAAAS6AAHX+NXWBUDjEu1LQL7oJyYmUmRkpBL+V1FRYagAat8ztb03b/7rCjiTe6rtveBIEOh4AqU1lUYh7doR9Yv3oXD5sHeQiedvYGCgkgbAmQWBOuhyWQDUxSaaGcjQ5DAK5LC+CguemznFVWaOcv9NUtX3VIlU9g2jD+p/p0w/3DmRoiLZI5SroTZufZvqN7/Jud5auH72ICIpLiLThpe4P37lExBB5MdhneoUlkSUwv6DicOIInuRN+9/kcOvn1qxl95ce8QI5rsbjtGCKanIs2ZExfzKd7tyaLmuqrK25cwhCdpVm5flO0O34G7KpD+oqKpIEQbVvG6nq4rptXUZ7PGXzS83stgZ1MwbPn0ndlyfumIq+dbyZ7Yd5lvjS8M+H0ZP+T5lthe/mKbN8tfySobZJthogYB49qVFppFU7Q33CycJ+Z6YNFHx8rRwCDaDAAiAAAiAgMsQ6LhfbS6DAANxZwLygz8+Pt6dLwFjBwGXJ5BReoIeX6G6iBgP999zu9PEPo4PITM+K9asEQhhr57X/jiKXlp5kMqq6+gEFwEpLG8OgztV2oIAZq1zF96nzcEnwwzw8aKe0ZwPUhJVxvQjj/OfJO9zHqK6U3to2287aPfuDOpftp7GeOxp4arY46mSwz9l0lrGp81r4d3Jd8TV9PCUa2hE93C69YNfDfvE63LtwXz22jyjuhj2YEFL4POtJ+iuT80/Z6Sdj5f43tvfxGtQBBytLfnpJ8rMkuI5HPrrXapMnj7FNCTFhy4YHqnkghNvN/Fsk7xw4uWWU55DBVXNuUi1/dm6LN5/E36aYGtzq+0mrJxAP0z/gUrDW/aAtdpRJ9kZ6R+pCMCSk8/f25/8vfwpLihO8dZLCU1RxDzJ3Shh5I+sfYRyKnKUvH0Svh3lH0UDowfS6PjRSp7HToIElwECIAACINAFCUAA7II3HZcMAiAAAq0hMIWLHIiGIrkt9RbIhSVgrkdAQnzVMN+7WVT5jMUV1XIVLzl1rfPMjxYYV+JMjQ029brzDSTv5JE0WqaZxHla+UOdzaLThpeJ9iwj4rDFNtnpY0Q//Y3o57/TrAGz6WRkNK0+HUnbG1KpnAJo45ECCIAtgH119WGrLe6f3t/qfnvuTAgNoMxCEQCl+EeEMnFhabph+Ag6f5BlL0TJPZdbnqvkHBQBSURByT94uuq0UXisIhzWliqfPx8vH/JlL1OfytN03vJz2u39p3IQL0DxJlxyxRJ1k0vMPfhaowKiKCYghgK8A0jyIPp4chVmzVy7rN+nrpttwyxF2PPjMH51UvIxcoEWEf1ssdjAWPpw1oe2NEUbEAABEAABEHA7Avjl5na3DAMGARAAAecSiAjypZHdI7igAedJ01lQJ68gqbtct1yNCzXORZDbST0ATxQZi3fJkQEt3i+lcJSE8V7yCldu4nDfMs7hd/o40cEfiI6uITq5jZXv2hb7MTSQtjs/pxt5w40cxVnR6Edv159HeeV/NjTBgimBSg5XP5Br2VOtV0wQ/X4Uh107yeLDTMUiedZJxWdrJqJTcihX2ubJJmPRj377mOjbB6i6JIg2/nw2Zw+2n038eSIVXFNA9TH1ijCm5qQT4VvyASqffz6diHKqqdvUdZmr+7X7DNvOHCtCZqhvqFLhNtA7UCl8IR51IvRJuKwIcTJJ9WQR8WAgAAIgAAIgAALOJwAB0PnMcUYQAAEQcDsC56TFmRUAg12kAIjbAXXigGNDjMWMpjx5ThyAnU7VwC6oe3JKKC7Un6KDjUVNOcUJxWOr+WTWiqE0t9IsefFXojAOZ5ep+1lNO2rZCyxvH7E6wxMLVNVlROzNRZmbWBzc0iQWspBiyQI9qmmB9zLK2reTKJe9imLTLDXt0tv38n3VexjfzoVTpPL18cIKSksIsVj0xhHgEswIgNMGshcZh5XbxY6s5oIzT/LnaAO7oTZ9fjLXXkJSwdee5l3tTXdsuYNSn0m1Z7foCwRAAARAAARAwE0JQAB00xuHYYMACICAMwlM7R9Lf/9mr8kp+8ZxYQSYSxPoDB6A9awOXfHaBtp0pFApcPLilcNJRGmtZeo8AJMiLVdD1h5nddmHvQjFQ1BvY25s2lLHuRVzfiPa8iZRxmfsRVitb6msJ1YfJnp1EtHYBUQDLiRKGMpuVc1eV2YP6kIbd2ezwKoxEeDuOLevskU8kJ1twX6mX48vGJrQ/mFIyPm654m+f4T74uUzVl0WTllbzldX7TrPejmLku9JJr94+4qLdh0kOgMBEAABEAABEHAKAdSndwpmfvGfm0vLly+nhx9+mKZPn07R0dFK6IWEU8ybN6/Vo1ixYgVdfPHFlJSURH5+fspc1mW7rVZXV0f/+c9/6Oyzz6aYGM7FEhBAvXv3phtvvJF27dplazdoBwIg0AUISD61FJ2gMn9CT/t5xHQBhh11iTFmPACV3HcdNaA2nPenvbmK+CeHSnXj2z/aTlmnJUdbkxVX1iqeYuq6zJMiWg4B1rZv07I3i1NJo4guWkx05x6i858iGjyHcoPTqK5R9xWrjpPI/fJskxD45nnsPZjZplN2xoP0BVzSe0R26GUOSAw1Of+E1HYWcRGxeNmtLP49zH03i39yIkd4/6kX0FDZQJlP47Om8sAcBEAABEAABLoyAdNXnF2ZhgOvPS7O2FOhradqaGigG264gd544w2jLk6ePEkyLV26lObPn0+vvPIKeXrqfnxojsjPz6cZM2bQ5s2bNVuJDh8+TK+++iq988479OKLLyp9GTXACgiAQJckIC8rbp7cm+7/IkO5fgnBnH92ry7Jwt0uWu8BWFPXQKcraqkjPKvaym5HJofdaqy0qo7u+WwHvXFNOj22fDd9siWTauuNRZVWhwBr+m/TYlAUe/jdrBz61doj9MHy7+h5nxepv+dx0+4yNxK9NoXoyo+Juo003d/FthSUNVeplkvvER3UoQSkYrMIyFJBW+zhWQPI19vydyqLgxWPv0M/Eu37pimvZNERk6bVFbGUtZUr0jjQ4AXoQLjoGgRAAARAAATciEAbvs240dW56FBTUlJo2rRpbRrdAw88YBD/hg8f5pFdzQAAQABJREFUTh9++CFt2rRJmcu62Ouvv04PPvigxf7r6+sV70FV/LvkkksUz8GNGzfS888/T7GxsVRdXa14ArbGo9DiCbEDBECgUxCYm55Mb/8pnf46I40+v/ksMpcov1NcaCe7CMmZJ1WctaYKG9ptrry8N4fz7+ls7cECmv7vNfT+xuMm4p+vl6dzPAB1Y1JXAzhX3IHGJLqo5v9oRX26utl4Xp5H9Mk8rjzc7Mlo3KDrrIlXp9Y6uriQD39+vlp4Nj120SB659rR9KfxPbTDs225kosmfTiX6L+XEm1+jchE/OM/yon3Umb1Mq4z49j38fACtO2WoRUIgAAIgAAIdHYCjv3G0dnpteL6JPQ3PT1dmcQb8OjRo9SzZ89W9EC0f/9++uc//6kcM2rUKFq9erUStisbpO/Zs2fTpEmTaMuWLfT000/TtddeS6mpqSbnEO++X375Rdm+YMECeuklrnx4xkaPHq2EKI8cOZJKSkpo4cKFtGfPHvL2xkdFZYQ5CHRVAuIFKFUwW6qE2VX5uOp1i5iREBZAJzUhs1JYYXBSmE1DPpxXRnWcg68j8z3uP2UqAMrgj+SXm72GK0Ynd2h4esCZ6tjV5Es31/6ZLg3NpGcGcxjm7qVEJSebx1zM3oGHfiJKc6wHWPMJXXNJqgBrTeWn3ebs5bAAH7p6bPe2nTab80J+cjWLfkfNH+/D+SkveZWqI6ZR1kz2BnWCwQvQCZBxChAAARAAARBwcQLwAHTSDXr00Udp1qxZ1J5Q4Oeee44kb5/YCy+8YBD/1EsIDAxUtsu6tPvXv/6l7jKaqyJiZGSkIhQa7eQVEQ3vv/9+ZfPBgwdpyZIl+iZYBwEQAAEQcCMC+vyN+oIZli7lhR8P0DnPrKJp/1pNi5btstTModvLq+tM8vtZOuGE1Gh66coRtGj2QEtNnLJdPACbzYM2N6ZxfsAniG5eRxQY1bxLllbcR5S1nQuINP37bryza6xV1uoEQCN+bsKgiguZ7F5G9PU9RG+ca1n8i+pD9KcVRP0voMx/ZFJDVYNTLhBegE7BjJOAAAiAAAiAgEsTgADo0reneXCSsP1///ufsiEtLY3Gjh3bvFOzJNv79eunbJH2+kTv4kUoHn1ic+bMIRENzZm2MAkEQHOEsA0EQAAE3IdAcmSA0WDFA7Alq61voP+sOmRo9va6o6Qv1mDY6cCFDYcLbO7933OH0cwhCUqRLZsPckBDvQebQeAKCFfCPo1OWcyegVIh+B8cFfDDIqIa816NRsd0spWKGmPxM9DXzaIOpAL0vwY1ef1tepXfwlYZ36HAaKLfcfGP+ezteQt7/HFl6eqcahKvPGeanE/OCwMBEAABEAABEOiaBCAAusl9P3LkCGVlNX1RlDBfa6bul6IgEmqsNTX0V7ap7bT71eX4+Hjq27evsrp27Vp1M+YgAAIgAAJuSMDEA9AGAVAq65brQjMX/9wsCDoDQwOHHr+08qBNp5JK1VFcnMYVzNgDkMgoxJU9v8jLzDir2YPsF/bcf2kMF41gDzEbTAq6yH3Sv+yz4VCXamLEh0cWeCaE2qUGaW4wUtlXPP4+v46outhcC64SnU5042qis+/i5ZFEnk3eoc70/lMHBi9AlQTmIAACIAACINA1CUAAdJP7vnv3bsNIxQPQmmn3q95+avu29JOZmUnl5V3PI0FlhjkIgAAIuDuB5Ehjb+9MGwRACb3V27e7cqhKF66pb2PP9ZfZA3HbceMKwH+ZnkbBfqYeYnNGJdnz1O3qy5wHoEGkC+tGNPMZIg8LX8HEI1CKRyweR/Tpn1gUfI6o9JTJeLYeK6JxT/1EQx/9jsbz/HkO1z5dwYKUG1qF7jNlxE8q6bqSyXhO8Xeybe8SvXU+kXj8WbL064nmfU0k91xjHeH9p54eXoAqCcxBAARAAARAoOsRMP0G3fUYuMUVnzhxwjDOpCTrP3KSk5MNbUW801pb+pEfLXKcGlqs7c/SsvY85tpkZ2eb24xtIAACIAACDiAgRUC0VlDWJBTtyDxN764/Rt3C/WnBlFSjwhllZgRA8ThLe+gbJc+ehNo62r7cYRwiKdV9LxuZRInhAfTAkgzFsy69RyRdMDSRXEoA1OWwq2dPxtr6RvL19mhCNuJqojjOU7jlDaJj64kKzXhW5u4ikmnXF0QrHycayqLgWbcRxTR550tOxvyypnDOrOIqevb7/UrI9tz0FLppci+KDfF39O2xrX/JbViRT41luXTo2DE6fvwInc7Loh7+FTQs1pMd4nxoYd1Jqvb2pBrypgD+f781HxKtZuGXj1GKpnizx+Q4vvYJdxifUyool/BnpIwFUmkrU9FRotPHOKcif8Yb+NzKxHn2fFkED4gk8g9lD0xfIulTPDF9mFNwXFNuRsN2dT/P1W0S1rv/O6KNL/P9Omw8Du1aj7OJek0m6sviYDyHBZuxnLdzyDuq476Cy/m7/6W7mZFhEwiAAAiAAAiAQGcm0HHfPjozVQdcW2lpcwXE4OBgq2cICgoy7C8rKzMsy4K9+jHq1MyKVoQ0sxubQAAEQAAEnEggNMD4n/tSFvdEPLrytQ2GMN+vMrJpyS3jKdTfRxlZeXW9xRHe8sE26hc/kVJjQyy2sceO/DNCpdrXZezlF81hvrNZ8Js+KJ68uDK1p+cZUU1t5AJzcznsJMzVl0Uug3UbQSSTWN4+oq84RPTomqZ1/f9FzBKPM5lCEqkypDtdeCqcEj370fHGOEU486U68q2tpYx1u+jR7URPzupJod4sfNXXKmLY8bwi2nPgICV6FFJaXAD5eGrGwhyV4iSN3F6ErjoWFtW5CGgigrFQR548ybK0q+U8kjIuaStzyV1YxWGwsiznbJDz8iShzWxyl1LPTLKu2Jl3lNfKUDTDoSNn9quzGv4u88MiolX/YGYcRltR2CT6sbDoMubNQuLMZ4mG/6HFIYn4BgGuRUxoAAIgAAIgAAIgYGcCxr8I7Nw5urMfgaoq/kJ+xnx9+cu3FfPz4zfaZ6yykt+Oa8xe/Wi6xCIIgAAIgICLE1BFPe0wX+HwWm2Ov0N55XQeV/v9H4uAsaH+VFbN4o0VW70/36ECoHifF1eymKSxuenJhjUf9gZ0VdPnAJRxSiGQMGoSV03GHdOP6JoviX77hOi7B4jK80yaGDaUZlEAT/P5G9x8WmHYbLQg2m1T3TDD5hRekkkxF9LN1CHZNBfR0ZJIalMHDmoU0ZMrq71LlDDEQSdAtyAAAiAAAiAAAiDQfgIQANvP0Ck9+Pvzm+UzVlNj/INI3a7Oq6ubQoJkPSDAOOxL3492XT1enVvrR21jaa4PPda3kxDg0aNH6zdjHQRAAARAwAEEQgNMhaevM3JMzpTNoaRf/HqSbprUmwVAyx6AcuCp0uYXUyYd2WGDCGYSNqu18ADrL8C0bTty2d/XVJw0VAK2NDDxwht6OdHAi4gyNxHl7yc6sYVo5+fsSdf877qlw7HdyQRCOR1L0iiiHhP4vl1B5Gc9OsPJo8PpQAAEQAAEQAAEQMCEAARAEySuuSEkpDnMSh/Wqx+xtmCHPlxY3481AdBaP/pz6tdbylOob491EAABEAABxxEI4qqqEinLqegMdvK0sYe4uuOpFXsVAdBcERC1jcyNQki1O+y0fLrC1AMxLNBUyLTT6ezajeQq9GLgkvtPtYoaDqW1xSQ3Xc+zm6b064imLuJCE68QbX6DQ2w5L56bWkOjBxVSCOU3hlFBYyjlsz9kSWMg+Xg0kmdjHc95onr+z5NmTEgnn9D4prDkJTe0fMW+LL4FxXAuv1gOkU4giurNghzn+vPkr7kyScEVCSOu5NDhak6pItV7RVSV8GVZL2UxXPar4czKnPfpzS+MqPdkIinuIcKfiLYwEAABEAABEAABEHATAhAA3eRGaQW1lgpsaL3v9Ln49P1ER0dbJKD248FfcLXHWTwAO0AABEAABFySgDzHxQvQnKhmacAtCYAVnNPOkaYfq2gtIWaq/zpyDG3tW3hLGLC2kEqbqyeHxBH97mGiSX8hKjhANbkHafHHS2m0x17q7ZlFcR5NomCjhxdVNXgp+QCryZcqGv24vkUgFVZxARIuriFTSWMQnWiMpkryo3gO8754eLcmDUty9UlePcnzJ7nsRIRU555eLJaxeKnk9hPhjNvKzfDhohpKO26rFNPgiAMpsCHHsei2M6eSHvlqP5VxWY8CFv1E/GtgcW94Sjj9qqvsrOUsXc+eNqNZXOs7jWjdi5zzj0U6EfekkEegTPz9JSypqcKuX/NLUm1f7VrmEHSlgIgqCkpnARHN42pX5zgYBEAABEAABEAABJxPAAKg85m36YwDBgwwHLd3717DsrkF7f7+/fsbNdH3M2zYMKP92hW1HxERtYVFtG2wDAIgAAIg4B4EJA+gXlSzNnKteGWuXYshreYO4m3VdfW0aNluWnMgj8b1jqJHZw+iAPZQ1FtxpbEHYBgLmK5Y8EM/bnXdXycAVtZw4Yz2mDeHP3Pl4CONKfRcXfPXNw+W1TIemcZObl40aNG3JLqVwaxlDGG9L4xDWH/XnwVGB9jqEwdpK3v9aW1ocjh9dMNYOuefq8iSB6oIpyKgGkxEt989ZFh12oKMQQRRmWAgAAIgAAIgAAIg0AkImCap6QQX1RkvoWfPnpSYmKhc2qpVq6xe4urVq5X93bp1ox49ehi1nTCBQ1bOmLV+cnJyaP/+/UrL8ePHq4dgDgIgAAIg4KYE9JWAW7qMsir2+rJibfVo+2zrCfpw03E6UVRJn2w5QZ9uzTR7Fn0BEBEA3ckCdaKmzSHALVzk4TwOVdVYbGgABQf4URB7R/aOaV0euqe/3Ud19Q1UVF7D+RbbKVBqxiSLxwu4YIfOXv7DCPLz9qIrxxjKkehasGOfjptJA2wAARAAARAAARAAARBoEwEIgG3C5vyD5G34hRdeqJxYPPM2bNhgdhCyXfXck/ZGb9H5iL59+5LqFfjJJ59QRYXpF3Tp+O2335aZYhdffLG6iDkIgAAIgICbEjBXCdjSpZRW1XKFYOsC4BIuFvLtrhz2ONO6nFnqsXn7/325u3mFl/7JIpQ503sAhruZAKivBNxWj0k9m0M6AbBXdLPod/5AzptnxmQsb81Lp2fnDDXauzenlFIfWEHDH/ueZj6/xqJXntFBNqxkF1fSR5uNhd17z+9HieFNhcmum9CTUiI5hNiMieckDARAAARAAARAAARAwP4EIADan6nDevzzn/9MXl5NX4xvu+02qqw0TuAu67JdzNvbm6S9Obv77ruVzYWFhXTvvfeaNDl06BA9+eSTyvbU1FSCAGiCCBtAAARAwO0ItEYAPJpfYVIF2MdLE5Z55upvfG8r3fXpjlaJgNV1xp5mJWY8DcUj7Xih8Qsqc5WMXfkmBPs3h+nKOEt0Ic1tHbuIdlpLjW0WAC8a3hQpoN0fwYVTPrh+DE1Ji6ULh3WjtHjz+fL2nyqjt345oj20TcviGXrp4nUmx/aICjJsE5Fv0ezm1CaGHbwAD0AtDSyDAAiAAAiAAAiAgP0IGH87tV+/6ElH4JdffqGDBw8atubn5xuWZbvW4052zJs3z7BfXRDvvXvuuYeeeuop2rJlC0lo7n333Ue9e/cmEe3+/ve/06+//qo0l3Z9+vRRDzWaX3PNNfTmm2/S2rVr6aWXXiIJ973++uspIiKCNm3aRI899hiVlJRwriVPev755xUx0agDrIAACIAACLgdgdaEAF/w4i8m1xcT7EdZxVUm27/YdpK6sWfXXdP60amSKgph4SvQ1/zXi0oLhUPu/Hg7/W9HFvWMDiIJ9d12vMg4lx2fNTyQc+C5kUUFGY83r8xaQj7bL0wvAPZP4MIbZyw1NoQuGdGN5J6IiTj4ytUjDaHBUpn4nvP60XXvbDlzhPEs42Sx8YZWrJ2uqKG31x2lxSsPUY2ZcGK9x985aXE0lfMP/rDnVCvOgqYgAAIgAAIgAAIgAAJtJWD+G3pbe8NxFgm8/vrr9M4775jdL0KcTFozJwDK/scff5xyc3MVAU/Evrlz52oPU5avu+46+tvf/mayXd0gXoRLly6lGTNm0ObNm+nzzz9XJnW/zP38/OjFF1+k6dOnazdjGQRAAARAwE0JWPIAFFGovqHlMN7oEPMCoOB44aeDyiTLIgCK6DSuN1dp1dn+U8bea+ruLzicWOxgrnF+O3W/zMMC3Osri/DSWkFZtXa1TcviXafPAZiWYOzR9+Qlg2nm4ATO6ddIk/vFkD6k9hz2BJyQGk2/HGx+EakOZseJporC6rqtcykYM/P5X6yGEHePMg35fXjWABMBUDwRYSAAAiAAAiAAAiAAAvYngBBg+zN1aI/ilffGG2/QV199peQElMIgvr6+SoEQyfn39ddfk4iN0s6aRUdH07p162jx4sUkhUGioqLI39+fevXqpXgDbt26lebPn2+tC+wDARAAARBwIwIi9Olt0QUDaOVdk+nsPqZinb5tNHsA2mKlHNL73PcHzDbdcLjA7HZbNka6mQdgtM4DMN8OAuCurGLSa7X94owFQCmyIZV9zx8UbyL+CWfJDfwSF+OQPHx6EyG44cwJlv+WRU+t2Et7skv0zUzWl2w7YVX86x0TxMKwj8lxKSwK6kN+p/aPNWmHDSAAAiAAAiAAAiAAAu0n4F6v09t/vR3Wg4T46sN82zMY8d6TqT0meQJvvvlmZWpPPzgWBEAABEDA9QmYqxA7d3SKIhK9d90Y2se55V5bc5j+t/2k4j2mvyIJAbbV9uaYikZSLORjXWEIW/uTduewqOVOZuoB2L4QYBHnHv9qjxEC8aqT6r+tNQmzfoi9764/uxeNffJHw+HiNXg353RUPTJlx+v8mVh97xRDAY/vuPCLCIPenBPy3vPSaOqAOJKCMJYsOthXOZel/a9fM4qufG2jYffYXlGGZSyAAAiAAAiAAAiAAAjYj0DrvzXa79zoCQRAAARAAARAwEkEzmOPsH98u5fyORedeAO+zF5g2vDQflwc4p+/H8qiTj/674Zj9DyH9armze3HpUbRx1uMK7uq+/VzKewh4ara/jceKaTD+eX6phbXh6eEcxhxFBXweKcNjKNhyeEW27rijqggY8G0vR6A73B+vW3HjUN0pahHeyyWw5R9vTyNcvZpxT/pu46Fx68zsmk+i4Wr9ufRTf/davBCvP69Lew9GmMyrmf4cyS5COVYES61nwP9eCVU/PkrhtOXnANS7vGfxpt6JuqPwToIgAAIgAAIgAAIgEDrCUAAbD0zHAECIAACIAACbkdAvL5+vHMyrdyXS305bHRAYnPxCO3FxIb6051c0OPqs3rQ/V/8xqGdVXTTpF6kL+KgPcbcsngU+vl4klR/FQHow03HzTWzuO3BmQNoZPcIi/tdfYd4vmlNhMxyzpX30sqDSoXjq8Z2J1u93Y4XVNDT3+7TdsdcA+nmSb2NtrV2xZOF3YRwfzrG/VszuZdij3+12yD+yTo7ddJqFgW1JsVPZg9LVEKNpXI03/oWbfbQRJIJBgIgAAIgAAIgAAIg4DgCEAAdxxY9gwAIgAAIgIBLEQgL9KGLhtvmNRbD3mGvX5NuGL+5sF7DTjMLF760VtkawiGqD87qTysycoxa3cTiVS1Xi5XiGEu3Zxntk5X+uuIWJg1cfEOULmS6lMW/R7/cRZ9sOaGMXKrfrrx7MiWEBbR4Jc98v48q2aNSa3+/dAgF+NqgrmkPMrOcyOdvSQCsqmtQKjzbUqDjz+f2ZdHPeh5iM8PAJhAAARAAARAAARAAAQcTwDc0BwNG9yAAAiAAAiDQGQgE+rTtnaEIX/d9nmEUZiphpzdO7KXkhntu7nCzeAJ923Y+s511wEZzORNV8U+GU1XboIRatzS0Tzns+n86gfSqsSk0xk658kb3jGxpCJRbUkW/Hi9qsd1A9ir9A+eVhIEACIAACIAACIAACLgeAQiArndPMCIQAAEQAAEQcDkC/r72+8owfXA8RWiq5AbpPNl8ve13ro4CGRrgTS1dx5c7sq0Ob+uxQrrns99M2tw6pY/JtrZuuJZz7s0cnMAhu5Z7yCutZgHQOP+gtPbT3aeFv+tDElYMAwEQAAEQAAEQAAEQcD0C7v8N2/WYYkQgAAIgAAIg0OkIBNiSzM3Gq75C5yV2B4eNau2xCwdqV91y2YMVNfGIs2Y5xVVUXWcc2qu2P8Ved5e+vF5dNcwl9198mL9hvb0LEhb+EheE2fzAVHp2zlD6w5gUGt3D2CswlwXADYcLjE618JxU+uTGs2gEF2sJ5z5uZ/FvGlcEhoEACIAACIAACIAACLgmAfeOr3FNphgVCIAACIAACHQ6ApYEQKnUu+6QsThk7eJ7RQfRGF3YqQiCu7NKFJFpclosXTw8yVoXbrNPwmvNec6pF1DDORC3HiviasfRVFxRS9X19RQb4k8NXDl3/jtb1GZG8wl9oo3W7bUSzTkLLxmRpEyH88ronGdWGbou4zDuHSeKDeuykM7XNpSr9n6xYDwXA2lUin4YNcAKCIAACIAACIAACICASxGAAOhStwODAQEQAAEQAAHXJOBtobDDm/PSlVx2H2w8Tofzyw2DF0+1bMXDrcGwTRZE7BPvOK0FcaGQZy8fpt3UKZZF6Hxl1WGr17LmQD7t5yq7jy7fTULlnvPSaFLfGMo4aSy4qZ3MG9dDXXTYXCpBWzOpKK2tYKy/n9aOxT4QAAEQAAEQAAEQAIGOIYAQ4I7hjrOCAAiAAAiAgNsTOJu90fw5NHj+2b3omz9PpAuHJXIFWA8a1T2C3r9+LEmlX631iQ2mq8Z2127q1MvpHEor4bHW7OWfD9GiL3ezFx0RO/7RM9/toxU7zecG/P6OiZQaG2KtO7vsk5yMljw+5QRT+8eh0q9dSKMTEAABEAABEAABEHAeAQiAzmONM4EACIAACICAWxMYnxplGL83F3tYNLs5V58UvPg3V/Q98PgM+uzmcdQtPIBumZJKM4ckKMUiJveLoXevG00BuoIfhg474UKIvw/9iz0b+8YF23x1dawCvvDTQZP2c0YlUZ84x4t/cmLx6BtgJX/hSBZ4YSAAAiAAAiAAAiAAAu5FACHA7nW/MFoQAAEQAAEQ6DACj104iP7yeQbll1XTrVwEoneMdWFLRMGXrhyh5LTrqtVhp/SLJZmqauvpRFEllXM+ves4v58wtNWig33pwVkDbG1ul3Y3TOxFN7631WxfrRE0zXaAjSAAAiAAAiAAAiAAAk4nAAHQ6chxQhAAARAAARBwTwK9WPD75KazWj34rir+aUFJqHQqh0CL3TWtL93/RYZ2t9Xlj244i0LZm9CZJhV9J6RG0y8H801O6yxPRJMTYwMIgAAIgAAIgAAIgECbCSAEuM3ocCAIgAAIgAAIgAAItJ7AnFHJXG23G4fatnxsZJAve1oGtdzQzi0kDPjhC0y9DsWrU4qAwEAABEAABEAABEAABNyLADwA3et+YbQgAAIgAAIgAAJuTsCL8yc+O2cYPco5FOvqG8nPx5MGPPyt2auSgiodVWW3L+cclKrDb687ahjbZK5QDAMBEAABEAABEAABEHA/AvAAdL97hhGDAAiAAAiAAAh0AgJSJCSCPfwCfb0piufmTCoJd6TdyeHKI1LClSGI558UdoGBAAiAAAiAAAiAAAi4HwF4ALrfPcOIQQAEQAAEQAAEOhmBbhEBVFBeY3JVo3p0bMVdyT0oOQiPFZRTbKg/wn9N7hA2gAAIgAAIgAAIgIB7EIAHoHvcJ4wSBEAABEAABECgExPoFh5gcnX+HBo8MDHMZLuzN0jePyn8gdx/ziaP84EACIAACIAACICA/QhAALQfS/QEAiAAAiAAAiAAAm0iYE4AHJ4cQSK+wUAABEAABEAABEAABECgvQTwrbK9BHE8CIAACIAACIAACLSTQHJkoEkPE/pEm2zDBhAAARAAARAAARAAARBoCwEIgG2hhmNAAARAAARAAARAwI4Epg6IIz+Nt1865/7741nd7XgGdAUCIAACIAACIAACINCVCaAISFe++7h2EAABEAABEAABlyAgIcBfLBhHX/2WTX05396sIQnk7YX3tC5xczAIEAABEAABEAABEOgEBCAAdoKbiEsAARAAARAAARBwfwJS8MMVin64P0lcAQiAAAiAAAiAAAiAgJ4AXi3riWAdBEAABEAABEAABEAABEAABEAABEAABEAABDoRAQiAnehm4lJAAARAAARAAARAAARAAARAAARAAARAAARAQE8AAqCeCNZBAARAAARAAARAAARAAARAAARAAARAAARAoBMRgADYiW4mLgUEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAE9AQgAOqJYB0EQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEOhEBCICd6GbiUkAABEAABEAABEAABEAABEAABEAABEAABEBATwACoJ4I1kEABEAABEAABEAABEAABEAABEAABEAABECgExGAANiJbiYuBQRAAARAAARAAARAAARAAARAAARAAARAAAT0BLz1G7AOAs4gUFdXZzhNdna2YRkLIAACIAACIAACIAACIAACIAACIAAC9iOg/c2t/S1uvzOgJ3cgAAHQHe5SJxxjXl6e4apGjx5tWMYCCIAACIAACIAACIAACIAACIAACICAYwjIb/EePXo4pnP06tIEEALs0rcHgwMBEAABEAABEAABEAABEAABEAABEAABEACB9hHwaGRrXxc4GgRaT6CqqooyMjKUA2NiYsjb27WdUcVlWvVU3LRpEyUkJLT+onGEXQjgXtgFo107wT2xK067dIZ7YheMdusE98NuKO3WEe6J3VDarSPcE7uhbHdHuBftRuiQDnBfHIK1XZ260z2RsF81Cm/w4MHk7+/frmvHwe5JwLVVF/dkilHbQEAeOOnp6Ta0dL0mIv4lJSW53sC64IhwL1zvpuOe4J64HgHXGhH+RlzrfshocE9wT1yPgOuMCH8frnMvtCPBfdHScI1ld7gnCPt1jc9KR44CIcAdSR/nBgEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEHE4AA6GDA6B4EQAAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEOpIABMCOpI9zgwAIgAAIgAAIgAAIgAAIgAAIgAAIgAAIgICDCUAAdDBgdA8CIAACIAACIAACIAACIAACIAACIAACIAACHUkAAmBH0se5QQAEQAAEQAAEQAAEQAAEQAAEQAAEQAAEQMDBBCAAOhgwugcBEAABEAABEAABEAABEAABEAABEAABEACBjiQAAbAj6ePcIAACIAACIAACIAACIAACIAACIAACIAACIOBgAh6NbA4+B7oHARAAARAAARAAARAAARAAARAAARAAARAAARDoIALwAOwg8DgtCIAACIAACIAACIAACIAACIAACIAACIAACDiDAARAZ1DGOUAABEAABEAABEAABEAABEAABEAABEAABECggwhAAOwg8DgtCIAACIAACIAACIAACIAACIAACIAACIAACDiDAARAZ1DGOUAABEAABEAABEAABEAABEAABEAABEAABECggwhAAOwg8DgtCIAACIAACIAACIAACIAACIAACIAACIAACDiDAARAZ1DGOUAABEAABEAABEAABEAABEAABEAABEAABECggwhAAOwg8DgtCIAACIAACIAACIAACIAACIAACIAACIAACDiDAARAZ1DGOUAABEAABEAABEAABEAABEAABEAABEAABECggwhAAOwg8DgtCIAACIAACIAACIAACIAACIAACIAACIAACDiDAARAZ1DGOUAABEAABEAABEAABEAABEAABEAABEAABECggwhAAOwg8DgtCIAACIAACIAACIAACIAACIAACIAACIAACDiDAARAZ1DGOUAABAwEqqurDctYAAEQAAF3IIDnljvcJYwRBEBASwDPLS0NLIMACIAACAgBCID4HHR6Ao2NjZ3+Gt3hAk+fPk1XXnmlMrnDeDFGEOhIAnhudST95nPjudXMAksg0BIBPLdaIuSc/XhuOYczzuL+BPDMcv97iCtoPQEIgK1nhiPchMDSpUvdZKSdf5j/+te/KDExkT766CNasmQJ7d69u/NfNK4QBNpAAM+tNkBz0CF4bjkILLrtdATw3HKdW4rnluvcC4zEdQngmeW69wYjczwBb8efAmcAAecSWL58Od1xxx106NAh+vbbb+ncc8+luro68vbGx925d4JoxYoVyr3Yv3+/curzzjuPbr75ZurTp4+zh4LzmSHw5ZdfUl5eHpWXl9OgQYNowIABFBcXp7RsaGggT0+8IzKDzSGb8NxyCNY2dYrnVpuwOe0gPLechrrFE+G51SIipzXAc8tpqFt9IjyzWo3MYQfgmeUwtOjYnQiw6ysMBDoFARYyGu+8885GDw8PwzRkyBDDtbGgYVjGgmMJ7N27t3HmzJmG+9CvX7/GV199tbGwsNCxJ0bvNhH45ptvGkeNGqXcn8DAQGXOYl9jWlpa46OPPtrIgrlN/aBR+wngudV+hvbqAc8te5F0TD94bjmGa1t6xXOrLdQccwyeW47hao9e8cyyB0X79IFnln04opfOQYA6x2XgKroqAVXUy8zMbLz33nsbY2JiGr28vBrDw8Mb/fz8FGFj8eLFCp7a2tquislp182eZI3s4WcQ/kJCQhofeOCBxsOHDzttDDiRZQL5+fmNt956q+H+dO/evXHixImNgwcPbvT39zdsnz9/fuOOHTuUjtS/Mcu9Yk9rCahM8dxqLTnHtMdzyzFc7dUrnlv2Itm+fvDcah8/ex+N55a9idqvPzyz7MeyPT3hmdUeeji2MxOAANiZ724XuTbxVhLPP1XAEG+z2267rTEpKUkRNEJDQxvli5JYfX19F6Hi/MssLS1tvOyyywwi0qxZsxr37NnTWFVVZTQY9R9kdW60EysOJfDCCy80yt9DQEBA4z333NO4c+fOxuzsbOWcHD7UOGfOHOX++fj4NMr94zB6ZR/+bux/W/Dcsj/TtvSI51ZbqDn3GDy3nMvb2tnw3LJGx3n78NxyHuu2nAnPrLZQc8wxeGY5hit6dW8CEADd+/5h9Exg2bJlBvFv0qRJBtFi3rx5jUFBQYqgsXDhQoUVhAzHfmTeeOONxr59+yrML7roIqOTCXvwN0Li1JUNGzY0RkZGKvfm2muvbZQ31Ho7ePBg4+TJk5U2vr6+jZdeeqm+CdbtRADPLTuBtEM3eG7ZAaKDusBzy0Fg29gtnlttBOeAw/DccgBUO3SJZ5YdINqxCzyz7AgTXXUaAl6L2NwpZyHGCgJ6AvHx8cRiBo0cOZL+8Y9/UK9evZQmCQkJtHLlSiooKKBNmzbR5ZdfThwiTCxCobiBHmI71/mJSJx7kVJTUykj4//bOxP4r6b8/5+/JSFDCkOKZC1lHUu2SFmjkLF7MEJlTKkZ22BIikw1jG0sU7ay75qyVtIgCpWdohAZa4iZx/mf9/E793s/n+/9rPfez+d8P5/nfTy+37ud7T5f97w/977vWV5XZkwaNW/ePLXtttsqM66c+uGHH5RxKNkwZhwONW3aNLVo0SI1Z84cZVqbKeOYilkCohcicM8996iHHnpISX0ZN26catOmTRDF6Sc6tG3bVt12223KtNBUpgWn2njjja2OLkwQiY1YBLBbsfAlEtnd09itRHCmkgh2KxWsZSeK3SobXWIRsVuJoUwlIWxWKljLThSbVTY6ItYyAfNDwgIBrwm4rqJRrcfcORkE+Z133ml0HTL+nIwHKBODmBloG53nQGkEHO98WkyZMkVvs802lrlxygat/pYvX66HDx+uzQzAQfdsN2FL3759tcRjSYeA6HXooYdaTYS/6/YblZtxmOsDDjjAhhV9zMOTNs7aqKAcy0OgmLqC3coDMMFTxWiB3UoQeEJJYbcSAllCMsXUFexWCUBjBC1GC+xWDMApRMVmpQC1QJLF1BNsVgGInK47ArQArGXvbo1cmzHutsWetDBzi6mptjWZO9a6deuMVmQSR86Z8QDVU089pT799FNlujfaVoKmi6oyY0LQCtDBLGFdjBYdOnRQCxYsUGZ8Obtu1aqVMhOzKNO1VN1///3KzARsW5eJBmaSEPXTTz+p+fPnq8mTJyszKYVtRbjSSiuVUCqCuvrg7vswETlnZvhVZjY6ZSb2UFJXBg8erPIxvvfee5VxqNtWm998842tSz179rS6uToXzoPtxgSKqSvYrcbc0jhSjBbYrTTI508Tu5WfTzXOFlNXsFuVUaYYLbBbldHC5YLNciT8WRdTT7BZ/uhFSfwggAPQDx0oRQQBcVZceeWV6tFHH7VdEs2MmdZpIV0XCzkh5Lz8UJsJD2yXXzMmh/r+++9tV2AzHqB1iLgf8oisOZRFoFgt5IdY2K+77rpq9uzZauHCheqFF15QEydOVIsXL1bbbbedOuecc9Txxx+vhg4dqn7zm9/YLtpff/21dQyK41C6aXfs2DGrBOzmI1DoAUicrTNnzrRdrpcsWaLMrL+qU6dOkd3hpUv2rbfeqswEINapLvVG4pqZgdWaa65p61Wh+pevrLV+rti6EsUBuxVFpfxjxWqB3SqfcZyY2K049JKNW2xdicoVuxVFpfxjxWqB3SqfcbkxsVnlkks+XrH1JCpnbFYUFY7VFQHjBGGBgFcEpAviqaeeGnRBNIY62JYZTMeMGaONo8iWWWZ3yrWYH2p7SmahlRlN3SzBxqlYMG6uNOvteBwtRCfpPir6GceRnXX2ww8/DLoEO5bGMagvu+yyQGPpDmycve406zwEzBiKesiQIXrgwIH6qKOO0qNHj9ZmvMuMGK679h133KFNi0vL2YzNqF39kLWEcXVp6tSp2rQYtJOBmHEzg3pjWg1mpMtOJoE4dSWcktMFuxWmUtp2HC2wW6WxLic0dqscaunEiVNXwiXCboVplLcdRwvsVnnMi42FzSqWVPrh4tSTcOmwWWEabNcbAWYBrjfFPb9eGadh7733znAGHXbYYdp0P9Ti/BNnkqy7d++uTauxglfjnB+PPfaYNt1LbfxVVllFm26oNq47XzChOgxQrhbOkSSOvT59+uhVV11Vn3322dq0PMugGGZvuplaJ63oayZx0XfddVdGWHYyCZTyAGS6WAeR99xzz6BuiUPvs88+C87JhjjWDzroIBvGtALUMiuwaCIOwa5duzIWYAathp1y60pDCplbrm5gtzK5FLNXrhbYrWLoxguD3YrHL+nY5daVXOXAbuUiU/h4uVpgtwqzjRMCmxWHXvJxy60nuUqCzcpFhuO1TgAHYK0r3MSu76KLLtKmC6Ju3769vu+++/RXX30VXIGZ0Vd36dIlcGAce+yxRTkBXQL9+vXTLVq0sPFNd0Z72Bl/F4Z1A4E4Wrgva7fccos+77zzitJp0qRJ1tEkDqeRI0fagrh0GkrFVjkPQD///LMF9+STT9pJWISx/Jku2Priiy/W1157rT733HO1GavRHjddhLWZAdjGEQe8hDVdhvVbb72FABEE4tSViOQyDmG3MnAU3ImjhbM32K2CmEsOgN0qGVnqEeLUlUKFw24VIpR5Po4W2K1MlkntYbOSIplcOnHqSaFSYLMKEeJ8LRHAAVhLajbxa5EfWzNQq3U2SJfGZcuWBVfkHHUvv/yy3muvvWwYcUqMGDFCL1261IZzD0FBpP/bcF9IzXgR1onhnB+vvPKKDRFuIeXyyU6j3vbjauEcTo698Mulj2MresgMtaLPvvvu6w6zziIQ9wFInBvi+HP1QNbSKtbt9+7dW5uxG4Ncb7vttsAxO2PGjOA4G78QiFtXctULV3ewW8XfaXG1wG4Vz7rUkNitUomlGz5uXcFuJadPXC2wW8lpEU4JmxWmUf3tuPUEm1V9DSmBPwRwAPqjRd2WxBllM0upbf0nrZCktV+uxUwKonfffXfrsDAzoOkJEybkCtro+LBhw/Taa69t40oabpGX7Xnz5mkpg3Rdrdelklo4xi5PM1OzNhOAWG2OO+44e9qdc2HrfV3MA5A4UnM5yYWfOLnNDL/6mGOOsd3iN9xwQ922bVtbp8wszdpM+mExOweUjB1oZgy2XbmnTJlS7xIE1+/uTexWgKRqG5XUwl2kyxO75YjkXmO3crOp9Bl332K3Kk2+cX6V1MLl7vLEbjki0WtsVjSXahx19yw2qxr0ybNWCeAArFVlm+B13Xjjjdb5Y2aQ1XPnzm3UYsz9CMjg+OKUcGMCyjhzMkCvLC5M9uW7ln0y5pk4/qSbsbR4krHm5OuppHfooYfqtdZaS19xxRVa8qjnJU0tcnF9+umntWgvusiXV5YGAu6+TuIByLUWkNQ///xz24L29ddfb8js/7ZcnTGzOAddg2fNmtUoXL0fSLOuOA2wW8XdZWlqkasE2K1cZBp+j7FbuRlV60yadQW7VZqqaWqRqyTYrWgyPGtFc/HhaJr1BJvlg8KUoZIEVqirKY+5WK8JmFZIykwYoYxTQpkWSso4gpT5MQ7KLPuymO6KqkePHurEE0+0++ZBRpmxzZTpymvj2INZ/8wkBsoYeGVamKnTTjtNma7GNoTpaqwGDRqkhg4dqh5++GFlJhZRZkIKJeHreUlTiyiuovnYsWOt9nLeTEQRFaxuj7l738yirEzLPNWqVSt7L5sfiwwmbt90oVb9+/dXZtZf9f7776u7775bma6kNqxpYRvEkXTkb+utt7bHpI7IIum4OiB1S+qhmUTH5mkD8C8gkGZdwW4FmIvaSFOLqAJgt6KoNBzDbjWw8G0rzbqC3SpN7TS1iCoJdiuKyi/HsFm52VT7TJr1BJtVbXXJv9IE6tvLUWna5JeXwPLly63jwXQ3VE888USGEyI7ojjyTjjhBGW6AFuH3eTJk5Vpsp8dLNgXh4ZzfJgWg2rLLbdUzZo1U2Y2YGUmQFCmO4R1gpgujsp0E1amhWAQtx430tQi7NQVtl9++aUaP368evbZZ9Waa66pzLiOyoxRV4/YC15zu3btEnWSu4ddl7GrI+64mRVY3XvvvfZ0t27dlOTPkkkgzbqC3cpkXWgvTS2wW4Xo5z6P3crNplpn0qwr2K3SVE1TC+xWaVq40NgsR8KfdZr1BJvlj86UpDIEcABWhjO5FEFAWn1Jyzxp4SStlswspHljiRNPnICySCvA1157LWd4cWiIgTezmKoHHnjAOg2lxaAcW2211dTVV19t40vLKZZfWuClpYV8aRPuplujmj59ujrzzDPVn/70J/Xtt9/aln99+/ZFghwE0nwAcq3/XNZLlixR119/vTLd623Lv5NPPtmdYh0igN0KwajyZppaYLfKFxe7VT67tGKmWVd43ipNtTS1wG6VpoULjc1yJPxZp1lPsFn+6ExJKkTAvIizQKDqBNz4CzL2mzHEdny/iRMn2gkL8hXOOJB0586dbZxevXrZoOaLZ6MopluvnSxEJpdYffXVbXjJZ8CAAVrOsTQQSEsL4fzee+/pcePG6XPOOUcfccQRukWLFoEW559/fjABRUNp2AoTkIk5TDcIy2z//fe3E9eEz2dvG6eqvuSSS2x4mVxHZvTNt4j2ixYt0lOnTrWThEgdkfEyL7vssnzR6vZcWnXFAcVuORKF12lpgd0qzL5QCOxWIUKVPZ9WXXFXgd1yJAqv09ICu1WYfb4Q2Kx8dCp/Lq164q4Em+VIsK4XAtIShwUC3hAw443pTTbZxDosxEFUaEZeGRzftAK04c2XTjt5iFxMthPQjJ2md955ZxtOnBr77bdfQeeJN1CqVJCktfjuu++0zMIs/N2fOKVMiz9tWntW6SqbTrZpPgC5h5+DDz5YH3jggRmO2UsvvbTuJ8UpdJckXVdcftgtR6L4ddJaYLeKZx8VErsVRSWZY2b4jFgJJV1XXGHq0W75pgV2y92Npa+xWaUzq1QMbFalSJNPrROgC3CFWlrWejYyht67775rL9P8eJZ9uR07dlQ9e/a08e+77z7btdfMWpozPRkLUOLIIuPHzZ49224bB5Ndu3/SnXXPPfe0XRkffPBBZWYlDOK5MLWy9lUL0/JSde3aVZmWmso4mezkKzLun0xQId25WfITkK48suyxxx6qffv2tsu0jM8neudbtthiC7XddtvZII899piaN2+enSzH/LgF0WTynWeeeUbJ+UmTJtlJP4wDXs2fP1+Zlpl24p0gcA1tmJckO9yAjAUqS5hJKZeJ3SqFVnRYX7XAbkXrVexR7FaxpIoP99FHH6kDDjjATmgmz1vYreLZJR3SVy2wW0p99dVXZcmNzSoLW9GRsselLDqiCcizVim0CAuBPARq3cPJ9aVLQL6UXXjhhVpa3+29996JZHb//ffrTp062VZiu+66qzazl0am677Smck/ghZlxplkw2a3AJSDcb/QRhbCo4M+a+H0kPUnn3xiu5l6hK4iRZHrNrNb27yke0m5y8cff6xPP/304J6Xbr1mPMu8yY0cOdKGb9myZaNuwK4eST0bPXq0lrAzZ87Mm15TPyn34XXXXafNS7Q2DlU9ZMgQvWzZsliXhd0qD5/PWmC3tJZhBGTohi+++MIK7JiUqjZ2q1RijcOLrb7gggsC29+8eXP7eyohy9UFu9WYczFHfNbC3QuyrsfnLWmBKkOkHHnkkVqetRyPYnQNh8FmhWmUty3szfjs2jQQ0WY86YxE3LNnxsEidrBZRUAiCAQKEKALcAFAnM5N4M4779QbbLBB8DB60kkn6aVLl+aOUOCM+5GWF41zzz1XS/dQ6Sp61lln6YULF9rYLkw4qRdffFGbFn427FVXXRU+VTfbaOGv1PKQ01Sc5IUcif5SLr5kpmWxNi0oA7slHy/MrNN61qxZxScSCulsEnYrBKXITbQoElQVgsl93VSc5PVgt7J/42VsVvmgIy/D5SzYrXKo/RIHLcpnl2ZMn52y2dddDzbL9FDR3bp1sw06TC8TvdZaa2kZZubmm2/OxlHUPjarKEwEgkBRBHAAFoWJQGEC8qIsrWbcOG477LCDvuOOOxKdTOOll17SMqmH5LHeeuvZiQxcqym3dmV64okntPy4rLTSSvq5555zh+tijRZ+y5z9ooCTvHp6iYNu0KBBgd3q0qWLHjFihJbJht5+++1ECobdKg4jWhTHqVqhcMxWi3zjfKN+40899VRrx+SZ55577rGRym1NI5GxW425Rx1BiygqfhzLftbCQV49XaTFX/fu3YNnLWmp7N4X3Vp+Y5xDr5ySYrPKoUYcCDQQwAHYwIKtAgQ+//xzffLJJweGfN1117Uv0IUm6iiQrD0tX8OkK+/XX39t98XJJ4O9rr/++jY/yStqJlLp3iCTFsiPinQblhlM4/yoFFNWH8KghQ8q5C5D1IsCTvLcvCpx5vbbb9dmzFC9xhpr2BbG0qrYjC8aZF2O3cBuBfhK2kCLknBVLDCO2YqhLphRvt94M16rbtOmjX3uOeOMMwqmlR0Au5VNJP8+WuTnU82zUc9aOMgrr4g8P8mffFDdcMMNrW2S5y3pwfWPf/xD33LLLbb1X4sWLey5bbbZRktX7WIXbFaxpAgHgeII4AAsjlPdh5IuudLKzn296d+/f86x+UqFJTPAykNss2bN9E033ZTxUi4/JtJFz+X7u9/9Tk+fPt2OJfH8889rKYd0FRYH4YQJE0rNukmGRwt/Zcv3ohC31DwAlU9Qvkivvfba1o4MHDhQm4lTMhLLblWccTLHDnYrB5gCh9GiAKAqnsYxW0X4oawvv/xy+zzknntkzFepN66Vn9geM8mDfTbq3bu3NpMdhGLn38Ru5eeTfRYtson4sZ/vWQsHeXU0kg9I0vJP3tl23313PW3aNP39998HhZHz8s622mqr2Wcxed+Txdm1IGDWBjYrCwi7EEiAAA7ABCDWQxJuPD75shM1zl62AS+mNY28hI8ZMyb4WiQPu8OGDbOD9oaZShjpZuwehs1sv/pXv/pV8EIvx81MpdrMIhmOVrPbaOGntDhm/dRFSnXttdda+7HjjjvaSQ1cScVOlWq7sFuOXnlrtCiPW9qxcMymTbhw+tIi+eijjw6edWSSoilTpujly5c3irznnnvacHvttZc9X+iZC7vVCGHeA2iRF09VT+KUrSr+nJkPHTo0sF3i3JOP1m5xvS2effZZLcOvyHvbiSee6E5HrrFZkVg4CIFECOAATARj7SbijLYM5ioGW77ciLNNZgaURc67MLIf9RCa/YL9ww8/2NZ64XEE5cVcvhaFFxdP1jILoTwYu8H7pRufDCgrX5vqZdw/xxktwneJP9s4Zv3RIlwSqTeHH364tV8DBgywp8QGhW2VzFAnY9KIDZo3b17gFAyHwW6FqZa3jRblcatELByzlaCcOw9na2688UbbekYGyv/yyy8jI8jHTjcci4wD6MYwdWmEI2G3wjSK23Yc0aI4XpUKJb8fOMgrRbv4fOQdTT5SSKs/af3Xrl274KOFq0vhtXMADh8+PDITbFYkFg5CIFECOAATxVnbiclsTuIElBkzH3300YyLlQfSG264QV966aW6X79++g9/+IMeN26cXrZsWRDOOfRmz55t05G0WrVqlTEjlPxIuHAuotuXbnoyZsTkyZO1NPGfMWOGC1J3a7TwR3Ics/5okask7mPDn//854wgYovkK7TYIvmoIGsZt6ZHjx5azjnbI5GwWxnoyt5Bi7LRpRYRx2xqaItO2L0gSwTp3lhokWcssVcy/Em+mYCxW4VINj6PFo2ZVPuI0wSnbLWVyJ3/9ttvb22S9NiSd7Xw85OLJcMVbLbZZnYGc5nAMWrBZkVR4RgEkiWAAzBZnjWZmnNwzJkzxxp3eeiUQXadc09aDrhBX+VrtJx3f/vss48d10/AuB9w2d53333tWBA//vij7NrF5eP2WTcm4BihRWM2PhzBMeuDCpllkAfOjTbayH6ZDk8kdP3112eMa9qyZUstMwc62yVfqWXw6vCC3QrTKH0bLUpnVqkYOGYrRTpePu6lWj6EOlslM6DK4s5l54DdyiaSzL7jjRbJ8MyXSvj9AQd5PlLVOSe9wk477bTAJj3++OMZ73xSKpnkccSIEVreE88880zb2+Kzzz6LHL4Jm1UdHcm1fgjgAKwfrQteafgHNjuwe9Bxs2vJFxxpvt2nT5/A4G+55ZZ6iy220Ntuu20wyKt7QH344Ydtkm6wfefIkoPh7ex863UfLZqW8u4exjFbed3y1RV3rlevXtZO9ezZ0xZQxtVaZZVV7DE5J8MITJ06VT/00EP244Trzr3ppptmtHZ2Oksi4e3KX7WfOTreUaVz59Aiik51j+GYrTx/Vx/Kzflf//pX8OH1hBNOiEzG2Si3lkDh7chIdXgQLWpHdPeuglM2eU0L1RPpBbbJJpvY56quXbvqRx55xBZCfl8++OADPWrUqGD2cvnguvHGG+tf//rXtseFDMHihpaSSGE7Fd5O/qpIEQL1SQAHYH3qbq9axr0SIz169Gi7n8/Iuh9VGZPGzQYsXU/EwSeta8aOHWu7yLlp3aUJ90knnWRnqpMw4hicP39+QFt+SOTPpRucqNMNtGgawud7AHL3Mk7ydLUspa5ISWQ8Gfna7Foni7Nv0KBB1naNHDmyUWHlK/V5551nz8t4NjvvvHMwmLV8wMBuNSBDiwYWPm/ls1vuHI7ZdBUsta7kKo3TSwbIl8nQ5PnqiCOOyDleoEsHu+VIaI0WDSx83XL3ebnlw0FeLrmGeMXWE6fVkiVL9ODBg21vC7FLzZs3t+MCyofXXXbZxdoq987YuXNn6wCUfflbe+219ZAhQwLHH89aDTqwBYE0COAATIOq52mKo++iiy4KjLFMpuGmandOjKhLcA7CK6+80sYV4y4vDS+++GKjpjx3JRsAACaRSURBVN4SX16kZdB9N7bWOeecY5N1PxZRedTbMbTwW/FiH4DkKlzdwUmejqbl1hUpjcxcLs48+XghD6PylbpNmzbB4PmuZXLYNu20006BnbvuuuvsRYXPp3OVTSNVtPBbp1LsllwJTvL09IxTV3KVyv3W9O7d29ooeZlmKUwALQozqlaIUm1WrnK632gc5LkIFT4ep55IKz55R9xuu+209KTYdddddbNmzaydWn311fWYMWP0F198oUUfeUeUfWkFKE7Atm3b6vHjx9sCOh0Ll5YQEIBAOQRwAJZDrQnHkR/Z8DgNzjknA0rL4h4soy4xbJBloHyZkff555+PdP65dF566SX7wi3GXRyNbuyOcFpRedXDMbTwV+VyH4Akniw4yZPVtty64uyMPGg6WxduNRNVSucMlDFsxG7JuIDSwuabb76JCl53x9DCX8nLtVtyRTjJk9e13LpSTEnEaXvMMcfYls0ynMHMmTOLiVa3YdDCT+nj2KxcV+TeP3CQ5yKU+3hS9UScfIsWLbIOvtVWW832pHj99deDjN2zmRyQMUzlWUschaLZf/7znyAcGxCAQDoEcACmw9XLVMX5dtZZZ9lZ48TYyjh+G2ywgTW8sv/mm2/acrsX4KiLcA4O6UYnf8Us0qxbWgtKHjKDF8svs/yhhZ93QpwHoPBDDU7yZPSNa7ecPRs2bJi1QeGx/wo59Vy3lT333NO2kgrrm8zVNa1U0MJfvcq1W+6exkmerLZx60q+0jjNLr30UmvTZDgWN85yvnj1eg4t/FS+XJtVzNXgIC+GUmaYNOrJ/vvvb23UFVdcYTOT5zFnv8K577bbbjacjCEfdhSGw7ANAQgkRwAHYHIsvU5p+fLldhwsccLJX8eOHfUrr7xiuwJLyzw5Joa61EUMeZQxl3TcVzgZCFbSlzG43KyaueKUmn9TDI8W/qqWxAMQTvLk9E2yrixdujRjzJndd99dL1y4MLKwYrvkQXXgwIHWdknrQemyUs8LWvirfly7hZM8WW2TrCtRJXPPT0899VQwzrLMai6L0zIqXj0eQws/VY9rs/JdlasfOMjzUco8l0Y9eeCBB+zzkwy38oGZBCRqce+JF1xwgQ0r74oyhjwLBCCQLoEVFEtdEDBNq5X5IqZM9zd17LHHqmnTpikzRoM65ZRT1Oabb67MWA3KzJqlHnvsMcvDPEQWxcUYayV/+RbTFFwZ558yhl6ZH2YbtFCcfOk19XNo4aeCP/30kzKtxJQZk0SZh1O11VZbqbvuukv169dPrbnmmrbQZvIIu5b6kmuRe10W80XT/hkTLh9aIoO7+tCtWzdlHsBsPXRh3ToyYp0cTLKutGrVSpkXgoDcjBkzlBm/NNgPb5jxAq0WpguLPSz3gmnFnFPHcNxa3UYLP5VNwm45e9a/f39lJvVSkqYsZjxT+xd15WK75Dd9hx12sKfNS5syrQgLPg9EpVVrx5KsK1Fs3POTrM24pjaIcQbatdMyKl49HkML/1RPwmYVc1Vm/Dllup/a57mPP/7YRhGbxdKYQJL1xD27yrufLKZLb/Du5555XQnkWUuWBQsW2LU8a2eHsSf4BwEIJEvAVFSWGifgvrDMmzfPjsfwxhtv2CuWLz6yyAD3bkZf6RbsFmOE3Was9e9//3v7ZUcGen3nnXdipdXUI6OF3woaZ582DyD6uOOO09JiTJaPPvpIy4QQbhbZRx991B53Lf3sTpn/3P0wbtw4O9aceaHTriVHmUnWTDTHJmm7ddBBBwVfmkXX9957L2AWtnlvvfWWnSxENDn55JODMPW4gRZ+q56k3br99tuD+iH3/j333JP34g899FAbXurSV199lbNHQN5EauhkWnUlCpH8BrlhXI466ii9bNmyuucf5oQWYRp+bSdps3Jd2dNPP61bt25t7VPfvn1zBav742nVk0suucSylx4UrguwwA4/Z8m+PGttuummNmynTp30jz/+KIdZIACBFAnQBThFuNVM2hn07DLIA6JbXBgxtvJS7Mbp++tf/2qDxO1KIg+nEydODBwnffr0sbMNu3xdOWp9net60cIf5Z1GSTubir1CnOS/kHI6ZHNLoq44e/b+++/rrbfeOnC4yovIrFmzgizl4VScv+eff76dOVg+XJjWgsH5etlAC/+VdholbbdwkpemvdMhO1YSdis7Tbcvecqzm0wEIo7aDTfckBdnAwct3B3i59rpk7TNirpaHORRVH455nTIDpGEzXJpz50719omsU977713ZNdeGVpl6NChNtx6662n77333uwisQ8BCKRAAAdgClArnaQMZC+z8c6ZM8f+lZK/M9Sm66/eaKONrBGWQfLdLEzufKE0s1tDyYOpzKIpU8CL8d9nn320vHjX+oIWTUfhXPd2Eg9AxVKoZyd5NeqK0/yhhx4KZic3Xeh0hw4d7Pik48eP1zfffLN2rZrEdl144YU5XyqL1dn3cGjhu0IN5XP3cMORX7aSsFs4ybOpNt6vRl1pXIqGI8cff7x9xmrZsqWeMmVKw4k62EKLpiFymjYrFwHJEwf5L3SqUU9cKz8zzJS1T6aLsTbDRehnn31Wy/iPMtHHpEmTMp61Bg8erM2wE7kk5TgEIJAgARyACcKsRlJXXXWVNuNT6Xbt2tnWKmuvvbY+5JBD9IQJE0oujrSEkaba8tIr27Lk+uHOlbh08X3iiSfs4Pli8CUtadp933335YpSM8fRwl8pq/EAlE0DJ3kDkWrVFfdQKiURWyWz+5pxUa2dElslf66rt6xHjRpVsg1suMqmsYUW/upUDbvlfvNxkje+L6pVVxqXpOHZ7MYbb7R2S+xYPTkA0SLqrqj+sWrYrHxXXc8OcuFS7Xoizj5pneyeq2TIAvnbcsstg14Y9fKsle8+5RwEKk0AB2CliSeU38svv6z32muv4MV1nXXWCQyse5E1ExboDz/80OboHuqjsndf/V999VUt4y+4+DJLsCzZjovsNGSMtL/85S92FmGZWdMMth+kYSYc0YsXL86OUlP7aOG3nNV+AMqmU89Ocl/qinMELlmyxI5x1r17d2u3pGvwtttuqwcMGGDHfszWrpb20cJvNatlt1zdEDo4yX+5R3ypK1F3rJn8I3j2u+2226KC1NQxtPBXzmrZrCgi7p2nXh3kPtQT924pjUKOPPLI4L1Q3jFbtGhhZzA/4YQTgvfUKB05BgEIpEMAB2A6XFNNVQbalgFtxYhusskm+u9//7ttVi0Gf8iQIYETT76qSGtA90NYTKFk0FZpRShpS+uYYhcz46mNY2bc0muttZbNtx7GzUKLYu+Qyofz4QHIXXW9O8mFg491xTk7ZC1j0ZhZTGve8YcWrlb6ufbFbrm6Uc9Ocl/rSvjOlYkO5GPwk08+GT5ck9s+/oaEQdeTFuHr9sVmhcvktuvNQS7X7WM9kfdQcQReeuml+m9/+5u+5pprtDQ6YYEABKpDAAdgdbiXlatz5F199dXW2SYOPpmxT1rouYd1SVgG1918882D5tUXX3xxMKNproxd2vKwL868lVde2eZx99132yjZebh0XOvAF1980Xb7vfLKK/UzzzzjTtfs2vFCCz8l9vEBqF6d5D7WFT/v2vRLhRbpM46Tg492yz1b1JuTnLoS505ONi5aJMszydR8tFnh66snpyz1JKw82xCAQD4COADz0fH0nMymKy309ttvv0YldD8AMqmHzLok4Vq3bq1vuukm/dNPPzUKHz7g4v7zn//UMvOlxJWxG7KXL774InKg1h9++CHDEZkdrxb30cIvVd09jGPWL12kNL7WFf9IpV8itEifcSk5+Gi3Sil/LYelrvijLlr4owU2yx8tskviez1xH5Wyy80+BCBQOQIrmrHb/qJYmgyBTz75RI0ZM0YtXbpUmRl2lTH0yhhTZZx1wTXItpl4Q5nZLdVLL72kTNc29d1339ljZqbfIFzUhsTt3Lmz+ve//60WLFigzIxMasUVV1SmO7Ayjj97/LrrrlOmS6PaYostbB4uHdMiMaMc7nitrtHCP2VdPRg5cqR68803VY8ePdQVV1yhVlhhheDelPqy7rrrKjPzq1q0aJG9z82MZMo4u+29L/d71CJpS1wzdolNz8y8rczMm2rmzJnqrLPOysjDzKKtli9frpo3b26PS3pt2rRRZjZstccee6j27dtHZVGzx3yuKzULPceFoUUOMFU87KPdqiIOb7KmrngjhUILf7SQkmCz/NLDlaYp1BN377gys4YABKpAoHK+RnJKgoB8dZPZk4wBtQPVS5ruS5xL331dkenUhw0bZsMaB4g2TgotrfdkcWFcHLd2g7bKbHIyvqDkI3EnT56spXvv9ttvb4/JAK7G8eGi1eUaLfyU/eOPP9YdO3a096nMACdLuI64e1/WEydO1MYpbsMa55yeNm1a3otycaWeHHbYYdo42W1cqWeyGMe8ljFnzjjjDD127FhtHIF506uXk9QVf5RGC3+0CJcEuxWm4cc2dcUPHaQUaOGPFq4k2CxHwp819cQfLSgJBHwmQBdgT9URIx61yJTq++67r3U6bLXVVnawVwnnHBPZcd5+++1gtuAuXbroSZMmZQfJ2A/nK04McfSJE7Bt27Z2Ldvi9DCtqjLi1fJOmEn4OtEiTMOfbR6AqqcFdaV67LNzRotsIn7vY7eqpw91pXrss3NGi2wi/u5js6qnDfWkeuzJGQK1QGCFKjQ6JMsIAm+88YZ65513bBfbb775RhyzNpRbuyhmPD/VsmVLu2taIanp06fbbeOYc0Ey1tLV8KSTTrLHpJvjs88+q7799tuMMOEd6Sopy48//hh08ZUukdJVUpZTTz1Vma9+6o9//KPdr8V/aNE0VDVO78iCSvdb6c4ri5mQRpmZXW033HBdcvXFzFitfvvb39ou7nLezKSozIQ2Nq4LY3dC/9xx6V584IEHqtVXX93W11NOOcXWi9mzZ9uuvxdeeKHaZZddQjFrb5O64o+maOGPFvlKgt3KR6cy56grleFcTC5oUQyl6obBZlWXv+ROPam+BpQAAjVFwLz0slSRgMyee/jhh2tpzbfeeuvZ7rbSxfeoo47S7733XtCyT1r4ue65jz/+eNAaT2b4NeP75b0CSefggw+2cSTtxYsX5wxvnI+2G+TQoUODLsDG4aHNGIDaODZyxquFE2jht4rz58/X0qJVup4bp15QH6RuZC99+/a19/tmm22mH3nkkezTGfsyk/W4ceOCOnX22WdrqQeFFpn0RiYbWWeddbTMyC31RP5OO+20yElyCqXXlM5TV/xRCy380SKqJNitKCrVOUZdqQ73qFzRIoqKH8ewWX7oIKWgnvijBSWBQC0RoAtwldSUscJMa7rAabDaaqvZ7WbNmgXHZEyyBx54wJYw7OQwE3BoM5GADbfzzjtr07Iv71XI7L/SZdd15xVnhyzOoegiS7jbb7/dOiOdM0O6/t51110uSE2u0cJvWXkA8kcf6gpayG8DvyGF7wPsVmFGlQqB3aoU6cL5oEVhRtUKgc2qFvnG+VJPGjPhCAQgkBwBHIDJsSw6JdMNV3ft2tU68GSCjX79+tnJCB588EF9zTXX2NZ28pIlzsBu3bppcfjJ4hx2ZuZRfdlll2nTNdemYWY81d9//31k/s5xKBMTuMkOevfuHbQsDEeSMSVuvfXWwAE5fPjw8Oma3EYLf2XlAcgvbagr/uiBFv5okV0S7FY2keruU1eqyz+cO1qEafizjc3yRwspCfXELz0oDQRqkQAOwAqrKt1xxQEnjr9tttnGtq4T551z1ElxZPbenj17WkecdC8cNWpUo1I+//zzweQeHTp00DNmzGgUJvtA586dbZpHHHGEdSaG83RhZVavq666Km83YRe2qa/Rwl8FeQDySxvqij96oIU/WmSXBLuVTaS6+9SV6vIP544WYRr+bGOz/NFCSkI98UsPSgOBWiWAA7CCysq4YtKtV1r3mYkD9Pjx47WMI+YWcci5Vn5z5swJWuKdfvrpQTjntFu+fLkeMWKENhOC2HBmAgL9wQcfuKQy1jLGmSzS0lDylvEG3bGMgHW0gxb+is0DkF/aUFf80QMt/NEiuyTYrWwi1d2nrlSXfzh3tAjT8Gcbm+WPFlIS6olfelAaCNQyARyAFVRXnHvt2rWzzr9bbrklZ87i5JOJPbp3724ddmYm0YywzgloZoXSxx57rA0jDkXpsvvVV1/ZsFFTxEt3YnEA9urVS8t4f1FhMjKq4R208FNcHoD804W64o8maOGPFuGSYLfCNPzYpq74oYOUAi380cKVBJvlSPizpp74owUlgUCtE1ihpqY09vxizJh96rbbblOme686+uijbWnNDdao1MZJpySsceYp2Tat9ZSZ9TQIJ8dkMTP6qhNPPFFtvfXWynQjVqZFobr++uuDcG5D8njttdfUu+++aw+ZLsNq5ZVXVqYbsgtSd2u08FNyMxmOvU9lbWbYVSeccIJq3rx5UFhXN+Se3nTTTZVpUWvPmRazQTgJI+fNGJrKdLdXBx54oA0zYcIEdeeddwZ1yTjSg3TNLL52+5133rFrSVvSCIcJAtfZBnXFH8HRwh8twiXBboVp+LFNXfFDBykFWvijhSsJNsuR8GdNPfFHC0oCgZonYF5yWSpM4Isvvsibo3wFkqVHjx62xd5uu+3WKLxrBSgt+WSmYOP0sH8ytuANN9ygP/nkExtHuhjLJCJnnnmmHXdws80203Pnzm2UXr0eQAv/lJ86daru06dPo27v2SWVe3uHHXaw97WsXevX7HBTpkzRbvzLzTffXMukObKEW8BKfXr11Vf1hhtuaOvRoEGDspOp+33qij+3AFr4o4UrCXbLkfBrTV3xRw+08EcLKQk2yy89XGmoJ44EawhAIC0CdAFOi2yBdMPOh6ign3/+uW7btq11RgwYMMAGcU6/qPDDhg0Lwq+xxhp2nD8ZF3Dw4MF61113temYr0v68ssvt+P/5UsrKv1aPoYW/qnLA5B/mkiJqCv+6IIW/mjhSoLdciT8WlNX/NEDLfzRQkqCzfJLD1ca6okjwRoCEEiDAA7ANKgmkKZM6LH++utbx53MyptrcT8S0hLw8ccft44/1xpQ1tIiUNatW7fWt956a65kOJ6HAFrkgZPiKXdv58oCJ3kuMtU7Tl2pHvvsnNEim0hl9rFbleGcZC7UlSRpxksLLeLxKyc2NqscatWNQz2pLn9yh0BTJ/DLwFc139G56V3gggUL1KeffmoLvuOOO9q1udnsmIDhq3Hj+MmYfgcccIAdF/C5555TDz74oDI/6spMDqK23XZbNXDgQCVjfrCUTgAtSmeWRAx3b+dKy0yUo0x3eXtaxsOUxTi77Tr8z7R2teNdnn322cp0FVZDhgxRb775ZvAncaRutWrVSo0ePVodf/zx4ehsl0CAulICrJSDokXKgHMkj93KAcbjw9QVf8RBi8prgc2qPPO4OVJP4hIkPgTqmwAOQE/1nzRpki2ZTEYgf7JEOTfsidC/9u3bK/kzswNbp4cZJ02tuuqqoRBslkoALUolVpnwPABVhnMpuVBXSqGVbli0SJdvualjt8oll1486kp6bEtNGS1KJZZ+eGxW+oxLzYF6UioxwkMAAmECOADDNDzYltZK4uibPXu2LU2nTp1sy6RSiyZf9KRVE86/Usk1hEeLBhY+bvEA5I8q1BW08IeA3yXBbvmjD3YLLfwh4G9JsFn+aIPN8kcLSgKBpkxghaZc+Fosuzj/fvzxR/Xee+/Zy9t+++1tSz4x+tnL0qVL7aGoc3KimBaD2Wmy30AALRpY+LQl97s4t3GS+6MKdQUt/CHgZ0mwW/7pgt3yRxO08EcLVxJsliPhz5p64o8WlAQCTZkADkDP1BPj/sorrygzwKst2U477WTXctwtixYtUsOHD1fdu3dXH330kXUQikOEJVkCaJEsz6RS4wEoKZLJpUNdSY5l3JTQIi7BdOJjt9LhGidV6kocesnGRYtkeSaRGjYrCYrJpkE9SZYnqUGgXgngAPRQ+cmTJ9tStWvXTm2++eZ2W4z+N998o+644w7Vq1cvdcEFF6jXX39d3X///cF5Dy+lyRcJLfyTkAcg/zSRElFX/NEFLfzRwpUEu+VI+LWmrvijB1r4o4WUBJvllx6uNNQTR4I1BCBQNgHTcozFEwI///yzLUmfPn20+eHVpoWf3ZfjzzzzjD7kkEPscTnXtm1bfffdd3tS8torBlr4ralxgNu6sNFGG+n3338/KOzXX3+tb7/9dm1mvg7qytixY4PzbCRPgLqSPNNyU0SLcslVJh52qzKci8mFulIMpcqEQYvKcC4nF2xWOdTSiUM9SYcrqUKgHgnIWFosHhH473//qzt06GCdF+edd542XXx1//799Yorrhg4NIYNG+ZRiWu3KGjhn7Y8APmniZSIuuKPLmjhjxauJNgtR8KvNXXFHz3Qwh8tpCTYLL/0cKWhnjgSrCEAgTgEcADGoZdC3BkzZuiVVlpJN2vWTO+xxx7adAMOHH/HHHOMXrx4cQq5kmQUAbSIolL9YzwAVV+D7BJQV7KJVG8fLarHPl/O2K18dKpzjrpSHe5RuaJFFJXqHsNmVZd/VO7UkygqHIMABEolsFLZfYeJmAqBWbNmKZl5yzgB1XPPPWfz2HHHHZXpxqi6du2aSp4kGk0ALaK5VPvoCy+8oBYuXKhWXnllNX36dGW6/NrJcKRcRx99tBo1apTaYIMNql3MusqfuuKP3GjhjxbhkmC3wjT82Kau+KGDlAIt/NHClQSb5Uj4s6ae+KMFJYFAUyaAA9Az9fbZZx9plamWL1+uWrZsaZ0ZJ598smelrI/ioIWfOvMA5J8u1BV/NEELf7QIlwS7FabhxzZ1xQ8dpBRo4Y8WriTYLEfCnzX1xB8tKAkEmjKB/ydNBpvyBdRi2cXAb7XVVmr06NFqlVVWqcVLbDLXhBb+STV37lzVpUsXWzCc5P7oQ11BC38I+FcS7JZ/mkiJsFv+6IIW/mghJcFm+aWHKw31xJFgDQEIlEsAB2C55FKM97///U+ZST9SzIGkiyWAFsWSqmw4HoAqy7uY3KgrxVCqTBi0qAznUnPBbpVKLP3w1JX0GRebA1oUS6py4bBZlWNdbE7Uk2JJEQ4CEMhFAAdgLjIchwAEvCXAA5C30lAwCEAgBwHsVg4wHIYABLwkgM3yUhYKBQEIQCAWARyAsfARGQIQgAAEIAABCEAAAhCAAAQgAAEIQAACfhNYwe/iUToIQAACEIAABCAAAQhAAAIQgAAEIAABCEAgDgEcgHHoERcCEIAABCAAAQhAAAIQgAAEIAABCEAAAp4TwAHouUAUDwIQgAAEIAABCEAAAhCAAAQgAAEIQAACcQjgAIxDj7gQgAAEIAABCEAAAhCAAAQgAAEIQAACEPCcAA5AzwWieBCAAAQgAAEIQAACEIAABCAAAQhAAAIQiEMAB2AcesSFAAQgAAEIQAACEIAABCAAAQhAAAIQgIDnBHAAei4QxYMABCAAAQhAAAIQgAAEIAABCEAAAhCAQBwCOADj0CMuBCAAAQhAAAIQgAAEIAABCEAAAhCAAAQ8J4AD0HOBKB4EIAABCEAAAhCAAAQgAAEIQAACEIAABOIQwAEYhx5xIQABCEAAAhCAAAQgAAEIQAACEIAABCDgOQEcgJ4LRPEgAAEIQAACEIAABCAAAQhAAAIQgAAEIBCHAA7AOPSICwEIQAACEIAABCAAAQhAAAIQgAAEIAABzwngAPRcIIoHAQhAAAIQgAAEIAABCEAAAhCAAAQgAIE4BHAAxqFHXAhAAAIQgAAEIAABCEAAAhCAAAQgAAEIeE4AB6DnAlE8CEAAAhCAAAQgAAEIQAACEIAABCAAAQjEIYADMA494kIAAhCAAAQgAAEIQAACEIAABCAAAQhAwHMC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" <th>2015-01-02 21:00:00+00:00</th>\n",
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" <td>107.750</td>\n",
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" <td>-0.015715</td>\n",
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" <th>2015-01-09 21:00:00+00:00</th>\n",
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" <td>6</td>\n",
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" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-12 21:00:00+00:00</th>\n",
" <td>109.250</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>-0.014061</td>\n",
" <td>0.203321</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>7</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-13 21:00:00+00:00</th>\n",
" <td>110.220</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>-0.016834</td>\n",
" <td>0.188301</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>8</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-14 21:00:00+00:00</th>\n",
" <td>109.800</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>-0.022769</td>\n",
" <td>0.177393</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>9</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-15 21:00:00+00:00</th>\n",
" <td>106.820</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>-0.031721</td>\n",
" <td>0.170557</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>10</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-16 21:00:00+00:00</th>\n",
" <td>105.990</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>-0.019023</td>\n",
" <td>0.179591</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>11</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-20 21:00:00+00:00</th>\n",
" <td>108.720</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>-0.016931</td>\n",
" <td>0.172126</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>12</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-21 21:00:00+00:00</th>\n",
" <td>109.550</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>-0.011968</td>\n",
" <td>0.167201</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>13</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-22 21:00:00+00:00</th>\n",
" <td>112.400</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002725</td>\n",
" <td>0.173978</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>14</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-23 21:00:00+00:00</th>\n",
" <td>112.980</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>-0.002773</td>\n",
" <td>0.169288</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>15</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-26 21:00:00+00:00</th>\n",
" <td>113.100</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>-0.000438</td>\n",
" <td>0.163843</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>16</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-27 21:00:00+00:00</th>\n",
" <td>109.140</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>-0.013623</td>\n",
" <td>0.166597</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>17</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-28 21:00:00+00:00</th>\n",
" <td>115.310</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>-0.026272</td>\n",
" <td>0.167814</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>18</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-29 21:00:00+00:00</th>\n",
" <td>118.900</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>-0.017272</td>\n",
" <td>0.167650</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>19</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-30 21:00:00+00:00</th>\n",
" <td>117.160</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>-0.029629</td>\n",
" <td>0.168390</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>20</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-02-02 21:00:00+00:00</th>\n",
" <td>118.630</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>-0.017612</td>\n",
" <td>0.170979</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>21</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-02-03 21:00:00+00:00</th>\n",
" <td>118.650</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>-0.003406</td>\n",
" <td>0.174661</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>22</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-02-04 21:00:00+00:00</th>\n",
" <td>119.560</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>-0.007201</td>\n",
" <td>0.171086</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>23</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-02-05 21:00:00+00:00</th>\n",
" <td>119.940</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.002822</td>\n",
" <td>0.170656</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>24</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-02-06 21:00:00+00:00</th>\n",
" <td>118.930</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000049</td>\n",
" <td>0.167323</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>25</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-02-09 21:00:00+00:00</th>\n",
" <td>119.720</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>-0.004427</td>\n",
" <td>0.164548</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>26</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-02-10 21:00:00+00:00</th>\n",
" <td>122.020</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.006179</td>\n",
" <td>0.164675</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>27</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-02-11 21:00:00+00:00</th>\n",
" <td>124.880</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.006763</td>\n",
" <td>0.161599</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>28</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-02-12 21:00:00+00:00</th>\n",
" <td>126.460</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.016444</td>\n",
" <td>0.161051</td>\n",
" <td>0.000000</td>\n",
" <td>0.0</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>29</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-02-13 21:00:00+00:00</th>\n",
" <td>127.080</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.000000</td>\n",
" <td>0.020629</td>\n",
" <td>0.158575</td>\n",
" <td>0.000000</td>\n",
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" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>1.000000e+07</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>30</td>\n",
" <td>[]</td>\n",
" <td>0.0</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",
" <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>2017-11-16 21:00:00+00:00</th>\n",
" <td>171.100</td>\n",
" <td>0.000157</td>\n",
" <td>0.000534</td>\n",
" <td>0.000166</td>\n",
" <td>0.258247</td>\n",
" <td>0.125812</td>\n",
" <td>0.000216</td>\n",
" <td>0.0</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17110.0</td>\n",
" <td>...</td>\n",
" <td>157.284780</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.879972</td>\n",
" <td>9.988229e+06</td>\n",
" <td>16908.0</td>\n",
" <td>16908.0</td>\n",
" <td>726</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-11-17 21:00:00+00:00</th>\n",
" <td>170.150</td>\n",
" <td>0.000157</td>\n",
" <td>0.000524</td>\n",
" <td>0.000163</td>\n",
" <td>0.254549</td>\n",
" <td>0.125740</td>\n",
" <td>0.000217</td>\n",
" <td>0.0</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17015.0</td>\n",
" <td>...</td>\n",
" <td>157.533680</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.842296</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17110.0</td>\n",
" <td>17110.0</td>\n",
" <td>727</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-11-20 21:00:00+00:00</th>\n",
" <td>169.980</td>\n",
" <td>0.000157</td>\n",
" <td>0.000523</td>\n",
" <td>0.000162</td>\n",
" <td>0.256690</td>\n",
" <td>0.125656</td>\n",
" <td>0.000217</td>\n",
" <td>0.0</td>\n",
" <td>9.988229e+06</td>\n",
" <td>16998.0</td>\n",
" <td>...</td>\n",
" <td>157.802300</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.834970</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17015.0</td>\n",
" <td>17015.0</td>\n",
" <td>728</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-11-21 21:00:00+00:00</th>\n",
" <td>173.140</td>\n",
" <td>0.000158</td>\n",
" <td>0.000554</td>\n",
" <td>0.000172</td>\n",
" <td>0.264912</td>\n",
" <td>0.125622</td>\n",
" <td>0.000221</td>\n",
" <td>0.0</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17314.0</td>\n",
" <td>...</td>\n",
" <td>158.099130</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.944532</td>\n",
" <td>9.988229e+06</td>\n",
" <td>16998.0</td>\n",
" <td>16998.0</td>\n",
" <td>729</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-11-22 21:00:00+00:00</th>\n",
" <td>174.960</td>\n",
" <td>0.000158</td>\n",
" <td>0.000573</td>\n",
" <td>0.000178</td>\n",
" <td>0.263793</td>\n",
" <td>0.125538</td>\n",
" <td>0.000220</td>\n",
" <td>0.0</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17496.0</td>\n",
" <td>...</td>\n",
" <td>158.419340</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>2.006981</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17314.0</td>\n",
" <td>17314.0</td>\n",
" <td>730</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-11-24 18:00:00+00:00</th>\n",
" <td>174.970</td>\n",
" <td>0.000158</td>\n",
" <td>0.000573</td>\n",
" <td>0.000178</td>\n",
" <td>0.266712</td>\n",
" <td>0.125458</td>\n",
" <td>0.000220</td>\n",
" <td>0.0</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17497.0</td>\n",
" <td>...</td>\n",
" <td>158.733780</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>2.005958</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17496.0</td>\n",
" <td>17496.0</td>\n",
" <td>731</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-11-27 21:00:00+00:00</th>\n",
" <td>174.090</td>\n",
" <td>0.000158</td>\n",
" <td>0.000564</td>\n",
" <td>0.000174</td>\n",
" <td>0.266080</td>\n",
" <td>0.125373</td>\n",
" <td>0.000220</td>\n",
" <td>0.0</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17409.0</td>\n",
" <td>...</td>\n",
" <td>159.052960</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.971077</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17497.0</td>\n",
" <td>17497.0</td>\n",
" <td>732</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-11-28 21:00:00+00:00</th>\n",
" <td>173.070</td>\n",
" <td>0.000158</td>\n",
" <td>0.000554</td>\n",
" <td>0.000170</td>\n",
" <td>0.278924</td>\n",
" <td>0.125419</td>\n",
" <td>0.000217</td>\n",
" <td>0.0</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17307.0</td>\n",
" <td>...</td>\n",
" <td>159.347500</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.930550</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17409.0</td>\n",
" <td>17409.0</td>\n",
" <td>733</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-11-29 21:00:00+00:00</th>\n",
" <td>169.480</td>\n",
" <td>0.000159</td>\n",
" <td>0.000518</td>\n",
" <td>0.000158</td>\n",
" <td>0.278145</td>\n",
" <td>0.125334</td>\n",
" <td>0.000218</td>\n",
" <td>0.0</td>\n",
" <td>9.988229e+06</td>\n",
" <td>16948.0</td>\n",
" <td>...</td>\n",
" <td>159.597370</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.764426</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17307.0</td>\n",
" <td>17307.0</td>\n",
" <td>734</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-11-30 21:00:00+00:00</th>\n",
" <td>171.850</td>\n",
" <td>0.000160</td>\n",
" <td>0.000541</td>\n",
" <td>0.000165</td>\n",
" <td>0.289335</td>\n",
" <td>0.125345</td>\n",
" <td>0.000222</td>\n",
" <td>0.0</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17185.0</td>\n",
" <td>...</td>\n",
" <td>159.866260</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.843918</td>\n",
" <td>9.988229e+06</td>\n",
" <td>16948.0</td>\n",
" <td>16948.0</td>\n",
" <td>735</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-01 21:00:00+00:00</th>\n",
" <td>171.050</td>\n",
" <td>0.000160</td>\n",
" <td>0.000533</td>\n",
" <td>0.000162</td>\n",
" <td>0.286660</td>\n",
" <td>0.125268</td>\n",
" <td>0.000222</td>\n",
" <td>0.0</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17105.0</td>\n",
" <td>...</td>\n",
" <td>160.125060</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.813485</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17185.0</td>\n",
" <td>17185.0</td>\n",
" <td>736</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-04 21:00:00+00:00</th>\n",
" <td>169.800</td>\n",
" <td>0.000160</td>\n",
" <td>0.000521</td>\n",
" <td>0.000157</td>\n",
" <td>0.285103</td>\n",
" <td>0.125186</td>\n",
" <td>0.000223</td>\n",
" <td>0.0</td>\n",
" <td>9.988229e+06</td>\n",
" <td>16980.0</td>\n",
" <td>...</td>\n",
" <td>160.351140</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.765153</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17105.0</td>\n",
" <td>17105.0</td>\n",
" <td>737</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-05 21:00:00+00:00</th>\n",
" <td>169.640</td>\n",
" <td>0.000160</td>\n",
" <td>0.000519</td>\n",
" <td>0.000157</td>\n",
" <td>0.280481</td>\n",
" <td>0.125123</td>\n",
" <td>0.000223</td>\n",
" <td>0.0</td>\n",
" <td>9.988229e+06</td>\n",
" <td>16964.0</td>\n",
" <td>...</td>\n",
" <td>160.562970</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.758465</td>\n",
" <td>9.988229e+06</td>\n",
" <td>16980.0</td>\n",
" <td>16980.0</td>\n",
" <td>738</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-06 21:00:00+00:00</th>\n",
" <td>169.010</td>\n",
" <td>0.000160</td>\n",
" <td>0.000513</td>\n",
" <td>0.000154</td>\n",
" <td>0.280724</td>\n",
" <td>0.125038</td>\n",
" <td>0.000223</td>\n",
" <td>0.0</td>\n",
" <td>9.988229e+06</td>\n",
" <td>16901.0</td>\n",
" <td>...</td>\n",
" <td>160.763320</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.734808</td>\n",
" <td>9.988229e+06</td>\n",
" <td>16964.0</td>\n",
" <td>16964.0</td>\n",
" <td>739</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-07 21:00:00+00:00</th>\n",
" <td>169.452</td>\n",
" <td>0.000159</td>\n",
" <td>0.000517</td>\n",
" <td>0.000155</td>\n",
" <td>0.284762</td>\n",
" <td>0.124964</td>\n",
" <td>0.000223</td>\n",
" <td>0.0</td>\n",
" <td>9.988229e+06</td>\n",
" <td>16945.2</td>\n",
" <td>...</td>\n",
" <td>160.962910</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.748567</td>\n",
" <td>9.988229e+06</td>\n",
" <td>16901.0</td>\n",
" <td>16901.0</td>\n",
" <td>740</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-08 21:00:00+00:00</th>\n",
" <td>169.370</td>\n",
" <td>0.000159</td>\n",
" <td>0.000517</td>\n",
" <td>0.000155</td>\n",
" <td>0.291768</td>\n",
" <td>0.124915</td>\n",
" <td>0.000223</td>\n",
" <td>0.0</td>\n",
" <td>9.988229e+06</td>\n",
" <td>16937.0</td>\n",
" <td>...</td>\n",
" <td>161.152320</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.744599</td>\n",
" <td>9.988229e+06</td>\n",
" <td>16945.2</td>\n",
" <td>16945.2</td>\n",
" <td>741</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-11 21:00:00+00:00</th>\n",
" <td>172.670</td>\n",
" <td>0.000160</td>\n",
" <td>0.000550</td>\n",
" <td>0.000165</td>\n",
" <td>0.295660</td>\n",
" <td>0.124840</td>\n",
" <td>0.000225</td>\n",
" <td>0.0</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17267.0</td>\n",
" <td>...</td>\n",
" <td>161.381500</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.854754</td>\n",
" <td>9.988229e+06</td>\n",
" <td>16937.0</td>\n",
" <td>16937.0</td>\n",
" <td>742</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-12 21:00:00+00:00</th>\n",
" <td>171.700</td>\n",
" <td>0.000160</td>\n",
" <td>0.000540</td>\n",
" <td>0.000161</td>\n",
" <td>0.297947</td>\n",
" <td>0.124758</td>\n",
" <td>0.000224</td>\n",
" <td>0.0</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17170.0</td>\n",
" <td>...</td>\n",
" <td>161.601680</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.817940</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17267.0</td>\n",
" <td>17267.0</td>\n",
" <td>743</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-13 21:00:00+00:00</th>\n",
" <td>172.270</td>\n",
" <td>0.000160</td>\n",
" <td>0.000546</td>\n",
" <td>0.000163</td>\n",
" <td>0.297801</td>\n",
" <td>0.124675</td>\n",
" <td>0.000224</td>\n",
" <td>0.0</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17227.0</td>\n",
" <td>...</td>\n",
" <td>161.809430</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.835892</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17170.0</td>\n",
" <td>17170.0</td>\n",
" <td>744</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-14 21:00:00+00:00</th>\n",
" <td>172.220</td>\n",
" <td>0.000160</td>\n",
" <td>0.000545</td>\n",
" <td>0.000163</td>\n",
" <td>0.292498</td>\n",
" <td>0.124618</td>\n",
" <td>0.000224</td>\n",
" <td>0.0</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17222.0</td>\n",
" <td>...</td>\n",
" <td>162.010200</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.832971</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17227.0</td>\n",
" <td>17227.0</td>\n",
" <td>745</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-15 21:00:00+00:00</th>\n",
" <td>173.870</td>\n",
" <td>0.000160</td>\n",
" <td>0.000562</td>\n",
" <td>0.000168</td>\n",
" <td>0.296633</td>\n",
" <td>0.124545</td>\n",
" <td>0.000225</td>\n",
" <td>0.0</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17387.0</td>\n",
" <td>...</td>\n",
" <td>162.220300</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.887169</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17222.0</td>\n",
" <td>17222.0</td>\n",
" <td>746</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-18 21:00:00+00:00</th>\n",
" <td>176.420</td>\n",
" <td>0.000161</td>\n",
" <td>0.000587</td>\n",
" <td>0.000176</td>\n",
" <td>0.304856</td>\n",
" <td>0.124510</td>\n",
" <td>0.000228</td>\n",
" <td>0.0</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17642.0</td>\n",
" <td>...</td>\n",
" <td>162.484790</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.971507</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17387.0</td>\n",
" <td>17387.0</td>\n",
" <td>747</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-19 21:00:00+00:00</th>\n",
" <td>174.540</td>\n",
" <td>0.000161</td>\n",
" <td>0.000568</td>\n",
" <td>0.000169</td>\n",
" <td>0.299844</td>\n",
" <td>0.124451</td>\n",
" <td>0.000230</td>\n",
" <td>0.0</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17454.0</td>\n",
" <td>...</td>\n",
" <td>162.741040</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.895963</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17642.0</td>\n",
" <td>17642.0</td>\n",
" <td>748</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-20 21:00:00+00:00</th>\n",
" <td>174.350</td>\n",
" <td>0.000161</td>\n",
" <td>0.000566</td>\n",
" <td>0.000168</td>\n",
" <td>0.299163</td>\n",
" <td>0.124369</td>\n",
" <td>0.000230</td>\n",
" <td>0.0</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17435.0</td>\n",
" <td>...</td>\n",
" <td>163.001860</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.888252</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17454.0</td>\n",
" <td>17454.0</td>\n",
" <td>749</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-21 21:00:00+00:00</th>\n",
" <td>175.010</td>\n",
" <td>0.000161</td>\n",
" <td>0.000573</td>\n",
" <td>0.000170</td>\n",
" <td>0.301839</td>\n",
" <td>0.124289</td>\n",
" <td>0.000230</td>\n",
" <td>0.0</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17501.0</td>\n",
" <td>...</td>\n",
" <td>163.257330</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.908974</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17435.0</td>\n",
" <td>17435.0</td>\n",
" <td>750</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-22 21:00:00+00:00</th>\n",
" <td>175.010</td>\n",
" <td>0.000161</td>\n",
" <td>0.000573</td>\n",
" <td>0.000170</td>\n",
" <td>0.301498</td>\n",
" <td>0.124207</td>\n",
" <td>0.000230</td>\n",
" <td>0.0</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17501.0</td>\n",
" <td>...</td>\n",
" <td>163.442180</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.907702</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17501.0</td>\n",
" <td>17501.0</td>\n",
" <td>751</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-26 21:00:00+00:00</th>\n",
" <td>170.570</td>\n",
" <td>0.000163</td>\n",
" <td>0.000529</td>\n",
" <td>0.000155</td>\n",
" <td>0.299942</td>\n",
" <td>0.124128</td>\n",
" <td>0.000232</td>\n",
" <td>0.0</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17057.0</td>\n",
" <td>...</td>\n",
" <td>163.598270</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.704187</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17501.0</td>\n",
" <td>17501.0</td>\n",
" <td>752</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-27 21:00:00+00:00</th>\n",
" <td>170.600</td>\n",
" <td>0.000163</td>\n",
" <td>0.000529</td>\n",
" <td>0.000155</td>\n",
" <td>0.300574</td>\n",
" <td>0.124045</td>\n",
" <td>0.000232</td>\n",
" <td>0.0</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17060.0</td>\n",
" <td>...</td>\n",
" <td>163.746493</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.704022</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17057.0</td>\n",
" <td>17057.0</td>\n",
" <td>753</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-28 21:00:00+00:00</th>\n",
" <td>171.080</td>\n",
" <td>0.000163</td>\n",
" <td>0.000534</td>\n",
" <td>0.000156</td>\n",
" <td>0.303250</td>\n",
" <td>0.123966</td>\n",
" <td>0.000232</td>\n",
" <td>0.0</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17108.0</td>\n",
" <td>...</td>\n",
" <td>163.899510</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.718340</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17060.0</td>\n",
" <td>17060.0</td>\n",
" <td>754</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-29 21:00:00+00:00</th>\n",
" <td>169.230</td>\n",
" <td>0.000163</td>\n",
" <td>0.000515</td>\n",
" <td>0.000150</td>\n",
" <td>0.298336</td>\n",
" <td>0.123907</td>\n",
" <td>0.000234</td>\n",
" <td>0.0</td>\n",
" <td>9.988229e+06</td>\n",
" <td>16923.0</td>\n",
" <td>...</td>\n",
" <td>163.997270</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.648975</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17108.0</td>\n",
" <td>17108.0</td>\n",
" <td>755</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>755 rows × 40 columns</p>\n",
"</div>"
],
"text/plain": [
" AAPL algo_volatility algorithm_period_return \\\n",
"2015-01-02 21:00:00+00:00 109.330 NaN 0.000000 \n",
"2015-01-05 21:00:00+00:00 106.250 0.000000 0.000000 \n",
"2015-01-06 21:00:00+00:00 106.260 0.000000 0.000000 \n",
"2015-01-07 21:00:00+00:00 107.750 0.000000 0.000000 \n",
"2015-01-08 21:00:00+00:00 111.890 0.000000 0.000000 \n",
"2015-01-09 21:00:00+00:00 112.010 0.000000 0.000000 \n",
"2015-01-12 21:00:00+00:00 109.250 0.000000 0.000000 \n",
"2015-01-13 21:00:00+00:00 110.220 0.000000 0.000000 \n",
"2015-01-14 21:00:00+00:00 109.800 0.000000 0.000000 \n",
"2015-01-15 21:00:00+00:00 106.820 0.000000 0.000000 \n",
"2015-01-16 21:00:00+00:00 105.990 0.000000 0.000000 \n",
"2015-01-20 21:00:00+00:00 108.720 0.000000 0.000000 \n",
"2015-01-21 21:00:00+00:00 109.550 0.000000 0.000000 \n",
"2015-01-22 21:00:00+00:00 112.400 0.000000 0.000000 \n",
"2015-01-23 21:00:00+00:00 112.980 0.000000 0.000000 \n",
"2015-01-26 21:00:00+00:00 113.100 0.000000 0.000000 \n",
"2015-01-27 21:00:00+00:00 109.140 0.000000 0.000000 \n",
"2015-01-28 21:00:00+00:00 115.310 0.000000 0.000000 \n",
"2015-01-29 21:00:00+00:00 118.900 0.000000 0.000000 \n",
"2015-01-30 21:00:00+00:00 117.160 0.000000 0.000000 \n",
"2015-02-02 21:00:00+00:00 118.630 0.000000 0.000000 \n",
"2015-02-03 21:00:00+00:00 118.650 0.000000 0.000000 \n",
"2015-02-04 21:00:00+00:00 119.560 0.000000 0.000000 \n",
"2015-02-05 21:00:00+00:00 119.940 0.000000 0.000000 \n",
"2015-02-06 21:00:00+00:00 118.930 0.000000 0.000000 \n",
"2015-02-09 21:00:00+00:00 119.720 0.000000 0.000000 \n",
"2015-02-10 21:00:00+00:00 122.020 0.000000 0.000000 \n",
"2015-02-11 21:00:00+00:00 124.880 0.000000 0.000000 \n",
"2015-02-12 21:00:00+00:00 126.460 0.000000 0.000000 \n",
"2015-02-13 21:00:00+00:00 127.080 0.000000 0.000000 \n",
"... ... ... ... \n",
"2017-11-16 21:00:00+00:00 171.100 0.000157 0.000534 \n",
"2017-11-17 21:00:00+00:00 170.150 0.000157 0.000524 \n",
"2017-11-20 21:00:00+00:00 169.980 0.000157 0.000523 \n",
"2017-11-21 21:00:00+00:00 173.140 0.000158 0.000554 \n",
"2017-11-22 21:00:00+00:00 174.960 0.000158 0.000573 \n",
"2017-11-24 18:00:00+00:00 174.970 0.000158 0.000573 \n",
"2017-11-27 21:00:00+00:00 174.090 0.000158 0.000564 \n",
"2017-11-28 21:00:00+00:00 173.070 0.000158 0.000554 \n",
"2017-11-29 21:00:00+00:00 169.480 0.000159 0.000518 \n",
"2017-11-30 21:00:00+00:00 171.850 0.000160 0.000541 \n",
"2017-12-01 21:00:00+00:00 171.050 0.000160 0.000533 \n",
"2017-12-04 21:00:00+00:00 169.800 0.000160 0.000521 \n",
"2017-12-05 21:00:00+00:00 169.640 0.000160 0.000519 \n",
"2017-12-06 21:00:00+00:00 169.010 0.000160 0.000513 \n",
"2017-12-07 21:00:00+00:00 169.452 0.000159 0.000517 \n",
"2017-12-08 21:00:00+00:00 169.370 0.000159 0.000517 \n",
"2017-12-11 21:00:00+00:00 172.670 0.000160 0.000550 \n",
"2017-12-12 21:00:00+00:00 171.700 0.000160 0.000540 \n",
"2017-12-13 21:00:00+00:00 172.270 0.000160 0.000546 \n",
"2017-12-14 21:00:00+00:00 172.220 0.000160 0.000545 \n",
"2017-12-15 21:00:00+00:00 173.870 0.000160 0.000562 \n",
"2017-12-18 21:00:00+00:00 176.420 0.000161 0.000587 \n",
"2017-12-19 21:00:00+00:00 174.540 0.000161 0.000568 \n",
"2017-12-20 21:00:00+00:00 174.350 0.000161 0.000566 \n",
"2017-12-21 21:00:00+00:00 175.010 0.000161 0.000573 \n",
"2017-12-22 21:00:00+00:00 175.010 0.000161 0.000573 \n",
"2017-12-26 21:00:00+00:00 170.570 0.000163 0.000529 \n",
"2017-12-27 21:00:00+00:00 170.600 0.000163 0.000529 \n",
"2017-12-28 21:00:00+00:00 171.080 0.000163 0.000534 \n",
"2017-12-29 21:00:00+00:00 169.230 0.000163 0.000515 \n",
"\n",
" alpha benchmark_period_return \\\n",
"2015-01-02 21:00:00+00:00 NaN -0.000535 \n",
"2015-01-05 21:00:00+00:00 0.000000 -0.018585 \n",
"2015-01-06 21:00:00+00:00 0.000000 -0.027829 \n",
"2015-01-07 21:00:00+00:00 0.000000 -0.015715 \n",
"2015-01-08 21:00:00+00:00 0.000000 0.001751 \n",
"2015-01-09 21:00:00+00:00 0.000000 -0.006276 \n",
"2015-01-12 21:00:00+00:00 0.000000 -0.014061 \n",
"2015-01-13 21:00:00+00:00 0.000000 -0.016834 \n",
"2015-01-14 21:00:00+00:00 0.000000 -0.022769 \n",
"2015-01-15 21:00:00+00:00 0.000000 -0.031721 \n",
"2015-01-16 21:00:00+00:00 0.000000 -0.019023 \n",
"2015-01-20 21:00:00+00:00 0.000000 -0.016931 \n",
"2015-01-21 21:00:00+00:00 0.000000 -0.011968 \n",
"2015-01-22 21:00:00+00:00 0.000000 0.002725 \n",
"2015-01-23 21:00:00+00:00 0.000000 -0.002773 \n",
"2015-01-26 21:00:00+00:00 0.000000 -0.000438 \n",
"2015-01-27 21:00:00+00:00 0.000000 -0.013623 \n",
"2015-01-28 21:00:00+00:00 0.000000 -0.026272 \n",
"2015-01-29 21:00:00+00:00 0.000000 -0.017272 \n",
"2015-01-30 21:00:00+00:00 0.000000 -0.029629 \n",
"2015-02-02 21:00:00+00:00 0.000000 -0.017612 \n",
"2015-02-03 21:00:00+00:00 0.000000 -0.003406 \n",
"2015-02-04 21:00:00+00:00 0.000000 -0.007201 \n",
"2015-02-05 21:00:00+00:00 0.000000 0.002822 \n",
"2015-02-06 21:00:00+00:00 0.000000 0.000049 \n",
"2015-02-09 21:00:00+00:00 0.000000 -0.004427 \n",
"2015-02-10 21:00:00+00:00 0.000000 0.006179 \n",
"2015-02-11 21:00:00+00:00 0.000000 0.006763 \n",
"2015-02-12 21:00:00+00:00 0.000000 0.016444 \n",
"2015-02-13 21:00:00+00:00 0.000000 0.020629 \n",
"... ... ... \n",
"2017-11-16 21:00:00+00:00 0.000166 0.258247 \n",
"2017-11-17 21:00:00+00:00 0.000163 0.254549 \n",
"2017-11-20 21:00:00+00:00 0.000162 0.256690 \n",
"2017-11-21 21:00:00+00:00 0.000172 0.264912 \n",
"2017-11-22 21:00:00+00:00 0.000178 0.263793 \n",
"2017-11-24 18:00:00+00:00 0.000178 0.266712 \n",
"2017-11-27 21:00:00+00:00 0.000174 0.266080 \n",
"2017-11-28 21:00:00+00:00 0.000170 0.278924 \n",
"2017-11-29 21:00:00+00:00 0.000158 0.278145 \n",
"2017-11-30 21:00:00+00:00 0.000165 0.289335 \n",
"2017-12-01 21:00:00+00:00 0.000162 0.286660 \n",
"2017-12-04 21:00:00+00:00 0.000157 0.285103 \n",
"2017-12-05 21:00:00+00:00 0.000157 0.280481 \n",
"2017-12-06 21:00:00+00:00 0.000154 0.280724 \n",
"2017-12-07 21:00:00+00:00 0.000155 0.284762 \n",
"2017-12-08 21:00:00+00:00 0.000155 0.291768 \n",
"2017-12-11 21:00:00+00:00 0.000165 0.295660 \n",
"2017-12-12 21:00:00+00:00 0.000161 0.297947 \n",
"2017-12-13 21:00:00+00:00 0.000163 0.297801 \n",
"2017-12-14 21:00:00+00:00 0.000163 0.292498 \n",
"2017-12-15 21:00:00+00:00 0.000168 0.296633 \n",
"2017-12-18 21:00:00+00:00 0.000176 0.304856 \n",
"2017-12-19 21:00:00+00:00 0.000169 0.299844 \n",
"2017-12-20 21:00:00+00:00 0.000168 0.299163 \n",
"2017-12-21 21:00:00+00:00 0.000170 0.301839 \n",
"2017-12-22 21:00:00+00:00 0.000170 0.301498 \n",
"2017-12-26 21:00:00+00:00 0.000155 0.299942 \n",
"2017-12-27 21:00:00+00:00 0.000155 0.300574 \n",
"2017-12-28 21:00:00+00:00 0.000156 0.303250 \n",
"2017-12-29 21:00:00+00:00 0.000150 0.298336 \n",
"\n",
" benchmark_volatility beta capital_used \\\n",
"2015-01-02 21:00:00+00:00 NaN NaN 0.0 \n",
"2015-01-05 21:00:00+00:00 0.196712 0.000000 0.0 \n",
"2015-01-06 21:00:00+00:00 0.139101 0.000000 0.0 \n",
"2015-01-07 21:00:00+00:00 0.206972 0.000000 0.0 \n",
"2015-01-08 21:00:00+00:00 0.236040 0.000000 0.0 \n",
"2015-01-09 21:00:00+00:00 0.218111 0.000000 0.0 \n",
"2015-01-12 21:00:00+00:00 0.203321 0.000000 0.0 \n",
"2015-01-13 21:00:00+00:00 0.188301 0.000000 0.0 \n",
"2015-01-14 21:00:00+00:00 0.177393 0.000000 0.0 \n",
"2015-01-15 21:00:00+00:00 0.170557 0.000000 0.0 \n",
"2015-01-16 21:00:00+00:00 0.179591 0.000000 0.0 \n",
"2015-01-20 21:00:00+00:00 0.172126 0.000000 0.0 \n",
"2015-01-21 21:00:00+00:00 0.167201 0.000000 0.0 \n",
"2015-01-22 21:00:00+00:00 0.173978 0.000000 0.0 \n",
"2015-01-23 21:00:00+00:00 0.169288 0.000000 0.0 \n",
"2015-01-26 21:00:00+00:00 0.163843 0.000000 0.0 \n",
"2015-01-27 21:00:00+00:00 0.166597 0.000000 0.0 \n",
"2015-01-28 21:00:00+00:00 0.167814 0.000000 0.0 \n",
"2015-01-29 21:00:00+00:00 0.167650 0.000000 0.0 \n",
"2015-01-30 21:00:00+00:00 0.168390 0.000000 0.0 \n",
"2015-02-02 21:00:00+00:00 0.170979 0.000000 0.0 \n",
"2015-02-03 21:00:00+00:00 0.174661 0.000000 0.0 \n",
"2015-02-04 21:00:00+00:00 0.171086 0.000000 0.0 \n",
"2015-02-05 21:00:00+00:00 0.170656 0.000000 0.0 \n",
"2015-02-06 21:00:00+00:00 0.167323 0.000000 0.0 \n",
"2015-02-09 21:00:00+00:00 0.164548 0.000000 0.0 \n",
"2015-02-10 21:00:00+00:00 0.164675 0.000000 0.0 \n",
"2015-02-11 21:00:00+00:00 0.161599 0.000000 0.0 \n",
"2015-02-12 21:00:00+00:00 0.161051 0.000000 0.0 \n",
"2015-02-13 21:00:00+00:00 0.158575 0.000000 0.0 \n",
"... ... ... ... \n",
"2017-11-16 21:00:00+00:00 0.125812 0.000216 0.0 \n",
"2017-11-17 21:00:00+00:00 0.125740 0.000217 0.0 \n",
"2017-11-20 21:00:00+00:00 0.125656 0.000217 0.0 \n",
"2017-11-21 21:00:00+00:00 0.125622 0.000221 0.0 \n",
"2017-11-22 21:00:00+00:00 0.125538 0.000220 0.0 \n",
"2017-11-24 18:00:00+00:00 0.125458 0.000220 0.0 \n",
"2017-11-27 21:00:00+00:00 0.125373 0.000220 0.0 \n",
"2017-11-28 21:00:00+00:00 0.125419 0.000217 0.0 \n",
"2017-11-29 21:00:00+00:00 0.125334 0.000218 0.0 \n",
"2017-11-30 21:00:00+00:00 0.125345 0.000222 0.0 \n",
"2017-12-01 21:00:00+00:00 0.125268 0.000222 0.0 \n",
"2017-12-04 21:00:00+00:00 0.125186 0.000223 0.0 \n",
"2017-12-05 21:00:00+00:00 0.125123 0.000223 0.0 \n",
"2017-12-06 21:00:00+00:00 0.125038 0.000223 0.0 \n",
"2017-12-07 21:00:00+00:00 0.124964 0.000223 0.0 \n",
"2017-12-08 21:00:00+00:00 0.124915 0.000223 0.0 \n",
"2017-12-11 21:00:00+00:00 0.124840 0.000225 0.0 \n",
"2017-12-12 21:00:00+00:00 0.124758 0.000224 0.0 \n",
"2017-12-13 21:00:00+00:00 0.124675 0.000224 0.0 \n",
"2017-12-14 21:00:00+00:00 0.124618 0.000224 0.0 \n",
"2017-12-15 21:00:00+00:00 0.124545 0.000225 0.0 \n",
"2017-12-18 21:00:00+00:00 0.124510 0.000228 0.0 \n",
"2017-12-19 21:00:00+00:00 0.124451 0.000230 0.0 \n",
"2017-12-20 21:00:00+00:00 0.124369 0.000230 0.0 \n",
"2017-12-21 21:00:00+00:00 0.124289 0.000230 0.0 \n",
"2017-12-22 21:00:00+00:00 0.124207 0.000230 0.0 \n",
"2017-12-26 21:00:00+00:00 0.124128 0.000232 0.0 \n",
"2017-12-27 21:00:00+00:00 0.124045 0.000232 0.0 \n",
"2017-12-28 21:00:00+00:00 0.123966 0.000232 0.0 \n",
"2017-12-29 21:00:00+00:00 0.123907 0.000234 0.0 \n",
"\n",
" ending_cash ending_exposure \\\n",
"2015-01-02 21:00:00+00:00 1.000000e+07 0.0 \n",
"2015-01-05 21:00:00+00:00 1.000000e+07 0.0 \n",
"2015-01-06 21:00:00+00:00 1.000000e+07 0.0 \n",
"2015-01-07 21:00:00+00:00 1.000000e+07 0.0 \n",
"2015-01-08 21:00:00+00:00 1.000000e+07 0.0 \n",
"2015-01-09 21:00:00+00:00 1.000000e+07 0.0 \n",
"2015-01-12 21:00:00+00:00 1.000000e+07 0.0 \n",
"2015-01-13 21:00:00+00:00 1.000000e+07 0.0 \n",
"2015-01-14 21:00:00+00:00 1.000000e+07 0.0 \n",
"2015-01-15 21:00:00+00:00 1.000000e+07 0.0 \n",
"2015-01-16 21:00:00+00:00 1.000000e+07 0.0 \n",
"2015-01-20 21:00:00+00:00 1.000000e+07 0.0 \n",
"2015-01-21 21:00:00+00:00 1.000000e+07 0.0 \n",
"2015-01-22 21:00:00+00:00 1.000000e+07 0.0 \n",
"2015-01-23 21:00:00+00:00 1.000000e+07 0.0 \n",
"2015-01-26 21:00:00+00:00 1.000000e+07 0.0 \n",
"2015-01-27 21:00:00+00:00 1.000000e+07 0.0 \n",
"2015-01-28 21:00:00+00:00 1.000000e+07 0.0 \n",
"2015-01-29 21:00:00+00:00 1.000000e+07 0.0 \n",
"2015-01-30 21:00:00+00:00 1.000000e+07 0.0 \n",
"2015-02-02 21:00:00+00:00 1.000000e+07 0.0 \n",
"2015-02-03 21:00:00+00:00 1.000000e+07 0.0 \n",
"2015-02-04 21:00:00+00:00 1.000000e+07 0.0 \n",
"2015-02-05 21:00:00+00:00 1.000000e+07 0.0 \n",
"2015-02-06 21:00:00+00:00 1.000000e+07 0.0 \n",
"2015-02-09 21:00:00+00:00 1.000000e+07 0.0 \n",
"2015-02-10 21:00:00+00:00 1.000000e+07 0.0 \n",
"2015-02-11 21:00:00+00:00 1.000000e+07 0.0 \n",
"2015-02-12 21:00:00+00:00 1.000000e+07 0.0 \n",
"2015-02-13 21:00:00+00:00 1.000000e+07 0.0 \n",
"... ... ... \n",
"2017-11-16 21:00:00+00:00 9.988229e+06 17110.0 \n",
"2017-11-17 21:00:00+00:00 9.988229e+06 17015.0 \n",
"2017-11-20 21:00:00+00:00 9.988229e+06 16998.0 \n",
"2017-11-21 21:00:00+00:00 9.988229e+06 17314.0 \n",
"2017-11-22 21:00:00+00:00 9.988229e+06 17496.0 \n",
"2017-11-24 18:00:00+00:00 9.988229e+06 17497.0 \n",
"2017-11-27 21:00:00+00:00 9.988229e+06 17409.0 \n",
"2017-11-28 21:00:00+00:00 9.988229e+06 17307.0 \n",
"2017-11-29 21:00:00+00:00 9.988229e+06 16948.0 \n",
"2017-11-30 21:00:00+00:00 9.988229e+06 17185.0 \n",
"2017-12-01 21:00:00+00:00 9.988229e+06 17105.0 \n",
"2017-12-04 21:00:00+00:00 9.988229e+06 16980.0 \n",
"2017-12-05 21:00:00+00:00 9.988229e+06 16964.0 \n",
"2017-12-06 21:00:00+00:00 9.988229e+06 16901.0 \n",
"2017-12-07 21:00:00+00:00 9.988229e+06 16945.2 \n",
"2017-12-08 21:00:00+00:00 9.988229e+06 16937.0 \n",
"2017-12-11 21:00:00+00:00 9.988229e+06 17267.0 \n",
"2017-12-12 21:00:00+00:00 9.988229e+06 17170.0 \n",
"2017-12-13 21:00:00+00:00 9.988229e+06 17227.0 \n",
"2017-12-14 21:00:00+00:00 9.988229e+06 17222.0 \n",
"2017-12-15 21:00:00+00:00 9.988229e+06 17387.0 \n",
"2017-12-18 21:00:00+00:00 9.988229e+06 17642.0 \n",
"2017-12-19 21:00:00+00:00 9.988229e+06 17454.0 \n",
"2017-12-20 21:00:00+00:00 9.988229e+06 17435.0 \n",
"2017-12-21 21:00:00+00:00 9.988229e+06 17501.0 \n",
"2017-12-22 21:00:00+00:00 9.988229e+06 17501.0 \n",
"2017-12-26 21:00:00+00:00 9.988229e+06 17057.0 \n",
"2017-12-27 21:00:00+00:00 9.988229e+06 17060.0 \n",
"2017-12-28 21:00:00+00:00 9.988229e+06 17108.0 \n",
"2017-12-29 21:00:00+00:00 9.988229e+06 16923.0 \n",
"\n",
" ... short_mavg short_value \\\n",
"2015-01-02 21:00:00+00:00 ... NaN 0.0 \n",
"2015-01-05 21:00:00+00:00 ... NaN 0.0 \n",
"2015-01-06 21:00:00+00:00 ... NaN 0.0 \n",
"2015-01-07 21:00:00+00:00 ... NaN 0.0 \n",
"2015-01-08 21:00:00+00:00 ... NaN 0.0 \n",
"2015-01-09 21:00:00+00:00 ... NaN 0.0 \n",
"2015-01-12 21:00:00+00:00 ... NaN 0.0 \n",
"2015-01-13 21:00:00+00:00 ... NaN 0.0 \n",
"2015-01-14 21:00:00+00:00 ... NaN 0.0 \n",
"2015-01-15 21:00:00+00:00 ... NaN 0.0 \n",
"2015-01-16 21:00:00+00:00 ... NaN 0.0 \n",
"2015-01-20 21:00:00+00:00 ... NaN 0.0 \n",
"2015-01-21 21:00:00+00:00 ... NaN 0.0 \n",
"2015-01-22 21:00:00+00:00 ... NaN 0.0 \n",
"2015-01-23 21:00:00+00:00 ... NaN 0.0 \n",
"2015-01-26 21:00:00+00:00 ... NaN 0.0 \n",
"2015-01-27 21:00:00+00:00 ... NaN 0.0 \n",
"2015-01-28 21:00:00+00:00 ... NaN 0.0 \n",
"2015-01-29 21:00:00+00:00 ... NaN 0.0 \n",
"2015-01-30 21:00:00+00:00 ... NaN 0.0 \n",
"2015-02-02 21:00:00+00:00 ... NaN 0.0 \n",
"2015-02-03 21:00:00+00:00 ... NaN 0.0 \n",
"2015-02-04 21:00:00+00:00 ... NaN 0.0 \n",
"2015-02-05 21:00:00+00:00 ... NaN 0.0 \n",
"2015-02-06 21:00:00+00:00 ... NaN 0.0 \n",
"2015-02-09 21:00:00+00:00 ... NaN 0.0 \n",
"2015-02-10 21:00:00+00:00 ... NaN 0.0 \n",
"2015-02-11 21:00:00+00:00 ... NaN 0.0 \n",
"2015-02-12 21:00:00+00:00 ... NaN 0.0 \n",
"2015-02-13 21:00:00+00:00 ... NaN 0.0 \n",
"... ... ... ... \n",
"2017-11-16 21:00:00+00:00 ... 157.284780 0.0 \n",
"2017-11-17 21:00:00+00:00 ... 157.533680 0.0 \n",
"2017-11-20 21:00:00+00:00 ... 157.802300 0.0 \n",
"2017-11-21 21:00:00+00:00 ... 158.099130 0.0 \n",
"2017-11-22 21:00:00+00:00 ... 158.419340 0.0 \n",
"2017-11-24 18:00:00+00:00 ... 158.733780 0.0 \n",
"2017-11-27 21:00:00+00:00 ... 159.052960 0.0 \n",
"2017-11-28 21:00:00+00:00 ... 159.347500 0.0 \n",
"2017-11-29 21:00:00+00:00 ... 159.597370 0.0 \n",
"2017-11-30 21:00:00+00:00 ... 159.866260 0.0 \n",
"2017-12-01 21:00:00+00:00 ... 160.125060 0.0 \n",
"2017-12-04 21:00:00+00:00 ... 160.351140 0.0 \n",
"2017-12-05 21:00:00+00:00 ... 160.562970 0.0 \n",
"2017-12-06 21:00:00+00:00 ... 160.763320 0.0 \n",
"2017-12-07 21:00:00+00:00 ... 160.962910 0.0 \n",
"2017-12-08 21:00:00+00:00 ... 161.152320 0.0 \n",
"2017-12-11 21:00:00+00:00 ... 161.381500 0.0 \n",
"2017-12-12 21:00:00+00:00 ... 161.601680 0.0 \n",
"2017-12-13 21:00:00+00:00 ... 161.809430 0.0 \n",
"2017-12-14 21:00:00+00:00 ... 162.010200 0.0 \n",
"2017-12-15 21:00:00+00:00 ... 162.220300 0.0 \n",
"2017-12-18 21:00:00+00:00 ... 162.484790 0.0 \n",
"2017-12-19 21:00:00+00:00 ... 162.741040 0.0 \n",
"2017-12-20 21:00:00+00:00 ... 163.001860 0.0 \n",
"2017-12-21 21:00:00+00:00 ... 163.257330 0.0 \n",
"2017-12-22 21:00:00+00:00 ... 163.442180 0.0 \n",
"2017-12-26 21:00:00+00:00 ... 163.598270 0.0 \n",
"2017-12-27 21:00:00+00:00 ... 163.746493 0.0 \n",
"2017-12-28 21:00:00+00:00 ... 163.899510 0.0 \n",
"2017-12-29 21:00:00+00:00 ... 163.997270 0.0 \n",
"\n",
" shorts_count sortino starting_cash \\\n",
"2015-01-02 21:00:00+00:00 0 NaN 1.000000e+07 \n",
"2015-01-05 21:00:00+00:00 0 NaN 1.000000e+07 \n",
"2015-01-06 21:00:00+00:00 0 NaN 1.000000e+07 \n",
"2015-01-07 21:00:00+00:00 0 NaN 1.000000e+07 \n",
"2015-01-08 21:00:00+00:00 0 NaN 1.000000e+07 \n",
"2015-01-09 21:00:00+00:00 0 NaN 1.000000e+07 \n",
"2015-01-12 21:00:00+00:00 0 NaN 1.000000e+07 \n",
"2015-01-13 21:00:00+00:00 0 NaN 1.000000e+07 \n",
"2015-01-14 21:00:00+00:00 0 NaN 1.000000e+07 \n",
"2015-01-15 21:00:00+00:00 0 NaN 1.000000e+07 \n",
"2015-01-16 21:00:00+00:00 0 NaN 1.000000e+07 \n",
"2015-01-20 21:00:00+00:00 0 NaN 1.000000e+07 \n",
"2015-01-21 21:00:00+00:00 0 NaN 1.000000e+07 \n",
"2015-01-22 21:00:00+00:00 0 NaN 1.000000e+07 \n",
"2015-01-23 21:00:00+00:00 0 NaN 1.000000e+07 \n",
"2015-01-26 21:00:00+00:00 0 NaN 1.000000e+07 \n",
"2015-01-27 21:00:00+00:00 0 NaN 1.000000e+07 \n",
"2015-01-28 21:00:00+00:00 0 NaN 1.000000e+07 \n",
"2015-01-29 21:00:00+00:00 0 NaN 1.000000e+07 \n",
"2015-01-30 21:00:00+00:00 0 NaN 1.000000e+07 \n",
"2015-02-02 21:00:00+00:00 0 NaN 1.000000e+07 \n",
"2015-02-03 21:00:00+00:00 0 NaN 1.000000e+07 \n",
"2015-02-04 21:00:00+00:00 0 NaN 1.000000e+07 \n",
"2015-02-05 21:00:00+00:00 0 NaN 1.000000e+07 \n",
"2015-02-06 21:00:00+00:00 0 NaN 1.000000e+07 \n",
"2015-02-09 21:00:00+00:00 0 NaN 1.000000e+07 \n",
"2015-02-10 21:00:00+00:00 0 NaN 1.000000e+07 \n",
"2015-02-11 21:00:00+00:00 0 NaN 1.000000e+07 \n",
"2015-02-12 21:00:00+00:00 0 NaN 1.000000e+07 \n",
"2015-02-13 21:00:00+00:00 0 NaN 1.000000e+07 \n",
"... ... ... ... \n",
"2017-11-16 21:00:00+00:00 0 1.879972 9.988229e+06 \n",
"2017-11-17 21:00:00+00:00 0 1.842296 9.988229e+06 \n",
"2017-11-20 21:00:00+00:00 0 1.834970 9.988229e+06 \n",
"2017-11-21 21:00:00+00:00 0 1.944532 9.988229e+06 \n",
"2017-11-22 21:00:00+00:00 0 2.006981 9.988229e+06 \n",
"2017-11-24 18:00:00+00:00 0 2.005958 9.988229e+06 \n",
"2017-11-27 21:00:00+00:00 0 1.971077 9.988229e+06 \n",
"2017-11-28 21:00:00+00:00 0 1.930550 9.988229e+06 \n",
"2017-11-29 21:00:00+00:00 0 1.764426 9.988229e+06 \n",
"2017-11-30 21:00:00+00:00 0 1.843918 9.988229e+06 \n",
"2017-12-01 21:00:00+00:00 0 1.813485 9.988229e+06 \n",
"2017-12-04 21:00:00+00:00 0 1.765153 9.988229e+06 \n",
"2017-12-05 21:00:00+00:00 0 1.758465 9.988229e+06 \n",
"2017-12-06 21:00:00+00:00 0 1.734808 9.988229e+06 \n",
"2017-12-07 21:00:00+00:00 0 1.748567 9.988229e+06 \n",
"2017-12-08 21:00:00+00:00 0 1.744599 9.988229e+06 \n",
"2017-12-11 21:00:00+00:00 0 1.854754 9.988229e+06 \n",
"2017-12-12 21:00:00+00:00 0 1.817940 9.988229e+06 \n",
"2017-12-13 21:00:00+00:00 0 1.835892 9.988229e+06 \n",
"2017-12-14 21:00:00+00:00 0 1.832971 9.988229e+06 \n",
"2017-12-15 21:00:00+00:00 0 1.887169 9.988229e+06 \n",
"2017-12-18 21:00:00+00:00 0 1.971507 9.988229e+06 \n",
"2017-12-19 21:00:00+00:00 0 1.895963 9.988229e+06 \n",
"2017-12-20 21:00:00+00:00 0 1.888252 9.988229e+06 \n",
"2017-12-21 21:00:00+00:00 0 1.908974 9.988229e+06 \n",
"2017-12-22 21:00:00+00:00 0 1.907702 9.988229e+06 \n",
"2017-12-26 21:00:00+00:00 0 1.704187 9.988229e+06 \n",
"2017-12-27 21:00:00+00:00 0 1.704022 9.988229e+06 \n",
"2017-12-28 21:00:00+00:00 0 1.718340 9.988229e+06 \n",
"2017-12-29 21:00:00+00:00 0 1.648975 9.988229e+06 \n",
"\n",
" starting_exposure starting_value trading_days \\\n",
"2015-01-02 21:00:00+00:00 0.0 0.0 1 \n",
"2015-01-05 21:00:00+00:00 0.0 0.0 2 \n",
"2015-01-06 21:00:00+00:00 0.0 0.0 3 \n",
"2015-01-07 21:00:00+00:00 0.0 0.0 4 \n",
"2015-01-08 21:00:00+00:00 0.0 0.0 5 \n",
"2015-01-09 21:00:00+00:00 0.0 0.0 6 \n",
"2015-01-12 21:00:00+00:00 0.0 0.0 7 \n",
"2015-01-13 21:00:00+00:00 0.0 0.0 8 \n",
"2015-01-14 21:00:00+00:00 0.0 0.0 9 \n",
"2015-01-15 21:00:00+00:00 0.0 0.0 10 \n",
"2015-01-16 21:00:00+00:00 0.0 0.0 11 \n",
"2015-01-20 21:00:00+00:00 0.0 0.0 12 \n",
"2015-01-21 21:00:00+00:00 0.0 0.0 13 \n",
"2015-01-22 21:00:00+00:00 0.0 0.0 14 \n",
"2015-01-23 21:00:00+00:00 0.0 0.0 15 \n",
"2015-01-26 21:00:00+00:00 0.0 0.0 16 \n",
"2015-01-27 21:00:00+00:00 0.0 0.0 17 \n",
"2015-01-28 21:00:00+00:00 0.0 0.0 18 \n",
"2015-01-29 21:00:00+00:00 0.0 0.0 19 \n",
"2015-01-30 21:00:00+00:00 0.0 0.0 20 \n",
"2015-02-02 21:00:00+00:00 0.0 0.0 21 \n",
"2015-02-03 21:00:00+00:00 0.0 0.0 22 \n",
"2015-02-04 21:00:00+00:00 0.0 0.0 23 \n",
"2015-02-05 21:00:00+00:00 0.0 0.0 24 \n",
"2015-02-06 21:00:00+00:00 0.0 0.0 25 \n",
"2015-02-09 21:00:00+00:00 0.0 0.0 26 \n",
"2015-02-10 21:00:00+00:00 0.0 0.0 27 \n",
"2015-02-11 21:00:00+00:00 0.0 0.0 28 \n",
"2015-02-12 21:00:00+00:00 0.0 0.0 29 \n",
"2015-02-13 21:00:00+00:00 0.0 0.0 30 \n",
"... ... ... ... \n",
"2017-11-16 21:00:00+00:00 16908.0 16908.0 726 \n",
"2017-11-17 21:00:00+00:00 17110.0 17110.0 727 \n",
"2017-11-20 21:00:00+00:00 17015.0 17015.0 728 \n",
"2017-11-21 21:00:00+00:00 16998.0 16998.0 729 \n",
"2017-11-22 21:00:00+00:00 17314.0 17314.0 730 \n",
"2017-11-24 18:00:00+00:00 17496.0 17496.0 731 \n",
"2017-11-27 21:00:00+00:00 17497.0 17497.0 732 \n",
"2017-11-28 21:00:00+00:00 17409.0 17409.0 733 \n",
"2017-11-29 21:00:00+00:00 17307.0 17307.0 734 \n",
"2017-11-30 21:00:00+00:00 16948.0 16948.0 735 \n",
"2017-12-01 21:00:00+00:00 17185.0 17185.0 736 \n",
"2017-12-04 21:00:00+00:00 17105.0 17105.0 737 \n",
"2017-12-05 21:00:00+00:00 16980.0 16980.0 738 \n",
"2017-12-06 21:00:00+00:00 16964.0 16964.0 739 \n",
"2017-12-07 21:00:00+00:00 16901.0 16901.0 740 \n",
"2017-12-08 21:00:00+00:00 16945.2 16945.2 741 \n",
"2017-12-11 21:00:00+00:00 16937.0 16937.0 742 \n",
"2017-12-12 21:00:00+00:00 17267.0 17267.0 743 \n",
"2017-12-13 21:00:00+00:00 17170.0 17170.0 744 \n",
"2017-12-14 21:00:00+00:00 17227.0 17227.0 745 \n",
"2017-12-15 21:00:00+00:00 17222.0 17222.0 746 \n",
"2017-12-18 21:00:00+00:00 17387.0 17387.0 747 \n",
"2017-12-19 21:00:00+00:00 17642.0 17642.0 748 \n",
"2017-12-20 21:00:00+00:00 17454.0 17454.0 749 \n",
"2017-12-21 21:00:00+00:00 17435.0 17435.0 750 \n",
"2017-12-22 21:00:00+00:00 17501.0 17501.0 751 \n",
"2017-12-26 21:00:00+00:00 17501.0 17501.0 752 \n",
"2017-12-27 21:00:00+00:00 17057.0 17057.0 753 \n",
"2017-12-28 21:00:00+00:00 17060.0 17060.0 754 \n",
"2017-12-29 21:00:00+00:00 17108.0 17108.0 755 \n",
"\n",
" transactions treasury_period_return \n",
"2015-01-02 21:00:00+00:00 [] 0.0 \n",
"2015-01-05 21:00:00+00:00 [] 0.0 \n",
"2015-01-06 21:00:00+00:00 [] 0.0 \n",
"2015-01-07 21:00:00+00:00 [] 0.0 \n",
"2015-01-08 21:00:00+00:00 [] 0.0 \n",
"2015-01-09 21:00:00+00:00 [] 0.0 \n",
"2015-01-12 21:00:00+00:00 [] 0.0 \n",
"2015-01-13 21:00:00+00:00 [] 0.0 \n",
"2015-01-14 21:00:00+00:00 [] 0.0 \n",
"2015-01-15 21:00:00+00:00 [] 0.0 \n",
"2015-01-16 21:00:00+00:00 [] 0.0 \n",
"2015-01-20 21:00:00+00:00 [] 0.0 \n",
"2015-01-21 21:00:00+00:00 [] 0.0 \n",
"2015-01-22 21:00:00+00:00 [] 0.0 \n",
"2015-01-23 21:00:00+00:00 [] 0.0 \n",
"2015-01-26 21:00:00+00:00 [] 0.0 \n",
"2015-01-27 21:00:00+00:00 [] 0.0 \n",
"2015-01-28 21:00:00+00:00 [] 0.0 \n",
"2015-01-29 21:00:00+00:00 [] 0.0 \n",
"2015-01-30 21:00:00+00:00 [] 0.0 \n",
"2015-02-02 21:00:00+00:00 [] 0.0 \n",
"2015-02-03 21:00:00+00:00 [] 0.0 \n",
"2015-02-04 21:00:00+00:00 [] 0.0 \n",
"2015-02-05 21:00:00+00:00 [] 0.0 \n",
"2015-02-06 21:00:00+00:00 [] 0.0 \n",
"2015-02-09 21:00:00+00:00 [] 0.0 \n",
"2015-02-10 21:00:00+00:00 [] 0.0 \n",
"2015-02-11 21:00:00+00:00 [] 0.0 \n",
"2015-02-12 21:00:00+00:00 [] 0.0 \n",
"2015-02-13 21:00:00+00:00 [] 0.0 \n",
"... ... ... \n",
"2017-11-16 21:00:00+00:00 [] 0.0 \n",
"2017-11-17 21:00:00+00:00 [] 0.0 \n",
"2017-11-20 21:00:00+00:00 [] 0.0 \n",
"2017-11-21 21:00:00+00:00 [] 0.0 \n",
"2017-11-22 21:00:00+00:00 [] 0.0 \n",
"2017-11-24 18:00:00+00:00 [] 0.0 \n",
"2017-11-27 21:00:00+00:00 [] 0.0 \n",
"2017-11-28 21:00:00+00:00 [] 0.0 \n",
"2017-11-29 21:00:00+00:00 [] 0.0 \n",
"2017-11-30 21:00:00+00:00 [] 0.0 \n",
"2017-12-01 21:00:00+00:00 [] 0.0 \n",
"2017-12-04 21:00:00+00:00 [] 0.0 \n",
"2017-12-05 21:00:00+00:00 [] 0.0 \n",
"2017-12-06 21:00:00+00:00 [] 0.0 \n",
"2017-12-07 21:00:00+00:00 [] 0.0 \n",
"2017-12-08 21:00:00+00:00 [] 0.0 \n",
"2017-12-11 21:00:00+00:00 [] 0.0 \n",
"2017-12-12 21:00:00+00:00 [] 0.0 \n",
"2017-12-13 21:00:00+00:00 [] 0.0 \n",
"2017-12-14 21:00:00+00:00 [] 0.0 \n",
"2017-12-15 21:00:00+00:00 [] 0.0 \n",
"2017-12-18 21:00:00+00:00 [] 0.0 \n",
"2017-12-19 21:00:00+00:00 [] 0.0 \n",
"2017-12-20 21:00:00+00:00 [] 0.0 \n",
"2017-12-21 21:00:00+00:00 [] 0.0 \n",
"2017-12-22 21:00:00+00:00 [] 0.0 \n",
"2017-12-26 21:00:00+00:00 [] 0.0 \n",
"2017-12-27 21:00:00+00:00 [] 0.0 \n",
"2017-12-28 21:00:00+00:00 [] 0.0 \n",
"2017-12-29 21:00:00+00:00 [] 0.0 \n",
"\n",
"[755 rows x 40 columns]"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"%%zipline --start 2015-1-1 --end 2018-1-1 -o dma.pickle\n",
"\n",
"from zipline.api import order_target, record, symbol\n",
"import matplotlib.pyplot as plt\n",
"\n",
"def initialize(context):\n",
" context.i = 0\n",
" context.asset = symbol('AAPL')\n",
"\n",
"\n",
"def handle_data(context, data):\n",
" # Skip first 300 days to get full windows\n",
" context.i += 1\n",
" if context.i < 300:\n",
" record(AAPL=data.current(context.asset, 'price'))\n",
" order_target(context.asset, 0)\n",
" return\n",
"\n",
" # Compute averages\n",
" # data.history() has to be called with the same params from above and returns a pandas dataframe.\n",
" short_mavg = data.history(context.asset, 'price', bar_count=100, frequency=\"1d\").mean()\n",
" long_mavg = data.history(context.asset, 'price', bar_count=300, frequency=\"1d\").mean()\n",
"\n",
" # Trading logic\n",
" if short_mavg > long_mavg:\n",
" # order_target will place order for as many shares as needed to reach target quantity\n",
" order_target(context.asset, 100)\n",
" elif short_mavg < long_mavg:\n",
" order_target(context.asset, 0)\n",
"\n",
" # Save values for later inspection\n",
" record(AAPL=data.current(context.asset, 'price'),\n",
" short_mavg=short_mavg,\n",
" long_mavg=long_mavg)\n",
"\n",
"\n",
"def analyze(context, perf):\n",
" fig = plt.figure()\n",
" ax1 = fig.add_subplot(211)\n",
" perf.portfolio_value.plot(ax=ax1)\n",
" ax1.set_ylabel('portfolio value in $')\n",
"\n",
" ax2 = fig.add_subplot(212)\n",
" perf['AAPL'].plot(ax=ax2)\n",
" perf[['short_mavg', 'long_mavg']].plot(ax=ax2)\n",
"\n",
" perf_trans = perf.ix[[t != [] for t in perf.transactions]]\n",
" buys = perf_trans.ix[[t[0]['amount'] > 0 for t in perf_trans.transactions]]\n",
" sells = perf_trans.ix[\n",
" [t[0]['amount'] < 0 for t in perf_trans.transactions]]\n",
" ax2.plot(buys.index, perf.short_mavg.ix[buys.index],\n",
" '^', markersize=10, color='m')\n",
" ax2.plot(sells.index, perf.short_mavg.ix[sells.index],\n",
" 'v', markersize=10, color='k')\n",
" ax2.set_ylabel('price in $')\n",
" plt.legend(loc=0)\n",
" plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"results = _"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>AAPL</th>\n",
" <th>algo_volatility</th>\n",
" <th>algorithm_period_return</th>\n",
" <th>alpha</th>\n",
" <th>benchmark_period_return</th>\n",
" <th>benchmark_volatility</th>\n",
" <th>beta</th>\n",
" <th>capital_used</th>\n",
" <th>ending_cash</th>\n",
" <th>ending_exposure</th>\n",
" <th>...</th>\n",
" <th>short_mavg</th>\n",
" <th>short_value</th>\n",
" <th>shorts_count</th>\n",
" <th>sortino</th>\n",
" <th>starting_cash</th>\n",
" <th>starting_exposure</th>\n",
" <th>starting_value</th>\n",
" <th>trading_days</th>\n",
" <th>transactions</th>\n",
" <th>treasury_period_return</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2015-01-02 21:00:00+00:00</th>\n",
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" <th>2015-01-05 21:00:00+00:00</th>\n",
" <td>106.25</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
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" <td>-0.018585</td>\n",
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" <td>0.0</td>\n",
" <td>2</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-06 21:00:00+00:00</th>\n",
" <td>106.26</td>\n",
" <td>0.0</td>\n",
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" <td>0.0</td>\n",
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" <td>0.0</td>\n",
" <td>3</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-07 21:00:00+00:00</th>\n",
" <td>107.75</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>-0.015715</td>\n",
" <td>0.206972</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>10000000.0</td>\n",
" <td>0.0</td>\n",
" <td>...</td>\n",
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" <td>0</td>\n",
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" <td>4</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015-01-08 21:00:00+00:00</th>\n",
" <td>111.89</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>0.001751</td>\n",
" <td>0.236040</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>10000000.0</td>\n",
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" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>NaN</td>\n",
" <td>10000000.0</td>\n",
" <td>0.0</td>\n",
" <td>0.0</td>\n",
" <td>5</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows × 40 columns</p>\n",
"</div>"
],
"text/plain": [
" AAPL algo_volatility algorithm_period_return \\\n",
"2015-01-02 21:00:00+00:00 109.33 NaN 0.0 \n",
"2015-01-05 21:00:00+00:00 106.25 0.0 0.0 \n",
"2015-01-06 21:00:00+00:00 106.26 0.0 0.0 \n",
"2015-01-07 21:00:00+00:00 107.75 0.0 0.0 \n",
"2015-01-08 21:00:00+00:00 111.89 0.0 0.0 \n",
"\n",
" alpha benchmark_period_return \\\n",
"2015-01-02 21:00:00+00:00 NaN -0.000535 \n",
"2015-01-05 21:00:00+00:00 0.0 -0.018585 \n",
"2015-01-06 21:00:00+00:00 0.0 -0.027829 \n",
"2015-01-07 21:00:00+00:00 0.0 -0.015715 \n",
"2015-01-08 21:00:00+00:00 0.0 0.001751 \n",
"\n",
" benchmark_volatility beta capital_used \\\n",
"2015-01-02 21:00:00+00:00 NaN NaN 0.0 \n",
"2015-01-05 21:00:00+00:00 0.196712 0.0 0.0 \n",
"2015-01-06 21:00:00+00:00 0.139101 0.0 0.0 \n",
"2015-01-07 21:00:00+00:00 0.206972 0.0 0.0 \n",
"2015-01-08 21:00:00+00:00 0.236040 0.0 0.0 \n",
"\n",
" ending_cash ending_exposure \\\n",
"2015-01-02 21:00:00+00:00 10000000.0 0.0 \n",
"2015-01-05 21:00:00+00:00 10000000.0 0.0 \n",
"2015-01-06 21:00:00+00:00 10000000.0 0.0 \n",
"2015-01-07 21:00:00+00:00 10000000.0 0.0 \n",
"2015-01-08 21:00:00+00:00 10000000.0 0.0 \n",
"\n",
" ... short_mavg short_value \\\n",
"2015-01-02 21:00:00+00:00 ... NaN 0.0 \n",
"2015-01-05 21:00:00+00:00 ... NaN 0.0 \n",
"2015-01-06 21:00:00+00:00 ... NaN 0.0 \n",
"2015-01-07 21:00:00+00:00 ... NaN 0.0 \n",
"2015-01-08 21:00:00+00:00 ... NaN 0.0 \n",
"\n",
" shorts_count sortino starting_cash \\\n",
"2015-01-02 21:00:00+00:00 0 NaN 10000000.0 \n",
"2015-01-05 21:00:00+00:00 0 NaN 10000000.0 \n",
"2015-01-06 21:00:00+00:00 0 NaN 10000000.0 \n",
"2015-01-07 21:00:00+00:00 0 NaN 10000000.0 \n",
"2015-01-08 21:00:00+00:00 0 NaN 10000000.0 \n",
"\n",
" starting_exposure starting_value trading_days \\\n",
"2015-01-02 21:00:00+00:00 0.0 0.0 1 \n",
"2015-01-05 21:00:00+00:00 0.0 0.0 2 \n",
"2015-01-06 21:00:00+00:00 0.0 0.0 3 \n",
"2015-01-07 21:00:00+00:00 0.0 0.0 4 \n",
"2015-01-08 21:00:00+00:00 0.0 0.0 5 \n",
"\n",
" transactions treasury_period_return \n",
"2015-01-02 21:00:00+00:00 [] 0.0 \n",
"2015-01-05 21:00:00+00:00 [] 0.0 \n",
"2015-01-06 21:00:00+00:00 [] 0.0 \n",
"2015-01-07 21:00:00+00:00 [] 0.0 \n",
"2015-01-08 21:00:00+00:00 [] 0.0 \n",
"\n",
"[5 rows x 40 columns]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
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"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>AAPL</th>\n",
" <th>algo_volatility</th>\n",
" <th>algorithm_period_return</th>\n",
" <th>alpha</th>\n",
" <th>benchmark_period_return</th>\n",
" <th>benchmark_volatility</th>\n",
" <th>beta</th>\n",
" <th>capital_used</th>\n",
" <th>ending_cash</th>\n",
" <th>ending_exposure</th>\n",
" <th>...</th>\n",
" <th>short_mavg</th>\n",
" <th>short_value</th>\n",
" <th>shorts_count</th>\n",
" <th>sortino</th>\n",
" <th>starting_cash</th>\n",
" <th>starting_exposure</th>\n",
" <th>starting_value</th>\n",
" <th>trading_days</th>\n",
" <th>transactions</th>\n",
" <th>treasury_period_return</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2017-12-22 21:00:00+00:00</th>\n",
" <td>175.01</td>\n",
" <td>0.000161</td>\n",
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" <td>0.000170</td>\n",
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" <td>0</td>\n",
" <td>1.907702</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17501.0</td>\n",
" <td>17501.0</td>\n",
" <td>751</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-26 21:00:00+00:00</th>\n",
" <td>170.57</td>\n",
" <td>0.000163</td>\n",
" <td>0.000529</td>\n",
" <td>0.000155</td>\n",
" <td>0.299942</td>\n",
" <td>0.124128</td>\n",
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" <td>9.988229e+06</td>\n",
" <td>17057.0</td>\n",
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" <td>163.598270</td>\n",
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" <td>0</td>\n",
" <td>1.704187</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17501.0</td>\n",
" <td>17501.0</td>\n",
" <td>752</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-27 21:00:00+00:00</th>\n",
" <td>170.60</td>\n",
" <td>0.000163</td>\n",
" <td>0.000529</td>\n",
" <td>0.000155</td>\n",
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" <td>1.704022</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17057.0</td>\n",
" <td>17057.0</td>\n",
" <td>753</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-28 21:00:00+00:00</th>\n",
" <td>171.08</td>\n",
" <td>0.000163</td>\n",
" <td>0.000534</td>\n",
" <td>0.000156</td>\n",
" <td>0.303250</td>\n",
" <td>0.123966</td>\n",
" <td>0.000232</td>\n",
" <td>0.0</td>\n",
" <td>9.988229e+06</td>\n",
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" <td>0</td>\n",
" <td>1.718340</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17060.0</td>\n",
" <td>17060.0</td>\n",
" <td>754</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017-12-29 21:00:00+00:00</th>\n",
" <td>169.23</td>\n",
" <td>0.000163</td>\n",
" <td>0.000515</td>\n",
" <td>0.000150</td>\n",
" <td>0.298336</td>\n",
" <td>0.123907</td>\n",
" <td>0.000234</td>\n",
" <td>0.0</td>\n",
" <td>9.988229e+06</td>\n",
" <td>16923.0</td>\n",
" <td>...</td>\n",
" <td>163.997270</td>\n",
" <td>0.0</td>\n",
" <td>0</td>\n",
" <td>1.648975</td>\n",
" <td>9.988229e+06</td>\n",
" <td>17108.0</td>\n",
" <td>17108.0</td>\n",
" <td>755</td>\n",
" <td>[]</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
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"</table>\n",
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"</div>"
],
"text/plain": [
" AAPL algo_volatility algorithm_period_return \\\n",
"2017-12-22 21:00:00+00:00 175.01 0.000161 0.000573 \n",
"2017-12-26 21:00:00+00:00 170.57 0.000163 0.000529 \n",
"2017-12-27 21:00:00+00:00 170.60 0.000163 0.000529 \n",
"2017-12-28 21:00:00+00:00 171.08 0.000163 0.000534 \n",
"2017-12-29 21:00:00+00:00 169.23 0.000163 0.000515 \n",
"\n",
" alpha benchmark_period_return \\\n",
"2017-12-22 21:00:00+00:00 0.000170 0.301498 \n",
"2017-12-26 21:00:00+00:00 0.000155 0.299942 \n",
"2017-12-27 21:00:00+00:00 0.000155 0.300574 \n",
"2017-12-28 21:00:00+00:00 0.000156 0.303250 \n",
"2017-12-29 21:00:00+00:00 0.000150 0.298336 \n",
"\n",
" benchmark_volatility beta capital_used \\\n",
"2017-12-22 21:00:00+00:00 0.124207 0.000230 0.0 \n",
"2017-12-26 21:00:00+00:00 0.124128 0.000232 0.0 \n",
"2017-12-27 21:00:00+00:00 0.124045 0.000232 0.0 \n",
"2017-12-28 21:00:00+00:00 0.123966 0.000232 0.0 \n",
"2017-12-29 21:00:00+00:00 0.123907 0.000234 0.0 \n",
"\n",
" ending_cash ending_exposure \\\n",
"2017-12-22 21:00:00+00:00 9.988229e+06 17501.0 \n",
"2017-12-26 21:00:00+00:00 9.988229e+06 17057.0 \n",
"2017-12-27 21:00:00+00:00 9.988229e+06 17060.0 \n",
"2017-12-28 21:00:00+00:00 9.988229e+06 17108.0 \n",
"2017-12-29 21:00:00+00:00 9.988229e+06 16923.0 \n",
"\n",
" ... short_mavg short_value \\\n",
"2017-12-22 21:00:00+00:00 ... 163.442180 0.0 \n",
"2017-12-26 21:00:00+00:00 ... 163.598270 0.0 \n",
"2017-12-27 21:00:00+00:00 ... 163.746493 0.0 \n",
"2017-12-28 21:00:00+00:00 ... 163.899510 0.0 \n",
"2017-12-29 21:00:00+00:00 ... 163.997270 0.0 \n",
"\n",
" shorts_count sortino starting_cash \\\n",
"2017-12-22 21:00:00+00:00 0 1.907702 9.988229e+06 \n",
"2017-12-26 21:00:00+00:00 0 1.704187 9.988229e+06 \n",
"2017-12-27 21:00:00+00:00 0 1.704022 9.988229e+06 \n",
"2017-12-28 21:00:00+00:00 0 1.718340 9.988229e+06 \n",
"2017-12-29 21:00:00+00:00 0 1.648975 9.988229e+06 \n",
"\n",
" starting_exposure starting_value trading_days \\\n",
"2017-12-22 21:00:00+00:00 17501.0 17501.0 751 \n",
"2017-12-26 21:00:00+00:00 17501.0 17501.0 752 \n",
"2017-12-27 21:00:00+00:00 17057.0 17057.0 753 \n",
"2017-12-28 21:00:00+00:00 17060.0 17060.0 754 \n",
"2017-12-29 21:00:00+00:00 17108.0 17108.0 755 \n",
"\n",
" transactions treasury_period_return \n",
"2017-12-22 21:00:00+00:00 [] 0.0 \n",
"2017-12-26 21:00:00+00:00 [] 0.0 \n",
"2017-12-27 21:00:00+00:00 [] 0.0 \n",
"2017-12-28 21:00:00+00:00 [] 0.0 \n",
"2017-12-29 21:00:00+00:00 [] 0.0 \n",
"\n",
"[5 rows x 40 columns]"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"display(results.head())\n",
"display(results.tail())"
]
}
],
"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": "3.5.8"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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