BehaviorAnalysis_forShawn.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import sys\n",
    "sys.path.append(\"/Users/dorisv/Documents/imaging_behavior\")\n",
    "sys.path.append(\"C:\\Users\\dorisv\\Desktop\\Shawn's data\")\n",
    "\n",
    "try:\n",
    "    import aibs\n",
    "except:\n",
    "    import aibs\n",
    "    \n",
    "from aibs.dev.shawndev import FileTools\n",
    "from aibs.dev.shawndev.BehaviorEvents import BehaviorEvents\n",
    "from aibs.Analysis.InDevelopment import ForageSession\n",
    "from aibs.dev.shawndev import Forage, Psychometrics, ForageTools, FileTools\n",
    "%matplotlib inline\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import seaborn\n",
    "pd.set_option('display.notebook_repr_html',True)\n",
    "pd.set_option('display.width', 200)\n",
    "pd.set_option('display.max_rows', 30)\n",
    "pd.set_option('display.notebook_repr_html',True)\n",
    "%matplotlib inline\n",
    "import matplotlib\n",
    "import os\n",
    "from scipy.misc import comb\n",
    "import scipy.stats\n",
    "\n",
    "import imaging_behavior as im\n",
    "import imaging_behavior.plotting.plotting_functions as pf\n",
    "import imaging_behavior.plotting.utilities as pu\n",
    "from aibs.Analysis.Core import smooth\n",
    "\n",
    "from scipy.optimize import minimize\n",
    "from scipy.optimize import basinhopping\n",
    "import math\n",
    "from math import log\n",
    "from numpy import linalg as LA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Anaconda\\lib\\site-packages\\IPython\\nbformat\\current.py:19: UserWarning: IPython.nbformat.current is deprecated.\n",
      "\n",
      "- use IPython.nbformat for read/write/validate public API\n",
      "- use IPython.nbformat.vX directly to composing notebooks of a particular version\n",
      "\n",
      "  \"\"\")\n"
     ]
    }
   ],
   "source": [
    "#load data\n",
    "import io\n",
    "from IPython.nbformat import current\n",
    "\n",
    "def execute_notebook(nbfile):\n",
    "    \n",
    "    with io.open(nbfile) as f:\n",
    "        nb = current.read(f, 'json')\n",
    "    \n",
    "    ip = get_ipython()\n",
    "    \n",
    "    for cell in nb.worksheets[0].cells:\n",
    "        if cell.cell_type != 'code':\n",
    "            continue\n",
    "        ip.run_cell(cell.input)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Image</th>\n",
       "      <th>Ori</th>\n",
       "      <th>PosY</th>\n",
       "      <th>Size</th>\n",
       "      <th>abs_reward_rate</th>\n",
       "      <th>average_speed</th>\n",
       "      <th>duration</th>\n",
       "      <th>end_frame</th>\n",
       "      <th>end_time</th>\n",
       "      <th>first_lick_latency_0</th>\n",
       "      <th>...</th>\n",
       "      <th>lick_times_1</th>\n",
       "      <th>mouse_id</th>\n",
       "      <th>number_of_licks_0</th>\n",
       "      <th>number_of_licks_1</th>\n",
       "      <th>number_of_rewards</th>\n",
       "      <th>reward_times</th>\n",
       "      <th>start_date_time</th>\n",
       "      <th>start_frame</th>\n",
       "      <th>start_time</th>\n",
       "      <th>stop_date_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0   </th>\n",
       "      <td>     bird</td>\n",
       "      <td>-15</td>\n",
       "      <td> 0</td>\n",
       "      <td> 550</td>\n",
       "      <td> 1.408580</td>\n",
       "      <td> 54.905943</td>\n",
       "      <td> 1.742769</td>\n",
       "      <td>    104</td>\n",
       "      <td>    1.742769</td>\n",
       "      <td>      NaN</td>\n",
       "      <td>...</td>\n",
       "      <td> []</td>\n",
       "      <td> M130587</td>\n",
       "      <td>  0</td>\n",
       "      <td> 0</td>\n",
       "      <td> 0</td>\n",
       "      <td>              []</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "      <td>      0</td>\n",
       "      <td>    0.000000</td>\n",
       "      <td> 2014-10-03 14:49:45.315000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1   </th>\n",
       "      <td>     bird</td>\n",
       "      <td>  0</td>\n",
       "      <td> 0</td>\n",
       "      <td> 400</td>\n",
       "      <td> 1.408580</td>\n",
       "      <td> 74.060865</td>\n",
       "      <td> 1.182906</td>\n",
       "      <td>    175</td>\n",
       "      <td>    2.925675</td>\n",
       "      <td>      NaN</td>\n",
       "      <td>...</td>\n",
       "      <td> []</td>\n",
       "      <td> M130587</td>\n",
       "      <td>  0</td>\n",
       "      <td> 0</td>\n",
       "      <td> 0</td>\n",
       "      <td>              []</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "      <td>    105</td>\n",
       "      <td>    1.742769</td>\n",
       "      <td> 2014-10-03 14:49:45.315000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2   </th>\n",
       "      <td>     bird</td>\n",
       "      <td>-15</td>\n",
       "      <td> 0</td>\n",
       "      <td> 550</td>\n",
       "      <td> 1.373647</td>\n",
       "      <td> 75.229013</td>\n",
       "      <td> 1.250163</td>\n",
       "      <td>    250</td>\n",
       "      <td>    4.175839</td>\n",
       "      <td>      NaN</td>\n",
       "      <td>...</td>\n",
       "      <td> []</td>\n",
       "      <td> M130587</td>\n",
       "      <td>  0</td>\n",
       "      <td> 0</td>\n",
       "      <td> 0</td>\n",
       "      <td>              []</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "      <td>    176</td>\n",
       "      <td>    2.925675</td>\n",
       "      <td> 2014-10-03 14:49:45.315000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3   </th>\n",
       "      <td>     bird</td>\n",
       "      <td>  0</td>\n",
       "      <td> 0</td>\n",
       "      <td> 350</td>\n",
       "      <td> 1.317835</td>\n",
       "      <td> 45.388544</td>\n",
       "      <td> 3.349858</td>\n",
       "      <td>    451</td>\n",
       "      <td>    7.525696</td>\n",
       "      <td>      NaN</td>\n",
       "      <td>...</td>\n",
       "      <td> []</td>\n",
       "      <td> M130587</td>\n",
       "      <td>  0</td>\n",
       "      <td> 0</td>\n",
       "      <td> 0</td>\n",
       "      <td>              []</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "      <td>    251</td>\n",
       "      <td>    4.175839</td>\n",
       "      <td> 2014-10-03 14:49:45.315000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4   </th>\n",
       "      <td>     bird</td>\n",
       "      <td> 45</td>\n",
       "      <td> 0</td>\n",
       "      <td> 550</td>\n",
       "      <td> 1.261059</td>\n",
       "      <td> 25.822834</td>\n",
       "      <td> 5.015883</td>\n",
       "      <td>    752</td>\n",
       "      <td>   12.541580</td>\n",
       "      <td>      NaN</td>\n",
       "      <td>...</td>\n",
       "      <td> []</td>\n",
       "      <td> M130587</td>\n",
       "      <td>  0</td>\n",
       "      <td> 0</td>\n",
       "      <td> 0</td>\n",
       "      <td>              []</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "      <td>    452</td>\n",
       "      <td>    7.525696</td>\n",
       "      <td> 2014-10-03 14:49:45.315000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5   </th>\n",
       "      <td>     bird</td>\n",
       "      <td>  0</td>\n",
       "      <td> 0</td>\n",
       "      <td> 450</td>\n",
       "      <td> 1.214683</td>\n",
       "      <td> 84.197297</td>\n",
       "      <td> 1.483320</td>\n",
       "      <td>    841</td>\n",
       "      <td>   14.024900</td>\n",
       "      <td>      NaN</td>\n",
       "      <td>...</td>\n",
       "      <td> []</td>\n",
       "      <td> M130587</td>\n",
       "      <td>  0</td>\n",
       "      <td> 0</td>\n",
       "      <td> 0</td>\n",
       "      <td>              []</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "      <td>    753</td>\n",
       "      <td>   12.541580</td>\n",
       "      <td> 2014-10-03 14:49:45.315000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6   </th>\n",
       "      <td>     bird</td>\n",
       "      <td> 45</td>\n",
       "      <td> 0</td>\n",
       "      <td> 550</td>\n",
       "      <td> 1.167418</td>\n",
       "      <td> 70.252978</td>\n",
       "      <td> 2.033290</td>\n",
       "      <td>    963</td>\n",
       "      <td>   16.058190</td>\n",
       "      <td>      NaN</td>\n",
       "      <td>...</td>\n",
       "      <td> []</td>\n",
       "      <td> M130587</td>\n",
       "      <td>  0</td>\n",
       "      <td> 0</td>\n",
       "      <td> 0</td>\n",
       "      <td>              []</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "      <td>    842</td>\n",
       "      <td>   14.024900</td>\n",
       "      <td> 2014-10-03 14:49:45.315000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7   </th>\n",
       "      <td>     bird</td>\n",
       "      <td>-15</td>\n",
       "      <td> 0</td>\n",
       "      <td> 600</td>\n",
       "      <td> 1.084758</td>\n",
       "      <td> 63.358064</td>\n",
       "      <td> 2.100066</td>\n",
       "      <td>   1089</td>\n",
       "      <td>   18.158257</td>\n",
       "      <td>      NaN</td>\n",
       "      <td>...</td>\n",
       "      <td> []</td>\n",
       "      <td> M130587</td>\n",
       "      <td>  0</td>\n",
       "      <td> 0</td>\n",
       "      <td> 0</td>\n",
       "      <td>              []</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "      <td>    964</td>\n",
       "      <td>   16.058190</td>\n",
       "      <td> 2014-10-03 14:49:45.315000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8   </th>\n",
       "      <td>     bird</td>\n",
       "      <td> 45</td>\n",
       "      <td> 0</td>\n",
       "      <td> 400</td>\n",
       "      <td> 1.052723</td>\n",
       "      <td> 36.910872</td>\n",
       "      <td> 4.915870</td>\n",
       "      <td>   1384</td>\n",
       "      <td>   23.074127</td>\n",
       "      <td>      NaN</td>\n",
       "      <td>...</td>\n",
       "      <td> []</td>\n",
       "      <td> M130587</td>\n",
       "      <td>  0</td>\n",
       "      <td> 0</td>\n",
       "      <td> 0</td>\n",
       "      <td>              []</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "      <td>   1090</td>\n",
       "      <td>   18.158257</td>\n",
       "      <td> 2014-10-03 14:49:45.315000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9   </th>\n",
       "      <td>     bird</td>\n",
       "      <td>-15</td>\n",
       "      <td> 0</td>\n",
       "      <td> 400</td>\n",
       "      <td> 1.015602</td>\n",
       "      <td> 51.740277</td>\n",
       "      <td> 2.800250</td>\n",
       "      <td>   1552</td>\n",
       "      <td>   25.874377</td>\n",
       "      <td>      NaN</td>\n",
       "      <td>...</td>\n",
       "      <td> []</td>\n",
       "      <td> M130587</td>\n",
       "      <td>  0</td>\n",
       "      <td> 0</td>\n",
       "      <td> 0</td>\n",
       "      <td>              []</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "      <td>   1385</td>\n",
       "      <td>   23.074127</td>\n",
       "      <td> 2014-10-03 14:49:45.315000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10  </th>\n",
       "      <td> mushroom</td>\n",
       "      <td> 15</td>\n",
       "      <td> 0</td>\n",
       "      <td> 400</td>\n",
       "      <td> 0.980743</td>\n",
       "      <td> 24.475602</td>\n",
       "      <td> 4.299668</td>\n",
       "      <td>   1810</td>\n",
       "      <td>   30.174045</td>\n",
       "      <td> 2.364923</td>\n",
       "      <td>...</td>\n",
       "      <td> []</td>\n",
       "      <td> M130587</td>\n",
       "      <td>  8</td>\n",
       "      <td> 0</td>\n",
       "      <td> 1</td>\n",
       "      <td> [27.6072616137]</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "      <td>   1553</td>\n",
       "      <td>   25.874377</td>\n",
       "      <td> 2014-10-03 14:49:45.315000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11  </th>\n",
       "      <td>     bird</td>\n",
       "      <td>-45</td>\n",
       "      <td> 0</td>\n",
       "      <td> 500</td>\n",
       "      <td> 1.815128</td>\n",
       "      <td> 23.271427</td>\n",
       "      <td> 6.065864</td>\n",
       "      <td>   2174</td>\n",
       "      <td>   36.239909</td>\n",
       "      <td> 4.015518</td>\n",
       "      <td>...</td>\n",
       "      <td> []</td>\n",
       "      <td> M130587</td>\n",
       "      <td>  7</td>\n",
       "      <td> 0</td>\n",
       "      <td> 0</td>\n",
       "      <td>              []</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "      <td>   1811</td>\n",
       "      <td>   30.174045</td>\n",
       "      <td> 2014-10-03 14:49:45.315000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12  </th>\n",
       "      <td>     bird</td>\n",
       "      <td> 15</td>\n",
       "      <td> 0</td>\n",
       "      <td> 400</td>\n",
       "      <td> 1.777927</td>\n",
       "      <td> 15.914975</td>\n",
       "      <td> 8.116695</td>\n",
       "      <td>   2661</td>\n",
       "      <td>   44.356604</td>\n",
       "      <td> 1.500413</td>\n",
       "      <td>...</td>\n",
       "      <td> []</td>\n",
       "      <td> M130587</td>\n",
       "      <td>  2</td>\n",
       "      <td> 0</td>\n",
       "      <td> 0</td>\n",
       "      <td>              []</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "      <td>   2175</td>\n",
       "      <td>   36.239909</td>\n",
       "      <td> 2014-10-03 14:49:45.315000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13  </th>\n",
       "      <td> mushroom</td>\n",
       "      <td> 15</td>\n",
       "      <td> 0</td>\n",
       "      <td> 600</td>\n",
       "      <td> 1.719752</td>\n",
       "      <td> 81.630678</td>\n",
       "      <td> 1.082641</td>\n",
       "      <td>   2726</td>\n",
       "      <td>   45.439246</td>\n",
       "      <td>      NaN</td>\n",
       "      <td>...</td>\n",
       "      <td> []</td>\n",
       "      <td> M130587</td>\n",
       "      <td>  0</td>\n",
       "      <td> 0</td>\n",
       "      <td> 0</td>\n",
       "      <td>              []</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "      <td>   2662</td>\n",
       "      <td>   44.356604</td>\n",
       "      <td> 2014-10-03 14:49:45.315000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14  </th>\n",
       "      <td>     bird</td>\n",
       "      <td> 30</td>\n",
       "      <td> 0</td>\n",
       "      <td> 400</td>\n",
       "      <td> 1.688292</td>\n",
       "      <td> 75.701888</td>\n",
       "      <td> 1.850354</td>\n",
       "      <td>   2837</td>\n",
       "      <td>   47.289600</td>\n",
       "      <td>      NaN</td>\n",
       "      <td>...</td>\n",
       "      <td> []</td>\n",
       "      <td> M130587</td>\n",
       "      <td>  0</td>\n",
       "      <td> 0</td>\n",
       "      <td> 0</td>\n",
       "      <td>              []</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "      <td>   2727</td>\n",
       "      <td>   45.439246</td>\n",
       "      <td> 2014-10-03 14:49:45.315000</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>1275</th>\n",
       "      <td> mushroom</td>\n",
       "      <td> 15</td>\n",
       "      <td> 0</td>\n",
       "      <td> 400</td>\n",
       "      <td> 2.837113</td>\n",
       "      <td> 26.418836</td>\n",
       "      <td> 4.366235</td>\n",
       "      <td> 284423</td>\n",
       "      <td> 4740.058698</td>\n",
       "      <td> 1.983293</td>\n",
       "      <td>...</td>\n",
       "      <td> []</td>\n",
       "      <td> M130587</td>\n",
       "      <td> 11</td>\n",
       "      <td> 0</td>\n",
       "      <td> 1</td>\n",
       "      <td> [4737.39287935]</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "      <td> 284162</td>\n",
       "      <td> 4735.692463</td>\n",
       "      <td> 2014-10-03 14:49:45.315000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1276</th>\n",
       "      <td>     bird</td>\n",
       "      <td>-15</td>\n",
       "      <td> 0</td>\n",
       "      <td> 300</td>\n",
       "      <td> 2.901708</td>\n",
       "      <td> 63.765922</td>\n",
       "      <td> 2.100456</td>\n",
       "      <td> 284549</td>\n",
       "      <td> 4742.159154</td>\n",
       "      <td>      NaN</td>\n",
       "      <td>...</td>\n",
       "      <td> []</td>\n",
       "      <td> M130587</td>\n",
       "      <td>  0</td>\n",
       "      <td> 0</td>\n",
       "      <td> 0</td>\n",
       "      <td>              []</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "      <td> 284424</td>\n",
       "      <td> 4740.058698</td>\n",
       "      <td> 2014-10-03 14:49:45.315000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1277</th>\n",
       "      <td>     bird</td>\n",
       "      <td> 30</td>\n",
       "      <td> 0</td>\n",
       "      <td> 550</td>\n",
       "      <td> 3.511092</td>\n",
       "      <td> 30.668452</td>\n",
       "      <td> 4.549667</td>\n",
       "      <td> 284822</td>\n",
       "      <td> 4746.708821</td>\n",
       "      <td>      NaN</td>\n",
       "      <td>...</td>\n",
       "      <td> []</td>\n",
       "      <td> M130587</td>\n",
       "      <td>  0</td>\n",
       "      <td> 0</td>\n",
       "      <td> 0</td>\n",
       "      <td>              []</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "      <td> 284550</td>\n",
       "      <td> 4742.159154</td>\n",
       "      <td> 2014-10-03 14:49:45.315000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1278</th>\n",
       "      <td>     bird</td>\n",
       "      <td> 30</td>\n",
       "      <td> 0</td>\n",
       "      <td> 550</td>\n",
       "      <td> 3.967242</td>\n",
       "      <td> 59.913858</td>\n",
       "      <td> 1.882753</td>\n",
       "      <td> 284935</td>\n",
       "      <td> 4748.591574</td>\n",
       "      <td>      NaN</td>\n",
       "      <td>...</td>\n",
       "      <td> []</td>\n",
       "      <td> M130587</td>\n",
       "      <td>  0</td>\n",
       "      <td> 0</td>\n",
       "      <td> 0</td>\n",
       "      <td>              []</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "      <td> 284823</td>\n",
       "      <td> 4746.708821</td>\n",
       "      <td> 2014-10-03 14:49:45.315000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1279</th>\n",
       "      <td>     bird</td>\n",
       "      <td>-30</td>\n",
       "      <td> 0</td>\n",
       "      <td> 400</td>\n",
       "      <td> 3.939057</td>\n",
       "      <td> 55.006771</td>\n",
       "      <td> 1.716564</td>\n",
       "      <td> 285038</td>\n",
       "      <td> 4750.308138</td>\n",
       "      <td>      NaN</td>\n",
       "      <td>...</td>\n",
       "      <td> []</td>\n",
       "      <td> M130587</td>\n",
       "      <td>  0</td>\n",
       "      <td> 0</td>\n",
       "      <td> 0</td>\n",
       "      <td>              []</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "      <td> 284936</td>\n",
       "      <td> 4748.591574</td>\n",
       "      <td> 2014-10-03 14:49:45.315000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1280</th>\n",
       "      <td>     bird</td>\n",
       "      <td>  0</td>\n",
       "      <td> 0</td>\n",
       "      <td> 450</td>\n",
       "      <td> 4.146193</td>\n",
       "      <td> 51.320867</td>\n",
       "      <td> 1.916542</td>\n",
       "      <td> 285153</td>\n",
       "      <td> 4752.224680</td>\n",
       "      <td>      NaN</td>\n",
       "      <td>...</td>\n",
       "      <td> []</td>\n",
       "      <td> M130587</td>\n",
       "      <td>  0</td>\n",
       "      <td> 0</td>\n",
       "      <td> 0</td>\n",
       "      <td>              []</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "      <td> 285039</td>\n",
       "      <td> 4750.308138</td>\n",
       "      <td> 2014-10-03 14:49:45.315000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1281</th>\n",
       "      <td>     bird</td>\n",
       "      <td> 30</td>\n",
       "      <td> 0</td>\n",
       "      <td> 500</td>\n",
       "      <td> 4.313428</td>\n",
       "      <td> 46.464892</td>\n",
       "      <td> 1.916420</td>\n",
       "      <td> 285268</td>\n",
       "      <td> 4754.141100</td>\n",
       "      <td>      NaN</td>\n",
       "      <td>...</td>\n",
       "      <td> []</td>\n",
       "      <td> M130587</td>\n",
       "      <td>  0</td>\n",
       "      <td> 0</td>\n",
       "      <td> 0</td>\n",
       "      <td>              []</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "      <td> 285154</td>\n",
       "      <td> 4752.224680</td>\n",
       "      <td> 2014-10-03 14:49:45.315000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1282</th>\n",
       "      <td>     bird</td>\n",
       "      <td>-45</td>\n",
       "      <td> 0</td>\n",
       "      <td> 300</td>\n",
       "      <td> 3.828474</td>\n",
       "      <td> 53.133577</td>\n",
       "      <td> 1.816478</td>\n",
       "      <td> 285377</td>\n",
       "      <td> 4755.957578</td>\n",
       "      <td>      NaN</td>\n",
       "      <td>...</td>\n",
       "      <td> []</td>\n",
       "      <td> M130587</td>\n",
       "      <td>  0</td>\n",
       "      <td> 0</td>\n",
       "      <td> 0</td>\n",
       "      <td>              []</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "      <td> 285269</td>\n",
       "      <td> 4754.141100</td>\n",
       "      <td> 2014-10-03 14:49:45.315000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1283</th>\n",
       "      <td>     bird</td>\n",
       "      <td>-15</td>\n",
       "      <td> 0</td>\n",
       "      <td> 300</td>\n",
       "      <td> 3.925290</td>\n",
       "      <td> 45.073362</td>\n",
       "      <td> 3.700263</td>\n",
       "      <td> 285599</td>\n",
       "      <td> 4759.657841</td>\n",
       "      <td>      NaN</td>\n",
       "      <td>...</td>\n",
       "      <td> []</td>\n",
       "      <td> M130587</td>\n",
       "      <td>  0</td>\n",
       "      <td> 0</td>\n",
       "      <td> 0</td>\n",
       "      <td>              []</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "      <td> 285378</td>\n",
       "      <td> 4755.957578</td>\n",
       "      <td> 2014-10-03 14:49:45.315000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1284</th>\n",
       "      <td>     bird</td>\n",
       "      <td>  0</td>\n",
       "      <td> 0</td>\n",
       "      <td> 400</td>\n",
       "      <td> 4.079184</td>\n",
       "      <td> 28.017221</td>\n",
       "      <td> 5.632619</td>\n",
       "      <td> 285937</td>\n",
       "      <td> 4765.290459</td>\n",
       "      <td>      NaN</td>\n",
       "      <td>...</td>\n",
       "      <td> []</td>\n",
       "      <td> M130587</td>\n",
       "      <td>  0</td>\n",
       "      <td> 0</td>\n",
       "      <td> 0</td>\n",
       "      <td>              []</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "      <td> 285600</td>\n",
       "      <td> 4759.657841</td>\n",
       "      <td> 2014-10-03 14:49:45.315000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1285</th>\n",
       "      <td> mushroom</td>\n",
       "      <td>  0</td>\n",
       "      <td> 0</td>\n",
       "      <td> 500</td>\n",
       "      <td> 4.614564</td>\n",
       "      <td> 32.340502</td>\n",
       "      <td> 4.966122</td>\n",
       "      <td> 286235</td>\n",
       "      <td> 4770.256581</td>\n",
       "      <td> 1.915501</td>\n",
       "      <td>...</td>\n",
       "      <td> []</td>\n",
       "      <td> M130587</td>\n",
       "      <td> 11</td>\n",
       "      <td> 0</td>\n",
       "      <td> 1</td>\n",
       "      <td> [4766.90598388]</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "      <td> 285938</td>\n",
       "      <td> 4765.290459</td>\n",
       "      <td> 2014-10-03 14:49:45.315000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1286</th>\n",
       "      <td> mushroom</td>\n",
       "      <td> 45</td>\n",
       "      <td> 0</td>\n",
       "      <td> 300</td>\n",
       "      <td> 4.956338</td>\n",
       "      <td> 53.609111</td>\n",
       "      <td> 1.750334</td>\n",
       "      <td> 286340</td>\n",
       "      <td> 4772.006915</td>\n",
       "      <td>      NaN</td>\n",
       "      <td>...</td>\n",
       "      <td> []</td>\n",
       "      <td> M130587</td>\n",
       "      <td>  0</td>\n",
       "      <td> 0</td>\n",
       "      <td> 0</td>\n",
       "      <td>              []</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "      <td> 286236</td>\n",
       "      <td> 4770.256581</td>\n",
       "      <td> 2014-10-03 14:49:45.315000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1287</th>\n",
       "      <td> mushroom</td>\n",
       "      <td>-30</td>\n",
       "      <td> 0</td>\n",
       "      <td> 350</td>\n",
       "      <td> 5.159482</td>\n",
       "      <td> 51.750383</td>\n",
       "      <td> 1.716273</td>\n",
       "      <td> 286443</td>\n",
       "      <td> 4773.723188</td>\n",
       "      <td>      NaN</td>\n",
       "      <td>...</td>\n",
       "      <td> []</td>\n",
       "      <td> M130587</td>\n",
       "      <td>  0</td>\n",
       "      <td> 0</td>\n",
       "      <td> 0</td>\n",
       "      <td>              []</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "      <td> 286341</td>\n",
       "      <td> 4772.006915</td>\n",
       "      <td> 2014-10-03 14:49:45.315000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1288</th>\n",
       "      <td> mushroom</td>\n",
       "      <td> 15</td>\n",
       "      <td> 0</td>\n",
       "      <td> 450</td>\n",
       "      <td> 4.462697</td>\n",
       "      <td> 28.700524</td>\n",
       "      <td> 6.949890</td>\n",
       "      <td> 286860</td>\n",
       "      <td> 4780.673079</td>\n",
       "      <td> 1.933304</td>\n",
       "      <td>...</td>\n",
       "      <td> []</td>\n",
       "      <td> M130587</td>\n",
       "      <td> 10</td>\n",
       "      <td> 0</td>\n",
       "      <td> 1</td>\n",
       "      <td> [4775.35651121]</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "      <td> 286444</td>\n",
       "      <td> 4773.723188</td>\n",
       "      <td> 2014-10-03 14:49:45.315000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1289</th>\n",
       "      <td> mushroom</td>\n",
       "      <td>-15</td>\n",
       "      <td> 0</td>\n",
       "      <td> 500</td>\n",
       "      <td> 4.644082</td>\n",
       "      <td> 21.416369</td>\n",
       "      <td> 7.215661</td>\n",
       "      <td> 287293</td>\n",
       "      <td> 4787.888739</td>\n",
       "      <td> 4.349974</td>\n",
       "      <td>...</td>\n",
       "      <td> []</td>\n",
       "      <td> M130587</td>\n",
       "      <td> 10</td>\n",
       "      <td> 0</td>\n",
       "      <td> 1</td>\n",
       "      <td> [4784.73796704]</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "      <td> 286861</td>\n",
       "      <td> 4780.673079</td>\n",
       "      <td> 2014-10-03 14:49:45.315000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1290 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Image  Ori  PosY  Size  abs_reward_rate  average_speed  duration  end_frame     end_time  first_lick_latency_0          ...          lick_times_1 mouse_id number_of_licks_0  \\\n",
       "0         bird  -15     0   550         1.408580      54.905943  1.742769        104     1.742769                   NaN          ...                    []  M130587                 0   \n",
       "1         bird    0     0   400         1.408580      74.060865  1.182906        175     2.925675                   NaN          ...                    []  M130587                 0   \n",
       "2         bird  -15     0   550         1.373647      75.229013  1.250163        250     4.175839                   NaN          ...                    []  M130587                 0   \n",
       "3         bird    0     0   350         1.317835      45.388544  3.349858        451     7.525696                   NaN          ...                    []  M130587                 0   \n",
       "4         bird   45     0   550         1.261059      25.822834  5.015883        752    12.541580                   NaN          ...                    []  M130587                 0   \n",
       "5         bird    0     0   450         1.214683      84.197297  1.483320        841    14.024900                   NaN          ...                    []  M130587                 0   \n",
       "6         bird   45     0   550         1.167418      70.252978  2.033290        963    16.058190                   NaN          ...                    []  M130587                 0   \n",
       "7         bird  -15     0   600         1.084758      63.358064  2.100066       1089    18.158257                   NaN          ...                    []  M130587                 0   \n",
       "8         bird   45     0   400         1.052723      36.910872  4.915870       1384    23.074127                   NaN          ...                    []  M130587                 0   \n",
       "9         bird  -15     0   400         1.015602      51.740277  2.800250       1552    25.874377                   NaN          ...                    []  M130587                 0   \n",
       "10    mushroom   15     0   400         0.980743      24.475602  4.299668       1810    30.174045              2.364923          ...                    []  M130587                 8   \n",
       "11        bird  -45     0   500         1.815128      23.271427  6.065864       2174    36.239909              4.015518          ...                    []  M130587                 7   \n",
       "12        bird   15     0   400         1.777927      15.914975  8.116695       2661    44.356604              1.500413          ...                    []  M130587                 2   \n",
       "13    mushroom   15     0   600         1.719752      81.630678  1.082641       2726    45.439246                   NaN          ...                    []  M130587                 0   \n",
       "14        bird   30     0   400         1.688292      75.701888  1.850354       2837    47.289600                   NaN          ...                    []  M130587                 0   \n",
       "...        ...  ...   ...   ...              ...            ...       ...        ...          ...                   ...          ...                   ...      ...               ...   \n",
       "1275  mushroom   15     0   400         2.837113      26.418836  4.366235     284423  4740.058698              1.983293          ...                    []  M130587                11   \n",
       "1276      bird  -15     0   300         2.901708      63.765922  2.100456     284549  4742.159154                   NaN          ...                    []  M130587                 0   \n",
       "1277      bird   30     0   550         3.511092      30.668452  4.549667     284822  4746.708821                   NaN          ...                    []  M130587                 0   \n",
       "1278      bird   30     0   550         3.967242      59.913858  1.882753     284935  4748.591574                   NaN          ...                    []  M130587                 0   \n",
       "1279      bird  -30     0   400         3.939057      55.006771  1.716564     285038  4750.308138                   NaN          ...                    []  M130587                 0   \n",
       "1280      bird    0     0   450         4.146193      51.320867  1.916542     285153  4752.224680                   NaN          ...                    []  M130587                 0   \n",
       "1281      bird   30     0   500         4.313428      46.464892  1.916420     285268  4754.141100                   NaN          ...                    []  M130587                 0   \n",
       "1282      bird  -45     0   300         3.828474      53.133577  1.816478     285377  4755.957578                   NaN          ...                    []  M130587                 0   \n",
       "1283      bird  -15     0   300         3.925290      45.073362  3.700263     285599  4759.657841                   NaN          ...                    []  M130587                 0   \n",
       "1284      bird    0     0   400         4.079184      28.017221  5.632619     285937  4765.290459                   NaN          ...                    []  M130587                 0   \n",
       "1285  mushroom    0     0   500         4.614564      32.340502  4.966122     286235  4770.256581              1.915501          ...                    []  M130587                11   \n",
       "1286  mushroom   45     0   300         4.956338      53.609111  1.750334     286340  4772.006915                   NaN          ...                    []  M130587                 0   \n",
       "1287  mushroom  -30     0   350         5.159482      51.750383  1.716273     286443  4773.723188                   NaN          ...                    []  M130587                 0   \n",
       "1288  mushroom   15     0   450         4.462697      28.700524  6.949890     286860  4780.673079              1.933304          ...                    []  M130587                10   \n",
       "1289  mushroom  -15     0   500         4.644082      21.416369  7.215661     287293  4787.888739              4.349974          ...                    []  M130587                10   \n",
       "\n",
       "     number_of_licks_1  number_of_rewards     reward_times             start_date_time start_frame   start_time              stop_date_time  \n",
       "0                    0                  0               []  2014-10-03 13:29:50.625000           0     0.000000  2014-10-03 14:49:45.315000  \n",
       "1                    0                  0               []  2014-10-03 13:29:50.625000         105     1.742769  2014-10-03 14:49:45.315000  \n",
       "2                    0                  0               []  2014-10-03 13:29:50.625000         176     2.925675  2014-10-03 14:49:45.315000  \n",
       "3                    0                  0               []  2014-10-03 13:29:50.625000         251     4.175839  2014-10-03 14:49:45.315000  \n",
       "4                    0                  0               []  2014-10-03 13:29:50.625000         452     7.525696  2014-10-03 14:49:45.315000  \n",
       "5                    0                  0               []  2014-10-03 13:29:50.625000         753    12.541580  2014-10-03 14:49:45.315000  \n",
       "6                    0                  0               []  2014-10-03 13:29:50.625000         842    14.024900  2014-10-03 14:49:45.315000  \n",
       "7                    0                  0               []  2014-10-03 13:29:50.625000         964    16.058190  2014-10-03 14:49:45.315000  \n",
       "8                    0                  0               []  2014-10-03 13:29:50.625000        1090    18.158257  2014-10-03 14:49:45.315000  \n",
       "9                    0                  0               []  2014-10-03 13:29:50.625000        1385    23.074127  2014-10-03 14:49:45.315000  \n",
       "10                   0                  1  [27.6072616137]  2014-10-03 13:29:50.625000        1553    25.874377  2014-10-03 14:49:45.315000  \n",
       "11                   0                  0               []  2014-10-03 13:29:50.625000        1811    30.174045  2014-10-03 14:49:45.315000  \n",
       "12                   0                  0               []  2014-10-03 13:29:50.625000        2175    36.239909  2014-10-03 14:49:45.315000  \n",
       "13                   0                  0               []  2014-10-03 13:29:50.625000        2662    44.356604  2014-10-03 14:49:45.315000  \n",
       "14                   0                  0               []  2014-10-03 13:29:50.625000        2727    45.439246  2014-10-03 14:49:45.315000  \n",
       "...                ...                ...              ...                         ...         ...          ...                         ...  \n",
       "1275                 0                  1  [4737.39287935]  2014-10-03 13:29:50.625000      284162  4735.692463  2014-10-03 14:49:45.315000  \n",
       "1276                 0                  0               []  2014-10-03 13:29:50.625000      284424  4740.058698  2014-10-03 14:49:45.315000  \n",
       "1277                 0                  0               []  2014-10-03 13:29:50.625000      284550  4742.159154  2014-10-03 14:49:45.315000  \n",
       "1278                 0                  0               []  2014-10-03 13:29:50.625000      284823  4746.708821  2014-10-03 14:49:45.315000  \n",
       "1279                 0                  0               []  2014-10-03 13:29:50.625000      284936  4748.591574  2014-10-03 14:49:45.315000  \n",
       "1280                 0                  0               []  2014-10-03 13:29:50.625000      285039  4750.308138  2014-10-03 14:49:45.315000  \n",
       "1281                 0                  0               []  2014-10-03 13:29:50.625000      285154  4752.224680  2014-10-03 14:49:45.315000  \n",
       "1282                 0                  0               []  2014-10-03 13:29:50.625000      285269  4754.141100  2014-10-03 14:49:45.315000  \n",
       "1283                 0                  0               []  2014-10-03 13:29:50.625000      285378  4755.957578  2014-10-03 14:49:45.315000  \n",
       "1284                 0                  0               []  2014-10-03 13:29:50.625000      285600  4759.657841  2014-10-03 14:49:45.315000  \n",
       "1285                 0                  1  [4766.90598388]  2014-10-03 13:29:50.625000      285938  4765.290459  2014-10-03 14:49:45.315000  \n",
       "1286                 0                  0               []  2014-10-03 13:29:50.625000      286236  4770.256581  2014-10-03 14:49:45.315000  \n",
       "1287                 0                  0               []  2014-10-03 13:29:50.625000      286341  4772.006915  2014-10-03 14:49:45.315000  \n",
       "1288                 0                  1  [4775.35651121]  2014-10-03 13:29:50.625000      286444  4773.723188  2014-10-03 14:49:45.315000  \n",
       "1289                 0                  1  [4784.73796704]  2014-10-03 13:29:50.625000      286861  4780.673079  2014-10-03 14:49:45.315000  \n",
       "\n",
       "[1290 rows x 28 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Size</th>\n",
       "      <th>Image</th>\n",
       "      <th>Ori</th>\n",
       "      <th>PosY</th>\n",
       "      <th>trial</th>\n",
       "      <th>time</th>\n",
       "      <th>terraincode</th>\n",
       "      <th>pausetime</th>\n",
       "      <th>choice</th>\n",
       "      <th>selectiontime</th>\n",
       "      <th>istarget</th>\n",
       "      <th>speed</th>\n",
       "      <th>lapdistance</th>\n",
       "      <th>timebeforezone</th>\n",
       "      <th>slowing_f</th>\n",
       "      <th>mouse</th>\n",
       "      <th>date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0   </th>\n",
       "      <td> 400</td>\n",
       "      <td>     bird</td>\n",
       "      <td>  0</td>\n",
       "      <td> 0</td>\n",
       "      <td>    1</td>\n",
       "      <td>    1.840244</td>\n",
       "      <td> 53</td>\n",
       "      <td> 0.267095</td>\n",
       "      <td> False</td>\n",
       "      <td> 1</td>\n",
       "      <td> False</td>\n",
       "      <td> 2152.301946</td>\n",
       "      <td> 3937</td>\n",
       "      <td> 0.099917</td>\n",
       "      <td>  1.151120</td>\n",
       "      <td> M130587</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1   </th>\n",
       "      <td> 550</td>\n",
       "      <td>     bird</td>\n",
       "      <td>-15</td>\n",
       "      <td> 0</td>\n",
       "      <td>    2</td>\n",
       "      <td>    3.024151</td>\n",
       "      <td> 36</td>\n",
       "      <td> 0.268031</td>\n",
       "      <td> False</td>\n",
       "      <td> 1</td>\n",
       "      <td> False</td>\n",
       "      <td> 2155.681332</td>\n",
       "      <td> 2455</td>\n",
       "      <td> 0.100434</td>\n",
       "      <td>  0.995480</td>\n",
       "      <td> M130587</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2   </th>\n",
       "      <td> 350</td>\n",
       "      <td>     bird</td>\n",
       "      <td>  0</td>\n",
       "      <td> 0</td>\n",
       "      <td>    3</td>\n",
       "      <td>    4.273621</td>\n",
       "      <td> 54</td>\n",
       "      <td> 0.399960</td>\n",
       "      <td> False</td>\n",
       "      <td> 1</td>\n",
       "      <td> False</td>\n",
       "      <td> 1231.647159</td>\n",
       "      <td> 2661</td>\n",
       "      <td> 0.115117</td>\n",
       "      <td>  1.148952</td>\n",
       "      <td> M130587</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3   </th>\n",
       "      <td> 550</td>\n",
       "      <td>     bird</td>\n",
       "      <td> 45</td>\n",
       "      <td> 0</td>\n",
       "      <td>    4</td>\n",
       "      <td>    7.623390</td>\n",
       "      <td> 92</td>\n",
       "      <td> 0.667990</td>\n",
       "      <td> False</td>\n",
       "      <td> 1</td>\n",
       "      <td> False</td>\n",
       "      <td> 1416.589407</td>\n",
       "      <td> 4376</td>\n",
       "      <td> 0.200129</td>\n",
       "      <td> 11.667522</td>\n",
       "      <td> M130587</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4   </th>\n",
       "      <td> 450</td>\n",
       "      <td>     bird</td>\n",
       "      <td>  0</td>\n",
       "      <td> 0</td>\n",
       "      <td>    5</td>\n",
       "      <td>   12.638539</td>\n",
       "      <td> 52</td>\n",
       "      <td> 0.232075</td>\n",
       "      <td> False</td>\n",
       "      <td> 1</td>\n",
       "      <td> False</td>\n",
       "      <td> 2709.459253</td>\n",
       "      <td> 3349</td>\n",
       "      <td> 0.115528</td>\n",
       "      <td>  0.995757</td>\n",
       "      <td> M130587</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5   </th>\n",
       "      <td> 550</td>\n",
       "      <td>     bird</td>\n",
       "      <td> 45</td>\n",
       "      <td> 0</td>\n",
       "      <td>    6</td>\n",
       "      <td>   14.122473</td>\n",
       "      <td> 92</td>\n",
       "      <td> 0.249965</td>\n",
       "      <td> False</td>\n",
       "      <td> 1</td>\n",
       "      <td> False</td>\n",
       "      <td> 1959.213561</td>\n",
       "      <td> 3544</td>\n",
       "      <td> 0.083261</td>\n",
       "      <td>  1.200958</td>\n",
       "      <td> M130587</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6   </th>\n",
       "      <td> 600</td>\n",
       "      <td>     bird</td>\n",
       "      <td>-15</td>\n",
       "      <td> 0</td>\n",
       "      <td>    7</td>\n",
       "      <td>   16.155746</td>\n",
       "      <td> 35</td>\n",
       "      <td> 0.314834</td>\n",
       "      <td> False</td>\n",
       "      <td> 1</td>\n",
       "      <td> False</td>\n",
       "      <td> 1996.971224</td>\n",
       "      <td> 4097</td>\n",
       "      <td> 0.150395</td>\n",
       "      <td>  0.997373</td>\n",
       "      <td> M130587</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7   </th>\n",
       "      <td> 400</td>\n",
       "      <td>     bird</td>\n",
       "      <td> 45</td>\n",
       "      <td> 0</td>\n",
       "      <td>    8</td>\n",
       "      <td>   18.256180</td>\n",
       "      <td> 95</td>\n",
       "      <td> 0.832834</td>\n",
       "      <td> False</td>\n",
       "      <td> 1</td>\n",
       "      <td> False</td>\n",
       "      <td> 1103.000564</td>\n",
       "      <td> 3796</td>\n",
       "      <td> 0.132865</td>\n",
       "      <td>  1.263148</td>\n",
       "      <td> M130587</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8   </th>\n",
       "      <td> 400</td>\n",
       "      <td>     bird</td>\n",
       "      <td>-15</td>\n",
       "      <td> 0</td>\n",
       "      <td>    9</td>\n",
       "      <td>   23.172326</td>\n",
       "      <td> 39</td>\n",
       "      <td> 0.384844</td>\n",
       "      <td> False</td>\n",
       "      <td> 1</td>\n",
       "      <td> False</td>\n",
       "      <td> 1537.117166</td>\n",
       "      <td> 5221</td>\n",
       "      <td> 0.150351</td>\n",
       "      <td>  0.998283</td>\n",
       "      <td> M130587</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9   </th>\n",
       "      <td> 400</td>\n",
       "      <td> mushroom</td>\n",
       "      <td> 15</td>\n",
       "      <td> 0</td>\n",
       "      <td>   10</td>\n",
       "      <td>   25.971682</td>\n",
       "      <td> 60</td>\n",
       "      <td> 2.282713</td>\n",
       "      <td>  True</td>\n",
       "      <td> 1</td>\n",
       "      <td>  True</td>\n",
       "      <td> 1009.442921</td>\n",
       "      <td> 4172</td>\n",
       "      <td> 0.165107</td>\n",
       "      <td>  1.319022</td>\n",
       "      <td> M130587</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10  </th>\n",
       "      <td> 500</td>\n",
       "      <td>     bird</td>\n",
       "      <td>-45</td>\n",
       "      <td> 0</td>\n",
       "      <td>   11</td>\n",
       "      <td>   30.271798</td>\n",
       "      <td>  9</td>\n",
       "      <td> 0.384991</td>\n",
       "      <td> False</td>\n",
       "      <td> 1</td>\n",
       "      <td> False</td>\n",
       "      <td>  479.653339</td>\n",
       "      <td> 2654</td>\n",
       "      <td> 0.132996</td>\n",
       "      <td>  0.751802</td>\n",
       "      <td> M130587</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11  </th>\n",
       "      <td> 400</td>\n",
       "      <td>     bird</td>\n",
       "      <td> 15</td>\n",
       "      <td> 0</td>\n",
       "      <td>   12</td>\n",
       "      <td>   36.338231</td>\n",
       "      <td> 67</td>\n",
       "      <td> 5.199634</td>\n",
       "      <td>  True</td>\n",
       "      <td> 1</td>\n",
       "      <td> False</td>\n",
       "      <td> 1134.592683</td>\n",
       "      <td> 3835</td>\n",
       "      <td> 0.200371</td>\n",
       "      <td>  0.997547</td>\n",
       "      <td> M130587</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12  </th>\n",
       "      <td> 600</td>\n",
       "      <td> mushroom</td>\n",
       "      <td> 15</td>\n",
       "      <td> 0</td>\n",
       "      <td>   13</td>\n",
       "      <td>   44.454317</td>\n",
       "      <td> 56</td>\n",
       "      <td> 0.232885</td>\n",
       "      <td> False</td>\n",
       "      <td> 1</td>\n",
       "      <td>  True</td>\n",
       "      <td> 2296.542044</td>\n",
       "      <td> 2994</td>\n",
       "      <td> 0.100001</td>\n",
       "      <td>  0.828894</td>\n",
       "      <td> M130587</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13  </th>\n",
       "      <td> 400</td>\n",
       "      <td>     bird</td>\n",
       "      <td> 30</td>\n",
       "      <td> 0</td>\n",
       "      <td>   14</td>\n",
       "      <td>   45.537133</td>\n",
       "      <td> 81</td>\n",
       "      <td> 0.249979</td>\n",
       "      <td> False</td>\n",
       "      <td> 1</td>\n",
       "      <td> False</td>\n",
       "      <td> 2189.160042</td>\n",
       "      <td> 2485</td>\n",
       "      <td> 0.100368</td>\n",
       "      <td>  0.996217</td>\n",
       "      <td> M130587</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14  </th>\n",
       "      <td> 600</td>\n",
       "      <td>     bird</td>\n",
       "      <td> 30</td>\n",
       "      <td> 0</td>\n",
       "      <td>   15</td>\n",
       "      <td>   47.387035</td>\n",
       "      <td> 77</td>\n",
       "      <td> 0.349928</td>\n",
       "      <td> False</td>\n",
       "      <td> 1</td>\n",
       "      <td> False</td>\n",
       "      <td> 1816.723874</td>\n",
       "      <td> 4015</td>\n",
       "      <td> 0.133068</td>\n",
       "      <td>  1.127178</td>\n",
       "      <td> M130587</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1274</th>\n",
       "      <td> 400</td>\n",
       "      <td> mushroom</td>\n",
       "      <td> 15</td>\n",
       "      <td> 0</td>\n",
       "      <td> 1275</td>\n",
       "      <td> 4735.792264</td>\n",
       "      <td> 60</td>\n",
       "      <td> 2.617672</td>\n",
       "      <td>  True</td>\n",
       "      <td> 1</td>\n",
       "      <td>  True</td>\n",
       "      <td> 1418.312466</td>\n",
       "      <td> 3336</td>\n",
       "      <td> 0.165583</td>\n",
       "      <td>  1.310952</td>\n",
       "      <td> M130587</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1275</th>\n",
       "      <td> 300</td>\n",
       "      <td>     bird</td>\n",
       "      <td>-15</td>\n",
       "      <td> 0</td>\n",
       "      <td> 1276</td>\n",
       "      <td> 4740.156945</td>\n",
       "      <td> 41</td>\n",
       "      <td> 0.266927</td>\n",
       "      <td> False</td>\n",
       "      <td> 1</td>\n",
       "      <td> False</td>\n",
       "      <td> 1791.990335</td>\n",
       "      <td> 2845</td>\n",
       "      <td> 0.115663</td>\n",
       "      <td>  0.995913</td>\n",
       "      <td> M130587</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1276</th>\n",
       "      <td> 550</td>\n",
       "      <td>     bird</td>\n",
       "      <td> 30</td>\n",
       "      <td> 0</td>\n",
       "      <td> 1277</td>\n",
       "      <td> 4742.257880</td>\n",
       "      <td> 78</td>\n",
       "      <td> 0.532857</td>\n",
       "      <td> False</td>\n",
       "      <td> 1</td>\n",
       "      <td> False</td>\n",
       "      <td> 1885.810632</td>\n",
       "      <td> 3853</td>\n",
       "      <td> 0.150081</td>\n",
       "      <td> 15.657505</td>\n",
       "      <td> M130587</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1277</th>\n",
       "      <td> 550</td>\n",
       "      <td>     bird</td>\n",
       "      <td> 30</td>\n",
       "      <td> 0</td>\n",
       "      <td> 1278</td>\n",
       "      <td> 4746.807329</td>\n",
       "      <td> 78</td>\n",
       "      <td> 0.317938</td>\n",
       "      <td> False</td>\n",
       "      <td> 1</td>\n",
       "      <td> False</td>\n",
       "      <td> 1803.310858</td>\n",
       "      <td> 3617</td>\n",
       "      <td> 0.133047</td>\n",
       "      <td>  1.127365</td>\n",
       "      <td> M130587</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1278</th>\n",
       "      <td> 400</td>\n",
       "      <td>     bird</td>\n",
       "      <td>-30</td>\n",
       "      <td> 0</td>\n",
       "      <td> 1279</td>\n",
       "      <td> 4748.691669</td>\n",
       "      <td> 25</td>\n",
       "      <td> 0.349984</td>\n",
       "      <td> False</td>\n",
       "      <td> 1</td>\n",
       "      <td> False</td>\n",
       "      <td> 1615.194855</td>\n",
       "      <td> 3214</td>\n",
       "      <td> 0.133229</td>\n",
       "      <td>  1.125503</td>\n",
       "      <td> M130587</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1279</th>\n",
       "      <td> 450</td>\n",
       "      <td>     bird</td>\n",
       "      <td>  0</td>\n",
       "      <td> 0</td>\n",
       "      <td> 1280</td>\n",
       "      <td> 4750.407205</td>\n",
       "      <td> 52</td>\n",
       "      <td> 0.417001</td>\n",
       "      <td> False</td>\n",
       "      <td> 1</td>\n",
       "      <td> False</td>\n",
       "      <td> 1596.888169</td>\n",
       "      <td> 2681</td>\n",
       "      <td> 0.150383</td>\n",
       "      <td>  1.097408</td>\n",
       "      <td> M130587</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1280</th>\n",
       "      <td> 500</td>\n",
       "      <td>     bird</td>\n",
       "      <td> 30</td>\n",
       "      <td> 0</td>\n",
       "      <td> 1281</td>\n",
       "      <td> 4752.323583</td>\n",
       "      <td> 79</td>\n",
       "      <td> 0.517064</td>\n",
       "      <td> False</td>\n",
       "      <td> 1</td>\n",
       "      <td> False</td>\n",
       "      <td> 1555.536869</td>\n",
       "      <td> 2800</td>\n",
       "      <td> 0.150368</td>\n",
       "      <td>  1.329957</td>\n",
       "      <td> M130587</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1281</th>\n",
       "      <td> 300</td>\n",
       "      <td>     bird</td>\n",
       "      <td>-45</td>\n",
       "      <td> 0</td>\n",
       "      <td> 1282</td>\n",
       "      <td> 4754.241048</td>\n",
       "      <td> 13</td>\n",
       "      <td> 0.367688</td>\n",
       "      <td> False</td>\n",
       "      <td> 1</td>\n",
       "      <td> False</td>\n",
       "      <td> 1502.693105</td>\n",
       "      <td> 2517</td>\n",
       "      <td> 0.133231</td>\n",
       "      <td>  1.011983</td>\n",
       "      <td> M130587</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1282</th>\n",
       "      <td> 300</td>\n",
       "      <td>     bird</td>\n",
       "      <td>-15</td>\n",
       "      <td> 0</td>\n",
       "      <td> 1283</td>\n",
       "      <td> 4756.056101</td>\n",
       "      <td> 41</td>\n",
       "      <td> 0.399956</td>\n",
       "      <td> False</td>\n",
       "      <td> 1</td>\n",
       "      <td> False</td>\n",
       "      <td> 1324.786870</td>\n",
       "      <td> 2757</td>\n",
       "      <td> 0.165626</td>\n",
       "      <td>  1.116007</td>\n",
       "      <td> M130587</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1283</th>\n",
       "      <td> 400</td>\n",
       "      <td>     bird</td>\n",
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       "      <td> 0</td>\n",
       "      <td> 1284</td>\n",
       "      <td> 4759.755876</td>\n",
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       "      <td>  True</td>\n",
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       "      <td> 1213.378869</td>\n",
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       "      <td> 0.415119</td>\n",
       "      <td>  0.522918</td>\n",
       "      <td> M130587</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
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       "      <th>1284</th>\n",
       "      <td> 500</td>\n",
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       "      <td> M130587</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
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       "    <tr>\n",
       "      <th>1285</th>\n",
       "      <td> 300</td>\n",
       "      <td> mushroom</td>\n",
       "      <td> 45</td>\n",
       "      <td> 0</td>\n",
       "      <td> 1286</td>\n",
       "      <td> 4770.355938</td>\n",
       "      <td> 90</td>\n",
       "      <td> 0.332929</td>\n",
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       "      <td>  True</td>\n",
       "      <td> 1459.365217</td>\n",
       "      <td> 4128</td>\n",
       "      <td> 0.133304</td>\n",
       "      <td>  0.997450</td>\n",
       "      <td> M130587</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1286</th>\n",
       "      <td> 350</td>\n",
       "      <td> mushroom</td>\n",
       "      <td>-30</td>\n",
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       "      <td> 1287</td>\n",
       "      <td> 4772.105389</td>\n",
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       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1287</th>\n",
       "      <td> 450</td>\n",
       "      <td> mushroom</td>\n",
       "      <td> 15</td>\n",
       "      <td> 0</td>\n",
       "      <td> 1288</td>\n",
       "      <td> 4773.822187</td>\n",
       "      <td> 59</td>\n",
       "      <td> 3.964735</td>\n",
       "      <td>  True</td>\n",
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       "      <td> 1656.725038</td>\n",
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       "      <td>  1.500442</td>\n",
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       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1288</th>\n",
       "      <td> 500</td>\n",
       "      <td> mushroom</td>\n",
       "      <td>-15</td>\n",
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       "      <td> 1289</td>\n",
       "      <td> 4780.771671</td>\n",
       "      <td> 30</td>\n",
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       "      <td>  True</td>\n",
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       "      <td>  True</td>\n",
       "      <td> 1461.607078</td>\n",
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       "      <td> 0.182853</td>\n",
       "      <td> 13.752887</td>\n",
       "      <td> M130587</td>\n",
       "      <td> 2014-10-03 13:29:50.625000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1289 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Size     Image  Ori  PosY  trial         time  terraincode  pausetime choice  selectiontime istarget        speed  lapdistance  timebeforezone  slowing_f    mouse                        date\n",
       "0      400      bird    0     0      1     1.840244           53   0.267095  False              1    False  2152.301946         3937        0.099917   1.151120  M130587  2014-10-03 13:29:50.625000\n",
       "1      550      bird  -15     0      2     3.024151           36   0.268031  False              1    False  2155.681332         2455        0.100434   0.995480  M130587  2014-10-03 13:29:50.625000\n",
       "2      350      bird    0     0      3     4.273621           54   0.399960  False              1    False  1231.647159         2661        0.115117   1.148952  M130587  2014-10-03 13:29:50.625000\n",
       "3      550      bird   45     0      4     7.623390           92   0.667990  False              1    False  1416.589407         4376        0.200129  11.667522  M130587  2014-10-03 13:29:50.625000\n",
       "4      450      bird    0     0      5    12.638539           52   0.232075  False              1    False  2709.459253         3349        0.115528   0.995757  M130587  2014-10-03 13:29:50.625000\n",
       "5      550      bird   45     0      6    14.122473           92   0.249965  False              1    False  1959.213561         3544        0.083261   1.200958  M130587  2014-10-03 13:29:50.625000\n",
       "6      600      bird  -15     0      7    16.155746           35   0.314834  False              1    False  1996.971224         4097        0.150395   0.997373  M130587  2014-10-03 13:29:50.625000\n",
       "7      400      bird   45     0      8    18.256180           95   0.832834  False              1    False  1103.000564         3796        0.132865   1.263148  M130587  2014-10-03 13:29:50.625000\n",
       "8      400      bird  -15     0      9    23.172326           39   0.384844  False              1    False  1537.117166         5221        0.150351   0.998283  M130587  2014-10-03 13:29:50.625000\n",
       "9      400  mushroom   15     0     10    25.971682           60   2.282713   True              1     True  1009.442921         4172        0.165107   1.319022  M130587  2014-10-03 13:29:50.625000\n",
       "10     500      bird  -45     0     11    30.271798            9   0.384991  False              1    False   479.653339         2654        0.132996   0.751802  M130587  2014-10-03 13:29:50.625000\n",
       "11     400      bird   15     0     12    36.338231           67   5.199634   True              1    False  1134.592683         3835        0.200371   0.997547  M130587  2014-10-03 13:29:50.625000\n",
       "12     600  mushroom   15     0     13    44.454317           56   0.232885  False              1     True  2296.542044         2994        0.100001   0.828894  M130587  2014-10-03 13:29:50.625000\n",
       "13     400      bird   30     0     14    45.537133           81   0.249979  False              1    False  2189.160042         2485        0.100368   0.996217  M130587  2014-10-03 13:29:50.625000\n",
       "14     600      bird   30     0     15    47.387035           77   0.349928  False              1    False  1816.723874         4015        0.133068   1.127178  M130587  2014-10-03 13:29:50.625000\n",
       "...    ...       ...  ...   ...    ...          ...          ...        ...    ...            ...      ...          ...          ...             ...        ...      ...                         ...\n",
       "1274   400  mushroom   15     0   1275  4735.792264           60   2.617672   True              1     True  1418.312466         3336        0.165583   1.310952  M130587  2014-10-03 13:29:50.625000\n",
       "1275   300      bird  -15     0   1276  4740.156945           41   0.266927  False              1    False  1791.990335         2845        0.115663   0.995913  M130587  2014-10-03 13:29:50.625000\n",
       "1276   550      bird   30     0   1277  4742.257880           78   0.532857  False              1    False  1885.810632         3853        0.150081  15.657505  M130587  2014-10-03 13:29:50.625000\n",
       "1277   550      bird   30     0   1278  4746.807329           78   0.317938  False              1    False  1803.310858         3617        0.133047   1.127365  M130587  2014-10-03 13:29:50.625000\n",
       "1278   400      bird  -30     0   1279  4748.691669           25   0.349984  False              1    False  1615.194855         3214        0.133229   1.125503  M130587  2014-10-03 13:29:50.625000\n",
       "1279   450      bird    0     0   1280  4750.407205           52   0.417001  False              1    False  1596.888169         2681        0.150383   1.097408  M130587  2014-10-03 13:29:50.625000\n",
       "1280   500      bird   30     0   1281  4752.323583           79   0.517064  False              1    False  1555.536869         2800        0.150368   1.329957  M130587  2014-10-03 13:29:50.625000\n",
       "1281   300      bird  -45     0   1282  4754.241048           13   0.367688  False              1    False  1502.693105         2517        0.133231   1.011983  M130587  2014-10-03 13:29:50.625000\n",
       "1282   300      bird  -15     0   1283  4756.056101           41   0.399956  False              1    False  1324.786870         2757        0.165626   1.116007  M130587  2014-10-03 13:29:50.625000\n",
       "1283   400      bird    0     0   1284  4759.755876           53   1.682798   True              1    False  1213.378869         4832        0.415119   0.522918  M130587  2014-10-03 13:29:50.625000\n",
       "1284   500  mushroom    0     0   1285  4765.390659           44   2.749807   True              1     True  1716.132505         4039        0.133261   1.500831  M130587  2014-10-03 13:29:50.625000\n",
       "1285   300  mushroom   45     0   1286  4770.355938           90   0.332929  False              1     True  1459.365217         4128        0.133304   0.997450  M130587  2014-10-03 13:29:50.625000\n",
       "1286   350  mushroom  -30     0   1287  4772.105389           19   0.367001  False              1     True  1554.079078         2669        0.150007   1.101244  M130587  2014-10-03 13:29:50.625000\n",
       "1287   450  mushroom   15     0   1288  4773.822187           59   3.964735   True              1     True  1656.725038         2517        0.133237   1.500442  M130587  2014-10-03 13:29:50.625000\n",
       "1288   500  mushroom  -15     0   1289  4780.771671           30   2.481823   True              1     True  1461.607078         5273        0.182853  13.752887  M130587  2014-10-03 13:29:50.625000\n",
       "\n",
       "[1289 rows x 17 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "(-10, 90)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%capture capt\n",
    "\n",
    "execute_notebook(\"C:\\Users\\dorisv\\Desktop\\Shawn's data\\Object recognition - Running speed from behavioral log file.ipynb\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index([u'Image', u'Ori', u'PosY', u'Size', u'abs_reward_rate', u'duration', u'end_frame', u'end_time', u'first_lick_latency_0', u'first_lick_latency_1', u'image', u'jcam_end_ind_exclusive', u'jcam_start_ind', u'lap_number', u'lick_duration_0', u'lick_duration_1', u'lick_times_0', u'lick_times_1', u'mouse_id', u'number_of_licks_0', u'number_of_licks_1', u'number_of_rewards', u'reward_times', u'start_date_time', u'start_frame', u'start_time', u'stop_date_time', u'choice', u'total_trial_ind'], dtype='object')\n",
      "['M143454']\n",
      "747\n",
      "282 465\n"
     ]
    },
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Image</th>\n",
       "      <th>Ori</th>\n",
       "      <th>PosY</th>\n",
       "      <th>Size</th>\n",
       "      <th>abs_reward_rate</th>\n",
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       "      <th>first_lick_latency_0</th>\n",
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       "      <th>number_of_licks_1</th>\n",
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       "      <th>stop_date_time</th>\n",
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       "      <td> 2014-10-27 12:54:41.393000</td>\n",
       "      <td> 1356</td>\n",
       "      <td> 22.649692</td>\n",
       "      <td> 2014-10-27 14:05:33.684000</td>\n",
       "      <td> False</td>\n",
       "      <td> 4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Image  Ori  PosY  Size  abs_reward_rate  duration  end_frame   end_time  first_lick_latency_0 first_lick_latency_1         ...          number_of_licks_0 number_of_licks_1 number_of_rewards  \\\n",
       "1      bird  -15     0   500         1.786181  3.449961        390   6.549960                   NaN                 None         ...                          0                 0                 0   \n",
       "2  mushroom  -30     0   400         1.600021  6.633207        788  13.183167              1.649916                 None         ...                          5                 0                 1   \n",
       "3      bird   45     0   400         1.552413  3.216621        980  16.399788                   NaN                 None         ...                          0                 0                 0   \n",
       "4  mushroom    0     0   550         2.169573  6.249905       1355  22.649692              1.016686                 None         ...                         24                 0                 1   \n",
       "5      bird   45     0   500         2.720092  8.333357       1854  30.983049              1.200000                 None         ...                         15                 0                 0   \n",
       "\n",
       "      reward_times             start_date_time start_frame start_time              stop_date_time choice  total_trial_ind  \n",
       "1               []  2014-10-27 12:54:41.393000         185   3.099999  2014-10-27 14:05:33.684000   True                0  \n",
       "2  [8.74988234113]  2014-10-27 12:54:41.393000         391   6.549960  2014-10-27 14:05:33.684000  False                1  \n",
       "3               []  2014-10-27 12:54:41.393000         789  13.183167  2014-10-27 14:05:33.684000   True                2  \n",
       "4  [18.4498032981]  2014-10-27 12:54:41.393000         981  16.399788  2014-10-27 14:05:33.684000   True                3  \n",
       "5               []  2014-10-27 12:54:41.393000        1356  22.649692  2014-10-27 14:05:33.684000  False                4  \n",
       "\n",
       "[5 rows x 29 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sizes = np.sort(dataFrame.Size.unique())\n",
    "orientations = np.sort(dataFrame.Ori.unique())\n",
    "\n",
    "#for the purposes of the experiment, should be m=n=7\n",
    "m = len(sizes)\n",
    "n = len(orientations)\n",
    "\n",
    "evenTest1 = isinstance((m/float(2)), (int, long))\n",
    "evenTest2 = isinstance((n/float(2)), (int, long))\n",
    "    \n",
    "if evenTest1:\n",
    "    s_T = sizes[m/2-1]\n",
    "else:\n",
    "    s_T = sizes[m/2]\n",
    "        \n",
    "if evenTest2:\n",
    "    o_T = orientations[n/2-1]    \n",
    "else:\n",
    "    o_T = orientations[n/2]\n",
    "                \n",
    "s_max = sizes[m-1]\n",
    "\n",
    "print dataFrame.columns\n",
    "print dataFrame.mouse_id.unique()\n",
    "#dataFrame[dataFrame.Image==]\n",
    "\n",
    "dataFrame.Image[dataFrame.Image == \"CoxImage1.png\"] = \"mushroom\"\n",
    "dataFrame.Image[dataFrame.Image == \"CoxImage2.png\"] = \"bird\"\n",
    "\n",
    "N = len(dataFrame)\n",
    "print N\n",
    "\n",
    "N_m = len(dataFrame.Image[dataFrame.Image==\"mushroom\"])\n",
    "N_b = len(dataFrame.Image[dataFrame.Image==\"bird\"])\n",
    "print N_m, N_b\n",
    "\n",
    "dataFrame[\"total_trial_ind\"] = range(0, len(dataFrame))\n",
    "dataFrame.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def p_real(j):\n",
    "    \n",
    "    dataFrame = dataFrame_list[j]\n",
    "            \n",
    "    p_m_real = np.zeros((len(orientations),len(sizes)))\n",
    "    p_b_real = np.zeros((len(orientations),len(sizes)))\n",
    "    trials_tot = np.zeros((len(orientations),len(sizes)))\n",
    "    trials_stop = np.zeros((len(orientations),len(sizes)))\n",
    "    trials_m = np.zeros((len(orientations),len(sizes)))\n",
    "    trials_b = np.zeros((len(orientations),len(sizes)))\n",
    "    trials_stop_m = np.zeros((len(orientations),len(sizes)))\n",
    "    trials_stop_b = np.zeros((len(orientations),len(sizes)))\n",
    "    correct_m = np.zeros((len(orientations), len(sizes)))\n",
    "    correct_b = np.zeros((len(orientations), len(sizes)))\n",
    "\n",
    "    for ind2,o in enumerate(orientations):\n",
    "        for ind1,s in enumerate(sizes):\n",
    "            \n",
    "            trials_tot[ind2,ind1] = len(dataFrame[(dataFrame.Size==s)&(dataFrame.Ori==o)].total_trial_ind)\n",
    "            #print ind1, ind2, trials_tot[ind2,ind1]\n",
    "            trials_stop[ind2,ind1] = len(dataFrame[(dataFrame.Size==s)&(dataFrame.Ori==o)&(dataFrame.choice==1)].total_trial_ind)\n",
    "\n",
    "            trials_m[ind2,ind1] = len(dataFrame[(dataFrame.Size==s)&(dataFrame.Ori==o)&(dataFrame.Image=='mushroom')].total_trial_ind)\n",
    "            trials_b[ind2,ind1] = len(dataFrame[(dataFrame.Size==s)&(dataFrame.Ori==o)&(dataFrame.Image=='bird')].total_trial_ind)   \n",
    "            \n",
    "            trials_stop_m[ind2,ind1] = len(dataFrame[(dataFrame.Size==s)&(dataFrame.Ori==o)&(dataFrame.Image=='mushroom')&(dataFrame.choice==1)].total_trial_ind)\n",
    "            trials_stop_b[ind2,ind1] = len(dataFrame[(dataFrame.Size==s)&(dataFrame.Ori==o)&(dataFrame.Image=='bird')&(dataFrame.choice==1)].total_trial_ind)   \n",
    "            \n",
    "            p_m_real[ind2, ind1] = trials_m[ind2,ind1]/trials_tot[ind2,ind1]\n",
    "            p_b_real[ind2, ind1] = trials_b[ind2,ind1]/trials_tot[ind2,ind1]   \n",
    "            \n",
    "            correct_m[ind2, ind1] = len(dataFrame.total_trial_ind[(dataFrame.Size==s) & (dataFrame.Ori==o) & (dataFrame.Image==\"mushroom\") & (dataFrame.choice == 1)])/trials_m[ind2,ind1]\n",
    "            correct_b[ind2, ind1] = len(dataFrame.total_trial_ind[(dataFrame.Size==s) & (dataFrame.Ori==o) & (dataFrame.Image==\"bird\") & (dataFrame.choice == 0)])/trials_b[ind2,ind1]\n",
    "          \n",
    "    return p_m_real, p_b_real, trials_tot, trials_stop, trials_m, trials_b, trials_stop_m, trials_stop_b, correct_m, correct_b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 0.5         0.46153846  0.33333333  0.35714286  0.44444444  0.73333333\n",
      "   0.125     ]\n",
      " [ 0.5         0.6         0.3         0.46666667  0.25        0.38461538\n",
      "   0.54545455]\n",
      " [ 0.16666667  0.3         0.25        0.14285714  0.27272727  0.22222222\n",
      "   0.33333333]\n",
      " [ 0.25        0.36363636  0.4         0.5         0.125       0.28571429\n",
      "   0.26666667]\n",
      " [ 0.61111111  0.33333333  0.42857143  0.16666667  0.25        0.14285714\n",
      "   0.5       ]\n",
      " [ 0.1         0.61538462  0.375       0.33333333  0.16666667  0.125\n",
      "   0.58333333]\n",
      " [ 0.35714286  0.4         0.33333333  0.28571429  0.21428571  0.\n",
      "   0.35714286]]\n",
      "[[ 0.8         0.72727273  0.81818182  0.46666667  0.57142857  0.48        0.4       ]\n",
      " [ 0.70588235  0.66666667  0.35714286  0.64285714  0.46153846  0.63636364\n",
      "   1.        ]\n",
      " [ 0.56521739  0.5         0.44444444  0.46153846  0.57142857  0.4         0.4       ]\n",
      " [ 0.66666667  0.71428571  0.46153846  0.54166667  0.44444444  0.61111111\n",
      "   0.46666667]\n",
      " [ 0.6875      0.52631579  0.58823529  0.61111111  0.66666667  0.61538462\n",
      "   0.55555556]\n",
      " [ 0.55555556  0.42857143  0.58823529  0.73333333  0.73333333  0.64285714\n",
      "   0.875     ]\n",
      " [ 0.75        0.68421053  0.71428571  0.61111111  0.88235294  0.6875\n",
      "   0.77777778]]\n"
     ]
    },
    {
     "data": {
      "image/png": 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XLoq5j3+jU/NnVG5Ur9Z4H954HdOTSYPKT/o+y8avWmtQ8MVXGtsLda69qT2FBRo+L7hO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PJOR5A/aCsLF3/IwhGfUrK6iJDx1c87CZTX8vGkv3Pm7OG4iT4+T/mKzW4xc196jf3rS1hwz+vc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\nOr/pKLsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1bbb7ba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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UXzUP26DeGNNiY6B2sBiFEMUUYGUd6cxmD0+3uiaZAix8h5ezALCxEhtrKCgo\nQHV6SeV5AAxUkcVdmNhBkN5N5S1sZhcvopFy9AI7TN7FmyAUpsubvyOwbidVjy4kc+4NQOT+V057\nh/Qnx2PK6Uz9Wytp2F1FqKgcFIU333yTYSv+SvWTH5I59waq/rIIx+UDsV/aD99X2wgVljRNVGqe\n/DAygVGiGe2+NnfqxPakREya1uq4BqxOT+PSncUYNY2PcnPo5vFQbrMSVhSGF+9i1J138qdPPmHo\nnr2sSU8jr6KCDJ+frzPS2W2309nvpzAlhRE7dhJWVT7KySbLszNGvqK0k7gKprUjWfrZCoymg9/e\nu1e76TkkkkHommdn78Z9Z726rrP4wWIumZ6LoijsXu2m137KlGz0ULS0ljeuc/Hfe7cT9ISp3OYn\n56xEDGYVo1klrY+NPWs9HRnSEalZXUrakMjEISUvg7qNFU3nvN/XYkqxsuOljXw9fhGh+iD2XilU\nfrELR99OTJo0iTWTPiLjwsi30Jo1pQRKPKy68b/sXbiV1LO7NtXV4A2xbe5qTrznnKMb4CHYrOV4\nvZF+BgJpWKxVLc6q7Nh5Gbpuapxk6Oi6itlcjao28Otf/5puXT/BYqloVWfn1A3U1jgJh20A6LrC\n7t0XomkH/WOIR51vzQ4SzusLgDUvh8DG5m+Voe0VqMkJVL/8Bbuufx6t3o+5ZzoAFY99wLhx4zCm\nN2eesh6/GoszCwA9pKFYTASLykg4sxeK2YhqNmLuk4l/3c6jGOHBWVmNhyEA+MnDwsZ9zltZTy1X\no6ADYOcLAjiZNGkS3fgtbi4EQMFLJbdRxxXQeC1omNlBJveTwziSeOdohXZYAmu2Yzsv8kXMkpdL\ncOOupnMN28tRkxOoe/lz9l7/DFq9D1PPDBIuOoXOM66KXLOnGkOSrbGuHTTsraHkxufwvL8G69mR\nL3ueD9eDqmIb4mz+zxIjEkNBhuzZu0+3as1mEkMhzJqGCqT7fJTZbJRbbXT1RD678/LyqLJEMudV\nFgsZvsiXkC4eLyX2BKqsVtJ9PlTApGkkBkPUNF4vYt9hT1RcLte7QEMH9gWAgFvD4mieGqoGBV1r\n/dbd+kktaX1tpPawHrCMFtbpmmfngj9nc81rTlJyLCybu5f0vjZ2raon6Anjq25g9xo3IX/rGXw0\nNXiCGB3NA6jSIv5gTYCaNaXkXncyp780kqrle6hasYdgTYC6TRXMmTOHk6cPZv3kpQD49rgxJls4\n48WRWLurDx0GAAAgAElEQVQ4+P655j8auPvtQrJG9MSUElu/rKragKa1SPTpCq0/URXs9mJycz7E\n58tE143oupHq6pN44YUXKCs/k6zM5U1lDAY/NlspdfU9m2rw+bLQtNiKG0BzB1AdLfqlquiN3y7D\n1V78a3eSct05dHtxAt4V2/CuLKJuwWoMqQmcd955jYUicf8wafGt2UHtmyvodMNgLH2z8K36Hs0T\naKpP94eOZogHZcD9o2UYA5Hv02CgjM7Mo4yptHw/GKjGykbmzJlDKTPowp0ANJCNn36t6lfwUcN4\nSvgLu3ieFN7AzEH/dfmjSnMHUBzW5gOq0ur+B9buIOm6c8l68SZ8K7biW7kVAMWgMmXKFCofeg/7\nzyNZw4Y91RhSEsh68SaMXVKofX4pwcISPIvWknLbJeh6jM1SgBy3B2U//WpQVUzh5s9ok6YRUlUa\nDCrGFtmXH/7FOxRln2tDqtoqU2NsPB5XovOXaY+Kdu3GxcY/kkxWm+ooc8wmz5PHSEYC8Io2jF+r\nb7a65o/v/5H7briBAQxoVQbgRt7gFW0YvzG8Sd3FdSQlRTItQy/eyoMPPsjk3i/T89q3eec379C1\na1fO7ZfFqE5XM5jBbeo30C65ptkOLRK/Eol/mLaIuYY/A7AtZRt/zC3kxd4PA/DykCwaNjVQ2ymH\n1N6pGI1GXuz1EFdYNjKj+jesSXmPly76C8lKMt9e+C1PPPEETyl3ATB20VieeuopMpXM/XfkJ3gq\n3PY6Zs+eTV5eHiNHNsY/bAlFRTP2uU7XdaZMmcKgQXn8/Oc/b/rgDfgf55e//CUrVkwiMzOT119/\nHbe7J7fccss+dVx44Wds2XI/ZnNsZFZmJ24lz5vHSLUxdv0pFhnHArCt0zb+mLuU93tH/rbSy0N8\nNGxqYOnS9SiKwvjl4zFtqSTl7iX8/e9/p3PnzvznP//hmWc+5b//V0B252zoDG9fl847N0fe+336\nnc3VqSMYrLbDe78dxvvZsx3k5XlovPUMG6ZR9GlkMJk//0MWLKjGbr+JiooK/H4/t93Wi6KiTqSm\n9sZoNBJ09eSKKyx881IVqamRZY65cyEtDfLzQdNs+HzjsdstgIXHHjubvn23cMUVzrZ3nivaXMPs\nxG/J857W4v7/lf8ZI/ttIvd/Me/3vgmAl4fU0bCpgd+c09ju7Cu48847GTt2LP9atIjhKY+x6KI7\nSVaT+faivjzxxBP0CdbxdZkBy6/eoWH3bkwmE/fnXNZiktsGevt82du1axfFd9zB9J3/aDrmcrl4\n/PHHmf5//wfArFmzGDhwIGvWrGn1WZGUk8PMoiI+HTaM6du2AbB48WKWL1/O4MGD+fzzz5k2bRoA\nt956KxMnTuSUU05pl36LjtWuE5XFDX+j1tS2VHL1wGqeX/Iee0fOZ/daNwlOLy9yTatrlm/cQL8B\nZaz5UZmRI0fywNrLm8rMv2kLF9+bQ5d+dr5ZXoZ2apC5VWPZ5K5k+JuZBOp3MT9/CyflleJiXpv6\nDbBG79/mOkoH7OTDJV/wnxEbqFlbRoPTyO/1RwHQssMUe/fy6x33kZCbxNpVH9Ptl31B09n56kIm\nTJjATSXT2Onbw9Tk51AH2rlx6WS6Xn4CO77aSKCPl9/rjxKqD1IULObBjFfaNf07z9j2zWl2ezEO\n+1JKy1ZitVSQmqo27TtRlRBdun7K7t0XAAbS0zfyzLMlKMq7WMw1lJYuxGS+i+xu2+nS9WlAoUvW\n51RWncrESdP3aatH9xqstgdoj8Xdn4VObXMd7v4B3l76KvMu9eBbu5O6vkn8XHsbAL1bA9u95Vyy\n/VnMuZ3Zs+o9ksecjv3GKwFYqI6h//gR1Ey/kBs6LaHuX2upfetrur5yHb9NXgEahKs91NWvpdPr\nV7G53s+ucc+ytd8gVG1vm/u+6KQxba7DwUDsLKH0jyOxspZUnChNc4jxjT+QxALMFDF6yijsLCWF\nV5kwYQJGZyk5+Oh8TqemOlOJ/GMj46aBme/J4nZ2sgAIk8M3lDKa4F1t7jqXfPvvNtfh6d/AP5e+\nxt8uDeJfu4PavilcqkXq1bs1sNtbwYXbX8SU25myVe/jGHMWLy2YSkNpLSt/+yTjzB9Tqvq4nEV4\nBmbxsyV/xXH5QOpWfkHDCQo77ugLRJYWPfM+wpCeyAPnVoLW9r6fYziiPzR6QG6jkeIuWUxXmrMd\nGrC6R3fuMRgxaBqLc3Oo2b2HCpuVpXYHK0tLuXLNatSt25iuqBi6dmFSgp0Mn4+vMzLI9Hpx+2ay\nJLsbDTNmElYUVubk0Gne0+2yreN3ZbWkpyce+sKOFiPZj47wU0Lr0Jxh3+EpbF9Wx2v5WwD42awe\nbF5YRdAbpv/YdLxVISyJhv2Wyc/Pp4xd/GxWDwAunZHL/2bsxGBUsGeYGDGzO2a7garv/bw65ltQ\nFS6YnN1q2SjaMoZ3p/LL3Xw17n0ATnl4KHsXbiPsDZE99kROefA81t+5FHSdlIGZpA/NAaB6VQlj\nxoxhh7aXk6aei6Iq9P3zIDbf9zm73vwWY5KZ0/4SeVjLu70WW3YM/GLth8eTTUJCCdndPgKgtGwQ\nDsd2VLWBuroTqK/vQXb2x6CrBAIp1Nf3AHQyM1Zy7bXX0iVrB6Wlg/ghvWUy1dMQio3NoodiH34y\n3i+3UnzNswBkPnQV9YvWoXmCJI89k8wHR1My+S3QdWwDumMfuv9MgB7WKH94IaauKey97XUAbGf1\npPPvLiL0fQU7xz6Noqik3Xkpqj12lsDcDCeBZeQ0PqFTwiwSWYiKl1rGtrpWb7y/Hs7HxteMGTOG\nbmiUMY19U5uR10F6U8eV5HA1YKSO0a022kZbwvBT8X/5HXuviXxpSntoLO5Fa9A9QRLHDqLzg2Mo\nn/xG5Im/Ad1JGHoimj9Exd3/4LrrrqM0VEbq3ZejWkyk3vVzKu5/m/qC5aiJNtL/Mi7K0R2+H+7e\n9kQHDarKCbV1DCivYEl2NwB61dZhC4fJdnsoSUjgo5xstsyezYDycgAGlFfwVWYGmqKQFAyS43aj\nAM7qGhbnRPb/9ausiOe9p3FHac+1yndCU/S2ZlTa4kbe2Cf7cjS1R0alLZ5S7mrKvkRDe2RU2kIL\nT2/11M/R1B4ZlbZYqI5pyr5EQ3tkVNpCd9Ei+3L0tUdGpS0+VK9oyr5EQ3tlVH6q6brWKgtzNDVm\nVKL/DNW9SsckER7Sox5bHCeLhBBCiONEHI/mcbbtWQghhBDxJI7nYEIIIcRxIo5Hc8moCCGEECJm\nxfEcTAghhDhOxPFoLhkVIYQQQsSsOJ6DCSGEEMeJOP7DMDJREUIIIY51cTyay9KPEEIIIWJWHM/B\nhBBCiONEHI/mklERQgghRMyK4zmYEEIIcZyQzbRCCCGEiFlxPJrL0o8QQgghYlYcz8GEEEKI40Qc\nj+aSURFCCCFEzIrjOZgQQghxnIjjzbSSURFCCCFEzJKMihBCCHGsi+PRPI5DE0IIIY4TcTyay9KP\nEEIIIWJWHM/BhBBCiONEHI/mklERQgghRMyK4zmYEEIIcZyQx5OFEEIIIY4+yagIIYQQx7o4Hs3j\nODQhhBDiOBHHo7ks/QghhBAiZim6rrdbZf3XNOjrg9Hb0aMNUlBXtl88R0p/Rola2wD6S6BMiGIH\nCqLYNqD7QLFFqfHcKLXbSHeB4oxiB96OYtuAfhooG6LYgbxvotg46NrpKGoU+9CO48hPa/4MFGVV\nVNouK3OSnp4Y3Q9/gP8pHXMTLtGjHptkVIQQQggRs+J4VUsIIYQ4TsTxaC4ZFSGEEELErDiegwkh\nhBDHiTgezeM4NCGEEOI4IX+ZVgghhBDi6JOMihBCCHGsi+PRPI5DE0IIIURHcTqdKvA00A8IAL9x\nuVzbWpwfBdwD6MCLLpfrmUOV2R9Z+hFCCCGOdcYO+jm4KwGzy+U6F5gCPP6j838FhgODgTucTmdK\nYxnLQcrsQyYqQgghhPgpBgMfALhcrpXAGT86HwJSgARAIZJZGQz89yBl9iETFSGEEOJYF52MShJQ\n1+J1uHFp5wePA98AG4D3XS5X7WGU2W9oQgghhDiWRefx5DogscVr1eVyaQBOpzMXuBXoDniB15xO\n55iDlTkQyagIIYQQ4qdYBvwMwOl0ng2sb3HOCoSBQONEpIzIMtDByuyXZFSEEEKIY110RvMFwHCn\n07ms8fUEp9M5DnC4XK7nnE7nK8CXTqfTD2wFXiYyeWlV5lCNyERFCCGEEEfM5XLpwMQfHS5scf4J\n4In9FP1xmYOSiYoQQghxrIvj0Vz2qAghhBAiZsXxHEwIIYQ4TsTxP0ooExUhhBDiWBfHo7ks/Qgh\nhBAiZsXxHEwIIYQ4TsTxaC4ZFSGEEELErDiegwkhhBDHiTgezSWjIoQQQoiYFcdzMCGEEOL4oHfQ\n48lKx1R7RGSiIoQQQhzjwh00msfCJEGWfoQQQggRsw46WXI6nSbgRaA7YAEedLlc73dojzSNjFdm\nYC52oZvMlN34IKHM3KbTKR+8TNKn7xBO6gRA2YSZhLJ60On9Z8l/Yik5NSFqLr6W+iGjsGzfTJcn\nJhLK6g5A7UXX4D5rBCkfvIxj5X8B8OYNperK33VoSEdE18gomo7FW4iumCg94SFC1hbx73mZ5NK3\nCZsi8Zf2foCQtTsZRdPIzy8ke1tzGZNvB1lbp6ArKkFbH8p6TQNFIbn0LZJL/oGuGKnKnogn9fwo\nBbs/GhmdpmMxF6LrJkqrHiLUkLvPVRmp96OFU6iovaPpWGVlJT27jmZX2cuEGno2HU9MeJ+UxNcp\nLi1o1U639Jtx+y6m1p3fkQEdAY0MpmOhEB0TpTxEiP3Ezv1opFBBJPZOPEt+/hJyCVHDddQxquna\ndB4mSC9qyW98/SA2VqNhBxT28DQajqMS3SFpGhnPTceyoxDdZKJ04kOEslq8999/meRP3m763S+9\nZSa2wrUkLXmX8XbIqQ5g2bGFoue/REuIxJT+0sMEu/Wi9pL8Vu10e/hm3Gdd3Pp41GlkZLyExbwz\n8t4vu4lQKHOfqzIynkMLJ1JRmd9UJj//MbK7BZrKmEwlZGU+g45KMJBNWfkEQCE56ROSkz9B11Wq\nqkbh8Q446lEeWGP8lmJ03Uhp6YHifx5Nc1BR0TL+v5Cd7W8qYzKVkJX1LLquEAzmUFb2K0AhOfkT\nkpOXNMZ/JR5PLMXfNvGcUTlUH64Fyl0u13in09kJWAt06ETF/s1iaAixa2oBlm3rSHvzEfb+cV7T\necv2zZTe8giBHic3HbN9uxLr1rUUFBRg+MxDp0XPN167iZoRv6JmZPO/Im0sKyZx+UKKp/8TFIXs\nB67BffrFBHOcHRnWYXNULUbRQxSfVoC1fh3p22ez58Snm85bPZso6fMoAUdz/I7K/6HoIQoKCrCN\naS6Tvn0WFbm340s+k4xt07BXfYw/MY+UvfPZ0e9dVC1AzsZxeFLOBdUcjXD34bAtRlFCFJcWYDWv\nIz1lNnsqnm51TbKjAIvpO7zhs1ocDTF16lR03dbqWotpM0mOd/Zpp3Py31DVetBjYQU2wsFiFEIU\nU4CVdaQzmz38KHYKsPAdXiKx21iJjTUUFBSgOr2kEnnvG6gii7swsYMgvZvKW9jMLl5EI+XoBXaY\nHF8tRmkIUfxwAdbCdaS/Mps9f27x3v9+EyW/f5RAr+b3fqhrT+rOH8X80yDzDzOpveiXaAkODLVV\nZD11F6aSHQSze7dqp/Obf0P11oMSO/cewGFfhUIDxbtmYLVsJT3tNfbsvaPVNclJH2Mx78LrO6lV\nmYKCAmy2fzSVSU97jYqKq/H5TyIj/QXs9lX4/X1ISfmQHTsfQlWD5GTPwLPzNGJjKAKH4xsUJUxx\n8XSs1q2kp7/Onj23t7omOfljLJZdeL0ntSoTib+gqUx6+utUVIzF5zuJjIwXsdu/we8/gZSU/7Fj\nx4OR+HNm4vHETvziwA51h/4JvN34/1WgoWO7A7bvVuPtNwSAQO88LN9vbHXesn0Tnd5/FmNtBZ68\nYVT/4mYSNnxBMLsvkyZNouseNxX5k5uuNZdsx776Y0JZPSi/9m4aOndh9+Tnmz6klHADutna0WEd\nNmvdajwpkfj9iXlY3D+K372J1N3PYAhW4Ol0PtXZNx+wjMWzGV/ymQB4Og3FXrMMFBVf4kBQTWiq\niaC1Oxavi4DjtKMY5YFZLavx+BtjCeZhMbeO32pejdW8nlr31ZiNRU3H01MeZdy4cby38NmmY6pa\nTVrKE5RX30Nm6v1Nxx22DwAVj28IKHrHBnQErKzGQ2Ps5GFh4z7nraynlqsxE4ndzhcEcDJp0iS6\n4aacuwBQ8FLJbSTwGfBDjBpmdpDJ/RipoJYx1HHV0QrvkKyu1XgGNMbfNw/Lth+994s2kfruMxhq\nKvCcfj7Vo25uOrdhwwbMxd9R9pupACgBL5VX30bCms9Ab77HjuUfgKri6T+k1fFYYLUV4vHmAeAP\nnIDF8n3r89ZCrNZt1NZehNm856BlLJbt+PyRwdzj7Y89YT2g4vP1BYxompFgKAuLZSeBQK+jEt+h\nWK0uPJ5+APj9J2CxFP3o/A/xX9gc/wHKWCzf42uczHk8edjtG9gn/mBmTMXfVg2GjtnJYemQWo/M\nQSNzuVwel8vldjqdiUQmLfd2eId8HjRbi1S0agBNa3rpPvsyyibMYNeUl7EVfkPC2qUY3DVYtm9i\nzpw5lP1qOlnPRCYq/t79qMi/i933vkYoPZvOC+aBwYjmSAFdJ+3NR/D3OJlQZveODuuwGcJuNEPL\nVLwB9Ob469Muo7TXTHad8gq2+m+wVy09QJkwCs0fxJrBjhquRw270YyJrY83uDswoiNjUN1o2o9i\nQWs8V0bn5HmUVU+FFrEl2d8lrKVy3nnnNR7RgTBZqfdSVj0FTUtoutZsKiTRvojK2j+gxNAkBcCA\n+0fLMC1ip4zOzKOM1rEbqMbKRubMmUMpM+jCnQA0kI2ffq3qV/BRw3hK+Au7eJ4U3sCMq4OjOnwG\nr/ugv/v1gy+j9JaZ7Jr+CrZvv8H+zdKmc88++yyVY3/f9LohIxt/n9bxm3cWkvjFIirz/4ASY5MU\nAIPqQ9NaZgRVmu6/oZrOqe9SVv4rWt3/A5Rp+d7WNCuq6kNVfa1+FyLHvR0Ryk9iMBwi/s4LGpdw\n9EOWaZks+yHOfeO3xVT84sAOmfNyOp05wLvAPJfLVXCwa98+0cAJtralU2cvcZCX7WHkoEg9w0wa\nRec0P3flPuUGHI7Ih9kbO86npuZbfH07kZraG6PRSODKXlzxkoVv+lRjOvkSEhMjg/LWzsN58MEH\neXmQQiAQ4J577sGR7GD69Oko7ZUCHtT2KmbPdpCX52HkyMjrYcM0il5unk+63S3if2MYNTWbqauL\nlAHQX/qhjIFhw1S2vRQpt3ixm+XLkxg82MHnn3uYNi1y/NZbPUycmMQpp7S977zU9ir2G/+2SPzz\n53/IggXV2O03UVFRgd/v57bbevHOO++iKArjx39JVsYWzhk0hbvuuovp03fSqdN0gsEgW7du5bc3\nP4zJZOLrr0uxWK5n9+7dmEwm7r8/u8UkJ3r2G/unB4+9qKj5vR909eSKKyx881IVqampAMydC2lp\nkJ8f+WD2+cZjt1sAC489djZ9+27hiitiY9lzdq6DvHQPIxuTe8OMGkV5Ld77PVu8938Ree9POu18\n6urquGb7drxzz9qnzrmfNsZ/Gjz2wb/52l+K5bEW935QO9177fQ2VzF79kfk5XVh5MhIXcOGGSkq\nimRE58+fz4IFYez2p1vc/3NxuXqQl9cFAF07vanMsGEWtm2L1LN4cTXLl/dg8ODT+PzzGqZNixy/\n9VYrEyeewSnt8svfdrNnLyYvrysjR54BwLBhJoqKIve0Of6/t4h/MC5XT/LyugKg62c0lYnEH6ln\n8eIali/v2SL+yPFI/GfGTPxtFTbG7xLWoTbTZgL/Aya5XK4lh6pszJYw64Nte5jb7hiA450llKaO\nwLp1LamZTtSVkRm06q0n994r2DF7IbrZRtZ/VlA3bAwYwqQsfJUJEyZg+qCE7Gofaa5ksh8YR/n4\n+wj0Oo3k/32JMfVU1JU6XR+diO+Uc6j+2W944CtoOUNvC/2Ztk94HJUDsS9cQulbI7HWryXV70Rp\n3GKjNtTTfe3lbB+wCF210aVwBbUZY1A1P/aFSygZORLbmOYyXQMnkTD6K3zJZ5Gx7TO8yefg29KP\n7M1PMKMoiKIFyNmwjXn1fdrn+a+DTmMPj8M2ELttCaVVI7Ga15Ka7ERp+sI0vvEHkuwLMBuLGH3N\nKGjcPKr7IKf7eNZtmck/3+8JLATAaNhNl7TbufeBe1q1lZo0l3A4nSHD22Gg2nfP6xFzMBA7Syj9\n40isrCUVJ0rTHKJF7CzATBGjp4zCzlJSiLz3jc5ScvDR+ZxOTXWmAmFg3DQw8z1Z3M5OFgBhcviG\nUkYTvKvtfW9aIG4DR+eB2P+9hNLskVgL15La1YmyIXJO9dTT/Y7L2f63RegWG10+XEHtRWP43Qaw\nf/01U84+u+nallJLIRyAcRuAEZNhROPxt+YS7pTOkOTzYD/ljljeN22uwmFPxu54l9LSDKzW70hN\nzUJRf6j35MYfSEr8DJN5D6OvysVhL8HueJeSvSOxJRQ0lenapSsJ9tca92i8i9d7Cr6ZkN3tc2bM\nXIGihMjJ2cS8p91A2/veHstoDkcydvu7lJamN8evrGo8e1LjDyQlfYbJtJfRo3NwOEqw29+lpGQk\nNtubTWW6du1KQsL8xvjfwes9FZ9PJzv7c2bMWN4c/7x6YNWBunRYysqcpKcnHvrCDhY2dNAfUokB\nh5qC3QMkA1OdTufUxmMjXS6Xv6M65DljOAmbviT7gXEAlP7mYRzLF6L6vdRdMJaKsbeTPesGdKMZ\n7ynnNO1nsblWMWbMGLrWa5TfMBVUlbIJM8h4ZSa60Ug4OZ3SG2diX/URNtcqlHADCes/A6Dyl7fj\nP6F/R4V0RNypw0moWUbOhsjTCCUnzCKxfCGq5qU2cywV3e8gZ9P1aIoZb8q5eDsNBV0noWYZ+fn5\npG+PlAEo7zGFzG33o+wMEbT1xt15BCgK1V2uJ2fjNaBrVObeHjMbaQHcvuEkWJeRk9kYf+UsEhMW\noipeaj1jW12rH/afItKJjT9bdHBuhpPAMnIan9ApYRaJLETFSy37j93D+dj4mjFjxtANjTKmsW+s\nkddBelPHleRwNWCkjtGtNtpGm3vQcBLWLyPn3sb4fzeLxC8Wovq81A4fS8V1d5Az/Xo0oxlvv3Px\nDhgKgHnPdnJzDzJTjLFNswfi9pxJQsIGcrKnA1BSeguJji9RVT+1dRcetEx+fj7paR5KSm8BoLzi\nWjIznkdRGggGu+F2DwIUqmtGkJM9A9CprIi8D2KF231GJP6c6QCUlNxCYmJj/LUHiL+xTH5+Punp\nbkpKGuMvv5bMzJbxnwUoVFdfSk7OTECnsnIssRS/ODBFb8e12v5rGvS2ZlTaQhukNGVfoqE9Mipt\nav8lmrIvUdEOGZW20H20yL4cZe2QUWkL3UWL7Mv/s3ff8VGU+QPHP7Ob7G6STSGkUJJQlIwFQRER\nUAQLCjaUw0jVw97ud3fYQATBAwSxnAh4yikqKogiitjxsIFgAQKhDFU66b1sdnee3x8bUhBpKZuN\n3/frldcrM8+z88w3s7P7zXee2fWDOqio1IY6h6NWVBpMHVRUakOZ51ervvhjB/w750eprtWqLw2r\noqLi92w4i/B6OQgxFPo9NvnANyGEEEI0WlL3EkIIIQKch6Y7R0UqKkIIIYRotKSiIoQQQgQ4bxN+\nO2+6kQkhhBB/El659COEEEII0fCkoiKEEEIEOKmoCCGEEEL4gVRUhBBCiAAnFRUhhBBCCD+QiooQ\nQggR4JryB75JoiKEEEIEuKb8OSpy6UcIIYQQjVbTTcGEEEKIPwmZTCuEEEII4QdSURFCCCECnFRU\nhBBCCCH8QCoqQgghRICT25OFEEII0WjJ7clCCCGEEH7QdFMwIYQQ4k9CJtMKIYQQQviBVFSEEEKI\nANeUKyqSqAghhBABriknKnLpRwghhBCNllRUhBBCiADXlD9HRSoqQgghhGi0pKIihBBCBDh/fOCb\nrusWYDbQCXABdxiGsaOiLR5YUK37ucCjwFzgNaANYAcmGYbx8bHGqdPIUjq+Sa/grLrc5El6hPsv\nnO630Xt1+8FvY/ss4d3Xrvfb6Df/sMRvY1dK8NO44/w0bnX+3IfufhwboNi/+9DB4///+fy5D9s6\nd/bb2JU6dvXTwIV+GrdRuAGwGYbRU9f1C4FnK9ZhGEY6cCmArus9gH8Bc4C/ApmGYYzQdb0ZsA44\nZqIil36EEEKIAOfFWi8/x3ER8DmAYRirgd9li7qua8AM4F7DMBSwEBhf0WwBPMcbxP//BgghhBCi\nVvx0e3IEUFB9N3RdtxiGYVZbdx2QZhjGNgDDMIoBdF0PB94Dxh5vEKmoCCGEEOJUFADh1ZaPTFIA\nhgGvVF+h63oi8D/gTcMwFnAcUlERQgghApyfbk9ega9i8p6u692B9Ufp09UwjB8PL1RMsv0SuM8w\njOUnMogkKkIIIYQ4FYuBvrqur6hYHqnr+hDAaRjGHF3XY4H8Ix7zGBAJjNd1/fBclf6GYZT90SCS\nqAghhBABzh+3J1dMjr33iNVbq7VnAl2OeMzfgb+fzDgyR0UIIYQQjZZUVIQQQogA15S/lFASFSGE\nECLANeVERS79CCGEEKLRkoqKEEIIEeDk25OFEEIIIfxAKipCCCFEgPPH7ckNRSoqQgghhGi0mm4K\nJoQQQvxJNOW7fiRREUIIIQJcU05U5NKPEEIIIRotqagIIYQQAU4qKkIIIYQQfiAVFSGEECLAyQe+\nCSGEEEL4gVRUhBBCiADXlD/wrelGJoQQQvxJyGRaIYQQQgg/kIqKEEIIEeCkoiKEEEII4QdSURFC\nCE6BpnsAACAASURBVCECXFO+Pfm4iYqu61ZgDpAMKOAewzA21tcOKVOxecJKCrfmYAm2cvbkiwlN\niqhsz1+fiTFtNShwxIfScVpvLDYrO19OZfDywexw7yVx+Fm0vrEDruxSNj3+A57CcpRSnDOtN56i\ncrZMXl21vdQMzp19BTEXJ9RXSCfFNBVLJ6ZzyHARZNO4YVILopNsABRleVg46kBl34NbXFz5YCwX\n3BwFQGpqKq89s4fb3kyqsc3UjwtY/XYudy1oA8Dqt3NZ+2EBmgYX3RZNx37hDRTdiTCJ0yZgZyuK\nYNLVZNwk/a5XnDYOkyiy1IMANONlBg9eTpLmJk8Np4AbK/vGalMoV+3JZ3DF8iRCWINJGKBxQM3G\nxNkg0R2TMon7dAL2jK0oazDp107GHV0Ve9Sq14lc9z7e0GYApF/zJO7m7QDIzs6m3QsD2Tf89cp1\nALFfTqG8eXvyzx+M/dBmYr+cUtnm2J/KgZTZlJx2cQMFeDwmcVETsAdvRalg0nMn4/Ye5dhHjcM0\no8gqeLByXXZ2Nu1aDGRf1uu4PVXxh4d8TJTzbfZmLqgxTuuYuygqvYL84sH1GdDJM0148r9g7AFb\nMPzrbkhqUdW+YTtMmwcoiIuGqQ+AreJlPHUbPPcOvPFEVf+vfoIvV8H0/6ta98YnkJ0Po4Y2SEgn\nTJnEeSdgVxXnftBk3NpRjr+n4twPqjj3vRXnvttNnmU4BdYbsaps4j2PY6EQUBwKmoZFFRHnnVy5\nHYdK5UDQbEosjeX5L/7IiVRUrgVMwzAu1nW9NzAZuKG+dihj2W5Mt5cLF1xHXmoGxtTVnDe7LwBK\nKTaN/4HOL15OaGIE+xZuoXRfIa7MUvLXZvDJgq+4t3gyv726AYBt03+m5YDTadGvHTmrD1K0LZfY\nS5O4YN7VABz6bBeOFqGNJkkB2LysCK9bcdeCNuxNLeWzaZkMm9UaAGdMUGUSsmdtKV/PyKJrSiQA\n3/83m3lLHscTqmps78CmMtZ8kF+5XJzr4acFedz/YVvcZYoXr93VqBIVJ8vQcLNXLcBBKrHaVA6o\n2TX6RLIAO9sooRsAIawmRFvLggULsHQoIVr7LyiwkkML7RGC2U05p1U+3s4m9qnXMIlq0NiOx7ll\nGZrXzd6RC3DsTyX2q6kcuLkqdsehjRwa8DSulmfVfKDXzfjx41HBIZWrrMU5tPjoEYJzdlPe0xe7\nq8WZ7Ltlnm+sTZ/hjGjRiJIUcDqWoWlu9mYuwGFLJTZqKgeyjzj2YQuwB2+jxNWt2tqK+FVIjb72\n4E1EhC363TjNI/6NRSsEtHqIopaW/QxuD8yf5Es8nn4TZj7ia1MKnngFXngQEuNh4TLYnwHtWjFn\nzhxYshBCHVXbmjIXVqyHM9v6lsvKYdx/YMMOuOrCBg/teJyq4twPXoDDTCXWM5UDwUccf+8C7Gob\nJVrFuW+uJsSsOPc7FhPtfRWAGO90CqwDKLL0I8RcjV1to9hyKfssFc9/8zOcZosmlaQ05duTjztH\nxTCMj4C7KxbbArn1uUN5a9KJ6eVLHKI6x1GQllXZVrIrn+AoB7vnpvHziE9wF5QT1j6K7B/24dSb\ncd9997H23q+Iu8z3Zp63Nh3XoWJ+GfkZBz/eTnT3VpXb8pS42TFzDWeM7VGf4Zy0PWtKOb1XGACJ\nnUM4kFb2uz5KKT6dnMH1T8Sjab4X2+gkGzNnzvTVvCqU5HpZ9u8srh4TV7k+rFkQ93/UFotVoyjT\nQ5Ctcb1YO7Q1FKteAJTRGTtpNdtZg0NbT766Ga0iqDDtB1zo3HfffbTW7qFIXQaARgnZ6v8oUAOo\n+sOY2NhNvDaORG0IEfz+jcxfHPvWUHxaReytO2M/WDN2+8GNRK/4DwmvD6XZilcq18cue5ohQ4bg\nccZWrtPcJWT3/j8Kzhnge4OrRisvofm3M8m4amw9RnPyHPY1FJdVxF/eGXvwEcfetgaHbT35xVXH\nHiA2siJ+b1X8FksuMRHPk5n3GNVPCmfI54ClYpyaf5dGYa0BF5/r+71zB0jbWdX220GIDIfXl8It\nE6CwBNr5XtPatGkDMx6qeazP0+GJO6rWlbvhhj5wz42NMnSHuYZireL4WzpjV2m/a3eo9eRbqp37\n5g+4tIpz33MvRRbfuR9iriVIHaK1eyQR5seUaN0rt6OpEpp7Z5JhbVzP/9ryYq2Xn8bghCbTGobh\n1XX9dWAG8E597pCnqJwgp61yWbNqKNP3pCzPdZG3Np2k4Wdx/tz+5Px4gJxVByjPc1GQlsWMGTM4\na+JFrH/oGwBK9xcRFGmn69z+OFo62TVnfeV297+/lRb92xEcZa/PcE6aq9jE4ax6cmhW3+Wg6rYs\nLyaug43mbav+TmdfGY7VWvU406tY/Pgh+o+OxRZa8zBbLBqr387llcF76DwggsbEStERl2GsgFnx\nWwbNtVlkqPFUf6W1kouDNGbMmEG6mkhL7SEAPCRQRqca29coJU+N4JB6hn3qv0Rp72DDqOeoTozV\nVYRprxa7xQrKrFwsPPsa0q95kn0j3iBk76+EbfuGiNQP8IZGc/HFFf8ZVrwpeaISKGtdM/bDIte9\nT+FZ/TFDGldFyaoVYZp/cOwtGTSPmEVGbs1jHxH6AV6zWvwowEuLZmPJyB+NqUIr+9qCthIe8gnZ\nBX9H0xrhOzVAUQk4q/YZi8V3OQggtwDWGTC8P7w2DlZtgNW+N/Mrr7wSgo54Oe/fs+ZyRBhcdPTn\nRGNgpQhTO+L4Vzz/rSqD5t5ZZFiPcu6rinM/aCItPb5zP5j9mESyP3gubq0l0d45lY+JNN+n0NIf\nU2tcz3/xx064VmQYxl91XX8UWK3r+pmGYZQe2efOoBuJpVmtdmiq06RzcWf60x+A3uYnzLQ8CsCO\nqB38I2krr7X3XWd/vVcLPGke8qMSiW4fTVBQEK+1m8wAexoTc+5gbdQS5l72DJFEsvmyzTz//PO8\niK+MmrI0hRdffJF44mu1vzVoj9R6EzudU33xa774Z5m9GWz9uEaff3z8Dx699VbO086rsX4f+2iu\nnUGK9i7rN63Hu+cxVk1oRnl5Obk7MtgxtQdjxowBIGU4uG92c+edd9Lmp3u58MLal4JTttV6E0yd\n6qRz52L6+8Knd2+Tnd/6XoDnzfuCxYtzCQu7k6ysLMrKyvi//2vPzp3NiI4+jaCgIMq3tWPAADu/\nzs0hOjoagJkzISYGBg8G0wyhtHQEYWF2wM706d1JTt7CgAF67Xe+lqbuOyL2OSY7R1S9+RTdcCtO\np++F/J3g3uTlbWLlypVomsaIEStpkbuFHitHM3v2bGJiYgCYmVcV+2EpS5b6nvt1+NRneO03cdRj\nv+PYx37Rog+q4o/bQo8LR/PII48wYcIemjWbQHl5Odu3b+eeu6YQHBzMzz+nY7ffwv79+wkODmbc\nuIRqSU5tdK6DbcDU8DZ0Lomjv8W3vd4qiG+DfOf5jmZO/pHUlo9P8/2BXu91NZ6NpdzRw9f3f9qZ\nPKiF8a6lal9Wa2W8q/3Cc9XWLdZ2slPz8KClbvYZgA2130Stz/20qnP/+uuj+PmTy4iMhM2bL+P5\n55/nlYoiZEpKXT//G8el88ZS/agPJzKZdgSQYBjGU0Apvn9xzKP1neNZzMHgrKM1nbD0Lnv4YvkP\nfNp/A3nrMvDoQfyNpwEwE73sLTnI7XseJzQpgnW/fk3rQcmgFHveXMrIkSO5M/0J9pQdYHzUHCxd\nwrjtm4dpNeB0dv+UhqtDCX/jadyF5ews38uk+Ddqta9H6qV+qPU2Ss8r5I3liyjs9xJ715USoRey\nUF1fo8+qtJ30PHcn2474p7Ans8lWW3z9z4FbPrYA+eTtd5M9ysNpo39k1o5+fPV8JkNfbI2yKrJt\n+/nWMpbd1f7zPFU3Jy+p9TacdCFMW076//XHwTqiNR2tw+HWERU/EMFibNpOBj5yI2F8Q5T2JiNH\njiSoQzqJWinNL6xKmKMBLzBkHNjYRQttFHvUYsBLovYr6Wog5Q/VcsefOH6X43EWdiFs7nLSs/vj\n2LeOaKeO9pavzVJWSJtXrue3ez5BBYfQctEq8s8dREm/+wBQwyHxyhGkXvQk730eU7nN6FTwOmGI\np2o7CYfKafFVXWYpVF0crgWnowthIctJz+2Pw7aO6HAdLexwa7VjH7oYW9BOBg6/ESomTatiSGwz\ngtStT/LeJ+2ApQAEWffTMnoUYyc/VmOs6PCZeM1Yel1VN3MUOhSm1sl2ODcavvmQv1/VCtZtheSW\nJJsV227tgZI8kn/7wjfB9pevYdDlPG2mstXSmcvUZlDFVf0B1A5QuSytsW4PqAxeNuton4FtnWuf\n9DjNLoS9sZz0R/rjMNcR7dXRzjncWu34exdjUzsZOP5GwsxviPJWnPsd00l0l9H8kihaerqQ2OMb\nCq0DiPL+RJDqwJxzwKIKSfCU0+KKunv+Z/yvkNjYxpGsNFUnUlF5H3hd1/VvgWDg74ZhuOprh+L6\ntiF7xX5+GuyrIpz91CUcXLoDb4mbhJQzOHvyxax/8BtQiqgu8cT2TgQg9+dDDBo0iN3mQc4c3xPN\nopE8+kI2Pf49++ZvJijCxjnPXgr45rqEJDTOJ9ZZfZ3sWFnMnCG7AbhxSkvWLy2gvMSka0oUxTke\nHOHHuGJ3lCknSlWtj21vo+UZdl65eTdokNzbSduutU9S6koRfQllBYmarwRwSD1FOEuxUEI+KTX6\nqoqgiulDCD8zaNAgWmsmGeoJfv+H8C2XcxoF6gYStZuBIArUwBoTbf2p6Iy+hO5aQeLcitivf4rw\ntKVYykvI75JC1mUPkjjvFkyrjZJ2PSk5/ZIT27BW9bcIztmFO6rxTB6vrqisL6GOFSTGVsSf+xTh\nIUuxWErILz76sT++ak/+QNC3G6xcD0PH+ZYn3wuf/ADFZZByBUy6Bx6e4Tupz9PhkppV1erHumLF\nUdbRKP8kRVrFue+uOP5BTxHurTj3rX9w7lv6EGJWnPsek4yg8aBZyAwaTbzncaLM+XiJ4FDQswAE\nq124aZzP/9pqyhUVTam6u1Y7xf2aqm1FpTZe5JHK6os/1EVFpTZStCW/q740pLqoqNSG2ka16ksD\nq4OKSm2o4VRWX/yiDioqtaGKqVZ9aXh1VlE5RVstnWtWUhpYXVRUakNtoFr1pWFVVFT8nvqNZmK9\nTLyayhN+j63p3s8khBBC/En8qT/wTQghhBCN25/6c1SEEEIIIfyl6aZgQgghxJ9EU55MKxUVIYQQ\nQjRaUlERQgghApxUVIQQQggh/EAqKkIIIUSAk9uThRBCCNFoye3JQgghhBB+0HRTMCGEEOJPQibT\nCiGEEEL4gVRUhBBCiAAnFRUhhBBCCD+QiooQQggR4JpyRUUSFSGEECLANeXPUZFLP0IIIYRotKSi\nIoQQQgQ4+cA3IYQQQgg/aLopmBBCCPEn4Y/JtLquW4DZQCfABdxhGMaOau0XAM8CGrAfuMUwjPKK\ntjjgV+BywzC2HmscqagIIYQQ4lTcANgMw+gJjMaXlACg67oGvAL81TCMXsDXQLuKtmDgZaD4RAaR\nREUIIYQIcF6s9fJzHBcBnwMYhrEa6FqtLRnIBkbpuv4NEGUYhlHRNh14CTh4IrHJpR8hhBAiwPnp\n9uQIoKDaslfXdYthGCYQA/QE7gd2AEt1Xf8FaANkGobxpa7rY/BdFjomqagIIYQQ4lQUAOHVlg8n\nKeCrpmw3fDz4Ki9dgZFAX13XlwPnAm/ouh5/rEGkoiKEEEIEOD/dnrwCuA54T9f17sD6am07Aaeu\n66dVTLDtBfzXMIzphztUJCt3G4aRfqxBJFERQgghxKlYjK86sqJieaSu60MAp2EYc3Rdvx14p2Ji\n7QrDMD47lUEkURFCCCECnD9uTzYMQwH3HrF6a7X25cCFx3j8pScyTp0mKjFkA4fqcpMnraUfxx/8\n/Ed+GxsgZZR/98Hxc47fxvaJ9ts+JEbt9cu4VTrTYXiq30a/ctiXfhvb52HuL5p+/G715H/a5X4b\n+7Agi9d/gz/vv6ErNYZ98KOm/KWEMplWCCGEEI2WXPoRQgghApx8e7IQQgghhB9IRUUIIYQIcPLt\nyUIIIYQQftB0UzAhhBDiT6Ip3/UjiYoQQggR4JpyoiKXfoQQQgjRaElFRQghhAhwUlERQgghhPAD\nqagIIYQQAU4+8E0IIYQQwg+koiKEEEIEuKb8gW9NNzIhhBDiT0Im0wohhBBC+IFUVIQQQogAJxUV\nIYQQQgg/kIqKEEIIEeDk9mQhhBBCCD+QiooQQggR4OT2ZCGEEEI0WjKZVgghhBDCD6SiIoQQQgQ4\nqagIIYQQQviBVFSEEEKIAOc166mi0gjKGY1gF4QQQgghjk4qKkIIIUSA83jqqaJiq5/NngxJVIQQ\nQogA5/XU09t5oCQquq7HAb8ClxuGsbU+d0iZilUT0sjdWoA12EKPyZ2ISAqrbM9an8fP0zaDUoTG\nO7h42rlYgjRWjl3PkN+GsM/yGz3/dQ6R7Z18O2otZZllABTuLyXuvGZc8ux5/DRpIxlrcgkOs4Km\ncens87E5g+szrBOnTOK+n4gtx0BZbWRcMgl3ZFJlc9T614nYsghvSDMAMi55ErezNfHfjmXYrwdI\n3FNOznn3UNz2Mqyl2cR9Ow5LeQGagkOXTcUTnkBk2ttEbP0QNI3cTrdRdFo/f0X7e6ZJs6enY9u+\nHRVsI2fsGDwJCZXN4fPnE7ZkKWZUFAA5Y0bjSWhN9OQpDDlwkDjTJOex0XjatCHot9+InvwUaBqe\npERyxj4Gmkb4/PmEfvU1AKU9e1Bwx+1+CfUPmSZM+C9s3QPBwTD5bkhqUdW+fjtMmwdKQXw0THug\n6sUkdRs88w7Me6Kq/1c/weer4Nn/q1r3+ieQnQ8PDm2QkE6EMhWbJ66gyMjBYrNy1qRehCZFVLbn\nb8hk67TVoBT2+DA6Tu2NxWZl18vrGPzNYHa495I47Cxa3ZhMeXYpm8Z9j7ugHICOU3vjKSrHmLKq\nanupGZw7qy/NL0743b74gzJN1ITXUBXH3TL5LrSk+Kr29Tswp70FSqHFR6NNuw/N5nsJT01NxfvM\nv7DOG+fru2kX5j3PQBvf80YbcgWWq3tUjmPe9TTaFV2xDL6igaM8BtMk7t0J2PdvRQUFkz5sMu7Y\naq99/3udyJXv43X6XvvSh/4Ld1xbkqbeyIg3nCTkgjsmkfThU7Dv3USr/9yDO7YNAHmXDKWoS39C\nN35L889mA1CWdA6ZKY83fJzipB03UdF1PRh4GSiu/92BPcsOYbpNrl5wEZmpufwydTOXze4KgFKK\nH8dvoM+L5xOeGMrWhXso2ldC0b4SPKVe5s+fzwMrb2Htvw36zDif3s+dB0B5gZsvblnFBWPOAiB7\nUz59X+uGPaoRpIpHCNu1DEw3+25YgD09lZhV0zh41azKdnvWJtIvm4Yr5qzKdeHGB3gdzXj77ekE\nPZVH0vs3Utz2MmJWTacw+XqK2vcj5MBq7DnbMIPDiNy8gD1/+RDNW0abhdc2qkQl5Nvv0Nxu0v87\nB1vaRqJeeJGs6dMq221btpI9YTxuXa9c5/jxR7SyMubPn0/Ul58T9dLLZE2dQuScVym47a+U9ehB\n8ycm4FixAne7doR+8RXpc18FTSPuzrsp7dMb9+mn+yPco1v2M7g9sGCSL/GY+ibMfsTXphSMfwVe\nfBAS42HhMtiXAe2BOR/Bku8hzFG1rUlzYcV6OKutb7msHMb+B9J2wFUXNnRkx5Sx7DeU26TbguvJ\nT81g67TVnDurL+A79zeP/4FOMy4nNDGCfQu3ULqvEFdmCXnrMvhkwVfcUzSF3a+uB2Dr9J9oeX0H\n4vu1I2f1AYq25RJ7aRJd37wGgPTPd+JoEdZokhQAlv0Cbg/WBU+iUrdjTn0L6+wHAV/85vg5WF78\nJ1piPObCryuOeyvMOUt4fMmvEKYqN6U27kIbeTWWkdf8bhj174VQWAKa1mChnQjn+mVoHjd7H1qA\nY1cqsR9M5cDdsyvbHXs2cujWp3ElVr32aW4XAPPmzUNbVrUt+56N5F42krzLR1b1LSsi9sNn2PuP\neZhhUTT78hWshTl4w6PrP7gG4K2vSz+NwIlUVKYDLwFj6nlfAMhYk0vrXrEAxHZuRnZafmVbwa5i\n7FHBbJy7k7xthST0jiOyvZPSLBflhR6UUrgL3ViCa84RXjtjK2eMaEtIjB1lKgp2l7By3AbKslyc\nPiiRDn9JbIjQTkhI+hpKEnsB4IrvjD0zrUa7PXMjzda+TFBJFsVJvck97y6K2vejqP1Vvg7KRFl8\nh9WRvhZX8zNovfQ23OGtyez5GCo4hD2DPgLNQlBhJsrauJI1+/r1lPXoDkB5x7Oxbd5co922ZQuR\nr7+BJTuHsot6UnDrLSi7HUtREUopLEXFqGBf/Mpux5Jf4PsPtLgEgoLxxseT+cLzlS/SmteDstsb\nNsjjWWNAr3N9v3fuAGk7q9p2HYSocJi7FLbthd5doH0rX1ubFjDzIXjkxar+XXTo2w3e/cq3XO6G\ngX3g4k6w80CDhHOi8tak07yXL3GI7BxHQVpmZVvJrnyCo+zsmZtG0bYcYvokEdY+igOLtxGe3Iz7\n7ruPdUWbSH7Yl3zlr00n/Ixofr3tU0Jah6M/1qNyW94SNztmruGCt65t2ACPQ60xoFdnALTOpx/1\nuKu5n2Ju24vW+zy0iuOutWnBzJkzufKR+6v6b9yF2nUQ79e/oLVpifbYLWhhDtTnq8FiQevVyZf0\nNiKOHWsoPsv32lfWrjP2PUe89u3dSPQX/8FakEVxxz7kXnkX9n1bsJSXcvvtt5OQ4SHr+lGUteuM\nY08atozfcK7/GndcGzL+8hghO9fiapVM7KKpBGftJf+im5pMktLkKaX+8Cc5OfmvycnJYyt+X56c\nnKwfq3+2maFqa+zYserbb7+tXO7Tp4/yer1KKaV++eUX1alTJ7Vjxw7ldrvVbbfdpn788UfldrvV\n8OHD1ZVXXqm6deum1qxZU/n4rKwsdc011yjTNJVSShUVFamXXnpJlZWVqaKiIjVw4EC1ZcuWWu93\nXTlW/EopNXPmTJWbm6vKy8vVXXfdpZYvX17ZVlhYqIYPH66WLl2qlFLq7LPPVh988EHl41544YXK\nvm+99Zbq1q2bmjlzZj1HdHJOJX6Px3PU45+Wlqa6deum+vXrp1JSUpTL5arcjmmaaurUqWr8+PEN\nF9wJOpVz4LC9e/eqlJSUGttbtWqV+uc//1lj3QcffKCeeeaZeozi5J1K3I8//ri67bbblNvtVjt3\n7lRXXXWVUurYz/033nhDvfjiiw0Y2Ympy+O+aNEitXHjRqWUUi+99JKaOnWqMgxDPfDAA8o0TTVj\nxgw1f/78BorsxJzKuW8Yhlq4cKFSSqldu3apK664Qnk8nqPGv2TJEnXRRReprKwsVVxcrG644Qa1\na9euutr9Y76XNsSPLTtf1cePv+NSSh23ojISULquXwGcC7yh6/oAwzDSj9b5fc/rZAUfrFXitNG5\niYziHfzAhwDkmTlMtTwEQH5UESFJwSxoPxMAV68cZqQ9hblO4eni4Yt/fsHYQ/dy1623c/3Hl2C1\nWdjy+W+EX2fhKa2ihBqi8Izw8qx9DNiB7iU8vWUcp+m1LwE//tyztd5GjBHGjNxiin7x/bfTNt8k\n6N8a4Fu2lN/C315zAhDp6c37/91E7preBBUd5LrUv7EsZihvG1eDoWgXHMVNWy7FfE5hy7qUmJ//\nzT88h/+LGgqDbuLAort4ZNcqSlvV/jKA/bbcWm8jKjiI2ZnplOblANDK4yGsIK+yXRtwPQ9hQnEh\nzm4X8OGaX2HdGrSzzuTQvHk4jS385f4HOPjOW7QcNYrM/7yEp11bnO8vou3ECeQ+/BC4XDSfNBnT\n6ST3kYd5umKs2kiM2lvrbVRylrKweBMQ6Vs2XZxh2eD7PSodkuLo174Q2Ai9TuP7tK/Y2r07yaQC\nGUBxxe+H7QByWVpj3R4gg5drrDt1V6ova70NI2wzRnE2C9VqALLNfP5PexYUFEflEZQUwnPtFgGQ\n0cvDpLRZuCNd2No5CAoK4tm275Npz+eu7CfRooL4/NKNfK22U3hpNtv//Qtble8ywU9LP6LTjCt4\nQE2v9T4f9j/t8lpvw3QWs6g4DQ3f+e01y+hoWQeAijqAmRTLte3zgDzMXu1YkfYFlu6+iuiXxLGO\nYs5ija9/3zi08DJgDapva8x/fcVcSyYqfSdn3DIQ9mdCcBATE8rQLu5U633fvKxLrbcRk+3khVXF\nFPmmFdGuxMT6v6rquCXpVh74peK1L74373+8iZy+PdGcbbgJaLe9LYlaFI7FWZj2vpgHwuEA2Jx9\nif30X+SG9CSqRUdi1jYHIDa+K+cs3ExRl7a12u+MzoXExobXahvi2I75OSqGYfQ2DKOPYRiXAuuA\nW/4oSakrcV2ase+7DAAy1+XSTK96AjgTQ3GXeCjY45suk/5rDlEdwvGUeggO802GtUUEY7pNlOl7\nQz74YxatL4mt3Eb+riI+G/ojylSYbpP0X3Np3jGyPkM6KaXxXQjb8y0AjvR1lDevmothcRWS9N71\naO4SUIqQA6twxXTEWpJF609u5+GHH6ZQH1i1rRZdCNvt21bowZ9xNetAcN4uWn7xt4oNBqGsNpTW\neK5tujp1ImTFjwDYNqTVmDuiFRXRcthwtNJSUArHL79QfuYZaKVlmGG+CddmRDia14tmmmiuMlRo\nKADemOZYiooAiH34UcqTk8l99JFGd50e8F2u+W6t7/d1W0GvmlBIYjyUlMGeQ77lXzdDh8Zz6bI2\norrEk/WtL+HLW5dBuF5Vlg9JCMdb4qFkT4Gv/ZdDODs0I+r8eLK+3wdAWXoxZqmH4CgHUV1akPXt\nHgByfz6Is4NvAqa7sByz3MQRH0Zjo3XRUd9VJCbrth3luLtQe3wvv+pXA+0Yx928Yypq/Q5fN/vZ\n8AAAIABJREFU35Ub0Dq2x/LwUKwLfRNutYGXoN12TZ0kKXWl7LQuhG38DgDHrnW4Wld77SstpM3k\n69Bcvte+0K2rKEvqSOSPHxD7wVQArHnpWFzFeCJiaD3rDuy7ffOVQresxJXUEVfi2dgObMNSlAte\nD45dqZS37NDwgdYTj9taLz+NQaO7PTmpbwsOrMji08ErAbjoqU7sXLofT4mX5JQkek7uxPcPrkMp\nRVyXaBJ6xxF3XjN+GJPK0KFD2e3ZQZcHzyDI4fsDF/xWjDMxtHL7UaeFc9oNrfn05pVYgjROH5hA\n1GmNJxsubteX0P0rSfhwCADpfabg3L4Ui7uEgjNTyLpwFAkf34qy2ihp3YOSpF7ErJiMpbyQWbNm\n0Xqfb+Ltgf5zyOr+KHHfPU7kpvmY9ggOXfYMpj0cV8wZJCy+GTSN4qTelLXs6s+Qayjt0xvHTz8R\nf+ddAGSPe5zQL75EKy2l+IYB5N13L3H33Y8KtlHW7QLKevTA1bEjzf81iaFDhxJXVkbevfegHA6y\nHxtDzJjHUHab7w6ix0YT8s032NetRfN4CFnpS4jy7ruX8nM6+jPsmvp2802AHey7g4On7oWlP/gS\nlJQrYPI98OAM3xyDLjr0Pq/m449MvjTt6AlZI8vR4vq2JWflfn4asgSAs6f05uDSHXhL3CSknMFZ\nk3qx4aHloHxJTcwlvjfqvF8OMWjQIH4zD3LG+J5oFo3kRy9k0+Pfs3f+ZoIj7HR85lIASn7LJyTB\n6bcYj6nvBbBiA97Bvju2LE/dg7l0BZSUYUm5HMvkuzAffBEUaF2S0XqfW/Px1Y6nZeLtmBPnQpAV\nLS4K7ck7GzCQU1PUuS+hm1eQ+OxgAA4Nf4rwX5ZicZWQf1EKWTc8SOILt2AG2SjRe1Jy9iXg9dBi\n3hiGDRtGy1xIHz4FLFbSB08k/t2JKGsQnsg40oc8iXKEkTXgQRJm+e7yK+xyNeUtG9Ek+loyvY3u\n7bzOaKoOJ1S94p6uanvppzYe4zmmMMpv49fFpZ/aMEdpWJ7z3wS5urj0UxulUdGE1MFlnFNRp5d+\nTsFWOh9xuadh1cWln9qYqT1cp5dyTlZdXPqpjU10qbzs4w91cemnNtQV1LjrpyFVXPrxe9qvHXDV\ny4u/amX3e2xNNwUTQggh/iya8O3J8l0/QgghhGi0pKIihBBCBDqpqAghhBBCNDypqAghhBCBzuP3\nOa/1RhIVIYQQItB5/L0D9Ucu/QghhBCi0ZKKihBCCBHopKIihBBCCNHwpKIihBBCBLomXFGRREUI\nIYQQJ03XdQswG+gEuIA7DMPYUa39n8DtQGbFqrsMw9im6/oY4DogGJhpGMYbxxpHEhUhhBAi0Ln9\nMuoNgM0wjJ66rl8IPFux7rAuwAjDMNYeXqHreh+gR8VjwoBHjjeIzFERQgghAp23nn6O7SLgcwDD\nMFYDXY9oPx94TNf173VdH12x7ipgg67rHwIfA0uON4gkKkIIIYQ4FRFAQbVlb8XloMPmA3cDlwEX\n67p+DdAcXwIzCLgHePt4g0iiIoQQQgQ6Tz39HFsBEF5t2WIYhllt+QXDMHIMw3ADnwDnAdnAl4Zh\neAzD2AqU6boec6xBJFERQgghxKlYAVwNoOt6d2D94QZd1yPxXeIJ03Vdw1dV+QX4AehX0acVEIYv\neflDMplWCCGECHT+uT15MdBX1/UVFcsjdV0fAjgNw5hTMS9lOb47gpYZhvE5gK7rl+i6/hO+Ysl9\nhmGoYw0iiYoQQgghTlpFgnHvEau3Vmufj2+eypGPe/RkxpFERQghhAh08oFvQgghhGi0mnCiIpNp\nhRBCCNFoSUVFCCGECHRSURFCCCGEaHhSURFCCCECnVRUhBBCCCEanlRUhBBCiEDnn29PbhCSqAgh\nhBCB7vjfdBywNKWO+cm1J+XclR61vtRaZ9s7WeblGpav6y6ek6X6+m1o3/imhmbxX/whuTl+Gxug\nJLI5ofnH/MqIevNp5DV+GfewPqziG7r7dR/8yd/xP6dG+W1sgCVaCterhX4b/6PbBvttbABtroka\n6Z+ZDFlP5xMbG675ZfBqtHeolxd/NRS/xyYVFSGEECLQyWRaIYQQQoiGJxUVIYQQItA14YqKJCpC\nCCFEoGvCiYpc+hFCCCFEoyUVFSGEECLQSUVFCCGEEKLhSUVFCCGECHRSURFCCCGEaHhSURFCCCEC\nXROuqEiiIoQQQgS6JvylhHLpRwghhBCNllRUhBBCiEDXhL89WSoqQgghhGi0pKIihBBCBLomPJlW\nKipCCCGEaLSkoiKEEEIEuiZcUZFERQghhAh0TThRkUs/QgghhGi0pKIihBBCBDr5wDchhBBCiIYn\nFRUhhBAi0MkHvgkhhBBCNDypqAghhBCBrgnf9SOJihBCCBHomnCiIpd+hBBCCNFoSUVFCCGECHRN\n+Pbk4yYquq6vAfIrFncahnF7ve6RaRK3YCK2/QYqyEbG8Em4Y5Mqm6O+fp2IlYvwOpsBkDHsSdxx\nbUl8aiAjXnfSOhfcMYlkjJiMfe8mWr50L+7YNgDk9x5KUZd+hG78juhPZwHganMOmSmP12tIJ8ck\nLm4idpuBUjbSMybhdif9rldc3DhMbxRZ2Q8CblrEj2XYsAMkJpaTk3MPxcWXERy8kxbxj6PQcJe3\nJT1jEqARGvodzaN98Ze5ziEzsxHFb5o0m/YMwdu3o2w2csaOxpuQUNnsfGcBziUf423mO/65Yx7F\nk9CaZpOfYsj+g8SaXnLHjsbTpg1Bv/1G9OSpgIY7KZHcx8eApuF8ZwGhy74GoKxnDwruuM0fkf6O\naSrmTyhh31YvQcEat0wOJTbJCkBBlsmcfxZX9t23xcuND4Vw8U025o0t4eXfhlCgFTJsYiitOlg5\nsN3LW+N8/ePaWrllUigWq8byt8tYtbgcNLjyNgfn97f5Jdaj+bPHr0yT9IlLcRmH0GxBtJh0A7ak\n6Mr20g37yJz2OSgIig+n5dS/oNl8L+HZ2dnsGDidxLkjsbWLoWzzQTImfwIWC5rNSstpfyGouZOc\nuSso+DgVzRZEs+Hdibi2k7/C/R1TwcSdcRglNmyaYtLpGSQ5qt59v8oO4+V90Wga/CWugMEt8vkg\nI5wPMyJgxAhcmxLYUmJnRddd7CkL5t4tLWlT8fihLfLpF1PEwvQIFh6KxKop7k3IoU90ib/CFSfh\nmImKrusOAMMwLm2Y3YGw1GXgdbPv4QXYd6USs2gaB++ZVdlu37uJ9L9Ow5V4VuU6ze0CYN68eVi+\nVlV992wk7/K/knf5yKq+ZUXELJ7Ovn/OwwyLotmXc7AW5uANr3pB8Cdn2DI03OzdtwCHPZXYmGkc\nODirRp/IiAXYbdsoKe0GQETEErzeZrz99nSsQXm0SbqRXcWX0bz5TLJz7qWkpBct4h8mLOwbSkou\nIDZmOnv3zcM0o2jWbA5Waw5eb+OIP+Tb78DjJuPVV7ClbSTq3y+S/cy0ynabYZA9cTxuXa9c5/hx\nFZbSMubPn0+zrz4n8qWXyZ46hcg5r1Jw218p69Gd6PETcPywEnf7toR98SXpr78KmkbcnfdQ2qc3\n7tNP80e4Naxb5sbjhkcXRLAr1cN7U0u5b7YTgIgYCw/OCwdgx1oPS14opVeKjdSv3WgWmD9/Pq/8\ndD4fPu97zEfPlzLwwVBO7xrE62OKWb/czeldgvhugYtxH0ZQXgYTrslvVG/Uf/b4i5ZtRrm9tFlw\nF6Wpe8mc9hmtZw0DQClF+viPaDVjCLbEaPIW/oJ7Xy629rEot5fx48djCamKJWPKp8SNuxaH3oK8\nd38mZ873RA7sQsFH62iz8G4UsPsvLxHavT1BMU4/RVzTspww3AoWnLOP1EI7036LYdYZByvbp/4W\ny+LOewixmFy7rg3XxBQyMM73o82dx8Te8QyKL8AZZLKx2M5fW+UxslVe5eMzy628dTCKRZ324DIt\nDE1LoGfUHmxNZQJEE749+XgVlc5AqK7rX1T0fcwwjNX1uUMhO9dQclYvAFztOmPfk1aj3b5nI80+\nf5mggiyKO/Ym96q7sO3bgqW8lNtvv53WmR6yrv9nxWM3Ysv4jbDUr3HHtSVz0BhCdq6lvFUysYum\nEpy1j/yegxpNkgLgCFlDcYkv/jJXZ+z2mvE7HGtwODaQn38zNttOAAoL+1NIv4oeJkr5DqtSdqzW\nPEBhsRSjVDAhIetwlScTGzuV4OB95OcPajRJCoA9dT1l3bsDUN7xbGxbttRot20xiJj7JtbsHEov\n7kHhrbeg7Ha0oiKUUliKilBBwQAoux1Lfj4ohaWkBBUchDc+nswXngdN823Q40HZ7Q0a4x/ZscbD\n2b18+96ucxC7034/O04pxbuTSrj92TA0TePcK2x0utT3mOz9JqGRvrjufjEMi0XDU64oyDQJCddw\nRlsY91EEFotGfqaXYLvWcMGdgD97/KVr9hDW63QAQjonUpZ2oLLNvSsLa1QouXNX4tqWjrOPjq19\nLACZ07/g0SF3sOLlHZX9Wz2XQlCsL7FTHhPNEUz5zkxCu7VDswWhAfYOcZSm7iX88jMbLshjWFMQ\nQq8oX4Wjc7iLtKKa52WQpijwWLAEgQKqH70NGzawvcTG+PaZAGwqsrOrzMbXOWG0dbgZ0y6TDUUO\nuoSXEmyBYItJG4cbo8TOOU5XA0UoTtXxEpViYLphGK/qut4B+EzX9WTDMMz62iFLWTGmo1qGb7GC\naYLFl/YWdb2GvN5DMR1htHr5AVwbvsHTvBW5V9zOq+Nvwj5/F61m3cXuJz6jrG0nCi5OwZV4Fs0+\n/w/NP52FK/FMQrb+xJ6xH2LaQkh4bjhl7c/FHde2vkI6KVZLMaZZ/T8cK2ACFqzWDJpHz+bAwZmE\nOz+t7KFUKABFRUW0avkPsrP/DkBe3nASWt9OdPRLmN5wSku74XR+QWjIT+ze8yGmGUJiwnDKys7F\n7W7bYDEei1ZcjHKGVa2wWGoc/5Ir+1I06C+YYaHEPDwa92krKOvRnYjycvr160eznByynpsOQGHK\nTcT+7R9EvPY6ptOJq8t5EBSEGRUJShE5YyZuXceTmHC0XWlwZUUKh7Pq5ddi1TBNhcVStW79/9y0\nSrYS39Zao9/o0aP57KsS7p7he+5YLBo5B0yeH1lIaLhGgm6tXL/87TI+nlHG5bc0jgTtsD97/Gax\nC6vTUbXCqqFME81iwZNXQunavcSPu5bgpGj23fMWjrNb4T6QhzU6lIsvvhheBpSvonw4SSlds4e8\nd1aT9NYdeHKLyX7lO8xiF6rcS+navTgvaxxJCkCx14LTWvXWYsV3Oejw4R/ZKpe/rE8i1GJyZfMi\nnEFVfV9++WUeSMypXD4nvIyb4gs4y+niP/uaMWtvc84McxFe7TGhVpMiT1Mpp9Ck7/pBKfWHP8nJ\nybbk5GRHteXVycnJrf+o/7ZiU9XWU089pT799NPK5UsuuaRGe2FhYeXvb7/9tpo1a5ZyuVyqrKys\ncv2gQYPUoUOHVEFBQeW67du3q1tvvVV999136u67765cP2nSpBrj+dux4n/zzTfVjTfeqIYPH676\n9eun+vTpoxYvXqyUUurAgQNq4MCBatGiRZX9+/fvr7Zv366UUuqtt95SEydODOj4lTr68X/ppZfU\nc889p5RS6uDBg+rKK69ULpfrqPErpVRZWZkaNWqUGj9+vDLN2j9n68rxYldKqb///e9qzZo1R318\nZmamuvTSS1VpaWmN9QsXLlSPPvpojXXl5eXq1ltvVatWraqDPa8bEv8fx799+3Z17bXXVi7PnTtX\nzZkzRw0bNkwNHz5cDR8+XHXt2lXddNNNKisrSyml1CeffKKuu+46tXfv3srHvffee2rw4MFq1KhR\n6m9/+5v64YcfGiCyE3Os+Pfv36+uvfZaVVRUpLxerxo1apT67LPPlFJK5efnq2uuuabGto722v/1\n11+rCRMmVK6///77VVpaWl3t/jHfSxvihyFK1cePv+NSSh23ojIS6ATcr+t6KyACOPhHnQet87K+\n1PpHzSckLOg8nAuWk27rh2PXOqKb65XzTiylhSRNHsDucUtRthBaLFlFQc9BPDZlEfb9W0mf8wTB\niw7ROqOYluubk/DsUDJvehxX23OIXL6CoPCOvJ19FonrtxH0UQ5mSDgJ36WS0SaF8mpzW06V6lvr\nTeAMO48w53LS0/vhcKwjOlpHsxzet+EVPxARvhibbSc3DhyA1ZpJQsJtLJj/BD16XoivMArt2pZy\nxpmheDwKZ1gsTudanvzXWSQmbsMalINphpOYkEp6Rgrl5bWPPyQ35/idjreNMzoQsuxLcnp2w7Yh\njYjT2hGanw2AVlREi6EjOPTuOyiHg+bff0fxgOuwr12HGRbGP4HT8NCivJxmuZm0KCnmXG853vxs\nQsJCCMnOZGp+NjF/+weuC7pSeMtwphfUfp8BPo28ptbbsHUp593lbxPSfyI713mI0Uv5hu41+vyc\nls8N563im4rlVR+6yE03mXZ3Kj87rsFlKeB7rTev3FPMTWNCiGtj5bewcjIsbt7d9TUfPFvKvTOd\nqCBFoa2I9dYNlBJc632vC4Ec/3NqVK23UXheKYuWv8FL/QopXbeXQj2C69VCAFSCh10lmfTb/R9s\nSdHs/+UjIm86H+ft1wOwREvh3BH9KJjYh5HRX5P/0TryF/5C6zeHcV/kSlDgyS2moCiV6HduZEth\nGXuGvMLOThdgUftrve8f3Ta41ts4LzuM5Uud9FuYzrpCB3pZNGqkr+JRVhqMZV9Lgu8LR7NA9K4Y\nCja/inq3gJ9zwuje/dHKvgC3r0/g8XaZnBPuYsXBSDqWB3HOq2/z/KbWuHY+icvU2LEhkdMLZ6Nq\nWVTJejqf2IoKlqgfx0tUXgXm6rr+XcXyyPq87ANQfG5fQresJOGZIQCkj5iC8+elWFwlFFycQtaA\nUST8+1ZUkI2SM3pQcnYv8HqIn/cYw4YNo2UeZIyYDBYrGUMmEvfukyhLEN7IWNKHPolyhJE1YBSt\nZ94BQOH5V1Pe8vT6DOmkFBX3JTR0JYkJvvgPpU8h3LkUi6WE/IKUGn1VxVXa6GYvY7UUMmvWLBJa\nzwI09h94hfT0SbRs8XeUslXcQfQvvN5osrJGkdC6Iv7Cqykvbzzxl/bpjWP1z8TdcTcAOePGEvrF\nl2ilpRTfMID8++8l9t4HINhGWbeulPXojqvj2UQ/OZmhQ4cS6yoj7767UQ4HOWPH0HzMWJTNhgoO\nJnfsaEKWf4t93To0jwfHj6sAyL/vHsrP6ejPsAE4r28wm1e4eXpwAQC3PhXGT0vLcZUoeqXYKczx\nzbWorks/G6+PLmb48OFkewpJeSyEYLtGv7sdvD66mKBgDVuoxi2TQomIsZB4hpWpNxegadDxkmA6\ndG0cSQpI/M6+Z1G8cge7h8wBoOWUGylYuh6zpJyolK60mHQDBx96D5QipEsSzkuSj7od5TXJmPwp\nwa2j2P+3+QCEdmtLzAOXUb4ri903/QcsGrEPXYXF2Xguf/WNLmZlXihDNvguxU45PZ2lmU5KTAsp\n8QXcEFfAkA2J2C2KJIebG+N8z5NdpcEkJSVB1RQdJp6WwZM74wjSFLE2L0+elk6YVTGiZR7D0hIw\nFfwzKavpTKSFJn17sqZU7f+TPuzclR5V24pKbZiXazXu+mlodVFRqdX4plat+tLw6qKiUhslkc0r\nqy8NrS4qKrXRh1W/qz78mfg7/rqoqNTGEi2lsvriD3VRUakNba5Zo6LSkCoqKn6fma3dRL28+Kv3\n8Hts8oFvQgghRKBrwrcnN6XClxBCCCGaGKmoCCGEEIGuCd+eLImKEEIIEej8kKjoum4BZuO7O9gF\n3GEYxo6j9HsFyDYMY0zFY/4LJOP7kLA7DcMwjjWOXPoRQgghxKm4AbAZhtETGA08e2QHXdfvBjpC\n5WTfK4EwwzAuBp4EJh9vEElUhBBCiEDnrqefY7sI+Byg4ut1ulZv1HW9J9AN3+cmH757qBSI1HVd\nAyKB8uMNIomKEEIIIU5FBFBQbdlbcWkHXddbAuOBB6j51UwrAAewBV8C8+LxBpE5KkIIIUSg88/t\nyQVA9Y/ltVT7UNhBQAzwKdAC3xccbwFaAysMwxir63oC8D9d1zsahvGHlRWpqAghhBDiVKwArgbQ\ndb07sP5wg2EYLxqG0dUwjEuBqcDbhmG8AYRRVYXJBYLxfQflH5KKihBCCBHo/HN78mKgr67rKyqW\nR+q6PgRwGoYx5w8eMx3fV/N8jy9JGWMYRumxBpFERQghhAh0fkhUDMNQwL1HrN56lH5vVPs9D7jx\nZMaRSz9CCCGEaLSkoiKEEEIEuib87clSURFCCCFEoyUVFSGEEOL/27vz8KjKu//j7zOThZAJhCUg\nQgKichcXAhEVUESrWLCtWy0IipRai0t9Cqh9AEGxgsDjWkTrLpYHBfuoVZa6oNSFVUXCIpwo+w4J\nCVlJMjPn98eJWQRBfyFzJuHzuq5cF3O2+3tz5sx853vfZ6a+068ni4iIiESeKioiIiL1nX49WURE\nRKJWA05UNPQjIiIiUUsVFRERkfpOtyeLiIiIRJ4qKiIiIvWdbk8WERERiTxVVEREROq7BnzXjxIV\nERGR+q4BJyoa+hEREZGopYqKiIhIfafbk0VEREQi77hWVF4/90pCseuP5yF/os2su7SjZ62/EfqN\nZ227HuHB0D2etd7JyvKsbdc7zGg6zJOWhzvPeNLud2zL2xg2XJ/hWdsAzIE+A1d41vzSOUs9a9s1\ngJ6WdzEEH3c8axsg1ssYoqWSoduTRURERCJPc1RERETquwZ8148SFRERkfquAScqGvoRERGRqKWK\nioiISH0XLZN664AqKiIiIhK1VFERERGp7xrw7clKVEREROo7b7/Kpk5p6EdERESilhIVERERiVpK\nVERERCRqKVERERGRqKVERURERKKWEhURERGJWro9WUREpN6rq6+mja2j4/54qqiIiIhI1FJFRURE\npN6rq59PVkVFRERE5AepoiIiIlLv1dUclYQ6Ou6Pp4qKiIiIRC1VVEREROq9upqj4j0lKiIiIvVe\nXQ39eE9DPyIiIhK1VFERERGp91RREREREYk4VVRERETqvYY7mVYVFREREYlax6yoGGPGAL/G/R7d\n6bZtv1KXAYXD8OwEP1uyLGJj4Y5JQdqkuevysuGRkVUhb95gcdPdIX4xMMyoa2JoGRhCMTG0TnW4\n86EQu7fCtNExWD5IO91h+P0hLAvef93H+3N8+GPgt7eF6H6xU5dd+kmcsMPyB9aQZ+fji/PRc2I6\nSWmJleuz1+Tx5dR14EBC60ZcMKUbvhiLpeMyGbRlEDt8W+jx13SadgxU7rN57g7sWVvoN/tCAL6e\nsZGt/94FQNuLWtPljk6R7eRRhMMO8ybsZU9WKTGxFldPOonmaXEAFGYHeX3krsptd28o5fK7Uzh3\nYDIAmZmZvPTINn4/M63GMTPn5rN8Vi5/nN0egOWzcvnqrXwsCy74fXPO6p8Uod79SOEwPPAi2Nsg\nLgYmDoe0k6rWr/kWps4EB2jdDKb8CeIr1mV+A4++Cv+4v2r7D1bAe8vgkf+qWvbKfMg+CHcNjkSP\nfpSwAw/saIVdEkecz2Fi6j7S4qvG3T/IS+TZvc2xLPhN83yub3mQsAPjtrdiy6BB+L5px19T99Kx\nUTnri+OYtLMVPsshznKYmraXFrGhynaGbzqZS5sWcn3LfK+6exgn7LB0wlpyswrwx/roNelsmlS/\n9lfn8fnU9TgONG7diN5T0/HFWCy+dw2Dtgxip28zvR48m6YdA3w86itK9pcCULCzhFbdkunzaDeW\nT/yafSsPEJsYA5bFz5/OIC7g/Vekg/u0f/B/WpH1bTxxsQ4P3LuXtHbu+c/O8XPPuDaV29rfxDPi\n9mzi4x3+Na8JVswQDhWlYn8bz38WbOKBya3IOeC+V+zcHUvXs0v4nwf3MPuNprw1tymWBbf8LodL\n+xR50te60XDnqBw1UTHGXAz0tG27lzEmEfhLXQe0fKFFsBymzg6SlWnx8pQYxj7tlrSSW8LEme6/\nN3xl8erf/Fw+IEyZez0yc+ZM1nNK5bFemhzDjaNCnHmuwzP3+1n+oYVJd5g/08ejbwYpK4Uxg2JI\n7xUkNq6ue/bjbF+4h3B5mH6zL2R/Zi5fTF3HJU+dB4DjOCy7L5M+07qTlJrIN69vpXBHMYU7iwmW\nhHjttde4Y/FQVj2xgT7TugNw4OuDfPvm9srjF2wvYsu8nfT/Z28sy+LdwZ+RetlJNDNNPOnv961f\nWEio3OGPs9uzPbOEf0/Zzw1PtwUg0DKmMgnZ9lUJH/4tm+4DmgLw6fM5zHxnHMHEmknnrq8PsfKN\ng5WPiw4EWTE7jzv+1YHyQw5P/nJz9CUqCz+H8iDMftBNPKbOhKfucdc5Dtz3PEwbBamt4fUPYcc+\nOBV44W145zNo3KjqWJNmwOJM6FxxXRwqg3HPwJpN8IvzI9yxo1t4MJFyB2Z32kFmUTxTd7bkqY67\nK9dP2ZXCW522keAP86v17bkiuYDM4kaUhH289tprLL4ikSd2t2DaKXt4aGcK49vtwySUMSe7Cc/v\na8bottkAPLG7BfkhH5ZXHf0B2xbuJVzu8MvZvdifmcfnUzZw6dPnAO61v+S+tVzyZAZJqY3Jen0b\nhTuKKdhRUnnt37lkCCufyOKSaRn0eawbAKX55bx303LOG3MGADlfH+Tyl84jPjlKXvCq+fDjAOXl\nFrNe2M7qtY145G8pTHvY/WDSskWIl/++A4BVaxox/dkW/Paag1gWXPXLfGKTZzLh3tZce9VBkgJh\nHpm0B4D8Ah+/v70dfxmxn+Jiixn/24x5/9xCcYmP64a059I+mz3r7/F34g79XA6sMcb8C5gLvFPX\nAa1f6aNbb/fNplO6w8a1h7+cOA68MNHPrROCWBZs2WBRWmJx8803M35oDFmZ7j6bvrYOcQkGAAAQ\n+UlEQVQ481z3WBkXhVm9xMc3ayw6ZzjExELjALRpD1vt6HnJ2rfyACf3bgVASnozDqytepPN31xE\nfHIc61/exPtDllBWUE7TjgFi4n2UF5TjOA5lBeX4Yt3TWppbxldPbKD7mDNxKt6/E9skcOkLPbAs\nt8/hoIO/kT+ynTyKbStLOK23+ykyNT2BXWsPHbaN4zgsmLiPKye0ruxH8/ZxTJ8+3a0yVCjODbHw\n8WyuGNuqcnli8xjueLsDPr9F4f4gMfHRc+4rrbShd1f33+mnw9pNVes274bkALw8H4Y8AAVF0PFk\nd13aSfDkXVSebIAMA/f/oWpZWTlcczHcek3N7aLAyqIEeicVA5CeWMrakvga62Msh/yQj0NhHw7g\nsyDe51AQ8uE4DgUhP7EVp/OxDnswCWUABB2LRj63r+/mBfBbDr2bFBNdvYd9K3Np2zsFgJT0ZHIO\nu/ZjWffyZv49ZBll+UH32m/ko6zGtV/z+bxqWhadh7QnoWU8Ttghf2sRS8avYcGgpXzzxnaiyarV\njbiwp1vh6HLWIdatjz9sG8eByY+2Yvxf9mFV6+qaNWv4dlMc111Vs0I2/bkW3DAgj5YtQnyXmRaX\n+Cgq9uHzRdszoP4xxviMMc8YY5YYYxYZY079ge2eM8ZM/in7VHesRCUFOAe4DrgVmPUT+/GTlRRC\n40DVE8jnd0uC1X3+kUVaJ4eTO7iP4xPg6ptDvPjii9z2QJDH7o4hFKr5OpyQCEUFUFJo0Tip+nKH\nosK6689PVV4UJDZQVeiy/BZO2O1IaV4Z+786gLnxFC57uQd7lmazZ1k2KRnNCZWG6devH8vuW83P\nhpxCOOSwZNwquo8+g9jGVcfzxfiIT47DcRy+nLqOFmc0pUn7xMPi8EppYZhGgarEyfK7w0HVbfio\niFad4mjRoepT4ZmXJ+H3V+0XDjm8de8e+o9OIa5xzae5z2exfFYuzw3cRvqV0VFJqqGoBALVfl/D\n76u6CPLy4assuLEfvDwOlq6FZWvddZef725bXf+eNR83SYQLutRd7LVQFPIR8Fdd7H7cYZrvDEvJ\n5TdZaVy5IY1LmhYR8IfJSCyhNGzRr18/7t/eihtT8gBIqRjmWVnUiFezmzI0JZeskjjm5ybxXycd\niLYcDYCywu9f+1Re+4dyy9j3VS6db2zPL14+j11Ls9m9LIdWGc0IlbnX/tL71tL5xg6V+5fklLJ7\nWQ6nXdsOgGBJiDOGdKD3I13p+8K5bHh1G7l29Ax9FRb5CSRWnf8jvfb/59NETu9YSvu0msMczz77\nLLffklNjWc4BPyu+aMzVv3L72DjBof/lBVx1fQcGDk3jhgF5ddMRz5TX0d9RXQ3E2bbdCxgNPPr9\nDYwxw4GzqPoYecx9vu9Yc1SygfW2bQeBLGPMIWNMS9u2s4+0cfuYp4mnw7HaPKp2gSk0L0qnM/0B\n8If7cKbv4xrbPDt3BH8cOpTOuOXNUzuUcUl79//g0g6beSb5t7Tc/yRxvoF0xt13Z+FCUpsspVPg\nAvYWfUpn3DH8mKI/cXaT2+jMmbWKG2DccfhwPiUwhfSidPpbbv8/CPdhvN89jxuTN7I5bQQPn/oM\nAGm9ZxBcFySYGeSac1IZOXIke/bsYejQoUyadBsrttnsmVBMWVkZhzaW45/SgjFjxlBaWsrYsWPp\nEjiPCRMmVFYlosGm7/pfcf6fCvfhet/cGtuMmDuC/x46lG4V5/87O9hBC37GAOawet1qQtvGsmxC\nM8rKysj9dh8bJ/dkzJgxAAy4AcoHlHPLLbfQfvltnH9+7YZBBhzH/8IpgfakF7Wmv+VWVfqEY/jY\nnwHAxuQkRqR1YO6pVwAwo/cVBNcdgp5gW13ZYe3gLiuRORX7Aiy3Spljfclj1Za9ZW1mkxXkrmrL\namVO+NjbHENgyhSK0tOx+rvnPtynD/7X3WrSrl27eHX4cBZ9PpuEhATuuece3uvbly1btnBOz5Ia\nz/25M+cSFxfHggULeOaZZ3huwdM0b9eOFx9+mH2ff87Q+Hh2xuwkNiaW1DvHc+GFF9Y69jG1PkK1\na7/iuf9uuA9jfU8A7rW/MW0EUzo+D0Db3jMIrg0SXBXkmowONfo/de5zxMXFMevdWbT9dTrDreEA\nhBPClAwpITE+EeIhocfDdNrQiavMVbUPPvnxWh+iSfMpHCKd2GS3/w59iG++qcY2Cz4awdChQ4lN\nrrr28/Pz2bJlML1+Xlxj2w/nz+LKqwuJa+b2f+XKlaxe/wQfLXoBgJtvvpnuve6hS5faJe4ptdq7\n3rsAeBfAtu3lxpju1VcaY3oB5wHPAj/7MfscybESlc+APwOPGWNOBhKBnB/aeGvwdkKx64/V5lG1\nyrB4Z5GPDv1D2Kss2hp/jXknACvXxjK829t819J7b/rYYls8cf+3LN57CgeKYslO6Ulq5xj+uaIj\nZ53n8M4nfrr0DJPQ5SUWPx7D6rIZlJXC+o2xhE6fT+2idr3h/KbWx9jWbTefLFrIl/0+ZP+qXPwm\nzETnbgBC7cLsKt7Bf2+9jaS0RD7+4nNOuy7NnRwXiAVG8vekKewv38u8M2fRY677vCjcWcyOUVsJ\njc7hwfBdfHjbctr0bMmZfziNSdzD8aqBd7Kyan2MkowCXln0BgX9/872VSU0MQW8zpU1tlm2dhO9\num3im+/t24unyWGDu30XuGmeDzhI3s5yckYFOXXMUp7a1I8PHtvP4OltcWIccuJ28rH/XrbSuFZx\nj3f+Wqv9a+jWDBa9xYh+bWBVFpg2GGeVu65dEIrzMFvfdYd6vvgQfvtz/gDuNs4+cIqqtgdwvgUn\nl/k1lm0DZy/PVV9WCxuuz6j1MbrlJbLo7QD9ZuxlVVEjTHFznIFuhejQoVh829oQOywJy4LmO1py\nMPNFistiCfjCMHIkSX9qS/mu9oRuSODtvACv5zTlH6fsouldaTjA3eCW/8tgeqg5KVaQC568COfJ\nWofOlDl/rvUxtmbs4dNF77Oq//vsW5VLjAkxmZEAhFLD7Crezphtf6RJWiKLvvyS069LZd/KXHdi\nLCN5rskkssv3MjV8NzH4+Wjpl6TfcTqT2QBA3uZCPh71FVe+dSFOyOHdL5fT69qz+Zr/1Dr2u/Oe\nqPUxupgA//kgkct67iVzTSNO79ic8ryanwDWrO7AWaf8jfJqxZBlnyTSo8fow7Zd8kkbbr35AOV5\ntwJQsL8xcf5krGJ3SCnQ6GTy9rxJeVrNBOenyivPJyUlGua5eTJHpQlQvSwXMsb4bNsOG2PaAPcB\n1wADf8w+P9TIURMV27bnG2MuMsaswB0mut227Totmvbo65C5GEZf74Z25+Qgn8zzcagYLh8Q5uAB\nSEyqGcJl14WZNsbPDTfcQDEx3PlQEL8fho0O8tT4GILlkHqqQ69+DpYFv7opzNjBMYTDcOOo6JlI\nC5Da9yR2L9nPu4M+A6DXQ13ZPG8nweIgpw9oT8+J6Xx690pwICWjGW37tCalW3OWjF3F4MGD2Rrc\nSLdRnYmpPu/EoXI8d/vCPez7IodwMMzOT/YB0G1UZ1K6Not0V4/ojL4BNi4u4vnrtwJwzeQ2rJ6X\nT1lxmO4Dkik6EKRR0lFGLI9Q2XCcquUpHeNo87N4nhu4FSzodFGADt1rl6Qcd33PgyVrYNB49/FD\nt8G8xVB8CAZc6t4FdPeTbscyDFxUs7LE9ytklnX4siNt57G+TYtYUtCYQd+4QxUPpe5lXm6A4rCP\nAS3yubp5PoOyUon3OaTFl3Nt83yKQz7Gbm/N4MGDCW5sy6g22cRZDpN2ptA2rpw7t7h3ipybWMKd\nbQ542b1jSuvbml2Ls1lw/VIALph8Npvm7SJYHKTTgDQumNSFT+5aBQ60ymhGuz6tSOnWjMVjVlde\n+xl3mcprP39LEUmpVUOIyacGOO3qtswfuARfjI/Trm1L8qmBI8bihcsuLmTpisbceEsqABPH72HB\ne0nuxNerD3Ig109S4PD3si3b4khLSzvi8nYnVw1d9Dq/mKUrGjPo96n4fHBO1xJ6nle7JEXIB6pn\nadUTjuuAlsAC4CSgsTFmwzH2OSLLOY6DtVnlVzi1rajURmc2H1Z9iaTjUVGpjXHWI5XVFy8cj4pK\nbQzgncOqL5FyXCsq/x9sq2vNKkqEHY+KSm1Yc8KV1RcvHI+KSm2M4fHK6osXjkdFpTZik53DKiqR\nUlFR8Tzrt6zldVJEcJzzf7BvxphrgV/btj3MGNMDGG/b9i+PsN1QwNi2PfbH7lOdvplWRESk3vNk\n6OctoK8xZnHF42HGmEFAwLbt53/sPsdqRImKiIiI/GQVU0Fu+97iw0rr1b8o9gf2OSolKiIiIvVe\nw/1mWv3Wj4iIiEQtVVRERETqvRP3K/RFREREPKOKioiISL3XcOeoKFERERGp9zT0IyIiIhJxqqiI\niIjUew136EcVFREREYlaqqiIiIjUe6qoiIiIiEScKioiIiL1XsO960eJioiISL2noR8RERGRiFNF\nRUREpN5ruEM/qqiIiIhI1FJFRUREpN7THBURERGRiFNFRUREpN5ruHNUlKiIiIjUexr6EREREYk4\nVVRERETqvYY79KOKioiIiEQtVVRERETqPc1REREREYm441pRiQmdcjwP99PFgr+8s2fNt6SNZ20D\nEAstg97FEKDMs7YBiIVAeQdPmu5EnCftVoqFTkHvYgimpnvWNkCsxzG0KPf+2vcyhqDT1bO2oeL8\nexyD9xruHBXLcRyvYxARERE5Ig39iIiISNRSoiIiIiJRS4mKiIiIRC0lKiIiIhK1lKiIiIhI1FKi\nIiIiIlFLiYqIiIhErQbxFfrGGB/wNNAFKAX+YNv2Rm+jijxjzPnAFNu2L/E6lkgxxsQCLwHtgXhg\nom3bc72NKnKMMX7geaAT4AC32ra9ztuoIs8Y0wr4ErjUtu0sr+OJJGPMSuBgxcNNtm3f7GU8kWSM\nGQP8Gvc736bbtv2KxyFJHWgoFZWrgTjbtnsBo4FHPY4n4owxf8F9w4r3OpYIuwHYb9v2RUA/YLrH\n8UTar4CwbdsXAuOASR7HE3EVyeqzQJHXsUSaMaYRgG3bl1T8nUhJysVAz4rX/YuBjp4GJHWmoSQq\nFwDvAti2vRzo7m04nvgWuBawvA4kwv4J3Ffxbx8N+Xukj8C27beB4RUPOwC53kXjmYeBvwO7vQ7E\nA+lAY2PMe8aYDyuqqieKy4E1xph/AXOBdzyOR+pIQ0lUmgD51R6HKoaDThi2bb/JCfYmDWDbdpFt\n24XGmCTcpOVer2OKNNu2Q8aYGcA04FWPw4koY8zvcCtq71csOtES9SLgYdu2fwHcCsw6gV77UoBz\ngOuo6Lu34UhdaShP6Hwgqdpjn23bYa+CkcgyxqQCHwH/sG17ttfxeMG27d/hzlN53hiT4HE4kTQM\n6GuMWQR0BV4xxrT2OKZIyqLiDdq27W+AHPD611EjJht437btYMW8pEPGmJZeByXHX0NJVBYDVwAY\nY3oAq70NRyKl4k3pfeAvtm3P8DiciDPGDKmYUAhQAoQr/k4Itm33sW374ooJ5KuAm2zb3ut1XBE0\njIo5ecaYk3GryyfKENhnuPPSvut7Im6iJg1Mg7jrB3gL91PV4orHw7wMxmMn2s9hjwWaAvcZY76b\nq9Lftu1DHsYUSf8HzDDGfIx758Ofbdsu9TgmiZwXgZeNMZ9UPB52olSTbdueb4y5yBizAvdD9+22\nbZ9or38nBMtxdF5FREQkOjWUoR8RERFpgJSoiIiISNRSoiIiIiJRS4mKiIiIRC0lKiIiIhK1lKiI\niIhI1FKiIiIiIlHr/wGK6rPOpl0UhwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x21b70e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mushroom 0.337943462433 0.156343684069\n",
      "bird 0.610161279427 0.140883467857\n",
      "mushroom 0.486111111111 0.139172046958\n",
      "bird 0.491134036032 0.119476916815\n",
      "mushroom 0.373242630385 0.130118429056\n",
      "bird 0.592905733722 0.114589499268\n",
      "mushroom 0.402696793003 0.15563571354\n",
      "bird 0.482745825603 0.139672229107\n",
      "mushroom 0.662779397473 0.185824326297\n",
      "bird 0.403896103896 0.143163779527\n",
      "mushroom 0.342970521542 0.132749930714\n",
      "bird 0.553244374673 0.125596191779\n",
      "mushroom 0.847424684159 0.148489421886\n",
      "bird 0.18556998557 0.128906477702\n",
      "mushroom 0.271036899608 0.162722121341\n",
      "bird 0.602818270165 0.100311506892\n",
      "mushroom 0.855685131195 0.141343467903\n",
      "bird 0.184353741497 0.13142854013\n",
      "mushroom 0.448412698413 0.18082789508\n",
      "bird 0.565184815185 0.128781663134\n",
      "mushroom 0.759475218659 0.174516308468\n",
      "bird 0.331292517007 0.152623376432\n",
      "mushroom 0.684766763848 0.174686271277\n",
      "bird 0.360379303236 0.179661070139\n",
      "mushroom 0.544946550049 0.191048782617\n",
      "bird 0.423933209647 0.139429554884\n",
      "mushroom 0.321145124717 0.175987313447\n",
      "bird 0.606750392465 0.131744390332\n",
      "mushroom 0.515022675737 0.220351335372\n",
      "bird 0.463855872019 0.175534952929\n",
      "mushroom 0.433673469388 0.130077028408\n",
      "bird 0.490074211503 0.151596781111\n",
      "mushroom 0.614795918367 0.197106569103\n",
      "bird 0.379035250464 0.165656506656\n",
      "mushroom 0.409620991254 0.162762625508\n",
      "bird 0.542517006803 0.136893565295\n",
      "mushroom 0.583090379009 0.197696160267\n",
      "bird 0.317254174397 0.148782033298\n",
      "mushroom 0.662585034014 0.207635719412\n",
      "bird 0.431405895692 0.177607809269\n",
      "mushroom 0.620019436346 0.182279872097\n",
      "bird 0.337641723356 0.172232335692\n",
      "mushroom 0.451895043732 0.214231166576\n",
      "bird 0.532137703566 0.152726235665\n",
      "mushroom 0.707288629738 0.17425884662\n",
      "bird 0.447845804989 0.15649544497\n",
      "mushroom 0.597667638484 0.136430805739\n",
      "bird 0.405936920223 0.166279934948\n",
      "mushroom 0.443148688047 0.192939389446\n",
      "bird 0.480272108844 0.167357078026\n",
      "mushroom 0.595238095238 0.198739607592\n",
      "bird 0.435657596372 0.154065738795\n",
      "mushroom 0.64139941691 0.175452725075\n",
      "bird 0.312152133581 0.140225494789\n",
      "mushroom 0.593002915452 0.204113607565\n",
      "bird 0.395547309833 0.147402568213\n",
      "mushroom 0.474246841594 0.193060501471\n",
      "bird 0.402154195011 0.132512668697\n",
      "mushroom 0.58527696793 0.162916771878\n",
      "bird 0.375324675325 0.13166294999\n"
     ]
    }
   ],
   "source": [
    "p_m_real, p_b_real, trials_tot, trials_stop, trials_m, trials_b, trials_stop_m, trials_stop_b, correct_m, correct_b = p_real(1)\n",
    "\n",
    "#print trials_stop_m/trials_m, trials_stop_b/trials_b\n",
    "#print sum(sum(trials_stop_m/trials_m > trials_stop_b/trials_b))\n",
    "\n",
    "print correct_m\n",
    "print correct_b\n",
    "\n",
    "fig = plt.figure(figsize=(12, 8))\n",
    "plt.imshow(correct_m, interpolation = 'none')\n",
    "plt.jet()\n",
    "plt.colorbar()\n",
    "\n",
    "for y in range(correct_m.shape[0]):\n",
    "    for x in range(correct_m.shape[1]):\n",
    "        plt.text(x, y, '%.4f' % correct_m[y, x],\n",
    "                 horizontalalignment='center',\n",
    "                 verticalalignment='center',\n",
    "                 )\n",
    "\n",
    "plt.show()\n",
    "\n",
    "fig = plt.figure(figsize=(12, 8))\n",
    "plt.imshow(correct_b, interpolation = 'none')\n",
    "plt.colorbar()\n",
    "\n",
    "for y in range(correct_b.shape[0]):\n",
    "    for x in range(correct_b.shape[1]):\n",
    "        plt.text(x, y, '%.4f' % correct_b[y, x],\n",
    "                 horizontalalignment='center',\n",
    "                 verticalalignment='center',\n",
    "                 )\n",
    "\n",
    "plt.show()\n",
    "\n",
    "for j in good_ones:\n",
    "    p_m_real, p_b_real, trials_tot, trials_stop, trials_m, trials_b, trials_stop_m, trials_stop_b, correct_m, correct_b = p_real(j)\n",
    "    print \"mushroom\", np.mean(correct_m), np.std(correct_m)\n",
    "    print \"bird\", np.mean(correct_b), np.std(correct_b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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