{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "from tqdm import tqdm_notebook as tqdm\n", "from hippocampus.plotting import tsplot_boot\n", "import matplotlib.pyplot as plt\n", "from definitions import ROOT_FOLDER\n", "import os\n", "import pandas as pd\n", "from hippocampus.agents import CombinedAgent\n", "from hippocampus.environments import HexWaterMaze\n", "import numpy as np" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(<Figure size 432x288 with 1 Axes>,\n", " <matplotlib.axes._subplots.AxesSubplot at 0x1a1d5adb00>)" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "g = HexWaterMaze(6)\n", "g.set_platform_state(30) \n", "\n", "g.plot_grid()" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "3890ed470be94f099cac3b38c2a7630a", "version_major": 2, "version_minor": 0 }, "text/plain": [ "HBox(children=(IntProgress(value=0, max=40), HTML(value='')))" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n" ] } ], "source": [ "agent = CombinedAgent(g, init_sr='rw', lesion_dls=False, lesion_hpc=False)\n", "agent_results = []\n", "agent_ets = []\n", "\n", "session = 0\n", "\n", "for ep in tqdm(range(40)):\n", " agent.env.starting_state = np.random.choice(agent.env.grid.edge_states)\n", " if ep == 4: \n", " g.set_platform_state(25)\n", " if ep == 8: \n", " g.set_platform_state(20)\n", " if ep == 12: \n", " g.set_platform_state(34)\n", " if ep == 16:\n", " g.set_platform_state(45)\n", " res = agent.one_episode(random_policy=False)\n", " agent.DLS.eta=.09\n", " agent.HPC.eta=.09\n", " res['trial'] = ep\n", " res['escape time'] = res.time.max()\n", " res['session'] = session\n", " agent_results.append(res)\n", " agent_ets.append(res.time.max())\n", " \n", " if ep % 4 == 0:\n", " session += 1\n", " \n", " \n", "df = pd.concat(agent_results)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>DLS reliability</th>\n", " <th>HPC reliability</th>\n", " <th>M_hat</th>\n", " <th>RPE</th>\n", " <th>R_hat</th>\n", " <th>SPE</th>\n", " <th>choice</th>\n", " <th>reward</th>\n", " <th>state</th>\n", " <th>time</th>\n", " <th>trial</th>\n", " <th>escape time</th>\n", " <th>session</th>\n", " <th>total time</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>[[1.3715083334840434, 0.4153999698742993, 0.41...</td>\n", " <td>0.0</td>\n", " <td>[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ...</td>\n", " <td>[0.00012972656119814713, -0.003883678129003476...</td>\n", " <td>None</td>\n", " <td>0.0</td>\n", " <td>67.0</td>\n", " <td>1.0</td>\n", " <td>0</td>\n", " <td>143.0</td>\n", " <td>0</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>[[1.3715083334840434, 0.4153999698742993, 0.41...</td>\n", " <td>0.0</td>\n", " <td>[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ...</td>\n", " <td>[-0.003884897545248421, -0.007711827169924246,...</td>\n", " <td>None</td>\n", " <td>0.0</td>\n", " <td>67.0</td>\n", " <td>2.0</td>\n", " <td>0</td>\n", " <td>143.0</td>\n", " <td>0</td>\n", " <td>1</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>[[1.3715083334840434, 0.4153999698742993, 0.41...</td>\n", " <td>0.0</td>\n", " <td>[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ...</td>\n", " <td>[-0.003545297204845234, -0.014179292768027457,...</td>\n", " <td>None</td>\n", " <td>0.0</td>\n", " <td>68.0</td>\n", " <td>3.0</td>\n", " <td>0</td>\n", " <td>143.0</td>\n", " <td>0</td>\n", " <td>2</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>[[1.3715083334840434, 0.4153999698742993, 0.41...</td>\n", " <td>0.0</td>\n", " <td>[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ...</td>\n", " <td>[0.007462145199232717, 0.0061539747741933964, ...</td>\n", " <td>None</td>\n", " <td>0.0</td>\n", " <td>43.0</td>\n", " <td>4.0</td>\n", " <td>0</td>\n", " <td>143.0</td>\n", " <td>0</td>\n", " <td>3</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>[[1.3715083334840434, 0.4153999698742993, 0.41...</td>\n", " <td>0.0</td>\n", " <td>[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ...</td>\n", " <td>[-0.02018272995848177, -0.03512075747291382, -...</td>\n", " <td>None</td>\n", " <td>0.0</td>\n", " <td>69.0</td>\n", " <td>5.0</td>\n", " <td>0</td>\n", " <td>143.0</td>\n", " <td>0</td>\n", " <td>4</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " DLS reliability HPC reliability \\\n", "0 0.0 0.0 \n", "1 0.0 0.0 \n", "2 0.0 0.0 \n", "3 0.0 0.0 \n", "4 0.0 0.0 \n", "\n", " M_hat RPE \\\n", "0 [[1.3715083334840434, 0.4153999698742993, 0.41... 0.0 \n", "1 [[1.3715083334840434, 0.4153999698742993, 0.41... 0.0 \n", "2 [[1.3715083334840434, 0.4153999698742993, 0.41... 0.0 \n", "3 [[1.3715083334840434, 0.4153999698742993, 0.41... 0.0 \n", "4 [[1.3715083334840434, 0.4153999698742993, 0.41... 0.0 \n", "\n", " R_hat \\\n", "0 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... \n", "1 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... \n", "2 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... \n", "3 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... \n", "4 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... \n", "\n", " SPE choice reward state \\\n", "0 [0.00012972656119814713, -0.003883678129003476... None 0.0 67.0 \n", "1 [-0.003884897545248421, -0.007711827169924246,... None 0.0 67.0 \n", "2 [-0.003545297204845234, -0.014179292768027457,... None 0.0 68.0 \n", "3 [0.007462145199232717, 0.0061539747741933964, ... None 0.0 43.0 \n", "4 [-0.02018272995848177, -0.03512075747291382, -... None 0.0 69.0 \n", "\n", " time trial escape time session total time \n", "0 1.0 0 143.0 0 0 \n", "1 2.0 0 143.0 0 1 \n", "2 3.0 0 143.0 0 2 \n", "3 4.0 0 143.0 0 3 \n", "4 5.0 0 143.0 0 4 " ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['total time']= np.arange(len(df))\n", "df.head()" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "<matplotlib.axes._subplots.AxesSubplot at 0x1a1daa82e8>" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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uGHR5H3BKtPcM5OhlRp9UXq8OBPqmzj5m5I/wDQlW3eKmKDsN34dHIUQkzLcz1iEzejNo6Oyl11/51NiZ3Bn9voZOzrhnHe/uk4VhIaJhukAvVTfmYMzmwVd9k0wHm3xjqWruSuo4hDhRmS7QB2b0cspUUhnBFaCxsy+JI/F9ugBo6kruOIQ4UcWUo08EmdGbQ1WzG4vyvfE2JXkx1kgdNSf5DUeIE5UJA73M6M3gULObyVlpOO1WGjuSG2CNn98sM3ohomK6QG+1KFJTLDKjT7KDTV1MyXGi0aaZ0UvqRojomC5HD3LKlBlUNXczNddJbrqDpiSnTAKpGwn0QkTFlIE+zW7FLambpHH3DdDY2UtJjpP8dEfSyyuNNxoJ9EJEx3SpG5AZfbIZpZVTcpx4vZr2ngF6Bzw4bNakjOdo6qYXrbVsmhIiQqac0cu5sclV5S+tNFI3kLzZ9IDHS7O7j7QUKz39Xvl7IUQUTBno5dzY5Aqe0eem+06CTFaevtndh9YwqyDd93tJ3wgRMVMGet8pUzJzS5aqZjcZqTay0lLI88/ok5WnN0orZxVkAFJ5I0Q0TBnofefGyow+Waqa3UzNdaKUIs8/o0/W7ljjDWb2JF+gb5ZOmkJEzJSB3ilVN0lV1exmSo4TIJCjT1a/GyPQzzRm9LI7VoiImTLQy4w+eTxeTXVzNyX+QO+yW3HYLElLmQRm9AXGjF4CvRCRMmWgd9p9FRYe7+gdYVff0cPF9/2LA43ju0PikfYe+jzewIzel75JXi19Y2cfdpuFgkwHdptFAr0QUTBloDdOmeruH730zdZDbWyvbWfD/vHd89youJma4wpcy0u3JzVHn5/uQClFrssui7FCRMGUgT4Z58bWtnUDcKjFPcIzxzajht6Y0QP+NgjJm9EbC8I5LrvM6IWIgikDfTLOja1p8QX64AM3xqOqZjdWi2JydmrgWq7LnrRF0MaO3kCJZ47M6IWISkyBXimVrZR6Wim1Sym1Uyl1mlIqRym1Vim1x//rhEjva/SkH81NUzWt/hm9BHqKstNIsR79q5GX4Qi0HxhtjZ1HA32uyy7llUJEIdYZ/S+Al7TWc4BFwE7gFuA1rfVM4DX/7yNinDI1mpumaluNGX33qP1MMzoYVFppyHXZ6fdo2rtHtxLK69U0dfWRl2Gkbhxy+IgQUYg60CulMoEzgYcBtNZ9WutW4DLgUf/THgUuj/TegRn9KJZYGjP6xs7ecd0L/1CzO1BaaQjsjh3l2XRrdz8erz46o0+309XnoWcUF+mFGAtimdFPBxqA3yml3ldKPaSUcgEFWus6AP+vEyO9cWBGP0qbpvoGvNR39DI931dpUt0yPmf1HT39NHf1MTV30Iw+Sf1ujJLO3KAcPUgtvRCRiiXQ24ClwK+01kuALiJI0yilblRKbVJKbWpoaDjmsdGe0R9p70FrWD49FzhaeTLeHPKnrQanbvKStDu2saPX//OPVt2ABHohIhVLoK8GqrXW6/2/fxpf4D+ilJoM4P+1PtQ3a60f1FqXa63L8/Pzj3nMqLoZrfJKYwZ/6rQcYPyWWFY1+zaLHZejD/S7Gd1A3+D/eflBi7Egjc2EiFTUgV5rfRg4pJSa7b90LrADeB5Y7b+2Gngu0nsbdfSjVV5pLMQuLM7GabeO2xLLQHviQambHGdyGpsZqaK841I3UnkjRCRiPWHqy8AapZQd2Ad8Bt+bx1NKqc8CVcBVkd7UbrVgs6hRWxQ1Av3krFSm5DjHbYllVbObbGcKmakpx1y3WS1McKaM+iHhjZ292CyKrDTfeHJdRgpJZvRCRCKmQK+1/gAoD/HQubHcVymF026la5QWY2tau8lLd5CaYqV4wvgN9Aebji+tNOQl4ZDwxs5ectPtWCy+owMz02zYLEpy9EJEyJQ7Y8FXeTNaM/qa1m6K/DtBp+Q4qWp2J2VzULIdClFDb8hNt496jt7X/sAR+L1SignSBkGIiJk20Dvt1lHL0de0dlM0IQ2Akpw0uvs9427Bz+PVVLd0DxPokzOjDw704FuQTVaDNSFOVKYN9C6HbVSqbrTW1LZ2U5jlC/RGoBtvC7K1rd0MePXQqRtXEmb0HSECfbq0QRAiUqYN9KM1o29x99PT76Uw+9hAP97y9IeGqLgx5KU7aO8ZoG/AOyrj0Vof07nSkONySOpGiAiZONCPTo7e6FpppG6KJ4zPQB8orRwmdQOjt1mpvWeAPo83ZOpmvKXVhIiViQP96Jwba/S4KfLP6NPsVvIzHOMudXOw2Y3NopjsT2ENNtqbpoxduEZDM0OOy07HKH6yEGIsMG2gd9lH59xYo4beSN0AlExIC7QDGC+qmt0UT0jD6i9lHCxvlAN946DNUgZj01SLW2b1QoTLtIHe6Ri9GX1aipUJzqObhIwSy/HkULObKbmuIR8/2u9mdAKs8YYSKnUzmuMQYiwwbaA3ZvSJrmevbe2mMDsVpY7OZKfkOKlr66bfM37SA77NUqHTNnA0Rz9au2OHCvTS2EyIyJk20DsdVrwaehOci61t7aZowrELkMU5Trz6aFpnrGtz99PW3T/kQiyAy27FYbOMWg17Y0cvFnU0sBsCLZOlxFKIsJk20AfOjU1wLX3wrljDeKulN7p1TskZOnWjlCIv3TFqOfqGzj5yXPbj1gxyXKNb/SPEWGDaQG/0pE/kcYI9/R4aO/sCm6UMJYFa+vExoz/YNHxppSEvffQOCQ+1KxYgOy0Fi5JAL0QkTBvoR+Pc2Lq2HuBoDb1hUmYqKVY1bmb0Q7UnHiw33TGqOfrcQZulACwWxQSn1NILEQnTBvrROGXK2CwVXFoJYLWocdXFsqrZTa7LTrpj+GamuS47jR3JndGDL28vh4QLET7TBvrRODe2dtBmqWDFE9LGzUlTVc1dxx0IHooxox+Nzp5NgzpXBsuRDpZCRMS0gX40ZvTVrd0oBZOyUo97bDzV0lcN0544WF66nX6Ppr0nsQvk7r4B3H2eIQN9brpdqm6EiIBpA33g3NgEBvra1m4KMlJJsR7/MpTkOGl199Pe05+wn28G/R4vta09TB0hPw+jd0i4kR4a3NDMIDN6ISJj2kAfODc2wambwuzjZ/MwfrpY1rZ24/HqMFM3o3N2bEOgz81QqRsHrd39eLzj73CYE1F7T/+Y/3dkdqYN9KMxo68JsVnKMF4C/UhdK4MdPbM1wTN6//3zh0rduOxoLf1uThQ//PtOrv7NO8kexrgWc6BXSlmVUu8rpV7w/36aUmq9UmqPUupJ/8HhEUtLSeyM3uvV1LX2DDmjL5kwPmrpjUAfXurGP6NPcNpkqPYHBmmDcGJ5q7KRurYeWuWNOWniMaP/KrAz6Pf3APdqrWcCLcBnoxqYxXdAeKJm9I1dvfR5vCErbgCynClkptrG/IJsVZMbu9VCQUboN7xgOYGGYqOTox/c/sBgNDYb7ROvROQOt/UEJkv7GruSPJrxK6ZAr5QqBi4GHvL/XgHnAE/7n/IocHm093fabQk7ZSpw4MgQgR58C7JjvcSyqtlNcU4aliHaEwezWS1McKYkPMA2dvaSlZaC3Rb6r2dOuszoTxQbDjQHvt7fIIE+WWKd0f8c+G/A6DyWC7RqrY1peDVQFO3NXQ5rws6NrW317YodvFkq2HgosQy3tNIwGoeE+zZLDZ3xk9TNiWPTgWacdis2i2JfY2eyhzNuRR3olVKXAPVa683Bl0M8NWRphFLqRqXUJqXUpoaGhpA/I5Ez+lAHjgw2JcdJdXM33jFa3aG1pqrJzdRIAr0r8f1uhtssBZDjlJ70J4oN+5s5eeoEpuQ42S+pm6SJZUa/AlillDoA/AlfyubnQLZSythLXwzUhvpmrfWDWutyrXV5fn5+yB/gSmCOvqa1mwyHjay0lCGfU5zjpM/jpb5jbOaCW939dPQOhFVaacjLcNCY4M1KjZ29Q5ZWgi+FlO1MkRm9ybV197P7SAfLSnOYludin6RukibqQK+1vlVrXay1LgWuAV7XWl8LrAOu9D9tNfBctD/D6bAlrOqmprV72Nk8jP12xZGUVhryXHYaE/zG19DZO2RppUE2TZnf5oPNaA3LSnOYnu9if2PXmP10bHaJqKP/NvB1pdRefDn7h6O9USJn9MNtljKU+LtajtVa+qOllUP3oR8sN91BewIP5+7p99DRMzBsjh78KSRpg2BqGw+0kGJVLC7JZlpeOr0DXmrbxna5slnFJdBrrd/QWl/i/3qf1voUrfVJWuurtNZR/2t02hM7ox/cnniwoglpKDX2Z/QlwxwhOFhugitejPbDw+XoQWb0J4KN+5uZX5RFmt3K9HzfZELSN8lh2p2x4K+6ScCMvqt3gFZ3/4ipG4fNyuTM1LE7o29yk5fuwGkfvj1xMCMAJ6rE0kgLjRzoHXEP9Fpr2rrHdm+j0dLT72FrdRunlOYAMD3PF+hlQTY5TB3o0+zWhFTdDNeeeLDiMVxLX9XsDmtHbLDA7thEBfoR+twYcl12Wtz9cc35PrHhECt+/DodY7yR3WjYWt1Gn8dLuT/Q52c4SHfY2NcgJZbJYOpA77Lb6Bvw0u+Jbz64JoJAP5Zr6SOtoYfgfjeJSZsYgT53iF2xhhyXHY83vjPwV3ceobN3gO217XG753i10b9RqnzqBMB35vC0PJfsjk0SUwf6RJ0bG85mKUPJBCdH2nvp6U9cF83Bdh1up769J6E/o8+/MBZJaSUczdEnaiHU6IyZP9KMPjCO+Lzh9Hu8rN/XBCCBPg427G9mVkE6E4LesKfnS4llspg60B89Nza+efqaVjdWi6Igc+T+LlNyfW8G1S2jUy2gtea6hzZw5ws7EvpzDjZ1oTWURpi6SXfYcNgsCZ3RpztspPqb2g0l3rtjt9W0BdKE22va4nLP8crj1bx3sIVl/rSNYVqei9q27lGdNAkfUwf6wClTca68qW3tYVJmKtYw+ruMdrvi6pZuGjt7ee9gS0J/zjZ/MCsrzIro+5RS5KU7Aj3j462xs2/E0koIDvTxGcc7lb7Z/KKSbJnRx2jX4XY6egeOC/TT89PRGg40yax+tJk60CeqJ31Na3dY+XkIalc8SguyW6t9Abi2rSeh6ZttNW2kpliYkR9+Db0hNz1xbRAaO4Y+FPyYMRhrBXGa0b9T2cScSRmcOTOPvQ2dMuuMwcb9vvz8smmDAr1ReSPpm1Fn6kBvnDIV7xx9TcvINfSG/AwHDpuFqqZRCvQ1rYGvPzjUOswzY1NR08a8yZnYQhyjOJJEblbyNTQbOdBPcPlaVzTH4Q2nd8DDxgPNnDYjl7LCTDxeza7DHTHfd7zaeKCFouy04yZT0/yBXhZkR5+pA30iZvQer+Zw+9AHjgymlBrVdsVbD7UxqyAdm0WxpToxgd7j1WyvbWdBUWRpG0NeAjtY+vrcjJy6cdisZDhscZnRv1/VSu+Al9Nn5AVSWdtrJU8fDa01Gw40U1464bjHXA4bBZkOWZBNgvB3yiSBKwHnxtZ39ODx6rAqbgy+EsvEL8Z6vZqKmjZWLS7EbrOw5VBigs3+xi7cfR7mRxnojVbFWmt8RxDER7/HS4u7P6wZPfj60sdjMfbtyiYsCk6ZlkNmqo3MVJvk6aNU1eymoaP3uPy8YXpeurQrTgJTz+idCZjRh3PgyGAlE9I41OxG68Q2ZNrf1EVH7wCLirNZVJzNlkOtCWkCVeFfiF1QHO2M3k6fx0t7T3zXTprDbH9giFcbhHcrm1hQlEVWWgpKKcoKs6TyJkob/Pn5U6aFDvTT/M3NxOgydaA3UjfxnNFHslnKUJLjpNPfNiGRtvpTNQtLslhckk1H70BC8pnGQuxJ+elRfX+ghj3OlTcNgfYH4R0znOuyx7xD1903wPuHWlg+Izdwrawwk12HOxiI80a98WDjgWay0lKG/Ls1Pc9Fq7tf+hSNMlMH+rTAhqn4zRwj2SxlGK12xVsOHQ3Ai0uygcQsyG6raWNulAuxcHTGHa+KF8NIh4IPFo8Z/aYDLfR7NKfPyAtcm1+URe+Al0rJJUds44EWlpVOGPJoSqO52f4EpG8+9fB67vxbYvefnKhMHejtNgt2q2XEfjc1rd389OVdYbXOrWl1k+1MCWzGCoexezTRC7KERkwUAAAgAElEQVTbatqYX5iFzWphRn466Q4bW+Ic6L1ezY4YFmIhuA1CfGf0xgJv+IHeQYu7L6aU2tuVTdgsimVBi4dlhZnA0RSXCE9DRy/7G7uGzM+DL0cPxP1N9FCzm3/taeSJDVXSqygEUwd68JVYjnRu7P97bQ/3r6vk2fdrRrxfbWsPhVnhz+bhaKBP5Ix+wONle21bIG9usSgWFmfFfUa/v6mLzt6BqBdi4WhqpSHOlTfhNjQz5Lrs9Ht0TGsF71Q2smRK9jEdPKfnp5OaYpEF2QhtOhC6fj5Y8YQ0Uqwq7nn6V3ceAaC738PfttTF9d5jgekDvWuEc2Pbe/p57gPfaYW//mclnhEWL2taRj5ZarB0h40clz2hu2P31HfS0+9lUXF24Nrikmx21rXHdfNOYCE2hkBv9C+J94y+sbOX1BQLLvvw7Q8MsbZBaO/pZ1tNG6cFpW0ArBbF3MmZUmIZoQ0HmklNsTB/mN3WNquFKTnOuHexXLvjCDPyXcwuyOCpTYfieu+xwPSB3jnCKVN/3VxNd7+Hz581g32NXby8/fCw96tt7aY4zM1SwUpynBxKYIllYCE2qBJmUUk2A/6a93jZVt2Gw2Zh5sToFmIBUqwWJjhT4l5L3+g/FDzcks2c9NjaIGzY14xXw2nTc497rKwwkx217XL0XQQ2HWhhcUk2dtvwYWVaXnpcZ/Rt7n7W729mZdkkriov5oNDrXx4RDa8BTN/oB/m3FitNY+tr2JRcRbfumA20/Nc3L9u75A52/Ye32HY4W6WCpbodsVbqtvIcNgoDTrWz1iQjWeefltNG3NiWIg15KY74r47NtxdsYa8GFsmv13ZhMNmYcmU7OMem1+YRUfvwJg9iyDefO2djx40MpwZ+S4ONLlH/PQdrnW76/F4NefNLeCKJUWkWBVPbpRZfTDTB/rhzo19d18ze+s7uW75VKwWxefPmsH22nbe3NMY8vlGDX2kqRvw1dLXtnYnrORuW7UvPx9crVCQmcrkrNS45em9gR2xmTHfK9dlp7EjvjP6hjD73BhyYjzW8O3KRspLJ4TslHl0h6zk6cPx3sEWvJrAQSPDmZbn8rXJbo3PJ+S1O46Ql+5gSUk2uekOzptbwDPv10R1rrHWmjZ3/7D/dY6wZmhGUe+MVUqVAH8AJgFe4EGt9S+UUjnAk0ApcAC4WmsddStGp9025F+Ix9YfJCsthUsXFQJw+ZIi7n31Q+5ft5ezZuUf9/xITpYabEqOkwGvpq6tJ+Ie7iPpHfCw63A7nz1j+nGPLSrOjlsrhAP+hdhY8vOGvHQHOw/HNwg2dvYFPsWEwzicJJoyz6bOXnYd7uBbF8wO+fisSb42FBU1bXxsweSI7z/ebDzQjEXB0qnHtz4YbHq+UXnTGfO/pd4BD2/srufSRYWBSdLVy0r4R8VhXtt5hIsi/H/3jT9v4a/vjVzU8YtrFnPZ4qKoxpwMsbRAGAC+obV+TymVAWxWSq0Frgde01r/WCl1C3AL8O1of8hQ58bWd/TwcsVhVp9eGpiR2W0WPveR6dz5wg42HWg+bnYRS6AvCWpXHO9Av7Oug36PPiY/b1g8JZuXth+mpavvmEMcomG0Jo6l4saQF+cOlh6vprkrshl9aooVp90a1Yx+vX8H5/IQ+Xnw9dKZWZAhM/owbTzQTFlhFulhlC1PCzo/9uzQ77Nhe6eyia4+D+fPKwhcO3NmPpMyU3lq06GIAv27+5r463s1XLGkaNjJ0EP/2sdf36sZH4Fea10H1Pm/7lBK7QSKgMuAs/1PexR4gxgCvXOIqpunNh5iwKu59tQpx1y/5pQS/t/re3jgjUoeuf7YQF/d2o3daokomBimJLCWfluIhViDUYXzQXUrH509Maafs722HbvNwqyCjJjuA74cfVt3P30D3hEX38LR4u7Dq8PfFWuIdtPU25WNuOzWkK+5oawwkzd218e9p89Y0zfg5f2qVj456N/iUPLS7WSk2uLS3GztjiOkpVhZcdLRyimrRXHlycU88MZeDrf1MClr5DU5r1dz1993UJiVyo8+vmDYg2+OtPfwyFv7aevuJystJeY/w2iIS45eKVUKLAHWAwX+NwHjzSBkdFJK3aiU2qSU2tTQ0DDkvV324+voPV7N4+urOOOkvMDHQIPTbuOGFdN4fVc9O+uOnY3VtvYwOTt1yF17w5mc5TuoJBELsluq28hx2UN+0lhYnIVFxWdBdlt1G3MnZZAS40IsHG2DEK+t7IHNUmHW0AfG4bJHlbp5u7KJU6blDPtalBVm0tjZR31HYloyjxXbatroHfCGtRALvo6w0/Ni73mjtebVnUc4c1becYH56vISvBqe3hzeouwz79dQUdPOf184Z8TTzS6cP4l+j+Y1f+3+iSDmf/FKqXTgL8B/aa3D/pyrtX5Qa12utS7Pzz8+n25wOmy4+z3HlLm9vque2rYerlseegbx6dNKcdmt/OqNymOu17Z2R7xZymCzWijMTk1IieW26jYWFmeFnDW6HDZmTsyIeUFWa01FbVtc0jZwdHdsrL1mDJG2PzD4ZvSRjeFwWw/7GrqOaXsQivFaST398AIHgYcZ6MGXp4+1ln5bTRtH2ns5f96k4x6bkuvktOm5PLWpesQS2e4+Dz99eTcLi7NY5V/vG86i4mwmZ6Xyj4rhS7nNJKZAr5RKwRfk12it/+q/fEQpNdn/+GSgPpaf4bJb0Rp6Bo6mbx579yAFmb7V9VCynClcd9pUXthay4GgWUMkB46EkogSS3ffAHvqO1hYPPQi5KKSLLYcao1pq//BJjcdPfFZiAXIz4jv4dzRB3pHxIePvLPPV5V12ozQ+XnD3MmZKAUVNfHN02880Mwbu2P6ZzFq1u9r4vdv7effexo50t4T8u/gpgPNTM9zjXigezDf+bE9dMdwqNDaHUewKDhnTuiU5tXLiqlqdgfWY4by23/t43B7D9+5eF5Yn/YtFsUFZZN488MGuk6QCpyoA73yTT8fBnZqrX8W9NDzwGr/16uB56If3vHnxh5s6uLNPQ1cs2zKsLXgnz1jGjarhd+8uQ/w9To/0tETVWmlYXZBJjvq2mmJYzOvipp2vBoWDhOAF5dMoMXdH9ObTDwXYiGyfjfhlLkZnSvzIwz0uem+1E0kb4LvVDaRlZbCvMnDl5mm+/c1xGtGr7XmwTcr+c/fvMP1v9vImvUH43LfROnqHeCmxzbz/b/t4LqH13PqD19j4fdf4YoH3uJbf97Cg29Wsm5XPZsOtoQ8aGQ4R5ubRZ++WbvjCOWlOYEd0oNdNH8yGam2YXfK1rf38Ot/VnJh2aQhWyuHvvckege8rDtB3rBjmdGvAD4FnKOU+sD/38eAHwPnK6X2AOf7fx+1wT3pH19fhUUpPnHK8As/EzNSubq8mL9sruZIew+H23rQGoqi2CxluKq8mL4BL09vro76HoMFtyYeyiL/Y7Gkbypq2rBb47MQC0dz9COlbv747kGW/mDtiA3CGjv7sFstZKZFVh+Q47LTO+CN6LjJtyubWD49J6zZW1lhZlwqb3r6PXztyQ/44Yu7uHD+JM6ZM5Hbn6ng92/tj/neifLEhipa3f08vLqcxz93KndeVsYVS4tItVl548MGfvjiLj7z+420uvs5ddrwn44GC668icahZje7Dnewcl7oT/Xgq8pataiQF7fV0T5Eo7P/e+VD+j1ebrloTkQ/v7w0h7x0+wmTvoml6ubfwFD/Us6N9r6DBZ8y1dPv4alNhzh/bkFYK+k3nTmDJzYc4qF/7eNcf5qnKDv60si5kzMpnzqBNesP8tkzpkW1qDvY1uo2JmelMjFj6D/P7IIMUlMsfHCoNeqSLt+O2Iy4VMiAb7Zrt1mGLbHcW9/JXS/soHfAy+3PbOOvX1yBdYjXrLGzl9x0e8TVLcH9bsLpSHqo2U11Szef+8jxexZCKSvM4oWtdbS6+8h2RlfeWtvazU1/3ExFbRvfXDmLmz96Ev0ezZcef4/v/20HfR4vN545I6p7J0rvgIeH/rWfU6flBP7tDF7TaHP3s7ehg7q2HlaGyJMPJ3B+bJR5+ld2+BZCzx8m0AP857IS1qyv4vkParlu+dRjHttR285Tmw9xw4pplOa5hrhDaFaLYmXZJJ59v4aefs+IC7jJZvqdscEz+n9U1NHi7j/uf9hQSnKcrFpUyJr1VYFZWTTtD4Jdt3wqB5rcvFUZevdtpLbVtI2YN7dZLSwoyoq68kZr3xGF8UrbgK9yIj/dQeMQgX7A4+Ubf95Cmt3KbR+bw5bqNh7fUDXk/YxAH6lIN0297f//dvoI+XmD0bJ4R5Sz+o0Hmln1y3+zv7GL336qnC+dMxOlFHabhfuvXcrFCyfzwxd38cvX90R1/+Hsb+yKOof87Ps1HG7v4eaPnjTkc7KcKZw8NYdLFhZGPIFw2m1MzkqNeka/dsdhZhWkMzV3+AC9oCiLOZMy+POg9I3Wmh++uJOstBS+cs7MqMZw0fxJuPs8/PPDoasGzcL0gT4wo+/z8Ni7VUzPc4X9jxTgC2fPwN3n4YF1e4Ho2h8Eu2jBJHJcdh57N/b8alt3P/sbu1gUxm7QRcXZVNS20x9FC4aqZjftcVyINfjy46FTN796o5Ith1q56/L5fO4j0zl9Ri4/eWkX9R09IZ8faZ8bw9EZfXiVN29XNpGX7uCkMJu6GYE+mvTN4+ur+ORv3yUjNYVnbz6d8wbNPlOsFn7xn4u5YkkR//vKh/xs7YdxO65yf2MXF/z8TT73h00R39Pj1fz6n/uYX5TJR2YOX5kUi+n5LiqjCPSt7j42HmgZcTYPvgnJ1eUlbKluY1fQTu43djfw772NfOWcmWQ5o6uFXz49l6y0FF46AdI3pg/0xox+84FmNh9s4ZOnTokoZTKrIIPz5hbQ1NVHXro95o9YDpuVq8tLWLvjCHVtsZVabqsOv2Xw4inZ9A142VUXeVe+bXFoTRzKUEf5VdS08YvX9nDpokIuWViIUoofXD6f3n4vP/z7zpD3auzoiyrQHy3zHHlGr7XmncomTpuRG3aKKDfdweSsVCoiWJDt86eqbntmG6fPyOPZm1dw0sTQayM2q4X/vWoRV51czH2v7eGel3bHHOy11nz32QoGPF7ermwKtPEO1z8q6tjf2MXNZ5+U0I1i0/Jc7G/ojPjP+/ouXxOzUGWVoVyxpAi71RJodDbg8XL3izspzXWGnR0IJcVq4fx5Bby680hEfXX6PV4+87sN/NZfKDIaTB/ojXNj//juQRw2C1eeXBzxPb74UV/+M9bZvOHaU6eggSc2xNYhb2vN0DtiBwveIRupbTVtpFgVMwuib00cSm6647gcfU+/h68/9QE5Ljs/uKwscH1GfjqfP3sGz35Qy1t7j017aa1pirD9gSGSxmaVDV3Ud/RG9IkQIluQ7ejp57qH1rNmfRU3nTWdR65fNuLuSatFcc9/LOTaU6fw639WcucLO2IK9s9vqeXfexv53iXzWFySzV1/30FbmOcda625f10l0/NdXFAWWd49UtPz0mnvGYi4RHftjiNMzHAMW6kWbILLzvllBTz7fg29Ax6e2HiIvfWd3PqxuTGvWV00fxIdPQMRpXL/tKGKdbsb+NE/drL5YNRtwCJi+kDv9KduWtz9XLqoMKoFsaVTJnDZ4sKQjc6iUZLj5KxZ+fxpQ1VUqRTD1kNtTM11hvVnKp6QRl66nQ+qIg/0FTVtzJ6UgcMW3wWjXH+/m+CgdO/aD/nwSCf3XLnwuD/XF8+ewdRcJ995tuKYw1Tauwfo9+iI2x+Ab5+F3WYJK9C/E2F+3lBWmMW+hs6wzi7+yUu72XSwmV9cs5hbL5o75OLzYBaL4q7L5/OZFaX87q0DfPe5iqh64bd193PX33eysDiLT51Wyt1XzKe5q4+fvLwrrO9/48MGdta184WzZsSl2GA406Iosezp9+XEz5tXENH4ri4vocXdz7Pv13Dv2g85ZVrOsBU74TpjZh7pDhsvbQsvfdPe08+9r+6hfOoEJmel8c0/b4nrmdhDMX2gdwUd8fapGD5m/eKaJXxjZYwdlIJcd+pU6jt6eXVH9Nugt1a3hp1OUUpF1cnStxAb2xmxQ8lPd9Dn8dLhX/DbsL+ZB/+1j0+eOiVkX57UFCs/uGw++xu7+M0/j35sbfCnfyLZcGNQSvnaIISRunm7somi7LRA36JwlRVm4tW+5nPD+eBQK4+tP8jq00ujqo5SSvG9S+Zx01nTeezdKu4aIs01nP97ZTdNnb3cffkCrBZFWWEWn1kxjcc3VPF+1cizxwfW7aUwK3VUGnbN8J8fG0nlzTuVTbgHNTELxxkn5VGYlcp3nq2guauP7148Ly5pKYfNyjlzJvLKjsNhtTC/f91eWtx9fH9VGT+9aiH7G7v48T/CexOOhekDfWqKBaV8+eVwFi1Hy0fnTKQoO40/Rrko29DRS21bzzFHB45kcUk2lQ2dQ9YEh1Ld0k1bd39cK24MgVr6jl66egf45p+3UDLBye0fmzvk95w5K59LFxVy/xt7AzO5aHfFGsJpg9A34OXdfU0snx5+ft5Q5n/tdgyTpx/w+PLyEzMcfP38WRHdP5hSilsunMP1p5fyyFv7efjf4dfZbznUyh/fPcinTysNnD0M8LXzZ1GQkcrtz1QMG4w27G9m44EWbjxzetzKcIdTNCENu9XCvghm9K/sOILLbo34U5nVoriyvIR+j+bjS4qOeX1i9bEFk2hx97NhhB24h5rd/O7fB/j4kmLmF2Vx+ow8blgxjT+8c5B/D3GGRryYPtArpbjpzBnc+rHINjQkmtWi+OSpU3i7sonKKGqBt0WQnzcsKslG66OLuOH9nMQsxELQ7tiuPu5+cSeHWtz871WLRqxn/+7Fc3FYLXzvuQq01nEK9MPP6H/7r320uPtZtXjkXiaDFWalMsGZMmye/g/vHGR7bTt3XFpGRmpsHQ2VUnz3knlcUFbAXX/fwYvbRj7sesDj5bZntpGf7uAbK499o0l32Ljj0nnsqGvn0XeGnpg88MZecl12/nNZeF0oY2W1KKbmOsPuYun1+pqYnTU7P6o05HXLp7BqUSHfjnBz1EjOmjWRtBTriJun7nlpFxYLx5yB8N8XzmZGvotvPb2Ftu7wJ3CRMn2gB7jlojkjNqBKhqvLS0ixKta8O3R9+FC2Vreh1NHZYjgCC7IR1NMbC7GzJ8VnR2wwY0b/l83VPL6+ihs/Mj2sbeQTM1P51oWz+deeRl7YWkdjhxHoo9uQNFIHy6omN/e9tocLyyZFtU6jlC8FMlTlzeG2Hv7vld2cPTufi+bHZwHTalH84polLCnJ5r+e/CDQOGwof3zX90bzvUvnhXyjuXD+JD46O5+fvbI7ZLXY9to23tjdwA1nTCMtzMPZ42FaBF0st1S30tDRG3HaxjAxI5X7PrGEgszY9tIMlma3cvbsfF7efnjIdZXNB1t4YWsdN54545jNnqkpVn529WLqO3r5n+e3x3VcwU6IQG9W+RkOLiibxNObD0XcnGlrdRsn5aeHdVCDIcuZwvQ8V0SBvqKmjVkF8V+IhaN9af608RCzCtL5WgQpi2tPncrC4izufGEH+xu7sCii3nma43IMOaPXWvO95yuwWRR3rJoX1f3Bl6f/8HBnyMX3O1/YzoBXc+eq+XEtR0xNsfLQ6mUUZafxuT9sGvKT45H2Hv7vlQ85c1Y+Fw9x0IZSijsvm+8b5992HPf4A29Uku6wxVRuGI3p+ekcbOoKK7+9dscRrBYV87kMiXDh/EnUd/TyXoh1EK19ve7zMxzcdGaIU+RKsrn5oyfx1/dreKli5E9v0ZBAH6NPLZ9Ke88Af9sSfq2y1tq3EBtFnnBRSTYfhNnJUmsd1s7baBknXtksip9dvTiiPQpWi+LuyxfQ1NnLmvVV5LgcYVeoDJabbsfd5zmmksfwUsVh3tjdwNfOn8XkKFtUg++TV5/Hy54jxwbbdbvreXHbYb58zklMyY3vyWPgS0s9+plTsFkUqx/ZEHLD2Z0v+Noo/OCysmHfaEpynHzl3Jn8o+Iw63Ydbca1r6GTF7fV8anTpo76QRrT81z0ezQ1YZwfu3bHEU4pzYl6QpBI58yZiN1q4cUQ1TcvbK3j/apWvrVy9pBpzS+fcxLzizK57ZmKQIO/eJJAH6NTpuUwqyCdxyLoRFjX1kNjZ19EC7GGxSXZNHT0UtcWeodpsOqWblrdiVmIBd+GkY/Ozuf2i+dG9TMWFGfx6dNKGfBGV1ppGKoNQmfvAP/ztx3MnZzJ9aeXRn1/OLpDNjh909Pv4XvPVTAj38XnQszU4mVKrpOHVy+jqbOPz/5+0zFtDd7YXc/ft9bx5Y+eNGI7AIDPfWQ6J01M53vPVwQ+hf7mn/uwWy3csGJawv4MQzG6WI6Upz/Q2MWe+s6o0zaJlpGawkdm5vHy9sPHTMJ6+j3c89Iu5k7O5D+G2QOUYrXws6sX09k7wG3PbIvbDmmDBPoYKaW49tSpbK1uC3SiHMnWYY4OHIlReRRO35uKBC7EGn73mVP4TAwB4usrZzExw0FxDOcEBNogDCqxvHfthxzp6OHuK+YP29I6HNNyXTjt1mN63vzy9b0cau7mrssXJCQ1FmxRSTa//OQStte28aXH32PA4/W/0Wxner6LG88K743GbrNw9+XzOdTczS/X7aGurZu/vl/N1eUlUZW3xirQ3GyYPH2ru4/bn92GUiM3MUumC+dPoqa1m61BxRK/f/sA1S3dfOfikfdUzCrI4FsrZ7N2xxH+EsYB5ZGQQB8HVywtIi3FGnb/my3Vbdgsirkj9EMPZe7kDOxWS1h5+m01vp+TiIXYeMlMTeHZm1fwwysWRH0PY1E4uO9ORU0bv3trP584ZQpLp0TWKz0Ui0Uxb3JmoDf93voOfvNmJR9fWjTiASbxcu7cAn5w+XzW7W7gu89V8MvX91LV7Oauy+dH9EZz6vRcrjy5mAff3Md3n63Aq+HGBH4iGU6Oy05WWsqQtfQfHulg1S/fYsP+Zu75+EJKItwDMZrOn1eAzaIC1TdNnb3c//pezp0z8ZgzbYdzwxnTOKU0h/95fntY6axwSaCPg8zUFC5fUsTzW2rD2mq+rdq3UzWavjsOm5W5hZlhB/pZBdH9nNFUmJ3GxBgqIXL8ZZ7GgqzHq7n92QomOO18+4L4ldKVFWayo7bdd/9nKnDabdw2zJ6BRLj21Knc/FFf++1frtvLFUuKoqpIu/WiOTjtNl7dWc9liwqTFkCVUkNW3ry8/TBX3P8W7j4Pf7pxOVcvK0nCCMOX7bRz2oxcXqqoQ2vNz1/dg7vfw60R/B2xWhT/e9UivFrzjac+oL595BRtOCTQx8l1y6fQ0+/l6feGP5TEWIgd7ujAkSwuzmJbTRueYbbIG62JE5m2MYvgnvTgOzBjy6FWvnPJ3Kg7E4ZSVphFV5+Hn7/6Iev3N3PLRXOirv2PxTdXzubq8mImZjiifqPJTXdwx6XzyHamBHpBJcv0fNcxOXqvV/OLV/dw0x83c9LEdP725RWcPDX805+S6cL5kzjQ5Obv2+p4fEMV1546JexOqYYpuU7uWFXGu/uaOfVHr3Hlr97moX/to7ol+hPmJNDHSVlhFkumZLNm/cFhF1IONvlaBkeTnzcsmTIBd5+H63+3gT9tqAp5nF9Nazct7n7mx3EHoFllptpIsSqauvpo6Ojlnpd2cdr0XC6P8zb+siJfqu3/vb6XpVOy+c/y5MwwlVL85MpFvHXLOTHl1T++tJiNt583ZGfN0TI9z8Xh9h66egfo7B3gC2s2c++rH/LxpUU8edNpMVVLjbaV8yahFHz9qS04U6x89dzoet1fXV7C2q+dydfOm0VXn4e7/r6TM+5Zx6pf/psHgnaVhyvqE6bE8T61fCpff2oLNz/+3jE9eoId9n8UiyXQX7xwMnvqO/jbljpu+auvHe6p03K5aMEkLiibREFmauBA6/mFka8DnGiUUkxw2mnu7OOHL+6kt9/LXVfEt6YdYObEDFKsCq+Guy5fkPCmXyNJiXGBOV73iNX0fN+M980PG7j31Q/ZW9/Jdy+Zxw0rShPaJjkR8jMcLCvNYcP+Zr5x/ixyY/jEN7Mgg5kFGXzl3JkcaOzipe2H+UfFYX7y0m5+8tJu5kSw9iaBPo4+tmAya9ZXjdhhclnphJjObk2xWvjWBXP45srZbK9t56WKw/yjoo7vPbedO57fztIpE0ixKqxRLvieiHJcdt7c00BdWw9fOeckZuTHtyUz+CpWriovoWSCk3nj4A10tBiVN198/D0yU1P4ww2nckYCDzxJtBtWTCM1xcrqGEt6g5Xmufj8WTP4/FkzqGnt5qWKwxFtrlLxrtcM3FipC4FfAFbgIa31kIeEl5eX602bNiVkHOPJniMd/KPC966/s66dRcVZPPelM5I9rFFx7UPv8tbeJqbmOnn5v840/QK0OKqn38PJP1hL8QQnD3765LD2AwgfpdRmrXX5SM9LyIxeKWUF7gfOB6qBjUqp57XWx++9FnET/FGvqslNqj35H8tHi1F5c+dl8yXIn2BSU6y88vWzyHXFfgKcCC1RqZtTgL1a630ASqk/AZcBEuhHSSK245vZtadOYVFxVtwOlxGjqyhOp7+J0BIV6IuA4HP2qoFTg5+glLoRuBFgypTRaYsqxq7l03NZPn10Ni4JcaJJ1Gf7UEvlxywGaK0f1FqXa63L8/NlFiaEEImSqEBfDQQXGRcDkR1FL4QQIi4SFeg3AjOVUtOUUnbgGuD5BP0sIYQQw0hIjl5rPaCU+hLwMr7yyke01ok7PkUIIcSQErZhSmv9IvBiou4vhBAiPOOn0FoIIcYpCfRCCDHGSaAXQogxLmG9biIahFIdwO5kjyNMeUBjsgcRJhlrYshYE0PGGrmpWusRNyKZpXvl7nAa85iBUmqTjDX+ZKyJIWNNjM1sol0AAAUFSURBVBNprCCpGyGEGPMk0AshxBhnlkD/YLIHEAEZa2LIWBNDxpoYJ9JYzbEYK4QQInHMMqMXQgiRIEkP9EqpC5VSu5VSe5VStyR7PMNRSh1QSm1TSn2glDLV2YdKqUeUUvVKqYqgazlKqbVKqT3+Xyckc4yGIcb6faVUjf+1/UAp9bFkjtE/phKl1Dql1E6l1Hal1Ff91033ug4zVjO+rqlKqQ1KqS3+sf6P//o0pdR6/+v6pL8holnH+nul1P6g13Vxssc6LK110v7D1/CsEpgO2IEtwLxkjmmE8R4A8pI9jiHGdiawFKgIuvYT4Bb/17cA9yR7nMOM9fvAN5M9tkHjnAws9X+dAXwIzDPj6zrMWM34uiog3f91CrAeWA48BVzjv/5r4AsmHuvvgSuTPb5w/0v2jD5w5KDWug8wjhwUEdJavwk0D7p8GfCo/+tHgctHdVBDGGKspqO1rtNav+f/ugPYie/0NNO9rsOM1XS0T6f/tyn+/zRwDvC0/7pZXtehxnpCSXagD3XkoCn/cvpp4BWl1Gb/UYhmV6C1rgNfIAAmJnk8I/mSUmqrP7WT9HRIMKVUKbAE34zO1K/roLGCCV9XpZRVKfUBUA+sxffJvlVrPeB/imliweCxaq2N1/Vu/+t6r1LKkcQhjijZgX7EIwdNZoXWeilwEXCzUurMZA9oDPkVMANYDNQB/5fc4RyllEoH/gL8l9a6PdnjGU6IsZryddVae7TWi/GdPncKMDfU00Z3VKENHqtSaj5wKzAHWAbkAN9O4hBHlOxAf0IdOai1rvX/Wg88g+8vqJkdUUpNBvD/Wp/k8QxJa33E/w/KC/wWk7y2SqkUfIFzjdb6r/7LpnxdQ43VrK+rQWvdCryBL++drZQy2rKYLhYEjfVCf6pMa617gd9hstd1sGQH+hPmyEGllEsplWF8DawEKob/rqR7Hljt/3o18FwSxzIsI3D6XYEJXlullAIeBnZqrX8W9JDpXtehxmrS1zVfKZXt/zoNOA/fmsI64Er/08zyuoYa666gN3qFby0h6a/rcJK+Ycpf7vVzjh45eHdSBzQEpdR0fLN48DWDe9xMY1VKPQGcja+r3hHgDuBZfJUMU4Aq4CqtddIXQYcY69n40gsaX3XTTUYePFmUUmcA/wK2AV7/5dvw5b5N9boOM9ZPYL7XdSG+xVYrvsnmU1rrO/3/xv6ELxXyPnCdf8acNMOM9XUgH1/6+QPg80GLtqaT9EAvhBAisZKduhFCCJFgEuiFEGKMk0AvhBBjnAR6IYQY4yTQCyHEGCeBXoxbSqlspdQXh3n87TDuYdqSOiEMEujFeJYNHBfolVJWAK316aM+IiESwDbyU4QYs34MzPA3rOoHOvH1g1kMzFNKdWqt0/39Y54DJuDrXvgdrXXSd20KES7ZMCXGLX+Xxxe01vOVUmcDfwfma633+x83Ar0NcGqt25VSecC7wEyttTaek6Q/ghBhkRm9EEdtMIL8IAr4ob9bqRdf+9wC4PBoDk6IaEmgF+KoriGuX4uvr8nJWut+pdQBIHXURiVEjGQxVoxnHfiO3RtJFlDvD/IfBaYmdlhCxJfM6MW4pbVuUkq95T+kvBtfJ81Q1gB/U74D4T8Ado3WGIWIB1mMFUKIMU5SN0IIMcZJoBdCiDFOAr0QQoxxEuiFEGKMk0AvhBBjnAR6IYQY4yTQCyHEGCeBXgghxrj/D5w2l2Sey58tAAAAAElFTkSuQmCC\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "df.plot(x='trial', y='escape time')" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "<matplotlib.axes._subplots.AxesSubplot at 0x1a22744470>" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "df.plot(x='session', y='escape time')" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "<matplotlib.axes._subplots.AxesSubplot at 0x1a22831588>" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "df.plot(x='trial',y=['DLS reliability', 'HPC reliability'])" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.8" } }, "nbformat": 4, "nbformat_minor": 2 }