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@diazona
Last active August 27, 2016 10:54
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Data informing the Physics SE homework policy update
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This analyzes the data collected about on/off-topic questions for the new Physics SE closure policy that is to replace the homework policy. The rating data come from responses to [a questionnaire](https://docs.google.com/forms/d/e/1FAIpQLSfm5QLFJVPUiWEQb45fLGtjhZHhxeC560PoE5ia3LrXr6FMiA/viewform) I asked people to fill out. The score data come from [the meta question](http://meta.physics.stackexchange.com/questions/7645/replacing-the-homework-policy-1-what-existing-questions-should-be-on-off-topic)."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T17:59:54.016756",
"start_time": "2016-08-27T17:59:47.920931"
},
"collapsed": false
},
"outputs": [],
"source": [
"import itertools as it\n",
"import more_itertools as mt\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"import pandas as pd\n",
"import re\n",
"import seaborn as sns\n",
"import scipy.stats as spst\n",
"import sklearn.cross_decomposition as skcd\n",
"import sklearn.decomposition as skd\n",
"import statsmodels.stats.proportion as smsp"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T17:59:54.064626",
"start_time": "2016-08-27T17:59:54.018148"
},
"collapsed": true
},
"outputs": [],
"source": [
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T17:59:54.068881",
"start_time": "2016-08-27T17:59:54.065999"
},
"collapsed": true
},
"outputs": [],
"source": [
"sns.set_style('whitegrid')\n",
"sns.set_style({'figure.figsize': (16, 10)})"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Loading data "
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T17:59:54.083445",
"start_time": "2016-08-27T17:59:54.070332"
},
"collapsed": false
},
"outputs": [],
"source": [
"def load_full_rating_data(filename):\n",
" qratings = pd.read_csv(filename, index_col=False, header=0, names=['Timestamp', 'Effort', 'Level', 'Conceptual', 'Interest', 'Tedious', 'Context', 'Check My Work', 'Correct?', 'Detailed Calc', 'Question URL', 'Aux ID', 'Research'])\n",
" # Convert question levels and yes/no to numbers\n",
" qratings = qratings.replace({\n",
" 'High school/layperson (kinematics, EM, typically precalculus)': 1,\n",
" 'Intro college (Newtonian, EM, optics, etc.)': 2,\n",
" 'Intermediate/advanced college (Lagrangian & Hamiltonian, QM, stat mech, etc.)': 3,\n",
" 'Graduate level (QFT etc.)': 4,\n",
" 'Professional': 5,\n",
" 'Yes': 1,\n",
" 'No': 0\n",
" }).apply(lambda col: pd.to_numeric(col, errors='ignore'))\n",
" # Add QID column\n",
" qratings['QID'] = qratings['Question URL'].apply(lambda s: int(re.search('\\d+', s).group(0)))\n",
" # Invert ratings for the yes/no questions so that large numbers correspond\n",
" # to factors that we'd expect to support on-topicness\n",
" qratings[['Check My Work', 'Correct?', 'Detailed Calc']] = 1 - qratings[['Check My Work', 'Correct?', 'Detailed Calc']]\n",
" # Create index\n",
" qratings.set_index(['QID', 'Timestamp'], inplace=True)\n",
" qratings.sort_index(inplace=True)\n",
" return qratings"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T17:59:54.091284",
"start_time": "2016-08-27T17:59:54.085056"
},
"collapsed": true
},
"outputs": [],
"source": [
"def strip_rating_data(qratings):\n",
" # This if statement isn't strictly necessary\n",
" if not set(['Aux ID', 'Timestamp']) & set(qratings.columns):\n",
" return qratings\n",
" return qratings.reset_index() \\\n",
" .drop(['Aux ID', 'Timestamp'], axis=1, errors='ignore') \\\n",
" .set_index(['QID', pd.Index(np.random.permutation(range(len(qratings))), name='Rating ID')]) \\\n",
" .sort_index()\n",
"def write_stripped_rating_data(filename, qratings):\n",
" strip_rating_data(qratings).to_csv(filename)\n",
"def load_stripped_rating_data(filename):\n",
" return pd.read_csv(filename, index_col=[0,1])"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T17:59:54.099457",
"start_time": "2016-08-27T17:59:54.093359"
},
"collapsed": false
},
"outputs": [],
"source": [
"def load_score_data(filename):\n",
" qscore = pd.read_csv(filename, index_col=1)\n",
" # Add some columns\n",
" qscore['Score'] = qscore['Upvotes'] - qscore['Downvotes']\n",
" qscore['Votes'] = qscore['Upvotes'] + qscore['Downvotes']\n",
" qscore['Approval'] = qscore['Upvotes'] / qscore['Votes']\n",
" qscore['Wilson Lower 1'], qscore['Wilson Upper 1'] = tuple((2 * w - 1) * qscore['Votes'] for w in\n",
" smsp.proportion_confint(count=qscore['Upvotes'], nobs=qscore['Votes'], method='wilson', alpha=0.34))\n",
" qscore['Wilson Lower 2'], qscore['Wilson Upper 2'] = tuple((2 * w - 1) * qscore['Votes'] for w in\n",
" smsp.proportion_confint(count=qscore['Upvotes'], nobs=qscore['Votes'], method='wilson'))\n",
" return qscore"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Here we do the actual loading"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T17:59:54.184995",
"start_time": "2016-08-27T17:59:54.100924"
},
"collapsed": false
},
"outputs": [],
"source": [
"try:\n",
" qratings = strip_rating_data(load_full_rating_data('qratings.csv'))\n",
"except OSError:\n",
" qratings = load_stripped_rating_data('qratings_stripped.csv')\n",
"else:\n",
" import os.path\n",
" if not os.path.exists('qratings_stripped.csv'):\n",
" write_stripped_rating_data('qratings_stripped.csv', qratings)\n",
"qscore = load_score_data('qscore.csv')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Score analysis "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This plot shows the score of each question with the $p=0.05$ confidence interval as computed by the Wilson score. (Without the continuity correction, because I didn't have time for it.) The error bars are large, meaning more votes would be useful!"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T17:59:54.914836",
"start_time": "2016-08-27T17:59:54.186343"
},
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.text.Text at 0x111fb17f0>"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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WLMjq1av7KwsAAAD0So/23A4YMCBHH310xowZk0GDBnWOz549u8+DAbDzOGzP\n5V3GHl05ogpJAICdVY/K7QUXXNBfOQDYiR02/NUuY8otANCXelRuDznkkNx222159NFHs2HDhkya\nNCmnnnpqf2UDAAB+x5hJk5IkLy5dmv1GjapyGqgtPSq3V199dRYvXpyPfvSj6ejoyJ133pnnn38+\nl1xySX/lAwAAfmvs5MlJkuWtrRnb3FzlNFBbelRuH3744dx9990ZMOA356E66qij8qEPfahfggEA\nAEClenS25Pb29mzYsGGzn+vr6/s8FAAAAPREj/bcfuhDH8onP/nJfPCDH0yS/PCHP+y8DAAAANXS\no3L76U9/OgcccECefvrpbNy4Mccff3xOOeWU/soGAAAAFelRuZ09e3buuuuu3HXXXXn++edzxhln\nZLfddstJJ53UX/kAAHYIZ6EFKFuPyu13v/vdfPe7302SjB49OnfeeWc+9rGPKbf9aM2KZd1POqDr\n0KrlL2zfMgFgF+MstABl61G5Xb9+fXbffffOn3fbbbc+D8QbGhsbM2fWyd3Oe+6ee7qMffOiqd0u\nGwAAYGfRo3I7derUnHbaaTn22GNTV1eXH//4x3nf+97XX9l2efX19Wlqaup23pbKbSW3AwAA2Fn0\nqNxecMEF+dGPfpTHH388u+22Wz75yU9m6tRt7yEEAHZdPse6a7P+gR2p4nL7k5/8JG9729sybdq0\n1NfX54477sjgwYPz3ve+1+HJAMAW+Rzrrs36B3akAZVM+ta3vpXrr78+r7/+eubPn58LLrggU6dO\nzYoVK3L11Vf3d0YAAADYpor23P7gBz/I7bffnsGDB+fLX/5yjjnmmPzpn/5pOjo6ctxxx/V3RgAA\nANimivbc1tXVZfDgwUmSefPm5cgjj+wcBwAAgGqraM9tfX19Vq5cmTVr1uSZZ57J4YcfniR54YUX\nMnBgj85JBQAAAH2uomZ65pln5oQTTsiGDRty4oknZuTIkbnnnnvy1a9+NZ/5zGf6OyMAwC5jzYpl\n255wQNehVctf6P3yAHYSFZXbadOm5d3vfneWL1+ecePGJUmGDh2aL33pS5n021O8AwCwfRobGzNn\n1snbnLOl77f/5kXb/mrGxsbG7coFUIKKjyned999s++++3b+/N73vrdfAgEA7Krq6+vT1NS0zTlb\nKrfd3QZgV1DRCaUAAACglim3AAAAFE+5BQAAoHjKLQAAAMVTbgEAACiecgsAAEDxKv4qIGDHW7Ni\nWfeTDuhKNeB1AAAgAElEQVQ6tGr5C71fHgAAFEi5hRrV2NiYObNO7nbelr7v8JsXTd3mcgEAYGej\n3EKNqq+vT1NTU7fztlRuK7kdAADsTHzmFgAAgOIptwAAABTPYckAUKAxkyYlSV5cujT7jRpV5TQA\nUH3KLQAUaOzkyUmS5a2tGdvcXOU0AFB9DksGAACgePbcAhTKYakAAG9QbgEK5bBUAIA3KLfAdluz\nYln3kw7oOrRq+Qvbt0wAAPgt5RbYLo2NjZkz6+Ru5z13zz1dxr550dRulw0AAJVQboHtUl9fn6am\npm7nbancVnI7AACohLMlAwAAUDzlFgAAgOIptwAAABRPuQUAAKB4yi0AAADFU24BAAAonq8CAgAo\nyJhJk5IkLy5dmv1GjapyGoDaodwCABRk7OTJSZLlra0Z29xc5TQAtcNhyQAAABRPuQUAAKB4yi0A\nAADFU24BAAAoXk2V23//93/PF77whc6fn3zyyXzsYx/LySefnOuvv76KyQAAAKhlNVNuL7/88nz1\nq1/dbGzmzJm55pprcuutt+app57KM888U6V0AAAA1LKaKbcHH3xwLr300s6fV61alfXr12f06NFJ\nkiOOOCItLS1VSgcAAEAt2+Hfc3vHHXfk5ptv3mxs1qxZOfbYY/PYY491jq1evToNDQ2dPw8dOjTP\nP//8DssJAABAOeo6Ojo6qh1ik8ceeyy33357vvKVr2TVqlU56aST8sMf/jBJMnv27LS3t+f000/f\n6u1bW1t3VNSa8upDD3UZ2+vII6uQhGooZf2XkpOeWbx4ca7715fSMGL/bc4774BFXcaufW7MFueu\nWv5Czj3+zXnrW9/aJxkBgJ1Lc3PzFsd3+J7bSjU0NGT33XfPc889l9GjR2fu3Lk555xzur3d1n7R\n3mptbe3zZfa1+7ZQGmo5cwn36SYlZC1l/ZeS83eVsP6T6uYcNmxY8q8v9flyx48fn6ampj5fbqVK\nWfdJOVlLyZmUk7WUnEk5WUvJmZSTtZScSTlZS8mZ9E/Wbe3QrNlymySXXXZZzj///GzcuDGHH354\nJkyYUO1IAAAA1KCaKreHHnpoDj300M6fJ0yYkNtvv72KiQAAAChBzZwtGQAAAHpLuQUAAKB4yi0A\nAADFU24BAAAonnILAABA8ZRbAAAAiqfcAgAAUDzlFgAAgOIptwAAABRPuQUAAKB4yi0AAADFU24B\nAAAonnILAABA8ZRbAAAAijew2gEAKNuaFcu6n3RA16FVy1/o/fIAAH6PcgtArzU2NmbOrJO7nffc\nPfd0GfvmRVO3uVwAgJ5QbgHotfr6+jQ1NXU7b0vltpLbAQBUymduAQAAKJ5yCwAAQPEclgyFGzNp\nUpLkxaVLs9+oUVVOAwAA1aHcQuHGTp6cJFne2pqxzc1VTgMAANXhsGQAAACKp9wCAABQPOUWAACA\n4im3AAAAFE+5BQAAoHjKLQAAAMVTbgEAACiecgsAAEDxlFsAAACKp9wCAABQPOUWAACA4im3AAAA\nFE+5BQAAoHjKLQAAAMVTbgEAACiecgsAAEDxlFsAAACKp9wCAABQPOUWAACA4im3AAAAFE+5BQAA\noHjKLQAAAMVTbgEAACiecgsAAEDxlFsAAACKp9wCAABQPOUWAACA4im3AAAAFG9gtQOw/cZMmpQk\neXHp0uw3alSV0wAAAOx4yu1OYOzkyUmS5a2tGdvcXOU0AAAAO57DkgEAACiecgsAAEDxlFsAAACK\np9wCAABQPOUWAACA4im3AAAAFE+5BQAAoHjKLQAAAMVTbgEAACiecgsAAEDxlFsAAACKp9wCAABQ\nPOUWAACA4im3AAAAFE+5BQAAoHjKLQAAAMVTbgEAACiecgsAAEDxlFsAAACKN7DaAYBdw5hJk5Ik\nLy5dmv1GjapyGgAAdjbKLbBDjJ08OUmyvLU1Y5ubq5wGAICdjcOSAQAAKJ5yCwAAQPGUWwAAAIqn\n3AIAAFA85RYAAIDiKbcAAAAUT7kFAACgeMotAAAAxVNuAQAAKJ5yCwAAQPGUWwAAAIqn3AIAAFA8\n5RYAAIDiDax2gCRZtWpVzj///KxevTrr16/PxRdfnHe961352c9+liuuuCIDBw7Me97znpxzzjnV\njgoAAEANqok9t9/+9rfznve8J3PmzMmsWbNy2WWXJUkuvfTSXHPNNbn11lvz1FNP5ZlnnqlyUgAA\nAGpRTey5Pf3007P77rsnSTZs2JBBgwZl1apVWb9+fUaPHp0kOeKII9LS0pIDDzywmlEBAACoQTu8\n3N5xxx25+eabNxubNWtWxo8fn5dffjl/+Zd/mUsuuSSrV69OQ0ND55yhQ4fm+eef39FxAQAAKEBd\nR0dHR7VDJMkvfvGLnH/++bnwwgtzxBFHZNWqVTnppJPywx/+MEkye/bstLe35/TTT9/qMlpbW3dU\nXAB64NWHHuoytteRR1YhCQBQuubm5i2O18Rhyc8++2zOO++8XHvttfkf/+N/JEkaGhqy++6757nn\nnsvo0aMzd+7cik4otbVftLdaW1v7fJn9pZSspeRMZO0PpeRMyslaQs77tlBuazlzCffpJqVkLSVn\nUk7WUnIm5WQtJWdSTtZSciblZC0lZ9I/Wbe1Q7Mmyu0111yTdevW5fLLL09HR0f23HPPfO1rX8ul\nl16a888/Pxs3bszhhx+eCRMmVDsqAAAANagmyu0NN9ywxfF3vetduf3223dwGgAAAEpTE18FBAAA\nANtDuQUAAKB4yi0AAADFU24BAAAonnILAABA8ZRbAAAAiqfcAgAAUDzlFgAAgOIptwAAABRPuQUA\nAKB4yi0AAADFU24BAAAonnILAABA8ZRbAAAAiqfcAgAAUDzlFgAAgOIptwAAABRPuQUAAKB4yi0A\nAADFU24BAAAonnILAABA8ZRbAAAAiqfcAgAAUDzlFgAAgOIptwAAABRPuQUAAKB4A6sdAICd35hJ\nk5IkLy5dmv1GjapyGgBgZ6TcAtDvxk6enCRZ3tqasc3NVU4DAOyMHJYMAABA8ZRbAAAAiqfcAgAA\nUDzlFgAAgOIptwAAABRPuQUAAKB4yi0AAADFU24BAAAonnILAABA8ZRbAAAAiqfcAgAAUDzlFgAA\ngOIptwAAABRPuQUAAKB4yi0AAADFU24BAAAonnILAABA8ZRbAAAAiqfcAgAAUDzlFgAAgOIptwAA\nABRPuQUAAKB4yi0AAADFU24BAAAonnILAABA8ZRbAAAAiqfcAgAAUDzlFgAAgOIptwAAABRPuQUA\nAKB4yi0AAADFU24BAAAonnILAABA8ZRbAAAAiqfcAgAAUDzlFgAAgOIptwAAABRPuQUAAKB4yi0A\nAADFU24BAAAonnILAABA8ZRbAAAAiqfcAgAAUDzlFgAAgOIptwAAABRPuQUAAKB4yi0AAADFU24B\nAAAonnILAABA8ZRbAAAAiqfcAgAAUDzlFgAAgOIptwAAABRPuQUAAKB4yi0AAADFU24BAAAonnIL\nAABA8QZWO0CSrF27Nl/4wheyYsWKDBkyJFdffXVGjBiRn/3sZ7niiisycODAvOc978k555xT7agA\nAADUoJrYc/vd734348ePzy233JLjjjsuX//615Mkl156aa655prceuuteeqpp/LMM89UOSkAAAC1\nqCb23J522mnp6OhIkrz44ot505velFWrVmX9+vUZPXp0kuSII45IS0tLDjzwwGpGBQAAoAbt8HJ7\nxx135Oabb95sbNasWRk/fnxOO+20/Nd//Vf+8R//MatXr05DQ0PnnKFDh+b555/f0XEBAAAoQF3H\npl2mNWLhwoU566yzcvfdd+djH/tYfvjDHyZJZs+enfb29px++ulbvW1ra+uOigkAAEAVNDc3b3G8\nJg5LvvHGG7Pvvvvmwx/+cAYPHpz6+voMHTo0u+++e5577rmMHj06c+fO7faEUlv7JQEAANi51cSe\n21//+te58MIL8/rrr6ejoyPnn39+DjrooDz55JO54oorsnHjxhx++OE577zzqh0VAACAGlQT5RYA\nAAC2R018FRAAAABsD+UWAACA4im3AAAAFE+5BQAAoHjKLQAAAMVTboEdwonZ+8evf/3rakfoVknr\n/pVXXklra2teffXVakfZaZS0/gHovVWrVlU7gnK7M6nFF7lHHHFEHnnkkWrHqMgrr7yS6dOn59hj\nj80xxxyTk08+OV/+8pezevXqakfbzPLly3P55Zfn+OOPz1FHHZUPfehDueyyy2py/S9ZsiSf+tSn\ncvTRR2f8+PH52Mc+li984Qt5+eWXqx1tM6+//nq+/vWv54wzzsgpp5ySc889N7fddlva29urHa2L\nRYsWbfbf2Wef3Xm5lpSy7pPkzDPPTJI88MAD+bM/+7PMmTMnp5xySu6///4qJ9vcV7/61SS/2QZO\nPPHETJkyJR//+Mdrbt0n5az/kh77H//4x/Pss89WO0a3StpOS3mNsunv/o033pj58+fn/e9/f6ZN\nm5b/83/+T7WjdbFu3brN/jv11FOzfv36rFu3rtrRuihpW/1dX/jCF6odYasOP/zwfO9736tqBt9z\n+ztuv/32rV530kkn7cAklfn9B9+FF16Yq666KkkyZsyYakTq4oQTTsib3/zmDB8+POecc04OOOCA\nakfaqs985jM55ZRTcvDBB+e+++7LSy+9lNGjR+eee+7JtddeW+14nc4666x8+MMfzpQpUzJ06NCs\nXr06//Ef/5Hvfe97uemmm6odbzOf+tSnMn369IwZMyY/+9nP8sADD2Tq1Kn5u7/7u9x4443Vjtfp\nL//yL3PooYfm3e9+d+6///4MGDAgAwYMyKJFi/LXf/3X1Y63maOOOip77LFHRo4cmY6OjsyfPz/j\nxo1LXV1dZs+eXe14nUpZ90nyyU9+MrNnz84nPvGJXHfddfmDP/iDrF69Ov/rf/2v3HbbbdWO12lT\nzrPOOitnnnlmmpubM3/+/Fx11VX59re/Xe14myll/Zf02D/22GOz55575vDDD89f/MVfpKGhodqR\ntqik7bSU1yhnnHFGjjvuuLz44ou55ZZb8p3vfCeDBw/OBRdckO985zvVjreZiRMnZtCgQdljjz3S\n0dGRX/3qV3nTm96Uurq63HfffdWOt5lSttWjjjoqGzZs6Pz51VdfzV577ZUkmTt3brVibdFJJ52U\nd7zjHXn22Wdzzjnn5NBDD93hGey5/R0LFy7Mt771rbz88std/qtFp59+es4+++zMnDkzM2bMyKJF\nizJjxozMnDmz2tE67bnnnvnGN76R973vffnc5z6XT33qU7nppptq7gku+c2TxeTJkzNo0KAcd9xx\nmTt3bj7wgQ/kpZdeqna0zaxatSrHHXdcGhoaUldXl4aGhnzwgx+syXdFV61a1flGy0EHHZSf/vSn\nGT9+fFauXFnlZJt78cUXc+KJJ6axsTFnnHFGHn300Zx++uk1uZfk+9//ft72trflrLPOypw5czJu\n3LjMmTOnpoptUs66T9L5omHYsGGdLxiGDh2ajRs3VjPWVq1duzbNzc1JknHjxm32oqdWlLL+S3rs\n77PPPrnlllsybNiwnHjiiZkxY0buvffezJ8/v9rRtqiE7bSU1yhr1qzJRz7ykXzmM5/J29/+9owd\nOzajRo1KXV1dtaN1cfvtt2f8+PG54YYbcv/99+dd73pX7r///pq7T39XrW+rf/u3f5sJEybkzjvv\nzNy5c/Pud787c+fOrblimySDBg3KjBkzcsEFF2TOnDk5/vjjc/nll+/Q1ygDd9i/VICLL744Cxcu\nzJQpUzJhwoRqx+nW97///cycOTN/9md/lsMPPzynnnpq5syZU+1Ym9l0YMAHPvCBfOADH0hbW1se\neeSRPPLII3nf+95X5XSbGzp0aG688cZMmTIl9913X/bdd9889thj1Y7Vxd57753rr78+U6ZMSUND\nQ+ee23322afa0boYPXp0ZsyYkSlTpuSBBx7IgQcemH/7t3/L4MGDqx2ti3vuuSdHHnlk7rvvvgwe\nPDgLFizI66+/Xu1YXey999659tprc9VVV+U///M/qx1nq0pa98OHD88HP/jBrFy5MrNnz85JJ52U\n8847LwcddFC1o23mv//7v3P22Wdn1apV+fGPf5xjjjkmN998c4YMGVLtaF2UtP5Leex3dHRk4MCB\nOf3003PKKafkkUceSUtLS+6444584xvfqHa8TiVtp6W8Rhk+fHhuuOGGnH322bn55puTJD/4wQ8y\naNCgKifrqrGxMV/5ylcyY8aMHHXUUTVZwDcpZVs95JBDcsABB2TGjBn5i7/4i5q+Tzc9pt75znfm\nuuuuy2uvvZbHH398hx7q7bDk3/PKK69kzZo1GT16dLWjVGTDhg256qqrsvfee+fhhx+uuXJ74403\ndn6erdatWLEi3/jGN9LW1pYDDzwwZ555Zp544omMGTMmb3nLW6odr9Prr7+e2267La2trVm1alWG\nDRuWgw8+OB//+Mezxx57VDveZtatW5fvfe97efbZZ3PggQfmox/9aP7zP/8zb33rWzNixIhqx+v0\n/PPP5+qrr87ChQszbty4XHjhhXn44YczduzYmn6j684778ydd95Zc4elJeWs+9/161//OuvXr88+\n++yThx9+OFOmTKl2pC6WLFmSp59+OiNHjsz48eNz/fXX58wzz8yee+5Z7WibKWX9b3rsb3rer+XH\n/hVXXJG/+qu/qnaMimxpOz3rrLMybNiwakfbTCmvUdauXZvvfve7Oe200zrHbrzxxnz0ox/N3nvv\nXcVk23bdddflX//1X/PjH/+42lG2qpTn1OQ3z6t//dd/ndbW1vzv//2/qx1ni+6666585CMfqWoG\n5fZ3LFy4MGPHjq12jF6p5Re5v2vu3Lk54ogjqh1jpzJv3rzU19dn4sSJ1Y6yRT/5yU8yaNCgvOc9\n7+kcu/feezN16tQqpurq//2//5df/OIXWbt2bUaMGJGmpqaafXe0lPv01VdfzZAhQzJw4MD84Ac/\nSF1dXT784Q/X3P26YsWK/Pd//3cmTJiQu+66K08//XTe9v/bu/e4mvL9j+Pv2l1EuwiDSYMiyiUM\n9aDHMJkwk0zj0kXajON2qDjDICYmjcOMMIzENC4lqaMhuXXMYEIuIaaQKVLkdma6yK7Yu8v390e/\nvU5bmTnnd47W9/t7fJ6Ph8dkjx5e1t5r7/VtrfX9du8OHx8fGBnxdYFTWVkZ2rRpg3v37uHWrVvo\n3r07unfvLndWk0R5nTaku4edV9XV1cjNzYVarYaFhQV69OgBExMTubMaycvLg6mpKbp06SI9lpWV\nBScnJxmrGvvb3/4GHx8f7t6T/sj169ehVqv19i1e8X6M0hDP27Xhvm9sbIx+/fpxue8DgFqtlm6b\nO378OJ49e4Zx48Y12+cpDW4bcHR0xKxZsxAYGAhjY2O5c/5feHmSrl27dmHatGkA+Juk6/fuWeXp\nDSQtLQ1hYWGwsLDA6NGjcfnyZZiamsLJyQlz586VO09PWFgY1Go1ampq8Pz5c0RGRsLExESaxIEX\naWlp+Oabb9ClSxf8/PPP6NevH548eYJFixZx94EsyjZNSkrCjh07ANRfUqXVamFmZgZDQ0OsWLFC\n5jp906dPh6+vL7KysvD06VO4ubnh8uXLKC4uxvr16+XOk4SHh8Pa2hpt27ZFbGwsBg0ahKysLIwe\nPRrTp0+XO0+PKK/Tl+9Zi4iIwKJFiwCAux/Enj59GuvWrUPXrl3RsmVLVFZW4u7du1iwYAFXPzCI\njIzEuXPnUFNTA0dHR4SFhcHAwIC75x6of2/q3bs3Vq5cqTcQ582JEyewevVqGBoaQqVS4cSJE1Aq\nlejWrZv0euVFU8coJiYm6N+/P3fHKKJs17S0NKxfv577fR8AEhMTsXPnTgD1E2GVlJTAysoKFRUV\nWLNmTfNEMCIJCAhg27dvZx9++CE7cOAA02g0cif9rrt3777yFy9mzJjBfHx82ObNm9nmzZuZm5ub\n9DVvRo0axd5++202YsQI5ubmpvdfnnh7e7OKigpWUFDAnJ2dWXV1Naurq2O+vr5ypzXi5+cnfb17\n9242Z84cxlj9vsaTgIAAaX8vLS1lISEhTK1Ws0mTJslc1pgo29Tb25vV1tay4uJi5urqKj3u7+8v\nY1XTdNvu5W3I2z6l6/H392eVlZWMMcaqq6vZ+PHj5cxqkiivUy8vLzZu3DgWEhLCQkJCmKurq/Q1\nb3x9fZlardZ77NmzZ9w9/z4+Pqyuro4xxtiXX37JPv/8c8YYf889Y/VN165dY+PHj2chISHs6tWr\ncic1aeLEiay8vJw9fvyYDR06VPq84u09ijH9YxQXFxeuj1FE2a6i7PuM1W9TrVbL1Go1e/fdd6X3\ngub87OfreiuZGRgYYPr06RgzZgxiYmKwbds22NnZwcbGBkuXLpU7r5Fly5ahqKgItra20g3cALha\nEiQ6OhobN25EbW0t5s2bh4yMDAQFBcmd1aSEhARppkRLS0u5c16prq4OZmZm6Nq1K+bNmydd5sE4\nvAijtrYWWq0WJiYmUKlUePToEVatWiV3ViO6S2iA+pn+7t+/D3Nzcy5noBZlm9bV1eH58+do27at\nNIO7VqtFdXW1zGWNGRkZITs7GwMHDsTly5cxePBgZGZmwtCQrwUFGGN4+vQpbGxs8OLFC7Rs2RIV\nFRW07/8HEhISEB4ejoEDB8Lb2xsqlar5zi78m6qrqxvNq2BqasrdJbWMMalpyZIlWLhwIbZv385d\nJ1B/vNS/f3/s378fp06dQmxsLBYvXgxzc3MkJyfLnSepra1Fq1atANQ367YljzO6NzxGCQ4O5v4Y\nRYTtKsq+D9Rv0xcvXqC8vBxVVVWoqqqCiYlJsx5P0WXJDbw82zBjDHl5eSgoKMD7778vY1nTnj9/\njoCAAERFRaFDhw5y5/yu48eP48iRI/j1119/dz1huaWnp0OhUGDIkCFyp7xSfHw8EhMTkZKSIh18\nBwcHo1evXggMDJS5Tt+RI0fwzTffIDExEVZWVmCMYfny5Thw4ABycnLkzpNER0fj2LFjcHZ2xpUr\nV+Dv74+ysjIUFRVxt9alKNv0+PHj2LBhA1JTU6XXqUqlwocffghvb2+Z6/Tdv38fy5cvR2lpKW7f\nvo1WrVqhW7duWLVqFVf3X+ouS7W3t0dGRgb69u2L27dvY8GCBfDw8JA7T48or1OdnTt3orCwEHfu\n3MHevXvlzmnSvn37EBcXh7fffhtKpRIVFRXIzMyESqXiap+KiYnBkSNHsH37drRu3RparRZz5szB\nlStXkJWVJXeenletMlFaWgorKysZipq2Y8cO7NmzB9bW1ujQoQOKi4vRokUL9OnTB8HBwXLn6RHp\nGEWU7SrKvg8Ahw4dwtq1a9GrVy/06NEDaWlpMDMzg4+PD/z8/JqlgQa3DZw9exbvvPOO3Bn/lhs3\nbqC6uhoDBgyQO+UP3b59GykpKfj000/lThGeblIZnYKCAmlNSd5oNJpGyxXk5OTA0dFRpqKm5eXl\n4e7du7C3t4etrS13BzcNibJN6+rq9M5+VlRUwNzcXMai36fRaPD06VO0bt2ayyU2AKCyshLXrl2T\n3gMcHR3pdfpfcuHCBezfvx/r1q2TO+WViouLkZ2djcrKSpibm6Nv375o166d3FmNFBUV4c0334RC\noZAe43EyseLiYi63X1PUarW0lNaZM2dgaWkprc3KG5GOUUTZrqLs+y/Lzc2FUqnEm2++2Wx/pyIs\nLCys2f42zrVu3Rq5ubno0KEDkpOTkZSUhIcPH8LBwYG7y9N03njjDXTq1EnujFeKi4uDk5MTiouL\nERERgYsXL+LatWsYNGgQd+uI+fn5oX///tweKOr4+flhyJAhep08La3RkEajwffff49bt27BxsYG\n8+fPx969e+Hm5sbVm7JGo8GBAwdw8uRJ/Pjjj/jpp5+g1Wrh6OjI3b5fVlaGTZs2Ye3atYiOjsb+\n/ftx+/ZtjBgxgqt9qqysDF9//bVe571799C3b1+uOoF/tt6+fRsdOnSASqXC3r170adPH3Ts2FHu\nPIlGo8G+fftw9OhRXL16Fbm5uSgvL4ejoyN3szprNBokJibi4cOHUCqVmDt3LlJSUuDu7s7V+1Vq\naip69OiBqqoqJCUl4f79+7hz5w6cnJy4mkgQqN+mycnJ+Pvf/47MzEzcuXMHz5494+7512g0OHz4\nML799lskJCTgxx9/xJMnT+Dp6clVJ4BG70ULFy7E6NGjZap5tbi4OAwePBilpaVYtmwZkpOT8eTJ\nE26PpUQ5RhFlu4qy7wP1awevWLECJ0+eRM+ePWFnZwelUonPP/8cbm5uzdJAZ24bmD59Ovz8/PDz\nzz9zPWOmTllZGaKionDhwgVpvdNBgwYhKCiIm3XPdLMj/uUvf8F7772HkSNH4vz589i3bx9Xi84D\nwAcffAALCwu4urriT3/6E7dnmETpBICgoCDY2dmhsrISZ8+exbJly9C+fXusWbOGqzWZFy9eDGdn\nZwwYMACnTp2CoaEhDA0NUVBQwN1lybNnz4aXlxeGDRuGVq1aobKyEqdPn0ZSUhJiYmLkzpOI0gkA\nM2fOhIeHBx49eoT4+Hjs2bMHZmZmWLRoEVfLqy1YsAC9evXS26ZnzpxBVlYWtmzZIneenk8++QR2\ndnZ4/PgxLl26hPDwcLRs2RIbN27Erl275M6T6D6jPvvsM9jY2GDkyJG4cOECrl27xt3nvijPvyid\nQP1srjU1NdLvdVduAI1n0pYTHUu9HqJsV5H2KZVKhdmzZ6OmpgYRERGIiIiAo6PjK28BeB34Gu7L\nTKvVYuTIkdi9e7f0BLi7uzfbNeL/rpCQEHh5eWH+/Pl6B48LFy7k7uCxpKQEY8eOBQCMGDGCuz4A\naN++PXbu3Im4uDhMnDgRzs7OGDZsGDp37szVfXeidAL164d+8sknAABPT08MHz5c5qKmPXr0CBMn\nTosIys0AABD3SURBVAQA2NnZYebMmfjuu+/g7+8vc1ljFRUVevdXmpubY8yYMYiPj5exqjFROgGg\nqqpKWnT+0qVL0nrnvE3W8euvv2LDhg16j/Xq1YvL1+lvv/2Gr7/+GnV1dRg7dqw0jwFvE7Xo3Lt3\nD3/9618B1L8H/PDDDzIXNSbK8y9KJ1C/9NOuXbsQFhaGN954o1kPwP8v6Fjq9eB9u4q0TwH/XEbt\nrbfeQnBwcLNPKMfX9XYye3nGTABczpipozt4NDc3lxZLHjNmDFczvObl5WHVqlWoqanBhQsXUFdX\nh9TUVLmzmsQYg5GREaZNm4bDhw/jvffew5UrV7Bx40a50/SI0qmTkJCAbdu24enTpzh//jyys7O5\n3KeOHTsGtVqNgwcPwszMDHl5edBoNHJnNdK2bVtERkYiOzsbd+/exfXr1xEZGYn27dvLnaZHlE4A\nsLS0RFRUFBhjiI2NBQCkpKRwd9+tqakpDh48iJKSEmi1WpSWliI5OZmry+d0jIyMcOjQIRgaGiIl\nJQUAkJGRwd3gtrCwEDExMTAyMpImurp+/TpXn6M6TT3/Bw8e5O75F+l1OnjwYKxYsQIrVqzApUuX\nuPuBlg4dS70eomxXUfZ9oP69/9SpU6itrYWtrS2WL1+O2bNno7i4uNka6LLkBm7cuIGIiAhpxkxz\nc3N07dqVuxkzdebNmwd7e3sMGzYM5ubm0pnb27dvY9OmTXLnAag/c5eTk4MbN27Azs4OLi4uCA0N\nxaeffgpra2u58/SsXr0ay5YtkzvjD4nSCQCPHz9GTEwMHBwc0KFDB0RERMDS0hKhoaGws7OTO0/y\n4MEDrF27Fvn5+XBwcMCSJUtw7tw52Nraol+/fnLn6dFoNEhISEBmZqZ0O8LAgQPh5+fXaKkAOYnS\nCdTPPL9v3z5MnTpVeiw6OhoTJkzg5hYPoP5WlC1btuDq1auorKxEq1atMHDgQMyZM4erTqB+8pPo\n6Gi996qVK1dCpVJJZ8Z5kJOTg5s3b+LmzZtwcnKCu7s7pk+fjpUrV8LBwUHuPD0Nn3/d5Gw8Pv+i\ndDak1WoRHh6OzMxMLgc3rzqWWrhwITp37ix3nh6RjlFE2a4ivfc/fvwYmzZtQkhIiHSJ/8WLF7Fm\nzRrpB52vGw1uG3ByckJoaCi8vLxQVlbG9YyZgBgHj+np6dLlCbwTpVWUTkCcVlE6m5KdnY2KigoM\nHTpU7pTfJUonUH/mTq1Wc9mq0Wjwyy+/oKqqCm3atEHPnj25Pduk0WiQm5srtdrb23PbWlZWJn2O\n6g7IeKRWq2FkZCTN7goADx8+5O6HxQ0VFRXB0NCQ60adq1evokOHDty3irRNf/nlFy5PEOnU1tZC\noVCgoqICBQUF6NKlCywsLOTOIv8Bmi25gbS0NBgYGCAmJga9evXCW2+9JXfS7zIyMkL//v3h4eGB\njz76CFZWVujYsSNX3Z6ensjPz4eLiws3A+5X0bU6Oztz3SpKJ1DfevfuXe6ff1E6gfrlNGbMmIG4\nuDgwxrBnzx7k5uYiJycHrq6ucudJROkEGrfGxcVx2ZqWlobFixejsLAQ8fHxKCoqQkxMDLp169as\nyyz8K3StBQUF2LNnD7et2dnZCAwMREpKCs6ePYukpCQkJiaiZ8+e3K1EkJSUhCVLlmDv3r3QaDTS\nciVBQUHSPeM8yM7OxqxZs3DixAkwxvDFF1/g+PHjUCgU6N27t9x5el5uXb9+PZetIm3T9PR03L9/\nX/q1cuVK2NjY4P79+1wdnwLA1q1bcfHiRVRXVyMwMBD5+fn49ttvYWlpiZ49e8qdR/6vGJGoVCrG\nGGPZ2dksKCiIjRkzhq1atYrFxsbKXNa0n376iQ0fPpyNHTuWRUZGsqlTp7JZs2axLVu2yJ0mCQgI\nYKmpqczDw4Nt3ryZPXnyRO6kVxKlVZROxsRpFaWTMcYmTpzIysvL2ePHj9nQoUOZRqNhjDHm6+sr\nc5k+UToZE6c1ICBAaistLWUhISFMrVazSZMmyVzWmCitfn5+7NGjR3qPPXz4kE2cOFGmolebOHEi\n02g0TKPRsAULFrCtW7cyxuq3NU98fX3ZgwcPWEZGBhs4cCCrrKxkWq2Wu/2JMXFaRelkjDEvLy82\nbtw4FhISwkJCQpirq6v0NW8mTJjA6urq2OTJk1lJSQljjLHKyko2btw4mcv0eXp6MldX1yZ/8YaH\nVpotuQH2v1do9+3bF5s3b4Zarcbly5dRUFAgc1nToqKicPToUfz222/w9fXFuXPnoFAoMGnSJMyd\nO1fuPAD1s42+//77GD58OL7//nsEBwejuroa1tbWiIyMlDtPjyitonQC4rSK0gnUX0LVqlUrAPXd\nuss8eZuoR5ROQJxWtVottZmamuL+/fswNzfncvIjUVpramoanaHt1KkTl5dPKxQKae3dr776CjNm\nzEDnzp25a62rq4O1tTWsra0REBAgTXrDWycgTqsonUD9JJLh4eEYOHAgvL29oVKpsGbNGrmzmmRo\naIjq6mq0a9dOutSft3VjASAyMhILFixAfHw891eX8dDK3zMoo/Hjx+v9XqlUYsSIETLV/LG6ujqY\nmZmha9eumDdvnrRDMo5uo9a1mJmZQaVSQaVSSfc18EaUVlE6AXFaRekEgDFjxsDd3R3W1tZwcXHB\njBkz0KJFC7zzzjtyp+kRpRMQp9XDwwPe3t5wdnbGlStX4O/vj++++w6Ojo5ypzUiSuvw4cPx8ccf\nw9XVFUqlEhUVFUhPT8ewYcPkTmtkwIABCA4OxurVq6FUKrFp0yZMmzYNDx48kDtNz5AhQzBt2jTs\n2LFDWgouPDycy8s8RWkVpROo/xxds2YNdu7ciRUrVqC2tlbupFfy8/ODSqVC79694evrC2dnZ1y6\ndElaGpAXXbp0wZQpU5CRkcHtkoo6PLTShFICi4+PR2JiIlJSUqSlVYKDg9GrVy8EBgbKXFeP94kE\nGhKlVZROQJxWUTp11Gq19FPmM2fOwMLCAoMGDZK5qjFROgFxWvPy8pCfnw97e3vY2dmhtLQUVlZW\ncmc1SZTWnJwcZGZmorKyUprZl7dBuE5GRgYGDBggncHVTSz58ccfyxv2klu3bunNNn3x4kU4Oztz\nuQycKK2idDZ04cIF7N+/H+vWrZM75ZWKiopw/vx5lJWVoU2bNhgwYADs7e3lziL/AX73CPKHJk+e\njN27d+u9sS1YsICbgS2ARgMGXi9NAcRpFaUTEKdVlE4dpVIJIyMjGBkZISMjg8tBGCBOJyBOq729\nPT744APY2dlhzZo1XA4WdURoTU1NhaOjI8aPH4/y8nKcOHECx44dQ2VlpdxpjaSmpsLFxQXV1dX4\n6quvMG3aNGzevBne3t5yp+lJTU2Fg4MDqqqqpM709HQ8f/5c7rRGRGkVpROAtJRSVVUVzpw5g+Li\nYqxbt47bfcrGxgaenp4oLy9HamoqDh06xF3rwoULUVJSInfGv4SHVjpzK7CioiJphtfo6GjcvHkT\n3bt3x5///GcolUq58wDUX/KhwxhDfn4+unfvDgBITEyUK6tJorSK0gmI0ypKJyBOqyidgDitonQC\n4rROmTIFu3fvRmhoKGxsbODu7o4LFy7g2rVrWL9+vdx5ehq2du7cGSNHjuSyVdf52WefwcbGhttO\nQJxWUToBMVt53/9HjBgBS0tLBAQEYPz48Vzea63DRWuzTV1F/usmTZrELl68yEJDQ1lkZCTLyclh\nsbGxbObMmXKnSQ4dOsSmTp3K8vLyWFFREfPx8WEPHjxgDx48kDutEVFaRelkTJxWUToZE6dVlE7G\nxGkVpZMxcVp1qyRMnjy5ycd5IkqrKJ2MidMqSidj1Po6BAQEsPLycvbFF18wT09Ptm3bNpaTk8PU\narXcaY3w0EqXJQtMoVDAxcUFDx48QGBgIBwcHDBlyhSo1Wq50yRjx47FkiVLsHbtWmi1Wpiamkoz\n/vFGlFZROgFxWkXpBMRpFaUTEKdVlE5AnNbCwkLExMRAoVAgJycHAHD9+nXuZnUGxGkVpRMQp1WU\nToBaXwcDAwNYWFggNDQUsbGxUCqViIqKwqRJk+ROa4SHVkVYWFhYs/1t5L/qxIkTUCgUaNeuHQoL\nC9GpUyf88MMPyM/Ph5eXl9x5kvbt22PYsGFYtWoV/vGPf8Df3x9arRYKhULutEZEaRWlExCnVZRO\nQJxWUToBcVpF6QTEaHVxcUF5eTlqampgZGSEzp07Y+HChQgJCWm0RJDcRGkVpRMQp1WUToBaX4ez\nZ89i9OjRAOpno+7bty88PDwwYcIE7pYu4qK12c4Rk/+6kpISFhISwkaNGsV69+7NXF1d2bx589jD\nhw/lTpOcPHmSvfvuu8zd3Z0dPnyYZWVlMcb4u+SDMXFaRelkTJxWUToZE6dVlE7GxGkVpZMxcVob\ndh45ckR6nLdOxsRpFaWTMXFaRelkjFpfh4adR48elR7nrZMxPlr5Gu6Tf4uVlRX3s7pu27YNycnJ\nYIxh/vz5GDduHPr168fVWrw6orSK0gmI0ypKJyBOqyidgDitonQC4rS+3KnVajFu3DjuOgFxWkXp\nBMRpFaUToNbX4eVOjUbDZSfARysNbgWmUqlQXV3d5P/jZTZKY2NjtG7dGgAQFRWFqVOnolOnTlzO\n9CZKqyidgDitonQC4rSK0gmI0ypKJyBOqyidgDitonQC4rSK0glQ6+sgSifARystBSSwrKwshIaG\nYsuWLY3uYeJl0o7FixejTZs2mD9/Plq2bInHjx9j+vTpePbsGdLT0+XO0yNKqyidgDitonQC4rSK\n0gmI0ypKJyBOqyidgDitonQC4rSK0glQ6+sgSifARytNKCWwjh07oqqqCjU1Nejfvz8sLCykX7xw\nc3NDSUkJevToAWNjYyiVSowePRrl5eUYNmyY3Hl6RGkVpRMQp1WUTkCcVlE6AXFaRekExGkVpRMQ\np1WUTkCcVlE6AWp9HUTpBPhopTO3hBBCCCGEEEKER+vcEkIIIYQQQggRHg1uCSGEEEIIIYQIjwa3\nhBBCCCGEEEKER4NbQgghhBBCCCHCo3VuCSGEEE49f/4cmzZtQlpaGlq0aAGlUomgoCC4uLggMjIS\nABAUFISQkBBkZGSgdevWqKmpgbGxMWbMmAEPDw+Z/wWEEEJI86HBLSGEEMKpwMBA2Nra4ujRo1Ao\nFLh16xZmz56NDRs26P05AwMDzJ8/Hx999BEAoKioCJMnT0abNm0wZMgQOdIJIYSQZkeXJRNCCCEc\nyszMRGFhIZYuXQqFQgEAcHBwwJw5cxAVFfW732tjY4MpU6YgISGhOVIJIYQQLtDglhBCCOHQ9evX\n4eDgIA1sdQYPHoysrKw//P4ePXrg7t27ryuPEEII4Q4NbgkhhBAOMcZgYGDQ6PEXL16grq7uD7/f\nwMAApqamryONEEII4RINbgkhhBAO9e3bFzdv3kRtbS0AoLS0FACQlZWFPn36/OH35+bmonv37q+1\nkRBCCOEJDW4JIYQQDg0aNAi2trb48ssvUVNTg+TkZPj5+WHr1q0IDAxs9OcZY9LXhYWFSEhIgL+/\nf3MmE0IIIbIyYA0/DQkhhBDCDY1Gg3Xr1uHMmTMwMTGBhYUFGGMYMGAAjIyMYGxsjKCgICxduhQZ\nGRmwtLQEABgZGWHmzJkYNWqUzP8CQgghpPnQ4JYQQggRzOnTpzF8+HC5MwghhBCu0OCWEEIIIYQQ\nQojw6J5bQgghhBBCCCHCo8EtIYQQQgghhBDh0eCWEEIIIYQQQojwaHBLCCGEEEIIIUR4NLglhBBC\nCCGEECI8GtwSQgghhBBCCBHe/wB1Y/4WwvvpMwAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x111f515f8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"qscore['Score'].sort_index().plot(\n",
" kind='bar',\n",
" yerr=np.array([[qscore['Score'] - qscore['Wilson Lower 2'], qscore['Wilson Upper 2'] - qscore['Score']]]),\n",
" error_kw={'ecolor':'rosybrown', 'linewidth':5})\n",
"plt.ylabel(r'Score, with $p=0.05$ CI')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Rating analysis "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Group the results by question and compute the average and standard deviation of each score. I also compute a normalized version of the means: first shift each rating column to a mean of zero and a standard deviation of one, then group them."
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T17:59:54.921874",
"start_time": "2016-08-27T17:59:54.916116"
},
"collapsed": false
},
"outputs": [],
"source": [
"g = qratings.groupby(level=0)\n",
"qratings_mean = g.mean()\n",
"qratings_std = g.std()\n",
"del g"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Look for correlations within the ratings. These results show a _slight_ positive correlation between effort and prior research, inverse between research and tediousness, and inverse between level and tediousness, but it's very little to go on."
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:04.087781",
"start_time": "2016-08-27T17:59:54.923112"
},
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<seaborn.axisgrid.PairGrid at 0x112070828>"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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LUrUv7X81//+pcEBgZKv379dO7Pz8+X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\nAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x112070fd0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.pairplot(qratings_mean.apply(spst.zscore))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"A better visualization of the same data:"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:04.542297",
"start_time": "2016-08-27T18:00:04.088928"
},
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x11671a2e8>"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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B3Ncyihe/yP/WskrpIJIu+gZ4y5Gz3Fwvgg8ea4nJMFiwPoGTReAgxmKxMGT4CP476DEc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XGqLIuluXPn0rt3b5KTk1m+fDkFChRwRC4REREREXEhabnwS2kzLZaGDBli/wJab29vIiIimDBh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\nyZIQQgghhBBClOD/AC48ff5EtHJGAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x11667c588>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.heatmap(qratings_mean.corr(), annot=True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Correlative analysis "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Simple correlation "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Here I plot the ratings (survey results) for each category for each of the 21 questions. The color of each bar shows the question's score. If there are any correlations, we'd see a plot where the red bars tend to be tall and the blue ones short, or vice versa. But we don't."
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:06.645937",
"start_time": "2016-08-27T18:00:04.543674"
},
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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gs1JjPLpvrC7ff2b3faAAGi6KUuAMGNUUAFAdh4oKlbp0TaX3nkl1+/4zu+8D\nrY3bCKBmUJQCAAD4QFX3nkl1//4z7gMFYAfuKQUAAAAA+A1FKQAAAADAb7h8FwAAoIEwZWVVDirE\n4ES1W5kHr6FUtwfRQsNDUQoAANBAFB3L0cFxExUQGlZhG/d1VytQ0oEhIyuNlXYsR7pxgM0Z1j12\nDo7ovvCKKtsczzqih5fuqteDaKHh8VlR6na7NXHiRB08eFAlJSW6++671bNnT1+tDgAAAB44PzRM\n7cKaVLh8V0CAJFXaRpL+V1hga17wXEMYRAsNi8+K0jVr1igiIkJz5szR0aNH1a9fP4pSAAAAAMBp\nfFaU3njjjerdu7ckyRij4GCuFPa31NRUFRcXKzY21t+pAAAAAIAkHxalYWEn7lXIzc3VAw88oLFj\nx/pqVbBRaWmpMjIyKm3j6QAIkhQdHa2goCC70gMAAABQz/j09OWhQ4d03333KSkpSX369KmyfVpa\nWvnPTqdTtfG26/T0dLlcLo/anro9v+R0OhVuV1LyLK/i4mKP8pq2al2lN897cuO8dOI+hWn9r1VU\nVFS1crKqqlhOp9O2ddnJzmOrIfB0f9W2Y2tf+Hl2peOxhnBsWdlGAABQu/isKM3KytKoUaOUkpKi\nP/zhDx4959TLSh0Ohwp2pfsqPa916NBBMTExVbZLS0ur9DJZh8OhAzWc1+bNm6u8fNfhcCh0w85K\nb5735MZ5T/PyJCcrqtrv0olt1IadtqzPTnYeW/9ybrIztVrJk/3lyfHgKY+Pre37bFmfnew8tl7d\n862dqdnmTNto5xcSAADAdwJ9FXjhwoU6fvy4FixYoOTkZA0fPrz8rFh9l5qaqnXr1vk7DQAAAACo\n9Xx2pnTSpEmaNGmSr8IDAAAAAOoBhsQFgCowcjUAAIDv+OzyXQAAAAAAqkJRCgBAPfL5558rOTn5\nV4+vX79eAwcO1ODBg/Xaa6/5ITMAAM6My3cBAKgnFi9erNWrV6tJkyanPe52uzV79mytWrVKISEh\nGjJkiHr27KnIyIqn/wIAoKZwphQAgHoiKipKzz333K8ez8jIUFRUlMLDw3XWWWcpNjZWO3bs8EOG\n/jOqU2eN6tTZ32kAdc7HitDHivB3GqjnOFMKnzFlZcrMzKy0jdvtltvt1v79+6uMFx0draCgILvS\nA4B65/rrr9fBgwd/9Xhubu6JeXR/0qRJE7lcrppMDQCAClGUwmeKjuXo4LiJCggNq7CN+7qrFSjp\nwJCRlcbLhTSLAAAgAElEQVT6X2GB9OZyxcTE2Jwl6itGzAV+Fh4ertzc3PLf8/Ly1LRpUz9mBKC+\n8eRkhCQ5nc7TviQ7E0/ieKqsluaF01GUwqfODw1Tu7AmFS7fFRAgSZW2AQBYY4w57ffo6Gg5nU4d\nP35coaGh2r59u0aNGuVRrLS0tPKfnU6nom3NFEB9UXQsRw8vXaPQCA/uVd+ws9LFx5wZ6tkj3pa8\njmcd0aNv7FeTyBZVN96+r9LFWRn/VVDr823JqyFIT0/3+KocilIAAOqZgJ++8HvnnXdUUFCgxMRE\nTZgwQSNHjpQxRomJiWrVqpVHsU692sDhcKhgV7pPcgZQ94VGRKpxpGefLZUpzMm2IZufNYlsIUfL\nc6odJ+/HLBXbkE9D0aFDh19d5XjqF52noigFAKAeOe+887RixQpJUkJCQvnj8fHxio+P91NWAABU\njKIUAACgjmN0VAB1GVPCAAAAAAD8hqIUAAAAAOA3FKUAAAAAAL/hntJ6oNQYj+ZNcrvdcrvd2r9/\nf4VtmH8JAAAAQE2iKK0HDhUVKtWDeaF6RJw4MZ40b1mFbY45M9QsilnoAAAAANQMitJ6wpN5oQKU\nI0lqXMnkwXbPCwUAAGAHRhhGXcBx6h2KUgtMWZmtl8kG2JkcAAAAANRBFKUWFB3LUd4nacr95mCl\n7coKCxUsKXfTlgrb/Dc9XTE25wcAAAAAdQ1FqUVtzzlHF553fqVtNmX9IEmVtnMe/t7WvAAAAACg\nLqIoBdCglZaWKiMjo9I2nlySLzF6NQAAqJ2OtL7I3ylUiqIUQIOWkZGhqUteVfOWrSts0zK/UJL0\n9LubKo31zd7d0tkVxwEAAMCvUZQCaPCat2ytyHMrvtw+8KssSaq0jSQd/eGwfrQ1MwD1XW0cqfOW\nLZ/aFqs2bl9Dwb5HXUJRCqDO8WQkbC65BQAAqBsoSgHUOUXHcvTw0jUKjYissE2PiEBJUtK8ZZXG\nOubMUM8e8XamBwAAAAsoSgHUSaERkWoc2arC5QHKkSQ1jmxRaZzCnGxb8wIAAIA1gf5OAAAAAADQ\ncFGUAgAAAAD8xqdF6eeff67k5GRfrgIAAAAAUIf57J7SxYsXa/Xq1WrSpImvVgEAAAAAqON8dqY0\nKipKzz33nK/CAwAAAADqAZ8Vpddff72CgoJ8FR4AAAAAUA8wJQzqhFJjlJmZWWU7p9Mph8NRaRtP\n4tS00rIyj/Oqahtr4/bBfwzHFgAAqOV8XpQaYzxum5aWVv6z0+lUtC8SQp10qKhQqUvXKDQisurG\nG3ZWuviYM0PNomrX0fXd8WOa7en2SZVu4zFnhnr2iLcnMdR5Rcdy9LCNx9Zvf/c7mzKzV3p6ulwu\nl7/TAADANh8rwt8p1BifF6UBAQEet42NjS3/2eFwqGBXui9SQh0VGhGpxpGtqh2nMCfbhmzsV9+3\nD/7TEI6tDh06KCYm5rTHTv2is6EwxmjatGnat2+fGjVqpMcff1xt2rQpX/7YY4/ps88+Kx+EcMGC\nBQoPD/dXugAASPJxUXreeedpxYoVvlwFAAD4ydq1a1VcXKwVK1bo888/16xZs7RgwYLy5Xv27NEL\nL7yg5s2b+zFLAABOxz2lDUhDugQAABqitLQ0XXPNNZKkTp06KT395yuOjDFyOp1KSUnRkSNHNHDg\nQA0YMMBfqQIAUI6iFACAeiI3N/e0waqCg4NVVlamwMBA5efnKzk5WbfffrvcbreGDx+uyy+//FeX\nPQMAUNMoSn1gVKfO/k4BANAAhYeHKy8vr/z3kwWpJIWFhSk5OVkhISEKCQnRH/7wB+3du7fKopRB\nCAEA3rAyCKHP5ikFAAA1q3Pnztq0aZMkaefOnacVnJmZmRo6dKiMMSopKVFaWpouu+yyKmPGxsaW\n/+vQoYPPcgcA1C8dOnQ4rQ85dVDbX+JMKfzqli2f+jsFAKg3rr/+em3dulWDBw+WJM2aNUtLlixR\nVFSUevTooZtvvlmJiYk666yz1K9fP0VHc94TAOB/FKWwjAGTAKB2CggI0PTp0097rF27duU/jxo1\nSqNGjarptAAAqBRFKYB6yc4vT9wXXmFbLAAAAJyOe0oBAAAAAH5DUQoAAAAA8BuKUgAAAACA31CU\nAgAAAAD8hqIUAAAAAOA3FKUAAAAAAL+hKAUAAAAA+A1FKQAAAADAbyhKAQAAAAB+Q1EKAAAAAPAb\nilIAAAAAgN9QlAIAAAAA/IaiFAAAAADgNxSlAAAAAAC/oSgFAAAAAPgNRSkAAAAAwG8oSgEAAAAA\nfkNRCgAAAADwG4pSAAAAAIDfUJQCAAAAAPyGohQAAAAA4DcUpQAAAAAAvwn2VWBjjKZNm6Z9+/ap\nUaNGevzxx9WmTRtfrQ4AgAavqr731Vdf1cqVK3XWWWfp7rvvVnx8vP+SBQDgJz47U7p27VoVFxdr\nxYoVeuihhzRr1ixfrQoAAKjyvjcrK0tLly7VypUrtXjxYj355JMqKSnxY7YAAJzgs6I0LS1N11xz\njSSpU6dOSk9P99WqAACAKu97d+3apdjYWAUHBys8PFxt27bVvn37/JUqAADlfHb5bm5urhwOx88r\nCg5WWVmZAgM9r4MPfPedLbn874cfVJiTXe04RceP6sD339uQkXTwSJYaFxbYEuv7okJbtk86sY12\nKTp+VP9rANv4bXFAteMcch1XYSP7tu/okcO2xDr+Y5YK8+w5k2L3frczlp37K88E2RKrICdHJY0K\nqx3H7n3lyvrBlli5OdkqLLVnX9n12VAfVNb3/nJZ48aN5XK5LK+Dvtkztbnfom/2DH2zf2PRN3se\nqz70zT4rSsPDw5WXl1f+uycFaVpa2mm/n9+tq9w25PL7dlH6vQ1xTjI2xOjauZM0fJgNkaQbfvpX\nn9X3bYz/6V+t072zvzOoW2zdX71sjFUL3Xi1reFcLtev+pCGqLK+Nzw8XLm5ueXL8vLy1LRp0ypj\n0jd7p773W1L938Z40TfXC/TNnvNj3+yzorRz587asGGDevfurZ07dyomJqbS9rGxsb5KBQCABqGy\nvrdjx45KTU1VcXGxioqK9PXXX+uiiy6qNB59MwCgJgQYY+z4cvFXTh0BUJJmzZqldu3a+WJVAABA\nZ+57N23apKioKPXo0UOvvfaaVq5cKWOMxowZo+uuu87PGQMA4MOiFAAAAACAqvhs9F0AAAAAAKpC\nUQoAAAAA8BuKUgAAAACA31CUAgAAAAD8hqIUAAAAAOA3PpunFPWTMUYBAQFeP7+oqEgvvviiPv30\nUxUUFCgiIkJXXXWVBg0apKCgoGrllp2drcjIyGrFkKq/jaf68ccflZmZqejoaDVv3tyWmHaozjba\n+RoOHjxYjz32mC688EKvckH9kpubq/DwcH+nAdQ59M3W0DdXjr4Zp6qpvrlOnSlduXJlhf/skJ2d\n7dXzrr76am3bts2WHH788UdNnjxZN954o3r27KmhQ4dq7ty5ysvLsxQnJydHjz/+uBISEhQfH6+b\nbrpJ06dP92obv/nmG40aNUo9evRQhw4dNGjQID300EM6cuSI5VhTpkxRy5YtNX78eMXFxemKK65Q\nYWGhpk+fbjlWZmbmaf/GjBlT/rNVdm7j6NGjJUkbN27UkCFDtHTpUiUlJWn9+vWWYz399NOSTmzr\nwIED1b17dw0ePNiv22jna3js2DFNmjRJzz77rHJzcy0//1R27is739Mn34uLFi3S3r17df3116t3\n79767LPPLMcqLi4+7V9ycrJKSkpUXFxsOZad++uXHnroIa+e161bN7322mvVXj9qFn2z5+ibraFv\n9hx9szX0zZ6rsb7Z1CEzZ840119/vZk3b96v/nnj66+/Pu1fYmJi+c9W3HLLLeauu+4yf/nLX8w3\n33zjVS4n3XPPPWbbtm2msLDQvPvuu+aFF14wH374oXnggQcsxRk9erR59913jcvlMmVlZcblcpl3\n3nnHjBgxwnJOI0eOLN8nn332mXn66afNF198Ye68807LsYYNG3ba73fccYcxxpghQ4ZYjhUXF2du\nuOEGk5ycbJKSkkyXLl1MUlKSSU5OthzLzm08uf6hQ4ea7OxsY4wxubm5ZvDgwV7HGj16tNmxY4cx\nxpgvv/zS3HbbbZZj2bWNdr6GycnJpqSkxLz44ovmhhtuMFOmTDH/+te/zJdffulVLGPs2Vd2vqfv\nuOMOs2rVKjN//nzTtWtXk5GRYb777rtf7UdPxMbGmquuusr07NnT9OjRw1x++eWmR48epmfPnpZj\n2bm/4uLiTLdu3cr/XXbZZeU/WzFo0CAzffp0k5ycbP7zn/9YzgP+Qd/sOfpma+ibPUffbA19s+dq\nqm+uU5fvTpgwQV9//bW6d++ujh07Vjve7bffrtDQULVq1UrGGGVmZiolJUUBAQF6+eWXPY7TtGlT\nPf/88/roo480duxYNWvWTNdcc43atGmja6+91lJOR48eVdeuXSVJffr00ciRI/Xiiy/qxRdftBQn\nNzdXffr0Kf89PDxcffv21SuvvGIpzslY7dq1kyRdccUVeuqpp/Tggw/q+PHjlmNJ0nvvvadrrrlG\n69atU1hYmPbv36+ioiLLcd544w1NnTpVQ4YMUbdu3ZScnKylS5d6lZOd2+h2uyVJDoej/LKgJk2a\nqKyszKvcJKmgoECxsbGSpEsuuaR8HVbYuY12vYbGGAUHB+v2229XUlKStm3bpv/7v//T66+/ruef\nf95yPMmefWXnezo/P1/9+vWTJH3yySe64IILJMmrS7RWrlypOXPmaNy4cbr44ourdcyfZMf++utf\n/6p//OMfmjZtmlq1auV1XiEhIUpJSdEXX3yhRYsWacaMGeratavatGmj4cOHW46HmkHf7Dn6Zmvo\nm62hb/YcfbPnaqpvrlNFqSQ98cQTys/PtyWWXR+cxhhJUq9evdSrVy9lZGRo27Zt2rZtm+U3SZMm\nTbRo0SJ1795d69atU+vWrfXJJ59YzikyMlLz589X9+7dFR4erry8PG3atEktW7a0HOv8889XSkqK\nunfvro0bN6p9+/b66KOPFBYWZjnW7NmzNWfOHC1YsECXXHKJpkyZoq1bt2rq1KmWY0VGRio1NVVP\nPPGEvvjiC8vPP5Wd29isWTP17dtXx48f18svv6xbb71VDz74oK644grLsQ4cOKAxY8YoNzdXH374\noXr27KmXXnpJjRs3thzLrm08+Ro+99xzat++fbVew/bt25f/fNZZZykuLk5xcXGW40j27is739PN\nmjXTggULNGbMGL300kuSpNWrVyskJMRyXtHR0XryySeVkpKi+Pj4at1fZef+uvLKK9WmTRulpKRo\n5MiRXud1cr9ffvnlmjdvnlwul7Zv327LZUvwLfpmz9A3W0Pf7Dn6ZvrmX6prfXOAObmmOuDrr78u\n/ybDLm63W0888YQiIyO1detWrzq+RYsWld+rUF3Hjh3T888/r4yMDLVv316jR4/Wjh071K5dO/3m\nN7/xOE5RUZGWL1+utLQ05ebmyuFwqHPnzho8eLBCQ0Mt5VRcXKzXXntNX331ldq3b68BAwboiy++\nUFRUlCIiIqxuogoLC7Vv377yG/FjYmKqPXjBqlWrtGrVKi1btsyr59u9jdKJ+6BKSkrUsmVLbd26\nVd27d/cqzjfffKP09HS1atVKHTp00Pz58zV69Gg1bdrUUhxfbKMk7d27V5dcconXzy8pKdG+ffvk\ncrnUtGlTXXTRRWrUqJFXsc60r+666y45HA5Lcex8TxcUFOjVV1/ViBEjTos/YMCAag3+MW/ePL3z\nzjv68MMPvY5h17F1UnFxsWbMmKG0tDS9//77lp//5ptvln9zjbqDvpm+uSL0zVWjb/YcfXP97pvr\nVFF66aWXavTo0br33nt11lln2Rq7uh+cp9qyZYuuvvpqG7Kyz3/+8x8FBQWpS5cuXj1/w4YNCgkJ\n0VVXXVX+2Nq1a3XddddZirNx40Y9++yzioqK0s6dO9WxY0d9//33evjhh73Kza68pBOXZzVu3FjB\nwcFavXq1AgICdMstt1julI8dO6YDBw6oY8eOevPNN5Wenq4LL7xQgwYNUnCw9YsTcnJyFBERIafT\nqS+//FIXXnih1yPi2bG/tmzZctrvf/3rX/Xwww9LkuXjftOmTZo7d67atm2rxo0bKy8vT19//bXG\njRvn1Wu4f/9+hYSEKCoqqvyxzz//XJ06dbIUZ+XKlRo0aJBtIz2e6osvvpDL5TrtNfBWdd/XduZ1\n6h8wZ511ljp27OjVHzAul0sBAQEKDw/Xhx9+qOPHj6tfv35evXdQM+ibvUffXDX6Zs/QN1cPfXPl\naqJvrlNFaXJysuLj47VmzRrddttt6tu3r9ff2tjplyMM/uMf/9Dtt98uSbr11lstxapspC4r27px\n40ZNmzZNTZs21Q033KDt27crJCREnTp10j333GMpp2nTpsnlcsntdqugoEDz589Xo0aNNHz4cEv3\n90gnXsMXXnhBjRo1Uk5OjubMmaNJkyZp9OjR+uc//+m3vF577TW98MILkk5c7lBcXKywsDAFBgYq\nJSXFUqxRo0bp1ltv1eeff66jR4+qR48e2r59u7KysvTkk09aijVjxgydd955ioyM1EsvvaQuXbro\n888/1w033KBRo0ZZimXX/vrjH/+owMBAXXzxxZKkzZs365prrpEkzZo1y1JOgwcP1uLFi08batzl\ncum2227TG2+8YSnW/PnztXXrVrndbl166aWaNm2aAgICvDoerrzySl122WWaPn36aZ2oN9auXauZ\nM2cqMDBQycnJWrt2rRwOh9q1a1f+B4OnzvS+btSoka644grL72u783ryySer/QfMihUryu/Ri4+P\nV3Z2ts4++2zl5uZaPrZQc+ib6Zt9lRd9M33zqeib63nf7LMhlHzg5IhUhw4dMrNmzTK9evUyY8aM\nMTNnzvQq3i9H+Dv1nxV33HGHGTRoUPlogz169PB65MFevXqZ2NjY8hG8Tv3fisTERJObm2syMzPN\n7373O1NSUmLKysrMrbfeajmnU0eme/nll82YMWOMMcYkJSVZjnXLLbeY4uJiY4wxeXl5ZujQocYY\nYwYMGODXvBITE01paanJyso6bVSyk/lZcXL9v8zDm31/8jlDhw41eXl5xhhjSkpKTP/+/S3Hsmt/\n5efnm/Hjx5tXX33Vq+efqn///qakpOS0x4qKirw6HgYNGmTKysqMMcbMnj3bTJ061ev8kpKSzGef\nfWb69+9vxo8fbz799FPLMU4aOHCgOXbsmDl06JC56qqrTFFRkTHGu+Ph1Pf173//+2q9r+3M69Zb\nbzUul+u0x44fP275OB04cKApLi42LpfLxMfHl7+e3rwPUXPomz1H32wNfbPn6JutoW+2llNN9M11\n6noo89NJ3XPOOUfjx4/XI488ov3793t9o+3EiRP17bff6oILLiiPLcnyCH+LFi1SamqqSktL9ac/\n/Un/+c9/dN9993mV0/LlyzVq1CgtWbJEzZo18yqGJJWVlSksLExt27bVn/70p/LT68aLE+OlpaUq\nLi5Wo0aNlJycrO+++06PPfaYV3n16dNHiYmJ+t3vfqcdO3Zo6NCh+vvf/65LL73Ur3mVlZWpoKBA\nkZGR5YMCFBcXq6SkxHKs4OBg7dq1S507d9b27dt15ZVXKi0tTYGB1qcFNsbo6NGjatOmjQoLC9W4\ncWPl5ub69XUMCwvTrFmz9OKLLyolJUWlpaWWY5x06623ql+/foqNjZXD4VBubq7S0tKUnJxsOZY5\nZdLxRx55RA899JAWL17s1WU+AQEBuuKKK/TGG29o/fr1eumll/SXv/xF4eHhevPNNy3FKi0tVZMm\nTcrjnszHmxEfT31f33///dV+X9uVV0lJya/uhwsJCbG870tLS1VYWKhjx44pPz9f+fn5atSokVdz\nvaHm0Dd7jr7ZGvpmz9E30zf/Up3rm20tcX3s3//+t63x8vPzTf/+/c33339vS7wPPvjA3HfffWbQ\noEHVirN582azbdu2asVYtmyZSUhIMKWlpeWP3XfffWb+/PmWY7399tvm+uuvL5/Xq6yszEyaNMm0\nb9/eq9z27dtn3n//fZORkWGMMeVx/ZnXBx98YHr16nXa/kpKSir/xtEKp9Nphg8fbhISEszFF19s\nOnfubAYMGODV/F4bN240CQkJZty4caZbt27m7rvvNtdee6159913Lcey+3U0xpht27aZhx56yOvn\nG2PMkSNHzLp168yaNWvM+vXrzZEjR7yK849//MMMGDDA5OTkGGNOfKs7cuRI07FjR8uxKvoG15tj\ndfHixSY+Pt4MGzbMjBs3zgwfPtyMHj3aPPvss5Zj2fm+tjOvlStXmoSEBDN16lQzd+5cM23aNHPT\nTTdZfv+sXr3adOvWzYwaNcrMnj3b9O7d2/Tr188sX77cck6oOfTNnqNvtoa+2Tv0zVWjb/ZcTfXN\ndeqeUrtvUpek9PR0lZSU6Le//a0tOf73v//V6tWr9ec//9mWeNVx8ib8kzIzM8vnwrKqqKjoV8Nk\n79mzx/K3qEVFRXrxxReVlpamwsJCRURE6KqrrtKgQYMUFBTkt7ykE99CnfqNaW5u7mn3U3iT29Gj\nR9W8eXOvhhg/KS8vT5999ln563nppZfq7LPP9jqn6u6v999/XzfeeKPy8/M1b948ffnll+rQoYPG\njBlT/u2elXxWrFihbdu2lY/w16VLFyUlJVkeiVKSvv32W5177rmnHUveDK6RlZWlFi1aWF5/RVwu\nV/nw/v/+97/VrFmz8vnHrLLzfW1nXllZWdq1a5fy8vIUHh6uyy+/vNr7cN++fXI4HDr33HOrFQe+\nRd9sDX2zNfTNnqFvto6+2Tu+6putX7PgR+PGjdMPP/yguXPnKi0tTVdddZWcTqceeeQRr2N26NCh\n2p3eyaHqs7KyNG/ePH344YcaO3assrKyLMcaPHiwvvrqq2rlczJOdnb2aY9Vp9N7/fXXtXLlSh07\ndkx33XWXhgwZ4tUlL1OmTFHLli01YcIExcXF6YorrlBhYaGmT59uOVZOTo7mzp2rhIQExcfH66ab\nbtL06dPVunVrr2LNmjXrtFhPPvnkr/ahp7Fmzpypl156STk5OUpISFDv3r21c+dOy7FO7vulS5dq\nxYoVWrZsmVatWqXCwkKvYq1YsULvvvuuDh06pOTkZI0YMcJyB7N8+XJJ0uOPP65mzZppypQpOuec\ncywPOiFJEyZMUFFRkcaOHasnnnhCDz74oMrKyvTQQw9ZjlVUVKT169fr3nvv1bBhw3T33Xdr8eLF\nXo22+csPbG/yOWnp0qVyOBw6evSoxo0bp1mzZmnZsmVefz7Y9b62M6+ioiK9++67WrlypZYvX66V\nK1fqrbfesnycHjhwQH/605/05z//WU6nUxdffLHOPfdcr+bZQ82hb7YWh77ZWiz6Zs/QN1tD3+y5\nGuubbT3v6mN23qRujDE//vijeeyxx0zfvn1NXFycSUhIMNOmTTNZWVmW4pwc5OGBBx4wa9asMQUF\nBWbdunXmrrvuspxT7969zaBBg8wzzzzzq5uT/RHHGGPuvfde89RTT5lHH33U9OrVy2zcuNHs3r3b\nq5vUhw0bdtrvd9xxhzHGmCFDhliONXr0aPPuu+8al8tlysrKjMvlMu+8844ZMWKEX2PdcccdZtWq\nVWb+/Pmma9euJiMjw3z33Xe/2nZPjB071ixcuNB8+eWX5ptvvjFffvmlWbhwobnnnnssx3rwwQfN\nvHnzzMSJE811111ntm3bZnbu3Gluu+02S3FOHu+/3J6Tj1tR0T7x5niwc1/FxcWZbt26lf+77LLL\nyn+2qjZ+Ptidl137PikpyWzevNls2LDB9OnTx+zevbv8cdRe9M01H8cY+mar6Js9R99sDX2zPerU\nmdJf3qQuyeub1CVp/Pjx+u1vf6sVK1Zow4YNWr58ubp06eL1Ny/Z2dm66aabFBoaqp49eyo/P99y\njJYtW+qVV16Rw+HQwIEDlZKSorVr12rv3r1+iSOduDRr7Nixmjx5ss466yzFxcV5dQnOSe+9955c\nLpfeeusthYWFaf/+/SoqKrIcJzc3V3369FF4eHj53El9+/b16sZrO2Pl5+erX79+uvfee3XRRRfp\nggsu0P/7f//Pq5v6f/jhB40ePVqXXHKJ2rRpo0suuUSjR49WTk6O5VhHjhzRfffdp0cffVSNGjVS\n165d1alTJ8s3zx84cEBLlixRcHCw9uzZI+nEPFre7KuQkBC99dZbys7OVnFxsX788Ue99dZbaty4\nseVYdu6rv/71r+rYsaNWrVqlLVu26Le//a22bNnyq3ngrKhNnw9252Xnvr/66qsVHx+vefPm6eGH\nH9ahQ4d8Micd7EPfXPNxJPpmq+ibPUffbA19sz3qVFH60EMP6cknn9T69euVnJysLl26aNasWV5d\nmiDZ92G3f/9+PfbYY3K73fq///s/lZWV6f333/cqJ2OMgoODdfvtt+vtt9/Wtddeqx07dig1NdUv\ncU5avny5nn/+eR09elTbtm3Trl27vPqDY/bs2frggw80ePBgbdmyRVOmTNGePXu8ugQgMjJS8+fP\n165du/T111/riy++0Pz589WyZUu/xmrWrJkWLFggY4xeeuklSdLq1au9unflTB3Dm2++6VXHEBwc\nrDVr1igwMFCrV6+WdGKCZ6sd3/PPP68mTZqobdu25RMyP/roo169hnPnzlV6erruvPNOJSQk6I47\n7lB6erqeeOIJy7Hs3FdXXnmlUlJSlJKSok8++aRaH7y18fPB7rzs+gMmODhY69evV2lpqS644AJN\nmTJFd911l1eXLaHm0DfXfJyT6Js9R9/sOfpma+ib7VGnBjrq1KmTJk+erFtuuUU5OTnVvkn9T3/6\nk2JiYtS9e3eFh4crLy9PmzZt0n//+18988wzHsc5duyY9uzZo/T0dEVHR+v3v/+9Jk+erD//+c86\n75LcY6EAACAASURBVLzzLOU0c+ZMTZw40eqm+CyOJB06dEhLlixR+/bt1bp1a/31r39Vs2bNNHny\nZEVHR1uKtWXLFq/uIziToqIiLV++XGlpacrNzZXD4VDnzp01ePBgy/di2BmroKBAr776qkaMGFH+\n2KJFizRgwABFRkZaipWTk6PnnntOn376qfLy8tSkSRN17txZY8aMsRwrKytLixYtOu24mD59upKT\nk3XBBRdYinUyt5P7qnnz5paff5LL5VJwcHD5Tf2SdPDgQcvvnVP31cmBMLzdVycVFxdrxowZSktL\n87pTqOjz4aGHHtL5559vKZad72s787LrOD106JCeeeYZjR8/vvyY+vjjjzVr1qzyP9ZQ+9A313wc\nib6Zvrni3Oibq0bfXPv65jpVlN5666267LLL9NVXX+n+++/XlVdeWa14dn3Y2flhbles2piTJHXs\n2FE33HCDJk+eXK253s5k165dys3N1VVXXVWrYn3xxRdyuVxexyoqKtLevXuVn5+viIgIXXzxxV5/\nO1hUVKR9+/aVx4qJibEca9euXZoxY4bKysrUpEmT8rnZpk6danlgktdee01///vfVVZWpltvvVV3\n3nmnJGn48OGW5iM8k2+//VaBgYGWO9Az+fTTT9W6dWtbYtmZ1969e3XJJZd4/fzS0lIFBQUpNzdX\nmZmZioqKUtOmTaudFxoW+uaaj2N3LPpm6+ibvUPfXLWG2jcHTZs2bZq/k/DU22+/rdTUVF144YV6\n8cUXtWDBAmVmZurAgQPq1KmT5XjBwcG64oor1KdPH/3xj3/U2WefrXPOOUe/+c1vLMVJSEhQRkaG\nfv/733s1VPaZYv3ud7+rViy74pyM9fXXX9uyfdu2bdMtt9yiRx55RDk5OYqKivJ6aPe1a9fqjjvu\n0NKlS2WM0bJly7Rv3z7t2bNH3bp1qzWxli5d6nWsjRs36i9/+YsOHDigV155Rd9++62WLFmidu3a\nWR6K+2SszMxMLVu2zOtYDz74oJ555hndcccd6t+/vwYPHqzu3btr0qRJGjRokKWcpk2bpjfeeEPD\nhg3TypUrlZmZqS5dumjVqlXq37+/pVi7du3S6NGjtXbtWhlj9Oijj+rDDz9UUFCQLrvssmrFevLJ\nJ22LVZ28tmzZom+++ab83/Tp09WmTRt98803lj+3/va3v+njjz9WSUmJ7r33XmVkZGjhwoVq1qyZ\nLr74Ykux0LDRN9d8nJOx6Ju9j0XfXDH6Zvpmv7B12CQf++UoT8ePHzfr1q0zixcv9irehg0bTFxc\nnLnpppvM/2fvzsOjKLO+j/86iSSBhC0ijMgrEmQE2UHnYVBkEwHxQZRVEhERHQR0lFGRXVxQcUFZ\nRB6VXRZZBAVGBURFWSQiiMgWQtiRQIAkJOks9/sHkwygCV2d6lQn+X6uy8uQVJ86Vd1dp09X1X1P\nmjTJ9OnTxzz66KNm8uTJlvNatWqV6dixo5k4cWKBJvy2K5Y/5mTMf0cVO3/+vJk1a5bp1q2buffe\ne83AgQMtx+ratas5e/asOXbsmPn73/9u0tPTjTHejfjor7GioqJyH3/69GkzdOhQk5SU5NUIeHbF\n6tq16x9+l52dbbp162Y5p4v3SUZGhunTp4/57LPPvBotsEePHubw4cNm06ZNpnHjxiYlJcW43W6v\n9ru/xurcubPp0qWLGTp0qBk6dKhp3rx57s9W3X///SY7O9v07t07d+LxlJQU06VLF8uxOnXqdMmI\niBf/50QcFC5qc9HOyRhqs1XUZmux/LGeUpsLP86VeDertUMu/3YmPDxcrVu39jrelClTtGLFCp08\neVI9evTQ999/r8DAQPXq1UuPP/64x3FcLpfat2+vO+64Q4sWLdLgwYOVkZGhqlWratKkSZZysiuW\nP+YkXbgZXJJCQ0MVHR2t6Ojo3MsTrMrKysqdENrlcuVe6mJ1cAB/jpWUlJT7+ODgYB08eFBhYWFe\njaZnV6w77rhDDz30kJo3b67w8HAlJydr/fr1atGiheWcGjVqpMGDB+uVV15ReHi43nnnHfXt21eH\nDx+2HCs7O1tVq1ZV1apVFRUVlXsjvzeXU/lrrHnz5mns2LFq3LixunXrpujoaI0bN85yHEkKCAhQ\nRkaGrr766tx7hoKCvCsJkyZN0tNPP625c+cW6IyNXXFQuKjN1OaL+Ws9pTZ7jtpsDbXZHkXqnlK7\nde3aVQsXLlRAQIDmzp2r3r17S7pwf8yCBQs8jhMdHZ07SXeOnIN5vXr1LOVkVyx/zEkq+HX2F/vw\nww81Z84cVa1aVZUrV1ZCQoJCQkJUt25dDR48uFjEmjZtmlauXKlbb71VW7Zs0QMPPKDExEQdOnRI\nY8eOdSzWzp07FRMTo5SUlNxBC7ydimDTpk1q1KiRSpUqJem/95M99NBDluK8/fbb2r59uz788MPc\n0Sdz7q+xepeCv8bK8dFHH+nAgQPat2+fPv74Y69iLFmyRAsWLNDNN9+sLVu26NZbb9XmzZvVtWtX\nPfjgg5bjLVu2TOXLl9cdd9zhVT52x0HRRW0u/FjUZmrz5ajN1lGbC8jW865FzJw5c0ynTp1MVlZW\n7u8GDRpkJk2aZCnOb7/9ZltOdsXyx5z+zCuvvFKgx587d85kZGSYjIwMs2bNGvPjjz8Wu1i7d+82\nK1euNPv27TPGmNzLOZyKtXLlSmOMMcnJyebVV181ffr0MePHjzfJyckFjvXQQw95HcsYY3bu3HnJ\nvzds2HDJ+7s4xMrxww8/mCFDhhQoxsGDB838+fPNe++9Z+bPn292795doHiAHajNhR/rctTmK6M2\ne85f6ym12b8UqXlK7da7d2/NmjXrkjm9nn76aQ0cONBSnMu/XfT2lL2dsfwxJ0nq2bNn7n89evTQ\n4sWLc//tjfDwcAUFBSkoKEibNm1S06ZNvc7NX2PVqlVLHTp0UGRkpMaNG6eKFSs6GmvevHmSLrwO\nypcvr5EjR6pKlSpezUl4caycqQy8jbVq1SrVrl1b58+f12uvvaa+fftq/fr1Sk1NLVaxpAuTwH/7\n7bdKSEjQG2+8oZSUFK9iVatWTZ06ddLZs2e1atUqLV++3KtYQ4YM0alTpyw/zldxULRRmws/FrXZ\nOmqzZ/y5nlKbCzfOlZToy3cPHTqUO3LdtGnT9Ouvv6pmzZr6xz/+ofDwcI/jXHzQNsYoNjZWNWvW\nlCTNnz/fUk52xfLHnKQLozQuXrxYw4cPV2hoqIYMGaK33npLkiwPw+2v21jcY+UMCR8VFaU5c+b8\n4fdW+CLW8OHDVa1aNd15553asGGDtm7dqjfffJNYecQaMWKEqlWrprZt23odq3Xr1ipXrpyioqJ0\n3333eT0tgl1xULRRmws/FrW56MeiNhevWCWyNhfuiVn/0qtXL7Nx40YzYsQIM2nSJLNz504zc+ZM\n079/f0txli9fbvr06WP27NljDh06ZLp3724OHz5sDh8+bDknu2L5Y045du7caR555BETGxvr1Uhu\nvsiLWJ67/fbbzfTp082DDz5ofv31V2OMMdu3b/dqxDo7Y+W8lnr37v2nvyeW72JFRUWZs2fPmhdf\nfNF06tTJTJ061ezcudMkJSU5EgdFG7W58GMZQ20u6rGozcS6XFGrzSX68t3AwED97W9/0+HDhzVw\n4EDVrl1bDz74oJKSkizFueeee/Tcc8/p9ddfl9vtVnBwcO6IXlbZFcsfc8pRu3ZtjR8/Xm+++aYS\nExMlyasR6/x1G4t7rKlTpyosLEw1atTQ7t27lZSUpBdffFHPPfec5ZzsjHXgwAHNmDFDgYGB2rlz\np6QLk6N789oiljUul0tly5bViBEjNHPmTIWHh2vKlCnq1auXI3FQtFGbCz+WRG0u6rGozcS6XJGr\nzba2uEXMgAEDzKpVq8z06dPN0qVLzZkzZ8yyZctM3759vYqXmJhoHn/8cdOpUydjjMmdd8rJWP6W\n05o1a0zLli1N27ZtzWeffWa2bdtmjPHuGyA78yKW5y5+Dj///PPc33vzHNoZ69dffzWffPKJGTNm\njFmyZIk5d+6c6datm/npp5+I5eNYTz311J/+Pi0tzZE4KNqozYUfi9pc9GNRm4l1uaJWm0t0U3rq\n1CkzdOhQ065dO3PzzTeb5s2bmyeeeMIcOXLEUhw7D+Z2xfLHnIwxplu3biYxMdGcPn3aREdHmyVL\nlhhj/jj5emHnRSzP2fkc+ur14E8FuaTFWrFihdex7IqDoo3aXPixqM1FPxa1mVj5xSoKtdm72ViL\niYoVKxZotLocU6dO1dKlS2WM0ZNPPqkuXbqofv36uZNROxHLH3OSpKuuukrly5eXdGGC9D59+ugv\nf/mLVzdN++s2FvdYdj6Hvnw9uN1udenSxZZ9RSxrsdLT072KZVccFG3U5sKPRW0u+rGozcS6Uix/\nr80luimNjo5WRkbGn/7Nyohn/ngg8MecpAuj+I0bN05PPvmkwsLCNGnSJPXr10/nzp1zNC9iec7O\n55DXA7F8lROKLmpz4cfiWFz0Y1GbieWrWIVWmwt+srXo+vnnn02nTp1MfHx87khn3ox49swzz5hX\nXnnFpKSkGGOMOXr0qOnQoYNp3ry55ZzsiuWPORljTEZGhlm8eLE5f/587u9OnjxpXnrpJUfzIpbn\n7HwOeT0Qy1c5oeiiNhd+LI7FRT8WtZlYvopVWLW5RDelxhjzf//3f+bLL78sUAx/PBD4Y05289dt\nLAmx/JG/7itiOZMTijZqc+HGspO/bmNJiOWP/HVfEcuZnPLjMoabdQAAAAAAzijR85QCAAAAAJxF\nUwoAAAAAcAxNKQAAAADAMSV6ShjAH6Wmpuqdd97RunXrFBISovDwcA0aNEh/+9vfNGnSJEnSoEGD\nNHToUG3atEnly5dXZmamrrrqKj3yyCPq2LGjw1sAAEDxQm0GfIumFPAzAwcOVI0aNbRixQoFBgbq\nt99+02OPPaa33nrrkuVcLpeefPJJ3XvvvZKkQ4cOqXfv3qpQoYKaNWvmROoAABRL1GbAt7h8F/Aj\nMTExOnDggJ5//nkFBgZKkmrXrq0BAwZoypQp+T62WrVqevDBBzVv3rzCSBUAgBKB2gz4Hk0p4Ed+\n+eUX1a5dO7fo5bjlllu0bdu2Kz7+xhtv1P79+32VHgAAJQ61GfA9mlLAjxhj5HK5/vD7tLQ0ZWdn\nX/HxLpdLwcHBvkgNAIASidoM+B5NKeBH6tWrp19//VVZWVmSpNOnT0uStm3bprp1617x8bt371bN\nmjV9miMAACUJtRnwPZpSwI80bdpUNWrU0KuvvqrMzEwtXbpUPXv21HvvvaeBAwf+YXljTO7PBw4c\n0Lx58/TAAw8UZsoAABRr1GbA91zm4ncOAMelp6frjTfe0LfffqtSpUqpbNmyMsaoUaNGCgoK0lVX\nXaVBgwbp+eef16ZNm1SuXDlJUlBQkPr376927do5vAUAABQv1GbAt2hKgSLim2++0R133OF0GgAA\n4D+ozYA9aEoBAAAAAI7hnlIAAAAAgGNoSgEAAAAAjqEpBQAAAAA4hqYUAAAAAOAYmlIAAAAAgGNo\nSgEAAAAAjqEpBQAAAAA4hqYUKIDs7GxNnz5d999/v7p06aJOnTrpjTfekNvtdjo1SdLkyZO1du1a\nrx+/efNm3XPPPTZmBACAf2jdurV+/fXXPP+enJysPn36FEouhw8f1hNPPFEo6wL8EU0pUACjR4/W\ntm3bNHPmTC1dulSLFi1SXFycRo4c6XRqkqSNGzcqMzPT6TQAAChyzpw5o19++aVQ1nXkyBHFxcUV\nyroAfxTkdAJAUXXkyBF9/vnn+v7771W6dGlJUkhIiMaOHauffvpJycnJeuGFF7Rr1y65XC7dfvvt\nGjJkiAICAlS/fn09+uijWr9+vRISEtSvXz/16tVLkvT+++/r008/VVBQkKpXr65x48YpLCxMixYt\n0scffyxJKl++vEaOHKkbbrhBzz//vIKDg7Vr1y6dPn1azZs31/Dhw7VgwQLt2LFDr7/+ugICArRm\nzRrVqlVLffv2lSQ9//zzuf/++uuv9f777yszM1OnT59W586d9eSTTzqzYwEAKAQul0vGmD/U5Ece\neUQ9e/bUsGHDlJaWpi5dumjJkiXav3+/XnnlFZ05c0bZ2dmKjo7Wfffdp82bN+vll19WaGioUlNT\ntWjRIn333XeaOnWqMjMzFRISomeffVYNGzbU/v37NXz4cLndbhlj1K1bN/Xo0UMjR47U77//rkce\neUQffPCB07sGKHwGgFe++OIL061btzz//txzz5mXX37ZGGOM2+02Dz/8sJk2bZoxxpi//vWvZu7c\nucYYY3bs2GHq1atn0tPTzerVq0379u1NUlKSMcaYV1991UydOtVs3rzZ9O7d26SlpRljjFm/fr3p\n0KGDMcaYoUOHmi5dupjU1FTjdrtNVFSUmTNnjjHGmKioKPPll1/mLvfRRx/l5nfxvx988EETHx9v\njDHmxIkTpk6dOiYxMdFs2rTJdOrUyZ4dBgCAH2ndurX55Zdf8qzJhw8fNo0aNTLGGJOZmWnuvvtu\ns3PnTmOMMUlJSaZjx45m27ZtZtOmTaZOnTrm2LFjxhhjDhw4YDp16mTOnDljjDFm7969pnnz5iY1\nNdUMGzYs97PAyZMnzdNPP22MMdRblHicKQW8FBAQoOzs7Dz//u2332r+/PmSpKuuukq9evXSzJkz\n1b9/f0lSmzZtJEk333yzMjIylJqaqg0bNqh9+/YKCwuTJD333HOSpPHjx+vgwYPq2bOnjDGSpKSk\nJJ07d06SdN999ykkJESS1LlzZ61Zs0a9e/eWpNzl8/Pee+9p3bp1Wr58ufbv3y9JSk1NtbZDAAAo\nov6sJl/swIEDOnjwoIYNG5ZbV9PT07Vz507VqFFDVapUUZUqVSRJ33//vRISEvTQQw/lLhsUFKT4\n+Hjdeeedeu6557R9+3Y1a9ZMw4cPL8StBPwXTSngpfr16ys2Nlbnz5/PvXxXkk6cOKGRI0cqOztb\nLpcr9/fZ2dmX3N8ZHBx8STxjjIKCgi55TE7jmZ2drc6dO2vIkCGXrKds2bKSpMDAwEviXPzvy9eR\nI2cwptTUVN17771q166dmjZtqq5du2r16tUeNbMAABR1LpfrkppsjPlDDczKylLZsmW1dOnS3N+d\nOnVK4eHh+vnnny/5HJCdna1mzZrprbfeyv3d8ePHVblyZf31r3/Vl19+qe+//14bNmzQ5MmTtWTJ\nEh9uHVA0MNAR4KVrrrlG99xzj4YNG6bk5GRJyr2PtGLFirr99ts1e/ZsSRcawAULFqh58+Z/Giun\n+DVr1kxfffWVUlJSJEkTJ07UjBkzdPvtt2vFihU6efKkJGnu3Ll66KGHch+/cuVKud1upaena+nS\npWrdurWkC9/M5jTCFStW1I4dOyRdaGh//PFHSVJ8fLzOnz+vf/7zn2rZsqU2btyojIwMZWVl2bm7\nAADwKzm1N68vYYOCgnKviLrhhhsUHBys5cuXS5KOHTumTp06/enovc2aNdP333+fe+XRN998o86d\nOystLU1DhgzRihUr1LFjR40ePVphYWE6dOiQAgMDGZgQJRpnSoECGDNmjCZPnqxevXopKChIbrdb\nbdu21eDBg5WcnKwXX3xR99xzjzIyMnT77bfrH//4hyRdcjb04n/fcccd2r9/v3r27CmXy6Ubb7xR\nL774okqXLq1HHnlEDz/8sAICAhQWFqZJkyblPj40NFS9e/fWuXPn1L59e913332SLgx3/+abb8rt\nduvBBx/UkCFD1KFDB1WtWlXNmjWTJN10002644471L59ewUHB6tWrVqqWbOmDh48qKuuuqowdiMA\nAIUup/bmVZMrVaqkevXqqVOnTpo7d66mTJmil156SR988IGysrL01FNPqVGjRtq8efMlj4+MjNTY\nsWP19NNPS7pwNdN7772n0NBQPf744xoxYoQWLlyogICA3KuUzp49q1KlSql79+5auHBhIWw94F9c\nhmv0gCLt4lF0AQAAgKLGp2dKp02bprVr1yojI0MPPPCA7r//fl+uDgAAXAG1GQDgb3zWlG7evFlb\nt27V/Pnzdf78eX300Ue+WhVQoo0bN87pFAAUEdRmAIA/8tnlu2+99ZZcLpf27t2rlJQUPfvss7r5\n5pt9sSoAAOABajMAwB/57ExpYmKijh49qvfff1+HDh3SgAED9O9//9tXqwMAAFdAbQYA+COfNaXl\ny5dXZGSkgoKCcofRPn36tCpWrPiny8fExPgqFQBACdWkSROnU/Ar1GYAgNP+tDYbH/n666/Nww8/\nbIwx5vjx46Zdu3YmOzs7z+W3bNni1Xq8fRyx/CMOsYjlqzjEIpadORQX1ObiHcsfcyJW8YjljzkR\nq2jGyutxPjtT2rJlS23ZskVdu3aVMUajR4/+wzxQAACg8FCbAQD+yKdTwvzrX//yZXgAAGARtRkA\n4G8CnE4AAAAAAFBy0ZQCAAAAABxDUwoAAAAAcAxNKQAAAADAMTSlAAAAAADH0JQCAAAAABxDUwoA\nAAAAcAxNKQAAAADAMTSlAAAAAADH0JQCAAAAABxDUwoAAAAAcAxNKQAAAADAMTSlAAAAAADH0JQC\nAAAAABxDUwoAAAAAcEyQ0wmg8EyYMEFut1tNmjRxOhWfKO7bBwAAABRHnCkFAAAAADiGphQAAAAA\n4Bgu3wUAAAAAP1OSbk3jTCkAAAAAwDE0pQAAAAAAx9CUAgAAAAAcQ1MKAAAAAHAMTSkAAAAAwDE0\npQAAAAAAxzAlDBxVkoa6BgAAAPBHnCkFAAAAADiGphQAAAAA4BifXr7bpUsXhYeHS5Kuu+46vfLK\nK75cHQAAuAJqMwDA3/isKXW73XK5XJo1a5avVgEAACygNgMA/JHPLt/dtWuXzp8/r379+umhhx7S\ntm3bfLUqAADgAWozAMAf+exMaUhIiPr166du3brpwIED6t+/v7744gsFBHAbKwAATqA2AwD8kc+a\n0urVq+v666/P/bl8+fI6efKkKleu7KtVAgCAfFCbAQD+yGWMMb4IPG/ePO3Zs0ejR4/WiRMn1Ldv\nX33++ed5fhsbExPjizRwkTVr1kiS2rRp43Am/2VnTv64fQCcxRzIl6I2A0DRUVw/2/5pbTY+4na7\nzZAhQ0yvXr1M7969zdatW/NdfsuWLV6tx9vHlcRYb7/9tnnttddsieWPOdkZy5ji/xwa45/b6I85\nEatoxrIzh+KC2ly8Y/ljTsQqHrH8MaeSEKs4fu7L63E+u3z3qquu0htvvOGr8AAAwCJqMwDAHzGy\nAQAAAADAMT47U1qSTZgwQW63m3uZAPgUxxoAAFAccKYUAAAAAOAYzpQCwBVwRhIAAMB3OFMKAAAA\nAHAMTSkAAAAAwDE0pQAAAAAAx9CUAgAAAAAcQ1MKAAAAAHAMTSkAAAAAwDFMCQOgWGIaFwAAgKKB\nphQAYCs7vxDgywUAAIo/Lt8FAAAAADiGphQAAAAA4Bgu3y0GsrKyFBsbe8XlMjMzlZmZqT179uS7\nXGRkpAIDA+1KDwAAAADyRFNaDMTGxqrr2HcUUiEi3+VaVbhwYjxq4pw8l0lLPKVFo55UrVq1bM0R\nAFAycB8wAMAqmtJiIqRChEpHXJPvMi4lSpJKR1xdGCkBAAAAwBVxTykAAAAAwDE0pQAAAAAAx9CU\nAgAAAAAcwz2lKBI8GWHY09GFJUYYBgAAAPwFTSmKBE9GGPZkdGGJEYYBAAAAf0JTiiLjSiMMM7ow\nAAAAUPTQlMJn7LzkNi4uzs7UAAAAAPgJmlL4TGxsrNZ36aXrQkLzXCaz7W0KkHSg18P5xoo5myh1\nuN/mDAEAAAA4jaYUPnVdSKhuCC2T59+3u1ySlO8yknQ4LdXWvAAAAAD4B5pSAAAAACjGJkyYILfb\nrSZNmjidyp9inlIAAAAAgGNoSgEAAAAAjvFpU3rq1Cm1bNmSkVMBAPAT1GYAgL/xWVOamZmp0aNH\nKyQkxFerAAAAFlCbAQD+yGdN6WuvvaZevXrpmmuu8dUqAACABdRmAIA/8snou0uWLFFERISaN2+u\nqVOn+mIVAADAAmozAPiHrKwsxcbGXnG5zMxMZWZmas+ePfkuFxkZqcDAQLvSc4TLGGPsDhoVFSXX\nf+af3LVrl2644Qa99957ioiIyPMxMTExdqfhmDVr1kiS2rRpUyjri4+P16tf/6zSEfl/8/0/SpQk\nbVSFPJc5f+p3DW3VUNdff70teYW9/Fa+c5Auu62xJKnz+p/yjfVdYoKmtr473230ZPske7exsBX2\na6sos3Nf+et+Lwl5FTSWvw5974TCqs3++roEAH8RHx+vMUvWKKRC3sdfSWpV4cJFrV8nZue5TFri\nKY25r80VP9f607H5z2qzT86UzpkzJ/fn6OhojR07Nt+il8ObDw8xMTG2feiwK9Z3331n6zxAV8or\nPDxc+vpnW9YlSXXr1lWtWrUKlFNOXgdsy8pedm2jp4rqa8uJWP64r/x1v5eEvAoSqzh92WmHwqrN\n/vq6LAmx/DEnYhWPWP6YU1GOFR4erhAPTii5/nPCpXTE1fku58nnWn85NudVm30+JUzOt7IAAMA/\nUJsBAP7EJ2dKLzZr1ixfrwKAwyZMmGDrt28AfIvaDADwJz5vSgEAAJzGl2cA4L9oSmEZhR3wHu8f\nAHAex2LAv9CUWsDwzQAKiyfHG441AACgOKAptSA2NlY7FixS9SpV8l0uOy1NQZKSv1mf5zIHjh+X\nenS94khZAEqm2NhYdR37Tr7DxecMFR81cU6ey6QlntKiUU9yrAEAAH6LptSi6lWqqGbV6/Jd5puE\n3yXpissBQH5CKkTkO1y8p0PFA4AVXNoKoLD5fEoYAAAAAADywplSAAAACziTCAD2oikFUKLZOaCQ\nxKBCAAAAVtGUAijRYmNjNXrGQpWvVDnPZSqdT5Mkvb3im3xjnTl5Qi881J1BhQAAACygKQVQYiVn\nygAAIABJREFU4pWvVFkR1+Y9MFnAvgRJyncZAAAAeIeBjgAAAAAAjuFMqZ9jMAUAAAAAxRlnSgEA\nAAAAjuFMKeBjnO0GUFwwWjUA+BeTna24uLgrLufpsdmp4zJNaQmyURWcTgEAUITFxsbqt39/qerX\nXpvnMtlut4IkpW7fkW+sA0ePSu3bMVo1cBE7v8jmS/GSIf1sot5d9a3Cr96V73KRWeclSaMWrspz\nmaSE3/X2430cOS4X6aaUNxsAAIWr+rXX6sb/d32ef1+7f58k5bsMAMA+4Vdfo/KV8/6yUJICTqRI\n0hWXcwr3lAIAAAAAHFOkz5QC8B5XGuBivB4AAIBTOFMKAAAAAHAMZ0oB5MmTkTYl/x/RDQAAAP6L\nphRAnmJjY9V17DsKqRCR73KtKly46CJq4pw8l0lLPKVFo55kpE0AAABcgqYUQL5CKkSodMQ1+S7j\nUqIkqXTE1YWREgAAAIoRmlI4qvP6n5xOwS9wmSwAAABKKppSwA9wmSwAAABKKppSwE9wmSwAoLhh\nuikAnmBKGAAAAACAYzhTimJjoyo4nQIAAAAAi2hKAQAAAPgcl3MjLz5rSrOzszVixAjFxcUpKChI\nr7zyiqpVq+ar1QEAgCugNgMA/JHP7ildu3atXC6X5s2bp8GDB2vcuHG+WhUAAPAAtRkA4I98dqa0\nbdu2at26tSTpyJEjuvpqRgsFAMBJ1GYAgD/y6T2lAQEBGjp0qFavXq13333Xl6sCUIJkZWUpNjY2\n32UyMzOVmZmpPXv25LtcXFycnakBfo/aDAC+w32z3vH5QEevvvqqTp06pW7dumnlypUKCQnJc9mY\nmBhLsd1ut1ePy09+seLj41XdtjVJO3bsUFJSUr7LeLKN8fHxNmZ15bw83e/x8fEKszUz+3iy7yV7\nXlv++Bz6a15r1qzxKE58fLzGLFmjkAoReS7TqsKFuxOiJs7JN9bZ+Fi1btXSo/V6ws73T2HlZCUv\nT/hrLPyXt7U5Pj5ekTbm4W/HYidi5bArlr9tn52xPK0RnvDX59Af972/7nc788pRVD/32cnT47Jk\n7/vHZ03psmXLdOLECT366KMKDg5WQECAAgLyv4XV6jcK3333na3fRMTExOQbKzw8XMnfrLdlXZJU\nt25d1apVK99lPNnG8PBw6eufCy0vT/d7eHi4DtiWlb082fdXej14yh+fQ3/Ny8prK+Trn1U64po8\nl3EpUZJUOiL/yxPTEk/l+3er7NxGu/a9Xa8HT/lLLBrZPypobQ4PD1fq9h225eNvx2InYkn2bWNx\n31f+Gksq3vveH3OyO5ZUtD/32cmT47Lk/f7Kqzb7rClt166dnn/+eUVFRSkzM1PDhw9XqVKlfLU6\nAABwBdRmAIA/8llTGhoaqgkTJvgqPAAAsIjaDADwRz6/pxQoirhJHQAAACgcPpunFAAAAACAK6Ep\nBQAAAAA4hst3AQBAkeXJvMWS53MXR0ZGKjAw0K70AAAeoCkFAABFVmxsrHYsWKTqVarku1x2WpqC\npHyndjtw/LjUo6tH0yEAQFFysvKNTqeQL5pSAAW2URWcTgFACVa9ShXVrHpdvst8k/C7JF1xOQBA\n4eOeUgAAAACAYzhT6gP9GjR2OgUAJQBnqIGijynIij6eQ6DgaEoBAABgmSeDTHk6wJTEIFNASUZT\nCgAAAMtiY2PVdew7CqkQkecyrSpcuFMsauKcfGOlJZ7SolFPMsgUUELRlP4Hl14AAFCyZWVnKy4u\n7orLMb3Mf4VUiFDpiGvy/LtLiZKk0hFXF1ZKAIogmlIAAABJh0/+rsR335MrJDTf5TLb3qYASQd6\nPZx3rLRUaek8zvwB8FpJGjuCphQAAOA/rgsJ1Q2hZfJdZrvLJUlXXA4A4BmmhAEAAAAAOIYzpbiE\n8eB+Gk/vpYmLi5PLzuQAh2TWbOh0Cn7Bk5E2Jc+OEVlZWZJ0xfvtuHcPsJedI+Z6cv+tE+zcRruO\nLRw/gfzRlOIS6WcT9czs5baMpHc2PlYTbc0OgJNiY2P11JSZCr8670FNJCky67wkadTCVXkuc2zv\nb0rMCsz3WCN5drxh1E7/8ljLNrbFYhBC+8XGxmp9l166Lp/7Zj25Z1aSYs4mSh3utznDgouNjdWW\nEWNVrXze9+NlVa6gQEkn3sj7k8qhM4nSS6NsObbExsZq9IyFKl+pcr7LVTqfJkl6e8U3eS5zcNev\nOpSSwfETxQpNKf7ArpH00hJPSUfibc0NgLPCr75G5Stfm+8yASdSJCnf5ZISfldqVmC+xxqJkTsB\nX7jSfbOe3jN7OC3V1rzsVK18BUVWzLtp2/yfG9jyW8Zu5StVVsS11+W7TMC+BEnKd7kzv59QSCk3\nx08UK9xTCgAAAABwDE0pAAAAAMAxNKUAAAAAAMf47T2ldo6cJjGyGHzDrtepv45gCGuybR69GgAA\noCTw26Y0NjZWv/37S1W/Nu+BMrLdbgVJSt2+I99YB44eldq3Y2Qx2M6uEf52HIqXmHakyDuXcFIv\nLt6jMvkMKtE42C1JGjx9cb6xEmL3KrBy/gNiAEAORioGUJT5bVMqSdWvvVY3/r/r8/z72v37JCnf\nZQBfs2OEv0NnEu1OCw4pE3G1witVyfPvAclHJCnfZSQp5XSC3LZmBgAA4J+4pxQAAAAA4Bi/PlMK\nAAAAAL7k6eXvjCXiOzSlAAAAAHAFsbGx6jr2HYVUyPuWrFYVLlyIGjVxTp7LnI2PVbnrI23Pryij\nKQUAAAAAD4RUiFDpiGvy/LtLF8YJKZ3PoIdpiadsz6uo455SAAAAAIBjfHamNDMzU8OGDdORI0eU\nkZGhf/zjH2rdurWvVgcAAK6A2gwA8Ec+a0qXL1+uChUq6PXXX9eZM2fUpUsXCh8AAA6iNgMA/JHP\nmtIOHTqoffv2kiRjjIKCuH0VAAAnUZtR2DaqgtMpACgCfFaNQkNDJUnJycl68skn9dRTT/lqVQAA\nwAPUZgCAP/LpV6THjh3ToEGDFBUVpY4dO/pyVQD+w2RnezT/VWHPo+VJXp7kZHdexZ2/vh7gHGoz\n/JHdNaK0nckVY3bu96ysLElSYGCgX8WSpMjIyHxj4YJsDz8zSFJ8fLzCw8PzXcbKfvdZU5qQkKB+\n/fpp1KhR+p//+R+PHhMTE5P7c3x8vOycvWfHjh1KSkrK8+9ut/sPOVwuPj5e1QsxJyt5wRo7Xg/S\nhX1fydbMCi79bKJmfPOjyu88mO9ylc6nSZLeXvFNnssc3PWrVKqsbXk9M3t5gef2kpjfywpP9rvk\n+bxqjW691db87OLJ8RTU5sJmV533hJW6FVagNfmG3TXigyoVbcmruH9Ws3u/B5ctb1usxnVrq3yl\nynku48nnGEk6c/KEujWto+uvvz7PZay8f4qzlNMJHn1myPX1z3n+KS3xlMbc1ybf/X4xnzWl77//\nvs6dO6cpU6Zo8uTJcrlc+uCDD1SqVKk8H9OkSZPcn8PDw5W6fYdt+dStW1e1atXK8+/fffed3G73\nJTlcLjw8XMnfrC+0nKzkld+LAn9kx+tBurDvT/z7a7vTK7DylSor4trr8l0mYF+CJOW73JnfT+hk\nstu2vOyY20tifi+rrrTfpaI/r9qfvacL+iG/OKI2Fy676rwnrNStAwVak+/4Y42w87PaV/H5N09O\nsXO/2xnrSp9lPPkck8POz33F/TO3J58ZPGWlNvusKR0+fLiGDx/uq/AAAMAiajMAwB8FOJ0AAAAA\nAKDkoikFAAAAADiGphQAAAAA4JgSMWt2VlaWLcNdx8XF2TbSahbTNDiGYecBAAAA/1EimtLDJ05o\nxGfrCjxE9dn4WM27p409OZ38XYnvvidXSGi+y2W2vU0Bkg70ejjPZWLOJkod7rclr5LAX4edBwAA\nAEqiEtGUSvYMd233dAjXhYTqhtAy+S6z3eWSpHyXO5yWamteJYE/DjsPACg+soyx7Yooydok9LAH\nV7UBhafENKUAAACF5Vh6miZ4MAm9J1fmpCWe0qJRT15xvkzY6+i5s3rVpufwbHysWrdqaWd6QLFC\nUwoAAIq9fg0aF/o6PZmE3tMrc+AMu55DrqwC8kdTCgAAAKBYyrZ5gEv4Bk0pAAAAgGLpXMJJvbh4\nj8rkcya7cbBbkjR4+uJ8YyXE7lVg5etszQ8X0JQCAIBC54/TtQEonspEXK3wSlXy/HtA8hFJyncZ\nSUo5nSC3rZkhB00pAAAodP44XRsAwBk0pQAAwBH+OF0bAKDw0ZQCRchGVXA6BQAAAMBWNKUAAAB+\nzNg8eqjLzuQAwAY0pQAAAH4s/Wyinpm9vMD330oX7sGdaGt2sFNmzYa2xeLqKhQlNKUAAAAWdF7/\nU6Gv0477b6X/3IN7JN7W3ACgoAKcTgAAAAAAUHLRlAIAAAAAHENTCgAAAABwDPeUAiiWGOABAAAU\nNj5/eIczpQAAAAAAx9CUAgAAAAAcQ1MKAAAAAHAMTSkAAAAAwDEMdAQAAIBcndf/5HQKAEoYzpQC\nAAAAABxTpM+UPtayjdMpAAAAAAAKgDOlAAAAAADH+LQp3bZtm6Kjo325CjhgoyowMbAFvdIv/AcA\n/oDaDFCbAX/js8t3P/jgAy1btkxlypTx1SoAAIAF1GYA+KPdYVWdTqHE89mZ0uuvv16TJ0/2VXgA\nAGARtRkA4I981pTeeeedCgwM9FV4AABgEbUZAOCP/Gr03ZiYmNyf4+PjFelgLgAKH/cqw1s7duxQ\nUlKS02kUS9Rm+AtqhDP8db9n1mzodAq4Aiu12edNqTHG42WbNGmS+3N4eLhSt+/wRUp/yl/fcACA\nK6tbt65q1ap1ye8ubqZwqaJSmwEARZeV2uzzKWFcLpevVwEAACygNgMA/IlPm9KqVatq/vz5vlwF\nAACwgNoMAPA3Pj9TCgAAAABAXmhKAQAAAACO8avRdwEAAAAUTwwsirzQlAJAIdodVtXpFAAAAPwK\nTSkAAIBDOHNU9PEcAgXHPaUAAAAAAMfQlAIAAAAAHMPlu8Cf4FIcAHAex2IAKBloSgEAAIo4GngA\nRRmX7wIAAAAAHENTCgAAAABwDJfvAiVUZs2GTqcAP8KlfwAAwCmcKQUAAAAAOIamFAAAAADgGJpS\nAAAAAIBjaEoBAAAAAI6hKQUAAAAAOIamFAAAAADgGJpSAAAAAIBjmKcUAGCrk5VvtC0W86cCAFD8\ncaYUAAAAAOAYmlIAAAAAgGNoSgEAAAAAjqEpBQAAAAA4hqYUAAAAAOAYmlIAAAAAgGNoSgEAAAAA\njqEpBQAAAAA4JshXgY0xGjNmjHbv3q1SpUrp5ZdfVrVq1Xy1OgAAcAXUZgCAP/LZmdLVq1fL7XZr\n/vz5GjJkiMaNG+erVQEAAA9QmwEA/shnTWlMTIxuv/12SVKDBg20Y8cOX60KAAB4gNoMAPBHPrt8\nNzk5WeHh4f9dUVCQsrOzFRDgeR984OhRW3I5/PvvSks8VeA46efO6MDx4zZkJB05maDSaalXXC7T\nGElSXGpKnsscT0+zZfukC9tol/RzZ3TYg230hD9v4yG3q8BxjiWdU1op+7bvzMkTtsQ6dzpBaSkZ\ntsSye7/bGcvO/ZViAm2JlZqYqIxSaQWOY/e+Skr43ZZYyYmnlJZlz76y69hQElCb8+dpbfaEP9ct\narNnqM3OxqI2ex6rONRmlzH/6Xps9uqrr6phw4Zq3769JKlly5Zat25dnsvHxMT4Ig0AQAnWpEkT\np1PwK9RmAIDT/qw2++xMaePGjfX111+rffv2+vnnn1WrVi3LyQEAAPtQmwEA/shnZ0ovHuFPksaN\nG6cbbrjBF6sCAAAeoDYDAPyRz5pSAAAAAACuxGej7wIAAAAAcCU0pQAAAAAAx9CUAgAAAAAcQ1MK\nAAAAAHAMTSkAAAAAwDE0pbDEnwdrPnXqlC1x7NzG06dPKyYmRmfOnLEtph38+XlEyZWcnOx0CkCR\n5M/HdGqz5/z5eUTJVVi1mab0It4eOG+77Tb98MMPtuRw+vRpjRgxQh06dFDr1q31wAMP6I033lBK\nSoqlOImJiXr55ZfVqVMntWzZUvfcc49eeOEFr7bx4MGD6tevn1q1aqW6deuqe/fuGjJkiE6ePGk5\nVnp6ut577z31799fUVFRGjx4sObNm6esrCzLseLi4i75b8CAAbk/W2XnNj766KOSpHXr1qlXr16a\nPXu2oqKitHbtWsux3n77bUkXtrVr165q0aKFevbs6eg22vkc9uzZU/v27bP8uD9j576y8z2d816c\nNm2adu3apTvvvFPt27fX1q1bLcdyu92X/BcdHa2MjAy53W7LsezcX5cbMmSIV49r3ry5PvnkkwKv\nH8ULtfnPUZutoTZ7jtpsDbXZHkVqntIFCxbk+bcePXpYjnf5E/zcc8/ptddekyRLk4nfe++9qlKl\nisqVK6dBgwapWrVqlnPJMXDgQEVFRalx48Zas2aNjh8/ruuuu04rV67UhAkTPI7z2GOPqXPnzmrR\nooXKlCmjlJQUffPNN/rkk080Y8YMSzn169dPI0aM0A033KCff/5Z69atU9u2bfXuu+9q2rRplmI9\n++yzuvXWW9WoUSOtXbtWAQEBCggIUFxcnMaOHWspVsuWLRUSEqJrrrlGxhjt2rVLN910k1wul2bN\nmmUplp3b+OCDD2rWrFnq3bu3Jk6cqIoVKyolJUWPPPKI5s2b51Wsxx57TI8++qiaNGmiXbt26bXX\nXtP06dMtxbJrG+18Djt06KCyZcuqefPmevjhhxUWFmbp8Rezc1/Z+Z7u37+/OnbsqKNHj2ru3Lma\nM2eOQkND9cwzz2jOnDmWYjVt2lTBwcEKCQmRMUYJCQm6+uqr5XK5tGbNGkux7NxfLVu2VGZmZu6/\nz5w5o/Lly0uS1q9f73GcHj166Oabb9a+ffs0aNAg3XrrrZbygDOozdTmi1Gbqc0XozZTmz1VpM6U\n7t+/Xx9++KFOnjz5h/+80bdvXw0YMECjR4/WqFGjFBcXp1GjRmn06NGW4pQtW1ZTp05VmzZt9NRT\nT6lfv36aMWOG5ReidOEF06xZMwUHB6tjx45av3692rVrp+PHj1uKk5ycrI4dOyosLEwul0thYWG6\n++67vfrWJjk5OfeDQMOGDfXTTz+pbt26OnfunOVYR48eVdeuXRUZGan+/ftr48aN6tu3r1ffyC1e\nvFg1a9bUY489ptmzZ+umm27S7NmzLRc9yd5tzDkAhIeH5775y5Qpo+zsbMuxcqSmpqpJkyaSpJtu\nuumSg4yn7NpGO5/DSpUqae7cuQoPD1fXrl01atQorV69Wrt27bIcK4cd+8rO9/T58+fVpUsXDRw4\nUDfeeKNq1Kihv/zlL3K5XJZjLViwQHXr1tWUKVO0du1aNWjQQGvXrvUqrxx27K/x48erfv36WrJk\nidavX69GjRpp/fr1loqeJAUHB2vUqFF65plnNHv2bHXq1Ekvv/yyV+9pFB5qs+eozdZQmz1HbbaG\n2uy5wqrNQbZG87Hnn39e+/fvV4sWLVS/fv0Cx1u8eLFGjx6tXr16qXnz5oqOjtbs2bMtx8k52dyu\nXTu1a9dOsbGx+uGHH/TDDz+oTZs2lmKVKVNG06ZNU4sWLbRmzRpVrlxZmzdvtpxTRESEJk2apBYt\nWigsLCz329hKlSpZjnXddddp1KhRatGihdatW6fatWvryy+/VGhoqOVYkrRy5UrdfvvtWrNmjUJD\nQ7Vnzx6lp6dbjhMREaEJEybotdde0y+//OJVLjns3MZy5crp7rvv1rlz5zRr1iz16NFD//znP9Ww\nYUPLsQ4cOKABAwYoOTlZX3zxhVq3bq2ZM2eqdOnSlmPZuY12PYfGGAUFBalv376KiorSDz/8oA0b\nNmjRokWaOnWqpVh27is739PlypXTlClTNGDAAM2cOVOStGzZMgUHB1vOKzIyUm+++aZGjRqlli1b\nelU8c9i5v2655RZVq1ZNo0aN0sMPP+x1Xjn7vV69epo4caKSkpL0448/2nLZEnyH2uw5arM11GZr\nqM2eozZ7rtBqsyliTp06ZQ4dOmRbvIyMDPPSSy+Z9957z0RFRXkV4/3337ctnzNnzphXX33V9O/f\n37z11lsmOTnZrFu3zsTHx1uKk5aWZqZPn24GDRpkHnroITN48GAzffp0k5qaajmn9PR0M2fOHDNm\nzBizYMECk5mZabZu3WpOnz5tOdahQ4fM4MGDzd13322GDBlifv/9d7N06VKzbds2y7EutnjxYtO7\nd2+vH2/nNuZISEgwx44dM5mZmeabb77xOk58fLxZsWKF+fHHH01qaqoZP368OXv2rOU4dm1jznPY\nsWPHAj+HL7/8suXH5OfP9tW5c+csx7HzPX3+/HkzY8aMP8RPSEgoUNx3333XtGvXrkAx7Hpt5UhP\nTzfDhw837du39+rxS5Ys8XrdcBa12TPUZmuozZ6jNltDbfZcYdXmInVP6f79+1WjRg2fxF6yZImW\nLFli+TryP7N+/XrddtttNmRln02bNikwMFBNmzb16vFff/21goOD9fe//z33d6tXr1bbtm0tx0pL\nS9Pu3buVmpqqChUqqFatWl5/e2NnXmfOnFHp0qUVFBSkZcuWyeVyqXPnzpZzO3v2rA4cOKD69etr\n6dKl2rFjh2rWrKnu3bsrKMj6xQmJiYmqUKGC4uPj9dtvv6lmzZqqWbOm5TiSvfsrR879Qt7KyMjQ\n7t27lZSUpLJly+rGG29UqVKlvIq1Z88eBQcH6/rrr8/93bZt29SgQQNLcRYsWKDu3bsX6NvOvPzy\nyy9KSkq65DnwVkHf13bmdfHzeNVVV6l+/fpePY9JSUm5lzV+8cUXOnfunLp06eLVeweFg9rsPWrz\nlVGbvUNttobanL/CqM1FqimtU6eOHn30UQ0cOFBXXXWV0+nkunyQh+nTp6tv376SrA/ykN99JVZe\nROvWrdOYMWNUtmxZ3XXXXfrxxx8VHBysBg0a6PHHH7eU05gxY5SUlKTMzEylpqZq0qRJKlWqVO7N\n2FasW7dO7777rq6//nr9/PPPql+/vo4fP65nnnnG8pvXzrw++eQTffjhh5IuXO7gdrsVGhqqgIAA\njRo1ylKsfv36qUePHtq2bZvOnDmjVq1a6ccff1RCQoLefPNNS7HGjh2rqlWrKiIiQjNnzlTTpk21\nbds23XXXXerXr5+lWHbtr8vvRRg/fryeeeYZSbL8ge+bb77RG2+8oerVq6t06dJKSUnR/v379fTT\nT1suxpMmTdL333+vzMxM1alTR2PGjJHL5fLq9XDLLbfo5ptv1gsvvHBJEfXG6tWr9corryggIEDR\n0dFavXq1wsPDdcMNN+TuN0/92fu6VKlSatiwoeX3td15vfnmmwV+HufPn6+PPvpI0oUBGk6dOqWK\nFSsqOTlZ48aNs5QTCg+1mdrsq7yozdTmi1Gbi3ltLpTzsTaJiooyH3zwgfnf//1fs2TJEpOenl6g\nePv378/zPyseeeQR0717dzNx4kQzceJE06pVq9yfrWrXrp1p0qSJad26tWnVqtUl/7eiW7duJjk5\n2cTFxZlbb73VZGRkmOzsbNOjRw/LOfXs2TP351mzZpkBAwYYY4xXl1RFRUXlPm+nT582Q4cONUlJ\nSaZXr16O5tWtWzeTlZVlEhISTPPmzXN//8ADD1iOlbP+y/PwZt/nPOaBBx4wKSkpxpgLl7Xdd999\nlmPZtb86d+5sunTpYoYOHWqGDh1qmjdvnvuzVT169DBJSUmX/O7cuXNebV/37t1Ndna2McaYV199\n1YwePdoY4/3rdOvWrea+++4zQ4cONT/99JPlGDm6du1qzp49a44dO2b+/ve/577+vXk9XPy+/tvf\n/lag97Wdedn1PHbt2tW43W6TlJRkWrZsmft8evM+ROGhNnuO2mwNtdlz1GZrqM3WciqM2lykrody\nuVzq16+f7r77bs2YMUNTp05VZGSkqlWrpueff95yvGHDhunQoUOqUaPGJRMWWx22fNq0aZowYYKy\nsrL0xBNPaNOmTRo0aJDlfCRp3rx5uaOJlStXzqsYkpSdna3Q0FBVr15dTzzxRO7pdePFifGsrCy5\n3W6VKlVK0dHROnr0qF566SWv8so5/S9dGM3r4MGDCgsL82rkQTvzys7OVmpqqiIiInJHeHS73crI\nyLAcKygoSNu3b1fjxo31448/6pZbblFMTIwCAqwPdm2M0ZkzZ1StWjWlpaWpdOnSSk5OdvR5nDdv\nnsaOHavGjRurW7duio6O9vqbsoyMDIWEhFzyu+DgYK8uzTHG5D7uueee05AhQ/TBBx94Fcvlcqlh\nw4ZavHix1q5dq5kzZ+rZZ59VWFiYli5dailWVlaWypQpkxs3Jx9vRny8+H09ePDgAr+v7crLrucx\nKytLaWlpOnv2rM6fP6/z58+rVKlSXh0fUHiozZ6jNltDbfYctZnafLmiVpuL1OW7l4/AZ4zRnj17\nFBcXp/bt21uOl5qaqqioKE2ZMkWVK1cucH5ffPGFPv/8c/3+++/5ztt2JevXr1dgYKCaNWvmdYy5\nc+dq/vz5WrZsWe4Bd/Dgwbrppps0cOBAS7E+//xzvfvuu5o/f74qVqwoY4xGjhypJUuWaOfOnZZi\nTZs2TStXrtStt96qLVu26IEHHlBiYqIOHTpkeR4tO/P64osv9NZbb2nVqlW5+ys6Olr/+7//q27d\nulmKdfDgQY0cOVKnT5/W3r17VaZMGd1www166aWXLN/fkXMJTa1atbRp0ybVq1dPe/fu1dNPP62O\nHTtaimXn/pKkjz76SAcOHNC+ffv08ccfW368JC1cuFCzZ89WkyZNFB4eruTkZMXExCg6Otryfp8x\nY4Y+//xzffDBBypfvrzcbrcGDBigLVu2aNu2bZZi5TXa5+nTp1WxYkVLsT788EPNmTNHVatWVeXK\nlZWQkKCQkBDVrVtXgwcPthTLzve1nXnZ9TwuX75cr7/+um666SbdeOONWrdunUJDQ9UikWZ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B9++EHlypVT8+bNi1TWoUOHFBUVpdq1ays0NFQJCQmqWLGirVn79+9XZGSkUlJSnDPpudOMpUtT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\nrXL0jG6BeB8DsSYns0rDY+jkfXQyKxD3FVnBmeX2QOWmktKbS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ZpQMji1toBzFba2MjMz\nJRXv2vJ3vUsF12WVk1klVXH0Zn/4sy6lwH3ec2qNu3Xs+bPfI5wqCpb48xj6e/xYwc8fzh4/8J+V\n51NbQ2nLli21fPlyde3aVRs3blSDBg18140ZM8b39fTp01WzZk2/mp4kRUVF+b72er1K27ylgK2t\nadKkSZ46LyQxMTFPDefyer1KWbnasZpQMji1trR8o9OlIcgVtrZWrVqlzMzMYl1b/qx3qfA1b4Xd\nrNI2yBZHb/aHP+tSCtznPafWuBvHnj/Hitfr1V7HqoIV/jyG/h4//uLnjzOcPH5Kw/5yyoX2e369\n2dZQ2qVLF61Zs0axsbGSpPj4eM2ZM0eRkZHq2LGjnUgAAFAE9GYAQLCyNZR6PB5NmjQpz2V169Y9\nb7vhw4fbqwoAAFhCbwYABCtbJzoCAAAAAMAJDKUAAAAAANfYevsuCjakeUu3SwAAIOh9o6pul4AA\nwnoASi5eKQUAAAAAuIahFAAAAADgGoZSAAAAAIBrGEoBAAAAAK5hKAUAAAAAuIahFAAAAADgGoZS\nAAAAAIBrGEoBAAAAAK5hKAUAAAAAuIahFAAAAADgmlC3CwAAnM/k5mrPnj0FbpOdna3s7Gzt3Lkz\n320KywCsyMnJ0a5duwrcxp91KbE2Ubr485wu+X/81KtXTyEhIU6VB7iOoRS4gG9U1e0SLrrs+tc6\nllUa9ldxO33imMbM+1jhVavnu03Hqmfe7DLolXfy3eZk0i5VjqzneH0onXbt2qWf/v2l6lx+eb7b\n5GZmKlRS2uYtBWdt3OhwdUDgyjh5XHNWfqcq2/YVuF3N0+mSpBeXrMx3mxOHf9eku/qpQYMGjtYI\nuImhFAACVHjV6qpQ/ZJ8r/fouCSpQvUa+W6Tfvyo43WhdKtz+eW66v9F5nv9V7t/kaQCt5GkpF9/\nlU7+4WhtQCCrUvNSVb/8igK3KfPLEUkqdDugpLE1lBpjNHHiRO3YsUNhYWF6+umnVbt2bd/1c+bM\n0WeffSaPx6Po6GgNGzbMsYIBAMD56M0AgGBl60RHS5cuVWZmphISEjR69GjFx8f7rtu/f78+/fRT\nvffee0pISNDq1asLfV88AAAoGnozACBY2RpKExMT1b59e0lS8+bNtWXL/z43cvnll2vWrFmSJI/H\no+zsbJUrV86BUgEAQH7ozQCAYGVrKE1JSZHX6/V9HxoaqtzcXElSSEiIqlSpIkl65pln1KhRI0VG\nFvy5EgAAUDT0ZgBAsLL1mdKIiAilpqb6vs/NzVWZMv+bbzMzMzVu3Dh5vV5NnDjR79zExETf10lJ\nSXLyfJFbtmxRcnKypRrOlZSUpDoO1oSSwam1BQQDf9e7VPCat8rJrJIqGHtzIHJqjTv9vO5Er5HO\n1BXhVFFwTaCu00Dl5PED/1lZp7aG0pYtW2r58uXq2rWrNm7ceN4pqR988EG1adNG9957r6XcqKgo\n39der7fQ08lb0aRJk0JPnZ2YmJinhnN5vV6lrFztWE0oGZxaW1rOn0dA4PNnvUuFr3kr7GaVtkE2\nGHtzIHJqjTv9vO5Erzlb117HqoJbAnWdBionj5/SsL+ccqH9nl9vtjWUdunSRWvWrFFsbKwkKT4+\nXnPmzFFkZKRycnK0YcMGZWVlaeXKlfJ4PBo9erSaN29u558CAAB+oDcDAIKVraHU4/Fo0qRJeS6r\nW7eu7+tNmzYVrSoAAGAJvRkAEKxsnegIAAAAAAAnMJQCAAAAAFzDUAoAAAAAcA1DKQAAAADANQyl\nAAAAAADXMJQCAAAAAFzDUAoAAAAAcA1DKQAAAADANQylAAAAAADXMJQCAAAAAFzDUAoAAAAAcA1D\nKQAAAADANQylAAAAAADXMJQCAAAAAFwT6nYBAHDWN6rqdgkAAAAoZrxSCgAAAABwje2h1BijCRMm\nKDY2VoMHD9b+/fvzXP/ee+/p9ttvV2xsrFasWFHUOgEAQCHozQCAYGT77btLly5VZmamEhIStGnT\nJsXHx2vGjBmSpCNHjmjevHlavHix0tPTNWDAALVr105ly5Z1rHAAAJAXvRkAEIxsv1KamJio9u3b\nS5KaN2+uLVu2+K7bvHmzoqKiFBoaqoiICNWpU0c7duwoerUAACBf9GYAQDCy/UppSkqKvF7v/4JC\nQ5Wbm6syZcqcd12FChWUnJxs+d/Y++uvdss7LyfcW7HQ7ZKSkvLUfa49e/Yo9dAhR2o6ePiIKqSn\nOZJ1KCNd6cePOpKVceqEIzlnsw6U8PuYfvyo9uzZU+h2/qwtJ+/ficO/O5J16tgRpadmOZLl9Npy\nMsvJ/ZVqQhzJSjt+XFlh6QVuY6qe+b3i6eN/5LuNG+tdKnzNW+FPVoMGDRz5t4JdIPTmrOxsSdLP\n+5IK3O7AH3848ryXceqE9jrUm/ceOqSKDq1xJ5/Xneo1Z+s6WMJ7c8apE9qf6Slyzm/Jp5QeVry9\nuWZOjiTp6K8H8t3mxOHfHXsudvrnD6c42Zv93V/+Hj9OPW85JePUCSUfyf/nACtSjh9Veo4zP8dY\n3U8eY4yx8w9NnTpV1157rbp27SpJ6tChg+/zKV999ZVWrVqlCRMmSJKGDx+uBx98UI0bN843LzEx\nMc/3OTk5OnAg/wPSqrNNuShycnIUEuLMA5WTkyOPx1PkmshyN0tibZHlXtb27dslSQ0bNiyWmiRn\n1vvFEBkZecHLo6KiirkSdwVCb/ZnXZ7NcmJtBuoad/J5XQrMuoL5+TNQa/L3+GE9WBNo+ytQ95XT\n+/2KK6644P66YG82Nn3xxRdm7NixxhhjfvjhBzN06FDfdYcPHzY9evQwGRkZ5tSpU+aWW24xGRkZ\nBeZt2LDBVh12b0dWYOSQRdbFyikNWS+++KJ55plnHMkyJjDvY1GynKwhWARCb2ZdupcViDWRZU2g\nHj+BuK/ICs6s/G5n++27Xbp00Zo1axQbGytJio+P15w5cxQZGamOHTsqLi5OAwcOlDFGo0aNUlhY\nmN1/CgAA+IHeDAAIRraHUo/Ho0mTJuW5rG7dur6v+/btq759+9qvDAAAWEJvBgAEo8D7YBAAAAAA\noNRgKAUAAAAAuIahFAAAAADgGoZSAAAAAIBrGEoBAAAAAK5hKAUAAAAAuIahFAAAAADgGoZSAAAA\nAIBrGEoBAAAAAK5hKAUAAAAAuIahFAAAAADgGoZSAAAAAIBrGEoBAAAAAK5hKAUAAAAAuIahFAAA\nAADgGoZSAAAAAIBrQu3cKCMjQ2PGjNHRo0cVERGhqVOnqmrVqnm2efbZZ/X9998rJydH/fr1U9++\nfR0pGAAAnI/eDAAIVrZeKZ0/f74aNGigd999Vz179tSMGTPyXL9+/Xrt379fCQkJevfdd/XGG28o\nOTnZkYIBAMD56M0AgGBlayhNTExUdHS0JCk6Olrr1q3Lc32LFi00ZcoU3/e5ubkKDbX1oiwAAPAD\nvRkAEKwK7UYLFy7U3Llz81xWo0YNRURESJIqVqyolJSUPNeHhYUpLCxM2dnZGjdunPr376/y5cs7\nWDYAAKUXvRkAUJIUOpTGxMQoJiYmz2UjRoxQamqqJCk1NVVer/e82506dUojR47UX/7yFw0dOtSh\ncgEAAL0ZAFCSeIwxxuqNZs+erdTUVA0fPlxLlizRhg0bNGHCBN/1GRkZGjBggO655x51797dr8zE\nxESrZQBAqbZs2TJJ0k033eRyJYErKirK7RKKTaD0ZtYlYB/HD0qDC/ZmY0NaWpoZOXKkGTBggLnz\nzjvNkSNHjDHGPPvss2bz5s1m9uzZ5rrrrjNxcXFm0KBBJi4uzhw4cKDAzA0bNtgpxfbtyAqMHLLI\nulg5pSHrxRdfNM8884wjWcYE5n0sSpaTNQSDQOnNrEv3sgKxJrKsCdTjJxD3FVnBmZXf7Wyd4SA8\nPFz//Oc/z7t8zJgxkqSmTZvqrrvushMNAABsoDcDAIKVrbPvAgAAAADgBIZSAAAAAIBrGEoBAAAA\nAK7hr2YDQJD6+9//zpnLEXBYl4B9HD8orXilFAAAAADgGoZSAAAAAIBrGEoBAAAAAK5hKAUAAAAA\nuIahFAAAAADgGoZSAAAAAIBrGEoBAAAAAK5hKAUAAAAAuIahFAAAAADgGoZSAAAAAIBrGEoBAAAA\nAK5hKAUAAAAAuMbWUJqRkaGRI0fqjjvu0P3336/jx49fcLu0tDT16tVLq1evLlKRAACgYPRmAECw\nsjWUzp8/Xw0aNNC7776rnj17asaMGRfcbvLkySpThhdjAQC42OjNAIBgZasrJSYmKjo6WpIUHR2t\ndevWnbfNW2+9pZYtW+rqq68uWoUAAKBQ9GYAQLAKLWyDhQsXau7cuXkuq1GjhiIiIiRJFStWVEpK\nSp7r161bp6SkJE2aNEnff/+9g+UCAAB6MwCgJCl0KI2JiVFMTEyey0aMGKHU1FRJUmpqqrxeb57r\nFy5cqN9++01xcXHas2ePtm3bpho1aqhhw4YOlg4AQOlEbwYAlCQeY4yxeqPZs2crNTVVw4cP15Il\nS7RhwwZNmDDhgtuOGzdOt956q2644YYCMxMTE62WAQBAgaKiotwuodjQmwEAweBCvbnQV0ovZMCA\nAXr00Uc1cOBAhYWF6fnnn5ckPffcc+ratauaNm3qSHEAAMA/9GYAQLCy9UopAAAAAABO4JzwAAAA\nAADXMJQCAAAAAFzDUAoAAAAAcA1DKQAAAADANQylAAAAAADXMJTCktJwsmbuI+COlJQUt0sAglJp\neE7nPgLuKK7ezFDqgBtuuEFr1651JOvYsWN64okndMstt+RnAfMAACAASURBVKhTp04aOHCgpk2b\nptTUVEs5x48f19NPP63u3burQ4cO6tGjhyZNmqSjR49armnfvn0aMmSIOnbsqCZNmqhfv34aPXq0\nDh8+bDkrIyNDr732moYOHapBgwZpxIgRmj9/vnJycixnncvOfTvLyfv4Z8eOHVNiYqJOnDhh6/Yv\nvviiJGnPnj2KiYlRdHS0YmNjtWfPHstZTt1HJx/D2NhY/fLLL5ZvdyFO7isnj+mzx+LMmTO1fft2\ndenSRV27dtUPP/xgOSszMzPPf3FxccrKylJmZqblLCf317lGjx5t63bt2rXT+++/X+R/H5DozVbQ\nm62hN/uP3mxNae7NQfV3ShcsWJDvdf379y9y/tGjR1W9enXLt+vVq5cuu+wyVa5cWcOHD1ft2rVt\n1zBs2DANGjRILVu21LJly3To0CFdccUV+uyzz/TSSy/5nXP//ferZ8+eio6OVsWKFZWamqqVK1fq\n/fff15w5cyzVNGTIED3xxBOqW7euNm7cqBUrVqhz5856+eWXNXPmTEtZjzzyiFq3bq0WLVroq6++\nUpkyZVSmTBnt2bNHkydPtpR17gH66KOP6plnnpEk1a1b11KWk/fxvvvu08yZM7VixQrFx8frmmuu\n0S+//KJRo0apU6dOlrIGDx6st99+W/fff7/uu+8+RUVFafv27XrmmWc0e/ZsS1lO3UcnH8NbbrlF\nlSpVUrt27XTPPfcoIiLC0u3/zMl95eQxPXToUHXr1k2//vqr3n33Xb3zzjsqX768xowZo3feecdS\nVqtWrVSuXDmFh4fLGKMjR46oRo0a8ng8WrZsmaUsJ/dXhw4dlJ2d7fv+xIkTqlKliiRp9erVfuf0\n799fjRs31i+//KLhw4erdevWluqAO+jN9OY/ozfTm/+M3kxv9lfoRUm9SHbv3q3ly5frtttucyTP\nqSfOSpUq6fXXX9eXX36phx9+WJUrV1b79u1Vu3Zt3XTTTZZqOnHihNq0aSNJ6tatm+655x699dZb\neuuttyzlpKSkqFu3br7vIyIidOutt+rdd9+1lHM26+z+uPbaa/XCCy/o73//u06dOmU569dff1VM\nTIwkqV69eho6dKjeeOMNDRw40HLW3XffrfDwcF1yySUyxmjPnj0aP368PB6P3n77bUtZTt7H9PR0\nSdIbb7yh+fPnq1q1akpNTdW9995rufGdlZaWpqioKElSw4YN8zzJ+Mup++jkY1izZk299dZbmjdv\nnmJiYtS6dWtFR0friiuuUMOGDS3nSc7sKyeP6dOnT6t3796SpG+//VZXXnmlJMnj8Viua8GCBXr2\n2Wc1atQoXX311YqLi9O8efMs5/yZE/vrueee0+zZszVx4kRdcskltusqV66cxo8frx9//FEzZ87U\n5MmT1aZNG9WuXVuDBw+2nIfiQW/2H72Z3nwuerP/6M3WBFtvDqqhdNy4cdq9e7eio6PVrFmzIuc5\n9cR59sXmm2++WTfffLN27dqltWvXau3atZYPkooVK2rmzJmKjo7WsmXLdOmll+rbb7+1lCFJ1atX\n1/Tp0xUdHa2IiAjfb2Nr1qxpOeuKK67Q+PHjFR0drRUrVuiaa67Rl19+qfLly1vOkqTPPvtM7du3\n17Jly1S+fHnt3LlTGRkZlnM++OADTZgwQQMGDFC7du2K9CTg5H08+8Th9Xp9v5GqWLGicnNzLWft\n3btXDz74oFJSUvTFF1+oU6dOmjt3ripUqGA5y8n76NRjaIxRaGio7r77bg0aNEhr167VunXrtHDh\nQr3++uuWspzcV04e05UrV9aMGTP04IMPau7cuZKkjz76SOXKlbNcV7169fT8889r/Pjx6tChg63m\neZaT++u6665T7dq1NX78eN1zzz226zq735s2bapXXnlFycnJ+u677xx52xIuHnqz/+jN1tCbraE3\n+4/e7L9i680myBw9etTs37/fkawjR46YYcOGmdWrVxtjjBk0aJCtnH/961+O1GOMMSdOnDBTp041\nQ4cONS+88IJJSUkxK1asMElJSZZy0tPTzezZs83w4cPNXXfdZUaMGGFmz55t0tLSLNeUkZFh3nnn\nHTNx4kSzYMECk52dbX744Qdz7Ngxy1n79+83I0aMMLfeeqsZPXq0+eOPP8zixYvNpk2bLGcZY0xW\nVpZ56qmnzGuvvWb78TPG2fv4wAMPmG7dupkbbrjBzJ4925w+fdrcd999ZsqUKbZqS0pKMkuWLDHf\nffedSUtLM88995w5efKk5Ryn7uPZx7Bbt25Ffgyffvppy7cpyIX21alTpyznOHlMnz592syZM+e8\n/CNHjhQp9+WXXzY333xzkTKcWltnZWRkmMcff9x07drV1u0XLVpk+9+Gu+jN/qE3W0Nv9h+92Rp6\ns/+KqzcH1WdKd+/e7Xt53SnZ2dl65plnVL16da1Zs6bIL7dLZ96nfcMNNzhQnXPWr1+vkJAQtWrV\nytbtly9frnLlyqlt27a+y5YuXarOnTtbzkpPT9eOHTuUlpamqlWrqkGDBkX6rZIkLVq0SIsWLbL8\nOYA/O3HihCpUqKDQ0FB99NFH8ng86tmzp+3ajh49qqysLNWsWVNr1qxRdHS0rZzjx4+ratWqSkpK\n0k8//aT69eurfv36trKcfBzP2r59u+2380hSVlaWduzYoeTkZFWqVElXXXWVwsLCbGXt3LlT5cqV\nU2RkpO+yTZs2qXnz5pZyFixYoH79+hV5XV7Ijz/+qOTk5DyPgV1FPa6drOvPj2PZsmXVrFkzW49j\ncnKyPB6PIiIi9MUXX+jUqVPq3bu3QkOD6o09pQq92T56c+HozfbQm62hNxesOHpzUA2ljRo10n33\n3adhw4apbNmyjmYX5Ynz3JM8zJ49W3fffbck6yd5KOhMXVYW0YoVKzRx4kRVqlRJf/3rX/Xdd9+p\nXLlyat68uR566CFLNU2cOFHJycnKzs5WWlqapk+frrCwMN+Hsa1YsWKFXn75ZUVGRmrjxo1q1qyZ\nDh06pDFjxtg6eJ16In///ff15ptvSjrzdofMzEyVL19eZcqU0fjx4y1lnTx5Unv37lWzZs20ePFi\nbdmyRfXr11e/fv0sH7yTJ09WrVq1VL16dc2dO1etWrXSpk2b9Ne//lVDhgyxlOXU43juh+Ofe+45\njRkzRpIs/8C3cuVKTZs2TXXq1FGFChWUmpqq3bt3a9SoUZYfw+nTp2vNmjXKzs5Wo0aNNHHiRHk8\nHlvr9LrrrlPjxo01adKkPE3UjqVLl2rKlCkqU6aM4uLitHTpUnm9XtWtW9e33/x1oeM6LCxM1157\nreXj2um6nn/++SI/jgkJCb7P6HXo0EFHjx5VtWrVlJKSovj4eEs1ofjQm+nN56I3+4/e7D96cwnv\nzcXyeqxDBg0aZGbNmmVuu+02s2jRIpORkeF2ScYYY+69917Tr18/88orr5hXXnnFdOzY0fe1VTff\nfLOJiooynTp1Mh07dszzfyv69u1rUlJSzJ49e0zr1q1NVlaWyc3NNf3797dcU2xsrO/rt99+2zz4\n4IPGGHtvqRo0aJDvcTt27JgZO3asSU5ONgMGDLCcNWHCBDNq1CgzcuRIM3ToUF9uXFyc5ay+ffua\nnJwcc+TIEdOuXTvf5QMHDrScdc8995gvvvjCPPvss+axxx4z//nPf8yUKVPMqFGjLGedfbwGDhxo\nUlNTjTFn3hbVp08fy1lOPY49e/Y0vXv3NmPHjjVjx4417dq1831tVf/+/U1ycnKey06dOmXr/vXr\n18/k5uYaY4yZOnWqmTBhgjHG/jr94YcfTJ8+fczYsWPN999/bznjrJiYGHPy5Enz22+/mbZt2/rW\nqZ1j8c/H9fXXX1+k49rJupx6HGNiYkxmZqZJTk42HTp08D2edo5DFB96s//ozdbQm/1Hb7aG3myt\npuLozUH1fiiPx6MhQ4bo1ltv1Zw5c/T666+rXr16ql27tsaNG2c5r6AP6Fo5w9/MmTP10ksvKScn\nRyNHjtT69es1fPhwy/VI0vz58zVkyBDNmTNHlStXtpUhSbm5uSpfvrzq1KmjkSNH+n4LaGy8MJ6T\nk6PMzEyFhYUpLi5Ov/76q5566ilbdZ19+V86czavffv2KSIiwtbfctqxY4fmz58vSZo3b57+/ve/\na8aMGbbuY25urtLS0lS9enVNmDBB0pnfjGdlZVnOyszM1M0336x58+b53nLWuXNnxcbGWs4yxujE\niROqXbu20tPTVaFCBaWkpLj6OM6fP1+TJ09Wy5Yt1bdvX8XFxdn+TVlWVpbCw8PzXFauXDlbb80x\nxvhu9+ijj2r06NGaNWuWrSyPx6Nrr71WH3zwgb766ivNnTtXjzzyiCIiIrR48WJLWTk5OapYsaIv\n92w9dk6u8efjesSIEUU+rp2qy6nHMScnR+np6Tp58qROnz6t06dPKywszNbzA4oPvdl/9GZr6M3+\nozfTm88VbL05qIbSsw/uZZddprFjx+rRRx/Vzp07bZ/96bHHHtP+/ft15ZVX5lk4Vs/w5/F49PDD\nD+uLL77QyJEji/QgVatWTaNHj9a2bdt8p5+3o3fv3urZs6c++ugj3XHHHZKkESNG2PrsxODBg9W9\ne3clJCSoWrVqeuSRR/Tkk08qMTHRcla3bt3Ut29ftW7dWhs2bNDAgQP1xhtvqFGjRpaznGzIQ4cO\nVZ8+ffT555+rS5cuks787bC+fftazgoNDdXmzZvVsmVLfffdd7ruuuuUmJioMmXKWM566KGHFBcX\npwYNGui2225T06ZN9fPPP2vUqFGWs5x6HMuXL6/4+Hi99dZbGj9+fJH+uHr//v3Vu3dvRUVFyev1\nKiUlRYmJiYqLi7Oc1a1bN8XExGjWrFmqUqWK4uPj9eCDD2rTpk2Ws/78fNCpUyffnws4duyY5axb\nb71VnTt3Vq1atXT99dfr3nvvVXh4uNq3b285y8nj2sm6nHoc77rrLt1yyy1q2LCh+vTpo5iYGJUv\nX179+vWzXBOKD73Zf/Rma+jN/qM3W0Nv9l+x9WZHX3e9yL7++mtH806fPm369OljDh065Fjmzp07\nzXPPPedYXlGce+a23bt3285KT08/77KtW7faytqxY4f5/PPPza5du4wxZ87aaMcnn3xiunTp4rt9\nbm6uefzxx80111xjKy8nJyfP9+e+5cFfSUlJZvDgwaZ79+7m6quvNi1btjS33367+emnn2zlpaSk\nmFWrVpmPP/7YrFq1yvb+MsbZx9EYY9auXWtGjx5t+/bGGHP48GGzbNky8/HHH5uvvvrKHD582HbW\nvn37THZ2dp7L/vOf/9iqyUmnTp0yWVlZJisryyxbtsxs2LDBdpaTx7WTdTn5OJ61fft2c/DgwSLn\n4OKiN1tDb7aG3mwdvdk/9GZ7LlZvDqoTHTn5IfWztmzZoqysLLVo0cJ2XfPmzVNcXJyOHDmiyZMn\n66efflKTJk30+OOPq0aNGpayYmNj9dRTT9k+g5vTOZKUkZGhhQsXKjQ0VF27dtUjjzyiU6dOacKE\nCZbP7JaRkaG33npLiYmJSk9PV9WqVdW2bVv169dPISEhtmo7929Kbdu2zfJvd48fP64ZM2Zo3bp1\nSklJkdfrVatWrTR8+HBVr17dcl1naztx4sT/Z+/e46Kq8z+OvwcQURkT0dxEf2QUZuma4nYzTU3K\n1LZMTUwxK8u1tJtb6ep6S8UsdzEvXdbKUldSU/NSW2lmapY6pUaWtITkbSsVFRAYLuf3h8uspMBc\nDpwBXs/Hw8cDZs6853MOx/ny4ZzzPWrQoIFX970qzkhKStLnn39eoq7Bgwefd0qGu1mNGjVS+/bt\n9cwzzyggIEATJ070aObMDz74QLfffrvOnDmjOXPmuPb3ESNGuE458Wb9imf483X9tm/frszMTJ+2\n1W+NHj1as2bN8uq1/vj5YHZdZv0cDxw4oL/97W8KDg7WqFGjXBNZTJw4UZMnT/aoJlQexubKz5EY\nmxmbS2Js9ow/fj6YXVdVG5urVFP64IMPKi4uTrt379bJkyfVtWtX7dy5U8eOHfN6pzRD8QxiTzzx\nhG655RbFxsbq888/17Jlyzy+yfDtt9+u+vXrq2PHjnrggQcUGhrqVU1m5UjSyJEjFRUVpezsbG3Z\nskV/+ctf1LhxYyUkJHg8Tf8zzzyja6+9Vu3atdMnn3yigIAABQQEKC0tTVOmTPEoy8zBavjw4brz\nzjvVuXNn1atXz3VD8+XLl2vhwoUe1/Xyyy+rUaNG6ty5s0aNGqXAwEDNmDFD11xzjUdZTz31lK68\n8soSdX322Wfas2eP5s2b51HWk08+qaioKB09elQ7duzQlClTVLduXSUmJurNN990O6d4fx83bpya\nN2+u2NhYbd++XV9//bXH/w/NXD8zs7p06eK60bok1y8w0vkzHJbHHz8fzK7LrG0fHx+v4cOHq6Cg\nQC+88IJeeOEFXXXVVYqPjzflliCoGIzNlZ8jMTYzNpfE2MzY/FtVbmw2/dhrBSqeqeu3M3Z5MyOV\nYZw91D516lSjV69exs0332z07t3bmDRpksc3zi2eUe63dXkz01x8fLyRn59vvPHGG8Ztt91m/PWv\nfzU+/vhjj08vMSvHMEquV69evS74uLsGDRpU4vthw4YZhmF4NcPfww8/bKxfv97IzMw0ioqKjMzM\nTGPdunXGfffd53FWaTOIeVPXsGHDjJUrVxpz5841brjhBiM1NdU4cuTIeevujtJe401dxVmFhYVG\nz549XY8PGTLEo5zi/fq3tXmzv1fE+pmRtWPHDmPEiBHGzz//bBiGd/t6MX/8fDC7LrO2/bm1pKam\nGj179jSOHDniVU2oPIzNlZ9jGIzNnmJs9rym32JsLj2Lsdl3nl/dbaHfXqQuyeuL1CVpzJgxateu\nnZKSkrRp0yYtXbpUHTp00OjRoz3KSUlJ0dSpU1VQUKDt27erqKhIH3zwgVc1GYahoKAg3X///Vq7\ndq1uueUW7dq1S4mJiZbkFFu6dKleeeUVnTx5Up9//rn27t3r9XZ///33lZmZqdWrV6tOnTpKSUlR\nXl6exzlZWVnq2bOnQkNDXTf07dWrl1eTWYSHh2vu3Lnau3evfvzxR33zzTeaO3euGjdu7HHWmTNn\n1KdPHz366KO64oordNlll+mSSy7xaqa52rVra/Xq1Tp+/LicTqdOnDihVatWqW7duh5nBQUFac2a\nNQoICNB7770n6ewNnj2d0e3AgQNauHChgoKCtG/fPklnb+7szXa/0PqtXr3aq/Uzc1v94Q9/0IQJ\nEzRhwgTt2LHDpxt1++Png9l1mfVzDAoK0ieffKLCwkJddtll+utf/6rhw4fr2LFjXtWFysHYXPk5\nxRib3cfY7D7GZs8wNpujSp2+m5ycrBdeeEEnTpzQDz/8oNDQUF166aWaOnWqx9dPSNKgQYO0ZMmS\n8x6/99579c9//tPtnFOnTmnfvn1KTk5WVFSUrrvuOo0fP15//vOfFRER4VFN06dP11/+8hePXlOR\nOZJ09OhRLVy4UK1atVKTJk30wgsv6KKLLtL48eMVFRXlUdahQ4c0c+ZMpaamqlWrVnr22We1bds2\nXXbZZfr973/vUdZjjz2m6Ohode7cWaGhoa7Ten744QfNnj3bo6y8vDwtXbpUDofDdbpR+/btFRcX\n5/E1D4888ojrOo7iD8z33ntPa9eu1YIFCzzKysjI0Lx58/TVV18pOztb9erVU/v27TVixAiPT4M6\nduyYXnvttRL7xeTJkxUfH+/RdSv79u3Tt99+q2+//VZt27ZV9+7d9eCDD2ry5Mlq1aqVRzWdu35Z\nWVkKDQ31ev3MzCrmdDo1ZcoUORwOrweF0j4fRo8erWbNmnmUZeb/azPrMms/PXr0qGbPnq0xY8a4\nTsn64osvlJCQ4PplDf6HsbnycyTGZsbmkhibPcPY7H9jc5VqStu2bavx48frzjvvVEZGhk8XqUvm\nfXBu3bpVN910k9d1VESWP9ZkdpaZg9Vv7d27V1lZWbrxxhs9fm1OTo6WLVum++67z/XYa6+9pr59\n+3r1AZyXl6fvv/9eZ86cUVhYmFq2bOn1Xwfz8vK0f/9+V1Z0dLTXWRkZGa7tXvwh5Y3MzEwFBQWp\nTp06rscOHz7s8S+Nv3Xw4EEFBAT4nCNJX331lZo0aWJKlpl1ff/991790l+ssLBQgYGBysrKUlpa\nmiIjI1W/fn2f60LNwthc+Tn+nMXY7DnGZu8wNlcvgZMmTZpkdRHu+vTTT2Wz2bRw4UJdeeWV+r//\n+z+f8rp166aUlBStW7dOGzZsUHJysiIjI/Xkk096NGNg7969lZqaquuuu87nD9zirGuvvdanLLNy\nirN+/PFH09bPrKygoCBdc8016tmzp+666y5FRETIbrd7dHP1Yhs2bNCwYcO0aNEiGYahxYsXa//+\n/dq3b586duzoUVatWrVKTJrwzTffqEGDBmrZsqXHdX366ad65plndODAAS1ZskQHDx7UwoUL1aJF\nCzVt2tSrrLS0NC1evNjrrL179+rRRx/Ve++9py1btmj58uVKSkpSy5Ytdckll3hU0/Lly/Xss8/q\nn//8p/Ly8hQTEyPp7AQeffr08Shr7969evjhh7VhwwYZhqHnnntOH374oQIDA3X11Vf7lDVr1izT\nsnypa+vWrfrpp59c/yZPnqzmzZvrp59+8vjz8OWXX9YXX3yh/Px8Pfroo0pNTdWrr76qiy66yKt9\nFTUXY3Pl5xRnMTa7j7HZfYzNjM2WMPUK1QpWfEHt3r17jZEjRxq9evUypk6darz11lum5H/xxRfG\nzp07PX7d4MGDjQ8++MDo2bOnMWfOHJ/urWZWlj/WZHbWxx9/bHTt2tW45ZZbjIULFxqDBw82RowY\nYcycOdPjrH79+hmnTp0yjh49atx4441GXl6eYRjeTdRhZl2DBw921XLixAljzJgxRmZmplcTBJiV\nFRcXZxw5cqTEY4cPHzb69evncU39+vUz8vLyjLy8POOpp54yXn75ZVetnhowYIBx6NAh48svvzTa\nt29vZGdnG06n06ufob9m3XnnnUafPn2MMWPGGGPGjDE6duzo+tpTffv2NYqKioxBgwa57q+XnZ1t\n9OnTx+Os3r17Gx07drzgPytyULkYm6t2TWZnMTZbk8XYbF0WY7M5vLuBmEWM/55p3KZNG82ZM0eZ\nmZnauXOn0tLSvMr79NNPNWnSJNWvX1+33Xabdu7cqdq1a2vHjh165JFH3M6x2Wzq0aOHbr75Zq1Y\nsUKjRo1Sfn6+IiIiNHfuXI9qMivLH2syO+vVV1/V6tWrdebMGfXt21ebNm1ScHCw4uLiPMqRzp4q\nUXwfL5vN5jptxtOJBsyuKzMz01VL7dq19dNPPyk0NNSriQvMyiooKDjvr67eThYRGBio4OBgSdLz\nzz+vYcOGqVmzZl5lFRUVKSIiQhERERo8eLDrQv7qlLV06VJNmTJF7du3V//+/RUfH6+EhASPcyQp\nICBA+fn5atSokev0LG/vKTl37lw99dRTWrJkiU9HWczKQeVibGZsPhdjszVZjM3WZTE2m6NKNaV3\n3313ie/tdru6devmdd78+fO1fv16/frrrxowYIC2bdumwMBADRw40KOBr3hArlOnjuLj4xUfH+86\nD9xTZmX5Y01mZ5k5WPXq1Uvdu3dXRESErrvuOg0bNkwhISHq1KmTpXX17NlT/fv317XXXqtdu3bp\n3nvv1T/+8Q+Pb0BuZtbNN9+soUOHqmPHjrLb7crKytLWrVvVuXNnj2tq166dRo0apenTp8tut2v2\n7Nm6//77dejQIY+zbrjhBt1///16/fXX9eSTT0qSpkyZ4tXpLv6aVadOHSUkJOiNN97QhAkTVFhY\n6HFGsbi4OMXHx+vqq6/WgAEDdO2112rHjh3q16+fx1mRkZEaMmSIvvzyS918881e12RWDioXY3Pl\n5/hzFmOzNVmMzdZlMTabo0pNdGS2fv36admyZQoICNCSJUs0aNAgSdKAAQP0zjvvuJ3j6wXNFZHl\njzWZnfX6669r8eLFioiIUJMmTXTs2DGFhISodevWGjVqlMd5mZmZrr9KffbZZ6pfv746dOhgeV0p\nKSlKTU1VdHS0oqKidOLECTVs2NDjHDOz9u3bJ4fDoezsbNdMet4MxtLZqe/btWvn+qts8SQZQ4cO\n9Tjru+++KzHL4BdffKFrr73Wq1sk+GtWse3bt+vdd9/Viy++6HXGwYMH9fnnnysjI0NhYWFq166d\noqOjvc4DzMDYXLWzGJs9x9hc9bOKMTb7wNSTgauYxYsXG7179zYKCwtdj40cOdKYO3euT7nTp0/3\ntTTTs/yxJjOyTp8+beTn5xv5+fnGxo0bvbruqCbVZUbW+++/bxiGYWRlZRkzZsww7rvvPuOFF14w\nsrKyfM4aOnSoz1nZ2dk1JsvMbe9L1lNPPWUcO3bM49dVVA6qNsbmqp/lr2Ogv9ZlRhZjs/9kMTZ7\np0YfKZXk+itEsbS0NI9niDv3egTDMJSamqrLL79ckpSUlGRJlj/WZHbWbyUkJGjs2LFevbYm1GVW\n1pAhQ/T2229r/Pjxat68ubp3767t27fr66+/1qxZszyq6dysZs2aKTY21uescePGqXnz5mS5mWXG\nz7Fbt2666KKLNHjwYN19991e38rArBxUfYzNVTfrt/xlDPTXuhibybpQVo0cmyu87fVjP/30k/Hp\np58aOTk5xuzZs42HH37YmDlzpnH69GmPctasWWPcd999RkpKinHw4EHjnnvuMQ4dOmQcOnTI45rM\nyvLHmszOGjBggOvfPffcY8TExLi+p66KyyqeaXPQoEEXfJysmpc1ePBg49SpU8Zzzz1n9O7d23jl\nlVeMffv2GZmZmZbkoGpjbK7aWf46BvprXYzNZFVUVlUbm70/aboaePbZZxUSEqJp06YpMDBQTzzx\nhJo0aaLRo0d7lHPHHXfo2Wef1cyZM+V0OlW7dm3XSOk/CAAAIABJREFUjF6eMivLH2syO2vQoEEK\nCQnRc889p1mzZikqKkqzZs3y+C9JNaUus7IOHDighQsXKjAwUPv27ZN09n5v3sw6SFb1yLLZbKpf\nv77Gjx+vt956S3a7XfPnz9fAgQMtyUHVxthctbP8dQz017oYm8mqqKwqNzab2uJWMcX3Wxo6dGiJ\nx+Pi4rzKy8jIMB555BGjd+/ehmEYrvtOWZnljzWZmbVv3z5j2LBhRmpqqld/RappdZmR9e233xrL\nly83Jk2aZKxcudI4ffq00b9/f+Orr77yuBayqkfWk08+ecHHc3NzLclB1cbYXPWz/HUM9Ne6zMjy\n1/GBLOuyqtrYXKOb0hEjRhgffPCB8eabbxqrVq0yTp48abz33nvG/fff71HOxo0bjS5duhjdu3c3\n1q5da+zZs8cwDO8OtZuV5Y81mZ1VzIxBoSbUVRH71rp161yP+1oTWdUja/369V5nmZWDqo2xuWpn\nFfO3MdBf62JsJqsysqrC2Fyjm9Ljx48bY8aMMW699Vbj6quvNjp27Gg89thjxuHDhz3K6d+/v5GR\nkWGcOHHCiI+PN1auXGkYxv/+2mtFlj/WZHaWmYNCTaiLfYssf88ysyZUXYzNVTvLX8dAf62LfYss\nf8+qrLE5yNyTgauWhg0bKiEhweecWrVqqUGDBpLO3vT7vvvu0yWXXOLV7FRmZfljTWZnvfLKK1q1\napUMw9Djjz+uPn366Pe//73rJuDUVTFZ/lgTWdUjy8yaUHUxNlftLH8dA/21LvYtsvw9q7LG5ho9\n0VF8fLzi4uIu+M8TERERSkhI0JkzZxQaGqq5c+dqypQp+vHHHz2uyawsf6zJ7Kzi/yRhYWGaP3++\nFi9erC+++MKr/yQ1oS72LbL8PcvMmlB1MTZX7Sx/HQP9tS72LbL8PavSxmZTj7tWMbt37zZ69+5t\npKenu6bf9mYa7vz8fOPdd981zpw543rs119/NaZOnepxTWZl+WNNZmc9/fTTxvTp043s7GzDMAzj\nyJEjxu2332507NiRuiowyx9rIqt6ZJlZE6ouxuaqneWvY6C/1sW+RZa/Z1XW2GwzDC/OW6hGFixY\noMjISMXGxlpdCjxUUFCgNWvW6Pbbb1edOnUkSceOHdOrr76qcePGURcAVFGMzVWXv46B/loXgLNq\nfFMKAAAAALBOjb6mFAAAAABgLZpSAAAAAIBlaEoBAAAAAJap0fcpBfxRTk6OZs+erU8//VQhISGy\n2+0aOXKkrrvuOs2dO1eSNHLkSI0ZM0ZffvmlGjRooIKCAtWqVUvDhg1Tz549LV4DAACqF8ZmoGLR\nlAJ+5tFHH9Vll12m9evXKzAwUN99952GDx+uv/3tbyWWs9lsevzxx3XXXXdJkg4ePKhBgwYpLCxM\nN9xwgxWlAwBQLTE2AxWL03cBP+JwOHTgwAGNHTtWgYGBkqRWrVppxIgRmj9/fpmvbd68uYYMGaKl\nS5dWRqkAANQIjM1AxaMpBfzIN998o1atWrkGvWJ/+MMftGfPnnJff8UVV+jHH3+sqPIAAKhxGJuB\nikdTCvgRwzBks9nOezw3N1dFRUXlvt5ms6l27doVURoAADUSYzNQ8WhKAT/Spk0bffvttyosLJQk\nnThxQpK0Z88etW7dutzX79+/X5dffnmF1ggAQE3C2AxUPJpSwI906NBBl112mWbMmKGCggKtWrVK\ncXFxevnll/Xoo4+et7xhGK6vDxw4oKVLl+ree++tzJIBAKjWGJuBimczzv2fA8ByeXl5evHFF/XZ\nZ58pODhY9evXl2EYateunYKCglSrVi2NHDlSY8eO1ZdffqmLLrpIkhQUFKSHHnpIt956q8VrAABA\n9cLYDFQsmlKgiti8ebNuvvlmq8sAAAD/xdgMmIOmFAAAAABgGa4pBQAAAABYhqYUAAAAAGAZmlIA\nAAAAgGVoSgEAAAAAlqEpBQAAAABYhqYUAAAAAGAZmlIAAAAAgGWCrC4A8HeHDx9WbGysWrZsKUkq\nLCxUvXr1NGTIEN1+++3lvn758uUqKCjQwIEDy1xu+PDheuaZZ3T8+HE999xzWrt2rUd1tmvXTuvX\nr1fTpk3Pe+6rr77S/Pnzdfz4cRUWFqpp06YaPXq0rrjiijIzx44dq+joaN1///0e1QIAgL+48sor\nFR0drYCAANlsNuXk5Mhut2vixIlq3bq11eWdZ9WqVfrwww/1yiuvWF0KUGloSgE3hISEaNWqVa7v\njxw5oqFDhyooKEixsbFlvvarr75SdHR0ue/x6quvSpKOHz/uVY02m+2Cj+/cuVPPPPOM5s+fr1at\nWkmS1q5dq/j4eH3wwQcKCwvz6v0AAKgKbDabFi1apIsuusj12BtvvKGpU6cqKSnJwsoAFKMpBbzQ\ntGlTPfbYY1qwYIFiY2OVn5+vF198UTt37lRRUZFatWqlcePG6YsvvtAnn3yizz//XLVr19Ztt92m\nCRMm6Pjx4zp27JiaNm2qxMRENWzYUN26ddOcOXNKvM+FcsePH6969epp165dmjp1qgICAtS6dWsZ\nhnHBWufMmaNHH33U1ZBK0h133KGQkBAVFRXJMAxNmzZN33zzjbKzs2UYhqZOnap27dqVyNmzZ4+m\nTZumnJwc1apVS88884yuv/568zcuAAAmMgyjxBhZWFioI0eOqEGDBq7HXnnlFX300UcyDEMRERGa\nOHGiGjdurI8++kivvPKKAgICFBgYqKefflodOnRQVlaWpk2bppSUFBUUFOiGG27QM888o4CAAK1Y\nsULLli1TQUGBTp48qYcfflhxcXFatWqVVqxY4TpS+9Zbb+nVV1/V6tWrFRQUpEsvvVQJCQmSpF9+\n+UXDhw/XkSNHVKtWLb344ou67LLLKn3bAZWFa0oBL1155ZVKSUmRdPYoZ1BQkFauXKnVq1fr4osv\n1qxZs9S9e3d169ZNQ4cO1b333qv169erXbt2SkpK0oYNGxQSEqI1a9aU+h6vvfbaBXPz8/P1xBNP\naOzYsVq5cqWuu+465ebmXjAjOTn5vAZTkmJjYxUeHq49e/bo2LFjeuedd7Ru3Trdeeedeu2110os\nW1BQoEcffVQjR47U2rVr9dxzz2n69Ok+bD0AACrPkCFD9Mc//lGdOnXSbbfdJpvN5hrHVq9erZSU\nFK1YsUKrVq1S586dNW7cOEnSCy+8oEmTJmnFihV6/PHHtWPHDknS9OnT1bp1a7377rtatWqVTpw4\noTfffFNnzpzRihUr9I9//EMrV67U3//+d82cOdNVx7///W8tXrxYb731ljZu3KjVq1dr+fLlWrt2\nrZo1a6YlS5ZIOnvp0Pjx47V27VrFxMTojTfeqOQtBlQujpQCXrLZbKpTp44kafPmzcrMzNS2bdsk\nnW3iwsPDz3vNkCFDtGvXLi1cuFAHDhzQv//9b7Vt27bU9/j0008vmJuSkqJatWrpuuuukyT16tVL\nEyZMuGBGQEBAqUdRJemaa67R448/rqVLl+qnn37Sjh07FBoaWmKZlJQUBQUFqXPnzpKkq6++usxm\nGgAAf1J8+u6+ffv08MMP67rrrlPDhg0lnR1rv/nmG919992SpKKiIuXl5Uk6O74+8sgj6tKli268\n8UYNGzasxGuWL18uScrLy5PNZlPdunX1yiuvaNOmTUpPT9d3332nnJwcVx0tW7ZU3bp1JUnbt29X\njx49XGPus88+K+nsNaVt2rRR8+bNJUmtWrXSxx9/XNGbCLAUTSngpb1797quFS0sLNS4cePUqVMn\nSVJOTo5rQDvXCy+8oOTkZPXt21fXX3+9CgoKymwYS8s9fPjwea8LCrrwf+drrrlGX3/9tS6//PIS\nj0+ZMkWxsbFyOp2aNm2aHnjgAXXv3l2XXXbZeZMsBQYGnpf7ww8/KCoqSgEBnHABAPBvxWPmVVdd\npbFjx2rMmDFas2aNmjZtqqKiIj300EOKi4uTdPbSmVOnTkmSnnjiCfXt21eff/65Vq1apTfffFPL\nly9XYWGhZs+e7TqlNjMzUzabTT///LMGDBigAQMGqEOHDrrtttu0efNmVx3FDal0dtw+dz6IzMxM\nnT592vVcMZvNVubvCkB1wG+TgBt+OxikpaXp5Zdf1gMPPCBJ6tSpk5YsWaL8/HwVFRVp3Lhx+tvf\n/ibpbEOXn58vSdq2bZvuu+8+/fGPf1RYWJg+//xzFRUVlfq+peW2bNlShmHos88+kyRt3LjRNZD9\n1p/+9CfNnz9f+/btcz22cuVKffTRR2rZsqW2bdumbt26KS4uTldffbU2btx4Xk0tWrRQQECAtm/f\nLkn69ttvNXTo0DJrBwDAH/Xq1Utt27Z1nb570003afny5crKypIkJSYm6tlnn1VhYaG6deumnJwc\nDRgwQBMnTlRKSory8/N10003aeHChZIkp9OpESNGaMmSJfrmm2/UsGFDjRgxQh07dtSmTZsknf97\nhCTdcMMN+vjjj5WdnS3p7BwQxZlATcORUsANTqdTffr0kXT2L5a1a9fWn//8Z9fprI888ohmzpyp\nPn36uCYkKj4Np3PnzpoxY4YkaeTIkXr++ec1e/ZsBQUFKSYmRunp6a7c3yotNygoSPPmzdOECRP0\n97//XVdeeeUFTxeWpA4dOmjq1KmaOnWqcnJylJ+fr+bNm+vtt99Ww4YNFRcXp9GjR+uOO+5QUVGR\nOnbsqI8++qhERnBwsObMmaNp06bp+eefV3BwsObOnVvq0VkAAPzFhcbX8ePH684779S2bdt0zz33\n6JdfftGAAQMUEBCgSy65RAkJCQoMDNS4ceM0evRo1apVSwEBAUpISFCtWrU0fvx4TZ8+XXfccYcK\nCgrUsWNHDRs2TPn5+Vq5cqVuu+02BQYG6g9/+IMaNmzoGuvPdfPNN+vHH39UXFycbDabrrjiCj33\n3HP68MMPK2OzAH7FZnA+AAAAAADAIj6dvrtnzx7Fx8eX+vyECRNcpzACAADrvfbaa4qLi1Pfvn31\n7rvvWl0OAADeN6ULFizQ+PHjXdfK/VZSUpLrdhkAAMB6O3bs0Ndff62kpCQtWrRIR48etbokAAC8\nb0ojIyM1b968Cz63e/du7d271zWLGQAAsN7WrVsVHR2tRx55RCNGjFDXrl2tLgkAAO+b0tjY2Ave\nJuLXX3/VnDlzNHHiRKavBgDAj2RkZCg5OVkvvfSSJk2apNGjR1tdEgAA5s+++69//UsnT57UQw89\npF9//VV5eXm67LLLdNddd5X5OofDYXYpAIAaLiYmxuoS/EqDBg0UFRWloKAgtWjRQrVr19aJEyfU\nsGHDCy7P2AwAMNsFx2bDB4cOHTLuueeeUp9fuXKlMWvWLLeydu3a5VUN3r6OLP/IIYusisohiywz\na6guNm3aZDzwwAOGYRjGf/7zH+PWW281ioqKSl3eH7Y9WZWfQxZZFZVDFlmlvc7nI6XF935at26d\ncnJy1L9/f18jAQBABejSpYt27dqlfv36yTAMTZw48YL3cAQAoDL51JRGREQoKSlJktS7d+/znu/T\np48v8QAAwGR//vOfrS4BAIASfLpPKQAAAAAAvqApBQAAAABYhqYUAAAAAGAZmlIAAAAAgGVoSgEA\nAAAAlqEpBQAAAABYhqYUAAAAAGAZmlIAAAAAgGVoSgEAAAAAlqEpBQAAAABYJsjqAgAAAADAKomJ\niXI6nYqJibG6lBqLI6UAAAAAAMvQlAIAAAAALENTCgAAAACwTJW+ppTzvwEAAACgaqvSTam/qu7N\ncnVfP3iOfcIabHcAAFAd+HT67p49exQfH3/e4+vWrdM999yjgQMHatKkSb68BQAAAACgGvO6KV2w\nYIHGjx+v/Pz8Eo/n5eXppZde0uLFi7V06VJlZmZq06ZNPhcKAAAAAKh+vG5KIyMjNW/evPMeDw4O\nVlJSkoKDgyVJBQUFql27tvcVAgAAAACqLa+b0tjYWAUGBp73uM1mU8OGDSVJixYtUk5Ojm688Ubv\nKwQAAAAAVFsVMtGRYRiaOXOm0tPTNXfuXLdf53A4PHofp9Pp1evMrOFC/LUus7Kq+/qR5Tmz9wl/\nWz9/zTJzu2/cuNHnjN/yt+0FAAD8k89NqWEY5z3217/+VSEhIZo/f75HWZ7OILllyxZTZ550OBym\nZPlrXWZlVff1I8tzZu4T/rh+/ppl5navjv+vaWQBAKgafG5KbTabpLMz7ubk5Ojqq6/WypUrFRMT\no/j4eNlsNg0ZMkTdu3f3uVigKuK2HQAAAEDpfGpKIyIilJSUJEnq3bu36/F9+/b5VhUAAAAAoEbw\n6T6lAAAAAAD4gqYUAAAAAGAZmlIAAAAAgGUq5JYwVRGT0eBc7A/WYLsDAADUPDSlAADUIH369JHd\nbpckNWvWTNOnT7e4IgBATUdTCgBADeF0OmWz2fT2229bXQoAAC5cUwoAQA3x/fff68yZM3rwwQc1\ndOhQ7dmzx+qSAADgSCkAADVFSEiIHnzwQfXv318HDhzQQw89pA8//FABAfyNGgBgHZpSAABqiEsv\nvVSRkZGurxs0aKBff/1VTZo0sbgyAIA3CgsLlZqa6tay6enprjkFSsuSpMDAQJ+zJCkqKsqtLImm\nFACAGuPdd99VSkqKJk6cqJ9//lnZ2dlq3Lhxma9xOBxevZe3ryPLP3LIIquicvwxy+l0mpZVrLKy\n0tPT9fpnDtkbXexW1rJ9B0t97ugP3ymjMFAhYeHuFbZpd6lP5WYc16S7b3H9IbQ8NKUAANQQ/fr1\n09ixY3XvvfcqICBA06dPL/fUXW9u0eRwOEy7tRNZlZ9DFlkVleOvWVu2bDH1lnSVuY52u132fQfV\noElTn98r89gvyikMVN1w9xrc8rRu3VrR0dElHiutwaYpBQCghqhVq5ZefPFFq8sAAKAEZjYAAAAA\nAFiGphQAAAAAYBmaUgAAAACAZWhKAQAAAACW8akp3bNnj+Lj4897/JNPPlG/fv0UFxen5cuX+/IW\nAAAAACySmJiojRs3Wl0GqjmvZ99dsGCB3nvvPdWrV6/E4wUFBZoxY4ZWrlyp2rVra+DAgerWrZvC\nw9283w0AAAAAoMbw+khpZGSk5s2bd97jqampioyMVGhoqGrVqqWYmBjt2rXLpyIBAAAAANWT101p\nbGysAgMDz3s8KytLdrvd9X29evWUmZnp7dsAAIAaitMGAaBm8Pr03dKEhoYqKyvL9X12drbq169v\n9tvgHIWFhUpNTXVr2fT09BJ/NLiQqKioC/7BoaLqcqemwsJCSSq3LneyJPPW0Sz++jP0V/66b7Gf\n/k956+jutnInS/K/bQUAANznc1NqGEaJ76OiopSenq7Tp08rJCREO3fu1IMPPuhWlsPh8Oi9nU6n\nV6+rSlnFyspKT0/XpJUbFRLm5nW7m3aX+lRuxnFNuvsWRUZGlrqMu+uXnp6uk3+dpmYhdcpcLlTS\ngTKXkHadylDS9V3cW8cy1k8ydx3d4U5WZf8Mz+VP+7wn+5bb26uc/eFUeqrat26lBo2blBv1cfrm\nMp//6ftvdcoIVL3wRuXXtXN/mU9nHz+mp3p09Lv99PXPHLI3utitzGX7Dpb63NEfvlNGYaAl+zwA\nAPAvPjelNptNkrRu3Trl5OSof//+Gjt2rB544AEZhqH+/fvr4ovd+wUmJibGo/fesmWLnE6nx6+r\nSlnS2V8Sy8qy2+0K2bRbdcPd287lad26taKjo0t93t31s9vtOhBSRy3q1CtzOXccys1RSFi4362j\nO9zJquyfYbHy9i13mbW9PNm3zNpeuRnH1aBxE4U3beZz1slfflaBAmVv/DufsyT/3E/t+w6qQZOm\nPr9f5rFflFMYWKH7vJl/GIT7EhMTTR0DAQDVn09NaUREhJKSkiRJvXv3dj3epUsXdenSxafCAAAA\nAADVn0/3KQUAAAAAwBemT3QEAAAA+DNOMwf8C0dKAQAAAACW4Uipn+MveQAAAACqM46UAgAAAAAs\nQ1MKAAAAALAMTSkAAAAAwDI0pQAAAAAAy9CUAgAAAAAsQ1MKAAAAALAMTSkAAAAAwDI0pQAAAAAA\ny9CUAgAAAAAsQ1MKAAAAALBMkNUFAAAAVCWJiYlyOp2KiYmxuhQAqBY4UgoAAAAAsIxXR0oNw9Ck\nSZO0f/9+BQcHa9q0aWrevLnr+ddff13r169XYGCghg8fru7du5tWMCqWUVSktLS0MpcpKChQQUGB\nUlJSylwuLS1NNjOLAwD47Pjx4+rbt6/efPNNtWjRwupyAADwrindsGGDnE6nkpKStGfPHiUkJGj+\n/PmSpMzMTC1evFgbNmxQdna27rrrLprSKiTvVIaeXrRGIWHhpS7TNezsAfbBcxaXmXUqPVVzTK0O\nAOCLgoICTZw4USEhIVaXAgCAi1dNqcPhUKdOnSRJbdu2VXJysuu5OnXqKCIiQtnZ2Tpz5owCAjhD\nuKoJCQtX3fCLS33epgxJUt3wRmXm5GYclw6nm1obAMB7zz//vAYOHKhXX33V6lIAAHDxqmPMysqS\n3W53fR8UFKSioiLX902aNFHPnj3Vt29fxcfH+14lAADwycqVKxUeHq6OHTvKMAyrywEAwMWrI6Wh\noaHKzs52fV9UVOQ6IvrZZ5/p2LFj2rRpkwzD0IMPPqj27durTZs25lRsocLCQqWmppa7nLvXXEZF\nRSkwMNCs8gBUI2Ze381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0Nfb53c4yc99yR8Hl17i1nDusuL+ou9ursvcHf1TZ+5YVPFlH\nr5rS2NhYbdu2TXFxcZKkhIQELVy4UJGRkSosLNSuXbuUn5+vzZs3y2azafTo0Wrbtm25uefe/NZu\ntytnb3IZSwMAcFbr1q3P+wOpmb9QVxevvvqqTp8+rfnz52vevHmy2WxasGCBgoODS31NVRibL/Tz\nvxCHw1FifX7LbrfrgB/W5Y4tW7bI6XT6nGN2lmTO+knu12W32/Xzvzb5/H6SufvWx+ml3xe8unBn\ne1mxP2jnfp/fz2xm7lvL9h00szTTeDI2e9WU2mw2TZ48ucRjLVq0cH29Z88eb2IBAEAFGjdunMaN\nG2d1GQAAlMC0ewAAABZJTEw09agkAFRFXk10BAAAAACAGWhKAQAAAACW4fRdoIINzLO6AgAAAMB/\ncaQUAAAAAGAZmlIAAAAAgGU4fRcAAFR7zHILAP6LI6UAAAAAAMtwpBQAAKCGKCwsVGpqapnLFBQU\nqKCgQCkpKeXmRUVFKTAw0K/qSktLU12fKwJQmWhKAQAAaojU1FRt7TNQzULqlLpMQfebFCDpwMAH\nysw6lJsjrVqq6OhoU+rqN2W2QsLCS12ma9jZE/wGz1lcZtap9FQt+F1Dn2sCUHloSgH47AuFWV0C\nAFRbZh9FbBZSRy3q1Ct1mb02mySVuUxFCAkLV93wi0t93qYMSVLd8EZl5uRmHDe1LgAVj6YUAADA\nj5l9FHGOqdUBgO9oSgEAAPycqUcRD6ebWhsA+IrZdwEAAAAAluFI6X9xTRzOxf5gDbY7AAAw+zrq\nysTvMt6hKQUAAADgN1JTUzVx4TI1aNyk1GUan8mVJP19/eYys376/lupYek58A9eN6WGYWjSpEna\nv3+/goODNW3aNDVv3tz1/LJly/TOO++oVq1a+tOf/qQuXbqYUS8AAACAaq5B4yYKb9qs1OcD/n1M\nkspcRpJO/vKzTphaGSqC103phg0b5HQ6lZSUpD179ighIUHz58+XJB07dkyLFi3SqlWrlJubq4ED\nB6pjx46qVauWaYUDAAAAAKo+ryc6cjgc6tSpkySpbdu2Sk5Odj23d+9excTEKCgoSKGhobr00ku1\nf/9+36sFAAAAAFQrXh8pzcrKkt1u/19QUJCKiooUEBBw3nN169ZVZmamb5UCAAAAgMn2h0ZYXUKN\n53VTGhoaquzsbNf3xQ1p8XNZWVmu57Kzs1W/fn2P3+PAkSPellfCoV9+OXtfLh/lnT6pA//5jwkV\nSYd/Paa6uTnlLldgGJKktJzsUpf5T16uKesnnV1Hs+SdPqlDbqyjO/x5HQ86bT7nHM08rdxg89bv\n5K8/l7tc48JCSdLxI4dKXeb0iWPKzc43rS6zmJ3lzvZyx+kTx5RtBJqSlZORofzgXJ9z3N1WRtjZ\nz+8zGb+UmZV5rPTnPZGVcVy5heZsK7M+GwAzFRqGW7N+ujODaGXPHgoAlc3rprR9+/batGmTevTo\nod27dys6Otr13O9//3slJibK6XQqLy9PP/74o6644opyMx0Oh+vrwsJCFTZrqrIng3ZP47ZtNOEa\nm6tp9lZhYRsV2Ww64GOOJDW56QbZOt2orHKyir7/XpKUNe6pUpe5orBQE2y+r590dh1tJmeVt47u\n8Pd1/NXHrP+zYP2+//5XSVJsZHjpWc06mr6tqnWWmdur/eWmZLm/P5z9rBnT9Uqfs9yqq2VT07Ik\n6eTJkyXGEMBqR/NylbhojULCSv+MlaSu//2D0OA5i0td5lR6qi6KjDK1PgDwJ143pbGxsdq2bZvi\n4uIkSQkJCVq4cKEiIyPVtWtXxcfH695775VhGHrqqacUHBxcbmZMTEyJ76+99tpyX+NwOM57nbf8\nMau4ub/77rtNqMq8uvxxW5HlGfYtss7lr/uDL1k0qbBaSFi46oZfXOYyNmVIkuqGNyp1Gc4GAFDd\ned2U2mw2TZ48ucRjLVq0cH3dv39/9e/f3/vKAAAAymEUFZl6mqzvF2QAADzldVMKAABgtbxTGcre\n4VDWT4fLXK4oN1dBkrI2by11mR+SkxVd6rMAgIpCUwoAAKq0S3/3O10e0azMZTb/d5KuspZL/9mc\nyQwBAJ4xZ4YJAAAAAAC8QFMKAAAAALAMTSkAADXInj17FB8fb3UZVdqdW7/SnVu/sroMAKg2uKYU\nAIAaYsGCBXrvvfdUr149q0sBAMCFI6UAANQQkZGRmjdvntVlwM9xJBhAZaMpBQCghoiNjVVgYKDV\nZQAAUAKn7wIAAMBjhYahtLS0cpdLT0+X3W4vcxl3cipbYVGR23WVt47+uH5mM9zcXlV1fzCTu9tK\nqjn7Fk0pAAA1jGEYbi/rcDhcX6enpyuqIgpClXQ0L1eJi9YoJCy8/IU37S7z6VPpqboo0r/2riOn\nT2mGu+snlbmOp9JT1a1rF3MK81N5pzL0tIn7Q3XeXh5tK6ncfavdtdeaVJm5kpOTlZmZ6dayNKUA\nANQwNpvN7WVjYmJcX9vtduXsTa6IklBFhYSFq274xT7n5GYcN6Ea81X39TMb28t9NWFbtW7dWtHR\n0SUeO/cPnefimlIAAGqQiIgIJSUlWV0GAAAuNKUAAAAAAMvQlAIAAAAALENTCgAAAACwDBMd+bkn\nnnii1AuCAQAAAKCq86opzcvL09NPP63jx48rNDRUM2bMUFhYWIllZs6cqa+++kqFhYW655571L9/\nf1MKBgAAAFCzFVx+jdUlwERenb67dOlSRUdHa8mSJbrzzjs1f/78Es9/+eWXOnjwoJKSkrRkyRL9\n4x//cPseNQAAAACAmsOrI6UOh0MPPfSQJKlz587nNaXt2rXTVVdd5fq+qKhIQUGcKQwAAKzxYNv2\nVpdwQV8orPyFAKCaK7dTXLFihd56660SjzVq1EihoaGSpHr16ikrK6vE88HBwQoODlZBQYHGjh2r\nAQMGqE6dOiaWDQAAAACoDsptSvv166d+/fqVeGzUqFHKzs6WJGVnZ8tut5/3utOnT+uxxx7T9ddf\n7zqqCgAAAPNxxBVAVebVObXt27fX5s2b1aZNG23evFkdOnQo8XxeXp6GDh2qBx54QL1793Y719tZ\nZs2cnZasys8hy5osp9NpWlYx9q2qm+XP+4PZWQAAwL941ZQOHDhQzz77rO69914FBwdr1qxZkqQX\nXnhBPXr0kMPh0KFDh7Rs2TK98847stlsSkhIUERERJm5MTExHtficDi8eh1Z/pFDlnVZW7ZskdPp\n9Lu6/HFb1YSsmJgYv6zLlywaWQAAqgavmtKQkBDNnj37vMeffvppSVKbNm00dOhQnwoDAAAAAFR/\nXt0SBgAAAAAAM9CUAgAAAAAsQ1MKAAAAALCMV9eUAqj6nnjiCSaCAQBUGdz2Bqi+OFIKAAAAALAM\nTSkAAAAAwDI0pQAAAAAAy3BNKQAAMM3wLrdYXQIAoIrhSCkAAAAAwDI0pQAAAAAAy9CUAgAAAAAs\nQ1MKAAAAALAMTSkAAAAAwDI0pQAAAAAAy9CUAgAAAAAsQ1MKAAAAALAMTSkAAAAAwDJeNaV5eXl6\n7LHHNGjQIA0fPlwZGRkXXC4nJ0d33XWXtm7d6lORAADAd4ZhaOLEiYqLi9OQIUN08OBBq0sCAMC7\npnTp0qWKjo7WkiVLdOedd2r+/PkXXG7KlCkKCOBgLAAA/mDDhg1yOp1KSkrS6NGjlZCQYHVJAAB4\n15Q6HA517txZktS5c2dt3779vGXeeOMNtW/fXi1btvStQgAAYAqHw6FOnTpJktq2bavk5GSLKwIA\nQAoqb4EVK1borbfeKvFYo0aNFBoaKkmqV6+esrKySjy/fft2paena/Lkyfrqq69MLBcAAHgrKytL\ndrvd9X1QUJCKioo8OqvpwJEjptRy6JdflJtx3OecvNMndeA//zGhIunwr8dUNzfHlKz/5OWasn7S\n2XU0S97pkzpUA9bxoNPmc87RzNPKDTZv/U7++rMpWadPHFNudr4pWWZvdzOzzNxe2UagKVk5GRnK\nD871OcfsbZV57BdTsrIyjiu30Jxt5elng80wDMPTNxk1apQefvhhtWnTRllZWRo4cKDWrl3ren70\n6NE6evSoAgMDlZaWpvDwcD3//PO68sorS810OByelgEAQJliYmKsLsGvzJgxQ9dcc4169OghSerS\npYs+/fTTUpdnbAYAmO1CY3O5R0ovpH379tq8ebPatGmjzZs3q0OHDiWenzVrluvrsWPHqlevXmU2\npKUVBwDA/7d331FR3O8awB8EQRTEEqOJIcYSFQs21KNEQGMXj6JUYcGCGAQrMWJExBKxR+PGGGIX\ng2jEisRcCxrEoGIBRTEiWKI5EUTcpSwrvPcP7+7FksgMA7vo+zmH88P9ZR/enS0Ps+x8h0mna9eu\nOHnyJAYPHozLly+jdevW//nfczczxhirCqKOKfXw8MCff/6JMWPGYM+ePQgMDAQArFixAqmpqZIO\nyBhjjDFpDBgwAMbGxnB3d8fSpUsxZ84cXY/EGGOMifv4LmOMMcYYY4wxJgU+XwtjjDHGGGOMMZ3h\nnVLGGGOMMcYYYzrDO6WMMcYYY4wxxnSGd0oZY4wxxhhjjOkM75QyxhhjjDHGGNMZUecpZe8uIoKB\ngYHo66tUKmzevBkXL15EYWEh6tevj969e8PV1RWGhoYVmi0nJwcNGzasUAZQ8dtY1uPHj5GZmYmW\nLVuiXr16kmRKoSK3Ucr70N3dHYsXL0arVq1EzcLeLkqlEmZmZroeg7Fqh7tZGO7m/8bdzMqqqm6u\nVn8pjY6O/tcvKeTk5Ii63meffYbExERJZnj8+DFCQkIwZMgQ9OvXD2PGjMHKlSuRn58vKCc3Nxff\nfPMNHB0d4eDggOHDh2PBggWibuPdu3cxYcIE9O3bFx06dICrqyuCgoLw6NEjwVnz5s1Do0aNEBwc\nDHt7e3Tu3BlFRUVYsGCB4KzMzMwXvvz9/bXfCyXlbfTz8wMAxMfHw8PDAzt27ICXlxdOnDghOOvb\nb78F8Py2Ojs7w87ODu7u7jq9jVLeh3l5eZg7dy6+++47KJVKwdcvS8ptJeVzWvNcjIiIwI0bNzBg\nwAAMHjwYly5dEpxVXFz8wpdMJoNarUZxcbHgLCm318uCgoJEXc/W1hZ79uyp8M9nVYu7ufy4m4Xh\nbi4/7mZhuJvLr8q6maqRJUuW0IABA2jdunWvfIlx+/btF75cXFy03wsxYsQImjRpEn311Vd09+5d\nUbNoTJ48mRITE6moqIhiY2Np06ZNdPToUZo2bZqgHD8/P4qNjSWFQkGlpaWkUCjo8OHD5OPjI3im\n8ePHa7fJpUuX6Ntvv6XU1FSaOHGi4CxPT88X/u3r60tERB4eHoKz7O3tadCgQSSTycjLy4tsbGzI\ny8uLZDKZ4Cwpb6Pm548ZM4ZycnKIiEipVJK7u7voLD8/P7pw4QIREV2/fp3Gjh0rOEuq2yjlfSiT\nyUitVtPmzZtp0KBBNG/ePPqf//kfun79uqgsImm2lZTPaV9fX4qJiSG5XE69evWijIwMevDgwSvb\nsTy6detGvXv3pn79+lHfvn2pY8eO1LdvX+rXr5/gLCm3l729Pdna2mq/2rdvr/1eCFdXV1qwYAHJ\nZDJKSkoSPAfTDe7m8uNuFoa7ufy4m4Xhbi6/qurmavXx3Tlz5uD27duws7ODtbV1hfPGjRuHWrVq\n4f333wcRITMzE6GhoTAwMMD27dvLnVO3bl1s2LABv/32G2bMmAELCwv06dMHlpaW+PzzzwXN9OTJ\nE/Tq1QsAMHToUIwfPx6bN2/G5s2bBeUolUoMHTpU+28zMzMMGzYMO3fuFJSjyWrevDkAoHPnzli9\nejWmT5+Op0+fCs4CgCNHjqBPnz44fvw4TE1NcfPmTahUKsE5e/fuxfz58+Hh4QFbW1vIZDLs2LFD\n1ExS3sZnz54BAMzNzbUfC6pTpw5KS0tFzQYAhYWF6NatGwCgbdu22p8hhJS3Uar7kIhgZGSEcePG\nwcvLC4mJiTh79ix++eUXbNiwQXAeIM22kvI5XVBQACcnJwDAuXPn0KJFCwAQ9RGt6OhoLF++HDNn\nzkSbNm0q9JjXkGJ7rVixAlu2bEFYWBjef/990XOZmJggNDQUqampiIiIwMKFC9GrVy9YWlrC29tb\ncB6rGtzN5cfdLAx3szDczeXH3Vx+VdXN1WqnFACWLVuGgoICSbKkeuEkIgDAwIEDMXDgQGRkZCAx\nMRGJiYmCnyR16tRBREQE7OzscPz4cTRu3Bjnzp0TPFPDhg0hl8thZ2cHMzMz5Ofn49SpU2jUqJHg\nrI8++gihoaGws7NDfHw8rKys8Ntvv8HU1FRw1tKlS7F8+XKsX78ebdu2xbx583DmzBnMnz9fcFbD\nhg2xZs0aLFu2DKmpqYKvX5aUt9HCwgLDhg3D06dPsX37dri5uWH69Ono3Lmz4KysrCz4+/tDqVTi\n6NGj6NevH7Zt24batWsLzpLqNmruw++//x5WVlYVug+trKy039esWRP29vawt7cXnANIu62kfE5b\nWFhg/fr18Pf3x7Zt2wAABw4cgImJieC5WrZsiVWrViE0NBQODg4VOr5Kyu3VvXt3WFpaIjQ0FOPH\njxc9l2a7d+zYEevWrYNCocD58+cl+dgSq1zczeXD3SwMd3P5cTdzN7+sunWzAWl+UjVw+/Zt7TsZ\nUnn27BmWLVuGhg0b4syZM6KKLyIiQnusQkXl5eVhw4YNyMjIgJWVFfz8/HDhwgU0b94cH3/8cblz\nVCoVoqKikJycDKVSCXNzc3Tt2hXu7u6oVauWoJmKi4uxZ88e3Lp1C1ZWVhg9ejRSU1PRrFkz1K9f\nX+hNRFFREdLT07UH4rdu3brCixfExMQgJiYGkZGRoq4v9W0Enh8HpVar0ahRI5w5cwZ2dnaicu7e\nvYurV6/i/fffR4cOHSCXy+Hn54e6desKyqmM2wgAN27cQNu2bUVfX61WIz09HQqFAnXr1sWnn34K\nY2NjUVmv21aTJk2Cubm5oBwpn9OFhYXYvXs3fHx8XsgfPXp0hRb/WLduHQ4fPoyjR4+KzpDqsaVR\nXFyMhQsXIjk5GXFxcYKvv2/fPu0716z64G7mbv433M1vxt1cftzNb3c3V6ud0nbt2sHPzw8BAQGo\nWbOmpNkVfeEsKyEhAZ999pkEU0knKSkJhoaGsLGxEXX9kydPwsTEBL1799ZeduzYMfTv319QTnx8\nPL777js0a9YMly9fhrW1Nf7++2/MmjVL1GxSzQU8/3hW7dq1YWRkhAMHDsDAwAAjRowQXMp5eXnI\nysqCtbU19u3bh6tXr6JVq1ZwdXWFkZHwDyfk5uaifv36uHPnDq5fv45WrVqJXhFPiu2VkJDwwr9X\nrFiBWbNmAYDgx/2pU6ewcuVKfPLJJ6hduzby8/Nx+/ZtzJw5U9R9ePPmTZiYmKBZs2bay65cuYJO\nnToJyomOjoarq6tkKz2WlZqaCoVC8cJ9IFZFn9dSzlX2F5iaNWvC2tpa1C8wCoUCBgYGMDMzw9Gj\nR/H06VM4OTmJeu6wqsHdLB5385txN5cPd3PFcDf/t6ro5mq1UyqTyeDg4ICDBw9i7NixGDZsmOh3\nbaT08gqDW7Zswbhx4wAAbm5ugrL+a6UuIbc1Pj4eYWFhqFu3LgYNGoTz58/DxMQEnTp1wuTJkwXN\nFBYWBoVCgWfPnqGwsBByuRzGxsbw9vYWdHwP8Pw+3LRpE4yNjZGbm4vly5dj7ty58PPzw88//6yz\nufbs2YNNmzYBeP5xh+LiYpiamqJGjRoIDQ0VlDVhwgS4ubnhypUrePLkCfr27Yvz588jOzsbq1at\nEpS1cOFCNG3aFA0bNsS2bdtgY2ODK1euYNCgQZgwYYKgLKm218iRI1GjRg20adMGAPD777+jT58+\nAIDw8HBBM7m7u2Pjxo0vLDWuUCgwduxY7N27V1CWXC7HmTNn8OzZM7Rr1w5hYWEwMDAQ9Xjo3r07\n2rdvjwULFrxQomIcO3YMS5YsQY0aNSCTyXDs2DGYm5ujefPm2l8Yyut1z2tjY2N07txZ8PNa6rlW\nrVpV4V9gdu3apT1Gz8HBATk5OWjQoAGUSqXgxxarOtzN3M2VNRd3M3dzWdzNb3k3V9oSSpVAsyLV\nw4cPKTw8nAYOHEj+/v60ZMkSUXkvr/BX9ksIX19fcnV11a422LdvX9ErDw4cOJC6deumXcGr7P8K\n4eLiQkqlkjIzM6lHjx6kVquptLSU3NzcBM9UdmW67du3k7+/PxEReXl5Cc4aMWIEFRcXExFRfn4+\njRkzhoiIRo8erdO5XFxcqKSkhLKzs19YlUwznxCan//yHGK2veY6Y8aMofz8fCIiUqvVNGrUKMFZ\nUm2vgoICCg4Opt27d4u6flmjRo0itZr85wkAABoKSURBVFr9wmUqlUrU48HV1ZVKS0uJiGjp0qU0\nf/580fN5eXnRpUuXaNSoURQcHEwXL14UnKHh7OxMeXl59PDhQ+rduzepVCoiEvd4KPu87tmzZ4We\n11LO5ebmRgqF4oXLnj59Kvhx6uzsTMXFxaRQKMjBwUF7f4p5HrKqw91cftzNwnA3lx93szDczcJm\nqopurlafh6L/+6NukyZNEBwcjNmzZ+PmzZuiD7T9+uuvce/ePbRo0UKbDUDwCn8RERFYs2YNSkpK\nMHXqVCQlJSEwMFDUTFFRUZgwYQK2bt0KCwsLURkAUFpaClNTU3zyySeYOnWq9s/rJOIP4yUlJSgu\nLoaxsTFkMhkePHiAxYsXi5pr6NChcHFxQY8ePXDhwgWMGTMGP/30E9q1a6fTuUpLS1FYWIiGDRtq\nFwUoLi6GWq0WnGVkZISUlBR07doV58+fR/fu3ZGcnIwaNYSfFpiI8OTJE1haWqKoqAi1a9eGUqnU\n6f1oamqK8PBwbN68GaGhoSgpKRGcoeHm5gYnJyd069YN5ubmUCqVSE5OhkwmE5xFZU46Pnv2bAQF\nBWHjxo2iPuZjYGCAzp07Y+/evThx4gS2bduGr776CmZmZti3b5+grJKSEtSpU0ebq5lHzIqPZZ/X\nU6ZMqfDzWqq51Gr1K8fDmZiYCN72JSUlKCoqQl5eHgoKClBQUABjY2NR53pjVYe7ufy4m4Xhbi4/\n7mbu5pdVu26WdBe3kp0+fVrSvIKCAho1ahT9/fffkuT9+uuvFBgYSK6urhXK+f333ykxMbFCGZGR\nkeTo6EglJSXaywIDA0kulwvOOnToEA0YMEB7Xq/S0lKaO3cuWVlZiZotPT2d4uLiKCMjg4hIm6vL\nuX799VcaOHDgC9vLy8tL+46jEHfu3CFvb29ydHSkNm3aUNeuXWn06NGizu8VHx9Pjo6ONHPmTLK1\ntaUvvviCPv/8c4qNjRWcJfX9SESUmJhIQUFBoq9PRPTo0SM6fvw4HTx4kE6cOEGPHj0SlbNlyxYa\nPXo05ebmEtHzd3XHjx9P1tbWgrP+7R1cMY/VjRs3koODA3l6etLMmTPJ29ub/Pz86LvvvhOcJeXz\nWsq5oqOjydHRkebPn08rV66ksLAwGj58uODnz4EDB8jW1pYmTJhAS5cupcGDB5OTkxNFRUUJnolV\nHe7m8uNuFoa7WRzu5jfjbi6/qurmanVMqdQHqQPA1atXoVar0aVLF0lm/PPPP3HgwAF8+eWXkuRV\nhOYgfI3MzEztubCEUqlUryyTnZaWJvhdVJVKhc2bNyM5ORlFRUWoX78+evfuDVdXVxgaGupsLuD5\nu1Bl3zFVKpUvHE8hZrYnT56gXr16opYY18jPz8elS5e092e7du3QoEED0TNVdHvFxcVhyJAhKCgo\nwLp163D9+nV06NAB/v7+2nf3hMyza9cuJCYmalf4s7GxgZeXl+CVKAHg3r17+PDDD194LIlZXCM7\nOxvvvfee4J//bxQKhXZ5/9OnT8PCwkJ7/jGhpHxeSzlXdnY2UlJSkJ+fDzMzM3Ts2LHC2zA9PR3m\n5ub48MMPK5TDKhd3szDczcJwN5cPd7Nw3M3iVFY3C//Mgg7NnDkT//zzD1auXInk5GT07t0bd+7c\nwezZs0VndujQocKlp1mqPjs7G+vWrcPRo0cxY8YMZGdnC85yd3fHrVu3KjSPJicnJ+eFyypSer/8\n8guio6ORl5eHSZMmwcPDQ9RHXubNm4dGjRphzpw5sLe3R+fOnVFUVIQFCxYIzsrNzcXKlSvh6OgI\nBwcHDB8+HAsWLEDjxo1FZYWHh7+QtWrVqle2YXmzlixZgm3btiE3NxeOjo4YPHgwLl++LDhLs+13\n7NiBXbt2ITIyEjExMSgqKhKVtWvXLsTGxuLhw4eQyWTw8fERXDBRUVEAgG+++QYWFhaYN28emjRp\nInjRCQCYM2cOVCoVZsyYgWXLlmH69OkoLS1FUFCQ4CyVSoUTJ04gICAAnp6e+OKLL7Bx40ZRq22+\n/IItZh6NHTt2wNzcHE+ePMHMmTMRHh6OyMhI0a8PUj2vpZxLpVIhNjYW0dHRiIqKQnR0NPbv3y/4\ncZqVlYWpU6fiyy+/xJ07d9CmTRt8+OGHos6zx6oOd7OwHO5mYVnczeXD3SwMd3P5VVk3S/p310om\n5UHqRESPHz+mxYsX07Bhw8je3p4cHR0pLCyMsrOzBeVoFnmYNm0aHTx4kAoLC+n48eM0adIkwTMN\nHjyYXF1dae3ata8cnKyLHCKigIAAWr16NS1atIgGDhxI8fHxdO3aNVEHqXt6er7wb19fXyIi8vDw\nEJzl5+dHsbGxpFAoqLS0lBQKBR0+fJh8fHx0muXr60sxMTEkl8upV69elJGRQQ8ePHjltpfHjBkz\n6Mcff6Tr16/T3bt36fr16/Tjjz/S5MmTBWdNnz6d1q1bR19//TX179+fEhMT6fLlyzR27FhBOZrH\n+8u3R3O5EP+2TcQ8HqTcVvb29mRra6v9at++vfZ7ofTx9UHquaTa9l5eXvT777/TyZMnaejQoXTt\n2jXt5Ux/cTdXfQ4Rd7NQ3M3lx90sDHezNKrVX0pfPkgdgOiD1AEgODgYXbp0wa5du3Dy5ElERUXB\nxsZG9DsvOTk5GD58OGrVqoV+/fqhoKBAcEajRo2wc+dOmJubw9nZGaGhoTh27Bhu3Lihkxzg+Uez\nZsyYgZCQENSsWRP29vaiPoKjceTIESgUCuzfvx+mpqa4efMmVCqV4BylUomhQ4fCzMxMe+6kYcOG\niTrwWsqsgoICODk5ISAgAJ9++ilatGiBDz74QNRB/f/88w/8/PzQtm1bWFpaom3btvDz80Nubq7g\nrEePHiEwMBCLFi2CsbExevXqhU6dOgk+eD4rKwtbt26FkZER0tLSADw/j5aYbWViYoL9+/cjJycH\nxcXFePz4Mfbv34/atWsLzpJyW61YsQLW1taIiYlBQkICunTpgoSEhFfOAyeEPr0+SD2XlNv+s88+\ng4ODA9atW4dZs2bh4cOHlXJOOiYd7uaqzwG4m4Xibi4/7mZhuJulUa12SoOCgrBq1SqcOHECMpkM\nNjY2CA8PF/XRBEC6F7ubN29i8eLFePbsGc6ePYvS0lLExcWJmomIYGRkhHHjxuHQoUP4/PPPceHC\nBaxZs0YnORpRUVHYsGEDnjx5gsTERKSkpIj6hWPp0qX49ddf4e7ujoSEBMybNw9paWmiPgLQsGFD\nyOVypKSk4Pbt20hNTYVcLkejRo10mmVhYYH169eDiLBt2zYAwIEDB0Qdu/K6Yti3b5+oYjAyMsLB\ngwdRo0YNHDhwAMDzEzwLLb4NGzagTp06+OSTT7QnZF60aJGo+3DlypW4evUqJk6cCEdHR/j6+uLq\n1atYtmyZ4Cwpt1X37t0RGhqK0NBQnDt3rkIvvPr4+iD1XFL9AmNkZIQTJ06gpKQELVq0wLx58zBp\n0iRRH1tiVYe7uepzNLiby4+7ufy4m4XhbpZGtVroqFOnTggJCcGIESOQm5tb4YPUp06ditatW8PO\nzg5mZmbIz8/HqVOn8Oeff2Lt2rXlzsnLy0NaWhquXr2Kli1bomfPnggJCcGXX36Jpk2bCpppyZIl\n+Prrr4XelErLAYCHDx9i69atsLKyQuPGjbFixQpYWFggJCQELVu2FJSVkJAg6jiC11GpVIiKikJy\ncjKUSiXMzc3RtWtXuLu7Cz4WQ8qswsJC7N69Gz4+PtrLIiIiMHr0aDRs2FBQVm5uLr7//ntcvHgR\n+fn5qFOnDrp27Qp/f3/BWdnZ2YiIiHjhcbFgwQLIZDK0aNFCUJZmNs22qlevnuDraygUChgZGWkP\n6geAv/76S/Bzp+y20iyEIXZbaRQXF2PhwoVITk4WXQr/9voQFBSEjz76SFCWlM9rKeeS6nH68OFD\nrF27FsHBwdrH1B9//IHw8HDtL2tM/3A3V30OwN3M3fzvs3E3vxl3s/51c7XaKXVzc0P79u1x69Yt\nTJkyBd27d69QnlQvdlK+mEuVpY8zAYC1tTUGDRqEkJCQCp3r7XVSUlKgVCrRu3dvvcpKTU2FQqEQ\nnaVSqXDjxg0UFBSgfv36aNOmjeh3B1UqFdLT07VZrVu3FpyVkpKChQsXorS0FHXq1NGem23+/PmC\nFybZs2cPfvrpJ5SWlsLNzQ0TJ04EAHh7ews6H+Hr3Lt3DzVq1BBcoK9z8eJFNG7cWJIsKee6ceMG\n2rZtK/r6JSUlMDQ0hFKpRGZmJpo1a4a6detWeC72buFurvocqbO4m4XjbhaHu/nN3tVuNgwLCwvT\n9RDldejQIaxZswatWrXC5s2bsX79emRmZiIrKwudOnUSnGdkZITOnTtj6NChGDlyJBo0aIAmTZrg\n448/FpTj6OiIjIwM9OzZU9RS2a/L6tGjR4WypMrRZN2+fVuS25eYmIgRI0Zg9uzZyM3NRbNmzUQv\n7X7s2DH4+vpix44dICJERkYiPT0daWlpsLW11ZusHTt2iM6Kj4/HV199haysLOzcuRP37t3D1q1b\n0bx5c8FLcWuyMjMzERkZKTpr+vTpWLt2LXx9fTFq1Ci4u7vDzs4Oc+fOhaurq6CZwsLCsHfvXnh6\neiI6OhqZmZmwsbFBTEwMRo0aJSgrJSUFfn5+OHbsGIgIixYtwtGjR2FoaIj27dtXKGvVqlWSZVVk\nroSEBNy9e1f7tWDBAlhaWuLu3buCX7d++OEH/PHHH1Cr1QgICEBGRgZ+/PFHWFhYoE2bNoKy2LuN\nu7nqczRZ3M3is7ib/x13M3ezTki6bFIle3mVp6dPn9Lx48dp48aNovJOnjxJ9vb2NHz4cJLL5eTj\n40N+fn70/fffC54rLi6Ohg4dSuvWravQCb+lytLHmYj+f1WxgoIC2r59O7m4uNDIkSMpICBAcJaz\nszPl5eXRw4cPqXfv3qRSqYhI3IqP+prl5eWlvf7jx48pODiYFAqFqBXwpMpydnZ+5bLS0lJycXER\nPFPZbaJWq8nHx4cOHTokarVANzc3un//PiUlJVHXrl0pPz+fiouLRW13fc0aMWIEOTk5UXBwMAUH\nB5Otra32e6FGjx5NpaWl5OnpqT3xeH5+Pjk5OQnOcnR0fGFFxLJfushhVYu7uXrPRMTdLBR3s7As\nfexT7uaqz3kTcWe11pGX350xNzdHv379ROetX78esbGxePToEdzc3HDmzBkYGhrCw8MDkydPLneO\ngYEBBg8eDHt7e/zyyy+YMmUK1Go1mjZtCrlcLmgmqbL0cSbg+cHgAGBqagqZTAaZTKb9eIJQJSUl\n2hNCGxgYaD/qInRxAH3OUigU2uubmJjg7t27MDMzE7WanlRZ9vb2GDt2LGxtbWFubg6lUomEhATY\n2dkJnqlLly6YMmUKlixZAnNzc6xduxbjxo3D/fv3BWeVlpaiadOmaNq0Kby8vLQH8ov5OJW+ZkVF\nRWHhwoXo2rUrXFxcIJPJEB4eLjgHAGrUqAG1Wo333ntPe8yQkZG4SpDL5Zg5cyZ27txZob/YSJXD\nqhZ3M3dzWfrap9zN5cfdLAx3szSq1TGlUnN2dsbu3btRo0YN7Ny5E56engCeHx8THR1d7hyZTKY9\nSbeG5sW8Y8eOgmaSKksfZwIq/jn7sjZt2oTIyEg0bdoUjRs3RnZ2NmrVqoUOHTpgypQpb0VWREQE\njhw5gh49euDChQsYM2YMcnNzce/ePSxcuFBnWWlpaUhOTkZ+fr520QKxpyJISkpCly5dYGxsDOD/\njycbO3asoJxvv/0WKSkp2LRpk3b1Sc3xNUKPUtDXLI3NmzcjKysLt27dws8//ywqIyYmBtHR0Wjf\nvj0uXLiAHj164Ny5c3B2doa3t7fgvAMHDqBevXqwt7cXNY/UOaz64m6u+izuZu7ml3E3C8fdXEGS\n/t21momMjCRHR0cqKSnRXhYYGEhyuVxQzvXr1yWbSaosfZzpdZYsWVKh6z99+pTUajWp1Wo6fvw4\nnT9//q3LSk9PpyNHjtCtW7eIiLQf59BV1pEjR4iISKlU0tKlS8nHx4dWrFhBSqWywlljx44VnUVE\nlJaW9sK/z549+8Lz+23I0khMTKSgoKAKZdy9e5d27dpFP/zwA+3atYvS09MrlMeYFLibqz7rZdzN\nb8bdXH762qfczfqlWp2nVGqenp7Yvn37C+f0mjlzJgICAgTlvPzuotg/2UuZpY8zAYC7u7v2y83N\nDXv37tX+Wwxzc3MYGRnByMgISUlJsLGxET2bvma1bt0aQ4YMQcuWLREeHo4GDRroNCsqKgrA88dB\nvXr1MG/ePDRp0kTUOQnLZmlOZSA2Ky4uDlZWVigoKMCyZcswbtw4JCQkoLCw8K3KAp6fBP706dPI\nzs7GypUrkZ+fLyrL0tISjo6OyMvLQ1xcHA4ePCgqKygoCDk5OYKvV1k5rHrjbq76LO5m4biby0ef\n+5S7uWpz3uSd/vjuvXv3tCvXRURE4Nq1a2jVqhW++OILmJublzun7Is2ESEjIwOtWrUCAOzatUvQ\nTFJl6eNMwPNVGvfu3Yu5c+fC1NQUQUFBWL16NQAIXoZbX2/j256lWRLey8sLkZGRr1wuRGVkzZ07\nF5aWlhgwYADOnj2LS5cuYdWqVZz1L1khISGwtLRE//79RWf169cPFhYW8PLywqhRo0SfFkGqHFa9\ncTdXfRZ3c/XP4m5+u7LeyW6u2j/M6hcPDw/6448/KCQkhORyOaWlpdG2bdto4sSJgnIOHjxIPj4+\ndPPmTbp37x65urrS/fv36f79+4JnkipLH2fSSEtLI19fX8rIyBC1kltlzMVZ5denTx/asmULeXt7\n07Vr14iIKCUlRdSKdVJmaR5Lnp6er72csyovy8vLi/Ly8mjRokXk6OhIGzZsoLS0NFIoFDrJYdUb\nd3PVZxFxN1f3LO5mznpZdevmd/rju4aGhujZsyfu37+PgIAAWFlZwdvbGwqFQlDO8OHDMXv2bCxf\nvhzFxcUwMTHRrugllFRZ+jiThpWVFVasWIFVq1YhNzcXAEStWKevt/Ftz9qwYQPMzMzQokULpKen\nQ6FQYNGiRZg9e7bgmaTMysrKwtatW2FoaIi0tDQAz0+OLuaxxVnCGBgYoG7duggJCcG2bdtgbm6O\n9evXw8PDQyc5rHrjbq76LIC7ubpncTdz1suqXTdLuotbzfj7+1NcXBxt2bKF9u3bR0+ePKEDBw7Q\nuHHjROXl5ubS5MmTydHRkYhIe94pXWbp20zHjx8nBwcH6t+/Px06dIiuXLlCROLeAZJyLs4qv7L3\n4eHDh7WXi7kPpcy6du0a7dmzh8LCwigmJoaePn1KLi4udPHiRc6q5KwZM2a89vKioiKd5LDqjbu5\n6rO4m6t/FnczZ72sunXzO71TmpOTQ8HBwTRw4EBq37492dra0tSpU+mvv/4SlCPli7lUWfo4ExGR\ni4sL5ebm0uPHj0kmk1FMTAwRvXry9aqei7PKT8r7sLIeD/pUyO9aVmxsrOgsqXJY9cbdXPVZ3M3V\nP4u7mbP+K6s6dLO4s7G+JRo0aFCh1eo0NmzYgH379oGIMG3aNDg5OcHa2lp7MmpdZOnjTABQs2ZN\n1KtXD8DzE6T7+Pjggw8+EHXQtL7exrc9S8r7sDIfD8XFxXBycpJkW3GWsCyVSiUqS6ocVr1xN1d9\nFndz9c/ibuasN2Xpeze/0zulMpkMarX6tf+fkBXP9PGFQB9nAp6v4hceHo5p06bBzMwMcrkcEyZM\nwNOnT3U6F2eVn5T3IT8eOKuyZmLVF3dz1Wfxa3H1z+Ju5qzKyqqybq74H1urr8uXL5OjoyPduXNH\nu9KZmBXPZs2aRUuWLKH8/HwiInrw4AENGTKEbG1tBc8kVZY+zkREpFarae/evVRQUKC97NGjR7R4\n8WKdzsVZ5SflfciPB86qrJlY9cXdXPVZ/Fpc/bO4mzmrsrKqqpvf6Z1SIqKffvqJfvvttwpl6OML\ngT7OJDV9vY3vQpY+0tdtxVm6mYlVb9zNVZslJX29je9Clj7S123FWbqZ6b8YEPHBOowxxhhjjDHG\ndOOdPk8pY4wxxhhjjDHd4p1SxhhjjDHGGGM6wzuljDHGGGOMMcZ05p0+JQxj+qiwsBBr165FfHw8\natWqBXNzcwQGBqJnz56Qy+UAgMDAQAQHByMpKQn16tXDs2fPULNmTfj6+mLo0KE6vgWMMcbY24W7\nmbHKxTuljOmZgIAAtGjRArGxsTA0NMT169cxadIkrF69+oX/zsDAANOmTcPIkSMBAPfu3YOnpyfq\n16+PXr166WJ0xhhj7K3E3cxY5eKP7zKmR5KTk5GVlYU5c+bA0NAQAGBlZQV/f3+sX7/+P69raWkJ\nb29vREVFVcWojDHG2DuBu5mxysc7pYzpkdTUVFhZWWlLT6N79+64cuXKG6//6aef4vbt25U1HmOM\nMfbO4W5mrPLxTiljeoSIYGBg8MrlRUVFKC0tfeP1DQwMYGJiUhmjMcYYY+8k7mbGKh/vlDKmRzp2\n7Ihr166hpKQEAPD48WMAwJUrV9ChQ4c3Xj89PR2tWrWq1BkZY4yxdwl3M2OVj3dKGdMjNjY2aNGi\nBZYuXYpnz55h3759cHd3xw8//ICAgIBX/nsi0n6flZWFqKgojBkzpipHZowxxt5q3M2MVT4DKvvM\nYYzpnEqlwsqVK3H69GkYGxujbt26ICJ06dIFRkZGqFmzJgIDAzFnzhwkJSXBwsICAGBkZISJEydi\n4MCBOr4FjDHG2NuFu5mxysU7pYxVE6dOnYK9vb2ux2CMMcbY/+FuZkwavFPKGGOMMcYYY0xn+JhS\nxhhjjDHGGGM6wzuljDHGGGOMMcZ0hndKGWOMMcYYY4zpDO+UMsYYY4wxxhjTGd4pZYwxxhhjjDGm\nM7xTyhhjjDHGGGNMZ3inlDHGGGOMMcaYzvwvljcdfpowWV4AAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1173f01d0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"scores = qscore.loc[qratings_mean.index, 'Score']\n",
"colors = sns.diverging_palette(220, 10, as_cmap=True)(scores / scores.abs().max())\n",
"fig, axes = plt.subplots(nrows=5, ncols=2, gridspec_kw={'hspace': 0.35}, figsize=(16, 25))\n",
"for col, ax in zip(qratings_mean.columns, axes.flat):\n",
" qratings_mean[col].plot(kind='bar', yerr=qratings_std[col], color=colors, legend=False, width=1, ax=ax, error_kw={'ecolor': 'gray'}, title=col)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:06.649908",
"start_time": "2016-08-27T18:00:06.647218"
},
"collapsed": false
},
"outputs": [],
"source": [
"ratingcols = ['Effort', 'Level', 'Conceptual', 'Interest', 'Tedious', 'Context', 'Check My Work', 'Correct?', 'Detailed Calc', 'Research']\n",
"scorecols = ['Upvotes', 'Downvotes', 'Score', 'Approval', 'Wilson Lower 2', 'Wilson Lower 1', 'Wilson Upper 1', 'Wilson Upper 2']"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This computes the correlations between various measures of score and the ratings. I normalize each column to zero mean and unit standard deviation using `zscore` before computing the correlation, otherwise we get weird results like the same factor being correlated with both upvotes and downvotes! (Actually, it still happens, a bit, e.g. with asking for a detailed calculation, the next-to-last factor)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:07.030171",
"start_time": "2016-08-27T18:00:06.651209"
},
"collapsed": false
},
"outputs": [],
"source": [
"# Use expanding window but we really only want the last element, corresponding to the whole sequence\n",
"correlations = qscore[scorecols].apply(spst.zscore).expanding().corr(\n",
" pairwise=True,\n",
" other=qratings_mean.apply(spst.zscore)\n",
").iloc[-1,:,:]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The strongest correlations seem to occur with interest and context, which indicates that people tend to upvote questions that are interesting and (more so) downvote those which are not, and also upvote questions which provide a physical context and downvote those which do not."
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:07.411617",
"start_time": "2016-08-27T18:00:07.031491"
},
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x117c39780>"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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3+PwlrCeSrhHi421R/tr6b6lepTxv92ptHgjPX7vNG5/+yLz+HcxLPe3BqNGjWbN2HT/8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\nCvPgbUnyhBBCCCGEECKXzEKc5UmSJ4QQQgghhBC5GPNiUl4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l9u6D59YXOWUaja/0Kghe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\nCCFWkP8A2m8/e/FOxtgAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1173df278>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(16, 5))\n",
"sns.heatmap(correlations, annot=True)"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:07.426784",
"start_time": "2016-08-27T18:00:07.412783"
},
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Effort</th>\n",
" <th>Level</th>\n",
" <th>Conceptual</th>\n",
" <th>Interest</th>\n",
" <th>Tedious</th>\n",
" <th>Context</th>\n",
" <th>Check My Work</th>\n",
" <th>Correct?</th>\n",
" <th>Detailed Calc</th>\n",
" <th>Research</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Upvotes</th>\n",
" <td>0.148273</td>\n",
" <td>0.217743</td>\n",
" <td>-0.011375</td>\n",
" <td>0.212158</td>\n",
" <td>-0.107551</td>\n",
" <td>0.379700</td>\n",
" <td>0.114359</td>\n",
" <td>-0.158452</td>\n",
" <td>-0.259192</td>\n",
" <td>-0.099042</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Downvotes</th>\n",
" <td>-0.035003</td>\n",
" <td>-0.162502</td>\n",
" <td>-0.154530</td>\n",
" <td>-0.474895</td>\n",
" <td>0.178645</td>\n",
" <td>-0.332984</td>\n",
" <td>0.102870</td>\n",
" <td>-0.089512</td>\n",
" <td>-0.355703</td>\n",
" <td>-0.284199</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Score</th>\n",
" <td>0.163353</td>\n",
" <td>0.291312</td>\n",
" <td>0.060237</td>\n",
" <td>0.430365</td>\n",
" <td>-0.189426</td>\n",
" <td>0.530953</td>\n",
" <td>0.065879</td>\n",
" <td>-0.115821</td>\n",
" <td>-0.092588</td>\n",
" <td>0.033253</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Approval</th>\n",
" <td>0.095191</td>\n",
" <td>0.091956</td>\n",
" <td>-0.058501</td>\n",
" <td>0.544496</td>\n",
" <td>-0.057679</td>\n",
" <td>0.594331</td>\n",
" <td>0.148292</td>\n",
" <td>-0.106553</td>\n",
" <td>-0.017308</td>\n",
" <td>0.012379</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Wilson Lower 2</th>\n",
" <td>0.190454</td>\n",
" <td>0.319437</td>\n",
" <td>0.109858</td>\n",
" <td>0.519210</td>\n",
" <td>-0.243530</td>\n",
" <td>0.568267</td>\n",
" <td>-0.034007</td>\n",
" <td>-0.057220</td>\n",
" <td>0.026212</td>\n",
" <td>0.156597</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Wilson Lower 1</th>\n",
" <td>0.183851</td>\n",
" <td>0.309774</td>\n",
" <td>0.080748</td>\n",
" <td>0.474303</td>\n",
" <td>-0.216906</td>\n",
" <td>0.554764</td>\n",
" <td>0.019201</td>\n",
" <td>-0.091580</td>\n",
" <td>-0.042778</td>\n",
" <td>0.090595</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Wilson Upper 1</th>\n",
" <td>0.144379</td>\n",
" <td>0.275290</td>\n",
" <td>0.051279</td>\n",
" <td>0.367079</td>\n",
" <td>-0.165672</td>\n",
" <td>0.487916</td>\n",
" <td>0.098728</td>\n",
" <td>-0.134314</td>\n",
" <td>-0.140776</td>\n",
" <td>-0.018874</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Wilson Upper 2</th>\n",
" <td>0.134326</td>\n",
" <td>0.247903</td>\n",
" <td>0.041829</td>\n",
" <td>0.292249</td>\n",
" <td>-0.139063</td>\n",
" <td>0.439026</td>\n",
" <td>0.118905</td>\n",
" <td>-0.150043</td>\n",
" <td>-0.191708</td>\n",
" <td>-0.065697</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Effort Level Conceptual Interest Tedious Context \\\n",
"Upvotes 0.148273 0.217743 -0.011375 0.212158 -0.107551 0.379700 \n",
"Downvotes -0.035003 -0.162502 -0.154530 -0.474895 0.178645 -0.332984 \n",
"Score 0.163353 0.291312 0.060237 0.430365 -0.189426 0.530953 \n",
"Approval 0.095191 0.091956 -0.058501 0.544496 -0.057679 0.594331 \n",
"Wilson Lower 2 0.190454 0.319437 0.109858 0.519210 -0.243530 0.568267 \n",
"Wilson Lower 1 0.183851 0.309774 0.080748 0.474303 -0.216906 0.554764 \n",
"Wilson Upper 1 0.144379 0.275290 0.051279 0.367079 -0.165672 0.487916 \n",
"Wilson Upper 2 0.134326 0.247903 0.041829 0.292249 -0.139063 0.439026 \n",
"\n",
" Check My Work Correct? Detailed Calc Research \n",
"Upvotes 0.114359 -0.158452 -0.259192 -0.099042 \n",
"Downvotes 0.102870 -0.089512 -0.355703 -0.284199 \n",
"Score 0.065879 -0.115821 -0.092588 0.033253 \n",
"Approval 0.148292 -0.106553 -0.017308 0.012379 \n",
"Wilson Lower 2 -0.034007 -0.057220 0.026212 0.156597 \n",
"Wilson Lower 1 0.019201 -0.091580 -0.042778 0.090595 \n",
"Wilson Upper 1 0.098728 -0.134314 -0.140776 -0.018874 \n",
"Wilson Upper 2 0.118905 -0.150043 -0.191708 -0.065697 "
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"correlations"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:07.432133",
"start_time": "2016-08-27T18:00:07.428094"
},
"collapsed": false
},
"outputs": [],
"source": [
"from IPython.display import HTML\n",
"fmt_dict = {'URL': lambda s: re.sub('/questions/(\\d+).*$', '/q/\\\\1', s)}\n",
"def linkify(s):\n",
" '''Turns simple http(s) URLs into links'''\n",
" return re.sub(r'(https?://[\\w./]+)', r'<a href=\"\\1\">\\1</a>', s)\n",
"def display_link_table(df):\n",
" '''Displays a DataFrame as a table, turning URLs into links'''\n",
" return HTML(linkify(df.to_html(formatters=fmt_dict)))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Here are the questions which were most consistently judged to show physical context (or not)"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:07.598582",
"start_time": "2016-08-27T18:00:07.433373"
},
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Context</th>\n",
" <th>Score</th>\n",
" <th>URL</th>\n",
" </tr>\n",
" <tr>\n",
" <th>QID</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>247999</th>\n",
" <td>5.000000</td>\n",
" <td>18</td>\n",
" <td><a href=\"https://physics.stackexchange.com/q/247999\">https://physics.stackexchange.com/q/247999</a></td>\n",
" </tr>\n",
" <tr>\n",
" <th>271004</th>\n",
" <td>5.000000</td>\n",
" <td>2</td>\n",
" <td><a href=\"https://physics.stackexchange.com/q/271004\">https://physics.stackexchange.com/q/271004</a></td>\n",
" </tr>\n",
" <tr>\n",
" <th>256585</th>\n",
" <td>5.000000</td>\n",
" <td>0</td>\n",
" <td><a href=\"https://physics.stackexchange.com/q/256585\">https://physics.stackexchange.com/q/256585</a></td>\n",
" </tr>\n",
" <tr>\n",
" <th>248024</th>\n",
" <td>3.333333</td>\n",
" <td>-3</td>\n",
" <td><a href=\"https://physics.stackexchange.com/q/248024\">https://physics.stackexchange.com/q/248024</a></td>\n",
" </tr>\n",
" <tr>\n",
" <th>271287</th>\n",
" <td>3.000000</td>\n",
" <td>-1</td>\n",
" <td><a href=\"http://physics.stackexchange.com/q/271287\">http://physics.stackexchange.com/q/271287</a></td>\n",
" </tr>\n",
" <tr>\n",
" <th>163014</th>\n",
" <td>2.400000</td>\n",
" <td>-5</td>\n",
" <td><a href=\"https://physics.stackexchange.com/q/163014\">https://physics.stackexchange.com/q/163014</a></td>\n",
" </tr>\n",
" </tbody>\n",
"</table>"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"display_link_table(\n",
" qratings_mean.sort_values('Context', ascending=False).iloc[[0,1,2,-3,-2,-1]] \\\n",
" .join(qscore)[['Context', 'Score', 'URL']]\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"And the most/least interesting ones"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:07.609064",
"start_time": "2016-08-27T18:00:07.599981"
},
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Interest</th>\n",
" <th>Score</th>\n",
" <th>URL</th>\n",
" </tr>\n",
" <tr>\n",
" <th>QID</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>256585</th>\n",
" <td>4.000000</td>\n",
" <td>0</td>\n",
" <td><a href=\"https://physics.stackexchange.com/q/256585\">https://physics.stackexchange.com/q/256585</a></td>\n",
" </tr>\n",
" <tr>\n",
" <th>7671</th>\n",
" <td>3.500000</td>\n",
" <td>11</td>\n",
" <td><a href=\"http://meta.physics.stackexchange.com/a/7671/124\">http://meta.physics.stackexchange.com/a/7671/124</a></td>\n",
" </tr>\n",
" <tr>\n",
" <th>271004</th>\n",
" <td>3.500000</td>\n",
" <td>2</td>\n",
" <td><a href=\"https://physics.stackexchange.com/q/271004\">https://physics.stackexchange.com/q/271004</a></td>\n",
" </tr>\n",
" <tr>\n",
" <th>253583</th>\n",
" <td>1.666667</td>\n",
" <td>1</td>\n",
" <td><a href=\"https://physics.stackexchange.com/q/253583\">https://physics.stackexchange.com/q/253583</a></td>\n",
" </tr>\n",
" <tr>\n",
" <th>163014</th>\n",
" <td>1.600000</td>\n",
" <td>-5</td>\n",
" <td><a href=\"https://physics.stackexchange.com/q/163014\">https://physics.stackexchange.com/q/163014</a></td>\n",
" </tr>\n",
" <tr>\n",
" <th>247829</th>\n",
" <td>1.500000</td>\n",
" <td>-8</td>\n",
" <td><a href=\"https://physics.stackexchange.com/q/247829\">https://physics.stackexchange.com/q/247829</a></td>\n",
" </tr>\n",
" </tbody>\n",
"</table>"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"display_link_table(\n",
" qratings_mean.sort_values('Interest', ascending=False).iloc[[0,1,2,-3,-2,-1]] \\\n",
" .join(qscore)[['Interest', 'Score', 'URL']]\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Regression analysis "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's go beyond simple correlation to a partial least-squares regression. This technique attempts to find the linear combination of one set of factors (here, the rating criteria - effort, interest, etc.) that best predicts the variation in a set of responses (here, the score)."
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:07.615926",
"start_time": "2016-08-27T18:00:07.610387"
},
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"PLSRegression(copy=True, max_iter=500, n_components=1, scale=True, tol=1e-06)"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pls = skcd.PLSRegression(n_components=1)\n",
"pls.fit(qratings_mean, qscore[['Score']])"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:07.620143",
"start_time": "2016-08-27T18:00:07.617331"
},
"collapsed": false
},
"outputs": [],
"source": [
"predicted_scores = pd.Series(pls.predict(qratings_mean)[:,0], index=qratings_mean.index)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The following plot shows that, according to the PLS analysis, the rating criteria are fairly useless at predicting the score."
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:07.820864",
"start_time": "2016-08-27T18:00:07.621718"
},
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.legend.Legend at 0x118c7bef0>"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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45hxH8vPzycnJCTqGdMy8lpUIvI6VKLyWdVTefRe+9a2gU9TzOtbRmD9/PiUlJVx99dVB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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x118c7bc50>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(qscore['Score'].sort_values(), qscore['Score'].sort_values(),\n",
" '-r',\n",
" linewidth=0.3,\n",
" label='Predicted = Actual')\n",
"plt.errorbar(qscore['Score'], predicted_scores,\n",
" label='Partial least squares',\n",
" xerr=np.abs(qscore.as_matrix(['Wilson Lower 2', 'Wilson Upper 2']) - qscore.as_matrix(['Score'])).T,\n",
" linestyle='None',\n",
" marker='o',\n",
" elinewidth=0.5,\n",
" markersize=8)\n",
"plt.xlabel('Actual score')\n",
"plt.ylabel('Predicted score')\n",
"plt.legend()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"If we do it with the maximum number of components (10, same as the number of factors), it's equivalent to regular least-squares regression."
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:07.828925",
"start_time": "2016-08-27T18:00:07.822293"
},
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"PLSRegression(copy=True, max_iter=500, n_components=10, scale=True, tol=1e-06)"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pls = skcd.PLSRegression(n_components=10)\n",
"pls.fit(qratings_mean, qscore['Score'])"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:07.832537",
"start_time": "2016-08-27T18:00:07.830141"
},
"collapsed": true
},
"outputs": [],
"source": [
"predicted_scores = pd.Series(pls.predict(qratings_mean)[:,0], index=qratings_mean.index)"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:08.029189",
"start_time": "2016-08-27T18:00:07.834100"
},
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.legend.Legend at 0x118d04d30>"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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4cKAeeOABffzxx4qOjtYVV1yhyspKZWRk6M4771R8fLxiY2N144036vTp09q/f79+//vf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\nAAAAAMuj3AIAAAAALI9yCwAAAACwPMo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"text/plain": [
"<matplotlib.figure.Figure at 0x118d04ef0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(qscore['Score'].sort_values(), qscore['Score'].sort_values(), '-r', linewidth=0.3, label='Predicted = Actual')\n",
"plt.errorbar(qscore['Score'], predicted_scores,\n",
" label='Partial least squares',\n",
" xerr=np.abs(qscore.as_matrix(['Wilson Lower 2', 'Wilson Upper 2']) - qscore.as_matrix(['Score'])).T,\n",
" linestyle='None',\n",
" marker='o',\n",
" elinewidth=0.5,\n",
" markersize=8)\n",
"plt.xlabel('Actual score')\n",
"plt.ylabel('Predicted score')\n",
"plt.legend()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's try something else: repeating the scores in each row of ratings"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:08.144690",
"start_time": "2016-08-27T18:00:08.030618"
},
"collapsed": false
},
"outputs": [],
"source": [
"# nan-filling trick from https://stackoverflow.com/a/19966142/56541\n",
"qalldata = qratings.join(qscore)[ratingcols + scorecols].groupby(level=0).transform(lambda x: x.fillna(x.mean()))"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:08.168150",
"start_time": "2016-08-27T18:00:08.146016"
},
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th></th>\n",
" <th>Effort</th>\n",
" <th>Level</th>\n",
" <th>Conceptual</th>\n",
" <th>Interest</th>\n",
" <th>Tedious</th>\n",
" <th>Context</th>\n",
" <th>Check My Work</th>\n",
" <th>Correct?</th>\n",
" <th>Detailed Calc</th>\n",
" <th>Research</th>\n",
" <th>Upvotes</th>\n",
" <th>Downvotes</th>\n",
" <th>Score</th>\n",
" <th>Approval</th>\n",
" <th>Wilson Lower 2</th>\n",
" <th>Wilson Lower 1</th>\n",
" <th>Wilson Upper 1</th>\n",
" <th>Wilson Upper 2</th>\n",
" </tr>\n",
" <tr>\n",
" <th>QID</th>\n",
" <th>Rating ID</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th rowspan=\"4\" valign=\"top\">7671</th>\n",
" <th>1</th>\n",
" <td>4.0</td>\n",
" <td>2.0</td>\n",
" <td>3.000000</td>\n",
" <td>3.0</td>\n",
" <td>3</td>\n",
" <td>4.0</td>\n",
" <td>1.0</td>\n",
" <td>0</td>\n",
" <td>1.0</td>\n",
" <td>4.00</td>\n",
" <td>13</td>\n",
" <td>2</td>\n",
" <td>11</td>\n",
" <td>0.866667</td>\n",
" <td>3.635405</td>\n",
" <td>7.851166</td>\n",
" <td>12.889944</td>\n",
" <td>13.879162</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>5.0</td>\n",
" <td>2.0</td>\n",
" <td>3.000000</td>\n",
" <td>3.0</td>\n",
" <td>2</td>\n",
" <td>5.0</td>\n",
" <td>1.0</td>\n",
" <td>1</td>\n",
" <td>0.0</td>\n",
" <td>1.00</td>\n",
" <td>13</td>\n",
" <td>2</td>\n",
" <td>11</td>\n",
" <td>0.866667</td>\n",
" <td>3.635405</td>\n",
" <td>7.851166</td>\n",
" <td>12.889944</td>\n",
" <td>13.879162</td>\n",
" </tr>\n",
" <tr>\n",
" <th>57</th>\n",
" <td>5.0</td>\n",
" <td>2.0</td>\n",
" <td>1.000000</td>\n",
" <td>5.0</td>\n",
" <td>4</td>\n",
" <td>5.0</td>\n",
" <td>1.0</td>\n",
" <td>0</td>\n",
" <td>1.0</td>\n",
" <td>2.50</td>\n",
" <td>13</td>\n",
" <td>2</td>\n",
" <td>11</td>\n",
" <td>0.866667</td>\n",
" <td>3.635405</td>\n",
" <td>7.851166</td>\n",
" <td>12.889944</td>\n",
" <td>13.879162</td>\n",
" </tr>\n",
" <tr>\n",
" <th>64</th>\n",
" <td>5.0</td>\n",
" <td>2.0</td>\n",
" <td>2.333333</td>\n",
" <td>3.0</td>\n",
" <td>5</td>\n",
" <td>5.0</td>\n",
" <td>1.0</td>\n",
" <td>0</td>\n",
" <td>1.0</td>\n",
" <td>2.50</td>\n",
" <td>13</td>\n",
" <td>2</td>\n",
" <td>11</td>\n",
" <td>0.866667</td>\n",
" <td>3.635405</td>\n",
" <td>7.851166</td>\n",
" <td>12.889944</td>\n",
" <td>13.879162</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"4\" valign=\"top\">163014</th>\n",
" <th>36</th>\n",
" <td>5.0</td>\n",
" <td>2.0</td>\n",
" <td>1.000000</td>\n",
" <td>1.0</td>\n",
" <td>3</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>1</td>\n",
" <td>0.0</td>\n",
" <td>5.00</td>\n",
" <td>5</td>\n",
" <td>10</td>\n",
" <td>-5</td>\n",
" <td>0.333333</td>\n",
" <td>-10.447103</td>\n",
" <td>-8.108932</td>\n",
" <td>-1.318845</td>\n",
" <td>2.485936</td>\n",
" </tr>\n",
" <tr>\n",
" <th>52</th>\n",
" <td>5.0</td>\n",
" <td>2.0</td>\n",
" <td>3.000000</td>\n",
" <td>3.0</td>\n",
" <td>5</td>\n",
" <td>5.0</td>\n",
" <td>0.0</td>\n",
" <td>1</td>\n",
" <td>1.0</td>\n",
" <td>3.00</td>\n",
" <td>5</td>\n",
" <td>10</td>\n",
" <td>-5</td>\n",
" <td>0.333333</td>\n",
" <td>-10.447103</td>\n",
" <td>-8.108932</td>\n",
" <td>-1.318845</td>\n",
" <td>2.485936</td>\n",
" </tr>\n",
" <tr>\n",
" <th>66</th>\n",
" <td>4.0</td>\n",
" <td>2.0</td>\n",
" <td>2.000000</td>\n",
" <td>2.0</td>\n",
" <td>2</td>\n",
" <td>2.0</td>\n",
" <td>0.0</td>\n",
" <td>1</td>\n",
" <td>1.0</td>\n",
" <td>4.00</td>\n",
" <td>5</td>\n",
" <td>10</td>\n",
" <td>-5</td>\n",
" <td>0.333333</td>\n",
" <td>-10.447103</td>\n",
" <td>-8.108932</td>\n",
" <td>-1.318845</td>\n",
" <td>2.485936</td>\n",
" </tr>\n",
" <tr>\n",
" <th>76</th>\n",
" <td>4.0</td>\n",
" <td>2.0</td>\n",
" <td>2.000000</td>\n",
" <td>1.0</td>\n",
" <td>3</td>\n",
" <td>3.0</td>\n",
" <td>0.0</td>\n",
" <td>1</td>\n",
" <td>1.0</td>\n",
" <td>3.75</td>\n",
" <td>5</td>\n",
" <td>10</td>\n",
" <td>-5</td>\n",
" <td>0.333333</td>\n",
" <td>-10.447103</td>\n",
" <td>-8.108932</td>\n",
" <td>-1.318845</td>\n",
" <td>2.485936</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Effort Level Conceptual Interest Tedious Context \\\n",
"QID Rating ID \n",
"7671 1 4.0 2.0 3.000000 3.0 3 4.0 \n",
" 27 5.0 2.0 3.000000 3.0 2 5.0 \n",
" 57 5.0 2.0 1.000000 5.0 4 5.0 \n",
" 64 5.0 2.0 2.333333 3.0 5 5.0 \n",
"163014 36 5.0 2.0 1.000000 1.0 3 1.0 \n",
" 52 5.0 2.0 3.000000 3.0 5 5.0 \n",
" 66 4.0 2.0 2.000000 2.0 2 2.0 \n",
" 76 4.0 2.0 2.000000 1.0 3 3.0 \n",
"\n",
" Check My Work Correct? Detailed Calc Research Upvotes \\\n",
"QID Rating ID \n",
"7671 1 1.0 0 1.0 4.00 13 \n",
" 27 1.0 1 0.0 1.00 13 \n",
" 57 1.0 0 1.0 2.50 13 \n",
" 64 1.0 0 1.0 2.50 13 \n",
"163014 36 0.0 1 0.0 5.00 5 \n",
" 52 0.0 1 1.0 3.00 5 \n",
" 66 0.0 1 1.0 4.00 5 \n",
" 76 0.0 1 1.0 3.75 5 \n",
"\n",
" Downvotes Score Approval Wilson Lower 2 Wilson Lower 1 \\\n",
"QID Rating ID \n",
"7671 1 2 11 0.866667 3.635405 7.851166 \n",
" 27 2 11 0.866667 3.635405 7.851166 \n",
" 57 2 11 0.866667 3.635405 7.851166 \n",
" 64 2 11 0.866667 3.635405 7.851166 \n",
"163014 36 10 -5 0.333333 -10.447103 -8.108932 \n",
" 52 10 -5 0.333333 -10.447103 -8.108932 \n",
" 66 10 -5 0.333333 -10.447103 -8.108932 \n",
" 76 10 -5 0.333333 -10.447103 -8.108932 \n",
"\n",
" Wilson Upper 1 Wilson Upper 2 \n",
"QID Rating ID \n",
"7671 1 12.889944 13.879162 \n",
" 27 12.889944 13.879162 \n",
" 57 12.889944 13.879162 \n",
" 64 12.889944 13.879162 \n",
"163014 36 -1.318845 2.485936 \n",
" 52 -1.318845 2.485936 \n",
" 66 -1.318845 2.485936 \n",
" 76 -1.318845 2.485936 "
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"qalldata.head(8)"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:08.176650",
"start_time": "2016-08-27T18:00:08.169985"
},
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"PLSRegression(copy=True, max_iter=500, n_components=1, scale=True, tol=1e-06)"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pls = skcd.PLSRegression(n_components=1)\n",
"pls.fit(qalldata[ratingcols], qalldata['Score'])"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:08.181692",
"start_time": "2016-08-27T18:00:08.177940"
},
"collapsed": true
},
"outputs": [],
"source": [
"predicted_scores = pd.Series(pls.predict(qalldata[ratingcols])[:,0], index=qalldata.index)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Even here, there is basically no predictive value. The algorithm predicts wildly different scores from different survey responses even for a single question."
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:08.393661",
"start_time": "2016-08-27T18:00:08.183274"
},
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.legend.Legend at 0x118cd08d0>"
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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wwQd9Umwlyeb+8ZhzAMnMzFRycrLRMYAW41qGFXAdwyq4ltEs+/ZJV11ldIoaXMdojuXL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\nAAAAyyPcAgAAAAAsj3ALAAAAALC8/w8FD8ew24wrewAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x118cd0d68>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.plot(qscore['Score'].sort_values(), qscore['Score'].sort_values(), '-r', linewidth=0.3, label='Predicted = Actual')\n",
"plt.errorbar(qalldata['Score'], predicted_scores,\n",
" label='Partial least squares',\n",
" xerr=np.abs(qalldata.as_matrix(['Wilson Lower 2', 'Wilson Upper 2']) - qalldata.as_matrix(['Score'])).T,\n",
" linestyle='None',\n",
" marker='o',\n",
" elinewidth=0.5,\n",
" markersize=8)\n",
"plt.xlabel('Actual score')\n",
"plt.ylabel('Predicted score')\n",
"plt.legend()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Principal component analysis"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Principal component analysis attempts to determine the linear combinations of factors which capture the most variance in the collected data. In our case, with 10 factors, it's like plotting them in a 10-dimensional space and then rotating the resulting cluster to see which dimension it is most spread out along.\n",
"\n",
"By applying this to the ratings we can determine how consistent they are."
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:08.402527",
"start_time": "2016-08-27T18:00:08.395103"
},
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"PCA(copy=True, n_components=None, whiten=False)"
]
},
"execution_count": 31,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pca = skd.PCA()\n",
"pca.fit(qalldata[ratingcols].apply(spst.zscore))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This shows that about 30% of the variance is accounted for by one dimension, about 17% by the next orthogonal dimension, and 14% by the next orthogonal dimension. There is no dimension that's particularly negligible relative to the previous one."
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:08.407631",
"start_time": "2016-08-27T18:00:08.403831"
},
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"array([ 0.30742263, 0.16544336, 0.13702009, 0.09297218, 0.08270651,\n",
" 0.07330201, 0.04674457, 0.0398007 , 0.036227 , 0.01836094])"
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pca.explained_variance_ratio_"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:08.615619",
"start_time": "2016-08-27T18:00:08.409970"
},
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.text.Text at 0x11948a6a0>"
]
},
"execution_count": 33,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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9e1wf9rl6pe3x4eJ7wKB973vf2//2T37yk3zve99LY2NjTj311EyfPv2ITrxg\nwYJs27YtixYtSvKbq7rr1q3LlClTMn/+/P6Pe/4V2gsvvDArV67M1q1b09TUdERXggEAAHjlqfka\n2v/9v/93Nm7cmNNPPz09PT25+OKLs2zZsrzvfe+ruXhDQ0PWrFlzyGPTpk17wcfdd999/W8fffTR\nuemmm45kdgAAAF7Bagbt7bffnrvuuivNzc1Jko9+9KM5//zzjyhoAQAAoCo1f23Psccem6am33Xv\nUUcdlXHjxlU6FAAAANRS8wrtq1/96px33nl55zvfmaampvyf//N/0tzcnOuvvz5Jsnz58sqHBAAA\ngP+/mkE7adKkTJo0Kd3d3enu7s6pp55aj7kAAADgsGoG7RlnnJHXve51hzz2t3/7t1m4cGFlQwEA\nAEAtNV9De8kll+Tmm29OkvzqV7/Kxz72MXchBgAAYMjVDNq77rorO3fuzKJFi/KBD3wgM2fOzDe/\n+c16zAYAAAADqhm0fX19GTlyZH7961+nr68vDQ0NGTGi5qcBAABApWqW6dlnn51JkyblzjvvzB13\n3JHt27fn/e9/fz1mAwAAgAHVvCnUV7/61Zx44olJkvHjx+e6667L3/zN31Q+GAAAABzOgFdob731\n1iTJiSeemH/913895Ng//uM/VjsVAAAA1DBg0N5xxx39b//xH//xIcd++MMfVjcRAAAAHIEBg7av\nr+9F336x9wEAAKDejuh2xQ0NDYd9HwAAAOptwKAVrQAAALycDXiX43/913/N6aefniR57LHH+t/u\n6+vLE088UZ/pAAAAYAADBu3f/d3f1XMOoCI9PT3p7OysZO09e/akpaVl0NedPn16GhsbB31dAACG\nlwGDdtKkSfWcA6hIZ2dnlqy6NWOPmVDNCTY9OqjLHdz3eDa0LU5ra+ugrgsAwPAzYNACw8fYYyak\nebx/pAIAYHg5orscAwAAwMuNoAUAAKBIghYAAIAiCVoAAACKJGgBAAAokqAFAACgSIIWAACAIgla\nAAAAiiRoAQAAKJKgBQAAoEiCFgAAgCIJWgAAAIokaAEAACiSoAUAAKBIghYAAIAiCVoAAACKJGgB\nAAAokqAFAACgSIIWAACAIglaAAAAiiRoAQAAKJKgBQAAoEiCFgAAgCIJWgAAAIokaAEAACiSoAUA\nAKBIghYAAIAiCVoAAACKJGgBAAAokqAFAACgSIIWAACAIglaAAAAiiRoAQAAKJKgBQAAoEiCFgAA\ngCIJWgB8IZjLAAAXIElEQVQAAIokaAEAACiSoAUAAKBIghYAAIAiCVoAAACKJGgBAAAokqAFAACg\nSIIWAACAIglaAAAAiiRoAQAAKJKgBQAAoEiCFgAAgCIJWgAAAIokaAEAACiSoAUAAKBIghYAAIAi\nCVoAAACKJGgBAAAoUqVB29fXl8985jNZtGhRLrjggjzyyCMv+Jhf/vKXOeuss9Ld3Z0keeaZZ3Lp\npZfmgx/8YJYtW5a9e/dWOSIAAACFqjRoN2/enO7u7mzcuDErVqxIW1vbIccfeOCBfOQjH8lTTz3V\n/9htt92W1tbW3HLLLXn3u9+dG264ocoRAQAAKFSlQdve3p65c+cmSWbOnJmOjo5Djjc2NmbdunU5\n5phjDvmcefPmJUnmzZuX7373u1WOCAAAQKGaqly8q6srLS0tvztZU1N6e3szYsRvOnrOnDlJfvPU\n5Od/TnNzc5Jk3Lhx6erqqnJEAAAAClVp0DY3N+fAgQP97z8/Zp+voaHhRT/nwIEDhwTx4bS3t/+e\n0x5qz549g7pevXR0dGT//v1DPcYRscf1UeI+l7bHVRvsn2+8kD2uD/tcPXtcPXtcH/a5esNljysN\n2lmzZmXLli1ZuHBhtm/fntbW1hf9uOdfoZ01a1a2bt2ak046KVu3bs0pp5xyROeaPXv2oMz8Wy0t\nLcmmRwd1zXqYMWPGgPv8cmOP66PEfS5tj6vU3t4+6D/fOJQ9rg/7XD17XD17XB/2uXql7fHh4rvS\noF2wYEG2bduWRYsWJUna2tqybt26TJkyJfPnz+//uOdfoT3//PNzxRVXZPHixRk1alSuvfbaKkcE\nAACgUJUGbUNDQ9asWXPIY9OmTXvBx9133339b48ZMyZf+tKXqhwLAACAYaDSuxwDAABAVQQtAAAA\nRRK0AAAAFEnQAgAAUCRBCwAAQJEELQAAAEWq9Nf2ALwS9PT0pLOzs5K19+zZk5aWlkFfd/r06Wls\nbBz0dQEA6knQAvyeOjs7s2TVrRl7zIRqTrDp0UFd7uC+x7OhbXFaW1sHdV0AgHoTtACDYOwxE9I8\nftJQjwEA8IriNbQAAAAUSdACAABQJEELAABAkQQtAAAARRK0AAAAFEnQAgAAUCRBCwAAQJEELQAA\nAEUStAAAABRJ0AIAAFAkQQsAAECRBC0AAABFErQAAAAUqWmoBwCAWnp6etLZ2VnJ2nv27ElLS0sl\na0+fPj2NjY2VrA0ACFoACtDZ2Zklq27N2GMmVHOCTY8O+pIH9z2eDW2L09raOuhrAwC/IWgBKMLY\nYyakefykoR4DAHgZ8RpaAAAAiiRoAQAAKJKgBQAAoEiCFgAAgCIJWgAAAIokaAEAACiSoAUAAKBI\nghYAAIAiCVoAAACKJGgBAAAokqAFAACgSIIWAACAIjUN9QAAwNDr6elJZ2dnZevv2bMnLS0tg77u\n9OnT09jYOOjrAlAGQQsApLOzM0tW3Zqxx0yo7iSbHh3U5Q7uezwb2hantbV1UNcFoByCFgBIkow9\nZkKax08a6jEA4Ih5DS0AAABFErQAAAAUSdACAABQJEELAABAkQQtAAAARRK0AAAAFEnQAgAAUCRB\nCwAAQJEELQAAAEUStAAAABRJ0AIAAFAkQQsAAECRBC0AAABFErQAAAAUSdACAABQJEELAABAkQQt\nAAAARRK0AAAAFEnQAgAAUCRBCwAAQJEELQAAAEUStAAAABRJ0AIAAFAkQQsAAECRBC0AAABFErQA\nAAAUSdACAABQJEELAABAkQQtAAAARRK0AAAAFEnQAgAAUKSmKhfv6+vL6tWrs2vXrowaNSpr167N\n5MmT+49/4xvfyO23356RI0fmoosuymmnnZZ9+/blrLPOSmtra5JkwYIFWbJkSZVjAgAAUKBKg3bz\n5s3p7u7Oxo0bs2PHjrS1teWGG25Ikjz55JPZsGFD7r777jz99NM5//zzc+qpp+bHP/5x3vWud+Wq\nq66qcjQAAAAKV+lTjtvb2zN37twkycyZM9PR0dF/7J//+Z8ze/bsNDU1pbm5OVOnTs2uXbvS0dGR\nhx56KEuWLMnHPvaxPPHEE1WOCAAAQKEqDdqurq60tLT0v9/U1JTe3t4XPTZ27Njs378/06dPz6WX\nXpoNGzbk9NNPz9VXX13liAAAABSq0qccNzc358CBA/3v9/b2ZsSIEf3Hurq6+o8dOHAgRx99dE4+\n+eQcddRRSX7z+tkvf/nLR3Su9vb2QZw82bNnz6CuVy8dHR3Zv3//UI9xROxxfZS4z/a4eva4Pkra\nZ3s8PAz234d4IXtcH/a5esNljysN2lmzZmXLli1ZuHBhtm/f3n+jpyQ5+eSTc91116W7uzvPPPNM\n/u3f/i2vec1rcsUVV+TMM8/M29/+9jz44IN5wxvecETnmj179qDO3tLSkmx6dFDXrIcZM2Ycss8v\nZ/a4PkrcZ3tcPXtcHyXtsz0uX3t7+6D/fYhD2eP6sM/VK22PDxfflQbtggULsm3btixatChJ0tbW\nlnXr1mXKlCmZP39+lixZksWLF6evry8f//jHM2rUqKxYsSJXXnllbrvttowdOzb/83/+zypHBAAA\noFCVBm1DQ0PWrFlzyGPTpk3rf/sDH/hAPvCBDxxy/IQTTsj69eurHAsAAIBhoNKbQgEAAEBVKr1C\nCwDA7/T09KSzs7OStffs2XPIb5AYLNOnT09jY+OgrwswGAQtAECddHZ2ZsmqWzP2mAnVnGCQb+x1\ncN/j2dC22I23gJctQQsAUEdjj5mQ5vGThnoMgGHBa2gBAAAokqAFAACgSIIWAACAIglaAAAAiiRo\nAQAAKJKgBQAAoEiCFgAAgCIJWgAAAIrUNNQDAADAYOnp6UlnZ2cla+/ZsyctLS2VrD19+vQ0NjZW\nsjYMZ4IWAIBho7OzM0tW3Zqxx0yo5gSbHh30JQ/uezwb2hantbV10NeG4U7QAgAwrIw9ZkKax08a\n6jGAOvAaWgAAAIokaAEAACiSpxwDAABHrMobbyXV3XzLjbeGJ0ELAAAcscpvvJUM+s233Hhr+BK0\nAADAS+LGW7xceA0tAAAARRK0AAAAFEnQAgAAUCRBCwAAQJEELQAAAEUStAAAABRJ0AIAAFAkQQsA\nAECRBC0AAABFErQAAAAUSdACAABQJEELAABAkQQtAAAARRK0AAAAFEnQAgAAUCRBCwAAQJEELQAA\nAEUStAAAABRJ0AIAAFAkQQsAAECRBC0AAABFErQAAAAUSdACAABQJEELAABAkQQtAAAARRK0AAAA\nFKlpqAcAAADgd3p6etLZ2VnZ+nv27ElLS8ugrzt9+vQ0NjYO+rqHI2gBAABeRjo7O7Nk1a0Ze8yE\n6k6y6dFBXe7gvsezoW1xWltbB3XdWgQtAADAy8zYYyakefykoR7jZc9raAEAACiSoAUAAKBIghYA\nAIAiCVoAAACKJGgBAAAokqAFAACgSIIWAACAIglaAAAAiiRoAQAAKJKgBQAAoEiCFgAAgCIJWgAA\nAIokaAEAACiSoAUAAKBIghYAAIAiCVoAAACKJGgBAAAokqAFAACgSIIWAACAIglaAAAAiiRoAQAA\nKJKgBQAAoEiCFgAAgCI1Vbl4X19fVq9enV27dmXUqFFZu3ZtJk+e3H/8G9/4Rm6//faMHDkyF110\nUU477bTs3bs3n/jEJ/LMM89kwoQJaWtry+jRo6scEwAAgAJVeoV28+bN6e7uzsaNG7NixYq0tbX1\nH3vyySezYcOG3H777bn55ptz7bXX5tlnn82f//mf5+yzz87Xv/71vO51r8ttt91W5YgAAAAUqtKg\nbW9vz9y5c5MkM2fOTEdHR/+xf/7nf87s2bPT1NSU5ubmTJ06NTt37sw//uM/9n/OvHnz8r3vfa/K\nEQEAAChUpU857urqSktLy+9O1tSU3t7ejBgx4gXHxo0bl66urhw4cKD/8XHjxmX//v1VjnhYB/c9\nPmTn/o8obd6kvJlLm/e3Spq7pFmfr6S5S5r1+Uqbu7R5k/JmLm3e3ypp7pJmfb7S5i5t3qS8mUub\nNylv5qGat6Gvr6+vqsWvueaavPGNb8zChQuTJKeddlq+/e1vJ0nuv//+fOc738lnPvOZJMny5ctz\n8cUX51Of+lRuvvnm/MEf/EF27tyZ6667Ll/5ylcOe5729vaqvgQAAACG2OzZs1/08Uqv0M6aNStb\ntmzJwoULs3379rS2tvYfO/nkk3Pdddelu7s7zzzzTP7t3/4tr3nNazJr1qxs3bo1733ve/MP//AP\nOeWUU2qeZ6AvDgAAgOGr0iu0z7/LcZK0tbVl69atmTJlSubPn5877rgjt99+e/r6+nLxxRfnjDPO\nyFNPPZUrrrgiBw8ezPjx43PttddmzJgxVY0IAABAoSoNWgAAAKhKpXc5BgAAgKoIWgAAAIokaAEA\nACiSoAUAAKBIgraOent7h3oEGHTd3d1DPcKw9fTTT9vfij311FNDPcKw19vbm8cee8yfgRX75S9/\nGff5HFxdXV1DPcIrTnd3d55++umhHmNYG44/JwRtxR555JFccsklmTdvXs4444ycdtppufDCC7N7\n9+6hHg1ekvvvvz/z58/PggULcu+99/Y/vnTp0iGcanj57c+LT3/603nwwQfzjne8I+94xzuyZcuW\noR5t2Ni9e/ch/1188cX9bzN4rrzyyiTJjh07ctZZZ2X58uV517vele3btw/xZMPHnXfemeuvvz4P\nPfRQFi5cmA9/+MNZuHBhHnzwwaEebdg49dRTc8cddwz1GMPa7t27c+mll2bFihXZvn17zj777Lzz\nne885O8Z/P4efvjhfOQjH8n8+fMzY8aMnHvuuVmxYkWeeOKJoR5tUDQN9QDD3Sc/+cmsWLEiM2fO\n7H9s+/btWbVqVTZu3DiEk8FL85WvfCV33313+vr6ctlll+WZZ57Je9/73mH5L31D5corr8z/+B//\nIz/72c9y6aWX5u/+7u8yevToLF26NPPnzx/q8YaFD3/4wxkzZkwmTJiQvr6+7N69O5/+9KfT0NCQ\n9evXD/V4w8ZPf/rTJMkXv/jF/K//9b8yderUPPbYY1mxYkW+/vWvD/F0w8Ott96aDRs25OKLL86N\nN96YadOm5bHHHssll1ySt7zlLUM93rDwute9Lj/5yU9ywQUXZPny5Xnzm9881CMNO5/61KdyySWX\nZP/+/Vm2bFn+8i//Mi0tLfnwhz+cd7zjHUM93rCxZs2aXHXVVZk2bVq2b9+eb3/72znjjDPyyU9+\nMl/96leHerzfm6CtWHd39yExmyRvfOMbh2ia4WvJkiV59tlnD3msr68vDQ0N/uFgkIwcOTLHHnts\nkuSGG27If/tv/y2vetWr0tDQMMSTDR/PPfdc/1+Yvv/97+e4445LkjQ1+VE9WO6888585jOfyfnn\nn59TTz01S5YsyYYNG4Z6rGGrsbExU6dOTZIcf/zxnnY8iEaOHJmxY8dm3LhxmTx5cpLf7LGfyYNn\n9OjR+fSnP50f/ehH+epXv5rPfvazmTNnTiZPnpwLLrhgqMcbFp577rm85S1vSV9fX77whS/k+OOP\nT+LPvcHW1dWVadOmJflNh3zhC1/Ixz72sfy///f/hniyweG7pWKvfe1rs2rVqsydOzctLS05cOBA\ntm7dmte+9rVDPdqw8olPfCJXXXVV/vzP/zyNjY1DPc6wNGnSpLS1teWyyy5Lc3Nzrr/++nzkIx8Z\nNj8MXw6mTZuWT37yk7n66qtzzTXXJEm++tWv5g//8A+HeLLh47jjjst1112Xz33uc/nRj3401OMM\nW/v3788f/dEf5eDBg7njjjtyzjnn5JprrsnEiROHerRh421ve1suvvjitLa2ZtmyZZk7d26+853v\n5L/+1/861KMNG799BtJJJ52UL3/5y9m/f3/+7//9v16iMIgmTZqUyy+/PD09PRk3bly++MUvprm5\nOf/pP/2noR5tWDnhhBPy6U9/OvPmzcu3v/3tvP71r8/f//3f56ijjhrq0QZFQ5/nC1aqr68vmzdv\nTnt7e7q6utLc3JxZs2ZlwYIF/hV1kN18882ZMmVKFixYMNSjDEvPPfdc/vIv/zJvf/vb+38APvnk\nk7npppvyyU9+coinGx56e3tz//3354wzzuh/7J577smZZ545bP7QeTm56667ctddd3kKbEW6u7uz\nc+fOjBkzJlOnTs2dd96Z97///Rk5cuRQjzZs/OAHP8gDDzyQvXv35thjj83s/6+9uwmpKv/jOP72\nuTQwi56RQiiULoRMC0EJkzZZRiK0ku4qoax2CZIVuRAqCCLLRZuiMFHqlmKbQipDE0KCHiQUekRT\nClJc9KDXWfyZy/jPiZlxhutt3q/V5Zzf7/y+nM3lw/d3zvnlFwoLC6Nd1k8jFApRWloa7TJ+ahMT\nE9y7d481a9aQlpbGxYsXSU9PJxgMkpqaGu3yfhpfv36lpaWFgYEBcnJyKCsr48mTJ6xevZqMjIxo\nlzdrBlpJkiRJUkzyLceSJEmSpJhkoJUkSZIkxSQDrSRJkiQpJhloJUn6B4yPj1NbW0tJSQmlpaUE\ng0GeP38e7bL+tvHxcfbv3x/tMiRJ+iE/2yNJ0ixNTU1RUVFBXl4eN2/eJD4+np6eHioqKmhvbyc9\nPT3aJf5lnz59oq+vL9plSJL0Q77lWJKkWeru7ubw4cN0dHRMO37//n0CgQDNzc20tbWRkJBAfn4+\nVVVVDA4OUllZSVZWFv39/axfv57c3FxCoRBjY2PU19eTlZVFUVERW7dupauri7i4OOrq6sjOzubV\nq1ccOXKE0dFRUlNTqampIRAIUF1dzYIFC3j27BkjIyPs27cv8k3Y2tpa+vv7CYfD7Nmzh+LiYkKh\nEJ2dnYyOjvL27VsKCgo4evQoe/fu5cGDBxQWFnL27Nko3VlJkn7MLceSJM1SX18f2dnZ3x3ftGkT\nT58+5e7du4RCIW7cuMHr16+5evUqAC9evKCiooK2tjZ6e3sZHBykqamJ4uJimpubI9dJS0sjFApx\n4MABqqqqADh06BDBYJDW1laqq6s5ePAg3759A2B4eJjGxkbOnz/PiRMnAGhoaCAQCHDt2jUuX75M\nQ0MD7969A+Dx48fU19fT2tpKR0cH/f391NTUsHTpUsOsJGlOM9BKkjRL8fHxpKSkzHiuu7ubbdu2\nkZycTHx8PGVlZTx8+BCAJUuWRILwsmXLyMvLA2DVqlWMjo5GrrFr1y4ANm/ezPDwMMPDw7x584Yt\nW7YAsGHDBhYuXMjLly8ByM/PB2DdunWMjY0B0NXVRVNTEzt37qS8vJzPnz8zMDAAQG5uLvPnz2fe\nvHlkZmZOW1uSpLnMZ2glSZqlQCAQ6br+3unTp+np6aG0tDRybGpqiomJCQCSkpKmjU9MnPlvOSEh\nYdr8cDj83ZhwOMzk5CTAjOE6HA5z6tQpcnJyAPj48SPp6em0tbWRnJw8baxPI0mSYoUdWkmSZmnj\nxo0sWrSI+vr6SNjs7OwkFAqxe/du2tvb+fLlCxMTE1y/fj3Sif2zwfHWrVsA3L59m6ysLFasWEFm\nZiZ37twB/rdl+MOHD6xdu/a7ub+tkZeXR2NjIwAjIyPs2LGDoaGhP1wzMTExEpAlSZqr7NBKkvQP\naGhooK6uju3bt5OUlERGRgYXLlwgOzub9+/fU1ZWxuTkJAUFBZSXlzM0NERcXFxk/u9//7/e3l5a\nWlpITU2NPBN78uRJjh07xpkzZ0hJSeHcuXMzdnh/u25lZSXHjx+npKSEcDhMVVUVmZmZPHr0aMbx\nixcvZvny5QSDQS5dujTr+yNJ0r/BtxxLkjSHFRUVceXKFVauXBntUiRJmnPccixJ0hz2o86tJEn/\ndXZoJUmSJEkxyQ6tJEmSJCkmGWglSZIkSTHJQCtJkiRJikkGWkmSJElSTDLQSpIkSZJikoFWkiRJ\nkhSTfgUCo+l8ftiumgAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x118e9b240>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"pd.Series(pca.explained_variance_ratio_).plot(kind='bar')\n",
"plt.xlabel('Component')\n",
"plt.ylabel('Explained variance ratio')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"These are the linear combination coefficients. Each row indicates some degree of correlation among the components; for instance, we can conclude from the first row that there is some correlation between questions being low-effort, low-research, conceptual, not asking for a tedious calculation, and not asking for us to check their work."
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:08.634011",
"start_time": "2016-08-27T18:00:08.617002"
},
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Effort</th>\n",
" <th>Level</th>\n",
" <th>Conceptual</th>\n",
" <th>Interest</th>\n",
" <th>Tedious</th>\n",
" <th>Context</th>\n",
" <th>Check My Work</th>\n",
" <th>Correct?</th>\n",
" <th>Detailed Calc</th>\n",
" <th>Research</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Component</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>-0.430028</td>\n",
" <td>-0.186645</td>\n",
" <td>0.364720</td>\n",
" <td>0.046863</td>\n",
" <td>0.405997</td>\n",
" <td>0.219436</td>\n",
" <td>0.368570</td>\n",
" <td>0.152944</td>\n",
" <td>0.335498</td>\n",
" <td>-0.400303</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>0.345233</td>\n",
" <td>0.315220</td>\n",
" <td>0.306732</td>\n",
" <td>0.491200</td>\n",
" <td>0.167045</td>\n",
" <td>0.398214</td>\n",
" <td>-0.191071</td>\n",
" <td>0.149609</td>\n",
" <td>0.296089</td>\n",
" <td>0.336230</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>-0.245454</td>\n",
" <td>0.207344</td>\n",
" <td>0.247303</td>\n",
" <td>-0.156832</td>\n",
" <td>-0.151148</td>\n",
" <td>-0.429621</td>\n",
" <td>-0.417349</td>\n",
" <td>0.634036</td>\n",
" <td>0.164443</td>\n",
" <td>-0.019038</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>0.178939</td>\n",
" <td>-0.649179</td>\n",
" <td>0.046144</td>\n",
" <td>-0.346529</td>\n",
" <td>0.416154</td>\n",
" <td>0.003953</td>\n",
" <td>-0.265325</td>\n",
" <td>0.093448</td>\n",
" <td>0.091727</td>\n",
" <td>0.404466</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>-0.005115</td>\n",
" <td>-0.519197</td>\n",
" <td>0.147526</td>\n",
" <td>0.672554</td>\n",
" <td>-0.138424</td>\n",
" <td>-0.165498</td>\n",
" <td>-0.129061</td>\n",
" <td>0.141632</td>\n",
" <td>-0.384931</td>\n",
" <td>-0.157723</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>-0.025118</td>\n",
" <td>-0.081759</td>\n",
" <td>0.244147</td>\n",
" <td>0.162795</td>\n",
" <td>-0.099558</td>\n",
" <td>-0.521372</td>\n",
" <td>-0.059154</td>\n",
" <td>-0.586626</td>\n",
" <td>0.520742</td>\n",
" <td>0.077672</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>-0.173539</td>\n",
" <td>-0.169403</td>\n",
" <td>-0.740550</td>\n",
" <td>0.274866</td>\n",
" <td>-0.096378</td>\n",
" <td>0.050288</td>\n",
" <td>-0.005060</td>\n",
" <td>0.224231</td>\n",
" <td>0.502121</td>\n",
" <td>0.054530</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>-0.037479</td>\n",
" <td>-0.295759</td>\n",
" <td>0.276119</td>\n",
" <td>-0.197841</td>\n",
" <td>-0.754754</td>\n",
" <td>0.400741</td>\n",
" <td>0.108877</td>\n",
" <td>0.045024</td>\n",
" <td>0.184369</td>\n",
" <td>0.132732</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>-0.104540</td>\n",
" <td>-0.019739</td>\n",
" <td>-0.056904</td>\n",
" <td>-0.072338</td>\n",
" <td>0.007365</td>\n",
" <td>0.357412</td>\n",
" <td>-0.731606</td>\n",
" <td>-0.295898</td>\n",
" <td>0.054963</td>\n",
" <td>-0.476014</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>-0.748677</td>\n",
" <td>0.092545</td>\n",
" <td>0.018482</td>\n",
" <td>0.114418</td>\n",
" <td>0.056229</td>\n",
" <td>0.136380</td>\n",
" <td>-0.125649</td>\n",
" <td>-0.198593</td>\n",
" <td>-0.236294</td>\n",
" <td>0.533537</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Effort Level Conceptual Interest Tedious Context \\\n",
"Component \n",
"0 -0.430028 -0.186645 0.364720 0.046863 0.405997 0.219436 \n",
"1 0.345233 0.315220 0.306732 0.491200 0.167045 0.398214 \n",
"2 -0.245454 0.207344 0.247303 -0.156832 -0.151148 -0.429621 \n",
"3 0.178939 -0.649179 0.046144 -0.346529 0.416154 0.003953 \n",
"4 -0.005115 -0.519197 0.147526 0.672554 -0.138424 -0.165498 \n",
"5 -0.025118 -0.081759 0.244147 0.162795 -0.099558 -0.521372 \n",
"6 -0.173539 -0.169403 -0.740550 0.274866 -0.096378 0.050288 \n",
"7 -0.037479 -0.295759 0.276119 -0.197841 -0.754754 0.400741 \n",
"8 -0.104540 -0.019739 -0.056904 -0.072338 0.007365 0.357412 \n",
"9 -0.748677 0.092545 0.018482 0.114418 0.056229 0.136380 \n",
"\n",
" Check My Work Correct? Detailed Calc Research \n",
"Component \n",
"0 0.368570 0.152944 0.335498 -0.400303 \n",
"1 -0.191071 0.149609 0.296089 0.336230 \n",
"2 -0.417349 0.634036 0.164443 -0.019038 \n",
"3 -0.265325 0.093448 0.091727 0.404466 \n",
"4 -0.129061 0.141632 -0.384931 -0.157723 \n",
"5 -0.059154 -0.586626 0.520742 0.077672 \n",
"6 -0.005060 0.224231 0.502121 0.054530 \n",
"7 0.108877 0.045024 0.184369 0.132732 \n",
"8 -0.731606 -0.295898 0.054963 -0.476014 \n",
"9 -0.125649 -0.198593 -0.236294 0.533537 "
]
},
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pd.DataFrame(pca.components_.T, index=ratingcols, columns=pd.Index(range(10), name='Component')).T"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Significance of PCA results "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The standard way to evaluate whether the correlation is significant is to scramble the columns of the data set and compute the PCA a large number of times, and see where our original explained variance ratio falls in the resulting distribution."
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:28.961820",
"start_time": "2016-08-27T18:00:08.635578"
},
"collapsed": false
},
"outputs": [],
"source": [
"random_pca = np.array([skd.PCA().fit(qalldata[ratingcols].apply(np.random.permutation)).explained_variance_ratio_ for i in range(10000)])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This suggests that the correlation indicated by the first component (first row) is significant, but the one indicated by the second component is not."
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:29.219386",
"start_time": "2016-08-27T18:00:28.963308"
},
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.text.Text at 0x119522f60>"
]
},
"execution_count": 36,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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HBysgIMCt/bfN1JLzjMxFVwqTpNTU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\nggEAAAAAlvH/phohnjrBf68AAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x11949b908>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.hist(random_pca[:,0])\n",
"plt.hist(random_pca[:,1])\n",
"plt.axvline(x=pca.explained_variance_ratio_[0], color='red')\n",
"plt.axvline(x=pca.explained_variance_ratio_[1], color='maroon')\n",
"plt.legend(['Primary (original data set)', 'Secondary (original data set)', 'Primary (shuffled)', 'Secondary (shuffled)'], loc=(0.7,0.88))\n",
"plt.xlabel('Component\\'s explained variance ratio')\n",
"plt.ylabel('Number of random samples')"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"# Overlapping factors "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Perhaps there's no one reason or combination of reasons that covers all the questions people would like to close, but of different reasons, so let's see if we can cover the set of closeable questions with two or three different factors. Here we're looking for a set of several factors such that each closeable question scores low on at least one of them, but the non-closeable questions score high on all of them."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Clearly on-topic questions "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's look at the questions which seem to be unambiguously on topic, meaning that the 95% ($p=0.05$) confidence interval is entirely positive."
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:29.223493",
"start_time": "2016-08-27T18:00:29.220635"
},
"collapsed": true
},
"outputs": [],
"source": [
"definite_yes = qscore[qscore['Wilson Lower 2'] > 0]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"There are five of them. Not a lot, but perhaps enough to suggest some possible directions."
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:29.238017",
"start_time": "2016-08-27T18:00:29.224909"
},
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>URL</th>\n",
" <th>Answer posted</th>\n",
" <th>Upvotes</th>\n",
" <th>Downvotes</th>\n",
" <th>Score</th>\n",
" <th>Votes</th>\n",
" <th>Approval</th>\n",
" <th>Wilson Lower 1</th>\n",
" <th>Wilson Upper 1</th>\n",
" <th>Wilson Lower 2</th>\n",
" <th>Wilson Upper 2</th>\n",
" </tr>\n",
" <tr>\n",
" <th>QID</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>247719</th>\n",
" <td>https://physics.stackexchange.com/questions/24...</td>\n",
" <td>2016-04-06 07:08:42Z</td>\n",
" <td>26</td>\n",
" <td>8</td>\n",
" <td>18</td>\n",
" <td>34</td>\n",
" <td>0.764706</td>\n",
" <td>12.848896</td>\n",
" <td>22.212258</td>\n",
" <td>6.802626</td>\n",
" <td>25.542850</td>\n",
" </tr>\n",
" <tr>\n",
" <th>247547</th>\n",
" <td>https://physics.stackexchange.com/questions/24...</td>\n",
" <td>2016-04-06 07:30:57Z</td>\n",
" <td>21</td>\n",
" <td>9</td>\n",
" <td>12</td>\n",
" <td>30</td>\n",
" <td>0.700000</td>\n",
" <td>6.914531</td>\n",
" <td>16.378576</td>\n",
" <td>1.274528</td>\n",
" <td>20.001151</td>\n",
" </tr>\n",
" <tr>\n",
" <th>247999</th>\n",
" <td>https://physics.stackexchange.com/questions/24...</td>\n",
" <td>2016-04-07 12:25:19Z</td>\n",
" <td>23</td>\n",
" <td>5</td>\n",
" <td>18</td>\n",
" <td>28</td>\n",
" <td>0.821429</td>\n",
" <td>13.585118</td>\n",
" <td>21.281190</td>\n",
" <td>8.068802</td>\n",
" <td>23.588039</td>\n",
" </tr>\n",
" <tr>\n",
" <th>248365</th>\n",
" <td>https://physics.stackexchange.com/questions/24...</td>\n",
" <td>2016-04-11 09:43:27Z</td>\n",
" <td>24</td>\n",
" <td>9</td>\n",
" <td>15</td>\n",
" <td>33</td>\n",
" <td>0.727273</td>\n",
" <td>9.764167</td>\n",
" <td>19.430389</td>\n",
" <td>3.816411</td>\n",
" <td>23.055489</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7671</th>\n",
" <td>http://meta.physics.stackexchange.com/a/7671/124</td>\n",
" <td>2016-04-12 19:46:40Z</td>\n",
" <td>13</td>\n",
" <td>2</td>\n",
" <td>11</td>\n",
" <td>15</td>\n",
" <td>0.866667</td>\n",
" <td>7.851166</td>\n",
" <td>12.889944</td>\n",
" <td>3.635405</td>\n",
" <td>13.879162</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" URL \\\n",
"QID \n",
"247719 https://physics.stackexchange.com/questions/24... \n",
"247547 https://physics.stackexchange.com/questions/24... \n",
"247999 https://physics.stackexchange.com/questions/24... \n",
"248365 https://physics.stackexchange.com/questions/24... \n",
"7671 http://meta.physics.stackexchange.com/a/7671/124 \n",
"\n",
" Answer posted Upvotes Downvotes Score Votes Approval \\\n",
"QID \n",
"247719 2016-04-06 07:08:42Z 26 8 18 34 0.764706 \n",
"247547 2016-04-06 07:30:57Z 21 9 12 30 0.700000 \n",
"247999 2016-04-07 12:25:19Z 23 5 18 28 0.821429 \n",
"248365 2016-04-11 09:43:27Z 24 9 15 33 0.727273 \n",
"7671 2016-04-12 19:46:40Z 13 2 11 15 0.866667 \n",
"\n",
" Wilson Lower 1 Wilson Upper 1 Wilson Lower 2 Wilson Upper 2 \n",
"QID \n",
"247719 12.848896 22.212258 6.802626 25.542850 \n",
"247547 6.914531 16.378576 1.274528 20.001151 \n",
"247999 13.585118 21.281190 8.068802 23.588039 \n",
"248365 9.764167 19.430389 3.816411 23.055489 \n",
"7671 7.851166 12.889944 3.635405 13.879162 "
]
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"definite_yes"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Since these questions were judged to be on topic, let's look for categories in which these questions have high ratings. I'll normalize the ratings so that the complete data set has zero mean and unit standard deviation, then we can look for categories where the normalized ratings are mostly/entirely positive."
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:29.245432",
"start_time": "2016-08-27T18:00:29.239110"
},
"collapsed": false
},
"outputs": [],
"source": [
"definite_yes_normalized_ratings = qalldata[ratingcols].apply(spst.zscore)[qalldata['Wilson Lower 2'] > 0]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Here is a visualization of all the individual ratings. Columns which have mostly red/orange and not much blue are likely candidates for good criteria. That suggests context, level, check-my-work, correctness, and detailed calculation. (Remember these results are adjusted so that high numbers indicate responses we would associated with being _on_ topic.)"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:30.000305",
"start_time": "2016-08-27T18:00:29.246912"
},
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x1197901d0>"
]
},
"execution_count": 40,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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zezx6kN8SnfxuAzsXvM/Ohe8jSaJ3979SKRQm/TMFs+rknTx5kjZtDJ0Ta2tr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uz/Ba1WS7M2HdSIXuGOxJ3Gv20rAFo08eZkYpKhzMnRnq/XfoBWq+Xq9Uwc73wxJKVcpGO70vf4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\nhBBCCCGEEKWINPKEEEIIIYQQohT5f/sbRqOI0v88AAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1199165c0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.heatmap(definite_yes_normalized_ratings, annot=True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Specifically, what we're looking for is categories where, for every question, most people believe that the question rates highly. Accordingly we should look at something like the per-question mean minus the per-question standard deviation, which approximates the lower bound of the 68% confidence interval of ratings for that question. It's the same idea as with the Wilson score of the question scores computed above."
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:30.007163",
"start_time": "2016-08-27T18:00:30.001805"
},
"collapsed": true
},
"outputs": [],
"source": [
"g = definite_yes_normalized_ratings.groupby(level=0)\n",
"definite_yes_norm_mean = g.mean()\n",
"definite_yes_norm_std = g.std()\n",
"del g"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"High numbers indicate where different survey respondents agree that the question rates highly, and low numbers indicate either disagreement about the rating of the question, or a low rating. Either situation makes the category undesirable.\n",
"\n",
"We want to look for rating categories where there are no large negative numbers. However small negative numbers are to be expected because we are looking at a mean minus a standard deviation, and the distribution of this statistic is going to skew negative. Accordingly I center the color distribution on the mean of the per-question averages (but there's no rigorous justification for using that number specifically)."
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:30.016886",
"start_time": "2016-08-27T18:00:30.008765"
},
"collapsed": false
},
"outputs": [],
"source": [
"def heatmap_with_summary_row(data, summary_func, summary_caption=None, center_on_mean=False, **heatmap_kw):\n",
" fig = plt.figure()\n",
" grid = plt.GridSpec(data.shape[0] + 1, data.shape[1] + 1, hspace=1)\n",
" main = fig.add_subplot(grid.new_subplotspec((0, 0), data.shape[0], data.shape[1]))\n",
" summary = fig.add_subplot(grid.new_subplotspec((data.shape[0], 0), 1, data.shape[1]))\n",
" colorbar = fig.add_subplot(grid.new_subplotspec((0, data.shape[1]), data.shape[0] + 1, 1))\n",
" if center_on_mean and 'center' not in heatmap_kw:\n",
" heatmap_kw['center'] = data.as_matrix().mean()\n",
" sns.heatmap(data, ax=main, cbar_ax=colorbar, **heatmap_kw)\n",
" sns.heatmap(pd.DataFrame(data.apply(summary_func), columns=[summary_caption or '']).T,\n",
" ax=summary, cbar=False, **heatmap_kw)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The following plot shows per-question mean minus per-question standard deviation. The only column that doesn't have a strongly blue cell (a signficant negative number for one question) is context. Interest and prior research are the next best options, closely followed by effort and level."
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {
"ExecuteTime": {
"end_time": "2016-08-27T18:00:30.527560",
"start_time": "2016-08-27T18:00:30.018578"
},
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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M9PCaeE7a9l/kXzNKZUdNkiSdem+uQtt2VM6p40rftUXZRw+p3EPPyO12Kz1mmzJj98he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\nd17fvH/ZDytXrqK+/ftrzty5KlYsWNGzZ8liyVJ4p06aMm2aJk2erKm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