bsampler-model-comp.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpyro\n",
    "numpyro.util.set_host_device_count(4)\n",
    "import numpyro.distributions as dist\n",
    "from numpyro.infer import MCMC, NUTS, Predictive, DiscreteHMCGibbs\n",
    "\n",
    "from jax import numpy as jnp\n",
    "from jax import random\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "# import seaborn as sns\n",
    "import arviz as az\n",
    "\n",
    "# from dfply import *\n",
    "from siuba import _\n",
    "import siuba as s\n",
    "\n",
    "import pickle\n",
    "from plotnine import *\n",
    "# %run -i 'model_helpers.py'\n",
    "# %run -i 'models.py'\n",
    "# %run -i 'ic-compare.py'\n",
    "from lib.helpers import *\n",
    "from lib.models import *\n",
    "from lib.icc import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>condition</th>\n",
       "      <th>querytype</th>\n",
       "      <th>querydetail</th>\n",
       "      <th>estimate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>A</td>\n",
       "      <td>icy</td>\n",
       "      <td>0.503333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>AandB</td>\n",
       "      <td>icy and frosty</td>\n",
       "      <td>0.616667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>AandnotB</td>\n",
       "      <td>icy and not frosty</td>\n",
       "      <td>0.453333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>AgB</td>\n",
       "      <td>icy given frosty</td>\n",
       "      <td>0.766667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>AgnotB</td>\n",
       "      <td>icy given not frosty</td>\n",
       "      <td>0.340000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID  condition querytype            querydetail  estimate\n",
       "0   0          0         A                    icy  0.503333\n",
       "1   0          0     AandB         icy and frosty  0.616667\n",
       "2   0          0  AandnotB     icy and not frosty  0.453333\n",
       "3   0          0       AgB       icy given frosty  0.766667\n",
       "4   0          0    AgnotB   icy given not frosty  0.340000"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = load_query_avg_data_exp1() # see data_helpers.py\n",
    "df1 = df1[~df1.querytype.str.contains('or')]\n",
    "# df1 = df1[df1[\"condition\"]!=2] # filter out \"warm/snowy\" as per paper\n",
    "df1.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>condition</th>\n",
       "      <th>querytype</th>\n",
       "      <th>querydetail</th>\n",
       "      <th>estimate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>A</td>\n",
       "      <td>windy</td>\n",
       "      <td>0.733333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>AandB</td>\n",
       "      <td>windy and cloudy</td>\n",
       "      <td>0.773333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>AandnotB</td>\n",
       "      <td>windy and not cloudy</td>\n",
       "      <td>0.676667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>AgB</td>\n",
       "      <td>windy given cloudy</td>\n",
       "      <td>0.816667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>AgnotB</td>\n",
       "      <td>windy given not cloudy</td>\n",
       "      <td>0.600000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "   ID  condition querytype              querydetail  estimate\n",
       "0   0          0         A                    windy  0.733333\n",
       "1   0          0     AandB         windy and cloudy  0.773333\n",
       "2   0          0  AandnotB     windy and not cloudy  0.676667\n",
       "3   0          0       AgB       windy given cloudy  0.816667\n",
       "4   0          0    AgnotB   windy given not cloudy  0.600000"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = load_query_avg_data_exp2() # see data_helpers.py\n",
    "df2 = df2[df2[\"condition\"]!=2] # filter out \"warm/snowy\" as per paper\n",
    "df2.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "fits = dict()\n",
    "fits[\"exp1\"] = dict()\n",
    "fits[\"exp2\"] = dict()\n",
    "\n",
    "fits[\"exp1\"][\"Relative Freq.\"] = pickle.load(open(\"local/exp1/az_data_rf.p\", \"rb\"))\n",
    "fits[\"exp1\"][\"Bayesian Sampler simple\"] = pickle.load(open(\"local/exp1/az_data_bs_simple.p\", \"rb\"))\n",
    "fits[\"exp1\"][\"Bayesian Sampler complex\"] = pickle.load(open(\"local/exp1/az_data_bs.p\", \"rb\"))\n",
    "fits[\"exp1\"][\"Bayesian Sampler simple hier.\"] = pickle.load(open(\"local/exp1/az_data_bs_mlm_simple.p\", \"rb\"))\n",
    "fits[\"exp1\"][\"Bayesian Sampler complex hier.\"] = pickle.load(open(\"local/exp1/az_data_bs_mlm.p\", \"rb\"))\n",
    "fits[\"exp1\"][\"PT+N complex\"] = pickle.load(open(\"local/exp1/az_data_ptn.p\", \"rb\"))\n",
    "fits[\"exp1\"][\"PT+N simple\"] = pickle.load(open(\"local/exp1/az_data_ptn_simple.p\", \"rb\"))\n",
    "fits[\"exp1\"][\"PT+N complex hier.\"] = pickle.load(open(\"local/exp1/az_data_ptn_mlm.p\", \"rb\"))\n",
    "fits[\"exp1\"][\"PT+N simple hier.\"] = pickle.load(open(\"local/exp1/az_data_ptn_mlm_simple.p\", \"rb\"))\n",
    "fits[\"exp1\"][\"Unrestricted BS hier.\"] = pickle.load(open(\"local/exp1/az_data_ptn_mlm_simplecond.p\", \"rb\"))\n",
    "\n",
    "fits[\"exp2\"][\"Relative Freq.\"] = pickle.load(open(\"local/exp2/az_data_rf.p\", \"rb\"))\n",
    "fits[\"exp2\"][\"Bayesian Sampler simple\"] = pickle.load(open(\"local/exp2/az_data_bs_simple.p\", \"rb\"))\n",
    "fits[\"exp2\"][\"Bayesian Sampler complex\"] = pickle.load(open(\"local/exp2/az_data_bs.p\", \"rb\"))\n",
    "fits[\"exp2\"][\"Bayesian Sampler simple hier.\"] = pickle.load(open(\"local/exp2/az_data_bs_mlm_simple.p\", \"rb\"))\n",
    "fits[\"exp2\"][\"Bayesian Sampler complex hier.\"] = pickle.load(open(\"local/exp2/az_data_bs_mlm.p\", \"rb\"))\n",
    "fits[\"exp2\"][\"PT+N complex\"] = pickle.load(open(\"local/exp2/az_data_ptn.p\", \"rb\"))\n",
    "fits[\"exp2\"][\"PT+N simple\"] = pickle.load(open(\"local/exp2/az_data_ptn_simple.p\", \"rb\"))\n",
    "fits[\"exp2\"][\"PT+N complex hier.\"] = pickle.load(open(\"local/exp2/az_data_ptn_mlm.p\", \"rb\"))\n",
    "fits[\"exp2\"][\"PT+N simple hier.\"] = pickle.load(open(\"local/exp2/az_data_ptn_mlm_simple.p\", \"rb\"))\n",
    "fits[\"exp2\"][\"Unrestricted BS hier.\"] = pickle.load(open(\"local/exp2/az_data_ptn_mlm_simplecond.p\", \"rb\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "loos = dict()\n",
    "loos[\"exp1\"] = dict()\n",
    "loos[\"exp2\"] = dict()\n",
    "\n",
    "loos[\"exp1\"][\"Relative Freq.\"] = pickle.load(open(\"local/exp1/loo_rf.p\", \"rb\"))\n",
    "loos[\"exp1\"][\"Bayesian Sampler simple\"] = pickle.load(open(\"local/exp1/loo_bs_simple.p\", \"rb\"))\n",
    "loos[\"exp1\"][\"Bayesian Sampler complex\"] = pickle.load(open(\"local/exp1/loo_bs.p\", \"rb\"))\n",
    "loos[\"exp1\"][\"Bayesian Sampler simple hier.\"] = pickle.load(open(\"local/exp1/loo_bs_mlm_simple.p\", \"rb\"))\n",
    "loos[\"exp1\"][\"Bayesian Sampler complex hier.\"] = pickle.load(open(\"local/exp1/loo_bs_mlm.p\", \"rb\"))\n",
    "loos[\"exp1\"][\"PT+N complex\"] = pickle.load(open(\"local/exp1/loo_ptn.p\", \"rb\"))\n",
    "loos[\"exp1\"][\"PT+N simple\"] = pickle.load(open(\"local/exp1/loo_ptn_simple.p\", \"rb\"))\n",
    "loos[\"exp1\"][\"PT+N complex hier.\"] = pickle.load(open(\"local/exp1/loo_ptn_mlm.p\", \"rb\"))\n",
    "loos[\"exp1\"][\"PT+N simple hier.\"] = pickle.load(open(\"local/exp1/loo_ptn_mlm_simple.p\", \"rb\"))\n",
    "loos[\"exp1\"][\"Unrestricted BS hier.\"] = pickle.load(open(\"local/exp1/loo_ptn_mlm_simplecond.p\", \"rb\"))\n",
    "\n",
    "loos[\"exp2\"][\"Relative Freq.\"] = pickle.load(open(\"local/exp2/loo_rf.p\", \"rb\"))\n",
    "loos[\"exp2\"][\"Bayesian Sampler simple\"] = pickle.load(open(\"local/exp2/loo_bs_simple.p\", \"rb\"))\n",
    "loos[\"exp2\"][\"Bayesian Sampler complex\"] = pickle.load(open(\"local/exp2/loo_bs.p\", \"rb\"))\n",
    "loos[\"exp2\"][\"Bayesian Sampler simple hier.\"] = pickle.load(open(\"local/exp2/loo_bs_mlm_simple.p\", \"rb\"))\n",
    "loos[\"exp2\"][\"Bayesian Sampler complex hier.\"] = pickle.load(open(\"local/exp2/loo_bs_mlm.p\", \"rb\"))\n",
    "loos[\"exp2\"][\"PT+N complex\"] = pickle.load(open(\"local/exp2/loo_ptn.p\", \"rb\"))\n",
    "loos[\"exp2\"][\"PT+N simple\"] = pickle.load(open(\"local/exp2/loo_ptn_simple.p\", \"rb\"))\n",
    "loos[\"exp2\"][\"PT+N complex hier.\"] = pickle.load(open(\"local/exp2/loo_ptn_mlm.p\", \"rb\"))\n",
    "loos[\"exp2\"][\"PT+N simple hier.\"] = pickle.load(open(\"local/exp2/loo_ptn_mlm_simple.p\", \"rb\"))\n",
    "loos[\"exp2\"][\"Unrestricted BS hier.\"] = pickle.load(open(\"local/exp2/loo_ptn_mlm_simplecond.p\", \"rb\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/derekpowell/Projects/Repositories/bayesian-sampler/lib/icc.py:671: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  ics = ics.append([dataset])\n",
      "/Users/derekpowell/Projects/Repositories/bayesian-sampler/lib/icc.py:671: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  ics = ics.append([dataset])\n",
      "/Users/derekpowell/Projects/Repositories/bayesian-sampler/lib/icc.py:671: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  ics = ics.append([dataset])\n",
      "/Users/derekpowell/Projects/Repositories/bayesian-sampler/lib/icc.py:671: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  ics = ics.append([dataset])\n",
      "/Users/derekpowell/Projects/Repositories/bayesian-sampler/lib/icc.py:671: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  ics = ics.append([dataset])\n",
      "/Users/derekpowell/Projects/Repositories/bayesian-sampler/lib/icc.py:671: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  ics = ics.append([dataset])\n",
      "/Users/derekpowell/Projects/Repositories/bayesian-sampler/lib/icc.py:671: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  ics = ics.append([dataset])\n",
      "/Users/derekpowell/Projects/Repositories/bayesian-sampler/lib/icc.py:671: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  ics = ics.append([dataset])\n",
      "/Users/derekpowell/Projects/Repositories/bayesian-sampler/lib/icc.py:671: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  ics = ics.append([dataset])\n",
      "/Users/derekpowell/Projects/Repositories/bayesian-sampler/lib/icc.py:671: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  ics = ics.append([dataset])\n",
      "/Users/derekpowell/Projects/Repositories/bayesian-sampler/lib/icc.py:671: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  ics = ics.append([dataset])\n",
      "/Users/derekpowell/Projects/Repositories/bayesian-sampler/lib/icc.py:671: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  ics = ics.append([dataset])\n",
      "/Users/derekpowell/Projects/Repositories/bayesian-sampler/lib/icc.py:671: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  ics = ics.append([dataset])\n",
      "/Users/derekpowell/Projects/Repositories/bayesian-sampler/lib/icc.py:671: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  ics = ics.append([dataset])\n",
      "/Users/derekpowell/Projects/Repositories/bayesian-sampler/lib/icc.py:671: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  ics = ics.append([dataset])\n",
      "/Users/derekpowell/Projects/Repositories/bayesian-sampler/lib/icc.py:671: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  ics = ics.append([dataset])\n"
     ]
    }
   ],
   "source": [
    "# exp1_model_comparison = az.compare(fits[\"exp1\"], scale=\"deviance\", ic=\"loo\", method=\"BB-pseudo-BMA\")\n",
    "# exp2_model_comparison = az.compare(fits[\"exp2\"], scale=\"deviance\", ic=\"loo\", method=\"BB-pseudo-BMA\")\n",
    "\n",
    "# exp1_model_comparison = exp1_model_comparison >> s.mutate(Experiment = \"Exp. 1\", model = exp1_model_comparison.index)\n",
    "# exp2_model_comparison = exp2_model_comparison >> s.mutate(Experiment = \"Exp. 2\", model = exp2_model_comparison.index)\n",
    "\n",
    "exp1_model_comparison = compare(loos[\"exp1\"], method=\"BB-pseudo-BMA\")\n",
    "exp2_model_comparison = compare(loos[\"exp2\"], method=\"BB-pseudo-BMA\")\n",
    "\n",
    "exp1_model_comparison = exp1_model_comparison >> s.mutate(Experiment = \"Exp. 1\", model = exp1_model_comparison.index)\n",
    "exp2_model_comparison = exp2_model_comparison >> s.mutate(Experiment = \"Exp. 2\", model = exp2_model_comparison.index)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>rank</th>\n",
       "      <th>loo</th>\n",
       "      <th>p_loo</th>\n",
       "      <th>d_loo</th>\n",
       "      <th>weight</th>\n",
       "      <th>se</th>\n",
       "      <th>dse</th>\n",
       "      <th>warning</th>\n",
       "      <th>loo_scale</th>\n",
       "      <th>Experiment</th>\n",
       "      <th>model</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Unrestricted BS hier.</th>\n",
       "      <td>0</td>\n",
       "      <td>1110.611889</td>\n",
       "      <td>267.198466</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.814023e-01</td>\n",
       "      <td>52.535630</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>True</td>\n",
       "      <td>log</td>\n",
       "      <td>Exp. 1</td>\n",
       "      <td>Unrestricted BS hier.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bayesian Sampler complex</th>\n",
       "      <td>1</td>\n",
       "      <td>1076.279129</td>\n",
       "      <td>276.030389</td>\n",
       "      <td>34.332761</td>\n",
       "      <td>1.846676e-02</td>\n",
       "      <td>47.672372</td>\n",
       "      <td>18.679564</td>\n",
       "      <td>True</td>\n",
       "      <td>log</td>\n",
       "      <td>Exp. 1</td>\n",
       "      <td>Bayesian Sampler complex</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bayesian Sampler complex hier.</th>\n",
       "      <td>2</td>\n",
       "      <td>1071.921901</td>\n",
       "      <td>285.579599</td>\n",
       "      <td>38.689989</td>\n",
       "      <td>1.292998e-04</td>\n",
       "      <td>50.444762</td>\n",
       "      <td>16.756306</td>\n",
       "      <td>True</td>\n",
       "      <td>log</td>\n",
       "      <td>Exp. 1</td>\n",
       "      <td>Bayesian Sampler complex hier.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bayesian Sampler simple</th>\n",
       "      <td>3</td>\n",
       "      <td>1045.174803</td>\n",
       "      <td>253.552087</td>\n",
       "      <td>65.437087</td>\n",
       "      <td>1.614178e-06</td>\n",
       "      <td>46.668741</td>\n",
       "      <td>21.946914</td>\n",
       "      <td>True</td>\n",
       "      <td>log</td>\n",
       "      <td>Exp. 1</td>\n",
       "      <td>Bayesian Sampler simple</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bayesian Sampler simple hier.</th>\n",
       "      <td>4</td>\n",
       "      <td>1032.288531</td>\n",
       "      <td>266.158386</td>\n",
       "      <td>78.323359</td>\n",
       "      <td>1.357987e-10</td>\n",
       "      <td>49.369520</td>\n",
       "      <td>24.027210</td>\n",
       "      <td>True</td>\n",
       "      <td>log</td>\n",
       "      <td>Exp. 1</td>\n",
       "      <td>Bayesian Sampler simple hier.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PT+N complex hier.</th>\n",
       "      <td>5</td>\n",
       "      <td>988.731121</td>\n",
       "      <td>273.269651</td>\n",
       "      <td>121.880768</td>\n",
       "      <td>4.028813e-44</td>\n",
       "      <td>44.674485</td>\n",
       "      <td>9.998794</td>\n",
       "      <td>True</td>\n",
       "      <td>log</td>\n",
       "      <td>Exp. 1</td>\n",
       "      <td>PT+N complex hier.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PT+N complex</th>\n",
       "      <td>6</td>\n",
       "      <td>980.479881</td>\n",
       "      <td>245.884383</td>\n",
       "      <td>130.132009</td>\n",
       "      <td>1.315781e-37</td>\n",
       "      <td>40.299727</td>\n",
       "      <td>14.117065</td>\n",
       "      <td>True</td>\n",
       "      <td>log</td>\n",
       "      <td>Exp. 1</td>\n",
       "      <td>PT+N complex</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PT+N simple</th>\n",
       "      <td>7</td>\n",
       "      <td>873.166526</td>\n",
       "      <td>236.171479</td>\n",
       "      <td>237.445363</td>\n",
       "      <td>8.232626e-76</td>\n",
       "      <td>36.211737</td>\n",
       "      <td>24.008039</td>\n",
       "      <td>True</td>\n",
       "      <td>log</td>\n",
       "      <td>Exp. 1</td>\n",
       "      <td>PT+N simple</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PT+N simple hier.</th>\n",
       "      <td>8</td>\n",
       "      <td>860.285045</td>\n",
       "      <td>254.127554</td>\n",
       "      <td>250.326845</td>\n",
       "      <td>4.261730e-87</td>\n",
       "      <td>48.047865</td>\n",
       "      <td>25.226264</td>\n",
       "      <td>True</td>\n",
       "      <td>log</td>\n",
       "      <td>Exp. 1</td>\n",
       "      <td>PT+N simple hier.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Relative Freq.</th>\n",
       "      <td>9</td>\n",
       "      <td>629.272406</td>\n",
       "      <td>309.041296</td>\n",
       "      <td>481.339483</td>\n",
       "      <td>2.470008e-175</td>\n",
       "      <td>42.256370</td>\n",
       "      <td>31.282944</td>\n",
       "      <td>True</td>\n",
       "      <td>log</td>\n",
       "      <td>Exp. 1</td>\n",
       "      <td>Relative Freq.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                rank          loo       p_loo       d_loo  \\\n",
       "Unrestricted BS hier.              0  1110.611889  267.198466    0.000000   \n",
       "Bayesian Sampler complex           1  1076.279129  276.030389   34.332761   \n",
       "Bayesian Sampler complex hier.     2  1071.921901  285.579599   38.689989   \n",
       "Bayesian Sampler simple            3  1045.174803  253.552087   65.437087   \n",
       "Bayesian Sampler simple hier.      4  1032.288531  266.158386   78.323359   \n",
       "PT+N complex hier.                 5   988.731121  273.269651  121.880768   \n",
       "PT+N complex                       6   980.479881  245.884383  130.132009   \n",
       "PT+N simple                        7   873.166526  236.171479  237.445363   \n",
       "PT+N simple hier.                  8   860.285045  254.127554  250.326845   \n",
       "Relative Freq.                     9   629.272406  309.041296  481.339483   \n",
       "\n",
       "                                       weight         se        dse  warning  \\\n",
       "Unrestricted BS hier.            9.814023e-01  52.535630   0.000000     True   \n",
       "Bayesian Sampler complex         1.846676e-02  47.672372  18.679564     True   \n",
       "Bayesian Sampler complex hier.   1.292998e-04  50.444762  16.756306     True   \n",
       "Bayesian Sampler simple          1.614178e-06  46.668741  21.946914     True   \n",
       "Bayesian Sampler simple hier.    1.357987e-10  49.369520  24.027210     True   \n",
       "PT+N complex hier.               4.028813e-44  44.674485   9.998794     True   \n",
       "PT+N complex                     1.315781e-37  40.299727  14.117065     True   \n",
       "PT+N simple                      8.232626e-76  36.211737  24.008039     True   \n",
       "PT+N simple hier.                4.261730e-87  48.047865  25.226264     True   \n",
       "Relative Freq.                  2.470008e-175  42.256370  31.282944     True   \n",
       "\n",
       "                               loo_scale Experiment  \\\n",
       "Unrestricted BS hier.                log     Exp. 1   \n",
       "Bayesian Sampler complex             log     Exp. 1   \n",
       "Bayesian Sampler complex hier.       log     Exp. 1   \n",
       "Bayesian Sampler simple              log     Exp. 1   \n",
       "Bayesian Sampler simple hier.        log     Exp. 1   \n",
       "PT+N complex hier.                   log     Exp. 1   \n",
       "PT+N complex                         log     Exp. 1   \n",
       "PT+N simple                          log     Exp. 1   \n",
       "PT+N simple hier.                    log     Exp. 1   \n",
       "Relative Freq.                       log     Exp. 1   \n",
       "\n",
       "                                                         model  \n",
       "Unrestricted BS hier.                    Unrestricted BS hier.  \n",
       "Bayesian Sampler complex              Bayesian Sampler complex  \n",
       "Bayesian Sampler complex hier.  Bayesian Sampler complex hier.  \n",
       "Bayesian Sampler simple                Bayesian Sampler simple  \n",
       "Bayesian Sampler simple hier.    Bayesian Sampler simple hier.  \n",
       "PT+N complex hier.                          PT+N complex hier.  \n",
       "PT+N complex                                      PT+N complex  \n",
       "PT+N simple                                        PT+N simple  \n",
       "PT+N simple hier.                            PT+N simple hier.  \n",
       "Relative Freq.                                  Relative Freq.  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "exp1_model_comparison"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/_g/mndhmt091j90xgl5ppfk0hbr0000gn/T/ipykernel_93779/4026912646.py:5: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "/Users/derekpowell/anaconda3/envs/bsampler/lib/python3.9/site-packages/plotnine/ggplot.py:718: PlotnineWarning: Saving 6.4 x 4.8 in image.\n",
      "/Users/derekpowell/anaconda3/envs/bsampler/lib/python3.9/site-packages/plotnine/ggplot.py:719: PlotnineWarning: Filename: paper-rmd/plot_compare.png\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (8760460060922)>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from plotnine import *\n",
    "import siuba as s\n",
    "from siuba import _\n",
    "\n",
    "model_comparison = exp1_model_comparison.append(exp2_model_comparison)\n",
    "\n",
    "plt_compare = (\n",
    "    model_comparison >>\n",
    "    s.filter(_.model!=\"Relative Freq.\") >>\n",
    "    s.mutate(ul = _.d_loo + _.dse*2, ll = _.d_loo - _.dse*2) >>\n",
    "    ggplot(aes(y=\"reorder(model, -d_loo)\",  x= \"d_loo\", xmin=\"ll\", xmax=\"ul\")) +\n",
    "    geom_point(size=2) +\n",
    "    geom_vline(xintercept=0, linetype=\"dashed\", color=\"grey\") +\n",
    "    geom_errorbarh(height=.01, size=.5) +\n",
    "    facet_wrap(\"Experiment\", scales=\"free_x\") +\n",
    "    labs(x = \"$\\\\widehat{elpd}_{LOO}$ difference\", y = \"Model\") +\n",
    "    theme_bw() +\n",
    "    theme(panel_grid = element_blank())\n",
    ")\n",
    "plt_compare.save(filename=\"paper-rmd/plot_compare.png\")\n",
    "plt_compare"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>rank</th>\n",
       "      <th>loo</th>\n",
       "      <th>p_loo</th>\n",
       "      <th>d_loo</th>\n",
       "      <th>weight</th>\n",
       "      <th>se</th>\n",
       "      <th>dse</th>\n",
       "      <th>warning</th>\n",
       "      <th>loo_scale</th>\n",
       "      <th>Experiment</th>\n",
       "      <th>model</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Unrestricted BS hier.</th>\n",
       "      <td>0</td>\n",
       "      <td>1110.611889</td>\n",
       "      <td>267.198466</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.814023e-01</td>\n",
       "      <td>52.535630</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>True</td>\n",
       "      <td>log</td>\n",
       "      <td>Exp. 1</td>\n",
       "      <td>Unrestricted BS hier.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bayesian Sampler complex</th>\n",
       "      <td>1</td>\n",
       "      <td>1076.279129</td>\n",
       "      <td>276.030389</td>\n",
       "      <td>34.332761</td>\n",
       "      <td>1.846676e-02</td>\n",
       "      <td>47.672372</td>\n",
       "      <td>18.679564</td>\n",
       "      <td>True</td>\n",
       "      <td>log</td>\n",
       "      <td>Exp. 1</td>\n",
       "      <td>Bayesian Sampler complex</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bayesian Sampler complex hier.</th>\n",
       "      <td>2</td>\n",
       "      <td>1071.921901</td>\n",
       "      <td>285.579599</td>\n",
       "      <td>38.689989</td>\n",
       "      <td>1.292998e-04</td>\n",
       "      <td>50.444762</td>\n",
       "      <td>16.756306</td>\n",
       "      <td>True</td>\n",
       "      <td>log</td>\n",
       "      <td>Exp. 1</td>\n",
       "      <td>Bayesian Sampler complex hier.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bayesian Sampler simple</th>\n",
       "      <td>3</td>\n",
       "      <td>1045.174803</td>\n",
       "      <td>253.552087</td>\n",
       "      <td>65.437087</td>\n",
       "      <td>1.614178e-06</td>\n",
       "      <td>46.668741</td>\n",
       "      <td>21.946914</td>\n",
       "      <td>True</td>\n",
       "      <td>log</td>\n",
       "      <td>Exp. 1</td>\n",
       "      <td>Bayesian Sampler simple</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bayesian Sampler simple hier.</th>\n",
       "      <td>4</td>\n",
       "      <td>1032.288531</td>\n",
       "      <td>266.158386</td>\n",
       "      <td>78.323359</td>\n",
       "      <td>1.357987e-10</td>\n",
       "      <td>49.369520</td>\n",
       "      <td>24.027210</td>\n",
       "      <td>True</td>\n",
       "      <td>log</td>\n",
       "      <td>Exp. 1</td>\n",
       "      <td>Bayesian Sampler simple hier.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PT+N complex hier.</th>\n",
       "      <td>5</td>\n",
       "      <td>988.731121</td>\n",
       "      <td>273.269651</td>\n",
       "      <td>121.880768</td>\n",
       "      <td>4.028813e-44</td>\n",
       "      <td>44.674485</td>\n",
       "      <td>9.998794</td>\n",
       "      <td>True</td>\n",
       "      <td>log</td>\n",
       "      <td>Exp. 1</td>\n",
       "      <td>PT+N complex hier.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PT+N complex</th>\n",
       "      <td>6</td>\n",
       "      <td>980.479881</td>\n",
       "      <td>245.884383</td>\n",
       "      <td>130.132009</td>\n",
       "      <td>1.315781e-37</td>\n",
       "      <td>40.299727</td>\n",
       "      <td>14.117065</td>\n",
       "      <td>True</td>\n",
       "      <td>log</td>\n",
       "      <td>Exp. 1</td>\n",
       "      <td>PT+N complex</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PT+N simple</th>\n",
       "      <td>7</td>\n",
       "      <td>873.166526</td>\n",
       "      <td>236.171479</td>\n",
       "      <td>237.445363</td>\n",
       "      <td>8.232626e-76</td>\n",
       "      <td>36.211737</td>\n",
       "      <td>24.008039</td>\n",
       "      <td>True</td>\n",
       "      <td>log</td>\n",
       "      <td>Exp. 1</td>\n",
       "      <td>PT+N simple</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PT+N simple hier.</th>\n",
       "      <td>8</td>\n",
       "      <td>860.285045</td>\n",
       "      <td>254.127554</td>\n",
       "      <td>250.326845</td>\n",
       "      <td>4.261730e-87</td>\n",
       "      <td>48.047865</td>\n",
       "      <td>25.226264</td>\n",
       "      <td>True</td>\n",
       "      <td>log</td>\n",
       "      <td>Exp. 1</td>\n",
       "      <td>PT+N simple hier.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Relative Freq.</th>\n",
       "      <td>9</td>\n",
       "      <td>629.272406</td>\n",
       "      <td>309.041296</td>\n",
       "      <td>481.339483</td>\n",
       "      <td>2.470008e-175</td>\n",
       "      <td>42.256370</td>\n",
       "      <td>31.282944</td>\n",
       "      <td>True</td>\n",
       "      <td>log</td>\n",
       "      <td>Exp. 1</td>\n",
       "      <td>Relative Freq.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Unrestricted BS hier.</th>\n",
       "      <td>0</td>\n",
       "      <td>1981.644618</td>\n",
       "      <td>362.995311</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>45.904263</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>True</td>\n",
       "      <td>log</td>\n",
       "      <td>Exp. 2</td>\n",
       "      <td>Unrestricted BS hier.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bayesian Sampler complex hier.</th>\n",
       "      <td>1</td>\n",
       "      <td>1907.006068</td>\n",
       "      <td>400.536815</td>\n",
       "      <td>74.638549</td>\n",
       "      <td>3.080374e-13</td>\n",
       "      <td>40.167248</td>\n",
       "      <td>12.451867</td>\n",
       "      <td>True</td>\n",
       "      <td>log</td>\n",
       "      <td>Exp. 2</td>\n",
       "      <td>Bayesian Sampler complex hier.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PT+N complex hier.</th>\n",
       "      <td>2</td>\n",
       "      <td>1901.904880</td>\n",
       "      <td>351.710854</td>\n",
       "      <td>79.739738</td>\n",
       "      <td>6.726010e-18</td>\n",
       "      <td>41.128103</td>\n",
       "      <td>12.631937</td>\n",
       "      <td>True</td>\n",
       "      <td>log</td>\n",
       "      <td>Exp. 2</td>\n",
       "      <td>PT+N complex hier.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bayesian Sampler simple hier.</th>\n",
       "      <td>3</td>\n",
       "      <td>1898.541468</td>\n",
       "      <td>379.336391</td>\n",
       "      <td>83.103149</td>\n",
       "      <td>2.008353e-18</td>\n",
       "      <td>40.830757</td>\n",
       "      <td>13.643313</td>\n",
       "      <td>True</td>\n",
       "      <td>log</td>\n",
       "      <td>Exp. 2</td>\n",
       "      <td>Bayesian Sampler simple hier.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PT+N complex</th>\n",
       "      <td>4</td>\n",
       "      <td>1895.292139</td>\n",
       "      <td>386.576881</td>\n",
       "      <td>86.352478</td>\n",
       "      <td>2.027968e-22</td>\n",
       "      <td>43.130950</td>\n",
       "      <td>12.543560</td>\n",
       "      <td>True</td>\n",
       "      <td>log</td>\n",
       "      <td>Exp. 2</td>\n",
       "      <td>PT+N complex</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bayesian Sampler complex</th>\n",
       "      <td>5</td>\n",
       "      <td>1864.709734</td>\n",
       "      <td>455.166118</td>\n",
       "      <td>116.934883</td>\n",
       "      <td>1.175739e-33</td>\n",
       "      <td>40.216174</td>\n",
       "      <td>14.163498</td>\n",
       "      <td>True</td>\n",
       "      <td>log</td>\n",
       "      <td>Exp. 2</td>\n",
       "      <td>Bayesian Sampler complex</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bayesian Sampler simple</th>\n",
       "      <td>6</td>\n",
       "      <td>1863.669638</td>\n",
       "      <td>416.109161</td>\n",
       "      <td>117.974980</td>\n",
       "      <td>8.936078e-31</td>\n",
       "      <td>41.123184</td>\n",
       "      <td>15.690673</td>\n",
       "      <td>True</td>\n",
       "      <td>log</td>\n",
       "      <td>Exp. 2</td>\n",
       "      <td>Bayesian Sampler simple</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PT+N simple</th>\n",
       "      <td>7</td>\n",
       "      <td>1821.056230</td>\n",
       "      <td>319.899010</td>\n",
       "      <td>160.588387</td>\n",
       "      <td>1.050835e-47</td>\n",
       "      <td>42.113498</td>\n",
       "      <td>18.234468</td>\n",
       "      <td>False</td>\n",
       "      <td>log</td>\n",
       "      <td>Exp. 2</td>\n",
       "      <td>PT+N simple</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PT+N simple hier.</th>\n",
       "      <td>8</td>\n",
       "      <td>1820.587806</td>\n",
       "      <td>305.709387</td>\n",
       "      <td>161.056812</td>\n",
       "      <td>2.494055e-48</td>\n",
       "      <td>40.574635</td>\n",
       "      <td>18.350878</td>\n",
       "      <td>False</td>\n",
       "      <td>log</td>\n",
       "      <td>Exp. 2</td>\n",
       "      <td>PT+N simple hier.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Relative Freq.</th>\n",
       "      <td>9</td>\n",
       "      <td>645.545835</td>\n",
       "      <td>423.025424</td>\n",
       "      <td>1336.098783</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>40.476405</td>\n",
       "      <td>44.099373</td>\n",
       "      <td>True</td>\n",
       "      <td>log</td>\n",
       "      <td>Exp. 2</td>\n",
       "      <td>Relative Freq.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                rank          loo       p_loo        d_loo  \\\n",
       "Unrestricted BS hier.              0  1110.611889  267.198466     0.000000   \n",
       "Bayesian Sampler complex           1  1076.279129  276.030389    34.332761   \n",
       "Bayesian Sampler complex hier.     2  1071.921901  285.579599    38.689989   \n",
       "Bayesian Sampler simple            3  1045.174803  253.552087    65.437087   \n",
       "Bayesian Sampler simple hier.      4  1032.288531  266.158386    78.323359   \n",
       "PT+N complex hier.                 5   988.731121  273.269651   121.880768   \n",
       "PT+N complex                       6   980.479881  245.884383   130.132009   \n",
       "PT+N simple                        7   873.166526  236.171479   237.445363   \n",
       "PT+N simple hier.                  8   860.285045  254.127554   250.326845   \n",
       "Relative Freq.                     9   629.272406  309.041296   481.339483   \n",
       "Unrestricted BS hier.              0  1981.644618  362.995311     0.000000   \n",
       "Bayesian Sampler complex hier.     1  1907.006068  400.536815    74.638549   \n",
       "PT+N complex hier.                 2  1901.904880  351.710854    79.739738   \n",
       "Bayesian Sampler simple hier.      3  1898.541468  379.336391    83.103149   \n",
       "PT+N complex                       4  1895.292139  386.576881    86.352478   \n",
       "Bayesian Sampler complex           5  1864.709734  455.166118   116.934883   \n",
       "Bayesian Sampler simple            6  1863.669638  416.109161   117.974980   \n",
       "PT+N simple                        7  1821.056230  319.899010   160.588387   \n",
       "PT+N simple hier.                  8  1820.587806  305.709387   161.056812   \n",
       "Relative Freq.                     9   645.545835  423.025424  1336.098783   \n",
       "\n",
       "                                       weight         se        dse  warning  \\\n",
       "Unrestricted BS hier.            9.814023e-01  52.535630   0.000000     True   \n",
       "Bayesian Sampler complex         1.846676e-02  47.672372  18.679564     True   \n",
       "Bayesian Sampler complex hier.   1.292998e-04  50.444762  16.756306     True   \n",
       "Bayesian Sampler simple          1.614178e-06  46.668741  21.946914     True   \n",
       "Bayesian Sampler simple hier.    1.357987e-10  49.369520  24.027210     True   \n",
       "PT+N complex hier.               4.028813e-44  44.674485   9.998794     True   \n",
       "PT+N complex                     1.315781e-37  40.299727  14.117065     True   \n",
       "PT+N simple                      8.232626e-76  36.211737  24.008039     True   \n",
       "PT+N simple hier.                4.261730e-87  48.047865  25.226264     True   \n",
       "Relative Freq.                  2.470008e-175  42.256370  31.282944     True   \n",
       "Unrestricted BS hier.            1.000000e+00  45.904263   0.000000     True   \n",
       "Bayesian Sampler complex hier.   3.080374e-13  40.167248  12.451867     True   \n",
       "PT+N complex hier.               6.726010e-18  41.128103  12.631937     True   \n",
       "Bayesian Sampler simple hier.    2.008353e-18  40.830757  13.643313     True   \n",
       "PT+N complex                     2.027968e-22  43.130950  12.543560     True   \n",
       "Bayesian Sampler complex         1.175739e-33  40.216174  14.163498     True   \n",
       "Bayesian Sampler simple          8.936078e-31  41.123184  15.690673     True   \n",
       "PT+N simple                      1.050835e-47  42.113498  18.234468    False   \n",
       "PT+N simple hier.                2.494055e-48  40.574635  18.350878    False   \n",
       "Relative Freq.                   0.000000e+00  40.476405  44.099373     True   \n",
       "\n",
       "                               loo_scale Experiment  \\\n",
       "Unrestricted BS hier.                log     Exp. 1   \n",
       "Bayesian Sampler complex             log     Exp. 1   \n",
       "Bayesian Sampler complex hier.       log     Exp. 1   \n",
       "Bayesian Sampler simple              log     Exp. 1   \n",
       "Bayesian Sampler simple hier.        log     Exp. 1   \n",
       "PT+N complex hier.                   log     Exp. 1   \n",
       "PT+N complex                         log     Exp. 1   \n",
       "PT+N simple                          log     Exp. 1   \n",
       "PT+N simple hier.                    log     Exp. 1   \n",
       "Relative Freq.                       log     Exp. 1   \n",
       "Unrestricted BS hier.                log     Exp. 2   \n",
       "Bayesian Sampler complex hier.       log     Exp. 2   \n",
       "PT+N complex hier.                   log     Exp. 2   \n",
       "Bayesian Sampler simple hier.        log     Exp. 2   \n",
       "PT+N complex                         log     Exp. 2   \n",
       "Bayesian Sampler complex             log     Exp. 2   \n",
       "Bayesian Sampler simple              log     Exp. 2   \n",
       "PT+N simple                          log     Exp. 2   \n",
       "PT+N simple hier.                    log     Exp. 2   \n",
       "Relative Freq.                       log     Exp. 2   \n",
       "\n",
       "                                                         model  \n",
       "Unrestricted BS hier.                    Unrestricted BS hier.  \n",
       "Bayesian Sampler complex              Bayesian Sampler complex  \n",
       "Bayesian Sampler complex hier.  Bayesian Sampler complex hier.  \n",
       "Bayesian Sampler simple                Bayesian Sampler simple  \n",
       "Bayesian Sampler simple hier.    Bayesian Sampler simple hier.  \n",
       "PT+N complex hier.                          PT+N complex hier.  \n",
       "PT+N complex                                      PT+N complex  \n",
       "PT+N simple                                        PT+N simple  \n",
       "PT+N simple hier.                            PT+N simple hier.  \n",
       "Relative Freq.                                  Relative Freq.  \n",
       "Unrestricted BS hier.                    Unrestricted BS hier.  \n",
       "Bayesian Sampler complex hier.  Bayesian Sampler complex hier.  \n",
       "PT+N complex hier.                          PT+N complex hier.  \n",
       "Bayesian Sampler simple hier.    Bayesian Sampler simple hier.  \n",
       "PT+N complex                                      PT+N complex  \n",
       "Bayesian Sampler complex              Bayesian Sampler complex  \n",
       "Bayesian Sampler simple                Bayesian Sampler simple  \n",
       "PT+N simple                                        PT+N simple  \n",
       "PT+N simple hier.                            PT+N simple hier.  \n",
       "Relative Freq.                                  Relative Freq.  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model_comparison"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Model parameters\n",
    "\n",
    "## Experiment 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>sd</th>\n",
       "      <th>hdi_3%</th>\n",
       "      <th>hdi_97%</th>\n",
       "      <th>mcse_mean</th>\n",
       "      <th>mcse_sd</th>\n",
       "      <th>ess_bulk</th>\n",
       "      <th>ess_tail</th>\n",
       "      <th>r_hat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>d_base_sd</th>\n",
       "      <td>1.437</td>\n",
       "      <td>0.187</td>\n",
       "      <td>1.099</td>\n",
       "      <td>1.782</td>\n",
       "      <td>0.004</td>\n",
       "      <td>0.003</td>\n",
       "      <td>2011.0</td>\n",
       "      <td>3822.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d_delta_sd</th>\n",
       "      <td>1.052</td>\n",
       "      <td>0.279</td>\n",
       "      <td>0.560</td>\n",
       "      <td>1.569</td>\n",
       "      <td>0.005</td>\n",
       "      <td>0.004</td>\n",
       "      <td>2907.0</td>\n",
       "      <td>4164.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             mean     sd  hdi_3%  hdi_97%  mcse_mean  mcse_sd  ess_bulk  \\\n",
       "d_base_sd   1.437  0.187   1.099    1.782      0.004    0.003    2011.0   \n",
       "d_delta_sd  1.052  0.279   0.560    1.569      0.005    0.004    2907.0   \n",
       "\n",
       "            ess_tail  r_hat  \n",
       "d_base_sd     3822.0    1.0  \n",
       "d_delta_sd    4164.0    1.0  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model1 = fits[\"exp1\"][\"Unrestricted BS hier.\"]\n",
    "\n",
    "az.summary(\n",
    "    model1,\n",
    "    var_names = [\"d_base_sd\", \"d_delta_sd\"]\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "model1.posterior[\"d_prime_pop\"] = model1.posterior.d_base_pop + np.exp(model1.posterior.d_delta_pop)\n",
    "# az.plot_posterior(model1, var_names = [\"d_base_pop\", \"d_prime_pop\"], transform=lambda x: np.exp(-np.logaddexp(0, -x))/2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (8760362533599)>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# plot them all\n",
    "# az.plot_forest(data=model1, var_names=[\"d_subj\"], combined=True)\n",
    "# az.plot_forest(data=model1, var_names=[\"d_prime_subj\"], combined=True)\n",
    "\n",
    "from re import X\n",
    "\n",
    "\n",
    "post1 = posterior_to_df_mlm(model1, [\"k\"], [\"d_subj\", \"d_prime_subj\"])\n",
    "\n",
    "(\n",
    "    posterior_to_df_mlm(model1, [\"k\"], [\"d_subj\", \"d_prime_subj\"]) >>\n",
    "    s.gather(\"var\", \"val\", _.d_subj, _.d_prime_subj) >>\n",
    "    s.group_by(_.ID, _.var) >>\n",
    "    s.summarize(\n",
    "        M = _.val.mean(),\n",
    "        ll = _.val.quantile(.025),\n",
    "        ul = _.val.quantile(.975),\n",
    "    ) >>\n",
    "    ggplot(aes(x=\"reorder(ID,M)\", y=\"M\", ymin=\"ll\", ymax=\"ul\", color=\"var\")) +\n",
    "    geom_pointrange(position=position_dodge(width=1)) +\n",
    "    labs(color=\"Variable\", x = \"Participant\", y = \"Estimate\") +\n",
    "    theme_bw() +\n",
    "    theme(\n",
    "        panel_grid = element_blank(), \n",
    "        legend_position=\"bottom\", \n",
    "        legend_box_spacing=.5,\n",
    "        axis_text_x = element_text(angle=90, hjust=.5, vjust=1)\n",
    "        )\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<xarray.DataArray 'd_subj' ()>\n",
      "array(11)\n",
      "<xarray.DataArray 'd_prime_subj' ()>\n",
      "array(18)\n"
     ]
    }
   ],
   "source": [
    "# how many individual participant estimates are over .33 ?\n",
    "print(np.sum(model1.posterior.stack(draws=(\"chain\", \"draw\")).d_subj.mean(axis=1) > 1/3))\n",
    "print(np.sum(model1.posterior.stack(draws=(\"chain\", \"draw\")).d_prime_subj.mean(axis=1) > 1/3))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Experiment 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>sd</th>\n",
       "      <th>hdi_3%</th>\n",
       "      <th>hdi_97%</th>\n",
       "      <th>mcse_mean</th>\n",
       "      <th>mcse_sd</th>\n",
       "      <th>ess_bulk</th>\n",
       "      <th>ess_tail</th>\n",
       "      <th>r_hat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>d_base_sd</th>\n",
       "      <td>0.807</td>\n",
       "      <td>0.099</td>\n",
       "      <td>0.623</td>\n",
       "      <td>0.993</td>\n",
       "      <td>0.002</td>\n",
       "      <td>0.002</td>\n",
       "      <td>1928.0</td>\n",
       "      <td>3547.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d_delta_sd</th>\n",
       "      <td>0.206</td>\n",
       "      <td>0.128</td>\n",
       "      <td>0.015</td>\n",
       "      <td>0.433</td>\n",
       "      <td>0.002</td>\n",
       "      <td>0.001</td>\n",
       "      <td>3864.0</td>\n",
       "      <td>4990.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             mean     sd  hdi_3%  hdi_97%  mcse_mean  mcse_sd  ess_bulk  \\\n",
       "d_base_sd   0.807  0.099   0.623    0.993      0.002    0.002    1928.0   \n",
       "d_delta_sd  0.206  0.128   0.015    0.433      0.002    0.001    3864.0   \n",
       "\n",
       "            ess_tail  r_hat  \n",
       "d_base_sd     3547.0    1.0  \n",
       "d_delta_sd    4990.0    1.0  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model2 = fits[\"exp2\"][\"Unrestricted BS hier.\"]\n",
    "\n",
    "az.summary(\n",
    "    model2,\n",
    "    var_names = [\"d_base_sd\", \"d_delta_sd\"]\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/_g/mndhmt091j90xgl5ppfk0hbr0000gn/T/ipykernel_93779/3311883561.py:11: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "/Users/derekpowell/anaconda3/envs/bsampler/lib/python3.9/site-packages/plotnine/ggplot.py:718: PlotnineWarning: Saving 6.4 x 4.8 in image.\n",
      "/Users/derekpowell/anaconda3/envs/bsampler/lib/python3.9/site-packages/plotnine/ggplot.py:719: PlotnineWarning: Filename: paper-rmd/plot_params.png\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x485.39 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (8760324320509)>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model2 = fits[\"exp2\"][\"Unrestricted BS hier.\"]\n",
    "model2.posterior[\"d_prime_pop\"] = model2.posterior.d_base_pop + np.exp(model2.posterior.d_delta_pop)\n",
    "# az.plot_posterior(model2, var_names = [\"d_base_pop\", \"d_prime_pop\"], transform=lambda x: np.exp(-np.logaddexp(0, -x))/2)\n",
    "param_posterior1 = model1.posterior.stack(draws=(\"chain\", \"draw\"))[[\"d_base_pop\", \"d_prime_pop\"]].to_dataframe()\n",
    "param_posterior2 = model2.posterior.stack(draws=(\"chain\", \"draw\"))[[\"d_base_pop\", \"d_prime_pop\"]].to_dataframe()\n",
    "\n",
    "param_posterior1 = param_posterior1 >> s.mutate(Experiment = \"Exp. 1\")\n",
    "param_posterior2 = param_posterior2 >> s.mutate(Experiment = \"Exp. 2\")\n",
    "\n",
    "plt_params = (\n",
    "    param_posterior1.append(param_posterior2) >> \n",
    "    # s.rename(d = _.d_base_pop, d = _.d_prime_pop) >>\n",
    "    s.gather(\"term\", \"value\", _.d_base_pop, _.d_prime_pop) >>\n",
    "    s.mutate(term = s.if_else(_.term==\"d_base_pop\", \"d\", \"d'\")) >>\n",
    "    s.mutate(value = _.value.transform(lambda x: np.exp(-np.logaddexp(0, -x))/2)) >>\n",
    "    ggplot(aes(x=\"value\")) +\n",
    "    geom_density(fill=\"lightblue\", alpha=.5) +\n",
    "    geom_vline(xintercept=.3333, linetype=\"dashed\", color=\"grey\") +\n",
    "    facet_grid(\"term ~ Experiment\") +\n",
    "    theme_bw() +\n",
    "    theme(aspect_ratio=.75) +\n",
    "    theme(panel_grid = element_blank())\n",
    ")\n",
    "plt_params.save(filename=\"paper-rmd/plot_params.png\")\n",
    "plt_params"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<ggplot: (8760303661734)>"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# # plot them all\n",
    "# az.plot_forest(data=model2, var_names=[\"d_subj\"], combined=True)\n",
    "# az.plot_forest(data=model2, var_names=[\"d_prime_subj\"], combined=True)\n",
    "(\n",
    "    posterior_to_df_mlm(model2, [\"k\"], [\"d_subj\", \"d_prime_subj\"]) >>\n",
    "    s.gather(\"var\", \"val\", _.d_subj, _.d_prime_subj) >>\n",
    "    s.group_by(_.ID, _.var) >>\n",
    "    s.summarize(\n",
    "        M = _.val.mean(),\n",
    "        ll = _.val.quantile(.025),\n",
    "        ul = _.val.quantile(.975),\n",
    "    ) >>\n",
    "    ggplot(aes(x=\"reorder(ID,M)\", y=\"M\", ymin=\"ll\", ymax=\"ul\", color=\"var\")) +\n",
    "    geom_pointrange(position=position_dodge(width=1)) +\n",
    "    labs(color=\"Variable\", x = \"Participant\", y = \"Estimate\") +\n",
    "    theme_bw() +\n",
    "    theme(\n",
    "        panel_grid = element_blank(), \n",
    "        legend_position=\"bottom\", \n",
    "        legend_box_spacing=.5,\n",
    "        axis_text_x = element_text(angle=90, hjust=.5, vjust=1)\n",
    "        )\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<xarray.DataArray 'd_subj' ()>\n",
      "array(37)\n",
      "<xarray.DataArray 'd_prime_subj' ()>\n",
      "array(67)\n"
     ]
    }
   ],
   "source": [
    "# how many individual participant estimates are over .33 ?\n",
    "print(np.sum(model2.posterior.stack(draws=(\"chain\", \"draw\")).d_subj.mean(axis=1) > 1/3))\n",
    "print(np.sum(model2.posterior.stack(draws=(\"chain\", \"draw\")).d_prime_subj.mean(axis=1) > 1/3))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### conditional trials\n",
    "\n",
    "Experiment 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Bayesian Sampler conditional response corr =  0.9061\n",
      "Bayesian Sampler conditional query-level corr 0.9836\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='preds', ylabel='estimate'>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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fNpokWe5M1lSBGyY8HEVTKqYwTWlaeUGfhqnlKiZV0K4ZU8qjtx4OcKOEpqXytTfzanGqELyyVedGx5molcr1HoZBzFbL5KuuN6baumyLA1QLREXFleeicvgsave4WgqFSgfyFBWmrnBr1cmVSls6tqkxcGP+wzv7fObtLqau8Ovv9Xl7z+cPvbbNZ+90ubN/6Ly+tRry2q0OAH0/pjc2UQ3GSfBe2WoedrgNwdjfESUpfS+hVTO51rZwDI0Hw4AkE+NzBA1bY7tTYxjESPJ7tg5z93F77XhF0WfvdHlnz6fnxjwahLjRgJaVV5azDY26Zcz9Hk6TofZpU6mYKiquMMtGEp9Xu7v9w0WjqKVQRBK7UcKdfY8oSdl3Q9498Pnyg1xNtNPNJ+DtTo04S/jC/SFNW8MxNDLg0+90+dRbj6YWB4A7+16+o1jiOcsR3EWkc2N8DzdK0JU8N9Ls9ctGfpfZ7Xvc2c/rQ6w4Bvf7ATvdgCBJadoaozC9lKqk01LtICoqrjAXlcNnUbtD/9DrWqiTYFxLYcwoTKbyF8VJOuWM7vvJZJdRtCCB+/2Aee+sQz9BU+a/y84+ZznY7NbaYdI9P9Lo+wlywfWnDVIrxkHK3Fm+UtfRVIW2rdO2i/rUl0+VdFqqHURFxRVgGMTsDY++kV5UDp9F15fzDBXqJEFeszmMM/xxXAKAECBlLj+NknSy6Kw3zCPJLQRwrWUxS5gkhEnK3iggStIj183rZ1G4pzDlrDUs2o5xZHGYvb583Uk0bC2Xy6bpWLIqUESuVCrucxlVSaelWiAqKi45O12Pd/Y87vdD3tnzJuYaWD4x3mlZ1O5WqzZlxll1dOIso+sljMKUhqnhJwlC5Lr/Az+i7yW8e+Bz4EYAfPB6m9dvdyaTvQBev93h619a59bqoc2+64cg4c2HHl+47/LWnsu+G06uO81znvc4bbVqNCyN3X4eQW2qCpsNc5L6e8W5nKqk01KZmCoqLjHL1Am4qBw+i9pt2Toyk2TAWkPP9f3j+geWphImKaGe8XaUsFozgfyNOxznJWpYOn/otW0+sFXn0TBkvWHywettAF671eF62+ThMGTg6eyN4skbua4oSClp2dqJqp956qvzHKdhELPZtDB1BS+McUwdW1epmQqOoV9aVdJpqRaIiopLzLI+hmWVMbMT50ny2Nl2d7oeO/sebpTiGCoNWxs7fouI6RRTU2lYGkIVxEmKoanEacb9nouhCT6wlbf3wetttoOY3Z7Pp97Zp2npXG/bbLVqaIqCF2TEaUA/iInG7dRNB9s4TNa30/URHCYANHWVvj+9qJpa7kgunrF47r1hMDUO8+pIz5PcFuMvgZZt0LKNyfG1ujkl2S1Y1M5lp1ogKiouMefpY5iVrRaS1OIN/SR57DCI+c93ury9d2jiur1iY1oqXnCYOmLF0fnAVp0gkQhD48sPh7w3LqLT8xPcMOW1Wx12uh7/+U6Xz+8O6XsxlqHwVddbfP2LK7RsHT+OeeP+gHtdn2GYUjNUBkHCrXWHnQOfX3l7n3sHPsMoZr1u8rXbbW60bfb9eCK7fTAMGPoJN1dsDE2dmJnKdaajNOPAiyaO5xUnT5z3cBAulNye5ns5Trp72al8EBUVl5jzsp3PmqoKSWpYUh+dJI/d7flTiwPAOwce/dH0NXEmccy83z0/miwOTVvDUFXu7Hu8/WjIzr7HW3sufS+/Pogy3nw44p09FzeMcaMEKSWjMH9bT7OMLJW8+WDAF3YH3DvwCdOMMJbc7Qa8uefS86Mp2W0x6ReKqwf9gJ3uYcW3MEl58+GQh4NgcuzAjXnn0Ygv7A6mnquQ3MLy30shh13UzmWn2kFUVFxyzsN2PmuqKmSpRfGb8nmL2vdLi4kQkElJEGeoquBa25oUyHEMjTBO2e7U6Loha/VDE0yUphiqyoEb4UZ5kjtVCDRVkGYSRYAfxTwchkSJpGaovLzhIDOJoakg4MCN8KN0nIBvnLAPCOOMOJVTz1cwyQeVSJIspXjoKJHEqSTNDpPqQR6Ul6TTxyCXt2618p+X+V7KsuBF7VxmqgWiouIK8LjRt7OmD11TgXiqTvO888psNExqloofpvhxSt+LsU2FKMkYhcnErFNuZ71hEqXZJEkf5DuJr3GaxGPHtkRyvx8iAT/Og++apkGYZLhhyjBIcAyNIMlwLI1OzUAVCQIfRVGADAFYuoJjqGQyl91ahoYgpm6qxBP/iEBkh89oaAJdFQgxbUxp2Tr94OjkXpb5wsnfy+z5Jx2/bFQmpoqK54BZk4hjaNxarU1FFp9kutpq1XjthQ7tmk6WZbRrOl91rcWNtj0x68y245g6rZmSmy07jzfYXq1xa6VGkGRIwNQFm02TMM4wNIUbbZtrHRtLU0iyDMdUeXHN4atf6PDqVpPrKzamqmDqgu2OxVbTZM+N0bW8BnTdVNlqWYyilPuDgHcPfBB5zYgCU1N530aDjebh4rbi6Nxer/NqOY0HcGu1dmoH81arNiXdPWs7T4sLXcaEEN8O/C1ABX5KSvkjM5+3gP83cHPcl/+HlPLvXWSfKiqeV+aZRE6b5O+1Wx0cU+VOw6Bm5lHDkAeINS2NrbY91U4Yp7yy0WC9YeKF8eSawgRVlAgdRgl1Q8PSVEZhSpBIVhyTb7i1wvvWHQxVYbNlc33c/nanxlbbnKiYaobK/ihCG5u4insjYKt1aP7SVYWWnS9as+Mwq2La7tS43jYfW31USHcrFVMJIYQK/BjwB4Ad4FNCiE9IKd8onfaXgDeklN8lhFgHviiE+IdSyuii+lVR8Sxz3IRfrs9ccJKJpFxLOssyklRiqIIbbYe8hE7u8I6TlBud/C28LB81dfWIHHQUJfiRxm7fQwFWGxY3x5O6G+UBdwLJKEgASd0wuL1uH5lYt1qHb+J740R8ZQp/Q7tmwjgfU88LOXC1SQLB2XEoxq84lt9jycE/hvNq50lzkTuIbwDelFK+BSCE+Bngo0B5gZBAQ+Sx+XXgAJjv1amoqDiW47K6fvZOl3cPvElBnWtti1e3msdKW4ta0j0/Zm8Ucq/nc61ts1oz891C0+L+WEa64uh87t4QTRGsOiaydP9yLYcHwwBDEby957LvxjRtDU0REx+GY2g0LI0Ho5BRcNhXx9JIMm9hX+f5ToySv6GQuwLUjHBcnnS6rYvKinuVucgF4gbwXun3HeAbZ875UeATwD2gAfxRKWVGRUXFqTgu4toNY+7se0iZl+IEuN8LWB+ri+ZVdCvXks6k5O2HLhLojiJq48n4elvi6BodWyfJZF6TGaibGoamTu5fmLYO3Igo0RHAnbH0deAnXG9b1BVB09ZyJzJg+hF9L2KtYaApysS/saj63GxRIYDNcW6nna4/FeNglvpWtLVMxPrzyEUuELN5tYAj+bK+Dfg14FuAl4F/JYT491LKKQGyEOIHgB8AuHnz5vn3tKLiCnCc+ei4iOticiwkoAVumLBany9tLdeSLiSlwFi9FBHpKY+GGoaeLwaeFwL5P3o3TCapN4q2G1Zu8x9o6th0NJbKZpK+F7JatyalRCWgCoWGdSiPjZNcmnqcDHeR7FRmEpmNk+eNq9gVz1icc1FZcWe5qMJOF8VFLhA7wAul37fJdwpl/jTwI1JKCbwphHgbeBX4T+WTpJQfBz4O8Prrr89LylhR8UxzkvnjuMjeQlKpq9PvbI6pLby2XEvaNlQEMIxi0kxlX+RBbRsNk9DNHa91M5eU9vyITMpJRteGpU1STxT3MTQxSea3P8p3CW4kaVga19r25Jwy+lhtdVIE+TyfStsxJoWGypNHua2Lyopb5iqasC5S5vop4BUhxItCCAP4PnJzUpl3gd8HIITYBD4AvHWBfaqouHKctlhOQSE3LaSWiiJYHZuVrrUtVuvWQmlrUUt6xdHRVMH2io2KoG5qhHHGixsOCWCbymSHousCXVVQlPHiUErQV+6jqak0rVx1VLNUbF2bnFv0uyj4U7TjGNqZs68uE/V8UVlxCy6qsNNFc2E7CCllIoT4IeAXyGWuPy2l/JwQ4gfHn38M+G+Bvy+E+E3y3ekPSyn3LqpPFRVXkQM3oueFE0loOVp5tliOphwmhXNMfaIoKqSW+8OQRGa0a9Ykwd28+tJJlmFpCh/YqjP0Ezq2xq0VmzDNSLNx5HMKqi5wDIUwTthsmNR1FaXUx6K94j5+mPBo5JNlGS9t2LQs48i5haloq2Ueqed8VhaZn8rPvmzE+lnMRE/KhHXeXGgchJTyk8AnZ459rPTzPeBbL7IPFRVXmZ2ux94w5IsPR3hBXs6ybRvUbY3ba/NVOAK4tzuaqhVdvB1nKChCYeAnqIqYZD4t15eGPBXEqpM7lHeHIVJKdvshK45OlGV0bJN9L6TvS7pugqLkNZ4zCbdXHdq1w6nF1NVJYr7/+NY+e25M3VC41rK5veHw/o3m1LlwMXWb52WmnWfyOe6+ZzUTPQkT1kVQRVJXVFxSCrNEkknssQ1+4CdEaYquiLnnwtFa0ZAreR70g6lryseKax4OAg5GucN5bxTxXtfnfi8gzSRNW6PrxViqSt8LIZP4UUacSRQh8IIUBXg4CKaiqgF29j0+d3/A3riPbpxxv+exPwjYHwWTc5/U2/RZTD6PYya6aBPWRXE1EoJUVDyHFGaJKElxTA1bV4lTybWWRadmLFThHKkVbWjESYpU1KnEfOVjxTVJmiGlgq7mqid/3G6cZrRtg5qhsuaYtGsaPS/h0TAkyUKkzB3Ahiq41jJZremTqOq9YYAbpUSlPkoJiqpSM3UaVr4bepKT5VlMPo9rJrqowk4XSbVAVFRcUgrzg66pSBkjhMDQBDVDHecumq/CKSuACvWPrqlHdh3lY8U1mqqgjY/pqsDWVdwwRRvXjdBVlVZN53rHQhLQ82NkSRqkKAq2oU+l3DB1FcdQMWbMKaoA29C40bHPlPbjcVjW5FPu03mYiS7CdHaRVAtERcUlpWyWaNjaJGLZ1FTaC1Q4XTeeKIDiTE6cv0WCurKJpHzs8Jr8/KGfsFY3EICuKWhKbo0uai1vtWokWS5V9eN0okjaaFpsd+wjfdterfHhUZORH7PnxtR0hVe2Gry85rDVqj1xCei8wLpZk8+8Pp10zbNGtUBUVFxiCrPEtSUUPWUTxq2xA/toPel5NaaPXlO+FzC3HGeumsoXjYw839LKglrM2y2LjWsjvsXexzXWeKBeZ72V51d6WlHMx5l8FvXp9lrtSKK/Z5lqgaiouAQcZ145jVli9txl2pp3TZGkz41SVhyDW6vOkXsdvmErKMDAj4jilD01mCTqa1g6ZBnpG5/A+Oc/iBH7OLrNynf/BO+Z38Iu3mR3MstpJaBnMVEtGtvj/A1rDeuZXxgKqgWi4qly1VIPXAQnmVee9BgVSfoOxn1q2BqvbjWO9Klc1/nLD4fc7fo0LZWen04lA+z47+L88x+EeFzqM/bRPvEXUP/IL/Af7q6x1TZpGPqRPDynse2ft4nqqspSz5tqgah4alzF1APnzUnmlSc9RuUkfZNjfsJO16dlH75tl9+wi7rTmgq7wwhLUyfJAKMkxXHv4sT+9I1iHzN4BKzxoBdS31Apq+5PY9u/CBPVMj6K54Fqgah4KlTZM3OOM2UAT2yMil2KH6Xj8pzTxEk6ZfIpv0l7Yd7HOGWigILcgW1qGkN9jY5uH+4gAHQbz1iDJJfHWprKVts+007poqKUr6Is9bypAuUqngonTYzPC8eZMp7UGO10Pd7Z87jfD7nbDxiFMWImF7OuTcs8ywqrmpn/v1PT0Ev+BMfUGIQRnxq06X7b3wF9XOpTt+l929/hC+H6YXu2RsPSz2Tfv0hz0Fn79KxQ7SAqngqVjTfnLKaM8xyj2Z2cY2iMwoSmpdL3x5XVbC2Xrhoq7H0ZhrvQ2GJ75eWxosdEVQUP+yGqokyK/FiGhhKntNs23fT96N/7P0Hssqdf49fdVYrKL+9br7EV34W383ZZeRkWOK7nUZmDLo5qgah4KlT/qA9ZZMp4EmNU7EZ0RbKZ3EXzHrLtbOLWbyKlIINcumqo8IWfhX/653NTkW7D9/wkjVe/a/KWXS5p2rB0/CjFC2NuP/q3mD/3FyfXmd/9E9Refj99P6Vlq2zc/dfwD6bb5dXvOtUiUZmDLgYh5dUqr/D666/LT3/600+7GxXnxFVXMS3qf3F8Np7guGyi5euLybbIylrUhV4UZzDbTrmW9Ipj4IYxe8MQL0rzdBkNk61Wjd2+x529EV89/F+xf/5wEk8/+jHUD3334SS992X4yf/yiB9h9Kf+F+Tq+xY+W/LwS3T+X7/vyHX8+X8Pa68sbHfy+RnG/rTf0TJ/e8MgnhsLcpUQQnxGSvn6aa6pdhAVT5XLmHpg2YljkcJop+vRc2P23ZADNz4s2DNTrxmYe/1n73S5s+8BedW1hqmx0cyzsg785IiSabYfSZoxDGL2x8e6bogQsNMNuNfzWXV0PnS9xVbTYrNpcUs8OFwcAGIf9Z//IGx+CNbfPx6U3elJfHyeu3+XX75fZ7NhsjJTi7ph6QTho7nXMdrNF4AF7U4+P+XYL3veadRhO12PL+wOp8qWvrxRfy4Ud9UCUVFRYtmJY5EKS1Py66NxdlSAg1GYZ2TVtUm95gf9YCoVRnF9nAwniwPkJTk/d2+AqsBq3ZqcVyiZZvvhRgn3uj5JlqGPs66+s+8SJxlRKpHAnhvzzv6Inh9h6Aq30r35k/SDz8Hq+/JdRGMrf7OfedN3jTXuPwyQUuLM1KJuWDpK89rc66hv5T8vaHfy+RyWVcCd9B2ddH3RRrmmNcCBG1PvB1Oy32eVSsVUcaUZBjF7w+BcKnOdJp3zIiVRMZFMZVRNJUmaTR2PEplnWp3hwI2mfh9FMV4Uc+BNHw/jlGEQs9vzJ6m1IZejxqmc1J/245QkAz9JSbLDPnlRSpzmEtW4tnmoMCrQbXj0eTj4Sv77ysu5b6CkRBp95Ef57LCNIK9b3fPyhVGM+7fT9XhXbpL+V/8QvvmH4Xf/H2HlJZKP/gSj+s2F7fI9P5kfX8Cy6q6TvqNl2g3jdO73FCXyuVDcVTuIiivLeQeRnUZPv0hJ1LA1gmE8nVFVFQiRv4sVxw1NILKjbaw4Bu8e5PUR9r2QKE4ZBSlBlPFgGEwKAHX9mKAfEiUp93sBDVtjs2HlGVpVMakJbesqmgK2phKlknB8n5qhoqu5RPWBdp3mH/wfUH/+vz50FP/u/wY+9VPw4n+Zm3oUBV79LqI/9yrBwT266gqfD9aJ4phhGJMhaVgxgyBPKLjW0Bn5ES8++reoJQd18p1/m3fWfi/+XkDHyavH8ep3wZ//UG5Wqp+sYlpWAXfSd7RMu6aujjPiTp9vaOK5UNxVC0TFleQiAu1OI71dpDDKs5x69NzcVn3gxqzUTSD3QZhanqp7s3VoLipfv92p0fUSvrA7yAvwCPiqG00sPc/mWjcTVmo6YZTvSIosrAduTN1McAyNF9eciQ+iVTO5vcrEB+FFuQ/i9mqdraZF2zaIMxiuvUb7m/4KyDSPXPvUT4F/MG3qURSMzQ/w0HiBdx6O8JO873VTY61hoigCKSHOJGGSq6Im6iXIU2z83F9h9U/8G3aU7enva+2VE53SJ439vBxTx31Hy6jDGpbOdsdmFCZTPojN1vMRG1EtEBVPnadV43f2vqeVlS6SVi6qqVz0b14m1eK83b7Hat3g5dUaKzUdU1Xo1AwkMAoTTCXvtxumE3/GqmNSNzWaljapw1BWMZmaYOgnDIKYNJNTKqZiDDT9Nkn3g2if+AvTctOSqeftR0MO3IgVx+ADW3X2hiFhkrHdtuj7MZmUrDdMWraBAmjew7m+Dc17BPXtU39fZVq2TprJE1VFJ31Hy/zd5efqp1IxnUVhBUf/Pp421QJR8VR5WjV+F933tHr6RSqs447P/t73Y3puzIEb8taeS0Zenm1vFLHZMOkHKaoCXpTgRnnthTjNuNG2eXHNYcUxMcapKsoxFEUup0djc4qhaflztqzct/D2Lo3GFo2Vl/nse33e9L+O3/bdP48T7yPrmxgb7+Pa2NTzb954wOfuDVBEXl2uaet844urvLU/5Iv3hwRxBhKur9h81bUmt9ZqKOF8B3VSO4ygPouZZva7E4o49ns67Xd0mjaW6d8yCqsHw+CIyu0yqKSqBaLiqfE4ZqLHCSI76b5PUnpb9CVKUnYHAQM/QVPBDVPCJKXnx+iqwqNRSKumMQpSTE0lSFL23QjbUHFMba7JY95zjvyI9O4v5jLWwi/w3T/B3fR1dgcxu4Mm0IQDeE141C2DvWHA5+4NgNw1sN+P2BtFrNUN7ncD9kd5PwSCewc+L7Rz85mz9f48nqJ0r/A7f5wH2g3Izhb0d9lzeJ1FYeVGh+ar+hwl2NOkWiAqnhpPq8bvRSV3OwuHdacPlUdxCmmW0bIM6paKpkLD0tCECuTntywD21BwxuaieW+b855zM7l7OGHDJPX2h//wv+Rtpms+eGE+tmVlVTx2UQDsjwLiNJfqOqaKOi5XamrKZCzVD303bH144oCO6zdZi+WZzSiX6btb1I9Fx8v9K59XVklFiZzUDb8Mz1QtEBVPjadV4/e880CVo563WiebBebVOTY0ga6OFU4q+EIQJikdRaNmaISJxDZUcA/bcUyN1YbFimMsfB4BhEmRoVWiRA/m+gVq4R6KcFCUfBHQVXDMvOhPuX1TA0tT8JMUx9IZBOnkXkXhn9r4OgAUhWH9NqH5wmRRGIdznInjvrvLEJWfZBmjIMlVTmNBQtG/MuXfC5WUECCQh9dfApVUtUBUPDWeVj6m87xvOeoZ4NZqyGu3OgvPX1TnuOfCVtPCj/L4BktV6AcJd7oemYRVxyBFslo3jq3/PPucUZrx3oFPz48Y+AnXb67SmuMX0FvXMHoK7+57ucqqaWIb2mQB/vB1j8/fHxDGGftuiKGpPBpEqIpgxdHRFQUJvLBic3vNmfTpvKXIi767vh+f633OQvGsbpywO8jlvquOeaR+OEw/h2NoNG0NL0zYHYRIcilu369MTBXPOU8rydpp7zvv7XS3700tDgB39j2ut825O4mT6hxvtUxeWLF5e98jSTK6XgQo6KrgRttGAo6V/5O1xm/2JylkdFWhXdMYBBFrDYM3AoeN7/xxrFJsAt/zk5hb7+P9QY/1hoGuKqw1LHRVYRjkk9Tv+9Am19smn3m3x6pjYOkqYSoxVMFm08QxNeqWzvWSo/yi/AWz3x3AO3vT38OTtuGXn3WzYVE3E+IkZa2hL9xVlp9jvaHzzr5PnKTomopjaJfCD1EtEBWn4iK28U8rH9Oy9130Fjz0E4TI02HEqURXBVGacrfr45hH2y7bnQXQ9yP6fkSYJHxgq8naOAiuZensjwJ0VUUZF+AZRSmaorCuq7Qdg54bcbfr4hj6lOyy/P3c6/nc77mkUtC0czORF2d8uv47efWP/2uayT5G+zqsvEzgRqzWrUk6j3Kfi7bXGxa3VmrsjfKxcFSI0pRRmLDiGFOLw27f427XJ04kDUsnKz13z41O/Tc0T5JcXLs3DOZec5E2/Nn+zPoeHEMDQ1tYb7ugeI69YTC5pszT9kNUC0TF0jyPJUKLN8PClh8lkihJ8zw8toYbJuyPciduP4ioGxovrji8s+cdGZ/ibVcAbz4c8qWHI/pezGrd4L0Dn69/cQUvTHj3wMePE/aGEeuNPAYiSlIMTWUQRXhByr6X/79pa7y05vDSRh3I35wV4K29EfcHAUGUkWQZNVOlaensDSOSLOOR2uHD12/y/rXmVN9mKR8vRxULxqVGux6rjsEoTNl3Y17eqPNwEHJn35s8w4trNV5aqyOBfTdkFCWTHFTL/A3tdD12uodv19sde+64Htf382Tev4OWPX8SX7YPl7U+SrVAVCzFZZcXXhRhnOcWKjKzFli64OZqHUPL3xDDJE+HsVJTJsdmx6ewO7+z53LnwKPvxTimiq4ovHfg03GGWLo2yf5as1K6XoSlK6zULGxDwfVTvvJohKoINEVh4CfsDgIMVQFF4BgawyDm7T0PIcA0FEQEIz9h5CesNUwMVaVu547vwoS0jF+mHFV8MAp5NAypG+MEhKrKgRujPhrxbtfH1jVsXaNmpby957FeN9E1hTiTrMwkKDzub2gYxFOZVCFmFCZTifIu2pc1G8w2/9/B4/XhafnjTqJaICqW4rLLC0/irKYxU1cJS5lZJ+2FGQduxKtbTdbrBg+HATfaNjVDI0gk9QVSxe1Oja4bUjc10rqcOHcBBl6M6oiJDXutrjMKYvwko26qKKogThPSLEOiMF6HiFOJG6V5nidDw43y70pKqGkKHVsniFMsXeFay57YuGf7t4xfpogqfntvRE1XCJIMTTlU6/T9OE9MOL50tWZS03NVTs1U8CKBW9pBzBuj8ve1NwoYzSTXG/oJB250ZFw15exqskV/E0eC8oQk3wNOE8bpY/vTLmPRo2qBqFiKy7oFXobHMY01LB1Tn7YjN2wNx9AmqZBX63l5zfu9AAlTifrmjc96w6RhabhhSrlcV7Omj004hzZsL05JwpRhmCKlxI1jVEVBVaaTATqGCuNjjnF4T1VV0NVcgrri6LRr5lRfZvu3jF+mYem8uFbHi7LJMxe0bJ1+MD2h1wwNVVVww2zsv4gnyQXn9aH8fe2NAnp+RNs2pu4za9kvXxMMY5LMO/Y7XuZvYt6uOYyzI2nay8/wuP60p+WPW0SV7rtiKYotcJnLsAU+idOk8F7ErVWHa22LtbrOtbY1mdjajjEZE8fITUMrjo45nuQXjc9Wq8b7Nho07cNJ5oUVm/dtNNjuHKbddqMEW1PZGhcLUhSBrancXLFp1vJ2m7bGVtNie7U2uTafwGvULBVbz+/x4prD+zYbU/14nO+vMDc1Ss+w4ujcXq/z6lZz+nmbFopQJokFId8FuFFypA+z31fN0NFVhSg93MGuOLljftE1cPx3vOz583bNpqbSMKenzavw7+CsVDuIiqW5jFvgkzgP01gxGc6zDzcsfTImt9dqk7ZPGp/XbnW43jZ5NMxjCsoKoKI9P9Loj80riiLwwpj1eo2bK/l93Cg+omIqrr25VsMN4yMml/P8/maT2Ola7hd5ZbPO9bY5ubemKNzv5/r+IrFglEhutKwjb+2z31fN0NhqWRiqgqYoGJo4klbktN/xsufP2/1J4NZqfXL+Vfl3cFYudIEQQnw78LcAFfgpKeWPzDnn9wB/k9xquSel/OaL7FPFciyyzxaTYlGo57L8A1kUzfw4prHyGJQXxyLzatnBW5aZzmtjGMQkqZz0b7fvTRaHlq1NJq1ye8Mg5uEw5E7XIwhzH4MXSTZaFq9sNI70t7geDifBjmNMRRkXfT8vir6WkwLm99V5ZbyTGAYxbpRMafwNjaldQMG872WjYbHe0CdZcWf/3k77HS97/CTH8WX4u79oLmyBEEKowI8BfwDYAT4lhPiElPKN0jlt4MeBb5dSviuE2Lio/lQsz0n22csmdz0umvms6pBFz3hcxG75GgFEaYauKnxhd8D9XsBq3aBuaZAd0Pdj+kGCH6fULY0PbDbYaFhT7fX9mM/vDvj8vSECWK0bvLJZJ4qyyeK0qN8PhgFDP2F1bNKJM4mmiEmN7M2Zez0OJync+n6R0+nQ//DqVmNu/xd9X8c5nU/7HZ/m/Ku4az5PLnIH8Q3Am1LKtwCEED8DfBR4o3TO9wP/REr5LoCU8uEF9qdiCU76x37Z5K7LRDOfJWr6tLWMi58LwiTl3QMf2xDc740rxI0iVAGfvz+gbukYmkLfixl4MR1bxzHzf45FeztdH5lJNpomSSpRFEGcSoIkXaj86brxVHbQ3UEw2TEESYpdKjxU3Otxv7eTSoB23XjKtGRoYmHcAJxtUj7tNac5/7I5jp8kS+81hRC3hBC/f/yzLYSYv8c95AbwXun3nfGxMu8HOkKIXxJCfEYI8ScX3PsHhBCfFkJ8+tGjR8t2ueIMnPSPfdl6wE+KRfWFZ483LJ21xnJVwM5Sy7i4RpAHtfW9GD9KeNgPkMg8EZvI/QZxlp+TjWtESyCIk0lWz6K9OElRVQWBQB//Pw/Uk3PNJEUfytlBi/rU5brY5XPO43s7zmRTtJ+ru1TqVp7O+qT7nub7Ous1Z7nH88ZSC4QQ4n8H/M/AT44PbQP/7KTL5hyTM79rwG8H/iDwbcD/WQjx/iMXSflxKeXrUsrX19fXZz+uOEdOss9eNrlrWUWzzPFlOK6W8aLzi8yp+27Iewc+Oz2PN+4NOPBjHg1DgvGk78cZAy+i5ydEaTbO4AmWrk0krkV7uqaOg81KmT9VwVpzfg6mot9FO8X5xX+aevjPvXyvx+U4hdtl+3upOB3L/iv6S+Qmo/8IIKX88hL+gh3ghdLv28C9OefsSSldwBVC/DLwNcCXluxXxTmzjGPuMkV8brVq3FoNZ3wQtaUCpRZxnB38uFrGpqFw8DAmTtM8c+qKTZLkGVj3hiGbTRMFwVfdaNHzIoZBHhHsWBobTQvH0KbaK6KWAWp6QtPSeP9m41gHdTFRN+zclFRIZONMsqoYEx/E7L0el0Umm8v291JxOpZdIEIpZSREvikQQmgc3Q3M8ingFSHEi8Bd4PvIfQ5l/jnwo+P2DOAbgf9hyT5VXBAn2WcXff64ifzOen0hGT0pivY07S9TyzjJMuJEcmffZcUxsFQFS4M0k7RsFUvXURSBpkhatoYqJJutGp2aSc+NGEUJt8bxC2GS11cu2+ZPqoU873mK/l0b18Mu2i0kqEWfs5l7LTNWyxybN67L1o+uuHwsu0D8OyHEXwdsIcQfAP4i8LPHXSClTIQQPwT8ArnM9aellJ8TQvzg+POPSSk/L4T4l8BvABm5FPa3zvowFefHSY652c8fV9n0uNdvtWpstc63/UVjUChzvvJwxIGbF3pBSrwor77mxykHoxDH1vCChKatE8UZihA8Gias1A06NRNFKLRqBkkGg7F/o+cnU31b1IfjnqcsPR2U/CbF7qI3PjaYuddxbQNLHTuprZPqR1dcLoSUJ20EQAihAH8W+FZyk+kvSCn/7gX3bS6vv/66/PSnP/00bl2xgGEQH8nHD3B7rbbUZPC41z/p9odBzJd2h7x7kBfdkVLyXtcjTjNaNZ13H3mMogRdEWRAGKW8er2BF6W8+WDEB2+02GyYeXCcqRHNSd1wXN+WeZ5550RJOjdNxEnXueNnMUq+jbO2ddKzVVwcQojPSClfP801y6qY/rKU8u9KKf+IlPJ7pZR/VwjxV8/Qx4pnkMdVNp2nMqoI4CsHrJ238iqM87TfBblCKFcJ6QI69bw2wvW2TbumsVI3GAUJe6MYx9IRCOqmyppjEiZySnW0TN+WeZ5550RL3GvedXEy/byP09ZxxysuH8suEP/bOcf+1Dn2o+IK87hKlfNSuux0Pd7Z87jfD3lnz2On651r++Xrygn5JiohRSFKM/woQZA7ii1NI04zkkySZhlhFKOrkmGYEiR5dHRZdbRM35at3TBLcS83Suh5IW6ULHWdrk0/b7mt0/bhuOMVl49jfRBCiD9G7lh+UQjxidJHDWD/IjtWcXV4XKXKeShdTgrgO08lTcPS2WxZeV0EN0ZVBWt1g7f2XIYHCRKJBFq2Q8s2SGXGlx6MCOOM7Y7N0E+wjDxo7IVVe9LXZfu2zPPMO2ezZU2K+eTE3FqtnXhdkQRwtq2T+l0pmK4+JzmpfwW4D6wB/8/S8SG5Y7miAnj8lASPe/1JCdjOO2VCoTDquRFenLLby4vkeHGCKgSaKtho5DWmHVNBEXmwmyIgzcBSVbZaxsSpexGRw/NqN/fcmJsr9iSi2SjVnT6p7WWOzaqanvdUFVedYxcIKeUd4A7wXzyZ7lRcZZZNSXBSIsCzsIw543FTJgyDmJ4bkQErJblmf2/EcFwDwTF1Ct2HoaqMwoQgzmhZGomEJANTh7Vx8rn39t1Je2sN61RJEBc9zyLp6d4wmEQ0G1rufPa8kIarHWlnXtvl7LDlOIfi50XKquc5VcVVZymZqxDidwB/B/ggebyCCrhSyuaxF1ZUzHBRif4u2pyx0/UmslbI6zCs1AwGQcyDQcCd/VzFdHvVoWZqIMGLY/bclLceufS9GC+MadRM2raGH2Z8bneAH2ZT7WVSTt7uN+ekw16mn4vGt7xYFsn8AGpGiKqIY+91XEJEeH5L0j7rLBsH8aPkgW7/CHgd+JPA+y6qUxXPJhc9iVyUOWMYxDzoB1NlR/tezMNB/kZe0zXWGybvdT12BwG3Vx2aloYfp6QZXGvZvNf1CGKJkaQ0LIt9P8KKDwv6DPyYO/suln54bLb28jL9PG58i0V0p+tPFoeiwNFx38MyCRGveknaivksnbBGSvmmEEKVUqbA3xNC/MoF9qviGWTZSeRxIrKLifA4U81p25+VtUIubQ3iBF1VyKSkbmi8tOYgydho6DRrBvujkP1RRCozbq44RGlK284TxPlRRpgkk9rNUSJ5OAi43rYnxw7c3KS17BgsM77bnRoyk8gsVyKZ2mE96UWTeTlJoRCQZXnyv71hOFkgKsXSs8myC4QnhDCAXxNC/N/JHdfOxXWr4iqzaAJeZhI5DxPUcW2cpf1ZWSvk0taaoeFGKb2eT9eLeDgIud4yeTSI2WhZDPyIIMqwDYWDUUTNVFl1TFYcg4dpSCpLKnMpURVlKqEe5OkFlmXZSbrtGJNoannMeQVFkkIhwA0T9kcRAJtNg52uN/EzVIqlZ49l4yD+BLnf4YcAlzwJ3x++qE5VXF0WxSLAyXWtT6oVPC8Ibpbj2jhrfepC1rpS6nurpnN7tY4iBEmWca8X0K5p9PyEJMt42A8QQjCKEpB5sR9NVahZGm3b4MU1hxvtw/rTnbrO7TVnYl4CxjWuj1ZdO66fy9QNX/a8gjwhYo0sk5PF4VrbYrVuTY3fdqfG7bUa11omt9dqT7WIVMX5sNQOYqxmAvCB/9vFdafiKrOMj+E4P8FxJpLjKrnNnruojUUsYycvy1oL1VEYp0gB7+6NCOMUTVH4yiOXdHKNxaubDRxTpWao6KrKRsNka1x/elYV1fdjdrr+pDTndsc+9Rv4sn6Y0/prXrvVoWYITE3gmBqrdWvyWXn8KsXSs8WyKqbvBP5b4Nb4mjw9WaViqiixrI9h0SQyz8QhyBee3X40ZTNf5FQt2hDkVd0KRdBs2+XPk8ZR/X7BvOM9N+Ju10UVCsMgRNdhzdFJMsmNtoGpgp/AwI2o6yo3Wk0URUXXxGRxmDcODUunZevc7bokqUSb2d+X60oP/QQ/SfMFZ+wHWFSXexHl+y/jl7nRcej5KSM/5n7fp2nrOIZW+RmeYZb1QfxN4H8D/KZcJrtfxXPJ4zoqZ+3YRV3nbjdkb5QfW3F0Vh0Tyfw3/6KNsiRVV8HSBTdX63QcnZ4bs++GHLgxTVvji7sj4kyy2cjfiovdyay/IknzWtBfejQiiFKyLCVNUt7a8/n1nT5unPDSqoOpKbhRSiYlwzDh0TDihRWbrXFN6+PesL/8YDRRDH35oTeRk5ZrTX/x/oAoyetdW6bKay90EMA7x8hQj2NZv0zfj3k0CHh7nICvZuX3rnYMzy7LLhDvAb9VLQ4Vx3EejsrZeguPhvE450/e5oEbUzfzspWLFp6WnVcyW6vDIEyIY8mXHuQy082WxVpDp+uFXGtb6IqYZGWtmwmOoc2tP+1GCfe6fh5cFqRkSB72Q+I45TfvDhiECWkmefPRiOsdmxfaNTIpedAPiJOMrXZek/ksctJOTWMUZrjjEqbvHXikEl5YsfGDlP/87gENS0dX1anryjLURSwrPS6kvqnMU2/EqURXBfF40awWiWeTZReI/wb4pBDi3wFhcVBK+d9fSK8qriznEYtQmD72hgEAjqFNKqRBLgndbC1eeMI4xTE0XCAaHU5+USLpjncN7ZoJwCg4lHAO/JiRH5MBkgxR0nDESZpLW8cJ7sI4I4wzvDglkRnZ+N0pSiR7w5iWFZNkEhB5vYcgYeDHOIa2UNb7cDj5pzXFgRthaBpxknLghhMF0v4wwjYUFFVDhNC2FRRFTCK5h35ybI2MYqwWHZ/1D0WJREoQQkxUXVGSVrEOzzDLLhD/HTACLPJI6opnlMetCgfn56gs7xA2GxZ1MyFOUl5ct499My6um01HXUxqypxj+15I15OMglxYmmYZuqZOzE66pqKrAsvQ8OMYU1ewdAWJgoYgGy8GigKqCoaqgMwIk3zxEELQ8yIURXB77bDvZfOOF6TseyGr48WrYMUxGIUZaSZJ5GGxd11VcMPxBG0bjIKM1bqBY2pIuVxd7mXNgvOkvsW4VD6IZ5dlF4gVKeW3XmhPKp46F5UG46zMmqwcQ6PTOX5xKF+Xp7M+9F0UDu62YyAUQdeNMTUV21RgJHHjfHFYrRtEqUQouVnHMfIazi+uOfkCmuY+iLWGQZpq+Neb/NbdPqMoZbNu8tJGnTBOEQI2mxbX2jYrto6hqujK4SQ7a95pWDqbdZNhmEzkrrdWa7y43mCn69HzQpqWxo2ORRRnuQM/jPntN9vYhs69XsD+KMLWVW6vOUs7qpcxC85msIV8ATqL0qri6rDsAvGvhRDfKqX8xQvtTcUTYVFt4dOkwSi3AZx7feqCeRlJiwjpefedvk6nbqqEcYY5rl1gGQphnNKyc8VQ/rOGIeC9ro+l61hGbqbRhMBQGEdHmzhmLnNtOzpBnOKFMXvDkFXH4He83CaKoaaDaUCWqWRSQdcVVm0dyzDQNYGlqfTciDBO8aM0lwOO+5wBL63VJ2/qZTXSdqeGpoCmqLy62cCPEwZBgh85vLRRxzE01uoGbpjw8obDq9fac7+rZbK+Hi+N1ecmLFzEef0dVDwdli05OiSPnA7JX8memsy1Kjn6eCzaJewNA+73j9rAr7VM1hrW1LFyGw+GAboiJsqiZWsVP07fBbDvhnOVR/MoJqkDNyIspcworvmVNx/xbz7/kLu9AAV4ad2h7WiYqoKpaxiqSpxlbDZy08+BG/Pegcu9no9tajwahLywavPymsNXHrnc7/s0LJ04yWg7Bl93q831Zt63fTfE1NXcRxIlhHE6GbuC40pylsc+SlK6fjwZg3nXP81d4WXbkT7vnKXk6LKBco2zdaniMnHcLmFZW3S5DTdKJo7jQlm00/WP1C8+j4R85fuGSToxc5SVR4vuURwLZ/Ipdd2YOBnm8lABtq7gxxlf3B3ytTdbqELQUFWiNGW3H5KkGaoi8KKEN+4PadkaAy9is2nyziOPjYZB14swNZVMgqoo9LyInhuzWsv9IXEmWRnXcXYMjVGYECbpZLxOUn3Nvu3PCyA8667wPKmyuz4bnFRR7lUp5ReEEK/N+1xK+dmL6VbFRXCcYmWtYS1liy63UXYC5wFp+TGp5PUGZq97nIkhV9HkSpo4PTTNxElKcbPj7rHo2Q/ciCTNaFkGlqYSxClBnFAzFExNy++R5gtLECcYmsYoyKvGBUmKpak0LI1Xtuo0LZ0PXmvxcBiMFxMFU1OxdJWmpWHo6tTCCbnzvWlrOIa6tBmmLALIg+tOH5l+0ZN0ld312eCkHcT/AfgBpqvJFUjgW869RxUXxkm7hGVs0eU2yvEJhd1c16YdsSfde1kO3GgSryClZBDEtG1jqi7ySXWcj0RXayorjjFJkGdq6uGEbluEcYo3ri8tBFi6hqYIVEUw9BOyTCWMJWt1iampvLzu8Ll7IwQC29BQRO7LWHEMtsZ5lwalzKgFy9jyj+M0kenHHT9PquyuzwYnVZT7gfGPH5FSBuXPhBDWnEsqLjHLKFZOkqiW2yjiE3TlMAXGvPrFj5vVcxjEhImcxEIoSl6+U9cFznj3sEwd5yjNJosM5Aqhr1pv0fUSPht38YL8rffVrQYNQ+NenLI/ihBAzVTZbttEScaDYcgHrjV40AtYqRsM/YSven+T1YaNbfhjE1hKq6bz/o06t9ecSd+eZMbTp5lhtcru+mywrJP6s1LK10469iSonNSPz3koS56UigmYcqC7UR4LYWgq11sW9pKmmWEQ886eN7le13JHceHQ3e17PByG2JpKw9Z4NIzxogQvipEIWpbOjY7F0E94MAzRhIIbR3hhSsPWeXmtTs/Pdxs9P6LnRqiqwtfdbB2Rmz5pZc/TVBJVKqbLw7k7qYUQW8ANwBZCfB2HMTpNoJIjcDX/AZwlkG1enWM3jOn2ookcs0jHnWQZmqLMXTDmfXbcfWC+WaKIZzhuQSofO3Ajel6Irql0aiZRktLzIt7Zy7i9VmerVcMx9Sn5ac3QqI13KIVDvmFrhIlEAo6lIRq52arrR8RJbmpq2bnZKk7SI47x047/ZQpcvGr3rnh8TvJBfBvwp4Btcj9EsUAMgb9+cd26GjwvMr55z/loEE6SwwmgYQ3ZbFrsjmsdF0n12k6RAfUwQV7D1tgcO8XL43Vc0fuOo/OF3WGpVCaTxHfzrgOmpLhkklGUAjFxktDzE3pezI2OzYNhxErNwFAVJByRnxb1m3VFECSSOM3ySGkO5bZ1U+N+L2BlnNV1cIp6z6cZ96vw93UVX5oq5nOSD+J/BP5HIcQfllL+4yfUpyvB8yLjm/ecbz4YcuDGCDHOx5OmfO6eB2QMx6kqiqR6D/opcSbRFTGRpg79hLqZT6DFeJ00ni1bp2PrOLo2cTDPS6oH5AnyMjmJNRiOTT9NW+WdA4+7+z5elNCwdbw45WAU8nAQ8IHNBsbY9FTIT+NMTha8ws+iqwprDZ04kYyiZCJbbdgad3s+lqYihFiq3vNpxv0q/H1d1UWtYj7LRlJvCyGa5DuHvwu8Bvy15zmy+nmR8c17TjdMiFM5US4VMtC+nyDEYaajoo5zkuXS1zKFPLUYr+NkqAduxNDPncVNSyNIUoZBgqEJhv5RxVSUSJIsb7+Q4kryJHOOpuGYGrqm4BgaXpCiAJoiJlJdOJSfRnE65YQv0BSFkJQkSRmkeUqONM1oWSo1XadZ00+s93zcm/ZV/Pu6qotaxWKWXSD+jJTybwkhvg3YAP408PeA53aBeF5kfPOexzE1wuRwItDVfJJu2RqD4LCKcrGAiOyo9LWQpxbtz7vPg2HAvX6GF2b4cb7jaFoaSXqYnuKl9RqqUKYmb0MTiEwt3afoq0TXFCxDgfiwDYFEU48moyvKfQZ7HrOehK4fM/Ri3uv6fOnBiAMvpGHoNGyND2412GhaU/WkZ5/vpDftq/j3dRUXtYrjWbYmdfEv5w8Cf09K+eulY88lhV28zLMo45v3nO/bbPDimjP53VBVPny9yWazNskgWphXNlsW2x17HHMwDu6y8+R35fGavY8b5bWd/SifZm09N/u8e+ARpemkHUUomMb0n3FxTzhMFb7i6NQMHUUR3FypsdU8VGmvNyxe3WpO8jXB4Xc57/lNTRCO+zX0E3b7AWEsCdM84+q+F03VuZ79u1imNvZV/Pu6iotaxfEsu4P4jBDiF4CXgL8mhGjA1AvSc8l51D64Csx7zu1OjWttc6rE5TCI2WqZc5VKLXvxZ/Pu40caSZLih4d/Zo6hkcoMx1BZbViHMRC2jtlUj3wPRVtFeu0wTlmpG0RRlquY/AhVFbx/szHp/7zvcvb5wzjlfj8kTCSaKug4OmkmaVoaDVOnpuvULJVrLfOxzEdX7e+rin149lh2gfizwP8JeENK6QkhbgL/+5MuEkJ8O/C3ABX4KSnljyw47+uBXwX+qJTyf16yT5eC85DxnSTRPK7981KMzLYzG+fQcyO8OMUa/96wdLZatamCNOWxKK4vHz9NGolhEHO3H3BoHspNWbaiTy0OAEmWQcyRMZjkYBo/x1rDYq1hMQxi3t0fYWc6dUPjbjdgbxRxa9WZSkw4DOKpzKVrDWsSL+EFKZamYOkqAoE2zj8lx/3caBwmOZxtJ8ky3CBh7BmZmLbcKCXpe4SJROFQxnsesSVPSll01Ra1iuNZdoH4MfIdw7cA/zW5s/q/B75+0QVCCHV83R8AdoBPCSE+IaV8Y855fwP4hVP3/hngJIlmcWyeEuS8FCOz7RQyzkLi6YcJo3Ft5ZqlcnvV4dWtxsJ7nUe/8l2KzSg8TAi41bRoWPokNUbR171hPPERlO91XD8yqVA3lIn0FmAUpmx37Ek96nJd66atgYRhkODFCfujkBc6NW52bLpexME4Sd9q3eDFUi2GcjtC5GlCGrZO14243wtYbxhI8gJDB37MO/sutqbimBqdms7LG/W59bFPM6ZPWln0NGIfKmntxbDsAvGNUsrXhBD/GUBK2RVCnFRZ7huAN6WUbwEIIX4G+Cjwxsx5fxn4xxyz2DyrzLNFL5sN9bwUI7PtuFHC/V7AzRWbOJMcjELu94OJI9oLUh4OAuqmRss+OhGcp5KlqD9w4EZTb9TloLvy4lC+V/Fz+bl6XjiuqZAvMOWssJArqwrp7IN+MPXZ/ijkzr5Hq6YTRBkg+PLDEddfWeUP//Yb9LyIJJWsNQ7rQBd1nIt2skyy0/XpOAmqIlhvGERJQpwBusbOvosXpHik2LqaS4X7AZrCmcf0eVAWVdLai2PZBSIev+lLACHEOif7IG4A75V+3wG+sXyCEOIG8D3kO5PjdiM/QJ40kJs3by7Z5cvPPFv0stlQH0cxUn7bmm2nkIUWUtFRmDAK8sprxaKVpFkeJTznXuetZJn3Nloc2xsGR9RF8/pQBLoBaIrPWtOYPGOZQlk19JPJZ0LkE/sojMkyiRskqMphcr9hmOGY+tzqbUUd56KdaByBHcUJlq4SZdD3M5I0o09CKjPsUgZZQ8ult8M5Cf6K9k8a02IsZlOMPCvKoudhAXyaLLtA/G3gnwIbQoj/Dvhecp/EccxTOc3+e/6bwA9LKdMi6GoeUsqPAx+HPBfTkn2+9MxTdyybDfWsipHZty1rRgFUyEINTXAwTBgGCVGSkWXgJyktK08jsagW8ZNUsixzr3LNCsglsGGUYWqCqCRrLZRVxc+DIEGIPOZjfxSRZBn3+j63VmsoArLxX6FjqJPJdtbMUdRxLtrZG4U8HIT4tsZaXSGIUvKu5v0Ig4xYyZ34xY7N0AQNWyMYTk+Cxz3/7DnlBRLySPZyXeyrTCWtvViWLRj0D4UQnwF+H/lf8x+SUn7+hMt2gBdKv28D92bOeR34mfHisAZ8hxAikVL+s2X6ddWZp/pYNhvqWRQj8962ismyyBnkGBq3VmvEaUYcS9q2TtPSGPgxj4YRmgMbTWthLeInqWQ56V4dR6fnHVbJK0dDrzgG19o2li7yXUApK+xWq0aSQd+PeHecTqRV0/mg0eRu1+daWyVL4cVxoj9TV9npeux0/clbeuHL2GxZk3YUIdhsmtQsDT/MzUydWu6D8MdlUIdBzIpjoCiCTi2vA53356gZZdkxPRKDMucF5KpSSWsvlmV3EEgpvwB84RRtfwp4RQjxInAX+D7g+2fafLH4WQjx94Gfe14WB8gnbEtTWG/oc2Why9UIXt45F8bpVE0Ec/wGbWrakT68t+8SJRkrjo6lKvhJihsmbLYs3r/VPDYqOK+f7E0ksI6pT+pILzOpnUbBlWa5Kaamq+iaQFMUhkE8keLGSUo8rv+gKyqjIK+YmzR01iyLD9/oTKmMNCXPHtuydV7eaOBHKWGaUTNy00zT0rB1Na9RbWhIIXHDmC/uDku1HmJGYULLzvuQZhI/ShlFCbXxM0WpBOS43yqaIogTyWbLQFGUIz6XRX8nJ1HklKqb2lQdjGflDbuS1l4sSy8Qp0VKmQghfohcnaQCPy2l/JwQ4gfHn3/sou59FZjnWCtLLE8rC10GU1cnqp0iLbWuKrxvo06QyKk++HHK3iiamEfiNKNtG8TZYZK8ec8igCjN0FUFAdzbHS1dO3rRuCxScBXJ+wSgKlAzNTZK9wFww4x+ELPT9XPTUAbbKzZ1SyPJPLY7Nfp+TM9PJqaYFUdnzTEZhglRCgdezN2DAEXJTUu3VzUeuSHDOGW7VeM3dgY8GoY4poaU4McJwyDibtvk1WttojTj0Sg6TOBnRdxedbi16owd3jmbraPPetLfyUmYer5jMrRDv5bk2XrDrqS1F8eFLRAAUspPAp+cOTZ3YZBS/qmL7Mtl4mk61uKx8TxKUwZ+Qs3K317LfQAmBXoGXsz+KAJgvWkeqf88+yxhkvLugc+1tjWVoG+Z2tHLjstwPOEXdvUoTdk9CNnu2Dhm7kso1GA5gnZN527XG0dQizxFt8sk2V/ZV3Hgxpiqwu4wRBMSL8gVUweDiFevNQiTjCiVSJkRJnkup/1RlCuP/GhSeOjRMEZVhwy9GL0kzS3aK6K5F01s5/F38ry8YVdpxS+GC10gKuZznGOt+P9FvAmFccpmw6JuJuwPA9YaBrauTSWpK/dts2GhCBiFMZqq0DS1qbbmJdkrVDuFGqtgmdrRyzocwzidqoddJAuMUzm5z+z9FSEmqTaKfhoak0Wh3B7kQWtSgqoJtjs2wzDG0vMa02GSkWYZ6Hk7dVunaWu4UYwbJCSpZLNpUjdU9gYRfpLgmLlpKk4luiqojxVkaw1r4fd8Xg7Y6g274qxUC8RTYFF95K4fE/QPnarnrecuzAqOoUHDIkrzKrLlJHVJlhEnEjfK3/hblk7fymWhaSbpeSFpJmnbGsMgPmKqmFeb2o8TBj74cUbT1jH1+c90ksOxHP9QTsJXKH50VUykqrNqsOKcIsiu6GehEJpO6perkwZBQs3QiNIEW1d5NAgJ7SSPnJ7UsRZIYK1ukKaSnpdgG4JMSoZhQt3UCBKJlHk22eK+2gIV2GnGYxHzfDiX9Q37ogPcqgC6x6NaIJ4CuZNyuj7yZtOgxXTs4Xmbncrmhnn1pIuoZMjfUkdhwlbDYsXReTgM6XkJe15ellMRghU/oe1MmzBMTeXWam3igwBJ143YH0VICS+s2GdSQM36OQxVmdSoNlSVF9dq1MxDqWqhBuu5MSuOTs+Da22LLIOWrWJpKq2JYilXKhXtrYzvaegqhqrQ9YZ86cEQgC/eH/HCSo2VusGqozMKE/bdmExm7A0DGmZesjRNBXujiIapcaNdQxGHAXMNW1s4BsuOxyKuUtDYRff1Ko3FZaVaIJ4CwyC3SV9rWxNZZJykBONay2XOW21SNjeUk9jNRiWvOiZhktKwNdYaOg1ToxfEZFKiKIJ9N8YxNbou3F7LI55nczkduBHXx3b2KMlNK0IIdrr+3Cjs2f6V2yr/Qy9SU3zV9cZU3qLiWeYlCbzb83kwCImTlCQDXRO0bH2iWGrZOtfmJBPc7Xvc62u8tFZHcBjIs92y2WyZ7HR9DD2PGYlSuNf3aNdytZGUsNbQ+brbK1xr21P5mJb9Tk9jHrpKQWMX3derNBaXmWqBmMOi5HmzKR9OumYRhW3ZMbSJXd7l0C5eRL2WTTknTQynmXzmJbErRyWXzV95MR1lbLJJUIQgSfPP9oYBGw2LnhthG7nJxA1jdnt+brqJUx4MA4I4xTZyhY+UzI3Cnk0OODteUckcl2SSaLx43Vp1pq6dTbZ3r+fTHYV84cGAJMmVTo4Jn7s34F7PR1Vys9RKTcfWVTLAz2K6boRrx2hjyWmcZgghsHUFXVUBwShM8OM88Z6mKmRSkmaSLJXoOjimjqEdfn+niXA/S4K+ZXwWl8HkMgzyv5HCjFnmvF6IqgC686FaIGaYty31woQ37g+IkgxDVek4h0nUFl1z3FZ2bhEeQ8MyFO7s5/ED+3NMOYvknuWkcg1bOzaR3qL+tuz8H42AqQR2QoGVmo6hSF7VHxIr9+npK/z8Q5u9kcabj1xe3qyz3arx+d18jBqWxm4/wIsTFAQPByHXV2yut2yk5EgU9v2eizV4B9N7yFBf4125Sd3K60EX41+Y44pxydVKIfujaEohVIz9Ttfj028f8JVHI/bdkN94r89aw2SjYfG+tRoHXsxGy2KlZjIIXEZRyppjcLfnE6eS7Y5NzdCo6Qpv7Y147yD317RqOlsNk5atkkiV3b5Pz0to2to44DDDjVJScj/DKEyWmpQeJ2ljwUk+i8tgcin6ECUp93vBpD75bF8flyqA7nyoFogSs9tSAXxpd8C7+x6DsXSxOS6I86AfTCbV025lF9mWW7bOwItRxlk/Z0058+Ses0nlhn5yrAln8dY771O5vSL9RJZlvLT3v2D87F+A2Oe6brP1rX+Hf+Z/HXcHIZ1RhC7gfi+fRHVV5BHIIo85aNZ07h34dGyd9Zko7FEQsnLnFzB/7i9C7NPQbZof+VHeMr4FoaiT+tINW+PhIJgks7veMomSjDsHPjc6Fm07j0guku29s+dy58BjFI4L+iSSAzfCMlTe6/okwCaSKM19Lfe6AVmasTfMJb2mprDRgK889NloWlhGRBBlDLyYay0LP81Yb9hstCx63oiBn9CpaazVDQSSjbpBq5bXy0iy49OWPU7SxmX+ruaZ6ZZp77wp96EoIJXXLk+OFJB6XJ4Xee9FUy0QJWa3pWGS8mgY45eOD/yEmqESJXLhNrZo67g/xnm25b1hgDE25QghkGObT2F6mif3nE04B/NNOIuesXy8iPr1omSS1A1gM7k7WRzyG/is/OJf5nd/zyf5ZNTIk82V8h2NwrEvQ+YRki+t1fDjjM2GwYtrNSztMNpZ6749WRyKtuv/4ofY+v5/zQPlhUnSwM2GBVmuBjJUQZRk3Ou77I8iwiTh1qrDqpPvOoZ+ghfGJKkkTjL8OGOtYTDyY5JEIpHUDA1L13Jp7LiEaZQeTuRJKgniPEBQFYIPX2sxivIAw7V6XkdCAtutWh506Cas1DQ0VcGNU1o1E8jTexTZYxfxOEkbZ1nks7gMJpdyHyRMIryblsZW+2Sn/Wmp5L2PT7VAlJjdfhaO1Vy/Pq27NzRx7HZ1ma3srF26uGZWcllII+cl7Juto1xcf9otdnF8xTFKKSNyNO/h4QReEPvY0R6CBpqq0LI1drr5R3VTnzh0a6ZGmEh6bkzdVPm19wasODqrjknb0dla1HbcY1sVqPEDQnuDfWWbuq0zDFPiNMWNsinpav4mqmFouYqoZupoqkDXFASCJMu41rG41rJYb5hstSxUkX+vupqbjuqWxv4oHrcpsHQNVcmlvEIIGmbuCO/YJiiFRguut2q07ITVmk6zZqApYkq+fBY567JJG+cxz99xGUwus/cqIrwvYnEouKzy3qtCtUCUmN2WGpqgVdNZrRt8+dFoEiG72TDZbB0GOJ3XVra4P0xLLk1Npb0gYd9my2IUJktLKE/aes/7XDqboNvTE7lu01dWWWkY3GjbrDomB16e+dXSVW6u1gjilJqu8V7XZ7VhIMiLEBWTedeFjfqctldeoubfQ/1H35sf122a3/njvL3+LYxsjSRRCJIMQ6hca1uTN/QokWy2DpPt7Q1DkjTj5mqNh32f9Xq+MHzNdpubq05uvkok63WDvp8gEbhhSpxK1hsmtqHx2s0OQuQ7xyhNaVo6q00TW1cnEdhxktK0dTpObuYKS4GH8763Zb6TZZM2LstlMLlchj5UnA4h5VETxWXm9ddfl5/+9Kcv9B5lpUffj+m5MWGS0g9iOrbG+zaPT1b3uH/w5YCwZZKznVbFtEx/y5/HcYL9lX+B/fN/cTJhD779R/lV85v44LUWbceYnOuG8SRJH8Ddrs8wyDOX7o0OJ4atpkXd0rjRMlh57xfhn/75SdvZH/3/oPxP339kQQr+zC8Rd17GDWO+/GA0MYMVk/Qrm/WpugyFiskNYlKZYenaePdQO/KMwGQMsywjSeVUre0v7g4YBjE1Q6c2tpf7ccr+IMKLYwZBSt3S2GpYmIaS18k+5d/C46qYznqPJ81l6MPziBDiM1LK109zTbWDmEN5W9qw9KXsmOe5lT1tW6c9f3ZinJdptdzmEPjyyu+h/Ud+ATN4hGes8YVwnZWaOVU3eRjEeeZUXcUx82OOqfPOnsf+KKDvhURpRiYlLVshSmJ0VZLc+P00/8wvIUYPkPVNNO8ByhyzkxU+Iubl/G0/ywsXKeTpq+uOgWMercnwga2jUtpZ2bAb5nLW2ViKYmySLMPSNMz6WJIcJTzo+1iGiq2r9Af5znLoJ9TNBImG2Txa23uRrPe4727Wh3AWqexse097Ur4MfahYjmqBWIJn6Q+6LHV8MAzQFTFx7i6SPTYsnfWmiYzAESGO6CMtBVd/YTIux8lt4zTjrT2Xtx+5vPPIZbNt8sXdIe9bb7DT9fFTyWqtjhANOpnO19gZ7TkmLddY51+/8YD3DnyEgLqpjKWrNqYUfPZOd2Hm2EUZZ4sMrqtj0140vr48Nl0vJJO5U3V3fL4XJWiKgmNOO6CLXFBhnNL347my0tNIWk8jTb0MMtaKZ4tqgXiOKMsMy9lLC+fuQtljlrG5869Q/vkPTsxA9W/+YcLO+xkFvx+JslBuqyl5kFnLNlCFx4sbDvtuRJJJ3tl3eUV16AcpAy/m9qrDgRvzlrHB+z/yo9T/xQ9N7uf/wR/nN7wO7x0MgDzgbhCkdD2XTs2cqi89mzkWpiffIuNsp6ZNxmBvXDVOV1U0EUyNja6p3O8FqIqYHNdVMXFGB0mKref/lIpcUEmWzZWVFtljyxRS3nLQ2KJzF31Hl0HGWvHsUS0QV5zT2HMP3IieF05SexTMZnM90s7BVw4XB8j//+/+BuY3/RXkyss8MF5gfxTgx8lkogQY+DF3uzD0Y4IoJc4kYZqRZnmd5zBJ8RMwVfjdawM2uENU2+BudI3/Vfsmvu6P/Stq0T6BucZveCsMB9FUuc8klaRS4oUxqjh8k5/NHDtLIQ12w3yy9+OEMM6d1J2aOjlenFu38rxVXjjtQ4G8VkTT0ojTw7iRzjHS1nn1pQsp76ym9TS1qC+DjLXi2aNaIK4wpzU/7A3DsaM4xtAPJZRlqexc2eNwd64UFZmSDnbZMzcYhXmQWc1KWa2Z7HshcarRNDUejkIycn+BJkAVwDhJYF2H7zJ/nY1P/tXJbmHjO36Mf6/+F7zNdUZyg2E3wY/zPFDx2DSUyVyKKjKomfrUM+il4LJ5z1Oc65ga9/dcvCBFU3P5cga8b80h8pKpc/M06Qq7/WgiXy3aWGuYmONqduX8UfOYV1/a0AQiO9rP09Sivgwy1opnj+MjeCqeKMMgZm8YLJxcZs+dZ1KYd21xbhG9ChDHEl09rNMMx0gOG1u5FLWMboNQiex1TE1lrW6wWjfwgpS+F6IJwVYzlwLfaNukUnJz1UZXFFbrBuuOwfs363xDu8/Gv/mrU7uT2if/El/X2M/7Pn6LvtG2udayURVB8XLetnW+ZrtN2zYmz1a8xZefpywfhsOMs5ahoeX10OnUDNYbJpoQWONMt7Nj8+J6gxdWbYxx9lsJbLYsbq06bLVqU7UdZu9ZtLHVqh05vtmyJrLWk85d9B0tul+1e6h4HKodxGNwWrneced/+eGQvcHh2+mi3EsFpzEpFOeWo1ejRLLdsWg7xiQJYZE65EhfV16GP/Qx+GeHPgi++YdJ1j7AA+0GMoMVx6Rpaux5IVGc0rQNVmomaemeUmb8thstFFWwXjfxw4T17jtzdyft9IAbnZeQGaQyI4xTUglfvd1CV0EVCpstixfXG5O+3iplp50d43lRte/tu5AVI3NYq6FhaXz4enNuW7P1tsuy2lkWRfIuOn6ac09zv4qKs1ItEGfktIqR487/0u6Az90bTj4r3vKPczCexqRQPlauT9x2DPp+PImc7vnJQkVNr/nNdP6rX2AlugeGQ2BuoG+8SLyX518SwHs9n7f3PJqWypuPfF5cq/HSWp0M6PoxHVvHsQ6jxdcaFkGyNTcIj8YWbcfgiw9H7Bx4kz6mMuNrt1usNwxGYcZON68rPSvRncesGq3tGPTm2PnLkb2zbZW/x2AYT+paL2KRAm7e8dOce9r7VVSchcrEdAZOY9456fxhEPNgEEx9djAOzDsu19NpTAqLzi36UeZBP2CnO/1G/+aDIV966PKfhmv8y/Cr+ZfDl/mlvQajMJ20Mwxi3t7zqFkqrZpJzVJ5e88jjGO24vf47dlv8ZKyi67Iqfsm7RfxvuPHDk1Yuk383T+Bsf5K/nsmJ4tDmORJk/bdKP+Z48f9JE5rljnt915RcdWpdhBn4LSKkZNqUM/mXoJc2XKSg/FxzQ97w+DIefMUNW6YTPJPlRn6Ca9sNWnZMV/aHUxqXAOs1kzWaikfGvwy1s8dRmDXxikz4kwQxinX2g6jD34no40PoboPUVtb+eKgKIRxRN3U2e7YxKkkShP6XkKYyJOVV0tymjGslEIVzxvVAnEGljHvlG34s+cXBXncKMXUxKT8Z1nWuNZcLmXGac0PcDjRLVL4lBU1bpT3KZMZoCBELlGNU4mmFjZ7nRsdm3fHNROKc77WOcD6x9OZWs2f+4ts/ol/w46yPbl/3TLhxgeBD071Jf88z8iKEBjjug+6Kk5WXp2CZcewuE+R2qNI9TF7/yqVRMWzQrVAnIGTko7N8zcU5xcFeeJMYmgqgjyQLJdR5hPPZtPilY3Guff7uH4VbLZyfX/XjSdRxmuOjgQejkJMVWV/FHGtbU35ALZaNW6thrx74OGGCfujiN+p7811QGveIzqbL544efb9mPd6Pl/ZG+GFaa5+ahhca1oTdZFpKEunoViG4yoHNiydOM0mdS8g5tbqtP+jimaueJaoFogzssg0schOXdRt7rkRoyhhZWwfKeorrzV0rinmhb11ntSv2efQFI9RkORJ5zSVFcekbes8HIV89XaT1frhQlI401+71aFT03jj3oAbbQujdn2uA9rsXDtx0hwG8TgSW+H2moMXJkjg9lqd9204aIrCgZsX8bkfhcDjT8Y7XY8v7A4nO7mVmcqBwyDGUBVurtiTdN6GeljboopmrnjWqJzUp2A2TqFh6VPadziMVi5MMwWFndo21CN1eCV53efZts6Tk/wgkCet2xsG7PZzGaelCUZhzFuPhuy7AXGagczrL4gFbSiKQtPWsQyNL4SrjD7yo1MOaL7nJw8d0Cf0t4j2tnWNmqlhagpRepjhNpwpljTrMJ4XV7Io1qRYkMpmvgM3r9hXnBvG6UQFVre0STxE8fzLjPFJ/aiouExUO4glWcZ0MButXK63W9ipn1bE66L2u35M2A/Zd0O6bkw8TjHumApfejDkzr5Pw9DIZEaYZqw4JjvdgBdWbF7ZaCBLbRfPvz+Kudvr0/UiPm39Nn7XR36W61ofo32NoHmbaydUWCv6Wzjv971wUoujbsa5ZHbBdcVCfNoaz+UFqUxRObBh6Sd+d8t+t5UZquKqUO0glmAZeeO8aOWhn+BGydyCPGWeRMTrvPuamiCMskmiuyjNC8n7ccK9ns97XZ/9UYCqwpcfujwchuhj5/B7Bz49P5qqeVwU4NFV2O0FeFHKe92AX9pr8o8e3eJz4QZ7o2Spt+aGlauXdJXJ4rBaN1irG4RRtrDOs6mrc7+vefLd8ndo6uqk3GqcppMdUrly4Enf3TLfbSWVrbhKVDuIJVhG3rgoWvlGyzrydvi0Il5n7xvGKff7IVEisTXB19QO0JQHxLUNfnG3RhhnGJpKGGcoqsBQVZCSrbZJnEpatjZ5tnf3R7x7kE/AfpTQqumoQpAhJ7mTvDCmZRtLy0K3OzVkJmlaOkIIHEOdmHU0RVkoFFhWvguH32HfjxFC4Ccp+6OUpq3x0pozVTlw3hjOPsdJn1dS2YqrRLVALMEypoPjopXncZ4Rr2eVVRZ9dgzBbxv8CvWfPUyv/X3f+nf4seGr7PQzaqZKluaJ8mxDQ1dVdBXWG+bk/sPw8I3e0lW6XkTL1lAQpBJ0FRxTn7rvMrQdg07JL1B4HUw9j8SeNxmX2y8kxXGaoigCBQiS9LBmdGnHUSzs/SBGIHn/Vn1uKo2Tvrt5n5erBBb1ustUSfUqLiPVArEEJ8lalz3nInjcgjIdR8cZ7hzWXgCIfTq/+Jf5Ix/9eX7q8xpRLHllw0Ei2WjkDudbq7XJ5BnG6SSWYxQkREnKqmMwCGLcKCNKfV5eq5Nm8tRjctK4LkpZ0XF0em7Mvhty4Ob+IDLJW3sjUpnXk2jYGn0/xtJyS2uxsK/X88l6Ucru0zI77nGaYajKZJGokupVXFaqBWJJljELPWnT0WlklcfJXO2D/bnxCtfVAR/9mg/TH+dRutaxp2o1FxRvv5sNC0uLeOtRxPaKjRcZZFke2LbZsjF0dSoh4LKcZVyLpHpdL+Ra25rUrn44CLjWMrENfVJUaL1xunxXp2HeuOtjWfNsvfEqwK7isnGhC4QQ4tuBvwWowE9JKX9k5vM/Dvzw+NcR8BeklL9+kX06C+V/uGtjVdIiljEdnWUimHfNPHu2AHpudOTcnhvhBglF5lJ9nDU2jFMarWtz4xVCe52OZmIbGqY+X4Zb9MsyFKIoQ0owNQ1LFxiqNnlLtvX8bXy350N7flDbceNSjGshD11m7DRFoV0zJ7/H48pvlqZPSY2P82c8Lj03YhQkkyy9xXgUsubiebp+TBhlU7uKStlU8bS5sAVCCKECPwb8AWAH+JQQ4hNSyjdKp70NfLOUsiuE+AjwceAbL6pPZ+G8JYnHtbdoglx0zbwUHvtuyChKpmoiANzrB3xlb8T+KKJpa7Rtg46j5ymynZfhe34S/umfn/ggwu/8cd7jGiMvQNc0DCl4Z887ts7zIIjGabkzklRlEES07dwH0/dj4jRGVwTBTDvLjvNpv4vZ8Slks7M5pY7zZzwOO12Pu/2A3XEyxhVHn9T/NnV18jxulHC/F0x9XgXYVVwGLnIH8Q3Am1LKtwCEED8DfBSYLBBSyl8pnf+rwPYF9ufUnHdk7HHtLSpwf1Ifym++YZKX9VwpvR3vdH10Ja+f7I91/gM/oWaoxNn4PEWBV7+L6M+9Sti9T1Jb54F2gyzK2BslXGtrR+5d/FwQJikPBnkKDhTBKEjQVYUoTXGs3I9RFOCZnQCXGeezfBez4+MYGrdWawvt/+ctHOi68VSerQM3pm5qU+lMgEn8RfG5MU4jUimbKp42F7lA3ADeK/2+w/G7gz8L/It5HwghfgD4AYCbN2+eV/9O5LwliYvaO3CjSUrrgmLyO6kPZfu8G6WTyaUgTlKkkh9brZnU9IQkzWjXDDYb1uGzKAqD2i3u+OtEkcTIMuJxpPLAj6eS0y2q8+zHCfvDgNWGRd3USJKU9aaFAgyCZMrEUn6G08iIjztnHvP8F49r61/m+nJ/t8a+GS+MqVu5NLiQ4gpACEGUZOiqIC5lqa2UTRVPm4tcIMScY7PqvvxEIX4v+QLxu+Z9LqX8OLn5iddff31uGxfBeUc9L7pukVammIROaqt48zWD+MhCo2squnL4Vdi6Bjo07aOS0AM3msQyADRMla6f15Z21dw807A1bq8dNesMwoi9YYSmCKJeMIkiv97OVU/BnrdQ2nlaGfGicxYxuzN4nJ3Csmauol+F2e9gfE3Xi9nperRsfeqzYRTjBSlNS6NuabQrZVPFJeAiI6l3gBdKv28D92ZPEkJ8NfBTwEellPsX2J9Tc95Rz4vaWxQrUbyhPk5hoO2OzWbLmorwLuo2l9sZBjFhkiuUCh6NQtZqRh4gN6ZYbMr3cqMEP8p4ca02OXfoJ5iamEzGjxuB/KQj0BflcVo2CrrobxGlDofjXrRhGsrks9WayUvrtbEYoHJQV1wOLnIH8SngFSHEi8Bd4PuA7y+fIIS4CfwT4E9IKb90gX05M+ctXV3U3nEqmvOoS9yyY7ZaJkmWHZFXwqFJpJx2PIxV6qaOronDwLJC+VQyb+32cj+HpalTQWgrpYXvcSOQTzsOj8OiXcJpzVzbndokfUdhnitf07F1rrWtKfMdnF/8RUXF43JhC4SUMhFC/BDwC+Qy15+WUn5OCPGD488/BvxfgFXgx4UQAImU8vWL6tNJLLItHxcZO2+iOstnhW5/6CeTOIPZc4+Thg6DGDfMJyJDFZN4hfJbOgAxc/tl6upUIZx2zWR/FBBnGToqLUtjEMT0vBjHPJRo9tyIbNwPT8nvX7e0SZvlCOJ5C1OZk57xuHE4L/JnionGC10qM/peiKYcRoLPcpyZa8Uxjpj9ytc4hnYk/Ufle6i4LFxoHISU8pPAJ2eOfaz0858D/txF9mFZHjcieZ7086yfBcOYe73uEbXNItnnF3YHfPnBkJqu0nUjTF3hpfU6lqFxcyXktVudE5+v7+eTcG7yiEmyjM2GSZRmHPQi/DDh0TDCtlQGQcJbjzwMVbDnxnT9kCSRmJpCyzao2xqvbjXo+/GRaObNhnUqqfCTznwaxumkv0UW2dW6gaaobK8ev9Obx0mR4E8j+r6iYlmqSGrOJyJ5nvTzrJ8VuvibK/ZElbRI9rk/CnjvwMMNUw7ciEzCw1FE3dbZbqvc2ffo1DRGYTb33mWZaTkXUW8sudQ1FVUJ+Py9PltNi1bNxI8T3t4bcWvVIUxSRn6KIqBd01lxdBxTQ1Pg0TB/Ey/s7EM/oW7mb9PLSIWfRgGeJMs4cGP8OJlkkd0fRby8Jo8tsHQcx5nGnlbixoqKZaiMnZyu0Mtx5571s9kiQ4UuPpopiFNuo/jZDROSTI7PHxfYMVSiOCNOJULk6qTjnq+cidYYq56EEJOCPGkKNUNHGTuokzQjySR+lJKk+cKTSYhTia7mGVeLwjuzz1A826LxWPS8yxw/DzRFoWFrk+cSAuqWghelREk68TectrjTcdecpb2KiidBtYPgdBLKs8gtj/us68cMvHiqyFDd1FgU8Tv7c/62np9nGxpSwt2uj20o6AOFtbrJimMc2UGU2zgp4tgxxsnrVGXyf00R2IZKWDKv66qYXNOwNYLh0WfQteOlrYued5nj54Gpq2w2LDQBmhLgRQlukNHzY/pBQsPSTky3UlHxrFDtIDidhPK4c0/7WVGwZ7bIEOTZUs1S0Nsi2edq3eKFlRqOqfJCx8YPEzaaBh3bQBECQ8sdyqeRmRYRx8X9G5bOh6838xgK8liKr9lus1E38nKglkrT1thq5nLajqOz1arRcfQT5bXH8aSlreV7rtYtWo6OF2Ws1A0URdCwNcJEVsV9Kp4bqh3EmNNKSWcVR7PtFOqecvbSlq2TZhKFvM5Bz43YHwUYmmBtpsjQC6vOlEpoXhbU4l7XWiav32rzoB9we80hk5JRkMch3FjJ5ZlnkZmW1UMf3m6x2/d4OAyxNZWtcQBc0T9Ty6OAy30tnrdla3xgS5yoYnrc7+W8KO5paYKWpSOkRAqBKpQpM1NFxbNOtUCUWFZCOas4SjLviCKoN94JDPzkSD1kATwaRURpdiSRW7nI0Lx2ZhU8RZ/XGhZrDYv/+PYBOwfeRFrZDfp5qc6xjfskxc1x8t4kA4FCkMhJ4r4XVp3JmBR9HfoJUZqhq4cb1HxXcTbTzEVLWxfdkzaEicxVTaOo9FllZqp4PqhMTKfkpGjaeZ/vdH0e9A/LYIZJyp19D2ASuXzgxoRJOlXj+Uy1izM5pbu3NZWDUfTYZpHj+jP7WfF8hdN96b5fMhqWPhXtDFRmpornimoHcUpOiqad93mRMK+IhyqUPXGSTkUurzXMyQ7hLMnpwjilbupsd+yxokigKOJczCKnURSVn4+Z6OGrZppZFO18FZ+louK0VAvEKZmnoBHk+vm9YTC35vBswrxC2VMoeopo2nJqiiTLeND3ycgT6zmGNnWfRdHQupZLVIt7SJnfZ16/T5PV9CRFUVSu8zzzfCe18aQ57XPPi3Y+7nuoqHhWqBaIUzIbGSuAKM14NFxcc3i7kzt0J0naNJVbq7UjNvpiotnperz1cMSDYcj+KKJmqby46tCpGVP3mfVJNCydzZbFKEymEsRtd+wjk9hpI5SPiwje6Xp0/XiiwFp19GOf72lyHs8dpxl7w/jU1d+qkqIVV41qgTgDZWVNkk0vDrC45vAydQmGQcyDfsC+G+OYGrauEqcSVeGI43deVHGusIJHwxBDU7nePro4nDVCeZHSqevGU6YyXVN5ZbMO8EQmxGUn3vN47nznEE/tEJdp40mnDKmoOA+qBWIBu/35MtaChqXjhjF3uz7DIGGtbhGWzCxhohGS4kdpbnoaJ88rt1Woc8p1lsM4b0OQ2/CDOAUh2B9GtOz8+IEbkaYZbccgjPOay8UEeViZTiFKJH3/6MT1OIWQZhVF5bbKppgwTp9IdPBpJt7zeO69YTC3qMm8NsqJCp90ypCKivOgWiDm8Nk73YnKCODWap7wbt45Ukru9XyatkfDyn0I+15Ix9bRVYXdfkDPj1mtG6zUzCNtzU5wpiawNEHfj7jf93HDlL1RxK21GroiUESueMok1E2VUZiw3a4hyf0AXT9/my+YNxGdZ4Ty04h2LjjtjuA8+rpsG+XvdRQkuHEy9b1A5eiuuPxUMtcZdvve1OIAcGffY7fvzT1HUfK6B1/aHdH3Qvw4Ic0k93oBQZzy7r5H34sZBQl+nEy1NW+CCxOJoSsIJHEi2RtFGLpAFaAIwRv3hqRSTu79hfsDen6u0Y8SydBPcKP8vyK/0+yb83lGKD+NaOeC0+ZqOo++LtPG7PdqaGLyvZS5LE77iopFVDuIGYalGAI/TsiyDFVRuNvNS3HGieRe1wMkcZohxpqljZaJokBNVxgGECUZfhRjGwpJJkkzSZwk1PS8gP1W63Ai86KEnhsRphkrjsFmw+Rap4YUEt0Q6KgoSh5fsFI3cEwVVREgJFEq8cIYTVUIkjhfpKIYhBinxogngXJlW/15Rig/iWjneX6Gs+wIzqOvJ7Uxu0AV6UbKst/L4rSvqDiOaoGYoQhc2/dCgjAlTjMO3Ig4TfnNuwNMTWEUxLxxf4CpqQy8mJqpsudGfOhak4GfcLfnE8QZllHjzp6HG+e1huM1ByGUyT2SLOOtvSH3ez53uwGZBMtQ+Ob3r9GydB4pGiPPQ5IikbRtHT9KMDWFNANVAVXNF4ndXsAgiDjwIrw4pWka1KyUV9brRFHGl3YHk+yscGirP69J6iKjnRf5GU6qtXCRfT2ujdkFSgKrjjlXuFBRcZmpTEwzbLVqbDYNvCBFUfJaAJtNk56X8GgY0vUi+n5CkGTc6/kEacbdbsB6w2R/FI1t4DrXWhaPeiEZEltXMXVlXA9BxzFzaei7+z5DP+KL90cIAaYq0BTBu/s+qgJBmherEUDD1BAKvLrVZGxhomnpvLReI4hTojSl5yWsOyZrNYO2o7FiG1h6Xgb0wSCYes6rEtl8UkT5dqfG7bUa11omt9dql0IZNM8M1R4nMKzSeldcJaodxBzev9lAQbDvhqzUDMIk5X7fB/I39zBJaVo6SImuKtTGwVS6KqhbBteaFplMudsT3NZV2raOqSlYhsb1ls2BGzH0Ex4OA3Z6eVnPB/2AtaZFGmXsdD2ut00+dK3FMIjJUok+9kvoQuGD1xrEqaRp6WRZRoogSvKSnkJA10+oSRAij6LOFPVI0BpcDSfpMsqjp5Gr6SSqQkAVzwLVAjEHU1dxLB1bU/jlR494Z98jTDLSLOPWah1VyR3EDcvA1hXcKEVKiaooGCromiCTGk1bR1MVVusm1jhVtq4JFPJFZhAkGKoKEoZhihwEbHdqqIqCMi5cv9W0J/1yo4QkzdCEgm3mi5IbJZiKoGbkpUCFIN91jAO3dU1ltW4QRIvrQVxmnqZK6nG5jAtXRcVpqExMcyhMBJ/b7fPZOz2+8sjl0TAgTiW7PR9DUxFIthomigBbV0kziaWprNcNgjilH0Q4hkYmJWGSp99YcfJI57ZjECUSW9do1XRW67k8VlEEigo3OhY1XaNhTn89hqqQZZK9Ucz9XsCDYcB2x2azZU0coVLCVsviA5sNXtl0+PD1Jq9sNJ6a0uhxeZoqqYqK551qB7GAOEl598DHMTUatoahKrhhyrW2ye1Vh296aY2+FyIUgVAElqahCIjTlCDJ2DbyetIf2GrQD2JeaNtslaKa15oGu4OAlZqJuanQtg2iLOPWSg3L0LjbC/iq7SZbTYswTscR1gl1M684F44D8lp2Plm27JitlkmSZXMdoVfZ5HGV+15RcZWpFgjmSyi7boShqXS9mIw855KuCqJUstG0cCydOMvQFJW6dTiMoyBBVVLaNXNybL2u0nGMqYntlY0GMpM8GARca1u0azp9P8EayyBbtsr+IKJhqiRZnjI8L0t6WDtCcmiLX8accZVNHk+y71XOpIqKnOd+gVgkobQNlb4bc61jcq8boggYeDEvrtVp2waSwyytAiZpNgQSY+wQdqPD3ESmnqtrihQempoH2DVtDU1RuNGyeDQMiRLJKIx5MAiJU59HI5/mWI0EeT8P3Ji6qWEsyNJacXaqnEkVFYc81wtEIaEsT/BRktKyddYbFjfX8jiG921oxGnG9Y7NK+uNI1lav3BvwINhiK4KVusmjqHx7v6IMJF5pHUNdgcBv/Zuj71RSJikPBiEtGsGH9hqsN2x8xKkfoIk5Z1dDy8o1DuCB6OIr9tu07C1SSBflEg2W1d3R3AZOWsyv4qKZ5XneoEI4xQBeUnJ8cTgxwlRkvLiusM3vLjKjY7FwI9p2jo32g7rpWAnN4z58oMhX9kbYesqqqKwNwx4K0iwNAVVUdhsmAjg//elRwzDhFTC0I8Jk4xHoxCZZYzChG98cYWOo/OlB8FkcWjaGrau0OvH9IM8x5ImAtwwYatlVG+258zjJPOrqHgWea4XCFNXCZN0sjjseyFekKIpAlNTQQhutB1utPPzO+NgJ8iT9b2z5/Je1+fhIGC9YdCs6bz1wMU2FFRV5HEKUlIzNIIk5WAU0/ND3nrksdkyqRkqfpwy9BMO3Ihbqw5+mHC/F6CrIpfAki8UAsmDYcDQT1hxdNwwj5eoFonz4ypLaisqLoLndoEoHJFCSITI8yF5QUrT1jBUlTCRNCx1bnqEIllfXtYzd2A/HIYEcYIE3DhFSwRDP8WvZTRqCaoQ3B/42LqKBNIMHg4i3rcxTrw37tdW22a7E3DgHtYceGnN4YUVm91+RMfWMbW8jcr8cb6cNXVHRcWzynO5QJQdkVGa5z8yVA1Nyd/aJXkGTgloisLaTJrmwg+gq4IsywPTHgwCsiyvNrZWN8ikZBikICBJJTVDpVPT8aOMlZqOpkDNUImSDNtUaI/LjTYsnZc36tT7waS2xGbLwtIURmEe7FauR1CZP86XSlJbUXHIc7dAzDoiHUNjFOby0jCJkOQy0uItfZ55oUi2V6T6fjgM2GpZ1HSFl9Yd9twYmZHHQWw2sHSFIE4ZtFK8MOLFNZtBkJCkcK1pU9PUqcI++SSlH6ncBkw51A1NVOaPC+Aqy4ErKs6T52aBGAYxB27EwI+42/NJU0kqJX6cogLX2haWCpmUuEHEyI9yZZGrHakIt9WqsdX2eHN3hBvGGJrCet1krW7gJymqouDFKVsNixUnz+X00rqDqSt50jwp0TWVzYbFy2sOmqYeMRfNTlKF+eMrD0dT9abnVYyrqKioOA+eiwVip+vxhd0hQz9hp+fycJwuY6cX4EYxtqZSN1U0VaHvxURpRpikXGvZbLUtTFWlUdPp2HlFuI2mSRxnCAX6fkynprPZtFhzTHaHPoEmaSgKdwc+e27EzY7Newc+qlBYdUzefDjC0lU0RaEfJqyO4yZOMhe1bB1TV1mr5zEYjqFVfoiKiooL40JzMQkhvl0I8UUhxJtCiL8253MhhPjb489/Qwjx2nn3YRjE7HR9hn5C3wt51I9wTJ33Djzu932yVOLFKW/vuzwY5HLXd/Y84gx2ewFv7AzZdyOCKMWPE76wO+CdRyP23RiBwDZ0ggR2ej6DIKbvp6w7Rm6mUlV0VaCrCvtuTNeLOfBiVuomXpQRprmCKkxyeeVJ5qIwTnEMjXYtj7UoH6+oqKg4by5sgRBCqMCPAR8BPgT8MSHEh2ZO+wjwyvi/HwB+4rz7EcZpXskL8OOUVEqSTLLSMFlz8kprAz8mTCRRmpFkGRmQppIwy0hkRpRmxCkkaUaSZvT93MSjq2JynyTNcKP8PrqWV3yrGRq6qk6Ox6kkSTNsXaNmqcRp7m6OErmUWqaSYVZUVDxJLnIH8Q3Am1LKt6SUEfAzwEdnzvko8A9kzq8CbSHEtfPshKkf1kKwxxOprirITBIkGVGSoigCVcmzpWqKggKoqsBUFDShYKgKugqaqqCpCi07n8gNVaU5dlhrqoJjqDRsLa8NUaq/4BjFfQWamg/5as3kRttira7z4rq9VDxDldm0oqLiSXKRPogbwHul33eAb1zinBvA/fJJQogfIN9hcPPmzVN1omHpbHdsRmEuTV1rxGgCVp06iqIwCCLev9lg4EU0bZ1hkNC0NaIkY6NpTnwQlqFi6xq3VmtsNE1SmTuL27bBetPk9orNzdU6fT9XSTlGngVWVwQNSydMM5JMsqoYHLgxDVtjtW5NBd8tQyXDrKioeFJc5AIh5hyTZzgHKeXHgY8DvP7660c+P4lCNnrgRrx+q02SZSSp5He+kpuFFMA2VIZhQhKnZDJDUTUcU2GlZk3OL1RMkDuMe25EBqyUMrUWqbfDOOX2Wn5uGKfcLP28KCX3slQyzIqKiifBRS4QO8ALpd+3gXtnOOdcOO9J9bj25klU5/1cUVFRcZm5SB/Ep4BXhBAvCiEM4PuAT8yc8wngT47VTL8D6Esp7882VFFRUVHx5LmwHYSUMhFC/BDwC4AK/LSU8nNCiB8cf/4x4JPAdwBvAh7wpy+qPxUVFRUVp+NCA+WklJ8kXwTKxz5W+lkCf+ki+1BRUVFRcTYuNFCuoqKiouLqUi0QFRUVFRVzEbmV5+oghHgE3AHWgL2n3J3LQDUOh1RjkVONQ041DjnFONySUq6f5sIrt0AUCCE+LaV8/Wn342lTjcMh1VjkVOOQU41DzuOMQ2ViqqioqKiYS7VAVFRUVFTM5SovEB9/2h24JFTjcEg1FjnVOORU45Bz5nG4sj6IioqKioqL5SrvICoqKioqLpBqgaioqKiomMulXyAuQ9nSy8AS4/DHx8//G0KIXxFCfM3T6OdFc9I4lM77eiFEKoT43ifZvyfFMuMghPg9QohfE0J8Tgjx7550H58ES/y7aAkhflYI8evjcXgm870JIX5aCPFQCPFbCz4/2zwppby0/5En+fsK8BJgAL8OfGjmnO8A/gV5bYnfAfzHp93vpzQO3wR0xj9/5Hkdh9J5/5Y8D9j3Pu1+P6W/hzbwBnBz/PvG0+73UxqHvw78jfHP68ABYDztvl/AWPxu4DXgtxZ8fqZ58rLvIC5F2dJLwInjIKX8FSlld/zrr5LX1njWWObvAeAvA/8YePgkO/cEWWYcvh/4J1LKdwGklM/iWCwzDhJoCCEEUCdfIJIn282LR0r5y+TPtogzzZOXfYFYVJL0tOdcdU77jH+W/G3hWePEcRBC3AC+B/gYzy7L/D28H+gIIX5JCPEZIcSffGK9e3IsMw4/CnyQvBDZbwJ/VUqZPZnuXSrONE9eaLrvc+DcypZecZZ+RiHE7yVfIH7Xhfbo6bDMOPxN4IellGn+0vhMssw4aMBvB34fYAP/QQjxq1LKL110554gy4zDtwG/BnwL8DLwr4QQ/15KObjgvl02zjRPXvYF4lKVLX2KLPWMQoivBn4K+IiUcv8J9e1Jssw4vA78zHhxWAO+QwiRSCn/2RPp4ZNh2X8Xe1JKF3CFEL8MfA3wLC0Qy4zDnwZ+ROaG+DeFEG8DrwL/6cl08dJwpnnyspuYqrKlOSeOgxD///buJ8SmMA7j+PcJpYkSihUjQpJkg5hYSDY2ysJCFFlQkpSNWNiwsaSwoKYmmZSiFMuZzEL+1yjl/85OiYU8FveVm85cl+HecXo+dbt/znlP73279zz3Pef2O5oHXAN21uxXYrNfjoPtBbZ7bfcCg8D+moUDtPe9uA70SZosqQdYDYx2uJ//Wjvj8IbGLApJc4AlwIuO9nJi+KP95ISeQTiXLQXaHofjwCzgbPn1/MU1q2TZ5jjUXjvjYHtU0i3gMfAVuGi78i+Q/6s2Pw8ngUuSntA4zHLUdu1KgEsaADYCsyW9A04AU2B8+8mU2oiIiEoT/RBTRER0SQIiIiIqJSAiIqJSAiIiIiolICIiolICIqIDSmXVG93uR8TvSEBEjIOkSd3uQ8S/koCIGIOkXknPJF0uNfQHJfVIeiXpuKQhYLukzZLuSrov6aqkaaX9ltJ+CNjWtN0N5ToNDyU9kDS9W+8xopUERERrS4DztlcAH4D95fXPttcDd4BjwCbbq4B7wGFJU4ELwFagD5jbtM0jwAHbK8uyT514IxG/KwER0dpb28PlcT8/quReKfdrgGXAsKSHwC5gPo2CcC9tPy+F4vqbtjkMnJF0EJhhu3bXJ4h6SEBEtPZzLZrvzz+WewG3ba8st2W294zRtvGifQrYS6MM94ikpX+70xF/QwIiorV5ktaWxzuAoZ+WjwDrJC0CKOcoFgPPgAWSFja1payz0PYT26dpHJJKQMSElICIaG0U2CXpMTATONe80PZ7YDcwUNYZAZba/gzsA26Wk9Svm5odkvRU0iMa5x/qePW/qIFUc40Yg6Re4Ibt5d3uS0Q3ZAYRERGVMoOIiIhKmUFERESlBERERFRKQERERKUEREREVEpAREREpW9+RMKRBHgomgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# zoom in on conditional trials\n",
    "import seaborn as sns\n",
    "d = df1\n",
    "d[\"preds\"] = fits[\"exp1\"][\"Unrestricted BS hier.\"].posterior_predictive.mean(dim=['chain', 'draw']).yhat\n",
    "d = d[d.querytype.transform(is_cond).astype(\"bool\")]\n",
    "trial_df = (d\n",
    "                .groupby([\"querytype\", \"querydetail\"])\n",
    "                .agg({\"preds\":\"mean\", \"estimate\":\"mean\"}).reset_index()\n",
    "               )\n",
    "\n",
    "print(\"Bayesian Sampler conditional response corr = \", np.round(np.corrcoef(d.estimate, d.preds)[0,1],4))\n",
    "sns.scatterplot(x = d.preds, y = d.estimate, alpha=.2)\n",
    "print(\"Bayesian Sampler conditional query-level corr\", np.round(np.corrcoef(trial_df.estimate, trial_df.preds)[0,1],4))\n",
    "sns.scatterplot(x = trial_df.preds, y = trial_df.estimate)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PT+N conditional response corr =  0.8937\n",
      "PT+N conditional query-level corr 0.9694\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='preds', ylabel='estimate'>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "d = df1\n",
    "d[\"preds\"] = fits[\"exp1\"][\"PT+N complex hier.\"].posterior_predictive.mean(dim=['chain', 'draw']).yhat\n",
    "d = d[d.querytype.transform(is_cond).astype(\"bool\")]\n",
    "\n",
    "trial_df = (d\n",
    "                .groupby([\"querytype\", \"querydetail\"])\n",
    "                .agg({\"preds\":\"mean\", \"estimate\":\"mean\"}).reset_index()\n",
    "               )\n",
    "\n",
    "print(\"PT+N conditional response corr = \", np.round(np.corrcoef(d.estimate, d.preds)[0,1],4))\n",
    "sns.scatterplot(x = d.preds, y = d.estimate, alpha=.2)\n",
    "print(\"PT+N conditional query-level corr\", np.round(np.corrcoef(trial_df.estimate, trial_df.preds)[0,1],4))\n",
    "sns.scatterplot(x = trial_df.preds, y = trial_df.estimate)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Experiment 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Bayesian Sampler conditional response corr =  0.7186\n",
      "Bayesian Sampler conditional query-level corr 0.9244\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='preds', ylabel='estimate'>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "d = df2\n",
    "d[\"preds\"] = fits[\"exp2\"][\"Unrestricted BS hier.\"].posterior_predictive.mean(dim=['chain', 'draw']).yhat\n",
    "d = d[d.querytype.transform(is_cond).astype(\"bool\")]\n",
    "trial_df = (d\n",
    "                .groupby([\"querytype\", \"querydetail\"])\n",
    "                .agg({\"preds\":\"mean\", \"estimate\":\"mean\"}).reset_index()\n",
    "               )\n",
    "\n",
    "print(\"Bayesian Sampler conditional response corr = \", np.round(np.corrcoef(d.estimate, d.preds)[0,1],4))\n",
    "sns.scatterplot(x = d.preds, y = d.estimate, alpha=.2)\n",
    "print(\"Bayesian Sampler conditional query-level corr\", np.round(np.corrcoef(trial_df.estimate, trial_df.preds)[0,1],4))\n",
    "sns.scatterplot(x = trial_df.preds, y = trial_df.estimate)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PT+N conditional response corr =  0.6702\n",
      "PT+N conditional query-level corr 0.8541\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='preds', ylabel='estimate'>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "d = df2\n",
    "d[\"preds\"] = fits[\"exp2\"][\"PT+N complex hier.\"].posterior_predictive.mean(dim=['chain', 'draw']).yhat\n",
    "d = d[d.querytype.transform(is_cond).astype(\"bool\")]\n",
    "\n",
    "trial_df = (d\n",
    "                .groupby([\"querytype\", \"querydetail\"])\n",
    "                .agg({\"preds\":\"mean\", \"estimate\":\"mean\"}).reset_index()\n",
    "               )\n",
    "\n",
    "print(\"PT+N conditional response corr = \", np.round(np.corrcoef(d.estimate, d.preds)[0,1],4))\n",
    "sns.scatterplot(x = d.preds, y = d.estimate, alpha=.2)\n",
    "print(\"PT+N conditional query-level corr\", np.round(np.corrcoef(trial_df.estimate, trial_df.preds)[0,1],4))\n",
    "sns.scatterplot(x = trial_df.preds, y = trial_df.estimate)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Create fit summary table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.884\n",
      "0.964\n"
     ]
    }
   ],
   "source": [
    "def response_level_r(orig_data, model):\n",
    "    \n",
    "    d = orig_data\n",
    "    d[\"preds\"] = model.posterior_predictive.mean(dim=['chain', 'draw']).yhat\n",
    "    \n",
    "    return np.round(np.corrcoef(d.estimate, d.preds)[0,1],3)\n",
    "    \n",
    "def trial_level_r(orig_data, model):\n",
    "    \n",
    "    d = orig_data\n",
    "    d[\"preds\"] = model.posterior_predictive.mean(dim=['chain', 'draw']).yhat\n",
    "\n",
    "    trial_df = (d\n",
    "                .groupby([\"querytype\", \"querydetail\"])\n",
    "                .agg({\"preds\":\"mean\", \"estimate\":\"mean\"})\n",
    "               )\n",
    "    \n",
    "    return np.round(np.corrcoef(trial_df.estimate, trial_df.preds)[0,1],3)\n",
    "\n",
    "\n",
    "    \n",
    "print(response_level_r(df1, fits[\"exp1\"][\"Unrestricted BS hier.\"]))\n",
    "print(trial_level_r(df1, fits[\"exp1\"][\"Unrestricted BS hier.\"]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "exp1_corrs = pd.DataFrame({\n",
    "    \"model\": fits[\"exp1\"].keys(),\n",
    "    \"resp_r\": [response_level_r(df1, fits[\"exp1\"][k]) for k in fits[\"exp1\"].keys()],\n",
    "    \"trial_r\": [trial_level_r(df1, fits[\"exp1\"][k]) for k in fits[\"exp1\"].keys()],\n",
    "    \"Experiment\": \"Exp. 1\"\n",
    "     }\n",
    ")\n",
    "\n",
    "exp2_corrs = pd.DataFrame({\n",
    "    \"model\": fits[\"exp2\"].keys(),\n",
    "    \"resp_r\": [response_level_r(df2, fits[\"exp2\"][k]) for k in fits[\"exp1\"].keys()],\n",
    "    \"trial_r\": [trial_level_r(df2, fits[\"exp2\"][k]) for k in fits[\"exp1\"].keys()],\n",
    "    \"Experiment\": \"Exp. 2\"\n",
    "     }\n",
    ")\n",
    "\n",
    "full_model_compare = s.left_join(model_comparison, exp1_corrs.append(exp2_corrs), by=[\"model\",\"Experiment\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Experiment</th>\n",
       "      <th>model</th>\n",
       "      <th>loo</th>\n",
       "      <th>penalty</th>\n",
       "      <th>resp_r</th>\n",
       "      <th>trial_r</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Exp. 1</td>\n",
       "      <td>Unrestricted BS hier.</td>\n",
       "      <td>1118.7</td>\n",
       "      <td>259.3</td>\n",
       "      <td>0.884</td>\n",
       "      <td>0.964</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Exp. 1</td>\n",
       "      <td>Bayesian Sampler complex hier.</td>\n",
       "      <td>1088.3</td>\n",
       "      <td>269.6</td>\n",
       "      <td>0.883</td>\n",
       "      <td>0.960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Exp. 1</td>\n",
       "      <td>Bayesian Sampler complex</td>\n",
       "      <td>1087.8</td>\n",
       "      <td>264.6</td>\n",
       "      <td>0.883</td>\n",
       "      <td>0.961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Exp. 1</td>\n",
       "      <td>Bayesian Sampler simple</td>\n",
       "      <td>1045.6</td>\n",
       "      <td>253.8</td>\n",
       "      <td>0.874</td>\n",
       "      <td>0.952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Exp. 1</td>\n",
       "      <td>Bayesian Sampler simple hier.</td>\n",
       "      <td>1039.6</td>\n",
       "      <td>259.1</td>\n",
       "      <td>0.874</td>\n",
       "      <td>0.953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Exp. 1</td>\n",
       "      <td>PT+N complex hier.</td>\n",
       "      <td>993.0</td>\n",
       "      <td>268.9</td>\n",
       "      <td>0.867</td>\n",
       "      <td>0.946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Exp. 1</td>\n",
       "      <td>PT+N complex</td>\n",
       "      <td>966.1</td>\n",
       "      <td>259.8</td>\n",
       "      <td>0.864</td>\n",
       "      <td>0.941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Exp. 1</td>\n",
       "      <td>PT+N simple hier.</td>\n",
       "      <td>864.0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>0.839</td>\n",
       "      <td>0.919</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Exp. 1</td>\n",
       "      <td>PT+N simple</td>\n",
       "      <td>863.5</td>\n",
       "      <td>245.5</td>\n",
       "      <td>0.838</td>\n",
       "      <td>0.918</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Exp. 1</td>\n",
       "      <td>Relative Freq.</td>\n",
       "      <td>649.3</td>\n",
       "      <td>289.4</td>\n",
       "      <td>0.820</td>\n",
       "      <td>0.875</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Exp. 2</td>\n",
       "      <td>Unrestricted BS hier.</td>\n",
       "      <td>1978.6</td>\n",
       "      <td>366.4</td>\n",
       "      <td>0.688</td>\n",
       "      <td>0.878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Exp. 2</td>\n",
       "      <td>Bayesian Sampler complex hier.</td>\n",
       "      <td>1912.3</td>\n",
       "      <td>395.0</td>\n",
       "      <td>0.675</td>\n",
       "      <td>0.852</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Exp. 2</td>\n",
       "      <td>PT+N complex hier.</td>\n",
       "      <td>1902.4</td>\n",
       "      <td>351.5</td>\n",
       "      <td>0.658</td>\n",
       "      <td>0.835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Exp. 2</td>\n",
       "      <td>Bayesian Sampler simple hier.</td>\n",
       "      <td>1900.7</td>\n",
       "      <td>377.8</td>\n",
       "      <td>0.667</td>\n",
       "      <td>0.839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Exp. 2</td>\n",
       "      <td>PT+N complex</td>\n",
       "      <td>1886.9</td>\n",
       "      <td>395.5</td>\n",
       "      <td>0.667</td>\n",
       "      <td>0.840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Exp. 2</td>\n",
       "      <td>Bayesian Sampler complex</td>\n",
       "      <td>1876.9</td>\n",
       "      <td>443.4</td>\n",
       "      <td>0.679</td>\n",
       "      <td>0.848</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Exp. 2</td>\n",
       "      <td>Bayesian Sampler simple</td>\n",
       "      <td>1861.2</td>\n",
       "      <td>419.1</td>\n",
       "      <td>0.667</td>\n",
       "      <td>0.831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Exp. 2</td>\n",
       "      <td>PT+N simple hier.</td>\n",
       "      <td>1821.9</td>\n",
       "      <td>305.3</td>\n",
       "      <td>0.617</td>\n",
       "      <td>0.772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Exp. 2</td>\n",
       "      <td>PT+N simple</td>\n",
       "      <td>1821.5</td>\n",
       "      <td>319.5</td>\n",
       "      <td>0.619</td>\n",
       "      <td>0.777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Exp. 2</td>\n",
       "      <td>Relative Freq.</td>\n",
       "      <td>643.8</td>\n",
       "      <td>424.6</td>\n",
       "      <td>0.516</td>\n",
       "      <td>0.639</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Experiment                           model     loo  penalty  resp_r  \\\n",
       "0      Exp. 1           Unrestricted BS hier.  1118.7    259.3   0.884   \n",
       "1      Exp. 1  Bayesian Sampler complex hier.  1088.3    269.6   0.883   \n",
       "2      Exp. 1        Bayesian Sampler complex  1087.8    264.6   0.883   \n",
       "3      Exp. 1         Bayesian Sampler simple  1045.6    253.8   0.874   \n",
       "4      Exp. 1   Bayesian Sampler simple hier.  1039.6    259.1   0.874   \n",
       "5      Exp. 1              PT+N complex hier.   993.0    268.9   0.867   \n",
       "6      Exp. 1                    PT+N complex   966.1    259.8   0.864   \n",
       "7      Exp. 1               PT+N simple hier.   864.0    250.0   0.839   \n",
       "8      Exp. 1                     PT+N simple   863.5    245.5   0.838   \n",
       "9      Exp. 1                  Relative Freq.   649.3    289.4   0.820   \n",
       "10     Exp. 2           Unrestricted BS hier.  1978.6    366.4   0.688   \n",
       "11     Exp. 2  Bayesian Sampler complex hier.  1912.3    395.0   0.675   \n",
       "12     Exp. 2              PT+N complex hier.  1902.4    351.5   0.658   \n",
       "13     Exp. 2   Bayesian Sampler simple hier.  1900.7    377.8   0.667   \n",
       "14     Exp. 2                    PT+N complex  1886.9    395.5   0.667   \n",
       "15     Exp. 2        Bayesian Sampler complex  1876.9    443.4   0.679   \n",
       "16     Exp. 2         Bayesian Sampler simple  1861.2    419.1   0.667   \n",
       "17     Exp. 2               PT+N simple hier.  1821.9    305.3   0.617   \n",
       "18     Exp. 2                     PT+N simple  1821.5    319.5   0.619   \n",
       "19     Exp. 2                  Relative Freq.   643.8    424.6   0.516   \n",
       "\n",
       "    trial_r  \n",
       "0     0.964  \n",
       "1     0.960  \n",
       "2     0.961  \n",
       "3     0.952  \n",
       "4     0.953  \n",
       "5     0.946  \n",
       "6     0.941  \n",
       "7     0.919  \n",
       "8     0.918  \n",
       "9     0.875  \n",
       "10    0.878  \n",
       "11    0.852  \n",
       "12    0.835  \n",
       "13    0.839  \n",
       "14    0.840  \n",
       "15    0.848  \n",
       "16    0.831  \n",
       "17    0.772  \n",
       "18    0.777  \n",
       "19    0.639  "
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "table_output = (\n",
    "    full_model_compare >> \n",
    "    s.mutate(loo = np.round(_.loo,1), penalty = np.round(_.p_loo, 1)) >>\n",
    "    s.select(_.Experiment, _.model, _.loo, _.penalty, _.resp_r, _.trial_r)\n",
    ")\n",
    "\n",
    "table_output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('paper-rmd/model-comparison-table.csv', 'w') as tf:\n",
    "     tf.write(table_output.to_csv())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Supplemental plots: pairs plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<AxesSubplot:ylabel='d_prime_pop'>, <AxesSubplot:>],\n",
       "       [<AxesSubplot:xlabel='d_base_pop', ylabel='k'>,\n",
       "        <AxesSubplot:xlabel='d_prime_pop'>]], dtype=object)"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1472x1104 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "az.plot_pair(model1, var_names=[\"d_base_pop\",\"d_prime_pop\", \"k\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<AxesSubplot:ylabel='d_prime_pop'>, <AxesSubplot:>],\n",
       "       [<AxesSubplot:xlabel='d_base_pop', ylabel='k'>,\n",
       "        <AxesSubplot:xlabel='d_prime_pop'>]], dtype=object)"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1472x1104 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "az.plot_pair(model2, var_names=[\"d_base_pop\",\"d_prime_pop\", \"k\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Py3-basic",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.2"
  },
  "vscode": {
   "interpreter": {
    "hash": "f0ef5f7d10080c600b0562a944fa966eaa386c980e0d8cd0525dadb77bc4588e"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}