Lecture21_01 - Poisson Regression - tools on islands part 2.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Poisson Regression - tools on islands part 2\n",
    "\n",
    "##### Keywords: poisson distribution, poisson regression, glm, centering, counterfactual plot, regression, interaction-term, model-comparison, varying intercept, WAIC, hierarchical, overdispersion, oceanic tools"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import scipy as sp\n",
    "import matplotlib as mpl\n",
    "import matplotlib.cm as cm\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "pd.set_option('display.width', 500)\n",
    "pd.set_option('display.max_columns', 100)\n",
    "pd.set_option('display.notebook_repr_html', True)\n",
    "import seaborn as sns\n",
    "sns.set_style(\"whitegrid\")\n",
    "sns.set_context(\"poster\")\n",
    "import pymc3 as pm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We go back to our island tools data set to illustrate\n",
    "\n",
    "- model comparison using WAIC\n",
    "- model averaging using WAIC\n",
    "- fighting overdispersion by making a hierarchical regression model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>culture</th>\n",
       "      <th>population</th>\n",
       "      <th>contact</th>\n",
       "      <th>total_tools</th>\n",
       "      <th>mean_TU</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Malekula</td>\n",
       "      <td>1100</td>\n",
       "      <td>low</td>\n",
       "      <td>13</td>\n",
       "      <td>3.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Tikopia</td>\n",
       "      <td>1500</td>\n",
       "      <td>low</td>\n",
       "      <td>22</td>\n",
       "      <td>4.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Santa Cruz</td>\n",
       "      <td>3600</td>\n",
       "      <td>low</td>\n",
       "      <td>24</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Yap</td>\n",
       "      <td>4791</td>\n",
       "      <td>high</td>\n",
       "      <td>43</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Lau Fiji</td>\n",
       "      <td>7400</td>\n",
       "      <td>high</td>\n",
       "      <td>33</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Trobriand</td>\n",
       "      <td>8000</td>\n",
       "      <td>high</td>\n",
       "      <td>19</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Chuuk</td>\n",
       "      <td>9200</td>\n",
       "      <td>high</td>\n",
       "      <td>40</td>\n",
       "      <td>3.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Manus</td>\n",
       "      <td>13000</td>\n",
       "      <td>low</td>\n",
       "      <td>28</td>\n",
       "      <td>6.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Tonga</td>\n",
       "      <td>17500</td>\n",
       "      <td>high</td>\n",
       "      <td>55</td>\n",
       "      <td>5.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Hawaii</td>\n",
       "      <td>275000</td>\n",
       "      <td>low</td>\n",
       "      <td>71</td>\n",
       "      <td>6.6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      culture  population contact  total_tools  mean_TU\n",
       "0    Malekula        1100     low           13      3.2\n",
       "1     Tikopia        1500     low           22      4.7\n",
       "2  Santa Cruz        3600     low           24      4.0\n",
       "3         Yap        4791    high           43      5.0\n",
       "4    Lau Fiji        7400    high           33      5.0\n",
       "5   Trobriand        8000    high           19      4.0\n",
       "6       Chuuk        9200    high           40      3.8\n",
       "7       Manus       13000     low           28      6.6\n",
       "8       Tonga       17500    high           55      5.4\n",
       "9      Hawaii      275000     low           71      6.6"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=pd.read_csv(\"data/islands.csv\", sep=';')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>culture</th>\n",
       "      <th>population</th>\n",
       "      <th>contact</th>\n",
       "      <th>total_tools</th>\n",
       "      <th>mean_TU</th>\n",
       "      <th>logpop</th>\n",
       "      <th>clevel</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Malekula</td>\n",
       "      <td>1100</td>\n",
       "      <td>low</td>\n",
       "      <td>13</td>\n",
       "      <td>3.2</td>\n",
       "      <td>7.003065</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Tikopia</td>\n",
       "      <td>1500</td>\n",
       "      <td>low</td>\n",
       "      <td>22</td>\n",
       "      <td>4.7</td>\n",
       "      <td>7.313220</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Santa Cruz</td>\n",
       "      <td>3600</td>\n",
       "      <td>low</td>\n",
       "      <td>24</td>\n",
       "      <td>4.0</td>\n",
       "      <td>8.188689</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Yap</td>\n",
       "      <td>4791</td>\n",
       "      <td>high</td>\n",
       "      <td>43</td>\n",
       "      <td>5.0</td>\n",
       "      <td>8.474494</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Lau Fiji</td>\n",
       "      <td>7400</td>\n",
       "      <td>high</td>\n",
       "      <td>33</td>\n",
       "      <td>5.0</td>\n",
       "      <td>8.909235</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Trobriand</td>\n",
       "      <td>8000</td>\n",
       "      <td>high</td>\n",
       "      <td>19</td>\n",
       "      <td>4.0</td>\n",
       "      <td>8.987197</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Chuuk</td>\n",
       "      <td>9200</td>\n",
       "      <td>high</td>\n",
       "      <td>40</td>\n",
       "      <td>3.8</td>\n",
       "      <td>9.126959</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Manus</td>\n",
       "      <td>13000</td>\n",
       "      <td>low</td>\n",
       "      <td>28</td>\n",
       "      <td>6.6</td>\n",
       "      <td>9.472705</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Tonga</td>\n",
       "      <td>17500</td>\n",
       "      <td>high</td>\n",
       "      <td>55</td>\n",
       "      <td>5.4</td>\n",
       "      <td>9.769956</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Hawaii</td>\n",
       "      <td>275000</td>\n",
       "      <td>low</td>\n",
       "      <td>71</td>\n",
       "      <td>6.6</td>\n",
       "      <td>12.524526</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      culture  population contact  total_tools  mean_TU     logpop  clevel\n",
       "0    Malekula        1100     low           13      3.2   7.003065       0\n",
       "1     Tikopia        1500     low           22      4.7   7.313220       0\n",
       "2  Santa Cruz        3600     low           24      4.0   8.188689       0\n",
       "3         Yap        4791    high           43      5.0   8.474494       1\n",
       "4    Lau Fiji        7400    high           33      5.0   8.909235       1\n",
       "5   Trobriand        8000    high           19      4.0   8.987197       1\n",
       "6       Chuuk        9200    high           40      3.8   9.126959       1\n",
       "7       Manus       13000     low           28      6.6   9.472705       0\n",
       "8       Tonga       17500    high           55      5.4   9.769956       1\n",
       "9      Hawaii      275000     low           71      6.6  12.524526       0"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['logpop']=np.log(df.population)\n",
    "df['clevel']=(df.contact=='high')*1\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def postscat(trace, thevars):\n",
    "    d={}\n",
    "    for v in thevars:\n",
    "        d[v] = trace.get_values(v)\n",
    "    df = pd.DataFrame.from_dict(d)\n",
    "    g = sns.pairplot(df, diag_kind=\"kde\", plot_kws={'s':10})\n",
    "    for i, j in zip(*np.triu_indices_from(g.axes, 1)):\n",
    "        g.axes[i, j].set_visible(False)\n",
    "    return g"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Centered Model\n",
    "\n",
    "As usual, centering the log-population fixes things:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df.logpop_c = df.logpop - df.logpop.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "from theano import tensor as t\n",
    "with pm.Model() as m1c:\n",
    "    betap = pm.Normal(\"betap\", 0, 1)\n",
    "    betac = pm.Normal(\"betac\", 0, 1)\n",
    "    betapc = pm.Normal(\"betapc\", 0, 1)\n",
    "    alpha = pm.Normal(\"alpha\", 0, 100)\n",
    "    loglam = alpha + betap*df.logpop_c + betac*df.clevel + betapc*df.clevel*df.logpop_c\n",
    "    y = pm.Poisson(\"ntools\", mu=t.exp(loglam), observed=df.total_tools)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Auto-assigning NUTS sampler...\n",
      "Initializing NUTS using jitter+adapt_diag...\n",
      "Multiprocess sampling (2 chains in 2 jobs)\n",
      "NUTS: [alpha, betapc, betac, betap]\n",
      "100%|██████████| 6000/6000 [00:08<00:00, 677.13it/s]\n"
     ]
    }
   ],
   "source": [
    "with m1c:\n",
    "    trace1c = pm.sample(5000, tune=1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x114e02908>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pm.traceplot(trace1c);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115e6cd30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pm.autocorrplot(trace1c);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'alpha': 6874.0, 'betac': 5729.0, 'betap': 8246.0, 'betapc': 6812.0}"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pm.effective_n(trace1c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x116424748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "postscat(trace1c,trace1c.varnames);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115acbf28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pm.plot_posterior(trace1c);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model comparison for interaction significance\n",
    "\n",
    "This is an example of feature selection, where we want to decide whether we should keep the interaction term or not, that is, whether the interaction is significant or not? We'll use model comparison to achieve this!\n",
    "\n",
    "We can see some summary stats from this model:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\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>mc_error</th>\n",
       "      <th>hpd_2.5</th>\n",
       "      <th>hpd_97.5</th>\n",
       "      <th>n_eff</th>\n",
       "      <th>Rhat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>betap</th>\n",
       "      <td>0.262633</td>\n",
       "      <td>0.036001</td>\n",
       "      <td>0.000406</td>\n",
       "      <td>0.193631</td>\n",
       "      <td>0.335489</td>\n",
       "      <td>8246.0</td>\n",
       "      <td>1.000064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>betac</th>\n",
       "      <td>0.283962</td>\n",
       "      <td>0.116508</td>\n",
       "      <td>0.001489</td>\n",
       "      <td>0.054386</td>\n",
       "      <td>0.507466</td>\n",
       "      <td>5729.0</td>\n",
       "      <td>0.999912</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>betapc</th>\n",
       "      <td>0.069461</td>\n",
       "      <td>0.171149</td>\n",
       "      <td>0.002120</td>\n",
       "      <td>-0.255683</td>\n",
       "      <td>0.412522</td>\n",
       "      <td>6812.0</td>\n",
       "      <td>0.999901</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>alpha</th>\n",
       "      <td>3.311851</td>\n",
       "      <td>0.089442</td>\n",
       "      <td>0.001194</td>\n",
       "      <td>3.132732</td>\n",
       "      <td>3.484661</td>\n",
       "      <td>6874.0</td>\n",
       "      <td>1.000020</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            mean        sd  mc_error   hpd_2.5  hpd_97.5   n_eff      Rhat\n",
       "betap   0.262633  0.036001  0.000406  0.193631  0.335489  8246.0  1.000064\n",
       "betac   0.283962  0.116508  0.001489  0.054386  0.507466  5729.0  0.999912\n",
       "betapc  0.069461  0.171149  0.002120 -0.255683  0.412522  6812.0  0.999901\n",
       "alpha   3.311851  0.089442  0.001194  3.132732  3.484661  6874.0  1.000020"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfsum=pm.summary(trace1c)\n",
    "dfsum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "//anaconda/envs/py3l/lib/python3.6/site-packages/ipykernel_launcher.py:1: DeprecationWarning: dic has been deprecated. Use `waic` or `loo` instead.\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "95.700834543217113"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pm.dic(trace1c, m1c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "//anaconda/envs/py3l/lib/python3.6/site-packages/pymc3/stats.py:222: UserWarning: For one or more samples the posterior variance of the\n",
      "        log predictive densities exceeds 0.4. This could be indication of\n",
      "        WAIC starting to fail see http://arxiv.org/abs/1507.04544 for details\n",
      "        \n",
      "  \"\"\")\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "WAIC_r(WAIC=84.092688492420706, WAIC_se=12.194906568168383, p_WAIC=7.0510128813693722)"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pm.waic(trace1c, m1c)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Sampling from multiple different centered models\n",
    "\n",
    "**(A)** Our complete model\n",
    "\n",
    "**(B)** A model with no interaction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Auto-assigning NUTS sampler...\n",
      "Initializing NUTS using jitter+adapt_diag...\n",
      "Multiprocess sampling (2 chains in 2 jobs)\n",
      "NUTS: [alpha, betac, betap]\n",
      "100%|██████████| 6000/6000 [00:07<00:00, 795.67it/s]\n"
     ]
    }
   ],
   "source": [
    "with pm.Model() as m2c_nopc:\n",
    "    betap = pm.Normal(\"betap\", 0, 1)\n",
    "    betac = pm.Normal(\"betac\", 0, 1)\n",
    "    alpha = pm.Normal(\"alpha\", 0, 100)\n",
    "    loglam = alpha + betap*df.logpop_c + betac*df.clevel\n",
    "    y = pm.Poisson(\"ntools\", mu=t.exp(loglam), observed=df.total_tools)\n",
    "    trace2c_nopc = pm.sample(5000, tune=1000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**(C)** A model with no contact term"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Auto-assigning NUTS sampler...\n",
      "Initializing NUTS using jitter+adapt_diag...\n",
      "Multiprocess sampling (2 chains in 2 jobs)\n",
      "NUTS: [alpha, betap]\n",
      "100%|██████████| 6000/6000 [00:04<00:00, 1270.55it/s]\n"
     ]
    }
   ],
   "source": [
    "with pm.Model() as m2c_onlyp:\n",
    "    betap = pm.Normal(\"betap\", 0, 1)\n",
    "    alpha = pm.Normal(\"alpha\", 0, 100)\n",
    "    loglam = alpha + betap*df.logpop_c\n",
    "    y = pm.Poisson(\"ntools\", mu=t.exp(loglam), observed=df.total_tools)\n",
    "    trace2c_onlyp = pm.sample(5000, tune=1000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**(D)** A model with only the contact term"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Auto-assigning NUTS sampler...\n",
      "Initializing NUTS using jitter+adapt_diag...\n",
      "Multiprocess sampling (2 chains in 2 jobs)\n",
      "NUTS: [alpha, betac]\n",
      "100%|██████████| 6000/6000 [00:06<00:00, 968.85it/s]\n"
     ]
    }
   ],
   "source": [
    "with pm.Model() as m2c_onlyc:\n",
    "    betac = pm.Normal(\"betac\", 0, 1)\n",
    "    alpha = pm.Normal(\"alpha\", 0, 100)\n",
    "    loglam = alpha +  betac*df.clevel\n",
    "    y = pm.Poisson(\"ntools\", mu=t.exp(loglam), observed=df.total_tools)\n",
    "    trace2c_onlyc = pm.sample(5000, tune=1000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**(E)** A model with only the intercept."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Auto-assigning NUTS sampler...\n",
      "Initializing NUTS using jitter+adapt_diag...\n",
      "Multiprocess sampling (2 chains in 2 jobs)\n",
      "NUTS: [alpha]\n",
      "100%|██████████| 6000/6000 [00:03<00:00, 1904.33it/s]\n"
     ]
    }
   ],
   "source": [
    "with pm.Model() as m2c_onlyic:\n",
    "    alpha = pm.Normal(\"alpha\", 0, 100)\n",
    "    loglam = alpha\n",
    "    y = pm.Poisson(\"ntools\", mu=t.exp(loglam), observed=df.total_tools)\n",
    "    trace2c_onlyic = pm.sample(5000, tune=1000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We create a dictionary from these models and their traces, so that we can track the names as well"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "modeldict=dict(m1c=(m1c, trace1c), m2c_nopc = (m2c_nopc, trace2c_nopc),\n",
    "              m2c_onlyp=(m2c_onlyp, trace2c_onlyp),\n",
    "              m2c_onlyc=(m2c_onlyc, trace2c_onlyc),\n",
    "              m2c_onlyic=(m2c_onlyic, trace2c_onlyic))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "names, models, traces=zip(*[(a, b, c) for a, (b, c) in modeldict.items()])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Comparing the models using WAIC\n",
    "\n",
    "Finally we use `pm.compare` to create a dataframe of comparisions, and do some pandas stuff to label the rows."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>WAIC</th>\n",
       "      <th>pWAIC</th>\n",
       "      <th>dWAIC</th>\n",
       "      <th>weight</th>\n",
       "      <th>SE</th>\n",
       "      <th>dSE</th>\n",
       "      <th>warning</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>79.06</td>\n",
       "      <td>4.24</td>\n",
       "      <td>0</td>\n",
       "      <td>0.87</td>\n",
       "      <td>11.06</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>84.09</td>\n",
       "      <td>7.05</td>\n",
       "      <td>5.04</td>\n",
       "      <td>0.07</td>\n",
       "      <td>12.19</td>\n",
       "      <td>3.77</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>84.43</td>\n",
       "      <td>3.75</td>\n",
       "      <td>5.37</td>\n",
       "      <td>0.06</td>\n",
       "      <td>8.94</td>\n",
       "      <td>7.93</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>141.65</td>\n",
       "      <td>8.38</td>\n",
       "      <td>62.6</td>\n",
       "      <td>0</td>\n",
       "      <td>31.7</td>\n",
       "      <td>32.84</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>150.44</td>\n",
       "      <td>16.94</td>\n",
       "      <td>71.38</td>\n",
       "      <td>0</td>\n",
       "      <td>44.67</td>\n",
       "      <td>44.44</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     WAIC  pWAIC  dWAIC weight     SE    dSE warning\n",
       "1   79.06   4.24      0   0.87  11.06      0       1\n",
       "0   84.09   7.05   5.04   0.07  12.19   3.77       1\n",
       "2   84.43   3.75   5.37   0.06   8.94   7.93       1\n",
       "4  141.65   8.38   62.6      0   31.7  32.84       1\n",
       "3  150.44  16.94  71.38      0  44.67  44.44       1"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "comparedf = pm.compare(traces, models, method=\"pseudo-BMA\")\n",
    "comparedf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>WAIC</th>\n",
       "      <th>pWAIC</th>\n",
       "      <th>dWAIC</th>\n",
       "      <th>weight</th>\n",
       "      <th>SE</th>\n",
       "      <th>dSE</th>\n",
       "      <th>warning</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>m2c_nopc</th>\n",
       "      <td>79.06</td>\n",
       "      <td>4.24</td>\n",
       "      <td>0</td>\n",
       "      <td>0.87</td>\n",
       "      <td>11.06</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>m1c</th>\n",
       "      <td>84.09</td>\n",
       "      <td>7.05</td>\n",
       "      <td>5.04</td>\n",
       "      <td>0.07</td>\n",
       "      <td>12.19</td>\n",
       "      <td>3.77</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>m2c_onlyp</th>\n",
       "      <td>84.43</td>\n",
       "      <td>3.75</td>\n",
       "      <td>5.37</td>\n",
       "      <td>0.06</td>\n",
       "      <td>8.94</td>\n",
       "      <td>7.93</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>m2c_onlyic</th>\n",
       "      <td>141.65</td>\n",
       "      <td>8.38</td>\n",
       "      <td>62.6</td>\n",
       "      <td>0</td>\n",
       "      <td>31.7</td>\n",
       "      <td>32.84</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>m2c_onlyc</th>\n",
       "      <td>150.44</td>\n",
       "      <td>16.94</td>\n",
       "      <td>71.38</td>\n",
       "      <td>0</td>\n",
       "      <td>44.67</td>\n",
       "      <td>44.44</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              WAIC  pWAIC  dWAIC weight     SE    dSE warning\n",
       "name                                                         \n",
       "m2c_nopc     79.06   4.24      0   0.87  11.06      0       1\n",
       "m1c          84.09   7.05   5.04   0.07  12.19   3.77       1\n",
       "m2c_onlyp    84.43   3.75   5.37   0.06   8.94   7.93       1\n",
       "m2c_onlyic  141.65   8.38   62.6      0   31.7  32.84       1\n",
       "m2c_onlyc   150.44  16.94  71.38      0  44.67  44.44       1"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp=comparedf.sort_index()\n",
    "temp['name']=names\n",
    "comparedf = temp.sort_values('WAIC').set_index('name')\n",
    "comparedf"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From McElreath, here is how to read this table:\n",
    "\n",
    ">(1)\tWAIC is obviously WAIC for each model. Smaller WAIC indicates better estimated out-of-sample deviance.\n",
    "\n",
    ">(2)\tpWAIC is the estimated effective number of parameters. This provides a clue as to how flexible each model is in fitting the sample.\n",
    "\n",
    ">(3)\tdWAIC is the difference between each WAIC and the lowest WAIC. Since only relative deviance matters, this column shows the differences in relative fashion.\n",
    "\n",
    ">(4)\tweight is the AKAIKE WEIGHT for each model. These values are transformed information criterion values. I'll explain them below.\n",
    "\n",
    ">(5)\tSE is the standard error of the WAIC estimate. WAIC is an estimate, and provided the sample size N is large enough, its uncertainty will be well approximated by its standard error. So this SE value isn't necessarily very precise, but it does provide a check against overconfidence in differences between WAIC values.\n",
    "\n",
    ">(6)\tdSE is the standard error of the difference in WAIC between each model and the top-ranked model. So it is missing for the top model. \n",
    "\n",
    ">The weight for a model i in a set of m models is given by:\n",
    "\n",
    "$$w_i = \\frac{exp(-\\frac{1}{2}dWAIC_i)}{\\sum_j exp(-\\frac{1}{2}dWAIC_j)}$$\n",
    "\n",
    ">The Akaike weight formula might look rather odd, but really all it is doing is putting WAIC on a probability scale, so it just undoes the multiplication by −2 and then exponentiates to reverse the log transformation. Then it standardizes by dividing by the total. So each weight will be a number from 0 to 1, and the weights together always sum to 1. Now larger values are better.\n",
    "\n",
    ">But what do these weights mean? \n",
    "\n",
    ">Akaike's interpretation:\n",
    "\n",
    ">A model's weight is an estimate of the probability that the model will make the best predictions on new data, conditional on the set of models considered...the Akaike weights are analogous to posterior probabilities of models, conditional on expected future data.\n",
    "\n",
    ">So you can heuristically read each weight as an estimated probability that each model will perform best on future data. In simulation at least, interpreting weights in this way turns out to be appropriate. (McElreath 199-200)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can make visual comparison plots in the style of McElreath's book. We can see that all the weight is in the no-interaction, full, and only log(population) models."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1141f93c8>"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x113e876d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pm.compareplot(comparedf)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Comparing for non-centered models\n",
    "\n",
    "We can redo the coparison for non-centered models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Auto-assigning NUTS sampler...\n",
      "Initializing NUTS using jitter+adapt_diag...\n",
      "Multiprocess sampling (2 chains in 2 jobs)\n",
      "NUTS: [alpha, betapc, betac, betap]\n",
      "100%|██████████| 12000/12000 [01:23<00:00, 143.29it/s]\n"
     ]
    }
   ],
   "source": [
    "with pm.Model() as m1:\n",
    "    betap = pm.Normal(\"betap\", 0, 1)\n",
    "    betac = pm.Normal(\"betac\", 0, 1)\n",
    "    betapc = pm.Normal(\"betapc\", 0, 1)\n",
    "    alpha = pm.Normal(\"alpha\", 0, 100)\n",
    "    loglam = alpha + betap*df.logpop + betac*df.clevel + betapc*df.clevel*df.logpop\n",
    "    y = pm.Poisson(\"ntools\", mu=t.exp(loglam), observed=df.total_tools)\n",
    "    trace1 = pm.sample(10000, tune=2000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Auto-assigning NUTS sampler...\n",
      "Initializing NUTS using jitter+adapt_diag...\n",
      "Multiprocess sampling (2 chains in 2 jobs)\n",
      "NUTS: [alpha, betap]\n",
      "100%|██████████| 12000/12000 [00:26<00:00, 445.51it/s]\n",
      "The acceptance probability does not match the target. It is 0.893725363713, but should be close to 0.8. Try to increase the number of tuning steps.\n",
      "The number of effective samples is smaller than 25% for some parameters.\n"
     ]
    }
   ],
   "source": [
    "with pm.Model() as m2_onlyp:\n",
    "    betap = pm.Normal(\"betap\", 0, 1)\n",
    "    alpha = pm.Normal(\"alpha\", 0, 100)\n",
    "    loglam = alpha + betap*df.logpop\n",
    "    y = pm.Poisson(\"ntools\", mu=t.exp(loglam), observed=df.total_tools)\n",
    "    trace2_onlyp = pm.sample(10000, tune=2000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Auto-assigning NUTS sampler...\n",
      "Initializing NUTS using jitter+adapt_diag...\n",
      "Multiprocess sampling (2 chains in 2 jobs)\n",
      "NUTS: [alpha, betac, betap]\n",
      "100%|██████████| 12000/12000 [00:47<00:00, 251.99it/s]\n",
      "The number of effective samples is smaller than 25% for some parameters.\n"
     ]
    }
   ],
   "source": [
    "with pm.Model() as m2_nopc:\n",
    "    betap = pm.Normal(\"betap\", 0, 1)\n",
    "    betac = pm.Normal(\"betac\", 0, 1)\n",
    "    alpha = pm.Normal(\"alpha\", 0, 100)\n",
    "    loglam = alpha + betap*df.logpop + betac*df.clevel\n",
    "    y = pm.Poisson(\"ntools\", mu=t.exp(loglam), observed=df.total_tools)\n",
    "    trace2_nopc = pm.sample(10000, tune=2000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "modeldict2=dict(m1=(m1, trace1), m2_nopc = (m2_nopc, trace2_nopc),\n",
    "              m2_onlyp=(m2_onlyp, trace2_onlyp),\n",
    "              m2_onlyc=(m2c_onlyc, trace2c_onlyc),\n",
    "              m2_onlyic=(m2c_onlyic, trace2c_onlyic))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "names2, models2, traces2=zip(*[(a, b, c) for a, (b, c) in modeldict2.items()])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>WAIC</th>\n",
       "      <th>pWAIC</th>\n",
       "      <th>dWAIC</th>\n",
       "      <th>weight</th>\n",
       "      <th>SE</th>\n",
       "      <th>dSE</th>\n",
       "      <th>warning</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>m2_nopc</th>\n",
       "      <td>78.95</td>\n",
       "      <td>4.17</td>\n",
       "      <td>0</td>\n",
       "      <td>0.61</td>\n",
       "      <td>11.12</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>m1</th>\n",
       "      <td>80.05</td>\n",
       "      <td>4.83</td>\n",
       "      <td>1.1</td>\n",
       "      <td>0.35</td>\n",
       "      <td>11.24</td>\n",
       "      <td>1.25</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>m2_onlyp</th>\n",
       "      <td>84.39</td>\n",
       "      <td>3.73</td>\n",
       "      <td>5.44</td>\n",
       "      <td>0.04</td>\n",
       "      <td>8.94</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>m2_onlyic</th>\n",
       "      <td>141.65</td>\n",
       "      <td>8.38</td>\n",
       "      <td>62.7</td>\n",
       "      <td>0</td>\n",
       "      <td>31.7</td>\n",
       "      <td>32.89</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>m2_onlyc</th>\n",
       "      <td>150.44</td>\n",
       "      <td>16.94</td>\n",
       "      <td>71.48</td>\n",
       "      <td>0</td>\n",
       "      <td>44.67</td>\n",
       "      <td>44.48</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             WAIC  pWAIC  dWAIC weight     SE    dSE warning\n",
       "name                                                        \n",
       "m2_nopc     78.95   4.17      0   0.61  11.12      0       1\n",
       "m1          80.05   4.83    1.1   0.35  11.24   1.25       1\n",
       "m2_onlyp    84.39   3.73   5.44   0.04   8.94      8       1\n",
       "m2_onlyic  141.65   8.38   62.7      0   31.7  32.89       1\n",
       "m2_onlyc   150.44  16.94  71.48      0  44.67  44.48       1"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "comparedf2 = pm.compare(traces2, models2, method=\"pseudo-BMA\")\n",
    "temp=comparedf2.sort_index()\n",
    "temp['name']=names2\n",
    "comparedf2 = temp.sort_values('WAIC').set_index('name')\n",
    "comparedf2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What we find now is that the full-model has much more weight."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x116788f28>"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x116658a20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pm.compareplot(comparedf2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In either the centered or non-centered case, our top model excludes the interaction, but the second top model includes it. In the centered case, the non-interacting model has most of the weight, while in the non-centered model, the weights were more equally shared.\n",
    "\n",
    "In a situation where the interaction model has so much weight, we can say its probably overfit. So in a sense, centering even helps us with our overfitting issues by clearly preferring the sans-interaction model, as it removes correlation and thus spurious weight being borrowed."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Computing the (counterfactual) posterior predictive for checking\n",
    "\n",
    "We now write some code to compute the posterior predictive at artbitrary points without having to use theano shared vaiables and sample_ppc, in two different counterfactual situations of low contact and high contact. Since some of our models omit certain terms, we use traces with 0s in them to construct a general function to do this."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def trace_or_zero(trace, name):\n",
    "    if name in trace.varnames:\n",
    "        return trace[name]\n",
    "    else:\n",
    "        return np.zeros(2*len(trace))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5000, 10000)"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# why the 2 above? see output below\n",
    "len(trace1c), len(trace1c['alpha'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from scipy.stats import poisson\n",
    "def compute_pp(lpgrid, trace, contact=0):\n",
    "    alphatrace = trace_or_zero(trace, 'alpha')\n",
    "    betaptrace = trace_or_zero(trace, 'betap')\n",
    "    betactrace = trace_or_zero(trace, 'betac')\n",
    "    betapctrace = trace_or_zero(trace, 'betapc')\n",
    "    tl=2*len(trace)\n",
    "    gl=lpgrid.shape[0]\n",
    "    lam = np.empty((gl, tl))\n",
    "    lpgrid_c = lpgrid - lpgrid.mean()\n",
    "    for i, v in enumerate(lpgrid):\n",
    "        temp = alphatrace + betaptrace*lpgrid_c[i] + betactrace*contact + betapctrace*contact*lpgrid_c[i]\n",
    "        lam[i,:] = poisson.rvs(np.exp(temp))\n",
    "    return lam"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We compute the posterior predictive in the counterfactual cases: remember what we are doing here is turning on and off a feature."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [],
   "source": [
    "lpgrid = np.linspace(6,13,30)\n",
    "pplow = compute_pp(lpgrid, trace1c)\n",
    "pphigh = compute_pp(lpgrid, trace1c, contact=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We compute the medians and the hpds, and plot these against the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [],
   "source": [
    "pplowmed = np.median(pplow, axis=1)\n",
    "pplowhpd = pm.stats.hpd(pplow.T)\n",
    "pphighmed = np.median(pphigh, axis=1)\n",
    "pphighhpd = pm.stats.hpd(pphigh.T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11360dfd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "with sns.plotting_context('poster'):\n",
    "    plt.plot(df[df['clevel']==1].logpop, df[df['clevel']==1].total_tools,'.', color=\"g\")\n",
    "    plt.plot(df[df['clevel']==0].logpop, df[df['clevel']==0].total_tools,'.', color=\"r\")\n",
    "    plt.plot(lpgrid, pphighmed, color=\"g\", label=\"c=1\")\n",
    "    plt.fill_between(lpgrid, pphighhpd[:,0], pphighhpd[:,1], color=\"g\", alpha=0.2)\n",
    "    plt.plot(lpgrid, pplowmed, color=\"r\", label=\"c=0\")\n",
    "    plt.fill_between(lpgrid, pplowhpd[:,0], pplowhpd[:,1], color=\"r\", alpha=0.2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is for the full centered model. The high contact predictive and data is in green. We undertake this exercise as a prelude to ensembling the models with high Akaike weights"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Ensembling\n",
    "\n",
    "Ensembles are a good way to combine models where one model may be good at something and the other at something else. Ensembles also help with overfitting if the variance cancels out between the ensemble members: they would all probably overfit in slightly different ways. Lets write a function to do our ensembling for us."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def ensemble(grid, modeldict, comparedf, modelnames, contact=0):\n",
    "    accum_pp=0\n",
    "    accum_weight=0\n",
    "    for m in modelnames:\n",
    "        weight = comparedf.loc[m]['weight']\n",
    "        pp = compute_pp(grid, modeldict[m][1], contact)\n",
    "        print(m, weight, np.median(pp))\n",
    "        accum_pp += pp*weight\n",
    "        accum_weight +=weight\n",
    "    return accum_pp/accum_weight\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "m1c 0.07 28.0\n",
      "m2c_nopc 0.87 28.0\n",
      "m2c_onlyp 0.06 33.0\n"
     ]
    }
   ],
   "source": [
    "ens_pp_low = ensemble(lpgrid, modeldict, comparedf, ['m1c', 'm2c_nopc', 'm2c_onlyp'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "m1c 0.07 37.0\n",
      "m2c_nopc 0.87 37.0\n",
      "m2c_onlyp 0.06 32.0\n"
     ]
    }
   ],
   "source": [
    "ens_pp_high = ensemble(lpgrid, modeldict, comparedf, ['m1c', 'm2c_nopc', 'm2c_onlyp'], contact=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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FMpnE79b6/Jl4s/ZNlry8hFAsBMBE30R+ccIvOGS3Q9Jqz93ShremXqF/hCn4i4iIyJjXEe6gvLUcn8uHx6UNoNJl2zZ/XPNH7n73biy7fyumeZPmccfn72CPiXvs4urtc7e246uuU+gfBQr+IiIiMqZVdlbS2NOop/wZiiai3PzGzTxd8XSq9uk9Ps1Pjv0Jxd7itNp0tXXiq6zBDuhnMxoU/EVERGRMSlpJ1rWuIxQLKfRnqK2vjSteuII1LWtStbMOOosLP3EhLqcrrTadHUH8ldUK/aNIwV9ERETGnFgyxorGFThwaKnODJW1lnH5C5fT0tsCgNfl5brPXMfJ809Ou01nZxeBjdXYfoX+0aTgLyIiImNKT7SH1c2r8bl8aS0pKR94duOz3PTaTalNuaYXTee2z9/G/tP3T7tNZ1c3gYoqjenPAQV/ERERGTOaQ81saN9Akaco110paJZtcf979/Oblb9J1fafvj+3nXAb0ydMT7tdZ3cPfrNSoT9HFPxFRERkTKjqrKK+p16hP0OhWIjrXrmO12teT9VOmX8KS45ektZOvFs4Q70EyjdqTH8OKfiLiIhIQbNtm/K2coKRIAG3NuXKRF13HZc+dymVwUoAHDi4+LCL+daB38po2JSjt4/AugqF/hxT8BcREZGClbASrGpaRTwZ1yTeDL1b/y5Xv3Q13dFuACZ4JvDTY3/Kp+d+OqN2HX1hitZtwA7o55NrCv4iIiJSkMLxMKuaVuFyurQpVwZs2+bPZX/mjrfuIGknAdijdA/u+PwdzJs8L6O2HeFIf+jXmP68oOAvIiIiBacz3Mm61nX4XX6t3JOBeDLOrctu5e/r/56qfWrOp/jZcT+j1FeaUduOSJTAWhPb5820m5IlCv4iIiJSUBq6G6gKVmk8f4Y6w51c+eKVrGhakap97YCv8f1PfR+3M7OI2B/614NXn8TkEwV/ERERKRgb2zfS3NusnXgztKF9A5c9fxmNoUYA3E4313z6Gk4zTsu4bUcs3h/6PR7QpzGryTopAAAgAElEQVR5RcFfRERE8p5lW6xrWUcoFlLoz9BLVS9x/avXE0lEAJgSmMKtx9/KwbMOzrzxeILAmnKF/jyl4C8iIiJ5LZ6Ms7JpJZZt4XVpvHi6LNvi4fcf5sH3H0zV9p26L3d8/g5mFc/K/AXiCYrWrAe3W6E/Tyn4i4iISN4KxUKsbl6N1+nNeNz5eBaOh7n+P9fzctXLqdrx847n+s9eT8CThbkSiQRFa8rB6VToz2P6FyQiIiJ5qa23jfXt6zWJN0NVnVVc8/I1bOzYmKotOnQR3/n4d7KzItKWJ/1OZ/+X5C0FfxEREck7NcEaartrFfozYNs2LzW8xCOvPEI0GQUg4A5w4+du5Jh5x2TlNdxNrfhq6rG9nhEJ/Y5YHGdfH1ZRUf9rSEYU/EVERCRv2LaN2WbSGenUJN4MdEe7uX3N7bzT8k6qNrd0LrccfwsfmfqRjNt3RKL4N1bhiERHZHOuQHkFU/7xHCXL3sORSGK7XXQf+Qk6Tj+JyIL5WX+98ULBX0RERPJC0kqyunk1sWRMk3gzsKJxBde+ci3Nvc2p2qn7nsoVR15Bkacos8ZtG099E976pv7A783+z2nSMy8z695HcFh2quZIJJn42juUvvEuTRedTfCUY7P+uuOBgr+IiIjkXCQeYWXzSpw4NYk3TQkrwa9W/IpfrfgVlm0BEHAFuO6z1/H5fT6fcfuOvjCBiipIJLADI/NpTKC84kOhf6s+WDaz7n2EyLy5evKfBv3LEhERkZzqCHdQ3lqOz+XLzmTTcaixp5FrX7mWVc2rUrV9J+7L9w/4Pp/a51OZNW7beGsb8DS29Ad+z8iNtZ/yj+d2GPq3cFg2U/7xLA0Lvjdi/RirFPxFREQkJ2zbprKzkqZQk8bzZ+DFyhf5yes/IRQLAeB0OPn2wd/m+MnH43K6MmrbGerFv6EKbHvEnvJv4YjFKVn23pDOLV32Ho2xuCb8DpOCv4iIiIy6WDLG6ubVJKyEQn+awvEwt711G0+aT6ZqMyfM5KZjbuKQ3Q6hqqoq/cYtC29VLZ7WDuyi0fn5OPv6cCSSQzrXkUji7AuTVPAfFgV/ERERGVWtva2Y7SZ+lx+PU8EtHevb1rPk5SVs7tqcqh2z1zFce/S1TPRPzKhtZ1c3/o2bwcGohX6gf8lOt2tI4d92u7CKtNTrcCn4i4iIyKiwbIsN7RtoCbVkZ7fYcci2bf609k/c8+49xK04AD6Xj0uPuJQz9jsjszkSySS+yhrcnV0jskTnrtheDz1HfoLS197Z5bndR35Cw3zSoOAvIiIiIy6SiFDRVcHckrkK/WnqCHdww39uYFntslRt/pT53Hzszew9ee+M2na1deKrrgWXKyehf4v200+i5I13dzrB13Y66Dj9pFHs1dih4C8iIiIjqinUxLrOdficPjwuPaVNx9t1b3P9q9fTHm5P1b66/1dZfNhifO4Mgno8gX9jNa7unhGfvDsUkQXzabro7B0u6Wk7HTR975z8W8ozmWTK359l3t/+Te+ee8CXzx2RnYwzpeAvIiIiI8KyLcpbywlGgvhduQ+VhSiejHPfe/fx+9W/T9Um+iZy/Wev5zN7fiajtt0tbfiq67C9nrwI/VsETzmWyLy5TPnHs5QO3rn3qE/ScdqJeRf6fVU17Hbnw/17HAD+zi5oaYFZs3Lcsw9T8BcREZGs6431srZlLYBW7UlTTVcNS15eQnlbeap22OzD+PHnfsz0CdPTbtcRi+OvqMQRDud0WM/ORBbMp2HB92iMxXH2hbGKAnk3pt8RizP1saeY9ud/4kh+MCF58xdPZs88DP2g4C8iIiJZVtddR3WwmoBbY/nTYds2/6r4F7e+eSvhRBgAl8PFBZ+4gDMPOhOnI/0hJO6GZrx1jeDzgjc/Q/9gtteTl0t2Bsor2O3Oh/HVNqRq0TmzWPON/yF06KHsmcO+7YyCv4iIiGRF0kpS1lpGT7RHoT9NoViIm9+4mec3PZ+qzSmZw0+P/SkHzDgg7XYdfWH8G6txxOKQp0/5C4EjHGHGb//C5Keex2H3z0GwnU7av3QKbd/4IsG21rwO1/ncNxERESkQPdEe1rWuw4kzs8mm49jq5tVc98p11PfUp2onzz+Zq466imJvcXqNWhbeqho8re3YPh/k4dPzQjHh/TXMuvvXeJvbUrXI3nvS+INziczfK3cdGwYFfxEREclIdbCauq46LdOZpoSV4Ncrfs2vVvyKpN0/VrzIU8TVR13NKR85Je12PcEeiusacc+Zje3XPIt0OXt6mfnQo0x64bVUzXK7afvGF2n/8ingLpw4XTg9FRERkbySsBKsbVlLX7xPoT9Ndd11/OiVH7G6ZXWqtv/0/fnpsT9l99Ld02t0YInOkpp6LK+noIJpvil587/Muve3uDu7UrW+j36ExkvOJbbH7Bz2LD36TRAREZFhC4aDlLWW4XF58Lk0tGe4bNvmmY3PcOubt9Ib7wXA6XByzsHn8N1DvovbmUZEs208A5N3bZ+3P/RLWlwdQWbd9ztK3/xvqmb5fbSc81U6v3DcDtfoj1kxpnhKRqubw6bgLyIiIkNm2zZVwSoauhv0lD9NPdEefvbmz7aawDureBY3fe4mPr7bx9Nq09HbR2BjNcQTebUmf8GxbSa++DozH3wUV6g3VQ4d+jEaL/42iZnTtntZ0kpi2zbzSvfG45s4Wr0dNgV/ERERGZJYMsaa5jXErbhCf5reb3yfH736I5pCTanaifucyNVHXU2JL40nxckk3uo6PG0d/YFfT/nT5mluZdYvf03xirWpWrJ4As3nf5Ou444Ch2O718WSMYo8E9h78jxqwjUkt3tWflDwFxERkZ1KWkmqOqto6m3C7/LjcSpcDlfCSvDA8gd4ZOUj2PQvAznBM4GrjrqKk+efjGMHoXJnXG2d+KprweXUU/5MJC0m/+sFZjzyBM5INFXuPvowmi44k+TkHT/BjyajzJgwg9klhTHeX8FfREREtsuyLWq7aqnrrsPtdGtt/jTVdNVw7SvXUtZalqodOPNAbvrcTcwpnTPs9vp33q3C2duXtzvvFgpvTT273fUwReUbU7XE5Ik0XXQ2PUd9YofX2bZNzIqxz6R9KPHn75j+bSn4i4iIyFZs26Yp1ER1sBoAv1tPk9Nh2zZPmk9y+1u3b7UD77mHnMs5B58z/Am8to2nvglPQzP4vAr9mUgkmPrEv5j26JM4E4lUOXjiZ2n+ztewSibs+NJkApfLxf7T98fjKqxPvxT8RUREJKW9r51NHZuI23H8LgX+dAUjQX76+k95pfqVVG1OyRxuOuYmDpx54LDbc4Z68VdUg5XUzrsZ8ldUsdudD+Gvqk3VYrOm07j42/R9fOe7I0eTUSb7JzN34ty0hmflmoK/iIiI0BPtYUP7BiKJCH63HxeuXHepYL1b/y7Xv3o9rX2tqdrCjyzkiiOvGP4OvMkk3qpaPO1B7IAPXNtfRlKGIJFg2uNPMe3RJ3FYFgC2w0HH6SfSeuaXdrnJWSQRYe7EuUwtmjoavR0RCv4iIiLjWDgepqK9gu5YNwF3QMN6MhBLxrj/vfv5w+o/pCbwFnuLuebT13DiPicOuz1XWwe+qjpwO/tDv6TNW9vA7NseILChMlWLzp1DwyXnElkwf6fXblmqc79pCwh4Cvvfh4K/iIjIOBRPxqlor6Aj3IHf7dfE3QxVdVZx7SvXYrabqdohsw7hxmNuZFbxrGG15YhE8W+qxtEXAZ83210dXyyLyf98gRm/fhxnLA6A7XTQ/uWFtH3jDOxdLH86eKlOl7PwPwVT8BcRERlHBi/N6XP5tB5/hmzb5q/lf+XOt+8kmuxfCtLlcLHoE4s488AzhxcWEwm8m+vxtHdi+7wK/Rlyt7Qx+46HmLDqg9WUYrNm0HD5+YT333eX1xfaUp1DoeAvIiIyDti23b80Z08dLodLT/izoDPcyY2v3cjrNa+nanNL53LTsTex//T9h96QZeGpb8Lb2ILtcWu1nkzZNqUvv8ms+36Hqy+cKneecizN535tl3seWLZF3IoX3FKdQ6HgLyIiMobZtk1zbzObg5uxbAufS6EyG5bVLuPH//kx7eH2VO004zQuO+IyijxFQ2vEtnE3tuBtaAanQ4E/C1zBbmb9v99Q+uZ7qVp8yiQaLzmX3k8etMvrP1iq8wA8rrEXk8fedyQiIiJA/9KclcFKYsmYlubMkt5YL//vv/+PJ8qeSNVKfaUsOXoJx807bsjtuFrb8dU2gm3BLsaZy9AUv/0+u/3yV7iD3ala92c+RdNFZ5Es3fWT+0JfqnMoFPxFRETGmJ5oDxUdFYTjYfxuv0J/lry2+TVuefMWmnubU7VPzv4kN3z2BmYWzxxSG87OLvzVdZBMgNcLWjY1Y87eMDMf/AOTnn8tVUsWF9F00dl0f+6IIbURSUaZW7pHQS/VORQK/iIiImOEZVts6thEc6iZgEdLc2ZLW18bty27jRerXkzVvC4viw5dxDcP/CZOx67X1neGevFV1eAMR/uH9Lg0cTcbilaXs9sdD+JtbkvVQod8jMYfnEti2pRdXp+0ktjAflP3K/ilOodCwV9ERGQMCMVClLWUYWNrpZ4ssW2bJ80n+eU7v6Qn1pOqH7rbofzw0z9kz0l77rINR18YX3Udrp4QdsCvcfxZ4ojFmP7bvzDl78/isPv3TLB8XprP/RrBhcfBEIbqjLWlOodCwV9ERKSA2bZNdbCa+u56Bf4squmq4aev/5TljctTtRJvCd//1Pc5zThtl2PAHbE43qoa3MFubL9vlyvJyND5N1Yz+xdL8dXUp2p9+82n4fLzic/Z9Z4Jtm0TTUaZVTyL3Up2G8mu5h0FfxERkQIViUdY27qWeDKu0J8lCSvB71b9jodXPEwsGUvVT9j7BC474jKmFU3bRQOD1uL3ehT4symZZOqf/8n0P/4DRzIJgO120frNM2j/8kJw7fqpfSwZw+vyjoldeNOh4C8iIlKA6rrrqA5W43f58Wq8eFasbVnLT17/CRs7NqZqMyfM5KqjruIze35m5xcnk3jrm/A0tWJ7PBrSk2XeukZm3/YAAXNTqhbZa3caLl9EdJ9dD7nasjb/nOI5TC+ePpJdzWsK/iIiIgUknoxT1lpGb7xXm3BlSV+8j/vfu5/H1j6GTf94cQcOvvLRr3DhJy+k2Fu844ttG09DM57GFq3FPxIsi8lPv8SMXz2GM9r/CYztcNDxpZNp/daXsL27ftMbSUQp8RWz70RjTK7NPxzj+7sXEREpIC2hFio6KvC6vNqIK0veqHmDn7/5c5pCTana3pP35tqjr+XAmQfu+ELbxt3ajre2sf/vWos/69ytHex250MUr1ibqsVmTafhsvMJH2Ds8vpEMgHAPpP3ptRfOmL9LCRZDf6GYRwH3AwcCLQAjwA3mqaZNAzDAfwQOB+YBrwJXGya5vps9kFERGSsSVpJytvKCUaCesqfJR3hDm576zae3/R8quZxevjOx7/DWQedhce14yDvau/EW9uAI54An4ZZZZsjFmfyU88z7U9P4uoLp+qdJ32Olu9+Hato5/8GbNsmasWYFpjGnNLZQ1pudbzIWvA3DOMo4N/Ao8A1wKHATYAF/Bj4EXA1cBVQDVwLvGQYxkdN0+zKVj9ERETGkmA4SHlbOS6HS6E/C2zb5p8b/sld79xFd/SDHV4/PuvjLDl6CXtN2muH1zq7uvs334rF+wO/Qn922TYlb7zLjF8/jrepNVVOTJ5I4/e/Q+hTH99lE7FkDK/bx4Ip+2kfi+3I5hP/nwPPm6Z59sDfXzYMYypwjGEYdwCXAzeYpnk3gGEYrwObge8Ad2SxHyIiIgXPsi02dmykpbdFgT9L6rrruPn1m3m34d1UrdhbzOLDFnP6fqfv8Mmwoy+Mv3Izzr5I/xh+Bf6s86/fyMyHHqWorGKrevC4o2j57jdITizZ6fVJK0nCToz7ybu7kpXgbxjGdOAo4PTBddM0rx44fgJQDDw16FinYRj/AU5CwV9ERCQlFAuxrmUdgEJ/FiSsBH9Y/Qceev8hosloqn7MXsdw5ZFXMn3C9oOiIxzBV12HqzuEHfBp4u4IcDe3MeORPzPx1be2qvcdYND83a8T2XfvXbYRSUaZ6C1l7qS5uJ2avroz2bo7HwMcQK9hGP8ETgC6gfuAG4F9B87btM11lcBp6bxgeXl5ej3NUDgczunrj0e656NP93z06Z6Pvny857ZtU9dbR0u4Bb9rbA1TiEb7A3dVVdWovu6m7k3cX3Y/m0ObU7XJvsmca5zLYTMOI9QSIkRoq2sc8TjFdU14u0MkvZ4h7QKbj+LxOAD19fW7OHP0ucIR9vr3q8x9/g1ciUSq3jd9KhVfPpnWQ/bvv+876XvCTuDAweyiOTi8Dmq7akej6zsViUZJOp159f+VwbIV/Le8Vf4d/WP87wA+S/84/jDgBKKmaca2ua4H0DRrEREZ9yKJCBu7N5K0k2Mu9OdCOBHmz5V/5umap1NLdAJ8fvfP8/X5X2eCe8KHrnEkkhQ1NOPv7CLpcZPUkJ6scySTzH7jPfb+xwv4ej54wxUv8lP1heOoPfYIbPfO46kNxJJRpvinMjMwY5e7KMsHshX8t0x9f840zSsG/vsVwzCm0R/+fw6D/tVtzUrnBRcsWJDOZRnb8g4uV68/Humejz7d89Gnez768ume13XX0d7Zzrwp88ZsiNnypH/evHkj+jq2bfNy9cvc/t/baeltSdXnTZrHkqOXcPCsgz980ZbNt1pbsUsnweQpI9rH0bLlSf+cOXNy3JN+E5avZsZDj+Lf/MFTfNvlovMLx9P29dNIlpYwexdtxJIxfG4fe03aKy8n71ZVVZH0+5mfw/+vLF++fIfHshX8t7xle3ab+gvARUAQ8BmG4TFNMz7oeAmgFX1ERGRciifjrGtdR1+8j4BHY/kzVdtVyy+W/YJldctSNbfTzbcP/jZnH3z2h3c4tiw8Dc14G1uwXU6N4R8hvupaZjz8J4qXr9mq3nPEobR8+6vEdt9tl20krSRJO8mc0jlMK5o2Qj0d+7IV/Lfsbb3tZ2JbPgmI0z8HYB6wYdDxvQEzS30QEREpGE2hJjZ1bNJmXFkQTUT57arf8siqR4glPxhV/MnZn+Sqo6768BKdto27uQ1vfSMOG2wN6RkRrs4upv/+r0x67lUc1gcDPyL77Enzed+g78ChPRXX5N3sydbdKwPqga8AfxhUXwg0AI8Bv6R/1Z9bAQzDmEz/PIAfZ6kPIiIieS+WjFHWWkZfrC8vhyoUmrfr3uaWN2+htvuDiZ1TA1P5weE/4MR9TvzQ0ClXW0f/5ltJC7yeHY5DlvQ5ojGm/ONZpj7+T1zhSKoenzqZ1rO+QtdxR4Fz15tqRZJRvE4P8yfPp8RXPJJdHjeyEvxN07QMw/gh8FvDMO4H/gIcD5wFXGCaZrdhGPcANxmGYdH/1H8J/Sv/PJyNPoiIiOS72q5aarpq8Ll8+Nx6yp+Jlt4W7nz7Tl6ofCFVczqc/O9H/5dFn1hEsXfroOgMduGvrodEDLw+cLlGu8tjn2VR+p+3mfHIn/G0tH9Q9nlp/8oXaP/Sydj+nb/ZTVhJElacYm8J80v3UODPsqx9XmKa5u8Mw4gDPwTOAWqBRaZpPjhwyg/pn8h7Of1r+i8DztKuvSIiMtaF42HKWsuIJqN6yp+hhJXg8XWP88DyB+iL96XqB8w4gKuPupr9pu231fnOUC++qpr+zbcC/v7QL1kXWLeBmQ/9kYBZmarZDgddJxxN65lfJjF18k6vjyajuHAxuWgyMyfMwuPSkJ6RkNW7aprmn4A/7eBYArh64EtERGTMs22bqmAVDT0N+F1+jeXP0Mqmldzy5i1UdHywu2upr5TvffJ7H9p51xnqxVtdh6svjO339Yd+yTpPUwszfv04pa+/u1W996CP0vzdrxPdZ88dXmvZFrFkjIAnwJ6T9mKSb+KYXdUqX+jtlIiIyAjoifawvm09STup3XczFIwEufudu3lqw1Nb1U/d91QWH7aYyYEPniY7Q714N9fjCvViB/xaqWeEOMIRpj3+T6b87d844x8s2BjdfTdazv0aocMO3uHGZ/FkHAuLSf5JzC+er2Fvo0jBX0REJIss22JTxyaae5sJuANbPYWW4bFsi6fMp7jn3Xvoin4wMnifyftwzaev2WpNfkdfGF9V7QeBX0/4R4ZtU/rKMmb8+nE87Z2pcqK0mLZvnkHnycfAdjbgsm2baDKG1+1hVvEspk2Ypn8bOaDgLyIikiXBcJD17etx4NBT/gxtaN/Az9/4OatbVqdqAXeA8w89n/874P9Syzo6+sL4qutw9YQ0pGeE+TdUMnPp7ykq35iq2S4XHaceT9vXv4hV8uHdkBNWkoSdoMRbzJ6T9mSC98PnyOhR8BcREclQ0kpitpl0RDoU+DMUioV4YPkDPL7ucSzbStWPm3cclx5+KTOLZwKDA38vtt+rwD+CXB1BZjzyBJNeeG2reujQj9F83jeIzf3wzsCxZAynw8WUwGRmFs/U+vt5Qj8FERHJa9FElK5oFxN9E/NyLHBrbysV7RW4nW6F/gzYts2LlS9yx9t30NrXmqrvXro7Vx55JUfucSSwvcCff78TY0Y8wZQnn2Pao//Yaj3+2OyZNJ/3jQ+N498yWbfIU8Sek/Zkoibr5h0FfxERyUtv1b7FXe/cxd/L/07ciuNxejhjwRlccvglHL774bnuHvFknPK2cnqiPVqiM0Obg5u5ddmtvFP/TqrmcXo4++CzOeugs/C7/f2Bf3M9ru6QAv9Is22K313JjIcexVfflConA37avnYanaediO31pOqJZAILi8n+ycwqnoXXrZ2Q85WCv4iI5J0Hlz/IBU9fsNVQj7gV5/F1j/NE2RPcv/B+zjv0vJz1r6G7gapgFV6XV6E/A6FYiN+s/A2PrnmUuPXByjCHzzmcK4+6krkT5+IIR/BVbMTV1YMd8CnwjzBvbQMzH/gDxcvXbFUPnnA0LWf/L8kpk1I1y7aIWXGmF01jdslsTdYtAAr+IiKSV96qfetDoX8wy7a44OkLOHDmgaP+5D8Sj1DeVk44EVbgz0DCSvDX8r/y0PsPEYwEU/XpRdO57IjLOG7ecTgjUXzlG3F19/RP2i3S/R5JzlAv0x79B1OeegFHMpmq9+03n+ZF3yJi7L3V+ZFklBJPMftO3RePy7Ntc5KnFPxFRCSv3PXOXTsM/VtYtsVdb9/FY19+bFT6ZNs2NV011HbV4ndrI6502bbNq9Wvcvc7d1PTXZOqu51uvrr/VznvkPMoTrrwmptwd/VolZ7RkLSY9Px/mP7bJ3B39aTK8amTafn2V+n+3BHg/OBJfiwZw+Py8JEp8yn2Fueix5IBBX8REckb0USUv5f/fUjn/q38b0QT0RGf8Nsb66WstYyElSDg0eTddFV0VfD7it9THizfqn7cvOP43ie/x1zvdLyVdbi7urH9Wod/NATWmsxa+nv8mzanapbbTceXTqHtq6du9TNIWEls22J2yRymT5iWi+5KFij4i4hI3uiKdm011ntn4lac7mg3093Ts94P27Zp62ujtquWvngfAU8Ar0sTFtPR0NPAvf+9l+c2PbdV/WMzPsYlh1/CQVP3x1dVi7uzHNvnww7ozdVIc7e0MeNXjzHxtXe2qvcccSjN3/068d1mpGr9G29FmRaYxuzS2bicrtHurmSRgr+IiOSNib6JeJyeIYV/j9NDqa80q68fT8ap7a6lJdRCkiR+l19P+dPUE+3h1yt/zWNrH9vq5zmnZA4XH3Yxx+11LN6GZrzvr8X2eLD9esI/0hyRKFP/+jRTn3gaZzSWqkf2nEPz+d+k7+MHbHV+JBGl2DOB+VPma6WeMULBX0RE8obP7eOLC77In9f9eZfnnrHgjKwN8+mOdlPTVUMwHMTj8vR/oQmL6Ygn46mJu13RrlR9gnsCX573Zc4/+nwCwV58K8twWBa2X/MlRpxlUfraO8z4zeN4WtpT5WTxBFq/9SU6Fx4Lrg+e5MeTcZwOJ/Mn70OJvyQXPZYRouAvIiJ55QeH/4C/lP1lpxN8nQ4nlxx+SUavY9kWreFWeht6CcfDFHmK9HQ/A7Zt80r1K9zz7j3Udtem6lsm7h435TgmJr1MLNuEMxztn7iLho2MKNtm6toNzPvZ/VuN47edDjpPOZa2b32JZOkHwT5pJUnaSWYVz2LGhBnafGsMUvAXEZG8cvjuh3P/wvt3uKSn0+Fk6cKlaS/lGUlE2BzczMq2lTgdTvZlX4o8RZl2e1xb27KWO9++k1XNq7aqHz/veL532PfYvWgWba+/hberB8e8vfSUfxQE1m3g0Ad+z+SK6q3qvQcuoHnRN4nOm5uq9Y/jjzE5MIndS3fH7VQ8HKv0kxURkbxz3qHnceDMA7nr7bv42/9n706j47rPO89/71L7girsJLhLJATu4iKRlCiJWqw1kiwvcTyZxHYcp9NOJu45fU67u+f0THe/sM/MnDmemcTp7mRsJWnJsmRbkmNrsRbaEiWKEsGdIkFxEReQxF573XvrLvPiAiBLAClSxEo8n3N4dFT3FnBBEIVfPff5P/9DvxjeufcLS7/AX936V1cd+j3Po6/cx+nsaQpWQUZyjpHOXCd//cFf89rx16oeX9m0ku/c+h1WNq4g0Hme4OEDDJTKOKEgSBV5XIVOnKLhyedIvL+n6nFjwVx6/viLFG69uep7YDomYT1MW+1NsjfFDCDBXwghxJS0Yc4GnvniM5i2Sc7MkQwlr7qn33ZtTmVP0VPswXZtwnpYqvtjIGfm+NHuH/HTgz+tWrg7JzmHv7zlL7l7wd3ofRlCuw9e6ONXZVfX8RQ420XDP/2c5O/eQ/G84cdLDbUMfO3L5O7cCNqF70HFqaAoKgtSC0iFU6N9SHEdkuAvhBBiSgvpoase2f3qRIoAACAASURBVJk385zMnhxerKururQvjIGKU+G5D5/j73f/PTkzN/x4MpTkmzd/ky8t/RJB0yZ84DCKYUEoKH3840zvG6D+6RdIvfq7qh137XQNRx+6i87N65k9f/7w447rYHs2TbEmmuPN0sc/w8iroBBCiOuC67mcz5+ns9CJWfHbF2Sx7thwPZc3T7zJX3/w15zJnRl+PKAG+P1lv883bv4GSTVK6Ngp9IGsX+EPyfjH8aTmC9Q9+ytq//m1qtGcTjxK35ceof/R+zjTd2GCj+u5WI5FTaiGuTXzCGgSAWci+a4LIYSY1mzX5mTmJF3FLvD8OwQS+MeG53lsP7OdH+78IYd7D1cdu2/RfXx7/beZk2jx+/jPHvfn8cuOu+NKKRvUvvAqdT9/Ca1YGn7cDQXpf/x++r7wMG4iNvy47dl+4A/XsDi+WObxz3AS/IUQQkxLFafCicwJugvdBLSALNYdY3vO7+GHH/yQXed3VT2+qmkV37n1O6xoWoHWO1Ddxy/GjWJVSL28lfpnXkTPXGiz8nSNgQe30PuVx3BqL/Tqm46Ji0tduI7ljctlx10BSPAXQggxzViOxfGB4/QWewlqQanuj7EjfUf44Qc/ZNvpbVWPL0ov4l+u+5fcOf9O1LJBeP8h6eOfCI5LzZvvUP/ULwh29Q4/7CkKuS2b6PnDJ6jMagQutPNEA1EWphZSU64BkNAvhknwF0IIMS2UK2WODxxnwBggpEk7z1g7lT3Ff23/r7x67NWqx1sSLfzZ2j/j/hvuR3M8Qh+d8Pv4I2Hp4x9Pnkfi3XYa/vFnhE51Vh3Kb1hDzx99EXPhXABs18HxbGrCKW6I3zA8lrOf/gm/bDG1SfAXQggxpZWsEscGjpExMkT0CBFdAv9Y6i5283e7/o5fdvwSx7swFaYuUsc313yTx1sfJ1Q0CHacQMsX8ILSxz/eonsO0vjks0Q6jlc9XlxxEz1f/zLltsWAf/dLVTTqo3U0xhqlsi8+lQR/IYQQU1LezHN84Dh5My/z98dBxsjw5J4nee7D5zAdc/jxZCjJH638I36/9Qsk+wro+zpQrQpeJCx9/OMs8uER6v/7L4jvPlj1ePnGBfR87UsU16zAA0zbJBIIMz81n5pQjYzkFFdMgr8QQogpJWtkOT5wnGKl6Ff4paVnTBWtIk8feJr/vu+/U6wUhx8P62G+uvyr/PENT1DbXUDbfwx0DXQdLyKV5PEUOdBB/dPPjwj8ZkszPX/8RfK3rcfGw3EtksEkC9OLiATkrou4ehL8hRBCTAn9pX4+znxMqVIiEpCWnrFm2iY/O/Qzfrznx2SMzPDjuqrzhZue4Fstj9GcsVGPnscLBUGq++Musv8wDU89T2zvh1WPV+pr6fnDz5O9dzMmNhoeddFaGmONshHdVGbbKKaJ09Q02VdySfKvRwghxKTqLfXyceZjTFs23RoPtmvzqyO/4u92/Z2/18EgVVF5eOH9fLvhYeYbYbw+CwK6tPNMgOi+Q9Q/9TyxfYeqHq801NH75UfIfO4ODNUlrOnMT8whJe08U5ttg+NAczPlWAy0qXuHTIK/EEKICed5Hl3FLk5nT1NxKoT00PAkEjE2XM/ljeNv8Lftf8up7KmqY/fOup2/rH+YJUo9nhfCC0uoHHeeR3Tvh37gP9BRdajSWEfv7z9K9t7NlFWXRCjGgsQcaeeZ6ioVcF2YPRvmzvUD/6FDn/68SSTBXwghxITxPI+z+bOcyZ3B8RxCWoiQLhXmseR5Hu+eeZcffvBDOvqqA+bG9Cr+54ZHWR5bgBcM4k3SNc4onkd0z0Eannqe6MEjVYespnr6fv9RMvdupqJ6aKrGktQNxIKxS3wwMSVYFiiKH/jnzAFVnewrumIS/IUQQoy7ilPhdO40XQW/1SSoBdHlV9CY8jyP98++z9/v+nt2n99ddWxV/Eb+VcNj3FK/ElRVAv9E8Dxiuw5Q//TzRD/8qOqQ1dxA71ceJXvP7biaiuVUaI410xxvkpaeqcw0/ar+vHl+6J+G3yt51RVCCDFu8maek9mTZMoZglqQoCYbPo0113N5+9Tb/Gj3jzjYUz0VZnG4hb+a9QRbGtZLoJwonkesfT/1Tz1P9PDRqkPWrEZ6v/IY2bs3ga5j2CYJLcKSulYCmkSyKcswIBCAhQuhuXlaBv4h8q9MCCHEmHI9l65CF535TsqVsozkHCeO6/D6idf58Z4fc7S/OmDODTbwFy1P8FDDJjRl+rQhTGueR+yDvTQ8/fyIjbfMlmb6vvIY2S0bQdOwHRtchxvSi0iGk5N0weJTGQYEg7B4MTQ0TOvAP0SCvxBCiDFhORanMqfoKfUAfjuPbLo19ipOhZeOvsQ/7PkHTuWqF+3eEJrFn7Y8ykP1G9GVqTtZ5LriecTf30P9U88T+ehE1SGzpZnerz5O7s4NoGl4nodpmzTE6mlJtMhdmKnKMCAUgtZWqK+f7KsZUxL8hRBCXJOcmePjgY/JWTmCqrTzjBfDNnix40X+ad8/cb5wvupYW3gef9byKPfWrUeVCv/E8DziO3ZT//QLIwP/3Nn0/sFj5O7YAJr//TAdk4geYWltmyxon6rKZYhGYelSSKcn+2rGhQR/IYQQV831XM7nz9NZ6MSoGEQDUdlwa5wUrSI/P/Rzntr/FH3lvqpja6I38q2WR9mcXi3V44niuCS2t1P/zIuEj52sOmTOa/ED/+ZbhwO/7Tp4nsv8mvmkI9dnmJz2SiWIx2H5ckilJvtqxpUEfyGEEFfMcixOZk7SU+pBQZF2nnGUNbL89OBPeebgM+TMXNWxjfE2/kXL46yraZPAP0EUy6LmjXeo/flLhDqr77gY81vo/ernyd++fni0o+d5mI5FfaSOlpoWuRMz1XieX+FPJmH1akgkJvuKJoQEfyGEEJ8qa2Q5mTlJ1sz6s/c1aVUYL32lPp7a/xQ/O/QzSpVS1bG7k6v5VsujrEwunqSrm3nUYon0r9+k9oVX0AeyVceMBXPp/erj5G9bVzXL3XIsgnqIm9I3ySZcU41h+N+rVAra2iA2s/ZMkOAvhBBiVK7nci5/jrP5s8P9yVLdHz/nC+f5x73/yIsdL2I65vDjKioP1KzlW3MeY0l8/iRe4cyi92dIP/8K6ZfeRCuVq46Vli6h70sPU7hldVXgd1wH27NpScyhIXZ9LQqd1splf/5+MgmLFvmhf4beKZPgL4QQokrRKnImd4beUi+qohLUgtK/P45OZU/x5J4neenoS9iuPfy4rmg8mt7IN1t+jwXR2ZN4hTNL8Mw5an/+EjWvb0O17apj+Vtvpu9Lj1BetmTE8wzbJBWuYW7NXHRV4tWkMww/3EvYryL/MoUQQlCySpzNn6W/3I/pmIT1MGFdWhTG09H+o/x4z4957fhruJ47/HhIDfLF9O18veURZkcaJvEKZ5ZwxzHqnvsViXfbUbwLext7mkZ2y0b6vvgw1vw5I55XcSpoqsaSusXEgjOrbWTKuTjsL1zoT+aRsF9Fgr8QQsxQhm3Qmeukv9yPYRuE9TCaqhFVpZ1nPO3v2s+P9/6Yt06+VfV4VAvzlbq7+ONZD9IQrp2kq5thBnfZrXvuV8T2Hao65IZDDDy4hf7PP4DdUDfiqUNtPc3xZppiTbLIerIYhv/fmhoJ+1dAgr8QQswgpm3Sme+kr9Q3HPZVRZXe/XHmeR47Onfw4z0/pv1ce9WxpB7nD+u28IezHiAVkl1cJ4TjkHxrB3U/+zXh49WboNk1Cfof+xwDj9yLm4iPeKrpmGhopMIpmhOzCGgSpSacObgGJpmE+fOhtrZqrYW4NPnXKoQQ1znLsejMddJX7qNcKRPSQn5lX8L+uHNch60fb+XJvU9yuPdw1bG6QA1fq7+XrzTfJy0iE0QxTFK/eYvaX7xEsKu36pjVVE//Fx4ic98deOHqqVX2YHU/HojTkmghEUpIhX+iDVX2k0mYNw/q6iTsfwYS/IUQ4jpUcSqczZ+lt9RLqVIiqAXRVV3C/gSpOBV+/dGv+cd9/8ipbHVFeU6wnm80PsDjs7YQVmWX44mg5fKk//l10r98DT2XrzpmLJpH35ceIbf5Fn/yyyB/Dr9JUA9SH62nIVYvi3Ynmuv61f2aGpg7F+rrJexfI/kXLIQQ14mKU+F84Tw9pR6KVlHC/iQoVUo8f/h5ntr3FN2l7qpjSyJz+Obs3+OBulvRFe0SH0GMJb27l9rnXyH9ym9RDbPqWHFVG31feoTimhVVPeGWYwGQDNewMLaQSEAmWk0K04RoFFatgqC8QR4rEvyFEGIas12brkIX3cVuipUiATUgYX8SZIwMP93/DM9++FOyVnVF+eb4Yv509u9xZ2q1tIdMBM8jcvgotS+8SmLbByjuhYlJnqKQ37SOvi89gtG6aPhxx3WouDbRQIQ5yTmkI2nZaXeyuC5Ylr9Qd7aMsR1rEvyFENOeaZtkzSw1oRpC+szYUdaoGBwdOEqmnEFXdQJaQGbtT4LugU6e3vkjfn7qFcpudUV5c81K/nT277E20SqBfyJUbJLb3qf2xVeJdByvOuTqOtl7b6f/Cw9hzZk1/Lhhm+iq7i/UjTcR0AITfdXiYlLlH3cS/IUQ09b209v5wY4f8Pyh56m4FQJqgCfanuA7G77DhjkbJvvyxoVpmxztP8pAeYCwHpY2hInmeailMmdO7OUfPnqOX/a9Q8Vzhg+rKNxfewvfnP17tMVkl92JoGXzpF7eSvpXrxPoG6g6ZifiZB68i4HH7seuTfmPOTYODvFgnDnJuSRCIyf3iAkmVf4JI8FfCDEt/bf2/8af//rPqzY+qrgVfnrwpzz34XP87cN/y7fWfmsSr3BsWY7F0b6j9Bv9hLSQBP6J5LpoA1n0nj46eg7xd+d+xW+yu/C4sMlTQNF5vP52vjH7EeaHmybxYmeO0MenSb/4G2refAfVqlQdM+fOpv/x+8nefRteOITruViOSVgL0RBvoCHagKbKOospQar8E0qCvxBi2tl+evuI0H8x13P581//OSubVk77yr/lWBwfOE5vqdcP/NLOM2GUUpng6bNomRwfFI/w33pf4Z3s/qpzomqY32+6mz9ufoDGYHqSrnQGcV3iH+wl/eKrxHcfHHG4sH4V/Y/fT/Hm5aAoVJwKOBWS4SSLYs1EArIb9ZQhVf5JIcFfCDHt/GDHDy4Z+oe4nssP3vsBz3zxmQm6qrFVcSocHzhOT7GHkC6Bf8K4LnpPP4GuHigWedM8xN+f+zV7C0erTkvpcf7H5vv5g6Z7SenSKjLe1FKZmte3kf7lbwh1nq865oaCZD53BwOPfm64f990TAJqgOZ4M/WxelmoO9WYJsRiUuWfBBL8hRDTimmbPH/o+Ss69xeHfoFpm9Nqwa/t2hwfOE53sZugGpSWngmiGCaBM+cJDGQwvQo/y73Pk+de5oRxruq85mAtX5/1EF9ouJOoJtXj8RY43036n18n9cpv0UrlqmOVxjr6f+8+MvffhZuI+e08tkE0EGVRahHJsOyCPOVIlX/SSfAXQkwrWTNLxa18+on4Pf85M0eD3jDOV3XtbNfmTPEM/Wf6CagyoWdCeB7BTI5wsQOtUGJAt3imdytPdb1GXyVbdeqi8Gz+ZPbDPFy3iaBs4jS+PI/IgQ5qX3yVxPZ2FNerOlxatoT+xx8gv3ENaJq/q65tkoqkuCF+A2Fd3pBNSVLlnxLk1UsIMa3UhGoIqIErCv8BNUAyNLWrfrZrczJzkr19ewmoARr1xsm+pOueYlUInD1P+uARFNfj3OwY/9D9Cj/v+d2IkZyr4jfyjVkPcU96rbSLjDPFqpB8awe1L7xC+NjJqmOerpG9cwMDj92PsXgh4LfzaI5HXayOpliTLNadqqTKP6VI8BdCTCshPcTn2z7Pswef/dRzn2h7Ysq2+Tiuw8nsSc7lz6GrOmFpGxl3aiZLsLMLrVjCCwQ44nbxbP4t3t6zH4fqNSN3p9fwjVkPsyaxZJKudubQ+wZIvbKV9K/fRB+ovtNiJxMMPHwPmUfuwa5N4Xkepm0Q1sPMS84jHUnLHglT2VCVf/VqCMgeCVOBBH8hxLTzrzb8K3724c8uu8BXVVS+s+E7E3hVV2ZE4Je2hPFl2wTO9xDo6UOpVHBDId4yOvjRiV+zI/dh1akBReex+tv52qwHWRSRyuS4clzi7ftIvbyV+Pt7qnbXBTAWzqX/8QfI3bUBLxj0d9Z1TBLBOPNT84kFY5N04eKKDFX5Fy2CWbM+/XwxYST4CyGmnQ1zNvC3D//tJUd6qorKf3n4v0ypUZ6u53Iqe4qz+bNoinbNgd9yLApWgXgwTlCTftlPUvMFAp3n0XIF0DUsFV7O7+THR17iSPl01blJLcZXmu7hf2i6j4ZgapKueGYI9WWof/M9Ur95i0Bvf9UxT1EobLiZ/sfup7SybXgcp+dYpMNpZiVmyc6604FU+ae0MQ/+ra2tIWAPsKOjo+Nrg48pwL8D/gyoB94B/rKjo+PwWH9+IcTM8K2132Jl00p+8N4P+MWhXwzv3PuFpV/gr279qykT+suVMucK5+gqdKGgENKurfVoX9c+fnLgJ2z9eCu2a6OrOlsWbOGry7/KiqYVY3TV05TjoHf1EujuRTUtvHCIgu7ybM/r/NO5V+mqVO/q2qSl+EJ8M19f/CgxabUaP7ZNYsceVr/wCnUHj6B41Yt17VSSzL2byTy4hcpsf/Mz0zHRVZ2meBMNsQZZXzEduK4f+m+4Qar8U9h4VPz/V+AmYMdFj/0H4LvAvwE+Bv4X4I3W1talHR0d2REfQQghrsCGORt45ovPYNomOTNHMpSc9J5+13PJlDN0FbvImTksxyKkhcakKv+LQ7/g++98v+ouh+3avHb8Nd448Qbfve27PNH2xDV/nulGzRcInO1CzxVAUfCCAc5rJf7p9PM8272VglM9BnJpdAHfmP0Qy8staIomoX+cBM51k3r1t6R+89aI3n1PUSiuWU7mgS3kb70ZAvpg/75JJBBmYWohNeGaSbpycVU8D8plSCalyj8NjGnwb21tvRn4n4Deix5LAP8a+N86Ojr+n8HH3gZOAn8C/F9jeQ1CiJknpIcmdWSn5Vh0FbroL/dTsAoAhPUwuqqjj9Hox31d+0aE/ou5nsv33/k+i2sXz4jKv2JVCJzvRuvPDFf3vVCQj0qn+fHpl/hV33Zsz6l6zu01K/nGrIe4NbkURVHo7OycpKu/jlVsEtvbSb2yddSddY1UksKDW8jcfyeVJv9n1nEdKrZJTSjJwvQi2V13urAsP/Sn07B0KUSjk31F4gqMWfBvbW3VgR8B/wfw+YsObQDiwC+HHujo6BhobW39HfAAEvyFENOM53kUrALnC+fJGBkM2yCoBcd1se5PDvzkinYrfvrA03yv6Xvjcg2TznXR+gYIdPX6k3mCAdA03HCI93OH+NG5X/N2dl/VU3RF4+G6jXx91kMsic6dpAu//gXPnCP1ym+pee1t9Fy+6pinKhTWreLYLSvpW9HK7HnzgMHA79mkwylaEnMIaLLscMobqu6HwzBvHjQ3gyZjVKeTsfwp+zdAEPge1cF/aBbasU+cfxx47LN+skOHDn3Wp16Tcrk8qZ9/JpK/84knf+cj2a5NxsrQb/RTtIs4nkNYDY/ZKEHT9OfHnzhxYsSxilvhzRNvXtHHefPEmxw5doSAev3cbtdKZaJdvQQKRUDBDfi/urrtDK+VdvFaaReddm/Vc6JKiIdjt/L5+G006DUwAJ0D1RX+SsXfC0Iq/5+NWqnQ2H6AlrfeJ31k5L/bcm2Ks5vXcfa29Zi1Nf7ft+ty+sxpHBySgSSNkUa8sseZgdOjfAZxrYzLvK5cFdtGsW3sZBJ79my8WAxyOf+PqDLVf3+OSfBvbW1tA/49cE9HR4fV2tp68eEkYHZ0dFifeFp+8JgQQkxJhm3QY/SQr+Qp22VUVIJakKA6sVN0SnYJ5xNtK5fieA4lu0RNcHr3Ryu2Tbinn9BAFq1i4wQDuIEAhmuxrbib35Ta2WMew6N6oWidmuSJxG08HLuVmCotI+Mh1tlFy9vvM+vdXQRK1esnXFWld1UbnXfcQt+yxaBeWJRruw6u59AYaaQ+0oAuG25NfYaBFwjgNDZiNzZKdf86cM3Bv7W1VQX+Hvj/Ojo6to9yigKfeGW+4PL3rS+jra3tsz71mgy9g5uszz8Tyd/5xJupf+ejLcxNpVPUqXXj/rmHKnILFy4cccxyLPRtOrZrf+rH0VWdpTcunZ4jPj2vupUnEoN4Es/zaM8f4YXet3i1732KrjHiqWviS/hi4108VLeR4BWuqxiq9Le0tIzpl3E9UgyT5Ns7SL28leihoyOOW82NZB64k+x9d2DXpggDQ3+rtmPj4VHuK1MXruPGG26c0GufyS73unJJtg2VCqRSMHcu1EzvIsJEmwq/P9vb2y95bCwq/n8JzAMeHuzzH6IM/n8WCLW2tgY6OjoqFx1PDB4TQohJ43ke/eV+zhXOkTX8l6SxXph7rYJakC0LtvDa8dc+9dwtC7ZMu9CvlMoEz3ahD2TxFAWCAbxwiE6zhxfPbePF3m2cNrtHPK85WMfj9bfzaMPtLAg3T8KVX/9CH58m9dJWat58B61Yqjrm6Rr5TesYeGALpVVtVdV9gIrj/8pviDXSFG/kZPnkRF22+CwMw5/I09Dg9+/rU+P1T4ytsfiufh6YAwx84vFVwB/hz+5XgIXAkYuOLwI6xuDzCyHEVcuZOc5kz5A1s7ieS1gPT+lddL+6/Ku8ceKNT92t+KvLvzqBV3UNKjaBrh703v6qqTxFx+C1nvd4oedt3s+P7JGNqEHuq13P4/WbuSXZJvPdx4Ff3X+f1MtvjlrdN1uayTy4hew9t+OkRnbsVpwKiqLKDP7pwHH82fs1Nf4uu+n0ZF+RGGdjEfz/DL96f7Gn8EP+fxz87/8NPA787wCtra1p4M7B40IIMSFKVonOfCf95X4qboWwFp421fEVTSv47m3fveRIT1VR+be3/9upPcrT89D6M34rT76AF9BB13HCQXbmD/NCz1u82v8BZdcc8dR1iVYeb7iD+2vXE9Mik3Dx17/Qx6dJvTxY3S9UV/ddXSd/+3oyD26htOImGGVRu+mYaIrOrPgs6mP1Y7bwXYwDw/D79Rsa/Hae4PR4HRTX7pqDf0dHx4iqfWtraxno6+jo2Dn4//8v8J9bW1td/DcC/x7I4a8NEEKIcWM5FmdyZ+gr9WE6JiEtNKXaeK7GE21PsLh2MU8feLpq5967F97NHyz7gykb+tV8gcC5bvRs3l/wFQriRcKcMrp48fw2ftm7jU6zd8TzWkL1PFa/mcfqb2duuHHCr3smUEyL5Fs7SL2yleiHH404bs6ZdaG6X/PJGp/Pcix0VWdOcg51kToJ/FOVbfuz9+NxaG2FurpR38CJ69tE/eb7d/gLef81/kz/d4E/ll17hRDjwXZtugpddBW7KFrF4Rn7EX36V4pXNK3ge03fw3IsilaRWDA2Je9aKIZJ4Jzft69U7Itaecq80v07Xuh9m/b8yG7PiBri/tpb+HzDZtYmWqVNZJwET54h/dKbn7m6D2DYJkE9wLyaeaQj0iIyJTkOijU4VLGpCWbPlur+DDcuwb+jo2P1J/7fBr47+EcIIcac67n0Fns5XzxPzsihqzoBLUA0cH3uJhnUggQjU+wX+FDffn8GtWzihQKg67iaxp7CRzzXvZVX+9+n7H5yujPcmmzj8fo7uLd2HTFt6q61mM4U07rQuz9adb+lmcxDd1+2ug9gOCZhLcTC9AJS4dR4XrL4LBzHr+yHw9jpNE5TE6xaNdlXJaaI6XevWwghBnmeR8bI0JnvJGfkQIGQFiISmP6V/WljaDfd7j60QnG4b9+LhMjZRX7Z/Q7PdW/lo/KZEU+dG2rk8YbNPFp/Gy2hhkm4+JkhePIM6Ze3UvPGts9c3fc8D9OxiATC3Ji6gUT40m8MxCRwXX+RbigE9fV+ZT8cxp6im0iJySPBXwgx7RTMAmfyZ8gYGRzXIayHCemhyb6smcPzULM5Aud70HMFUBW8oN+373kee/Mf8Wz3m7zS/z7GJ6r7UTXMg3W38njDZtbEl0g/+Di5UN3fSvTDIyOOD0/muXfzZav7tuvgeDbJYJJFtYum9OSrGcd1/UW64bA/jaelBSJS9BCXJ8FfCDEtlKwSZ/Nn6S/3YzomET1CQA0QUAOTfWkzhlIqEzjbjZ7N+qEjFMIL+2+4cnaRf+59l+e6t3KkfHrEc5fHFvLlxrt5sG6DtPKMF88jdOwkqdffvqbqPgxO6EGjLlZHY6xxWi6Gvy55HpTLfmU/nfYr+7HYZF+VmEbkJ1kIMWUZtsHZ/NmqiTyaqhFVr8++/alIsSoEznej9WdQDdMP+gH/zZbneewrHOOn3W/ySv+OUav7j9Rv4suNW1gaWzAJVz8z6P0Zklvfpeb1bYQ/Hvmmy2xpJvPAXX51f5S5+0P8dh6TsB5mXtJfsCt3ZKYAz/Mr+7ruh/2bbvIn8wjxGUjwF0JMKZZjcTZ/lt5SL+VKeTjsXw8TeaYN20bv6UfvG0ArlfACAdA0vKj/PcjbJf659x2e69lKR2lk0FwWW8iXG7fwUN0Gmbk/ThTLIr59F6nX3ya2az+K61Ud93SN3G2D1f2VbZet7juuQ8WtkAglmJ+aTywoFeRJNxT2Nc0P+0uWQPLSb9qEuFIS/IUQk67iVDiXP0dvubdq/Ob1OpFnKlLKBoHuXrRs3q/saxoEdLyw35bjeR77isd4tnsrL/e9N2p1/+H6jXy5cQvLYgsn40u4/nkekUMfUfP6NpJv7UArlkacUl68kOw9t5O7c8Nlq/vg/9wBpMNpmhOzCGgSCSZVpeL/CYUgkYDFi/2wL3ddxBiSn3IhxKQYmrXfXeymWCkSUAMS9ieS66Jm8wR6+tDyBRTbwQsGsi9qPgAAIABJREFUQVOH+/bBr+7/qu9dnu1+c9Tq/tLoAr7ctIWH6zZKdX+c6F29pN7YRs0b2wie7RpxvFKbInf3JjL3bsaaP+dTP57hmATVALPis6iL1cleCZPFcfxJPIGA37rT3OxP5AnJoAIxfiT4CyEmjOM6dBe76S52kzfzw7P2pY1nYihWBa23H30gi1Ys4Sn4ISMQ8Nt5Bnmex/7icZ7tfpOX+94bMXc/ooZ4pG4jX266W6r740QtlUm88wE1r28jtm/kSEY3GCC/aR3Ze2+nuHqZ3xJyGa7nYjkWsUBMxnFOlqGRm4riL8itq/M31ZJJPGICSfAXQoyrizfWypt5VEUlqAVl1v4EUYsl9O5etFwB1TD8gK/rVVX9IZ1mDy/37eDXfe+OWt1vi87ny41380i9VPfHheMS3fchNW9sI7ntA1Rz5EZnpWVLyN67mdzmW3Bjn353zHZsHBxS4RSL44sJ6lNs07frmef5Qd/zIBr1e/WbmvzqvrTviEkiwV8IMeZs1yZjZDhfOE/WyKIoCiEtJDPAJ4LjoGVy6D19aMWS38ITCoKq4o1SWeyxMrzSv4OX+95jT+HoiOND1f0vNW5heXzRRHwFM07wzDlqXn+bmjfeIdDbP+K41dxA9p7byd59G5XZTVf0MU3HRFN06mMNNMYa0NTL3xEQY8Q0/RaecNjv01+0CGpqPvWOjBATRYK/EOKaGbZBX6mPrJmlWCli2iYKCmE9LGF/Aiim5Qf9TA61VEZRFD/sf6KFZ0imkue1gZ281PceH+QO4eKNOGdpdAFfbLyLR+o2EZdWrDGnZfMk3t5B6vVtRDqOjTjuRMLkN99C5t7NlJctAfXyffie52G6FioKsWCM2YnZJENJGcc53mwbLAuCQb99Z84cqK0dHnkrxFQjwV8IcVU8z6NgFegp9VC0ihQrRSpOxd9MSwugokrP/idYjkXBKhAPxglqY9NqoRZL6F09gy08Fl7IH7lJODRKjIeiU+aNgV283Pce72T3Y3vOiHMWhJt5qG4jD9VtYFFk9phcp7hAzRdJvLuT5Ns7iO0+iOK6Vcc9RaG4ehnZe28nv2ndqO1YVecPzt3XFI1EKMHc6FziwbiE/YlQLvu9+bNnQ2OjLMgV04YEfyHEZdmuTdbI0lvqpVQpUaqUcD13eL6+7J57afu69vGTAz9h68dbsV0bXdXZsmALX13+VVY0rbi6D+Z5qPkCge7BKTxW5UILT3T0uyqGa/FWZi8v9W7nd5k9mF5lxDmzgnU8VLeBh+o2clN0noTGMaYWSyS27yLx9g7iu/aj2CPfcJlzZ5O9dzPZuzdh19de9uMNLdLV1QCJUJx50XnEAjH5vk2Eodn68TgsXw6p1GRfkRBXTYK/EKKKYRt0lbrIV/IUzhaG23ZCWghFUaR15wr94tAv+P4738f1LlR1bdfmteOv8caJN/jubd/libYnLv9BPA81k/Pn6+eLKK6DFwr5m2lFRu8Ztlyb7bkDvNT7Hm8MtFNyjRHn1AdqeKD2Vh6q28Cq+I0SGseYWioT37Hbr+x/sA/VtkecU6lLk7/9FrJbNmEsWXhFG2wFtSCJYIKGWIMsjp9IrusH/lQK2tr8lh4hpikJ/kLMYBe37RTMAiW75G+mVTpHQJW2nc9qX9e+EaH/Yq7n8v13vs/i2sUjK/+uizaQ8XfOzRfx8Pw2gmAAj9HvrDieywe5Q7zc9x6/GdhJ1i6MOCepxbi/dj0P1m1gfbINTWa3jynFMIh/sJfk73YQ/2APqjXy7oqdriF3+3pyd2ygvHTxZfv2bdfB9mxCWpBUJEVDtIGQLu0kE8px/P792lpYuVLaecR1QYK/EDOM67kMlAc4VzhHzszhuM6Ith1p3bk2Pznwk0uG/iGu5/L0gaf5XtP3wLYJ9fYTyuSJdWf89p1Q0G/luQTP89hXOMav+7bzSv8OeivZEedE1TD3pNfyUN0GNtYsJ6jKS/5YUkyL+M59JN56j8SO3aOO37STCfK3ryd3x62Ult8E2qeEfbdCOBChLlpLQ7SBgCY/ixPOtv0/DQ2wcKEs1BXXFfktIMQM4HoufaU+uopdZA0/IIb1MCEtBDJlbkxZjsXWj7de0blbT2xF3XeAiGETPd+DF9DxIpdupXI8l935I/ym/wNeH9jJeWvk6MegEuCu1GoerNvAHalVRDSpUo4lxaoQ27Wf5Fs7iL+3C608spXKicfI37aO3B23Uly19LKjHCtOBcdziQYiNMTS1EXqCWjyq3lSVCp+H39TE8yfLyM4xXVJXl2EuE45rkNvqZeuYhd5My+z9CdIwSpguyN7ukdjezalSpFwOIkXGP3luOLafJA/xG/6d/LGQDt9o1T2dUVjU81yHqrdwN3ptTJ+c6zZNrHdB0m+9R6J7bvQiqURpzixKPmNa8jdsYHizctAv/Sv16EFupFAhFmJ2aQjKXS5GzN5TNMP+bNn++M4P2V0qhDTmbzSCHEdsV2brkIXvaVe8lYeFZWQLmF/IsWDcXRVv6Lwrysa8VF2wLXcCu9mD/Cb/g/Ymtk9as++hsr6ZBsP1N3C59LrSQUSY3L9wqeYFrHdB0hsbye+fRd6fuT3wImEKWxcS27zLRTXrMALXr4lpOJU8PCoCddwQ/wG+bmcbIbhz99fuBCam2U3XTEjSPAXYpqrOBXOF87TW+qlaBXRVI2gFpRFuZPB8wgbNvc03MqrXe986un3pdcRHFxPUXYtdhodtB99kd8O7KY4yjSeocr+fen13JNeI2F/jGm5PPH39xLf3k68fd+oPftuKEh+wxrym2+lsG7lZddhwIVZ+yE9xKz4LOpidaiysHpylUoQjUJrK9TXT/bVCDGhJPgLMQ1ZjsW5/Dn6yn0UrSJBLYiu6jLibxIoZQO9bwAtl0crlsF1+Frt3bzW9e6oO+IOUVH4YsMWftX7Lq/1f8Bbmb2jztkPq0Fur1nJfbXruCt1Mwk9Op5fzowT7u0n/cEBEu+1E93fMWJTLQA3GKCwfjW5O2+lsH71p26sBf5CXcezSQQTLEgtIBqU79uk8jx/061EAlaskBn8YsaS4C/ENGHaJp35TgbKA5QqpeGwHw1IoJhIimEOB321WEZxHLxgEDR1uPq7KrKE/7Dwa/ynE0+OGv4V4MbIHP7Fkf+TijeyJSiqhrkrvZr70uvZnFpJVJOWkDHjeYSOnyLxXjtzfvceidPnRj3NicfI33ozhY1rKaxdjhe+su+B6ZgE1AD10XoaYw1oqiwQnVSm6c/hr6mRGfxCIMFfiCnL9VyyRpbuYjc5M4dhG8NjNyXsTxzFqqANV/RLKBXbX4ir65edrf/lxrtpjczjH8+/wm/6P8DBZaiD2AOOlE9XnZ9QImyItPH4nDvZVLOckHr5FhJxFRyH6MEjJN5tJ769nWB376inWY31FDauJb9xDaXlrVc81WVoDGc8mGBOci6JUHwsr15cDcPwq/uhkL/D7ty5kE7LSE4hBknwF2IKKVrF4ZGbRas4PIlHVVQJ+xOlYqNlsn5Vv1RGsQaD/mDY9y4zreViZ4xudhc+oruSGa76f7L2X6cnubt2LZ9Lr2dOoQZd0WhJt4zxFzQzKYZBvP2A36///p5RF+cC5OfOwrhjA/mNazEXzbuqBZ6mY6KhkY6maYo1yxjOieZ5fkXf8yAc9oP+/Pl+G88V/pwKMdPIT4YQk8hyLPpKffSV+yhYBSpOZbiqL/36E0OxKqjZHHp/BrVs+As6Nc2f0HIVQd/zPDpKp3h9oJ03BnbSUTo96nlNgTT31q7jc7XrWZNoHd5Bt7PYOWZf00ylZXLEd+wmsb2d2O4Do+6e66kKpeU3kd+4lqMLZ2PU19LScuVvtoZGcUYDUeanFpAK1aDINJiJcXHQj0T8fv1Fi/w2Hpm5L8QVkeAvxARyPZdMOUN3qZu8mcewDX+nXE12zJ0oimmh9Wf81p1SGcWyQNP9oK+ql91A65OGNtR6Y6CdNwbaOWP2jHrenFAD99Wu53Pp9ayIL5KpLmMocLaLxHu7SGxvJ/LhERR35JoKNxSksHal369/yyqcpD8Nyei88jdbFcd/E5EKp2iONxPUpRVr3Hme37oD/hSeZNLfTTeRkKAvxGckwV+IcXZx+06p4m/8I+07E2d46k6hiPrJ1h1Nw4tc3Z0V07XYnj3I6wM72TqwmwE7P+p5N0Xnc096DffWrmNJZK5UhceK5xE+dpL4u+0ktrcT/nj0Oyt2MkFhw83kN66luHrZFU3i+STTMfGAiB5mdnI2tZFaedM2nlzXr+grih/0E4kLQV821RJiTEjwF2KMWY5FT7GH/nL/8C6uQ+07smHPOPM81FLZr+jnC6glY3DqTsCvEF5F687FcnaRtzJ7eX1gJ29n9lF2zRHnqCisSSzh3vQ67k6vYU64cSy+IgFg20QPdJDY3k5i+y4CPX2jnmY1N5LftJb8xrWU2xaDdnVh0XEdKm4FXdGJhWI0J2aRDCZkMs94K5f9jbTq6qCx0e/VlzfKQowLCf5CXCPbtckYGXqKPRSsQlX7TlALEtSkJWDcuC5qqYze249aKKGVyuB5w+M1Lzd159N0WwO8OdDOGwO72JH7ENtzRpwTVALcVrOcu9Nr2ZK+mdpA8lq/IjHo4sW5iR270QrFUc8r37jAn8SzaS3m/DlXHRgrbgXDMYnqERKRBPXRenmDPhEcx6/uJ5OwbJk/eUcIMe4k+AtxlVzPJWfm6Cp0UbAKlCtlFEUhrIelfWe8VWzUQhF9IINWNFBLJVDwg76qfqZ2jot9XD43uDi3nb2Fo6Oek9Ci3JlazT3ptdyeWklshs7YV6wKaqmEG436d1TGgJbNX1icu2v/JRbnqpRW+Itz8xvXYDde3c6rw1V91X9jXh+uZ0XjCqnqTxDFssCy/BaeefP8Sr8QYsJI8BfiU3ieR8EqDM/Tv7hPX1EUmb4zThTTQi0U0LJ5f9qOYaLYNiiDG2UpylUtxB2N47nsLRzltwO7eXNgF8eNs6Oe1xBIcU96LffWrmVdoo2gOnNfOiOHPqL2hVdJvLsTxXbwdI3cpnX0P/4ARtuNV/3xAue7iW/3F+dGD3Zc1eLcKzXUq//Jqv6J0gkACf3jbXDXXA+w5s6FDRuklUeISTJzf3sJcRmlSonuYvfwPH3Hc4Yr+tIGMMY8z5+0k8uj5oqoxmDId1xQFb+arCgQCOCNwSY8BbvMtuw+fpvZzVuZvWTs0ee7Lwg3c296HffUrmVFTCbxAKReepPmv3myKpwrtkPNWztIbnuf89/+GpmH7r78BxnaOXf74OLc46dGPc1Oxincuob8pqtfnHtxVT8WjEqv/mSpVPyWnnQali7FPHnSf1xCvxCTRoK/EIBhG/QUe8gaWfJWvmpBbki/tvYRcRHPQzFMtEzOn7JjmKhlw5/moesXWkaCgRGbXV2LM0Y3WzO7+e3Abj7IHx61Xx9gRWwR96TXck/tWm6IyEZaF4sc+mhE6L+Y4no0/82TGAvnjaj8a7k80X2Hie05SGznXoJdl945N79pLYWNayktW3JVIxttx8bBf4OeiqSkV38ylcv+zrktLTB7tozeFGIKkeAvZqSKU6G31EtfuY+iVcRyLIJaEF3VZUHuWHFd1LKBNpBFLZb8kG/403C8wV1wgWvuyx+N47nsKxxl68BufpvZzdHy6PPaw2qQjcll3JW+mTtTq2kMygLDS6l94dVLhv4hiutR+8IrnJ//J0QOdBDb+yGxPR8SOnEKxRv9ucaieYP9+le/c66/mVaFsB6iKd5EXbROqvqTZWixbioFN97ob6olhJhyJPiL65bruZi2SalSImtmMWwD0zaxHAvLsYZDvq7q6DO4Z3ssKWWDQE8fWraAUi6jeO7ghB1tTHryL6folNmW2T/cwnOp+fqNgTR3plezJXUzG2qWEVblTd6nUawKiXd3XtG5ybd2kHxnJ4oz+l0VT1UoLV1CftM6ChvXUGm++rGnlmOholITrqEp3iR35SaTYfg/342NMHcujEE7nhBi/EjaEdOa53mYjknJ8sN92S5j2RaW64d7z/NQFZWgFhzu0ZagP4YcB20g62+QVSyhVOwLozTDoTFt1xlNp9njV/UHdvN+/tAlW3iWxRZyV2o1W9JraIvOl820rpJaKqHYo//dfpICfvX3Isb8FkqrllJctZTSijbcROyqr8F2HWzPJh6IMzsxm2QoKd/HyeK6fuCPx2HJEqivl759IaYJST9iyvM8j4pbYaA8MDxVx3IsTMfEsi1QQEGpCveaohHRZdrOeFBK5cGqft5v3VEVP+x/xs2xrobjuewvHBvu1/+ofGbU80JKgI01fgvPXambpYXnGrnhMJ6m+guur4DVVE/x5uV+2F/ZhlOb+kyf1/M8TNcipAWpj9bTEKuXN+2TxfMuVPfTaVi+HK5y12shxOSTV1Ax5Zi2SVeha7g950jfEVzPpZAsEFADwz28mqLJKM2JYNvVVX3b8cdpjsHc/E/jeR6nzW62Zw+yPXuA93IfknNG38ipIZDirtRq7krfzIbkMiKatH98Zp5H4Fy3vxh374dE9354xaE/t34Vnf/pX1/TpzcdExWVZDjJwtgiIgFZpDsphir7waDfs794sb/hllT3hZi2JPiLSed6Lplyhu5SNzkjh+mYw733qqISUv0AJxM6JojnoZXKhPszRHJlv6qvaf7EnTEaqXk5A5U87+U+5L3sAd7NHaDTHH0CDMDS6ALuSt/MlvTNtEXny8jNa6Dmi37Q37Wf+K79BLr7rvpjeKpC3x88/pk+v+062G6FeDBOc2IWqVCNtPJMBtv2N9gKh/3K/qxZELv61iwhxNQkwV9MCsM26Cp0kTEyFCx/jvrQ+MyoKjvfTriKjd6fQe8fQC2WSZ05gxPQUWrS47ogF8BwLXblj7A9e4Dt2YMcKp3Eu8TqgJga5pZkG3ekVnNXejVNwdpxvbbrmuMQOXKcWPt+Yu37iRw5dsmpPW4oSGnFTbihoL9x1yinearC+b/4+lVt4jW0RieoBamL1tIQbSSgya+lCWdZ/rqMWAyam/0/IbljJsT1SF5hxYQYqup3FbvIm/mqqr5U8ieY6/obZg3N0i99oqofDOCExm/SjeO5HC6dZHv2IO9mD7ArfwTLq4x6rq5orIzfwKbkcjbWLGN5bBEB6fH+zPTuXuLt+4nt2k9sz0G0QmnU8zxNo9R2I6XVyyiuWkq59QYI+H/v4UNHqX3hFZIX79x723r6H7v/ikO/5VgAJENJFqQWEA3Km/0JZxj+fxMJf9Z+Q8PwiF0hxPVLfsrFuDFsg/OF835V3yygKAphPSxV/YnkOKilsr8Q91Kz9Md5zCbAaaOb7Tm/ov9e7kOyl9gtF+DGSAsba5azMbmM9cmbiGmyjuOzUgyD6L7DxHcdILZrP6HTZy95rjW7icLaFRTXrKC0sg03Ovrfu9F2I2fb/oJzVgW1VMaNRi5svHYJtmNjeza6qhPRIzTGGklH0tKaNZE8z99YS9f9sD9/PtTWgirfAyFmEgn+YsxcXNXPmbmqTbFkEe74U6wKaqGIls2hlg1U00KxKniK4s/W1tQJCfkAmUqeHblDvJs7wHvZg5w2uy95bkMgxcaaZWxKLmdDzTKZwHMtPI/Qx6eJte8n3r6fyIEOVNse9VQnEqa0etlw2K/Murp5+l4wgHOJwG85Fq7nEdQChPUw9ZF6asI1BHXZM2FCDW2qFQr5i3OXLPFDv6ydEGLGkuAvPjPHdShVSvSV+xgoD1CqlECBsBaWWfnjyfNQDBMtX0DLFVAGq/iK7YCm+tVXRfFbdyITs4tptzXAzvxh2nMd7Mx3XHLMJkBUDXNL8qbBqv5ybojMlkWc10DL5IjtPuCH/V370Qeyo57nKQrGjQsorl1BYe1KyjfdMCatHZ7nYbkWngchPUhEj9AUayIRSkq//mQYCvuRiD9ff9YsGbsphBgmr8riUw0twMubebJGllKlhOEY/gx9IKgF0VRNevXHg+uilg20gexwL75qmP5t+6GefIBg4FPbLcaK53mcMXvYmT/MznwHO3OHL1vR11y4tRM22y2sWfY5blp2h/TpXwOlbBA9eITo3g+J7f2Q8NGPUbzRF+VWalMUByv6xZuX49Qkrvnzu56L5fhrMiKBMLFAjJpwDfFgfHjUrphgnwz7LS2yOFcIMSr57Suq2K5NySrRb/RTtIoYtoFhG3h4qPg74CqKIjP0x4Pj+CE/kxvux1dMC8VzB3fD9UPVeM/O/yTXczlWPkv7YNBvz3XQVRm45PmKByu64M6TcO9xuOtjSJoAnXjqk5z/NmQeunuiLn/aUwyTyKGPiO09RHTfh0SOnEBxRt9F1w0EKC1vHQ775oI519zWMTRmU1VUInqERChBOpwmEohIj/5kkrAvhPgMJPjPUJ7nYdgGWTNL1sgOB/yK61fygmpwuHonlfxxYNuopTJ6JjdcyVdM/w6KH/L9fnzCoUsMthzHS/Mcjlhn2G+e4KMj52nPd5C5zGJcDZVlsYWsS7ayKZPk8//xGWpHHxaD4no0/82TGAvnXdXYx5lEsSwih4/5Ff19hwgfPnbJPn0Ac+5sv09/7UpKy1uv+Y2h4zpU3MrgxK0IqXCKVCRNWAtJS9Zkk7AvhLhGEvyvc57nYTkWpUqJAcPvwzdsA9M2cT0XXdUJav6CO+nLHycVG7VYQs9k/UW3hnlh0W0w4E/VUNUJWXQ7GsutsL94nJ25Dtrzh9md/4iia1zy/JASYFX8RtYmW1mbaGVV/EZimn/tLU/9NclLhP4hiutR+8IrnG37i7H8Mqavik3kyHEWbnuP9OHjpI6fQrVGH28KYDU3UlrVRnFlG6WVbdj1176XgemYeEBED5OKpKiL1MkdvalCwr4QYgxJyrtOWI6FUfEr+MVKEcu2MB1zcLqGi4JCSA+hKioKilTxx8mIyTqGiWLbgOL34KvqhC66HU3RMdhb+Ggw6Hewt3DsknP0wd806+bEEtYlWlmXvInlsYUE1ZHrCRSrQuLdnVd0Dcl3d3LOqkzYuoQpxXEIf3SC2L5DRPceInqwA3Xwbs9oKg11fshf1UZx5VLspvprvgTbdfzxmopOLBilOTGLZDAhPfpThYR9IcQ4keA/jVScCoZtkDNzFKyCH/YHF9m6ngswPD4TQFVUCfjjyXH8Sv7QwtuygVKx/er90GQdXceb5E1xBip52vMdtOeP0J4/zKHiSRzcS56f0uMs0+ezMrSQu+feQmt0Hrry6YFQLZX8yUJXQLH9/QUuNQ7yuuK4hE+cIrr3Q6L7DhHdfxitfOk7KpXaFKWVbZRWLaW4ss0fs3mNLTYXT96JBaLURGuoi9QR0iVMThkS9oUQE0CC/xTjuA6GbZC38hTMgt+W45iYjonrunh41eEeCfcTYnCEpt6fQS0Uh6frVLXrTIGQD3DO7KM974/VbM93cKzcednzmwJp1iVvYm2ilXWJm1gUmcW5s+cAaIm1XPHndaNRPF27ovDv6dolN4ia7vTefiIdxwl3HCNy5BjhIycuG/TtmgSlVUvpnDeLgZtuIL1m1ZjMWR9alBvUgkSDMVrCLSRCCVmQO5XYNliWhH0hxISZ/JQywzmuQ8bI0FPqIW/mMWw/IOiqTkANDC+mC2khkLvwE0bNFwmcOw+2h+o4qIYBjuNX8idot9sr4XkeHxvn/Rn6g0G/0+y97HPmh5tZl/D789cmWpkTahiTRZteMEB+0zqSb+341HNzm9ZdF20+aqlM+OjHRA4fI3zkGJHDxwj0XXriEYCdiFNacROllW0UVy/FmtcCikJnp/8GLf0ZvxdDVX0FhageJR1LUxuulU2zphLL8sN+MAixGDQ0QFOThH0hxISR4D/BXM8lb+bpKnaRN/OUKiVURSWk+f330UB0si9x5nH8thN9IEvsgz3UP/srEu/tQrEdPF0jt2kd/Y8/MCWm0DieS0fplB/yB3v0++zcJc9XUFgSnVsV9BuCqXG7vr7HHyCx7X0U99KziDxVof/xB8btGsaN4xD6+AyRjmNEOo4RPnKc0KnOy36tAHYqSfmmGymtvIniyqWYC+f6d4jGwFBVP6SHiAajzI3MIx6MyfSdqcDz/NYd14Vw2A/6LS1QW+sHfyGEmAQS/MeZ53kUrSLdpW5yRo5ipYiHR1gLoyiKBP2J5roopoU2kEXLF6padlJvbKP5h/9QFeQU26HmrR0kt73P+W9/bcLnzxcdg0PFj9mVP8LOfAd7Ch9RcMqXPF9XNFbEFg2H/JsTi0nqsQm7XqPtRs5/+2s0/82TowZiT1U4/xdfnxJvoi7L89C7+4gMVvEjHccIH/34sotwAdxQEOPGBZRbbxj+YzfWjUnrzsUsx6/s10ZraYo1EdCm/92Tac91/aAPEI1CPA6LFkEyOSY7JAshxFiQV6NxUK6U6S52kzEyFCtFHNchrIdlse0EU0zLn7CTy/sB37TAqqB4Hl5Ar2rZiRz6aETor/pYEzB/3vFcjpbPsL9wnH2FY+wvHuOj0hncy0zyj6hBVscX+/35yZtYEVtERJvctoHMQ3djLJxH7QuvkHx354U7J7etp/+x+6dk6FeLJcJHjg+H/MiR4+gD2cs+x1MUzHmzMS4K+eaCOcMbrY0Hwzb5/9u78yjJ0rrM49+734iM3JfKtaoys7pvF223Ou2MjDgjogyocxDBFfWAI+4osqhsLgwj4HpQQRDQQY6j6DjAwdEREVsHaUAsx6bp5XbX1lWVS+1rZuz3zh9vRGZWUZWVmZUZERnxfM6Jc7NuZES9dTs744k3fu/vDVyfiZ4JBjODmtlvpnp9vuOY2fzublO609W1bZ/oiIhsNwX/bVCsFDm3fI4L+QsslZcoV8srC3BVm98AlYrZ8fbyVbPjbbGEXShCkoKzpsOObd9yQ6yBj378tiUb29l/Pk1TFksXVgL+F64d4dGl4+RwO3A2AAAgAElEQVST4rqP63G6zGx+z918Vfc9HMzuw2vBvRcKBw8wf/AVLJTK2Mt5kmymdWr6kwT/5AKZJ54yQf/xpwhOzGOl6//3Lw/2k49mKUQz5njXdEMWKCdpQqlaIufluGtwipyf2/G/U27iZvX5w8OmjEdvwERkl2i9xLALJGnC6WunObd8jqXyEsVKEc/28BzPHG/S41y2Qb1M5/JVnGtLWIUidrFoZpQtCzzP7HgLm9q9tBH9569Wlvni0rHrgv658vozygAz4Tj352a4PzfLA90Rs5mJXdWVJfW9prfstK8umVn8Jw6TefwwmfgIztL6u4xVMyGFu6avC/rbsVHWZlSqFapU6Q/7Ge8eVzlPoxUKqs8Xkbaj4L8F+Uqex84+Rk/Qg2M5qtPfbrWAby/nca5cpefI0zilMtmzl02ZjuuCV/vR9TxS784C0Xb3ny8nFZ7Mn+SRaybgf+HaUY4VFkjXKdkBGPJ6uT83y31ds9yfm+XLuqbpdvWztSnVhODE3GrIf+Iwwcn5dR+SWhbFfRPk7zlA/p5ZCtEsxamJlTeRjVasFnFtl+HcMCNdI7vqjd6uVV+Im6Ym6OdysHcv9PerPl9E2op+o22R24LlFbtKmmKVylj5As61JbP5VbGEXS5DuWLKLmobYdnlipnRv0WZzp26k/7zaZoyXzrHw9cOm9n8a0d5bOk4xXV2wgVTm39v1/R1QX/UH1DN9iY5V64SPnGEbC3oh/GRdXvmg2mnWbhn1nTaOXiAwt2zJF3N3VMgTVOK1SKhEzLdN01v2NvU8bS9WtC3CgWSTMbU58/MQG/vjq7REBFptm1Lr1EUOcArgR8C9gJPA78LvCuO4zSKIgt4A/AjwBDwaeAn4zh+YrvGIK3HhPs8zlWz6ZVVLGKXK1jFEqSAbZkZ+/rsquOA4+xIwL+VzfSfP/UfvoKH8k/yhbP12fzD67bTBLCxuCs7uRLw78vNMJuZ2NBuuLJGvZ3m2tn8ucV1H5LaFsX9U7XZ/APkDx6gNDHaMjXZlaRKJa3Q6/cw0ztL6AQK/Tuh3nHHslY77gwPk+/rM2t/oqjZIxQRaYjtnLb+eeB1wFuAzwL/AXgHkAV+FfiF2v0/BxwH3gR8MoqiZ8RxfPtiZ2ld5Qp2sYh9dQl7KY9dLmGVytilMlQTsKmF+1rQte2W2PxqrZv1n69a8OgIfG4CPjsJn5uEx0YOkT5xaN3nGvUHuT83w31ds3x5bpaDXfvpclrr37sbuBcumVn8Jw6vdNq5XTvNSk83+YMm4OfvOUD+7pmW+1kD047TxqY/289obhTXdjl2+Vizh9U+qlUT9B3HBP2+PhgZ+dKOOwsLzRujiEgTbEvwr832vxr4tTiOf7l2+pNRFA0Dr42i6N3Aa4FfiuP4t2uP+RTmU4EfBH5zO8YhO88qlbGvXsO5dAW7UDCz+NUqKRa4zmo9rGWRBrtnEVzh4AEefsV3cuwTf8rnJkzY//wELN3mn5C1Q+7LTddC/gHuz83u6AZZ7coqlgiPmB1wM08cNjvgnj2/7mNS26Yws3c15N9zgPLYSMvM5t9MvR3nZM8kA5nV0q5itcS5ymW6ba3p2JK1QT+XM7X59aDfwj8PIiKNtl0z/j3AB4EP33A+BoaB5wA54GMrd8TxxSiK/gF4Pgr+LckqlU0f/IuXV0N+pbpSe0+tk86dLq5thkJS4tFal50vXDvCw9eOsDhwHr7r1o+xsDiQmeD+3GrIn81M4Gjx5eakKd7CmZWAn3niMOHRE1jV9ddYlAf6yN9zgEI0a2rz75reVPemZqgmVcpJGSyLnNvF3YN76fJXN1T7zMUv8I6jf8JHFh+knFbwLIcXXX4OPz39Ep7Zf18TR97iksR03bHt1aC/Z4+Z3VfQFxG5JSu9Te/qOxFF0SeAe4C3A+8EgjiOS2vu/y3gW+M43r+Z5z106FCazTZnZiyfz7NUWeJ4/jgZt7kLAreTVS7jLuXxr17DKRRxi2Uzk29ZJJ7b1BfTctkslPW2+AajlFY4Xl7kqdIcT5XneLI0x9HyAlWSdR/Xb3Vx0N/LPcFe7vGnuNufpMtuvbKRnXCn13wtZ7lA77GT9B47Qc/Rk/QePYF/7TbtNF2Xq/smuDwzxeXZvVye2Uuxv7elQ12SJpTTMhYWnu3hOz6hHZLzcwR2gGNfv6bjTy58gp9feN9NN2izsXjL2A/xPQPPbdTwW1uSQKmEZVkk2SzVbJbq4CDpHQb9fN7sgp3JtM/v8lam6914uuaN1wrXfHl5mQceeOCmvxx3rDVNFEUvB74R+CnMJwLFtaG/5mrtPmmgjYT8xHVM6c4uU0rLHCsv8mRpjsPleZ4qzXGsvEiF9WeTfVwO+BMc9KdM2PenGHH61GVnk5zlArm5RXKnFuk9fpKeYyfpWjh7282xlkcGuTy9GvKvTY6atq0tqppWqSQVbNvGs0zIz7gZcl4O3/Zv24LzX5bjW4Z+gISUn194H/eE+/jK7N078U9obWmKVVuMm2QyJLkc1YEBEu2KKyJyR3bklTWKou8F3gP8OWam//Vwy0Yt60+73sLBgwe3Nrg79Pjjj5OUE/bv2d/a/fvr7TJLJbPoNl/40nKd3n7oa/1gOzc3B8DExMR154tJiXj5JI8tHePRpeM8unScw/lTVNLbt+XcF45yf23x7f25We7O7sVXi9YVt7rmKyoVglMLBMdPERw7QXD8FOHxk3hn1q/LB6hmM2ZjrFpLzfzdM1T7Vt//99BaswGVaoVKWsGyLAInJHQDurwuusMeQifY0pvD1x167y1Df11Cyp8V/54X3fu8rQ5991jbR7/edWdkBHp6djToP/7440DzXk86ja534+maN14rXPNDh27dhGTbk04URa8Gfh1Tz/+9tVael4EgiiIvjuO1Dc67AXX02apKBbtUxlrOm51sS2VTl182R7DAqm145W7fhlfNUEzLPHz1MI8uHePR5eM8tnSMw8tzty3XAZgKRri3a5p7u/bzjK5pntG1n16367aPEyBNcc9dIDh2kvD4SYJjJwmOnyI4Nb+xfQ9si+K+SRPwIxP0S1NjLTtrW6qWSNIE27IJ3IDADcllc3QHOYIthvwbFaslPrL44Ia+98MLD1Kslgic3bNQfsPqO+Nms+qjLyLSINsa/KMoeitmdv+DwA/GcVyp3fUUYAHTwJNrHjKDWQAsN5MkJswXimaTq0IRqxbq7VLZvGiSguOSrq3DdxzSzO598bxcWeJw/hSPLz3NY0vHePjyYZ4unyGZu33I3xeO1gL+fu7NTnOwax89CvkbYi8tExw/RXD8JLkvPkFubpGehTM4t6nHr0sCn+LeCYr7pyhOT1KY2UfhrunrNjxrJfWFtysz+V7ISNcI3X43vrtzQfty5RrltHL7bwTKaYUrlSWG2yH4l0pQqazujLtvn2mz2cIlXSIi7WY7N/B6JSb0/xbwqjiO136O/RBQAF6I6elPFEX9wNcBb96uMexWVm3W3r1yFStfwC5VsMolqFSxksSU5Xju6kzYLmuVeStXK8scyc/xVP4Uh/NzHF42x7PlS7d9rIXF/nCUZ9RDftc0B7P76HZbuPyqRdjLefxTC/gn5wlOzLGZMh2A1LIoje+huH+yFvKnKOyfojw6sroRWwsqVoukaYpre2TckN6wl76gj4yXaehajl43h2e5Gwr/nuXu3jeulYoJ+75vgv7kJAwMwC78xFFEpF1sVx//MeBXgEeADwFfHV2/E+I/A78DvCWKogQz6/9G4Arw/u0Yw65QrmAvL5tdbJeWsUtl7EKxtsmVZVpk1ksgauU5jdzBdqcsVfO1YD/H4fwcR2pBf7F0YUOPt7CYcoe5v/cA99ZDftc+upzWnEluCWmKc/EywakF/BNzBCfn8U8uEJycxzu3sesOUOnrobh/isL0lAn5+ycp7p1o+TaalaRKOSmZkh0nJOOFjOZGyfndeE5zZ5gDx+fbRr+eP1v4xG2/90VjX797ynzqQd/zTNAfHYWhIQha+2dFRKSTbNcr4POAALgP+MxN7h8G3oBZyPtaTE//h4CXtuWuvZUKdr6Ac/kq9nIeu1jGKhaxqhUzW+/5KzOj7TBzX7dcLXA0P29C/sos/hzzpXMbfo4uO+RAdpIDmQnuzk6ZevxLHhk7uPVC005WTfBOn60F+3mCE/P4p+YJTs5vuEQH1pTp1Gbv57ozXJsYZeRgdPsHN1mappSSEmma4jkeoRPSF/bRG/Q2fDZ/o1418xL+fOGTJOusUbGx+enplzRwVJtU76Vf3zRrcND00lfbQBGRlrUtwT+O4w8AH9jAt76udmsP1arplnPlGs7SMlaxhF00XXNSy4K15Tm+R0p7fMRdTiocLywQL5/kyeWTK+U6c8VzpBv8jCJjBxzITDCbmeCu7CQHMibsj/oDXxLU5q7M7cQ/Y1exiiX8UwurAb82g+/PLWKXy7d/gppqJqQ0OUZx7zilqXFKk+MU9k9+SZnOxbnWveb12vz6AtyMl2EsHCfn5Zo+m79Rz+y/j3ff9zp+7JG33zT829i8577Xt9YmXmlqgj5od1wRkV1qd7xKthirUKD7qS8Q2uYj7NTb/V1zbiZNU86UL/Lk8imeXD5hjvkTHMnPb6hlJkBo+8yE47VwP2ECfnaCMX/wtr3OO5V74RLBkacJjzxNePRpgqMn8OdP37YX/lqV/l6KUybcF6fGascJKkP9uzKklatlqmmV0MvQl+ljMDu05VaareKH972I+3vu4h3H/pgPL6zu3PvisW/gldPf0xqhv1BYbbHZ0wMHDux4i00REdk5Cv5bYFWrWElK2tU+u7guVws8lT/FU8uniJdP8OTySZ7Mn+Jy5dqGHu9bHtOZMe6qzdzXy3UmgmEcBfybSxL8+dPXhfzw6Ancixurfktti/Ke4TUBf5zS3nGKk+Mk3bt0QegaxWoRgC6vi6HMEP3Zftw222vhmf338aH+t1Gslnjk6GPk7Cz3zDZpw64kMb30wZTrdHXB/v2m845abIqItIX2ehWV26qmCSeLZ3hy+STx8omVoH+qeHZDZToWFlPBCFF2irtrt7syk0yGI7iWwsGtWKUSwbFTtRn8WtA/dtIs7r6N1HEoTo2b8py9Zua+NDVOaWIPqd8+a0TSNKVYLeJYDl1+F+Pd43QH3R3xyVDg+Ay6vY39S+uLcR3HhPzublOn392tGX0RkTal4N+mykmFueJZjhUWOF5YNHX4y6d4Kn+KQlLa0HP0uTmi7BR3ZabMMTvFgcwEWad9PunYCfbVaybYHzEz+MGR4wQnF0xr1tuoZkKKs/sozO4zffBn91GaGjcdn9pQJalSScr4jk+3383+7H6yvlqybrv6zrhJYvroZ7Nms6zBQS3GFRHpIAr+u1i9Bv94fpHjhfrNBP1ThTMb2tUWTK/wmcz4dSH/7uwUw17frq6h3lFpinvxsumHP7dojqcWNtUPvzzYT2F2nwn6tZBf3jPU9rOtpl4/IfRCBrMDDGWGdnTDrI5UrZrZfDAhP5czZTu9veqjLyLSwRT8d4GrleXrQv3x/MJK0M8nty8VWWvMH1wp0bk7Y477w1G8Nqud3i72Uh5/fnE13M+tfu3kCxt6jtS2KE2MmVn82X0UZ/ZSmNlHta9nh0ffOorVIhYWWa+Loeww/Zm+tqvXb6py2dw8zwT9/n4YHjYlPG3+RlJERDZOr7wtopRUOFk8XZu9Xw32x/MLnK9c2dRzeZbL3nAP+8PR1Vtt4e2u3QV0J5Ur+KfPrsza18N9cGphwwtt65LANxterZTr7KW4f6rlN7zaTpWkSjWtmF1yLZdckOuoev0dVy/bSVOzOVZXF4yNmbIdbZYlIiLrUPBvsKuVZY4W5jman+dYfoGjBXM8WTyz4RaZdWP+4HXBfn84xv5wlPFgSJ10bpSmuOcvXj9rXwv33uLZDdXfr1UeHqQ0MUppYpTixCilyTFKE6OU9wxf1w+/nSRpQiWpkKQJYIEFDjau4+JaLo7t4NkevuuTcTMEbkDoaj3IHVu7CLdetjM0ZBbhqtuOiIhsgoL/DkjTlMXSBY7m51eC/bHCPEfy85wrb24GucfpYjozxnQ4yr5asN+fGWVvsIeMo9m9G9nXltaU4ywSzC3gn1rEn1/cUAedtaq5LKWJMYqTJuDXw31pfA9p2D6BNk1Tqkm19sbTdHYqJxUc28ayLFzbxbVdfMcndEJCL8SzPVzb1RqQ7VbfJKs+m792EW4Y7so9GEREpHUo+N+BUlLm6cIiR2vB/mh+wczkFxY2VXvvWg57gz3MZMbZH44ynTEBfzoco8/r3sF/we5klcp4C2cIVmbvV2fx3UubK4tKXJfSxB5KE2PXh/uJUaq93W0ZtErVEkma4DkeoRMSuCGhG5JxQzzHBPq+wgkApoemmzzaNlefzbdtUschCUM4eNBskuXq17OIiGwvvbJs0mMXH+OdD7+DI5di5krnSDbQ+76u28kykxlnOhxbOc5mxpkIhrW49kZJgnv2AsHcApOPxmRPn2Xg0lX8uUW8M+ewko1f99SyVktzJsdM0K+X5gwPtW1pDkA1qVJOKgCErpmtH82NkvO78Rz9zDXU2paa9dn84WFTtpPJUHziCfN9AwPNHaeIiLQtvfJv0psPvZlHLjyy7veM+oPMrgT8MWYyE0yHYwx5vSqNWCtNcS5eNrP184u1kpzTZgZ/4Qx2qbypp6v0dFOql+VMjJpZ/MlRSmN7SIPOaBdZb5Xp2g6hm6E76KY/7CfjZbSwttFKJdNW07ZNr/xsFqanzWy+WmqKiEgTKPhv0jNHnskXL3wR13JWynJmwnFmMua2LxylSxtcXce+em3NgtpasJ8/jT+3uOGWmHUpkHRlKRzYT/7gAVODPzFKaXKUpDu3M/+AFpWkCaXEvDkKHLOgdrhrmB6/R33xG61UMmU7jmNCfiYDExPQ12dq80VERFqAgv8mver+V/H9499GduFJsj2DzR5Oy7DyhdVwP7825C/iXr22qedKbZvyniESzyM4Mcfaz0gswFlaJvvI41z5j1/N5W/82m39d7Sy+i63tmWTcTPk/G76wl6yXhbHVneXhlHIFxGRXUrBfwu63CyO1WFBq5rgnr+Av3gW7/Q5vNNnzW3xLP78abwLlzb9lOXhQUrje9aU5tRue4bJHD7Gvte+hVsVRllJyui7PkBhei+Fgwfu7N/WouqLcH3HJ3RDBjPd9IQ9apHZSOuF/CBoy8XfIiLSvhT8xUgS3IuXV8K8d/oc/pqvvbPnsaqb22cAoNLf+6XhfnyU0tjIuptaDXz047ddwGslKQMf/WvmD75i0+NqNWmaUkpKpGlK4AZk3AwjXSP0BL1ahNsIlYq5JYmpyc9mFfJFRKTtKFF0ijTFuXzFhPjFs/g3zNp7Z85jlze3mLbO9LuvLaZdG/LHR0m6Mpt+PqtUpvuhf97Q9/Y89M8slMqk/u5aLJmmKcWkBEDohGT9DOPhODk/h6sOT9srSaBcNsHeskyw97zVm++bkJ/LmaNCvoiItCkljDZilUom1C+exVs4g7d4xny9eMZ0ySmWtvS8SeBT3jNMec8QpdFhyiNDlEdHKO8ZorxniGp3bluDkr28jFXZ2KcLVqWKvZyn2uLB37TVLGNZFhk3Q9bLMpXpp8vPqtvOnUhT0zln7ZtW1zU33zfBPghMqO/qMudcV8FeREQ6koL/bpKmOJeu4C+ewVswYX4l3C+cwTt/cUtPm7huLcSbcF+uhfvS6DDlPcNU+3oaGpSSbJbUdTYU/lPXIclu/lOFnbZ2IW7WzdKd6WYgHCDjZdTSdSvqtfaWZcL72lCfzZpQHwTmvK03UiIiIjej4N9irFLJlOMsrJmtXxP0tzJrn9o25eEBE+j3mFtp5eshKgN9LRWWUt/j6td8FT3/93O3/d4rX/NVTS/zqSZVymkF0hTX9si4IX1hP/2ZPgInUNDfqDRd7X1vWSbIh6E59vSYWxi21M+qiIjIbqLg3yhpin1tGe/8Bdzzl3DPX8Q9fxHv/EXcCxdxz13EvXAJ98IlrHTju9LWVbuylMZGKI8OUxodoVz/emwP5eEBU96wi5x/4fPp/sd/WneBb2pbXHjh8xs2piRNKCdl0jTFtmx8JyBwTcedHr+H0AtVn78Ra3ewtW0zSx+Gpr6+pwe6u82f9YZJRERkWymlbAOrWLo+yJ+vhfhzF/AuXFr581Zr7MGE3PLwIOXRERPwx0ZMwB8dpjQ20nabVxUOHmDxJ17G6Ls+cNPwn9oWi6/4gR1p5ZmmKeWkTJImWJaF7/grLTW7/W6yXhbPae01BS0hScwMfj3g12fwMxno7TV191pIKyIi0jAK/pvkHz3K0Pt/j/DYU3iXruKdv4RzbWlbnrvSk6MyNFgL9qsz96XREcojg7tu1v5OXfrm51CY3kvmTz7CyL88il2tkroOV571b7nwrc/bltBfqVYop2Usy8a3PTOL7/jk/Bxdfhe+46tUZyOSxMzip6kJ85mMqb3v719dVKvrKCIi0lSdlSS3wdgb30j24Yc39Zgk8CkPDVAZ6KMy2E9lsJ9y7VgZ6KMyZI6p7+/QqHevwsEDHPmRl2CVK0z19ZNkMxuq6a8kVZK0SpImtTMmdDqWjWM7uLaL7wbkMl3kwm4Cx1d3nY2qVk3Ih9UZ/GwWBgfNLL7TYZvbiYiI7BIK/ptUuPfeleCf2vZKmF8J8oN9VAb6KQ/1UxnopzJkwqpmO7cuJaXiwnJ3QJpWoWLCvGWBY7k4to1jOeZmO7iWi+t4hG6AZ3u4jotjubi2o9n7zapUVltl1mfyczkT8rNZhXwREZFdRMF/k06/6U3Mffu3Yp87jD0+CY5mibdLvQUmWASuT+AEuLZLt9eNZ3vM9M3guT5uLeBrhn6bVSqmJt+ySNOUNAxhdBQGBky5jrrpiIiI7GoK/ltQHt2DUzmDr9C/ZfUNrbAsfMcjdEL6wi56A9MdZ22oTy6aGf6esKdZw20f9V1sq7U9EuqLbusddfr7IZulGMfm/n37mjdWERER2VYK/rLjbgz5gRPQF/bRE/SQ8TKaud9O9U461aoJ9ba9utFV/djdff0utiIiItIR9Kov22ol5AO+4xO4Ab1hL71Br0L+dqhWzYx9Ulu07DjX72QbhibYZ7MK9iIiInIdpQLZkkpSpZpWSNMUWJ3J7w176fHNTL5ja+HnplUq5pYktdXLzvUz9vVgn8mYc1pcKyIiIhuk4C/XSdOUappQSSqA2TjLtmxcxzXdcmxzC9yAjJvBdwN821PI36i1XXLAzMivDfb1rjmZjJmxV7AXERGRbaLg30GSNKGaVKmSmI2WLAuHNaHecfFsn9AJCL0Q3/FxbVehfqPSdDXY19uGep651ctxslkT7MPQ/FmdckRERKRBFPx3uWpSpXrdRlVgWdZKT/uV/vaOi2e7ZNwMoRuu9LdXzf0GVaurZTj1sF6frfc88/XaPvdBoN1qRUREpKUo+LeYJE1IkoRKWiUlwbJsSNOVIG9bTm0W3sa1XDzHJ3B8fMfHc7yVXWllg+qz9JWK+RpW6+rrgb5eW5/Nmlv9PoV6ERER2UWUEJskTVNKSYk0TbEsi8AJVrrgBE5I6Aa4jlerq9eOs1t2YxecepCvd8HxfTNL39W1WmevunoRERFpQwr+DVCpViinZSzLxrc9fCcgdAJyQY4urwvP8RTst6q+IVW9BMe2V+vpff9L21sq1IuIiEiHUvDfRtWkSjk1JSOu7eI7Pr4b0JXJ0h10E7iBauo3K02hXMaqVCCfN+U1a4O9NqQSERER2RClpC0qV8sklcJ1ZTqZMEO3303oZvAcXdoNqZfiVKvX962vl+IEAaXJSdJsFu6/35wTERERkU1TOt2CwAkYHzhAtncQ3/FVprOeW/WtX7vTbC637k6zSalkvlDoFxEREdkyBf8tcG2X/kwfuEGzh9JctTKclb719TKcm/Wtr7e3VN96ERERkaZQ8Jf1JQmUSuZoWdeH+vpsfS63GvhFREREpCUp+Mv15Tg3Lp4NQ+jpMTP3QaAZexEREZFdSsG/XaWpuSXJ6rG+gLbe8rJefpPNmnAfhtptVkRERKRNKfi3grWbTN0YuutBvX6r19LX/1zvS7/2e+rf5zhmsWz9mMmsblIlIiIiIh1FwX+n3SzU1+vh67cwNH3os9nVoF4P9yIiIiIi20DB/06sDfVwfVebm4X6+jkRERERkQZT8N+CxPNMJ5tMxoT6TEZdbURERESkpSn4b4Xvwz33NHsUIiIiIiIbpiJyEREREZEOoOAvIiIiItIBFPxFRERERDqAgr+IiIiISAdQ8BcRERER6QAK/iIiIiIiHUDBX0RERESkAyj4i4iIiIh0AAV/EREREZEOoOAvIiIiItIB3Eb/hVEU/RDws8Ak8K/Aq+M4/kyjxyEiIiIi0kkaOuMfRdFLgfcAfwS8GLgEfDyKoulGjkNEREREpNM0LPhHUWQBbwbeG8fxm+M4/ivgBcA54FWNGoeIiIiISCdq5Iz/AWAf8LH6iTiOy8BfAs9v4DhERERERDpOI2v8764dD99w/igwG0WRE8dxdaNP9vjjj2/bwDYjn8839e/vRLrmjadr3ni65o2na95Yut6Np2veeK1+zRs5499TO1694fzV2ji6GjgWEREREZGO0sgZf6t2TG9xf7KZJzt48OCdjWaL6u/gmvX3dyJd88bTNW88XfPG0zVvLF3vxtM1b7xWuOaHDh265X2NnPG/XDt233C+G6jGcXytgWMREREREekojQz+T9WOMzecnwGebOA4REREREQ6TqOD/0nghfUTURR5wLcAn2zgOEREREREOo6Vprcqud9+URT9OPBO4G3Ap4FXAF8LfEUcx0c3+jyHDh1q3KBFRERERHaRBx54wLrZ+YYGf4Aoil4DvBIYAv4VeE0cx59p6CBERERERDpMw4O/iMiVON4AAAeUSURBVIiIiIg0XiNr/EVEREREpEkU/EVEREREOoCCv4iIiIhIB1DwFxERERHpAAr+IiIiIiIdQMFfRERERKQDKPiLiIiIiHQABX8RERERkQ6g4C8iIiIi0gHcZg9gt4mi6BuAtwL3A2eADwD/NY7jajPH1Y6iKHo28OA637I/juOnGzScjhBFkQO8BvhhYBR4FHh9HMd/19SBtbEoinLA24HvALLAQ8DPxnH8cFMH1oaiKHoB8D/iOO5ec84C3gD8CDAEfBr4yTiOn2jOKNvLza75Dfe/Bvj+OI6/orEja1+3+DnPAG8Cvgvzu/0p4O1xHP9pc0bZXm5xzXuBtwHfBuSAvwNeHcfxkeaM0tCM/yZEUfQs4P8AjwPfArwT+DnM/0yy/f4F+Pc33L4eOA/8DXCyeUNrWz+DeWP7B8ALgSPAX0dR9JVNHVV7+1/Ay4BfA14MLAKfiqIoauag2k0URV8D/BFg3XDXL2B+h/868N1AL/DJ2ou23IF1rnn9/m/HvOmVbbLONX838BPAOzC/2z8FfCiKou9s7AjbzzrX/I8x1/pnMW+4RoC/j6Kop7EjvJ5m/Dfn7cDfxHH8stqf/y6KokFMGH1z00bVpuI4vgJ8du25KIreAaTA98VxnDRlYO3tpcAfx3H8VoAoih4Evhb4QeAVzRxYO4qi6AHgPwE/Gsfx79VO/00URXcBbwH0onyHoigKgFdirucS4K+5rxt4LfBLcRz/du3cp4CnMT/zv9nwAbeB9a557f4e4BeBVwGXGj7ANnSbn/MRzO/2l8dx/Pu1038bRdEs5uf/zxo83LZwm2v+DOCbgRfHcfzh2rlHgePACzBvFJpCM/4bFEXRMPAs4L1rz8dx/Lo4jp/dlEF1mNr/SK8A3hTH8dlmj6dNBcCV+h9qJWyXgYGmjai93V07fvyG858GntfgsbSrbwJej/k063duuO+ZmI/gP1Y/EcfxReAfgOc3aoBtaL1rDqaU8Ltrt79q4Lja2XrXPAe8B/NJ+VoxML3zQ2tb613zo5jfL2t/vku1Y7DzQ7s1Bf+Nuw/zMc5SFEV/EUVRIYqiM1EU/VIURbqOjfHLwJPA+5o9kDb2LuD7oyj6hiiKeqMoeiVwL/ChJo+rXdXL1fbecH4a6ImiSG+47tzngenajH56w331N1431tweXXOfbN561xzgI8BsHMeaad4+t7zmcRwfjeP4x+I4XimPra3n+iZAa1m2br1rXojj+HNxHBeiKHJrE5d/AJwGPtqEsa5Qqc/GDdeOH8TUbf0m8HWY2tA88CtNGldHiKJoBvPx2A+rxGdHvRt4DvC3a869KY7jj93i++XOfB7zZvZ3oyh6GXAYUwv6zbX7u4ALzRlae4jjeG6du3uAYhzHpRvOX63dJ1twm2tOsxc3tqPbXfObeDNwD+Z1VbZgE9f8fZh1XAnwX+I4Pr9jg9oAzVRvnFc7fjyO45+J4/jBOI5/CfPx2Ztq755l57wcuEgT6+LaXa27yccxH0/+OGbtyi8DvxhF0U80c2ztKo7jIvAioIp5E3ARU4v7q7VvWW7S0DqFxc1npMG8SIu0nSiKfg54I/AbcRz/RbPH0wHqE2rvBD4QRdHLmzkYzfhv3LXa8a9vOP8JzEr5/Xzpx8WyfV4IfLQWlGRnPAuzkPc74zj+n7Vzfx9FkQv8ahRFfxjH8bVbP1y2Io7jR4Evj6JoCnDjOD4WRdEvYoLn5eaOru1dBoIoirw4jstrznejay9tpja58xuYRdW/i6lNlx0Wx/E/1b58MIqiSUz74Pc3azwK/ht3uHb0bzhf/yTgVrNGcoeiKNoLHMR0H5CdM1U7fvaG8/+IaVu7H/hiIwfU7qIoymJaeH5ybf0tZp+QL8ZxXGnOyDrGU5hZ/2lMyVXdDGbho0hbqK1F/EPg+4C3xnH8xiYPqa3VypOfDfz3OI7X5sP/h2kH3zQq9dm4x4A5zCY7a30LMI9p0SQ749/VjjcGUtle9eDzrBvOfzVQAU41djgdoYwpF/zu+okoiqYxNf7/u1mD6iAPAQXMJ4oARFHUj1m/9clmDUpkB/wGJvS/RqG/Ie4Gfh8T/oGVT1yeCzzSpDEBmvHfsDiOkyiK3gD8YRRF7wb+HPhGTD3uj2nB6Y76MuBcHMda5LiD4jg+FEXRX2IWmg5gNqp7Nma2/7fiOFa/7W0Wx3E5iqL3A2+MougMppXqrwBnUQ/5HRfH8bUoin4HeEsURQnmze8bMf8dmvZRvMh2iqLo32D6zX8CeCiKomeuubsax/HnmzOytva3mMnKD0RR9EbgHGZvkGdhuik1jYL/JsRx/MEoisqY+qwfwLTi+9E4jt+7/iPlDo2gTV4a5TuA/4YJPwOYUoifAn5vvQfJHXkdplTw14AQs637zzS780MHeQNmPcVrMf3OHwJeGsexavylXbwAU9L23NptrSXMz71soziOK1EU/WfgbZjJnAHgEPDcOI4fbObYrDRVabqIiIiISLtTjb+IiIiISAdQ8BcRERER6QAK/iIiIiIiHUDBX0RERESkAyj4i4iIiIh0AAV/EREREZEOoOAvIiIiItIBFPxFRERERDrA/wdje7F4/Uy8hAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115c962e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "with sns.plotting_context('poster'):\n",
    "    pplowmed = np.median(ens_pp_low, axis=1)\n",
    "    pplowhpd = pm.stats.hpd(ens_pp_low.T)\n",
    "    pphighmed = np.median(ens_pp_high, axis=1)\n",
    "    pphighhpd = pm.stats.hpd(ens_pp_high.T)\n",
    "    plt.plot(df[df['clevel']==1].logpop, df[df['clevel']==1].total_tools,'o', color=\"g\")\n",
    "    plt.plot(df[df['clevel']==0].logpop, df[df['clevel']==0].total_tools,'o', color=\"r\")\n",
    "    plt.plot(lpgrid, pphighmed, color=\"g\")\n",
    "    plt.fill_between(lpgrid, pphighhpd[:,0], pphighhpd[:,1], color=\"g\", alpha=0.2)\n",
    "    plt.plot(lpgrid, pplowmed, color=\"r\")\n",
    "    plt.fill_between(lpgrid, pplowhpd[:,0], pplowhpd[:,1], color=\"r\", alpha=0.2)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The ensemble gives sensible limits and even regularizes down the green band at high population by giving more weight to the no-interaction model."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Hierarchical Modelling\n",
    "\n",
    "**Overdispersion** is a problem one finds in most poisson models where the variance of the data is larger than the mean, which is the constraint the poisson distribution imposes.\n",
    "\n",
    "To simplify things, let us consider here, only the model with log(population). Since there is no contact variable, there are no counterfactual plots and we can view the posterior predictive."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PolyCollection at 0x113f09b70>"
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x114f8c748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ppsamps = compute_pp(lpgrid, trace2c_onlyp)\n",
    "ppmed = np.median(ppsamps, axis=1)\n",
    "pphpd = pm.stats.hpd(ppsamps.T)\n",
    "plt.plot(df[df['clevel']==1].logpop, df[df['clevel']==1].total_tools,'o', color=\"g\")\n",
    "plt.plot(df[df['clevel']==0].logpop, df[df['clevel']==0].total_tools,'o', color=\"r\")\n",
    "plt.plot(lpgrid, ppmed, color=\"b\")\n",
    "plt.fill_between(lpgrid, pphpd[:,0], pphpd[:,1], color=\"b\", alpha=0.1)\n",
    "#plt.ylim([0, 300])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "By taking the ratio of the posterior-predictive variance to the posterior-predictive mean, we see that the model is overdispersed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ppvar=np.var(ppsamps, axis=1)\n",
    "ppmean=np.mean(ppsamps, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1.30421519,  1.26489919,  1.2693647 ,  1.20461164,  1.25536688,\n",
       "        1.19957498,  1.1793642 ,  1.17456651,  1.14728935,  1.15605154,\n",
       "        1.09427345,  1.12326509,  1.13490696,  1.09674559,  1.12324651,\n",
       "        1.10038695,  1.11064864,  1.11575808,  1.11499395,  1.14792792,\n",
       "        1.15350445,  1.18526221,  1.22732124,  1.29480132,  1.30994366,\n",
       "        1.41243637,  1.48317552,  1.58211591,  1.67981142,  1.79674707])"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ppvar/ppmean"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Overdispersion can be fixed by considering a mixture model. We shall see this next week. But hierarchical modelling is also a great way to do this.\n",
    "\n",
    "### Varying Intercepts hierarchical model\n",
    "\n",
    "What we are basically doing is splitting the intercept into a value constant across the societies and a residual which is society dependent. It is this residual that we will assume is drawn from a gaussian with 0 mean and `sigmasoc` ($\\sigma_{society}$) standard deviation. Since there is a varying intercept for **every** observation, $\\sigma_{society}$ lands up as an estimate of overdispersion amongst societies."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [],
   "source": [
    "with pm.Model() as m3c:\n",
    "    betap = pm.Normal(\"betap\", 0, 1)\n",
    "    alpha = pm.Normal(\"alpha\", 0, 100)\n",
    "    sigmasoc = pm.HalfCauchy(\"sigmasoc\", 1)\n",
    "    alphasoc = pm.Normal(\"alphasoc\", 0, sigmasoc, shape=df.shape[0])\n",
    "    loglam = alpha + alphasoc + betap*df.logpop_c \n",
    "    y = pm.Poisson(\"ntools\", mu=t.exp(loglam), observed=df.total_tools)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Auto-assigning NUTS sampler...\n",
      "Initializing NUTS using jitter+adapt_diag...\n",
      "Multiprocess sampling (2 chains in 2 jobs)\n",
      "NUTS: [alphasoc, sigmasoc_log__, alpha, betap]\n",
      "100%|██████████| 6000/6000 [00:15<00:00, 386.45it/s]\n",
      "The number of effective samples is smaller than 25% for some parameters.\n"
     ]
    }
   ],
   "source": [
    "with m3c:\n",
    "    trace3 = pm.sample(5000, tune=1000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice that we are fitting 13 parameters to 10 points. Ordinarily this would scream overfitting, but thefocus of our parameters is at different levels, and in the hierarchial set up, 10 of these parameters are really pooled together from one sigma. So the effective number of parameters is something lower."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x115b51198>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x115e669b0>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x114fe6b38>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x116842588>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x115eeeb00>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x1162fdcf8>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x1188bf5f8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x119c85400>]], dtype=object)"
      ]
     },
     "execution_count": 128,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1155edef0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pm.traceplot(trace3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0"
      ]
     },
     "execution_count": 129,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.mean(trace3['diverging'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\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>mc_error</th>\n",
       "      <th>hpd_2.5</th>\n",
       "      <th>hpd_97.5</th>\n",
       "      <th>n_eff</th>\n",
       "      <th>Rhat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>betap</th>\n",
       "      <td>0.259400</td>\n",
       "      <td>0.079289</td>\n",
       "      <td>0.001079</td>\n",
       "      <td>0.103152</td>\n",
       "      <td>0.421723</td>\n",
       "      <td>4488.0</td>\n",
       "      <td>0.999985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>alpha</th>\n",
       "      <td>3.448287</td>\n",
       "      <td>0.120423</td>\n",
       "      <td>0.001770</td>\n",
       "      <td>3.200975</td>\n",
       "      <td>3.677543</td>\n",
       "      <td>3919.0</td>\n",
       "      <td>0.999915</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>alphasoc__0</th>\n",
       "      <td>-0.210082</td>\n",
       "      <td>0.243427</td>\n",
       "      <td>0.003397</td>\n",
       "      <td>-0.728636</td>\n",
       "      <td>0.234597</td>\n",
       "      <td>5045.0</td>\n",
       "      <td>0.999912</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>alphasoc__1</th>\n",
       "      <td>0.035751</td>\n",
       "      <td>0.218266</td>\n",
       "      <td>0.002822</td>\n",
       "      <td>-0.380003</td>\n",
       "      <td>0.503895</td>\n",
       "      <td>6020.0</td>\n",
       "      <td>0.999900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>alphasoc__2</th>\n",
       "      <td>-0.050208</td>\n",
       "      <td>0.192201</td>\n",
       "      <td>0.002430</td>\n",
       "      <td>-0.435754</td>\n",
       "      <td>0.335806</td>\n",
       "      <td>6532.0</td>\n",
       "      <td>0.999932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>alphasoc__3</th>\n",
       "      <td>0.322955</td>\n",
       "      <td>0.185538</td>\n",
       "      <td>0.002634</td>\n",
       "      <td>-0.032226</td>\n",
       "      <td>0.692806</td>\n",
       "      <td>4217.0</td>\n",
       "      <td>0.999951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>alphasoc__4</th>\n",
       "      <td>0.038710</td>\n",
       "      <td>0.176232</td>\n",
       "      <td>0.002034</td>\n",
       "      <td>-0.315874</td>\n",
       "      <td>0.383337</td>\n",
       "      <td>6676.0</td>\n",
       "      <td>1.000008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>alphasoc__5</th>\n",
       "      <td>-0.320876</td>\n",
       "      <td>0.206979</td>\n",
       "      <td>0.002859</td>\n",
       "      <td>-0.745401</td>\n",
       "      <td>0.055176</td>\n",
       "      <td>4959.0</td>\n",
       "      <td>1.000079</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>alphasoc__6</th>\n",
       "      <td>0.140740</td>\n",
       "      <td>0.172141</td>\n",
       "      <td>0.002258</td>\n",
       "      <td>-0.185500</td>\n",
       "      <td>0.497224</td>\n",
       "      <td>5333.0</td>\n",
       "      <td>0.999988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>alphasoc__7</th>\n",
       "      <td>-0.172323</td>\n",
       "      <td>0.185173</td>\n",
       "      <td>0.002393</td>\n",
       "      <td>-0.548562</td>\n",
       "      <td>0.189961</td>\n",
       "      <td>6245.0</td>\n",
       "      <td>1.000587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>alphasoc__8</th>\n",
       "      <td>0.272111</td>\n",
       "      <td>0.174620</td>\n",
       "      <td>0.002321</td>\n",
       "      <td>-0.055450</td>\n",
       "      <td>0.624651</td>\n",
       "      <td>4475.0</td>\n",
       "      <td>1.000024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>alphasoc__9</th>\n",
       "      <td>-0.094881</td>\n",
       "      <td>0.282000</td>\n",
       "      <td>0.003884</td>\n",
       "      <td>-0.695863</td>\n",
       "      <td>0.450101</td>\n",
       "      <td>4451.0</td>\n",
       "      <td>1.000008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sigmasoc</th>\n",
       "      <td>0.309760</td>\n",
       "      <td>0.124590</td>\n",
       "      <td>0.002286</td>\n",
       "      <td>0.103297</td>\n",
       "      <td>0.569363</td>\n",
       "      <td>2491.0</td>\n",
       "      <td>0.999920</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 mean        sd  mc_error   hpd_2.5  hpd_97.5   n_eff      Rhat\n",
       "betap        0.259400  0.079289  0.001079  0.103152  0.421723  4488.0  0.999985\n",
       "alpha        3.448287  0.120423  0.001770  3.200975  3.677543  3919.0  0.999915\n",
       "alphasoc__0 -0.210082  0.243427  0.003397 -0.728636  0.234597  5045.0  0.999912\n",
       "alphasoc__1  0.035751  0.218266  0.002822 -0.380003  0.503895  6020.0  0.999900\n",
       "alphasoc__2 -0.050208  0.192201  0.002430 -0.435754  0.335806  6532.0  0.999932\n",
       "alphasoc__3  0.322955  0.185538  0.002634 -0.032226  0.692806  4217.0  0.999951\n",
       "alphasoc__4  0.038710  0.176232  0.002034 -0.315874  0.383337  6676.0  1.000008\n",
       "alphasoc__5 -0.320876  0.206979  0.002859 -0.745401  0.055176  4959.0  1.000079\n",
       "alphasoc__6  0.140740  0.172141  0.002258 -0.185500  0.497224  5333.0  0.999988\n",
       "alphasoc__7 -0.172323  0.185173  0.002393 -0.548562  0.189961  6245.0  1.000587\n",
       "alphasoc__8  0.272111  0.174620  0.002321 -0.055450  0.624651  4475.0  1.000024\n",
       "alphasoc__9 -0.094881  0.282000  0.003884 -0.695863  0.450101  4451.0  1.000008\n",
       "sigmasoc     0.309760  0.124590  0.002286  0.103297  0.569363  2491.0  0.999920"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pm.summary(trace3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can ask the WAIC how many effective parameters it has, and it tells us roughly 5. Thus you really care about the number of hyper-parameters you have, and not so much about the lower level parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "//anaconda/envs/py3l/lib/python3.6/site-packages/pymc3/stats.py:222: UserWarning: For one or more samples the posterior variance of the\n",
      "        log predictive densities exceeds 0.4. This could be indication of\n",
      "        WAIC starting to fail see http://arxiv.org/abs/1507.04544 for details\n",
      "        \n",
      "  \"\"\")\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "WAIC_r(WAIC=70.176914155345884, WAIC_se=2.5510130691737838, p_WAIC=5.0619370952485738)"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pm.waic(trace3, m3c)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We now write code where now we use sampling from the normal corresponding to $\\sigma_{society}$ to simulate our societies. Again, we dont use theano's shareds, opting simply to generate samples for the residual intercepts for multiple societies. How many? As many as the traces. You might have thought you only need to generate as many as there are grid points, ie 30, but at the end the posterior predictive must marginalize over the traces at all these points, and thus marginalizing over the full trace at each point suffices!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def compute_pp2(lpgrid, trace, contact=0):\n",
    "    alphatrace = trace_or_zero(trace, 'alpha')\n",
    "    betaptrace = trace_or_zero(trace, 'betap')\n",
    "    sigmasoctrace = trace_or_zero(trace, 'sigmasoc')\n",
    "    tl=2*len(trace)\n",
    "    gl=lpgrid.shape[0]\n",
    "    lam = np.empty((gl, tl))\n",
    "    lpgrid_c = lpgrid - lpgrid.mean()\n",
    "    #simulate. 5000 alphasocs gen here\n",
    "    alphasoctrace=np.random.normal(0, sigmasoctrace)\n",
    "    for i, v in enumerate(lpgrid):\n",
    "        temp = alphatrace + betaptrace*lpgrid_c[i] + alphasoctrace\n",
    "        lam[i,:] = poisson.rvs(np.exp(temp))\n",
    "    return lam"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {},
   "outputs": [],
   "source": [
    "ppsamps = compute_pp2(lpgrid, trace3)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PolyCollection at 0x118d9d358>"
      ]
     },
     "execution_count": 136,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x117928cc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ppmed = np.median(ppsamps, axis=1)\n",
    "pphpd = pm.stats.hpd(ppsamps.T)\n",
    "plt.plot(df[df['clevel']==1].logpop, df[df['clevel']==1].total_tools,'o', color=\"g\")\n",
    "plt.plot(df[df['clevel']==0].logpop, df[df['clevel']==0].total_tools,'o', color=\"r\")\n",
    "plt.plot(lpgrid, ppmed, color=\"b\")\n",
    "plt.fill_between(lpgrid, pphpd[:,0], pphpd[:,1], color=\"b\", alpha=0.1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The envelope of predictions is much wider here, but overlaps all the points! This is because of the varying intercepts, and it reflects the fact that there is much more variation in the data than is expected from a pure poisson model."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cross Validation and stacking BMA in pymc3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LOO</th>\n",
       "      <th>pLOO</th>\n",
       "      <th>dLOO</th>\n",
       "      <th>weight</th>\n",
       "      <th>SE</th>\n",
       "      <th>dSE</th>\n",
       "      <th>warning</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>79.84</td>\n",
       "      <td>4.63</td>\n",
       "      <td>0</td>\n",
       "      <td>0.93</td>\n",
       "      <td>11.17</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>85.26</td>\n",
       "      <td>4.17</td>\n",
       "      <td>5.43</td>\n",
       "      <td>0.06</td>\n",
       "      <td>8.96</td>\n",
       "      <td>8.01</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>89.92</td>\n",
       "      <td>9.96</td>\n",
       "      <td>10.08</td>\n",
       "      <td>0.01</td>\n",
       "      <td>13.53</td>\n",
       "      <td>6.11</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>141.77</td>\n",
       "      <td>8.44</td>\n",
       "      <td>61.93</td>\n",
       "      <td>0</td>\n",
       "      <td>31.74</td>\n",
       "      <td>32.63</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>151.24</td>\n",
       "      <td>17.34</td>\n",
       "      <td>71.4</td>\n",
       "      <td>0</td>\n",
       "      <td>44.91</td>\n",
       "      <td>44.37</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      LOO   pLOO   dLOO weight     SE    dSE warning\n",
       "1   79.84   4.63      0   0.93  11.17      0       1\n",
       "2   85.26   4.17   5.43   0.06   8.96   8.01       1\n",
       "0   89.92   9.96  10.08   0.01  13.53   6.11       1\n",
       "4  141.77   8.44  61.93      0  31.74  32.63       1\n",
       "3  151.24  17.34   71.4      0  44.91  44.37       1"
      ]
     },
     "execution_count": 137,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "comparedf = pm.compare(traces, models, method=\"pseudo-BMA\", ic='LOO')\n",
    "comparedf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LOO</th>\n",
       "      <th>pLOO</th>\n",
       "      <th>dLOO</th>\n",
       "      <th>weight</th>\n",
       "      <th>SE</th>\n",
       "      <th>dSE</th>\n",
       "      <th>warning</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>m2c_nopc</th>\n",
       "      <td>79.84</td>\n",
       "      <td>4.63</td>\n",
       "      <td>0</td>\n",
       "      <td>0.93</td>\n",
       "      <td>11.17</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>m2c_onlyp</th>\n",
       "      <td>85.26</td>\n",
       "      <td>4.17</td>\n",
       "      <td>5.43</td>\n",
       "      <td>0.06</td>\n",
       "      <td>8.96</td>\n",
       "      <td>8.01</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>m1c</th>\n",
       "      <td>89.92</td>\n",
       "      <td>9.96</td>\n",
       "      <td>10.08</td>\n",
       "      <td>0.01</td>\n",
       "      <td>13.53</td>\n",
       "      <td>6.11</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>m2c_onlyic</th>\n",
       "      <td>141.77</td>\n",
       "      <td>8.44</td>\n",
       "      <td>61.93</td>\n",
       "      <td>0</td>\n",
       "      <td>31.74</td>\n",
       "      <td>32.63</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>m2c_onlyc</th>\n",
       "      <td>151.24</td>\n",
       "      <td>17.34</td>\n",
       "      <td>71.4</td>\n",
       "      <td>0</td>\n",
       "      <td>44.91</td>\n",
       "      <td>44.37</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               LOO   pLOO   dLOO weight     SE    dSE warning\n",
       "name                                                         \n",
       "m2c_nopc     79.84   4.63      0   0.93  11.17      0       1\n",
       "m2c_onlyp    85.26   4.17   5.43   0.06   8.96   8.01       1\n",
       "m1c          89.92   9.96  10.08   0.01  13.53   6.11       1\n",
       "m2c_onlyic  141.77   8.44  61.93      0  31.74  32.63       1\n",
       "m2c_onlyc   151.24  17.34   71.4      0  44.91  44.37       1"
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp=comparedf.sort_index()\n",
    "temp['name']=names\n",
    "comparedf = temp.sort_values('LOO').set_index('name')\n",
    "comparedf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11738c6d8>"
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x117c240f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pm.compareplot(comparedf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>WAIC</th>\n",
       "      <th>pWAIC</th>\n",
       "      <th>dWAIC</th>\n",
       "      <th>weight</th>\n",
       "      <th>SE</th>\n",
       "      <th>dSE</th>\n",
       "      <th>warning</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>79.06</td>\n",
       "      <td>4.24</td>\n",
       "      <td>0</td>\n",
       "      <td>0.76</td>\n",
       "      <td>11.06</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>84.09</td>\n",
       "      <td>7.05</td>\n",
       "      <td>5.04</td>\n",
       "      <td>0</td>\n",
       "      <td>12.19</td>\n",
       "      <td>3.77</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>84.43</td>\n",
       "      <td>3.75</td>\n",
       "      <td>5.37</td>\n",
       "      <td>0.24</td>\n",
       "      <td>8.94</td>\n",
       "      <td>7.93</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>141.65</td>\n",
       "      <td>8.38</td>\n",
       "      <td>62.6</td>\n",
       "      <td>0</td>\n",
       "      <td>31.7</td>\n",
       "      <td>32.84</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>150.44</td>\n",
       "      <td>16.94</td>\n",
       "      <td>71.38</td>\n",
       "      <td>0</td>\n",
       "      <td>44.67</td>\n",
       "      <td>44.44</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     WAIC  pWAIC  dWAIC weight     SE    dSE warning\n",
       "1   79.06   4.24      0   0.76  11.06      0       1\n",
       "0   84.09   7.05   5.04      0  12.19   3.77       1\n",
       "2   84.43   3.75   5.37   0.24   8.94   7.93       1\n",
       "4  141.65   8.38   62.6      0   31.7  32.84       1\n",
       "3  150.44  16.94  71.38      0  44.67  44.44       1"
      ]
     },
     "execution_count": 142,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "comparedf_s = pm.compare(traces, models, method=\"stacking\", ic='WAIC')\n",
    "comparedf_s.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "        text-align: right;\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>WAIC</th>\n",
       "      <th>pWAIC</th>\n",
       "      <th>dWAIC</th>\n",
       "      <th>weight</th>\n",
       "      <th>SE</th>\n",
       "      <th>dSE</th>\n",
       "      <th>warning</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>m2c_nopc</th>\n",
       "      <td>79.06</td>\n",
       "      <td>4.24</td>\n",
       "      <td>0</td>\n",
       "      <td>0.76</td>\n",
       "      <td>11.06</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>m1c</th>\n",
       "      <td>84.09</td>\n",
       "      <td>7.05</td>\n",
       "      <td>5.04</td>\n",
       "      <td>0</td>\n",
       "      <td>12.19</td>\n",
       "      <td>3.77</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>m2c_onlyp</th>\n",
       "      <td>84.43</td>\n",
       "      <td>3.75</td>\n",
       "      <td>5.37</td>\n",
       "      <td>0.24</td>\n",
       "      <td>8.94</td>\n",
       "      <td>7.93</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>m2c_onlyic</th>\n",
       "      <td>141.65</td>\n",
       "      <td>8.38</td>\n",
       "      <td>62.6</td>\n",
       "      <td>0</td>\n",
       "      <td>31.7</td>\n",
       "      <td>32.84</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>m2c_onlyc</th>\n",
       "      <td>150.44</td>\n",
       "      <td>16.94</td>\n",
       "      <td>71.38</td>\n",
       "      <td>0</td>\n",
       "      <td>44.67</td>\n",
       "      <td>44.44</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              WAIC  pWAIC  dWAIC weight     SE    dSE warning\n",
       "name                                                         \n",
       "m2c_nopc     79.06   4.24      0   0.76  11.06      0       1\n",
       "m1c          84.09   7.05   5.04      0  12.19   3.77       1\n",
       "m2c_onlyp    84.43   3.75   5.37   0.24   8.94   7.93       1\n",
       "m2c_onlyic  141.65   8.38   62.6      0   31.7  32.84       1\n",
       "m2c_onlyc   150.44  16.94  71.38      0  44.67  44.44       1"
      ]
     },
     "execution_count": 144,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp=comparedf_s.sort_index()\n",
    "temp['name']=names\n",
    "comparedf_s = temp.sort_values('WAIC').set_index('name')\n",
    "comparedf_s"
   ]
  }
 ],
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