{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Chapter 8. Conditional Manatees"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install -q numpyro arviz"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import math\n",
    "import os\n",
    "import warnings\n",
    "\n",
    "import arviz as az\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "\n",
    "import jax.numpy as jnp\n",
    "from jax import random\n",
    "\n",
    "import numpyro\n",
    "import numpyro.distributions as dist\n",
    "import numpyro.optim as optim\n",
    "from numpyro.diagnostics import print_summary\n",
    "from numpyro.infer import Predictive, SVI, Trace_ELBO, log_likelihood\n",
    "from numpyro.infer.autoguide import AutoLaplaceApproximation\n",
    "\n",
    "if \"SVG\" in os.environ:\n",
    "    %config InlineBackend.figure_formats = [\"svg\"]\n",
    "warnings.formatwarning = lambda message, category, *args, **kwargs: \"{}: {}\\n\".format(\n",
    "    category.__name__, message\n",
    ")\n",
    "az.style.use(\"arviz-darkgrid\")\n",
    "numpyro.set_platform(\"cpu\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code 8.1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "rugged = pd.read_csv(\"../data/rugged.csv\", sep=\";\")\n",
    "d = rugged\n",
    "\n",
    "# make log version of outcome\n",
    "d[\"log_gdp\"] = d[\"rgdppc_2000\"].apply(math.log)\n",
    "\n",
    "# extract countries with GDP data\n",
    "dd = d[d[\"rgdppc_2000\"].notnull()].copy()\n",
    "\n",
    "# rescale variables\n",
    "dd[\"log_gdp_std\"] = dd.log_gdp / dd.log_gdp.mean()\n",
    "dd[\"rugged_std\"] = dd.rugged / dd.rugged.max()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code 8.2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1000/1000 [00:01<00:00, 944.10it/s, init loss: 810.4496, avg. loss [951-1000]: -91.4252]\n"
     ]
    }
   ],
   "source": [
    "def model(rugged_std, log_gdp_std=None):\n",
    "    a = numpyro.sample(\"a\", dist.Normal(1, 1))\n",
    "    b = numpyro.sample(\"b\", dist.Normal(0, 1))\n",
    "    sigma = numpyro.sample(\"sigma\", dist.Exponential(1))\n",
    "    mu = numpyro.deterministic(\"mu\", a + b * (rugged_std - 0.215))\n",
    "    numpyro.sample(\"log_gdp_std\", dist.Normal(mu, sigma), obs=log_gdp_std)\n",
    "\n",
    "\n",
    "m8_1 = AutoLaplaceApproximation(model)\n",
    "svi = SVI(\n",
    "    model,\n",
    "    m8_1,\n",
    "    optim.Adam(0.1),\n",
    "    Trace_ELBO(),\n",
    "    rugged_std=dd.rugged_std.values,\n",
    "    log_gdp_std=dd.log_gdp_std.values,\n",
    ")\n",
    "svi_result = svi.run(random.PRNGKey(0), 1000)\n",
    "p8_1 = svi_result.params"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code 8.3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "predictive = Predictive(m8_1.model, num_samples=1000, return_sites=[\"a\", \"b\", \"sigma\"])\n",
    "prior = predictive(random.PRNGKey(7), rugged_std=0)\n",
    "\n",
    "# set up the plot dimensions\n",
    "plt.subplot(xlim=(0, 1), ylim=(0.5, 1.5), xlabel=\"ruggedness\", ylabel=\"log GDP\")\n",
    "plt.gca().axhline(dd.log_gdp_std.min(), ls=\"--\")\n",
    "plt.gca().axhline(dd.log_gdp_std.max(), ls=\"--\")\n",
    "\n",
    "# draw 50 lines from the prior\n",
    "rugged_seq = jnp.linspace(-0.1, 1.1, num=30)\n",
    "mu = Predictive(m8_1.model, prior, return_sites=[\"mu\"])(\n",
    "    random.PRNGKey(7), rugged_std=rugged_seq\n",
    ")[\"mu\"]\n",
    "for i in range(50):\n",
    "    plt.plot(rugged_seq, mu[i], \"k\", alpha=0.3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code 8.4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DeviceArray(0.564, dtype=float32)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "jnp.sum(jnp.abs(prior[\"b\"]) > 0.6) / prior[\"b\"].shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code 8.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1000/1000 [00:01<00:00, 950.36it/s, init loss: 852.5239, avg. loss [951-1000]: -94.8615]\n"
     ]
    }
   ],
   "source": [
    "def model(rugged_std, log_gdp_std=None):\n",
    "    a = numpyro.sample(\"a\", dist.Normal(1, 0.1))\n",
    "    b = numpyro.sample(\"b\", dist.Normal(0, 0.3))\n",
    "    sigma = numpyro.sample(\"sigma\", dist.Exponential(1))\n",
    "    mu = numpyro.deterministic(\"mu\", a + b * (rugged_std - 0.215))\n",
    "    numpyro.sample(\"log_gdp_std\", dist.Normal(mu, sigma), obs=log_gdp_std)\n",
    "\n",
    "\n",
    "m8_1 = AutoLaplaceApproximation(model)\n",
    "svi = SVI(\n",
    "    model,\n",
    "    m8_1,\n",
    "    optim.Adam(0.1),\n",
    "    Trace_ELBO(),\n",
    "    rugged_std=dd.rugged_std.values,\n",
    "    log_gdp_std=dd.log_gdp_std.values,\n",
    ")\n",
    "svi_result = svi.run(random.PRNGKey(0), 1000)\n",
    "p8_1 = svi_result.params"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code 8.6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "                mean       std    median      5.5%     94.5%     n_eff     r_hat\n",
      "         a      1.00      0.01      1.00      0.98      1.02    931.50      1.00\n",
      "         b      0.00      0.06      0.00     -0.08      0.10   1111.63      1.00\n",
      "     sigma      0.14      0.01      0.14      0.13      0.15    949.29      1.00\n",
      "\n"
     ]
    }
   ],
   "source": [
    "post = m8_1.sample_posterior(random.PRNGKey(1), p8_1, sample_shape=(1000,))\n",
    "print_summary({k: v for k, v in post.items() if k != \"mu\"}, 0.89, False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code 8.7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# make variable to index Africa (0) or not (1)\n",
    "dd[\"cid\"] = jnp.where(dd.cont_africa.values == 1, 0, 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code 8.8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1000/1000 [00:00<00:00, 1061.70it/s, init loss: 1785.1527, avg. loss [951-1000]: -127.6097]\n"
     ]
    }
   ],
   "source": [
    "def model(cid, rugged_std, log_gdp_std=None):\n",
    "    a = numpyro.sample(\"a\", dist.Normal(1, 0.1).expand([2]))\n",
    "    b = numpyro.sample(\"b\", dist.Normal(0, 0.3))\n",
    "    sigma = numpyro.sample(\"sigma\", dist.Exponential(1))\n",
    "    mu = numpyro.deterministic(\"mu\", a[cid] + b * (rugged_std - 0.215))\n",
    "    numpyro.sample(\"log_gdp_std\", dist.Normal(mu, sigma), obs=log_gdp_std)\n",
    "\n",
    "\n",
    "m8_2 = AutoLaplaceApproximation(model)\n",
    "svi = SVI(\n",
    "    model,\n",
    "    m8_2,\n",
    "    optim.Adam(0.1),\n",
    "    Trace_ELBO(),\n",
    "    cid=dd.cid.values,\n",
    "    rugged_std=dd.rugged_std.values,\n",
    "    log_gdp_std=dd.log_gdp_std.values,\n",
    ")\n",
    "svi_result = svi.run(random.PRNGKey(0), 1000)\n",
    "p8_2 = svi_result.params"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code 8.9"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "UserWarning: For one or more samples the posterior variance of the log predictive densities exceeds 0.4. This could be indication of WAIC starting to fail. \n",
      "See http://arxiv.org/abs/1507.04544 for details\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>rank</th>\n",
       "      <th>waic</th>\n",
       "      <th>p_waic</th>\n",
       "      <th>d_waic</th>\n",
       "      <th>weight</th>\n",
       "      <th>se</th>\n",
       "      <th>dse</th>\n",
       "      <th>warning</th>\n",
       "      <th>waic_scale</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>m8.2</th>\n",
       "      <td>0</td>\n",
       "      <td>-252.36</td>\n",
       "      <td>4.15389</td>\n",
       "      <td>0</td>\n",
       "      <td>0.9998</td>\n",
       "      <td>13.2547</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>deviance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>m8.1</th>\n",
       "      <td>1</td>\n",
       "      <td>-188.818</td>\n",
       "      <td>2.65329</td>\n",
       "      <td>63.5418</td>\n",
       "      <td>0.000200227</td>\n",
       "      <td>14.8249</td>\n",
       "      <td>14.9592</td>\n",
       "      <td>False</td>\n",
       "      <td>deviance</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     rank     waic   p_waic   d_waic       weight       se      dse warning  \\\n",
       "m8.2    0  -252.36  4.15389        0       0.9998  13.2547        0    True   \n",
       "m8.1    1 -188.818  2.65329  63.5418  0.000200227  14.8249  14.9592   False   \n",
       "\n",
       "     waic_scale  \n",
       "m8.2   deviance  \n",
       "m8.1   deviance  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "post = m8_1.sample_posterior(random.PRNGKey(2), p8_1, sample_shape=(1000,))\n",
    "logprob = log_likelihood(\n",
    "    m8_1.model, post, rugged_std=dd.rugged_std.values, log_gdp_std=dd.log_gdp_std.values\n",
    ")\n",
    "az8_1 = az.from_dict({}, log_likelihood={k: v[None] for k, v in logprob.items()})\n",
    "post = m8_2.sample_posterior(random.PRNGKey(2), p8_2, sample_shape=(1000,))\n",
    "logprob = log_likelihood(\n",
    "    m8_2.model,\n",
    "    post,\n",
    "    rugged_std=dd.rugged_std.values,\n",
    "    cid=dd.cid.values,\n",
    "    log_gdp_std=dd.log_gdp_std.values,\n",
    ")\n",
    "az8_2 = az.from_dict({}, log_likelihood={k: v[None] for k, v in logprob.items()})\n",
    "az.compare({\"m8.1\": az8_1, \"m8.2\": az8_2}, ic=\"waic\", scale=\"deviance\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code 8.10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "                mean       std    median      5.5%     94.5%     n_eff     r_hat\n",
      "      a[0]      0.88      0.02      0.88      0.86      0.90   1049.96      1.00\n",
      "      a[1]      1.05      0.01      1.05      1.03      1.07    824.00      1.00\n",
      "         b     -0.05      0.05     -0.05     -0.13      0.02    999.08      1.00\n",
      "     sigma      0.11      0.01      0.11      0.10      0.12    961.35      1.00\n",
      "\n"
     ]
    }
   ],
   "source": [
    "post = m8_2.sample_posterior(random.PRNGKey(1), p8_2, sample_shape=(1000,))\n",
    "print_summary({k: v for k, v in post.items() if k != \"mu\"}, 0.89, False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code 8.11"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DeviceArray([-0.19981882, -0.13967244], dtype=float32)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "post = m8_2.sample_posterior(random.PRNGKey(1), p8_2, sample_shape=(1000,))\n",
    "diff_a1_a2 = post[\"a\"][:, 0] - post[\"a\"][:, 1]\n",
    "jnp.percentile(diff_a1_a2, q=jnp.array([5.5, 94.5]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code 8.12"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "rugged_seq = jnp.linspace(start=-1, stop=1.1, num=30)\n",
    "\n",
    "# compute mu over samples, fixing cid=1\n",
    "post.pop(\"mu\")\n",
    "predictive = Predictive(m8_2.model, post, return_sites=[\"mu\"])\n",
    "mu_NotAfrica = predictive(random.PRNGKey(2), cid=1, rugged_std=rugged_seq)[\"mu\"]\n",
    "\n",
    "# compute mu over samples, fixing cid=0\n",
    "mu_Africa = predictive(random.PRNGKey(2), cid=0, rugged_std=rugged_seq)[\"mu\"]\n",
    "\n",
    "# summarize to means and intervals\n",
    "mu_NotAfrica_mu = jnp.mean(mu_NotAfrica, 0)\n",
    "mu_NotAfrica_ci = jnp.percentile(mu_NotAfrica, q=jnp.array([1.5, 98.5]), axis=0)\n",
    "mu_Africa_mu = jnp.mean(mu_Africa, 0)\n",
    "mu_Africa_ci = jnp.percentile(mu_Africa, q=jnp.array([1.5, 98.5]), axis=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code 8.13"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1000/1000 [00:00<00:00, 1080.73it/s, init loss: 1670.7773, avg. loss [951-1000]: -132.0968]\n"
     ]
    }
   ],
   "source": [
    "def model(cid, rugged_std, log_gdp_std=None):\n",
    "    a = numpyro.sample(\"a\", dist.Normal(1, 0.1).expand([2]))\n",
    "    b = numpyro.sample(\"b\", dist.Normal(0, 0.3).expand([2]))\n",
    "    sigma = numpyro.sample(\"sigma\", dist.Exponential(1))\n",
    "    mu = numpyro.deterministic(\"mu\", a[cid] + b[cid] * (rugged_std - 0.215))\n",
    "    numpyro.sample(\"log_gdp_std\", dist.Normal(mu, sigma), obs=log_gdp_std)\n",
    "\n",
    "\n",
    "m8_3 = AutoLaplaceApproximation(model)\n",
    "svi = SVI(\n",
    "    model,\n",
    "    m8_3,\n",
    "    optim.Adam(0.1),\n",
    "    Trace_ELBO(),\n",
    "    cid=dd.cid.values,\n",
    "    rugged_std=dd.rugged_std.values,\n",
    "    log_gdp_std=dd.log_gdp_std.values,\n",
    ")\n",
    "svi_result = svi.run(random.PRNGKey(0), 1000)\n",
    "p8_3 = svi_result.params"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code 8.14"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "                mean       std    median      5.5%     94.5%     n_eff     r_hat\n",
      "      a[0]      0.89      0.02      0.89      0.86      0.91   1009.20      1.00\n",
      "      a[1]      1.05      0.01      1.05      1.04      1.07    755.33      1.00\n",
      "      b[0]      0.13      0.07      0.13      0.01      0.24   1045.06      1.00\n",
      "      b[1]     -0.15      0.06     -0.14     -0.23     -0.05   1003.36      1.00\n",
      "     sigma      0.11      0.01      0.11      0.10      0.12    810.01      1.00\n",
      "\n"
     ]
    }
   ],
   "source": [
    "post = m8_3.sample_posterior(random.PRNGKey(1), p8_3, sample_shape=(1000,))\n",
    "print_summary({k: v for k, v in post.items() if k != \"mu\"}, 0.89, False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code 8.15"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "UserWarning: For one or more samples the posterior variance of the log predictive densities exceeds 0.4. This could be indication of WAIC starting to fail. \n",
      "See http://arxiv.org/abs/1507.04544 for details\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>rank</th>\n",
       "      <th>waic</th>\n",
       "      <th>p_waic</th>\n",
       "      <th>d_waic</th>\n",
       "      <th>weight</th>\n",
       "      <th>se</th>\n",
       "      <th>dse</th>\n",
       "      <th>warning</th>\n",
       "      <th>waic_scale</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>m8.3</th>\n",
       "      <td>0</td>\n",
       "      <td>-259.176</td>\n",
       "      <td>5.10348</td>\n",
       "      <td>0</td>\n",
       "      <td>0.824888</td>\n",
       "      <td>13.4328</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>deviance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>m8.2</th>\n",
       "      <td>1</td>\n",
       "      <td>-252.36</td>\n",
       "      <td>4.15389</td>\n",
       "      <td>6.81647</td>\n",
       "      <td>0.175111</td>\n",
       "      <td>14.6901</td>\n",
       "      <td>6.67691</td>\n",
       "      <td>True</td>\n",
       "      <td>deviance</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>m8.1</th>\n",
       "      <td>2</td>\n",
       "      <td>-188.818</td>\n",
       "      <td>2.65329</td>\n",
       "      <td>70.3582</td>\n",
       "      <td>4.90447e-08</td>\n",
       "      <td>14.6588</td>\n",
       "      <td>15.3423</td>\n",
       "      <td>False</td>\n",
       "      <td>deviance</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     rank     waic   p_waic   d_waic       weight       se      dse warning  \\\n",
       "m8.3    0 -259.176  5.10348        0     0.824888  13.4328        0    True   \n",
       "m8.2    1  -252.36  4.15389  6.81647     0.175111  14.6901  6.67691    True   \n",
       "m8.1    2 -188.818  2.65329  70.3582  4.90447e-08  14.6588  15.3423   False   \n",
       "\n",
       "     waic_scale  \n",
       "m8.3   deviance  \n",
       "m8.2   deviance  \n",
       "m8.1   deviance  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "post = m8_1.sample_posterior(random.PRNGKey(2), p8_1, sample_shape=(1000,))\n",
    "logprob = log_likelihood(\n",
    "    m8_1.model, post, rugged_std=dd.rugged_std.values, log_gdp_std=dd.log_gdp_std.values\n",
    ")\n",
    "az8_1 = az.from_dict({}, log_likelihood={k: v[None] for k, v in logprob.items()})\n",
    "post = m8_2.sample_posterior(random.PRNGKey(2), p8_2, sample_shape=(1000,))\n",
    "logprob = log_likelihood(\n",
    "    m8_2.model,\n",
    "    post,\n",
    "    rugged_std=dd.rugged_std.values,\n",
    "    cid=dd.cid.values,\n",
    "    log_gdp_std=dd.log_gdp_std.values,\n",
    ")\n",
    "az8_3 = az.from_dict({}, log_likelihood={k: v[None] for k, v in logprob.items()})\n",
    "post = m8_3.sample_posterior(random.PRNGKey(2), p8_3, sample_shape=(1000,))\n",
    "logprob = log_likelihood(\n",
    "    m8_3.model,\n",
    "    post,\n",
    "    rugged_std=dd.rugged_std.values,\n",
    "    cid=dd.cid.values,\n",
    "    log_gdp_std=dd.log_gdp_std.values,\n",
    ")\n",
    "az8_3 = az.from_dict({}, log_likelihood={k: v[None] for k, v in logprob.items()})\n",
    "az.compare({\"m8.1\": az8_1, \"m8.2\": az8_2, \"m8.3\": az8_3}, ic=\"waic\", scale=\"deviance\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code 8.16"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "UserWarning: For one or more samples the posterior variance of the log predictive densities exceeds 0.4. This could be indication of WAIC starting to fail. \n",
      "See http://arxiv.org/abs/1507.04544 for details\n"
     ]
    }
   ],
   "source": [
    "waic_list = az.waic(az8_3, pointwise=True, scale=\"deviance\").waic_i.values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code 8.17"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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nzx7s3r3bsK1t27YASuqejbtgHD9+HG+88YYhIXVl0mOYOXOmoUZaFEX89NNPWLZsmdXHIH3ScOTIEbtqy0NDQzFixAgAwPvvv29S25+cnGxYIfTBBx+0OinXHlOnTsUff/yBoqIik+2//PILkpKSIAgCmjdv7vD9EJHyWEZCRC5DEARMnjwZL7zwgtWRyJ49e+KZZ57BkiVL8Morr2D27NmoXr06Ll68iLy8PISHh2Pu3LmGkU5nkUap27Rpg/r165d57EMPPYQZM2bg8uXLOHbsmF1dQuSoU6eOoYXf+vXr8fPPP6Nx48bQ6/VISUlBXl4eJk+ejJ49ewIAHn/8caxevRrJycl48MEH0bBhQ2i1Wly6dAlNmjTBQw89ZPMoeWWZMmUK/vrrL/z++++47777UL9+fdy6dQsajQaPPPIIrl+/jkOHDpndrm/fvvjss8+wdetWHDt2DLVr14ZKpcLgwYMxZMiQMu/zxRdfxKlTpxAfH4/BgwejSZMm8PX1xT///AOdToemTZvinXfeUeTx7d27F9u2bYO/vz8aNGiAgIAA3LhxA7du3QIATJw40eklSkQkD0e2icil3H///WjWrFmZx0ybNg1ffvklunbtiry8PJw7dw5qtRrDhw/Hpk2b0KpVK6fGWHp59vKo1WpDWUtFlZJ06dIFW7ZswahRo1CnTh1cvHgRN27cQL169fD000+bTEINDQ3FqlWrMGjQIISGhuLSpUvQarUYO3YsfvjhB8Um+DlTbGwsVq5cia5du0Kv1+PSpUuoXr063nrrLcMCM5bcdddd+PLLL9GhQwdkZmYiISEBhw4dMtSAlyUwMBBff/013nzzTcTGxuLatWu4fPkyGjdujJdeeglr1qxRrC3fzJkz8fjjj6NBgwbQaDQ4d+4cgoKC0LdvX3z//fd48cUXFbkfIlKeIMrpyUREREREROXiyDYRERERkZMw2SYiIiIichIm20RERERETsJkm4iIiIjISZhsExERERE5CZNtIiIiIiInYbJNREREROQkXEGyDOnp6Vb3hYeHmyyBTJ6P19w78bp7J15378Nr7p2sXXelFqQCOLItm0rFp87b8Jp7J15378Tr7n14zb1TRVx3vrKIiIiIiJzEZctINm3ahISEBJw8eRJJSUnQarWYMWMGhgwZYvM54uPj8eOPP+L06dO4desWtFotatWqhbi4OEyYMAGNGjVy4iMgIiIiIm/nssn2vHnzkJqaCrVajcjISKSmptp9jr/++gsJCQlo1aoVunXrBj8/P1y8eBGbNm3Cli1bsHTpUnTq1MkJ0RMRERERuXCy/eGHH6J+/fqIiorCkiVLMHv2bLvPMXHiREydOtVs+4EDB/DUU0/hk08+wfr165UIl4iIiIjIjMsm2126dHH4HAEBARa3d+7cGeHh4UhOTnb4PoiIiIiIrPHKCZJHjx5FZmYm7r777soOhYiIiIg8mMuObCspPj4ehw4dQlFREa5cuYLdu3dDrVZj+vTplR0aEREREXkwr0i2Dx06hIULFxq+r1+/PubMmYPY2NgybxceHl5m/0UlG56Te+A190687t6J19378Jp7J2dfd69ItqdMmYIpU6YgLy8P58+fx6JFizBixAh89NFHGDhwoNXblbWSlFqtLnOFSfI8vObeidfdO/G6ex9ec+9k7bpzBUmZgoOD0apVKyxcuBCNGjXCO++8g7S0tMoOi4iIiIg8lFcl2xJfX1907NgReXl5OHHiRGWHQ0REREQeyiuTbQDQaDQAShJvIiIiIiJn8IhkOy0tDRcuXDArCTl8+DBEUTQ7ft++fdi1axfCwsLQpk2bigqTiIiIiLyMyw7rrl27FgkJCQCApKQkw7ZDhw4BAPr06YM+ffoAAFauXImFCxdi8uTJmDJliuEczz//PNRqNVq2bIlatWqhsLAQ586dw+HDh+Hn54cPP/wQwcHBFfzIyBYajYiUVKBuFBAZKVR2OERERESyuGyynZCQgI0bN5psS0xMRGJiIgAgKirKkGxbM2XKFOzduxcJCQlIS0uDIAioXbs2hg0bhjFjxnBRGxe1ZauIWbNF6PWASgW8Og0Y0J8JNxEREbkfQbRUZ0EAUGYLILYIcg6NRsTQ4SWJtkSlAtatESp9hJvX3DvxunsnXnfvw2vundj6j7xOSipMEm2g5PuU1MqJh4iIiMgRTLbJpdSNKhnJNqZSlWwnIiIicjdMtsmlREYKeHWaYEi4S2q2K7+EhIiIiEgOl50gSd5rQH8BHdqD3UiIiIjI7THZJpcUGSkgMrKyoyAiIiJyDMtIiIiIiIichMk2EREREZGTMNkmIiIiInISJttERERERE7CZJuIiIiIyEmYbBMREREROQmTbSIiIiIiJ2GyTURERETkJEy2iYiIiIicRJFkW6/XIysrC3q9XonTERERERF5BFnLtR8/fhx79uzBkSNHcPbsWWRnZ0MURQiCgLCwMDRr1gzt2rXDfffdh1atWikdMxERERGRW7A52S4uLsa6deuwZs0anDt3DqIoGvaFhIQgNDQU2dnZyMzMxMGDB3Hw4EF8/vnniImJwYgRI/Doo4/C11dWbk9ERERE5JZsyn5//fVXzJkzB1euXEFISAgefvhhdOjQAa1atUKjRo3g4+NjOLa4uBgXL17E8ePHER8fj99//x3vvvsuli1bhpdffhkPPPCA0x4MEREREZErEUTjIWormjZtiqZNm+KZZ55B7969ERAQYPMdFBYWYufOnVi6dCmSkpJw5swZhwKuSOnp6Vb3qdXqMveT5+E190687t6J19378Jp7J2vXXa1WK3YfNo1sL1y4EH369JF1BwEBARgwYAAGDBiAXbt2yToHEREREZE7sqkbidxE21nnISIiIiJyB+yzTURERETkJEy2iYiIiIicRHYvvvPnz+Orr77C4cOHcevWLWi1WovHCYKA06dPyw6QiIiIiMhdyUq2jx49irFjx6KgoAAAULVqVQQHBysaGBERERGRu5OVbM+ZMwcFBQUYM2YMnn/+eVStWlXhsIiIiIiI3J+sZPvkyZNo1qwZpk+frnQ8REREREQeQ9YEST8/P9x1111Kx0JERERE5FFkJdtxcXFISkpSOhYiIiIiIo8iK9l++eWXcePGDSxbtkzpeIiIiIiIPIasmu3Tp09jyJAh+OSTT7B792506dIFtWrVgiAIFo8fNGiQIzESEREREbklWcn266+/DkEQIIoiDh8+jCNHjlg8ThRFCILAZJuIiIiIvJKsZHvSpElWR7GJiIiIiKiErGR7ypQpSsdBRERERORxZE2QJCIiIiKi8jHZJiIiIiJyElllJJIjR47gt99+w5UrV5CbmwtRFM2OEQQBy5cvd+RuiIiIiIjckqxkWxRFvPHGG/jpp58MCbbUnUQifc+JlERERETkrWSVkaxevRobN25EixYt8M033+D+++8HAPzyyy9YunQpBg8eDJVKhaeffhq7du1SNGAiIiIiIncha2R748aNCAoKwtKlS6FWq/Hzzz8DABo0aIAGDRrg3nvvRffu3TF16lS0adMGUVFRigZNREREROQOZI1sX7hwAW3atIFarTbZrtPpDP/v168fWrRowSXdiYiIiMhryUq2RVE0SbSDgoIAAJmZmSbH1a9fH0lJSQ6ER+Q4jUZE4lERGo35BF4ivj6IiMiZZJWRREZG4saNG4bv69SpAwA4c+YMunbtath++fJl+Pj4OBgikXxbtoqYNVuEXg+oVMCr04AB/Tlpl0rw9UFERM4ma2S7RYsWOH/+PIqLiwEA3bp1gyiKmDVrFi5cuICcnBx89dVXOHXqFJo3b65owES20mj+TaQAQK8HZs3mCCaV4OuDiIgqgqxku1evXsjMzMQff/wBAGjatCn69++Pc+fOYcCAAWjfvj1mz54NX19fTJ06Vcl4iWyWkgpDIiXR60u2E/H1QUREFUFWGcmAAQNw//33m5SIzJw5EzExMdi1axcyMzPRsGFDjB8/Hq1atVIsWCJ71I0qKQ0wTqhUqpLtRHx9EBFRRZC9gqS/v7/J935+fnjmmWfwzDPPOBwUkRIiIwW8Og2lanIFREayJpf4+iAioorh0HLtRK5uQH8BHdqXlAbUjQITKTLB1wcRETmbQ8l2Wloafv75Z5w4cQIZGRno1KkTJkyYAABISkrC1atX0aVLF0NrQKLKEBkpIDKysqMgV8XXBxEROZPsZHvr1q14++23kZ+fD1EUIQgCIo3+Yl25cgUvvPACZsyYgUGDBikRKxERERGRW5HVjeTIkSP4z3/+A39/f0yfPh3r1q2DKJq2y+rRowfCwsKwc+dORQIl5+GiHkRERETOIWtke/HixfD19cW3336Lpk2bWjzGz88PjRo1wvnz5x0KkJyLi3oQEZG70WhEzrUgtyFrZPvvv//GPffcYzXRltSqVQsajUZWYOR8XNSDiIjczZatIoYOF/HC1JJ/t2zl3yxybbKS7YKCAqjV6nKPy8nJgSDwHaer4qIeRETkTjhIRO5IVrJdp04dnDt3rsxjiouLce7cOdSvX19WYOR80qIexrioBxG5E8458S4cJCJ3JCvZ7tmzJ5KTk7Fy5Uqrx3zzzTe4ffs2+vTpIzs4b1CZfyhKFvUQDAk3F/WoPEwYiOzHcgLvw0EickeyJkhOmDABW7duxYcffohjx46hd+/eAEr6bu/evRu7du3Cxo0bUbt2bTz55JOyAtu0aRMSEhJw8uRJJCUlQavVYsaMGRgyZIjN5zhy5Ah27dqFQ4cOITU1FXl5eYiKikLv3r3x7LPPokqVKrJiM+bIJA1XmJzIRT0qnyu8DojcjbVygg7t+XvMk3HlV3JHgli6Z5+NLly4gJdeegn//PMPBEEw9NoGAFEU0ahRIyxcuBCNGjWSFVivXr2QmpoKtVqN4OBgpKam2p1sd+3aFenp6Wjbti2aNWsGQRBw6NAhnD59GnfddRfWrFmD6tWrW719enq61X1qtRorvk8z+4G3NUnSaEpGYow/DlOpgHVr+EvDVanV6jJfE3LwdeD6nHHdyXGJR0tGtEub/5mAuDaO/+zwurs2Z3Qj4TX3Ttauuy1zE20le1Gbxo0bY9OmTfj999/x119/ITU1FTqdDrVq1UKXLl3wwAMPwMfHR3ZgH374IerXr4+oqCgsWbIEs2fPtvscY8aMwaBBg0wW2xFFEf/973+xevVqLFy4EO+++66s+G7c1Dk0qlJW3RlXs/MefB0QySOVE5R+o8pyAu/AlV/JnTi0XLtKpUKfPn2cUpfdpUsXh8/xzDPPmG0TBAETJ07E6tWrcfjwYdnnvnJF71CS5Kw/FK7ce9SVY6ssTBiI5GE5ARG5C4eSbXfl61vysB0Zea9fX+VQkuSMPxSuXPvryrFVJiYMRPJxzgkRuQOHku38/HycPHkSt27dQlFRkdXjBg0a5MjdKG79+vUASmq65apV0wevThMcSpKU/EPhypOFXDk2V8CEgUg+lhMQkauTlWyLooh58+Zh+fLlKCgoKPM4QRBcKtk+c+YMPv/8c1SvXh3jx48v89jw8HCoSvcYMjJ6VDX07atDcrIed92lQq2a9o+Uq9VATIzdNzOT9I8Wen2WyTa9HsjMCkNMjJ/d57txU4crV/SoX1/e43JmbJVJyQkTpudV5nVAzuGs606ujdfd+/CaeydnX3dZyfbnn3+OL7/8En5+fujTpw/q1auH4OBgpWNT3NWrV/Hss89Cp9Nhzpw5qFatWpnHZ2ZmWt0nzV4N8AfublKyrTInMVcNFy2WtYRXyUZ6uqMtCW3vsuLs2CoTZ6pXDFer7ed190687t6H19w7uWw3knXr1iE0NBQ//PADGjdurFgwzpSamooxY8YgLS0NCxYsQKdOnSo7JEUpVfurRMlH6WSJdclkK1et7Xe1NwBEROQ+ZCXb6enp6NKli9sk2ikpKXjyySeh0Wgwd+5c9OzZs1LiUPIPtqVzKVH7a60V3e49Inp2L/+c1pIlV6lLZtLkuly1tn/9hgK894HrvQEgIiL3IGu59vr16yM3N1fpWJzCONH+7LPPKm35eCWXFS7rXJGRJQs6yE1OLC2FCwALPke5cVtLlqQlyB2NzVFc2tm1ldVzvLJoNCLe+yDX6muaiIioPLKS7REjRuD48eO4cOGC0vHIkpaWhgsXLiAtLc1ku5Ro37x5E3PmzEHfvn0rJb7yktDKOpclJSUfgsWEu7z7csVkSeLs540cZ+mNXmX1HNdoRCQeFXHilOiyr2kiInIPsspIRowYgQsXLuDpp5/GSy+9hM6dO6NmzZqKBrZ27VokJCQAAJKSkgzbDh06BAAmi+msXLkSCxcuxOTJkzFlyhTDOZ588kmkpqaidevWOHfuHM6dO2d2P8bHO4uSqwRWxIqDUsnH7j0iFnxu+3258gItXKnR9bhqbb9xKZQglHyJRu/JXOU1TURE7kF2n+3hw4fj4MGDmD59epnHCYKA06dP233+hIQEbNy40WRbYmIiEhMTAQBRUVHlloSkppYMPx07dgzHjh2zeExFJNtKJqEVldBGRgro2R34/AvR5vtylWTJEld+I+CNXLW2v/QnIKJomnC70muaiIjcgyCKot2fox89ehTjxo1Dfn4+BEFA1apVERQUZPX433//3aEgK0tZLYDsbRGkZDs9pVvzKX1frjoJ0dHnjW2hlKHRlNTMl37js25N5SexiUdLavpLe/9doGpVweVe0+Q8/Hn3Przm3sllW/998sknyM/Px+TJk/HUU08hNDRUsYA8lZIjdhU5+ifnvlx1RbfKHjWtLK725seVS3qsfQIS26Ly3wgQEZF7kpVsnzlzBq1bt8bkyZOVjsdt3Lipw6lTol0JjJJJaEUmtK6aPMvhSY/FFq7Yt9qVS3oslUK993YIIiPzKzs0IiJyU7KS7ZCQEERERCgdi9soSWAyXCqBISrNVftWu3JtP2D+CUhMTCDS05lsExGRPLKS7fvuuw/79+9HUVER/P39lY7JpblqAkNUmiuXa7h6SY+3fQJCRETOI6vP9iuvvAJ/f39Mnz4dOTk5Ssfk0ly5lzSRMVfqW21JZS9yREREVBFkT5CMjo7Gtm3bsHfvXsTGxlrtsy0IAj766COHgnQlrlxvSmTM1cs1iIiIvIGs1n9Nmza1/Q4EAWfOnLH3LlyCtRZAFdl6j1yH0m2h5HYJsfd2rtaNxN2wHZh34nX3Przm3sllW/999913igXgjgb0F9C3bzhOncpkAkOyyO0SYu/tmGgTERFVLlnJdocOHZSOw+3UqumDAH8mL2Q/uZNs7b2dK7b9IyIi8jayJkgSkXxyJ9nacztriblGY3fVGBERETmAyTZRBZPbJcSe27FrDhERkWtgsk1UwUq6hAiGxNnWLiH23M7V2/4RERF5C1k120RycLLev+Qu6mLr7dj2j4iIyDUw2aYKwcl65uSuUmjr7Vx9lUbiG1AiIm/AZJucjkvcVx4uO+66+AaUiMg72FSzPX36dKxbt87w/bVr15CRkeGsmMjDcLIekSl2iyEi8h42JdsbN25EQkKC4fvevXtj1qxZTguKPAsn6xFQkmAmHmVCCfANKBGRN7Ep2fb19UVRUZHhe1EUIWOVd/JScrtvkOfYslXE0OEiXpha8u+Wrd79+4NvQImIvIdNNdu1a9fGkSNHkJqaiqgo/jUg+3Gynvdizb45doshIvIeNiXbAwYMwBdffIE+ffoYtv3000/46aefyr2tIAg4ffq07ADJc3Cynncqq2TCm18PfANKROQdbEq2p0yZgipVquC3337DjRs3kJKSgsDAQKjVamfHR0RuTiqZME64WTJRgm9AiYg8n03JtkqlwtixYzF27FgAQNOmTdGvXz/MmDHDqcGRe2MPYQJYMkFERN5NVp/twYMHo23btkrHQh7Em3oIO+tNhSe9WWHJBBEReStZyTZHtKks3jQhzllvKjzxzQpLJoiIyBs5tIKkVqvFzp07kZCQAI1GA0EQEBERgbZt26Jv377w8/NTKk5yI94yIc5Zbyq86c0KERGRp5OdbCckJOCVV17BjRs3zHpur1q1CrVr18ann36KuLg4h4Mk9+ItE+Kc9abCW96sEBEReQNZyfalS5cwYcIE5OXloUWLFnj44YcN/bevXbuGn3/+GSdPnsSECROwfv16NGjQQMmYycV5y4Q4Z72p8JY3K+TaPGnOABFRZZKVbH/55ZfIy8vD9OnTMWbMGLP9Tz75JL777jt89NFH+PLLLzFz5kyHAyX34g0T4pz1psJb3qyQ6/LEOQNERJVFEGWsu37fffehRo0a2LBhQ5nHDRkyBLdv38aff/4pO8DKlJ6ebnWfWq022c9RIM9X+ppL2I3Es1m77p5KoxExdLho9snKujXe9YbP26478Zp7K2vXXcm1ZGSNbKelpaF9+/blHtewYUP8888/cu7CrXAUyLs5q8sGu3e4Dm9648M5A0REylLJuVHVqlVx+fLlco+7fPkywsPD5dyF27DWOUKjsfsDAyJyQes3FGDocBEvTC0Z8d2y1bN/tqU5A8Y4Z4CISD5ZyXbHjh1x+vRp/Pjjj1aP+fHHH3Hq1Cl06tRJdnDuoKxRICJybxqNiPc+yPWqN9MlcwYEQ8LNOQNERI6RVUYyceJE/Pbbb3j33XexefNmDBw4EFFRURAEASkpKdi8eTOOHDmCoKAgPP/880rH7FLYOYKohCeWWnhrSYU3THAmIqoospLtxo0b44svvsArr7yCw4cP48iRIyb7RVFEjRo18Mknn6Bx48aKBOqqnNU5whMTF/JcnjpvwZvfTHPOABGRMmR1I5Hk5+dj+/btOHLkCDQaDQAgMjIS7dq1w4MPPoigoCDFAq0MldGNRKMRsXa9iDU/AqL4b/LuCYmLu+NMdcs8vXvF77uDDKUk/Hn0Hvx59z685t7JZbuRSIKCgjBkyBAMGTJEqXjclhKjQFu2ivj4UxHGb3+4VDe5Ok8vtXh0SCBiW+TxkyYiIpLFoWSblCN1NbH0OYMnJS7kebyh1IIlFUREJJesbiSkPEujgxJPS1xsodGISDxqvetDefup4rB7BRERkXUc2XYRlkYHAe9MXMqbbOepk/HcGbtXEBERWcaRbRdRenRQEIARj5dMMvOmRLK8RYK4iJDriowUENfGu94YEhERlYcj2y6Eo4PlT7bz9Ml4RERE5FmYbLsYb5+IVd5kO2+YjEdERESeg2Uk5FLKm2zHyXhERETkTjiyTS6nvHIaltsQERGRu5CdbBcVFWHLli04fPgwbt26haKiIovHCYKA5cuXyw6QvFN55TTeXm5DRERE7kFWsn3z5k2MGTMGV65cQXmrvQsCRx2JiIiIyDvJSrZnzZqFy5cvo02bNhg3bhwaNGiA4OBgpWMjIiIiInJrspLtffv2oU6dOvj2228REBCgdExERERERB5BVjeSoqIixMbGMtEmIiIiIiqDrGQ7OjoaN2/eVDoWkkGjEZF4lCsoEhEREbkiWcn2hAkTcOLECRw6dEjpeMgOW7aKGDpcxAtTS/7dspUJNxEREZErkVWz3bx5c4wdOxbPPfccxo4diy5duqBWrVpWO4/UqVPHoSDJnEYjYtZs0bCSol4PzJotokN79p0mIiIichWyku1evXpBEASIoohFixZh0aJFVo8VBAGnT5+WHSBZlpJqumQ5UPJ9SirYf7ocGo3IBXGIiIioQshKttu3b690HGSnulElS5UbJ9wqVcl2sm7L1n8/EShZ6r1kRUoiIiIiZ5CVbK9YsULpOMhOkZECXp2GUomjwJHaMrD0hoiIiCqa7OXaqfIN6C+gQ3t4fEmEUmUfLL0hIiKiiqZIsp2eng6NRgNBEBAREQG1Wu3wOTdt2oSEhAScPHkSSUlJ0Gq1mDFjBoYMGWLzOe7cuYN169bh1KlTOHnyJFJTUwEA586dczg+VxEZKbhNoignaVay7IOlN0RERFTRHEq2V69ejRUrVuDSpUsm2xs1aoRRo0ZhxIgRss89b948pKamQq1WIzIy0pAo2+P8+fOYM2cOBEFA/fr1ERQUhPz8fNkxkXxykmalyz5YekNEREQVTVayrdfr8dJLL2Hnzp0QRRFVqlQxtPe7fv06Lly4gPfffx8HDhzAvHnzrLYELMuHH36I+vXrIyoqCkuWLMHs2bPtPkfjxo3x/fffo1mzZggNDUW/fv3M3hiQ88lNmp1R9uEtpTdERETkGmQl2z/88AN27NiBhg0b4tVXX0XPnj1N9v/xxx+YNWsWdu7ciR9++AHDhw+3+z66dOkiJzQTNWrUQI0aNRw+DzlGbtLsrLIPdyq9ISIiIvcmawXJDRs2IDQ0FCtWrDBLtAGgR48eWL58OYKDg7F+/XqHgyT3JiXNxmxJmkvKPgTDbVn2QURERO5G1sj2+fPn0bVr1zJHjSMiItC5c2fs379fdnDkGRyplWbZBxEREbkzp7b+k1Or7UrCw8OhKj0ka0SJriveYvQooG9fHZKT9bjrLhVq1fSx+bZqNRAT48Tg7FCZ1/zGTR2uXNGjfn37nj9yHH/WvROvu/fhNfdOzr7uspLthg0bIj4+Hunp6VYDTEtLw8GDB9GwYUOHAqxMmZmZFrdrNCIyMsNQNTybI612CPAH7m5S8v/09MqNRQ61Wo30SgrcvJuLwJUvK0hlXneqPLzu3ofX3DtZu+5KJuCyarYHDx6M7OxsjB07FocOHTLbHx8fj3HjxiEnJ8euvtjuYMtWEUOHixg3IQtDh4vYslWs7JDIw1nr5qLR8LVHRETk6mSNbI8cORJ79+7Fn3/+iTFjxqBGjRqIioqCIAhISUnB7du3IYoiunfvjpEjRyodc6Xhct9UGbjyJRERkXOIooji4mLo9XrodDrodDro9XpFR7ZlJds+Pj748ssv8e2332LFihW4fv06bt26Zdhfp04djBo1Ck899VSZNc+uTq/Xm8TPpIcqA1e+JCIi+pderzdLjqXvrW3X6XQoLi5GUVERiouLUVxcDK1Wi+DgYGRlZZkcL4oi6tevr1i8sidIqlQqjBs3DuPGjcP169eh0WgAAJGRkahdu7ZiAdoiLS3NUD9erVo1xc67f/9+BAUFISQkBMHBwfDz9YNe7wdR9IcglHz5+AhMesipuPIlERG5M+NEuPT/y9onJcRardbwf+NEWqfTQRRF6HQ6ADBsFwQBoihCFEWoVCqIYknZpY+PDwRBgEqlMvw/MDDQ8L3xdiUp0o2kdu3aiifYa9euRUJCAgAgKSnJsE2qEe/Tpw/69OkDAFi5ciUWLlyIyZMnY8qUKSbnef311w3/l0bfjbe9+uqrVhN0vV6PjIwM3L5923AhH+gD/LTJDyJ8ofLxx1Ojg5CREYaCgkD4+/ubfPn5+bl9RxZyDWyBSEREFcE4kTVOiMtLmIuLi6HT6QyJsZQcl06KRVE0jB4bjyRbIiXGlr58fHzg5+dncZ89qlSp4vQqDKe2/nNEQkICNm7caLItMTERiYmJAICoqChDsl2W0ucovW3y5MlWk+3w8HCzbXXqiOjUsQgZmf7w98tAaGg+zp+/aXihCIIAPz8/+Pn5wd/fH4GBgQgJCUFgYKBhm5SI+/v7w8fH9hZuGo3IZMuLceVLIiKSSMlr6eTX2nZLJRWWEmNLXwAMiXLpxFgaRQZMR45VKhUEQTBsK50clz7OkwmitbcTRqZPnw5BEPDyyy+jRo0amD59uu13IAj46KOPHAqysuzevdvqvipVqiArK8tsu16vN/vIQyq8B0qeD19fX8NXQEAAgoODERwcjICAAEMSbvyvIAhs/eYC2BbKO/G6eyded+/jrGsuNymWtknJcOkyCkujxaVHjI0ZJ8WlE93SI8PGSXLp4zwtMbaWz1laIV0um0a2N27cCEEQMGHCBNSoUcPiaLE17pxsy6FSqRAQEICAgACL+6VZr9IPTW5uLjIyMgw/LNI5fH19DSPkBQWBeP/DYEAI/P9acT/MmOWPVi39ERUVYNfoOBEREZmSklZLo7sVnRSXVjoJLp0QS7XGlhJncg02JdvfffcdgJIuI8bfe6u0NBHJycUIDRVRrZp97/CMy0yCgoIsHmM8KaC4uBj/nE9DQcFNADoAAgAREHyx/Rc/NGtaMvotTeK0NDru7+/vce9EiYjI8xknpJaSYGv7Su83Lp0o/a90TEhICLKyskxuK5VNGP+/NGnEmEkxWWNTst2hQ4cyv/cme/eJ+O57EXp9DlQq4MlRwL3dlE1kVSqVIUkGgOi7RQQE/NvfGwAEoRj16hZDEHTIz89HdnY2tFqt0X7BZHRcqh0PCgqyWDvu6+uy5ftEROSCbEmELY0Cl76dpQS4dOs2S5PqAJjsLx1b6UGm0qUQlv719fW1mCwzKSZHyMqwDh8+jBo1apS7FPvly5dx69YttG/fXlZwriYtTUq0S77X64HvvhfRojnsHuG2R7VqAp4cBcN9lyT5fqhTx9/qbUqPjmdmZuL27duGX0rSO22pdtzPzw+hoaEIDAxEQECASaJu/MVfNkRE7qG8UV9LiXDphNa4w0R5ibDx92WNBhsnwdKIcHlJsEqlMsxhsnaco6pUqeLwOYgskZVsjx49GkOGDCm3Fvurr77C+vXrcebMGVnBuRrNLcuL2mhuAWW1905LE6G5BURGyE/K7+0moEVz2Hye0qPjlhi36CksLERubq7JZE7pPMZJeUBAAIKCgiwm5b6+vobRciblRERlK52klk5gLXWRsFQaUToRNi6NsDT6DFgfES7NliS4IhJhIncmu3bAhiYmNh3jTiIjLK/kFxlh/Tb/lp1II9Lyy06qVRPKTOrtJdWQlcW4zq24uBi5ubnIysoqNyn39/dHcHCw1aRcKl9xx6ScLRiJvIu1CXGlE19ro8jGE+aMJ9FZG1EuPYnOuIsEYNpVwlpyW3rxjrISZiJyLqcW6mo0GgQHBzvzLiqU5XIOweooc2WVnShJSsjLGiEHzJPyvLw8ZGdno7i42ORjxNJJuZ+fH4KDgxEUFGQ1Kffz83OZjivmLRjBFoxElayspLe82mFpu3ESXFxcjJCQENy5c8fs2NLlEcadpKyxNBJs/L1xnbBxksxkmMgz2Jxs//TTTybfJycnm22TFBcX49KlSzhw4ADuueceR+JzOVI5R05uCEJDcstMmuWWnbgjuUl5fn4+cnJyyh0pl7q3SB1XSiflxl/O+sjyxk2dIdEGSq7lrNkiOrTnCDdReWxJeMv6Mi6ZkH5/lG6tVt4IcVlKj/hK5XXGSbBxqUTppJmIyBqbk+3XX3/dkMQIgmCymqMloigiICAAkyZNcjxKF1OtmoAGDXyRlVV2giWn7MTTKZWUG0+qkZJy43MHBAQgMDDQ0GlF+kMp/d84Obf1D+WVK3qLb55SUsGVHcljSclw6eTWeJtxqYSl+mHjRTwsJcHGybDxv8Z/cwDLJROWOklYWoRDzhLO5f2eIiKyhc3J9qRJkwx1Yp9//jmaNWuG3r17WzzWz88PkZGR6Nq1KyK9OAuxt+yE/mVrUm48W176ysnJQWZmpskfeInUElE6v5R4S7XlUp9yabtxgl6rVgAEQQdR/LekRaUqqd0mz6TRiEj6R4uq4aJbf3ph6eekrIS5sLAQRUVFJivgll6cQ1/6nSdgNuprqY6YE+mIyNvYnGxPmTLF8P+NGzeic+fOmDx5slOC8iT2dhEh+0hdV2xlnDRIiYY0ai5tK72krTS5SK1WY+CDeVizzgeAP3xUgZjwdADy8wOQkmJa8lJ69NxVcHKn7f6tz8+q9Pp8afS3rIRZem1Lo8uFhYWG/xtPxpPmUVirNTZeeEP6v/TGt/R2IiIqn6wsoE+fPggJCVE6Fo+ldBeRyqBE+0JnsyVG4zZVtpCSEp1Oh4CAAHTunI+77y7ETU0e1FV1CAvT4+RJ04RFSkSkRNu4tEX6kmrL5XwBkHW7rdvAyZ1lkCa8iaKImzf1mPmJDnq9CECEXi9i5iciYlsANWqYHlvel/FkOuMSidLHWJrQJ40uS0tIl+5vrNPpLD4W49XqjF+PpbdzJJmIyPlkJdurVq1Cr169lI6FnMTRRFnJ9oXO4qwYpbITX19fhISEQKfTISwMKGs9J0ujjgUFBSaJUln3Z2lb6WS7rH2WtmVkAO99AIiiCoAKgIB3/yvA388H1atb7pBgz+pplkZIS9fglrdd6XOVTm6tLdphafGNpH/0yMnWSycCIEKEHr/8AjRqZH4fpZNpuYxLKYzbtkkJckBAgNnoMhNmIiLXJivZrlmzpsf10K5oFTVS7GgS6g7tC10tRlv6l9uqrBFRe77X3NL//yht8f8nj0CxXsSlyyWvC1vPB/z7hsCe3wHWEkJ7tztyH+W9MTH+vmakD3xUPtCLAvD/+3xUAurXV6Fq1ZI3HaUTY0tvhoiIiGQl23379sXGjRuRk5OD0NBQpWPyeBU1UqxEEuoO7QvdIUa5lErgGjUU4ecnmjxPKhVwdxPXmbDrSqVKYWHAU2NK/5wKqF3bNZ4rIiJyH7KS7cmTJyM+Ph7PPPMM3nrrLTRv3lzpuDxWRY7CKpGEukP7QneIsbK5emccVyxVsqenPhERkTWyku2JEyfC398fiYmJePTRRxEREYE6depY7AohCAKWL1/ucKCeoiJHYZVIQl09SQPcI0ZX4KqdcVytDMiYrT31iYiIrJGVbB86dMjwf1EUodFooNFoLB7LGkZTFTkKq1QS6qpJmjF3iNEVuGJnHE8uAyIiIpKVbP/2229Kx+GSrl69iuDgYAQHByMwMFCRNw4VPQqrVBLqiklaae4QI5ljGRAREXkyWcl2VJR3LJk3ZswYw/9VKhWCgoIMyXdYWBgCAgIM30tfQUFBCAkJMfm39DFduwSiRXOhwkZhmYSSK2MZEBEReTLXWdrOBYWEhCAvL8/Qhzc3Nxe5ubkOn1cQBJMk3FqCbi1ZL53ccyU3cncsAyIiIk/lULKdlpaG9evXIyEhwVCzHRkZiXbt2mHw4MGoXr26IkFWls2bN0MURRQUFCAvLw95eXnIz883JNy3b9822WbpX+l20pe0eIb0vRKkhLys0fTyRuClbUr1hyayFz+BISIiTyQ72f7111/x5ptvIjc312Rxi9OnT2PPnj348ssv8dFHH+H+++9XJNDKIo1CBwUFmbx5qFKlCrKysuw615979Vi+ogC64nyIyMVD/fLRNKbAJEG3lryXTtrz8vIMSzXn5+cjPz9fkccbGBjoUNJufBtfX35wQkRERN5NVjZ04sQJTJs2DXq9Hn379sXDDz+MunXrAgBSU1OxadMm7Nq1Cy+//DJWr16Nli1bKhq0O0pLE7FiJQAEwsc3EIAau34H+vaRV5sqiiK0Wq0hQS898l5eol76q7i4GABQUFCAgoICpKenO/yY/f397UrQy0rw/fz8HI6HiIiIqKLJSraXLFkCnU6HefPmmY1cN23aFL1798auXbswefJkLF26FPPnz1ckWHemdHszQRDg7+8Pf39/qNVqh+MrKioyS9jlJu9ardZwzqKiImRkZDgcn5+fn12TUMv68vPzY0tKIiIiqhCyku2EhAS0adOmzBKRPn36IC4uDkeOHJEdnCdx9fZmUuJetWpVh8+l1WrNEnVbRteNk33p/4WFhYZzZmZmIjMz0+H4fH197e4gExwcjIiICIiiaLLN39+fibsDXGmJdiIiImeQlWxnZ2ejdu3a5R5Xu3ZtnDhxQs5deBxvam/m5+eH8PBwhIeHO3wunU5nc4Je3gh8QUEBAKC4uBhZWVl219xb4uPjo8hoe3BwMAICArwqcXfFJdqJiIiUJivZjoiIwNmzZ8s97uzZs4iIcJGhWxfA9mb28/HxQVhYGMLCwhw+l06nkzXKLiXvpctrpHNmZ2cjOzvb4fikXu72Ju2WOssotQiTs7jyEu1ERERKkpVsd+vWDWvXrsXcuXPx4osvmv1RF0URc+fOxcWLFzFs2DBFAvUUtrQ340frzuHj44PQ0FCEhobKur1xBxq9Xl9u4m6cnFvbJiXxzujlLiXiZSXo1pJ2Z/dy5xLtRETkLWQl2xMnTsSOHTuwePFibNu2DQ8++CCioqIgCAJSUlKwbds2pKSkoGrVqpg4caLSMXs0frTuHlQqFUJCQhASEuLwufR6vUkvdzklMsZfoihCFEXFEncA5Sbt1hL10tukXu6uPoeBiIhIKbKS7Vq1amH58uV45ZVX8M8//2Dx4sWG0W2p53Z0dDQ+/fRT1KpVS7loPRw/Wi+fJ476q1QqQzLqKGkRptIJutwJq/r/fzFKI/B37txxOMbAwEAEBwdDEIKQkxMCQRUElSoYTRoHY/nyYLvKaLgIExERuTrZq47ExMRg8+bNiI+Px5EjR8xWkOzYsaNiQXoLfrReNo76l894EaZqDr5oRFFEUVGRzQl6WSPwubm5hkWYpF7upR0/XvJlj4CAAIdKZIy/uAgTERE5g8N/XTp27MjEWiH8aN06jvpXPEEQEBAQgICAAIfPJS3CpFRnGamXe2FhIQoLC52yCJOUoFepUsWkz7utvdyJiIgABZJtSU5ODgDInnxG3tUe0F4c9XdvxoswKdnL3VKCLo2kl1c2I+0vKioCoPwiTEp1luEiTERE7s2hZHv37t1YuXIljh49iry8PAAlE6ni4uIwcuRI9OrVS5EgvQnbA1rGUX8ypmQv9+Li4jJH1fV6PdLS0kwSdWtJvPEiTFqtVrFe7rYk7eWVz4SEhHARJiKiSiAr2RZFEW+++SY2btxomBBZpUoViKKI7Oxs7Nu3D/v378cjjzyCGTNm8Je7nWxpD+htOOpPzuLr64sqVaqgSpUqFvcbt3wsj9TL3VrLR3smqUp17TqdTrFFmIwn48oZZTfe5uq93ImIXIWsZHv58uXYsGEDIiMjMXHiRAwYMMBQPpKTk4MtW7Zg0aJF2LRpE5o2bYqnnnpKyZjJS3HUn1ydo73cjUmJu6OdZaRjgJI2kzk5OYayP0dIizDJSd5Lt4dk4k5EnkwQpaFpOzz00EO4fv06fv75Z9SrV8/iMVevXsXDDz+M2rVrY9u2bQ4HWhl2795tdZ89o11Uwt3b9vGaeyc5193VXutSL3clOstIvdyVJHXRKS9Bt7WcRolFmPjz7n14zb2Tteves2dPxe5D1sh2SkoKunbtajXRBoB69eqhU6dO2L9/v+zgyHOwbR95C1d8rTujl7tSnWX0ej1EUTR8rwQpEXdkkqogCNDpdOzlTkQOk5VsV6tWzabWVn5+flCr1XLugjwI2/ZVDFcbTfVG3vBaN+7lXr16dYfOJYoiCgsLy0zU7UnepV7uUvmNEgIDA+1K1ssqm2EvdyLvJOsnv0+fPti8eTMyMzOtdgPIyMhAfHw8BgwY4FCA5DzSiBIAwxLfSn88DACp10QUF5ueV68HUq8JCA0VFLlPQRCgUqlM/vUmrjia6o3YotI+giAgMDAQgYGBii3CJGe03VLiXlxcDODfRZiU6uVuS0cZW8pm2MudyH3ISrZfeuklHD16FGPGjMFrr72Gzp07m+w/cOAAPvnkE9StWxdTp05VJFB3YZy0iqJoWO669HbjxLasfdYS4tLHCYJtSWvpJFQQBEOCqjTpvoICRUAE9EbhqQQgKBDIzLScEGZmirh9R0CN6kDVquUnjdLzrNPpDM9LZiZwJw2oXk1EeLhgEpNxYl46SZe2ld4undvVEnlvGE11F2xRWXmMF2FS4hPVwMBA3Lhxw6ZR9vISfGkRJqmXuxKJu6WFliyVzViblGq8zd/f3+F4iMg6Wcn2xIkT4efnh1OnTmHcuHEIDw9HnTp1AADXr183LApxzz33YOLEiSa3FQQBy5cvdyzqCnL79m1Dwmz8LwBkZmZanNFvnLwaJ2Wlt5VOco2TPKCkq4F0vPR/4y8fHx/DPulcZd2H8THWtkm3sYXdCacg4rP5IkQ9IKiAl19QoV8/y+f45RcRcxeI0IslSfnUFwSLx0oxlL5Ger0ev/xSjAVf6KDX66ESRDw7QY+ePUr263Q6FBcXQ6vVGv6v0+kMX9Jqh9K5pES+sLAQWVlZZm9qSr/RsZasl97m4+Nj+Crr+SyvPISjqa6DLSo9h7QAk5KLMFlL0G1J2qX9xr3cMzMzkZmZ6XB8vr6+drWBLKuchr3ciczJ6kbStGlT+XcoCDhz5ozs21ekXbt2wdfXFz4+Pib/qlQqqNVqZGVlmY2Elk60LH2Vtc+Tf0lpNCJSUoG6UUBkpOXHqdGIGDpcNBsZXLdGsHobJc8hiiJ0Op1Joi19ValSBWlpaYbvpeOMk3wpcZf+1Wq1hv9bOqd0m9I/hlISfviICus2qCDqfaDy8cGokb64715fk0lbaWkiXnvD/PF+/BGTPCV4QjcSsp+rdqbQ6XQ2J+jl1blLvdyV5OPjY1eiXlbyHhAQUKF/E131mpNzuWw3kt9++02xAFxZ27Ztre5Tq9WKfBToTSIjBURGln1MSqrlUdqUVJR7WyXOIQiC1UlMjn40bZyUl07MpS8pQS8sLMT16wVYv7EAoqiFCB2KiwuxfIUetWvpEBZmmpwP7C9g408q6EUf+Kh8MGyYLwIDfVFYaNvoOSnL0sJUTMBJCT4+PggLC0NYWJjD55J6uTvaUUY6TjpndnY2srOzHY7PuIuOI51lgoOD2cudKpWsZDsqKkrpONyKRiMi6R8tqoaLNo+2km3qRlmuea1rx0tOiXM4g1T2I41KBwQEmOzXaETcuFkSZ6NGAvILRAQFS3X5xRDFkq/adfRo0VxnUgZz991F6H5fAVJSi1A1vBBhYToUFBQYRtSl8hgpDlEUTcpYpC/pExypdImUwQms5IqUXIRJr9cbEnE5K6aWPlYanFBqESZBEMpcXCk4OBhqtdpkZN5agq9UL3fyHuxDZKctW0XMmi1Cr8+CSgW8Og0Y0N/z/2jaUgKihMhIAa9Ow/8/x/j/59j2EhKlzlEWZzwX/76uYHhddWgvvWkQAPhBEPygUgHNmgqoUcP8fqOj//1/6RFza6PnhYWFKCgoMOwrLCw0qV0vXYvu6+sLX19f+Pn5wc/Pz5Cck3WcwEreQKVSISQkBCEhIQ6fS6/Xo7Cw0OKKqbYm78ZJvFTul5ubi9zcXNy+fdvhGMsbWbeWqJfeFhQUxN+hXkBWzbYkLS0N69evR0JCAjQaDQAgMjIS7dq1w+DBgx3uwVrZSpeJKFFP7I7ME0HB6W8wlEholU6K1Wo1VnyfpvhzUdbr6tBh8zcNznjupbIW44S89P+l5DwnJwdardbwpTcK3N/f362TcUulHo7WcZ49J+KT2ea/Zv8zTUDTGM/9veHuWL/rGaRFmEon6paS9+LiYmRkZJSZvOtL1ygqIDAwUFb/dktJvDv9vnUVLluzDQC//vor3nzzTeTm5pqMfp0+fRp79uzBl19+iY8++gj333+/IoG6AiXqid2NRvNvog2UPN5Zs0V0aO/8EW5Hn1MlzmHsxk2dU56Lsl5XA/oL6NAeTv9UQaVSwd/f3+YWYFqt1tDGrKioCFqt1rCqoJSM5+fno7i42PDHSRAEQwIuJeN+fn4u83Gss0o92A6QqPIYL8JUXi/38t5gSb3cHSmRMf5XWoRJ6uWelpbm8OOVFmGSm7Qbf3ERJuXIeiZPnDiBadOmQa/Xo2/fvnj44YdRt25dAEBqaio2bdqEXbt24eWXX8bq1avRsmVLRYOuLK5aC+xM1hLB3/8Q0auHcxNuV3Plit4pb7bKe10p/aZBCVKibO0j49LJeFFREQoKCgwfCxcVFVlNxqWEXBolr4hkvKxSjypVHDs32wESeQbjXu6OklrM2loOU15vd6mXu9KLMCnVWcbbF2GSlWwvWbIEOp0O8+bNMxu5btq0KXr37o1du3Zh8uTJWLp0KebPn69IsJXN2bXArshSIggACxcBi74UvaZmHQDq11c55c2WJ76ubEnGCwsLTf41TsY1mkLcuJGH8PBiVKny78ROZyXjZfUqb9DA4dPj3m4CWjQHu5EQEYCS32fSp4lK9nK3NppuT+17UVERgH8XYZLWTnGE8SJM9nSUsdRZxs/Pz+06y8hKthMSEtCmTZsyS0T69OmDuLg4HDlyRHZwrkj6WD8zKwzhVbLdOiGyRelE0FhFlZS4ilo1ffDqNMEpSXFFlYu4CilptmTzFj1mz9NCV1wICFpMfLYI3e8rNvnDIC3LLY2MSz3qjctTpKTclmS8Iko9LLUDJCJSgp+fH8LDwxEeHu7wuYqLi+1uBWktiXfmIkxy2kGWTt4ravVUWcl2dnY2ateuXe5xtWvXxokTJ+TchUuLjBQQE+OH9HTPTogkUiL4+x8iFi4y3efpNeulOTMpdsVykYqm0Yj4ZA4gin5Q+ZQk40u+Bu7vK6BevX9XDC2rTCU/P9/QyaD0gkFSAl76q1o1FUs9iIhQksxWqVIFVRytocO/izA52sfdeBGm4uJiZGVlKTKBWaVSITQ01OIk1UqfIBkREYGzZ8+We9zZs2cREcFZQJ4gMlJArx4lpSPeVLNuCZNi57FlErLxx6+WlE7GCwsLDd1UpF/kUnIudVwRRRGNGgIvTRGRkemLmpE+iIjwR06OD/z9/aHT6TjLn4jITs5chElOiUzpRZj0er1iiXtZZCXb3bp1w9q1azF37ly8+OKLZrUzoihi7ty5uHjxIoYNG6ZIoFT5PLG2mFyLEpOQy0vGgZJfsFJCXlxcbOioYlw7LtWSZ2dnIz093dA5oCQmlcURcl9fX7erJTTGVS6JyFUpvQiT9Lvex8cHN2/eNEvQlSSrz/aNGzcwaNAgZGZmol69enjwwQcRFRUFQRCQkpKCbdu2ISUlBVWrVsXGjRtRq1YtRYOuKGXN5vXm5doraoEbV+PN17wiKdXX3dHXqSiKKC4uRkhICG7dumWSkBcWFhpGR7RarUmPcuNfqVKbQx8fH5MSFldpd2jMvPWh4NWrXLLPtvfhNfdOFdFnW/aiNufOncMrr7yCf/75p+REwr/1lAAQHR2NTz/9FNHGy9q5GSbbZIzXvOI4migruRBTede9uLjYZJEf6UuaxCm14pKO0+l0hhXtBEGAj4+P2ei4lKBXlLQ0Ea+9YV4i9vFH3lu3zsTL+/CaeyeXXtQmJiYGmzdvRnx8PI4cOWK2gmTHjh0dCmzTpk1ISEjAyZMnkZSUBK1WixkzZmDIkCF2nUev12PVqlX44YcfcOXKFQQHB6Njx46YOnUqGijR04uIFOdIXXxFL8QkJchBQUFWjymvbEWatS99L63aKYqioWTF39/fpNOKkuUqZbU+ZAcVIiLHyEq2J0+ejIiICLz77rvo2LGjw4m1JfPmzUNqairUajUiIyORmpoq6zzvvvsufvzxRzRp0gSjRo3CnTt3sG3bNuzfvx9r1qxBkyZNFI6ciCqTK670qlKpyl0MQypbMU7ICwsLDZ1VcnJyLHZZkUbCpTp1OWUqXOWSiMh5ZCXbe/bsQZ8+fZSOxcSHH36I+vXrIyoqCkuWLMHs2bPtPsfBgwfx448/ol27dvjmm28ME6YGDRqEsWPH4r333sP333+vdOhEVIncdaVX4z7hlkhdVgoKCgyJeFFREXJycpCTk4OioiJkZmZCq9UaEnEfHx+zEXFL5Slc5ZKIyHlkJdt169Y1tE1xli5dujh8jrVr1wIAXnrpJZPOBJ07d0a3bt2wd+9eXLp0CQ0bNnT4vojK4q2TSiuDp3bNKa/LijRx09qIeE5ODrRaLfT//y5EmrQpfXXp7I8WzVXsRkJEpDBZyXb//v2xbNky3Lp1y6X7aMfHxyM4OBhxcXFm+6Rk+/Dhw0y2yanMJ+t5zxL3lcXbVuQEyl6VU+ozbjwiLiXiUrurzMxM6HQ6hIUCBQUCbt/2N5SnSJ1UiIjIfrJ+ez777LM4fvw4Ro0ahVdeeQU9evSw+ku+suTl5eHWrVuIjo62+LGpNDny8uXLFRsYeZWKnqxX+r69KdksjYsP/UuaxBkSEmK2T6fTmSXi+fn5yMnJMSwOkZWVheLiYsNtpATcOBF35/7iRETOJCvZ7tevH0RRxPXr1/HCCy9AEARUq1bN4uQfQRCwa9cuhwO1V3Z2NgBYbX4ubc/JybF6jvDw8DInGqnValmx3bipw5UretSvr0KtmlyVzp3Ye82T/tFCrzdtKaTXA5lZYYiJcd4b1PUbCvDeB7mG0fT33g7Go0MCnXZ/nk7uz7q70+v1htU2pdKUgoICZGdnG+rEpRaHQMnve6lzijRZ09/f3yX7ittCieWqyb3wmnsnZ193Wcl26c4goiji9u3bigTkSjIzM63uk9tzWcn+v1SxbL3mxiPKVcMtT9YLr5KN9HTnXHeNRsR7H5iOpr/3QS5iW+R55Qi3o9hfvYSUQIeFhSEiIgKiKJqMhksJuVSekpuba2hxKIoiRFE0qROXknFX+1RUwp7L3ofX3DtVxHWXlWyfPXtW6TgUFxYWBsD6yLW0XYllP21VmSUFVDEsvZl6dZpQoZP1XLH1HXkeQRDKbGdoPGFT+srPz0d2djby8/ORn59vWOhH6icuJePG5SkVubgPEZEzeOyMl+DgYERERCAlJQU6nc7sF7ZUq12RC9swCfJs1t5MrVsjYN0aocLqp9219R15lrImbErlKcadU4wnbUqJeXFxsaF7ikqlMumewlpxInIXHptsA0CHDh2wdetWJCYmon379ib79u3bBwBm253JniTI3slt3j4ZzhWU9WYqrk3FTdazpfUdXy9UmVQqFQIDAxEYaHkegaXuKQUFBcjJyUFeXp7h/1qt1nAb48V9KmPJeyIiaxxKts+ePYvVq1cjMTHRZLn2uLg4PP7442jevLkiQZYnLS0N6enpUKvVqGa0tvBjjz2GrVu3Yu7cuSaL2hw4cAD79u1D+/btK7Ttn639f+1tFcfWcq7BlUaUy2p9x9cLubqyuqeIomhSnlJ6cR+tVmvWU1xaMMh4gR+OihNRRRFEaakxO33++edYtGgRdDqdxf0+Pj547rnnMGXKFFmBrV27FgkJCQCApKQknDp1CnFxcahfvz4AoE+fPoZVLBcsWICFCxdi8uTJZvf31ltvYe3atWjSpAm6d+9uWK49ICCg3OXay5oU5cikqbJGFTUaEUOHi2YJ27o1lut87T2e5LPlmrv6BFi+XuzHCZLuxXhU3LhWXBoVLyoqQnFxsWHJe0EQoFKpzFbaVKvVnCznZThB0jtZu+49e/ZU7D5kjWz/9NNPWLBgAYKDg/HEE0+gf//+qFu3LoCSTiVbtmzBqlWrsGjRItSrVw+DBg2y+z4SEhKwceNGk22JiYlITEwEAERFRdm0ZPz777+PmJgY/PDDD1ixYgWCg4PRs2dPTJ06tdIWsymr/6+9dd2sA3ctrr6YCl8v5OnKGxU3Hg0vLCyEVqu1uNKmNFJuXCvOBX6ISA5ZI9tDhgxBUlIS1qxZg9jYWIvHnDx5EsOHD0d0dDQ2bNjgcKCVwVkj22XhyLbr8oQRTr5e7OcJ151sYzwqHhQUBI1GY9JBRavVQqvVWlzgx/iL5SnuiSPb3sllR7YvXLiAjh07Wk20ASA2NhadOnXC4cOHZQfnjWyt65Z7PHk3vl6IrDMeFVer1SYTOPV6fZmTNqUe41IrQ0EQ4OPjY5aMc9ImkfeRlWyHhoYiPDy83OPCwsIqtI+1p7C3FMHVSxfItfD1QmQ/lUqFoKAgBAUFme0TRdGkr3jpVobG5SmWWhmyPIXIs8n6yb733nuxb98+FBQUWG3dVFBQgMOHD6Nbt24OBeityqrrVuJ48m58vRApRxAEwwqbllhqZVh6gZ+srCzFylPS0kRobgGREUC1anwzTVTZZCXb06ZNw6FDhzB58mS8/fbbhg4hkitXruDDDz+Ev78/XnnlFUUCJSIickdlTdq0tTzFuHuK8UqbUlIuJeJ794n47vt/y8SeHAXc240JN1FlkpVsz5kzB02bNsXvv/+OBx98EM2aNUNUVEkz4dTUVJw9exZ6vR49evTAnDlzTG4rCAI++ugjxyOncnHhEiIi11ZeeUrp7imly1MyMjIMdeLZ2Sos+9YPougPQQiAKPrhu++BFs05wk1UmWQl28Yt+fR6PU6dOoVTp06ZHbd7926zbUy27SM3YebCJURE7k0QBAQEBCAgIMDifq1Wi/z8fMOS94cO50AQMiGK+dDrsyCKRSjWijh9WoWmTUvOI42Gs2MKUcWRlWx/9913SsdBFshNmDWaf28HlPRRnjVbRIf2HOGmysFPWYiUJ9VyS/z9RYSGidDpiqHX50MUCwEUoF27Avj6ZiEvLw9ZWVmGiZpSrblxEq5SqSrvARF5KFnJdocOHZSOg0pxJGHmwiUklzOSYn7KQlQx/m3t6QtBCINKFYZXpwno1Knk5624uBgFBQUoLCw0mZgplaUUFRUZ6sKNa8L9/f3ZspDIAewz5KIcSZjrRpUkNaUXLqkbpXyc5DnKS4rlJOL8lIWoYpXV2tPX1xehoaFmLXl1Oh0KCgpMvjIzM5Gbm4u8vDykp6dDWv/OOAFnEk5kGybbLsqRhJkLl5C9ykuK5Y5O81MWoopnb2tPHx8fhISEmHVL0ev1Zkl4VlaWoVNKRkaGoRzF19fXpCSFSTjRv5hsuyhHE2YuXGIZa4ctKyspBuSPTvNTFiL3pVKpEBwcjODgYJPtUrtC4yQ8OzsbOTk5yM/PR2ZmJnQ6HYCS0XTjmnAu3EPeiK96F+ZowsyFS0yxdti6spJiR0an+SkLkeex1q5QFEVDTbhxEp6dnW34v7Rwj5SEcyScvAGTbRfHhFkZrB0uW9lJsejQ6DQ/ZSHyDoIgWE3CpfaEUqvCrKwswwqa0kh46YmZAQEB7I5CHoHJNnkF1g6Xz1pSrMToNN80khws+/IMgiAgMDAQgYGBCA8PN2w3Hgk37o4i1YRLEzOlJNx4JJx9wsmdMNl2A/yD4zjWDpfN+DUW18b8NcbRaapoLPvyfMYj4VWrVjVsN56YWToJN+4TrlKpTBJw42XriVyJ4sl2Tk4OLl26hFq1aiEiIkLp03sdV/6D405vAlg7bJ2trzGOTlNFYdmXd7M2MVOn0yE/P9+QiOfl5SEzM9PQGUWr1RpuLyXgAQEBJgv/EFUGWcn2vn37sHXrVowePRrNmzc3bF+1ahVmzpwJrVYLQRAwZswYvPbaa4oF621c+Q+OK78JsIajs+Zc+TVG3otlX2SJj4+PxT7hxcXFJkm4NAKen5+PvLw8QxLu4+NjMhLOzihUUWS90tauXYs9e/bgzTffNGw7f/48PvzwQ6hUKtxzzz24ePEivv32W7Rv3x69evVSLGBv4qp/cNw5QePorClXfY2Rd2PZF9nD19cXYWFhCAsLM9leVFRkKEUpLCxEdnY2MjMzzTqjSJMyfX19odPp2BmFFCcr2T59+jSaNWtm8u5y/fr1EEURM2bMwMCBA5GamoqHHnoIq1atYrItk6v+wWGC5jlc9TVG3o1lX6QEqatJlSpVDNtKd0YpvVDPnTt3oP//X4jGXVH8/f3ZGYVkk5Vs3759G7GxsSbbDhw4gCpVqqB///4AgKioKLRr1w7nz593PEov5ap/cJigeQ5XfY0RseyLnKGszihBQUG4fv26SRIuLdZTVFRk1hlFSsaZhFN5ZCXbvr6+hhooAMjNzcU///yD7t27m7zoqlWrhsOHDzsepRdzxT84TNA8iyu+xogAln1RxZE6o6jVaqjVasN2vV5vKEMp3RmFSTjZSlayHRUVhVOnThm+37NnD3Q6Hbp27WpyXEZGhkk7H5LHFf/geHuC5k6dWGzhiq8xIqLKplKpEBISgpCQEJPtOp3OZLl6aXGe3NxcQxKu1+shCIJJZxT2CPdOspLthx56CHPmzMGUKVPQvn17fPXVV/Dz80OfPn0Mx4iiiFOnTqFhw4aKBUuuxVsTNHfsxEJERMrx8fGxmoSXHgmX2hMa9wiXknDjkXAm4Z5LVrI9evRo/P7779i5cyd27twJlUqFV199FTVr1jQcc/DgQaSlpWH48OGKBUtkSUWOMrtzJxYiInIua+0JSyfhUvJdOglXqVQmo+BMwj2DrGQ7KCgIq1atwpEjR3Dnzh00a9YMDRo0MDlGpVJh+vTp7ERCTk2GK3qUmZ1YiIjIXmX1CDcuRykrCS+9UA+TcPchu6O7SqVChw4drO7v2LEjOnbsKPf05CGcmQxXxigzO7EQEZFSfH19y1yop7Cw0GS1zPz8fGRkZKC4uNgwMZNJuOvj8knkNM5OhitjlNndO7F42sROIiJPZG2hHuPVMgsLC5Gbm2tYLbP0kvWly1Go8jiUbOfn5yM+Ph6XL19Gbm4uRFE0O0YQBEyaNMmRuyE35exkuLJGmd21EwsndhIRuTdrSbhWqzWUokhJuPFIuKUl6wMCArhaZgWRnWxv2LABM2bMQE5OjmGb9JFG6e+ZbHsnZyfDlTnK7G6dWDixk4jIc/n5+cHPz6/MJeulZeqzsrIMi/bodDoApqtlBgQEsBRFYbKS7b/++gtvvvkmwsLC8OyzzyI+Ph7Hjh3D+++/j+TkZOzcuRNXrlzBqFGj0KJFC6VjJjdREcmwu44yVzRO7CQi8j7Wlqw37g9eeqGetLQ0k0mZLEVxnKxke9myZRAEAd999x2aNm2K6dOn49ixY3jssccAAFOnTsWsWbPw448/GraRd3JmMmxcfxzXhkl2WTixk4iIgH9Xy5RWzJRI7QmlRJylKMqRlWyfOHEC99xzD5o2bWpxv4+PD1577TXs2rULCxYswIIFCxwKktybM0ouWH9sH3ef2ElERM5lrT0hS1EcJyvZzsvLQ506dQzfSx8t5OTkGC6SSqXCPffcgwMHDigQJtG/WH8sD0tuiIjIXixFcZysZDsiIgLp6ekm3wPA5cuXERsba9iemZmJgoICB0MkMsX6Y/ncbWInERG5HkdKUURRhK+vr1eVoshKths2bIhLly4Zvm/Tpg1EUcTSpUsxd+5cCIKAxMREHDx4EDExMYoFSwSw/piIiMgVySlFyczMhE6ngyAIhtFv6ctTknBZyXaPHj2wf/9+HDt2DK1bt0bnzp0RExODHTt24N5770VkZCSSkpKg1+sxZswYpWMmL8f6YyIiIvdhbymKtGKmVA/u4+NjOIfU5lClUlXWw7GbrGR70KBBaNCggaF8RKVSYcmSJXjjjTdw4MAB3L59G2FhYRg/fjweeeQRRQMmAlh/TERE5M6slaLo9XoUFhYalqovLCxEXl6eYSQ8Pz/fUI4ClPQYl5Jw6V9XIyvZDgsLw7333muyrWbNmvj666+Rn5+P7OxsVK9e3WOG/8k1sf6YiIjIs6hUKkMSXlpxcbEhAZf+lSZlSitnSi0KpbIUKQmvzLIUh5Zrt8TaE0REREREJJevr6/FmnBRFFFUVGQYEZdGw7Ozs5GXl4e8vDxkZGRA//+TvYzLUgICAsxWQFc8bqedmYiIiIjIyQRBMHQ2KU2v16OgoMAwSVMaAc/OzkZBQQEyMjKQnp5uVpaiJJuS7WnTpmHSpElo1KiR7Du6cOECFi1ahNmzZ8s+BxERERGRrVQqFYKDgxEcHGy2T6vVIjg4GDdu3DBpV5iTk6NoDDYl2/v27cMvv/yC3r1745FHHkH37t3h61v+TYuKirB7925s2rQJf/zxh8ksVCIiIiKiyuLn54fQ0FBUr17dZLs0yq0Um5LtXbt2YdGiRVi5ciV27tyJKlWqoHXr1mjZsiUaNmyIKlWqICQkBDk5OcjMzMTFixdx/Phx/P3338jNzYW/vz/Gjh2L5557TtHgiYiIiIiUpHT9tiDakb7funUL69atw/r165GSkmI1IOmUdevWxbBhw/Doo4+iRo0aCoVccYxXySxNrVaXuZ88jztdc41GZFtEhbjTdSfl8Lp7H15z72Ttuhu3I3SUXRMkIyIi8Pzzz+P555/H+fPnceTIEZw7dw537txBTk6OYSi+adOmaNeuHRo3bqxYoERkmy1bxVIL/pT0JSciIqKKJ7sbSZMmTdCkSRMlYyEiB2k0/ybaQMmS9rNmi+jQ3v1GuDk6T0REnoCt/4g8SEoqDIm2RK8v2e5OCwBxdJ6IiDyF+ywsT0TlqhtVkpwaU6lKtrsLa6PzGo2ys8OJiIgqApNtIg8SGSng1WmCIeEuGRUW3KoMo6zReU+g0YhIPMo3D0RE3oJlJOQyHK3RZY1viQH9BXRoD7d9LqTReeOE291G561heQwRkffhyDa5hC1bRQwdLuKFqSX/btlq36ifo7f3NJGRAuLauNeItsQTRuctYXkMEZF34sg2VTpHO2h4UgcOKuHuo/OWeMrkVSIisg9HtqnSOVqj6+k1vpZ4Q92vO4/OW+IJk1eJiMh+difbOp0Ot2/fRlZWljPiIS/kaBLibUkMS2bck6eWxxARUdlsLiO5du0aPv74Y+zZsweFhYUAgJo1a2LkyJGYMGGC4uvIk/coSUJQauKY7UmIo7d3JyyZcW+eWB5DRERlsynZvn37Nh5//HHcvn0bovjvKNqNGzfw2Wef4fLly/joo4+cFiR5PkeTEG9JYlj36/4iIwVeKyIiL2JTGcnSpUtx69YttGjRAt9//z0SEhLw559/4r333kNISAg2btyIs2fPKh7c8ePHMWHCBLRv3x6tW7fG0KFDsXnzZrvOcePGDbzzzjvo0aMHYmNj0a1bN0yfPh3Xr19XPF5yjKM1up5W42uJt5XMEBERuTubku0///wT4eHhWLp0Kdq1a4eQkBBERkZi+PDhmD59OkRRxJ9//qloYPHx8Rg5ciSOHDmCBx54ACNGjEB6ejpeeeUVfPnllzadIzk5GUOGDMEPP/yARo0aYfTo0WjVqhU2btyIRx99FMnJyYrGTORsrPslIiJyLzaVkVy7dg2dOnWCWq0229ezZ0/DMUopLi7GW2+9BUEQsHLlSjRv3hwAMGnSJAwfPhwLFixAv3790KBBgzLP87///Q937tzBm2++iSeffNKwffv27XjppZfw3//+F19//bVicRNVBG8pmSEiIvIENo1sFxYWolq1ahb3SdulSZNKOHjwIJKTkzFgwABDog0AoaGhmDhxIoqLi7Fhw4ZyY963bx9q1KiB0aNHm+x78MEH0axZM+zbtw9Xr15VLG6iiuINJTNERESewCX7bB86dAgA0K1bN7N9Xbt2NTnGmoyMDBQXF6NOnToWO6XUrVsXQEliT0RERETkDDa3/ktOTsZPP/0ka/+gQYPsCury5csAgPr165vtCw8Ph1qtxpUrV8o8R5UqVeDj44Nr165BFEWzhDslJcXkvoiIiIiIlGZzsp2YmIjExESr+xMSEqzutzfZzsnJAQCEhYVZ3B8aGoobN26UeY6goCC0b98eBw8exKpVq/DEE08Y9u3YsQNnzpwBAGRnZ1s9R3h4OFSlWz8YsVTDTp6N19w78bp7J15378Nr7p2cfd1tSrYHDx7s1CCcZfr06RgxYgTef/99/P7774iJiUFycjJ+++03xMTE4Ny5c2Um05mZmVb3qdVqpKenOyNsclG85t6J19078bp7H15z72TtuiuZgNuUbM+YMUOxO7RFaGgoAOujzjk5OVZHvY01bdoU69atw4IFCxAfH4/4+HjUr18f77//PrKysjBr1iyrEz+JyDk0GpGdVIiIyGvYXEZSkaSWfleuXEFsbKzJvszMTKSnp6NNmzY2natx48aYO3eu2fbXX38dAMzOT0TOs2Xrv8vNl/QIL2llSERE5Kkc6kZSXFyMtLQ0pKWlQafTKRUT2rdvDwDYt2+f2b79+/cDADp06CD7/Dk5Odi9ezeqVq1q6G5CRM6l0fybaAMly8zPmi1CoxErNzAiIiInsntk+9y5c/j+++8RHx9v1qO6fv366NSpE0aNGoUmTZrIDqpz586oV68etmzZgieffBLNmjUDUJIkL1q0CL6+viZ15GlpaUhPT4darTYpCykoKICvry98ff99mEVFRXjzzTeRkZGBN998EwEBAbLjJCLbpaTCkGhL9PqS7ZGRlRMTERGRs9mVbH/22WdYsmQJAEAUzUejLl++jMuXL+PHH3/ExIkTMXnyZHlB+friww8/xPjx4zFy5EgMGDAAoaGh2LFjB1JSUvDSSy+hYcOGhuNXrlyJhQsXYvLkyZgyZYph+8mTJzFlyhR06dIFtWvXRk5ODvbs2YNr167hscceM1vshojksaUOu25USemIccKtUpVsJyIi8lQ2J9tLly7F4sWL4ePjg/79+6N///5o2rSpYbZmeno6zpw5gy1btmD79u34/PPPERISgrFjx8oKrFOnTli1ahXmz5+P7du3Q6vVokmTJnjxxRfx8MMP23SOOnXqoEOHDkhISMDt27cRFBSE5s2b4/XXX8cDDzwgKy4iMmVrHXZkpIBXp6HUsVwFkyoHJ+oSUUURREtD1KXcuXMHPXr0gK+vLxYvXlxuvXR8fDyee+456PV67N692207fpTVAsgTWwTxj0/ZKuuau/J10WhEDB0umo1Wr1tjPYl25cdjiSf+rHs78zeIgtkbRF5378Nr7p0qovWfTRMkN27cCK1Wi1deecWmiYkdO3bEtGnTUFhYiE2bNjkcJDnflq0lSdMLU0v+3bKVk9Zcgatfl7LqsK2JjBQQ14Yj2lQ5OFGXiCqaTcn2kSNHEBQUhGHDhtl84sceewxBQUGIj4+XHRxVDP7xcU3ucF2kOmxjrMMmVybnDSIRkSNsSraTkpLQvHlz+Pv723xif39/tGjRAv/884/s4Khi8I+Pa3KH61JShy0YEm5Xr8PWaEQkHnWtNyxUsfgGkYgqmk0TJLOystCqVSu7T16jRg2cPXvW7ttRxWKXCNfkLtdlQH8BHdrD5euwuaAOAZyoS0QVz6aR7dzcXAQFBdl98qCgIOTl5dl9O6pY7jY66S3c6bq4eh22O5TkUMUZ0F/AujUC5n9W8i/fdBGRM9k0sm1DwxKn3JYqjruMTnobXhdlcEEdKi0yUuC1J6IKYXOf7eTkZPz00092nfzKlSv2xkOViH98XBOvi+PcpSSHiIg8j83JdmJiIhITE+06uSiKEASOxBFR5WKdLhERVRabku3Bgwc7Ow4iIqdiSQ4REVUGm5LtGTNmODsOIiKnY0kOERFVNJu6kRARERERkf2YbJNH4yImREREVJlsniCZkJCAmzdvomXLlqhXr55h+zfffIO//vrL4m369u2Lxx57zPEoiWTgIiZERERU2WxKttPS0jB+/Hio1Wr8/PPPJvuSkpKwd+9ei7dLSEjA/fffj6pVqzocKJE9rC1i0qE9J8YRERFRxbEp2d66dSvy8/Px5ptvIjQ01Gy/IAhYvny5ybZDhw5h4cKF2Lx5M0aPHq1MtEQ24iIm5GwajcjOJuS2+Polqjg2Jdt79+5FUFAQHn74YavHdOjQweT71q1bY8WKFdi7dy+TbapwXMSEnIklSuTO+Polqlg2TZA8d+4cYmNj4e/vb/OJ/f39ER0djXPnzskOjkiukkVMBKj+/xXORUxIKdZKlDgJl9wBX79EFc+mke309HS0a9fO4r64uDirt4uMjMTx48flRUYVyhM/UuQiJuQMLFEid8bXL1HFsynZ9vHxQVFRkcV9w4YNw7Bhwyzu02q1UKnYXdDVefJHilzEhJTGEiVyZ3z9ElU8mzLhiIgIXLp0ye6TX7x4ETVq1LD7dt6ksvtA8yNFIvuwRIncGV+/RBXPppHtuLg4bNq0CefPn0eTJk1sOnFSUhLOnz+PRx55xKEAPZkrjCjzI0Ui+7FEidwZX79EFcumke1HHnkEoijinXfesVpOYqyoqAjvvPMOBEFgsm2Fq4woSx8pGuNHikTli4wUENeGI4Lknvj6Jao4NiXbnTt3Rs+ePZGYmIjhw4cjPj7e6rEHDx7E448/jr///hvdu3dHly5dFAvWk5Q1olyR+JEiERERkfPYvFz7p59+igkTJiAxMRFPPfUUqlWrhqZNm6Jq1aoQBAHp6ek4e/Ys0tLSIIoi2rRpg08//dSZsbs1V5qkwo8UiYiIiJzD5mQ7JCQEK1aswLJly7B8+XLcvn0b+/fvNzuuRo0aePLJJzFu3Dj4+tp8eq9TMqKMUjXblTeizK4dRERERMoTRFG0u0hYr9fj9OnTOHv2LNLT0yGKItRqNZo2bYrmzZvDx8fHGbFWuPT0dKv71Gp1mftt5Yn9rT2VUtec3Auvu3fidfc+vObeydp1V6vVit2HrKFnlUqF2NhYxMbGKhaIt+KIMhEREZHn4oozVCkqu784ERERUUVgUTVVOFfoL05ERGQPln2SXBzZpgrlKv3FiYiIbLVlq4ihw0W8MLXk3y1b+TeLbMdkmyqUq/QXJyIisgUHichRTLapQnHFSiIiciccJCJHMdmmCsUVK4mIyJ1wkIgcxQmSVOG4YiUREbkLV1uEjtwPk22qFOwvTkRE7oKDROQIWcl27969bTrOz88PVatWRbNmzTBgwAC0bdtWzt0RERERVSoOEpFcspLt1FT7ZgUcO3YMa9aswYgRI/DOO+/IuUsiIiIiIrcja4Lk2bNnMXr0aISHh2PSpEnYvHkzjhw5giNHjmDz5s2YNGkSwsPDMWrUKOzZswdz5sxBrVq1sHr1amzatEnpx0BERERE5JJkjWyvWLECP/zwA9atW4fo6GiTfXfffTfuvvtuPPDAAxg6dCjq1auHMWPGoHHjxhgyZAjWrVuHRx55RJHgiYiIiIhcmayR7TVr1qBTp05mibax6OhodOrUCT/88AMAICYmBrGxsTh37py8SImIiIiI3IysZDslJQXBwcHlHhccHIyUlBTD91FRUcjPz5dzl0REREREbkdWsq1Wq3H48GHk5eVZPSY3NxeHDh1CtWrVDNsyMzMRHh4u5y6JiIiIiNyOrGT7wQcfxJ07dzB+/HgcP37cbP/x48fxzDPPID09HQ8++CAAQBRFJCUloUGDBg4FTERERETkLmRNkJwyZQqOHDmCxMREPP7446hVqxZq1aoFQRBw/fp13LhxA6IoIjY2FpMnTwYAnDt3DqGhoXjooYcUfQBERERERK5KVrIdHByMlStX4quvvsKPP/6I69ev4/r164b9kZGRePzxxzF+/HgEBAQAAJo2bYrt27crEzURERERkRuQvVy7v78/Jk6ciIkTJ+L69evQaDQAgIiICNSpU0exAImIiIiI3JXsZNtY7dq1Ubt2bSVORURERETkMRxOtjUaDY4ePQqNRgNBEBAREYE2bdogMjJSifiIiIiIiNyW7GQ7LS0NH3zwAXbs2AG9Xm+yT6VS4f7778fbb79t0vqPiIiIiMibyEq2s7Oz8cQTT+DSpUsIDAxE165dERUVBQC4du0a9u/fj+3bt+Ps2bP48ccfERYWpmjQRERERETuQFayvWTJEly6dAn9+vXDO++8YzZ6LY16b9++HUuXLsXLL7+sSLBERERERO5E1qI2O3fuRO3atfHJJ59YLBOpVq0aZs2ahdq1a+PXX391OEgiIiIiInckK9m+du0a4uLi4OfnZ/UYPz8/xMXFmfTfJiIiIiLyJrKS7cDAQKSnp5d7XHp6OgIDA+XcBRERERGR25OVbLdo0QKHDh3CyZMnrR5z8uRJHDp0CLGxsbKDIyIiIiJyZ7KS7aeeegrFxcV46qmnsHDhQly+fBlFRUUoKirC5cuXsWDBAowdOxY6nQ5jxoxROmYiIiIiIrcgiKIoyrnh4sWLMW/ePEg3FwQBAEy+f/HFF/Hss8/KDu748eNYsGABjh07Bq1WiyZNmmDMmDEYOHCgzefIysrCN998g127diElJQX+/v6oW7cuBg8ejGHDhiEgIMDqbcsqlVGr1TaV0pDn4DX3Trzu3onX3fvwmnsna9ddrVYrdh+yk20AOHHiBL7//nskJCRAo9EAACIjI9GuXTuMHDkSrVq1kh1YfHw8nn76afj5+aF///4ICwvDjh07kJKSgqlTp+K5554r9xxZWVkYMmQIrl69irZt2+Kee+5BUVER/vzzTyQnJ6NTp0745ptvoFJZHuBnsk3GeM29E6+7d+J19z685t6pIpJth5Zrb9myJT7++GOlYjEoLi7GW2+9BUEQsHLlSjRv3hwAMGnSJAwfPhwLFixAv3790KBBgzLP88MPP+Dq1at46qmnMH36dMP2oqIijBw5EgcPHkRCQgLat2+v+GMgIiIiIpJVs+1sBw8eRHJyMgYMGGBItAEgNDQUEydORHFxMTZs2FDuea5evQoA6N69u8l2f39/dO3aFQBw584dBSMnIiIiIvqXSybbhw4dAgB069bNbJ+UJEvHlOXuu+8GAOzdu9dku1arxV9//YXAwEC0adPG0XCJiIiIiCyyqYykd+/esu9AEATs2rXLrttcvnwZAFC/fn2zfeHh4VCr1bhy5Uq55xk2bBg2bdqEZcuW4eTJk4iNjYVWq8XevXuRmZmJ2bNno2bNmnbFRkRERERkK5uS7dTUVGfHYSInJwcAEBYWZnF/aGgobty4Ue55AgMDsWLFCrzzzjv4+eefDaPhKpUKTzzxBOLi4sq8fXh4uNXJk4CyxfPkHnjNvROvu3fidfc+vObeydnX3aZk++zZs04NwlnS0tIwceJEpKWlYcmSJYiLi0NhYSF+//13zJw5E3/88QfWr1+P8PBwi7fPzMy0em7OWvY+vObeidfdO/G6ex9ec+9UEd1IXLJmOzQ0FACQnZ1tcX9OTo7VUW9jM2fOxNGjRzF//nx0794dYWFhqFGjBh577DH85z//wdWrV7F8+XJFYyciIiIikrhksi219LNUl52ZmYn09HSL9dyl7dmzB1WrVkXTpk3N9nXq1AkAcOrUKceCJSIiIiKywiWTbanv9b59+8z27d+/HwDQoUOHcs9TVFSEnJwcFBUVme1LS0sDUNIGkIiIiIjIGVwy2e7cuTPq1auHLVu24MyZM4btOTk5WLRoEXx9fTF48GDD9rS0NFy4cMGQQEvi4uJQXFyMRYsWmWwvKioybOvYsaMTHwkREREReTOHVpB0Fl9fX3z44YcYP348Ro4ciQEDBiA0NNSwXPtLL72Ehg0bGo5fuXIlFi5ciMmTJ2PKlCmG7a+88gqOHj2KL774Avv37zdMkNy3bx+uXr2KFi1aYNiwYZXxEImIiIjIC7hksg2U1FSvWrUK8+fPx/bt26HVatGkSRO8+OKLePjhh206R7NmzbBhwwYsXrwYBw8exMqVK+Hj44O77roLU6ZMwdNPP42AgAAnPxIiIiIi8laCKIpiZQfhqspqAcQWQd6H19w78bp7J15378Nr7p28tvUfEZESNBoRiUdFaDQcUyAiosrhsmUkRESO2LJVxKzZIvR6QKUCXp0GDOgvVHZYRERl0mhEpKQCdaOAyEj+zvIEHNkmIo+j0fybaAOAXg/Mms0RbiJybVu2ihg6XMQLU0v+3bKVv7M8AZNtIvI4KakwJNoSvb5kOxGRK+Iggedisk1EHqduVEnpiDGVqmQ7EZEr4iCB52KyTUQeJzJSwKvTBEPCXVKzLbD+kYhcFgcJPBcnSBKRRxrQX0CH9uBEIyJyCyWDBCg1sZuDBJ6AyTYReazISAGRkZUdBRGRbThI4JmYbBMRERG5CA4SeB7WbBMREREROQmTbSIiIiIiJ2GyTURERETkJEy2iYiIiIichMk2EREREZGTMNkmIiIiInISJttERERERE7CZJuIiIiIyEmYbBMREREROQmTbSIiIiIiJ2GyTURERETkJEy2iYiIiIichMk2EREREZGTCKIoipUdBBERERGRJ+LINhERERGRkzDZJiIiIiJyEibbREREREROwmSbiIiIiMhJmGwTERERETmJb2UH4AqOHz+OBQsW4NixY9BqtWjSpAnGjBmDgQMH2nwOvV6PVatW4YcffsCVK1cQHByMjh07YurUqWjQoIHzgifZHL3uR44cwa5du3Do0CGkpqYiLy8PUVFR6N27N5599llUqVLFyY+A5FDi592YVqvF0KFDcfbsWTRs2BC//PKLwhGTEpS67jk5OVi2bBl27NiBq1evws/PD/Xq1UPv3r0xefJkJ0VPcihxzbOysvDNN99g165dSElJgb+/P+rWrYvBgwdj2LBhCAgIcOIjIHtt2rQJCQkJOHnyJJKSkqDVajFjxgwMGTLErvMondN5feu/+Ph4PP300/Dz80P//v0RFhaGHTt2ICUlBVOnTsVzzz1n03nefvtt/Pjjj2jSpAm6d++OO3fuYNu2bQgICMCaNWvQpEkTJz8SsocS171r165IT09H27Zt0axZMwiCgEOHDuH06dO46667sGbNGlSvXr0CHg3ZSqmfd2Pz5s3Dt99+i7y8PCbbLkqp637t2jWMGTMGV69eRZcuXdCsWTMUFRUhOTkZ165dw+bNm538SMhWSlzzrKwsDBkyBFevXkXbtm1xzz33oKioCH/++SeSk5PRqVMnfPPNN1CpWCTgKnr16oXU1FSo1WoEBwcjNTVVVrKteE4nejGtViv26dNHjI2NFU+dOmXYnp2dLfbv319s3ry5eOnSpXLPc+DAATE6OlocOXKkWFhYaNj+119/iTExMeITTzzhjPBJJqWu++LFi8WbN2+abNPr9eK7774rRkdHi++9957SoZMDlLruxk6ePCk2b95c/O6778To6GjxgQceUDhqcpRS1724uFh89NFHxVatWokHDhyweD/kGpS65kuWLBGjo6PFjz76yGR7YWGh+Oijj4rR0dHioUOHlA6fHLB//34xJSVFFMWSv9HR0dHi+vXr7TqHM3I6r347dvDgQSQnJ2PAgAFo3ry5YXtoaCgmTpyI4uJibNiwodzzrF27FgDw0ksvwd/f37C9c+fO6NatGw4fPoxLly4p/wBIFqWu+zPPPIPIyEiTbYIgYOLEiQCAw4cPKxs4OUSp6y4pKirC66+/jnvuuQejRo1yRsikAKWu+6+//ooTJ05g3Lhx6NSpk9l+X19WZboKpa751atXAQDdu3c32e7v74+uXbsCAO7cuaNg5OSoLl26ICoqyqFzOCOn8+pk+9ChQwCAbt26me2TfpCkY8oSHx+P4OBgxMXFme2Tzs3Ey3Uodd2tkf7o+vj4yD4HKU/p675w4UJcuXIF//vf/yAIgjJBkuKUuu7btm0DAPTr1w/Xr1/H6tWrsWTJEmzfvh25ubkKRkyOUuqa33333QCAvXv3mmzXarX466+/EBgYiDZt2jgaLrkYZ+R0Xv1W/PLlywCA+vXrm+0LDw+HWq3GlStXyjxHXl4ebt26hejoaIvJlVRIL90XVT4lrntZ1q9fD+DfX+rkGpS87sePH8dXX32FqVOnomHDhkqGSQpT6rqfPHkSAJCQkIAZM2agqKjIsK9atWqYO3cuOnbsqEzQ5BClrvmwYcOwadMmLFu2DCdPnkRsbCy0Wi327t2LzMxMzJ49GzVr1lQ6fKpEzsrpvHpkOycnBwAQFhZmcX9oaCiys7PLPIe0PzQ01Oo5jO+LKp8S192aM2fO4PPPP0f16tUxfvx42TGS8pS67kVFRZg+fTqaNWuGcePGKRojKU+p6y6VC3z44YcYM2YM9uzZgwMHDuCtt95CdnY2Jk2aBI1Go1zgJJtS1zwwMBArVqzAww8/jEOHDmHZsmVYsWKFoUTF0sgnuTdn5XRenWwTKenq1at49tlnodPpMGfOHFSrVq2yQyInmDt3Lq5cuYKPPvqIpUJeRPz/xl09evTAK6+8glq1aqFatWoYPXo0nnrqKWRnZ2PdunWVHCUpKS0tDWPHjsXff/+NJUuW4MiRI9i/fz/++9//YsOGDXjssceQmZlZ2WGSG/DqZFt6h2LtHW5OTo7Vd8YSab+1dznSdmvvkqjiKXHdS0tNTcWYMWOQlpaG+fPnW5xARZVLiet+6tQpfPvtt3juuecQExOjeIykPKV+3qXz9OrVy2xfz549AfxbakKVS6lrPnPmTBw9ehTz589H9+7dERYWhho1auCxxx7Df/7zH1y9ehXLly9XNHaqXM7K6bw62ZZqbyzVbmVmZiI9Pd1izZex4OBgREREICUlBTqdzmy/VNfDhW1chxLX3VhKSgpGjx4NjUaDuXPnGv7wkmtR4rqfO3cOOp0OCxYsQExMjMkXAFy6dAkxMTFo166d4vGTPEr9vEu1+ZYWq5K2FRYWOhApKUWpa75nzx5UrVoVTZs2NdsnDaicOnXKsWDJpTgrp/PqZLt9+/YAgH379pnt279/PwCgQ4cO5Z6nQ4cOyMvLQ2Jiotk+6dzSfVHlU+q6AyWJ9pNPPgmNRoPPPvsMffr0US5QUpQS171BgwYYOnSoxS+gZFRk6NChGDRokLLBk2xK/bxLydX58+fN9knbHG05RspQ6poXFRUhJyfHZDKsJC0tDQBMWsORZ3BKTmd3Z24PotVqxd69e4uxsbHi6dOnDduNG99fvHjRsP3OnTvi+fPnxTt37pich4vauBelrvvVq1fFnj17is2bNxd//fXXCouf5FHqulvDRW1ck1LXPTk5WYyNjRU7d+4s3rhxw+Q8jzzyiBgdHS3+9ddfzn9AVC6lrvm4cePE6Oho8bPPPjPZXlhYaNi3YsUKpz4Wkq+8RW0qMqfz+uXaDx48iPHjx8PPzw8DBgxAaGioYUnXl156Cc8//7zh2AULFmDhwoWYPHkypkyZYnKet956C2vXruVy7W5CiesuLQvbunVri/1cAZi9TqhyKfXzbklMTAyXa3dRSl33FStW4MMPP0TVqlXRt29f+Pv7448//kBqaioef/xxvP/++xX90MgKJa75mTNn8MQTTyA3NxetWrVCXFwcCgsLsW/fPly9ehUtWrTA6tWrERAQUBkPkSxYu3YtEhISAABJSUk4deoU4uLiDGVDffr0MXwCXZE5nVf32QZKPhpctWoV5s+fj+3bt0Or1aJJkyZ48cUX8fDDD9t8nvfffx8xMTH44YcfsGLFCgQHB6Nnz57sw+uilLjuqampAIBjx47h2LFjFo9hsu1alPp5J/ei1HUfPXo0oqKi8PXXX2Pr1q3Q6XRo0qQJnnvuOTz22GNOfARkLyWuebNmzbBhwwYsXrwYBw8exMqVK+Hj44O77roLU6ZMwdNPP81E28UkJCRg48aNJtsSExMNJSFRUVE2lXsqndN5/cg2EREREZGzePUESSIiIiIiZ2KyTURERETkJEy2iYiIiIichMk2EREREZGTMNkmIiIiInISJttERERERE7CZJuIiIiIyEmYbBMREREROQmTbSIiIiIiJ2GyTURer1evXoiJiansMCrcxo0bERMTg71791Z2KE61YMECxMTEYMOGDZUax4YNGxATE4MFCxaYbH/99dcRExOD+Pj4SorM3OjRoxETE4OUlBTDNo1Gg1atWuG///1vJUZG5H6YbBMReaHCwkLMmzcPrVu3xr333iv7PDExMejVq5eCkZGrioyMxGOPPYYff/wRFy9erOxwiNwGk20iIi+0evVqXL9+HRMmTKjsULzeyy+/jG3btqFVq1aVHUq5JkyYAL1ej/nz51d2KERuw7eyAyAiooq3evVqqNVqdO/evbJD8XqRkZGIjIys7DBsUrNmTXTs2BG7du3C7du3UaNGjcoOicjlcWSbyMukpKQgJiYGo0ePRk5ODmbOnIlevXqhRYsW+N///geg/BpSa6UDWq0WX3zxBfr27YuWLVuid+/eWLBgAbRardW6aFEUsWrVKgwYMAAtW7bEfffdh//973/IycmxWDdq/Djeeecd9OrVC7GxsejUqRNeeOEFnD171mLMxcXFWLx4Me6//35DbHPnzkVRUZHF4+Pj4xETE4PXX38dGRkZePfdd9GtWzfExsZiwIABWLduXZnPsT2x7d27F08//TTuu+8+xMbGolu3bhgxYgQWLlxo9lxt3boVTzzxBLp27YqWLVuie/fueOqpp7By5Uqr8ZR26NAhXL58Gf369YOfn5/Z/vT0dMyZMwf9+/dHmzZt0LZtWzzwwAN49dVXcfz4cQD/1h8DQGpqKmJiYgxfo0ePNpzrzJkzmDVrFoYMGYJOnTohNjYWvXv3xnvvvYebN29afO6kcxQUFODTTz9Fz549ERsbi759+2LJkiUQRdHq4xo9ejTatGmDjh07YtKkSbhw4YLV58GR2Kz97ADA2bNn8eyzz6Jt27Zo27Ytxo4di6NHj1qNw9LPm7StrK/SP59paWn4+OOP8cADD6Bly5Zo3749xo8fj8OHD1u97x9++AEDBw5Ey5Ytce+99+KDDz5Adna21eMBYMCAAdBqtZVeA0/kLjiyTeSlCgoKMGrUKFy7dg3t27dHixYtEB4eLvt8oijixRdfxG+//YaQkBDcd9990Ov1WLZsGc6cOWP1dv/73/+wYsUK+Pv7o3PnzggMDMTPP/+Mo0ePwtfX8q+oI0eO4Nlnn0VOTg7uvvtu9OrVCxqNBjt27MCePXuwePFidOrUyeQ2L7/8Mn799VcEBwfj3nvvhSiK+Pbbb3HmzBmryRsAZGVl4fHHH0dOTg5atmyJvLw8HDlyBG+++SZEUcSwYcMcim316tV477334O/vj3bt2qF9+/ZIS0vDhQsXsGDBAkyePNlw7OzZs7F06VKEhISgbdu2qFKlCjQaDc6ePYvk5GQ88cQTZV4jye7duwEAHTp0MNuXm5uLxx9/HFeuXEGDBg3QrVs3AMC1a9ewdetW1KtXD61atcJdd92FwYMHY+PGjQgODsYDDzxgOEejRo0M/1+yZAl+/fVX3H333YiLi4MgCDhz5gxWr16NXbt2Yf369ahZs6ZZHFqtFuPGjcP58+fRsmVLNGrUCIcPH8bs2bORm5uLqVOnmhy/a9cuvPDCC9DpdGjTpg3q1KmD48eP47HHHkPPnj0tPg9yYyvrZ+fvv//GmDFjkJ+fj2bNmqFRo0b4559/MHr0aAwePLi8S2PQtm1bi9t1Oh22bt0KnU4HHx8fw/YLFy5g7NixuHnzJu666y50794dGRkZOHjwIPbv349Zs2Zh4MCBJuf6+OOPsWzZMvj7+6NTp04ICgrC5s2bkZiYCH9/f6uxdezYEQCwZ88ePPPMMzY/JiKvJRKRV7l69aoYHR0tRkdHi48//riYmZlpdsxrr70mRkdHiwcPHrR4jujoaLFnz54m23766ScxOjpa7Nu3r3jz5k3D9mvXrok9e/Y03Kexw4cPi9HR0WLHjh3F8+fPG7ZnZGSIgwcPNtzm6tWrhn3Z2dli165dxRYtWojbt283Od/+/fvFFi1aiPfee69YWFho2L5582YxOjpa7N27t3jjxg3D9uTkZPG+++6zGNvBgwcN26dMmSLm5uYa9u3cuVOMjo4We/ToYXIbObH17NlTjIuLM3mMoiiKer1ePHDggOH7goICMTY2VuzZs6eYnp5ucqxWqxUPHTok2mrYsGFidHS0mJycbLZv/fr1YnR0tPjBBx+Y7bt9+7Z47tw5k22WXgvG/vrrL5PXgyiKok6nExcsWCBGR0eLr7/+usk+49fnyJEjxTt37hj2HT9+XGzevLl4zz33iDk5OYbt2dnZYseOHcXo6Ghx8+bNhu1ardbwWo6OjhbXr1+vWGyWfnZ0Op3Yr18/MTo6Wly8eLHJvs8++8xw2/nz55vsK+/nzdgHH3wgRkdHi88++6yo0+lEURTF4uJiccCAAWJ0dLS4fPlyUa/XG44/deqU2KFDB7F169bi7du3DdsTEhLE6OhosUOHDmJSUpJhe1pamjhw4ECLP3vGOnbsKMbGxpq8lonIMpaREHmxN998E1WqVFHkXGvWrAEAvPjiiyb1p7Vr18akSZPKvM24cePQuHFjw/bw8HC8+uqrFm+zbt063Lp1C+PGjUO/fv1M9nXp0gUjR47EzZs38ccffxi2r1692hCb8UhlvXr1MHHixDIfV2hoKN5//30EBwcbtvXp0wfR0dG4du2aSYmLnNju3LmDunXrom7duibHC4JgMgKek5ODoqIiNG3aFFWrVjU51tfXF+3bty/zcRg7d+4c/Pz8UK9ePbN9d+7cAQCzTwYAoHr16oiOjrb5fgCgc+fOZvXIKpUKkydPRs2aNfH7779bvJ1KpcKHH36IatWqGbZJpQ75+fk4efKkYfsvv/yC9PR0dO3aFQMGDDBs9/X1xfTp002unRKxAZZ/duLj43Hx4kU0aNDAbOLp5MmTUadOHavns8XatWuxYsUKNGnSBJ9++ilUqpI/4bt370ZSUhIGDBiAJ598EoIgGG7TvHlzTJw4EXl5efj5558N26WfvbFjx+Luu+82bFer1VZ/9ow1bNgQRUVF7EpCZAMm20ReKiIiAi1btlTkXFqtFidOnIBKpULfvn3N9pdOPCVSHaul/Z06dTJLKgHgr7/+AlCS8Foiffx+4sQJQ2x///03VCqVSamDpH///hbPI4mNjbUYR8OGDQEAt27dkh0bALRo0QJnz57Fp59+iuTkZKtxVK9eHbVq1cKePXvw1VdfWawptkVubi4KCgqsvsmKjY0FAMyZMwe7d+9GYWGhrPsxlp6ejvXr12PmzJl444038Prrr+P1119HcXExMjIykJGRYXabqKgow3NszNLznpCQAAB48MEHzY4PDw83lMIoFZu1nx0pjn79+pkkvEBJ4m/p9WerI0eO4L///S+qVq2KL7/8EqGhoYZ9+/fvBwD07t3b4m0tve7Kes66detm8TVvTCqbSU9Pt/1BEHkp1mwTeSlHR9mMZWRkQKvVIiIiwmKtZ0hICMLDw5GZmWmyXaPRQBAE1KpVy2qMpZOd1NRUADCrlS5NSgLKiy00NBRVqlRBVlaWxfNYi00aLTWeYGlvbADwzjvvYNKkSVi6dCmWLl2KyMhItGvXDg888ADuv/9+w+glAMycORMvv/wyPvnkE3zyySeoW7cu2rdvjwEDBpSZUBrLyckBUHJNLOncuTOeeuopLF++HM899xz8/PzQrFkzdO3aFUOHDjUbgS/Pli1b8PbbbyMvL8/qMbm5uWbJnT3Pu0ajAVDyKYol1rbLjc3az44Uh7X91uIoT2pqKqZMmQJRFDFv3jyzTySk193UqVPNatmNGb/upJ+9sp4zS280JFKyX95kSiJisk3ktQICAmTdTq/XW91XejTPmFjGJER7bqPT6QCUjB4GBQVZve0999xjco6yYiuLPbezNzYAaNq0KbZt24a9e/diz549OHToELZt24Zt27ahbdu2+Pbbbw1vEjp37oydO3di9+7d2Lt3Lw4fPoyNGzdi48aNePDBBzF37txyY5SSJCnptmT69Ol4/PHH8dtvv+HgwYNITEzE8ePH8dVXX2Hu3LlWR+5LS01Nxeuvvw4AeOONN9CjRw/UrFkTgYGBAIDhw4fj6NGjFq+znOtlz20cia28nx25rzVL8vLy8PzzzyMtLQ3vvvuuxfIe6XV33333oXr16lbPZTxx1VHS6ycsLEyxcxJ5KibbRGRGagdnacTv+vXrZtuqVq0KPz8/3L59G0VFRWYjyLm5uRZHjiMiIpCamoobN27grrvuMtt/48YNs221atXCpUuX8Pzzz6Np06blPha1Wl1mbDk5OVZHte1lb2ySgIAA9OnTx5DEnj9/Hi+//DISEhKwbt06jBw50nBsaGgoBg4caOgscezYMbz44ovYvn07Bg8eXG7f7JCQEAQGBpb7mBs1aoRGjRphwoQJKCwsxMqVK/Hxxx/jnXfesTnZ3rNnj6GryJgxY8z2X7161abzlEequ7527ZrF/ZZes86ITYpDGmm2JY6yiKKIV199FefOncOIESNMXgfGpE8Bhg8fbrWUpDTpZ+/69euoX7++3bFKn1Kp1Wqb7o/Im7Fmm4jMREREAAAuX75stk+qDzXm5+eH2NhY6PV67Nq1y2z/r7/+avF+2rRpA6Bkgltp8fHxFutBu3TpAgAW78cSPz8/tGrVCnq9Hjt27DDbv23bNpvOYwt7Y7OmSZMmhjZ+SUlJZR7bunVrPPLIIzYdK2natCmKi4tx5coVm44PCAjAuHHjEBERgTt37hgmUQIlz29xcbHF20kJvaWSkMOHD+P27ds23X954uLiAFh+HWVlZWHfvn0VEptUG71jxw6zEfHi4mKLr7+yzJs3Dzt37kTHjh3x1ltvWT1OzutOitXSc7Z///4yS0gA4OLFiwgICFB0tJzIUzHZJiIzUmeL1atXmyS8p06dwrx58yzeZvjw4QBKEgTjyWs3btzA559/bvE2jz/+OADgm2++MelqkJWVhU8++cTqbapVq4bFixdj/fr1ZklNXl4efvrpJ5NRcel+5s+fb6irBUpGIBctWmTxfuSwN7b8/Hx89913ZqPMer3e8KZGqv+9du0aNmzYgPz8fJNji4qKDIub2FqHLyVa0gI1xnbt2oVjx46ZbT99+jTu3LmDkJAQk8mVkZGRuHPnjsWR8gYNGgAAfv75Z5NPSW7evIl3333Xplht8eCDD6Jq1arYt2+fyZsnnU6HmTNnWvyExhmxdezYEQ0aNMDFixfx9ddfm+z74osvrI54W7Jt2zZ88cUXqFevHubNm2e15zwAPPDAA2jUqBE2btyIJUuWQKvVmuwvKirCjh07cO7cOcM2458944V/MjIyrP7sSZKTk5GRkYFWrVqV2Y+biEqwjISIzHTq1AkdOnTAoUOH0L9/f8TFxSEtLQ3Hjx/H6NGjsWzZMrPbPPLII/jll1+we/du9OvXD507d4Zer8eBAwfQsWNH6PV6kyQcKFlU5YknnsDKlSsxaNAgdO7cGQEBAYiPj0dUVBRat26NY8eOmaxyGB4ejoULF2LixIl444038Pnnn+Puu++Gv78/rl27hosXLxqSWmnU8uGHH8bOnTuxc+dOQ2yiKOLAgQNo3749BEGwWoJgD3tj02q1+N///odZs2ahRYsWiIqKglarxcmTJ3Ht2jXUq1fPkBRlZmZi+vTpeP/99xEbG4uaNWsiPz8fR48eRVpaGlq1amWxE4wlPXr0wNdff434+HizhU7i4+Px3XffoWbNmmjevDlCQkKg0WiQmJgIvV6PF1980eR69OrVCytWrMDgwYPRpk0bBAQEoGHDhhg/fjx69eqFu+++GydPnsT999+PuLg4FBYWIj4+Hk2bNkWbNm3KXFnRVlJ7xpdeeglTp07FihUrDIvapKWlYeDAgdi8ebPJbZwRm0qlwsyZM/HUU0/hk08+wdatW9GoUSMkJSXh0qVLGDZsGNauXWvTuebMmQOg5M3Mxx9/bPGYCRMmoHHjxvD19cXChQsxfvx4zJ49G9999x1iYmIQGhqKGzdu4OLFi8jKysLnn39uWPWzXbt2GDNmDJYvX45BgwahS5cuhp+92rVrG372LJHe3N133312PT9E3ooj20RkRhAELFq0CMOHD4cgCNizZw+ysrLw5ptv4rXXXrN6m/nz5+OFF16AWq3GH3/8gbNnz2LMmDGYN28ebt++bbGd2Ntvv423334bdevWxf79+3H06FH0798f3333HdLT0yEIgtnKlm3btsXPP/+McePGISAgAAcPHsS+ffuQk5ODHj164LPPPjPp2y0IAj777DNMnToV1apVw549e3D27FmMGjUKCxcuVHRCmz2xBQcH45133kHPnj2RlpaG33//HQcPHkSVKlXw4osvYsOGDYbHXq9ePbz22mvo0KEDrl27hp07dyIxMRFRUVF46623DKtw2qJDhw5o0KABduzYYbZc/ZAhQzBu3DhERkbi+PHj2LFjB1JTU3Hffffhu+++M6tvfvnllzFq1CjodDps374d69atw549ewAA/v7+WLlyJUaMGAF/f3/s3r0bFy5cwKhRo/DNN99YXCpergceeADLli1Du3btcObMGfz5559o3LgxfvjhB4s1yc6KrU2bNlizZg3uu+8+XLlyBbt370a1atWwfPlyQ7mLLaSJyAkJCYZJsKW/jEtdGjdujJ9++glTpkxB9erVkZiYiD179iAtLQ3t2rXDjBkz0LlzZ5P7mD59Ot577z3Ur18f+/fvR2JiIvr164fvvvuuzNfSli1b4OfnhyFDhtj57BB5J0GU0yKAiMgOf//9Nx577DHce++9+Oqrr2y6zc2bN9GrVy/cdddd2L59u5Mj9D7Lly/HRx99hAULFuD++++v7HDITdy4cQM9e/bEAw88YFP3GyLiyDYRKejcuXNm9aIpKSl47733AMBkdT/JhQsXUFBQYLItLS0N06dPR3FxscXbkOOGDx+OOnXqYOnSpZUdCrmR/2vvDlEVjQIwDH8o4gLEaLKIdxFGi9VkErtG9+AaLIJJsOkGxCX8/MEViAgaLLZpw4QZhoH7c7nD86zgnPaGj3PW63VqtVrm8/lXHwW+DZtt4NOsVqsURZFer5dWq5Xr9ZqiKPJ+vzMYDH6+mvGrzWaTw+GQfr+fdrud+/2esizzer3y8fGR2Wz2BTf5/zWbzSwWiyyXy5xOJ/tb/up2u2W322U8HnuFBP6BGQnwaY7HY/b7fS6XS57PZxqNRrrdbkajUSaTyW93sOfzOdvtNmVZ5vF4pF6vp9PpZDgcZjqd/vGnQwD4DsQ2AABUxGYbAAAqIrYBAKAiYhsAACoitgEAoCJiGwAAKiK2AQCgImIbAAAqIrYBAKAiPwCpGDgSvO68egAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot non-Africa - cid=1\n",
    "d_A0 = dd[dd[\"cid\"] == 1]\n",
    "az.plot_pair(d_A0[[\"rugged_std\", \"log_gdp_std\"]].to_dict(orient=\"list\"))\n",
    "plt.gca().set(\n",
    "    xlim=(-0.01, 1.01),\n",
    "    xlabel=\"ruggedness (standardized)\",\n",
    "    ylabel=\"log GDP (as proportion of mean)\",\n",
    ")\n",
    "mu = predictive(random.PRNGKey(2), cid=1, rugged_std=rugged_seq)[\"mu\"]\n",
    "mu_mean = jnp.mean(mu, 0)\n",
    "mu_ci = jnp.percentile(mu, q=jnp.array([1.5, 98.5]), axis=0)\n",
    "plt.plot(rugged_seq, mu_mean, \"k\")\n",
    "plt.fill_between(rugged_seq, mu_ci[0], mu_ci[1], color=\"k\", alpha=0.2)\n",
    "plt.title(\"Non-African nations\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code 8.18"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "rugged_seq = jnp.linspace(start=-0.2, stop=1.2, num=30)\n",
    "post = m8_3.sample_posterior(random.PRNGKey(1), p8_3, sample_shape=(1000,))\n",
    "post.pop(\"mu\")\n",
    "predictive = Predictive(m8_3.model, post, return_sites=[\"mu\"])\n",
    "muA = predictive(random.PRNGKey(2), cid=0, rugged_std=rugged_seq)[\"mu\"]\n",
    "muN = predictive(random.PRNGKey(2), cid=1, rugged_std=rugged_seq)[\"mu\"]\n",
    "delta = muA - muN"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code 8.19"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 27 entries, 0 to 26\n",
      "Data columns (total 4 columns):\n",
      " #   Column  Non-Null Count  Dtype  \n",
      "---  ------  --------------  -----  \n",
      " 0   bed     27 non-null     object \n",
      " 1   water   27 non-null     int64  \n",
      " 2   shade   27 non-null     int64  \n",
      " 3   blooms  27 non-null     float64\n",
      "dtypes: float64(1), int64(2), object(1)\n",
      "memory usage: 992.0+ bytes\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bed</th>\n",
       "      <th>water</th>\n",
       "      <th>shade</th>\n",
       "      <th>blooms</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>a</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>a</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>a</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>111.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>a</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>183.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>a</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>59.16</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  bed  water  shade  blooms\n",
       "0   a      1      1    0.00\n",
       "1   a      1      2    0.00\n",
       "2   a      1      3  111.04\n",
       "3   a      2      1  183.47\n",
       "4   a      2      2   59.16"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tulips = pd.read_csv(\"../data/tulips.csv\", sep=\";\")\n",
    "d = tulips\n",
    "d.info()\n",
    "d.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code 8.20"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "d[\"blooms_std\"] = d.blooms / d.blooms.max()\n",
    "d[\"water_cent\"] = d.water - d.water.mean()\n",
    "d[\"shade_cent\"] = d.shade - d.shade.mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code 8.21"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DeviceArray(0.6182, dtype=float32)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = dist.Normal(0.5, 1).sample(random.PRNGKey(0), (int(1e4),))\n",
    "jnp.sum((a < 0) | (a > 1)) / a.shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code 8.22"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DeviceArray(0.0471, dtype=float32)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = dist.Normal(0.5, 0.25).sample(random.PRNGKey(0), (int(1e4),))\n",
    "jnp.sum((a < 0) | (a > 1)) / a.shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code 8.23"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1000/1000 [00:00<00:00, 1306.10it/s, init loss: 753.9799, avg. loss [951-1000]: -9.9633]\n"
     ]
    }
   ],
   "source": [
    "def model(water_cent, shade_cent, blooms_std=None):\n",
    "    a = numpyro.sample(\"a\", dist.Normal(0.5, 0.25))\n",
    "    bw = numpyro.sample(\"bw\", dist.Normal(0, 0.25))\n",
    "    bs = numpyro.sample(\"bs\", dist.Normal(0, 0.25))\n",
    "    sigma = numpyro.sample(\"sigma\", dist.Exponential(1))\n",
    "    mu = numpyro.deterministic(\"mu\", a + bw * water_cent + bs * shade_cent)\n",
    "    numpyro.sample(\"blooms_std\", dist.Normal(mu, sigma), obs=blooms_std)\n",
    "\n",
    "\n",
    "m8_4 = AutoLaplaceApproximation(model)\n",
    "svi = SVI(\n",
    "    model,\n",
    "    m8_4,\n",
    "    optim.Adam(1),\n",
    "    Trace_ELBO(),\n",
    "    shade_cent=d.shade_cent.values,\n",
    "    water_cent=d.water_cent.values,\n",
    "    blooms_std=d.blooms_std.values,\n",
    ")\n",
    "svi_result = svi.run(random.PRNGKey(0), 1000)\n",
    "p8_4 = svi_result.params"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code 8.24"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1000/1000 [00:00<00:00, 1205.86it/s, init loss: 133.8938, avg. loss [951-1000]: -16.3747]\n"
     ]
    }
   ],
   "source": [
    "def model(water_cent, shade_cent, blooms_std=None):\n",
    "    a = numpyro.sample(\"a\", dist.Normal(0.5, 0.25))\n",
    "    bw = numpyro.sample(\"bw\", dist.Normal(0, 0.25))\n",
    "    bs = numpyro.sample(\"bs\", dist.Normal(0, 0.25))\n",
    "    bws = numpyro.sample(\"bws\", dist.Normal(0, 0.25))\n",
    "    sigma = numpyro.sample(\"sigma\", dist.Exponential(1))\n",
    "    mu = a + bw * water_cent + bs * shade_cent + bws * water_cent * shade_cent\n",
    "    numpyro.sample(\"blooms_std\", dist.Normal(mu, sigma), obs=blooms_std)\n",
    "\n",
    "\n",
    "m8_5 = AutoLaplaceApproximation(model)\n",
    "svi = SVI(\n",
    "    model,\n",
    "    m8_5,\n",
    "    optim.Adam(1),\n",
    "    Trace_ELBO(),\n",
    "    shade_cent=d.shade_cent.values,\n",
    "    water_cent=d.water_cent.values,\n",
    "    blooms_std=d.blooms_std.values,\n",
    ")\n",
    "svi_result = svi.run(random.PRNGKey(0), 1000)\n",
    "p8_5 = svi_result.params"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code 8.25"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x300 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_, axes = plt.subplots(1, 3, figsize=(9, 3), sharey=True)  # 3 plots in 1 row\n",
    "for ax, s in zip(axes, range(-1, 2)):\n",
    "    idx = d.shade_cent == s\n",
    "    ax.scatter(d.water_cent[idx], d.blooms_std[idx])\n",
    "    ax.set(xlim=(-1.1, 1.1), ylim=(-0.1, 1.1), xlabel=\"water\", ylabel=\"blooms\")\n",
    "    post = m8_4.sample_posterior(random.PRNGKey(1), p8_4, sample_shape=(1000,))\n",
    "    post.pop(\"mu\")\n",
    "    mu = Predictive(m8_4.model, post, return_sites=[\"mu\"])(\n",
    "        random.PRNGKey(2), shade_cent=s, water_cent=jnp.arange(-1, 2)\n",
    "    )[\"mu\"]\n",
    "    for i in range(20):\n",
    "        ax.plot(range(-1, 2), mu[i], \"k\", alpha=0.3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code 8.26"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "predictive = Predictive(\n",
    "    m8_5.model, num_samples=1000, return_sites=[\"a\", \"bw\", \"bs\", \"bws\", \"sigma\"]\n",
    ")\n",
    "prior = predictive(random.PRNGKey(7), water_cent=0, shade_cent=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Code 8.27"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "nettle = pd.read_csv(\"../data/nettle.csv\", sep=\";\")\n",
    "d = nettle\n",
    "d[\"lang.per.cap\"] = d[\"num.lang\"] / d[\"k.pop\"]"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}