RBABambiTest.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "8d92e36d-00db-4160-b4fc-ba9e0b83e082",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "pd.set_option(\"display.max_rows\", 500)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "cf317870-db73-4295-976e-25aad866199e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import bambi as bmb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "97ac0880-c1f0-4330-8802-6ebe0de07f8d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpyro"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d0525683-d067-4868-8869-2733c27af743",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pymc as pm\n",
    "import arviz as az"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e7a886c3-64f0-4a39-a2b1-4ff6f2242628",
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "from matplotlib import pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "9bc71b7a-7956-4a68-9e66-70e245efa3c2",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_frame = pd.read_table(\"tbl.txt\", delimiter=\"\\s+\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "64f6a132-fb16-4065-87b3-a17cf1209a02",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>subject</th>\n",
       "      <th>ROI</th>\n",
       "      <th>y</th>\n",
       "      <th>x</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>HMN001</td>\n",
       "      <td>RPCC</td>\n",
       "      <td>0.3457</td>\n",
       "      <td>17.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>HMN002</td>\n",
       "      <td>RPCC</td>\n",
       "      <td>0.5166</td>\n",
       "      <td>17.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>HMN003</td>\n",
       "      <td>RPCC</td>\n",
       "      <td>0.0919</td>\n",
       "      <td>15.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>HMN004</td>\n",
       "      <td>RPCC</td>\n",
       "      <td>0.3635</td>\n",
       "      <td>15.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>HMN005</td>\n",
       "      <td>RPCC</td>\n",
       "      <td>0.7323</td>\n",
       "      <td>17.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2599</th>\n",
       "      <td>HMN194</td>\n",
       "      <td>vmPFC</td>\n",
       "      <td>0.1730</td>\n",
       "      <td>18.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2600</th>\n",
       "      <td>HMN196</td>\n",
       "      <td>vmPFC</td>\n",
       "      <td>0.2926</td>\n",
       "      <td>19.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2601</th>\n",
       "      <td>HMN197</td>\n",
       "      <td>vmPFC</td>\n",
       "      <td>0.1925</td>\n",
       "      <td>18.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2602</th>\n",
       "      <td>HMN199</td>\n",
       "      <td>vmPFC</td>\n",
       "      <td>0.3157</td>\n",
       "      <td>15.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2603</th>\n",
       "      <td>HMN201</td>\n",
       "      <td>vmPFC</td>\n",
       "      <td>0.5199</td>\n",
       "      <td>17.21</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2604 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     subject    ROI       y      x\n",
       "0     HMN001   RPCC  0.3457  17.76\n",
       "1     HMN002   RPCC  0.5166  17.05\n",
       "2     HMN003   RPCC  0.0919  15.81\n",
       "3     HMN004   RPCC  0.3635  15.19\n",
       "4     HMN005   RPCC  0.7323  17.31\n",
       "...      ...    ...     ...    ...\n",
       "2599  HMN194  vmPFC  0.1730  18.93\n",
       "2600  HMN196  vmPFC  0.2926  19.31\n",
       "2601  HMN197  vmPFC  0.1925  18.00\n",
       "2602  HMN199  vmPFC  0.3157  15.26\n",
       "2603  HMN201  vmPFC  0.5199  17.21\n",
       "\n",
       "[2604 rows x 4 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "112fb4c9-23a8-44f7-9689-143b7df6468b",
   "metadata": {},
   "outputs": [],
   "source": [
    "model = bmb.Model(\"y ~ x + (1|subject) + (x|ROI)\", data_frame)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "4be01ae4-386b-4d26-a09d-2c1c381b5066",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Compiling...\n",
      "Compilation time =  0:00:03.724621\n",
      "Sampling...\n"
     ]
    },
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     "text": [
      "Sampling time =  0:00:40.162220\n",
      "Transforming variables...\n",
      "Transformation time =  0:00:00.283781\n"
     ]
    }
   ],
   "source": [
    "results = model.fit(\n",
    "    tune=4000, \n",
    "    draws=1000, \n",
    "    chains=8, \n",
    "    method=\"nuts_numpyro\", \n",
    "    nuts_kwargs=dict(max_tree_depth=100),\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "a0027d35-a892-4561-a594-fcb58a690a19",
   "metadata": {},
   "outputs": [
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     },
     "execution_count": 33,
     "metadata": {},
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   "source": [
    "model.graph()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "4564a5e3-ab63-448a-b8ea-a541e8d585d0",
   "metadata": {},
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       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:              (chain: 8, draw: 1000, subject__factor_dim: 124,\n",
       "                          ROI__factor_dim: 21)\n",
       "Coordinates:\n",
       "  * chain                (chain) int64 0 1 2 3 4 5 6 7\n",
       "  * draw                 (draw) int64 0 1 2 3 4 5 6 ... 994 995 996 997 998 999\n",
       "  * subject__factor_dim  (subject__factor_dim) &lt;U9 &#x27;HMN001&#x27; ... &#x27;HMN201&#x27;\n",
       "  * ROI__factor_dim      (ROI__factor_dim) &lt;U10 &#x27;ACC&#x27; &#x27;LAmy/Hippo&#x27; ... &#x27;vmPFC&#x27;\n",
       "Data variables:\n",
       "    Intercept            (chain, draw) float64 0.1091 -0.2002 ... 0.05866\n",
       "    x                    (chain, draw) float64 0.005101 0.01742 ... 0.006123\n",
       "    1|subject_sigma      (chain, draw) float64 0.07333 0.07989 ... 0.08394\n",
       "    1|ROI_sigma          (chain, draw) float64 0.09823 0.05739 ... 0.03256\n",
       "    x|ROI_sigma          (chain, draw) float64 0.008992 0.007208 ... 0.007508\n",
       "    y_sigma              (chain, draw) float64 0.155 0.1516 ... 0.1549 0.1519\n",
       "    1|subject            (chain, draw, subject__factor_dim) float64 0.07035 ....\n",
       "    1|ROI                (chain, draw, ROI__factor_dim) float64 -0.04694 ... ...\n",
       "    x|ROI                (chain, draw, ROI__factor_dim) float64 -0.006957 ......\n",
       "Attributes:\n",
       "    created_at:                  2022-06-18T13:04:22.688785\n",
       "    arviz_version:               0.12.1\n",
       "    modeling_interface:          bambi\n",
       "    modeling_interface_version:  0.9.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-e08ce691-1f3c-4372-94d9-a3a75022bf41' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e08ce691-1f3c-4372-94d9-a3a75022bf41' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>chain</span>: 8</li><li><span class='xr-has-index'>draw</span>: 1000</li><li><span class='xr-has-index'>subject__factor_dim</span>: 124</li><li><span class='xr-has-index'>ROI__factor_dim</span>: 21</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-acc97f23-fa8b-4604-8fd2-f451d3f77097' class='xr-section-summary-in' type='checkbox'  checked><label for='section-acc97f23-fa8b-4604-8fd2-f451d3f77097' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>chain</span></div><div class='xr-var-dims'>(chain)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 7</div><input id='attrs-41387faf-d24e-4501-91e7-a9c43a87145b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-41387faf-d24e-4501-91e7-a9c43a87145b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3f102444-3218-47da-8ae0-20d608dda010' class='xr-var-data-in' type='checkbox'><label for='data-3f102444-3218-47da-8ae0-20d608dda010' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 1, 2, 3, 4, 5, 6, 7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>draw</span></div><div class='xr-var-dims'>(draw)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 995 996 997 998 999</div><input id='attrs-17a8d59c-d7af-40ba-a8a5-7df1af0d9be0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-17a8d59c-d7af-40ba-a8a5-7df1af0d9be0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0d96e085-13aa-4467-a5ce-8b0408202330' class='xr-var-data-in' type='checkbox'><label for='data-0d96e085-13aa-4467-a5ce-8b0408202330' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  0,   1,   2, ..., 997, 998, 999])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>subject__factor_dim</span></div><div class='xr-var-dims'>(subject__factor_dim)</div><div class='xr-var-dtype'>&lt;U9</div><div class='xr-var-preview xr-preview'>&#x27;HMN001&#x27; &#x27;HMN002&#x27; ... &#x27;HMN201&#x27;</div><input id='attrs-3d8c9ad7-1b47-48f2-bd4c-24e84572d62d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3d8c9ad7-1b47-48f2-bd4c-24e84572d62d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f091d53b-06ce-4b0d-8171-1555bd1da13a' class='xr-var-data-in' type='checkbox'><label for='data-f091d53b-06ce-4b0d-8171-1555bd1da13a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;HMN001&#x27;, &#x27;HMN002&#x27;, &#x27;HMN003&#x27;, &#x27;HMN004&#x27;, &#x27;HMN005&#x27;, &#x27;HMN006&#x27;, &#x27;HMN007&#x27;,\n",
       "       &#x27;HMN008&#x27;, &#x27;HMN011&#x27;, &#x27;HMN012&#x27;, &#x27;HMN013&#x27;, &#x27;HMN014&#x27;, &#x27;HMN018&#x27;, &#x27;HMN019&#x27;,\n",
       "       &#x27;HMN020&#x27;, &#x27;HMN021&#x27;, &#x27;HMN023&#x27;, &#x27;HMN024&#x27;, &#x27;HMN025&#x27;, &#x27;HMN026&#x27;, &#x27;HMN027&#x27;,\n",
       "       &#x27;HMN028&#x27;, &#x27;HMN029&#x27;, &#x27;HMN030&#x27;, &#x27;HMN031&#x27;, &#x27;HMN032&#x27;, &#x27;HMN033&#x27;, &#x27;HMN035&#x27;,\n",
       "       &#x27;HMN037&#x27;, &#x27;HMN038&#x27;, &#x27;HMN039&#x27;, &#x27;HMN040&#x27;, &#x27;HMN041&#x27;, &#x27;HMN042&#x27;, &#x27;HMN043&#x27;,\n",
       "       &#x27;HMN045&#x27;, &#x27;HMN048&#x27;, &#x27;HMN049&#x27;, &#x27;HMN050_2&#x27;, &#x27;HMN052&#x27;, &#x27;HMN053&#x27;, &#x27;HMN055&#x27;,\n",
       "       &#x27;HMN056&#x27;, &#x27;HMN057&#x27;, &#x27;HMN058&#x27;, &#x27;HMN060&#x27;, &#x27;HMN062&#x27;, &#x27;HMN065&#x27;, &#x27;HMN068&#x27;,\n",
       "       &#x27;HMN069&#x27;, &#x27;HMN072&#x27;, &#x27;HMN073&#x27;, &#x27;HMN074&#x27;, &#x27;HMN075&#x27;, &#x27;HMN077&#x27;, &#x27;HMN079&#x27;,\n",
       "       &#x27;HMN080_W2&#x27;, &#x27;HMN081&#x27;, &#x27;HMN082&#x27;, &#x27;HMN083_W2&#x27;, &#x27;HMN085&#x27;, &#x27;HMN086&#x27;,\n",
       "       &#x27;HMN087&#x27;, &#x27;HMN088&#x27;, &#x27;HMN090&#x27;, &#x27;HMN092&#x27;, &#x27;HMN095&#x27;, &#x27;HMN096&#x27;, &#x27;HMN099&#x27;,\n",
       "       &#x27;HMN101&#x27;, &#x27;HMN102&#x27;, &#x27;HMN103&#x27;, &#x27;HMN104&#x27;, &#x27;HMN105&#x27;, &#x27;HMN108&#x27;, &#x27;HMN109&#x27;,\n",
       "       &#x27;HMN110&#x27;, &#x27;HMN111&#x27;, &#x27;HMN113&#x27;, &#x27;HMN114&#x27;, &#x27;HMN115&#x27;, &#x27;HMN116&#x27;, &#x27;HMN117&#x27;,\n",
       "       &#x27;HMN118&#x27;, &#x27;HMN119&#x27;, &#x27;HMN120&#x27;, &#x27;HMN121&#x27;, &#x27;HMN122&#x27;, &#x27;HMN123&#x27;, &#x27;HMN124&#x27;,\n",
       "       &#x27;HMN125_W2&#x27;, &#x27;HMN126&#x27;, &#x27;HMN127&#x27;, &#x27;HMN129_W2&#x27;, &#x27;HMN130&#x27;, &#x27;HMN134&#x27;,\n",
       "       &#x27;HMN136&#x27;, &#x27;HMN138&#x27;, &#x27;HMN140&#x27;, &#x27;HMN143&#x27;, &#x27;HMN144&#x27;, &#x27;HMN161_W2&#x27;, &#x27;HMN167&#x27;,\n",
       "       &#x27;HMN169&#x27;, &#x27;HMN172&#x27;, &#x27;HMN174&#x27;, &#x27;HMN175&#x27;, &#x27;HMN178&#x27;, &#x27;HMN180&#x27;, &#x27;HMN182&#x27;,\n",
       "       &#x27;HMN183&#x27;, &#x27;HMN184&#x27;, &#x27;HMN186&#x27;, &#x27;HMN187&#x27;, &#x27;HMN188&#x27;, &#x27;HMN189&#x27;, &#x27;HMN190&#x27;,\n",
       "       &#x27;HMN191&#x27;, &#x27;HMN193&#x27;, &#x27;HMN194&#x27;, &#x27;HMN196&#x27;, &#x27;HMN197&#x27;, &#x27;HMN199&#x27;, &#x27;HMN201&#x27;],\n",
       "      dtype=&#x27;&lt;U9&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>ROI__factor_dim</span></div><div class='xr-var-dims'>(ROI__factor_dim)</div><div class='xr-var-dtype'>&lt;U10</div><div class='xr-var-preview xr-preview'>&#x27;ACC&#x27; &#x27;LAmy/Hippo&#x27; ... &#x27;vmPFC&#x27;</div><input id='attrs-41da384a-b16b-4e57-a772-dc389a1ebf85' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-41da384a-b16b-4e57-a772-dc389a1ebf85' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b933914-69f8-4107-b360-c5f7a1cfb528' class='xr-var-data-in' type='checkbox'><label for='data-9b933914-69f8-4107-b360-c5f7a1cfb528' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;ACC&#x27;, &#x27;LAmy/Hippo&#x27;, &#x27;LCing&#x27;, &#x27;LIFG&#x27;, &#x27;LIPL&#x27;, &#x27;LMTG&#x27;, &#x27;LSFG&#x27;, &#x27;LTPJ&#x27;,\n",
       "       &#x27;LaMTS/aMTG&#x27;, &#x27;LvBG&#x27;, &#x27;PCC&#x27;, &#x27;RAmy/Hippo&#x27;, &#x27;RIFG_BA45&#x27;, &#x27;RIFG_BA9&#x27;,\n",
       "       &#x27;RIns&#x27;, &#x27;RPCC&#x27;, &#x27;RTPJp&#x27;, &#x27;RvBG&#x27;, &#x27;SGC&#x27;, &#x27;dmMPFC&#x27;, &#x27;vmPFC&#x27;], dtype=&#x27;&lt;U10&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d78a57ca-0fd8-4311-ad7d-6df7d9ba75c8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d78a57ca-0fd8-4311-ad7d-6df7d9ba75c8' class='xr-section-summary' >Data variables: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>Intercept</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.1091 -0.2002 ... 0.06703 0.05866</div><input id='attrs-24b13509-693b-4182-8ecc-2a83da94ef23' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-24b13509-693b-4182-8ecc-2a83da94ef23' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65db32de-a665-426c-b448-2fbf62728767' class='xr-var-data-in' type='checkbox'><label for='data-65db32de-a665-426c-b448-2fbf62728767' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 0.10914107, -0.20015381, -0.07305449, ..., -0.06779714,\n",
       "        -0.04163863, -0.09934183],\n",
       "       [ 0.18204761,  0.13565211,  0.10070439, ...,  0.15155632,\n",
       "        -0.01319795,  0.1554207 ],\n",
       "       [ 0.09740854,  0.13439296,  0.0477594 , ...,  0.03834495,\n",
       "         0.06878644,  0.0607652 ],\n",
       "       ...,\n",
       "       [ 0.07620605, -0.04314799, -0.07893021, ...,  0.08706148,\n",
       "         0.04289604,  0.07650326],\n",
       "       [ 0.09032188,  0.03702545,  0.11653177, ...,  0.0467546 ,\n",
       "         0.11487394,  0.01103328],\n",
       "       [ 0.14066816,  0.08177956,  0.14900074, ...,  0.05053242,\n",
       "         0.06703093,  0.0586639 ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.005101 0.01742 ... 0.006123</div><input id='attrs-483609ed-b778-4664-a1e5-fac3dd625130' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-483609ed-b778-4664-a1e5-fac3dd625130' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2ac69cf3-3498-4240-a528-78fe5e1ed42b' class='xr-var-data-in' type='checkbox'><label for='data-2ac69cf3-3498-4240-a528-78fe5e1ed42b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 0.00510055,  0.01742104,  0.01001721, ...,  0.01244883,\n",
       "         0.00874285,  0.0110417 ],\n",
       "       [ 0.00129176,  0.0057838 ,  0.00526335, ..., -0.00082639,\n",
       "         0.00877754,  0.00425608],\n",
       "       [ 0.00326146,  0.00190734,  0.0069036 , ...,  0.00743662,\n",
       "         0.00430907,  0.00439955],\n",
       "       ...,\n",
       "       [ 0.0088288 ,  0.0088295 ,  0.01075743, ...,  0.00466013,\n",
       "         0.00726667,  0.00644266],\n",
       "       [ 0.00380186,  0.00984528,  0.00188892, ...,  0.00805096,\n",
       "         0.00652614,  0.00620238],\n",
       "       [ 0.0028263 ,  0.00675614,  0.00298531, ...,  0.00838491,\n",
       "         0.00664813,  0.00612309]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>1|subject_sigma</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.07333 0.07989 ... 0.07418 0.08394</div><input id='attrs-364ac0f1-3d98-44ad-bc80-3f2c52c15a7e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-364ac0f1-3d98-44ad-bc80-3f2c52c15a7e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2b49cc20-fca5-4c2f-9135-882f93694fa3' class='xr-var-data-in' type='checkbox'><label for='data-2b49cc20-fca5-4c2f-9135-882f93694fa3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.07333448, 0.07989272, 0.07442004, ..., 0.07046666, 0.07057015,\n",
       "        0.07504239],\n",
       "       [0.08796816, 0.08182926, 0.08343758, ..., 0.07946167, 0.09103816,\n",
       "        0.08180559],\n",
       "       [0.09271584, 0.08020128, 0.07807265, ..., 0.07006556, 0.0712682 ,\n",
       "        0.07684988],\n",
       "       ...,\n",
       "       [0.07704805, 0.07672804, 0.07849507, ..., 0.09253411, 0.08686262,\n",
       "        0.09581273],\n",
       "       [0.06907359, 0.06499536, 0.071857  , ..., 0.08113339, 0.07420178,\n",
       "        0.07488587],\n",
       "       [0.08223663, 0.08558567, 0.08425045, ..., 0.08290207, 0.07418117,\n",
       "        0.08393924]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>1|ROI_sigma</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.09823 0.05739 ... 0.03507 0.03256</div><input id='attrs-def4ef3d-d11a-4ee8-bf43-97ea96b7eebb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-def4ef3d-d11a-4ee8-bf43-97ea96b7eebb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8f2e4598-3e11-46ff-8b11-ea6ac468eb38' class='xr-var-data-in' type='checkbox'><label for='data-8f2e4598-3e11-46ff-8b11-ea6ac468eb38' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.09823456, 0.05739014, 0.06826485, ..., 0.04029732, 0.05095824,\n",
       "        0.12631944],\n",
       "       [0.04066669, 0.09078584, 0.04185155, ..., 0.02355347, 0.0707369 ,\n",
       "        0.11359451],\n",
       "       [0.04303944, 0.09091724, 0.08532896, ..., 0.08188749, 0.04037235,\n",
       "        0.04579975],\n",
       "       ...,\n",
       "       [0.08061593, 0.05577094, 0.12502058, ..., 0.06595619, 0.06426722,\n",
       "        0.07253271],\n",
       "       [0.00812215, 0.0471957 , 0.02940549, ..., 0.05982433, 0.06185981,\n",
       "        0.073588  ],\n",
       "       [0.05417241, 0.00755295, 0.00676309, ..., 0.06681447, 0.03507011,\n",
       "        0.03255595]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x|ROI_sigma</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.008992 0.007208 ... 0.007508</div><input id='attrs-199535e6-3c5e-47c3-9225-c00b631c0f59' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-199535e6-3c5e-47c3-9225-c00b631c0f59' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ac44facc-38a1-4385-bb54-b93b7fd68804' class='xr-var-data-in' type='checkbox'><label for='data-ac44facc-38a1-4385-bb54-b93b7fd68804' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.00899231, 0.00720763, 0.00818139, ..., 0.01011278, 0.01140474,\n",
       "        0.00793548],\n",
       "       [0.00810356, 0.00877814, 0.00902476, ..., 0.01049474, 0.00860127,\n",
       "        0.00394483],\n",
       "       [0.00843895, 0.00995524, 0.0084315 , ..., 0.01245935, 0.00809426,\n",
       "        0.01298834],\n",
       "       ...,\n",
       "       [0.00788545, 0.00736683, 0.01039766, ..., 0.01077473, 0.01113211,\n",
       "        0.0103    ],\n",
       "       [0.00942827, 0.00648795, 0.00857694, ..., 0.01023509, 0.00801955,\n",
       "        0.01032694],\n",
       "       [0.01049424, 0.00676479, 0.00850139, ..., 0.00747347, 0.0082123 ,\n",
       "        0.00750764]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y_sigma</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.155 0.1516 ... 0.1549 0.1519</div><input id='attrs-3882cd17-bed0-4735-a0e4-51a9e765ff59' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3882cd17-bed0-4735-a0e4-51a9e765ff59' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8fd7d9dd-0c74-4986-b363-f6bbfadffd7b' class='xr-var-data-in' type='checkbox'><label for='data-8fd7d9dd-0c74-4986-b363-f6bbfadffd7b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.15498183, 0.15160899, 0.15242071, ..., 0.15172699, 0.15501005,\n",
       "        0.15186296],\n",
       "       [0.15605206, 0.15701019, 0.15263653, ..., 0.15377596, 0.15291051,\n",
       "        0.15427967],\n",
       "       [0.15381541, 0.15543691, 0.15306321, ..., 0.15851777, 0.14970526,\n",
       "        0.15384872],\n",
       "       ...,\n",
       "       [0.15224678, 0.15197885, 0.15873838, ..., 0.1499601 , 0.14997043,\n",
       "        0.14975592],\n",
       "       [0.15737719, 0.15445361, 0.15572596, ..., 0.15371509, 0.15324621,\n",
       "        0.15262377],\n",
       "       [0.15409758, 0.15441225, 0.15567494, ..., 0.15647884, 0.1549085 ,\n",
       "        0.15191385]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>1|subject</span></div><div class='xr-var-dims'>(chain, draw, subject__factor_dim)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.07035 0.01079 ... 0.03299 0.1607</div><input id='attrs-5c0a8447-e918-4eb7-b243-b94098540697' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5c0a8447-e918-4eb7-b243-b94098540697' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f9c586f1-426f-4a6c-b52a-c17eae3cf951' class='xr-var-data-in' type='checkbox'><label for='data-f9c586f1-426f-4a6c-b52a-c17eae3cf951' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[ 7.03516622e-02,  1.07916769e-02, -1.97834812e-02, ...,\n",
       "          6.71924593e-03,  7.49517314e-02,  1.40171834e-01],\n",
       "        [ 4.44808222e-02,  9.87004603e-02,  5.44088196e-02, ...,\n",
       "         -1.82759281e-02,  5.29226096e-02,  1.02625538e-01],\n",
       "        [ 3.57500267e-02,  3.88775624e-02, -2.74752679e-02, ...,\n",
       "          1.30225260e-02,  9.82361911e-02,  1.13423955e-01],\n",
       "        ...,\n",
       "        [ 8.12654028e-02,  2.17377342e-02, -4.59871870e-02, ...,\n",
       "         -6.73198172e-02,  9.04724802e-02,  1.15263156e-01],\n",
       "        [ 4.38457414e-02,  6.54680846e-02,  6.90366418e-02, ...,\n",
       "          2.77541466e-02,  1.75621309e-02,  1.66377408e-01],\n",
       "        [ 1.52596149e-01,  1.70202913e-02, -2.51661051e-02, ...,\n",
       "         -3.89337875e-02,  6.60336676e-02,  1.01186591e-01]],\n",
       "\n",
       "       [[ 8.37357655e-02,  1.72367062e-02, -2.92290913e-02, ...,\n",
       "          4.34039372e-03, -9.26738017e-03,  1.31005588e-01],\n",
       "        [ 4.49938224e-02,  3.91056800e-02,  3.17173645e-02, ...,\n",
       "          4.23417551e-05,  3.93242871e-02,  3.69763701e-02],\n",
       "        [ 6.71539188e-02,  5.04368884e-02, -4.34631462e-02, ...,\n",
       "         -8.52894469e-03,  3.80299804e-02,  1.67182100e-01],\n",
       "...\n",
       "        [ 1.14153285e-01,  1.01340582e-02, -3.64161618e-02, ...,\n",
       "         -3.46448883e-02,  4.28957154e-02,  1.30196589e-01],\n",
       "        [ 2.04662218e-02,  9.50096273e-02, -1.34208230e-02, ...,\n",
       "          2.34014809e-02,  1.02678746e-02,  1.26672539e-01],\n",
       "        [ 3.24387413e-02,  5.15986375e-02, -2.43778200e-03, ...,\n",
       "         -4.90694886e-02,  3.08092745e-02,  1.18891904e-01]],\n",
       "\n",
       "       [[ 3.69173836e-02,  1.50375998e-02, -4.77736886e-02, ...,\n",
       "         -2.62635084e-02,  1.24875318e-02,  1.34757147e-01],\n",
       "        [ 1.15202768e-01,  2.84615239e-02,  2.81902722e-03, ...,\n",
       "         -3.89059057e-02,  6.07265938e-02,  1.01930584e-01],\n",
       "        [ 7.10334440e-02, -1.21968921e-02,  7.34048492e-03, ...,\n",
       "         -4.01442826e-02,  4.65346210e-02,  1.19327974e-01],\n",
       "        ...,\n",
       "        [-3.43622201e-02,  2.60341696e-02, -1.16671615e-02, ...,\n",
       "         -5.15172987e-02,  3.07335497e-02,  1.34357595e-01],\n",
       "        [ 1.41340184e-02, -3.60518129e-02, -3.05280552e-02, ...,\n",
       "         -2.49843046e-02,  6.37374052e-02,  8.72525978e-02],\n",
       "        [ 9.27084072e-02,  1.31766287e-02, -5.44556175e-02, ...,\n",
       "         -2.25262240e-02,  3.29939227e-02,  1.60679637e-01]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>1|ROI</span></div><div class='xr-var-dims'>(chain, draw, ROI__factor_dim)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.04694 -0.0689 ... -0.00329</div><input id='attrs-8405cde0-bc41-4e5f-9349-1c1c96612ed8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8405cde0-bc41-4e5f-9349-1c1c96612ed8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66abafd2-6c42-478a-969a-ea864d4117be' class='xr-var-data-in' type='checkbox'><label for='data-66abafd2-6c42-478a-969a-ea864d4117be' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[-0.04694138, -0.06890263, -0.14614331, ..., -0.06323855,\n",
       "         -0.05572808,  0.00757246],\n",
       "        [-0.0815638 ,  0.03541494,  0.05387609, ..., -0.06091668,\n",
       "         -0.02292469,  0.00415094],\n",
       "        [ 0.04278671,  0.09840186, -0.06640557, ..., -0.06232643,\n",
       "         -0.05165173, -0.02821536],\n",
       "        ...,\n",
       "        [ 0.01021104,  0.02204818,  0.07406246, ..., -0.02745914,\n",
       "          0.09132035, -0.05865638],\n",
       "        [-0.04256866,  0.09369637, -0.04679577, ..., -0.01038514,\n",
       "         -0.11703268, -0.01458548],\n",
       "        [-0.12642192,  0.0253372 , -0.00450875, ..., -0.00508891,\n",
       "         -0.05769612, -0.02723294]],\n",
       "\n",
       "       [[-0.04855059, -0.01219166, -0.02478311, ..., -0.00513987,\n",
       "         -0.03997268,  0.03295679],\n",
       "        [-0.11500369, -0.05686765, -0.15559753, ...,  0.00033473,\n",
       "          0.0096197 ,  0.0957295 ],\n",
       "        [ 0.0664257 , -0.02549804, -0.04168877, ..., -0.03605065,\n",
       "          0.13413021, -0.00271836],\n",
       "...\n",
       "        [-0.03704148,  0.02936941,  0.03466267, ..., -0.06391198,\n",
       "         -0.02864498, -0.01898821],\n",
       "        [ 0.03635657, -0.00914934, -0.09498303, ...,  0.02457266,\n",
       "          0.00632249, -0.04607414],\n",
       "        [-0.00314445,  0.00807056, -0.08094047, ..., -0.04648298,\n",
       "         -0.08572712, -0.10378942]],\n",
       "\n",
       "       [[-0.01975191, -0.04327923, -0.00506719, ...,  0.02038092,\n",
       "          0.03255594,  0.08444245],\n",
       "        [-0.00602349, -0.00701272, -0.00445327, ...,  0.00449239,\n",
       "         -0.01281379,  0.00018572],\n",
       "        [-0.00137457, -0.01603232,  0.00078596, ...,  0.0002127 ,\n",
       "         -0.004259  , -0.00198282],\n",
       "        ...,\n",
       "        [-0.05141695,  0.06772225,  0.00305573, ...,  0.07537628,\n",
       "         -0.02451166, -0.06245736],\n",
       "        [-0.02562588,  0.03341293, -0.01527792, ...,  0.0019612 ,\n",
       "         -0.0383582 ,  0.00566595],\n",
       "        [ 0.04973205, -0.02230793, -0.0210355 , ..., -0.03073104,\n",
       "         -0.04871969, -0.00328951]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x|ROI</span></div><div class='xr-var-dims'>(chain, draw, ROI__factor_dim)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.006957 -0.001913 ... -0.0004439</div><input id='attrs-446ac639-d98a-4196-a358-62260e76ae41' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-446ac639-d98a-4196-a358-62260e76ae41' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3fb33a75-d5bb-4746-8e9a-f22c799b3aa6' class='xr-var-data-in' type='checkbox'><label for='data-3fb33a75-d5bb-4746-8e9a-f22c799b3aa6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[-6.95710020e-03, -1.91313068e-03, -4.24361690e-03, ...,\n",
       "         -4.82559207e-03,  1.51330983e-03, -3.16703905e-03],\n",
       "        [-6.73962595e-06, -3.27695481e-03, -1.14927951e-02, ...,\n",
       "          4.34893107e-04,  5.08533615e-03,  3.11182608e-03],\n",
       "        [-4.55984020e-03, -6.60611574e-03, -5.72264759e-03, ...,\n",
       "          2.92333105e-03,  7.60457347e-03,  5.06811843e-03],\n",
       "        ...,\n",
       "        [-4.70216003e-03, -4.57919113e-03, -1.65111490e-02, ...,\n",
       "         -1.46978161e-03, -3.58111547e-03,  2.20174267e-03],\n",
       "        [-2.34710182e-03, -6.84725610e-03, -5.89502590e-03, ...,\n",
       "         -1.39151013e-03,  1.04260438e-02,  3.67442740e-03],\n",
       "        [ 5.14968024e-03, -1.41668318e-03, -6.96908494e-03, ...,\n",
       "         -5.47659844e-04,  7.36974867e-03,  4.68213144e-03]],\n",
       "\n",
       "       [[-4.72230194e-03, -4.85275447e-03, -1.33605306e-02, ...,\n",
       "         -6.27362491e-03,  9.00344157e-04, -5.73811594e-03],\n",
       "        [-3.74723379e-03, -3.95219850e-03, -5.95508087e-03, ...,\n",
       "         -9.04058868e-03, -1.65622691e-03, -8.42375055e-03],\n",
       "        [-1.22268533e-02, -4.21662371e-03, -1.18453460e-02, ...,\n",
       "         -4.85851928e-03, -6.81520796e-03, -1.37186351e-04],\n",
       "...\n",
       "        [-4.52221082e-03, -7.24656402e-03, -1.57325563e-02, ...,\n",
       "         -2.26713779e-03,  1.56966909e-03, -1.53316807e-03],\n",
       "        [-1.15002310e-02, -7.91792998e-03, -1.01730654e-02, ...,\n",
       "         -1.06477861e-02, -2.45163087e-03, -2.08923190e-03],\n",
       "        [-1.64924599e-03, -1.72350800e-03, -5.53957782e-03, ...,\n",
       "          4.38643964e-04,  8.44747456e-03,  9.51813961e-03]],\n",
       "\n",
       "       [[-6.07684943e-03, -2.10309126e-03, -1.21698394e-02, ...,\n",
       "         -6.33981775e-03, -1.18357780e-03, -5.88487076e-03],\n",
       "        [-7.68373231e-03, -5.02840537e-03, -1.35310683e-02, ...,\n",
       "         -7.04587069e-03, -6.94912674e-05, -1.76317273e-03],\n",
       "        [-7.78121608e-03, -3.88321986e-03, -1.36159676e-02, ...,\n",
       "         -6.27330614e-03, -8.22312850e-04, -4.56245241e-04],\n",
       "        ...,\n",
       "        [-4.21644422e-03, -8.00531060e-03, -1.47427557e-02, ...,\n",
       "         -1.16291773e-02,  4.38913975e-05,  1.73199462e-03],\n",
       "        [-4.07015961e-03, -5.32789745e-03, -1.15558416e-02, ...,\n",
       "         -5.63513528e-03,  2.36079299e-03, -1.31645958e-03],\n",
       "        [-8.37226649e-03, -2.30547756e-03, -1.11790500e-02, ...,\n",
       "         -3.36866336e-03,  4.85287881e-03, -4.43907708e-04]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e86d1127-8162-4cc6-94a2-2562cfcc38ac' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e86d1127-8162-4cc6-94a2-2562cfcc38ac' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>created_at :</span></dt><dd>2022-06-18T13:04:22.688785</dd><dt><span>arviz_version :</span></dt><dd>0.12.1</dd><dt><span>modeling_interface :</span></dt><dd>bambi</dd><dt><span>modeling_interface_version :</span></dt><dd>0.9.0</dd></dl></div></li></ul></div></div><br></div>\n",
       "                      </ul>\n",
       "                  </div>\n",
       "            </li>\n",
       "            \n",
       "            <li class = \"xr-section-item\">\n",
       "                  <input id=\"idata_log_likelihood4f3fe4e6-2bc7-447f-b6b2-a7251fdbabfa\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
       "                  <label for=\"idata_log_likelihood4f3fe4e6-2bc7-447f-b6b2-a7251fdbabfa\" class = \"xr-section-summary\">log_likelihood</label>\n",
       "                  <div class=\"xr-section-inline-details\"></div>\n",
       "                  <div class=\"xr-section-details\">\n",
       "                      <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
       "                          <div style=\"padding-left:2rem;\"><div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "</symbol>\n",
       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
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       "\n",
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       "\n",
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       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
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       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
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       "  padding-right: 10px;\n",
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       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
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       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
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       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (chain: 8, draw: 1000, y_dim_0: 2604)\n",
       "Coordinates:\n",
       "  * chain    (chain) int64 0 1 2 3 4 5 6 7\n",
       "  * draw     (draw) int64 0 1 2 3 4 5 6 7 8 ... 992 993 994 995 996 997 998 999\n",
       "  * y_dim_0  (y_dim_0) int64 0 1 2 3 4 5 6 ... 2598 2599 2600 2601 2602 2603\n",
       "Data variables:\n",
       "    y        (chain, draw, y_dim_0) float64 0.7354 0.5207 ... 0.5368 0.04514\n",
       "Attributes:\n",
       "    created_at:                  2022-06-18T13:04:22.695740\n",
       "    arviz_version:               0.12.1\n",
       "    modeling_interface:          bambi\n",
       "    modeling_interface_version:  0.9.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-4d659fc8-7e15-45cc-97c6-853e31bf758e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4d659fc8-7e15-45cc-97c6-853e31bf758e' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>chain</span>: 8</li><li><span class='xr-has-index'>draw</span>: 1000</li><li><span class='xr-has-index'>y_dim_0</span>: 2604</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-30dec76a-0c98-4dab-a5c2-1e726664247f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-30dec76a-0c98-4dab-a5c2-1e726664247f' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>chain</span></div><div class='xr-var-dims'>(chain)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 7</div><input id='attrs-10642523-4330-46d3-b6b4-509d1e3c8e10' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-10642523-4330-46d3-b6b4-509d1e3c8e10' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-173664e9-dc6f-4ba5-aacd-473a412ea2c5' class='xr-var-data-in' type='checkbox'><label for='data-173664e9-dc6f-4ba5-aacd-473a412ea2c5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 1, 2, 3, 4, 5, 6, 7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>draw</span></div><div class='xr-var-dims'>(draw)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 995 996 997 998 999</div><input id='attrs-0c2b463c-b6ab-437b-aea0-a5c529e71c59' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0c2b463c-b6ab-437b-aea0-a5c529e71c59' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-16bd62d7-9952-4bb1-b0f4-cc2d877743eb' class='xr-var-data-in' type='checkbox'><label for='data-16bd62d7-9952-4bb1-b0f4-cc2d877743eb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  0,   1,   2, ..., 997, 998, 999])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y_dim_0</span></div><div class='xr-var-dims'>(y_dim_0)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 2600 2601 2602 2603</div><input id='attrs-4378e73a-9a79-4fc6-bca0-ecd231e7fbd3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4378e73a-9a79-4fc6-bca0-ecd231e7fbd3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8a71d54a-b424-4250-bbef-5b3c18bdb3d2' class='xr-var-data-in' type='checkbox'><label for='data-8a71d54a-b424-4250-bbef-5b3c18bdb3d2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 2601, 2602, 2603])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-85bc464a-607a-41e1-8ea3-4b8f7110b8bf' class='xr-section-summary-in' type='checkbox'  checked><label for='section-85bc464a-607a-41e1-8ea3-4b8f7110b8bf' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>y</span></div><div class='xr-var-dims'>(chain, draw, y_dim_0)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.7354 0.5207 ... 0.5368 0.04514</div><input id='attrs-13092aee-6c14-4226-b01d-0f6b729a2393' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-13092aee-6c14-4226-b01d-0f6b729a2393' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cc813d8e-52ec-4720-8d99-a5da861d363e' class='xr-var-data-in' type='checkbox'><label for='data-cc813d8e-52ec-4720-8d99-a5da861d363e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[ 7.35434196e-01,  5.20717271e-01, -1.44545814e-01, ...,\n",
       "          9.21069837e-01,  7.59496639e-01, -1.53186713e-01],\n",
       "        [ 8.82613885e-01,  8.43675795e-01, -5.93215486e-01, ...,\n",
       "          9.37429878e-01,  5.07318962e-01, -5.01939021e-01],\n",
       "        [ 9.09105745e-01,  5.72652055e-01,  1.42559062e-01, ...,\n",
       "          9.60346121e-01,  7.93486812e-01, -3.62874633e-01],\n",
       "        ...,\n",
       "        [ 5.28236835e-01,  7.25557515e-01, -1.02142845e-01, ...,\n",
       "          6.40474106e-01,  6.10255713e-01, -7.23355442e-01],\n",
       "        [ 7.47408516e-01,  8.47144370e-01, -1.32073957e+00, ...,\n",
       "          9.45192441e-01,  3.79665679e-01,  1.45559959e-01],\n",
       "        [ 2.25425931e-01,  5.22722424e-01,  7.79481274e-02, ...,\n",
       "          8.43952850e-01,  5.63094769e-01, -6.69936152e-01]],\n",
       "\n",
       "       [[ 6.93938539e-01,  5.79113545e-01, -2.31834258e-01, ...,\n",
       "          8.80539219e-01,  2.89447422e-01, -3.48853593e-01],\n",
       "        [ 8.69000568e-01,  6.06640629e-01, -6.60054627e-01, ...,\n",
       "          9.31007700e-01,  7.85001454e-01, -8.56268441e-01],\n",
       "        [ 6.90269645e-01,  8.06537851e-01, -1.70395001e-01, ...,\n",
       "          9.58267011e-01,  7.39838976e-01,  3.65730366e-01],\n",
       "...\n",
       "        [ 5.91247662e-01,  4.20945521e-01,  1.57920684e-01, ...,\n",
       "          8.11227155e-01,  5.05261295e-01, -3.66371723e-01],\n",
       "        [ 9.18648781e-01,  8.71554955e-01, -2.38054778e-01, ...,\n",
       "          9.47880589e-01,  3.49224793e-01, -3.53417951e-01],\n",
       "        [ 7.74543056e-01,  8.50543268e-01, -6.75329554e-01, ...,\n",
       "          9.04228335e-01,  5.53535848e-01, -1.08629695e-01]],\n",
       "\n",
       "       [[ 8.23168598e-01,  6.32420285e-01, -1.09261371e-01, ...,\n",
       "          9.01277545e-01,  6.23409067e-01, -1.10824699e-03],\n",
       "        [ 4.40128332e-01,  6.75258913e-01, -5.01416568e-01, ...,\n",
       "          8.74782674e-01,  7.52630678e-01, -3.62246362e-01],\n",
       "        [ 6.65517975e-01,  4.86521477e-01, -6.60239584e-01, ...,\n",
       "          9.07865482e-01,  7.97012085e-01,  3.09430369e-02],\n",
       "        ...,\n",
       "        [ 9.35446384e-01,  6.40165521e-01, -2.52865899e-01, ...,\n",
       "          8.24564670e-01,  5.21196554e-01, -8.28162287e-02],\n",
       "        [ 8.94144028e-01,  2.21085012e-01, -3.47841346e-02, ...,\n",
       "          8.96326356e-01,  7.46260624e-01, -5.52711750e-01],\n",
       "        [ 5.55032510e-01,  6.18200257e-01,  4.32261894e-02, ...,\n",
       "          8.94053609e-01,  5.36795174e-01,  4.51352062e-02]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d5e37277-521f-4f2d-8832-f984e9561199' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d5e37277-521f-4f2d-8832-f984e9561199' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>created_at :</span></dt><dd>2022-06-18T13:04:22.695740</dd><dt><span>arviz_version :</span></dt><dd>0.12.1</dd><dt><span>modeling_interface :</span></dt><dd>bambi</dd><dt><span>modeling_interface_version :</span></dt><dd>0.9.0</dd></dl></div></li></ul></div></div><br></div>\n",
       "                      </ul>\n",
       "                  </div>\n",
       "            </li>\n",
       "            \n",
       "            <li class = \"xr-section-item\">\n",
       "                  <input id=\"idata_sample_statse3b3afe7-4689-4167-9592-9d1f0b2741e4\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
       "                  <label for=\"idata_sample_statse3b3afe7-4689-4167-9592-9d1f0b2741e4\" class = \"xr-section-summary\">sample_stats</label>\n",
       "                  <div class=\"xr-section-inline-details\"></div>\n",
       "                  <div class=\"xr-section-details\">\n",
       "                      <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
       "                          <div style=\"padding-left:2rem;\"><div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
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       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
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       " *\n",
       " */\n",
       "\n",
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       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
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       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
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       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
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       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
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       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
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       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
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       "\n",
       ".xr-section-item input {\n",
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       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
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       "\n",
       ".xr-section-item input:enabled + label {\n",
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       "  color: var(--xr-font-color2);\n",
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       "\n",
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       "\n",
       ".xr-section-summary {\n",
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       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
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       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
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       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
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       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
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       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
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       "\n",
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       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
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       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
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       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
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       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
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       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
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       "\n",
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       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
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       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
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       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
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       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
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       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
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       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
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       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
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       "  padding-left: 25px !important;\n",
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       "\n",
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       "  grid-column: 1 / -1;\n",
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       "\n",
       "dl.xr-attrs {\n",
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       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
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       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
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       "\n",
       ".xr-attrs dd {\n",
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       "\n",
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       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:          (chain: 8, draw: 1000)\n",
       "Coordinates:\n",
       "  * chain            (chain) int64 0 1 2 3 4 5 6 7\n",
       "  * draw             (draw) int64 0 1 2 3 4 5 6 ... 993 994 995 996 997 998 999\n",
       "Data variables:\n",
       "    acceptance_rate  (chain, draw) float64 0.9993 0.9846 0.8659 ... 0.8553 0.999\n",
       "    step_size        (chain, draw) float64 0.04374 0.04374 ... 0.05095 0.05095\n",
       "    diverging        (chain, draw) bool False False False ... False False False\n",
       "    energy           (chain, draw) float64 -837.9 -835.4 ... -859.2 -861.4\n",
       "    n_steps          (chain, draw) int64 127 127 127 127 127 ... 63 127 63 63 63\n",
       "    tree_depth       (chain, draw) int64 7 7 7 7 7 7 7 7 7 ... 7 6 6 6 6 7 6 6 6\n",
       "    lp               (chain, draw) float64 -932.1 -927.6 ... -945.9 -940.8\n",
       "Attributes:\n",
       "    created_at:                  2022-06-18T13:04:22.694199\n",
       "    arviz_version:               0.12.1\n",
       "    modeling_interface:          bambi\n",
       "    modeling_interface_version:  0.9.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-1c3f553c-aee3-4b11-806f-2bb752a5345e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-1c3f553c-aee3-4b11-806f-2bb752a5345e' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>chain</span>: 8</li><li><span class='xr-has-index'>draw</span>: 1000</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-35e80d41-0f28-41f3-badd-07c1ce4b980f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-35e80d41-0f28-41f3-badd-07c1ce4b980f' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>chain</span></div><div class='xr-var-dims'>(chain)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 7</div><input id='attrs-fe8e7bf6-c625-4e8c-9873-64312ccb228b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fe8e7bf6-c625-4e8c-9873-64312ccb228b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-efb66989-c632-4a04-8a9c-7d97584fdf6b' class='xr-var-data-in' type='checkbox'><label for='data-efb66989-c632-4a04-8a9c-7d97584fdf6b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 1, 2, 3, 4, 5, 6, 7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>draw</span></div><div class='xr-var-dims'>(draw)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 995 996 997 998 999</div><input id='attrs-6287c695-5918-4097-ada9-2993b89a859c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6287c695-5918-4097-ada9-2993b89a859c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e1856d83-cc14-492d-86a4-f086a870a460' class='xr-var-data-in' type='checkbox'><label for='data-e1856d83-cc14-492d-86a4-f086a870a460' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([  0,   1,   2, ..., 997, 998, 999])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0f308f94-1c75-404d-9598-8214708415cf' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0f308f94-1c75-404d-9598-8214708415cf' class='xr-section-summary' >Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>acceptance_rate</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.9993 0.9846 ... 0.8553 0.999</div><input id='attrs-a1350e25-ddb4-4609-8141-ea2faecc7fcd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a1350e25-ddb4-4609-8141-ea2faecc7fcd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-38444b21-49a5-4d4f-b219-fd79c2969f3d' class='xr-var-data-in' type='checkbox'><label for='data-38444b21-49a5-4d4f-b219-fd79c2969f3d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.99927038, 0.98457107, 0.86590295, ..., 0.99388637, 0.99745458,\n",
       "        0.91096615],\n",
       "       [0.9103201 , 0.97424395, 0.99268592, ..., 0.94581283, 0.98970199,\n",
       "        0.97056085],\n",
       "       [0.51265445, 0.98493941, 0.98497656, ..., 0.94378964, 0.99282582,\n",
       "        0.98710411],\n",
       "       ...,\n",
       "       [0.63982998, 0.97739422, 0.91320702, ..., 0.99684466, 0.93901755,\n",
       "        0.97106329],\n",
       "       [0.8767064 , 0.97329433, 0.9823211 , ..., 0.89224613, 0.97762596,\n",
       "        0.98758155],\n",
       "       [0.6724152 , 0.99224584, 0.99050716, ..., 0.91586161, 0.85532657,\n",
       "        0.99896166]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>step_size</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.04374 0.04374 ... 0.05095 0.05095</div><input id='attrs-cff1ecde-9491-4448-ace7-66aabb066a82' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cff1ecde-9491-4448-ace7-66aabb066a82' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-815cb113-42dd-47a7-836d-462510b2e26d' class='xr-var-data-in' type='checkbox'><label for='data-815cb113-42dd-47a7-836d-462510b2e26d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.04374289, 0.04374289, 0.04374289, ..., 0.04374289, 0.04374289,\n",
       "        0.04374289],\n",
       "       [0.04001906, 0.04001906, 0.04001906, ..., 0.04001906, 0.04001906,\n",
       "        0.04001906],\n",
       "       [0.05601724, 0.05601724, 0.05601724, ..., 0.05601724, 0.05601724,\n",
       "        0.05601724],\n",
       "       ...,\n",
       "       [0.04958334, 0.04958334, 0.04958334, ..., 0.04958334, 0.04958334,\n",
       "        0.04958334],\n",
       "       [0.04886011, 0.04886011, 0.04886011, ..., 0.04886011, 0.04886011,\n",
       "        0.04886011],\n",
       "       [0.05094777, 0.05094777, 0.05094777, ..., 0.05094777, 0.05094777,\n",
       "        0.05094777]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>diverging</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>bool</div><div class='xr-var-preview xr-preview'>False False False ... False False</div><input id='attrs-16c97332-255d-4625-83e9-f19da0952d51' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-16c97332-255d-4625-83e9-f19da0952d51' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-865524f5-909e-4040-9576-e3d63531bed8' class='xr-var-data-in' type='checkbox'><label for='data-865524f5-909e-4040-9576-e3d63531bed8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[False, False, False, ..., False, False, False],\n",
       "       [False, False, False, ..., False, False, False],\n",
       "       [False, False, False, ..., False, False, False],\n",
       "       ...,\n",
       "       [False, False, False, ..., False, False, False],\n",
       "       [False, False, False, ..., False, False, False],\n",
       "       [False, False, False, ..., False, False, False]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>energy</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-837.9 -835.4 ... -859.2 -861.4</div><input id='attrs-133009ad-64c7-4701-8b58-87566cc34e4e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-133009ad-64c7-4701-8b58-87566cc34e4e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-14211c49-df66-4dd6-b260-188e40115fd2' class='xr-var-data-in' type='checkbox'><label for='data-14211c49-df66-4dd6-b260-188e40115fd2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-837.8919278 , -835.35950221, -829.67118531, ..., -845.57306266,\n",
       "        -847.59825093, -849.90375791],\n",
       "       [-866.91474682, -823.34639142, -850.62841578, ..., -862.07017052,\n",
       "        -870.5688339 , -870.25533912],\n",
       "       [-872.59437989, -854.54261881, -850.64526746, ..., -862.0131271 ,\n",
       "        -841.98493478, -855.49911954],\n",
       "       ...,\n",
       "       [-869.4461979 , -845.73997171, -843.66180231, ..., -891.74015837,\n",
       "        -897.55089615, -884.91089419],\n",
       "       [-844.36029312, -829.48992178, -818.31471964, ..., -873.97332957,\n",
       "        -863.40733072, -861.64558963],\n",
       "       [-862.53312242, -851.12519006, -847.40834186, ..., -862.40968328,\n",
       "        -859.15997147, -861.3932246 ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>n_steps</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>127 127 127 127 ... 127 63 63 63</div><input id='attrs-cf1187b6-85fd-4fd5-b104-13060d01d9eb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cf1187b6-85fd-4fd5-b104-13060d01d9eb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d74a9b0c-6c1c-415f-8c2e-6161676db1fc' class='xr-var-data-in' type='checkbox'><label for='data-d74a9b0c-6c1c-415f-8c2e-6161676db1fc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[127, 127, 127, ..., 127, 127, 127],\n",
       "       [127, 127, 127, ..., 127, 127, 127],\n",
       "       [ 63,  63,  63, ...,  63,  63,  63],\n",
       "       ...,\n",
       "       [127,  63,  63, ...,  63,  63,  63],\n",
       "       [ 63, 127, 127, ...,  63, 127, 127],\n",
       "       [ 63,  63,  63, ...,  63,  63,  63]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tree_depth</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>7 7 7 7 7 7 7 7 ... 6 6 6 6 7 6 6 6</div><input id='attrs-88ffc2b9-70d1-4427-86e2-5c5be0d82417' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-88ffc2b9-70d1-4427-86e2-5c5be0d82417' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c8f9d79e-192b-4bd9-90ae-b580852cb6a5' class='xr-var-data-in' type='checkbox'><label for='data-c8f9d79e-192b-4bd9-90ae-b580852cb6a5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[7, 7, 7, ..., 7, 7, 7],\n",
       "       [7, 7, 7, ..., 7, 7, 7],\n",
       "       [6, 6, 6, ..., 6, 6, 6],\n",
       "       ...,\n",
       "       [7, 6, 6, ..., 6, 6, 6],\n",
       "       [6, 7, 7, ..., 6, 7, 7],\n",
       "       [6, 6, 6, ..., 6, 6, 6]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lp</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-932.1 -927.6 ... -945.9 -940.8</div><input id='attrs-1d8ed7e3-5181-4abb-8b7a-51d3d5b81f58' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1d8ed7e3-5181-4abb-8b7a-51d3d5b81f58' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-47637e2a-d098-4e05-a862-f87748a5c3b6' class='xr-var-data-in' type='checkbox'><label for='data-47637e2a-d098-4e05-a862-f87748a5c3b6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-932.12881453, -927.58944311, -938.23218426, ..., -925.94117435,\n",
       "        -930.15581706, -944.07220605],\n",
       "       [-941.21735475, -928.88238508, -953.88200964, ..., -947.32520664,\n",
       "        -954.64964122, -953.79395073],\n",
       "       [-949.10753336, -939.52765291, -944.61356364, ..., -935.86801417,\n",
       "        -936.49961923, -949.08254504],\n",
       "       ...,\n",
       "       [-945.89473365, -924.471582  , -943.37087232, ..., -976.34372843,\n",
       "        -970.46658608, -959.33090174],\n",
       "       [-917.82779143, -911.95458127, -908.68811952, ..., -953.01570668,\n",
       "        -945.0177698 , -946.51521013],\n",
       "       [-945.46006672, -931.21627457, -935.12411511, ..., -940.93667341,\n",
       "        -945.91554964, -940.83245441]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e80c06d7-485e-4473-b270-9c20c5d6533e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e80c06d7-485e-4473-b270-9c20c5d6533e' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>created_at :</span></dt><dd>2022-06-18T13:04:22.694199</dd><dt><span>arviz_version :</span></dt><dd>0.12.1</dd><dt><span>modeling_interface :</span></dt><dd>bambi</dd><dt><span>modeling_interface_version :</span></dt><dd>0.9.0</dd></dl></div></li></ul></div></div><br></div>\n",
       "                      </ul>\n",
       "                  </div>\n",
       "            </li>\n",
       "            \n",
       "            <li class = \"xr-section-item\">\n",
       "                  <input id=\"idata_observed_data25ad7452-b0b9-4795-8e2a-fe58863c266a\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
       "                  <label for=\"idata_observed_data25ad7452-b0b9-4795-8e2a-fe58863c266a\" class = \"xr-section-summary\">observed_data</label>\n",
       "                  <div class=\"xr-section-inline-details\"></div>\n",
       "                  <div class=\"xr-section-details\">\n",
       "                      <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
       "                          <div style=\"padding-left:2rem;\"><div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
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       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
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       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (y_dim_0: 2604)\n",
       "Coordinates:\n",
       "  * y_dim_0  (y_dim_0) int64 0 1 2 3 4 5 6 ... 2598 2599 2600 2601 2602 2603\n",
       "Data variables:\n",
       "    y        (y_dim_0) float64 0.3457 0.5166 0.0919 ... 0.1925 0.3157 0.5199\n",
       "Attributes:\n",
       "    created_at:                  2022-06-18T13:04:22.696087\n",
       "    arviz_version:               0.12.1\n",
       "    inference_library:           numpyro\n",
       "    inference_library_version:   0.9.2\n",
       "    sampling_time:               29.795361\n",
       "    modeling_interface:          bambi\n",
       "    modeling_interface_version:  0.9.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-a45838e4-aa8f-4ecc-a001-6afb24808104' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a45838e4-aa8f-4ecc-a001-6afb24808104' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>y_dim_0</span>: 2604</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-ba4c6de4-f7c2-47ab-abbc-950fb319d8fe' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ba4c6de4-f7c2-47ab-abbc-950fb319d8fe' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y_dim_0</span></div><div class='xr-var-dims'>(y_dim_0)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 2600 2601 2602 2603</div><input id='attrs-88846c4c-0ab2-480f-a5aa-dad959b3b576' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-88846c4c-0ab2-480f-a5aa-dad959b3b576' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8f96a625-8993-4084-bf7a-65c0ba8a42c8' class='xr-var-data-in' type='checkbox'><label for='data-8f96a625-8993-4084-bf7a-65c0ba8a42c8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 2601, 2602, 2603])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4c33b21f-9dd6-4cfc-b9fd-4d139d1339e3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4c33b21f-9dd6-4cfc-b9fd-4d139d1339e3' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>y</span></div><div class='xr-var-dims'>(y_dim_0)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.3457 0.5166 ... 0.3157 0.5199</div><input id='attrs-dfcf5950-96be-4d02-8e08-83b8099c5d51' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-dfcf5950-96be-4d02-8e08-83b8099c5d51' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a92b8e0a-d028-4abe-84e7-436883b5d531' class='xr-var-data-in' type='checkbox'><label for='data-a92b8e0a-d028-4abe-84e7-436883b5d531' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0.3457, 0.5166, 0.0919, ..., 0.1925, 0.3157, 0.5199])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fab96605-e39f-4c38-8a50-e6c6d7bb403c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-fab96605-e39f-4c38-8a50-e6c6d7bb403c' class='xr-section-summary' >Attributes: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>created_at :</span></dt><dd>2022-06-18T13:04:22.696087</dd><dt><span>arviz_version :</span></dt><dd>0.12.1</dd><dt><span>inference_library :</span></dt><dd>numpyro</dd><dt><span>inference_library_version :</span></dt><dd>0.9.2</dd><dt><span>sampling_time :</span></dt><dd>29.795361</dd><dt><span>modeling_interface :</span></dt><dd>bambi</dd><dt><span>modeling_interface_version :</span></dt><dd>0.9.0</dd></dl></div></li></ul></div></div><br></div>\n",
       "                      </ul>\n",
       "                  </div>\n",
       "            </li>\n",
       "            \n",
       "              </ul>\n",
       "            </div>\n",
       "            <style> /* CSS stylesheet for displaying InferenceData objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
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       "\n",
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       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
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       "\n",
       ".xr-wrap {\n",
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       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
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       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
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       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
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       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
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       "\n",
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       "\n",
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       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
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       "\n",
       ".xr-sections.group-sections {\n",
       "  grid-template-columns: auto;\n",
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       "\n",
       ".xr-section-item {\n",
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       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
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       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
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       "\n",
       ".xr-section-item input:enabled + label {\n",
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       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
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       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
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       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
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       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
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       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
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       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
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       "\n",
       ".xr-array-wrap > label {\n",
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       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
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       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
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       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
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       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
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       ".xr-var-list > li:nth-child(odd) > div,\n",
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       "\n",
       ".xr-var-name {\n",
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       "}\n",
       "\n",
       ".xr-var-dtype {\n",
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       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
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       "\n",
       ".xr-var-preview {\n",
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       "\n",
       ".xr-var-name,\n",
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       ".xr-var-dims:hover,\n",
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       ".xr-attrs dt:hover {\n",
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       "\n",
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       "\n",
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       "\n",
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       ".xr-var-data,\n",
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       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
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       "}\n",
       "\n",
       ".xr-attrs dt, dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
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       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
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       ".xr-wrap{width:700px!important;} </style>"
      ],
      "text/plain": [
       "Inference data with groups:\n",
       "\t> posterior\n",
       "\t> log_likelihood\n",
       "\t> sample_stats\n",
       "\t> observed_data"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "32abac95-4438-4f55-9821-d02b337db868",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "number_of_divergences = int(results.sample_stats.diverging.sum())\n",
    "number_of_divergences"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "f28ac39e-da31-4b69-b7f4-1bc5b077d4e0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bool(np.all((0.9 <= az.rhat(results) <= 1.05).to_array()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "0678eadb-8cc1-43b9-b0d2-d880cab40fd7",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
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       "      <th>1|subject[HMN031]</th>\n",
       "      <td>0.089</td>\n",
       "      <td>0.032</td>\n",
       "      <td>0.027</td>\n",
       "      <td>0.148</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>10484.0</td>\n",
       "      <td>5314.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN032]</th>\n",
       "      <td>0.037</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.024</td>\n",
       "      <td>0.096</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>8882.0</td>\n",
       "      <td>5580.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN033]</th>\n",
       "      <td>-0.014</td>\n",
       "      <td>0.036</td>\n",
       "      <td>-0.082</td>\n",
       "      <td>0.051</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.000</td>\n",
       "      <td>4922.0</td>\n",
       "      <td>5752.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN035]</th>\n",
       "      <td>0.104</td>\n",
       "      <td>0.032</td>\n",
       "      <td>0.046</td>\n",
       "      <td>0.164</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9143.0</td>\n",
       "      <td>5871.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN037]</th>\n",
       "      <td>-0.070</td>\n",
       "      <td>0.031</td>\n",
       "      <td>-0.127</td>\n",
       "      <td>-0.010</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>10149.0</td>\n",
       "      <td>5960.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN038]</th>\n",
       "      <td>0.024</td>\n",
       "      <td>0.031</td>\n",
       "      <td>-0.033</td>\n",
       "      <td>0.083</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>10430.0</td>\n",
       "      <td>6034.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN039]</th>\n",
       "      <td>-0.022</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.082</td>\n",
       "      <td>0.037</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>11153.0</td>\n",
       "      <td>5394.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN040]</th>\n",
       "      <td>-0.030</td>\n",
       "      <td>0.034</td>\n",
       "      <td>-0.094</td>\n",
       "      <td>0.031</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>7325.0</td>\n",
       "      <td>6155.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN041]</th>\n",
       "      <td>-0.046</td>\n",
       "      <td>0.031</td>\n",
       "      <td>-0.105</td>\n",
       "      <td>0.012</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>10178.0</td>\n",
       "      <td>5515.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN042]</th>\n",
       "      <td>-0.035</td>\n",
       "      <td>0.031</td>\n",
       "      <td>-0.097</td>\n",
       "      <td>0.019</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9431.0</td>\n",
       "      <td>5814.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN043]</th>\n",
       "      <td>0.018</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.038</td>\n",
       "      <td>0.082</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>11478.0</td>\n",
       "      <td>5919.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN045]</th>\n",
       "      <td>-0.059</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.120</td>\n",
       "      <td>0.002</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>7747.0</td>\n",
       "      <td>5851.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN048]</th>\n",
       "      <td>-0.086</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.145</td>\n",
       "      <td>-0.027</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9801.0</td>\n",
       "      <td>5933.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN049]</th>\n",
       "      <td>0.026</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.034</td>\n",
       "      <td>0.086</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>11033.0</td>\n",
       "      <td>6136.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN050_2]</th>\n",
       "      <td>0.028</td>\n",
       "      <td>0.031</td>\n",
       "      <td>-0.029</td>\n",
       "      <td>0.088</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>8726.0</td>\n",
       "      <td>5388.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN052]</th>\n",
       "      <td>0.042</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.016</td>\n",
       "      <td>0.105</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9575.0</td>\n",
       "      <td>5563.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN053]</th>\n",
       "      <td>-0.027</td>\n",
       "      <td>0.034</td>\n",
       "      <td>-0.094</td>\n",
       "      <td>0.036</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>5743.0</td>\n",
       "      <td>5662.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN055]</th>\n",
       "      <td>0.028</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.032</td>\n",
       "      <td>0.087</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9629.0</td>\n",
       "      <td>5603.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN056]</th>\n",
       "      <td>-0.015</td>\n",
       "      <td>0.033</td>\n",
       "      <td>-0.076</td>\n",
       "      <td>0.046</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>7725.0</td>\n",
       "      <td>5482.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN057]</th>\n",
       "      <td>0.000</td>\n",
       "      <td>0.031</td>\n",
       "      <td>-0.059</td>\n",
       "      <td>0.057</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>10108.0</td>\n",
       "      <td>5424.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN058]</th>\n",
       "      <td>0.002</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.060</td>\n",
       "      <td>0.060</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>8541.0</td>\n",
       "      <td>5803.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN060]</th>\n",
       "      <td>0.012</td>\n",
       "      <td>0.033</td>\n",
       "      <td>-0.049</td>\n",
       "      <td>0.073</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>7838.0</td>\n",
       "      <td>5601.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN062]</th>\n",
       "      <td>-0.070</td>\n",
       "      <td>0.031</td>\n",
       "      <td>-0.127</td>\n",
       "      <td>-0.009</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>8934.0</td>\n",
       "      <td>5830.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN065]</th>\n",
       "      <td>0.160</td>\n",
       "      <td>0.031</td>\n",
       "      <td>0.102</td>\n",
       "      <td>0.218</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9674.0</td>\n",
       "      <td>6067.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN068]</th>\n",
       "      <td>0.066</td>\n",
       "      <td>0.031</td>\n",
       "      <td>0.008</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>8914.0</td>\n",
       "      <td>6198.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN069]</th>\n",
       "      <td>0.090</td>\n",
       "      <td>0.031</td>\n",
       "      <td>0.033</td>\n",
       "      <td>0.148</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>10172.0</td>\n",
       "      <td>5776.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN072]</th>\n",
       "      <td>0.001</td>\n",
       "      <td>0.031</td>\n",
       "      <td>-0.056</td>\n",
       "      <td>0.061</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9712.0</td>\n",
       "      <td>6049.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN073]</th>\n",
       "      <td>0.095</td>\n",
       "      <td>0.032</td>\n",
       "      <td>0.034</td>\n",
       "      <td>0.156</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>10223.0</td>\n",
       "      <td>5453.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN074]</th>\n",
       "      <td>0.037</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.024</td>\n",
       "      <td>0.097</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9874.0</td>\n",
       "      <td>5660.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN075]</th>\n",
       "      <td>0.123</td>\n",
       "      <td>0.031</td>\n",
       "      <td>0.066</td>\n",
       "      <td>0.184</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>8674.0</td>\n",
       "      <td>4821.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN077]</th>\n",
       "      <td>0.051</td>\n",
       "      <td>0.031</td>\n",
       "      <td>-0.006</td>\n",
       "      <td>0.109</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9378.0</td>\n",
       "      <td>5708.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN079]</th>\n",
       "      <td>0.005</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.052</td>\n",
       "      <td>0.067</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9598.0</td>\n",
       "      <td>5678.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN080_W2]</th>\n",
       "      <td>0.030</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.027</td>\n",
       "      <td>0.092</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9764.0</td>\n",
       "      <td>6116.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN081]</th>\n",
       "      <td>0.006</td>\n",
       "      <td>0.033</td>\n",
       "      <td>-0.058</td>\n",
       "      <td>0.068</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>7413.0</td>\n",
       "      <td>5839.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN082]</th>\n",
       "      <td>-0.002</td>\n",
       "      <td>0.038</td>\n",
       "      <td>-0.077</td>\n",
       "      <td>0.065</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.000</td>\n",
       "      <td>4013.0</td>\n",
       "      <td>5347.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN083_W2]</th>\n",
       "      <td>-0.038</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.096</td>\n",
       "      <td>0.024</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9497.0</td>\n",
       "      <td>5720.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN085]</th>\n",
       "      <td>-0.073</td>\n",
       "      <td>0.033</td>\n",
       "      <td>-0.133</td>\n",
       "      <td>-0.009</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>7482.0</td>\n",
       "      <td>5710.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN086]</th>\n",
       "      <td>0.033</td>\n",
       "      <td>0.031</td>\n",
       "      <td>-0.023</td>\n",
       "      <td>0.095</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>10677.0</td>\n",
       "      <td>5979.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN087]</th>\n",
       "      <td>-0.018</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.079</td>\n",
       "      <td>0.042</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>7959.0</td>\n",
       "      <td>5780.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN088]</th>\n",
       "      <td>-0.077</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.139</td>\n",
       "      <td>-0.017</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>8166.0</td>\n",
       "      <td>5395.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN090]</th>\n",
       "      <td>-0.091</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.153</td>\n",
       "      <td>-0.033</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>6739.0</td>\n",
       "      <td>6046.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN092]</th>\n",
       "      <td>-0.013</td>\n",
       "      <td>0.034</td>\n",
       "      <td>-0.077</td>\n",
       "      <td>0.050</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>6375.0</td>\n",
       "      <td>5254.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN095]</th>\n",
       "      <td>-0.071</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.131</td>\n",
       "      <td>-0.013</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9302.0</td>\n",
       "      <td>5524.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN096]</th>\n",
       "      <td>0.013</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.048</td>\n",
       "      <td>0.072</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>10587.0</td>\n",
       "      <td>5721.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN099]</th>\n",
       "      <td>-0.134</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.195</td>\n",
       "      <td>-0.076</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>10034.0</td>\n",
       "      <td>5460.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN101]</th>\n",
       "      <td>0.010</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.049</td>\n",
       "      <td>0.073</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>8022.0</td>\n",
       "      <td>6196.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN102]</th>\n",
       "      <td>0.190</td>\n",
       "      <td>0.035</td>\n",
       "      <td>0.125</td>\n",
       "      <td>0.255</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>6116.0</td>\n",
       "      <td>5609.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN103]</th>\n",
       "      <td>-0.053</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.110</td>\n",
       "      <td>0.008</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>10335.0</td>\n",
       "      <td>5544.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN104]</th>\n",
       "      <td>0.021</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.040</td>\n",
       "      <td>0.077</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>10737.0</td>\n",
       "      <td>5661.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN105]</th>\n",
       "      <td>-0.003</td>\n",
       "      <td>0.031</td>\n",
       "      <td>-0.060</td>\n",
       "      <td>0.055</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>10786.0</td>\n",
       "      <td>6015.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN108]</th>\n",
       "      <td>0.000</td>\n",
       "      <td>0.031</td>\n",
       "      <td>-0.058</td>\n",
       "      <td>0.058</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9626.0</td>\n",
       "      <td>6031.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN109]</th>\n",
       "      <td>0.096</td>\n",
       "      <td>0.032</td>\n",
       "      <td>0.036</td>\n",
       "      <td>0.157</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>8259.0</td>\n",
       "      <td>6260.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN110]</th>\n",
       "      <td>-0.116</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.177</td>\n",
       "      <td>-0.058</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>10445.0</td>\n",
       "      <td>5880.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN111]</th>\n",
       "      <td>-0.172</td>\n",
       "      <td>0.033</td>\n",
       "      <td>-0.237</td>\n",
       "      <td>-0.112</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>7908.0</td>\n",
       "      <td>6140.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN113]</th>\n",
       "      <td>-0.042</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.103</td>\n",
       "      <td>0.019</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>8035.0</td>\n",
       "      <td>5258.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN114]</th>\n",
       "      <td>-0.080</td>\n",
       "      <td>0.031</td>\n",
       "      <td>-0.138</td>\n",
       "      <td>-0.020</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9348.0</td>\n",
       "      <td>5884.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN115]</th>\n",
       "      <td>0.042</td>\n",
       "      <td>0.031</td>\n",
       "      <td>-0.015</td>\n",
       "      <td>0.099</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>10367.0</td>\n",
       "      <td>6159.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN116]</th>\n",
       "      <td>-0.043</td>\n",
       "      <td>0.031</td>\n",
       "      <td>-0.101</td>\n",
       "      <td>0.016</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9815.0</td>\n",
       "      <td>5844.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN117]</th>\n",
       "      <td>-0.080</td>\n",
       "      <td>0.033</td>\n",
       "      <td>-0.144</td>\n",
       "      <td>-0.019</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9674.0</td>\n",
       "      <td>5630.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN118]</th>\n",
       "      <td>0.037</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.023</td>\n",
       "      <td>0.097</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>8703.0</td>\n",
       "      <td>5523.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN119]</th>\n",
       "      <td>-0.059</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.120</td>\n",
       "      <td>-0.001</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9540.0</td>\n",
       "      <td>5382.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN120]</th>\n",
       "      <td>0.060</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.001</td>\n",
       "      <td>0.117</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9802.0</td>\n",
       "      <td>5533.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN121]</th>\n",
       "      <td>0.035</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.024</td>\n",
       "      <td>0.094</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9631.0</td>\n",
       "      <td>5918.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN122]</th>\n",
       "      <td>-0.050</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.111</td>\n",
       "      <td>0.010</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9662.0</td>\n",
       "      <td>5444.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN123]</th>\n",
       "      <td>-0.143</td>\n",
       "      <td>0.031</td>\n",
       "      <td>-0.204</td>\n",
       "      <td>-0.086</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>11092.0</td>\n",
       "      <td>6327.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN124]</th>\n",
       "      <td>-0.009</td>\n",
       "      <td>0.031</td>\n",
       "      <td>-0.068</td>\n",
       "      <td>0.050</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9710.0</td>\n",
       "      <td>5436.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN125_W2]</th>\n",
       "      <td>-0.137</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.194</td>\n",
       "      <td>-0.074</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9331.0</td>\n",
       "      <td>5541.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN126]</th>\n",
       "      <td>0.041</td>\n",
       "      <td>0.033</td>\n",
       "      <td>-0.023</td>\n",
       "      <td>0.102</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>6445.0</td>\n",
       "      <td>6187.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN127]</th>\n",
       "      <td>-0.028</td>\n",
       "      <td>0.031</td>\n",
       "      <td>-0.088</td>\n",
       "      <td>0.030</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>10651.0</td>\n",
       "      <td>5432.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN129_W2]</th>\n",
       "      <td>-0.080</td>\n",
       "      <td>0.033</td>\n",
       "      <td>-0.143</td>\n",
       "      <td>-0.022</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>8719.0</td>\n",
       "      <td>6096.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN130]</th>\n",
       "      <td>0.030</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.033</td>\n",
       "      <td>0.086</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9748.0</td>\n",
       "      <td>6054.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN134]</th>\n",
       "      <td>0.018</td>\n",
       "      <td>0.033</td>\n",
       "      <td>-0.043</td>\n",
       "      <td>0.081</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>6049.0</td>\n",
       "      <td>5663.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN136]</th>\n",
       "      <td>-0.029</td>\n",
       "      <td>0.031</td>\n",
       "      <td>-0.087</td>\n",
       "      <td>0.030</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>10662.0</td>\n",
       "      <td>5231.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN138]</th>\n",
       "      <td>0.062</td>\n",
       "      <td>0.031</td>\n",
       "      <td>0.002</td>\n",
       "      <td>0.119</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>10687.0</td>\n",
       "      <td>6367.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN140]</th>\n",
       "      <td>0.065</td>\n",
       "      <td>0.032</td>\n",
       "      <td>0.007</td>\n",
       "      <td>0.127</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>7418.0</td>\n",
       "      <td>5820.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN143]</th>\n",
       "      <td>-0.005</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.065</td>\n",
       "      <td>0.054</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>8531.0</td>\n",
       "      <td>5668.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN144]</th>\n",
       "      <td>-0.116</td>\n",
       "      <td>0.031</td>\n",
       "      <td>-0.175</td>\n",
       "      <td>-0.056</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9795.0</td>\n",
       "      <td>5013.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN161_W2]</th>\n",
       "      <td>0.181</td>\n",
       "      <td>0.033</td>\n",
       "      <td>0.121</td>\n",
       "      <td>0.241</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>10389.0</td>\n",
       "      <td>5567.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN167]</th>\n",
       "      <td>0.107</td>\n",
       "      <td>0.031</td>\n",
       "      <td>0.049</td>\n",
       "      <td>0.166</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>10606.0</td>\n",
       "      <td>5448.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN169]</th>\n",
       "      <td>-0.010</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.068</td>\n",
       "      <td>0.051</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>10816.0</td>\n",
       "      <td>5724.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN172]</th>\n",
       "      <td>-0.008</td>\n",
       "      <td>0.031</td>\n",
       "      <td>-0.068</td>\n",
       "      <td>0.048</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>10120.0</td>\n",
       "      <td>6046.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN174]</th>\n",
       "      <td>-0.023</td>\n",
       "      <td>0.031</td>\n",
       "      <td>-0.078</td>\n",
       "      <td>0.037</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9851.0</td>\n",
       "      <td>5945.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN175]</th>\n",
       "      <td>0.116</td>\n",
       "      <td>0.032</td>\n",
       "      <td>0.054</td>\n",
       "      <td>0.175</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>8207.0</td>\n",
       "      <td>5808.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN178]</th>\n",
       "      <td>-0.058</td>\n",
       "      <td>0.031</td>\n",
       "      <td>-0.114</td>\n",
       "      <td>0.004</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>8783.0</td>\n",
       "      <td>5822.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN180]</th>\n",
       "      <td>0.056</td>\n",
       "      <td>0.031</td>\n",
       "      <td>-0.002</td>\n",
       "      <td>0.114</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>10509.0</td>\n",
       "      <td>6410.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN182]</th>\n",
       "      <td>-0.060</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.118</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9609.0</td>\n",
       "      <td>5743.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN183]</th>\n",
       "      <td>0.041</td>\n",
       "      <td>0.031</td>\n",
       "      <td>-0.020</td>\n",
       "      <td>0.098</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9942.0</td>\n",
       "      <td>5356.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN184]</th>\n",
       "      <td>0.083</td>\n",
       "      <td>0.031</td>\n",
       "      <td>0.026</td>\n",
       "      <td>0.141</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>10059.0</td>\n",
       "      <td>6261.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN186]</th>\n",
       "      <td>-0.055</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.114</td>\n",
       "      <td>0.003</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>11139.0</td>\n",
       "      <td>5314.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN187]</th>\n",
       "      <td>-0.112</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.174</td>\n",
       "      <td>-0.054</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>7598.0</td>\n",
       "      <td>5952.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN188]</th>\n",
       "      <td>0.157</td>\n",
       "      <td>0.031</td>\n",
       "      <td>0.097</td>\n",
       "      <td>0.215</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>10535.0</td>\n",
       "      <td>5882.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN189]</th>\n",
       "      <td>0.101</td>\n",
       "      <td>0.031</td>\n",
       "      <td>0.043</td>\n",
       "      <td>0.162</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>10239.0</td>\n",
       "      <td>5554.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN190]</th>\n",
       "      <td>-0.015</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.073</td>\n",
       "      <td>0.045</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9997.0</td>\n",
       "      <td>5794.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN191]</th>\n",
       "      <td>-0.097</td>\n",
       "      <td>0.031</td>\n",
       "      <td>-0.156</td>\n",
       "      <td>-0.038</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9577.0</td>\n",
       "      <td>6010.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN193]</th>\n",
       "      <td>-0.066</td>\n",
       "      <td>0.036</td>\n",
       "      <td>-0.131</td>\n",
       "      <td>0.004</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.000</td>\n",
       "      <td>4950.0</td>\n",
       "      <td>5637.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN194]</th>\n",
       "      <td>-0.062</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.119</td>\n",
       "      <td>-0.001</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>8457.0</td>\n",
       "      <td>6114.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN196]</th>\n",
       "      <td>0.035</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.023</td>\n",
       "      <td>0.096</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>8004.0</td>\n",
       "      <td>6317.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN197]</th>\n",
       "      <td>-0.011</td>\n",
       "      <td>0.031</td>\n",
       "      <td>-0.069</td>\n",
       "      <td>0.048</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9265.0</td>\n",
       "      <td>6011.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN199]</th>\n",
       "      <td>0.041</td>\n",
       "      <td>0.032</td>\n",
       "      <td>-0.018</td>\n",
       "      <td>0.102</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9262.0</td>\n",
       "      <td>5816.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|subject[HMN201]</th>\n",
       "      <td>0.125</td>\n",
       "      <td>0.031</td>\n",
       "      <td>0.064</td>\n",
       "      <td>0.182</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>10147.0</td>\n",
       "      <td>5905.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|ROI[ACC]</th>\n",
       "      <td>-0.029</td>\n",
       "      <td>0.058</td>\n",
       "      <td>-0.142</td>\n",
       "      <td>0.080</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>5842.0</td>\n",
       "      <td>5011.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|ROI[LAmy/Hippo]</th>\n",
       "      <td>0.017</td>\n",
       "      <td>0.057</td>\n",
       "      <td>-0.087</td>\n",
       "      <td>0.137</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>6830.0</td>\n",
       "      <td>5328.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|ROI[LCing]</th>\n",
       "      <td>-0.041</td>\n",
       "      <td>0.063</td>\n",
       "      <td>-0.169</td>\n",
       "      <td>0.071</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>4893.0</td>\n",
       "      <td>5058.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|ROI[LIFG]</th>\n",
       "      <td>-0.019</td>\n",
       "      <td>0.057</td>\n",
       "      <td>-0.131</td>\n",
       "      <td>0.088</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>6835.0</td>\n",
       "      <td>5060.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|ROI[LIPL]</th>\n",
       "      <td>-0.025</td>\n",
       "      <td>0.059</td>\n",
       "      <td>-0.140</td>\n",
       "      <td>0.088</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>6256.0</td>\n",
       "      <td>5324.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|ROI[LMTG]</th>\n",
       "      <td>0.038</td>\n",
       "      <td>0.060</td>\n",
       "      <td>-0.069</td>\n",
       "      <td>0.159</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>5374.0</td>\n",
       "      <td>5515.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|ROI[LSFG]</th>\n",
       "      <td>-0.030</td>\n",
       "      <td>0.058</td>\n",
       "      <td>-0.144</td>\n",
       "      <td>0.076</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>5416.0</td>\n",
       "      <td>5174.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|ROI[LTPJ]</th>\n",
       "      <td>0.023</td>\n",
       "      <td>0.058</td>\n",
       "      <td>-0.087</td>\n",
       "      <td>0.135</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>6228.0</td>\n",
       "      <td>5472.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|ROI[LaMTS/aMTG]</th>\n",
       "      <td>-0.041</td>\n",
       "      <td>0.063</td>\n",
       "      <td>-0.171</td>\n",
       "      <td>0.068</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>5124.0</td>\n",
       "      <td>5264.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|ROI[LvBG]</th>\n",
       "      <td>-0.012</td>\n",
       "      <td>0.056</td>\n",
       "      <td>-0.126</td>\n",
       "      <td>0.093</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>7796.0</td>\n",
       "      <td>5292.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|ROI[PCC]</th>\n",
       "      <td>-0.025</td>\n",
       "      <td>0.057</td>\n",
       "      <td>-0.140</td>\n",
       "      <td>0.079</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>5799.0</td>\n",
       "      <td>5485.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|ROI[RAmy/Hippo]</th>\n",
       "      <td>0.020</td>\n",
       "      <td>0.059</td>\n",
       "      <td>-0.091</td>\n",
       "      <td>0.137</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>6577.0</td>\n",
       "      <td>4526.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|ROI[RIFG_BA45]</th>\n",
       "      <td>0.017</td>\n",
       "      <td>0.056</td>\n",
       "      <td>-0.087</td>\n",
       "      <td>0.134</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>7111.0</td>\n",
       "      <td>4861.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|ROI[RIFG_BA9]</th>\n",
       "      <td>0.008</td>\n",
       "      <td>0.058</td>\n",
       "      <td>-0.105</td>\n",
       "      <td>0.118</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>6830.0</td>\n",
       "      <td>5378.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|ROI[RIns]</th>\n",
       "      <td>0.026</td>\n",
       "      <td>0.059</td>\n",
       "      <td>-0.081</td>\n",
       "      <td>0.144</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>5350.0</td>\n",
       "      <td>4938.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|ROI[RPCC]</th>\n",
       "      <td>0.004</td>\n",
       "      <td>0.059</td>\n",
       "      <td>-0.106</td>\n",
       "      <td>0.124</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>7058.0</td>\n",
       "      <td>4489.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|ROI[RTPJp]</th>\n",
       "      <td>0.164</td>\n",
       "      <td>0.106</td>\n",
       "      <td>-0.015</td>\n",
       "      <td>0.344</td>\n",
       "      <td>0.002</td>\n",
       "      <td>0.002</td>\n",
       "      <td>1934.0</td>\n",
       "      <td>2133.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|ROI[RvBG]</th>\n",
       "      <td>-0.001</td>\n",
       "      <td>0.057</td>\n",
       "      <td>-0.114</td>\n",
       "      <td>0.106</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>7444.0</td>\n",
       "      <td>5805.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|ROI[SGC]</th>\n",
       "      <td>-0.030</td>\n",
       "      <td>0.059</td>\n",
       "      <td>-0.145</td>\n",
       "      <td>0.079</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>6205.0</td>\n",
       "      <td>5305.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|ROI[dmMPFC]</th>\n",
       "      <td>-0.026</td>\n",
       "      <td>0.058</td>\n",
       "      <td>-0.144</td>\n",
       "      <td>0.074</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>6390.0</td>\n",
       "      <td>4741.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1|ROI[vmPFC]</th>\n",
       "      <td>-0.039</td>\n",
       "      <td>0.059</td>\n",
       "      <td>-0.160</td>\n",
       "      <td>0.064</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.001</td>\n",
       "      <td>5795.0</td>\n",
       "      <td>5907.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x|ROI[ACC]</th>\n",
       "      <td>-0.005</td>\n",
       "      <td>0.004</td>\n",
       "      <td>-0.012</td>\n",
       "      <td>0.002</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>4120.0</td>\n",
       "      <td>4736.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x|ROI[LAmy/Hippo]</th>\n",
       "      <td>-0.005</td>\n",
       "      <td>0.004</td>\n",
       "      <td>-0.012</td>\n",
       "      <td>0.002</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>4140.0</td>\n",
       "      <td>4748.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x|ROI[LCing]</th>\n",
       "      <td>-0.010</td>\n",
       "      <td>0.004</td>\n",
       "      <td>-0.018</td>\n",
       "      <td>-0.002</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>3904.0</td>\n",
       "      <td>4630.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x|ROI[LIFG]</th>\n",
       "      <td>-0.007</td>\n",
       "      <td>0.004</td>\n",
       "      <td>-0.013</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>4570.0</td>\n",
       "      <td>4805.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x|ROI[LIPL]</th>\n",
       "      <td>0.006</td>\n",
       "      <td>0.004</td>\n",
       "      <td>-0.001</td>\n",
       "      <td>0.013</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>4062.0</td>\n",
       "      <td>5080.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x|ROI[LMTG]</th>\n",
       "      <td>-0.002</td>\n",
       "      <td>0.004</td>\n",
       "      <td>-0.009</td>\n",
       "      <td>0.006</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>3622.0</td>\n",
       "      <td>4757.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x|ROI[LSFG]</th>\n",
       "      <td>-0.000</td>\n",
       "      <td>0.004</td>\n",
       "      <td>-0.007</td>\n",
       "      <td>0.007</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>3967.0</td>\n",
       "      <td>5143.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x|ROI[LTPJ]</th>\n",
       "      <td>0.008</td>\n",
       "      <td>0.004</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.016</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>3929.0</td>\n",
       "      <td>4655.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x|ROI[LaMTS/aMTG]</th>\n",
       "      <td>0.005</td>\n",
       "      <td>0.004</td>\n",
       "      <td>-0.002</td>\n",
       "      <td>0.013</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>4076.0</td>\n",
       "      <td>5375.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x|ROI[LvBG]</th>\n",
       "      <td>-0.004</td>\n",
       "      <td>0.004</td>\n",
       "      <td>-0.012</td>\n",
       "      <td>0.003</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>4815.0</td>\n",
       "      <td>5204.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x|ROI[PCC]</th>\n",
       "      <td>0.004</td>\n",
       "      <td>0.004</td>\n",
       "      <td>-0.003</td>\n",
       "      <td>0.011</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>3656.0</td>\n",
       "      <td>4894.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x|ROI[RAmy/Hippo]</th>\n",
       "      <td>-0.004</td>\n",
       "      <td>0.004</td>\n",
       "      <td>-0.012</td>\n",
       "      <td>0.003</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>4306.0</td>\n",
       "      <td>4706.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x|ROI[RIFG_BA45]</th>\n",
       "      <td>-0.006</td>\n",
       "      <td>0.004</td>\n",
       "      <td>-0.013</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>4538.0</td>\n",
       "      <td>4896.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x|ROI[RIFG_BA9]</th>\n",
       "      <td>-0.004</td>\n",
       "      <td>0.004</td>\n",
       "      <td>-0.011</td>\n",
       "      <td>0.003</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>4114.0</td>\n",
       "      <td>4971.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x|ROI[RIns]</th>\n",
       "      <td>-0.004</td>\n",
       "      <td>0.004</td>\n",
       "      <td>-0.011</td>\n",
       "      <td>0.004</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>3823.0</td>\n",
       "      <td>4406.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x|ROI[RPCC]</th>\n",
       "      <td>0.011</td>\n",
       "      <td>0.004</td>\n",
       "      <td>0.004</td>\n",
       "      <td>0.018</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>4641.0</td>\n",
       "      <td>5392.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x|ROI[RTPJp]</th>\n",
       "      <td>0.021</td>\n",
       "      <td>0.006</td>\n",
       "      <td>0.010</td>\n",
       "      <td>0.033</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>2066.0</td>\n",
       "      <td>2872.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x|ROI[RvBG]</th>\n",
       "      <td>-0.003</td>\n",
       "      <td>0.004</td>\n",
       "      <td>-0.011</td>\n",
       "      <td>0.004</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>4444.0</td>\n",
       "      <td>4401.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x|ROI[SGC]</th>\n",
       "      <td>-0.004</td>\n",
       "      <td>0.004</td>\n",
       "      <td>-0.011</td>\n",
       "      <td>0.003</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>4117.0</td>\n",
       "      <td>4764.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x|ROI[dmMPFC]</th>\n",
       "      <td>0.002</td>\n",
       "      <td>0.004</td>\n",
       "      <td>-0.005</td>\n",
       "      <td>0.009</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>4182.0</td>\n",
       "      <td>5443.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>x|ROI[vmPFC]</th>\n",
       "      <td>0.001</td>\n",
       "      <td>0.004</td>\n",
       "      <td>-0.006</td>\n",
       "      <td>0.009</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>3939.0</td>\n",
       "      <td>5329.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       mean     sd  hdi_3%  hdi_97%  mcse_mean  mcse_sd  \\\n",
       "Intercept             0.054  0.065  -0.069    0.176      0.001    0.001   \n",
       "x                     0.007  0.004  -0.001    0.015      0.000    0.000   \n",
       "1|subject_sigma       0.077  0.006   0.066    0.089      0.000    0.000   \n",
       "1|ROI_sigma           0.074  0.034   0.003    0.130      0.001    0.001   \n",
       "x|ROI_sigma           0.009  0.002   0.006    0.012      0.000    0.000   \n",
       "y_sigma               0.153  0.002   0.149    0.157      0.000    0.000   \n",
       "1|subject[HMN001]     0.057  0.031  -0.002    0.116      0.000    0.000   \n",
       "1|subject[HMN002]     0.051  0.031  -0.008    0.108      0.000    0.000   \n",
       "1|subject[HMN003]     0.000  0.032  -0.058    0.061      0.000    0.000   \n",
       "1|subject[HMN004]    -0.088  0.032  -0.149   -0.031      0.000    0.000   \n",
       "1|subject[HMN005]     0.033  0.031  -0.025    0.092      0.000    0.000   \n",
       "1|subject[HMN006]     0.030  0.033  -0.033    0.090      0.000    0.000   \n",
       "1|subject[HMN007]    -0.012  0.031  -0.071    0.047      0.000    0.000   \n",
       "1|subject[HMN008]    -0.129  0.033  -0.190   -0.067      0.000    0.000   \n",
       "1|subject[HMN011]     0.002  0.032  -0.058    0.061      0.000    0.000   \n",
       "1|subject[HMN012]    -0.011  0.033  -0.072    0.050      0.000    0.000   \n",
       "1|subject[HMN013]     0.030  0.032  -0.031    0.089      0.000    0.000   \n",
       "1|subject[HMN014]     0.085  0.031   0.029    0.146      0.000    0.000   \n",
       "1|subject[HMN018]     0.019  0.032  -0.043    0.076      0.000    0.000   \n",
       "1|subject[HMN019]    -0.014  0.032  -0.073    0.047      0.000    0.000   \n",
       "1|subject[HMN020]     0.086  0.031   0.026    0.142      0.000    0.000   \n",
       "1|subject[HMN021]    -0.106  0.032  -0.165   -0.046      0.000    0.000   \n",
       "1|subject[HMN023]     0.032  0.033  -0.031    0.092      0.000    0.000   \n",
       "1|subject[HMN024]    -0.036  0.032  -0.093    0.026      0.000    0.000   \n",
       "1|subject[HMN025]    -0.029  0.032  -0.088    0.031      0.000    0.000   \n",
       "1|subject[HMN026]    -0.029  0.031  -0.087    0.031      0.000    0.000   \n",
       "1|subject[HMN027]    -0.095  0.032  -0.155   -0.034      0.000    0.000   \n",
       "1|subject[HMN028]     0.008  0.032  -0.053    0.067      0.000    0.000   \n",
       "1|subject[HMN029]     0.006  0.032  -0.054    0.067      0.000    0.000   \n",
       "1|subject[HMN030]     0.041  0.032  -0.020    0.099      0.000    0.000   \n",
       "1|subject[HMN031]     0.089  0.032   0.027    0.148      0.000    0.000   \n",
       "1|subject[HMN032]     0.037  0.032  -0.024    0.096      0.000    0.000   \n",
       "1|subject[HMN033]    -0.014  0.036  -0.082    0.051      0.001    0.000   \n",
       "1|subject[HMN035]     0.104  0.032   0.046    0.164      0.000    0.000   \n",
       "1|subject[HMN037]    -0.070  0.031  -0.127   -0.010      0.000    0.000   \n",
       "1|subject[HMN038]     0.024  0.031  -0.033    0.083      0.000    0.000   \n",
       "1|subject[HMN039]    -0.022  0.032  -0.082    0.037      0.000    0.000   \n",
       "1|subject[HMN040]    -0.030  0.034  -0.094    0.031      0.000    0.000   \n",
       "1|subject[HMN041]    -0.046  0.031  -0.105    0.012      0.000    0.000   \n",
       "1|subject[HMN042]    -0.035  0.031  -0.097    0.019      0.000    0.000   \n",
       "1|subject[HMN043]     0.018  0.032  -0.038    0.082      0.000    0.000   \n",
       "1|subject[HMN045]    -0.059  0.032  -0.120    0.002      0.000    0.000   \n",
       "1|subject[HMN048]    -0.086  0.032  -0.145   -0.027      0.000    0.000   \n",
       "1|subject[HMN049]     0.026  0.032  -0.034    0.086      0.000    0.000   \n",
       "1|subject[HMN050_2]   0.028  0.031  -0.029    0.088      0.000    0.000   \n",
       "1|subject[HMN052]     0.042  0.032  -0.016    0.105      0.000    0.000   \n",
       "1|subject[HMN053]    -0.027  0.034  -0.094    0.036      0.000    0.000   \n",
       "1|subject[HMN055]     0.028  0.032  -0.032    0.087      0.000    0.000   \n",
       "1|subject[HMN056]    -0.015  0.033  -0.076    0.046      0.000    0.000   \n",
       "1|subject[HMN057]     0.000  0.031  -0.059    0.057      0.000    0.000   \n",
       "1|subject[HMN058]     0.002  0.032  -0.060    0.060      0.000    0.000   \n",
       "1|subject[HMN060]     0.012  0.033  -0.049    0.073      0.000    0.000   \n",
       "1|subject[HMN062]    -0.070  0.031  -0.127   -0.009      0.000    0.000   \n",
       "1|subject[HMN065]     0.160  0.031   0.102    0.218      0.000    0.000   \n",
       "1|subject[HMN068]     0.066  0.031   0.008    0.125      0.000    0.000   \n",
       "1|subject[HMN069]     0.090  0.031   0.033    0.148      0.000    0.000   \n",
       "1|subject[HMN072]     0.001  0.031  -0.056    0.061      0.000    0.000   \n",
       "1|subject[HMN073]     0.095  0.032   0.034    0.156      0.000    0.000   \n",
       "1|subject[HMN074]     0.037  0.032  -0.024    0.097      0.000    0.000   \n",
       "1|subject[HMN075]     0.123  0.031   0.066    0.184      0.000    0.000   \n",
       "1|subject[HMN077]     0.051  0.031  -0.006    0.109      0.000    0.000   \n",
       "1|subject[HMN079]     0.005  0.032  -0.052    0.067      0.000    0.000   \n",
       "1|subject[HMN080_W2]  0.030  0.032  -0.027    0.092      0.000    0.000   \n",
       "1|subject[HMN081]     0.006  0.033  -0.058    0.068      0.000    0.000   \n",
       "1|subject[HMN082]    -0.002  0.038  -0.077    0.065      0.001    0.000   \n",
       "1|subject[HMN083_W2] -0.038  0.032  -0.096    0.024      0.000    0.000   \n",
       "1|subject[HMN085]    -0.073  0.033  -0.133   -0.009      0.000    0.000   \n",
       "1|subject[HMN086]     0.033  0.031  -0.023    0.095      0.000    0.000   \n",
       "1|subject[HMN087]    -0.018  0.032  -0.079    0.042      0.000    0.000   \n",
       "1|subject[HMN088]    -0.077  0.032  -0.139   -0.017      0.000    0.000   \n",
       "1|subject[HMN090]    -0.091  0.032  -0.153   -0.033      0.000    0.000   \n",
       "1|subject[HMN092]    -0.013  0.034  -0.077    0.050      0.000    0.000   \n",
       "1|subject[HMN095]    -0.071  0.032  -0.131   -0.013      0.000    0.000   \n",
       "1|subject[HMN096]     0.013  0.032  -0.048    0.072      0.000    0.000   \n",
       "1|subject[HMN099]    -0.134  0.032  -0.195   -0.076      0.000    0.000   \n",
       "1|subject[HMN101]     0.010  0.032  -0.049    0.073      0.000    0.000   \n",
       "1|subject[HMN102]     0.190  0.035   0.125    0.255      0.000    0.000   \n",
       "1|subject[HMN103]    -0.053  0.032  -0.110    0.008      0.000    0.000   \n",
       "1|subject[HMN104]     0.021  0.032  -0.040    0.077      0.000    0.000   \n",
       "1|subject[HMN105]    -0.003  0.031  -0.060    0.055      0.000    0.000   \n",
       "1|subject[HMN108]     0.000  0.031  -0.058    0.058      0.000    0.000   \n",
       "1|subject[HMN109]     0.096  0.032   0.036    0.157      0.000    0.000   \n",
       "1|subject[HMN110]    -0.116  0.032  -0.177   -0.058      0.000    0.000   \n",
       "1|subject[HMN111]    -0.172  0.033  -0.237   -0.112      0.000    0.000   \n",
       "1|subject[HMN113]    -0.042  0.032  -0.103    0.019      0.000    0.000   \n",
       "1|subject[HMN114]    -0.080  0.031  -0.138   -0.020      0.000    0.000   \n",
       "1|subject[HMN115]     0.042  0.031  -0.015    0.099      0.000    0.000   \n",
       "1|subject[HMN116]    -0.043  0.031  -0.101    0.016      0.000    0.000   \n",
       "1|subject[HMN117]    -0.080  0.033  -0.144   -0.019      0.000    0.000   \n",
       "1|subject[HMN118]     0.037  0.032  -0.023    0.097      0.000    0.000   \n",
       "1|subject[HMN119]    -0.059  0.032  -0.120   -0.001      0.000    0.000   \n",
       "1|subject[HMN120]     0.060  0.032  -0.001    0.117      0.000    0.000   \n",
       "1|subject[HMN121]     0.035  0.032  -0.024    0.094      0.000    0.000   \n",
       "1|subject[HMN122]    -0.050  0.032  -0.111    0.010      0.000    0.000   \n",
       "1|subject[HMN123]    -0.143  0.031  -0.204   -0.086      0.000    0.000   \n",
       "1|subject[HMN124]    -0.009  0.031  -0.068    0.050      0.000    0.000   \n",
       "1|subject[HMN125_W2] -0.137  0.032  -0.194   -0.074      0.000    0.000   \n",
       "1|subject[HMN126]     0.041  0.033  -0.023    0.102      0.000    0.000   \n",
       "1|subject[HMN127]    -0.028  0.031  -0.088    0.030      0.000    0.000   \n",
       "1|subject[HMN129_W2] -0.080  0.033  -0.143   -0.022      0.000    0.000   \n",
       "1|subject[HMN130]     0.030  0.032  -0.033    0.086      0.000    0.000   \n",
       "1|subject[HMN134]     0.018  0.033  -0.043    0.081      0.000    0.000   \n",
       "1|subject[HMN136]    -0.029  0.031  -0.087    0.030      0.000    0.000   \n",
       "1|subject[HMN138]     0.062  0.031   0.002    0.119      0.000    0.000   \n",
       "1|subject[HMN140]     0.065  0.032   0.007    0.127      0.000    0.000   \n",
       "1|subject[HMN143]    -0.005  0.032  -0.065    0.054      0.000    0.000   \n",
       "1|subject[HMN144]    -0.116  0.031  -0.175   -0.056      0.000    0.000   \n",
       "1|subject[HMN161_W2]  0.181  0.033   0.121    0.241      0.000    0.000   \n",
       "1|subject[HMN167]     0.107  0.031   0.049    0.166      0.000    0.000   \n",
       "1|subject[HMN169]    -0.010  0.032  -0.068    0.051      0.000    0.000   \n",
       "1|subject[HMN172]    -0.008  0.031  -0.068    0.048      0.000    0.000   \n",
       "1|subject[HMN174]    -0.023  0.031  -0.078    0.037      0.000    0.000   \n",
       "1|subject[HMN175]     0.116  0.032   0.054    0.175      0.000    0.000   \n",
       "1|subject[HMN178]    -0.058  0.031  -0.114    0.004      0.000    0.000   \n",
       "1|subject[HMN180]     0.056  0.031  -0.002    0.114      0.000    0.000   \n",
       "1|subject[HMN182]    -0.060  0.032  -0.118    0.001      0.000    0.000   \n",
       "1|subject[HMN183]     0.041  0.031  -0.020    0.098      0.000    0.000   \n",
       "1|subject[HMN184]     0.083  0.031   0.026    0.141      0.000    0.000   \n",
       "1|subject[HMN186]    -0.055  0.032  -0.114    0.003      0.000    0.000   \n",
       "1|subject[HMN187]    -0.112  0.032  -0.174   -0.054      0.000    0.000   \n",
       "1|subject[HMN188]     0.157  0.031   0.097    0.215      0.000    0.000   \n",
       "1|subject[HMN189]     0.101  0.031   0.043    0.162      0.000    0.000   \n",
       "1|subject[HMN190]    -0.015  0.032  -0.073    0.045      0.000    0.000   \n",
       "1|subject[HMN191]    -0.097  0.031  -0.156   -0.038      0.000    0.000   \n",
       "1|subject[HMN193]    -0.066  0.036  -0.131    0.004      0.001    0.000   \n",
       "1|subject[HMN194]    -0.062  0.032  -0.119   -0.001      0.000    0.000   \n",
       "1|subject[HMN196]     0.035  0.032  -0.023    0.096      0.000    0.000   \n",
       "1|subject[HMN197]    -0.011  0.031  -0.069    0.048      0.000    0.000   \n",
       "1|subject[HMN199]     0.041  0.032  -0.018    0.102      0.000    0.000   \n",
       "1|subject[HMN201]     0.125  0.031   0.064    0.182      0.000    0.000   \n",
       "1|ROI[ACC]           -0.029  0.058  -0.142    0.080      0.001    0.001   \n",
       "1|ROI[LAmy/Hippo]     0.017  0.057  -0.087    0.137      0.001    0.001   \n",
       "1|ROI[LCing]         -0.041  0.063  -0.169    0.071      0.001    0.001   \n",
       "1|ROI[LIFG]          -0.019  0.057  -0.131    0.088      0.001    0.001   \n",
       "1|ROI[LIPL]          -0.025  0.059  -0.140    0.088      0.001    0.001   \n",
       "1|ROI[LMTG]           0.038  0.060  -0.069    0.159      0.001    0.001   \n",
       "1|ROI[LSFG]          -0.030  0.058  -0.144    0.076      0.001    0.001   \n",
       "1|ROI[LTPJ]           0.023  0.058  -0.087    0.135      0.001    0.001   \n",
       "1|ROI[LaMTS/aMTG]    -0.041  0.063  -0.171    0.068      0.001    0.001   \n",
       "1|ROI[LvBG]          -0.012  0.056  -0.126    0.093      0.001    0.001   \n",
       "1|ROI[PCC]           -0.025  0.057  -0.140    0.079      0.001    0.001   \n",
       "1|ROI[RAmy/Hippo]     0.020  0.059  -0.091    0.137      0.001    0.001   \n",
       "1|ROI[RIFG_BA45]      0.017  0.056  -0.087    0.134      0.001    0.001   \n",
       "1|ROI[RIFG_BA9]       0.008  0.058  -0.105    0.118      0.001    0.001   \n",
       "1|ROI[RIns]           0.026  0.059  -0.081    0.144      0.001    0.001   \n",
       "1|ROI[RPCC]           0.004  0.059  -0.106    0.124      0.001    0.001   \n",
       "1|ROI[RTPJp]          0.164  0.106  -0.015    0.344      0.002    0.002   \n",
       "1|ROI[RvBG]          -0.001  0.057  -0.114    0.106      0.001    0.001   \n",
       "1|ROI[SGC]           -0.030  0.059  -0.145    0.079      0.001    0.001   \n",
       "1|ROI[dmMPFC]        -0.026  0.058  -0.144    0.074      0.001    0.001   \n",
       "1|ROI[vmPFC]         -0.039  0.059  -0.160    0.064      0.001    0.001   \n",
       "x|ROI[ACC]           -0.005  0.004  -0.012    0.002      0.000    0.000   \n",
       "x|ROI[LAmy/Hippo]    -0.005  0.004  -0.012    0.002      0.000    0.000   \n",
       "x|ROI[LCing]         -0.010  0.004  -0.018   -0.002      0.000    0.000   \n",
       "x|ROI[LIFG]          -0.007  0.004  -0.013    0.001      0.000    0.000   \n",
       "x|ROI[LIPL]           0.006  0.004  -0.001    0.013      0.000    0.000   \n",
       "x|ROI[LMTG]          -0.002  0.004  -0.009    0.006      0.000    0.000   \n",
       "x|ROI[LSFG]          -0.000  0.004  -0.007    0.007      0.000    0.000   \n",
       "x|ROI[LTPJ]           0.008  0.004   0.001    0.016      0.000    0.000   \n",
       "x|ROI[LaMTS/aMTG]     0.005  0.004  -0.002    0.013      0.000    0.000   \n",
       "x|ROI[LvBG]          -0.004  0.004  -0.012    0.003      0.000    0.000   \n",
       "x|ROI[PCC]            0.004  0.004  -0.003    0.011      0.000    0.000   \n",
       "x|ROI[RAmy/Hippo]    -0.004  0.004  -0.012    0.003      0.000    0.000   \n",
       "x|ROI[RIFG_BA45]     -0.006  0.004  -0.013    0.001      0.000    0.000   \n",
       "x|ROI[RIFG_BA9]      -0.004  0.004  -0.011    0.003      0.000    0.000   \n",
       "x|ROI[RIns]          -0.004  0.004  -0.011    0.004      0.000    0.000   \n",
       "x|ROI[RPCC]           0.011  0.004   0.004    0.018      0.000    0.000   \n",
       "x|ROI[RTPJp]          0.021  0.006   0.010    0.033      0.000    0.000   \n",
       "x|ROI[RvBG]          -0.003  0.004  -0.011    0.004      0.000    0.000   \n",
       "x|ROI[SGC]           -0.004  0.004  -0.011    0.003      0.000    0.000   \n",
       "x|ROI[dmMPFC]         0.002  0.004  -0.005    0.009      0.000    0.000   \n",
       "x|ROI[vmPFC]          0.001  0.004  -0.006    0.009      0.000    0.000   \n",
       "\n",
       "                      ess_bulk  ess_tail  r_hat  \n",
       "Intercept               2181.0    3719.0    1.0  \n",
       "x                       2048.0    3666.0    1.0  \n",
       "1|subject_sigma         2530.0    2534.0    1.0  \n",
       "1|ROI_sigma             1555.0    1713.0    1.0  \n",
       "x|ROI_sigma             2798.0    4273.0    1.0  \n",
       "y_sigma                10357.0    6009.0    1.0  \n",
       "1|subject[HMN001]      11657.0    5775.0    1.0  \n",
       "1|subject[HMN002]      11060.0    5647.0    1.0  \n",
       "1|subject[HMN003]      10508.0    5744.0    1.0  \n",
       "1|subject[HMN004]       8628.0    5920.0    1.0  \n",
       "1|subject[HMN005]      10868.0    5935.0    1.0  \n",
       "1|subject[HMN006]       7277.0    6279.0    1.0  \n",
       "1|subject[HMN007]      10842.0    5775.0    1.0  \n",
       "1|subject[HMN008]       7853.0    5653.0    1.0  \n",
       "1|subject[HMN011]      10048.0    5906.0    1.0  \n",
       "1|subject[HMN012]       8405.0    5899.0    1.0  \n",
       "1|subject[HMN013]       7203.0    5299.0    1.0  \n",
       "1|subject[HMN014]      11209.0    6009.0    1.0  \n",
       "1|subject[HMN018]      10206.0    6141.0    1.0  \n",
       "1|subject[HMN019]       8100.0    5307.0    1.0  \n",
       "1|subject[HMN020]       9727.0    6453.0    1.0  \n",
       "1|subject[HMN021]      10342.0    5898.0    1.0  \n",
       "1|subject[HMN023]       8321.0    5579.0    1.0  \n",
       "1|subject[HMN024]       8782.0    5075.0    1.0  \n",
       "1|subject[HMN025]       8007.0    5869.0    1.0  \n",
       "1|subject[HMN026]       9235.0    5848.0    1.0  \n",
       "1|subject[HMN027]       8369.0    5639.0    1.0  \n",
       "1|subject[HMN028]      10084.0    5787.0    1.0  \n",
       "1|subject[HMN029]       7946.0    6108.0    1.0  \n",
       "1|subject[HMN030]       9632.0    6213.0    1.0  \n",
       "1|subject[HMN031]      10484.0    5314.0    1.0  \n",
       "1|subject[HMN032]       8882.0    5580.0    1.0  \n",
       "1|subject[HMN033]       4922.0    5752.0    1.0  \n",
       "1|subject[HMN035]       9143.0    5871.0    1.0  \n",
       "1|subject[HMN037]      10149.0    5960.0    1.0  \n",
       "1|subject[HMN038]      10430.0    6034.0    1.0  \n",
       "1|subject[HMN039]      11153.0    5394.0    1.0  \n",
       "1|subject[HMN040]       7325.0    6155.0    1.0  \n",
       "1|subject[HMN041]      10178.0    5515.0    1.0  \n",
       "1|subject[HMN042]       9431.0    5814.0    1.0  \n",
       "1|subject[HMN043]      11478.0    5919.0    1.0  \n",
       "1|subject[HMN045]       7747.0    5851.0    1.0  \n",
       "1|subject[HMN048]       9801.0    5933.0    1.0  \n",
       "1|subject[HMN049]      11033.0    6136.0    1.0  \n",
       "1|subject[HMN050_2]     8726.0    5388.0    1.0  \n",
       "1|subject[HMN052]       9575.0    5563.0    1.0  \n",
       "1|subject[HMN053]       5743.0    5662.0    1.0  \n",
       "1|subject[HMN055]       9629.0    5603.0    1.0  \n",
       "1|subject[HMN056]       7725.0    5482.0    1.0  \n",
       "1|subject[HMN057]      10108.0    5424.0    1.0  \n",
       "1|subject[HMN058]       8541.0    5803.0    1.0  \n",
       "1|subject[HMN060]       7838.0    5601.0    1.0  \n",
       "1|subject[HMN062]       8934.0    5830.0    1.0  \n",
       "1|subject[HMN065]       9674.0    6067.0    1.0  \n",
       "1|subject[HMN068]       8914.0    6198.0    1.0  \n",
       "1|subject[HMN069]      10172.0    5776.0    1.0  \n",
       "1|subject[HMN072]       9712.0    6049.0    1.0  \n",
       "1|subject[HMN073]      10223.0    5453.0    1.0  \n",
       "1|subject[HMN074]       9874.0    5660.0    1.0  \n",
       "1|subject[HMN075]       8674.0    4821.0    1.0  \n",
       "1|subject[HMN077]       9378.0    5708.0    1.0  \n",
       "1|subject[HMN079]       9598.0    5678.0    1.0  \n",
       "1|subject[HMN080_W2]    9764.0    6116.0    1.0  \n",
       "1|subject[HMN081]       7413.0    5839.0    1.0  \n",
       "1|subject[HMN082]       4013.0    5347.0    1.0  \n",
       "1|subject[HMN083_W2]    9497.0    5720.0    1.0  \n",
       "1|subject[HMN085]       7482.0    5710.0    1.0  \n",
       "1|subject[HMN086]      10677.0    5979.0    1.0  \n",
       "1|subject[HMN087]       7959.0    5780.0    1.0  \n",
       "1|subject[HMN088]       8166.0    5395.0    1.0  \n",
       "1|subject[HMN090]       6739.0    6046.0    1.0  \n",
       "1|subject[HMN092]       6375.0    5254.0    1.0  \n",
       "1|subject[HMN095]       9302.0    5524.0    1.0  \n",
       "1|subject[HMN096]      10587.0    5721.0    1.0  \n",
       "1|subject[HMN099]      10034.0    5460.0    1.0  \n",
       "1|subject[HMN101]       8022.0    6196.0    1.0  \n",
       "1|subject[HMN102]       6116.0    5609.0    1.0  \n",
       "1|subject[HMN103]      10335.0    5544.0    1.0  \n",
       "1|subject[HMN104]      10737.0    5661.0    1.0  \n",
       "1|subject[HMN105]      10786.0    6015.0    1.0  \n",
       "1|subject[HMN108]       9626.0    6031.0    1.0  \n",
       "1|subject[HMN109]       8259.0    6260.0    1.0  \n",
       "1|subject[HMN110]      10445.0    5880.0    1.0  \n",
       "1|subject[HMN111]       7908.0    6140.0    1.0  \n",
       "1|subject[HMN113]       8035.0    5258.0    1.0  \n",
       "1|subject[HMN114]       9348.0    5884.0    1.0  \n",
       "1|subject[HMN115]      10367.0    6159.0    1.0  \n",
       "1|subject[HMN116]       9815.0    5844.0    1.0  \n",
       "1|subject[HMN117]       9674.0    5630.0    1.0  \n",
       "1|subject[HMN118]       8703.0    5523.0    1.0  \n",
       "1|subject[HMN119]       9540.0    5382.0    1.0  \n",
       "1|subject[HMN120]       9802.0    5533.0    1.0  \n",
       "1|subject[HMN121]       9631.0    5918.0    1.0  \n",
       "1|subject[HMN122]       9662.0    5444.0    1.0  \n",
       "1|subject[HMN123]      11092.0    6327.0    1.0  \n",
       "1|subject[HMN124]       9710.0    5436.0    1.0  \n",
       "1|subject[HMN125_W2]    9331.0    5541.0    1.0  \n",
       "1|subject[HMN126]       6445.0    6187.0    1.0  \n",
       "1|subject[HMN127]      10651.0    5432.0    1.0  \n",
       "1|subject[HMN129_W2]    8719.0    6096.0    1.0  \n",
       "1|subject[HMN130]       9748.0    6054.0    1.0  \n",
       "1|subject[HMN134]       6049.0    5663.0    1.0  \n",
       "1|subject[HMN136]      10662.0    5231.0    1.0  \n",
       "1|subject[HMN138]      10687.0    6367.0    1.0  \n",
       "1|subject[HMN140]       7418.0    5820.0    1.0  \n",
       "1|subject[HMN143]       8531.0    5668.0    1.0  \n",
       "1|subject[HMN144]       9795.0    5013.0    1.0  \n",
       "1|subject[HMN161_W2]   10389.0    5567.0    1.0  \n",
       "1|subject[HMN167]      10606.0    5448.0    1.0  \n",
       "1|subject[HMN169]      10816.0    5724.0    1.0  \n",
       "1|subject[HMN172]      10120.0    6046.0    1.0  \n",
       "1|subject[HMN174]       9851.0    5945.0    1.0  \n",
       "1|subject[HMN175]       8207.0    5808.0    1.0  \n",
       "1|subject[HMN178]       8783.0    5822.0    1.0  \n",
       "1|subject[HMN180]      10509.0    6410.0    1.0  \n",
       "1|subject[HMN182]       9609.0    5743.0    1.0  \n",
       "1|subject[HMN183]       9942.0    5356.0    1.0  \n",
       "1|subject[HMN184]      10059.0    6261.0    1.0  \n",
       "1|subject[HMN186]      11139.0    5314.0    1.0  \n",
       "1|subject[HMN187]       7598.0    5952.0    1.0  \n",
       "1|subject[HMN188]      10535.0    5882.0    1.0  \n",
       "1|subject[HMN189]      10239.0    5554.0    1.0  \n",
       "1|subject[HMN190]       9997.0    5794.0    1.0  \n",
       "1|subject[HMN191]       9577.0    6010.0    1.0  \n",
       "1|subject[HMN193]       4950.0    5637.0    1.0  \n",
       "1|subject[HMN194]       8457.0    6114.0    1.0  \n",
       "1|subject[HMN196]       8004.0    6317.0    1.0  \n",
       "1|subject[HMN197]       9265.0    6011.0    1.0  \n",
       "1|subject[HMN199]       9262.0    5816.0    1.0  \n",
       "1|subject[HMN201]      10147.0    5905.0    1.0  \n",
       "1|ROI[ACC]              5842.0    5011.0    1.0  \n",
       "1|ROI[LAmy/Hippo]       6830.0    5328.0    1.0  \n",
       "1|ROI[LCing]            4893.0    5058.0    1.0  \n",
       "1|ROI[LIFG]             6835.0    5060.0    1.0  \n",
       "1|ROI[LIPL]             6256.0    5324.0    1.0  \n",
       "1|ROI[LMTG]             5374.0    5515.0    1.0  \n",
       "1|ROI[LSFG]             5416.0    5174.0    1.0  \n",
       "1|ROI[LTPJ]             6228.0    5472.0    1.0  \n",
       "1|ROI[LaMTS/aMTG]       5124.0    5264.0    1.0  \n",
       "1|ROI[LvBG]             7796.0    5292.0    1.0  \n",
       "1|ROI[PCC]              5799.0    5485.0    1.0  \n",
       "1|ROI[RAmy/Hippo]       6577.0    4526.0    1.0  \n",
       "1|ROI[RIFG_BA45]        7111.0    4861.0    1.0  \n",
       "1|ROI[RIFG_BA9]         6830.0    5378.0    1.0  \n",
       "1|ROI[RIns]             5350.0    4938.0    1.0  \n",
       "1|ROI[RPCC]             7058.0    4489.0    1.0  \n",
       "1|ROI[RTPJp]            1934.0    2133.0    1.0  \n",
       "1|ROI[RvBG]             7444.0    5805.0    1.0  \n",
       "1|ROI[SGC]              6205.0    5305.0    1.0  \n",
       "1|ROI[dmMPFC]           6390.0    4741.0    1.0  \n",
       "1|ROI[vmPFC]            5795.0    5907.0    1.0  \n",
       "x|ROI[ACC]              4120.0    4736.0    1.0  \n",
       "x|ROI[LAmy/Hippo]       4140.0    4748.0    1.0  \n",
       "x|ROI[LCing]            3904.0    4630.0    1.0  \n",
       "x|ROI[LIFG]             4570.0    4805.0    1.0  \n",
       "x|ROI[LIPL]             4062.0    5080.0    1.0  \n",
       "x|ROI[LMTG]             3622.0    4757.0    1.0  \n",
       "x|ROI[LSFG]             3967.0    5143.0    1.0  \n",
       "x|ROI[LTPJ]             3929.0    4655.0    1.0  \n",
       "x|ROI[LaMTS/aMTG]       4076.0    5375.0    1.0  \n",
       "x|ROI[LvBG]             4815.0    5204.0    1.0  \n",
       "x|ROI[PCC]              3656.0    4894.0    1.0  \n",
       "x|ROI[RAmy/Hippo]       4306.0    4706.0    1.0  \n",
       "x|ROI[RIFG_BA45]        4538.0    4896.0    1.0  \n",
       "x|ROI[RIFG_BA9]         4114.0    4971.0    1.0  \n",
       "x|ROI[RIns]             3823.0    4406.0    1.0  \n",
       "x|ROI[RPCC]             4641.0    5392.0    1.0  \n",
       "x|ROI[RTPJp]            2066.0    2872.0    1.0  \n",
       "x|ROI[RvBG]             4444.0    4401.0    1.0  \n",
       "x|ROI[SGC]              4117.0    4764.0    1.0  \n",
       "x|ROI[dmMPFC]           4182.0    5443.0    1.0  \n",
       "x|ROI[vmPFC]            3939.0    5329.0    1.0  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "az.summary(results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5c5d3dd8-8a64-41ee-ac93-55466c4bcf48",
   "metadata": {},
   "outputs": [],
   "source": [
    "_ = az.plot_trace(results, figsize=(20, 35))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "287d3915-e341-4d25-a46c-340be1a7c637",
   "metadata": {},
   "outputs": [],
   "source": [
    "sample_frame = results[\"posterior\"][\"x|ROI\"].stack(y=[\"draw\", \"chain\"]).to_pandas().transpose()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "7336a811-b3ac-44d3-836f-4f89d2af5a6e",
   "metadata": {},
   "outputs": [],
   "source": [
    "sample_frame.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "746b45e0-0607-41cd-b3aa-ff8e0ecc13a8",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>ROI__factor_dim</th>\n",
       "      <th>draw</th>\n",
       "      <th>chain</th>\n",
       "      <th>ACC</th>\n",
       "      <th>LAmy/Hippo</th>\n",
       "      <th>LCing</th>\n",
       "      <th>LIFG</th>\n",
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       "      <th>LMTG</th>\n",
       "      <th>LSFG</th>\n",
       "      <th>LTPJ</th>\n",
       "      <th>...</th>\n",
       "      <th>RAmy/Hippo</th>\n",
       "      <th>RIFG_BA45</th>\n",
       "      <th>RIFG_BA9</th>\n",
       "      <th>RIns</th>\n",
       "      <th>RPCC</th>\n",
       "      <th>RTPJp</th>\n",
       "      <th>RvBG</th>\n",
       "      <th>SGC</th>\n",
       "      <th>dmMPFC</th>\n",
       "      <th>vmPFC</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "      <td>-0.008134</td>\n",
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       "      <td>0.003603</td>\n",
       "      <td>-0.001939</td>\n",
       "      <td>-0.004810</td>\n",
       "      <td>0.006834</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.004187</td>\n",
       "      <td>-0.005564</td>\n",
       "      <td>-0.003937</td>\n",
       "      <td>-0.007552</td>\n",
       "      <td>0.010234</td>\n",
       "      <td>0.031353</td>\n",
       "      <td>-0.006321</td>\n",
       "      <td>-0.007327</td>\n",
       "      <td>-0.000511</td>\n",
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       "      <th>1</th>\n",
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       "      <td>1</td>\n",
       "      <td>-0.002013</td>\n",
       "      <td>-0.003709</td>\n",
       "      <td>-0.002448</td>\n",
       "      <td>-0.001720</td>\n",
       "      <td>0.005571</td>\n",
       "      <td>-0.005693</td>\n",
       "      <td>-0.000702</td>\n",
       "      <td>0.013438</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.003605</td>\n",
       "      <td>-0.002402</td>\n",
       "      <td>0.000092</td>\n",
       "      <td>-0.003852</td>\n",
       "      <td>0.013609</td>\n",
       "      <td>0.011907</td>\n",
       "      <td>0.001897</td>\n",
       "      <td>-0.004217</td>\n",
       "      <td>0.001925</td>\n",
       "      <td>0.003396</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>-0.006694</td>\n",
       "      <td>0.002950</td>\n",
       "      <td>-0.003497</td>\n",
       "      <td>-0.001823</td>\n",
       "      <td>0.011083</td>\n",
       "      <td>-0.000167</td>\n",
       "      <td>0.001206</td>\n",
       "      <td>0.011488</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.007433</td>\n",
       "      <td>-0.006098</td>\n",
       "      <td>-0.012347</td>\n",
       "      <td>-0.011778</td>\n",
       "      <td>0.010089</td>\n",
       "      <td>0.011941</td>\n",
       "      <td>-0.009018</td>\n",
       "      <td>0.003037</td>\n",
       "      <td>0.003127</td>\n",
       "      <td>-0.003641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>-0.000876</td>\n",
       "      <td>-0.003906</td>\n",
       "      <td>-0.004926</td>\n",
       "      <td>-0.010739</td>\n",
       "      <td>0.000019</td>\n",
       "      <td>-0.010054</td>\n",
       "      <td>-0.002554</td>\n",
       "      <td>0.006410</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.005483</td>\n",
       "      <td>-0.005760</td>\n",
       "      <td>-0.005541</td>\n",
       "      <td>-0.003116</td>\n",
       "      <td>0.006522</td>\n",
       "      <td>0.014354</td>\n",
       "      <td>-0.003270</td>\n",
       "      <td>-0.000937</td>\n",
       "      <td>-0.000358</td>\n",
       "      <td>0.003343</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>-0.005583</td>\n",
       "      <td>-0.008253</td>\n",
       "      <td>-0.010550</td>\n",
       "      <td>0.000068</td>\n",
       "      <td>-0.001252</td>\n",
       "      <td>-0.001652</td>\n",
       "      <td>-0.001108</td>\n",
       "      <td>0.009022</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.008035</td>\n",
       "      <td>-0.005116</td>\n",
       "      <td>-0.006883</td>\n",
       "      <td>-0.008417</td>\n",
       "      <td>0.011356</td>\n",
       "      <td>0.020262</td>\n",
       "      <td>-0.004668</td>\n",
       "      <td>-0.002549</td>\n",
       "      <td>0.000760</td>\n",
       "      <td>0.003656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15995</th>\n",
       "      <td>999</td>\n",
       "      <td>11</td>\n",
       "      <td>-0.007034</td>\n",
       "      <td>-0.004224</td>\n",
       "      <td>-0.014528</td>\n",
       "      <td>-0.009185</td>\n",
       "      <td>0.002745</td>\n",
       "      <td>-0.000273</td>\n",
       "      <td>-0.004441</td>\n",
       "      <td>0.007418</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.004063</td>\n",
       "      <td>-0.007413</td>\n",
       "      <td>-0.005800</td>\n",
       "      <td>-0.004469</td>\n",
       "      <td>0.010120</td>\n",
       "      <td>0.029713</td>\n",
       "      <td>-0.003989</td>\n",
       "      <td>-0.006888</td>\n",
       "      <td>-0.000503</td>\n",
       "      <td>-0.002218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15996</th>\n",
       "      <td>999</td>\n",
       "      <td>12</td>\n",
       "      <td>-0.002164</td>\n",
       "      <td>-0.005878</td>\n",
       "      <td>-0.003454</td>\n",
       "      <td>-0.004217</td>\n",
       "      <td>0.006823</td>\n",
       "      <td>0.004227</td>\n",
       "      <td>0.007275</td>\n",
       "      <td>0.006520</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.003074</td>\n",
       "      <td>-0.003785</td>\n",
       "      <td>-0.008335</td>\n",
       "      <td>-0.004459</td>\n",
       "      <td>0.010221</td>\n",
       "      <td>0.017118</td>\n",
       "      <td>-0.005651</td>\n",
       "      <td>-0.000691</td>\n",
       "      <td>0.001324</td>\n",
       "      <td>0.001231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15997</th>\n",
       "      <td>999</td>\n",
       "      <td>13</td>\n",
       "      <td>-0.001947</td>\n",
       "      <td>-0.002335</td>\n",
       "      <td>-0.008087</td>\n",
       "      <td>-0.002408</td>\n",
       "      <td>0.010143</td>\n",
       "      <td>0.001916</td>\n",
       "      <td>0.002659</td>\n",
       "      <td>0.012860</td>\n",
       "      <td>...</td>\n",
       "      <td>0.002791</td>\n",
       "      <td>-0.000150</td>\n",
       "      <td>-0.000390</td>\n",
       "      <td>0.005769</td>\n",
       "      <td>0.017976</td>\n",
       "      <td>0.031910</td>\n",
       "      <td>0.004032</td>\n",
       "      <td>0.000773</td>\n",
       "      <td>0.005465</td>\n",
       "      <td>0.003096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15998</th>\n",
       "      <td>999</td>\n",
       "      <td>14</td>\n",
       "      <td>-0.004338</td>\n",
       "      <td>-0.008323</td>\n",
       "      <td>-0.012995</td>\n",
       "      <td>-0.009232</td>\n",
       "      <td>-0.001154</td>\n",
       "      <td>-0.000266</td>\n",
       "      <td>-0.005939</td>\n",
       "      <td>0.006934</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.005122</td>\n",
       "      <td>-0.006606</td>\n",
       "      <td>-0.010178</td>\n",
       "      <td>-0.003517</td>\n",
       "      <td>0.009843</td>\n",
       "      <td>0.018538</td>\n",
       "      <td>-0.006108</td>\n",
       "      <td>-0.004328</td>\n",
       "      <td>0.001868</td>\n",
       "      <td>-0.002963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15999</th>\n",
       "      <td>999</td>\n",
       "      <td>15</td>\n",
       "      <td>-0.002418</td>\n",
       "      <td>-0.000722</td>\n",
       "      <td>-0.013735</td>\n",
       "      <td>-0.010784</td>\n",
       "      <td>0.001460</td>\n",
       "      <td>-0.006558</td>\n",
       "      <td>-0.000484</td>\n",
       "      <td>0.007037</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.002431</td>\n",
       "      <td>-0.003964</td>\n",
       "      <td>-0.003008</td>\n",
       "      <td>-0.005631</td>\n",
       "      <td>0.014302</td>\n",
       "      <td>0.014802</td>\n",
       "      <td>0.001115</td>\n",
       "      <td>-0.003247</td>\n",
       "      <td>-0.000263</td>\n",
       "      <td>-0.004179</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16000 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "ROI__factor_dim  draw  chain       ACC  LAmy/Hippo     LCing      LIFG  \\\n",
       "0                   0      0 -0.010695   -0.008134 -0.014992 -0.009796   \n",
       "1                   0      1 -0.002013   -0.003709 -0.002448 -0.001720   \n",
       "2                   0      2 -0.006694    0.002950 -0.003497 -0.001823   \n",
       "3                   0      3 -0.000876   -0.003906 -0.004926 -0.010739   \n",
       "4                   0      4 -0.005583   -0.008253 -0.010550  0.000068   \n",
       "...               ...    ...       ...         ...       ...       ...   \n",
       "15995             999     11 -0.007034   -0.004224 -0.014528 -0.009185   \n",
       "15996             999     12 -0.002164   -0.005878 -0.003454 -0.004217   \n",
       "15997             999     13 -0.001947   -0.002335 -0.008087 -0.002408   \n",
       "15998             999     14 -0.004338   -0.008323 -0.012995 -0.009232   \n",
       "15999             999     15 -0.002418   -0.000722 -0.013735 -0.010784   \n",
       "\n",
       "ROI__factor_dim      LIPL      LMTG      LSFG      LTPJ  ...  RAmy/Hippo  \\\n",
       "0                0.003603 -0.001939 -0.004810  0.006834  ...   -0.004187   \n",
       "1                0.005571 -0.005693 -0.000702  0.013438  ...   -0.003605   \n",
       "2                0.011083 -0.000167  0.001206  0.011488  ...   -0.007433   \n",
       "3                0.000019 -0.010054 -0.002554  0.006410  ...   -0.005483   \n",
       "4               -0.001252 -0.001652 -0.001108  0.009022  ...   -0.008035   \n",
       "...                   ...       ...       ...       ...  ...         ...   \n",
       "15995            0.002745 -0.000273 -0.004441  0.007418  ...   -0.004063   \n",
       "15996            0.006823  0.004227  0.007275  0.006520  ...   -0.003074   \n",
       "15997            0.010143  0.001916  0.002659  0.012860  ...    0.002791   \n",
       "15998           -0.001154 -0.000266 -0.005939  0.006934  ...   -0.005122   \n",
       "15999            0.001460 -0.006558 -0.000484  0.007037  ...   -0.002431   \n",
       "\n",
       "ROI__factor_dim  RIFG_BA45  RIFG_BA9      RIns      RPCC     RTPJp      RvBG  \\\n",
       "0                -0.005564 -0.003937 -0.007552  0.010234  0.031353 -0.006321   \n",
       "1                -0.002402  0.000092 -0.003852  0.013609  0.011907  0.001897   \n",
       "2                -0.006098 -0.012347 -0.011778  0.010089  0.011941 -0.009018   \n",
       "3                -0.005760 -0.005541 -0.003116  0.006522  0.014354 -0.003270   \n",
       "4                -0.005116 -0.006883 -0.008417  0.011356  0.020262 -0.004668   \n",
       "...                    ...       ...       ...       ...       ...       ...   \n",
       "15995            -0.007413 -0.005800 -0.004469  0.010120  0.029713 -0.003989   \n",
       "15996            -0.003785 -0.008335 -0.004459  0.010221  0.017118 -0.005651   \n",
       "15997            -0.000150 -0.000390  0.005769  0.017976  0.031910  0.004032   \n",
       "15998            -0.006606 -0.010178 -0.003517  0.009843  0.018538 -0.006108   \n",
       "15999            -0.003964 -0.003008 -0.005631  0.014302  0.014802  0.001115   \n",
       "\n",
       "ROI__factor_dim       SGC    dmMPFC     vmPFC  \n",
       "0               -0.007327 -0.000511 -0.003715  \n",
       "1               -0.004217  0.001925  0.003396  \n",
       "2                0.003037  0.003127 -0.003641  \n",
       "3               -0.000937 -0.000358  0.003343  \n",
       "4               -0.002549  0.000760  0.003656  \n",
       "...                   ...       ...       ...  \n",
       "15995           -0.006888 -0.000503 -0.002218  \n",
       "15996           -0.000691  0.001324  0.001231  \n",
       "15997            0.000773  0.005465  0.003096  \n",
       "15998           -0.004328  0.001868 -0.002963  \n",
       "15999           -0.003247 -0.000263 -0.004179  \n",
       "\n",
       "[16000 rows x 23 columns]"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sample_frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "ba9f34c6-0c31-44ba-9491-94076985c8eb",
   "metadata": {},
   "outputs": [],
   "source": [
    "melt_frame = sample_frame.melt(id_vars=[\"draw\", \"chain\"]).rename(columns=dict(ROI__factor_dim=\"ROI\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "id": "cb2bf1d7-9a77-4c30-a78e-2b16e3e2c92b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>draw</th>\n",
       "      <th>chain</th>\n",
       "      <th>ROI</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>ACC</td>\n",
       "      <td>-0.010695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>ACC</td>\n",
       "      <td>-0.002013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>ACC</td>\n",
       "      <td>-0.006694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>ACC</td>\n",
       "      <td>-0.000876</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>ACC</td>\n",
       "      <td>-0.005583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>335995</th>\n",
       "      <td>999</td>\n",
       "      <td>11</td>\n",
       "      <td>vmPFC</td>\n",
       "      <td>-0.002218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>335996</th>\n",
       "      <td>999</td>\n",
       "      <td>12</td>\n",
       "      <td>vmPFC</td>\n",
       "      <td>0.001231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>335997</th>\n",
       "      <td>999</td>\n",
       "      <td>13</td>\n",
       "      <td>vmPFC</td>\n",
       "      <td>0.003096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>335998</th>\n",
       "      <td>999</td>\n",
       "      <td>14</td>\n",
       "      <td>vmPFC</td>\n",
       "      <td>-0.002963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>335999</th>\n",
       "      <td>999</td>\n",
       "      <td>15</td>\n",
       "      <td>vmPFC</td>\n",
       "      <td>-0.004179</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>336000 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        draw  chain    ROI     value\n",
       "0          0      0    ACC -0.010695\n",
       "1          0      1    ACC -0.002013\n",
       "2          0      2    ACC -0.006694\n",
       "3          0      3    ACC -0.000876\n",
       "4          0      4    ACC -0.005583\n",
       "...      ...    ...    ...       ...\n",
       "335995   999     11  vmPFC -0.002218\n",
       "335996   999     12  vmPFC  0.001231\n",
       "335997   999     13  vmPFC  0.003096\n",
       "335998   999     14  vmPFC -0.002963\n",
       "335999   999     15  vmPFC -0.004179\n",
       "\n",
       "[336000 rows x 4 columns]"
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "melt_frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "6e69ad28-39dd-4ffa-8f71-63a6ae5f60a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='value', ylabel='Density'>"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.kdeplot(x=\"value\", hue=\"ROI\", data=melt_frame)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "id": "3b842a78-94f9-43ac-9702-fa1e3f0c3fb4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ROI\n",
       "RTPJp         0.021336\n",
       "RPCC          0.011067\n",
       "LTPJ          0.008371\n",
       "LIPL          0.005733\n",
       "LaMTS/aMTG    0.005160\n",
       "PCC           0.003730\n",
       "dmMPFC        0.001956\n",
       "vmPFC         0.001412\n",
       "LSFG         -0.000014\n",
       "LMTG         -0.001577\n",
       "RvBG         -0.003572\n",
       "SGC          -0.003606\n",
       "RAmy/Hippo   -0.004040\n",
       "RIns         -0.004136\n",
       "LvBG         -0.004434\n",
       "RIFG_BA9     -0.004536\n",
       "LAmy/Hippo   -0.005146\n",
       "ACC          -0.005183\n",
       "RIFG_BA45    -0.006350\n",
       "LIFG         -0.006567\n",
       "LCing        -0.010202\n",
       "Name: value, dtype: float64"
      ]
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "means = melt_frame.groupby([\"ROI\"]).value.mean().sort_values(ascending=False)\n",
    "means"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "id": "a85445df-2990-4857-9408-3223c46fc32a",
   "metadata": {},
   "outputs": [],
   "source": [
    "melt_frame[\"mean\"] = np.nan\n",
    "for label, mean in means.items():\n",
    "    melt_frame.loc[melt_frame.ROI == label, \"mean\"] = mean * 1000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "id": "d8a2f482-ff50-4ef9-9270-53d26bd39a80",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>draw</th>\n",
       "      <th>chain</th>\n",
       "      <th>ROI</th>\n",
       "      <th>value</th>\n",
       "      <th>mean</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>ACC</td>\n",
       "      <td>-0.010695</td>\n",
       "      <td>-5.182582</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>ACC</td>\n",
       "      <td>-0.002013</td>\n",
       "      <td>-5.182582</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>ACC</td>\n",
       "      <td>-0.006694</td>\n",
       "      <td>-5.182582</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>ACC</td>\n",
       "      <td>-0.000876</td>\n",
       "      <td>-5.182582</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>ACC</td>\n",
       "      <td>-0.005583</td>\n",
       "      <td>-5.182582</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>335995</th>\n",
       "      <td>999</td>\n",
       "      <td>11</td>\n",
       "      <td>vmPFC</td>\n",
       "      <td>-0.002218</td>\n",
       "      <td>1.411533</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>335996</th>\n",
       "      <td>999</td>\n",
       "      <td>12</td>\n",
       "      <td>vmPFC</td>\n",
       "      <td>0.001231</td>\n",
       "      <td>1.411533</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>335997</th>\n",
       "      <td>999</td>\n",
       "      <td>13</td>\n",
       "      <td>vmPFC</td>\n",
       "      <td>0.003096</td>\n",
       "      <td>1.411533</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>335998</th>\n",
       "      <td>999</td>\n",
       "      <td>14</td>\n",
       "      <td>vmPFC</td>\n",
       "      <td>-0.002963</td>\n",
       "      <td>1.411533</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>335999</th>\n",
       "      <td>999</td>\n",
       "      <td>15</td>\n",
       "      <td>vmPFC</td>\n",
       "      <td>-0.004179</td>\n",
       "      <td>1.411533</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>336000 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        draw  chain    ROI     value      mean\n",
       "0          0      0    ACC -0.010695 -5.182582\n",
       "1          0      1    ACC -0.002013 -5.182582\n",
       "2          0      2    ACC -0.006694 -5.182582\n",
       "3          0      3    ACC -0.000876 -5.182582\n",
       "4          0      4    ACC -0.005583 -5.182582\n",
       "...      ...    ...    ...       ...       ...\n",
       "335995   999     11  vmPFC -0.002218  1.411533\n",
       "335996   999     12  vmPFC  0.001231  1.411533\n",
       "335997   999     13  vmPFC  0.003096  1.411533\n",
       "335998   999     14  vmPFC -0.002963  1.411533\n",
       "335999   999     15  vmPFC -0.004179  1.411533\n",
       "\n",
       "[336000 rows x 5 columns]"
      ]
     },
     "execution_count": 176,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "melt_frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "id": "43d3687b-2f4a-46a2-82fc-725605e270ff",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ugbiQnHMc7ovz/MkRXjw1Qv/4FNetquX29Q3csLqOdY2xyzZUiXCRHggFCJFlYGgixb7uMfb1jLO3e4wDveMc7p8g4POwoi5/a+jV9THWNVVQGy2PeyWUS4A418hkile6xtjbPcqernES6SzbO6vZsaKG7Z01XNleRaUuEZXLh4YwRC53qUyO3rEkJ4cmOTY4yaG+cfb1jHOgN/8mt7IuSntNmLbqMG/b1kZ7TVj3QpiD6kiAW9bWc8vaeiAfzg705v+tv/tyD0cH4tTHgmxqqWRDcwUr6qK0VoVoqAhSEw1QHfZrCEQuCwoQIovMOUcm58hkHelcLv81myOVyTGVyZFMZ89+TaSyTKQyJFJZ4lMZ4lMZxhJpRhJpRhNphidSDE/mPydiYipDTTRAU0WQxsoQTZUhbl5Tz/uv7aQ+FlA3+wKpjQa4YXUdN6yuA/KfJto1kuDE0CRdIwleOjXKYHyK0USa0WSaiWSWoN9DZchPVdhPTdRPXTRIXSxAbSFgVIT8RINeQv78I+DzEPB6CPo8+ec+D37vmYfh83jweQyPR/+PZfFcdAjDzB4A6hevOVA438Ain7OcLOf6F7R2C4Qj/tq2TQt1/EuRnRzFG6ma287OOedyWVwui1uaw4655LjXE6rIlrodi8IAPF485jHzeC/p//0SlRnpOZhLxsfQ77ulUPuAc+6e862YaQ7EojOzZ5xzO0rdjlJZzvWr9uVZOyzv+lW7al+qNBAnIiIiRVOAEBERkaKVY4D4TKkbUGLLuX7Vvnwt5/pV+/K05GsvuzkQIiIiUv7KsQdCREREypwChIiIiBRNAUJERESKpgAhIiIiRVOAEBERkaIpQIiIiEjRFCBERESkaAoQIiIiUjQFCBERESmaAoSIiIgUTQFCREREijZjgDCzY2Z2V+F5fNojZ2aJaa8/ZGafMLN04fWImT1uZjcW9t1pZqcWuiARERFZeEX1QDjnYmcewAngrdOWfaGw2ZcK6xuAR4Gvm5nNb7NFRESklBZsCMM5lwb+CWgG6hbqPCIiIrL4FixAmFkQ+Ahwyjk3sFDnERERkcW3EAHivWY2ApwErgHevgDnEBERkRLyLcAxv+yc+7kFOK6IiIiUCV3GKSIiIkWbbQ+E38xC015nFqIxIiIisjTMNkB895zX/22O53Nz3E9ERETKiDm3OO/pZnYv8F+cc9sW5YQiIiKyYBZlDoSZ+YB3Ac8sxvlERERkYS3EVRivYmZV5C/pfBb48EKfT0RERBbeog1hiIiIyOVDl3GKiIhI0WYawlD3hIgUbefOnQDs2rWrpO0QkUt2wQ/DXPA5ECJy+cvmHN2jCU4PJ+gZS9I9miSVyfEfvvQ8o5NpEuksOQdBn4faaIAVtRHWN1ewpbWKFXUR9IG9IkuPAoSIFO30SIJHD/bz1JEhXj49yvGhSSpDPhorQtRGA8STGbweo6kixOr6GEGfB48ZqUyOsWSaUyMJfnpsiMP9E2SyOa5bVctt6xu4bV0DHbWRUpcnIrMw0yRKDWGICAA9o0m+8fwpvvlCF92jSa5qr2JdYwWrG6K014QJ+rxnt/3oB+8F4NP3fWvG4w7Ep9jTNcae7jFePDlCbTTAPVuaefNVLWxuqVTvhEhpaQhDRIqXzTkeOtDH5584zjPHh7luZS3vuaadjc2VeDzz88ZeHwvmex/WN5BzjsN9cZ45PswvffZpIgEf77u2g3dd0059LDgv5xOR+aEAISKvcWp4kq88c4ovPX2SipCP121o5MM3riTk98688yXwmLGuqYJ1TRW8/9oO9veM89DBfv76x4fYuaGBj9y0kmtW1KhXQqQMKECICJAfSvjeKz3c//xpDvaNc9PqOj525zpW1UdL0h4zY2NLJRtbKvnQ9RkePtDPx774PBVBPz9/4wru3dZKZchfkraJiOZAiCxrRwcmeHBPDw/s7mV/zxjbOmq4flUtWzuq8XvnfpuYYuZAFCPnHK+cHmXX/j5ePj3Gbevrefu2Nm5b37DgvSMiy9QFu/sUIESWkdFEmiePDPLwgX4eOtBPIpVle2c12ztq2NJWRcA3P/eWW6gAMd1YMl/L08eGODYwyS1r63njlc3csbGRCvVMiMwXBQiR5SiTzfHciREe2t/HQwf6OTIwwYamCja3VnJlWxWdtQtzD4bFCBDTjSXSPHt8mGdPDLO3e4wbVtfx9u1t3LWpkUhAI7Uil0ABQmS56BtP8siBAX60t5dHDw3QUBHkyrYqtrRVsb6p4pKGJmZrsQPEdBNTGZ45PsxTRwc52BvntvX1vOWqVm5b30AsqDAhUiQFCJHL0WgizcHecfb2jPPiiRGePTFM//gUW9qquLKtim0d1dRGA4verlIGiOnGEml+emyI544Ps69nnKvaq3jdxkZuW9fAxuaKebsUVeQypvtAiCxlU5ksh/sm2NeTv+HSnq4xDvbGiU9l6KyN0F4TprMuwr+5dTUraiN6YyyoDPu5a1MTd21qIpHKsrt7lOdPDPO5J46RTGW5aW09t66r59qVtayqj+ryUJEiqAdCpAw45xieTNMzmsx/psRIguODkxzpj3NkYILukSTNVSE6a8O01UTorInQURuhPhYoyze9cumBuJj+8SQvnR5lf884+3rGmUpn2dhSyYamCtY0RFlZH2VlXZS2mvCiDPuIlCkNYYgsllQmx2QqQ3yq8EhmGE9mGE2kGZlMMTyZon88RX88Sf9Yir7xJAPxFEG/h/pYkNpogLrCo6kqRGtVmOaq0JJ6E1sKAeJcI5Mpjg9OcnokQe9Ykr7xKXrGkgzGp6iPBWmvCdNaFaalOkRDRYiaiJ+qsJ9Y0Ef0zCPgJRr0EQl4yzLYiczB3AKEmT0A1C9Eiy6iHhhY5HOWk2VZvwWjlZ5AZK03WrU8fus6l3O5XBaXzbhcLpNLjHs9wUii1M0qldzURMgTjCZL3Y4LMDxev3m8fjxen3k88zr0m50cxRupms9DXpyDzGjv4VxyfGTxTnpBy/L3XcFSqX3AOXfP+VbM1AOx6MzsGefcjlK3o1SWc/2qfXnWDsu7ftWu2peqpdMnKiIiImVDAUJERESKVo4B4jOlbkCJLef6VfvytZzrV+3L05KvvezmQIiIiEj5K8ceCBERESlzChAiIiJSNAUIERERKZoChIiIiBRNAUJERESKpgAhIiIiRVOAEBERkaIpQIiIiEjRFCBERESkaAoQIiIiUjQFCBERESnajAHCzI6Z2V3nLNtpZqemvd5lZkkzi5vZgJl93cxaCus+a2Z/Mv9NFxERkVKZzx6IX3fOxYD1QDXw/87jsUVERKSMzPsQhnNuCPgasGW+jy0iIiLlYd4DhJnVA+8Cnp/vY4uIiEh5mM8A8VdmNgK8CHQDvzWPxxYREZEy4pvHY33MOfd/5vF4IiIiUqZ0GaeIiIgUbbY9EH4zC81hvzO85+yfc86lijyGiIiIlInZ9kB8F0hMe3yiyPP87jn7/7jI/UVERKSMmHOu1G0QERGRJUZzIERERKRoChAiIiJSNAUIERERKZoChIiIiBRtpssxNcNSZBnauXMnALt27SppO0Sk5OxCK+bzTpQiskRksjm6R5P0jCUZnkiRSGfJ5hxejxHyexlLpPF5PQzEp6iLBjC74O8QEVmmFCBELnPjyTQvnBzhxZMjvHJ6jH09Y3SNJKmK+KmPBqgI+Qj4vHgMcg5S2RzHhybJ5hx3/OUuUpkcK2qjXNFWybUra7lxdR0r6iIKFSLL3Ez3gdAQhsgSdLB3nO+81M2De3s53D/B6oYoq+qjdNZG6KyN0FIVJuC78BSoj37wXgA+fd+3SKSydI0mONI/weH+OK+cHiXk9/K6DQ3cuamJG1bXEQ54F6s0EVlcGsIQudwl01m++cJp/unx4/SNJ7l+VR1v29bGhuYK/N65z5cOB7ysaYixpiHG3TThnOPE0CQvnhrhL36wnyMDE1zTWcMdGxu5bX09axpi6p0QWQYUIESWuLFkms89fox/eOwYq+qjvHVrC1e1VePxLMybuJmxoi7Kiroo925tY2Iqw8unR3ns0AB/+9BhAG5cU8et6xq4ZW09zVWhGY4oIkuRhjBElqjhiRT/8OhRPv/kca7qqOYtV7bQURuZl2NPH8IohnOO3rEpXukaZW/3GK+cHqWxIsRdmxt5wxXNbG1fuGAjIgtCQxgil4vD/XH+8dGjfPPFLq5fVcvH33pF2fyVb2Y0V4Vorgpx16YmcjnHof44z58Y5mP/8jypbI63XNXKW65qYVtHtYY6RJYw9UCILAHxqQwPvNLDl54+wcG+OHdsaOTOTU3URgMLcr659kDM5OTQJE8dHeSpo0Pkco43F8LEVe1VChMi5Uk9ECJLzVgyzU/29fHtl7p5/NAAm1sruXlNPR+7Yx2+S5gUWUodtRE6aiO86+p2jg9N8tMjg/zaF54j5xxvurKFN13ZwvYODXOILAUKECJl5OTQJD/a28v39/Ty4skRNrdUcvWKGt57TQex0OXz42pmrKyLsrIuynt2dHBiaJKnjw3xm196nslUlrs2NXHnpiZuXFNHLHj51C1yOdEQhkgJ5XKOF0+N8MM9vfxgdy8DE1Ns76hmW0cNV7ZVlez+Cgs1hDEbXSMJnjsxzMunRznYG2ddY4wb1tSxY0UN2zqraawoj/keIsuEhjBEysXoZJrHDg/w4719/GR/H9Ggj+2d1fz8jStY2xBb9t33rdVhWqvDvOWqVlKZHAd6xznQO87fPnSYA71xYkEf2zqquWZFDVs7qtnSVkkkoF9lIotNP3UiC2gyleFQX5w9XWO8cHKE504Mc2o4waaWSq5oreQP3ry5bK6gKEcBn4ctbVVsaasCIOccvaNJDvXHeeb4EF959iTHByfpqI1wVWG7jc0VrG6I0VQZ1MRMkQWkACEyR+lsjpHJNEMTKQbiU/SNJ+kaSXJqeJJjA5McG5xgcCJFW3WYztoIK+oi/Nz1K1jVEMXnWZqTIEvNY0ZLdZiW6jC3rmsA8v8fTgxNcnRggqeODPK1507RNZJgMpWltTpMS1WIxsogTRUh6mIBqiMBqsJ+qsJ+KkN+KsM+KkJ+YkEf3mXe+yNSDAUIKQuJVJb7XzjNZCp7dtmF5uecWexwOJefqJP/mn+dyzlyDrLOkc3lyJ1dll+ec45czhXWO9JZRyqTI5XJkcxkSaayJDJZkukcyVSWyXSWRCrLxFTmgpOCAl4PNVE/NZEA9bEgLdUhtndW01ARxHvOX8FH+yfm4V9sYSXS+f8PB3vHS9yS2VtRG2HFtBtpJdJZ+uNTDE2kGJ5Ic2JwmPhUmvhUhompLPGpDNnczNO8Qn4PIb+XkM9L0OchMO0R9Hrw+zwEfR783ukPw+c1fB4PXo/h9RgeM8zAYxSeG97CMoOzQ1f514bHfvb8zPIzpvesnO/n5GJT287tlDlzLJ/HePv2NqrC/hn/TURghkmUZvYAUL94zYHC+QYW+ZzlZFnWb4FIzBOKbvBGqkrdlItzzjmXy+JcFpfLzrzD7GQT4z5vuCIzX8dbasqmfjMP5vGCeczMsxhjINnJUcrl+z4z2ns4lxgfWcRTLsvfdwVLpfYB59w951sx01UYi87MnnHO7Sh1O0plOdev2pdn7bC861ftqn2p0kCsiIiIFE0BQkRERIpWjgHiM6VuQIkt5/pV+/K1nOtX7cvTkq+97OZAiIiISPkrxx4IERERKXMKECIiIlI0BQgREREpmgKEiIiIFE0BQkRERIqmACEiIiJFU4AQERGRoilAiIiISNEUIERERKRoChAiIiJSNAUIERERKdqMAcLMjpnZXcUc1Mx2mZkzs63nLL+/sHynmf2tmcULj5SZpae9/l5h+18ys31mNm5mvWb2HTOrOOeYB8xs/QztWVk473PnLK8vnPtY4XV82iNnZolprz9U2GadmX3RzPrNbMzMDprZX5tZezH/RiIiIkvZQvZAHAA+fOaFmdUBNwD9AM65X3HOxZxzMeBPgS+dee2ce6OZ3V5Y/gHnXAWwCfjy9BOY2RrA45w7MMs2Rc1sy7TXHwSOnnkx7fwx4ATw1mnLvmBma4GngC5gu3OuErgZOAzcMut/GRERkSVuTgHCzGrM7NuFv8KHC8/P/Qv8C8D7zMxbeP0B4BtAapanuRZ4wjn3PIBzbsg590/OufFp27wZ+G6hTW82s+cLvQInzewT5znm54FfmPb6w8DnZtkegE8Ajznnfss5d6rQrj7n3Kecc18s4jgiIiJL2lx7IDzAPwIrgE4gAfyvc7bpAvYAry+8LvbN+ingDWb2x2Z2s5kFz7PNm4DvFJ5PFM5RTT5Y/KqZvf2c7f8ZeL+Zec1sE1BROM9s3QV8rYjtRURELktzChDOuUHn3Necc5OFHoH/Btx+nk0/B3zYzDYA1c65J4o4xyPAO4GryYeEQTP75JkeDTOLkO+leKiw/S7n3MvOuZxz7iXgX87TplPAfvJB4BcoLtAA1AM9Z16Y2a+b2UhhjsTfFXksERGRJWuuQxgRM/vfZnbczMaAh4HqacMVZ3wduAP4DfLDB0Vxzn3POfdWoBZ4G/AR4JcLq+8EHnfOJQttut7MflIYVhkFfoX8G/65Plc4zgfI90gUYxBomda+/+WcqwY+BfiLPJaIiMiSNdchjN8GNgDXFyYS3lZYbtM3cs5NAt8DfpU5BIhpx8k5534E/Bg4Mwly+vAFwH3At4AO51wV8Lfntqfga+SHOI44544X2ZQfke8VERERWdZmGyD8ZhY68wBqyM97GDGzWuDjF9n394HbnXPHimmYmb3NzN5fmLBpZnYd+SGJJwubvJHCBMqCCmDIOZcsbPvB8x3XOTdBvlfkl8+3fgafAG4tDKW0FdpZT/4KERERkWVjtgHiu+QDw5lHNRAGBsi/oT9woR2dc13OuUfn0LZh4N8AB4Ex8sMNf164nHILEHfOnZi2/a8B/8XMxoE/4pxLPs9p0zPOucPFNqhwuegNQDvwYuFcj5GfMPqHxR5PRERkqTLnXKnbUDQz+x2g3jn3O6Vui4iIyHLkK3UD5ugY8K+lboSIiMhytSR7IERERKS09GFaIiIiUjQFCBERESnaTHMgNL4hsgzs3LkTgF27dpW0HSJSds53PyVg6U6iFJFZ6B+f4pXTo+zvHedI/wS9Y0nGEmkyOYffa1SF/TRUhDg9nCDo9/DCyRFW1UepCuvGqiJycQoQIpeRk0OTPH54gMcODfLMsSHGkhnWNsZoqw7TVBmkY2UN0YAPr8fI5BwTyQwjiRSJdJaxZJrf/vILdI0kiQS8rG+qYGtHFVd31nDdqlqqI4FSlyciZWSmqzA0hCFSxpLpLE8cGeTBPb08dKCfiakMW9qq2NBUwcbmSlqqQ3jsgj2QZ330g/cC8On7voVzjsGJFCcGJzk6OMHhvjj7e8dZURdh5/pGXrexke2d1fi9mkIlsgxoCEPkcpHNOR47NMBXnz3FT/b30VETYWtHFb/+urV01kawWQSGizEz6mNB6mNBrl5RA0Amm+NgX5yXTo3w+994mZ7RJNeurOGWdQ3cuLqOjc0VeDyXdl4RWVoUIESWiMH4FPf99ARfePIEsaCPm9fV8WfvumpRhhZ8Xg+bWirZ1FLJ+4CxRJpXukZ58sgA//DoUeJTGa5fVcut6xu4bV09K+qiC94mESktBQiRMre7a5S/f+QoP9jTy3WravjYnetYVV/aN+jKsJ+b1tRz05p6AIYmUuzuGuXBPb38vz88QDTg5Y6Njbz+imauW1Wr4Q6Ry5AChEgZSqSyfO+Vbj73xHFOD09y56Ym/vK9W6kMlefVEbXRALeua+DWdQ3knOP44CQvnBzmj/91D92jCW5b18AbtjRz+/oGXeEhcplQgBApE+lsjiePDPLN57v4/p4e1jXGuGNDI1evqMG7hOYXeMxYVR9lVX2Ud2xvZ3gyxXPHh/nc48f4z199iU0tFezc0MiNa+q4qr2KoM9b6iaLyBwoQIiUUCKV5eGD/TzwSjc/3tdPU2WQ61bV8t/feRW10cvjssmaSIA7NzVx56YmpjJZ9naPsbtrjG+92MWp4UnWN1awvbOabZ3VbG2vZmVdVBMyRZYAXcYpssiGJlL8aG8vD7zSwxNHBlnbGGN7Rw07VtZQHwuWpE3TL+NcTMl0liMD+UtFjw1OcLg/TiKV5ar2aq5dWcO1K2vZ1llNJKC/dURKRJdxipSKc479vePs2t/PD/f0sq97jCvbq7m6s5r3X9dJLLh8fwxDfi+bWyrZ3FJ5dtnIZIqDvXEO9o3zwCs9HB2cYFV9lGs6a7h6RQ1XtVezul69FCKlph4IkXk2PJFib88Yr5we5ZljwzxzbIig38tVbVVc1VHNltYqAr7yuiqhVD0Qs5HK5Dg2OMHB3jhHB+Ic7o8zPpVhY3MlV7ZVsrmlijWNMVbXR6mO+C/5Phgi8irqgRCZT845esemONwf51BfnAO94xzoHedQX5xUJseKuigr6iKsa6rgLVe10lBRmqGJy0HA52F9UwXrmyrOLhtLpjk2MMHxwUm+83I3XSMJukYSmBmt1SFaqsK0VYdpqwnTVBmiuTJEU2WQxooQlWGfQobIPFCAkMuScw7n8l1oOefI5hw550hnHZlsjlQ2x1Q6RzKTJZnOkUhl889TWRLp/LJkOr9scirLeDLN8GSa/vEpesaSdI8mCPm8tNWEz75h3bWpiV+4cSW10YDeoBZYZcjPVe3VXNVefXaZc474VIaBeIqB8SkGJ1Ls7xnjp0eHGJ5MMTyZYiieIpXNURMJUBMJUBXxUxnyEQv5iAV8RII+IgEvIb+XkM9DuPA86PPmn/s8hPxeAj5P/uH1EPR58Hk9+LyG1+zsFTNmYFjha/7qFDP0vSGXjYsOYZjZA0D94jUHCucbWORzlpPLr36P1xdoXLV1ps2yk6N4I1WL0aJL55xzzuXm63C5xJh5wpXLdshwMes3M8OsbMaQFvv7PjPWfyw3OTq4aCe8uMvv993sLZXaB5xz95xvxUxzIBadmT3jnNtR6naUynKuX7Uvz9phedev2lX7UlU2KVxERESWDgUIERERKVo5BojPlLoBJbac61fty9dyrl+1L09LvvaymwMhIiIi5a8ceyBERESkzClAiIiISNEUIERERKRoChAiIiJSNAUIERERKZoChIiIiBRNAUJERESKpgAhIiIiRVOAEBERkaIpQIiIiEjRFCBERESkaDMGCDM7ZmYJM4ubWa+Z/aOZxQrr3mBmD5vZuJn1m9lDZnbvtH1bzOzvzay7sM0+M/tjM4suZFEiIiKysGbbA/FW51wMuBq4FvgDM3s38BXgc0A70AT8EfBWADOrBZ4AwsCNzrkK4G6gGlgzjzWIiIjIIpvx0zjN7Bjwy865Bwuv/xzYDFwJ/LVz7s8vsN+fAG8DtjrncvPZaBERESmtouZAmFkH8CZgEugAvnqRze8Cvq7wICIicvmZbYC438xGgEeBh4BPFZZ3X2SfuhnWi4iIyBLlm+V2bz8zhAFgZhsLT1uAoxfYZ7CwXkRERC4zc72Mcz9wEnjXRbZ5EHiHmelSURERkcvMnN7cXX7m5W8Bf2hm/5eZVZqZx8xuMbPPFDb7JFAJ/JOZrQAwszYz+6SZXTUvrRcREZGSmHPvgHPuq8D7gF8EuoBe4E+AbxbWDwE3AWngKTMbB34EjAKHLq3ZIiIiUkozXsYpIiIici7NTxAREZGiKUCIiIhI0RQgREREpGgKECIiIlK0mW4kpRmWIkvczp07Adi1a1dJ2yEiS5JdaMVs70QpImUolclxqC/Ogd5xDvXFOTowQc9YktFEmnQ2R8DrYXfXGH6v8YlvvUJTZZjGiiANFUGaq0K0VYeJBvVrQESKp98cIkvIqeFJHj80yNPHhnjp1CjHBidoqgzRXhOmpSrEiroI2zuriQV9+Dwe0rkcn/h8gEwuRzrr2N01yhOJNKOJNEOTKfrGpqiJBNjWUc3N6+q5fV0DnXWRUpcpIkuAAoRImesZTfK1505y//Nd9I9PsaWtirWNMX7uhk46a6MEfBefyhQNeAEvb7mq9TXrcs7RO5rkYF+cH+3p5S9/sJ/aSIDXX9HE3Zub2NZRg9dzwR5MEVnGFCBEytRzJ4b5zENHeOzwADesquWD13WyvqkCzzy+oXvMaKkO01Id5rb1DeSc40h/nOeOD/PbX3mRkYk0t66r567NTdy2roGaaGDezi0iS9tMd6LUJEqRRZTLOR7c28v/t+swXaMJ3nBFM7evbyASmHvW/+gH7wXg0/d9q+h9B+NTPH9yhJdPjfJK1ygbmiq4Z0szb7qyhY5aDXWILAOaRClSzsaSab76zCk++/gxgj4Pb9zSzHWr6ko+fFAXC3LXpibu2tREKpNjT/cozxwb4v/bdZgVdRHee20H925tpSLkL2k7RWTxqQdCpESyOcdTRwb5yrMneXBPH1e2V3H35iY2NFVgNn/B4VJ6IC4kk8vx0qlRHjnYz+7TY7zpyhY+fNMKrmitmrdziEhZUA+ESDlwzvHiqVHuf/4033mpm8qwj5vW1PPn79lKVXjp/BXv83i4urOGqztrGJ5MsWt/Hx/5x6dpqQrxkZtW8qYrWwj5vaVupogsIPVAiCyCI/1xvvHcab7xwmkArl9Vy42r62mrCS/4uReiB+J8sjnHcyeG+cn+Po70T/C2ba2855oOtrRVzmuPiogsKvVAiCy23rEk33mpi689d5ru0SQ3rq7jV29fw6r66GX5hur1GNeurOXalbX0jyd5+EA///bzz+D3enjTlc3ctamJrR3V+L26g77I5UA9ECLzJJPN8UrXGI8e7OfBvX0c7o9zzYoablxdxxWtVSWbELlYPRDn45zjyMAEzx4f5sVTI/SOJdnaXs21K2u4qr2aK1qraKoMXpaBSuQyoR4IkfmSyzl6xpIcG5jg8MAE+7vH2N09xv6ecRorgmxureSeK5rZ3Fq57P/aNjPWNMRY0xDjvTs6GEumOdAzzqH+OA8fGODIwAQGrG+u4IrWSja3VLK5tZJ1jRUz3iBLREpLPRAiFxCfyuRDQn/87OdNHO6f4OTQJNGgj5aqEC1VIZorw6yoi7CyPkqsDD9XopQ9EDNxzjE8mebE0CQnhiY5PTzJ8cFJuseSdNSEWddYwdrGGJ11EdqqwzRVhmiqDBIL+tRrIbI41AMhy5tzjqlMjvFkhrFkmvFkhtHCZ0KMTqYYmkjTP56kdzxJ90iS0yMJJlNZWqvznzHRXBViXWMFt69vpLkyRDigKwzmg5lRGw1QG81/HscZqUyO0yMJukYS9Iwlefn0KEMTUwxNpBiaSJF1UFfYrzYaoDrspyrsJxbyEQv6CAd8RAJeIgEv0YDv7PJY8GfPgz6PQojIJbhoD4SZPQDUL15zoHC+gUU+ZzlZ0Pp9VU2dnnBFw0Id/1JkJ0fxRkp8HwHnnMvlMuSyaeeyGRapFy6XjAc8oVhqMc5Vjoqv3zzm8fgwjxePx2vmWbKJbr6+73PJicHMSPexS2/RolrOv++XSu0Dzrl7zrdipiGMRWdmzzjndpS6HaWynOtX7cuzdlje9at21b5UaZaSiIiIFE0BQkRERIpWjgHiM6VuQIkt5/pV+/K1nOtX7cvTkq+97OZAiIiISPkrxx4IERERKXMKECIiIlI0BQgREREpmgKEiIiIFE0BQkRERIqmACEiIiJFU4AQERGRoilAiIiISNEUIERERKRoChAiIiJStDkFCDP7rJn9yXw3RkRERJaGRe2BMLNPmJkzs4+ds/w/FJZ/ovB6p5nlzCxuZuNmtt/M/q/CupWFbePTHi9OO1aLmf29mXUX9t1nZn9sZtHFrFVERORyVoohjAPAL5yz7MOF5dN1OediQCXwn4G/M7PN09ZXO+dihcdWADOrBZ4AwsCNzrkK4G6gGlgz75WIiIgsU7MKEGa23cyeK/xF/yUgVFi+08xOmdnvmFlf4a/+t5vZm8zsgJkNmdnvn3O4p4GImV1ROMYV5N/wnz7fuV3e/cAwsPl820zzW8A48HPOuWOF/U865/69c+6l2dQqIiIiM5sxQJhZALgf+DxQC3wFeNe0TZrJB4o24I+AvwN+DrgGuBX4IzNbfc5hP0++1wHyvRGfu8j5PWb2DvK9CC/P0Ny7gK8753Iz1SUiIiJzN5seiBsAP/Ap51zaOfdVXt1bkAb+m3MuDXwRqAf+p3Nu3Dm3G9gNXHXOMf8Z+ICZ+YH3F16fq9XMRoAB4OPAzzvn9k9bP2BmI4XHfywsqwO6Z1GTiIiIXALfLLZpBU4759y0ZcenPR90zmULzxOFr73T1ieA2PQDOudOmNkh4E+Bg865k2Z27nm7nHPtF2lXvXMuc86yQaDlIvuIiIjIPJhND0Q30GavfofvnIdzfw74bS4yfDEHDwLvMDPd30JERGQBzeaN9gkgA3zMzHxm9k7gunk495eA1wNfnodjnfFJ8ldt/JOZrQAwszYz+6SZnTuMIiIiInM0Y4BwzqWAdwIfIX8lxPuAr1/qiZ1zCefcg865xMxbz/qYQ8BN5OdlPGVm48CPgFHg0HydR0REZLmzV09tEBEREZmZ5gqIiIhI0RQgREREpGgKECIiIlI0BQgREREp2kw3ktIMS5EytHPnTgB27dpV0naIyGXvNXd5PGM2d6IUkRKbymTpHknSO5ZkeDLNQHwKgG+/1EVV2E9TZYiOmgjhgLfELRWR5UIBQqSMTGWyHB2YYH/POHu7x9jbPc7BvjgD41PUxgLURQPEgj76x6cw4AtPnWBiKsPwRIre8SnqY0G2tFayY2UNO1bWcmVbFX6vRipFZP7NdB8IDWGILADnHCeGJnnh5Ah7u8fY3zPO4f4JekaTNFUF6aiJ0FYdzn+tCdNYGcTn+VkQ+OgH7wXg0/d96+yyXM7RM5bkyMAEh/vjHOgZp2csydWdNdy6rp7b1jewsbmC83zujIjIhWgIQ6TUnHO8cHKErz93mh/u6SWdzbGuqYKOmjBbO6p545YWmqtCc+4x8HiM1uowrdVhbllbD0A8mWFP9xjPHR/mnx4/RjrreN3GRt64pZmb1tYR9GnIQ0TmRj0QIgssk83x7Ze6+d8PH2Z0Ms0t6+q5bmUdrdWhOfcGnK8HYja6RxI8d3KY546PcHJ4kjdsbubdO9q5bmUtHo96JkTkNdQDIbLYkuksX332JH/zk8PURAO89apWtnZU4ynhEEJLdZg3V4d585WtDManeOLIIL/7tZfI5Bwfur6T9+zooD4WLFn7RGTpUIAQmWfdownue/IEX/jpCVY3RPm3t61hQ3NFqZv1GnWxIG+5qpU3X9nC4f44P9nfx6d/cpjXbWzgIzet5OrOGs2XEJELUoAQmQeD8Sl+uKeX+1/oYnfXKDetqeP33riR9ppIqZs2IzNjbWMFaxsr+MC1GR4+2M/H/uUFQn4P77u2g3u3ttFcFSp1M0WkzChAiMzR8cEJfrC7hwd297Kve4ytHdVcv6qWX719DQHf0rx0Mhby8aYrW3jjlmb29ozz2KF+/vrHh1hVH+UNVzRx56YmNjTpSg4R0SRKkVlzzrG7a4zvv9LD917pYWBiih0ratjeWcOW1qpFDQ1znUQ5F5lsjt1dY7xwaoQXToyQc/krOe7e1MTNa+t18yqRy9sF/1pQgBC5iGQ6y1NHh/jh7h5+uLcXrxnXrKjhmhW1rGuMlezKhcUMENM55+gaTfLCyWFeODnC4f4Jdqyo4Y6Njdy8tp51jTH1TohcXnQVhshspDI59naP8fSxIR4+0M8zx4dZURdha3s1v333Btprwsv6DdLMaKsO01a4kmNiKsNLp0Z55GA/n3n4CBOpDFe1VXNVexUbWypZ1xhjVX2UkF+9FCKXGwUIWZbS2RwnhyY50p+/a+P+nnH29YxxuH+C1uow6xtjbOuo4edvWEkspB+TC4kGfdy4po4b19QBMDSR4nB/nOODEzx/YoTTIwl6RpNUR/x01EZorwnTWRuhtTpMS1WIlqowzZUhKsO+ZR3MRJYi/WaUy4pzjkQ6S3wqw3gy/xkR/eNTdI0mOTE4wdHBSY4N5G8ZXRcL5N/AqkK0VoV437WddNZG9NfyJaiNBqiN1nLtytqzy3I5x0B8ir7xKQbiU3SNJNjdNcbwRIrBiRSD8SkyOUdtNEB9LEhd4TM/GiqC1Mfyj9pogJpIgOqIn8qQn2jQi0+f8SFSUgoQl4kv/vQEjxwcAMCdM3Xl3GkuF5/2cmHn/oHo3M/O5RzkXP4NPOfyS3MXOc+ZuTc558jm8o901pHK5Ehlc0yls0xlckxlciQLzy9FdcRPQyxIY2WI61bV0lgRfM0to4cmUgxNpC7pPItlLJkB4MkjgyVuSXFCfi/tNRHaa169fCqTZWQyzVgizWgyw4HeOM8cG2YsmWY0kb7o99KF+L2G3+vB7/Xg8xg+rxHwevD7PPg9Hnxew+cxPB7Da/mvRv773LD818L3/JnXAB4rrIOzvSZn9ps+XHy+DpXpi2bqcLHC1rPtmDn/+fJ1//s717G6ITa7A4nM0kUnUZrZA0D94jUHCucbWORzlpM51e+r69jg8QeX9G+I7OQo3kjVhTdwzjlcLp9anMO5XOFRWJ7Lv16CclMTAU8wujTSywKYU/3m8ZiZF/N4MPNg5gUzyz9fMuMhM37fz4PMaN/RXGJsaEFPMjfL+ff9Uql9wDl3z/lWzHQVxqIzs2eccztK3Y5SWc71q/blWTss7/pVu2pfqjSIKCIiIkVTgBAREZGilWOA+EypG1Biy7l+1b58Lef6VfvytORrL7s5ECIiIlL+yrEHQkRERMqcAoSIiIgUTQFCREREiqYAISIiIkVTgBAREZGiKUCIiIhI0RQgREREpGgKECIiIlI0BQgREREpmgKEiIiIFG1RA4SZOTObMLO4mZ02s0+ambew7piZJQrrzjxaC+sCZvYJMztY2P+Ymf2Dma1czPaLiIhIXil6ILY652LAncAHgX8zbd1bnXOxaY+uwvKvAvcWtq8CtgLPFo4hIiIii8w30wZm9rvADufcu6ct+5+AAVcBjwJ3FJ7/BPgI8FfAW4H9wHucc8fOPa5zbp+ZPQJsmeH8dwF3A+udcycLi0eBT8/UdhEREVkYs+mB+BfgTWZWCVAYcngvcF9h/fuBnwfagDXAE8A/ArXAXuDj5zuomW0GbgWen+H8dwE/nRYeREREpMRmDBDOuePAc8DbC4vuACadc08WXv+jc+6wc24U+B5w2Dn3oHMuA3wF2H7OIZ8zs2HgX4H/Qz5snHG/mY0UHvcXltUB3cWXJiIiIgtlxiGMgvuADwCfIz8P4b5p63qnPU+c53XsnGNd7Zw7dIHzvN059+A5ywaB9bNsp4iIiCyC2U6i/Aqw08zagXfw6gCx0B4EriucW0RERMrArAKEc64f2EV+uOGoc27vQjbqnHM/CPwQ+IaZXWNmPjOrMLNfMbNfXKx2iIiIyM8UcxnnfeQnNC5m78MZ7wa+C3yJ/BUYrwA7yPdOiIiIyCIz51yp2yAiIiJLjG5lLSIiIkVTgBAREZGiKUCIiIhI0RQgREREpGgz3UhKMyxFysDOnTsB2LVrV0nbISLLjl1ohXogRMpULufI5ZThRaQ8zfZW1iIyz7I5x9GBOHu6xznQM87BvnFODE7SNz7FWDJNOpsPD0Gfh+4TwwR8Hv7TV15kS1sVWzuq2dxSScCnvwFEpDQUIEQWSSab47kTIzxyoJ8njgyyp3uMqrCflXVRWqpDrGus4Ja1DdRGA8SCPvzefM/hVCbHbzwQIZ11VIR8PHKwn88+foye0SSbWyu5YVUt16+u45oVNUSD+pEWkcWh3zYiCyiXczx1dIivP3eKH+zppS4W4MrWKu7c1Mi/u30NsVm84Yf8XgJeDwEv3L25+ezyyVSGg71x9veM8T8e2MeR/gk2NFdw27p6blvfwNaOavxe9VCIyMJQgBBZAF0jCb7yzEm+9PRJAj4PN6+t57++bQsNFcF5O0ck4GNrRzVbO6oBmMpk2d8zzu6uMb79tZfoHUuyY0Utt66r5/pVdWxqqcCnQCEi80QBQmSepLM5fryvjy88eZznT45w0+o6fu11a1ldH8XsghOZ503Q5+Wq9mquaq8GYDSRZk/XGE8fHeLzTx5nID7F9o4abl5bx63rGtjcUonHs/DtEpHLkwKEyCU6NTzJvzx1gi89c5LGihC3rW/gF29ZRdDnLWm7qsJ+blxTx41r6gAYS6bZ1z3Oi6dGue+nJxhPZLhlXT13bmrk9vWN1EYDJW2viCwtM32Ylq4hEzmPXM7x2OEB/vGxYzxzbIib19bzug2NdNRGFuR8H/3gvQB8+r5vzdsxB+JTvHhyhJdPj/LK6VFWN8S4Y2Mjt29o4Kq2Kg13iAhc5D4Q6oEQKcLoZJqvPXeSf3r8OB6PcefGRn7+hhWE/KXtbZiL+liQOzc1ceemJtLZHPt7xnnp1AjffPE0g/EU162q5da19dy8tp61jbFFGYYRkaVDAUJkBpOpDA8f6Of+57t49NAA2zur+YWbVrKxueKyeVP1ez1saatiS1sVACOTKXZ3jfHwwX7+9qHDpLOOm9bUsXNDI7eur6exIlTiFotIqWkIQ+QcuZxjT/cYTxweZNeBPp4/McK6xhg7VtZyw+q6WV16Od8WYgijGL1jSV45Pcru7jFePjVKW3WYnRsauG19A9esqFmSPTAiMisawhC5kFzOcaBvnCcPD/LooUF+enSQqoifzc2VXLeyjl+8eRWRwPL+UWmqDNFUGeLOTU1kc45DfXFeOjXCf/nXPZwYmuSK1kquW1XL9s4armyroqkyeNn0zojI+S3v34qy7Djn6BpNsq97jFdOj/LciRGePzFMLOhjU0slG1sqecf2Nl2RcBFej7GhuYINzRW8h/wQz6G+OAd6x/mbnxzicH8cr8dY31RReMRYWR+lszZCS1VYt98WuUwoQMhlxTlHfCpD71iSrpEkp4YTnBya5OjgBMcHJjg+NEnI72VFbYTO2gjbO6t5744OBYZLEAn4XnX/Ceccw5NpTgxNcno4wcMH+/nKs6foHUsyNJGiMuSnsTJIc2WI5qoQrVXhfA9HVYjGiiD1sSC10QBe3aNCpKwpQAjZnGM0kX7NcufcqybBOAcOd3ZmzPkmyJzZxjnIufzXbM6RdflPlsx/LRxn2j5nvmady2+fc6QyOVLZLFPpHIl0lslUlslUhvhUlvFEmtFkmrFEmpHJNCOJNEMTKYYmUhhQHwtQFwtSFwtSHwvQURPh2hU1NFeFiQZfO14/lcnO/R9wEZz5UM5yb+cZ0aCXTS0VbGqpeNXyXA5GEimGJ1IMT+b/n+3pHuPxI4OMTKYYnkgzMpkimckR9HmoCvupDPupCPqIhXzEgj6iQR+xgI9I0Esk4CXk9xL0ewl6PQR8+YfPY/i9Hjwew2uGx8DMMAPP2a/5516Pnf06/fmZ9QB2Zv9CHeeOzpxZY3bOgLG9et20xRd1vuGfqrBfoUrKykUnUZrZA0D94jUHCucbWORzlpNFr98bq23yxmrbF/Oc55OdHMUbqbr0A80wM7gcZSfH8EYqS92Mkjlv/ctkEsVsv++z8aFT2fhQ7yI0aTEt59/3S6X2AefcPedbMdNVGIvOzJ5xzu0odTtKZTnXr9qXZ+2wvOtX7ap9qdJsJhERESmaAoSIiIgUrRwDxGdK3YASW871q/blaznXr9qXpyVfe9nNgRAREZHyV449ECIiIlLmFCBERESkaAoQIiIiUjQFCBERESmaAoSIiIgUTQFCREREiqYAISIiIkVTgBAREZGiKUCIiIhI0RQgREREpGgKECIiIlK0GQOEmR0zs7vOs/z3zeyomcXN7JSZfWnaul1mliysO/O4sbDOzOzXzewlM5s0s57C9u+f39JERERkocypB8LMfgH4eeAu51wM2AH86JzNft05F5v2eKKw/K+A/wD8NlAHtAF/ANwzl7aIiIjI4vPNcb9rge875w4DOOd6mMVHk5rZeuDXgOudc89MW/Vo4SEiIiJLwFwDxJPAX5nZaeAnwPPOuews9rsDOHlOeBAREZElZk5DGM65fwZ+A3gD8BDQZ2a/e85mf2VmI4XHc4Vl9UDP9I0K8ydGCnMmVsylPSIiIrK45nwVhnPuC865u4Bq4FeA/2Jmb5i2ycecc9WFx9WFZYNAyznHaScfLIKAzbU9IiIisngu+TJO51zaOfcV4CVgywyb/xhoN7Mdl3peERERKZ3ZBgi/mYWmPX7ZzN5sZhVm5jGzNwJXAE9d7CDOuf3A/wa+aGZ3m1nYzLzATZdWhoiIiCym2U6i/O45r/cCw8A/A17gOPCrzrnZXEnxUfLzJz4JrAVGgAPA+4ATs2yPiIiIlJA550rdBhEREVlidCtrERERKZoChIiIiBRNAUJERESKpgAhIiIiRZvpKgzNsBSZB5OpDHu7xzg1nCCbc1SF/XTURlhZF+X1d90BwK5du0rbSBGR17rgDR7n+lkYIjKDiakM33ulh689d4oXTozQURumoSKI14yJVJbesSR941P0nxwhHPDy37+3l9bqMA2xIHWxIPWxAI2VIWJB/ZiKSPnRbyaReZTLOX56bIivPnuK77/Sw8aWCm5aU8+/vXU1Ib/3NdunMjl+9XthptJZhibSHOmfYCyZZjSRYSyRYiCeIujzsKo+yhWtVVy7qoab19TTWBkqQXUiIj8z030gNIQhMoN0NsdTR4b43ivdfH93DxUhPzeuruOWdfXURAIz7v/RD94LwKfv+9Zr1jnnGE2k6RpNcmxggoN9cXZ3jbKyLso7trfy9u3t1EZnPoeIyBxpCENkPmVzjscODXD/86d5cG8vzVVhrllRze+9cROt1eF5O4+ZUR0JUB0JsLmlEoBMLseerjF2HRjgkz88yO3rG/jIzSvZsaIGM30enYgsDgUIkSKcHJrkvp+e4KvPnKIq4uemNXX86TuupC4WXLQ2+Dwermqv5qr2auJTGR452M9vfukFgj4PH7q+U70SIrIoFCBEZpDK5Pjxvl4+98RxdneNccvaev7TGzbQURspddOIBX28cUsL91zRzN7uMXbt7+cvf3CA61fX8Y7tbdy1qYlw4LVzL0RELpUChMgF7OsZ48tPn+T+F7porQpx2/oG/t1tawj4yu/2KWbG5tYqNrdWMZnK8PSxIf7h0aP83tdf5tZ19bzpyhZet7FRV3SIyLzRJEqRaQbjU3zzhS6+8uxJBsanuGVdA7euq6elav7mNZzrYpMoL9VYIs3Tx4d4/sQIe7vH2NZRzV2bmnjdxkZW1Ufn/XwictnRJEqRC0mms/xobx9ff+4UTx0d4urOat6xvZ0rWirxeJb2pMTKsJ87NzZx58YmEqksL50e4dFD/Xz6J4cIB7zcsbGROzY2csPquvNeZioiciEKELIsxacyPHygn++81M1DB/pZ2xjjhtW1fOj6FZftnIFwwMv1q+q4flUdzjmOD03y4skR/uyB/RwbnOC6lbXctbmJ29c3lMX8DhEpbxrCkGXj1PAkP9nXx/d39/LciWE2NFWwvbOGa1fWUD2L+zUslIUcwpiteDLDi6dGeOn0KC+dGqEy5OfmtXXcvLae61bV0lihG1eJLFMX7IZVgJDL1vBEimeOD/PYoX4eOjDA8ESKrR3VbOuo5qr2KiKB8uiAK4cAMV3OOU4OTfLy6VEO9I6zr2ecqrCfbR3VbG2vZn1zBavqorRUh/B7y29CqYjMK82BkMtTMp3/TImukSSnRxIcH5xgf+84e7vGGJxIsaGpgvXNFfzSLatYVR/Foxstzchjxoq6KCvq8pMsc85xejjB4f44z50Y5tsvddE9mmRoIkVFyEddNEhN1E9tNEB9LEhTZYimyiAtVWFaq8O014Q1v0LkMqQAISXjnCObc0xlciTTWZKFr4lUlompDBOpDOPJDKOJNCOTaQbjUwzEU/SNJxmIpxiIT5FMZ6mLBgtvXgEaKoKsb6zg7k1NtFaFl/wkyHLgMaOjNvKaeRHZnGMsmWYskWY8mWG88BkeRwpBY2gi//9oYDxFJOClqTJEY2WQhliQ+liQmmiAqrCfWMhHLOglEvAR8nsJ+T0EvB4CvsLD+7OvXo/pbpsiZeKiQxhm9gBQv3jNgcL5Bhb5nOVkVvV7Kxs7vJHKxkVoz6LJTo7ijVTNaluXy2VxuQwul70cBtqyyXGfN1SRKXU7FoQB5vGax+vH7LxjHsX8v1/K0gMnXnGZ1NQ5i5fz7zzVXv4GnHP3nG/FTHMgFp2ZPeOc21HqdpTKcq5ftS/P2mF516/aVftSpRlQIiIiUjQFCBERESlaOQaIz5S6ASW2nOtX7cvXcq5ftS9PS772spsDISIiIuWvHHsgREREpMwpQIiIiEjRFCBERESkaAoQIiIiUjQFCBERESmaAoSIiIgUTQFCREREiqYAISIiIkVTgBAREZGiKUCIiIhI0RQgREREpGgzBggzO2Zmd52zbKeZOTP7+jnLtxaW7zKzTjOLT3s4M5uY9vrWwj47zOzbZjZsZiNmtsfM/puZ1cxvqSIiIjJfLqUHoh+4yczqpi37BeAAgHPuhHMuduZRWL912rJHzOwmYBfwGLDROVcN3ANkgK2X0DYRERFZQJcSIFLA/cD7AczMC7wX+EIRx/gz4B+dc/+Pc64XzgaPjzvndl1C20RERGQBXeociM8BHy48fwOwG+iazY5mFgVuBL52iW0QERGRRXZJAcI59zhQa2YbyAeJzxWxe03h/D1nFpjZnxXmQUyY2R9cSttERERk4czHVRifB34deB3wjSL2GwZyQMuZBc653ynMg/gG4JuHtomIiMgCmK8A8WvAd51zk7PdyTk3ATwFvHMe2iAiIiKLaLZ/5fvNLHS+/ZxzR83sduDIHM7/O8D3zew08A/OuT4zawdWAYfmcDwRERFZBLMNEN895/Vj01845x6dy8mdc4+a2R3Ax4HfNTOAU8A3gb+eyzFFRERk4ZlzrtRtEBERkSVGt7IWERGRoilAiIiISNEUIERERKRoChAiIiJStJmuwtAMS5E52rlzJwC7du0qaTtERC6BXWiF7vYossAG41MMxFMMxqcYnkwzmcrggLDfS2NFkJX1URorghQuYxYRWRIUIETmwUB8ipdPjbKne4wDveMcH5jkuePDpHOO1/3FLqojAarCfmIhH0GfBzOYSucYnkzTNZLAY7C1o5qb1tRxy9oGNrVUKFCISFlTgBApknOOk0MJnjwyyBNHBnj62DDDkynWNsTorI3QUhXmqvZqDtdF8Hk9/M3P75jxeEMTKQ72xXn22DCffewYmZzjzk2NvOnKFm5YXYffq+lKIlJeFCBEZmF4IsXDB/t56EA/jx8aJJ3Nsbm1knWNFXzsjnW01YTxnNNjMNs3fTOjLhakLhbkhtV1OOfoGk3y7PEh/uu399A7NsXdm5p4y9YWbl5brzAhImVBAULkAo70x/n+7h6+v7uXg73jbG6tZEtrFf/xDRtorQot2BCDmdFWHaatuo17t7YxEJ/ip0eH+H++u4/esST3bGnmnVe3s2NFDR6PhjlEpDRmupW1rsKQZcM5x/7ecb7zUjfffbmb4ck0O1bUsL2zhitaK4v+y/+jH7wXgE/f9615a2P/eJInjgzy+OFBMlnHe3e0875rO2muCs28s4hI8S74V4oChCxrzjleOT3Gd1/Oh4ZkJsu1K2vZsaKWdU2x1wxLFGMhAsQZzjmODkzw0IF+njgyyHUra/n5G1dw27oG9UqIyHzSZZwiZ0xlsvz06BA/3NPLD3b34vHAtStr+Te3rWZ1fXRJXP1gZqxuiLG6IcYHruvkscMD/Ndv7yGZzvGh6zt59zXtNFaqV0JEFo4ChFz2sjnH3u4xnjwyyMMH+nn2xDAdNRG2tlfzW3evp70mvCRCw4WE/F7u3NjEHRsaOdw/wUMH+vibXYfZ3lnNu65u567NTcSC+lEXkfmlIQy57MSnMrx4coRnjg3x02NDvHhylJqon43NlWxuqeSK1koqQv4Fb8dCDmHMJJnO8szxYZ48Msi+7jGuXVnLG7Y087oNjZovISLF0BwIuTylMjkO9I7z4qkRnj8xwgsnRzg1PMmq+ihrG2Ksa6pgQ1MFleGFDwznKmWAmG5iKsMLJ/P/Ni+dGqGpMsSt6+q5eW09166qpXIRwpSILFmaAyFLXzqb41BfnJdPjfLiqfwb4uH+OE2VIVbXR1lZF+UjN61kRW3+Bk6SFw36uHltPjDkco7D/XF2d43xVz86yIHeOCvqItywupbrV9Vx7apa6mPBUjdZRJYA9UBI2Ulnc5weTnB0YIJDfXH29oyxr3uMw/0TNFQEWVUIC6vro6ysjxLye0vd5PMqlx6Ii8lkcxwZmGBfzxgHeuPs6xmjPhrk6hXVbOuoYVNLJesaY9REA6VuqoiUhnogpDSccyTSWUYTaUYTaYYn0oxMphhJpBmeTDEYTzE4MZX/Gp+ifzzFSCJFXTRAc1WYlqoQrdVh3ndtJ521kbINC0uVz+thfVMF65sqAMjlHCeHJznYF+eRg/3c99QJTo1M4i3c3Kq1JkxbdZiWqjCNFUHqK4LUxwLURvOf9RH2e5f0hFQRmT0FiDLy8qlRfvPLLzCWSL9quQN+1lHkzj7PL3dnu4mce/XrMxs5IOfy+7nC/s7ll+UfC1jURXgMYiE/FUEfFSEfVWE/nXVRasL+V93LIJnOcqB3nAO946Vp6BwNTqQA+PZLXSVuydw0VYZoqgyxgxrGkxn6x6c4MTjJCydGGJpIzXv3pNdjeM3weMBjhpG/XPXsd4K9+k8hM8MKy86EFju7bvqrM6/h1Ut/ZsfKGv7s3Vt1tYpIES46hGFmDwD1i9ccKJxvYJHPWRYsGK3wBCPrvZGqxT+5g2kxJR833Jk1zvGzbxRX+G/6a5d/7ZxzzoHL4VwOl8s5l8viZvde41KTYQtEEvNZ1lJxudRuZh7MPJgn/xUzK3zFKHy116zLJkYpyfd9gcukJtNDpw+Qy2ZLcPpl+zsP1b4Uah9wzt1zvhUzzYFYdGb2jHPu4h9feBlbzvWr9uVZOyzv+lW7al+qNFVdREREiqYAISIiIkUrxwDxmVI3oMSWc/2qfflazvWr9uVpyddednMgREREpPyVYw+EiIiIlDkFCBERESmaAoSIiIgUTQFCREREiqYAISIiIkVTgBAREZGiKUCIiIhI0RQgREREpGgKECIiIlI0BQgREREp2owBwsyOmVnCzOJm1mNmnzWz2Cz2+4SZpQv7xc1sr5m965xt1pnZF82s38zGzOygmf21mbVfSlEiIiKysGbbA/FW51wM2AZsB35vlvt9yTkXK+z7H4B/NrMmADNbCzwFdAHbnXOVwM3AYeCWWVcgIiIii66oIQznXA/wfWCbmd1Q6JHwnllvZu8ws5cusO/3gXFgTWHRJ4DHnHO/5Zw7Vdimzzn3KefcF+dQi4iIiCySogJEYWjhjcAh59yTwARwx7RNPgjcd579zMzeDASAPYXFdwFfm0ujRUREpLRmGyDuN7Nx4CTQB3y8sPxfgA8AmFkF8KbCsjPea2Yj5IPGt4A/dc6NFNbVAz1nNjSzXzezkcJ8ib+bWzkiIiKyGGYbIN7unKsAdgIbyb/5Q7634Z1mFgTeCTznnDs+bb8vO+eqnXMR8kMXHzazf1dYNwi0nNnQOfe/nHPVwKcA/9zKERERkcVQ7ByIh4DPAn9ReL0HOE5+WOO8wxfT9j0GfA94a2HRj8iHDhEREVli5nIfiE8Bd5vZtsLr+4CPAbcBX7nQToX5E/cAuwuLPgHcamafNLO2wjb1wKY5tElEREQWUdEBwjnXD3wO+MPCon8hP7TxY+fcwDmbv+/MfSCAp4HHgD8uHOcAcAPQDrxYmGPxGPnLOv8QERERKVvmnCt1G0RERGSJ0a2sRUREpGgKECIiIlI0BQgREREpmgKEiIiIFM03w3rNsBQp2LlzJwC7du0qaTtERBaRXWjFTAFCZNlyzjE8maZnNMngxBSDEylyOcc/P3mcbC6frX1eIxLwUh0J0FIVYkVtlHDAO8ORRUSWPgUIEWAsmealk6O8fHqU3V2jHOqLc2JoEo8ZDRVBKkI+eseSeMx46EAfXjMckM05Upkc41MZBuMpeseStNeEuXF1HXdf0cxNa+rwezVSKCKXn5nuA6EhDLksZbI5fnpsiB/t7eORg/2cHEqwuiHKiroonbVh2qojtFSFiAZ/lrE/+sF7Afj0fd+66HGPD02yu2uU546PMBCf4j072vnwjStprQ4veF0iIvNMQxgiAHu6xvji0yf49otd1MaCbOuo5kPXr2B1fRTfPPQU+Lwe1jTEWNMQ496tbZweSfDjfb284VMPc/v6Bn7l9jVsaauah0pEREpLPRBy2Utnc3zvlR7+/pEjdI0kuH19A7esa6CpMlTUcWbTA3Ehk6kMP97Xxw/29NJRE+YXblrJG65oJuTXfAkRKWvqgZDlZyA+xRd/eoLPPXGcxoogr9/czNUravB6LvjzsGAiAR9vuaqVe7Y08+zxYf7hsaP80Td386Yrm3nn1e1c01mDpwTtEhGZKwUIuaykszkeOdjPl58+xaOHBrhuVQ2/efd6VtZFS900AHweD9evquP6VXX0j0/x2OEB/uNXXiSZznLv1jbevr2VzS2VmClMiEh50xCGLHmTqQyPHBzggVe6+fG+ftqqw9ywuo6b1tS9ahLkpbqUIYyZnBia5InDgzx5ZIBIwMc7r27jHVe306aJlyJSWhrCkMtL10iCH+3r44e7e3jm+DBrG2Ns76jhv719C3WxYKmbV7TO2gidtRHeu6OdA71xHj88wGceOcL6xgrefU07b9zSQlXEX+pmioicpR4IWRJSmRzPnxhm1/5+frSvl56xJNvaq9nWUc1V7dXz2tNwIQvZA3E+6WyOF06O8PjhAV4+Ncp1q2p5y1Wt3LGxkZpoYFHaICLLnnogZGnJ5hx7u8d44vAgjxzs59kTw7RWhdnSWskHrutkfWPFZT/p0O/1cO3KWq5dWctkKsOzx4f5yrMn+cNvvsKahhi3rqvn+tV1bO+spjKk3gkRWVwKEFIWpjJZdneN8eyxYR4/PMCzx4epivjZ3FzJ9s4aPnTDimX9JhkJ+Lh1XQO3rmsgnc2xv2ecPV2j/Pn393G4L05DRYgtrZVc2V7NFa2VbG6tpH4JDuWIyNKhACGLKpXJ0TWS4NjgBIf7J9jXPcburlEO90/QVh1mXVOMK9uqeO+ODqoj6qY/H7/Xw5a2qrM3pMrmHKdHEhwdmODl06N89+VujgzEifh9bGqpYEtbFZtbK9nYXMnKusi83DBLREQBQuZFIpVlIJ7/wKnB+BQD8SkGCp8N0TNaeIwlGZpIUR8L0FwVprkySEt1mPdd20lnbUQ3VZojr8fOTsI8wzlH//gUxwcnOT40wbPHhzkxNMngRIrO2ghrG2Osa4yxqj5KR23+tt2NFSECPoULEZkdBYhZSqazPHpw4Oys0umTT3+27OLHuNCl/ecuPvceAM453NnjO5yDnIOcc2cfzr32/O7Mvg4cjmwOss6Ryzmyufx+2ZwjU/hAqHQ2x1Qmx1QmSzJdeJ7OkkxnSWVypLI5kpkcyVSW+FSG8WSGRDr7qnOG/V6qwn6qwn4qwz6qwn5qIgFW1kepiwaoiQTOeyOnoYnUxf/xysBUJgfkrwBZKtpqwrTV/OxS0KlCD1DXSIKnjw3xnZe76RubIj6VedV+kYCXaMBHOOAl7PcS8nsI+b0EffmvIb+XgM9D0OchcObh9eD3evB5jYDXg89j+H35rx4zfN78V48ZZmDYBX8mppu+SX57m/b8Z+vP/Nycb2L49CUz/bytqIuwvqli5oaJLHMXvQrDzB4A6hevOVA438Ain3NGnnBVra+qYdVCnyc7OYo3soQ+K8GBc9kMzmVn3vjicolxrydcccnHWYrKpHbDPF7zeBa9K6icvu9dLpdN9x15YRFPWZa/8xaJai9/A865e863YqbLOBedmT3jnNtR6naUynKuX7Uvz9phedev2lX7UqUBTxERESmaAoSIiIgUrRwDxGdK3YASW871q/blaznXr9qXpyVfe9nNgRAREZHyV449ECIiIlLmFCBERESkaAoQIiIiUjQFCBERESmaAoSIiIgUTQFCREREiqYAISIiIkVTgBAREZGiKUCIiIhI0RQgREREpGizChBmdouZPW5mo2Y2ZGaPmdm1hXUtZvZ3ZtZlZnEzO2JmnzWzjdP2D5jZJ8zsoJlNmNkxM/sHM1u5QHWJiIjIApoxQJhZJfBt4K+BWqAN+GNgyszqgMeBCHArUAFcDTwE3D3tMF8F7gU+CFQBW4FngTvnqxARERFZPDN+mJaZ7QAedM5Vn2fdnwBvBbY753IX2P8u4F+B9c65k5fcYhERESm52QxhHACyZvZPZvZGM6uZtu4u4BsXCg/TtvmpwoOIiMjlY8YA4ZwbA24BHPB3QL+ZfcvMmoB6oOfMtmZ2r5mNmNm4mf2gsLgO6J7/pouIiEipzGoSpXNur3PuI865dmAL0Ap8ChgEWqZt963CUMdvAoHC4ldtIyIiIktf0ZdxOuf2AZ8lHyR+BLzdzC52nAeB68ysfU4tFBERkbIzm6swNprZb58JAGbWAXwAeBL4JFADfN7M1lheBbDtzP7OuQeBHwLfMLNrzMxnZhVm9itm9osLUJOIiIgssNn0QIwD1wNPmdkE+eDwCvDbzrkB4AYgCTxa2PYF8pdz/uq0Y7wb+C7wJWC0sP8O8r0TIiIissTMeBmniIiIyLl0K2sREREpmgKEiIiIFE0BQkRERIqmACEiIiJFU4AQERGRovlmWK9LNESAnTt3ArBr166StkNEZJHZhVbMFCBELnuJVJbD/XFOjyQYmkgxmcqSyzk8HiPg8xD2exmcSOE145ljQ1SG/VRH/NRGAvi86sQTkeVJAUKWnXQ2x9PHhvjJvn4ePdTPkf4JWqpCNFaGqAj6CPg8eMzIOUc255jK5OgdS+Kc4w/vf4WJVJbxZJrxZIb6WJCV9RGuaK1ia0c1166soaUqXOoSRUQW3Ew3ktIQhlwW4lMZHtrfzwO7u3lofz9NlSG2tlexpa2aVfVRAr6L9yR89IP3AvDp+751dlkml2MwnqJ7NMGJoUmO9E+wt3uMqrCfm9fWs3NDAzeuqacq7F/Q2kREFtAFhzAUIOSy1Tee5Ae7e/neK908f2KEDc0VbO+o5poVtdRGAzMfYJrzBYjzyTnHyaFJXjk9xp7uUfZ2j7OppYLXX9HMPVc0s7I+Oud6RERKQHMgZHkYnUzznZe7+fpzp9jXM872zmp2rKjlF29eRSSw8N/uHjNW1EVZURflzVe1kMrk2N01yrPHh/nfDx2muSrEu65u5+3b26iPBRe8PSIiC0U9ELLkpbM5HjnYz5efPsWjhwa4sq2SG1fXs7WjesahidmabQ/ExeRyjt3dYzx+aIBnjg9z/epa3n9tJzs3NODXZEwRKU8awpDLi3OOF0+Ncv/zp/jWi900VgS5aU09N66pIxac/56G+QgQ0yVSWZ44Msijh/rpHU3y5qtaeevWVq5ZUYPXc8GfVxGRxaYhDLk8HOgd55vPn+abL3bhHNywupY/ePOmJXflQzjg5Y6NjdyxsZGe0SRPHBngP3/tJUYmU9y2viE/AXN1Pc1VoVI3VUTkvNQDIWWvbyzJN54/zdeeO8XwRIobVtdxw+o6VtVHMVucv9bnuwfiQvrHkzx/coS93WPs6RqjIuRnx4oadqyqZXtHNRuaKzTcISKLSUMYsrQkUlke3NvLl585yfMnRrhuVQ03ralnU0slnkUKDdMtVoCYLuccp4cTHOgd58jABIf64vSNJ9nQVMH2zmq2d9awraOaztrIogUpEVl2NIQh5W8wPsWjhwb4/is9PHJwgDWNMW5aU8cv3ryKkN9b6uYtOo8ZHbUROmoj3FlYlkhlOToQ51BfnH/56Un+5Nt7SWVzXNlWxfbOaq5sq2JzayVt1WGFChFZUAoQUhLJdJa93WO80jXGiydGeO7EML1jSTa3VrK1vZo/f89W3YDpPMIBL5tbq9jcWnV22dBEiiP9cY4MTPD44UGODUyQSGdZXR9ldUOM1fVROuvyQaSjJkJjRRCPJmqKyCVSgJAFNTGV4cTQJMcGJjjYF2df9xh7e8bpGknQXhMu3DMhwi/dsooVdVFdgTAHtdEAtdFadqysPbssnszQNZqgayTB8aFJnjsxTN/4FL1jSSZSWVqrQnTWRVlVF2FlfZSOmgjttWHaqsNUhBTcRGRmChDLnHOOnINszpFz+Ucm58jl8l8zWUcqk2MqkyWRzjKZyjIxlSE+lWEsmSGezJz9XIixZJqxRJrRRJqhiRSDEylSmRzNlSGaqkI0VwZZWR/ltvUNtFWH9UFUCygW8rE+VMH6porXrEums/QXwkTv2BRPHhnk2/Fu+saT9I9P4TGjPhakPhagJhKgMuynMuQjGsw/Qn4vIb+HkM9LyO8l6PMQKDyCPg9Bn3facw8+rwef1/B78l99HtPwishl4KKTKM3sAaB+8ZoDhfMNLPI5i+ZvWHmleX3F3Q95FrKTo3gjVTNvuAQ4l8uSy2Vnu30uMe7xhCtyC9mmclVWtZvHax7Pok46Kafv+/TgqT0unUws4imXxO+8BaLay9+Ac+6e862Y6SqMRWdmzzjndpS6HaWynOtX7cuzdlje9at21b5UqQ9ZREREiqYAISIiIkUrxwDxmVI3oMSWc/2qfflazvWr9uVpyddednMgREREpPyVYw+EiIiIlDkFCBERESmaAoSIiIgUTQFCREREiqYAISIiIkVTgBAREZGiKUCIiIhI0RQgREREpGgKECIiIlI0BQgREREp2mUdIMwsbmarS90OERGRy82MAcLMjplZovBm3GNmnzWz2LT10cK67y5sU8HMbjKzxwvPnZmtPWf9J8zsn8+8ds7FnHNHFrpdIiIiy81seyDe6pyLAduA7cDvTVv3bmAKeL2Ztcxv817jTcCCBxURERG5uKKGMJxzPcD3yQeJM34B+FvgJeBD07cv9F78JzN7ycwmzOzvzazJzL5nZuNm9qCZ1RS2/Y6Z/cY5+79kZm+ftqioADG9l6LQc/K3ZvbDwrkfMrMV52z7MTM7YmYDZvbnZuYprPOY2R+Y2XEz6zOzz5lZ1WzbISIicrkpKkCYWTvwRuBQ4XUnsBP4QuHx4fPs9i7gbmA98Fbge8DvA/WF83+ssN0/AT837VxbgTYKgaHQu9EEPF9Mm8/xIeC/Fs79QqHN070D2AFcDbwN+MXC8o8UHq8DVgMx4H9dQjtERESWtNkGiPvNbBw4CfQBHy8s/zDwknNuD/AvwBVmtv2cff/aOdfrnDsNPAI85Zx73jk3BXyD/JAIwDeBdWa2rvD654EvOedShddvAh5wzrlpx37OzEbOPIDfnaGO7zjnHi6c+/8GbjSzjmnr/4dzbsg5dwL4FPCBwvIPAZ90zh1xzsXJD+G838x8M5xPRETksjTbAPF251wF+d6GjeT/god8gPgCgHOuC3iI/JDGdL3TnifO8zpW2H8K+DLwc4Whgw8An5+27fmGL652zlWfeQD/fYY6Tp55UggCQ0Dr+dYDx6etay28nr7OR75HREREZNkpdg7EQ8Bngb8ws5uAdcDvFa7O6AGuBz5wCX+Z/xP5v/bvBCadc08AmJkfuB344RyPe8bZ3obClSS1QNf51gOd09Z1ASvOWZfh1WFIRERk2ZjLfSA+RX5Ow8fJv6FvJj+pchuwBYiQnydRtEJgyAF/yat7H24lP1QyNpfjTvMmM7vFzALk50I85Zyb3uvwn8yspjCs8e+BLxWW/wvwm2a2qhA8/pT88ErmEtsjIiKyJBUdIJxz/eSHGq4jP7+hZ9rjKPk3/nOHMYrxOeBK4J+nLZuvyzfvIx98hoBrOOeqEfLzMJ4lP8HyO8DfF5b/A/m6HgaOAkngNxAREVmm7NVzEkvPzD4M/Fvn3C3Tlu0B3l2YrDnX434WOOWc+4MLrHfAOufcobmeQ0REZLkoq1tZm1kE+DXgM9OWBYDPXUp4EBERkflVNgHCzN4A9JOfmHjfmeXOuZRzbqarK0RERGQRld0QhoiIiJS/sumBEBERkaVjpvs1qHtClrWdO3eSzub4/Ne/Szrr8HogEvBRGw0Q8ntL3TwRkYVmF1qhWzGLFDjnODIwweOHB3n66BC7u0b56dEhPAY/9/dP4fd6yOUck+ksY4k0saCPNQ0xtnZUc/2qWm5aW08sqB8pEVkeZpoDoR4Iuawl01meODzID/f08pP9fWSyjivaKlnXWMGq+ih/9hsfwGPw6fu+9ar9cs4xMpnm1PAkR/on2NczxoHeONetquUd29u4e3MTUYUJEVn6LtgDoQAhy07vWJJd+/v4/u5enjo6yMq6KFvbq9nWUU17TRizn/28fPSD9wKvDRDnM5nK8OzxYZ46OsT+nnF2bmjgHdvbuHVdAwGfphuJyJKkACHLVyab47kTI/xkXx8/3t9H10iCre1VXFUIDRUh/wX3LSZATDeWSPPk0UGeOjLEqeFJXn9FM2/f1sYNq2vxeRUmRGTJ0BwIWV6mMlkeOTDAt1/q4if7+6mLBdjaVsX7r+1gXWMFXs8FfybmRWXYz+s3N/P6zc0MxKd46uggf/yvuxmaSHHvtlbefU07m1sqX9XbISKylKgHQi4b2ZzjqSODfP350/xgdw/tNRGuXVnLtStrqIsF53TMufZAXEj3SIJHDw3w2OEBKkN+3rOjnbdvb6OxIjQvxxcRmWcawpDLUy7nePbEMN9+sYvvvNxNZdjPjavruHF13ZxDw3TzHSDOyDnHvu4xHj00wNPHhtnWUc27rmnj9ZubNflSRMqJAoRcPs5cOfHA7h4e3NNLRdjHtStquX51HW3V4Xk910IFiOmS6SzPHh/miSOD7O8Z5/b1Dbz7mnZuXVev+RIiUmoKELK09Y0n+cm+Pn6wu5cnC1dObOuoZseKWpqrFq77fzECxHRjiTRPHhnkiSOD9I1P8bZtrbznmg42t1YuyvlFRM6hSZSytDjn2N87zoN7evnBnl6O9E+wtb2KrR3VvO/ajoteObGUVYb9vP6KZl5/RTPdowkePTjAL/zjT6mJ+Hnn1e28dWvrvPeyiIjMhQKElAXnHCeHEjxzfIjHDg3wyMEBPAbbOmt485UtbG6pXHbd+S1VYd6zo4N3XdPO3u4xnjg8yN/sOkRHTYTXb27i1vUNXNlWhX+Z/buISHnQEIYsqkw2x6nhBMcGJzg2MMGhvjj7e8fZ3zOO3+thQ3MF65sq2NJWRWtVqOSXOS72EMZMMrkc+7rHefHUCLu7xugdS3JFayVXd9awtaOaK1or6aiJ4Fngy1RFZNnQEIYsnmzO0T8+xanhSY4PTnKkP86BvnEO9U1wejhBTdRPS1WYpoogjZUh7trUxC/evIrqSKDUTS97Po+HLW1VbGmrAiCezHCof5zD/RN89vFjHO2fYDKdYV1jBVe0VrKxpZL1jTFWN8SojwVKHshE5PKhACHnlc05pjJZkukcE1MZRhNpRhNphidTDE+kGJ5MMzQxxfBkmpHJ9Nn1I5MpxpIZqsN+6mNBmirzIWFTcyV3bmyipSqs2zrPo1jIx7aOGrZ11JxdNp5Mc3xwkpPDk+za18d9T53g9PAkmZyjpSpEc1WI5sr818aKEHWxAHXRILXRANURP1VhP0GfR2FDRC7qokMYZvYAUL94zYHC+QYW9Yxen99f27bevP6S380nOzmKN1JV6mbMnnM553JZXC6LczmXKzyfw/BXLjkR9ISiUwvQyrK3KLWbeczj9WNev3k8vnJKCPPxfZ8Z6TmUS8ZH56lJi2nxf+eVD9Ve/gacc/ecb8VMcyAWnZk945zbUep2lMpyrl+1L8/aYXnXr9pV+1KlvmQREREpmgKEiIiIFK0cA8RnSt2AElvO9av25Ws516/al6clX3vZzYEQERGR8leOPRAiIiJS5hQgREREpGgKECIiIlI0BQgREREpmgKEiIiIFE0BQkRERIqmACEiIiJFU4AQERGRoilAiIiISNEUIERERKRoChAiIiJStBkDhJkdM7OEmcXNrMfMPmtmscK6z5rZnyx8M0VERKSczLYH4q3OuRiwDdgO/N6CtUhERETKXlFDGM65HuD75IPEq5jZSjNzZvYLZnbCzAbM7P+etv46M3vGzMbMrNfMPnnJrRcREZGSKCpAmFk78Ebg0EU2uwXYANwJ/JGZbSos/5/A/3TOVQJrgC8X31wREREpB7MNEPeb2ThwEugDPn6Rbf/YOZdwzr0IvAhsLSxPA2vNrN45F3fOPTnnVouIiEhJzTZAvN05VwHsBDYC9RfZtmfa80kgVnj+S8B6YJ+ZPW1mbymyrSIiIlImip0D8RDwWeAvij2Rc+6gc+4DQCPwP4Cvmlm02OOIiIhI6c3lPhCfAu42s23F7GRmP2dmDc65HDBSWJydw/lFRESkxIoOEM65fuBzwB8Wues9wG4zi5OfUPl+51yy2POLiIhI6ZlzrtRtEBERkSVGt7IWERGRoilAiIiISNEUIERERKRoChAiIiJSNN8M6zXDUpatnTt3ArBr166StkNEpITsQitmChAiy0oileVQX5xTw5P0jiXJ5hyf/OEBptJZ0tkc2ZzD6zGiQR8NFUFW1EXZ3FJJQ0Ww1E0XEVlUChCyrDnnePHUKD/Y3cNDB/o51BentTpMY0WQkUQajxmnhifxez34PIbXY0xlcowmEuzrGeOrz57i6MAEsaCP61bVcvPaem5aU0d7TaTUpYmILKiZ7gOhIQy57KSzOZ4+NsQPdvfyvVe68Xs9XLOihq3t1axtjOH35qcGffSD9wLw6fu+ddHjOefoGkmyt2eM/T1jvHJ6jIqQj9vXN3DX5iZuWlNPwKfpRiKyJGkIQ5a3I/1xHjrQz8MH+nn62DAtVSG2d1bz23dvoL0mjNkFf0ZmZGa01YRpqwlz16Ymcs5xYmiSF0+O8N+/t4+ukQT3bGnh/dd1sL2j+pLOJSJSLhQg5LJ1cmiSrz57im++0MV4Ms22jmq2tFXx/us6qQz5F+y8HjNW1kVZWRflbdvaGIxP8djhAX79C89RGfbzS7es4t5trQR93gVrg4jIQtMQhlxWMtkcP9nfz+eeOMaLp0a4aU09N62uY01jDE+Rf/nPdghjtnLO8dKpEb6/u5cTQ5N86PpOfv6GFTRWhubl+CIiC0BDGHL5cs6xp3uMb77QxTeeO01tLMDrNjTyy7esLqu5Bx4ztnXUsK2jhlPDk/xwTy93/OVD3LSmjp+7YQW3rK3H49HwhogsDeqBkCUpkcry1NFBfrKvjwf39pHNOW5YXctNa+rpqJ2fKyDmuwfifCZTGR47NMhDB/qYmMryvms7eN+1HbRWhxfsnCIiRVAPhCxtyXSWF06O8NSRQR45OMDurjFWN0TZ0lbFb9yxls7ayJKcnBgJ+Lh7cxN3b27i6MAED+3v4w2fepit7dV84LpO7tzUSMivuRIiUn7UAyFlKZnO8syxYZ44PMBjhwfZ3zNOR22Ejc0VhUcl4cDCvrEuRg/E+Uxlsvz06BCPHhrg2MAEr7+imXu3tnLjmrqzl5iKiCySC/5lpgAhZSGVyfFK1yhPHB7g4QMDvHR6lJV1ETY1V7KhuYL1TRWL/pd4qQLEdIPxKZ44MsjTx4boGU1y+4YG3nBFM7eua6AqvHBXkoiIFChASPmYymQ53DfB3u4xXj49wgsnR9nfM05LVYiNLRVsbqliU0sFkUBpR9jKIUBMNxif4rkTw7x4apS93WOsb6pg5/oGblxTx9aOag11iMhCUICQxZXLOfrGpzg9MsnxwUmODkxwoHecg71xTo0kaK4M0VkboaM2wur6KKsboiUPDOcqtwAxXSqTY2/3GHu6x9jXM8aJoUnWNMTY1lHNlW1VbGypZF1jjGiwvP5NRWTJ0SRKmR/OOSZTWUYTaYYnU/SPT9E7luT0cIITw5OcGk7QNZKkfzxJLOijsSJEQ0WQxsog6xoreN2GRlqrwxrLv0QBn4etHdVs7agG8nNGjg5McHRgggd29/B3jxzh1HCCqrCflfVROmsjdNZGaK4M0VAZpCEWpDYaoCYSIOT3LMkJqCJSWgoQ82x31yj/+mL32dfuTCfOtC9nen0u3vlzZtv8MZzL75dz+RsSTd81f5z8NjnnyObyXzM5RzaXI5N1ZHNnXjtS2RzpTI5UNkcinWUqnSWRzj9PpXNkZ2rYNAbURgPUxQLUx4K0VoW5sq2KumjwvPdgGEtmGOsZn/XxS2kilQXg5dOjJW7J7HUUenVYk+8FGpiYonc0ycmhSV44MczQZJrhidSMXYuRgJdIwEvY7yUc8BL0eQn6PAR8HvxeD35v/oPFfB4P3sKHjJmB1wyPGR6P4fXk731x5mH26j9lzteGM+vN8rcIt+kLz25j3LGxketW1c71n0lE5sFFhzDM7AGgfvGaA4XzDSzyOeeNt7KhzRupap7r/tnJUbyRqvlsUvHygSTnnHPgcjjncC5XeJ5zM0afuckl435PKJZeiGOXu1LWbpgHj8eLebxmHi9mi949VOz3fS45MZgZ6T62cC1aVEv6d94lUu3lb8A5d8/5Vsw0B2LRmdkzzrkdpW5HqSzn+lX78qwdlnf9ql21L1UaiBYREZGiKUCIiIhI0coxQHym1A0oseVcv2pfvpZz/ap9eVrytZfdHAgREREpf+XYAyEiIiJlTgFCREREiqYAISIiIkVTgBAREZGiKUCIiIhI0RQgREREpGgKECIiIlI0BQgREREpmgKEiIiIFE0BQkRERIo2Y4Aws2NmdtdsD2hmK83MmVm88Og1s78xM/+0bQJm9kdmtt/MJszstJl9z8xeP9dCREREZPEsZA9EtXMuBlwJ3Ah8dNq6rwJvAz4M1ACrgP8JvHkB2yMiIiLzZE4Bwsz2mtlbpr32mdmAmV197rbOuT7gh8DmwrZ3AXcDb3POPeWcSxUeDzjn/v3cyhAREZHFNNceiH8BPjDt9RuAAefcc+duaGathfVPFhbdBTzlnDs1x3OLiIhIic01QNwH3GtmkcLrDxaWTTdgZiPAaWCC/LAFQD3Qc2YjM6s1sxEzGzWz5BzbIyIiIotoTgHCOXcI2Au8tRAi7uW1AaLeOVcNRIDHgAcKyweBlmnHGipsdw0QnEt7REREZHFdyiTKM8MYbwP2FELFazjnEsBngRvNrB74EXCtmbVfwrlFRESkhGYbIPxmFpr28AFfBF4P/Cqv7X04y8yCwM+TH7YYdM79APgJcL+ZXV+4pNMP3HBJlYiIiMiimW2A+C6QmPb4hHOuG3gCuAn40nn2GTGzONBL/jLOe51zrrDuncC3gX8GRoCjwIeAe+ZWhoiIiCwm+9l7uoiIiMjs6FbWIiIiUjQFCBERESmaAoSIiIgUTQFC/v/27js8zuu88/73ngIMBoPeCwESLCIpUSyiKFLNdJVs2bTsuEWyrbR3d7PK7maz2d04PbvZ3XfTXq8TO1mn2E5iOY677NiyZNm0erdEsZMgQQJE7xi0wcyc948ZyBAFEBi0mSF+n+t6Lsw87dw3MMDcOOc8z4iIiKRMBYSIiIikzDfPdl2iIWvCxFSMofEpJqZifOjQnRjwlW9/n7wcL6FcHwG/N90hioikg821Yb4CQuSq4ZyjY2iCo5eGONExzImOEZp7wnQMTTAZjRHK9ZHr93KyYwRwfOCvnmJyKs5oJIrXY1QVBthQns+OuiL2ri/lxvUlBHP0KyQia9N894FQD4RktfO9ozx2uocnz/by4oUBYnFHU0WIdaV51JcEqS0KUFGQSyjXh1mi0L7/nkMAfPqBB4FE4TE+FaMvHKFjaIKW3jCnu8Oc6x1lb2MJ77m+ljt3VFMY8KctTxGRFaIeCFk7zvWE+cZLl/j2kQ5GJqbYua6IrdWF3LWjhoqC3NcKhYUyM4I5PoKlPtaVBtm3oRSAsUiUl1sH+fpP2vhv3znOwWsq+Nj+RvZtKE25DRGRbKMCQq4K0Vich4938XdPnqe5O8zNm8r5xVs3sLEif8XezIM5Pm7eWM7NG8sZmZjiibO9/KevvEKe38sv3rqBu3fXae6EiFy1NIQhWW1iKsY/PXeRzz52juJgDm/bVsWN60vweRd/gdHlQxipcM7x6qUhHjnexdnuMO/fU8fP7mtgc1XBouMREUkjDWHI1aUvPMk/PnOBLzx9gU2VIf71mzayJQPepM2M6+uLub6+mK7hCQ6f6uYjn32G8oJc3nVdNQevqeS6uiK8Hg1xiEh2UwEhWSMWdzxzro8vP9/KD092s29DCZ9451bqS4LpDm1WVYUBPnxjAx+8YR0nu0Z46cIAX32xjaHxKW7cUMrNG8vZ31TKtupCPCooRCTLqICQjBaJxnn6XB/fe7WDh493URrM4eZNZfzph3ZmzVUPHo+xvaaQ7TWFQCP9oxFOdAzzTHMvn3vyPMPjU+xvKuPgNZUcvKaC2uK8dIcsIjIvzYGQjDMZjfHY6V6+c6SdH57spq44jz0NJdy4vpTqosCKt7+UORCL0T8a4eilIY61D/Fy2yDVhQHuvLaaO66rZntNoa7oEJF0mvMPkAoIyQjjkRiPn+nhX17t4Icnu2ksDSZv1lRKaX7Oqsay2gXETPG443TXCC9eHOClCwPEnOMtWyt505ZKDjSVURTMjl4XEblqqICQzDIZjXGiY4Tnz/fz2JkeXrwwwKbKEHsaSti3oZSS4OoWDTOls4CYyTnHpcFxXmkb5NilYU51jSR6YxpLuKGhhOvqithcFcK/hCtORETmoQJC0iMeT7wJnu0Jc7YrzInOYU50DHO+d5Saojy2VIXYVl3ItXVFhHIzY0pOphQQl4vG47T0jnGme4QLfWOc6w3TPTzJhvJ8ttUUsLW6kE2VIZoqQtSX5KmwEJHloMs4ZflNxeIMjEXoH43QH47QOxqhe3iCjqEJLvaP0tI7RuvAGPm5PuqL86hNLh+5sYGG0qBuspQin8fDpsoQmypDr62bmIrR2j/GxYExjrQN8f1jnbQPjtM3GqE8lEtdcR51JXk0lAapK86jpjiP2qIAlYUBCgM+za8QkUVTAZHlnHM4B3HniDlHPA4x54jFHNF4nGjcMRWLMxVzRKe/xhNfY/HkuumvsTiRmGNyKsZENM5EJMZoJMrIRJSBsQiDY1OJYmE0wsBYhLFIjMKAj8KAn4KAj8I8P0V5fkqCOWyvKeLN11RRXRggL0eFwkoJ+L1srip4w42qorE4veEIPeFJesOTtA+Oc6x9mP7RCH2jk/SHI0zFHMVBP8VBP4UBP/m5PkLJpSAv8XOdfh7M9ZKf4yPX7yHg95Lj9ZDr8+DzevB5DL/Xg89reM3weAyvxzDADCz5D4zDEZ+lT9OT3MfjAY9ZckHFjUiGu+IQhpk9BJSvXjiQbK93pRvxBAqKfcVVG1e6nVTFxobwBovSHcbCzDP+larY2DDeYOFynjJrpCX3DHqHXo7XfaTz7IvLFM5qW5W/eRlKuWe+XufcnbNtmG8OxKozsxecc3vTHUe6rOX8lfvazB3Wdv7KXblnK82yEhERkZSpgBAREZGUZWIB8dl0B5Bmazl/5b52reX8lfvalPW5Z9wcCBEREcl8mdgDISIiIhlOBYSIiIikTAWEiIiIpEwFhIiIiKRMBYSIiIikTAWEiIiIpEwFhIiIiKRMBYSIiIikTAWEiIiIpEwFhIiIiKRMBYSIiIikTAWEiIiIpGzeAsLMWsxs3MzCZtZpZp83s1By2+fN7A+Tj9ebmUvuN728MuM8NWb212bWntx2Lnn81nnav/y8XWb2GTPzz7LvYTMbMLPcy9YXm9kXzKw7ufz+Ar8/IiIiMouF9kC8xzkXAnYBu4FPXGHfYudcKLnsBDCzMuApIAjcBhQAe4AfA29fYAzFyRh2AAeA+2duNLP1yXM74NBlx/5/ybbXA/uAj5nZzy+wXREREbmML5WdnXOdZvZ9EoVEKv4jMAx8zDkXT64bBD6X4nlwznWb2SPA9ss2fRx4BngWuA/4yoxt7wHe6ZwbA1rM7G+BX1hM+yIiIpLiHAgzqwfeCZxNsZ23Ad+YUTwsmpnVAneQKBZm+jjwxeRyh5lVXX7oZY+vW2osIiIia9VCC4hvmtkI0Ap0A793hX17zWwwufx6cl050Dm9g5kdSm4fMbOHFxhDr5kNApeAUeCrM853K9AI/LNz7kWgGbhnxrEPAb9hZgVmtolE70Nwge2KiIjIZRZaQNztnCsADgJbSRQEcyl3zhUnlz9JrusDaqZ3cM496JwrJjG0kbPAGMqTxwSBJ0kUBdPuAx52zvUmnz+QXDft3wPjwBngW8CXgLYFtisiIiKXSWkIwzn3Y+DzwJ/Ms+vlHgXuNrMlXzbqnBtPxnDAzMrNLA/4EPCm5FUinSQKk51mtjN5TL9z7l7nXLVz7loSeT+31FhERETWqsW8oX8SeLuZ7UrhmD8DSoB/MLONllBA6pMxSV6i+TESQyJ9wN1AjMSkyl3JZRvwOIl5ESTbLDMzr5m9E/hXwB+m2raIiIgkpFxAOOd6gL8HfieFY3qB/cAE8AQwArxM4nLOX17gaQbNLAx0kbiM85BzzpEYqvicc+6ic65zegH+ArjXzHzADcCryXb/F3Cvc+7YQuMXERGR17PEe7CIiIjIwulW1iIiIpKyjCggzOzey26BPb1omEFERCQDaQhDREREUjbfraxVXciac/DgQQAOHz6c1jhERDKAzbUhpc/CELlaOOdo7R/nZOcwF/vH6BiaoHdkkqGJKY61DxOPO976p4eZiiVqaK/HCPg8FAX9VBYEWF8WZHttITc0llJRkDtPayIiVx8VELJmDI1N8cNTXTxyvItnmvswM9aX51NZkEtJMIea4gCbckI8nZ+Dx+Bf3b4Rr8cwIBZ3RGJxRiejDIxFaB0Y56nmPn79K0doLAvyvt11/MyeekryF3pjVRGR7KYCQq5qfeFJHj3RzYOvtPOTiwNcW1vEznXF/P6hmjl7DvJzvAA0lM7/cSmxuON4xzCPnenlkz84w6GdtfzywY2sW8CxIiLZTAWEXFViccerl4Z4/EwPj57o5kzXCNfXF7F3fSm/eOsGAn7vsrbn9Rg76orYUVfE4FiEh493cdefP86btlTwy2/axPbawmVtT0QkU8x3FYYmUUrGG56Y4tETXTx8rIsnz/ZSHMzhurpCrq8rZltNITm+1K5Wvv+eQwB8+oEHFxXPWCTKD04khkoay/K5Z18Dd1xXTShX9bqIZJ05J1GqgJCsFI87nmru4x+fucDjZ3q4traIXQ3F7KwvpnSJ8xCWWkBMi8bjvHhhgCfO9HKiY5h9G0p52/Yqbt9coSEOEckWugpDrg7hyShfe7GVzz95AYfjzVsr+eRHdmfkf/c+j4ebNpRx04YywpNRXmkd5OFjXfzxQ6coyvNz8JoK3rKtiv1NpeT6lndoRURkpWXeX12RyzjnONY+zAPPXuTbR9q5rraQjx5oZFt1AWZzFscZJZTr45ZN5dyyqZy4c1zoG+OVtkH+3++doLV/nNs2l/Pu62t5y9ZK8nJUTIhI5tMQhmQk5xJXNzx8rItvv9LOWCTKbZsrOHhN5ZKHKOazXEMYCzU0PsULF/p5oWWAs91h3rK1kg/cUM8tm8rxerKjQBKRq5aGMCSzOedo6Rvj+fP9PNncy1Nn+/B5jT2NJXz8wHq2VIWyprchVUV5ft66tYq3bq1icCzC0+f6+G/fOc7Q2BTv3V3L+3bXsb2m8KrNX0Syk3ogJC0i0TivXhri+ZZ+nj3fx8sXB/F5PWytLmBLVQHX1hZSXRhIy5vmavdAzOXSwDhPnO3lmXO95Pq83HFdNW++ppI9jcWaMyEiq0VXYUh6dY9McKR1iBcvDPBcSz/H24epLQ6wpaqAzZUhtlQVUBbKjFtCZ0oBMc05x7neUV66MMDR9mFa+8fYXlvInoYSdq0rZkddEetK89RDISIrQUMYsvImpmJ0D09yaXCcC32jnO0Jc7JjhJOdw0SicTZWhGiqyOcd26v4twc3EszRy28hzIyNFSE2VoT4IIn7TJztDnO2J8wXnmrhfO8oE9EY11QVsL22kK3VhTRV5NNYFqSyIKB5FCKyIvQXfA1zzjEZjROejDI6GWVkIvF1NBJlLBJjLBJjcir22uPRyE/3C09GCU8kHo9MRhkajzA5Fac0P4eKglwqC3KpLAywv6mMD+2tpzyUq/+Ql0kwx8f19cVcX1/82rrh8Sla+ka52D/GD0500fnMBJ3DEwyPT1Gan0Npfg7FQT9FeX4KA34K8/wUBHyEcn0UBhKPCwJ+8nO95Of6yPN7Cfi9BPweAn4vfm9qN+MSkavfFYcwzOwhoHz1woFke72r3OZrvEWV67x5hZXpaj82NoQ3WJSu5hfOAcTjzrkYLh7HuZiLx2NLOWV8Iuz3BEJTyxNgdlmp3M3MMI8Pj8dr5vFilpGVwGq87uOTowPRgY5zK9rI4qT1b16aKffM1+ucu3O2DfPNgVh1ZvaCc25vuuNIl7Wcv3Jfm7nD2s5fuSv3bJWR/42IiIhIZlMBISIiIinLxALis+kOIM3Wcv7Kfe1ay/kr97Up63PPuDkQIiIikvkysQdCREREMpwKCBEREUmZCggRERFJmQoIERERSZkKCBEREUmZCggRERFJmQoIERERSZkKCBEREUmZCggRERFJmQoIERERSdlVW0CY2TEzO5juOERERK5G8xYQZtZiZm+bY5uZ2TkzO778ob2hrVoza5srJjP7OTN7Yvq5c+5a59zhlY5LRERkLVpqD8TtQCXQZGY3LkM8V/Iu4KEVbkNEREQWYKkFxH3At4DvJh+/xswOm9kfmtlTZhY2s2+bWZmZfdHMhs3seTNbn9z302b2p5cd/20z+9UZq96VbGdBZvZSmNnvm9lXzezLZjZiZi+Z2c7L9v2EmR03swEz+5yZBWZs/3/M7KyZ9ZvZg2ZWu+DvkIiIyFVo0QWEmQWBDwBfTC4fMbOcy3b7CPAxoA7YCDwNfA4oBU4Av5fc7wvAz5qZJ3nucuCtwJeSz/0kejseWWy8wHuBryTbfgD4ZvK80+4F7kjGuQX47WTbbwH+F/AhoAa4APzTEuIQERHJekvpgXg/MAk8DHwH8AF3XbbP55xzzc65IeB7QLNz7gfOuSiJN/PdAM6554AhEkUDJAqPw865ruTz24FXnHMjM879TTMbnF6Az8wT74vOua8656aAPwMCwP4Z2//COdfqnOsH/gfws8n19wJ/55x7yTk3CXwCODDdeyIiIrIWLaWAuA/4Z+dcNPnG+nUuG8YAumY8Hp/leWjG8y8AH00+/ijwDzO2zTZ8cbdzrnh6Af7tPPG2Tj9wzsWBNqB2tu0kehmmt9Umn08fGwb6SPSqiIiIrEm+xRxkZvXAW4B9ZvYzydVBIGBm5c653kWc9h+Bo8m5CduAb87Y9i7gfYuJdYZ10w+SQyX1QPts24GGGdvagcYZx+YDZcClJcYjIiKStRbaA+E3s8D0Avw8cBq4BtiVXLaQ+K/+Z+c6yZU459qA50n0PHzNOTcOYGYbgFzn3MnFnHeGG8zs/WbmA36VxPDLMzO2329m9WZWCvwm8OXk+geAnzezXWaWC/xP4FnnXMsS4xEREclaCy0gvktiyGF6uQ/4jHOuc+YC/BVvHMZIxReAHbx++OIuUrj64gq+BXwYGCAxsfP9yfkQ0x4gMZ/jXHL5QwDn3KPA7wBfAzpITLL8yDLEIyIikrXMOZfuGF5jZreTGMpYn5yngJl9l8QEx0UXEWb2+8Am59xH59jeAvySc+4Hi21DRERkLcmYW1knL6n8D8DfTBcPSYeBH6UlKBEREZlVRhQQZrYNGCRxn4VPztzmnPuj6fkQIiIikhkyaghDREREskNG9ECIiIhIdpnvPhDqnpCr3sGDB4nGHF/61vcwg4KAn8KADzNLd2giIuk25x/CRd1ISiSbtfaP8XRzH8+19HOkbZDnzvdjBh/4q6eIOxidjOIcNJQG2VQZYnttIdfVFbGrvpiioH/+BkRE1gAVEHLVm5iK8fS5Pn54opvDp7oJT0a5traIzVUhPn5gPd1fKsBj8MkP737tmLFIlI6hCdoGxjnRMcxDRztp7glTW5THrZvLece1VexbX4rPq1FAEVmbVEDIVal/NMIPTnTx/WOdPN3cx/qyfHauK+L+N2+ioTT4uuEJzywddMEcHxsrQmys+OnHtcTijvO9oxy5NMjvfusY/eFJ3r2zlg/tXcd1dUWrkZaISMZQASFXjaHxKb73agfffPkSr7YNcX19EbsbSvjw3nUUBJY+9OD1GJsqQ2yqDPH+3fV0Dk3w5NkefvELz1Oan8NH9zfy3l11hHL1ayUiV7/5LuPUJErJaJFonMOnuvnaS208caaXHfVF7G8qY9e6YnJ93gWd4/57DgHw6QceXFQM8bjj1UtD/OhUN8fbh7nzumruuamBXeuKNRFTRLKdJlHK1SMSjfNUcy/fOdLBw8c6WVca5EBTGf/nI7vJT8N//x6PsXNdMTvXFTMwFuGx0z3c/8WXCPi9fOCGeg7tqqW+JLjqcYmIrCT1QEhWGBqb4vDpbh462skTZ3upL8ljb2Mp+zaUUh7KXdK5l9oDMRvnHKc6R3iquZfnWgZYV5rHe66v5V07alhXqmJCRLLGnD0QKiAkY10aHOeRY51872gnr14a4traQnatK2FPQzHFwZxla2clCoiZovE4x9uHeb6ln+dbBmgoDfIze+o4tKuO0vzly0NEZAWogJDMNz2X4AcnunjkeBftg+PsaShhT2MJO+qKCPgXNqchVStdQMwUjcc5emmYp5p7+cnFQW7ZVMY9NzVy26ZyPLNdDiIikl6aAyGZxzlHa/84T5/r5bHTvTx5tpeCgI9d64r54N51XFNVgPcqe1P1eTzsWlfMrnXFjEWiPHm2l//+7eOMRqJ88IZ6fuaGehrL8tMdpojIvNQDIasmFnec6R7hhZYBnj2XuBPkVMxxbW0h26oTd3usKFjafIbFWM0eiLmc7x3l8TM9PN3cR11JHnftqOGt26rYUhXSlRwikk7qgZDVNTAaobknzJnuMCc7hjnaPsyJjmGKg362VBawuaqA/3rHVqqLAnqDBDaU57OhPJ97b2rkeMcwL13o5++fbiEWhwMby7h5Yxl715fSVJ6voQ4RyQjqgZBFi8Ud7YPjnO8dpbknzOmuEU53hTnXEyYSjVNfGqS2KEBtcR4NpUE2lOcvyw2dllsm9EDMxjlH1/AkxzqGON05wumuEUYjMbZWF7C9ppDNVQVsKM+noTRIdVEAv26rLSLLTz0QsjDOOSam4oxMTjE8HmVwLEJvOEJPeJKuoQkuDY5zaXCc9sFxuoYnKM7LoaY4QE1hgOqiPO64tpq64jxKgn71LCyRmVFdFKC6KMBbt1YBibtttvSO0jowxuFT3Xz5+Qk6hycZGI1Qmp9DVWGA6qJcaoryqCoMUBHKpbwgh7L8XErzcyjJzyE/x6ufjYgsmQqIBfjGT9r44jMX37B+untmuhfHAdMdOo6fPnFA3DmcS6xyM455wzlnrHa4158vedx0O7G4++niHLFY4mvcOeJxR9xBzDmisTjxJfYleT1GSdBPaX7izWhPQwlloZw3/NfbG56kNzy5tMZW2eD4FAA/OtWd5kgWLj/XR1NFiKbkZ3XE446BsQh94Qhdw5Oc7AwzOBZhZCK6qPP7vUaOz4Pf48HrMXxew2uGmeHxgCX/KTH76b8nZsm1yXVmhscS+15er3hmnOe1cySPn3nOK71sp9uYfjzTR/c3cvfuukXlLiILc8UhDDN7CChfvXAg2V7vKrd5Rd6iynXevMLK1WgrNjaEN7hCH8zkEiWMc8Rx8Tg4h3MxnIs75xLrnIu/voxZPfHJsYAnNziRjrbTbXVzN8Pj8Zl5PJjHi5lnejHMk47uieV+3cfGhrtjw92ty3bClZVxf/NWkXLPfL3OuTtn2zDfHIhVZ2YvOOf2pjuOdFnL+Sv3tZk7rO38lbtyz1aadSUiIiIpUwEhIiIiKcvEAuKz6Q4gzdZy/sp97VrL+Sv3tSnrc8+4ORAiIiKS+TKxB0JEREQynAoIERERSZkKCBEREUmZCggRERFJmQoIERERSZkKCBEREUmZCggRERFJmQoIERERSZkKCBEREUmZCggRERFJ2YILCDM7bGYDZpZ72fp7zOwFMwubWYeZfc/Mbp2xfYuZfcXMes1syMyOmNmvmZl3ORMRERGR1bOgAsLM1gO3AQ44NGP9rwGfBP4nUAU0AJ8B3pvcvhF4FmgFdjjnioAPAnuBgmXKQURERFbZgj5My8x+F7iDRDGwxTn3bjMrAi4BP++c+8ocx/0jUOKcu2sZYxYREZE0W+gQxseBLyaXO8ysCjgABIBvXOG4twFfXVKEIiIiknF88+2QnM/QCPyzc67XzJqBe4BuoNc5F73C4WVAx7JEKiIiIhljIT0Q9wEPO+d6k88fSK7rA8rN7EpFSB9Qs7QQRUREJNNccQ6EmeUBnYAXCCdX5wLFwC7gSeDnnHOzDlMk50AUO+fevXwhi4iISLrN1wNxNxADtpMoGHYB24DHScyL+F3g02Z2t5kFzcxvZu80sz9KHv97wM1m9sdmVg1gZpvM7B/NrHi5kxEREZHVMd8ciPuAzznnLs5caWZ/AXwKqAe6gN8mMcFyBHgR+B8AzrlmMzsA/CFwLDnc0QJ8LrmviIiIZKEFXcYpIiIiMpNuZS0iIiIpUwEhIiIiKVMBISIiIilTASEiIiIpm+8qDM2wlKvewYMHATh8+HBa4xARyUA214Z5b2UtcrUZj8QYi0RxQChXvwIiIouhv55y1QpPRjnSOsjLbYMcbRviTHeYtoFxYnFHXo4XSBQTl1r68Xs93Pd3z7GpMkRTRT4byvNpKg9RVZiL2ZwFuIjImqUCQq4aPSOTPHu+j2fP9fPc+X4u9I+yoTyfDeUh1pfnc+vmCqoKc8nze18rCpxz/PIjIaZijhsaS+gYmuBHJ7t5YGiC9sFxIrE4mypC7Kgr4sYNpRxoKqOyMJDmTEVE0k8FhGStSDTO8y39/PBkNz8+1UPn8ATbagrYXFnAvTc1sL48H7/3yvOEzQyvGV6fceP60jdsH5mYorV/jHO9ozzw7EV++5tHqS3O453XVvPe3XVsKM9fqfRERDKaCgjJKuHJKD862c33jnbw+Jleaory2FlfxH03r6epPB+PZ3mHGwoCfrbXFrG9tgiAWNxxumuE51v6ed9nnqSxNMi9NzXy7p01BHP06yQia8d8t7LWVRiSduHJKA8f6+TBl9t5rqWfbTWF7F5XzA2NJRQHc5Z8/vvvOQTApx94MKXjYnHHy62D/Ph0Nyc7R3jXjho+cuM6dq0r1rwJEbla6CoMyS7OOV66OMjfP93Coye62VZTwL4NZXzsQGPG/Kfv9Rg3NJZwQ2MJ/aMRHjvdw/0PvITP4+Hd19fw9u1VXF9fjHeZe0VERDKBeiAko8Tiju8f6+QvDzfTG57kLVsruX1zBYV5/hVrc7E9ELNxznGud5TnzvfzStsgg2NT3LShlFs2lbNvQynXVBUs+zCLiMgKUg+EZLbRyShffbGVv378PPm5Pu66roYbGkuy7s3WzNhYEWJjRYif3ddAX3iS4x3DPHa6h//7WDPhiSh715dy++Zybt1czsaKkIY7RCQrqYCQtHHOcax9mC8/38q3Xr7EtppCfunWJrZUXT1vqmWhXG7bXMFtmysA6B+NcKJjmMfP9PKZw80A3La5nNu3VHDzxnIqCnLTGa6IyIJpCENWVTzuONo+xMPHuvjOkQ4mpqLcuqmc27dUpu3NczmHMFLhnKNjaIJXLw1xrH2I4x3DVBYE2LehlL2NJexuKKapPJR1vTAiclWZ8w+QCghZUdOXPb5wYYCnm3t5urmPUK6P3Q2JyYebK9Pf25CuAuJysbjjQt8op7vCNPckluGJKbbXFLK7oYSd9cVcX19EfUle2r9nIrJmaA6ErLypWJwzXWGOtQ9x9NIQr7QNcbprhNL8HDZXhthcVcAfHKpRN/0cvB6jqSJEU0XotXUjE1Oc6xmluTfMF546T3PvKFOxONuqC7muroit1QVsqSqgqSKfgsDKTTQVEbmcCghZsKlYnKHxKQZGI/SMTNIxNEFr/xhnusOc7hrhQv8YVYW5NJbm01Aa5K4dNfzKmzeRrw+sWrSCgJ+d64rZua74tXUDYxFaeke52D/Gt19p59LgOO2D4wT8XhpKg9SXBKkryaO2KEBlYYDyUC6l+X6KgzkU5fnnvTuniMhCZNVf9u6RCQZGp96w3qU40mIzemSW69iZI0HOXfm8l5/j8mNnnjtxrsR4edwltsRdYi5B3P10fdw54i5xrnhyXSzuiMUd0XicqZgjGoszFXdMReNEYnEi0TgTUzEmpuKMRaKMTkYJT0YZmUguk1OEJxLr4jNiLMj1URT0U5afQ3kol+qiAO/bXUd9SR45Pu/rco3GHUPjb/yZZZJoMrlMj3Oax97YU+GcY3B8iq7hCXpHIrT2j3GkbZCh8SmGxqaSP8/oa/sbEMz1kp/jI5jjJZjrIz/HS36uj/wcH/m5XoI5PgJ+LwG/h1yflxyfB7/X8Hk8+DyGN7l4PMnbgXsSsU2v81jile4xw2OJK1Q8xmvbvJ7k8+RwjMeM2UZmrjzKOruZ57n8nHZZj+ymypDu1SGyCFecA2FmDwHlqxcOJNvrnW1DTvWmG1Y5llUXGxvCGyxKdxhv5JxzzsVZwXkx8fFhjyevML5S589kq5i7mZkn0yZRpPN1Hx3uaYmPDfWlpfGEOf/mrQHKPfP1OufunG3DfJMoV52ZveCc25vuONJlLeev3Ndm7rC281fuyj1baTBUREREUqYCQkRERFKWiQXEZ9MdQJqt5fyV+9q1lvNX7mtT1ueecXMgREREJPNlYg+EiIiIZDgVECIiIpIyFRAiIiKSMhUQIiIikjIVECIiIpIyFRAiIiKSMhUQIiIikjIVECIiIpIyFRAiIiKSMhUQIiIikjIVECIiIpKyeQsIM2sxs3EzC5tZp5l93sxCyW2fN7M/TD5eb2Yuud/08sqM89SY2V+bWXty27nk8Vvnaf/y83aZ2WfMzD/LvofNbMDMcuc4V46ZnTSztivkGDazh+f7voiIiKxlC+2BeI9zLgTsAnYDn7jCvsXOuVBy2QlgZmXAU0AQuA0oAPYAPwbevsAYipMx7AAOAPfP3Ghm65PndsChOc7xn4HuOba9Z0bc71hgTCIiImuSL5WdnXOdZvZ9EoVEKv4jMAx8zDkXT64bBD6X4nlwznWb2SPA9ss2fRx4BngWuA/4ysyNZrYB+Cjwa8Bfp9quiIiI/FRKcyDMrB54J3A2xXbeBnxjRvGwaGZWC9xBoliY6ePAF5PLHWZWddn2Pwd+Exif49RfNLMeM3vYzHYuNU4REZGr2UILiG+a2QjQSmII4PeusG+vmQ0ml19PrisHOqd3MLNDye0jKcw36DWzQeASMAp8dcb5bgUagX92zr0INAP3zNj+PsDnnPvGHOe+F1ifPMePgO+bWfEC4xIREVlzFlpA3O2cKwAOAltJFARzKXfOFSeXP0mu6wNqpndwzj3onCsmMbSRs8AYypPHBIEngYdmbLsPeNg515t8/kByHWaWD/wR8O/mOrFz7knn3Lhzbsw5979IDK/ctsC4RERE1pxU50D82Mw+D/wJcHcKhz4K3G1mf7DUYQzn3Hgyhl83s3ISvREfArxmNt3LkQsUJ4cijETvwuNmBomCpSi5737nXMtszSSPExERkVks5j4QnwTebma7Ujjmz4AS4B/MbKMlFJD6ZEySl2h+jMSQSB+JQiZGYlLlruSyDXicxLyIo8C6Gdt+CehKPm41swYzuyV5iWfAzP4ziR6WJ1ONTUREZK1IuYBwzvUAfw/8TgrH9AL7gQngCWAEeJnE5Zy/vMDTDJpZmMSb/wHgkHPOkRiq+Jxz7qJzrnN6Af6CxNwGLlvfD8STz2PJGP4SGCAxv+JO4J3Oub6F5iciIrLWWOI9WERERGThdCtrERERSVlGFBBmdu9lt8CeXo6lOzYRERF5Iw1hiIiISMoyogdCREREsst894FQ94RkrVjc0do/xt13vYOpaJz//KkHiDvI8XkoCPioCOVSW5xHXUkefq9qaRGRWcx5T6SUbiQlkqlicUdzT5iXWwd5pXWQI21DnOkeoSjPT1v/GD6vh2fO9WFmRONxxiIxhsen6BmJ0D8aYX15kBsaS7hlUzm3baqgKPiGT4sXEZEZ5psDoR4IyUjRWJxX2gZ54kwvT5/r49VLQxTl+dlUEaKxLJ+m8nwayoIEc3zcf0/i090//cCDs54rEo1zsX+U011hTnQMc7xjmOvri3j39bXceV015aHc1UxNRCSTzNkDoQJCskYs7njibC/f+sklHj3ZTVl+DttrC9lWXcjmqhAFgdl7DeYrIC43MRXjlbZBXmgZ4OXWAa6rK+LQzjretaOa4uBCP7pFROSqoAJCslf74DhfevYi//R8KyX5fvY3lbFvfSllC+wZSLWAmCkSjfNy6yDPnu/jldZBbmoq48M3ruMtWys1b0JE1gIVEJJdnHM8e76fv3viPE+f6+PmjWW8ZWsVDaXBlM+1lAJipvFIjOda+njsdC/dIxN85MYG7rmpgdrivCWdV0Qkg2kSpWSH7pEJvvWTS3zpuVai8Thv3VbF//nwbvJyvOkOjbwcL2/aUsmbtlTS2j/GD091c+cnH2PfhlI+fmA9t24qx+PRh7iKyNqgHghJu77wJA8f7+LBV9p5tW2QvetLuX1zBVurC0h+BPuSLFcPxGwmpmI8cbaXH53sZjIa596bGvjg3nVUFGjipYhcFdQDIZmlY2ic7x/t5F9e7eB4+zA71xWzb30p//r2JnJ96e9tWKiA38vbtlXx1q2VNPeE+dGpbj5zuJnbNpfzsf2N7G8qU6+EiFyVVEDIqnDOcborzMPHO3noaCet/WPsaSjh9i0V/MqbN5Pjy+4JiWbGpsoCNlUWcM++KE+c7eU3v/EqUzHHB2+o572769hQnp/uMEVElo0KCFkxE1MxnjvfzyPHu3j0RBcx59jTUMLdu+rYWlOAz5PdRcNc8nN93HFtNe/YXsW53lGePNvLz/zlU5QGc3jz1kpu21zODY0l5Ofq109EspfmQMiyicUdpzpHePZ8Hz8+1cNzLf00lAbZua6Y3euKaSgNLsuchlSt5ByIhYon75R5pG2QE50jnOsZpakiP3FJ6oZS9q0vpSRf95gQkYyjORCyfOJxR9fIBOd7RmnuCXOyc4TjHcOc6hyhND+HrdUF7Kgv4p6bGua8udNa4/EYm6sK2FxVACTuL9HcE+ZU5wh/dbiZ/9j1MtWFAfauL2VvYwk76ovYXBnCp3tNiEiGUg+EvI5zjuHxKF0jE3QPT9I1PEHXyASXBsZpGxinbWCMtoFx8nN91BYFqCkOUF2YR0NpkPVl+YQCmVeTZkIPxHxicceFvsTttM/1hjnfO0pveJINZflcU13A1ppCNlWE2FCRT31JXlZNNBWRrKYeiKtVLO6YjMYYj8SYiMaZmIoRicaZiiWWSNQRicWZnIoxPpXYbzQSY3QyytD4FANjEQZGEx8o1ROO0BuexO8xSvNzKMnPoTjPT3HQT0kwh72NJbzzumoqCwIZcV+Gq4nXYzRVhGiqCL22bmIqRtvAGBf7xznSNsTDx7roHBqnJzxJSTCHmqIA1UUBKkK5lBfkUpTnpyDgJ5TrI5TrIy/HS57fS16Ol4DfQ67PS67PQ47Pg89jaRlOEpGrxxV7IMzsIaB89cKBZHu9q9zmG5gvN+AvX3ftarcbGxvCGyxa7WYBcC4eIx6P4lw8He3HJ0Z8nkBBNB1tp1uKuRser988nqumilvM6z461HM+Pj7Uv0IhraaM+JuXJso98/U65+6cbcN8QxirzsxecM7tTXcc6bKW81fuazN3WNv5K3flnq00Q0tERERSpgJCREREUpaJBcRn0x1Amq3l/JX72rWW81fua1PW555xcyBEREQk82ViD4SIiIhkOBUQIiIikjIVECIiIpIyFRAiIiKSMhUQIiIikjIVECIiIpIyFRAiIiKSMhUQIiIikjIVECIiIpIyFRAiIiKSMhUQIiIikrJ5CwgzazGzt1227qCZtc14ftjMJswsPGM5kNxmZvYrZnbEzMbMrDO5/0eWPx0RERFZDcvZA/ErzrnQjOXp5PpPAb8K/CegDKgDfhu4cxnbFhERkVXkW8mTm9kW4N8CNznnXpix6YnkIiIiIllopedAvAVovax4EBERkSy3nAXEp8xsMLm8lFxXDnTO3MnM2pL7TJhZ4zK2LyIiIqtkOYcw/r1z7m8uW9cH1Mxc4ZyrNzMfMAXYMrYvIiIiq2SlhzB+CNSb2d4VbkdERERW0UILCL+ZBaYXFthz4Zw7Bfxf4J/M7O1mlmdmXuDmRcYrIiIiGWChQxjfvez5kym0cT/w74A/AzYBg8Bp4MPAxRTOIyIiIhnCnHPpjkFERESyjG5lLSIiIilTASEiIiIpUwEhIiIiKVMBISIiIimb7yoMzbCUrHbw4EEADh8+nNY4RESy1Jw3fFzRD9MSWWkTUzFeujDACxcGON4+zMWBMQZGI0SicQDOXBzAa8ahP3+CoqCfyoJcGkqDXFNdwJ7GEioLAmnOQEQkO813Gad6ICTjdA5N8IMTXTx8rJMXLgzQUBpkS1UBDaVBqgpzKQj48XsTo3P/9Rfej3PwX/78S4xMRBkcj9A7MknbwDgnO0eoLQ7wnp21vG93HfUlwTRnJiKScdQDIdnLOcfJzhG+f7STh4930jowzq51xexeV8zHD6wnP3ful3FOspDYUlXwhm3xuONU1wjPnuvjrx8/x3W1RdxzUwNv315Frs+7YvmIiFwN1AMhGau5J8w3X7rEt15pZzIaY29jKbsbirmmugCfZ2Hzf++/5xAAn37gwSvuF4nGeb6ln8fO9HChb4y3b6/irh01HNhYRsCvYkJE1iz1QEh2GBiN8J0j7Xz5hVbaByc40FTGv7q9iabyfMxW7sNbc3webtlUzi2byukNT/Ls+T7++PunaOkb5cb1pbz5mgredE0lG8rzVywGEZFsogJC0m48EuPRk118/aVLPHe+n53rirhrRw076orxelb/E9/LQ7nctaOWu3bUMjIxxdFLQzx2poc//+FZ8nN9id6J62vYva54RYsaEZFMpgJC0iIedzzX0s9XXmjl4WNdbKwMsb+pjHtvaiCYkzkvy4KAnwMbyzmwsRznHC19Y7x4oZ//8KWfEI077t5Vx/v31LF5ljkWIiJXM82BkFXVPjjOV19o48svtOL3GrduLufmjeWUBHNWpL2FzoFIlXOOi/1jPHm2l6ea+6goyOXu3XXctaOGdaW6mkNErhqaAyHpMxaJ8vCxLv75hVaOXhriQFMZv3xw44rPa1hJZkZjWT6NZfl85MYGjncM8+z5Pv7ycDPVRQHevq2KN2+tYGd9MT6vbvgqIlcf9UDIihiPxHjsTA/ffqWdw6d6uKa6gANNZdy4vpQc3+q9oa5UD8RcYnHH6a4RXm4d5NVLQ/SFJ9nfVMbBayq5bXO5eidEJNvM+V+eCghZFrG440THME8393H4dDcvXRxkc2WIGxpLuGlDGUV5/rTEtdoFxOUGxiK82jbEsfYhjlwaIpTr4+aN5exvKmXnumI2lOXjScNEURGRBVIBIcsrPBnlSOsgL14c4Nlz/bzcOkhJ0M+2mkK21xZyXW3RFW/wtFrSXUDM5JyjdWCcY+1DnO0Oc64nzPBElA3l+WyqCLGxMkRTRT4bK0JsKM/X/SdEJBNoDoSkbiwSpX1wgo6hcS4NjNPSN0pzT5hTnWG6RybYUJ54s9u3vpSP7W+kME29DNnCzGgoDdIwYxhjdDLKpcFxLg2O09wT5qnmXtoHJ+gcnqC6MMDmqhBbqwvYUlVAU3mIxvIghQF9n0Uk/VRArBGxuGMyGmM8EmMsEmNofIrh8Sn6RiP0hSfpCU/SMTRB59AEXcMTdI9MMhmNUx7KoTyUS1l+DuUFuWyrLuTt26qpLc5Lyz0arjb5uT62VBW84Vbb0VicjqEJ2gbGuDQ4zk8uDtI5NEHH0ARej1FVmEtFQS5l+bmUBP0UB3MozPNREPBTGPBTmOdLfvVTGEisX825JyJy9VMBQaJr+be/eZQHnrt42fo0BZQGHoOSYA7FQT9l+blsqiwglOtlZu9VPA6XBie4NDiRvkBT1BOeBOCrL7alOZKlMGqK8qgpymM3jvBkjP7RSfrCEVp6xwhPRhmNRK/K1+vMi3Ru3VTOX9yzJ23zaUTk9a44B8LMHgLKVy8cSLbXu8pt4iuqavTkFaxcrq/7Ns/6TXcAsbEh8wYLnXO4xDqX2OZeO86Be/1z55xzLg4ujnNxnHM4F3fE44kjnWOeyS6ZIB4ZD3py8sbSHUc6rEruZh4zjwfzeDHzJBaPxzAPZoZhibfs6ceJo173ZcYTS+z/hvUzG5xry+ViY0N4g0VX3CcemRiJDrQ34+KxK58t66Tlb16GUO6Zr9c5d+dsG+abRLnqzOwF59zedMeRLms5f+W+NnOHtZ2/clfu2UqDoiIiIpIyFRAiIiKSskwsID6b7gDSbC3nr9zXrrWcv3Jfm7I+94ybAyEiIiKZLxN7IERERCTDqYAQERGRlKmAEBERkZSpgBAREZGUqYAQERGRlKmAEBERkZSpgBAREZGUqYAQERGRlKmAEBERkZStWAFhZsfM7OBKnV9ERETSZ94CwsxazOxts6wvNLNPmtlFMwub2dnk83IA59y1zrnDKxCziIiIpNmieiDMLAd4FLgWuBMoBG4G+oB9yxadiIiIZCTfIo/7ONAAvNk5F06u6wb++/QOZtYC/JJz7gdm9vvAdmACeB9wEbjPOfdCct89wN8Cm4CHgDhwxjn324uMT0RERFbQYudAvA14aEbxsBCHgH8CioEHgb+A13ozvgF8HigFvkSiyBAREZEMtdgCogzoSPGYJ5xz33XOxYB/AHYm1+8n0RPyKefclHPu68Bzi4xLREREVsFiC4g+oCbFYzpnPB4DAmbmA2qBS845N2N76yLjEhERkVWw2ALiB8AdZpa/DDF0AHVmZjPWrVuG84qIiMgKWWgB4TezwPRCYgiiFfiamW01M4+ZlZnZb5rZu1KM4WkgBvyKmfnM7L3oSg4REZGMttAC4rvA+Izld0hMpDwJPAIMk5i3UA48m0oAzrkI8H7gF4FB4KPAd4DJVM4jIiIiq8deP/UgM5jZs8BfOec+l+5YRERE5I0y4rMwzOxNZladHMK4D7iexP0gREREJAMt9kZSy+0a4J+BENAMfMA5l+ploiIiIrJKMnIIQ0RERDJbRgxhiIiISHaZbwhD3ROy4g4ePAjA4cOH0xqHiIi8gc21QT0QIiIikrJMmUQpa0B4MkpL7ygX+8doHxyne2SS8ESU872jeD3G5588z8bKEDvqiigO5qQ7XBERuQIVELJsYnFH28AYLX1jtA2M0dY/TuvAGK39Y7QOjDM6GaW2OI/KglzKQjkUBPzk+b2YQTTmeLq5j6++1Ma5nlFqigLcsqmcN19Tyf6mMvJyvOlOT0REZlABIYsWnozy1Nlenmru5YWWAc72hCkM+KkpClAeyqU0P4eG0iB7GkqoKgxQHPTjsTcOpz2Y7G34uVs2AIlCpKVvlKOXhvjTR07R3DPKjtpCbt1cwb4NpeysL1ZBISKSZiogJCWDYxEeOtrJd4508OKFAbZUhdhWU8j799Szvix/Wd7YvR5jY0WIjRUh3rurjvFIjBMdw5zoHOZfjnTQ0jfKupIg19YVsqOuiB11RVxXV0R+rl7OIiKrRX9xZV4TUzEePdHN115q49lzfVxfX8SN60v5hVs2rEpPQF6Olz2NJexpLAFgKhbnYv8YLX2jPN/Sz1deaONC/yhNFSFu3VTOm7ZUsHd9Cbk+9VKIiKwUFRAyq1jc8dz5fr7+UhsPHetkQ3k+N28s496bGgjmpPdl4/d6XuuhmBaJxmnuCXOsfYj/9u3jtA2OsW9DKW/dWsXtmytoKAumMWIRkavPfHei1H0g1hDnHK9eGuJbL7fz7VfaCeX6OLCxjANNZZSFcles3fvvOQTApx94cNnOOTwxxZG2IY5eGuJI2yDBHB83byzj1s3lHNhYRmVBYNnaEhG5is15HwgVEEJr/xhff6mNr790ialYPFk0lFNXkrcq7a9EATGTc462gXGOtg9xqnOEY+3DVBbkcsumcm7ZVMb+pjJdNioiMjsVEPJ6A6MRvnu0g6++mLhs8kBTKTdvLGdTZQib5UqJlbTSBcTl4nHH+b7RxMTMjhFOdg7TUBrklk3lHGgqY19TKYUB/6rEIiKS4VRACHQOTfDDk938y6vtvHxxkJ3rijmwsYxd9cX4vOm7KelqFxCXi8bjNHcnCoqTncOc7gqzoSIx5+NAUxl7G0spCqqgEJE1ac4CQpMor2J94UleujjI0829PH6ml67hCXauK+aGhlJ+6dYmAn5dpQDg83i4prqAa6oLgDqmYnHOdoc50TnMpx49w+muMDVFAfY0lrC7oZgddUVsqSrQ909E1jQVEFeBWNxxoW+U011hTnUOc6x9mKPtwwyNR9hSWcCWqgI+tr+RpooQXs/qDk9kI7/Xw7aaQrbVFAKJHoqLfWOc7Q7zyPEu/ubx81waHKe6MMDGinw2VoZYX5ZPY1mQ+pIgdcV55Pj0MTMicnVTAZHhpmJxRiaiDI9PMTAWoS8coXN4gtbkfRCau0e5ODBGadD/2pvXlqoC3nFtNTVFgVnv/Cip8Xk8NFWEaJpx2Wg0FqdjaIL2oXE6hyY4fKqb7pFJukcm6QtPUpyXQ01RgNriPGqLA1QXBagoyKU0P5fSYA5FeX4K83zk5/rwp3H4SERksdJWQExMxfjuqx1MTMUBcLNMt5hresZs74mWHKZZyHnesEdyB3fZvs6519a56ecu0UYsDnHncM4Rd4legFjcEY07YvE4UzHHVCxOJBpnKpZ4HonFmYrGmYzGicQSXyenYkxMxRibijE6GX3t+zFr3kBx0E9JMIeyUA5VhQHevLWSmqIAuZf9xzs5FaOld3TOc2WS8akYAOd6wmmOJHUVoVwqLrvENe4cA6NT9I5O0heOcKJjhKeb+xiamGJ4PEp4MnrFcxoQzPGSn+sjL8dLfk7ia67PQ47Xg8/rwecxvF7D5zF8Hg9+r+H3evBNr5vex2N4zfB4DI8ZZuCxn/6+zPq7lFxpM7Zbcr3ZZQOiZq97/tP9f7p2U2WIfRtK5/1eikh2ueIkSjN7CChfkYZzgwX+ktotl6+PjQ3hDRatRJNZITY2hDevMO5cPIZzcZyLr5W5rPHxsM+TF7ryu+tVx8DwxCfCPk9eEWbmWfXLYFaYi8djU93nXp5nt3KgdxXCyUTKfW3Kltx7nXN3zrZhvqswVp2ZveCc25vuONJlLeev3Ndm7rC281fuyj1bafBVREREUqYCQkRERFKWiQXEZ9MdQJqt5fyV+9q1lvNX7mtT1ueecXMgREREJPNlYg+EiIiIZDgVECIiIpKytBQQZlZqZo+Y2Znk15I59rvTzE6Z2Vkz+40Z6/+7mR0xs5fN7GEzq1296JduGfL/YzM7mfwefMPMilct+CVahtw/aGbHzCxuZllxCdRcuczYbmb2qeT2I2a2Z6HHZrol5v53ZtZtZkdXN+rlsdjczWydmf3IzE4kX+v/YfWjX7ol5B8ws+fM7JVk/n+w+tEvzVJe98ntXjP7iZl9Z/WiXgSXvJviai7AHwG/kXz8G8D/nmUfL9AMNAE5wCvA9uS2whn7/Xvgr9KRRxrzfwfgSz7+37Mdn6nLMuS+DbgGOAzsTXc+C8h3zlxm7PMu4HskbvK4H3h2ocdm8rKU3JPbbgf2AEfTncsq/9xrgD3JxwXA6Wz6uS9D/gaEko/9wLPA/nTntBq5z9j+a8ADwHfSnc+VlnQNYbwX+ELy8ReAu2fZZx9w1jl3zjkXAf4peRzOueEZ++WTfbdqXGr+Dzvnpu/Y+AxQv7LhLqul5n7COXdqNQJdJnPmMsN7gb93Cc8AxWZWs8BjM9lScsc59xjQv6oRL59F5+6c63DOvQTgnBsBTgB1qxn8MlhK/s45N31fe39yyaa/8Ut63ZtZPXAX8DerGfRipKuAqHLOdQAkv1bOsk8d0DrjeRszfonM7H+YWStwL/C7KxjrSlhy/jP8AolKNlssZ+7ZYCG5zLVPtn8flpJ7tluW3M1sPbCbxH/h2WRJ+Se78F8GuoFHnHPZlP9Sf/afBP4LMPcHI2WIFfswLTP7AVA9y6bfWugpZln3WhXqnPst4LfM7BPArwC/l3KQK2il80+28VtAFPhiatGtrNXIPYssJJe59sn278NScs92S87dzELA14BfvazXNRssKX/nXAzYlZzf9Q0zu845ly1zYRadu5m9G+h2zr1oZgeXO7DltmIFhHPubXNtM7Ou6a66ZLdN9yy7tQHrZjyvB9pn2e8B4F/IsAJipfM3s/uAdwNvdclBs0yxij/7bLCQXObaJ2cBx2aypeSe7ZaUu5n5SRQPX3TOfX0F41wpy/Kzd84Nmtlh4E4gWwqIpeT+AeCQmb0LCACFZvaPzrmPrmC8i5auIYwHgfuSj+8DvjXLPs8Dm81sg5nlAB9JHoeZbZ6x3yHg5ArGuhKWmv+dwH8FDjnnxlYh3uW0pNyz0EJyeRD4eHJm9n5gKDm8k+3fh6Xknu0WnbuZGfC3wAnn3J+tbtjLZin5VyR7HjCzPOBtZNff+EXn7pz7hHOu3jm3PnncDzO1eADSdhVGGfAocCb5tTS5vhb47oz93kViBnIz8Fsz1n+NRDV6BPg2UJeOPNKY/1kS42cvJ5esuQplGXJ/H4nqfRLoAr6f7pwWkPMbcgH+DfBvko8N+HRy+6vMuLpkru9DtixLzP1LQAcwlfyZ/2K681mN3IFbSXR5H5nxO/6udOezivlfD/wkmf9R4HfTnctq5X7ZOQ6S4Vdh6FbWIiIikjLdiVJERERSpgJCREREUqYCQkRERFKmAkJERERSpgJCREREUqYCQkRERFKmAkJERERS9v8D07FFZS7UMBsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 576x1008 with 21 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.FacetGrid(\n",
    "    melt_frame, \n",
    "    row=\"ROI\",\n",
    "    row_order=means.index, \n",
    "    sharex=True, \n",
    "    height=2 / 3, \n",
    "    aspect=12\n",
    ")\n",
    "\n",
    "g.map_dataframe(sns.kdeplot, x=\"value\", fill=True)\n",
    "\n",
    "g.set_axis_labels(\"\")\n",
    "\n",
    "axes = g.axes.ravel()\n",
    "for i, (label, ax, mean) in enumerate(zip(order, axes, means)):\n",
    "    ax.set_title(\"\")\n",
    "    ax.set_title(label, loc=\"left\")\n",
    "    \n",
    "    ax.spines[\"left\"].set_visible(False)\n",
    "    ax.set_ylabel(\"\")\n",
    "    ax.set_yticks([])\n",
    "    \n",
    "    ax.axvline(x=mean, color=\"black\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "id": "e6104b51-563c-4e39-88d1-1df3f873af0f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'monochrome': False,\n",
       " 'colors': array([[0.76805788, 0.88417562, 0.89908506, 1.        ],\n",
       "        [0.76253291, 0.88079348, 0.89664309, 1.        ],\n",
       "        [0.76253291, 0.88079348, 0.89664309, 1.        ],\n",
       "        ...,\n",
       "        [0.12773581, 0.14704718, 0.25329666, 1.        ],\n",
       "        [0.12773581, 0.14704718, 0.25329666, 1.        ],\n",
       "        [0.12477747, 0.14301385, 0.24734758, 1.        ]]),\n",
       " 'name': 'seaborn_cubehelix',\n",
       " 'N': 256,\n",
       " '_rgba_bad': (0.0, 0.0, 0.0, 0.0),\n",
       " '_rgba_under': None,\n",
       " '_rgba_over': None,\n",
       " '_i_under': 256,\n",
       " '_i_over': 257,\n",
       " '_i_bad': 258,\n",
       " '_isinit': True,\n",
       " 'colorbar_extend': False,\n",
       " '_lut': array([[0.76805788, 0.88417562, 0.89908506, 1.        ],\n",
       "        [0.76253291, 0.88079348, 0.89664309, 1.        ],\n",
       "        [0.76253291, 0.88079348, 0.89664309, 1.        ],\n",
       "        ...,\n",
       "        [0.76805788, 0.88417562, 0.89908506, 1.        ],\n",
       "        [0.12477747, 0.14301385, 0.24734758, 1.        ],\n",
       "        [0.        , 0.        , 0.        , 0.        ]])}"
      ]
     },
     "execution_count": 179,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cmap.__dict__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "db55e5cf-6390-44e2-977e-18f0b33f6c3e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "52c5e7f2-494f-420f-84e1-92e676ac516f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<AxesSubplot:title={'center':'ROI__factor_dim = RTPJp'}, ylabel='Density'>,\n",
       " <AxesSubplot:title={'center':'ROI__factor_dim = RPCC'}, ylabel='Density'>,\n",
       " <AxesSubplot:title={'center':'ROI__factor_dim = LTPJ'}, ylabel='Density'>,\n",
       " <AxesSubplot:title={'center':'ROI__factor_dim = LIPL'}, ylabel='Density'>,\n",
       " <AxesSubplot:title={'center':'ROI__factor_dim = LaMTS/aMTG'}, ylabel='Density'>,\n",
       " <AxesSubplot:title={'center':'ROI__factor_dim = PCC'}, ylabel='Density'>,\n",
       " <AxesSubplot:title={'center':'ROI__factor_dim = dmMPFC'}, ylabel='Density'>,\n",
       " <AxesSubplot:title={'center':'ROI__factor_dim = vmPFC'}, ylabel='Density'>,\n",
       " <AxesSubplot:title={'center':'ROI__factor_dim = LSFG'}, ylabel='Density'>,\n",
       " <AxesSubplot:title={'center':'ROI__factor_dim = LMTG'}, ylabel='Density'>,\n",
       " <AxesSubplot:title={'center':'ROI__factor_dim = RvBG'}, ylabel='Density'>,\n",
       " <AxesSubplot:title={'center':'ROI__factor_dim = SGC'}, ylabel='Density'>,\n",
       " <AxesSubplot:title={'center':'ROI__factor_dim = RAmy/Hippo'}, ylabel='Density'>,\n",
       " <AxesSubplot:title={'center':'ROI__factor_dim = RIns'}, ylabel='Density'>,\n",
       " <AxesSubplot:title={'center':'ROI__factor_dim = LvBG'}, ylabel='Density'>,\n",
       " <AxesSubplot:title={'center':'ROI__factor_dim = RIFG_BA9'}, ylabel='Density'>,\n",
       " <AxesSubplot:title={'center':'ROI__factor_dim = LAmy/Hippo'}, ylabel='Density'>,\n",
       " <AxesSubplot:title={'center':'ROI__factor_dim = ACC'}, ylabel='Density'>,\n",
       " <AxesSubplot:title={'center':'ROI__factor_dim = RIFG_BA45'}, ylabel='Density'>,\n",
       " <AxesSubplot:title={'center':'ROI__factor_dim = LIFG'}, ylabel='Density'>,\n",
       " <AxesSubplot:title={'center':'ROI__factor_dim = LCing'}, xlabel='value', ylabel='Density'>]"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "bc58a48a-a183-4407-8e16-8662a1c79034",
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "'numpy.ndarray' object has no attribute 'spines'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "Input \u001b[0;32mIn [106]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mg\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43maxes\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mspines\u001b[49m\n",
      "\u001b[0;31mAttributeError\u001b[0m: 'numpy.ndarray' object has no attribute 'spines'"
     ]
    }
   ],
   "source": []
  }
 ],
 "metadata": {
  "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": "3.10.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}