03_2PL_MDNRMa_truncated_normal_numpyro.ipynb

{"cells":[{"cell_type":"markdown","metadata":{"id":"view-in-github"},"source":["<a href=\"https://colab.research.google.com/github/jurader/2PL-MDNRM/blob/main/03_2PL_MDNRMa_truncated_normal_numpyro.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"]},{"cell_type":"markdown","metadata":{"id":"aXuHT7ESzWcn"},"source":["# MDNRMa with truncated normal distribution\n"]},{"cell_type":"code","execution_count":4,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"SbNsogL9zWcn","outputId":"5a663325-8cc5-4d50-d0e0-a73ff57bab67","executionInfo":{"status":"ok","timestamp":1712353408390,"user_tz":-540,"elapsed":9600,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[{"output_type":"stream","name":"stdout","text":["\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m292.7/292.7 kB\u001b[0m \u001b[31m5.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.6/1.6 MB\u001b[0m \u001b[31m17.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[?25h"]}],"source":["! pip install -q numpyro==0.10.1 watermark==2.3.1"]},{"cell_type":"code","execution_count":5,"metadata":{"id":"K6MbPew0gKQ_","executionInfo":{"status":"ok","timestamp":1712353408391,"user_tz":-540,"elapsed":16,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[],"source":["import numpy as np\n","import pandas as pd\n","\n","import matplotlib.pyplot as plt"]},{"cell_type":"code","execution_count":6,"metadata":{"id":"ukB0HOcOzWco","executionInfo":{"status":"ok","timestamp":1712353411703,"user_tz":-540,"elapsed":3327,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[],"source":["import jax\n","import numpyro\n","import numpyro.distributions as dist\n","\n","import arviz as az\n","import jax.numpy as jnp"]},{"cell_type":"code","execution_count":7,"metadata":{"id":"U03BclmYzWco","executionInfo":{"status":"ok","timestamp":1712353411704,"user_tz":-540,"elapsed":13,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[],"source":["numpyro.set_platform('cpu')\n","numpyro.set_host_device_count(8)"]},{"cell_type":"markdown","metadata":{"id":"YQiPeoTmzWco"},"source":["## Import & Check Data"]},{"cell_type":"code","execution_count":8,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"nnc9cu91zbzD","outputId":"27f38dfa-05fc-4d97-c962-14667000f37d","executionInfo":{"status":"ok","timestamp":1712353412056,"user_tz":-540,"elapsed":364,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[{"output_type":"stream","name":"stdout","text":["--2024-04-05 21:43:31--  https://filedn.com/lpAczQGgeBjkX6l7SpI5JJy/__ws/stan_irt_nrm_rad/nrm_ground_truth_and_results.csv\n","Resolving filedn.com (filedn.com)... 23.109.93.100\n","Connecting to filedn.com (filedn.com)|23.109.93.100|:443... connected.\n","HTTP request sent, awaiting response... 200 OK\n","Length: 2272 (2.2K) [text/csv]\n","Saving to: ‘ground_truth_and_results.csv’\n","\n","ground_truth_and_re 100%[===================>]   2.22K  --.-KB/s    in 0s      \n","\n","2024-04-05 21:43:31 (1.04 GB/s) - ‘ground_truth_and_results.csv’ saved [2272/2272]\n","\n"]}],"source":["! wget https://filedn.com/lpAczQGgeBjkX6l7SpI5JJy/__ws/stan_irt_nrm_rad/nrm_ground_truth_and_results.csv -O ground_truth_and_results.csv"]},{"cell_type":"code","execution_count":9,"metadata":{"id":"6d34VYxOdiz3","executionInfo":{"status":"ok","timestamp":1712353412056,"user_tz":-540,"elapsed":3,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[],"source":["df = pd.read_csv('./ground_truth_and_results.csv')"]},{"cell_type":"code","execution_count":10,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"mA8nVf1qiG7r","outputId":"d9936b8b-778b-43d1-a960-be69e11b2653","executionInfo":{"status":"ok","timestamp":1712353412652,"user_tz":-540,"elapsed":599,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[{"output_type":"execute_result","data":{"text/plain":["   GT  MN  YU  EN  HM  DK  YW\n","0   1   1   0   1   1   1   1\n","1   1   1   1   1   1   1   0\n","2   0   1   0   0   0   0   0\n","3   1   1   1   2   2   2   2\n","4   1   1   1   1   1   2   2"],"text/html":["\n","  <div id=\"df-eb17e87a-e7ce-48de-91ec-4c88dff8e4f0\" class=\"colab-df-container\">\n","    <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>GT</th>\n","      <th>MN</th>\n","      <th>YU</th>\n","      <th>EN</th>\n","      <th>HM</th>\n","      <th>DK</th>\n","      <th>YW</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>2</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>2</td>\n","      <td>2</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-eb17e87a-e7ce-48de-91ec-4c88dff8e4f0')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n","    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n","  </svg>\n","    </button>\n","\n","  <style>\n","    .colab-df-container {\n","      display:flex;\n","      gap: 12px;\n","    }\n","\n","    .colab-df-convert {\n","      background-color: #E8F0FE;\n","      border: none;\n","      border-radius: 50%;\n","      cursor: pointer;\n","      display: none;\n","      fill: #1967D2;\n","      height: 32px;\n","      padding: 0 0 0 0;\n","      width: 32px;\n","    }\n","\n","    .colab-df-convert:hover {\n","      background-color: #E2EBFA;\n","      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n","      fill: #174EA6;\n","    }\n","\n","    .colab-df-buttons div {\n","      margin-bottom: 4px;\n","    }\n","\n","    [theme=dark] .colab-df-convert {\n","      background-color: #3B4455;\n","      fill: #D2E3FC;\n","    }\n","\n","    [theme=dark] .colab-df-convert:hover {\n","      background-color: #434B5C;\n","      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n","      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n","      fill: #FFFFFF;\n","    }\n","  </style>\n","\n","    <script>\n","      const buttonEl =\n","        document.querySelector('#df-eb17e87a-e7ce-48de-91ec-4c88dff8e4f0 button.colab-df-convert');\n","      buttonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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Ohta","userId":"15998100295259505885"}}},"outputs":[],"source":["df = df + 1\n"]},{"cell_type":"code","execution_count":12,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"kXSVRtDhkOmi","outputId":"747aad33-5413-4e3e-b28a-0b9a0eee5b82","executionInfo":{"status":"ok","timestamp":1712353412652,"user_tz":-540,"elapsed":32,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[{"output_type":"execute_result","data":{"text/plain":["   GT  MN  YU  EN  HM  DK  YW\n","0   2   2   1   2   2   2   2\n","1   2   2   2   2   2   2   1\n","2   1   2   1   1   1   1   1\n","3   2   2   2   3   3   3   3\n","4   2   2   2   2   2   3   3"],"text/html":["\n","  <div id=\"df-6f3e7765-79b6-4ada-bd07-72d97fe3e151\" class=\"colab-df-container\">\n","    <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    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<th>GT</th>\n","      <th>MN</th>\n","      <th>YU</th>\n","      <th>EN</th>\n","      <th>HM</th>\n","      <th>DK</th>\n","      <th>YW</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>count</th>\n","      <td>150.000000</td>\n","      <td>150.000000</td>\n","      <td>150.000000</td>\n","      <td>150.000000</td>\n","      <td>150.000000</td>\n","      <td>150.000000</td>\n","      <td>150.000000</td>\n","    </tr>\n","    <tr>\n","      <th>mean</th>\n","      <td>2.000000</td>\n","      <td>1.993333</td>\n","      <td>2.026667</td>\n","      <td>2.000000</td>\n","      <td>1.766667</td>\n","      <td>1.973333</td>\n","      <td>1.606667</td>\n","    </tr>\n","    <tr>\n","      <th>std</th>\n","      <td>0.819232</td>\n","      <td>0.823291</td>\n","      <td>0.818795</td>\n","      <td>0.819232</td>\n","      <td>0.870213</td>\n","      <td>0.826951</td>\n","      <td>0.818385</td>\n","    </tr>\n","    <tr>\n","      <th>min</th>\n","      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    3.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"}},"metadata":{},"execution_count":13}],"source":["df.describe()"]},{"cell_type":"code","execution_count":14,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"Kdi0fXEDijkm","outputId":"3a19d960-4558-4463-a452-2d0185f484c5","executionInfo":{"status":"ok","timestamp":1712353412653,"user_tz":-540,"elapsed":27,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[{"output_type":"stream","name":"stdout","text":["0 0\n","1 50\n","2 50\n","3 50\n"]}],"source":["print( 0, (df[\"GT\"]==0).sum() )\n","print( 1, (df[\"GT\"]==1).sum() )\n","print( 2, (df[\"GT\"]==2).sum() )\n","print( 3, (df[\"GT\"]==2).sum() )\n","\n","# 1 -> normal\n","# 2 -> non-COVID19 pneumonia\n","# 3 -> COVID19 pneumonia"]},{"cell_type":"markdown","metadata":{"id":"p5M6z3FbzWcp"},"source":["## Convert Data"]},{"cell_type":"code","execution_count":15,"metadata":{"id":"Dccdo8NAzWcp","executionInfo":{"status":"ok","timestamp":1712353412653,"user_tz":-540,"elapsed":22,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[],"source":["num_classes = 3"]},{"cell_type":"code","execution_count":16,"metadata":{"id":"WdTyR9Buk5lA","executionInfo":{"status":"ok","timestamp":1712353412653,"user_tz":-540,"elapsed":22,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[],"source":["rad_resp = df.iloc[:,1:].copy()\n"]},{"cell_type":"code","execution_count":17,"metadata":{"id":"gnCFgoKQj0a2","executionInfo":{"status":"ok","timestamp":1712353412653,"user_tz":-540,"elapsed":21,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[],"source":["num_cases = rad_resp.shape[0]\n","num_doctors = rad_resp.shape[1]\n","gt_types = df[\"GT\"]\n"]},{"cell_type":"code","execution_count":18,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"4J66KTdDlekC","outputId":"5f32dbea-db7f-4b86-fdf0-8546ac855a6d","executionInfo":{"status":"ok","timestamp":1712353412653,"user_tz":-540,"elapsed":20,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[{"output_type":"stream","name":"stdout","text":["150\n","6\n"]}],"source":["print(num_cases)\n","print(num_doctors)"]},{"cell_type":"code","execution_count":19,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"PP8y40CslC3C","outputId":"c1cab0e2-294d-4a1c-bd85-e8161c84845a","executionInfo":{"status":"ok","timestamp":1712353412653,"user_tz":-540,"elapsed":18,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[{"output_type":"execute_result","data":{"text/plain":["0      2\n","1      2\n","2      1\n","3      2\n","4      2\n","      ..\n","145    2\n","146    2\n","147    3\n","148    3\n","149    3\n","Name: GT, Length: 150, dtype: int64"]},"metadata":{},"execution_count":19}],"source":["gt_types"]},{"cell_type":"code","execution_count":20,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":424},"id":"ilpKXzE3k-tm","outputId":"d6048a7a-76e2-40f4-ca65-57ba229b62ac","executionInfo":{"status":"ok","timestamp":1712353412653,"user_tz":-540,"elapsed":17,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[{"output_type":"execute_result","data":{"text/plain":["     MN  YU  EN  HM  DK  YW\n","0     2   1   2   2   2   2\n","1     2   2   2   2   2   1\n","2     2   1   1   1   1   1\n","3     2   2   3   3   3   3\n","4     2   2   2   2   3   3\n","..   ..  ..  ..  ..  ..  ..\n","145   2   2   2   3   3   3\n","146   2   2   2   2   2   2\n","147   3   3   2   3   3   3\n","148   3   3   3   1   2   3\n","149   3   2   3   2   2   2\n","\n","[150 rows x 6 columns]"],"text/html":["\n","  <div id=\"df-e3cea656-7f0a-4f01-bf1c-5ba7f2bbbe40\" class=\"colab-df-container\">\n","    <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>MN</th>\n","      <th>YU</th>\n","      <th>EN</th>\n","      <th>HM</th>\n","      <th>DK</th>\n","      <th>YW</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>2</td>\n","      <td>1</td>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>2</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>2</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>3</td>\n","      <td>3</td>\n","      <td>3</td>\n","      <td>3</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>3</td>\n","      <td>3</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","    </tr>\n","    <tr>\n","      <th>145</th>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>3</td>\n","      <td>3</td>\n","      <td>3</td>\n","    </tr>\n","    <tr>\n","      <th>146</th>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>2</td>\n","    </tr>\n","    <tr>\n","      <th>147</th>\n","      <td>3</td>\n","      <td>3</td>\n","      <td>2</td>\n","      <td>3</td>\n","      <td>3</td>\n","      <td>3</td>\n","    </tr>\n","    <tr>\n","      <th>148</th>\n","      <td>3</td>\n","      <td>3</td>\n","      <td>3</td>\n","      <td>1</td>\n","      <td>2</td>\n","      <td>3</td>\n","    </tr>\n","    <tr>\n","      <th>149</th>\n","      <td>3</td>\n","      <td>2</td>\n","      <td>3</td>\n","      <td>2</td>\n","      <td>2</td>\n","      <td>2</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>150 rows × 6 columns</p>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-e3cea656-7f0a-4f01-bf1c-5ba7f2bbbe40')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg 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3\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"EN\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 1,\n        \"max\": 3,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          2,\n          1,\n          3\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"HM\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 1,\n        \"max\": 3,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          2,\n          1,\n          3\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DK\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 1,\n        \"max\": 3,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          2,\n          1,\n          3\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"YW\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 1,\n        \"max\": 3,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          2,\n          1,\n          3\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"}},"metadata":{},"execution_count":20}],"source":["rad_resp"]},{"cell_type":"code","execution_count":21,"metadata":{"id":"y0pmIkI_zWcp","executionInfo":{"status":"ok","timestamp":1712353412653,"user_tz":-540,"elapsed":15,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[],"source":["num_classes = 3"]},{"cell_type":"code","execution_count":22,"metadata":{"id":"WoitygN0zWcp","executionInfo":{"status":"ok","timestamp":1712353412654,"user_tz":-540,"elapsed":16,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[],"source":["y = rad_resp.to_numpy() - 1\n","y_true = gt_types.to_numpy() - 1"]},{"cell_type":"code","execution_count":23,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"2r2n_0EnzWcp","outputId":"d1b16d20-5953-4ee4-e070-fb9deaa5b9fa","executionInfo":{"status":"ok","timestamp":1712353412654,"user_tz":-540,"elapsed":16,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[{"output_type":"stream","name":"stdout","text":["(150, 6)\n","(150,)\n"]}],"source":["print(y.shape)\n","print(y_true.shape)"]},{"cell_type":"markdown","metadata":{"id":"SqzB0ltjzWcq"},"source":["## Generate Index"]},{"cell_type":"code","execution_count":24,"metadata":{"id":"OBv-IJ1gzWcq","executionInfo":{"status":"ok","timestamp":1712353412654,"user_tz":-540,"elapsed":14,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[],"source":["i_beta = np.zeros((num_cases, num_doctors, num_classes), dtype=int)\n","\n","for i in range(num_cases):\n","    for j in range(num_doctors):\n","        for k in range(num_classes):\n","            i_beta[i, j, k] = k"]},{"cell_type":"markdown","metadata":{"id":"P4bbiO0SzWcq"},"source":["## Define Model\n","\n","### Overview of Paramters\n","\n","**theta**: radiologist's ability\n","- theta.shape: (number of classes) x (number of radiologists) x (number of classes)\n","\n","**alpha**: item's discrimination\n","- alpha.shape: (number of items) x (number of classes)\n","\n","**beta**: difficulty based on class\n","- beta.shape: (number of classes)\n"]},{"cell_type":"code","execution_count":25,"metadata":{"id":"7af-qrPVzWcq","executionInfo":{"status":"ok","timestamp":1712353412654,"user_tz":-540,"elapsed":13,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[],"source":["theta_sd = 2\n","beta_sd = 2"]},{"cell_type":"code","execution_count":26,"metadata":{"id":"TRZjNCsrzWcq","executionInfo":{"status":"ok","timestamp":1712353412654,"user_tz":-540,"elapsed":13,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[],"source":["def model(y=None, y_true=None, i_beta=None, num_cases=0, num_doctors=0, num_classes=0):\n","\n","    theta = numpyro.sample('theta', dist.Normal(0, theta_sd), sample_shape=(num_classes, num_doctors, num_classes))\n","    alpha = numpyro.sample('alpha', dist.HalfNormal(10), sample_shape=(num_cases, 1, num_classes))\n","    beta = numpyro.sample('beta', dist.Normal(0, beta_sd), sample_shape=(num_classes,))\n","\n","    alpha_tiled = jnp.tile(alpha, (1, num_doctors, 1))\n","\n","    # logits.shape : (num_cases, num_doctors, num_classes)\n","    logits = theta[y_true, :, :] * alpha_tiled + beta[i_beta]\n","\n","    numpyro.sample('obs', dist.Categorical(logits=logits), obs=y)"]},{"cell_type":"markdown","metadata":{"id":"P23PyE8_zWcq"},"source":["## Inference"]},{"cell_type":"code","execution_count":27,"metadata":{"id":"IPSOabLWzWcq","executionInfo":{"status":"ok","timestamp":1712353412655,"user_tz":-540,"elapsed":14,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[],"source":["nuts = numpyro.infer.NUTS(model)"]},{"cell_type":"code","execution_count":28,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":308,"referenced_widgets":["18973faae3d4488cb05e2253550010e9","e0b59bbf898541a880ca9585df33d347","da00125660ec44c3b2e83e4053a3ab3f","d339369f3a2d41e58e11dd37c3cb6e0f","2e7ac6e05a444b929f146e9c5aefd61b","748fc02a8e4248bea7aa98e68f209c66","885770283f7b4afba282696045deb41c","34264be8a7484ec4b947c8694017307c","1b2fbfa73b904084afcfebefb4ab8ab7","9feb651a167e4eeb9aa43b6d73f88556","9166ea0687954801b98940a8bb6204b3","f4ad869395174fb092c319354c762009","bcac0e6bb16c4fe390e0c157a3e6b679","faa662cbdd324af099e8af2b5ac833ba","3d4c580ef1f0457782567c0e84e5a644","c2259ca9660442e692b26b52e2213bed","e0ec5e780b45439c883ce5170cf8adf1","aecea1e88e534ceba17421b32644f897","511fe2f44b4e4309b63677bd92af57e5","89230a2d28644fe781484329f593f189","3bf79474e85146bdbd1395878b2ed1dd","dbcc5b46148844ceb1c1ac61462ed6bb","b3cebcb7092446b795954874d3326a0c","e620ca499e5948a592d22bc3a5b54034","e71855153b1a4cf28ec7d0dc2172d46b","1bfd28d5f83744faae168a10d060a641","eac0bd1e56604a26904059e896a84c13","037831185ffa43f9b0cfae30ce89bd6f","1676a140d09546c8a1f1aeb04507538a","de263d50fc69411faf49d45c0e22c080","58c81e082f9647d0b1efd5a2ba2f6331","65e0743b5b7542468b3a5dbbdc72cc76","5489b605665045c6b5affe9f54d899d7","da86f2c45dcb415da8047de76c116de5","eb045e53a7bb4a589a007188fd2a9985","d1728450b2594b93a10d75e577878c69","58c0fb0c5e8e401183636864a0dacb23","86f55129bd27471893b05bcb42e017c5","4a83e8c1d6bb43869d5e52330f3e8d9d","c1522cf6168d46f1822accdb61631f15","5e116da714d043179beecfbe86ef191d","262779bc2a4747b8a90ec54bc5e3ef17","8fdba7bbd6904a61b096987a9f0c91f2","b3f19a4dfd18403d8ccdb457c38f2847","b16d6141aa3a4b0ca9473fa7ca3f1b7f","fdbd83492a994070932e41b01d18f4d1","92c8b656658643b6b61560459ca278ca","f3152b548c28411792aa0f15a380349e","72e8f1d45a5148f4b897942a848cf86b","f1229cbf641d4a068c7bcc8f7784d5f3","7f70dc87ba314e6fa5ad69615602a1b9","7ae8318c55c04f649f59d9319e3362f9","3d5e72800167451ba4de58ec76a880d4","2a91b033943c4f97b838c10199900466","2fddf8afc7a14d66ad2cc3c81426acd1","4bea94e61df34f0987960676877c85c6","15ac164248e246469e12989ebb16f75b","79a6d61c80244bffb8a8550db9008365","7cd6c68a7f254e44b6e20a3bab530bfb","b58f7d568dae4af8904a63fccb91573e","a02a1e262a894befb62d42b0ffeb7adb","20fb2b0d6cf14edd99ff90a766768e18","06eaae9a9eb24814ad3d92fcf0b92c14","f00625611b214bf687f333fd93bd301e","5ecdc4335fc84f6388cd60f02fc17770","fb5dd78c726d49879f33d44f7669f559","eb06706865f8473cbdd27acb32589b16","6edb3ddd79bc41abacf21e93c4b3ccd3","99839d964bb94b17888e6ec3d9ee8861","77d4e4262db24d169fcf971816eeb8ec","ec953f7784f24d33a9941475019d8896","08d07e537ade4be1bfde54a92a0668df","bfc71c42d4d24b55805ed6e982d32d0d","43da2625792a4f70ab7113598e2bb6ad","6294a163a83f4ad690ff6db5615a6756","de7e7eadf5c0428da8f0237520fd8363","fbd09e2e4add481fb6bc85f0b115b3f6","e2329703aed24404b6f9b96eb055c412","a8a280eff86c4705a6d5d712895784a9","b64d1736476340fcbef457d57a416e28","a21aedd9527b432a9bf2829243f969ab","2bd85f1ba4c642c7b3e0cbe364a98bbf","7c872ed72cc04212ab6ef23061d241a4","6dd496772ce44dc6adbcd47b39acb839","b8aa9dfd9437452fa6f2783869a8f5d3","19f3d5d086bc448dbb45f803c7cb2422","9a641f5a52b444c8a82423e250f07818","ddcbc29b39074390bb98e33a09498703"]},"id":"fbqPX8hnzWcq","outputId":"c3d9edd6-10f0-47b8-d481-e2c33ab0622b","executionInfo":{"status":"ok","timestamp":1712353862260,"user_tz":-540,"elapsed":449619,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[{"output_type":"display_data","data":{"text/plain":["  0%|          | 0/9000 [00:00<?, ?it/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"18973faae3d4488cb05e2253550010e9"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["  0%|          | 0/9000 [00:00<?, ?it/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"f4ad869395174fb092c319354c762009"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["  0%|          | 0/9000 [00:00<?, ?it/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"b3cebcb7092446b795954874d3326a0c"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["  0%|          | 0/9000 [00:00<?, ?it/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"da86f2c45dcb415da8047de76c116de5"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["  0%|          | 0/9000 [00:00<?, ?it/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"b16d6141aa3a4b0ca9473fa7ca3f1b7f"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["  0%|          | 0/9000 [00:00<?, ?it/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"4bea94e61df34f0987960676877c85c6"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["  0%|          | 0/9000 [00:00<?, ?it/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"eb06706865f8473cbdd27acb32589b16"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["  0%|          | 0/9000 [00:00<?, ?it/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"e2329703aed24404b6f9b96eb055c412"}},"metadata":{}},{"output_type":"stream","name":"stdout","text":["CPU times: user 12min 15s, sys: 2.65 s, total: 12min 18s\n","Wall time: 7min 29s\n"]}],"source":["%%time\n","\n","mcmc = numpyro.infer.MCMC(nuts, num_warmup=1000, num_samples=8000, num_chains=8)\n","\n","mcmc.run(jax.random.PRNGKey(0), y=y, y_true=y_true, i_beta=i_beta, num_cases=num_cases, num_doctors=num_doctors, num_classes=num_classes)\n","mcmc_samples = mcmc.get_samples()"]},{"cell_type":"markdown","metadata":{"id":"ra4Nv7EYzWcq"},"source":["## Evaluate Results"]},{"cell_type":"code","execution_count":29,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":161},"id":"osbbULx3g04H","outputId":"d4e2a9c1-69b7-4b81-a861-29cc9344b0ec","executionInfo":{"status":"ok","timestamp":1712353868041,"user_tz":-540,"elapsed":5786,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[{"output_type":"execute_result","data":{"text/plain":["Inference data with groups:\n","\t> posterior\n","\t> log_likelihood\n","\t> sample_stats\n","\t> observed_data"],"text/html":["\n","            <div>\n","              <div class='xr-header'>\n","                <div class=\"xr-obj-type\">arviz.InferenceData</div>\n","              </div>\n","              <ul class=\"xr-sections group-sections\">\n","              \n","            <li class = \"xr-section-item\">\n","                  <input id=\"idata_posterior90056da2-f67d-4ed3-b83b-8217bffecff0\" class=\"xr-section-summary-in\" type=\"checkbox\">\n","                  <label for=\"idata_posterior90056da2-f67d-4ed3-b83b-8217bffecff0\" class = \"xr-section-summary\">posterior</label>\n","                  <div class=\"xr-section-inline-details\"></div>\n","                  <div class=\"xr-section-details\">\n","                      <ul id=\"xr-dataset-coord-list\" 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4;\n","}\n","\n",".xr-index-preview {\n","  grid-column: 2 / 5;\n","  color: var(--xr-font-color2);\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",".xr-index-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",".xr-index-data-in:checked ~ .xr-index-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-index-name div,\n",".xr-index-data,\n",".xr-attrs {\n","  padding-left: 25px !important;\n","}\n","\n",".xr-attrs,\n",".xr-var-attrs,\n",".xr-var-data,\n",".xr-index-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",".xr-no-icon {\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: 8000, alpha_dim_0: 150, alpha_dim_1: 1,\n","                  alpha_dim_2: 3, beta_dim_0: 3, theta_dim_0: 3,\n","                  theta_dim_1: 6, theta_dim_2: 3)\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 ... 7994 7995 7996 7997 7998 7999\n","  * alpha_dim_0  (alpha_dim_0) int64 0 1 2 3 4 5 6 ... 144 145 146 147 148 149\n","  * alpha_dim_1  (alpha_dim_1) int64 0\n","  * alpha_dim_2  (alpha_dim_2) int64 0 1 2\n","  * beta_dim_0   (beta_dim_0) int64 0 1 2\n","  * theta_dim_0  (theta_dim_0) int64 0 1 2\n","  * theta_dim_1  (theta_dim_1) int64 0 1 2 3 4 5\n","  * theta_dim_2  (theta_dim_2) int64 0 1 2\n","Data variables:\n","    alpha        (chain, draw, alpha_dim_0, alpha_dim_1, alpha_dim_2) float32 ...\n","    beta         (chain, draw, beta_dim_0) float32 -0.2702 0.112 ... 0.4236\n","    theta        (chain, draw, theta_dim_0, theta_dim_1, theta_dim_2) float32 ...\n","Attributes:\n","    created_at:                 2024-04-05T21:51:03.347221\n","    arviz_version:              0.15.1\n","    inference_library:          numpyro\n","    inference_library_version:  0.10.1</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-4d519300-7ddb-4b67-a088-ecc2e404629e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4d519300-7ddb-4b67-a088-ecc2e404629e' 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>: 8000</li><li><span class='xr-has-index'>alpha_dim_0</span>: 150</li><li><span class='xr-has-index'>alpha_dim_1</span>: 1</li><li><span class='xr-has-index'>alpha_dim_2</span>: 3</li><li><span class='xr-has-index'>beta_dim_0</span>: 3</li><li><span class='xr-has-index'>theta_dim_0</span>: 3</li><li><span class='xr-has-index'>theta_dim_1</span>: 6</li><li><span class='xr-has-index'>theta_dim_2</span>: 3</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-a21a934f-07cd-492a-9401-f5e3ac76b472' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a21a934f-07cd-492a-9401-f5e3ac76b472' class='xr-section-summary' >Coordinates: <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 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-5cdc2fe2-4d9b-4be9-936a-55435ac2bc41' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5cdc2fe2-4d9b-4be9-936a-55435ac2bc41' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-54c059e4-e940-477f-915f-5463c4ccdc3b' class='xr-var-data-in' type='checkbox'><label for='data-54c059e4-e940-477f-915f-5463c4ccdc3b' 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 ... 7996 7997 7998 7999</div><input id='attrs-32c5bed3-1127-4449-bd0a-f6dbfdb56700' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-32c5bed3-1127-4449-bd0a-f6dbfdb56700' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eceac215-1b7e-4133-8e8e-a8c1243187e8' class='xr-var-data-in' type='checkbox'><label for='data-eceac215-1b7e-4133-8e8e-a8c1243187e8' 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, ..., 7997, 7998, 7999])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>alpha_dim_0</span></div><div class='xr-var-dims'>(alpha_dim_0)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 145 146 147 148 149</div><input id='attrs-a76de7b4-be08-41bd-8825-3db4e4e77f8e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a76de7b4-be08-41bd-8825-3db4e4e77f8e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b9f15374-e46d-46a4-a1e1-989981e2daa9' class='xr-var-data-in' type='checkbox'><label for='data-b9f15374-e46d-46a4-a1e1-989981e2daa9' 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,   8,   9,  10,  11,  12,  13,\n","        14,  15,  16,  17,  18,  19,  20,  21,  22,  23,  24,  25,  26,  27,\n","        28,  29,  30,  31,  32,  33,  34,  35,  36,  37,  38,  39,  40,  41,\n","        42,  43,  44,  45,  46,  47,  48,  49,  50,  51,  52,  53,  54,  55,\n","        56,  57,  58,  59,  60,  61,  62,  63,  64,  65,  66,  67,  68,  69,\n","        70,  71,  72,  73,  74,  75,  76,  77,  78,  79,  80,  81,  82,  83,\n","        84,  85,  86,  87,  88,  89,  90,  91,  92,  93,  94,  95,  96,  97,\n","        98,  99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111,\n","       112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125,\n","       126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139,\n","       140, 141, 142, 143, 144, 145, 146, 147, 148, 149])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>alpha_dim_1</span></div><div class='xr-var-dims'>(alpha_dim_1)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-16e5e0b2-f222-4276-a172-7e882e940f76' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-16e5e0b2-f222-4276-a172-7e882e940f76' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9fbe329e-d513-402e-b0e2-c1dcc7bbcb6c' class='xr-var-data-in' type='checkbox'><label for='data-9fbe329e-d513-402e-b0e2-c1dcc7bbcb6c' 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])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>alpha_dim_2</span></div><div class='xr-var-dims'>(alpha_dim_2)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2</div><input id='attrs-ef7cd64d-c475-4303-b158-442fca46c75a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ef7cd64d-c475-4303-b158-442fca46c75a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b5746d7c-f8dd-4b4a-b64b-14fb3390d7fc' class='xr-var-data-in' type='checkbox'><label for='data-b5746d7c-f8dd-4b4a-b64b-14fb3390d7fc' 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])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beta_dim_0</span></div><div class='xr-var-dims'>(beta_dim_0)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2</div><input id='attrs-5f28cead-3aaf-44c3-b644-d6ca0fc86fbb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5f28cead-3aaf-44c3-b644-d6ca0fc86fbb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-283fef97-0fe5-44eb-bcc6-7652442ff68f' class='xr-var-data-in' type='checkbox'><label for='data-283fef97-0fe5-44eb-bcc6-7652442ff68f' 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])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>theta_dim_0</span></div><div class='xr-var-dims'>(theta_dim_0)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2</div><input id='attrs-1bac2194-b320-4e48-bd90-d10f7c82b7fd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1bac2194-b320-4e48-bd90-d10f7c82b7fd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fa4bfe8a-9c7b-4f00-903f-1c8c213b1d06' class='xr-var-data-in' type='checkbox'><label for='data-fa4bfe8a-9c7b-4f00-903f-1c8c213b1d06' 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])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>theta_dim_1</span></div><div class='xr-var-dims'>(theta_dim_1)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5</div><input id='attrs-6c90fb3b-784f-40d6-be34-8bb4f908c3bd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6c90fb3b-784f-40d6-be34-8bb4f908c3bd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1667d981-dbe0-40fd-8e7b-4b83ab8d6997' class='xr-var-data-in' type='checkbox'><label for='data-1667d981-dbe0-40fd-8e7b-4b83ab8d6997' 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])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>theta_dim_2</span></div><div class='xr-var-dims'>(theta_dim_2)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2</div><input id='attrs-45a88303-35d1-49cd-9206-390650579db8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-45a88303-35d1-49cd-9206-390650579db8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7825a514-6254-4f83-ac86-307bbb5ec833' class='xr-var-data-in' type='checkbox'><label for='data-7825a514-6254-4f83-ac86-307bbb5ec833' 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])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1b9c8a43-4832-42f3-89ce-f9fa3212dfcd' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1b9c8a43-4832-42f3-89ce-f9fa3212dfcd' class='xr-section-summary' >Data variables: <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>alpha</span></div><div class='xr-var-dims'>(chain, draw, alpha_dim_0, alpha_dim_1, alpha_dim_2)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.171 0.1445 10.02 ... 0.2369 16.86</div><input id='attrs-68f98d20-722a-49e6-8c81-8ba2f955c698' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-68f98d20-722a-49e6-8c81-8ba2f955c698' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-af9063d5-57d1-445d-8397-dcede917955e' class='xr-var-data-in' type='checkbox'><label for='data-af9063d5-57d1-445d-8397-dcede917955e' 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([[[[[1.71003059e-01, 1.44459471e-01, 1.00246639e+01]],\n","\n","         [[7.17384958e+00, 1.29445200e+01, 1.03731947e+01]],\n","\n","         [[7.83141994e+00, 2.02330804e+00, 1.71581669e+01]],\n","\n","         ...,\n","\n","         [[1.75155163e+01, 2.94366693e+00, 2.50048351e+00]],\n","\n","         [[5.53468227e+00, 5.23155165e+00, 3.35963869e+00]],\n","\n","         [[6.61367130e+00, 5.31298578e-01, 5.64436913e+00]]],\n","\n","\n","        [[[4.11482066e-01, 6.90296814e-02, 1.37173786e+01]],\n","\n","         [[4.78848505e+00, 1.37011738e+01, 1.84249249e+01]],\n","\n","         [[7.06823397e+00, 4.23798037e+00, 3.97455335e+00]],\n","...\n","\n","         [[1.95257413e+00, 6.95655727e+00, 2.20029354e+00]],\n","\n","         [[6.23015213e+00, 5.54971874e-01, 6.88997746e+00]]],\n","\n","\n","        [[[1.69454682e+00, 4.55725193e+00, 9.13557434e+00]],\n","\n","         [[4.54139471e+00, 6.80177498e+00, 1.73740444e+01]],\n","\n","         [[5.22432899e+00, 7.88980770e+00, 2.38530693e+01]],\n","\n","         ...,\n","\n","         [[4.80770874e+00, 3.02698708e+00, 7.31658340e-01]],\n","\n","         [[7.85664654e+00, 1.90570319e+00, 1.43476558e+00]],\n","\n","         [[9.74758625e+00, 2.36857623e-01, 1.68644600e+01]]]]],\n","      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beta</span></div><div class='xr-var-dims'>(chain, draw, beta_dim_0)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2702 0.112 ... 1.526 0.4236</div><input id='attrs-37d86040-4db0-4818-a60e-c32f4a52b857' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-37d86040-4db0-4818-a60e-c32f4a52b857' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7c78d6e5-ca2f-4cf1-a8c6-8d1936990774' class='xr-var-data-in' type='checkbox'><label for='data-7c78d6e5-ca2f-4cf1-a8c6-8d1936990774' 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([[[-0.27020115,  0.11196517, -0.40572354],\n","        [ 0.82580686,  1.2242558 ,  0.49270025],\n","        [ 0.6860313 ,  1.5559596 ,  0.7082424 ],\n","        ...,\n","        [-1.320229  , -0.449974  , -1.964863  ],\n","        [-0.55290985,  0.37222165, -1.4004228 ],\n","        [ 0.12744959,  1.1947155 , -0.1587231 ]],\n","\n","       [[ 0.12478039,  0.39002022, -0.86552334],\n","        [ 0.8977357 ,  0.38656133, -1.026484  ],\n","        [ 0.7017297 ,  0.3983933 , -1.2877768 ],\n","        ...,\n","        [ 1.6194018 ,  1.8321007 ,  0.49553254],\n","        [ 1.7621549 ,  1.6717277 ,  0.03114158],\n","        [-0.2134628 , -0.49364835, -2.3482618 ]],\n","\n","       [[-0.20580715, -0.74379456, -2.6211245 ],\n","        [-0.635291  , -0.7467279 , -2.4685714 ],\n","        [ 0.11628127, -0.12974747, -1.9454542 ],\n","        ...,\n","...\n","        ...,\n","        [ 1.1706362 ,  1.4257722 ,  0.8190383 ],\n","        [ 1.2885449 ,  1.3202876 ,  0.5201458 ],\n","        [ 2.6951063 ,  3.190474  ,  1.9266232 ]],\n","\n","       [[ 1.2316496 ,  0.80115944, -0.04654217],\n","        [-0.526449  , -0.98441625, -2.0780447 ],\n","        [-1.0714285 , -0.95479447, -1.7104703 ],\n","        ...,\n","        [-1.0135593 , -0.5463499 , -1.3220794 ],\n","        [-0.29538372, -0.00721557, -0.9067962 ],\n","        [ 0.35325032,  0.34969652, -0.5557978 ]],\n","\n","       [[ 0.6481884 ,  1.0505823 , -0.21750599],\n","        [ 2.4725864 ,  3.3622985 ,  2.5839245 ],\n","        [ 2.3013668 ,  3.097323  ,  2.50894   ],\n","        ...,\n","        [-0.15997508,  0.7980689 , -0.7309194 ],\n","        [-0.5879835 , -0.01286017, -1.5947102 ],\n","        [ 1.0433706 ,  1.5263166 ,  0.42362228]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>theta</span></div><div class='xr-var-dims'>(chain, draw, theta_dim_0, theta_dim_1, theta_dim_2)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.02603 -0.8967 ... -2.773 -2.453</div><input id='attrs-44897d76-d52d-45c4-93a5-4bbeaea9f9d7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-44897d76-d52d-45c4-93a5-4bbeaea9f9d7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ebe1b5b-3b4e-472f-965a-768ed28286fe' class='xr-var-data-in' type='checkbox'><label for='data-5ebe1b5b-3b4e-472f-965a-768ed28286fe' 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([[[[[ 2.60288958e-02, -8.96681845e-01, -2.12289882e+00],\n","          [ 5.52179754e-01, -1.01307534e-01,  6.48849756e-02],\n","          [ 1.64878547e-01, -8.61781418e-01, -6.06659114e-01],\n","          [ 1.14926553e+00, -1.16441831e-01, -1.20981956e+00],\n","          [-3.68356049e-01, -2.99195409e+00, -2.94843984e+00],\n","          [ 3.61961746e+00,  6.72979653e-02, -2.28880191e+00]],\n","\n","         [[-5.80046713e-01, -2.79030185e-02, -1.03895865e-01],\n","          [-2.29335451e+00, -2.07391590e-01, -5.65928519e-01],\n","          [-8.68610620e-01, -3.78987156e-02, -3.42301399e-01],\n","          [-7.20414162e-01, -3.43351513e-01, -3.73188734e-01],\n","          [-9.18552399e-01, -1.97485194e-01, -1.65281981e-01],\n","          [-5.36828160e-01, -7.89559484e-01, -7.25166917e-01]],\n","\n","         [[-1.73554516e+00, -6.27102792e-01, -2.46161729e-01],\n","          [-2.05096912e+00, -1.85635373e-01,  8.04078132e-02],\n","          [-1.85779536e+00, -6.50548518e-01, -7.53091574e-02],\n","          [-1.02218235e+00, -3.36954117e+00, -7.29012311e-01],\n","          [-4.81268942e-01, -4.70113575e-01, -2.08170563e-01],\n","          [-1.36232281e+00, -2.13434458e+00, -1.61565542e+00]]],\n","...\n","          [ 1.58834711e-01, -2.55496442e-01, -3.31784934e-02],\n","          [ 5.96176565e-01, -2.20363855e-01, -5.82228713e-02],\n","          [ 4.80853653e+00,  4.61108267e-01, -2.78416371e+00],\n","          [-2.57997692e-01, -2.05338550e+00, -1.94656777e+00],\n","          [ 2.13646555e+00, -2.81388909e-01, -1.43916929e+00]],\n","\n","         [[-1.73201358e+00, -2.34282225e-01, -1.56487614e-01],\n","          [-7.54213929e-01, -2.76439637e-01, -2.61946380e-01],\n","          [-1.41245437e+00, -1.76710531e-01, -2.09099546e-01],\n","          [-1.64545369e+00, -9.46687818e-01, -9.95744824e-01],\n","          [-1.76408613e+00, -3.06171864e-01, -1.21543735e-01],\n","          [-3.61957580e-01, -4.76430088e-01, -2.32684419e-01]],\n","\n","         [[-7.77132750e-01, -4.73946005e-01, -9.90476906e-02],\n","          [-1.09098411e+00, -5.58035791e-01, -2.84049865e-02],\n","          [-1.07574379e+00, -2.82951444e-01,  2.37656698e-01],\n","          [-4.21721518e-01, -1.26611841e+00, -2.58165032e-01],\n","          [-4.76444274e-01, -5.27065396e-01, -9.14180279e-02],\n","          [-1.93557072e+00, -2.77331066e+00, -2.45273423e+00]]]]],\n","      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8cec5187-e18c-4d51-bccc-181af1687cfa' class='xr-section-summary-in' type='checkbox'  ><label for='section-8cec5187-e18c-4d51-bccc-181af1687cfa' class='xr-section-summary' >Indexes: <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-index-name'><div>chain</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d704f693-b6b5-423e-a533-42424b0cdb4c' class='xr-index-data-in' type='checkbox'/><label for='index-d704f693-b6b5-423e-a533-42424b0cdb4c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0, 1, 2, 3, 4, 5, 6, 7], dtype=&#x27;int64&#x27;, name=&#x27;chain&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>draw</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-4afe9df6-6336-4eea-8d3d-2155fd48f77d' class='xr-index-data-in' type='checkbox'/><label for='index-4afe9df6-6336-4eea-8d3d-2155fd48f77d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0,    1,    2,    3,    4,    5,    6,    7,    8,    9,\n","       ...\n","       7990, 7991, 7992, 7993, 7994, 7995, 7996, 7997, 7998, 7999],\n","      dtype=&#x27;int64&#x27;, name=&#x27;draw&#x27;, length=8000))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>alpha_dim_0</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a40f152e-f09e-47d7-bb88-aab386e14afc' class='xr-index-data-in' type='checkbox'/><label for='index-a40f152e-f09e-47d7-bb88-aab386e14afc' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,\n","       ...\n","       140, 141, 142, 143, 144, 145, 146, 147, 148, 149],\n","      dtype=&#x27;int64&#x27;, name=&#x27;alpha_dim_0&#x27;, length=150))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>alpha_dim_1</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b3167543-ad11-47f7-b541-2160caa60198' class='xr-index-data-in' type='checkbox'/><label for='index-b3167543-ad11-47f7-b541-2160caa60198' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0], dtype=&#x27;int64&#x27;, name=&#x27;alpha_dim_1&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>alpha_dim_2</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f45a3f86-dbbb-435b-bcad-24125df41b3f' class='xr-index-data-in' type='checkbox'/><label for='index-f45a3f86-dbbb-435b-bcad-24125df41b3f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0, 1, 2], dtype=&#x27;int64&#x27;, name=&#x27;alpha_dim_2&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>beta_dim_0</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8c32e5ae-fca2-417f-9895-3027a151c0ff' class='xr-index-data-in' type='checkbox'/><label for='index-8c32e5ae-fca2-417f-9895-3027a151c0ff' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0, 1, 2], dtype=&#x27;int64&#x27;, name=&#x27;beta_dim_0&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>theta_dim_0</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-26994823-bf4f-49e8-82e1-62d0f3ba673d' class='xr-index-data-in' type='checkbox'/><label for='index-26994823-bf4f-49e8-82e1-62d0f3ba673d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0, 1, 2], dtype=&#x27;int64&#x27;, name=&#x27;theta_dim_0&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>theta_dim_1</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-696745e2-837a-495f-9a88-042b16b8700e' class='xr-index-data-in' type='checkbox'/><label for='index-696745e2-837a-495f-9a88-042b16b8700e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0, 1, 2, 3, 4, 5], dtype=&#x27;int64&#x27;, name=&#x27;theta_dim_1&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>theta_dim_2</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c867a3da-f061-42d8-bce5-4f04734f14c4' class='xr-index-data-in' type='checkbox'/><label for='index-c867a3da-f061-42d8-bce5-4f04734f14c4' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0, 1, 2], dtype=&#x27;int64&#x27;, name=&#x27;theta_dim_2&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-391c6077-41b3-4bee-b0cf-b4b503408f94' class='xr-section-summary-in' type='checkbox'  checked><label for='section-391c6077-41b3-4bee-b0cf-b4b503408f94' 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>2024-04-05T21:51:03.347221</dd><dt><span>arviz_version :</span></dt><dd>0.15.1</dd><dt><span>inference_library :</span></dt><dd>numpyro</dd><dt><span>inference_library_version :</span></dt><dd>0.10.1</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_likelihood9320d8ba-dbb9-4a91-9848-cb55a2269d1d\" 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1;\n","}\n","\n",".xr-var-attrs,\n",".xr-var-data,\n",".xr-index-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",".xr-index-data-in:checked ~ .xr-index-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-index-name div,\n",".xr-index-data,\n",".xr-attrs {\n","  padding-left: 25px !important;\n","}\n","\n",".xr-attrs,\n",".xr-var-attrs,\n",".xr-var-data,\n",".xr-index-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",".xr-no-icon {\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: 8000, obs_dim_0: 150, obs_dim_1: 6)\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 ... 7993 7994 7995 7996 7997 7998 7999\n","  * obs_dim_0  (obs_dim_0) int64 0 1 2 3 4 5 6 7 ... 143 144 145 146 147 148 149\n","  * obs_dim_1  (obs_dim_1) int64 0 1 2 3 4 5\n","Data variables:\n","    obs        (chain, draw, obs_dim_0, obs_dim_1) float32 -0.6052 ... 0.0\n","Attributes:\n","    created_at:                 2024-04-05T21:51:07.549556\n","    arviz_version:              0.15.1\n","    inference_library:          numpyro\n","    inference_library_version:  0.10.1</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-a6294d0e-3916-42f2-8eb9-d1e787d4639a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a6294d0e-3916-42f2-8eb9-d1e787d4639a' 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>: 8000</li><li><span class='xr-has-index'>obs_dim_0</span>: 150</li><li><span class='xr-has-index'>obs_dim_1</span>: 6</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-5c092402-7e88-4cfa-b33c-331241e798cc' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5c092402-7e88-4cfa-b33c-331241e798cc' 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-2ee2c576-b757-4143-8f17-7bb78eb08c73' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2ee2c576-b757-4143-8f17-7bb78eb08c73' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fe44cbb4-a91c-401b-b1fe-cb6b6032a8a1' class='xr-var-data-in' type='checkbox'><label for='data-fe44cbb4-a91c-401b-b1fe-cb6b6032a8a1' 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 ... 7996 7997 7998 7999</div><input id='attrs-d56c710e-e2a1-43e2-9efb-92aff1961590' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d56c710e-e2a1-43e2-9efb-92aff1961590' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5d260aa6-c9ac-44c3-9522-27c13b9a40f3' class='xr-var-data-in' type='checkbox'><label for='data-5d260aa6-c9ac-44c3-9522-27c13b9a40f3' 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, ..., 7997, 7998, 7999])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>obs_dim_0</span></div><div class='xr-var-dims'>(obs_dim_0)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 145 146 147 148 149</div><input id='attrs-78f86cc1-7744-47ef-83ca-e006232945f9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-78f86cc1-7744-47ef-83ca-e006232945f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-39a0db74-3e88-463f-bbc8-b1f8814652a7' class='xr-var-data-in' type='checkbox'><label for='data-39a0db74-3e88-463f-bbc8-b1f8814652a7' 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,   8,   9,  10,  11,  12,  13,\n","        14,  15,  16,  17,  18,  19,  20,  21,  22,  23,  24,  25,  26,  27,\n","        28,  29,  30,  31,  32,  33,  34,  35,  36,  37,  38,  39,  40,  41,\n","        42,  43,  44,  45,  46,  47,  48,  49,  50,  51,  52,  53,  54,  55,\n","        56,  57,  58,  59,  60,  61,  62,  63,  64,  65,  66,  67,  68,  69,\n","        70,  71,  72,  73,  74,  75,  76,  77,  78,  79,  80,  81,  82,  83,\n","        84,  85,  86,  87,  88,  89,  90,  91,  92,  93,  94,  95,  96,  97,\n","        98,  99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111,\n","       112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125,\n","       126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139,\n","       140, 141, 142, 143, 144, 145, 146, 147, 148, 149])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>obs_dim_1</span></div><div class='xr-var-dims'>(obs_dim_1)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5</div><input id='attrs-68c759cd-7b85-46af-9efb-b7b346171bd9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-68c759cd-7b85-46af-9efb-b7b346171bd9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-67fb053e-4fd0-42e2-8656-b0b02426d8b4' class='xr-var-data-in' type='checkbox'><label for='data-67fb053e-4fd0-42e2-8656-b0b02426d8b4' 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])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5c7e4ac4-1c3d-4d43-95da-143c049ae133' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5c7e4ac4-1c3d-4d43-95da-143c049ae133' 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>obs</span></div><div class='xr-var-dims'>(chain, draw, obs_dim_0, obs_dim_1)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.6052 -1.134 ... -0.08362 0.0</div><input id='attrs-54c50b96-4059-4c77-8815-3c7c47677196' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-54c50b96-4059-4c77-8815-3c7c47677196' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4a4cc7fb-66a0-45d3-9f3f-9901dc301d31' class='xr-var-data-in' type='checkbox'><label for='data-4a4cc7fb-66a0-45d3-9f3f-9901dc301d31' 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([[[[-6.05185688e-01, -1.13448513e+00, -4.76729900e-01,\n","          -5.00063002e-01, -5.40585577e-01, -5.29572904e-01],\n","         [-2.67217636e-01, -2.43370533e-02, -2.96824872e-02,\n","          -8.70540142e-01, -8.73365879e-01, -2.44312286e-02],\n","         [-1.81389344e+00, -4.97555733e-02, -6.80948496e-02,\n","          -1.43051147e-04, -5.97984791e-02,  0.00000000e+00],\n","         ...,\n","         [-3.98967028e-01, -5.84825635e-01, -1.47020650e+00,\n","          -5.11407852e-04, -5.35432220e-01, -1.63936138e-01],\n","         [-1.34927511e-01, -3.95419359e-01, -6.94665909e-02,\n","          -3.11797023e+00, -1.61344719e+00, -1.34497643e-01],\n","         [-1.76227224e+00, -7.10694134e-01, -1.03563619e+00,\n","          -6.11236095e-02, -2.41031185e-01, -4.61816788e-04]],\n","\n","        [[-3.45535874e-01, -1.26076114e+00, -4.37906384e-01,\n","          -2.37742662e-01, -2.86445856e-01, -3.85601044e-01],\n","         [-1.85565174e-01, -3.05795670e-02, -9.91189480e-02,\n","          -3.53702545e-01, -1.55549765e-01, -1.23977661e-05],\n","         [-2.78883934e+00, -1.62067652e-01, -3.74431610e-02,\n","          -4.48226929e-05, -1.62087679e-02,  0.00000000e+00],\n","...\n","          -8.92162323e-03, -2.17996240e-01, -3.62491608e-03],\n","         [-3.87832880e-01, -4.32332277e-01, -3.02225262e-01,\n","          -9.07027245e-01, -1.85739803e+00, -1.31950426e+00],\n","         [-1.87209606e+00, -3.81240636e-01, -2.73480177e-01,\n","          -3.07416916e-03, -9.54700410e-02, -1.19209290e-07]],\n","\n","        [[-2.82553703e-01, -1.03926396e+00, -2.11887121e-01,\n","          -1.34563923e+00, -4.48988706e-01, -1.45329070e+00],\n","         [-1.03377946e-01, -1.43745512e-01, -3.20402086e-02,\n","          -1.98439121e-01, -2.80707181e-01, -3.20028305e-01],\n","         [-1.66004384e+00, -1.82758093e-01, -1.84335709e-02,\n","           0.00000000e+00, -5.96046448e-07, -2.86102295e-06],\n","         ...,\n","         [-5.98345995e-01, -4.56141651e-01, -6.61902189e-01,\n","          -3.17983806e-01, -6.17516994e-01, -5.10048866e-03],\n","         [-8.80448341e-01, -7.34122038e-01, -8.10693324e-01,\n","          -2.72105932e+00, -6.06975257e-01, -4.15518999e-01],\n","         [-2.72870994e+00, -2.10821390e-01, -4.99205589e-02,\n","          -1.92277431e-02, -8.36210251e-02,  0.00000000e+00]]]],\n","      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-262550a5-9996-478c-94db-149f3f8afb96' class='xr-section-summary-in' type='checkbox'  ><label for='section-262550a5-9996-478c-94db-149f3f8afb96' class='xr-section-summary' >Indexes: <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-index-name'><div>chain</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-dde9242e-10ad-463e-884f-91b8d9e78317' class='xr-index-data-in' type='checkbox'/><label for='index-dde9242e-10ad-463e-884f-91b8d9e78317' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0, 1, 2, 3, 4, 5, 6, 7], dtype=&#x27;int64&#x27;, name=&#x27;chain&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>draw</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0916d739-990d-4f56-a279-400dac914b79' class='xr-index-data-in' type='checkbox'/><label for='index-0916d739-990d-4f56-a279-400dac914b79' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0,    1,    2,    3,    4,    5,    6,    7,    8,    9,\n","       ...\n","       7990, 7991, 7992, 7993, 7994, 7995, 7996, 7997, 7998, 7999],\n","      dtype=&#x27;int64&#x27;, name=&#x27;draw&#x27;, length=8000))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>obs_dim_0</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-946bcf71-9780-4aa3-8a4c-2c425786a12c' class='xr-index-data-in' type='checkbox'/><label for='index-946bcf71-9780-4aa3-8a4c-2c425786a12c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,\n","       ...\n","       140, 141, 142, 143, 144, 145, 146, 147, 148, 149],\n","      dtype=&#x27;int64&#x27;, name=&#x27;obs_dim_0&#x27;, length=150))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>obs_dim_1</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-518b869d-baac-49fd-9822-8d87b184804c' class='xr-index-data-in' type='checkbox'/><label for='index-518b869d-baac-49fd-9822-8d87b184804c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0, 1, 2, 3, 4, 5], dtype=&#x27;int64&#x27;, name=&#x27;obs_dim_1&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b96aa3f9-5fbf-45fb-a2a7-7fd92a7c4a10' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b96aa3f9-5fbf-45fb-a2a7-7fd92a7c4a10' 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>2024-04-05T21:51:07.549556</dd><dt><span>arviz_version :</span></dt><dd>0.15.1</dd><dt><span>inference_library :</span></dt><dd>numpyro</dd><dt><span>inference_library_version :</span></dt><dd>0.10.1</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_stats53f8546e-5404-49d6-8994-afa9e47f6b90\" class=\"xr-section-summary-in\" type=\"checkbox\">\n","                  <label for=\"idata_sample_stats53f8546e-5404-49d6-8994-afa9e47f6b90\" 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: 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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 / 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!important;\n","}\n","\n",".xr-attrs,\n",".xr-var-attrs,\n",".xr-var-data,\n",".xr-index-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",".xr-no-icon {\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: 8000)\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 ... 7993 7994 7995 7996 7997 7998 7999\n","Data variables:\n","    diverging  (chain, draw) bool False False False False ... False False False\n","Attributes:\n","    created_at:                 2024-04-05T21:51:03.454293\n","    arviz_version:              0.15.1\n","    inference_library:          numpyro\n","    inference_library_version:  0.10.1</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-11c885b3-b785-4f0a-a3ad-022d30dc4b85' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-11c885b3-b785-4f0a-a3ad-022d30dc4b85' 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>: 8000</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-48d9fa77-10bc-4077-85bf-86d777428832' class='xr-section-summary-in' type='checkbox'  checked><label for='section-48d9fa77-10bc-4077-85bf-86d777428832' 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-5dd418ac-6f3b-4bae-8371-d90ab0359474' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5dd418ac-6f3b-4bae-8371-d90ab0359474' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dbca206a-f40c-4808-95de-c6c3f868a017' class='xr-var-data-in' type='checkbox'><label for='data-dbca206a-f40c-4808-95de-c6c3f868a017' 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 ... 7996 7997 7998 7999</div><input id='attrs-a931b6c0-a457-4762-8200-b3dfe5f4c0cb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a931b6c0-a457-4762-8200-b3dfe5f4c0cb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4f6cb96-4129-47da-979b-0fb4e97309a4' class='xr-var-data-in' type='checkbox'><label for='data-f4f6cb96-4129-47da-979b-0fb4e97309a4' 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, ..., 7997, 7998, 7999])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f1a9da28-f219-45b1-aa72-0ecb811320c6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f1a9da28-f219-45b1-aa72-0ecb811320c6' 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>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-9b504496-2b89-4f3e-a9e6-79263d014274' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9b504496-2b89-4f3e-a9e6-79263d014274' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-47a7e656-224a-4464-b8a7-c27c505f2b98' class='xr-var-data-in' type='checkbox'><label for='data-47a7e656-224a-4464-b8a7-c27c505f2b98' 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></ul></div></li><li class='xr-section-item'><input id='section-080f0c73-4a26-490e-b140-426942ce370f' class='xr-section-summary-in' type='checkbox'  ><label for='section-080f0c73-4a26-490e-b140-426942ce370f' class='xr-section-summary' >Indexes: <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-index-name'><div>chain</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-756e8d14-0fab-4673-bd91-19ce85361ed0' class='xr-index-data-in' type='checkbox'/><label for='index-756e8d14-0fab-4673-bd91-19ce85361ed0' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0, 1, 2, 3, 4, 5, 6, 7], dtype=&#x27;int64&#x27;, name=&#x27;chain&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>draw</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-dda0a98d-a75d-4f34-9d5e-d43911f9ccf9' class='xr-index-data-in' type='checkbox'/><label for='index-dda0a98d-a75d-4f34-9d5e-d43911f9ccf9' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0,    1,    2,    3,    4,    5,    6,    7,    8,    9,\n","       ...\n","       7990, 7991, 7992, 7993, 7994, 7995, 7996, 7997, 7998, 7999],\n","      dtype=&#x27;int64&#x27;, name=&#x27;draw&#x27;, length=8000))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a66b19f1-55c8-4b33-9ac3-028e7adddb35' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a66b19f1-55c8-4b33-9ac3-028e7adddb35' 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>2024-04-05T21:51:03.454293</dd><dt><span>arviz_version :</span></dt><dd>0.15.1</dd><dt><span>inference_library :</span></dt><dd>numpyro</dd><dt><span>inference_library_version :</span></dt><dd>0.10.1</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_datac9559d84-6817-448f-89b7-94c1bd78b954\" class=\"xr-section-summary-in\" type=\"checkbox\">\n","                  <label for=\"idata_observed_datac9559d84-6817-448f-89b7-94c1bd78b954\" 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","                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div,\n",".xr-index-data,\n",".xr-attrs {\n","  padding-left: 25px !important;\n","}\n","\n",".xr-attrs,\n",".xr-var-attrs,\n",".xr-var-data,\n",".xr-index-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",".xr-no-icon {\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:    (obs_dim_0: 150, obs_dim_1: 6)\n","Coordinates:\n","  * obs_dim_0  (obs_dim_0) int64 0 1 2 3 4 5 6 7 ... 143 144 145 146 147 148 149\n","  * obs_dim_1  (obs_dim_1) int64 0 1 2 3 4 5\n","Data variables:\n","    obs        (obs_dim_0, obs_dim_1) int64 1 0 1 1 1 1 1 1 ... 1 2 2 1 2 1 1 1\n","Attributes:\n","    created_at:                 2024-04-05T21:51:07.565656\n","    arviz_version:              0.15.1\n","    inference_library:          numpyro\n","    inference_library_version:  0.10.1</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-bf8858fd-70be-4596-bff6-e3ea0ee67bb6' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-bf8858fd-70be-4596-bff6-e3ea0ee67bb6' 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'>obs_dim_0</span>: 150</li><li><span class='xr-has-index'>obs_dim_1</span>: 6</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-b3826b3b-6925-47b4-880d-20a5df625d38' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b3826b3b-6925-47b4-880d-20a5df625d38' 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'>obs_dim_0</span></div><div class='xr-var-dims'>(obs_dim_0)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 145 146 147 148 149</div><input id='attrs-0fb3ce48-d24e-43eb-aa5c-b8e4633bb654' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0fb3ce48-d24e-43eb-aa5c-b8e4633bb654' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-31ce9f53-638b-4a5b-a41c-97661c06ca01' class='xr-var-data-in' type='checkbox'><label for='data-31ce9f53-638b-4a5b-a41c-97661c06ca01' 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,   8,   9,  10,  11,  12,  13,\n","        14,  15,  16,  17,  18,  19,  20,  21,  22,  23,  24,  25,  26,  27,\n","        28,  29,  30,  31,  32,  33,  34,  35,  36,  37,  38,  39,  40,  41,\n","        42,  43,  44,  45,  46,  47,  48,  49,  50,  51,  52,  53,  54,  55,\n","        56,  57,  58,  59,  60,  61,  62,  63,  64,  65,  66,  67,  68,  69,\n","        70,  71,  72,  73,  74,  75,  76,  77,  78,  79,  80,  81,  82,  83,\n","        84,  85,  86,  87,  88,  89,  90,  91,  92,  93,  94,  95,  96,  97,\n","        98,  99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111,\n","       112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125,\n","       126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139,\n","       140, 141, 142, 143, 144, 145, 146, 147, 148, 149])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>obs_dim_1</span></div><div class='xr-var-dims'>(obs_dim_1)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5</div><input id='attrs-63bbf316-332c-4075-988c-eb5ebd4609e1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-63bbf316-332c-4075-988c-eb5ebd4609e1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3661dc67-1a4d-4a40-ba98-7c0d36624d1f' class='xr-var-data-in' type='checkbox'><label for='data-3661dc67-1a4d-4a40-ba98-7c0d36624d1f' 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])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-64143d31-1ab1-475b-91e0-d74c004d7225' class='xr-section-summary-in' type='checkbox'  checked><label for='section-64143d31-1ab1-475b-91e0-d74c004d7225' 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>obs</span></div><div class='xr-var-dims'>(obs_dim_0, obs_dim_1)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 0 1 1 1 1 1 1 ... 1 2 2 1 2 1 1 1</div><input id='attrs-6020e206-688e-4e6b-8ccb-49d3216614be' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6020e206-688e-4e6b-8ccb-49d3216614be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-31d14621-43ee-463a-b0e5-9e49367e037c' class='xr-var-data-in' type='checkbox'><label for='data-31d14621-43ee-463a-b0e5-9e49367e037c' 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([[1, 0, 1, 1, 1, 1],\n","       [1, 1, 1, 1, 1, 0],\n","       [1, 0, 0, 0, 0, 0],\n","       [1, 1, 2, 2, 2, 2],\n","       [1, 1, 1, 1, 2, 2],\n","       [2, 1, 1, 1, 1, 0],\n","       [2, 0, 1, 0, 0, 0],\n","       [2, 2, 0, 1, 0, 0],\n","       [2, 1, 2, 2, 1, 1],\n","       [0, 0, 0, 0, 0, 0],\n","       [2, 2, 2, 2, 2, 0],\n","       [0, 0, 2, 0, 2, 0],\n","       [2, 2, 1, 2, 2, 0],\n","       [0, 0, 0, 0, 0, 0],\n","       [0, 0, 0, 0, 0, 0],\n","       [1, 0, 1, 1, 0, 0],\n","       [2, 0, 1, 0, 2, 0],\n","       [2, 2, 2, 2, 2, 2],\n","       [2, 1, 1, 1, 1, 0],\n","       [2, 2, 2, 0, 2, 2],\n","...\n","       [2, 2, 2, 2, 2, 2],\n","       [1, 2, 2, 0, 0, 0],\n","       [0, 0, 0, 0, 0, 0],\n","       [1, 1, 1, 2, 1, 2],\n","       [0, 0, 0, 0, 0, 0],\n","       [2, 2, 2, 2, 2, 2],\n","       [2, 2, 2, 2, 0, 0],\n","       [1, 1, 1, 1, 1, 0],\n","       [0, 0, 0, 0, 0, 0],\n","       [1, 1, 1, 0, 0, 0],\n","       [2, 1, 1, 1, 1, 2],\n","       [2, 2, 2, 2, 2, 1],\n","       [1, 1, 1, 1, 1, 1],\n","       [0, 0, 0, 0, 0, 0],\n","       [0, 2, 2, 0, 0, 0],\n","       [1, 1, 1, 2, 2, 2],\n","       [1, 1, 1, 1, 1, 1],\n","       [2, 2, 1, 2, 2, 2],\n","       [2, 2, 2, 0, 1, 2],\n","       [2, 1, 2, 1, 1, 1]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ebfd5f6e-c191-492f-8e54-cc1910af70fe' class='xr-section-summary-in' type='checkbox'  ><label for='section-ebfd5f6e-c191-492f-8e54-cc1910af70fe' class='xr-section-summary' >Indexes: <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-index-name'><div>obs_dim_0</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8dc05648-545c-478d-8d10-75aadab7c6b6' class='xr-index-data-in' type='checkbox'/><label for='index-8dc05648-545c-478d-8d10-75aadab7c6b6' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  0,   1,   2,   3,   4,   5,   6,   7,   8,   9,\n","       ...\n","       140, 141, 142, 143, 144, 145, 146, 147, 148, 149],\n","      dtype=&#x27;int64&#x27;, name=&#x27;obs_dim_0&#x27;, length=150))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>obs_dim_1</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-15cd7846-9a75-47ca-8476-318f9e5768ba' class='xr-index-data-in' type='checkbox'/><label for='index-15cd7846-9a75-47ca-8476-318f9e5768ba' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0, 1, 2, 3, 4, 5], dtype=&#x27;int64&#x27;, name=&#x27;obs_dim_1&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b02dd153-a4bd-49aa-9559-aae77650d282' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b02dd153-a4bd-49aa-9559-aae77650d282' 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>2024-04-05T21:51:07.565656</dd><dt><span>arviz_version :</span></dt><dd>0.15.1</dd><dt><span>inference_library :</span></dt><dd>numpyro</dd><dt><span>inference_library_version :</span></dt><dd>0.10.1</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: 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az.from_numpyro(mcmc)\n","idata"]},{"cell_type":"code","execution_count":30,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":598},"id":"PUhu-Gb5zWcq","outputId":"72300fe9-a154-46c5-e805-658b81497120","executionInfo":{"status":"ok","timestamp":1712354080759,"user_tz":-540,"elapsed":212723,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.10/dist-packages/arviz/utils.py:184: NumbaDeprecationWarning: The 'nopython' keyword argument was not supplied to the 'numba.jit' decorator. The implicit default value for this argument is currently False, but it will be changed to True in Numba 0.59.0. See https://numba.readthedocs.io/en/stable/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit for details.\n","  numba_fn = numba.jit(**self.kwargs)(self.function)\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 1200x600 with 6 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\n"},"metadata":{}}],"source":["axes = az.plot_trace(idata)\n","plt.gcf().subplots_adjust(wspace=0.5, hspace=0.5)"]},{"cell_type":"code","execution_count":31,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"25lh29fMzWcq","outputId":"9c2348c7-a3ef-4e49-ba38-c260db87be59","executionInfo":{"status":"ok","timestamp":1712354084310,"user_tz":-540,"elapsed":3557,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.10/dist-packages/arviz/utils.py:184: NumbaDeprecationWarning: The 'nopython' keyword argument was not supplied to the 'numba.jit' decorator. The implicit default value for this argument is currently False, but it will be changed to True in Numba 0.59.0. See https://numba.readthedocs.io/en/stable/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit for details.\n","  numba_fn = numba.jit(**self.kwargs)(self.function)\n"]},{"output_type":"execute_result","data":{"text/plain":["                 mean     sd  hdi_3%  hdi_97%  mcse_mean  mcse_sd  ess_bulk  \\\n","theta[0, 0, 0] -0.024  0.155  -0.317    0.263      0.002    0.001    7101.0   \n","theta[0, 0, 1] -0.678  0.436  -1.464   -0.050      0.004    0.003   10932.0   \n","theta[0, 0, 2] -1.472  1.010  -3.385   -0.034      0.008    0.005   18031.0   \n","theta[0, 1, 0]  0.206  0.237  -0.121    0.628      0.003    0.003    7614.0   \n","theta[0, 1, 1] -0.432  0.373  -1.106    0.094      0.005    0.004    8174.0   \n","theta[0, 1, 2] -0.086  0.219  -0.474    0.239      0.003    0.003    7362.0   \n","theta[0, 2, 0]  0.065  0.212  -0.322    0.471      0.003    0.002    6429.0   \n","theta[0, 2, 1] -0.830  0.679  -2.106    0.017      0.008    0.005    8769.0   \n","theta[0, 2, 2] -0.916  0.758  -2.343    0.064      0.007    0.005   13512.0   \n","theta[0, 3, 0]  1.367  1.112  -0.128    3.487      0.009    0.007   12122.0   \n","theta[0, 3, 1] -0.478  0.660  -1.787    0.464      0.006    0.004   12984.0   \n","theta[0, 3, 2] -1.728  1.227  -3.982    0.136      0.007    0.005   40193.0   \n","theta[0, 4, 0] -0.379  0.247  -0.857    0.041      0.003    0.002    7235.0   \n","theta[0, 4, 1] -1.820  0.984  -3.610   -0.226      0.010    0.007    8138.0   \n","theta[0, 4, 2] -2.084  1.191  -4.213   -0.140      0.012    0.008    9023.0   \n","theta[0, 5, 0]  2.075  1.292   0.029    4.408      0.008    0.006   24417.0   \n","theta[0, 5, 1] -0.461  0.735  -1.955    0.536      0.006    0.005   15311.0   \n","theta[0, 5, 2] -1.649  1.240  -3.978    0.204      0.007    0.005   39896.0   \n","theta[1, 0, 0] -1.694  0.802  -3.200   -0.443      0.006    0.004   22874.0   \n","theta[1, 0, 1] -0.202  0.086  -0.367   -0.051      0.001    0.000   19216.0   \n","theta[1, 0, 2] -0.125  0.104  -0.322    0.054      0.001    0.001   15141.0   \n","theta[1, 1, 0] -1.524  0.748  -2.912   -0.378      0.007    0.006   13268.0   \n","theta[1, 1, 1] -0.265  0.138  -0.513   -0.050      0.002    0.001   12078.0   \n","theta[1, 1, 2] -0.450  0.333  -1.020   -0.018      0.004    0.003   10045.0   \n","theta[1, 2, 0] -1.396  0.703  -2.697   -0.340      0.006    0.005   16081.0   \n","theta[1, 2, 1] -0.140  0.096  -0.316    0.018      0.001    0.001   11877.0   \n","theta[1, 2, 2] -0.254  0.215  -0.599    0.038      0.003    0.003   12255.0   \n","theta[1, 3, 0] -2.167  1.030  -4.068   -0.528      0.011    0.008    8167.0   \n","theta[1, 3, 1] -1.154  0.593  -2.250   -0.253      0.007    0.005    7080.0   \n","theta[1, 3, 2] -1.319  0.795  -2.806   -0.156      0.009    0.006    7583.0   \n","theta[1, 4, 0] -1.768  0.771  -3.217   -0.551      0.005    0.004   23846.0   \n","theta[1, 4, 1] -0.310  0.125  -0.546   -0.106      0.001    0.001   18632.0   \n","theta[1, 4, 2] -0.182  0.132  -0.424    0.036      0.001    0.001   15448.0   \n","theta[1, 5, 0] -0.492  0.334  -1.028   -0.102      0.007    0.005    5878.0   \n","theta[1, 5, 1] -0.556  0.363  -1.124   -0.134      0.008    0.006    6035.0   \n","theta[1, 5, 2] -0.402  0.401  -1.015    0.027      0.009    0.007    5143.0   \n","theta[2, 0, 0] -1.164  0.603  -2.287   -0.278      0.005    0.004   17626.0   \n","theta[2, 0, 1] -0.529  0.230  -0.953   -0.157      0.002    0.002   14414.0   \n","theta[2, 0, 2] -0.033  0.114  -0.248    0.176      0.001    0.001    8565.0   \n","theta[2, 1, 0] -1.849  0.961  -3.666   -0.361      0.006    0.004   29125.0   \n","theta[2, 1, 1] -0.405  0.182  -0.748   -0.105      0.001    0.001   18963.0   \n","theta[2, 1, 2]  0.160  0.128  -0.065    0.413      0.001    0.001   10862.0   \n","theta[2, 2, 0] -1.230  0.763  -2.662   -0.155      0.005    0.004   25950.0   \n","theta[2, 2, 1] -0.206  0.129  -0.449    0.022      0.001    0.001   16019.0   \n","theta[2, 2, 2]  0.325  0.184   0.020    0.671      0.002    0.001    9833.0   \n","theta[2, 3, 0] -0.892  0.400  -1.629   -0.287      0.004    0.003   15055.0   \n","theta[2, 3, 1] -2.861  1.061  -4.841   -1.085      0.008    0.005   21253.0   \n","theta[2, 3, 2] -0.421  0.271  -0.927   -0.015      0.003    0.002   10233.0   \n","theta[2, 4, 0] -0.799  0.382  -1.500   -0.244      0.004    0.003   15059.0   \n","theta[2, 4, 1] -0.456  0.193  -0.803   -0.161      0.002    0.002   13386.0   \n","theta[2, 4, 2] -0.079  0.118  -0.290    0.115      0.001    0.001    9032.0   \n","theta[2, 5, 0] -1.384  0.620  -2.504   -0.346      0.006    0.004   12568.0   \n","theta[2, 5, 1] -2.657  1.070  -4.623   -0.810      0.009    0.006   15042.0   \n","theta[2, 5, 2] -1.397  0.725  -2.726   -0.229      0.007    0.005   12352.0   \n","\n","                ess_tail  r_hat  \n","theta[0, 0, 0]   10682.0    1.0  \n","theta[0, 0, 1]   12945.0    1.0  \n","theta[0, 0, 2]   24775.0    1.0  \n","theta[0, 1, 0]   10251.0    1.0  \n","theta[0, 1, 1]    7639.0    1.0  \n","theta[0, 1, 2]    8640.0    1.0  \n","theta[0, 2, 0]   12244.0    1.0  \n","theta[0, 2, 1]   11219.0    1.0  \n","theta[0, 2, 2]   18308.0    1.0  \n","theta[0, 3, 0]   18952.0    1.0  \n","theta[0, 3, 1]   14902.0    1.0  \n","theta[0, 3, 2]   35759.0    1.0  \n","theta[0, 4, 0]    8377.0    1.0  \n","theta[0, 4, 1]   12302.0    1.0  \n","theta[0, 4, 2]   14383.0    1.0  \n","theta[0, 5, 0]   37449.0    1.0  \n","theta[0, 5, 1]   17073.0    1.0  \n","theta[0, 5, 2]   38167.0    1.0  \n","theta[1, 0, 0]   26289.0    1.0  \n","theta[1, 0, 1]   23628.0    1.0  \n","theta[1, 0, 2]   22969.0    1.0  \n","theta[1, 1, 0]   12633.0    1.0  \n","theta[1, 1, 1]    8707.0    1.0  \n","theta[1, 1, 2]    7781.0    1.0  \n","theta[1, 2, 0]   14520.0    1.0  \n","theta[1, 2, 1]    9559.0    1.0  \n","theta[1, 2, 2]    9647.0    1.0  \n","theta[1, 3, 0]   18719.0    1.0  \n","theta[1, 3, 1]   14096.0    1.0  \n","theta[1, 3, 2]   17889.0    1.0  \n","theta[1, 4, 0]   26768.0    1.0  \n","theta[1, 4, 1]   18013.0    1.0  \n","theta[1, 4, 2]   16614.0    1.0  \n","theta[1, 5, 0]    2816.0    1.0  \n","theta[1, 5, 1]    2772.0    1.0  \n","theta[1, 5, 2]    2658.0    1.0  \n","theta[2, 0, 0]   19333.0    1.0  \n","theta[2, 0, 1]   16485.0    1.0  \n","theta[2, 0, 2]   13929.0    1.0  \n","theta[2, 1, 0]   33202.0    1.0  \n","theta[2, 1, 1]   22791.0    1.0  \n","theta[2, 1, 2]   18769.0    1.0  \n","theta[2, 2, 0]   25505.0    1.0  \n","theta[2, 2, 1]   25544.0    1.0  \n","theta[2, 2, 2]   19357.0    1.0  \n","theta[2, 3, 0]   14966.0    1.0  \n","theta[2, 3, 1]   28623.0    1.0  \n","theta[2, 3, 2]   14145.0    1.0  \n","theta[2, 4, 0]   12919.0    1.0  \n","theta[2, 4, 1]   12869.0    1.0  \n","theta[2, 4, 2]   10891.0    1.0  \n","theta[2, 5, 0]   22515.0    1.0  \n","theta[2, 5, 1]   27605.0    1.0  \n","theta[2, 5, 2]   21621.0    1.0  "],"text/html":["\n","  <div id=\"df-a06dd343-dc2d-4c47-94a6-02924099ecf3\" class=\"colab-df-container\">\n","    <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>mean</th>\n","      <th>sd</th>\n","      <th>hdi_3%</th>\n","      <th>hdi_97%</th>\n","      <th>mcse_mean</th>\n","      <th>mcse_sd</th>\n","      <th>ess_bulk</th>\n","      <th>ess_tail</th>\n","      <th>r_hat</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>theta[0, 0, 0]</th>\n","      <td>-0.024</td>\n","      <td>0.155</td>\n","      <td>-0.317</td>\n","      <td>0.263</td>\n","      <td>0.002</td>\n","      <td>0.001</td>\n","      <td>7101.0</td>\n","      <td>10682.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[0, 0, 1]</th>\n","      <td>-0.678</td>\n","      <td>0.436</td>\n","      <td>-1.464</td>\n","      <td>-0.050</td>\n","      <td>0.004</td>\n","      <td>0.003</td>\n","      <td>10932.0</td>\n","      <td>12945.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[0, 0, 2]</th>\n","      <td>-1.472</td>\n","      <td>1.010</td>\n","      <td>-3.385</td>\n","      <td>-0.034</td>\n","      <td>0.008</td>\n","      <td>0.005</td>\n","      <td>18031.0</td>\n","      <td>24775.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[0, 1, 0]</th>\n","      <td>0.206</td>\n","      <td>0.237</td>\n","      <td>-0.121</td>\n","      <td>0.628</td>\n","      <td>0.003</td>\n","      <td>0.003</td>\n","      <td>7614.0</td>\n","      <td>10251.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[0, 1, 1]</th>\n","      <td>-0.432</td>\n","      <td>0.373</td>\n","      <td>-1.106</td>\n","      <td>0.094</td>\n","      <td>0.005</td>\n","      <td>0.004</td>\n","      <td>8174.0</td>\n","      <td>7639.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[0, 1, 2]</th>\n","      <td>-0.086</td>\n","      <td>0.219</td>\n","      <td>-0.474</td>\n","      <td>0.239</td>\n","      <td>0.003</td>\n","      <td>0.003</td>\n","      <td>7362.0</td>\n","      <td>8640.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[0, 2, 0]</th>\n","      <td>0.065</td>\n","      <td>0.212</td>\n","      <td>-0.322</td>\n","      <td>0.471</td>\n","      <td>0.003</td>\n","      <td>0.002</td>\n","      <td>6429.0</td>\n","      <td>12244.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[0, 2, 1]</th>\n","      <td>-0.830</td>\n","      <td>0.679</td>\n","      <td>-2.106</td>\n","      <td>0.017</td>\n","      <td>0.008</td>\n","      <td>0.005</td>\n","      <td>8769.0</td>\n","      <td>11219.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[0, 2, 2]</th>\n","      <td>-0.916</td>\n","      <td>0.758</td>\n","      <td>-2.343</td>\n","      <td>0.064</td>\n","      <td>0.007</td>\n","      <td>0.005</td>\n","      <td>13512.0</td>\n","      <td>18308.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[0, 3, 0]</th>\n","      <td>1.367</td>\n","      <td>1.112</td>\n","      <td>-0.128</td>\n","      <td>3.487</td>\n","      <td>0.009</td>\n","      <td>0.007</td>\n","      <td>12122.0</td>\n","      <td>18952.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[0, 3, 1]</th>\n","      <td>-0.478</td>\n","      <td>0.660</td>\n","      <td>-1.787</td>\n","      <td>0.464</td>\n","      <td>0.006</td>\n","      <td>0.004</td>\n","      <td>12984.0</td>\n","      <td>14902.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[0, 3, 2]</th>\n","      <td>-1.728</td>\n","      <td>1.227</td>\n","      <td>-3.982</td>\n","      <td>0.136</td>\n","      <td>0.007</td>\n","      <td>0.005</td>\n","      <td>40193.0</td>\n","      <td>35759.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[0, 4, 0]</th>\n","      <td>-0.379</td>\n","      <td>0.247</td>\n","      <td>-0.857</td>\n","      <td>0.041</td>\n","      <td>0.003</td>\n","      <td>0.002</td>\n","      <td>7235.0</td>\n","      <td>8377.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[0, 4, 1]</th>\n","      <td>-1.820</td>\n","      <td>0.984</td>\n","      <td>-3.610</td>\n","      <td>-0.226</td>\n","      <td>0.010</td>\n","      <td>0.007</td>\n","      <td>8138.0</td>\n","      <td>12302.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[0, 4, 2]</th>\n","      <td>-2.084</td>\n","      <td>1.191</td>\n","      <td>-4.213</td>\n","      <td>-0.140</td>\n","      <td>0.012</td>\n","      <td>0.008</td>\n","      <td>9023.0</td>\n","      <td>14383.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[0, 5, 0]</th>\n","      <td>2.075</td>\n","      <td>1.292</td>\n","      <td>0.029</td>\n","      <td>4.408</td>\n","      <td>0.008</td>\n","      <td>0.006</td>\n","      <td>24417.0</td>\n","      <td>37449.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[0, 5, 1]</th>\n","      <td>-0.461</td>\n","      <td>0.735</td>\n","      <td>-1.955</td>\n","      <td>0.536</td>\n","      <td>0.006</td>\n","      <td>0.005</td>\n","      <td>15311.0</td>\n","      <td>17073.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[0, 5, 2]</th>\n","      <td>-1.649</td>\n","      <td>1.240</td>\n","      <td>-3.978</td>\n","      <td>0.204</td>\n","      <td>0.007</td>\n","      <td>0.005</td>\n","      <td>39896.0</td>\n","      <td>38167.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[1, 0, 0]</th>\n","      <td>-1.694</td>\n","      <td>0.802</td>\n","      <td>-3.200</td>\n","      <td>-0.443</td>\n","      <td>0.006</td>\n","      <td>0.004</td>\n","      <td>22874.0</td>\n","      <td>26289.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[1, 0, 1]</th>\n","      <td>-0.202</td>\n","      <td>0.086</td>\n","      <td>-0.367</td>\n","      <td>-0.051</td>\n","      <td>0.001</td>\n","      <td>0.000</td>\n","      <td>19216.0</td>\n","      <td>23628.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[1, 0, 2]</th>\n","      <td>-0.125</td>\n","      <td>0.104</td>\n","      <td>-0.322</td>\n","      <td>0.054</td>\n","      <td>0.001</td>\n","      <td>0.001</td>\n","      <td>15141.0</td>\n","      <td>22969.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[1, 1, 0]</th>\n","      <td>-1.524</td>\n","      <td>0.748</td>\n","      <td>-2.912</td>\n","      <td>-0.378</td>\n","      <td>0.007</td>\n","      <td>0.006</td>\n","      <td>13268.0</td>\n","      <td>12633.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[1, 1, 1]</th>\n","      <td>-0.265</td>\n","      <td>0.138</td>\n","      <td>-0.513</td>\n","      <td>-0.050</td>\n","      <td>0.002</td>\n","      <td>0.001</td>\n","      <td>12078.0</td>\n","      <td>8707.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[1, 1, 2]</th>\n","      <td>-0.450</td>\n","      <td>0.333</td>\n","      <td>-1.020</td>\n","      <td>-0.018</td>\n","      <td>0.004</td>\n","      <td>0.003</td>\n","      <td>10045.0</td>\n","      <td>7781.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[1, 2, 0]</th>\n","      <td>-1.396</td>\n","      <td>0.703</td>\n","      <td>-2.697</td>\n","      <td>-0.340</td>\n","      <td>0.006</td>\n","      <td>0.005</td>\n","      <td>16081.0</td>\n","      <td>14520.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[1, 2, 1]</th>\n","      <td>-0.140</td>\n","      <td>0.096</td>\n","      <td>-0.316</td>\n","      <td>0.018</td>\n","      <td>0.001</td>\n","      <td>0.001</td>\n","      <td>11877.0</td>\n","      <td>9559.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[1, 2, 2]</th>\n","      <td>-0.254</td>\n","      <td>0.215</td>\n","      <td>-0.599</td>\n","      <td>0.038</td>\n","      <td>0.003</td>\n","      <td>0.003</td>\n","      <td>12255.0</td>\n","      <td>9647.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[1, 3, 0]</th>\n","      <td>-2.167</td>\n","      <td>1.030</td>\n","      <td>-4.068</td>\n","      <td>-0.528</td>\n","      <td>0.011</td>\n","      <td>0.008</td>\n","      <td>8167.0</td>\n","      <td>18719.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[1, 3, 1]</th>\n","      <td>-1.154</td>\n","      <td>0.593</td>\n","      <td>-2.250</td>\n","      <td>-0.253</td>\n","      <td>0.007</td>\n","      <td>0.005</td>\n","      <td>7080.0</td>\n","      <td>14096.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[1, 3, 2]</th>\n","      <td>-1.319</td>\n","      <td>0.795</td>\n","      <td>-2.806</td>\n","      <td>-0.156</td>\n","      <td>0.009</td>\n","      <td>0.006</td>\n","      <td>7583.0</td>\n","      <td>17889.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[1, 4, 0]</th>\n","      <td>-1.768</td>\n","      <td>0.771</td>\n","      <td>-3.217</td>\n","      <td>-0.551</td>\n","      <td>0.005</td>\n","      <td>0.004</td>\n","      <td>23846.0</td>\n","      <td>26768.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[1, 4, 1]</th>\n","      <td>-0.310</td>\n","      <td>0.125</td>\n","      <td>-0.546</td>\n","      <td>-0.106</td>\n","      <td>0.001</td>\n","      <td>0.001</td>\n","      <td>18632.0</td>\n","      <td>18013.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[1, 4, 2]</th>\n","      <td>-0.182</td>\n","      <td>0.132</td>\n","      <td>-0.424</td>\n","      <td>0.036</td>\n","      <td>0.001</td>\n","      <td>0.001</td>\n","      <td>15448.0</td>\n","      <td>16614.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[1, 5, 0]</th>\n","      <td>-0.492</td>\n","      <td>0.334</td>\n","      <td>-1.028</td>\n","      <td>-0.102</td>\n","      <td>0.007</td>\n","      <td>0.005</td>\n","      <td>5878.0</td>\n","      <td>2816.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[1, 5, 1]</th>\n","      <td>-0.556</td>\n","      <td>0.363</td>\n","      <td>-1.124</td>\n","      <td>-0.134</td>\n","      <td>0.008</td>\n","      <td>0.006</td>\n","      <td>6035.0</td>\n","      <td>2772.0</td>\n","      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     <td>0.400</td>\n","      <td>-1.629</td>\n","      <td>-0.287</td>\n","      <td>0.004</td>\n","      <td>0.003</td>\n","      <td>15055.0</td>\n","      <td>14966.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[2, 3, 1]</th>\n","      <td>-2.861</td>\n","      <td>1.061</td>\n","      <td>-4.841</td>\n","      <td>-1.085</td>\n","      <td>0.008</td>\n","      <td>0.005</td>\n","      <td>21253.0</td>\n","      <td>28623.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[2, 3, 2]</th>\n","      <td>-0.421</td>\n","      <td>0.271</td>\n","      <td>-0.927</td>\n","      <td>-0.015</td>\n","      <td>0.003</td>\n","      <td>0.002</td>\n","      <td>10233.0</td>\n","      <td>14145.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[2, 4, 0]</th>\n","      <td>-0.799</td>\n","      <td>0.382</td>\n","      <td>-1.500</td>\n","      <td>-0.244</td>\n","      <td>0.004</td>\n","      <td>0.003</td>\n","  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1]</th>\n","      <td>-2.657</td>\n","      <td>1.070</td>\n","      <td>-4.623</td>\n","      <td>-0.810</td>\n","      <td>0.009</td>\n","      <td>0.006</td>\n","      <td>15042.0</td>\n","      <td>27605.0</td>\n","      <td>1.0</td>\n","    </tr>\n","    <tr>\n","      <th>theta[2, 5, 2]</th>\n","      <td>-1.397</td>\n","      <td>0.725</td>\n","      <td>-2.726</td>\n","      <td>-0.229</td>\n","      <td>0.007</td>\n","      <td>0.005</td>\n","      <td>12352.0</td>\n","      <td>21621.0</td>\n","      <td>1.0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a06dd343-dc2d-4c47-94a6-02924099ecf3')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 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\"num_unique_values\": 12,\n        \"samples\": [\n          0.001,\n          0.012,\n          0.002\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"mcse_sd\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.0021026255591019907,\n        \"min\": 0.0,\n        \"max\": 0.008,\n        \"num_unique_values\": 9,\n        \"samples\": [\n          0.006,\n          0.003,\n          0.007\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ess_bulk\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 7539.9578216877435,\n        \"min\": 5143.0,\n        \"max\": 40193.0,\n        \"num_unique_values\": 54,\n        \"samples\": [\n          19216.0,\n          13386.0,\n          15059.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ess_tail\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 8382.590599321613,\n        \"min\": 2658.0,\n        \"max\": 38167.0,\n        \"num_unique_values\": 54,\n        \"samples\": [\n          23628.0,\n          12869.0,\n          12919.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"r_hat\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.0,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"}},"metadata":{},"execution_count":31}],"source":["az.summary(idata, var_names=['theta'])"]},{"cell_type":"markdown","metadata":{"id":"gAOTWSGWzWcq"},"source":["## Evaluate Rhat\n","\n","Evaluate whether the Rhat values of all parameters were less than 1.10."]},{"cell_type":"code","execution_count":32,"metadata":{"id":"5Oox-MLfzWcr","executionInfo":{"status":"ok","timestamp":1712354117102,"user_tz":-540,"elapsed":32832,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[],"source":["df = az.summary(idata)"]},{"cell_type":"code","execution_count":33,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"2ETRj8vezWcr","outputId":"41878dd1-bd7a-47cd-d857-f9fbe3fb270c","executionInfo":{"status":"ok","timestamp":1712354117102,"user_tz":-540,"elapsed":22,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[{"output_type":"execute_result","data":{"text/plain":["alpha[0, 0, 0]    1.0\n","alpha[0, 0, 1]    1.0\n","alpha[0, 0, 2]    1.0\n","alpha[1, 0, 0]    1.0\n","alpha[1, 0, 1]    1.0\n","                 ... \n","theta[2, 4, 1]    1.0\n","theta[2, 4, 2]    1.0\n","theta[2, 5, 0]    1.0\n","theta[2, 5, 1]    1.0\n","theta[2, 5, 2]    1.0\n","Name: r_hat, Length: 507, dtype: float64"]},"metadata":{},"execution_count":33}],"source":["df['r_hat']"]},{"cell_type":"code","execution_count":34,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"T3PVpBpNzWcr","outputId":"d30552f4-5774-4f3f-a6bb-262db68ce6c7","executionInfo":{"status":"ok","timestamp":1712354117103,"user_tz":-540,"elapsed":18,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[{"output_type":"execute_result","data":{"text/plain":["0"]},"metadata":{},"execution_count":34}],"source":["np.count_nonzero(df['r_hat'] > 1.1)"]},{"cell_type":"markdown","metadata":{"id":"fxYpDrCyzWcr"},"source":["## Evaluate Theta"]},{"cell_type":"code","execution_count":35,"metadata":{"id":"aoB5XWX8zWcr","executionInfo":{"status":"ok","timestamp":1712354117103,"user_tz":-540,"elapsed":14,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[],"source":["# Doctor's ids to compare\n","idA = 1\n","idB = 5"]},{"cell_type":"code","execution_count":36,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"4x7T-sq4zWcr","outputId":"d1e70d9b-6963-4abf-e5fb-00a19bafa9cb","executionInfo":{"status":"ok","timestamp":1712354117103,"user_tz":-540,"elapsed":13,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[{"output_type":"execute_result","data":{"text/plain":["(8, 8000, 6, 3, 3)"]},"metadata":{},"execution_count":36}],"source":["theta = idata.posterior['theta'].to_numpy()\n","theta = theta.swapaxes(2, 3)\n","theta.shape"]},{"cell_type":"code","execution_count":37,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"gltnSIPpzWcr","outputId":"326c728e-a79d-49e8-8fd2-8d523ead888a","executionInfo":{"status":"ok","timestamp":1712354117104,"user_tz":-540,"elapsed":11,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[{"output_type":"stream","name":"stdout","text":["(8, 8000)\n","(8, 8000)\n"]}],"source":["theta_idA = theta[:, :, idA, 2, 2]\n","theta_idB = theta[:, :, idB, 2, 2]\n","\n","print(theta_idA.shape)\n","print(theta_idB.shape)"]},{"cell_type":"code","execution_count":38,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":0},"id":"2ZyGAiryzWcr","outputId":"35978da4-6b76-4cbc-9a20-2da6f35182e4","executionInfo":{"status":"ok","timestamp":1712354117867,"user_tz":-540,"elapsed":770,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 1000x400 with 2 Axes>"],"image/png":"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\n"},"metadata":{}}],"source":["fig, axes = plt.subplots(1, 2, figsize=(10, 4))\n","\n","az.plot_posterior(theta_idA, ax=axes[0])\n","az.plot_posterior(theta_idB, ax=axes[1])\n","\n","plt.show()"]},{"cell_type":"code","execution_count":39,"metadata":{"id":"7CKqIgwLzWcr","executionInfo":{"status":"ok","timestamp":1712354117868,"user_tz":-540,"elapsed":23,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[],"source":["d = theta_idA - theta_idB"]},{"cell_type":"code","execution_count":40,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":54},"id":"BXZ_xJLwzWcr","outputId":"5e7c7fb9-c79e-4ebc-9b8d-6b76cad6806a","executionInfo":{"status":"ok","timestamp":1712354117868,"user_tz":-540,"elapsed":21,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}],"source":["az.plot_posterior(d, ref_val=0)\n","plt.show()"]},{"cell_type":"markdown","metadata":{"id":"jy9s_E2rzWcr"},"source":["## Calculate WAIC and LOO"]},{"cell_type":"code","execution_count":41,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"EFSSothCzWcs","outputId":"10af488a-ab28-4afb-c915-273bff8f3891","executionInfo":{"status":"ok","timestamp":1712354119180,"user_tz":-540,"elapsed":1330,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[{"output_type":"stream","name":"stderr","text":["<ipython-input-41-aa33c236106c>:1: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead.\n","  az.waic(idata, scale='deviance')\n","/usr/local/lib/python3.10/dist-packages/arviz/stats/stats.py:1645: UserWarning: For one or more samples the posterior variance of the log predictive densities exceeds 0.4. This could be indication of WAIC starting to fail. \n","See http://arxiv.org/abs/1507.04544 for details\n","  warnings.warn(\n"]},{"output_type":"execute_result","data":{"text/plain":["Computed from 64000 posterior samples and 900 observations log-likelihood matrix.\n","\n","              Estimate       SE\n","deviance_waic   998.52    40.79\n","p_waic          175.46        -\n","\n","There has been a warning during the calculation. Please check the results."]},"metadata":{},"execution_count":41}],"source":["az.waic(idata, scale='deviance')"]},{"cell_type":"code","execution_count":42,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"FX67stnNZoCF","outputId":"7beeffcf-1610-49c3-f6a2-48bb0a51bf68","executionInfo":{"status":"ok","timestamp":1712354134480,"user_tz":-540,"elapsed":15304,"user":{"displayName":"Eiji Ohta","userId":"15998100295259505885"}}},"outputs":[{"output_type":"stream","name":"stderr","text":["<ipython-input-42-f6188337fe90>:1: DeprecationWarning: `product` is deprecated as of NumPy 1.25.0, and will be removed in NumPy 2.0. Please use `prod` instead.\n","  az.loo(idata, scale='deviance')\n","/usr/local/lib/python3.10/dist-packages/arviz/stats/stats.py:1037: RuntimeWarning: overflow encountered in exp\n","  weights = 1 / np.exp(len_scale - len_scale[:, None]).sum(axis=1)\n","/usr/local/lib/python3.10/dist-packages/arviz/stats/stats.py:803: UserWarning: Estimated shape parameter of Pareto distribution is greater than 0.7 for one or more samples. You should consider using a more robust model, this is because importance sampling is less likely to work well if the marginal posterior and LOO posterior are very different. This is more likely to happen with a non-robust model and highly influential observations.\n","  warnings.warn(\n"]},{"output_type":"execute_result","data":{"text/plain":["Computed from 64000 posterior samples and 900 observations log-likelihood matrix.\n","\n","             Estimate       SE\n","deviance_loo  1121.28    48.07\n","p_loo          236.84        -\n","\n","There has been a warning during the calculation. Please check the results.\n","------\n","\n","Pareto k diagnostic values:\n","                         Count   Pct.\n","(-Inf, 0.5]   (good)      411   45.7%\n"," (0.5, 0.7]   (ok)        294   32.7%\n","   (0.7, 1]   (bad)       185   20.6%\n","   (1, Inf)   (very bad)   10    1.1%"]},"metadata":{},"execution_count":42}],"source":["az.loo(idata, scale='deviance')"]},{"cell_type":"markdown","metadata":{"id":"PWxHVp74zWcs"},"source":["## Export Inference Data"]},{"cell_type":"code","execution_count":43,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":34},"id":"AakVzoqezWcs","outputId":"2877f969-ec0e-4a08-fde8-333a81e38c21","executionInfo":{"status":"ok","timestamp":1712354154939,"user_tz":-540,"elapsed":20462,"user":{"displayName":"Eiji 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