diff --git a/notebooks/Linear Regression/LR_3_6.ipynb b/notebooks/Linear Regression/LR_3_6.ipynb
index 55a2e6c6124b4b2dc43464e0c8a241ba8c4f7cff..b538a06d5ac358b9a9a101deed2b0914aa967041 100644
--- a/notebooks/Linear Regression/LR_3_6.ipynb
+++ b/notebooks/Linear Regression/LR_3_6.ipynb
@@ -10,12 +10,20 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 1,
"id": "9b297a0e-f8a2-4d90-9e54-c0aca8c9f5e0",
"metadata": {
"tags": []
},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "WARNING (pytensor.tensor.blas): Using NumPy C-API based implementation for BLAS functions.\n"
+ ]
+ }
+ ],
"source": [
"import arviz as az\n",
"import matplotlib.pyplot as plt\n",
@@ -29,7 +37,7 @@
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 2,
"id": "3f34cf56-8b10-4508-b280-da0637859962",
"metadata": {
"tags": []
@@ -59,7 +67,7 @@
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 3,
"id": "c8e3cb1d-d402-4684-9925-137757ca12da",
"metadata": {
"tags": []
@@ -104,7 +112,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
- "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 60 seconds.\n"
+ "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 5 seconds.\n"
]
}
],
@@ -120,7 +128,7 @@
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": 4,
"id": "81cd5230-463c-422e-989c-e400442c0aac",
"metadata": {
"tags": []
@@ -169,8 +177,8 @@
" <ul class=\"xr-sections group-sections\">\n",
" \n",
" <li class = \"xr-section-item\">\n",
- " <input id=\"idata_posterior3ad2e5a1-c01a-4f6a-a78d-a3f837694125\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
- " <label for=\"idata_posterior3ad2e5a1-c01a-4f6a-a78d-a3f837694125\" class = \"xr-section-summary\">posterior</label>\n",
+ " <input id=\"idata_posteriorbc6fbd08-54b5-4699-94d1-c37a4c937e6e\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+ " <label for=\"idata_posteriorbc6fbd08-54b5-4699-94d1-c37a4c937e6e\" 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\" class=\"xr-var-list\">\n",
@@ -204,14 +212,14 @@
" --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
"}\n",
"\n",
- "html[theme=dark],\n",
- "html[data-theme=dark],\n",
- "body[data-theme=dark],\n",
+ "html[theme=\"dark\"],\n",
+ "html[data-theme=\"dark\"],\n",
+ "body[data-theme=\"dark\"],\n",
"body.vscode-dark {\n",
" --xr-font-color0: rgba(255, 255, 255, 1);\n",
" --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
" --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
- " --xr-border-color: #1F1F1F;\n",
+ " --xr-border-color: #1f1f1f;\n",
" --xr-disabled-color: #515151;\n",
" --xr-background-color: #111111;\n",
" --xr-background-color-row-even: #111111;\n",
@@ -266,6 +274,7 @@
".xr-section-item input {\n",
" display: inline-block;\n",
" opacity: 0;\n",
+ " height: 0;\n",
"}\n",
"\n",
".xr-section-item input + label {\n",
@@ -302,7 +311,7 @@
"\n",
".xr-section-summary-in + label:before {\n",
" display: inline-block;\n",
- " content: 'â–º';\n",
+ " content: \"â–º\";\n",
" font-size: 11px;\n",
" width: 15px;\n",
" text-align: center;\n",
@@ -313,7 +322,7 @@
"}\n",
"\n",
".xr-section-summary-in:checked + label:before {\n",
- " content: 'â–¼';\n",
+ " content: \"â–¼\";\n",
"}\n",
"\n",
".xr-section-summary-in:checked + label > span {\n",
@@ -385,15 +394,15 @@
"}\n",
"\n",
".xr-dim-list:before {\n",
- " content: '(';\n",
+ " content: \"(\";\n",
"}\n",
"\n",
".xr-dim-list:after {\n",
- " content: ')';\n",
+ " content: \")\";\n",
"}\n",
"\n",
".xr-dim-list li:not(:last-child):after {\n",
- " content: ',';\n",
+ " content: \",\";\n",
" padding-right: 5px;\n",
"}\n",
"\n",
@@ -555,12 +564,12 @@
" mu (chain, draw, mu_dim_0) float64 6MB 17.95 9.331 ... 20.87 18.44\n",
" sigma (chain, draw) float64 32kB 3.315 3.293 3.16 ... 2.95 3.264 3.322\n",
"Attributes:\n",
- " created_at: 2024-09-23T09:27:23.416025+00:00\n",
+ " created_at: 2025-03-30T18:12:39.293994+00:00\n",
" arviz_version: 0.19.0\n",
" inference_library: pymc\n",
" inference_library_version: 5.16.2\n",
- " sampling_time: 60.4934868812561\n",
- " tuning_steps: 1000</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-4ae048f5-0b1d-4a69-a3a3-fb052c72439a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4ae048f5-0b1d-4a69-a3a3-fb052c72439a' 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>: 4</li><li><span class='xr-has-index'>draw</span>: 1000</li><li><span class='xr-has-index'>mu_dim_0</span>: 200</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-1dd9a482-d027-4497-8a80-ee3f973c5f6f' class='xr-section-summary-in' type='checkbox' checked><label for='section-1dd9a482-d027-4497-8a80-ee3f973c5f6f' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>chain</span></div><div class='xr-var-dims'>(chain)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3</div><input id='attrs-1adf3aa1-ec1f-4e2b-a011-70ac744a7e92' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1adf3aa1-ec1f-4e2b-a011-70ac744a7e92' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cf23eaf8-b16a-417c-b3af-6a5d14899546' class='xr-var-data-in' type='checkbox'><label for='data-cf23eaf8-b16a-417c-b3af-6a5d14899546' 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])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>draw</span></div><div class='xr-var-dims'>(draw)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 995 996 997 998 999</div><input id='attrs-afeb3c0b-04d1-45a3-b999-c006ffdb8bcd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-afeb3c0b-04d1-45a3-b999-c006ffdb8bcd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bee6b295-258b-42ce-b1ca-62ef44660de4' class='xr-var-data-in' type='checkbox'><label for='data-bee6b295-258b-42ce-b1ca-62ef44660de4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0, 1, 2, ..., 997, 998, 999])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>mu_dim_0</span></div><div class='xr-var-dims'>(mu_dim_0)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 195 196 197 198 199</div><input id='attrs-59c1ed23-5678-4819-8f95-06732a37d7ce' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-59c1ed23-5678-4819-8f95-06732a37d7ce' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c8bbff16-0c4a-49ea-adc8-a8cd10d030d9' class='xr-var-data-in' type='checkbox'><label for='data-c8bbff16-0c4a-49ea-adc8-a8cd10d030d9' 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",
+ " sampling_time: 4.794890403747559\n",
+ " tuning_steps: 1000</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-587f3042-2efa-4cd4-8525-512fe00fb72f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-587f3042-2efa-4cd4-8525-512fe00fb72f' 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>: 4</li><li><span class='xr-has-index'>draw</span>: 1000</li><li><span class='xr-has-index'>mu_dim_0</span>: 200</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-f17ca743-c98a-4a13-8bfe-c276f106ada1' class='xr-section-summary-in' type='checkbox' checked><label for='section-f17ca743-c98a-4a13-8bfe-c276f106ada1' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>chain</span></div><div class='xr-var-dims'>(chain)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3</div><input id='attrs-6d093942-fe3a-4f09-88ac-855590459979' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6d093942-fe3a-4f09-88ac-855590459979' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-422c06c6-b68b-4d93-a124-8dcc8cc7e952' class='xr-var-data-in' type='checkbox'><label for='data-422c06c6-b68b-4d93-a124-8dcc8cc7e952' 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])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>draw</span></div><div class='xr-var-dims'>(draw)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 995 996 997 998 999</div><input id='attrs-9892b2c9-e932-4f46-881a-1836f2ac5218' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9892b2c9-e932-4f46-881a-1836f2ac5218' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-14ef9630-4f14-4ff9-80c2-ba95caf4fced' class='xr-var-data-in' type='checkbox'><label for='data-14ef9630-4f14-4ff9-80c2-ba95caf4fced' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0, 1, 2, ..., 997, 998, 999])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>mu_dim_0</span></div><div class='xr-var-dims'>(mu_dim_0)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 195 196 197 198 199</div><input id='attrs-788b848e-b3f8-48b2-a0c3-96fa3466961b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-788b848e-b3f8-48b2-a0c3-96fa3466961b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2388124d-7350-4285-ac48-054526d4d784' class='xr-var-data-in' type='checkbox'><label for='data-2388124d-7350-4285-ac48-054526d4d784' 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",
@@ -574,21 +583,21 @@
" 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167,\n",
" 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181,\n",
" 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195,\n",
- " 196, 197, 198, 199])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-342fdd6c-9555-458b-af84-eabe747968cb' class='xr-section-summary-in' type='checkbox' checked><label for='section-342fdd6c-9555-458b-af84-eabe747968cb' class='xr-section-summary' >Data variables: <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>beta_0</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.265 7.077 7.22 ... 6.944 7.475</div><input id='attrs-cf2534b2-bd77-44fa-9ded-77051ee39c0c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cf2534b2-bd77-44fa-9ded-77051ee39c0c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6916ce13-345f-4144-bf38-15aee2e91ccf' class='xr-var-data-in' type='checkbox'><label for='data-6916ce13-345f-4144-bf38-15aee2e91ccf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[7.26500617, 7.07682019, 7.21955109, ..., 6.8559947 , 6.57954256,\n",
+ " 196, 197, 198, 199])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d269eb0b-6532-41b1-8d79-7f13358df0aa' class='xr-section-summary-in' type='checkbox' checked><label for='section-d269eb0b-6532-41b1-8d79-7f13358df0aa' class='xr-section-summary' >Data variables: <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>beta_0</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.265 7.077 7.22 ... 6.944 7.475</div><input id='attrs-06464d59-af0e-4d15-a8e6-3c146b177b5f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-06464d59-af0e-4d15-a8e6-3c146b177b5f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-76cfe65f-47d6-4c26-8a65-55799f96e160' class='xr-var-data-in' type='checkbox'><label for='data-76cfe65f-47d6-4c26-8a65-55799f96e160' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[7.26500617, 7.07682019, 7.21955109, ..., 6.8559947 , 6.57954256,\n",
" 7.00922815],\n",
" [6.71233945, 7.81606666, 7.66308642, ..., 6.12442414, 6.15426083,\n",
" 6.545233 ],\n",
" [6.38929607, 7.35131061, 6.35367154, ..., 6.79215836, 6.36530338,\n",
" 6.73434692],\n",
" [6.55377364, 6.95142639, 7.03213021, ..., 7.5660602 , 6.94414066,\n",
- " 7.47468976]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beta_1</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.04643 0.04773 ... 0.04966 0.04724</div><input id='attrs-c9d44b2f-66be-4e03-a244-d957a4ac08c1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c9d44b2f-66be-4e03-a244-d957a4ac08c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-95df2f01-2678-4904-a558-fa17ee609f1c' class='xr-var-data-in' type='checkbox'><label for='data-95df2f01-2678-4904-a558-fa17ee609f1c' 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([[0.04642829, 0.04773313, 0.04603266, ..., 0.04959686, 0.04961614,\n",
+ " 7.47468976]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beta_1</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.04643 0.04773 ... 0.04966 0.04724</div><input id='attrs-55fd0257-decf-45f1-9925-06f2197249bb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-55fd0257-decf-45f1-9925-06f2197249bb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-24cae23b-c3a3-4ccc-8793-e72d0d253af3' class='xr-var-data-in' type='checkbox'><label for='data-24cae23b-c3a3-4ccc-8793-e72d0d253af3' 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([[0.04642829, 0.04773313, 0.04603266, ..., 0.04959686, 0.04961614,\n",
" 0.04698685],\n",
" [0.0482838 , 0.04525793, 0.0462707 , ..., 0.05137193, 0.0522589 ,\n",
" 0.05113689],\n",
" [0.05433799, 0.04668428, 0.05179651, ..., 0.04929776, 0.05120773,\n",
" 0.04853955],\n",
" [0.04858248, 0.04943209, 0.04624127, ..., 0.04542056, 0.04965926,\n",
- " 0.04723799]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mu</span></div><div class='xr-var-dims'>(chain, draw, mu_dim_0)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>17.95 9.331 8.064 ... 20.87 18.44</div><input id='attrs-15013731-bf47-4a35-bb4a-fad72f3efb89' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-15013731-bf47-4a35-bb4a-fad72f3efb89' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c8a3d152-f0fb-4116-ae07-6fa30567e7a7' class='xr-var-data-in' type='checkbox'><label for='data-c8a3d152-f0fb-4116-ae07-6fa30567e7a7' 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([[[17.94815668, 9.33106526, 8.06357283, ..., 15.48281426,\n",
+ " 0.04723799]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mu</span></div><div class='xr-var-dims'>(chain, draw, mu_dim_0)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>17.95 9.331 8.064 ... 20.87 18.44</div><input id='attrs-1692b99d-5d2d-408a-93b4-e861d34177bc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1692b99d-5d2d-408a-93b4-e861d34177bc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d526365a-91e3-48b0-943c-419045dc6bb6' class='xr-var-data-in' type='checkbox'><label for='data-d526365a-91e3-48b0-943c-419045dc6bb6' 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([[[17.94815668, 9.33106526, 8.06357283, ..., 15.48281426,\n",
" 20.43207043, 18.04101327],\n",
" [18.06021323, 9.20094444, 7.89783001, ..., 15.52558407,\n",
" 20.61393565, 18.15567949],\n",
@@ -628,27 +637,27 @@
" [18.37073675, 9.1539778 , 7.79827996, ..., 15.73382996,\n",
" 21.02750724, 18.47005527],\n",
" [18.344152 , 9.57678046, 8.28718325, ..., 15.83581456,\n",
- " 20.87138464, 18.43862799]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sigma</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.315 3.293 3.16 ... 3.264 3.322</div><input id='attrs-b2c91779-94d6-4c03-9ff9-2371d99fa5c9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b2c91779-94d6-4c03-9ff9-2371d99fa5c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c7ef7e59-44ce-4ef5-93f9-0e73b8c9b58e' class='xr-var-data-in' type='checkbox'><label for='data-c7ef7e59-44ce-4ef5-93f9-0e73b8c9b58e' 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([[3.31546957, 3.29332037, 3.16014744, ..., 3.16884599, 3.11543427,\n",
+ " 20.87138464, 18.43862799]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sigma</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.315 3.293 3.16 ... 3.264 3.322</div><input id='attrs-16e95215-e150-49e3-bd6b-8986efd52075' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-16e95215-e150-49e3-bd6b-8986efd52075' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c6537e0-7fe9-40c2-b3fd-e432094d9ed4' class='xr-var-data-in' type='checkbox'><label for='data-8c6537e0-7fe9-40c2-b3fd-e432094d9ed4' 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([[3.31546957, 3.29332037, 3.16014744, ..., 3.16884599, 3.11543427,\n",
" 3.38792598],\n",
" [3.45042322, 3.45751029, 3.17477667, ..., 3.20576149, 3.19943222,\n",
" 3.24512331],\n",
" [3.39274682, 3.22235001, 3.35976371, ..., 3.39949674, 3.15923725,\n",
" 3.46370478],\n",
" [3.04791099, 3.06068845, 3.17057898, ..., 2.94973418, 3.26359728,\n",
- " 3.32156649]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fdd877e0-d8d4-4355-a945-85bd704580c5' class='xr-section-summary-in' type='checkbox' ><label for='section-fdd877e0-d8d4-4355-a945-85bd704580c5' class='xr-section-summary' >Indexes: <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-index-name'><div>chain</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-265a895f-a6b8-4852-bef7-98ad8ca444f4' class='xr-index-data-in' type='checkbox'/><label for='index-265a895f-a6b8-4852-bef7-98ad8ca444f4' 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], dtype='int64', name='chain'))</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-31b22c13-f9b3-45b0-90ec-3fb8951ee614' class='xr-index-data-in' type='checkbox'/><label for='index-31b22c13-f9b3-45b0-90ec-3fb8951ee614' 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",
+ " 3.32156649]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d06431dd-9e54-4e71-afc3-38a9d193158c' class='xr-section-summary-in' type='checkbox' ><label for='section-d06431dd-9e54-4e71-afc3-38a9d193158c' class='xr-section-summary' >Indexes: <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-index-name'><div>chain</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-fe5bb7a3-31dc-4b6a-a6aa-1712c7453aad' class='xr-index-data-in' type='checkbox'/><label for='index-fe5bb7a3-31dc-4b6a-a6aa-1712c7453aad' 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], dtype='int64', name='chain'))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>draw</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-1549e142-2efd-4cc9-9a00-b6352d939103' class='xr-index-data-in' type='checkbox'/><label for='index-1549e142-2efd-4cc9-9a00-b6352d939103' 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",
" 990, 991, 992, 993, 994, 995, 996, 997, 998, 999],\n",
- " dtype='int64', name='draw', length=1000))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>mu_dim_0</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e19bf253-17c3-4c47-bbe4-18bfada64cd0' class='xr-index-data-in' type='checkbox'/><label for='index-e19bf253-17c3-4c47-bbe4-18bfada64cd0' 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",
+ " dtype='int64', name='draw', length=1000))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>mu_dim_0</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-9ef31356-8380-414a-b2e0-30e2e3e57eab' class='xr-index-data-in' type='checkbox'/><label for='index-9ef31356-8380-414a-b2e0-30e2e3e57eab' 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",
" 190, 191, 192, 193, 194, 195, 196, 197, 198, 199],\n",
- " dtype='int64', name='mu_dim_0', length=200))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e9cf1830-dd6b-41c6-8547-8c97a0d72fed' class='xr-section-summary-in' type='checkbox' checked><label for='section-e9cf1830-dd6b-41c6-8547-8c97a0d72fed' class='xr-section-summary' >Attributes: <span>(6)</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>2024-09-23T09:27:23.416025+00:00</dd><dt><span>arviz_version :</span></dt><dd>0.19.0</dd><dt><span>inference_library :</span></dt><dd>pymc</dd><dt><span>inference_library_version :</span></dt><dd>5.16.2</dd><dt><span>sampling_time :</span></dt><dd>60.4934868812561</dd><dt><span>tuning_steps :</span></dt><dd>1000</dd></dl></div></li></ul></div></div><br></div>\n",
+ " dtype='int64', name='mu_dim_0', length=200))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6aca8b9f-a673-4d5a-8aa8-921a5240e7ae' class='xr-section-summary-in' type='checkbox' checked><label for='section-6aca8b9f-a673-4d5a-8aa8-921a5240e7ae' class='xr-section-summary' >Attributes: <span>(6)</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>2025-03-30T18:12:39.293994+00:00</dd><dt><span>arviz_version :</span></dt><dd>0.19.0</dd><dt><span>inference_library :</span></dt><dd>pymc</dd><dt><span>inference_library_version :</span></dt><dd>5.16.2</dd><dt><span>sampling_time :</span></dt><dd>4.794890403747559</dd><dt><span>tuning_steps :</span></dt><dd>1000</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_posterior_predictive5409a18f-4865-4b14-bb02-3f9a7c4b8b3a\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
- " <label for=\"idata_posterior_predictive5409a18f-4865-4b14-bb02-3f9a7c4b8b3a\" class = \"xr-section-summary\">posterior_predictive</label>\n",
+ " <input id=\"idata_posterior_predictive6bd0c305-f8dd-4a36-9de0-136b5a94ac8e\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+ " <label for=\"idata_posterior_predictive6bd0c305-f8dd-4a36-9de0-136b5a94ac8e\" class = \"xr-section-summary\">posterior_predictive</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",
@@ -682,14 +691,14 @@
" --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
"}\n",
"\n",
- "html[theme=dark],\n",
- "html[data-theme=dark],\n",
- "body[data-theme=dark],\n",
+ "html[theme=\"dark\"],\n",
+ "html[data-theme=\"dark\"],\n",
+ "body[data-theme=\"dark\"],\n",
"body.vscode-dark {\n",
" --xr-font-color0: rgba(255, 255, 255, 1);\n",
" --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
" --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
- " --xr-border-color: #1F1F1F;\n",
+ " --xr-border-color: #1f1f1f;\n",
" --xr-disabled-color: #515151;\n",
" --xr-background-color: #111111;\n",
" --xr-background-color-row-even: #111111;\n",
@@ -744,6 +753,7 @@
".xr-section-item input {\n",
" display: inline-block;\n",
" opacity: 0;\n",
+ " height: 0;\n",
"}\n",
"\n",
".xr-section-item input + label {\n",
@@ -780,7 +790,7 @@
"\n",
".xr-section-summary-in + label:before {\n",
" display: inline-block;\n",
- " content: 'â–º';\n",
+ " content: \"â–º\";\n",
" font-size: 11px;\n",
" width: 15px;\n",
" text-align: center;\n",
@@ -791,7 +801,7 @@
"}\n",
"\n",
".xr-section-summary-in:checked + label:before {\n",
- " content: 'â–¼';\n",
+ " content: \"â–¼\";\n",
"}\n",
"\n",
".xr-section-summary-in:checked + label > span {\n",
@@ -863,15 +873,15 @@
"}\n",
"\n",
".xr-dim-list:before {\n",
- " content: '(';\n",
+ " content: \"(\";\n",
"}\n",
"\n",
".xr-dim-list:after {\n",
- " content: ')';\n",
+ " content: \")\";\n",
"}\n",
"\n",
".xr-dim-list li:not(:last-child):after {\n",
- " content: ',';\n",
+ " content: \",\";\n",
" padding-right: 5px;\n",
"}\n",
"\n",
@@ -1030,10 +1040,10 @@
"Data variables:\n",
" y_pred (chain, draw, y_pred_dim_2) float64 6MB 16.02 9.174 ... 17.3\n",
"Attributes:\n",
- " created_at: 2024-09-23T09:27:24.018235+00:00\n",
+ " created_at: 2025-03-30T18:12:53.116440+00:00\n",
" arviz_version: 0.19.0\n",
" inference_library: pymc\n",
- " inference_library_version: 5.16.2</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-ecd11cb4-4214-4537-bc84-ce1ca32b389d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ecd11cb4-4214-4537-bc84-ce1ca32b389d' 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>: 4</li><li><span class='xr-has-index'>draw</span>: 1000</li><li><span class='xr-has-index'>y_pred_dim_2</span>: 200</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-325cd63a-8178-420c-84e4-028dca700a73' class='xr-section-summary-in' type='checkbox' checked><label for='section-325cd63a-8178-420c-84e4-028dca700a73' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>chain</span></div><div class='xr-var-dims'>(chain)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3</div><input id='attrs-df900d57-7bd1-43bb-92b1-9c7e08cd29f5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-df900d57-7bd1-43bb-92b1-9c7e08cd29f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1dd43f32-bf55-4aaa-b507-de98de43fd88' class='xr-var-data-in' type='checkbox'><label for='data-1dd43f32-bf55-4aaa-b507-de98de43fd88' 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])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>draw</span></div><div class='xr-var-dims'>(draw)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 995 996 997 998 999</div><input id='attrs-e8a2944d-d9f4-4091-b2ef-84b63467cb83' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e8a2944d-d9f4-4091-b2ef-84b63467cb83' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dc22746a-ba9c-41e9-8192-673d4904305f' class='xr-var-data-in' type='checkbox'><label for='data-dc22746a-ba9c-41e9-8192-673d4904305f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0, 1, 2, ..., 997, 998, 999])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y_pred_dim_2</span></div><div class='xr-var-dims'>(y_pred_dim_2)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 195 196 197 198 199</div><input id='attrs-64687761-5a1e-4af8-85fc-c67daf009f63' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-64687761-5a1e-4af8-85fc-c67daf009f63' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b876caf2-c7a1-4968-b928-1ef6c4da3a2e' class='xr-var-data-in' type='checkbox'><label for='data-b876caf2-c7a1-4968-b928-1ef6c4da3a2e' 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",
+ " inference_library_version: 5.16.2</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-2af09ac0-b30d-4e5b-a574-5b176e57d515' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2af09ac0-b30d-4e5b-a574-5b176e57d515' 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>: 4</li><li><span class='xr-has-index'>draw</span>: 1000</li><li><span class='xr-has-index'>y_pred_dim_2</span>: 200</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-32bb97bb-3622-4a15-a6ef-bfe52ab2f4ff' class='xr-section-summary-in' type='checkbox' checked><label for='section-32bb97bb-3622-4a15-a6ef-bfe52ab2f4ff' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>chain</span></div><div class='xr-var-dims'>(chain)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3</div><input id='attrs-b8a402e3-6d82-4070-b4a1-3cb1088103c9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b8a402e3-6d82-4070-b4a1-3cb1088103c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2596d568-629d-41ca-b2c8-5e2ac612141e' class='xr-var-data-in' type='checkbox'><label for='data-2596d568-629d-41ca-b2c8-5e2ac612141e' 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])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>draw</span></div><div class='xr-var-dims'>(draw)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 995 996 997 998 999</div><input id='attrs-ca1e7e74-a80f-42be-ab34-09b8204c787e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ca1e7e74-a80f-42be-ab34-09b8204c787e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5629a697-5fd0-4727-beec-33957545bce2' class='xr-var-data-in' type='checkbox'><label for='data-5629a697-5fd0-4727-beec-33957545bce2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0, 1, 2, ..., 997, 998, 999])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y_pred_dim_2</span></div><div class='xr-var-dims'>(y_pred_dim_2)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 195 196 197 198 199</div><input id='attrs-862da67a-0b70-4289-8693-8f1b989db87a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-862da67a-0b70-4289-8693-8f1b989db87a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eeb4515c-f191-498e-a865-c385282a532a' class='xr-var-data-in' type='checkbox'><label for='data-eeb4515c-f191-498e-a865-c385282a532a' 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",
@@ -1047,7 +1057,7 @@
" 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167,\n",
" 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181,\n",
" 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195,\n",
- " 196, 197, 198, 199])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2788fbc3-40ea-4b51-8874-a616a3d1649c' class='xr-section-summary-in' type='checkbox' checked><label for='section-2788fbc3-40ea-4b51-8874-a616a3d1649c' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>y_pred</span></div><div class='xr-var-dims'>(chain, draw, y_pred_dim_2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>16.02 9.174 7.694 ... 15.86 17.3</div><input id='attrs-af1d34ab-1005-4b06-9e6e-4beff429e87a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-af1d34ab-1005-4b06-9e6e-4beff429e87a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5996a306-e4f4-41f7-858a-e8af5e6031dd' class='xr-var-data-in' type='checkbox'><label for='data-5996a306-e4f4-41f7-858a-e8af5e6031dd' 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([[[16.02112788, 9.17358303, 7.69405692, ..., 10.77953181,\n",
+ " 196, 197, 198, 199])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ec3f5696-345d-4973-ba99-32f2e64fea05' class='xr-section-summary-in' type='checkbox' checked><label for='section-ec3f5696-345d-4973-ba99-32f2e64fea05' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>y_pred</span></div><div class='xr-var-dims'>(chain, draw, y_pred_dim_2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>16.02 9.174 7.694 ... 15.86 17.3</div><input id='attrs-65fe2019-6c07-49ae-aebb-f132670f627e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-65fe2019-6c07-49ae-aebb-f132670f627e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9926ed4d-76ff-4ed2-9c8c-6da5acfd080d' class='xr-var-data-in' type='checkbox'><label for='data-9926ed4d-76ff-4ed2-9c8c-6da5acfd080d' 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([[[16.02112788, 9.17358303, 7.69405692, ..., 10.77953181,\n",
" 15.26537236, 24.05630149],\n",
" [14.88025195, 12.89526215, 10.80539835, ..., 14.99595036,\n",
" 19.26973804, 15.34161261],\n",
@@ -1087,20 +1097,20 @@
" [18.00991715, 11.54234399, 9.04496734, ..., 16.4331185 ,\n",
" 20.56369506, 16.97208852],\n",
" [18.1923307 , 13.25266756, 12.47602704, ..., 17.41472199,\n",
- " 15.85819599, 17.30355213]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3fa2838b-4cf4-465a-b579-d0044912602f' class='xr-section-summary-in' type='checkbox' ><label for='section-3fa2838b-4cf4-465a-b579-d0044912602f' class='xr-section-summary' >Indexes: <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-index-name'><div>chain</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-68935c88-9be9-416e-8ad7-e96d38c0c6e7' class='xr-index-data-in' type='checkbox'/><label for='index-68935c88-9be9-416e-8ad7-e96d38c0c6e7' 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], dtype='int64', name='chain'))</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-8c90b0b0-6497-42ff-8306-1d96d027be47' class='xr-index-data-in' type='checkbox'/><label for='index-8c90b0b0-6497-42ff-8306-1d96d027be47' 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",
+ " 15.85819599, 17.30355213]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9e7b03f0-3f82-4495-9951-db632711a248' class='xr-section-summary-in' type='checkbox' ><label for='section-9e7b03f0-3f82-4495-9951-db632711a248' class='xr-section-summary' >Indexes: <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-index-name'><div>chain</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-25c0bde4-9b30-4c28-9b0b-5dd599440a30' class='xr-index-data-in' type='checkbox'/><label for='index-25c0bde4-9b30-4c28-9b0b-5dd599440a30' 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], dtype='int64', name='chain'))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>draw</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-d2b98174-a637-483e-8450-016046d1361c' class='xr-index-data-in' type='checkbox'/><label for='index-d2b98174-a637-483e-8450-016046d1361c' 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",
" 990, 991, 992, 993, 994, 995, 996, 997, 998, 999],\n",
- " dtype='int64', name='draw', length=1000))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y_pred_dim_2</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d1f06110-e10b-4a76-a3d0-efe1dc10a2ab' class='xr-index-data-in' type='checkbox'/><label for='index-d1f06110-e10b-4a76-a3d0-efe1dc10a2ab' 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",
+ " dtype='int64', name='draw', length=1000))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y_pred_dim_2</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-10e5bac6-13d9-4943-8a29-2275c0230898' class='xr-index-data-in' type='checkbox'/><label for='index-10e5bac6-13d9-4943-8a29-2275c0230898' 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",
" 190, 191, 192, 193, 194, 195, 196, 197, 198, 199],\n",
- " dtype='int64', name='y_pred_dim_2', length=200))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-25d06467-e1e6-4a63-b89a-d528978c4db8' class='xr-section-summary-in' type='checkbox' checked><label for='section-25d06467-e1e6-4a63-b89a-d528978c4db8' 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>2024-09-23T09:27:24.018235+00:00</dd><dt><span>arviz_version :</span></dt><dd>0.19.0</dd><dt><span>inference_library :</span></dt><dd>pymc</dd><dt><span>inference_library_version :</span></dt><dd>5.16.2</dd></dl></div></li></ul></div></div><br></div>\n",
+ " dtype='int64', name='y_pred_dim_2', length=200))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ab902c2c-2caf-49f1-84f8-f48ab6feab94' class='xr-section-summary-in' type='checkbox' checked><label for='section-ab902c2c-2caf-49f1-84f8-f48ab6feab94' 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>2025-03-30T18:12:53.116440+00:00</dd><dt><span>arviz_version :</span></dt><dd>0.19.0</dd><dt><span>inference_library :</span></dt><dd>pymc</dd><dt><span>inference_library_version :</span></dt><dd>5.16.2</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_stats4e5e066e-b6a7-42a5-8780-dd730afb9ba1\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
- " <label for=\"idata_sample_stats4e5e066e-b6a7-42a5-8780-dd730afb9ba1\" class = \"xr-section-summary\">sample_stats</label>\n",
+ " <input id=\"idata_sample_stats30d646a8-8ea2-48ba-a26c-85fb518c3a32\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+ " <label for=\"idata_sample_stats30d646a8-8ea2-48ba-a26c-85fb518c3a32\" 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",
@@ -1134,14 +1144,14 @@
" --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
"}\n",
"\n",
- "html[theme=dark],\n",
- "html[data-theme=dark],\n",
- "body[data-theme=dark],\n",
+ "html[theme=\"dark\"],\n",
+ "html[data-theme=\"dark\"],\n",
+ "body[data-theme=\"dark\"],\n",
"body.vscode-dark {\n",
" --xr-font-color0: rgba(255, 255, 255, 1);\n",
" --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
" --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
- " --xr-border-color: #1F1F1F;\n",
+ " --xr-border-color: #1f1f1f;\n",
" --xr-disabled-color: #515151;\n",
" --xr-background-color: #111111;\n",
" --xr-background-color-row-even: #111111;\n",
@@ -1196,6 +1206,7 @@
".xr-section-item input {\n",
" display: inline-block;\n",
" opacity: 0;\n",
+ " height: 0;\n",
"}\n",
"\n",
".xr-section-item input + label {\n",
@@ -1232,7 +1243,7 @@
"\n",
".xr-section-summary-in + label:before {\n",
" display: inline-block;\n",
- " content: 'â–º';\n",
+ " content: \"â–º\";\n",
" font-size: 11px;\n",
" width: 15px;\n",
" text-align: center;\n",
@@ -1243,7 +1254,7 @@
"}\n",
"\n",
".xr-section-summary-in:checked + label:before {\n",
- " content: 'â–¼';\n",
+ " content: \"â–¼\";\n",
"}\n",
"\n",
".xr-section-summary-in:checked + label > span {\n",
@@ -1315,15 +1326,15 @@
"}\n",
"\n",
".xr-dim-list:before {\n",
- " content: '(';\n",
+ " content: \"(\";\n",
"}\n",
"\n",
".xr-dim-list:after {\n",
- " content: ')';\n",
+ " content: \")\";\n",
"}\n",
"\n",
".xr-dim-list li:not(:last-child):after {\n",
- " content: ',';\n",
+ " content: \",\";\n",
" padding-right: 5px;\n",
"}\n",
"\n",
@@ -1486,120 +1497,120 @@
" index_in_trajectory (chain, draw) int64 32kB 4 4 -1 -1 -2 ... 1 -7 7 3 4\n",
" largest_eigval (chain, draw) float64 32kB nan nan nan ... nan nan\n",
" ... ...\n",
- " process_time_diff (chain, draw) float64 32kB 0.002919 ... 0.002439\n",
+ " process_time_diff (chain, draw) float64 32kB 0.001107 ... 0.001467\n",
" reached_max_treedepth (chain, draw) bool 4kB False False ... False False\n",
" smallest_eigval (chain, draw) float64 32kB nan nan nan ... nan nan\n",
" step_size (chain, draw) float64 32kB 0.6073 0.6073 ... 0.6137\n",
" step_size_bar (chain, draw) float64 32kB 0.5163 0.5163 ... 0.5243\n",
" tree_depth (chain, draw) int64 32kB 3 3 3 3 2 3 ... 2 3 4 3 3 4\n",
"Attributes:\n",
- " created_at: 2024-09-23T09:27:23.464126+00:00\n",
+ " created_at: 2025-03-30T18:12:39.312298+00:00\n",
" arviz_version: 0.19.0\n",
" inference_library: pymc\n",
" inference_library_version: 5.16.2\n",
- " sampling_time: 60.4934868812561\n",
- " tuning_steps: 1000</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-b8eb7587-20f0-4eb9-87e1-202d1c8ebe8f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b8eb7587-20f0-4eb9-87e1-202d1c8ebe8f' 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>: 4</li><li><span class='xr-has-index'>draw</span>: 1000</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-833fbd78-69bd-4b84-ac02-a4a6332ed3dd' class='xr-section-summary-in' type='checkbox' checked><label for='section-833fbd78-69bd-4b84-ac02-a4a6332ed3dd' 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</div><input id='attrs-703668df-318a-4151-8921-c300752321d5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-703668df-318a-4151-8921-c300752321d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-be16e1ef-2657-432a-9591-952a3b531c1b' class='xr-var-data-in' type='checkbox'><label for='data-be16e1ef-2657-432a-9591-952a3b531c1b' 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])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>draw</span></div><div class='xr-var-dims'>(draw)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 995 996 997 998 999</div><input id='attrs-a714a1bb-4384-42c3-b206-177a2d0f409f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a714a1bb-4384-42c3-b206-177a2d0f409f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-19891ec9-a125-4004-a1f5-888182ac4faa' class='xr-var-data-in' type='checkbox'><label for='data-19891ec9-a125-4004-a1f5-888182ac4faa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0, 1, 2, ..., 997, 998, 999])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-45fdc683-e359-4138-9445-4f2f08a9946a' class='xr-section-summary-in' type='checkbox' ><label for='section-45fdc683-e359-4138-9445-4f2f08a9946a' class='xr-section-summary' >Data variables: <span>(17)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>acceptance_rate</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.9986 0.9151 ... 0.9707 0.8525</div><input id='attrs-d312bd66-f1b1-471d-bdd7-a85a1477c0d2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d312bd66-f1b1-471d-bdd7-a85a1477c0d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a987d060-8f13-4c1e-a429-c9ce9f6f661c' class='xr-var-data-in' type='checkbox'><label for='data-a987d060-8f13-4c1e-a429-c9ce9f6f661c' 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([[0.99864594, 0.91514541, 0.95356728, ..., 1. , 0.71430128,\n",
+ " sampling_time: 4.794890403747559\n",
+ " tuning_steps: 1000</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-9d55fe81-aec8-4bfe-8566-5e25ebbb77ff' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-9d55fe81-aec8-4bfe-8566-5e25ebbb77ff' 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>: 4</li><li><span class='xr-has-index'>draw</span>: 1000</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-e7219cdf-337d-4227-a59c-2d7399dd4203' class='xr-section-summary-in' type='checkbox' checked><label for='section-e7219cdf-337d-4227-a59c-2d7399dd4203' 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</div><input id='attrs-59f91333-260d-4563-95ca-dffc1c48c269' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-59f91333-260d-4563-95ca-dffc1c48c269' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-92b8a2ad-0ce0-4114-8a09-ca7b4d94b9ef' class='xr-var-data-in' type='checkbox'><label for='data-92b8a2ad-0ce0-4114-8a09-ca7b4d94b9ef' 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])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>draw</span></div><div class='xr-var-dims'>(draw)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 995 996 997 998 999</div><input id='attrs-d4db5e64-e40e-4a0a-a3cd-29d0ab5013a8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d4db5e64-e40e-4a0a-a3cd-29d0ab5013a8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5127551-06a9-4427-b44c-c429b36ec6e6' class='xr-var-data-in' type='checkbox'><label for='data-d5127551-06a9-4427-b44c-c429b36ec6e6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 0, 1, 2, ..., 997, 998, 999])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-702f7bef-0171-4e79-851b-074f5b33fd0b' class='xr-section-summary-in' type='checkbox' ><label for='section-702f7bef-0171-4e79-851b-074f5b33fd0b' class='xr-section-summary' >Data variables: <span>(17)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>acceptance_rate</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.9986 0.9151 ... 0.9707 0.8525</div><input id='attrs-7d2228bc-491a-4ac6-9d66-f1a87d7c69fa' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7d2228bc-491a-4ac6-9d66-f1a87d7c69fa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8f86ef7b-2def-4497-b619-69444e0abfa4' class='xr-var-data-in' type='checkbox'><label for='data-8f86ef7b-2def-4497-b619-69444e0abfa4' 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([[0.99864594, 0.91514541, 0.95356728, ..., 1. , 0.71430128,\n",
" 0.92821709],\n",
" [0.99716108, 0.81690716, 0.79203067, ..., 0.89217827, 0.99186895,\n",
" 0.58977061],\n",
" [0.82046302, 0.98772897, 0.98550308, ..., 0.8815962 , 0.97931664,\n",
" 0.88946023],\n",
" [1. , 0.95407619, 0.99176581, ..., 0.90245232, 0.97066821,\n",
- " 0.85254356]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>diverging</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>bool</div><div class='xr-var-preview xr-preview'>False False False ... False False</div><input id='attrs-013a7d35-75bf-4943-a166-83cc77583f6b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-013a7d35-75bf-4943-a166-83cc77583f6b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d0efb30a-3067-4a26-b9d7-07a44b76d565' class='xr-var-data-in' type='checkbox'><label for='data-d0efb30a-3067-4a26-b9d7-07a44b76d565' 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",
+ " 0.85254356]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>diverging</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>bool</div><div class='xr-var-preview xr-preview'>False False False ... False False</div><input id='attrs-19044b2f-7bb0-4b4c-ab55-ffc3f5d35cfd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-19044b2f-7bb0-4b4c-ab55-ffc3f5d35cfd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f43f35bb-d55e-49ba-81a2-bd17e19401a5' class='xr-var-data-in' type='checkbox'><label for='data-f43f35bb-d55e-49ba-81a2-bd17e19401a5' 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",
- " [False, False, False, ..., False, False, False]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>energy</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>529.7 530.0 531.6 ... 533.3 531.4</div><input id='attrs-f02d6d79-819f-4a92-87dd-e9bf16fc360a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f02d6d79-819f-4a92-87dd-e9bf16fc360a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b1a355e-446c-4c0d-9cb7-05cb4c41dea9' class='xr-var-data-in' type='checkbox'><label for='data-9b1a355e-446c-4c0d-9cb7-05cb4c41dea9' 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([[529.68793195, 529.97221667, 531.57259425, ..., 530.21933301,\n",
+ " [False, False, False, ..., False, False, False]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>energy</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>529.7 530.0 531.6 ... 533.3 531.4</div><input id='attrs-a6f6da93-6fc9-40ea-9a69-8843cfea6c86' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a6f6da93-6fc9-40ea-9a69-8843cfea6c86' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7eac5349-15e5-4ccc-8414-42404b0e6c0b' class='xr-var-data-in' type='checkbox'><label for='data-7eac5349-15e5-4ccc-8414-42404b0e6c0b' 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([[529.68793195, 529.97221667, 531.57259425, ..., 530.21933301,\n",
" 530.99830682, 530.65798956],\n",
" [531.05894662, 533.15595595, 533.96176741, ..., 534.59235677,\n",
" 531.7396891 , 532.33947562],\n",
" [534.20612692, 533.3792547 , 531.47530059, ..., 530.74164895,\n",
" 531.10977779, 531.7995552 ],\n",
" [532.5840646 , 532.1239607 , 531.45870008, ..., 533.71368189,\n",
- " 533.25744413, 531.43416263]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>energy_error</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.00653 0.01079 ... 0.02984 0.3306</div><input id='attrs-d74862ad-23c4-410e-9a27-7444b52d058c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d74862ad-23c4-410e-9a27-7444b52d058c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cdfd3fa6-cb28-4abf-9b5f-e2485968bece' class='xr-var-data-in' type='checkbox'><label for='data-cdfd3fa6-cb28-4abf-9b5f-e2485968bece' 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([[ 0.00653029, 0.01079353, -0.00613459, ..., -0.02314382,\n",
+ " 533.25744413, 531.43416263]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>energy_error</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.00653 0.01079 ... 0.02984 0.3306</div><input id='attrs-f08bfb0e-f1aa-4f59-8f73-148e23cf5617' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f08bfb0e-f1aa-4f59-8f73-148e23cf5617' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-12df3407-1c9e-4a16-b701-5cba9e66b18d' class='xr-var-data-in' type='checkbox'><label for='data-12df3407-1c9e-4a16-b701-5cba9e66b18d' 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([[ 0.00653029, 0.01079353, -0.00613459, ..., -0.02314382,\n",
" -0.10623452, 0.0181384 ],\n",
" [-0.05300755, 0.44051905, -0.01430279, ..., 0.01533033,\n",
" -0.27881175, 0.02796653],\n",
" [ 0.53521374, -0.81384768, -0.05584936, ..., 0.0145976 ,\n",
" 0.01206605, 0.07139101],\n",
" [-0.20807377, -0.25429457, -0.11679125, ..., 0.20386936,\n",
- " 0.02984396, 0.330598 ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>index_in_trajectory</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>4 4 -1 -1 -2 5 -4 ... 3 1 -7 7 3 4</div><input id='attrs-13825916-c2dd-4bd4-808e-a86e94b559ed' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-13825916-c2dd-4bd4-808e-a86e94b559ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0257dabe-1b8e-42c8-ae62-b4e385259be4' class='xr-var-data-in' type='checkbox'><label for='data-0257dabe-1b8e-42c8-ae62-b4e385259be4' 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([[ 4, 4, -1, ..., 2, -2, 4],\n",
+ " 0.02984396, 0.330598 ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>index_in_trajectory</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>4 4 -1 -1 -2 5 -4 ... 3 1 -7 7 3 4</div><input id='attrs-529629f7-1101-421c-9a06-9a634d3c80df' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-529629f7-1101-421c-9a06-9a634d3c80df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4686a33c-f2c5-4585-8731-477835f3657a' class='xr-var-data-in' type='checkbox'><label for='data-4686a33c-f2c5-4585-8731-477835f3657a' 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([[ 4, 4, -1, ..., 2, -2, 4],\n",
" [ -1, -3, 4, ..., -2, 1, 2],\n",
" [ 3, 6, 4, ..., -14, 4, 5],\n",
- " [ -2, -2, 2, ..., 7, 3, 4]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>largest_eigval</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b6549c7c-7fe0-4869-b3c7-fd534aaa8f99' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b6549c7c-7fe0-4869-b3c7-fd534aaa8f99' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f14fb701-22fb-4cf5-9b15-fde8776e66ae' class='xr-var-data-in' type='checkbox'><label for='data-f14fb701-22fb-4cf5-9b15-fde8776e66ae' 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([[nan, nan, nan, ..., nan, nan, nan],\n",
+ " [ -2, -2, 2, ..., 7, 3, 4]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>largest_eigval</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-78cdd273-dc8b-4932-85f5-384d3cea83fc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-78cdd273-dc8b-4932-85f5-384d3cea83fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e62ed03-5596-40da-a945-20afafe586a2' class='xr-var-data-in' type='checkbox'><label for='data-3e62ed03-5596-40da-a945-20afafe586a2' 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([[nan, nan, nan, ..., nan, nan, nan],\n",
" [nan, nan, nan, ..., nan, nan, nan],\n",
" [nan, nan, nan, ..., nan, nan, nan],\n",
- " [nan, nan, nan, ..., nan, nan, nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lp</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-529.7 -529.6 ... -530.3 -531.0</div><input id='attrs-e1f46af2-9909-419f-81c6-d17785b35e99' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e1f46af2-9909-419f-81c6-d17785b35e99' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dfb3c14b-b84f-43d7-8199-5e02e4e69477' class='xr-var-data-in' type='checkbox'><label for='data-dfb3c14b-b84f-43d7-8199-5e02e4e69477' 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([[-529.67770941, -529.5591685 , -529.80455923, ..., -530.06582281,\n",
+ " [nan, nan, nan, ..., nan, nan, nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lp</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-529.7 -529.6 ... -530.3 -531.0</div><input id='attrs-5d1bfc26-d37a-4bc9-853a-442b95823872' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5d1bfc26-d37a-4bc9-853a-442b95823872' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-432ee268-e5fa-4f22-9da7-a32b6cfb0e2f' class='xr-var-data-in' type='checkbox'><label for='data-432ee268-e5fa-4f22-9da7-a32b6cfb0e2f' 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([[-529.67770941, -529.5591685 , -529.80455923, ..., -530.06582281,\n",
" -530.38153443, -529.92517296],\n",
" [-530.57072543, -532.21299517, -531.65463157, ..., -531.70881825,\n",
" -531.44595458, -530.39022505],\n",
" [-533.88727023, -529.89599779, -530.89335321, ..., -530.06767287,\n",
" -530.78259238, -530.5049978 ],\n",
" [-531.54281083, -530.90764974, -530.07655409, ..., -532.40271687,\n",
- " -530.25469814, -531.01024556]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>max_energy_error</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.01106 0.1638 ... -0.2604 0.5249</div><input id='attrs-ae4b8a56-c1ca-4564-ba5d-cc357c9f60e0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ae4b8a56-c1ca-4564-ba5d-cc357c9f60e0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a97e56e4-f0a9-4420-9440-c88779fde4a1' class='xr-var-data-in' type='checkbox'><label for='data-a97e56e4-f0a9-4420-9440-c88779fde4a1' 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([[-0.01105577, 0.1638225 , 0.126127 , ..., -0.05976064,\n",
+ " -530.25469814, -531.01024556]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>max_energy_error</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.01106 0.1638 ... -0.2604 0.5249</div><input id='attrs-fe1d2c1a-d5ed-4868-a74b-45980bc56351' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fe1d2c1a-d5ed-4868-a74b-45980bc56351' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-56443af9-326f-4980-adfa-34f9634618df' class='xr-var-data-in' type='checkbox'><label for='data-56443af9-326f-4980-adfa-34f9634618df' 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([[-0.01105577, 0.1638225 , 0.126127 , ..., -0.05976064,\n",
" 0.59335897, 0.15874793],\n",
" [-0.14149464, 0.51646905, 0.60953154, ..., 0.4709047 ,\n",
" -0.28593648, 0.95381116],\n",
" [ 0.53521374, -0.84415243, -0.09188661, ..., 0.28572098,\n",
" 0.04653303, 0.2336704 ],\n",
" [-0.40133454, -0.25429457, -0.11679125, ..., 0.22159366,\n",
- " -0.26041404, 0.52492848]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>n_steps</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.0 7.0 7.0 7.0 ... 7.0 7.0 11.0</div><input id='attrs-54a95ae0-d12f-4e7a-9c4a-2129dd726825' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-54a95ae0-d12f-4e7a-9c4a-2129dd726825' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fb5d1c3c-153b-42f4-afd9-57407642abb8' class='xr-var-data-in' type='checkbox'><label for='data-fb5d1c3c-153b-42f4-afd9-57407642abb8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 7., 7., 7., ..., 3., 3., 7.],\n",
+ " -0.26041404, 0.52492848]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>n_steps</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.0 7.0 7.0 7.0 ... 7.0 7.0 11.0</div><input id='attrs-665b9bab-151c-46f4-ab54-93a49915f3fb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-665b9bab-151c-46f4-ab54-93a49915f3fb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-96ba992a-8852-40c1-8235-06a9c5f3c13a' class='xr-var-data-in' type='checkbox'><label for='data-96ba992a-8852-40c1-8235-06a9c5f3c13a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 7., 7., 7., ..., 3., 3., 7.],\n",
" [ 7., 7., 7., ..., 7., 3., 3.],\n",
" [ 7., 15., 11., ..., 15., 7., 7.],\n",
- " [ 3., 3., 7., ..., 7., 7., 11.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>perf_counter_diff</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.00292 0.002671 ... 0.002438</div><input id='attrs-70d9e3e5-a2a1-4eb2-8e0c-143abd5c807d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-70d9e3e5-a2a1-4eb2-8e0c-143abd5c807d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-00a9dbe5-b2bf-4b7f-af67-e39492e0695f' class='xr-var-data-in' type='checkbox'><label for='data-00a9dbe5-b2bf-4b7f-af67-e39492e0695f' 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([[0.00291991, 0.00267108, 0.00283784, ..., 0.00138986, 0.00159195,\n",
- " 0.00303157],\n",
- " [0.00221688, 0.00171608, 0.00170091, ..., 0.00246503, 0.00131611,\n",
- " 0.00118487],\n",
- " [0.00320605, 0.0054105 , 0.00392095, ..., 0.00195648, 0.00096621,\n",
- " 0.00092805],\n",
- " [0.00148395, 0.00149595, 0.00273813, ..., 0.00231418, 0.00173073,\n",
- " 0.00243789]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>perf_counter_start</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.382e+06 2.382e+06 ... 2.382e+06</div><input id='attrs-60059c69-6e99-4dd5-9344-cc150e13b7d5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-60059c69-6e99-4dd5-9344-cc150e13b7d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0699e85a-29e3-4b58-ac63-7bcc5f69b1d9' class='xr-var-data-in' type='checkbox'><label for='data-0699e85a-29e3-4b58-ac63-7bcc5f69b1d9' 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([[2381996.70125474, 2381996.70460627, 2381996.70768432, ...,\n",
- " 2382014.61231519, 2382014.61407795, 2382014.70077207],\n",
- " [2381997.51135119, 2381997.51382159, 2381997.51578832, ...,\n",
- " 2382016.40806282, 2382016.41090161, 2382016.41254288],\n",
- " [2382000.60974019, 2382000.7008325 , 2382000.7066695 , ...,\n",
- " 2382017.04193916, 2382017.04409823, 2382017.04522228],\n",
- " [2381997.00544503, 2381997.00733118, 2381997.00922361, ...,\n",
- " 2382016.11276041, 2382016.11532191, 2382016.11729418]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>process_time_diff</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.002919 0.002672 ... 0.002439</div><input id='attrs-8a0f515f-9b98-4f7e-9d2d-98764b674d79' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8a0f515f-9b98-4f7e-9d2d-98764b674d79' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0c136a8b-7644-4196-84ee-3a1b30be25c8' class='xr-var-data-in' type='checkbox'><label for='data-0c136a8b-7644-4196-84ee-3a1b30be25c8' 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([[0.00291883, 0.00267211, 0.00278788, ..., 0.00139138, 0.00154237,\n",
- " 0.0030302 ],\n",
- " [0.0022161 , 0.00171702, 0.00170187, ..., 0.00246564, 0.00130538,\n",
- " 0.00118575],\n",
- " [0.00320654, 0.00541159, 0.00392219, ..., 0.00195808, 0.00096705,\n",
- " 0.00092926],\n",
- " [0.00148432, 0.00149755, 0.00274006, ..., 0.00231456, 0.00173169,\n",
- " 0.00243914]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>reached_max_treedepth</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-efabfba5-e45e-40d4-b518-889b8bf4d5a2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-efabfba5-e45e-40d4-b518-889b8bf4d5a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3425a3f6-a888-48f4-82ed-eb6e9286e5ff' class='xr-var-data-in' type='checkbox'><label for='data-3425a3f6-a888-48f4-82ed-eb6e9286e5ff' 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",
+ " [ 3., 3., 7., ..., 7., 7., 11.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>perf_counter_diff</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.001107 0.001573 ... 0.001466</div><input id='attrs-3f24dd0e-feda-4341-8e24-520060a0eae7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3f24dd0e-feda-4341-8e24-520060a0eae7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-88788bb9-d024-4999-9d30-3c016c174fff' class='xr-var-data-in' type='checkbox'><label for='data-88788bb9-d024-4999-9d30-3c016c174fff' 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([[0.00110664, 0.0015733 , 0.001547 , ..., 0.0006589 , 0.00059037,\n",
+ " 0.00109872],\n",
+ " [0.00108006, 0.00112787, 0.00112531, ..., 0.00104273, 0.00055597,\n",
+ " 0.00057452],\n",
+ " [0.00101652, 0.00197753, 0.0015139 , ..., 0.00281256, 0.00141311,\n",
+ " 0.00137335],\n",
+ " [0.00059067, 0.00059717, 0.00098187, ..., 0.00106256, 0.00111782,\n",
+ " 0.00146637]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>perf_counter_start</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9.435e+06 9.435e+06 ... 9.435e+06</div><input id='attrs-b345580e-8dea-4e6a-89ec-179e157e403d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b345580e-8dea-4e6a-89ec-179e157e403d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cfd54713-ca13-4b55-a44a-d5f41f2af634' class='xr-var-data-in' type='checkbox'><label for='data-cfd54713-ca13-4b55-a44a-d5f41f2af634' 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([[9435167.37337396, 9435167.37465058, 9435167.37659899, ...,\n",
+ " 9435168.6278672 , 9435168.62870892, 9435168.62945977],\n",
+ " [9435167.32369815, 9435167.32499814, 9435167.32630857, ...,\n",
+ " 9435168.5441957 , 9435168.54540916, 9435168.54631613],\n",
+ " [9435167.8556132 , 9435167.85680287, 9435167.85895235, ...,\n",
+ " 9435169.250339 , 9435169.2533869 , 9435169.25499622],\n",
+ " [9435167.52123542, 9435167.5220059 , 9435167.52275491, ...,\n",
+ " 9435168.90689245, 9435168.90822101, 9435168.90951942]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>process_time_diff</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.001107 0.001575 ... 0.001467</div><input id='attrs-6304ca53-8197-4dcc-873e-92c688b87dc5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6304ca53-8197-4dcc-873e-92c688b87dc5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-339bc3ee-ea80-45f6-afe2-251d28aad8b2' class='xr-var-data-in' type='checkbox'><label for='data-339bc3ee-ea80-45f6-afe2-251d28aad8b2' 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([[0.00110743, 0.00157451, 0.00154685, ..., 0.00066018, 0.00059133,\n",
+ " 0.00110067],\n",
+ " [0.00108046, 0.00112664, 0.00112705, ..., 0.00104422, 0.00055669,\n",
+ " 0.00057542],\n",
+ " [0.00101707, 0.00197929, 0.00151536, ..., 0.00281419, 0.00141451,\n",
+ " 0.0013751 ],\n",
+ " [0.00059138, 0.00059814, 0.00098323, ..., 0.00106378, 0.00111887,\n",
+ " 0.00146709]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>reached_max_treedepth</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-8dbbe827-949e-4040-84bf-87d1ff0c3a8c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8dbbe827-949e-4040-84bf-87d1ff0c3a8c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f8891cdb-8098-4db4-9ac3-d76faf93bc1b' class='xr-var-data-in' type='checkbox'><label for='data-f8891cdb-8098-4db4-9ac3-d76faf93bc1b' 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",
- " [False, False, False, ..., False, False, False]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>smallest_eigval</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-053d4539-20ea-4daf-affc-d33ba089e2f4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-053d4539-20ea-4daf-affc-d33ba089e2f4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0b41eb3f-4f88-406b-9d06-ad49edc56750' class='xr-var-data-in' type='checkbox'><label for='data-0b41eb3f-4f88-406b-9d06-ad49edc56750' 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([[nan, nan, nan, ..., nan, nan, nan],\n",
+ " [False, False, False, ..., False, False, False]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>smallest_eigval</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-055e284a-85de-40cf-b30f-c2cba5f15238' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-055e284a-85de-40cf-b30f-c2cba5f15238' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dea80003-bc90-487c-9179-47e96c3b20f2' class='xr-var-data-in' type='checkbox'><label for='data-dea80003-bc90-487c-9179-47e96c3b20f2' 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([[nan, nan, nan, ..., nan, nan, nan],\n",
" [nan, nan, nan, ..., nan, nan, nan],\n",
" [nan, nan, nan, ..., nan, nan, nan],\n",
- " [nan, nan, nan, ..., nan, nan, nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>step_size</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.6073 0.6073 ... 0.6137 0.6137</div><input id='attrs-1a4f3639-eb26-4643-af99-5b1769befbb1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1a4f3639-eb26-4643-af99-5b1769befbb1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0f76a48e-147d-46a9-993e-e7a7a30bfdd0' class='xr-var-data-in' type='checkbox'><label for='data-0f76a48e-147d-46a9-993e-e7a7a30bfdd0' 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([[0.60731086, 0.60731086, 0.60731086, ..., 0.60731086, 0.60731086,\n",
+ " [nan, nan, nan, ..., nan, nan, nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>step_size</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.6073 0.6073 ... 0.6137 0.6137</div><input id='attrs-a035b9d3-4f52-43f0-ad17-0bfd4cb16b00' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a035b9d3-4f52-43f0-ad17-0bfd4cb16b00' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e3313f5-0378-42ac-a916-6b70465aebf9' class='xr-var-data-in' type='checkbox'><label for='data-4e3313f5-0378-42ac-a916-6b70465aebf9' 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([[0.60731086, 0.60731086, 0.60731086, ..., 0.60731086, 0.60731086,\n",
" 0.60731086],\n",
" [0.44569627, 0.44569627, 0.44569627, ..., 0.44569627, 0.44569627,\n",
" 0.44569627],\n",
" [0.49126627, 0.49126627, 0.49126627, ..., 0.49126627, 0.49126627,\n",
" 0.49126627],\n",
" [0.61371751, 0.61371751, 0.61371751, ..., 0.61371751, 0.61371751,\n",
- " 0.61371751]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>step_size_bar</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.5163 0.5163 ... 0.5243 0.5243</div><input id='attrs-aa0f3e2d-30a1-4037-bdf0-0433e0cf8990' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-aa0f3e2d-30a1-4037-bdf0-0433e0cf8990' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b1434339-3cec-4e89-871d-f91b8d314554' class='xr-var-data-in' type='checkbox'><label for='data-b1434339-3cec-4e89-871d-f91b8d314554' 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([[0.51625884, 0.51625884, 0.51625884, ..., 0.51625884, 0.51625884,\n",
+ " 0.61371751]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>step_size_bar</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.5163 0.5163 ... 0.5243 0.5243</div><input id='attrs-50215513-d007-43fa-9d6d-594356ac9fb9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-50215513-d007-43fa-9d6d-594356ac9fb9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fc1adbd4-670e-4a87-9cc8-a06afc7db3ad' class='xr-var-data-in' type='checkbox'><label for='data-fc1adbd4-670e-4a87-9cc8-a06afc7db3ad' 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([[0.51625884, 0.51625884, 0.51625884, ..., 0.51625884, 0.51625884,\n",
" 0.51625884],\n",
" [0.47754971, 0.47754971, 0.47754971, ..., 0.47754971, 0.47754971,\n",
" 0.47754971],\n",
" [0.48028585, 0.48028585, 0.48028585, ..., 0.48028585, 0.48028585,\n",
" 0.48028585],\n",
" [0.52425611, 0.52425611, 0.52425611, ..., 0.52425611, 0.52425611,\n",
- " 0.52425611]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tree_depth</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>3 3 3 3 2 3 3 3 ... 3 1 2 3 4 3 3 4</div><input id='attrs-2763f53f-2519-4284-a77c-257006beb928' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2763f53f-2519-4284-a77c-257006beb928' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b5fb3cb3-b86c-4887-91e8-256b12505621' class='xr-var-data-in' type='checkbox'><label for='data-b5fb3cb3-b86c-4887-91e8-256b12505621' 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([[3, 3, 3, ..., 2, 2, 3],\n",
+ " 0.52425611]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tree_depth</span></div><div class='xr-var-dims'>(chain, draw)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>3 3 3 3 2 3 3 3 ... 3 1 2 3 4 3 3 4</div><input id='attrs-c853f343-724b-47f9-af62-4cb95e981933' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c853f343-724b-47f9-af62-4cb95e981933' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c9168d77-5d15-472d-91ec-c7b4171d853f' class='xr-var-data-in' type='checkbox'><label for='data-c9168d77-5d15-472d-91ec-c7b4171d853f' 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([[3, 3, 3, ..., 2, 2, 3],\n",
" [3, 3, 3, ..., 3, 2, 2],\n",
" [3, 4, 4, ..., 4, 3, 3],\n",
- " [2, 2, 3, ..., 3, 3, 4]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c52cb7a1-761b-49e3-9a96-151e741b1891' class='xr-section-summary-in' type='checkbox' ><label for='section-c52cb7a1-761b-49e3-9a96-151e741b1891' 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-0bc2a011-ee2f-4d6f-a665-23ae6fba4463' class='xr-index-data-in' type='checkbox'/><label for='index-0bc2a011-ee2f-4d6f-a665-23ae6fba4463' 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], dtype='int64', name='chain'))</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-19c897bd-bc5c-4fa8-a5dc-e1b4dbc86b59' class='xr-index-data-in' type='checkbox'/><label for='index-19c897bd-bc5c-4fa8-a5dc-e1b4dbc86b59' 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",
+ " [2, 2, 3, ..., 3, 3, 4]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-67703f59-fd63-4ef4-87d0-57d7f923618e' class='xr-section-summary-in' type='checkbox' ><label for='section-67703f59-fd63-4ef4-87d0-57d7f923618e' 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><input type='checkbox' disabled/><label></label><input id='index-2611f10a-b89a-46d7-ab75-0e3866287f89' class='xr-index-data-in' type='checkbox'/><label for='index-2611f10a-b89a-46d7-ab75-0e3866287f89' 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], dtype='int64', name='chain'))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>draw</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-114084ea-841f-48ab-83d1-270d3a968022' class='xr-index-data-in' type='checkbox'/><label for='index-114084ea-841f-48ab-83d1-270d3a968022' 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",
" 990, 991, 992, 993, 994, 995, 996, 997, 998, 999],\n",
- " dtype='int64', name='draw', length=1000))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-056d0fb9-5137-4214-ac2f-891b8f469428' class='xr-section-summary-in' type='checkbox' checked><label for='section-056d0fb9-5137-4214-ac2f-891b8f469428' class='xr-section-summary' >Attributes: <span>(6)</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>2024-09-23T09:27:23.464126+00:00</dd><dt><span>arviz_version :</span></dt><dd>0.19.0</dd><dt><span>inference_library :</span></dt><dd>pymc</dd><dt><span>inference_library_version :</span></dt><dd>5.16.2</dd><dt><span>sampling_time :</span></dt><dd>60.4934868812561</dd><dt><span>tuning_steps :</span></dt><dd>1000</dd></dl></div></li></ul></div></div><br></div>\n",
+ " dtype='int64', name='draw', length=1000))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-16722dda-c5a7-4bd4-b43e-554cb10aff2b' class='xr-section-summary-in' type='checkbox' checked><label for='section-16722dda-c5a7-4bd4-b43e-554cb10aff2b' class='xr-section-summary' >Attributes: <span>(6)</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>2025-03-30T18:12:39.312298+00:00</dd><dt><span>arviz_version :</span></dt><dd>0.19.0</dd><dt><span>inference_library :</span></dt><dd>pymc</dd><dt><span>inference_library_version :</span></dt><dd>5.16.2</dd><dt><span>sampling_time :</span></dt><dd>4.794890403747559</dd><dt><span>tuning_steps :</span></dt><dd>1000</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_data02662df6-2ccb-4353-9f96-7a6b346d04e5\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
- " <label for=\"idata_observed_data02662df6-2ccb-4353-9f96-7a6b346d04e5\" class = \"xr-section-summary\">observed_data</label>\n",
+ " <input id=\"idata_observed_datada9c543a-3e03-405f-886a-aed13867d379\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+ " <label for=\"idata_observed_datada9c543a-3e03-405f-886a-aed13867d379\" 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",
@@ -1633,14 +1644,14 @@
" --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
"}\n",
"\n",
- "html[theme=dark],\n",
- "html[data-theme=dark],\n",
- "body[data-theme=dark],\n",
+ "html[theme=\"dark\"],\n",
+ "html[data-theme=\"dark\"],\n",
+ "body[data-theme=\"dark\"],\n",
"body.vscode-dark {\n",
" --xr-font-color0: rgba(255, 255, 255, 1);\n",
" --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
" --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
- " --xr-border-color: #1F1F1F;\n",
+ " --xr-border-color: #1f1f1f;\n",
" --xr-disabled-color: #515151;\n",
" --xr-background-color: #111111;\n",
" --xr-background-color-row-even: #111111;\n",
@@ -1695,6 +1706,7 @@
".xr-section-item input {\n",
" display: inline-block;\n",
" opacity: 0;\n",
+ " height: 0;\n",
"}\n",
"\n",
".xr-section-item input + label {\n",
@@ -1731,7 +1743,7 @@
"\n",
".xr-section-summary-in + label:before {\n",
" display: inline-block;\n",
- " content: 'â–º';\n",
+ " content: \"â–º\";\n",
" font-size: 11px;\n",
" width: 15px;\n",
" text-align: center;\n",
@@ -1742,7 +1754,7 @@
"}\n",
"\n",
".xr-section-summary-in:checked + label:before {\n",
- " content: 'â–¼';\n",
+ " content: \"â–¼\";\n",
"}\n",
"\n",
".xr-section-summary-in:checked + label > span {\n",
@@ -1814,15 +1826,15 @@
"}\n",
"\n",
".xr-dim-list:before {\n",
- " content: '(';\n",
+ " content: \"(\";\n",
"}\n",
"\n",
".xr-dim-list:after {\n",
- " content: ')';\n",
+ " content: \")\";\n",
"}\n",
"\n",
".xr-dim-list li:not(:last-child):after {\n",
- " content: ',';\n",
+ " content: \",\";\n",
" padding-right: 5px;\n",
"}\n",
"\n",
@@ -1979,10 +1991,10 @@
"Data variables:\n",
" y_pred (y_pred_dim_0) float64 2kB 22.1 10.4 9.3 ... 12.8 25.5 13.4\n",
"Attributes:\n",
- " created_at: 2024-09-23T09:27:23.472162+00:00\n",
+ " created_at: 2025-03-30T18:12:39.318653+00:00\n",
" arviz_version: 0.19.0\n",
" inference_library: pymc\n",
- " inference_library_version: 5.16.2</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-224627ec-2ba6-442c-ac21-139f2f2b8a37' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-224627ec-2ba6-442c-ac21-139f2f2b8a37' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>y_pred_dim_0</span>: 200</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-86eb5b50-e09b-4844-b36e-6be9aa1aa8b3' class='xr-section-summary-in' type='checkbox' checked><label for='section-86eb5b50-e09b-4844-b36e-6be9aa1aa8b3' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y_pred_dim_0</span></div><div class='xr-var-dims'>(y_pred_dim_0)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 195 196 197 198 199</div><input id='attrs-e25770b0-4126-4ab8-a52c-ce8caa263b60' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e25770b0-4126-4ab8-a52c-ce8caa263b60' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e6bf9b1c-2d2c-4fbd-a939-1e5c5c0278d0' class='xr-var-data-in' type='checkbox'><label for='data-e6bf9b1c-2d2c-4fbd-a939-1e5c5c0278d0' 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",
+ " inference_library_version: 5.16.2</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-61fb2554-a069-495e-9aba-336177361dc7' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-61fb2554-a069-495e-9aba-336177361dc7' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>y_pred_dim_0</span>: 200</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-b6175c1c-fbe0-4a63-bce1-950548626c80' class='xr-section-summary-in' type='checkbox' checked><label for='section-b6175c1c-fbe0-4a63-bce1-950548626c80' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y_pred_dim_0</span></div><div class='xr-var-dims'>(y_pred_dim_0)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 ... 195 196 197 198 199</div><input id='attrs-c165b450-7557-4e42-950e-de6dc1549a2b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c165b450-7557-4e42-950e-de6dc1549a2b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ee55cb67-e327-4d01-a88d-558330148b1d' class='xr-var-data-in' type='checkbox'><label for='data-ee55cb67-e327-4d01-a88d-558330148b1d' 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",
@@ -1996,7 +2008,7 @@
" 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167,\n",
" 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181,\n",
" 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195,\n",
- " 196, 197, 198, 199])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7e42cf9a-e469-4e51-bf14-cf3d7bf280e4' class='xr-section-summary-in' type='checkbox' checked><label for='section-7e42cf9a-e469-4e51-bf14-cf3d7bf280e4' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>y_pred</span></div><div class='xr-var-dims'>(y_pred_dim_0)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>22.1 10.4 9.3 ... 12.8 25.5 13.4</div><input id='attrs-9a808144-a06f-400a-8fb0-9cbd5bcbd2cd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9a808144-a06f-400a-8fb0-9cbd5bcbd2cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-60f3d852-d743-4a4e-bdbd-553f862834c0' class='xr-var-data-in' type='checkbox'><label for='data-60f3d852-d743-4a4e-bdbd-553f862834c0' 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([22.1, 10.4, 9.3, 18.5, 12.9, 7.2, 11.8, 13.2, 4.8, 10.6, 8.6,\n",
+ " 196, 197, 198, 199])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-dcac4a27-19be-49ad-a319-37a3224941ef' class='xr-section-summary-in' type='checkbox' checked><label for='section-dcac4a27-19be-49ad-a319-37a3224941ef' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>y_pred</span></div><div class='xr-var-dims'>(y_pred_dim_0)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>22.1 10.4 9.3 ... 12.8 25.5 13.4</div><input id='attrs-13f0f785-821a-4690-973f-25e4bbc2ba4a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-13f0f785-821a-4690-973f-25e4bbc2ba4a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-81281aa5-21e8-4cb6-8f62-daa134c47411' class='xr-var-data-in' type='checkbox'><label for='data-81281aa5-21e8-4cb6-8f62-daa134c47411' 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([22.1, 10.4, 9.3, 18.5, 12.9, 7.2, 11.8, 13.2, 4.8, 10.6, 8.6,\n",
" 17.4, 9.2, 9.7, 19. , 22.4, 12.5, 24.4, 11.3, 14.6, 18. , 12.5,\n",
" 5.6, 15.5, 9.7, 12. , 15. , 15.9, 18.9, 10.5, 21.4, 11.9, 9.6,\n",
" 17.4, 9.5, 12.8, 25.4, 14.7, 10.1, 21.5, 16.6, 17.1, 20.7, 12.9,\n",
@@ -2014,10 +2026,10 @@
" 11.9, 8. , 12.2, 17.1, 15. , 8.4, 14.5, 7.6, 11.7, 11.5, 27. ,\n",
" 20.2, 11.7, 11.8, 12.6, 10.5, 12.2, 8.7, 26.2, 17.6, 22.6, 10.3,\n",
" 17.3, 15.9, 6.7, 10.8, 9.9, 5.9, 19.6, 17.3, 7.6, 9.7, 12.8,\n",
- " 25.5, 13.4])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d47ea9be-799c-4477-bf54-ba7e63d5a553' class='xr-section-summary-in' type='checkbox' ><label for='section-d47ea9be-799c-4477-bf54-ba7e63d5a553' class='xr-section-summary' >Indexes: <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-index-name'><div>y_pred_dim_0</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-34536ff7-dbe0-4b24-9cb3-c8f6eabed9e6' class='xr-index-data-in' type='checkbox'/><label for='index-34536ff7-dbe0-4b24-9cb3-c8f6eabed9e6' 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",
+ " 25.5, 13.4])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-665a54b9-2813-4670-80b0-07119cc58984' class='xr-section-summary-in' type='checkbox' ><label for='section-665a54b9-2813-4670-80b0-07119cc58984' class='xr-section-summary' >Indexes: <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-index-name'><div>y_pred_dim_0</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-fa92dd11-af5b-4b55-bdc7-4fd265c8b691' class='xr-index-data-in' type='checkbox'/><label for='index-fa92dd11-af5b-4b55-bdc7-4fd265c8b691' 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",
" 190, 191, 192, 193, 194, 195, 196, 197, 198, 199],\n",
- " dtype='int64', name='y_pred_dim_0', length=200))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c05f2244-f0c2-4b4a-884f-11c8317f2a2e' class='xr-section-summary-in' type='checkbox' checked><label for='section-c05f2244-f0c2-4b4a-884f-11c8317f2a2e' 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>2024-09-23T09:27:23.472162+00:00</dd><dt><span>arviz_version :</span></dt><dd>0.19.0</dd><dt><span>inference_library :</span></dt><dd>pymc</dd><dt><span>inference_library_version :</span></dt><dd>5.16.2</dd></dl></div></li></ul></div></div><br></div>\n",
+ " dtype='int64', name='y_pred_dim_0', length=200))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-471410c1-d311-41fc-a9ab-5b3004f685cb' class='xr-section-summary-in' type='checkbox' checked><label for='section-471410c1-d311-41fc-a9ab-5b3004f685cb' 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>2025-03-30T18:12:39.318653+00:00</dd><dt><span>arviz_version :</span></dt><dd>0.19.0</dd><dt><span>inference_library :</span></dt><dd>pymc</dd><dt><span>inference_library_version :</span></dt><dd>5.16.2</dd></dl></div></li></ul></div></div><br></div>\n",
" </ul>\n",
" </div>\n",
" </li>\n",
@@ -2374,7 +2386,7 @@
"\t> observed_data"
]
},
- "execution_count": 8,
+ "execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
@@ -2385,7 +2397,7 @@
},
{
"cell_type": "code",
- "execution_count": 14,
+ "execution_count": 5,
"id": "8ee76239-ae7e-4a5d-8976-ee808313f0e2",
"metadata": {
"tags": []
@@ -2393,7 +2405,7 @@
"outputs": [
{
"data": {
- "image/png": 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",
+ "image/png": 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",
"text/plain": [
"<Figure size 1200x500 with 1 Axes>"
]
@@ -2427,7 +2439,7 @@
"\n",
"ax.set_xlabel(\"TV Werbebudget\")\n",
"ax.set_ylabel(\"Verkauf\")\n",
- "plt.savefig(\"linear_verkauf_posterior_predictive.png\")"
+ "# plt.savefig(\"linear_verkauf_posterior_predictive.png\")"
]
}
],
diff --git a/notebooks/Linear Regression/LR_4_1.ipynb b/notebooks/Linear Regression/LR_4_1.ipynb
index d3a7767d276327f79f28a30c0f9d1e87798d476e..b6ed1a587dc7a9bb75890441e912c9fc26f40636 100644
--- a/notebooks/Linear Regression/LR_4_1.ipynb
+++ b/notebooks/Linear Regression/LR_4_1.ipynb
@@ -13,12 +13,20 @@
},
{
"cell_type": "code",
- "execution_count": 30,
+ "execution_count": 2,
"id": "9b297a0e-f8a2-4d90-9e54-c0aca8c9f5e0",
"metadata": {
"tags": []
},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "WARNING (pytensor.tensor.blas): Using NumPy C-API based implementation for BLAS functions.\n"
+ ]
+ }
+ ],
"source": [
"import arviz as az\n",
"import matplotlib.pyplot as plt\n",
@@ -32,7 +40,7 @@
},
{
"cell_type": "code",
- "execution_count": 31,
+ "execution_count": 3,
"id": "3f34cf56-8b10-4508-b280-da0637859962",
"metadata": {
"tags": []
@@ -62,7 +70,7 @@
},
{
"cell_type": "code",
- "execution_count": 32,
+ "execution_count": 4,
"id": "7c6d3aba-232f-4c8b-b4fb-7551b2e726ba",
"metadata": {
"tags": []
@@ -107,7 +115,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
- "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 53 seconds.\n"
+ "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 4 seconds.\n"
]
},
{
@@ -130,7 +138,7 @@
"* To see a summary or plot of the posterior pass the object returned by .fit() to az.summary() or az.plot_trace()"
]
},
- "execution_count": 32,
+ "execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
@@ -162,7 +170,7 @@
},
{
"cell_type": "code",
- "execution_count": 22,
+ "execution_count": 5,
"id": "73f1ceee-38de-4e47-bfff-d98c96e6ad0a",
"metadata": {
"tags": []
@@ -196,7 +204,7 @@
"<text text-anchor=\"middle\" x=\"49.5\" y=\"-279.68\" font-family=\"Times,serif\" font-size=\"14.00\">Normal</text>\n",
"</g>\n",
"<!-- mu -->\n",
- "<g id=\"node5\" class=\"node\">\n",
+ "<g id=\"node4\" class=\"node\">\n",
"<title>mu</title>\n",
"<polygon fill=\"none\" stroke=\"black\" points=\"169.5,-213.93 55.5,-213.93 55.5,-160.93 169.5,-160.93 169.5,-213.93\"/>\n",
"<text text-anchor=\"middle\" x=\"112.5\" y=\"-198.73\" font-family=\"Times,serif\" font-size=\"14.00\">mu</text>\n",
@@ -218,7 +226,7 @@
"<text text-anchor=\"middle\" x=\"267.5\" y=\"-168.73\" font-family=\"Times,serif\" font-size=\"14.00\">HalfStudentT</text>\n",
"</g>\n",
"<!-- Verkauf -->\n",
- "<g id=\"node4\" class=\"node\">\n",
+ "<g id=\"node5\" class=\"node\">\n",
"<title>Verkauf</title>\n",
"<ellipse fill=\"lightgrey\" stroke=\"black\" cx=\"115.5\" cy=\"-76.48\" rx=\"50.41\" ry=\"37.45\"/>\n",
"<text text-anchor=\"middle\" x=\"115.5\" y=\"-87.78\" font-family=\"Times,serif\" font-size=\"14.00\">Verkauf</text>\n",
@@ -226,7 +234,7 @@
"<text text-anchor=\"middle\" x=\"115.5\" y=\"-57.78\" font-family=\"Times,serif\" font-size=\"14.00\">Normal</text>\n",
"</g>\n",
"<!-- sigma->Verkauf -->\n",
- "<g id=\"edge3\" class=\"edge\">\n",
+ "<g id=\"edge4\" class=\"edge\">\n",
"<title>sigma->Verkauf</title>\n",
"<path fill=\"none\" stroke=\"black\" d=\"M224.35,-155.5C203.98,-140.9 179.72,-123.51 159.28,-108.86\"/>\n",
"<polygon fill=\"black\" stroke=\"black\" points=\"161.23,-105.95 151.06,-102.97 157.15,-111.64 161.23,-105.95\"/>\n",
@@ -246,7 +254,7 @@
"<polygon fill=\"black\" stroke=\"black\" points=\"135.34,-220.95 127.31,-214.04 129.28,-224.45 135.34,-220.95\"/>\n",
"</g>\n",
"<!-- mu->Verkauf -->\n",
- "<g id=\"edge4\" class=\"edge\">\n",
+ "<g id=\"edge3\" class=\"edge\">\n",
"<title>mu->Verkauf</title>\n",
"<path fill=\"none\" stroke=\"black\" d=\"M113.2,-160.89C113.5,-149.98 113.86,-136.89 114.21,-124.35\"/>\n",
"<polygon fill=\"black\" stroke=\"black\" points=\"117.72,-124.09 114.49,-114 110.72,-123.9 117.72,-124.09\"/>\n",
@@ -255,10 +263,10 @@
"</svg>\n"
],
"text/plain": [
- "<graphviz.graphs.Digraph at 0x7f62f723ce80>"
+ "<graphviz.graphs.Digraph at 0x7eff9aeee9e0>"
]
},
- "execution_count": 22,
+ "execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
@@ -277,104 +285,30 @@
},
{
"cell_type": "code",
- "execution_count": 33,
+ "execution_count": 6,
"id": "4f8cdfc9-ecfd-4a60-823e-7c03d97158d8",
"metadata": {
"tags": []
},
"outputs": [
{
- "data": {
- "text/html": [
- "<div>\n",
- "<style scoped>\n",
- " .dataframe tbody tr th:only-of-type {\n",
- " vertical-align: middle;\n",
- " }\n",
- "\n",
- " .dataframe tbody tr th {\n",
- " vertical-align: top;\n",
- " }\n",
- "\n",
- " .dataframe thead th {\n",
- " text-align: right;\n",
- " }\n",
- "</style>\n",
- "<table border=\"1\" class=\"dataframe\">\n",
- " <thead>\n",
- " <tr style=\"text-align: right;\">\n",
- " <th></th>\n",
- " <th>mean</th>\n",
- " <th>sd</th>\n",
- " <th>hdi_3%</th>\n",
- " <th>hdi_97%</th>\n",
- " <th>mcse_mean</th>\n",
- " <th>mcse_sd</th>\n",
- " <th>ess_bulk</th>\n",
- " <th>ess_tail</th>\n",
- " <th>r_hat</th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>Intercept</th>\n",
- " <td>7.033</td>\n",
- " <td>0.469</td>\n",
- " <td>6.176</td>\n",
- " <td>7.944</td>\n",
- " <td>0.006</td>\n",
- " <td>0.004</td>\n",
- " <td>5886.0</td>\n",
- " <td>3153.0</td>\n",
- " <td>1.0</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>TV</th>\n",
- " <td>0.048</td>\n",
- " <td>0.003</td>\n",
- " <td>0.043</td>\n",
- " <td>0.053</td>\n",
- " <td>0.000</td>\n",
- " <td>0.000</td>\n",
- " <td>6668.0</td>\n",
- " <td>3114.0</td>\n",
- " <td>1.0</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>sigma</th>\n",
- " <td>3.277</td>\n",
- " <td>0.164</td>\n",
- " <td>2.968</td>\n",
- " <td>3.580</td>\n",
- " <td>0.002</td>\n",
- " <td>0.001</td>\n",
- " <td>6184.0</td>\n",
- " <td>3096.0</td>\n",
- " <td>1.0</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " mean sd hdi_3% hdi_97% mcse_mean mcse_sd ess_bulk \\\n",
- "Intercept 7.033 0.469 6.176 7.944 0.006 0.004 5886.0 \n",
- "TV 0.048 0.003 0.043 0.053 0.000 0.000 6668.0 \n",
- "sigma 3.277 0.164 2.968 3.580 0.002 0.001 6184.0 \n",
- "\n",
- " ess_tail r_hat \n",
- "Intercept 3153.0 1.0 \n",
- "TV 3114.0 1.0 \n",
- "sigma 3096.0 1.0 "
- ]
- },
- "execution_count": 33,
- "metadata": {},
- "output_type": "execute_result"
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ " mean sd hdi_3% hdi_97% mcse_mean mcse_sd ess_bulk \\\n",
+ "Intercept 7.033 0.469 6.176 7.944 0.006 0.004 5886.0 \n",
+ "TV 0.048 0.003 0.043 0.053 0.000 0.000 6668.0 \n",
+ "sigma 3.277 0.164 2.968 3.580 0.002 0.001 6184.0 \n",
+ "\n",
+ " ess_tail r_hat \n",
+ "Intercept 3153.0 1.0 \n",
+ "TV 3114.0 1.0 \n",
+ "sigma 3096.0 1.0 \n"
+ ]
}
],
"source": [
- "az.summary(idata_t)"
+ "print(az.summary(idata_t))"
]
},
{