GStechschulte/interpret_vector_preds.ipynb

## interpret_vector_preds.ipynb
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     "text": [
      "WARNING (pytensor.tensor.blas): Using NumPy C-API based implementation for BLAS functions.\n"
     ]
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   "source": [
    "import arviz as az\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import xarray as xr\n",
    "import warnings\n",
    "\n",
    "import bambi as bmb\n",
    "\n",
    "warnings.simplefilter(action='ignore', category=FutureWarning)\n",
    "\n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Interpret with ordinal and categorical models"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Categorical regression"
   ]
  },
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    "length = [\n",
    "    1.3, 1.32, 1.32, 1.4, 1.42, 1.42, 1.47, 1.47, 1.5, 1.52, 1.63, 1.65, 1.65, 1.65, 1.65,\n",
    "    1.68, 1.7, 1.73, 1.78, 1.78, 1.8, 1.85, 1.93, 1.93, 1.98, 2.03, 2.03, 2.31, 2.36, 2.46,\n",
    "    3.25, 3.28, 3.33, 3.56, 3.58, 3.66, 3.68, 3.71, 3.89, 1.24, 1.3, 1.45, 1.45, 1.55, 1.6,\n",
    "    1.6, 1.65, 1.78, 1.78, 1.8, 1.88, 2.16, 2.26, 2.31, 2.36, 2.39, 2.41, 2.44, 2.56, 2.67,\n",
    "    2.72, 2.79, 2.84\n",
    "]\n",
    "choice = [\n",
    "    \"I\", \"F\", \"F\", \"F\", \"I\", \"F\", \"I\", \"F\", \"I\", \"I\", \"I\", \"O\", \"O\", \"I\", \"F\", \"F\",\n",
    "    \"I\", \"O\", \"F\", \"O\", \"F\", \"F\", \"I\", \"F\", \"I\", \"F\", \"F\", \"F\", \"F\", \"F\", \"O\", \"O\",\n",
    "    \"F\", \"F\", \"F\", \"F\", \"O\", \"F\", \"F\", \"I\", \"I\", \"I\", \"O\", \"I\", \"I\", \"I\", \"F\", \"I\",\n",
    "    \"O\", \"I\", \"I\", \"F\", \"F\", \"F\", \"F\", \"F\", \"F\", \"F\", \"O\", \"F\", \"I\", \"F\", \"F\"\n",
    "]\n",
    "\n",
    "sex = [\"Male\"] * 32 + [\"Female\"] * 31\n",
    "\n",
    "data = pd.DataFrame({\"choice\": choice, \"length\": length, \"sex\": sex})\n",
    "\n",
    "data[\"choice\"]  = pd.Categorical(\n",
    "    data[\"choice\"].map({\"I\": \"Invertebrates\", \"F\": \"Fish\", \"O\": \"Other\"}),\n",
    "    [\"Other\", \"Invertebrates\", \"Fish\"],\n",
    "    ordered=True\n",
    ")"
   ]
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     "text": [
      "Auto-assigning NUTS sampler...\n",
      "Initializing NUTS using jitter+adapt_diag...\n",
      "Multiprocess sampling (4 chains in 4 jobs)\n",
      "NUTS: [Intercept, length, sex]\n"
     ]
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       "\n",
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       "      <progress value='8000' class='' max='8000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
       "      100.00% [8000/8000 00:02&lt;00:00 Sampling 4 chains, 0 divergences]\n",
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       "    "
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     "text": [
      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 2 seconds.\n"
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   ],
   "source": [
    "# numeric data\n",
    "model = bmb.Model(\"choice ~ length + sex\", data, family=\"categorical\")\n",
    "idata = model.fit(\n",
    "    draws=1000, target_accept=0.95, random_seed=1234, chains=4\n",
    ")"
   ]
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  {
   "cell_type": "code",
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     "name": "stderr",
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     "text": [
      "Auto-assigning NUTS sampler...\n",
      "Initializing NUTS using jitter+adapt_diag...\n",
      "Multiprocess sampling (4 chains in 4 jobs)\n",
      "NUTS: [Intercept, length, sex]\n"
     ]
    },
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       "\n",
       "<style>\n",
       "    /* Turns off some styling */\n",
       "    progress {\n",
       "        /* gets rid of default border in Firefox and Opera. */\n",
       "        border: none;\n",
       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
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       "\n",
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       "      <progress value='8000' class='' max='8000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
       "      100.00% [8000/8000 00:03&lt;00:00 Sampling 4 chains, 0 divergences]\n",
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       "    "
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     "text": [
      "Sampling 4 chains for 1_000 tune and 1_000 draw iterations (4_000 + 4_000 draws total) took 3 seconds.\n"
     ]
    }
   ],
   "source": [
    "cat_data = data.copy()\n",
    "\n",
    "cat_data[\"length\"] = np.round(cat_data[\"length\"], 0)\n",
    "cat_data[\"length\"] = pd.Categorical(cat_data[\"length\"], ordered=True)\n",
    "\n",
    "# categorical cat_data\n",
    "categorical_model = bmb.Model(\"choice ~ length + sex\", cat_data, family=\"categorical\")\n",
    "categorical_idata = categorical_model.fit(\n",
    "    draws=1000, target_accept=0.95, random_seed=1234, chains=4\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### bmb.interpret.plot_comparisons"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Numeric data type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>term</th>\n",
       "      <th>estimate_type</th>\n",
       "      <th>value</th>\n",
       "      <th>length</th>\n",
       "      <th>estimate_dim</th>\n",
       "      <th>estimate</th>\n",
       "      <th>lower_3.0%</th>\n",
       "      <th>upper_97.0%</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>sex</td>\n",
       "      <td>diff</td>\n",
       "      <td>(Female, Male)</td>\n",
       "      <td>1.240000</td>\n",
       "      <td>Other</td>\n",
       "      <td>0.063479</td>\n",
       "      <td>-0.026309</td>\n",
       "      <td>0.167179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>sex</td>\n",
       "      <td>diff</td>\n",
       "      <td>(Female, Male)</td>\n",
       "      <td>1.240000</td>\n",
       "      <td>Invertebrates</td>\n",
       "      <td>-0.199827</td>\n",
       "      <td>-0.428052</td>\n",
       "      <td>0.003367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>sex</td>\n",
       "      <td>diff</td>\n",
       "      <td>(Female, Male)</td>\n",
       "      <td>1.240000</td>\n",
       "      <td>Fish</td>\n",
       "      <td>0.136348</td>\n",
       "      <td>-0.039829</td>\n",
       "      <td>0.322773</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>sex</td>\n",
       "      <td>diff</td>\n",
       "      <td>(Female, Male)</td>\n",
       "      <td>1.294082</td>\n",
       "      <td>Other</td>\n",
       "      <td>0.069023</td>\n",
       "      <td>-0.022305</td>\n",
       "      <td>0.183825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>sex</td>\n",
       "      <td>diff</td>\n",
       "      <td>(Female, Male)</td>\n",
       "      <td>1.294082</td>\n",
       "      <td>Invertebrates</td>\n",
       "      <td>-0.216157</td>\n",
       "      <td>-0.450717</td>\n",
       "      <td>0.003146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>sex</td>\n",
       "      <td>diff</td>\n",
       "      <td>(Female, Male)</td>\n",
       "      <td>3.835918</td>\n",
       "      <td>Invertebrates</td>\n",
       "      <td>-0.004696</td>\n",
       "      <td>-0.020876</td>\n",
       "      <td>0.000946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>sex</td>\n",
       "      <td>diff</td>\n",
       "      <td>(Female, Male)</td>\n",
       "      <td>3.835918</td>\n",
       "      <td>Fish</td>\n",
       "      <td>-0.100021</td>\n",
       "      <td>-0.432812</td>\n",
       "      <td>0.150422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>sex</td>\n",
       "      <td>diff</td>\n",
       "      <td>(Female, Male)</td>\n",
       "      <td>3.890000</td>\n",
       "      <td>Other</td>\n",
       "      <td>0.104663</td>\n",
       "      <td>-0.146865</td>\n",
       "      <td>0.432678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>sex</td>\n",
       "      <td>diff</td>\n",
       "      <td>(Female, Male)</td>\n",
       "      <td>3.890000</td>\n",
       "      <td>Invertebrates</td>\n",
       "      <td>-0.004199</td>\n",
       "      <td>-0.018789</td>\n",
       "      <td>0.000890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>sex</td>\n",
       "      <td>diff</td>\n",
       "      <td>(Female, Male)</td>\n",
       "      <td>3.890000</td>\n",
       "      <td>Fish</td>\n",
       "      <td>-0.100464</td>\n",
       "      <td>-0.424758</td>\n",
       "      <td>0.155744</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>150 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    term estimate_type           value    length   estimate_dim  estimate  \\\n",
       "0    sex          diff  (Female, Male)  1.240000          Other  0.063479   \n",
       "1    sex          diff  (Female, Male)  1.240000  Invertebrates -0.199827   \n",
       "2    sex          diff  (Female, Male)  1.240000           Fish  0.136348   \n",
       "3    sex          diff  (Female, Male)  1.294082          Other  0.069023   \n",
       "4    sex          diff  (Female, Male)  1.294082  Invertebrates -0.216157   \n",
       "..   ...           ...             ...       ...            ...       ...   \n",
       "145  sex          diff  (Female, Male)  3.835918  Invertebrates -0.004696   \n",
       "146  sex          diff  (Female, Male)  3.835918           Fish -0.100021   \n",
       "147  sex          diff  (Female, Male)  3.890000          Other  0.104663   \n",
       "148  sex          diff  (Female, Male)  3.890000  Invertebrates -0.004199   \n",
       "149  sex          diff  (Female, Male)  3.890000           Fish -0.100464   \n",
       "\n",
       "     lower_3.0%  upper_97.0%  \n",
       "0     -0.026309     0.167179  \n",
       "1     -0.428052     0.003367  \n",
       "2     -0.039829     0.322773  \n",
       "3     -0.022305     0.183825  \n",
       "4     -0.450717     0.003146  \n",
       "..          ...          ...  \n",
       "145   -0.020876     0.000946  \n",
       "146   -0.432812     0.150422  \n",
       "147   -0.146865     0.432678  \n",
       "148   -0.018789     0.000890  \n",
       "149   -0.424758     0.155744  \n",
       "\n",
       "[150 rows x 8 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "summary_df = bmb.interpret.comparisons(\n",
    "    model=model,\n",
    "    idata=idata,\n",
    "    contrast=\"sex\",\n",
    "    conditional=\"length\"\n",
    ")\n",
    "summary_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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",
      "text/plain": [
       "<Figure size 700x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = bmb.interpret.plot_comparisons(\n",
    "    model,\n",
    "    idata,\n",
    "    contrast=\"sex\",\n",
    "    conditional=\"length\",\n",
    "    fig_kwargs={\"figsize\": (7, 3)},\n",
    "    legend=False\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x300 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# or using subplots\n",
    "fig, ax = bmb.interpret.plot_comparisons(\n",
    "    model,\n",
    "    idata,\n",
    "    contrast=\"sex\",\n",
    "    conditional=\"length\",\n",
    "    subplot_kwargs={\"main\": \"length\", \"group\": \"estimate_dim\", \"panel\": \"estimate_dim\"},\n",
    "    fig_kwargs={\"figsize\": (12, 3)},\n",
    "    legend=False\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Categorical data type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>term</th>\n",
       "      <th>estimate_type</th>\n",
       "      <th>value</th>\n",
       "      <th>length</th>\n",
       "      <th>estimate_dim</th>\n",
       "      <th>estimate</th>\n",
       "      <th>lower_3.0%</th>\n",
       "      <th>upper_97.0%</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>sex</td>\n",
       "      <td>diff</td>\n",
       "      <td>(Female, Male)</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Other</td>\n",
       "      <td>0.077142</td>\n",
       "      <td>-0.038947</td>\n",
       "      <td>0.246584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>sex</td>\n",
       "      <td>diff</td>\n",
       "      <td>(Female, Male)</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Invertebrates</td>\n",
       "      <td>-0.146194</td>\n",
       "      <td>-0.396272</td>\n",
       "      <td>0.123805</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>sex</td>\n",
       "      <td>diff</td>\n",
       "      <td>(Female, Male)</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Fish</td>\n",
       "      <td>0.069052</td>\n",
       "      <td>-0.179775</td>\n",
       "      <td>0.322601</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>sex</td>\n",
       "      <td>diff</td>\n",
       "      <td>(Female, Male)</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Other</td>\n",
       "      <td>0.097278</td>\n",
       "      <td>-0.046026</td>\n",
       "      <td>0.265520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>sex</td>\n",
       "      <td>diff</td>\n",
       "      <td>(Female, Male)</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Invertebrates</td>\n",
       "      <td>-0.145301</td>\n",
       "      <td>-0.398757</td>\n",
       "      <td>0.096287</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>sex</td>\n",
       "      <td>diff</td>\n",
       "      <td>(Female, Male)</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Fish</td>\n",
       "      <td>0.048023</td>\n",
       "      <td>-0.212884</td>\n",
       "      <td>0.299446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>sex</td>\n",
       "      <td>diff</td>\n",
       "      <td>(Female, Male)</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Other</td>\n",
       "      <td>0.204309</td>\n",
       "      <td>-0.139517</td>\n",
       "      <td>0.560875</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>sex</td>\n",
       "      <td>diff</td>\n",
       "      <td>(Female, Male)</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Invertebrates</td>\n",
       "      <td>-0.078857</td>\n",
       "      <td>-0.262107</td>\n",
       "      <td>0.033840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>sex</td>\n",
       "      <td>diff</td>\n",
       "      <td>(Female, Male)</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Fish</td>\n",
       "      <td>-0.125451</td>\n",
       "      <td>-0.473435</td>\n",
       "      <td>0.160578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>sex</td>\n",
       "      <td>diff</td>\n",
       "      <td>(Female, Male)</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Other</td>\n",
       "      <td>0.139247</td>\n",
       "      <td>-0.088173</td>\n",
       "      <td>0.512614</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>sex</td>\n",
       "      <td>diff</td>\n",
       "      <td>(Female, Male)</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Invertebrates</td>\n",
       "      <td>-0.009234</td>\n",
       "      <td>-0.059843</td>\n",
       "      <td>0.012636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>sex</td>\n",
       "      <td>diff</td>\n",
       "      <td>(Female, Male)</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Fish</td>\n",
       "      <td>-0.130014</td>\n",
       "      <td>-0.499456</td>\n",
       "      <td>0.115820</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   term estimate_type           value length   estimate_dim  estimate  \\\n",
       "0   sex          diff  (Female, Male)    1.0          Other  0.077142   \n",
       "1   sex          diff  (Female, Male)    1.0  Invertebrates -0.146194   \n",
       "2   sex          diff  (Female, Male)    1.0           Fish  0.069052   \n",
       "3   sex          diff  (Female, Male)    2.0          Other  0.097278   \n",
       "4   sex          diff  (Female, Male)    2.0  Invertebrates -0.145301   \n",
       "5   sex          diff  (Female, Male)    2.0           Fish  0.048023   \n",
       "6   sex          diff  (Female, Male)    3.0          Other  0.204309   \n",
       "7   sex          diff  (Female, Male)    3.0  Invertebrates -0.078857   \n",
       "8   sex          diff  (Female, Male)    3.0           Fish -0.125451   \n",
       "9   sex          diff  (Female, Male)    4.0          Other  0.139247   \n",
       "10  sex          diff  (Female, Male)    4.0  Invertebrates -0.009234   \n",
       "11  sex          diff  (Female, Male)    4.0           Fish -0.130014   \n",
       "\n",
       "    lower_3.0%  upper_97.0%  \n",
       "0    -0.038947     0.246584  \n",
       "1    -0.396272     0.123805  \n",
       "2    -0.179775     0.322601  \n",
       "3    -0.046026     0.265520  \n",
       "4    -0.398757     0.096287  \n",
       "5    -0.212884     0.299446  \n",
       "6    -0.139517     0.560875  \n",
       "7    -0.262107     0.033840  \n",
       "8    -0.473435     0.160578  \n",
       "9    -0.088173     0.512614  \n",
       "10   -0.059843     0.012636  \n",
       "11   -0.499456     0.115820  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "summary_df = bmb.interpret.comparisons(\n",
    "    categorical_model,\n",
    "    categorical_idata,\n",
    "    contrast=\"sex\",\n",
    "    conditional=\"length\"\n",
    ")\n",
    "summary_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bmb.interpret.plot_comparisons(\n",
    "    categorical_model,\n",
    "    categorical_idata,\n",
    "    contrast=\"sex\",\n",
    "    conditional=\"length\",\n",
    "    fig_kwargs={\"figsize\": (7, 3)},\n",
    "    legend=True\n",
    ");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### bmb.interpret.plot_predictions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Numeric data type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>length</th>\n",
       "      <th>sex</th>\n",
       "      <th>estimate_dim</th>\n",
       "      <th>estimate</th>\n",
       "      <th>lower_3.0%</th>\n",
       "      <th>upper_97.0%</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.240000</td>\n",
       "      <td>Male</td>\n",
       "      <td>Other</td>\n",
       "      <td>0.097136</td>\n",
       "      <td>1.304773e-02</td>\n",
       "      <td>0.203471</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.240000</td>\n",
       "      <td>Male</td>\n",
       "      <td>Invertebrates</td>\n",
       "      <td>0.638881</td>\n",
       "      <td>4.061813e-01</td>\n",
       "      <td>0.847234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.240000</td>\n",
       "      <td>Male</td>\n",
       "      <td>Fish</td>\n",
       "      <td>0.263982</td>\n",
       "      <td>8.537557e-02</td>\n",
       "      <td>0.443943</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.294082</td>\n",
       "      <td>Male</td>\n",
       "      <td>Other</td>\n",
       "      <td>0.106339</td>\n",
       "      <td>1.872622e-02</td>\n",
       "      <td>0.216027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.294082</td>\n",
       "      <td>Male</td>\n",
       "      <td>Invertebrates</td>\n",
       "      <td>0.603465</td>\n",
       "      <td>3.747282e-01</td>\n",
       "      <td>0.811450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>3.835918</td>\n",
       "      <td>Male</td>\n",
       "      <td>Invertebrates</td>\n",
       "      <td>0.002870</td>\n",
       "      <td>2.029736e-07</td>\n",
       "      <td>0.010814</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>3.835918</td>\n",
       "      <td>Male</td>\n",
       "      <td>Fish</td>\n",
       "      <td>0.682811</td>\n",
       "      <td>2.814741e-01</td>\n",
       "      <td>0.989905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>3.890000</td>\n",
       "      <td>Male</td>\n",
       "      <td>Other</td>\n",
       "      <td>0.316271</td>\n",
       "      <td>8.958170e-03</td>\n",
       "      <td>0.728521</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>3.890000</td>\n",
       "      <td>Male</td>\n",
       "      <td>Invertebrates</td>\n",
       "      <td>0.002594</td>\n",
       "      <td>1.421154e-07</td>\n",
       "      <td>0.009800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>3.890000</td>\n",
       "      <td>Male</td>\n",
       "      <td>Fish</td>\n",
       "      <td>0.681135</td>\n",
       "      <td>2.710408e-01</td>\n",
       "      <td>0.989952</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>150 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      length   sex   estimate_dim  estimate    lower_3.0%  upper_97.0%\n",
       "0   1.240000  Male          Other  0.097136  1.304773e-02     0.203471\n",
       "0   1.240000  Male  Invertebrates  0.638881  4.061813e-01     0.847234\n",
       "0   1.240000  Male           Fish  0.263982  8.537557e-02     0.443943\n",
       "1   1.294082  Male          Other  0.106339  1.872622e-02     0.216027\n",
       "1   1.294082  Male  Invertebrates  0.603465  3.747282e-01     0.811450\n",
       "..       ...   ...            ...       ...           ...          ...\n",
       "48  3.835918  Male  Invertebrates  0.002870  2.029736e-07     0.010814\n",
       "48  3.835918  Male           Fish  0.682811  2.814741e-01     0.989905\n",
       "49  3.890000  Male          Other  0.316271  8.958170e-03     0.728521\n",
       "49  3.890000  Male  Invertebrates  0.002594  1.421154e-07     0.009800\n",
       "49  3.890000  Male           Fish  0.681135  2.710408e-01     0.989952\n",
       "\n",
       "[150 rows x 6 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "summary_df = bmb.interpret.predictions(\n",
    "    model=model,\n",
    "    idata=idata,\n",
    "    covariates=\"length\",\n",
    "    pps=False\n",
    ")\n",
    "\n",
    "summary_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bmb.interpret.plot_predictions(\n",
    "    model,\n",
    "    idata,\n",
    "    \"length\",\n",
    "    fig_kwargs={\"figsize\": (7, 3)},\n",
    "    legend=True\n",
    ");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x300 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bmb.interpret.plot_predictions(\n",
    "    model,\n",
    "    idata,\n",
    "    [\"length\", \"sex\"],\n",
    "    subplot_kwargs={\"main\": \"length\", \"group\": \"sex\", \"panel\": \"estimate_dim\"},\n",
    "    fig_kwargs={\"figsize\": (10, 3), \"tight_layout\": True, \"sharey\": True},\n",
    "    legend=True\n",
    ");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Categorical data type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bmb.interpret.plot_predictions(\n",
    "    categorical_model,\n",
    "    categorical_idata,\n",
    "    \"length\",\n",
    "    fig_kwargs={\"figsize\": (7, 3)},\n",
    "    legend=True\n",
    ");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### bmb.interpret.plot_slopes\n",
    "\n",
    "Only numeric data type because if categorical, then it calls `comparisons`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Numeric data type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>term</th>\n",
       "      <th>estimate_type</th>\n",
       "      <th>value</th>\n",
       "      <th>sex</th>\n",
       "      <th>estimate_dim</th>\n",
       "      <th>estimate</th>\n",
       "      <th>lower_3.0%</th>\n",
       "      <th>upper_97.0%</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>length</td>\n",
       "      <td>dydx</td>\n",
       "      <td>(2.1055555555555556, 2.105655555555556)</td>\n",
       "      <td>Female</td>\n",
       "      <td>Other</td>\n",
       "      <td>0.110888</td>\n",
       "      <td>-0.018116</td>\n",
       "      <td>0.263740</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>length</td>\n",
       "      <td>dydx</td>\n",
       "      <td>(2.1055555555555556, 2.105655555555556)</td>\n",
       "      <td>Female</td>\n",
       "      <td>Invertebrates</td>\n",
       "      <td>-0.623775</td>\n",
       "      <td>-0.960417</td>\n",
       "      <td>-0.268078</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>length</td>\n",
       "      <td>dydx</td>\n",
       "      <td>(2.1055555555555556, 2.105655555555556)</td>\n",
       "      <td>Female</td>\n",
       "      <td>Fish</td>\n",
       "      <td>0.512887</td>\n",
       "      <td>0.199947</td>\n",
       "      <td>0.826456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>length</td>\n",
       "      <td>dydx</td>\n",
       "      <td>(2.1055555555555556, 2.105655555555556)</td>\n",
       "      <td>Male</td>\n",
       "      <td>Other</td>\n",
       "      <td>0.091945</td>\n",
       "      <td>-0.106514</td>\n",
       "      <td>0.318009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>length</td>\n",
       "      <td>dydx</td>\n",
       "      <td>(2.1055555555555556, 2.105655555555556)</td>\n",
       "      <td>Male</td>\n",
       "      <td>Invertebrates</td>\n",
       "      <td>-0.306054</td>\n",
       "      <td>-0.496101</td>\n",
       "      <td>-0.142805</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>length</td>\n",
       "      <td>dydx</td>\n",
       "      <td>(2.1055555555555556, 2.105655555555556)</td>\n",
       "      <td>Male</td>\n",
       "      <td>Fish</td>\n",
       "      <td>0.214109</td>\n",
       "      <td>-0.044910</td>\n",
       "      <td>0.460758</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     term estimate_type                                    value     sex  \\\n",
       "0  length          dydx  (2.1055555555555556, 2.105655555555556)  Female   \n",
       "1  length          dydx  (2.1055555555555556, 2.105655555555556)  Female   \n",
       "2  length          dydx  (2.1055555555555556, 2.105655555555556)  Female   \n",
       "3  length          dydx  (2.1055555555555556, 2.105655555555556)    Male   \n",
       "4  length          dydx  (2.1055555555555556, 2.105655555555556)    Male   \n",
       "5  length          dydx  (2.1055555555555556, 2.105655555555556)    Male   \n",
       "\n",
       "    estimate_dim  estimate  lower_3.0%  upper_97.0%  \n",
       "0          Other  0.110888   -0.018116     0.263740  \n",
       "1  Invertebrates -0.623775   -0.960417    -0.268078  \n",
       "2           Fish  0.512887    0.199947     0.826456  \n",
       "3          Other  0.091945   -0.106514     0.318009  \n",
       "4  Invertebrates -0.306054   -0.496101    -0.142805  \n",
       "5           Fish  0.214109   -0.044910     0.460758  "
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "summary_df = bmb.interpret.slopes(\n",
    "    model,\n",
    "    idata,\n",
    "    wrt=\"length\",\n",
    "    conditional=\"sex\"\n",
    ")\n",
    "summary_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bmb.interpret.plot_slopes(\n",
    "    model,\n",
    "    idata,\n",
    "    wrt=\"length\",\n",
    "    conditional=\"sex\",\n",
    "    fig_kwargs={\"figsize\": (7, 3)}\n",
    ");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Ordinal regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "trolly = pd.read_csv(\"https://raw.githubusercontent.com/rmcelreath/rethinking/master/data/Trolley.csv\", sep=\";\")\n",
    "trolly = trolly[[\"response\", \"action\", \"intention\", \"contact\"]]\n",
    "trolly[\"action\"] = pd.Categorical(trolly[\"action\"], ordered=False)\n",
    "trolly[\"intention\"] = pd.Categorical(trolly[\"intention\"], ordered=False)\n",
    "trolly[\"contact\"] = pd.Categorical(trolly[\"contact\"], ordered=False)\n",
    "trolly[\"response\"] = pd.Categorical(trolly[\"response\"], ordered=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ordinal_model = bmb.Model(\n",
    "    \"response ~ 0 + action + intention + contact + action:intention + contact:intention\", \n",
    "    data=trolly, \n",
    "    family=\"cumulative\"\n",
    ")\n",
    "ordinal_idata = ordinal_model.fit(draws=250, tune=250, chains=4, random_seed=1234)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### bmb.interpret.plot_predictions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Categorical data type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>action</th>\n",
       "      <th>contact</th>\n",
       "      <th>intention</th>\n",
       "      <th>estimate_dim</th>\n",
       "      <th>estimate</th>\n",
       "      <th>lower_3.0%</th>\n",
       "      <th>upper_97.0%</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.067407</td>\n",
       "      <td>0.061353</td>\n",
       "      <td>0.074183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.059205</td>\n",
       "      <td>0.053890</td>\n",
       "      <td>0.063700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0.081588</td>\n",
       "      <td>0.075751</td>\n",
       "      <td>0.088043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0.217249</td>\n",
       "      <td>0.206988</td>\n",
       "      <td>0.226542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0.166043</td>\n",
       "      <td>0.158738</td>\n",
       "      <td>0.173949</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0.190386</td>\n",
       "      <td>0.180766</td>\n",
       "      <td>0.200750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>0.218122</td>\n",
       "      <td>0.203489</td>\n",
       "      <td>0.233038</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.103076</td>\n",
       "      <td>0.095070</td>\n",
       "      <td>0.109943</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.084249</td>\n",
       "      <td>0.079016</td>\n",
       "      <td>0.090115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0.107509</td>\n",
       "      <td>0.101204</td>\n",
       "      <td>0.113569</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0.245955</td>\n",
       "      <td>0.237750</td>\n",
       "      <td>0.255164</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0.156463</td>\n",
       "      <td>0.149322</td>\n",
       "      <td>0.163961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0.153554</td>\n",
       "      <td>0.143876</td>\n",
       "      <td>0.161183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>0.149194</td>\n",
       "      <td>0.138878</td>\n",
       "      <td>0.159047</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  action contact intention estimate_dim  estimate  lower_3.0%  upper_97.0%\n",
       "0      0       0         0            1  0.067407    0.061353     0.074183\n",
       "0      0       0         0            2  0.059205    0.053890     0.063700\n",
       "0      0       0         0            3  0.081588    0.075751     0.088043\n",
       "0      0       0         0            4  0.217249    0.206988     0.226542\n",
       "0      0       0         0            5  0.166043    0.158738     0.173949\n",
       "0      0       0         0            6  0.190386    0.180766     0.200750\n",
       "0      0       0         0            7  0.218122    0.203489     0.233038\n",
       "1      1       0         0            1  0.103076    0.095070     0.109943\n",
       "1      1       0         0            2  0.084249    0.079016     0.090115\n",
       "1      1       0         0            3  0.107509    0.101204     0.113569\n",
       "1      1       0         0            4  0.245955    0.237750     0.255164\n",
       "1      1       0         0            5  0.156463    0.149322     0.163961\n",
       "1      1       0         0            6  0.153554    0.143876     0.161183\n",
       "1      1       0         0            7  0.149194    0.138878     0.159047"
      ]
     },
     "execution_count": 234,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bmb.interpret.predictions(\n",
    "    ordinal_model,\n",
    "    ordinal_idata,\n",
    "    \"action\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bmb.interpret.plot_predictions(\n",
    "    ordinal_model,\n",
    "    ordinal_idata,\n",
    "    \"action\",\n",
    "    fig_kwargs={\"figsize\": (7, 3)},\n",
    "    legend=True\n",
    ");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 9 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bmb.interpret.plot_predictions(\n",
    "    ordinal_model,\n",
    "    ordinal_idata,\n",
    "    [\"action\", \"intention\"],\n",
    "    subplot_kwargs={\"main\": \"action\", \"group\": \"intention\", \"panel\": \"estimate_dim\"},\n",
    "    fig_kwargs={\"figsize\": (10, 6), \"tight_layout\": True, \"sharey\": True},\n",
    "    legend=True\n",
    ");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Numeric data type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "bambinos",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.0"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
No results found