notebooks/interpretability/InterpretabilityTest.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "e5351047",
   "metadata": {},
   "source": [
    "# Interpretability Test"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "58677e27",
   "metadata": {},
   "source": [
    "### Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "135430fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import pandas as pd\n",
    "from iqual import tests"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "e5526ce9",
   "metadata": {},
   "source": [
    "### Load datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "c924ac97",
   "metadata": {},
   "outputs": [],
   "source": [
    "data_dir         = \"../../data\"\n",
    "\n",
    "### Enhanced qualitative data\n",
    "enhanced_data = pd.read_csv(os.path.join(data_dir,\"kfold_enh_pred_mean.csv\"))\n",
    "\n",
    "### Quantitative data\n",
    "quant_df      = pd.read_csv(os.path.join(data_dir,\"quant_data.csv\"))"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "1ea4e1f5",
   "metadata": {},
   "source": [
    "### Variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "61800ceb",
   "metadata": {},
   "outputs": [],
   "source": [
    "annotation_vars = [\n",
    "     \"ability_high\",\n",
    "     \"ability_low\",\n",
    "     \"awareness_information_high\",\n",
    "     \"awareness_information_low\",\n",
    "     \"budget_high\",\n",
    "     \"budget_low\",\n",
    "     \"covid_impacts\",\n",
    "     \"education_high\",\n",
    "     \"education_low\",\n",
    "     \"education_neutral\",\n",
    "     \"education_religious\",\n",
    "     \"entrepreneur\",\n",
    "     \"job_secular\",\n",
    "     \"marriage\",\n",
    "     \"migration\",\n",
    "     \"no_ambition\",\n",
    "     \"public_assistance\",\n",
    "     \"reliance_on_god\",\n",
    "     \"religious\",\n",
    "     \"secular\",\n",
    "     \"vague_job\",\n",
    "     \"vague_non_specific\",\n",
    "     \"vocational_training\",\n",
    "     \"worries_anxieties\",\n",
    "    ]"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "6a7e068c",
   "metadata": {},
   "source": [
    "### Variables to Groupby"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "24b23b23",
   "metadata": {},
   "outputs": [],
   "source": [
    "id_vars_human    = ['uid','data_round','refugee','annotated']\n",
    "id_vars_enhanced = ['uid','data_round','refugee','annotated','bootstrap_run']"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "a737e6a3",
   "metadata": {},
   "source": [
    "### Human Annotated Dataframe (Merged with quantiative data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "1612ec87",
   "metadata": {},
   "outputs": [],
   "source": [
    "human_df = enhanced_data.loc[enhanced_data.annotated==1,[*id_vars_human,*human_annotation_vars]].copy()\n",
    "human_df = human_df.rename(columns={c+\"_act\":c for c in annotation_vars}).drop_duplicates()\n",
    "human_df = pd.merge(human_df,quant_df,on=['uid','data_round'],how='left')\n",
    "\n",
    "human_df['sample_type'] = 'Human'"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "aab6d862",
   "metadata": {},
   "source": [
    "### Enhanced Dataframe (Merged with quantiative data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "1a229676",
   "metadata": {},
   "outputs": [],
   "source": [
    "enhanced_df = enhanced_data[[*id_vars_enhanced,*annotation_vars]].copy()\n",
    "enhanced_df = pd.merge(enhanced_df,quant_df,on=['uid','data_round','refugee'],how='left')\n",
    "\n",
    "enhanced_df['sample_type'] = 'Enhanced'"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "9de75124",
   "metadata": {},
   "source": [
    "### HH characteristic variables for `Interpretability`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "id": "b3c303df",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Numerical regressors\n",
    "numerical_vars = [\n",
    "     'hh_head_sex',\n",
    "     'eld_sex',\n",
    "     'parent_reledu',\n",
    "     'num_child',\n",
    "     'hh_head_age',\n",
    "     'parent_eduyears',\n",
    "     'eld_age',\n",
    "     'hh_asset_index',\n",
    "     'hh_income',\n",
    "     'int_trauma_exp',\n",
    "]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a810649d",
   "metadata": {},
   "source": [
    "### Interpretability tests on Human Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "75e72c26",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>annotation</th>\n",
       "      <th>fstat</th>\n",
       "      <th>log_fstat</th>\n",
       "      <th>pval</th>\n",
       "      <th>sample_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ability_high</td>\n",
       "      <td>4.092906</td>\n",
       "      <td>1.409255</td>\n",
       "      <td>1.705786e-05</td>\n",
       "      <td>Human</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ability_low</td>\n",
       "      <td>2.220586</td>\n",
       "      <td>0.797771</td>\n",
       "      <td>1.520367e-02</td>\n",
       "      <td>Human</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>awareness_information_high</td>\n",
       "      <td>4.439502</td>\n",
       "      <td>1.490542</td>\n",
       "      <td>4.458398e-06</td>\n",
       "      <td>Human</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>awareness_information_low</td>\n",
       "      <td>1.594255</td>\n",
       "      <td>0.466406</td>\n",
       "      <td>1.039609e-01</td>\n",
       "      <td>Human</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>budget_high</td>\n",
       "      <td>5.604002</td>\n",
       "      <td>1.723481</td>\n",
       "      <td>4.496422e-08</td>\n",
       "      <td>Human</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   annotation     fstat  log_fstat          pval sample_type\n",
       "0                ability_high  4.092906   1.409255  1.705786e-05       Human\n",
       "1                 ability_low  2.220586   0.797771  1.520367e-02       Human\n",
       "2  awareness_information_high  4.439502   1.490542  4.458398e-06       Human\n",
       "3   awareness_information_low  1.594255   0.466406  1.039609e-01       Human\n",
       "4                 budget_high  5.604002   1.723481  4.496422e-08       Human"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "interpreter = tests.Interpretability(human_df,\n",
    "                                     annotation_vars=annotation_vars,\n",
    "                                     numerical_regressors=numerical_vars,\n",
    "                ).fit_all()\n",
    "\n",
    "human_interp_df = interpreter.get_results()\n",
    "human_interp_df['sample_type'] = 'Human'\n",
    "\n",
    "human_interp_df.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d8242ce6",
   "metadata": {},
   "source": [
    "### Interpretability tests on Enhanced Data (Looping over Bootstrap runs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "fcc8612c",
   "metadata": {},
   "outputs": [],
   "source": [
    "enh_interp_dfs = []\n",
    "\n",
    "bootstrap_runs = enhanced_df['bootstrap_run'].unique()\n",
    "\n",
    "for b in bootstrap_runs:\n",
    "    interpreter = tests.Interpretability(enhanced_df[enhanced_df['bootstrap_run']==b],\n",
    "                                         annotation_vars=annotation_vars,\n",
    "                                    #     categorical_regressors=categorical_vars,\n",
    "                                         numerical_regressors=numerical_vars,\n",
    "                    ).fit_all()\n",
    "    \n",
    "    interp_df = interpreter.get_results()\n",
    "    interp_df['bootstrap_run'] = b\n",
    "    \n",
    "    enh_interp_dfs.append(interp_df)\n",
    "    \n",
    "enhanced_interp_df = pd.concat(enh_interp_dfs)    \n",
    "enhanced_interp_df['sample_type'] = 'Enhanced'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "id": "bfd50a24",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>annotation</th>\n",
       "      <th>fstat</th>\n",
       "      <th>log_fstat</th>\n",
       "      <th>pval</th>\n",
       "      <th>sample_type</th>\n",
       "      <th>bootstrap_run</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>worries_anxieties</td>\n",
       "      <td>9.836116</td>\n",
       "      <td>2.286061</td>\n",
       "      <td>2.895519e-16</td>\n",
       "      <td>Enhanced</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>worries_anxieties</td>\n",
       "      <td>10.534363</td>\n",
       "      <td>2.354643</td>\n",
       "      <td>1.333396e-17</td>\n",
       "      <td>Enhanced</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>worries_anxieties</td>\n",
       "      <td>10.886772</td>\n",
       "      <td>2.387548</td>\n",
       "      <td>2.812771e-18</td>\n",
       "      <td>Enhanced</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>worries_anxieties</td>\n",
       "      <td>8.596269</td>\n",
       "      <td>2.151328</td>\n",
       "      <td>6.682446e-14</td>\n",
       "      <td>Enhanced</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>worries_anxieties</td>\n",
       "      <td>5.055125</td>\n",
       "      <td>1.620403</td>\n",
       "      <td>3.978705e-07</td>\n",
       "      <td>Human</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          annotation      fstat  log_fstat          pval sample_type  \\\n",
       "0  worries_anxieties   9.836116   2.286061  2.895519e-16    Enhanced   \n",
       "1  worries_anxieties  10.534363   2.354643  1.333396e-17    Enhanced   \n",
       "2  worries_anxieties  10.886772   2.387548  2.812771e-18    Enhanced   \n",
       "3  worries_anxieties   8.596269   2.151328  6.682446e-14    Enhanced   \n",
       "4  worries_anxieties   5.055125   1.620403  3.978705e-07       Human   \n",
       "\n",
       "   bootstrap_run  \n",
       "0           10.0  \n",
       "1            3.0  \n",
       "2            1.0  \n",
       "3            9.0  \n",
       "4            NaN  "
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "interpret_data = pd.concat([human_interp_df,enhanced_interp_df],axis=0)\n",
    "interpret_data = interpret_data.sort_values('annotation',ascending=False,ignore_index=True)\n",
    "interpret_data.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "950c89cb",
   "metadata": {},
   "source": [
    "### Calculate Differences"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "id": "57ad9f89",
   "metadata": {},
   "outputs": [],
   "source": [
    "enhanced_avg_df = enhanced_interp_df.groupby('annotation')['log_fstat'].mean().reset_index()\n",
    "enhanced_avg_df['sample_type'] = 'Enhanced'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "id": "e95d4735",
   "metadata": {},
   "outputs": [],
   "source": [
    "enhanced_avg_dict =  dict(enhanced_avg_df[['annotation','log_fstat']].values)\n",
    "human_avg_dict    =  dict(human_interp_df[['annotation','log_fstat']].values)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b7a0f14d",
   "metadata": {},
   "source": [
    "### Visualize"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "id": "80cace36",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(10,10))\n",
    "\n",
    "# Difference in F-statistic (Logarithmic) averages \n",
    "for annotation in annotation_vars:\n",
    "    enh_value, human_value = enhanced_avg_dict[annotation], human_avg_dict[annotation]\n",
    "    line_color = 'lightgreen' if enh_value >= human_value else 'red'\n",
    "    ax.plot([enh_value, human_value], [annotation, annotation], color=line_color, linewidth=2)\n",
    "\n",
    "# Enhanced Data Log F-statistic values for all bootstrap runs\n",
    "enhanced_x = interpret_data.loc[interpret_data['sample_type'] == 'Enhanced', 'log_fstat'].tolist()\n",
    "enhanced_y = interpret_data.loc[interpret_data['sample_type'] == 'Enhanced', 'annotation'].tolist()\n",
    "ax.scatter(enhanced_x, enhanced_y, fc=(0,0,0, 0.1), marker='o', s=50, ec='k', lw=1, label='Enhanced')\n",
    "    \n",
    "# Human Data F-statistic (Logarithmic) values\n",
    "human_x = interpret_data.loc[interpret_data['sample_type'] == 'Human', 'log_fstat'].tolist()\n",
    "human_y = interpret_data.loc[interpret_data['sample_type'] == 'Human', 'annotation'].tolist()\n",
    "ax.scatter(human_x, human_y, c='black', marker='x', s=50, label='Human',)\n",
    "\n",
    "# Titles, Labels, Legends and formatting\n",
    "ax.set_xlabel('log F statistic',fontsize=12)\n",
    "ax.set_ylabel('Annotation', fontsize=12)\n",
    "ax.legend(title='Sample',fontsize=12,loc='best')\n",
    "ax.set_title('Figure 9: Interpretability test',fontsize=18, pad=25)\n",
    "ax.grid(True, color='lightgray')\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}