{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Meta-Learner Benchmarks with Synthetic Data in Nie and Wager (2020)\n",
    "This notebook compares X-, R-, T- and S-learners across the simulation setups discussed by [Nie and Wager (2020)](https://arxiv.org/pdf/1712.04912.pdf). Note that the experiments don't include the parameter tuning described in the paper."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using `tqdm.autonotebook.tqdm` in notebook mode. Use `tqdm.tqdm` instead to force console mode (e.g. in jupyter console)\n",
      "Failed to import duecredit due to No module named 'duecredit'\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "from causalml.inference.meta import BaseSRegressor\n",
    "from causalml.inference.meta import BaseTRegressor\n",
    "from causalml.inference.meta import BaseXRegressor\n",
    "from causalml.inference.meta import BaseRRegressor\n",
    "\n",
    "from causalml.dataset import synthetic_data\n",
    "\n",
    "from sklearn.metrics import mean_squared_error\n",
    "from sklearn.model_selection import train_test_split, cross_val_predict\n",
    "from sklearn.base import clone\n",
    "\n",
    "from sklearn.linear_model import LogisticRegression, Lasso\n",
    "from xgboost import XGBRegressor\n",
    "\n",
    "from copy import deepcopy\n",
    "from itertools import product\n",
    "\n",
    "from tqdm import tqdm\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "sns.set_style('whitegrid')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.14.0\n"
     ]
    }
   ],
   "source": [
    "import importlib\n",
    "print(importlib.metadata.version('causalml') )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def run_experiments(n_list, p_list, s_list, m_list, learner_dict, num_iter,\n",
    "                    propensity_learner):\n",
    "    \n",
    "    result_list = []    \n",
    "\n",
    "    for i in tqdm(range(num_iter)):\n",
    "        \n",
    "        for n, p, s, m, learner in product(n_list, p_list, s_list, m_list, learner_dict.keys()):\n",
    "\n",
    "            y, X, W, tau, _, _ = synthetic_data(mode=m, n=n, p=p, sigma=s)\n",
    "            X_train, X_test, W_train, _, y_train, _, _, tau_test = train_test_split(\n",
    "                X, W, y, tau, test_size=0.2, random_state=111)\n",
    "\n",
    "            if propensity_learner is not None:\n",
    "                em = clone(propensity_learner)\n",
    "                em.fit(X_train, W_train)\n",
    "                e_hat_train = cross_val_predict(em, X_train, W_train, method='predict_proba')[:, 1]\n",
    "                e_hat_test = em.predict_proba(X_test)[:, 1]\n",
    "\n",
    "            model = deepcopy(learner_dict[learner])\n",
    "            model.fit(X=X_train, treatment=W_train, y=y_train, p=e_hat_train)\n",
    "            hat_tau = model.predict(X_test, p=e_hat_test)\n",
    "\n",
    "            pehe = mean_squared_error(tau_test, hat_tau)\n",
    "\n",
    "            result_list.append([n, p, s, m, learner, pehe])\n",
    "    \n",
    "    cols = ['num_samples', 'num_features', 'sigma', 'sim_mode', 'learner', 'pehe']\n",
    "    df_res = pd.DataFrame(result_list, columns=cols)\n",
    "    return df_res"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Lasso based experiments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 100/100 [04:00<00:00,  2.40s/it]\n"
     ]
    }
   ],
   "source": [
    "# Simulation params from Nie and Wager (2020)\n",
    "n_list = [100, 500]\n",
    "p_list = [6, 12]\n",
    "s_list = [0.5, 1, 2, 4]\n",
    "m_list = [1, 2, 3, 4]\n",
    "num_iter = 100\n",
    "\n",
    "learner_dict = {\n",
    "    'S-Learner': BaseSRegressor(learner=Lasso()),\n",
    "    'T-Learner': BaseTRegressor(learner=Lasso()),\n",
    "    'X-Learner': BaseXRegressor(learner=Lasso()),\n",
    "    'R-Learner': BaseRRegressor(learner=Lasso())\n",
    "}\n",
    "\n",
    "propensity_learner = LogisticRegression(penalty='l1', solver='liblinear')\n",
    "\n",
    "df_res_lasso = run_experiments(n_list, p_list, s_list, m_list, learner_dict, num_iter, propensity_learner=propensity_learner)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "learner    sim_mode\n",
       "R-Learner  1           0.135057\n",
       "           2           1.228229\n",
       "           3           0.056223\n",
       "           4           1.769802\n",
       "S-Learner  1           0.290226\n",
       "           2           1.911610\n",
       "           3           1.000000\n",
       "           4           1.696009\n",
       "T-Learner  1           0.214197\n",
       "           2           1.229950\n",
       "           3           2.133935\n",
       "           4           1.848652\n",
       "X-Learner  1           0.213853\n",
       "           2           1.257568\n",
       "           3           1.910579\n",
       "           4           1.826252\n",
       "Name: pehe, dtype: float64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_res_lasso.groupby(['learner', 'sim_mode'])['pehe'].median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_generation_descs = {\n",
    "    1: 'Difficult nuisance and easy treatment',\n",
    "    2: 'Randomized trial',\n",
    "    3: 'Easy propensity and a difficult baseline',\n",
    "    4: 'Unrelated treatment and control'\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x='learner', y='pehe', data=df_res_lasso, linewidth=1, showfliers=False)\n",
    "plt.ylabel('PEHE (MSE)')\n",
    "plt.xlabel('')\n",
    "plt.title('All experiments (Lasso)')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(2, 2, figsize=(15, 10))\n",
    "axs = axs.ravel()\n",
    "for i, m in zip(range(4), m_list):\n",
    "    sns.boxplot(x='learner', y='pehe', data=df_res_lasso.loc[df_res_lasso['sim_mode'] == m], linewidth=1, showfliers=False, ax=axs[i])\n",
    "    axs[i].title.set_text(data_generation_descs[m] + ' (Lasso)')\n",
    "    axs[i].set_ylabel('PEHE (MSE)')\n",
    "    axs[i].set_xlabel('') # Hack\n",
    "    axs[i].tick_params(labelsize=18)\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Gradient boosting based experiments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 100/100 [17:46:40<00:00, 640.00s/it]\n"
     ]
    }
   ],
   "source": [
    "n_list = [500, 1000]\n",
    "p_list = [6, 12]\n",
    "s_list = [0.5, 1, 2, 4]\n",
    "m_list = [1, 2, 3, 4]\n",
    "num_iter = 100\n",
    "\n",
    "learner_dict = {\n",
    "    'S-Learner': BaseSRegressor(learner=XGBRegressor(n_jobs=-1)),\n",
    "    'T-Learner': BaseTRegressor(learner=XGBRegressor(n_jobs=-1)),\n",
    "    'X-Learner': BaseXRegressor(learner=XGBRegressor(n_jobs=-1)),\n",
    "    'R-Learner': BaseRRegressor(learner=XGBRegressor(n_jobs=-1))\n",
    "}\n",
    "\n",
    "propensity_learner = LogisticRegression(penalty='l1', solver='liblinear')\n",
    "\n",
    "df_res_xgb = run_experiments(n_list, p_list, s_list, m_list, learner_dict, num_iter, propensity_learner=propensity_learner)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "learner    sim_mode\n",
       "R-Learner  1           5.178797\n",
       "           2           3.969635\n",
       "           3           6.766369\n",
       "           4           5.581396\n",
       "S-Learner  1           0.364403\n",
       "           2           0.802687\n",
       "           3           0.507753\n",
       "           4           1.030971\n",
       "T-Learner  1           1.401733\n",
       "           2           1.829172\n",
       "           3           2.266735\n",
       "           4           1.623793\n",
       "X-Learner  1           0.712560\n",
       "           2           0.818282\n",
       "           3           0.864205\n",
       "           4           1.196562\n",
       "Name: pehe, dtype: float64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_res_xgb.groupby(['learner', 'sim_mode'])['pehe'].median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x='learner', y='pehe', data=df_res_xgb, linewidth=1, showfliers=False)\n",
    "plt.ylabel('PEHE (MSE)')\n",
    "plt.xlabel('')\n",
    "plt.title('All experiments (XGB)')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(2, 2, figsize=(15, 10))\n",
    "axs = axs.ravel()\n",
    "for i, m in zip(range(4), m_list):\n",
    "    sns.boxplot(x='learner', y='pehe', data=df_res_xgb.loc[df_res_xgb['sim_mode'] == m], linewidth=1, showfliers=False, ax=axs[i])\n",
    "    axs[i].title.set_text(data_generation_descs[m] + ' (XGB)')\n",
    "    axs[i].set_ylabel('PEHE (MSE)')\n",
    "    axs[i].set_xlabel('') # Hack\n",
    "    axs[i].tick_params(labelsize=18)\n",
    "plt.tight_layout()"
   ]
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "4acd3287ba5216ad775c02c376e708ed794f511501a155bfdfe52a215149642e"
  },
  "kernelspec": {
   "display_name": "causal3.9",
   "language": "python",
   "name": "causal3.9"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.5"
  },
  "orig_nbformat": 2
 },
 "nbformat": 4,
 "nbformat_minor": 2
}