120 lines (119 with data), 2.4 kB

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "import os\n",
    "sys.path.insert(0, '/home/rnshishir/deepmed/TBEHRT_pl/')\n",
    "\n",
    "import scipy\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from src.CV_TMLE import *"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# CV TMLE tutorial"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "running CV-TMLE for binary outcomes...\n"
     ]
    }
   ],
   "source": [
    "# folds in the npz format\n",
    "foldNPZ = ['TBEHRT_Test__CUT0.npz', 'TBEHRT_Test__CUT1.npz', 'TBEHRT_Test__CUT2.npz', 'TBEHRT_Test__CUT3.npz', 'TBEHRT_Test__CUT4.npz' ]\n",
    "\n",
    "# cvtmle runner \n",
    "TMLErun = CVTMLE(fromFolds=foldNPZ,truncate_level=0.03 )\n",
    "\n",
    "# estiamte the risk ratio for binary outcome\n",
    "est = TMLErun.run_tmle_binary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0.10878099048487283, 5.2854239704810925e-08, 223885.61366048577]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "est\n",
    "# prints estimate and lower and upper conf interval bounds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_parquet('test.parquet')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# raw\n",
    "# data[data.explabel ==1].label.mean()/data[data.explabel ==0].label.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "real3",
   "language": "python",
   "name": "py3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.8"
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