primary_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "338856e8-0514-4f9b-909d-3e1618762174",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as  pd\n",
    "import nibabel as nb\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import os\n",
    "import glob\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from tqdm import tqdm\n",
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "791a06e7-1ecc-4d8a-bc14-b5088e32f103",
   "metadata": {},
   "source": [
    "### Visualize data (each image size (113, 137, 113))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "59ad5adf-07fa-461d-bfa3-39a4ea2099fe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Gray matter (Traverse)')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1600x1600 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "slice = 50\n",
    "demo_filepath_whitematter = '/cis/home/jdey4/data_MRI/sub-A00008326/mri/mwp2sub-A00008326_T1w.nii'\n",
    "demo_filepath_graymatter = '/cis/home/jdey4/data_MRI/sub-A00008326/mri/mwp1sub-A00008326_T1w.nii'\n",
    "\n",
    "img_whitematter = nb.load(demo_filepath_whitematter).get_fdata()\n",
    "sliced_img_whitematter = img_whitematter[:,:,slice]\n",
    "\n",
    "img_graymatter = nb.load(demo_filepath_graymatter).get_fdata()\n",
    "sliced_img_graymatter = img_graymatter[:,:,slice]\n",
    "\n",
    "fig, ax = plt.subplots(2,2, figsize=(16,16))\n",
    "ax[0][0].imshow(sliced_img_whitematter)\n",
    "ax[0][1].imshow(sliced_img_graymatter)\n",
    "ax[1][0].hist(sliced_img_whitematter.reshape(-1))\n",
    "ax[1][1].hist(sliced_img_whitematter.reshape(-1))\n",
    "\n",
    "ax[0][0].set_title('White matter (Traverse)', fontsize=20)\n",
    "ax[0][1].set_title('Gray matter (Traverse)', fontsize=20)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "479277c8-b4aa-44e7-af66-e8b3a400be5a",
   "metadata": {},
   "source": [
    "### Analyze class distribution and age "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e58e3b63-dbae-4c55-91f4-98c51d38d945",
   "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>ID</th>\n",
       "      <th>Age</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Dataset</th>\n",
       "      <th>Dataset-ID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>sub-ABIDE1050339</td>\n",
       "      <td>18.0000</td>\n",
       "      <td>MALE</td>\n",
       "      <td>ABIDE</td>\n",
       "      <td>50339</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>sub-ABIDE1050701</td>\n",
       "      <td>18.0000</td>\n",
       "      <td>MALE</td>\n",
       "      <td>ABIDE</td>\n",
       "      <td>50701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>sub-ABIDE1050445</td>\n",
       "      <td>18.1383</td>\n",
       "      <td>MALE</td>\n",
       "      <td>ABIDE</td>\n",
       "      <td>50445</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>sub-ABIDE1050459</td>\n",
       "      <td>18.1547</td>\n",
       "      <td>MALE</td>\n",
       "      <td>ABIDE</td>\n",
       "      <td>50459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>sub-ABIDE1050341</td>\n",
       "      <td>18.2000</td>\n",
       "      <td>FEMALE</td>\n",
       "      <td>ABIDE</td>\n",
       "      <td>50341</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 ID      Age     Sex Dataset Dataset-ID\n",
       "0  sub-ABIDE1050339  18.0000    MALE   ABIDE      50339\n",
       "1  sub-ABIDE1050701  18.0000    MALE   ABIDE      50701\n",
       "2  sub-ABIDE1050445  18.1383    MALE   ABIDE      50445\n",
       "3  sub-ABIDE1050459  18.1547    MALE   ABIDE      50459\n",
       "4  sub-ABIDE1050341  18.2000  FEMALE   ABIDE      50341"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_excel('/Users/jayantadey/data_MRI/subjects_age_sex_data_MRI.xlsx')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9bd5e532-595f-4488-b918-1a0d97506efe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Age')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1600x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1,2, figsize=(16,8), sharey=True)\n",
    "\n",
    "total_female = len(df[df['Sex']=='FEMALE'])\n",
    "total_male = len(df[df['Sex']=='MALE'])\n",
    "\n",
    "df[df['Sex']=='FEMALE'].hist(ax=ax[0])\n",
    "df[df['Sex']=='MALE'].hist(ax=ax[1])\n",
    "\n",
    "ax[0].set_title('Female ('+str(total_female)+')', fontsize=20)\n",
    "ax[1].set_title('Male ('+str(total_male)+')', fontsize=20)\n",
    "\n",
    "ax[0].set_ylabel('Age', fontsize=20)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bf796c60-3680-4f21-a68b-fd4fce216c64",
   "metadata": {},
   "source": [
    "### Load data and build (feature, label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4c99b081-0f43-4911-b54c-dbd8210425b7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "sub-HBN_CBIC_NDARRX084UML  missing\n",
      "sub-HBN_CBIC_NDARLR168NP5  missing\n",
      "sub-HBN_RU_NDARYX806FL1  missing\n",
      "sub-HBN_CUNY_NDARGJ317VC9  missing\n",
      "sub-HBN_RU_NDARCB142ZPB  missing\n",
      "sub-HBN_CBIC_NDARJK482MZB  missing\n",
      "sub-HBN_CBIC_NDARLK690ZK9  missing\n",
      "sub-HBN_CBIC_NDARRN996JZK  missing\n",
      "sub-HBN_CUNY_NDARXW455MJ1  missing\n",
      "sub-HBN_CBIC_NDARJC399UW7  missing\n",
      "sub-HBN_RU_NDARHP924ZHW  missing\n",
      "sub-HBN_CBIC_NDARAR935TGZ  missing\n",
      "sub-HBN_CUNY_NDARUZ408MRL  missing\n",
      "sub-HBN_CBIC_NDARUZ221YL6  missing\n",
      "sub-HBN_CBIC_NDARCC140AAK  missing\n",
      "sub-HBN_CBIC_NDARMX259HUH  missing\n",
      "sub-HBN_CBIC_NDARJL656RDA  missing\n",
      "sub-HBN_RU_NDARWF259RB2  missing\n",
      "sub-HBN_CBIC_NDARAU939WUK  missing\n",
      "sub-HBN_CBIC_NDARVV095BWU  missing\n",
      "sub-HBN_RU_NDARRK882CLT  missing\n",
      "sub-HBN_SI_NDAREE196FEG  missing\n",
      "sub-HBN_CBIC_NDARPJ395JDY  missing\n",
      "sub-HBN_SI_NDARXE684LUY  missing\n",
      "sub-HBN_SI_NDARRK457MBX  missing\n",
      "sub-HBN_CBIC_NDARWV826NEC  missing\n",
      "sub-HBN_CBIC_NDARWV952EZT  missing\n",
      "sub-HBN_RU_NDAREN519BLJ  missing\n",
      "sub-HBN_CBIC_NDARJZ167VEZ  missing\n",
      "sub-HBN_CUNY_NDARTC795CR3  missing\n",
      "sub-HBN_CUNY_NDARTG982TV1  missing\n",
      "sub-HBN_CBIC_NDARFB322DRA  missing\n",
      "sub-HBN_CBIC_NDARLH881FBD  missing\n",
      "sub-HBN_CBIC_NDARVC997CME  missing\n",
      "sub-HBN_CBIC_NDAREA788ZAM  missing\n",
      "sub-HBN_CUNY_NDARGD751MMW  missing\n",
      "sub-HBN_CBIC_NDARRV877ERG  missing\n",
      "sub-HBN_CBIC_NDARXB692PXC  missing\n",
      "sub-HBN_CBIC_NDARWL758PAM  missing\n",
      "sub-HBN_CBIC_NDARWV452YZN  missing\n",
      "sub-HBN_RU_NDARFN553LUV  missing\n",
      "sub-HBN_RU_NDAREG590BNY  missing\n",
      "sub-HBN_CBIC_NDARHX252NVH  missing\n",
      "sub-HBN_CUNY_NDARAB282FDJ  missing\n",
      "sub-HBN_CBIC_NDARDN090KP6  missing\n",
      "sub-HBN_RU_NDARTH473LF8  missing\n",
      "sub-HBN_CBIC_NDARDW969AW5  missing\n",
      "sub-HBN_CBIC_NDARCH628LKW  missing\n",
      "sub-HBN_CUNY_NDARUT650LBR  missing\n",
      "sub-HBN_CBIC_NDARVV704MND  missing\n",
      "sub-HBN_CBIC_NDARRB561VCP  missing\n",
      "sub-HBN_CBIC_NDARBA004KBT  missing\n",
      "sub-HBN_RU_NDARKB547TCK  missing\n",
      "sub-HBN_CBIC_NDARVJ827RGV  missing\n",
      "sub-HBN_CUNY_NDARWC788HHV  missing\n",
      "sub-HBN_RU_NDARXZ685TU4  missing\n",
      "sub-HBN_CBIC_NDARDZ425JVB  missing\n",
      "sub-HBN_CUNY_NDARCP952HZA  missing\n",
      "sub-HBN_RU_NDARBU607ZZ3  missing\n",
      "sub-HBN_RU_NDARNT113YX7  missing\n",
      "sub-HBN_CBIC_NDARKP414AZ5  missing\n",
      "sub-HBN_CBIC_NDARCX021XWF  missing\n",
      "sub-HBN_CBIC_NDARMV189NXG  missing\n",
      "sub-HBN_SI_NDARWF090RZ7  missing\n",
      "sub-HBN_RU_NDARZM580BG2  missing\n",
      "sub-HBN_RU_NDARGC255BUN  missing\n",
      "sub-HBN_RU_NDARZA183DDY  missing\n",
      "sub-HBN_CBIC_NDARVG246LT7  missing\n",
      "sub-HBN_SI_NDARFW292PBD  missing\n",
      "sub-HBN_RU_NDARHM611GDR  missing\n",
      "sub-HBN_SI_NDARAV747WVL  missing\n",
      "sub-HBN_RU_NDARXG670HFE  missing\n",
      "sub-HBN_RU_NDARUJ894ZXG  missing\n",
      "sub-HBN_RU_NDARRA717GYV  missing\n",
      "sub-HBN_CBIC_NDARXX955UYH  missing\n",
      "sub-HBN_RU_NDARAU967RWU  missing\n",
      "sub-HBN_RU_NDARDB146NWY  missing\n",
      "sub-HBN_RU_NDARFR108JNB  missing\n",
      "sub-HBN_CUNY_NDARVD437JV0  missing\n",
      "sub-HBN_RU_NDARDL511UND  missing\n",
      "sub-HBN_SI_NDARJT730WP0  missing\n",
      "sub-HBN_RU_NDARXF203DCD  missing\n",
      "sub-HBN_RU_NDARWM848AKP  missing\n",
      "sub-HBN_RU_NDARYY218LU2  missing\n",
      "sub-HBN_CUNY_NDARCT531TC0  missing\n",
      "sub-HBN_CBIC_NDARKN477EBH  missing\n",
      "sub-HBN_RU_NDARFL506HVX  missing\n",
      "sub-HBN_RU_NDARTZ018PD5  missing\n",
      "sub-HBN_CUNY_NDARYK236YUD  missing\n",
      "sub-HBN_CUNY_NDARTG982UC3  missing\n",
      "sub-HBN_RU_NDARMY254BGN  missing\n",
      "sub-HBN_CUNY_NDARAY665GWN  missing\n",
      "sub-HBN_RU_NDARXL588FFJ  missing\n",
      "sub-HBN_RU_NDARUG091CY1  missing\n",
      "sub-HBN_RU_NDARMV718DYL  missing\n",
      "sub-HBN_CBIC_NDARFP503KJF  missing\n",
      "sub-HBN_CBIC_NDARWW790AKX  missing\n",
      "sub-HBN_RU_NDARPP726XBF  missing\n",
      "sub-HBN_RU_NDARGR354WBH  missing\n",
      "sub-HBN_CBIC_NDARLT294VUD  missing\n",
      "sub-HBN_CBIC_NDARRA321UKA  missing\n",
      "sub-HBN_SI_NDARHL358LGQ  missing\n",
      "sub-HBN_RU_NDARHZ476MJP  missing\n",
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      "sub-HBN_RU_NDARAX283MAK  missing\n",
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      "sub-HBN_RU_NDARYC466ER1  missing\n",
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      "sub-HBN_RU_NDARAT709MMX  missing\n",
      "sub-HBN_RU_NDARHC661KGK  missing\n",
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      "sub-HBN_CBIC_NDARWT694TXM  missing\n",
      "sub-HBN_RU_NDARMT882AWE  missing\n",
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      "sub-HBN_RU_NDARHB689WH7  missing\n",
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      "sub-HBN_SI_NDARUL341DD2  missing\n",
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      "sub-HBN_CBIC_NDARNZ504BUW  missing\n",
      "sub-HBN_RU_NDARNL134VF0  missing\n",
      "sub-HBN_CBIC_NDARRG715JGY  missing\n",
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      "sub-HBN_SI_NDARBA507GCT  missing\n",
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      "sub-HBN_CBIC_NDARTV785XCD  missing\n",
      "sub-HBN_CBIC_NDARGB015CT3  missing\n",
      "sub-HBN_RU_NDARZP630WYL  missing\n",
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      "sub-HBN_SI_NDARWP237VB3  missing\n",
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      "sub-HBN_RU_NDARTT194LTU  missing\n",
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      "sub-HBN_RU_NDARYG665JUD  missing\n",
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      "sub-HBN_RU_NDARRY280KNW  missing\n",
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      "sub-HBN_RU_NDARBH133TK6  missing\n",
      "sub-HBN_RU_NDARYA503XVQ  missing\n",
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      "sub-HBN_SI_NDARBU112XZE  missing\n",
      "sub-HBN_CBIC_NDARHP344PRU  missing\n",
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      "sub-HBN_CBIC_NDARPL194XDX  missing\n",
      "sub-HBN_RU_NDARZW363UGM  missing\n",
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      "sub-HBN_CBIC_NDARFU786BN4  missing\n",
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      "sub-HBN_RU_NDARBE641DGZ  missing\n",
      "sub-HBN_CBIC_NDARNJ633HHX  missing\n",
      "sub-HBN_CBIC_NDARFG118DW3  missing\n",
      "sub-HBN_RU_NDARHL164JHH  missing\n",
      "sub-HBN_RU_NDARLE554GYT  missing\n",
      "sub-HBN_CUNY_NDARTG029XTK  missing\n",
      "sub-HBN_CBIC_NDARTB661TVR  missing\n",
      "sub-HBN_SI_NDARDX770PJK  missing\n",
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      "sub-HBN_RU_NDARTK507RJW  missing\n",
      "sub-HBN_RU_NDARCW933FD5  missing\n",
      "sub-HBN_CBIC_NDARYT509KUF  missing\n",
      "sub-HBN_SI_NDARZH629NVF  missing\n",
      "sub-HBN_CBIC_NDARJF479TBL  missing\n",
      "sub-HBN_CBIC_NDARME789TD2  missing\n",
      "sub-HBN_RU_NDARHG232EWH  missing\n",
      "sub-HBN_RU_NDARCN669XPR  missing\n",
      "sub-HBN_CBIC_NDAREN999ERM  missing\n",
      "sub-HBN_CBIC_NDARWH778CPD  missing\n",
      "sub-HBN_CUNY_NDARCE826DYW  missing\n",
      "sub-HBN_CBIC_NDARCP642KML  missing\n",
      "sub-HBN_CBIC_NDARXM571XCC  missing\n",
      "sub-HBN_RU_NDARMH249AWF  missing\n",
      "sub-HBN_CUNY_NDARMR744CZ7  missing\n",
      "sub-HBN_CBIC_NDARVU464RBF  missing\n",
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      "sub-HBN_CBIC_NDARCA050RZL  missing\n",
      "sub-HBN_RU_NDARWN709HA2  missing\n",
      "sub-HBN_RU_NDARTW889JN9  missing\n",
      "sub-HBN_CBIC_NDARAV474ADJ  missing\n",
      "sub-HBN_RU_NDARYW945PJU  missing\n",
      "sub-HBN_RU_NDARKK774VP5  missing\n",
      "sub-HBN_CBIC_NDARLP507NKW  missing\n",
      "sub-HBN_SI_NDARBZ216FW8  missing\n",
      "sub-HBN_RU_NDARDC704GKW  missing\n",
      "sub-HBN_CBIC_NDARUF230BYM  missing\n",
      "sub-HBN_CBIC_NDARWM682YJ0  missing\n",
      "sub-HBN_CUNY_NDAREK862TN1  missing\n",
      "sub-HBN_CUNY_NDARZV458LDP  missing\n",
      "sub-HBN_CBIC_NDARXP873PZZ  missing\n",
      "sub-HBN_RU_NDARNT676ZN4  missing\n",
      "sub-HBN_CUNY_NDARGL289TB8  missing\n",
      "sub-HBN_CBIC_NDAREH333KZD  missing\n",
      "sub-HBN_RU_NDARRL660CME  missing\n",
      "sub-HBN_RU_NDARMM486AJU  missing\n",
      "sub-HBN_RU_NDARHM413HVA  missing\n",
      "sub-HBN_RU_NDARTF133LLM  missing\n",
      "sub-HBN_CBIC_NDARTA246MJP  missing\n",
      "sub-HBN_CBIC_NDARUK931MGT  missing\n",
      "sub-HBN_CBIC_NDARAC331VEH  missing\n",
      "sub-HBN_CBIC_NDARAW216PM7  missing\n",
      "sub-HBN_CBIC_NDARNT151UN1  missing\n",
      "sub-HBN_CBIC_NDARNX672HNV  missing\n",
      "sub-HBN_SI_NDARMM905VYR  missing\n",
      "sub-HBN_CBIC_NDARKT312RUD  missing\n",
      "sub-HBN_RU_NDARVR116KG5  missing\n",
      "sub-HBN_CBIC_NDARUX534HZQ  missing\n",
      "sub-HBN_CBIC_NDARCP452ZVH  missing\n",
      "sub-HBN_CBIC_NDARJV062AM0  missing\n",
      "sub-HBN_RU_NDARBU730PN8  missing\n",
      "sub-HBN_SI_NDARKC452YVR  missing\n",
      "sub-HBN_RU_NDARUP249AMD  missing\n",
      "sub-HBN_RU_NDARTT667RKQ  missing\n",
      "sub-HBN_CBIC_NDARGC471KD1  missing\n",
      "sub-HBN_SI_NDARTK657DV6  missing\n",
      "sub-HBN_RU_NDARRX819BZ0  missing\n",
      "sub-HBN_RU_NDARTP270UAV  missing\n",
      "sub-HBN_CUNY_NDARNY393MAC  missing\n",
      "sub-HBN_CBIC_NDARZR180BM6  missing\n",
      "sub-HBN_RU_NDARUR153ZWB  missing\n",
      "sub-HBN_CUNY_NDARMW623RTE  missing\n",
      "sub-HBN_CBIC_NDARYM277DEA  missing\n",
      "sub-HBN_CBIC_NDARYX572VEW  missing\n",
      "sub-HBN_CBIC_NDARKR155ME9  missing\n",
      "sub-HBN_RU_NDARVC305AC6  missing\n",
      "sub-HBN_CBIC_NDAREK255DEE  missing\n",
      "sub-HBN_SI_NDAREK544ENR  missing\n",
      "sub-HBN_SI_NDARAT299YRR  missing\n",
      "sub-HBN_RU_NDARPW313LAJ  missing\n",
      "sub-HBN_RU_NDARCV628UUW  missing\n",
      "sub-HBN_CBIC_NDARNC489BX5  missing\n",
      "sub-HBN_RU_NDARJY645CRH  missing\n",
      "sub-HBN_RU_NDARWX338NDL  missing\n",
      "sub-HBN_CUNY_NDARBF911MLX  missing\n",
      "sub-HBN_RU_NDARCA153NKE  missing\n",
      "sub-HBN_SI_NDARAV945MCQ  missing\n",
      "sub-HBN_RU_NDARUE603CHQ  missing\n",
      "sub-HBN_CBIC_NDARHG906MEZ  missing\n",
      "sub-HBN_CBIC_NDARRY006EMB  missing\n",
      "sub-HBN_CBIC_NDARHB452LTW  missing\n",
      "sub-HBN_RU_NDARGK736HF4  missing\n",
      "sub-HBN_CBIC_NDARRR595LRJ  missing\n",
      "sub-HBN_CBIC_NDARAW298ZA9  missing\n",
      "sub-HBN_SI_NDARTA808DEQ  missing\n",
      "sub-HBN_RU_NDARBE287EFC  missing\n",
      "sub-HBN_CBIC_NDARYF699FW0  missing\n",
      "sub-HBN_RU_NDARPT910NEE  missing\n",
      "sub-HBN_RU_NDAREB093GH6  missing\n",
      "sub-HBN_RU_NDARXN764AC7  missing\n",
      "sub-HBN_CUNY_NDARAW558WUT  missing\n",
      "sub-HBN_SI_NDARCW419GBD  missing\n",
      "sub-HBN_RU_NDARLY687YDQ  missing\n",
      "sub-HBN_RU_NDARCH868WVX  missing\n",
      "sub-HBN_CUNY_NDARWK625CUV  missing\n",
      "sub-HBN_RU_NDARWC801CB5  missing\n",
      "sub-HBN_CUNY_NDARTF081PRL  missing\n",
      "sub-HBN_CUNY_NDARNN042YCH  missing\n",
      "sub-HBN_CBIC_NDARTE115TAE  missing\n",
      "sub-HBN_CBIC_NDARLZ745EUN  missing\n",
      "sub-HBN_CBIC_NDARUC591FWN  missing\n",
      "sub-HBN_CUNY_NDARYW170CAA  missing\n",
      "sub-HBN_RU_NDARDE294HNX  missing\n",
      "sub-HBN_CUNY_NDARNL971TL5  missing\n",
      "sub-HBN_RU_NDARLL720BGU  missing\n",
      "sub-HBN_CUNY_NDARMY291ZPH  missing\n",
      "sub-HBN_CUNY_NDARMH127CEW  missing\n",
      "sub-HBN_RU_NDARHX418ZGJ  missing\n",
      "sub-HBN_CBIC_NDARLT365LHK  missing\n",
      "sub-HBN_RU_NDARLV387GP4  missing\n",
      "sub-HBN_RU_NDARDT181RP4  missing\n",
      "sub-HBN_CUNY_NDARAL897CYV  missing\n",
      "sub-HBN_CBIC_NDARPF682GDC  missing\n",
      "sub-HBN_RU_NDARUN300FG1  missing\n",
      "sub-HBN_SI_NDARUY876VL1  missing\n",
      "sub-HBN_CUNY_NDARBK739HXR  missing\n",
      "sub-HBN_RU_NDARJK154PF5  missing\n",
      "sub-HBN_CUNY_NDARPA414ARE  missing\n",
      "sub-HBN_CBIC_NDARYG130LBT  missing\n",
      "sub-HBN_RU_NDARDJ970ELG  missing\n",
      "sub-HBN_CBIC_NDARLE282UHJ  missing\n",
      "sub-HBN_CBIC_NDARZK745JGG  missing\n",
      "sub-HBN_CUNY_NDARPL108LAV  missing\n",
      "sub-HBN_CBIC_NDARVB012UWL  missing\n",
      "sub-HBN_RU_NDARAP176AD1  missing\n",
      "sub-HBN_CBIC_NDAREK130FBX  missing\n",
      "sub-HBN_CBIC_NDARXN893UEZ  missing\n",
      "sub-HBN_CUNY_NDARCY049DAF  missing\n",
      "sub-HBN_SI_NDARCJ007GF8  missing\n",
      "sub-HBN_CBIC_NDARPB957JXE  missing\n",
      "sub-HBN_CUNY_NDARVL789JCG  missing\n",
      "sub-HBN_CBIC_NDARAR238RZ8  missing\n",
      "sub-HBN_CBIC_NDARCR582GKJ  missing\n",
      "sub-HBN_CUNY_NDARRG346DNL  missing\n",
      "sub-HBN_CUNY_NDARNP962TJK  missing\n",
      "sub-HBN_CBIC_NDARKN139APF  missing\n",
      "sub-HBN_RU_NDARRD326KB9  missing\n",
      "sub-HBN_CUNY_NDARRM938ZXD  missing\n",
      "sub-HBN_CUNY_NDARYH501UH3  missing\n",
      "sub-HBN_CBIC_NDARZK601NG9  missing\n",
      "sub-HBN_RU_NDAREH074NG8  missing\n",
      "sub-HBN_RU_NDAREW074ZM2  missing\n",
      "sub-HBN_CUNY_NDARHR448DEV  missing\n",
      "sub-HBN_CBIC_NDARYF272EDC  missing\n",
      "sub-HBN_CBIC_NDARGW450YUX  missing\n",
      "sub-HBN_CBIC_NDARWN739ED2  missing\n",
      "sub-HBN_RU_NDARNP812WAQ  missing\n",
      "sub-HBN_RU_NDARUZ206DRV  missing\n",
      "sub-HBN_RU_NDARXD345GBN  missing\n",
      "sub-HBN_CBIC_NDARJF517HC8  missing\n",
      "sub-HBN_CBIC_NDARYN174NPH  missing\n",
      "sub-HBN_RU_NDARUY379PT5  missing\n",
      "sub-HBN_CUNY_NDARUN771DPA  missing\n",
      "sub-HBN_CUNY_NDARLB291FBV  missing\n",
      "sub-HBN_CBIC_NDARUZ200NRJ  missing\n",
      "sub-HBN_CBIC_NDARDB720VEA  missing\n",
      "sub-HBN_RU_NDAREG561ML5  missing\n",
      "sub-HBN_CBIC_NDARFR696PLG  missing\n",
      "sub-HBN_CBIC_NDARMV605LGH  missing\n",
      "sub-HBN_CBIC_NDARHC426PAW  missing\n",
      "sub-HBN_SI_NDARHT218GFA  missing\n",
      "sub-HBN_RU_NDARNZ043VH0  missing\n",
      "sub-HBN_CBIC_NDARKZ198TAA  missing\n",
      "sub-HBN_RU_NDARCY178KJP  missing\n",
      "sub-HBN_RU_NDARHN749RW4  missing\n",
      "sub-HBN_RU_NDARJG494YDY  missing\n",
      "sub-HBN_RU_NDARWG831JJ8  missing\n",
      "sub-HBN_CUNY_NDARAV082JHA  missing\n",
      "sub-HBN_RU_NDARWA102TY7  missing\n",
      "sub-HBN_CBIC_NDARYP863PZ4  missing\n",
      "sub-HBN_CUNY_NDARLJ933JPP  missing\n",
      "sub-HBN_CBIC_NDARFU395UBW  missing\n",
      "sub-HBN_CBIC_NDARAX277ATU  missing\n",
      "sub-HBN_CBIC_NDARTU841ZAE  missing\n",
      "sub-HBN_CUNY_NDARMN151FLL  missing\n",
      "sub-HBN_CUNY_NDARZN501NFF  missing\n",
      "sub-HBN_RU_NDARPM105MKA  missing\n",
      "sub-HBN_RU_NDARMJ334ZK3  missing\n",
      "sub-HBN_CBIC_NDARCB305AFY  missing\n",
      "sub-HBN_CBIC_NDARXW330ZJT  missing\n",
      "sub-HBN_CUNY_NDARXG961UAB  missing\n",
      "sub-HBN_CBIC_NDARVF544YP6  missing\n",
      "sub-HBN_RU_NDARYZ770NA1  missing\n",
      "sub-HBN_SI_NDARWB685NUG  missing\n",
      "sub-HBN_CBIC_NDARFZ143BUQ  missing\n",
      "sub-HBN_CBIC_NDARVC140PKY  missing\n",
      "sub-HBN_RU_NDARER379GTP  missing\n",
      "sub-HBN_RU_NDARGV948BFZ  missing\n",
      "sub-HBN_CBIC_NDARNV375KEK  missing\n",
      "sub-HBN_RU_NDARDU986RBM  missing\n",
      "sub-HBN_CBIC_NDARUT233WU9  missing\n",
      "sub-HBN_CBIC_NDARET671FTC  missing\n",
      "sub-HBN_RU_NDARGU100JH4  missing\n",
      "sub-HBN_CUNY_NDAREW531JV9  missing\n",
      "sub-HBN_CUNY_NDARTH990UEC  missing\n",
      "sub-HBN_CBIC_NDARZX384XVQ  missing\n",
      "sub-HBN_SI_NDARXY337ZH9  missing\n",
      "sub-HBN_CBIC_NDAREW326RXX  missing\n",
      "sub-HBN_CBIC_NDARAX075WL9  missing\n",
      "sub-HBN_RU_NDARRA933RLX  missing\n",
      "sub-HBN_CBIC_NDARGC407NV7  missing\n",
      "sub-HBN_CUNY_NDARZA151EU8  missing\n",
      "sub-HBN_CUNY_NDARGB101GUF  missing\n",
      "sub-HBN_CBIC_NDARAD256AHU  missing\n",
      "sub-HBN_SI_NDARHM304AXP  missing\n",
      "sub-HBN_CBIC_NDARHD841JAE  missing\n",
      "sub-HBN_CBIC_NDARHC825ZFZ  missing\n",
      "sub-HBN_CUNY_NDARPM172XGD  missing\n",
      "sub-HBN_CUNY_NDARTP149FG8  missing\n",
      "sub-HBN_RU_NDARNZ792HBN  missing\n",
      "sub-HBN_RU_NDARRJ989YPA  missing\n",
      "sub-HBN_CBIC_NDARVF786FUU  missing\n",
      "sub-HBN_CBIC_NDARML681XZJ  missing\n",
      "sub-HBN_CBIC_NDARGA589KWK  missing\n",
      "sub-HBN_CBIC_NDARDL377ZT7  missing\n",
      "sub-HBN_CBIC_NDARCW932EU6  missing\n",
      "sub-HBN_CBIC_NDARLA048NYE  missing\n",
      "sub-HBN_CBIC_NDARWP732GD1  missing\n",
      "sub-HBN_CBIC_NDARJU787GF5  missing\n",
      "sub-HBN_CBIC_NDARHE199NGL  missing\n",
      "sub-HBN_CUNY_NDARLV311HWL  missing\n",
      "sub-HBN_CBIC_NDARJH159UD4  missing\n",
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      "sub-HBN_SI_NDARMH763YZD  missing\n",
      "sub-HBN_RU_NDARBX121UM9  missing\n",
      "sub-HBN_RU_NDARET550NXC  missing\n",
      "sub-HBN_CBIC_NDARPC222WN6  missing\n",
      "sub-HBN_CBIC_NDARYN152YMW  missing\n",
      "sub-HBN_CBIC_NDARMH364EMW  missing\n",
      "sub-HBN_SI_NDARVG148WHV  missing\n",
      "sub-HBN_CBIC_NDARFA780CUG  missing\n",
      "sub-HBN_SI_NDARCB959FY4  missing\n",
      "sub-HBN_SI_NDARWX380JJK  missing\n",
      "sub-HBN_CUNY_NDARCJ667UPL  missing\n",
      "sub-HBN_RU_NDARCZ915NC1  missing\n",
      "sub-HBN_RU_NDARCV944JA6  missing\n",
      "sub-HBN_RU_NDARWP815VUP  missing\n",
      "sub-HBN_RU_NDARMR134HUY  missing\n",
      "sub-HBN_CBIC_NDARKP458TM1  missing\n",
      "sub-HBN_CBIC_NDARUE991BE0  missing\n",
      "sub-HBN_CUNY_NDARPE497UEY  missing\n",
      "sub-HBN_CUNY_NDARKK633KD2  missing\n",
      "sub-HBN_CBIC_NDARKN175HWB  missing\n",
      "sub-HBN_CBIC_NDARFV725DEQ  missing\n",
      "sub-HBN_CBIC_NDAREN352YZQ  missing\n",
      "sub-HBN_CUNY_NDARYK713TGJ  missing\n",
      "sub-HBN_RU_NDARGZ361JJ9  missing\n",
      "sub-HBN_CBIC_NDARFA233CUK  missing\n",
      "sub-HBN_CUNY_NDARMA657LLB  missing\n",
      "sub-HBN_CUNY_NDARCB492BAD  missing\n",
      "sub-HBN_SI_NDARGM498YFL  missing\n",
      "sub-HBN_SI_NDARWV677EFC  missing\n",
      "sub-HBN_CBIC_NDARTF776EYR  missing\n",
      "sub-HBN_CBIC_NDARKD590VF4  missing\n",
      "sub-HBN_CUNY_NDARUD345RW8  missing\n",
      "sub-HBN_CBIC_NDARAN525BVK  missing\n",
      "sub-HBN_CBIC_NDARCD687JUZ  missing\n",
      "sub-HBN_RU_NDARGH790CEF  missing\n",
      "sub-HBN_RU_NDARED628HMQ  missing\n",
      "sub-HBN_SI_NDARPF118ABV  missing\n",
      "sub-HBN_SI_NDARKH741PL8  missing\n",
      "sub-HBN_CUNY_NDARRK617NRL  missing\n",
      "sub-HBN_CBIC_NDARAX287BLD  missing\n",
      "sub-HBN_CUNY_NDARAR998KMM  missing\n",
      "sub-HBN_CBIC_NDARRF525ME3  missing\n",
      "sub-HBN_RU_NDARFJ372JDJ  missing\n",
      "sub-HBN_CUNY_NDARRP175MBY  missing\n",
      "sub-HBN_CBIC_NDARUL077YNE  missing\n",
      "sub-HBN_RU_NDARLA226ADX  missing\n",
      "sub-HBN_RU_NDARHV527DNK  missing\n",
      "sub-HBN_CBIC_NDARKE254HKM  missing\n",
      "sub-HBN_RU_NDARMD575AXD  missing\n",
      "sub-HBN_RU_NDARXG571WPL  missing\n",
      "sub-HBN_RU_NDARBJ482HJL  missing\n",
      "sub-HBN_CBIC_NDARDE597GKQ  missing\n",
      "sub-HBN_RU_NDARAM848GTE  missing\n",
      "sub-HBN_CUNY_NDARPE460HAN  missing\n",
      "sub-HBN_RU_NDARGW404GJL  missing\n",
      "sub-HBN_SI_NDAREC182WW2  missing\n",
      "sub-HBN_CBIC_NDARLU939YX4  missing\n",
      "sub-HBN_SI_NDAREY962BM7  missing\n",
      "sub-HBN_RU_NDARZE389XF0  missing\n",
      "sub-HBN_RU_NDARKM301DY0  missing\n",
      "sub-HBN_CBIC_NDARNC287MK5  missing\n",
      "sub-HBN_RU_NDARNZ917TDK  missing\n",
      "sub-HBN_CBIC_NDARBF293YRB  missing\n",
      "sub-HBN_CBIC_NDARXN641PWT  missing\n",
      "sub-HBN_RU_NDARDZ440NGK  missing\n",
      "sub-HBN_CBIC_NDARMZ477MNH  missing\n",
      "sub-HBN_CUNY_NDARNT858ZU2  missing\n",
      "sub-HBN_RU_NDARXJ973GFA  missing\n",
      "sub-HBN_RU_NDARXL023NG9  missing\n",
      "sub-HBN_RU_NDARVC310XV2  missing\n",
      "sub-HBN_CBIC_NDARJG581CCK  missing\n",
      "sub-HBN_CUNY_NDARLZ995KLB  missing\n",
      "sub-HBN_CBIC_NDARKX116PGU  missing\n",
      "sub-HBN_CBIC_NDARVX547MA0  missing\n",
      "sub-HBN_CBIC_NDARKX371CJY  missing\n",
      "sub-HBN_CUNY_NDARNR630AK6  missing\n",
      "sub-HBN_RU_NDARGC124PAW  missing\n",
      "sub-HBN_SI_NDARGA967MGC  missing\n",
      "sub-HBN_RU_NDARLU529MP7  missing\n",
      "sub-HBN_CUNY_NDARAM357BUA  missing\n",
      "sub-HBN_CUNY_NDARCG099GTV  missing\n",
      "sub-HBN_RU_NDARMN695VFH  missing\n",
      "sub-HBN_RU_NDARME736MN8  missing\n",
      "sub-HBN_CBIC_NDARHZ852XY0  missing\n",
      "sub-HBN_CBIC_NDARPL406KX4  missing\n",
      "sub-HBN_CUNY_NDARJZ919LPL  missing\n",
      "sub-HBN_RU_NDARBJ375VP4  missing\n",
      "sub-HBN_RU_NDARHF545HFW  missing\n",
      "sub-HBN_SI_NDARHP656DLC  missing\n",
      "sub-HBN_SI_NDARWV470ATB  missing\n",
      "sub-HBN_RU_NDAREG013BLG  missing\n",
      "sub-HBN_RU_NDARJA157YB3  missing\n",
      "sub-HBN_CBIC_NDARUC994BLZ  missing\n",
      "sub-HBN_RU_NDARHW158PPR  missing\n",
      "sub-HBN_CUNY_NDARTL107DMD  missing\n",
      "sub-HBN_SI_NDARXK164TNN  missing\n",
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      "sub-HBN_RU_NDARCC824FCL  missing\n",
      "sub-HBN_SI_NDARUA421HT8  missing\n",
      "sub-HBN_CBIC_NDARYV538EBP  missing\n",
      "sub-HBN_CUNY_NDARHD079LCL  missing\n",
      "sub-HBN_RU_NDARRU729XRU  missing\n",
      "sub-HBN_CBIC_NDARGY542TJ5  missing\n",
      "sub-HBN_CBIC_NDARZA511FYF  missing\n",
      "sub-HBN_RU_NDAREX065KJU  missing\n",
      "sub-HBN_SI_NDAREM141CKP  missing\n",
      "sub-HBN_CUNY_NDARFJ423LW9  missing\n",
      "sub-HBN_CBIC_NDARWV403LV8  missing\n",
      "sub-HBN_CUNY_NDARBH275EXT  missing\n",
      "sub-HBN_CBIC_NDARTJ963NC8  missing\n",
      "sub-HBN_CBIC_NDARGZ553TMQ  missing\n",
      "sub-HBN_SI_NDARHJ946UPH  missing\n",
      "sub-HBN_CBIC_NDARGV455JV1  missing\n",
      "sub-HBN_CUNY_NDARNE098NPR  missing\n",
      "sub-HBN_RU_NDARFE299MWU  missing\n",
      "sub-HBN_CBIC_NDARGY959RN8  missing\n",
      "sub-HBN_CBIC_NDARRN626DC4  missing\n",
      "sub-HBN_RU_NDARPK300HMV  missing\n",
      "sub-HBN_CUNY_NDARWV731NCC  missing\n",
      "sub-HBN_CBIC_NDARFW253GZM  missing\n",
      "sub-HBN_CBIC_NDAREK549XUQ  missing\n",
      "sub-HBN_CBIC_NDARAB977GFB  missing\n",
      "sub-HBN_CBIC_NDARLJ280UCN  missing\n",
      "sub-HBN_CUNY_NDARGN205MUG  missing\n",
      "sub-HBN_RU_NDARRP163YRC  missing\n",
      "sub-HBN_CBIC_NDARLB162XP2  missing\n",
      "sub-HBN_RU_NDARGD507TDZ  missing\n",
      "sub-HBN_RU_NDARUU801VFA  missing\n",
      "sub-HBN_CBIC_NDARCG785NND  missing\n",
      "sub-HBN_RU_NDARAR305LXG  missing\n",
      "sub-HBN_RU_NDARLB547HJD  missing\n",
      "sub-HBN_CBIC_NDARGC822DBX  missing\n",
      "sub-HBN_SI_NDARVB607WW4  missing\n",
      "sub-HBN_CBIC_NDARDL471LWJ  missing\n",
      "sub-HBN_CBIC_NDARKZ312XR1  missing\n",
      "sub-HBN_CUNY_NDARGZ888HJN  missing\n",
      "sub-HBN_CBIC_NDARDT889RT9  missing\n",
      "sub-HBN_RU_NDARPK223WVZ  missing\n",
      "sub-HBN_CBIC_NDARBX830ZD4  missing\n",
      "sub-HBN_RU_NDARRY714GEY  missing\n",
      "sub-HBN_RU_NDARUL694GYN  missing\n",
      "sub-HBN_RU_NDARBJ674TVU  missing\n",
      "sub-HBN_RU_NDARZR529EJ1  missing\n",
      "sub-HBN_RU_NDARBH228RDW  missing\n",
      "sub-HBN_CBIC_NDARTW567YUQ  missing\n",
      "sub-HBN_RU_NDARZZ740MLM  missing\n",
      "sub-HBN_RU_NDARGA346NA7  missing\n",
      "sub-HBN_CBIC_NDARAH129BMC  missing\n",
      "sub-HBN_RU_NDARXF890FLA  missing\n",
      "sub-HBN_CBIC_NDARGM196JMM  missing\n",
      "sub-HBN_CUNY_NDAREW557WZM  missing\n",
      "sub-HBN_CBIC_NDARPD855ARC  missing\n",
      "sub-HBN_CBIC_NDARPV915ZPE  missing\n",
      "sub-HBN_CBIC_NDARTV107XD4  missing\n",
      "sub-HBN_RU_NDARWV794VM2  missing\n",
      "sub-HBN_CBIC_NDARCG808HDJ  missing\n",
      "sub-HBN_SI_NDARLP181HLA  missing\n",
      "sub-HBN_SI_NDARCA186WGH  missing\n",
      "sub-HBN_RU_NDARNK055HVH  missing\n",
      "sub-HBN_CBIC_NDARKA170RFD  missing\n",
      "sub-HBN_CBIC_NDARWM560DXH  missing\n",
      "sub-HBN_CUNY_NDARNN761ZPA  missing\n",
      "sub-HBN_CBIC_NDARPK337CLE  missing\n",
      "sub-HBN_RU_NDARFA165XBV  missing\n",
      "sub-HBN_CUNY_NDARWK212ZPX  missing\n",
      "sub-HBN_CBIC_NDARLR924YAV  missing\n",
      "sub-HBN_SI_NDARZW013RUH  missing\n",
      "sub-HBN_CUNY_NDARWU079DJZ  missing\n",
      "sub-HBN_SI_NDARRP592GHK  missing\n",
      "sub-HBN_CUNY_NDARCF777CT1  missing\n",
      "sub-HBN_CBIC_NDARLL846UYQ  missing\n",
      "sub-HBN_CBIC_NDARKN633WZA  missing\n",
      "sub-HBN_CUNY_NDARWY550FH5  missing\n",
      "sub-HBN_CBIC_NDARAB348EWR  missing\n",
      "sub-HBN_RU_NDARME100GK1  missing\n",
      "sub-HBN_CUNY_NDARKK117YX5  missing\n",
      "sub-HBN_CBIC_NDARHR690ZAM  missing\n",
      "sub-HBN_RU_NDARLB671TLU  missing\n",
      "sub-HBN_RU_NDARYT155NHX  missing\n",
      "sub-HBN_CBIC_NDARLJ228ZF8  missing\n",
      "sub-HBN_RU_NDARHR099EWX  missing\n",
      "sub-HBN_SI_NDARXN047RUT  missing\n",
      "sub-HBN_CBIC_NDARVZ086GL6  missing\n",
      "sub-HBN_CBIC_NDARBD328NUQ  missing\n"
     ]
    }
   ],
   "source": [
    "path = '/Users/jayantadey/data_MRI/'\n",
    "subjects = os.listdir(path)\n",
    "X = []\n",
    "y = []\n",
    "IDs = set(df['ID'])\n",
    "for subject in subjects:\n",
    "    if subject in IDs:\n",
    "        #print(df[df['ID']==subject]['Sex'])\n",
    "        sex = int(df[df['ID']==subject]['Sex'].item()=='FEMALE')\n",
    "        current_file = os.path.join(path, subject)\n",
    "        tmp = []\n",
    "        save = True\n",
    "        for file in glob.glob(current_file+'/mri/*'):\n",
    "            try:\n",
    "                img = nb.load(file).get_fdata()\n",
    "                #print(img.shape)\n",
    "                tmp.append(img.reshape(-1))\n",
    "            except:\n",
    "                save = False\n",
    "                print(file,' corrupted')\n",
    "\n",
    "        '''if len(tmp)<2:\n",
    "            print(subject, ' has less files')'''\n",
    "            \n",
    "        if save and len(tmp)==2:\n",
    "            X.append(np.array(tmp).reshape(1,-1))\n",
    "            y.append(sex)\n",
    "    else:\n",
    "        print(subject, \" missing\")\n",
    "X = np.concatenate(X,axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "fd7fa4f0-933a-4e2f-9386-7efa4a8c4c61",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2368, 3498706)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "b19f305e-0ca2-4f1e-97c0-63a75ef1ea1b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5025337837837838"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.mean(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "75785696-ec90-45a0-a505-8a0ce625d0a1",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 5/5 [3:25:06<00:00, 2461.40s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy is  0.7995780590717301\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "reps = 5\n",
    "accuracy = 0.0\n",
    "\n",
    "for _ in tqdm(range(reps)):\n",
    "    x_train, x_test, y_train, y_test = train_test_split(\n",
    "                    X, y, train_size=0.6, random_state=0, stratify=y)\n",
    "    clf = RandomForestClassifier(n_estimators=1000)\n",
    "    clf.fit(x_train,y_train)\n",
    "    accuracy += np.mean(clf.predict(x_test)==y_test)\n",
    "\n",
    "print('Accuracy is ',accuracy/reps)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "bd2c3276-55fc-4ec7-a162-7f4403f7f2b6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0., 0., 0., ..., 0., 0., 0.])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.feature_importances_"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "adbca822-85d6-4736-88a9-d36b52affe40",
   "metadata": {},
   "source": [
    "### Notes\n",
    "\n",
    "1. propensity matching\n",
    "2. run sporf and morf\n",
    "3. see feature importace"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "45eb6278-870f-41e4-b771-090bcd0c455b",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.15"
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