{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "4cb533b4-32b9-4f6e-a7cd-8c5c850faf5b",
   "metadata": {},
   "outputs": [],
   "source": [
    "#adapted version of Tinashe's gather_qc.ipynb to conatenate xcp qc csvs across subjects/sessions\n",
    "\n",
    "import pandas as pd\n",
    "import glob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "7bef3b67-aa60-465c-a7ef-20d11892f1e5",
   "metadata": {},
   "outputs": [],
   "source": [
    "#write list of subj csvs\n",
    "qc_path = [\"/cbica/projects/wolf_satterthwaite_reward/Margaret/Day2/production/derivatives-unzipped/DERIVATIVES/XCP//sub-*/ses-*/func/*space-MNI152NLin6Asym*.csv\"]\n",
    "\n",
    "qc_files = []\n",
    "\n",
    "for x in qc_path:\n",
    "    qc_files.extend(glob.glob(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "2de7b162-65b1-4696-aa35-1f78aa6a131f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['/cbica/projects/wolf_satterthwaite_reward/Margaret/Day2/production/derivatives-unzipped/DERIVATIVES/XCP/sub-13373/ses-day2/func/sub-13373_ses-day2_task-rest_space-MNI152NLin6Asym_desc-qc_res-2_bold.csv',\n",
       " '/cbica/projects/wolf_satterthwaite_reward/Margaret/Day2/production/derivatives-unzipped/DERIVATIVES/XCP/sub-13373/ses-day2/func/sub-13373_ses-day2_task-card_run-2_space-MNI152NLin6Asym_desc-qc_res-2_bold.csv',\n",
       " '/cbica/projects/wolf_satterthwaite_reward/Margaret/Day2/production/derivatives-unzipped/DERIVATIVES/XCP/sub-13373/ses-day2/func/sub-13373_ses-day2_task-face_run-2_space-MNI152NLin6Asym_desc-qc_res-2_bold.csv',\n",
       " '/cbica/projects/wolf_satterthwaite_reward/Margaret/Day2/production/derivatives-unzipped/DERIVATIVES/XCP/sub-13373/ses-day2/func/sub-13373_ses-day2_task-card_run-1_space-MNI152NLin6Asym_desc-qc_res-2_bold.csv',\n",
       " '/cbica/projects/wolf_satterthwaite_reward/Margaret/Day2/production/derivatives-unzipped/DERIVATIVES/XCP/sub-10180/ses-day2/func/sub-10180_ses-day2_task-face_run-2_space-MNI152NLin6Asym_desc-qc_res-2_bold.csv',\n",
       " '/cbica/projects/wolf_satterthwaite_reward/Margaret/Day2/production/derivatives-unzipped/DERIVATIVES/XCP/sub-10180/ses-day2/func/sub-10180_ses-day2_task-face_run-1_space-MNI152NLin6Asym_desc-qc_res-2_bold.csv',\n",
       " '/cbica/projects/wolf_satterthwaite_reward/Margaret/Day2/production/derivatives-unzipped/DERIVATIVES/XCP/sub-10180/ses-day2/func/sub-10180_ses-day2_task-card_run-1_space-MNI152NLin6Asym_desc-qc_res-2_bold.csv',\n",
       " '/cbica/projects/wolf_satterthwaite_reward/Margaret/Day2/production/derivatives-unzipped/DERIVATIVES/XCP/sub-10180/ses-day2/func/sub-10180_ses-day2_task-rest_space-MNI152NLin6Asym_desc-qc_res-2_bold.csv',\n",
       " '/cbica/projects/wolf_satterthwaite_reward/Margaret/Day2/production/derivatives-unzipped/DERIVATIVES/XCP/sub-10180/ses-day2/func/sub-10180_ses-day2_task-card_run-2_space-MNI152NLin6Asym_desc-qc_res-2_bold.csv',\n",
       " '/cbica/projects/wolf_satterthwaite_reward/Margaret/Day2/production/derivatives-unzipped/DERIVATIVES/XCP/sub-12738/ses-day2/func/sub-12738_ses-day2_task-face_run-2_space-MNI152NLin6Asym_desc-qc_res-2_bold.csv']"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qc_files[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "eb21527c-b4ca-4ef0-b832-844f447ef193",
   "metadata": {},
   "outputs": [],
   "source": [
    "dfs = [pd.read_csv(x) for x in qc_files]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "87e5c454-0d3d-4b76-80f1-cb635b38764d",
   "metadata": {},
   "outputs": [],
   "source": [
    "output = pd.concat(dfs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "0af845e4-20b7-404a-866e-ff5286abca9b",
   "metadata": {},
   "outputs": [],
   "source": [
    "output.to_csv(\"/cbica/projects/wolf_satterthwaite_reward/Margaret/Day2/curation/code/sandbox/qc_d2.csv\", index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b71dd772-9c2b-489d-ba1f-183ffe2ee6f6",
   "metadata": {},
   "outputs": [],
   "source": [
    "#listing scans with normCrossCor < 0.8 (per Ted's review of QC plots)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
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    "name": "ipython",
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