nibetaseries_template.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip3 install \"nibetaseries==0.6.0\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install \"numpy == 1.18.4\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip3 uninstall numpy -y"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "Running NiBetaSeries\n",
    "====================\n",
    "\n",
    "This example runs through a basic call of NiBetaSeries using\n",
    "the commandline entry point ``nibs``.\n",
    "While this example is using python, typically ``nibs`` will be\n",
    "called directly on the commandline.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import all the necessary packages\n",
    "=================================\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tempfile  # make a temporary directory for files\n",
    "import os  # interact with the filesystem\n",
    "import urllib.request  # grad data from internet\n",
    "import tarfile  # extract files from tar\n",
    "from subprocess import Popen, PIPE, STDOUT  # enable calling commandline\n",
    "\n",
    "import matplotlib.pyplot as plt  # manipulate figures\n",
    "import seaborn as sns  # display results\n",
    "import pandas as pd   # manipulate tabular data\n",
    "import nibabel as nib  # load the beta maps in python\n",
    "from nilearn import plotting  # plot nifti images"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Download relevant data from ds000164 (and Atlas Files)\n",
    "======================================================\n",
    "The subject data came from `openneuro\n",
    "<https://openneuro.org/datasets/ds000164/versions/00001/>`_\n",
    ":cite:`n-Verstynen2014`.\n",
    "The atlas data came from a `recently published parcellation\n",
    "<https://www.ncbi.nlm.nih.gov/pubmed/28981612>`_\n",
    "in a publically accessible github repository.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Our working directory: /tmp/tmpabo1ms7h\n"
     ]
    }
   ],
   "source": [
    "# atlas github repo for reference:\n",
    "\"\"\"https://github.com/ThomasYeoLab/CBIG/raw/master/stable_projects/\\\n",
    "brain_parcellation/Schaefer2018_LocalGlobal/Parcellations/MNI/\"\"\"\n",
    "data_dir = tempfile.mkdtemp()\n",
    "print('Our working directory: {}'.format(data_dir))\n",
    "\n",
    "# download the tar data\n",
    "url = \"https://www.dropbox.com/s/fvtyld08srwl3x9/ds000164-test_v2.tar.gz?dl=1\"\n",
    "\n",
    "tar_file = os.path.join(data_dir, \"ds000164.tar.gz\")\n",
    "u = urllib.request.urlopen(url)\n",
    "data = u.read()\n",
    "u.close()\n",
    "\n",
    "# write tar data to file\n",
    "with open(tar_file, \"wb\") as f:\n",
    "    f.write(data)\n",
    "\n",
    "# extract the data\n",
    "tar = tarfile.open(tar_file, mode='r|gz')\n",
    "tar.extractall(path=data_dir)\n",
    "\n",
    "os.remove(tar_file)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Display the minimal dataset necessary to run nibs\n",
    "=================================================\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tmpabo1ms7h/\n",
      "    ds000164/\n",
      "        dataset_description.json\n",
      "        task-stroop_events.json\n",
      "        task-stroop_bold.json\n",
      "        T1w.json\n",
      "        README\n",
      "        CHANGES\n",
      "        derivatives/\n",
      "            fmriprep/\n",
      "                dataset_description.json\n",
      "                sub-001/\n",
      "                    func/\n",
      "                        sub-001_task-stroop_desc-confounds_regressors.tsv\n",
      "                        sub-001_task-stroop_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz\n",
      "                        sub-001_task-stroop_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz\n",
      "            data/\n",
      "                Schaefer2018_100Parcels_7Networks_order.txt\n",
      "                Schaefer2018_100Parcels_7Networks_order_FSLMNI152_2mm.nii.gz\n",
      "        sub-001/\n",
      "            anat/\n",
      "                sub-001_T1w.nii.gz\n",
      "            func/\n",
      "                sub-001_task-stroop_bold.nii.gz\n",
      "                sub-001_task-stroop_events.tsv\n"
     ]
    }
   ],
   "source": [
    "# https://stackoverflow.com/questions/9727673/list-directory-tree-structure-in-python\n",
    "def list_files(startpath):\n",
    "    for root, dirs, files in os.walk(startpath):\n",
    "        level = root.replace(startpath, '').count(os.sep)\n",
    "        indent = ' ' * 4 * (level)\n",
    "        print('{}{}/'.format(indent, os.path.basename(root)))\n",
    "        subindent = ' ' * 4 * (level + 1)\n",
    "        for f in files:\n",
    "            print('{}{}'.format(subindent, f))\n",
    "\n",
    "\n",
    "list_files(data_dir)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Manipulate events file so it satifies assumptions\n",
    "=================================================\n",
    "1. the correct column has 1's and 0's corresponding to correct and incorrect,\n",
    "respectively.\n",
    "2. the condition column is renamed to trial_type\n",
    "nibs currently depends on the \"correct\" column being binary\n",
    "and the \"trial_type\" column to contain the trial types of interest.\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "read the file\n",
    "-------------\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    onset  duration correct  condition  response_time\n",
      "0   0.342         1       Y    neutral          1.186\n",
      "1   3.345         1       Y  congruent          0.667\n",
      "2  12.346         1       Y  congruent          0.614\n",
      "3  15.349         1       Y    neutral          0.696\n",
      "4  18.350         1       Y    neutral          0.752\n"
     ]
    }
   ],
   "source": [
    "events_file = os.path.join(data_dir,\n",
    "                           \"ds000164\",\n",
    "                           \"sub-001\",\n",
    "                           \"func\",\n",
    "                           \"sub-001_task-stroop_events.tsv\")\n",
    "events_df = pd.read_csv(events_file, sep='\\t', na_values=\"n/a\")\n",
    "print(events_df.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "replace condition with trial_type\n",
    "---------------------------------\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    onset  duration correct trial_type  response_time\n",
      "0   0.342         1       Y    neutral          1.186\n",
      "1   3.345         1       Y  congruent          0.667\n",
      "2  12.346         1       Y  congruent          0.614\n",
      "3  15.349         1       Y    neutral          0.696\n",
      "4  18.350         1       Y    neutral          0.752\n"
     ]
    }
   ],
   "source": [
    "events_df.rename({\"condition\": \"trial_type\"}, axis='columns', inplace=True)\n",
    "print(events_df.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "save the file\n",
    "-------------\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "events_df.to_csv(events_file, sep=\"\\t\", na_rep=\"n/a\", index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Manipulate the region order file\n",
    "================================\n",
    "There are several adjustments to the atlas file that need to be completed\n",
    "before we can pass it into nibs.\n",
    "Importantly, the relevant column names **MUST** be named \"index\" and \"regions\".\n",
    "\"index\" refers to which integer within the file corresponds to which region\n",
    "in the atlas nifti file.\n",
    "\"regions\" refers the name of each region in the atlas nifti file.\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "read the atlas file\n",
    "-------------------\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   0                   1    2   3    4  5\n",
      "0  1  7Networks_LH_Vis_1  120  18  131  0\n",
      "1  2  7Networks_LH_Vis_2  120  18  132  0\n",
      "2  3  7Networks_LH_Vis_3  120  18  133  0\n",
      "3  4  7Networks_LH_Vis_4  120  18  135  0\n",
      "4  5  7Networks_LH_Vis_5  120  18  136  0\n"
     ]
    }
   ],
   "source": [
    "atlas_txt = os.path.join(data_dir,\n",
    "                         \"ds000164\",\n",
    "                         \"derivatives\",\n",
    "                         \"data\",\n",
    "                         \"Schaefer2018_100Parcels_7Networks_order.txt\")\n",
    "atlas_df = pd.read_csv(atlas_txt, sep=\"\\t\", header=None)\n",
    "print(atlas_df.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "drop color coding columns\n",
    "-------------------------\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   0                   1\n",
      "0  1  7Networks_LH_Vis_1\n",
      "1  2  7Networks_LH_Vis_2\n",
      "2  3  7Networks_LH_Vis_3\n",
      "3  4  7Networks_LH_Vis_4\n",
      "4  5  7Networks_LH_Vis_5\n"
     ]
    }
   ],
   "source": [
    "atlas_df.drop([2, 3, 4, 5], axis='columns', inplace=True)\n",
    "print(atlas_df.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "rename columns with the approved headings: \"index\" and \"regions\"\n",
    "----------------------------------------------------------------\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   index             regions\n",
      "0      1  7Networks_LH_Vis_1\n",
      "1      2  7Networks_LH_Vis_2\n",
      "2      3  7Networks_LH_Vis_3\n",
      "3      4  7Networks_LH_Vis_4\n",
      "4      5  7Networks_LH_Vis_5\n"
     ]
    }
   ],
   "source": [
    "atlas_df.rename({0: 'index', 1: 'regions'}, axis='columns', inplace=True)\n",
    "print(atlas_df.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "remove prefix \"7Networks\"\n",
    "-------------------------\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   index   regions\n",
      "0      1  LH_Vis_1\n",
      "1      2  LH_Vis_2\n",
      "2      3  LH_Vis_3\n",
      "3      4  LH_Vis_4\n",
      "4      5  LH_Vis_5\n"
     ]
    }
   ],
   "source": [
    "atlas_df.replace(regex={'7Networks_(.*)': '\\\\1'}, inplace=True)\n",
    "print(atlas_df.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "write out the file as .tsv\n",
    "--------------------------\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "atlas_tsv = atlas_txt.replace(\".txt\", \".tsv\")\n",
    "atlas_df.to_csv(atlas_tsv, sep=\"\\t\", index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Run nibs\n",
    "========\n",
    "This demonstration mimics how you would use nibs on the command line\n",
    "If you only wanted the beta maps and not the correlation matrices, do not\n",
    "include the atlas (-a) and lookup table options (-l)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "import subprocess\n",
    "from subprocess import Popen, PIPE, STDOUT  # enable calling commandline\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The Example Command:\n",
      " nibs -c WhiteMatter CSF --participant-label 001 --estimator lsa --hrf-model glover -w /tmp/tmpabo1ms7h/ds000164/derivatives/work -a /tmp/tmpabo1ms7h/ds000164/derivatives/data/Schaefer2018_100Parcels_7Networks_order_FSLMNI152_2mm.nii.gz -l /tmp/tmpabo1ms7h/ds000164/derivatives/data/Schaefer2018_100Parcels_7Networks_order.tsv /tmp/tmpabo1ms7h/ds000164 fmriprep /tmp/tmpabo1ms7h/ds000164/derivatives participant\n",
      "\n",
      "b'200611-15:05:50,81 nipype.utils INFO:\\n'\n",
      "b'\\t Running nipype version 1.4.2 (latest: 1.5.0)\\n'\n",
      "b\"/home/lily/.local/lib/python3.6/site-packages/bids/layout/models.py:157: UserWarning: Accessing entities as attributes is deprecated as of 0.7. Please use the .entities dictionary instead (i.e., .entities['task'] instead of .task.\\n\"\n",
      "b'  % (attr, attr))\\n'\n",
      "b\"/home/lily/.local/lib/python3.6/site-packages/bids/layout/models.py:157: UserWarning: Accessing entities as attributes is deprecated as of 0.7. Please use the .entities dictionary instead (i.e., .entities['space'] instead of .space.\\n\"\n",
      "b'  % (attr, attr))\\n'\n",
      "b'200611-15:05:50,589 nipype.workflow INFO:\\n'\n",
      "b\"\\t Workflow nibetaseries_participant_wf settings: ['check', 'execution', 'logging', 'monitoring']\\n\"\n",
      "b'200611-15:05:50,610 nipype.workflow INFO:\\n'\n",
      "b'\\t Running in parallel.\\n'\n",
      "b'200611-15:05:50,617 nipype.workflow INFO:\\n'\n",
      "b'\\t [MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 226.69/226.69, Free processors: 32/32.\\n'\n",
      "b'200611-15:05:50,700 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"nibetaseries_participant_wf.single_subject001_wf.betaseries_wf.betaseries_node\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/betaseries_wf/925968acad4677cdf87bd74827c135468f16a99e/betaseries_node\".\\n'\n",
      "b'200611-15:05:50,711 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Running \"betaseries_node\" (\"nibetaseries.interfaces.nistats.LSABetaSeries\")\\n'\n",
      "b'200611-15:05:52,617 nipype.workflow INFO:\\n'\n",
      "b'\\t [MultiProc] Running 1 tasks, and 0 jobs ready. Free memory (GB): 226.49/226.69, Free processors: 31/32.\\n'\n",
      "b'                     Currently running:\\n'\n",
      "b'                       * nibetaseries_participant_wf.single_subject001_wf.betaseries_wf.betaseries_node\\n'\n",
      "b'200611-15:06:03,183 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Finished \"nibetaseries_participant_wf.single_subject001_wf.betaseries_wf.betaseries_node\".\\n'\n",
      "b'200611-15:06:04,630 nipype.workflow INFO:\\n'\n",
      "b'\\t [Job 0] Completed (nibetaseries_participant_wf.single_subject001_wf.betaseries_wf.betaseries_node).\\n'\n",
      "b'200611-15:06:04,636 nipype.workflow INFO:\\n'\n",
      "b'\\t [MultiProc] Running 0 tasks, and 2 jobs ready. Free memory (GB): 226.69/226.69, Free processors: 32/32.\\n'\n",
      "b'200611-15:06:06,635 nipype.workflow INFO:\\n'\n",
      "b'\\t [MultiProc] Running 0 tasks, and 6 jobs ready. Free memory (GB): 226.69/226.69, Free processors: 32/32.\\n'\n",
      "b'200611-15:06:06,704 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"_ds_betaseries_file0\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/925968acad4677cdf87bd74827c135468f16a99e/ds_betaseries_file/mapflow/_ds_betaseries_file0\".\\n'\n",
      "b'200611-15:06:06,706 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"_ds_betaseries_file1\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/925968acad4677cdf87bd74827c135468f16a99e/ds_betaseries_file/mapflow/_ds_betaseries_file1\".\\n'\n",
      "b'200611-15:06:06,708 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"_censor_volumes0\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/925968acad4677cdf87bd74827c135468f16a99e/censor_volumes/mapflow/_censor_volumes0\".\\n'\n",
      "b'200611-15:06:06,708 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"_ds_betaseries_file2\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/925968acad4677cdf87bd74827c135468f16a99e/ds_betaseries_file/mapflow/_ds_betaseries_file2\".\\n'\n",
      "b'200611-15:06:06,709 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Running \"_ds_betaseries_file0\" (\"nibetaseries.interfaces.bids.DerivativesDataSink\")\\n'\n",
      "b'200611-15:06:06,710 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"_censor_volumes2\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/925968acad4677cdf87bd74827c135468f16a99e/censor_volumes/mapflow/_censor_volumes2\".\\n'\n",
      "b'200611-15:06:06,711 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"_censor_volumes1\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/925968acad4677cdf87bd74827c135468f16a99e/censor_volumes/mapflow/_censor_volumes1\".\\n'\n",
      "b'200611-15:06:06,712 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Running \"_ds_betaseries_file1\" (\"nibetaseries.interfaces.bids.DerivativesDataSink\")\\n'\n",
      "b'200611-15:06:06,713 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Running \"_censor_volumes0\" (\"nibetaseries.interfaces.nilearn.CensorVolumes\")\\n'\n",
      "b'200611-15:06:06,715 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Running \"_censor_volumes2\" (\"nibetaseries.interfaces.nilearn.CensorVolumes\")\\n'\n",
      "b'200611-15:06:06,717 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Running \"_ds_betaseries_file2\" (\"nibetaseries.interfaces.bids.DerivativesDataSink\")\\n'\n",
      "b'200611-15:06:06,718 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Running \"_censor_volumes1\" (\"nibetaseries.interfaces.nilearn.CensorVolumes\")\\n'\n",
      "b'200611-15:06:06,731 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Finished \"_ds_betaseries_file0\".\\n'\n",
      "b'200611-15:06:06,736 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Finished \"_ds_betaseries_file2\".\\n'\n",
      "b'200611-15:06:06,742 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Finished \"_ds_betaseries_file1\".\\n'\n",
      "b'200611-15:06:06,781 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Finished \"_censor_volumes2\".\\n'\n",
      "b'200611-15:06:06,788 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Finished \"_censor_volumes0\".\\n'\n",
      "b'200611-15:06:06,800 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Finished \"_censor_volumes1\".\\n'\n",
      "b'200611-15:06:08,635 nipype.workflow INFO:\\n'\n",
      "b'\\t [Job 7] Completed (_ds_betaseries_file0).\\n'\n",
      "b'200611-15:06:08,637 nipype.workflow INFO:\\n'\n",
      "b'\\t [Job 8] Completed (_ds_betaseries_file1).\\n'\n",
      "b'200611-15:06:08,639 nipype.workflow INFO:\\n'\n",
      "b'\\t [Job 9] Completed (_ds_betaseries_file2).\\n'\n",
      "b'200611-15:06:08,641 nipype.workflow INFO:\\n'\n",
      "b'\\t [Job 10] Completed (_censor_volumes0).\\n'\n",
      "b'200611-15:06:08,643 nipype.workflow INFO:\\n'\n",
      "b'\\t [Job 11] Completed (_censor_volumes1).\\n'\n",
      "b'200611-15:06:08,644 nipype.workflow INFO:\\n'\n",
      "b'\\t [Job 12] Completed (_censor_volumes2).\\n'\n",
      "b'200611-15:06:08,646 nipype.workflow INFO:\\n'\n",
      "b'\\t [MultiProc] Running 0 tasks, and 2 jobs ready. Free memory (GB): 226.69/226.69, Free processors: 32/32.\\n'\n",
      "b'200611-15:06:08,715 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"nibetaseries_participant_wf.single_subject001_wf.ds_betaseries_file\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/925968acad4677cdf87bd74827c135468f16a99e/ds_betaseries_file\".\\n'\n",
      "b'200611-15:06:08,717 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"nibetaseries_participant_wf.single_subject001_wf.censor_volumes\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/925968acad4677cdf87bd74827c135468f16a99e/censor_volumes\".\\n'\n",
      "b'200611-15:06:08,730 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"_ds_betaseries_file0\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/925968acad4677cdf87bd74827c135468f16a99e/ds_betaseries_file/mapflow/_ds_betaseries_file0\".\\n'\n",
      "b'200611-15:06:08,730 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"_censor_volumes0\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/925968acad4677cdf87bd74827c135468f16a99e/censor_volumes/mapflow/_censor_volumes0\".\\n'\n",
      "b'200611-15:06:08,733 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Running \"_ds_betaseries_file0\" (\"nibetaseries.interfaces.bids.DerivativesDataSink\")\\n'\n",
      "b'200611-15:06:08,732 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Cached \"_censor_volumes0\" - collecting precomputed outputs\\n'\n",
      "b'200611-15:06:08,735 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] \"_censor_volumes0\" found cached.\\n'\n",
      "b'200611-15:06:08,736 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"_censor_volumes1\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/925968acad4677cdf87bd74827c135468f16a99e/censor_volumes/mapflow/_censor_volumes1\".\\n'\n",
      "b'200611-15:06:08,737 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Cached \"_censor_volumes1\" - collecting precomputed outputs\\n'\n",
      "b'200611-15:06:08,737 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] \"_censor_volumes1\" found cached.\\n'\n",
      "b'200611-15:06:08,738 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"_censor_volumes2\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/925968acad4677cdf87bd74827c135468f16a99e/censor_volumes/mapflow/_censor_volumes2\".\\n'\n",
      "b'200611-15:06:08,739 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Cached \"_censor_volumes2\" - collecting precomputed outputs\\n'\n",
      "b'200611-15:06:08,739 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] \"_censor_volumes2\" found cached.\\n'\n",
      "b'200611-15:06:08,742 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Finished \"nibetaseries_participant_wf.single_subject001_wf.censor_volumes\".\\n'\n",
      "b'200611-15:06:08,752 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Finished \"_ds_betaseries_file0\".\\n'\n",
      "b'200611-15:06:08,756 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"_ds_betaseries_file1\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/925968acad4677cdf87bd74827c135468f16a99e/ds_betaseries_file/mapflow/_ds_betaseries_file1\".\\n'\n",
      "b'200611-15:06:08,758 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Running \"_ds_betaseries_file1\" (\"nibetaseries.interfaces.bids.DerivativesDataSink\")\\n'\n",
      "b'200611-15:06:08,771 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Finished \"_ds_betaseries_file1\".\\n'\n",
      "b'200611-15:06:08,772 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"_ds_betaseries_file2\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/925968acad4677cdf87bd74827c135468f16a99e/ds_betaseries_file/mapflow/_ds_betaseries_file2\".\\n'\n",
      "b'200611-15:06:08,775 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Running \"_ds_betaseries_file2\" (\"nibetaseries.interfaces.bids.DerivativesDataSink\")\\n'\n",
      "b'200611-15:06:08,793 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Finished \"_ds_betaseries_file2\".\\n'\n",
      "b'200611-15:06:08,797 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Finished \"nibetaseries_participant_wf.single_subject001_wf.ds_betaseries_file\".\\n'\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "b'200611-15:06:10,636 nipype.workflow INFO:\\n'\n",
      "b'\\t [Job 1] Completed (nibetaseries_participant_wf.single_subject001_wf.ds_betaseries_file).\\n'\n",
      "b'200611-15:06:10,638 nipype.workflow INFO:\\n'\n",
      "b'\\t [Job 2] Completed (nibetaseries_participant_wf.single_subject001_wf.censor_volumes).\\n'\n",
      "b'200611-15:06:10,640 nipype.workflow INFO:\\n'\n",
      "b'\\t [MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 226.69/226.69, Free processors: 32/32.\\n'\n",
      "b'200611-15:06:10,706 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"nibetaseries_participant_wf.single_subject001_wf.check_beta_series_list\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/925968acad4677cdf87bd74827c135468f16a99e/check_beta_series_list\".\\n'\n",
      "b'200611-15:06:10,715 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Running \"check_beta_series_list\" (\"nipype.interfaces.utility.wrappers.Function\")\\n'\n",
      "b'200611-15:06:10,729 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Finished \"nibetaseries_participant_wf.single_subject001_wf.check_beta_series_list\".\\n'\n",
      "b'200611-15:06:12,639 nipype.workflow INFO:\\n'\n",
      "b'\\t [Job 3] Completed (nibetaseries_participant_wf.single_subject001_wf.check_beta_series_list).\\n'\n",
      "b'200611-15:06:12,642 nipype.workflow INFO:\\n'\n",
      "b'\\t [MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 226.69/226.69, Free processors: 32/32.\\n'\n",
      "b'200611-15:06:14,643 nipype.workflow INFO:\\n'\n",
      "b'\\t [MultiProc] Running 0 tasks, and 3 jobs ready. Free memory (GB): 226.69/226.69, Free processors: 32/32.\\n'\n",
      "b'200611-15:06:14,714 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"_atlas_corr_node0\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/correlation_wf/925968acad4677cdf87bd74827c135468f16a99e/atlas_corr_node/mapflow/_atlas_corr_node0\".\\n'\n",
      "b'200611-15:06:14,715 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"_atlas_corr_node1\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/correlation_wf/925968acad4677cdf87bd74827c135468f16a99e/atlas_corr_node/mapflow/_atlas_corr_node1\".\\n'\n",
      "b'200611-15:06:14,716 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"_atlas_corr_node2\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/correlation_wf/925968acad4677cdf87bd74827c135468f16a99e/atlas_corr_node/mapflow/_atlas_corr_node2\".\\n'\n",
      "b'200611-15:06:14,719 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Running \"_atlas_corr_node0\" (\"nibetaseries.interfaces.nilearn.AtlasConnectivity\")\\n'\n",
      "b'200611-15:06:14,720 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Running \"_atlas_corr_node1\" (\"nibetaseries.interfaces.nilearn.AtlasConnectivity\")\\n'\n",
      "b'200611-15:06:14,721 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Running \"_atlas_corr_node2\" (\"nibetaseries.interfaces.nilearn.AtlasConnectivity\")\\n'\n",
      "b'200611-15:06:16,642 nipype.workflow INFO:\\n'\n",
      "b'\\t [MultiProc] Running 3 tasks, and 0 jobs ready. Free memory (GB): 226.09/226.69, Free processors: 29/32.\\n'\n",
      "b'                     Currently running:\\n'\n",
      "b'                       * _atlas_corr_node2\\n'\n",
      "b'                       * _atlas_corr_node1\\n'\n",
      "b'                       * _atlas_corr_node0\\n'\n",
      "b'[NiftiLabelsMasker.fit_transform] loading data from /tmp/tmpabo1ms7h/ds000164/derivatives/data/Schaefer2018_100Parcels_7Networks_order_FSLMNI152_2mm.nii.gz\\n'\n",
      "b'Resampling labels\\n'\n",
      "b'[NiftiLabelsMasker.transform_single_imgs] Loading data from /tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/betaseries_wf/925968acad4677cdf87bd74827c135468f16a99e/betaseries_node/desc-neutral_betase\\n'\n",
      "b'[NiftiLabelsMasker.transform_single_imgs] Extracting region signals\\n'\n",
      "b'[NiftiLabelsMasker.transform_single_imgs] Cleaning extracted signals\\n'\n",
      "b'200611-15:06:22,988 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Finished \"_atlas_corr_node0\".\\n'\n",
      "b'[NiftiLabelsMasker.fit_transform] loading data from /tmp/tmpabo1ms7h/ds000164/derivatives/data/Schaefer2018_100Parcels_7Networks_order_FSLMNI152_2mm.nii.gz\\n'\n",
      "b'Resampling labels\\n'\n",
      "b'[NiftiLabelsMasker.transform_single_imgs] Loading data from /tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/betaseries_wf/925968acad4677cdf87bd74827c135468f16a99e/betaseries_node/desc-incongruent_be\\n'\n",
      "b'[NiftiLabelsMasker.transform_single_imgs] Extracting region signals\\n'\n",
      "b'[NiftiLabelsMasker.transform_single_imgs] Cleaning extracted signals\\n'\n",
      "b'200611-15:06:23,503 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Finished \"_atlas_corr_node2\".\\n'\n",
      "b'[NiftiLabelsMasker.fit_transform] loading data from /tmp/tmpabo1ms7h/ds000164/derivatives/data/Schaefer2018_100Parcels_7Networks_order_FSLMNI152_2mm.nii.gz\\n'\n",
      "b'Resampling labels\\n'\n",
      "b'[NiftiLabelsMasker.transform_single_imgs] Loading data from /tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/betaseries_wf/925968acad4677cdf87bd74827c135468f16a99e/betaseries_node/desc-congruent_beta\\n'\n",
      "b'[NiftiLabelsMasker.transform_single_imgs] Extracting region signals\\n'\n",
      "b'[NiftiLabelsMasker.transform_single_imgs] Cleaning extracted signals\\n'\n",
      "b'200611-15:06:23,835 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Finished \"_atlas_corr_node1\".\\n'\n",
      "b'200611-15:06:24,650 nipype.workflow INFO:\\n'\n",
      "b'\\t [Job 13] Completed (_atlas_corr_node0).\\n'\n",
      "b'200611-15:06:24,651 nipype.workflow INFO:\\n'\n",
      "b'\\t [Job 14] Completed (_atlas_corr_node1).\\n'\n",
      "b'200611-15:06:24,652 nipype.workflow INFO:\\n'\n",
      "b'\\t [Job 15] Completed (_atlas_corr_node2).\\n'\n",
      "b'200611-15:06:24,654 nipype.workflow INFO:\\n'\n",
      "b'\\t [MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 226.69/226.69, Free processors: 32/32.\\n'\n",
      "b'200611-15:06:24,724 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"nibetaseries_participant_wf.single_subject001_wf.correlation_wf.atlas_corr_node\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/correlation_wf/925968acad4677cdf87bd74827c135468f16a99e/atlas_corr_node\".\\n'\n",
      "b'200611-15:06:24,735 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"_atlas_corr_node0\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/correlation_wf/925968acad4677cdf87bd74827c135468f16a99e/atlas_corr_node/mapflow/_atlas_corr_node0\".\\n'\n",
      "b'200611-15:06:24,738 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Cached \"_atlas_corr_node0\" - collecting precomputed outputs\\n'\n",
      "b'200611-15:06:24,741 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] \"_atlas_corr_node0\" found cached.\\n'\n",
      "b'200611-15:06:24,742 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"_atlas_corr_node1\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/correlation_wf/925968acad4677cdf87bd74827c135468f16a99e/atlas_corr_node/mapflow/_atlas_corr_node1\".\\n'\n",
      "b'200611-15:06:24,743 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Cached \"_atlas_corr_node1\" - collecting precomputed outputs\\n'\n",
      "b'200611-15:06:24,743 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] \"_atlas_corr_node1\" found cached.\\n'\n",
      "b'200611-15:06:24,745 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"_atlas_corr_node2\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/correlation_wf/925968acad4677cdf87bd74827c135468f16a99e/atlas_corr_node/mapflow/_atlas_corr_node2\".\\n'\n",
      "b'200611-15:06:24,746 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Cached \"_atlas_corr_node2\" - collecting precomputed outputs\\n'\n",
      "b'200611-15:06:24,746 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] \"_atlas_corr_node2\" found cached.\\n'\n",
      "b'200611-15:06:24,749 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Finished \"nibetaseries_participant_wf.single_subject001_wf.correlation_wf.atlas_corr_node\".\\n'\n",
      "b'200611-15:06:26,652 nipype.workflow INFO:\\n'\n",
      "b'\\t [Job 4] Completed (nibetaseries_participant_wf.single_subject001_wf.correlation_wf.atlas_corr_node).\\n'\n",
      "b'200611-15:06:26,655 nipype.workflow INFO:\\n'\n",
      "b'\\t [MultiProc] Running 0 tasks, and 2 jobs ready. Free memory (GB): 226.69/226.69, Free processors: 32/32.\\n'\n",
      "b'200611-15:06:28,657 nipype.workflow INFO:\\n'\n",
      "b'\\t [MultiProc] Running 0 tasks, and 6 jobs ready. Free memory (GB): 226.69/226.69, Free processors: 32/32.\\n'\n",
      "b'200611-15:06:28,728 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"_ds_correlation_fig1\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/925968acad4677cdf87bd74827c135468f16a99e/ds_correlation_fig/mapflow/_ds_correlation_fig1\".\\n'\n",
      "b'200611-15:06:28,728 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"_ds_correlation_fig0\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/925968acad4677cdf87bd74827c135468f16a99e/ds_correlation_fig/mapflow/_ds_correlation_fig0\".\\n'\n",
      "b'200611-15:06:28,730 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"_ds_correlation_fig2\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/925968acad4677cdf87bd74827c135468f16a99e/ds_correlation_fig/mapflow/_ds_correlation_fig2\".\\n'\n",
      "b'200611-15:06:28,732 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"_ds_correlation_matrix0\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/925968acad4677cdf87bd74827c135468f16a99e/ds_correlation_matrix/mapflow/_ds_correlation_matrix0\".\\n'\n",
      "b'200611-15:06:28,733 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"_ds_correlation_matrix1\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/925968acad4677cdf87bd74827c135468f16a99e/ds_correlation_matrix/mapflow/_ds_correlation_matrix1\".\\n'\n",
      "b'200611-15:06:28,735 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"_ds_correlation_matrix2\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/925968acad4677cdf87bd74827c135468f16a99e/ds_correlation_matrix/mapflow/_ds_correlation_matrix2\".\\n'\n",
      "b'200611-15:06:28,740 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Running \"_ds_correlation_fig1\" (\"nibetaseries.interfaces.bids.DerivativesDataSink\")\\n'\n",
      "b'200611-15:06:28,740 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Running \"_ds_correlation_matrix2\" (\"nibetaseries.interfaces.bids.DerivativesDataSink\")\\n'\n",
      "b'200611-15:06:28,740 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Running \"_ds_correlation_matrix1\" (\"nibetaseries.interfaces.bids.DerivativesDataSink\")\\n'\n",
      "b'200611-15:06:28,740 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Running \"_ds_correlation_fig0\" (\"nibetaseries.interfaces.bids.DerivativesDataSink\")\\n'\n",
      "b'200611-15:06:28,740 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Running \"_ds_correlation_matrix0\" (\"nibetaseries.interfaces.bids.DerivativesDataSink\")\\n'\n",
      "b'200611-15:06:28,741 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Running \"_ds_correlation_fig2\" (\"nibetaseries.interfaces.bids.DerivativesDataSink\")\\n'\n",
      "b'200611-15:06:28,760 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Finished \"_ds_correlation_matrix2\".\\n'\n",
      "b'200611-15:06:28,760 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Finished \"_ds_correlation_matrix0\".\\n'\n",
      "b'200611-15:06:28,760 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Finished \"_ds_correlation_matrix1\".\\n'\n",
      "b'200611-15:06:28,762 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Finished \"_ds_correlation_fig0\".\\n'\n",
      "b'200611-15:06:28,762 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Finished \"_ds_correlation_fig2\".\\n'\n",
      "b'200611-15:06:28,762 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Finished \"_ds_correlation_fig1\".\\n'\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "b'200611-15:06:30,657 nipype.workflow INFO:\\n'\n",
      "b'\\t [Job 16] Completed (_ds_correlation_fig0).\\n'\n",
      "b'200611-15:06:30,659 nipype.workflow INFO:\\n'\n",
      "b'\\t [Job 17] Completed (_ds_correlation_fig1).\\n'\n",
      "b'200611-15:06:30,660 nipype.workflow INFO:\\n'\n",
      "b'\\t [Job 18] Completed (_ds_correlation_fig2).\\n'\n",
      "b'200611-15:06:30,661 nipype.workflow INFO:\\n'\n",
      "b'\\t [Job 19] Completed (_ds_correlation_matrix0).\\n'\n",
      "b'200611-15:06:30,663 nipype.workflow INFO:\\n'\n",
      "b'\\t [Job 20] Completed (_ds_correlation_matrix1).\\n'\n",
      "b'200611-15:06:30,664 nipype.workflow INFO:\\n'\n",
      "b'\\t [Job 21] Completed (_ds_correlation_matrix2).\\n'\n",
      "b'200611-15:06:30,667 nipype.workflow INFO:\\n'\n",
      "b'\\t [MultiProc] Running 0 tasks, and 2 jobs ready. Free memory (GB): 226.69/226.69, Free processors: 32/32.\\n'\n",
      "b'200611-15:06:30,738 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"nibetaseries_participant_wf.single_subject001_wf.ds_correlation_fig\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/925968acad4677cdf87bd74827c135468f16a99e/ds_correlation_fig\".\\n'\n",
      "b'200611-15:06:30,738 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"nibetaseries_participant_wf.single_subject001_wf.ds_correlation_matrix\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/925968acad4677cdf87bd74827c135468f16a99e/ds_correlation_matrix\".\\n'\n",
      "b'200611-15:06:30,750 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"_ds_correlation_matrix0\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/925968acad4677cdf87bd74827c135468f16a99e/ds_correlation_matrix/mapflow/_ds_correlation_matrix0\".\\n'\n",
      "b'200611-15:06:30,750 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"_ds_correlation_fig0\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/925968acad4677cdf87bd74827c135468f16a99e/ds_correlation_fig/mapflow/_ds_correlation_fig0\".\\n'\n",
      "b'200611-15:06:30,753 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Running \"_ds_correlation_fig0\" (\"nibetaseries.interfaces.bids.DerivativesDataSink\")\\n'\n",
      "b'200611-15:06:30,753 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Running \"_ds_correlation_matrix0\" (\"nibetaseries.interfaces.bids.DerivativesDataSink\")\\n'\n",
      "b'200611-15:06:30,771 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Finished \"_ds_correlation_matrix0\".\\n'\n",
      "b'200611-15:06:30,775 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"_ds_correlation_matrix1\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/925968acad4677cdf87bd74827c135468f16a99e/ds_correlation_matrix/mapflow/_ds_correlation_matrix1\".\\n'\n",
      "b'200611-15:06:30,774 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Finished \"_ds_correlation_fig0\".\\n'\n",
      "b'200611-15:06:30,778 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Running \"_ds_correlation_matrix1\" (\"nibetaseries.interfaces.bids.DerivativesDataSink\")\\n'\n",
      "b'200611-15:06:30,778 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"_ds_correlation_fig1\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/925968acad4677cdf87bd74827c135468f16a99e/ds_correlation_fig/mapflow/_ds_correlation_fig1\".\\n'\n",
      "b'200611-15:06:30,780 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Running \"_ds_correlation_fig1\" (\"nibetaseries.interfaces.bids.DerivativesDataSink\")\\n'\n",
      "b'200611-15:06:30,790 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Finished \"_ds_correlation_matrix1\".\\n'\n",
      "b'200611-15:06:30,791 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"_ds_correlation_matrix2\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/925968acad4677cdf87bd74827c135468f16a99e/ds_correlation_matrix/mapflow/_ds_correlation_matrix2\".\\n'\n",
      "b'200611-15:06:30,793 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Running \"_ds_correlation_matrix2\" (\"nibetaseries.interfaces.bids.DerivativesDataSink\")\\n'\n",
      "b'200611-15:06:30,797 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Finished \"_ds_correlation_fig1\".\\n'\n",
      "b'200611-15:06:30,798 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Setting-up \"_ds_correlation_fig2\" in \"/tmp/tmpabo1ms7h/ds000164/derivatives/work/NiBetaSeries_work/nibetaseries_participant_wf/single_subject001_wf/925968acad4677cdf87bd74827c135468f16a99e/ds_correlation_fig/mapflow/_ds_correlation_fig2\".\\n'\n",
      "b'200611-15:06:30,800 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Running \"_ds_correlation_fig2\" (\"nibetaseries.interfaces.bids.DerivativesDataSink\")\\n'\n",
      "b'200611-15:06:30,805 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Finished \"_ds_correlation_matrix2\".\\n'\n",
      "b'200611-15:06:30,808 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Finished \"nibetaseries_participant_wf.single_subject001_wf.ds_correlation_matrix\".\\n'\n",
      "b'200611-15:06:30,816 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Finished \"_ds_correlation_fig2\".\\n'\n",
      "b'200611-15:06:30,819 nipype.workflow INFO:\\n'\n",
      "b'\\t [Node] Finished \"nibetaseries_participant_wf.single_subject001_wf.ds_correlation_fig\".\\n'\n",
      "b'200611-15:06:32,659 nipype.workflow INFO:\\n'\n",
      "b'\\t [Job 5] Completed (nibetaseries_participant_wf.single_subject001_wf.ds_correlation_fig).\\n'\n",
      "b'200611-15:06:32,662 nipype.workflow INFO:\\n'\n",
      "b'\\t [Job 6] Completed (nibetaseries_participant_wf.single_subject001_wf.ds_correlation_matrix).\\n'\n",
      "b'200611-15:06:32,666 nipype.workflow INFO:\\n'\n",
      "b'\\t [MultiProc] Running 0 tasks, and 0 jobs ready. Free memory (GB): 226.69/226.69, Free processors: 32/32.\\n'\n",
      "b'/home/lily/.local/lib/python3.6/site-packages/nibetaseries/interfaces/nistats.py:216: DeprecationWarning: The parameter \"mask\" will be removed in next release of Nistats. Please use the parameter \"mask_img\" instead.\\n'\n",
      "b'  minimize_memory=False,\\n'\n",
      "b'Computing run 1 out of 1 runs (go take a coffee, a big one)\\n'\n",
      "b'\\n'\n",
      "b'Computation of 1 runs done in 10 seconds\\n'\n",
      "b'\\n'\n",
      "b\"/home/lily/.local/lib/python3.6/site-packages/nistats/regression.py:339: FutureWarning: 'resid' from RegressionResults has been deprecated and will be removed. Please use 'residuals' instead.\\n\"\n",
      "b'  FutureWarning,\\n'\n",
      "b'/home/lily/.local/lib/python3.6/site-packages/nibetaseries/interfaces/nilearn.py:130: RuntimeWarning: invalid value encountered in greater\\n'\n",
      "b'  n_lines = int(np.sum(connmat > 0) / 2)\\n'\n",
      "b'/home/lily/.local/lib/python3.6/site-packages/nibetaseries/interfaces/nilearn.py:130: RuntimeWarning: invalid value encountered in greater\\n'\n",
      "b'  n_lines = int(np.sum(connmat > 0) / 2)\\n'\n",
      "b'/home/lily/.local/lib/python3.6/site-packages/nibetaseries/interfaces/nilearn.py:130: RuntimeWarning: invalid value encountered in greater\\n'\n",
      "b'  n_lines = int(np.sum(connmat > 0) / 2)\\n'\n"
     ]
    }
   ],
   "source": [
    "out_dir = os.path.join(data_dir, \"ds000164\", \"derivatives\")\n",
    "work_dir = os.path.join(out_dir, \"work\")\n",
    "atlas_mni_file = os.path.join(data_dir,\n",
    "                              \"ds000164\",\n",
    "                              \"derivatives\",\n",
    "                              \"data\",\n",
    "                              \"Schaefer2018_100Parcels_7Networks_order_FSLMNI152_2mm.nii.gz\")\n",
    "cmd = \"\"\"\\\n",
    "nibs -c WhiteMatter CSF \\\n",
    "--participant-label 001 \\\n",
    "--estimator lsa \\\n",
    "--hrf-model glover \\\n",
    "-w {work_dir} \\\n",
    "-a {atlas_mni_file} \\\n",
    "-l {atlas_tsv} \\\n",
    "{bids_dir} \\\n",
    "fmriprep \\\n",
    "{out_dir} \\\n",
    "participant\n",
    "\"\"\".format(atlas_mni_file=atlas_mni_file,\n",
    "           atlas_tsv=atlas_tsv,\n",
    "           bids_dir=os.path.join(data_dir, \"ds000164\"),\n",
    "           out_dir=out_dir,\n",
    "           work_dir=work_dir)\n",
    "\n",
    "# Since we cannot run bash commands inside this tutorial\n",
    "# we are printing the actual bash command so you can see it\n",
    "# in the output\n",
    "print(\"The Example Command:\\n\", cmd)\n",
    "\n",
    "# call nibs\n",
    "p = Popen(cmd, shell=True, stdout=PIPE, stderr=STDOUT)\n",
    "\n",
    "while True:\n",
    "    line = p.stdout.readline()\n",
    "    if not line:\n",
    "        break\n",
    "    print(line)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Observe generated outputs\n",
    "=========================\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tmpabo1ms7h/\n",
      "    ds000164/\n",
      "        dataset_description.json\n",
      "        task-stroop_events.json\n",
      "        task-stroop_bold.json\n",
      "        T1w.json\n",
      "        README\n",
      "        CHANGES\n",
      "        derivatives/\n",
      "            fmriprep/\n",
      "                dataset_description.json\n",
      "                fMRIPrep.sqlite\n",
      "                sub-001/\n",
      "                    func/\n",
      "                        sub-001_task-stroop_desc-confounds_regressors.tsv\n",
      "                        sub-001_task-stroop_space-MNI152NLin2009cAsym_desc-preproc_bold.nii.gz\n",
      "                        sub-001_task-stroop_space-MNI152NLin2009cAsym_desc-brain_mask.nii.gz\n",
      "            data/\n",
      "                Schaefer2018_100Parcels_7Networks_order.txt\n",
      "                Schaefer2018_100Parcels_7Networks_order.tsv\n",
      "                Schaefer2018_100Parcels_7Networks_order_FSLMNI152_2mm.nii.gz\n",
      "            work/\n",
      "                dbcache\n",
      "                NiBetaSeries_work/\n",
      "                    nibetaseries_participant_wf/\n",
      "                        graph1.json\n",
      "                        index.html\n",
      "                        graph.json\n",
      "                        d3.js\n",
      "                        single_subject001_wf/\n",
      "                            betaseries_wf/\n",
      "                                925968acad4677cdf87bd74827c135468f16a99e/\n",
      "                                    betaseries_node/\n",
      "                                        desc-residuals_bold.nii.gz\n",
      "                                        desc-congruent_betaseries_censored.nii.gz\n",
      "                                        _inputs.pklz\n",
      "                                        desc-incongruent_betaseries_censored.nii.gz\n",
      "                                        result_betaseries_node.pklz\n",
      "                                        _node.pklz\n",
      "                                        desc-neutral_betaseries.nii.gz\n",
      "                                        desc-incongruent_betaseries.nii.gz\n",
      "                                        desc-congruent_betaseries.nii.gz\n",
      "                                        _0xb1da39d6210c8d2a0c7b1174598dba66.json\n",
      "                                        desc-neutral_betaseries_censored.nii.gz\n",
      "                                        _report/\n",
      "                                            report.rst\n",
      "                            correlation_wf/\n",
      "                                925968acad4677cdf87bd74827c135468f16a99e/\n",
      "                                    atlas_corr_node/\n",
      "                                        _inputs.pklz\n",
      "                                        _0x7eda21d9201c393c24c1112de16d5a13.json\n",
      "                                        _node.pklz\n",
      "                                        result_atlas_corr_node.pklz\n",
      "                                        mapflow/\n",
      "                                            _atlas_corr_node2/\n",
      "                                                result__atlas_corr_node2.pklz\n",
      "                                                desc-incongruent_correlation.svg\n",
      "                                                _inputs.pklz\n",
      "                                                _0x9f3ec7224be713ca0151e7addb8e69f7.json\n",
      "                                                _node.pklz\n",
      "                                                desc-incongruent_correlation.tsv\n",
      "                                                _report/\n",
      "                                                    report.rst\n",
      "                                            _atlas_corr_node1/\n",
      "                                                desc-congruent_correlation.tsv\n",
      "                                                _inputs.pklz\n",
      "                                                desc-congruent_correlation.svg\n",
      "                                                _0x9128d279b6467cf3b65ec1242883c6e2.json\n",
      "                                                _node.pklz\n",
      "                                                result__atlas_corr_node1.pklz\n",
      "                                                _report/\n",
      "                                                    report.rst\n",
      "                                            _atlas_corr_node0/\n",
      "                                                _0xa9d873eb1e5bb0b2d93e6e17c6d0434a.json\n",
      "                                                desc-neutral_correlation.svg\n",
      "                                                _inputs.pklz\n",
      "                                                _node.pklz\n",
      "                                                desc-neutral_correlation.tsv\n",
      "                                                result__atlas_corr_node0.pklz\n",
      "                                                _report/\n",
      "                                                    report.rst\n",
      "                                        _report/\n",
      "                                            report.rst\n",
      "                            925968acad4677cdf87bd74827c135468f16a99e/\n",
      "                                ds_correlation_matrix/\n",
      "                                    _0x9c5bf50a0b5b3c7cf947986c47e939b0.json\n",
      "                                    _inputs.pklz\n",
      "                                    result_ds_correlation_matrix.pklz\n",
      "                                    _node.pklz\n",
      "                                    mapflow/\n",
      "                                        _ds_correlation_matrix1/\n",
      "                                            _0xe8c4e334f709104952aa7edc2f3c5747.json\n",
      "                                            _inputs.pklz\n",
      "                                            _node.pklz\n",
      "                                            result__ds_correlation_matrix1.pklz\n",
      "                                            _report/\n",
      "                                                report.rst\n",
      "                                        _ds_correlation_matrix2/\n",
      "                                            _0x2eefe5b23524ee715d1f921a321059f1.json\n",
      "                                            _inputs.pklz\n",
      "                                            result__ds_correlation_matrix2.pklz\n",
      "                                            _node.pklz\n",
      "                                            _report/\n",
      "                                                report.rst\n",
      "                                        _ds_correlation_matrix0/\n",
      "                                            _0xd85b77e63133e4cc388693d77c364484.json\n",
      "                                            _inputs.pklz\n",
      "                                            result__ds_correlation_matrix0.pklz\n",
      "                                            _node.pklz\n",
      "                                            _report/\n",
      "                                                report.rst\n",
      "                                    _report/\n",
      "                                        report.rst\n",
      "                                ds_betaseries_file/\n",
      "                                    _0x8b48fb4111bb8b139c5e0f5c434942ca.json\n",
      "                                    result_ds_betaseries_file.pklz\n",
      "                                    _inputs.pklz\n",
      "                                    _node.pklz\n",
      "                                    mapflow/\n",
      "                                        _ds_betaseries_file1/\n",
      "                                            _inputs.pklz\n",
      "                                            _node.pklz\n",
      "                                            _0x31242a13acde28e6e4f28c2ae5e4394e.json\n",
      "                                            result__ds_betaseries_file1.pklz\n",
      "                                            _report/\n",
      "                                                report.rst\n",
      "                                        _ds_betaseries_file0/\n",
      "                                            _0x8971c77889d3faf520d353a96ff07a5e.json\n",
      "                                            _inputs.pklz\n",
      "                                            _node.pklz\n",
      "                                            result__ds_betaseries_file0.pklz\n",
      "                                            _report/\n",
      "                                                report.rst\n",
      "                                        _ds_betaseries_file2/\n",
      "                                            _inputs.pklz\n",
      "                                            result__ds_betaseries_file2.pklz\n",
      "                                            _node.pklz\n",
      "                                            _0xb96ee62cd3fdbba637742695d0a5b66b.json\n",
      "                                            _report/\n",
      "                                                report.rst\n",
      "                                    _report/\n",
      "                                        report.rst\n",
      "                                censor_volumes/\n",
      "                                    _inputs.pklz\n",
      "                                    _node.pklz\n",
      "                                    _0xa432d007b78ef449c85071ec731e2d27.json\n",
      "                                    result_censor_volumes.pklz\n",
      "                                    mapflow/\n",
      "                                        _censor_volumes2/\n",
      "                                            _0xaaa4b170aae23941baabacdf9bf41f83.json\n",
      "                                            _inputs.pklz\n",
      "                                            result__censor_volumes2.pklz\n",
      "                                            _node.pklz\n",
      "                                            _report/\n",
      "                                                report.rst\n",
      "                                        _censor_volumes0/\n",
      "                                            result__censor_volumes0.pklz\n",
      "                                            _inputs.pklz\n",
      "                                            _0xb7b9823d3cb3e1877bcea7fe8c0dec84.json\n",
      "                                            _node.pklz\n",
      "                                            _report/\n",
      "                                                report.rst\n",
      "                                        _censor_volumes1/\n",
      "                                            _inputs.pklz\n",
      "                                            result__censor_volumes1.pklz\n",
      "                                            _node.pklz\n",
      "                                            _0xd03ade88b3abcee3da07be73bdf5ba91.json\n",
      "                                            _report/\n",
      "                                                report.rst\n",
      "                                    _report/\n",
      "                                        report.rst\n",
      "                                ds_correlation_fig/\n",
      "                                    _0x2ad65b723905063347c78402fbdaf20d.json\n",
      "                                    _inputs.pklz\n",
      "                                    _node.pklz\n",
      "                                    result_ds_correlation_fig.pklz\n",
      "                                    mapflow/\n",
      "                                        _ds_correlation_fig1/\n",
      "                                            _inputs.pklz\n",
      "                                            _0x6824418016e00784c9130e621164deaa.json\n",
      "                                            _node.pklz\n",
      "                                            result__ds_correlation_fig1.pklz\n",
      "                                            _report/\n",
      "                                                report.rst\n",
      "                                        _ds_correlation_fig2/\n",
      "                                            _0xa6142baab05c910a776bac379ac63f42.json\n",
      "                                            _inputs.pklz\n",
      "                                            result__ds_correlation_fig2.pklz\n",
      "                                            _node.pklz\n",
      "                                            _report/\n",
      "                                                report.rst\n",
      "                                        _ds_correlation_fig0/\n",
      "                                            result__ds_correlation_fig0.pklz\n",
      "                                            _inputs.pklz\n",
      "                                            _0x0218244666623bd5e0de0ddb084cba1e.json\n",
      "                                            _node.pklz\n",
      "                                            _report/\n",
      "                                                report.rst\n",
      "                                    _report/\n",
      "                                        report.rst\n",
      "                                check_beta_series_list/\n",
      "                                    _inputs.pklz\n",
      "                                    _node.pklz\n",
      "                                    result_check_beta_series_list.pklz\n",
      "                                    _0x11a8ebe20ecab786c1bf9879eac69107.json\n",
      "                                    _report/\n",
      "                                        report.rst\n",
      "            nibetaseries/\n",
      "                logs/\n",
      "                    CITATION.md\n",
      "                    CITATION.bib\n",
      "                    CITATION.html\n",
      "                    CITATION.tex\n",
      "                sub-001/\n",
      "                    func/\n",
      "                        sub-001_task-stroop_space-MNI152NLin2009cAsym_desc-congruent_correlation.svg\n",
      "                        sub-001_task-stroop_space-MNI152NLin2009cAsym_desc-neutral_correlation.svg\n",
      "                        sub-001_task-stroop_space-MNI152NLin2009cAsym_desc-incongruent_correlation.svg\n",
      "                        sub-001_task-stroop_space-MNI152NLin2009cAsym_desc-neutral_correlation.tsv\n",
      "                        sub-001_task-stroop_space-MNI152NLin2009cAsym_desc-congruent_betaseries.nii.gz\n",
      "                        sub-001_task-stroop_space-MNI152NLin2009cAsym_desc-neutral_betaseries.nii.gz\n",
      "                        sub-001_task-stroop_space-MNI152NLin2009cAsym_desc-incongruent_correlation.tsv\n",
      "                        sub-001_task-stroop_space-MNI152NLin2009cAsym_desc-incongruent_betaseries.nii.gz\n",
      "                        sub-001_task-stroop_space-MNI152NLin2009cAsym_desc-congruent_correlation.tsv\n",
      "        sub-001/\n",
      "            anat/\n",
      "                sub-001_T1w.nii.gz\n",
      "            func/\n",
      "                sub-001_task-stroop_bold.nii.gz\n",
      "                sub-001_task-stroop_events.tsv\n"
     ]
    }
   ],
   "source": [
    "list_files(data_dir)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Collect correlation results\n",
    "===========================\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          LH_Vis_1  LH_Vis_2  LH_Vis_3  LH_Vis_4  LH_Vis_5  LH_Vis_6  \\\n",
      "LH_Vis_1       NaN  0.218441 -0.193264  0.122960  0.284347  0.425336   \n",
      "LH_Vis_2  0.218441       NaN  0.448418  0.526585  0.534536  0.234280   \n",
      "LH_Vis_3 -0.193264  0.448418       NaN  0.433505  0.193010 -0.054097   \n",
      "LH_Vis_4  0.122960  0.526585  0.433505       NaN  0.086387 -0.053358   \n",
      "LH_Vis_5  0.284347  0.534536  0.193010  0.086387       NaN  0.624164   \n",
      "\n",
      "          LH_Vis_7  LH_Vis_8  LH_Vis_9  LH_SomMot_1  ...  RH_Default_Temp_1  \\\n",
      "LH_Vis_1  0.629166  0.347698  0.465092     0.700271  ...          -0.467447   \n",
      "LH_Vis_2  0.639844  0.659352  0.389759     0.344053  ...          -0.102012   \n",
      "LH_Vis_3  0.055205  0.505267 -0.020612    -0.081670  ...          -0.123051   \n",
      "LH_Vis_4  0.148364  0.335062  0.209862    -0.139957  ...           0.282268   \n",
      "LH_Vis_5  0.385814  0.353675 -0.123407     0.372037  ...          -0.510798   \n",
      "\n",
      "          RH_Default_Temp_2  RH_Default_Temp_3  RH_Default_PFCv_1  \\\n",
      "LH_Vis_1           0.552852           0.294541           0.275316   \n",
      "LH_Vis_2          -0.120641           0.384393           0.055202   \n",
      "LH_Vis_3          -0.495170           0.432884          -0.287028   \n",
      "LH_Vis_4          -0.233384           0.316979          -0.375295   \n",
      "LH_Vis_5           0.025153           0.485287           0.329859   \n",
      "\n",
      "          RH_Default_PFCv_2  RH_Default_PFCm_1  RH_Default_PFCm_2  \\\n",
      "LH_Vis_1           0.404237           0.096254           0.463110   \n",
      "LH_Vis_2           0.180601           0.322161           0.386165   \n",
      "LH_Vis_3          -0.055817           0.172316           0.302639   \n",
      "LH_Vis_4           0.066427           0.331797           0.407542   \n",
      "LH_Vis_5           0.173753          -0.123728           0.172403   \n",
      "\n",
      "          RH_Default_PFCm_3  RH_Default_PCC_1  RH_Default_PCC_2  \n",
      "LH_Vis_1           0.467991         -0.229994          0.030440  \n",
      "LH_Vis_2          -0.048633         -0.272071          0.051983  \n",
      "LH_Vis_3           0.182801          0.087879          0.083368  \n",
      "LH_Vis_4           0.082900         -0.185481          0.188477  \n",
      "LH_Vis_5           0.018889         -0.393536         -0.288098  \n",
      "\n",
      "[5 rows x 100 columns]\n"
     ]
    }
   ],
   "source": [
    "output_path = os.path.join(out_dir, \"nibetaseries\", \"sub-001\", \"func\")\n",
    "trial_types = ['congruent', 'incongruent', 'neutral']\n",
    "# filename_template = ('sub-001_task-stroop_space-MNI152NLin2009cAsym_'\n",
    "#                      'desc-{trial_type}_{suffix}.{ext}')\n",
    "\n",
    "filename_template = ('sub-001_task-stroop_space-MNI152NLin2009cAsym_'\n",
    "                     'desc-{trial_type}_{suffix}.{ext}')\n",
    "\n",
    "pd_dict = {}\n",
    "for trial_type in trial_types:\n",
    "    fname = filename_template.format(trial_type=trial_type, suffix='correlation', ext='tsv')\n",
    "    file_path = os.path.join(output_path, fname)\n",
    "    pd_dict[trial_type] = pd.read_csv(file_path, sep='\\t', na_values=\"n/a\", index_col=0)\n",
    "# display example matrix\n",
    "print(pd_dict[trial_type].head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Graph the correlation results\n",
    "=============================\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/mnt/chrastil/lab/snlbin/programs/mnt/lib/python3.7/site-packages/ipykernel_launcher.py:12: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n",
      "  if sys.path[0] == '':\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x2160 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(nrows=3, ncols=1, sharex=True, sharey=True, figsize=(10, 30),\n",
    "                         gridspec_kw={'wspace': 0.025, 'hspace': 0.075})\n",
    "\n",
    "cbar_ax = fig.add_axes([.91, .3, .03, .4])\n",
    "r = 0\n",
    "for trial_type, df in pd_dict.items():\n",
    "    g = sns.heatmap(df, ax=axes[r], vmin=-.5, vmax=1., square=True,\n",
    "                    cbar=True, cbar_ax=cbar_ax)\n",
    "    axes[r].set_title(trial_type)\n",
    "    # iterate over rows\n",
    "    r += 1\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Collect beta map results\n",
    "========================\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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OxX2mTJnSo21Zq8bz5s0reo0jjjiieF79WWF985vfXNxn+vTpxX2++tWvFtVfffXVxa8x3LnyI0mSqmL4kSRJVTH8SJKkqhh+JElSVQw/kiSpKoYfSZJUFcOPJEmqiuFHkiRVxfAjSZKqMuw+4fmwww5rXVvyKZ+PP/5469qSvb1efPHF1rUAd9xxR+va4447rnXt1772tda1v/3tb1vXfvnLX25d++yzz77i+Z1j7wRg8uTJvdbfeOONrccu+RTU8847r3XthAkTWtfeddddrWtL9/Yq+TThRYsWFY0tSbVx5UeSJFXF8CNJkqoy7E57SdKK4O///u+L+/RnY9ONNtqoqL7k1Pny6M/GrnvuuWdxnz//8z/v0basU+aHHHJI0WtsvvnmxfPqbcPVZfnud79b3Oeb3/xmcZ93vOMdRfXHHHNM8WsMd678SJKkqhh+JElSVQw/kiSpKoYfSZJUFcOPJEmqiuFHkiRVxfAjSZKqMuw+5+f0009vXXv44Ye3rr366qtb15Z8VsVZZ53VuhZgxowZrWv33Xff1rVf+cpXWtcef/zxrWtLPrdk5syZr2x4Xdcfn/70p1uP0Zd77rmnde3b3/721rXTpk1rXTtnzpzWtTfddFPrWujl706S1G+u/EiSpKoYfiRJUlUMP5IkqSqGH0mSVJVhd8GzJA1XX/va14r7/PCHPyyqL7n4f7GIKO7zF3/xF8V9rrjiiuI+vc5tGTdLHHjggUWv8da3vrV0Wuyzzz7FfebNm1fc53e/+11xnxo3Ki3lyo8kSaqK4UeSJFXF8CNJkqpi+JEkSVUx/EiSpKoMu7u9pk6d2rq2ZCuM+++/v3Xt3Xff3br2sssua10LcPPNN7euffTRR1vXHn300a1rN99889a1JfPdeeedX/F81pqzANh25217rb/22mtbj13yfVFisMaVJHWOKz+SJKkqhh9JklQVw48kSaqK4UeSJFXF8CNJkqpi+JEkSVUZdre6S9KKoD+bgfbnoxM+//nPF9Vfc801xa+RmcV9hsqSH5EBy/6YjNGjRxe9xgUXXFA8r1GjRhX36c+ms7vttltxn1VXXbW4T21c+ZEkSVUx/EiSpKoYfiRJUlVW6mt+Ss6vb7fddoMyh6uuumpQxgWYP39+69pDDjlkUOawzz779LvvI+s8AsCee+7Z63G3lpAkDQZXfiRJUlUMP5IkqSqGH0mSVBXDjyRJqorhR5IkVcXwI0mSqmL4kSRJVVmpP+dHkgbLMcccU9ynP3tovf3tbx/UeoAzzjijuM+jjz5a3Kc/evscsGV9Rljpvmuf/OQni+f13e9+t7hPf75nTjzxxCF5ndq48iNJkqpi+JEkSVUx/EiSpKoYfiRJUlUMP5IkqSqGH0mSVBXDjyRJqorhR5IkVcXwI0mSqmL4kSRJVTH8SJKkqhh+JElSVdzYVJIqN1SblA6VodjYc6g2D3WT0sHhyo8kSaqK4UeSJFXF8CNJkqpi+JEkSVUx/EiSpKoYfiRJUlUMP5IkqSqGH0mSVBXDjyRJqorhR5IkVcXwI0mSqmL4kSRJVTH8SJKkqhh+JElSVQw/kiSpKoYfSZJUFcOPJEmqiuFHkiRVxfAjSZKqYviRJElVMfxIkqSqGH4kSVJVDD+SJKkqhh9JklQVw48kSaqK4UeSJFXF8CNJkqpi+JEkSVUZubwDTJs2LQZiIhp+ImJ+Zo7pb/9pTFv8QJKkIePKjyRJqorhR5IkVcXwI0mSqmL4kSRJVTH8SJKkqhh+JElSVQw/kiSpKoYf9dvyfMaPJEmdYviRJElVMfxIkqSqGH4kSVJVDD+SJKkqhh9JklQVw48kSaqK4UeSJFUlMrPTc5AkSRoyrvxIkoadiJjf6Tlo+DL8SJKkqhh+JElSVQw/kiSpKoYfSZJUFcOPJEmqiuFHkiRVxfAjSZKq4occSpKkqrjyI0mSqmL4kSRJVTH8SJJWCBHx8Yi4ptPz0MrP8CNJGjAR8bOIOKGX9ikR8fuIGNmJeUndGX4kSQPp+8DHIiKWaP8YcF5mLhz6KUmvZPiRJA2k/wTGArstboiIdYD3AudExFoRcU5EPBERD0TEMRHR4/9FEbFFRGT3laKIuDIi/qZ5/PGI+O+IOC0i/hAR90XELk37QxHxeEQc2K3vqhHxTxHxYEQ8FhHfiYjVm2PrRcRPmnHmRsTVvc1JKw//cSVJAyYzXwAuBA7o1vwXwG8z89fAPwNrAVsCb2vq/qqfLzcJuA1YF/g34HzgLcBWwEeBb0bEmKb2q8BrgYnN8XHAsc2xvwPmAOsDGwJHA34OzErM8CNJGmhnAx9cvLJCV8A5OyJGAB8CvpSZz2bm74BT6Dol1h/3Z+a/ZuYi4AJgU+CEzFyQmZcBfwS2ak7BfQL4XGbOzcxngb8H9m/GeQnYGNg8M1/KzKvTD8FbqRl+1C8R8f5mSXqbTs9F0oolM68BngCmRMSWdK3G/BuwHjAKeKBb+QN0rcL0x2PdHr/QvPaSbWPoWtEZDdzUnNr6A/BfTTvAPwKzgcua02dH9XM+GiYMP+qvDwPX8H+/OUlSd+fQteLzMeCyJpQ8Sdcqy+bd6jYDHu6l/3PNn6O7tW3Uz7k8SVcQ2jYz126+1srMMQDNKtTfZeaWwL7AERHxzn6+loYBw4+KNefQdwUOwvAjqXfnAHvSdbrpbIDm9NSFwEkRsUZEbA4cAZy7ZOfMfIKuUPTRiBgREX8N/El/JpKZLwP/ApwWERsARMS4iHh38/i9EbH49Ng8YFHzpZWU4Uf9sR/wX5l5NzA3Inbo9IQkrVia63n+B3g1MKPbob+la1XnPrpWj/8NmN7HMJ8AvgA8BWzbjNdfR9J1auu6iJgHXAFs3Ryb0DyfD1wLnJGZVy7Ha2kF58amKhYRPwVOz8zLI+JQYNPM/EKn5yVJUhuGHxWJiHXpuiX0cbpuBR3R/Lm5d0dIkoYDT3up1AeAczJz88zcIjM3Be4H/rTD85IkqRXDj0p9GPjREm0XAX/ZgblIklTM016SJKkq7q4raViKUZGM6ePgQuDZoZyNpCH2ZGauv+yy3hl+JA1PY4Dt+ji2EV2bHUhaWT2w7JK+ec2PJEmqiuFHkiRVxfAjabk12w/cEhE/aZ6Pj4jrI+KeiLggIkY17as2z2c3x7foNsaXmva7Fm87IEmDwfCjfgvi9CBO7/Q8tEI4DLiz2/OvAqdl5gTgabr2gaP58+nM3Ao4rakjIl5P1z5x2wKTgTMiYsQQzV1SZYb8guepU6d6b/1KYrO/3gyAqdOnHtbhqajQtGnTYqDGiohNgPcAJ9G1G3YAe/B/n/10NvAV4NvAlOYxwA+Abzb1U4DzM3MBcH9EzAZ2omufJUkaUK78SFpepwNfBF5unq8L/CEzFzbP5wDjmsfjgIcAmuPPNPX/295Ln/8VEQdHxMyImMmCgX4bkmph+JHUbxHxXuDxzLype3MvpbmMY0vr838NmWdm5o6ZuSOrFk9XkgA/50fS8tkVeF9E7AOsBqxJ10rQ2hExslnd2QR4pKmfA2wKzImIkcBawNxu7Yt17yNJA8qVH0n9lplfysxNMnMLui5Y/kVmfgT4JV2b4AIcCFzcPJ7RPKc5/ovs2mNnBrB/czfYeGACcMMQvQ1JlXHlR9JgOBI4PyJOBG4BzmrazwL+X3NB81y6AhOZOSsiLgTuoGtzis9k5qKhn7akGhh+JA2IzLwSuLJ5fB9dd2stWfMi8ME++p9E1x1jkjSoPO0lSZKqYviRJElVMfxIkqSqGH4kSVJVDD+SJKkqhh9JklQVw48kSaqK4UeSJFXF8CNJkqpi+JEkSVUx/EiSpKoYfiRJUlUMP5IkqSqGH0mSVBXDjyRJqorhR5IkVcXwI0mSqmL4kSRJVTH8SJKkqhh+JElSVQw/kiSpKoYfSZJUFcOPJEmqiuFHkiRVxfAjSZKqYviRJElVMfxI6reIWC0iboiIX0fErIg4vmkfHxHXR8Q9EXFBRIxq2ldtns9ujm/RbawvNe13RcS7O/OOJNXA8CNpeSwA9sjMNwETgckRsTPwVeC0zJwAPA0c1NQfBDydmVsBpzV1RMTrgf2BbYHJwBkRMWJI34mkaozs9ARqExGta3/9618Xjb3xxhsX1T/44IOta9/0pjf1aMtMABYuXNjj2BNPPNF67PXXX791LcDIkX7briiy65tgfvN0leYrgT2Av2zazwa+AnwbmNI8BvgB8M3o+o9iCnB+Zi4A7o+I2cBOwLWD/y4k1caVH0nLJSJGRMStwOPA5cC9wB8yc3EqngOMax6PAx4CaI4/A6zbvb2XPt1f6+CImBkRM1kwGO9GUg0MP5KWS2YuysyJwCZ0rda8rrey5s/elj5zKe1LvtaZmbljZu7Iqv2dsaTaGX4kDYjM/ANwJbAzsHZELD4/uQnwSPN4DrApQHN8LWBu9/Ze+kjSgDL8SOq3iFg/ItZuHq8O7AncCfwS+EBTdiBwcfN4RvOc5vgvmuuGZgD7N3eDjQcmADcMzbuQVBuvHJW0PDYGzm7uzHoVcGFm/iQi7gDOj4gTgVuAs5r6s4D/11zQPJeuO7zIzFkRcSFwB7AQ+ExmLhri9yKpEoYfSf2WmbcB2/fSfh9d1/8s2f4i8ME+xjoJOGmg5yhJS/K0lyRJqorhR5IkVcXwI0mSqmL4kSRJVfGC5+V0+OGHF9XfcsstrWtXW221orGfffbZovpf/epXrWt721Li+eeeB2DWrFk9jm2wwQatx77mmmta1wLsu+++rWvvvffeorFL5i1JGp5c+ZEkSVUx/EiSpKoYfiRJUlUMP5IkqSqGH0mSVBXDjyRJqorhR5IkVcXwI0mSqmL4kSRJVTH8SJKkqhh+JElSVdzbqxfTpk1rXfunf/qnRWNvs802rWvXXHPNorGfeOKJovq99967de2PfvSjHm3zn5sPwO23397j2F577dV67EmTJrWuBcjM1rUjRowoGrvk3x5g6tSpRfWSpM5z5UeSJFXF8CNJkqpi+JEkSVUx/EiSpKoYfiRJUlUMP5IkqSqGH0mSVBXDjyRJqorhR5IkVcXwI6nfImLTiPhlRNwZEbMi4rCmfWxEXB4R9zR/rtO0R0R8IyJmR8RtEbFDt7EObOrviYgDO/WeJK383N6iFyeffHLr2o985CNFY++0006ta88666yisT/wgQ8U1Z9++umta3feeecebT9f8+d9Httqq61ajz1mzJjWtQDjx49vXbvWWmsVjf2Wt7ylqH7y5MlF9SuhhcDfZebNEbEGcFNEXA58HPh5Zp4cEUcBRwFHAnsDE5qvScC3gUkRMRY4DtgRyGacGZn59JC/I0krPVd+JPVbZj6amTc3j58F7gTGAVOAs5uys4H9msdTgHOyy3XA2hGxMfBu4PLMnNsEnsuB6pOlpMHhyo+kARERWwDbA9cDG2bmo9AVkCJig6ZsHPBQt25zmra+2pd8jYOBgwEYPaDTl1QRV34kLbeIGANcBByemfOWVtpLWy6l/ZUNmWdm5o6ZuSOr9m+ukmT4kbRcImIVuoLPeZn5w6b5seZ0Fs2fjzftc4BNu3XfBHhkKe2SNOAMP5L6LSICOAu4MzNP7XZoBrD4jq0DgYu7tR/Q3PW1M/BMc3rsZ8BeEbFOc2fYXk2bJA04r/mRtDx2BT4G3B4RtzZtRwMnAxdGxEHAg8AHm2OXAPsAs4Hngb8CyMy5ETENuLGpOyEz5w7NW5BUG8OPpH7LzGvo/XodgHf2Up/AZ/oYazowfeBmJ0m987SXJEmqiuFHkiRVxfAjSZKqYviRJElVqeKC5+9+97tF9Yceemjr2lmzZhWNfe6557aunTRpUtHY9957b1H91ltv3bp20aJFPdpGjBgB9L431ymnnNJ67FVXLfu0uueee6517YQJE4rGfs973lNU/8Y3vrF17a233rrsIknSoHPlR5IkVcXwI0mSqmL4kSRJVTH8SJKkqhh+JElSVQw/kiSpKoYfSZJUFcOPJEmqiuFHkiRVxfAjSZKqUsX2FiXbOADMnDmzde1HP/rRorFHjx7duvbHP/5x0dhHH310Uf3222/funb33Xfv0bbHq/YA4Dvf+U6PY5/+9Kdbj33xxRe3rgX41re+1Qrs5vQAABRFSURBVLr2qKOOKhr7scceK6ov2a7kDW94Q9HYkqTB4cqPJEmqiuFHkiRVxfAjSZKqYviRJElVMfxIkqSqGH4kSVJVDD+SJKkqhh9JklQVw48kSaqK4UeSJFXF8COp3yJiekQ8HhG/6dY2NiIuj4h7mj/XadojIr4REbMj4raI2KFbnwOb+nsi4sBOvBdJ9ahib683vvGNRfUbbrhh69qrr766aOy11167de2kSZOKxn7ooYeK6i+55JLWtZdffnmPtt/9ze8AmPq9qT2O7bLLLq3Hfv3rX9+6FmDbbbdtXXvssccWjb3bbrsV1W+22WZF9Suh7wPfBM7p1nYU8PPMPDkijmqeHwnsDUxoviYB3wYmRcRY4DhgRyCBmyJiRmY+PWTvQlJVXPmR1G+ZeRUwd4nmKcDZzeOzgf26tZ+TXa4D1o6IjYF3A5dn5twm8FwOTB782UuqVRUrP5KG1IaZ+ShAZj4aERs07eOA7suTc5q2vtp7iIiDgYMBGD2wk5ZUD1d+JA2V6KUtl9LeszHzzMzcMTN3ZNUBnZukihh+JA20x5rTWTR/Pt60zwE27Va3CfDIUtolaVBEZq+/YA2aze/ffGhfEFj40sKi+lVGrTJoY48c2f5M44sLXiwae/TqZecB5j83v3Xt6qut3qPtsY0fA2DDR3teIL7mWmu2HvvlRS+3rgV4+JGHW9eW/vustfZaRfXR66JF70aMHFE09mDZ6NGNuH6X69tPfBkiYgvgJ5n5hub5PwJPdbvgeWxmfjEi3gN8FtiHrguev5GZOzUXPN8ELL7762bgzZm55LVEr3zdsZFs18fBjYALlvONSVqR3ZSZO/a3s9f8SOq3iPh34O3AehExh667tk4GLoyIg4AHgQ825ZfQFXxmA88DfwWQmXMjYhpwY1N3wrKCjyQtjyEPPwdMP2CoX5KnnnqqqL7kVve5c8t+Rpfc6v7AAw8Ujf3a1762qP72229vXTt+/Pgebef9zXkAfOR7H+lxrORW9+eff751LcAZZ5zRuvbpp8vuli691X3EiParOWuu2X41bNC1/+dZqsz8cB+H3tlLbQKf6WOc6cD0gZmVJC2d1/xIkqSqGH4kSVJVDD+SJKkqhh9JklSVKu72+uMf/1hU/+Y3v7l17Q033FA09qJFi1rXllx4DXDRRRcV1Z999tnLLmqsv/76PdquXOdKAA477LAex/bZZ5/WY5de8Hzccce1rn3HO95RNPbxxx9fVF9yUfrEiROLxpYkDQ5XfiRJUlUMP5IkqSqGH0mSVBXDjyRJqorhR5IkVcXwI0mSqjIo4Sci2m8XLmmFExGLIuLWiPhNRPw4ItpvSidJKzhXfiT15oXMnJiZbwDm0seGpJI0HBl+JC3LtcC4Tk9CkgaK4UdSnyJiBPBOYEan5yJJA6WK7S322muvovqSbSL+5E/+pGjsG2+8sXXtvvvuWzR2yXYVAL/85S9b126//fY92l544wsA3HPPPT2O7b777q3H3mCDDVrXAuy///6ta0v/fUq3t3jiiSda186dO7do7A5bPSJuBbYAbgIu7+x0JGnguPIjqTcvZOZEYHNgFF7zI2klYviR1KfMfAY4FPh8RKzS6flI0kAYrPAzOiLmdPs6YpBeR9Igy8xbgF8D7c83StIKbFCu+clMV5SkYSwzxyzxvOwCNElagRlSJElSVQw/kiSpKoYfSZJUFcOPJEmqiuFHkiRVxfAjSZKqYviRtMKIiMkRcVdEzI6Iozo9H0krpyr29rr33nuL6jfccMPWtVOnTi0ae+edd25de9111xWNfemllxbVl+zt9dOf/rRH21OvearPY9dee23rsb/whS+0rgXYddddW9fed999RWPPnj27qL5kL7BjjjmmaOzaNJuofgt4FzAHuDEiZmTmHZ2dmaSVTRXhR9KwsBMwOzPvA4iI84EpQK/hZ5O14e8+3sdIo4D2v2dIGmY+97nl6+9pL0krinHAQ92ez2na/ldEHBwRMyNiJi8P6dwkrURc+ZG0oohe2vIVTzLPBM4EiLGRn/t+HyNtBFwwoHOTtBJx5UfSimIOsGm355sAj3RoLpJWYoYfSSuKG4EJETE+IkbRtYv8jA7PSdJKyNNeklYImbkwIj4L/AwYAUzPzFkdnpaklZDhR9IKIzMvAS7p9Dwkrdw87SVJkqpi+JEkSVUx/EiSpKpUcc3PlltuWVT//e9/v3Xtl770paKx991339a1//qv/1o09sSJE4vqn3jiida1Z511Vo+2F194Eeh9C4k99tij9dgvvfRS61qAD33oQ61rv/jFLxaNPWbMmKL6v/3bvy2qlyR1nis/kiSpKoYfSZJUFcOPJEmqiuFHkiRVxfAjSZKqYviRJElVMfxIkqSqGH4kSVJVDD+SJKkqhh9JklQVw48kSapKFXt7zZs3r6h++vTprWtvuOGGorEPPfTQ1rWve93risY+6aSTiupPO+201rWnnHJKj7Zfr/trAPbee+8ex+bPn9967HHjxrWuBdhqq61a1z755JNFY//0pz8tqt9///1b11566aVFY0uSBocrP5IkqSqGH0mSVBXDjyRJqorhR5IkVcXwI0mSqmL4kSRJVTH8SJKkqhh+JElSVQw/kiSpKoYfSZJUlSq2t7jqqquK6l9++eXWtf/5n/9ZNPZqq63WuvaJJ54oGvu9731vUf3Xvva11rXbbbddj7Yxrx7T57F/+Id/aD32Hnvs0boW4L//+79b1371q18tGvvUU08tqv+P//iP1rVjxowpGntFFxEfBL4CvA7YKTNndjv2JeAgYBFwaGb+rGmfDHwdGAF8LzNPbtrHA+cDY4GbgY9l5h+H7t1IqokrP5L66zfAnwGv+O0iIl4P7A9sC0wGzoiIERExAvgWsDfweuDDTS3AV4HTMnMC8DRdwUmSBoXhR1K/ZOadmXlXL4emAOdn5oLMvB+YDezUfM3OzPuaVZ3zgSkREcAewA+a/mcD+w3+O5BUK8OPpIE2Dnio2/M5TVtf7esCf8jMhUu09xARB0fEzIiYyYIBn7ekSlRxzY+k/omIK4CNejn05cy8uK9uvbQlvf+ylUup79mYeSZwJkCMjV5rJGlZDD+S+pSZe/aj2xxg027PNwEeaR731v4ksHZEjGxWf7rXS9KA87SXpIE2A9g/IlZt7uKaANwA3AhMiIjxETGKrouiZ2RmAr8EPtD0PxDoa1VJkpab4UdSv0TE+yNiDvBW4KcR8TOAzJwFXAjcAfwX8JnMXNSs6nwW+BlwJ3BhUwtwJHBERMym6xqgs4b23Uiqiae9JPVLZv4I+FEfx04CTuql/RLgkl7a76PrbjBJGnSu/EiSpKoYfiRJUlUMP5IkqSpVXPMzb968ovoddtihde29995bNPb111/fuvaII44oGrt0LltttVXr2nPPPbdH22OffqzPY/vvv3/rsS+77LLWtQBrrrlm69pPfvKTRWP/4he/KKpfY401iuolSZ3nyo8kSaqK4UeSJFXF8CNJkqpi+JEkSVUx/EiSpKoYfiRJUlUMP5IkqSqGH0mSVBXDjyRJqorhR5IkVaWK7S222267ovqZM2e2rt16662Lxl6wYEHr2uOPP75o7MmTJxfVP/74461rX3zxxR5tL7/8cp/Hvv3tb7ce+61vfWvrWij7O3zmmWeKxr7jjjuK6idNmlRUL0nqPFd+JElSVQw/kiSpKoYfSZJUFcOPJEmqiuFHkiRVxfAjSZKqYviRJElVMfxIkqSqGH4kSVJVDD+SJKkqhh9JklSVKvb2KvXII4+0rt19992Lxr7qqqta177jHe8oGvu5554rqt9iiy1a1z700EM92l7Orr29XnrppR7HNttss9Zjl8774Ycfbl177rnnFo195JFHFtXXLCL+EdgX+CNwL/BXmfmH5tiXgIOARcChmfmzpn0y8HVgBPC9zDy5aR8PnA+MBW4GPpaZfxzadySpFq78SOqvy4E3ZOZ2wN3AlwAi4vXA/sC2wGTgjIgYEREjgG8BewOvBz7c1AJ8FTgtMycAT9MVnCRpUBh+JPVLZl6WmQubp9cBmzSPpwDnZ+aCzLwfmA3s1HzNzsz7mlWd84EpERHAHsAPmv5nA/sN1fuQVB/Dj6SB8NfApc3jcUD386Rzmra+2tcF/tAtSC1u7yEiDo6ImRExkwUDOHtJVfGaH0l9iogrgI16OfTlzLy4qfkysBA4b3G3XuqT3n/ZyqXU92zMPBM4EyDGRq81krQshh9JfcrMPZd2PCIOBN4LvDMzF4eROcCm3co2ARbfRdBb+5PA2hExsln96V4vSQPO016S+qW5c+tI4H2Z+Xy3QzOA/SNi1eYurgnADcCNwISIGB8Ro+i6KHpGE5p+CXyg6X8gcPFQvQ9J9XHlR1J/fRNYFbi865plrsvMT2XmrIi4ELiDrtNhn8nMRQAR8VngZ3Td6j49M2c1Yx0JnB8RJwK3AGcN7VuRVBPDj6R+ycytlnLsJOCkXtovAS7ppf0+uu4Gk6RB52kvSZJUFcOPJEmqiuFHkiRVJf7v7tShMXXq1Ko/m2PMmDGta4866qiisU855ZSi+iOOOKJ1bXNB6yv9svmzly3IjjvuuNZjv+lNb2pdC3DzzTcX1aunadOm9fbZOsNKjI1kuz4ObgRcMJSzkTTEbsrMHfvb2ZUfSZJUFcOPJEmqiuFHkiRVxfAjSZKqYviRJElVMfxIkqSqGH4kSVJVDD+SJKkqhh9JklQVw48kSaqK21uo387563MAOGD6AR2eiUq5vYWkYc7tLSRJktoy/EiSpKoYfiRJUlUMP5IkqSqGH0mSVBXDjyRJqorhR5IkVcXwI0mSqmL4kSRJVTH8SJKkqhh+JPVLREyLiNsi4taIuCwiXtO0R0R8IyJmN8d36NbnwIi4p/k6sFv7myPi9qbPNyJi2G+/IWnFZfiR1F//mJnbZeZE4CfAsU373sCE5utg4NsAETEWOA6YBOwEHBcR6zR9vt3ULu43eajehKT6GH4k9Utmzuv29NXA4k2LpwDnZJfrgLUjYmPg3cDlmTk3M58GLgcmN8fWzMxrs2un5XOA/YbunUiqzchOT0DS8BURJwEHAM8A72iaxwEPdSub07QtrX1OL+2SNChc+ZHUp4i4IiJ+08vXFIDM/HJmbgqcB3x2cbdehsp+tPc2n4MjYmZEzGRB+fuRJHDlR9JSZOaeLUv/DfgpXdf0zAE27XZsE+CRpv3tS7Rf2bRv0kt9b/M5EzgTIMZGrwFJkpbFlR9J/RIRE7o9fR/w2+bxDOCA5q6vnYFnMvNR4GfAXhGxTnOh817Az5pjz0bEzs1dXgcAFw/dO5FUG1d+JPXXyRGxNfAy8ADwqab9EmAfYDbwPPBXAJk5NyKmATc2dSdk5tzm8SHA94HVgUubL0kaFIYfSf2SmX/eR3sCn+nj2HRgei/tM4E3DOgEJakPnvaSJElVMfxIkqSqGH4kSVJVDD+SJKkqhh9JklQVw48kSaqK4UeSJFXF8CNJkqpi+JEkSVWJrg9jlcpExCLgdro+JfxO4MDMfL6zs1JNIuIJurbVWGw94MkOTWeo1PAel6bm91/ze4ee73/zzFy/v4MZftQvETE/M8c0j88DbsrMUzs8LVUsImZm5o6dnsdgquE9Lk3N77/m9w4D//497aWBcDWwVacnIUlSG4YfLZeIGAnsTdcpMEmSVnju6q7+Wj0ibm0eXw2c1cnJSMCZnZ7AEKjhPS5Nze+/5vcOA/z+veZH/dL9mh9JkoYTT3tJkqSqGH4kDWsRMTki7oqI2RFxVKfnMxgi4nMRMSsifhMR/x4Rq3V6ToMpIqZHxOMR8ZtubRdExK3N1++6nXZf6UTEphHxy4i4s/l3P6zbsb9tvt9nRcTXOjnPwRIRq0XEDRHx6+Z9Ht+0fz8i7u/2fTCx36/haS9Jw1VEjADuBt4FzAFuBD6cmXd0dGIDKCLGAdcAr8/MFyLiQuCSzPx+Z2c2eCJid2A+cE5mvqGX46cAz2TmCUM+uSEQERsDG2fmzRGxBnATsB+wIfBl4D2ZuSAiNsjMxzs518EQEQG8OjPnR8QqdH3/HwZ8CvhJZv5geV/DC54lDWc7AbMz8z6AiDgfmAKsNOGnMZKumwxeAkYDj3R4PoMqM6+KiC16O9b8j/EvgD2Gck5DKTMfBR5tHj8bEXcC44BPACdn5oLm2EoXfACya1VmfvN0leZrQFdqPO0laTgbBzzU7fmcpm2lkZkPA/8EPEjX/xCfyczLOjurjtoNeCwz7+n0RIZCEwK3B64HXgvsFhHXR8SvIuItnZzbYIqIEc2pzceByzPz+ubQSRFxW0ScFhGr9nd8w4+k4Sx6aVupzuVHxDp0rWaNB14DvDoiPtrZWXXUh4F/7/QkhkJEjAEuAg7PzHl0rQCuA+wMfAG4sFkJW+lk5qLMnAhsAuwUEW8AvgRsA7wFGAsc2d/xDT+ShrM5wKbdnm/CyndKaE/g/sx8IjNfAn4I7NLhOXVE86GqfwZc0Om5DLbmWpeLgPMy84dN8xzgh9nlBuBluva8Wmll5h+AK4HJmflo894XAP9K12nvfjH8SBrObgQmRMT4iBgF7A/M6PCcBtqDwM4RMbr5Lf+ddG0mXKM9gd9m5pxOT2QwNf/OZwF3LrFn4n/SXOsUEa8FRrESbnYaEetHxNrN49Vp/t2bC8EX//3sB/ym71GWzgueJQ1bmbkwIj4L/AwYAUzPzFkdntaAyszrI+IHwM3AQuAWVvJP+42IfwfeDqwXEXOA4zLzLLrCbQ2nvHYFPgbc3u2W/qOB6cD05iMA/ggcmCvnLdsbA2c3d3O+CrgwM38SEb+IiPXpOt19K113f/WLt7pLkqSqeNpLkiRVxfAjSZKqYviRJElVMfxIkqSqGH4kSVJVDD+SJKkqhh9JklQVw48kSarK/wej+IvrxOa7mgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 576x576 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "nii_dict = {}\n",
    "for trial_type in trial_types:\n",
    "    fname = filename_template.format(trial_type=trial_type, suffix='betaseries', ext='nii.gz')\n",
    "    file_path = os.path.join(output_path, fname)\n",
    "    nii_dict[trial_type] = nib.load(file_path)\n",
    "\n",
    "# view incongruent beta_maps\n",
    "nib.viewers.OrthoSlicer3D(nii_dict['incongruent'].get_fdata(),\n",
    "                          title=\"Incongruent Betas\").set_position(10, 13, 10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Graph beta map standard deviation\n",
    "=================================\n",
    "We can find where the betas have the highest standard deviation for each trial type.\n",
    "Unsuprisingly, the largest deviations are near the edge of the brain mask and\n",
    "the subcortical regions.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x1440 with 15 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# standard deviations for each trial type\n",
    "std_dict = {tt: nib.Nifti1Image(img.get_fdata().std(axis=-1), img.affine, img.header)\n",
    "            for tt, img in nii_dict.items()}\n",
    "\n",
    "fig, axes = plt.subplots(nrows=3, ncols=1, figsize=(10, 20))\n",
    "\n",
    "for idx, (trial_type, nii) in enumerate(std_dict.items()):\n",
    "    plotting.plot_stat_map(nii, title=trial_type, cut_coords=(0, 0, 0),\n",
    "                           threshold=5, vmax=20, axes=axes[idx])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### References\n",
    "==========\n",
    ".. bibliography:: ../../src/nibetaseries/data/references.bib\n",
    "   :style: plain\n",
    "   :labelprefix: notebook-\n",
    "   :keyprefix: n-\n",
    "\n",
    "\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}