# set subjects_dir
subjects_dir = os.path.join(script_dir, 'subjects')
# set template directory
template_dir = os.path.join(script_dir, 'anat_templates')
# APPEND TO PYHTONPATH
prep_script_dir = os.path.join(script_dir, 'preprocessing')
plots_script_dir = os.path.join(script_dir, 'plots')
sys.path.extend([prep_script_dir, plots_script_dir])
# GET SUBJECT LIST FROM TXT FILE
full_subjects_list = load_subjects_list(subjects_dir, subjects_file)
# reduce subjects list to fold
subjects_list = get_subjects_list_fold(full_subjects_list, fold_n, fold_size)
# check pandas version
import pandas as pd
print('Using pandas version %s' % pd.__version__)
if LooseVersion(pd.__version__) >= '0.16':
print('pandas version OK')
else:
raise Exception('pandas version >= 0.16 required')
fsl_v_str = subprocess.check_output('cat $FSLDIR/etc/fslversion', shell=True).strip()
import os, glob, datetime
import json
from variables import freesurfer_dir, subjects_dir
from utils import load_subjects_list
dicom_dir = '/scr/kaiser2/NKI/nki_r5_onwards/r6_onwards/dicoms/all_studies_V2'
os.chdir(dicom_dir)
previous_subjects_file = 'subjects_2015-09-04_r5_r6_r7.txt'
previous_subjects = load_subjects_list(subjects_dir, previous_subjects_file)
subjects_list = [s for s in glob.iglob('A*')]
#dicom_dict = {'t1w':'anat', 'rs':'session_1/RfMRI_mx_645', 'diffusion':'session_1/DTI_mx_137'}
# r8 schema
dicom_dict = {'t1w':'MPRAGE_SIEMENS_DEFACED*', 'rs':'REST_645_*', 'diffusion':'DIFF_137_AP_*'}
dicom_missing = {'t1w':[], 'rs':[], 'diffusion':[], 'fs':[]}
bad_subjects_list = []
for subject in subjects_list:
for img, img_file in dicom_dict.items():
check_file = os.path.join(dicom_dir, subject, '*', img_file)
file_exists = glob.glob(check_file)
if len(file_exists)==0:
print ('NOOOK: %s %s does not exist'%(subject, img))
dicom_missing[img].append(subject)
if not subject in bad_subjects_list:
bad_subjects_list.append(subject)
# set subjects_dir
subjects_dir = os.path.join(script_dir, 'subjects')
# set template directory
template_dir = os.path.join(script_dir, 'anat_templates')
# APPEND TO PYHTONPATH
prep_script_dir = os.path.join(script_dir, 'preprocessing')
plots_script_dir = os.path.join(script_dir, 'plots')
sys.path.extend([prep_script_dir, plots_script_dir])
# GET SUBJECT LIST FROM TXT FILE
full_subjects_list = load_subjects_list(subjects_dir, subjects_file)
# reduce subjects list to fold
subjects_list = get_subjects_list_fold(full_subjects_list, fold_n, fold_size)
#check CPAC version
print('Using CPAC version %s' % CPAC.__version__)
if LooseVersion(CPAC.__version__) >= '0.3.9.1':
print('CPAC version OK')
else:
raise Exception('CPAC version >= 0.3.9.1 required')
#check pandas version
import pandas as pd
print('Using pandas version %s' % pd.__version__)
script_dir = os.path.dirname(os.path.realpath(__file__))
template_dir = os.path.join(script_dir, 'templates')
wd_root_path = '/data/liem-3/LIFE/'
metrics_root_path = '/scr/adenauer2/Franz/LeiCA_LIFE/'
ds_root_path = '/scr/adenauer2/Franz/LeiCA_LIFE'
subjects_list_folder = '/home/raid2/liem/data/LIFE/behavioral'
subject_file = '/scr/adenauer2/Franz/LIFE16/LIFE16_preprocessed_subjects_list_n2557.txt'
behav_file = '/home/raid2/liem/data/LIFE/behavioral/LIFE_subjects_behav_n2615.pkl'
qc_file = '/home/raid2/liem/data/LIFE/behavioral/LIFE_subjects_QC_n2557.pkl'
subjects_list = load_subjects_list(subject_file)
in_data_root_path = '/data/liem-1/LIFE/preprocessed'
selectfiles_templates = {
'epi_MNI_bp': '{subject_id}/resting_state/ants/rest_mni_unsmoothed.nii.gz',
'epi_MNI_fullspectrum': '{subject_id}/resting_state/ants/rest_mni_unsmoothed_fullspectrum.nii.gz',
'moco_parms_file': '{subject_id}/resting_state/realign/rest_realigned.par',
'jenkinson_file': '{subject_id}/resting_state/realign/rest_realigned_rel.rms',
'rest2anat_cost_file': '{subject_id}/resting_state/coregister/rest2anat.dat.mincost',
}
from qc_reports.create_qc_report_pdf import create_qc_report_pdf
from variables import ds_dir, report_base_dir, subjects_dir
from variables import TR_list, full_subjects_list, subjects_file_prefix
from variables import plugin_name, use_n_procs
#fixme
full_subjects_list.remove('A00056097')
#fixme
plugin_name = 'MultiProc'
use_n_procs = 25
subjects_list = full_subjects_list
subjects_missing_files_list = load_subjects_list(subjects_dir, subjects_file_prefix + '_excluded.txt')
report_str = 'rsfMRI_preprocessing'
wf = Workflow('qc_reports_wf')
wf.base_dir = report_base_dir
wf.config['execution']['crashdump_dir'] = os.path.join(report_base_dir, 'crash')
wf.config['execution']['stop_on_first_crash'] = False
# collect dfs
df = pd.DataFrame()
for TR in TR_list:
script_dir = os.path.dirname(os.path.realpath(__file__))
template_dir = os.path.join(script_dir, 'templates')
wd_root_path = '/data/liem-3/LIFE/'
metrics_root_path = '/scr/adenauer2/Franz/LeiCA_LIFE/'
ds_root_path = '/scr/adenauer2/Franz/LeiCA_LIFE'
subjects_list_folder = '/home/raid2/liem/data/LIFE/behavioral'
subject_file = '/scr/adenauer2/Franz/LIFE16/LIFE16_preprocessed_subjects_list_n2557.txt'
behav_file = '/home/raid2/liem/data/LIFE/behavioral/LIFE_subjects_behav_n2615.pkl'
qc_file = '/home/raid2/liem/data/LIFE/behavioral/LIFE_subjects_QC_n2557.pkl'
subjects_list = load_subjects_list(subject_file)
in_data_root_path = '/data/liem-1/LIFE/preprocessed'
selectfiles_templates = {
'epi_MNI_bp':
'{subject_id}/resting_state/ants/rest_mni_unsmoothed.nii.gz',
'epi_MNI_fullspectrum':
'{subject_id}/resting_state/ants/rest_mni_unsmoothed_fullspectrum.nii.gz',
'moco_parms_file':
'{subject_id}/resting_state/realign/rest_realigned.par',
'jenkinson_file':
'{subject_id}/resting_state/realign/rest_realigned_rel.rms',
'rest2anat_cost_file':
'{subject_id}/resting_state/coregister/rest2anat.dat.mincost',
}
root_dir = '/data/liem-1/LIFE/'
check_file_list = [
'preprocessed/{subject_id}/resting_state/ants/rest_mni_unsmoothed_fullspectrum.nii.gz',
'preprocessed/{subject_id}/resting_state/ants/rest_mni_unsmoothed.nii.gz',
'preprocessed/{subject_id}/resting_state/denoise/rest_preprocessed_nativespace_fullspectrum.nii.gz',
'preprocessed/{subject_id}/resting_state/denoise/rest_preprocessed_nativespace.nii.gz',
'preprocessed/{subject_id}/resting_state/FWHM6/rest_mni_smoothed.nii.gz',
'preprocessed/{subject_id}/resting_state/realign/rest_realigned.par',
'preprocessed/{subject_id}/structural/transforms2mni/transform0GenericAffine.mat',
'preprocessed/{subject_id}/structural/transforms2mni/transform1InverseWarp.nii.gz',
'preprocessed/{subject_id}/structural/transforms2mni/transform1Warp.nii.gz',
]
subjects_list = load_subjects_list(
'/scr/adenauer2/Franz/LIFE16/LIFE16_preprocessed_subjects_list_n2557.txt')
print subjects_list
print('\n\n CHECKING FOR MISSING FILES...')
missing_files = False
for subject_id in subjects_list:
for file_template in check_file_list:
subject_file = os.path.join(
root_dir, file_template.format(subject_id=subject_id))
# print subject_file
if not os.path.exists(subject_file):
print('MISSING FILE %s: %s' % (subject_id, subject_file))
missing_files = True
if missing_files:
print('\n SOME FILES MISSING')
import os, glob
root_dir = '/data/liem-1/LIFE/'
check_file_list = ['preprocessed/{subject_id}/resting_state/ants/rest_mni_unsmoothed_fullspectrum.nii.gz',
'preprocessed/{subject_id}/resting_state/ants/rest_mni_unsmoothed.nii.gz',
'preprocessed/{subject_id}/resting_state/denoise/rest_preprocessed_nativespace_fullspectrum.nii.gz',
'preprocessed/{subject_id}/resting_state/denoise/rest_preprocessed_nativespace.nii.gz',
'preprocessed/{subject_id}/resting_state/FWHM6/rest_mni_smoothed.nii.gz',
'preprocessed/{subject_id}/resting_state/realign/rest_realigned.par',
'preprocessed/{subject_id}/structural/transforms2mni/transform0GenericAffine.mat',
'preprocessed/{subject_id}/structural/transforms2mni/transform1InverseWarp.nii.gz',
'preprocessed/{subject_id}/structural/transforms2mni/transform1Warp.nii.gz',
]
subjects_list = load_subjects_list('/scr/adenauer2/Franz/LIFE16/LIFE16_preprocessed_subjects_list_n2557.txt')
print subjects_list
print('\n\n CHECKING FOR MISSING FILES...')
missing_files = False
for subject_id in subjects_list:
for file_template in check_file_list:
subject_file = os.path.join(root_dir, file_template.format(subject_id=subject_id))
# print subject_file
if not os.path.exists(subject_file):
print('MISSING FILE %s: %s' % (subject_id, subject_file))
missing_files = True
if missing_files:
print('\n SOME FILES MISSING')
else:
import pandas as pd
from nipype.pipeline.engine import Node, Workflow
import nipype.interfaces.utility as util
from utils import get_condor_exit_status, check_if_wf_crashed, load_subjects_list
from qc_reports.create_qc_report_pdf import create_qc_report_pdf
from variables import ds_dir, report_base_dir, subjects_dir
from variables import TR_list, full_subjects_list, subjects_file_prefix
from variables import plugin_name, use_n_procs
#fixme
plugin_name = 'MultiProc'
use_n_procs = 25
subjects_list = full_subjects_list
subjects_missing_files_list = load_subjects_list(
subjects_dir, subjects_file_prefix + '_excluded.txt')
report_str = 'rsfMRI_preprocessing'
wf = Workflow('qc_reports_wf')
wf.base_dir = report_base_dir
wf.config['execution']['crashdump_dir'] = os.path.join(report_base_dir,
'crash')
wf.config['execution']['stop_on_first_crash'] = False
# collect dfs
df = pd.DataFrame()
for TR in TR_list:
rel_report_dir = os.path.join(report_str + '_TR_%s' % TR)
os.chdir(report_base_dir)