def main(data_files, roi_files, mask):
for subdat in data_files:
submeants = extract_seed_ts(subdat, roi_files, mask)
subid = utils.get_subid(subdat)
outname = '_'.join([subid, 'timecourses.csv'])
outfile = os.path.join(outdir, outname)
subdf = save_to_csv(submeants, outfile, dropna=True)
def main(datadir, outdir, outname, tc_files, tr, tc_subset=None, subgroup=None):
group_cov = {} #Create empty dataframe to hold group covariance
group_precision = {} #Create empty dataframe to hold group precision
group_corr = {} # Create empty dataframe to hold group correlation
group_coh = {} # Create empty dataframe to hold group coherence
for subtc_file in tc_files:
subid = utils.get_subid(subtc_file)
print 'Starting on subject %s'%(subid)
if not subgroup:
sub_cov, sub_precision, sub_corr, sub_coh = run_subject(subtc_file,
tr,
tc_subset)
group_cov[subid] = sub_cov
group_precision[subid] = sub_precision
group_corr[subid] = sub_corr
group_coh[subid] = sub_coh
elif subgroup and subid in subgroup:
sub_cov, sub_precision, sub_corr, sub_coh = run_subject(subtc_file,
tr,
tc_subset)
group_cov[subid] = sub_cov
group_precision[subid] = sub_precision
group_corr[subid] = sub_corr
group_coh[subid] = sub_coh
else:
print 'Subject %s not in list of subject, skipping...'%(subid)
continue
cov_outfile = os.path.join(outdir, ''.join(['Covariance_',outname,'.csv']))
group_cov_df = save_group_data(group_cov, cov_outfile)
precision_outfile = os.path.join(outdir, ''.join(['Precision_',outname,'.csv']))
group_precision_df = save_group_data(group_precision, precision_outfile)
corr_outfile = os.path.join(outdir, ''.join(['Correlation_',outname,'.csv']))
group_corr_df = save_group_data(group_corr, corr_outfile)
coh_outfile = os.path.join(outdir, ''.join(['Coherence_',outname,'.csv']))
group_coh_df = save_group_data(group_coh, coh_outfile)
def main(datafiles):
for subj_file in datafiles:
subid = gu.get_subid(subj_file, subjstr)
print 'Starting on subject %s'%(subid)
dat, aff = gu.load_nii(subj_file)
nets_dat = dat[:,:,:,net_idx]
nets_diff_array = calculate_diff_map(nets_dat)
nets_diff_outfile = os.path.join(outdir, ''.join(['nets_diff_',subid,'.nii.gz']))
gu.save_nii(nets_diff_outfile, nets_diff_array, aff)
