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)