outdir = os.path.join(basedir, 'ic_files')
subic_globstr = os.path.join(basedir, '*sub*_component_ica_s1_.nii') # search string for sub ic files
ic4d_globstr = os.path.join(outdir, 'dr_stage2_ic*_4D.nii.gz')
subid_pattern = u'sub[0-9]{3}'
#######################################
# Make output directory
if os.path.isdir(outdir)==False:
os.mkdir(outdir)
else:
raise OSError('%s exists, remove to re-run'%outdir)
# Split files of each subject containing all ic's
infiles = glob(subic_globstr)
for subfile in infiles:
subid = pydr.get_subid(subfile, pattern=subid_pattern)
allic = pydr.split_components(subfile, subid, outdir)
# Merge files of each ic across subjects
for cn, item in enumerate(allic): #Search through ics using last subject's output
datadir, ic = os.path.split(item)
subid = pydr.get_subid(item, pattern=subid_pattern)
globstr = ic.replace(subid, '*')
mergefile, subject_order = pydr.merge_components(datadir,
globstr = globstr,
subid_pattern = subid_pattern)
outfile = os.path.join(outdir, 'subject_order_ic%04d'%cn)
with open(outfile, 'w+') as fid:
fid.write('\n'.join(subject_order)) #Write out subject order for each ic
# Rename files with ic count starting at 1 and unzip
'B*.ica', # subject speccific
'reg_standard', # registered to standard
'filtered_func_data.nii.gz') # data
infiles = glob(globstr)
infiles.sort()
### RUN DUAL REGRESSION
############################
startdir = os.getcwd()
os.chdir(outdir)
subd = {}
for tmpf in infiles: #subject-wise
subid = pydr.get_subid(tmpf)
###Run dr_stage1
txtf = pydr.template_timeseries_sub(tmpf, template, mask, outdir)
###Run dr_stage2
## If you want to add movement params & spike regressors to stage2 of model
## mvtfile = <confound file>
## Must change input of mvt parameter from None in dr_stage2 below
sub_icadir = ''.join([subid, sub_icadirname])
mvtfile = os.path.join(basedir,
subid,
'func',
'confound_regressors_6mm.txt') #Name of confound file
## If you want residuals to be output, change out_res to True below
stage2_ts, stage2_tsz = pydr.sub_spatial_map(tmpf, txtf, mask, outdir,