op = OpenFMRIData(data_dir, raw_dir,study_name)
subject_names = op.get_subject_names() # All subjects
# create open fMRI data structure and conver .dcms to .nii
for name in subject_names:
x=2
# subject_dir = op.create_subject_dir(name, overwrite=True)
#TODO: agree on a standard to include open behvadata.txt files in raw directory structure
# copy over the behavdata.txt files to correct place in open-fmri data struc created above:
# you need to do this with a mat script of by hand for each run for eahc subject
# ~/sub001/behav/tak00X_run00X/behavdata.txt
for name in subject_names:
subject = op.load_subject_dir(subname=name)
subject_dir_name = subject._path
op.create_subject_evs(subject_dir_name= subject_dir_name , mode = 'basic')
op.create_subject_evs(subject_dir_name= subject_dir_name , mode = 'trial_base')
# run preprocessing and first levle naalysis
for name in subject_names:
subject = op.load_subject_dir(subname=name)
# if we want to create new data for analysis
# subject_dir = op.create_subject_dir(name)
# if we want to load new data for analysis
# structural:
subject_dir = subject._path
preproc = PreProcessing(op,[subject])
brain_image = preproc.extract_brain(subject,automatic_approval = True)
condition_name = "cond{:0>3d}.txt".format(condition_number + 1)
print ">>> condition mapping: {}->{}".format(
key, condition_number)
for onset_dir in onset_dirs:
value.to_csv(os.path.join(subjectdir.model_dir(),
onset_dir, task_sequence,
condition_name),
sep='\t',
index=False,
header=False)
op = OpenFMRIData(data_dir, raw_dir, study_name)
#subject_names = ['MoCa'] # Specific subject names
subject_names = op.get_subject_names() # All subjects
for name in subject_names:
subject_dir = op.load_subject_dir(subname=name,
create_behav_dict={
'func':
create_evs,
'behav':
os.path.join(behavioural_dir,
study_name, name)
})
# if we want to create new data for analysis
# subject_dir = op.create_subject_dir(name)
analyzer = OpenFMRIAnalyzer(op, [subject_dir])
analyzer.analyze(mc_merge=True)
