def main():
conf = AnalysisConfiguration()
data_dir = os.environ.get('DATA_DIR') or '/home/user/data'
op = OpenFMRIData(data_dir, conf.study_name)
analyzer = OpenFMRIAnalyzer(op, conf)
all_subject_dirs = op.all_subjects_dirs_with_raw()
for subject in all_subject_dirs:
analyzer.extract_brain(subject)
for subject in all_subject_dirs:
analyzer.anatomical_registration(subject)
for subject in all_subject_dirs:
#for task in conf.mvpa_tasks:
#subject.remove_volumes_from_model(1, "", task, conf.num_of_volumes_to_delete)
analyzer.motion_correction(subject)
analyzer.functional_registration(subject)
if conf.func_seg:
analyzer.functional_segmentation(subject)
else:
analyzer.segmentation(subject)
analyzer.generate_functional_gm_masks(subject)
#analyzer.warp_standard_mask(subject)
for subject in all_subject_dirs:
# DO SL
out_dir = _opj(subject.path(),'results',conf.dir_name())
if not os.path.exists(out_dir):
os.makedirs(out_dir)
run_searchlight(op, subject, conf, out_dir)
# run_searchlight(op.study_dir(), subject.subcode(), mask_name, k, [['G1','G4']], out_dir,flavor)
#Group Level
output_dir = _opj(op.study_dir(), 'results', "{}".format(conf.dir_name()))
if not os.path.exists(output_dir):
os.makedirs(output_dir)
files = glob(_opj(op.study_dir(), "**", 'results', conf.dir_name(), '*acc_mni.nii.gz'))
print files
generate_group_level_map( files, output_dir)
