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)