if __name__ == "__main__":
if len(sys.argv) < 4:
print("Usage: python %s <data_root_dir> " "<preproc_root_dir> <glm_root_dir>" % sys.argv[0])
print("Example:\r\npython %s ~/datasets/raw" " ~/datasets/preproc ~/datasets/glm") % sys.argv[0]
sys.exit(1)
root_dir, preproc_dir, glm_dir = sys.argv[1:]
# download data
data_dir = fetch_openfmri(FULL_ID, root_dir)
# alternative task_contrasts (errors in original file?)
contrasts_file = "%s_task_contrasts.txt" % SHORT_ID
assert os.path.isfile(contrasts_file), "BUG: No contrasts file in code repo: %s" % contrasts_file
dest = os.path.join(data_dir, SHORT_ID, "models", MODEL_ID, "task_contrasts.txt")
if not os.path.isfile(dest):
os.symlink(contrasts_file, dest)
# apply SPM preprocessing
apply_preproc(SHORT_ID, data_dir, preproc_dir, ignore_list, dataset_description=DESCRIPTION)
# prepare GLM (get data and design)
preproc_data, motion_params = load_preproc(SHORT_ID, preproc_dir)
glm_params = load_glm_params(
SHORT_ID, data_dir, MODEL_ID, subject_ids=preproc_data.keys(), motion_params=motion_params
)
apply_glm(SHORT_ID, glm_dir, preproc_data, glm_params, resample=True, n_jobs=-1)
return data, motion
if __name__ == '__main__':
# set hard coded data paths
preproc_root_dir = '/volatile/home/edohmato/openfmri_pypreproc_runs'
data_root_dir = '/neurospin/tmp/havoc/openfmri_raw'
out_root_dir = '/volatile/protocols/glm_open'
# more data path business
ds_id = 'ds052' # XXX ds011 has have model101...
model_id = 'model001'
ds_name = datasets[ds_id].lower().replace(' ', '_')
data_dir = os.path.join(data_root_dir, ds_name, ds_id)
preproc_dir = os.path.join(preproc_root_dir, ds_id)
out_dir = os.path.join(out_root_dir, ds_name, ds_id)
# load preproc data
preproc_data, motion_params = load_preproc_data(
preproc_dir)
# load glm params
glm_params = load_glm_params(data_dir, model_id,
subject_ids=preproc_data.keys(),
motion_params=motion_params,
)
# apply glm
apply_glm(out_dir, preproc_data, glm_params, n_jobs=-1)
