PROJECT_ID = 'MRH017'
datasets = {DatasetMatch('coils', zip_format, 'swi_coils')}
visit_ids = visit_ids['MR01']
repository = XnatRepository(cache_dir='/scratch/dq13/xnat_cache3')
if args.cache_project:
project = repository.project(PROJECT_ID,
subject_ids=ids,
visit_ids=visit_ids)
with open(CACHE_PROJECT_PATH, 'w') as f:
pkl.dump(project, f)
else:
with open(CACHE_PROJECT_PATH) as f:
project = pkl.load(f)
repository.cache(PROJECT_ID,
datasets.values(),
subject_ids=ids,
visit_ids=visit_ids)
study = T2StarStudy(name='qsm',
project_id=PROJECT_ID,
repository=repository,
input_datasets=datasets)
study.qsm_pipeline().submit(subject_ids=ids,
visit_ids=visit_ids,
work_dir=WORK_PATH,
email='*****@*****.**',
project=project)
from nianalysis.file_format import dicom_format
from arcana.dataset import DatasetMatch
from arcana.repository.xnat import XnatRepository
repository = XnatRepository()
repository.cache('MRH032', [
Dataset('t1_mprage_sag_p2_iso_1mm', format=dicom_format),
Dataset('t2_tra_tse_320_4mm', format=dicom_format)
],
subject_ids=['MRH032_{:03}'.format(i) for i in range(1, 20)],
visit_ids=['MR01', 'MR03'])