analyze_format.set_converter(dicom_format, MrtrixConverter)
analyze_format.set_converter(nifti_format, MrtrixConverter)
analyze_format.set_converter(nifti_gz_format, MrtrixConverter)
analyze_format.set_converter(mrtrix_image_format, MrtrixConverter)
mrtrix_image_format.set_converter(dicom_format, MrtrixConverter)
mrtrix_image_format.set_converter(nifti_format, MrtrixConverter)
mrtrix_image_format.set_converter(nifti_gz_format, MrtrixConverter)
mrtrix_image_format.set_converter(analyze_format, MrtrixConverter)
STD_IMAGE_FORMATS = [dicom_format, nifti_format, nifti_gz_format,
nifti_gz_x_format, analyze_format, mrtrix_image_format]
multi_nifti_gz_format = FileFormat(name='multi_nifti_gz', extension=None,
directory=True, within_dir_exts=['.nii.gz'])
multi_nifti_gz_format.set_converter(zip_format, UnzipConverter)
multi_nifti_gz_format.set_converter(targz_format, UnTarGzConverter)
# Tractography formats
mrtrix_track_format = FileFormat(name='mrtrix_track', extension='.tck')
# Tabular formats
rfile_format = FileFormat(name='rdata', extension='.RData')
tsv_format = FileFormat(name='tab_separated', extension='.tsv')
# matlab_format = FileFormat(name='matlab', extension='.mat')
csv_format = FileFormat(name='comma_separated', extension='.csv')
text_matrix_format = FileFormat(name='text_matrix', extension='.mat')
# Diffusion gradient-table data formats
fsl_bvecs_format = FileFormat(name='fsl_bvecs', extension='.bvec')
fsl_bvals_format = FileFormat(name='fsl_bvals', extension='.bval')
mrtrix_image_format.set_converter(dicom_format, MrtrixConverter)
mrtrix_image_format.set_converter(nifti_format, MrtrixConverter)
mrtrix_image_format.set_converter(nifti_gz_format, MrtrixConverter)
mrtrix_image_format.set_converter(analyze_format, MrtrixConverter)
STD_IMAGE_FORMATS = [
dicom_format, nifti_format, nifti_gz_format, nifti_gz_x_format,
analyze_format, mrtrix_image_format
]
multi_nifti_gz_format = FileFormat(name='multi_nifti_gz',
extension=None,
directory=True,
within_dir_exts=['.nii.gz'])
multi_nifti_gz_format.set_converter(zip_format, UnzipConverter)
multi_nifti_gz_format.set_converter(targz_format, UnTarGzConverter)
# Tractography formats
mrtrix_track_format = FileFormat(name='mrtrix_track', extension='.tck')
# Tabular formats
rfile_format = FileFormat(name='rdata', extension='.RData')
tsv_format = FileFormat(name='tab_separated', extension='.tsv')
# matlab_format = FileFormat(name='matlab', extension='.mat')
csv_format = FileFormat(name='comma_separated', extension='.csv')
text_matrix_format = FileFormat(name='text_matrix', extension='.mat')
# Diffusion gradient-table data formats
fsl_bvecs_format = FileFormat(name='fsl_bvecs', extension='.bvec')
fsl_bvals_format = FileFormat(name='fsl_bvals', extension='.bval')
tree = self.dataset.tree
for subj_id, visits in self.PROJECT_STRUCTURE.items():
for visit_id in visits:
session = tree.subject(subj_id).session(visit_id)
fileset = session.fileset('thousand',
from_analysis=self.STUDY_NAME)
fileset.format = text_format
self.assertContentsEqual(fileset, targets[subj_id][visit_id],
"{}:{}".format(subj_id, visit_id))
test1_format = FileFormat('test1', extension='.t1')
test2_format = FileFormat('test2', extension='.t2')
test3_format = FileFormat('test3', extension='.t3')
test2_format.set_converter(test1_format, IdentityConverter)
class TestInputValidationAnalysis(with_metaclass(AnalysisMetaClass, Analysis)):
add_data_specs = [
InputFilesetSpec('a', (test1_format, test2_format)),
InputFilesetSpec('b', test3_format),
FilesetSpec('c', test2_format, 'identity_pipeline'),
FilesetSpec('d', test3_format, 'identity_pipeline')
]
def identity_pipeline(self, **name_maps):
pipeline = self.new_pipeline(
name='pipeline',
desc="A dummy pipeline used to test analysis input validation",