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",