def test_create_surface_pipe(): # params params = { "nii_to_mesh_pipe": { "split_hemi_pipe": {}, } } # params_template template_name = "haiko89_template" template_dir = load_test_data(template_name) params_template = format_template(template_dir, template_name) # running workflow segment_pnh = create_nii_to_mesh_pipe(params=parse_key( params, "nii_to_mesh_pipe"), params_template=params_template, name="nii_to_mesh_pipe") segment_pnh.base_dir = data_path segment_pnh.write_graph(graph2use="colored") assert op.exists(op.join(data_path, "nii_to_mesh_pipe", "graph.png"))
def test_create_long_multi_preparation_pipe(): params = { "long_multi_preparation_pipe": { "mapnode_prep_T1": { "crop": { "args": [ "Should not be used, specific to all", "Should not be used, specific to all" ] }, "norm_intensity": { "dimension": [3, 3], "bspline_fitting_distance": [200, 200], "n_iterations": [[50, 50, 40, 30], [50, 50, 40, 30]], "convergence_threshold": [0.00000001, 0.00000001], "shrink_factor": [2, 2], "args": ["-r 0 --verbose 1", "-r 0 --verbose 1"] }, "denoise": { "shrink_factor": [3, 3] } }, "mapnode_prep_T2": { "crop": { "args": ["Should not be used, specific to all"] }, "norm_intensity": { "dimension": [3], "bspline_fitting_distance": [200], "n_iterations": [50, 50, 40, 30], "convergence_threshold": [0.00000001], "shrink_factor": [2], "args": ["-r 0 --verbose 1"] }, "denoise": { "shrink_factor": [3] } }, "align_T2_on_T1": { "dof": 6, "cost": "normmi" } } } # running workflow segment_pnh = create_long_multi_preparation_pipe( params=parse_key(params, "long_multi_preparation_pipe"), name="long_multi_preparation_pipe") segment_pnh.base_dir = data_path segment_pnh.write_graph(graph2use="colored") assert op.exists( op.join(data_path, "long_multi_preparation_pipe", "graph.png"))
def test_create_long_single_preparation_pipe(): params = { "long_single_preparation_pipe": { "prep_T1": { "crop": { "args": "should be defined in indiv" }, "norm_intensity": { "dimension": 3, "bspline_fitting_distance": 200, "n_iterations": [50, 50, 40, 30], "convergence_threshold": 0.00000001, "shrink_factor": 2, "args": "-r 0 --verbose 1" }, "denoise": { "shrink_factor": 1 } }, "prep_T2": { "crop": { "args": "should be defined in indiv" }, "norm_intensity": { "dimension": 3, "bspline_fitting_distance": 200, "n_iterations": [50, 50, 40, 30], "convergence_threshold": 0.00000001, "shrink_factor": 2, "args": "-r 0 --verbose 1" }, "denoise": { "shrink_factor": 1 } }, "align_T2_on_T1": { "dof": 6, "cost": "normmi" } } } # running workflow segment_pnh = create_long_single_preparation_pipe( params=parse_key(params, "long_single_preparation_pipe"), name="long_single_preparation_pipe") segment_pnh.base_dir = data_path segment_pnh.write_graph(graph2use="colored") assert op.exists( op.join(data_path, "long_single_preparation_pipe", "graph.png"))
def test_MapNodeParams(): params = {"crop": {"args": "88 144 14 180 27 103"}} crop_bb = MapNodeParams(fsl.ExtractROI(), name='crop_bb', params=parse_key(params, "crop"), iterfield=["in_file"]) crop_bb.inputs.in_file = [T1_file, T2_file] with pytest.raises(ValueError): crop_bb.run()
def test_create_short_manual_preparation_pipe(): params = {"short_preparation_pipe": {"crop": {"args": ""}}} # running workflow segment_pnh = create_short_preparation_pipe( params=parse_key(params, "short_preparation_pipe"), name="short_manual_preparation_pipe") segment_pnh.base_dir = data_path segment_pnh.write_graph(graph2use="colored") assert op.exists( op.join(data_path, "short_manual_preparation_pipe", "graph.png"))
def test_create_short_auto_reorient_preparation_pipe(): params = { "short_preparation_pipe": { "reorient": { "new_dims": "x z -y" }, "bet_crop": {} } } # running workflow segment_pnh = create_short_preparation_pipe( params=parse_key(params, "short_preparation_pipe"), name="short_auto_reorient_preparation_pipe") segment_pnh.base_dir = data_path segment_pnh.write_graph(graph2use="colored") assert op.exists( op.join(data_path, "short_auto_reorient_preparation_pipe", "graph.png"))
def test_parse_key_empty(): params = {} val = parse_key(params, "test") assert not val
def test_parse_key_Undefined(): params = traits.Undefined val = parse_key(params, "test") assert not val