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
