def test_DARTELNorm2MNI_outputs():
output_map = dict(normalization_parameter_file=dict(),
normalized_files=dict(),
)
outputs = DARTELNorm2MNI.output_spec()
for key, metadata in output_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(outputs.traits()[key], metakey), value
def test_DARTELNorm2MNI_outputs():
output_map = dict(
normalization_parameter_file=dict(),
normalized_files=dict(),
)
outputs = DARTELNorm2MNI.output_spec()
for key, metadata in output_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(outputs.traits()[key], metakey), value
def test_DARTELNorm2MNI_inputs():
input_map = dict(
apply_to_files=dict(
copyfile=False,
field='mni_norm.data.subjs.images',
mandatory=True,
),
bounding_box=dict(field='mni_norm.bb', ),
flowfield_files=dict(
field='mni_norm.data.subjs.flowfields',
mandatory=True,
),
fwhm=dict(field='mni_norm.fwhm', ),
ignore_exception=dict(
nohash=True,
usedefault=True,
),
matlab_cmd=dict(),
mfile=dict(usedefault=True, ),
modulate=dict(field='mni_norm.preserve', ),
paths=dict(),
template_file=dict(
copyfile=False,
field='mni_norm.template',
mandatory=True,
),
use_mcr=dict(),
use_v8struct=dict(
min_ver='8',
usedefault=True,
),
voxel_size=dict(field='mni_norm.vox', ),
)
inputs = DARTELNorm2MNI.input_spec()
for key, metadata in input_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(inputs.traits()[key], metakey), value
def test_DARTELNorm2MNI_inputs():
input_map = dict(apply_to_files=dict(copyfile=False,
field='mni_norm.data.subjs.images',
mandatory=True,
),
bounding_box=dict(field='mni_norm.bb',
),
flowfield_files=dict(field='mni_norm.data.subjs.flowfields',
mandatory=True,
),
fwhm=dict(field='mni_norm.fwhm',
),
ignore_exception=dict(nohash=True,
usedefault=True,
),
matlab_cmd=dict(),
mfile=dict(usedefault=True,
),
modulate=dict(field='mni_norm.preserve',
),
paths=dict(),
template_file=dict(copyfile=False,
field='mni_norm.template',
mandatory=True,
),
use_mcr=dict(),
use_v8struct=dict(min_ver='8',
usedefault=True,
),
voxel_size=dict(field='mni_norm.vox',
),
)
inputs = DARTELNorm2MNI.input_spec()
for key, metadata in input_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(inputs.traits()[key], metakey), value
