def test_VBMSegment_outputs():
output_map = dict(bias_corrected_images=dict(),
dartel_input_images=dict(),
forward_deformation_field=dict(),
inverse_deformation_field=dict(),
jacobian_determinant_images=dict(),
modulated_class_images=dict(),
native_class_images=dict(),
normalized_bias_corrected_images=dict(),
normalized_class_images=dict(),
pve_label_native_images=dict(),
pve_label_normalized_images=dict(),
pve_label_registered_images=dict(),
transformation_mat=dict(),
)
outputs = VBMSegment.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_VBMSegment_outputs():
output_map = dict(
bias_corrected_images=dict(),
dartel_input_images=dict(),
forward_deformation_field=dict(),
inverse_deformation_field=dict(),
jacobian_determinant_images=dict(),
modulated_class_images=dict(),
native_class_images=dict(),
normalized_bias_corrected_images=dict(),
normalized_class_images=dict(),
pve_label_native_images=dict(),
pve_label_normalized_images=dict(),
pve_label_registered_images=dict(),
transformation_mat=dict(),
)
outputs = VBMSegment.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_VBMSegment_inputs():
input_map = dict(
bias_corrected_affine=dict(
field='estwrite.output.bias.affine',
usedefault=True,
),
bias_corrected_native=dict(
field='estwrite.output.bias.native',
usedefault=True,
),
bias_corrected_normalized=dict(
field='estwrite.output.bias.warped',
usedefault=True,
),
bias_fwhm=dict(
field='estwrite.opts.biasfwhm',
usedefault=True,
),
bias_regularization=dict(
field='estwrite.opts.biasreg',
usedefault=True,
),
cleanup_partitions=dict(
field='estwrite.extopts.cleanup',
usedefault=True,
),
csf_dartel=dict(
field='estwrite.output.CSF.dartel',
usedefault=True,
),
csf_modulated_normalized=dict(
field='estwrite.output.CSF.modulated',
usedefault=True,
),
csf_native=dict(
field='estwrite.output.CSF.native',
usedefault=True,
),
csf_normalized=dict(
field='estwrite.output.CSF.warped',
usedefault=True,
),
dartel_template=dict(
field='estwrite.extopts.dartelwarp.normhigh.darteltpm', ),
deformation_field=dict(
field='estwrite.output.warps',
usedefault=True,
),
display_results=dict(
field='estwrite.extopts.print',
usedefault=True,
),
gaussians_per_class=dict(usedefault=True, ),
gm_dartel=dict(
field='estwrite.output.GM.dartel',
usedefault=True,
),
gm_modulated_normalized=dict(
field='estwrite.output.GM.modulated',
usedefault=True,
),
gm_native=dict(
field='estwrite.output.GM.native',
usedefault=True,
),
gm_normalized=dict(
field='estwrite.output.GM.warped',
usedefault=True,
),
ignore_exception=dict(
nohash=True,
usedefault=True,
),
in_files=dict(
copyfile=False,
field='estwrite.data',
mandatory=True,
),
jacobian_determinant=dict(
field='estwrite.jacobian.warped',
usedefault=True,
),
matlab_cmd=dict(),
mfile=dict(usedefault=True, ),
mrf_weighting=dict(
field='estwrite.extopts.mrf',
usedefault=True,
),
paths=dict(),
pve_label_dartel=dict(
field='estwrite.output.label.dartel',
usedefault=True,
),
pve_label_native=dict(
field='estwrite.output.label.native',
usedefault=True,
),
pve_label_normalized=dict(
field='estwrite.output.label.warped',
usedefault=True,
),
sampling_distance=dict(
field='estwrite.opts.samp',
usedefault=True,
),
spatial_normalization=dict(usedefault=True, ),
tissues=dict(field='estwrite.tpm', ),
use_mcr=dict(),
use_sanlm_denoising_filter=dict(
field='estwrite.extopts.sanlm',
usedefault=True,
),
use_v8struct=dict(
min_ver='8',
usedefault=True,
),
warping_regularization=dict(
field='estwrite.opts.warpreg',
usedefault=True,
),
wm_dartel=dict(
field='estwrite.output.WM.dartel',
usedefault=True,
),
wm_modulated_normalized=dict(
field='estwrite.output.WM.modulated',
usedefault=True,
),
wm_native=dict(
field='estwrite.output.WM.native',
usedefault=True,
),
wm_normalized=dict(
field='estwrite.output.WM.warped',
usedefault=True,
),
)
inputs = VBMSegment.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_VBMSegment_inputs():
input_map = dict(bias_corrected_affine=dict(field='estwrite.output.bias.affine',
usedefault=True,
),
bias_corrected_native=dict(field='estwrite.output.bias.native',
usedefault=True,
),
bias_corrected_normalized=dict(field='estwrite.output.bias.warped',
usedefault=True,
),
bias_fwhm=dict(field='estwrite.opts.biasfwhm',
usedefault=True,
),
bias_regularization=dict(field='estwrite.opts.biasreg',
usedefault=True,
),
cleanup_partitions=dict(field='estwrite.extopts.cleanup',
usedefault=True,
),
csf_dartel=dict(field='estwrite.output.CSF.dartel',
usedefault=True,
),
csf_modulated_normalized=dict(field='estwrite.output.CSF.modulated',
usedefault=True,
),
csf_native=dict(field='estwrite.output.CSF.native',
usedefault=True,
),
csf_normalized=dict(field='estwrite.output.CSF.warped',
usedefault=True,
),
dartel_template=dict(field='estwrite.extopts.dartelwarp.normhigh.darteltpm',
),
deformation_field=dict(field='estwrite.output.warps',
usedefault=True,
),
display_results=dict(field='estwrite.extopts.print',
usedefault=True,
),
gaussians_per_class=dict(usedefault=True,
),
gm_dartel=dict(field='estwrite.output.GM.dartel',
usedefault=True,
),
gm_modulated_normalized=dict(field='estwrite.output.GM.modulated',
usedefault=True,
),
gm_native=dict(field='estwrite.output.GM.native',
usedefault=True,
),
gm_normalized=dict(field='estwrite.output.GM.warped',
usedefault=True,
),
ignore_exception=dict(nohash=True,
usedefault=True,
),
in_files=dict(copyfile=False,
field='estwrite.data',
mandatory=True,
),
jacobian_determinant=dict(field='estwrite.jacobian.warped',
usedefault=True,
),
matlab_cmd=dict(),
mfile=dict(usedefault=True,
),
mrf_weighting=dict(field='estwrite.extopts.mrf',
usedefault=True,
),
paths=dict(),
pve_label_dartel=dict(field='estwrite.output.label.dartel',
usedefault=True,
),
pve_label_native=dict(field='estwrite.output.label.native',
usedefault=True,
),
pve_label_normalized=dict(field='estwrite.output.label.warped',
usedefault=True,
),
sampling_distance=dict(field='estwrite.opts.samp',
usedefault=True,
),
spatial_normalization=dict(usedefault=True,
),
tissues=dict(field='estwrite.tpm',
),
use_mcr=dict(),
use_sanlm_denoising_filter=dict(field='estwrite.extopts.sanlm',
usedefault=True,
),
use_v8struct=dict(min_ver='8',
usedefault=True,
),
warping_regularization=dict(field='estwrite.opts.warpreg',
usedefault=True,
),
wm_dartel=dict(field='estwrite.output.WM.dartel',
usedefault=True,
),
wm_modulated_normalized=dict(field='estwrite.output.WM.modulated',
usedefault=True,
),
wm_native=dict(field='estwrite.output.WM.native',
usedefault=True,
),
wm_normalized=dict(field='estwrite.output.WM.warped',
usedefault=True,
),
)
inputs = VBMSegment.input_spec()
for key, metadata in input_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(inputs.traits()[key], metakey), value
