def test_SmoothTessellation_outputs():
output_map = dict(surface=dict(), )
outputs = SmoothTessellation.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_SmoothTessellation_inputs():
input_map = dict(
args=dict(argstr='%s', ),
curvature_averaging_iterations=dict(
argstr='-a %d',
position=-1,
usedefault=True,
),
disable_estimates=dict(argstr='-nw', ),
environ=dict(
nohash=True,
usedefault=True,
),
gaussian_curvature_norm_steps=dict(
argstr='%d ',
position=4,
),
gaussian_curvature_smoothing_steps=dict(
argstr='%d',
position=5,
),
ignore_exception=dict(
nohash=True,
usedefault=True,
),
in_file=dict(
argstr='%s',
mandatory=True,
position=1,
),
normalize_area=dict(argstr='-area', ),
out_area_file=dict(argstr='-b %s', ),
out_curvature_file=dict(argstr='-c %s', ),
out_file=dict(
argstr='%s',
genfile=True,
position=2,
),
smoothing_iterations=dict(
argstr='-n %d',
position=-2,
usedefault=True,
),
snapshot_writing_iterations=dict(argstr='-w %d', ),
subjects_dir=dict(),
terminal_output=dict(
mandatory=True,
nohash=True,
),
use_gaussian_curvature_smoothing=dict(
argstr='-g',
position=3,
),
use_momentum=dict(argstr='-m', ),
)
inputs = SmoothTessellation.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_SmoothTessellation_outputs():
output_map = dict(surface=dict(),
)
outputs = SmoothTessellation.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_SmoothTessellation_inputs():
input_map = dict(ignore_exception=dict(nohash=True,
usedefault=True,
),
smoothing_iterations=dict(position=-2,
argstr='-n %d',
usedefault=True,
),
normalize_area=dict(argstr='-area',
),
snapshot_writing_iterations=dict(argstr='-w %d',
),
out_file=dict(position=2,
genfile=True,
argstr='%s',
),
disable_estimates=dict(argstr='-nw',
),
out_area_file=dict(argstr='-b %s',
),
args=dict(argstr='%s',
),
use_gaussian_curvature_smoothing=dict(position=3,
argstr='-g',
),
out_curvature_file=dict(argstr='-c %s',
),
curvature_averaging_iterations=dict(position=-1,
argstr='-a %d',
usedefault=True,
),
terminal_output=dict(mandatory=True,
nohash=True,
),
environ=dict(nohash=True,
usedefault=True,
),
in_file=dict(position=1,
mandatory=True,
argstr='%s',
),
gaussian_curvature_smoothing_steps=dict(position=5,
argstr='%d',
),
subjects_dir=dict(),
gaussian_curvature_norm_steps=dict(position=4,
argstr='%d ',
),
use_momentum=dict(argstr='-m',
),
)
inputs = SmoothTessellation.input_spec()
for key, metadata in input_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(inputs.traits()[key], metakey), value
