def test_RobustStatisticsSegmenter_outputs():
output_map = dict(segmentedImageFileName=dict(position=-1, ), )
outputs = RobustStatisticsSegmenter.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_RobustStatisticsSegmenter_outputs():
output_map = dict(segmentedImageFileName=dict(position=-1,
),
)
outputs = RobustStatisticsSegmenter.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_RobustStatisticsSegmenter_inputs():
input_map = dict(
args=dict(argstr='%s', ),
curvatureWeight=dict(argstr='--curvatureWeight %f', ),
environ=dict(
nohash=True,
usedefault=True,
),
expectedVolume=dict(argstr='--expectedVolume %f', ),
ignore_exception=dict(
nohash=True,
usedefault=True,
),
intensityHomogeneity=dict(argstr='--intensityHomogeneity %f', ),
labelImageFileName=dict(
argstr='%s',
position=-2,
),
labelValue=dict(argstr='--labelValue %d', ),
maxRunningTime=dict(argstr='--maxRunningTime %f', ),
originalImageFileName=dict(
argstr='%s',
position=-3,
),
segmentedImageFileName=dict(
argstr='%s',
hash_files=False,
position=-1,
),
terminal_output=dict(
mandatory=True,
nohash=True,
),
)
inputs = RobustStatisticsSegmenter.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_RobustStatisticsSegmenter_inputs():
input_map = dict(args=dict(argstr='%s',
),
curvatureWeight=dict(argstr='--curvatureWeight %f',
),
environ=dict(nohash=True,
usedefault=True,
),
expectedVolume=dict(argstr='--expectedVolume %f',
),
ignore_exception=dict(nohash=True,
usedefault=True,
),
intensityHomogeneity=dict(argstr='--intensityHomogeneity %f',
),
labelImageFileName=dict(argstr='%s',
position=-2,
),
labelValue=dict(argstr='--labelValue %d',
),
maxRunningTime=dict(argstr='--maxRunningTime %f',
),
originalImageFileName=dict(argstr='%s',
position=-3,
),
segmentedImageFileName=dict(argstr='%s',
hash_files=False,
position=-1,
),
terminal_output=dict(mandatory=True,
nohash=True,
),
)
inputs = RobustStatisticsSegmenter.input_spec()
for key, metadata in input_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(inputs.traits()[key], metakey), value
