def test_N4ITKBiasFieldCorrection_outputs():
output_map = dict(outputbiasfield=dict(),
outputimage=dict(),
)
outputs = N4ITKBiasFieldCorrection.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_N4ITKBiasFieldCorrection_outputs():
output_map = dict(
outputbiasfield=dict(),
outputimage=dict(),
)
outputs = N4ITKBiasFieldCorrection.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_N4ITKBiasFieldCorrection_inputs():
input_map = dict(
args=dict(argstr='%s', ),
bsplineorder=dict(argstr='--bsplineorder %d', ),
convergencethreshold=dict(argstr='--convergencethreshold %f', ),
environ=dict(
nohash=True,
usedefault=True,
),
histogramsharpening=dict(
argstr='--histogramsharpening %s',
sep=',',
),
ignore_exception=dict(
nohash=True,
usedefault=True,
),
inputimage=dict(argstr='--inputimage %s', ),
iterations=dict(
argstr='--iterations %s',
sep=',',
),
maskimage=dict(argstr='--maskimage %s', ),
meshresolution=dict(
argstr='--meshresolution %s',
sep=',',
),
outputbiasfield=dict(
argstr='--outputbiasfield %s',
hash_files=False,
),
outputimage=dict(
argstr='--outputimage %s',
hash_files=False,
),
shrinkfactor=dict(argstr='--shrinkfactor %d', ),
splinedistance=dict(argstr='--splinedistance %f', ),
terminal_output=dict(
mandatory=True,
nohash=True,
),
weightimage=dict(argstr='--weightimage %s', ),
)
inputs = N4ITKBiasFieldCorrection.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_N4ITKBiasFieldCorrection_inputs():
input_map = dict(args=dict(argstr='%s',
),
bsplineorder=dict(argstr='--bsplineorder %d',
),
convergencethreshold=dict(argstr='--convergencethreshold %f',
),
environ=dict(nohash=True,
usedefault=True,
),
histogramsharpening=dict(argstr='--histogramsharpening %s',
sep=',',
),
ignore_exception=dict(nohash=True,
usedefault=True,
),
inputimage=dict(argstr='--inputimage %s',
),
iterations=dict(argstr='--iterations %s',
sep=',',
),
maskimage=dict(argstr='--maskimage %s',
),
meshresolution=dict(argstr='--meshresolution %s',
sep=',',
),
outputbiasfield=dict(argstr='--outputbiasfield %s',
hash_files=False,
),
outputimage=dict(argstr='--outputimage %s',
hash_files=False,
),
shrinkfactor=dict(argstr='--shrinkfactor %d',
),
splinedistance=dict(argstr='--splinedistance %f',
),
terminal_output=dict(mandatory=True,
nohash=True,
),
weightimage=dict(argstr='--weightimage %s',
),
)
inputs = N4ITKBiasFieldCorrection.input_spec()
for key, metadata in input_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(inputs.traits()[key], metakey), value
