def test_BRAINSConstellationModeler_outputs():
output_map = dict(outputModel=dict(),
resultsDir=dict(),
)
outputs = BRAINSConstellationModeler.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_BRAINSConstellationModeler_outputs():
output_map = dict(
outputModel=dict(),
resultsDir=dict(),
)
outputs = BRAINSConstellationModeler.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_BRAINSConstellationModeler_inputs():
input_map = dict(BackgroundFillValue=dict(argstr='--BackgroundFillValue %s',
),
args=dict(argstr='%s',
),
environ=dict(nohash=True,
usedefault=True,
),
ignore_exception=dict(nohash=True,
usedefault=True,
),
inputTrainingList=dict(argstr='--inputTrainingList %s',
),
mspQualityLevel=dict(argstr='--mspQualityLevel %d',
),
numberOfThreads=dict(argstr='--numberOfThreads %d',
),
optimizedLandmarksFilenameExtender=dict(argstr='--optimizedLandmarksFilenameExtender %s',
),
outputModel=dict(argstr='--outputModel %s',
hash_files=False,
),
rescaleIntensities=dict(argstr='--rescaleIntensities ',
),
rescaleIntensitiesOutputRange=dict(argstr='--rescaleIntensitiesOutputRange %s',
sep=',',
),
resultsDir=dict(argstr='--resultsDir %s',
hash_files=False,
),
saveOptimizedLandmarks=dict(argstr='--saveOptimizedLandmarks ',
),
terminal_output=dict(nohash=True,
),
trimRescaledIntensities=dict(argstr='--trimRescaledIntensities %f',
),
verbose=dict(argstr='--verbose ',
),
writedebuggingImagesLevel=dict(argstr='--writedebuggingImagesLevel %d',
),
)
inputs = BRAINSConstellationModeler.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_BRAINSConstellationModeler_inputs():
input_map = dict(
BackgroundFillValue=dict(argstr='--BackgroundFillValue %s', ),
args=dict(argstr='%s', ),
environ=dict(
nohash=True,
usedefault=True,
),
ignore_exception=dict(
nohash=True,
usedefault=True,
),
inputTrainingList=dict(argstr='--inputTrainingList %s', ),
mspQualityLevel=dict(argstr='--mspQualityLevel %d', ),
numberOfThreads=dict(argstr='--numberOfThreads %d', ),
optimizedLandmarksFilenameExtender=dict(
argstr='--optimizedLandmarksFilenameExtender %s', ),
outputModel=dict(
argstr='--outputModel %s',
hash_files=False,
),
rescaleIntensities=dict(argstr='--rescaleIntensities ', ),
rescaleIntensitiesOutputRange=dict(
argstr='--rescaleIntensitiesOutputRange %s',
sep=',',
),
resultsDir=dict(
argstr='--resultsDir %s',
hash_files=False,
),
saveOptimizedLandmarks=dict(argstr='--saveOptimizedLandmarks ', ),
terminal_output=dict(nohash=True, ),
trimRescaledIntensities=dict(argstr='--trimRescaledIntensities %f', ),
verbose=dict(argstr='--verbose ', ),
writedebuggingImagesLevel=dict(
argstr='--writedebuggingImagesLevel %d', ),
)
inputs = BRAINSConstellationModeler.input_spec()
for key, metadata in input_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(inputs.traits()[key], metakey), value