def test_BRAINSCut_outputs():
output_map = dict()
outputs = BRAINSCut.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_BRAINSCut_inputs():
input_map = dict(NoTrainingVectorShuffling=dict(argstr='--NoTrainingVectorShuffling ',
),
applyModel=dict(argstr='--applyModel ',
),
args=dict(argstr='%s',
),
computeSSEOn=dict(argstr='--computeSSEOn ',
),
createVectors=dict(argstr='--createVectors ',
),
environ=dict(nohash=True,
usedefault=True,
),
generateProbability=dict(argstr='--generateProbability ',
),
histogramEqualization=dict(argstr='--histogramEqualization ',
),
ignore_exception=dict(nohash=True,
usedefault=True,
),
method=dict(argstr='--method %s',
),
modelConfigurationFilename=dict(argstr='--modelConfigurationFilename %s',
),
modelFilename=dict(argstr='--modelFilename %s',
),
multiStructureThreshold=dict(argstr='--multiStructureThreshold ',
),
netConfiguration=dict(argstr='--netConfiguration %s',
),
numberOfTrees=dict(argstr='--numberOfTrees %d',
),
randomTreeDepth=dict(argstr='--randomTreeDepth %d',
),
terminal_output=dict(nohash=True,
),
trainModel=dict(argstr='--trainModel ',
),
trainModelStartIndex=dict(argstr='--trainModelStartIndex %d',
),
validate=dict(argstr='--validate ',
),
verbose=dict(argstr='--verbose %d',
),
)
inputs = BRAINSCut.input_spec()
for key, metadata in input_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(inputs.traits()[key], metakey), value
