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