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