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
Пример #2
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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
Пример #4
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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