Ejemplo n.º 1
0
def test_GenerateLabelMapFromProbabilityMap_outputs():
    output_map = dict(outputLabelVolume=dict(), )
    outputs = GenerateLabelMapFromProbabilityMap.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_GenerateLabelMapFromProbabilityMap_outputs():
    output_map = dict(outputLabelVolume=dict(),
    )
    outputs = GenerateLabelMapFromProbabilityMap.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_GenerateLabelMapFromProbabilityMap_inputs():
    input_map = dict(args=dict(argstr='%s',
    ),
    environ=dict(nohash=True,
    usedefault=True,
    ),
    ignore_exception=dict(nohash=True,
    usedefault=True,
    ),
    inputVolumes=dict(argstr='--inputVolumes %s...',
    ),
    numberOfThreads=dict(argstr='--numberOfThreads %d',
    ),
    outputLabelVolume=dict(argstr='--outputLabelVolume %s',
    hash_files=False,
    ),
    terminal_output=dict(nohash=True,
    ),
    )
    inputs = GenerateLabelMapFromProbabilityMap.input_spec()

    for key, metadata in input_map.items():
        for metakey, value in metadata.items():
            yield assert_equal, getattr(inputs.traits()[key], metakey), value
Ejemplo n.º 4
0
def test_GenerateLabelMapFromProbabilityMap_inputs():
    input_map = dict(
        args=dict(argstr='%s', ),
        environ=dict(
            nohash=True,
            usedefault=True,
        ),
        ignore_exception=dict(
            nohash=True,
            usedefault=True,
        ),
        inputVolumes=dict(argstr='--inputVolumes %s...', ),
        numberOfThreads=dict(argstr='--numberOfThreads %d', ),
        outputLabelVolume=dict(
            argstr='--outputLabelVolume %s',
            hash_files=False,
        ),
        terminal_output=dict(nohash=True, ),
    )
    inputs = GenerateLabelMapFromProbabilityMap.input_spec()

    for key, metadata in input_map.items():
        for metakey, value in metadata.items():
            yield assert_equal, getattr(inputs.traits()[key], metakey), value