Example #1
0
def test_Tensor2ApparentDiffusion_outputs():
    output_map = dict(ADC=dict(), )
    outputs = Tensor2ApparentDiffusion.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_Tensor2ApparentDiffusion_inputs():
    input_map = dict(args=dict(argstr='%s',
    ),
    debug=dict(argstr='-debug',
    position=1,
    ),
    environ=dict(nohash=True,
    usedefault=True,
    ),
    ignore_exception=dict(nohash=True,
    usedefault=True,
    ),
    in_file=dict(argstr='%s',
    mandatory=True,
    position=-2,
    ),
    out_filename=dict(argstr='%s',
    genfile=True,
    position=-1,
    ),
    quiet=dict(argstr='-quiet',
    position=1,
    ),
    terminal_output=dict(mandatory=True,
    nohash=True,
    ),
    )
    inputs = Tensor2ApparentDiffusion.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_Tensor2ApparentDiffusion_outputs():
    output_map = dict(ADC=dict(),
    )
    outputs = Tensor2ApparentDiffusion.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_Tensor2ApparentDiffusion_inputs():
    input_map = dict(
        args=dict(argstr='%s', ),
        debug=dict(
            argstr='-debug',
            position=1,
        ),
        environ=dict(
            nohash=True,
            usedefault=True,
        ),
        ignore_exception=dict(
            nohash=True,
            usedefault=True,
        ),
        in_file=dict(
            argstr='%s',
            mandatory=True,
            position=-2,
        ),
        out_filename=dict(
            argstr='%s',
            genfile=True,
            position=-1,
        ),
        quiet=dict(
            argstr='-quiet',
            position=1,
        ),
        terminal_output=dict(
            mandatory=True,
            nohash=True,
        ),
    )
    inputs = Tensor2ApparentDiffusion.input_spec()

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