Пример #1
0
def test_DARTELNorm2MNI_outputs():
    output_map = dict(normalization_parameter_file=dict(),
    normalized_files=dict(),
    )
    outputs = DARTELNorm2MNI.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
0
def test_DARTELNorm2MNI_outputs():
    output_map = dict(
        normalization_parameter_file=dict(),
        normalized_files=dict(),
    )
    outputs = DARTELNorm2MNI.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 #3
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def test_DARTELNorm2MNI_inputs():
    input_map = dict(
        apply_to_files=dict(
            copyfile=False,
            field='mni_norm.data.subjs.images',
            mandatory=True,
        ),
        bounding_box=dict(field='mni_norm.bb', ),
        flowfield_files=dict(
            field='mni_norm.data.subjs.flowfields',
            mandatory=True,
        ),
        fwhm=dict(field='mni_norm.fwhm', ),
        ignore_exception=dict(
            nohash=True,
            usedefault=True,
        ),
        matlab_cmd=dict(),
        mfile=dict(usedefault=True, ),
        modulate=dict(field='mni_norm.preserve', ),
        paths=dict(),
        template_file=dict(
            copyfile=False,
            field='mni_norm.template',
            mandatory=True,
        ),
        use_mcr=dict(),
        use_v8struct=dict(
            min_ver='8',
            usedefault=True,
        ),
        voxel_size=dict(field='mni_norm.vox', ),
    )
    inputs = DARTELNorm2MNI.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_DARTELNorm2MNI_inputs():
    input_map = dict(apply_to_files=dict(copyfile=False,
    field='mni_norm.data.subjs.images',
    mandatory=True,
    ),
    bounding_box=dict(field='mni_norm.bb',
    ),
    flowfield_files=dict(field='mni_norm.data.subjs.flowfields',
    mandatory=True,
    ),
    fwhm=dict(field='mni_norm.fwhm',
    ),
    ignore_exception=dict(nohash=True,
    usedefault=True,
    ),
    matlab_cmd=dict(),
    mfile=dict(usedefault=True,
    ),
    modulate=dict(field='mni_norm.preserve',
    ),
    paths=dict(),
    template_file=dict(copyfile=False,
    field='mni_norm.template',
    mandatory=True,
    ),
    use_mcr=dict(),
    use_v8struct=dict(min_ver='8',
    usedefault=True,
    ),
    voxel_size=dict(field='mni_norm.vox',
    ),
    )
    inputs = DARTELNorm2MNI.input_spec()

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