# AUTO-GENERATED by tools/checkspecs.py - DO NOT EDIT
from __future__ import unicode_literals
from ..brainsuite import Bfc


def test_Bfc_inputs():
    input_map = dict(args=dict(argstr='%s',
    ),
    biasEstimateConvergenceThreshold=dict(argstr='--beps %f',
    ),
    biasEstimateSpacing=dict(argstr='-s %d',
    ),
    biasFieldEstimatesOutputPrefix=dict(argstr='--biasprefix %s',
    ),
    biasRange=dict(argstr='%s',
    ),
    controlPointSpacing=dict(argstr='-c %d',
    ),
    convergenceThreshold=dict(argstr='--eps %f',
    ),
    correctWholeVolume=dict(argstr='--extrapolate',
    ),
    correctedImagesOutputPrefix=dict(argstr='--prefix %s',
    ),
    correctionScheduleFile=dict(argstr='--schedule %s',
    ),
    environ=dict(nohash=True,
    usedefault=True,
    ),
    histogramRadius=dict(argstr='-r %d',
    ),
    histogramType=dict(argstr='%s',
    ),
    ignore_exception=dict(nohash=True,
    usedefault=True,
    ),
    inputMRIFile=dict(argstr='-i %s',
    mandatory=True,
    ),
    inputMaskFile=dict(argstr='-m %s',
    hash_files=False,
    ),
    intermediate_file_type=dict(argstr='%s',
    ),
    iterativeMode=dict(argstr='--iterate',
    ),
    maxBias=dict(argstr='-U %f',
    usedefault=True,
    ),
    minBias=dict(argstr='-L %f',
    usedefault=True,
    ),
    outputBiasField=dict(argstr='--bias %s',
    hash_files=False,
    ),
    outputMRIVolume=dict(argstr='-o %s',
    genfile=True,
    hash_files=False,
    ),
    outputMaskedBiasField=dict(argstr='--maskedbias %s',
    hash_files=False,
    ),
    splineLambda=dict(argstr='-w %f',
    ),
    terminal_output=dict(deprecated='1.0.0',
    nohash=True,
    ),
    timer=dict(argstr='--timer',
    ),
    verbosityLevel=dict(argstr='-v %d',
    ),
    )
    inputs = Bfc.input_spec()

    for key, metadata in list(input_map.items()):
        for metakey, value in list(metadata.items()):
            assert getattr(inputs.traits()[key], metakey) == value


def test_Bfc_outputs():
    output_map = dict(correctionScheduleFile=dict(),
    outputBiasField=dict(),
    outputMRIVolume=dict(),
    outputMaskedBiasField=dict(),
    )
    outputs = Bfc.output_spec()

    for key, metadata in list(output_map.items()):
        for metakey, value in list(metadata.items()):
            assert getattr(outputs.traits()[key], metakey) == value
