def METHOD_NAME():
    input_map = dict(
        absolute_threshold=dict(
            argstr="-Thresh %f %s",
            extensions=None,
            name_source="in_file",
            suffix="_thresh",
            xor=(
                "absolute_threshold",
                "var_absolute_threshold",
                "var_absolute_threshold_normalize",
            ),
        ),
        args=dict(
            argstr="%s",
        ),
        automask=dict(
            argstr="-automask",
        ),
        average_expr=dict(
            argstr="-Aexpr %s %s",
            extensions=None,
            name_source="in_file",
            suffix="_aexpr",
            xor=("average_expr", "average_expr_nonzero", "sum_expr"),
        ),
        average_expr_nonzero=dict(
            argstr="-Cexpr %s %s",
            extensions=None,
            name_source="in_file",
            suffix="_cexpr",
            xor=("average_expr", "average_expr_nonzero", "sum_expr"),
        ),
        bandpass=dict(
            argstr="-bpass %f %f",
        ),
        blur_fwhm=dict(
            argstr="-Gblur %f",
        ),
        correlation_maps=dict(
            argstr="-CorrMap %s",
            extensions=None,
            name_source="in_file",
        ),
        correlation_maps_masked=dict(
            argstr="-CorrMask %s",
            extensions=None,
            name_source="in_file",
        ),
        environ=dict(
            nohash=True,
            usedefault=True,
        ),
        expr=dict(),
        histogram=dict(
            argstr="-Hist %d %s",
            extensions=None,
            name_source="in_file",
            suffix="_hist",
        ),
        histogram_bin_numbers=dict(),
        in_file=dict(
            argstr="-input %s",
            copyfile=False,
            extensions=None,
            mandatory=True,
        ),
        mask=dict(
            argstr="-mask %s",
            extensions=None,
        ),
        mean_file=dict(
            argstr="-Mean %s",
            extensions=None,
            name_source="in_file",
            suffix="_mean",
        ),
        num_threads=dict(
            nohash=True,
            usedefault=True,
        ),
        out_file=dict(
            argstr="-prefix %s",
            extensions=None,
            name_source=["in_file"],
            name_template="%s_afni",
        ),
        outputtype=dict(),
        pmean=dict(
            argstr="-Pmean %s",
            extensions=None,
            name_source="in_file",
            suffix="_pmean",
        ),
        polort=dict(
            argstr="-polort %d",
        ),
        qmean=dict(
            argstr="-Qmean %s",
            extensions=None,
            name_source="in_file",
            suffix="_qmean",
        ),
        regress_out_timeseries=dict(
            argstr="-ort %s",
            extensions=None,
        ),
        seeds=dict(
            argstr="-seed %s",
            extensions=None,
            xor="seeds_width",
        ),
        seeds_width=dict(
            argstr="-Mseed %f",
            xor="seeds",
        ),
        sum_expr=dict(
            argstr="-Sexpr %s %s",
            extensions=None,
            name_source="in_file",
            suffix="_sexpr",
            xor=("average_expr", "average_expr_nonzero", "sum_expr"),
        ),
        thresholds=dict(),
        var_absolute_threshold=dict(
            argstr="-VarThresh %f %f %f %s",
            extensions=None,
            name_source="in_file",
            suffix="_varthresh",
            xor=(
                "absolute_threshold",
                "var_absolute_threshold",
                "var_absolute_threshold_normalize",
            ),
        ),
        var_absolute_threshold_normalize=dict(
            argstr="-VarThreshN %f %f %f %s",
            extensions=None,
            name_source="in_file",
            suffix="_varthreshn",
            xor=(
                "absolute_threshold",
                "var_absolute_threshold",
                "var_absolute_threshold_normalize",
            ),
        ),
        zmean=dict(
            argstr="-Zmean %s",
            extensions=None,
            name_source="in_file",
            suffix="_zmean",
        ),
    )
    inputs = TCorrMap.input_spec()
    for key, metadata in list(input_map.items()):
        for metakey, value in list(metadata.items()):
            assert getattr(inputs.traits()[key], metakey) == value