How to use the specutils.wcs.specwcs.Spectrum1DPolynomialWCS function in specutils

raise FITSWCSSpectrum1DError

    if wcs_info.affine_transform_dict['crval'][spectral_axis] is None:
        raise FITSWCSSpectrum1DError
    else:
        dispersion_start = wcs_info.affine_transform_dict['crval'][spectral_axis]

    pixel_offset = wcs_info.affine_transform_dict['crpix'][spectral_axis] or 1
    pixel_offset -= 1

    dispersion_unit = wcs_info.units[spectral_axis] or dispersion_unit

    if None in [dispersion_start, dispersion_delta, pixel_offset]:
        raise FITSWCSSpectrum1DError
    dispersion_start += -pixel_offset * dispersion_delta
    return specwcs.Spectrum1DPolynomialWCS(degree=1, unit=dispersion_unit,
                                           c0=dispersion_start,
                                           c1=dispersion_delta)

if dispersion_unit is None:
        dispersion_unit = wcs_info.wcs_attributes[0]['units']

    multispec_dict = _parse_multispec_dict(wcs_info.wcs_attributes[1])
    wcs_dict = OrderedDict()
    for spec_key in multispec_dict:
        single_spec_dict = multispec_dict[spec_key]
        if single_spec_dict['dispersion_type'] == 1:
            #log-linear dispersion
            log = True
        else:
            log = False

        if single_spec_dict['dispersion_type'] in [0, 1]:
            #linear or log-linear dispersion
            dispersion_wcs = specwcs.Spectrum1DPolynomialWCS(
                degree=1, c0=single_spec_dict["dispersion0"],
                c1=single_spec_dict["average_dispersion_delta"])

        else:
            # single_spec_dict['dispersion_type'] == 2
            dispersion_wcs = specwcs.WeightedCombinationWCS()
            for function_dict in single_spec_dict["functions"]:
                if function_dict['type'] == 'legendre':
                    ##### @embray can you figure out if that's the only way to
                    ##  instantiate a polynomial (with c0=xx, c1=xx, ...)?

                    coefficients = dict([('c{:d}'.format(i),
                                        function_dict['coefficients'][i])
                                        for i in range(function_dict['order'])])

                    wcs = specwcs.Spectrum1DIRAFLegendreWCS(

def evaluate(self, pixel_indices, *coeffs):
        return super(Spectrum1DPolynomialWCS, self).evaluate(pixel_indices,
                                                            *coeffs) * self.unit