How to use the tweakwcs.linearfit.iter_linear_fit function in tweakwcs

ref_idx = self._mref_idx

        refxy = refxy[ref_idx]

        # process weights:
        if 'weight' in self._catalog.colnames:
            im_weight = np.asarray(self._catalog['weight'])[minput_idx]
        else:
            im_weight = None

        if 'weight' in refcat.catalog.colnames:
            ref_weight = np.asarray(refcat.catalog['weight'])[ref_idx]
        else:
            ref_weight = None

        fit = iter_linear_fit(
            refxy, im_xyref, ref_weight, im_weight,
            fitgeom=fitgeom, nclip=nclip, sigma=sigma, center=None
        )

        # re-compute shifts for the center at (0, 0):
        fit['shift_ld'] += fit['center_ld'] - np.dot(fit['center_ld'], fit['matrix_ld'].T)
        fit['shift'] = fit['shift_ld'].astype(np.double)

        xy_fit = fit['shift'] + np.dot(im_xyref[fit['fitmask']], fit['matrix'].T)

        fit['fit_xy'] = xy_fit
        fit['fit_RA'], fit['fit_DEC'] = tanplane_wcs.tanp_to_world(*(xy_fit.T))

        log.info("Computed '{:s}' fit for {}:".format(fitgeom, self.name))
        if fitgeom == 'shift':
            log.info("XSH: {:.6g}  YSH: {:.6g}".format(*fit['shift']))