def METHOD_NAME(self):
    fittingSequence = FittingSequence(
        self.kwargs_data_joint,
        self.kwargs_model,
        self.kwargs_constraints,
        self.kwargs_likelihood,
        self.kwargs_params,
    )
    fitting_list = []
    kwargs_align = {
        "n_particles": 20,
        "n_iterations": 40,
        "compute_bands": [False, True],
        "align_offset": True,
        "align_rotation": True,
        "delta_shift": 0.3,
        "delta_rot": 0.5,
    }
    fitting_list.append(["align_images", kwargs_align])
    chain_list = fittingSequence.fit_sequence(fitting_list)
    multi_band_list_new = fittingSequence.multi_band_list
    kwargs_data2_new = multi_band_list_new[1][0]
    ra_shift = kwargs_data2_new["ra_shift"]
    npt.assert_almost_equal(ra_shift, self.delta_x_offset, decimal=1)
    phi_rot = kwargs_data2_new["phi_rot"]
    npt.assert_almost_equal(phi_rot, self.phi_rot, decimal=1)