def METHOD_NAME(self):
    args = self.param.set_params(self.kwargs)
    kwargs_new, _ = self.param.get_params(args, i=0)
    args_new = self.param.set_params(kwargs_new)
    for k in range(len(args)):
        npt.assert_almost_equal(args[k], args_new[k], decimal=8)
    param_fixed = SpecialParam(
        Ddt_sampling=True,
        kwargs_fixed=self.kwargs,
        point_source_offset=True,
        num_images=2,
        source_size=True,
        num_z_sampling=3,
        num_tau0=2,
        kinematic_sampling=True,
    )
    kwargs_new, i = param_fixed.get_params(args=[], i=0)
    kwargs_new["D_dt"] = self.kwargs["D_dt"]
    kwargs_new["b_ani"] = self.kwargs["b_ani"]
    kwargs_new["incli"] = self.kwargs["incli"]
    kwargs_new["D_d"] = self.kwargs["D_d"]
    special_param = SpecialParam(
        num_z_sampling=1,
        kwargs_lower={"z_sampling": [0.1]},
        kwargs_upper={"z_sampling": [0.2]},
    )
    kwargs_test, i = special_param.get_params(args=[0.3], i=0, impose_bound=True)
    assert kwargs_test["z_sampling"] == [0.2]