def METHOD_NAME(par):
    """Dot-test, comparison of dense vs lop implementation and
    inversion for PoststackLinearModelling in 1d with stationary wavelet
    """
    # Dense
    PPop_dense = PoststackLinearModelling(wav, nt0=nt0, explicit=True)
    assert dottest(PPop_dense, nt0, nt0, rtol=1e-4)
    # Linear operator
    PPop = PoststackLinearModelling(wav, nt0=nt0, explicit=False)
    assert dottest(PPop, nt0, nt0, rtol=1e-4)
    # Compare data
    d = PPop * m.ravel()
    d_dense = PPop_dense * m.T.ravel()
    assert_array_almost_equal(d, d_dense, decimal=4)
    # Inversion
    for explicit in [True, False]:
        if par["epsR"] is None:
            dict_inv = {}
        else:
            dict_inv = dict(damp=0 if par["epsI"] is None else par["epsI"], iter_lim=80)
        minv = PoststackInversion(
            d,
            wav,
            m0=mback,
            explicit=explicit,
            epsR=par["epsR"],
            epsI=par["epsI"],
            simultaneous=par["simultaneous"],
            **dict_inv
        )[0]
        assert np.linalg.norm(m - minv) / np.linalg.norm(minv) < 1e-2