def METHOD_NAME():
    rng = np.random.RandomState(3491349965)
    a = rng.standard_normal(64)
    dln = rng.uniform(-1, 1)
    # let xp = (mu+1+q)/2, xm = (mu+1-q)/2, M = {0, -1, -2, ...}
    # case 1: xp in M, xm in M => well-defined transform
    mu, bias = -4.0, 1.0
    with pytest.warns(None) as record:
        fht(a, dln, mu, bias=bias)
        assert not record, 'fht warned about a well-defined transform'
    # case 2: xp not in M, xm in M => well-defined transform
    mu, bias = -2.5, 0.5
    with pytest.warns(None) as record:
        fht(a, dln, mu, bias=bias)
        assert not record, 'fht warned about a well-defined transform'
    # case 3: xp in M, xm not in M => singular transform
    mu, bias = -3.5, 0.5
    with pytest.warns(Warning) as record:
        fht(a, dln, mu, bias=bias)
        assert record, 'fht did not warn about a singular transform'
    # case 4: xp not in M, xm in M => singular inverse transform
    mu, bias = -2.5, 0.5
    with pytest.warns(Warning) as record:
        ifht(a, dln, mu, bias=bias)
        assert record, 'ifht did not warn about a singular transform'