'Check that if normalize_kernel is False then the normalization
tolerance is respected.'

@pytest.mark.parametrize(option_names, options)
def test_normalization_is_respected(self, boundary, nan_treatment, normalize_kernel):

    array = np.array([1, 2, 3])
    base_kernel = np.array([1.0])
    normalization_rtol = 0.0001
    norm_error = [(normalization_rtol / 10), (normalization_rtol * 10)]
    for err in norm_error:
        kernel = (base_kernel + err)
        result = convolve_fft(array, kernel, normalize_kernel=normalize_kernel, nan_treatment=nan_treatment, normalization_zero_tol=normalization_rtol)
        if normalize_kernel:
            assert_allclose(result, array, atol=1e-14)
        else:
            assert_allclose(result, (array * kernel), atol=1e-14)
