Function test_raise_errors

test/test_partial.py:15–65

()

def test_raise_errors():
    n_samples = 20  # nb samples (gaussian)
    n_noise = 20  # nb of samples (noise)

    mu = np.array([0, 0])
    cov = np.array([[1, 0], [0, 2]])

    rng = np.random.RandomState(42)
    xs = ot.datasets.make_2D_samples_gauss(n_samples, mu, cov, random_state=rng)
    xs = np.append(xs, (rng.rand(n_noise, 2) + 1) * 4).reshape((-1, 2))
    xt = ot.datasets.make_2D_samples_gauss(n_samples, mu, cov, random_state=rng)
    xt = np.append(xt, (rng.rand(n_noise, 2) + 1) * -3).reshape((-1, 2))

    M = ot.dist(xs, xt)

    p = ot.unif(n_samples + n_noise)
    q = ot.unif(n_samples + n_noise)

    with pytest.raises(ValueError):
        ot.partial.partial_wasserstein_lagrange(p + 1, q, M, 1, log=True)

    with pytest.raises(ValueError):
        ot.partial.partial_wasserstein(p, q, M, m=2, log=True)

    with pytest.raises(ValueError):
        ot.partial.partial_wasserstein(p, q, M, m=-1, log=True)

    with pytest.raises(ValueError):
        ot.partial.entropic_partial_wasserstein(p, q, M, reg=1, m=2, log=True)

    with pytest.raises(ValueError):
        ot.partial.entropic_partial_wasserstein(p, q, M, reg=1, m=-1, log=True)

    with pytest.raises(ValueError):
        ot.partial.partial_gromov_wasserstein(M, M, p, q, m=2, log=True)

    with pytest.raises(ValueError):
        ot.partial.partial_gromov_wasserstein(M, M, p, q, m=-1, log=True)

    with pytest.raises(ValueError):
        ot.partial.entropic_partial_gromov_wasserstein(M, M, p, q, reg=1, m=2, log=True)

    with pytest.raises(ValueError):
        ot.partial.entropic_partial_gromov_wasserstein(
            M, M, p, q, reg=1, m=-1, log=True
        )

    with pytest.raises(AssertionError):
        xs_2d = rng.randn(n_samples, 2)
        xt_2d = rng.randn(n_samples, 2)
        ot.partial.partial_wasserstein_1d(xs_2d, xt_2d)


def test_partial_wasserstein_lagrange():