Function test_prw

test/test_dr.py:111–148

()

@pytest.mark.skipif(nogo, reason="Missing modules (autograd or pymanopt)")
def test_prw():
    d = 100  # Dimension
    n = 100  # Number samples
    k = 3  # Subspace dimension
    dim = 3

    def fragmented_hypercube(n, d, dim, rng):
        assert dim <= d
        assert dim >= 1
        assert dim == int(dim)

        a = (1.0 / n) * np.ones(n)
        b = (1.0 / n) * np.ones(n)

        # First measure : uniform on the hypercube
        X = rng.uniform(-1, 1, size=(n, d))

        # Second measure : fragmentation
        tmp_y = rng.uniform(-1, 1, size=(n, d))
        Y = tmp_y + 2 * np.sign(tmp_y) * np.array(dim * [1] + (d - dim) * [0])
        return a, b, X, Y

    rng = np.random.RandomState(42)
    a, b, X, Y = fragmented_hypercube(n, d, dim, rng)

    tau = 0.002
    reg = 0.2

    pi, U = ot.dr.projection_robust_wasserstein(
        X, Y, a, b, tau, reg=reg, k=k, maxiter=1000, verbose=1
    )

    U0 = rng.randn(d, k)
    U0, _ = np.linalg.qr(U0)

    pi, U = ot.dr.projection_robust_wasserstein(
        X, Y, a, b, tau, U0=U0, reg=reg, k=k, maxiter=1000, verbose=1
    )


@pytest.mark.skipif(nogo, reason="Missing modules (autograd or pymanopt)")