Python Lhs._lhs_normalized Examples

Example #1

File: test_sampler.py Project: xyliu09/scikit-optimize

def test_lhs_random_state(criterion):
    n_dim = 2
    n_samples = 20
    lhs = Lhs()

    h = lhs._lhs_normalized(n_dim, n_samples, 0)
    h2 = lhs._lhs_normalized(n_dim, n_samples, 0)
    assert_array_equal(h, h2)
    lhs = Lhs(criterion=criterion, iterations=100)
    h = lhs.generate([
        (0., 1.),
    ] * n_dim, n_samples, random_state=0)
    h2 = lhs.generate([
        (0., 1.),
    ] * n_dim, n_samples, random_state=0)
    assert_array_equal(h, h2)

Example #2

File: test_sampler.py Project: xyliu09/scikit-optimize

def test_lhs_pdist():
    n_dim = 2
    n_samples = 20
    lhs = Lhs()

    h = lhs._lhs_normalized(n_dim, n_samples, 0)
    d_classic = spatial.distance.pdist(np.array(h), 'euclidean')
    lhs = Lhs(criterion="maximin", iterations=100)
    h = lhs.generate([
        (0., 1.),
    ] * n_dim, n_samples, random_state=0)
    d = spatial.distance.pdist(np.array(h), 'euclidean')
    assert np.min(d) > np.min(d_classic)