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Diffstat (limited to 'test/test_utils.py')
| -rw-r--r-- | test/test_utils.py | 202 |
1 files changed, 202 insertions, 0 deletions
diff --git a/test/test_utils.py b/test/test_utils.py new file mode 100644 index 0000000..640598d --- /dev/null +++ b/test/test_utils.py @@ -0,0 +1,202 @@ +"""Tests for module utils for timing and parallel computation """ + +# Author: Remi Flamary <remi.flamary@unice.fr> +# +# License: MIT License + + +import ot +import numpy as np +import sys + + +def test_parmap(): + + n = 10 + + def f(i): + return 1.0 * i * i + + a = np.arange(n) + + l1 = list(map(f, a)) + + l2 = list(ot.utils.parmap(f, a)) + + np.testing.assert_allclose(l1, l2) + + +def test_tic_toc(): + + import time + + ot.tic() + time.sleep(0.5) + t = ot.toc() + t2 = ot.toq() + + # test timing + np.testing.assert_allclose(0.5, t, rtol=1e-2, atol=1e-2) + + # test toc vs toq + np.testing.assert_allclose(t, t2, rtol=1e-2, atol=1e-2) + + +def test_kernel(): + + n = 100 + + x = np.random.randn(n, 2) + + K = ot.utils.kernel(x, x) + + # gaussian kernel has ones on the diagonal + np.testing.assert_allclose(np.diag(K), np.ones(n)) + + +def test_unif(): + + n = 100 + + u = ot.unif(n) + + np.testing.assert_allclose(1, np.sum(u)) + + +def test_dist(): + + n = 100 + + x = np.random.randn(n, 2) + + D = np.zeros((n, n)) + for i in range(n): + for j in range(n): + D[i, j] = np.sum(np.square(x[i, :] - x[j, :])) + + D2 = ot.dist(x, x) + D3 = ot.dist(x) + + # dist shoul return squared euclidean + np.testing.assert_allclose(D, D2) + np.testing.assert_allclose(D, D3) + + +def test_dist0(): + + n = 100 + M = ot.utils.dist0(n, method='lin_square') + + # dist0 default to linear sampling with quadratic loss + np.testing.assert_allclose(M[0, -1], (n - 1) * (n - 1)) + + +def test_dots(): + + n1, n2, n3, n4 = 100, 50, 200, 100 + + A = np.random.randn(n1, n2) + B = np.random.randn(n2, n3) + C = np.random.randn(n3, n4) + + X1 = ot.utils.dots(A, B, C) + + X2 = A.dot(B.dot(C)) + + np.testing.assert_allclose(X1, X2) + + +def test_clean_zeros(): + + n = 100 + nz = 50 + nz2 = 20 + u1 = ot.unif(n) + u1[:nz] = 0 + u1 = u1 / u1.sum() + u2 = ot.unif(n) + u2[:nz2] = 0 + u2 = u2 / u2.sum() + + M = ot.utils.dist0(n) + + a, b, M2 = ot.utils.clean_zeros(u1, u2, M) + + assert len(a) == n - nz + assert len(b) == n - nz2 + + +def test_cost_normalization(): + + C = np.random.rand(10, 10) + + # does nothing + M0 = ot.utils.cost_normalization(C) + np.testing.assert_allclose(C, M0) + + M = ot.utils.cost_normalization(C, 'median') + np.testing.assert_allclose(np.median(M), 1) + + M = ot.utils.cost_normalization(C, 'max') + np.testing.assert_allclose(M.max(), 1) + + M = ot.utils.cost_normalization(C, 'log') + np.testing.assert_allclose(M.max(), np.log(1 + C).max()) + + M = ot.utils.cost_normalization(C, 'loglog') + np.testing.assert_allclose(M.max(), np.log(1 + np.log(1 + C)).max()) + + +def test_check_params(): + + res1 = ot.utils.check_params(first='OK', second=20) + assert res1 is True + + res0 = ot.utils.check_params(first='OK', second=None) + assert res0 is False + + +def test_deprecated_func(): + + @ot.utils.deprecated('deprecated text for fun') + def fun(): + pass + + def fun2(): + pass + + @ot.utils.deprecated('deprecated text for class') + class Class(): + pass + + if sys.version_info < (3, 5): + print('Not tested') + else: + assert ot.utils._is_deprecated(fun) is True + + assert ot.utils._is_deprecated(fun2) is False + + +def test_BaseEstimator(): + + class Class(ot.utils.BaseEstimator): + + def __init__(self, first='spam', second='eggs'): + + self.first = first + self.second = second + + cl = Class() + + names = cl._get_param_names() + assert 'first' in names + assert 'second' in names + + params = cl.get_params() + assert 'first' in params + assert 'second' in params + + params['first'] = 'spam again' + cl.set_params(**params) + + assert cl.first == 'spam again' |