diff options
Diffstat (limited to 'test/test_stochastic.py')
| -rw-r--r-- | test/test_stochastic.py | 52 |
1 files changed, 26 insertions, 26 deletions
diff --git a/test/test_stochastic.py b/test/test_stochastic.py index 155622c..736df32 100644 --- a/test/test_stochastic.py +++ b/test/test_stochastic.py @@ -30,7 +30,7 @@ import ot def test_stochastic_sag(): # test sag - n = 15 + n = 10 reg = 1 numItermax = 30000 rng = np.random.RandomState(0) @@ -43,11 +43,11 @@ def test_stochastic_sag(): G = ot.stochastic.solve_semi_dual_entropic(u, u, M, reg, "sag", numItermax=numItermax) - # check constratints + # check constraints np.testing.assert_allclose( - u, G.sum(1), atol=1e-04) # cf convergence sag + u, G.sum(1), atol=1e-03) # cf convergence sag np.testing.assert_allclose( - u, G.sum(0), atol=1e-04) # cf convergence sag + u, G.sum(0), atol=1e-03) # cf convergence sag ############################################################################# @@ -60,9 +60,9 @@ def test_stochastic_sag(): def test_stochastic_asgd(): # test asgd - n = 15 + n = 10 reg = 1 - numItermax = 100000 + numItermax = 10000 rng = np.random.RandomState(0) x = rng.randn(n, 2) @@ -73,11 +73,11 @@ def test_stochastic_asgd(): G, log = ot.stochastic.solve_semi_dual_entropic(u, u, M, reg, "asgd", numItermax=numItermax, log=True) - # check constratints + # check constraints np.testing.assert_allclose( - u, G.sum(1), atol=1e-03) # cf convergence asgd + u, G.sum(1), atol=1e-02) # cf convergence asgd np.testing.assert_allclose( - u, G.sum(0), atol=1e-03) # cf convergence asgd + u, G.sum(0), atol=1e-02) # cf convergence asgd ############################################################################# @@ -90,9 +90,9 @@ def test_stochastic_asgd(): def test_sag_asgd_sinkhorn(): # test all algorithms - n = 15 + n = 10 reg = 1 - nb_iter = 100000 + nb_iter = 10000 rng = np.random.RandomState(0) x = rng.randn(n, 2) @@ -105,19 +105,19 @@ def test_sag_asgd_sinkhorn(): numItermax=nb_iter) G_sinkhorn = ot.sinkhorn(u, u, M, reg) - # check constratints + # check constraints np.testing.assert_allclose( - G_sag.sum(1), G_sinkhorn.sum(1), atol=1e-03) + G_sag.sum(1), G_sinkhorn.sum(1), atol=1e-02) np.testing.assert_allclose( - G_sag.sum(0), G_sinkhorn.sum(0), atol=1e-03) + G_sag.sum(0), G_sinkhorn.sum(0), atol=1e-02) np.testing.assert_allclose( - G_asgd.sum(1), G_sinkhorn.sum(1), atol=1e-03) + G_asgd.sum(1), G_sinkhorn.sum(1), atol=1e-02) np.testing.assert_allclose( - G_asgd.sum(0), G_sinkhorn.sum(0), atol=1e-03) + G_asgd.sum(0), G_sinkhorn.sum(0), atol=1e-02) np.testing.assert_allclose( - G_sag, G_sinkhorn, atol=1e-03) # cf convergence sag + G_sag, G_sinkhorn, atol=1e-02) # cf convergence sag np.testing.assert_allclose( - G_asgd, G_sinkhorn, atol=1e-03) # cf convergence asgd + G_asgd, G_sinkhorn, atol=1e-02) # cf convergence asgd ############################################################################# @@ -136,7 +136,7 @@ def test_stochastic_dual_sgd(): # test sgd n = 10 reg = 1 - numItermax = 15000 + numItermax = 5000 batch_size = 10 rng = np.random.RandomState(0) @@ -148,7 +148,7 @@ def test_stochastic_dual_sgd(): G, log = ot.stochastic.solve_dual_entropic(u, u, M, reg, batch_size, numItermax=numItermax, log=True) - # check constratints + # check constraints np.testing.assert_allclose( u, G.sum(1), atol=1e-03) # cf convergence sgd np.testing.assert_allclose( @@ -167,7 +167,7 @@ def test_dual_sgd_sinkhorn(): # test all dual algorithms n = 10 reg = 1 - nb_iter = 15000 + nb_iter = 5000 batch_size = 10 rng = np.random.RandomState(0) @@ -181,13 +181,13 @@ def test_dual_sgd_sinkhorn(): G_sinkhorn = ot.sinkhorn(u, u, M, reg) - # check constratints + # check constraints np.testing.assert_allclose( - G_sgd.sum(1), G_sinkhorn.sum(1), atol=1e-03) + G_sgd.sum(1), G_sinkhorn.sum(1), atol=1e-02) np.testing.assert_allclose( - G_sgd.sum(0), G_sinkhorn.sum(0), atol=1e-03) + G_sgd.sum(0), G_sinkhorn.sum(0), atol=1e-02) np.testing.assert_allclose( - G_sgd, G_sinkhorn, atol=1e-03) # cf convergence sgd + G_sgd, G_sinkhorn, atol=1e-02) # cf convergence sgd # Test gaussian n = 30 @@ -206,7 +206,7 @@ def test_dual_sgd_sinkhorn(): G_sinkhorn = ot.sinkhorn(a, b, M, reg) - # check constratints + # check constraints np.testing.assert_allclose( G_sgd.sum(1), G_sinkhorn.sum(1), atol=1e-03) np.testing.assert_allclose( |