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Diffstat (limited to 'test/test_bregman.py')
| -rw-r--r-- | test/test_bregman.py | 67 |
1 files changed, 67 insertions, 0 deletions
diff --git a/test/test_bregman.py b/test/test_bregman.py index 90eaf27..7f4972c 100644 --- a/test/test_bregman.py +++ b/test/test_bregman.py @@ -1,6 +1,7 @@ """Tests for module bregman on OT with bregman projections """ # Author: Remi Flamary <remi.flamary@unice.fr> +# Kilian Fatras <kilian.fatras@irisa.fr> # # License: MIT License @@ -187,3 +188,69 @@ def test_unmix(): ot.bregman.unmix(a, D, M, M0, h0, reg, 1, alpha=0.01, log=True, verbose=True) + + +def test_empirical_sinkhorn(): + # test sinkhorn + n = 100 + a = ot.unif(n) + b = ot.unif(n) + + X_s = np.reshape(np.arange(n), (n, 1)) + X_t = np.reshape(np.arange(0, n), (n, 1)) + M = ot.dist(X_s, X_t) + M_m = ot.dist(X_s, X_t, metric='minkowski') + + G_sqe = ot.bregman.empirical_sinkhorn(X_s, X_t, 1) + sinkhorn_sqe = ot.sinkhorn(a, b, M, 1) + + G_log, log_es = ot.bregman.empirical_sinkhorn(X_s, X_t, 0.1, log=True) + sinkhorn_log, log_s = ot.sinkhorn(a, b, M, 0.1, log=True) + + G_m = ot.bregman.empirical_sinkhorn(X_s, X_t, 1, metric='minkowski') + sinkhorn_m = ot.sinkhorn(a, b, M_m, 1) + + loss_emp_sinkhorn = ot.bregman.empirical_sinkhorn2(X_s, X_t, 1) + loss_sinkhorn = ot.sinkhorn2(a, b, M, 1) + + # check constratints + np.testing.assert_allclose( + sinkhorn_sqe.sum(1), G_sqe.sum(1), atol=1e-05) # metric sqeuclidian + np.testing.assert_allclose( + sinkhorn_sqe.sum(0), G_sqe.sum(0), atol=1e-05) # metric sqeuclidian + np.testing.assert_allclose( + sinkhorn_log.sum(1), G_log.sum(1), atol=1e-05) # log + np.testing.assert_allclose( + sinkhorn_log.sum(0), G_log.sum(0), atol=1e-05) # log + np.testing.assert_allclose( + sinkhorn_m.sum(1), G_m.sum(1), atol=1e-05) # metric euclidian + np.testing.assert_allclose( + sinkhorn_m.sum(0), G_m.sum(0), atol=1e-05) # metric euclidian + np.testing.assert_allclose(loss_emp_sinkhorn, loss_sinkhorn, atol=1e-05) + + +def test_empirical_sinkhorn_divergence(): + #Test sinkhorn divergence + n = 10 + a = ot.unif(n) + b = ot.unif(n) + X_s = np.reshape(np.arange(n), (n, 1)) + X_t = np.reshape(np.arange(0, n * 2, 2), (n, 1)) + M = ot.dist(X_s, X_t) + M_s = ot.dist(X_s, X_s) + M_t = ot.dist(X_t, X_t) + + emp_sinkhorn_div = ot.bregman.empirical_sinkhorn_divergence(X_s, X_t, 1) + sinkhorn_div = (ot.sinkhorn2(a, b, M, 1) - 1 / 2 * ot.sinkhorn2(a, a, M_s, 1) - 1 / 2 * ot.sinkhorn2(b, b, M_t, 1)) + + emp_sinkhorn_div_log, log_es = ot.bregman.empirical_sinkhorn_divergence(X_s, X_t, 1, log=True) + sink_div_log_ab, log_s_ab = ot.sinkhorn2(a, b, M, 1, log=True) + sink_div_log_a, log_s_a = ot.sinkhorn2(a, a, M_s, 1, log=True) + sink_div_log_b, log_s_b = ot.sinkhorn2(b, b, M_t, 1, log=True) + sink_div_log = sink_div_log_ab - 1 / 2 * (sink_div_log_a + sink_div_log_b) + + # check constratints + np.testing.assert_allclose( + emp_sinkhorn_div, sinkhorn_div, atol=1e-05) # cf conv emp sinkhorn + np.testing.assert_allclose( + emp_sinkhorn_div_log, sink_div_log, atol=1e-05) # cf conv emp sinkhorn |