replaced marginal tests

Author: Kilian Fatras

test/test_stochastic.py

@@ -97,7 +97,6 @@ def test_sag_asgd_sinkhorn():
 
     x = rng.randn(n, 2)
     u = ot.utils.unif(n)
-    zero = np.zeros(n)
     M = ot.dist(x, x)
 
     G_asgd = ot.stochastic.solve_semi_dual_entropic(u, u, M, reg, "asgd",
@@ -108,13 +107,13 @@ def test_sag_asgd_sinkhorn():
 
     # check constratints
     np.testing.assert_allclose(
-        zero, (G_sag - G_sinkhorn).sum(1), atol=1e-03)  # cf convergence sag
+        G_sag.sum(1), G_sinkhorn.sum(1), atol=1e-03)
     np.testing.assert_allclose(
-        zero, (G_sag - G_sinkhorn).sum(0), atol=1e-03)  # cf convergence sag
+        G_sag.sum(0), G_sinkhorn.sum(0), atol=1e-03)
     np.testing.assert_allclose(
-        zero, (G_asgd - G_sinkhorn).sum(1), atol=1e-03)  # cf convergence asgd
+        G_asgd.sum(1), G_sinkhorn.sum(1), atol=1e-03)
     np.testing.assert_allclose(
-        zero, (G_asgd - G_sinkhorn).sum(0), atol=1e-03)  # cf convergence asgd
+        G_asgd.sum(0), G_sinkhorn.sum(0), atol=1e-03)
     np.testing.assert_allclose(
         G_sag, G_sinkhorn, atol=1e-03)  # cf convergence sag
     np.testing.assert_allclose(
@@ -175,7 +174,6 @@ def test_dual_sgd_sinkhorn():
 # Test uniform
     x = rng.randn(n, 2)
     u = ot.utils.unif(n)
-    zero = np.zeros(n)
     M = ot.dist(x, x)
 
     G_sgd = ot.stochastic.solve_dual_entropic(u, u, M, reg, batch_size,
@@ -185,17 +183,16 @@ def test_dual_sgd_sinkhorn():
 
     # check constratints
     np.testing.assert_allclose(
-        zero, abs(G_sgd - G_sinkhorn).sum(1), atol=1e-03)  # cf convergence sgd
+        G_sgd.sum(1), G_sinkhorn.sum(1), atol=1e-03)
     np.testing.assert_allclose(
-        zero, abs(G_sgd - G_sinkhorn).sum(0), atol=1e-03)  # cf convergence sgd
+        G_sgd.sum(0), G_sinkhorn.sum(0), atol=1e-03)
     np.testing.assert_allclose(
         G_sgd, G_sinkhorn, atol=1e-03)  # cf convergence sgd
 
 # Test gaussian
     n = 30
     reg = 1
     batch_size = 30
-    zero = np.zeros(n)
 
     a = ot.datasets.make_1D_gauss(n, 15, 5)  # m= mean, s= std
     b = ot.datasets.make_1D_gauss(n, 15, 5)
@@ -211,8 +208,8 @@ def test_dual_sgd_sinkhorn():
 
     # check constratints
     np.testing.assert_allclose(
-        zero, abs(G_sgd - G_sinkhorn).sum(1), atol=1e-03)  # cf convergence sgd
+        G_sgd.sum(1), G_sinkhorn.sum(1), atol=1e-03)
     np.testing.assert_allclose(
-        zero, abs(G_sgd - G_sinkhorn).sum(0), atol=1e-03)  # cf convergence sgd
+        G_sgd.sum(0), G_sinkhorn.sum(0), atol=1e-03)
     np.testing.assert_allclose(
         G_sgd, G_sinkhorn, atol=1e-03)  # cf convergence sgd