out of samples transform and inverse transform by batch

1 files changed, 33 insertions, 33 deletions

diff --git a/test/test_da.py b/test/test_da.py
index 93f7e83..196f4c4 100644
--- a/test/test_da.py
+++ b/test/test_da.py
@@ -28,14 +28,14 @@ def test_sinkhorn_lpl1_transport_class():
     clf.fit(Xs=Xs, ys=ys, Xt=Xt)
 
     # test dimensions of coupling
-    assert_equal(clf.Cost.shape, ((Xs.shape[0], Xt.shape[0])))
-    assert_equal(clf.Coupling_.shape, ((Xs.shape[0], Xt.shape[0])))
+    assert_equal(clf.cost_.shape, ((Xs.shape[0], Xt.shape[0])))
+    assert_equal(clf.coupling_.shape, ((Xs.shape[0], Xt.shape[0])))
 
     # test margin constraints
     mu_s = unif(ns)
     mu_t = unif(nt)
-    assert_allclose(np.sum(clf.Coupling_, axis=0), mu_t, rtol=1e-3, atol=1e-3)
-    assert_allclose(np.sum(clf.Coupling_, axis=1), mu_s, rtol=1e-3, atol=1e-3)
+    assert_allclose(np.sum(clf.coupling_, axis=0), mu_t, rtol=1e-3, atol=1e-3)
+    assert_allclose(np.sum(clf.coupling_, axis=1), mu_s, rtol=1e-3, atol=1e-3)
 
     # test transform
     transp_Xs = clf.transform(Xs=Xs)
@@ -64,13 +64,13 @@ def test_sinkhorn_lpl1_transport_class():
     # test semi supervised mode
     clf = ot.da.SinkhornLpl1Transport()
     clf.fit(Xs=Xs, ys=ys, Xt=Xt)
-    n_unsup = np.sum(clf.Cost)
+    n_unsup = np.sum(clf.cost_)
 
     # test semi supervised mode
     clf = ot.da.SinkhornLpl1Transport()
     clf.fit(Xs=Xs, ys=ys, Xt=Xt, yt=yt)
-    assert_equal(clf.Cost.shape, ((Xs.shape[0], Xt.shape[0])))
-    n_semisup = np.sum(clf.Cost)
+    assert_equal(clf.cost_.shape, ((Xs.shape[0], Xt.shape[0])))
+    n_semisup = np.sum(clf.cost_)
 
     assert n_unsup != n_semisup, "semisupervised mode not working"
 
@@ -91,14 +91,14 @@ def test_sinkhorn_l1l2_transport_class():
     clf.fit(Xs=Xs, ys=ys, Xt=Xt)
 
     # test dimensions of coupling
-    assert_equal(clf.Cost.shape, ((Xs.shape[0], Xt.shape[0])))
-    assert_equal(clf.Coupling_.shape, ((Xs.shape[0], Xt.shape[0])))
+    assert_equal(clf.cost_.shape, ((Xs.shape[0], Xt.shape[0])))
+    assert_equal(clf.coupling_.shape, ((Xs.shape[0], Xt.shape[0])))
 
     # test margin constraints
     mu_s = unif(ns)
     mu_t = unif(nt)
-    assert_allclose(np.sum(clf.Coupling_, axis=0), mu_t, rtol=1e-3, atol=1e-3)
-    assert_allclose(np.sum(clf.Coupling_, axis=1), mu_s, rtol=1e-3, atol=1e-3)
+    assert_allclose(np.sum(clf.coupling_, axis=0), mu_t, rtol=1e-3, atol=1e-3)
+    assert_allclose(np.sum(clf.coupling_, axis=1), mu_s, rtol=1e-3, atol=1e-3)
 
     # test transform
     transp_Xs = clf.transform(Xs=Xs)
@@ -127,13 +127,13 @@ def test_sinkhorn_l1l2_transport_class():
     # test semi supervised mode
     clf = ot.da.SinkhornL1l2Transport()
     clf.fit(Xs=Xs, ys=ys, Xt=Xt)
-    n_unsup = np.sum(clf.Cost)
+    n_unsup = np.sum(clf.cost_)
 
     # test semi supervised mode
     clf = ot.da.SinkhornL1l2Transport()
     clf.fit(Xs=Xs, ys=ys, Xt=Xt, yt=yt)
-    assert_equal(clf.Cost.shape, ((Xs.shape[0], Xt.shape[0])))
-    n_semisup = np.sum(clf.Cost)
+    assert_equal(clf.cost_.shape, ((Xs.shape[0], Xt.shape[0])))
+    n_semisup = np.sum(clf.cost_)
 
     assert n_unsup != n_semisup, "semisupervised mode not working"
 
@@ -154,14 +154,14 @@ def test_sinkhorn_transport_class():
     clf.fit(Xs=Xs, Xt=Xt)
 
     # test dimensions of coupling
-    assert_equal(clf.Cost.shape, ((Xs.shape[0], Xt.shape[0])))
-    assert_equal(clf.Coupling_.shape, ((Xs.shape[0], Xt.shape[0])))
+    assert_equal(clf.cost_.shape, ((Xs.shape[0], Xt.shape[0])))
+    assert_equal(clf.coupling_.shape, ((Xs.shape[0], Xt.shape[0])))
 
     # test margin constraints
     mu_s = unif(ns)
     mu_t = unif(nt)
-    assert_allclose(np.sum(clf.Coupling_, axis=0), mu_t, rtol=1e-3, atol=1e-3)
-    assert_allclose(np.sum(clf.Coupling_, axis=1), mu_s, rtol=1e-3, atol=1e-3)
+    assert_allclose(np.sum(clf.coupling_, axis=0), mu_t, rtol=1e-3, atol=1e-3)
+    assert_allclose(np.sum(clf.coupling_, axis=1), mu_s, rtol=1e-3, atol=1e-3)
 
     # test transform
     transp_Xs = clf.transform(Xs=Xs)
@@ -190,13 +190,13 @@ def test_sinkhorn_transport_class():
     # test semi supervised mode
     clf = ot.da.SinkhornTransport()
     clf.fit(Xs=Xs, Xt=Xt)
-    n_unsup = np.sum(clf.Cost)
+    n_unsup = np.sum(clf.cost_)
 
     # test semi supervised mode
     clf = ot.da.SinkhornTransport()
     clf.fit(Xs=Xs, ys=ys, Xt=Xt, yt=yt)
-    assert_equal(clf.Cost.shape, ((Xs.shape[0], Xt.shape[0])))
-    n_semisup = np.sum(clf.Cost)
+    assert_equal(clf.cost_.shape, ((Xs.shape[0], Xt.shape[0])))
+    n_semisup = np.sum(clf.cost_)
 
     assert n_unsup != n_semisup, "semisupervised mode not working"
 
@@ -217,14 +217,14 @@ def test_emd_transport_class():
     clf.fit(Xs=Xs, Xt=Xt)
 
     # test dimensions of coupling
-    assert_equal(clf.Cost.shape, ((Xs.shape[0], Xt.shape[0])))
-    assert_equal(clf.Coupling_.shape, ((Xs.shape[0], Xt.shape[0])))
+    assert_equal(clf.cost_.shape, ((Xs.shape[0], Xt.shape[0])))
+    assert_equal(clf.coupling_.shape, ((Xs.shape[0], Xt.shape[0])))
 
     # test margin constraints
     mu_s = unif(ns)
     mu_t = unif(nt)
-    assert_allclose(np.sum(clf.Coupling_, axis=0), mu_t, rtol=1e-3, atol=1e-3)
-    assert_allclose(np.sum(clf.Coupling_, axis=1), mu_s, rtol=1e-3, atol=1e-3)
+    assert_allclose(np.sum(clf.coupling_, axis=0), mu_t, rtol=1e-3, atol=1e-3)
+    assert_allclose(np.sum(clf.coupling_, axis=1), mu_s, rtol=1e-3, atol=1e-3)
 
     # test transform
     transp_Xs = clf.transform(Xs=Xs)
@@ -253,13 +253,13 @@ def test_emd_transport_class():
     # test semi supervised mode
     clf = ot.da.EMDTransport()
     clf.fit(Xs=Xs, Xt=Xt)
-    n_unsup = np.sum(clf.Cost)
+    n_unsup = np.sum(clf.cost_)
 
     # test semi supervised mode
     clf = ot.da.EMDTransport()
     clf.fit(Xs=Xs, ys=ys, Xt=Xt, yt=yt)
-    assert_equal(clf.Cost.shape, ((Xs.shape[0], Xt.shape[0])))
-    n_semisup = np.sum(clf.Cost)
+    assert_equal(clf.cost_.shape, ((Xs.shape[0], Xt.shape[0])))
+    n_semisup = np.sum(clf.cost_)
 
     assert n_unsup != n_semisup, "semisupervised mode not working"
 
@@ -326,9 +326,9 @@ def test_otda():
     da_emd.predict(xs)    # interpolation of source samples
 
 
-if __name__ == "__main__":
+# if __name__ == "__main__":
 
-    test_sinkhorn_transport_class()
-    test_emd_transport_class()
-    test_sinkhorn_l1l2_transport_class()
-    test_sinkhorn_lpl1_transport_class()
+#     test_sinkhorn_transport_class()
+#     test_emd_transport_class()
+#     test_sinkhorn_l1l2_transport_class()
+#     test_sinkhorn_lpl1_transport_class()