diff options
Diffstat (limited to 'test/test_da.py')
| -rw-r--r-- | test/test_da.py | 20 |
1 files changed, 10 insertions, 10 deletions
diff --git a/test/test_da.py b/test/test_da.py index 497a8ee..ecd2a3a 100644 --- a/test/test_da.py +++ b/test/test_da.py @@ -63,12 +63,12 @@ def test_sinkhorn_lpl1_transport_class(): assert_equal(transp_Xs.shape, Xs.shape) # test semi supervised mode - clf = ot.da.SinkhornTransport(mode="semisupervised") - clf.fit(Xs=Xs, Xt=Xt) + clf = ot.da.SinkhornLpl1Transport() + clf.fit(Xs=Xs, ys=ys, Xt=Xt) n_unsup = np.sum(clf.Cost) # test semi supervised mode - clf = ot.da.SinkhornTransport(mode="semisupervised") + 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) @@ -126,12 +126,12 @@ def test_sinkhorn_l1l2_transport_class(): assert_equal(transp_Xs.shape, Xs.shape) # test semi supervised mode - clf = ot.da.SinkhornTransport(mode="semisupervised") - clf.fit(Xs=Xs, Xt=Xt) + clf = ot.da.SinkhornL1l2Transport() + clf.fit(Xs=Xs, ys=ys, Xt=Xt) n_unsup = np.sum(clf.Cost) # test semi supervised mode - clf = ot.da.SinkhornTransport(mode="semisupervised") + 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) @@ -189,12 +189,12 @@ def test_sinkhorn_transport_class(): assert_equal(transp_Xs.shape, Xs.shape) # test semi supervised mode - clf = ot.da.SinkhornTransport(mode="semisupervised") + clf = ot.da.SinkhornTransport() clf.fit(Xs=Xs, Xt=Xt) n_unsup = np.sum(clf.Cost) # test semi supervised mode - clf = ot.da.SinkhornTransport(mode="semisupervised") + 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) @@ -252,12 +252,12 @@ def test_emd_transport_class(): assert_equal(transp_Xs.shape, Xs.shape) # test semi supervised mode - clf = ot.da.SinkhornTransport(mode="semisupervised") + clf = ot.da.EMDTransport() clf.fit(Xs=Xs, Xt=Xt) n_unsup = np.sum(clf.Cost) # test semi supervised mode - clf = ot.da.SinkhornTransport(mode="semisupervised") + 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) |