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-rw-r--r--test/test_da.py65
1 files changed, 65 insertions, 0 deletions
diff --git a/test/test_da.py b/test/test_da.py
index f7f3a9d..2a5e50e 100644
--- a/test/test_da.py
+++ b/test/test_da.py
@@ -245,6 +245,71 @@ def test_sinkhorn_transport_class():
assert len(otda.log_.keys()) != 0
+def test_unbalanced_sinkhorn_transport_class():
+ """test_sinkhorn_transport
+ """
+
+ ns = 150
+ nt = 200
+
+ Xs, ys = make_data_classif('3gauss', ns)
+ Xt, yt = make_data_classif('3gauss2', nt)
+
+ otda = ot.da.UnbalancedSinkhornTransport()
+
+ # test its computed
+ otda.fit(Xs=Xs, Xt=Xt)
+ assert hasattr(otda, "cost_")
+ assert hasattr(otda, "coupling_")
+ assert hasattr(otda, "log_")
+
+ # test dimensions of coupling
+ assert_equal(otda.cost_.shape, ((Xs.shape[0], Xt.shape[0])))
+ assert_equal(otda.coupling_.shape, ((Xs.shape[0], Xt.shape[0])))
+
+ # test transform
+ transp_Xs = otda.transform(Xs=Xs)
+ assert_equal(transp_Xs.shape, Xs.shape)
+
+ Xs_new, _ = make_data_classif('3gauss', ns + 1)
+ transp_Xs_new = otda.transform(Xs_new)
+
+ # check that the oos method is working
+ assert_equal(transp_Xs_new.shape, Xs_new.shape)
+
+ # test inverse transform
+ transp_Xt = otda.inverse_transform(Xt=Xt)
+ assert_equal(transp_Xt.shape, Xt.shape)
+
+ Xt_new, _ = make_data_classif('3gauss2', nt + 1)
+ transp_Xt_new = otda.inverse_transform(Xt=Xt_new)
+
+ # check that the oos method is working
+ assert_equal(transp_Xt_new.shape, Xt_new.shape)
+
+ # test fit_transform
+ transp_Xs = otda.fit_transform(Xs=Xs, Xt=Xt)
+ assert_equal(transp_Xs.shape, Xs.shape)
+
+ # test unsupervised vs semi-supervised mode
+ otda_unsup = ot.da.SinkhornTransport()
+ otda_unsup.fit(Xs=Xs, Xt=Xt)
+ n_unsup = np.sum(otda_unsup.cost_)
+
+ otda_semi = ot.da.SinkhornTransport()
+ otda_semi.fit(Xs=Xs, ys=ys, Xt=Xt, yt=yt)
+ assert_equal(otda_semi.cost_.shape, ((Xs.shape[0], Xt.shape[0])))
+ n_semisup = np.sum(otda_semi.cost_)
+
+ # check that the cost matrix norms are indeed different
+ assert n_unsup != n_semisup, "semisupervised mode not working"
+
+ # check everything runs well with log=True
+ otda = ot.da.SinkhornTransport(log=True)
+ otda.fit(Xs=Xs, ys=ys, Xt=Xt)
+ assert len(otda.log_.keys()) != 0
+
+
def test_emd_transport_class():
"""test_sinkhorn_transport
"""