changed output of matching as a (n x 2) array, adapted tests and doc

3 files changed, 7 insertions, 7 deletions

diff --git a/src/python/doc/wasserstein_distance_user.rst b/src/python/doc/wasserstein_distance_user.rst
index d3daa318..9519caa6 100644
--- a/src/python/doc/wasserstein_distance_user.rst
+++ b/src/python/doc/wasserstein_distance_user.rst
@@ -69,5 +69,5 @@ The output is:
 
 .. testoutput::
     
-    Wasserstein distance value = 2.15, optimal matching: [(0, 0), (1, 2), (2, -1), (-1, 1)]
+    Wasserstein distance value = 2.15, optimal matching: [[0, 0], [1, 2], [2, -1], [-1, 1]]
 
diff --git a/src/python/gudhi/wasserstein.py b/src/python/gudhi/wasserstein.py
index 9efa946e..9e4dc7d5 100644
--- a/src/python/gudhi/wasserstein.py
+++ b/src/python/gudhi/wasserstein.py
@@ -88,7 +88,7 @@ def wasserstein_distance(X, Y, matching=False, order=2., internal_p=2.):
             if not matching:
                 return 0.
             else:
-                return 0., []
+                return 0., np.array([])
         else:
             if not matching:
                 return _perstot(Y, order, internal_p)
diff --git a/src/python/test/test_wasserstein_distance.py b/src/python/test/test_wasserstein_distance.py
index d0f0323c..ca9a4a61 100755
--- a/src/python/test/test_wasserstein_distance.py
+++ b/src/python/test/test_wasserstein_distance.py
@@ -61,15 +61,15 @@ def _basic_wasserstein(wasserstein_distance, delta, test_infinity=True, test_mat
 
     if test_matching:
         match = wasserstein_distance(emptydiag, emptydiag, matching=True, internal_p=1., order=2)[1]
-        assert match == []
+        assert np.array_equal(match, np.array([]))
         match = wasserstein_distance(emptydiag, emptydiag, matching=True, internal_p=np.inf, order=2.24)[1]
-        assert match == []
+        assert np.array_equal(match, np.array([]))
         match = wasserstein_distance(emptydiag, diag2, matching=True, internal_p=np.inf, order=2.)[1]
-        assert match == [(-1, 0), (-1, 1)]
+        assert np.array_equal(match , np.array([[-1, 0], [-1, 1]]))
         match = wasserstein_distance(diag2, emptydiag, matching=True, internal_p=np.inf, order=2.24)[1]
-        assert match == [(0, -1), (1, -1)]
+        assert np.array_equal(match , np.array([[0, -1], [1, -1]]))
         match = wasserstein_distance(diag1, diag2, matching=True, internal_p=2., order=2.)[1]
-        assert match == [(0, 0), (1, 1), (2, -1)]
+        assert np.array_equal(match, np.array_equal([[0, 0], [1, 1], [2, -1]]))