A bug in the Entropy function has been solved

1 files changed, 10 insertions, 1 deletions

diff --git a/src/python/test/test_representations.py b/src/python/test/test_representations.py
index d219ce7a..6a3dddc4 100755
--- a/src/python/test/test_representations.py
+++ b/src/python/test/test_representations.py
@@ -152,7 +152,16 @@ def test_vectorization_empty_diagrams():
     scv = Entropy(mode="vector", normalized=False, resolution=random_resolution)(empty_diag)
     assert not np.any(scv)
     assert scv.shape[0] == random_resolution
-
+    
+def test_entropy_miscalculation():
+    diag_ex = np.array([[0.0,1.0], [0.0,1.0], [0.0,2.0]])
+    def pe(pd):
+        l = pd[:,1] - pd[:,0]
+        l = l/sum(l)
+        return -np.dot(l, np.log(l))
+    sce = Entropy(mode="scalar")
+    assert [[pe_max(diag_ex)]] == sce.fit_transform([diag_ex])
+    
 def test_kernel_empty_diagrams():
     empty_diag = np.empty(shape = [0, 2])
     assert SlicedWassersteinDistance(num_directions=100)(empty_diag, empty_diag) == 0.