Merge branch 'master' into coxeter_integration

2 files changed, 29 insertions, 3 deletions

diff --git a/src/python/test/test_bottleneck_distance.py b/src/python/test/test_bottleneck_distance.py
index 6915bea8..07fcc9cc 100755
--- a/src/python/test/test_bottleneck_distance.py
+++ b/src/python/test/test_bottleneck_distance.py
@@ -25,3 +25,15 @@ def test_basic_bottleneck():
     assert gudhi.bottleneck_distance(diag1, diag2, 0.1) == pytest.approx(0.75, abs=0.1)
     assert gudhi.hera.bottleneck_distance(diag1, diag2, 0) == 0.75
     assert gudhi.hera.bottleneck_distance(diag1, diag2, 0.1) == pytest.approx(0.75, rel=0.1)
+
+    import numpy as np
+
+    # Translating both diagrams along the diagonal should not affect the distance,
+    # checks that negative numbers are not an issue
+    diag1 = np.array(diag1) - 100
+    diag2 = np.array(diag2) - 100
+
+    assert gudhi.bottleneck_distance(diag1, diag2) == 0.75
+    assert gudhi.bottleneck_distance(diag1, diag2, 0.1) == pytest.approx(0.75, abs=0.1)
+    assert gudhi.hera.bottleneck_distance(diag1, diag2, 0) == 0.75
+    assert gudhi.hera.bottleneck_distance(diag1, diag2, 0.1) == pytest.approx(0.75, rel=0.1)
diff --git a/src/python/test/test_representations.py b/src/python/test/test_representations.py
index e5c211a0..43c914f3 100755
--- a/src/python/test/test_representations.py
+++ b/src/python/test/test_representations.py
@@ -39,11 +39,11 @@ def test_multiple():
     d2 = BottleneckDistance(epsilon=0.00001).fit_transform(l1)
     d3 = pairwise_persistence_diagram_distances(l1, l1b, e=0.00001, n_jobs=4)
     assert d1 == pytest.approx(d2)
-    assert d3 == pytest.approx(d2, abs=1e-5) # Because of 0 entries (on the diagonal)
+    assert d3 == pytest.approx(d2, abs=1e-5)  # Because of 0 entries (on the diagonal)
     d1 = pairwise_persistence_diagram_distances(l1, l2, metric="wasserstein", order=2, internal_p=2)
     d2 = WassersteinDistance(order=2, internal_p=2, n_jobs=4).fit(l2).transform(l1)
     print(d1.shape, d2.shape)
-    assert d1 == pytest.approx(d2, rel=.02)
+    assert d1 == pytest.approx(d2, rel=0.02)
 
 
 def test_dummy_atol():
@@ -53,8 +53,22 @@ def test_dummy_atol():
 
     for weighting_method in ["cloud", "iidproba"]:
         for contrast in ["gaussian", "laplacian", "indicator"]:
-            atol_vectoriser = Atol(quantiser=KMeans(n_clusters=1, random_state=202006), weighting_method=weighting_method, contrast=contrast)
+            atol_vectoriser = Atol(
+                quantiser=KMeans(n_clusters=1, random_state=202006),
+                weighting_method=weighting_method,
+                contrast=contrast,
+            )
             atol_vectoriser.fit([a, b, c])
             atol_vectoriser(a)
             atol_vectoriser.transform(X=[a, b, c])
 
+
+from gudhi.representations.vector_methods import BettiCurve
+
+
+def test_infinity():
+    a = np.array([[1.0, 8.0], [2.0, np.inf], [3.0, 4.0]])
+    c = BettiCurve(20, [0.0, 10.0])(a)
+    assert c[1] == 0
+    assert c[7] == 3
+    assert c[9] == 2