Merge branch 'master' into coxeter_integration

3 files changed, 47 insertions, 12 deletions

diff --git a/src/python/test/test_representations.py b/src/python/test/test_representations.py
index 43c914f3..cda1a15b 100755
--- a/src/python/test/test_representations.py
+++ b/src/python/test/test_representations.py
@@ -46,6 +46,32 @@ def test_multiple():
     assert d1 == pytest.approx(d2, rel=0.02)
 
 
+# Test sorted values as points order can be inverted, and sorted test is not documentation-friendly
+# Note the test below must be up to date with the Atol class documentation
+def test_atol_doc():
+    a = np.array([[1, 2, 4], [1, 4, 0], [1, 0, 4]])
+    b = np.array([[4, 2, 0], [4, 4, 0], [4, 0, 2]])
+    c = np.array([[3, 2, -1], [1, 2, -1]])
+
+    atol_vectoriser = Atol(quantiser=KMeans(n_clusters=2, random_state=202006))
+    # Atol will do
+    # X = np.concatenate([a,b,c])
+    # kmeans = KMeans(n_clusters=2, random_state=202006).fit(X) 
+    # kmeans.labels_ will be : array([1, 0, 1, 0, 0, 1, 0, 0])
+    first_cluster = np.asarray([a[0], a[2], b[2]])
+    second_cluster = np.asarray([a[1], b[0], b[2], c[0], c[1]])
+
+    # Check the center of the first_cluster and second_cluster are in Atol centers
+    centers = atol_vectoriser.fit(X=[a, b, c]).centers
+    np.isclose(centers, first_cluster.mean(axis=0)).all(1).any() 
+    np.isclose(centers, second_cluster.mean(axis=0)).all(1).any() 
+
+    vectorization = atol_vectoriser.transform(X=[a, b, c])
+    assert np.allclose(vectorization[0], atol_vectoriser(a))
+    assert np.allclose(vectorization[1], atol_vectoriser(b))
+    assert np.allclose(vectorization[2], atol_vectoriser(c))
+
+
 def test_dummy_atol():
     a = np.array([[1, 2, 4], [1, 4, 0], [1, 0, 4]])
     b = np.array([[4, 2, 0], [4, 4, 0], [4, 0, 2]])
diff --git a/src/python/test/test_simplex_tree.py b/src/python/test/test_simplex_tree.py
index 3b23fa0b..a3eacaa9 100755
--- a/src/python/test/test_simplex_tree.py
+++ b/src/python/test/test_simplex_tree.py
@@ -8,7 +8,7 @@
       - YYYY/MM Author: Description of the modification
 """
 
-from gudhi import SimplexTree
+from gudhi import SimplexTree, __GUDHI_USE_EIGEN3
 import pytest
 
 __author__ = "Vincent Rouvreau"
@@ -353,11 +353,16 @@ def test_collapse_edges():
 
     assert st.num_simplices() == 10
 
-    st.collapse_edges()
-    assert st.num_simplices() == 9
-    assert st.find([1, 3]) == False
-    for simplex in st.get_skeleton(0):
-        assert simplex[1] == 1.
+    if __GUDHI_USE_EIGEN3:
+        st.collapse_edges()
+        assert st.num_simplices() == 9
+        assert st.find([1, 3]) == False
+        for simplex in st.get_skeleton(0):
+            assert simplex[1] == 1.
+    else:
+        # If no Eigen3, collapse_edges throws an exception
+        with pytest.raises(RuntimeError):
+            st.collapse_edges()
 
 def test_reset_filtration():
     st = SimplexTree()
diff --git a/src/python/test/test_subsampling.py b/src/python/test/test_subsampling.py
index 31f64e32..4019852e 100755
--- a/src/python/test/test_subsampling.py
+++ b/src/python/test/test_subsampling.py
@@ -141,12 +141,16 @@ def test_simple_sparsify_points():
     # assert gudhi.sparsify_point_set(points = [], min_squared_dist = 0.0) == []
     # assert gudhi.sparsify_point_set(points = [], min_squared_dist = 10.0) == []
     assert gudhi.sparsify_point_set(points=point_set, min_squared_dist=0.0) == point_set
-    assert gudhi.sparsify_point_set(points=point_set, min_squared_dist=1.0) == point_set
-    assert gudhi.sparsify_point_set(points=point_set, min_squared_dist=2.0) == [
+    assert gudhi.sparsify_point_set(points=point_set, min_squared_dist=0.999) == point_set
+    assert gudhi.sparsify_point_set(points=point_set, min_squared_dist=1.001) == [
         [0, 1],
         [1, 0],
     ]
-    assert gudhi.sparsify_point_set(points=point_set, min_squared_dist=2.01) == [[0, 1]]
+    assert gudhi.sparsify_point_set(points=point_set, min_squared_dist=1.999) == [
+        [0, 1],
+        [1, 0],
+    ]
+    assert gudhi.sparsify_point_set(points=point_set, min_squared_dist=2.001) == [[0, 1]]
 
     assert (
         len(gudhi.sparsify_point_set(off_file="subsample.off", min_squared_dist=0.0))
@@ -157,11 +161,11 @@ def test_simple_sparsify_points():
         == 5
     )
     assert (
-        len(gudhi.sparsify_point_set(off_file="subsample.off", min_squared_dist=40.0))
+        len(gudhi.sparsify_point_set(off_file="subsample.off", min_squared_dist=40.1))
         == 4
     )
     assert (
-        len(gudhi.sparsify_point_set(off_file="subsample.off", min_squared_dist=90.0))
+        len(gudhi.sparsify_point_set(off_file="subsample.off", min_squared_dist=89.9))
         == 3
     )
     assert (
@@ -169,7 +173,7 @@ def test_simple_sparsify_points():
         == 2
     )
     assert (
-        len(gudhi.sparsify_point_set(off_file="subsample.off", min_squared_dist=325.0))
+        len(gudhi.sparsify_point_set(off_file="subsample.off", min_squared_dist=324.9))
         == 2
     )
     assert (