filtration value fixed

2 files changed, 12 insertions, 2 deletions

diff --git a/src/python/gudhi/weighted_rips_complex.py b/src/python/gudhi/weighted_rips_complex.py
index 9df2ddf9..7e504b2c 100644
--- a/src/python/gudhi/weighted_rips_complex.py
+++ b/src/python/gudhi/weighted_rips_complex.py
@@ -51,7 +51,7 @@ class WeightedRipsComplex:
                 st.insert([i], F[i])
         for i in range(num_pts):
             for j in range(i):
-                value = (dist[i][j] + F[i] + F[j]) / 2
+                value = max(F[i], F[j], (dist[i][j] + F[i] + F[j]) / 2)
                 if value < self.max_filtration:
                     st.insert([i,j], filtration=value)
                     
diff --git a/src/python/test/test_weighted_rips.py b/src/python/test/test_weighted_rips.py
index 7896fb78..a3235276 100644
--- a/src/python/test/test_weighted_rips.py
+++ b/src/python/test/test_weighted_rips.py
@@ -14,13 +14,23 @@ import numpy as np
 from scipy.spatial.distance import cdist
 import pytest
 
+def test_non_dtm_rips_complex():
+      dist = [[], [1]]
+      weights = [1, 100]
+      w_rips = WeightedRipsComplex(distance_matrix=dist, weights=weights)
+      st = w_rips.create_simplex_tree(max_dimension=2)
+      assert st.filtration([0,1]) == pytest.approx(100.0)
+
+
 def test_dtm_rips_complex():
     pts = np.array([[2.0, 2], [0, 1], [3, 4]])
     dist = cdist(pts,pts)
     dtm = DTM(2, q=2, metric="precomputed")    
     r = dtm.fit_transform(dist)
-    w_rips = WeightedRipsComplex(distance_mattix=dist, weights=r)
+    w_rips = WeightedRipsComplex(distance_matrix=dist, weights=r)
     st = w_rips.create_simplex_tree(max_dimension=2)
+    st.persistence()
     persistence_intervals0 = st.persistence_intervals_in_dimension(0)
     assert persistence_intervals0 == pytest.approx(np.array([[1.58113883, 2.69917282],[1.58113883, 2.69917282], [1.58113883, float("inf")]]))
     
+