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authorVincent Rouvreau <10407034+VincentRouvreau@users.noreply.github.com>2022-02-16 08:51:34 +0100
committerGitHub <noreply@github.com>2022-02-16 08:51:34 +0100
commit1c1f8b98b37322d728d8a226e9ec04e21f995b42 (patch)
tree4abffba172ed4c169710a19dae3931153e2a4b42 /src
parent5e9f99b8b8ad7bf97a070b3578605a48fb484297 (diff)
parent362ac0955656d7c131e042901d6606fdeaab7fc9 (diff)
Merge pull request #585 from mglisse/docdtm
More details in the doc of weighted rips
Diffstat (limited to 'src')
-rw-r--r--src/python/gudhi/weighted_rips_complex.py6
1 files changed, 4 insertions, 2 deletions
diff --git a/src/python/gudhi/weighted_rips_complex.py b/src/python/gudhi/weighted_rips_complex.py
index 0541572b..16f63c3d 100644
--- a/src/python/gudhi/weighted_rips_complex.py
+++ b/src/python/gudhi/weighted_rips_complex.py
@@ -12,9 +12,11 @@ from gudhi import SimplexTree
class WeightedRipsComplex:
"""
Class to generate a weighted Rips complex from a distance matrix and weights on vertices,
- in the way described in :cite:`dtmfiltrations`.
+ in the way described in :cite:`dtmfiltrations` with `p=1`. The filtration value of vertex `i` is `2*weights[i]`,
+ and the filtration value of edge `ij` is `distance_matrix[i][j]+weights[i]+weights[j]`,
+ or the maximum of the filtrations of its extremities, whichever is largest.
Remark that all the filtration values are doubled compared to the definition in the paper
- for the consistency with RipsComplex.
+ for consistency with RipsComplex.
"""
def __init__(self,
distance_matrix,