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authorMarc Glisse <marc.glisse@inria.fr>2022-02-14 23:33:38 +0100
committerMarc Glisse <marc.glisse@inria.fr>2022-02-14 23:33:38 +0100
commit362ac0955656d7c131e042901d6606fdeaab7fc9 (patch)
tree4abffba172ed4c169710a19dae3931153e2a4b42
parent5e9f99b8b8ad7bf97a070b3578605a48fb484297 (diff)
More details in the doc of weighted rips
-rw-r--r--biblio/bibliography.bib25
-rw-r--r--src/python/gudhi/weighted_rips_complex.py6
2 files changed, 28 insertions, 3 deletions
diff --git a/biblio/bibliography.bib b/biblio/bibliography.bib
index b5afff52..e75e8db2 100644
--- a/biblio/bibliography.bib
+++ b/biblio/bibliography.bib
@@ -1280,7 +1280,7 @@ year = "2011"
publisher={Springer}
}
-@inproceedings{dtmfiltrations,
+@inproceedings{dtmfiltrationsconf,
author = {Hirokazu Anai and
Fr{\'{e}}d{\'{e}}ric Chazal and
Marc Glisse and
@@ -1305,6 +1305,29 @@ year = "2011"
bibsource = {dblp computer science bibliography, https://dblp.org}
}
+@InProceedings{dtmfiltrations,
+author="Anai, Hirokazu
+and Chazal, Fr{\'e}d{\'e}ric
+and Glisse, Marc
+and Ike, Yuichi
+and Inakoshi, Hiroya
+and Tinarrage, Rapha{\"e}l
+and Umeda, Yuhei",
+editor="Baas, Nils A.
+and Carlsson, Gunnar E.
+and Quick, Gereon
+and Szymik, Markus
+and Thaule, Marius",
+title="DTM-Based Filtrations",
+booktitle="Topological Data Analysis",
+year="2020",
+publisher="Springer International Publishing",
+address="Cham",
+pages="33--66",
+isbn="978-3-030-43408-3",
+doi="10.1007/978-3-030-43408-3_2",
+}
+
@InProceedings{edgecollapsesocg2020,
author = {Jean-Daniel Boissonnat and Siddharth Pritam},
title = {{Edge Collapse and Persistence of Flag Complexes}},
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,