change of two too ambiguous citation keys ('dtm' and 'tomato')

hschreiber · May 17, 2024 · 03e0490 · 03e0490
1 parent b9c9888
commit 03e0490
Show file tree

Hide file tree

Showing 3 changed files with 5 additions and 4 deletions.
diff --git a/biblio/bibliography.bib b/biblio/bibliography.bib
@@ -316,7 +316,7 @@ @article{turner2014frechet
 % G
 %-----------------------------
 
-@article{dtm,
+@article{dtmgeoinference2011,
   author   = {Chazal, Fr{\'e}d{\'e}ric
               and Cohen-Steiner, David
               and M{\'e}rigot, Quentin},
@@ -503,7 +503,7 @@ @phdthesis{KachanovichThesis
 % P
 %-----------------------------
 
-@article{tomato,
+@article{tomato2013,
   author     = {Chazal, Fr\'{e}d\'{e}ric and Guibas, Leonidas J. and Oudot, Steve Y. and Skraba, Primoz},
   title      = {Persistence-Based Clustering in Riemannian Manifolds},
   year       = {2013},

diff --git a/src/python/doc/clustering.rst b/src/python/doc/clustering.rst
@@ -6,7 +6,7 @@
 Clustering manual
 =================
 
-We provide an implementation of ToMATo :cite:`tomato`, a persistence-based clustering algorithm. In short, this algorithm uses a density estimator and a neighborhood graph, starts with a mode-seeking phase (naive hill-climbing) to build initial clusters, and finishes by merging clusters based on their prominence.
+We provide an implementation of ToMATo :cite:`tomato2013`, a persistence-based clustering algorithm. In short, this algorithm uses a density estimator and a neighborhood graph, starts with a mode-seeking phase (naive hill-climbing) to build initial clusters, and finishes by merging clusters based on their prominence.
 
 The merging phase depends on a parameter, which is the minimum prominence a cluster needs to avoid getting merged into another, bigger cluster. This parameter determines the number of clusters, and for convenience we allow you to choose instead the number of clusters. Decreasing the prominence threshold defines a hierarchy of clusters: if 2 points are in separate clusters when we have k clusters, they are still in different clusters for k+1 clusters.
 

diff --git a/src/python/gudhi/point_cloud/dtm.py b/src/python/gudhi/point_cloud/dtm.py
@@ -17,7 +17,8 @@
 
 class DistanceToMeasure:
     """
-    Class to compute the distance to the empirical measure defined by a point set, as introduced in :cite:`dtm`.
+    Class to compute the distance to the empirical measure defined by a point set, 
+    as introduced in :cite:`dtmgeoinference2011`.
     """
 
     def __init__(self, k, q=2, **kwargs):