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authorROUVREAU Vincent <vincent.rouvreau@inria.fr>2019-09-09 16:15:18 +0200
committerROUVREAU Vincent <vincent.rouvreau@inria.fr>2019-09-09 16:15:18 +0200
commitd066372ac3ce5256fcd780a9dfc8e8f871fe65aa (patch)
tree12d609b56bc6052d4f0fa06981d4a7883ed1122c /src/python/doc/rips_complex_user.rst
parent68753b3c28321e28eedd5829c94234da84e25c8d (diff)
parentf510a7e607b46ba8cc118cd787ff9b0b8bff091f (diff)
Merge branch 'master' into split_gudhi_python_in_modules
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diff --git a/src/python/doc/rips_complex_user.rst b/src/python/doc/rips_complex_user.rst
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--- a/src/python/doc/rips_complex_user.rst
+++ b/src/python/doc/rips_complex_user.rst
@@ -19,7 +19,9 @@ The `Rips complex <https://en.wikipedia.org/wiki/Vietoris%E2%80%93Rips_complex>`
generalizes proximity (:math:`\varepsilon`-ball) graphs to higher dimensions. The vertices correspond to the input
points, and a simplex is present if and only if its diameter is smaller than some parameter α. Considering all
parameters α defines a filtered simplicial complex, where the filtration value of a simplex is its diameter.
-The filtration can be restricted to values α smaller than some threshold, to reduce its size.
+The filtration can be restricted to values α smaller than some threshold, to reduce its size. Beware that some
+people define the Rips complex using a bound of 2α instead of α, particularly when comparing it to an ambient
+Čech complex. They end up with the same combinatorial object, but filtration values which are half of ours.
The input discrete metric space can be provided as a point cloud plus a distance function, or as a distance matrix.