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authorMarc Glisse <marc.glisse@inria.fr>2020-04-14 19:49:49 +0200
committerMarc Glisse <marc.glisse@inria.fr>2020-04-14 19:49:49 +0200
commit3f1e4bf5f139afe887ae501f20c5d3f40b5a6f79 (patch)
tree936aa887b1e7a0e23854262f17a5d21cf2f604c1 /src/python/doc/wasserstein_distance_sum.inc
parent9518287cfa2a62948ede2e7d17d5c9f29092e0f4 (diff)
parent6d02ca0e077cc9750275abdfc024429cec0ba5a5 (diff)
Merge remote-tracking branch 'origin/master' into dtm
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+-----------------------------------------------------------------+----------------------------------------------------------------------+------------------------------------------------------------------+
| .. figure:: | The q-Wasserstein distance measures the similarity between two | :Author: Theo Lacombe |
- | ../../doc/Bottleneck_distance/perturb_pd.png | persistence diagrams. It's the minimum value c that can be achieved | |
- | :figclass: align-center | by a perfect matching between the points of the two diagrams (+ all | :Since: GUDHI 3.1.0 |
- | | diagonal points), where the value of a matching is defined as the | |
- | Wasserstein distance is the q-th root of the sum of the | q-th root of the sum of all edge lengths to the power q. Edge lengths| :License: MIT |
- | edge lengths to the power q. | are measured in norm p, for :math:`1 \leq p \leq \infty`. | |
+ | ../../doc/Bottleneck_distance/perturb_pd.png | persistence diagrams using the sum of all edges lengths (instead of | |
+ | :figclass: align-center | the maximum). It allows to define sophisticated objects such as | :Since: GUDHI 3.1.0 |
+ | | barycenters of a family of persistence diagrams. | |
+ | | | :License: MIT |
+ | | | |
| | | :Requires: Python Optimal Transport (POT) :math:`\geq` 0.5.1 |
+-----------------------------------------------------------------+----------------------------------------------------------------------+------------------------------------------------------------------+
| * :doc:`wasserstein_distance_user` | |