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.. table::
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| .. figure:: | The p-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 achieve by| |
| :figclass: align-center | a perfect matching between the points of the two diagrams (+ all the | :Introduced in: GUDHI 3.1.0 |
| | diagonal points), where the value of a matching is defined as the | |
| Wasserstein distance is the p-th root of the sum of the | p-th root of the sum of all edges lengths to the power p. Edges | :Copyright: MIT |
| edges lengths to the power p. | lengths are measured in norm q, for :math:`1 \leq q \leq \infty`. | |
| | | :Requires: Python Optimal Transport (POT) :math:`\geq` 0.5.1 |
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| * :doc:`wasserstein_distance_user` | |
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