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diff --git a/src/python/doc/barycenter_user.rst b/src/python/doc/barycenter_user.rst deleted file mode 100644 index 83e9bebb..00000000 --- a/src/python/doc/barycenter_user.rst +++ /dev/null @@ -1,60 +0,0 @@ -:orphan: - -.. To get rid of WARNING: document isn't included in any toctree - -Barycenter user manual -================================ -Definition ----------- - -.. include:: barycenter_sum.inc - -This implementation is based on ideas from "Frechet means for distribution of -persistence diagrams", Turner et al. 2014. - -Function --------- -.. autofunction:: gudhi.barycenter.lagrangian_barycenter - - -Basic example -------------- - -This example computes the Frechet mean (aka Wasserstein barycenter) between -four persistence diagrams. -It is initialized on the 4th diagram. -As the algorithm is not convex, its output depends on the initialization and -is only a local minimum of the objective function. -Initialization can be either given as an integer (in which case the i-th -diagram of the list is used as initial estimate) or as a diagram. -If None, it will randomly select one of the diagram of the list -as initial estimate. -Note that persistence diagrams must be submitted as -(n x 2) numpy arrays and must not contain inf values. - -.. testcode:: - - import gudhi.barycenter - import numpy as np - - dg1 = np.array([[0.2, 0.5]]) - dg2 = np.array([[0.2, 0.7]]) - dg3 = np.array([[0.3, 0.6], [0.7, 0.8], [0.2, 0.3]]) - dg4 = np.array([]) - pdiagset = [dg1, dg2, dg3, dg4] - bary = gudhi.barycenter.lagrangian_barycenter(pdiagset=pdiagset,init=3) - - message = "Wasserstein barycenter estimated:" - print(message) - print(bary) - -The output is: - -.. testoutput:: - - Wasserstein barycenter estimated: - [[0.27916667 0.55416667] - [0.7375 0.7625 ] - [0.2375 0.2625 ]] - - |