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/* This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT.
* See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details.
* Author(s): Clement Jamin
*
* Copyright (C) 2016 Inria
*
* Modification(s):
* - YYYY/MM Author: Description of the modification
*/
#ifndef DOC_SUBSAMPLING_INTRO_SUBSAMPLING_H_
#define DOC_SUBSAMPLING_INTRO_SUBSAMPLING_H_
// needs namespace for Doxygen to link on classes
namespace Gudhi {
// needs namespace for Doxygen to link on classes
namespace subsampling {
/** \defgroup subsampling Subsampling
*
* \author Clément Jamin, Siargey Kachanovich
*
* @{
*
* \section subsamplingintroduction Introduction
*
* This Gudhi component offers methods to subsample a set of points.
*
* \section sparsifyexamples Example: sparsify_point_set
*
* This example outputs a subset of the input points so that the
* squared distance between any two points
* is greater than or equal to 0.4.
*
* \include Subsampling/example_sparsify_point_set.cpp
*
* \section farthestpointexamples Example: choose_n_farthest_points
*
* This example outputs a subset of 100 points obtained by González algorithm,
* starting with a random point.
*
* \include Subsampling/example_choose_n_farthest_points.cpp
*
* \section randompointexamples Example: pick_n_random_points
*
* This example outputs a subset of 100 points picked randomly.
*
* \include Subsampling/example_pick_n_random_points.cpp
*/
/** @} */ // end defgroup subsampling
} // namespace subsampling
} // namespace Gudhi
#endif // DOC_SUBSAMPLING_INTRO_SUBSAMPLING_H_
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