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Diffstat (limited to 'include/gudhi/sparsify_point_set.h')
| -rw-r--r-- | include/gudhi/sparsify_point_set.h | 113 |
1 files changed, 0 insertions, 113 deletions
diff --git a/include/gudhi/sparsify_point_set.h b/include/gudhi/sparsify_point_set.h deleted file mode 100644 index db10e0b1..00000000 --- a/include/gudhi/sparsify_point_set.h +++ /dev/null @@ -1,113 +0,0 @@ -/* This file is part of the Gudhi Library. The Gudhi library - * (Geometric Understanding in Higher Dimensions) is a generic C++ - * library for computational topology. - * - * Author(s): Clement Jamin - * - * Copyright (C) 2016 Inria - * - * This program is free software: you can redistribute it and/or modify - * it under the terms of the GNU General Public License as published by - * the Free Software Foundation, either version 3 of the License, or - * (at your option) any later version. - * - * This program is distributed in the hope that it will be useful, - * but WITHOUT ANY WARRANTY; without even the implied warranty of - * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - * GNU General Public License for more details. - * - * You should have received a copy of the GNU General Public License - * along with this program. If not, see <http://www.gnu.org/licenses/>. - */ - -#ifndef SPARSIFY_POINT_SET_H_ -#define SPARSIFY_POINT_SET_H_ - -#include <gudhi/Kd_tree_search.h> -#ifdef GUDHI_SUBSAMPLING_PROFILING -#include <gudhi/Clock.h> -#endif - -#include <cstddef> -#include <vector> - -namespace Gudhi { - -namespace subsampling { - -/** - * \ingroup subsampling - * \brief Outputs a subset of the input points so that the - * squared distance between any two points - * is greater than or equal to `min_squared_dist`. - * - * \tparam Kernel must be a model of the <a target="_blank" - * href="http://doc.cgal.org/latest/Spatial_searching/classSearchTraits.html">SearchTraits</a> - * concept, such as the <a target="_blank" - * href="http://doc.cgal.org/latest/Kernel_d/classCGAL_1_1Epick__d.html">CGAL::Epick_d</a> class, which - * can be static if you know the ambiant dimension at compile-time, or dynamic if you don't. - * \tparam Point_range Range whose value type is Kernel::Point_d. It must provide random-access - * via `operator[]` and the points should be stored contiguously in memory. - * \tparam OutputIterator Output iterator whose value type is Kernel::Point_d. - * - * @param[in] k A kernel object. - * @param[in] input_pts Const reference to the input points. - * @param[in] min_squared_dist Minimum squared distance separating the output points. - * @param[out] output_it The output iterator. - */ -template <typename Kernel, typename Point_range, typename OutputIterator> -void -sparsify_point_set( - const Kernel &k, Point_range const& input_pts, - typename Kernel::FT min_squared_dist, - OutputIterator output_it) { - typedef typename Gudhi::spatial_searching::Kd_tree_search< - Kernel, Point_range> Points_ds; - -#ifdef GUDHI_SUBSAMPLING_PROFILING - Gudhi::Clock t; -#endif - - Points_ds points_ds(input_pts); - - std::vector<bool> dropped_points(input_pts.size(), false); - - // Parse the input points, and add them if they are not too close to - // the other points - std::size_t pt_idx = 0; - for (typename Point_range::const_iterator it_pt = input_pts.begin(); - it_pt != input_pts.end(); - ++it_pt, ++pt_idx) { - if (dropped_points[pt_idx]) - continue; - - *output_it++ = *it_pt; - - auto ins_range = points_ds.incremental_nearest_neighbors(*it_pt); - - // If another point Q is closer that min_squared_dist, mark Q to be dropped - for (auto const& neighbor : ins_range) { - std::size_t neighbor_point_idx = neighbor.first; - // If the neighbor is too close, we drop the neighbor - if (neighbor.second < min_squared_dist) { - // N.B.: If neighbor_point_idx < pt_idx, - // dropped_points[neighbor_point_idx] is already true but adding a - // test doesn't make things faster, so why bother? - dropped_points[neighbor_point_idx] = true; - } else { - break; - } - } - } - -#ifdef GUDHI_SUBSAMPLING_PROFILING - t.end(); - std::cerr << "Point set sparsified in " << t.num_seconds() - << " seconds." << std::endl; -#endif -} - -} // namespace subsampling -} // namespace Gudhi - -#endif // SPARSIFY_POINT_SET_H_ |