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Diffstat (limited to 'include/gudhi/Landmark_choice_by_furthest_point.h')
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diff --git a/include/gudhi/Landmark_choice_by_furthest_point.h b/include/gudhi/Landmark_choice_by_furthest_point.h new file mode 100644 index 00000000..df93155b --- /dev/null +++ b/include/gudhi/Landmark_choice_by_furthest_point.h @@ -0,0 +1,105 @@ +/* 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): Siargey Kachanovich + * + * Copyright (C) 2015 INRIA Sophia Antipolis-Méditerranée (France) + * + * 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 LANDMARK_CHOICE_BY_FURTHEST_POINT_H_ +#define LANDMARK_CHOICE_BY_FURTHEST_POINT_H_ + +#include <boost/range/size.hpp> + +#include <limits> // for numeric_limits<> +#include <iterator> +#include <algorithm> // for sort +#include <vector> + +namespace Gudhi { + +namespace witness_complex { + + typedef std::vector<int> typeVectorVertex; + + /** + * \ingroup witness_complex + * \brief Landmark choice strategy by iteratively adding the furthest witness from the + * current landmark set as the new landmark. + * \details It chooses nbL landmarks from a random access range `points` and + * writes {witness}*{closest landmarks} matrix in `knn`. + * + * The type KNearestNeighbors can be seen as + * Witness_range<Closest_landmark_range<Vertex_handle>>, where + * Witness_range and Closest_landmark_range are random access ranges + * + */ + + template <typename KNearestNeighbours, + typename Point_random_access_range> + void landmark_choice_by_furthest_point(Point_random_access_range const &points, + int nbL, + KNearestNeighbours &knn) { + int nb_points = boost::size(points); + assert(nb_points >= nbL); + // distance matrix witness x landmarks + std::vector<std::vector<double>> wit_land_dist(nb_points, std::vector<double>()); + // landmark list + typeVectorVertex chosen_landmarks; + + knn = KNearestNeighbours(nb_points, std::vector<int>()); + int current_number_of_landmarks = 0; // counter for landmarks + double curr_max_dist = 0; // used for defining the furhest point from L + const double infty = std::numeric_limits<double>::infinity(); // infinity (see next entry) + std::vector< double > dist_to_L(nb_points, infty); // vector of current distances to L from points + + // TODO(SK) Consider using rand_r(...) instead of rand(...) for improved thread safety + // or better yet std::uniform_int_distribution + int rand_int = rand() % nb_points; + int curr_max_w = rand_int; // For testing purposes a pseudo-random number is used here + + for (current_number_of_landmarks = 0; current_number_of_landmarks != nbL; current_number_of_landmarks++) { + // curr_max_w at this point is the next landmark + chosen_landmarks.push_back(curr_max_w); + unsigned i = 0; + for (auto& p : points) { + double curr_dist = euclidean_distance(p, *(std::begin(points) + chosen_landmarks[current_number_of_landmarks])); + wit_land_dist[i].push_back(curr_dist); + knn[i].push_back(current_number_of_landmarks); + if (curr_dist < dist_to_L[i]) + dist_to_L[i] = curr_dist; + ++i; + } + curr_max_dist = 0; + for (i = 0; i < dist_to_L.size(); i++) + if (dist_to_L[i] > curr_max_dist) { + curr_max_dist = dist_to_L[i]; + curr_max_w = i; + } + } + for (int i = 0; i < nb_points; ++i) + std::sort(std::begin(knn[i]), + std::end(knn[i]), + [&wit_land_dist, i](int a, int b) { + return wit_land_dist[i][a] < wit_land_dist[i][b]; }); + } + +} // namespace witness_complex + +} // namespace Gudhi + +#endif // LANDMARK_CHOICE_BY_FURTHEST_POINT_H_ |