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Diffstat (limited to 'src/Witness_complex/include/gudhi/Landmark_choice_by_random_point.h')
| -rw-r--r-- | src/Witness_complex/include/gudhi/Landmark_choice_by_random_point.h | 82 |
1 files changed, 82 insertions, 0 deletions
diff --git a/src/Witness_complex/include/gudhi/Landmark_choice_by_random_point.h b/src/Witness_complex/include/gudhi/Landmark_choice_by_random_point.h new file mode 100644 index 00000000..bc3e72d9 --- /dev/null +++ b/src/Witness_complex/include/gudhi/Landmark_choice_by_random_point.h @@ -0,0 +1,82 @@ +/* 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 GUDHI_LANDMARK_CHOICE_BY_RANDOM_POINT_H_ +#define GUDHI_LANDMARK_CHOICE_BY_RANDOM_POINT_H_ + +/** + * \class Landmark_choice_by_random_point + * \brief The class `Landmark_choice_by_random_point` allows to construct the matrix + * of closest landmarks per witness by iteratively choosing a random non-chosen witness + * as a new landmark. + * \ingroup witness_complex + */ + +class Landmark_choice_by_random_point { + + + /** \brief Landmark choice strategy by taking random vertices for landmarks. + * It takes a random access range points and outputs a matrix {witness}*{closest landmarks} + * in knn. + */ + + template <typename KNearestNeighbours, + typename Point_random_access_range> + void landmark_choice_by_random_points(Point_random_access_range &points, KNearestNeighbours &knn) + { + int nbP = points.end() - points.begin(); + std::set<int> &landmarks; + int current_number_of_landmarks=0; // counter for landmarks + + int chosen_landmark = rand()%nbP; + for (current_number_of_landmarks = 0; current_number_of_landmarks != nbL; current_number_of_landmarks++) + { + while (landmarks.find(chosen_landmark) != landmarks.end()) + chosen_landmark = rand()% nbP; + landmarks.insert(chosen_landmark); + } + + int D = points.begin().size(); + typedef std::pair<double,int> dist_i; + typedef bool (*comp)(dist_i,dist_i); + for (int points_i = 0; points_i < nbP; points_i++) + { + std::priority_queue<dist_i, std::vector<dist_i>, comp> l_heap([&](dist_i j1, dist_i j2){return j1.first > j2.first;}); + std::set<int>::iterator landmarks_it; + int landmarks_i = 0; + for (landmarks_it = landmarks.begin(), landmarks_i=0; landmarks_it != landmarks.end(); landmarks_it++, landmarks_i++) + { + dist_i dist = std::make_pair(euclidean_distance(points[points_i],points[*landmarks_it]), landmarks_i); + l_heap.push(dist); + } + for (int i = 0; i < D+1; i++) + { + dist_i dist = l_heap.top(); + knn[points_i].push_back(dist.second); + l_heap.pop(); + } + } + } + +}; + +#endif |