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author | vrouvrea <vrouvrea@636b058d-ea47-450e-bf9e-a15bfbe3eedb> | 2017-03-03 08:42:09 +0000 |
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committer | vrouvrea <vrouvrea@636b058d-ea47-450e-bf9e-a15bfbe3eedb> | 2017-03-03 08:42:09 +0000 |
commit | 78f3ee686f87c30b19320dc51ce3d611b764ee3c (patch) | |
tree | 79dc0fa194329974c3381ee0e638cc2f532dadc5 /src/Witness_complex/include/gudhi/Construct_closest_landmark_table.h | |
parent | f7082d14b1c30b1b5c15741aa4bc183695861d10 (diff) | |
parent | effc4723dfa2604c8c505b0dfff48b4cab8012ca (diff) |
Merge last trunk modifications
git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/gudhi_doc_2.0.0@2140 636b058d-ea47-450e-bf9e-a15bfbe3eedb
Former-commit-id: 7213c9eb7d01812a5dcf0133ca29cfdca6121519
Diffstat (limited to 'src/Witness_complex/include/gudhi/Construct_closest_landmark_table.h')
-rw-r--r-- | src/Witness_complex/include/gudhi/Construct_closest_landmark_table.h | 92 |
1 files changed, 0 insertions, 92 deletions
diff --git a/src/Witness_complex/include/gudhi/Construct_closest_landmark_table.h b/src/Witness_complex/include/gudhi/Construct_closest_landmark_table.h deleted file mode 100644 index a8cdd096..00000000 --- a/src/Witness_complex/include/gudhi/Construct_closest_landmark_table.h +++ /dev/null @@ -1,92 +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): Siargey Kachanovich - * - * Copyright (C) 2015 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 CONSTRUCT_CLOSEST_LANDMARK_TABLE_H_ -#define CONSTRUCT_CLOSEST_LANDMARK_TABLE_H_ - -#include <boost/range/size.hpp> - -#include <queue> // for priority_queue<> -#include <utility> // for pair<> -#include <iterator> -#include <vector> -#include <set> - -namespace Gudhi { - -namespace witness_complex { - - /** - * \ingroup witness_complex - * \brief Construct the closest landmark tables for all witnesses. - * \details Output a table 'knn', each line of which represents a witness and - * consists of landmarks sorted by - * euclidean distance from the corresponding witness. - * - * The type WitnessContainer is a random access range and - * the type LandmarkContainer is a range. - * 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 and - * Vertex_handle is the label type of a vertex in a simplicial complex. - * Closest_landmark_range needs to have push_back operation. - */ - - template <typename FiltrationValue, - typename WitnessContainer, - typename LandmarkContainer, - typename KNearestNeighbours> - void construct_closest_landmark_table(WitnessContainer const &points, - LandmarkContainer const &landmarks, - KNearestNeighbours &knn) { - int nbP = boost::size(points); - assert(nbP >= boost::size(landmarks)); - - int dim = boost::size(*std::begin(points)); - typedef std::pair<double, int> dist_i; - typedef bool (*comp)(dist_i, dist_i); - knn = KNearestNeighbours(nbP); - 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; - }); - typename LandmarkContainer::const_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], *landmarks_it), - landmarks_i); - l_heap.push(dist); - } - for (int i = 0; i < dim + 1; i++) { - dist_i dist = l_heap.top(); - knn[points_i].push_back(dist.second); - l_heap.pop(); - } - } - } - -} // namespace witness_complex - -} // namespace Gudhi - -#endif // CONSTRUCT_CLOSEST_LANDMARK_TABLE_H_ |