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+/* 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 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 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_