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diff --git a/src/Spatial_searching/test/test_Kd_tree_search.cpp b/src/Spatial_searching/test/test_Kd_tree_search.cpp
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+/* This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT.
+ * See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details.
+ * Author(s): Clement Jamin
+ *
+ * Copyright (C) 2016 Inria
+ *
+ * Modification(s):
+ * - YYYY/MM Author: Description of the modification
+ */
+
+#define BOOST_TEST_DYN_LINK
+#define BOOST_TEST_MODULE Spatial_searching - test Kd_tree_search
+#include <boost/test/unit_test.hpp>
+
+#include <gudhi/Kd_tree_search.h>
+
+#include <CGAL/Epick_d.h>
+#include <CGAL/Random.h>
+
+#include <vector>
+
+BOOST_AUTO_TEST_CASE(test_Kd_tree_search) {
+ typedef CGAL::Epick_d<CGAL::Dimension_tag<4> > K;
+ typedef K::FT FT;
+ typedef K::Point_d Point;
+ typedef std::vector<Point> Points;
+
+ typedef Gudhi::spatial_searching::Kd_tree_search<
+ K, Points> Points_ds;
+
+ CGAL::Random rd;
+
+ Points points;
+ for (int i = 0; i < 500; ++i)
+ points.push_back(Point(rd.get_double(-1., 1), rd.get_double(-1., 1), rd.get_double(-1., 1), rd.get_double(-1., 1)));
+
+ Points_ds points_ds(points);
+
+ // Test k_nearest_neighbors
+ std::size_t closest_pt_index =
+ points_ds.k_nearest_neighbors(points[10], 1, false).begin()->first;
+ BOOST_CHECK(closest_pt_index == 10);
+
+ auto kns_range = points_ds.k_nearest_neighbors(points[20], 10, true);
+
+ std::vector<std::size_t> knn_result;
+ FT last_dist = -1.;
+ for (auto const& nghb : kns_range) {
+ BOOST_CHECK(nghb.second > last_dist);
+ knn_result.push_back(nghb.second);
+ last_dist = nghb.second;
+ }
+
+ // Test incremental_nearest_neighbors
+ closest_pt_index =
+ points_ds.incremental_nearest_neighbors(points[10]).begin()->first;
+ BOOST_CHECK(closest_pt_index == 10);
+
+ auto inn_range = points_ds.incremental_nearest_neighbors(points[20]);
+
+ std::vector<std::size_t> inn_result;
+ last_dist = -1.;
+ auto inn_it = inn_range.begin();
+ for (int i = 0; i < 10; ++inn_it, ++i) {
+ auto const& nghb = *inn_it;
+ BOOST_CHECK(nghb.second > last_dist);
+ inn_result.push_back(nghb.second);
+ last_dist = nghb.second;
+ }
+
+ // Same result for KNN and INN?
+ BOOST_CHECK(knn_result == inn_result);
+
+ // Test k_furthest_neighbors
+ auto kfn_range = points_ds.k_furthest_neighbors(points[20], 10, true);
+
+ std::vector<std::size_t> kfn_result;
+ last_dist = kfn_range.begin()->second;
+ for (auto const& nghb : kfn_range) {
+ BOOST_CHECK(nghb.second <= last_dist);
+ kfn_result.push_back(nghb.second);
+ last_dist = nghb.second;
+ }
+
+ // Test k_furthest_neighbors
+ auto ifn_range = points_ds.incremental_furthest_neighbors(points[20]);
+
+ std::vector<std::size_t> ifn_result;
+ last_dist = ifn_range.begin()->second;
+ auto ifn_it = ifn_range.begin();
+ for (int i = 0; i < 10; ++ifn_it, ++i) {
+ auto const& nghb = *ifn_it;
+ BOOST_CHECK(nghb.second <= last_dist);
+ ifn_result.push_back(nghb.second);
+ last_dist = nghb.second;
+ }
+
+ // Same result for KFN and IFN?
+ BOOST_CHECK(kfn_result == ifn_result);
+
+ // Test all_near_neighbors
+ Point rs_q(rd.get_double(-1., 1), rd.get_double(-1., 1), rd.get_double(-1., 1), rd.get_double(-1., 1));
+ std::vector<std::size_t> rs_result;
+ points_ds.all_near_neighbors(rs_q, 0.5, std::back_inserter(rs_result));
+ K k;
+ for (auto const& p_idx : rs_result)
+ BOOST_CHECK(k.squared_distance_d_object()(points[p_idx], rs_q) <= 0.5);
+}