\( \newcommand{\E}{\mathrm{E}} \) \( \newcommand{\A}{\mathrm{A}} \) \( \newcommand{\R}{\mathrm{R}} \) \( \newcommand{\N}{\mathrm{N}} \) \( \newcommand{\Q}{\mathrm{Q}} \) \( \newcommand{\Z}{\mathrm{Z}} \) \( \def\ccSum #1#2#3{ \sum_{#1}^{#2}{#3} } \def\ccProd #1#2#3{ \sum_{#1}^{#2}{#3} }\)

CGAL 4.8 - dD Spatial Searching

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Spatial_searching/searching_sphere_orthogonally.cpp
#include <CGAL/Simple_cartesian.h>
#include <CGAL/point_generators_2.h>
#include <CGAL/Euclidean_distance.h>
#include <CGAL/Orthogonal_k_neighbor_search.h>
#include <CGAL/Search_traits_2.h>
typedef CGAL::Simple_cartesian<double> Kernel;
typedef Kernel::Point_2 Point_2;
typedef CGAL::Random_points_in_square_2<Point_2> Random_points_iterator;
typedef Kernel::Circle_2 Sphere_2;
typedef CGAL::Search_traits_2<Kernel> TreeTraits;
typedef CGAL::Euclidean_distance<TreeTraits> Distance;
typedef CGAL::Orthogonal_k_neighbor_search<TreeTraits, Distance> Neighbor_search;
typedef TreeTraits::Construct_center_d Construct_center_d;
typedef TreeTraits::Compute_squared_radius_d Compute_squared_radius_d;
typedef Neighbor_search::Tree Tree;
int main() {
const int N = 1000;
const unsigned int K = 10;
Tree tree;
Random_points_iterator rpg;
for(int i = 0; i < N; i++){
tree.insert(*rpg++);
}
Sphere_2 query(*rpg,0.5);
Distance tr_dist;
Point_2 center = Construct_center_d()(query);
Neighbor_search N1(tree, center, K, 0.0, false); // eps=0.0, nearest=false
std::cout << "For the query circle " << std::endl
<< "The " << K << " approximate furthest neighbors are: " << std::endl;
double radius = Compute_squared_radius_d()(query);
for (Neighbor_search::iterator it = N1.begin();it != N1.end();it++) {
std::cout << " Point " << it->first << " at distance = " << tr_dist.inverse_of_transformed_distance(it->second - radius) << std::endl;
}
return 0;
}