CGAL 6.2 - dD Spatial Searching

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Spatial_searching/general_neighbor_searching.cpp
#include <CGAL/Epick_d.h>
#include <CGAL/point_generators_d.h>
#include <CGAL/Manhattan_distance_iso_box_point.h>
#include <CGAL/K_neighbor_search.h>
#include <CGAL/Search_traits_d.h>
typedef CGAL::Epick_d<CGAL::Dimension_tag<4> > Kernel;
typedef Kernel::Point_d Point_d;
typedef CGAL::Random_points_in_cube_d<Point_d> Random_points_iterator;
typedef Kernel::Iso_box_d Iso_box_d;
typedef Kernel TreeTraits;
typedef CGAL::Manhattan_distance_iso_box_point<TreeTraits> Distance;
typedef CGAL::K_neighbor_search<TreeTraits, Distance> Neighbor_search;
typedef Neighbor_search::Tree Tree;
int main()
{
const int N = 1000;
const unsigned int K = 10;
Tree tree;
Random_points_iterator rpit(4,1000.0);
for(int i = 0; i < N; i++)
tree.insert(*rpit++);
Point_d pp(0.1,0.1,0.1,0.1);
Point_d qq(0.2,0.2,0.2,0.2);
Iso_box_d query(pp,qq);
Distance tr_dist;
Neighbor_search N1(tree, query, 5, 10.0, false); // eps=10.0, nearest=false
std::cout << "For query rectangle = [0.1, 0.2]^4 " << std::endl
<< "the " << K << " approximate furthest neighbors are: " << std::endl;
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) << std::endl;
}
return 0;
}
CGAL::K_neighbor_search
The class K_neighbor_search implements approximate k-nearest and k-furthest neighbor searching using ...
Definition: K_neighbor_search.h:31
CGAL::Manhattan_distance_iso_box_point
The class Manhattan_distance_iso_box_point provides an implementation of the GeneralDistance concept ...
Definition: Manhattan_distance_iso_box_point.h:22
CGAL::Random_points_in_cube_d
Kernel
CGAL::Epick_d