#include <CGAL/Simple_cartesian.h>
#include <CGAL/point_generators_2.h>
#include <CGAL/Search_traits_2.h>
#include <CGAL/Orthogonal_k_neighbor_search.h>
#include <cmath>
typedef R::Point_2 Point_d;
typedef CGAL::Random_points_in_square_2<Point_d> Random_points_iterator;
typedef Neighbor_search::Tree Tree;
int main()
{
const unsigned int N = 1000;
Random_points_iterator rpit( 1.0);
Fair fair(5);
Tree tree(N_Random_points_iterator(rpit,0),
N_Random_points_iterator(N),
fair);
Point_d query(0,0);
Neighbor_search search(tree, query, N);
for(Neighbor_search::iterator it = search.begin(); it != search.end(); ++it)
std::cout << it->first << " "<< std::sqrt(it->second) << std::endl;
return 0;
}
The class Euclidean_distance provides an implementation of the concept OrthogonalDistance,...
Definition: Euclidean_distance.h:20
Implements the fair splitting rule.
Definition: Splitters.h:30
The class Orthogonal_k_neighbor_search implements approximatek-nearest and k-furthest neighbor search...
Definition: Orthogonal_k_neighbor_search.h:31
The class Search_traits_2 can be used as a template parameter of the kd tree and the search classes.
Definition: Search_traits_2.h:19