CGAL 5.6 - dD Spatial Searching
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Spatial_searching/using_fair_splitting_rule.cpp
#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 CGAL::Counting_iterator<Random_points_iterator> N_Random_points_iterator;
typedef CGAL::Search_traits_2<R> Traits;
typedef CGAL::Fair<Traits> Fair;
typedef Neighbor_search::Tree Tree;
int main()
{
const unsigned int N = 1000;
// generator for random data points in the square ( (-1,-1), (1,1) )
Random_points_iterator rpit( 1.0);
Fair fair(5); // bucket size=5
// Insert number_of_data_points in the tree
Tree tree(N_Random_points_iterator(rpit,0),
N_Random_points_iterator(N),
fair);
Point_d query(0,0);
// Initialize the search structure, and search all N points
Neighbor_search search(tree, query, N);
// report the N nearest neighbors and their distance
// This should sort all N points by increasing distance from origin
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:20