\( \newcommand{\E}{\mathrm{E}} \) \( \newcommand{\A}{\mathrm{A}} \) \( \newcommand{\R}{\mathrm{R}} \) \( \newcommand{\N}{\mathrm{N}} \) \( \newcommand{\Q}{\mathrm{Q}} \) \( \newcommand{\Z}{\mathrm{Z}} \) \( \def\ccSum #1#2#3{ \sum_{#1}^{#2}{#3} } \def\ccProd #1#2#3{ \sum_{#1}^{#2}{#3} }\)
CGAL 4.10.2 - dD Spatial Searching
 All Classes Namespaces Files Functions Variables Typedefs Enumerations Enumerator Groups Pages
Spatial_searching/searching_with_point_with_info.cpp
#include <CGAL/Exact_predicates_inexact_constructions_kernel.h>
#include <CGAL/Search_traits_3.h>
#include <CGAL/Search_traits_adapter.h>
#include <CGAL/point_generators_3.h>
#include <CGAL/Orthogonal_k_neighbor_search.h>
#include <CGAL/property_map.h>
#include <boost/iterator/zip_iterator.hpp>
#include <utility>
typedef Kernel::Point_3 Point_3;
typedef boost::tuple<Point_3,int> Point_and_int;
typedef CGAL::Random_points_in_cube_3<Point_3> Random_points_iterator;
typedef CGAL::Search_traits_3<Kernel> Traits_base;
typedef CGAL::Search_traits_adapter<Point_and_int,
CGAL::Nth_of_tuple_property_map<0, Point_and_int>,
Traits_base> Traits;
typedef K_neighbor_search::Tree Tree;
typedef K_neighbor_search::Distance Distance;
int main() {
const unsigned int K = 5;
// generator for random data points in the cube ( (-1,-1,-1), (1,1,1) )
Random_points_iterator rpit( 1.0);
std::vector<Point_3> points;
std::vector<int> indices;
points.push_back(Point_3(*rpit++));
points.push_back(Point_3(*rpit++));
points.push_back(Point_3(*rpit++));
points.push_back(Point_3(*rpit++));
points.push_back(Point_3(*rpit++));
points.push_back(Point_3(*rpit++));
points.push_back(Point_3(*rpit++));
indices.push_back(0);
indices.push_back(1);
indices.push_back(2);
indices.push_back(3);
indices.push_back(4);
indices.push_back(5);
indices.push_back(6);
// Insert number_of_data_points in the tree
Tree tree(
boost::make_zip_iterator(boost::make_tuple( points.begin(),indices.begin() )),
boost::make_zip_iterator(boost::make_tuple( points.end(),indices.end() ) )
);
Point_3 query(0.0, 0.0, 0.0);
Distance tr_dist;
// search K nearest neighbours
K_neighbor_search search(tree, query, K);
for(K_neighbor_search::iterator it = search.begin(); it != search.end(); it++){
std::cout << " d(q, nearest neighbor)= "
<< tr_dist.inverse_of_transformed_distance(it->second) << " "
<< boost::get<0>(it->first)<< " " << boost::get<1>(it->first) << std::endl;
}
return 0;
}