\( \newcommand{\E}{\mathrm{E}} \) \( \newcommand{\A}{\mathrm{A}} \) \( \newcommand{\R}{\mathrm{R}} \) \( \newcommand{\N}{\mathrm{N}} \) \( \newcommand{\Q}{\mathrm{Q}} \) \( \newcommand{\Z}{\mathrm{Z}} \) \( \def\ccSum #1#2#3{ \sum_{#1}^{#2}{#3} } \def\ccProd #1#2#3{ \sum_{#1}^{#2}{#3} }\)
CGAL 4.14 - dD Spatial Searching
Spatial_searching/circular_query.cpp
#include <CGAL/Simple_cartesian.h>
#include <CGAL/Kd_tree.h>
#include <CGAL/point_generators_2.h>
#include <CGAL/algorithm.h>
#include <CGAL/Fuzzy_sphere.h>
#include <CGAL/Search_traits_2.h>
typedef K::Point_2 Point_d;
typedef CGAL::Random_points_in_square_2<Point_d> Random_points_iterator;
typedef CGAL::Search_traits_2<K> Traits;
typedef CGAL::Fuzzy_sphere<Traits> Fuzzy_circle;
typedef CGAL::Kd_tree<Traits> Tree;
int main() {
const int N = 30;
Tree tree;
Random_points_iterator rpg;
for(int i = 0; i < N; i++){
tree.insert(*rpg++);
}
// fuzziness = 0
// Note that a fuzziness of 0 does not imply that we can gather exactly all the
// points within the disk: even with eps=0, the border is a fuzzy zone.
Point_d center(0., 0.);
Fuzzy_circle default_range(center, 0.5);
std::list<Point_d> result;
tree.search(std::back_inserter( result ), default_range);
std::cout << "The points in the fuzzy circle centered at (0., 0.) ";
std::cout << "with fuzzy radius (0.5, 0.5) are: " << std::endl;
std::copy (result.begin(),result.end(),std::ostream_iterator<Point_d>(std::cout,"\n") );
std::cout << std::endl;
// approximate range searching using value 0.4 for fuzziness parameter
// We do not write into a list but directly in the outpout stream
std::cout << "The points in the fuzzy circle centered at (0., 0.) ";
std::cout << "with fuzzy radius (0.1, 0.9) are: " << std::endl;
Fuzzy_circle approximate_range(center, 0.5, 0.4);
tree.search(std::ostream_iterator<Point_d>(std::cout,"\n"), approximate_range);
return 0;
}