\( \newcommand{\E}{\mathrm{E}} \) \( \newcommand{\A}{\mathrm{A}} \) \( \newcommand{\R}{\mathrm{R}} \) \( \newcommand{\N}{\mathrm{N}} \) \( \newcommand{\Q}{\mathrm{Q}} \) \( \newcommand{\Z}{\mathrm{Z}} \) \( \def\ccSum #1#2#3{ \sum_{#1}^{#2}{#3} } \def\ccProd #1#2#3{ \sum_{#1}^{#2}{#3} }\)
CGAL 4.7 - dD Spatial Searching
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Spatial_searching/searching_with_circular_query.cpp
#include <CGAL/Simple_cartesian.h>
#include <CGAL/Kd_tree.h>
#include <CGAL/Search_traits_2.h>
#include <CGAL/point_generators_2.h>
#include <CGAL/algorithm.h>
#include <CGAL/Fuzzy_sphere.h>
typedef K::Point_2 Point;
typedef CGAL::Random_points_in_square_2<Point> Random_points_iterator;
typedef CGAL::Counting_iterator<Random_points_iterator> N_Random_points_iterator;
typedef CGAL::Search_traits_2<K> Traits;
typedef CGAL::Fuzzy_sphere<Traits> Fuzzy_circle;
typedef CGAL::Kd_tree<Traits> Tree;
typedef CGAL::Random Random;
int main() {
const int N=1000;
// generator for random data points in the square ( (-1,-1), (1,1) )
Random rnd(0);
Random_points_iterator rpit(1.0, rnd);
// Insert also the N points in the tree
Tree tree(N_Random_points_iterator(rpit,0),
N_Random_points_iterator(N));
// define exact circular range query
Point center(0.2, 0.2);
Fuzzy_circle exact_range(center, 0.2);
std::list<Point> result;
tree.search(std::back_inserter( result ), exact_range);
std::cout << "\nPoints in cirle with center " << center << " and radius 0.2" << std::endl;
std::list<Point>::iterator it;
for (it=result.begin(); (it != result.end()); ++it) {
std::cout << *it << std::endl;
}
result.clear();
// approximate range searching using value 0.1 for fuzziness parameter
Fuzzy_circle approximate_range(center, 0.2, 0.1);
tree.search(std::back_inserter( result ), approximate_range);
std::cout << "\n\nPoints in cirle with center " << center << " and fuzzy radius [0.1,0.3]" << std::endl;
for (it=result.begin(); (it != result.end()); ++it) {
std::cout << *it << std::endl;
}
std::cout << "\ndone" << std::endl;
return 0;
}