mirror of https://github.com/CGAL/cgal
109 lines
4.3 KiB
C++
109 lines
4.3 KiB
C++
// file : test/Spatial_searching/Circular_query.C
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// test whether circular queries are computed correctly for random data
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//
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// 1) generate list of query points using report_all
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// 2) remove and check reported points from these list
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// 3) check if no remaining points should have been reported
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#include <CGAL/Cartesian.h>
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#include <cassert>
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#include <CGAL/Kd_tree.h>
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#include <CGAL/Search_traits_2.h>
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#include <CGAL/Search_traits_adapter.h>
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#include <CGAL/point_generators_2.h>
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#include <CGAL/algorithm.h>
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#include <CGAL/Fuzzy_sphere.h>
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#include <CGAL/iterator.h>
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#include "Point_with_info.h"
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typedef CGAL::Cartesian<double> K;
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typedef K::Point_2 Point;
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typedef CGAL::Random_points_in_square_2<Point> Random_points_iterator;
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typedef CGAL::Counting_iterator<Random_points_iterator> N_Random_points_iterator;
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typedef CGAL::Search_traits_2<K> Traits;
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//for Point_with_info
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typedef Point_with_info_helper<Point>::type Point_with_info;
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typedef Point_property_map<Point> Ppmap;
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typedef CGAL::Search_traits_adapter<Point_with_info,Ppmap,Traits> Traits_with_info;
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template <class Traits>
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void run(std::list<Point> all_points){
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typedef CGAL::Fuzzy_sphere<Traits> Fuzzy_circle;
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typedef CGAL::Kd_tree<Traits> Tree;
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// Insert also the N points in the tree
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Tree tree(
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boost::make_transform_iterator(all_points.begin(),Create_point_with_info<typename Traits::Point_d>()),
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boost::make_transform_iterator(all_points.end(),Create_point_with_info<typename Traits::Point_d>())
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);
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// define exact circular range query (fuzziness=0)
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Point center(0.25, 0.25);
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Fuzzy_circle exact_range(typename Traits::Point_d(center), 0.25);
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std::list<typename Traits::Point_d> result;
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tree.search(std::back_inserter( result ), exact_range);
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typedef std::vector<typename Traits::Point_d> V;
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V vec;
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vec.resize(result.size());
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typename V::iterator it = tree.search(vec.begin(), exact_range);
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assert(it == vec.end());
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tree.search(CGAL::Emptyset_iterator(), Fuzzy_circle(center, 0.25) ); //test compilation when Point != Traits::Point_d
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// test the results of the exact query
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std::list<Point> copy_all_points(all_points);
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for (typename std::list<typename Traits::Point_d>::iterator pt=result.begin(); (pt != result.end()); ++pt) {
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// a point with distance d to the center may be reported if d <= r
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assert(CGAL::squared_distance(center, get_point(*pt)) <= 0.0625);
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copy_all_points.remove(get_point(*pt));
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}
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for (std::list<Point>::iterator pt=copy_all_points.begin(); (pt != copy_all_points.end()); ++pt) {
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if(CGAL::squared_distance(center, *pt) < 0.0625){
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// all points with a distance d < r must be reported
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std::cout << "we missed " << *pt << " with distance = " << CGAL::squared_distance(center,*pt) << std::endl;
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}
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assert(CGAL::squared_distance(center, *pt) >= 0.0625);
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}
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result.clear();
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// approximate range searching using value 0.125 for fuzziness parameter
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Fuzzy_circle approximate_range(typename Traits::Point_d(center), 0.25, 0.125);
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tree.search(std::back_inserter( result ), approximate_range);
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// test the results of the approximate query
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for (typename std::list<typename Traits::Point_d>::iterator pt=result.begin(); (pt != result.end()); ++pt) {
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// a point with distance d to the center may be reported if d <= r + eps
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assert(CGAL::squared_distance(center,get_point(*pt))<=0.140625); // (0.25 + 0.125)²
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all_points.remove(get_point(*pt));
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}
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for (std::list<Point>::iterator pt=all_points.begin(); (pt != all_points.end()); ++pt) {
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// all points with a distance d < r - eps must be reported
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if(CGAL::squared_distance(center, *pt) < 0.015625){ // (0.25 - 0.125)²
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std::cout << "we missed " << *pt << " with distance = " << CGAL::squared_distance(center,*pt) << std::endl;
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}
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assert(CGAL::squared_distance(center,*pt) >= 0.015625);
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}
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std::cout << "done" << std::endl;
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}
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int main() {
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const int N=1000;
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// generator for random data points in the square ( (-1,-1), (1,1) )
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Random_points_iterator rpit(1.0);
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// construct list containing N random points
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std::list<Point> all_points(N_Random_points_iterator(rpit,0),
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N_Random_points_iterator(N));
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run<Traits>(all_points);
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run<Traits_with_info>(all_points);
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return 0;
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}
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