mirror of https://github.com/CGAL/cgal
83 lines
2.8 KiB
C++
83 lines
2.8 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/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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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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typedef CGAL::Fuzzy_sphere<Traits> Fuzzy_circle;
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typedef CGAL::Kd_tree<Traits> Tree;
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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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// Insert also the N points in the tree
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Tree tree(all_points.begin(),all_points.end());
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// define exact circular range query (fuzziness=0)
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Point center(0.2, 0.2);
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Fuzzy_circle exact_range(center, 0.2);
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std::list<Point> result;
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tree.search(std::back_inserter( result ), exact_range);
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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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std::list<Point>::iterator pt;
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for (pt=result.begin(); (pt != result.end()); ++pt) {
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assert(CGAL::squared_distance(center,*pt)<=0.04);
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copy_all_points.remove(*pt);
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}
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for (pt=copy_all_points.begin(); (pt != copy_all_points.end()); ++pt) {
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if(CGAL::squared_distance(center,*pt)<=0.04){
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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)>0.04);
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}
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result.clear();
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// approximate range searching using value 0.1 for fuzziness parameter
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Fuzzy_circle approximate_range(center, 0.2, 0.1);
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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 (pt=result.begin(); (pt != result.end()); ++pt) {
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// a point we found may be slighlty outside the circle
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assert(CGAL::squared_distance(center,*pt)<=0.09);
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all_points.remove(*pt);
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}
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for (pt=all_points.begin(); (pt != all_points.end()); ++pt) {
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if(CGAL::squared_distance(center,*pt)<=0.01){
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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)> 0.01);
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}
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std::cout << "done" << std::endl;
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return 0;
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}
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