mirror of https://github.com/CGAL/cgal
103 lines
3.5 KiB
C++
103 lines
3.5 KiB
C++
// file: Iso_rectangle_2_query.C
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#include <CGAL/Simple_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/Fuzzy_iso_box.h>
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#include <CGAL/iterator.h>
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#include "Point_with_info.h"
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#include <vector>
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#include <iostream>
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typedef CGAL::Simple_cartesian<double> K;
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typedef K::Point_2 Point;
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typedef K::Vector_2 Vector;
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typedef K::Iso_rectangle_2 Iso_rectangle;
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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 Point_with_info_helper<Point>::type Point_with_info;
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typedef CGAL::Search_traits_adapter<Point_with_info,Point_property_map,Traits> Traits_with_info;
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template <class SearchTraits>
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void run(std::list<Point> all_points)
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{
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typedef CGAL::Fuzzy_iso_box<SearchTraits> Fuzzy_box;
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// Insert also the N points in the tree
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CGAL::Kd_tree<SearchTraits> tree(
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boost::make_transform_iterator(all_points.begin(),Create_point_with_info<typename SearchTraits::Point_d>()),
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boost::make_transform_iterator(all_points.end(),Create_point_with_info<typename SearchTraits::Point_d>())
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);
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Point p(0.1, 0.2);
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Point q(0.3, 0.5);
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typename SearchTraits::Point_d pp(p);
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typename SearchTraits::Point_d qq(q);
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Iso_rectangle exact_ic(p,q);
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Fuzzy_box exact_range(pp,qq);
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std::list<typename SearchTraits::Point_d> result;
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// Searching the box r exactly
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tree.search( std::back_inserter( result ), exact_range);
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tree.search(CGAL::Emptyset_iterator(), Fuzzy_box(p,q) ); //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 SearchTraits::Point_d>::iterator pt=result.begin(); (pt != result.end()); ++pt) {
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assert(! exact_ic.has_on_unbounded_side(get_point(*pt)) || exact_ic.has_on_boundary(get_point(*pt)));
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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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assert(exact_ic.has_on_unbounded_side(*pt) || exact_ic.has_on_boundary(*pt));
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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_box approximate_range(pp,qq,0.05);
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Iso_rectangle inner_ic(p+ 0.05*Vector(1,1),q-0.05*Vector(1,1));
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Iso_rectangle outer_ic(p- 0.05*Vector(1,1),q+0.05*Vector(1,1));
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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 (typename std::list<typename SearchTraits::Point_d>::iterator pt=result.begin(); (pt != result.end()); ++pt) {
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// a point we found may be slighlty outside the isorectangle
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assert(! outer_ic.has_on_unbounded_side(get_point(*pt)) || outer_ic.has_on_boundary(get_point(*pt)));
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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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assert(inner_ic.has_on_unbounded_side(*pt) || inner_ic.has_on_boundary(*pt));
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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=10000;
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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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