CGAL 6.0.1 - dD Spatial Searching
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Spatial_searching/splitter_worst_cases.cpp
#include <CGAL/Simple_cartesian.h>
#include <CGAL/Orthogonal_k_neighbor_search.h>
#include <CGAL/Search_traits_2.h>
typedef Kernel::Point_2 Point_2;
typedef CGAL::Sliding_midpoint<Traits_2> Sliding_midpoint;
typedef CGAL::Median_of_rectangle<Traits_2> Median_of_rectangle;
typedef Neighbor_search_sliding::Tree Tree_sliding;
typedef Neighbor_search_median::Tree Tree_median;
typedef std::vector<Point_2> Points;
int main()
{
Points sliding_worst_case;
for (int i = 0 ,j = 1; i < 10 ; ++i , j *= 2)
{
sliding_worst_case.push_back(Point_2(((double)i)/10 , 0));
sliding_worst_case.push_back(Point_2( (double)j , 0));
}
Sliding_midpoint sliding(10);
Median_of_rectangle median(10);
Tree_sliding tree1(sliding_worst_case.begin(), sliding_worst_case.end() , sliding);
tree1.build();
std::cout << "Worst case tree for Sliding midpoint and Midpoint of max spread : "<<std::endl;
tree1.statistics(std::cout);
tree1.clear();
std::cout<<std::endl<<"Same data with median splitter:"<<std::endl;
Tree_median tree2(sliding_worst_case.begin(), sliding_worst_case.end() , median );
tree2.statistics(std::cout);
tree2.clear();
Points median_worst_case;
for(int i = 0 ; i < 19 ; ++i)
median_worst_case.push_back(Point_2( 0 , i));
median_worst_case.push_back(Point_2(20,0));
Tree_median tree3(median_worst_case.begin() , median_worst_case.end() , median);
tree3.build();
std::cout <<std::endl<< "Worst case tree for Median of rectangle, Median of max spread : "<<std::endl;
tree3.statistics(std::cout);
tree3.clear();
std::cout<<std::endl<<"Same data with midpoint splitter:"<<std::endl;
Tree_sliding tree4(median_worst_case.begin() , median_worst_case.end() , sliding);
tree4.build();
tree4.statistics(std::cout);
tree4.clear();
return 0;
}
The class Euclidean_distance provides an implementation of the concept OrthogonalDistance,...
Definition: Euclidean_distance.h:20
Implements the median of rectangle splitting rule.
Definition: Splitters.h:135
The class Orthogonal_k_neighbor_search implements approximatek-nearest and k-furthest neighbor search...
Definition: Orthogonal_k_neighbor_search.h:31
The class Search_traits_2 can be used as a template parameter of the kd tree and the search classes.
Definition: Search_traits_2.h:19
Implements the sliding midpoint splitting rule.
Definition: Splitters.h:361