CGAL 5.6.3 - dD Spatial Searching

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Spatial_searching/parallel_kdtree.cpp
#include <CGAL/Simple_cartesian.h>
#include <CGAL/point_generators_3.h>
#include <CGAL/Orthogonal_k_neighbor_search.h>
#include <CGAL/Search_traits_3.h>
#include <tbb/blocked_range.h>
#include <tbb/parallel_for.h>
using Kernel = CGAL::Simple_cartesian<double>;
using Point_3 = Kernel::Point_3;
using Traits = CGAL::Search_traits_3<Kernel>;
using Neighbor_search = CGAL::Orthogonal_k_neighbor_search<Traits>;
using Tree = Neighbor_search::Tree;
using Point_with_distance = Neighbor_search::Point_with_transformed_distance;
using Generator = CGAL::Random_points_in_sphere_3<Point_3>;
int main()
{
const unsigned int N = 1000;
const unsigned int k = 6;
// Generate N points in a sphere
std::vector<Point_3> points;
points.reserve (N);
Generator generator;
for (unsigned int i = 0; i < N; ++ i)
points.push_back (*(generator++));
// Build tree in parallel
Tree tree(points.begin(), points.end());
tree.build<CGAL::Parallel_tag>();
// Query tree in parallel
std::vector<std::vector<Point_3> > neighbors (points.size());
tbb::parallel_for (tbb::blocked_range<std::size_t> (0, points.size()),
[&](const tbb::blocked_range<std::size_t>& r)
{
for (std::size_t s = r.begin(); s != r.end(); ++ s)
{
// Neighbor search can be instantiated from
// several threads at the same time
Neighbor_search search (tree, points[s], k);
neighbors[s].reserve(k);
// neighbor search returns a set of pair of
// point and distance <Point_3,FT>, here we
// keep the points only
for (const Point_with_distance pwd : search)
neighbors[s].push_back (pwd.first);
}
});
return 0;
}
CGAL::Orthogonal_k_neighbor_search
The class Orthogonal_k_neighbor_search implements approximatek-nearest and k-furthest neighbor search...
Definition: Orthogonal_k_neighbor_search.h:31
CGAL::Search_traits_3
The class Search_traits_3 can be used as a template parameter of the kd tree and the search classes.
Definition: Search_traits_3.h:20
Kernel::Point_3
Kernel
CGAL::Parallel_tag
CGAL::Simple_cartesian