int main()
{
const int N=10000;
CGAL::Random rnd = CGAL::get_default_random();
std::cout << "seed: " << rnd.get_seed() << std::endl;
// generator for random data points in the square ( (-1,-1), (1,1) )
Random_points_iterator rpit(1.0, rnd);
// construct list containing N random points
std::list<Point> all_points(N_Random_points_iterator(rpit,0),
N_Random_points_iterator(N));
// add some interesting points
all_points.push_back(Point(0., 0.));
all_points.push_back(Point(-CGAL_PI/10.+0.1, -CGAL_PI/10.+0.1));
all_points.push_back(Point(1., 1.));
all_points.push_back(Point(0., 1.));
all_points.push_back(Point(0.3, 0.4));
all_points.push_back(Point(0.2, 0.3));
all_points.push_back(Point(0., 0.1));
run<Traits>(all_points, rnd);
run<Traits_with_info>(all_points, rnd);
return 0;
}
int main() {
const int D = 4;
const int N = 1000;
// generator for random data points in the square ( (-1000,-1000), (1000,1000) )
Random_points_iterator rpit(4, 1000.0);
// Insert N points in the tree
Tree tree(N_Random_points_iterator(rpit,0),
N_Random_points_iterator(rpit,N));
// define range query objects
double pcoord[D] = { 300, 300, 300, 300 };
double qcoord[D] = { 900.0, 900.0, 900.0, 900.0 };
Point_d p(D, pcoord, pcoord+D);
Point_d q(D, qcoord, qcoord+D);
Fuzzy_sphere fs(p, 700.0, 100.0);
Fuzzy_iso_box fib(p, q, 100.0);
std::cout << "points approximately in fuzzy range query" << std::endl;
std::cout << "with center (300.0, 300.0, 300.0, 300.0)" << std::endl;
std::cout << "and fuzzy radius <200.0,400.0> are:" << std::endl;
tree.search(std::ostream_iterator<Point_d>(std::cout, "\n"), fs);
std::cout << "points approximately in fuzzy range query ";
std::cout << "[<200,4000>,<800,1000>]]^4 are:" << std::endl;
tree.search(std::ostream_iterator<Point_d>(std::cout, "\n"), fib);
return 0;
}
int main() {
const unsigned int K = 5;
// generator for random data points in the cube ( (-1,-1,-1), (1,1,1) )
Random_points_iterator rpit( 1.0);
std::vector<Point_3> points;
points.push_back(Point_3(*rpit++));
points.push_back(Point_3(*rpit++));
points.push_back(Point_3(*rpit++));
points.push_back(Point_3(*rpit++));
points.push_back(Point_3(*rpit++));
points.push_back(Point_3(*rpit++));
points.push_back(Point_3(*rpit++));
My_point_property_map ppmap(points);
// Insert number_of_data_points in the tree
Tree tree(
boost::counting_iterator<std::size_t>(0),
boost::counting_iterator<std::size_t>(points.size()),
Splitter(),
Traits(ppmap)
);
Point_3 query(0.0, 0.0, 0.0);
Distance tr_dist(ppmap);
// search K nearest neighbours
K_neighbor_search search(tree, query, K,0,true,tr_dist);
for(K_neighbor_search::iterator it = search.begin(); it != search.end(); it++){
std::cout << " d(q, nearest neighbor)= "
<< tr_dist.inverse_of_transformed_distance(it->second) << " "
<< points[it->first] << " " << it->first << std::endl;
}
return 0;
}
int main() {
const int N=1000;
// generator for random data points in the square ( (-1,-1), (1,1) )
Random rnd(0);
Random_points_iterator rpit(1.0, rnd);
// Insert also the N points in the tree
Tree tree(N_Random_points_iterator(rpit,0),
N_Random_points_iterator(N));
// define exact circular range query
Point center(0.2, 0.2);
Fuzzy_circle exact_range(center, 0.2);
std::list<Point> result;
tree.search(std::back_inserter( result ), exact_range);
std::cout << "\nPoints in cirle with center " << center << " and radius 0.2" << std::endl;
std::list<Point>::iterator it;
for (it=result.begin(); (it != result.end()); ++it) {
std::cout << *it << std::endl;
}
result.clear();
// approximate range searching using value 0.1 for fuzziness parameter
Fuzzy_circle approximate_range(center, 0.2, 0.1);
tree.search(std::back_inserter( result ), approximate_range);
std::cout << "\n\nPoints in cirle with center " << center << " and fuzzy radius [0.1,0.3]" << std::endl;
for (it=result.begin(); (it != result.end()); ++it) {
std::cout << *it << std::endl;
}
std::cout << "\ndone" << std::endl;
return 0;
}
int main() {
const unsigned int K = 5;
// generator for random data points in the cube ( (-1,-1,-1), (1,1,1) )
Random_points_iterator rpit( 1.0);
std::vector<Point_3> points;
std::vector<int> indices;
points.push_back(Point_3(*rpit++));
points.push_back(Point_3(*rpit++));
points.push_back(Point_3(*rpit++));
points.push_back(Point_3(*rpit++));
points.push_back(Point_3(*rpit++));
points.push_back(Point_3(*rpit++));
points.push_back(Point_3(*rpit++));
indices.push_back(0);
indices.push_back(1);
indices.push_back(2);
indices.push_back(3);
indices.push_back(4);
indices.push_back(5);
indices.push_back(6);
// Insert number_of_data_points in the tree
Tree tree(
boost::make_zip_iterator(boost::make_tuple( points.begin(),indices.begin() )),
boost::make_zip_iterator(boost::make_tuple( points.end(),indices.end() ) )
);
Point_3 query(0.0, 0.0, 0.0);
Distance tr_dist;
// search K nearest neighbours
K_neighbor_search search(tree, query, K);
for(K_neighbor_search::iterator it = search.begin(); it != search.end(); it++){
std::cout << " d(q, nearest neighbor)= "
<< tr_dist.inverse_of_transformed_distance(it->second) << " "
<< boost::get<0>(it->first)<< " " << boost::get<1>(it->first) << std::endl;
}
return 0;
}
int main(int argc, char* argv[]) {
const unsigned int D = 4;
const unsigned int N = 100000;
CGAL::Random rand(42);
Random_points_iterator rpit(D, 1.0, rand);
std::vector<Point_d> pts;
pts.reserve(N);
for(int i = 0; i < N; i++) {
pts.push_back(*rpit++);
}
WSPD wspd(D, 1.0, pts.begin(), pts.end());
// Uncomment to print the size of the sets of each pair in the WSPD.
/*for(Well_separated_pair_iterator it = wspd.wspd_begin(); it < wspd.wspd_end(); it++) {
Well_separated_pair &pair = *it;
std::cout << "(" << pair.a()->point_container().size() << ", " << pair.b()->point_container().size() << ")" << std::endl;
}*/
// Prints the number of pairs in the WSPD.
std::cout << wspd.wspd_size() << std::endl;
return 0;
}
int main() {
const int N = 1000;
const unsigned int K = 10;
Tree tree;
Random_points_iterator rpit(4,1000.0);
for(int i = 0; i < N; i++){
tree.insert(*rpit++);
}
Point_d pp(0.1,0.1,0.1,0.1);
Point_d qq(0.2,0.2,0.2,0.2);
Iso_box_d query(pp,qq);
Distance tr_dist;
Neighbor_search N1(tree, query, 5, 10.0, false); // eps=10.0, nearest=false
std::cout << "For query rectangle = [0.1, 0.2]^4 " << std::endl
<< "the " << K << " approximate furthest neighbors are: " << std::endl;
for (Neighbor_search::iterator it = N1.begin();it != N1.end();it++) {
std::cout << " Point " << it->first << " at distance " << tr_dist.inverse_of_transformed_distance(it->second) << std::endl;
}
return 0;
}
