void compare_libraries(std::size_t data_size,
const Distribution& distribution) {
std::cout << "\t" << N << " dimensions, " << data_size
<< " objects:" << std::endl;
std::vector<Point> data;
std::vector<Point> targets;
data.reserve(data_size);
targets.reserve(data_size);
for (std::size_t i = 0; i < data_size; ++i) {
data.push_back(Point(distribution));
targets.push_back(Point(distribution));
}
{
// Nearest neighbor begin into an idle_point_multiset
std::cout << "\t\tidle_point_multiset:\t" << std::flush;
spatial::idle_point_multiset<0, Point> cobaye(N);
cobaye.insert_rebalance(data.begin(), data.end());
utils::time_point start = utils::process_timer_now();
for (typename std::vector<Point>::const_iterator i = targets.begin();
i != targets.end(); ++i)
neighbor_begin(cobaye, *i);
utils::time_point stop = utils::process_timer_now();
std::cout << (stop - start) << "sec" << std::endl;
}
{
// Nearest neighbor begin into an idle_point_multiset
std::cout << "\t\tpoint_multiset:\t" << std::flush;
spatial::point_multiset<0, Point> cobaye(N);
cobaye.insert(data.begin(), data.end());
utils::time_point start = utils::process_timer_now();
for (typename std::vector<Point>::const_iterator i = targets.begin();
i != targets.end(); ++i)
neighbor_begin(cobaye, *i);
utils::time_point stop = utils::process_timer_now();
std::cout << (stop - start) << "sec" << std::endl;
}
{
// Nearest neighbor into an KDtree
std::cout << "\t\tKDtree:\t" << std::flush;
KDTree::KDTree<N, Point> cobaye;
cobaye.insert(data.begin(), data.end());
cobaye.optimise();
utils::time_point start = utils::process_timer_now();
for (typename std::vector<Point>::const_iterator i = targets.begin();
i != targets.end(); ++i)
cobaye.find_nearest(*i);
utils::time_point stop = utils::process_timer_now();
std::cout << (stop - start) << "sec" << std::endl;
}
}
void compare_libraries
(std::size_t data_size, const Distribution& distribution)
{
std::cout << "\t" << N << " dimensions, " << data_size << " objects:" << std::endl;
std::vector<Point> data;
data.reserve(data_size);
for (size_t i = 0; i < data_size; ++i)
data.push_back(Point(distribution));
{
// Erase into a point_multiset
std::cout << "\t\tpoint_multiset:\t" << std::flush;
spatial::point_multiset<N, Point> cobaye;
cobaye.insert(data.begin(), data.end());
std::random_shuffle(data.begin(), data.end(), random_integer);
utils::time_point start = utils::process_timer_now();
for (typename std::vector<Point>::const_iterator i = data.begin();
i != data.end(); ++i)
cobaye.erase(*i);
utils::time_point stop = utils::process_timer_now();
std::cout << (stop - start) << "sec" << std::endl;
}
{
// Erase into an idle_point_multiset
std::cout << "\t\tidle_point_multiset:\t" << std::flush;
spatial::idle_point_multiset<N, Point> cobaye;
cobaye.insert_rebalance(data.begin(), data.end());
std::random_shuffle(data.begin(), data.end(), random_integer);
utils::time_point start = utils::process_timer_now();
for (typename std::vector<Point>::const_iterator i = data.begin();
i != data.end(); ++i)
cobaye.erase(*i);
utils::time_point stop = utils::process_timer_now();
std::cout << (stop - start) << "sec" << std::endl;
}
{
// Insert into a KDtree
std::cout << "\t\tKDtree:\t" << std::flush;
KDTree::KDTree<N, Point> cobaye;
cobaye.insert(data.begin(), data.end());
cobaye.optimise();
std::random_shuffle(data.begin(), data.end(), random_integer);
utils::time_point start = utils::process_timer_now();
for (typename std::vector<Point>::const_iterator i = data.begin();
i != data.end(); ++i)
cobaye.erase(*i);
utils::time_point stop = utils::process_timer_now();
std::cout << (stop - start) << "sec" << std::endl;
}
}
