nanoflann-knn/examples/pointcloud_example.cpp

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#include <cstdlib>
#include <ctime>
#include <iostream>
#include <nanoflann.hpp>
#include <type_traits>

#include "utils.h"

template <typename num_t>
void kdtree_demo(const size_t N)
{
    static_assert(
        std::is_standard_layout<nanoflann::ResultItem<num_t, size_t>>::value,
        "Unexpected memory layout for nanoflann::ResultItem");

    PointCloud<num_t> cloud;

    // Generate points:
    generateRandomPointCloud(cloud, N);

    num_t query_pt[3] = {0.5, 0.5, 0.5};

    // construct a kd-tree index:
    using my_kd_tree_t = nanoflann::KDTreeSingleIndexAdaptor<
        nanoflann::L2_Simple_Adaptor<num_t, PointCloud<num_t>>,
        PointCloud<num_t>, 3 /* dim */
        >;

    dump_mem_usage();

    my_kd_tree_t index(3 /*dim*/, cloud, {10 /* max leaf */});

    dump_mem_usage();
    {
        // do a knn search
        const size_t                   num_results = 1;
        size_t                         ret_index;
        num_t                          out_dist_sqr;
        nanoflann::KNNResultSet<num_t> resultSet(num_results);
        resultSet.init(&ret_index, &out_dist_sqr);
        index.findNeighbors(resultSet, &query_pt[0]);

        std::cout << "knnSearch(nn=" << num_results << "): \n";
        std::cout << "ret_index=" << ret_index
                  << " out_dist_sqr=" << out_dist_sqr << std::endl;
    }

    {
        // radius search:
        const num_t                                       squaredRadius = 1;
        std::vector<nanoflann::ResultItem<size_t, num_t>> indices_dists;
        nanoflann::RadiusResultSet<num_t, size_t>         resultSet(
            squaredRadius, indices_dists);

        index.findNeighbors(resultSet, query_pt);

        // Get worst (furthest) point, without sorting:
        nanoflann::ResultItem<size_t, num_t> worst_pair =
            resultSet.worst_item();
        std::cout << "Worst pair: idx=" << worst_pair.first
                  << " squaredDist=" << worst_pair.second << std::endl;
    }
}

int main()
{
    // Randomize Seed
    srand(static_cast<unsigned int>(time(nullptr)));
    kdtree_demo<float>(1000000);
    kdtree_demo<double>(1000000);
    return 0;
}