kdtree.hpp

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#ifndef PCL_SEARCH_KDTREE_IMPL_HPP_
#define PCL_SEARCH_KDTREE_IMPL_HPP_

#include <pcl/search/kdtree.h>
#include <pcl/search/impl/search.hpp>

template <typename PointT>
pcl::search::KdTree<PointT>::KdTree (bool sorted)
  : pcl::search::Search<PointT> ("KdTree", sorted)
  , tree_ (new pcl::KdTreeFLANN<PointT> (sorted))
{
}

template <typename PointT> void
pcl::search::KdTree<PointT>::setPointRepresentation (
    const PointRepresentationConstPtr &point_representation)
{
  tree_->setPointRepresentation (point_representation);
}

template <typename PointT> void
pcl::search::KdTree<PointT>::setSortedResults (bool sorted_results)
{
  sorted_results_ = sorted_results;
  tree_->setSortedResults (sorted_results);
}

template <typename PointT> void
pcl::search::KdTree<PointT>::setEpsilon (float eps)
{
  tree_->setEpsilon (eps);
}

template <typename PointT> void
pcl::search::KdTree<PointT>::setInputCloud (
    const PointCloudConstPtr& cloud, 
    const IndicesConstPtr& indices)
{
  tree_->setInputCloud (cloud, indices);
  input_ = cloud;
  indices_ = indices;
}

template <typename PointT> int
pcl::search::KdTree<PointT>::nearestKSearch (
    const PointT &point, int k, std::vector<int> &k_indices, 
    std::vector<float> &k_sqr_distances) const
{
  return (tree_->nearestKSearch (point, k, k_indices, k_sqr_distances));
}

template <typename PointT> int
pcl::search::KdTree<PointT>::radiusSearch (
    const PointT& point, double radius, 
    std::vector<int> &k_indices, std::vector<float> &k_sqr_distances,
    unsigned int max_nn) const
{
  return (tree_->radiusSearch (point, radius, k_indices, k_sqr_distances, max_nn));
}

#define PCL_INSTANTIATE_KdTree(T) template class PCL_EXPORTS pcl::search::KdTree<T>;

#endif  //#ifndef _PCL_SEARCH_KDTREE_IMPL_HPP_