gtsam_points::UnsafeKdTree< PointCloud, Projection_ > Struct Template Reference

"Unsafe" KdTree. More...

#include <small_kdtree.hpp>

Collaboration diagram for gtsam_points::UnsafeKdTree< PointCloud, Projection_ >:

Public Types
using	Projection = Projection_
using	Node = KdTreeNode< Projection >

Public Member Functions
template<typename Builder = KdTreeBuilder>
	UnsafeKdTree (const PointCloud &points, const Builder &builder=KdTreeBuilder())
	Constructor.
size_t	nearest_neighbor_search (const Eigen::Vector3d &query_, size_t *k_indices, double *k_sq_dists, const KnnSetting &setting=KnnSetting()) const
	Find the nearest neighbor.
size_t	knn_search (const Eigen::Vector3d &query_, int k, size_t *k_indices, double *k_sq_dists, const KnnSetting &setting=KnnSetting()) const
	Find k-nearest neighbors. This method uses dynamic memory allocation.
template<int N>
size_t	knn_search (const Eigen::Vector3d &query_, size_t *k_indices, double *k_sq_dists, const KnnSetting &setting=KnnSetting()) const
	Find k-nearest neighbors. This method uses fixed and static memory allocation. Might be faster for small k.
size_t	radius_search (const Eigen::Vector3d &query_, double radius, std::vector< size_t > &indices, std::vector< double > &sq_dists, const KnnSetting &setting=KnnSetting()) const
	Find neighbors in a search radius.

Public Attributes
const PointCloud &	points
	Input points.
std::vector< size_t >	indices
	Point indices refered by nodes.
NodeIndexType	root
	Root node index (should be zero)
std::vector< Node >	nodes
	Kd-tree nodes.

Detailed Description

template<typename PointCloud, typename Projection_ = AxisAlignedProjection>
struct gtsam_points::UnsafeKdTree< PointCloud, Projection_ >

"Unsafe" KdTree.

Note

This class does not hold the ownership of the input points. You must keep the input points along with this class.

Constructor & Destructor Documentation

UnsafeKdTree()

template<typename PointCloud , typename Projection_ = AxisAlignedProjection>

template<typename Builder = KdTreeBuilder>

gtsam_points::UnsafeKdTree< PointCloud, Projection_ >::UnsafeKdTree ( const PointCloud &  points, const Builder &  builder = KdTreeBuilder()  )

inlineexplicit

Constructor.

Parameters

points	Point cloud
builder	Kd-tree builder

Member Function Documentation

knn_search() [1/2]

template<typename PointCloud , typename Projection_ = AxisAlignedProjection>

size_t gtsam_points::UnsafeKdTree< PointCloud, Projection_ >::knn_search ( const Eigen::Vector3d &  query_, int  k, size_t *  k_indices, double *  k_sq_dists, const KnnSetting &  setting = KnnSetting()  ) const

inline

Find k-nearest neighbors. This method uses dynamic memory allocation.

Parameters

query	Query point
k	Number of neighbors
k_indices	Indices of neighbors
k_sq_dists	Squared distances to neighbors
setting	KNN search setting

Returns

Number of found neighbors

knn_search() [2/2]

template<typename PointCloud , typename Projection_ = AxisAlignedProjection>

template<int N>

size_t gtsam_points::UnsafeKdTree< PointCloud, Projection_ >::knn_search ( const Eigen::Vector3d &  query_, size_t *  k_indices, double *  k_sq_dists, const KnnSetting &  setting = KnnSetting()  ) const

inline

Find k-nearest neighbors. This method uses fixed and static memory allocation. Might be faster for small k.

Parameters

query	Query point
k_indices	Indices of neighbors
k_sq_dists	Squared distances to neighbors
setting	KNN search setting

Returns

Number of found neighbors

nearest_neighbor_search()

template<typename PointCloud , typename Projection_ = AxisAlignedProjection>

size_t gtsam_points::UnsafeKdTree< PointCloud, Projection_ >::nearest_neighbor_search ( const Eigen::Vector3d &  query_, size_t *  k_indices, double *  k_sq_dists, const KnnSetting &  setting = KnnSetting()  ) const

inline

Find the nearest neighbor.

Parameters

query	Query point
k_indices	Index of the nearest neighbor
k_sq_dists	Squared distance to the nearest neighbor
setting	KNN search setting

Returns

Number of found neighbors (0 or 1)

radius_search()

template<typename PointCloud , typename Projection_ = AxisAlignedProjection>

size_t gtsam_points::UnsafeKdTree< PointCloud, Projection_ >::radius_search ( const Eigen::Vector3d &  query_, double  radius, std::vector< size_t > &  indices, std::vector< double > &  sq_dists, const KnnSetting &  setting = KnnSetting()  ) const

inline

Find neighbors in a search radius.

Parameters

query	Query point
radius	Search radius
indices	Indices of neighbors
sq_dists	Squared distances to neighbors
setting	KNN search setting

Returns

Number of found neighbors

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The documentation for this struct was generated from the following files:

• /home/runner/work/gtsam_points/gtsam_points/include/gtsam_points/ann/kdtree.hpp
• /home/runner/work/gtsam_points/gtsam_points/include/gtsam_points/ann/small_kdtree.hpp