Ponca::KdTree< DataPoint > Struct Template Reference

Abstract KdTree type with KdTreeDefaultTraits. More...

#include <kdTree.h>

Inheritance diagram for Ponca::KdTree< DataPoint >:

Collaboration diagram for Ponca::KdTree< DataPoint >:

Additional Inherited Members
Public Types inherited from Ponca::KdTreeBase< KdTreeDefaultTraits< DataPoint > >
using	DataPoint = typename Traits::DataPoint
	DataPoint given by user via Traits.
using	IndexType = typename Traits::IndexType
	Type used to index points into the PointContainer.
using	LeafSizeType = typename Traits::LeafSizeType
	Type used to store the size of leaf nodes.
using	PointContainer = typename Traits::PointContainer
	Container for DataPoint used inside the KdTree.
using	IndexContainer = typename Traits::IndexContainer
	Container for indices used inside the KdTree.
using	NodeIndexType = typename Traits::NodeIndexType
	Type used to index nodes into the NodeContainer.
using	NodeType = typename Traits::NodeType
	Type of nodes used inside the KdTree.
using	NodeContainer = typename Traits::NodeContainer
	Container for nodes used inside the KdTree.
using	Scalar = typename DataPoint::Scalar
	Scalar given by user via DataPoint.
using	VectorType = typename DataPoint::VectorType
	VectorType given by user via DataPoint.
using	AabbType = typename NodeType::AabbType
	Bounding box type given by user via NodeType.
Public Member Functions inherited from Ponca::KdTreeBase< KdTreeDefaultTraits< DataPoint > >
void	build (PointUserContainer &&points, Converter c)
	Generate a tree from a custom contained type converted using the specified converter.
void	build (PointUserContainer &&points)
	Generate a tree from a custom contained type converted using DefaultConverter.
void	build (PointUserContainer &&points, Converter c)
void	clear ()
	Clear tree data.
NodeIndexType	node_count () const
IndexType	sample_count () const
IndexType	pointCount () const
NodeIndexType	leaf_count () const
PointContainer &	points ()
const PointContainer &	points () const
const NodeContainer &	nodes () const
const IndexContainer &	samples () const
LeafSizeType	minCellSize () const
	Read leaf min size.
void	setMinCellSize (LeafSizeType min_cell_size)
	Write leaf min size.
IndexType	pointFromSample (IndexType sample_index) const
	Return the point index associated with the specified sample index.
DataPoint &	pointDataFromSample (IndexType sample_index)
	Return the DataPoint associated with the specified sample index.
const DataPoint &	pointDataFromSample (IndexType sample_index) const
	Return the DataPoint associated with the specified sample index.
KdTreeKNearestPointQuery< KdTreeDefaultTraits< DataPoint > >	kNearestNeighbors (const VectorType &point, IndexType k) const
	Computes a Query object to iterate over the k-nearest neighbors of a point. The returned object can be reset and reused with the () operator (using the same argument types as parameters).
KdTreeKNearestIndexQuery< KdTreeDefaultTraits< DataPoint > >	kNearestNeighbors (IndexType index, IndexType k) const
	Computes a Query object to iterate over the k-nearest neighbors of a point. The returned object can be reset and reused with the () operator (using the same argument types as parameters).
KdTreeKNearestPointQuery< KdTreeDefaultTraits< DataPoint > >	kNearestNeighborsQuery () const
	Convenience function that provides an empty k-nearest neighbors Query object.
KdTreeKNearestIndexQuery< KdTreeDefaultTraits< DataPoint > >	kNearestNeighborsIndexQuery () const
	Convenience function that provides an empty k-nearest neighbors Query object.
KdTreeNearestPointQuery< KdTreeDefaultTraits< DataPoint > >	nearestNeighbor (const VectorType &point) const
	Computes a Query object that contains the nearest point. The returned object can be reset and reused with the () operator (using the same argument types as parameters).
KdTreeNearestIndexQuery< KdTreeDefaultTraits< DataPoint > >	nearestNeighbor (IndexType index) const
	Computes a Query object that contains the nearest point. The returned object can be reset and reused with the () operator (using the same argument types as parameters).
KdTreeNearestIndexQuery< KdTreeDefaultTraits< DataPoint > >	nearestNeighborQuery () const
	Convenience function that provides an empty nearest neighbor Query object.
KdTreeNearestIndexQuery< KdTreeDefaultTraits< DataPoint > >	nearestNeighborIndexQuery () const
	Convenience function that provides an empty nearest neighbor Query object.
KdTreeRangePointQuery< KdTreeDefaultTraits< DataPoint > >	rangeNeighbors (const VectorType &point, Scalar r) const
	Computes a Query object to iterate over the neighbors that are inside a given radius. The returned object can be reset and reused with the () operator (using the same argument types as parameters).
KdTreeRangeIndexQuery< KdTreeDefaultTraits< DataPoint > >	rangeNeighbors (IndexType index, Scalar r) const
	Computes a Query object to iterate over the neighbors that are inside a given radius. The returned object can be reset and reused with the () operator (using the same argument types as parameters).
KdTreeRangePointQuery< KdTreeDefaultTraits< DataPoint > >	rangeNeighborsQuery () const
	Convenience function that provides an empty range neighbor Query object.
KdTreeRangeIndexQuery< KdTreeDefaultTraits< DataPoint > >	rangeNeighborsIndexQuery () const
	KdTreeBase::rangeNeighborsQuery.
bool	valid () const
void	print (std::ostream &os, bool verbose=false) const
void	buildWithSampling (PointUserContainer &&points, IndexUserContainer sampling, Converter c)
Static Public Attributes inherited from Ponca::KdTreeBase< KdTreeDefaultTraits< DataPoint > >
static constexpr std::size_t	MAX_NODE_COUNT
	The maximum number of nodes that the kd-tree can have.
static constexpr std::size_t	MAX_POINT_COUNT
	The maximum number of points that can be stored in the kd-tree.
static constexpr int	MAX_DEPTH
	The maximum depth of the kd-tree.
static constexpr bool	SUPPORTS_SUBSAMPLING
Protected Member Functions inherited from Ponca::KdTreeBase< KdTreeDefaultTraits< DataPoint > >
void	buildWithSampling (PointUserContainer &&points, IndexUserContainer sampling, Converter c)
	Generate a tree sampled from a custom contained type converted using a Converter
void	buildWithSampling (PointUserContainer &&points, IndexUserContainer sampling)
	Generate a tree sampled from a custom contained type converted using a KdTreeBase::DefaultConverter.
Protected Attributes inherited from Ponca::KdTreeBase< KdTreeDefaultTraits< DataPoint > >
PointContainer	m_points
NodeContainer	m_nodes
IndexContainer	m_indices
LeafSizeType	m_min_cell_size
	Minimal number of points per leaf.
NodeIndexType	m_leaf_count
	Number of leaves in the Kdtree (computed during construction)

Detailed Description

template<typename DataPoint>
struct Ponca::KdTree< DataPoint >

Abstract KdTree type with KdTreeDefaultTraits.

See also

KdTreeDefaultTraits for the default trait interface documentation.

KdTreeBase for complete API

Warning

It is not possible to create instances of type KdTree. This type must only be used to store pointers to KdTreeDense or KdTreeSparse objects, e.g. the declaration

    // Abstract pointer type that can receive KdTreeSparse or KdTreeDense objects
    Ponca::KdTree<DataPoint> *kdtree {nullptr};

    // Assign sparse
    kdtree = &kdtreeSparse; // Or kdtree = new Ponca::KdTreeSparse<DataPoint> (points, sampling);

    // Assign dense
    kdtree = &kdtreeDense; // Or kdtree = new Ponca::KdTreeDense<DataPoint> (points, sampling);

[KdTree type definition]

Definition at line 47 of file kdTree.h.