Customizable base class for KdTreeSparse datastructure. More...

#include <kdTree.h>

Inheritance diagram for Ponca::KdTreeSparseBase< Traits >:

Collaboration diagram for Ponca::KdTreeSparseBase< Traits >:

Public Member Functions
	KdTreeSparseBase ()=default
	Default constructor creating an empty tree.

template<typename PointUserContainer >
	KdTreeSparseBase (PointUserContainer &&points)
	Constructor generating a tree from a custom contained type converted using a KdTreeBase::DefaultConverter.

template<typename PointUserContainer , typename IndexUserContainer >
	KdTreeSparseBase (PointUserContainer &&points, IndexUserContainer sampling)
	Constructor generating a tree sampled from a custom contained type converted using a KdTreeBase::DefaultConverter.

template<typename PointUserContainer , typename IndexUserContainer , typename Converter >
void	buildWithSampling (PointUserContainer &&points, IndexUserContainer sampling, Converter c)
	Generate a tree sampled from a custom contained type converted using a `Converter`

template<typename PointUserContainer , typename IndexUserContainer >
void	buildWithSampling (PointUserContainer &&points, IndexUserContainer sampling)
	Generate a tree sampled from a custom contained type converted using a KdTreeBase::DefaultConverter.

template<typename PointUserContainer , typename IndexUserContainer , typename Converter >
void	buildWithSampling (PointUserContainer &&points, IndexUserContainer sampling, Converter c)

Public Member Functions inherited from Ponca::KdTreeBase< Traits >
template<typename PointUserContainer , typename Converter >
void	build (PointUserContainer &&points, Converter c)
	Generate a tree from a custom contained type converted using the specified converter.

template<typename PointUserContainer >
void	build (PointUserContainer &&points)
	Generate a tree from a custom contained type converted using DefaultConverter.

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< Traits >	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< Traits >	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< Traits >	kNearestNeighborsQuery () const
	Convenience function that provides an empty k-nearest neighbors Query object.

KdTreeKNearestIndexQuery< Traits >	kNearestNeighborsIndexQuery () const
	Convenience function that provides an empty k-nearest neighbors Query object.

KdTreeNearestPointQuery< Traits >	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< Traits >	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< Traits >	nearestNeighborQuery () const
	Convenience function that provides an empty nearest neighbor Query object.

KdTreeNearestIndexQuery< Traits >	nearestNeighborIndexQuery () const
	Convenience function that provides an empty nearest neighbor Query object.

KdTreeRangePointQuery< Traits >	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< Traits >	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< Traits >	rangeNeighborsQuery () const
	Convenience function that provides an empty range neighbor Query object.

KdTreeRangeIndexQuery< Traits >	rangeNeighborsIndexQuery () const
	KdTreeBase::rangeNeighborsQuery.

bool	valid () const

void	print (std::ostream &os, bool verbose=false) const

template<typename PointUserContainer , typename Converter >
void	build (PointUserContainer &&points, Converter c)

template<typename PointUserContainer , typename IndexUserContainer , typename Converter >
void	buildWithSampling (PointUserContainer &&points, IndexUserContainer sampling, Converter c)

Static Public Attributes
static constexpr bool	SUPPORTS_SUBSAMPLING = false

Static Public Attributes inherited from Ponca::KdTreeBase< Traits >
static constexpr std::size_t	MAX_NODE_COUNT = NodeType::MAX_COUNT
	The maximum number of nodes that the kd-tree can have.

static constexpr std::size_t	MAX_POINT_COUNT = std::size_t(2) << sizeof(IndexType)*8
	The maximum number of points that can be stored in the kd-tree.

static constexpr int	MAX_DEPTH = Traits::MAX_DEPTH
	The maximum depth of the kd-tree.

static constexpr bool	SUPPORTS_SUBSAMPLING = false

Additional Inherited Members
Public Types inherited from Ponca::KdTreeBase< Traits >
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.

Protected Member Functions inherited from Ponca::KdTreeBase< Traits >
template<typename PointUserContainer , typename IndexUserContainer , typename Converter >
void	buildWithSampling (PointUserContainer &&points, IndexUserContainer sampling, Converter c)
	Generate a tree sampled from a custom contained type converted using a `Converter`

template<typename PointUserContainer , typename IndexUserContainer >
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< Traits >
PointContainer	m_points

NodeContainer	m_nodes

IndexContainer	m_indices

LeafSizeType	m_min_cell_size {64}
	Minimal number of points per leaf.

NodeIndexType	m_leaf_count {0}
	Number of leaves in the Kdtree (computed during construction)

Detailed Description

template<typename Traits>
class Ponca::KdTreeSparseBase< Traits >

Customizable base class for KdTreeSparse datastructure.

This version of the KdTree supports construction using a subset of samples.

See also: buildWithSampling; Ponca::KdTreeDense; Ponca::KdTreeSparse

Template Parameters

Traits Traits type providing the types and constants used by the kd-tree. Must have the same interface as the default traits type.

See also: KdTreeDefaultTraits for the trait interface documentation.

Definition at line 506 of file kdTree.h.

Constructor & Destructor Documentation

◆ KdTreeSparseBase() [1/3]

template<typename Traits >

Ponca::KdTreeSparseBase< Traits >::KdTreeSparseBase ( )

default

Default constructor creating an empty tree.

See also: build

◆ KdTreeSparseBase() [2/3]

template<typename Traits >

template<typename PointUserContainer >

Ponca::KdTreeSparseBase< Traits >::KdTreeSparseBase ( PointUserContainer && points )

inlineexplicit

Constructor generating a tree from a custom contained type converted using a KdTreeBase::DefaultConverter.

Definition at line 520 of file kdTree.h.

◆ KdTreeSparseBase() [3/3]

template<typename Traits >

template<typename PointUserContainer , typename IndexUserContainer >

Ponca::KdTreeSparseBase< Traits >::KdTreeSparseBase	(	PointUserContainer &&	points,
		IndexUserContainer	sampling
	)

inline

Constructor generating a tree sampled from a custom contained type converted using a KdTreeBase::DefaultConverter.

Template Parameters

PointUserContainer	Input points, transformed to PointContainer
IndexUserContainer	Input sampling, transformed to IndexContainer

Parameters

point	Input points
sampling	Samples used in the tree

Definition at line 532 of file kdTree.h.

Member Function Documentation

◆ buildWithSampling() [1/3]

template<typename Traits >

template<typename PointUserContainer , typename IndexUserContainer >

void Ponca::KdTreeBase< Traits >::buildWithSampling	(	PointUserContainer &&	points,
		IndexUserContainer	sampling
	)

inline

Generate a tree sampled from a custom contained type converted using a KdTreeBase::DefaultConverter.

Template Parameters

PointUserContainer	Input points, transformed to PointContainer
IndexUserContainer	Input sampling, transformed to IndexContainer

Parameters

points	Input points
sampling	Samples used in the tree

Definition at line 446 of file kdTree.h.

◆ buildWithSampling() [2/3]

template<typename Traits >

template<typename PointUserContainer , typename IndexUserContainer , typename Converter >

void Ponca::KdTreeBase< Traits >::buildWithSampling	(	PointUserContainer &&	points,
		IndexUserContainer	sampling,
		Converter	c
	)

inline

Generate a tree sampled from a custom contained type converted using a Converter

Template Parameters

PointUserContainer	Input point, transformed to PointContainer
IndexUserContainer	Input sampling, transformed to IndexContainer
Converter

Parameters

points	Input points
sampling	Indices of points used in the tree
c	Cast/Convert input point type to DataType

◆ buildWithSampling() [3/3]

template<typename Traits >

template<typename PointUserContainer , typename IndexUserContainer , typename Converter >

void Ponca::KdTreeBase< Traits >::buildWithSampling	(	PointUserContainer &&	points,
		IndexUserContainer	sampling,
		Converter	c
	)

inline

Definition at line 121 of file kdTree.hpp.

Member Data Documentation

◆ SUPPORTS_SUBSAMPLING

template<typename Traits >

constexpr bool Ponca::KdTreeSparseBase< Traits >::SUPPORTS_SUBSAMPLING = false

staticconstexpr

Definition at line 512 of file kdTree.h.

Public Member Functions

Static Public Attributes

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ KdTreeSparseBase() [1/3]

◆ KdTreeSparseBase() [2/3]

◆ KdTreeSparseBase() [3/3]

Member Function Documentation

◆ buildWithSampling() [1/3]

◆ buildWithSampling() [2/3]

◆ buildWithSampling() [3/3]

Member Data Documentation

◆ SUPPORTS_SUBSAMPLING