KDTree, unbalanced, points in leaves, stack, implicit bounds, ANN_KD_SL_MIDPT, optimised implementation. More...

#include <nabo_private.h>

Inheritance diagram for Nabo::KDTreeUnbalancedPtInLeavesImplicitBoundsStackOpt< T, Heap, CloudType >:

Classes
struct	BucketEntry
	entry in a bucket More...
struct	Node
	search node More...
Public Types
typedef NearestNeighbourSearch < T, CloudType >::Index	Index
	an index to a Vector or a Matrix, for refering to data points
typedef NearestNeighbourSearch < T, CloudType >::IndexMatrix	IndexMatrix
	a matrix of indices to data points
typedef NearestNeighbourSearch < T, CloudType >::IndexVector	IndexVector
	a vector of indices to data points
typedef NearestNeighbourSearch < T, CloudType >::Matrix	Matrix
	a column-major Eigen matrix in which each column is a point; this matrix has dim rows
typedef NearestNeighbourSearch < T, CloudType >::Vector	Vector
	an Eigen vector of type T, to hold the coordinates of a point
Protected Types
typedef std::vector< BucketEntry >	Buckets
	bucket data
typedef std::vector< Index >	BuildPoints
	indices of points during kd-tree construction
typedef BuildPoints::const_iterator	BuildPointsCstIt
	const-iterator to indices of points during kd-tree construction
typedef BuildPoints::iterator	BuildPointsIt
	iterator to indices of points during kd-tree construction
typedef std::vector< Node >	Nodes
	dense vector of search nodes, provides better memory performances than many small objects
Protected Member Functions
uint32_t	createDimChildBucketSize (const uint32_t dim, const uint32_t childIndex) const
	create the compound index containing the dimension and the index of the child or the bucket size
uint32_t	getChildBucketSize (const uint32_t dimChildBucketSize) const
	get the child index or the bucket size out of the coumpount index
uint32_t	getDim (const uint32_t dimChildBucketSize) const
	get the dimension out of the compound index
Protected Attributes
Buckets	buckets
	buckets
const unsigned	bucketSize
	size of bucket
const uint32_t	dimBitCount
	number of bits required to store dimension index + number of dimensions
const uint32_t	dimMask
	mask to access dim
Nodes	nodes
	search nodes
std::pair< T, T >	getBounds (const BuildPointsIt first, const BuildPointsIt last, const unsigned dim)
	return the bounds of points from [first..last[ on dimension dim
unsigned	buildNodes (const BuildPointsIt first, const BuildPointsIt last, const Vector minValues, const Vector maxValues)
	construct nodes for points [first..last[ inside the hyperrectangle [minValues..maxValues]
unsigned long	onePointKnn (const Matrix &query, IndexMatrix &indices, Matrix &dists2, int i, Heap &heap, std::vector< T > &off, const T maxError, const T maxRadius2, const bool allowSelfMatch, const bool collectStatistics, const bool sortResults) const
	search one point, call recurseKnn with the correct template parameters
template<bool allowSelfMatch, bool collectStatistics>
unsigned long	recurseKnn (const T *query, const unsigned n, T rd, Heap &heap, std::vector< T > &off, const T maxError, const T maxRadius2) const
	recursive search, strongly inspired by ANN and [Arya & Mount, Algorithms for fast vector quantization, 1993]
	KDTreeUnbalancedPtInLeavesImplicitBoundsStackOpt (const CloudType &cloud, const Index dim, const unsigned creationOptionFlags, const Parameters &additionalParameters)
	constructor, calls NearestNeighbourSearch<T>(cloud)
virtual unsigned long	knn (const Matrix &query, IndexMatrix &indices, Matrix &dists2, const Index k, const T epsilon, const unsigned optionFlags, const T maxRadius) const
virtual unsigned long	knn (const Matrix &query, IndexMatrix &indices, Matrix &dists2, const Vector &maxRadii, const Index k=1, const T epsilon=0, const unsigned optionFlags=0) const

Detailed Description

template<typename T, typename Heap, typename CloudType = Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>>
struct Nabo::KDTreeUnbalancedPtInLeavesImplicitBoundsStackOpt< T, Heap, CloudType >

KDTree, unbalanced, points in leaves, stack, implicit bounds, ANN_KD_SL_MIDPT, optimised implementation.

Definition at line 98 of file nabo_private.h.

Member Typedef Documentation

template<typename T, typename Heap, typename CloudType = Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>>

typedef std::vector<BucketEntry> Nabo::KDTreeUnbalancedPtInLeavesImplicitBoundsStackOpt< T, Heap, CloudType >::Buckets [protected]

bucket data

Definition at line 175 of file nabo_private.h.

template<typename T, typename Heap, typename CloudType = Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>>

typedef std::vector<Index> Nabo::KDTreeUnbalancedPtInLeavesImplicitBoundsStackOpt< T, Heap, CloudType >::BuildPoints [protected]

indices of points during kd-tree construction

Definition at line 115 of file nabo_private.h.

template<typename T, typename Heap, typename CloudType = Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>>

typedef BuildPoints::const_iterator Nabo::KDTreeUnbalancedPtInLeavesImplicitBoundsStackOpt< T, Heap, CloudType >::BuildPointsCstIt [protected]

const-iterator to indices of points during kd-tree construction

Definition at line 119 of file nabo_private.h.

template<typename T, typename Heap, typename CloudType = Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>>

typedef BuildPoints::iterator Nabo::KDTreeUnbalancedPtInLeavesImplicitBoundsStackOpt< T, Heap, CloudType >::BuildPointsIt [protected]

iterator to indices of points during kd-tree construction

Definition at line 117 of file nabo_private.h.

template<typename T, typename Heap, typename CloudType = Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>>

typedef NearestNeighbourSearch<T, CloudType>::Index Nabo::KDTreeUnbalancedPtInLeavesImplicitBoundsStackOpt< T, Heap, CloudType >::Index

an index to a Vector or a Matrix, for refering to data points

Reimplemented from Nabo::NearestNeighbourSearch< T, CloudType >.

Definition at line 102 of file nabo_private.h.

template<typename T, typename Heap, typename CloudType = Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>>

typedef NearestNeighbourSearch<T, CloudType>::IndexMatrix Nabo::KDTreeUnbalancedPtInLeavesImplicitBoundsStackOpt< T, Heap, CloudType >::IndexMatrix

a matrix of indices to data points

Reimplemented from Nabo::NearestNeighbourSearch< T, CloudType >.

Definition at line 104 of file nabo_private.h.

template<typename T, typename Heap, typename CloudType = Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>>

typedef NearestNeighbourSearch<T, CloudType>::IndexVector Nabo::KDTreeUnbalancedPtInLeavesImplicitBoundsStackOpt< T, Heap, CloudType >::IndexVector

a vector of indices to data points

Reimplemented from Nabo::NearestNeighbourSearch< T, CloudType >.

Definition at line 103 of file nabo_private.h.

template<typename T, typename Heap, typename CloudType = Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>>

typedef NearestNeighbourSearch<T, CloudType>::Matrix Nabo::KDTreeUnbalancedPtInLeavesImplicitBoundsStackOpt< T, Heap, CloudType >::Matrix

a column-major Eigen matrix in which each column is a point; this matrix has dim rows

Reimplemented from Nabo::NearestNeighbourSearch< T, CloudType >.

Definition at line 101 of file nabo_private.h.

template<typename T, typename Heap, typename CloudType = Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>>

typedef std::vector<Node> Nabo::KDTreeUnbalancedPtInLeavesImplicitBoundsStackOpt< T, Heap, CloudType >::Nodes [protected]

dense vector of search nodes, provides better memory performances than many small objects

Definition at line 159 of file nabo_private.h.

template<typename T, typename Heap, typename CloudType = Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>>

typedef NearestNeighbourSearch<T, CloudType>::Vector Nabo::KDTreeUnbalancedPtInLeavesImplicitBoundsStackOpt< T, Heap, CloudType >::Vector

an Eigen vector of type T, to hold the coordinates of a point

Reimplemented from Nabo::NearestNeighbourSearch< T, CloudType >.

Definition at line 100 of file nabo_private.h.

Constructor & Destructor Documentation

template<typename T , typename Heap , typename CloudType >

Nabo::KDTreeUnbalancedPtInLeavesImplicitBoundsStackOpt< T, Heap, CloudType >::KDTreeUnbalancedPtInLeavesImplicitBoundsStackOpt	(	const CloudType &	cloud,
		const Index	dim,
		const unsigned	creationOptionFlags,
		const Parameters &	additionalParameters
	)

constructor, calls NearestNeighbourSearch<T>(cloud)

Definition at line 231 of file nabo/kdtree_cpu.cpp.

Member Function Documentation

template<typename T , typename Heap , typename CloudType >

unsigned Nabo::KDTreeUnbalancedPtInLeavesImplicitBoundsStackOpt< T, Heap, CloudType >::buildNodes	(	const BuildPointsIt	first,
		const BuildPointsIt	last,
		const Vector	minValues,
		const Vector	maxValues
	)		`[protected]`

construct nodes for points [first..last[ inside the hyperrectangle [minValues..maxValues]

Definition at line 113 of file nabo/kdtree_cpu.cpp.

template<typename T, typename Heap, typename CloudType = Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>>

uint32_t Nabo::KDTreeUnbalancedPtInLeavesImplicitBoundsStackOpt< T, Heap, CloudType >::createDimChildBucketSize	(	const uint32_t	dim,
		const uint32_t	childIndex
	)		const `[inline, protected]`

create the compound index containing the dimension and the index of the child or the bucket size

Definition at line 130 of file nabo_private.h.

template<typename T , typename Heap , typename CloudType >

pair< T, T > Nabo::KDTreeUnbalancedPtInLeavesImplicitBoundsStackOpt< T, Heap, CloudType >::getBounds	(	const BuildPointsIt	first,
		const BuildPointsIt	last,
		const unsigned	dim
	)		`[protected]`

return the bounds of points from [first..last[ on dimension dim

Definition at line 97 of file nabo/kdtree_cpu.cpp.

template<typename T, typename Heap, typename CloudType = Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>>

uint32_t Nabo::KDTreeUnbalancedPtInLeavesImplicitBoundsStackOpt< T, Heap, CloudType >::getChildBucketSize ( const uint32_t dimChildBucketSize ) const [inline, protected]

get the child index or the bucket size out of the coumpount index

Definition at line 136 of file nabo_private.h.

template<typename T, typename Heap, typename CloudType = Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>>

uint32_t Nabo::KDTreeUnbalancedPtInLeavesImplicitBoundsStackOpt< T, Heap, CloudType >::getDim ( const uint32_t dimChildBucketSize ) const [inline, protected]

get the dimension out of the compound index

Definition at line 133 of file nabo_private.h.

template<typename T , typename Heap , typename CloudType >

unsigned long Nabo::KDTreeUnbalancedPtInLeavesImplicitBoundsStackOpt< T, Heap, CloudType >::knn	(	const Matrix &	query,
		IndexMatrix &	indices,
		Matrix &	dists2,
		const Index	k,
		const T	epsilon,
		const unsigned	optionFlags,
		const T	maxRadius
	)		const `[virtual]`

Definition at line 277 of file nabo/kdtree_cpu.cpp.

template<typename T , typename Heap , typename CloudType >

unsigned long Nabo::KDTreeUnbalancedPtInLeavesImplicitBoundsStackOpt< T, Heap, CloudType >::knn	(	const Matrix &	query,
		IndexMatrix &	indices,
		Matrix &	dists2,
		const Vector &	maxRadii,
		const Index	k = `1`,
		const T	epsilon = `0`,
		const unsigned	optionFlags = `0`
	)		const `[virtual]`

Definition at line 309 of file nabo/kdtree_cpu.cpp.

template<typename T , typename Heap , typename CloudType >

unsigned long Nabo::KDTreeUnbalancedPtInLeavesImplicitBoundsStackOpt< T, Heap, CloudType >::onePointKnn	(	const Matrix &	query,
		IndexMatrix &	indices,
		Matrix &	dists2,
		int	i,
		Heap &	heap,
		std::vector< T > &	off,
		const T	maxError,
		const T	maxRadius2,
		const bool	allowSelfMatch,
		const bool	collectStatistics,
		const bool	sortResults
	)		const `[protected]`

search one point, call recurseKnn with the correct template parameters

Parameters:

query	pointer to query coordinates
indices	indices of nearest neighbours, must be of size k x query.cols()
dists2	squared distances to nearest neighbours, must be of size k x query.cols()
i	index of point to search
heap	reference to heap
off	reference to array of offsets
maxError	error factor (1 + epsilon)
maxRadius2	square of maximum radius
allowSelfMatch	whether to allow self match
collectStatistics	whether to collect statistics
sortResults	wether to sort results

Definition at line 341 of file nabo/kdtree_cpu.cpp.

template<typename T , typename Heap , typename CloudType >

template<bool allowSelfMatch, bool collectStatistics>

unsigned long Nabo::KDTreeUnbalancedPtInLeavesImplicitBoundsStackOpt< T, Heap, CloudType >::recurseKnn	(	const T *	query,
		const unsigned	n,
		T	rd,
		Heap &	heap,
		std::vector< T > &	off,
		const T	maxError,
		const T	maxRadius2
	)		const `[protected]`

recursive search, strongly inspired by ANN and [Arya & Mount, Algorithms for fast vector quantization, 1993]

Parameters:

query	pointer to query coordinates
n	index of node to visit
rd	squared dist to this rect
heap	reference to heap
off	reference to array of offsets
maxError	error factor (1 + epsilon)
maxRadius2	square of maximum radius

Definition at line 370 of file nabo/kdtree_cpu.cpp.

Member Data Documentation

template<typename T, typename Heap, typename CloudType = Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>>

Buckets Nabo::KDTreeUnbalancedPtInLeavesImplicitBoundsStackOpt< T, Heap, CloudType >::buckets [protected]

buckets

Definition at line 181 of file nabo_private.h.

template<typename T, typename Heap, typename CloudType = Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>>

const unsigned Nabo::KDTreeUnbalancedPtInLeavesImplicitBoundsStackOpt< T, Heap, CloudType >::bucketSize [protected]

size of bucket

Definition at line 122 of file nabo_private.h.

template<typename T, typename Heap, typename CloudType = Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>>

const uint32_t Nabo::KDTreeUnbalancedPtInLeavesImplicitBoundsStackOpt< T, Heap, CloudType >::dimBitCount [protected]

number of bits required to store dimension index + number of dimensions

Definition at line 125 of file nabo_private.h.

template<typename T, typename Heap, typename CloudType = Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>>

const uint32_t Nabo::KDTreeUnbalancedPtInLeavesImplicitBoundsStackOpt< T, Heap, CloudType >::dimMask [protected]

mask to access dim

Definition at line 127 of file nabo_private.h.

template<typename T, typename Heap, typename CloudType = Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>>

Nodes Nabo::KDTreeUnbalancedPtInLeavesImplicitBoundsStackOpt< T, Heap, CloudType >::nodes [protected]

search nodes

Definition at line 178 of file nabo_private.h.

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

Classes

Public Types

Protected Types

Protected Member Functions

Protected Attributes

Detailed Description

template<typename T, typename Heap, typename CloudType = Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>> struct Nabo::KDTreeUnbalancedPtInLeavesImplicitBoundsStackOpt< T, Heap, CloudType >

Member Typedef Documentation

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation

template<typename T, typename Heap, typename CloudType = Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic>>
struct Nabo::KDTreeUnbalancedPtInLeavesImplicitBoundsStackOpt< T, Heap, CloudType >