#include <kdtree_single_index.h>

Inheritance diagram for rtflann::KDTreeSingleIndex< Distance >:

Classes
struct	Interval

struct	Node

Public Types
typedef NNIndex< Distance >	BaseClass

typedef Distance::ResultType	DistanceType

typedef Distance::ElementType	ElementType

typedef bool	needs_kdtree_distance

Public Types inherited from rtflann::NNIndex< Distance >
typedef Distance::ResultType	DistanceType

typedef Distance::ElementType	ElementType

Public Member Functions
void	addPoints (const Matrix< ElementType > &points, float rebuild_threshold=2)
	Incrementally add points to the index. More...

virtual void	buildIndex ()

virtual void	buildIndex (const Matrix< ElementType > &dataset)

BaseClass *	clone () const

void	findNeighbors (ResultSet< DistanceType > &result, const ElementType *vec, const SearchParams &searchParams) const

flann_algorithm_t	getType () const

	KDTreeSingleIndex (const IndexParams &params=KDTreeSingleIndexParams(), Distance d=Distance())

	KDTreeSingleIndex (const KDTreeSingleIndex &other)

	KDTreeSingleIndex (const Matrix< ElementType > &inputData, const IndexParams &params=KDTreeSingleIndexParams(), Distance d=Distance())

void	loadIndex (FILE *stream)

KDTreeSingleIndex &	operator= (KDTreeSingleIndex other)

void	saveIndex (FILE *stream)

template<typename Archive >
void	serialize (Archive &ar)

int	usedMemory () const

virtual	~KDTreeSingleIndex ()

Public Member Functions inherited from rtflann::NNIndex< Distance >
virtual void	buildIndex ()

virtual void	buildIndex (const Matrix< ElementType > &dataset)

IndexParams	getParameters () const

virtual ElementType *	getPoint (size_t id)

virtual int	knnSearch (const Matrix< ElementType > &queries, Matrix< size_t > &indices, Matrix< DistanceType > &dists, size_t knn, const SearchParams &params) const
	Perform k-nearest neighbor search. More...

int	knnSearch (const Matrix< ElementType > &queries, std::vector< std::vector< int > > &indices, std::vector< std::vector< DistanceType > > &dists, size_t knn, const SearchParams &params) const

virtual int	knnSearch (const Matrix< ElementType > &queries, std::vector< std::vector< size_t > > &indices, std::vector< std::vector< DistanceType > > &dists, size_t knn, const SearchParams &params) const
	Perform k-nearest neighbor search. More...

	NNIndex (const IndexParams &params, Distance d)

	NNIndex (const NNIndex &other)

	NNIndex (Distance d)

int	radiusSearch (const Matrix< ElementType > &queries, Matrix< int > &indices, Matrix< DistanceType > &dists, float radius, const SearchParams &params) const

virtual int	radiusSearch (const Matrix< ElementType > &queries, Matrix< size_t > &indices, Matrix< DistanceType > &dists, float radius, const SearchParams &params) const
	Perform radius search. More...

int	radiusSearch (const Matrix< ElementType > &queries, std::vector< std::vector< int > > &indices, std::vector< std::vector< DistanceType > > &dists, float radius, const SearchParams &params) const

virtual int	radiusSearch (const Matrix< ElementType > &queries, std::vector< std::vector< size_t > > &indices, std::vector< std::vector< DistanceType > > &dists, float radius, const SearchParams &params) const
	Perform radius search. More...

size_t	removedCount () const

virtual void	removePoint (size_t id)

template<typename Archive >
void	serialize (Archive &ar)

size_t	size () const

size_t	sizeAtBuild () const

size_t	veclen () const

virtual	~NNIndex ()

Public Member Functions inherited from rtflann::IndexBase
virtual	~IndexBase ()

Protected Member Functions
void	buildIndexImpl ()

Protected Member Functions inherited from rtflann::NNIndex< Distance >
void	cleanRemovedPoints ()

void	extendDataset (const Matrix< ElementType > &new_points)

size_t	id_to_index (size_t id)

void	indices_to_ids (const size_t in, size_t out, size_t size) const

void	setDataset (const Matrix< ElementType > &dataset)

void	swap (NNIndex &other)

Private Types
typedef std::vector< Interval >	BoundingBox

typedef BranchSt *	Branch

typedef BranchStruct< NodePtr, DistanceType >	BranchSt

typedef Node *	NodePtr

Private Member Functions
void	computeBoundingBox (BoundingBox &bbox)

DistanceType	computeInitialDistances (const ElementType *vec, std::vector< DistanceType > &dists) const

void	computeMinMax (int *ind, int count, int dim, ElementType &min_elem, ElementType &max_elem)

void	copyTree (NodePtr &dst, const NodePtr &src)

NodePtr	divideTree (int left, int right, BoundingBox &bbox)

void	freeIndex ()

void	middleSplit (int *ind, int count, int &index, int &cutfeat, DistanceType &cutval, const BoundingBox &bbox)

void	middleSplit_ (int *ind, int count, int &index, int &cutfeat, DistanceType &cutval, const BoundingBox &bbox)

void	planeSplit (int *ind, int count, int cutfeat, DistanceType cutval, int &lim1, int &lim2)

template<bool with_removed>
void	searchLevel (ResultSet< DistanceType > &result_set, const ElementType *vec, const NodePtr node, DistanceType mindistsq, std::vector< DistanceType > &dists, const float epsError) const

void	swap (KDTreeSingleIndex &other)

Private Attributes
Matrix< ElementType >	data_

int	leaf_max_size_

PooledAllocator	pool_

bool	reorder_

BoundingBox	root_bbox_

NodePtr	root_node_

std::vector< int >	vind_

Additional Inherited Members
Protected Attributes inherited from rtflann::NNIndex< Distance >
ElementType *	data_ptr_

Distance	distance_

std::vector< size_t >	ids_

IndexParams	index_params_

size_t	last_id_

std::vector< ElementType * >	points_

bool	removed_

size_t	removed_count_

DynamicBitset	removed_points_

size_t	size_

size_t	size_at_build_

size_t	veclen_

Detailed Description

template<typename Distance>
class rtflann::KDTreeSingleIndex< Distance >

Single kd-tree index

Contains the k-d trees and other information for indexing a set of points for nearest-neighbor matching.

Definition at line 97 of file kdtree_single_index.h.

Member Typedef Documentation

◆ BaseClass

template<typename Distance >

typedef NNIndex<Distance> rtflann::KDTreeSingleIndex< Distance >::BaseClass

Definition at line 103 of file kdtree_single_index.h.

◆ BoundingBox

template<typename Distance >

typedef std::vector<Interval> rtflann::KDTreeSingleIndex< Distance >::BoundingBox

private

Definition at line 362 of file kdtree_single_index.h.

◆ Branch

template<typename Distance >

typedef BranchSt* rtflann::KDTreeSingleIndex< Distance >::Branch

private

Definition at line 365 of file kdtree_single_index.h.

◆ BranchSt

template<typename Distance >

typedef BranchStruct<NodePtr, DistanceType> rtflann::KDTreeSingleIndex< Distance >::BranchSt

private

Definition at line 364 of file kdtree_single_index.h.

◆ DistanceType

template<typename Distance >

typedef Distance::ResultType rtflann::KDTreeSingleIndex< Distance >::DistanceType

Definition at line 101 of file kdtree_single_index.h.

◆ ElementType

template<typename Distance >

typedef Distance::ElementType rtflann::KDTreeSingleIndex< Distance >::ElementType

Definition at line 100 of file kdtree_single_index.h.

◆ needs_kdtree_distance

template<typename Distance >

typedef bool rtflann::KDTreeSingleIndex< Distance >::needs_kdtree_distance

Definition at line 105 of file kdtree_single_index.h.

◆ NodePtr

template<typename Distance >

typedef Node* rtflann::KDTreeSingleIndex< Distance >::NodePtr

private

Definition at line 345 of file kdtree_single_index.h.

Constructor & Destructor Documentation

◆ KDTreeSingleIndex() [1/3]

template<typename Distance >

rtflann::KDTreeSingleIndex< Distance >::KDTreeSingleIndex	(	const IndexParams &	params = `KDTreeSingleIndexParams()`,
		Distance	d = `Distance()`
	)

inline

KDTree constructor

Params: params = parameters passed to the kdtree algorithm

Definition at line 113 of file kdtree_single_index.h.

◆ KDTreeSingleIndex() [2/3]

template<typename Distance >

rtflann::KDTreeSingleIndex< Distance >::KDTreeSingleIndex	(	const Matrix< ElementType > &	inputData,
		const IndexParams &	params = `KDTreeSingleIndexParams()`,
		Distance	d = `Distance()`
	)

inline

KDTree constructor

Params: inputData = dataset with the input features params = parameters passed to the kdtree algorithm

Definition at line 127 of file kdtree_single_index.h.

◆ KDTreeSingleIndex() [3/3]

template<typename Distance >

rtflann::KDTreeSingleIndex< Distance >::KDTreeSingleIndex ( const KDTreeSingleIndex< Distance > & other )

inline

Definition at line 137 of file kdtree_single_index.h.

◆ ~KDTreeSingleIndex()

template<typename Distance >

virtual rtflann::KDTreeSingleIndex< Distance >::~KDTreeSingleIndex ( )

inlinevirtual

Standard destructor

Definition at line 159 of file kdtree_single_index.h.

Member Function Documentation

◆ addPoints()

template<typename Distance >

void rtflann::KDTreeSingleIndex< Distance >::addPoints	(	const Matrix< ElementType > &	points,
		float	rebuild_threshold = `2`
	)

inlinevirtual

Incrementally add points to the index.

Parameters

points	Matrix with points to be added
rebuild_threshold

Reimplemented from rtflann::NNIndex< Distance >.

Definition at line 171 of file kdtree_single_index.h.

◆ buildIndex() [1/2]

template<typename Distance >

virtual void rtflann::NNIndex< Distance >::buildIndex

inline

Builds the index

Definition at line 153 of file nn_index.h.

◆ buildIndex() [2/2]

template<typename Distance >

virtual void rtflann::NNIndex< Distance >::buildIndex

inline

Builds the index using the specified dataset

Parameters

dataset the dataset to use

Definition at line 169 of file nn_index.h.

◆ buildIndexImpl()

template<typename Distance >

void rtflann::KDTreeSingleIndex< Distance >::buildIndexImpl ( )

inlineprotectedvirtual

Builds the index

Implements rtflann::NNIndex< Distance >.

Definition at line 267 of file kdtree_single_index.h.

◆ clone()

template<typename Distance >

BaseClass* rtflann::KDTreeSingleIndex< Distance >::clone ( ) const

inlinevirtual

Implements rtflann::NNIndex< Distance >.

Definition at line 164 of file kdtree_single_index.h.

◆ computeBoundingBox()

template<typename Distance >

void rtflann::KDTreeSingleIndex< Distance >::computeBoundingBox ( BoundingBox & bbox )

inlineprivate

Definition at line 391 of file kdtree_single_index.h.

◆ computeInitialDistances()

template<typename Distance >

DistanceType rtflann::KDTreeSingleIndex< Distance >::computeInitialDistances	(	const ElementType *	vec,
		std::vector< DistanceType > &	dists
	)		const

inlineprivate

Definition at line 599 of file kdtree_single_index.h.

◆ computeMinMax()

template<typename Distance >

void rtflann::KDTreeSingleIndex< Distance >::computeMinMax	(	int *	ind,
		int	count,
		int	dim,
		ElementType &	min_elem,
		ElementType &	max_elem
	)

inlineprivate

Definition at line 466 of file kdtree_single_index.h.

◆ copyTree()

template<typename Distance >

void rtflann::KDTreeSingleIndex< Distance >::copyTree	(	NodePtr &	dst,
		const NodePtr &	src
	)

inlineprivate

Definition at line 379 of file kdtree_single_index.h.

◆ divideTree()

template<typename Distance >

NodePtr rtflann::KDTreeSingleIndex< Distance >::divideTree	(	int	left,
		int	right,
		BoundingBox &	bbox
	)

inlineprivate

Create a tree node that subdivides the list of vecs from vind[first] to vind[last]. The routine is called recursively on each sublist. Place a pointer to this new tree node in the location pTree.

Params: pTree = the new node to create first = index of the first vector last = index of the last vector

Definition at line 416 of file kdtree_single_index.h.

◆ findNeighbors()

template<typename Distance >

void rtflann::KDTreeSingleIndex< Distance >::findNeighbors	(	ResultSet< DistanceType > &	result,
		const ElementType *	vec,
		const SearchParams &	searchParams
	)		const

inlinevirtual

Find set of nearest neighbors to vec. Their indices are stored inside the result object.

Params: result = the result object in which the indices of the nearest-neighbors are stored vec = the vector for which to search the nearest neighbors maxCheck = the maximum number of restarts (in a best-bin-first manner)

Implements rtflann::NNIndex< Distance >.

Definition at line 248 of file kdtree_single_index.h.

◆ freeIndex()

template<typename Distance >

void rtflann::KDTreeSingleIndex< Distance >::freeIndex ( )

inlineprivatevirtual

Implements rtflann::NNIndex< Distance >.

Definition at line 369 of file kdtree_single_index.h.

◆ getType()

template<typename Distance >

flann_algorithm_t rtflann::KDTreeSingleIndex< Distance >::getType ( ) const

inlinevirtual

Implements rtflann::IndexBase.

Definition at line 178 of file kdtree_single_index.h.

◆ loadIndex()

template<typename Distance >

void rtflann::KDTreeSingleIndex< Distance >::loadIndex ( FILE * stream )

inlinevirtual

Implements rtflann::IndexBase.

Definition at line 223 of file kdtree_single_index.h.

◆ middleSplit()

template<typename Distance >

void rtflann::KDTreeSingleIndex< Distance >::middleSplit	(	int *	ind,
		int	count,
		int &	index,
		int &	cutfeat,
		DistanceType &	cutval,
		const BoundingBox &	bbox
	)

inlineprivate

Definition at line 477 of file kdtree_single_index.h.

◆ middleSplit_()

template<typename Distance >

void rtflann::KDTreeSingleIndex< Distance >::middleSplit_	(	int *	ind,
		int	count,
		int &	index,
		int &	cutfeat,
		DistanceType &	cutval,
		const BoundingBox &	bbox
	)

inlineprivate

Definition at line 524 of file kdtree_single_index.h.

◆ operator=()

template<typename Distance >

KDTreeSingleIndex& rtflann::KDTreeSingleIndex< Distance >::operator= ( KDTreeSingleIndex< Distance > other )

inline

Definition at line 150 of file kdtree_single_index.h.

◆ planeSplit()

template<typename Distance >

void rtflann::KDTreeSingleIndex< Distance >::planeSplit	(	int *	ind,
		int	count,
		int	cutfeat,
		DistanceType	cutval,
		int &	lim1,
		int &	lim2
	)

inlineprivate

Subdivide the list of points by a plane perpendicular on axe corresponding to the 'cutfeat' dimension at 'cutval' position.

On return: dataset[ind[0..lim1-1]][cutfeat]<cutval dataset[ind[lim1..lim2-1]][cutfeat]==cutval dataset[ind[lim2..count]][cutfeat]>cutval

Definition at line 577 of file kdtree_single_index.h.

◆ saveIndex()

template<typename Distance >

void rtflann::KDTreeSingleIndex< Distance >::saveIndex ( FILE * stream )

inlinevirtual

Implements rtflann::IndexBase.

Definition at line 216 of file kdtree_single_index.h.

◆ searchLevel()

template<typename Distance >

template<bool with_removed>

void rtflann::KDTreeSingleIndex< Distance >::searchLevel	(	ResultSet< DistanceType > &	result_set,
		const ElementType *	vec,
		const NodePtr	node,
		DistanceType	mindistsq,
		std::vector< DistanceType > &	dists,
		const float	epsError
	)		const

inlineprivate

Performs an exact search in the tree starting from a node.

Definition at line 621 of file kdtree_single_index.h.

◆ serialize()

template<typename Distance >

template<typename Archive >

void rtflann::KDTreeSingleIndex< Distance >::serialize ( Archive & ar )

inline

Definition at line 185 of file kdtree_single_index.h.

◆ swap()

template<typename Distance >

void rtflann::KDTreeSingleIndex< Distance >::swap ( KDTreeSingleIndex< Distance > & other )

inlineprivate

Definition at line 673 of file kdtree_single_index.h.

◆ usedMemory()

template<typename Distance >

int rtflann::KDTreeSingleIndex< Distance >::usedMemory ( ) const

inlinevirtual

Computes the inde memory usage Returns: memory used by the index

Implements rtflann::IndexBase.

Definition at line 234 of file kdtree_single_index.h.

Member Data Documentation

◆ data_

template<typename Distance >

Matrix<ElementType> rtflann::KDTreeSingleIndex< Distance >::data_

private

Definition at line 699 of file kdtree_single_index.h.

◆ leaf_max_size_

template<typename Distance >

int rtflann::KDTreeSingleIndex< Distance >::leaf_max_size_

private

Definition at line 689 of file kdtree_single_index.h.

◆ pool_

template<typename Distance >

PooledAllocator rtflann::KDTreeSingleIndex< Distance >::pool_

private

Pooled memory allocator.

Using a pooled memory allocator is more efficient than allocating memory directly when there is a large number small of memory allocations.

Definition at line 718 of file kdtree_single_index.h.

◆ reorder_

template<typename Distance >

bool rtflann::KDTreeSingleIndex< Distance >::reorder_

private

Definition at line 692 of file kdtree_single_index.h.

◆ root_bbox_

template<typename Distance >

BoundingBox rtflann::KDTreeSingleIndex< Distance >::root_bbox_

private

Root bounding box

Definition at line 709 of file kdtree_single_index.h.

◆ root_node_

template<typename Distance >

NodePtr rtflann::KDTreeSingleIndex< Distance >::root_node_

private

Array of k-d trees used to find neighbours.

Definition at line 704 of file kdtree_single_index.h.

◆ vind_

template<typename Distance >

std::vector<int> rtflann::KDTreeSingleIndex< Distance >::vind_

private

Array of indices to vectors in the dataset.

Definition at line 697 of file kdtree_single_index.h.

The documentation for this class was generated from the following file:

kdtree_single_index.h

Classes

Public Types

Public Member Functions

Protected Member Functions

Private Types

Private Member Functions

Private Attributes

Additional Inherited Members

Detailed Description

template<typename Distance> class rtflann::KDTreeSingleIndex< Distance >

Member Typedef Documentation

◆ BaseClass

◆ BoundingBox

◆ Branch

◆ BranchSt

◆ DistanceType

◆ ElementType

◆ needs_kdtree_distance

◆ NodePtr

Constructor & Destructor Documentation

◆ KDTreeSingleIndex() [1/3]

◆ KDTreeSingleIndex() [2/3]

◆ KDTreeSingleIndex() [3/3]

◆ ~KDTreeSingleIndex()

Member Function Documentation

◆ addPoints()

◆ buildIndex() [1/2]

◆ buildIndex() [2/2]

◆ buildIndexImpl()

◆ clone()

◆ computeBoundingBox()

◆ computeInitialDistances()

◆ computeMinMax()

◆ copyTree()

◆ divideTree()

◆ findNeighbors()

◆ freeIndex()

◆ getType()

◆ loadIndex()

◆ middleSplit()

◆ middleSplit_()

◆ operator=()

◆ planeSplit()

◆ saveIndex()

◆ searchLevel()

◆ serialize()

◆ swap()

◆ usedMemory()

Member Data Documentation

◆ data_

◆ leaf_max_size_

◆ pool_

◆ reorder_

◆ root_bbox_

◆ root_node_

◆ vind_

template<typename Distance>
class rtflann::KDTreeSingleIndex< Distance >