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rtflann::KDTreeSingleIndex< Distance > Class Template Reference

#include <kdtree_single_index.h>

Inheritance diagram for rtflann::KDTreeSingleIndex< Distance >:
Inheritance graph
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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)
 
BaseClassclone () 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)
 
KDTreeSingleIndexoperator= (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 ElementTypegetPoint (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< IntervalBoundingBox
 
typedef BranchStBranch
 
typedef BranchStruct< NodePtr, DistanceTypeBranchSt
 
typedef NodeNodePtr
 

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< ElementTypedata_
 
int leaf_max_size_
 
PooledAllocator pool_
 
bool reorder_
 
BoundingBox root_bbox_
 
NodePtr root_node_
 
std::vector< intvind_
 

Additional Inherited Members

- Protected Attributes inherited from rtflann::NNIndex< Distance >
ElementTypedata_ptr_
 
Distance distance_
 
std::vector< size_tids_
 
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
pointsMatrix 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
datasetthe 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:


rtabmap
Author(s): Mathieu Labbe
autogenerated on Thu Jul 25 2024 02:50:29