Detailed Description

template<typename Distance, class DatasetAdaptor, int DIM = -1, typename IndexType = size_t>
class nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >

kd-tree index

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

The class "DatasetAdaptor" must provide the following interface (can be non-virtual, inlined methods):

// Must return the number of data points
inline size_t kdtree_get_point_count() const { ... }
// Must return the Euclidean (L2) distance between the vector "p1[0:size-1]" and the data point with index "idx_p2" stored in the class:
inline DistanceType kdtree_distance(const T *p1, const size_t idx_p2,size_t size) const { ... }
// Must return the dim'th component of the idx'th point in the class:
inline T kdtree_get_pt(const size_t idx, int dim) const { ... }
// Optional bounding-box computation: return false to default to a standard bbox computation loop.
//   Return true if the BBOX was already computed by the class and returned in "bb" so it can be avoided to redo it again.
//   Look at bb.size() to find out the expected dimensionality (e.g. 2 or 3 for point clouds)
template <class BBOX>
bool kdtree_get_bbox(BBOX &bb) const
{
   bb[0].low = ...; bb[0].high = ...;  // 0th dimension limits
   bb[1].low = ...; bb[1].high = ...;  // 1st dimension limits
   ...
   return true;
}

Template Parameters

IndexType Will be typically size_t or int

Definition at line 739 of file nanoflann.hpp.

#include <mrpt/otherlibs/nanoflann/nanoflann.hpp>

Classes
struct	BranchStruct
	This record represents a branch point when finding neighbors in the tree. More...

struct	Interval

struct	LR

struct	Node

struct	Sub

Public Types
typedef Distance::ElementType	ElementType

typedef Distance::DistanceType	DistanceType

Public Member Functions
	KDTreeSingleIndexAdaptor (const int dimensionality, const DatasetAdaptor &inputData, const KDTreeSingleIndexAdaptorParams &params=KDTreeSingleIndexAdaptorParams())
	KDTree constructor. More...

	~KDTreeSingleIndexAdaptor ()
	Standard destructor. More...

void	freeIndex ()
	Frees the previously-built index. More...

void	buildIndex ()
	Builds the index. More...

size_t	size () const
	Returns size of index. More...

size_t	veclen () const
	Returns the length of an index feature. More...

size_t	usedMemory () const
	Computes the inde memory usage Returns: memory used by the index. More...

void	saveIndex (FILE *stream)
	Stores the index in a binary file. More...

void	loadIndex (FILE *stream)
	Loads a previous index from a binary file. More...

Query methods
template<typename RESULTSET >
void	findNeighbors (RESULTSET &result, const ElementType *vec, const SearchParams &searchParams) const
	Find set of nearest neighbors to vec[0:dim-1]. More...

void	knnSearch (const ElementType query_point, const size_t num_closest, IndexType out_indices, DistanceType *out_distances_sq, const int nChecks_IGNORED=10) const
	Find the "num_closest" nearest neighbors to the query_point[0:dim-1]. More...

size_t	radiusSearch (const ElementType *query_point, const DistanceType radius, std::vector< std::pair< IndexType, DistanceType > > &IndicesDists, const SearchParams &searchParams) const
	Find all the neighbors to query_point[0:dim-1] within a maximum radius. More...

Public Attributes
Distance	distance

Protected Types
typedef Node *	NodePtr

typedef array_or_vector_selector< DIM, Interval >::container_t	BoundingBox
	Define "BoundingBox" as a fixed-size or variable-size container depending on "DIM". More...

typedef array_or_vector_selector< DIM, DistanceType >::container_t	distance_vector_t
	Define "distance_vector_t" as a fixed-size or variable-size container depending on "DIM". More...

typedef BranchStruct< NodePtr, DistanceType >	BranchSt

typedef BranchSt *	Branch

Protected Attributes
std::vector< IndexType >	vind
	Array of indices to vectors in the dataset. More...

size_t	m_leaf_max_size

const DatasetAdaptor &	dataset
	The dataset used by this index. More...

const KDTreeSingleIndexAdaptorParams	index_params

size_t	m_size

int	dim
	Dimensionality of each data point. More...

NodePtr	root_node
	Array of k-d trees used to find neighbours. More...

BoundingBox	root_bbox

PooledAllocator	pool
	Pooled memory allocator. More...

Private Member Functions
	KDTreeSingleIndexAdaptor (const KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType > &)
	Hidden copy constructor, to disallow copying indices (Not implemented) More...

void	init_vind ()
	Make sure the auxiliary list vind has the same size than the current dataset, and re-generate if size has changed. More...

ElementType	dataset_get (size_t idx, int component) const
	Helper accessor to the dataset points: More...

void	save_tree (FILE *stream, NodePtr tree)

void	load_tree (FILE *stream, NodePtr &tree)

void	computeBoundingBox (BoundingBox &bbox)

NodePtr	divideTree (const IndexType left, const IndexType right, BoundingBox &bbox)
	Create a tree node that subdivides the list of vecs from vind[first] to vind[last]. More...

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

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

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

void	planeSplit (IndexType *ind, const IndexType count, int cutfeat, DistanceType cutval, IndexType &lim1, IndexType &lim2)
	Subdivide the list of points by a plane perpendicular on axe corresponding to the 'cutfeat' dimension at 'cutval' position. More...

DistanceType	computeInitialDistances (const ElementType *vec, distance_vector_t &dists) const

template<class RESULTSET >
void	searchLevel (RESULTSET &result_set, const ElementType *vec, const NodePtr node, DistanceType mindistsq, distance_vector_t &dists, const float epsError) const
	Performs an exact search in the tree starting from a node. More...

Member Typedef Documentation

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

typedef array_or_vector_selector<DIM,Interval>::container_t nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::BoundingBox

protected

Define "BoundingBox" as a fixed-size or variable-size container depending on "DIM".

Definition at line 807 of file nanoflann.hpp.

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

typedef BranchSt* nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::Branch

protected

Definition at line 836 of file nanoflann.hpp.

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

typedef BranchStruct<NodePtr, DistanceType> nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::BranchSt

protected

Definition at line 835 of file nanoflann.hpp.

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

typedef array_or_vector_selector<DIM,DistanceType>::container_t nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::distance_vector_t

protected

Define "distance_vector_t" as a fixed-size or variable-size container depending on "DIM".

Definition at line 810 of file nanoflann.hpp.

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

typedef Distance::DistanceType nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::DistanceType

Definition at line 746 of file nanoflann.hpp.

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

typedef Distance::ElementType nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::ElementType

Definition at line 745 of file nanoflann.hpp.

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

typedef Node* nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::NodePtr

protected

Definition at line 798 of file nanoflann.hpp.

Constructor & Destructor Documentation

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::KDTreeSingleIndexAdaptor ( const KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType > & )

private

Hidden copy constructor, to disallow copying indices (Not implemented)

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::KDTreeSingleIndexAdaptor	(	const int	dimensionality,
		const DatasetAdaptor &	inputData,
		const KDTreeSingleIndexAdaptorParams &	params = `KDTreeSingleIndexAdaptorParams()`
	)

inline

KDTree constructor.

Params: inputData = dataset with the input features params = parameters passed to the kdtree algorithm (see http://code.google.com/p/nanoflann/ for help choosing the parameters)

Definition at line 860 of file nanoflann.hpp.

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::~KDTreeSingleIndexAdaptor ( )

inline

Standard destructor.

Definition at line 878 of file nanoflann.hpp.

Member Function Documentation

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

void nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::buildIndex ( )

inline

Builds the index.

Definition at line 892 of file nanoflann.hpp.

Referenced by nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance, IndexType >::KDTreeEigenMatrixAdaptor(), mrpt::vision::TSIFTDescriptorsKDTreeIndex< distance_t, metric_t >::regenerate_kdtreee(), and mrpt::vision::TSURFDescriptorsKDTreeIndex< distance_t, metric_t >::regenerate_kdtreee().

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

void nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::computeBoundingBox ( BoundingBox & bbox )

inlineprivate

Definition at line 1033 of file nanoflann.hpp.

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

DistanceType nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::computeInitialDistances	(	const ElementType *	vec,
		distance_vector_t &	dists
	)		const

inlineprivate

Definition at line 1253 of file nanoflann.hpp.

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

void nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::computeMinMax	(	IndexType *	ind,
		IndexType	count,
		int	element,
		ElementType &	min_elem,
		ElementType &	max_elem
	)

inlineprivate

Definition at line 1117 of file nanoflann.hpp.

References nanoflann::KNNResultSet< DistanceType, IndexType, CountType >::count.

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

ElementType nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::dataset_get	(	size_t	idx,
		int	component
	)		const

inlineprivate

Helper accessor to the dataset points:

Definition at line 1003 of file nanoflann.hpp.

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

NodePtr nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::divideTree	(	const IndexType	left,
		const IndexType	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 1067 of file nanoflann.hpp.

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

template<typename RESULTSET >

void nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::findNeighbors	(	RESULTSET &	result,
		const ElementType *	vec,
		const SearchParams &	searchParams
	)		const

inline

Find set of nearest neighbors to vec[0:dim-1].

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

Template Parameters

RESULTSET Should be any ResultSet<DistanceType>

See also: knnSearch, radiusSearch

Definition at line 941 of file nanoflann.hpp.

References nanoflann::CArray< T, N >::assign(), nanoflann::KNNResultSet< DistanceType, IndexType, CountType >::dists, and nanoflann::SearchParams::eps.

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

void nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::freeIndex ( )

inline

Frees the previously-built index.

Automatically called within buildIndex().

Definition at line 883 of file nanoflann.hpp.

References nanoflann::PooledAllocator::free_all().

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

void nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::init_vind ( )

inlineprivate

Make sure the auxiliary list vind has the same size than the current dataset, and re-generate if size has changed.

Definition at line 994 of file nanoflann.hpp.

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

void nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::knnSearch	(	const ElementType *	query_point,
		const size_t	num_closest,
		IndexType *	out_indices,
		DistanceType *	out_distances_sq,
		const int	nChecks_IGNORED = `10`
	)		const

inline

Find the "num_closest" nearest neighbors to the query_point[0:dim-1].

Their indices are stored inside the result object.

See also: radiusSearch, findNeighbors

Note: nChecks_IGNORED is ignored but kept for compatibility with the original FLANN interface.

Definition at line 959 of file nanoflann.hpp.

References nanoflann::KNNResultSet< DistanceType, IndexType, CountType >::init(), and MRPT_UNUSED_PARAM.

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

void nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::load_tree	(	FILE *	stream,
		NodePtr &	tree
	)

inlineprivate

Definition at line 1020 of file nanoflann.hpp.

References nanoflann::PooledAllocator::allocate(), nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::Node::child1, nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::Node::child2, and nanoflann::load_value().

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

void nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::loadIndex ( FILE * stream )

inline

Loads a previous index from a binary file.

IMPORTANT NOTE: The set of data points is NOT stored in the file, so the index object must be constructed associated to the same source of data points used while building the index. See the example: examples/saveload_example.cpp

See also: loadIndex

Definition at line 1345 of file nanoflann.hpp.

References nanoflann::load_value().

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

void nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::middleSplit	(	IndexType *	ind,
		IndexType	count,
		IndexType &	index,
		int &	cutfeat,
		DistanceType &	cutval,
		const BoundingBox &	bbox
	)

inlineprivate

Definition at line 1128 of file nanoflann.hpp.

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

void nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::middleSplit_	(	IndexType *	ind,
		IndexType	count,
		IndexType &	index,
		int &	cutfeat,
		DistanceType &	cutval,
		const BoundingBox &	bbox
	)

inlineprivate

Definition at line 1173 of file nanoflann.hpp.

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

void nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::planeSplit	(	IndexType *	ind,
		const IndexType	count,
		int	cutfeat,
		DistanceType	cutval,
		IndexType &	lim1,
		IndexType &	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 1224 of file nanoflann.hpp.

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

size_t nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::radiusSearch	(	const ElementType *	query_point,
		const DistanceType	radius,
		std::vector< std::pair< IndexType, DistanceType > > &	IndicesDists,
		const SearchParams &	searchParams
	)		const

inline

Find all the neighbors to query_point[0:dim-1] within a maximum radius.

The output is given as a vector of pairs, of which the first element is a point index and the second the corresponding distance. Previous contents of IndicesDists are cleared.

If searchParams.sorted==true, the output list is sorted by ascending distances.

For a better performance, it is advisable to do a .reserve() on the vector if you have any wild guess about the number of expected matches.

See also: knnSearch, findNeighbors

Returns: The number of points within the given radius (i.e. indices.size() or dists.size() )

Definition at line 979 of file nanoflann.hpp.

References nanoflann::RadiusResultSet< DistanceType, IndexType >::size(), and nanoflann::SearchParams::sorted.

Referenced by mrpt::math::KDTreeCapable< CFeatureList >::kdTreeRadiusSearch2D(), and mrpt::math::KDTreeCapable< CFeatureList >::kdTreeRadiusSearch3D().

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

void nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::save_tree	(	FILE *	stream,
		NodePtr	tree
	)

inlineprivate

Definition at line 1008 of file nanoflann.hpp.

References nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::Node::child1, nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::Node::child2, and nanoflann::save_value().

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

void nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::saveIndex ( FILE * stream )

inline

Stores the index in a binary file.

IMPORTANT NOTE: The set of data points is NOT stored in the file, so when loading the index object it must be constructed associated to the same source of data points used while building it. See the example: examples/saveload_example.cpp

See also: loadIndex

Definition at line 1331 of file nanoflann.hpp.

References nanoflann::save_value().

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

template<class RESULTSET >

void nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::searchLevel	(	RESULTSET &	result_set,
		const ElementType *	vec,
		const NodePtr	node,
		DistanceType	mindistsq,
		distance_vector_t &	dists,
		const float	epsError
	)		const

inlineprivate

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

Template Parameters

RESULTSET Should be any ResultSet<DistanceType>

Definition at line 1277 of file nanoflann.hpp.

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

size_t nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::size ( ) const

inline

Returns size of index.

Definition at line 904 of file nanoflann.hpp.

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

size_t nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::usedMemory ( ) const

inline

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

Definition at line 921 of file nanoflann.hpp.

References nanoflann::PooledAllocator::usedMemory, and nanoflann::PooledAllocator::wastedMemory.

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

size_t nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::veclen ( ) const

inline

Returns the length of an index feature.

Definition at line 912 of file nanoflann.hpp.

Member Data Documentation

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

const DatasetAdaptor& nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::dataset

protected

The dataset used by this index.

The source of our data

Definition at line 760 of file nanoflann.hpp.

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

int nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::dim

protected

Dimensionality of each data point.

Definition at line 765 of file nanoflann.hpp.

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

Distance nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::distance

Definition at line 851 of file nanoflann.hpp.

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

const KDTreeSingleIndexAdaptorParams nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::index_params

protected

Definition at line 762 of file nanoflann.hpp.

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

size_t nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::m_leaf_max_size

protected

Definition at line 754 of file nanoflann.hpp.

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

size_t nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::m_size

protected

Definition at line 764 of file nanoflann.hpp.

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

PooledAllocator nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::pool

protected

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 847 of file nanoflann.hpp.

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

BoundingBox nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::root_bbox

protected

Definition at line 838 of file nanoflann.hpp.

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

NodePtr nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::root_node

protected

Array of k-d trees used to find neighbours.

Definition at line 834 of file nanoflann.hpp.

template<typename Distance , class DatasetAdaptor , int DIM = -1, typename IndexType = size_t>

std::vector<IndexType> nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::vind

protected

Array of indices to vectors in the dataset.

Definition at line 752 of file nanoflann.hpp.

Detailed Description

template<typename Distance, class DatasetAdaptor, int DIM = -1, typename IndexType = size_t> class nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >

Classes

Public Types

Public Member Functions

Public Attributes

Protected Types

Protected Attributes

Private Member Functions

Member Typedef Documentation

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation

template<typename Distance, class DatasetAdaptor, int DIM = -1, typename IndexType = size_t>
class nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >