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 581 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	Node

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.

	~KDTreeSingleIndexAdaptor ()
	Standard destructor.

void	buildIndex ()
	Builds the index.

size_t	size () const
	Returns size of index.

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

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

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].

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].

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.

Public Attributes
Distance	distance

Protected Types
typedef Node *	NodePtr

typedef std::vector< Interval >	BoundingBox

typedef BranchStruct< NodePtr, DistanceType >	BranchSt

typedef BranchSt *	Branch

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

size_t	m_leaf_max_size

const DatasetAdaptor &	dataset
	The dataset used by this index.

const KDTreeSingleIndexAdaptorParams	index_params

size_t	m_size

int	dim
	Dimensionality of each data point.

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

BoundingBox	root_bbox

PooledAllocator	pool
	Pooled memory allocator.

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

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

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].

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.

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

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

void	saveIndex (FILE *stream)

void	loadIndex (FILE *stream)

Member Typedef Documentation

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

typedef std::vector<Interval> nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::BoundingBox

protected

Definition at line 643 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 670 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 669 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 585 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 584 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 635 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 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 694 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 712 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 719 of file nanoflann.hpp.

Referenced by mrpt::math::KDTreeCapable< CFeatureList >::rebuild_kdTree_2D(), mrpt::math::KDTreeCapable< CFeatureList >::rebuild_kdTree_3D(), mrpt::math::KDTreeCapable< CFeatureList >::rebuild_kdTree_Nd(), 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 857 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,
		std::vector< DistanceType > &	dists
	)		const

inlineprivate

Definition at line 1076 of file nanoflann.hpp.

References mrpt::math::distance().

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 940 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 827 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 890 of file nanoflann.hpp.

References nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::Node::child1, nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::Node::child2, nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::Node::lr, and nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::Node::sub.

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 766 of file nanoflann.hpp.

References nanoflann::KNNResultSet< DistanceType, IndexType, CountType >::dists, and nanoflann::SearchParams::eps.

Referenced by mrpt::math::KDTreeCapable< CFeatureList >::kdTreeClosestPoint2D(), mrpt::math::KDTreeCapable< CFeatureList >::kdTreeClosestPoint3D(), mrpt::math::KDTreeCapable< CFeatureList >::kdTreeNClosestPoint2D(), mrpt::math::KDTreeCapable< CFeatureList >::kdTreeNClosestPoint2DIdx(), mrpt::math::KDTreeCapable< CFeatureList >::kdTreeNClosestPoint3D(), mrpt::math::KDTreeCapable< CFeatureList >::kdTreeNClosestPoint3DIdx(), and mrpt::math::KDTreeCapable< CFeatureList >::kdTreeTwoClosestPoint2D().

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 815 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 781 of file nanoflann.hpp.

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

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 844 of file nanoflann.hpp.

References 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 )

inlineprivate

Definition at line 1159 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 951 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 996 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 1047 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 800 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 832 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 )

inlineprivate

Definition at line 1149 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,
		std::vector< DistanceType > &	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 1099 of file nanoflann.hpp.

References nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::Node::child1, nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::Node::child2, mrpt::math::distance(), nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::Node::lr, and nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::Node::sub.

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 729 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 746 of file nanoflann.hpp.

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 737 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 599 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 604 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 685 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 601 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 593 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 603 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 681 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 672 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 668 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 591 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 >