nanoflann: nanoflann::KDTreeBaseClass< Derived, Distance, DatasetAdaptor, DIM, IndexType > Class Template Reference

nanoflann

C++ header-only ANN library

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nanoflann
KDTreeBaseClass

#include <nanoflann.hpp>

Classes
struct	Interval

struct	Node

Public Member Functions
void	freeIndex (Derived &obj)

Protected Types
typedef Distance::ElementType	ElementType

typedef Distance::DistanceType	DistanceType

typedef Node *	NodePtr

typedef array_or_vector_selector< DIM, Interval >::container_t	BoundingBox

typedef array_or_vector_selector< DIM, DistanceType >::container_t	distance_vector_t

Protected Member Functions
size_t	size (const Derived &obj) const

size_t	veclen (const Derived &obj)

size_t	usedMemory (Derived &obj)

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

NodePtr	divideTree (Derived &obj, const IndexType left, const IndexType right, BoundingBox &bbox)

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

void	planeSplit (Derived &obj, IndexType *ind, const IndexType count, int cutfeat, DistanceType &cutval, IndexType &lim1, IndexType &lim2)

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

Detailed Description

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

kd-tree base-class

Contains the member functions common to the classes KDTreeSingleIndexAdaptor and KDTreeSingleIndexDynamicAdaptor_.

Template Parameters

Derived	The name of the class which inherits this class.
DatasetAdaptor	The user-provided adaptor (see comments above).
Distance	The distance metric to use, these are all classes derived from nanoflann::Metric
DIM	Dimensionality of data points (e.g. 3 for 3D points)
IndexType	Will be typically size_t or int

Member Typedef Documentation

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

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

protected

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

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

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

protected

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

Member Function Documentation

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

NodePtr nanoflann::KDTreeBaseClass< Derived, Distance, DatasetAdaptor, DIM, IndexType >::divideTree	(	Derived &	obj,
		const IndexType	left,
		const IndexType	right,
		BoundingBox &	bbox
	)

inlineprotected

Create a tree node that subdivides the list of vecs from vind[first] to vind[last]. The routine is called recursively on each sublist.

Parameters

left	index of the first vector
right	index of the last vector

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

void nanoflann::KDTreeBaseClass< Derived, Distance, DatasetAdaptor, DIM, IndexType >::freeIndex ( Derived & obj )

inline

Frees the previously-built index. Automatically called within buildIndex().

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

void nanoflann::KDTreeBaseClass< Derived, Distance, DatasetAdaptor, DIM, IndexType >::planeSplit	(	Derived &	obj,
		IndexType *	ind,
		const IndexType	count,
		int	cutfeat,
		DistanceType &	cutval,
		IndexType &	lim1,
		IndexType &	lim2
	)

inlineprotected

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

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

size_t nanoflann::KDTreeBaseClass< Derived, Distance, DatasetAdaptor, DIM, IndexType >::size ( const Derived & obj ) const

inlineprotected

Returns number of points in dataset

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

size_t nanoflann::KDTreeBaseClass< Derived, Distance, DatasetAdaptor, DIM, IndexType >::usedMemory ( Derived & obj )

inlineprotected

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

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

size_t nanoflann::KDTreeBaseClass< Derived, Distance, DatasetAdaptor, DIM, IndexType >::veclen ( const Derived & obj )

inlineprotected

Returns the length of each point in the dataset

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

include/nanoflann.hpp