nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance > Struct Template Reference

#include <nanoflann.hpp>

Public Types
typedef KDTreeSingleIndexAdaptor< metric_t, self_t, MatrixType::ColsAtCompileTime, IndexType >	index_t
typedef MatrixType::Index	IndexType
typedef Distance::template traits< num_t, self_t >::distance_t	metric_t
typedef MatrixType::Scalar	num_t
typedef KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance >	self_t

Public Member Functions
	KDTreeEigenMatrixAdaptor (const self_t &)=delete
	KDTreeEigenMatrixAdaptor (const size_t dimensionality, const std::reference_wrapper< const MatrixType > &mat, const int leaf_max_size=10)
	Constructor: takes a const ref to the matrix object with the data points. More...
void	query (const num_t *query_point, const size_t num_closest, IndexType *out_indices, num_t *out_distances_sq, const int=10) const
	~KDTreeEigenMatrixAdaptor ()
Interface expected by KDTreeSingleIndexAdaptor
const self_t &	derived () const
self_t &	derived ()
size_t	kdtree_get_point_count () const
num_t	kdtree_get_pt (const IndexType idx, size_t dim) const
template<class BBOX >
bool	kdtree_get_bbox (BBOX &) const

Public Attributes
index_t *	index
const std::reference_wrapper< const MatrixType >	m_data_matrix

Detailed Description

template<class MatrixType, int DIM = -1, class Distance = nanoflann::metric_L2>
struct nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance >

An L2-metric KD-tree adaptor for working with data directly stored in an Eigen Matrix, without duplicating the data storage. Each row in the matrix represents a point in the state space.

Example of usage:

 Eigen::Matrix<num_t,Dynamic,Dynamic>  mat;
 // Fill out "mat"...
 
 typedef KDTreeEigenMatrixAdaptor< Eigen::Matrix<num_t,Dynamic,Dynamic> >
my_kd_tree_t; const int max_leaf = 10; my_kd_tree_t   mat_index(mat, max_leaf
); mat_index.index->buildIndex(); mat_index.index->... 

Template Parameters

DIM	If set to >0, it specifies a compile-time fixed dimensionality for the points in the data set, allowing more compiler optimizations.
Distance	The distance metric to use: nanoflann::metric_L1, nanoflann::metric_L2, nanoflann::metric_L2_Simple, etc.

Definition at line 1953 of file nanoflann.hpp.

Member Typedef Documentation

index_t

template<class MatrixType , int DIM = -1, class Distance = nanoflann::metric_L2>

typedef KDTreeSingleIndexAdaptor<metric_t, self_t, MatrixType::ColsAtCompileTime, IndexType> nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance >::index_t

Definition at line 1961 of file nanoflann.hpp.

IndexType

template<class MatrixType , int DIM = -1, class Distance = nanoflann::metric_L2>

typedef MatrixType::Index nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance >::IndexType

Definition at line 1956 of file nanoflann.hpp.

metric_t

template<class MatrixType , int DIM = -1, class Distance = nanoflann::metric_L2>

typedef Distance::template traits<num_t, self_t>::distance_t nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance >::metric_t

Definition at line 1958 of file nanoflann.hpp.

num_t

template<class MatrixType , int DIM = -1, class Distance = nanoflann::metric_L2>

typedef MatrixType::Scalar nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance >::num_t

Definition at line 1955 of file nanoflann.hpp.

self_t

template<class MatrixType , int DIM = -1, class Distance = nanoflann::metric_L2>

typedef KDTreeEigenMatrixAdaptor<MatrixType, DIM, Distance> nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance >::self_t

Definition at line 1954 of file nanoflann.hpp.

Constructor & Destructor Documentation

KDTreeEigenMatrixAdaptor() [1/2]

template<class MatrixType , int DIM = -1, class Distance = nanoflann::metric_L2>

nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance >::KDTreeEigenMatrixAdaptor ( const size_t  dimensionality, const std::reference_wrapper< const MatrixType > &  mat, const int  leaf_max_size = 10  )

inline

Constructor: takes a const ref to the matrix object with the data points.

The kd-tree index for the user to call its methods as usual with any other FLANN index.

Definition at line 1967 of file nanoflann.hpp.

KDTreeEigenMatrixAdaptor() [2/2]

template<class MatrixType , int DIM = -1, class Distance = nanoflann::metric_L2>

nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance >::KDTreeEigenMatrixAdaptor ( const self_t &  )

delete

Deleted copy constructor

~KDTreeEigenMatrixAdaptor()

template<class MatrixType , int DIM = -1, class Distance = nanoflann::metric_L2>

nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance >::~KDTreeEigenMatrixAdaptor ( )

inline

Definition at line 1988 of file nanoflann.hpp.

Member Function Documentation

derived() [1/2]

template<class MatrixType , int DIM = -1, class Distance = nanoflann::metric_L2>

self_t& nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance >::derived ( )

inline

Definition at line 2010 of file nanoflann.hpp.

derived() [2/2]

template<class MatrixType , int DIM = -1, class Distance = nanoflann::metric_L2>

const self_t& nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance >::derived ( ) const

inline

Definition at line 2009 of file nanoflann.hpp.

kdtree_get_bbox()

template<class MatrixType , int DIM = -1, class Distance = nanoflann::metric_L2>

template<class BBOX >

bool nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance >::kdtree_get_bbox ( BBOX &  ) const

inline

Definition at line 2027 of file nanoflann.hpp.

kdtree_get_point_count()

template<class MatrixType , int DIM = -1, class Distance = nanoflann::metric_L2>

size_t nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance >::kdtree_get_point_count ( ) const

inline

Definition at line 2013 of file nanoflann.hpp.

kdtree_get_pt()

template<class MatrixType , int DIM = -1, class Distance = nanoflann::metric_L2>

num_t nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance >::kdtree_get_pt ( const IndexType  idx, size_t  dim  ) const

inline

Definition at line 2018 of file nanoflann.hpp.

query()

template<class MatrixType , int DIM = -1, class Distance = nanoflann::metric_L2>

void nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance >::query ( const num_t *  query_point, const size_t  num_closest, IndexType *  out_indices, num_t *  out_distances_sq, const int  = 10  ) const

inline

Query for the num_closest closest points to a given point (entered as query_point[0:dim-1]). Note that this is a short-cut method for index->findNeighbors(). The user can also call index->... methods as desired.

Note

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

Definition at line 1998 of file nanoflann.hpp.

Member Data Documentation

index

template<class MatrixType , int DIM = -1, class Distance = nanoflann::metric_L2>

index_t* nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance >::index

Definition at line 1963 of file nanoflann.hpp.

m_data_matrix

template<class MatrixType , int DIM = -1, class Distance = nanoflann::metric_L2>

const std::reference_wrapper<const MatrixType> nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance >::m_data_matrix

Definition at line 1990 of file nanoflann.hpp.

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

• nanoflann.hpp