#include <nanoflann.hpp>

Public Types
using	self_t

using	num_t = typename MatrixType::Scalar

using	IndexType = typename MatrixType::Index

using	metric_t

using	index_t

using	Offset = typename index_t::Offset

using	Size = typename index_t::Size

using	Dimension = typename index_t::Dimension

Public Member Functions
	KDTreeEigenMatrixAdaptor (const Dimension dimensionality, const std::reference_wrapper< const MatrixType > &mat, const int leaf_max_size=10, const unsigned int n_thread_build=1)
	Constructor: takes a const ref to the matrix object with the data points.

	KDTreeEigenMatrixAdaptor (const self_t &)=delete

	~KDTreeEigenMatrixAdaptor ()

void	query (const num_t query_point, const Size num_closest, IndexType out_indices, num_t *out_distances) const

Interface expected by KDTreeSingleIndexAdaptor
const self_t &	derived () const

self_t &	derived ()

Size	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

Data Fields
index_t *	index_

const std::reference_wrapper< const MatrixType >	m_data_matrix

Detailed Description

template<class MatrixType, int32_t DIM = -1, class Distance = nanoflann::metric_L2, bool row_major = true>
struct nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance, row_major >

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

Example of usage:

Eigen::Matrix<num_t,Eigen::Dynamic,Eigen::Dynamic>  mat;
 
// Fill out "mat"...
using my_kd_tree_t = nanoflann::KDTreeEigenMatrixAdaptor<
  Eigen::Matrix<num_t,Dynamic,Dynamic>>;
 
const int max_leaf = 10;
my_kd_tree_t mat_index(mat, max_leaf);
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.
row_major	If set to true the rows of the matrix are used as the points, if set to false the columns of the matrix are used as the points.

Definition at line 2629 of file nanoflann.hpp.

Member Typedef Documentation

◆ Dimension

template<class MatrixType, int32_t DIM = -1, class Distance = nanoflann::metric_L2, bool row_major = true>

using nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance, row_major >::Dimension = typename index_t::Dimension

Definition at line 2649 of file nanoflann.hpp.

◆ index_t

template<class MatrixType, int32_t DIM = -1, class Distance = nanoflann::metric_L2, bool row_major = true>

using nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance, row_major >::index_t

Initial value:

 KDTreeSingleIndexAdaptor<
        metric_t, self_t,
        row_major ? MatrixType::ColsAtCompileTime
                  : MatrixType::RowsAtCompileTime,
        IndexType>

Definition at line 2638 of file nanoflann.hpp.

◆ IndexType

template<class MatrixType, int32_t DIM = -1, class Distance = nanoflann::metric_L2, bool row_major = true>

using nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance, row_major >::IndexType = typename MatrixType::Index

Definition at line 2634 of file nanoflann.hpp.

◆ metric_t

template<class MatrixType, int32_t DIM = -1, class Distance = nanoflann::metric_L2, bool row_major = true>

using nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance, row_major >::metric_t

Initial value:

typename Distance::template traits<

num_t, self_t, IndexType>::distance_t

nanoflann::KDTreeEigenMatrixAdaptor::num_t

typename MatrixType::Scalar num_t

Definition nanoflann.hpp:2633

Definition at line 2635 of file nanoflann.hpp.

◆ num_t

template<class MatrixType, int32_t DIM = -1, class Distance = nanoflann::metric_L2, bool row_major = true>

using nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance, row_major >::num_t = typename MatrixType::Scalar

Definition at line 2633 of file nanoflann.hpp.

◆ Offset

template<class MatrixType, int32_t DIM = -1, class Distance = nanoflann::metric_L2, bool row_major = true>

using nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance, row_major >::Offset = typename index_t::Offset

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

Definition at line 2647 of file nanoflann.hpp.

◆ self_t

template<class MatrixType, int32_t DIM = -1, class Distance = nanoflann::metric_L2, bool row_major = true>

using nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance, row_major >::self_t

Initial value:

KDTreeEigenMatrixAdaptor<MatrixType, DIM, Distance, row_major>

nanoflann::KDTreeEigenMatrixAdaptor::KDTreeEigenMatrixAdaptor

KDTreeEigenMatrixAdaptor(const Dimension dimensionality, const std::reference_wrapper< const MatrixType > &mat, const int leaf_max_size=10, const unsigned int n_thread_build=1)

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

Definition nanoflann.hpp:2652

Definition at line 2631 of file nanoflann.hpp.

◆ Size

template<class MatrixType, int32_t DIM = -1, class Distance = nanoflann::metric_L2, bool row_major = true>

using nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance, row_major >::Size = typename index_t::Size

Definition at line 2648 of file nanoflann.hpp.

Constructor & Destructor Documentation

◆ KDTreeEigenMatrixAdaptor() [1/2]

template<class MatrixType, int32_t DIM = -1, class Distance = nanoflann::metric_L2, bool row_major = true>

nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance, row_major >::KDTreeEigenMatrixAdaptor	(	const Dimension	dimensionality,
		const std::reference_wrapper< const MatrixType > &	mat,
		const int	leaf_max_size = 10,
		const unsigned int	n_thread_build = 1 )

inlineexplicit

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

Definition at line 2652 of file nanoflann.hpp.

◆ KDTreeEigenMatrixAdaptor() [2/2]

template<class MatrixType, int32_t DIM = -1, class Distance = nanoflann::metric_L2, bool row_major = true>

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

delete

Deleted copy constructor

◆ ~KDTreeEigenMatrixAdaptor()

template<class MatrixType, int32_t DIM = -1, class Distance = nanoflann::metric_L2, bool row_major = true>

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

inline

Definition at line 2678 of file nanoflann.hpp.

Member Function Documentation

◆ derived() [1/2]

template<class MatrixType, int32_t DIM = -1, class Distance = nanoflann::metric_L2, bool row_major = true>

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

inline

Definition at line 2703 of file nanoflann.hpp.

◆ derived() [2/2]

template<class MatrixType, int32_t DIM = -1, class Distance = nanoflann::metric_L2, bool row_major = true>

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

inline

Definition at line 2702 of file nanoflann.hpp.

◆ kdtree_get_bbox()

template<class MatrixType, int32_t DIM = -1, class Distance = nanoflann::metric_L2, bool row_major = true>

template<class BBOX>

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

inline

Definition at line 2729 of file nanoflann.hpp.

◆ kdtree_get_point_count()

template<class MatrixType, int32_t DIM = -1, class Distance = nanoflann::metric_L2, bool row_major = true>

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

inline

Definition at line 2706 of file nanoflann.hpp.

◆ kdtree_get_pt()

template<class MatrixType, int32_t DIM = -1, class Distance = nanoflann::metric_L2, bool row_major = true>

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

inline

Definition at line 2715 of file nanoflann.hpp.

◆ query()

template<class MatrixType, int32_t DIM = -1, class Distance = nanoflann::metric_L2, bool row_major = true>

void nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance, row_major >::query	(	const num_t *	query_point,
		const Size	num_closest,
		IndexType *	out_indices,
		num_t *	out_distances ) 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: If L2 norms are used, all returned distances are actually squared distances.

Definition at line 2690 of file nanoflann.hpp.

Field Documentation

◆ index_

template<class MatrixType, int32_t DIM = -1, class Distance = nanoflann::metric_L2, bool row_major = true>

index_t* nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance, row_major >::index_

Definition at line 2644 of file nanoflann.hpp.

◆ m_data_matrix

template<class MatrixType, int32_t DIM = -1, class Distance = nanoflann::metric_L2, bool row_major = true>

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

Definition at line 2680 of file nanoflann.hpp.

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

nanoflann.hpp

Public Types

Public Member Functions

Data Fields

Detailed Description

Member Typedef Documentation

◆ Dimension

◆ index_t

◆ IndexType

◆ metric_t

◆ num_t

◆ Offset

◆ self_t

◆ Size

Constructor & Destructor Documentation

◆ KDTreeEigenMatrixAdaptor() [1/2]

◆ KDTreeEigenMatrixAdaptor() [2/2]

◆ ~KDTreeEigenMatrixAdaptor()

Member Function Documentation

◆ derived() [1/2]

◆ derived() [2/2]

◆ kdtree_get_bbox()

◆ kdtree_get_point_count()

◆ kdtree_get_pt()

◆ query()

Field Documentation

◆ index_

◆ m_data_matrix