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

#include <DTK_nanoflann.hpp>

Public Member Functions
	KDTreeEigenMatrixAdaptor (const int dimensionality, 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 nChecks_IGNORED=10) const
Interface expected by KDTreeSingleIndexAdaptor
const self_t &	derived () const
self_t &	derived ()
size_t	kdtree_get_point_count () const
num_t	kdtree_distance (const num_t *p1, const size_t idx_p2, size_t size) const
num_t	kdtree_get_pt (const size_t idx, int dim) const
template<class BBOX >
bool	kdtree_get_bbox (BBOX &bb) const

Detailed Description

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

A simple 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(dimdim, 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.
IndexType	The type for indices in the KD-tree index (typically, size_t of int)

Definition at line 1642 of file DTK_nanoflann.hpp.

Constructor & Destructor Documentation

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

DataTransferKit::nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance, IndexType >::KDTreeEigenMatrixAdaptor ( const int  dimensionality, 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 1655 of file DTK_nanoflann.hpp.

Member Function Documentation

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

void DataTransferKit::nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance, IndexType >::query ( const num_t *  query_point, const size_t  num_closest, IndexType *  out_indices, num_t *  out_distances_sq, const int  nChecks_IGNORED = 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 1680 of file DTK_nanoflann.hpp.

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

• DTK_nanoflann.hpp