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

An L2-metric KD-tree adaptor for working with data directly stored in an Eigen Matrix, without duplicating the data storage. More...

#include <nanoflann.hpp>

Collaboration diagram for nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance, IndexType >:

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

Public Member Functions
	KDTreeEigenMatrixAdaptor (const int dimensionality, const MatrixType &mat, const int leaf_max_size=10)
	The kd-tree index for the user to call its methods as usual with any other FLANN index.
	~KDTreeEigenMatrixAdaptor ()
void	query (const num_t *query_point, const size_t num_closest, IndexType *out_indices, num_t *out_distances_sq, const int=10) const
	Query for the num_closest closest points to a given point (entered as query_point[0:dim-1]).
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

Public Attributes
index_t *	index
const MatrixType &	m_data_matrix

Detailed Description

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

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(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 1540 of file nanoflann.hpp.

Member Typedef Documentation

index_t

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

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

Definition at line 1544 of file nanoflann.hpp.

metric_t

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

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

Definition at line 1543 of file nanoflann.hpp.

num_t

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

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

Definition at line 1542 of file nanoflann.hpp.

self_t

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

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

Definition at line 1541 of file nanoflann.hpp.

Constructor & Destructor Documentation

KDTreeEigenMatrixAdaptor()

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

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

inline

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

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

Definition at line 1549 of file nanoflann.hpp.

      : m_data_matrix(mat) {
    const size_t dims = mat.cols();
    if (DIM > 0 && static_cast<int>(dims) != DIM)
      throw std::runtime_error(
          "Data set dimensionality does not match the 'DIM' template argument");
    index = new index_t(
        dims, *this /* adaptor */,
        nanoflann::KDTreeSingleIndexAdaptorParams(leaf_max_size, dims));
    index->buildIndex();
  }

References nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::buildIndex().

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~KDTreeEigenMatrixAdaptor()

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

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

inline

Definition at line 1566 of file nanoflann.hpp.

                              {
    delete index;
  }

Member Function Documentation

derived() [1/2]

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

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

inline

Definition at line 1592 of file nanoflann.hpp.

                     {
    return *this;
  }

derived() [2/2]

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

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

inline

Definition at line 1589 of file nanoflann.hpp.

                                 {
    return *this;
  }

kdtree_distance()

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

num_t nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance, IndexType >::kdtree_distance ( const num_t * p1, const size_t idx_p2, size_t size ) const

inline

Definition at line 1602 of file nanoflann.hpp.

                                                  {
    num_t s = 0;
    for (size_t i = 0; i < size; i++) {
      const num_t d = p1[i] - m_data_matrix.coeff(idx_p2, i);
      s += d * d;
    }
    return s;
  }

kdtree_get_bbox()

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

template<class BBOX >

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

inline

Definition at line 1621 of file nanoflann.hpp.

                                       {
    return false;
  }

kdtree_get_point_count()

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

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

inline

Definition at line 1597 of file nanoflann.hpp.

                                               {
    return m_data_matrix.rows();
  }

kdtree_get_pt()

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

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

inline

Definition at line 1613 of file nanoflann.hpp.

                                                              {
    return m_data_matrix.coeff(idx, dim);
  }

query()

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

void 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 = 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 1577 of file nanoflann.hpp.

                                           {
    nanoflann::KNNResultSet<typename MatrixType::Scalar, IndexType> resultSet(
        num_closest);
    resultSet.init(out_indices, out_distances_sq);
    index->findNeighbors(resultSet, query_point, nanoflann::SearchParams());
  }

References nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::findNeighbors(), and nanoflann::KNNResultSet< DistanceType, IndexType, CountType >::init().

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Member Data Documentation

index

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

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

Definition at line 1546 of file nanoflann.hpp.

m_data_matrix

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

const MatrixType& nanoflann::KDTreeEigenMatrixAdaptor< MatrixType, DIM, Distance, IndexType >::m_data_matrix

Definition at line 1570 of file nanoflann.hpp.

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

• src/particles/subgrid3DLegacyFramework/contactDetection/nanoflann.hpp