nanoflann.hpp File Reference

#include <vector>
#include <string>
#include <cassert>
#include <map>
#include <algorithm>
#include <stdexcept>
#include <limits>
#include <cstring>
#include <cstdio>
#include <cmath>

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Classes
class	nanoflann::KNNResultSet< DistanceType, IndexType, CountType >
class	nanoflann::RadiusResultSet< DistanceType, IndexType >
	A result-set class used when performing a radius based search. More...
struct	nanoflann::IndexDist_Sorter
	operator "<" for std::sort() More...
struct	nanoflann::L1_Adaptor< T, DataSource, _DistanceType >
	Manhattan distance functor (generic version, optimized for high-dimensionality data sets). More...
struct	nanoflann::L2_Adaptor< T, DataSource, _DistanceType >
	Squared Euclidean distance functor (generic version, optimized for high-dimensionality data sets). More...
struct	nanoflann::L2_Simple_Adaptor< T, DataSource, _DistanceType >
	Squared Euclidean distance functor (suitable for low-dimensionality datasets, like 2D or 3D point clouds) Corresponding distance traits: nanoflann::metric_L2_Simple. More...
struct	nanoflann::metric_L1
	Metaprogramming helper traits class for the L1 (Manhattan) metric. More...
struct	nanoflann::metric_L1::traits< T, DataSource >
struct	nanoflann::metric_L2
	Metaprogramming helper traits class for the L2 (Euclidean) metric. More...
struct	nanoflann::metric_L2::traits< T, DataSource >
struct	nanoflann::metric_L2_Simple
	Metaprogramming helper traits class for the L2_simple (Euclidean) metric. More...
struct	nanoflann::metric_L2_Simple::traits< T, DataSource >
struct	nanoflann::KDTreeSingleIndexAdaptorParams
	Parameters (see http://code.google.com/p/nanoflann/ for help choosing the parameters) More...
struct	nanoflann::SearchParams
	Search options for KDTreeSingleIndexAdaptor::findNeighbors() More...
class	nanoflann::PooledAllocator
class	nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >
	kd-tree index More...
struct	nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::Node
struct	nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::Interval
struct	nanoflann::KDTreeSingleIndexAdaptor< Distance, DatasetAdaptor, DIM, IndexType >::BranchStruct< T, DistanceType >
	This record represents a branch point when finding neighbors in the tree. More...
struct	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. More...

Namespaces
namespace	nanoflann

Macros
#define	NANOFLANN_VERSION   0x112
	Library version: 0xMmP (M=Major,m=minor,P=path)

Functions
template<typename T >
void	nanoflann::save_value (FILE *stream, const T &value, size_t count=1)
template<typename T >
void	nanoflann::save_value (FILE *stream, const std::vector< T > &value)
template<typename T >
void	nanoflann::load_value (FILE *stream, T &value, size_t count=1)
template<typename T >
void	nanoflann::load_value (FILE *stream, std::vector< T > &value)
template<typename T >
T	nanoflann::abs (T x)
template<>
int	nanoflann::abs< int > (int x)
template<>
float	nanoflann::abs< float > (float x)
template<>
double	nanoflann::abs< double > (double x)
template<>
long double	nanoflann::abs< long double > (long double x)
template<typename T >
T *	nanoflann::allocate (size_t count=1)
	Allocates (using C's malloc) a generic type T.

Variables
const size_t	nanoflann::WORDSIZE =16
	Pooled storage allocator.
const size_t	nanoflann::BLOCKSIZE =8192