rtflann::L2< T > Struct Template Reference

#include <dist.h>

Public Types
typedef T	ElementType
typedef bool	is_kdtree_distance
typedef Accumulator< T >::Type	ResultType

Public Member Functions
template<typename U , typename V >
ResultType	accum_dist (const U &a, const V &b, int) const
template<typename Iterator1 , typename Iterator2 >
ResultType	operator() (Iterator1 a, Iterator2 b, size_t size, ResultType worst_dist=-1) const

Detailed Description

template<class T>
struct rtflann::L2< T >

Squared Euclidean distance functor, optimized version

Definition at line 133 of file dist.h.

Member Typedef Documentation

template<class T>

typedef T rtflann::L2< T >::ElementType

Definition at line 137 of file dist.h.

template<class T>

typedef bool rtflann::L2< T >::is_kdtree_distance

Definition at line 135 of file dist.h.

template<class T>

typedef Accumulator<T>::Type rtflann::L2< T >::ResultType

Definition at line 138 of file dist.h.

Member Function Documentation

template<class T>

template<typename U , typename V >

ResultType rtflann::L2< T >::accum_dist ( const U &  a, const V &  b, int    ) const

inline

Partial euclidean distance, using just one dimension. This is used by the kd-tree when computing partial distances while traversing the tree.

Squared root is omitted for efficiency.

Definition at line 186 of file dist.h.

template<class T>

template<typename Iterator1 , typename Iterator2 >

ResultType rtflann::L2< T >::operator() ( Iterator1  a, Iterator2  b, size_t  size, ResultType  worst_dist = -1  ) const

inline

Compute the squared Euclidean distance between two vectors.

This is highly optimised, with loop unrolling, as it is one of the most expensive inner loops.

The computation of squared root at the end is omitted for efficiency.

Definition at line 150 of file dist.h.

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

• dist.h