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A Modern Library for 3D Data Processing
flann::L2< T > Struct Template Reference

#include <dist.h>

Public Types

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

Public Member Functions

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

Detailed Description

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

Squared Euclidean distance functor, optimized version

Definition at line 133 of file dist.h.

Member Typedef Documentation

◆ ElementType

template<class T >
typedef T flann::L2< T >::ElementType

Definition at line 137 of file dist.h.

◆ is_kdtree_distance

template<class T >
typedef bool flann::L2< T >::is_kdtree_distance

Definition at line 135 of file dist.h.

◆ ResultType

template<class T >
typedef Accumulator<T>::Type flann::L2< T >::ResultType

Definition at line 138 of file dist.h.

Member Function Documentation

◆ accum_dist()

template<class T >
template<typename U , typename V >
ResultType flann::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.

◆ operator()()

template<class T >
template<typename Iterator1 , typename Iterator2 >
ResultType flann::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.

References result, and size.


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