Digital Image Correlation Engine  Version 1.0
A modular, high-performance, image correlation tool used to compute full-field displacements and strains from digital images
Classes | Public Member Functions | Public Attributes | List of all members
Point_Cloud_3D< T > Struct Template Reference

point clouds More...

#include <DICe_PointCloud.h>

Classes

struct  Point
 point struct More...
 

Public Member Functions

size_t kdtree_get_point_count () const
 Must return the number of data points.
 
kdtree_distance (const T *p1, const size_t idx_p2, size_t) const
 Returns the distance between the vector "p1[0:size-1]" and the data point with index "idx_p2" stored in the class:
 
kdtree_get_pt (const size_t idx, int dim) const
 
template<class BBOX >
bool kdtree_get_bbox (BBOX &) const
 

Public Attributes

std::vector< Pointpts
 vector of points
 

Detailed Description

template<typename T>
struct Point_Cloud_3D< T >

point clouds

Member Function Documentation

◆ kdtree_get_bbox()

template<typename T >
template<class BBOX >
bool Point_Cloud_3D< T >::kdtree_get_bbox ( BBOX &  ) const
inline

Optional bounding-box computation: return false to default to a standard bbox computation loop. Return true if the BBOX was already computed by the class and returned in "bb" so it can be avoided to redo it again. Look at bb.size() to find out the expected dimensionality (e.g. 2 or 3 for point clouds)

◆ kdtree_get_pt()

template<typename T >
T Point_Cloud_3D< T >::kdtree_get_pt ( const size_t  idx,
int  dim 
) const
inline

Returns the dim'th component of the idx'th point in the class: Since this is inlined and the "dim" argument is typically an immediate value, the "if/else's" are actually solved at compile time.