CCCoreLib::TrueKdTree Class Reference

Proper KD-tree implementation. More...

#include <TrueKdTree.h>

Collaboration diagram for CCCoreLib::TrueKdTree:

Classes
class	BaseNode
	Tree base node. More...
class	Leaf
	Tree leaf. More...
class	Node
	Tree node. More...

Public Types
using	LeafVector = std::vector< Leaf * >
	A vector of leaves.

Public Member Functions
	TrueKdTree (GenericIndexedCloudPersist *cloud)
	Default constructor.
	~TrueKdTree ()
	Destructor.
GenericIndexedCloudPersist *	associatedCloud () const
	Returns the associated cloud.
bool	build (double maxError, DistanceComputationTools::ERROR_MEASURES errorMeasure=DistanceComputationTools::RMS, unsigned minPointCountPerCell=3, unsigned maxPointCountPerCell=0, GenericProgressCallback *progressCb=nullptr)
	Builds KD-tree. More...
void	clear ()
	Clears structure.
double	getMaxError () const
	Returns max error threshold used for planarity-based split strategy.
DistanceComputationTools::ERROR_MEASURES	getMaxErrorType () const
	Returns max error estimator used for planarity-based split strategy.
bool	getLeaves (LeafVector &leaves) const
	Returns all leaf nodes.

Static Public Attributes
static const uint8_t	X_DIM = 0
static const uint8_t	Y_DIM = 1
static const uint8_t	Z_DIM = 2
static const uint8_t	NODE_TYPE = 0
static const uint8_t	LEAF_TYPE = 1

Protected Member Functions
BaseNode *	split (ReferenceCloud *subset)
	Recursive split process.

Protected Attributes
BaseNode *	m_root
	Root node.
GenericIndexedCloudPersist *	m_associatedCloud
	Associated cloud.
double	m_maxError
	Max error for planarity-based split strategy (see m_errorMeasure)
DistanceComputationTools::ERROR_MEASURES	m_errorMeasure
	Error measurement.
unsigned	m_minPointCountPerCell
	Min number of points per cell (speed-up) More...
unsigned	m_maxPointCountPerCell
	Max number of points per cell (speed-up) More...

Detailed Description

Proper KD-tree implementation.

Member Function Documentation

build()

bool TrueKdTree::build	(	double	maxError,
		DistanceComputationTools::ERROR_MEASURES	errorMeasure = DistanceComputationTools::RMS,
		unsigned	minPointCountPerCell = 3,
		unsigned	maxPointCountPerCell = 0,
		GenericProgressCallback *	progressCb = nullptr
	)

Builds KD-tree.

Parameters

maxError	maximum error per cell (relatively to the best LS plane fit)
errorMeasure	error measurement
minPointCountPerCell	minimum number of points per cell (can't be smaller than 3)
maxPointCountPerCell	maximum number of points per cell (speed-up - ignored if < 6)
progressCb	the client application can get some notification of the process progress through this callback mechanism (see GenericProgressCallback)

Member Data Documentation

m_maxPointCountPerCell

unsigned CCCoreLib::TrueKdTree::m_maxPointCountPerCell

protected

Max number of points per cell (speed-up)

Ignored if < 6

m_minPointCountPerCell

unsigned CCCoreLib::TrueKdTree::m_minPointCountPerCell

protected

Min number of points per cell (speed-up)

Can't be < 3

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The documentation for this class was generated from the following files:

• TrueKdTree.h
• TrueKdTree.cpp