#include <KdTree.hpp>

Public Types
using	iterator = typename PointDataType::iterator

enum	Method : char { Method::MIDPOINT, Method::MEDIAN, Method::GEOMETRIC_MEAN }

using	PointDataType = NodeDataType

using	PointGetter = typename PointDataType::PointGetter

using	PointListType = typename NodeDataType::PointListType

using	PointType = typename PointDataType::PointType

using	QualityEvaluator = TQualityEvaluator

enum	SearchCriteria : char { SearchCriteria::FIND_FIRST, SearchCriteria::FIND_BEST }

using	SplitAxisType = typename NodeType::SplitAxisType

Public Member Functions
std::pair< NodeDataType , NodeDataType >	doSplit (NodeType *node, SplitAxisType &splitAxis, PREC &splitPosition)

std::string	getStatisticsString ()

void	init (const std::initializer_list< Method > &m, unsigned int allowSplitAboveNPoints=100, PREC minExtent=0.0, SearchCriteria searchCriteria=SearchCriteria::FIND_BEST, const QualityEvaluator &qualityEval=QualityEvaluator(), PREC minSplitRatio=0.0, PREC minPointRatio=0.0, PREC minExtentRatio=0.0)

void	resetStatistics ()

	SplitHeuristicPointData ()

Private Member Functions
bool	checkPosition (AABB< Dimension > &aabb)

PREC	computeExtentRatio (AABB< Dimension > &aabb)

PREC	computePointRatio (NodeDataType *data)

bool	computeSplitPosition (NodeType *node, unsigned int tries=1)

PREC	computeSplitRatio (AABB< Dimension > &aabb)

void	computeStatistics ()

void	updateSolution ()

Private Attributes
std::size_t	m_allowSplitAboveNPoints = 100

PREC	m_avgExtentRatio = 0

PREC	m_avgPointRatio = 0

PREC	m_avgSplitRatio = 0

PREC	m_bestExtentRatio = 0

Method	m_bestMethod

PREC	m_bestPointRatio = 0

PREC	m_bestQuality = std::numeric_limits<PREC>::lowest()

SplitAxisType	m_bestSplitAxis

PREC	m_bestSplitPosition = 0.0

PREC	m_bestSplitRatio = 0

iterator	m_bestSplitRightIt

ArrayStat< Dimension >	m_extent

PREC	m_extentRatio = 0
	minimal ratio of min/max extent of the left and right splitted box, in range (0,1] ; More...

bool	m_found = false

Method	m_method

std::vector< Method >	m_methods

PREC	m_minExtent = 0.0

PREC	m_minExtentRatio = 0.0

PREC	m_minPointRatio = 0.0

PREC	m_minSplitRatio = 0.0

PREC	m_pointRatio = 0
	ratio of points in left and right splittet box, in range [0,0.5] More...

PREC	m_quality = 0.0

QualityEvaluator	m_qualityEval

SearchCriteria	m_searchCriteria

std::vector< SplitAxisType >	m_splitAxes

SplitAxisType	m_splitAxis

unsigned int	m_splitCalls = 0

PREC	m_splitPosition = 0.0

PREC	m_splitRatio = 0
	ratio of the splitting plane in range (0,0.5) More...

iterator	m_splitRightIt

unsigned int	m_splits = 0

unsigned int	m_tries = 0

bool	m_wasLastTry = false
	Flag which tells if the best values have just been updated when we finished the opt. loop. More...

Detailed Description

template<typename TQualityEvaluator, typename Traits>
class ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >

Definition at line 297 of file KdTree.hpp.

Member Typedef Documentation

template<typename TQualityEvaluator , typename Traits >

using ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::iterator = typename PointDataType::iterator

Definition at line 305 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

using ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::PointDataType = NodeDataType

Definition at line 302 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

using ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::PointGetter = typename PointDataType::PointGetter

Definition at line 306 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

using ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::PointListType = typename NodeDataType::PointListType

Definition at line 303 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

using ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::PointType = typename PointDataType::PointType

Definition at line 304 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

using ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::QualityEvaluator = TQualityEvaluator

Definition at line 316 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

using ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::SplitAxisType = typename NodeType::SplitAxisType

Definition at line 318 of file KdTree.hpp.

Member Enumeration Documentation

template<typename TQualityEvaluator , typename Traits >

enum ApproxMVBB::KdTree::SplitHeuristicPointData::Method : char

strong

Enumerator
MIDPOINT
MEDIAN
GEOMETRIC_MEAN

Definition at line 308 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

enum ApproxMVBB::KdTree::SplitHeuristicPointData::SearchCriteria : char

strong

Search Criterias how to find the best split axis which fullfills the constraints, minExtent etc. FIND_BEST has not been implemented so far, because we shuffle the point array constantly while searching!

Enumerator
FIND_FIRST
FIND_BEST

Definition at line 314 of file KdTree.hpp.

Constructor & Destructor Documentation

template<typename TQualityEvaluator , typename Traits >

ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::SplitHeuristicPointData ( )

inline

Definition at line 321 of file KdTree.hpp.

Member Function Documentation

template<typename TQualityEvaluator , typename Traits >

bool ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::checkPosition ( AABB< Dimension > & aabb )

inlineprivate

Definition at line 592 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

PREC ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::computeExtentRatio ( AABB< Dimension > & aabb )

inlineprivate

Definition at line 640 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

PREC ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::computePointRatio ( NodeDataType * data )

inlineprivate

Definition at line 622 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

bool ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::computeSplitPosition	(	NodeType *	node,
		unsigned int	tries = `1`
	)

inlineprivate

Compute the split position and maybe the splitAxis

Definition at line 504 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

PREC ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::computeSplitRatio ( AABB< Dimension > & aabb )

inlineprivate

Definition at line 633 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

void ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::computeStatistics ( )

inlineprivate

Definition at line 660 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

std::pair<NodeDataType , NodeDataType > ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::doSplit	(	NodeType *	node,
		SplitAxisType &	splitAxis,
		PREC &	splitPosition
	)

inline

Compute the split with the set heuristic and return the two new node data types if a split happened otherwise (nullptr)

Definition at line 385 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

std::string ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::getStatisticsString ( )

inline

Definition at line 371 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

void ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::init	(	const std::initializer_list< Method > &	m,
		unsigned int	allowSplitAboveNPoints = `100`,
		PREC	minExtent = `0.0`,
		SearchCriteria	searchCriteria = `SearchCriteria::FIND_BEST`,
		const QualityEvaluator &	qualityEval = `QualityEvaluator()`,
		PREC	minSplitRatio = `0.0`,
		PREC	minPointRatio = `0.0`,
		PREC	minExtentRatio = `0.0`
	)

inline

Definition at line 328 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

void ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::resetStatistics ( )

inline

Definition at line 361 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

void ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::updateSolution ( )

inlineprivate

Definition at line 605 of file KdTree.hpp.

Member Data Documentation

template<typename TQualityEvaluator , typename Traits >

std::size_t ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_allowSplitAboveNPoints = 100

private

Definition at line 712 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

PREC ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_avgExtentRatio = 0

private

Definition at line 673 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

PREC ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_avgPointRatio = 0

private

Definition at line 672 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

PREC ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_avgSplitRatio = 0

private

Definition at line 671 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

PREC ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_bestExtentRatio = 0

private

Definition at line 702 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

Method ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_bestMethod

private

Definition at line 703 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

PREC ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_bestPointRatio = 0

private

Definition at line 702 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

PREC ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_bestQuality = std::numeric_limits<PREC>::lowest()

private

Definition at line 701 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

SplitAxisType ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_bestSplitAxis

private

Definition at line 705 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

PREC ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_bestSplitPosition = 0.0

private

Definition at line 704 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

PREC ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_bestSplitRatio = 0

private

Definition at line 702 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

iterator ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_bestSplitRightIt

private

Definition at line 700 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

ArrayStat<Dimension> ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_extent

private

Temp. values

Definition at line 679 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

PREC ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_extentRatio = 0

private

minimal ratio of min/max extent of the left and right splitted box, in range (0,1] ;

Definition at line 685 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

bool ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_found = false

private

Definition at line 699 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

Method ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_method

private

Definition at line 692 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

std::vector<Method> ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_methods

private

Definition at line 709 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

PREC ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_minExtent = 0.0

private

Definition at line 713 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

PREC ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_minExtentRatio = 0.0

private

Definition at line 690 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

PREC ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_minPointRatio = 0.0

private

Definition at line 689 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

PREC ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_minSplitRatio = 0.0

private

Min values to allow a split

Definition at line 688 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

PREC ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_pointRatio = 0

private

ratio of points in left and right splittet box, in range [0,0.5]

Definition at line 684 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

PREC ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_quality = 0.0

private

Definition at line 681 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

QualityEvaluator ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_qualityEval

private

Definition at line 676 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

SearchCriteria ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_searchCriteria

private

Definition at line 710 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

std::vector<SplitAxisType> ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_splitAxes

private

Fixed values

Definition at line 708 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

SplitAxisType ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_splitAxis

private

Definition at line 694 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

unsigned int ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_splitCalls = 0

private

Statistics

Definition at line 668 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

PREC ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_splitPosition = 0.0

private

Definition at line 693 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

PREC ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_splitRatio = 0

private

ratio of the splitting plane in range (0,0.5)

Definition at line 683 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

iterator ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_splitRightIt

private

Definition at line 680 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

unsigned int ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_splits = 0

private

Definition at line 670 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

unsigned int ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_tries = 0

private

Definition at line 669 of file KdTree.hpp.

template<typename TQualityEvaluator , typename Traits >

bool ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >::m_wasLastTry = false

private

Flag which tells if the best values have just been updated when we finished the opt. loop.

Best values

Definition at line 698 of file KdTree.hpp.

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

KdTree.hpp

Public Types

Public Member Functions

Private Member Functions

Private Attributes

Detailed Description

template<typename TQualityEvaluator, typename Traits> class ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >

Member Typedef Documentation

Member Enumeration Documentation

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation

template<typename TQualityEvaluator, typename Traits>
class ApproxMVBB::KdTree::SplitHeuristicPointData< TQualityEvaluator, Traits >